Sang-Hee Lee. 21st Century Anthropology: A Reference Handbook. Editor: H James Birx. Volume 2. Thousand Oaks, CA: Sage Reference, 2010.
The link between human longevity and world population seems direct and obvious: The world population is increasing, and the proportion of elderly is increasing as well, as more humans are living longer. Will human life span increase infinitely? Why is there an aging process? How does human longevity compare to that of other primates? How did longevity change over human evolutionary history? What follows is a review of research examining these questions and other aspects of human longevity and a discussion of world population growth.
Definitions of Longevity
Longevity, or life span, is the period of time between the birth and death of an organism. This definition is misleadingly straightforward, because the point when life begins and ends is a matter of some arbitrariness. Although most definitions of life would begin with birth, arguments have been made that life begins at various points before birth— for example, fertilization, implantation, beginning of the third trimester in humans, or after birth, as can be seen in the effective age calculations for prematurely born babies. The point of birth that is culturally acknowledged adds further variation in the concept of birth.
Most definitions of death include cessation of breath and heartbeats, but arguments have been made for different kinds of deaths, as not all organs in a body cease to function at the same time—for example, brain death. As in the case of life, the point of death that is culturally acknowledged can vary from biological point of death. However, the range of variation in the beginning and ending points is small compared to the total length of life span.
It is thought that maximum life span is biologically determined and not variable. The maximum life span can be empirically noted by observing the longest survival of an individual member of a species, which provides the minimum threshold of the maximum life span. This is a difficult challenge for studying long-lived organisms such as humans, since researchers do not outlive the subjects and cannot record births and deaths. Researchers have to rely on records and age estimations. Living to the age of 100 is unlikely for humans, but not rare: About 7 in 1,000 people are estimated to reach the centenarian milestone. Beyond 100, surviving each additional year is subject to a 50% probability. The maximum human life span is estimated to be between 115 and 150 years, with the longest-lived human on record having lived 122 years (died in 1997). The majority of centenarians are women, and most of the oldest old are women. Reasons for sex differences in longevity are not clear, although many have attributed it to greater testosterone-driven mortality in males.
As a group, primates show a strong tendency for increased longevity as a result of long gestation, long maturation, and long adulthood. Cross-species comparisons of life spans that are explained by biological variables such as brain size, body size, metabolic rate, and body temperature have yielded statistically significant relationships (Cutler, 1975; Sacher, 1978), which suggest that life span is an evolutionary variable that contributes to the fitness of a species. The maximum life spans of most mammalian species form a straight line when they are plotted against various biological variables. Human life span is not noteworthy, given that there are many other mammals, such as whales and elephants, with life spans as long as or longer than those of humans. While human life span falls within the expected range based on brain size, it is extraordinarily long for body size (Hill, 1993). However, the statistical nature of such studies should be kept in mind. Human life span easily exceeds 90 when looking at the species as a whole, after sampling millions of people; however, a random sample of a village population would more likely yield 60 or 70 years of average life span. In contrast, life span data for nonhumans are based on a very small sample. It is unknown how much of the life span differences are attributable to the extreme discrepancy in sample sizes.
The maximum potential life span of humans is longer than that of other great apes. Among hunter-gatherers, life spans in the 70s and 80s are well-known, while chimpanzees in the wild rarely reach 45 years of age, and orangutans in the wild, 50 years. Even in captivity, maximum life span on record is about 60 years for apes, in contrast to the markedly longer life span of the oldest human on record.
Making a uniformitarian assumption that the relationships between body size, brain size, and maximum life span that are observed in the present are as valid for species in the past, maximum life span can be estimated for various fossil human ancestors (hominids; Weiss, 1981). The maximum life span for hominids that existed before the genus Homo came into being (Australopithecus africanus, A. robustus, and A. boisei) is around 50. The value increases with Homo habilis at 61, Homo erectus at 69 and 78, archaic Homo at 89, and more than 90 years of life span is predicted for Neanderthals as well as modern humans (Weiss, 1981). There is an increase in the estimated maximum life span through the years. This acceleration of the increase in maximum life span plateaus with the modern humans. However, it should be remembered that the estimation of maximum life span of fossil hominids was based on estimated brain size and body size. Therefore, the observed increase pattern in maximum life span is actually the increase pattern in brain size and body size over time.
