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AJPH First Look, published online ahead of print Jul 16, 2009
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AJPH.2007.131961v1
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September 2009, Vol 99, No. 9 | American Journal of Public Health 1632-1637
© 2009 American Public Health Association
DOI: 10.2105/AJPH.2007.131961

RESEARCH AND PRACTICE

Environmental Characteristics Associated With Pedestrian–Motor Vehicle Collisions in Denver, Colorado

Anne K. Sebert Kuhlmann, PhD, John Brett, PhD, Deborah Thomas, PhD and Stephan R. Sain, PhD

At the time of the study, Anne K. Sebert Kuhlmann was with the Health and Behavioral Sciences Program, University of Colorado Denver. John Brett was with the Department of Anthropology, University of Colorado Denver. Deborah Thomas was with the Department of Geography and Environmental Sciences, University of Colorado Denver. Stephan R. Sain was with the Department of Mathematics, University of Colorado Denver.

Correspondence: Correspondence should be sent to John Brett, PhD, Department of Anthropology, University of Colorado Denver, Campus Box 103, P. O. Box 173364, Denver, CO 80217-3364 (e-mail: John.Brett{at}ucdenver.com). Reprints can be ordered at http://www.ajph.org by clicking on the "Reprints/Eprints" link.

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.






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