Less is more: the influence of traffic count on drinking and driving behaviour

Drinking and driving road checks are often organized with either a clear prevention or repression objective in mind. The objective of a prevention strategy is to make as many people as possible believe that police officers are enforcing drinking and driving laws and that drinking drivers will most likely be caught. As such, targeting high traffic count road sites with high-visibility road checks is a priority because it serves to increase awareness of the enforcement activity. An alternative to this prevention approach is the "repression" approach that involves targeting times and places where the highest number of drinking drivers are to be expected. Rather than attempting to affect the subjective chance of getting caught, this approach seeks to increase the objective likelihood of getting caught; the aim is to apprehend as many drinking drivers as possible. Regardless of the chosen strategy, there is a need to understand how traffic count influences drinking and driving behaviour as traffic count may play a role in a police officer's choice of sites for a road check. The objective of this paper is to shed some light on this relationship between drinking and driving behaviour and traffic count. In this paper, data from a roadside survey, carried out in British Columbia in 2003, are used. A two-level logistic regression analysis was carried out with data from 2627 drivers coming from 48 different road sites to replicate a model that was previously obtained with comparable data from a Belgian roadside survey, also carried out in 2003. The present study successfully replicated the findings of the Belgian model, substantiating that the probability for drivers to be drinking and driving significantly decreases with an increasing level of traffic count. This supports the suggestion that drinking drivers avoid high traffic count road sites. The relevance of these findings with respect to organizing preventive or repressive road checks and possible confounding variables are discussed at the end of this paper.