Abstract Body (Do not enter title and authors here): Background: Structural racism has emerged as an important contributor to poor health outcomes. Historic redlining, the previously legal practice of systematically denying credit access and insurance, resulted from Home Owners’ Loan Corporation (HOLC) residential security maps graded on a color coded scale (A (Green)=Best; B (Blue); C (Yellow); D (Red)=Hazardous), hence the term redlining. The goal of this study was to investigate the direct and indirect relationships between historic redlining and prevalence of diabetes in a national sample.

Methods: We combined census tract level data across multiple sources: a) diabetes prevalence from CDC PLACES 2019 database, b) HOLC grade from Mapping Inequality project, and c) incarceration risk, poverty, housing, education, employment, job environment, economic mobility, and demographics, from Opportunity Insights database. The assignment of redlining to present-day census tract was done based on overlap with historically HOLC graded areas. The final analytic sample consisted of 9,590 US census tracts. Structural equation modeling was then used to investigate direct and indirect relationships between redlining and diabetes prevalence through possible mediators of health care access, community resources, social capital, and social risk. Stata v16 was used for the analysis and analyses were adjusted for population.

Results: Higher prevalence of diabetes was directly associated with more redlining within a census tract (0.28, p<0.001). All indirect paths were significant with the three strongest indicating diabetes prevalence is indirectly associated with redlining via health care access (0.48, p<0.001); community resources measured via education level (-0.44, p<0.001); and social risk measured via income (-0.23, p<0.001). Figure 1 shows standardized coefficients to allow comparison with higher numbers indicating stronger relationships.

Conclusions: Consistent with our conceptual framework, redlining has significant direct and indirect relationships with diabetes prevalence. Indirect relationships include health care access, community resources including employment and education, social capital, and social risk factors of low income and high incarceration.