Use of city-archival data to inform dimensional structure of neighborhoods.

A growing body of research has explored the impact of neighborhood residence on child and adolescent health and well-being. Most previous research has used the US Census variables as the measures of neighborhood ecology, although informative census data are not designed to represent the sociological and structural features that characterize neighborhoods. Alternatively, this study explored the use of large-city administrative data and geographical information systems to develop more uniquely informative empirical dimensions of neighborhood context. Exploratory and confirmatory structural analyses of geographically referenced administrative data aggregated to the census-block group identified three latent dimensions: social stress, structural decline, and neighborhood crime. Resultant dimensions were compared through canonical regression to those derived from US Census data. The relative explanatory capacity of the city-archival and census dimensions was assessed through multilevel linear modeling to predict standardized reading and mathematics achievement of 31,742 fifth- and 28,922 eight-grade children. Results indicated that the city-archival dimensions uniquely augmented predictions, and the combination of city and census dimensions explained significantly more neighborhood effects on achievement than did either source of neighborhood information independently.