Life Expectancy

Life expectancy refers to the number of years that people in a given country or population can expect to live. Conceptually, life expectancy and longevity are identical; the difference between them lies in measurement issues. Life expectancy is calculated in a very precise manner, using what social scientists call "life table analysis." Longevity is not associated with any particular statistical technique. Both life expectancy and longevity are distinct from life span, which refers to the number of years that humans could live under ideal conditions. While life expectancy is based on existing data, life span is speculative. Partly because of its speculative nature, there is considerable debate about the possible length of the human life span. Some social scientists argue that Western populations are approaching a biologically fixed maximum, or finite life span, probably in the range of 85 to 100 years. Others believe that the human life span can be extended by many more years, due to advances in molecular medicine or dietary improvements, for example. An intermediate position is taken by other researchers, who suggest that there is no rigid limit to the human life span and as-yet-unforeseen biomedical technological breakthroughs could gradually increase life span.

A considerable amount of research, based on the foundational assumption of a finite human life span, has focussed on the concept of dependency-free life expectancy (also called dependence-free life expectancy, healthy life expectancy, active life expectancy, disability-free life expectancy, and functional life expectancy). These varying terms refer to the number of years that people in a given population can expect to live in reasonably good health, with no or only minor disabling health conditions. Most of the research on dependency-free life expectancy tests, in varying ways, the validity of the compression of morbidity hypothesis, originally formulated by the researcher James F. Fries in 1983. This hypothesis states that, at least among Western populations, proportionately more people are able to postpone the age of onset of chronic disability; hence, the period of time between onset of becoming seriously ill or disabled and dying is shortening or compressing. Research findings on morbidity compression are variously supportive, negative, and mixed.

The Measurement of Life Expectancy

Life expectancy is a summary measure of mortality in a population. Statistics on life expectancy are derived from a mathematical model known as a life table. Life tables create a hypothetical cohort (or group) of 100,000 persons (usually of males and females separately) and subject it to the age-sex-specific mortality rates (the number of deaths per 1,000 or 10,000 or 100,000 persons of a given age and sex) observed in a given population. In doing this, researchers can trace how the 100,000 hypothetical persons (called a synthetic cohort) would shrink in numbers due to deaths as they age. The average age at which these persons are likely to have died is the life expectancy at birth. Life tables also provide data on life expectancy at other ages; the most commonly used statistic other than life expectancy at birth is life expectancy at age sixty-five, that is, the number of remaining years of life that persons aged sixty-five can expect to live.

Life expectancy statistics are very useful as summary measures of mortality, and they have an intuitive appeal that other measures of mortality, such as rates, lack. However, it is important to interpret data on life expectancy correctly. If it reported that life expectancy at birth in a given population is 75 years in 2000, this does not mean that all members of the population can expect to live to the age of 75. Rather, it means that babies born in that population in 2000 would have a life expectancy at birth of 75 years, if they live their lives subject to the age-specific mortality rates of the entire population in 2000. This is not likely; as they age, age-specific mortality rates will almost certainly change in some ways. Also, older people in that population will have lived their life up to the year 2000 under a different set of age-specific mortality rates. Thus, it is important to be aware of the hypothetical nature of life expectancy statistics.

Life tables require accurate data on deaths (by age and sex) and on the population (by age and sex); many countries lack that basic data and their life expectancy statistics are estimates only. However, age-specific mortality tends to be very predictable; thus, if the overall level of mortality in a population is known, it is possible to construct quite reasonable estimates of life expectancy using what are called model life tables.

Life Expectancy at Birth, Circa 2001

Life expectancy at birth for the world's population at the turn of the twenty-first century was 67 years, with females having a four-year advantage (69 years) over males (65 years); see Table 1. As expected, developed countries experience substantially higher life expectancy than less developed countries—75 years and 64 years, respectively.

Also, the gender difference in life expectancy that favors females is larger in the developed countries (seven years) than in the less developed parts of the world (three years). Regionally, North America (the United States and Canada) has the highest life expectancy overall, and for males and females separately. It might be expected that Europe would have this distinction and, indeed, there are a number of European countries with life expectancies higher than in North America; for example, the Scandinavian countries and the nations of Western Europe. However, the European average is pulled down by Russia; in 2001, this large country of 144 million people has a male life expectancy at birth of only 59 years and a female life expectancy at birth of 72 years. Male life expectancy in Russia declined over the last decades of the twentieth century, and shows no indication of improvement. A considerable amount of research has focused on the trend of increasing mortality (and concomitant decreasing life expectancy) among Russian men, pointing to a number of contributing factors: increased poverty since the fall of communism, which leads to malnutrition, especially among older people, and increases susceptibility to infectious diseases; unhealthy lifestyle behaviors, including heavy drinking and smoking, sedentary living, and high-fat diets; psychological stress, combined with heavy alcohol consumption, leading to suicide; and a deteriorating health care system.

With the exception of Russia (and Eastern Europe more generally), life expectancy at birth does not vary much within European and North American populations. However, the less developed countries have considerably more range in mortality, as measured by life expectancy at birth. This can be seen in Table 1, which shows a range in life expectancy at birth among females from 55 in Africa to 74 in Latin America. It is clear that Africa lags behind the rest of the world in achieving improvements in life expectancy. However, even within Africa, large differences in life expectancy exist. Life expectancy at birth (both sexes combined) statistics range from the low seventies (in Mauritius (71), Tunisia (72) and Libya (75)) to the low forties (in Swaziland and Zimbabwe (both 40), Niger and Botswana (both 41)) with one country—Rwanda—having an estimated life expectancy at birth of only 39 years.

