life expectancy

n.
The number of years that an individual is expected to live as determined by statistics.

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life expectancy

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age to which an average person can be expected to live, as calculated by an Actuary. Insurance companies base their projections of benefit payouts on actuarial studies of such factors as sex, heredity, and health habits and base their rates on actuarial analysis.
Life expectancy can be calculated at birth or at some other age and generally varies according to age. Thus, all persons at birth might have an average life expectancy of 80 years and all persons aged 40 years might have an average life expectancy of 85 years.
Life expectancy projections determine such matters as the ages when an individual retirement account may start and finish withdrawing funds. Annuities payable for lifetimes are usually based on separate male or female tables, except that a qualified plan or trust must use unisex tables.

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Gale Encyclopedia of Public Health:

Life Expectancy and Life Tables

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A life table converts a set of age-specific mortality rates into a survival curve, from which summary statistics, such as life expectancy, can be derived. The procedure was developed first for humans, primarily for the purpose of calculating premiums for life insurance and annuities. Later the same approach was used to study the survival of patients, other living species, and inanimate objects.

Crude life tables were produced by the Roman Aemilius Macer in Rome in 225 C.E., and by John Graunt and William Petty in the seventeenth century. The astronomer Edmund Halley, in 1693, was the first to employ correct mathematical methods to calculate a life table, using vital statistics collated by Caspar Neumann of Breslau. Figure 1 shows Halley's Breslau life table, William Farr's life table for England and Wales 150 years later, and a life table for Canada 300 years later.

A life table is easy to calculate if the mortality rates are known for each year of age. Starting with an arbitrary large number, say 1,000, of newborn infants, the number surviving to age one year can be estimated from the mortality rate in the first year of life. Then the number surviving to the age two years can be estimated using the mortality rate in the second year of life, and so on.

In practice, calculations are complicated by the fact that the mortality rates for single years of age cannot be estimated precisely, even in large populations, and some form of smoothing is required. The sharp decline in mortality during infancy and childhood, and the small numbers in extreme old age, also create problems. However the simple method can be used to calculate abridged life tables, using mortality rates for broader age groups, which are more readily available. Such tables are usually sufficient for public health purposes.

Figure 2 shows the distribution of the ages at death implied by the English and Canadian life tables of Figure 1. In the earlier table the distribution has two peaks, one in the early childhood and the other in the 70–74 age group. In the later table the deaths in childhood have shifted to old age, producing a single peak at 80–84 years. The arithmetic mean of the distribution of ages at death is called life expectancy (i.e., expectation of life at birth), and is widely used as an indicator of the health of the population. The expectation of life at birth is forty-five years for the English life table and eighty-one years for the Canadian life table.

The vast majority of published life tables are period life tables, which are based on mortality rates over a limited time period. Since mortality changes over time, no actual population experiences the survival depicted in a period life table. Such a table represents, instead, a hypothetical, or synthetic, cohort. Comparing values of life expectancy from different period life tables is really equivalent to comparing age-standardized mortality rates, since reciprocal of life expectancy is a form of age-standardized mortality rate.

True cohort, or generation, life tables require age-specific mortality rates covering nearly 100 years. Table 1 shows the life expectancy for two completed cohorts. Life expectancy is consistently greater for females than for males, and the difference has widened over the sixty-year period between the two groups. Information on the cause of death can be incorporated into the life table calculations in two ways. First, it is possible to calculate the number, out of those alive at a given age, who will die subsequently from a particular cause. Second, the gain in life expectancy which would be obtained by eliminating a particular cause of death can be calculated.

As life expectancy increases toward its natural upper limit, life tables become less useful as indices of the health of a population. Beginning in the 1960s procedures were developed to incorporate information on disability into life tables. The simplest approach is to multiply the number living at a

Table 1

Mean and Median Survival (Years) in Two Canadian Cohort Life Tables
Cohort Date of Birth	1831		1891
	Males	Femals	Males	Femals
SOURCE: Statistics Canada. Report on the Demographic Situation in Canada 1992. Current Demographic Analysis. Ottawa: Minister of Industry, Science and Technology, 1992; p. 150
Mean Survival (e₀) 4	0	42	49	54
Median Survival	45	48	62	68

given age, derived from a current life table, by the proportion of the population at that age who are found, in a health survey, to be free of disability. The sum of these products over the life span gives the disability-free life expectation. In such calculations people are considered to be either disabled or not disabled, and the definition is somewhat arbitrary. The method can be expanded to incorporate different levels of disability, which are weighted to give the disability-adjusted life expectancy.

Bibliography

Benjamin, B. (1968). Demographic Analysis. London: George Allen and Unwin, Ltd.

Chiang, C. L. (1984). The Life Table and Its Applications. Malabar, FL: Robert E. Krieger Publishing Company.

Colvez, A., and Blanchet, M. (1983). "Potential Gains in the Life Expectancy Free of Disability: A Tool for Health Planning." International Journal of Epidemiology 12:224, 229.

Preston, S. H.; Keyfitz, N.; and Schoen, R. (1972). Causes of Death. Life Tables for National Populations. New York and London: Seminar Press.

Statistics Canada (1992). Report on the Demographic Situation in Canada 1992. Current Demographic Analysis. Ottawa: Minister of Industry, Science and Technology.

— GERRY B. HILL

Oxford Dictionary of Geography:

life expectancy

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The average number of years which an individual can expect to live in a given society, normally derived from a national life table. Life expectancy is usually given from birth but may apply at any age, and because, in all societies, mortality rates tend to be rather high in the first year of life, life expectancy at birth is usually significantly lower than at one year old. Women consistently have a longer life expectancy than men, especially in more economically developed countries where the risks of childbirth are less than those in less developed countries. Between 1970 and 1998, world life expectancy rose from 56 to 64; from 72 to 78 in the industrialized countries, and from 53 to 62 in the developing countries (Unicef 2000, The State of the World's Children).

The lower life expectancies for less economically developed countries shown above generally reflect high infant mortality rates, but by the age of 70, the years of life remaining to an individual are, globally, very similar. Thus, the strong correlation between GDP per capita and life expectancy becomes weaker as the age of an individual increases.

