Citation

Chen GG, Wilson RJ. J. Traffic Med. 2001; 29(1-2): 44-52.

Copyright

(Copyright © 2001, International Association for Accident and Traffic Medicine)

DOI

unavailable

PMID

unavailable

Abstract

Objective: Detection of impaired drivers in sobriety checkpoints is typically low. This study determines if a set of observable driver, vehicle and situational variables has potential value in identifying impaired drivers passing through sobriety checkpoints. The study predicts the blood alcohol concentrations (BAC) of a randomly selected sample of nighttime drivers and classifies them into BAC groups. Methods: The data were obtained from a 1998 roadside survey in three British Columbia communities. Multinomial logit models and discriminant models were estimated to describe, explain, and classify the BAC of nighttime drivers. Results: Several factors increase the odds of being an impaired driver: age group, 26 to 45; education, high school or less; trip origin, bar; passengers, group same sex as driver; and advancing hour of night. The classification function correctly classified more than 65% of all drivers and 62% of impaired drivers. Conclusion. Information in the model is not sufficient to make a reliable determination of BAC but could be used to increase the likelihood of identifying impaired drivers in sobriety checkpoints, thereby improving the efficiency of enforcement operation.

Keywords

Ethanol impaired driving