Living and dying in the U.S.A.: Sociodemographic determinants of death among blacks and whites

Abstract

This paper examines the demographic and social factors associated with differences in length of life by race. The results demonstrate that sociodemographic factors—age, sex, marital status, family size, and income—profoundly affect black and white mortality. Indeed, the racial gap in overall mortality could close completely with increased standards of living and improved lifestyles. Moreover, examining cause-specific mortality while adjusting for social factors shows that compared to whites, blacks have a lower mortality risk from respiratory diseases, accidents. and suicide; the same risk from circulatory diseases and cancer; and higher risks from infectious diseases, homicide, and diabetes. These results underscore the importance of examining social characteristics to understand more clearly the race differences in overall and cause-specific mortality.

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Correspondence to Richard G. Rogers.

Additional information

The 1986 National Health Interview Survey (NHIS) data set employed in this article was made available in part by the Inter-University Consortium for Political and Social Research. The data for the 1986 NHIS were originally collected by the U.S. Department of Health and Human Services and by the National Center for Health Statistics. I thank Eve Powell-Griner, Harriet Orcutt Duleep, Kenneth C. Land, Robert McNown, Thomas Pullum, the editor of Demography, and the anonymous reviewers for their insightful comments and suggestions. Neither the collector of the original data nor the Consortium bears responsibility for the analysis or interpretations presented here. An earlier draft of this paper was presented at the annual meetings of the Population Association of America held March 21–23, 1991 in Washington, DC.

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Rogers, R.G. Living and dying in the U.S.A.: Sociodemographic determinants of death among blacks and whites. Demography 29, 287–303 (1992). https://doi.org/10.2307/2061732

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Keywords

  • Family Size
  • Racial Disparity
  • National Health Interview Survey
  • Circulatory Disease
  • Polytomous Logistic Regression