The literature on neighborhoods and health highlights the difficulty of operationalizing "neighborhood" in a conceptually and empirically valid manner. Most studies, however, continue to define neighborhoods using less theoretically relevant boundaries, risking erroneous inferences from poor measurement. We review an innovative methodology to address this problem, called the socio-spatial neighborhood estimation method (SNEM). To estimate neighborhood boundaries, researchers used a theoretically informed combination of qualitative GIS and on-the-ground observations in Texas City, Texas. Using data from a large sample, we assessed the SNEM-generated neighborhood units by comparing intra-class correlation coefficients (ICCs) and multi-level model parameter estimates of SNEM-based measures against those for census block groups and regular grid cells. ICCs and criterion-related validity evidence using SF-36 outcome measures indicate that the SNEM approach to operationalization could improve inferences based on neighborhoods and health research.
ASJC Scopus subject areas
- Public Health, Environmental and Occupational Health
- Geography, Planning and Development
- Health(social science)