Analysis of Differing Life Expectancy Amongst Developed Nations

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Abstract: This research paper attempts to analyze the determinants of varying life

expectancy of males and females in developed nations. Specifically, calorie

intake per day, alcohol consumption, and health care expenditure per capita

were used as variables. Hypothesized that with increased calorie intake and

increased alcohol consumption the result would be decreased life expectancy.

Whereas, increased health care expenditures per capita by the government will

result in increased male and female life expectancy. After analysis of results,

hypothesis was indeed correct in regards to the correlation between life

expectancy and the chosen variables.

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Introduction: According to the World Health Organization, life expectancy is defined as

the expected or average number of years an individual will live.10,11 Life

expectancy can vary depending on various factors such as gender of the

individual, the environment and country one resides in, life style (diet, exercise,

etc.), public health, and health care. 8, Based on the Organization for Economic

Co-operation and Development (OECD) database provided, it can be observed

that there are variations in both male and female life expectancies across the

globe. Not only are there differences between countries, but there are also

differences seen amongst male and female life expectancies from within the

same country. Although medical technology continues to advance and our

longevity has been seemingly increasing, there are many factors that must be

taken into consideration when determining life expectancy. Drastic differences in

social and economic states between developed and developing nations are only

two such factors that have been of great impact in determining an individual’s life

expectancy.

Amongst developed nations specifically, possible contributing factors for

differing life expectancies include an individual’s diet and governmental health

care expenditures. Research has shown that a high calorie intake and increased

alcohol consumption can result in serious health problems both in the short and

long run. 3,5,10 Consistently consuming more calories than one can burn off

eventually leads to an accumulation of excess calories, which the human body

begins to store as fat. 2 Over the long term, increased calorie consumption can

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induce serious health issues such as obesity. 13 It may even increase the

chances of developing cancer. 2,12 The condition known as obesity is in itself a

gateway for numerous diseases and health problems. Health issues that arise

from being obese include: high blood pressure, type-2 diabetes, cardiovascular

disease, gallbladder disease, varicose veins, and stroke. 2 A consistently high

calorie diet has also been associated with the onset and development of various

types of cancers. 2,12 Research has shown that excessive calorie intake can lead

to colon cancer, breast cancer, and even prostate cancer. 2 All of these health

issues mentioned could be induced by increased calorie consumption and if

acquired will slowly deteriorate an individual’s health. Consequently, poor health

will reduce the number of quality years of life.7 According to the University of

Maryland Medical Center, there are no medications, herbs, or supplements that

can aid in reducing a significant amount of weight.15 In order to lose weight, many

health care professionals emphasize to decrease daily caloric intake and to

become more active and exercise more. 15

Along with maintaining a well-balanced caloric intake, it is also

recommended to limit alcohol consumption, as excessive alcohol consumption

has been known to be harmful and the primary source of numerous health

problems. Many chronic diseases, neurological problems and even social issues

arise with increased alcohol consumption. A few serious health conditions that

can result from excessive alcohol consumption include: stroke, myocardial

infarction, depression, various types of cancers, hepatitis, and cirrhosis. 3,5 These

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serious conditions can be influential factors that contribute to the decrease in life

expectancy.

Finally, the economic and financial states of every country can greatly

impact the life expectancy of its citizens. Certain developing nations consistently

have lower life expectancies when compared to certain developed nations. For

example, in 2012 the average life expectancy in Zimbabwe was approximately 52

years of life, whereas the life expectancy in the United States of America was

78.2 years. 8 There are many economical and social differences between the two

countries mentioned that could attribute to the severe difference in life

expectancies. For example, the amount of health care expenditures, GDP, and

even easy access of advanced technology are all factors that can cause

variations in life expectancies between different nations. It has been statistically

proven that developed nations have higher life expectancies when compared to

developing nations’ life expectancies. 4,8

This paper will take into consideration the effects of three variables on life

expectancy. The focus will be on the effects of a properly balanced diet,

specifically daily calorie intake and daily alcohol consumption, and a country’s

health care expenditures on male and female life expectancy. Analysis was

conducted using the Organization for Economic Co-operation and Development

database.

