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An Aging World: 2001

U.S. Department of CommerceEconomics and Statistics Administration

U.S. CENSUS BUREAU

Issued November 2001

P95/01-1

International Population Reports

Demographic Programs

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By Kevin Kinsellaand Victoria A. Velkoff

U.S. Department of Health and Human ServicesNational Institutes of Health

NATIONAL INSTITUTE ON AGING

This report was prepared by Kevin Kinsella and Victoria A.Velkoff under the general direction ofPeter O. Way, Chief, InternationalPrograms Center (IPC), PopulationDivision, Census Bureau. Research forand production of this report were sup-ported under an interagency agreementwith the Behavioral and Social ResearchProgram, National Institute on Aging,Agreement No. Y1-AG-9414-01.

For their review of and/or suggestionsregarding this report, the authors aregrateful to Emily M. Agree, Departmentof Population Dynamics, Johns HopkinsUniversity; Nikolai Botev, PopulationActivities Unit, Economic Commission forEurope; Richard V. Burkhauser,Department of Policy Analysis andManagement, Cornell University;James C. Gibbs, Assistant Center Chief,IPC; Albert I. Hermalin, Institute forSocial Research, University of Michigan;Linda Hooper, Aging Studies Branch,IPC; Rose Maria Li, Behavioral andSocial Research Program, NationalInstitute on Aging; Jean-Marie Robine,Equipe INSERM Demographie et Sante,Montpellier; Beth J. Soldo, PopulationStudies Center, University ofPennsylvania; Richard M. Suzman,Behavioral and Social Research Program,National Institute on Aging; Peter O.Way, Chief, IPC, Loraine A. West,Eurasia Branch, IPC; and Richard Woodbury, National Bureau of Economic Research. We also thankDavid Rajnes, Housing and HouseholdEconomic Statistics Division, U.S. CensusBureau, who provided useful data andother information regarding retirementand pensions.

A very special debt of gratitude is owedto George C. Myers, former director ofthe Center for Demographic Studies atDuke University, who passed away in2000. Not only did Dr. Myers offerinstructive comments on this report, buthe also provided invaluable advice andguidance to the aging-related products

and activities of the Census Bureau (aswell as to many other agencies in theUnited States and worldwide) for the bet-ter part of two decades.

Within the IPC Aging Studies Branch,Valerie Lawson was instrumental tothe completion of myriad tasks involvingdata compilation, verification, table andgraph production, and general reportpreparation. Branch members Wan Heand Jennifer Zanini also contributed tothis report.

Frances Scott, Janet Sweeney,Barbara Adams, and Arlene C. Butlerof the Administrative and CustomerServices Division, Walter C. Odom,Chief, provided publication and printingmanagement, graphics design, and com-position and editorial review for printand electronic media. General directionand production management were pro-vided by Michael G. Garland, AssistantChief, and Gary J. Lauffer, Chief,Publications Services Branch.

Thanks also are due to Lorraine Wrightof the Bureau’s Information andResources Services Branch, who cheer-fully and efficiently handled the acquisi-tion of a multitude of necessary sourcesand references.

Finally, we would like to thank thoseinternational organizations and associa-tions engaged in the collection, tabula-tion, analysis and dissemination of datarelevant to the aging of the world’s pop-ulation. In particular, we would like toacknowledge the efforts of the EconomicCommission for Europe, the InternationalLabour Office, the International Networkon Healthy Life Expectancy, theInternational Social SecurityAdministration, the Organization forEconomic Co-Operation andDevelopment, the Statistical Office of theEuropean Union, the United NationsPopulation Division, the United NationsStatistical Office, and the World HealthOrganization.

ACKNOWLEDGMENTS

U.S. Department of CommerceDonald L. Evans,

Secretary

Economics and Statistics AdministrationKathleen B. Cooper,

Under Secretary for Economic Affairs

U.S. CENSUS BUREAUWilliam G. Barron, Jr.,

Acting Director

An Aging World: 2001P95/01-1

Issued November 2001

Suggested Citation

Kinsella, Kevin and Victoria A. Velkoff, U.S. Census Bureau, Series P95/01-1,

An Aging World: 2001, U.S. Government Printing Office,

Washington, DC, 2001.

ECONOMICS

AND STATISTICS

ADMINISTRATION

Economics and StatisticsAdministration

Kathleen B. Cooper,Under Secretary for Economic Affairs

U.S. CENSUS BUREAU

William G. Barron, Jr.,Acting Director

William G. Barron, Jr.,Deputy Director

John H. Thompson,Principal Associate Director for Programs

Nancy M. Gordon,Associate Director for Demographic Programs

John F. Long,Chief, Population Division

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U.S. Census Bureau An Aging World: 2001 iii

1. True or false? In the year 2000, children under theage of 15 still outnumbered elderly people (aged 65and over) in almost all nations of the world.

2. The world’s elderly population is increasing by approx-imately how many people each month?

a. 50,000 b. 300,000 c. 500,000 d. 800,000

3. Which of the world’s developing regions has thehighest aggregate percent elderly?

a. Africa b. Latin Americac. The Caribbean d. Asia (excluding Japan)

4. China has the world’s largest total population (morethan 1.2 billion people). Which country has theworld’s largest elderly (65+) population?

a. Japan b. Germany c. China d. Nigeria

5. True or false? More than half of the world’s elderlytoday live in the industrialized nations of Europe, North America, and Japan.

6. Of the world’s major countries, which had the highestpercentage of elderly people in the year 2000?

a. Sweden b. Turkey c. Italy d. France

7. True or false? Current demographic projections sug-gest that 35 percent of all people in the United Stateswill be at least 65 years of age by the year 2050.

8. True or false? The number of the world’s “oldest old”(people aged 80 and over) is growing more rapidlythan that of the elderly as a whole.

9. More than one-third of the world’s oldest old live inwhich three countries?

a. Germany, the United States, and the United Kingdom

b. India, China, and the United Statesc. Japan, China, and Brazild. Russia, India, and Indonesia

10. Japan has the highest life expectancy at birth amongthe major countries of the world. How many yearscan the average Japanese baby born in 2000 expectto live?

a. 70 years b. 75 years c. 81 years d. 85 years

11. True or false? Today in some countries life expectancyat birth is less than 40 years.

12. What are the leading killers of elderly women inEurope and North America?

a. Cancers b. Circulatory diseasesc. Respiratory diseases d. Accidents

13. True or false? Elderly women outnumber elderly menin all developing countries.

14. There are more older widows than widowers in virtu-ally all countries because:

a. Women live longer than menb. Women typically marry men older than themselvesc. Men are more likely than women to remarry after

divorce or the death of a spoused. All of the above

15. In developed countries, recent declines in labor forceparticipation rates of older (55 and over) workers aredue almost entirely to changing work patterns of

a. Men b. Women c. Men and women

16. What proportion of the world’s countries have a publicold-age security program?

a. All b. Three-fourths c. One-half d. One-fourth

17. Approximately what percent of the private sectorlabor force in the United States is covered by a privatepension plan (as opposed to, or in addition to, publicSocial Security)?

a. 10 percent b. 25 percent c. 33 percent d. 60 percent

18. In which country are elderly people least likely to livealone?

a. The Philippines b. Hungary c. Canada d. Denmark

19. True or false? In developing countries, older men aremore likely than older women to be illiterate.

20. True or false? In most nations, large cities haveyounger populations (i.e., a lower percent elderly) thanthe country as a whole.

20 Questions About Global Aging (to test your knowledge of global population aging at the turn of the century)

Answers appear on next page.

1. True. Although the world’spopulation is aging, children stilloutnumber the elderly in allmajor nations except six:Bulgaria, Germany, Greece, Italy,Japan, and Spain.

2. d. The estimated change in thetotal size of the world’s elderlypopulation between July 1999and July 2000 was more than9.5 million people, an average of795,000 each month.

3. c. The Caribbean, with 7.2 per-cent of all people aged 65 orolder. Corresponding figures forother regions are: Asia (exclud-ing Japan), 5.5 percent; LatinAmerica, 5.3 percent; and Africa,3.1 percent.

4. c. China also has the largestelderly population, numberingnearly 88 million in 2000.

5. False. Although industrializednations have higher percentagesof elderly people than do mostdeveloping countries, 59 percentof the world’s elderly now live inthe developing countries ofAfrica, Asia, Latin America, theCaribbean, and Oceania.

6. c. Italy, with 18.1 percent of allpeople aged 65 or over. Monaco,a small principality of about32,000 people located on theMediterranean, has more than22 percent of its residents aged65 and over.

7. False. Although the UnitedStates will age rapidly when theBaby Boomers (people bornbetween 1946 and 1964) beginto reach age 65 after the year2010, the percent of populationaged 65 and over in the year2050 is projected to be slightlyabove 20 percent (comparedwith about 13 percent today).

8. True. The oldest old are thefastest-growing component ofmany national populations. The

world’s growth rate for the 80+population from 1999 to 2000was 3.5 percent, while that ofthe world’s elderly (65+) popula-tion as a whole was 2.3 percent(compared with 1.3 percent forthe total (all ages) population).

9. b. India has roughly 6.2 millionpeople aged 80 and over, Chinahas 11.5 million, and the UnitedStates 9.2 million. Taken togeth-er, these people constitute nearly38 percent of the world’s oldestold.

10. c. 81 years, up from about 52in 1947.

11. True. In some African countries(e.g., Malawi, Swaziland, Zambia,and Zimbabwe) where theHIV/AIDS epidemic is particularlydevastating, average lifeexpectancy at birth may be asmuch as 25 years lower than itotherwise would be in theabsence of HIV/AIDS.

12. b. Circulatory diseases (especial-ly heart disease and stroke) typi-cally are the leading cause ofdeath as reported by the WorldHealth Organization. In Canadain 1995, for example, 44 percentof all deaths occurring to womenat age 65 or above were attrib-uted to circulatory disease. Thepercentage was virtually thesame for elderly men.

13. False. Although there are moreelderly women than elderly menin the vast majority of theworld’s countries, there areexceptions such as India, Iran,and Bangladesh.

14. d. All of the above.

15. a. From the late 1960s untilvery recently, labor force partici-pation rates of older men indeveloped countries were declin-ing virtually everywhere, where-as those for women were oftenholding steady or increasing.

But because older men work inmuch greater numbers than doolder women, increases infemale participation were morethan offset by falling male partic-ipation.

16. b. Of the 227 countries/areas of the world with populations ofat least 5,000, 167 (74 percent)reported having some form of an old age/disability/survivorsprogram circa 1999.

17. d. The share of the private sec-tor U.S. labor force covered byprivate pension plans was about60 percent in the mid-1990s.However, not all employees whoare covered by such plans actu-ally participate in them.

18. a. The Philippines. The percentof elderly people living alone indeveloping countries is usuallymuch lower than that in devel-oped countries; levels in the lat-ter may exceed 40 percent.

19. False. Older women are lesslikely to be literate. In China in1990, for example, only 11 per-cent of women aged 60 andover could read and write, com-pared with half of men aged 60and over.

20. We do not know. Data forselected cities/countries are pre-sented in Chapter 5. Some liter-ature from developed countriessuggests that the statement isfalse; evidence from certaindeveloping countries suggeststhat it is true. Both the CensusBureau’s International ProgramsCenter and the National Instituteon Aging’s Behavioral and SocialResearch Program would bemost interested in empiricalinput from interested parties.Understanding global aging is adialectical process.

iv An Aging World: 2001 U.S. Census Bureau

Answers

20 Questions About Global Aging . . . . . . . . . . . . . .iii

Chapter

1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . .1

2. The Demographics of Aging . . . . . . . . . . . . . . . .7

3. Life Expectancy and Changing Mortality . . . . . .23

4. Health and Disability . . . . . . . . . . . . . . . . . . . .37

5. Urban and Rural Dimensions . . . . . . . . . . . . . .49

6. Sex Ratios and Marital Status . . . . . . . . . . . . . .57

7. Living Arrangements . . . . . . . . . . . . . . . . . . . .65

8. Family and Social Support of Older People . . . .73

9. Educational Attainment and Literacy . . . . . . . . .85

10. Labor Force Participation and Retirement . . . . .93

11. Pensions and Income Security . . . . . . . . . . . .115

Appendix A.Detailed Tables . . . . . . . . . . . . . . . . . . . . . . .125

Table

1. Total Population, Percent Elderly, and Percent Oldest Old: 1975, 2000, 2015, and 2030 . . . .126

2. Population by Age: 2000 and 2030 . . . . . . . . .128

3. Average Annual Growth Rate and Percent Change Over Time for Older Age Groups: 2000 to 2015 and 2015 to 2030 . . . . . . . . . .130

4. Median Population Age: 2000, 2015, and 2030 . . . . . . . . . . . . . . . . . .132

5. Total and Elderly Urban Population by Sex: Available Data From 1970 to the Present . . . .133

6. Sex Ratio for Population 25 Years and Over by Age: 2000 and 2030 . . . . . . . . . . . . .136

7. Marital Status of Older Persons by Sex: Selected Years 1970 to 1995 . . . . . . . . . . . . .137

8. Support Ratios: 2000, 2015, and 2030 . . . . . .154

9. Parent Support Ratios: 1950, 2000, and 2030 . . . . . . . . . . . . . . . . . . . . . .155

10. Labor Force Participation Rates by Age and Sex: Selected Years, 1970 to 1999 . . . . . . . . .156

Appendix B.Sources and Limitations of the Data . . . . . .163

Appendix C.International Comparison of Urban and Rural Definitions . . . . . . . . . . . . .167

Appendix D.References . . . . . . . . . . . . . . . . . . . . . . . . . . .169

U.S. Census Bureau An Aging World: 2001 v

Contents

The United Nations designated 1999as "The Year of the Older Person,”thereby recognizing and reaffirmingwhat demographers and many othershave known for decades: our globalpopulation is aging, and aging at anunprecedented rate. Fertility declineand urbanization arguably have beenthe dominant global demographictrends during the second half of thetwentieth century, much as rapidimprovements in life expectancycharacterized the early 1900s. As webegin the twenty-first century, popu-lation aging is poised to emerge as apreeminent worldwide phenomenon.The confluence of lowered fertilityand improved health and longevityhas generated growing numbers andproportions of older populationthroughout most of the world. Aseducation and income levels rise,increasing numbers of individualsreach "old age” with markedly differ-ent life expectancies and personalexpectations than their forebears.

Population aging represents, in onesense, a human success story; soci-eties now have the luxury of aging.However, the steady, sustainedgrowth of elderly1 populations also

poses myriad challenges to policy-makers in many societies. After theyear 2010, the numbers and propor-tions of elderly, especially the oldestold, will rise rapidly in most devel-oped and many developing coun-tries.2 The projected increase is pri-marily the result of high fertility afterWorld War II. It is secondarily, butincreasingly, the result of reduceddeath rates at all ages; in mostnations of the world, there have beenmajor reductions in the prevalence ofinfectious and parasitic diseases,declines in infant and maternal mor-tality, and improved nutrition duringthe 1900s. One focus of this reportis a look at the numbers, propor-tions, and growth rates (past, cur-rent, and projected) of the elderlypopulation.

Most people, for good reason, asso-ciate the growth of elderly popula-tions with the developed, industrial-ized countries of Europe and NorthAmerica. Most developed nationsare in fact the demographically old-est in the world today, and somemay have more grandparents thanchildren before the middle of thetwenty-first century. In the early1990s, developed nations as a wholehad about as many children under15 years of age as people aged 55and over (approximately 22 percent

of the total population in each cate-gory). The developing world, bycontrast, still had a high proportionof children (35 percent of all peopleunder age 15) and a relatively lowproportion of older people (10 per-cent aged 55 and over).

What is less widely appreciated isthat absolute numbers of elderly indeveloping nations often are largeand everywhere are increasing.Well over half of the world’s elderly(people aged 65 and over) now livein developing nations (59 percent,or 249 million people, in 2000). By2030, this proportion is projectedto increase to 71 percent (686 mil-lion).3 Many developing countrieshave had or are now experiencing asignificant downturn in their rate ofnatural population increase (birthsminus deaths) similar to what previ-ously occurred in most industrial-ized nations. As this process accel-erates, age structures will change.The elderly will be an ever-largerproportion of each nation’s total

U.S. Census Bureau An Aging World: 2001 1

CHAPTER 1.

Introduction

1 There is a growing awareness that theterm “elderly” is an inadequate generalizationthat conceals the diversity of a broad agegroup, spanning more than 40 years of life. Forcross-national comparative purposes, however,some chronological demarcation of age cate-gories is required. This report uses the follow-ing terms for component age groups: the elder-ly (65 and over); the young old (65 to 74years); and the oldest old (80 years and over).In some contexts (e.g., older people in the laborforce), it may be most useful or necessary (dueto data restrictions) to refer to the “older popu-lation,” those 55 years and older. The term“frail elderly” refers to people 65 years or olderwith significant physical and cognitive healthproblems. This term is used to emphasize thefact that a majority of the elderly, especially theyoung old, do not have serious health prob-lems.

2 The “developed” and “developing” countrycategories used in this report correspond direct-ly to the “more developed” and “less developed”classification employed by the United Nations.Developed countries comprise all nations inEurope (including some nations that formerlywere part of the Soviet Union) and NorthAmerica, plus Japan, Australia, and NewZealand. The remaining nations of the worldare classified as developing countries. Whilethese categories commonly are used for com-parative purposes, it is increasingly evident thatthey no longer accurately reflect developmentaldifferences between nations.

3 Throughout this report, projections of pop-ulation size and composition come from theInternational Programs Center, PopulationDivision, U.S. Census Bureau, unless otherwiseindicated. As discussed further in Appendix B,these projections are based on empirical analy-ses of individual national population age andsex structures, components of populationchange (rates of fertility, mortality, and netmigration), and assumptions about the futuretrajectories of fertility, mortality, and migrationfor each country.

Projections, strictly speaking, are neitherforecasts nor predictions. Projections are “cor-rect” in the sense that they are actual results ofmathematical calculations based on specifiedassumptions. Forecasts are projections thatanalysts judge to be the most probable endresults. There can be alternative projections,but it would be contradictory to make alterna-tive forecasts. It may, however, be appropriateto develop numerical ranges for forecast values.Predictions have no formal statistical meaning;they are related more to forecasts than to pro-jections.

population. Elderly populationsalso have grown because of world-wide improvements in health servic-es, educational status, and econom-ic development. The characteristicsof the elderly are likely to beincreasingly heterogeneous withinnations. Thus, a second focus ofAn Aging World: 2001 is to summa-rize socioeconomic statistics forboth developed and developingnations. This report shows suchdata for 52 nations when availableand reasonably comparable. In2000, these 52 nations (listed inAppendix A, Table 1) contained 77 percent of the world’s total pop-ulation, and are referred to as“study countries” at various pointsin the text.4

This report focuses primarily onpeople aged 65 years old and over.As is true of younger age groups,people aged 65 and over have verydifferent economic resources, healthstatuses, living arrangements, andlevels of integration into social life.An Aging World: 2001 acknowl-edges this diversity by disaggregat-ing statistics into narrower agegroups where possible. Such exam-ination may reveal important demo-graphic, social, and economic differ-ences that have direct bearing onsocial policy now and in the future.For example, the fastest growingportion of the elderly population inmany nations are those aged 80and over, referred to as the oldestold. Rapidly expanding numbers ofvery old people represent a socialphenomenon without historicalprecedent, and one that is bound toalter previously held stereotypes ofolder people. The growth of theoldest old is salient to public policybecause individual needs and social

responsibilities change considerablywith increased age.

An Aging World: 2001 is the sev-enth major cross-national report ina Census Bureau series on theworld’s elderly/older populations.The first two reports, An AgingWorld (1987) and Aging in theThird World (1988), used data pri-marily from the 1970 and 1980rounds of worldwide censuses(those taken from 1965 to 1974and 1975 to 1984, respectively),as well as demographic projectionsproduced by the United NationsPopulation Division from its 1984assessment of global population.Subsequent reports — Populationand Health Transitions (1992);Aging in Eastern Europe and theFormer Soviet Union (1993); AnAging World II (1993); OlderWorkers, Retirement and Pensions(1995); and the current report —include historical data from theearlier reports, available data fromthe 1990 and 2000 rounds of cen-suses, information from nationalsample surveys and administrativerecords, historical and projecteddata from the United Nations, anddata from component populationprojections prepared by theInternational Programs Center(IPC), Population Division, U.S.Census Bureau. Differences amongreports in projected data mayreflect either a change in thesource of the projections or, moreimportantly, revised demographicinsights based on the most recentinformation.

Many of the data included in thisreport are from the Census Bureau’sInternational Data Base (IDB). Thetabular statistics provided inAppendix A represent only a smallportion of the total IDB files. TheIDB is maintained and updated by

the IPC and is funded in part by theBehavioral and Social ResearchProgram of the U.S. NationalInstitute on Aging. IDB contents arereadily available from the CensusBureau’s Web site; the direct accessaddress is www.census.gov/ipc/www/idbnew.html

Appendix B provides more informa-tion about the sources, limitations,and availability of IDB files andreport data in general. There arevast differences in both the quantityand quality of statistics reported byvarious countries. The UnitedNations has provided internationalrecommendations for the standardi-zation of concepts and definitionsof data collected in censuses andsurveys. Nevertheless, there arestill wide discrepancies in data col-lection and tabulation practicesbecause of legitimate differences inthe resources and informationneeds among countries. As aresult, any attempt to compile stan-dard data across countries requiresconsideration of whether and howthe reported data should be ana-lyzed to achieve comparability.

The demographic data in this reporthave been judged by Census Bureauanalysts to be as representative aspossible of the situation in a givencountry. The data are internally con-sistent and congruent with otherfacts known about the nations.These demographic data also havebeen checked for external consisten-cy, that is, compared with informa-tion on other countries in the sameregion or subregion and with thoseelsewhere at approximately thesame level of socioeconomic devel-opment. The socioeconomic data,by contrast, typically are as reportedby the countries themselves.Although Census Bureau analystshave not directly evaluated these

2 An Aging World: 2001 U.S. Census Bureau

4 In some parts of the text, data from addi-tional countries have been included.

data, analysts have attempted toresolve discrepancies in reported fig-ures and to eliminate internationalinconsistencies; data with obviousincongruities are not included.

We are all part of an increasinglyinterdependent and aging world(Figure 1-1). Current growth of eld-erly populations is steady in somecountries and explosive in others.As the World War II baby-boomcohorts, common to many coun-tries, begin to reach their elderyears after 2010, there will be asignificant jump by 2030 in the

proportion of the world’s populationthat is elderly (Figure 1-2). Thecoming growth, especially of theoldest old, will be stunning. Astheir numbers grow, there is aheightened need to understand thecharacteristics of older populations,their strengths, and their require-ments. The effects will be felt notjust within individual nations butthroughout the global economy.Understanding the dynamics ofaging requires accurate descriptionsof the elderly from interrelated per-spectives including demographic,social, economic, medical, and

increasingly, biologic and genetic.The IDB and this report are an effortto contribute to a consistent, sys-tematic, quantitative comparison ofolder populations in various coun-tries. Information is the first steptoward a better understanding ofthe effects of population aging with-in and across national boundaries.As individuals, as nations, and as aninternational community, we facethe challenge of anticipating thechanging needs and desires of anaging world in a new millennium.


Source: U.S. Census Bureau, 2000a.

Figure 1-1.

Percent Aged 65 and Over: 2000

Less than 3.03.0 to 7.98.0 to 12.913.0 or more

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Figure 1-2.

Percent Aged 65 and Over: 2030

Less than 3.03.0 to 7.98.0 to 12.913.0 or more

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The current level and pace of popula-tion aging vary widely by geographicregion, and usually within regions aswell. But virtually all nations are nowexperiencing growth in their num-bers of elderly residents. Developednations have relatively high propor-tions of people aged 65 and over, butthe most rapid increases in elderlypopulation are in the developingworld. Even in nations where theelderly percentage of total populationremains small, absolute numbersmay be rising steeply. Everywhere,the growth of elderly populationsposes challenges to social institutionsthat must adapt to changing agestructures.

WORLD’S ELDERLYPOPULATION INCREASING795,000 EACH MONTH

The world’s elderly population hasbeen growing for centuries. What isnew is the rapid pace of aging. Theglobal population aged 65 and overwas estimated to be 420 millionpeople as of midyear 2000, anincrease of 9.5 million sincemidyear 1999. The net balance ofthe world’s elderly population grewby more than 795,000 people eachmonth during the year. Projectionsto the year 2010 suggest that thenet monthly gain will then be onthe order of 847,000 people. In1990, 26 nations had elderly popu-lations of at least 2 million, and by2000, 31 countries had reached the2-million mark. Projections to theyear 2030 indicate that more than60 countries will have 2 million ormore people aged 65 and over(Figure 2-1).

Projections of older populationsmay be more accurate than projec-tions of total population, whichmust incorporate assumptionsabout the future course of humanfertility. Short-term andmedium-term projections of tomor-row’s elderly are not contingentupon fertility, because anyone whowill be aged 65 or over in 2030 hasalready been born. When projectingthe size and composition of theworld’s future elderly population,human mortality is the key demo-graphic component. As discussedin the next chapter, current andfuture uncertainties about changingmortality may produce widely diver-gent projections of the size oftomorrow’s elderly population.

ELDERLY POPULATIONGROWING FASTEST INDEVELOPING COUNTRIES

Population aging has become awell-publicized phenomenon in theindustrialized nations of Europeand North America. What is notwidely appreciated is the fact thatdeveloping countries are aging aswell, often at a much faster ratethan in the developed world.Seventy-seven percent of theworld’s net gain of elderly individu-als from July 1999 to July 2000 —615,000 people monthly —occurred in developing countries.Figure 2-2 shows the different pat-terns of growth in developed ver-sus developing countries. Mostnotable in developed countries isthe steep plunge in growth in theearly 1980s. The slowing of thegrowth rate was the result of lowbirth rates that prevailed in many

developed countries during andafter World War I. A second, lesssevere, decline in the rate ofgrowth began in the mid-1990sand will be most noticeable in theearly 2000s. This decline corre-sponds to lowered fertility duringthe Great Depression and WorldWar II. These drops in growth ratehighlight the important influencethat past fertility trends have oncurrent and projected changes inthe size of elderly populations.

The current aggregate growth rateof the elderly population in devel-oping countries is more than doublethat in developed countries, andalso double that of the total worldpopulation. The rate in developingcountries began to rise in the early1960s, and has generally continuedto increase until recent years. Aftera brief downturn — again related tolower wartime fertility — the elderlygrowth rate in developing countriesis expected to rise beyond andremain above 3.5 percent annuallyfrom 2015 through 2030 beforedeclining in subsequent decades.

EUROPE STILL THE “OLDEST”WORLD REGION, AFRICA THE“YOUNGEST”

Europe has had the highest propor-tion of population aged 65 and overamong major world regions formany decades and should remainthe global leader well into thetwenty-first century (Table 2-1).Until recently, this region also hadthe highest proportions of popula-tion in the most advanced age cate-gories. But in 2000, the percentageof population aged 80 and over in


CHAPTER 2.

The Demographics of Aging

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Figure 2-1.

Countries With 2 Million or More Elderly People: 2000 and 2030

20002030


North America was equal to that ofEurope as a whole, probably as aresult of small European birthcohorts around the time of WorldWar I. By 2015, however, these per-centages are again expected to behighest in Europe; in 2030, nearly12 percent of all Europeans are pro-jected to be over the age of 74 and7 percent are projected to be overthe age of 79.

North America and Oceania alsohave relatively high aggregate per-centages of elderly, and these areprojected to increase substantiallybetween 2000 and 2030. Levels for2000 in Asia and LatinAmerica/Caribbean are expected tomore than double by 2030, whileaggregate proportions of elderlypopulation in Sub-Saharan Africawill grow rather modestly as aresult of continued high fertility inmany nations.

Two important factors bear mentionwhen considering aggregate elderlyproportions of regional populations.The first is that regional averagesoften hide great diversity.Bangladesh and Thailand may beclose geographically, but thesecountries have divergent paths ofexpected population aging.Likewise, many Caribbean nationshave high proportions of elderlypopulation (the Caribbean is the“oldest” of all developing worldregions) in relation to their CentralAmerican neighbors. Secondly andmore importantly, percentages bythemselves may not give a sense ofpopulation momentum. Althoughthe change in percent elderly inSub-Saharan Africa from 2000 to2015 is barely perceptible, the sizeof the elderly population is expect-ed to jump by 50 percent, from19.3 million to 28.9 million people.

Figure 2-2.

Average Annual Percent Growth of Elderly Population in Developed and Developing Countries

Source: United Nations, 1999.

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4

5

20502040203020202010200019901980197019601950

Total world, all ages

Percent growth

Developed countries, 65 years and over

Developing countries, 65 years and over

Table 2-1.Percent Elderly by Age: 2000 to 2030

Region Year65 yearsand over

75 yearsand over

80 yearsand over

Europe . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2000 15.5 6.6 3.32015 18.7 8.8 5.22030 24.3 11.8 7.1

North America . . . . . . . . . . . . . . . . . . . . . . 2000 12.6 6.0 3.32015 14.9 6.4 3.92030 20.3 9.4 5.4

Oceania . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2000 10.2 4.4 2.32015 12.4 5.2 3.12030 16.3 7.5 4.4

Asia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2000 6.0 1.9 0.82015 7.8 2.8 1.42030 12.0 4.6 2.2

Latin America/Caribbean . . . . . . . . . . . . . 2000 5.5 1.9 0.92015 7.5 2.8 1.52030 11.6 4.6 2.4

Near East/North Africa . . . . . . . . . . . . . . . 2000 4.3 1.4 0.62015 5.3 1.9 0.92030 8.1 2.8 1.3

Sub-Saharan Africa. . . . . . . . . . . . . . . . . . 2000 2.9 0.8 0.32015 3.2 1.0 0.42030 3.7 1.3 0.6



ITALY NOW THE WORLD’S“OLDEST” MAJOR COUNTRY

The percent of population aged 65and over ranged from 12 to 16 per-cent in 2000 in most developedcountries. For many years Swedenhad the highest such proportion,but recently Italy became the demo-graphically oldest of the world’smajor1 nations. Over 18 percent ofall Italians are aged 65 or over, withlevels approaching or exceeding 17 percent in Greece, Sweden,Japan, Spain, and Belgium. Withthe exception of Japan, the world’s25 oldest countries are all in Europe(Figure 2-3). The United States,with an elderly proportion of lessthan 13 percent in 2000, is ratheryoung by developed-country stan-dards, and its proportion elderlywill increase only slightly during thenext decade. However, as the largebirth cohorts of the baby boom(people born from 1946 through1964) begin to reach age 65 after2010, the percent elderly in theUnited States will rise markedly,likely reaching 20 percent by theyear 2030. Still, this figure will belower than in most countries ofWestern Europe.

Figure 2-3.

The World's 25 Oldest Countries: 2000


(Percent of population 65 years and over)

Czech Republic

Ukraine

Luxembourg

Slovenia

Estonia

Hungary

Serbia

Denmark

Finland

Latvia

Croatia

Switzerland

Norway

Austria

Portugal

United Kingdom

France

Germany

Bulgaria

Belgium

Spain

Japan

Sweden

Greece

Italy

13.9

18.1

17.3

17.3

17.0

16.9

16.8

16.5

16.2

16.0

15.7

15.4

15.4

15.2

15.1

15.0

15.0

14.9

14.9

14.8

14.6

14.1

14.0

13.9

14.5

1 Some small areas/jurisdictions have veryhigh proportions of elderly population. In2000, three of the world’s seven highest esti-mated percentages of elders were in theEuropean principality of Monaco (more than 22percent), Guernsey (17 percent) and the Isle ofMan (more than 17 percent).


SOME ELDERLY POPULATIONSTO MORE THAN TRIPLE BY 2030

During the period 2000-2030, theprojected increase in elderly popu-lation in the 52 study countriesranges from 14 percent in Bulgariato 372 percent in Singapore (Figure2-4). Today’s “older” nations willexperience relatively little changecompared with many developingnations; in countries as diverse asMalaysia and Colombia, elderlypopulations are expected toexpand to more than three timestheir size in 2000.

Figure 2-4.

Percent Increase in Elderly Population: 2000 to 2030


BulgariaUkraine

HungaryMalawiGreece

ItalyZimbabwe

SwedenUruguay

RussiaBelgium

JapanUnited Kingdom

FranceNorway

GermanyCzech Republic

DenmarkAustriaPoland

ArgentinaLuxembourgNew ZealandUnited States

IsraelAustralia

KenyaCanadaJamaicaPakistan

LiberiaChina

TunisiaIndia

TurkeySri Lanka

ChileBrazil

MoroccoGuatemala

ThailandPeru

BangladeshEgypt

South KoreaMexico

IndonesiaPhilippinesCosta RicaColombiaMalaysia

Singapore

Developed countriesDeveloping countries

372277

258250

240240

227216

210207206

197196193192

183

178177174171170

160153

134126

117108102102

9287

8175

67646363

62565554

5048484545

43434137

2114


THE LEGACY OF FERTILITY DECLINE

The most prominent historical fac-tor in population aging has beenfertility decline. The generally sus-tained decrease in total fertilityrates (TFRs) in industrialized nationssince at least 1900 has resulted incurrent levels below the populationreplacement rate of 2.1 live birthsper woman in most such nations(Figure 2-5). Persistent low fertilitysince the late 1970s has led to adecline in the size of successivebirth cohorts and a correspondingincrease in the proportion of olderrelative to younger population.

Fertility change in the developingworld has been more recent andmore rapid, with most regions hav-ing achieved major reductions infertility rates over the last 30 years.Although the aggregate TFRremains in excess of 4.5 childrenper woman in Africa and manycountries of the Near East, overalllevels in Asia and Latin Americadecreased by about 50 percent(from 6 to 3 children per woman)during the period 1965 to 1995.Total fertility in many developingcountries — notably China, SouthKorea, Thailand, and at least adozen Caribbean nations — is nowat or below replacement level.

Figure 2-5.

Total Fertility Rate: 2000


ZimbabweTunisia

MoroccoMalawiLiberiaKenyaEgypt

UruguayPeru

MexicoJamaica

GuatemalaCosta RicaColombia

ChileBrazil

Argentina

TurkeyThailandSri Lanka

South KoreaSingapore

PhilippinesPakistanMalaysia

IsraelIndonesia

IndiaChina

Bangladesh

United StatesNew Zealand

JapanCanada

Australia

UkraineRussiaPoland

HungaryCzech Republic

Bulgaria

United KingdomSwedenNorway

LuxembourgItaly

GreeceGermany

FranceDenmarkBelgiumAustria

(Births per woman)

Western Europe

3.3

1.41.61.71.8

1.41.3

1.21.71.8

1.51.7

1.11.21.31.4

1.31.3

1.81.6

1.41.8

2.1

2.91.8

3.12.62.6

3.34.6

3.51.2

1.72.0

1.92.2

2.52.12.2

2.72.5

4.72.1

2.73.0

2.4

3.23.7

6.45.3

3.12.0

Eastern Europe

Other Developed

Asia

Latin America/Caribbean

Africa


EAST AND SOUTHEAST ASIAAGING THE FASTEST

In only one-quarter of a century —from 1970 to 1996 — the percentof population aged 65 and over inJapan increased from 7 to 14 per-cent (Figure 2-6). Similarly swiftincreases are expected in China,beginning around the turn of thecentury, and elsewhere in East and

Southeast Asia (South Korea,Taiwan, and Thailand), fueled bydramatic drops in fertility levels.The rapidity of change in thisregion stands in stark contrast tosome European countries, wherethe comparable change occurredover a period of up to 115 years.Such rapidly aging societies aresoon likely to face the often-

fractious debates over health carecosts, social security, and intergen-erational equity that have emergedin Europe and North America.

AN AGING INDEX

An easily understood indicator ofage structure is the aging index,defined here as the number of peo-ple aged 65 and over per 100youths under age 15. Among the52 study countries in 2000, 5 coun-tries (Germany, Greece, Italy,Bulgaria, and Japan) had more elder-ly than youth aged 0 to 14. By2030, however, all developed coun-tries in Figure 2-7 have a projectedaging index of at least 100, andseveral European countries andJapan are in excess of 200. Today’saging index typically is much lowerin developing countries than in thedeveloped world, and the pattern offuture change is likely to be morevaried. If future fertility ratesremain relatively high, the absolutechange in the aging index will besmall. Generally, however, the pro-portional rise in the aging index indeveloping countries is expected tobe greater than in developedcountries.

The aging index also is useful inexamining within-country differ-ences in the level of populationaging. As noted in Chapter 5, therecan be significant differences in theextent of aging between urban andrural areas. There may also be

Figure 2-6.

Speed of Population Aging

Sources: Kinsella and Gist, 1995; U.S. Census Bureau, 2000a.

(Number of years required or expected for percent of population aged 65 and over to rise from 7 percent to 14 percent)

Colombia (2017-2037)

Brazil (2011-2032)

Thailand (2003-2025)

Tunisia (2009-2032)

Sri Lanka (2004-2027)

Jamaica (2009-2033)

Chile (2000-2025)

Singapore (2001-2028)

China (2000-2027)

Azerbaijan (2000-2041)

Japan (1970-1996)

Spain (1947-1992)

United Kingdom (1930-1975)

Poland (1966-2013)

Hungary (1941-1994)

Canada (1944-2009)

United States (1944-2013)

Australia (1938-2011)

Sweden (1890-1975)

France (1865-1980)

20

115

85

73

69

6553

47

45

45

26

41

27

27

25

24

23

22

21

23

Developed countries

Developing countries


Figure 2-7.

Aging Index: 2000 and 2030


United States

New Zealand

Japan

Canada

Australia

Ukraine

Russia

Poland

Hungary

Czech Republic

Bulgaria

United Kingdom

Sweden

Norway

Luxembourg

Italy

Greece

Germany

France

Denmark

Belgium

Austria

20002030

92186

96172

80143

85155

103187

114206

261127

74117

76131

94169

82152

106

24484

21687

64179

160

70141

78133

60126

66148

115231

51103

59102

(People aged 65 and over per 100 people aged 0-14)

Western Europe

Eastern Europe

Other Developed Countries

Zimbabwe

Tunisia

Morocco

Malawi

Liberia

Kenya

Egypt

Uruguay

Peru

Mexico

Jamaica

Guatemala

Costa Rica

Colombia

Chile

Brazil

Argentina

Turkey

Thailand

Sri Lanka

South Korea

Singapore

Philippines

Pakistan

Malaysia

Israel

Indonesia

India

China

Bangladesh

Asia


Africa

DEVELOPING COUNTRIES

DEVELOPED COUNTRIES

9

27

14

15

36

12

10

10

38

32

25

27

21

32

91

38

52

73

36

25

30

96

125

85

96

71

39

18

26

14

16

9

22

13

13

53

74

69

90

50

64

18

67

45

43

73

11

6

8

6

13

20

9

34

19

11

10

40

71

23


Amazonas Para

Amapa

Mato Grosso

Acre

Roraima

Rondonia

Parana

Rio Grandedo Sul

Mato Grossodo Sul

SantaCatarina

Sao Paulo

Minas Gerais

Rio deJaneiro

EspiritoSanto

Bahia

Goias

Tocantins

Maranhao

Piaui

Ceara

Sergipe

Alagoas

Pernambuco

Paraiba

Rio Grandedo Norte

Figure 2-8.

Aging Index in Brazil by State: 1991

Source: 1991 Census of Brazil.

5.4 to 8.99.0 to 11.912.0 to 13.914.0 to 21.0

Aging index

(Population aged 65 and over per 100 population aged 0-14)


broader regional differences, espe-cially in large nations such as Brazil(Figure 2-8). Based on 1991 censusdata, the overall aging index inBrazil was 14. However, this meas-ure ranged from less than 6 in sev-eral northern states of the countryto 21 in the state of Rio de Janeiro.

MEDIAN AGE TO RISE IN ALL COUNTRIES

Population aging refers most simplyto increasing proportions of olderpeople within an overall populationage structure. Another way to thinkof population aging is to consider asociety’s median age, the age thatdivides a population into numerical-ly equal parts of younger and olderpeople. For example, the 2000median age in the United States was36 years, indicating that the num-ber of people under age 36 equalsthe number who have already cele-brated their 36th birthday.

The 2000 median ages of the 52study countries ranged from 17 inMalawi to 41 in Japan. Developedcountries are all above the 32-yearlevel, while a majority of develop-ing nations have median ages under25. During the next three decades,the median age will increase in all52 countries, though at very differ-ent rates. By 2030, Italy is project-ed to have the highest median age,with half its population aged 52 orover (Figure 2-9), reflecting in largepart the extremely low level of fer-tility now occurring. By way of con-trast, persistently high birth ratesare likely to preclude a large changein median age in some developingcountries (e.g., Liberia and Malawi).

Figure 2-9.

Median Age in 12 Countries: 2000, 2015, and 2030


2000 2015 2030

Thailand

Pakistan

Mexico

Malawi

Liberia

China

Brazil

United States

Italy

Japan

Germany

Canada

Developed countries


37

40

41

40

36

41

45

45

46

38

44

47

50

52

39

26

30

18

17

23

19

29

31

36

18

20

28

24

35

37

41

20

23

34

29

40

(In years)

THE DYNAMICS OFPOPULATION AGING

The process of population aging is,as noted earlier, primarily deter-mined by fertility (birth) rates andsecondarily by mortality (death)rates, so that populations with highfertility tend to have low propor-tions of older people and viceversa. Demographers use the term“demographic transition” to refer toa gradual process2 wherein a socie-ty moves from a situation of highrates of fertility and mortality toone of low rates of fertility andmortality. This transition is charac-terized first by declines in infantand childhood mortality as infec-tious and parasitic diseases arereduced. The resulting improve-ment in life expectancy at birthoccurs while fertility tends toremain high, thereby producinglarge birth cohorts and an expand-ing proportion of children relativeto adults. Other things being equal,this initial decline in mortality gen-erates a younger population agestructure (Lee, 1994).

Generally, populations begin to agewhen fertility declines and adultmortality rates improve. Successivebirth cohorts may eventuallybecome smaller and smaller,although countries may experiencea “baby boom echo” as women ofprior large birth cohorts reach child-bearing age. International migrationusually does not play a major rolein the aging process, but can beimportant in smaller populations.Certain Caribbean nations, forexample, have experienced a com-bination of emigration of working-age adults, immigration of elderly

retirees from other countries, andreturn migration of former emi-grants who are above the averagepopulation age; all three factorscontribute to population aging.Some demographers expect interna-tional migration to assume a moreprominent role in the aging process,particularly in graying countrieswhere persistently low fertility hasled to stable or even declining totalpopulation size (see Box 2-1).Eventual shortages of workers maygenerate demands for immigrantlabor (Peterson, 1999) and mayforce nations to choose betweenrelaxed immigration policies andpronatalist strategies to raise birthrates (Kojima, 1996).

Figure 2-10 illustrates the historicaland projected aggregate populationage structure transition in develop-ing and developed countries. Atone time, most if not all countrieshad a youthful age structure similarto that of developing countries as awhole in 1950, with a large percent-age of the entire population underthe age of 15. Given the relativelyhigh rates of fertility that prevailedin most developing countries from1950 through the early 1970s, theoverall pyramid shape had notchanged greatly by 1990. However,the effects of fertility and mortalitydecline can be seen in the projectedpyramid for 2030, which loses itsstrictly triangular shape as the sizeof younger 5-year cohorts stabilizesand the elderly portion of the totalpopulation increases.

The picture in developed countrieshas been and will be quite different.In 1950, there was relatively littlevariation in the size of 5-yeargroups between the ages of 5 and24. The beginnings of the post-World War II baby boom can beseen in the 0-4 age group. By1990, the baby-boom cohorts were

aged 25 to 44, and younger cohortswere becoming successively small-er. If fertility rates continue as pro-jected through 2030, the aggregatepyramid will start to invert, withmore weight on the top than on thebottom. The size of the oldest-oldpopulation (especially women) willincrease, and people aged 80 andover may eventually outnumber anyyounger 5-year group. Althoughthe effect of fertility decline usuallyhas been the driving force in chang-ing population age structures, cur-rent and future changes in mortalitywill assume much greater weight,particularly in relatively “aged”countries (Caselli and Vallin, 1990),and are discussed further in thenext chapter.

ELDERLY POPULATIONSTHEMSELVES OFTEN ARE AGING

An increasingly important feature ofsocietal aging is the progressiveaging of the elderly populationitself. Over time, a nation’s elderlypopulation may grow older on aver-age as a larger proportion survivesto 80 years and beyond. In manycountries, the “oldest old” (peopleaged 80 and over) are now thefastest growing portion of the totalpopulation. In the mid-1990s, theglobal growth rate of the oldest oldwas somewhat lower than that ofthe world’s elderly, a result of lowfertility that prevailed in manycountries around the time of WorldWar I. In other words, people whowere reaching age 80 in 1996, forexample, were part of a relativelysmall birth cohort. The growth rateof the world’s oldest-old populationfrom 1996 to 1997 was only 1.3 percent. Just a few years later,however, the fertility effects ofWorld War I had dissipated; from1999 to 2000, the growth rate ofthe world’s 80-and-over populationhad jumped to 3.5 percent,


2 The concept of demographic transitionadmittedly is a broad one, and some wouldargue that it has many permutations or thatthere is more than one form of demographictransition; see, for example, the discussion inCoale and Watkins (1986).


European demographers have sounded warning bellsfor at least the last 30 years with regard to the pos-sibility of declining population size in industrializednations. Until very recently, however, this idea hadnot permeated public discourse. Societies wereaware that they were aging, but the equation ofaging with population decline was uncommon. Inthe last 2 years, the visibility of likely populationdecline has increased dramatically, in large part dueto United Nations (2000a; 2000b) reports suggestingthat populations in most of Europe and Japan willdecrease in size over the next 50 years, and to pub-licity accorded to actual declines in Spain, Italy,Russia, and other nations.

This trend raises several contentious issues: Is per-sistent below-replacement fertility a threat toEuropean and other societies, and if so, can it bealtered? To what extent, if any, should so-called“replacement migration” be encouraged as a mecha-nism to offset population aging? Are there importantmacroeconomic (e.g., transnational capital flows;changes in national savings rates) and national securi-ty issues that should be considered?

There are no hard and fast answers to these ques-tions. One study (Bongaarts and Bulatao, 2000) exam-ined the experience of the diverse set of countriesthat have made the transition to low fertility. In veryfew of these countries has fertility stabilized at ratesabove two children per woman. Such an occurrencewould be dependent on substantial proportions ofhigher-order births, but higher-order births are largely“anachronistic” in industrial-country settings. The ten-tative conclusion was that fertility is unlikely torebound significantly, but it has been noted that fewdemographers anticipated the post-World War II babyboom that will soon have a major impact on popula-tion aging. Governments have employed various

means to affect fertility, including direct financialincentives for additional births; indirect pension (i.e.,early retirement) or in-kind benefits such as preferen-tial access for mothers with many children to subsi-dized housing; or measures to reduce the opportunitycosts of additional childbearing. These policies havehad modest impacts in authoritarian states, but onlyminimal impacts in liberal democracies such as Franceand Sweden (Teitelbaum, 2000). Industrial societiesalready provide various rewards, but using them todeliberately manipulate fertility is a sensitive issue,potentially involving substantial economic transfers.

The United Nations (2000a) undertook an examinationof the likely impact of migration as a counterbalanceto aging, building on earlier work by Lesthaeghe,Page, and Surkyn (1988), the Organization forEconomic Co-Operation and Development (1991), andothers. The conclusion was that inflows of migrantswill not be able to prevent European populationdeclines in the future, nor rejuvenate national popula-tions, unless the migration flows are of very largemagnitude (i.e., millions annually). On the heels ofthis report, the United Nations convened an ExpertGroup Meeting on Policy Responses to PopulationAging and Population Decline in October 2000. Theconsensus of the experts was that replacement migra-tion was not a viable “solution” in and of itself, butcould buffer the likely impact of future aging if usedby governments in conjunction with other policies(e.g., increased labor force participation, especiallyamong women; fertility inducements as noted above).With regard to global financial and security issues, lit-tle systematic work has been done on overallimpacts, though researchers are beginning to exploreand model various scenarios (see, e.g., CSIS andWatson Wyatt, 2000; Eberstadt, 2000; MacKellar andErmolieva, 2001; Mason et al., 2001).

Box 2-1.

Population Aging in the Context of Overall Population Decline


Figure 2-10.

Population by Age and Sex: 1950, 1990, and 2030

Sources: United Nations, 1999 and U.S. Census Bureau, 2000a.

Developing countriesDeveloped countries

1950

Millions

400 300 200 100

0- 4 5- 9

10-14 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65-69 70-74 75-79

80+

0 100 200 300 400

1990

400 300 200 100

0- 4 5- 9

10-14 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65-69 70-74 75-79

80+

0 100 200 300 400

2030

400 300 200 100

0- 4 5- 9

10-14 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65-69 70-74 75-79

80+

0 100 200 300 400

Male FemaleAge


considerably higher than that of theworld’s elderly as a whole (2.3 per-cent). In the future, we expect tosee sustained high growth of theoldest old. In the first decade of thetwenty-first century, the projectedaverage annual growth rate of the80-and-over population is 3.9 per-cent (versus 2.0 percent for the 65-and-over population), and isexpected to remain above 3 percentduring the period 2010-2020.

The oldest old constituted 17 per-cent of the world’s elderly in 2000:22 percent in developed countriesand 13 percent in developing coun-tries. More than half (53 percent) ofthe world’s oldest old in 2000 livedin just six countries: China, theUnited States, India, Japan,Germany, and Russia (Figure 2-11).About an additional one-fifth (22percent) lived elsewhere in Europe,while 7 percent lived in LatinAmerica/Caribbean and about 6percent lived in Africa/Near Eastregions, and another 9 percent inAsian countries other than China,India, and Japan.

Among the 52 study countries, thepercentage of oldest old in the totalpopulation in 2000 was less thanhalf a percent in several developingcountries (e.g., Egypt, Guatemala,Indonesia, Kenya, and Malawi). Incontrast, the oldest old constituted5 percent of the total population of

Sweden, and 4 percent or more ofthe total in several other Europeancountries (Denmark, Italy, Norway,and the United Kingdom). In gener-al, Western European nations areabove 3 percent, while otherdeveloped countries are between 2and 3 percent. In most developingnations, less than 1 percent of thepopulation is aged 80 and over,although some developing

countries (e.g., Barbados, Cuba,Puerto Rico, and Uruguay) havehigher levels than many EasternEuropean nations.

Countries vary considerably in theprojected age components of elder-ly populations. In the United States,the oldest old were 26 percent of allelderly in 2000, and are expectedto continue to be 26 percent in

Figure 2-11.

Percent Distribution of World Population Aged 80 and Over: 2000

Note: Data represent the share of the world's total oldest old in each country or region. Individual countries with more than 2.0 percent of the total are shown separately. Source: U.S. Census Bureau, 2000a.

All remaining countries

Africa/Near East


Other Europe

Spain

France

Italy

United Kingdom

Germany

Russia

Other Asia

Japan

India

China

United States 13.1

16.3

8.7

6.6

8.9

4.2

4.1

3.4

3.3

3.1

2.1

10.5

6.9

5.8

3.1


2030 (Figure 2-12). Some Europeannations will experience a sustainedrise in this ratio, while others willsee an increase during the next twodecades and then a subsequentdecline. The most striking globalincrease is likely to occur in Japan;by 2030, nearly 40 percent of allelderly Japanese are expected to beat least 80 years old. Mostdeveloping countries should experi-ence modest long-term increases inthis ratio.

Stability in the proportion of oldestold in the elderly population shouldnot deflect attention from burgeon-ing absolute numbers. In theUnited States, the oldest oldincreased from 374 thousand in1900 to more than 9 million today.The small percentage decline forthe United States in Figure 2-12masks a projected absolute increaseof over 9 million oldest-old people.Four-generation families are becom-ing increasingly common (Soldo,1996), and the aging of the baby

boom may produce a great-grand-parent boom in many countries.The numerical growth and increas-ing heterogeneity of the oldest oldcompel social planners to seek fur-ther health and socioeconomicinformation about this group,because the oldest old consumedisproportionate amounts of healthand long-term care services(Suzman, Willis, and Manton, 1992).Past population projections oftenhave underestimated the improve-ment in mortality rates among theoldest old, and as the next chapterpoints out, actual numbers oftomorrow’s oldest old could bemuch higher than presently antici-pated. Because of the sustainedincreases in longevity in manynations, greater age detail is neededfor the oldest old. In the past, com-parable population projections forthe world’s countries often groupedeveryone aged 80 and over into asingle, open-ended component.Today, for the first time, agencies(e.g., the United Nations PopulationDivision; the U.S. Census Bureau’sInternational Programs Center) areproducing sets of international pop-ulation projections that expand therange of older age groups up to anopen-ended category of age 100and over.

Figure 2-12.

Oldest Old as a Percent of All Elderly: 2000 and 2030


United States

Russia

Pakistan

Japan

Bulgaria

Argentina

(People aged 80 and over as a percent of people aged 65 and over)

20002030

26.4

21.7

13.2

21.7

13.3

15.9

26.5

27.3

27.8

39.3

14.4

20.0


As average length of life increases, the concept of“oldest old” will change. While people of extreme oldage constitute a tiny portion of total population inmost of the world, their numbers are of growingimportance, especially in more-developed nations.Thanks to improvements in nutrition, health, andhealth care, we now have for the first time in historythe opportunity to consider significant numericgrowth of the population aged 100 and over.According to researchers in Europe, the number ofcentenarians has doubled each decade since 1950 inindustrialized countries. Using reliable statistics fromten Western European countries and Japan, Vaupel andJeune (1995) estimated that some 8,800 centenarianslived in these countries as of 1990, and that the num-ber of centenarians grew at an average annual rate ofapproximately 7 percent between the early 1950s andthe late 1980s. They also estimate that, over thecourse of human history, the odds of living from birthto age 100 may have risen from 1 in 20 million to 1in 50 for females in low-mortality nations such asJapan and Sweden.

There are several problems with obtaining accurateage data on very old people (Kestenbaum, 1992; Eloet al., 1996), and estimates of centenarians from cen-suses and other data sources should be scrutinizedcarefully. For example, the 1990 United States censusrecorded some 37,000 centenarians, although due toage misreporting, the actual figure is thought to becloser to 28,000, (Krach and Velkoff, 1999). Still, thisrepresents a doubling of the population aged 100 andover from 1980 to 1990, similar to estimates forEuropean nations. The potentially spectacularincrease in numbers of centenarians is illustrated bydata and projections for France. Dinh (1995) has esti-mated that there were about 200 centenarians inFrance in 1950, and that by the year 2000 the num-ber would be 8,500. His 50-year projections suggest41,000 people aged 100 and over by 2025, increas-ing to 150,000 in 2050. If these projections are real-ized, the number of centenarians in France will havemultiplied by a factor of 750 in one century.

Box 2-2.

The Growth of Centenarians

The spectacular increases in humanlife expectancy that began in themid-1800s and continued duringthe following century are oftenascribed primarily to improvementsin medicine. However, the majorimpact of improvements both inmedicine and sanitation did notoccur until the late nineteenth cen-tury. Earlier and more importantfactors in lowering mortality wereinnovations in industrial and agri-cultural production and distribution,which improved nutrition for largenumbers of people (Thomlinson,1976). A growing research consen-sus attributes the gain in humanlongevity since the early 1800s to acomplex interplay of advancementsin medicine and sanitation coupledwith new modes of familial, social,economic, and political organization(Moore, 1993).

LIFE EXPECTANCY AT BIRTHEXCEEDS 78 YEARS IN 28COUNTRIES

Life expectancy at birth in Japanand Singapore has reached 80 years, the highest level of all theworld’s major countries, and hasreached 79 years in several otherdeveloped nations (e.g., Australia,Canada, Italy, Iceland, Sweden, andSwitzerland). Levels for the UnitedStates and most other developedcountries fall in the 76-78 yearrange (Figure 3-1). Throughout thedeveloping world, there areextreme variations in life expectan-cy at birth (Figure 3-2). While thelevels in some developing nationsmatch or exceed those in many

European nations, the normallifetime in many African countriesspans fewer than 45 years. Onaverage, an individual born in amore-developed country can nowexpect to outlive his/her counter-part in the less-developed world by13 years.

TWENTIETH CENTURY LIFEEXPECTANCY HAS DOUBLED INSOME DEVELOPED COUNTRIES

Table 3-1 shows the enormousstrides that countries have made inextending life expectancy since1900. In developed countries, theaverage national gain in lifeexpectancy at birth was 66 percentfor males and 71 percent forfemales during the period 1900-90.In Italy, life expectancy at birth forwomen increased from 43 years in1900 to over 82 years in 2000. Insome cases, life expectancy hasmore than doubled during the cen-tury (e.g., Spain).

Increases in life expectancy weremore rapid in the first half than inthe second half of the century.Expansion of public health servicesand facilities and disease eradica-tion programs greatly reduceddeath rates, particularly amonginfants and children. From 1900 to1950, people in many Westernnations were able to add 20 yearsor more to their life expectancies.

Reliable estimates of life expectancyfor many developing countries priorto 1950 are unavailable. SinceWorld War II, changes in lifeexpectancy in developing regions of

the world have been fairly uniform.Practically all nations have showncontinued improvement, with someexceptions in Latin America andmore recently in Africa, the latterdue to the impact of the HIV/AIDSepidemic. The most dramatic gainsin the developing world have beenin East Asia, where life expectancyat birth increased from less than 45 years in 1950 to more than 72 years today.

TREND IN RISING LIFEEXPECTANCY MAY BECHALLENGED

While global gains in life expectancyat birth have been the norm,unforeseen changes and epidemicsmay reverse the usual historical pat-tern. Beginning in the 1950s, thetypical sustained increase in lifeexpectancy at birth in developedcountries began to take differentpaths. While female life expectancycontinued to rise virtually every-where, male gains slowed signifi-cantly and in some cases leveledoff. From the early 1950s to theearly 1970s, for example, male lifeexpectancy changed little inAustralia, the Netherlands, Norway,and the United States. After thisperiod of stagnation, male lifeexpectancy again began to rise.

In Eastern Europe and the formerSoviet Union, the pace of improve-ment in the 1950s and early 1960swas extraordinary. Advances inliving conditions and public healthpolicies combined to produce largedeclines in mortality by reducingsome major causes of death


CHAPTER 3.

Life Expectancy and Changing Mortality

(e.g., tuberculosis) to minimal lev-els (Vishnevsky, Shkolnikov, andVassin, 1991). Resultant gains inlife expectancy in excess of 5 years per decade were common.By the mid-1960s, however, therate of increase had deceleratedsharply. In the 1970s and 1980s,changes in female life expectancyat birth were erratic, while malelife expectancy fell throughout theregion (Bobadilla and Costello,1997). Following the demise ofthe former Soviet Union, thedecline has continued into the1990s in some countries. Thedecline has been particularlysevere for Russian men; between1987 and 1994, male lifeexpectancy at birth plummeted 7.3 years to a level of 57.6, beforebeginning to rise again in recentyears (Figure 3-3). The largeincreases in adult male mortalityusually are attributed to a combi-nation of factors includingincreased homicide and accidentrates, excessive alcohol consump-tion, poor diet, and environmen-tal/workplace degradation(Virganskaya and Dmitriev, 1992;Murray and Bobadilla, 1997),although most researchers takepains to point out that clear causalmechanisms remain poorlyunderstood.


Figure 3-1.

Life Expectancy at Birth: 2000


MalawiZimbabwe

KenyaLiberiaEgypt

MoroccoTunisia

BrazilGuatemala

PeruColombia

MexicoArgentina

JamaicaUruguay

ChileCosta Rica

BangladeshPakistan

IndiaPhilippinesIndonesiaThailandMalaysia

TurkeyChina

Sri LankaSouth Korea

IsraelSingapore

New ZealandCanada

AustraliaJapan

UkraineRussia

BulgariaHungary

PolandCzech Republic

DenmarkLuxembourg

GermanyUnited Kingdom

AustriaBelgiumGreece

NorwayFrance

ItalySweden

United States

Developed countriesDeveloping countries(In years)

37.6

77.1

79.679.078.878.778.477.877.777.777.477.176.5

74.573.2

71.470.9

67.266.0

80.779.879.4

77.8

80.178.6

74.471.871.471.070.8

68.668.067.5

62.561.160.2

75.875.775.275.275.1

71.570.370.0

66.262.9

73.769.1

63.351.0

48.037.8

Western Europe

Eastern Europe

Other Developed

Asia


Africa

U.S. C

ensu

s Bureau

An

Agin

g W

orld

: 20

01

25


Figure 3-2.

Life Expectancy at Birth: 2000

Under 50 years50 to 64 years65 to 74 years75 years and over


Table 3-1.Life Expectancy at Birth in 34 Countries: 1900 to 2000(In years)

Region/countryCirca 1900 Circa 1950 2000

Male Female Male Female Male Female

DEVELOPED COUNTRIES

Western EuropeAustria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37.8 39.9 62.0 67.0 74.5 81.0Belgium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45.4 48.9 62.1 67.4 74.5 81.3Denmark . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51.6 54.8 68.9 71.5 74.0 79.3France . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45.3 48.7 63.7 69.4 74.9 82.9Germany1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43.8 46.6 64.6 68.5 74.3 80.8Norway . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52.3 55.8 70.3 73.8 75.7 81.8Sweden . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52.8 55.3 69.9 72.6 77.0 82.4United Kingdom . . . . . . . . . . . . . . . . . . . . . . . . . . . 46.4 50.1 66.2 71.1 75.0 80.5

Southern and Eastern EuropeCzech Republic1 . . . . . . . . . . . . . . . . . . . . . . . . . . 38.9 41.7 60.9 65.5 71.0 78.2Greece. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38.1 39.7 63.4 66.7 75.9 81.2Hungary. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36.6 38.2 59.3 63.4 67.0 76.1Italy. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42.9 43.2 63.7 67.2 75.9 82.4Spain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33.9 35.7 59.8 64.3 75.3 82.5

OtherAustralia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53.2 56.8 66.7 71.8 76.9 82.7Japan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42.8 44.3 59.6 63.1 77.5 84.1United States . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48.3 51.1 66.0 71.7 74.2 79.9

Circa 1950 2000

Male Female Male Female

DEVELOPING COUNTRIES

AfricaEgypt . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41.2 43.6 61.3 65.5Ghana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40.4 43.6 56.1 58.8Mali. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31.1 34.0 45.5 47.9South Africa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44.0 46.0 50.4 51.8Uganda . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38.5 41.6 42.2 43.7Congo (Brazzaville) . . . . . . . . . . . . . . . . . . . . . . . . 37.5 40.6 44.5 50.5

AsiaChina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39.3 42.3 69.6 73.3India . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39.4 38.0 61.9 63.1Kazakhstan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51.6 61.9 57.7 68.9South Korea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46.0 49.0 70.8 78.5Syria. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44.8 47.2 67.4 69.6Thailand. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45.0 49.1 65.3 72.0

Latin AmericaArgentina. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60.4 65.1 71.7 78.6Brazil . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49.3 52.8 58.5 67.6Costa Rica . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56.0 58.6 73.3 78.5Chile. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57.8 61.3 72.4 79.2Mexico . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49.2 52.4 68.5 74.7Venezuela . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53.8 56.6 70.1 76.3

1Figures for Germany and Czech Republic prior to 1999 refer to the former West Germany and Czechoslovakia, respectively.

