In the US, childhood obesity has reached epidemic proportions, with approximately a third of the current population identified as overweight or obese. There are of course many increased health risks associated with this condition (e.g., diabetes, CVD). Students in New York City schools are no exception, following the overall populaton trend. Policies to combat obesity in children include integrating educational materials into classroom instruction and improving the food served in cafeterias within schools (some students eat two meals per day at school). However, students spend substantial time outside of the school environment, and it is unclear how the “food environment” near the student’s home and proximate to the school are related to childhood obesity.

In this study, we make use of multiple datasets that provide a comprehensive inventory of food establishments in New York City and link these to student residences and schools. Building a map of the food environment, we document the relationship between this environment and a normalized student Body Mass Index (BMI) over the academic years 2009-2013. Initial multilevel models partition the total variation into student, school and census tract (neighborhood) components, explaining a small percentage of these via student demographics and the school and home food environment. The effects associated with Fast Food and Bodega (“Shops”) Establishments appear to warrant further investigation.

Making use of a natural quasi-experiment, in which the majority of students change schools in the transition to middle and high school, we evaluate whether changes in this environment are associated with changes in BMI, net of other factors. A student—level change (first difference) model apportions the covariate effects into between- and within-school components (a so-called “hybrid” model), and the remaining unexplained variance is captured via random effects. The conditions needed for a plausible causal interpretation of effects are discussed. Given the size of the school population and the costs associated with new initiatives, the magnitude of the effects associated with changes in the food environment near schools are subjected to a sensitivity analysis using software developed by the authors as part of a related methodological research effort.