Purpose: The purpose of this research paper is to analyze the determinants of

varying life expectancy of males and females in different developed nations using

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the Organization for Economic Co-operation and Development database

provided. This paper will focus on three possible variables that could be related

to and possible causes of the differing life expectancies. The three variables are:

calorie intake per day, alcohol consumption, and government health care

expenditure per capita. In order to provide a complete analysis, variables

regarding both diet and health care expenditure within each country have been

taken into consideration.

Hypothesis:

Null Hypothesis - The null hypothesis states that there is no relation

between male and female life expectancy and the three chosen variables. Thus,

there is no relation between life expectancy and the amount of caloric intake,

alcohol consumption, or health care expenditures per capita.

Alternative Hypothesis – The alternative hypothesis states that there is a

relationship between male and female life expectancy and the three chosen

variables. Specifically, increased calorie intake and increased alcohol

consumption are contributing factors that will result in decreased life expectancy.

On the other hand, it is hypothesized that increased health care expenditures per

capita by the government will result in increased male and female life

expectancy.

Literature Review:

Research has proven that calorie restriction, the reduction of the total

number of calories consumed, within a variety of species ranging from

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invertebrates to mammals can in fact increase longevity and the maximum life

expectancy. 15 A research study conducted at the NIH investigated the effects of

calorie intake on aging in mice. This study found an inverse relationship between

life span and total calorie intake. 14 As the total amount of calories administered

decreased, the mice began to live longer. 14 According to the article ‘Secret to a

long life is ultra low calorie diet’, a 20-year research study was conducted at the

University of Wisconsin that investigated the effects of calorie restriction on

rhesus adult monkeys. 1,15 Since primates are known to have many anatomical

and physiological similarities to humans, this study provides great insight into

possible effects of calorie restriction on human life expectancy.1 The adult

monkeys were split into two groups, a control group that was administered a

normal diet, and an experimental group that was administered a calorie restricted

diet that was 30% lower in calories than an average diet. 1,15 Researchers

observed that the calorie restricted group physically appeared younger. Also,

upon completion of autopsies of individuals that died during the experiment,

various age-related deaths were discovered in the control group. These age-

related deaths demonstrated that individuals with a higher caloric intake were

more prone to death at an earlier age as opposed to the experimental group. 1

In summary, the research study concluded that none of the calorie

restricted monkeys developed diabetes, there was a 50% reduction in

cardiovascular disease compared to controls, and that there was reduced age-

related brain atrophy in the experimental group. 1,15 Within the control group on

the other hand, five individuals were diabetic at the end of the experiment, 11

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were categorized as pre-diabetic, and certain age-related diseases were three

times more prevalent in this group. 1,15 At the time of the article publication, the

survival rate was recorded as 80% for the calorie restricted group and 50% for

the control group. 1,15 As previously mentioned, primates have known biological

similarities with humans, thus this study provides insight into the possibility that a

reduced calorie diet may in fact increase human life expectancy.

Although this previously mentioned study is noteworthy, very few human

related experiments have been conducted. One research study, conducted by

the Calorie Restriction Society (CRS), concluded that a reduced calorie diet does

in fact affect homeostasis within the human body and decreases certain levels

such as the amount of fats, sugars, cholesterol etc.15 Members practicing a

calorie restricted diet consumed between 1112-1958 kcal/day, for an average of

6 years. 15 This group was compared to a control group, which consumed 1976-

3537 kcal/day.15 The results demonstrated that individuals consuming calorie

restricted diets experienced a decrease in total body fat, cholesterol, insulin,

blood glucose levels, blood pressure as well as reduced chronic inflammation. 15

Studies have shown that elevated levels of many of these elements can result in

detrimental health conditions. For example, increased cholesterol levels have

proven to result in coronary heart disease, and increased blood pressure has

been known to augment the risk of myocardial infarctions and strokes. This study

provides evidence that by simply decreasing calorie intake one can reduce the

risk of future health complications and thus can increase one’s life expectancy.

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Studies have also been conducted in regards to excessive alcohol

consumption and its negative health consequences, especially premature deaths

in adults. A research study conducted by Dr. David Nelson from the National

Cancer Institute in 2009 investigated the prevalence of various types of cancers

and increased alcohol consumption within the United States.5 Dr. Nelson also

focused on years of potential life lost due to excessive alcohol consumption. 5 Dr.