While maximum life span implies a biological limit to how long an individual lives, average life span is estimated from the mortality data. Although maximum life span for humans is more than 100 years, the average life span is over 70 years. This is a substantial increase from less than 30 years, which was the average life span for humans from the time of ancient Greece until the 18th century. The life expectancy at birth in North America and northwestern Europe is thought to have been 35 to 40 years until the end of the 18th century. Despite the increase in average life span, there is no evidence of increase in the maximum life span. There is no evidence that mortality of centenarians decreased: The increase in the number of centenarians is a result of the decrease in mortality for people under 100 years of age. It seems to be the case that the trend is for more people to reach the maximum life span rather than for the maximum life span to increase. Few studies show that maximum life span has changed much over time (Wilmoth & Robine, 2003).
In contrast, if human longevity is defined as average life expectancy, it has increased over time. Life span is related to, but different from, life expectancy, which is a hypothetical number derived from mortality tables. Life expectancy is the number of years that a cohort is expected to live. Life expectancy at a specific age is the average number of years the cohort (those born into a population at the same time) will live to be.
Estimated life expectancy through human evolution has increased. Since it is impossible to get an accurate measurement of life expectancy, it is estimated by using demographic models. Assuming a stationary population (zero growth), life expectancy at birth is the inverse of the crude birth rate. Based on the life tables collected for anthropological societies, the crude birth rate for hunter-gatherers is around 0.045, which yields life expectancy at birth to be 22 years (Weiss, 1973). In contrast, life expectancy at birth in some developed countries is more than 75. When life expectancies at different points in life (birth, puberty, old age) are compared, it can be seen that life expectancy at birth is the one that changes the most, followed by life expectancy at puberty; life expectancy at old age has not changed much over time.
Humans have a distinctively long average adult life span. While great ape females in the wild who survive to age 15 can be expected to live 15 to 20 more years (Hill et al., 2001; Wich et al., 2004), humans of forager populations who survive to age 15 can be expected to live at least 30 more years (Blurton Jones, Hawkes, & O’Connell, 2002; Hill & Hurtado, 1996; Howell, 1979). The average adult life span beyond maturity for Ache hunter-gatherers is about 42 years (Goodall, 1986; Hill & Hurtado, 1996).
Fossil data show that adult survivorship increased quite recently in human evolution. Adult survivorship has been very low for much of human evolution, increasing dramatically with the modern humans of the Upper Paleolithic age (Caspari & Lee, 2004). Further work has shown that this increase in adult survivorship is not a direct consequence of the emergence of modern humans as a taxon (Caspari & Lee, 2006).
Although the adoption of agriculture is believed to have led to population growth, it is not clear that it was accompanied by an increase in longevity: In other words, although more people were born, they were not living longer. A substantial increase in longevity took place only after the Industrial Revolution, probably due to better nutrition and public hygiene measures that reduced infectious diseases, which decreased adult mortality. Advances in biomedicine started to play a big role in longevity only in the 20th century.
Considering the plasticity of longevity, it can be concluded that the differences in life expectancy between different populations are due to external mortality differences originating from physical and cultural environments. Across populations, mortality causes are the same, but in different order of importance. Extensive study of populations shows that there is a strong relationship between different causes of death and life expectancy (Preston, Keyfitz, & Schoen, 1972): Extrinsic causes of mortality, such as infectious diseases, are correlated with a higher crude death rate (the number of deaths each year in a population), while chronic degenerative diseases, such as cancer and cardiovascular diseases, are correlated with a lower crude death rate. Considering that infectious diseases affect a younger demography, while chronic degenerative diseases are more likely to affect an older demography, a higher incidence of chronic degenerative diseases in a population implies that more people have survived longer to be subject to chronic degenerative diseases. In other words, the increase in life expectancy that has been seen since the Industrial Revolution is likely due to a decrease in the number of deaths due to infectious diseases.
