The drivers of future mortality: Why aren’t we dead yet? · 2017-04-10 · Why are you [we] not...

SCOR Global Life Canadaat the AHOU in San Diego, April 2017

The drivers of future mortality:Why aren’t we dead yet?

Presented by Philippe Aussel

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Why are you [we] not dead yet?Because life expectancy doubled in the past 150 years.

“The most important difference between the world today and 150 years ago isn’t airplane flight or nuclear weapons or the Internet. It’s lifespan. We used to live 35 or 40 years on average … but now we live almost to 80. We used to get one life. Now we get two.”|http://www.slate.com/articles/health_and_science/science_of_longevity/2013/09/life_expectancy_history_public_health_and_medical_a

dvances_that_lead_to.html

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How mortality improved over time

What were the historical determinants

What are the possible future drivers

Looking from a different perspective

The drivers of future mortality: Why aren’t we dead yet?

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Resources

A. Case, C. Paxson, 2010. "Causes and consequences of early-life health," Demography, Springer, vol. 47(1), pages S65-S85, March. http://www.nber.org/papers/w15637.pdf

D.M. Cutler, A. Deaton and A. Lleras-Muney. "The Determinants Of Mortality," Journal of Economic Perspectives, 2006, v20 (3, Summer), 97-120. Available from: http://www.nber.org/papers/w11963

D.M. Cutler, E. L. Glaeser, A. B. Rosen, 2009. "Is the U.S. Population Behaving Healthier?," NBER Chapters, in: Social Security Policy in a Changing Environment National Bureau of Economic Research, Inc. Available from: http://www.nber.org/papers/w13013.pdf

S.S. Morse. “Factors in the emergence of infectious diseases”. Available from: http://wwwnc.cdc.gov/eid/article/1/1/pdfs/95-0102.pdf

National Institutes of Health (US); Biological Sciences Curriculum Study. NIH Curriculum Supplement Series [Internet]. Bethesda (MD): National Institutes of Health (US); 2007-. Understanding Emerging and Re-emerging Infectious Diseases. Available from: http://www.ncbi.nlm.nih.gov/books/NBK20370/

J. Olshansky, B.A. Carnes and A. Désesquelles. “Prospects for Human longevity”, Science, Vol 291, Issue 5508, 1491-1492, 23 February 2001. Available from: http://sjayolshansky.com/sjo/Manuscripts_files/Science2001.pdf

R.J. Pokorsky, MD, MBA. “Pricing implications of trends in population mortality and underwriting effectiveness”, J Insur Med 2004;36:54-59. Available from: http://aaimedicine.org/journal-of-insurance-medicine/jim/2004/036-01-0054.pdf

M.C. Purushotham. “Mortality improvements”, The Actuary Magazine, August/September 2011 – Volume 8 Issue 4. Available from: http://www.soa.org/library/newsletters/the-actuary-magazine/2011/august/act-2011-vol8-iss4-purushotham.pdf

J. Vaupel. “The advancing frontier of human survival” presented at the Living to 100 symposium of the SOA – January 8-10, 2014. Available from: https://www.soa.org/Library/Monographs/Life/Living-To-100/2014/mono-li14-1-soa-informal-discussant.pdf

SCOR inFORM - February 2011

World life expectancy and futurelongevity scenarios

SCOR inFORM - February 2011

World life expectancy and futurelongevity scenarios

EditorsMatthew [email protected]

Christ ian [email protected]

SCOR Global Life Americas401 North Tryon StreetSuite 800Charlotte, North Carolina 28202

www.scor.com/SGLA

David Wesley: Our clients need to predict future mortality, but many business leaders are uncomfortable with simple linear extrapolation of previous mortality spreads. You have been a proponent of what you term three-dimensional forecasting. Will you please explain?

