Journal article
Multilevel models for evaluating the risk of pedestrian–motor vehicle collisions at intersections and mid-blocks
Accident analysis and prevention, v 84, pp 99-111
01 Nov 2015
PMID: 26339944
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
•Novel spatiotemporal estimate of pedestrian collision rates citywide.•Spatiotemporal model estimated risk at intersections and mid-blocks.•Crosswalks and traffic signals had higher rates accounting for pedestrian activity.•One-way streets and pedestrian warning signs had lower pedestrian collision rates.•Rates were lower in more walkable areas (higher intersection density).
Walking is a popular form of physical activity associated with clear health benefits. Promoting safe walking for pedestrians requires evaluating the risk of pedestrian–motor vehicle collisions at specific roadway locations in order to identify where road improvements and other interventions may be needed. The objective of this analysis was to estimate the risk of pedestrian collisions at intersections and mid-blocks in Seattle, WA. The study used 2007–2013 pedestrian–motor vehicle collision data from police reports and detailed characteristics of the microenvironment and macroenvironment at intersection and mid-block locations. The primary outcome was the number of pedestrian–motor vehicle collisions over time at each location (incident rate ratio [IRR] and 95% confidence interval [95% CI]). Multilevel mixed effects Poisson models accounted for correlation within and between locations and census blocks over time. Analysis accounted for pedestrian and vehicle activity (e.g., residential density and road classification). In the final multivariable model, intersections with 4 segments or 5 or more segments had higher pedestrian collision rates compared to mid-blocks. Non-residential roads had significantly higher rates than residential roads, with principal arterials having the highest collision rate. The pedestrian collision rate was higher by 9% per 10 feet of street width. Locations with traffic signals had twice the collision rate of locations without a signal and those with marked crosswalks also had a higher rate. Locations with a marked crosswalk also had higher risk of collision. Locations with a one-way road or those with signs encouraging motorists to cede the right-of-way to pedestrians had fewer pedestrian collisions. Collision rates were higher in locations that encourage greater pedestrian activity (more bus use, more fast food restaurants, higher employment, residential, and population densities). Locations with higher intersection density had a lower rate of collisions as did those in areas with higher residential property values. The novel spatiotemporal approach used that integrates road/crossing characteristics with surrounding neighborhood characteristics should help city agencies better identify high-risk locations for further study and analysis. Improving roads and making them safer for pedestrians achieves the public health goals of reducing pedestrian collisions and promoting physical activity.
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Details
- Title
- Multilevel models for evaluating the risk of pedestrian–motor vehicle collisions at intersections and mid-blocks
- Creators
- D. Alex Quistberg - University of WashingtonEric J. Howard - University of WashingtonBeth E. Ebel - University of WashingtonAnne V. Moudon - University of WashingtonBrian E. Saelens - University of WashingtonPhilip M. Hurvitz - University of WashingtonJames E. Curtin - Seattle Department of Transportation, Seattle Municipal Tower, P.O. Box 34996, 700 Fifth Avenue, Suite 3800, Seattle, WA 98124-4996, USAFrederick P. Rivara - University of Washington
- Publication Details
- Accident analysis and prevention, v 84, pp 99-111
- Publisher
- Elsevier
- Number of pages
- 13
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Urban Health Collaborative; Environmental and Occupational Health
- Web of Science ID
- WOS:000363348000012
- Scopus ID
- 2-s2.0-84940571617
- Other Identifier
- 991021966369704721
UN Sustainable Development Goals (SDGs)
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Source: SDGs in the Output
InCites Highlights
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- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Ergonomics
- Public, Environmental & Occupational Health
- Social Sciences, Interdisciplinary
- Transportation