Abstract 13149: Sociodemographic Factors and Prevalence in Physical Inactivity: Analysis of Rural and Non-Rural Counties in the United States, 2004-2019

Introduction: US rural areas have a disproportionate burden of CVD and hypertension. Physical inactivity is a major risk factor, with 25% prevalence in US adults. However, rural disparities in physical inactivity are incompletely described. The aim was to evaluate differences in prevalence of physical inactivity based on 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 physical inactivity as self-reported lack of leisure time physical activity in the month preceding the survey. Rurality was based on six categories ordered from least rural (large central metro) to most rural (noncore). We used weighted least squares regression to compare prevalence by rurality level, adjusting for 13 county-level sociodemographic factors; results reported as prevalence ratios (95% CI) with partial F -tests and P -values.

Results: In age and sex ratio adjusted analysis (model 1), we observed a gradient in the prevalence of physical inactivity across levels of rurality, with significantly higher rates in small metro (1.03 [1.00–1.06]), micropolitan (1.05 [1.02–1.07]), and noncore (1.05 [1.02–1.08]) compared with large central metro counties ( F -statistic=7.5; P <.001). With further adjustment for other sociodemographic factors (model 2), the relative differences were negated in noncore counties (0.99 [0.97-1.02]), attenuated in intermediate counties, and accentuated in large fringe metro counties (1.06 [1.04-1.08]) ( F -statistic=14.3; P <.001). Further adjustment for obesity (model 3) largely attenuated the association of rurality with physical inactivity, resulting in no significant differences relative to large central metro counties ( F -statistic=4.8; P <.001).

Conclusions: County-level rurality was associated with prevalence of physical inactivity. These disparities were largely accounted for by obesity, which may be targeted for intervention.