The Geography of Obesity: Predicting Obesity Rates in California Based on Access to Health Care

Health outcomes vary on a small scale; therefore, national level statistics inaccurately represent the true health of U.S. citizens. In order to get a better idea of why such variation exists, this paper looks at how geography affects county level obesity rates in California. County level obesity rates are predicted using an OLS regression that includes not only health predictors and socioeconomic variables, but also variables representing distance to health clinics and the emphasis on primary care in each county. The results ultimately show that distance to health facilities is significant in predicting obesity rates, and that more urbanized areas, with higher densities of clinics and doctors, are likely to have the lowest obesity rates.