Abstract
Objective. The purpose of this study was to examine predictors of subsequent motor vehicle collision injuries, with a particular focus on health-related variables, using the longitudinal dataset from the Canadian National Population Health Survey (NPHS) for the years 1994–2002.
Methods. Multiple logistic regression analysis was used to determine the relations between motor vehicle collision injury and four risk factors: binge drinking, health status, distress, and medication use. Age and sex were included as control variables. The total sample size was 14,529.
Results. A higher percentage of females and younger persons reported a motor vehicle collision injury. Binge drinkers, respondents with poor health, respondents with distress, and respondents reported using two or more medications reported a higher percentage of subsequent injuries. Logistic regression analysis found that persons with poorer health status and persons who used more medications had higher odds of motor vehicle injuries. Only one statistically significant interaction effect was found: alcohol bingeing and medication use.
Conclusions. Among a nationally representative sample of Canadians, various demographic and risk factors predict subsequent injuries. Given that this number represents a considerable economic burden, this study underscores the need for continued research and countermeasures on alcohol, drugs, and driving.
Acknowledgment
This research was supported by a grant from AUTO21, a member of the Networks of Centres of Excellence (NCE) program, which is administered and funded by the Natural Sciences and Engineering Research Council (NSERC), the Canadian Institutes of Health Research (CIHR), and the Social Sciences and Humanities Research Council (SSHRC), in partnership with Industry Canada. Access to the National Population Health Survey microdata files was granted through an application to the CISS-ACCESS to the Research Data Centre Program. While the research and analysis are based on data from Statistics Canada, the opinions expressed do not necessarily represent the views of Statistics Canada.