Healthier, Wealthier, and Wiser: A Demonstration of Compositional Changes in Aging Cohorts Due to Selective Mortality
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The gradual changes in cohort composition that occur as a result of selective mortality processes are of interest to all aging research. We present the first illustration of changes in the distribution of specific cohort characteristics that arise purely as a result of selective mortality. We use data on health, wealth, education, and other covariates from two cohorts (the AHEAD cohort, born 1900–1923 and the HRS cohort, born 1931–1941) included in the Health and Retirement Survey, a nationally representative panel study of older Americans spanning nearly two decades (N = 14,466). We calculate sample statistics for the surviving cohort at each wave. Repeatedly using only baseline information for these calculations so that there are no changes at the individual level (what changes is the set of surviving respondents at each specific wave), we obtain a demonstration of the impact of mortality selection on the cohort characteristics. We find substantial changes in the distribution of all examined characteristics across the nine survey waves. For instance, the median wealth increases from about $90,000 to $130,000 and the number of chronic conditions declines from 1.5 to 1 in the AHEAD cohort. We discuss factors that influence the rate of change in various characteristics. The mortality selection process changes the composition of older cohorts considerably, such that researchers focusing on the oldest old need to be aware of the highly select groups they are observing, and interpret their conclusions accordingly.
KeywordsMortality selection Cohorts Aging Cohort composition
- Adams, P., Hurd, M. D., McFadden, D. L., Merrill, A., & Ribeiro, T. (2004). Healthy, wealthy, and wise? Tests for direct causal paths between health and socioeconomic status. In D. A. Wise (Ed.), Perspectives on the economics of aging (pp. 415–526). Chicago: University Of Chicago Press.CrossRefGoogle Scholar
- Elo, I. T., & Drevenstedt, G. L. (2002). Educational differences in cause-specific mortality in the United States. Yearbook of Population Research in Finland, 38, 37–54.Google Scholar
- Ferraro, K. F., Shippee, T. P., & Schafer, M. H. (2009). Cumulative inequality theory for research on aging and the life course. In V. L. Bengtson, D. Gans, N. M. Putney, & M. Silverstein (Eds.), Handbook of theories of aging (pp. 413–433). New York: Springer.Google Scholar
- Hodes, R. J., & Suzman, R. (2007). Growing older in America: The health and retirement study. Bethesda: National Institute on Aging, National Institute of Health, U.S. Department of Health and Human Services.Google Scholar
- Keyfitz, N. (1985). Heterogeneity and selection in population analysis. In Applied mathematical demography. New York: Springer.Google Scholar
- RAND Corp. (2011). The RAND HRS Data (Version L) 2012. http://www.rand.org/labor/aging/dataprod/hrs-data.html. Accessed 30 Mar 2012.
- Trussell, J., & Richards, T. (1985). Correcting for unmeasured heterogeneity in hazard models using the heckman-singer procedure. In N. B. Tuma (Ed.), Sociological methodology (pp. 242–276). San Francisco: Jossey-Bass.Google Scholar
- Trussell, J., & Rodríguez, G. (1990). Heterogeneity in demographic research. In J. Adams, D. A. Lam, A. I. Hermalin, & P. E. Smouse (Eds.), Convergent issues in genetics and demography (pp. 111–132). New York: Oxford University Press.Google Scholar
- Vaupel, J. W., & Yashin, A. I. (1985). Heterogeneity’s ruses: Some surprising effects of selection on population dynamics. The American Statistician, 39(3), 176–185.Google Scholar