Publication

County-level contextual factors associated with diabetes incidence in the United States

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Last modified
  • 05/15/2025
Type of Material
Authors
    Solveig A. Cunningham, Emory UniversityShivani Patel, Emory UniversityGloria L. Beckles, Centers for Disease Control and PreventionLinda S. Geiss, Centers for Disease Control and PreventionNeil Mehta, Emory UniversityHui Xie, Centers for Disease Control and PreventionGiuseppina Imperatore, Centers for Disease Control and Prevention
Language
  • English
Date
  • 2018-01-01
Publisher
  • Elsevier: 12 months
Publication Version
Copyright Statement
  • © 2017 Elsevier Inc.
License
Final Published Version (URL)
Title of Journal or Parent Work
ISSN
  • 1047-2797
Volume
  • 28
Issue
  • 1
Start Page
  • 20
End Page
  • 25
Grant/Funding Information
  • Neil Mehta was supported by the National Institute on Aging [grant number R01-AG040212].
  • Shivani Patel and Neil Mehta were supported by funding from the Robert Wood Foundation [grant number 70769].
Abstract
  • Purpose: Health and administrative systems are facing spatial clustering in chronic diseases such as diabetes. This study explores how geographic distribution of diabetes in the United States is associated with socioeconomic and built environment characteristics and health-relevant policies. Methods: We compiled nationally representative county-level data from multiple data sources. We standardized characteristics to a mean = 0 and a SD = 1 and modeled county-level age-adjusted diagnosed diabetes incidence in 2013 using 2-level hierarchical linear regression. Results: Incidence of age-standardized diagnosed diabetes in 2013 varied across U.S. counties (n = 3109), ranging from 310 to 2190 new cases/100,000, with an average of 856.4/100,000. Socioeconomic and health-related characteristics explained ∼42% of the variation in diabetes incidence across counties. After accounting for other characteristics, counties with higher unemployment, higher poverty, and longer commutes had higher incidence rates than counties with lower levels. Counties with more exercise opportunities, access to healthy food, and primary care physicians had fewer diabetes cases. Conclusions: Features of the socioeconomic and built environment were associated with diabetes incidence; identifying the salient modifiable features of counties can inform targeted policies to reduce diabetes incidence.
Author Notes
  • Corresponding Author: Solveig A. Cunningham; Hubert Department of Global Health, Rollins School of Public Health, Emory University; 1518 Clifton Road; Atlanta GA 30322; tel.: 404-727-6486; sargese@emory.edu.
Keywords
Research Categories
  • Sociology, Public and Social Welfare
  • Health Sciences, Public Health

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