Assessing county-level determinants of diabetes in the United States (2003–2012). (May 2020) - Feldman, Justin M.; Lee, David C.; Lopez, Priscilla; Rummo, Pasquale E.; Hirsch, Annemarie G.; Carson, April P.; McClure, Leslie A.; Elbel, Brian; Thorpe, Lorna E.
Abstract: Using data from the United States Behavioral Risk Factor Surveillance System (2003–2012; N = 3, 397, 124 adults), we estimated associations between prevalent diabetes and four county-level exposures (fast food restaurant density, convenience store density, unemployment, active commuting). All associations confirmed our a priori hypotheses in conventional multilevel analyses that pooled across years. In contrast, using a random-effects within-between model, we found weak, ambiguous evidence that within-county changes in exposures were associated with within-county change in odds of diabetes. Decomposition revealed that the pooled associations were largely driven by time-invariant, between-county factors that may be more susceptible to confounding versus within-county associations. Highlights: Multilevel analyses of repeated cross-sectional surveys depend on model choice. 4 county-level measures predicted diabetes in a model that ignored temporality. There is marginal evidence that increasing walkability led to decreased diabetes. No other findings were supported by a model that considered change over time. Models of repeated-cross sectional survey data should incorporate temporality.