Heterogeneous Associations of Socioeconomic Status with Metabolic Disease in Racial and Ethnic Subgroups in the United States: A Cross-Sectional Cohort Study in NHANES and

Background: Unfavorable socioeconomic status (SES) is associated with adverse health outcomes and is believed to at least partially mediate racial and ethnic health disparities such that some authors have recommended incorporation of SES measures in clinical risk algorithms. However, whether the associations of improved SES with improved health are uniform across US racial and ethnic subpopulations and optimal strategies for modeling SES across populations are unknown. Methods and Findings: Among adult participants in the National Health and Nutrition Examination Survey 1999-2018 and the Results: Age-adjusted rates of T2D and obesity were highest among non-Hispanic Black, Mexican American, Other Hispanic, and Other/Multi-Racial participants and in those with lower SES. In stratified analyses, higher educational attainment and income were independently associated with lower rates of prevalent T2D and obesity among non-Hispanic White and Asian participants, with smaller or even reversed associations observed among other racial and ethnic groups, particularly non-Hispanic Black participants, in both data sets. Heterogeneity was confirmed by significant race-by-socioeconomic interaction terms. SES measures demonstrated variable patterns of association with disease (e.g., linear, threshold, or U-shaped associations) based on the SES measure, outcome, racial or ethnic group, and data set used. The association between educational attainment and T2D was significantly mediated through BMI among non-Hispanic White participants (32-35% mediation) but not among non-Hispanic Black, Mexican American, and Other Hispanic participants (0-11% mediation). Conclusions: The associations between SES and metabolic disease, the pathways mediating them, and the patterns of association of SES with disease are heterogeneous or even reversed in different US racial and ethnic groups. To prevent biased estimates in both research and clinical calculators which increasingly attempt to incorporate social determinants of health, researchers and clinicians should examine for heterogeneity between groups, particularly racial and ethnic groups.