Oxford Dictionary of Archaeology:

life expectancy

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[Ge]

The number of further years that people of a given age can, on average, expect to live.

Gale Encyclopedia of US History:

Life Expectancy

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Life Expectancy at birth is defined as the average number of years that a newborn would live under mortality conditions prevailing at that time. For example, life expectancy for females born in the United States in 1900 was forty-nine years. This means that if mortality conditions existing in 1900 did not change, baby girls born at that time would have lived, on average, until they were forty-nine. In addition to life expectancy at birth, one can also examine life expectancy at other ages. For example, life expectancy at age sixty (which was fifteen years for women in 1900) is the average number of years of life remaining for someone who survives to age sixty, under mortality conditions prevailing at that time. A life table provides information on life expectancy at various ages. When correctly understood, life expectancy provides a useful summary measure of mortality conditions at a particular time in history.

Although life expectancy is a good starting point for discussing mortality patterns, it is important to note two significant limitations of this measure. First, mortality conditions often change over time, so this measure may not reflect the actual experience of a birth cohort. (A birth cohort consists of all individuals born in a particular time period.) To illustrate this point, females born in the United States in 1900 actually lived for an average of fifty-eight years. The discrepancy between life expectancy in 1900 and the average years lived by those born in 1900 occurred because mortality conditions improved as this cohort aged over the twentieth century. The second limitation of life expectancy as a mortality index is its failure to reveal anything about the distribution of deaths across ages. Relatively few of the girls born in 1900 actually died around age forty-nine; 20 percent died before reaching age ten, and over fifty percent were still alive at age seventy. In other words, the average age at death does not mean that this was the typical experience of individuals. Given the limited information contained in the life expectancy statistic, a satisfying discussion of changing mortality experiences in American history must use additional information on the timing and patterning of deaths.

To calculate the life expectancy for a population, one would ideally have a complete registration of deaths by age and a complete enumeration of the population by age. With these data, it is a straightforward exercise to calculate age-specific death rates and to construct the life table. In the United States, mortality and population data of good quality are available for most of the twentieth century, so we can report with confidence life expectancy patterns over this period. Because of data limitations, there is less certainty about mortality conditions in earlier American history. However, a number of careful and creative studies of the existing death records for some communities (or other populations) provide enough information to justify a discussion of changing mortality conditions from the colonial era to the present.

Colonial America

The first life table for an American population was published by Edward Wigglesworth in 1793, and was based on mortality data from Massachusetts, Maine, and New Hampshire in 1789. Until the 1960s, this life table, which reported an expectation of life of about thirty-five years for New England, was the primary source of information on the level of mortality in America prior to the nineteenth century. Since the 1960s, however, quantitative historians have analyzed a variety of mortality records from various sources, providing a more comprehensive and varied picture of mortality conditions in the colonial era.

These historical studies have presented conflicting evidence regarding the trend in life expectancy between the founding of the colonies and the Revolutionary War (1775–1783)—some reported a significant decline over time, while others argued that life expectancy was increasing. One explanation for the different findings is that there were large fluctuations in death rates from year to year (as epidemics broke out and then rescinded) and significant variations across communities. Based on the most reliable data, it seems likely that overall conditions were not much different around 1800 than they were around 1700. After considerable work to analyze data from various sources, the Wigglesworth estimate of life expectancy around thirty-five years in New England during the colonial period appears reasonable. Although this is an extraordinarily low life expectancy by contemporary standards, it reflects a higher survival rate than the population of England enjoyed at that time. Life expectancy in the Southern and Mid-Atlantic colonies, where severe and frequent epidemics of smallpox, malaria, and yellow fever occurred throughout the eighteenth century, was significantly lower than in New England.

There are two primary reasons life expectancy was so low in colonial America. First, the average years lived reflects the impact of many babies dying in infancy or childhood. Studies from various communities found that between 10 and 30 percent of newborns died in the first year of life (now only seven out of 1,000 die before age one). Those who survived the perilous early years of life and reached age twenty could expect, on average, to live another forty years. The second factor was that, lacking public health and medical knowledge of how to prevent or treat infectious diseases, the population was extremely vulnerable to both endemic diseases (malaria, dysentery and diarrhea, tuberculosis) and epidemics (smallpox, diphtheria, yellow fever). An indication of the deadly potential of epidemics is seen in Boston in 1721, when 10 percent of the population died in one year from a smallpox out-break, and in New Hampton Falls, New Hampshire, in 1735, when one-sixth of the population died from a diphtheria epidemic. Despite the dramatic effects of epidemics, it was the infectious endemic diseases that killed most people in colonial America.

Nineteenth Century

Life expectancy increased significantly over the nineteenth century, from about thirty-five years in 1800 to forty-seven years in 1900. However, this increase was not uniform throughout the century. In fact, death rates may have increased during the first several decades, and by midcentury, life expectancy was not much higher than it had been at the beginning of the century. After the Civil War (1861–1865) there was a sustained increase in life expectancy, and this upward trend would continue throughout the twentieth century.

Two conflicting forces were influencing mortality patterns prior to the Civil War. On one hand, per capita income was increasing, a trend that is generally associated with increasing life expectancy. On the other hand, the proportion of the population living in urban areas was also increasing, and death rates were higher in urban than in rural environments. An examination of data from 1890, for example, found death rates 27 percent higher in urban areas than in rural areas. This excess mortality in urban areas was common in almost all societies before the twentieth century, and is explained by the greater exposure to germs as population density increased. Studies of nineteenth century death rates in such cities as New York, Philadelphia, Baltimore, Boston, and New Orleans document the high risks that urban residents had of contracting such infectious diseases as tuberculosis, pneumonia, cholera, typhoid, and scarlet fever. It was not until after the 1870s that the health picture in American cities improved and life expectancy for the entire population began its steady ascent.