Life Expectancy at Birth in African Countries: The Role of HIV/AIDS

The HIV/AIDS (human immunodeficiency virus/ acquired immunodeficiency syndrome) epidemic has, thus far, hit hardest in parts of Africa, especially sub-Saharan Africa, which contains approximately 70 percent of the world's population with HIV/AIDS. Many of the African countries with the lowest life expectancies have the highest rates of HIV/AIDS infection. However, this is not always the case; for example, Niger and Rwanda, mentioned above as countries with very low life expectancies, do not have high rates of HIV/AIDS in their populations. Thus, AIDS cannot solely account for low life expectancy in Africa; social and political upheaval, poverty, and the high risk of death due to other infectious (and parasitic) diseases cannot be discounted in the African case. Nevertheless, HIV/AIDS does have a devastating impact on life expectancy in many places in Africa. The United Nations projects that by 2050 the effect of the AIDS epidemic will be to keep life expectancy at birth low in many sub-Saharan African countries, perhaps even lower than that experienced in the latter part of the twentieth century. Figure 1 shows two projected life expectancy at birth statistics for seven sub-Saharan African countries, one based on the assumption that HIV/AIDS continues to claim lives prematurely, and the other based on the optimistic assumption that HIV/AIDS was to disappear immediately. The effect of HIV/AIDS is to keep life expectancy in 2050 at levels well under 50; in the absence of the pandemic, life expectancy at birth would improve to the 65 to 70 year range. The projections based on the continuation of HIV/AIDS mark a sad departure for the demographers who make them. Until the 1990s, projections were based on a taken-for-granted assumption that life expectancy would gradually improve. And, for the most part, subsequent mortality trends backed up that assumption.

Trends in Life Expectancy at Birth in Developed Countries

In the developed countries, the fragmentary data that are available suggest that life expectancy at birth was around 35 to 40 years in the mid-1700s, that it rose to about 45 to 50 by the mid-1800s, and that rapid improvements began at the end of the nineteenth century, so that by the middle of the twentieth century it was approximately 66 to 67 years. Since 1950 gains in life expectancy have been smaller, approximately eight more years have been added (see Table 2).

The major factors accounting for increasing life expectancy, especially in the period of rapid improvement, were better nutrition and hygiene practices (both private and public), as well as enhanced knowledge of public health measures. These advances were particularly important in lowering infant mortality; when mortality is not controlled, the risk of death is high among infants and young children (and their mothers), and the major cause of death is infectious diseases (which are better fought off by well-fed infants and children). Being that a large proportion of deaths occurs to infants and young children, their improved longevity plays a key role in increasing life expectancy at birth. The period from the late 1800s to 1950 in the West, then, saw significant improvement in the mortality of infants and children (and their mothers); it was reductions in their mortality that led to the largest increases in life expectancy ever experienced in developed countries. It is noteworthy that medical advances, save for smallpox vaccination, played a relatively small role in reducing infant and childhood mortality and increasing life expectancy.

Since the middle of the twentieth century, gains in life expectancy have been due more to medical factors that have reduced mortality among older persons. These reductions are harder to achieve than decreases in infant mortality; hence, improvements in life expectancy at birth have slowed down. However, reductions in deaths due to cardiovascular disease, cancer (at least for some kinds), and cerebrovascular disease (strokes)—the three major takers-of-life in developed countries— as well as in other types of chronic and degenerative disease have gradually taken place, and life expectancy continues to improve. Nevertheless, looking at the twentieth century as a whole, reductions in mortality among younger persons played the major role in increasing life expectancy at birth; for example, 58 percent of the gain in American life expectancy over the century was due to mortality reductions among persons aged under 20 and a further 17 percent can be accounted for by reductions among the age group 20 to 39.

Trends in Life Expectancy in Less Developed Countries

Very little improvement in life expectancy at birth had occurred in the third world by the middle of the twentieth century. Unlike the developed countries, which had a life expectancy at birth of 67

years at that time, the third world's life expectancy approximated 41 years—a difference of 26 years. However, after the end of World War II, life expectancy in the developing countries began to increase very rapidly. For example, between 1950 and 1970, life expectancy at birth improved by 14 years (see Table 2). Mortality decline was faster than in the West during its period of most rapid decline, and it was much faster than in the West over the second half of the twentieth century. By the end of the century, the 26-year difference had been reduced to 10 years (although Africa lags behind the rest of the developing world).

The rapid improvement in life expectancy at birth in the third world occurred for different reasons than in the West. In the West, mortality declined paralleled socioeconomic development. In contrast, in the developing countries, mortality reductions were, in large part, due to the borrowing of Western death-control technology and public health measures. This in part was the result of the post-cold-war that saw the United States and other Western countries assist nonaligned countries with public health and mortality control in order to win their political allegiance. Whatever the political motives, the result was very successful. As in the West, life expectancy at birth was initially improved by controlling the infectious diseases to which infants and children are particularly susceptible and was accomplished by improvements in diet, sanitation, and public health. In addition, the third world was able to benefit from Western technology, such as pesticides, which played a major role in killing the mosquitoes that cause malaria, a leading cause of death in many countries. This exogenously caused reduction in mortality led to very rapid rates of population growth in most third world countries, creating what became known as the "population bomb." It also left these poor countries without a basic health (and public health) infrastructure, making them vulnerable to the effects of cutbacks in aid from foreign (Western) governments and foundations. It is in such a context that many third world countries (especially in sub-Saharan Africa but also in Southeast Asia and the Caribbean) are attempting to deal with the HIV/AIDS crisis, as well as a number of infectious diseases that were believed to have been conquered but have resurfaced through mutations.

It is difficult to predict if life expectancy differences at birth between the more and less developed countries will continue to converge. On the one hand, further increases in life expectancy in the West will be slow, resulting from improvements in the treatment and management of chronic diseases among older people. Theoretically, it would be expected that the third world could, thus, continue to catch up with West. However, new infectious diseases such as HIVS/AIDS and the re-emergence of "old" infectious diseases, sometimes in more virulent or antibiotic resistant forms, are attacking many third world countries that lack the resources to cope.

Differentials in Life Expectancy at Birth

Within populations, differences in life expectancy exist; that is, with regard to gender. Females tend to outlive males in all populations, and have lower mortality rates at all ages, starting from infancy. However, the degree to which females outlive males varies; as seen in Table 1, the difference is around three years in the less developed countries and approximately seven years in developed countries.

Another difference in life expectancy lies in social class, as assessed through occupation, income, or education. This research tends to deal with life expectancy among adults, rather than at birth. The earliest work on occupational differences was done in England using 1951 data; in 1969 the researcher Bernard Benjamin, grouping occupations into five classes, found that mortality was 18 percent higher than average in the lowest class, and 2 percent lower than average in the highest class. In the United States in 1973, Evelyn Kitagawa and Philip Hauser, using 1960 data, found that both higher education and higher income were independently associated with longer life expectancy, that is, having both high income and high education was more advantageous than just having one or the other. This was later replicated by researchers in 1993, with the additional finding that the socioeconomic difference was widening over time.

