title: Modeling motor vehicle crashes for street racers using zero-inflated models.
abstract: Motor vehicle crashes are a leading cause of death for young people in the United States. Assessing which drivers are at a high risk of experiencing a crash is important for the implementation of traffic regulations. Illegal street racing has been associated with a high rate of motor vehicle crashes. In this study, we link Utah statewide driver license citations and motor vehicle crash data to evaluate the rate of crashes for drivers with street racing citations relative to other drivers. Using a zero-inflated negative binomial model we found that drivers with no citations are approximately three times more likely to be at zero risk of a crash compared to drivers with street racing citations. Moreover, among drivers at non-negligible risk of crash, cited street racers are more likely to be involved in a crash compared to drivers without citations or those cited for violations other than street racing. However, drivers with increased numbers of non-street-racing citations experience crash risks approaching those of the cited street racers.
authors.affiliation: Department of Family and Preventive Medicine, University of Utah, 375 Chipeta Way, Salt Lake City, UT 84108, USA.
authors.forename: Zhuo
authors.initials: Z
authors.lastname: Li
authors.forename: Stacey
authors.initials: S
authors.lastname: Knight
authors.forename: Lawrence J
authors.initials: LJ
authors.lastname: Cook
authors.forename: Lisa K
authors.initials: LK
authors.lastname: Hyde
authors.forename: Richard
authors.initials: R
authors.lastname: Holubkov
authors.forename: Lenora M
authors.initials: LM
authors.lastname: Olson
mesh_terms: D000063:Accidents, Traffic / Q000331:legislation & jurisprudence / Q000706:statistics & numerical data*; D000293:Adolescent; D000328:Adult; D001334:Automobile Driving / Q000331:legislation & jurisprudence / Q000706:statistics & numerical data*; D003415:Crime / Q000331:legislation & jurisprudence* / Q000706:statistics & numerical data; D005260:Female; D006801:Humans; D008297:Male; D015233:Models, Statistical; D008962:Models, Theoretical; D012306:Risk; D018570:Risk Assessment; D014589:Utah