OBJECTIVES: We examined patterns of pedestrian-motor vehicle collisions and associated environmental characteristics in Denver, Colorado. METHODS: We integrated publicly available data on motor vehicle collisions, liquor licenses, land use, and sociodemographic characteristics to analyze spatial patterns and other characteristics of collisions involving pedestrians. We developed both linear and spatially weighted regression models of these collisions. RESULTS: Spatial analysis revealed global clustering of pedestrian-motor vehicle collisions with concentrations in downtown, in a contiguous neighborhood, and along major arterial streets. Walking to work, population density, and liquor license outlet density all contributed significantly to both linear and spatial models of collisions involving pedestrians and were each significantly associated with these collisions. CONCLUSIONS: These models, constructed with data from Denver, identified conditions that likely contribute to patterns of pedestrian-motor vehicle collisions. Should these models be verified elsewhere, they will have implications for future research directions, public policy to enhance pedestrian safety, and public health programs aimed at decreasing unintentional injury from pedestrian-motor vehicle collisions and promoting walking as a routine physical activity.
OBJECTIVES: We examined patterns of pedestrian-motor vehicle collisions and associated environmental characteristics in Denver, Colorado. METHODS: We integrated publicly available data on motor vehicle collisions, liquor licenses, land use, and sociodemographic characteristics to analyze spatial patterns and other characteristics of collisions involving pedestrians. We developed both linear and spatially weighted regression models of these collisions. RESULTS: Spatial analysis revealed global clustering of pedestrian-motor vehicle collisions with concentrations in downtown, in a contiguous neighborhood, and along major arterial streets. Walking to work, population density, and liquor license outlet density all contributed significantly to both linear and spatial models of collisions involving pedestrians and were each significantly associated with these collisions. CONCLUSIONS: These models, constructed with data from Denver, identified conditions that likely contribute to patterns of pedestrian-motor vehicle collisions. Should these models be verified elsewhere, they will have implications for future research directions, public policy to enhance pedestrian safety, and public health programs aimed at decreasing unintentional injury from pedestrian-motor vehicle collisions and promoting walking as a routine physical activity.
Authors: Patrick Morency; Lise Gauvin; Céline Plante; Michel Fournier; Catherine Morency Journal: Am J Public Health Date: 2012-04-19 Impact factor: 9.308
Authors: D Alex Quistberg; Thomas D Koepsell; J Jaime Miranda; Linda Ng Boyle; Brian D Johnston; Beth E Ebel Journal: Traffic Inj Prev Date: 2014-11-10 Impact factor: 1.491
Authors: Linda Rothman; Alison Macpherson; Ron Buliung; Colin Macarthur; Teresa To; Kristian Larsen; Andrew Howard Journal: BMC Public Health Date: 2015-08-12 Impact factor: 3.295