Jay Olshansky: The key component of three-dimensional forecast ing is that it factors in the health status of the living when project ing life expectancy. Most researchers have generated these forecasts by looking into the past. They take historical trends in life expectancy at birth or at later ages and essent ially pull out a ruler and extend those into the future.

For example, let ’s say you’re looking at life expectancy at age 65 and higher for the last 50 years, and you want to project forward. Linear forecasting completely ignores the health status of the living population; it assumes that t rends observed for populat ions that have died w ill cont inue into the future. With three dimensional forecasting models, we take into account the health status of the populat ions that w ill experience the mortality that you’re forecasting.

DW: Can you give us a specific instance where linear modeling has missed or would miss the mark?

JO: Yes, I can give you a couple examples. Several years ago, the Social Security Administrat ion was forecast ing death rates from diabetes. They looked at historical t rends in death rates f rom diabetes going back the last few decades and extended that trend forward. What they failed to consider was the dramat ic rise in obesity that had already occurred but which had not yet expressed itself in its impact on diabetes. As these more obese generat ions move through the age st ructure, we would expect to see a higher rate of diabetes than previous generat ions. By using linear forecast ing models this experience is completely lost .

By David Wesley, MDVice President, Medical Research & Development

November 2011

Here’s to a Long Life: Understanding Life ExpectancyLife expectancy takes on greater importance as Baby Boomers ret ire and we begin to realize the “ risk” that a large group of long-lived benef iciaries may st rain public and private ret irement and medical plans.

Project ing life expectancy is the topic of the interview conducted by Dr . David Wesley, Vice President , Medical Research & Development , w ith Dr. Jay Olshansky, Professor of Epidemiology and Biostat ist ics at the University of Ill inois at Chicago. Dr . Olshansky cites weaknesses in t radit ional models and emphasizes the need to focus on the health status of the living when forecasting life expectancy.

Jay has published numerous papers on aging and life expectancy. He is a f requent presenter at medical and insurance meet ings. Jay earned his bachelor’ s degree in psychology f rom Michigan State University and his MA and PhD in Sociology f rom the University of Chicago.

S. Jay Olshansky, PhDProfessor of Epidemiology and Biostatistics,University of Illinois at Chicago

EditorsMatthew [email protected]

Christ ian [email protected]

SCOR Global Life Americas401 North Tryon StreetSuite 800Charlotte, North Carolina 28202

www.scor.com/SGLA

David Wesley: Our clients need to predict future mortality, but many business leaders are uncomfortable with simple linear extrapolation of previous mortality spreads. You have been a proponent of what you term three-dimensional forecasting. Will you please explain?

Jay Olshansky: The key component of three-dimensional forecast ing is that it factors in the health status of the living when project ing life expectancy. Most researchers have generated these forecasts by looking into the past. They take historical trends in life expectancy at birth or at later ages and essent ially pull out a ruler and extend those into the future.

For example, let ’s say you’re looking at life expectancy at age 65 and higher for the last 50 years, and you want to project forward. Linear forecasting completely ignores the health status of the living population; it assumes that t rends observed for populat ions that have died w ill cont inue into the future. With three dimensional forecasting models, we take into account the health status of the populat ions that w ill experience the mortality that you’re forecasting.

DW: Can you give us a specific instance where linear modeling has missed or would miss the mark?

JO: Yes, I can give you a couple examples. Several years ago, the Social Security Administrat ion was forecast ing death rates from diabetes. They looked at historical t rends in death rates f rom diabetes going back the last few decades and extended that trend forward. What they failed to consider was the dramat ic rise in obesity that had already occurred but which had not yet expressed itself in its impact on diabetes. As these more obese generat ions move through the age st ructure, we would expect to see a higher rate of diabetes than previous generat ions. By using linear forecast ing models this experience is completely lost .

By David Wesley, MDVice President, Medical Research & Development

November 2011

Here’s to a Long Life: Understanding Life ExpectancyLife expectancy takes on greater importance as Baby Boomers ret ire and we begin to realize the “ risk” that a large group of long-lived benef iciaries may st rain public and private ret irement and medical plans.

