Steve Mooney, one of our recently minted PhD’s, won a best poster presentation award at the 2016 Epidemiology Congress of the Americas for his work on the “Neighborhood Environment-Wide Association Study” design.
New spatial tools and the expanding availability of spatially referenced data allow researchers to characterize study subjects’ neighborhood environments more completely in terms of social, built, compositional, business and economic factors. Furthermore, through GIS tools and spatial analytic approaches, researchers are moving beyond zip codes and Census geometries and are defining neighborhoods in creative new ways. With more data, at more spatial resolutions, and with a myriad ways to define neighborhood, researchers can characterize study subjects’ residential, work and activity space environments in high-dimensional space, efficiently creating 1,000s of variables that describe aspects of the neighborhood environment. Drawing an analogy with genomic research, Dr. Mooney and colleagues proposed the ‘Neighborhood Environment-Wide Association Study’ (or NE-WAS) as one approach to address this richness and complexity of data. His original writing on this idea is here.
The GWAS to NE-WAS analogy
Dr. Mooney’s poster, available as a PDF here, explored the potential to apply theory-agnostic empirical data analysis approaches (NE-WAS, LASSO and Random Forest analyses) to finding the neighborhood characteristics most predictive of physical activity among older adults in the NYCNAMES-II cohort.