Data on social class differences in life expectancy are difficult to obtain, even in highly developed countries. A 1999 study by Tapani Valkonen contains exceptionally good data on occupational differences in life expectancy in Finland. Figure 2 shows life expectancy at age 35 for four classes of workers, by gender, for the period of 1971 to 1996. While this figure indicates that life expectancy differences by occupation show a female advantage for all occupations and that male longevity differentials are much bigger than female ones, the most important information conveyed for the purposes here is that the occupational gap in life expectancy increased over the period. This finding concurs with that for the United States.

It is not clear why socioeconomic differences in adult life expectancy are growing in Western populations. The major cause of death responsible for the widening differential is cardiovascular disease; persons of higher social classes have experienced much larger declines in death due to cardiovascular disease than persons of lower classes. It is possible that the widening is only temporary, the result of earlier declines in cardiovascular mortality among higher socioeconomic groups. Or, it may be that the widening reflects increasing polarization in health status and living conditions within Western populations. It does not appear that differences in access to health care are responsible, seeing as the trend appears in countries that both have and do not have national medical/health insurance.

Another difference in life expectancy relates to race/ethnicity. For example, in the United States, the expectation of life at birth for whites is six years higher than for African Americans. However, the difference in life expectancy at age sixty-five is less than two years. The narrowing gap with age suggests that mortality associated with younger age groups is an important factor; this inference is reinforced by high rates of homicide among African Americans, especially young males. Ethnic differences in mortality are not unique to the United States. Among countries with reliable data, it is known that the Parsis in India and the Jews in Israel have lower mortality than other ethnic groups; they share, along with whites in the United States, a place of privilege in the socioeconomic order.

See also: Aids; Causes of Death; Public Health

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ELLEN M. GEE

LIFE EXPECTANCY

Life expectancy (or the expectation of life) is the average length of life remaining to be lived by a population at a given age. It is computed in the process of building a life table and can be computed for any age in the life table. Life expectancy at birth is the most commonly presented value because this measure provides a succinct indicator of mortality that reflects mortality conditions across the age range and is unaffected by the age structure of the actual population and thus can be compared across populations. The symbol used to represent life expectancy is e̊x where x represents an exact age.

LIFE EXPECTANCY IN THE UNITED STATES

In 1996, life expectancy at birth, e̊0, in the United States was 76.1 years; at age 65, e̊65 was 17.5 years; and at age 85, e̊85 was 6.1 years (Anderson 1998). These figures can be interpreted to mean that if a baby born in 1996 were exposed to the mortality conditions existing at each age of the life span in 1996, the baby with an average length life would live 76.1 years.

PERIOD AND COHORT VALUES OF LIFE EXPECTANCY

The 1996 U.S. life table is a period life table, based on cross-sectional data collected over a year; thus, this life table indicates the mortality experience of a hypothetical cohort. No actual cohort ever experiences the mortality in a period or cross-sectional life table; rather, the table indicates mortality conditions if the mortality levels of each age group at the period of time used as a reference were experienced by the hypothetical cohort. Because mortality has been falling over time, period life tables for a cohort's year of birth have indicated an average expected length of life that is lower than that actually achieved by the cohort. For instance, in 1900 the cross-sectional life table for the United States showed life expectations of 46 for males and 49 for females. On the basis of their actual experience up through the age of 80, the 1900 birth cohort had an average length of life of 52 years for males and 58 years for females (Faber and Wade 1983).

Generation or cohort life tables, like the one mentioned above, based on the experience of an actual cohort are sometimes constructed. These indicate the average length of life actually lived after specific ages for a real cohort. The major difficulty faced in building cohort life tables is obtaining population and death data for a cohort from birth until the last survivors have died—over a 100-year period.

A mistaken notion held by many people is that life expectancy at birth is a good indicator of the age at which an older individual will die. This notion has undoubtedly led to some poor planning for old age because a person who has already reached older adulthood on average will die at an age that exceeds life expectancy at birth by a significant amount. As mentioned above, expectation of life in 1996 was 17.5 years for 65-year-olds, 11.1 for 75-year-olds, and 6.1 for 85-year-olds. With this number of years remaining to be lived on average, 65-year-olds should expect to live to 83 on average. Those who live to 75 should expect to live to 86, and those who live to 85 can expect to live to 91 on average. While expectation of life decreases as age increases, the expected age at death increases for those who survive.

CHANGES IN LIFE EXPECTANCY OVER TIME

As noted above, life expectancy has been increasing over time. This has probably been going on since some time in the last half of the nineteenth century, although reliable data for large sections of the country are not available to track the increase before 1900. In 1900, life expectancy at birth for both sexes was 47.3 years (U.S. Bureau of the Census 1975). This indicates an increase in life expectancy between 1900 and 1996 of 28.8 years. Most of this increase in life expectancy since 1900 is due to declines in mortality among infants and children. These mortality declines were primarily due to the diminishing force of infectious and parasitic diseases which were the most important causes of death among children.

Because life expectancy was low in the past, people often hold the mistaken notion that very few people ever reached old age under high mortality conditions. Yin and Shine (1985) have demonstrated that this mistaken notion was so prevalent that it was commonly incorporated into gerontology textbooks. The fact is that even under conditions of low life expectancy, once childhood is survived, the chances of living to old age are quite high. This is indicated by the fact that life expectancy at the older years has not increased over time nearly as much as life expectancy at birth. For instance, while life expectancy at birth for white males has increased almost 26 years since 1900, from 48.2 to 73.9 years, life expectancy for white males at age 40 has increased almost 9 years between 1900 and 1996, from 27.7 years to 36.4 years; at age 70, the increase for males has been just over 3 1/2 years, from 9.0 to 12.6 (Anderson 1998).

It should be noted, however, that in the past three decades the pace of improvement in life expectancy at the oldest ages has increased. In 1970 expectation of life for white males at age 70 was 10.5 years, indicating an improvement of 1.5 years in the 70 years between 1900 and 1970. Between 1970 and 1998, the increase was 2 years—significantly greater than the improvement during the first seven decades of the century. This reflects the new era of mortality decline in which decreases in mortality are due to decreased mortality from chronic conditions and are concentrated among the old.

