Future Directions for the Demography of Aging Proceedings of a Workshop (2018) / Chapter Skim
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11 The Demography of Aging in Low- and Middle-Income Countries: Chronological versus Functional Perspectives - Nikkil Sudharsanan and David E. Bloom
11 The Demography of Aging in Low- and Middle-Income Countries: Chronological versus Functional Perspectives - Nikkil Sudharsanan and David E. Bloom
Pages 309-338
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while simultaneously stressing health and pension systems (Bongaarts, 2004)
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Researchers, governments, and global policy makers focus on indicators, such as the share of the population above the age of 60 or 70, with the idea that these chronological measures indicate the size of the dependent population. Within this view, 10 percent growth in the share of indi iduals v over 60 is thought to represent 10 percent growth in the dependent population, resulting in a corresponding increase in the resources required to sup
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(2008) compared chronological measures of population aging with measures based on the population share with a remaining life expectancy of 15 years and found that the magnitude of population aging is smaller when also considering changing patterns of longevity.
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They concluded that mortality reductions across cohorts drove aging in more-developed countries, while fertility declines played a larger role in less-developed countries. Our main goal in this section is to expand on Preston and Stokes' work by estimating the historic sources of population aging between 1970 and 2015 and looking forward to 2050 by countryincome groups and regions of the world.
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Specifically, we take advantage of the 5-year data intervals in UN WPP to express the share of the population above the age of 65 at any time t as a function of the population counts at time t−5, the mortality experience between times t−5 and t (estimated based on the 5-year life tables) , and the age-specific fertility rates between times t−5 and t.
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Panel B of Table 11-1 presents the same set of results, this time for regions rather than income groups. As with income groups, the magnitude of historical population aging differed substantially across regions, with the largest absolute growth in Europe (7.2%)
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Fertility declines had the largest influence in Asia and Latin America, explaining about 15 percent of population aging, while mortality improvements were most important in Northern America and Oceania (20.5% for Northern America and 23.1% for Oceania)
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The aging of large cohorts is, once again, by far the largest contributor to future population aging, accounting for more than 90 percent of aging in every region except Africa, where it still accounts for 83 percent. Mortality reductions are expected to have a much smaller influence, explaining only 4–10 percent of growth in the share of older individuals across regions.
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Using historical and projected information on population aging, gross domestic product (GDP) per capita, and national health expenditure per capita, we assess whether aging in LMICs will actually occur at lower overall levels of per capita income and health expenditure relative to the historical experience of HICs.
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The solid points represent observed data points, while the crosses represent projected data points based on historic GDP per capita growth rates and expected future shares of older individuals. Because LICs are not expected to reach levels of population aging comparable to MICs and HICs by 2040, the main comparison in the figure is between MICs and HICs.
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Conclusions Despite the widespread concern that LMICs are growing old before rich, we do not find evidence to support this view. Our results suggest that MICs will actually have higher levels of both GDP per capita and health expenditures per capita when they reach shares of older individuals comparable to the recent experiences of HICs.
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This discrepancy between chronological age and functional ability can also affect cross-sectional interpretations of age composition across countries. For example, if two countries have similar shares of the population above age 65 but highly disparate levels of disability, chronological measures would equate the two populations when in reality one has a much larger dependent subpopulation.
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for any given chronological age, how much variation exists in functional age across countries; and (2) for a given chronological age, is functional age within countries improving over time (e.g., is 60 really the new 50, or is it the new 70)
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, measuring indi viduals' ability to perform essential self-care tasks such as bathing, dressing, and eating independently. ADL limitations are appealing as a measure of functional age because they capture individuals' ability to function independently.
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To answer this question, we would ideally compare functional age across several birth cohorts. Unfortunately, the HRS sister studies are relatively recent, and few have collected data long enough to permit comparisons across multiple birth cohorts.
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Using the Sullivan method, we compared cross-country differences in two measures of disability duration: the expected number of years an individual will spend disabled at age 60 and the fraction of remaining life expectancy at age 60 spent disabled. A major limitation of ADL measures is that they are self-reported.
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Surprisingly, we do not observe a clear country-income gradient in the prevalence of ADL disability. At any given age, substantial heterogeneity exists across countries, with richer countries such as Spain and the United States often underperforming poorer countries such as Indonesia and South Africa.
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Overall, these results reveal pronounced and consistent variation in functional age at any given chronological age, with differences between the best- and worst-performing countries ranging from 10 to 20 years across chronological ages.
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These results for Indonesia show a pattern similar to those for Mexico: at many ages, levels of disability are higher in 2014 than in 2000. These findings bring into question the stability of disability over time in Mexico and Indonesia and suggest a substantial expansion of morbidity, even as life expectancy continues to increase in both countries (United Nations Department of Economic and Social Affairs, 2017)
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After accounting for differences in old-age mortality, our conclusions about the relative levels of functional ability across countries remain mostly unchanged. For example, Mexican adults have the highest levels of disability duration, both in absolute numbers of years lived with disability and as a share of overall life expectancy.
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across Countries Share Share Country e60 e60 Disabled e60 Healthy Disabled Healthy China 20.7 4.4 16.3 0.21 0.79 Costa Rica 25.0 4.6 20.3 0.19 0.81 Indonesia 17.8 2.8 15.0 0.15 0.85 Mexico 23.7 6.8 16.9 0.29 0.71 South Africa 18.6 2.3 16.3 0.12 0.88 Netherlands 25.4 3.4 22.0 0.13 0.87 Spain 27.1 6.7 20.4 0.25 0.75 USA 24.7 4.9 19.7 0.20 0.80 to have the largest shares of overall life expectancy spent disabled. If we assume that countries with lower life expectancies will ultimately resemble the higher life-expectancy countries, our results suggest an almost systematic expansion of morbidity as life expectancy increases.
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Differences in the age-specific prevalence of disability at any given chronological age are stark and do not attenuate at older ages. In particular, Mexican and Chinese adults have much higher levels of disability compared with adults in other countries, a difference that translates to a 10- to 20-year gap in functional age relative to the best-performing countries.
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However, we do not find any support for this belief; indeed, our second major finding is that as MICs undergo population aging, they may actually have higher levels of national wealth compared with the historical experience of HICs. Third, large cross-national differences exist in functional ability, with countries such as Mexico and China having a functional age that is consistently 10 to 20 years higher than best-performing countries such as the Netherlands at any given chronological age.
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Research integrating biological insights into population science has become more feasible due to efforts to collect biomarkers in large-scale population surveys, such as the HRS sister studies (Rehkopf et al., 2016)
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However, other household and institutional considerations will determine whether healthy aging leads to growth or is offset by greater expenditure on older individuals. At the household level, postponing morbidity and increasing life expectancy could lead to greater household income through the direct effect of older individuals being more productive and the indirect effects on other members of the household.
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HRS Sister Studies The HRS sister studies have several important benefits, including a longitudinal study design; rich social, health, and economic information on individuals and households; and harmonization that facilitates crosscountry comparisons. The surveys' panel design is extremely well suited for studying aging, allowing researchers to track dynamic changes in aging and use individual-level variation to identify the determinants and consequences of functional changes with age.
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Thus, analyses that take advantage of both the large sample sizes of the National Sample Surveys and the richer detail of the HRS sister surveys will likely yield more compelling findings. Demographic and Health Surveys (DHS)
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For example, many countries in South America, Africa, and Central Asia do not have HRS-type sister studies. Building and developing new surveys for these regions will be critical for developing a more comprehensive global aging knowledge base.
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Vienna Yearbook of Population Research, 14, 41–65. doi: 10.1553/populationyearbook2016s041.
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Experimental Gerontology, 64, 70–77. United Nations Department of Economic and Social Affairs.
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