Kentucky crash data for the 2015-2016 period reveal that per capita crash rates and increases in crash-related fatalities in the state outpaced the national average. To explain why the U.S. Southeast sees higher crash rates than other regions of the country, previous research has argued the region’s unique socioeconomic conditions provide a compelling explanation. Taking this observation as a starting point, this study uses an extensive crash dataset from Kentucky to examine the relationship between highway safety and socioeconomic and demographic characteristics. Its focus is single- and two-unit crashes that involve commercial motor vehicles (CMVs) and automobiles. Using binary logistic regression and the quasi-induced exposure technique to analyze data on the socioeconomic and demographic attributes of the zip codes in which drivers reside, factors are identified which can serve as indicators of crash occurrence. Variables such as income, education level, poverty level, employment, age, gender, and rurality of the driver’s zip code influence the likelihood of a driver being at fault in a crash. Socioeconomic factors exert a similar influence on CMV and automobile crashes, irrespective of the number of vehicles involved. Research findings can be used to identify groups of drivers most likely to be involved in crashes and develop targeted and efficient safety programs.

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