In this research, we evaluated the relationship between obesity rates and altitude using a cross-county study design. We applied a geographically weighted regression (GWR) to examine the spatially varying association between adult obesity rates and altitude after adjusting for four predictor variables including physical activity. A significant negative relationship between altitude and adult obesity rates were found in the GWR model. Our GWR model fitted the data better than OLS regression (R2 = 0.583), as indicated by an improved R2 (average R2 = 0.670; range: 0.26-0.77) and a lower Akaike Information Criteria (AIC) value (14,736.88 vs. 15,386.59 in the OLS model). These approaches, evidencing spatial varying associations, proved very useful to refine interpretations of the statistical output on adult obesity. This study underscored the geographic variation in relationships between adult obesity rates and mean county altitude in the United States. Our study confirmed a varying overall negative relationship between county-level adult obesity rates and mean county altitude after taking other confounding factors into account.
Keywords: Adult obesity; altitude; geographically weighted regression; health geography.