Aging and Longevity in Humans
Humans are distinctive in having a long life span, a slow aging process, and a long postreproductive life span. Chimpanzees in the wild start a visible aging process characterized by external appearance of frailty and senescence in their 30s (Goodall, 1986), and once they reach this age, they seem to age rapidly, dying by age 40. In comparison, humans show a slow aging process, with muscular strength declining over several decades. However, a lot more research on the aging process of nonhuman primates would be necessary to arrive at a sound conclusion with comparative data on performance.
Longer adult life spans can be explained by lower adult mortality rates. Typically, mortality rate is highest for infants, decreases during childhood to reach a minimum at puberty, and increases after adulthood. Case studies of supercentenarians suggest that mortality plateaus after a certain point. Humans have low adult mortality rates compared to nonhuman primates and other mammals of similar body size. The adult mortality rate for humans doubles every 8 years, while for mice it doubles every 120 days (Hill, 1993). The decrease in adult mortality rates can be explained by a lower extrinsic mortality rate, which is determined by predation and environmental hazards (Harvey & Nee, 1991). With a lower extrinsic mortality rate, adults will live long enough to die from age-specific frailty (Robson, van Schaik, & Hawkes, 2006); therefore, senescence rates are directly related to the extrinsic mortality rate. A slower rate of aging among humans would lead to greater differences in maximum life spans between humans and great apes (Hawkes, 2003).
One unique aspect of human longevity is the long postreproductive phase, especially for women. In mammals, females are born with a store of oocytes that then go through the final stage of oogenesis and ovulation (release of egg) during the reproductive phase of life. Once the number of remaining oocytes nears zero, reproductive senescence begins, and reproduction ceases. Cessation of the menstrual cycle is called menopause. A mammalian female will experience menopause, if she lives long enough. Likewise in human females, ovulatory cycling stops when there are not enough oocytes to stimulate ovulation. However, in nonhuman species, there is more or less a correspondence of reproductive and somatic senescence; humans, in particular women, are unique in that reproductive senescence occurs far before somatic senescence. In fact, women can be expected to live 25 years or more after menopause; a woman undergoing menopause does not experience a corresponding aging process in other parts of her body.
Although not enough research has been done to document age-specific changes in fertility and fecundity in older female nonhuman primates, the few studies of captive female primates show that the age at which fertility declines for these females, about 45, is similar to that of human females. This suggests that the timing of menopause is consistent through different taxa; women undergo menopause in accordance with other primate species. What is unusual in humans is the slow rate of aging beyond menopause resulting in a long postreproductive period.
The long postreproductive phase for humans, specifically human females, is a rare phenomenon in biology and therefore warrants attention. Menopause is unique in the sense that women cease to be reproductive while survival probability is still quite high and will remain so for many years. This phenomenon is found only in humans; it is not observed in nonhuman primate females, who do not live for an extended period beyond the cessation of ovulation (Pavelka & Fedigan, 1991). The grandmother hypothesis proposes to explain the extended postreproductive period by positing that human females maximized reproductive fitness by helping their daughters take care of their own offspring (Hawkes, O’Connell, Blurton Jones, Alvarez, & Charnov, 1998). The hypothesis received much attention, but it still needs strong empirical support (Hill & Hurtado, 1991).
Theories on the Evolution of Longevity and Aging
The idea of an innate biological limit of life span is supported by the observation that maximum life span does not seem to change over time. In addition, there seems to be a limited number of cell divisions in vitro even when the medium is kept fresh. It is not clear that the same limit applies to cells in vivo. However, some consider it evidential for programmed death.
