There is no safe level of exposure to inorganic arsenic or uranium, yet recent studies identified sociodemographic and regional inequalities in concentrations of these frequently detected contaminants in public water systems across the US. We analyze the county-level association between racial/ethnic composition and public water arsenic and uranium concentrations from 2000–2011 using geospatial models. We find that higher proportions of Hispanic/Latino and American Indian/Alaskan Native residents are associated with significantly higher arsenic and uranium concentrations. These associations differ in magnitude and direction across regions; higher proportions of non-Hispanic Black residents are associated with higher arsenic and uranium in regions where concentrations of these contaminants are high. The findings from this nationwide geospatial analysis identifying racial/ethnic inequalities in arsenic and uranium concentrations in public drinking water across the US can advance environmental justice initiatives by informing regulatory action and financial and technical support to protect communities of color.

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Geocoding is a powerful tool for environmental exposure assessments that rely on spatial databases. Geocoding processes, locators, and reference datasets have improved over time; however, improvements have not been well-characterized. Enrollment addresses for the Agricultural Health Study, a cohort of pesticide applicators and their spouses in Iowa (IA) and North Carolina (NC), were geocoded in 2012–2016 and then again in 2019. We calculated distances between geocodes in the two periods. For a subset, we computed positional errors using “gold standard” rooftop coordinates (IA; N = 3566) or Global Positioning Systems (GPS) (IA and NC; N = 1258) and compared errors between periods. We used linear regression to model the change in positional error between time periods (improvement) by rural status and population density, and we used spatial relative risk functions to identify areas with significant improvement. Median improvement between time periods in IA was 41 m (interquartile range, IQR: −2 to 168) and 9 m (IQR: −80 to 133) based on rooftop coordinates and GPS, respectively. Median improvement in NC was 42 m (IQR: −1 to 109 m) based on GPS. Positional error was greater in rural and low-density areas compared to in towns and more densely populated areas. Areas of significant improvement in accuracy were identified and mapped across both states. Our findings underscore the importance of evaluating determinants and spatial distributions of errors in geocodes used in environmental epidemiology studies.