Examining Seat Belt Use Habits in Wyoming: A Bayesian Hierarchical Logit Approach

Abstract

Wyoming has one of the lowest seat belt law compliance rates in the United States. Understanding the factors associated with seat belt non-use is crucial for the development of appropriate mitigation measures that aid in increasing seat belt usage rates. In this study, Bayesian binary logistic regression models were developed to: i) investigate the factors associated with daytime seat belt non-use using observational survey data; and ii) assess the factors related to seat belt non-use in fatal crashes while accounting for possible intra-class correlation (effects of unobserved factors common to occupants in the same vehicle). The results indicated that males were less likely to use seat belts than females. Also, trips made in pick-up trucks, those made within urban areas, those made during weekdays, and those made by means of vehicles with Wyoming license plates were likely to involve seat belt non-use. Furthermore, counties with thriving oil and gas industries had lower seat belt use rates. It was also inferred that young occupants, rear seat occupants, impairment, weekdays, traveling around midnight, traveling on collector roads, and traveling on local roads were associated with seat belt non-use. A strong correlation in seat belt non-use among occupants within the same vehicle warrants the implementation of the hierarchical logistic model to investigate seat belt use among occupants involved in fatal crashes. The findings of this study highlight remarkable trends in seat belt use habits in Wyoming, which will aid legislatures in proposing road safety measures aimed at raising seat belt usage proportions.