It is clear that increasing life expectancy in the last third of the nineteenth century was due to decreasing death rates from infectious diseases. But why did death rates decline? Medical historians have given considerable attention to three possible explanations: improving medical practices, advances in public health, and improved diet, housing, and personal hygiene. Most agree that medicine had little to do with the decline in infectious diseases in the nineteenth century (although it later played an important role when penicillin and other antibiotic drugs became widely used after 1940). Physicians in the nineteenth century had few specific remedies for disease, and some of their practices (bleeding and purging their patients) were actually harmful. Some evidence suggests that diet and personal hygiene improved in the late nineteenth century, and these changes may account for some decline in diseases. The greatest credit for improving life expectancy, however, must go to intentional public health efforts. With growing acceptance of the germ theory, organized efforts were made to improve sanitary conditions in the large cities. The construction of municipal water and sewer systems provided protection against common sources of infection. Other important developments included cleaning streets, more attention to removal of garbage, draining stagnant pools of water, quarantining sick people, and regulating foodstuffs (especially the milk supply).

Twentieth Century

The gain in life expectancy at birth over the twentieth century, from forty-seven to seventy-seven years, far exceeded the increase that occurred from the beginning of human civilization up to 1900. This extraordinary change reflects profound changes both in the timing of deaths and the causes of deaths. In 1900, 20 percent of newborns died before reaching age five—in 1999, fewer than 20 percent died before age sixty-five. In 1900, the annual crude death rate from infectious diseases was 800 per 100,000—in 1980 it was thirty-six per 100,000 (but it crept back up to sixty-three per 100,000 by 1995, because of the impact of AIDS). At the beginning of the twentieth century the time of death was unpredictable and most deaths occurred quickly. By the end of the century, deaths were heavily concentrated in old age (past age seventy), and the dying process was often drawn out over months.

In 1999, the Centers for Disease Control ran a series in its publication Morbidity and Mortality Weekly Report to highlight some of the great public health accomplishments of the twentieth century. Among the most important accomplishments featured in this series that contributed to the dramatic increase in life expectancy were the following:

Vaccinations. Vaccination campaigns in the United States have virtually eliminated diseases that were once common, including diphtheria, tetanus, poliomyelitis, smallpox, measles, mumps, and rubella.

Control of infectious diseases. Public health efforts led to the establishment of state and local health departments that contributed to improving the environment (clean drinking water, sewage disposal, food safety, garbage disposal, mosquito-control programs). These efforts, as well as educational programs, decreased exposure to micro-organisms that cause many serious diseases (for example, cholera, typhoid, and tuberculosis).

Healthier mothers and babies. Deaths to mothers and infants were reduced by better hygiene and nutrition, access to prenatal care, availability of antibiotics, and increases in family planning programs. Over the century, infant death rates decreased by 90 percent and maternal mortality rates decreased by 99 percent.

Safer workplaces. Fatal occupational injuries decreased 40 percent after 1980, as new regulations greatly improved safety in the mining, manufacturing, construction, and transportation industries.

Motor vehicle safety. Important changes affecting vehicle fatalities include both engineering efforts to make highways and vehicles safer and public campaigns to change such personal behaviors as use of seat belts, use of child safety seats, and driving while drunk. The number of deaths per million vehicle miles traveled was 90 percent lower in 1997 than in 1925.

Recognition of tobacco use as a health hazard. Anti-smoking campaigns since the 1964 Surgeon General's report have reduced the proportion of smokers in the population and consequently prevented millions of smoking-related deaths.

Decline in deaths from coronary heart disease and stroke.

Educational programs have informed the public of how to reduce risk of heart disease through smoking cessation, diet, exercise, and blood pressure control. In addition, access to early detection, emergency services, and better treatment has contributed to the 51 percent decrease since 1972 in the death rate from coronary heart disease.

Despite the advances in life expectancy between 1900 and the present, several striking differences in longevity within the population have persisted. Researchers have given a lot of attention to three differentials in life expectancy—sex, race, and social class. The female advantage over males in life expectancy increased from 2.0 years in 1900 to 7.8 years in 1975. Most of this increasing gap is explained by the shift in cause of death from infectious diseases (for which females have no survival advantage over males) to degenerative diseases (where the female advantage is large). Also, the decline in deaths associated with pregnancy and childbearing contributed to the more rapid increase in life expectancy of females. After 1975, the gender gap in life expectancy decreased, and by 2000 it was down to 5.4 years. The primary explanation for the narrowing gap in the last decades of the twentieth century is that female cigarette smoking increased rapidly after mid-century and became increasingly similar to the male pattern. In other words, females lost some of the health advantage over males that they had when they smoked less.

The racial gap in life expectancy was huge in 1900—white Americans outlived African Americans by an average of 14.6 years. This gap declined to 6.8 years by 1960 (when the civil rights movement was beginning), but declined only slightly over the rest of the century (in 2000 the racial gap was still 5.6 years). A particularly telling indicator of racial inequality is the infant mortality rate, which continues to be more than twice as large for African Americans as for white Americans (13.9 per 1,000 versus 6.0 per 1,000 in 1998). Much of the racial disparity is explained by the persistent socioeconomic disadvantage of African Americans (lower education and lower income). Social resources are related to individual health behavior (diet, exercise, health care), and to the environment within which individuals live (neighborhood, occupation). After adjusting for family income and education, African Americans still experience some excess deaths compared to white Americans. A possible cause of this residual difference may be racial discrimination that causes stress and limits access to health care.

Active Life Expectancy

The marked declines in death rates that characterized the first half of the twentieth century appeared to end around the early 1950s, and life expectancy increased by only a few months between 1954 and 1968. A number of experts concluded that we should not expect further increases in life expectancy. They reasoned that by this time a majority of deaths were occurring in old age due to degenerative diseases, and there was no historical evidence that progress could be made in reducing cardiovascular diseases and cancer. But this prediction was wrong, and life expectancy continued its upward climb after 1970. As death rates for older people began to fall, a new concern was expressed. Were the years being added to life "quality years," or were people living longer with serious functional limitations? Would we experience an increasingly frail older population?