A number of authors have studied the relationships between changes in age-specific mortality and life expectancy. Vaupel (1986) concludes that a reduction in the force of mortality of 1 percent at all ages would not produce as much gain in life expectancy today as it did in 1900. This is because we have already made so much progress in lowering infant and child mortality, the ages that have the greatest effect on life expectancy. Vaupel also shows that as mortality moves to lower levels, more progress is made in increasing life expectancy from mortality declines at older ages rather than at younger ages. At the level of mortality now experienced in the United States, much of the future increase in life expectancy will come from mortality declines occurring at ages over 65. This is true because of the prior success in reducing mortality at earlier ages to such low levels.

CALCULATION OF LIFE EXPECTANCY WITHIN THE LIFE TABLE

These observations about changes in life expectancy should make clear that life expectancy at birth is heavily weighted by mortality conditions at the youngest ages. A brief explanation of the life table and how life expectancy is calculated demonstrates why this is the case.

The life table is a statistical model that provides a comprehensive description of the mortality level of a population. Life table measures are particularly valuable because they are succinct indicators of mortality that reflect mortality conditions across the age range, are unaffected by the age structure of the actual population, and thus can be compared across populations. Life table measures can also be used to describe the characteristics of the stationary population that would result from an unchanging schedule of age-specific mortality rates in a closed population with a constant number of births.

There are a number of functions that appear in most life tables and for which conventional notation is widely recognized: qx, lx, dx, Lx, Tx, and e̊x. Each of these measures provides information useful in describing some aspect of the mortality conditions and/or characteristics of the stationary population. The definitions and interpretations of the life table functions follow below. In order to clarify the interpretation of the abridged life table functions, the life table for the U.S. population for 1996 is used as an example (Table 1).

nqx is the probability of dying between exact age x and x + n. As shown in Table 1, the probability of dying in the first year of life is 0.00732. This is higher than at subsequent ages until age 60 to 65, when the probability of death is 0.06649.

lx is the number of survivors reaching exact age x out of the original life table population. The size of the original life table population, the radix or lo, is usually assumed to be 100,000; however, this is a convention and other values can be used. Mortality conditions in 1996 were such that out of 100,000 births, 99,268 would reach age 1. This column of the life table can be used to compute how many people who reach a given age will survive to a later age. For instance, among the 80,870 people who reach age 65, 33,629 people or 42 percent will reach age 85 with mortality conditions as shown in Table 1.

ndx is the number of deaths in the life table population between exact age x and x + n.

In the sample life table, 732 of the 100,000 births would die between ages 0 and 1 and 7,814 would die between ages 65 and 70.

nLx is the total number of years lived by the life table population between exact age x and x + n. Between birth and age 1, the life table population represented in Table 1 would live 99,370 years. This column also can be interpreted as the number of people in the stationary population at each year of age.

Tx is the total number of years lived after exact age x by the life table population surviving to age x, or the number of people in the stationary population age x and older. The 100,000 entrants to the life table in Table 1 would live a total of 7,611,825 years, and the 80,870 who reach age 65 would live a total of 1,416,873 more years.

e̊x is the expectation of life at exact age x or the average length of life remaining to be lived for the life table population which survives to exact age x. e̊x is computed from the Tx and lx columns of the life table: e̊x = Tx/lx. As indicated earlier, at birth, the life table population in Table 1 has a life expectancy of 76.1 years.

DIFFERENTIALS IN LIFE EXPECTANCY

There are large differentials in life expectancy among demographic and socioeconomic groups in the United States. Males have lower life expectancies than females throughout the age range. Males' lower chances for a longer life are thought to result from a combination of biological differences and lifestyle factors. In 1996, e̊0 was 73.1 for males and 79.1 for females (Anderson 1998). By age 50, the difference is narrowed to 4.3 years, with a life expectancy of 27.2 for men and 31.5 for women. At age 85, men can expect to live another 5.4 years, while women can expect to live 6.4 years.

There is also a significant difference in life expectancy between whites and African Americans in the United States. This is assumed to result primarily from the difference in socioeconomic status and accompanying life circumstances that exist between African Americans and whites in the United States. In 1996, life expectancy at birth was 76.8 for whites and only 70.2 for blacks. At age 65, white life expectancy was 17.6 years; while for blacks of that age, it was 15.8 years. At the oldest ages, a crossover in mortality rates by race has been observed in the past. After the age of crossover, African-American mortality rates are lower than white mortality rates. In 1987 this was true at ages above 83. In the past, this crossover has shown up repeatedly in comparisons of African-American and white mortality in the United States and has been attributed to the "survival of the fittest" among the black population (Manton and Stallard 1981). Recently, however, doubt has been raised as to whether the crossover is real or is a statistical artifact resulting from age misstatement by older African Americans in both the census and vital records of deaths (Coale and Kisker 1986; Elo and Preston 1994; Preston et al. 1996). Interestingly, Hispanics appear to have life expectancy values that are higher than non-Hispanic whites (Anderson et al. 1997).

INTERNATIONAL DIFFERENCES

In general, the life expectancy of a country is related to its level of socioeconomic development. Most countries that are classified as "more developed" have higher levels of life expectancy at birth than most of the countries classified as "developing"; however, within each of these groups of countries there is quite a bit of variability in life expectancy. While the United States has a high level of life expectancy compared to that of the developing countries of the world, the United States ranks quite low in life expectancy among developed countries and relative to its income level. A recent United Nations listing of the developed countries by level of life expectancy at birth ranks U.S. males as nineteenth and U.S. females as fourteenth (United Nations 1997). The countries with higher life expectancy for women include Japan and the Scandinavian countries. For men, most European countries including some in southern Europe have higher life expectancies at birth than the United States. The low ranking of the United States is attributed, in part, to the inequities in mortality among subgroups of the population, especially the high level among African Americans, and also to the high level of violent deaths. In recent years Japan has become the world leader in life expectancy at birth with values of e̊0 of 76.4 for men and 82.9 for women in 1995 (Ministry of Health and Welfare, Japan 1999). These values exceed 1996 U.S. values by 3.3 years for men and 3.8 years for women. The success of the Japanese in raising their levels of life expectancy has been due to large declines in mortality from cerebrovascular disease and maintenance of low levels of heart disease relative to other developed countries (Yanagishita and Guralnik 1988).