Project ing life expectancy is the topic of the interview conducted by Dr . David Wesley, Vice President , Medical Research & Development , w ith Dr. Jay Olshansky, Professor of Epidemiology and Biostat ist ics at the University of Ill inois at Chicago. Dr . Olshansky cites weaknesses in t radit ional models and emphasizes the need to focus on the health status of the living when forecasting life expectancy.

Jay has published numerous papers on aging and life expectancy. He is a f requent presenter at medical and insurance meet ings. Jay earned his bachelor’ s degree in psychology f rom Michigan State University and his MA and PhD in Sociology f rom the University of Chicago.

S. Jay Olshansky, PhDProfessor of Epidemiology and Biostatistics,University of Illinois at Chicago

AbstractAging is a simple concept which nonetheless encompasses a multiplicity of more or lessimplicit meanings, the misuse of which can lead to serious misconceptions that need tobe cleared up. The first one concerns the nature of the phenomenon, which is thought tobe typical of wealthy nations. The first part of this paper attempts to show how misguidedthis view is. The second misconception has to do with the scope of the phenomenon,which some limit to the question of how to finance the growing number of retirees who areno longer in the workforce. The second part of this paper will seek to show how this viewhas been overly influenced by the specific situation of Europe and Japan, whose repre-sentative power is at best very limited.

Aging: a Global Phenomenon

Par Philippe TrainarSCOR Chief Risk Officer

December 2010 N°9

After having set aside the misconceptions that are too often drawn from the Pres-ton curve, we will examine the multiple meanings of the concept of demographicaging before attempting to assess the global dimension of the phenomenon,which is in fact increasingly dominated by the situation found in the emerging anddeveloping countries..

1.1 The misleading findings of the Preston curveIt is fairly widely accepted that the phenomenon of demographic aging is linkedto development. In fact, when we correlate the level of development (as measu-red by per capita GDP) to life expectancy, we typically find the curve above, whichwas highlighted for the first time by Preston1: initially, life expectancy increasesvery rapidly as the level of development rises, then tapers off with higher levelsof development, becoming practically flat for the highest levels of development.

1 A global phenomenon

Texts appearing in SCOR Papers are theresponsibility of their authors alone. Inpublishing such articles, SCOR takes noposition on the opinions expressed by theauthors in their texts and disclaims allresponsibility for any opinions, incorrectinformation or legal errors found therein.

AbstractAging is a simple concept which nonetheless encompasses a multiplicity of more or lessimplicit meanings, the misuse of which can lead to serious misconceptions that need tobe cleared up. The first one concerns the nature of the phenomenon, which is thought tobe typical of wealthy nations. The first part of this paper attempts to show how misguidedthis view is. The second misconception has to do with the scope of the phenomenon,which some limit to the question of how to finance the growing number of retirees who areno longer in the workforce. The second part of this paper will seek to show how this viewhas been overly influenced by the specific situation of Europe and Japan, whose repre-sentative power is at best very limited.

Aging: a Global Phenomenon

Par Philippe TrainarSCOR Chief Risk Officer

December 2010 N°9

After having set aside the misconceptions that are too often drawn from the Pres-ton curve, we will examine the multiple meanings of the concept of demographicaging before attempting to assess the global dimension of the phenomenon,which is in fact increasingly dominated by the situation found in the emerging anddeveloping countries..

1.1 The misleading findings of the Preston curveIt is fairly widely accepted that the phenomenon of demographic aging is linkedto development. In fact, when we correlate the level of development (as measu-red by per capita GDP) to life expectancy, we typically find the curve above, whichwas highlighted for the first time by Preston1: initially, life expectancy increasesvery rapidly as the level of development rises, then tapers off with higher levelsof development, becoming practically flat for the highest levels of development.