Note: Reliable estimates for 1900 for most developing countries are not available.

Source: UNDIESA 1988; Siampos 1990; and U.S. Census Bureau, 2000a.

Elsewhere, the HIV/AIDS epidemichas had a devastating impact on lifeexpectancy, particularly in parts ofAfrica. The effect of the epidemicon life expectancy at birth may beconsiderable, given that AIDSdeaths often are concentrated in thechildhood and middle adult (30 to45) ages. Projections to the year2010 suggest that AIDS may reducelife expectancy at birth by morethan 30 years from otherwise-expected levels in countries such asBotswana, Namibia, South Africa,and Zimbabwe. And while the com-mon perception of AIDS mortalityusually associates AIDS deaths withchildren and younger adults, theepidemic may have a direct andgrowing effect on older popula-tions. In the United States in 1992,nearly three times as many peopleaged 60 and over died of AIDS asdid people under age 20. Between1987 and 1992, the annual numberof U.S. children who died of AIDSremained relatively stable, whereasthe number of deaths to peopleaged 60 and over nearly doubled(Hobbs and Damon, 1996).


Figure 3-3.

Life Expectancy at Birth in Four Countries: 1950 to 1998

Sources: United Nations, 1999; U.S. Census Bureau, 2000a; and country sources.

0

10

20

30

40

50

60

70

80

90

199819901980197019601950

South Korea

Life expectancy in years

United States

Russia

United States

Male

0

10

20

30

40

50

60

70

80

90

199819901980197019601950

Life expectancy in yearsFemale

Zimbabwe

RussiaSouth Korea

Zimbabwe

FEMALE ADVANTAGE IN LIFEEXPECTANCY NEARLYUNIVERSAL

The widening of the sex differentialin life expectancy has been a centralfeature of mortality trends in devel-oped countries in the twentieth cen-tury. In 1900, in Europe and NorthAmerica, women typically outlivedmen by 2 or 3 years. Today, theaverage gap between the sexes isroughly 7 years, but exceeds 12 years in parts of the formerSoviet Union as a result of theunusually high levels of male mor-tality discussed above (Figure 3-4).This differential reflects the fact thatin most nations females have lowermortality than males in every agegroup and for most causes of death.Female life expectancy now exceeds80 years in over 30 countries and isapproaching this level in many othernations. The gender differentialusually is smaller in developingcountries, commonly in the 3-6 yearrange, and even is reversed in someSouth Asian and Middle East soci-eties where cultural factors (such aslow female social status and prefer-ence for male rather than female off-spring) are thought to contribute tohigher male than female lifeexpectancy at birth.

MALE MORTALITYSUBSTANTIALLY HIGHER THANFEMALE MORTALITY ATOLDER AGES

The data in Figure 3-5 illustrate theusual gender pattern of mortality atolder ages, wherein male rates areseen to be consistently higher thanfemale rates. In Canada andGermany, for instance, male mortali-ty rates for ages 65 to 74 areroughly twice as great as correspon-ding female rates. Among coun-tries, though, age-specific mortalityrates can differ widely even whereoverall mortality appears similar.


Figure 3-4.

Female Advantage in Life Expectancy at Birth: 2000


Chile

China

Egypt

Mexico

Syria

Bangladesh

Spain

United States

Russia

Hungary

Japan

France

Belarus

(Difference in years between females and males)Developed countriesDeveloping countries

6.8

12.7

8.06.5

9.1

10.75.7

7.2-0.5

2.3

6.24.2

3.7

Figure 3-5.

Mortality Rates at Older Ages: 2000

Source: Estimated by the U.S. Census Bureau based on individual country sources.

80+

75-79

70-74

65-69

80+

75-79

70-74

65-69

80+

75-79

70-74

65-69

(Per 1,000 population in age/sex group)

MaleFemale

116

Canada

23

36

57

117

30

46

68

138

26

40

65

147

12

19

32

87

16

25

45

108

12

21

38

Uruguay

Germany

For example, total life expectancyat birth in 1995 was about thesame in Cuba (75.4 years) andPortugal (74.7 years). However,World Health Organization data for1995 show that the female mortali-ty rate for ages 55 to 64 was 30 percent lower in Portugal than inCuba, and the female mortality rateat ages 65 to 74 was about 20 per-cent lower. For older men, on theother hand, rates were 15 percenthigher in each age group inPortugal than in Cuba.

WILL THE GENDER GAP IN LIFEEXPECTANCY NARROW?

Precise explanations of the genderdifference in life expectancy stillelude scientists because of theapparent complex interplay of bio-logical, social, and behavioral condi-tions. Greater exposure to risk fac-tors such as tobacco and alcoholuse and occupational hazards is

cited as a source of higher malemortality rates (Statistics Canada,1997), suggesting that the gap inlife expectancy might decrease ifwomen increased their use oftobacco and alcohol and their par-ticipation in the labor force.However, data from industrializedcountries still show no clear patternof change in the gender gap; thegap is widening in most of EasternEurope and the former Soviet Unionand tends to be narrowing in otherdeveloped countries. In the UnitedStates, for instance, life expectancyat birth increased 3.0 years for menand 1.6 years for women between1980 and 1996. But in somenations with very high overall lifeexpectancy (e.g., France, Germany,Japan), gains in female longevitycontinue to outpace those of males.

Given the small average gender gapin life expectancy in developingcountries relative to developed

nations, most demographers expectto see a widening of thefemale/male difference in upcomingdecades, along the lines of the his-torical trend in industrializednations. Evidence suggests thatmany developing countries areexperiencing increases in alcoholand tobacco consumption andvehicular as well as industrial acci-dents, all of which tend, at least ini-tially, to adversely affect men morethan women. Another factor thatmay promote a widening gendergap is education, which is positivelyrelated to survival. As women“catch up” to men in terms of edu-cational attainment, female survivaland health status may improve (Liu,Hermalin, and Chuang, 1998).

OLD-AGE MORTALITY RATESDECLINING OVER TIME

In countries where infant mortalityrates are still relatively high butdeclining, most of the improvementin life expectancy at birth resultsfrom helping infants survive thehigh-risk initial years of life. Butwhen a nation’s infant and child-hood mortality reach low levels,longevity gains in older segmentsof the population begin to assumegreater weight (Caselli and Vallin,1990; Gjonca, Brockmann, andMaier, 1999). Most countries areexperiencing a rise in life expectan-cy at age 65, as exemplified byJapanese and U.S. data in Figure 3-6.The average Japanese womanreaching age 65 in 1998 couldexpect to live an additional 22 years, and the average manmore than 17 years. Overall (i.e.,both sexes combined) Japanese lifeexpectancy at age 65 increased 40 percent from 1970 to 1998,compared with an overall increasein life expectancy at birth of 9 per-cent. Comparative figures for theUnited States are 17 and 8 percent,


Figure 3-6.

Life Expectancy at Age 65 in Japan and the United States: 1970, 1980, and 1998


1998

1980

1970

1998

1980

1970

1998

1980

1970

1998

1980

1970

(Years of life remaining for those who reach age 65)

19.2

12.5

14.6

17.1

15.3

17.7

22.0

13.1

14.1

16.0

17.0

18.3

Japan, Male

Japan, Female

United States, Male

United States, Female

respectively. Although greater rela-tive improvement in life expectancyat older ages may not yet be wide-spread in developing regions of theworld, the proportional increase inlife expectancy at older ages isapproaching or has surpassed therelative increase in life expectancyat birth in some developing coun-tries, notably in Latin America andthe Caribbean (Kinsella, 1994).

The rise in life expectancy at age 65that is characteristic of most soci-eties means that the chances ofdying for particular older agegroups are declining. Figure 3-7shows across-the-board declines inmortality in two older age groups(with the exception of women aged80 to 84 in Mauritius) during a fair-ly recent 10-year period. In gener-al, mortality improvements forpeople aged 70 to 74 have beengreater than for people aged 80 to84, reflecting the growing robust-ness of younger elderly cohorts.

MORTALITY RATE INCREASEAPPEARS TO LESSEN AT VERYOLD AGES

As long ago as the early 1800s,research demonstrated that thehuman death rate increases withage in an exponential manner, atleast to the upper ranges of the agedistribution. Recently, researchershave documented that, at very oldages, the rate of increase in themortality rate tends to slow down.In a study of 28 countries with rea-sonably-reliable data for the period1950-90, Kannisto (1994) noted notonly a decline in mortality rates atages 80 and over, but a tendencytoward greater decline in more-recent time periods. Other workhas confirmed this tendency (e.g.,Wilmoth et al., 2000), and a recentstudy in the United States suggeststhat the age at which mortality

deceleration occurs is rising (Lynchand Brown, 2001).

Findings such as these have gener-ated at least two potential explana-tions. The “heterogeneity” hypothe-sis, an extension of the notion of“survival of the fittest,” posits thatthe deceleration in old-age mortalityis a result of frailer elderly dying atyounger ages, thus creating a veryold population with exceptionallyhealthy attributes resulting fromgenetic endowment and/or lifestyle.A second, “individual-risk” hypothe-sis, suggests that the rate of aging

may slow down at very old ages,and/or that certain genes that aredetrimental to survival may be sup-pressed (see Horiuchi and Wilmoth,1998, for a discussion and examina-tion of these hypotheses). Theobserved deceleration in mortality,combined with the fact that humanmortality at older ages has declinedsubstantially, has led to the ques-tioning of many of the theoreticaltenets of aging (Vaupel et al., 1998).Important insights are being gar-nered from “biodemographic”research which attempts to


Figure 3-7.

Percent Change in Death Rates for Two Older Age Groups: Circa 1985 to Circa 1995

Source: United Nations, various issues of the annual Demographic Yearbook.

Austria

Japan

Israel

Chile

United States

Mauritius

Netherlands

France

Male

Austria

Japan

Israel

Chile

United States

Mauritius

Netherlands

France

(Based on 3-year average of mortality rates centered on 1985 and 1995)

70-74 years 80-84 years

Female

-20

-6

-7

-27

-6

-24

-20

-27

-23

-20

-8

9

-8

-10

-16

-28

-22

-3

-13

-16

-14

-20

-16

-16

-19

-14

-3

-12

-10

-3

-13

-17

cross-fertilize the biologic anddemographic perspectives of agingand senescence. While a clearer pic-ture of the causes of mortality decel-eration at very old ages awaits fur-ther investigation (and will benefitfrom the study of evolutionary biol-ogy and aging in nonhumanspecies; see Olshansky, 1998;Wachter and Finch, 1997; Le Bourg,2001), its recognition at a timewhen numbers of the very old aregrowing rapidly has important poli-cy implications.

PACE OF MORTALITY CHANGEDIFFICULT TO PROJECT

The pace at which death rates atadvanced ages decline will play amajor role in determining futurenumbers of elderly and especially ofvery old population. Vaupel (1997)has noted that the remaining lifeexpectancy of 80-year-old women in

England and Wales is about 50 percent higher today than in1950. Consequently, the number offemale octogenarians is about 50percent higher than it would havebeen had oldest-old mortalityremained at 1950 levels; in absoluteterms, this means that there aremore than one-half million oldest-oldBritish women alive today who oth-erwise would have been dead in theabsence of mortality improvement.

An example from the United Statesillustrates the range of future uncer-tainty about the size of tomorrow’soldest-old population. The U.S.Census Bureau estimated the num-ber of people aged 85 and over inthe United States to be about 3.6 million in 1995 and has madeseveral projections of the futuresize of this age group (Day, 1996;U.S. Census Bureau, 2000b). TheCensus Bureau’s middle-mortality

series projection suggests thatthere will be 14.3 million peopleaged 85 and over in the year 2040,while the low-mortality (i.e., highlife expectancy) series implies 16.8 million. As those who will be85 years old and over in the year2040 are already at least 40 yearsold, the differences in these projec-tions result almost exclusively fromassumptions about adult mortalityrates and are not affected by futurebirth or infant mortality rates. Inthe middle-mortality series, theCensus Bureau assumes that lifeexpectancy at birth will reach 84.0 years in 2050, while in thelow-mortality series life expectancyis assumed to reach 86.1 years in2050 (Hollmann, Mulder, andKallen, 2000).

Alternative projections (Figure 3-8),using assumptions of lower deathrates and higher life expectancies,have produced even larger esti-mates of the future population ofthe United States aged 85 and over.Simply assuming that death rateswill continue falling at about therecent 2 percent rate results in aprojection of 23.5 million aged 85and over in 2040 (Guralnik,Yanagishita, and Schneider, 1988).Even more optimistic forecasts offuture reductions in death rateshave been made from mathematicalsimulations of potential reductionsin known risk factors for chronicdisease, morbidity, and mortality.Manton, Stallard, and Liu (1993)used such a method to generate anextreme “upper bound” projectionfor the United States of 54 millionpeople aged 85 and over in 2040.While such projections are not nec-essarily the most likely, they doillustrate the potential impact ofchanges in adult mortality on thefuture size of the extremely oldpopulation.


Figure 3-8.

Projections of the United States Population Aged 85 and Over

Note: U.S. Census Bureau projections for 2040 do not reflect the results of the 2000 census.Sources: Guralnik, Yanagishita, and Schneider, 1988; Manton, Stallard, and Liu, 1993; and U.S. Census Bureau, 1983, 1992, and 2000b.

(In millions)

0.9 1.5 2.2 3.1 4.2

14.316.8

23.5

53.9

20001990198019701960

1960-2000 Actual2040 Census Bureau middle mortality2040 Census Bureau low mortality2040 Guralnik et al.2040 Manton et al.

2040

As noted earlier, researchers areincreasingly concerned with overallpatterns of mortality decline inaddition to studying the pace ofdecline. One recent study ofmortality in the G71 countries dur-ing the second half of the twentiethcentury reached a provocative con-clusion: mortality at each age hasdeclined exponentially at a fairlyconstant rate in each country(Tuljapurkar, Li, and Boe, 2000).The possibility of a “universal pat-tern” of mortality decline raisesimportant questions about the rela-tionship between social expendi-tures on health and their effect ondeath rates, and about the likeli-hood that the mortality decline willbe sustained in the future.

THE IMPORTANCE OFCARDIOVASCULAR DISEASE

A major disadvantage of summarymortality indexes such as lifeexpectancy is that they maskchanges in mortality by age and/orcause of death. While one canexamine life expectancy at differentages, it may be more useful to con-sider cause-specific changes in mor-tality, particularly if the intention isto devise medical or nutritionalinterventions to affect overalllongevity and the quality of yearslived at older ages. Worldwide,data on cause-specific mortality arefar from ideal for policy making in amajority of countries (See Box 3-1).Many developed countries, howev-er, have had reasonably good cause-specific mortality data since at least1950.

Death rates due to cardiovascular dis-eases — a broad category thatincludes heart, cerebrovascular(stroke) and hypertensive diseases —

increase with age but in recent yearsthese rates have declined at olderages in many developed countries.Nevertheless, cardiovascular diseaseremains the primary killer among eld-erly populations, more so than foradults in general. For example, morethan two-thirds of all deaths to elderlypeople in Bulgaria and nearly half ofall deaths to elderly people inArgentina are attributed to cardiovas-cular disease, and in most countriesthe proportion increases with age(Figure 3-9). One comprehensiveanalysis of developed nations(Murray and Lopez, 1996) attributesnearly 60 percent of all deaths towomen aged 60 and over in the early1990s to cardiovascular disease; thecorresponding figure for older menwas 50 percent. Cancer deaths atolder ages usually rank a distant sec-ond, but may be more worrisome inthe public eye; in the 1995 CanadianWomen’s Health Test, most womenbelieved breast cancer to be the num-ber one killer of women (all ages).Only 16 percent of those surveyedcorrectly stated that heart disease isthe number one killer (Wiesenberg,1996). The prominence of

cardiovascular disease is not just adeveloped-country phenomenon; arecent U.S. Institute of Medicine study(Howson et al., 1998) identifies car-diovascular disease as the primarynoncommunicable health problemthroughout the developing world.

In the United States, the heart-disease component of cardiovascularmortality is the leading cause ofdeath within the elderly population.Among people aged 65 to 74, heartdisease and cancers were equallylikely to be reported as the majorcause of death in 1997, eachaccounting for about one-third of alldeaths in that age group. But as ageadvances, heart disease claims anincreasing share, about 49 percentof deaths to people aged 75 andover (versus 18 percent for cancers).This pattern also occurs in other (butnot all) developed countries.

LUNG CANCER RAMPANTSINCE THE 1950s

Although deaths from cardiovasculardisease are expected to remain mostprominent in the future, a majorconcern of health practitioners in


Box 3-1.Data on Causes of Death

Statistics on causes of death are prone to many biases and errors in allcountries. Underreporting of deaths, lack of precise causal informa-tion, inaccurate diagnoses, and cultural differences complicate bothnational and international studies of mortality. Also, by attributingdeath to one specific cause, comorbidities and underlying conditionssuch as anemia and nutritional deficiencies are often masked.Nevertheless, World Health Organization efforts to revise and extendcoverage of the International Classification of Diseases produce ongo-ing improvements in the quality and comparability of data such asthose referred to in this report. Although mortality data are imperfect,they can be used to illuminate general patterns and orders of magni-tude, and to focus the attention of research, planning, and practice.While decisionmaking should be skeptical of small differences betweengroups, major differences are likely to indicate underlying disparitiesand trends.

1 The G7 countries include Canada, France,Germany, Italy, Japan, the United Kingdom, andthe United States.

the industrialized world is the rise inlung cancer among older women asa result of increased tobacco usesince World War II. With regard tocancers in general, overall age-standardized death rates for cancerrose 30-50 percent among men dur-ing the period 1950-85, and fell byabout 10 percent among women.However, such broad trends oftenare the net result of quite differentchanges in mortality for the leadingsites of disease. In the UnitedStates and Western Europe, stomach

cancer has been declining steadilysince the 1930s, a decline clearlyattributed to nutritional change, i.e.,a reduction in salt content of food,especially preserved food (Lopez,1990).

On the other hand, prevalence oflung cancer has increased sinceWorld War II, initially among menbut now increasingly amongwomen. Estimates for the early1990s (Murray and Lopez, 1996)suggest that lung cancer is

responsible for 30 percent of allcancer deaths to males in devel-oped countries, and 12 percent ofall cancer deaths to females.Proportions for the 60-and-overpopulation are virtually identical.Male death rates from lung cancerappear to have peaked and are nowfalling in some countries and stabi-lizing in many others, perhaps por-tending future declines.Conversely, female death rates fromlung cancer are rising rapidly, inproportion to the large increases incigarette consumption which beganseveral decades ago (Bonita, 1996).Cigarette smoking has been labeledas the single most important pre-ventable cause of premature deathin women aged 35 to 69 in boththe United States and the UnitedKingdom (Amos, 1996). Still, breastcancer remains the principal neo-plasm site among females, andmortality rates from this sourcehave increased or remained con-stant in most countries since thepost-war period. The rise has beenmost pronounced in Southern andEastern Europe, which is consistentwith the hypothesis that a diet highin saturated fat is a leading risk fac-tor for breast cancer.

SUICIDE RATES MUCH HIGHERAMONG ELDERLY MEN THANWOMEN

Suicide rates in 21 countries withrelatively reliable data (Table 3-2)are consistently higher among menthan women in all age groups,including the elderly. This is a uni-versal trend even in societies as dis-parate as Singapore, the UnitedStates, Israel, and Bulgaria. Suiciderates generally increase with ageamong men, and are highest atages 75 and over. Suicide rates forwomen also tend to rise with age,although the peak rate for womenoccurs before age 75 in about one


Figure 3-9.

Percent of All Deaths From Cardiovascular Diseases and Malignant Neoplasms at Older Ages in Four Countries

Sources: World Health Organization, various issues of World Health Statistics Annual, and www-nt.who.int/whosis/statistics/whsa/whsa_table4.cfm?path=statistics,whsa,whsa_table4&language=english

75 years and over

Female, 65 to 74 years

75 years and over

Male, 65 to 74 years

75 years and over


75 years and over


75 years and over


75 years and over


75 years and over


75 years and over


Cardiovascular diseases Malignant neoplasms

Bulgaria, 1998

Argentina, 1996

France, 1996

United States, 1997

66

74

71

79

16

8

15

6

43

47

41

52

28

37

27

42

40

46

36

52

24

17

27

13

42

24

40

15

33

21

35

15

third of the countries in Table 3-2.The fact that the average womanoutlives her spouse — coupledwith studies that show that marriedelders are happier than nonmarriedelders — might lead one to predictthat older women would havehigher rates of suicide than oldermen, but this is clearly not the case.

Among the 23 countries examined,Hungary and Russia had the highestsuicide rates for elderly men, andHungary and Bulgaria had the high-est rates for elderly women. Thereported Hungarian rate for menaged 75 and over is five to seventimes higher than similar rates inIreland, the United Kingdom, andNorway. Belgium and France havecomparatively high rates among

their elderly male populations,while Japan, Switzerland, andRussia have comparatively highrates among elderly women. Levelsfor elderly men in the United Statesare average when compared withother countries, whereas the U.S.rate for women aged 65 and over isrelatively low. Although some ofthese differentials may be artificialdue to differences in the reportingand/or diagnosis of suicide, theirsheer magnitude suggests that realinternational differences do existand deserve closer study.

NO CLEAR TIME TREND INELDERLY SUICIDE WORLDWIDE

Data from the World HealthOrganization for the past 30 yearsdo not show any clear trend in

elderly suicide rates in the world’smore developed countries. Fewnations have experienced the verygradual rise seen in France until themid-1980s, or the downward ten-dency observed in England andWales (Figure 3-10). More often,national rates have fluctuated withno perceptible pattern.

There was a downward trend in eld-erly suicide in the United States fornearly half a century prior to 1980.From 1981 to 1988, however, thesuicide rate of older Americans roseabout 25 percent before beginningto decline in the 1990s. Such anincrease raised questions at a timewhen older people were livinglonger and were supposedly healthi-er and more financially secure


Table 3-2.Suicide Rates for Selected Age Groups in 23 Countries: Circa 1997(Rate per 100,000 population in each age group)

Country

Male Female

15 to 24years

45 to 54years

65 to 74years

75 yearsand over

15 to 24years

45 to 54years

65 to 74years

75 yearsand over

EuropeBelgium, 1994. . . . . . . . . . . . . . . . . . . . . 23 37 43 98 4 17 17 20Bulgaria, 1998. . . . . . . . . . . . . . . . . . . . . 15 27 48 116 6 9 20 50Denmark, 1996 . . . . . . . . . . . . . . . . . . . . 13 31 35 71 2 17 16 20Finland, 1996 . . . . . . . . . . . . . . . . . . . . . 34 55 50 48 7 18 14 7France, 1996. . . . . . . . . . . . . . . . . . . . . . 13 38 41 87 4 16 15 20Germany, 1997 . . . . . . . . . . . . . . . . . . . . 13 30 32 71 3 10 13 21Hungary, 1998 . . . . . . . . . . . . . . . . . . . . 18 93 80 131 4 20 24 50Ireland, 1996 . . . . . . . . . . . . . . . . . . . . . . 25 19 12 22 5 6 1 2Italy, 1995 . . . . . . . . . . . . . . . . . . . . . . . . 7 14 23 43 2 5 7 8Netherlands, 1997 . . . . . . . . . . . . . . . . . 11 16 16 34 4 8 9 12Norway, 1995 . . . . . . . . . . . . . . . . . . . . . 23 24 32 24 6 10 10 5Poland, 1996. . . . . . . . . . . . . . . . . . . . . . 17 42 31 31 3 8 7 6Portugal, 1998 . . . . . . . . . . . . . . . . . . . . 4 7 20 39 1 3 7 9Russia, 1997 . . . . . . . . . . . . . . . . . . . . . . 53 100 97 97 9 15 20 33Switzerland, 1996. . . . . . . . . . . . . . . . . . 25 37 47 80 6 16 17 24United Kingdom, 1997. . . . . . . . . . . . . . 10 14 9 17 2 4 4 4

North AmericaCanada, 1997 . . . . . . . . . . . . . . . . . . . . . 22 27 21 27 5 9 5 4United States, 1997 . . . . . . . . . . . . . . . . 19 23 26 45 4 7 5 5

OtherAustralia, 1995 . . . . . . . . . . . . . . . . . . . . 23 22 19 27 6 8 5 5Chile, 1994 . . . . . . . . . . . . . . . . . . . . . . . 11 14 20 27 2 2 2 1Israel, 1996 . . . . . . . . . . . . . . . . . . . . . . . 9 9 18 41 2 4 4 15Japan, 1997 . . . . . . . . . . . . . . . . . . . . . . 11 40 35 53 6 14 19 33Singapore, 1997 . . . . . . . . . . . . . . . . . . . 9 18 30 74 9 9 14 33

Sources: World Health Organization, various issues of World Health Statistics Annual, andwww-nt.who.int/whosis/statistics/whsa/whsa_table4.cfm?path=statistics,whsa,whsa_table4&language=english

(Robinson 1990). Likewise in Japan,a 30-year decline in elderly suicideappeared to level off in the 1980s,though more recent data show asignificant decline in the 1990s.However, social scientists remainpuzzled by the relatively high ratesof suicide among elderly Japanesewomen. The unpredictability of sui-cide trends is perhaps best illustrat-ed by the case of the Netherlands.Dutch society is widely recognizedas being more tolerant of voluntaryeuthanasia than are other Westernsocieties, and one might think itwould also have higher rates ofrecorded suicide. However, thecountry’s rates are lower than theindustrialized-country average formost age groups, including the eld-erly, and have not changed greatlyduring the past 30 years.


Figure 3-10.

Suicide Rates by Age in England and Wales and in France: 1965 to 1995

Source: World Health Organization, various issues of World Health Statistics Annual.

Rate per 100,000 population in each age groupEngland and Wales

Rate per 100,000 population in each age groupFrance

0

20

40

60

80

100

120

140

1995199019851980197519701965

0

20

40

60

80

100

120

140

1995199019851980197519701965

Male 75+Male 65-74Female 65-74Female 75+

Male 75+

Female 75+

Male 65-74

Female 65-74

Many societies worldwide haveexperienced a change from condi-tions of high fertility and high mor-tality to low fertility and low mortal-ity, a process commonly dubbed the“demographic transition.” Relatedto this trend is the “epidemiologictransition,” a phrase first used inthe early 1970s (Omran, 1971) torefer to a long-term change in lead-ing causes of death, from infectiousand acute to chronic and degenera-tive. In the classic demographictransition, initial mortality declinesresult primarily from the control ofinfectious and parasitic diseases atvery young ages. As children sur-vive and grow, they are increasinglyexposed to risk factors associatedwith chronic diseases and acci-dents. As fertility declines and pop-ulations begin to age, the preemi-nent causes of death shift fromthose associated with childhoodmortality to those associated witholder age (Kalache, 1996).Eventually, growing numbers ofadults shift national morbidity pro-files toward a greater incidence ofchronic and degenerative diseases(Frenk et al., 1989).

EPIDEMIOLOGIC TRANSITIONSHIFTS SURVIVAL CURVE

Figure 4-1, which shows survivalcurves for U.S. females in 1901 and1998, illustrates a general patternseen in developed countries. Thecurve for 1901 represents the earlystages of the epidemiologic transi-tion in which the level of infantmortality was high, there was con-siderable mortality through the mid-dle years, and a gradual increase atthe later ages. Female life

expectancy at birth was approxi-mately 50 years, and the medianage at death (the age to which 50 percent of females subject to the mortality risks of 1901 couldexpect to survive) was about 60 years. By 1998, the survivorshipcurve had shifted dramatically.Female life expectancy had risen to79 years, and the median age atdeath was above 80 years. Theproportion surviving is now quitehigh at all ages up to age 50, andthe survival curve at older ages isapproaching a much more rectangu-lar shape as a result of relativelymore chronic-disease mortality atolder ages.

DEVELOPING-COUNTRYTRANSITION APPEARSGREATEST IN LATIN AMERICA

Developing countries are in variousstages of epidemiologic transition.Change is most evident in LatinAmerica and the Caribbean, wherecardiovascular diseases were theleading cause of death in 29 of 33countries examined in 1990 (PAHO,1994). Most deaths from chronicand degenerative ailments occur atrelatively old ages. Comparativedata from the mid-1990s (Figure 4-2)show that half or more of all deathsin numerous nations of the WesternHemisphere now occur at ages 65and over.


CHAPTER 4.

Health and Disability

Figure 4-1.

Survival Curve for U.S. Females: 1901 and 1998

Note: Data for 1901 refer to White females. Sources: U.S. Census Bureau, 1936; U.S. Centers for Disease Control, 2001.

0

10

20

30

40

50

60

70

80

90

100

1009080706050403020100

1901

Percent surviving

1998

Age

The pace of epidemiologic changein East and Southeast Asian nationsis now especially rapid. In the caseof Singapore, where life expectancyat birth rose 30 years in little over ageneration (from 40 years in 1948to 70 years in the late-1970s), theshare of cardiovascular deaths rosefrom 5 to 32 percent of all deaths,while deaths due to infectious dis-eases declined from 40 to 12 per-cent. Data from Taiwan (Table 4-1)exemplify the typical shift in causesof death; the infectious and para-sitic diseases that dominatedTaiwanese mortality in the mid-1950s have given way to chronicand degenerative diseases. By1976, cerebrovascular disease andcancers had become the leadingcauses of death. The situation inthe 1996 was similar to that in1976, except that the relativeimportance of diabetes had risensubstantially while tuberculosis wasno longer a major killer. Althoughreliable data for much of theremainder of Asia and for Africa arelacking, scattered evidence sug-gests the increasing importance ofchronic disease patterns in adultpopulations.

DOES LONGER LIFE EQUAL BETTER LIFE?

Chapter 3 pointed out that continu-al increases in life expectancy, espe-cially at older ages, have been thenorm in most countries worldwide.As individuals live longer, the quali-ty of that longer life becomes a cen-tral issue for both personal andsocial well-being. Are we livinghealthier� as well as longer lives, or

are we spending an increasingportion of our older years with dis-abilities, mental disorders, and in illhealth? In aging societies, theanswer to this question will have a

profound impact on national health,retirement, and family systems, andparticularly on the demand for long-term care. In the future, healthexpectancy will come to be as


Figure 4-2.

Proportion of All Deaths Occurring at Ages 65 and Above in 20 Countries: Circa 1995

Source: Pan American Health Organization, 1998.

Nicaragua

Guyana

Venezuela

Colombia

Bahamas

Ecuador

Brazil

Suriname

Mexico

Paraguay

Costa Rica

Trinidad & Tobago

Saint Lucia

Chile

Argentina

Puerto Rico

Cuba

United States

Canada

Barbados

(Percent)

34

75

75

73

67

62

62

61

5957

56

49

45

45

4343

42

42

41

37

Table 4-1.Rank Order of the Ten Leading Causes of Death in Taiwan:1956, 1976, and 1996

Order 1956 1976 1996

1 . . . . . . . GDEC1 Cerebrovascular disease Malignant neoplasms2 . . . . . . . Pneumonia Malignant neoplasms Cerebrovascular disease3 . . . . . . . Tuberculosis Accidents Accidents4 . . . . . . . Perinatal conditions Heart disease Heart disease5 . . . . . . . Vascular lesions of CNS2 Pneumonia Diabetes mellitus6 . . . . . . . Heart disease Tuberculosis Cirrhosis/chronic liver disease7 . . . . . . . Malignant neoplasms Cirrhosis of the liver Nephritis/nephrosis8 . . . . . . . Nephritis/nephrosis Bronchitis3 Pneumonia9 . . . . . . . Bronchitis Hypertensive disease Hypertensive disease10 . . . . . . Stomach/duodenum ulcer Nephritis/nephrosis ulcer Bronchitis3

1Includes gastritis, duodenitis, enteritis, and colitis (except diarrhoea of newborns).2CNS refers to the central nervous system.3Includes emphysema and asthma.

Source: Taiwan Department of Health, 1997.

1 “Health” is a relative and continually devel-oping concept which “reflects on the one handthe progress made within the health sciencesand on the other hand the meanings, valuesand prejudices related to health in differentsociocultural contexts.” (Heikkinen 1998; seethis source for a useful discussion of the differ-ent orientations toward health that have beenadopted in the health sciences).

important a measure as lifeexpectancy is today.

Research into patterns of change inmortality, sickness, and disabilityhas suggested that these three fac-tors do not necessarily evolve in asimilar fashion. A four-countrystudy (Riley, 1990) notes that inJapan, the United States, and Britain,mortality decreased and sickness(morbidity) increased, while inHungary, mortality increased andsickness decreased.2 Discrepanciesbetween the trends in mortality,morbidity, and disability have

generated competing theories ofhealth change, several of which maybe characterized as: a pandemic ofchronic disease and disability(Gruenberg, 1977; Kramer, 1980); acompression of morbidity (Fries,1990); dynamic equilibrium(Manton, 1982); and the postpone-ment of all morbid events to olderages (Strehler, 1975). The WorldHealth Organization has proposed ageneral model of health transitionthat distinguishes between total sur-vival, disability-free survival, andsurvival without disabling chronicdisease. In other words, it is desir-able to quantitatively disaggregatelife expectancy into different healthstates to better understand the rela-tive health of populations. Thus, ageneral survival curve such as thatin Figure 4-1 can be partitioned intodifferent categories that indicateoverall survival, survival without dis-ability, and survival without disease.

An application of this model to datafrom France (Robine, Mormiche, andCambois, 1996) shows that theincrease in total survival between1981 and 1991 was generally con-sistent with the increase in disability-free life expectancy, whereas sur-vival without chronic diseaseshowed little change (Figure 4-3).In this case, the differing trajecto-ries of disability and morbidity maybe interpreted as support for thetheory of dynamic equilibrium,which says that increases in overalllife expectancy are driven in part bya reduction in the rate of progres-sion of chronic diseases.

HEALTHY LIFE EXPECTANCY

Since the early 1970s, research hasbeen moving toward the develop-ment of health indexes that takeinto account not only mortality butalso various gradations of ill health.As of 1998, 49 nations had esti-mates of healthy life expectancy,3

an indicator that attempts to inte-grate into a single index the mortal-ity and morbidity conditions of apopulation. Most estimates ofhealthy life expectancy are derivedfrom calculations of disability-freelife expectancy using a methodolo-gy pioneered by Sullivan (1971),which employs cross-sectionalprevalence data but may produceresults that underestimate temporaltrends in a given population.Recognizing that these earlier com-putational approaches could notcapture the full dynamic nature ofdisability, multistate models havebeen developed to incorporateprocesses such as recovery and


2 The author’s broader review of historicaldata concludes that the relationship betweenfalling sick and dying from sickness has shiftedover time, and that the link between death andhealth risks has been unstable rather than sta-ble across time. The risk of being sick hasincreased as a result of various obvious andnon-obvious factors — among them earlier andbetter detection of sickness, declining mortality,and rising real income — which themselvesconstitute valuable human achievements. Theimplication is that protracted sickness is abyproduct of such achievements.

Figure 4-3.

Survival Without Disease and Survival Without Disability for French Females: 1981 and 1991

Source: Robine, Mormiche, and Cambois, 1996.

0

10

20

30

40

50

60

70

80

90

100

1009080706050403020100

Percent

Total survival in 1981 Total survival in 1991Survival without disability in 1981Survival without disability in 1991Survival without disease in 1981Survival without disease in 1991

Age

3 The concept of healthy life expectancy astypically used refers to expectancy without limi-tations of function that may be the conse-quence of one or more chronic disease condi-tions. The concept is sometimes called “activelife expectancy” or “disability-free life expectan-cy,” to avoid the implication that “healthy”means “absence of disease.”

rehabilitation into the calculations(see, e.g., Manton and Stallard,1988; Rogers, Rogers, and Belanger,1990). These latter models, howev-er, require longitudinal data whichcurrently are unavailable in mostnations. To date, chronologicalseries are available only for somedeveloped nations.

In recent years, researchers havebeen working toward developingintegrated, comparable measuresof healthy life expectancy(Verbrugge, 1997). Presently, how-ever, it remains impossible tostrictly compare estimates amongnations, due both to different com-putational methods and, moreimportantly, to differences in con-cepts and definitions that definethe basic data. There are impor-tant but not-widely-appreciateddistinctions between impairments,disabilities, and handicaps that canlead to different measures ofhealth status (Chamie, 1989).Because “disability” is defined inmany ways, national estimates ofdisability vary enormously. Forexample, a compilation by theUnited Nations (1990a) showednational crude disability rates forthe total population ranging fromless than half a percent in severaldeveloping countries (Peru, Egypt,Pakistan, Sri Lanka) to nearly 21 percent in Austria. Perhaps themost commonly-used measure-ment tools are scales which assessthe ability of individuals to per-form activities of daily living(ADLs) such as eating, toiletting,and ambulation, as well as instru-mental activities of daily living(IADLs) such as shopping andusing transportation. These meas-ures originated in industrializedsocieties where debate has cen-tered on long-term care systems

and individuals’ ability to functionin everyday life.4

FEMALE ADVANTAGE IN LIFEEXPECTANCY PARTIALLYOFFSET BY DISABILITY

In spite of cross-national compara-bility problems, several generalobservations seem warranted. Forindividuals reaching age 65, healthexpectancy varies more thanremaining life expectancy. Oneexamination (Kinsella and Taeuber,1993) of REVES data (See Box 4-1)showed that the range of lifeexpectancy at age 65 varied byabout 12 percent among developed


Box 4-1.Network on Health Expectancy

To facilitate and promote analyses of health expectancy, an internationalnetwork (REVES, the French acronym for Network on Health Expectancyand Disability Process) was formed in 1989 to bring together researchersconcerned with the measurement of changes and inequalities in healthstatus, not only within but among nations. REVES has produced numer-ous documents and bibliographies of relevant materials, including a sta-tistical yearbook that includes existing estimates of health expectancy invarious countries. Further information may be obtained from Jean-MarieRobine, Network Coordinator, INSERM Equipe Demographie et Sante,Centre Val d’Aurelle, 34298 Montpellier Cedex 5, France.

4 ADL measures vary along several dimen-sions, including the number of activities consid-ered and the degree of independence in per-forming physical activities. ADLs do not coverall aspects of disability, however, and are notsufficient by themselves to estimate the needfor long-term care. Some older people havecognitive impairments not measured by ADLlimitations, which may or may not be capturedby IADL measures. And, of course, there aremany questions regarding the validity andapplicability of such measures in different cul-tural settings.

Figure 4-4.

Portion of Old Age Lived Without Severe Disability: Data From the Early 1990s

Note: Figures refer to the percent of a person's life, after reaching age 65, that she or he might expect to live without needing significant help (personal care) with at least one major activity of daily living. Source: Jacobzone, 1999.

United Kingdom

Japan

France

Canada

Australia

(Percent) Male Female

93

85

85

94

92

94

79

78

90

87

countries for both men and women.However, the percent of this timespent in “good health” (free of prob-lems with personal and instrumen-tal activities of daily living) had amuch wider range, from 45 to morethan 80 for males, and from 37 to76 for females (these figuresexclude apparent outlier estimateswhich would widen the ranges evenfurther). For men in developingcountries, the estimated range ofremaining life expectancy at age 65was 12 to 15 years. However, theestimated percent of remainingyears spent in relative health variedfrom less than 60 to 88 percent.For elderly women, the variation inlife expectancy was 28 percent,while the range of healthy remain-ing life was 50 to 87 percent.

Available but geographically limiteddata from the early 1990s suggest afurther tentative statement: womenreaching age 65 can expect to

spend a slightly greater proportionof their remaining years in a severe-ly disabled state relative to elderlymen, thus negating some of thepotential benefit of their higher lifeexpectancy (Figure 4-4). Otherstudies of gender differences in theincidence of disabling conditions atolder ages support this contention(Heikkinen, Jokela, and Jylha, 1996;Dunlop, Hughes, and Manheim,1997; Robine and Romieu, 1998).

DEVELOPED-COUNTRYDISABILITY RATES AT OLDERAGE SEEN TO BE DECLINING

In nations where time series esti-mates of health expectancy areavailable (e.g., Canada, the UnitedStates, Australia, England/Wales),the general view in the 1980s wasone of uncertainty regarding therelationship between rising lifeexpectancies and trends in healthexpectancies. One comprehensivereview of data in the United States

(Freedman and Soldo, 1994) founddeclines in less-severe disability(i.e., in IADLs) during the 1980s.Data from Australia, on the otherhand, revealed that the increase inyears of disability between 1981and 1988 was greater than theoverall increase in life expectancy.Data for Canada and Finland sug-gest that changes in disability-freelife expectancy have been andremain stagnant (Robine andRomieu, 1998). Researchers positeda number of potential factors —other than actual increases inchronic disease incidence and meas-urement error — which might havecontributed to stagnation ordeclines in healthy life expectancy,including increased survival ofchronically ill individuals due toimprovements in medical care, earli-er diagnosis or treatment of chronicdiseases, greater social awarenessof disease and disability, earlieradjustment to chronic conditionsdue to improved pension and healthcare/delivery systems, and risingexpectations of what constitutesgood health or normal functioning(Mathers, 1991; Verbrugge, 1989).

More recent data and rigorousanalyses, however, now stronglysuggest that rates of disability in anumber of developed countries aredeclining. In the United States,researchers (Manton, Corder, andStallard, 1997) used data from the1982, 1984, 1989 and 1994rounds of the U.S. National LongTerm Care Survey to demonstratethat the disability rate among peo-ple aged 65 and over declined overthe 12-year period, such that therewere 1.2 million fewer disabledolder people in 1994 than wouldhave been the case if the 1982rate had not changed (Figure 4-5).Five other U.S. surveys, while vary-ing in content and nature


Figure 4-5.

Number of Chronically Disabled People Aged 65 and Over in the United States: 1982 to 1996

Source: Manton, Corder, and Stallard, 1997.

0

2

4

6

8

10

1996199419891982

Millions

Based on declines in chronic disabilityrate occurring since 1982

If disability rate did not changesince 1982

(e.g., both longitudinal and cross-sectional), have yielded findingsthat support a temporal decline.Likewise, a U.S. study of changesbetween 1982 and 1993 in self-reported ability to work found sig-nificant improvement among bothmen and women who were in theirsixties (Crimmins, Reynolds, andSaito, 1999). Another U.S. study(Freedman and Martin, 1998) ofthe effect of changes in living envi-ronments, device use, and surveydesign on functional ability amongnoninstitutionalized people aged50 and over concludes that thesechanges alone could not accountcompletely for improved function-ing, and that there has indeedbeen some improvement in under-lying physiological capability.Increased levels of education havebeen identified as a potentiallypowerful factor influencing disabil-ity decline in the United States.

A review of trend data from nineother developed countries plusTaiwan concludes that, with a fewexceptions by gender, disability isdeclining among the elderly else-where as well (Waidmann andManton, 1998), as indicated by theFrench data in Figure 4-3.Researchers increasingly have dis-aggregated disability into more-severe versus less-severe cate-gories, and the current consensusin developed countries is that theoverall decline in disability is prima-rily the result of decreases in themore-severe forms (Robine andRomieu, 1998). Freedman, Aykan,and Martin (2001), for example,have recently demonstrated adecline between 1993 and 1998 insevere cognitive impairment amongthe noninstitutionalized populationaged 80 and over in the UnitedStates. Such trends, if sustained,

obviously have substantial implica-tions for public and private healthprograms and expenditures, andpossibly for the conceptualizationand definition of disability itself.5

Many countries with aging popula-tions now recognize the need forlongitudinal surveys as a means ofunderstanding adult health pat-terns, transitions to and from differ-ent health statuses, and how to dif-ferentiate between morbidity andaging per se (Svanborg, 1996).While such survey efforts involvesubstantial economic investment,the potential cost savings in policydesign and implementation wouldseem to dwarf the initial expense.And as various national longitudinalanalyses expand, both geographi-cally and in terms of specific dis-abling conditions, all health sys-tems stand to benefit from morecomprehensive comparisons andthe resultant implications for pro-gram priorities.

DEVELOPING-COUNTRYDISABILITY BURDEN LIKELY TOINCREASE AS POPULATIONSAGE

Two decades ago, the World HealthOrganization noted a distinction inprominent causes of disabilitybetween developed and developingcountries. In the latter, disabilitywas said to stem primarily frommalnutrition, communicable dis-eases, accidents, and congenitalconditions. In industrialized coun-tries disability resulted largelyfrom the chronic diseases dis-cussed earlier — cardiovasculardisease, arthritis, mental illness,and metabolic disorders, as well as

accidents and the consequences ofdrug and alcohol abuse. Aseconomies in developing countriesexpand and the demographic andepidemiologic pictures change, wemight expect to see relatedchanges in the nature and preva-lence of various disabilities.

Numbers of disabled people arealmost certain to increase as a cor-relate of sheer population growth.Figure 4-6 illustrates the applica-tion of empirical gross disabilityrates to the projected populationof the Philippines. This simplisticexample assumes that disabilityrates for men and women as meas-ured in 1980 will remain constantin the future. Even with no provi-sion for higher rates of disabilityas the population ages, the project-ed absolute increases are alarmingin terms of future service and carerequirements.

ESTIMATING THE BURDEN OF DISEASE

A major ongoing effort to under-stand and predict the effect of epi-demiologic change is the GlobalBurden of Disease Project under-taken jointly by the World HealthOrganization, Harvard University,and the World Bank. Using a com-putational (and controversial; see,e.g., Black and McLarty, 1996;Cohen, 2000) concept known asDisability-Adjusted Life Years(DALYs), this study attempts tomeasure global, regional, andcountry-specific disease burdens ina baseline year, and to project suchburdens into the future. Figure 4-7highlights the change in the esti-mated (1990) and projected (2020)rank order of disease burden forthe ten leading disease categorieson a global basis. In addition tounderscoring the expected shift


5 For a description of changes and paradigmshifts in disability policy in certain developedcountries, see Kalisch, Aman, and Buchele,1998.

from communicable to non-communicable disease patterns(largely driven by the changing sit-uation in developing countries;Murray and Lopez, 1997), thisstudy raises specific warning flagsfor many countries in terms of alikely increase in disease burdendue to neuro-psychiatric conditionsand accidents. Among the manyresults, several stand out: (1) theprojected prominence of tobaccouse vis-a-vis mortality (as men-tioned in Chapter 3) and throughvarious disease vectors, with theexpectation that tobacco will killmore people than any single dis-ease by 2020; (2) the concentra-tion of disease burden in certaindeveloping regions. For example,the inhabitants of India and Sub-Saharan Africa were estimated tobear more than 40 percent of theworld’s disease burden in 1990,while constituting only one-fourthof the world’s population. Thestudy also points out the fallacythat noncommunicable diseasesare necessarily related to affluence;the likelihood of dying from a non-communicable disease amongadults under age 70 in both Indiaand Sub-Saharan Africa is greaterthan in Western Europe; and (3) thevastly underestimated importanceof mental illnesses as major andincreasing sources of disease bur-den, which implies significantlong-term care challenges in agingsocieties (Murray and Lopez,1996).


Figure 4-6.

Projected Numbers of Disabled Males in the Philippines by Age: 1991 and 2020


Thousands

1991 2020

0

100

200

300

400

500

600

700

75+65-7455-6445-5435-4425-3415-245-140-4

Figure 4-7.

Change in Rank Order of Disease Burden for Top Ten Leading Causes in the World: 1990 and 2020

Source: Murray and Lopez, 1996.

(Disease burden measured in disability-adjusted life years)

1990 2020

Rank Disease or injury Disease or injury

1 Lower respiratory infections Ischemic heart disease2 Diarrhoeal diseases Unipolar major depression3 Conditions arising during Road traffic accidents

the perinatal period4 Unipolar major depression Cerebrovascular disease5 Ischemic heart disease Chronic obstructive pulmonary disease6 Cerebrovascular disease Lower respiratory infections7 Tuberculosis Tuberculosis8 Measles War9 Road traffic accidents Diarrhoeal diseases

10 Congenital anomalies HIV


Figure 4-8.

Share of Population Versus Health Expenditureby Age in Nine Countries: 1993

Source: OECD, 1997.

Population Health expenditure

Percent of total

75+

65+

<65

75+

65+

<65

75+

65+

<65

75+

65+

<65

75+

65+

<65

75+

65+

<65

75+

65+

<65

75+

65+

<65

75+

65+

<65

Australia

Finland

Germany

New Zealand

Portugal

Sweden

Switzerland

United Kingdom (England)

United States

21

88

12

4

86

14

6

85

15

6

89

11

5

86

14

5

82

18

8

86

14

6

84

16

7

87

13

5

66

34

20

62

38

22

68

32

16

67

33

21

64

36

19

62

38

21

60

40

26

58

42

27

63

37

AGING INCREASES HEALTHCARE COSTS

Population aging might be expectedto increase costs of health care inmost societies because healthexpenditures by and for older agegroups tend to be proportionallygreater than their population share(Figure 4-8). This expectationapplies especially to nations whereacute care and institutional (long-term care) services are widely avail-able. Cross-national comparativedata on health care expenditures byage are relatively uncommon, butongoing work by the Organizationfor Economic Co-Operation andDevelopment has begun to docu-ment age-specific differentials.Table 4-2 shows that per capitahealth expenditures for people aged65 and over are uniformly higherthan for the nonelderly, and thatthis difference varies by country.Much of the between-country differ-ence may be attributed to variationsin program coverage. In nationswhere relatively little long-term care

is included in public health schemes(e.g., Germany), per capita expendi-tures for people aged 65 and overmay be two to three times higherthan those for younger people; incountries with more inclusive long-term care coverage (e.g., Australiaand Finland), the ratio is four timeshigher (OECD, 1997).

Although the picture of rising healthcare costs with age is accurate in ageneral sense, disaggregation ofdata by age shows some surprisingfacets. A large fraction of healthcare costs associated with advanc-ing age is incurred in the periodjust prior to death, and since anincreasing proportion of people areliving to very old age, overall healthcare costs rise with age.Treatments to prolong life havemade once-certain death much lesscertain, but there is some indicationthat health care costs taper off atvery old ages (OECD, 1998b), sug-gesting that life may be prolongedup to a point but that treatment isnot desired indefinitely. Likewise,

among noninstitutionalized elderly,per capita health expenditure oftenpeaks at ages 75 to 79 and declinesthereafter. Costs per service (suchas hospital stays and medicine pre-scriptions) for older people are lessthan for the population as a whole,although usage rates for older peo-ple are much higher and hence theper capita costs are higher (OECD,1997). Governments and interna-tional organizations are now recog-nizing the need for cost-of-illnessstudies on age-related diseases, inpart to anticipate the likely burdenof increasingly-prevalent and expen-sive chronic conditions (of whichAlzheimer’s disease may be themost costly), and in part to under-stand the potentially salubriouseffects that may accrue to futuregenerations due to higher levels ofeducation and access to informationabout healthier lifestyle behaviors.

EARLY-LIFE CONDITIONSAFFECT ADULT HEALTH

The last decade has seen a rapidlygrowing interest in examining adulthealth outcomes from a life-courseperspective. Researchers increas-ingly suggest that many negativehealth conditions in adulthood stemfrom risks established early in life(Elo and Preston, 1992). Some(notably, Barker, 1995) argue thatadult health has a fetal origin,wherein nourishment in utero andduring infancy has a direct bearingon the development of risk factorsfor adulthood diseases (especiallycardiovascular diseases). Childhoodinfections may have long-termeffects on adult mortality. A WorldHealth Organization report statesunequivocally that slow growth andlack of emotional support in prena-tal life and early childhood reducephysical, cognitive, and emotionalfunctioning in later years (Wilkinsonand Marmot, 1998), as do certain


Table 4-2.Relative Per Capita Health Expenditure by Age Group in 12Countries: Circa 1993(0-64 = 1.0)

Country 65-74 65+ 75+

Australia . . . . . . . . . . . . . . . . . . 2.8 4.0 6.0Finland. . . . . . . . . . . . . . . . . . . . 2.8 4.0 5.5France . . . . . . . . . . . . . . . . . . . . 12.2 23.0 33.7Germany . . . . . . . . . . . . . . . . . . 2.3 2.7 3.2Japan . . . . . . . . . . . . . . . . . . . . . 43.1 4.8 35.7Netherlands . . . . . . . . . . . . . . . (NA) 4.4 (NA)New Zealand . . . . . . . . . . . . . . 2.3 3.9 6.2Portugal . . . . . . . . . . . . . . . . . . . 1.4 1.7 2.1Sweden . . . . . . . . . . . . . . . . . . . 2.3 2.8 3.4Switzerland . . . . . . . . . . . . . . . . 2.6 4.0 5.7United Kingdom (England). . . 2.5 3.9 5.6United States . . . . . . . . . . . . . . 3.1 4.2 5.2

NA Not available.

1Refers to ages 60-69.2Refers to ages 60+.3Refers to ages 70+.4Refers to ages 65-69.

Note: Data are relative to the level of per capita spending for people aged 0-64, whichis set at 1.0.

Source: OECD, 1997.

parental behaviors (particularlysmoking and alcohol consumption)and socioeconomic circumstances(e.g., poverty). Parental divorce hasbeen linked to decreased longevityof children (Schwartz et al., 1995).

While it seems intuitive that child-hood conditions should affect adultdevelopment and health outcomes,separating cohort effects from peri-od effects (e.g., from changing liv-ing conditions) is empirically diffi-cult. Indeed, some evidencesuggests that current conditionsmay be more important than early-life conditions; Kannisto (1996) hasfound period effects to be muchmore significant than cohort effectson oldest-old mortality (i.e., afterage 80). And in a study of cohortsborn just before, during, and justafter a severe famine in Finland inthe mid-1860s, the researchersfound no major differences in later-life survival; the extreme nutritionaldeprivation in utero and duringinfancy appeared not to translateinto higher adult mortality risks(Kannisto, Christensen, and Vaupel,1997). Such findings are likely tostimulate considerable futureresearch to explore the linkagesbetween lingering effects of early-life and survival at advanced ages(Vaupel, 1997).

SOCIOECONOMIC CORRELATESOF MORTALITY AND HEALTH

If early-life factors affect futurehealth and survival, then socioeco-nomic differences in childhood andthroughout life are likely to play anintrinsic role. A diverse and long-standing literature from the

industrialized world6 has identifieda number of socioeconomic factorsthat affect health and longevity:people with higher education tendto live longer (Kitigawa and Hauser,1973); being married encourageshealthier behaviors in U.S. adults,including people in old age (relativeto other marital statuses), and theeffects may be greater for oldermen than for older women (Schoneand Weinick, 1998); there are cleargradients in the United Kingdom inboth mortality and health when bro-ken down by social class, i.e., high-er social/occupational class is relat-ed to better health and loweredmortality risks (Devis, 1993;Wilkinson and Marmot, 1998); andamong the oldest old in Sweden,former white-collar workers hadbetter physical functioning than for-mer blue-collar workers (Parker,Thorslund, and Lundberg, 1994). Inthe United States (Crimmins,Hayward, and Saito, 1996) and inseveral European countries (Robineand Romieu, 1998), socioeconomicconditions more strongly affectfunctional change than mortality,which means that socioeconomicdifferences in active or healthy lifeexpectancy are greater than thosein total life expectancy. Such find-ings might be expected to haveimplications for the future healthstatus of elderly populations. For

example, if marriage equates withbetter health among olderindividuals, do rising rates ofdivorce and increased proportionsof never-married individuals por-tend poorer average health? Andwhat of other life dimensions? Aconsiderable amount of currentresearch is focused on not onlysocial but also psychological andbiological pathways by whichsocioeconomic status affects health(see, e.g., Adler et al., 1999).

While the weight of existing studiesclearly supports a strong relation-ship between social and economicfactors on the one hand and healthand mortality outcomes on theother, this relationship may not beas strictly predictive as some havesuggested. Research on marital sta-tus and health among the elderly inthe United States, for instance, hasshown that while widowhood is infact associated with poorer health,single women are likely to have bet-ter health outcomes than marriedwomen (Goldman, Korenman, andWeinstein, 1994). One Japanesestudy (Sugisawa, Liang, and Liu,1994) found no significant effect ofmarital status on the risk of dying;however, higher levels of social par-ticipation of older people werestrongly linked to lowered mortalityrisks. Research in Florence, Italyand Tampere, Finland uncovered nosystematic association betweenfunctional ability levels and educa-tion/previous occupation(Heikkinen, Jokela, and Jylha, 1996).In a study of nine industrializednations, differences in mortality byeducational level were found to befairly small in the Netherlands andthree Scandinavian nations, but


6 Research on socioeconomic correlates ofmortality and health in developing countries isstill sparse. Wu and Rudkin (2000) found thatlower socioeconomic status was associatedwith poorer health among Malaysians aged 50and over, and that this association held for allthree major ethnic groups (Malay, Chinese, andIndian). Liang et al. (2000) have found evi-dence of a socioeconomic gradient in old-agemortality in China, but they note that there aremajor differences between developed anddeveloping countries in terms of major healthparameters, and that much more work needs tobe done in validating gradients in Third Worldsettings.

much more substantial in largercountries such as the United States,France, and Italy. The authors sug-gest that between-country differ-ences may be related to differentsocial and economic policies. A 12-country study of occupationalclass and ischemic heart diseasemortality found the expected rela-tionship between lower class and

higher mortality in NorthernEuropean countries, but no suchrelationship in France, Switzerland,and Mediterranean nations (Kunst etal., 1999). Another multicountrystudy of income and mortalityimplies that the effect of income onmortality is largely determined bythe distribution of income within agiven nation (Duleep, 1995). Such

results point to the importance ofunderstanding population diversitywithin countries, and suggest thatpolicy planners pay particular atten-tion to socioeconomic differencesby gender and among subgroupswhen developing interventionstrategies (see Sacker et al., 2001and National Research Council,2001 for further discussion).


Urbanization is one of the mostsignificant population trends of thelast 50 years. Though we maythink of cities as synonymous withhistorical development, not until thenineteenth century did substantialportions of national populations liveand work in large cities, and only incertain parts of the world. In 1900,about 14 percent of the world’spopulation lived in cities (UnitedNations, 1991), and this percentagewas still below 20 by 1950.However, the global population ofall ages living in urban areas (asdefined by each country) more thandoubled between 1950 and 1975,and increased another 55 percentfrom 1975 to 1990. By 1995,about 46 percent (2.6 billion) of theearth’s people lived in urban areas(United Nations, 1998). Soon afterthe year 2000, the world likely willhave more urban dwellers thanrural dwellers. About three-fourthsof the population in developedcountries is urban, compared withslightly more than one-third indeveloping countries as a whole.However, the pace of urbanizationis much faster in the developingworld. And while the urban growthrate in most world regions hasbegun to decline, some parts of theglobe (notably Africa and SouthAsia) are now experiencing peakrates of urban growth. In spite ofdeclining growth rates, the world’surban population is projected tovirtually double between 1995 and2030, reaching a projected level of5.1 billion people (United Nations,1998).

Twentieth-century trends in urban-ization have stemmed from broad

economic and political changes.Closed national economies andtrading blocs have given way toopen economies that increasinglyare international in scope. In gener-al, the most rapidly-growingeconomies since 1950 also arethose with the most rapid increasein their levels of urbanization. Theworld’s largest cities tend to be con-centrated in the world’s largesteconomies (United Nations Centrefor Human Settlements, 1996).Urbanization is linked to changes inthe socioeconomic profile of aworkforce as workers shift frompredominantly agricultural pursuitsto industrial employment and thento services. Clark and Anker (1990)have shown that urbanization isrelated to decreased participation ofolder people in the labor force. Indeveloped countries, this decreaseaccompanies a decline in manufac-turing employment, an increasedprevalence of early retirementschemes, and lower levels of educa-tion and job flexibility among olderworkers relative to younger work-ers. In urban areas of developingnations, the increased importanceof the formal sector tends toexclude older workers who find itdifficult to compete with better-educated younger workers. Withurbanization come changes in thefamily unit and kinship networksthat have both beneficial andadverse consequences for the well-being of elderly members.

Urban growth affects all age groupsof a population. Since urbanizationoften is driven by youthful migra-tion from rural areas to cities, itinfluences the age distribution in

both sending and receiving areas.Definitions of urban and rural resi-dence often differ greatly from onecountry to the next, which compli-cates global and regional discus-sions of urbanization. The view ofthe United Nations has been that“differences in definition may reflectdifferences in the characteristic fea-tures of urban and rural settlementsconsidered most relevant in individ-ual countries” (United Nations,1973). In spite of definitional incon-sistencies, the basic questions con-cerning aging are similar in all soci-eties: are the elderly increasinglyconcentrated in particular areas? Ifso, what are the implications forsocial support and delivery of serv-ices? For individual cities, dochanges in age structure bringabout demands to reorder budgetpriorities?

DEVELOPED-COUNTRYELDERLY ABOUT THREE-FOURTHS URBAN; ONE-THIRDIN DEVELOPING COUNTRIES

In keeping with the worldwide pat-tern of increased urbanization, theelderly population has becomemore concentrated in urban areasduring the past 50 years. In devel-oped countries as a whole, an esti-mated 73 percent of people aged65 and over lived in urban areas in1990, and this figure is projected toreach 80 percent by the year 2015.In developing nations, which stillare predominantly rural, just overone-third (34 percent) of peopleaged 65 and over were estimated tolive in urban areas in 1990. Thisproportion is expected to exceedone-half by the year 2015 (UnitedNations, 1991).


CHAPTER 5.

Urban and Rural Dimensions

The elderly of Africa are more likelyto live in rural areas than are theelderly of other regions, eventhough the African population over-all is slightly more urbanized thanthat of the Asia/Oceania region(excluding Japan). The aggregatetrend toward urbanization isstronger in Asia than in Africa, how-ever. Half of the Asia/Oceania eld-erly are projected to live in cities by2015, compared with 42 percent in Africa.

As a region, Latin America and theCaribbean is already highly urban-ized. The proportion of elderly inurban locales is very similar to thatof the developed-country average.Unlike in other developing areas,the elderly in Latin America and theCaribbean have been somewhatmore likely than the general popula-tion to live in cities (Heligman,Chen, and Babakol, 1993).

