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BEYOND SIX BILLION: Forecasting the World's Population 5 Mortality Mortality rates vary tremendously among countries and even within countries. For example, life expectancy at birth1 in Japan reached 81 years in 1998, the highest ever observed for a nation-state. Life expectancy in Malawi, at 39 years, is less than half that in Japan and close to levels observed during the 18th and 19th centuries in Western Europe. Not only does life expectancy vary, but the age pattern of mortality is also sharply different. In such countries as Malawi, the risk of death is high in infancy and early childhood and in old age. In such countries as Japan, the risk of death is high only in old age. However, because the age pattern of mortality tends to vary in a predictable way with the level of life expectancy, the latter represents a good index of overall mortality experience. In what follows, we therefore focus mostly on life expectancy. 1 Life expectancy at birth (often called simply “life expectancy”) is a convenient and frequently used summary measure of mortality conditions at one point in time. For example, if the current life expectancy in 2000 is 50 years, this means that if mortality conditions in 2000 were to remain unchanged indefinitely into the future, babies born in 2000 would live an average of 50 years, although some would die at younger ages and others at much older ages. In other words, life expectancy summarizes mortality conditions in a given year. It is not a prediction of future mortality. Other summary measures are possible, such as the median age at death, the age at which exactly half of a hypothetical cohort of births exposed to particular mortality rates would die, or the modal age at death, the age at which the largest single number of deaths would occur. The median and modal ages at death tend to be higher than life expectancy.
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BEYOND SIX BILLION: Forecasting the World's Population How did life expectancy get to be so high in Japan and other industrial countries, and how much higher can it go? What are the prospects for Malawi and other developing countries to replicate this experience? Could unforeseen developments substantially alter prospects for rising life expectancy and falling mortality? The answers to these questions are the key to properly projecting mortality levels worldwide. We will consider, first, trends in life expectancy over several centuries in industrial countries and over several decades in developing countries. Interpretation of these trends provides clues about how mortality should be projected. Next, we explain how projections have actually been made and assess their accuracy. Then we consider what likely future mortality trends should be reflected in projections. In summarizing the discussion, we also note some possible research directions to help improve projections. CURRENT LEVELS OF LIFE EXPECTANCY Figure 5-1 shows how life expectancy has varied over the last 50 years across six major world regions. (Projections to 2050 are also shown and are considered below.) The magnitude of current variation (in 1990-1995) across regions is striking. Life expectancy ranges from 74 years in industrial countries to 49 years in Sub-Saharan Africa. The other developing regions—Latin America and the Caribbean, Asia, and the Middle East and North Africa—each have life expectancies between 66 and 70. Industrial countries are experiencing the highest life expectancies ever observed. If mortality rates at all ages remain at current levels, more than half of the babies born this year in these countries will live to celebrate their 80th birthdays. Among baby girls, two-thirds will become octogenarians and half will reach age 85. Partly because these survival chances are much higher than the survival experienced by cohorts born 80 years ago, the oldest-old population (those age 80 and older) will grow substantially, even with no further improvements in mortality. In contrast to life expectancy in industrial countries, life expectancy in developing regions is not only lower but also more variable. Across Sub-Saharan African countries, the highest and the lowest life expectancies are almost 40 years apart. This is because mortality is especially high in a few least-developed countries but close to industrial-country levels on some small islands. Although trends since 1950 suggest some narrowing of contrasts across regions, Sub-Saharan Africa remains an outlier. As life expectancy varies across countries, age patterns of mortality also vary, in predictable ways. This is easiest to show from the change over time in one country. Figure 5-2 shows the risk of death at different ages among Swedish females between 1900 (when life expectancy was
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BEYOND SIX BILLION: Forecasting the World's Population FIGURE 5-1 Estimated and projected life expectancy by region, 1950-2050. SOURCE: Data from United Nations (1999). FIGURE 5-2 Age patterns of female mortality and life expectancies, Sweden, 1900-1996. SOURCE: Data from Keyfitz and Flieger (1968), updated from U.N. Demographic Yearbooks.
