Biodemography Of Mortality Research Paper

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Demographers have increasingly incorporated biology into their theoretical models and empirical analyses of both fertility and mortality. This incorporation of biological thinking into the study of mortality and aging has been termed ‘biodemography.’ Olshanky defines biodemography as the study of ‘age patterns of mortality, interspecies comparisons of death rates, and biological explanations of why such patterns exist’ (Olshansky 1998, p. 384). Biodemography focuses on whether the senescent process or physiological change with age is immutable and programmed into the species or whether this process can be changed with intervention. Olshansky (1998) phrases the central questions as Why do we age? How do we age? When do we age? While demographers have been interested in the last question, when do we die, without some understanding of why and how this occurs, demographers will not be able to project and predict when.

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While it builds on centuries of work by both demographers and biologists, the contemporary approach to ‘biodemography’ came into prominence in the 1990s (Olshansky and Carnes 1997). The wide use of the term to describe this subfield of demography was adopted with the publication of the volume of papers by demographers and biologists, Between Zeus and the Salmon: The Biodemography of Longe ity (Wachter and Finch 1997). This volume, published under the auspices of the National Research Council of the National Academy of Sciences of the United States, provides a good introduction to the breadth of issues addressed in the field.

1. Why Did Biodemography Become A Research Focus In The 1990s?

Trends in mortality over the last half of the twentieth century set the stage for linking demography and biology. The stability of mortality during the late 1950s and most of the 1960s led demographers to predict little future decline in mortality or increase in life expectancy (Crimmins 1981). They reasoned that exogenous causes of death—e.g., infectious diseases— had largely been conquered and that endogenous causes could not be affected by environment and intervention. This view has been shown to be incorrect by the subsequent extensive mortality decline. Dramatic reductions in death rates beginning in the late 1960s were concentrated largely among what might have been considered endogenous causes. These reductions were responsible for the significant increases in life expectancy which occurred during the last three decades of the twentieth century in virtually all low mortality countries of the world. The rapid decreases in mortality at even the oldest ages contradicted conventional wisdom and left demographers insecure about predicting future mortality level, life expectancy, and age structure of populations. The central questions for demographers interested in mortality at the older ages became: How long will future populations live? Is there a limit to life expectancy? Can the expected length of life or length of the lifespan be changed? The observed increases in length of life at the older ages and the increasing growth in the numbers of older people led to an additional question: Does longer life mean better health?

At the same time as these questions were becoming prominent demographic issues, they were also being raised by biologists interested in aging. While demographers historically have had an empirical approach to examining mortality change, the biological approach to aging has strong theoretical underpinnings. In the past biologists had also emphasized the inevitable nature of the senescent process with aging. More recent biological theories stress a number of mechanisms that can potentially be affected by changes in the physiological makeup of organisms or in the external environment in which the organisms age (Ricklefs and Finch 1995). Both theoretical advances and empirical observations were leading biologists to the same set of questions arising among demographers.

The ability of biologists to examine mortality and aging among other species in experimental settings holds promise for further insight into human aging and has encouraged interest in biodemography. Because experimental conditions, including the characteristics of organisms as well as the environment, can be manipulated, nonhuman populations provide useful information on the potential for changing human longevity. The commonalities between the senescent patterns of other species are being examined for clues to the potential for human life expectancy. The methods of demography can be usefully adapted in analyzing mortality and aging processes in other species; while the experimental design and shorter life span of some species studied in biology can provide answers to the questions of demographers.

Biologists have examined the age patterns of mortality in a variety of organisms and found remarkable similarity across species (Finch 1990, Finch and Pike 1996). While the range of average life expectancy varies from hours to centuries across species, the Gompertz curve, first derived to describe age variation in human mortality, fits the age pattern observed within other species remarkably well. Insights to mortality at the oldest ages are gathered from the fact that for humans and nonhumans, at the end of the species lifespan, mortality is lower than predicted by the Gompertz model (Vaupel et al. 1998).