Nelson and his team discovered that 3.2 - 3.7% (~18, 200 – 21, 300 deaths) of all

cancer deaths in the United State were attributable to alcohol consumption. 5

Even more astounding was the fact that alcohol induced cancers resulted in a

loss of 17-19.1 years of potential life. 5 Alcohol is a known carcinogen with clear

negative consequences and yet the consumption of it continues to prevail.

Excessive alcohol consumption has proven to increase the risk of cancers such

as liver cancer, esophageal cancer, and breast cancer. 5

According to recent OECD analysis, increased health care expenditures

has been associated with improved quality of life as well as enhanced life

expectancies. 8 Although many other economical and environmental factors

contribute to the increased life expectancy, growing health care expenditures can

represent improved medical technology and more health care being provided.

According to the OECD database, the average total health care expenditure

currently is 9.7% of the country’s GDP.8 Switzerland, currently ranked 2nd in the

OECD list of highest life expectancy at 82.6 years, spends 11.4% of its GDP on

health care and spends approximately $ 4,627 USD on health per person, which

is much more then the average of $ 3,060 USD. 8 Because many factors

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contribute to life expectancy, simply increasing health expenditures does not

necessarily mean that life expectancy will increase as well. The United States, is

currently ranked 27th with a life expectancy of 78.7 years. 8 However, the U.S.

currently attributes 17.4% of its GDP to health care and on average spends

$7,538 USD on health care per person. 8 Thus, while the U.S. spends more on

health care per person then Switzerland does, its life expectancy is still lower

than Switzerland’s life expectancy.

Results:

The following data were taken from the Organization for Economic Co-

operation and Development database provided and appropriate graphs and

tables were created accordingly. Due to the lack of specific data for certain

nations and specific years, analysis was done using 13 different developed

nations and data was used from the following years: 1997 and 2007. The 13

nations included in this analysis are: Australia, Austria, Canada, Czech Republic,

Hungary, Japan, Korea, New Zealand, Poland Sweden, Switzerland, United

Kingdom, and United States. Data was used from 1997 and 2007 in order to

provide a comprehensive analysis of past trends (1997), current trends (2007),

and a comparison on how data has changed between these years. As a

reference the data from Japan and the United States will be compared.

Life Expectancy:

An average for both male and female life expectancies was calculated and

recorded below in Table 1 and Table 2 alongside the life expectancies for each

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individual country. As observed from the life expectancy data below and

consistent with previous studies, females had a higher average life expectancy in

1997 and in 2007 compared to their male counterparts.6 On average within these

13 countries, females lived to about 79.8 years in 1997 and 82.1 years in 2007

compared to males averaging 73.3 years in 1997 and 76.3 years in 2007. In

both males and females it was observed that life expectancy, within the 10-year

span, increased. Whether this increase can be accounted for by calorie intake,

alcohol consumption, or health care expenditures will be further explained. The

median values were also calculated in order to insure the calculated averages

were accurate. The median values were noted as Male: 74.5 years (1997) and

77.4 years (2007) and Female: 80.0 years (1997) and 82.7 years (2007), which

were fairly similar to the calculated average. The lowest life expectancy recorded

was in Hungary for males (66.4 yrs in 1997 and 69.2 yrs in 2007) and for females

(75.1 yrs in 1997 and 77.3 yrs in 2007). The highest life expectancy was seen in

Japan for both male and females. In 1997 Japanese males could expect to live

on average up to 77.2 years and in 2007 79.2 years, where as Japanese females

could expect to live 83.8 years and 86.0 years respectively. To put things into

perspective, the United States for both male and female life expectancy falls

below or near the average value of this specific basket of countries. A male’s life

expectancy within the U.S. was 73.6 years in 1997 and 75.3 in 2007, while a

female’s life expectancy was 79.4 and 80.4 years respectively.