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BEYOND SIX BILLION: Forecasting the World's Population 54.3 years) and 1996 (when life expectancy reached 81.5 years). Over this century, death was unlikely between the ages of 5 and 50, with the risk for an individual being less than 2 percent per year, although the mortality risk at each age was always slightly higher when life expectancy was low than after it had risen. Mortality risks were always sharply higher after age 60 relative to younger ages. Under age 5, on the other hand, mortality risks were high in 1900 but were much lower by 1996 (although still higher than from ages 5 to 50). MORTALITY TRANSITION Industrial countries attained their high levels of life expectancy through a remarkable two-centuries-long transition from high to low mortality (McKeown and Record, 1962; Flinn, 1974; McKeown, 1976, 1988; Dupaquier, 1979; Chesnais, 1992; Livi-Bacci, 1997, 2000). This transition is continuing, although it may be slowing. At the same time, it is spreading in developing countries, where the process started more recently but is proceeding at an even faster pace. We review the industrial-country experience in some detail, and then consider the transitions in progress in developing countries. Transition in Industrial Countries The transition to higher life expectancies in industrial countries was not entirely smooth and continuous. Regular progress was interrupted by occasional setbacks, periods of stagnation, and sometimes rapid improvement. The transition did not occur simultaneously in all societies or within a society in each social class or stratum. It spread irregularly from one society to another, leaving a trail of sharp contrasts between lower-mortality areas and other areas temporarily trapped within high-mortality regimes. No single path exists through which all countries inexorably pass on the way to lower mortality. Nevertheless, from the historical experience of diverse countries, we can identify common features of the process and distinguish a pretransitional situation and four subsequent stages of transition (Floud et al., 1990; Schofield and Reher, 1991; Horiuchi and Wilmoth, 1998; Livi-Bacci, 2000). Pretransition Life expectancy in prehistoric times was probably in the range of 20 to 30 years, as has been inferred from very slow population growth rates. By 1500 or 1600, when data on mortality first become available, mortality levels were still very high, and life expectancy rarely exceeded 35-40
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BEYOND SIX BILLION: Forecasting the World's Population years—roughly the minimum in developing countries today. Year-to-year mortality would fluctuate sharply, because of the impact of war, the vagaries of weather, recurrent crop failures, and periodic epidemics. These fluctuations, or short cycles, were superimposed on mortality fluctuations of longer duration, covering decades and even centuries. Why mortality would go up and down in these long cycles is not known. One hypothesis is that fluctuations in global weather patterns were responsible. Alternative explanations stress instead the role of fluctuations in the balance and accommodation between infective agents, microbes and vectors, and their human hosts. To the extent that changes in weather patterns affect the diversity and size of infective agents and vectors, these two explanations are complementary (Galloway, 1986). First Stage The first stage of transition, which occurred in Western Europe between 1700 and 1800, saw a reduction in the magnitude and frequency of fluctuations in mortality, but little average improvement in life expectancy. Crisis mortality began to decline, so that year-to-year mortality levels became more constant. The mechanisms behind the reduction of crisis mortality are not entirely known, although it is clear that several factors were involved (Flinn, 1974; McNeill, 1976; Dupaquier, 1979; Wrigley and Schofield, 1981; Livi-Bacci, 1990; Chesnais, 1992). Improvements in this period in cultivation techniques and the storage and transportation of food, as well as an increased range of food crops introduced from the Americas and elsewhere, played a major role. These changes helped reduce the impact of fluctuations in agricultural output on levels of individual consumption, thus stabilizing nutritional status and, more generally, standards of living. Studies indicate that changes in nutritional levels improve immune function, which would reduce year-to-year fluctuations in mortality, although the precise importance of this mechanism is still unclear (Scrimshaw et al., 1968; Martorell and Ho, 1984; Fogel, 1986, 1989, 1990, 1991; Floud et al., 1990; Lunn, 1991; Martorell, 1996; Fogel and Costa, 1997). Improvements in standards of living and nutrition are not the complete explanation, as shown by the unexpectedly high mortality among highly privileged groups, such as the English aristocracy (Hollingsworth, 1977). Reduction in severe epidemics must have played a role. Some historians and epidemiologists believe that improvements in living standards must have been reinforced by increased host resistance and changes in the genetic makeup of agents of infectious diseases. Accommodation between humans and agents of infectious disease occurs continuously. The process of adaptation may have accelerated and changed in character