RELATED CONCEPTS

There are some other concepts that are related to life expectancy and are sometimes confused with life expectancy. One is "life span." The life span of a species is the age to which the longest-lived members survive. The life span of humans is thought to be approximately 115 years; however, Madame Jeanne Calment, whose age was well documented, died in 1997 at the age of 122. Current thinking is that while life expectancy has increased dramatically over the last century, the life span of humans has not changed over time; however, this does not mean it will never change. If discoveries are made in the future that enable us to retard the aging process, it may be possible to lengthen the human life span in the future.

"Life endurancy" is a related concept that, like life expectancy, is computed from the life table. This is the age at which a specified proportion of the life table entry cohort is still alive. For instance, in 1990 the age at which 0.1, or 10 percent, of the life table population remained alive was 90 years for men and 96 years for women. Life endurancy has been increasing over time and is expected to continue to change with changes in survival rates. In 1900 the 10 percent survival age was 81 and 82 for men and women, respectively (Faber and Wade 1983).

Finally, "healthy or active life expectancy" is a subset of total life expectancy. Total life expectancy at any age is the sum of two parts: healthy life expectancy and unhealthy life expectancy. While the concept of health life expectancy was introduced in the 1960s (Sanders 1964) and developed in the 1970s (Sullivan 1971a, 1971b), it has only become widely adapted by governments and international organizations in the 1990s.

Interest in healthy life expectancy has grown recently as people have recognized that gains in total life expectancy today may not mean the same thing as in the past. Past gains in life expectancy came about largely because fewer people died of infectious diseases, either because they did not get the diseases or they received treatment that prevented death. People thus saved from death were generally free of the disease. Under these circumstances gains in life expectancy were accompanied by better health in the population surviving. Now, with gains in life expectancy being made because of declining death rates from chronic diseases especially among the old, it is not clear that the surviving population is a healthier population. This is because generally there is no cure for the chronic diseases, and for many their onset has not yet been prevented. People may be saved from death but they live with disease. This is the basis for questioning whether the additions to life expectancy are healthy or unhealthy years.

Crimmins and colleagues (1997) estimated that healthy life expectancy or disability-free life expectancy at birth in the United States in 1990 was 58.8 years for men and 63.9 years for women. The difference between blacks and whites in disability-free life expectancy at birth was even greater than the difference in total life expectancy. In 1990 black disability-free life expectancy for males at age 20 was 37.9 years while that for whites was 45.8 years (Hayward and Heron 1999). Studies that addressed the issue of changes in healthy life expectancy for the 1970 and 1980 period generally found that when healthy life was defined as nondisabled life, active life expectancy had not increased (Wilkins and Adams 1983; Crimmins et al. 1989). More recent studies have found increases in active life expectancy (Crimmins et al. 1997; Robine and Mormiche 1994).

Healthy life expectancy can be defined in many ways. Examples include average length of life free from a disability that causes a person to alter his or her normal activity; average length of life free of dependency on others for the performance of basic activities necessary to living, such as eating, bathing, and getting in and out of bed; and average length of life without disease (Bebbington 1988; Colvez et al. 1986; Crimmins et al. 1997; Crimmins et al. 1994; Rogers et al. 1989). Some measures of healthy life combine multiple indicators of health using weights; for instance, the U.S. National Center for Health Statistics measure combines self-assessed health and disability in its indicator of healthy life (Erickson et al. 1995).

There are multiple methodological approaches to estimating health expectancy. Most can be described under one of two headings: the Sullivan method or the multistate method (Sullivan 1971a; Schoen 1988). Microsimulation techniques have also been employed recently (Laditka and Wolf 1998).

REFERENCES

Anderson, R.N. 1998 United States Abridged Life Tables, 1996. National Vital Statistics Reports: from the Centers for Disease Control and Prevention, National Center for Health Statistics, National Vital Statistics System, 47(13). Hyattsville, Md.: National Center for Health Statistics.

——, K. D. Kochanek, and S. L. Murphy 1997 Report of Final Mortality Statistics, 1995. Monthly Vital Statistics Report, 45(11), suppl. 2. Hyattsville, Md.: National Center for Health Statistics.

Bebbington, A. C. 1988 "The Expectation of Life without Disability in England and Wales." Social Science and Medicine 27:321–326.

Coale, A. J., and E. E. Kisker 1986 "Mortality Crossovers: Reality or Bad Data?" Population Studies 40:389–401.

Colvez, A., J. M. Robine, D. Bucquet, F. Hatton, B. Morel, and S. Lelaidier 1986 "L'espérance de Vie Sans Incapacité en France en 1982." (Expectation of Life without Disability in France in 1982.) Population 41:1025–1042.

Crimmins, E. M., M. D. Hayward, and Y. Saito 1994 "Changing Mortality and Morbidity Rates and the Health Status and Life Expectancy of the Older Population." Demography 31:159–175.

Crimmins, E. M., Y. Saito, and D. Ingegneri 1989 "Changes in Life Expectancy and Disability-Free Life Expectancy in the United States." Population and Development Review 15:235–267.

——1997 "Trends in Disability-Free Life Expectancy in the United States, 1970–1990." Population and Development Review 23:555–572.

Elo, I. T., and S. H. Preston 1994 "Estimating African-American Mortality from Inaccurate Data." Demography 31:427–458.

Erickson, P., R. Wilson, and I. Shannon 1995 "Years of Healthy Life." Healthy People 2000: Statistical Notes 7:1–15.

Faber, J., and A. Wade 1983 Life Tables for the United States: 1900–2050. Actuarial Study No. 89. Washington: U.S. Department of Health and Human Services, Social Security Administration, Office of the Actuary.

Hayward, M. D., and M. Heron 1999 "Racial Inequality in Active Life among Adult Americans." Demography 36:77–91.

Laditka, S. B., and D. A. Wolf 1998 "New Methods for Modeling and Calculation Active Life Expectancy." Journal of Aging and Health 10:214–241.

Manton, K. G., and E. Stallard 1981 "Methods for Evaluating the Heterogeneity of Aging Processes in Human Populations Using Vital Statistics Data: Explaining the Black/White Mortality Crossover by a Model of Mortality Selection." Human Biology 53:47–67.

