Mark Braza1, Wendy Shoemaker, Anne Seeley. 1. Center for Design, Methods, and Analysis, US Government Accountability Office, Washington, DC 20548, USA. BrazaM@gao.gov
Abstract
PURPOSE: This study evaluates the relationship between neighborhood design and rates of students walking and biking to elementary school. DESIGN: Pairwise correlations and multiple regression models were estimated based on a cross-sectional study of elementary schools and their surrounding neighborhoods. Setting and Subjects. Thirty-four (23%) of 150 California public elementary schools holding October 1999 Walk to School Day events participated in the study. MEASURES: Teachers asked fifth-grade students how they arrived to school 1 week before Walk to School Day. 1990 U.S. Census data measured population density and number of intersections per street mile, whereas 1998-1999 California Department of Education data measured school size, the percentage of students receiving public welfare, and the percentage of students of various ethnicities. RESULTS: Population density (p = .000) and school size (p = .053) were significantly associated with walking and biking rates in regression models controlling for number of intersections per street mile, the percentage of students receiving public welfare, and the percentage of students of various ethnicities. The number of intersections per street mile was associated with walking and biking rates in pairwise correlations (p = .003) but not in regression models. CONCLUSIONS: The results support the hypothesis that the walking and biking rates are higher in denser neighborhoods and to smaller schools but do not support the hypothesis that rates are higher in neighborhoods with a high number of intersections per street mile. We suggest that detailed data for a larger sample of students would allow statistical models to isolate the effect of specific design characteristics.
PURPOSE: This study evaluates the relationship between neighborhood design and rates of students walking and biking to elementary school. DESIGN: Pairwise correlations and multiple regression models were estimated based on a cross-sectional study of elementary schools and their surrounding neighborhoods. Setting and Subjects. Thirty-four (23%) of 150 California public elementary schools holding October 1999 Walk to School Day events participated in the study. MEASURES: Teachers asked fifth-grade students how they arrived to school 1 week before Walk to School Day. 1990 U.S. Census data measured population density and number of intersections per street mile, whereas 1998-1999 California Department of Education data measured school size, the percentage of students receiving public welfare, and the percentage of students of various ethnicities. RESULTS: Population density (p = .000) and school size (p = .053) were significantly associated with walking and biking rates in regression models controlling for number of intersections per street mile, the percentage of students receiving public welfare, and the percentage of students of various ethnicities. The number of intersections per street mile was associated with walking and biking rates in pairwise correlations (p = .003) but not in regression models. CONCLUSIONS: The results support the hypothesis that the walking and biking rates are higher in denser neighborhoods and to smaller schools but do not support the hypothesis that rates are higher in neighborhoods with a high number of intersections per street mile. We suggest that detailed data for a larger sample of students would allow statistical models to isolate the effect of specific design characteristics.
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