Spatial Convergence of US Obesity Rates and Its Determinants

This article quantifies the importance of demographic and food environment variables in determining the convergence rates for obesity incidence across the U.S. Using a spatial autoregressive model with county level data for 2004-2012, a period of rapid spread of obesity in the U.S., to estimate 𝛽- and 𝜎convergence rates; then we estimate a probit model to assess their determinants. Empirical results show 𝛽-convergence and 𝜎-convergence occurred in the US and its four regions in 2004-2012. The Northeast and the West have the highest speed of convergence in years 2008-2012. It was also found that 𝛽convergence doesn’t occur in counties in metro area in 2004-2012 and 2008-2012. The convergence rate is the largest in completely rural counties and consistently higher for men compared to women. A second-step probit regression shows that states with higher Hispanic proportion, higher availability of fruit and vegetables stores and full-service restaurants are less likely to have 𝛽-convergence, while states with higher poverty rates and sex ratio are more likely to have 𝛽-convergence. It also shows 𝜎-convergence is more likely to happen in states with a higher proportion of Hispanics and higher availability of fruit and vegetables.