Ministry of Health and Welfare, Japan 1999 "Abridged Life Tables for Japan, 1995." http://www.mhw.go.jp/english/database/lifetbl/part6.html.

Preston, S. H., I. T. Elo, I. Rosenwaike, and M. Hill 1996 "African-American Mortality at Older Ages: Results of a Matching Study." Demography 33:193–209.

Robine, J. M., and P. Mormiche 1994 "Estimation de la Valeur de l'Espérance de Vie Sans Incapacité en France en 1991." (Estimation of Expectation of Life without Disability in France in 1991.) Les Français et Leur Santé 1:17–36.

Rogers, R., A. Rogers, and A. Belanger 1989 "Active Life among the Elderly in the United States: Multistate Life Table Estimates and Population Projections." Milbank Quarterly 67:370–411.

Sanders, B. 1964 "Measuring Community Health Level." American Journal of Public Health 54:1063–1070.

Schoen, R. 1988 Modeling Multigroup Population New York: Plenum.

Sullivan, D. F. 1971a "A Single Index of Mortality and Morbidity." HSMHA Health Reports 86:347–354.

——1971b Disability Components for an Index of Health. Vital and Health Statistics 2 (42). Rockville, Md.: National Center for Health Statistics.

United Nations 1997 "Life Expectancy and Infant Mortality Rate, 1995–2000: Developed Regions." http://www.un.org/Depts/unsd/gender/3-1dev.htm.

U.S. Bureau of the Census 1975 Historical Statistics of the U.S., Colonial Times to 1970. Bicentennial Edition. Part 2. Washington, D.C.: U.S. Government Printing Office.

Vaupel, J. 1986 "How Change in Age-Specific Mortality Affects Life Expectancy." Population Studies 40:147–157.

Wilkins, R., and O. B. Adams 1983 "Health Expectancy in Canada, Late 1970s: Demographic, Regional, and Social Dimensions." American Journal of Public Health 73:1073–1080.

Yanagishita, M., and J. Guralnik 1988 "Changing Mortality Patterns that Led Life Expectancy in Japan to Surpass Sweden's: 1972–1982." Demography 25:611–624.

Yin, P., and M. Shine 1985 "Misinterpretations of Increases in Life Expectancy in Gerontology Textbooks." Gerontologist 25:78–82.

EILEEN M. CRIMMINS

Life Expectancy

RACIAL INEQUALITIES IN LIFE EXPECTANCY

EXPLANATIONS FOR RACIAL INEQUALITIES IN LIFE EXPECTANCY

RESEARCH NEEDS

BIBLIOGRAPHY

Race is widely understood as a sociocultural phenomenon, not a biological one. This view is based on evidence that conventional racial categories fail to capture global patterns of human genetic variation. Yet severing the link between race and human biological variation may create an unintended blind spot: Race is biological in the sense that racial differences in life experiences are linked to biological outcomes, including death and disease. Historically, these health inequalities were interpreted as evidence of innate biological differences between racially defined groups. But researchers increasingly seek to understand them as the biological consequences of social inequalities among racialized groups.

Racial inequalities in health are often summarized by reference to life expectancy, a standard indicator of population health. This entry first defines life expectancy and then presents evidence for current and historical racial inequalities in life expectancy in the United States. It then reviews explanations for the persistent gap in life expectancy and identifies key needs for research to improve our understanding of racial inequalities in health.

RACIAL INEQUALITIES IN LIFE EXPECTANCY

Life expectancy is calculated on the basis of age-specific death rates for a population at a given point in time. It estimates the average number of years people who have reached a particular age would continue to live, if current death rates at each age remained constant over time. Because death rates do not remain constant, life expectancy does not measure the longevity of actual birth cohorts. Rather, it summarizes the overall mortality profile of a population at a particular point in time.

Life expectancy can be calculated for any age, but the most common summary of a population’s health status is life expectancy at birth. However, this measure is heavily influenced by rates of infant and child mortality, especially if these rates are high. When researchers wish to exclude the impact of early mortality on population health, they typically calculate life expectancy at ages five or fifteen.

Black and White Americans. In the United States, research on racial inequalities in life expectancy focuses largely on inequalities between black and white Americans.

Figure 1 shows how these inequalities persisted over the twentieth century. At the beginning of the century, the black-white gap in life expectancy at birth was 14.6 years. This gap reached a peak in 1903 (17.8 years) and declined through World War II. (It narrowed considerably but temporarily during the “colorblind” 1918 flu pandemic.) By 1955, the black-white gap in life expectancy had fallen to less than seven years.

However, during the second half of the century, racial inequalities in life expectancy scarcely changed, despite substantial gains in life expectancy for the population as a whole (Figure 1). Indeed, in 1995 the black-white gap in life expectancy was the same as it was in 1956 (6.9 years). Only in the last few years has this gap narrowed again, reaching a historic low of 5.3 years in 2003.

The apparent stability of this inequality masks the diverging fortunes of black men and women, as Figure 1 shows. From 1950 to 2003, the gap in life expectancy between black and white women fell from 9.3 to 4.4 years, such that black women’s life expectancy at birth now exceeds that of white men. During the same period, the gap between black and white men climbed to a peak of 8.5 in 1982, before falling again to 6.3 years in 2003. This gap between black and white men is still greater than it was in 1955.

The historical depth of inequalities between black and white Americans explains the usual focus on black-white comparisons of health and life expectancy. But these comparisons are limited in at least three ways. First, crude black-white comparisons neglect the diversity of health and mortality profiles within racial categories. Second, they ignore the changing racial demography of the United States in the wake of increasing immigration from Asia and Latin America since the 1960s. Third, they imply that race per se is the most important determinant of health disparities, rather than identifying the specific causal influences on racial inequalities of health.

“Eight Americas.” One group of researchers addressed these concerns by dividing the U.S. population into eight distinct groups based on race and the socioeconomic attributes of counties where people lived (Murray et al. 2006). The resulting “Eight Americas,” shown in Table 1, capture the striking range of inequalities in life expectancy in the United States.

