Journal article
Assessing county-level determinants of diabetes in the United States (2003–2012)
Health & place, v 63, 102324
May 2020
PMID: 32217279
Featured in Collection : UN Sustainable Development Goals @ Drexel
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.
•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.
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Details
- Title
- Assessing county-level determinants of diabetes in the United States (2003–2012)
- Creators
- Justin M. Feldman - New York UniversityDavid C. Lee - New York UniversityPriscilla Lopez - New York UniversityPasquale E. Rummo - New York UniversityAnnemarie G. Hirsch - Geisinger Health SystemApril P. Carson - University of Alabama at BirminghamLeslie A. McClure - Drexel UniversityBrian Elbel - New York UniversityLorna E. Thorpe - New York University
- Publication Details
- Health & place, v 63, 102324
- Publisher
- Elsevier
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Epidemiology and Biostatistics
- Web of Science ID
- WOS:000541164200006
- Scopus ID
- 2-s2.0-85081198217
- Other Identifier
- 991019168714504721
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- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Public, Environmental & Occupational Health