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Epidemiology, Big Data and Precision Medicine
Session Title: Regional and National Trends in Cardiovascular Health in the United States

Abstract 12637: Sociodemographic Measures and Disparities in Obesity in US Rural vs Nonrural Counties, 2004-2019

Originally publishedCirculation. 2023;148:A12637

    Introduction: US rural, compared with nonrural, counties have a higher burden of CVD. Obesity is a major CVD risk factor with 40% prevalence in adults. However, the rural-nonrural disparities in obesity are incompletely described. We aimed to evaluate differences in prevalence of obesity by county-level rurality.

    Methods: We used CDC county-level data for adults aged ≥20 years, 2004–2019, available for 97.6% of US counties (n=3148/3226). CDC defined obesity (body mass index ≥30 kg/m2) using self-reported weight and height. Rurality was based on six levels from large central metro (most urban) to noncore (most rural). We compared prevalence by rurality level using weighted least squares regression, adjusting for 13 county-level sociodemographic measures, and reported prevalence ratios (95% CI).

    Results: Counties with increasing rurality reflected older populations, as indicated by higher median age (from 35.6 years to 42.4 years). Also, increasing rurality was associated with differences in income and proportion uninsured. In age and sex ratio adjusted analysis (model 1), obesity prevalence was 1.05- to 1.06-fold higher in medium metro, small metro, and micropolitan counties compared with large central metro counties (global test, P<.001). With further adjustment for sociodemographic measures (model 2; model 1 covariates plus race, state, income, proportion uninsured) these relative differences were preserved but attenuated (each 1.03-fold higher), while a greater difference was revealed for large fringe metro (1.06-fold higher) counties. In both models, differences in obesity prevalence between noncore and large central metro counties were minimal. (Table)

    Conclusion: Counties with intermediate rurality were associated with higher obesity prevalence. The association was partly accounted for by nonmodifiable and modifiable sociodemographic measures, which may be targeted to reduce rural-nonrural disparities in obesity.


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