Heterogeneity in the Strehler-Mildvan General Theory of Mortality and Aging
- 246 Downloads
This study examines and further develops the classic Strehler-Mildvan (SM) general theory of mortality and aging. Three predictions from the SM theory are tested by examining the age dependence of mortality patterns for 42 countries (including developed and developing countries) over the period 1955–2003. By applying finite mixture regression models, principal component analysis, and random-effects panel regression models, we find that (1) the negative correlation between the initial adulthood mortality rate and the rate of increase in mortality with age derived in the SM theory exists but is not constant; (2) within the SM framework, the implied age of expected zero vitality (expected maximum survival age) also is variable over time; (3) longevity trajectories are not homogeneous among the countries; (4) Central American and Southeast Asian countries have higher expected age of zero vitality than other countries in spite of relatively disadvantageous national ecological systems; (5) within the group of Central American and Southeast Asian countries, a more disadvantageous national ecological system is associated with a higher expected age of zero vitality; and (6) larger agricultural and food productivities, higher labor participation rates, higher percentages of population living in urban areas, and larger GDP per capita and GDP per unit of energy use are important beneficial national ecological system factors that can promote survival. These findings indicate that the SM theory needs to be generalized to incorporate heterogeneity among human populations.
KeywordsStrehler-Mildvan theory Ecological system Population heterogeneity Age of expected zero vitality
This article is a revision of a paper presented at the 2008 annual meeting of the Population Association of America, New Orleans, Louisiana. We thank C. M. Suchindran for insightful comments and suggestions. We also benefitted from comments from two anonymous Demography reviewers and those of Anatoli Yashin, Eric Stallard, and other members of the Demography, Life Course, and Aging Workshop at Duke University. We also are grateful for the support from the Leadership in Aging Society Program at Duke University.
- Bryk, A. S., & Raudenbush, S. W. (1992). Hierarchical linear models for social and behavioral research: Application and data analysis methods. Newbury Park: Sage.Google Scholar
- Duncan, O. D. (1959). Human ecology and population studies. In P. M. Hauser & O. D. Duncan (Eds.), The study of population: An inventory and appraisal (pp. 678–716). Chicago: University of Chicago Press.Google Scholar
- Faloon, W. (2008). An overlooked method to prevent millions of needless deaths. Life Extension, 3–12.Google Scholar
- Goldstein, H. (1995). Multilevel statistical models (2nd ed.). London: Edward Arnold.Google Scholar
- Grant, W. B., & Holick, M. E. (2005). Benefits and requirements of vitamin D for optimal health: A review. Alternative Medicine Review, 10, 94–111.Google Scholar
- Gross, M. D. (2005). Vitamin D and calcium in the prevention of prostate and colon cancer: New approaches for the identification of needs. Journal of Nutrition, 135, 326–331.Google Scholar
- Hawley, A. H. (1950). Human ecology: A theory of community structure. New York: Ronald.Google Scholar
- Kirkwood, T. B. L. (1990). The disposable soma theory of aging. In D. E. Harrison (Ed.), Genetic effects on aging II (pp. 9–19). Caldwell: Telford.Google Scholar
- Martinez, I., Torres, R., & Frias, Z. (1975). Cancer incidence in the United States and Puerto Rico. Cancer Research, 35, 3265–3271.Google Scholar
- Omran, A. R. (1982). Epidemiologic transition. In International encyclopedia of population (pp. 172–83). New York: The Free Press.Google Scholar
- U.N. Department of International Economic and Social Affairs. (1982). Model life tables for developing countries. New York: United Nations.Google Scholar
- Vaupel, J. W. (1997). Trajectories of mortality at advanced ages. In K. H. Wachter & C. E. Finch (Eds.), Between Zeus and the salmon: The biodemography of longevity (pp. 17–37). Washington, DC: National Academy.Google Scholar
- Wilmoth, J. R. (1997). In search of limits. In K. H. Wachter & C. E. Finch (Eds.), Between Zeus and the salmon: The biodemography of longevity (pp. 38–64). Washington, DC: National Academy.Google Scholar
- Wooldridge, J. M. (2002). Econometric analysis of cross section and panel data. Cambridge: MIT.Google Scholar
- World Development Indicators. (2008). Indicators published by the World Bank. Available online at http://data.worldbank.org/indicator.
- Yashin, A. I., Ukraintseva, S. V., Boiko, S. I., & Arbeev, K. G. (2002b). Individual aging and mortality rate: How are they related? Social Biology, 49, 206–217.Google Scholar