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BEYOND SIX BILLION: Forecasting the World's Population during this period, as urban concentrations grew and more efficient communications and contacts developed. While mortality fluctuations were reduced, they did not entirely disappear. In addition, the gains in average life expectancy during this first period were not large. The average life span continued to be constrained below 40-45 years (Fogel, 1986, 1989, 1990, 1991; Fogel and Costa, 1997). Second Stage The second stage of mortality transition saw underlying mortality levels finally moving downward. This stage began sometime in the early 19th century in England and in other Northern European countries (McKeown and Record, 1962; McKeown, 1976, 1988). At first reductions in mortality were modest, and reversals did take place. But as the 19th century progressed, the downward trend accelerated and reversals became rare. Life expectancy increased from levels of around 40 years to over 50 by the first decade of the 20th century. Age patterns of mortality decline in this stage varied substantially among countries. In Sweden, for example, the period from 1800 to 1900 corresponds roughly to this stage. In this period, mortality declined most sharply under age 10 and over age 40. In England and Wales in a roughly comparable period, however, rates fell fastest between the ages of 1 and 30, with little improvement in infant mortality or mortality in middle age (Wrigley and Schofield, 1981; Keyfitz and Flieger, 1968). Among the reasons for the mortality declines were better standards of living, improved health behaviors, and various public health measures.2 Standards of living continued to improve from the previous stage, contributing to better nutritional intake and increasing individual resistance to some infectious diseases, particularly such diseases of the respiratory system as influenza, pneumonia, bronchitis, and respiratory tuberculosis (McKeown and Record, 1962; McKeown, 1976, 1988; Fogel, 1986, 2 Improved medical knowledge and public health measures alone could not have been responsible for such large improvements. The germ theory of disease was not accepted until the last three decades of the 19th century (Evans, 1987), and its widespread application and the generalized establishment of associated advances in prevention (immunization) and cure (new drugs), as well as the most important innovations in surgical techniques (antiseptic procedures), occurred after 1900, not before (although vaccination or inoculation against smallpox probably had substantial effects on mortality under age 5 early in the 19th century). Furthermore, the most significant advances in drug-based therapies, embodied in the introduction of sulfa, penicillin, and other antibiotics, took place after 1935.
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BEYOND SIX BILLION: Forecasting the World's Population 1989, 1990, 1991; Komlos, 1989; Floud et al., 1990; Fogel and Costa, 1997). Several public health interventions and movements emerged in the second half of the 19th century. Although based on erroneous or only partially correct theories and paradigms, they did reduce exposure to infectious diseases, particularly water-borne and food-borne ones (Leavitt, 1982; Rosen, 1993). Reduced exposure also improved nutritional status, which is a function not only of dietary intake but also of physiological expenditures to fight disease (Cipolla, 1981; Evans, 1987; Szreter, 1988; Preston and Haines, 1991; Guha, 1993).3 Preventive measures, particularly the practice of inoculation or vaccination against smallpox, a very widespread disease, had a substantial impact on mortality (Razzell, 1965, 1993). These effects were only partly countered by rising levels of urbanization, which facilitated disease transmission (Woods and Woodward, 1984). Third Stage The third stage of the transition saw an acceleration of mortality decline, with life expectancy rising by about one-third of a year per year, propelled by a new set of factors. This stage began with the institutional acceptance of the germ theory of disease around 1900. Knowledge about infectious diseases led to measures to reduce exposure and transmission. Simple techniques such as hand washing and better personal hygiene reduced mortality further. In addition, the development of drug-based therapies in the 1930s led to unparalleled increases in the individual's capacity to resist the onslaught of infections. During this period, infant mortality decreased sharply, and survival of younger adults improved substantially (Preston, 1976; Woods and Woodward, 1984; Preston and Haines, 1991; Vallin, 1991). Mortality reductions were particularly pronounced under the age of 50. Figure 5-3 illustrates this with percentage reductions in age-specific female mortality in Sweden in the period 1900-1960. The reductions were close to 90 percent under age 35, and still above 65 percent up to age 50. Such reductions were remarkably consistent from population to population. Mortality declines above age 60, however, were only modest. Reductions in mortality proceeded in a fairly regular manner during this period, despite the last huge fluctuation, caused by the Spanish influ 3 For example, water purification techniques limited exposure to such intestinal infections as dysentery, typhoid, and cholera, reducing nutritional expenditure and improving nutritional status. Systems to dispose of waste and excreta and quarantines and other controls over geographic movement of populations had similar effects.