1 A global phenomenon

Texts appearing in SCOR Papers are theresponsibility of their authors alone. Inpublishing such articles, SCOR takes noposition on the opinions expressed by theauthors in their texts and disclaims allresponsibility for any opinions, incorrectinformation or legal errors found therein.

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Causes of death have shifted over time

The prospect of longer life is generally viewed as a positive trend and a substantial societal achievement.

Causes of death have shifted from infectious diseases to chronic diseases, and the ages in which progress has been made shifted from younger ages to seniors.

Forecasting the rate of mortality improvement is paramount to many governmental and economic agents.

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How has mortality improved over time?

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Evolution of Western life expectancies over time

SCOR inFORM February 2011

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Life expectancies narrowing globally

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U.S. mortality trends over the past 113 years highlight the differences in age-adjusted death rates and life expectancy at birth

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Changes in the U.S. leading causes of death: Recent patterns in heart disease and cancer mortality

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U.S. life expectancy declines for the first time since 1993

For the first time in more than two decades, life expectancy for Americans declined last year — a troubling development linked to a panoply of worsening health problems in the United States … “This is unusual, and we don’t know what happened,” said Jiaquan Xu, an epidemiologist and lead author of the study. “So many leading causes of death increased.”

https://www.washingtonpost.com/national/health-science/us-life-expectancy-declines-for-the-first-time-since-1993/2016/12/07/7dcdc7b4-bc93-11e6-91ee-1adddfe36cbe_story.html?utm_term=.8e3541a60d47

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What were the historical determinants?

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Nutrition

“Agricultural yields increased significantly during the 18th Century. Better fed people resist most bacterial (not viral) disease better and recover more rapidly and more often.”

D. Cutler, A. Deaton, A. Lleras-MuneyThe Determinants of Mortality

Journal of Economic PerspectivesVolume 20, Number 3 – Summer 2006

Pages 97-200

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Public health

“Macro public health involves big public works projects … dramatic reduction in water- and food-borne diseases.”


Journal of Economic Perspectives Volume 20, Number 3 – Summer 2006

Pages 97-200

http://www.cdc.gov/mmwr/preview/mmwrhtml/mm4829a1.htm#fig1

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Urbanization

“Cities can be tremendously efficient. It is easier to provide water and sanitation to people living closer together, while access to health, education and other social and cultural services is also much more readily available. However, as cities grow, the cost of meeting basic needs increases as does the strain on the environment and natural resources”.

http://apps.who.int/iris/bitstream/10665/200009/1/9789241565110_eng.pdf?ua=1http://data.worldbank.org/indicator/SP.URB.TOTL.IN.ZS?end=2015&locations=US&start=1960&view=chart

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Socioeconomic factors: Education, income and poverty

“…individuals with low income, low wealth, low education or low social status often die younger than those who are better off or better educated.”


Journal of Economic Perspectives – Volume 20, Number 3 – Summer 2006 –Pages 97-200

“People die more often in states with low average incomes and where more people have debt in collection.”

https://www.debt.com/tools-tips/mortality-map/

http://inequality.org/inequality-health/http://www.decisionsonevidence.com/wp-content/uploads/2012/11/Life-Expectancy-and-Mean-Years-of-Schooling.png

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Preventable causes of death : behavioral and lifestyle changes

Smoking

Excessive alcohol

Personalsafety

Disease prevention

Exercising

Worksite safety

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Let’s pause … and reflect!

Will the (linear) trend of mortality improvement continue and if so, at what rate? Is it feasible to eliminate all possible risk

factors for an entire population? How will the new discoveries be

implemented at a population-level, and how cost-effective will they be? Past medical breakthroughs haven’t been

programmed or planned … they “just” happened! So, will the future be like the past or just different from what it has been? What does it take to push the current

average life expectancy of 80-85 to the magical 100 or the maximum global life span from 122 years to 150?

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What are the possible future drivers?

