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Demography

, Volume 51, Issue 6, pp 2025–2045 | Cite as

Why Lifespans Are More Variable Among Blacks Than Among Whites in the United States

  • Glenn FirebaughEmail author
  • Francesco Acciai
  • Aggie J. Noah
  • Christopher Prather
  • Claudia Nau
Article

Abstract

Lifespans are both shorter and more variable for blacks than for whites in the United States. Because their lifespans are more variable, there is greater inequality in length of life—and thus greater uncertainty about the future—among blacks. This study is the first to decompose the black-white difference in lifespan variability in America. Are lifespans more variable for blacks because they are more likely to die of causes that disproportionately strike the young and middle-aged, or because age at death varies more for blacks than for whites among those who succumb to the same cause? We find that it is primarily the latter. For almost all causes of death, age at death is more variable for blacks than it is for whites, especially among women. Although some youthful causes of death, such as homicide and HIV/AIDS, contribute to the black-white disparity in variance, those contributions are largely offset by the higher rates of suicide and drug poisoning deaths for whites. As a result, differences in the causes of death for blacks and whites account, on net, for only about one-eighth of the difference in lifespan variance.

Keywords

Lifespan variability Health disparities Life expectancy Adult mortality Cause of death 

Notes

Acknowledgments

This research was supported by funding from the Eunice Kennedy Shriver National Institute of Child Health and Human Development to the Population Research Institute at The Pennsylvania State University for Population Research Infrastructure (R24HD041025), and as well as from a Family Demography Training grant (T-32HD007514). We thank Jenny Van Hook for her comments and encouragement.

Supplementary material

13524_2014_345_MOESM1_ESM.docx (34 kb)
Online Resource 1 (DOCX 34.2 KB)