Although some have argued for a nonevolutionary explanation of life span and aging, an emerging consensus is that life span and aging are processes that are possibly subject to natural selection. In this view, life span is extended or shortened as a result of selection. One explanation for aging lies in pleiotropy or antagonistic pleiotropy: That is, the same gene responsible for benefits early in life is also responsible for aging and deterioration late in life (Williams, 1957). Since increasingly fewer individuals survive to older age, there will be fewer in the age cohort, and consequently deleterious effects will not be under strong selection; likewise, a gene that confers a slight advantage early in life, when there is stronger selection due to larger population size, would be selected for even if it causes a major deleterious effect later in life. A version of the antagonistic pleiotropy theory is the disposable soma theory, which explains senescence (Kirkwood & Rose, 1991). The proponents of the disposable soma theory argue that energy needs to be used for somatic maintenance and repair. Reproductive efforts divert the energy away from such somatic repair and maintenance, resulting in a tradeoff between survival and reproduction. Natural selection will favor energy allocation to reproduction at the expense of somatic maintenance, and therefore infinite survival is not achieved.
The decrease of mortality results in the increase in average life expectancy, as more people survive to later age. There are two components of death (mortality): external mortality, due to environment, and internal mortality, referring to the presumably innate biological limit of life span. In theory at least, there is a distinct difference between extrinsic and intrinsic mortality: Extrinsic mortality refers to mortality sources that are not results of reproductive and other life history decisions; intrinsic mortality refers to mortality that is not influenced by extrinsic sources and is, therefore, implicitly innate. Accordingly, aging can be defined as an increase in the intrinsic mortality with age. It is often assumed that internal mortality is specific to a species, while external mortality can be variable due to environmental factors including food supply, diseases, and accidents. In modern days, external factors also include medicine and public health measures. However, it is not easy to distinguish between intrinsic and extrinsic effects using empirical data. Once an individual survives all external mortality factors, senescence starts the process in which the individual’s likelihood of survival declines. The aging process is not well studied among organisms in the natural habitat, because few survive to be old.
A useful theory to explain life span comes from the evolutionary perspective, which views life span as a balance between external and internal forces (Stearns, 1992). External forces lengthen life span by changing the relative value of adults versus offspring. If adult mortality is low and not variable compared to juvenile mortality, allotting resources for repair and maintenance of adult soma retains value; hence, there is selective advantage on extending adult life span. However, if adult mortality is high and variable compared to juvenile mortality, selection for adult life span becomes weak; as a result, aging effects accumulate and life span shortens.
The contribution of genetics to life span is not clear, nor is the effect of environment. Although genetics have been shown to influence life span in organisms such as nematodes and fruit flies, even nematode longevity seems to be plastic, with great variation in aging and life span. Although it is often said that long life runs in families, this does not directly point to a high heritability of longevity as a trait. This is because human families share more than genetics; they share lifestyle, wealth, education, socioeconomic status, and so forth. Therefore, even if a strong familial connection is shown, it does not lead to a clear conclusion about the genetics of human longevity. Studies on monozygotic twins also support plasticity of longevity.
The idea that aging is programmed for the fitness of the species (Weismann, 1889) has not received much support, because most organisms in the wild do not live long enough for the aging trait to be effective, and because group selection in general is not supported. The programmed aging hypothesis has not been supported by empirical evidence, either. Although several genes have been discovered to extend longevity in their mutant form, no gene has been discovered that completely eliminates aging altogether in its mutant form.