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Table 1: Male – Life Expectancy

Male Life Expectancy 1997 2007

Japan 77.2 79.2 United Kingdom 74.7 77.6 sUnited States 73.6 75.3 Hungary 66.4 69.2 Poland 68.5 71.0 Sweden 76.7 78.9 Korea 70.6 76.1 Canada 75.4 78.3 Czech Republic 70.5 73.8 Australia 75.6 79.0 Austria 74.1 77.4 New Zealand 74.8 78.2 France 74.5 75.9 Average 73.3 76.3 Median 74.5 77.4

Calorie Consumption:

Table 3 summarizes the data for total daily calorie consumption per

person within each country. On average in 1997 the daily calorie intake was

approximately 3280.46 calories whereas in 2007 the average was 3355.15

calories. The daily calorie intake ranged from a low of 2812 calories to a high of

3819 calories in 2007. The Japanese were recorded as having the lowest caloric

intake, 2812 calories; approximately 16% lower than the average value whereas

Austria had the highest caloric intake, 3819 calories, approximately 13.8% higher

than the average value in 2007. The United States was ranked second to Austria

in regards to the most calories consumed, as the regular U.S. diet contained

11.7% more calories in 2007 than the average value. There was an increase in

Table 2: Female – Life Expectancy

Female Life Expectancy 1997 2007

Australia 81.3 83.7 Austria 80.7 83.1 Canada 81.2 83.0 Czech Republic 77.6 80.2 Hungary 75.1 77.3 Japan 83.8 86.0 Korea 78.1 82.7 New Zealand 80.0 82.2 Poland 77.0 79.7 France 82.3 84.4 Switzerland 82.2 84.4 United Kingdom 79.7 81.8 United States 79.4 80.4 Average 79.8 82.1 Median 80.0 82.7

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calorie consumption witnessed from 1997 to 2007 in 10 out of the 13 countries,

which included the United States.

Only three countries decreased calorie intake during this 10-year period.

These countries were Japan, New Zealand, and France. Within this 10 year span

Japan was able to reduce calorie consumption by an outstanding 4%, whereas

the United States increased its caloric intake by approximately 3.8%. Graph 1

and Graph 2 represent a scatter plot of the data, examining the effects of calorie

consumption on male and female life expectancy. According to the line of best fit

in Graph 1 and Graph 2, calorie consumption and life expectancy for both males

and females in 1997 and 2007 are inversely proportional. Thus, an increase in

daily calorie consumption results in a decrease the male and female life

expectancies. In addition, the higher life expectancy and lower calorie

consumption by the Japanese is clearly visible on Graph 1 and 2. Finally,

according to the regression analysis completed in Table 6 and 7, it is observed

that an increase in one unit of calorie consumption will result in a decrease in

(0.00378) units of male life expectancy with a standard error of (+/- 0.00547) and

a decrease in (0.00613) units of female life expectancy with a standard error of

(+/- 0.0042).

Table 3: Daily Calorie Intake

Calorie Consumption 1997 2007

Australia 3091 3227 Austria 3592 3819 Canada 3389 3532 Czech Republic 3239 3260 Hungary 3314 3465

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Japan 2922 2812 Korea 3060 3074 New Zealand 3160 3159 Poland 3303 3421 Sweden 3089 3110 France 3550 3532 United Kingdom 3328 3458 United States 3609 3748 Average 3280.462 3355.154 Median 3303 3421

Graph 1:

Graph 2:

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Alcohol Consumption:

Data in Table 4 represents the amount of alcohol consumed per capita for

each country. The calculated average was 9.9 liters of alcohol in 1997 and 10.02

liters in 2007. Over the past 10 years, alcohol consumption has not experienced

drastic changes within the country sample being analyzed. The most alcohol

consumed per capita in 1997 was by France at 14.5 liters and by Austria in 2007

at 12.9 liters per capita. The lowest amount of alcohol consumed was in Sweden

during 1997 and 2007 at 5.9 liters and 6.9 liters respectively. Both Japan and the

United States consumed just below the average amount of alcohol per capita in

1997 and in 2007 (Japan: 8.8L and 7.7L, U.S.A: 8.2L and 8.7L respectively).

Japan has actually reduced its alcohol during these 10 years by 12.5% while the

United States increased its consumption of alcohol by 6.1%. Graphs 3 and 4

represent the effect of alcohol consumption on male and female life expectancy.

According to the graphs, both male and female life expectancies are inversely

proportional to alcohol consumption. As represented by the lines of best fit, an

increase in alcohol consumption, measured in liters per capita, results in a

decrease in life expectancy. Interestingly, according to Tables 6 and 7, an

increase in one unit of alcohol consumption will decrease male life expectancy by

(0.20527) with a standard error of (+/- 0.64768), yet actually increase female life

expectancy by (0.19156) with a standard error of (+/-0.49692).

