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
24
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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