Higher socioeconomic status does not lead to equal reductions in type 2 diabetes and obesity rates among all racial and ethnic groups in the United States, according to a study published July 8 in PLOS One by Sara Cromer of Harvard Medical School and colleagues.
The researchers analyzed data from 54,991 adults in the US National Health and Nutrition Examination Survey between 1999 and 2018, along with information from 404,990 participants in the All of Us cohort. They examined how educational attainment and income related to the prevalence of type 2 diabetes and obesity.
The study found that age-adjusted rates of type 2 diabetes and obesity were generally highest among individuals with lower socioeconomic status, as well as among non-Hispanic Black, Mexican American, Other Hispanic, and Other/Multi-Racial participants. In adjusted models, higher educational attainment was associated with a 12% reduction in type 2 diabetes prevalence for non-Hispanic White participants but only a 4% reduction for non-Hispanic Black participants. Higher income was linked to lower obesity rates among non-Hispanic White participants but correlated with higher obesity rates among non-Hispanic Black participants. The effects varied depending on which measure of socioeconomic status was used—education or income—and differed by dataset.
The authors noted limitations including the cross-sectional design preventing conclusions about causation, as well as selection bias within the All of Us cohort. Despite these limitations, they concluded that treating associations between socioeconomic status and metabolic disease as uniform may obscure important differences across populations.
Sara Cromer said, "Although improving education or income is associated with lower rates of diabetes and obesity on average, the amount of improvement varies significantly by race. Overall, Black, Hispanic, and Asian individuals in the US have decreased protective effects of higher education and income than White individuals."
Chirag Patel said, "Socioeconomic status alone doesn't capture the full picture of health risk, and how we measure it matters. These findings set a clearer standard for how researchers should capture and report these variables so that predictive tools are accurate across the patients they're meant to serve."
