LAUSR

This map shows areas with significantly high and significantly low prevalence of diabetes and prediabetes in a health center population in Chicago. Prevalence was determined by ICD (International Classification of Diseases) codes and measured hemoglobin A1c (HbA1c). The map highlights regional clusters and isolated areas of diabetes prevalence that could be targeted with interventions to improve health outcomes. Diagnoses determined by ICD codes are shown in colors as hot and cold spot cluster cores corresponding to “high–high” (HH) and “low–low” (LL) LISA (local indicator of spatial autocorrelation) statistics, where selected census tracts and neighboring tracts both have high rates (HH) or both have low rates (LL) of diabetes. Hot spot outliers have high diabetes rates compared with neighboring tracts (“high–low” [HL]), whereas cold spot outliers have low diabetes rates compared with neighboring tracts (“low–high” [LH]). Hot spots of prediabetes and diabetes determined by measured HbA1c levels are also shown. LISA significance set at P < .05. Supermarket data are from Kolak et al (1). Census tract and community area boundary data are from the Chicago Data Portal (2,3). Basemap imagery is from OpenStreetMap, Leaflet, and Carto.