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Cyclist Injury Severity in Spain: A Bayesian Analysis of Police Road Injury Data Focusing on Involved Vehicles and Route Environment

Abstract: This study analyses factors associated with cyclist injury severity, focusing on vehicle type, route environment, and interactions between them. Data analysed was collected by Spanish police during 2016 and includes records relating to 12,318 drivers and cyclist involving in collisions with at least one injured cyclist, of whom 7230 were injured cyclists. Bayesian methods were used to model relationships between cyclist injury severity and circumstances related to the crash, with the outcome variable being whether a cyclist was killed or seriously injured (KSI) rather than slightly injured. Factors in the model included those relating to the injured cyclist, the route environment, and involved motorists. Injury severity among cyclists was likely to be higher where an Heavy Goods Vehicle (HGV) was involved, and certain route conditions (bicycle infrastructure, 30 kph zones, and urban zones) were associated with lower injury severity. Interactions exist between the two: collisions involving large vehicles in lower-risk environments are less likely to lead to KSIs than collisions involving large vehicles in higher-risk environments. Finally, motorists involved in a collision were more likely than the injured cyclists to have committed an error or infraction. The study supports the creation of infrastructure that separates cyclists from motor trac. Also, action needs to be taken to address motorist behaviour, given the imbalance between responsibility and risk.

 Fuente: International Journal of Environmental Research and Public Health 2020, 17(1), 96

 Editorial: MDPI

 Fecha de publicación: 01/01/2020

 Nº de páginas: 16

 Tipo de publicación: Artículo de Revista

 DOI: 10.3390/ijerph17010096

 ISSN: 1661-7827,1660-4601

 Proyecto español: BU300P18

Autoría

ALDRED, RACHEL

GARCÍA-HERRERO, SUSANA

ANAYA, ESTHER

MARISCAL, MIGUEL ÁNGEL