title: A Closer Look at Rural-Urban Health Disparities: Associations Between Obesity and Rurality Vary by Geospatial and Sociodemographic Factors.
abstract: Obesity affects over one-third of older adults in the United States. Both aging and obesity contribute to an increased risk for chronic disease, early mortality, and additional health care utilization. Obesity rates are higher in rural areas than in urban areas, although findings are mixed. The objectives of this study are to assess potential nonlinearity in the association between rurality and obesity, and to evaluate the potential for socioeconomic status and geographic area to moderate the associations between rurality and obesity.
  
  
  
  Using a representative sample of adults aged 65 and above from the Behavioral Risk Factor Surveillance System, obesity (BMI ≥ 30 kg/m2) was modeled against the primary exposure of rural-urban status, as measured by the Index of Relative Rurality. Binary logistic regression models were used to estimate the odds of obesity by rurality both as a continuous variable and by decile of rurality. Models were then stratified by per-capita income and state to assess potential moderation by these factors.
  
  
  
  The prevalence of obesity in older adults was highest in intermediate rurality areas (OR in rurality decile #5 1.134, 95% CI: 1.086-1.184) and lowest in the most rural and most urban areas. Obesity was highest in low- and middle-income areas, regardless of rural-urban status. In high-income areas, obesity among older adults was highest in areas of intermediate rurality and lowest in the most rural areas (OR 0.726, 95% CI: 0.606-0.870) and more urban areas, showing a J-shaped association. There were substantial differences in the associations between rurality and obesity in older adults among states.
  
  
  
  Associations between rurality and obesity varied by degree of rurality, socioeconomic status, and geography. Therefore, traditional "one-size-fits-all" approaches to reducing rural-urban health disparities in older adults may be more effective if tailored to the area-specific rural-urban gradients in health.
authors.affiliation: Health Studies Program, Department of Kinesiology, University of Rhode Island, Kingston, Rhode Island.
authors.forename: Steven A
authors.initials: SA
authors.lastname: Cohen
authors.affiliation: Center on Society and Health, Virginia Commonwealth University School of Medicine, Richmond, Virginia.
authors.forename: Sarah K
authors.initials: SK
authors.lastname: Cook
authors.affiliation: Center on Society and Health, Virginia Commonwealth University School of Medicine, Richmond, Virginia.|Division of Epidemiology,  Department of Family Medicine and Population Health, Virginia Commonwealth University, Richmond, Virginia.
authors.forename: Lauren
authors.initials: L
authors.lastname: Kelley
authors.affiliation: Division of Epidemiology,  Department of Family Medicine and Population Health, Virginia Commonwealth University, Richmond, Virginia.
authors.forename: Julia D
authors.initials: JD
authors.lastname: Foutz
authors.affiliation: Division of Epidemiology,  Department of Family Medicine and Population Health, Virginia Commonwealth University, Richmond, Virginia.
authors.forename: Trisha A
authors.initials: TA
authors.lastname: Sando
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D015992:Body Mass Index; D016009:Chi-Square Distribution; D005260:Female; D062305:Geographic Mapping; D054625:Healthcare Disparities / Q000639:trends*; D006801:Humans; D016015:Logistic Models; D008297:Male; D009765:Obesity / Q000453:epidemiology*; D015995:Prevalence; D012424:Rural Population / Q000706:statistics & numerical data; D012959:Socioeconomic Factors; D011795:Surveys and Questionnaires; D014481:United States; D014505:Urban Population / Q000706:statistics & numerical data
keywords: elderly; health disparities; obesity; rurality; socioeconomic status