The concern over quality of life in old age led demographers to develop a new measure, active life expectancy. Using data on age-specific disability rates, it is possible to separate the average number of years of life remaining into two categories—active years (disability-free years) and inactive years (chronic disability years). Using data since 1970, researchers have tried to determine whether gains in life expectancy have been gains in active life, gains in inactive life, or gains in both. There is some uncertainty about the 1970s, but since 1980 most of the gains have been in active life. Age-specific disability rates have been declining, so the percentage of years lived that is in good health is increasing. Two factors have contributed to increasing active-life expectancy. First, over time the educational level of the older population has risen, and disability rates are lower among more highly educated people. Second, medical advances (for example, cataract surgery, joint replacement) have reduced the disabling effect of some diseases. Thus, the good news is that at the end of the twentieth century, individuals were living both longer and healthier lives than ever before in history.

Bibliography

CDC. "Ten Great Public Health Achievements—United States, 1900–1999." Morbidity and Mortality Weekly Report 48 (1999): 241–243.

Crimmins, Eileen M., Yasuhiko Saito, and Dominique Ingegneri. "Trends in Disability-Free Life Expectancy in the United States, 1970–90." Population and Development Review 23 (1997): 555–572.

Hacker, David J. "Trends and Determinants of Adult Mortality in Early New England." Social Science History 21 (1997): 481–519.

Kunitz, Stephen J. "Mortality Change in America, 1620–1929." Human Biology 56 (1984): 559–582.

Leavitt, Judith Walzer, and Ronald L. Numbers, eds. Sickness and Health in America: Readings in the History of Medicine and Public Health. 3d ed. Madison: University of Wisconsin Press, 1997.

Vinovskis, Maris A. "The 1789 Life Table of Edward Wiggles-worth." Journal of Economic History 31 (1971): 570–590.

Gale Nutrition Encyclopedia:

Life Expectancy

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The term life expectancy is used to describe the average life span of an individual. Life expectancy can vary considerably in different areas of the world. Compared to other advanced countries, for example, people in the United States "die earlier and spend more time disabled" (WHO, 2000). Factors that affect life expectancy in the United States include: (1) the HIV epidemic, (2) cancers relating to tobacco, (3) high rates of coronary heart disease, (4) poor health among minority groups living in rural areas, and (5) high levels of violence.

According to the World Health Organization (WHO) the Japanese have the longest healthy life expectancy (74.5) among 191 countries the organization examined in 2000. In contrast, the shortest life expectancy (26 years) exists among the people of Sierra Leone. These figures were based on a new method of calculating healthy life expectancy called Disability Adjusted Life Expectancy (DALE), which was developed by the WHO. DALE summarizes the expected number of years to be lived in adequate health, rather than just the expected number of years lived.

According to DALE the United States ranks twenty-fourth, with an average life expectancy of 70.0 years for babies born in 1999. (Examined by gender, U.S. female babies in 1999 could expect 72.6 years of life, while male babies could expect only 67.5 years.) Life expectancy based on DALE for other countries are: Australia, 73.2 years; France, 73.1; Sweden, 73.0; Spain, 72.8; Italy, 72.7; Greece, 72.5; Switzerland, 72.5; Monaco, 72.4; and Andorra, 72.3.

The world's average life expectancy at birth rose to 67 years in 1998 (from 61 years in 1980). Although individual countries vary in average life-span years, the average number of years has increased due to increases in intake of nutritious food, primary health care (including safe water, sanitation, and immunizations), and education.

See also Infant mortality rate; Maternal mortality rate.

Internet Resources
World Bank. "Life Expectancy." Available from http://www.worldbank.org/depweb/english/modules
World Health Organization (2000). "Japan Number One in New 'Healthy Life' System." Available from http://www.int/inf-pr-2000/en/pr2000-life.html

Barron's Law Dictionary:

life expectancy

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The period of time a person is predicted to live, based on their present age and sex. This figure is most frequently used by actuaries to determine insurance premiums.

Investopedia Financial Dictionary:

Life Expectancy

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1. The age until which a person is expected to live.

2. The remaining number of years an individual is expected to live, based on IRS issued life expectancy tables. The life expectancy, for required minimum distribution (RMD) calculation purposes, is determined by the current age of the individual.

Investopedia Says:
1. Also referred to as the average life span. It is used mainly by insurance companies to determine your premium.

2. The IRS life expectancy tables are used to calculate the RMD for retirement account owners and their beneficiaries.

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Mosby's Dental Dictionary:

life expectancy

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The probable number of years a person will live after a given age, as determined by the mortality rate in a specific geographic area. This number may be individually qualified by the person’s condition, race, sex, age, and other demographic factors.

Random House Word Menu:

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For a list of words related to life expectancy, see:

Populations and Resources - life expectancy: statistical estimate of the number of years an individual is expected to live, based on such criteria as sex, race, health, and occupation

Wikipedia on Answers.com:

Life expectancy

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This article is about the measure of remaining life. For the Dean Koontz novel, see Life Expectancy (novel). For List of countries by life expectancy, see List of countries by life expectancy.

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This article may require cleanup to meet Wikipedia's quality standards. (Consider using more specific cleanup instructions.) Please help improve this article if you can. The talk page may contain suggestions. (June 2009)

Life expectancy is the expected (in the statistical sense) number of years of life remaining at a given age.^[1] It is denoted by e_x, which means the average number of subsequent years of life for someone now aged x, according to a particular mortality experience. (In technical literature, this symbol means the average number of complete years of life remaining, excluding fractions of a year. The corresponding statistic including fractions of a year, the normal meaning of life expectancy, has a symbol with a small circle over the e.) In modern times, life expectancy has substantially changed on a yearly basis and cannot be used accurately for long-term predictions.^{[citation needed]}

The term that is known as life expectancy is most often used in the context of human populations, but is also used in plant or animal ecology;^[2] it is calculated by the analysis of life tables (also known as actuarial tables). The term life expectancy may also be used in the context of manufactured objects^[3] although the related term shelf life is used for consumer products and the terms "mean time to breakdown" (MTTB) and "mean time before failures" (MTBF) are used in engineering literature.

