Near-miss crashes and other predictors of motorcycle crashes: Findings from a population-based survey

Abstract

Objective: Crash and injury surveillance studies have identified a range of rider-related factors, including age, sex, licensure, training and experience, as being associated with motorcycle crash risk. The aim of this study was to establish whether these previously identified factors were associated with crash involvement in an Australian-based population.

Methods: Data obtained from motorcyclists recruited from road authority licensing offices in a population-based survey design were analyzed. In addition to descriptive analysis, survey logistic regression was used to examine predictors of self-reported motorcycle crashes.

A statewide population prevalence study of motorcyclists in New South Wales, Australia, was conducted using a multistage stratified random sampling plan. Participants (n = 503) represented 47% of eligible riders invited to participate. The distribution of responses was weighted to represent the population based on motorcycle registrations as a proxy for active motorcyclists, adjusted for age, sex, and variations in sample size and population density between survey sites.

Results: This analysis investigated factors associated with having crashed in the past 12 months. The key predictors of increased crash risk included frequent near-crash experiences (6–10) in the past year (adjusted odds ratio [OR_adj] = 5.3; 95% confidence interval [CI], 1.3–21.8), having 4 or more riding demerit points (OR_adj = 4.1; 95% CI, 1.1–14.7), and motorcycle type and riding purpose. Sports (OR_adj = 2.8; 95% CI, 1.1–7.3) and commuter motorcycles (OR_adj = 4.0; 95% CI, 1.1–15.3) were associated with higher odds of crashes compared to cruiser/touring motorcycles.

Those whose purpose for riding frequently involved commuting, high-speed roads, or motorcycle sports had higher odds of being involved in a crash compared to riders who rarely took part in such activities. Rider age, license type, and time holding a motorcycle license were not predictive of crash involvement when other factors were taken into account.

Conclusions: These findings provide important population-level information and insights about risk exposure for motorcyclists. Taking a more tailored approach to data collection meant that factors associated with crash involvement were identified that are not commonly observed in studies relying on administrative data. In particular, the study highlights the importance of near-crash experiences as warnings to riders and the need to use such experiences as learning opportunities to improve their riding style and safety.

Keywords:

• Crash
• motorcycle
• near-crash
• predictors
• population

Additional information

Funding

This study was funded by the NSW Centre for Road Safety, Transport for NSW. Dr. Julie Brown is supported by an NHMRC research fellowship.