Driving while impaired by alcohol: An analysis of drink-drivers involved in UK collisions

Abstract

Objective: Drink-driving represents a critical issue on international organizations’ agendas as one of the key behavioral risk factors in road traffic safety, alongside speed and nonuse of motorcycle helmets, seat belts, and child restraints. Changing road user behaviors regarding these 5 factors is a critical component in reducing road traffic injuries and casualties. The objective of this study is the identification of drivers who are more likely to contribute to crashes in the UK while impaired by alcohol to design targeted drink drive compliance campaigns.

Method: To profile drivers with the factor “impaired by alcohol” assigned in collisions, an extensive data set is used, including all reported injury collisions between 2011 and 2015 in the UK (police records), merged with the Experian Mosaic Database. A multilevel mixed-effects logistic regression is conducted, utilizing the hierarchical nature of the data (drivers within Mosaic types).

Results: Using multilevel mixed-effects logistic regression analysis, the finding is that some driver profiles are more likely to contribute to crashes and are assigned the contributory factor “impaired by alcohol.” Drink-related crashes are more common in some circumstances or for some crash-involved driver groups than others. For instance, alcohol-related crashes are more likely to occur on single carriageways and among males and 25- to 35-year-olds. Drink-drive-related crashes are found to be strongly associated with dark lighting conditions and, more specifically, with late night hours (the interval between 3:00 a.m. and 4:00 a.m. accounts for a third of the drink-drive-related collisions). Using the Experian Mosaic Database which divides the UK population into 66 types based on demographic, lifestyle, and behavior characteristics, the finding is that, among crash-involved drivers, some Mosaic types are significantly more likely (e.g., pocket pensions, dependent greys, streetwise singles) and others are significantly less likely (e.g., crowded kaleidoscope, cultural comfort, penthouse chic) to contribute to a drink-related crash.

Conclusions: The outcome is a more nuanced understanding of drivers contributing to drink-related crashes in the UK. The study concludes by discussing the implications for governments and other interested bodies for better targeting and delivery of public education campaigns and interventions.

Keywords:

• Contributory factors
• drink-driving
• alcohol-related collisions
• driver behavior
• driver profiles