The geographic concentration of us adult obesity prevalence and associated social, economic, and environmental factors

Authors


  • Disclosure: The authors have no competing interests.

  • Author Contributions: Slack and Myers had full access to all of the data in the study and take responsibility for the accuracy of the analysis. Study concept and design. Slack, Myers, Martin, Heymsfield. Acquisition of data. Myers. Analysis and interpretation of data. Slack, Myers. Drafting the manuscript. Slack, Myers, Martin, Heymsfield. Critical revision of the manuscript for important intellectual content. Slack, Myers, Martin, Heymsfield.

Abstract

Objective

This study used spatial statistical methods to test the hypotheses that county-level adult obesity prevalence in the United States is (1) regionally concentrated at significant levels, and (2) linked to local-level factors, after controlling for state-level effects.

Methods

Data were obtained from the Centers for Disease Control and Prevention and other secondary sources. The units of analysis were counties. The dependent variable was the age-adjusted percentage of adults who were obese in 2009 (body mass index >30 kg/m2).

Results

The prevalence of county-level obesity varied from 13.5% to 47.9% with a mean of 30.3%. Obesity prevalence across counties was not spatially random: 15.8% belonged to high-obesity regions and 13.5% belonged to low-obesity regions. Obesity was positively associated with unemployment, outpatient healthcare visits, physical inactivity, female-headed families, black populations, and less education. Obesity was negatively correlated with physician numbers, natural amenities, percent ≥65 years, Hispanic populations, and larger population size. A number of variables were notable for not reaching significance after controlling for other factors, including poverty and food environment measures.

Conclusions

The findings demonstrate the importance of local-level factors in explaining geographic variation in obesity prevalence, and thus hold implications for geographically targeted interventions to combat the obesity epidemic.

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