The contribution of three dimensions of allostatic load to racial/ethnic disparities in poor/fair self-rated health

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Objective This study evaluates whether different dimensions of physiological dysregulation, modeled individually rather than additively mediate racial/ethnic disparities in self-reported health. Methods Using data from the National Health and Nutrition Examination Survey (2005–2010) and the Karlson, Hold, and Breen (KHB) mediation model, this paper explores what operationalization of biomarker data most strongly mediate racial/ethnic disparities in poor/fair self-rated health (SRH) among adults in the United States, net of demographic, socioeconomic, behavioral, and medication controls. Results Non-Hispanic blacks and Hispanics had significantly higher odds of reporting poor/fair self-rated health in comparison to non-Hispanic whites. Operationalizations of allostatic load that disaggregate three major dimensions of physiological dysregulation mediate racial/ethnic disparities strongly between non-Hispanic blacks and non-Hispanic whites, but not between Hispanics and non-Hispanic whites. Disaggregating these dimensions explains racial/ethnic disparities in poor/fair SRH better than the continuous score. Analyses on sex-specific disparities indicate differences in how individual dimensions of allostatic load contribute to racial/ethnic disparities in poor/fair SRH differently. All individual dimensions are strong determinants of poor/fair SRH for males. In contrast, for females, the only dimension that is significantly associated with poor/fair SRH is inflammation. For the analytic sample, additive biomarker scores fit the data as well or better than other approaches, suggesting that this approach is most appropriate for explaining individual differences. However, in sex-specific analyses, the interactive approach models fit the data best for men and women. Conclusions Future researchers seeking to explain racial/ethnic disparities in full or sex-stratified samples should consider disaggregating allostatic load by dimension.

Original languageEnglish (US)
Pages (from-to)55-65
Number of pages11
JournalSSM - Population Health
StatePublished - Apr 2018

All Science Journal Classification (ASJC) codes

  • Health(social science)
  • Health Policy
  • Public Health, Environmental and Occupational Health


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