Current evolutionary thinking on aging takes a combination of the mutation accumulation model and the antagonistic pleiotropy model. The mutation accumulation model posits that late-acting mutations will remain in the genome, even if they are detrimental to survival and reproduction, if not many individuals live long for these mutations to be exhibited due to high extrinsic mortality. Because of weak selective force, such mutations accumulate over generations, and the accumulative effect will result in aging for those individuals who survive long enough (Medawar, 1952). The antagonistic pleiotropy model provides a case for why late-acting mutations would be selected: If a pleiotropic gene provides a selective advantage during an individual’s life when selection is strong, while providing a selective disadvantage during the time when selection is weak, such a gene would be selected for (Williams, 1957). Genes associated with the aging process would be such an example. Antagonistic pleiotropy and mutation accumulation are not mutually exclusive; both mechanisms are a result of weakening selective forces later in life. Physiological and biochemical expressions of aging are thought to be a result of reduced investment in repair and maintenance from the two mechanisms. However, research efforts to find antagonistic pleiotropic genes involved in aging have so far yielded unconvincing results, except life-extending genes that have been shown to have detrimental effects during early life.
There is some evidential support in physiology research that shows a trade-off. The disposable soma model argues that a lifetime of trade-offs (decision to allocate resources to some and not to others among growth and development, somatic maintenance and repair, and reproduction) evolved to maximize fitness (Kirkwood, 1977). Resources are used for somatic maintenance only if there is a good chance of survival in terms of extrinsic mortality: Under high extrinsic mortality, resources are diverted toward reproduction, away from somatic maintenance. The cost of accumulation of wear and tear (somatic damage) that is not repaired is the aging process. Indirect support for this model can be found in the match between intrinsic longevity (maximum life potential) and extrinsic mortality (Ricklefs, 1998). If these two are associated, a decrease in extrinsic mortality should result in the increase of longevity. This connection has been used to explain human longevity.
The aging process is intimately associated with the accumulation of damage on the molecular or the cellular level. Organisms with longevity invest more on repair and maintenance than those with short lives do, resulting in slower accumulation of damage over life. Thus, slow aging and longevity are connected.
Although a substantial proportion of research concentrates on discovering a specific single gene that is directly responsible for aging, there is increasing awareness that aging is a phenomenon contributed to by multiple factors and genes. This is predicted by evolutionary theory, given the variation and plasticity of the aging process. However, it is also true that mutation in a single gene can have a major effect on life span in some organisms, such as C. elegans. There seems to be a central regulator of aging that regulates the multiple genes involved in aging (Cutler, 1975) by responding to environmental signals: When environment is hostile and nutritional access becomes difficult, organisms will change allocation of resources, diverting energy away from reproduction and into somatic maintenance. Findings that calorie restriction leads to life span extension can be explained by this hypothesis.
An evolutionary analysis of human longevity often applies life history theory. Life history theory aims to explain the variation in timing of fertility, growth, developmental rates, and death of living organisms according to trade-off mechanisms between mortality, fertility, and reproductive success. Life history variables include age-specific mortality and fertility as well as traits that are associated with age-specific mortality and fertility, such as life span, age at which an individual first gives birth (for females), and growth and development. First developed in the 1950s, life history research saw an increase in attention in the 1990s (Charnov, 1993; Roff, 1992; Stearns, 1992). The basic principle of life history theory relies on trade-offs; that is, due to limited resources, decisions have to be made in terms of resource allocation in such a way that allocation to one purpose deprives allocation to another, competing purpose. Assuming an optimal allocation strategy, one could posit a pattern of life history of organisms. Natural selection shapes life histories that lead to fitness advantage while also leading to evolution of the ability to change life history variables in different environments.
The human life history pattern differs from that observed in the great apes in its slow maturation, slower growth, higher fertility, and increased longevity, which is associated with menopause in women (Hawkes et al., 1998; Kaplan, Hill, Lancaster, & Hurtado, 2000; Robson et al., 2006). Within the framework of life history study, human longevity becomes a part of a configuration of life history variables that can be summarized as slow life: slow growth, late onset of reproduction, and slow mortality (Charnov & Berrigan, 1993). Primates in general are slow, and humans are particularly slow, although there are some parts of human life that are fast, such as increased fertility (Charnov, 1993; Harvey & Clutton-Brock, 1985; Harvey & Nee, 1991; Prothero & Jurgens, 1987).
