An examination of within-county disparities across three domains: race/ethnicity, income, and geography

Background: Centers for Disease Control and Prevention’s Public Health 3.0 emphasizes the need for granular, subcounty data and analysis of social determinants of health across diverse groups, including race and income, to enhance equity. Subcounty data are measured in different domains, the choice of which influences the understanding of within-county disparities. Objective: To compare within-county disparity between groups in three domains (race/ethnicity, income, and geography) using homeownership data as a case example. Methods: Within-county disparities by income (9 groups), race/ethnicity (8 groups), and census tracts (CTs) were measured using the standard deviation of population-weighted group means. Homeownership rates were extracted from the 2019-2023 American Community Survey. We examined disparity magnitudes, correlations across domains, and data coverage, with a focus on state-level patterns and variation across urbanicity categories. Results: Within-county disparities in homeownership were largest by income (11.7%), followed by race/ethnicity (9.5%) and tract (9.5%). Disparities by income and tract increased with urbanicity, while racial disparities were relatively low in smaller non-metro counties but exceeded other domains in the most rural areas. State-level patterns varied, with Connecticut and Massachusetts showing consistently high disparities, southern states showing greater racial disparities, and correlations between domains differing by both rurality and state context. Data coverage was highest for income disparities (83% of counties), with more missingness in race/ethnicity and tract domains. Only four states (Connecticut, Delaware, New Jersey, and Rhode Island) had complete data coverage across all domains.