Analysis of Geographic, Temporal, and Socioeconomic Shifts in Pedestrian & Bicyclist Traffic Injuries
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2025-06-01
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Edition:Final Report (June 2025)
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Abstract:We used quantitative and qualitative methods to explore shifts in fatal and severe (FSI) pedestrian injuries and FSI bicyclist injuries since 2008. We gathered police-reported crash data for more than 20,000 census tracts across eight states during 2008- 2012 and 2017-2021. We developed negative binomial and Poisson-Gamma conditional autoregressive models to analyze neighborhood-level factors associated with changes in FSI pedestrian and FSI bicyclist injuries. FSI pedestrian crashes were positively associated with certain neighborhood characteristics in both periods: larger proportions of Black, Hispanic, or low- income populations; higher unemployment rates; higher proportions of retail jobs; having transit nearby; and containing at least one high-traffic arterial roadway. FSI bicyclist crashes were positively associated with higher shares of Black residents; lower incomes; higher unemployment rates; higher proportions of retail jobs; higher population and employment densities; close proximity to transit stops; and at least one high-volume arterial roadway. Certain neighborhood crash disparities became more prominent over time. We also interviewed 13 practitioners to provide insights about local changes in pedestrian and bicyclist safety outcomes during the 2010s. These interviews suggested that increases in pedestrian and bicyclist fatalities may be related to shifts of pedestrian and bicyclist activity to higher-risk parts of urban regions, reduced traffic enforcement potentially leading to higher vehicle speeds and more reckless driving, and automobile-oriented roadways. Recognizing study limitations, information in this report will help practitioners understand policies and other actions that may have the greatest potential to prevent pedestrian and bicyclist injuries in the future.
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Main Document Checksum:urn:sha-512:8c5133d67effb1b35d9f614ecea762e0b80c5505363f8a0b754d7832fde3dc0cccae825289ba4c2de23a38739e8d9ef1b2e9b70a753efc30a7136fbaa2e5da3a