Integrating GIS and Modeling methods to enhance community & school childhood obesity interventions

Introduction: Obesity is at epidemic proportions in our nation, and obesity among children has long ranging consequences.  A realistic, agent-based simulation, using predictive models, can improve understanding of such public health problems and explore the possible outcome of various interventions

Approach: We develop a dynamic framework that integrates geospatial technologies with Agent Based Modeling (ABM) to enable exploration of complex public health problems (here, the nutrition of adolescents) and the possible effects of specific interventions.   Such modeling methods support better decision making and enhances public policies.  

Results: We generated a model that simulates children walking/riding to and from school along optimal routes.  The model incorporates geospatial layers (streets, homes, corner stores locations) as well as child food consumption behaviors as they encounter corner stores. Within the ABM framework, children make decisions every time they interact with other agents, including peers and corner stores.   Our model identifies the location of corner stores have a significant impact on consumption of empty calories and the overall nutritional health of adolescents. We examine simulating the impact of providing a healthy snack at the end of the school day and compare results of empty calorie consumption before and after this intervention. 

Discussion /Conclusions  The integration of GIS and ABM technologies provides an opportunity to examine nutritional behaviors within a changing social and physical environment, and the impact of school or community policies over time in a cost-effective manner.  We will also discuss the ABM framework, its strengths and limitations, and research recommendations.