Contents

1 Interpretation of life expectancy
2 Human life expectancy patterns
3 Evolution and aging rate
4 Calculating life expectancies
5 Life expectancy forecasting
6 Policy uses of life expectancy
7 Life expectancy vs. life span
8 See also
- 8.1 Increasing life expectancy
9 References
- 9.1 Further reading
10 External links

Interpretation of life expectancy

General explanation: It is important to note that life expectancy is an average. In many cultures, particularly before modern medicine was widely available, the combination of high infant mortality and deaths in young adulthood from accidents, wars, and childbirth, significantly lowers the overall life expectancy. But for someone who survived past these early hazards, living into their sixties or seventies would not be uncommon. For example, a society with a life expectancy of 40 may have very few people dying at age 40, most will die before 30 or after 55.

In countries with high infant mortality rates, the life expectancy at birth is highly sensitive to the rate of death in the first few years of life. Because of this sensitivity to infant mortality, simple life expectancy at age zero can be subject to gross misinterpretation, leading one to believe that a population with a low overall life expectancy will necessarily have a small proportion of older people. For example, in a hypothetical stationary population in which half the population dies before the age of five, but everybody else dies exactly at 70 years old, the life expectancy at age zero will be about 37 years, while about 25% of the population will be between the ages of 50 and 70. Another measure such as life expectancy at age 5 (e₅) can be used to exclude the effect of infant mortality to provide a simple measure of overall mortality rates other than in early childhood—in the hypothetical population above, life expectancy at age 5 would be another 65 years. Aggregate population measures such as the proportion of the population in various age classes should also be used alongside individual-based measures like formal life expectancy when analyzing population structure and dynamics.

Human life expectancy patterns

Humans live on average 31.88 years in Swaziland and 82.6 years in Japan, although Japan's recorded life expectancy may have been very slightly increased by counting many infant deaths as stillborn.^[4] An analysis published in 2011 in The Lancet attributes Japanese life expectancy to equal opportunities and public health as well as diet.^[5]^[6]

The oldest confirmed recorded age for any human is 122 years (see Jeanne Calment). This is referred to as the "maximum life span", which is the upper boundary of life, the maximum number of years any human is known to have lived.^[7]

Life expectancy variation over time

This section may be confusing or unclear to readers. Please help clarify the section; suggestions may be found on the talk page. (September 2011)

The following information is derived from Encyclopædia Britannica, 1961 and other sources, and unless otherwise stated represents estimates of the life expectancies of the population as a whole. In many instances life expectancy varied considerably according to class and gender.

Life expectancy at birth takes account of infant mortality but not pre-natal mortality.

Era	Life Expectancy at Birth (years)	Comment
Upper Paleolithic	33	At age 15, life expectancy an additional 39 years (total age 54).^[8]^[9]
Neolithic^[10]	20
Bronze Age and Iron Age^[11]	26
Classical Greece^[12]	28
Classical Rome^[12]	28	At age 15, life expectancy an additional 37 years (total age 52).
Pre-Columbian North America^[13]	25-30
Medieval Islamic Caliphate^[14]	35+
Medieval Britain^[15]^[16]	30	At age 21, life expectancy an additional 43 years (total age 64).^[17]
Early Modern Britain^[11]^[18]	25-40
Early 20th Century^[19]^[20]	31
Current world average^[21]	67.2	2010 est.

In some cases life expectancy may increase with age as the individual survives the higher mortality rates associated with childhood. For instance, the table above listed life expectancy at birth in Medieval Britain at 30. A male member of the English aristocracy at the same period could expect to live, having survived until the age of 21^[17]:

1200-1300 A.D.: 43 years (to age 64)
1300-1400 A.D.: 24 years (to age 45) (due to the impact of the Black Death)
1400-1500 A.D.: 48 years (to age 69)
1500-1550 A.D.: 50 years (to age 71).

In general, the available data indicate that longer lifespans became more common recently in human evolution.^[9]^[22] This increased longevity is attributed by some writers to cultural adaptations rather than genetic evolution,^[23] although some research indicates that during the Neolithic Revolution natural selection favored increased longevity.^[10] Nevertheless, all researchers acknowledge the effect of cultural adaptations upon life expectancy.^[22]

During the early 1600s in England, life expectancy was only about 35 years, largely because two-thirds of all children died before the age of four.^[24] The average life expectancy in Colonial America was under 25 years in the Virginia colony,^[25] and in New England about 40% of children failed to reach adulthood.^[26] During the Industrial Revolution, the life expectancy of children increased dramatically.^[27] The percentage of children born in London who died before the age of five decreased from 74.5% in 1730-1749 to 31.8% in 1810-1829.^[28]^[29]

Public health measures are credited with much of the recent increase in life expectancy. During the 20th century, the average lifespan in the United States increased by more than 30 years, of which 25 years can be attributed to advances in public health.^[30]

In order to assess the quality of these additional years of life, 'healthy life expectancies' have been calculated for the last 30 years. Since 2001, the World Health Organization publishes statistics called Healthy life expectancy (HALE), defined as the average number of years that a person can expect to live in "full health", excluding the years lived in less than full health due to disease and/or injury. Since 2004, Eurostat publishes annual statistics called Healthy Life Years (HLY) based on reported activity limitations. The United States of America uses similar indicators in the framework of their nationwide health promotion and disease prevention plan "Healthy People 2010". An increasing number of countries are using health expectancy indicators to monitor the health of their population.

Further information: Longevity

Regional variations

Further information: List of countries by life expectancy

World map on life expectancy from WLE

+80

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- 40

Plot of life expectancy vs. GDP per capita in 2009.

Graphs of life expectancy at birth for some sub-Saharan countries showing the fall in the 1990s primarily due to the AIDS pandemic.^[31]

There are great variations in life expectancy between different parts of the world, mostly caused by differences in public health, medical care and diet. Much of the excess mortality (higher death rates) in poorer nations is due to war, starvation, and diseases (AIDS, Malaria, etc.). The impact of AIDS is particularly notable on life expectancy in many African countries; According to the UN^[32] the life expectancy at birth for 2010–2015 (if HIV/AIDS did not exist) would have been:

70.7 years instead of 31.6 in Botswana
69.9 years instead of 41.5 in South Africa
70.5 years instead of 31.8 in Zimbabwe.

