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Does SES explain more of the black/white health gap than we thought? Revisiting our approach toward understanding racial disparities in health

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  • Do, D. Phuong
  • Frank, Reanne
  • Finch, Brian Karl

Abstract

Studies of racial health gaps often find that disparities persist even after adjusting for socioeconomic status (SES). We contend that the persistent residual variation may, in part, be the result of conceptual and methodological problems in the operationalization of SES. These include inadequate attention to the content validity of SES measures and insufficient adjustments for SES differences across racial groups. Using data from the 1997–2007 U.S. Panel Study of Income Dynamics (N = 9932), we use longitudinal and multi-level measures of SES and apply a propensity score adjustment strategy to examine the black/white disparity in self-rated health. Compared to conventional regression estimates that yield unexplained racial health gaps, propensity score adjustment accounts for the entire racial disparity in self-rated health. Results suggest that previous studies may have inadequately adjusted for differences in SES across racial groups, that social factors should be carefully and conscientiously considered, and that acknowledgment of the possibility of incomplete SES adjustments should be weighed before any inferences to non-SES etiology can be made.

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  • Do, D. Phuong & Frank, Reanne & Finch, Brian Karl, 2012. "Does SES explain more of the black/white health gap than we thought? Revisiting our approach toward understanding racial disparities in health," Social Science & Medicine, Elsevier, vol. 74(9), pages 1385-1393.
  • Handle: RePEc:eee:socmed:v:74:y:2012:i:9:p:1385-1393
    DOI: 10.1016/j.socscimed.2011.12.048
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    1. Mark R. Rank & Thomas A. Hirschl, 2001. "Rags or Riches? Estimating the Probabilities of Poverty and Affluence across the Adult American Life Span," Social Science Quarterly, Southwestern Social Science Association, vol. 82(4), pages 651-669, December.
    2. Orsi, J.M. & Margellos-Anast, H. & Whitman, S., 2010. "Black-white health disparities in the United States and Chicago: A 15-year progress analysis," American Journal of Public Health, American Public Health Association, vol. 100(2), pages 349-356.
    3. McDonough, Peggy & Sacker, Amanda & Wiggins, Richard D., 2005. "Time on my side? Life course trajectories of poverty and health," Social Science & Medicine, Elsevier, vol. 61(8), pages 1795-1808, October.
    4. Crimmins, E.M. & Kim, J.K. & Alley, D.E. & Karlamangla, A. & Seeman, T., 2007. "Hispanic paradox in biological risk profiles," American Journal of Public Health, American Public Health Association, vol. 97(7), pages 1305-1310.
    5. Subramanian, S.V. & Acevedo-Garcia, Dolores & Osypuk, Theresa L., 2005. "Racial residential segregation and geographic heterogeneity in black/white disparity in poor self-rated health in the US: a multilevel statistical analysis," Social Science & Medicine, Elsevier, vol. 60(8), pages 1667-1679, April.
    6. Keisuke Hirano & Guido W. Imbens & Geert Ridder, 2003. "Efficient Estimation of Average Treatment Effects Using the Estimated Propensity Score," Econometrica, Econometric Society, vol. 71(4), pages 1161-1189, July.
    7. Barsky R. & Bound J. & Charles K.K. & Lupton J.P., 2002. "Accounting for the Black-White Wealth Gap: A Nonparametric Approach," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 663-673, September.
    8. Browning, Christopher R. & Cagney, Kathleen A. & Wen, Ming, 2003. "Explaining variation in health status across space and time: implications for racial and ethnic disparities in self-rated health," Social Science & Medicine, Elsevier, vol. 57(7), pages 1221-1235, October.
    9. Ann Huff Stevens, 1999. "Climbing out of Poverty, Falling Back in: Measuring the Persistence of Poverty Over Multiple Spells," Journal of Human Resources, University of Wisconsin Press, vol. 34(3), pages 557-588.
    10. Heejung Bang & James M. Robins, 2005. "Doubly Robust Estimation in Missing Data and Causal Inference Models," Biometrics, The International Biometric Society, vol. 61(4), pages 962-973, December.
    11. Do, D. Phuong, 2009. "The dynamics of income and neighborhood context for population health: Do long-term measures of socioeconomic status explain more of the black/white health disparity than single-point-in-time measures," Social Science & Medicine, Elsevier, vol. 68(8), pages 1368-1375, April.
    12. Kaufman, Jay S., 2008. "Epidemiologic analysis of racial/ethnic disparities: Some fundamental issues and a cautionary example," Social Science & Medicine, Elsevier, vol. 66(8), pages 1659-1669, April.
    13. James Heckman & Hidehiko Ichimura & Jeffrey Smith & Petra Todd, 1998. "Characterizing Selection Bias Using Experimental Data," Econometrica, Econometric Society, vol. 66(5), pages 1017-1098, September.
    14. Franks, Peter & Muennig, Peter & Lubetkin, Erica & Jia, Haomiao, 2006. "The burden of disease associated with being African-American in the United States and the contribution of socio-economic status," Social Science & Medicine, Elsevier, vol. 62(10), pages 2469-2478, May.
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    2. Beck, Audrey N. & Finch, Brian K. & Lin, Shih-Fan & Hummer, Robert A. & Masters, Ryan K., 2014. "Racial disparities in self-rated health: Trends, explanatory factors, and the changing role of socio-demographics," Social Science & Medicine, Elsevier, vol. 104(C), pages 163-177.
    3. Boen, Courtney, 2016. "The role of socioeconomic factors in Black-White health inequities across the life course: Point-in-time measures, long-term exposures, and differential health returns," Social Science & Medicine, Elsevier, vol. 170(C), pages 63-76.
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    8. Joshua C. Hall & Brad R. Humphreys & Jane E. Ruseski, 2015. "Economic Freedom, Race, and Health Disparities: Evidence from US States," Working Papers 15-43, Department of Economics, West Virginia University.

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