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BEYOND SIX BILLION: Forecasting the World's Population FIGURE 5-3 Percentage declines in mortality among females by age, for two transition stages, Sweden, 1900-1996. SOURCE: Data from Keyfitz and Flieger (1968), updated from U.N. Demographic Yearbooks. enza pandemic in 1918-1919. Two world wars and the depression of the 1930s caused only minor fluctuations by comparison (except among combatants and certain targeted subpopulations). Fourth Stage Mortality reductions are continuing in industrial countries, and a fourth stage of transition can be identified beginning around 1960. In percentage terms, mortality has continued to decline rapidly, especially at ages under 40. Figure 5-3 shows that the decline at younger ages in Sweden in 1960-1996, although not as extreme in percentage terms as earlier in the century, has still been substantial. However, mortality is now so low at younger ages in Sweden and similar countries that further gains at these ages can have only a minor impact on life expectancies. At current death rates in a typical industrial country, the chance of reaching age 65 is more than 90 percent for females and more than 80 percent for males. In this stage of transition, life expectancy gains depend mainly on reduced
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BEYOND SIX BILLION: Forecasting the World's Population mortality over age 65. As Figure 5-3 shows for Sweden, few gains were made in this age range during the third stage of transition, but percentage gains rose appreciably after 1960. Large differences have opened up in this stage between the mortality risks of males and females at young adult ages, partly due to excess deaths among young males from violence and motor vehicle crashes. Young males are the one adult group, other than the elderly, among whom substantial reductions in mortality might still be possible. Among the elderly in industrial countries, progress against chronic disease, especially cardiovascular diseases but also cerebrovascular diseases and some cancers, is contributing significantly to increased life expectancy (Horiuchi, 1997). Early detection and prevention of chronic diseases, improvements in surgical procedures, and refinements of medical therapies are all fostering longer survival and better health status among the elderly.4 Synthesis For the long time span involved in the mortality transition, reliable vital-registration data on mortality are not available. However, estimates of life expectancy for England and Wales for 5-year periods from the mid-16th century to the late 19th century have been developed by a series of historical demographic methods (Wrigley and Schofield, 1981). These estimates are combined with registration-based estimates from 1841 onward and are shown in Figure 5-4. We also plot life expectancies for 5-year periods from vital-registration data for Sweden from the mid-18th century onward as an example of a quantitatively but not qualitatively different trajectory. The graph illustrates various characteristics already noted of the mortality transition in industrial countries. This transition is shown to have taken, so far, almost three centuries. Pretransitional life expectancy is seen to fluctuate considerably, even when calculated for 5-year periods. The first stage reduced this variability but did not produce substantial improvements in level of life expectancy, which was somewhat below 40 years at the start of this stage and still close to 40 years at the end. Improvements came in the 19th century, with life expectancy rising close to 53 years by the end of the century. Improvements accelerated in the third stage, when life expectancy rose further to around 70 years. Finally, in the 4 Earlier research in the medical sciences and recent evidence and interpretation (Barker, 1998) suggest that some of these changes were triggered by improved conditions experienced by these cohorts in utero and during infancy and childhood.
