Police-reported data from Transport Canada’s National Collision Database (NCDB) is analyzed with a view to identify and quantify various factors that can impact the survivability of cyclists involved in a motor vehicle collision. A Least Absolute Shrinkage and Selection Operator (LASSO) regression and a multiple imputation (MI) process address the variable selection and missing data problems, respectively. The resulting probabilistic model suggests that collision survivability depends largely on the cyclist’s age and helmet usage. Survivability improves with age up to age 21, peaks for cyclists aged 21 to 34, and falls after age 35. Controlling for age and other factors, a bicycle helmet reduces the risk that a cyclist fatality will occur by approximately 34% (OR: 0.66, 95% CI: 0.56-0.78). Survivability in general and the apparent safety benefits of bicycle helmets in particular do not appear to depend on the sex of the cyclist. Head-on and rear-end collisions tend to be more deadly. Certain environmental and situational variables like strong winds and traffic control devices also appear to impact survivability, independently from the type of collision or the characteristics of the cyclist. There might be opportunities to sensitize cyclists of various age groups about the risks they are exposed to while cycling, and prevent or better protect cyclists from head-on and rear-end collisions.
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