Another factor that encouraged the collaboration of demographers and biologists in addressing these questions during the 1990s was the mapping of the human genome. Understanding the genetic influences on mortality and morbidity or on susceptibility to diseases will clearly be an important factor in predicting and perhaps changing future mortality and aging (Weiss 1989, Weiss 1990). Currently there is interest in variation in genetic endowment across populations and how this affects differential mortality and how certain genetic characteristics interact with the environment and lifestyle to affect disease onset and longevity (Ewbank 2001). The incorporation of genetic indicators adds an additional dimension to studies of the determinants of both population and individual lifespans and disease experience. The study of factors affecting individual experiences has sometimes been termed ‘Medical Demography’ which can be regarded as a subset of ‘Biodemography.’

2. How Long Will Future Populations Live?/Is There A Limit To Life Expectancy?

The title of the book From Zeus to the Salmon represents the range of possible models of species survival. The gods, including Zeus, were immortal; they did not age after reaching maturity. At the other end of the continuum, salmon die shortly after reproducing. The human species obviously fits somewhere between these two models. Biologists emphasize the link between reproduction and mortality in a way that is novel for demographers but which offers important insights into population potential.

Evolutionary biologists have focused on the role of natural selection in affecting species lifespans. Natural selection promotes characteristics that increase survival up to the end of the reproductive period; it does not eliminate the characteristics of populations that are related to diseases and death occurring after reproduction ends. The characteristics related to the diseases and disabilities that increase in frequency after the end of the reproductive period have thus not been influenced by the process of natural selection (Olshanky et al. 1998). Understanding the influence of the evolutionary process is important for understanding both current and future age patterns of mortality. Projections of future human life expectancy depend on assumptions about possible reductions in mortality at the oldest ages. Because mortality before old age is already so low, increases in life expectancy will be achieved primarily through declining mortality at the oldest ages. In projecting future mortality at older ages, a central question arises: Is there an age beyond which humans cannot live? If there were such an age, mortality would be 100 percent at this age and there would be no survival beyond this age.

The empirical evidence on this point for humans is provided by both individual and population experience. Jeanne Calment, a French woman, lived to the oldest documented age—122. This provides the evidence that humans can live to at least that age. Data for populations from a number of countries indicates that mortality decline and the extension of life expectancy have occurred even at the oldest ages (Kannisto et al. 1994). There is no empirical evidence that we are reaching an age where there can be no further decrease in mortality or a limit to lifespan.

As noted above, the empirical evidence is that at the oldest ages, the age-specific increase in mortality is less than that predicted by the exponential Gompertz model. One explanation of lower mortality among the oldest old is the heterogeneity that occurs in population with regard to survival enhancing characteristics (Vaupel 1997). As mortality is examined at increasingly older ages, the population is increasingly selected for characteristics that affect survival which may reflect heterogeneity in initial endowment in the population. Of course it could also reflect heterogeneity in behavior and environment related to survival.

Demographers studying health and mortality in old age have also turned to increasingly complex models of individual life chances. In developing models to explain individual differences in age at death or disease onset, demographers have incorporated explanatory variables from other disciplines including biology. For instance, there has been recognition that early lifespan environmental circumstances may have significant effects on late life health outcomes. Early life includes uterine development as well as childhood conditions. Finch notes that the ‘the ova from which we arose were found in our mother’s ovaries while she was a fetus in our maternal grandmother’s uterus, which allows environmental effects to span at least three generations in mammals’ (Finch 1997, p. 245). This leads to a lifecycle view of individual aging prospects and the incorporation of indicators of early lifecycle events in explanations of old age heterogeneity in health outcomes (Barker 1998, Elo and Preston 1992).

3. Can The Expected Length Of Life Be Changed?

Recent work with a variety of species has clarified that there is plasticity to the aging process among a variety of nonhuman species, which leads to the expectation that human lifespan will be changed by similar influences. Longevity changes can be induced with environmental, behavioral, and physiological changes. For instance, food restriction in rodents has been shown to increase life expectancy; this provides clues to the way metabolic changes in humans may related to the aging process (Finch 1997). Experiments on fruit files in which the population was selected according to reproductive ability have been used to show that the longevity of the species can be changed and that evolutionary limits to lifespans do not exist (Finch 1997).

One of the central questions being addressed by biologists of aging is whether there is a set of genes that are more generally related to longevity. What are called longevity assurance genes (lag genes) have been identified in some nonhuman species. Manipulation of the genetic makeup of populations of organisms has resulted in experimental extension of average life expectancy in a number of species. Specific genes have been identified in some species that control some of mechanisms theorized to cause the aging process. For instance, one biological theory of aging emphasizes the role of oxidative stress as a cause of progressive physical deterioration with age. Genetic defects in the oxidative-stress response mechanisms of organisms have been linked to longer lifespans in a number of species including worms, flies, and mice. The success at finding similar classes of genes across species including mammals provides rationale for assuming that similar mechanisms will be identified in humans.

Knowledge of the human genome may allow us to increase both average life expectancy and potential life span. Longevity is partially under genetic control and the coming decades will provide extensive information on genetic determinants of both specific disease processes and possibly the aging process itself. Estimates derived from twin studies of human populations are that about 20–30 percent of the variation in age at death after adulthood can be explained by genetic makeup (Vaupel at al. 1998). Genes that cause agerelated diseases are being identified with increasing frequency. Specific genes related to familial types of breast cancer, colon cancer, and Alzheimer’s disease are now known. One genetic allele (ApoE2) appears to be protective of a variety of conditions that are part of the senescent process including cardiovascular deterioration and cognitive loss (Ewbank 2001).

One insight for the general pattern of mortality gained from experiments with genetically identical individuals is that the species age curve of mortality tends to retain its general shape even among genetically and environmentally fixed groups. Demographers might have expected constant genetic endowment and environment to eliminate the variability in mortality or to cause mortality for all individuals in the population to occur at an identical age. In other words, to cause the survival curve to be perfectly rectangular. The fact that the age curve of mortality retains its original shape means that additional factors affect variability in survival. Interesting hypotheses are suggested by Vaupel’s discussion of bioreliability (1997) and Finch’s (Finch and Tanzi 1997) notion of stochastic biological process.

The empirical results of demographers based on human populations and the experimental efforts of biological researchers both lead to the conclusion that there are no observable fixed limits to species’ lifespans. At this point we must conclude that the length of the lifespan can be influenced by a variety of factors both internal to the species and occurring in the environment in which species exist. This leads to the conclusions that there is dramatic potential for change in the human lifespan.

4. Does Longer Life Mean Better Health?

With recognition of the substantial mortality declines at the oldest ages and knowledge of the impending dramatic increase in the size of older populations projected for the low mortality part of the world, interest has turned to the expected length of healthy life as well as the expected total length of life. Demographers and policy makers wanted to know whether the increased length of life had been accompanied by increases in the length of healthy life. This discussion was initially generated by the introduction of the ‘Compression of Morbidity’ hypothesis by Fries (1980). Fries posited a fixed limit to life expectancy and assumed that as it was approached morbidity would be compressed into a shorter period at the end of life.

The question of the relationship between longer life and healthy life does not arise in a disease regime dominated by infectious diseases but only when health is dominated by the chronic ‘incurable’ conditions of older age. Mortality is the end of a process of individual health change that begins with the onset of diseases and conditions. It is possible to intervene in that process in a variety of places: to prevent disease, to prevent progression of disease, to prevent the disability arising from disease, or to prevent death among those with severe disability and disease. The point of change determines the answer to the question of whether longer life will be accompanied by improved health. If the reason for longer life is that disease has been prevented, then declining mortality will be accompanied by lengthened healthy life. If mortality decline occurs because severely ill people are being kept alive, the length of healthy life will not be longer and populations will not be healthier.

The length of healthy life can be measured by combining mortality and morbidity schedules using a life table approach to estimate years of life in good health and in poor health. This combination of mortality and morbidity is appropriate for measuring health status in populations with low mortality which are dominated by chronic disease. The empirical evidence for a number of countries showed that initially mortality decline at older ages was accompanied by increasing expected life with disease and moderate disability. For countries where change can be examined, the length of non-disabled life appears to have increased. Extending healthy life and improving population health in the future is likely to be accomplished by delaying the onset of diseases and conditions associated with aging (Bone et al. 1995).

5. Future Directions In Biodemography

This is a field whose boundaries are changing constantly with relevant scientific advances. It will become an increasing focus of demographers interested in both mortality and morbidity as the implications of the mapping of the human genome are developed. Demographers are beginning to integrate both biological and genetic information into surveys designed to examine individual variation in the length of life and the disease process (Finch et al. 2001).


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