A comparative case study (2017–2020) was conducted to identify demographic, social, medico-legal, and toxicological variables associated with non-fatal accidents in driving under the influence (DUI) subjects. A second aim was to identify the factors predictive of substance use disorders among subjects. Drivers charged with alcohol DUI (blood alcohol concentration (BAC) > 0.5) and/or psychoactive substance DUI were included; cases included those involved in an accident while intoxicated, and the comparison group included DUI offenders negative for road accident involvement. Significance was determined by chi-square and Mann–Whitney tests. To prevent confounding effects, a multivariate binary logistic regression analysis was performed. Our sample encompassed 882 subjects (381 in the case group and 501 in the comparison group). Parameters such as psychoactive substances and BAC at the time of the road crash/DUI and the day of the week, when subjects were involved in the road accident or found DUI, resulted in significant differences (p < 0.01) between groups. The model’s independent variables of BAC > 1.5 g/L (p = 0.013), BAC > 2.5 g/L (p < 0.001), and concurrent alcohol and psychoactive substance use (p < 0.001) were independent risk factors for an accident. Smoking >20 cigarettes/day was an independent risk factor for unfitness to drive (p < 0.01). Unfitness to drive was based primarily on ethyl glucuronide levels >30 pg/mg. Our results suggest a detailed assessment of DUI subjects with variables associated with accidents (BAC > 1.5 g/L and concurrent intake of psychoactive substances). Hair analysis, including ethylglucuronide (EtG) concentration, should be always performed. Based on our results, nicotine use should be investigated in cases of driving license regranting.
Driving license regranting in DUI subjects: Road accident variables and predictive factors of substance use disorder
Beccegato E.;Ruggeri A.;Montisci M.;Terranova C.
2021
Abstract
A comparative case study (2017–2020) was conducted to identify demographic, social, medico-legal, and toxicological variables associated with non-fatal accidents in driving under the influence (DUI) subjects. A second aim was to identify the factors predictive of substance use disorders among subjects. Drivers charged with alcohol DUI (blood alcohol concentration (BAC) > 0.5) and/or psychoactive substance DUI were included; cases included those involved in an accident while intoxicated, and the comparison group included DUI offenders negative for road accident involvement. Significance was determined by chi-square and Mann–Whitney tests. To prevent confounding effects, a multivariate binary logistic regression analysis was performed. Our sample encompassed 882 subjects (381 in the case group and 501 in the comparison group). Parameters such as psychoactive substances and BAC at the time of the road crash/DUI and the day of the week, when subjects were involved in the road accident or found DUI, resulted in significant differences (p < 0.01) between groups. The model’s independent variables of BAC > 1.5 g/L (p = 0.013), BAC > 2.5 g/L (p < 0.001), and concurrent alcohol and psychoactive substance use (p < 0.001) were independent risk factors for an accident. Smoking >20 cigarettes/day was an independent risk factor for unfitness to drive (p < 0.01). Unfitness to drive was based primarily on ethyl glucuronide levels >30 pg/mg. Our results suggest a detailed assessment of DUI subjects with variables associated with accidents (BAC > 1.5 g/L and concurrent intake of psychoactive substances). Hair analysis, including ethylglucuronide (EtG) concentration, should be always performed. Based on our results, nicotine use should be investigated in cases of driving license regranting.File | Dimensione | Formato | |
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