References

  1. Arriaga, E. (1984). Measuring and explaining the change in life expectancies. Demography, 21, 83–96.CrossRefGoogle Scholar
  2. Becker, G., Philipson, T., & Soares, R. (2005). The quantity and quality of life and the evolution of world inequality. American Economic Review, 95, 277–291.CrossRefGoogle Scholar
  3. Beltrán-Sánchez, H., Preston, S. H., & Canudas-Romo, V. (2008). An integrated approach to cause-of-death analysis: Cause-deleted life tables and decompositions of life expectancy. Demographic Research, 19(article 35), 1323–1350. doi: 10.4054/DemRes.2008.19.35 CrossRefGoogle Scholar
  4. Das Gupta, P. (1993). Standardization and decomposition of rates: A user’s manual. Washington, DC: U.S. Department of Commerce, Economics and Statistics Administration, Bureau of the Census.Google Scholar
  5. Edwards, R. D. (2011). Changes in world inequality in length of life: 1970–2000. Population and Development Review, 37, 499–528.CrossRefGoogle Scholar
  6. Edwards, R. D. (2013). The cost of uncertain lifespan. Journal of Population Economics, 26, 1485–1522.CrossRefGoogle Scholar
  7. Edwards, R. D., & Tuljapurkar, S. (2005). Inequality in life spans and a new perspective on mortality convergence across industrialized countries. Population and Development Review, 31, 645–674.CrossRefGoogle Scholar
  8. Engelman, M., Canudas-Romo, V., & Agree, E. M. (2010). The implications of increased survivorship for mortality variation in aging populations. Population and Development Review, 36, 511–539.CrossRefGoogle Scholar
  9. Fenelon, A. (2013). An examination of black/white differences in the rate of age-related mortality increase. Demographic Research, 29(article 17), 441–472. doi: 10.4054/DemRes.2013.29.17 CrossRefGoogle Scholar
  10. Fries, J. F. (1980). Aging, natural death, and the compression of morbidity. New England Journal of Medicine, 303, 130–135.CrossRefGoogle Scholar
  11. Fries, J. F. (1984). The compression of morbidity: Miscellaneous comments about a theme. Gerontologist, 24, 354–359.CrossRefGoogle Scholar
  12. Gillespie, D. O. S., Trotter, M. E., & Tuljapurkar, S. D. (2013). Mortality change and lifespan inequality (Working Paper No. 127). Stanford, CA: Stanford University, Morrison Institute for Population and Resource Studies.Google Scholar
  13. Harper, S., Lynch, J., Burris, S., & Davey Smith, G. (2007). Trends in the black-white life expectancy disparity in the United States, 1983–2003. Journal of the American Medical Association, 297, 1224–1232.CrossRefGoogle Scholar
  14. Harper, S., Rushani, D., & Kaufman, J. S. (2012). Trends in the black-white life expectancy disparity, 2003–2008. Journal of the American Medical Association, 307, 2257–2259.Google Scholar
  15. Heron, M. P., Hoyert, D. L., Murphy, S. L., Xu, J. Q., Kochanek, K. D., & Tejada-Vera, B. (2009). Deaths: Final data for 2006 (National Vital Statistics Reports). Hyattsville, MD: National Center for Health Statistics.Google Scholar
  16. Israel, R. A., Rosenberg, H. M., & Curtin, L. R. (1986). Analytical potential for multiple cause-of-death data. American Journal of Epidemiology, 124, 161–179.Google Scholar
  17. Kannisto, V. (2000). Measuring the compression of mortality. Demographic Research, 3(article 6), 1–24. doi: 10.4054/DemRes.2000.3.6 Google Scholar
  18. Kochanek, K. D., Arias, E., & Anderson, R. N. (2013). How did cause of death contribute to racial differences in life expectancy in the United States in 2010? (NCHS data brief). Hyattsville, MD: National Center for Health Statistics.Google Scholar
  19. Lariscy, J. T., Nau, C., Firebaugh, G., & Hummer, R. A. (2013, April). Racial/ethnic inequality in adult survival: Decomposition of age at death variation among U.S. adults. Paper presented at the annual meeting of the Population Association of America, New Orleans, LA.Google Scholar
  20. Lynch, S. M., & Brown, J. S. (2001). Reconsidering mortality compression and deceleration: An alternative model of mortality rates. Demography, 38, 79–95.CrossRefGoogle Scholar
  21. Lynch, S. M., Brown, J. S., & Harmsen, K. G. (2003). Black-white differences in mortality deceleration and compression and the mortality crossover reconsidered. Research on Aging, 25, 456–483.CrossRefGoogle Scholar
  22. Manton, K. G., & Singer, B. (1994). What’s the fuss about compression of mortality? Chance, 7, 21–30.Google Scholar
  23. Myers, G. C., & Manton, K. G. (1984). Compression of mortality: Myth or reality? Gerontologist, 24, 346–353.CrossRefGoogle Scholar
  24. National Center for Health Statistics (NCHS). (2012). Multiple cause of death file 2010. Washington, DC: CDC.Google Scholar
  25. Nau, C., & Firebaugh, G. (2012). A new method for determining why length of life is more unequal in some populations than in others. Demography, 49, 1207–1230.CrossRefGoogle Scholar
  26. Noymer, A., Penner, A. M., & Saperstein, A. (2011). Cause of death affects racial classification on death certificates. PloS One, 6(1), e15812. doi: 10.1371/journal.pone.0015812 CrossRefGoogle Scholar
  27. Peltzman, S. (2009). Mortality inequality. Journal of Economic Perspectives, 23, 175–190.CrossRefGoogle Scholar
  28. Pollard, J. H. (1982). The expectation of life and its relationship to mortality. Journal of Institute of Actuaries, 109, 225–240.CrossRefGoogle Scholar
  29. Pollard, J. H. (1988). On the decomposition of changes in expectation of life and differentials in life expectancy. Demography, 25, 265–276.CrossRefGoogle Scholar
  30. Smits, J., & Monden, C. (2009). Length of life inequality around the globe. Social Science & Medicine, 68, 1114–1123.CrossRefGoogle Scholar
  31. Tuljapurkar, S. (2010). The final inequality: Variance in age at death. In J. B. Shoven (Ed.), Demography and the economy (pp. 209–221). Chicago, IL: The University of Chicago Press.CrossRefGoogle Scholar
  32. Tuljapurkar, S., & Edwards, R. D. (2011). Variance in death and its implications for modeling and forecasting mortality. Demographic Research, 24(article 21), 497–526. doi: 10.4054/DemRes.2011.24.21 CrossRefGoogle Scholar
  33. U.S. Department of Health and Human Services. (2011). Healthy people 2020: Maternal, infant, and child health objectives. Washington, DC: U.S. Department of Health and Human Services.Google Scholar
  34. van Raalte, A. A., & Caswell, H. (2013). Perturbation analysis of indices of lifespan variability. Demography, 50, 1615–1640.CrossRefGoogle Scholar
  35. van Raalte, A. A., Martikainen, P., & Myrskylä, M. (2014). Lifespan variation by occupational class: Compression or stagnation over time? Demography, 51, 73–95.CrossRefGoogle Scholar
  36. Warner, M., Chen, L. H., Makuc, D. M., Anderson, R. N., & Miniño, A. M. (2011). Drug poisoning deaths in the United States, 1980–2008 (NCHS Data Brief No. 81). Hyattsville, MD: National Center for Health Statistics.Google Scholar
  37. Wilmoth, J. R., & Horiuchi, S. (1999). Rectangularization revisited: Variability of age at death within human populations. Demography, 36, 475–495.CrossRefGoogle Scholar
  38. World Health Organization. (2010). WHO mortality database documentation. Retrieved from http://www.who.int/healthinfo/statistics/mortality_rawdata/en/index1.html

Copyright information

© Population Association of America 2014

Authors and Affiliations

  • Glenn Firebaugh
    • 1
    • 2
    • 3
    Email author
  • Francesco Acciai
    • 2
    • 3
  • Aggie J. Noah
    • 2
    • 3
  • Christopher Prather
    • 2
    • 3
  • Claudia Nau
    • 4
  1. 1.University ParkUSA
  2. 2.Department of Sociology and CriminologyThe Pennsylvania State UniversityUniversity ParkUSA
  3. 3.The Population Research InstituteThe Pennsylvania State UniversityUniversity ParkUSA
  4. 4.The Johns Hopkins Global Center for Childhood Obesity, Bloomberg School of Public HealthBaltimoreUSA

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