Although it is often argued that humans have only recently started to live long lives, some argue that increased longevity and decreased mortality may have a long history in human evolution (Paine & Boldsen, 2006). According to Charnov, it is the slow growth that is driving the evolution of slow life history (Charnov & Berrigan, 1993). As such, longevity is an associated, correlated phenomenon (or an epiphenomenon) resulting from slow growth, and it is slow growth that needs to be explained. On the contrary, longevity itself may be selected for, and this needs to be explained. Examining the changes in longevity through time may shed light on this issue.
Longevity in the Human Fossil Record
Changes in longevity itself have not been empirically assessed. This lack of focus on longevity is at least partially due to constraints inherent in paleodemography that impede the reconstruction of life tables for fossil populations. Longevity is difficult to assess for prehistoric populations because of a number of well-known problems that affect paleodemography. First, fossils are almost always available only in small sample sizes, which limits application of conventional statistical methods. There is always a question of whether specimens adequately represent the populations to which they belonged.
Second, different age groups are differentially preserved. This is particularly problematic for juveniles, since their fragile skeletons are less likely to be preserved than those of older individuals. This has far-reaching implications, because most of the parameters of interest in demography, those that are present in life tables, are dependent on information about juveniles. Understanding of longevity is likewise affected by juvenile data, because life span is strongly influenced by juvenile mortality rates.
Finally, there is the problem of assessing age at death. Even for modern humans, adult ages at death can be difficult to estimate with precision, especially for older individuals. Virtually all aging methods become less accurate with increasing age, and are most effective with multifactoral approaches, which utilize many different criteria for aging a single skeleton. Because most fossils are fragmentary, multifactoral approaches are usually impossible, and because so much is unknown about maturation rates and other life history factors, estimation of age at death is daunting. In addition, uncertainties about maturation rates, which may have varied over the course of human evolution, make numerical assessments of age at death problematic.
These three problems—sample size and associated statistical limitations, the absence of representative juvenile data that impede the construction of demographic profiles, and the lack of resolution possible when determining ages at death for fossilized remains—have caused impediments to the empirical study of human longevity in the fossil record.
Because it is so hard to study directly, prehistoric longevity has been discussed through its correlation with other variables, such as body size, brain size, and growth and development patterns. The actual pattern of change in adult survivorship critical to testing the relevance of correlations between brain size and longevity for human evolution, and any of the other questions surrounding the evolution of human longevity, have yet to be empirically established.
Population Growth and World Population
Humans live everywhere in the world, in both northern and southern hemispheres. However, this was not always the case. At the beginning of the ancestral human lineage, after the divergence between humans and their closest related species, ancestral fossil humans (hominids) lived only in Africa, in small numbers. It is with the appearance of the genus Homo in the terminal Pliocene and Pleistocene epochs that ancestral humans spread out of Africa into the world. Presuming that population density was maintained during the worldwide spread of humans, the overall population size would have increased accordingly. As of January 1, 2009, world population was estimated at 6.75 billion.
While ancestral humans subsisted on foraged foods, population size increase was kept at a relatively modest rate. With food production through agriculture and animal domestication, population size and density increased substantially. With the Industrial Revolution, world population saw an increase in the increase rate, leading to an exponential increase in population that led to many alarmist concerns about a population explosion. World population has seen acceleration in its growth rate since the mid-18th century.
Population growth is a result of an accumulated surplus over time, a surplus generated from an imbalance between members coming in (births) and members going out (deaths). Regional population sizes are determined by migrations (emigrations and immigrations) in addition to births and deaths, but the effects cancel out when viewed from a world perspective.
