Association between speeding and use of alcohol and medicinal and illegal drugs and involvement in road traffic crashes among motor vehicle drivers

Prevalence of alcohol-impaired driving: a systematic review with a gender-driven approach and meta-analysis of gender differences

BACKGROUND

A growing number of studies investigated the factors that contribute to driving under the influence (DUI) of alcohol in relation to gender. However, a gendered approach of the scientific evidence is missing in the literature. To fill this gap, a gender-driven systematic review on real case studies of the last two decades was performed. In addition to the gender of the drivers involved, major independent variables such as the period of recruitment, the type of drivers recruited, and the geographical area where the study was conducted, were examined. Afterwards, a meta-analysis was performed comparing alcohol-positive rates (APR) between male and female drivers in three subgroups of drivers: those involved in road traffic accidents, those randomly tested on the road, and volunteers.

METHODS

Three databases were searched for eligible studies in October 2023. Real-case studies reporting APR in man and women convicted for DUI of alcohol worldwide were included. Univariate analysis by ANOVA with post-hoc tests identified the independent variables with a significant impact on the dependent variable APR, according to a relationship subsequently investigated by standard multiple linear regression. The meta-analysis of random effects estimates was performed to investigate the change in overall effect size (measured by Cohen's d standardized mean difference test) and 95% confidence interval (CI).

RESULTS

Among papers addressing driver gender, univariate analysis of independent variables revealed a higher Alcohol Positive Rate (APR) in men, particularly in drivers involved in crashes, with a noticeable decrease over time. Analyzing the gender of drivers involved in crashes, the meta-analysis showed that men had a significantly higher APR (30.7%; 95%CI 26.8-35.0) compared to women (13.2%; 95%CI 10.7-16.1). However, in drivers randomly tested, there was no significant difference in APR between genders (2.1% for men and 1.4% for women), while in volunteers, there was a statistically significant difference in APR with 3.4% (95%CI 1.5-7.6) for men and 1.1% (95%CI 0.5-2.7) for women.

CONCLUSION

Despite a progressive decrease in the epidemiological prevalence of alcohol-related DUI over time, this phenomenon remains at worryingly high levels among drivers involved in road traffic accidents in both genders, with a higher prevalence in men. It's important for policymakers, professionals, and scientists to consider gender when planning research, analysis, interventions, and policies related to psychoactive substances, such as alcohol or other licit drugs. Forensic sciences can play a vital role in this regard, enabling a thorough analysis of gender gaps in different populations.

Data-driven risk analysis of nonlinear factor interactions in road safety using Bayesian networks

This paper aims to demonstrate nonlinear risk factor interactions based on a data-driven approach using a Bayesian network model, providing a road safety use case. Road safety is a critical issue worldwide, with approximately 1.3 million road traffic deaths each year (WHO). Traditional road safety risk assessment methods often analyze individual factors separately; however, these assessments fail to capture the complex dynamics of real-world analysis, in which multiple factors interact through nonlinear relationships. In this study, a novel road safety risk assessment approach that uses a Bayesian network model to explore the nonlinear relationships among road safety risk factors is developed. Through the analysis of extensive crash reports from the state of Maryland, the complex interdependencies among various risk factors and their cumulative impact on road safety are investigated. Our findings show that two combined risk factors have different effects on risk level when considered individually. Two case studies related to human state risk factors and environmental risk factors, such as driving under the influence and snowy roads, as well as fatigue and snowy roads, have an amplified effect on the risk level. The findings highlight the importance of considering nonlinear interactions among risk factors when developing effective and targeted strategies for accident prevention and road safety improvement. This research contributes to the field of road safety by presenting a new methodology for understanding and mitigating road safety hazards.

Risk of Motor Vehicle Collisions and Culpability among Older Drivers Using Cannabis: A Meta-Analysis

Limited studies have investigated the effects of cannabis use on driving among older adults, who represent the fastest growing segment of drivers globally. We conducted a systematic review and meta-analysis to evaluate the effects of delta-9-tetrahydrocannabinol (THC) exposure on risks of (1) motor vehicle collisions (MVC) and (2) culpability for MVCs among adults 50 years and older. Three reviewers screened 7022 studies identified through MEDLINE, EMBASE, CENTRAL, and PsycINFO. Odds Ratios (OR) were calculated using the Mantel-Haenszel method in Review Manager 5.4.1. Heterogeneity was assessed using I2. The National Heart, Lung, and Blood Institute tool was used to assess the quality of each study. Seven cross-sectional studies were included. Three studies evaluated culpability while four evaluated MVC. The pooled risk of MVC was not significantly different between THC-positive and THC-negative older drivers (OR, 95% CI 1.15 [0.40, 3.31]; I2 = 72%). In culpability studies, THC exposure was not significantly associated with an increased risk of being culpable for MVC among adults over the age of 50 (OR, 95% CI 1.24 [0.95, 1.61]; I2 = 0%). Inspection of funnel plots did not indicate publication bias. Our review found that THC exposure was not associated with MVC involvement nor with culpability for MVCs.