ELDERLY MORE LIKELY THANNONELDERLY TO LIVE IN RURAL AREAS

Despite the increasingly urbannature of today’s elderly popula-tions, rural areas remain dispropor-tionately elderly in a majority ofcountries. In most nations, this isprimarily the result of the migrationof young adults to urban areas, andto some extent of return migrationof older adults from urban areasback to rural homes. Data for 39countries from the period 1989 to1997 show that the percent of allelderly living in rural areas washigher than the percent of totalpopulation in rural areas in 27 ofthe 39 nations, with no differencein 4 nations (Figure 5-1). Five ofthe eight countries where the elder-ly were less likely than the totalpopulation to live in rural areas arepredominantly-Muslim nations thatwere formerly part of the SovietUnion. Differences in the share of


Figure 5-1.

Percent of Total and Elderly Population Living in Rural Areas in 39 Countries


United States, 1990

New Zealand, 1991

Ecuador, 1990

Chile, 1997

Brazil, 1991

Bolivia, 1992

Uzbekistan, 1989

Ukraine, 1995

Tajikistan, 1993

Russia, 1995

Moldova, 1989

Lithuania, 1996

Latvia, 1996

Krygyzstan, 1997

Kazakhstan, 1996

Georgia, 1993

Estonia, 1996

Belarus, 1997

Azerbaijan, 1989

Armenia, 1992

Sweden, 1990

Norway, 1990

Greece, 1991

France, 1990

Austria, 1991

Turkey, 1990

Thailand, 1990

South Korea, 1995

Philippines, 1990

Malaysia, 1991

Japan, 1995

Indonesia, 1990

China, 1990

Bangladesh, 1991

Zimbabwe, 1992

Zambia, 1990

Tunisia, 1994

South Africa, 1991

Botswana, 1991

Total Aged 65+

Africa

Asia

Europe

Former Soviet Union

Latin America/Other

54

43

39

61

69

70

37

42

85

86

80

74

69

22

49

51

22

81

41

85

76

74

28

54

54

43

84

51

35

26

41

28

17

31

31

49

32

17

32

46

31

30

44

45

66

31

32

53

27

71

32

59

32

45

53

31

51

42

60

33

44

65

32

64

44

52

43

24

15

45

15

25

59

24

17

49

10

25

total versus elderly populationresiding in rural areas are moststriking in Belarus, Bolivia,Botswana, Zambia, and Zimbabwe.

SEX RATIOS OF URBANELDERLY TYPICALLY LESSTHAN 80

An examination of national data for54 countries from the period 1986to 1997 shows that more elderlywomen than elderly men have beenrecorded in urban areas in allexcept eight nations, six of whichare in Africa. Sex ratios (number ofmen per 100 women) for the urbanelderly usually are well below 100(Figure 5-2), and are below 50 inparts of the former Soviet Union.

ELDERLY MEN MORE LIKELYTHAN ELDERLY WOMEN TORESIDE IN RURAL AREAS

Since women live longer than menvirtually everywhere, we mightexpect to see sex ratios of less than100 for the elderly throughout agiven population. Although olderwomen outnumber older men inalmost every nation, the ratio ofolder men to older women general-ly is higher in rural areas than incities. In the rural areas of somecountries — e.g., New Zealand,Paraguay, and Sweden — older menactually outnumber older women.This rural male surplus is seen mostprominently in many countries ofLatin America and the Caribbean,which suggests region-specific pat-terns of gender-specific migrationthat have implications for healthand social security systems in bothrural and urban areas.


Figure 5-2.

Urban Sex Ratios for Persons Aged 65 and Over: 1986 or Later


Uruguay, 1990United States, 1990

Peru, 1993New Zealand, 1991

Mexico, 1995Ecuador, 1990

Costa Rica, 1995Colombia, 1993

Chile, 1997Canada, 1991

Brazil, 1991Bolivia, 1992

Australia, 1986Argentina, 1995

Ukraine, 1995Russia, 1995

Moldova, 1989Lithuania, 1996

Latvia, 1996Georgia, 1993Estonia, 1996Belarus, 1997

Armenia, 1992

Sweden, 1990Poland, 1994

Norway, 1990Hungary, 1995

Greece, 1991France, 1990

Czech Republic, 1994Bulgaria, 1994Austria, 1991

Turkey, 1990Thailand, 1990

South Korea, 1995Singapore, 1990

Philippines, 1990Pakistan, 1990Malaysia, 1991

Japan, 1995Israel, 1994

Indonesia, 1990China, 1990

Bangladesh, 1991

Zimbabwe, 1992Zambia, 1990Tunisia, 1994

Tanzania, 1988South Africa, 1991

Malawi, 1987Kenya, 1989Egypt, 1986

Cote d'Ivoire, 1988Botswana, 1991

(Males per 100 females)

Africa

Asia

Europe

Former Soviet Union

Latin America/Caribbean/Other

67

69106

123106109

7989

99134

108

13786

8276

7080

11377

8155

7577

5177

6162

7359

6657

69

664948

5446

5254

4450

6770

7776

6764

8077

8281

7087

64

Conversely, elderly women tend tobe somewhat more likely than eld-erly men to live in urban areas(Figure 5-3).1 The gender differencein residential concentration proba-bly is related to marital status andhealth. As discussed in Chapter 6,elderly women are much more like-ly than elderly men to be widowed,and also are more likely to havechronic illnesses. One study of theelderly in developed countries(Kinsella and Taeuber, 1993) notedan inverse relationship betweenwidowhood rates and sex ratios inurban areas. Urban residence mayprovide elderly women, especiallywidows, the benefits of closer prox-imity to children and/or to socialand health services.

SUBNATIONAL URBAN/RURALDIFFERENCES IN AGESTRUCTURE MAY BE STRIKING

The profile of aging in subnationalareas may be very different whenexamined in view of urban/rural dif-ferences. In Russia’s 73 oblasts(administrative areas), for example,the rural population of manyoblasts is skewed in favor of olderpeople.2 Figure 5-4 displays the ageand sex distribution of urban ver-sus rural populations in the KurskOblast, located in the CentralChernozem Region borderingUkraine. The pyramid for the ruralpopulation has a particularly oddshape, with people aged 65 andolder accounting for nearly one-fourth of the total population. Incontrast, the urban population ofKursk is 12 percent elderly, about

the same as the overall nationalaverage. The majority of Kursk’surban population is concentrated inthe working ages, which is not truein the rural areas. These pyramidsalso show disparities in sex compo-sition. Nearly 31 percent of Kursk’srural females are aged 65 and older,compared with just 15 percent ofrural males. The sex ratio for therural elderly population is 41 menper 100 women.

Kursk is not the only Russian oblastto have a large proportion of itsrural population, particularlywomen, in older age groups. Inseveral other oblasts, more thanone-fourth of the rural female popu-lation is aged 65 or over. In sevenoblasts, elderly women account for30 percent of the entire rural female

population. One reason that ruralareas have such high proportions inolder age groups is out-migration ofyounger people to urban areas insearch of work. Out-migration ofyoung people may leave olderwomen and men without the directsupport of their family. Harsh livingconditions and lack of amenities inmany rural areas pose additionaldifficulties for the elderly. In 1996,for instance, official statistics indi-cate that only 23 percent of Russia’srural population had running waterin their homes, and only 3 percenthad indoor toilet facilities.

Skewed age structures may presentproblems for certain localities interms of the provision of servicesand aid to older people. Skeldon(1999) has noted, based on the


Figure 5-3.

Percent of All Elderly Living in Urban Areas by Sex in Ten Countries

13Zimbabwe, 1992

Tunisia, 1994

South Korea, 1995

Colombia, 1993

China, 1990

United States, 1990

Russia, 1995

Poland, 1994

New Zealand, 1991

France, 1990

Developed countries


MaleFemale

68

87

54

69

73

24

67

55

56

16

72

92

57

67

77

24

75

59

61

Source: United Nations Demographic Yearbook, 1996.

1 Grewe and Becker (2000), in a preliminaryexamination of within-country migration ratesfor 65 countries with 128 observations fromthe period 1952-1996, also have noted a likelytrend toward disproportionate shares of elderlywomen in urban areas, and of elderly men inrural areas.

2 Although Russia is highly urbanized (over70 percent of the population lives in urbanareas), its rural population remains substantial,numbering approximately 40 million in 1996.

experiences of Japan and Korea, theconfluence of overall populationaging with rural depopulation andstagnation of small and medium-sized towns, and suggests that thispattern will be seen increasinglythroughout Asia in the first half ofthis century. A similar situation hasbeen noted by Golini (2000) withregard to Italy. While there are fewif any negative national economicconsequences associated with thisdevelopment, it seems clear that

important emerging issues willrevolve around the social conditionsof elderly individuals in relativelyisolated rural areas.

NO CLEAR TREND TOWARDDISPROPORTIONATE AGING OFLARGE CITIES

Although rural areas tend to be dis-proportionately elderly comparedwith urban areas in general, datafor some large cities reveal a rela-tively high proportion of elderly

residents. In countries where theyouthful influx of rural-to-urbanmigrants has slowed in recentdecades, many cities may now haveaging populations (Chesnais, 1991).Conversely, in countries whereurbanization rates remain high andyounger residents continue to gravi-tate toward cities, one wouldexpect the proportion of elderly incities to be lower than for the coun-try as a whole. Data for 13 majorcities (Table 5-1), however, do not


Figure 5-4.

Urban and Rural Population in Kursk Oblast: 1996


Urban

Thousands

40 30 20 10

0-45-9

10-1415-1920-2425-2930-3435-3940-4445-4950-5455-5960-6465-6970-7475-7980-84

85+

0 10 20 30 40

Rural

40 30 20 10

0-45-9

10-1415-1920-2425-2930-3435-3940-4445-4950-5455-5960-6465-6970-7475-7980-84

85+

0 10 20 30 40

Male FemaleAge

lend themselves to a clear interpre-tation of trends. The populations ofBudapest, London, and Moscow arein fact older than their respectivenational averages, but this is notthe case in Berlin, Paris, and Tokyo.Bangkok and Harare are youngerthan Thailand and Zimbabwe as awhole, but a similar relationshipdoes not hold in the Chinese citiesof Beijing and Shanghai, nor inMexico City. In the United States ingeneral, census data from 1960through 1990 indicate that the cen-tral cities of metropolitan areashave, on balance, consistently lostelderly migrants to nonmetropolitanareas (Fuguitt and Beale, 1993).

ARE RURAL ELDERLYDISADVANTAGED?

The exodus of younger people fromthe countryside to cities raises therural proportion of elderly residentsin many countries. As a result, tra-ditional family support systems forthe frail elderly may change.Younger family members living inurban areas are unlikely to providedirect care for distant elders remain-ing in rural areas. At the sametime, younger family members whomove to cities may have improvedfinancial resources that can be usedto help elderly relatives still living inthe rural birthplace.

Quality-of-life issues for older popu-lations in rural versus urban areasare beginning to receive additionalattention as migration streamsincrease and the costs of healthcare and public benefits escalate.Whereas graying rural communitieswere once associated with negativesocioeconomic consequences, morerecent research in developed coun-tries has considered positive resultsthat may stem from increased pro-portions of increasingly affluent eld-erly (Bean et al., 1994). Data from

Wales (Wenger, 1998) suggest thatrural dwellers are more likely thantheir urban counterparts to beinvolved in community and volun-tary activities. Nevertheless, theprovision of health and other sup-portive services to ill and disabledolder people in rural areas contin-ues to present special challenges.Perhaps because of these difficul-ties, the percentage of older dis-abled people remaining in thecommunity without being institu-tionalized is lower in predominantlyrural areas than in urban areas(Suzman, Kinsella, and Myers,1992).

MIGRATION PATTERNS OFOLDER PEOPLE NOT WELLDOCUMENTED

International migration of elderlypeople, as noted in Chapter 2, isnot a significant demographic factorin many countries. Within-countrymigration, however, may be sub-stantial. One common perceptionof older people is that they tend tobe much less mobile than youngerpeople, typically “aging in place” incommunities that have been homefor many years. While this may betrue in a general sense, variousnational studies suggest that geo-graphical mobility among older


Table 5-1.Percent of Older Population in 13 Cities Compared WithRespective National Average

City YearAge

groupCity

percentCountrypercent

Bangkok,Thailand. . . . . . . . . . . . . . . . . . . . . . . . . . 1995 65+ 4.2 5.4

Beijing,China . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1990 65+ 6.2 5.6

Berlin,Germany . . . . . . . . . . . . . . . . . . . . . . . . . . 1993 65+ 13.7 15.1

Budapest,Hungary. . . . . . . . . . . . . . . . . . . . . . . . . . 1990 60+ 21.5 18.9

Buenos Aires,Argentina . . . . . . . . . . . . . . . . . . . . . . . . . 1991 65+ 8.2 8.9

Harare,Zimbabwe . . . . . . . . . . . . . . . . . . . . . . . . 1992 65+ 1.6 3.3

Greater London,United Kingdom . . . . . . . . . . . . . . . . . . . 1991 65+ 14.4 10.0

Mexico City,Mexico . . . . . . . . . . . . . . . . . . . . . . . . . . . 1995 65+ 5.2 4.4

Moscow,Russia . . . . . . . . . . . . . . . . . . . . . . . . . . . 1989 65+ 12.0 9.6

New York,United States . . . . . . . . . . . . . . . . . . . . . 1990 65+ 13.0 12.6

Paris,France . . . . . . . . . . . . . . . . . . . . . . . . . . . 1990 60+ 15.7 19.9

Shanghai,China . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1990 65+ 10.1 5.6

Tokyo,Japan . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1990 65+ 9.4 12.0

Note: Data for Mexico City refer to the Federal District.

Source: Compiled by the U.S. Census Bureau from national statistical volumes.


people is increasing. In the 1970s,the mobility of the Japanese popula-tion declined in all age groups withthe exception of the elderly (Otomoand Itoh, 1989). Census data forCanada show that 23 percent of allpeople aged 60 and over changedtheir principal residence at leastonce during the 5-year period 1986to 1991. Thirteen of the fifty statesin the United States had net elderlyinmigration rates of more than 10per 1,000 elderly population duringthe 1985-90 period, and one out offive residents of Florida is now aged65 or older. A “retirement effect,”i.e., an increase in mobility rates atages 60 to 64, has been noted inthe United States and the UnitedKingdom (Long, 1992). Refugeemovements in Bosnia, Mozambique,and elsewhere have involved vastnumbers of older people (Kalache,1995) who are often overlooked inrelief operations that focus on chil-dren and young adults.

One of the few cross-national stud-ies of elderly migration (Rogers,1988) identified two basic patterns.One is characterized by amenity-motivated, long-distance relocation,the other by intracommunity,assistance-motivated short-distancemoves. Available studies in devel-oped countries suggest that the lat-ter are much more common,although the former may become

more prevalent as levels ofeducation and retirement incomeincrease. In the United States, theoldest old have been seen to movemore frequently than younger elder-ly, suggesting that the moves of theoldest old are related to healthproblems and the need for differentliving arrangements (Hobbs andDamon, 1996). Recent Canadiansurvey data find that older peoplemoved most often because of thesize of their home (usually optingfor a smaller residence), a desire tolive in a better neighborhood, or tobuild/purchase a home (Che-Alfordand Stevenson, 1998). Amongolder Canadians with daily activitylimitations in 1991, the percentwho moved in the previous 5 yearswas roughly the same as among theoverall older population (22 per-cent), but about one-third of thesepeople relocated to homes withspecial health features. A Germanstudy of motivating factors for eld-erly mobility in the city ofHeidelberg (Oswald, Wahl, andGang, 1997) suggests that basicneeds (e.g., health) were roughly asimportant as “higher-order” needssuch as privacy.

Information on migration patternsof older people in developing coun-tries is fragmented at best.Although rural-to-urban migrationusually is associated with younger

adults, there is mounting evidencethat the movement of older peopleto urban areas is becoming signifi-cant (Myers and Clark, 1991).There is much less empirical infor-mation on the topic of return migra-tion of older people to rural placesof origin. One review of availabledata for Africa (Becker, 1991) con-cludes that, while return migrationof older people to their ancestralhomes is not uncommon, severalfactors — growing land pressure,formalization of rural propertyrights, the increasing viability offamily support for elders in urbanareas — will dampen the likelihoodof future return migration. Skeldon(1999) notes that, while returnmigration may increase the size ofolder rural cohorts and aggravatesocial support issues, returnmigrants also may bring with themwealth, knowledge, and otherresources, particularly in the formof pension income earned duringyears spent in the urban labor mar-ket. Migration from and withindeveloping countries in general hascome to be seen as a strategic fami-ly decision rather than as an indi-vidual decision on the part of youngleavers (Vatuk, 1995). To the extentthat migration raises familyincomes and the ability to reunitemembers, increased movement ofolder people may be expected inthe future.

One common characteristic of pop-ulations throughout the world is thepreponderance of women at olderages. Women are the majority ofthe elderly population in the vastmajority of countries, and theirshare of the population increaseswith age. This gender imbalance atolder ages has many implicationsfor population and individual aging,perhaps the most important ofwhich involve marital status and liv-ing arrangements. As discussedfurther in Chapter 8, family mem-bers are the main source of emo-tional and economic support for theelderly, although in some developedcountries the state has assumed alarger share of the economicresponsibilities.

Marital status strongly affects manyaspects of one’s life. Studies indeveloped countries show that mar-ried people, particularly marriedmen, are healthier and live longerthan their nonmarried counterparts(Goldman, 1993; Hadju, McKee, andBojan, 1995; Waite, 1995; Schoneand Weinick, 1998). Older marriedcouples tend to be more financiallysecure than nonmarried people.Changes in marital status at olderages can affect pension potential,retirement income, and an individ-ual’s social support network; manyolder widowed men, in particular,may lose contact with much of theirsupport network after their wifedies (O’Bryant and Hansson, 1996).In contrast, widowed women tendto maintain their support networkafter the death of a spouse (Scottand Wenger, 1995). Marital statusalso influences one’s living arrange-ments and affects the nature of

caregiving that is readily availablein case of illness or disability.

HIGHER MALE MORTALITYRESULTS IN GENDERIMBALANCE AT OLDER AGES

The primary reason for the numeri-cal female advantage at older agesis the sex differential in mortalitydiscussed in Chapter 3. Althoughmore boys than girls are born,males typically have higher mortali-ty rates than females. The sex dif-ferential in mortality begins at birthand continues throughout the lifecourse. One outcome of higher

male mortality rates is that betweenage 30 and 40, women usuallybegin to outnumber men. In mostcountries, the relative female advan-tage increases with successivelyolder age (Figure 6-1).

WORLD WAR II IS STILLEVIDENT IN SEX COMPOSITIONAT OLDER AGES

Historical events can play a majorrole in shaping the gender composi-tion at older ages. For instance, thelingering effects of heavy war mor-tality during World War II still can beseen in the proportion female atolder ages in certain countries. In


CHAPTER 6.

Sex Ratios and Marital Status

Figure 6-1.

Percent Female for Older Age Groups: 2000


United States

India

Brazil

Germany

Russia

65-69 70-74 75-79 80+

Age

66

6266

75

80

5358

6774

5659

61

67

49

50

4948

5456

58

Russia, women account for 80 per-cent of the oldest old (aged 80 andolder) and in Germany they repre-sent nearly 74 percent. In con-trast, women account for only two-thirds of the oldest-old populationin Brazil and the United States.

THERE IS GREAT NATIONALDIVERSITY IN SEX RATIOS AMONG ELDERLY

A sex ratio is a common measureused to portray a population’s gen-der composition. A sex ratio is con-ventionally defined as the numberof men per 100 women in a givenpopulation or age category. Sexratios greater than 100 indicatemore men than women, and sexratios under 100 indicate thereverse (i.e., more women thanmen). In most countries of theworld, sex ratios at older ages arebelow 100, in some cases quite abit below (e.g., Russia’s sex ratio is46 men per 100 women aged 65and older). Developed countriestend to have lower sex ratios atolder ages than do developingcountries (Figure 6-2), althoughthere are many exceptions to thisgeneralization. The typical differ-ence between developed and devel-oping countries is explained by sexdifferentials in life expectancies atbirth. As shown in Chapter 3,developed countries tend to havelarger sex differentials in lifeexpectancy at birth than do devel-oping countries, which results ingreater numbers of women thanmen at older ages.

PROJECTED TREND IN SEXRATIO DIFFERS BYDEVELOPMENT STATUS

In the future, sex ratios at olderages are projected to move in oppo-site directions in the aggregate


Figure 6-2.

Sex Ratio for Population 65 Years and Over: 2000 and 2030


Zimbabwe

Turkmenistan

Turkey

Mexico

Kyrgyzstan

India

Guatemala

Brazil

Bangladesh

Argentina

United States

United Kingdom

Ukraine

Sweden

Russia

New Zealand

Italy

France

Canada

Australia

20002030

(Males per 100 females)

Developed countries


78

74

68

70

77

46

73

49

71

71

81

79

74

76

79

58

80

53

80

80

71

119

68

88

103

60

81

86

62

103

75

98

70

81

91

63

71

86

65

58

developed and developing worlds.Between today and 2030, sex ratiosfor the elderly are expected toincrease in many developed coun-tries because the gender gap in lifeexpectancy is projected to narrow(Figure 6-3). In other words, mostdemographers expect that male lifeexpectancies in developed countriesare likely to improve at a fasterpace than female life expectancies.The opposite is anticipated in manydeveloping countries. In view ofthe historical pattern in developednations, sex differentials in develop-ing-country life expectancies areprojected to widen, which will inturn lead to lower future sex ratios.

Regardless of the projected trends,women are expected to make upthe majority of the world’s elderlypopulation (particularly at the old-est ages) well into the next century.Continuing or growing disparities insex ratios mean that many of thechallenges and problems faced bythe elderly of today and tomorroware, in essence, challenges andproblems faced by older women.

Sex ratios at younger ages in somecountries of the world already arequite skewed in favor of women.This imbalance may be due toexcess male mortality at youngages because of wars and otherforms of violence, disease, or todisproportionate out-migration ofyoung men seeking work in othercountries. If mortality is the causeof such severe sex ratios at youngerages, then the implications for theeventual aging of these cohorts isdifferent than if the cause is


Figure 6-3.

Aggregate Sex Ratios for Older Age Groups: 2000 and 2030


81

57

86

6672

45

91

70

80+65-7980+65-79

20002030

Developed countries Developing countries

Table 6-1.Sex Ratios for Population Aged 65 and Over for CountriesWith More Elderly Men Than Women: 2000

Country Sex ratio

Qatar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 243United Arab Emirates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 226Kuwait . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 182Sudan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133Bangladesh. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119Saudi Arabia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118Iran . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112Taiwan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113Afghanistan. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112Niger . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111Oman. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111The Gambia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111Eritrea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104Yemen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104Bahrain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104Bhutan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103India . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103Tunisia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101



Figure 6-4.

Percent Married at Older Ages


MaleFemale

75+

65-74

55-64

75+

65-74

55-64

75+

65-74

55-64

75+

65-74

55-64

75+

65-74

55-64

75+

65-74

55-64

75+

65-74

55-64

75+

65-74

55-64

75+

65-74

55-64

75+

65-74

55-64

DEVELOPED COUNTRIES DEVELOPING COUNTRIES

Canada, 1991

Belgium, 1998

United States, 1995

Japan, 1990

Czech Republic, 1991

Argentina, 1991

Indonesia, 1990

Chile, 1992

South Korea, 1995

Zimbabwe, 1992

21

83

80

67

71

54

24

82

80

65

74

56

23

79

78

68

66

53

25

92

89

74

77

54

21

84

80

60

65

42

14

79

76

63

61

42

17

90

84

70

55

33

18

74

69

59

57

42

22

94

88

72

66

34

11

90

85

78

60

39


Figure 6-5.

Percent Widowed at Older Ages


MaleFemale

75+

65-74

55-64

75+

65-74

55-64

75+

65-74

55-64

75+

65-74

55-64

75+

65-74

55-64

75+

65-74

55-64

75+

65-74

55-64

75+

65-74

55-64

75+

65-74

55-64

75+

65-74

55-64

DEVELOPED COUNTRIES DEVELOPING COUNTRIES

Canada, 1991

Belgium, 1998

United States, 1995

Japan, 1990

Czech Republic, 1991

Argentina, 1991

Indonesia, 1990

Chile, 1992

South Korea, 1995

Zimbabwe, 1992

73

3

8

22

14

33

64

4

9

27

13

33

67

3

9

22

13

33

65

3

8

24

14

39

75

4

11

33

23

48

77

5

11

25

22

44

70

6

11

22

39

61

76

5

12

26

19

37

60

5

11

28

33

65

88

3

7

14

31

54

migration and the migrants returnto their native country when theyretire (or return for other reasons).

ELDERLY MEN OUTNUMBERELDERLY WOMEN IN SOMECOUNTRIES

While women outnumber men atolder ages in most countries, thereare 18 countries in Asia and Africawhere available data suggest thatthe reverse is true (Table 6-1). Onelikely explanation involves the socialstatus of women versus men in cer-tain cultures. The relatively lownumbers of women at older agesmay reflect past levels of higherfemale than male mortality, whichcould be related to discriminatorytreatment accorded girls and womenthroughout their lifetime. High sexratios at older ages also may be sta-tistical artifacts. That is, women(especially older women) may beundercounted to a greater extentthan men in some national census-es, insofar as men are more likely tointeract with census enumeratorsand may neglect to provide informa-tion on all female household mem-bers. Furthermore, certain concen-trated patterns of male labormigration may affect sex ratios tothe extent that a significant portionof migrants remains in the hostcountry after reaching age 65.

OLDER MEN ARE MARRIED;OLDER WOMEN ARE WIDOWED

Older men are more likely to bemarried and older women are morelikely to be widowed in most coun-tries of the world (Figures 6-4 and6-5). In all but six of the 51 studycountries with data on martial sta-tus, over 70 percent of men aged65 and older were married. Even atages 75 and older, a majority ofmen were married. In contrast,only 30 to 40 percent of women

aged 65 and over were married inmost study countries. Elderlywomen are much more likely to bewidowed. In 32 of the study coun-tries, over half of elderly women arewidowed.

For both men and women, the pro-portion married decreases witholder age and the proportion wid-owed increases. However, genderdifferences in survival and other fac-tors (see below) result in very differ-ent average ages of widowhood/widowerhood. In the case ofBelgium in 1998, 82 percent of menaged 55 to 64 were married, com-pared with 74 percent of women inthat age group. At ages 75 andover, 65 percent of men were stillmarried, compared with only 23 percent of women. The genderdifference in proportions widowed iscorrespondingly pronounced (Figure6-6). Data for Zimbabwe show that

3 percent of men and 31 percent ofwomen aged 55 to 64 were wid-owed in 1992. At ages 75 and over,the respective figures were 14 percent of men and 73 percentof women. These data are typical ofthe pattern seen in both developedand developing countries.

The gender difference in marital sta-tus results from a combination offactors. The first is the aforemen-tioned sex difference in longevity;women simply live longer thanmen. Secondly, women tend tomarry men older than themselveswhich, combined with the sex dif-ference in life expectancy, increasesthe chance that a woman will findherself without a spouse in herolder age. Furthermore, older wid-owed men have higher remarriagerates than older widowed women inmany countries, often as a functionof cultural norms (Velkoff and


Figure 6-6.

Percent Widowed in Belgium: 1998

Source: Belgium National Institute of Statistics, 1998.

0

20

40

60

80

100

100+90-9480-8470-7460-6450-5440-4430-3420-24

Percent

Age

Female

Male

Kinsella, 1993; Cattell, 1997). Thefact that women are likely to losetheir spouse has important econom-ic consequences for individuals andsocieties. A comparison of longitu-dinal data from Germany and theUnited States revealed that,although the level of poverty is dif-ferent in the two counties, mostwomen in both nations experienceda decline in living standards uponwidowhood, and many fell intopoverty as a result of the loss ofpublic/private pension support(Hungerford, 2001).

ELDERLY MORE LIKELY TO BEMARRIED THAN IN THE PAST

Over the last two or three decades,the marital status of the elderly haschanged. In a majority of the studycountries, the proportion of oldermen and women who are marriedhas increased slightly and the pro-portion who are widowed has

decreased. Some of the change isattributable to improved joint sur-vival of husbands and wives (Myers,1992). In certain countries, someof the change can be explained bythe different marital experiences ofbirth cohorts. For instance, thediminishing effects of World War IIcan be seen when the widowhoodrates of older women in Russia arecompared for 1979 and 1994. In1979, 72 percent of older women inRussia were widowed while only 58 percent were widowed in 1994.By 1994, the cohorts that weremost affected by the war were aged75 and older.

SMALL PROPORTIONS OFELDERLY HAVE NEVER MARRIED

Relatively few elderly in most coun-tries have never married. In morethan half of the study countries, 5 percent or less of elderly men and10 percent or less of elderly women

have never married. In someEuropean countries, the largerproportions of elderly women whohave never married may be attribut-able to World War II. Many oftoday’s elderly women were ofprime marriage age soon after thewar, when there was a shortage ofpotential spouses due to wardeaths. Higher-than-average pro-portions of never-married elderlyare found in several Latin Americanand Caribbean nations, which couldbe a function of the prevalence ofconsensual unions. While the cate-gory “consensual union” is widelyused in census tabulations in thesecountries, some people living (orwho have lived) in a consensualunion are likely to report them-selves to be never married.

FUTURE ELDERS MORE LIKELYTO BE DIVORCED

Percentages currently divorcedamong elderly populations tend tobe low. However, this will changein the near future in many countriesas younger cohorts with higher pro-portions of divorced/separated peo-ple move into the ranks of the eld-erly (Gierveld, 2001). For instance,in 1999 in the United States, around9 percent of the elderly weredivorced or separated comparedwith nearly 15 percent of men and19 percent of women aged 55 to64. The proportion divorced/sepa-rated is higher still for the agegroup 45 to 54 (Figure 6-7). Thechanging marital composition of theelderly population as these youngercohorts reach age 65 will affect thenature and types of support servic-es that both families and govern-ments may need to provide, espe-cially with regard to the growingnumber of elderly who lack directfamilial support (Pezzin and Schone,1999).


Figure 6-7.

Percent Divorced and Separated in the United States: 1999


17.6

20.821.7

18.6

9.3

15.8

18.0 17.8

15.1

8.8

65+55-6445-5440-4435-39

MaleFemale

Age group

Living arrangements are affected bya host of factors including maritalstatus, financial well-being, healthstatus, and family size and struc-ture, as well as cultural traditionssuch as kinship patterns, the valueplaced upon living independently,the availability of social servicesand social support, and the physicalfeatures of housing stock and localcommunities. On the individuallevel, living arrangements aredynamic, representing both a resultof prior events and an antecedentto other outcomes (Van Solinge,1994). On the societal level, pat-terns of living arrangements amongthe elderly reflect other characteris-tics — demographic, economic, andcultural — which influence the cur-rent composition and robustness ofolder citizens. In turn, livingarrangements affect life satisfaction,health, and most importantly for

those living in the community, thechances of institutionalization.

Three major observations emergefrom a cross-national comparison ofliving arrangements of the elderly.First, women in developed coun-tries are much more likely than mento live alone as they age; older menare likely to live in family settings.Second, both elderly men andwomen in developing countriesusually live with adult children.Third, the use of nonfamily institu-tions for care of the frail elderlyvaries widely around the world.

MORE THAN HALF OF ELDERLYDANISH WOMEN LIVE ALONE

Table 7-1 presents data from the1990s on proportions of older peo-ple living alone in what are usuallyconsidered to be private (i.e., nonin-stitutional) households. Sincewomen outlive men in virtually all

countries of the world, it is notsurprising to find that the share ofolder women living alone is higherthan that of men. For elderly men indeveloped countries, the propor-tions range from a low of 5 percentin Japan to a high of 25 percent inSweden. Proportions of elderlywomen residing singly are univer-sally higher, reaching half or morein Denmark, Germany, and Sweden.Percentages in developing countriestend to be much lower, althoughthe levels for men and women insome countries (e.g., Argentina,Cyprus) rival those of certainEuropean nations. Again, olderwomen are more likely than oldermen to live alone; St Lucia andTaiwan are the only exceptions inTable 7-1.

The gender gap for those livingalone generally increases with age(Figure 7-1). However, for countries


CHAPTER 7.

Living Arrangements

Table 7-1.Percent of Elderly Population Living Alone: Data From 1990 to 1999

Developed countries Male Female Developing countries Male Female

Australia . . . . . . . . . . . . . . . . . . . . . 13.7 29.3 Argentina . . . . . . . . . . . . . . . . . . . . 11.2 21.1Canada . . . . . . . . . . . . . . . . . . . . . . 14.1 33.7 Aruba . . . . . . . . . . . . . . . . . . . . . . . 12.5 15.4Czech Republic . . . . . . . . . . . . . . . 19.0 47.5 Bolivia. . . . . . . . . . . . . . . . . . . . . . . 13.2 15.7Denmark . . . . . . . . . . . . . . . . . . . . . 23.3 52.0 Cyprus . . . . . . . . . . . . . . . . . . . . . . 10.6 24.8Finland. . . . . . . . . . . . . . . . . . . . . . . 19.5 46.5 Hong Kong . . . . . . . . . . . . . . . . . . 11.6 13.2France . . . . . . . . . . . . . . . . . . . . . . . 15.3 40.2 Mexico . . . . . . . . . . . . . . . . . . . . . . 7.5 14.0Germany . . . . . . . . . . . . . . . . . . . . . 16.9 50.8 Morocco (60+) . . . . . . . . . . . . . . . 11.3 44.7Greece. . . . . . . . . . . . . . . . . . . . . . . 8.7 22.8 Philippines(60+) . . . . . . . . . . . . . . 4.4 6.4Ireland . . . . . . . . . . . . . . . . . . . . . . . 18.9 27.7 South Korea(60+) . . . . . . . . . . . . 3.1 11.8Japan . . . . . . . . . . . . . . . . . . . . . . . . 5.2 14.8 St. Lucia. . . . . . . . . . . . . . . . . . . . . 20.9 18.9New Zealand . . . . . . . . . . . . . . . . . 17.8 38.0 Taiwan . . . . . . . . . . . . . . . . . . . . . . 13.0 7.4Norway . . . . . . . . . . . . . . . . . . . . . . 21.3 44.7 Thailand(60+) . . . . . . . . . . . . . . . . 2.9 5.5Portugal . . . . . . . . . . . . . . . . . . . . . . 9.4 23.9 Vietnam(60+) . . . . . . . . . . . . . . . . 2.5 8.1Romania . . . . . . . . . . . . . . . . . . . . . 12.4 31.7Sweden . . . . . . . . . . . . . . . . . . . . . . 25.1 49.9United States . . . . . . . . . . . . . . . . . 15.1 36.8

Note: Data for Mexico are for seven cities, and refer to 1989. Data are for household populations aged 65 and over, unless otherwisenoted. Data for Morocco refer to urban areas only.

Sources: Compiled from data in United Nations Demographic Yearbooks (various dates) and national sources.

that disaggregate data at advancedages, the gender difference tends todiminish at very old ages, presum-ably as a result of health and/oreconomic factors that require insti-tutional caretaking, communal liv-ing, or sharing of housing costs.Both numbers and proportions ofelderly living alone have risensharply in developed countriessince the early 1960s, althoughrecent information suggests thatthe rise in proportions might beleveling off in some nations.Everywhere, however, the absolutenumbers are increasing. Figure 7-2illustrates a trend common to mostdeveloped countries, i.e., theincrease has been largely fueled bywomen. Data from the 1996 cen-sus of Canada show more than700,000 elderly women livingalone, a jump of more than 180,000since 1986. The number of elderlywomen living alone grew at anaverage annual rate of 5.4 percentfrom 1961 to 1996, compared witha rate of 1.4 percent for the entireCanadian population. One implica-tion of such change is that, in mostdeveloped countries, women mustanticipate a period of living alone atsome point during their older years.

“ELDERLY-ONLY” HOUSEHOLDSARE INCREASINGLY COMMON

An earlier version of this report(Kinsella and Taeuber, 1993) point-ed out that elderly people livingalone were a significant factor innational household profiles inEurope. In several nations (e.g.,Belgium, Denmark, France, and theUnited Kingdom) in the 1980s,more than 11 percent of all nationalhouseholds consisted of a solitaryindividual aged 65 or over. Themost common living arrangementfor the elderly in Europe was with


Figure 7-1.

Percent of Elderly Living Alone in Germany and the United States by Available Age Groups

Source: National sources.

32

45

66

32

51

61

13 14

24

14

20

36

85+75-8465-7475+70-7465-69

Germany, 1999 United States, 1995

MaleFemale

Age group

Figure 7-2.

Elderly Living Alone in Canada: 1961 to 1996

Source: National sources.

0

200

400

600

800

19961991198619811976197119661961

Thousands

Female

Male

another elderly person in a two-person household. A related calcu-lation revealed that three out ofevery ten households in a 12-nationEuropean aggregate contained atleast one elderly person.

Data from the 1991 census of GreatBritain (for England, Wales, andScotland) are even more striking; 15 percent of all households in GreatBritain consisted of a single pension-er living alone, while another 10 per-cent of households had two or morepensioners with no other peoplepresent. Hence, 25 percent of allhouseholds in the country consistedof pensioners only. Overall, one-third of Britain’s households had atleast one resident pensioner.

In developed countries, the growthin “elderly-only” households may bedue in part to changes in social andeconomic policies. These include:increases in benefits that allow olderpeople to live independently of theirchildren; programs that more easilypermit the conversion of housingwealth into income; programs thatencourage the building of elder-friendly housing; and revisions in

reimbursement payments which dis-courage institutional living.

MAJORITY OF ELDERLY INDEVELOPED COUNTRIES LIVEWITH OTHER PEOPLE

Although high proportions of elder-ly often live alone in developedcountries, a majority of those aged65 and over still live with otherpeople. Data from 13 Europeannations (Table 7-2) show that theproportion of elderly living with oneother elderly person only (in mostcases a spouse) tends to be higherthan the proportion living singly.Between 10 and 14 percent of theelderly in the 13 nations live withone other person who is less than65 years of age; many of these eld-erly are likely to be either men liv-ing with younger spouses, or wid-owed or divorced individuals livingwith a child. Nations vary greatly inthe proportion of elderly people liv-ing in households of three or morepeople, from only 5 to 6 percent inSweden and Denmark to 35 percentor more in Ireland, Greece, Portugal,and Spain. As earlier studies (Wall,1989; Pampel, 1992) have noted,

national differences in elderly livingarrangements in Europe are charac-terized more by diversity than bysimilarity.

TWO- OR THREE-GENERATIONHOUSEHOLD STILL THEDEVELOPING-COUNTRY NORM

In all developing regions of theworld, with the possible exceptionof the Caribbean, the most commonliving arrangement for elderly peo-ple (married or widowed) is withchildren and/or grandchildren.Between 72 and 79 percent of older(60 and over) respondents in 1984World Health Organization surveysin Malaysia, the Philippines, Fiji, andSouth Korea lived with children(Andrews et al., 1986), and similarresults have been observed in coun-tries as diverse as India, Indonesia,Cote d’Ivoire, Singapore, and (atearlier times) six Latin Americannations (Kinsella, 1990). Morerecent data from four Asian nations(Figure 7-3) show a persisting pat-tern. While the levels may appearsimilar, the broad category of “livingwith offspring” encompasses aplethora of specific family and


Table 7-2.Composition of European Households With Elderly Members: Early 1990s

Country

Percent elderly in households with:

One person 65years or over

(1 personhousehold)

Another person65 years or

over (2 personhousehold)

Another personunder 65 years

(2 personhousehold)

Twoother

persons

Three ormore other

persons

Denmark . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42.4 40.6 11.4 4.1 1.5Greece . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17.7 29.4 14.2 15.0 23.7Spain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16.6 31.4 11.3 17.4 23.3France . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32.1 39.9 11.9 9.7 6.5Ireland . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26.2 25.3 13.1 16.4 18.9Italy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25.9 31.3 12.7 14.7 15.4Netherlands. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35.5 45.4 11.5 5.5 2.2Austria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35.3 29.4 12.9 10.2 12.2Portugal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18.5 33.8 11.9 14.4 21.3Finland . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38.4 32.2 12.8 8.9 7.7Sweden . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41.1 44.4 10.0 3.6 0.9United Kingdom . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35.7 40.5 11.9 7.9 3.9Switzerland . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34.0 41.2 12.6 8.1 4.1

Source: Eurostat, 1996.

household types, differing not onlyamong nations but among ethnicgroups within nations. Such diver-sity points to the importance of cul-tural and ideological as well asdemographic factors in the determi-nation of living arrangements ofolder people (Albert and Cattell,1994).

A growing concern in developingcountries is the extent to which thetwin processes of modernizationand urbanization will change tradi-tional family structures (Zhou,2000). Data for most of the devel-oping world generally are insuffi-cient for documenting changes inliving arrangements of the elderly.Although the case of Japan may notseem especially relevant to develop-ing nations, the extended familystructure common to the latter hashistorically been a feature ofJapanese society as well. Timeseries data (Figure 7-4) show thatthe number and proportion ofextended-family households inJapan have been declining, and thatthe proportions of elderly livingalone or with spouse only havebeen increasing.

These trends in Japan have led tothe suggestion (Kamo, 1988) thatthe impact of industrialization hasundermined the indigenous cultureof Japan vis-a-vis the status of itselderly citizens, and set the stagefor the eventual predominance ofthe nuclear family. Related to thisis the notion of “intimacy at a dis-tance” (see, e.g., Stehouwer, 1968;Rowland, 1991). That is, as thefinancial (and to some extenthealth) status of elderly peopleimproves, a larger proportion areable to afford to live alone andchoose to do so in independentdwellings, while at the same timemaintaining close familial contactand exchange supports. A growing

literature relates improvements insocial security programs and gen-eral economic welfare to the abilityand desire of older persons tochoose independent living arrange-ments, presumably reflecting

normative changes toward individ-ualism and personal independence(see, e.g., the discussion and refer-ences in Gierveld, 2001). This con-cept has found general currency ina variety of cultural settings,


Figure 7-3.

Percent of People Aged 60 and Over Living With Children in Four Asian Countries: Circa 1996

Sources: Anh et al., 1997; Chan, 1997; Knodel and Chayovan, 1997; and Natividad and Cruz, 1997.

67.4

90.6

69.471.871.9

86.5

72.776.5

Vietnam(Red River Delta)

ThailandSingaporePhilippines

MaleFemale

Figure 7-4.

Living Arrangements of Japanese Elderly: 1960 to 1995

Note: "With kin" includes very small numbers of elderly cohabitating with nonkin. Source: Japan Management and Coordination Agency, cited in Atoh, 1998.

Institution

0 20 40 60 80 100

1995

1985

1975

1960

With kin Elderly couple only

Alone

Percent

although a recent analysis of datafrom the Indonesian Family LifeSurvey (Cameron, 2000) finds littleevidence that increases in theincome of the elderly, or that of theirchildren, lead to a significant changein traditional family structure.

NUMBERS OFINSTITUTIONALIZED ELDERLYRISING

A number of studies (e.g., Manton,Stallard, and Liu, 1993; Weiner andIllston, 1995; Leung, 2000) havedocumented the direct relationshipbetween population age-sex struc-ture, age-sex-specific rates of chron-ic disease and disability, and theneed for long-term care. The con-fluence of several macro trends indeveloped countries — older popu-lation age structures, higher inci-dence of noncommunicable disease,

lowered fertility, increased geo-graphical mobility, and the rapidadvance in medical technology —has led to a steep rise in numbersof institutionalized elderly. Thehighest rates of institutional use arefound in many of the world’s oldestcountries, and the absolute num-bers of users are expanding even inthe face of increasing efforts toenhance community-based servicesand avoid or greatly reduce levelsof institutionalization.

In spite of the intense media scruti-ny of and controversy surroundinginstitutional residence, the factremains that relatively small propor-tions of elderly populations residein institutions at any given time.Cross-national comparisons of insti-tutionalized populations are prob-lematic due to the absence of

internationally consistent data, anddifferences between countriesshould be construed as orders ofmagnitude rather then as precisemeasurements. One attempt to col-late reasonably-comparative data onresidential care in the 1990s (OECD,1996) suggests that usage rates fordeveloped countries (Figure 7-5)range from 2 percent in Portugal to9 percent in the Netherlands.1

There is substantial variation in theuse of custodial institutions and inthe mix of long-term care alterna-tives and services (see, e.g., Ribbeet al., 1997; Mechanic andMcAlpine, 2000). One study (Doty,1992) suggests that Japan,Australia, and North America havemade greater relative use of med-ical residential care, while anemphasis on nonmedical facilitieshas been more apparent in Belgium,Sweden, and Switzerland.

In Eastern Europe and parts of theformer Soviet Union, the combina-tion of low fertility and the rapidincrease in oldest-old populationmight be expected to translate intoa growing use of institutional healthcare and maintenance services. Todate, however, available informationindicates that institutionalization ofolder people is not common. InRussia, for instance, the capacity of(number of existing places in) oldpeople’s homes and nursing homesthroughout the former USSR in thelate 1980s was estimated to be


Figure 7-5.

Percent of Elderly in Residential Care: Early to Mid-1990s

Notes: Canada and Finland: figures represent the midpoint of an estimated range. Japan and the Netherlands: some of the residential care is provided in hospitals. Sources: OECD, 1996; Jacobzone, 1999.

Turkey

Portugal

Spain

Italy

Austria

Ireland

United Kingdom

United States

Japan

Finland

Belgium

France

Norway

New Zealand

Luxembourg

Germany

Canada

Australia

Denmark

Sweden

Netherlands

0.2

8.8

8.7

7.0

6.86.8

6.8

6.8

6.7

6.6

6.56.4

6.4

6.0

5.75.1

5.04.9

3.9

2.9

2.0

1 Although the percentage of elderly in insti-tutions at any given moment may be relativelylow, on average around 5 percent in developedcountries, an estimated 25 to 30 percent ofpeople who survive to age 65 can expect tospend some time in an institutional settingbefore they die (Sundstrom, 1994). Thus thelongitudinal risk of experiencing institutional-ization is much higher than cross-sectionalrates might suggest. Considerable researchinterest currently is devoted to untangling thedynamics of institutional use, including transi-tions to and from such facilities and the under-lying health conditions that drive the transi-tions.

between 320,000 (Muzafarov andKurleutov 1994) and 380,000(Bezrukov, 1993); the higher esti-mate represents less than 1.5 per-cent of the USSR population aged65 and over as of 1988. While theaverage Russian view of institution-alization may be extremely negative(Powell, 1991), there does appear tobe an unmet need for institutionalservices. Lengthy waiting lists forinstitutional admission have beenthe norm for many years, and offi-cial time series data for Russiashow a steady rise in the number ofnursing/old people’s homes, fromaround 700 in 1985 to more than900 in 1996. At the same time, thenumber of places in such institu-tions has remained fairly constant,suggesting a downsizing of theaverage facility. Older people livingalone, and especially never-marriedelderly men, are said to be at partic-ularly high risk of institutionaliza-tion. In rural areas of the country,district hospitals frequently serve aslong-term residences for the elderly,for social as well as health reasons(Bezrukov, 1993).

Rates of institutionalization usuallyare very low or negligible in thedeveloping world. In official rheto-ric, at least, the Western model ofinstitutional care for older peopleoften is rejected as culturally inap-propriate (Gibson, 1992). Outsideof Europe and North America, socialtraditions and official decrees of fil-ial and familial responsibility haveobviated, at least until recently,debate about living arrangementsof the elderly. Lately, however, anumber of countries have recog-nized that even if the family retainsmuch of its support function for theelderly, demographic and socioeco-nomic changes will inevitably pro-duce strains. Consequently, manydeveloping nations have adopted

new policies aimed at alleviatingcurrent and anticipated problems.Long-term care provision and/orhomes for the aged have becomeincreasingly accepted and commonin countries — especially inSoutheast Asia — where sustainedfertility declines have led to rapidpopulation aging and reduced thenumbers of potential family care-givers (Phillips, 2000; Bartlett andWu, 2000).

ELDERLY WOMENPREDOMINATE ININSTITUTIONAL POPULATIONS

Institutional use is strongly associ-ated with increasing age regardlessof national setting (Figure 7-6). Inmost developed countries, fewerthan 2 percent of the young old(aged 65 to 69) are in institutions.This level rises fairly slowly untilage 80, but many nations experi-ence a sharp increase in institu-tionalization rates among

octogenarians. More than half ofall Norwegians aged 85 and overreside in institutions at a givenpoint in time, as do one-third ormore of this age group in Australiaand New Zealand. In fact, a major-ity of people entering institutionsor other types of collectivedwellings have reached veryadvanced age. Those who enter atless-advanced ages tend to beeither single or widowed and child-less, i.e., people who are unlikelyto have young family members torely upon for support (Soldo, 1987).

Women and the oldest old, therefore,are disproportionately representedamong the institutionalized elderly(Figure 7-7). In the United States in1997, three-fourths of all nursinghome residents were women, andslightly more than half of all nursinghome residents were aged 85 orolder. People in institutions at onepoint in time, however, do not


Figure 7-6.

Percent of Elderly in Institutions in Austria and New Zealand: 1991

Source: OECD, 1996.

1.62.4

4.2

8.9

22.2

1.32.4

5.9

14.9

37.7

1.02.0

3.1

5.7

10.7

0.92.3

5.1

9.5

20.8

85+80-8475-7970-7465-6985+80-8475-7970-7465-69

Male Female

AustriaNew Zealand

Age group

necessarily remain there and “age inplace” indefinitely. Many older indi-viduals who enter an institutioneventually leave, and many make

multiple transitions. Some nationalnursing home systems (e.g., theNetherlands) have well-developedrehabilitative programs which

discharge a high proportion of usersback into the community, while oth-ers systems have relatively limitedrehabilitative services (Ribbe et al.,1997).

NATURE OF INSTITUTIONALUSE HAS CHANGED

Policies toward and practices ofinstitutionalization of older peoplein developed countries havechanged over the past half-century.In the United States and elsewhere,institutionalization in the early1900s was generally associatedwith poverty and/or inability towork. The elderly often werehoused with younger “welfare popu-lations” and were supported largelyby local agencies. By the middle ofthe twentieth century, hospital-based care for the elderly hadbecome more common, at least inthe United States, with financial andoperational control likely to comefrom state governments. Beginningin the 1950s, social policy encour-aged a shift away from hospital usetoward nursing-home use. TheUnited States experienced a rapidexpansion of nursing home capacity(OECD, 1996), with emphasis onproviding for chronic disease andphysical disability needs. Federalfunding assumed greater promi-nence, as did private sources offunding. More recently, the privatelong-term care insurance industryhas grown rapidly, while new formsof home and community-basedservices (e.g., assisted living) haveemerged. With U.S. long-term carecosts doubling each decade since1970 (reaching an annual level of$106 billion in 1995; Stallard,1998), the mix of institutional andhome-based care has been shiftingrapidly toward the latter, especiallyfor the oldest old (Cutler and Meara,1999).


Figure 7-7.

Percent of U.S. Elderly in Nursing Homes by Age: 1973-74, 1985, 1995, and 1997

Source: U.S. Centers for Disease Control, 1999.

PercentMale

PercentFemale

0

5

10

15

20

25

30

1997199519851973-74

0

5

10

15

20

25

30

1997199519851973-74

65-74

75-84

85+

65-74

75-84

85+

Countries in Europe also have beenactive in changing long-term carepolicies and practices in responseto population aging. Heightenedspending on institutional careprompted Great Britain to revamplegislation in the 1990s, transfer-ring more fiscal control to local gov-ernments and tightening means-tested provisions. Austria instituteda new federal act in 1993 aimedprimarily at increasing options relat-ed to personal care arrangementsand supporting individuals in theirown homes for as long as possible.Germany, in 1995, unveiled a sys-tem of universal long-term careinsurance which features expandedbenefits without major changes inmeans-testing. Importantly, the effi-cacy of such changes will be moni-tored and evaluated by researchprojects underway in each country(Wolf, 1998).

As noted above, developed coun-tries vary enormously in their useand view of institutional residencyfor older citizens. A study (Ribbe etal., 1997) of nursing homes in tennations found no apparent relationbetween the level of populationaging and the number of nursinghome beds. The surprising lack ofcross-national consistency is

attributed largely to differences inthe organization and financing oflong-term care as well as differingsectoral responsibilities for care.Nations clearly are struggling withalternative methods of long-termcare financing and provision, and itis hoped that countries can learnfrom one another via cross-nationalresearch that proceeds from thetypes of efforts now underway inEurope.

BEYOND LIVINGARRANGEMENTS

Living arrangements of older per-sons clearly are an important com-ponent of life, but we should becareful not to infer too much fromcross-sectional descriptive data onresidence patterns. We need to beaware of how living arrangementschange as a function of the growthin elderly populations and theirshifting health and kin-availabilityprofiles (Palloni, 2000). And asalluded to earlier, the well-being ofindividuals is not necessarily reflect-ed in living arrangements. Livingalone in old age has sometimesbeen interpreted as a lack of famil-ial and social integration, when infact it may be indicative of goodhealth, economic well-being, andsocial connectedness. Likewise, the

mere fact of elderly coresidencewith a younger generation(s) tellsus little about the quality of intra-household relationships and life sat-isfaction.

Instead of focusing on livingarrangements per se, attentionmight better be directed to under-standing the complex set of mecha-nisms and interpersonal relation-ships that determine the timing andcontent of support for older per-sons. This perspective is summedup well by the phrase “functionrather than form,” meaning that themechanisms and characteristics ofan individual’s support network aremuch more salient to well-being(and to policymaking) than are mereattributes of who lives with whom(Hermalin, 1999). Survey researchand methodology increasingly arefocused on the full mapping ofcomplex kin networks, householdand kin microsimulation techniques,and new data-record linkages thatallow analysts and policymakers tobetter understand the underlyingdynamics of intergenerational trans-fers and well-being in old age(Hagestad, 2000; Wolf, 2000).Chapters 8 and 11 look further atfamily and social support for olderpersons.


Shifts in population age structuregenerally result in new servicedemands and economic require-ments. With an increasingly olderage structure comes change in therelative numbers of people who canprovide support to those who needit. In the early 1980s, Myers andNathanson (1982) identified threeprominent issues regarding popula-tion and the family: 1) the extent towhich changes in social norms andresponsibilities, driven by the secu-lar processes of urbanization andmodernization, alter traditionalfamilial modes of caring for olderpeople; 2) the possible social sup-port burden resulting from reducedeconomic self-sufficiency of agedpeople and the likelihood of height-ened chronic disease morbidity andfunctional impairment related tolonger life expectancy; and 3) theways in which countries developfunding priorities for public caresystems given competing demandsfor scarce resources.

To gain a broad view of thesedynamics, demographic assess-ments of intergenerational supportoften consider various ratios of oneage group to another. This chapterconsiders societal support ratios,parent support ratios, and changesin kin availability. As seen through-out this report, the elderly popula-tion is diverse in terms of itsresources, needs, and abilities. Thestereotype of the elderly as a pre-dominately dependent group thatdrains a nation’s economy has erod-ed. Not all elderly require support

and not all working-age peopleactually work or provide direct sup-port to elderly family members.The statistics discussed in the firstpart of this chapter may be seen asrough guides to when we canexpect the particular age distribu-tion of a country to affect the needfor distinct types of social services,housing, and consumer products.These data suggest some of the fac-tors that will shape patterns ofsocial relationships and societalexpenditures in the comingdecades, but tell us little about thechanging nature of the health andeconomic resources of the aged inthe future.

RAPID RISE IN ELDERLYSUPPORT RATIOS EXPECTED INDEVELOPED COUNTRIESAFTER 2010

Broad changes in a nation’s agestructure are reflected in changingsocietal support ratios. These ratiostypically indicate the number ofyouth and/or elderly people per 100people aged 20 to 64 years, primaryages for participation in the laborforce. A commonly used measureof potential social support needs isthe elderly support ratio (sometimescalled the elderly dependency ratio),defined here as the number of peo-ple aged 65 and over per 100 peo-ple aged 20 to 64 in a given popula-tion. In the coming decades, elderlysupport ratios will rise in developedcountries as a result of both declin-ing fertility and increasing longevity.The rise has been and will continueto be modest in most countries

because the relatively large post-World War II birth cohorts will stillbe of working age through at least2010. In several nations (notablythe United Kingdom, the UnitedStates, and Russia), the elderly sup-port ratio will not change signifi-cantly from 2000 to 2010. Somedeveloped nations, however, areaging at a much faster pace.Between 2000 and 2015, the elderlysupport ratio in Denmark is likely toincrease 33 percent (from 24 to 32),and the increase in the CzechRepublic will likely be 36 percent(22 to 30). Most notably, Japan’selderly support ratio is expected tojump 63 percent (from 27 to 44)during the 15-year period.

From 2015 to 2030, the elderly sup-port ratio will increase by more than40 percent in several developednations as the large working-agecohorts begin to retire. In 2030,Japan’s elderly support ratio is pro-jected to be 52 (Figure 8-1). Italy islikely to have an elderly supportratio of 49 in 2030, and nearly allEuropean countries will have elderlysupport ratios over 40. NewZealand has the lowest projectedratio (30) among the developednations in this study, with other rela-tively low figures seen in the UnitedStates and Eastern Europe.

ELDERLY SUPPORT RATIOS INMOST DEVELOPING COUNTRIESTO CHANGE SLOWLY

Elderly support ratios are muchlower in developing than in devel-oped countries, often with ten or


CHAPTER 8.

Family and Social Support of Older People

fewer elderly people per 100 peopleaged 20 to 64. Among the 30developing countries in this study,Uruguay had the highest level (24)in 2000, followed by Argentina (19)and Israel (18). Many developingcountries will experience little if anychange in their elderly supportratios from 2000 to 2015, becausethe high-fertility cohorts of the1960s and 1970s will still be underage 65 in 2015. Thailand andSouth Korea stand out as excep-tions as they are expected to expe-rience relatively large increases inthe ratio between 2000 and 2015.In Bangladesh, Kenya, Malawi,Morocco, and Uruguay, on the otherhand, the elderly support ratio isexpected to remain stable between2000 and 2015. In Jamaica andPakistan the elderly support ratio isprojected to decline by 2015, eventhough the absolute numbers ofelderly population are increasing.

In countries where fertility remainshigh or has just recently begun todecline significantly — as in muchof Africa and South Asia — elderlysupport ratios should change littleduring the entire period 2000 to2030. Eastern and SoutheasternAsia and parts of Latin America, onthe other hand, could witness signif-icant change during that time. Theelderly support ratio is projected toat least double between 2000 and2030 in 11 Asian and LatinAmerican study countries, and totriple in South Korea.

YOUTH SUPPORT RATIOS TODECLINE

The working-age population alsoprovides support for young people.


Figure 8-1.

Elderly Support Ratios: 1950 to 2030


Number of people aged 65 and over per 100 people aged 20 to 64Developed countries

Number of people aged 65 and over per 100 people aged 20 to 64Developing countries

0

10

20

30

40

50

60

202520101995198019651950

0

10

20

30

40

50

60

202520101995198019651950

United States

South Korea

Argentina

Egypt

Belgium

Japan

Children outnumber working-ageadults in many developingcountries. As a result, youth sup-port ratios — defined here as peo-ple under age 20 per 100 adultsaged 20 to 64 years — for 2000were in excess of 100 in severaldeveloping countries (mainly inAfrica). In the developed countriesin this study, however, youth sup-port ratios ranged from only 31 inItaly to 49 in New Zealand.

In most countries of the world,youth support ratios are projectedto decline between 2000 and 2030.In countries where the present levelis high, the youth support ratio maydecline by half or more. In Kenya,for example, the 2000 level of 133is projected to plummet to 61 in2030.

DIVERGENT TOTAL SUPPORTRATIO PATTERNS INDEVELOPED VERSUSDEVELOPING COUNTRIES

The total support ratio (youth pluselderly in relation to the working-age population) provides a grossindication of the overall supportburden on working-age adults. Thelevel of the total support ratio overtime is pertinent to policymakers,but knowing the balance of old ver-sus young may be more importantbecause supporting the young isprobably less costly than support-ing the elderly (especially as theelderly population itself ages). Withthe major exception of education,the costs of young people are borneby families more than by govern-ment programs, although someEuropean governments provide the

bulk of support to both young andold alike.

From 2000 to 2015, the total sup-port ratio (TSR) should remain rela-tively stable in most developedcountries as declining numbers ofchildren more than offset growingnumbers of elderly (Figure 8-2).From 2015 to 2030, however,increasing numbers of elderly peo-ple will boost the TSR in all devel-oped nations even though theyouth component may declineslightly. Among the study countries,the proportional gain in the TSRfrom 2015 to 2030 is projected tobe greatest in Russia (30 percent).The United States is projected tohave the highest TSR (87) amongthe developed countries in the year2030, with 7 other developed coun-tries also projected to have TSRs inexcess of 80.

For the foreseeable future in devel-oping countries, major fertilityreductions are likely to outweighgrowing numbers of elderly people.At the same time, the working-agepopulation is increasing. Hence,future TSRs for the vast majority ofdeveloping countries are projectedto be lower than in 2000. Eventhough growth rates for the youthand elderly will be higher than indeveloped countries during thenext three decades, TSRs in devel-oping countries often will be lowerbecause of the massive numbers ofworking-age adults in their popula-tions. Such change may portend awindow of economic opportunityfor developing countries. As theratio of working-age to total popula-tion rises, economies have relativelymore productive units and thereforemore opportunity to grow (otherfactors being equal).


Figure 8-2.

Youth and Elderly Components of the Total Support Ratio: 2000, 2015, and 2030


2030

2015

Philippines, 2000

2030

2015

Uruguay, 2000

2030

2015

France, 2000

2030

2015

Australia, 2000

(Youth ratio: people aged 0 to 19 per 100 people aged 20 to 64; Elderly ratio: people aged 65 and over per 100 people aged 20 to 64)

YouthElderly

13

46

40

40

43

39

38

59

55

50

98

76

60

21

26

37

27

32

44

24

24

28

7

9

THE USEFULNESS OF ELDERLYSUPPORT RATIOS

Implicit in the standard definition ofan elderly support ratio is thenotion that all people over age 64are in some sense dependent on thepopulation in the working ages (20to 64) who provide indirect supportto the elderly through taxes andcontributions to social welfare pro-grams. We know, of course, thatelderly populations are extremelydiverse in terms of resources,needs, and abilities, and that manyelderly are not dependent in eithera financial or a physical (health)sense. Older people pay taxes,often have income and wealth thatfuel economic growth, and providesupport to younger generations.Likewise, substantial portions of theworking-age population may not befinancial earners, for reasons ofunemployment, inability to work,pursuit of education, choosing to beout of the labor force, and so forth.