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BEYOND SIX BILLION: Forecasting the World's Population FIGURE 5-4 Historical trends in life expectancy, England and Wales and Sweden, 1540-1996. SOURCE: Data from Wrigley and Schofield (1981) and Keyfitz and Flieger (1968), updated from U.N. Demographic Yearbooks. last observed stage of transition, increases in life expectancy are shown to occur more slowly as very high levels are reached. Life expectancy improved at a fairly steady pace within stages (with some reversals in the early stages) but was discontinuous from one stage to the next. Mortality changes in the first and second stages were largely due to slow political and institutional changes, gradual economic transformation, and limited behavioral and clinical developments. In contrast, the changes experienced in the third stage of the transition, beginning around 1900, were due largely to the rapid and unpredictable expansion of medical knowledge and associated techniques and the diffusion of this knowledge to the public, resulting in the adoption of health-promoting behaviors at the household level. The fourth stage, with reductions in old age cardiovascular mortality, reflects improvements in diagnosis and drug-based therapies, reinforced by behavioral changes, particularly the reduced prevalence of smoking. Transition in Developing Countries By and large, the mortality transition in developing countries has been driven by the same factors as in industrial countries but has proceeded much faster, with unprecedentedly rapid gains in life expectancy. The earliest transitions in developing countries began in earnest in the 1920s and 1930s. Because of substantial improvements in China, the great
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BEYOND SIX BILLION: Forecasting the World's Population est overall gains were made in the 1960s. The 1960s and 1970s saw large gains in other Asian countries and in Latin America, and the 1970s and early 1980s saw improved gains in Africa. For some developing countries, the stages of transition have been compressed within the last half-century, while other countries are still working their way through earlier transition stages. The key factors in reducing mortality have included the diffusion of health care knowledge, the increased ability to control vectors of infectious diseases, the widespread introduction of immunization measures and drug-based therapies, and perhaps large reductions in fertility5 (Meegama, 1967; Arriaga and Davis, 1969; Preston, 1980; Mosley, 1984; Hill and Pebley, 1989; Frenk et al., 1991). The development of effective governments capable of mobilizing the population and resources needed have made it possible to capitalize on the potential for improvement offered by these factors. Developing regions and countries do differ substantially in the degree to which they have progressed through the transition. For present purposes, countries can be divided into three groups based on the levels of life expectancy they reached by 1990-1995. Early Transitions The first group of countries includes all those with current life expectancy levels of 70 years or higher. These countries started transition early, before World War II. By the early 1950s, most already had life expectancies of 55 years or higher, equivalent to the start of the third stage of mortality transition in industrial countries. They may now be considered in the fourth stage of transition, although in this stage they have generally not progressed quite as far as the industrial countries. This varied group of countries includes Israel, Singapore, and Sri Lanka, as well as much but not all of Latin America and the Caribbean. Argentina, Chile, Costa Rica, Cuba, and Uruguay achieved early improvements in living standards and developed strong nation-states with relatively efficient central administrations. They also took advantage of foreign investment to erect infrastructure, reducing disease exposure directly through eradication programs or indirectly through water purification 5 Although the exact direction of causality is not well established and the magnitude of the relation has been routinely questioned, it is possible that at least part of the most recent mortality decline in developing countries is associated with fertility decline. As fertility begins a rapid descent, the proportion of infants born at high risk diminishes, contributing to increases in life expectancy.
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BEYOND SIX BILLION: Forecasting the World's Population with the steady increases of the previous decades replaced, for South Africa, by a fall of 13 years, in World Bank projections, and of 14 years, in U.N. projections, before an upward trend is reestablished. Both agencies forecast even larger reductions in Zimbabwe of either 14 or 16 years. These reductions would appear even larger if assessed against the life expectancy levels that could have been attained if AIDS deaths could have been entirely avoided. The differences between the two agencies reflect the inconclusiveness of existing data, even regarding current levels of life expectancy, but the agencies agree that reductions will wipe out the gains of several decades. As these examples also illustrate, the bulk of the mortality impact of HIV/AIDS lies in the future. HIV/AIDS has spread to most countries of Sub-Saharan Africa, where prevalence levels now average 8 percent among adults and range as high as 30 percent. It mostly affects mortality among young children and young adults, two age segments with the most influence on levels of life expectancy. The epidemic could be responsible for the loss of a decade or more of life expectancy in the most affected subregions of Sub-Saharan Africa. However, this is itself a projection, subject to considerable uncertainty (Stoto, 1993). The dimensions of the epidemic are not known with much precision, and the ultimate effectiveness of any societal response can only be guessed at. Equally uncertain is the extent to which the epidemic will establish itself in other regions of the world, in countries at later stages