Table 4: Alcohol Consumption

Alcohol Consumption 1997 2007

Australia 9.9 10

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Austria 13.6 12.9 Canada 7.3 8.1 Czech Republic 11.9 12.1 Hungary 12.3 12.6 Japan 8.8 7.7 Korea 8.9 8 New Zealand 8.7 9.2 Poland 8.7 10.3 Sweden 5.9 6.9 France 14.5 12.6 United Kingdom 10 11.2 United States 8.2 8.7 Average 9.9 10.02 Median 8.9 10

Graph 3:

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Graph 4:

Health Expenditures per capita:

According to Table 5, the health care expenditure per capita varies

considerably between nations. The average calculated health care expenditure

per capita was $1,678.77 in 1997 and $3,031.92 in 2007. Poland spent the least

amount of health expenditure per capita during 1997 and 2007 at a value of $497

and $1,049 respectively. The United States on the other hand, spends an

enormous amount on health expenditures per capita. In 1997 the United States

spent $4,055 and in 2007 they spent $7,482. This is approximately 147% more

spending than the average country within this group of nations. Health

expenditures continue to grow globally at alarming rates and the United States is

one of the leading nations in this development. Graphs 5 and 6 represent the

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affects of health care expenditure per capita on male and female life expectancy.

It can be concluded that there is a positive correlation and linear relationship

between both male and female life expectancies and health expenditures.

Consequently, as a nation’s health care expenditures per capita increase it will

result in an increase in life expectancy. The regression analysis conducted in

tables 6 and 7 demonstrate that increasing health care expenditures per capita

by one unit will actually increase life expectancy by (0.00115) in males with a

standard error of (+/- 0.00079). Although very slight, there will be an increase in

female life expectancy as well by (0.00084) with a standard error of (+/- 0.00061).

Table 5: Health Expenditures per Capita.

Health Expenditures 1997 2007

Australia 1804 3353 Austria 2446 3792 Canada 2151 3867 Czech Republic 921 1621 Hungary 678 1395 Japan 1695 2729 Korea 624 1685 New Zealand 1352 2471 Poland 497 1049 Sweden 1885 3349 France 2228 3592 United Kingdom 1488 3030 United States 4055 7482 Average 1678.7 3031.9 Median 1695 3030

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Graph 5:

Graph 6:

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Table 6: Male Life Expectancy - 2007 Regression Analysis

Linear Regression

Regression Statistics R 0.63372

R Square 0.40161 Adjusted R Square 0.17721 Standard Error 2.8762 Total Number Of Cases 12

ANOVA

d.f. SS MS F p-level Regression 3. 44.41634 14.80545 1.78971 0.22688

Residual 8. 66.18033 8.27254 Total 11. 110.59667

Coefficients Standard Error LCL UCL t Stat p-level

Intercept 87.33845 12.47894 51.19371 123.48318 6.99887 0.00011 Calorie -0.00378 0.00547 -0.01963 0.01208 -0.6898 0.50983 Alcohol -0.20527 0.64768 -2.08124 1.67069 -0.31694 0.7594 HC Exp. 0.00115 0.00079 -0.00115 0.00344 1.44498 0.18647

Table 7: Female Life Expectancy - 2007 Regression Analysis

Linear Regression

Regression Statistics R 0.58012

R Square 0.33654 Adjusted R Square 0.08774 Standard Error 2.20671 Total Number Of Cases 12

ANOVA

d.f. SS MS F p-level Regression 3. 19.76029 6.58676 1.35264 0.32462

Residual 8. 38.95638 4.86955 Total 11. 58.71667

Coefficients Standard Error LCL UCL t Stat p-level

Intercept 98.14694 9.5742 70.41567 125.87822 10.25119 0.00001 Calorie -0.00613 0.0042 -0.01829 0.00604 -1.45851 0.18281 Alcohol 0.19156 0.49692 -1.24773 1.63086 0.3855 0.70991 HC Exp. 0.00084 0.00061 -0.00092 0.00261 1.38499 0.20345

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Analysis:

Calorie Consumption:

Based on the results, it was observed that daily calorie consumption is in

fact inversely proportional to male and female life expectancies. As daily caloric

intake decreases, life expectancy can be expected to increase in both males and

females. The negative sloping lines of best fit in Graphs 1 and 2 clearly represent

this inversely proportional trend. Thus, the alternative hypothesis was correct in

stating that there is a relationship, a negative one, between calorie intake and life

expectancy. The regression analysis conducted shown in Tables 6 and 7 also

provides evidence for this relationship. It was also observed that from 1997 to

2007 there was a large increase in calorie consumption for many nations within

this analysis. There are many plausible reasons for this increase. For example,

with increased technology and machinery home cooked meals are becoming a

rare commodity. Individuals can simply purchase frozen dinners, ready-made

breakfasts, or merely get meals from a fast food chain down the road. With

cheaper and more convenient options with lower opportunity costs, individuals

will of course choose options such as those mentioned above. The negative side

affects however is that the majority of these options are extremely unhealthy, full

of excess calories, sugars, and fats. It is definitely a possibility that as we

continue to make things more convenient and faster, we are also creating more

health problems for ourselves, which could eventually lead to more premature

deaths in adults.

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Countries like Japan that consume significantly less then the rest of the

world have been experiencing a greater life expectancy consistently for several

years now. 9 Although concrete studies have yet to be conducted using humans,

it has been proven that reduced calorie diets can in fact reduce the chances of

future health issues and complications. Essentially, lower calorie diets can lead

to healthier lives and thus an increased life expectancy.

Alcohol Consumption:

The alternative hypothesis was correct in stating that there will be an

inversely proportional relationship observed between life expectancy and alcohol

consumption. Once again, this is confirmed with the negative sloping lines of best

fit seen in Graphs 3 and 4. As previously mentioned, increased and excessive

alcohol consumption has scientifically proven detrimental health consequences.

Studies have shown that increased alcohol consumption cannot only result in

physical defects but also mental and psychological defects. Consuming alcohol

increases the risk of various cancers, liver disease, cardiovascular disease and

many more complications. Acquiring any of these known health conditions

seriously reduces one’s quality years of life and thus decreases life expectancy.

It was interesting to observe in the regression analysis shown in Table 7 that an

increase in one unit of alcohol consumption would increase female life

expectancy by (0.19156). It is very plausible that due to the small sample size,

(13 countries), and only data from two specific years, that the results were not

entirely accurate. Although alcohol consumption is not the only factor affecting

life expectancy, it most certainly is an influential factor that decreases the quality

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of health in an individual. Often, the simple act of reducing the amount of alcohol

consumption can improve one’s health.

Health Expenditures per capita:

A positive correlation between health expenditures and life expectancy

was observed once the results were analyzed. The positive sloping lines of best

fit in both Graphs 5 and 6 are evidence for this relationship. Regression analysis

coefficients also confirm that an increase in health care expenditures can result

in an increase in life expectancy. Although a positive correlation was found

between these two variables, in the real world it does not necessarily mean that

the nation with the highest health care expenditures will have the highest life

expectancy. The U.S. is the world-leading spender in health care per capita

however they have below average, according to values found in this report, life

expectancy. Japan on the other hand has below average health care

expenditures and experiences the highest life expectancy. A few plausible

reasons for the remarkably high expenditure in the U.S. could be the presence of

higher income earning citizens, or more citizens in the U.S. require health care

compared to other countries, or even the increase in prices for medical

treatments, procedures and other medical goods and services. With improved

technology and new medical advancements taking place, the medical field has

drastically changed in its ability to treat more variety of patients. Unfortunately,

prices for these new treatments and procedures continue to rise and thus so do

health care expenditures. For the majority of the countries in this report, health

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care expenditures greatly increased during the 10-year period and a most likely

reason for this is the improvement in technology that occurred during those year.

Conclusion:

In conclusion, there are numerous factors that attribute to the differences

seen in life expectancy within developed nations. Data for both daily calorie

intake and alcohol consumption revealed that a negative relationship exists

between these two variables and life expectancy, as expected. It is known that

excessive alcohol consumption can lead to future health problems and that lower

calorie diets, in certain mammals, can reduce the risk of acquiring future health

issues. Thus, these results were accurate with previous research studies. The

health expenditures per capita data showed a positive relationship. These overall

results confirmed the alternative hypothesis previously stated. Since the sample

size was small due to lack of certain data and only two years were taken into

consideration, the results noted in this paper are not entirely conclusive. They are

indicative of possible trends however. There are many other factors, other then

the three chosen that can be taken into account in order to obtain more accurate

observations about the differences in life expectancy within developed nations.

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