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Introduction: Examining crash reports with linked community-level indicators may optimize efforts aimed at improving traffic safety behaviors, like seat belt use. To examine this, quasi-induced exposure (QIE) methods and linked data were used to (a) estimate trip-level seat belt non-use of New Jersey (NJ) drivers and (b) determine the degree to which seat belt non-use is associated with community-level indicators of vulnerability., Method: Driver-specific characteristics were identified from crash reports (age, sex, number of passengers, vehicle type) and licensing data (license status at the time of the crash). Geocoded residential addresses were leveraged within the NJ Safety and Health Outcomes warehouse to create quintiles of community-level vulnerability. QIE methods were applied to estimate trip-level prevalence of seat belt non-use in non-responsible, crash-involved drivers between 2010-2017 (n = 986,837). Generalized linear mixed models were then conducted to calculate adjusted prevalence ratios and 95 % confidence intervals for being unbelted for driver-specific variables and community-level indicators of vulnerability., Results: Drivers were unbelted during 1.2 % of trips. Males, those with suspended licenses, and those without passengers had higher rates of being unbelted than their counterparts. An increase was observed in traveling unbelted with increasing quintiles of vulnerability, such that drivers in the most vulnerable communities were 121 % more likely to be unbelted than those in the least vulnerable communities., Conclusions: Prevalence of driver seat belt non-use may be lower than previously estimated. Additionally, communities with the highest amount of the population living with three or more indicators of vulnerability have higher rates of seat belt non-use; this may be a particularly useful metric to inform future translational efforts improving seat belt use., Practical Applications: As evidenced by the findings that risk of being unbelted increased as drivers' community vulnerability increased, novel communication efforts tailored to drivers from vulnerable neighborhoods may optimize efforts., Competing Interests: Declaration of Competing Interest We declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 National Safety Council and Elsevier Ltd. All rights reserved.)

Objectives: Current information on the safety of rear row occupants of all ages is needed to inform further advances in rear seat restraint system design and testing. The objectives of this study were to describe characteristics of occupants in the front and rear rows of model year 2000 and newer vehicles involved in crashes and determine the risk of serious injury for restrained crash-involved rear row occupants and the relative risk of fatal injury for restrained rear row vs. front passenger seat occupants by age group, impact direction, and vehicle model year., Method: Data from the National Automotive Sampling System Crashworthiness Data System (NASS-CDS) and Fatality Analysis Reporting System (FARS) were queried for all crashes during 2007-2012 involving model year 2000 and newer passenger vehicles. Data from NASS-CDS were used to describe characteristics of occupants in the front and rear rows and to determine the risk of serious injury (AIS 3+) for restrained rear row occupants by occupant age, vehicle model year, and impact direction. Using a combined data set containing data on fatalities from FARS and estimates of the total population of occupants in crashes from NASS-CDS, logistic regression modeling was used to compute the relative risk (RR) of death for restrained occupants in the rear vs. front passenger seat by occupant age, impact direction, and vehicle model year., Results: Among all vehicle occupants in tow-away crashes during 2007-2012, 12.3% were in the rear row where the overall risk of serious injury was 1.3%. Among restrained rear row occupants, the risk of serious injury varied by occupant age, with older adults at the highest risk of serious injury (2.9%); by impact direction, with rollover crashes associated with the highest risk (1.5%); and by vehicle model year, with model year 2007 and newer vehicles having the lowest risk of serious injury (0.3%). Relative risk of death was lower for restrained children up to age 8 in the rear compared with passengers in the right front seat (RR=0.27, 95% CI 0.12-0.58 for 0-3 years, RR=0.55, 95% CI 0.30-0.98 for 4-8 years) but was higher for restrained 9-12-year-old children (RR=1.83, 95% CI 1.18-2.84). There was no evidence for a difference in risk of death in the rear vs. front seat for occupants ages 13-54, but there was some evidence for an increased relative risk of death for adults age 55 and older in the rear vs. passengers in the right front seat (RR=1.41, 95% CI 0.94-2.13), though we could not exclude the possibility of no difference. After controlling for occupant age and gender, the relative risk of death for restrained rear row occupants was significantly higher than that of front seat occupants in model year 2007 and newer vehicles and significantly higher in rear and right side impact crashes., Conclusions: Results of this study extend prior research on the relative safety of the rear seat compared with the front by examining a more contemporary fleet of vehicles. The rear row is primarily occupied by children and adolescents, but the variable relative risk of death in the rear compared with the front seat for occupants of different age groups highlights the challenges in providing optimal protection to a wide range of rear seat occupants. Findings of an elevated risk of death for rear row occupants, as compared with front row passengers, in the newest model year vehicles provides further evidence that rear seat safety is not keeping pace with advances in the front seat., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

Traditional methods for determining crash responsibility - most commonly moving violation citations - may not accurately characterize at-fault status among crash-involved drivers given that: (1) issuance may vary by factors that are independent of fault (e.g., driver age, gender), and (2) these methods do not capture driver behaviors that are not illegal but still indicative of fault. We examined the statistical implications of using moving violations to determine crash responsibility in young driver crashes by comparing it with a method based on crash-contributing driver actions. We selected all drivers in police-reported passenger-vehicle crashes (2010-2011) that involved a New Jersey driver <21 years old (79,485 drivers