of mortality transition, from India and Thailand to Central America and Brazil. Recent prevalence estimates suggest that the epidemic might still become demographically significant in India and Southeast Asia but is unlikely to make rapid progress elsewhere (United Nations, 1998; see also National Research Council, 1996). Projecting Mortality Crises Whether the types of events that produce mortality crises can be predicted or not is beyond the scope of this report; this depends on research in other fields, such as biology and medicine, politics, climatology, environmental science, and even astronomy. Even when such events are recognized, the degree of their mortality impact can be difficult to assess. For instance, the impact of the HIV/ AIDS epidemic depends on its special character. If the incubation period were shorter, infections would not spread as fast, because those infected would be more quickly identified. Similarly, the impact of war is variable The recovery from such events is also unpredictable. Life expectancy in China recovered quickly from devastating famine. Much more halting
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BEYOND SIX BILLION: Forecasting the World's Population recovery is predicted from the HIV/AIDS epidemic, but these predictions could be off substantially in either direction. Conventional projections can be thought of as incorporating the effects of unforeseeable events of small to moderate impact, which essentially form part of the average performance that is the basis of forecasting. However, they do not take into account events of major impact and obviously cannot incorporate the possibility of qualitatively new mortality crises. The best that can be done is to update forecasts often, certainly soon after such events are recognized and their potential impact can be assessed. CONCLUSIONS Transitions Mortality has been in a centuries-long transition from high to low levels. In industrial countries, the transition has progressed, since the 1700s, through four stages. First, as epidemics were reduced and food supply became more stable, fluctuations in mortality became smaller and less frequent. Second, as public health interventions and preventive measures took hold and standards of living continued to climb, levels of mortality began to decline, although somewhat irregularly. Third, with the acceptance of the germ theory of disease, better controls on infectious disease, and development of new drugs, large reductions in mortality took place among infants and among adults under age 50. Fourth, with continuing medical developments, child and young adult mortality have been brought to low levels, while gains in survival at older ages have begun to be made at a steady pace. The parallel transitions in developing countries have been much more recent and more rapid. For much of Latin America and the Caribbean, life expectancy has risen above 70 years, roughly the lower boundary for the fourth transition stage for industrial countries. A larger group of developing countries started transitions only after World War II and now have life expectancies between 55 and 70 years, similar to the third stage for industrial countries. These transitions have benefited from the diffusion of health care knowledge and its effective application. Some countries remain that have not reached the third stage of transition, and that have therefore still not realized many of the possible gains from medical knowledge. In some of these cases, especially in Sub-Saharan Africa, mortality is actually rising as a result of the HIV/AIDS epidemic.
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BEYOND SIX BILLION: Forecasting the World's Population Projections These transitional stages represent generalizations from demographic history, not an inexorable process through which countries must pass. Nevertheless, building on this historical record, as well as on the fact that mortality trends have become quite regular and gradual, forecasters have been able to project continuing improvements in life expectancy with reasonable, although far from perfect, accuracy. Discounting the error resulting from misestimates of initial levels of life expectancy, projections of the trend in life expectancy for the world as a whole over the last quarter-century have been quite accurate. Projections for countries, in contrast, have generally been biased downward, because forecasters somewhat underestimated the speed of transitions in developing regions and assumed that improvements would slow in industrial regions more than they have. Such errors have had only small effects on projected population, although larger effects are visible for particular age groups, especially the elderly. For one region, however, forecasters have been wrong in the opposite direction. They expected greater improvement in life expectancy in Sub-Saharan Africa than has actually taken place. They did not foresee the spread of HIV/AIDS or the uneven progress in developing health systems in the region. Future Trends Projections of future mortality trends can continue to build on the record of rising life expectancies. There is in fact no theoretical or empirical basis for believing that life expectancy will reach some absolute limit in the foreseeable future. It is true that, in industrial countries, mortality is now so low among children and adults other than the elderly that further gains at these ages (except potentially among young adult males) are likely to be slow and quite limited. However, gains in survival continue to be made among the elderly. Given the likelihood of future medical advances and the possibility of breakthroughs, these gains should continue and translate into steady, although relatively slow, gains in life expectancy, provided societies can preserve the conditions essential for such advances. Mortality projections would probably therefore be improved, and the downward bias in longer projections partly remedied, if no upper limit on life expectancy were imposed. Future gains in life expectancy will undoubtedly be interrupted by unexpected events, similar to the worldwide influenza pandemic of 1918-1919 or the more recent civil conflicts in Rwanda and Liberia. Demogra