Relative to global inequalities in life expectancy, racial disparities within the United States are massive. The gap between Americans with the longest and shortest life expectancies—Asian-American women and black men in high-risk urban settings—is an astonishing 21 years, more than the difference between Japan and Bangladesh, for example. Within sexes, the gap between the longest and shortest life expectancies is 13.1 years for women and 16.1 years for men. These gaps are 2.6 to 3 times greater than the inequalities between black and white women in the United States as a whole. They also rival the nearly 14-year gap in life expectancy between high-income OECD (Organisation for Economic CoOperation and Development) countries and low-income developing countries (United Nations Development Programme 2005). Indeed, the life expectancy of high-risk urban black men in the United States is more typical of life expectancy in developing countries than it is of high-income countries like the United States (Figure 2).

Table 1 also highlights diversity within conventional racial categories. Murray and colleagues identify three black and three white Americas. Across the white Americas, the gap in life expectancy is 4.0 years for women and 4.4 years for men. Across the black Americas, the gaps are smaller but still substantial—1.3 years for women and 2.9 years for men. These gaps cannot be attributed simply to socioeconomic inequalities. Despite low per capita income, rural whites in the northern plains and Dakotas have a significant mortality advantage over high-income whites in America. Likewise, despite greater poverty, rural black men in the South have a slight edge in longevity over black men in high-risk urban environments.

Murray and colleagues emphasize that inequalities in life expectancy across the eight Americas are not the result of differential mortality among children or the elderly. Although racial inequalities in infant mortality persist, the largest mortality differences are among young (ages 15–44) and middle-aged (ages 45–64) adults. These differences are the result primarily of noncommunicable causes such as cardiovascular disease, diabetes mellitus, cancer, and liver cirrhosis. Injuries and HIV/AIDS also contribute significantly to excessive mortality among young adults. In separate analyses, Wong and colleagues (2002) estimate that eliminating hypertension, or chronic high blood pressure, would have the largest impact on reducing racial differences in life expectancy, followed by HIV,

homicide, diabetes, colon cancer, pneumonia, and ischemic heart disease.

EXPLANATIONS FOR RACIAL INEQUALITIES IN LIFE EXPECTANCY

There remains debate about why these inequalities exist. Many critics note that the debate often ends prematurely with the assumption that race is biology and that racial differences in health are largely determined by genetic differences. However, in the last twenty years, clinicians and health researchers have become increasingly aware of the problems with race as a biological construct, and there is growing emphasis on the social and cultural factors that shape racial inequalities in health.

In a recent review, Dressler, Oths, and Gravlee (2005) identify five models for explaining racial inequalities in health:

1. A racial-genetic model
2. A socioeconomic model
3. A health-behavior model
4. A psychosocial stress model
5. A structural-constructivist model.

Although the review focuses largely on infant mortality and high blood pressure, the five models apply to explanations for racial health inequalities in general.

The racial-genetic model holds that racial inequalities in health are primarily genetic in origin. This view has a long history in American medicine (Krieger 1987). Indeed, many key figures in the history of scientific racism were physicians and medical scientists who asserted the natural biological inferiority of blacks as the basis of their greater susceptibility to disease and premature death. For example, during the first years of Reconstruction, as many as one-quarter to one-third of former slaves may have died in parts of the southern United States. Many white physicians interpreted this trend as evidence of African Americans” innate biological inferiority, not of fundamental social inequality.

The basic assumptions of this period remain surprisingly common today. Whereas social scientists generally take it for granted that race does not correspond to meaningful genetic differences, many physicians and biomedical researchers still assume that there are innate racial differences in the susceptibility to disease. Some prominent researchers explicitly defend race as a useful framework for identifying the genetic basis of common diseases (Risch et al. 2002). Yet there remains little reason to think that genes are to blame for racial inequalities in life expectancy (Goodman 2000).

Most research on the nongenetic basis of racial inequalities in health has focused on the role of socioeconomic status (SES), usually defined as some combination of education, occupation, and income. The rationale is that race and SES are confounded, such that controlling for differences in SES should either eliminate racial disparities in health or reveal the true causal effect of race. As a rule, accounting for SES reduces but does not eliminate racial inequalities in health. This pattern also holds for life expectancy, as the Eight Americas study suggests (Table 1).

Some researchers have interpreted the residual relationship between race and health, after controlling for SES, as support for the racial-genetic model. But this interpretation is untenable because race cannot be reduced to class; racial inequality affects health through mechanisms other than socioeconomic deprivation. Thus, controlling for SES, even when it is measured well, does not eliminate differences between racially defined groups in noneconomic factors that influence population health (Kaufman, Cooper, and McGee 1997).

The health behavior model is in part a response to the limitations of the socioeconomic model. One possible reason that SES does not account for racial inequalities in health is that it does not capture the unequal distribution of health-related behaviors across racially defined groups. The health behaviors most often discussed include dietary intake and physical activity (resulting in excessive weight and obesity), alcohol consumption, and smoking. These factors clearly impact health and longevity. However, there is little evidence that they account for the relationship between race and health (Dressler, Oths, and Gravlee 2005).

The incomplete success of socioeconomic and health-behavior models has stimulated research on the contribution of psychosocial stress to racial inequalities in health. Research in this tradition begins from the premise that institutional and interpersonal racism create stressful life circumstances that adversely impact the health of racially oppressed people. The literature in this area is enormous and growing. Dressler and colleagues (2005) distinguish three streams of research on psychosocial stress, including (1) studies that measure general markers of stress exposure such as depression and anxiety, (2) studies that assess the perceived experience of discrimination, and (3) studies that adapt general models of the stress process to the unique stressors and coping resources in African-American communities.

Each approach has produced novel insights, confirming the importance of psychosocial stress in the origin of racial inequalities in health. Yet much research in this tradition remains vulnerable to the limitations of stress research in general. First, many stressors, including exposure to racism, are difficult to measure apart from individuals” efforts to cope with those stressors. Second, research on psychosocial stress traditionally focuses on individual experience, with too little consideration of how stressors and coping resources are socially distributed and culturally constructed.

The structural-constructivist model addresses these limitations. This approach seeks to explain racial inequalities in health at the intersection of social structure and cultural meaning. For example, Dressler (2005) shows that racial inequalities in mental and physical health are associated with one’s ability to obtain culturally valued resources, which is partly constrained by structural inequalities. Gravlee, Dressler, and Bernard (2005) show that the association between skin color and blood pressure in Puerto Rico is shaped both by the meaning people attribute to skin color and by access to socioeconomic resources. These examples illustrate the promise of research that examines how social structural forces condition exposure to culturally defined stressors and coping resources.

