Neighborhood Characteristics of Alcohol-Related Pedestrian Injury Collisions: A Geostatistical Analysis
- Cite this article as:
- LaScala, E.A., Johnson, F.W. & Gruenewald, P.J. Prev Sci (2001) 2: 123. doi:10.1023/A:1011547831475
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This study conducted a geostatistical analysis of ecological data to examine the relationships of neighborhood characteristics, including alcohol availability and alcohol consumption patterns to pedestrian injury collisions. The central research question asked whether it was possible to identify unique neighborhood characteristics related to alcohol- and non–alcohol-involved pedestrian injuries. It was hypothesized that greater numbers of alcohol-involved pedestrian injuries would be observed in areas with greater concentrations of alcohol outlets, even after adjusting for socioeconomic characteristics, environmental factors, and drinking patterns of neighborhood residents. It was also hypothesized that independent of drinking patterns and alcohol availability, greater numbers of pedestrian injuries would be observed in areas with higher unemployment, lesser income, greater population, and a predominance of younger or older age populations. Archival and individual-level data from a general population telephone survey were obtained from four California communities. The survey data included sociodemographic and drinking pattern measures. Archival data included environmental measures relevant to pedestrian travel and measures of alcohol availability. Units of analysis were geographic areas within each community defined by the spatial clustering of telephone survey respondents. The results showed that alcohol-involved pedestrian collisions occurred more often in areas with greater bar densities and greater population, and where the local population reported drinking more alcohol per drinking occasion. Pedestrian collisions not involving alcohol occurred more often in lower income areas with greater population and cross-street densities, and in areas having either younger or older age populations. The identification of neighborhood variables associated with pedestrian collisions has important implications for policy formation and targeted prevention efforts.