While it is empirically difficult toinclude factors such as intrafamilyfinancial assistance and child careactivities into an aggregate measureof social support, it is feasible totake account of employment charac-teristics in both the working-ageand elderly populations. In Figure8-3, the topmost bar for each coun-try represents the standard elderlysupport ratio as defined above. Thesecond bar includes only the eco-nomically active population aged 20to 64 in the denominator, therebyexcluding people who choose not towork, unpaid household workers,nonworking students, and perhapsthose individuals whose health sta-tus keeps them out of the laborforce. The third bar represents acalculation similar to the second bar,but removes economically activepeople aged 65 and over from thenumerator on the assumption that

they are not economically depend-ent. The fourth bar builds on thethird bar by adding these economi-cally active elderly to the ratiodenominator of other economicallyactive individuals, on the assump-tion that these working elderly con-tinue to contribute tax revenue tonational coffers.

The alternative ratios in each coun-try are higher than the standard eld-erly support ratio, except in Japanwhere the elderly have a relativelyhigh rate of labor force participation(often as part-time workers). To theextent that policy and programagencies use support ratio calcula-tions, the effect of including versusexcluding labor force participationrates appears considerable in mostcountries. Data permitting, otheradjustments might be made tothese ratios to account for such

factors as (1) workers under age 20;(2) trends in unemployment; (3)average retirement ages; and (4)levels of pension receipt and institu-tionalization among the elderly,and/or the prevalence of high-costdisabilities.

RAPIDLY CHANGING AGESTRUCTURE IS A CHALLENGETO SUPPORT IN SOMEDEVELOPING COUNTRIES

One of the more dramatic demo-graphic developments in the lasttwo decades has been the pace offertility decline in many developingcountries. The common perceptionis that below-replacement fertilitylevels are seen only in the industri-alized nations of the NorthernHemisphere. As of 2000, however,the total fertility rate was belowreplacement level in 21 developingcountries, mostly in Latin America


Figure 8-3.

Standard and Alternative Elderly Support Ratios: 1998

Sources: International Labour Office Yearbook of Labour Statistics, 1999 and U.S. Census Bureau, 2000a.

Germany

UnitedStates

Spain

Japan

Finland

Total population 65 and over per 100total population 20-64

Noneconomically active population 65 and over per100 economically active population 20 and over

Noneconomically active population 65 and over per100 economically active population 20-64

Total population 65 and overper 100 economically activepopulation 20-64

32

24

313131

2633

25

23

2739

3939

2227

24

23

2534

33


Figure 8-4.

Population by Single Years of Age for China: 2000


Millions

Male FemaleAge

15 12 9 6 3

0

5

10

15

20

25

30

35

40

45

50

55

60

65

70

75

80

85+

0 3 6 9 12 15

and the Caribbean and parts of Asia(U.S. Census Bureau, 2000a), and isdeclining steeply in many otherdeveloping countries.

The situation in the People’sRepublic of China illustrates thepotential effect that rapidly-declining fertility may have vis-a-vispopulation aging. In 1979, Chinaestablished an official one-child-per-family policy aimed at curbinggrowth in the world’s most popu-lous nation. While the policy wasrelaxed somewhat in subsequentyears, China’s total fertility ratedeclined to an estimated level of1.8 children per woman in 2000.As a result, China will age soonerand more quickly than most devel-oping countries.

China’s age profile in 2000 con-tained a large “bulge” consisting ofpeople aged 26 to 37 (Figure 8-4).The oldest people in this age bulgewill be entering their sixties justprior to the year 2025. This popu-lation momentum will produce arapid aging of the Chinese popula-tion in the third and fourth decadesof the twenty-first century. Recentanalyses of 1995 sample censusdata from China suggest higher old-age mortality than had been previ-ously estimated, resulting in lowernumbers of projected elderly peo-ple. Nevertheless, the number ofChinese aged 65 years and over isnow projected to increase from 88 million in 2000 to 197 million in2025, and to 341 million in 2050.Short of a catastrophic rise in adultmortality or massive emigration ofan unprecedented scale, we can bereasonably certain that this growthwill occur, because the elderly ofthe middle decades of the twenty-first century are already born.Eventually, China’s projected youthand elderly support ratios are likely


Figure 8-5.

Youth and Elderly Support Ratios in China: 1985 to 2050


0

20

40

60

80

100

20502045204020352030202520202015201020052000199519901985

Youth ratio: people aged 0 to 19 per 100 people aged 20 to 64; Elderly ratio: people aged 65 and over per 100 people aged 20 to 64

Youth

Elderly

Figure 8-6.

Parent Support Ratios in Four World Regions: 1950, 2000, and 2030

Note: South America includes: Argentina, Bolivia, Brazil, Chile, Colombia, Ecuador, French Guiana, Guyana, Paraguay, Peru, Suriname, Uruguay, and Venezuela. Eastern Asia includes: China, North Korea, South Korea, Hong Kong, Japan, Macau, Mongolia, and Taiwan Western Europe includes: Austria, Belgium, France, Germany, Liechtenstein, Luxembourg, Monaco, Netherlands, and Switzerland. Western Africa includes: Benin, Burkina Faso, Cape Verde, Cote d' Ivoire, Gambia, Ghana, Guinea, Guinea-Bissau, Liberia, Mali, Mauritania, Niger, Nigeria, St. Helena, Senegal, Sierra Leone, and Togo.


1517

37

710 9

20

44 37

3

Western AfricaWestern EuropeEastern AsiaSouth America

195020002030(People aged 80 and over per 100 people aged 50 to 64)

to converge (Figure 8-5), and wemay anticipate a social and eco-nomic fabric radically different fromthat of today.

MORE PEOPLE WILL FACECARING FOR FRAIL RELATIVES

In the eighteenth and nineteenthcenturies, low levels of lifeexpectancy meant that people onaverage lived a relatively shortamount of time in a multigenera-tional family (United Nations,1990b). While most older individu-als lived with family members,years spent in an extended-familyarrangement were limited becausethe average person died shortlyafter becoming a grandparent(Hareven, 1996). Declining mortali-ty and increased longevity haveincreased the odds of joint survivalof different generations within afamily. In developed countries,joint survival has manifested itselfin the “beanpole family,” a verticalextension of family structure char-acterized by an increase in thenumber of living generations withina lineage and a decrease in thenumber of members within eachgeneration (Bengston, Rosenthal,and Burton, 1995). As mortalityrates continue to improve, moreand more people in their fifties andsixties are likely to have survivingparents, aunts, and uncles. Morechildren will know their grandpar-ents and even their great-grandparents, especially their great-grandmothers. There is nohistorical precedent for a majorityof middle-aged and young-oldadults having living parents.Menken (1985) has estimated thatone in three women 50 years oldhad living mothers in the UnitedStates in 1940, whereas by 1980the proportion had doubled to twoin three.

SANDWICH GENERATION ADEVELOPED-COUNTRYPHENOMENON

One aspect of the changing agestructure of families that hasreceived recent attention is the so-called “sandwich generation,” thatis, people who find themselves car-ing for elderly parents while stillcaring for/supporting their ownchildren or grandchildren and oftenparticipating in the labor force. Indeveloped countries especially,more people will face the concernand expense of caring for their veryold, frail relatives with multiple,chronic disabilities and illnesses.The need for help is likely to comeat the very time when the adult chil-dren of the frail elderly are near orhave reached retirement age.1 Indeveloping countries, the adult chil-dren may well have children of theirown living in the household. Someof the adult children may bearhealth limitations of their own.Those frail elderly without childrenmay face institutionalization at ear-lier ages than will people with sur-viving adult children.

One measure of the pressure thesandwich generation may experi-ence by caring for elderly parents isthe parent support ratio (PSR),defined here as the number of peo-ple aged 80 and over per 100 peo-ple aged 50 to 64, which in a gen-eral sense relates the oldest old totheir offspring who were born when

most of the oldest old were aged20 to 35. Of course, people in thenumerator (80 and over) are notnecessarily in the same families asthose in the denominator (50 to 64years). Thus, the PSR is only arough indication of need for familysupport over time.

Relatively few people aged 50 to 64in 1950 worried about caring forpeople aged 80 or older. In thedeveloped countries in this study,the PSR ranged from five in Japanand Hungary to eleven in Norway in1950. In developing countries, thePSR ranged from two in Bangladeshto eleven in Tunisia and Uruguay.Increases in the PSR since 1950imply that a relatively larger shareof middle-aged adults now mayexpect to provide care.Additionally, life expectancy hasincreased for the disabled, the men-tally retarded, and the chronicallyill. Today’s care for older peoplemay be more physically and psy-chologically demanding than in thepast, especially with regard to theincreased numbers of people withcognitive diseases. As advances inmedical technology affect the abilityto extend life, it is at least plausibleto expect the duration of chronic ill-ness and the consequent need forhelp to increase further, even if theaverage age at onset of disabilityrises.

In all countries examined exceptBangladesh, Jamaica, Morocco, andPakistan, the PSR is projected to behigher in 2030 than in 2000. Theratio has and will evolve very differ-ently within and among worldregions, however (Figure 8-6). InSouth America, Eastern Asia, andWestern Europe, PSRs more thandoubled between 1950 and 2000.PSRs will continue to rise between2015 and 2030. In Western Africa,most countries experienced little


1 It should be noted that the idea of a “sand-wich generation” needs further empirical eluci-dation. Some researchers question the extentto which middle generations actually providecare for younger and older generations. Onestudy of 12 European Union countries (reportedin Hagestad, 2000) reports that only 4 percentof men and 10 percent of women aged 45-54have overlapping responsibilities for childrenand for older persons who require care. Theimportance of the “sandwich” concept in agiven society is likely to be determined, in part,by the nature of formal institutions that provideassistance to elderly individuals and to familiesin general.

change in the PSR from 1950 to2000, and the aggregate level willremain low in 2030 even thoughabsolute numbers of oldest-old peo-ple in some nations are growingrapidly. The most pronouncedchanges have occurred in the indus-trialized world. In 2000, the PSRwas 20 or higher in 12 such nations(and also in Israel and Uruguay).The difference in parent supportratios between developed anddeveloping countries reflects differ-ent trends in fertility. In 2030,those aged 50 to 64 (the potentialsupport givers) were born between1966 and 1980. In most develop-ing countries, fertility was still highduring this period, or just begin-ning to decline. Hence, this agegroup will be fairly large, resultingin low parent support ratios. Indeveloped countries, fertility wasfairly low during this period, pro-ducing small birth cohorts that willresult in higher parent supportratios in 2030.

SPOUSE MAY BE MOST LIKELYTO PROVIDE CARE FORELDERLY

A clear cross-national picture ofcaregiving for the elderly has yet toemerge. In the 1980s, the stereo-typical view of caregiving was thatof children caring for their agedparent(s). More specifically, it gen-erally was thought that adultdaughters and daughters-in-law pro-vided most of the personal care andhelp with household tasks, trans-portation, and shopping for the eld-erly (United Nations, 1985).Although this may still be the case,increases in joint survival meanthat, for many older people in bothdeveloping as well as developedcountries, the main person whoprovides care is their spouse(Shuman, 1994). One survey inSpain found that 74 percent of

older men who were receivingassistance with an instrumentalactivity of daily living2 had theirwife as the caregiver. However,only 33 percent of older womenrelied on their husband as the care-giver, while 58 percent were aidedby a daughter (Beland andZunzunegui, 1996).

Whether in the role of spouse ordaughter, the fact remains thatwomen provide the bulk of informaland/or long-term care for elderlypeople worldwide. While joint sur-vival increases the number of elder-ly couples, the average womaneventually outlives her husband andmay have to rely on other familymembers for personal care.3 Moststudies (see, for example, Jensonand Jacobzone, 2000, and the com-pilation of research in Blieszner andBedford, 1996) have indicated thatthese other family members arewomen. Therefore, a variant of theparent support ratio may be useful,namely, the ratio of people aged 80and over to women aged 50 to 64.Changes in this parent support ratiofor females (PSRF) are similar tothose in the PSR, but the PSRF levelsare much higher. In 2000, the PSRFwas 54 in Norway and Sweden, thehighest level among the 52 studynations. Most developed countrieshad PSRF levels in the 30s and 40s,while many developing nations hadPSRFs of 15 or less in 2000.Projections for the year 2030 sug-gest that in Japan there will be 100people aged 80 and over per 100women aged 50 to 64, the highestlevel among the 52 nations.

FAMILY ABILITY TO CARE FORELDERLY MEMBERS MAY BECHANGING

Living with other people reducesthe likelihood of using formal med-ical care and increases the use ofinformal care, at least in the U.S.context (Cafferata, 1988). Sincemost physical, emotional, and eco-nomic care to older individuals isprovided by family members, thedemography of population aging isincreasingly concerned with under-standing and modeling kin availabil-ity. Kin availability refers to thenumber of family members who willpotentially be available to elderlyindividuals if and when variousforms of care are needed. A studyby Tomassini and Wolf (2000) exam-ined the effects of persistent lowfertility in Italy on shrinking kin net-works for the period 1994-2050;throughout the simulation period,about 15-20 percent of Italianwomen aged 25 to 45 are the onlyliving offspring of their survivingmothers and thus are potentiallyfully responsible for their mothers’care. While reduced fertility andsmaller families obviously implyfewer potential caregivers, thiseffect is offset to some extent byincreased longevity. Modeling isfurther complicated by the fact thatwhile demographic forces imposeconstraints on family, household,and kin structures, these structuresalso are determined by social andcultural factors that are difficult tomeasure (Myers, 1992; Wolf, 1994;Van Imhoff, 1999).

Research is now addressingwhether the high rates of divorceobserved in some nations will resultin a lack of kin support for peoplein older age, and whether “blended”families and other forms of socialarrangements will, in the future,provide the types of care and


2 Instrumental activities of daily livinginclude preparing meals, shopping for personalitems, managing money, using the telephone,and doing light housework.

3 Although, in countries with relatively highlevels of income, market developments increas-ingly allow older individuals or their children topurchase care services directly if desired.

support that are common today(Wachter, 1998; Murphy, 2001).The consensus to date foresees adeclining biological kinship supportnetwork for elderly people in devel-oped and many developing coun-tries. Childlessness is another traitthat will affect the nature of futurecaregiving. Data over time for theUnited States in Figure 8-7 show theincreasing likelihood of being child-less among women aged 40 to 44;nearly one out of five such womenin 1998 had no children. Trends inthis characteristic could be animportant determinant of eventualcare arrangements as current andfuture cohorts of middle-agedwomen reach older age.

The issue of kin availability hasbecome especially important in thecontext of East and Southeast Asiancountries, driven in large part bythe rapid declines in fertility thathave greatly reduced the averagefamily size of young-adult cohorts.The complex interplay of demo-graphic and cultural factors is illus-trated by the case of the Republicof Korea. There, two-thirds of theelderly are economically dependenton their adult children (KoreaInstitute for Health and SocialAffairs, 1991), and cultural normsdictate that sons provide economicsupport for elderly women whohave lost their spouses. Lee andPalloni (1992) have shown thatdeclining fertility means an increasein the proportion of Korean womenwith no surviving son (Figure 8-8).At the same time, increased malelongevity means that the proportionof elderly widows also will decline.Thus from the elderly woman’spoint of view, family status may not


Figure 8-7.

Childlessness Among U.S. Women 40 to 44 Years Old: 1976 to 1998

Source: U.S. Census Bureau, June Current Population Surveys, 1976 to 1998.

10 1011

1516

19

199819921988198419801976

(Percent)

Figure 8-8.

Percent of Women at Age 65 in South Korea With No Surviving Son: 1975 to 2025

Source: Lee and Palloni 1992.

1715 15

17

26

30

1110 10

13

24

29

202520152005199519851975

MarriedWidowed

deteriorate significantly in thecoming years. From society’s per-spective, however, the demand forsupport of elderly women is likelyto increase. The momentum ofrapid population aging means thatthe fraction of the overall popula-tion that is elderly women (especial-ly sonless and childless widows)will increase among successivecohorts. Given the strong trendtoward nuclearization of familystructure in the Republic of Korea,and the traditional absence of stateinvolvement in socioeconomic sup-port, the future standard of livingfor a growing number of elderlywidows is tenuous. A similarprospect looms in Taiwan and Japan(Hermalin, Ofstedal, and Chi, 1992;Jordan, 1995). Simulations of kinavailability in rural China (Jiang,1994) are more optimistic, suggest-ing that, in spite of relatively lowfertility, improvements in mortalitywill ease the future burden on thefamily support system. Only a verysmall percentage of rural house-holds will have to support two ormore elderly parents, and relativelyfew elderly will be childless. At thesame time, simulations using fami-ly-status life table models devel-oped by Zeng, Vaupel, andZhenglian (1997; 1998) suggestthat the family household structureand living arrangements of Chineseelders may change markedly duringthe first half of this century; by2050, the percentage of Chineseelderly living alone could be 11 and12 times larger in rural and urbanareas, respectively, than in 1990.

HOME HELP SERVICES AREMOST PREVALENT INSCANDINAVIA

The previous chapter alluded to achange in social and governmentalthinking about the desirability ofinstitutionalization. Some nations

now promote policies to maintainand support frail elderly people intheir own homes and communitiesfor as long as possible. Given thechanging nature of the family (in itsmany perturbations) and patterns ofkin availability, the developmentand use of home help serviceswould appear to be a reasonablestep toward reducing the need forinstitutionalization. To date, how-ever, the use of home help appearsto be widespread only inScandinavian countries and theUnited Kingdom. Comparative dataassembled by the Organization forEconomic Co-Operation andDevelopment from the early-to-mid-1990s show that the proportion ofelderly people receiving home helpexceeds 10 percent in only five

countries (Figure 8-9). Suchservices reached nearly one-fourthof all elderly in Finland in 1990, upslightly from the level of 22 percentin 1980. The available data sug-gest that countries with moreextensive provision of home helpservices are those that have had aprolonged process of populationaging and now have relatively high-er proportions of oldest-old resi-dents (OECD, 1996). Structural pro-grammatic factors also areimportant, insofar as governmentsupport or subsidization of homehelp will almost certainly result ingreater use. In the United States,the use of home health care servic-es has grown substantially since thelate 1980s, largely as a result ofchanges in medicare policy that


Figure 8-9.

Proportion of Elderly People Receiving Home Help Services: Early-to-Mid 1990s

Note: Data for France, Australia, and Italy refer to 1985, 1988 and 1988, respectively. Source: OECD, 1996.

(In percent)

Italy

New Zealand

Portugal

Spain

Canada

Japan

Germany

Ireland

Austria

United States

Belgium

Australia

France

Netherlands

United Kingdom

Sweden

Norway

Denmark

Finland

1

24

17

14

13

13

8

7

7

6

4

3

3

2

2

2

2

1

1

have made home health benefitsavailable to more beneficiaries forlonger periods of time. This in turnhas stimulated the home healthcare industry; the number of homehealth agencies more than tripledbetween 1980 and 1994(Freedman, 1999).

ELDERLY PROVIDE AS WELL ASRECEIVE SUPPORT

Many elderly receive financial helpfrom adult children, but support isnot a one-way street. In countrieswith well-established pension andsocial security programs, manyolder adults give support (includingfinancial help, shelter, childcare, andthe wisdom of experience) to theiradult children and grandchildren.In the North American context,studies suggest that elderly parentsare more likely to provide financialhelp than to receive it (Soldo andHill, 1993; Rosenthal, Martin-Matthews, and Matthews, 1996).The elderly in developing countriesappear less likely than in developedcountries to provide financial help;data from the Malaysian Family LifeSurvey indicate that the main direc-tion of monetary transfers betweennoncoresident parents and childrenis from the latter to the former(Lillard and Willis, 1997). Ongoingresearch in Asia is beginning toreveal the complexity of familialexchange, not just among parentsand children but among wider fami-ly and social networks as well(Agree, Biddlecom, and Valente,1999). Beyond the financial realm,it seems clear that older persons indeveloping countries make substan-tial contributions to family well-being, in ways ranging from social-ization to housekeeping and childcare. Such activities free youngeradult women for employment inunpaid family help in agricultural

production as well as paid employ-ment (Hashimoto, 1991; Apt, 1992).

An important component of manyolder people’s lives is their role asthe giver of care. Older people pro-vide care for a variety of people(spouses, older parents, siblings,children, and grandchildren) and doso for many reasons (illness of aspouse or sibling, increased numberof single-parent families, increasedfemale labor force participation,orphaned grandchildren). Often thecare provided by older family mem-bers is essential to the well-being ofa family.

THE IMPORTANCE OFGRANDPARENTS

In some countries, nontrivial pro-portions of older women and menare providing care to their grand-children. This care ranges fromoccasional babysitting to being acustodial grandparent. Survey datafor the United States from the mid-1990s (Fuller-Thomson and Minkler,2001) indicate that 9 percent of allAmericans with grandchildren underage 5 were providing extensivecaregiving.4 In 1997, 3.9 millionchildren (5.5 percent of all childrenunder age 18) lived in a householdmaintained by their grandparents(Casper and Bryson, 1998). Since1990, the number of children livingin households headed by grandpar-ents has increased, especially forchildren in households with onlygrandparents and grandchildren.Trends in several factors (e.g.,divorce, HIV/AIDS, drug abuse, andchild abuse) may have contributedto the increase in these types offamilies.

Grandparents in some developedcountries often provide day care forchildren so the grandchildren’s par-ents can work or go to school. Inthe United States in 1995, 29 per-cent of preschool children whoseparent(s) worked or were in schoolwere cared for by a grandparent(Smith, 2000), typically the grand-mother. Because of the lack of ade-quate day care in many EasternEuropean countries and nations ofthe former Soviet Union, the carethat grandmothers (babushkas) pro-vide for grandchildren may be inte-gral to family functioning.

In many Asian countries, wherecoresidency is the norm, propor-tions of grandparents providingcare for grandchildren are substan-tial. In the Philippines, Thailand,and Taiwan, approximately 40 per-cent of the population aged 50 andolder lived in a household with aminor grandchild (under 18 years ofage). In these same countries,approximately half or more of thoseaged 50 and older who had a cores-ident grandchild aged 10 oryounger provided care for the child(Hermalin, Roan, and Perez, 1998).As in the United States, grandmoth-ers are more likely than grandfa-thers in Asian countries to providecare for their grandchildren (Chan,1997; Uhlenberg, 1996).

Many grandparents find themselvesin the position of going beyond pro-viding occasional care to becomingthe sole providers of care for theirgrandchildren. One reason for thissituation is the migration of themiddle generation to urban areas towork. Past research has found thatthis is not unusual in Afro-Caribbean countries (Sennott-Miller,1989). These “skip-generation”families are found in all regions of


4 Extensive caregiving in this context meantproviding at least 30 hours of child care in anaverage week and/or caring for grandchildrenfor at least 90 nights in 1 year.

the world and may be quite preva-lent. One study in rural Zimbabwefound that 35 percent of house-holds were skip-generation house-holds (Hashimoto, 1991).

THE HIV/AIDS EPIDEMIC ISCHANGING GRANDPARENTS’ROLES

The AIDS epidemic has affected thenumber of grandparents who arecaring for grandchildren in manycountries of the world. The effects

of the epidemic are particularlydevastating in Sub-Saharan Africa,where it is estimated that in 19998.6 percent of the population aged15 to 49 was infected with an HIVvirus that causes AIDS. High ratesof adult infection and AIDS deathsleave many children in need ofcare. The cumulative number ofAIDS orphans5 in Sub-Saharan

Africa is estimated to be 12.1 mil-lion (UNAIDS/WHO 2000). Formany of these children, grandpar-ents have become the main care-giver (Levine, Michaels, and Back,1996). One study (Ryder et al.,1994) in the city of Kinshasa foundthat the principal guardian for 35 percent of AIDS orphans was agrandparent.


5 AIDS orphans are defined as HIV-negativechildren who lost their mother or both parentsto AIDS when the children were under age 15.

Educational attainment is linked tomany aspects of a person’s well-being. Research has shown thathigher levels of education usuallytranslate into better health status,higher incomes, and consequentlyhigher standards of living (Guralniket al., 1993; Preston and Taubman,1994; Smith and Kington, 1997; Liu,Hermalin and Chuang, 1998).People with higher educational lev-els tend to have lower mortalityrates and better overall health thantheir less-educated counterparts (Eloand Preston, 1996; Zimmer et al.,1998), as well as better cognitivefunctioning in older age (Stern andCarstensen, 2000). Part of the rea-son for this finding is that more-educated people tend to have higherincomes throughout their lifetime,which means they can afford betterhealth care than people with lowerlevels of education. Higher work-ing-life income also translates intohigher levels of retirement savingsand income. Hence, people withhigher educational levels may beless dependent on their family forfinancial assistance in later years.

Education significantly affects howeffectively people utilize healthcare. In the United States, forexample, where educational levelsof the elderly are relatively high,many older people, especially thoseaged 85 and older, have troubleunderstanding basic medicalinstructions. Even something assimple as taking medicine correctlymay be a problem. Education fur-ther affects health because well-educated people may be more

aware of the benefits and disadvan-tages of certain types of behaviorsassociated with personal health.Education also is related to jointsurvival of spouses, to livingarrangements, and to changingvalue systems which have

implications for intergenerationalsolidarity (Choi, 1992).

Educational attainment of the eld-erly varies substantially among thecountries in this report. The latestdata for the United States show


CHAPTER 9.

Educational Attainmentand Literacy

Figure 9-1.

Percent of People With Completed Secondary Education or More

Note: Data for Sweden 65+ refer to ages 65-74. Sources: U.S. Census Bureau, 2000a and national sources.

Sweden, 1998

Singapore, 1995

Russia, 1994

Romania, 1992

China, 1990

Bolivia, 1992

Brazil, 1991

United States, 1998

Male, 25-44 Female, 25-44 Male, 65+ Female, 65+

86.989.0

67.666.6

21.623.9

6.64.9

17.212.8

4.72.3

20.413.4

2.80.5

94.692.1

45.531.9

87.391.9

31.821.6

64.061.3

15.25.4

79.682.5

44.0 38.0

that two-thirds of all people aged65 and older had completed at leastsecondary education.1 Comparablecompletion levels in other devel-oped countries are somewhat lower.Less than a third of the elderly inRussia, for example, had finishedsecondary-level education (Figure 9-1). Levels of education of the eld-erly are much lower in developingcountries. In Brazil, Bolivia, andChina, less than 5 percent of theelderly population had a completedsecondary education.

FUTURE ELDERLY WILL HAVEMORE EDUCATION

During the twentieth century, educa-tional attainment has increasedmarkedly in most countries of theworld. This improvement is clearlyreflected in the data on educationalattainment by age. In some devel-oped countries, younger cohorts aremore than twice as likely as the eld-erly to have completed secondaryeducation. In developing countries,the difference between younger andolder cohorts is even more striking.Women aged 25 to 44 in Bolivia weremore than five times as likely aswomen aged 65 and older to have acompleted secondary education.

The educational attainment of theelderly has risen during the lastseveral decades in many countries,and will continue to increase in thefuture. For example, around 27 percent of the elderly in theUnited States had completed atleast secondary education in 1970;by 1998 the percentage had


1 Educational attainment in this report refersin theory to completion of a particular educa-tional level. Data have been derived from pri-mary national tabulations as well as from fig-ures reported to international organizations.While large differences in educational attain-ment exist, at least some of the variation is like-ly due to different concepts, definitions, andmethods of data collection. We have attemptedto make the data on educational attainment inthis report as comparable as possible acrosscountries.

Figure 9-2.

Percent of People With Completed University Level of Education: 1998

Note: Percent for females aged 55-64 in Indonesia is zero. Source: Organization for Economic Co-Operation and Development, 2001.

Turkey

South Korea

Jordan

Indonesia

India

China

Brazil

Argentina

United States

Sweden

Portugal

Poland

Netherlands

Italy

Germany

Australia

Male, 35-44Female, 35-44Male, 55-64Female, 55-64

1

19 18

119

1914

155

1211

73

2923

2212

91111

96

75

414

1312

1127

2626

18

911

54

89

644

25

211

35

13

11

033

1815

226

1114

29

45

Developed countries


jumped to 67 percent. As younger,more-educated cohorts continue toage, their attainment levels will bereflected in the educational statusof tomorrow’s elderly.

UNIVERSITY EDUCATION NOTYET THE NORM AT ANY AGE

Although educational attainmenthas been improving throughout thetwentieth century, university-leveleducation still is not widespread.Relatively few people complete thislevel of education and the propor-tion is usually lowest among theelderly. In many developed coun-tries, less than a third of peopleaged 35 to 44 have a universityeducation (OECD, 1998a; 2001).The proportion of the “near elderly”(i.e., aged 55 to 64) with this levelof education is even lower (Figure9-2). For the set of countriesincluded in this graph, among menaged 55 to 64, the proportion witha university education ranged from

5 to 25 percent in the developedcountries and from 1 to 12 percentin developing countries. Small pro-portions of women aged 55 to 64in developed countries have a uni-versity education, and proportionsin most developing countries aresmaller still.

LITERACY RATE OF MANYELDERLY POPULATIONS STILLLOW

In many developed countries, litera-cy data no longer are collectedbecause education, at least at theprimary level, is so widespread thatliteracy is considered to be univer-sal. However, this is not always thecase for the elderly, particularly forolder women and the oldest old.Data from some countries that stillcollect literacy information showthat substantial proportions of theelderly may be unable to read andwrite. In Greece, for example, only77 percent of people aged 65 and

older were literate in 1991, and just67 percent of the age group 75 andover. Proportions literate amongolder Greek women were evenlower — approximately two-thirdsof women aged 65 and older andslightly over half of women aged 75and older.

In developing countries, literacymay be uncommon among olderpopulations. Many of today’s elder-ly lived much of their lives prior tothe rapid increase in educationalattainment that occurred in the sec-ond half of the twentieth century.Consequently, many older people,and again particularly women, havelow levels of literacy. While cohortchanges ensure that the future edu-cation profile of the elderly willimprove, it is important to remem-ber that in many countries, a major-ity of today’s elderly are illiterate(Hugo, 1992). This fact needs to beexplicitly recognized and consid-ered when developing programs toassist older populations.

Figure 9-3 presents estimated litera-cy rates for the population aged 60and over, by sex, in five developingregions for 1980 and 1995.2 In allfive regions, older men are more lit-erate than older women. In three ofthe five regions, less than half ofolder men and less than 15 percentof older women were literate in1995. Among developing regions,Latin America and the Caribbeanhas the highest aggregate literacylevels for older populations; three-quarters of men and two-thirds ofwomen aged 60 and over were liter-ate, similar to the levels notedabove in Greece.


Figure 9-3.

Estimated Literacy Rates for Population Aged 60 and Over, by Sex, in Five Developing Regions: 1980 and 1995

Source: United Nations Educational Scientific and Cultural Organization, 1995.

Southern Asia

Sub-Saharan Africa


Eastern Asia/Oceania

Arab States

(Percent literate)19801995

M

F

M

F

M

F

M

F

M

F 13

2636

611

4064

927

6875

5868

2134

914

3341

8

2 These estimates were produced by theDivision of Statistics of UNESCO using the mostrecently available national data. For detailsabout the methodology used to produce theseestimates see UNESCO, 1995, MethodologyUsed in the 1994 Estimates and Projections ofAdult Illiteracy, Statistical Issue STE-18, Divisionof Statistics, Paris.

Countries vary greatly in rates of lit-eracy among the elderly. In Chile,over 80 percent of the elderly wereliterate in 1992, while in Ugandaless than a fifth of the elderly wereliterate (Figure 9-4). In most coun-tries, older men are much morelikely to be literate than olderwomen. In Brunei, older men werefour times as likely to be literate aswere older women. Although verysmall proportions of the elderlypopulation are literate in manydeveloping countries, the rates riserapidly for younger cohorts. For allthe countries in Figure 9-4, with theexception of women in Uganda,well over half of the populationaged 25 to 44 were literate. Andamong this younger age group, thedifference in literacy by sex tendsto dissipate.

GENDER DIFFERENTIAL INEDUCATIONAL LEVELS AMONGTHE ELDERLY IS OFTENSUBSTANTIAL

In nearly all countries, older menhave higher average levels of educa-tion than do older women. Just asoverall levels of education vary wide-ly among countries, so does the gen-der difference in education at olderages. The gender gap3 in education-al attainment of the elderly is largerin many developed countries than indeveloping countries, where thelevel of education for the elderly isso low for both men and womenthat the difference between them issmall. In many developed countries,where overall attainment levels are


3 The gender gap is defined as the absolutedifference in percentage points between theeducational level of men and women. Forinstance, in Romania in 1992, 45.5 percent ofmen and 31.9 percent of women aged 65 andolder had completed secondary or higher edu-cation. The gender gap for the population aged65 and older with these levels of schoolingwould be the difference between the two levels(13.6 points).

Figure 9-4.

Percent Literate in Two Age Groups: Latest Available Year

Sources: United Nations Educational Scientific and Cultural Organization, 1995 and country sources.

65+

25-44

65+

25-44

65+

25-44

65+

25-44

65+

25-44

65+

25-44

65+

25-44

65+

25-44

65+

25-44

MaleFemale

23.3

Bolivia, 1992

Botswana, 1993

Brunei, 1991

Chile, 1992

Iran, 1991

Jordan, 1994

Thailand, 1990

Uganda, 1991

Zimbabwe, 1992

91.976.6

53.828.3

70.275.2

12.911.3

96.091.1

45.110.6

96.696.9

81.380.9

79.456.1

31.314.0

96.686.9

51.016.9

97.395.4

76.353.2

73.044.0

26.77.2

89.574.5

41.0

higher, the difference between oldermen and women is larger.

As suggested by the data on litera-cy discussed earlier, gender differ-ences in educational attainmentare much smaller for younger than

older cohorts. In various coun-tries, younger women completesecondary education at higherrates than do men, and in somenations the gender difference inuniversity-level attainment atyounger ages is negligible. Thus,

the disadvantages that today’solder women may face because oftheir lower levels of education rela-tive to men should begin to abatewhen these younger cohorts reachthe ranks of the elderly.

GENDER GAP IS INVERSELYRELATED TO AGE AT OLDERAGES

Examining the gender gap by age indeveloping countries reveals thedifferential rate of improvement ineducational attainment. Figure 9-5presents the gender gap in literacyrates for five age groups in severalcountries with data from the 1990s.A somewhat counter-intuitive pic-ture emerges for the three older agegroups, namely, that the gendergap decreases as age increases. Inother words, there is a largerabsolute difference between maleand female literacy rates at ages 55to 59 than among people aged 65and over. The increase in the gen-der gap for younger-old age groupsreflects historical patterns of educa-tional promotion. When countrieswith low overall levels of educationand limited resources began toimprove the educational attainmentof their populations, the initialfocus was more on educating malesthan females. In most developingcountries, people aged 55 and overwere of school age when formaleducation was not widespread.Although educational attainmentwas improving, it was improvingmore for men than for women.Thus, for these older age groups,the gender gap is less among theelderly than among people aged 55to 64. For some countries in Figure9-5, the gender gap at ages 25 to29 and 35 to 39 is smaller than atthe older ages, indicating a moreequal inclusion of both sexes ineducational programs in recentyears.


Figure 9-5.

Gender Gap in Literacy Rates for Selected Age Groups: Latest Available Year

Note: The gender gap is defined as the absolute difference in percentage points between the literacy rate for men and women.Source: United Nations Educational Scientific and Cultural Organization, 1995 and country sources.

65+

60-64

55-59

35-39

25-29

65+

60-64

55-59

35-39

25-29

65+

60-64

55-59

35-39

25-29

65+

60-64

55-59

35-39

25-29

65+

60-64

55-59

35-39

25-29

65+

60-64

55-59

35-39

25-29

Bolivia, 1992

Brunei, 1991

Iran, 1991

Jordan, 1994

Uganda, 1991

Yemen, 1994

19.4

9.1

18.6

32.9

31.6

25.5

0.9

6.4

48.0

43.7

34.5

18.9

26.5

23.4

19.7

17.3

3.9

13.9

47.3

44.8

34.1

23.9

32.5

35.4

27.3

19.5

48.5

37.8

28.7

21.6

EDUCATIONAL DISADVANTAGEIS COMMON IN RURAL AREAS

The quality and quantity of ruraleducational facilities in mostnations tend to be inferior to thosein urban areas. Consequently, liter-acy levels and educational attain-ment are lower in rural areas, par-ticularly in developing countries.Data for Yemen (Figure 9-6) illus-trate the common pattern whereinthe rural disadvantage in literacy isevident for both sexes (i.e., ruralmales have lower rates than urbanmales and rural females have lowerrates than urban females). Itappears that differences by genderare greater than differences byurban/rural residence. Urbanwomen have lower literacy ratesthan rural men, except at the veryyoungest ages. The sexes also dif-fer in size of the rural/urban gap byage. Rural males consistently havelower literacy rates than urban


Figure 9-6.

Percent Literate by Age, Sex, and Urban and Rural Residence, Yemen: 1994

Source: Population and Housing Census of Yemen, 1994.

0

20

40

60

80

100

75+70656055504540353025201510

Percent

Age

Female rural

Male urban

Male rural

Female urban

Table 9-1.Earnings Ratios of Selected Age Groups in 15 Countries by Level of EducationalAttainment: 1995

Country

45-54 years/25-29 years 55-64 years/45-54 years

Less than uppersecondary

Uppersecondary

Nonuniversitytertiary University Overall

Australia . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.30 1.26 1.35 2.06 0.85Canada . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.05 1.46 1.37 1.96 0.86Denmark . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.21 1.23 1.29 1.60 0.92Finland. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.43 1.36 1.69 2.11 0.90France . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.18 1.47 1.45 1.95 1.07

Germany . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.97 1.28 1.10 1.76 0.97Ireland . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.24 1.59 1.59 2.25 (NA)Japan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.23 1.44 1.64 1.99 0.86Mexico . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.13 1.61 1.33 1.65 0.84New Zealand . . . . . . . . . . . . . . . . . . . . . . . 1.25 1.39 1.16 1.93 0.95

Norway . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.10 1.26 1.88 1.67 (NA)Sweden . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.38 1.26 1.67 1.70 0.90Switzerland . . . . . . . . . . . . . . . . . . . . . . . . . 1.06 1.25 1.52 1.80 0.97United Kingdom . . . . . . . . . . . . . . . . . . . . . 0.93 1.09 1.41 1.50 0.81United States . . . . . . . . . . . . . . . . . . . . . . . 1.29 1.28 1.39 1.67 0.89

NA Not available.

Note: Ratios reflect gross annual earnings before taxes. Data for Finland and Ireland refer to 1994 and 1993 respectively.

Source: Organization for Economic Co-Operation and Development (Employment Outlook 1998).

males in Yemen, and the gapbetween the two areas is fairly evenacross the age spectrum. Forwomen, on the other hand, the gapbetween rural and urban literacylevels is much wider at the youngerthan the older ages, suggesting thatin recent years urban women havebeen afforded greater relativeaccess to education than have theirrural counterparts.

EDUCATION AFFECTS OTHERDIMENSIONS OF LIFE

As mentioned earlier, education isrelated to health behavior andincome accumulation throughoutthe life course. Studies in theUnited States have shown that

reading skills generally worsen withage; a recent study also demon-strated that functional healthliteracy is markedly lower at olderages, even after controlling for vari-ables such as cognitive dysfunction,physical functioning and visual acu-ity (Baker et al., 2000). This studyraises questions about the effects oflife-long education, the efficacy oftests that measure cognitive ability,and other age-related changes thatmay affect testing procedures.

Table 9-1 shows ratios of averageearnings for workers in three agegroups. The earnings ratio of per-sons in the so-called peak earningyears (45 to 54) to those of recent

labor force entrants (25 to 29 years)generally rises with educationalattainment level, but the right-handcolumn of Table 9-1 indicates anoverall decline in earnings of people55 to 64 relative to people 45 to54. Because educational attainmentmay be very different by agecohort, this table may confoundpure age effects with returns toeducation. Further analysis of avail-able data suggests that, when aver-aged over all countries, the earn-ings premium of peak-earningworkers relative to recent entrantsrises considerably with higher edu-cational attainment (OECD, 1998Employment Outlook).


Rapid growth of elderly populationsmay put pressure on a nation’sfinancial resources. This concern isbased, at least partially, on theassumption that the elderly do notcontribute to the economy. However,many older people do work, andexamining the labor force participa-tion and characteristics of olderworkers gives a clearer picture oftheir contribution. Information onolder workers also is useful in plan-ning economic development and thefinancing of retirement.

Some characteristics of older work-ers seem not to vary among coun-tries. In all countries, the elderlyaccount for a small proportion ofthe overall labor force. Their shareof the total labor force in the studycountries ranges from less than 1 percent to 7 percent. A secondcommonality is that labor force par-ticipation declines as people nearretirement age. A third is that par-ticipation rates are higher for oldermen than for older women.

Other characteristics of older work-ers show interesting differencesacross countries. The rate ofparticipation of older workers variessubstantially, and generally is lowerin developed than in developingcountries. Only 2 percent of menaged 65 and over participate in thelabor force in some developedcountries, whereas in certain devel-oping countries well over half ofelderly men are economically active.The occupational concentration ofolder workers also varies widelyamong countries.

Figure 10-1 presents data on formaleconomic activity for older womenand men in three countries, chosento represent different levels of eco-nomic development. Some of thepatterns mentioned above areapparent in these data; olderwomen have lower participationrates than older men, and participa-tion rates for both sexes decrease

with age. On the other hand, thework status of older workers differsdramatically among the countries.In Rwanda, more than three-quarters of all women aged 60 to64 are economically active, andeven at ages 70 and older, a sub-stantial number remain active in thelabor force. In contrast, although anontrivial proportion of women


CHAPTER 10.

Labor Force Participationand Retirement

Figure 10-1.

Economically Active Older Population by Age for Rwanda, Peru, and New Zealand: Late 1990s

Source: International Labour Office (various issues of the Yearbook of Labour Statistics).

75+

70-74

65-69

60-64

75+

70-74

65-69

60-64

75+

70-74

65-69

60-64

MaleFemale

Rwanda, 1996

New Zealand, 1999

Peru, 1999

1.1

86.977.8

81.573.4

66.051.7

45.632.5

72.538.2

56.323.4

46.226.2

29.011.1

57.532.5

20.410.0

8.82.92.8

(Percent)

aged 60 to 64 are economicallyactive in New Zealand, participationrates decrease dramatically withage so that for women aged 70 to74, less than 3 percent are stillactive. Cross-national differences inlevels of labor force activity areassociated with societal wealth;countries with high GNP (grossnational product) tend to havemuch lower labor force participa-tion rates of the elderly and nearelderly than do low-income coun-tries (Clark, York, and Anker, 1997).In richer countries, the elderly ornear elderly can afford to retirebecause of pension schemes orsocial security systems. These pro-grams are often lacking in poorercountries.


Figure 10-2a.

Labor Force Participation Rates for Men Aged 55 to 59 in Developed Countries

Sources: U.S. Census Bureau, 2000a and International Labour Office (various issues of the Yearbook of Labour Statistics).

United States

Sweden

Poland

New Zealand

Luxembourg

Japan

Italy

Hungary

Germany

France

Czech Republic

Canada

Bulgaria

Belgium

Austria

Australia

Early 1970s Late 1990s

78.4

88.472.5

83.763.7

82.352.4

86.558.0

84.972.2

85.077.1

81.870.4

86.876.5

84.445.9

75.054.1

94.2

94.7

79.353.4

92.181.2

90.955.2

88.4

84.4

86.8

(Percent)

TIME TREND IN LABOR FORCEPARTICIPATION DIFFERS BYGENDER

The trend in most developed coun-tries has been for labor forceparticipation rates for older men todecline in recent decades. Figure10-2 shows male labor force partici-pation rates for three older agegroups in 16 developed countries;in all of these countries, participa-tion rates declined between theearly 1970s and the late 1990s.These declines are particularly pro-nounced for men aged 60 to 64.In ten of the sixteen countries inthe early 1970s, well over half ofmen aged 60 to 64 were still active.


Figure 10-2b.

Labor Force Participation Rates for Men Aged 60 to 64 in Developed Countries


United States

Sweden

Poland

New Zealand

Luxembourg

Japan

Italy

Hungary

Germany

France

Czech Republic

Canada

Bulgaria

Belgium

Austria

Australia


(Percent)

54.8

75.646.7

44.916.7

79.318.6

33.611.1

74.146.6

33.327.5

54.616.4

68.830.3

43.710.6

40.6

31.785.8

74.1

45.515.5

69.257.4

83.033.4

75.755.5

73.0

In the remaining six countries activ-ity rates ranged from 33 percent to46 percent. By the late 1990s, onlyJapan, New Zealand, Sweden, andthe United States had male partici-pation rates over 50 percent. Ratesalso have fallen for the 65-and-overage group.1 In the early 1970s,only two countries in Figure 10-2had participation rates lower than10 percent for elderly men; by thelate 1990s, most of the countrieshad rates less than 10 percent. Butas discussed later in this chapter,the trend in declining participationrates for older men has stopped oreven reversed in a number of devel-oped countries.


Figure 10-2c.

Labor Force Participation Rates for Men Aged 65+ in Developed Countries

Note: Later data for Belgium 65+ refer to ages 65-69 and for Hungary to ages 65-74; data for Sweden 65+ are not reported by the ILO. Sources: U.S. Census Bureau, 2000a and International Labour Office (various issues of the Yearbook of Labour Statistics).

United States

Sweden

Poland

New Zealand

Luxembourg

Japan

Italy

Hungary

Germany

France

Czech Republic

Canada

Bulgaria

Belgium

Austria

Australia


(Percent)

16.9

22.29.6

8.04.6

6.82.8

10.34.5

23.69.9

14.67.2

10.72.3

16.04.5

16.73.8

13.46.3

54.535.5

10.11.9

21.310.4

56.415.3

15.2

24.8

1 In the United States, much of the decline inlabor force participation rates for elderly menoccurred earlier in the twentieth century.According to Costa (1998), 70 percent of thedecline in participation rates between 1880 and1990 for men aged 65 and older occurredbefore 1960.

The trend for older women in thesedeveloped countries differs fromthe male pattern. In many coun-tries, female participation rateshave increased for almost all adultage groups up to age 60, whereasrates for elderly women havedeclined (Figure 10-3). In somecases, the increase among womenaged 55 to 59 has been quitemarked. In New Zealand, for exam-ple, 60 percent of women aged 55to 59 were economically active in1998, up from 28 percent in 1971.


Figure 10-3a.

Labor Force Participation Rates for Women Aged 55 to 59 in Developed Countries


United States

Sweden

Poland

New Zealand

Luxembourg

Japan

Italy

Hungary

Germany

France

Czech Republic

Canada

Bulgaria

Belgium

Austria

Australia


(Percent)

61.8

28.344.6

35.825.4

20.027.6

26.110.7

38.7

50.6

36.533.2

42.1

51.7

34.555.3

29.216.6

16.922.7

53.8

58.718.6

24.6

27.560.1

68.135.0

41.179.0

47.4

While female participation wasincreasing at younger ages, nearlyall developed countries experienceda decrease in elderly female laborforce participation between theearly 1970s and the late 1990s.Very small proportions of elderlywomen currently are economicallyactive in developed nations; amongthe 22 developed countries inAppendix A, Table 10, only Japan,Poland, and the United States haveelderly female participation ratesabove 4 percent.2


Figure 10-3b.

Labor Force Participation Rates for Women Aged 60 to 64 in Developed Countries


United States

Sweden

Poland

New Zealand

Luxembourg

Japan

Italy

Hungary

Germany

France

Czech Republic

Canada

Bulgaria

Belgium

Austria

Australia


(Percent)

38.8

16.018.3

13.28.7

7.66.7

8.24.7

29.126.0

18.212.9

27.915.2

17.712.7

17.15.5

9.98.1

43.339.8

12.011.7

15.532.5

51.119.2

25.746.5

36.1

2 Rates for Norway and Ukraine in AppendixTable 10 are about 9 percent, but these refer toonly a portion of their elderly female popula-tions, i.e., women aged 65 to 74.

WHY THE BIG DECREASE FOROLDER MEN?

Several reasons may account for thesharp decline in activity rates ofolder men in developed countries.An increase in societal wealth ismost likely the main reason for thedrop in participation rates. A sec-ondary reason may be that newtechnologies have changed theindustrial and occupational organi-zation of many economies, andgenerated the need for a recentlytrained labor force. New technolo-gies can make the skills of olderworkers obsolete and these workersmay choose to retire rather thanlearn new skills (Ahituv and Zeira,2000; Bartel and Sicherman, 1993).In countries with persistently highlevels of unemployment, there maybe formal and informal pressureson older workers to leave the laborforce to make room for youngerworkers. Perhaps most importantly,the growth and proliferation offinancial incentives for early retire-ment have enabled many olderworkers to afford to stop working.In much of Eastern Europe and theformer Soviet Union, older workersare choosing early retirement overunemployment as new marketmechanisms prompt firms to fireredundant workers (Commanderand Yemtsov, 1997).


Figure 10-3c.

Labor Force Participation Rates for Women Aged 65+ in Developed Countries

Note: Later data for Belgium 65+ refer to ages 65-69 and for Hungary to ages 65-74; data for Sweden 65+ are not reported by the ILO. Sources: U.S. Census Bureau, 2000a and International Labour Office (various issues of the Yearbook of Labour Statistics).

United States

Sweden

Poland

New Zealand

Luxembourg

Japan

Italy

Hungary

Germany

France

Czech Republic

Canada

Bulgaria

Belgium

Austria

Australia


(Percent)

8.9

4.23.1

3.22.0

2.20.8

1.72.1

8.33.4

5.22.7

5.02.0

5.71.6

5.81.6

3.21.7

19.7

14.9

4.00.6

3.53.9

33.08.5

3.2

10.0

ELDERLY IN DEVELOPINGCOUNTRIES HAVE HIGHPARTICIPATION RATES

The proportion of economicallyactive elderly men is high in devel-oping countries compared withmore-industrialized nations. Notsurprisingly, many elderly people inpredominantly rural agrarian soci-eties work of necessity, while“retirement” may be a luxuryreserved for urban elites. In nationsas diverse as Bangladesh,Indonesia, Jamaica, Mexico,Pakistan, and Zimbabwe, more than50 percent of all elderly men areconsidered to be economicallyactive. Economic activity rates ofolder and elderly women also arehigher in developing than in devel-oped countries. Some national datamay understate the true economicactivity of women, particularly indeveloping countries where muchof the work that women engage inis not counted or captured in cen-suses and labor force surveys, or isnot considered to be “economic.”Many of the activities that olderwomen are involved in, such assubsistence agriculture or house-hold industries, often are not welldocumented by conventional datacollection methods (Hedman,Perucci, and Sundström, 1996).


Figure 10-4a.

Labor Force Participation Rates for Men Aged 55 to 59 in Developing Countries

Note: Data for Ethiopia in the early 1970s are not available. Sources: U.S. Census Bureau, 2000a and International Labour Office (various issues of the Yearbook of Labour Statistics).

Uruguay

Turkey

Tunisia

South Korea

Singapore

Peru

Mexico

Ethiopia

Chile

Argentina


(Percent)

89.3

80.482.882.683.4

93.3

86.286.8

92.885.6

73.977.9

85.481.0

86.078.4

88.060.3

81.2

Figure 10-4b.

Labor Force Participation Rates for Men Aged 60 to 64 in Developing Countries


Uruguay

Turkey

Tunisia

South Korea

Singapore

Peru

Mexico

Ethiopia

Chile

Argentina


(Percent)

59.3

57.263.2

72.169.2

89.4

81.577.3

83.972.5

55.648.6

67.965.566.5

54.183.0

54.058.9

Data on economic activity ratesover time for developing countriesdo not show as clear a trend forolder workers as seen in developedcountries. Although many devel-oping countries have experienceda decrease in economic activity ofolder male workers, in most suchcountries the decrease is muchsmaller than in developed coun-tries (Figure 10-4). Akin to the pat-tern in developed countries, manydeveloping countries have wit-nessed an increase in labor forceparticipation rates for women aged55 to 64 (Figure 10-5). Unlike thepattern in developed nations, sev-eral developing countries also haveexperienced increases in participa-tion for women aged 65 and older.Because of the problems with sta-tistics on female economic activitymentioned above, these changescould reflect “real” increases inactivity rates as well as improve-ments in data collection.


Figure 10-4c.

Labor Force Participation Rates for Men Aged 65+ in Developing Countries


Uruguay

Turkey

Tunisia

South Korea

Singapore

Peru

Mexico

Ethiopia

Chile

Argentina


(Percent)

19.4

29.127.6

42.427.4

65.7

67.152.4

61.541.1

31.921.7

35.140.2

38.034.0

67.833.6

20.9

Figure 10-5a.

Labor Force Participation Rates for Women Aged 55 to 59 in Developing Countries


Uruguay

Turkey

Tunisia

South Korea

Singapore

Peru

Mexico

Ethiopia

Chile

Argentina


(Percent)

41.0

16.235.4

15.532.4

58.615.4

32.416.1

47.516.2

28.4

39.151.2

11.312.2

50.0

30.421.7

AGRICULTURE STILLIMPORTANT SOURCE OFEMPLOYMENT FOR ELDERLY

Just as labor force participationrates of older workers vary amongcountries, so do levels of concentra-tion in various occupations.Economies in developed countrieshave shifted from agriculture andheavy industries toward servicesand light industries, which is a shiftfrom physically demanding andsometimes hazardous jobs to workwhich requires less brawn and dif-ferent technical skills. This shiftmay benefit older workers insofaras jobs requiring mental abilityrather than physical strength mayenable them to remain activelonger. Conversely, the shift couldbe detrimental to older workers ifthe new jobs require skills or train-ing which older workers may nothave or easily acquire.


Figure 10-5b.

Labor Force Participation Rates for Women Aged 60 to 64 in Developing Countries


Uruguay

Turkey

Tunisia

South Korea

Singapore

Peru

Mexico

Ethiopia

Chile

Argentina


(Percent)

23.9

10.322.6

11.121.0

50.014.4

25.9

13.438.2

13.414.9

26.946.3

8.67.7

47.623.4

12.2

Figure 10-5c.

Labor Force Participation Rates for Women Aged 65+ in Developing Countries


Uruguay

Turkey

Tunisia

South Korea

Singapore

Peru

Mexico

Ethiopia

Chile

Argentina


(Percent)

6.7

4.78.9

6.56.5

27.511.8

14.68.5

19.2

6.55.2

10.621.4

4.83.5

35.113.3

3.6

Not surprisingly, agriculture is byfar the most common occupationfor older and elderly workers inmost developing countries (Figure10-6). And despite the worldwidetrend away from employment inagriculture, this sector was still animportant source of employment inmany developed countries duringthe 1970s and 1980s. Even in the1990s, a nontrivial proportion ofeconomically active elderly in somedeveloped countries worked in theagricultural sector. In 1995 inJapan, 31 percent of elderly menand 35 percent of elderly womenwere involved in agriculture.Aggregate data from the early1990s for 12 European Unionnations showed that agriculture


Figure 10-6.

Percent of Elderly Workers in Agriculture

Note: Data for New Zealand refer to ages 60 and over. Source: National sources.

United States, 1998

Turkey, 1990

Philippines, 1990

New Zealand, 1991

Japan, 1995

Ecuador, 1990

China, 1990

MaleFemale

3.2

88.393.2

57.030.030.7

34.721.2

15.376.4

32.275.7

95.6

11.4

Table 10-1.Older Workers (55 and Over) per 100 Younger Workers (Under 55) in Selected JobSectors: 1998

Goods-producing sector Service sector

Total

Agriculture,hunting and

forestryManu-

facturing TotalPersonalservices

Socialservices

OECD average 15 39 10 12 11 12

Austria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 28 6 7 7 7Belgium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 21 5 7 8 7Canada . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 27 10 10 9 10Czech Republic . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 12 9 10 9 13Denmark . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 34 11 12 15 13

Finland. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 24 9 9 8 10France . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 20 6 8 10 8Germany . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 30 14 15 16 16Greece. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 68 11 11 12 9Ireland . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 45 7 10 10 13

Italy. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 33 8 13 12 13Korea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 131 8 13 (NA) (NA)Luxembourg . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 19 6 7 5 10Mexico . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 28 8 11 13 7Netherlands . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 21 8 7 6 8

New Zealand . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 26 7 7 - 8Norway . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 36 16 15 9 18Portugal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 112 10 15 18 12Spain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 36 11 12 14 13Sweden . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 50 17 19 15 21

Switzerland . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 39 18 17 20 18United Kingdom . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 32 14 13 14 14United States . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 25 13 15 11 16

- Represents zero. NA Not available.

Source: Excerpted from Organization for Economic Co-Operation and Development (Employment Outlook 2000).

continued to employ a dispropor-tionate share of older relative toyounger workers (Eurostat, 1993a).More than 20 percent of economi-cally active men and women aged60 and older in these countriesworked in agriculture comparedwith about 5 percent of peopleaged 14 to 59. More recent infor-mation for 23 OECD countriesshows that the ratio of older (55+)to nonolder (54 and under) workersis generally much higher in agricul-ture, hunting, and forestry than inany other goods-producing or serv-ice sector (Table 10-1).

NEARLY TWO-THIRDS OFELDERLY FEMALE U.S.WORKERS IN SERVICE ANDSALES

Figure 10-7, which presents theoccupational distribution of elderlymale and female workers in theUnited States, shows distinct differ-ences by gender. In 1998, almosthalf of elderly working women wereemployed in clerical or service jobscompared with only 17 percent ofelderly men. A majority of workingelderly men held either manageri-al/professional/technical positions(34 percent) or production jobs (23 percent). Corresponding figuresfor elderly women were 25 percentand 8 percent. Unlike the situationin some developed countries, only11 and 3 percent of active elderlyU.S. men and women, respectively,worked in agriculture.

BRIDGES TO RETIREMENT

Just as the propensity to work atolder ages varies considerably fromcountry to country, so too do pat-terns of retirement and the concept

of retirement itself. During periodsof economic contraction in highlyindustrialized nations, governmentsmay actively encourage older work-ers to cease active employment atrelatively young ages. On the otherhand, when the labor market istight, governments may look formethods to entice older workers toremain in the labor force or re-enterthe labor force.

In developed countries, retirementfrom the workforce was an eventthat occurred almost exclusively ata regulated age until the 1950s,with little possibility of receiving apension prior to that age (Tracy,1979). Since then, countries haveadopted a wide range of approach-es to providing old-age security,and different potential routes haveemerged for people making thetransition from labor force participa-tion to retirement. Some of thesedifferent routes are working parttime, leaving career jobs for transi-tion jobs, or leaving the labor forcebecause of a disability.

OLDER WOMEN MORE LIKELYTHAN OLDER MEN TO WORKPART TIME

Some older workers use part-timework as a gradual transition toretirement (Walker, 1999). Part-timework is an option that may appealto older workers by enabling themto remain active in the labor forcewhile also pursuing leisure activities(Quinn and Kozy, 1996). Data forworking men aged 60-64 in ninedeveloped countries show large dif-ferences in the prevalence of part-time employment, ranging fromless than 8 percent in Italy andGermany to more than 35 percentin Sweden and the Netherlands(OECD, 2000). Available data fromdeveloped countries suggest thatolder working women are muchmore likely than older men to beinvolved in part-time work (Figure10-8). In Australia, three-fourths ofelderly women who were economi-cally active in 1999 worked parttime, compared to fewer than halfof economically active elderly men.


Figure 10-7.

Percent Distribution of Elderly Workers by Occupation in the United States: 1998

Source: Bureau of Labor Statistics, unpublished tabulations from the Current Population Survey, average annual data, 1998.

Agriculture

Production

Clerical/Service

Sales

Managerial/Professional/

Technical

MaleFemale

3.2

33.824.7

14.816.7

16.947.8

23.27.6

11.4

In the 15 European Union countriesas a whole, 41 percent of workingwomen aged 55-64 were in part-time positions in 1998, comparedwith just 8 percent of working menin that age group (Eurostat, 2000).

The rate of part-time work for peo-ple nearing retirement generally wasincreasing with time in the late1980s/early 1990s (Eurostat,1993b). Even though percentagesof older workers who work parttime may be substantial, a recentOECD (2000) analysis notes thatthese percentages often representonly a small fraction of the totalolder population, since many peoplehave retired by age 60. Looking atolder male cohorts as they aged inthe 1990s, the study concludes that

gradual retirement is still relativelyuncommon in industrialized nations.The strongest tendency toward part-time work was seen in Japan,Sweden, and the United States.

UNEMPLOYMENT LOW AMONG THE ELDERLY

The elderly typically have low lev-els of unemployment compared toyounger workers. In developedcountries, unemployment rates forthe elderly frequently are less than5 percent (OECD Labour ForceStatistics, 2000). However, peopleaged 55 to 64 often have unem-ployment rates higher than or simi-lar to rates for people aged 25 to54 (Figure 10-9). Establishing atime trend in unemployment ratesfor older people is hindered by

data availability, the effects of thebusiness cycle, and differences indefinitions across countries.3 Incountries with available data,unemployment rates for all agegroups commonly were higher in1999 than in 1980. Gender differ-ences in unemployment rates atolder ages are not consistent; insome countries, men have higherrates and in others the reverse istrue. When unemployment ratesfor ages 55 to 64 are disaggregat-ed, rates for the age group 55 to59 tend to be somewhat higherthan for the age group 60 to 64,perhaps because people in theolder age group may opt to retire ifpossible rather than be unemployed.

Although the unemployment ratemay be lower for older than foryounger workers, older people whoare unemployed tend to remainunemployed longer than theiryounger counterparts. In severalOECD countries, well over half ofunemployed people aged 55 andover had been unemployed continu-ously for more than 1 year. In mostOECD countries, the proportion oflong-term unemployed people aged55 and older is much higher thanamong younger age groups. A simi-lar pattern is seen in some EasternEuropean nations. In Bulgaria in1995, 74 percent of unemployedmen aged 50 to 59 and 78 percentof unemployed women aged 50 to54 had been without work for morethan 1 year (European Commission,1995).


Figure 10-8.

Percent of Economically Active Elderly Population Working Part Time in Australia, Canada, and France

Note: Data for France refer to ages 60 and over. Source: National sources.

74.2

53.2

38.6

44.1

33.2

20.7

France 1995Canada 1991Australia 1999

MaleFemale

3 And, in many developing countries, thelack of programs to provide monetary supportduring unemployment means that most peoplecannot “afford” to be unemployed.


Figure 10-9.

Unemployment for Three Age Groups: 1980, 1990, and 1999

Notes: Unemployment rates for people aged 65+ in Canada, Germany, Japan, and Sweden were reported to be zero in certain years. Latest data for Canada refer to 1998. 1980 data for Germany refer to West Germany. Source: Organization for Economic Co-Operation and Development, 2000 (Labor Force Statistics 1979-1999).