RESEARCH NEEDS

Racial inequalities in life expectancy pose three critical challenges for the social and biomedical sciences. First, given the persistence of racial-genetic determinism, it remains necessary to clarify the fallacy of race as a framework for understanding human biodiversity. Second, there is a need for research on how hidden assumptions about race shape biomedical research and clinical practice and how clinical practice and biomedical research, in turn, perpetuate prior beliefs about race. Third, researchers need to integrate multiple levels of analysis—sociocultural, environmental, behavioral, physiological, molecular—to understand how the sociocultural phenomena of race and racism become embodied in biological outcomes over the life course.

SEE ALSO Demographics and Race; Diseases, Racial; Hypertension and Coronary Heart Disease; Infant Mortality and Birth Weight; Infectious Disease, Susceptibility, and Race; Social Class and Mortality.

BIBLIOGRAPHY

Arias, Elizabeth. 2006. United States Life Tables, 2003. National Vital Statistics Reports Vol. 54, No. 14. Available from http://0-www.cdc.gov.mill1.sjlibrary.org/nchs/data/statab/lewk3_2003.pdf.

Dressler, William W. 2005. “What’s Cultural about Biocultural Research?” Ethos 33 (1): 20–45.

———, Kathryn S. Oths, and Clarence C. Gravlee. 2005. “Race and Ethnicity in Public Health Research: Models to Explain Health Disparities.” Annual Review of Anthropology 34 (1): 231–252.

Goodman, Alan H. 2000. “Why Genes Don’t Count (for Racial Differences in Health).” American Journal of Public Health 90 (11): 1699–1702.

Gravlee, Clarence C., William W. Dressler, and H. Russell Bernard. 2005. “Skin Color, Social Classification, and Blood Pressure in Southeastern Puerto Rico.” American Journal of Public Health 95 (12): 2191–2197.

Kaufman, Jay S., Richard S. Cooper, and Daniel L. McGee. 1997. “Socioeconomic Status and Health in Blacks and Whites: The Problem of Residual Confounding and the Resiliency of Race.” Epidemiology 8 (6): 621–628.

Krieger, Nancy. 1987. “Shades of Difference: Theoretical Underpinnings of the Medical Controversy on Black/White Differences in the United States, 1830–1870.” International Journal of Health Services 17 (2): 259–278.

Murray, Christopher J. L., C. Sandeep, Catherine Michaud Kulkarni, et al. 2006. “Eight Americas: Investigating Mortality Disparities Across Races, Counties, and Race-Counties in the United States.” PLoS Medicine 3 (9): e260.

National Center for Health Statistics. 2005. Health, United States, 2005. Hyattsville, MD: National Center for Health Statistics. Available from http://www.cdc.gov/nchs/hus.htm.

Risch, Neil, Esteban Burchard, Elad Ziv, and Hua Tang. 2002. “Categorization of Humans in Biomedical Research: Genes, Race and Disease.” Genome Biology 3: comment2007. 1–comment2007.12.

United Nations Development Programme. 2005. Human Development Report 2005. New York: United Nations Development Programme.

Wong, M. D., M. F. Shapiro, W. J. Boscardin, and S. L. Ettner. 2002. “Contribution of Major Diseases to Disparities in Mortality.” New England Journal of Medicine 347 (20): 1585-1592.

Clarence C. Gravlee

LIFE EXPECTANCY

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.

PeterUhlenberg

LIFE EXPECTANCY

Life expectancy is a summary measure of the average number of additional years a group of people can expect to live at a given exact age. Life expectancy figures are derived from a life table. Life table methodology has been developed for human populations to determine average lengths of life, of healthy life, of married life, and of working life. Indeed, life tables have recently been used to determine the average career length of professional athletes. And life tables have been used to determine the average length of life of nonhumans, including automobiles and animals.

Life expectancy at birth is derived by applying a set of age-specific mortality rates to a hypothetical group of newborns. For example, with data for the year 2000, we could impose the current age-specific mortality patterns of individuals from birth through the oldest ages onto a group of newborns. These calculations are based on mortality rates prevailing today, not in the future; individuals born today may actually experience lower (or possibly higher) mortality one hundred years hence, when they reach age one hundred. Thus, life expectancies represent a current, and not future, measure of survival. Further, period-specific events influence life expectancies. For instance, mortality due to human immunodeficiency virus (HIV), a cause of death that was not evident before the 1980s, affects current life expectancy estimates.

Life expectancy is most commonly used for cohorts of newborns, but can also be reported for other ages, as Table 1 depicts. The first row reveals that individuals born in the United States in 1998 can expect to live an average of 76.7 years, the highest figure ever achieved by individuals in this country. Indeed, in 1900, the average life expectancy at birth was just 47.3 years (Anderson).

The table shows the remaining life expectancy for selected ages. The remaining life expectancy is an additional 72.4 years at age 5 and 3.5 years at age 95. With increasing age, remaining years of expected life generally decreases because individuals have already lived through previous years; but the total life expectancy (age plus remaining years) increases because individuals have already survived earlier ages. Thus, at age 75, the remaining life expectancy is 11.3 years, while the total life expectancy is 86.3 years.

Life expectancy is often confused with life span, a demographic term that refers to the maximum number of years a person can be expected to live under the most ideal circumstances (Nam). Life span for humans is about 120 years. In contrast, life expectancy at birth for individuals in the most long-lived nations around the world is approximately eighty years.

A number of factors influence life expectancies, including socioeconomic status, health behaviors, chronic conditions, sex, race, and ethnicity. Indeed, life expectancy figures are often calculated separately by sex and by race/ethnicity. Life expectancy estimates contribute to aging research by providing an excellent summary measure of the length of life of current and future populations.

Richard G. Rogers Robert A. Hummer Patrick M. Krueger

See also Life Span Extension; Longevity: Social Aspects; Population Aging.

BIBLIOGRAPHY

Anderson, R. N. "United States Life Tables, 1997." National Vital Statistics Reports 47 (1999): 1–40.

Murphy, S. L. "Deaths: Final Data for 1998." National Vital Statistics Reports 48 (2000): 1–106.

Nam, C. B. Understanding Population Change. Itasca, Ill.: FE Peacock Publishers, 1994.