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1 Between Zeus and the Salmon: Introduction Kenneth W. Wachter This volume takes stock of what biology and demography have to tell and ask each other about human longevity as we move into the Third Millennium. The timing is auspicious. First, recently published works have made the base of accumulated biological knowledge accessible. Finch (1990) has written an authoritative summary of the comparative biology of senescence. Charlesworth (1994) and Rose (1991) have covered evolutionary theory for aging, and Steams (1992) has covered organism life-history analysis. A historical perspective has been given by Olshansky and Carnes (1997). Second, the initial harvest of results from program projects combining biology and demography sponsored by the U.S. National Institute on Aging has just reached the scientific literature. The remarkable hazard functions for a million Mediterranean fruit flies (Carey et al., 1992) and for genetically uniform populations of Drosophila (Curtsinger et al., 1992) are prominent examples. Now is the moment for planning the next waves of joint research. Third, forecasting survival and health for the oldest-old over the next 50 years has become an urgent political need, as developed societies try to plan for avoiding bankruptcy for their social insurance and medical systems. Our uncertainty as to whether current trends will continue or taper is bound up with our uncertainty about the general nature of biological limits to longevity. This introductory chapter is a personal overview from the vantage point of a demographer. A balancing perspective from the vantage point of a biologist appears in Caleb Finch's concluding chapter. As I see it, for demographers today, the golden challenge is to make the right judgment call predicting our children's life spans. Will the recent pace of gains in life expectancy and active life expectancy extend to the next generation, or are we approaching the point of diminish-
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ing returns? The deep theoretical questions in the demography of mortality and aging-including the proper framework for incorporating genetic variables and cofactors into demographic models-cluster around this very practical question of prediction, whose answer some of us may live to know. Confronting this question, the in-house tools of traditional demography—accurate accounting of vital trends and descriptive modeling of variability across time and circumstances—are indispensable but inconclusive. Knowledge of detailed mechanisms is too patchy for causal models with aggregate implications. Thus demographers are thrown back on a search for analogues. Biology is our cornucopia of analogues. I do not want to overstate the relevance of biology to demography. Biology will not settle demographic questions directly. Finding the causes behind the leveling out of fruit-fly hazard functions after 100 days will not disclose the causes behind any leveling out of human hazard functions after 100 years. Genes promoting survival at advanced ages may be found in nematode worms without giving us any right to expect usefully close counterparts in people. Darwinian theory, for all its triumphs, is a poor basis for predicting whether women's advantage in life expectancy over men will be increasing or decreasing in 2047. Nonetheless, biology is definitive. Experiments with laboratory organisms, genetic mapping, natural history, and evolutionary theory are defining the intellectual landscape within which demographic arguments and forecasts gain or lose their appeal. Uncertainties are so great and mortality prediction is so much a matter of bets and guesses that the powerful analogies provided by biology are the best guides we have. These analogies offer a basis for implicit choices about what to regard as ad hoc and what to regard as general, what forms of models to try, what kinds of data to put in the foreground. Biological analogies raise or lower our comfort level with particular kinds of scientific explanations. It seems to me, as I shall describe, that the newest work in biodemography is lowering our comfort level with accounts involving limits to life expectancy and programmed senescence and enhancing our openness to models and hunches that treat life spans as highly plastic. I begin by reviewing ideas from the evolutionary theory of longevity that have coexisted amicably with a pessimistic demographic stance in regard to open-ended further progress against old-age mortality. I then turn to new empirical results that are reviving an optimistic stance, to studies of the role of the elderly in nature, and to new theoretical departures. I conclude with a look at the immediate future and the knowledge we can hope to gain from further joint work in biodemography. Stern Theories The emphasis on limits and tradeoffs in biologists' discourse about longevity goes far back, and still predominates. In the 1960s, when a plateau seemed to be
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appearing in progress against human mortality at older ages in developed societies. The climate of biological opinion made it natural for demographers to see the plateau as a long-term phenomenon. Diminishing returns at older ages fitted into the broad-brush theoretical picture and made it reasonable to discount the likelihood of that resumption of progress that did, as it turned out, actually occur. Evolution coddles you when young and forsakes you when old. This central idea can be traced back more than a century to Alfred Russel Wallace (Rose, 1991:4); the evolutionary theory of senescence that has grown from it is described by Shripad Tuljapurkar, Linda Partridge, and Michael Rose in Chapters 4, 5, and 6, respectively. Natural selection clears away genes that compromise reproduction or survival to and through the ages of reproduction. Natural selection leaves to their own devices genes with bad effects at ages that no longer matter as far as the propagation of progeny is concerned. In most mathematical implementations of this kind of theory, ''ages that no longer matter" have been equated to postreproductive ages of zero fertility; the efficacy of natural selection on mortality as a function of age has been taken to decline smoothly throughout the reproductive period, reaching zero at its end. These ideas have ramified into two intertwining but distinguishable theories, the "mutation-accumulation theory" and "antagonistic pleiotropy." The mutation-accumulation theory recognizes that most mutations are unfavorable. Some portion of mutations elude repair. Suppose there are genes that specifically impair survival at some range of older ages without substantially reducing net reproduction. Suppose that the structures affected by the genes and the environmental preconditions for their actions have been in place for a very long time and that what is bad for survival stays bad in the face of surrounding change. Then mutations deleterious to survival at older, postreproductive or postnurturant ages should accumulate over eons, since selection is not clearing them away. Genes predisposing to cancers are often adduced as examples. In its simple forms, this mutation-accumulation theory predicts sharply rising hazard functions beyond some threshold age. Antagonistic pleiotropy, as it pertains to senescence, occurs if there are genes that have positive effects on net reproduction and negative effects on postreproductive survival. If such genes exist, then organisms would be making a tradeoff between investments in younger-age reproductive fitness, which matters to natural selection, and older-age viability, which does not matter to natural selection. Kirkwood's (1977) "disposable soma theory" sees tradeoffs of this kind as a general phenomenon arising as organisms allocate limited energy between functions of reproduction and functions of somatic—bodily—maintenance. Like mutation accumulation, antagonistic pleiotropy and the tradeoffs posited by the disposable soma theory are reasons for hazard rates to rise with age. Sustaining these considerations is the timeless observation that life in the wild is, as Hobbes put it, "nasty, brutish, and short"—in the wild few creatures survive to old age, so genes governing late-age processes have had little opportu-
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nity to matter. The higher the background frequency of deaths from predators or accidents, the more this should be so. Evolutionary theory successfully predicts an association between greater vulnerability and more rapidly rising age-specific mortality. Small insects are an example. Small, exposed, ground-dwelling mammals are another example, contrasting with safer, tree-dwelling mammals and birds (see Charlesworth, 1994:247-248). Finch (1990:22-25 and throughout) sets out an impressive array of evidence from modest samples from many species displaying rising and often accelerating hazard rates with age. Ever-accelerating hazard rates with age imply de facto limits on later life expectancy, and if the observed accelerations with age do share a common general evolutionary origin, that would be a rationale for expecting genetically preprogrammed limits to longevity. Alongside these ideas from evolutionary biology, there is the mystique of the "Hayflick limit" from cell biology (see Hayflick, 1994:111-136). Certain types of mammalian cells transplanted to cultures only divide up to a limited number of times. The limits correlate roughly with the typical life spans of the organisms from which the cells come. The cells that have stopped dividing often continue to survive in less-than-prime condition. While this process may be implicated in some localized phenomena of aging, any pervasive role for the Hayflick limit on cells in determining the senescent mortality of organisms remains uncertain, as Caleb Finch discusses in the concluding chapter. Nonetheless, as the most frequently cited result in all of gerontology, the Hayflick limit has contributed powerfully to a general sense that the study of longevity is a study of limits, tradeoffs, and diminishing returns. The ideas that lead to the theories of mutation accumulation and antagonistic pleiotropy are very general principles of evolution. They serve as a paradigm for thinking more broadly—transcending specific reference to genes—about the investments reflected in the ways we and other creatures are designed. Nature puts a premium on solving problems of the kind that show up early in the life course. Organ systems need not be constructed to implement repairs or withstand cumulating challenges late in life. Out of this essentially pessimistic view, however, has come a simile with an optimistic turn. In this volume, James Vaupel develops it in Chapter 2. The body is likened to a planetary space probe like the Pioneer mission to Mars. The Pioneer's engineers worked through all the problems and built in all the safeguards needed to be sure that the Pioneer probe would reach Mars and complete its mission. Just so, the body must be engineered to complete its evolutionary mission—produce and nurture its young and pass on its genes. After its mission is accomplished, it is disposable. No special provisions for longer operation or late-stage repair are advantageous. But the Pioneer space probe was still functioning as it left the Solar System. The same mechanisms built in to guarantee fail-safe completion of the mission may endow the body, as they did the Pioneer, with residual post-completion life.
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This simile is optimistic, for it emphasizes the degree to which we and other creatures may be preadapted for late-life survival. Preadaption means that a system honed by evolution to solve one problem turns out, serendipitously, to be a full-fledged good start on the solution to another problem. For longevity, the idea is that Murphy's Law functions in our favor. Most of the things that can go wrong do, early in life, during development or on its heels, and the list of specifically late-life major problems that evolution was able to leave unsolved is not endless but finite. Nature provides us with examples of preprogrammed senescence in its most dramatic form—hazard rates that rise abruptly toward infinity at the end of reproduction. Shripad Tuljapurkar, in Chapter 4, points to the most famous example, the salmon, struggling upstream, in Robert Lowell's words, ". . . alive enough to spawn and die." For an image of the opposite alternative, we may turn to the Greek gods on Mount Olympus. The gods are born and go through infancy. Hermes carries the infant Dionysus. The gods grow up. Each develops up to his or her own characteristic age. Artemis grows into a young woman, Apollo into a young man, Zeus into a patriarch in the prime of life, Hephaistos into middle age. When development is complete, aging stops. The Olympian gods stay the same age forever after. Their genes, as it were, specify their developmental stages. Programmed aging occurs up through the intervals of development. But then, when development is complete, aging is over. In the favorable environment of Mount Olympus, with the favorable nutrition of nectar and ambrosia, the organism simply goes on surviving. The gods become no frailer with further age. (They also become no wiser.) The celestial genome, as it were, has no genes with specific effects for late-age changes, and nothing stands obdurately in the way of uncurtailed longevity. The title of this book comes from the thought that the mission of biodemography is to find for us our proper place between Zeus and the salmon. Empirical Challenges The ideas that emphasize limits have been challenged in the last decades by new empirical results and by new theoretical departures. In this section I review the new empirical results. First is the discovery that hazard functions measured at extreme ages in large populations from several profoundly different species do not rise indefinitely with age. In some other cases, they rise, but at decreasing rates. These results come from the first wave of studies sponsored by the U.S. National Institute on Aging's initiative on the oldest-old, principally from the program project led by James Vaupel, and he sums them up in Chapter 2. The million Mediterranean fruit flies (medflies) and the genetically homogeneous populations of Drosophila flies mentioned at the outset of this introduction have been joined by nematode worms and
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Mexican fruit flies and millions more medflies. Controlled experiments have established that the leveling is not an effect of decreasing density. Some leveling-off of the hazard function at extreme ages has been detected in the best-recorded recent data on human populations, and decreasing hazards at extreme ages are implied by the survival of the world's oldest well-documented individuals. A second set of empirical results that challenge the ethos of limit theories are careful measurements that show human death rates in developed societies to be falling even among the oldest of the oldest-old. John Wilmoth describes these trends in Chapter 3. He shows how gains against mortality over age 80 and even over age 90 have been accelerating since 1960 in nine countries with high-quality data. Wilmoth's own studies of Swedish deaths show an aging of mortality decline; the ages at which one finds the most rapid improvements have been moving up. The graph of maximum reported age at death for each calendar year has a visible upward trend. Wilmoth brings some order into the grab bag of definitions people have given for what "limits to longevity" might mean and infers, on the basis of a cross-national comparison, that advanced societies are unlikely to be approaching any such limits at the present time. A third set of empirical results come from laboratory experiments with the selective breeding of flies, mice, and other laboratory animals. These have revealed an extraordinary plasticity of life span in the face of selection. An account of these studies, including many performed in his own laboratory, is given by Michael Rose in Chapter 6. Under favorable conditions in the laboratory, as has long been known, some individuals live many times as long as their typical life spans in the wild. There turns out to be enough genetic variability for traits related to longevity that artificial selection for late reproduction in the laboratory over 50 generations can increase average life spans by 80 percent. Genes have also been identified, preeminently in nematodes, with special alleles that increase average life spans up to several fold. These "longevity assurance genes" are discussed by Thomas Johnson and David Shook in Chapter 7. All this research suggests impressive genetic potential for enhanced longevity. Caleb Finch makes plasticity his theme in the concluding chapter of this volume. A fourth set of empirical results focus on the relationship between heterogeneity and hazard rates at extreme ages. They come from the studies of Drosophila and nematodes by James Curtsinger's and Thomas Johnson's groups. These studies indicate that the observed leveling of hazards at advanced ages is not produced solely by the selective effect of genetically frailer individuals dying earlier, leaving genetically more robust individuals to die at lower rates at later ages. The leveling occurs in pure-bred strains, among populations of individuals who are nearly genetically identical. A critical open question is whether selectivity in the face of developmental and environmental heterogeneity can account for all the leveling not attributable to genetic heterogeneity. James Vaupel debates this question in Chapter 2 and cites one calculation indicating that some part of the leveling is not a selectivity
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effect but is built into the life course of individuals. This calculation is preliminary and is uncomfortably closely tied to particular mathematical forms for the hazard function. If further research, however, does compel us to invoke a complicated dynamic of individual life-course changes at extreme ages for comparatively simple species of flies and worms, then we shall find ourselves prepared to expect it in ourselves. The Elderly In Nature These new empirical results promote a sense of a genetic heritage produced by evolution that is permissive or even positive, as far as old-age survival is concerned, in contrast to the sense of limits characteristic of earlier writings in the evolutionary theory of senescence. Paralleling this work is a renewed appreciation of the roles of the elderly in nature. The middle chapters of this volume shift attention away from the common case of species in which elderly individuals are hardly to be found alive in nature to the interesting exceptional cases in which postreproductive individuals are to be found. In Chapter 8, James Carey and Catherine Gruenfelder challenge the assumption that postreproductive years make little contribution to fitness in the face of natural selection. They draw on recently enriched natural histories and observational studies of elephants, toothed whales, and primates to document contributions of the elderly in social species that might be important in evolutionary terms. Demographers of aging will encounter in this chapter remarkable precedents in nature for human social roles. There are male dolphins of grandparental age baby-sitting the young in sheltered coves while parents cruise the coast for food. There are elephant matriarchs serving as the seasoned executives of their herds. Effects on fitness are difficult to quantify, but such a variety of contributions can be identified that substantial total effects are plausible. Kin selection is nothing new to Darwinian theory. But the mathematical theory for age-structured populations, taking off from Norton (1928) and developed by Charlesworth (1994), has been preoccupied with direct contributions to reproduction as reflected in Lotka's net maternity function. Expressions with grandparental and other postreproductive terms in them have been relegated to the background, and, for the most part, "out of sight is out of mind." The new interest in the elderly in nature reflected in this volume calls for a redeployment of mathematical attention. In thinking about biodemography, we have to remind ourselves continually that day by day we are not seeing humans within the relevant evolutionary environment. Neither, however, are the conditions under which humans evolved entirely a black box. Close observation of the small remaining groups of hunter-gatherers on the planet and of the small remaining groups of primates in unruined habitats can stretch our minds in an imaginative reconstruction of the constraints
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and opportunities our ancestors may have faced. The coming decade or two may be the last opportunity to gather priceless knowledge. Hillard Kaplan writes from personal experience and published studies in Chapter 10 about the demography and life-course patterns of hunter-gatherers. He singles out the skill-intensive food niche that these humans occupy in comparison with primates as a decisive evolutionary factor. This situation implies a long provisioning period for the young. High returns to investments in slowly acquired skills go in tandem with high returns to prolonged adult survival. Kaplan estimates that couples begin reproducing at ages when they are first able to support themselves alone. Food for their offspring must come initially as transfers from older members of the group, such as grandparents. Meticulous field work has given us estimates of interage and intergenerational transfers in several hunter-gatherer societies. Ronald Lee shows in Chapter 11 that these estimates fit in well with the patterns of downward age-specific resource flows measured by himself and others in agricultural societies, which have given way to upward flows in economically more developed societies. The theme of intergenerational transfers is probably the closest meeting ground between biodemography and the rest of contemporary demographic research. Steve Austad surveys precedents among other species in Chapter 9, including mother kangaroo rats who bequeath to their daughters mounds with food stores. There is a tantalizing circularity to intergenerational transfers. Downward age-specific flows imply a higher contribution of older individuals to Darwinian fitness, through the net reproduction of their descendants, letting evolution encourage older survival. Upward resource flows, however, help keep older individuals alive. Ronald Lee imagines what would happen if there were a gene governing behavior impelling offspring to take care of their parents in old age. The parents could then confidently sacrifice their own reproduction on behalf of their offspring's reproduction, having guaranteed that their offspring could not go back on the bargain, having endowed them already with the hypothetical "take-care-of-us" gene. The evolutionary role of the elderly is intertwined with the question of adaptive menopause. Steve Austad sets out the issues in Chapter 9. In those select species like our own with substantial postreproductive life, menopause might have evolved in response to tradeoffs favoring the cessation of one's own reproduction and the channeling of effort into protecting and endowing the reproductive chances of one's offspring, via the kinds of transfers emphasized in Chapters 8. 10, and 11 respectively by Carey and Gruenfelder, Kaplan. and Lee. On the other hand, menopause could be a somewhat accidental outcome of removing species from their stringent evolutionary environments, in our case taking us out of the wild and into our global zoo. A female's initial endowment of egg cells (oocytes) together with the depletion rate of egg cells over time determine the age when no more egg cells remain, which appears to be the age of menopause. The initial endowment and the rate of depletion could have been fine-tuned to match
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the life spans existing over evolutionary time in the wild and then stayed constant as life spans increased with the development of sociality or the adventure of civilization. The population age pyramid of prehistoric men and women is a crucial unknown in this debate. Ethnographers studying the remaining hunter-gatherer populations of today find significant postreproductive survival. Paleodemographers studying skeletons from prehistory estimate survival curves that drop quickly toward zero at ages like 50. Which is the better guide to human experience over evolutionary time? Ronald Lee provides a demographic analysis in Chapter 11. The ethnographic estimates are of debatable relevance, given the altered environments and impacts of contact that make the hunter-gatherers of today not wholly like our ancestors. The paleo-estimates suffer from selection biases in skeletal remains and difficulties in skeletal-age attributions. Carey and Gruenfelder, Kaplan, and Lee appear more comfortable with the ethnographic estimates. Austad is unconvinced. If postreproductive survival were a feature of our evolutionary past, then, as Lee points out, the question of whether the postreproductive elderly were net economic contributors remains distinct from the question of whether they contributed enough to their descendants' reproduction to make menopause an adaptive trait. Much that bears on the debate over adaptive menopause remains uncertain. The age of menopause may have changed, possibly under the influence of genes regulating gene expression. Genetic drift may be significant along with selective pressure. The narrow range of ages of menopause observed across human cultures today could bespeak detailed genetic programming, or it could be a shallow consequence of oocyte depletion. We do not know whether to think primarily about time scales of a hundred thousand years or a million years when we think about evolutionary changes relevant to menopause or longevity. The adaptive status of menopause has medical implications. Austad mentions its bearing on potential side effects of hormone-replacement therapy for postmenopausal women. Randy Nesse and George Williams in their book, Why We Get Sick: The New Science of Darwinian Medicine (1994), argue for the relevance of an adaptive evolutionary perspective in understanding a variety of acute and chronic conditions that now affect us. Questions that arise in this book with regard to death and survival are mirrored in their book with regard to morbidity and health. These parallels will need to be pursued in coming years. Biodemography has not yet come to grips very fully with diverse pathologies and causes of death. As Robert Wallace has often pointed out, medflies, Drosophila. and nematodes are not just dying, with a certain hazard function. Each is dying of something, although we can hardly say of what. Intelligent speculation about commensurable causes of death will be needed to strengthen the analogy with humans. Among humans, causes of death are more specificable among the younger-old than among the oldest-old. It might follow that arguments from general principles should be more relevant to the oldest-old. The thinking I have
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been describing about the elderly in nature, however, is relevant as yet mainly to the younger-old. Theoretical Departures The new empirical findings and broader studies of the elderly in nature are providing a powerful stimulus for new theoretical departures. James Vaupel introduces one of the main new movements in Chapter 2. He shows that automobiles resemble humans, medflies, and nematodes inasmuch as their rising "mortality" rates ultimately also taper with age. Theorists are looking beyond biology to general properties of modes of failure in complex systems. Just as Gauss's normal distribution in statistics arises as a limit under a wide range of basic probability laws, so a tapered modification of the Gompertz (exponential hazard) distribution might be shown to arise as a limiting form of hazard function for organisms with a wide range of detailed mortality dynamics. The trouble so far with complex-system models is that their assumptions can be fairly freely chosen to produce any desired hazard function. We need sharper biological constraints on the assumptions to dispel unpleasant feelings of "ad-hocracy." In the realm of mathematical models for evolutionary processes, the great challenge is for modeling that gives pride of place to the features—absent from Lotka's equation—bearing directly on the evolutionary role of the elderly. I have already mentioned grandparental and multigenerational terms. Two further features are critical—homeostatic feedback and fluctuating environments. The word "homeostasis" has different connotations in demography than it has in medicine and physiology, although the root meaning is the same. A homeostatic process in demography is one that tends to drive the population size or growth rate back toward some equilibrium level through some feedback mechanism. Fertility or survival rates that fall at higher family sizes or population densities and rise at lower ones are examples. In demographic homeostasis, it is the population that is subject to regulation; in medicine, it is the physiological state of the organism or the cell. Demographers view homeostatic models as one of the chief common interests uniting biology and demography (see R.D. Lee, 1987). Simple density-dependent models, formulated in terms of disjoint aggregate carrying capacities, have been treated in the evolutionary literature (see Charlesworth, 1994:54-56, 146-154), but more versatile models with intersecting response functions admitting cyclic as well as convergent solutions now deserve energetic study. For the biodemography of longevity, homeostatic processes that operate at the level of the family or small group are more interesting than population-wide density dependence. Contemporary demography emphasizes tradeoffs between quantity and quality of children, as does Kaplan in Chapter 10. Maximal family sizes are not optimal family sizes, just as with the great tits of Wytham Wood mentioned by Austad and by Partridge in Chapters 9 and 5. Splitting parental
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investment among too many offspring may compromise their long-term chances to command resources through times of scarcity. Fertility is well below its physiological maximum in hunter-gatherers today, and aggregate growth rates over human prehistory seem to have been fine-tuned remarkably close to zero. There may, therefore, have been little marginal cost to foregoing extra births and high marginal returns to parental survival and investment, especially in the face of recurrent scarcity. Calculations done without assuming homeostasis, cited in Chapter 9, have suggested that the help provided by postmenopausal human females to their kin is not sufficient to offset the losses to their own reproductive potential imposed by menopause. It is imperative to revisit such calculations within the context of homeostatic models. Fluctuating environments are another critical component of models for the evolution of senescence. Shripad Tuljapurkar has pioneered this subject and addresses it briefly in Chapter 4. When conditions are variable, there are advantages to the ability to prolong or postpone reproduction, wait out times of hardship, and generate families in times of plenty. This is an effect on reproductive spans. But the idea also fits together neatly with Carey's and Gruenfelder's emphasis in Chapter 8. They stress the protective role of surviving parents and parental ability to confer status on their offspring that translates into claims on resources under conditions of scarcity. These factors probably express themselves mainly in cultural and social arrangements, but those then change the parameters for further biological evolution. There is a fuzzy boundary between factors that can plausibly affect our evolving gene pool and factors that operate through culturally transmitted practices, and there is a potent analogy between genetic evolution and cultural evolution. The evolutionary theory of senescence is itself undergoing rapid evolution. The simple form of mutation-accumulation theory, with its stark force, is giving place to versions with escape clauses, fitter to survive in the face of new empirical evidence. Recent moves in this direction are found in Curtsinger's study of postreproductive mortality rates (unpublished work). As James Vaupel points out in Chapter 2, the mutations at stake in the theory may be rarities. They have to have two quite special properties. They must have specific bad effects on survival at ages unimportant for reproductive fitness. They also have to lack any generalized bad effects on development and viability at earlier ages, so as to accumulate despite natural selection. Genes with both these properties could be exceptional. Mutation accumulation may be just one among several of the stories evolution has to tell. The effect may be most relevant to immediately postreproductive years rather than to extreme ages, and it may imply a relatively short, rather than a nearly endless, list of pathologies and failure modes. Demographers delving into biological literature are apt to be struck by the frequent assumption that populations will be in genetic equilibrium. The physiological mechanisms that are specifically vulnerable to old-age, postreproductive
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decay or failure only come into being or salience at some stage in an organism's evolutionary development and only with the inauguration of some set of background environmental and interactive conditions. Mutations with deleterious specific effects on old-age survival have not been accumulating since forever. I miss in biological writing on the evolution of senescence the comparisons of competing time scales that are so common and so helpful in astronomical writing on the evolution of the physical universe. New theory is giving new emphasis to the historically contingent character of evolutionary change. Mutations produce incremental changes in preexisting physiological structures, gradually suiting them to new functions and purposes. Traits and structure may typically evolve because of one set of advantages and then prove to be preadapted for other advantageous uses. The playing field on which natural selection plays its role is always shifting. James Carey, Catherine Gruenfelder, and Hillard Kaplan discuss this theme in Chapters 8 and 10. To my mind, nutrition presents us with a mystery of preadaption. In work not well-represented in this volume but central to biodemography, Robert Fogel and his colleagues (see Fogel and Costa, 1997) ascribe a substantial portion of the gains in longevity over the last few centuries to improvements in net nutritional status. Fogel sees a long-term process of "technophysio" evolution that produces nongenetic biological change, such as increasing stature and body mass, translated via relationships called "Waaler surfaces" into gains in health and survival. The mystery is that the nutritional "improvements" should be improvements—taking us, as they do, so far outside the range of nutritional experience to which our bodies could have been adapting over evolutionary time. Of course, our recent diets are not unambiguously beneficial, and the point of diminishing returns may be approaching with nutrition or, indeed, with longevity. But Fogel is looking at the broader sweep of long-term trends. From this perspective, we seem to be preadapted to make use of the quantities of calories and varieties of nutrients that civilization has provided. We reach unprecedented average sizes, as well as unprecedented average life spans, perhaps in concert. This phenomenon is easier to understand if evolution has been selecting for plasticity of response to times of feast and times of famine, rather than for optimum vigor under fixed conditions. In Chapter 10, Hillard Kaplan writes: Recently, the concepts of phenotypic plasticity and evolved norms of reaction have become increasingly important in biologists' understanding of adaptation. Under many conditions genotypes are thought to code for mechanisms that translate environmental inputs into phenotypic outputs rather than for an invariant response. . . . The ability to alter allocations to survival, maintenance, reproductive effort, fertility, and parental investment in response to changing net energy intake rates must have been under selection. These ideas accord well with the central role that Caleb Finch assigns to plasticity in the conclusion of this volume.
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I have been describing new empirical results and theoretical departures that seem to me to be shifting the scientific ambience of ideas in the biology of longevity away from their long-standing emphasis on limits and tradeoffs. None of the new developments are so tightly connected with demographic processes in humans that they compel the adoption of different models or forecasts. But if further results and theoretical developments in biology in the next few years reinforce the recent developments described in this volume, then I think that demographers will find themselves far less at ease with models that posit strongly diminishing returns in the near future in progress against old-age mortality. The Promise Of Future Research Many chapters in this book point directly toward the future, to kinds of research that should come into their own in the next few years. Chief among these is quantitative trait locus (QTL) analysis of the kind discussed in Chapter 7 by Thomas Johnson and David Shook. We should learn soon how easy it is, in an organism like the elegantly named nematode worm C. elegans, to find genes or portions of the genome that do have specific effects on old-age survival. It is tempting for demographers who model hazard rates as functions of age to imagine that genes ''know about" ages beyond development and reproduction. In caricature, it is tempting to imagine a set of genes influencing the probability of dying between 50 and 55 and another set influencing the probability of dying between 80 and 85. Results that bolster or undermine this picture will shape the next generation of demographic models. Tests of predictions from the evolutionary theory of senescence are beginning to capitalize on the quantitative specificity permitted by QTL analysis. We should soon be learning, for some laboratory organisms, whether it is commonplace for portions of the genome that correlate positively with net reproduction to correlate negatively with older-age survival rates, as antagonistic pleiotropy posits. We should be learning systematically about the genetic variance in portions of the genome correlated with older-age hazard rates, and whether the variance increases with age in accordance with mutation-accumulation theory. QTL analysis, like most of genetics, focuses on polymorphic genes, genes for which two or more forms or alleles remain present in the population despite the ages-long operation of natural selection. However, most genes responsible for structures that promote longevity are doubtless not polymorphic. They have been selected and become fixed in the population. This is less of a worry for geneticists, who are interested in the persistence of genetic variation in its own right, than for demographers. Inducing mutations in genes that have become fixed may sometimes allow QTL analysis to circumvent this limitation, and any such results will be particularly intriguing to demographers. Necessarily, our speculations about fixed genetic components of programmed aging will continue
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to rely on qualitative comparisons among species, the outcomes of nature's own experiments. But there are enough polymorphic genes to produce nontrivial heritability in human life expectancy at older ages, and QTL analysis of laboratory organisms may guide our understanding of these influences. Central to my own thinking are a pair of questions that I call the "hundreds-thousands-tens-of-thousands" questions. The first question is this: How many genes should I imagine there being whose specific effects on old-age survival are strong enough to be noticeable in a population? The second question is the converse: How many genes should I imagine typically having to act in concert to produce any one noticeable effect on old-age survival in a population? I used to think that the answers to these questions were likely to be at the tens-of-thousands end of the scale of orders of magnitude and that the biodemography of longevity would have to become a sort of statistical mechanics before it could make sense. But I have been strongly impressed by the life of Madame Calment and the data on survival at extreme age discussed by Jim Vaupel and John Wilmoth in Chapters 2 and 3. Humans who make it to 110 years of age appear to have truly better further survival rates than those who make it to 95 or 100. No obvious behavioral and environmental determinants of extreme survival have turned up as yet. It therefore seems as if there could be a relatively small number of bad genes—hundreds, not tens-of-thousands—which one has to not have in order to survive ad extrema. I have already mentioned the hope that research will soon sort out the roles of environmental heterogeneity and individual life-course dynamics in the observed leveling of hazard functions. In the last generation of demographic models, treatment of heterogeneity (the frailty specification) has come first, and life-course dynamics reflected in a changing mix of causes of death by age has come distinctly second. What we learn about the sources of hazard-function leveling in flies and worms is likely to influence the balance of attention in the next generation of demographic models. In most practical demographic work, genetic heterogeneity is lumped together with a range of omitted variables under the rubric of "unobserved heterogeneity." The new technology of genetic mapping, however, holds out promise of converting some of the unobserved heterogeneity to observed predictor variables. We still have very little insight into the proper ways to incorporate such variables into demographic models. Besides its potential value in predictive models of health status, survival, and other outcomes, individual-level genetic information provides a remarkable source for the reconstruction of the history of population groups. Parametric models for aggregate hazard functions are at one end of a continuum of modeling in demography. At the other end of that continuum are multiparameter stochastic risk-factor models that derive estimates of transition rates from detailed national surveys with socioeconomic, behavioral, and medical information. In Chapter 12, Robert Wallace discusses the problems and pros-
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pects associated with collecting genetic information on specific alleles in conjunction with one or more existing national surveys. Until now, there has been a dearth of thinking on how genetic variables are best introduced into sophisticated mortality models. The availability of even a few genetic markers in large health and demographic data sets would be likely, in my view, to generate rapid improvements in the repertory of models. The central technical problem in recent survey-based research on the impact of health services, interventions, and behavioral changes has been the problem of self-selection bias. Approaches that come under the broad heading of "instrumental variable techniques" are enjoying a vogue in econometrics but remain substantively questionable, because convincing instrumental variables, actually satisfying the statistical assumptions of the models, are hardly to be found. Genetic indicators offer the best hope for obtaining usable instrumental variables and so for beginning to sort out the tangle of selection bias and causation. The most urgent need for genetic indicators in large national surveys is for confirmatory studies of causal effects of genes on medical conditions. The epidemiological samples on which searches for genes with causal influences are conducted are almost inevitably subject to grave potential selection biases and a large variety of potential confounding factors. Control groups are difficult to arrange. Population-based surveys rich in socioeconomic and demographic background information are going to be essential to confirm the effects on longevity, disability, dementia, and other health-status outcomes as candidate genes are identified. This research will not be easy, because many hard-to-measure factors like dietary patterns are likely to interact with and overshadow the genetic variables. The essential contribution is not to help in the process of screening for candidate genes but rather to detect spurious candidates and sort out the gene-environment-behavior interactions that must underlie many of the observable effects. The inclusion of biomarkers in nationally representative surveys with control variables for potential confounding factors is an essential step in confirming the true role in longevity and health of isolable genetic influences. The title Biodemography is meant to evoke the idea of a marriage of the disciplines of biology and demography. A mixer of metaphors might reasonably ask whether this marriage is to be grounded in mutual affection and commitment or is to be more in the nature of a practically advantageous but cautious arrangement for cohabitation. For neither partner is this a first union. The theories and findings from each discipline discussed in this book are bound to be somewhat in the nature of stepchildren to the other partner. But stepchildren are increasingly central to families in the world around us. The ideas about longevity put forward from the perspectives of biology and demography in the following pages deserve committed nurturance and promise lasting rewards.
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Representative terms from entire chapter: