ArticleEnvironmental epidemiology (Philadelphia, Pa.)2022
Latent growth trajectories of county-level diabetes prevalence in the United States, 2004-2017, and associations with overall environmental quality.
Article in Environmental epidemiology (Philadelphia, Pa.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed.
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- A Scoping Review and Assessment of the Area-Level Composite Measures That Estimate Social Determinants of Health Across the United States.Public health reports (Washington, D.C. : 1974)Article
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3 authors.
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Abstract
The prevalence of type 2 diabetes (T2D) has increased in the United States, and recent studies suggest that environmental factors contribute to T2D risk. We sought to understand if environmental factors were associated with the rate and magnitude of increase in diabetes prevalence at the county level. Methods: We obtained age-adjusted diabetes prevalence estimates from the CDC for 3,137 US counties from 2004 to 2017. We applied latent growth mixture models to these data to identify classes of counties with similar trends in diabetes prevalence over time, stratified by Rural Urban Continuum Codes (RUCC). We then compared mean values of the US EPA Environmental Quality Index (EQI) 2006-2010, overall and for each of the five domain indices (air, water, land, sociodemographic, and built), with RUCC-specific latent class to examine associations of environmental factors and class of diabetes prevalence trajectory. Results: Overall diabetes prevalence trends between 2004 and 2017 were similar across all RUCC strata. We identified two classes among metropolitan urbanized (RUCC 1) counties; four classes among non-metro urbanized (RUCC 2) counties; and three classes among less urbanized (RUCC 3) and thinly populated (RUCC 4) counties. Associations with overall EQI values and class of diabetes prevalence trends differed by RUCC strata, with the clearest association between poor air EQI and steeper increases in diabetes prevalence among rural counties (RUCC 3 and 4). Conclusions: Similarities in county-level diabetes prevalence trends between 2004 and 2017 were identified for each RUCC strata, although associations with environmental factors varied by rurality.
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