Patterns of alcohol consumption and alcohol-impaired driving in the United States

Abstract

Background: Alcohol-related motor vehicle crashes kill approximately 17,000 Americans annually and were associated with more than $51 billion in total costs in 2000. Relatively little is known about the drinking patterns of alcohol-impaired (AI) drivers in the United States.

Methods: 2006 Behavioral Risk Factor Surveillance System (BRFSS) was analyzed for alcohol consumption and self-reported AI driving among U.S. adults aged > or =18 years for all states. Alcohol consumption was divided into 4 categories: binge/heavy, binge/nonheavy, nonbinge/heavy, and nonbinge/nonheavy. Binge drinking was defined as > or =5 drinks for men or > or =4 drinks for women on one or more occasions in the past month, and heavy drinking was defined as average daily consumption of >2 drinks/day (men) or >1 drink/day (women). The prevalence of AI driving was examined by drinking pattern and by demographic characteristics. Logistic regression analysis was used to assess the association between drinking patterns and AI driving.

Results: Five percent of drinkers were engaged in AI driving during the past 30 days. Overall, 84% of AI drivers were binge drinkers and 88% of AI driving episodes involved binge drinkers. By drinking category, binge/nonheavy drinkers accounted for the largest percentage of AI drivers (49.4%), while binge/heavy drinkers accounted for the most episodes of AI driving (51.3%). The adjusted odds of AI driving were 20.1 (95% CI: 16.7, 24.3) for binge/heavy, 8.2 (6.9, 9.7) for binge/nonheavy, and 3.9 (2.4, 6.3) for nonbinge/heavy drinkers, respectively.

Conclusions: There is a strong association between binge drinking and AI driving. Most AI drivers and almost half of all AI driving episodes involve persons who are not heavy drinkers (based on average daily consumption). Implementing effective interventions to prevent binge drinking could substantially reduce AI driving.