An in-depth analysis of self-reported cycling injuries in single and multiparty bicycle crashes in Denmark. (June 2021)

• Record Type: Journal Article
• Authors: Hosseinpour, Mehdi; Madsen, Tanja Kidholm Osmann; Olesen, Anne Vingaard; Lahrmann, Harry
• Is Part Of: Journal of safety research. Volume 77(2021)
• Page Start: 114
• Page End: 124
• Publication Date: 2021-06
• Subjects: Bicycle crashes -- Injury severity -- Self-reported crashes -- Crash type -- Multilevel logistic model; Industrial safety -- Periodicals; Accidents -- Prevention -- Periodicals; Safety -- Periodicals; Accidents, Occupational -- Periodicals; Sécurité du travail -- Périodiques; Accidents -- Prévention -- Périodiques; Accidents -- Prevention; Industrial safety; Periodicals; 363.1
• DOI: 10.1016/j.jsr.2021.02.009
• Languages: English
• ISSNs: 0022-4375

Abstract

Highlights: Cyclist injury severity is analyzed using self-reporting crash data. Separate multilevel logit models are developed for single and multiparty bicycle crashes. Single bicycle crashes result in more serious injuries than multiparty bicycle crashes. The separate models of single and multiparty crashes are favored to the overall model. Different risk factors are associated with cyclist injury severity in single and multiparty crashes. Abstract: Introduction: Cycling is one of the main forms of transportation in Denmark. However, while the number of traffic crash fatalities in the country has decreased over the past decade, the frequency of cyclists killed or seriously injured has increased. The high rate of serious injuries and fatalities associated with cycling emphasizes the increasing need for mitigating the severity of such crashes. Method: This study conducted an in-depth analysis of cyclist injury severity resulting from single and multiparty bicycle-involved crashes. Detailed information was collected using self-reporting data undertaken in Denmark for a 12-month period between 1 November 2012 and 31 October 2013. Separate multilevel logistic (MLL) regression models were applied to estimate cyclist injury severity for single and multiparty crashes. The goodness-of-fit measures favored the MLL models over the standard logistic models, capturing the intercorrelation among bicycle crashes that occurred in the same geographical area. Results: The results also showed that single bicycle-involved crashes resulted in more serious outcomes when compared to multiparty crashes. For both single and multiparty bicycle crash categories, non-urban areas were associated with more serious injury outcomes. For the single crashes, wet surface condition, autumn and summer seasons, evening and night periods, non-adverse weather conditions, cyclists aged between 45 and 64 years, male sex, riding for the purpose of work or educational activities, and bicycles with light turned-off were associated with severe injuries. For the multiparty crashes, intersections, bicycle paths, non-winter season, not being employed or retired, lower personal car ownership, and race bicycles were directly related to severe injury consequences. Practical Applications: The findings of this study demonstrated that the best way to promote cycling safety is the combination of improving the design and maintenance of cycling facilities, encouraging safe cycling behavior, and intensifying enforcement efforts.