As a result, over the past 200 years, countries with African populations have generally not had the same improvements in mortality rates that have been enjoyed by populations of Asian, Latin American or European origin. Notably, even in countries with a majority of European people, such as the United States, Britain, or Ireland, African people still tend to have shorter life expectancies than their European counterparts. For example, in the United States, Euro-Americans are expected to live until age 78.2, but African Americans only until age 73.6.^[33]

In contrast, Asian-Americans live the longest of all ethnic groups in the United States, with a life expectancy of 87 years, almost ten years longer than Euro-Americans.,^[34] which falls in line with the longer life expectancy among East Asian countries globally compared to European, Latin American or African countries. Surprisingly, Latino-Americans are second place among ethnic groups on life expectancy, living on average two years longer than Euro-Americans and seven years longer than African-Americans, with a life expectancy of 80.6 years.,^[35] in contrast to the on average lower life expectancy of most Latin American countries. These variations among ethnic groups may be ascribed to differing economic circumstances of the groups, and in the United States, notably differing access to health care. It may also be ascribed to different cultural patterns of eating or diet that may cross international lines and explain the variation within ethnic groups in a multiethnic society such as the United States.

Climate may also have an effect, and the way data is collected may also influence the figures.

Economic circumstances may also affect life expectancy. For example, in the United Kingdom, life expectancy in the wealthiest areas is several years longer than in the poorest areas. This may reflect factors such as diet and lifestyle as well as access to medical care. It may also reflect a selective effect: people with chronic life-threatening illnesses are less likely to become wealthy or to reside in affluent areas.^[36] In Glasgow the disparity is among the highest in the world with life expectancy for males in the heavily deprived Calton standing at 54 – 28 years less than in the affluent area of Lenzie, which is only eight kilometres away.^[37]^[38]

The relationship between economic circumstance and life expectancy is not clear-cut, however. A study by José A. Tapia Granados and Ana Diez Roux at the University of Michigan found that life expectancy actually increased during the Great Depression, and during recessions and depressions in general.^[39] The authors suggest that when people are working extra hard during good economic times, they undergo more stress, exposure to pollution, and likelihood of injury among other longevity-limiting factors.

Life expectancy is also likely to be affected by exposure to high levels of highway air pollution or industrial air pollution.^{[citation needed]} This is one way that occupation can have a major effect on life expectancy. Coal miners (and in prior generations, asbestos cutters) often have shorter than average life expectancies. Other factors affecting an individual's life expectancy are genetic disorders, obesity, access to health care, diet, exercise, tobacco smoking, drug use and excessive alcohol use.

Sex differences

Comparison of male and female life expectancy at birth for countries and territories as defined in the 2011 CIA Factbook, with selected bubbles labelled. The dotted line corresponds to equal female and male life expectancy. The apparent 3D volumes of the bubbles are linearly proportional to their population.^[40]^[41]

Women tend to have a lower mortality rate at every age. In the womb, male fetuses have a higher mortality rate (babies are conceived in a ratio estimated to be from 107 to 170 males to 100 females, but the ratio at birth in the United States is only 105 males to 100 females).^[42] Among the smallest premature babies (those under 2 pounds or 900 g) females again have a higher survival rate. At the other extreme, about 90% of individuals aged 110 are female. The difference in life expectancy between men and women in the United States dropped from 7.8 years in 1979 to 5.3 years in 2005, with women expected to live to age 80.1 in 2005.^[43]

In the past, mortality rates for females in child-bearing age groups were higher than for males at the same age. This is no longer the case, and female human life expectancy is considerably higher than that of men. The reasons for this are not entirely certain. Traditional arguments tend to favor socio-environmental factors: historically, men have generally consumed more tobacco, alcohol and drugs than females in most societies, and are more likely to die from many associated diseases such as lung cancer, tuberculosis and cirrhosis of the liver.^[44] Men are also more likely to die from injuries, whether unintentional (such as car accidents) or intentional (suicide, violence, war).^[44] A 2005 study found that the level of patriarchy predicts men's mortality rates. High levels of patriarchy were associated with high levels of male mortality; low levels of patriarchy were correlated with low mortality levels. The researchers argue that while patriarchy grants men certain privileges over women, it also promotes gender stereotypes which harm men.^[45] Men are also more likely to die from most of the leading causes of death (some already stated above) than women. Some of these in the United States include: cancer of the respiratory system, motor vehicle accidents, suicide, cirrhosis of the liver, emphysema, and coronary heart disease.^[7] These far outweigh the female mortality rate from breast cancer and cervical cancer etc.

Some argue that shorter male life expectancy is merely another manifestation of the general rule, seen in all mammal species, that larger individuals tend on average to have shorter lives.^[46]^[47] This biological difference occurs because women have more resistance to infections and degenerative diseases.^[7]

In her extensive review of the existing literature, Kalben concluded that the fact that women live longer than men was observed at least as far back as 1750 and that, with relatively equal treatment, today males in all parts of the world experience greater mortality than females. Of 72 selected causes of death, only 6 yielded greater female than male age-adjusted death rates in 1998 in the United States. With the exception of birds, for almost all of the animal species studied, the males have higher mortality than the females. Evidence suggests that the sex mortality differential in humans is due to both biological/genetic and environmental/behavioral risk and protective factors.^[48]

Centenarians

In developed countries, the number of centenarians is increasing at approximately 5.5% per year, which means doubling the centenarian population every 13 years, pushing it from some 455,000 in 2009 to 4.1 million in 2050.^[49] Japan is the country with the highest ratio of centenarians (347 for every 1 million inhabitants in September 2010). Shimane prefecture had an estimated 743 centenarians per million inhabitants.^[50]

In the United States, the number of centenarians grew from 32,194 in 1980 to 71,944 in November 2010 (232 centenarians per million inhabitants).^[51]

Mentally ill

Adults with serious mental illness (SMI) die about 25 years earlier, on average at age 51 versus 76 for Americans generally, primarily due to cardiovascular disease.^[52]^[53]