Male Female

1980 1990 1999

7.2 7.0

2.7

6.9 6.7

2.9

7.26.2

1.5

7.6

5.75.1

4.4

1.8

6.8

5.1

65+55-6425-5465+55-6425-54

(Percent)

Canada

Male Female



7.3

12.8

0.8

8.7

15.5

2.2

3.6

6.5

0.4

5.8

8.1

0.6

2.0

4.9

3.8

5.9

65+55-6425-5465+55-6425-54

Germany

3.0 2.7 3.0 3.42.6

3.2

4.63.8

3.0

4.6

2.8 3.1

5.1

3.4 3.1

6.0

3.3 3.1

65+55-6425-5465+55-6425-54

United States

6.57.3

5.9 5.9

1.3 1.3 1.0 1.2 1.6 1.31.21.6 1.7 1.7

65+55-6425-5465+55-6425-54

Sweden

3.7

6.7

2.9

4.4

3.3

0.51.4

3.4

1.42.1

1.41.5

3.7

2.2 2.01.2

65+55-6425-5465+55-6425-54

Japan

9.0 8.7

1.9

12.6

8.7

1.5

5.9 6.0

0.5

10.7

7.6

0.8

2.8

4.8

0.5

6.3 6.2

0.6

65+55-6425-5465+55-6425-54

France

Age group Age group

DISCOURAGEMENT REDUCESNUMBER OF OLDER WORKERS

The definition of discouraged work-er differs somewhat from country tocountry, but the basic conceptrefers to people who are no longerlooking for work because they think

there is no work available orbecause they do not know where tolook. Workers who become dis-couraged from actively seekingwork are no longer considered partof the economically active popula-tion. In some countries,

discouragement of older workers isthought to be related to changes inoccupational structure and the sub-sequent need for a more-educatedworkforce which favor youngerover older workers.

Cross-national data on discouragedworkers are fairly sparse. One com-parison of 13 countries for 1993indicates that older workers makeup a disproportionate share of alldiscouraged workers, except inSweden. Illustrative data for six ofthese countries (Figure 10-10) showthat while people aged 55 to 64account for a small proportion of alleconomically active people, theyaccount for a much larger propor-tion of all discouraged workers,especially in the United Kingdomwhere more than two-thirds of alldiscouraged male workers wereaged 55 to 64. In countries withdata over time, discouraged olderworkers were more numerous inthe early 1990s than in the early1980s. Discouragement seems tobe more permanent among olderworkers, as they are less likely tore-enter the labor force than theiryounger counterparts. Survey datafor 1990 for Belgium and Franceshow that more than half of menaged 55 to 59 who had lost theirjobs in the 3 years preceding thesurveys were no longer in the laborforce (OECD, 1995). The correspon-ding figure for all workers was clos-er to one-quarter. Because of thedifficulties older people face inobtaining a new job, discourage-ment often becomes a transitionfrom unemployment to retirement.


Figure 10-10.

Older Share of Economically Active Population and Discouraged Worker Population: 1993

Note: Data for Norway include persons aged 64-74; data for the United States include people aged 65 and over.Sources: Organization for Economic Co-Operation and Development, Employment Outlook 1995 and International Labour Office Yearbook of Labour Statistics, 1994.

Females

Males

Female

Male

Female

Male

Female

Male

Female

Male

Female

Male

(In percent)Economicallyactive peopleaged 55-64 asa percent ofall economicallyactive peopleaged 25-64

Australia

Canada

Mexico

Discouragedworkers aged55-64 as a percentof all discouragedworkers aged25-64

United States

Denmark

United Kingdom

24

1155

729

1150

942

1344

1153

1236

826

1469

1253

1226

11

INVALIDITY AND DISABILITYPROGRAMS MAY BE AVENUESTO RETIREMENT

Another path to retirement for olderworkers has been disability pro-grams. In Europe during the lastthree decades, economic recessionsand high unemployment led somegovernments (e.g., Germany, theNetherlands, Sweden) to encourageretirement by means of publicmeasures such as disabilityschemes and long-term sicknessbenefits. In many countries in thelate 1980s and early 1990s, disabil-ity pensioners made up the largestproportion of all early pensioners(OECD, 1992). Data for 1990showed that the proportion of olderpeople receiving an invalidity bene-fit could be very large, e.g., nearlyone-third of all people aged 60 to64 in Finland and Sweden, andnearly half of the same age groupin Norway (OECD, 1995). Whilenumerous nations have modified orrevamped their disability/invalidityprograms during the last decade, itappears likely that the varyingnational provisions of such pro-grams have an impact on retirementpatterns. Comparative data for 16European countries in the mid-1990s (Figure 10-11) show that thepercentage of older retired menwho retired due to their own illnessor disability ranged from 2 percentin Portugal to 29 percent inSwitzerland.

ACTUAL RETIREMENT AGEOFTEN LOWER THANSTATUTORY AGE

Over several decades, many indus-trialized nations lowered the stan-dard age at which people become

fully entitled to public pensionbenefits. These reductions werepropelled by a combination of fac-tors including general economicconditions, changes in welfare phi-losophy, and private pensiontrends. The proliferation of earlyretirement schemes has increasedthe number and usually the propor-tion of older workers who availthemselves of such programs (Tracyand Adams, 1989).

One important issue for policymak-ers and pension funds is the rela-tionship between the standard(statutory) retirement age and “actu-al” retirement age, the average ageat which retirement benefits are

awarded. In spite of the loweringof statutory retirement ages, theactual average age of retirement islower than the statutory age in alarge majority of industrializedcountries. Of the 24 countries inTable 10-2, the actual age exceedsthe standard age only in Greece,Japan, and Turkey, and also inIceland for men and in Italy forwomen. In several countries (e.g.,Austria, Belgium, and Finland), theaverage man retires 6 years or morebefore the standard retirement age.Differences are often greater forwomen, approaching 10 years inLuxembourg and the Netherlands.


Figure 10-11.

Percent of Retired Men Aged 55 to 64 Who Left Last Job Due to Own Illness or Disability: 1995-96

Source: Excerpted from Organization for Economic Co-Operation and Development (Employment Outlook, 2000).

Portugal

Austria

Greece

Italy

Sweden

France

Belgium

Denmark

Ireland

Netherlands

Luxembourg

Spain

United Kingdom

Germany

Finland

Switzerland

2.1

28.9

25.0

22.9

22.8

18.3

16.6

15.6

15.1

9.5

7.7

7.3

7.0

5.2

4.1

2.6

TREND IN EARLY RETIREMENTMAY BE CHANGING

The downward shift in the statutoryage at retirement during the 1970sand 1980s in developed countrieswas accompanied by an increase inthe number of public early retire-ment programs and a correspon-ding increase in the number ofretirees leaving the labor force priorto the statutory age. Some coun-tries promoted early retirement as ameans of offsetting persistentlyhigh levels of unemployment. InDenmark, for example, a voluntaryearly retirement scheme was con-structed to encourage older work-ers to leave the labor market(Petersen, 1991). Mandatory retire-ment practices and worsening

health of older workers were twoother factors said to have increasedearly retirement. More recentresearch, however, discounts theimportance of these factors (Levineand Mitchell, 1993; Blondal andScarpetta, 1998; Fronstin, 1999)and points instead to changes insocial security/private pension pro-visions as well as to improved eco-nomic status of older workers andincreases in wealth overall. AsRuggles (1992) has noted in thecontext of the United States, com-parisons of today’s elderly with theelderly in previous decades suggestgreat increases in economic status.People entering the ranks of theelderly have higher educationalattainment, higher-paid employmenthistories, and higher average

income than did earlier cohorts ofelderly.

Some nations have raised (or areconsidering an increase in) statutoryretirement age as one means of off-setting the fiscal pressures of popu-lation aging,4 in addition to foster-ing policies that encourage laborforce participation at older ages.The effect of such actions is not yetcertain. Data for nine OECD coun-tries from 1975 to 1990 reveal ageneral downward trend in actualretirement age during the period1975-1990, with an apparent level-ing off in the latter part of the peri-od. Gendell’s (1998) analysis ofGermany, Japan, Sweden, and theUnited States generally supportsthis picture (Figure 10-12).However, several studies haveargued that the early retirementtrend in the United States hasstopped (Smeeding and Quinn,1997; Burkhauser and Quinn, 1997;Quinn, 1997). Furthermore, a recentOECD (2000) analysis of employ-ment rates notes that the rates formen aged 55 to 59 and 60 to 64have increased slightly in the late1990s in both the United States andthe Netherlands, and have stoppeddeclining in Canada, Germany,Finland, Japan, Sweden and theUnited Kingdom. The OECD studysuggests that this change is relatedto the secular economic upturn inthe latter 1990s.


Table 10-2.Standard and Actual Retirement Age in 24 Countries:1995

CountryMale Female

Standard Actual Standard Actual

Australia . . . . . . . . . . . . . . . . . . . . . . . . . . . 65 61.8 60 57.2Austria . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65 58.6 60 56.5Belgium . . . . . . . . . . . . . . . . . . . . . . . . . . . 65 57.6 60 54.1Canada . . . . . . . . . . . . . . . . . . . . . . . . . . . 65 62.3 65 58.8Denmark . . . . . . . . . . . . . . . . . . . . . . . . . . 67 62.7 67 59.4Finland . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65 59.0 65 58.9France . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60 59.2 60 58.3Germany . . . . . . . . . . . . . . . . . . . . . . . . . . 65 60.5 65 58.4Greece . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62 62.3 57 60.3Iceland . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67 69.5 67 66.0Ireland . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66 63.4 66 60.1Italy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62 60.6 57 57.2Japan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60 66.5 58 63.7Luxembourg . . . . . . . . . . . . . . . . . . . . . . . 65 58.4 65 55.4Netherlands. . . . . . . . . . . . . . . . . . . . . . . . 65 58.8 65 55.3New Zealand. . . . . . . . . . . . . . . . . . . . . . . 62 62.0 62 58.6Norway . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67 63.8 67 62.0Portugal . . . . . . . . . . . . . . . . . . . . . . . . . . . 65 63.6 62.5 60.8Spain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65 61.4 65 58.9Sweden . . . . . . . . . . . . . . . . . . . . . . . . . . . 65 63.3 65 62.1Switzerland . . . . . . . . . . . . . . . . . . . . . . . . 65 64.6 62 60.6Turkey . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60 63.6 55 66.6United Kingdom . . . . . . . . . . . . . . . . . . . . 65 62.7 60 59.7United States . . . . . . . . . . . . . . . . . . . . . . 65 63.6 65 61.6

Note: The standard age of retirement (also called the statutory age) refers to the ageof eligibility for full public pension benefits. The actual age reflects the estimated averageage of transition to inactivity among older workers.

Source: Organization for Economic andCo-Operation Development, 1998 (AgeingWorking Paper 1.4).

4 In the United States, for example, theSocial Security system was revised in 1983 toestablish higher statutory retirement ages forpeople born after 1937 (i.e., who reach age 65after the year 2002). An individual’s retirementage is linked to year of birth; beginning in theyear 2003, the “normal” retirement age of 65will edge higher in small increments until reach-ing 67 years in the year 2025 (Robertson,1992). Germany’s 1992 Pension Act also pro-vides for a progressive increase in pensionableage beginning at the turn of the century.


Figure 10-12.

Average Age at Labor Force Exit in Four Countries: Late 1960s to Early 1990s

Source: Gendell, 1998.

Male

Female

Male

Female

Male

Female

Male

Female

Germany Sweden

Japan United States

0

55

60

65

70

1995199019851980197519701965

Age

0

55

60

65

70

1995199019851980197519701965

Age

0

55

60

65

70

1995199019851980197519701965

Age

0

55

60

65

70

1995199019851980197519701965

Age

ADULTS SPENDING GREATERPORTION OF LIFE INRETIREMENT

Gains in life expectancy during thetwentieth century have intersectedwith declining retirement ages toproduce an increase in the propor-tion of an individual’s life spent inretirement. The OECD, using anaverage of unweighted data for 15member countries, has decomposedthe life course into four states:

years before entry into the labormarket (primarily spent in school);years not in work due to unemploy-ment and/or economic inactivity;years in the labor force; and yearsin retirement. Figure 10-13 showsthat in 1960, men on average couldexpect to spend 46 years in thelabor force and a little more than 1 year in retirement. By 1995, thenumber of years in the labor forcehad decreased to 37 while the

number of years in retirement hadjumped to 12. Unlike the trend formen, the average number of yearsin employment for women has beenincreasing, reflecting the temporalchanges in female labor force par-ticipation described earlier. At thesame time, the amount of timewomen live after reaching retire-ment age increased greatly, from 9 years in 1960 to more than 21 years in 1995.


Figure 10-13.

Decomposition of the Life Course, OECD Average: 1960 to 1995

Note: Based on an unweighted average of data for 15 member countries, using average life expectancies and labor force patterns as they existed for the years shown. These graphs are illustrative of overall trends, and should not be construed as representing the experience of any particular age cohort. Source: Organization for Economic Co-Operation and Development, 1998b.

Male Female

0

10

20

30

40

50

60

70

80

90

19951990198019701960

Age

0

10

20

30

40

50

60

70

80

90

19951990198019701960

Age

Age of entry inthe labormarket

Age ofretirement

Years in employment

Years in retirement

Years in employment

Years in retirementLife expectancy

Age of entry inthe labormarket

Age ofretirement

Life expectancy

Years not in work

Years not in work

Years before the labor market Years before the labor market

PUBLIC PENSION SYSTEMPROVISIONS SOMETIMESINDUCE EARLY RETIREMENT

Research has begun to considernational differences among laborforce participation at older ages asa consequence (intended or unin-tended) of retirement provisionsand/or tax policy. In some coun-tries, retirement benefit paymentsare increased for people who post-pone their retirement beyond theallowable early retirement age. Inother countries, there is no futurebenefit to be gained by postponingretirement. One synthesis of vari-ous studies in industrialized nations(Gruber and Wise, 1999) looked atthe “implicit tax on work,” a con-cept which contrasts the longerstream of future benefit paymentsthat a worker would receive byretiring at an early age versus theshorter stream of future paymentsthat a worker might receive bydelaying his/her retirement. InFrance, for example, social securitybenefits are first available at age60, and there is no increase in the

eventual benefit payment rate forpeople who retire after age 60. Inthe United States, social security

benefits may be initially obtained atage 62, but the benefit paymentrate is less than if a worker retires


Figure 10-14.

Implicit Tax Rate on Work in France and the United States: Circa 1995

Source: Gruber and Wise, 1999. Reproduced with permission from graphs in "Social Security and Retirement Around the World," Research Highlights in the Demography and Economics of Aging, Issue No. 2, June 1998.

-60

-30

0

30

60

90

7068666462605856

Percent

Age

France

United States

later, e.g., at age 65. Figure 10-14compares the implicit tax rates onwork in France and the United

States. The age-specific retirementage in France shows a steep jumpin retirement at age 60, which not

surprisingly corresponds to thelarge implicit tax rise at that age.

The same study also considered a“tax force to retire,” defined as thetotal of the annual tax rates onwork between the ages of 55 and69. Plotting this variable against ameasure of unused productivecapacity (simply, the percentage ofpeople aged 55 to 65 who were notworking) reveals a strong cross-national relationship between thetwo (Figure 10-15). This findingsuggests that the financial structureof national social security systemsmay reward early retirement, andthat attempts to encourageincreased labor force participationat older ages may be largely contin-gent upon policy changes in thesesystems. This study also highlightsthe potential power of focusing onsystem design features, and standsas a powerful example of theimportance of cross-nationalresearch on aging-related issues.


Figure 10-15.

Tax Rates and Unused Capacity in 11 Developed Countries: Circa 1995

Source: Gruber and Wise, 1999. Reproduced with permission from graphs in "Social Security and Retirement Around the World," Research Highlights in the Demography and Economics of Aging, Issue No. 2, June 1998.

Unused productive capacity (55-65), in percent

Tax force to retire (55-69)

0

10

20

30

40

50

60

70

80

109876543210

United States

Japan

Canada

Sweden

Spain

France

Germany

Netherlands

Belgium

Italy

United Kingdom

Public pensions have become thefinancial lifeline of the elderly inmany societies. While someEuropean public pension systemsdate back to the end of the nine-teenth century, current systems arethe result of changes institutedlargely after World War II. The mostobvious and, to governments, mostworrisome consequence of project-ed population aging will be anincrease in budgetary outlays in theform of old-age pension payments,especially in those countries inwhich public pensions are predomi-nately financed on a pay-as-you-gobasis. Increases in migration alsoare prompting governmental con-cern about the “exporting” of cashbenefits to retirees in other coun-tries (Bolderson and Gains, 1994).Many nations, both developed anddeveloping, are now reconsideringtheir existing old-age security sys-tems, often with an eye towardintroducing or strengthening privatepension schemes.

DEMOGRAPHIC CHANGEALONE MAY DOUBLERETIREE/WORKER RATIO

The potential effect of demographicchange on future retired popula-tion/worker ratios, holding otherfactors constant, may be approxi-mated in various ways. The mostcommonly used indicator, as dis-cussed in Chapter 8, is an elderlysupport ratio which contrasts onepopulation segment (people aged65 and over) to another (peopleaged 20 to 64). One variation onthis theme, shown in Figure 11-1for 10 developed countries, allowsfor national differences in average

retirement age. This example isbased on average ages of retire-ment for employees in 1995 esti-mated by the Organization forEconomic Co-Operation andDevelopment (OECD) and popula-tion age/sex structures for 2000and 2030 estimated and projectedby the U.S. Census Bureau. Thenumerator of the ratio comprises allpeople at or over the average ageof retirement in each country, andthe denominator all people betweenthe age of 20 and the averageretirement age, assuming nochange in the average age of retire-ment between 2000 and 2030. Theratio increases notably over time inall cases, and more than doublesfor men in the Netherlands.

PUBLIC OLD-AGE SECURITYSYSTEMS PROLIFERATING

Since the Second World War, publicpension plans have played anincreasingly important role in pro-viding retirement income to olderpeople. Old-age pension schemeshave become social institutions inmany if not most countries through-out the world. The goal of mostpublic old-age pension schemes isto provide all qualifying individualswith an income stream during theirlater years, income which is: 1)continuous; 2) adequate; 3) con-stant, in terms of purchasingpower; and 4) capable of maintain-ing the socioeconomic position ofthe retired in relation to that of theactive population (Nektarios, 1982).

The major impetus for developmentof public pension systems, particu-larly in industrialized countries, wasthe inability of private intergenera-

tional transfers to provide adequateretirement income for older citi-zens. The number of countrieswith an old age/disability/survivorsprogram increased from 33 in 1940to 167 in 1999 (Figure 11-2). TheWorld Bank (1994) has estimatedthat formal public programs providecoverage for approximately 30 per-cent of the world’s older (aged 60and over) population, with some 40percent of the world’s working-agepopulation making contributionstoward that support.

LABOR FORCE PENSIONCOVERAGE VARIES FROMUNIVERSAL TO NIL

Mandatory old-age pension plansnow cover more than 90 percent ofthe labor force in most developedcountries. Governments are respon-sible for mandating, financing, man-aging, and insuring public pensions.Public pension plans usually offerdefined benefits that are not tied toindividual contributions, but rather,are financed by payroll taxes. Thisarrangement is commonly referredto as a “pay-as-you-go” system inso-far as current revenues (taxes onworking adults) are used to financethe pension payments of peoplewho are retired from the labor force(Mortensen, 1992).

Most pay-as-you-go systems inindustrialized countries initiallypromised generous benefits.These pension programs, at theirinception, were based on a smallnumber of pensioners relative to alarge number of contributors(workers). As systems matured,ratios of pensioners to contributorsgrew and in some countries


CHAPTER 11.

Pensions and Income Security

became unsustainable, particularlyduring periods of economic stag-nation. One result of suchchanges was the development ofprivate pension systems to com-plement public pension systems(Fox, 1994). Other measures takenor considered have includedincreasing worker contributionrates, restructuring or reducingbenefits, and raising the standardage of retirement (ISSA, 1993;Holtzmann and Stiglitz, 2001).

In developing countries, public pen-sion systems typically cover a muchsmaller fraction of workers than inindustrialized nations (Figure 11-3).Even economically vibrant societiessuch as Hong Kong and Thailandoffer no publicly supported, compre-hensive retirement pension scheme(Bartlett and Phillips, 1995;Domingo, 1995). In many cases,coverage in developing countries isrestricted to certain categories ofworkers such as civil servants, mili-tary personnel, and employees inthe formal economic sector. Rural,predominantly agricultural workershave little or no pension coverage inmuch of the developing world,although some governments havetaken steps to address this situa-tion. Each state in India, for exam-ple, has implemented an old agepension scheme for destitute peoplewith no source of income and nofamily support (Kumar, 1998). Whilepension amounts are minimal andcoverage far from universal, the for-mal institution of such a systemaffords a nation a foundation uponwhich to expand future coverage.


Figure 11-1.

Ratio of Retirement-Age to Working-Age Population in Ten Countries: 2000 and 2030

Note: Ratios represent the number of persons at or above average retirement age per 100 persons between age 20 and the average retirement age in 1995. Each national average is shown in parentheses. Sources: OECD, 1998 (Aging Working Paper 1.4) and U.S. Census Bureau, 2000a.

United States (63.6)

United Kingdom (62.7)

Spain (61.4)

Netherlands (58.8)

Japan (66.5)

Italy (60.6)

France (59.2)

Finland (59.0)

Denmark (62.7)

Australia (61.8)

United States (61.6)

United Kingdom (59.7)

Spain (58.9)

Netherlands (55.3)

Japan (63.7)

Italy (57.2)

France (58.3)

Finland (58.9)

Denmark (59.4)

Australia (57.2)

(Average retirement age shown in parentheses)

20002030

37

52

23

43

24

44

40

75

34

57

35

63

21

41

30

63

30

54

26

45

20

40

72

42

69

46

81

48

80

58

105

3565

50

96

46

85

44

71

31

Male

Female

Informal (usually family) systemsprovide the bulk of social supportfor older individuals in many coun-tries, particularly in Africa andSouth Asia. As economies expandand nations urbanize, informal sup-port systems such as extended fam-ily care and mutual aid societieshave tended to weaken. A majorchallenge for governments in devel-oping nations is to effect the expan-sion of formal-system coverage(especially in rural areas) whilemaintaining support for extantinformal mechanisms.

HOW GENEROUS ARE PUBLICPENSIONS?

The “value” of pensions can be con-strued and measured in differentways, depending on how many andwhich people in a given householdrely on pension income, the taxablestatus of such income, the type ofjob a retiree was engaged in, thelevel of pension income in a givensociety vis-a-vis other benefits suchas universal health care, and soforth. The concept of “replacementrate” is often used as a measure ofhow much of a person’s pre-retirement income is supplied byher/his pension. MacKellar andMcGreevey (1999) note that, inindustrialized countries, the aver-age pension rose from 14 percentof the average wage in 1930 to 55percent in 1980. A comparison ofgross income replacement of socialsecurity and other compulsoryretirement pension programs in 12 European nations circa 1990(International Benefits Information


Figure 11-2.

Number of Countries With Public Old-Age/Disability/Survivors Program: 1940 to 1999

Source: U.S. Social Security Administration, 1999.

33

44

58

97

123

135

167

1999198919791969195819491940

Figure 11-3.

Percent of Labor Force Covered by Public Old-Age Pension Program: Circa 1995

Source: World Bank, 1998.

Italy

Germany

Russia

Poland

Brazil

Jordan

South Korea

Morocco

Zambia

Nigeria

96

1

10

21

30

40

50

66

72

94

Service, 1993) revealed that replace-ment rates ranged from 46 percentto 102 percent, based on averageannual pay for a manufacturingworker with dependent spouse.

For reasons mentioned above, thereis no single replacement rate in anynational retirement program, andcross-national comparisons there-fore are difficult. For comparativepurposes, however, the OECD hasconstructed, for 1995, a syntheticindicator of the expected grossreplacement rate (as a percent ofearnings) for a 55-year-old individ-ual who retires at the standard ageof entitlement to a public pension.This indicator takes account of twoearnings levels (average and two-thirds of average) and two types ofhouseholds (single earner andworker with a dependent spouse).Pensions in some countries can beexpected to replace a large percent-age of earnings, and even to matchor exceed the latter in Greece andSpain. At the other end of the spec-trum are Australia and Ireland,where the public-pension replace-ment rates are on the order of 40 percent. For the majority ofcountries examined, the expectedreplacement rates are about one-half to two-thirds of pre-retirementincome (Figure 11-4).


Figure 11-4.

Expected Old-Age Public Pension Replacement Rate in 26 Countries: 1995

Note: Synthetic indicator based on different earning levels and household types; see text and source for more detail. Source: OECD, 1998 (Aging Working Paper 1.4).

(Percent)

United States

United Kingdom

Switzerland

Sweden

Spain

Portugal

Poland

Norway

New Zealand

Netherlands

Luxembourg

Japan

Italy

Ireland

Iceland

Hungary

Greece

Germany

France

Finland

Denmark

Czech Republic

Canada

Belgium

Austria

Australia

56

41

80

68

52

53

56

60

65

55

120

5593

40

80

5293

46

61

6054

83

100

74

49

50

PUBLIC PENSIONS ABSORBONE-SEVENTH OF GDP IN SOMECOUNTRIES

The cost of public pensions general-ly is greatest among industrialnations, most of which have pay-as-you-go systems. Pension expendi-ture had, on average, come toexceed 9 percent of gross domesticproduct (GDP) in OECD nations inthe early 1990s, and represented 8percent of GDP in Eastern Europe.Between 1960 and 1990, one-quarter of the increase in total pub-lic expenditure in OECD countrieswas growth in pension expenditure;on average, the latter grew twice asfast as did GDP. By 1996, publicpension spending in Italy andUruguay had reached 15 percent ofGDP (Palacios and Pallares-Miralles,2000). Expenditure levels typicallyare much lower in most developingcountries (Figure 11-5), where rela-tively younger populations andsmaller pension programs do notyet place large demands on GDP.

ADMINISTRATIVE COSTS OFPUBLIC PENSION SYSTEMSHIGH IN SOME DEVELOPINGCOUNTRIES

The cost of administering a publicpension scheme is an important fac-tor in the scheme’s overall efficacy.In many developing countries,administrative costs as a percent oftotal old-age benefits have beenhigh (e.g., 10-15 percent in Braziland Turkey) relative to the devel-oped world — administrative costsas a percent of old-age benefits areless than 2 percent in most OECDcountries. In many developedcountries, the cost/benefit ratiodeclined in the 1970s and early


Figure 11-5.

Public Pension Expenditure as a Percent of Gross Domestic Product in 25 Countries: Circa 1996

Source: Palacios and Pallares-Miralles, 2000.

Cote d'Ivoire, 1997Mexico, 1996

Togo, 1997Uganda, 1997Ecuador, 1997Vietnam, 1998Algeria, 1997

Sri Lanka, 1996China, 1996

Turkey, 1995Australia, 1995

Brazil, 1996Kazakhstan, 1997

Russia, 1996Israel, 1996

Cyprus, 1996Japan, 1995

United States, 1995Hungary, 1996

United Kingdom, 1995Croatia, 1997

Germany, 1995France, 1995

Uruguay, 1996Italy, 1995

0.3

15.015.0

13.312.0

11.610.2

9.77.2

6.66.4

5.95.7

5.04.74.6

3.72.7

2.42.1

1.61.0

0.80.6

0.4

Figure 11-6.

Net Administrative Fees as a Percent of Total Contributions in Eight Latin American Individual-Account Systems: 1999

Source: James, Smalhout and Vittas, 2001.

Bolivia

Colombia

Uruguay

Chile

El Salvador

Peru

Mexico

Argentina

5.5

23.0

22.1

19.0

17.6

15.6

14.3

14.1

1980s (Estrin, 1988) as a result of:1) government austerity programsthat helped contain administrativecosts; 2) increases in total benefitexpenditures, reflecting not onlythe maturation and/or expansion ofprograms but also the impact ofinflation; and 3) greater use of com-puters for the processing of bene-fits, with corresponding gains inefficiency.

The World Bank (1994) compiledinformation on administrative costsper participant in publicly managedpension plans as a percent of percapita income in the early 1990s,demonstrating that such costs wereconsiderably higher in lower-incomecountries. For example, costs perparticipant as a percent of nationalper capita income were 8 percent inTanzania, 7 percent in Burundi, and2.3 percent in Chile, compared withone-tenth of 1 percent or less inSwitzerland and the United States.These data illustrate the importanceof an educated labor force, commu-nications infrastructure, and otheradvanced technological input to thepension production function. Morerecently, James, Smalhout, andVittas (2001) estimated the netadministrative fee in individualaccount systems as a percent of aperson’s total contribution in eightLatin American countries (Figure 11-6). These fees were in double dig-its in seven of the eight nations asof 1999, and exceeded 20 percentin Argentina and Mexico.

ROUGHLY ONE-THIRD OF OECD WORKERS COVERED BYOCCUPATIONAL PENSION PLANS

While public pension systems aremore widespread than occupationalpension plans, the latter are grow-ing in coverage. Occupationalpension plans tend to be a moreimportant source of retirementincome than public pensions for

high income workers in developedcountries. About one-third of thelabor force in OECD countries wasenrolled in occupational pensionplans circa 1990, but a muchsmaller proportion is covered inmost developing countries and tran-sitional economies, where employ-er-sponsored schemes tend to coveronly public-sector workers (WorldBank, 1994).

Cross-national estimates of occupa-tional-scheme coverage among allworkers vary widely in the pub-lished literature, due in part to dif-ferent temporal references as wellas different definitions of what anoccupational scheme is.1 Mostoccupational plans are employer-specific, but in some nations (e.g.,Denmark and the Netherlands)plans are organized on an industry-wide basis, with compulsory partici-pation a result of collective bargain-ing. Switzerland requires all

employers to provide pension bene-fits for employees above a certainincome level. OECD estimates forthe early 1990s, compiled from var-ious sources, show occupationalscheme coverage in 19 industrial-ized countries ranging from 5 per-cent in Italy and Greece to 90 per-cent in Sweden and the Netherlands(OECD, 1998, Ageing Working Paper2.2).

Of course, not all workers who arecovered by occupational plans arein fact enrolled in them. Further,the percent of older people actuallyreceiving benefits from employer-provided plans is likely to be lowerstill, because many retirees eitherdid not have access to such plansduring their working years, or didnot participate for enough years tobecome vested. Whitehouse (2000)has compiled data on the percent-age of pensioners with income fromemployer-provided pensions ineight developed countries in thelate 1990s (Figure 11-7). In coun-tries where a gender breakdown is


Figure 11-7.

Percent of Pensioners With Income From Employer-Provided Pensions: Late 1990s

Source: Whitehouse, 2000.

United States

United Kingdom

Netherlands

Germany

Canada

Australia

MaleFemale

26

20

7

5431

21

9

7623

66

32

48

1 For a useful discussion of occupationalpension schemes within the context of broaderretirement system reforms, see OECD, 1998,Ageing Working Paper 3.4.


Chile first enacted a public pension scheme in 1911,and expanded its program following the Europeansocial insurance model financed on a pay-as-you-gobasis. Between 1960 and 1980, the ratio of pension-ers to contributing workers increased from 9 per 100to 45 per 100, due to rapidly changing demographicsand increasing tax evasion on the part of employeesand employers (Williamson, 1992). These changes,occurring in the context of a stagnant economy,resulted in a situation where the pension system wasno longer able to meet current obligations. Facedwith an increasingly bleak future scenario, the Chileangovernment in 1980 abandoned its public system infavor of a compulsory savings plan administered byprivate-sector companies.

Since 1981, all wage and salary earners are required tocontribute 10 percent of their earnings to a privately

administered retirement fund (additional payrolldeductions are made for life insurance and fundexpenses). Workers themselves select from manycompeting investment companies, are free to switchtheir accounts, and have several options for with-drawal and annuities upon retirement. To reduce mis-management risks, the government assumes a majorsupervisory and regulatory role (Schulz, 1993).

By most accounts, the Chilean experiment during itsinitial decade was a success, with real annual returnson contributions averaging in excess of 12 percentduring the 1980s. From 1995 to 1998, however,annual rates of return were much lower and in 2 years were negative, before rebounding in 1999(Figure 11-8). Overall, the long-term (19-year) aver-age real return exceeds 11 percent. Observers havepointed out several drawbacks to the system, such as

high administrative costs,workers’ loss of freedom vis-a-vis one-tenth of their earn-ings, and the fact that even-tual income replacementrates are not guaranteed, i.e.,are reliant on investmentearnings that may suffer intimes of economic stagnation(Gillion and Bonilla, 1992).Nevertheless, many countriesin Latin America, EasternEurope, and Asia have adopt-ed or are seriously consider-ing aspects of the Chileansystem, or are experimentingwith variations on the theme(Kritzer, 2000; Fox andPalmer, 2001). Considerationof increased privatization ofsocial security systems isnow commonplace in muchof the developed world aswell, and has become a hotlydebated political topic.

Figure 11-8.

Real Rate of Return of Chile's Private Pension System: 1981 to 1999

Source: Reported in Palacios and Pallares-Miralles, 2000.

-5

0

5

10

15

20

25

30

1999199719951993199119891987198519831981

Percent

Average, 1981-1999:11.2%

Box 11-1.Chile is the Developing-Country Model for Pension Privatization

available, the data show that menare much more likely to receivesuch benefits, as would be expect-ed from past gender patterns oflabor force participation.

Company-based pension programsin the developing world are foundmost frequently in former Britishcolonies and in countries with largemultinational subsidiaries. Mostsuch programs are subject to lessregulation and lower fundingrequirements than their counter-parts in industrialized countries,although both Indonesia and SouthAfrica have developed comprehen-sive and well-regulated private pen-sion systems. Coverage of private-sector workers is increasing in anumber of other large developingnations such as Brazil, India, andMexico (World Bank, 1994).

PRIVATE PENSION FUNDASSETS A MAJOR SOURCE OFLONG-TERM CAPITAL

Private pension fund assets aresizeable in many developed coun-tries. In 1998, such assets wereequivalent to more than 80 percentof GDP in the Netherlands, theUnited Kingdom, and the UnitedStates (Figure 11-9). Most occupa-tional-plan funds have been invest-ed in private-sector assets, areinternationally diversified, and haveearned higher returns than publiclymanaged funds (Davis, 1993;1998).

These funds have grown consider-ably over the last three decades.The average annual growth rate ofpension funds for OECD countriesas a whole between 1990 and 1996was 11 percent (OECD, 1998b).


Figure 11-9.

Private Pension Fund Assets as a Percent of GDP: 1970 and 1998

Note: Later Swiss figure refers to 1996. Sources: World Bank, 1994 and OECD, 2000.

United States

United Kingdom

Switzerland

Netherlands

Denmark

Canada

19701998

86

14

48

19

22

29

86

38

75

2184

29

Table 11-1.Payroll Tax Rates for Provident Fund Schemes:Early-to-Mid-1990s(Percentage of wages)

Country Employees Employer

AfricaThe Gambia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 10Ghana. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 12.5Kenya . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 5Nigeria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 6Swaziland . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 5Tanzania. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 10Uganda. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 10Zambia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 5

AsiaFiji . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 7India . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 10Indonesia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 2Kiribati . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 5Malaysia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 11Nepal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 10Singapore . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-30 10Solomon Island. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 8Sri Lanka . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 12Western Samoa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 5

Latin AmericaArgentina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 0Chile . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 0Colombia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 9Peru . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 0

Source: World Bank, 1994.

This increase is expected to contin-ue for at least the short term,because many aging nations withrelatively underdeveloped pre-funded systems have considerableroom for growth. The looming poli-cy question is whether populationaging will depress rates of returnon private pension funds. As thelarge post-World War II cohortsmove into retirement, they areexpected to divest some of theirfinancial assets accumulated duringtheir working years. This prospecthighlights the importance of thenature of pension fund manage-ment, changes in government regu-lations, and the varying sociocultu-ral impetuses for retirement savings(OECD, 2000; National ResearchCouncil, 2001).

PROVIDENT FUNDSPARAMOUNT IN SOMEDEVELOPING COUNTRIES

A provident fund is a form of com-pulsory defined-contribution pro-gram wherein regular contributionsare withheld from employee wagesand invested for later repayment.Payouts typically are in the form ofa lump sum upon retirement, butmay also be made earlier in timesof special need. Except in someLatin American countries, employ-ers match or exceed the employeecontribution. Although providentfunds can cover private-sectorworkers, they are managed publicly.

Malaysia, in 1951, was the firstnation to establish a wide scaleprovident fund, and other Asiannations (e.g., India, Singapore, andSri Lanka) have had provident fundsfor more than 40 years. By themid-1990s more than 20 nationshad developed such schemes (Table11-1). None of these countries hada public pay-as-you-go system atthe time its provident fund wasestablished (World Bank, 1994).

Where provident-fund coverage isextensive, such funds may in effectbe the public pension system.

The performance of provident fundsglobally has been erratic. In someEast Asian countries (notablySingapore, which has the world’slargest provident fund), funds typi-cally have earned positive annualinvestment returns. In othernations, inflation and poor econom-ic growth have lessened the valueof fund contributions; in Sri Lanka,for example, the real annual rate ofreturn for the Employee ProvidentFund in the 1980s and early 1990soften was negative (InternationalLabour Office, 1993). Such perform-ance has led several countries toabandon provident schemes infavor of defined-benefit pensionplans (Palacios and Pallares-Miralles,2000).

ARE LIVING STANDARDS OFTHE ELDERLY CHANGING INDEVELOPED COUNTRIES?

Given the maturation of public pen-sions systems, increases in the levelof female labor force participation,and the development of privatepension schemes, one might expectthat older citizens in industrializednations are better off, economically,than previous generations of elderlypeople. And, there is a growingperception in some countries thatthe elderly as a whole are faringbetter than other population sub-groups. However, the complexity ofmeasuring economic well-beingoften precludes a definitive assess-ment of these issues, and there isconsiderable concern about the will-ingness and ability of households toadequately save for retirementneeds (see, e.g., MacKellar, 2000).One study of 12 European Unioncountries in the late 1980s com-pared survey data on consumptionexpenditure, income, and

nonmonetary indicators of welfare,and concluded that in all 12nations, the nonelderly were betteroff than the elderly (Tsakloglou,1996). Data for France, however,suggest that extreme poverty(below the level of guaranteed mini-mum income) is much less commonamong the elderly than amongyounger households (David andStarzec, 1993).

The OECD (2000) has concludedthat there has been a stable orimproving economic picture forolder people, both in absoluteterms and relative to the nonelderlypopulation. Poverty rates for olderpeople have declined in mostnations, as has the share of olderpeople among the poor. In theUnited States, the overall situationof elderly people improved dramati-cally during the last third of thetwentieth century. Studies of realmedian household income (adjustedfor household size) have demon-strated much larger gains for elder-ly people relative to the generalpopulation (Radner, 1995; McNeil,1998). And, poverty among theelderly has declined. One-third ofall U.S. elderly were below thepoverty line in 1960; by the mid-1990s, the level had declined to 10 percent, lower than among chil-dren under the age of 18 (Friedlandand Summer, 1999).

Data from the Luxembourg IncomeStudy reveal considerable inter-country variation in poverty ratesamong elderly citizens. An analysisof standardized information fromnine nations (Smeeding andSaunders, 1998) suggests thatCanada, Germany, and Hungary pro-vide their elderly the best overallprotection from poverty relative tothe other six countries (Figure 11-10). This analysis also highlightsthe fact that overall figures may


mask large differences amongpopulation subgroups, as seen inthe data for elderly women livingalone. The economic vulnerabilityof single elderly women also hasbeen noted in a 14-country study ofdata from the European CommunityHousehold Panel (Heinrich, 2000).

One obviously important compo-nent of elderly living standards ishealth care and its costs. As thelatter have escalated in the 1990s, agrowing body of research hasfocused on identifying the costs ofspecific illnesses and on projectinghealth expenditures (see, e.g.,Cutler and Meara, 1999; Mayhew,1999; and OECD, 2000). Othermajor thrusts of current research inthe economics of aging seek: tomore fully and accurately measurelevels of household wealth andassets; to better assess differencesin these variables within popula-tions; and to understand transitionsin income and poverty status,particularly as they relate to chang-ing health status at older ages.Data from the European CommunityHousehold Panel Survey is begin-ning to shed light on the interplayof health status and retirement deci-sions of older European couples

(Jiminez-Martin, Labeaga, andGranado, 1999). In order to capturethe complexity of such transitionsand understand their significancefor policy planning, several nationshave mounted (or are planning toinitiate) longitudinal studies akin to

the Health and Retirement Survey inthe United States (see Burkhauserand Gertler, 1995 for a comprehen-sive overview of this study, andNational Research Council, 2001 forfuture recommendations).


Figure 11-10.

Percent of Elderly Living in Households With Less Than 50 Percent of Adjusted National Median Disposable Income

Note: Percent for elderly women living alone in Japan is not reported. Source: Smeeding and Saunders, 1998.

United States, 1994

Taiwan, 1991

Poland, 1992

Japan, 1992

Hungary, 1995

Germany, 1989

Finland, 1991

Canada, 1991

Australia, 1990

All elderlyElderly womenliving alone

43

2962

716

1635

813

914

18

N/A11

19

2574

23


APPENDIX A.

Detailed Tables

Table 1.Total Population, Percent Elderly, and Percent Oldest Old: 1975, 2000, 2015, and 2030(In thousands)

Country

1975 2000

Totalpopulation

Percent ofpopulation

65+


80+

80+ as apercent of

65+Total

population


65+


80+

80+ as apercent of

65+

United States . . . . . . . . . . . . . . . 220,165 10.5 2.1 20.4 275,563 12.6 3.3 26.5

Western EuropeAustria . . . . . . . . . . . . . . . . . . . . . . . 7,579 14.9 2.3 15.5 8,131 15.4 3.4 22.2Belgium . . . . . . . . . . . . . . . . . . . . . . 9,796 13.9 2.3 16.4 10,242 16.8 3.5 20.8Denmark . . . . . . . . . . . . . . . . . . . . . 5,060 13.4 2.4 18.0 5,336 14.9 4.0 26.7France . . . . . . . . . . . . . . . . . . . . . . . 52,699 13.5 2.5 18.3 59,330 16.0 3.7 23.3Germany . . . . . . . . . . . . . . . . . . . . . 78,679 14.8 2.2 14.6 82,797 16.2 3.5 21.6Greece. . . . . . . . . . . . . . . . . . . . . . . 9,047 12.2 2.1 17.1 10,602 17.3 3.5 20.2Italy. . . . . . . . . . . . . . . . . . . . . . . . . . 55,441 12.0 1.9 16.0 57,634 18.1 4.0 22.2Luxembourg . . . . . . . . . . . . . . . . . . 362 13.0 2.2 17.0 437 14.0 3.0 21.2Norway . . . . . . . . . . . . . . . . . . . . . . 4,007 13.7 2.5 18.2 4,481 15.2 4.4 28.6Sweden . . . . . . . . . . . . . . . . . . . . . . 8,193 15.1 2.7 17.8 8,873 17.3 5.0 29.2United Kingdom . . . . . . . . . . . . . . . 56,226 14.0 2.4 17.0 59,508 15.7 4.0 25.5

Eastern EuropeBulgaria . . . . . . . . . . . . . . . . . . . . . . 8,722 10.9 1.4 12.8 7,797 16.5 2.2 13.2Czech Republic . . . . . . . . . . . . . . . 9,997 12.9 1.7 13.5 10,272 13.9 2.4 17.1Hungary. . . . . . . . . . . . . . . . . . . . . . 10,532 12.6 1.7 13.3 10,139 14.6 2.5 17.4Poland . . . . . . . . . . . . . . . . . . . . . . . 34,022 9.5 1.2 12.4 38,646 12.3 2.1 16.8Russia . . . . . . . . . . . . . . . . . . . . . . . 134,233 8.9 1.2 14.0 146,001 12.6 2.0 15.9Ukraine . . . . . . . . . . . . . . . . . . . . . . 49,016 10.5 1.6 15.0 49,153 13.9 2.2 16.0

North America/OceaniaAustralia . . . . . . . . . . . . . . . . . . . . . 13,900 8.7 1.5 17.4 19,165 12.4 3.0 24.0Canada . . . . . . . . . . . . . . . . . . . . . . 23,209 8.4 1.6 19.3 31,278 12.7 3.1 24.8New Zealand . . . . . . . . . . . . . . . . . 3,083 8.7 1.4 16.4 3,820 11.5 2.9 25.0

AsiaBangladesh. . . . . . . . . . . . . . . . . . . 76,582 3.6 0.3 8.4 129,194 3.3 0.5 15.0China . . . . . . . . . . . . . . . . . . . . . . . . 927,808 4.4 0.6 12.5 1,261,832 7.0 0.9 13.1India . . . . . . . . . . . . . . . . . . . . . . . . . 620,701 3.8 0.3 8.1 1,014,004 4.6 0.6 13.1Indonesia. . . . . . . . . . . . . . . . . . . . . 135,666 3.2 0.3 8.6 224,784 4.5 0.4 10.0Israel . . . . . . . . . . . . . . . . . . . . . . . . 3,455 7.8 1.0 12.3 5,842 9.9 2.4 23.9Japan. . . . . . . . . . . . . . . . . . . . . . . . 111,524 7.9 1.1 13.5 126,550 17.0 3.7 21.7Malaysia . . . . . . . . . . . . . . . . . . . . . 12,258 3.7 0.5 13.3 21,793 4.1 0.5 13.5Pakistan. . . . . . . . . . . . . . . . . . . . . . 74,734 3.0 0.3 10.9 141,554 4.1 0.5 13.3Philippines. . . . . . . . . . . . . . . . . . . . 43,010 2.7 0.4 13.4 81,160 3.6 0.5 13.6Singapore . . . . . . . . . . . . . . . . . . . . 2,263 4.1 0.4 9.7 4,152 6.8 1.5 21.3South Korea . . . . . . . . . . . . . . . . . . 35,281 3.6 0.4 10.1 47,471 7.0 1.0 13.9Sri Lanka. . . . . . . . . . . . . . . . . . . . . 13,603 4.1 0.5 13.2 19,239 6.5 1.0 15.6Thailand. . . . . . . . . . . . . . . . . . . . . . 41,359 3.0 0.3 10.9 61,231 6.4 0.9 13.9Turkey . . . . . . . . . . . . . . . . . . . . . . . 40,025 4.5 0.4 7.9 65,667 6.0 0.9 15.2

Latin America/CaribbeanArgentina. . . . . . . . . . . . . . . . . . . . . 26,049 7.6 0.9 12.1 36,955 10.4 2.2 21.7Brazil . . . . . . . . . . . . . . . . . . . . . . . . 108,167 3.9 0.5 12.5 172,860 5.3 0.8 15.3Chile. . . . . . . . . . . . . . . . . . . . . . . . . 10,337 5.3 0.8 14.5 15,154 7.2 1.2 16.8Colombia . . . . . . . . . . . . . . . . . . . . . 25,381 3.6 0.4 11.8 39,686 4.7 0.6 12.2Costa Rica . . . . . . . . . . . . . . . . . . . 1,968 3.4 0.5 13.6 3,711 5.2 0.9 17.9Guatemala . . . . . . . . . . . . . . . . . . . 6,018 2.8 0.4 13.1 12,640 3.6 0.5 13.5Jamaica . . . . . . . . . . . . . . . . . . . . . . 2,013 5.8 0.8 14.5 2,653 6.8 1.5 21.6Mexico . . . . . . . . . . . . . . . . . . . . . . . 59,099 4.0 0.7 17.9 100,350 4.3 0.6 14.9Peru . . . . . . . . . . . . . . . . . . . . . . . . . 15,161 3.5 0.3 9.1 27,013 4.7 0.7 15.0Uruguay. . . . . . . . . . . . . . . . . . . . . . 2,829 9.6 1.6 16.9 3,334 12.9 2.7 21.2

AfricaEgypt . . . . . . . . . . . . . . . . . . . . . . . . 38,841 4.2 0.4 9.7 68,360 3.8 0.4 10.2Kenya. . . . . . . . . . . . . . . . . . . . . . . . 13,741 3.7 0.5 12.8 30,340 2.7 0.4 13.0Liberia . . . . . . . . . . . . . . . . . . . . . . . 1,609 3.7 0.9 23.3 3,164 3.4 0.6 16.8Malawi . . . . . . . . . . . . . . . . . . . . . . . 5,244 2.2 0.2 8.0 10,386 2.8 0.3 9.9Morocco. . . . . . . . . . . . . . . . . . . . . . 17,305 3.7 0.5 14.2 30,122 4.6 0.7 14.2Tunisia . . . . . . . . . . . . . . . . . . . . . . . 5,668 3.5 0.5 13.1 9,593 6.0 0.8 13.3Zimbabwe . . . . . . . . . . . . . . . . . . . . 6,143 2.6 0.3 9.9 11,343 3.5 0.5 14.7


Table 1.Total Population, Percent Elderly, and Percent Oldest Old: 1975, 2000, 2015, and2030—Con.(In thousands)

Country

2015 2030

Totalpopulation


65+


80+

80+ as apercent of

65+Total

population


65+


80+

80+ as apercent of

65+

United States . . . . . . . . . . . . . . . . . . . 312,524 14.7 3.8 25.8 351,326 20.0 5.3 26.4

Western EuropeAustria . . . . . . . . . . . . . . . . . . . . . . . . . . . 8,316 18.8 4.9 26.2 8,278 25.2 7.0 27.9Belgium . . . . . . . . . . . . . . . . . . . . . . . . . . 10,336 19.4 5.7 29.3 10,175 25.4 7.3 28.8Denmark . . . . . . . . . . . . . . . . . . . . . . . . . 5,521 18.9 4.4 23.6 5,649 23.0 7.1 30.8France . . . . . . . . . . . . . . . . . . . . . . . . . . . 61,545 18.8 5.8 30.9 61,926 24.0 7.5 31.2Germany . . . . . . . . . . . . . . . . . . . . . . . . . 85,192 20.2 5.4 26.6 84,939 25.8 7.2 28.1Greece . . . . . . . . . . . . . . . . . . . . . . . . . . . 10,735 20.6 6.3 30.5 10,316 25.4 7.8 30.8Italy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56,631 22.2 6.8 30.5 52,868 28.1 9.0 32.1Luxembourg . . . . . . . . . . . . . . . . . . . . . . 519 15.3 4.1 27.1 580 19.8 5.2 26.2Norway . . . . . . . . . . . . . . . . . . . . . . . . . . . 4,767 17.4 4.6 26.3 5,018 22.0 6.6 30.0Sweden . . . . . . . . . . . . . . . . . . . . . . . . . . 8,900 21.4 5.7 26.8 8,868 25.1 8.6 34.3United Kingdom . . . . . . . . . . . . . . . . . . . 61,047 18.4 4.9 26.8 61,481 23.5 7.0 29.7

Eastern EuropeBulgaria . . . . . . . . . . . . . . . . . . . . . . . . . . 6,663 20.2 4.6 23.0 5,668 25.9 7.2 27.8Czech Republic . . . . . . . . . . . . . . . . . . . 10,048 18.8 4.2 22.3 9,409 24.7 7.4 30.0Hungary . . . . . . . . . . . . . . . . . . . . . . . . . . 9,666 17.6 4.3 24.2 9,034 22.5 6.3 27.9Poland . . . . . . . . . . . . . . . . . . . . . . . . . . . 38,668 15.0 3.8 25.1 37,377 22.2 5.5 24.8Russia . . . . . . . . . . . . . . . . . . . . . . . . . . . 141,073 13.8 3.1 22.7 132,859 20.5 4.1 20.0Ukraine. . . . . . . . . . . . . . . . . . . . . . . . . . . 45,294 15.0 3.2 21.1 42,273 19.7 4.2 21.5

North America/OceaniaAustralia . . . . . . . . . . . . . . . . . . . . . . . . . . 21,697 15.8 4.1 25.9 23,497 21.1 6.0 28.5Canada. . . . . . . . . . . . . . . . . . . . . . . . . . . 35,653 16.1 4.3 26.8 39,128 22.9 6.2 26.9New Zealand. . . . . . . . . . . . . . . . . . . . . . 4,396 13.7 3.5 25.7 4,768 17.8 5.0 28.2

AsiaBangladesh . . . . . . . . . . . . . . . . . . . . . . . 160,486 4.4 0.6 12.5 184,478 7.2 1.0 13.5China . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,397,414 9.5 1.7 18.0 1,483,121 16.0 2.9 18.3India . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,241,572 5.9 0.9 14.5 1,437,103 9.0 1.4 15.7Indonesia . . . . . . . . . . . . . . . . . . . . . . . . . 275,152 6.2 1.1 16.9 312,592 10.9 1.7 15.6Israel. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6,992 11.1 3.0 26.6 7,873 14.9 3.9 26.5Japan . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125,843 24.9 7.0 28.2 116,740 28.3 11.1 39.3Malaysia. . . . . . . . . . . . . . . . . . . . . . . . . . 28,414 5.9 0.8 14.3 35,306 9.4 1.6 16.9Pakistan . . . . . . . . . . . . . . . . . . . . . . . . . . 185,715 4.5 0.7 15.0 226,251 6.5 0.9 14.4Philippines . . . . . . . . . . . . . . . . . . . . . . . . 106,098 4.9 0.7 14.6 129,448 7.7 1.2 15.9Singapore . . . . . . . . . . . . . . . . . . . . . . . . 6,646 8.7 2.1 24.1 9,047 14.8 3.0 20.4South Korea . . . . . . . . . . . . . . . . . . . . . . 52,239 11.3 2.2 19.3 53,763 19.5 4.2 21.3Sri Lanka . . . . . . . . . . . . . . . . . . . . . . . . . 21,527 9.5 1.7 17.7 22,937 15.2 3.1 20.2Thailand . . . . . . . . . . . . . . . . . . . . . . . . . . 68,139 9.8 1.8 18.0 71,311 16.4 3.1 19.3Turkey. . . . . . . . . . . . . . . . . . . . . . . . . . . . 76,685 7.9 1.6 19.9 84,195 12.9 2.4 18.7

Latin America/CaribbeanArgentina . . . . . . . . . . . . . . . . . . . . . . . . . 42,916 11.8 3.1 26.0 47,229 14.7 4.0 27.3Brazil. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 192,313 8.1 1.5 18.7 203,489 13.2 2.7 20.6Chile . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17,405 10.7 2.1 19.3 18,915 16.4 3.7 22.3Colombia . . . . . . . . . . . . . . . . . . . . . . . . . 49,189 6.5 1.0 15.6 57,666 11.5 1.8 15.9Costa Rica. . . . . . . . . . . . . . . . . . . . . . . . 4,583 7.3 1.4 19.2 5,272 12.8 2.4 18.9Guatemala . . . . . . . . . . . . . . . . . . . . . . . . 18,105 4.1 0.7 17.8 24,038 5.6 1.0 17.6Jamaica . . . . . . . . . . . . . . . . . . . . . . . . . . 2,992 7.4 1.8 24.1 3,353 12.5 2.3 18.7Mexico . . . . . . . . . . . . . . . . . . . . . . . . . . . 121,712 6.3 1.0 16.6 139,125 10.2 1.9 18.7Peru . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33,551 6.4 1.2 18.3 39,253 9.9 1.9 19.0Uruguay . . . . . . . . . . . . . . . . . . . . . . . . . . 3,730 13.5 3.8 28.2 4,109 15.5 4.4 28.1

AfricaEgypt . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85,219 5.1 0.6 11.9 99,583 8.0 1.1 14.2Kenya . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33,612 3.8 0.6 16.6 34,836 5.2 1.1 20.7Liberia. . . . . . . . . . . . . . . . . . . . . . . . . . . . 4,655 4.0 0.8 21.1 6,745 4.2 1.0 24.9Malawi . . . . . . . . . . . . . . . . . . . . . . . . . . . 12,017 3.1 0.4 12.7 12,817 3.2 0.6 17.5Morocco . . . . . . . . . . . . . . . . . . . . . . . . . . 37,832 5.5 1.0 17.4 44,664 9.1 1.4 15.2Tunisia . . . . . . . . . . . . . . . . . . . . . . . . . . . 11,174 7.6 1.5 19.8 12,322 12.7 2.3 17.7Zimbabwe . . . . . . . . . . . . . . . . . . . . . . . . 10,548 5.0 1.0 20.2 9,086 6.4 1.8 27.7

Source: United Nations, 1999 and U.S. Census Bureau, 2000a.

