Mortality Crossover Research Paper

1. Empirical Evidence

One of the most widely noted mortality crossovers is that for African Americans and whites in the United States. Throughout the twentieth century, mortality estimates based on vital statistics and census data have consistently shown black death rates to exceed white rates until some age above the mid-seventies at which point white rates exceed black age-specific death rates. The greatest relative disadvantage for African Americans is observed in middle age, and the age at which the two rates cross has increased over time. Investigations of cause-specific mortality have revealed a similar crossover in cause-specific death rates, although the relative differentials by age and the age at which a crossover occurs appear to vary by cause (Elo and Preston 1997, Manton et al. 1979, Manton and Stallard 1997).

Evidence from linked data sources, where information for deaths and population at risk comes from a single source, also suggests a racial crossover in mortality. Kestenbaum (1992) has conducted a careful analysis of mortality based on Medicare and Social Security data for African and white Americans at ages 85 and above. Black mortality exceeded or was the same as white mortality up to age 87 for males and up to age 88 for females, at which ages the rates crossed over. Similarly, mortality estimates based on the National Longitudinal Mortality Study and small-scale, longitudinal data sources show a crossover in black and white death rates at the oldest ages (Elo and Preston 1997).

A mortality crossover is also observed for Hispanics and non-Hispanic whites in the United States, but at a younger age than for blacks and whites. Hispanic Americans have higher mortality than non-Hispanic whites at younger ages and lower mortality after about age 40–45 with the proportionate gap between Hispanic and white rates increasing with age. At least some of the Hispanic advantage appears to be due to the exceptionally low mortality of the foreign-born. Hispanic populations in Latin America are also known for having unusually low death rates at older ages relative to their level of mortality at younger ages (Elo and Preston 1997, Dechter and Preston 1991).

Empirically observed mortality crossovers are not limited to the United States. Coale and Kisker (1986) compared death rates in selected life tables for developed and developing countries with a similar life expectancy at age five. In each pair of life tables considered, death rates at younger ages in the developing country exceeded those of the developed country, while at the oldest ages the relative differentials were reversed. Based on indicators of data quality, the authors concluded that the observed crossovers were due to poor data quality at the oldest ages. Nam et al. (1978) investigated mortality crossovers by comparing life table death rates for pairs of national populations where one population was considered low and the other high income. Of the 1,035 pairs of mortality curves examined, in only 16 percent of the original pairs were the authors’ findings consistent with their original hypothesis with lower income population having higher mortality at younger ages but lower mortality at older ages.

More recently, Manton and Vaupel (1995) have suggested that a crossover in death rates at the very oldest ages also occurs between white Americans and populations in England, France, Sweden, and Japan. In Japan and the European countries, life expectancy at birth is notably higher than in the United States. Death rates, however, begin to converge around age 65, and above age 80 the US rates appear to fall below those of the European countries and Japan.

2. Proposed Explanations

Most observers attribute mortality crossovers either to selective survival and unobserved heterogeneity or to poor data quality at the oldest ages.

2.1 Selective Survival And Unobserved Heterogeneity

Manton and Vaupel have been at the forefront of advancing theories involving selective survival and unobserved heterogeneity (Vaupel et al. 1979, Manton and Stallard 1981, Manton et al. 1979). In a heterogeneous population where individuals have different susceptibilities to mortality that are fixed at birth, frailer members of a cohort die at younger ages leaving a more robust group of survivors at successively older ages. If we further consider two population subgroups that have the same distribution of frailty, but one is subject to more adverse conditions in early life, then its frailest members are eliminated more quickly than among the advantaged group. If such selection is appropriately balanced, it is theoretically possible that a crossover of the mortality curves for the two population subgroups is observed at some advanced age (Manton et al. 1979, Olshansky 1995).

Although the above mechanism is feasible, it requires that genetic endowments for longevity are fixed at birth and remain constant over the lifespan. However, lifestyle and environmental factors are likely to influence individual as well as population longevity. To address this possibility, Manton and his colleagues have extended the selection hypothesis to acknowledge the potential impact of environmental factors on differential rates of population aging (Manton et al. 1979). The authors have sought support for this hypothesis from epidemiological evidence on disease progression among whites, Hispanics, and African Americans (Manton and Stallard 1997).

The crossover in black and white death rates at older ages has provided much of the empirical support for the mortality selection and survival of the fittest explanations. Given large socioeconomic differentials between whites and blacks and adverse conditions African Americans experienced earlier this century, it is conceivable that selective survival has been more pronounced for blacks than whites. Evidence from other populations, however, suggests that cohorts who experienced unfavorable conditions in early life also tend to experience elevated mortality at older ages (Elo and Preston 1992, Mosley and Gray 1993).

2.2 Poor Quality Data And Age Misreporting

The second explanation for mortality crossovers is that they are produced by poor data quality. It is hypothesized that age misreporting in death statistics and/or censuses biases mortality estimates downwards at the oldest ages. Age overstatement has been considered the most common form of age misreporting, although other patterns have also been recorded (Ewbank 1981, Preston et al. 1999). Coale and Kisker (1986) concluded that the mortality crossovers they observed between developed and developing country populations were caused by poor data quality. Age misreporting has also been implicated in the black/white mortality crossover in the United States and the low mortality among Hispanics at older ages. Other potential explanations for the low mortality of Hispanics include the positive selection of migrants on such characteristics as healthiness and the difficulty of following the foreign-born in US death records (Elo and Preston 1997).

Preston et al. (1999) have shown that various patterns of age misreporting—net age overstatement, net age understatement, and symmetric age misreporting—bias mortality estimates downwards at the oldest ages. The downward bias is produced by all methods of mortality estimation the authors considered: conventional methods derived from vital statistics and censuses; longitudinal studies where age is identified at baseline; variable-r procedures based on age distribution of the population; variable-r procedures based on age distribution of deaths; and extinct generation methods. Thus, it is not unreasonable to propose that age misreporting at the oldest ages has led to downwardly biased death rates at the oldest ages and spurious mortality crossovers.

The most extensive studies of the potential impact of age misreporting on mortality crossovers pertain to the racial crossover in the Unites States. There is a general agreement that age misreporting has seriously biased African American death rates downwards at the oldest ages. The first study to document inconsistencies in age reporting for African Americans and whites in vital statistics and census data was the 1960 Matched Records study, which linked death certificates registered in May to August in 1960 to the 1960 Census of Population. For less than half of the nonwhite male and female matched cases was the age in the two sources identical. Age reporting was far better for whites. After the data were corrected for age misreporting, the racial crossover in mortality moved from the age interval 75 to 79 to the last open-ended age interval, 85 and older (Kitagawa and Hauser 1973).

Two recent matched-record studies of death certificates from the 1980s for whites and African Americans to early census records for these same individuals when they were children or adolescents continue to show substantial age misreporting for African Americans in death statistics at the oldest ages, but minimal problems for whites. Thus, conventionally constructed death rates from vital statistics and census data for African Americans continue to be seriously understated at the oldest ages. In contrast, death rates for whites do not show a systematic bias. A comparison of mortality rates for blacks and whites based on corrected data continue to reveal a mortality crossover for males in the age interval 95 and for females at ages 90–94 (Preston et al. 1996, Hill et al. 2000). Age-specific death rates for this comparison are, however, based on somewhat unconventional variable-r procedures and on a very small number of deaths for African Americans at the oldest ages. They do not provide conclusive evidence of whether the racial crossover in mortality is real.

The affirmation of the reliability of mortality estimates for whites in turn lends support to the findings by Manton and Vaupel that white mortality in the United States at the oldest ages is lower than in Japan and Europe. These findings raise compelling questions about the possible underlying factors. The authors suggest several possibilities, including differences in health care, mortality selection, and the potential role of immigration among others. It is unlikely that a single explanation will account for this finding or the convergence of death rates at the oldest ages under all circumstances. To gain greater insights into the variability in the aging process, it is important to explain not only those instances where crossovers occur, but also when they have failed to materialize.

Bibliography:

1. Coale A J, Kisker E E 1986 Mortality crossover: Reality or bad data? Population Studies–Journal of Demography 40: 389–401
2. Dechter A, Preston S H 1991 Age misreporting and its effects on adult mortality estimates in Latin America. Population Bulletin of the United Nations 31/32: 1–17
3. Elo I T, Preston S H 1992 Effects of early-life conditions on adult mortality: A review. Population Index 58(2): 186–212
4. Elo I T, Preston S H 1997 Racial and ethnic differences in mortality at older ages. In: Linda G, Soldo M, Soldo B J (eds.) Racial and Ethnic Differences in Health of Older Americans. National Academy Press, Washington, DC, pp. 10–42
5. Ewbank D C 1981 Age Misreporting and Age Selective Under enumeration: Sources, Patterns, and Consequences for Demographic Analysis. Committee on Population and Demography, Report No. 4. National Academy Press, Washington, DC
6. Hill M E, Preston S H, Rosenwaike I 2000 Age reporting among white Americans aged 85 : Results of a record linkage study. Demography 37: 175–86
7. Kestenbaum B 1992 A description of the extreme aged population based on improved Medicare enrollment data. Demography 29: 565–80
8. Kitagawa E M, Hauser P M 1973 Differential Mortality in the United State: A Study of Socioeconomic Epidemiology. Harvard University Press, Cambridge, MA
9. Manton K G, Poss S S, Wing S 1979 The black white mortality crossover: Investigation from the perspective of the components of aging. The Gerontologist 19(3): 291–300
10. Manton K G, Stallard E 1981 Methods for evaluating the heterogeneity of aging processes in human populations using vital statistics data: Explaining the black white mortality crossover by a model of mortality selection. Human Biology 53: 47–67
11. Manton K G, Stallard E 1997 Health and disability differences among racial and ethnic groups. In: Martin L G, Soldo B J (eds.) Racial and Ethnic Differences in Health of Older Americans. National Academy Press, Washington, DC, pp. 43–105
12. Manton K G, Vaupel J W 1995 Survival after the age of 80 in the United States, Sweden, France, England, and Japan. New England Journal of Medicine 333: 1232–5
13. Mosley W H, Gray R 1993 Childhood precursors of adult morbidity and mortality in developing countries: implications for health programs. In: Gribble J, Preston S H (eds.) The Epidemiological Transition: Policy and Planning Implications for De eloping Countries. National Academy Press, Washington, DC, pp. 69–100
14. Nam C B, Weatherby N L, Ockay K A 1978 Causes of death which contribute to the mortality crossover eff Social Biology 25(4): 306–14
15. Olshansky S J 1995 Introduction: New developments in mortality. The Gerontologist 35(5): 583–7
16. Preston S H, Elo I T, Rosenwaike I, Hill M 1996 African-American mortality at older ages: Results of a matching study. Demography 33(2): 193–209
17. Preston S H, Elo I T, Stewart Q 1999 Effects of age misreporting on mortality estimates at older ages. Population Studies–Journal of Demography 53: 165–77
18. Vaupel J W, Manton K G, Stallard E 1979 The impact of heterogeneity in individual frailty on the dynamics of mortality. Demography 16(3): 439–54