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BEYOND SIX BILLION: Forecasting the World's Population phers do not have the tools to predict such events and cannot therefore incorporate them in forecasts. This shortcoming is mitigated by three considerations. First, only a relatively small proportion of such events permanently alters the rising trend in life expectancy. Even the loss of 30 million people in China's famine of 1957-1961 does not seem to have permanently deflected the trajectory of rising life expectancy in China. Second, some such events are part of the historical record that forms the basis for projections, which can therefore be assumed to incorporate the effects of unexpected events of more moderate impact. Third, in the long view, the mortality impact of such events is being gradually mitigated by the development of national and international systems to cope with disasters. Nevertheless, some unexpected mortality crises are very likely to occur in unidentifiable countries, interrupting the upward march of life expectancy and shifting mortality trends to new trajectories. Research Priorities Like fertility projections, mortality projections would improve with more accurate demographic data. Levels of mortality and patterns of death by age are not known with much precision for most developing countries. Forecasters generally apply model age patterns of mortality, and while these probably fit reasonably well, their applicability at older ages and at higher levels of life expectancy is quite uncertain. For the majority of countries of the world, little is known with any certainty about deaths at adult ages and about the distribution of deaths by cause. Improvements in such data are neither simple nor quick, but without them, projections will continue to depend on uncertain mortality baselines and imperfect understanding of mortality patterns. Experimentation is advisable with alternative procedures for projecting mortality. At high life expectancy levels, one possibility is to investigate projecting age-specific mortality rates. By applying time-series methods when possible and focusing on the older ages at which most deaths take place, this approach could be a feasible and possibly superior alternative to projecting life expectancy. It would depend on better understanding of the determinants of mortality at older ages, particularly at age 80 and older. Significant progress in this area would require that demographers become better informed about and associate themselves with biomedical research, particularly on the biology of aging (see, e.g., National Research Council, 1997). A second possibility is projecting mortality from risk profiles related to causes of death in a population. This is not a straightforward matter, as past difficulties with projecting causes of death have demonstrated (e.g., Stoto and Durch, 1993). Reliable information on risk profiles and their
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BEYOND SIX BILLION: Forecasting the World's Population relationship to overall mortality at various ages is often lacking. Obtaining this information depends on further epidemiological and medical research. This approach also requires projecting risk profiles into the future, which may involve the development of structural equation models relating these profiles to broader socioeconomic conditions. Research in these two areas would probably also be useful in improving mortality projections at low life expectancy levels. Considerably more critical for particular developing countries, however, would be research to increase understanding and predictability of the course and demographic consequences of the HIV/AIDS epidemic. Although much has been learned about the epidemic in the last decade or so, prevalence estimates for affected areas continue to be drawn from limited data, and the long-term prognoses for the size of the epidemic and its demographic impact still rest on unverified assumptions. Other health, environmental, and political crises also deserve more attention, since they can interrupt the otherwise ineluctable gains in life expectancies. More basic is broader demographic research to distinguish patterns and trends at different stages of the mortality transition. We already know that the mortality experience of developing countries follows quite well the mortality experience of industrial countries. But there are important time lags and variations in the pace of improvement. The specific time path of mortality decline in one country may depend, for example, on its level of development, its literacy rate, and the capabilities of its government. Accurate projections require that we understand these dependencies better. At a more speculative level, perhaps research on cohort effects in mortality might eventually help improve mortality projections. Mortality rates vary not only from period to period but also across cohorts. Period effects are generally larger in magnitude than cohort effects and are captured by levels of current life expectancy. But cohort effects, reflecting individual life histories, also exist. If one were able to identify specific events or sets of conditions to which cohorts have been exposed in the past, it is at least feasible to associate them with specific mortality risks in the future. Such assessments of cohort influences may add an additional measure of accuracy to projections. A final area for research concerns the effects of public policy. Public expenditures on biomedical research, on the delivery of health services, and on campaigns to promote healthier lifestyles will be important in future gains in life expectancy. Will such expenditures be constrained, and will this slow mortality reductions, especially at older ages? Translating expenditures into mortality reductions is today a highly speculative exercise, and much more research would be needed before forecasters could take this into account.
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Representative terms from entire chapter: