Diabetes prevalence is associated with different community factors in the diabetes belt versus the rest of the United States

Abstract

Objective: To investigate differences in community characteristics associated with diabetes prevalence between the Diabetes Belt and the rest of the contiguous United States (U.S.) METHODS: County-level adult diabetes prevalence estimates (i.e., percent of people [≥20 years] with diagnosed diabetes 2009) were used from the Centers for Disease Control and Prevention, in addition to data from the U.S. Census Bureau, U.S. Department of Agriculture, and U.S. Department of Health and Human Services, to carry out a spatial regime analysis to identify county-level factors correlated with diabetes prevalence in the Diabetes Belt versus the remainder of the U.S.

Results: Counties outside of the Diabetes Belt demonstrated stronger positive associations between diabetes prevalence and persistent poverty and greater percentages of unemployed labor forces. For counties in the Diabetes Belt, diabetes prevalence showed a stronger positive association with natural amenities (e.g., temperate climate and topographic features) and a stronger negative association with fitness/recreation facility density.

Conclusions: Community-level correlates of diabetes prevalence differed between the Diabetes Belt and elsewhere in the U.S. Economic hardship was shown to be more relevant outside the Diabetes Belt, while recreational context effects were more pronounced among counties within the region. Prevention and treatment targets are geographically unique, and public health efforts should acknowledge these differences in crafting policy.

Figure 1. Local Indicators of Spatial Association (LISA) map of significant geographic concentrations of county-level diagnosed diabetes prevalence, 2009

Moran’s I = 0.74; p<0.05. Light gray-shaded counties are core members of geographic clusters with significantly (p<0.05) lower adult diagnosed diabetes prevalence than would be expected at random. Dark gray-shaded counties are core members of geographic clusters with significantly (p<0.05) higher adult diagnosed diabetes prevalence.