127An Aging World: 2001U.S. Census Bureau

Table 2.Population by Age: 2000 and 2030(In thousands)

Country

2000

All ages0 to 24

years25 to 54

years55 to 64

years65 to 69

years70 to 74

years75 to 79

years80 yearsand over

United States . . . . . . . . . . . . . . . 275,563 97,064 119,662 24,001 9,436 8,753 7,422 9,225

Western EuropeAustria . . . . . . . . . . . . . . . . . . . . . . . 8,131 2,325 3,629 926 347 332 294 278Belgium . . . . . . . . . . . . . . . . . . . . . . 10,242 3,033 4,432 1,052 521 462 383 358Denmark . . . . . . . . . . . . . . . . . . . . . 5,336 1,594 2,340 610 219 194 167 212France . . . . . . . . . . . . . . . . . . . . . . . 59,330 18,852 25,513 5,471 2,711 2,466 2,100 2,216Germany . . . . . . . . . . . . . . . . . . . . . 82,797 22,309 36,224 10,813 4,104 3,592 2,846 2,911Greece. . . . . . . . . . . . . . . . . . . . . . . 10,602 3,088 4,480 1,195 605 521 341 371Italy. . . . . . . . . . . . . . . . . . . . . . . . . . 57,634 14,873 25,640 6,696 3,093 2,766 2,253 2,313Luxembourg . . . . . . . . . . . . . . . . . . 437 133 199 44 19 17 12 13Norway . . . . . . . . . . . . . . . . . . . . . . 4,481 1,435 1,937 426 167 164 156 196Sweden . . . . . . . . . . . . . . . . . . . . . . 8,873 2,655 3,674 1,010 380 363 343 447United Kingdom . . . . . . . . . . . . . . . 59,508 18,549 25,496 6,138 2,585 2,347 2,018 2,373

Eastern EuropeBulgaria . . . . . . . . . . . . . . . . . . . . . . 7,797 2,354 3,255 902 453 382 282 169Czech Republic . . . . . . . . . . . . . . . 10,272 3,250 4,505 1,093 448 409 323 244Hungary. . . . . . . . . . . . . . . . . . . . . . 10,139 3,207 4,336 1,113 479 420 326 257Poland . . . . . . . . . . . . . . . . . . . . . . . 38,646 13,915 16,676 3,319 1,616 1,372 953 794Russia . . . . . . . . . . . . . . . . . . . . . . . 146,001 49,232 64,197 14,160 5,996 6,182 3,299 2,936Ukraine . . . . . . . . . . . . . . . . . . . . . . 49,153 16,052 20,607 5,647 2,080 2,294 1,377 1,096

North America/OceaniaAustralia . . . . . . . . . . . . . . . . . . . . . 19,165 6,629 8,427 1,727 668 633 509 573Canada . . . . . . . . . . . . . . . . . . . . . . 31,278 10,154 14,322 2,838 1,147 1,012 822 984New Zealand . . . . . . . . . . . . . . . . . 3,820 1,417 1,637 324 124 116 91 110

AsiaBangladesh. . . . . . . . . . . . . . . . . . . 129,194 76,298 42,947 5,645 1,744 1,206 710 643China . . . . . . . . . . . . . . . . . . . . . . . . 1,261,832 515,155 572,082 86,822 34,926 25,426 15,908 11,513India . . . . . . . . . . . . . . . . . . . . . . . . . 1,014,004 536,947 373,956 56,037 18,477 13,785 8,627 6,175Indonesia. . . . . . . . . . . . . . . . . . . . . 224,784 113,419 88,231 13,080 4,616 2,872 1,559 1,006Israel . . . . . . . . . . . . . . . . . . . . . . . . 5,842 2,617 2,257 391 168 152 120 138Japan. . . . . . . . . . . . . . . . . . . . . . . . 126,550 34,782 53,858 16,385 7,031 5,812 4,012 4,670Malaysia . . . . . . . . . . . . . . . . . . . . . 21,793 11,583 8,175 1,152 353 260 151 119Pakistan. . . . . . . . . . . . . . . . . . . . . . 141,554 86,109 43,165 6,485 2,317 1,637 1,071 770Philippines. . . . . . . . . . . . . . . . . . . . 81,160 46,410 28,087 3,717 1,220 820 504 401Singapore . . . . . . . . . . . . . . . . . . . . 4,152 1,333 2,281 253 98 76 49 61South Korea . . . . . . . . . . . . . . . . . . 47,471 18,091 22,191 3,875 1,365 895 594 460Sri Lanka. . . . . . . . . . . . . . . . . . . . . 19,239 8,759 7,933 1,295 455 358 244 195Thailand. . . . . . . . . . . . . . . . . . . . . . 61,231 25,879 27,045 4,386 1,591 1,086 699 545Turkey . . . . . . . . . . . . . . . . . . . . . . . 65,667 32,182 25,619 3,935 1,514 1,099 721 597

Latin America/CaribbeanArgentina. . . . . . . . . . . . . . . . . . . . . 36,955 16,326 13,856 2,946 1,209 1,026 761 831Brazil . . . . . . . . . . . . . . . . . . . . . . . . 172,860 84,691 68,842 10,136 3,501 2,594 1,693 1,403Chile. . . . . . . . . . . . . . . . . . . . . . . . . 15,154 6,733 6,194 1,133 391 310 210 184Colombia . . . . . . . . . . . . . . . . . . . . . 39,686 19,897 15,867 2,071 742 546 338 225Costa Rica . . . . . . . . . . . . . . . . . . . 3,711 1,888 1,438 193 70 53 35 34Guatemala . . . . . . . . . . . . . . . . . . . 12,640 7,922 3,765 496 184 132 79 62Jamaica . . . . . . . . . . . . . . . . . . . . . . 2,653 1,312 1,027 135 56 48 36 39Mexico . . . . . . . . . . . . . . . . . . . . . . . 100,350 54,699 36,241 5,092 1,722 1,197 757 642Peru . . . . . . . . . . . . . . . . . . . . . . . . . 27,013 14,735 9,606 1,409 500 351 223 189Uruguay. . . . . . . . . . . . . . . . . . . . . . 3,334 1,348 1,257 298 138 118 84 91

AfricaEgypt . . . . . . . . . . . . . . . . . . . . . . . . 68,360 37,706 24,572 3,509 1,162 748 401 261Kenya. . . . . . . . . . . . . . . . . . . . . . . . 30,340 20,064 8,423 1,021 340 237 146 108Liberia . . . . . . . . . . . . . . . . . . . . . . . 3,164 1,985 929 141 43 29 19 18Malawi . . . . . . . . . . . . . . . . . . . . . . . 10,386 6,955 2,757 385 126 85 49 28Morocco. . . . . . . . . . . . . . . . . . . . . . 30,122 16,826 10,472 1,434 538 393 262 197Tunisia . . . . . . . . . . . . . . . . . . . . . . . 9,593 4,834 3,638 542 223 173 106 77Zimbabwe . . . . . . . . . . . . . . . . . . . . 11,343 7,281 3,238 422 156 112 74 59


Table 2.Population by Age: 2000 and 2030—Con.(In thousands)

Country

2030

All ages0 to 24

years25 to 54

years55 to 64

years65 to 69

years70 to 74

years75 to 79


United States . . . . . . . . . . . . . . . 351,326 115,218 128,484 37,305 19,844 17,878 14,029 18,569

Western EuropeAustria . . . . . . . . . . . . . . . . . . . . . . . 8,278 1,916 3,034 1,244 636 500 367 582Belgium . . . . . . . . . . . . . . . . . . . . . . 10,175 2,553 3,683 1,357 709 628 501 744Denmark . . . . . . . . . . . . . . . . . . . . . 5,649 1,515 2,076 760 357 295 246 400France . . . . . . . . . . . . . . . . . . . . . . . 61,926 16,405 22,599 8,073 3,775 3,435 3,005 4,635Germany . . . . . . . . . . . . . . . . . . . . . 84,939 20,074 31,104 11,886 6,502 5,192 4,036 6,145Greece. . . . . . . . . . . . . . . . . . . . . . . 10,316 2,287 3,814 1,594 692 620 503 807Italy. . . . . . . . . . . . . . . . . . . . . . . . . . 52,868 10,165 18,788 9,033 4,115 3,307 2,685 4,775Luxembourg . . . . . . . . . . . . . . . . . . 580 164 229 72 35 29 22 30Norway . . . . . . . . . . . . . . . . . . . . . . 5,018 1,405 1,856 653 295 261 217 331Sweden . . . . . . . . . . . . . . . . . . . . . . 8,868 2,210 3,267 1,167 555 482 424 763United Kingdom . . . . . . . . . . . . . . . 61,481 16,077 22,663 8,296 4,215 3,336 2,598 4,296

Eastern EuropeBulgaria . . . . . . . . . . . . . . . . . . . . . . 5,668 1,096 2,240 866 381 362 315 408Czech Republic . . . . . . . . . . . . . . . 9,409 1,933 3,718 1,436 583 532 512 696Hungary. . . . . . . . . . . . . . . . . . . . . . 9,034 2,012 3,662 1,330 485 506 472 566Poland . . . . . . . . . . . . . . . . . . . . . . . 37,377 9,260 15,184 4,642 2,087 2,267 1,882 2,056Russia . . . . . . . . . . . . . . . . . . . . . . . 132,859 35,650 53,589 16,428 8,288 7,776 5,681 5,446Ukraine . . . . . . . . . . . . . . . . . . . . . . 42,273 11,383 17,099 5,479 2,553 2,292 1,683 1,783

North America/OceaniaAustralia . . . . . . . . . . . . . . . . . . . . . 23,497 6,643 8,941 2,960 1,356 1,212 975 1,410Canada . . . . . . . . . . . . . . . . . . . . . . 39,128 10,368 14,987 4,800 2,581 2,249 1,728 2,414New Zealand . . . . . . . . . . . . . . . . . 4,768 1,400 1,914 607 233 209 166 238

AsiaBangladesh. . . . . . . . . . . . . . . . . . . 184,478 71,167 84,043 16,060 5,248 3,821 2,356 1,783China . . . . . . . . . . . . . . . . . . . . . . . . 1,483,121 437,787 588,812 219,501 84,958 59,230 49,367 43,466India . . . . . . . . . . . . . . . . . . . . . . . . . 1,437,103 558,161 614,683 135,423 49,013 35,886 23,744 20,194Indonesia. . . . . . . . . . . . . . . . . . . . . 312,592 112,472 132,916 33,067 12,612 9,740 6,450 5,335Israel . . . . . . . . . . . . . . . . . . . . . . . . 7,873 2,724 3,154 825 327 288 246 310Japan. . . . . . . . . . . . . . . . . . . . . . . . 116,740 25,589 40,441 17,661 7,094 6,391 6,562 13,002Malaysia . . . . . . . . . . . . . . . . . . . . . 35,306 15,017 13,891 3,063 1,236 919 617 563Pakistan. . . . . . . . . . . . . . . . . . . . . . 226,251 95,929 98,625 17,008 5,826 4,186 2,568 2,109Philippines. . . . . . . . . . . . . . . . . . . . 129,448 55,474 53,369 10,581 3,738 2,814 1,877 1,596Singapore . . . . . . . . . . . . . . . . . . . . 9,047 2,345 4,158 1,204 468 360 239 274South Korea . . . . . . . . . . . . . . . . . . 53,763 14,515 20,967 7,819 3,470 2,959 1,803 2,231Sri Lanka. . . . . . . . . . . . . . . . . . . . . 22,937 7,102 9,580 2,771 1,142 945 694 703Thailand. . . . . . . . . . . . . . . . . . . . . . 71,311 21,219 28,987 9,441 3,927 3,189 2,303 2,245Turkey . . . . . . . . . . . . . . . . . . . . . . . 84,195 26,295 36,793 10,231 3,940 2,899 2,002 2,036

Latin America/CaribbeanArgentina. . . . . . . . . . . . . . . . . . . . . 47,229 16,082 19,374 4,834 1,963 1,705 1,376 1,895Brazil . . . . . . . . . . . . . . . . . . . . . . . . 203,489 66,334 87,458 22,898 9,091 7,080 5,099 5,530Chile. . . . . . . . . . . . . . . . . . . . . . . . . 18,915 5,863 7,817 2,133 1,006 823 582 691Colombia . . . . . . . . . . . . . . . . . . . . . 57,666 21,940 23,069 6,034 2,481 1,872 1,217 1,053Costa Rica . . . . . . . . . . . . . . . . . . . 5,272 1,796 2,248 554 235 188 124 127Guatemala . . . . . . . . . . . . . . . . . . . 24,038 12,128 9,105 1,455 493 368 252 238Jamaica . . . . . . . . . . . . . . . . . . . . . . 3,353 1,062 1,447 425 158 110 73 78Mexico . . . . . . . . . . . . . . . . . . . . . . . 139,125 52,128 58,225 14,646 5,165 3,700 2,621 2,639Peru . . . . . . . . . . . . . . . . . . . . . . . . . 39,253 14,952 16,694 3,735 1,394 1,031 711 736Uruguay. . . . . . . . . . . . . . . . . . . . . . 4,109 1,444 1,593 434 183 156 119 179

AfricaEgypt . . . . . . . . . . . . . . . . . . . . . . . . 99,583 38,878 43,516 9,212 3,144 2,261 1,437 1,136Kenya. . . . . . . . . . . . . . . . . . . . . . . . 34,836 15,729 15,402 1,902 610 472 349 373Liberia . . . . . . . . . . . . . . . . . . . . . . . 6,745 3,958 2,213 292 92 69 50 70Malawi . . . . . . . . . . . . . . . . . . . . . . . 12,817 6,856 5,087 466 144 111 81 71Morocco. . . . . . . . . . . . . . . . . . . . . . 44,664 17,220 19,141 4,225 1,546 1,180 735 618Tunisia . . . . . . . . . . . . . . . . . . . . . . . 12,322 3,806 5,428 1,517 581 442 270 278Zimbabwe . . . . . . . . . . . . . . . . . . . . 9,086 4,622 3,566 317 146 147 127 161



Table 3.Average Annual Growth Rate and Percent Change Over Time for Older Age Groups:2000 to 2015 and 2015 to 2030(In percent)

Country

Average annual growth rate

2000 to 2015 2015 to 2030

55 to 64years

65 to 79years

80 yearsand over

65 yearsand over

55 to 64years

65 to 79years

80 yearsand over

65 yearsand over

United States . . . . . . . . . . . . . . . . . . . 2.5 1.4 1.3 1.4 –0.5 2.8 3.0 2.8

Western EuropeAustria . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.8 0.9 1.9 1.1 0.9 1.7 2.3 1.9Belgium . . . . . . . . . . . . . . . . . . . . . . . . . . 1.5 0.2 2.5 0.8 –0.3 1.7 1.6 1.7Denmark . . . . . . . . . . . . . . . . . . . . . . . . . 0.7 1.6 0.7 1.4 0.6 0.8 3.3 1.5France . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.9 0.5 2.4 1.0 0.1 1.7 1.7 1.7Germany . . . . . . . . . . . . . . . . . . . . . . . . . 0.3 0.9 2.3 1.2 0.2 1.5 2.0 1.6Greece . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.7 0.2 3.0 0.9 0.9 1.1 1.2 1.1Italy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.5 0.4 2.5 0.9 1.3 1.0 1.5 1.1Luxembourg . . . . . . . . . . . . . . . . . . . . . . 1.8 0.9 2.5 1.3 0.9 2.6 2.2 2.5Norway . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.7 1.1 0.5 1.0 0.6 1.6 2.8 1.9Sweden . . . . . . . . . . . . . . . . . . . . . . . . . . 0.5 1.2 0.6 1.1 0.3 0.3 2.7 1.0United Kingdom . . . . . . . . . . . . . . . . . . . 1.0 0.9 1.2 0.9 0.7 1.4 2.4 1.7

Eastern EuropeBulgaria . . . . . . . . . . . . . . . . . . . . . . . . . . 0.2 –0.4 3.0 0.2 –0.6 0.1 1.8 0.6Czech Republic . . . . . . . . . . . . . . . . . . . 1.2 1.1 2.8 1.4 0.2 0.7 3.3 1.4Hungary . . . . . . . . . . . . . . . . . . . . . . . . . . 1.0 0.3 2.3 0.7 –0.1 0.8 2.1 1.2Poland . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.6 0.5 3.0 1.0 –1.3 2.4 2.3 2.4Russia . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.8 –0.2 2.0 0.3 –1.4 2.5 1.4 2.2Ukraine. . . . . . . . . . . . . . . . . . . . . . . . . . . 0.3 –0.4 1.3 –0.1 –0.6 1.3 1.5 1.4

North America/OceaniaAustralia . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 1.7 2.2 1.8 0.7 2.2 3.1 2.5Canada. . . . . . . . . . . . . . . . . . . . . . . . . . . 2.7 1.7 2.2 1.9 –0.1 3.0 3.0 3.0New Zealand. . . . . . . . . . . . . . . . . . . . . . 1.9 1.5 1.7 1.6 1.6 2.1 2.9 2.3

AsiaBangladesh . . . . . . . . . . . . . . . . . . . . . . . 2.8 2.6 1.6 2.5 3.2 4.1 4.7 4.2China . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.8 1.8 3.6 2.1 2.5 3.8 4.0 3.9India . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.5 2.2 2.7 2.2 2.6 3.6 4.3 3.7Indonesia . . . . . . . . . . . . . . . . . . . . . . . . . 2.9 2.3 5.3 2.7 2.3 4.7 4.1 4.6Israel. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.7 1.3 2.0 1.5 1.3 2.7 2.7 2.7Japan . . . . . . . . . . . . . . . . . . . . . . . . . . . . –0.2 1.5 3.2 1.9 0.7 –0.8 2.6 0.3Malaysia. . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 3.2 3.5 3.2 2.4 4.3 5.7 4.5Pakistan . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 1.8 2.5 1.9 3.5 3.8 3.4 3.7Philippines . . . . . . . . . . . . . . . . . . . . . . . . 3.0 2.7 3.1 2.8 3.0 4.3 5.0 4.4Singapore . . . . . . . . . . . . . . . . . . . . . . . . 5.2 3.4 4.2 3.6 3.5 5.9 4.5 5.6South Korea . . . . . . . . . . . . . . . . . . . . . . 2.5 2.5 4.5 2.9 1.4 3.7 4.5 3.8Sri Lanka . . . . . . . . . . . . . . . . . . . . . . . . . 2.6 2.3 3.1 2.5 1.7 3.3 4.4 3.5Thailand . . . . . . . . . . . . . . . . . . . . . . . . . . 2.6 2.4 3.9 2.6 1.7 3.6 4.2 3.7Turkey. . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.5 1.9 3.5 2.2 3.0 4.0 3.4 3.9

Latin America/CaribbeanArgentina . . . . . . . . . . . . . . . . . . . . . . . . . 1.6 1.1 2.3 1.4 1.2 2.0 2.4 2.1Brazil. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.5 2.4 3.6 2.6 2.1 3.5 4.3 3.6Chile . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3 2.5 3.3 2.6 1.1 3.2 4.4 3.4Colombia . . . . . . . . . . . . . . . . . . . . . . . . . 3.4 2.5 4.0 2.7 2.6 4.8 4.9 4.8Costa Rica. . . . . . . . . . . . . . . . . . . . . . . . 3.6 2.7 3.1 2.8 2.3 4.7 4.6 4.7Guatemala . . . . . . . . . . . . . . . . . . . . . . . . 2.9 2.1 3.8 2.4 3.4 4.0 4.0 4.0Jamaica . . . . . . . . . . . . . . . . . . . . . . . . . . 2.8 0.9 1.6 1.1 4.0 4.7 2.5 4.2Mexico . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.6 2.8 3.4 2.9 3.6 3.9 4.8 4.1Peru . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.6 2.5 3.7 2.7 3.1 3.8 4.2 3.9Uruguay . . . . . . . . . . . . . . . . . . . . . . . . . . 0.9 0.3 2.2 0.8 1.3 1.6 1.6 1.6

AfricaEgypt . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.6 2.5 3.4 2.6 2.9 3.9 5.2 4.0Kenya . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2 1.9 3.4 2.1 2.6 2.0 3.8 2.3Liberia. . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.5 2.4 3.8 2.7 2.9 2.5 3.9 2.8Malawi . . . . . . . . . . . . . . . . . . . . . . . . . . . – 1.1 2.5 1.3 1.3 0.3 2.8 0.6Morocco . . . . . . . . . . . . . . . . . . . . . . . . . . 3.0 1.8 3.0 2.0 3.3 4.7 3.6 4.5Tunisia . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.6 1.5 3.9 1.9 3.4 4.3 3.3 4.1Zimbabwe . . . . . . . . . . . . . . . . . . . . . . . . –0.2 1.1 3.0 1.4 –1.6 – 2.7 0.6


Table 3.Average Annual Growth Rate and Percent Change Over Time for Older Age Groups:2000 to 2015 and 2015 to 2030—Con.(In percent)

Country

Percent change

2000 to 2015 2015 to 2030

55 to 64years

65 to 79years

80 yearsand over

65 yearsand over

55 to 64years

65 to 79years

80 yearsand over

65 yearsand over

United States . . . . . . . . . . . . . . . . . . . 66 33 29 32 –7 52 56 53

Western EuropeAustria . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 19 48 25 15 30 42 33Belgium . . . . . . . . . . . . . . . . . . . . . . . . . . 34 4 64 16 –4 30 27 29Denmark . . . . . . . . . . . . . . . . . . . . . . . . . 14 37 16 32 9 13 63 24France . . . . . . . . . . . . . . . . . . . . . . . . . . . 45 10 61 22 1 28 30 29Germany . . . . . . . . . . . . . . . . . . . . . . . . . 6 20 57 28 3 25 34 27Greece . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 5 81 20 15 18 20 19Italy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 8 65 20 22 16 25 18Luxembourg . . . . . . . . . . . . . . . . . . . . . . 45 19 65 29 14 47 40 45Norway . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 26 11 22 10 26 52 33Sweden . . . . . . . . . . . . . . . . . . . . . . . . . . 10 28 14 24 5 5 50 17United Kingdom . . . . . . . . . . . . . . . . . . . 22 19 27 21 11 23 42 28

Eastern EuropeBulgaria . . . . . . . . . . . . . . . . . . . . . . . . . . 5 –7 83 5 –8 2 32 9Czech Republic . . . . . . . . . . . . . . . . . . . 27 25 73 33 4 11 65 23Hungary . . . . . . . . . . . . . . . . . . . . . . . . . . 22 5 60 15 –2 14 38 19Poland . . . . . . . . . . . . . . . . . . . . . . . . . . . 69 10 83 22 –17 44 42 43Russia . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 –3 50 5 –19 45 23 40Ukraine. . . . . . . . . . . . . . . . . . . . . . . . . . . 6 –7 30 –1 –8 22 25 23

North America/OceaniaAustralia . . . . . . . . . . . . . . . . . . . . . . . . . . 55 40 55 44 11 40 59 45Canada. . . . . . . . . . . . . . . . . . . . . . . . . . . 71 41 56 45 –1 56 57 56New Zealand. . . . . . . . . . . . . . . . . . . . . . 47 35 40 36 27 36 54 41

AsiaBangladesh . . . . . . . . . . . . . . . . . . . . . . . 76 69 37 64 62 85 102 87China . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75 43 107 51 45 78 82 78India . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64 54 73 57 47 72 89 75Indonesia . . . . . . . . . . . . . . . . . . . . . . . . . 79 58 188 71 41 102 84 99Israel. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72 29 49 34 22 51 50 51Japan . . . . . . . . . . . . . . . . . . . . . . . . . . . . –3 34 89 46 11 –11 47 5Malaysia. . . . . . . . . . . . . . . . . . . . . . . . . . 84 89 102 91 44 92 134 98Pakistan . . . . . . . . . . . . . . . . . . . . . . . . . . 55 42 64 45 70 76 67 75Philippines . . . . . . . . . . . . . . . . . . . . . . . . 82 73 87 75 57 92 112 95Singapore . . . . . . . . . . . . . . . . . . . . . . . . 182 97 130 104 68 143 96 131South Korea . . . . . . . . . . . . . . . . . . . . . . 64 66 148 78 23 73 96 78Sri Lanka . . . . . . . . . . . . . . . . . . . . . . . . . 67 59 86 64 29 65 94 70Thailand . . . . . . . . . . . . . . . . . . . . . . . . . . 67 62 120 70 29 73 87 75Turkey. . . . . . . . . . . . . . . . . . . . . . . . . . . . 66 46 103 55 57 81 68 79

Latin America/CaribbeanArgentina . . . . . . . . . . . . . . . . . . . . . . . . . 36 25 59 32 20 35 44 37Brazil. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64 62 107 69 38 68 90 72Chile . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59 64 95 70 19 61 93 67Colombia . . . . . . . . . . . . . . . . . . . . . . . . . 99 66 123 73 47 106 110 107Costa Rica. . . . . . . . . . . . . . . . . . . . . . . . 105 71 87 74 40 103 98 102Guatemala . . . . . . . . . . . . . . . . . . . . . . . . 77 54 113 62 65 83 81 83Jamaica . . . . . . . . . . . . . . . . . . . . . . . . . . 74 20 39 24 81 102 46 88Mexico . . . . . . . . . . . . . . . . . . . . . . . . . . . 68 74 99 78 72 80 107 84Peru . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67 64 108 71 58 78 87 80Uruguay . . . . . . . . . . . . . . . . . . . . . . . . . . 20 6 55 16 21 27 26 27

AfricaEgypt . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70 66 99 69 55 78 118 83Kenya . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 47 96 53 47 35 76 42Liberia. . . . . . . . . . . . . . . . . . . . . . . . . . . . 35 62 116 71 54 45 79 52Malawi . . . . . . . . . . . . . . . . . . . . . . . . . . . –1 25 65 29 22 4 51 10Morocco . . . . . . . . . . . . . . . . . . . . . . . . . . 80 43 83 49 63 103 72 97Tunisia . . . . . . . . . . . . . . . . . . . . . . . . . . . 68 36 120 47 66 90 65 85Zimbabwe . . . . . . . . . . . . . . . . . . . . . . . . –4 24 81 32 –22 –1 50 10



Table 4.Median Population Age: 2000, 2015, and 2030

Country 2000 2015 2030

United States . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36 38 39

Western EuropeAustria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 44 47Belgium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 43 46Denmark . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 42 43France . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 42 44Germany . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40 45 47Greece. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 44 49Italy. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40 46 52Luxembourg . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 40 41Norway . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37 41 42Sweden . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 43 45United Kingdom . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 42 44

Eastern EuropeBulgaria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40 44 50Czech Republic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 43 49Hungary. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 42 47Poland . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35 39 46Russia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37 39 44Ukraine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37 39 44

North America/OceaniaAustralia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35 39 42Canada . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37 41 44New Zealand . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32 37 40

AsiaBangladesh. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 27 33China . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 36 41India . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 28 32Indonesia. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 30 34Israel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 32 36Japan. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41 45 50Malaysia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 26 30Pakistan. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 24 29Philippines. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 25 29Singapore . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34 38 41South Korea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 38 43Sri Lanka. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 33 39Thailand. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 35 40Turkey . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 32 38

Latin America/CaribbeanArgentina. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 32 36Brazil . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 31 37Chile. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 33 39Colombia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 29 33Costa Rica . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 30 36Guatemala . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 21 25Jamaica . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 31 38Mexico . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 28 34Peru . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 27 33Uruguay. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 34 36

AfricaEgypt . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 27 32Kenya. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 23 28Liberia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 18 20Malawi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 20 23Morocco. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 27 33Tunisia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 32 39Zimbabwe . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 22 25



Table 5.Total and Elderly Urban Population by Sex: Available Data From 1970 to the Present

Country

Year

Males Females

Elderlysex ratioAll ages Elderly

Percentelderly All ages Elderly

Percentelderly

United States . . . . . . . . . . . . 1970 71,958,564 5,859,472 8.1 77,366,366 8,771,643 11.3 671980 80,287,243 7,327,774 9.1 86,767,395 11,672,992 13.5 631990 90,386,114 9,179,593 10.2 96,667,373 14,388,961 14.9 64

Western EuropeAustria . . . . . . . . . . . . . . . . . . . . 1971 1,762,775 223,701 12.7 2,103,790 403,229 19.2 55

1981 1,919,638 244,735 12.7 2,241,407 463,164 20.7 531991 2,386,002 272,021 11.4 2,646,187 533,663 20.2 51

Denmark . . . . . . . . . . . . . . . . . . 1970 1,922,558 206,818 10.8 2,023,599 290,237 14.3 711981 2,089,529 251,479 12.0 2,207,563 376,266 17.0 67

France . . . . . . . . . . . . . . . . . . . . 1975 18,658,540 1,858,540 10.0 19,728,800 3,054,920 15.5 611982 19,239,340 1,912,080 9.9 20,560,480 3,204,660 15.6 601990 20,194,431 2,236,685 11.1 21,728,802 3,625,554 16.7 62

Greece. . . . . . . . . . . . . . . . . . . . 1971 2,781,700 239,820 8.6 2,904,040 317,300 10.9 761981 3,311,565 316,153 9.5 3,478,383 413,686 11.9 761991 2,914,404 301,833 10.4 3,124,577 412,831 13.2 73

Norway . . . . . . . . . . . . . . . . . . . 1970 1,241,873 122,137 9.8 1,313,040 182,976 13.9 671980 1,409,663 133,166 9.4 1,483,530 211,705 14.3 631990 1,488,678 188,455 12.7 1,567,516 287,279 18.3 66

Sweden . . . . . . . . . . . . . . . . . . . 1970 3,232,096 342,732 10.6 3,342,837 474,392 14.2 721975 3,327,513 403,825 12.1 3,461,919 564,329 16.3 721980 3,378,530 452,876 13.4 3,534,963 642,174 18.2 711990 3,494,512 517,841 14.8 3,670,257 753,536 20.5 69

Eastern EuropeBulgaria . . . . . . . . . . . . . . . . . . . 1975 2,517,816 174,000 6.9 2,543,653 218,000 8.6 80

1987 2,923,029 221,049 7.6 2,998,215 281,896 9.4 781994 2,789,501 277,493 9.9 2,926,403 360,531 12.3 771996 2,741,483 272,800 10.0 2,893,119 364,313 12.6 75

Czech Republic . . . . . . . . . . . . 1994 3,731,186 365,443 9.8 3,989,275 602,153 15.1 611996 3,719,889 378,763 10.2 3,974,872 618,011 15.5 61

Hungary. . . . . . . . . . . . . . . . . . . 1970 2,217,658 205,423 9.3 2,449,193 326,340 13.3 631980 2,733,600 283,600 10.4 2,968,000 447,900 15.1 631988 3,000,826 289,051 9.6 3,284,713 486,970 14.8 591995 3,038,844 328,028 10.8 3,401,226 551,982 16.2 591996 3,037,842 331,902 10.9 3,405,105 559,268 16.4 59

Poland . . . . . . . . . . . . . . . . . . . . 1970 8,167,184 464,200 5.7 8,887,220 847,900 9.5 551978 9,667,100 660,000 6.8 10,472,600 1,171,000 11.2 561988 11,120,389 716,691 6.4 12,054,337 1,286,368 10.7 561994 11,422,337 847,910 7.4 12,435,702 1,476,495 11.9 571996 11,429,857 916,922 8.0 12,466,966 1,560,339 12.5 59

Russia . . . . . . . . . . . . . . . . . . . . 1970 36,930,897 1,432,200 3.9 43,700,474 3,909,327 8.9 371979 43,754,734 2,300,003 5.3 51,187,562 5,966,210 11.7 391989 50,332,668 2,566,076 5.1 57,626,334 6,960,412 12.1 371995 50,405,185 3,684,024 7.3 57,373,948 8,329,645 14.5 44

Ukraine . . . . . . . . . . . . . . . . . . . 1970 11,823,177 586,310 5.0 13,722,473 1,248,423 9.1 471979 13,953,878 887,799 6.4 16,215,059 1,897,668 11.7 471989 15,981,442 972,137 6.1 18,315,789 2,222,828 12.1 441995 16,298,622 1,292,193 7.9 18,529,728 2,602,852 14.0 50

North America/OceaniaAustralia . . . . . . . . . . . . . . . . . . 1971 5,424,345 379,844 7.0 5,489,106 557,526 10.2 68

1976 5,768,584 436,202 7.6 5,881,892 636,732 10.8 691986 6,567,861 605,540 9.2 6,749,084 867,372 12.9 70

Canada . . . . . . . . . . . . . . . . . . . 1971 8,104,535 557,750 6.9 8,306,250 762,300 9.2 731976 8,528,975 635,970 7.5 8,838,000 905,065 10.2 701981 9,013,665 746,085 8.3 9,422,265 1,096,860 11.6 681991 10,175,040 1,002,465 9.9 10,731,835 1,500,100 14.0 67


Table 5.Total and Elderly Urban Population by Sex: Available Data From 1970 to the Present—Con.

Country

Year

Males Females



Percentelderly

New Zealand . . . . . . . . . . . . . . 1981 1,299,006 115,065 8.9 1,351,878 165,414 12.2 701991 1,395,495 140,316 10.1 1,471,236 200,823 13.6 70

AfricaEgypt . . . . . . . . . . . . . . . . . . . . . 1976 8,539,623 265,355 3.1 8,018,049 247,043 3.1 107

1986 10,908,850 444,257 4.1 10,306,654 358,645 3.5 124

Kenya. . . . . . . . . . . . . . . . . . . . . 1979 1,307,158 21,142 1.6 1,075,045 18,128 1.7 1171989 1,933,437 23,090 1.2 1,606,451 21,877 1.4 106

Malawi . . . . . . . . . . . . . . . . . . . . 1977 253,545 3,842 1.5 217,113 3,203 1.5 1201987 445,863 7,085 1.6 407,527 6,479 1.6 109

Morocco. . . . . . . . . . . . . . . . . . . 1971 2,627,918 94,678 3.6 2,740,046 103,436 3.8 921982 4,378,706 138,248 3.2 4,354,801 140,753 3.2 98

Tunisia . . . . . . . . . . . . . . . . . . . . 1975 1,401,510 50,650 3.6 1,377,670 46,990 3.4 1081984 1,869,010 83,920 4.5 1,816,460 75,490 4.2 1111994 2,717,168 137,874 5.1 2,644,759 138,586 5.2 99

Zimbabwe . . . . . . . . . . . . . . . . . 1982 940,620 28,540 3.0 825,130 16,290 2.0 1751992 1,636,352 32,614 2.0 1,551,368 28,651 1.8 114

AsiaBangladesh. . . . . . . . . . . . . . . . 1974 3,538,531 84,854 2.4 2,734,781 63,247 2.3 134

1981 7,370,000 226,000 3.1 5,858,000 157,000 2.7 1441988 8,163,604 212,600 2.6 6,918,309 131,859 1.9 1611991 11,301,085 305,677 2.7 9,571,119 222,943 2.3 137

China . . . . . . . . . . . . . . . . . . . . . 1982 107,915,090 4,183,470 3.9 98,332,070 5,186,590 5.3 811990 157,491,587 7,081,751 4.5 142,665,833 8,260,440 5.8 86

India . . . . . . . . . . . . . . . . . . . . . . 1971 58,718,371 1,526,269 2.6 50,378,274 1,494,668 3.0 1021981 83,876,401 2,486,231 3.0 73,803,766 2,545,642 3.4 98

Indonesia. . . . . . . . . . . . . . . . . . 1971 10,194,359 196,839 1.9 10,255,961 245,422 2.4 801980 16,439,900 374,916 2.3 16,401,825 489,857 3.0 771990 27,683,319 800,720 2.9 27,750,471 981,431 3.5 82

Israel . . . . . . . . . . . . . . . . . . . . . 1972 1,343,341 100,705 7.5 1,341,228 104,050 7.8 971983 1,793,397 156,353 8.7 1,822,632 177,579 9.7 881994 2,390,900 205,500 8.6 2,453,000 271,200 11.1 761995 2,452,000 211,000 8.6 2,518,500 281,200 11.2 75

Japan. . . . . . . . . . . . . . . . . . . . . 1970 36,889,500 2,044,900 5.5 37,799,200 2,612,500 6.9 781975 41,988,960 2,579,504 6.1 42,933,417 3,387,121 7.9 761980 43,979,403 3,094,757 7.0 45,138,389 4,218,737 9.3 731985 45,766,358 3,559,634 7.8 47,082,519 5,138,386 10.9 691990 47,124,420 4,224,745 9.0 48,519,101 6,279,911 12.9 671995 48,210,196 5,385,903 11.2 49,798,911 7,693,917 15.4 70

Malaysia . . . . . . . . . . . . . . . . . . 1970 1,402,000 40,628 2.9 1,378,254 45,916 3.3 881980 2,044,873 69,340 3.4 2,028,232 79,699 3.9 871991 4,472,970 133,071 3.0 4,425,611 167,315 3.8 80

Pakistan. . . . . . . . . . . . . . . . . . . 1972 9,019,171 289,765 3.2 7,561,180 213,461 2.8 1361981 12,767,061 446,804 3.5 11,074,410 327,383 3.0 1361990 14,514,629 433,128 3.0 13,542,746 383,029 2.8 113

Philippines. . . . . . . . . . . . . . . . . 1970 5,670,816 149,101 2.6 5,999,388 170,339 2.8 881975 6,553,324 182,848 2.8 6,752,757 198,287 2.9 921980 8,765,413 244,103 2.8 9,178,240 341,658 3.7 711990 14,546,463 415,222 2.9 14,893,690 537,747 3.6 77

Singapore . . . . . . . . . . . . . . . . . 1970 1,062,127 30,589 2.9 1,012,380 38,775 3.8 791980 1,231,760 51,202 4.2 1,182,185 62,722 5.3 821990 1,517,776 75,403 5.0 1,498,603 93,266 6.2 81

South Korea . . . . . . . . . . . . . . . 1975 8,369,909 128,569 1.5 8,400,037 253,528 3.0 511980 10,697,843 183,694 1.7 10,711,606 365,207 3.4 501985 13,154,130 271,087 2.1 13,263,842 521,815 3.9 521995 17,595,723 536,398 3.0 17,396,241 978,119 5.6 55


Table 5.Total and Elderly Urban Population by Sex: Available Data From 1970 to the Present—Con.

Country

Year

Males Females



Percentelderly

Sri Lanka. . . . . . . . . . . . . . . . . . 1971 1,513,102 58,346 3.9 1,335,014 56,084 4.2 1041981 1,665,539 68,979 4.1 1,528,940 72,270 4.7 95

Thailand. . . . . . . . . . . . . . . . . . . 1970 2,257,068 55,778 2.5 2,296,032 79,328 3.5 701980 3,744,425 109,059 2.9 3,888,491 147,891 3.8 741990 4,941,000 173,200 3.5 5,265,900 230,700 4.4 75

Turkey . . . . . . . . . . . . . . . . . . . . 1980 10,272,130 345,047 3.4 9,372,877 457,407 4.9 751985 14,010,670 399,207 2.8 12,855,087 532,949 4.1 751990 17,247,553 518,630 3.0 16,078,798 675,302 4.2 77

Latin America/CaribbeanArgentina. . . . . . . . . . . . . . . . . . 1980 11,213,938 820,687 7.3 11,978,954 1,159,370 9.7 71

1995 14,820,662 1,185,585 8.0 15,736,243 1,761,004 11.2 67

Brazil . . . . . . . . . . . . . . . . . . . . . 1970 25,173,439 803,470 3.2 26,801,506 1,010,184 3.8 801980 39,192,230 1,447,919 3.7 41,172,542 1,864,900 4.5 781991 53,854,256 2,333,327 4.3 57,136,734 3,082,663 5.4 76

Chile. . . . . . . . . . . . . . . . . . . . . . 1970 3,173,323 139,527 4.4 3,501,814 193,934 5.5 721982 4,464,374 219,108 4.9 4,851,754 313,023 6.5 701992 5,364,760 288,375 5.4 5,775,645 427,059 7.4 681997 6,052,039 324,862 5.4 6,368,467 503,897 7.9 64

Colombia . . . . . . . . . . . . . . . . . . 1973 5,904,613 172,482 2.9 6,703,236 232,676 3.5 741985 8,927,542 321,963 3.6 9,786,011 407,186 4.2 791993 11,211,708 472,784 4.2 12,302,362 593,057 4.8 80

Costa Rica . . . . . . . . . . . . . . . . 1973 360,701 14,033 3.9 399,378 18,497 4.6 761984 514,426 24,261 4.7 560,828 32,416 5.8 751995 674,634 53,926 8.0 694,787 69,823 10.0 77

Guatemala . . . . . . . . . . . . . . . . 1973 905,685 29,216 3.2 972,506 36,717 3.8 801981 949,676 35,220 3.7 1,030,857 42,529 4.1 83

Jamaica . . . . . . . . . . . . . . . . . . . 1982 494,155 23,230 4.7 551,886 33,216 6.0 701991 543,108 27,635 5.1 605,083 39,724 6.6 70

Mexico . . . . . . . . . . . . . . . . . . . . 1970 13,882,914 463,048 3.3 14,425,642 580,730 4.0 801995 32,720,158 1,277,431 3.9 34,283,357 1,570,619 4.6 81

Peru . . . . . . . . . . . . . . . . . . . . . . 1972 4,028,169 125,390 3.1 4,030,326 154,174 3.8 811981 5,517,769 193,224 3.5 5,574,154 225,243 4.0 861993 7,606,489 324,827 4.3 7,852,110 372,285 4.7 87

Uruguay. . . . . . . . . . . . . . . . . . . 1975 1,099,634 99,670 9.1 1,214,722 138,060 11.4 721985 1,222,260 119,891 9.8 1,358,827 177,647 13.1 671990 1,306,601 130,547 10.0 1,441,721 194,640 13.5 671996 1,366,092 148,110 10.8 1,505,985 225,783 15.0 66

Notes: ‘‘Urban’’ refers to localities defined as such by each country. Individual national definitions are available in the annotations torespective International Data Base tables.

‘‘Elderly Sex Ratio’’ is defined as the number of men aged 65 years and over per 100 women aged 65 years and over.



Table 6.Sex Ratio for Population 25 Years and Over by Age: 2000 and 2030(Men per 100 women)

Country

2000 2030

25 to54

years

55 to64

years

65 to69

years

70 to74

years

75 to79


25 to54

years

55 to64

years

65 to69

years

70 to74

years

75 to79


United States. . . . . . . . . . . 98 91 85 79 72 52 98 92 89 86 81 64

Western EuropeAustria . . . . . . . . . . . . . . . . . . 103 95 85 72 50 38 104 99 96 89 79 58Belgium . . . . . . . . . . . . . . . . . 102 96 87 78 66 41 102 98 93 87 80 57Denmark. . . . . . . . . . . . . . . . . 103 99 90 82 70 49 102 98 96 90 82 62France . . . . . . . . . . . . . . . . . . 100 96 85 77 66 46 103 96 88 82 76 57Germany . . . . . . . . . . . . . . . . 105 98 89 73 49 35 102 98 94 87 77 56Greece . . . . . . . . . . . . . . . . . . 100 94 89 83 75 67 105 98 91 87 82 65Italy . . . . . . . . . . . . . . . . . . . . . 100 92 85 77 66 50 102 96 91 86 77 58Luxembourg. . . . . . . . . . . . . . 102 99 88 78 53 42 98 94 92 86 79 59Norway . . . . . . . . . . . . . . . . . . 104 99 91 83 70 50 100 97 95 90 82 62Sweden . . . . . . . . . . . . . . . . . 104 101 91 83 75 54 104 99 96 91 83 64United Kingdom . . . . . . . . . . 102 97 91 82 70 45 105 101 96 90 81 60

Eastern EuropeBulgaria . . . . . . . . . . . . . . . . . 97 87 82 75 67 62 102 89 79 72 63 48Czech Republic. . . . . . . . . . . 101 90 78 67 55 42 103 97 89 81 71 53Hungary . . . . . . . . . . . . . . . . . 98 80 70 62 53 43 102 92 80 70 61 42Poland . . . . . . . . . . . . . . . . . . 100 85 75 65 54 44 102 94 84 76 66 49Russia. . . . . . . . . . . . . . . . . . . 96 73 62 51 33 26 97 84 72 62 52 39Ukraine . . . . . . . . . . . . . . . . . . 93 73 66 54 37 29 97 80 67 58 49 34

North America/OceaniaAustralia . . . . . . . . . . . . . . . . . 102 101 94 88 75 55 102 98 93 87 80 66Canada. . . . . . . . . . . . . . . . . . 101 97 92 83 71 52 102 97 93 87 79 61New Zealand . . . . . . . . . . . . . 101 97 95 89 74 53 103 101 92 86 79 62

AsiaBangladesh . . . . . . . . . . . . . . 104 116 115 118 126 128 104 101 97 96 100 105China . . . . . . . . . . . . . . . . . . . 106 108 101 93 80 59 107 100 95 90 80 63India . . . . . . . . . . . . . . . . . . . . 106 108 103 100 106 106 107 99 90 92 92 89Indonesia . . . . . . . . . . . . . . . . 100 89 83 79 74 64 101 95 90 85 78 59Israel . . . . . . . . . . . . . . . . . . . . 101 91 84 74 72 70 104 101 96 87 80 66Japan . . . . . . . . . . . . . . . . . . . 102 95 89 83 64 48 104 100 94 88 81 61Malaysia . . . . . . . . . . . . . . . . . 99 96 84 80 71 64 104 97 86 76 71 61Pakistan . . . . . . . . . . . . . . . . . 104 98 98 97 95 96 105 102 95 87 78 70Philippines . . . . . . . . . . . . . . . 96 91 85 79 76 77 102 92 83 74 67 61Singapore. . . . . . . . . . . . . . . . 94 100 88 83 76 59 85 84 86 86 81 64South Korea . . . . . . . . . . . . . 103 94 76 62 55 40 108 97 88 82 75 56Sri Lanka . . . . . . . . . . . . . . . . 93 90 92 93 93 94 96 86 78 72 68 63Thailand . . . . . . . . . . . . . . . . . 96 91 85 82 75 59 102 90 82 77 71 56Turkey. . . . . . . . . . . . . . . . . . . 105 96 93 91 84 62 102 101 98 91 83 63

Latin America/CaribbeanArgentina . . . . . . . . . . . . . . . . 100 92 82 74 66 56 102 95 89 83 75 58Brazil . . . . . . . . . . . . . . . . . . . . 96 85 78 70 63 50 98 88 80 74 67 52Chile . . . . . . . . . . . . . . . . . . . . 99 91 83 76 68 46 102 96 90 85 76 55Colombia . . . . . . . . . . . . . . . . 94 82 85 83 80 72 97 89 84 79 70 53Costa Rica . . . . . . . . . . . . . . . 101 100 95 91 84 71 104 99 91 86 81 67Guatemala . . . . . . . . . . . . . . . 98 94 93 91 83 75 101 94 89 84 76 67Jamaica . . . . . . . . . . . . . . . . . 98 93 89 85 78 68 104 99 90 79 75 65Mexico . . . . . . . . . . . . . . . . . . 92 89 87 84 77 65 98 89 79 73 68 57Peru . . . . . . . . . . . . . . . . . . . . 101 97 93 87 80 68 101 97 93 89 82 68Uruguay . . . . . . . . . . . . . . . . . 97 87 82 75 68 53 103 96 86 78 72 52

AfricaEgypt. . . . . . . . . . . . . . . . . . . . 102 91 85 79 70 64 102 100 85 78 69 53Kenya . . . . . . . . . . . . . . . . . . . 101 85 78 80 80 77 108 88 73 66 61 56Liberia. . . . . . . . . . . . . . . . . . . 90 109 109 103 92 87 98 85 77 76 79 87Malawi . . . . . . . . . . . . . . . . . . 96 73 70 69 69 68 111 81 57 47 41 37Morocco . . . . . . . . . . . . . . . . . 98 84 83 86 84 81 101 94 88 84 75 58Tunisia . . . . . . . . . . . . . . . . . . 99 89 95 99 105 117 104 98 92 87 79 69Zimbabwe . . . . . . . . . . . . . . . 101 97 105 108 104 90 130 105 70 55 52 56



Table

7.

Mari

tal

Sta

tus

of

Old

er

Pers

on

sb

ySex:

Sele

cte

dYears

19

70

to1

99

5

Cou

ntry

,ye

ar,

and

age

Mal

esF

emal

es

Tota

lS

ingl

eM

arrie

dW

idow

edS

epar

ated

/di

vorc

edP

erce

ntw

idow

edTo

tal

Sin

gle

Mar

ried

Wid

owed

Sep

arat

ed/

divo

rced

Per

cent

wid

owed

Un

ited

Sta

tes

1977

55to

64..

....

....

....

...

9,47

6,00

054

9,00

08,

109,

000

323,

000

495,

000

3.4

10,6

01,0

0049

2,00

07,

434,

000

2,02

3,00

065

2,00

019

.165

and

over

....

....

....

..9,

132,

000

539,

000

7,00

7,00

01,

298,

000

288,

000

14.2

12,9

68,0

0083

1,00

05,

029,

000

6,75

0,00

035

8,00

052

.175

and

over

....

....

....

..2,

991,

000

139,

000

2,07

0,00

072

7,00

055

,000

24.3

4,96

8,00

032

7,00

01,

070,

000

3,46

3,00

010

8,00

069

.7

1987

55to

64..

....

....

....

...

10,2

77,0

0059

1,00

08,

439,

000

293,

000

954,

000

2.9

11,6

06,0

0048

5,00

07,

903,

000

1,93

5,00

01,

283,

000

16.7

65an

dov

er..

....

....

....

11,5

76,0

0052

6,00

08,

806,

000

1,62

2,00

062

2,00

014

.016

,396

,000

898,

000

6,56

5,00

08,

070,

000

863,

000

49.2

75an

dov

er..

....

....

....

3,96

9,00

017

2,00

02,

692,

000

937,

000

168,

000

23.6

6,77

3,00

043

5,00

01,

577,

000

4,54

1,00

022

0,00

067

.0

1990

55to

64..

....

....

....

...

9,98

1,41

755

6,41

28,

004,

491

347,

468

1,07

3,04

63.

511

,166

,506

508,

048

7,39

8,22

51,

776,

893

1,48

3,34

015

.965

and

over

....

....

....

..12

,565

,173

618,

893

9,39

8,67

21,

781,

502

766,

106

14.2

18,6

76,6

581,

025,

944

7,21

8,01

89,

225,

990

1,20

6,70

649

.475

and

over

....

....

....

..4,

623,

560

226,

579

3,11

1,15

41,

079,

851

205,

976

23.4

8,51

1,71

353

5,97

81,

964,

130

5,63

8,18

237

3,42

366

.2

1995

55to

64..

....

....

....

...

9,87

8,00

049

4,00

07,

821,

000

275,

000

1,28

8,00

02.

810

,878

,000

467,

000

7,15

2,00

01,

405,

000

1,85

4,00

012

.965

and

over

....

....

....

..13

,002

,000

543,

000

9,69

3,00

01,

755,

000

1,01

1,00

013

.518

,262

,000

768,

000

7,42

1,00

08,

636,

000

1,43

7,00

047

.375

and

over

....

....

....

..4,

905,

000

201,

000

3,35

3,00

01,

062,

000

289,

000

21.7

8,14

5,00

036

0,00

02,

057,

000

5,28

4,00

044

4,00

064

.9

Wes

tern

Eu

rop

e

Au

stri

a

1975

55to

64..

....

....

....

...

292,

514

18,0

6725

1,87

211

,958

10,6

174.

141

8,21

445

,134

234,

142

115,

307

23,6

3127

.665

and

over

....

....

....

..41

9,22

227

,803

303,

413

76,2

2611

,780

18.2

712,

408

89,8

0719

8,13

439

8,48

125

,986

55.9

75an

dov

er..

....

....

....

128,

104

8,29

075

,050

42,1

242,

640

32.9

270,

703

36,4

6337

,532

189,

810

6,89

870

.1

1982

55to

64..

....

....

....

...

325,

102

18,7

7028

2,40

111

,910

12,0

213.

746

4,43

648

,055

287,

062

100,

012

29,3

0721

.565

and

over

....

....

....

..39

8,38

125

,044

288,

932

72,4

2611

,979

18.2

717,

382

83,3

0918

9,29

041

4,18

830

,595

57.7

75an

dov

er..

....

....

....

151,

921

9,97

492

,455

45,7

293,

763

30.1

318,

738

39,7

3645

,590

223,

728

9,68

470

.2

1991

55to

64..

....

....

....

...

368,

200

24,3

0030

9,80

014

,600

19,5

004.

040

6,70

033

,400

269,

400

76,3

0027

,600

18.8

65an

dov

er..

....

....

....

404,

400

21,5

0030

3,40

066

,100

13,4

0016

.376

2,50

078

,900

229,

900

414,

900

38,8

0054

.480

and

over

....

....

....

..81

,000

4,90

045

,500

28,7

001,

900

35.4

201,

800

22,6

0019

,900

152,

200

7,10

075

.4

Bel

giu

m

1970

55to

64..

....

....

....

...

510,

104

41,6

7443

2,43

127

,202

8,79

75.

356

8,17

947

,653

397,

082

112,

424

11,0

2019

.865

and

over

....

....

....

..53

1,59

536

,822

367,

496

121,

407

5,87

022

.876

4,11

376

,475

289,

108

388,

803

9,72

750

.975

and

over

....

....

....

..16

5,28

110

,634

87,6

7365

,842

1,13

239

.827

8,50

431

,894

57,7

6218

5,98

12,

867

66.8

An Aging World: 2001U.S. Census Bureau 137

Table

7.

Mari

tal

Sta

tus

of

Old

er

Pers

on

sb

ySex:

Sele

cte

dYears

19

70

to1

99

5—

Con

.

Cou

ntry

,ye

ar,

and

age

Mal

esF

emal

es

Tota

lS

ingl

eM

arrie

dW

idow

edS

epar

ated

/di

vorc

edP

erce

ntw

idow

edTo

tal

Sin

gle

Mar

ried

Wid

owed

Sep

arat

ed/

divo

rced

Per

cent

wid

owed

1981

55to

64..

....

....

....

...

486,

328

35,1

6741

6,82

521

,167

13,1

694.

453

0,93

538

,830

381,

994

94,8

3015

,281

17.9

65an

dov

er..

....

....

....

559,

796

40,1

7239

4,28

811

5,14

910

,187

20.6

855,

497

76,6

6831

1,47

845

0,08

717

,264

52.6

75an

dov

er..

....

....

....

195,

638

13,0

5511

0,74

269

,243

2,59

835

.437

1,06

436

,273

75,7

2725

3,17

15,

893

68.2

1995

55to

64..

....

....

....

...

539,

184

38,1

7944

6,88

820

,822

33,2

953.

957

2,92

728

,877

426,

701

81,8

6135

,488

14.3

65an

dov

er..

....

....

....

639,

393

41,4

2047

3,13

610

4,99

819

,839

16.4

957,

152

70,0

1637

8,21

047

7,30

731

,619

49.9

75an

dov

er..

....

....

....

206,

173

12,8

7812

7,02

461

,994

4,27

730

.141

5,93

834

,652

84,2

9928

6,50

810

,479

68.9

Den

mar

k

1970

55to

64..

....

....

....

...

266,

499

23,9

5521

5,86

411

,862

14,8

184.

528

4,83

527

,815

189,

277

47,6

7920

,064

16.7

65an

dov

er..

....

....

....

267,

785

21,5

5118

1,55

155

,457

9,22

620

.734

2,45

647

,998

124,

958

154,

680

14,8

2045

.275

and

over

....

....

....

..91

,710

6,58

149

,619

33,2

942,

216

36.3

127,

693

19,0

7226

,203

78,2

294,

189

61.3

1984

55to

64..

....

....

....

...

259,

041

21,4

4820

6,02

811

,726

19,8

394.

527

8,75

716

,898

191,

979

44,9

4124

,939

16.1

65an

dov

er..

....

....

....

317,

829

24,9

5322

0,28

056

,838

15,7

5817

.944

3,74

244

,903

160,

494

209,

959

28,3

8647

.375

and

over

....

....

....

..11

6,03

88,

771

68,5

7634

,579

4,11

229

.819

8,62

725

,116

40,9

0312

2,34

410

,264

61.6

1988

55to

64..

....

....

....

...

246,

548

20,4

3819

2,43

411

,123

22,5

534.

526

4,29

214

,592

181,

376

41,8

1926

,505

15.8

65an

dov

er..

....

....

....

327,

558

25,0

1022

5,92

258

,379

18,2

4717

.846

3,44

340

,978

167,

399

222,

770

32,2

9648

.175

and

over

....

....

....

..12

6,19

39,

558

75,4

0236

,033

5,20

028

.621

8,57

724

,291

45,4

4913

6,45

012

,387

62.4

1991

55to

64..

....

....

....

...

242,

100

19,7

0018

6,30

010

,500

25,6

004.

325

6,50

013

,000

175,

500

39,0

0029

,000

15.2

65an

dov

er..

....

....

....

330,

700

24,9

0022

6,20

059

,300

20,3

0017

.947

1,20

037

,700

169,

600

229,

000

34,9

0048

.680

and

over

....

....

....

..63

,100

4,60

032

,900

23,3

002,

300

36.9

129,

200

14,6

0017

,600

90,1

006,

900

69.7

Fra

nce

1977

55to

64..

....

....

....

...

2,13

3,60

818

5,51

61,

796,

121

91,8

9660

,075

4.3

2,38

9,70

819

4,10

61,

623,

560

477,

261

94,7

8120

.065

and

over

....

....

....

..2,

814,

161

216,

482

2,04

0,53

949

9,83

257

,308

17.8

4,40

9,48

843

4,91

51,

523,

015

2,33

1,03

712

0,52

152

.975

and

over

....

....

....

..91

6,60

559

,680

565,

618

278,

799

12,5

0830

.41,

897,

529

203,

787

345,

672

1,30

8,85

739

,213

69.0

1987

55to

64..

....

....

....

...

2,82

9,06

326

4,79

42,

347,

412

104,

386

112,

471

3.7

3,11

7,29

923

5,94

52,

182,

303

542,

687

156,

364

17.4

65an

dov

er..

....

....

....

2,86

5,96

221

3,62

22,

100,

203

476,

298

75,8

3916

.64,

535,

745

388,

255

1,58

1,61

12,

406,

407

159,

472

53.1

75an

dov

er..

....

....

....

1,21

6,80

387

,804

775,

866

326,

761

26,3

7226

.92,

375,

929

220,

211

495,

629

1,59

1,50

468

,585

67.0

An Aging World: 2001 U.S. Census Bureau138

Table

7.

Mari

tal

Sta

tus

of

Old

er

Pers

on

sb

ySex:

Sele

cte

dYears

19

70

to1

99

5—

Con

.

Cou

ntry

,ye

ar,

and

age

Mal

esF

emal

es

Tota

lS

ingl

eM

arrie

dW

idow

edS

epar

ated

/di

vorc

edP

erce

ntw

idow

edTo

tal

Sin

gle

Mar

ried

Wid

owed

Sep

arat

ed/

divo

rced

Per

cent

wid

owed

1990

55to

64..

....

....

....

...

2,61

4,98

623

5,58

62,

194,

804

98,0

6086

,536

3.7

2,90

2,74

822

9,92

22,

023,

751

522,

574

126,

501

18.0

65an

dov

er..

....

....

....

2,77

3,47

921

1,88

52,

022,

866

477,

313

61,4

1517

.24,

421,

124

403,

594

1,51

2,80

02,

367,

851

136,

879

53.6

75an

dov

er..

....

....

....

1,11

4,97

676

,838

712,

221

306,

957

18,9

6027

.52,

193,

119

218,

872

450,

458

1,46

9,55

054

,239

67.0

1991

55to

64..

....

....

....

...

2,87

8,30

028

2,00

02,

366,

000

103,

900

126,

400

3.6

3,14

9,10

024

0,10

02,

213,

000

529,

300

166,

700

16.8

65an

dov

er..

....

....

....

3,13

9,50

024

2,30

02,

344,

500

473,

400

79,3

0015

.14,

860,

700

416,

200

1,78

0,30

02,

495,

300

168,

900

51.3

80an

dov

er..

....

....

....

649,

000

43,9

0037

8,40

021

6,40

010

,300

33.3

1,46

5,60

014

0,60

020

9,00

01,

078,

400

37,6

0073

.6

Ger

man

y

1970

55to

64..

....

....

....

...

3,13

6,60

013

5,84

92,

795,

380

123,

806

81,5

653.

94,

304,

130

391,

801

2,50

1,62

81,

240,

028

170,

673

28.8

65an

dov

er..

....

....

....

3,08

6,79

713

2,35

72,

317,

143

585,

809

51,4

8819

.04,

903,

787

573,

521

1,54

7,33

92,

655,

939

126,

988

54.2

75an

dov

er..

....

....

....

879,

316

36,1

7551

7,77

531

5,90

29,

464

35.9

1,68

0,05

420

0,60

027

5,03

21,

172,

131

32,2

9169

.8

1982

55to

64..

....

....

....

...

2,73

7,40

011

0,80

02,

445,

600

101,

800

79,2

003.

73,

806,

500

338,

900

2,49

4,50

078

8,40

018

4,70

020

.765

and

over

....

....

....

..3,

216,

000

130,

100

2,42

5,60

059

5,50

064

,800

18.5

5,95

7,10

056

8,70

01,

702,

800

3,47

8,20

020

7,40

058

.475

and

over

....

....

....

..1,

251,

000

55,8

0079

3,10

038

3,50

018

,600

30.7

2,63

1,40

028

7,60

042

2,80

01,

853,

800

67,2

0070

.4

1988

55to

64..

....

....

....

...

3,26

5,13

317

1,21

62,

822,

046

126,

924

144,

947

3.9

3,63

8,27

827

8,38

62,

515,

148

650,

779

193,

965

17.9

65an

dov

er..

....

....

....

3,24

5,68

812

3,37

92,

473,

976

567,

492

80,8

4117

.56,

269,

329

575,

328

1,87

4,54

63,

581,

410

238,

045

57.1

75an

dov

er..

....

....

....

1,40

3,90

457

,930

921,

075

397,

205

27,6

9428

.33,

158,

012

301,

265

515,

681

2,24

7,15

093

,916

71.2

1991

55to

64..

....

....

....

...

4,37

3,90

022

2,40

03,

763,

800

167,

100

220,

600

3.8

4,66

6,50

031

4,80

03,

274,

100

782,

600

295,

000

16.8

65an

dov

er..

....

....

....

4,02

0,00

013

5,00

03,

068,

800

713,

300

102,

900

17.7

7,89

4,30

068

4,60

02,

422,

900

4,43

1,40

035

5,40

056

.180

and

over

....

....

....

..83

9,10

032

,800

464,

100

328,

000

14,2

0039

.12,

173,

200

201,

800

221,

700

1,68

2,60

067

,100

77.4

Gre

ece

1971

55to

64..

....

....

....

...

443,

948

21,1

6040

4,51

613

,760

4,51

23.

147

5,72

427

,660

330,

596

109,

892

7,57

623

.165

and

over

....

....

....

..41

8,34

020

,520

333,

732

60,9

803,

108

14.6

537,

928

27,2

6820

9,62

029

6,29

24,

748

55.1

1981

55to

64..

....

....

....

...

423,

832

18,5

9039

2,22

59,

090

3,92

72.

147

4,84

429

,626

339,

831

96,2

679,

120

20.3

65an

dov

er..

....

....

....

549,

829

21,4

4245

5,56

269

,132

3,69

312

.668

9,37

232

,763

300,

341

349,

441

6,82

750

.775

and

over

....

....

....

..18

9,99

87,

189

139,

959

41,8

7697

422

.026

4,20

610

,700

75,1

1417

6,85

01,

542

66.9

1991

55to

64..

....

....

....

...

631,

100

24,4

0058

3,80

015

,100

7,80

02.

466

9,00

037

,200

505,

800

111,

100

14,9

0016

.665

and

over

....

....

....

..61

7,90

021

,300

506,

700

85,2

004,

700

13.8

786,

200

39,9

0033

3,70

040

3,30

09,

300

51.3

80an

dov

er..

....

....

....

127,

800

3,80

083

,200

40,3

0050

031

.518

2,40

07,

400

38,2

0013

5,80

01,

000

74.5


Table

7.

Mari

tal

Sta

tus

of

Old

er

Pers

on

sb

ySex:

Sele

cte

dYears

19

70

to1

99

5—

Con

.

Cou

ntry

,ye

ar,

and

age

Mal

esF

emal

es

Tota

lS

ingl

eM

arrie

dW

idow

edS

epar

ated

/di

vorc

edP

erce

ntw

idow

edTo

tal

Sin

gle

Mar

ried

Wid

owed

Sep

arat

ed/

divo

rced

Per

cent

wid

owed

Ital

y

1971

55to

64..

....

....

....

...

2,80

1,21

229

8,55

02,

349,

235

122,

338

31,0

894.

43,

113,

265

462,

317

1,96

4,47

265

8,67

027

,806

21.2

65an

dov

er..

....

....

....

2,55

1,02

727

4,11

81,

767,

979

490,

320

18,6

1019

.24,

291,

661

560,

307

1,19

9,33

02,

516,

342

15,6

8258

.675

and

over

....

....

....

..79

2,65

676

,604

440,

808

271,

304

3,94

034

.21,

599,

749

196,

832

231,

759

1,16

7,45

03,

708

73.0

1981

55to

64..

....

....

....

...

2,70

1,14

920

2,97

92,

373,

486

88,9

8535

,699

3.3

3,10

1,90

634

6,69

02,

106,

252

603,

772

45,1

9219

.565

and

over

....

....

....

..3,

069,

244

202,

032

2,33

2,39

950

8,42

326

,390

16.6

4,41

5,88

255

9,45

91,

574,

337

2,25

5,20

726

,879

51.1

75an

dov

er..

....

....

....

968,

219

58,6

3061

0,11

429

3,73

85,

737

30.3

1,71

5,51

422

6,39

332

8,58

91,

155,

103

5,42

967

.3

1991

55to

64..

....

....

....

...

3,18

1,51

728

0,97

52,

743,

058

101,

805

55,6

793.

23,

508,

194

319,

232

2,51

4,83

561

1,08

163

,046

17.4

65an

dov

er..

....

....

....

3,54

3,71

026

6,19

02,

723,

996

521,

379

32,1

4514

.75,

187,

215

598,

889

1,93

6,73

42,

609,

396

42,1

9650

.375

and

over

....

....

....

..1,

390,

939

98,7

9593

4,50

834

9,42

58,

211

25.1

2,41

2,27

729

6,75

952

1,42

61,

583,

248

10,8

4465

.6

Lu

xem

bo

urg

1970

55to

64..

....

....

....

...

19,2

441,

979

15,5

5698

772

25.

121

,480

2,53

613

,220

5,06

066

423

.665

and

over

....

....

....

..17

,886

1,87

511

,717

3,92

936

522

.024

,953

3,51

38,

121

12,9

3338

651

.875

and

over

....

....

....

..5,

214

541

2,58

12,

030

6238

.98,

252

1,21

31,

363

5,59

482

67.8

1981

55to

64..

....

....

....

...

15,7

681,

152

13,3

2073

056

64.

619

,580

1,99

112

,702

4,23

465

321

.665

and

over

....

....

....

..19

,475

1,82

813

,483

3,75

341

119

.330

,071

3,77

09,

354

16,3

9355

454

.575

and

over

....

....

....

..6,

355

640

3,56

22,

064

8932

.512

,003

1,66

62,

002

8,19

813

768

.3

1990

55to

64..

....

....

....

...

20,9

871,

541

17,6

2290

591

94.

322

,355

1,71

615

,488

4,19

695

518

.865

and

over

....

....

....

..18

,605

1,44

813

,364

3,40

339

018

.332

,079

3,47

810

,077

17,8

0472

055

.575

and

over

....

....

....

..7,

490

652

4,46

42,

253

121

30.1

15,3

051,

795

2,58

610

,657

267

69.6

1991

55to

64..

....

....

....

...

20,0

001,

600

17,4

0090

010

04.

521

,700

1,50

015

,200

4,00

01,

000

18.4

65an

dov

er..

....

....

....

18,7

001,

400

13,6

003,

400

300

18.2

31,5

003,

400

10,1

0017

,400

600

55.2

80an

dov

er..

....

....

....

3,50

030

01,

800

1,40

0-

40.0

8,20

01,

000

900

6,20

010

075

.6

No

rway

1977

55to

64..

....

....

....

...

225,

959

25,7

4718

3,35

57,

811

9,04

63.

524

0,00

322

,689

170,

526

36,1

0510

,683

15.0

65an

dov

er..

....

....

....

246,

374

29,3

7216

9,74

641

,329

5,92

716

.833

0,58

156

,141

122,

789

141,

280

10,3

7142

.775

and

over

....

....

....

..87

,866

10,6

3849

,369

26,3

621,

497

30.0

137,

309

27,3

3828

,632

77,5

513,

788

56.5


Table

7.

Mari

tal

Sta

tus

of

Old

er

Pers

on

sb

ySex:

Sele

cte

dYears

19

70

to1

99

5—

Con

.

Cou

ntry

,ye

ar,

and

age

Mal

esF

emal

es

Tota

lS

ingl

eM

arrie

dW

idow

edS

epar

ated

/di

vorc

edP

erce

ntw

idow

edTo

tal

Sin

gle

Mar

ried

Wid

owed

Sep

arat

ed/

divo

rced

Per

cent

wid

owed

1987

55to

64..