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Top 10 most recent breakthrough medical advances

Human genomeproject

Gene therapy

Stem cell research

Drug-eluting stents

HIV cocktail therapy

Targeted cancer therapy

Laparoscopic surgery

Bionic limbs

Smoke-free laws

Pandemic planning and

coordination of response

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Future (possible) medical and biological breakthroughs

Gene mutations

Interfacing graphene with

neurons

Pen-sized microscope

Implantable neural

interface

Light-activated

nanoparticles

Thin electronic sensors

Electronic skins

Vaccines for infectious diseases

3D-imaging

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Infectious diseases

“Specific factors precipitating disease emergence can be identified in virtually all cases. These include ecological, environmental or demographic factors that place people at increased contact with a previously unfamiliar microbe or its natural host or promote dissemination.

Drug resistance suggests that infections will continue to emerge and probably increase.”

S. MorseFactors in the Emergence of Infectious Diseases

Perspectives, Vol. 1, No. 1 – January-March 1995, pages 7 – 15

http://trialx.com/curebyte/2011/08/27/clinical-trials-and-images-of-emerging-infectious-diseases/

Zika

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Preventable causes of death : Smoking

“Smoking is a substantial factor in differences in lung cancer and cardiovascular disease mortality across education groups. Drinking, exercise, eating habits, use of preventative care, adherence to therapy and other health behaviors are also correlated with measures of socioeconomic status.”


Journal of Economic Perspectives – Volume 20, Number 3 –Summer 2006 – Pages 97-200

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Why do childhood overweight and obesity matter?

“A relatively large and fairly consistent body of evidence now demonstrates that overweight and obesity in childhood and adolescence have adverse consequences on premature mortality and physical morbidity in adulthood.

http://www.nature.com/ijo/journal/v35/n7/full/ijo2010222a.html

"No OECD country has seen a reversal of trends since the epidemic began…"

http://www.cbc.ca/news/business/canada-s-obesity-rate-higher-since-global-recession-oecd-1.2655646.

“Childhood obesity is associated with a higher chance of premature death and disability in adulthood. Overweight and obese children are more likely to stay obese into adulthood and to develop non-communicable diseases (NCDs) like diabetes and cardiovascular diseases at a younger age.”

http://www.who.int/dietphysicalactivity/childhood_consequences/en24

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World Health Day 2016: WHO calls for global action to halt rise in and improve care for people with diabetes

“The number of people living with diabetes has almost quadrupled since 1980 to 422 million adults, with most living in developing countries … [but] no longer a disease of predominantly rich nations, the prevalence of diabetes is steadily increasing everywhere, most markedly in the world’s middle-income countries.”

http://who.int/mediacentre/news/releases/2016/world-health-day/en/

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Is there any room for future improvements left?

“Two theories for future life expectancies trends are:

1. No foreseeable limit to the life expectancy, and

2. Life expectancy limited by biological factors.”

R.J. Pokorski, MD, MBAPricing Implications of Trends in Population Mortality and

Underwriting EffectivenessJournal of Insurance Medicine

J Insur Med 2004;36:54-59

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What are the biggest determinants in extending life expectancy and how has this changed?

“The vast majority of the decline in the death rate and the rise of life expectancy observed in the 20th century was due to reductions in early age mortality. Now we must rely on death rate reductions in middle- and older-age mortality, which is far more difficult to accomplish.”

S. Jay Olshansky, PhD Professor of Epidemiology and Biostatistics

University of Illinois at Chicagoin the SCOR Forecaster, Nov. 2011

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Possible biggest upcoming medical breakthroughs: nanorobotics and precision medicine

“In general, such nanotech-based medicines are therapeutic because they can effectively exploit the unique mechanical properties of cancer lesions and treat the various forms of the disease locally …”

http://www.technewsworld.com/story/69361.html

Precision medicine is an approach to patient care that allows doctors to select treatments that are most likely to help patients based on a genetic understanding of their disease.

https://www.cancer.gov/about-cancer/treatment/types/precision-medicine

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From a different perspective

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The Preston curve

http://www.princeton.edu/~deaton/downloads/cutler_deaton_lleras-muney_determinants_mortality_jep_2006.pdf

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Health care spending vs. life expectancy

http://www.oecd-ilibrary.org/sites/soc_glance-2011-en/images/thumbnails/g7_he5-02.gif

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Location, Location, Location: aka the Glasgow effect

“Rural areas of the U.S. may have less access to health care and engage in habits that may increase their risk of death, such as not wearing car seat belts, not exercising, smoking cigarettes, and carrying excess weight. Overall, the report stated, people in nonmetropolitan areas report poorer mental and physical health than those in metropolitan areas.”http://www.foxnews.com/health/2017/01/12/americans-in-rural-areas-more-likely-to-die-from-

leading-causes-death.html

Although a substantial proportion of these differences – such as for cardiovascular disease, self-assessed health, most causes of death, smoking and physical activity – can be accounted for by the distinct socio-economic profile of the area, there are aspects of health which transcend the socio-economic explanation and seem to truly represent a “Glasgow effect”.

http://www.sphsu.mrc.ac.uk/research-programmes/mh/hsco/glasefct.html/

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Pollution and climate change: air pollution causes 200,000 early deaths each year in the U.S. (mid-2010s)

“Climate variability and climate change has important consequences for health, ranging from the immediate impact of extreme weather events, to the longer term impacts of droughts and desertification, on food production and malnutrition, and the increased spread of infectious disease vectors”

http://apps.who.int/iris/bitstream/10665/200009/1/9789241565110_eng.pdf?ua=1

“A public-health burden of this magnitude clearly requires significant policy attention, especially since technologies are readily available to address a significant fraction of these emissions,” says Levy, who was not involved in the research. “We have certainly invested significant societal resources to address far smaller impacts on public health.”

http://news.mit.edu/2013/study-air-pollution-causes-200000-early-deaths-each-year-in-the-us-0829

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Squaring of the mortality curve

““Overall, probabilities of surviving to older ages have increased over the last century, and this trend is expected to continue in the future but at a slower pace”.

100 000

80 000

60 000

40 000

20 000

0

1876-18801886-18901896-19001906-19101916-19201926-19301936-19401946-19501956-19601966-19701976-19801986-19901996-20002001-2002

0 20 40 60 80 100 120

I(x)

Age

Figure 7 Female survival curve in Switzerland, 1876-2002.

http://www.ssa.gov/OACT/NOTES/as116/as116_V.html

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Population pyramid and the decline of the fertility rate in the U.S.

http://populationpyramid.nethttp://www.prb.org/Publications/Datasheets/2012/world-population-data-sheet/fact-sheet-us-population.aspx

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Quality at the end of life versus pure length of life: the dilemma of dying with dignity

“The Oregon law (1994/1997/2006) spearheaded the successful efforts to pass Death with Dignity statutes in Washington (2008), Vermont (2013), and California (2015); and led the Maine (2000), Hawaii (2002), and Massachusetts (2012) campaigns, which were all defeated only by narrow margins”

https://www.deathwithdignity.org/about/

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Why are you [we] not dead yet?Because life expectancy doubled in the past 150 years.

NutritionSanitation

VaccinationsUrbanization

EducationIncomeWealth

Medical advancesDiseases prevention

Smoking

Behaviors and lifestyleAlcohol and driving

Worksite safetyExercising

Metabolic risk factorsDrug resisting diseases

Processed foodsGlobalization and

transmission

Dying with dignityQuality of life at end of life

Breakthroughs?

Health care funding?

Resolving inequalities?

Will the trend continue?

If so, at what rate?

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The drivers of future mortality: Why aren’t we dead yet? · 2017-04-10 · Why are you [we] not...

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