For population to grow, fertility has to be higher than mortality. When the number of people reaching adulthood and reproducing equals the number of people dying, the population size is at equilibrium, and there is no growth. Such a population is said to be stationary. For most of human history, it is assumed that there has been a balance between fertility and mortality, that both fertility and mortality have been kept high. With recent advances in medical care and nutrition, mortality has decreased, while fertility has not changed much. The resulting increase in population size has subsequently met with another change, a decrease in fertility. Eventually, population size will reach a plateau with both fertility and mortality kept low. The demographic transitions model argues that human populations undergo a series of changes, first a decrease in mortality, then a decrease in fertility.
The actual birth rate, or the fertility rate, is lower than the maximum possible birth rate; biological events such as miscarriages, abortions, and stillbirths as well as sociocultural conditions such as contraception, delayed reproduction, late marriage, and celibacy contribute to the difference between possible birth rate and actual birth rate. Human populations differ in fertility rates, from more than 10 children per woman to 2 children per woman.
In the 1970s, there was quite an interest in the total number of humans that have lived throughout history, and some scholars gave estimates based on an exponential growth model for human populations. Based on the distribution pattern and density of archaeological sites, it seems that human species lived in small populations with low population density during most of human evolutionary history. Weiss used hunter-gatherer population density of 0.28 per square kilometer to estimate population size from areas of habitation during the Pleistocene: His calculations indicate that there were 0.5 million people between half a million and a million years ago, and that this number increased to 1.3 million in the Middle Paleolithic (Weiss, 1984), although such estimates are far from accurate and associated with large error.
With the appearance of the genus Homo in the early Pleistocene, hominid populations expanded throughout the world, continuing to grow in size. The world population now is well over 6 billion. For most of human history, humans lived in small, mobile groups. Consequently, population size was small. It is only in the last 10,000 years, with the adoption of food production through agriculture, that world population has seen an explosion in its growth rate. Considering that only 6 million people may have inhabited the world around the beginning of the Holocene (and agriculture), there is a 1,000-fold increase in world population in the last 12,000 years (Weiss, 1984). Such exponential population growth has continued since the start of agriculture in the early Holocene (Pennington, 1996) and possibly started before that during the late Pleistocene (Hawks, Hunley, Lee, & Wolpoff, 2000).
The proportions of people at different ages are often represented by a population pyramid, which shows the percentage of population by age and sex. The shape of a population pyramid reflects the mortality and growth rate of that population. A population pyramid with a wide base and narrow top (approximating a triangle) represents a high mortality or high fertility rate. If fertility rate increases, the base will expand, as there will be a higher proportion of younger people in the population. If fertility rate decreases, the base will narrow, and the population becomes older. The recent global trend of fertility decrease is producing a top-heavy population pyramid with a higher proportion of older people in many countries. Such countries have met this prospect with much concern about the economic support of the elderly, their healthcare, and their quality of life. It should be noted that the demographic shift has occurred with changes in fertility and few changes in mortality or adult life expectancy. In a forager population, only about 10% in a cohort will survive beyond age 60, and they will make up 3% of the population; in contrast, modern industrialized countries can easily see 75% to 85% in a cohort surviving to age 65 (Weiss, 1981).
There are several aspects of longevity. Maximum life span is thought to be biologically determined, while average life span or life expectancy is subject to extrinsic mortality rates. Several models have been proposed to explain the biology of longevity and aging. The hypothesis of programmed death does not have a strong support. Current research supports the combination of the mutation accumulation model and the antagonistic pleiotropy model.
Using the correlation between longevity and brain size or body size, life span of ancestral humans can be estimated. Increased longevity over time is one of the distinguishing features of the human species. Documenting the pattern of changes in longevity through time is critical in understanding the evolutionary origin of human longevity and its relationship with other human life history variables. However, empirical examination of past human longevity faces methodological difficulties due to the nature of fossil data. While there is a trend of increase in longevity over the course of human evolution, the increase is most dramatic in the modern age since the Industrial Revolution. Increased longevity is a result of decreased adult mortality and is one of the factors contributing to increase in population size. As in the case of longevity, human population size increased over time, with the most dramatic increase coming after the Industrial Revolution.