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Abstract
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PURPOSE
Understanding bicycle-vehicle collisions that result in hit-and-run (HAR) behavior is an important concern for multiple disciplines, such as public health, transportation safety, enforcement, and affected individuals. If bicyclists are injured, this issue has implications for expedient access to medical care and for protection from the financial burden of associated injury and property costs. This study aimed to identify significant predictors of vehicle-bicycle HARs, the results of which help inform interdisciplinary prevention interventions.
Method
Data were collected from Boston Police Department bicycle collision reports for 2009-2012. The data identified whether a collision was a HAR and other predictor variables including road and bicyclist characteristics. The probability of a HAR was fit to selected variables through logistic regression models. Effects of the predictors were reported as odds ratios.
Results
Police reported data from Boston, Massachusetts were examined for the years 2009 to 2012. Of the 1646 bike-vehicle collisions, 6% (n=93) resulted in a HAR and 80% (n=1309) involved an injury to the bicyclist. Controlling for all other variables, the odds of a HAR did not differ when the bicyclist was injured versus not injured or male versus female. The odds of a HAR were 2.40 (95% CI: 1.31, 4.23) times more likely when the vehicle was a taxi versus another type of vehicle, 1.65 (95% CI: 1.08, 2.54) times more likely during night as during daylight hours, and 1.74 (95%: 1.07, 2.66) times more likely during the weekend versus during the week. The interactions of male-by-injured, taxi-by-injured, and night-by-weekend were nonsignificant.
Conclusion
The probability of a HAR partially depends on time, day of the week, and whether the vehicle type was a taxi. We discuss implications for policies and interventions aimed at preventing this type of collision and crime. |