Demographic risk factors and injury severity scores in Substance-use behaviour related traffic crashes

Abstract

Alcohol and drugs, including Tetrahydrocannabinol (THC), significantly impact roadway safety by impairing cognitive functions, coordination, and reaction times, leading to increased crash risk and severity. This study examines the prevalence of alcohol and drugs among 4,586 injured roadway users (drivers, riders, and passengers) in the U.S. from 2019 to 2021, utilizing an XGBoost model to identify key variables associated with Injury Severity Score (ISS) in substance-related traffic crashes, and highlighting influential factors such as injury location, demographic characteristics (age, race), safety compliance, and alcohol and drug presence. These risk factors were further analyzed through Cluster Correspondence Analysis (CCA) to reveal patterns and trends affecting injury severity across different demographic and behavioral groups. The findings reveal that 55.8% of the injured tested positive for substances, with cannabinoids being the most common, followed by alcohol, stimulants, and opioids. This study identified six core crash clusters, each with distinct characteristics, including older drivers, impaired young drivers, specific driver ethnicities, and motorcyclists. Key findings from clusters indicate that older drivers, despite high safety compliance and negative substance tests, faced crash risks potentially due to age-related limitations. Impaired young adult crashes arecharacterized by risky behavior, including alcohol and THC use combined with low safety compliance, while motorcyclists with high substance involvement and inconsistent helmet use, are identified as a high-risk group, frequently experiencing severe leg injuries. These insights underscore the need for comprehensive traffic safety policies targeting substance use and promoting effective safety measures to mitigate crash risks and improve road safety.