Personal and behavioral predictors of automobile crash and injury severity

The purpose of this paper is to develop a statistical model explaining the relationships between certain driver characteristics and behaviors, crash severity, and injury severity. Applying techniques of categorical data analysis to comprehensive data on crashes in Hawaii during 1990, we build a structural model relating driver characteristics and behaviors to type of crash and injury severity. The structural model helps to clarify the role of driver characteristics and behaviors in the causal sequence leading to more severe injuries. From the model we estimate the effects of various factors in terms of odds multipliers--that is, how much does each factor increase or decrease the odds of more severe crash types and injuries. We found that driver behaviors of alcohol or drug use and lack of seat belt use greatly increase the odds of more severe crashes and injuries. Driver errors are found to have a small effect, while personal characteristics of age and sex are generally insignificant. We conclude with a discussion of our modeling approach and of the implications of our findings for appropriate traffic safety interventions and future research.