Sex-based differences in odds of motor vehicle crash injury outcomes

• Published in: Accident analysis and prevention 2024-02, Vol.195, p.107100-107100, Article 107100
• Main Authors: Craig, Matthew J, Liu, Cejun, Zhang, Fan, Enriquez, Jacob
• Format: Article
• Language: English
• Subjects: Abbreviated Injury Scale; Accidents, Traffic; Adolescent; Bayes Theorem; Female; Humans; Logistic Models; Male; Motor Vehicles; Wounds and Injuries - epidemiology; Wounds and Injuries - etiology
• ISSN: 0001-4575; 1879-2057
• DOI: 10.1016/j.aap.2023.107100

Several studies have documented the relative risk or odds of injury and fatality for females versus males in motor vehicle crashes (Parenteau et al. 2013, Forman et al. 2019, Brumbelow and Jermakian, 2022; Noh et al. 2022). Though, none combined National Automotive Sampling System-Crashworthiness Data System (NASS-CDS) and Crash Investigation Sampling System (CISS). The aim of this study was to document the relative odds of various injury outcomes for females versus males while considering a broad range of crash types, pre-crash and crash variables, and occupant characteristics. Multivariable logistic regression was carried out to study the odds of injury for females versus males. A select imputation method (Hot Deck, Approximate Bayesian Bootstrap) was applied as part of efforts to create multivariable logistic regression models for 25 different injury outcomes associated with occupants (age 13 years and older) involved in passenger vehicle crashes published in NASS-CDS (2000 to 2015) and CISS (2017-2021). Both pre-crash (n=7) and crashworthiness (n=22) predictor variables were considered, but only significant variables at p≤0.10 level were retained in final models. Six crash-type models were produced for each injury outcome; one that included all crashes, one for each of four different planar crash types (frontal, near-side, far-side, rear), and one for crashes involving rollover. These six sets of crash-type models were expanded further to include a model version that included both pre-crash/environment and crashworthiness predictor variables and one model limited to crashworthiness predictors only. Different than other recent studies, all crash types, occupant restraint conditions, and seating positions were considered. Occupant sex was retained in all models to facilitate female versus male injury outcome odds ratio (OR) assessments. Female versus male injury OR estimates for 300 unique models are presented. Females had significantly higher odds of injury than males in 36 models (OR>1.0, p-value ≤0.05). This contrasts with 43 models where females had significantly lower odds (OR0.05). In four cases, the OR estimate was 1.00. Amongst the results, there was a trend for females to have higher odds of AIS 2+ injuries (MAIS 2+ OR=1.75 and 1.69 f