....

....

....

...

205,

426

22,3

9616

2,18

56,

938

13,9

073.

421

4,78

513

,942

154,

254

32,8

0013

,789

15.3

65an

dov

er..

....

....

....

279,

469

30,2

7219

6,65

143

,209

9,33

715

.538

9,09

148

,425

149,

830

175,

993

14,8

4345

.275

and

over

....

....

....

..10

3,54

511

,613

62,2

0127

,508

2,22

326

.617

5,37

928

,112

37,7

4610

4,29

95,

222

59.5

1990

55to

64..

....

....

....

...

189,

896

19,4

9914

8,29

46,

241

15,8

623.

319

7,62

011

,176

141,

924

29,3

1115

,209

14.8

65an

dov

er..

....

....

....

287,

792

30,2

7020

2,54

243

,934

11,0

4615

.340

3,09

744

,698

157,

295

184,

534

16,5

7045

.875

and

over

....

....

....

..10

9,51

311

,652

66,7

8328

,460

2,61

826

.018

7,27

526

,518

41,7

8411

2,94

36,

030

60.3

Sw

eden

1977

55to

64..

....

....

....

...

485,

407

60,3

5237

3,89

217

,190

33,9

733.

550

3,76

841

,444

353,

317

69,4

3539

,572

13.8

65an

dov

er..

....

....

....

569,

226

72,6

9237

9,40

893

,513

23,6

1316

.473

1,30

711

1,36

027

7,79

530

6,84

135

,311

42.0

75an

dov

er..

....

....

....

196,

040

24,5

4610

8,31

457

,709

5,47

129

.429

9,05

355

,811

61,4

1517

0,69

211

,135

57.1

1987

55to

64..

....

....

....

...

430,

710

51,9

6131

4,44

512

,890

51,4

143.

045

3,16

729

,892

312,

671

54,3

7856

,226

12.0

65an

dov

er..

....

....

....

656,

804

75,8

3644

2,83

197

,296

40,8

4114

.887

3,68

992

,422

344,

972

375,

320

60,9

7543

.075

and

over

....

....

....

..26

2,79

330

,692

155,

617

65,1

6111

,323

24.8

418,

064

56,5

0097

,876

241,

690

21,9

9857

.819

90

55to

64..

....

....

....

...

410,

001

47,0

9630

0,16

511

,379

51,3

612.

843

0,34

127

,471

292,

651

49,4

1860

,801

11.5

65an

dov

er..

....

....

....

656,

389

73,1

0145

3,18

387

,668

42,4

3713

.488

3,65

282

,936

347,

240

384,

817

68,6

5943

.575

and

over

....

....

....

..26

7,77

429

,616

169,

597

57,3

7911

,182

21.4

431,

817

50,6

5610

2,24

025

3,53

025

,391

58.7

1991

55to

64..

....

....

....

...

410,

000

47,1

0029

6,50

011

,700

54,7

002.

943

0,40

027

,500

292,

700

49,4

0060

,800

11.5

65an

dov

er..

....

....

....

656,

400

73,1

0044

0,60

096

,800

45,9

0014

.788

3,70

082

,900

347,

200

384,

900

68,7

0043

.680

and

over

....

....

....

..13

1,90

014

,600

69,4

0042

,900

5,00

032

.524

5,50

033

,300

37,5

0016

2,50

012

,200

66.2

Un

ited

Kin

gd

om

1971

55to

64..

....

....

....

...

3,06

6,26

526

1,00

42,

625,

123

144,

487

35,6

514.

73,

429,

830

381,

665

2,36

2,67

462

7,13

558

,356

18.3

65an

dov

er..

....

....

....

2,79

7,59

420

5,57

62,

017,

125

558,

282

16,6

1120

.04,

478,

190

670,

920

1,56

0,50

22,

215,

089

31,6

7949

.575

and

over

....

....

....

..83

6,94

854

,024

477,

624

302,

586

2,71

436

.21,

758,

765

286,

784

328,

555

1,13

8,20

15,

225

64.7

1986

55to

64..

....

....

....

...

2,88

7,50

025

4,70

02,

378,

300

122,

800

131,

700

4.3

3,08

1,30

021

5,30

02,

206,

300

496,

500

163,

200

16.1

65an

dov

er..

....

....

....

3,35

3,20

025

3,00

02,

424,

800

595,

600

79,8

0017

.85,

141,

000

543,

800

1,90

1,90

02,

560,

500

134,

800

49.8

75an

dov

er..

....

....

....

1,20

0,90

090

,200

735,

900

355,

300

19,5

0029

.62,

401,

500

304,

900

513,

600

1,54

3,60

039

,400

64.3

1989

55to

64..

....

....

....

...

2,85

8,41

424

3,22

22,

338,

294

112,

999

163,

899

4.0

3,01

6,17

819

0,73

42,

170,

898

460,

063

194,

483

15.3

65an

dov

er..

....

....

....

3,57

2,01

027

4,56

22,

575,

814

620,

944

100,

690

17.4

5,38

1,75

652

3,57

62,

025,

176

2,66

4,39

916

8,60

549

.575

and

over

....

....

....

..1,

337,

065

102,

474

827,

817

380,

173

26,6

0128

.42,

595,

328

301,

632

575,

773

1,66

4,90

853

,015

64.2


Table

7.

Mari

tal

Sta

tus

of

Old

er

Pers

on

sb

ySex:

Sele

cte

dYears

19

70

to1

99

5—

Con

.

Cou

ntry

,ye

ar,

and

age

Mal

esF

emal

es

Tota

lS

ingl

eM

arrie

dW

idow

edS

epar

ated

/di

vorc

edP

erce

ntw

idow

edTo

tal

Sin

gle

Mar

ried

Wid

owed

Sep

arat

ed/

divo

rced

Per

cent

wid

owed

1991

55to

64..

....

....

....

...

2,83

0,90

023

9,00

02,

302,

100

111,

300

178,

500

3.9

2,97

2,20

018

1,30

02,

141,

800

440,

300

208,

800

14.8

65an

dov

er..

....

....

....

3,61

5,00

027

0,10

02,

588,

200

649,

500

107,

200

18.0

5,39

5,10

050

0,50

02,

067,

700

2,66

4,00

016

2,90

049

.480

and

over

....

....

....

..62

3,80

042

,600

335,

600

236,

500

9,10

037

.91,

464,

200

181,

200

225,

200

1,03

7,00

020

,800

70.8

Eas

tern

Eu

rop

e

Bu

lgar

ia

1975

55to

64..

....

....

....

...

399,

856

5,20

037

1,41

318

,158

5,08

54.

542

1,07

67,

511

325,

704

79,5

928,

269

18.9

65an

dov

er..

....

....

....

443,

012

5,26

133

7,88

496

,187

3,68

021

.752

3,53

37,

397

254,

612

256,

559

4,96

549

.075

and

over

....

....

....

..12

4,09

01,

302

72,3

4149

,703

744

40.1

168,

484

1,99

447

,626

117,

873

991

70.0

1985

55to

64..

....

....

....

...

546,

879

12,0

0349

6,11

925

,456

13,3

014.

758

5,81

112

,275

440,

441

112,

741

20,3

5419

.265

and

over

....

....

....

..45

7,84

27,

580

337,

949

106,

035

6,27

823

.256

5,29

110

,024

244,

652

300,

620

9,99

553

.275

and

over

....

....

....

..16

7,09

62,

710

97,0

0165

,537

1,84

839

.222

7,72

33,

910

61,0

2615

9,92

02,

867

70.2

Cze

chR

epu

blic

1980

55to

64..

....

....

....

...

646,

909

30,9

1556

0,44

025

,694

29,8

604.

075

7,77

535

,490

501,

161

175,

962

45,1

6223

.265

and

over

....

....

....

..74

8,67

430

,868

552,

105

144,

297

21,4

0419

.31,

142,

571

70,7

8536

2,73

166

9,79

439

,261

58.6

75an

dov

er..

....

....

....

216,

008

8,32

212

8,24

875

,290

4,14

834

.942

3,98

330

,902

65,0

3331

7,46

810

,580

74.9

1989

55to

64..

....

....

....

...

720,

089

34,6

5561

4,50

129

,873

41,0

604.

184

6,66

430

,023

554,

083

199,

660

62,8

9823

.665

and

over

....

....

....

..70

4,26

628

,969

533,

614

118,

548

23,1

3516

.81,

130,

671

55,2

1035

9,25

066

4,39

351

,818

58.8

75an

dov

er..

....

....

....

265,

668

10,5

2717

5,04

774

,270

5,82

428

.051

1,89

127

,642

91,9

4637

5,92

516

,378

73.4

1991

55to

64..

....

....

....

...

485,

282

21,7

6040

9,02

821

,265

33,2

294.

456

5,19

516

,135

368,

270

131,

779

49,0

1123

.365

and

over

....

....

....

..48

9,67

519

,107

356,

042

93,8

3820

,688

19.2

811,

044

34,9

3323

9,19

749

2,74

244

,172

60.8

80an

dov

er..

....

....

....

75,4

462,

608

37,8

5033

,167

1,82

144

.018

1,55

310

,137

15,2

9915

0,25

95,

858

82.8

Hu

ng

ary

1976

55to

64..

....

....

....

...

471,

397

16,8

0741

8,32

019

,074

17,1

964.

056

4,87

831

,121

361,

430

139,

244

33,0

8324

.765

and

over

....

....

....

..55

7,45

720

,147

414,

958

108,

933

13,4

1919

.580

0,00

850

,955

257,

228

464,

137

27,6

8858

.075

and

over

....

....

....

..16

2,65

24,

692

94,2

8360

,856

2,82

137

.428

0,96

218

,199

38,6

9821

7,79

06,

275

77.5

1986

55to

64..

....

....

....

...

567,

845

22,5

7248

7,56

027

,575

30,1

384.

968

5,09

429

,792

433,

756

166,

222

55,3

2424

.365

and

over

....

....

....

..51

5,49

818

,487

374,

827

107,

177

15,0

0720

.881

9,85

347

,980

231,

717

503,

256

36,9

0061

.475

and

over

....

....

....

..19

2,83

37,

412

113,

810

67,9

293,

682

35.2

357,

205

23,0

0549

,790

273,

930

10,4

8076

.7


Table

7.

Mari

tal

Sta

tus

of

Old

er

Pers

on

sb

ySex:

Sele

cte

dYears

19

70

to1

99

5—

Con

.

Cou

ntry

,ye

ar,

and

age

Mal

esF

emal

es

Tota

lS

ingl

eM

arrie

dW

idow

edS

epar

ated

/di

vorc

edP

erce

ntw

idow

edTo

tal

Sin

gle

Mar

ried

Wid

owed

Sep

arat

ed/

divo

rced

Per

cent

wid

owed

1989

55to

64..

....

....

....

...

547,

931

22,2

8546

5,53

027

,561

32,5

555.

066

2,67

125

,597

416,

800

161,

665

58,6

0924

.465

and

over

....

....

....

..53

5,38

918

,887

390,

517

109,

317

16,6

6820

.486

2,05

247

,279

248,

978

521,

985

43,8

1060

.675

and

over

....

....

....

..20

4,68

07,

760

121,

514

71,3

274,

079

34.8

385,

184

23,6

5352

,833

296,

162

12,5

3676

.9

1990

55to

64..

....

....

....

...

539,

776

21,0

9045

3,66

729

,436

35,5

835.

565

3,69

124

,073

409,

295

163,

563

56,7

6025

.065

and

over

....

....

....

..52

7,46

416

,842

390,

600

102,

433

17,5

8919

.484

6,45

844

,039

253,

434

509,

434

39,5

5160

.275

and

over

....

....

....

..19

9,76

86,

594

125,

595

62,9

064,

673

31.5

376,

704

21,8

4358

,239

284,

462

12,1

6075

.5

Po

lan

d

1978

55to

64..

....

....

....

...

1,21

1,20

038

,400

1,10

1,70

045

,200

25,9

003.

71,

522,

000

113,

600

993,

200

368,

600

46,6

0024

.265

and

over

....

....

....

..1,

388,

900

43,0

001,

104,

900

222,

300

18,7

0016

.02,

172,

200

181,

500

703,

300

1,25

8,80

028

,600

58.0

75an

dov

er..

....

....

....

385,

600

11,4

0025

6,70

011

3,90

03,

600

29.5

766,

200

67,8

0012

3,00

057

0,10

05,

300

74.4

1984

55to

64..

....

....

....

...

1,64

1,27

154

,071

1,47

3,34

973

,417

40,4

344.

52,

024,

326

123,

823

1,34

5,92

448

3,86

670

,713

23.9

65an

dov

er..

....

....

....

1,34

1,41

838

,950

1,04

3,81

224

1,08

017

,576

18.0

2,20

7,17

616

6,81

666

6,08

71,

344,

280

29,9

9360

.970

and

over

....

....

....

..93

8,47

926

,397

695,

277

205,

868

10,9

3721

.91,

644,

993

128,

420

397,

829

1,10

1,01

017

,734

66.9

1990

55to

64..

....

....

....

...

1,74

2,19

770

,907

1,53

3,88

183

,049

54,3

604.

82,

074,

692

118,

507

1,37

7,95

549

1,91

286

,318

23.7

65an

dov

er..

....

....

....

1,40

4,16

446

,287

1,08

1,22

125

3,36

523

,291

18.0

2,32

2,88

318

4,70

372

1,60

71,

378,

164

38,4

0959

.375

and

over

....

....

....

..52

8,95

218

,610

348,

848

155,

425

6,06

929

.41,

042,

532

89,8

3517

0,84

877

2,18

79,

662

74.1

Ru

ssia

1979

55to

64..

....

....

....

...

3,59

8,61

032

,251

3,32

2,87

913

9,19

110

4,28

93.

97,

055,

198

411,

867

3,54

5,58

02,

519,

277

578,

474

35.7

65an

dov

er..

....

....

....

3,70

0,36

226

,021

3,09

8,67

151

7,77

657

,894

14.0

9,96

8,77

836

3,73

02,

142,

027

7,14

0,17

032

2,85

171

.670

and

over

....

....

....

..1,

998,

396

14,4

701,

565,

276

392,

666

25,9

8419

.66,

182,

892

203,

761

948,

649

4,88

3,91

814

6,56

479

.0

1989

55to

64..

....

....

....

...

6,94

2,94

510

2,30

26,

116,

488

364,

262

359,

893

5.2

9,77

1,29

248

8,70

35,

699,

250

2,63

1,83

295

1,50

726

.965

and

over

....

....

....

..3,

692,

094

35,2

292,

930,

172

649,

073

77,6

2017

.610

,398

,320

565,

746

2,44

0,03

06,

921,

921

470,

623

66.6

70an

dov

er..

....

....

....

2,32

9,92

020

,141

1,75

0,40

252

1,42

637

,951

22.4

7,26

8,66

434

3,28

91,

186,

416

5,49

2,09

024

6,86

975

.6

1994

55to

64..

....

....

....

...

366,

460

9,15

531

7,39

419

,729

20,1

825.

448

6,53

521

,691

291,

920

119,

644

53,2

8124

.665

and

over

....

....

....

..25

2,86

54,

148

201,

743

40,6

726,

302

16.1

610,

580

46,9

6417

3,70

735

2,48

337

,425

57.7

70an

dov

er..

....

....

....

118,

227

2,12

886

,897

27,0

742,

128

22.9

371,

823

30,4

8968

,415

255,

071

17,8

4768

.6

Ukr

ain

e

1979

55to

64..

....

....

....

...

1,53

6,22

612

,883

1,43

4,15

655

,538

33,6

493.

62,

830,

603

157,

805

1,49

1,65

697

8,71

720

2,42

534

.665

and

over

....

....

....

..1,

817,

794

12,8

341,

498,

157

285,

300

21,5

0315

.74,

014,

982

123,

325

1,01

3,44

42,

768,

943

109,

270

69.0

70an

dov

er..

....

....

....

1,05

7,31

97,

467

811,

681

227,

721

10,4

5021

.52,

488,

489

67,8

4547

7,08

81,

894,

225

49,3

3176

.1


Table

7.

Mari

tal

Sta

tus

of

Old

er

Pers

on

sb

ySex:

Sele

cte

dYears

19

70

to1

99

5—

Con

.

Cou

ntry

,ye

ar,

and

age

Mal

esF

emal

es

Tota

lS

ingl

eM

arrie

dW

idow

edS

epar

ated

/di

vorc

edP

erce

ntw

idow

edTo

tal

Sin

gle

Mar

ried

Wid

owed

Sep

arat

ed/

divo

rced

Per

cent

wid

owed

1989

55to

64..

....

....

....

...

2,58

7,87

429

,964

2,32

7,83

612

8,68

510

1,38

95.

03,

591,

248

202,

424

2,14

8,57

592

5,49

631

4,75

325

.865

and

over

....

....

....

..1,

760,

852

15,3

671,

388,

448

326,

937

30,1

0018

.64,

272,

908

203,

089

1,11

0,95

92,

790,

571

168,

289

65.3

70an

dov

er..

....

....

....

1,09

8,49

78,

774

808,

501

266,

538

14,6

8424

.32,

891,

993

114,

439

514,

048

2,18

0,03

683

,470

75.4

No

rth

Am

eric

a/O

cean

ia

Au

stra

lia

1971

55to

64..

....

....

....

...

545,

204

45,3

3644

7,15

225

,203

27,5

134.

656

1,77

540

,449

379,

001

113,

384

28,9

4120

.265

and

over

....

....

....

..44

6,86

139

,512

304,

336

84,0

4518

,968

18.8

618,

134

66,0

2420

5,43

432

7,64

019

,036

53.0

75an

dov

er..

....

....

....

139,

676

11,8

4376

,882

46,2

064,

745

33.1

245,

906

29,1

8543

,297

168,

544

4,88

068

.5

1981

55to

64..

....

....

....

...

650,

931

49,7

7152

9,85

925

,983

45,3

184.

067

5,28

632

,792

473,

366

120,

806

48,3

2217

.965

and

over

....

....

....

..60

1,11

944

,954

433,

077

94,2

3628

,852

15.7

828,

278

67,5

7230

7,05

242

3,62

230

,032

51.1

1990

55to

64..

....

....

....

...

732,

290

56,1

2860

2,02

224

,079

50,0

613.

372

5,23

230

,065

528,

761

111,

423

54,9

8315

.465

and

over

....

....

....

..81

2,08

756

,227

609,

784

112,

308

33,7

6813

.81,

095,

493

66,5

7347

6,25

951

0,28

642

,375

46.6

75an

dov

er..

....

....

....

281,

389

19,3

8418

8,19

565

,739

8,07

123

.447

4,73

735

,973

132,

427

294,

852

11,4

8562

.1

1991

55to

64..

....

....

....

...

710,

813

54,1

2856

6,39

822

,934

67,3

533.

270

9,38

931

,267

507,

554

100,

234

70,3

3414

.165

and

over

....

....

....

..81

6,19

956

,745

599,

208

111,

264

48,9

8213

.61,

090,

493

67,9

2946

9,17

849

9,13

954

,247

45.8

Can

ada

1976

55to

64..

....

....

....

...

928,

045

76,1

9577

7,51

532

,395

41,9

403.

599

6,38

579

,035

689,

700

177,

195

50,4

5517

.865

and

over

....

....

....

..87

5,41

083

,760

627,

260

133,

350

31,0

4015

.21,

126,

900

115,

260

421,

745

561,

060

28,8

3549

.875

and

over

....

....

....

..29

5,52

529

,160

176,

600

81,4

158,

350

27.5

452,

260

47,8

0594

,615

303,

770

6,07

067

.2

1986

55to

64..

....

....

....

...

1,12

4,05

583

,035

925,

650

36,5

9078

,780

3.3

1,20

4,25

572

,305

849,

405

188,

285

94,2

6015

.665

and

over

....

....

....

..1,

133,

320

85,5

5584

3,94

015

3,37

050

,455

13.5

1,50

5,73

576

,300

618,

240

753,

915

57,2

8050

.175

and

over

....

....

....

..39

4,45

032

,270

255,

565

93,0

3513

,580

23.6

653,

025

65,0

0014

6,18

542

8,37

013

,470

65.6

1991

55to

64..

....

....

....

...

1,18

0,02

580

,375

976,

260

33,6

7089

,720

2.9

1,21

9,60

068

,575

864,

175

169,

170

117,

680

13.9

65an

dov

er..

....

....

....

1,33

0,43

592

,385

1,00

1,76

517

1,62

064

,665

12.9

1,84

2,54

014

1,15

575

5,16

585

9,38

086

,840

46.6

75an

dov

er..

....

....

....

478,

980

34,9

9032

0,30

510

5,82

017

,865

22.1

795,

925

73,5

4519

1,82

050

9,49

021

,070

64.0

New

Zea

lan

d

1976

55to

64..

....

....

....

...

127,

006

8,97

410

7,51

25,

224

5,29

64.

113

6,61

78,

869

97,1

8824

,638

5,92

218

.065

and

over

....

....

....

..11

8,52

88,

005

87,9

4819

,074

3,50

116

.115

9,91

715

,828

62,4

2377

,594

4,07

248

.575

and

over

....

....

....

..35

,170

2,40

521

,654

10,3

6874

329

.561

,522

6,81

613

,161

40,6

1692

966

.0


Table

7.

Mari

tal

Sta

tus

of

Old

er

Pers

on

sb

ySex:

Sele

cte

dYears

19

70

to1

99

5—

Con

.

Cou

ntry

,ye

ar,

and

age

Mal

esF

emal

es

Tota

lS

ingl

eM

arrie

dW

idow

edS

epar

ated

/di

vorc

edP

erce

ntw

idow

edTo

tal

Sin

gle

Mar

ried

Wid

owed

Sep

arat

ed/

divo

rced

Per

cent

wid

owed

1986

55to

64..

....

....

....

...

142,

167

10,1

4911

4,51

95,

778

11,7

214.

114

2,56

66,

996

101,

250

23,1

9611

,124

16.3

65an

dov

er..

....

....

....

141,

021

8,69

710

3,44

622

,389

6,48

915

.919

5,84

614

,643

77,7

7896

,273

7,15

249

.275

and

over

....

....

....

..47

,736

2,91

030

,357

12,9

031,

566

27.0

81,5

587,

431

18,6

0053

,670

1,85

765

.8

1991

55to

64..

....

....

....

...

137,

658

9,31

210

8,42

35,

502

14,4

214.

013

6,57

86,

048

95,7

1220

,871

13,9

4715

.365

and

over

....

....

....

..15

7,05

69,

573

113,

310

25,2

488,

925

16.1

215,

802

13,9

8385

,413

106,

851

9,55

549

.570

and

over

....

....

....

..97

,992

5,72

467

,209

20,5

894,

470

21.0

150,

327

10,6

5646

,923

87,5

495,

199

58.2

Afr

ica

Eg

ypt

1976

55to

64..

....

....

....

...

958,

317

37,1

7787

4,77

941

,407

4,95

44.

389

9,49

240

,880

443,

885

405,

378

9,34

945

.165

and

over

....

....

....

..63

4,40

233

,320

514,

470

82,7

363,

876

13.0

667,

501

38,0

5815

3,72

447

0,61

25,

107

70.5

1986

55to

64..

....

....

....

...

1,23

8,70

448

,149

1,12

0,34

263

,506

6,70

75.

11,

259,

315

43,4

5768

0,46

551

8,03

217

,361

41.1

65an

dov

er..

....

....

....

948,

486

83,0

8072

4,86

713

5,77

64,

763

14.3

849,

250

71,0

2420

1,22

856

9,02

67,

972

67.0

Lib

eria

1974

55to

59..

....

....

....

...

17,7

7586

014

,676

824

1,41

54.

611

,742

323

7,49

62,

783

1,14

023

.760

and

over

....

....

....

..51

,862

2,31

738

,598

5,41

85,

529

10.4

37,5

251,

252

14,5

3917

,150

4,58

445

.719

84

55to

64..

....

....

....

...

45,4

322,

228

37,2

372,

391

3,57

65.

336

,603

1,20

422

,801

9,34

83,

250

25.5

65an

dov

er..

....

....

....

50,0

882,

323

37,3

625,

606

4,79

711

.237

,029

1,47

514

,740

17,1

053,

709

46.2

75an

dov

er..

....

....

....

21,8

591,

005

15,5

793,

112

2,16

314

.215

,661

663

4,95

28,

440

1,60

653

.9

Mal

awi

1977

55to

64..

....

....

....

...

113,

484

1,54

110

5,27

62,

670

3,99

72.

412

1,33

21,

248

75,8

1330

,271

14,0

0024

.965

and

over

....

....

....

..12

2,19

41,

740

106,

166

8,79

45,

494

7.2

125,

828

1,71

149

,739

61,2

1513

,163

48.6

1987

55to

64..

....

....

....

...

146,

761

1,84

713

5,43

93,

620

5,85

52.

516

3,74

11,

211

101,

139

38,9

4422

,447

23.8

65an

dov

er..

....

....

....

157,

832

1,72

513

6,11

012

,234

7,76

37.

816

8,52

61,

724

65,3

9179

,558

21,8

5347

.2

Mo

rocc

o

1971

55to

64..

....

....

....

...

332,

610

11,0

2230

4,77

310

,540

6,27

53.

229

9,45

310

,486

132,

260

139,

550

17,1

5746

.665

and

over

....

....

....

..37

3,25

513

,137

314,

402

36,7

468,

970

9.8

340,

641

14,2

7565

,949

243,

393

17,0

2471

.5


Table

7.

Mari

tal

Sta

tus

of

Old

er

Pers

on

sb

ySex:

Sele

cte

dYears

19

70

to1

99

5—

Con

.

Cou

ntry

,ye

ar,

and

age

Mal

esF

emal

es

Tota

lS

ingl

eM

arrie

dW

idow

edS

epar

ated

/di

vorc

edP

erce

ntw

idow

edTo

tal

Sin

gle

Mar

ried

Wid

owed

Sep

arat

ed/

divo

rced

Per

cent

wid

owed

1982

55to

64..

....

....

....

...

481,

613

8,03

545

1,51

813

,881

8,17

92.

945

6,98

45,

515

240,

762

188,

131

22,5

7641

.265

and

over

....

....

....

..42

4,84

67,

546

367,

417

40,3

979,

486

9.5

375,

217

7,54

285

,414

266,

817

15,4

4471

.175

and

over

....

....

....

..17

0,26

03,

703

137,

207

24,4

924,

858

14.4

143,

225

2,93

918

,571

116,

189

5,52

681

.1

Tun

isia

1975

55to

64..

....

....

....

...

158,

120

3,92

014

7,15

05,

810

1,24

03.

712

9,47

03,

090

81,4

0041

,840

3,14

032

.365

and

over

....

....

....

..11

8,99

03,

390

100,

740

13,5

401,

320

11.4

100,

420

4,16

030

,890

61,7

203,

650

61.5

1984

55to

64..

....

....

....

...

191,

330

4,39

018

0,14

05,

840

960

3.1

172,

480

3,34

011

3,80

053

,310

2,03

030

.965

and

over

....

....

....

..16

7,26

06,

490

141,

600

18,2

2095

010

.913

1,95

04,

780

44,2

8081

,490

1,40

061

.875

and

over

....

....

....

..48

,480

3,51

035

,850

8,87

025

018

.341

,190

2,69

06,

760

31,4

2032

076

.3

Zim

bab

we

1982

55to

64..

....

....

....

...

144,

250

6,49

512

7,45

54,

515

5,78

53.

112

6,06

03,

852

76,4

0739

,088

6,71

331

.065

and

over

....

....

....

..11

5,93

06,

906

94,8

689,

267

4,88

98.

012

2,77

05,

902

44,3

8366

,995

5,49

054

.675

and

over

....

....

....

..47

,310

3,52

336

,815

5,25

51,

717

11.1

53,4

403,

138

14,8

7933

,147

2,27

662

.0

1992

55to

64..

....

....

....

...

190,

189

4,73

317

0,40

26,

016

9,03

83.

217

0,91

32,

809

101,

725

53,3

5813

,021

31.2

65an

dov

er..

....

....

....

161,

452

4,50

213

3,89

814

,600

8,45

29.

018

1,46

43,

796

57,9

8011

0,81

38,

875

61.1

75an

dov

er..

....

....

....

51,9

771,

616

40,4

957,

223

2,64

313

.968

,301

1,67

014

,061

49,9

742,

596

73.2

Asi

a

Ban

gla

des

h

1974

55to

64..

....

....

....

...

1,69

5,31

114

,144

1,59

5,45

183

,804

1,91

24.

91,

339,

206

4,10

457

7,70

275

2,36

95,

031

56.2

65an

dov

er..

....

....

....

1,37

2,98

712

,345

1,21

1,67

514

7,89

11,

076

10.8

1,00

1,34

04,

916

208,

707

785,

640

2,07

778

.5

1981

55to

64..

....

....

....

...

1,96

9,48

828

,747

1,86

4,98

574

,559

1,19

73.

81,

599,

535

13,7

3674

3,73

583

8,10

73,

957

52.4

65an

dov

er..

....

....

....

1,70

4,86

34,

187

1,51

8,41

918

1,20

41,

053

10.6

1,24

9,84

11,

360

344,

564

901,

865

2,05

272

.2

Ch

ina

1982

50to

59..

....

....

....

...

38,9

95,4

501,

158,

670

33,7

40,0

403,

315,

600

781,

140

8.5

35,6

26,3

0075

,270

29,2

71,1

406,

112,

760

167,

130

17.2

60to

79..

....

....

....

...

33,7

73,3

6085

8,01

023

,850

,350

8,53

4,66

053

0,34

025

.337

,708

,310

109,

310

16,6

58,8

2020

,794

,240

145,

940

55.1

80an

dov

er..

....

....

....

1,76

0,68

044

,160

654,

620

1,04

7,13

014

,770

59.5

3,28

0,38

08,

710

234,

240

3,03

3,14

04,

290

92.5

1990

55to

64..

....

....

....

...

39,3

80,2

601,

257,

460

33,4

11,9

804,

083,

470

627,

350

10.4

36,4

27,7

8072

,370

27,9

82,0

408,

234,

090

139,

280

22.6

65an

dov

er..

....

....

....

28,7

17,7

7064

5,97

019

,113

,740

8,62

3,42

033

4,64

030

.034

,476

,600

104,

770

12,7

94,2

8021

,463

,040

114,

510

62.3


Table

7.

Mari

tal

Sta

tus

of

Old

er

Pers

on

sb

ySex:

Sele

cte

dYears

19

70

to1

99

5—

Con

.

Cou

ntry

,ye

ar,

and

age

Mal

esF

emal

es

Tota

lS

ingl

eM

arrie

dW

idow

edS

epar

ated

/di

vorc

edP

erce

ntw

idow

edTo

tal

Sin

gle

Mar

ried

Wid

owed

Sep

arat

ed/

divo

rced

Per

cent

wid

owed

Ind

ia

1971

55to

64..

....

....

....

...

14,3

52,0

0234

7,16

411

,826

,418

2,11

2,13

366

,287

14.7

12,8

41,0

6658

,031

5,96

5,81

36,

753,

204

64,0

1852

.665

and

over

....

....

....

..9,

383,

212

226,

541

6,62

0,83

62,

491,

958

43,8

7726

.68,

928,

952

32,0

932,

220,

930

6,64

6,58

229

,347

74.4

1981

55to

64..

....

....

....

...

17,8

87,8

8036

8,49

815

,361

,824

2,08

7,57

669

,982

11.7

16,6

97,6

1059

,948

9,11

6,95

17,

438,

739

81,9

7244

.565

and

over

....

....

....

..12

,625

,093

253,

621

9,37

5,35

82,

947,

660

48,4

5423

.312

,377

,227

50,0

353,

579,

769

8,70

5,53

641

,887

70.3

Ind

on

esia

1971

55to

64..

....

....

....

...

2,20

8,41

935

,096

1,95

0,34

719

4,51

228

,464

8.8

2,35

6,11

520

,125

932,

949

1,31

4,94

488

,097

55.8

65an

dov

er..

....

....

....

1,43

9,84

219

,751

1,12

8,29

526

9,28

622

,510

18.7

1,52

8,53

512

,753

354,

997

1,11

5,34

345

,442

73.0

75an

dov

er..

....

....

....

380,

399

5,84

826

8,88

299

,578

6,09

126

.240

6,45

93,

749

68,8

8732

4,09

79,

726

79.7

1976

55to

64..

....

....

....

...

2,59

9,51

520

,860

2,31

6,78

624

9,73

012

,139

9.6

2,64

9,32

320

,146

1,05

8,86

71,

545,

260

25,0

5058

.365

and

over

....

....

....

..1,

572,

899

9,59

51,

251,

201

301,

798

10,3

0519

.21,

803,

247

12,5

9934

8,88

21,

431,

870

9,89

679

.475

and

over

....

....

....

..41

7,43

72,

362

300,

153

111,

812

3,11

026

.847

8,17

12,

938

58,9

5641

4,64

41,

633

86.7

1980

55to

64..

....

....

....

...

3,27

9,73

123

,881

3,01

5,92

819

1,39

948

,523

5.8

3,33

9,17

532

,654

1,61

8,49

01,

477,

193

210,

838

44.2

65an

dov

er..

....

....

....

2,18

8,60

919

,761

1,78

7,53

734

0,07

941

,232

15.5

2,58

1,30

726

,825

657,

722

1,76

4,13

213

2,62

868

.375

and

over

....

....

....

..68

8,42

27,

251

507,

540

159,

786

13,8

4523

.283

6,95

19,

420

144,

331

648,

026

35,1

7477

.4

1985

55to

64..

....

....

....

...

4,15

0,07

056

,189

3,77

1,23

726

4,78

857

,856

6.4

4,47

3,93

340

,512

2,04

1,87

32,

061,

647

329,

901

46.1

65an

dov

er..

....

....

....

2,61

8,92

226

,118

2,12

4,39

642

6,16

042

,248

16.3

2,95

4,02

621

,759

549,

132

2,21

3,24

516

9,89

074

.975

and

over

....

....

....

..72

9,00

55,

767

532,

776

178,

879

11,5

8324

.591

6,81

36,

372

90,5

1278

0,65

839

,271

85.1

1990

55to

64..

....

....

....

...

4,54

0,69

011

3,97

74,

088,

207

272,

502

66,0

046.

04,

817,

458

53,9

682,

655,

717

1,85

6,42

925

1,34

438

.565

and

over

....

....

....

..3,

142,

674

118,

932

2,51

8,40

744

9,03

856

,297

14.3

3,60

8,43

270

,754

1,02

1,49

72,

361,

881

154,

300

65.5

75an

dov

er..

....

....

....

867,

636

47,3

6460

6,68

119

3,90

219

,689

22.3

1,10

4,72

031

,098

194,

441

842,

176

37,0

0576

.2

Isra

el

1972

55to

64..

....

....

....

...

127,

355

3,59

611

6,91

54,

918

1,92

63.

913

4,12

03,

310

94,4

2032

,802

3,58

824

.565

and

over

....

....

....

..11

0,53

82,

677

88,7

1717

,656

1,48

816

.011

3,96

13,

430

41,6

0466

,832

2,09

558

.6

1983

55to

64..

....

....

....

...

141,

342

4,22

612

9,47

84,

393

3,24

53.

116

3,42

23,

530

119,

598

34,2

536,

041

21.0

65an

dov

er..

....

....

....

169,

283

4,03

013

7,30

224

,744

3,20

714

.619

2,01

94,

951

79,3

3610

2,41

15,

321

53.3

75an

dov

er..

....

....

....

60,4

651,

388

43,3

6614

,684

1,02

724

.367

,408

2,05

515

,846

47,9

821,

525

71.2


Table

7.

Mari

tal

Sta

tus

of

Old

er

Pers

on

sb

ySex:

Sele

cte

dYears

19

70

to1

99

5—

Con

.

Cou

ntry

,ye

ar,

and

age

Mal

esF

emal

es

Tota

lS

ingl

eM

arrie

dW

idow

edS

epar

ated

/di

vorc

edP

erce

ntw

idow

edTo

tal

Sin

gle

Mar

ried

Wid

owed

Sep

arat

ed/

divo

rced

Per

cent

wid

owed

Jap

an

1970

55to

64..

....

....

....

...

3,77

2,60

043

,100

3,47

8,00

019

8,50

053

,000

5.3

4,34

3,80

078

,400

2,72

2,20

01,

414,

300

128,

900

32.6

65an

dov

er..

....

....

....

3,22

6,90

032

,100

2,44

2,70

071

1,90

040

,200

22.1

4,10

7,70

048

,500

1,28

1,60

02,

704,

200

73,4

0065

.875

and

over

....

....

....

..87

6,60

08,

400

529,

800

329,

200

9,20

037

.61,

361,

100

14,2

0018

6,20

01,

141,

500

19,2

0083

.9

1985

55to

64..

....

....

....

...

5,78

4,98

210

9,14

15,

364,

533

191,

339

119,

969

3.3

6,60

9,45

326

3,40

04,

881,

645

1,18

1,84

328

2,56

517

.965

and

over

....

....

....

..5,

095,

746

47,2

094,

180,

133

797,

467

70,9

3715

.67,

351,

751

124,

142

2,69

4,77

84,

346,

636

186,

195

59.1

75an

dov

er..

....

....

....

1,81

3,50

913

,310

1,27

8,65

450

0,86

020

,685

27.6

2,88

7,62

232

,324

538,

231

2,26

5,12

651

,941

78.4

1990

55to

64..

....

....

....

...

6,99

0,98

517

6,50

46,

413,

813

221,

829

178,

839

3.2

7,41

0,53

531

2,82

05,

710,

590

1,07

1,49

331

5,63

214

.565

and

over

....

....

....

..5,

963,

891

64,3

654,

988,

364

823,

176

87,9

8613

.88,

810,

928

204,

089

3,56

9,89

44,

773,

326

263,

619

54.2

75an

dov

er..

....

....

....

2,22

0,23

417

,428

1,64

5,04

353

1,68

026

,083

23.9

3,68

6,49

353

,258

777,

384

2,77

6,36

179

,490

75.3

1995

55to

64..

....

....

....

...

7,51

8,56

927

2,59

16,

701,

187

227,

297

254,

228

3.0

7,91

0,02

032

5,15

66,

144,

309

1,03

0,40

437

3,26

113

.065

and

over

....

....

....

..7,

504,

253

105,

804

6,30

3,89

393

2,07

712

8,92

612

.410

,756

,569

321,

441

4,63

4,46

45,

391,

760

344,

639

50.1

75an

dov

er..

....

....

....

2,56

3,98

922

,958

1,93

6,33

156

7,38

930

,047

22.1

4,60

5,58

886

,456

1,01

0,94

43,

366,

835

106,

299

73.1

Mal

aysi

a

1970

55to

64..

....

....

....

...

251,

597

9,89

821

4,97

420

,924

5,80

18.

322

7,64

24,

287

122,

921

93,2

067,

228

40.9

65an

dov

er..

....

....

....

164,

368

9,38

411

9,93

829

,028

6,01

817

.715

2,48

93,

535

43,1

7999

,730

6,04

565

.4

1980

55to

64..

....

....

....

...

287,

996

8,65

425

5,70

918

,763

4,87

06.

529

9,08

05,

477

172,

777

104,

199

16,6

2734

.865

and

over

....

....

....

..23

3,96

58,

795

178,

027

40,2

056,

938

17.2

239,

300

5,08

871

,172

145,

507

17,5

3360

.8

1991

55to

64..

....

....

....

...

402,

570

9,85

236

8,46

520

,408

3,84

55.

141

9,47

38,

510

273,

984

124,

282

12,6

9729

.665

and

over

....

....

....

..30

5,24

45,

785

245,

931

48,5

125,

016

15.9

350,

597

4,97

012

6,99

620

4,69

313

,938

58.4

75an

dov

er..

....

....

....

98,5

291,

936

70,0

6024

,467

2,06

624

.812

0,09

81,

804

28,8

5884

,330

5,10

670

.2

Pak

ista

n

1972

55to

64..

....

....

....

...

1,68

3,11

880

,865

1,39

3,65

120

4,77

83,

824

12.2

1,27

3,40

020

,178

809,

238

440,

741

3,24

334

.665

and

over

....

....

....

..1,

478,

378

44,0

241,

079,

356

352,

154

2,84

423

.83,

234,

616

21,0

442,

030,

933

1,17

9,01

03,

629

36.4

75an

dov

er..

....

....

....

552,

803

18,0

4536

2,65

617

1,13

297

031

.041

9,93

19,

162

119,

092

290,

965

712

69.3

1981

55to

59..

....

....

....

...

859,

488

14,8

8479

4,80

148

,028

1,77

55.

675

1,36

97,

281

605,

383

136,

584

2,12

118

.260

and

over

....

....

....

..3,

313,

787

86,4

002,

831,

735

388,

411

7,24

111

.72,

419,

875

63,7

241,

200,

062

1,14

8,85

47,

235

47.5


Table

7.

Mari

tal

Sta

tus

of

Old

er

Pers

on

sb

ySex:

Sele

cte

dYears

19

70

to1

99

5—

Con

.

Cou

ntry

,ye

ar,

and

age

Mal

esF

emal

es

Tota

lS

ingl

eM

arrie

dW

idow

edS

epar

ated

/di

vorc

edP

erce

ntw

idow

edTo

tal

Sin

gle

Mar

ried

Wid

owed

Sep

arat

ed/

divo

rced

Per

cent

wid

owed

Ph

ilip

pin

es

1970

55to

64..

....

....

....

...

713,

283

20,1

1463

0,55

858

,108

4,50

38.

170

5,96

055

,312

461,

663

181,

836

7,14

925

.865

and

over

....

....

....

..50

4,46

413

,479

381,

080

106,

603

3,30

221

.152

5,33

938

,095

207,

556

276,

324

3,36

452

.6

1975

55to

64..

....

....

....

...

877,

576

40,7

2776

8,37

263

,484

4,99

37.

282

7,61

848

,835

580,

469

189,

778

8,53

622

.965

and

over

....

....

....

..60

4,96

433

,886

461,

399

105,

292

4,38

717

.459

5,71

142

,056

269,

671

277,

730

6,25

446

.6

1980

55to

64..

....

....

....

...

968,

578

29,2

5285

4,54

677

,289

7,49

18.

01,

029,

004

72,6

1669

3,84

625

0,47

012

,072

24.3

65an

dov

er..

....

....

....

792,

595

24,5

2061

6,18

514

6,46

55,

425

18.5

838,

298

69,6

0136

6,99

939

4,73

06,

968

47.1

75an

dov

er..

....

....

....

228,

270

8,05

115

4,00

364

,728

1,48

828

.424

6,43

721

,440

67,1

2615

6,11

51,

756

63.3

1990

55to

64..

....

....

....

...

1,25

2,03

338

,677

1,11

6,27

386

,573

10,5

106.

91,

313,

456

87,6

3789

2,94

931

5,34

417

,526

24.0

65an

dov

er..

....

....

....

948,

705

29,6

6973

8,41

217

3,75

36,

871

18.3

1,10

8,87

597

,039

467,

385

534,

591

9,86

048

.275

and

over

....

....

....

..30

7,42

210

,761

208,

594

85,9

652,

102

28.0

378,

595

38,1

6710

3,75

723

4,12

82,

543

61.8

Sin

gap

ore

1970

55to

64..

....

....

....

...

59,0

423,

531

50,3

144,

751

446

8.0

55,2

463,

133

28,8

9322

,784

436

41.2

65an

dov

er..

....

....

....

30,5

892,

147

21,6

216,

582

239

21.5

38,7

752,

161

8,78

727

,683

144

71.4

75an

dov

er..

....

....

....

5,84

045

33,

347

2,00

040

34.2

11,1

8752

71,

325

9,31

124

83.2

1980

55to

64..

....

....

....

...

66,7

843,

176

59,0

393,

749

820

5.6

64,3

082,

252

38,5

2022

,372

1,16

434

.865

and

over

....

....

....

..51

,202

2,35

038

,762

9,54

854

218

.662

,722

3,40

518

,485

40,3

3749

564

.375

and

over

....

....

....

..12

,036

579

7,70

23,

643

112

30.3

19,2

341,

030

2,99

915

,111

9478

.6

1990

55to

64..

....

....

....

...

90,5

005,

700

78,1

005,

500

1,20

06.

191

,400

3,20

060

,100

26,4

001,

700

28.9

65an

dov

er..

....

....

....

73,3

003,

700

54,2

0014

,800

600

20.2

89,0

003,

400

29,8

0055

,000

800

61.8

70an

dov

er..

....

....

....

44,0

002,

000

30,5

0011

,200

300

25.5

58,8

002,

500

15,6

0040

,300

400

68.5

So

uth

Ko

rea

1975

55to

64..

....

....

....

...

783,

671

1,09

572

8,83

150

,993

2,75

26.

589

2,96

51,

254

467,

699

420,

490

3,52

247

.165

and

over

....

....

....

..45

8,36

061

535

5,84

010

0,90

21,

003

22.0

748,

040

941

181,

991

563,

677

1,43

175

.4

1980

55to

64..

....

....

....

...

894,

976

1,91

283

4,59

555

,062

3,40

76.

21,

052,

347

1,46

656

5,99

548

0,35

14,

535

45.6

65an

dov

er..

....

....

....

539,

414

876

431,

132

106,

394

1,01

219

.790

6,57

191

322

0,23

668

3,93

71,

485

75.4

75an

dov

er..

....

....

....

116,

991

268

74,2

3442

,324

165

36.2

283,

692

286

32,9

6625

0,09

234

888

.2


Table

7.

Mari

tal

Sta

tus

of

Old

er

Pers

on

sb

ySex:

Sele

cte

dYears

19

70

to1

99

5—

Con

.

Cou

ntry

,ye

ar,

and

age

Mal

esF

emal

es

Tota

lS

ingl

eM

arrie

dW

idow

edS

epar

ated

/di

vorc

edP

erce

ntw

idow

edTo

tal

Sin

gle

Mar

ried

Wid

owed

Sep

arat

ed/

divo

rced

Per

cent

wid

owed

1995

55to

64..

....

....

....

...

1,59

6,59

15,

927

1,49

9,39

374

,968

16,3

034.

71,

810,

937

5,94

21,

186,

514

598,

709

19,7

7233

.165

and

over

....

....

....

..97

4,33

01,

808

815,

153

153,

578

3,79

115

.81,

665,

290

2,92

744

0,70

81,

215,

198

6,45

773

.075

and

over

....

....

....

..26

0,04

842

718

6,01

273

,003

606

28.1

573,

460

834

65,1

6550

6,33

41,

127

88.3

Sri

Lan

ka

1971

55to

64..

....

....

....

...

342,

783

25,2

1429

3,16

221

,899

2,50

86.

427

4,74

712

,435

177,

589

82,8

271,

896

30.1

65an

dov

er..

....

....

....

292,

430

22,0

3322

3,00

745

,656

1,73

415

.624

6,16

011

,096

100,

276

133,

899

889

54.4

1981

55to

64..

....

....

....

...

405,

454

25,7

7235

5,41

321

,676

2,59

35.

335

8,50

714

,579

244,

312

97,7

341,

882

27.3

65an

dov

er..

....

....

....

338,

873

22,7

7926

5,27

448

,884

1,93

614

.430

5,11

814

,813

136,

087

152,

809

1,40

950

.1

Th

aila

nd

1970

55to

64..

....

....

....

...

687,

607

25,3

3459

4,56

354

,016

13,6

947.

972

1,85

115

,945

434,

047

243,

036

28,8

2333

.765

and

over

....

....

....

..46

0,73

723

,922

333,

654

91,8

0811

,353

19.9

583,

995

11,5

9420

2,72

635

3,80

415

,871

60.6

1980

55to

64..

....

....

....

...

932,

326

15,3

6482

2,47

177

,139

17,3

528.

399

7,61

425

,938

613,

225

320,

551

37,9

0032

.165

and

over

....

....

....

..67

1,66

810

,201

501,

902

145,

231

14,3

3421

.685

3,18

817

,268

296,

823

517,

907

21,1

9060

.770

and

over

....

....

....

..38

6,27

55,

939

267,

797

103,

989

8,55

026

.952

8,19

110

,279

146,

404

360,

432

11,0

7668

.2

1990

55to

64..

....

....

....

...

1,62

7,82

252

,846

1,41

7,89

712

7,91

729

,162

7.9

1,72

3,07

556

,163

1,14

2,80

446

5,81

258

,296

27.0

65an

dov

er..

....

....

....

1,13

1,40

744

,519

835,

546

231,

174

20,1

6820

.41,

363,

274

30,2

0553

6,72

676

4,70

531

,638

56.1

70an

dov

er..

....

....

....

667,

111

27,4

0746

0,38

916

7,34

411

,971

25.1

860,

452

17,9

7327

4,95

655

0,12

017

,403

63.9

Turk

ey

1970

55to

64..

....

....

....

...

951,

639

16,6

9486

5,46

160

,010

9,47

46.

394

6,80

211

,550

638,

241

284,

091

12,9

2030

.065

and

over

....

....

....

..68

4,68

011

,572

549,

466

117,

734

5,90

817

.281

7,86

711

,765

308,

100

486,

917

11,0

8559

.5

1975

55to

64..

....

....

....

...

895,

135

32,2

2480

5,59

448

,186

9,13

15.

491

4,94

338

,931

614,

073

245,

626

16,3

1326

.865

and

over

....

....

....

..80

1,24

944

,047

619,

132

130,

474

7,59

616

.396

9,72

960

,407

388,

614

500,

981

19,7

2751

.7

1980

55to

64..

....

....

....

...

967,

439

22,1

2389

3,74

341

,817

9,75

64.

397

5,85

013

,164

693,

394

256,

682

12,6

1026

.365

and

over

....

....

....

..95

5,36

020

,399

752,

991

172,

800

9,17

018

.11,

157,

887

14,8

7148

1,67

164

8,20

813

,137

56.0

1985

55to

64..

....

....

....

...

1,38

0,06

628

,291

1,28

4,54

854

,261

12,9

663.

91,

398,

850

18,9

761,

017,

093

346,

272

16,5

0924

.865

and

over

....

....

....

..95

4,92

618

,470

748,

052

180,

204

8,20

018

.91,

170,

704

16,2

2347

5,64

266

7,26

911

,570

57.0


Table

7.

Mari

tal

Sta

tus

of

Old

er

Pers

on

sb

ySex:

Sele

cte

dYears

19

70

to1

99

5—

Con

.

Cou

ntry

,ye

ar,

and

age

Mal

esF

emal

es

Tota

lS

ingl

eM

arrie

dW

idow

edS

epar

ated

/di

vorc

edP

erce

ntw

idow

edTo

tal

Sin

gle

Mar

ried

Wid

owed

Sep

arat

ed/

divo

rced

Per

cent

wid

owed

1990

55to

64..

....

....

....

...

1,76

1,29

834

,446

1,65

0,09

959

,431

17,3

223.

41,

793,

326

22,0

371,

335,

717

413,

793

21,7

7923

.165

and

over

....

....

....

..1,

090,

850

20,9

6588

6,61

817

3,51

39,

754

15.9

1,32

5,94

318

,206

569,

358

724,

501

13,8

7854

.6

Lat

inA

mer

ica/

Car

ibb

ean

Arg

enti

na

1970

55to

64..

....

....

....

...

938,

600

118,

650

749,

600

49,9

5020

,400

5.3

992,

750

124,

750

614,

800

226,

800

26,4

0022

.865

and

over

....

....

....

..72

4,45

087

,850

493,

150

129,

950

13,5

0017

.987

6,70

011

0,85

030

8,40

044

5,75

011

,700

50.8

75an

dov

er..

....

....

....

208,

200

24,0

0011

7,30

064

,100

2,80

030

.829

1,50

036

,750

63,7

0018

8,65

02,

400

64.7

1980

55to

64..

....

....

....

...

1,09

0,96

511

6,15

989

6,47

450

,401

27,9

314.

61,

191,

687

133,

844

755,

984

262,

711

39,1

4822

.065

and

over

....

....

....

..98

7,98

210

7,11

770

6,28

115

5,41

919

,165

15.7

1,30

2,58

216

0,47

145

2,84

866

9,45

219

,811

51.4

70an

dov

er..

....

....

....

590,

415

64,4

9239

5,10

412

0,37

210

,447

20.4

826,

343

103,

444

222,

769

490,

740

9,39

059

.4

1991

55to

64..

....

....

....

...

1,12

9,07

712

0,78

388

8,80

957

,121

62,3

645.

11,

319,

846

127,

009

807,

549

296,

062

89,2

2622

.465

and

over

....

....

....

..1,

138,

581

110,

297

812,

425

174,

899

40,9

6015

.41,

627,

578

176,

108

522,

746

881,

156

47,5

6854

.175

and

over

....

....

....

..38

6,68

036

,748

243,

419

95,5

0611

,007

24.7

648,

202

74,7

6611

0,81

645

1,17

111

,449

69.6

Bra

zil

1970

55to

64..

....

....

....

...

2,08

0,90

611

7,99

21,

758,

355

133,

771

70,7

886.

42,

043,

382

175,

812

1,12

4,89

062

1,53

812

1,14

230

.465

and

over

....

....

....

..1,

396,

751

72,5

971,

015,

451

258,

351

50,3

5218

.51,

544,

432

140,

333

441,

444

893,

075

69,5

8057

.8

1980

55to

64..

....

....

....

...

2,70

9,66

214

3,38

02,

356,

365

132,

353

77,5

644.

92,

778,

572

231,

878

1,67

3,16

571

6,21

315

7,31

625

.865

and

over

....

....

....

..2,

199,

520

117,

384

1,66

8,83

134

7,74

965

,556

15.8

2,47

0,39

223

5,13

579

3,47

81,

356,

397

85,3

8254

.9

Ch

ile

1971

55to

64..

....

....

....

...

247,

633

24,5

3919

7,29

619

,359

6,43

97.

827

6,18

137

,411

151,

615

74,1

1413

,041

26.8

65an

dov

er..

....

....

....

201,

118

18,8

0213

6,28

741

,207

4,82

220

.525

1,02

737

,912

74,8

0313

1,43

36,

879

52.4

75an

dov

er..

....

....

....

60,6

755,

427

35,2

5818

,761

1,22

930

.986

,307

13,2

8815

,349

56,1

741,

496

65.1

1982

55to

64..

....

....

....

...

302,

711

31,2

9924

1,92

719

,558

9,92

76.

534

4,40

843

,255

203,

488

76,6

6920

,996

22.3

65an

dov

er..

....

....

....

287,

638

28,9

5419

7,50

852

,482

8,69

418

.237

1,87

953

,125

126,

330

178,

798

13,6

2648

.175

and

over

....

....

....

..92

,864

8,88

555

,420

26,0

752,

484

28.1

137,

260

21,1

0928

,832

83,9

843,

335

61.2

1992

55to

64..

....

....

....

...

406,

075

41,7

1632

3,12

620

,700

20,5

335.

146

2,02

658

,346

280,

729

88,2

2434

,727

19.1

65an

dov

er..

....

....

....

373,

449

37,6

5725

7,93

362

,475

15,3

8416

.750

3,59

563

,813

180,

658

235,

912

23,2

1246

.875

and

over

....

....

....

..13

2,29

212

,463

81,1

9734

,045

4,58

725

.720

7,62

327

,380

48,5

4712

5,07

06,

626

60.2


Table

7.

Mari

tal

Sta

tus

of

Old

er

Pers

on

sb

ySex:

Sele

cte

dYears

19

70

to1

99

5—

Con

.

Cou

ntry

,ye

ar,

and

age

Mal

esF

emal

es

Tota

lS

ingl

eM

arrie

dW

idow

edS

epar

ated

/di

vorc

edP

erce

ntw

idow

edTo

tal

Sin

gle

Mar

ried

Wid

owed

Sep

arat

ed/

divo

rced

Per

cent

wid

owed

Co

lom

bia

1973

55to

64..

....

....

....

...

395,

786

43,4

1431

6,83

626

,770

8,76

66.

840

3,63

469

,306

207,

199

111,

126

16,0

0327

.565

and

over

....

....

....

..29

9,48

431

,809

207,

661

53,0

656,

949

17.7

342,

120

60,8

7210

5,68

716

7,07

08,

491

48.8

1985

55to

59..

....

....

....

...

345,

873

26,7

6429

0,28

714

,411

14,4

114.

235

2,05

041

,175

203,

819

74,1

1632

,940

21.1

60an

dov

er..

....

....

....

784,

394

65,8

8158

6,75

110

0,88

030

,882

12.9

831,

744

107,

056

308,

816

364,

403

51,4

6943

.8

Co

sta

Ric

a

1973

55to

64..

....

....

....

...

39,3

514,

115

32,0

291,

909

1,29

84.

939

,167

6,45

823

,106

7,09

62,

507

18.1

65an

dov

er..

....

....

....

32,7

023,

599

22,6

425,

168

1,29

315

.833

,296

6,29

912

,145

13,5

481,

304

40.7

75an

dov

er..

....

....

....

10,8

071,

247

6,29

12,

851

418

26.4

11,5

442,

302

2,77

06,

202

270

53.7

1984

55to

64..

....

....

....

...

54,5

145,

213

45,0

031,

913

2,38

53.

556

,027

8,76

334

,001

8,52

24,

741

15.2

65an

dov

er..

....

....

....

52,0

415,

477

36,4

927,

570

2,50

214

.555

,933

9,85

221

,046

21,9

423,

093

39.2

Gu

atem

ala

1973

55to

64..

....

....

....

...

100,

058

8,15

983

,279

7,95

366

77.

994

,108

13,0

2353

,138

26,2

471,

700

27.9

65an

dov

er..

....

....

....

73,9

596,

582

51,9

7214

,867

538

20.1

74,8

0211

,814

24,6

5337

,424

911

50.0

75an

dov

er..

....

....

....

23,5

792,

097

14,3

167,

007

159

29.7

25,0

813,

993

5,52

415

,362

202

61.2

1981

55to

64..

....

....

....

...

125,

908

5,64

410

8,74

29,

040

2,48

27.

211

7,09

28,

227

70,3

5931

,774

6,73

227

.165

and

over

....

....

....

..93

,140

3,96

869

,588

17,3

152,

269

18.6

94,0

147,

839

33,0

9248

,828

4,25

551

.975

and

over

....

....

....

..32

,128

1,34

221

,124

8,91

574

727

.733

,955

2,97

17,

922

21,9

201,

142

64.6

1990

55to

64..

....

....

....

...

195,

354

7,86

317

2,36

210

,005

5,12

45.

119

9,17

47,

543

118,

131

56,0

7517

,425

28.2

65an

dov

er..

....

....

....

146,

250

3,22

811

6,37

923

,400

3,24

316

.015

9,00

63,

788

61,2

8583

,944

9,98

952

.8

Jam

aica

1970

55to

64..

....

....

....

...

53,8

0716

,138

34,4

152,

199

1,05

54.

150

,360

13,9

7427

,288

8,11

498

416

.165

and

over

....

....

....

..43

,594

11,3

8126

,398

5,02

878

711

.555

,256

20,4

2016

,128

18,1

0860

032

.8

1982

55to

64..

....

....

....

...

49,5

2115

,240

30,6

972,

050

1,53

44.

154

,979

17,4

6428

,053

7,97

71,

485

14.5

65an

dov

er..

....

....

....

61,4

2015

,029

36,8

747,

793

1,72

412

.773

,341

24,5

5024

,016

23,4

531,

322

32.0


Table

7.

Mari

tal

Sta

tus

of

Old

er

Pers

on

sb

ySex:

Sele

cte

dYears

19

70

to1

99

5—

Con

.

Cou

ntry

,ye

ar,

and

age

Mal

esF

emal

es

Tota

lS

ingl

eM

arrie

dW

idow

edS

epar

ated

/di

vorc

edP

erce

ntw

idow

edTo

tal

Sin

gle

Mar

ried

Wid

owed

Sep

arat

ed/

divo

rced

Per

cent

wid

owed

Mex

ico

1970

55to

64..

....

....

....

...

952,

598

55,6

3282

3,59

753

,600

19,7

695.

697

7,11

481

,251

623,

100

229,

334

43,4

2923

.565

and

over

....

....

....

..85

9,16

681

,679

645,

216

110,

833

21,4

3812

.993

2,23

912

0,54

039

2,10

638

2,91

936

,674

41.1

75an

dov

er..

....

....

....

271,

779

37,0

2217

7,07

450

,339

7,34

418

.532

8,79

054

,929

102,

390

159,

468

12,0

0348

.5

1980

55to

64..

....

....

....

...

1,27

3,53

265

,294

1,11

3,91

069

,869

24,4

595.

51,

304,

622

98,5

5686

0,34

528

6,55

059

,171

22.0

65an

dov

er..

....

....

....

1,20

3,23

862

,144

937,

252

179,

373

24,4

6914

.91,

353,

191

117,

562

617,

558

577,

993

40,0

7842

.7

1990

55to

64..

....

....

....

...

1,67

5,14

082

,527

1,47

7,32

379

,133

36,1

574.

71,

797,

342

125,

817

1,22

6,03

235

6,23

289

,261

19.8

65an

dov

er..

....

....

....

1,55

6,11

477

,296

1,20

6,94

123

4,19

137

,686

15.0

1,76

6,37

913

9,19

579

6,04

076

6,93

764

,207

43.4

Per

u

1972

55to

64..

....

....

....

...

280,

616

20,8

1622

7,27

826

,798

5,72

49.

528

8,57

832

,227

169,

416

77,6

449,

291

26.9

65an

dov

er..

....

....

....

235,

807

18,5

4516

1,29

051

,956

4,01

622

.027

9,07

935

,798

98,5

9113

9,36

35,

327

49.9

70an

dov

er..

....

....

....

147,

746

12,5

4994

,501

38,4

272,

269

26.0

182,

453

24,6

3054

,489

100,

448

2,88

655

.1

1981

55to

64..

....

....

....

...

368,

119

23,4

2830

7,24

929

,661

7,78

18.

136

3,54

230

,159

232,

596

86,2

5014

,537

23.7

65an

dov

er..

....

....

....

323,

413

19,8

9723

1,32

965

,962

6,22

520

.435

6,48

830

,420

139,

776

176,

824

9,46

849

.6

Uru

gu

ay

1975

55to

64..

....

....

....

...

125,

100

17,7

0097

,000

5,10

05,

300

4.1

132,

000

17,5

0079

,500

27,5

007,

500

20.8

65an

dov

er..

....

....

....

118,

100

14,8

0081

,100

17,5

004,

700

14.8

150,

500

23,1

0047

,600

74,5

005,

300

49.5

75an

dov

er..

....

....

....

37,5

004,

700

21,9

009,

700

1,20

025

.959

,100

9,90

010

,900

36,7

001,

600

62.1

1985

55to

64..

....

....

....

...

141,

422

17,7

9011

0,43

35,

090

8,10

93.

615

5,86

215

,924

95,9

5031

,577

12,4

1120

.365

and

over

....

