ABSTRACT
Since the early 1980s, obesity has become a major health issue in the United States. Here, we develop a GIS-based agent-based model to studying the prevalence of obesity in selected populations and districts in San Diego, California. This model allows for the explicit representation of individual health behavior, the incorporation of the influence of social networks on physical activity, and the spatially heterogeneous depiction of urban form in which the individuals operate. Based on our computational experiments, we conclude that the selected geographic factors play a substantial role in the spatiotemporal variability of individual weight measured with the body mass index.