Evolution and aging rate

Various species of plants and animals, including humans, have different lifespans. There is an evolutionary theory of aging, and general consensus in the academic community of evolutionary theorists; however the theory doesn't work well in practice, and there are many unexplained exceptions. Evolutionary theory states that organisms that, by virtue of their defenses or lifestyle, live for long periods whilst avoiding accidents, disease, predation, etc., are likely to have genes that code for slow aging - which often translates to good cellular repair. This is theorized to be true because if predation or accidental deaths prevent most individuals from living to an old age, then there will be less natural selection to increase intrinsic life span.^[54] The finding was supported in a classic study of opossums by Austad,^[55] however the opposite relationship was found in an equally-prominent study of guppies by Reznick.^[56]^[57]

One prominent and very popular theory attributes aging to a tight budget for food energy called caloric restriction.^[58] Caloric restriction observed in many animals (most notably mice and rats), shows a near doubling of life span due to a very limited calorific intake. Support for this theory has been bolstered by several new studies linking lower basal metabolic rate to increased life expectancy.^[59]^[60]^[61] This is the key to why animals like Giant Tortoises can live so long.^[62] Studies of humans with 100+ year life spans have shown a link to decreased thyroid activity, resulting in their lowered metabolic rate.^[63]

In theory, reproduction is costly and takes energy away from the repair processes that extend life spans. However, in actuality females of many species invest much more energy in reproduction than do their male counterparts, and live longer nevertheless. In a broad survey of zoo animals, no relationship was found between the fertility of the animal and its life span.^[64]

Calculating life expectancies

The starting point for calculating life expectancies is the age-specific death rates of the population members. A very simple model of age-specific mortality uses the Gompertz function, although these days more sophisticated methods can be used.^[65]

In cases where the amount of data is relatively small, the most common methods are to fit the data to a mathematical formula, such as an extension of the Gompertz function, or to look at an established mortality table previously derived for a larger population and make a simple adjustment to it (e.g. multiply by a constant factor) to fit the data.

With a large amount of data, one looks at the mortality rates actually experienced at each age, and applies smoothing (e.g. by cubic splines) to iron out any apparently random statistical fluctuations from one year of age to the next.

While the data required are easily identified in the case of humans, the computation of life expectancy of industrial products and wild animals involves more indirect techniques. The life expectancy and demography of wild animals are often estimated by capturing, marking and recapturing them.^[66] The life of a product, more often termed shelf life is also computed using similar methods. In the case of long-lived components such as those used in critical applications, such as in aircraft methods such as accelerated aging are used to model the life expectancy of a component.^[3]

The age-specific death rates are calculated separately for separate groups of data which are believed to have different mortality rates (e.g. males and females, and perhaps smokers and non-smokers if data is available separately for those groups) and are then used to calculate a life table, from which one can calculate the probability of surviving to each age. In actuarial notation the probability of surviving from age x to age x+n is denoted $\,_np_x\!$ and the probability of dying during age x (i.e. between ages x and x+1) is denoted $q_x\!$ . For example, if 10% of a group of people alive at their 90th birthday die before their 91st birthday, then the age-specific death probability at age 90 would be 10%. Note that this is a probability rather than a mortality rate.

The life expectancy at age x, denoted $\,e_x\!$ , is then calculated by adding up the probabilities to survive to every age. This is the expected number of complete years lived (one may think of it as the number of birthdays they celebrate).

$e_x =\sum_{t=1}^{\infty}\,_tp_x = \sum_{t=0}^{\infty}t \,_tp_x q_{x+t}$

Because age is rounded down to the last birthday, on average people live half a year beyond their final birthday, so half a year is added to the life expectancy to calculate the full life expectancy. (This is denoted by $\,e_x\!$ with a circle over the "e".)

Life expectancy is by definition an arithmetic mean. It can also be calculated by integrating the survival curve from ages 0 to positive infinity (or equivalently to the maximum lifespan, sometimes called 'omega'). For an extinct or completed cohort (all people born in year 1850, for example), of course, it can simply be calculated by averaging the ages at death. For cohorts with some survivors, it is estimated by using mortality experience in recent years. These estimates are called period cohort life expectancies.

It is important to note that this statistic is usually based on past mortality experience, and assumes that the same age-specific mortality rates will continue into the future. Thus such life expectancy figures need to be adjusted for temporal trends before calculating how long a currently living individual of a particular age is expected to live. Period life expectancy remains a commonly used statistic to summarize the current health status of a population.

However for some purposes, such as pensions calculations, it is usual to adjust the life table used, thus assuming that age-specific death rates will continue to decrease over the years, as they have done in the past. This is often done by simply extrapolating past trends; however some models do exist to account for the evolution of mortality (e.g., the Lee-Carter model^[67]).

As discussed above, on an individual basis, there are a number of factors that have been shown to correlate with a longer life. Factors that are associated with variations in life expectancy include family history, marital status, economic status, physique, exercise, diet, drug use including smoking and alcohol consumption, disposition, education, environment, sleep, climate, and health care.^[7]

Life expectancy forecasting

Forecasting life expectancy and mortality forms an important subdivision of demography. Future trends in life expectancy have huge implications for old-age support programs like U.S. Social Security and pension systems, because the cash flow in these systems depends on the number of recipients still living (along with the rate of return on the investments or the tax rate in PAYGO systems). With longer life expectancies, these systems see increased cash outflow; if these systems underestimate increases in life-expectancies, they won't be prepared for the large payments that will inevitably occur as humans live longer and longer.

Life expectancy forecasting usually is based on two different approaches:

Forecasting the life expectancy directly, generally using ARIMA or other time series extrapolation procedures: This approach has the advantage of simplicity, but it cannot account for changes in mortality at specific ages, and the forecasted number cannot be used to derive other life table results. Analyses and forecasts using this approach can be done with any common statistical/ mathematical software package, like R, SAS, Matlab, or SPSS.