....

....

..13

8,39

716

,131

97,2

0818

,833

6,22

513

.619

1,26

524

,851

61,4

4096

,336

8,63

850

.475

and

over

....

....

....

..49

,013

5,32

730

,593

11,2

251,

868

22.9

79,2

1811

,440

14,4

5150

,854

2,47

364

.2

Not

e:D

ata

for

‘‘Mar

ried’

’inc

lude

peop

leliv

ing

inco

nsen

sual

unio

ns.

Dat

afo

rC

zech

Rep

ublic

prio

rto

1991

refe

rto

Cze

chos

lova

kia.

Sou

rce:

U.S

.C

ensu

sB

urea

u,20

00a.


Table 8.Support Ratios: 2000, 2015, and 2030

CountryTotal1 Youth2 Elderly3 Oldest old4

2000 2015 2030 2000 2015 2030 2000 2015 2030 2000 2015 2030

United States . . . . . . . . . . 70 70 87 48 45 49 21 25 37 26 26 26Western EuropeAustria . . . . . . . . . . . . . . . . . . 62 61 77 37 31 32 25 30 45 22 26 28Belgium . . . . . . . . . . . . . . . . . 68 68 83 39 35 36 28 33 46 21 29 29Denmark . . . . . . . . . . . . . . . . 63 71 79 39 39 38 24 32 41 27 24 31France . . . . . . . . . . . . . . . . . . 71 71 81 43 39 38 27 32 44 23 31 31Germany . . . . . . . . . . . . . . . . 60 64 80 34 31 33 26 33 46 22 27 28Greece . . . . . . . . . . . . . . . . . . 64 66 74 36 32 30 28 34 44 20 30 31Italy . . . . . . . . . . . . . . . . . . . . . 60 65 75 31 28 26 29 36 49 22 30 32Luxembourg . . . . . . . . . . . . . 63 64 73 40 39 39 23 25 34 21 27 26Norway. . . . . . . . . . . . . . . . . . 70 70 80 44 41 40 26 30 40 29 26 30Sweden . . . . . . . . . . . . . . . . . 71 70 82 41 34 36 29 36 46 29 27 34United Kingdom . . . . . . . . . . 69 68 80 43 37 37 27 31 42 25 27 30

Eastern EuropeBulgaria . . . . . . . . . . . . . . . . . 64 58 69 37 26 25 27 32 44 13 23 28Czech Republic . . . . . . . . . . 59 58 68 37 28 27 22 30 42 17 22 30Hungary . . . . . . . . . . . . . . . . . 61 58 66 38 30 29 24 28 37 17 24 28Poland . . . . . . . . . . . . . . . . . . 67 56 71 46 33 33 20 23 38 17 25 25Russia . . . . . . . . . . . . . . . . . . 64 54 70 43 33 35 21 21 35 16 23 20Ukraine. . . . . . . . . . . . . . . . . . 65 57 68 42 34 35 23 24 33 16 21 21

North America/OceaniaAustralia. . . . . . . . . . . . . . . . . 67 67 77 46 40 40 21 26 37 24 26 28Canada . . . . . . . . . . . . . . . . . 63 62 78 42 35 37 21 26 41 25 27 27New Zealand. . . . . . . . . . . . . 69 65 69 49 42 39 19 23 30 25 26 28

AfricaEgypt . . . . . . . . . . . . . . . . . . . 97 73 65 90 64 51 7 9 13 10 12 14Kenya. . . . . . . . . . . . . . . . . . . 139 90 70 133 83 61 7 7 9 13 17 21Liberia . . . . . . . . . . . . . . . . . . 133 139 115 125 129 106 8 10 9 17 21 25Malawi . . . . . . . . . . . . . . . . . . 149 115 84 142 109 78 7 7 6 10 13 17Morocco. . . . . . . . . . . . . . . . . 103 73 67 93 64 51 9 9 15 14 17 15Tunisia . . . . . . . . . . . . . . . . . . 87 58 59 76 46 39 11 12 20 13 20 18Zimbabwe . . . . . . . . . . . . . . . 134 98 84 126 88 72 8 10 12 15 20 28

AsiaBangladesh . . . . . . . . . . . . . . 112 70 61 105 63 49 7 7 12 15 13 13China . . . . . . . . . . . . . . . . . . . 67 56 65 56 41 39 12 15 26 13 18 18India . . . . . . . . . . . . . . . . . . . . 94 73 67 85 63 52 9 10 15 13 14 16Indonesia . . . . . . . . . . . . . . . . 82 69 65 74 58 47 8 11 18 10 17 16Israel. . . . . . . . . . . . . . . . . . . . 86 76 73 67 56 48 18 20 26 24 27 26Japan . . . . . . . . . . . . . . . . . . . 61 78 82 33 34 31 27 44 52 22 28 39Malaysia. . . . . . . . . . . . . . . . . 96 81 79 88 70 62 8 11 17 14 14 17Pakistan. . . . . . . . . . . . . . . . . 126 87 68 117 79 57 9 8 11 13 15 14Philippines. . . . . . . . . . . . . . . 105 85 73 98 76 60 7 9 13 14 15 16Singapore . . . . . . . . . . . . . . . 46 42 54 36 30 31 10 12 23 21 24 20South Korea . . . . . . . . . . . . . 58 58 68 47 40 35 11 18 33 14 19 21Sri Lanka . . . . . . . . . . . . . . . . 75 62 66 64 46 40 11 15 25 16 18 20Thailand. . . . . . . . . . . . . . . . . 65 60 66 54 44 38 11 16 27 14 18 19Turkey . . . . . . . . . . . . . . . . . . 83 60 60 72 47 40 11 13 21 15 20 19

Latin America/CaribbeanArgentina . . . . . . . . . . . . . . . . 84 76 71 65 55 46 19 21 25 22 26 27Brazil . . . . . . . . . . . . . . . . . . . 80 64 64 71 51 42 10 13 22 15 19 21Chile . . . . . . . . . . . . . . . . . . . . 77 65 70 64 47 42 13 18 28 17 19 22Colombia . . . . . . . . . . . . . . . . 86 73 73 77 61 53 9 11 20 12 16 16Costa Rica. . . . . . . . . . . . . . . 90 67 66 80 55 45 10 12 21 18 19 19Guatemala. . . . . . . . . . . . . . . 132 109 88 123 101 78 8 9 11 14 18 18Jamaica . . . . . . . . . . . . . . . . . 89 61 60 76 49 40 13 12 20 22 24 19Mexico . . . . . . . . . . . . . . . . . . 95 73 67 87 62 50 8 11 17 15 17 19Peru . . . . . . . . . . . . . . . . . . . . 99 75 68 90 64 51 9 11 17 15 18 19Uruguay . . . . . . . . . . . . . . . . . 82 79 77 59 55 50 24 24 28 21 28 28

1Total support ratio is the number of people 0 to 19 years and 65 years and over per 100 people 20 to 64 years.2Youth support ratio is the number of people 0 to 19 years per 100 people 20 to 64 years.3Elderly support ratio is the number of people 65 years and over per 100 people 20 to 64 years.4Oldest old support ratio is the number of people 80 years and over per 100 people 65 years and over.

Note: Youth and elderly ratios may not sum to total due to rounding.Source: U.S. Census Bureau, 2000a.


Table 9.Parent Support Ratios: 1950, 2000, and 2030

CountryParent support ratio Parent support ratio for females

1950 2000 2030 1950 2000 2030

United States . . . . . . . . . . . . . . . . . . . . . . . . . 8 22 33 16 43 63

Western EuropeAustria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 20 33 12 39 66Belgium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 21 38 16 41 75Denmark . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 21 36 16 42 72France . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 23 39 18 46 78Germany . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 19 36 11 37 72Greece. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 20 34 17 39 67Italy. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 22 37 14 43 73Luxembourg . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 18 28 16 37 54Norway . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 27 35 21 54 69Sweden . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 27 45 18 54 90United Kingdom . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 23 36 17 46 73

Eastern EuropeBulgaria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 11 30 11 22 57Czech Republic . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 13 30 12 25 60Hungary. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 14 27 10 26 52Poland . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 14 27 11 26 53Russia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 13 21 14 23 39Ukraine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 13 21 17 23 38

North America/OceaniaAustralia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 19 32 15 39 64Canada . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 20 33 18 40 66New Zealand . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 20 26 16 39 51

AfricaEgypt . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 4 7 4 8 15Kenya. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 6 11 7 12 22Liberia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 8 14 6 15 26Malawi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 4 9 7 8 16Morocco. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 9 9 5 16 18Tunisia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 9 12 21 17 23Zimbabwe . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 9 30 6 17 65

AsiaBangladesh. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 7 7 6 14 13China . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 8 14 5 16 28India . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 6 9 6 13 19Indonesia. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 5 10 9 9 19Israel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 20 24 7 39 48Japan. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 18 50 9 34 100Malaysia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 6 12 18 12 23Pakistan. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 7 7 11 15 15Philippines. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 6 9 9 12 18Singapore . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 13 14 12 25 27South Korea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 7 19 5 14 38Sri Lanka. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 9 16 20 17 30Thailand. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 8 15 9 14 30Turkey . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 9 12 5 18 25

Latin America/CaribbeanArgentina. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 17 24 9 34 47Brazil . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 8 15 8 15 29Chile. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 10 21 9 19 41Colombia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 6 12 11 12 22Costa Rica . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 10 15 16 20 29Guatemala . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 7 10 7 14 19Jamaica . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 18 12 7 34 24Mexico . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 7 11 12 14 21Peru . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 8 12 7 16 24Uruguay. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 20 26 23 37 51

Note: The parent support ratio is the number of people aged 80 and over per 100 people aged 50 to 64. The parent support ratio forfemales is the number of people aged 80 and over per 100 women aged 50 to 64.



Table

10

.Lab

or

Forc

ePart

icip

ati

on

Rate

sb

yA

ge

an

dSex:

Sele

cte

dYears

19

70

to1

99

9

Cou

ntry

Year

Mal

esF

emal

es

25to

44ye

ars

45to

49ye

ars

50to

54ye

ars

55to

59ye

ars

60to

64ye

ars

65ye

ars

and

over

25to

44ye

ars

45to

49ye

ars

50to

54ye

ars

55to

59ye

ars

60to

64ye

ars

65ye

ars

and

over

Uni

ted

Sta

tes

....

....

....

....

.19

7094

.393

.591

.486

.873

.024

.847

.553

.052

.047

.436

.110

.019

8093

.492

.088

.580

.660

.419

.364

.861

.556

.348

.434

.08.

219

8292

.292

.090

.181

.157

.917

.769

.065

.359

.250

.234

.27.

919

9193

.992

.288

.479

.054

.815

.874

.975

.467

.855

.735

.18.

619

9692

.890

.886

.977

.954

.316

.976

.478

.071

.959

.838

.28.

619

9993

.090

.387

.078

.454

.816

.976

.878

.974

.061

.838

.88.

9

Wes

tern

Eu

rop

e

Aus

tria

....

....

....

....

....

....

.19

7197

.195

.892

.783

.744

.98.

052

.853

.748

.535

.813

.23.

219

8196

.596

.391

.577

.323

.33.

162

.257

.353

.532

.49.

51.

819

8895

.094

.790

.065

.314

.21.

863

.959

.451

.624

.65.

70.

919

9693

.694

.386

.663

.716

.74.

676

.769

.259

.325

.48.

72.

0

Bel

gium

....

....

....

....

....

....

1970

96.2

92.2

89.2

82.3

79.3

6.8

39.1

30.8

27.6

20.0

7.6

2.2

1977

96.8

92.4

87.7

79.2

42.1

4.2

51.1

33.3

27.3

18.6

5.8

1.2

1981

94.5

90.8

85.7

70.7

32.3

3.3

60.1

38.2

30.7

17.3

5.7

1.0

1997

94.4

90.5

81.6

49.2

18.4

1.9

77.0

59.5

44.2

21.8

4.6

0.7

1999

94.7

91.1

80.3

52.4

18.6

162.

879

.365

.048

.527

.66.

7160.

8

Den

mar

k..

....

....

....

....

....

.19

7093

.496

.394

.891

.181

.323

.555

.554

.449

.539

.824

.94.

619

7694

.393

.991

.687

.779

.324

.071

.765

.658

.347

.530

.14.

819

7996

.696

.193

.390

.862

.016

.384

.276

.166

.954

.832

.54.

319

8694

.192

.787

.481

.249

.612

.887

.981

.972

.960

.526

.63.

319

9693

.291

.587

.781

.242

.01218

.584

.782

.372

.758

.720

.5128.

7

Fra

nce

....

....

....

....

....

....

.19

7596

.295

.492

.181

.854

.610

.755

.049

.448

.242

.127

.95.

019

8295

.594

.990

.976

.939

.15.

066

.658

.354

.145

.022

.32.

219

8495

.495

.090

.870

.029

.94.

371

.361

.054

.141

.418

.02.

119

9096

.195

.991

.668

.618

.12.

877

.271

.863

.246

.816

.71.

519

9695

.895

.092

.670

.416

.42.

381

.380

.971

.551

.715

.22.

0

Ger

man

y..

....

....

....

....

....

.19

7096

.795

.993

.286

.868

.816

.047

.448

.342

.834

.517

.75.

719

8096

.196

.893

.382

.344

.27.

457

.152

.247

.238

.713

.03.

019

8894

.196

.493

.279

.834

.54.

964

.660

.953

.741

.111

.11.

819

9692

.994

.590

.473

.928

.74.

474

.874

.767

.450

.511

.31.

619

9993

.894

.590

.576

.530

.34.

577

.178

.370

.555

.312

.71.

6

Gre

ece

....

....

....

....

....

....

.19

7193

.8191

.7(N

A)

275

.3(N

A)

33.4

30.9

127

.9(N

A)

219

.8(N

A)

8.4

1981

96.8

95.1

90.0

81.1

61.7

26.2

33.4

28.9

25.8

20.0

13.4

5.0

1987

90.1

98.0

84.2

74.3

53.5

14.0

52.2

43.9

37.2

29.3

22.0

5.1

1997

96.2

95.2

89.2

75.0

47.8

10.7

64.4

49.9

39.3

30.7

20.3

3.4

1998

96.2

94.3

86.7

71.7

45.4

9.7

66.2

51.7

40.4

28.1

21.2

3.6

Italy

....

....

....

....

....

....

....

1971

95.5

92.1

87.2

75.0

40.6

13.4

31.8

29.7

26.3

16.9

9.9

3.2

1981

96.2

93.2

85.7

65.1

29.1

6.9

49.8

36.2

30.2

16.9

8.0

1.5

1989

95.6

95.6

87.5

67.8

35.2

7.9

59.5

44.7

34.1

20.2

9.8

2.2

1996

91.2

93.1

79.3

58.9

30.6

6.0

59.8

49.0

37.1

21.5

8.2

1.8

1998

91.7

93.5

80.1

54.1

31.7

6.3

60.8

50.9

38.7

22.7

8.1

1.7


Table

10

.Lab

or

Forc

ePart

icip

ati

on

Rate

sb

yA

ge

an

dSex:

Sele

cte

dYears

19

70

to1

99

9—

Con

.

Cou

ntry

Year

Mal

esF

emal

es

25to

44ye

ars

45to

49ye

ars

50to

54ye

ars

55to

59ye

ars

60to

64ye

ars

65ye

ars

and

over

25to

44ye

ars

45to

49ye

ars

50to

54ye

ars

55to

59ye

ars

60to

64ye

ars

65ye

ars

and

over

Luxe

mbo

urg

....

....

....

....

....

1970

98.0

95.9

91.4

79.3

45.5

10.1

26.3

23.9

22.1

18.6

12.0

4.0

1981

97.4

96.0

90.0

54.3

28.0

6.5

46.4

30.3

25.6

20.1

12.4

2.8

1987

96.0

96.0

90.2

55.4

21.2

3.8

53.4

36.4

28.7

18.6

10.3

1.0

1996

95.7

95.0

84.0

52.7

16.7

2.5

61.3

49.0

35.6

14.9

5.1

0.9

1999

95.1

94.7

87.1

53.4

15.5

1.9

65.6

60.3

44.1

24.6

11.7

0.6

Nor

way

....

....

....

....

....

....

1970

396

.1495

.7591

.4(N

A)

673

.6715

.7342

.9448

.7546

.8(N

A)

628

.073.

719

80394

.3493

.3587

.7(N

A)

662

.7712

.6367

.8474

.0561

.0(N

A)

632

.272.

919

8595

.395

.291

.786

.472

.7827

.175

.778

.272

.660

.035

.9814

.019

8993

.793

.890

.583

.264

.923

.678

.982

.075

.863

.244

.111

.819

9692

.691

.990

.583

.262

.516

.581

.983

.279

.168

.348

.99.

319

9992

.392

.289

.284

.861

.1813

.483

.285

.980

.171

.349

.588.

8

Sw

eden

....

....

....

....

....

....

1970

90.0

92.9

91.9

88.4

75.7

15.2

49.6

55.0

50.3

41.1

25.7

3.2

1975

91.9

92.2

90.2

85.5

68.5

11.0

68.2

74.8

68.8

57.7

35.1

3.5

1980

90.6

92.0

89.8

84.4

65.9

8.1

77.0

82.9

77.8

66.4

41.4

2.6

1985

90.6

92.1

90.3

85.3

63.2

11.3

85.6

87.5

83.1

72.5

45.6

3.1

1996

89.6

92.0

89.6

83.3

59.7

(NA

)84

.289

.987

.678

.449

.8(N

A)

1999

88.7

90.7

89.2

84.4

55.5

(NA

)83

.488

.185

.679

.046

.5(N

A)

Uni

ted

Kin

gdom

....

....

....

....

.19

7198

.098

.197

.195

.186

.419

.450

.461

.358

.950

.727

.86.

419

8197

.597

.395

.791

.574

.610

.759

.468

.563

.552

.022

.53.

719

8693

.9191

.6(N

A)

80.3

53.4

7.5

66.9

169

.9(N

A)

51.5

18.8

2.7

1993

94.5

92.8

88.1

75.7

52.2

7.4

73.5

77.9

70.0

54.5

24.7

3.5

1999

1092

.6(N

A)

1744

.7(N

A)

(NA

)(N

A)

1076

.6(N

A)

1728

.2(N

A)

(NA

)(N

A)

Eas

tern

Eu

rop

e

Bul

garia

....

....

....

....

....

....

1975

96.8

95.7

92.0

86.5

33.6

10.3

92.7

86.4

75.4

26.1

8.2

1.7

1985

96.4

94.6

88.1

80.9

39.2

15.2

95.3

91.0

83.6

32.0

16.5

4.3

1992

94.4

91.9

84.6

58.0

11.1

4.5

93.7

92.9

75.5

10.7

4.7

2.1

Cze

chR

epub

lic..

....

....

....

...

1970

98.3

96.0

93.2

85.0

33.3

14.6

79.7

77.3

70.1

36.5

18.2

5.2

1980

98.2

96.0

92.7

84.2

46.3

19.5

91.8

88.1

79.9

40.8

21.5

6.5

1991

97.9

95.5

91.5

80.0

28.4

11.6

95.1

93.4

85.7

31.1

16.2

4.9

1997

96.9

94.5

89.8

77.2

30.3

8.9

79.9

90.4

82.3

35.0

13.3

2.7

1999

96.5

94.9

90.1

77.1

27.5

7.2

79.9

90.8

81.5

33.2

12.9

2.7

Hun

gary

....

....

....

....

....

....

1970

98.1

95.4

91.8

84.4

43.7

16.7

68.6

64.0

56.6

29.2

17.1

5.8

1980

97.7

92.9

86.2

72.2

13.2

4.0

79.2

77.5

67.4

18.8

8.7

2.9

1996

90.0

83.1

70.0

46.1

9.2

4.3

69.8

76.1

55.4

15.5

6.0

2.1

1999

88.0

81.2

72.5

45.9

10.6

83.

870

.475

.361

.916

.65.

581.

6

Pol

and

....

....

....

....

....

....

.19

7096

.695

.194

.090

.983

.056

.478

.379

.275

.968

.151

.133

.019

7896

.192

.187

.181

.562

.434

.979

.278

.571

.657

.937

.419

.419

9692

.985

.176

.855

.233

.415

.379

.579

.163

.135

.019

.28.

5

Rus

sia

....

....

....

....

....

....

.19

8997

.395

.891

.779

.335

.414

.293

.893

.783

.834

.820

.46.

419

921092

.1(N

A)

93.9

80.5

38.1

1320

.71088

.9(N

A)

83.6

43.0

21.0

1311

.019

961090

.1(N

A)

87.4

74.2

1419

.0(N

A)

1082

.0(N

A)

71.3

30.9

147.

2(N

A)

1999

91.0

88.6

85.3

65.2

29.2

6.4

84.4

86.8

78.9

33.7

16.0

2.5


Table

10

.Lab

or

Forc

ePart

icip

ati

on

Rate

sb

yA

ge

an

dSex:

Sele

cte

dYears

19

70

to1

99

9—

Con

.

Cou

ntry

Year

Mal

esF

emal

es

25to

44ye

ars

45to

49ye

ars

50to

54ye

ars

55to

59ye

ars

60to

64ye

ars

65ye

ars

and

over

25to

44ye

ars

45to

49ye

ars

50to

54ye

ars

55to

59ye

ars

60to

64ye

ars

65ye

ars

and

over

Ukr

aine

....

....

....

....

....

....

1989

97.3

95.6

89.9

78.2

32.0

10.9

93.4

93.3

86.0

29.5

15.3

4.5

1995

387

.8497

.988

.582

.21534

.3(N

A)

384

.6498

.982

.745

.81522

.1(N

A)

1999

89.2

86.3

76.4

69.7

28.3

89.

883

.384

.370

.133

.416

.786.

0

No

rth

Am

eric

a/O

cean

ia

Aus

tral

ia..

....

....

....

....

....

.19

7194

.8193

.0(N

A)

88.4

75.6

22.2

41.5

140

.0(N

A)

28.3

16.0

4.2

1976

95.9

94.5

91.9

86.9

68.4

16.8

53.3

55.2

46.2

35.2

18.2

5.1

1981

94.8

92.5

89.4

81.3

53.1

12.3

56.2

56.5

46.3

32.8

15.5

4.9

1986

92.1

89.8

85.7

76.4

44.8

9.0

59.0

58.2

46.4

30.9

13.6

3.0

1997

92.6

187

.3(N

A)

72.3

45.7

10.1

69.8

168

.5(N

A)

41.9

18.9

2.9

1999

91.8

89.5

85.1

72.5

46.7

9.6

69.5

73.8

65.0

44.6

18.3

3.1

Can

ada

....

....

....

....

....

....

1971

92.7

91.3

89.1

84.9

74.1

23.6

44.2

45.4

43.3

38.7

29.1

8.3

1976

91.6

90.7

88.0

82.4

69.1

19.2

53.8

51.7

46.9

39.5

27.6

6.9

1981

95.3

93.6

90.9

84.4

68.8

17.3

65.2

59.6

52.1

41.9

28.3

6.0

1986

94.9

93.3

89.9

81.3

59.9

14.6

73.0

67.1

57.9

44.7

27.5

4.7

1996

91.8

90.8

86.8

72.5

44.7

10.3

78.1

76.3

66.2

48.9

23.8

3.5

1999

92.1

91.1

86.1

72.2

46.6

9.9

79.9

78.6

70.6

50.6

26.0

3.4

New

Zea

land

....

....

....

....

...

1971

98.4

98.0

96.3

92.1

69.2

21.3

33.2

40.0

35.2

27.5

15.5

3.5

1976

98.1

97.7

95.9

90.5

57.9

16.2

40.2

46.6

40.6

29.0

13.9

2.8

1981

96.0

95.8

94.1

87.5

45.7

10.9

45.3

52.5

43.7

30.9

11.7

1.9

1989

94.4

93.3

91.9

78.1

33.8

10.6

67.6

75.8

69.8

47.1

14.4

3.5

1992

93.4

94.2

89.5

80.0

33.5

8.8

69.2

79.7

65.7

49.9

15.7

2.9

1997

87.3

90.5

88.5

79.2

50.5

8.9

67.1

77.5

74.2

53.2

29.3

3.0

1999

89.0

90.7

88.4

81.2

57.4

10.4

71.1

79.9

73.6

60.1

32.5

3.9

Afr

ica

Egy

pt..

....

....

....

....

....

....

1976

97.6

99.0

98.0

96.0

77.9

40.9

7.5

3.5

3.1

2.8

2.2

1.0

1986

96.2

94.2

91.3

88.8

68.3

25.5

13.2

6.0

4.3

3.4

2.0

0.7

1995

1089

.3(N

A)

597

.9(N

A)

76.4

36.5

1027

.8(N

A)

516

.0(N

A)

6.6

2.1

1998

1091

.4(N

A)

598

.3(N

A)

61.8

33.5

1024

.7(N

A)

515

.4(N

A)

6.5

2.1

Libe

ria..

....

....

....

....

....

...

1974

86.8

91.8

90.4

89.6

80.3

66.0

28.8

33.9

31.4

30.4

23.7

16.2

1984

84.3

92.7

91.3

90.5

85.8

69.7

55.5

63.9

62.8

59.1

49.5

32.5

Mal

awi.

....

....

....

....

....

....

1977

95.3

196

.1(N

A)

294

.4(N

A)

83.6

67.4

172

.6(N

A)

269

.9(N

A)

55.3

1987

97.5

98.2

96.8

94.3

94.2

85.3

89.9

90.5

89.4

89.8

84.3

71.9

Mor

occo

....

....

....

....

....

....

1971

95.8

94.5

91.6

88.9

63.3

33.5

11.3

15.0

18.9

22.5

7.7

3.8

1982

97.1

96.6

93.3

89.5

68.9

42.1

17.9

14.1

14.6

14.6

11.2

5.3

1990

94.3

1190

.3(N

A)

(NA

)938

.1(N

A)

32.5

1117

.1(N

A)

(NA

)98.

9(N

A)

1995

96.0

1190

.1(N

A)

(NA

)933

.5(N

A)

38.5

1119

.0(N

A)

(NA

)97.

7(N

A)

1999

95.0

1190

.0(N

A)

(NA

)943

.7(N

A)

35.4

1130

.1(N

A)

(NA

)913

.0(N

A)


Table

10

.Lab

or

Forc

ePart

icip

ati

on

Rate

sb

yA

ge

an

dSex:

Sele

cte

dYears

19

70

to1

99

9—

Con

.

Cou

ntry

Year

Mal

esF

emal

es

25to

44ye

ars

45to

49ye

ars

50to

54ye

ars

55to

59ye

ars

60to

64ye

ars

65ye

ars

and

over

25to

44ye

ars

45to

49ye

ars

50to

54ye

ars

55to

59ye

ars

60to

64ye

ars

65ye

ars

and

over

Tuni

sia

....

....

....

....

....

....

.19

7597

.997

.394

.286

.066

.538

.016

.814

.113

.011

.38.

64.

819

8496

.996

.292

.882

.159

.238

.523

.012

.911

.69.

84.

43.

519

9494

.395

.690

.178

.354

.631

.526

.817

.612

.69.

67.

33.

319

9795

.495

.690

.478

.454

.134

.029

.221

.614

.412

.27.

73.

5

Zim

babw

e..

....

....

....

....

....

1969

69.8

61.3

52.5

49.1

43.1

24.9

11.8

10.2

9.8

9.2

9.0

2.7

1982

93.8

93.9

92.5

90.4

969

.1(N

A)

50.3

52.4

50.6

50.7

931

.5(N

A)

1992

96.0

95.1

92.2

88.8

77.5

52.0

51.3

54.0

49.7

47.1

40.0

21.7

Asi

a

Ban

glad

esh

....

....

....

....

....

.19

7497

.9198

.3(N

A)

295

.2(N

A)

84.2

3.0

13.

6(N

A)

24.

0(N

A)

3.3

1981

92.4

93.6

90.6

90.7

84.7

68.7

4.7

4.4

4.7

4.4

4.5

3.6

1986

99.4

99.7

99.3

98.0

93.4

70.4

10.6

10.3

10.8

9.8

9.0

10.9

1995

98.2

99.2

98.4

96.6

88.9

71.2

61.2

58.9

57.1

49.6

41.1

27.1

Chi

na..

....

....

....

....

....

....

1982

98.7

97.5

91.4

83.0

63.7

30.1

87.8

70.6

50.9

32.9

16.9

4.7

1990

98.9

97.9

93.5

83.9

63.7

33.6

90.8

81.1

62.0

45.1

27.4

8.4

Indi

a..

....

....

....

....

....

....

.19

71396

.0497

.1594

.0(N

A)

973

.8(N

A)

320

.8422

.4519

.4(N

A)

910

.5(N

A)

1981

1096

.1(N

A)

593

.3(N

A)

965

.0(N

A)

1034

.8(N

A)

529

.8(N

A)

914

.0(N

A)

1991

1095

.3(N

A)

592

.6(N

A)

671

.4742

.31039

.5(N

A)

535

.5(N

A)

620

.878.

2

Indo

nesi

a..

....

....

....

....

....

.19

7194

.293

.490

.686

.079

.362

.939

.945

.443

.540

.535

.224

.519

7698

.297

.596

.392

.487

.569

.755

.162

.260

.954

.148

.431

.219

8094

.394

.190

.084

.676

.753

.440

.546

.844

.340

.832

.919

.019

8897

.197

.895

.489

.179

.256

.359

.963

.660

.755

.646

.125

.419

9296

.897

.693

.889

.679

.756

.855

.460

.557

.752

.242

.725

.119

9698

.01199

.6(N

A)

(NA

)87

.956

.157

.91161

.4(N

A)

(NA

)42

.726

.319

9997

.298

.095

.787

.6966

.5(N

A)

57.7

62.2

60.0

54.3

934

.0(N

A)

Isra

el..

....

....

....

....

....

....

1972

90.7

192

.7(N

A)

286

.3(N

A)

34.5

35.9

133

.8(N

A)

223

.7(N

A)

7.2

1983

88.5

91.5

89.1

84.2

78.2

32.2

57.6

51.1

43.2

36.7

22.0

9.2

1989

86.0

189

.3(N

A)

78.6

66.3

21.4

60.5

153

.1(N

A)

39.0

19.0

6.3

1996

84.4

187

.4(N

A)

75.9

59.0

16.9

65.1

165

.8(N

A)

44.7

19.9

5.1

1999

83.0

186

.5(N

A)

74.3

56.4

14.6

67.5

169

.2(N

A)

47.6

23.6

4.6

Japa

n..

....

....

....

....

....

....

1970

98.4

98.1

97.3

94.2

85.8

54.5

52.6

64.7

60.9

53.8

43.3

19.7

1975

98.4

98.1

97.5

94.7

85.4

49.7

49.2

61.9

58.6

50.9

39.2

15.8

1980

98.3

98.0

97.3

94.0

81.5

46.0

52.9

62.3

58.7

50.7

38.8

16.1

1985

98.1

98.0

97.1

93.1

78.3

41.6

56.9

65.9

59.8

49.9

37.9

15.2

1989

97.0

97.6

96.0

91.6

71.4

35.8

61.1

70.7

64.2

52.2

39.2

15.7

1996

97.8

97.7

97.4

94.6

74.5

36.7

63.6

71.6

66.9

58.1

39.0

15.4

1999

97.1

97.5

97.1

94.7

74.1

35.5

64.5

71.8

67.9

58.7

39.8

14.9

Mal

aysi

a..

....

....

....

....

....

.19

7093

.491

.186

.776

.466

.146

.640

.642

.238

.230

.725

.113

.719

8097

.396

.192

.278

.169

.549

.743

.042

.337

.732

.626

.719

.019

9192

.392

.487

.165

.053

.331

.841

.935

.829

.620

.614

.66.

719

9998

.496

.892

.674

.659

.2(N

A)

52.3

46.5

38.3

27.6

20.8

(NA

)


Table

10

.Lab

or

Forc

ePart

icip

ati

on

Rate

sb

yA

ge

an

dSex:

Sele

cte

dYears

19

70

to1

99

9—

Con

.

Cou

ntry

Year

Mal

esF

emal

es

25to

44ye

ars

45to

49ye

ars

50to

54ye

ars

55to

59ye

ars

60to

64ye

ars

65ye

ars

and

over

25to

44ye

ars

45to

49ye

ars

50to

54ye

ars

55to

59ye

ars

60to

64ye

ars

65ye

ars

and

over

Pak

ista

n..

....

....

....

....

....

..19

7296

.096

.394

.390

.885

.665

.78.

67.

79.

57.

38.

68.

919

8189

.593

.992

.090

.475

.7(N

A)

3.3

2.7

3.1

2.4

2.3

(NA

)19

8998

.197

.494

.191

.281

.055

.712

.913

.810

.811

.29.

42.

419

9497

.597

.296

.591

.578

.852

.714

.115

.613

.915

.311

.87.

4

Phi

lippi

nes.

....

....

....

....

....

.19

7089

.589

.787

.185

.879

.356

.537

.138

.736

.533

.428

.617

.719

7594

.095

.793

.590

.784

.362

.625

.424

.823

.421

.719

.613

.719

7897

.6195

.9(N

A)

289

.1(N

A)

60.6

48.1

147

.5(N

A)

240

.9(N

A)

23.1

1983

95.5

196

.6(N

A)

288

.4(N

A)

60.1

56.9

160

.4(N

A)

256

.4(N

A)

28.0

1989

97.9

197

.4(N

A)

288

.9(N

A)

59.0

53.3

158

.2(N

A)

250

.7(N

A)

29.4

1996

97.9

196

.8(N

A)

287

.2(N

A)

57.3

55.3

162

.3(N

A)

254

.1(N

A)

29.0

1999

97.4

196

.8(N

A)

288

.1(N

A)

54.5

57.2

164

.0(N

A)

255

.8(N

A)

29.8

Sin

gapo

re..

....

....

....

....

....

1970

98.2

96.2

88.1

73.9

55.6

31.9

23.2

17.5

17.5

16.2

13.4

6.5

1980

97.7

95.7

89.6

70.7

52.5

28.6

45.9

26.5

20.4

14.5

11.3

6.4

1989

97.9

96.1

89.2

66.6

48.2

20.7

60.6

41.3

30.7

19.4

11.0

5.0

1996

97.8

96.8

91.4

77.9

48.6

21.7

66.6

53.9

43.7

28.4

14.9

5.2

Sou

thK

orea

....

....

....

....

....

1970

93.0

95.2

91.9

85.4

67.9

35.1

38.8

48.5

45.2

39.1

26.9

10.6

1975

97.7

96.8

93.7

85.6

68.3

34.4

45.9

59.8

57.1

50.9

33.6

12.0

1980

95.8

95.2

90.6

82.6

68.9

40.6

37.9

51.3

49.0

43.3

31.3

13.0

1989

94.8

93.6

89.7

82.4

65.6

39.0

51.3

63.5

60.4

52.7

41.6

18.1

1992

95.4

94.9

91.6

84.9

71.0

42.3

51.8

60.9

60.8

54.1

44.9

19.6

1996

94.7

95.3

91.7

83.7

954

.5(N

A)

56.0

62.2

57.2

53.3

929

.2(N

A)

1999

92.6

93.0

89.9

81.0

65.5

40.2

55.6

62.8

55.4

51.2

46.3

21.4

Sri

Lank

a..

....

....

....

....

....

.19

7189

.092

.089

.177

.963

.440

.327

.326

.221

.514

.68.

43.

619

8193

.192

.387

.474

.356

.635

.732

.525

.219

.313

.26.

93.

819

9695

.691

.991

.873

.0938

.6(N

A)

46.0

39.0

32.3

27.2

97.

8(N

A)

1999

95.1

95.3

88.6

81.1

943

.3(N

A)

48.3

45.8

34.4

30.4

99.

8(N

A)

Tha

iland

....

....

....

....

....

....

1970

96.2

95.9

93.5

89.3

74.6

44.6

79.3

79.6

73.8

65.9

47.5

21.2

1976

1093

.9(N

A)

592

.3(N

A)

954

.9(N

A)

1061

.5(N

A)

556

.2(N

A)

923

.2(N

A)

1980

94.2

93.7

90.7

84.4

67.8

39.3

74.1

73.5

68.6

59.1

43.1

19.0

1994

397

.4497

.5592

.8(N

A)

947

.2(N

A)

378

.0476

.7563

.8(N

A)

923

.5(N

A)

1997

397

.1497

.5592

.6(N

A)

946

.4(N

A)

383

.4483

.8567

.9(N

A)

926

.0(N

A)

1999

396

.3497

.3592

.3(N

A)

943

.9(N

A)

381

.6481

.9567

.6(N

A)

921

.1(N

A)

Turk

ey..

....

....

....

....

....

...

1970

94.5

94.9

91.9

88.0

83.0

67.8

51.8

52.9

53.6

50.0

47.6

35.1

1975

92.4

92.1

88.6

82.5

76.8

64.9

46.1

48.2

48.9

46.3

40.7

27.9

1980

95.8

91.1

84.9

76.8

67.4

43.9

43.3

48.3

46.1

42.4

36.3

20.8

1988

97.8

89.2

82.7

71.5

59.2

33.8

37.7

36.3

36.4

29.4

20.9

10.9

1996

97.3

83.0

71.0

60.3

54.0

33.6

32.7

29.7

29.3

30.4

23.4

13.3

Lat

inA

mer

ica/

Car

ibb

ean

Arg

entin

a..

....

....

....

....

....

.19

7097

.895

.891

.780

.457

.229

.131

.325

.222

.116

.210

.34.

719

8094

.992

.487

.677

.651

.917

.935

.330

.225

.417

.69.

83.

219

8997

.195

.090

.679

.456

.123

.538

.931

.927

.819

.811

.23.

719

9594

.693

.690

.082

.863

.227

.655

.553

.246

.635

.422

.68.

9


Table

10

.Lab

or

Forc

ePart

icip

ati

on

Rate

sb

yA

ge

an

dSex:

Sele

cte

dYears

19

70

to1

99

9—

Con

.

Cou

ntry

Year

Mal

esF

emal

es

25to

44ye

ars

45to

49ye

ars

50to

54ye

ars

55to

59ye

ars

60to

64ye

ars

65ye

ars

and

over

25to

44ye

ars

45to

49ye

ars

50to

54ye

ars

55to

59ye

ars

60to

64ye

ars

65ye

ars

and

over

Bra

zil

....

....

....

....

....

....

..19

7095

.192

.387

.782

.673

.549

.821

.318

.616

.514

.211

.46.

319

80396

.3493

.2582

.3(N

A)

657

.5721

.8334

.9430

.0521

.4(N

A)

610

.372.

819

861096

.3(N

A)

580

.5(N

A)

944

.6(N

A)

1048

.0(N

A)

530

.4(N

A)

99.

5(N

A)

1996

394

.9493

.5582

.1(N

A)

946

.9(N

A)

363

.2460

.8545

.3(N

A)

918

.5(N

A)

1998

395

.3492

.9581

.5(N

A)

947

.5(N

A)

365

.8462

.6546

.6(N

A)

919

.1(N

A)

Chi

le..

....

....

....

....

....

....

.19

7097

.394

.088

.582

.672

.142

.426

.021

.419

.315

.511

.16.

519

8294

.890

.182

.872

.861

.525

.532

.226

.021

.916

.210

.14.

519

9295

.994

.992

.482

.166

.631

.545

.239

.739

.328

.219

.26.

319

9795

.795

.390

.681

.269

.027

.947

.647

.538

.731

.817

.16.

919

9995

.695

.991

.383

.469

.227

.450

.147

.142

.932

.421

.06.

5

Col

ombi

a..

....

....

....

....

....

.19

7392

.891

.187

.181

.672

.949

.625

.319

.117

.114

.812

.48.

119

851091

.1(N

A)

1186

.0(N

A)

958

.4(N

A)

1044

.0(N

A)

1131

.4(N

A)

916

.7(N

A)

1996

1892

.4495

.1585

.3(N

A)

651

.7724

.41865

.9457

.5535

.3(N

A)

615

.776.

119

991892

.4496

.0588

.2(N

A)

655

.4725

.21874

.8469

.1543

.7(N

A)

619

.375.

4

Cos

taR

ica

....

....

....

....

....

.19

7397

.997

.996

.494

.386

.057

.123

.616

.813

.510

.77.

83.

919

8493

.892

.388

.783

.069

.638

.929

.520

.915

.511

.66.

93.

119

891096

.2(N

A)

587

.1(N

A)

945

.3(N

A)

1038

.8(N

A)

520

.5(N

A)

96.

4(N

A)

1996

395

.9494

.4585

.4(N

A)

651

.4721

.1343

.3444

.2522

.2(N

A)

69.

172.

819

99396

.3495

.9588

.4(N

A)

658

.2726

.7349

.0446

.6530

.8(N

A)

611

.873.

8

Gua

tem

ala

....

....

....

....

....

.19

7395

.695

.394

.092

.487

.769

.814

.313

.612

.912

.010

.27.

119

8193

.293

.291

.790

.385

.866

.914

.912

.211

.610

.19.

06.

519

8798

.398

.095

.295

.088

.563

.331

.231

.326

.623

.720

.613

.719

9494

.294

.791

.188

.881

.661

.921

.518

.516

.013

.111

.07.

919

98-9

997

.397

.795

.194

.187

.271

.451

.456

.446

.945

.141

.028

.8

Jam

aica

....

....

....

....

....

....

1975

97.9

197

.2(N

A)

290

.9(N

A)

64.7

78.6

176

.1(N

A)

256

.5(N

A)

27.0

1978

97.3

196

.9(N

A)

290

.9(N

A)

65.6

86.0

180

.3(N

A)

263

.6(N

A)

30.7

1982

80.7

80.1

78.2

75.1

64.7

37.9

52.8

45.1

40.5

34.6

23.7

9.8

1988

80.1

194

.6(N

A)

290

.5(N

A)

52.4

60.9

173

.7(N

A)

265

.4(N

A)

24.9

1990

95.8

194

.9(N

A)

284

.3(N

A)

53.6

85.7

182

.0(N

A)

261

.3(N

A)

23.6

Mex

ico

....

....

....

....

....

....

.19

7089

.289

.688

.086

.281

.567

.117

.316

.816

.215

.414

.411

.819

8095

.595

.393

.891

.485

.668

.632

.629

.127

.524

.624

.118

.619

8896

.496

.991

.985

.577

.558

.440

.838

.231

.724

.623

.216

.919

9697

.295

.691

.985

.674

.152

.044

.841

.335

.031

.223

.814

.119

9997

.195

.791

.986

.877

.352

.446

.143

.037

.632

.425

.914

.6

Per

u..

....

....

....

....

....

....

.19

7296

.397

.195

.592

.883

.961

.522

.319

.517

.916

.113

.48.

519

8196

.398

.797

.394

.988

.563

.230

.326

.926

.023

.623

.412

.519

8995

.294

.488

.383

.275

.034

.660

.354

.442

.938

.823

.912

.019

9995

.096

.893

.385

.672

.541

.169

.968

.157

.247

.538

.219

.2


Table

10

.Lab

or

Forc

ePart

icip

ati

on

Rate

sb

yA

ge

an

dSex:

Sele

cte

dYears

19

70

to1

99

9—

Con

.

Cou

ntry

Year

Mal

esF

emal

es

25to

44ye

ars

45to

49ye

ars

50to

54ye

ars

55to

59ye

ars

60to

64ye

ars

65ye

ars

and

over

25to

44ye

ars

45to

49ye

ars

50to

54ye

ars

55to

59ye

ars

60to

64ye

ars

65ye

ars

and

over

Uru

guay

....

....

....

....

....

....

1975

96.9

95.2

90.5

81.2

58.9

20.9

40.5

35.3

29.6

21.7

12.2

3.6

1985

96.5

94.3

89.4

80.0

51.8

16.2

51.7

46.4

37.5

25.3

13.3

3.6

1995

97.4

96.4

94.3

89.3

59.3

19.4

73.0

64.6

59.5

41.0

23.9

6.7

NA

-D

ata

not

avai

labl

e.1

Ref

ers

toag

es45

to54

year

s.2

Ref

ers

toag

es55

to64

year

s.3

Ref

ers

toag

es25

to39

year

s.4

Ref

ers

toag

es40

to49

year

s.5

Ref

ers

toag

es50

to59

year

s.6

Ref

ers

toag

es60

to69

year

s.7

Ref

ers

toag

es70

year

san

dov

er.

8R

efer

sto

ages

65to

74ye

ars.

9R

efer

sto

ages

60ye

ars

and

over

.10

Ref

ers

toag

es25

to49

year

s.11

Ref

ers

toag

es45

to59

year

s.12

Ref

ers

toag

es65

to66

year

s.13

Ref

ers

toag

es65

to72

year

s.14

Ref

ers

toag

es60

to72

year

s.15

Ref

ers

toag

es60

to70

year

s.16

Ref

ers

toag

es65

to69

year

s.17

Ref

ers

toag

es50

year

san

dov

er.

18

Ref

ers

toag

es20

to39

year

s.

Not

e:F

orso

me

coun

trie

sin

this

tabl

e,da

taar

ede

rived

from

labo

rfo

rce

surv

eys

asw

ella

spo

pula

tion

cens

uses

.La

bor

forc

esu

rvey

sar

em

ore

focu

sed

onec

onom

icac

tivity

than

are

gen-

eral

cens

usen

umer

atio

nsan

d,th

eref

ore,

may

yiel

dm

ore

com

preh

ensi

vein

form

atio

non

vario

usas

pect

sof

econ

omic

activ

ity.

The

user

shou

ldre

cogn

ize

that

tem

pora

ldiff

eren

ces

inla

bor

forc

epa

rtic

ipat

ion

rate

sw

ithin

aco

untr

ym

ay,

inpa

rtre

flect

diffe

rent

mod

esof

data

colle

ctio

n.T

hedi

scus

sion

inC

hapt

er10

touc

hes

upon

othe

rpo

tent

iald

iscr

epan

cies

with

inan

dam

ong

coun

trie

s.

Not

e:D

ata

for

Ger

man

ypr

ior

to19

96re

fer

toth

efo

rmer

Wes

tG

erm

any;

data

for

the

Cze

chR

epub

licpr

ior

to19

91re

fer

toth

efo

rmer

Cze

chos

lova

kia.

Sou

rce:

U.S

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sB

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u,20

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and

vario

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sues

ofth

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tern

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nalL

abou

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Year

book

ofLa

bour

Sta

tistic

s.


This report includes data compiledby the International ProgramsCenter (IPC), Population Division,U.S. Census Bureau from publica-tions and electronic files of nationalstatistical offices, several agenciesof the United Nations, and otherinternational organizations (e.g., theOrganization for Economic Co-oper-ation and Development and theEuropean Union). It also includescross-national information fromsources such as the LuxembourgIncome Study (http://lisweb.ceps.lu),the Network on Health Expectancyand Disability Process (see Chapter4), the Global Burden of Diseasestudy (http://www.hsph.harvard.edu/organizations.bdu/), and otheruniversity-based research projects.Some ongoing efforts (e.g., theLuxembourg Income Study and theUnited Nations EconomicCommission for Europe PopulationActivities Unit Census MicrodataSamples Project(http://www.unece.org/ead/pau)involve recoding of data from differ-ent countries in order to enhancecomparability.

The majority of statistics, includingall tabular data shown in AppendixA, are contained in an InternationalData Base (IDB), maintained andupdated by the IPC. The IDB con-tains annotated statistical tables ofdemographic, economic, and socialinformation for all countries of theworld. Available information from1950 to the present is supplement-ed with population projections tothe year 2050. Most of the projected

data in An Aging World: 2001 comefrom data files of the IPC.

With the initial and ongoing supportof the Office of the Demography ofAging, U.S. National Institute onAging, the Census Bureau hasundertaken a systematic effort tolocate and compile data on olderpopulations for a subset of IDBcountries and subject matter. Theintent of this effort is to make avail-able to researchers a relatively con-sistent, documented set of data thatcan be used to analyze and antici-pate international concerns relatedto the aging of the world’s popula-tion. To date, 105 countries havebeen examined in detail, and select-ed data for a subset of thesenations appear in the tables inAppendix A. Since 1985, IDB datahave been available in an evolvingvariety of formats, including printedhard copy, mainframe computertape, and PC diskettes. The currentIDB is maintained on and madeaccessible via the Internet at the fol-lowing address:http://www.census.gov/ipc/www/idbnew.html

General information about theCensus Bureau’s IDB may beobtained by contacting the Chief,International Programs Center, U.S.Census Bureau, Washington, DC20233.

BASIC DEMOGRAPHIC DATA

Estimated and projected populationdistributions, by age and sex, aretaken from IPC data files exceptwhere otherwise noted. Many of

the countries covered in this reporthave produced their own nationalpopulation projections, and differentstatistical agencies generate country-specific sets of projections for allbut the least populous countries.For the most part, the convergenceof national, IPC, United Nations, andother projection series is close forthe next 20 to 30 years. This isespecially true with regard to olderpopulation groups, since personswho will constitute the elderly in2020 and 2030 already have beenborn. Because the elderly of tomor-row have survived the risks of infantand childhood mortality, their con-tinued survival is subject to adultmortality rates that can be estimat-ed with a relatively high degree ofconfidence until the very old ages.Because the effects of migration onprojected cohorts are in most casesminimal, absolute numbers of elder-ly persons may therefore be consid-ered fairly reliable.

Of less certainty are projected popu-lation proportions and related meas-ures such as youth support ratios.The size of youth cohorts is oftenthe most important factor in deter-mining overall population aging.Population projections for develop-ing countries usually assume afuture decline in fertility rates thatwill eventually result in older popu-lation age structures. The pace andlevel of fertility reduction is debat-able, however; elderly proportionsin population projections will vary tothe extent that actual fertilitychange deviates from its assumed


APPENDIX B.

Sources and Limitations of the Data

trajectory. Projections for developedcountries are less sensitive to suchuncertainty because of the extent offertility decline that has alreadyoccurred. With fertility now wellbelow replacement level in numer-ous developed countries, the issuefor projections is whether to assumea future rise in fertility. In somedeveloped countries, changes inmigration levels could conceivablyhave a greater future impact thanbirth rates on overall age structure.

As discussed in Chapter 3, most ofthe variation in projections of elder-ly population appears to result fromuncertainty about mortality at theoldest ages. Projections requireassumptions about future trends,and most past projections have notanticipated the continued decline inmortality rates at older ages thathave occurred in developed coun-tries. In the Census Bureau’s 1987Aging World report, projectionsmade in 1984 implied that theJapanese population aged 80 andover would constitute slightly lessthan 5 percent of the total Japanesepopulation by the year 2025. In theyears after 1984, however, thedecline in fertility and the increasein life expectancy (both at birth andat older ages) have been sharperthan expected. Hence, revised pro-jections to 2025 imply a somewhatsmaller total population, and theoldest-old share of the total is nowprojected to be on the order of 9 percent by the year 2025. For themost part, best-guess demographicforecasts have tended to be “conser-vative” vis-a-vis assumed mortalityimprovement, with the result thatfuture numbers of the elderly maybe understated. In terms of socialservice planning for future cohortsof the oldest old, the example ofJapan underscores the magnitude ofpotential “error” with which planners

may be confronted. This suggests aneed for more analytical attention tothe assumptions and outcomes ofpopulation projections vis-à-visnumbers of elderly persons. Towardthis end, organizational units includ-ing the United Nations PopulationDivision, Eurostat, and the U.S.Census Bureau Population Division,in conjunction with members of aca-demia and sponsors such as the U.S.National Institute on Aging and theAmerican Association of RetiredPersons, have begun a concertedeffort to use their combined expert-ise to refine and improve projectionprocedures. For a detailed critiqueand discussion of such procedures,see Bongaarts and Bulatao, 2000.

IPC population projections for agiven country incorporate severalcomponents. The initial populationage/sex structure usually is basedon a national census distribution,with or without adjustment as deter-mined by Census Bureau analysts.Analysts then derive — either direct-ly using reported data or indirectlyusing demographic techniques —empirical age-sex-specific mortality,fertility, and international migrationrates, considering the range of avail-able data (e.g., from demographicand other surveys; vital registrationsystems; and other administrativestatistics). These benchmark esti-mates form the basis for projectedchanges in the population age/sexstructure. In countries where reli-able, nationally representative datafor one or more of these variablesare lacking, rates from demographicmodels or culturally similar neigh-boring countries may be employed.Future levels of fertility, mortality,and migration are incorporatedbased on observed country-specifictrends and the accumulated experi-ence of other nations at differentstages of demographic and socio-economic development.

With regard to the age structure ofelderly populations, potentialsources of error usually have beenassumed to be minor in most (butnot all) countries. To date, demogra-phers have devoted much moreattention to analyzing age inaccura-cies at younger rather than olderages. Inaccuracies at older ages dooccur. An individual’s age is oftenundocumented in some societiesand subcultures, and knowledge ofexact age may not be an importantconcern. Hence, reported ages ofelderly respondents tend to heap oncertain round numbers (60, 65, 70,etc.). Many of these inaccuracies canbe detected and statistically adjust-ed, and are commonly accounted forin population projections.

Available evidence suggests that theelderly as a whole are not under-counted in censuses to any signifi-cantly different extent than areother age groups. In many coun-tries, the elderly are less apt thanyounger age groups to be geograph-ically mobile and thus should beeasier in theory to enumerate.Within the elderly population, how-ever, there are strong indicationsthat women are missed more oftenthan men. In some South Asian andAfrican societies, national censusesroutinely count more men thanwomen in older age groups, in spiteof the fact that the estimated lifeexpectancy of women is and hasbeen greater than that of men inpractically all countries.

SOCIOECONOMICCHARACTERISTICS

Data on labor force participation,marital status, and other socioeco-nomic characteristics are primarilyderived from published census andsurvey data of various countries ascompiled by the U.S. Census Bureau.Although no techniques have been


applied to evaluate the quality ofthese socioeconomic statistics, theCensus Bureau attempts to resolvediscrepancies in reported figures,and to compile information in stan-dard formats within the structure ofthe International Data Base.

IDB data are not always comparableamong countries, essentially for tworeasons: (1) complete statistics maynot be available to allow manipula-tion of data into standard formats;and (2) concepts and definitionsvary according to the specific needsof each country. For example, acountry with only a few small urbancenters may need a different defini-tion of urban than does a highlyindustrialized country that is pre-dominantly urban. Uneven progress

has been made during the past halfcentury in encouraging disparatenational statistical agencies toadhere to defined international stan-dards of data collection and tabula-tion. As a result, some concepts (lit-eracy, for example) are moreinternationally comparable than oth-ers (e.g., labor force participation).

To the extent possible, the U.S.Census Bureau has accounted forstatistical and conceptual differ-ences when compiling IDB countryfiles. Remaining deviations fromstandard formats, and other dataanomalies, are documented in theannotation that forms part of theIDB files. Where applicable, nationaldefinitions of major concepts suchas “urban” and “economically active”

are included in IDB files to allow theuser to recognize differencesamong countries.

As population aging has assumedgreater importance and receivedgreater recognition over time, inter-national agencies have begun toproduce a growing amount of dataon older populations. This is espe-cially true in the areas of health,economic activity, income, andretirement. As a result, this reportdraws substantially on cross-nation-al data and comparisons producedby a variety of organizations andresearch consortia whose subject-matter expertise in these areas isinvaluable to a better understandingof an aging world.


Because of national differences inthe characteristics that distinguishurban from rural areas, the distinc-tion between urban and rural popu-lation is not amenable to a singledefinition applicable to all countries.For this reason, the United Nations(UN) recommended in 1970 thateach country should decide for itselfwhich areas are urban and which arerural.

The rural population as defined bymost national statistical organiza-tions is usually not defined directly,but is simply the residual populationafter the urban population is distin-guished. The UN Statistical Officehas classified extant urban defini-tions into the five principal typeslisted below.

1. Administrative Area. This con-cept treats as urban the adminis-trative divisions (for example,municipalities, cities, communes,districts, boroughs) that havebeen so classified by the nationalgovernment, or certain parts ofsaid divisions, such as theiradministrative centers, capitals,or principal localities. This classi-fication is based primarily on his-torical, political, or administrativeconsiderations rather than on sta-tistical considerations. It tends tobe relatively static and is notautomatically changed after eachcensus to recognize the decreas-ing size of formerly importantplaces or the increasing size ofplaces that have recently becomeimportant.

2. Population Size. This concepttreats as urban those places (forexample, cities, towns, agglomer-ations, localities) having either aspecified minimum number ofinhabitants or a specified mini-mum population density. The UNdiscussion of the concept “popu-lation density” recognizes thatsuburbs of large places, denselypopulated fringes around incor-porated municipalities, and thelike, are sometimes classified asurban in this approach.

Within a fairly broad range, thechoice of the minimum qualifyingsize or density value is arbitrary,although original efforts mayhave based the cutting score onstatistics regarding the presenceor absence of various facilities orfunctions in places of given sizes.The variety of minimum sizesthat are or have been in use innational statistical programsreflects the lack of consensus onthese matters. It also reflects thefact that a place of given size in asmall country with a subsistence-agricultural economy will be rela-tively more important than in ahighly industrialized, populouscountry such as Japan. Similarly,a size that might have represent-ed a fairly important place in feu-dal Japan might not be relevantto modern Japan. In some coun-tries (for example, New Zealand)the minimum required size usedto record the growth of urbanpopulation has increased fromcensus to census. The minimum

required size for urban used bycountries in this report during the1980 census round ranged fromagglomerations of at least 200inhabitants to localities of 10,000or more inhabitants.

3. Local Government Area. Thisconcept defines urban in terms ofthose places, agglomerations, orlocalities with a local govern-ment. For some countries, thispractice might be interpreted asreferring to a particular form oflocal government, especially onehaving relatively great autonomy.The equivalent in the UnitedStates would be the incorporatedmunicipality (city, town, borough,or village). Other terms cited bythe UN include chartered towns,local government areas, munici-pal communities, and burghs. Nominimum population size is usedin this definition. The remarksabout the relatively static charac-ter of classifications under thefirst concept apply here also.

4. Urban Characteristics. Thisconcept requires an urban placeto possess specific characteris-tics such as established streetpatterns, contiguously alignedbuildings, and public servicesthat might include a sewer sys-tem, a piped water supply, elec-tric lighting, a police station, ahospital, a school, a library, acourt of law, and/or a local trans-portation system. A classifica-tion of this sort would need tobe developed during or shortlybefore a census enumeration.


APPENDIX C.

International Comparisons of Urban and Rural Definitions

5. Predominant EconomicActivity. In this formulation,places or areas qualify as urbanif a specified minimum propor-tion of their economically activepopulation is engaged in nona-gricultural activities.

Individual national definitions ofurban areas are included in eachInternational Data Base country fileannotation. For a more thoroughdiscussion of international differ-ences and similarities in urban andrural areas, see Henry Shryock,Jacob Siegel, and Associates, 1971,

The Methods and Materials ofDemography, Volume 1, U.S. Bureauof the Census, Washington, DC, pp.151-68.


(Many of the data in this report aretaken or derived from hundreds ofsources not included in the follow-ing reference list. These unnamedsources consist mainly of primarycensus and survey volumes of indi-vidual nations, as well as periodicissues of international compendiasuch as the International LabourOffice Yearbook of Labour Statistics,the United Nations DemographicYearbook, and the World HealthOrganization World Health StatisticsAnnual).

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Agree, Emily, Ann E. Biddlecom, andThomas W. Valente, 1999, “Multi-Generational Exchanges inTaiwan and the Philippines: ASocial Network Approach,”Hopkins Population CenterWorking Paper WP 99-06, JohnsHopkins University, August.

Ahituv, Avner and Joseph Zeira,2000, “Technical Progress andEarly Retirement,” The HebrewUniversity of Jerusalem.

Albert, Steven M. and Maria G.Cattell, 1994, Old Age in GlobalPerspective, New York: G.K. Hall.

Amos, Amanda, 1996, “Women andSmoking: A Global Issue,” WorldHealth Statistics Quarterly, Vol.49, pp. 127-33.

Andrews, Gary, Adrian Esterman,Annette Braunack-Mayer, andCam Rungie, 1986, Aging in theWestern Pacific. A Four-CountryStudy, Geneva: World HealthOrganization.

Anh, Troung Si, Bui The Cuong,Daniel Goodkind, and JohnKnodel, 1997, “LivingArrangements, Patrilineality andSources of Support amongElderly Vietnamese,” Asia-PacificPopulation Journal, Vol. 12, No.4, pp. 69-88.

Apt, Nana Araba, 1992, “FamilySupport to Elderly People inGhana,” pp. 203-12 in Hal L.Kendig, Akiko Hashimoto, andLarry C. Coppard, eds., FamilySupport for the Elderly, Oxford:Oxford University Press.

Atoh, Makoto, 1998, “Who TakesCare of Children and the Elderlyin an Aging Society?”, Paper pre-pared for the Rencontres SauvyInternational Seminar, InstitutNational d’Etude Demographique,Paris, 14-15 October.

Baker, David W., Julie A.Gazmararian, Joseph Sudano,and Marian Patterson, 2000, “TheAssociation Between Age andHealth Literacy Among ElderlyPersons,” Journal Of Gerontology:Social Sciences, Vol. 55B., No. 6,pp. S368-74.

Barker, D.J.P., 1995, “Fetal Origins ofCoronary Heart Disease,” BritishMedical Journal, No. 311, pp.171-74.

Bartel, Ann P. and NachumSicherman, 1993, “Technological

Change and Retirement Decisionsof Older Workers,” Journal ofLabor Economics, Vol. 11, No. 1,pp.162-183.

Bartlett, Helen P. and David R.Phillips, 1995, “Aging Trends—Hong Kong,” Journal of Cross-Cultural Gerontology, Vol. 10,No. 3, pp. 257-65.

Bartlett, Helen P. and Shwu-ChongWu, 2000, “Ageing and AgedCare in Taiwan,” pp. 210-22 inDavid Phillips, ed., Ageing in theAsia-Pacific Region: Issues,Policies and Future Trends,London: Routledge.

Bean, Frank D., George C. Myers,Jacqueline L. Angel, and Omer R.Galle, 1994, “GeographicConcentration, Migration, andPopulation Redistribution Amongthe Elderly,” pp. 319-55 in LindaG. Martin and Samuel H. Preston,eds., Demography of Aging,Washington, DC: NationalAcademy Press.

Becker, Charles M., 1991, “Migrationof the Elderly in Sub-SaharanAfrica,” Paper prepared for theIBS conference on The ElderlyMigration Transition, Estes Park,Colorado, September.

Béland, François and Maria-VictoriaZunzunegui, 1996, “The Elderlyin Spain: The Dominance ofFamily and the Wherewithal ofthe State,” pp. 55-76 in HowardLitwin, ed., The Social Networksof Older People: A Cross-NationalAnalysis, Westport, CT: Praeger.

Belgium National Institute ofStatistics, 1998, Statistiques


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