Does SES explain more of the black/white health gap than we thought? Revisiting our approach toward understanding racial disparities in health
Introduction
In spite of remarkable reductions in mortality and morbidity rates over the past century, racial disparities in the U.S. remain broad and persistent (Orsi, Margellos-Anast, & Whitman, 2010). Blacks continue to suffer the most severe and broadest range of health disadvantages, with higher rates of asthma (Gold & Wright, 2005), diabetes (Peek, Cargill, & Huang, 2007), cardiovascular mortality (Davis, Vinci, Okwuosa, Chase, & Huang, 2007), cancer mortality (American Cancer Society, 2007) and infant mortality (MacDorman, Callaghan, Mathews, Hoyert, & Kochanek, 2007).
Elucidating the sources of the enduring black/white health disparities have proven to be a formidable challenge. Given the strong links between health and socioeconomic status (SES) and the well-documented differences in SES across racial/ethnic groups, it follows that racial differences in SES may account for racial/ethnic disparities in health (House & Williams, 2000; Link & Phelan, 1995). Yet, after adjustment of SES differences, racial health disparities are seldom fully explained, leaving unexplained residual variation (Crimmins, Kim, Alley, Karlamangla, & Seeman, 2007; Franks, Muennig, Lubetkin, & Jia, 2006; House & Williams, 2000; Rogers, Hummer, & Nam, 2000; Williams, Mohammed, Leavell, & Collins, 2010).
In this paper, we contend that the residual variation that has proven so persistent may be, in part, the result of methodological problems including a) inadequate attention to the content validity of SES and b) insufficient adjustments for SES differences across racial groups.
Section snippets
Limitations of conventional models
As a statistical practice, the explanation of racial health disparities starts with a baseline disparity (represented by dummy variables for race/ethnicity) in which race represents the proverbial epidemiological “black box”. Researchers attempt to explain away this effect—that is, reduce the magnitude of race coefficients in successive models—through the addition of various sets of variables (e.g., SES, health behaviors). Depending on the disciplinary background of the researcher, explanations
Research questions
Our two key research questions are: 1) how much of the black/white health disparity can be accounted for with a better operationalization of SES? and 2) how much of the black/white health disparity can be accounted for by utilizing statistical models that directly attempt to achieve covariate balance between blacks and whites?
Data and methods
Data for this study come from the 1997–2007 years of the U.S. Panel Study of Income Dynamics (PSID). Begun in 1968, the PSID is composed of families of the baseline 1968 sample as well their descendants and individuals who marry into the families. Information was collected annually from 1968 to 1997, and biennially thereafter. Because of its self-replenishing design, the PSID is a nationally representative sample of the non-immigrant U.S. population.
The PSID has several unique features that are
Covariate balance
Table 1 presents descriptive statistics of the sample by race before propensity score weighting is applied. Significant socioeconomic and demographic differences exist between blacks and whites over a wide range of characteristics. Blacks in the sample are on average younger, have lower educational attainment, are more likely to be female, unemployed, unmarried, uninsured, and a member of a female-headed household, compared to whites. Moreover, approximately 38% of blacks' 2007 income falls
Discussion
This study investigated two possible explanations for the persistence of the black/white health gap, net of conventional adjustments for SES. We first examined whether adjustments using more complete measures of SES (i.e., long-term family income, wealth, and neighborhood poverty) further explained the black health disadvantage. This application of this strategy adds to the growing literature that is attempting to investigate the role of SES in generating racial/ethnic disparities in a more
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