Forecasting age specific death rates and computing the life expectancy from the results with life table methods: This approach is usually more complex than simply forecasting life expectancy because the analyst must deal with correlated age specific mortality rates, but it seems to be more robust than simple one dimensional time series approaches. This approach also yields a set of age specific rates that may be used to derive other measures, like survival curves or life expectancies at different ages. The most important approach within this group is the Lee-Carter model,^[68] which uses the singular value decomposition on a set of transformed age-specific mortality rates to reduce their dimensionality to a single time series, forecasts that time series, and then recovers a full set of age-specific mortality rates from that forecasted value. Software for this approach include Professor Rob J. Hyndman's R package and UC Berkeley's LCFIT system.

Policy uses of life expectancy

This section requires expansion.

Life expectancy is one of the factors in measuring the Human Development Index (HDI) of each nation, along with adult literacy, education, and standard of living.^[69]

Life expectancy is also used in describing the physical quality of life of an area.

Life expectancies are also used when determining the value of a life settlement, a life insurance policy sold for a cash asset.

Life expectancy vs. life span

Life expectancy is often confused with life span to the point that they are nearly synonyms; when people hear 'life expectancy was 35 years' they often interpret this as meaning that people of that time or place had short life spans.^[70] One such example can be seen in the In Search of... episode "The Man Who Would Not Die" (About Count of St. Germain) where it is stated "Evidence recently discovered in the British Museum indicates that St. Germain may have well been the long lost third son of Rákóczi born in Transylvania in 1694. If he died in Germany in 1784, he lived 90 years. The average life expectancy in the 18th century was 35 years. Fifty was a ripe old age. Ninety... was forever."

This ignores the fact that the life expectancy generally quoted is the at birth number which is an average that includes all the babies that die before their first year of life as well as people that die from disease and war. The genetics of humans and rate of aging were no different in preindustrial societies than today, but people frequently died young because of untreatable diseases, accidents, and malnutrition. Many women did not survive childbirth, and when a person did reach old age they were likely to succumb quickly to health problems.

It can be argued that it is better to compare life expectancies of the period after adulthood to get a better handle on life span.^[71] Even during childhood life expectancy can take a huge jump as seen in the Roman Life Expectancy table at the University of Texas where at birth the life expectancy was 25 but at the age of 5 it jumped to 48. Studies like Plymouth Plantation; "Dead at Forty" and Life Expectancy by Age, 1850–2004 similarly show a dramatic increase in life expectancy once adulthood was reached.

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^ Ronald D. Lee and Lawrence Carter. 1992. "Modeling and Forecasting the Time Series of U.S. Mortality," Journal of the American Statistical Association 87 (September): 659-671.
^ http://www.soa.org/library/journals/north-american-actuarial-journal/2000/january/naaj0001_5.pdf
^ "International Human Development Indicators - UNDP". Hdrstats.undp.org. http://hdrstats.undp.org/indicators/6.html. Retrieved 2010-11-04.
^ Wanjek, Christopher (2002). Bad Medicine: Misconceptions and Misuses Revealed, from Distance Healing to Vitamin O. Wiley. pp. 70–71. ISBN 047143499X
^ Wanjek, Christopher (2002). Bad Medicine: Misconceptions and Misuses Revealed, from Distance Healing to Vitamin O. Wiley. p. 71. ISBN 047143499X

External links

Wikimedia Commons has media related to: Life expectancy

Charts for all countries
Rank Order - Life expectancy at birth from the CIA's World Factbook.
CDC year-by-year life expectancy figures for USA from the USA Centers for Disease Controls and Prevention, National Center for Health Statistics.
Life expectancy in Roman times from the University of Texas.
Animal lifespans: Animal Lifespans from Tesarta Online (Internet Archive); The Life Span of Animals from Dr Bob's All Creatures Site.

v d e Longevity

Terminology	Centenarian · Supercentenarian · Maximum life span · Life extension · Life expectancy · Immortality (Biological immortality)

Issues	Alleged Brazilian supercentenarians · Longevity claims · Incomplete longevity claims · Longevity myths · People reported to have lived beyond 130

Records	Oldest people · Oldest people by year of birth · 100 verified oldest people (males · females) · Oldest people by nation · Oldest living people by nation · Longest marriages · Oldest twins

Centenarians	Living · Activists, non-profit leaders, and philanthropists · Actors, filmmakers, and entertainers · Artists · Authors, poets, and journalists · Businessmen · Educators, school administrators, social scientists, and linguists · Explorers · Jurists and practitioners of law · Medical professionals · Military commanders · Musicians, composers, and music patrons · Philosophers and theologians · Politicians and government servants · Religious figures · Royalty and nobility · Scientists and mathematicians · Sportspeople · Miscellaneous

Supercentenarians	Living · Deaths by year (before 1980 · 1980s · 1990s · 2000 · 2001 · 2002 · 2003 · 2004 · 2005 · 2006 · 2007 · 2008 · 2009 · 2010 · 2011 · 2012) By continent (Europe) By country (Australia · Austria · Belgium · Canada · Denmark · Finland · France · Germany · Italy · Japan · Netherlands · Norway · Portugal · Spain · Sweden · United Kingdom · United States)

War-related lists	List of last surviving veterans of military insurgencies and wars (European · American · Canadian) · Last surviving World War I veterans by country · Surviving veterans of the Spanish Civil War · Living recipients of the Knight's Cross · Last survivors of historic events

Non-human	Long-living organisms · List of oldest trees · List of oldest dogs

See also Gerontology · Ageing · Life extension-related topics · Extreme longevity tracking · FOXO3 longevity gene

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life expectancy

life expectancy

life expectancy

Life Expectancy and Life Tables

life expectancy

life expectancy

Life Expectancy

Life Expectancy

life expectancy

Life Expectancy

life expectancy

categories related to 'life expectancy'

Life expectancy

Interpretation of life expectancy

Human life expectancy patterns

Life expectancy variation over time

Regional variations

Sex differences

Centenarians

Mentally ill

Evolution and aging rate

Calculating life expectancies

Life expectancy forecasting

Policy uses of life expectancy

Life expectancy vs. life span

See also

Increasing life expectancy

References

Further reading

External links

life expectancy