Disaggregating Heterogeneity among Non-Hispanic Whites: Evidence and Implications for U.S. Racial/Ethnic Health Disparities.

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2021-02

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Abstract

Research has made strides in disaggregating health data among racial/ethnic minorities, but less is known about the extent of diversity among Whites. Using logistic regression modeling applied to data on respondents aged 40+ from the 2008 to 2016 American Community Survey, we disaggregated the non-Hispanic White population by ancestry and other racial/ethnic groups (non-Hispanic Black, non-Hispanic Asian, and Hispanic) by common subgroupings and examined heterogeneity in disability. Using logistic regression models predicting six health outcome measures, we compared the spread of coefficients for each of the large racial/ethnic groups and all subgroupings within these large categories. The results revealed that health disparities within the White population are almost as large as disparities within other racial groups. In fact, when Whites were disaggregated by ancestry, mean health appeared to be more varied among Whites than between Whites and members of other racial/ethnic groups in many cases. Compositional changes in the ancestry of Whites, particularly declines in Whites of western European ancestry and increases in Whites of eastern European and Middle Eastern ancestry, contribute to this diversity. Together, these findings challenge the oft-assumed notion that Whites are a homogeneous group and indicate that the aggregate White category obscures substantial intra-ethnic heterogeneity in health.

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10.1007/s11113-020-09632-5

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Read, Jen'nan Ghazal, Scott M Lynch and Jessica S West (2021). Disaggregating Heterogeneity among Non-Hispanic Whites: Evidence and Implications for U.S. Racial/Ethnic Health Disparities. Population research and policy review, 40(1). pp. 9–31. 10.1007/s11113-020-09632-5 Retrieved from https://hdl.handle.net/10161/28661.

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