UNASSIGNED: Using alcohol or psychoactive drugs before driving a motor vehicle may increase the risk of crash involvement, injury, and death. This is better documented for alcohol than for drugs. The aim of this study was to expand a previous case-control study on substance use and driver fatality by doubling the number of cases and controls, and hence improve the statistical power and enable the analysis of combined substance use.
UNASSIGNED: We collected data on alcohol and drug use from all 1197 drivers of cars and vans who were fatally injured in road traffic crashes in Norway between 2005 and 2020 (\'cases\') by analyzing blood samples or reviewing other information on substance use. We also collected data on alcohol and drug use among 17,219 drivers in random road traffic (\'controls\') by analyzing oral fluid samples. Substance use was converted to dichotomous variables (no use/use). We used unconditional logistic regression to estimate adjusted odds ratios (aORs) with 95% confidence intervals (CIs) of driver fatality for mutually exclusive substance groups, adjusted for sex, age, geographic region, urban centrality class, and time interval of the week.
UNASSIGNED: Compared to no substance use, the aOR (95% CI) for driver fatality was for alcohol 91 (61-137), stimulants (primarily amphetamines) aOR 22 (9-56), benzodiazepines and z-hypnotics (BZDs) aOR 4.0 (2.7-5.9), tetrahydrocannabinol (THC) aOR 3.4 (1.7-6.7), and opioids aOR 1.4 (0.4-4.9). The aOR for any polysubstance use was 168 (96-297). The combinations of BZDs with stimulants or THC were associated with markedly higher aORs for driver fatality than the use of single substance groups.
UNASSIGNED: Alcohol and polysubstance use are the most important predictors of fatal injury, followed by stimulants.

In June 2013, an alcohol-related traffic law took effect in Turkey. The law 6487 introduced administrative fines for not respecting blood alcohol concentration limits, health warning messages on alcohol containers (bottles, cans), and prohibited the sale of alcohol beverages in retail facilities between 10 p.m. and 6 a.m.. This article examines how this law is associated with traffic fatality variation.
Data from the Turkish Statistical Institute for the 2008-2019 period were analyzed. Outcomes were traffic fatality rates per 100,000 population and 10,000 motor vehicles. Exposure variable was the presence of law 6487. Alcohol, tobacco, and related beverages\' household expenditure, unemployment rate, number of health professionals, number of crashes, and lags of the outcomes represented control variables. A time-series cross-regional fixed effect model was applied.
Empirical estimates suggest that the law 6487 was associated with a reduction of 15% (Incidence Rate Ratio (IRR) 0.85, 95% Confidence Interval (CI): 082, 0.94) in the traffic fatality per population rate and with a reduction of 14% (IRR: 0.86 (95% CI: 0.78, 0.92) in the traffic fatality per motor-vehicle rate. After 6 years of its implementation, this intervention was associated with an absolute reduction of 1519 (95% reduction interval: 1177, 1810) traffic fatalities.
Our research emphasizes that legislation with direct and indirect measures targeting driving under the influence of alcohol (DUIA) may be related to traffic fatalities reduction.
This finding has important implications for policy and future research in contexts in which alcohol consumption is low such is in Turkey. Future research should seek to identify mechanisms that explain how laws are ultimately associated with DUIA variation.

BACKGROUND: Very few studies have examined predictors of Driving Under the Influence (DUI) as a function of gender. This oversight is relevant, because analyzing gender differences prevents generalization of results observed in men, who still currently account for the majority of drivers worldwide, to women. The aim of this study is to analyze the prevalence of DUI of drugs in men and women reported in real case studies published in the last two decades, and to assess gender differences in risky DUI behaviour.
METHODS: PubMed, Scopus, Web of Science were searched for eligible studies in May 2021; a follow-up literature search was conducted in August 2021. Real-case studies of drivers convicted for DUI of psychoactive drugs with positive toxicological confirmatory analysis were included. The extracted outcome was the prevalence of positive findings of men and women for cocaine, cannabinoids, amphetamine-like drugs, opioids, and psychoactive prescription drugs. A meta-analysis of random effects estimates was performed to investigate the change in the size of the overall effect (by Cohen d standardized mean difference test). A Mann Whitney U test was performed to test for differences between genders.
RESULTS: Of the 2877 studies screened, 439 were retrieved in full-text and 26 were included. The meta-analysis showed a significant higher prevalence among men for cocaine (1.8% vs 0.9%; p < 0.001), cannabinoids (3.5% vs 1.6%; p = <0.01) and amphetamine-like drugs (1.2% vs 0.6%; p < 0.01). Surprisingly, no differences were observed in the use of opioids (2.3% vs 2.2%; p = 0.45) and benzodiazepines/Z-drugs (2.9% vs 3.7%; p = 0.52).
CONCLUSIONS: Contrary to the extraordinary number of real-case studies reported in literature, only a few papers differentiate the prevalence of DUI between men and women. This can lead to an underestimation of the influence of gender in DUI phenomenon or complicate the evaluation of the results for some classes of substances, as observed for medications and opioids. The primary goal in the future will be to collect the data concerning DUI drivers following shared and homogeneous methodologies, in order to allow the analysis of data disaggregated by gender, which can be used for monitoring evolving trends and developing gender-specific targeted prevention and enforcement efforts.

Isopropanol intoxication, whether accidental or intentional, is not unusual. Alcoholics have long-resorted to isopropanol because of its availability and cost. The incidence of isopropanol intoxication with driving, however, has been reported only a few times in the literature. A unique case is reported where an individual intentionally drank isopropanol and was involved in a minor traffic incident. The individual\'s impairment was not consistent with a preliminary breath test of 0.062%. The officer proceeded to an evidential breath test, but received an \"interferent-detected\" result, and then requested a drug recognition expert (DRE). A full DRE evaluation was performed, indicating central nervous system depressants, marijuana, and narcotic analgesics. Laboratory analysis included chromatographic testing for volatiles and an immunoassay drug screen. Results were positive for isopropanol and acetone; no other compounds were detected. This case report provides a unique comprehensive evaluation of a driver under the influence of isopropanol.

Many medications impair driving skills yet their influence on collision risk remains uncertain. We aimed to systematically investigate the risk of collision responsibility associated with common classes of prescription medications.
In this population-based case-control study we analysed linked driving and health records in British Columbia, Canada from Jan 1, 1997, to Dec 31, 2016. The study cohort included all drivers involved in an incident collision (defined as first collision after 3 collision-free years) that resulted in a police report. We scored police collision reports and classified drivers as responsible for the collision (cases) or not responsible (controls); drivers with indeterminate scores were excluded. We used logistic regression to determine odds of collision responsibility in drivers with current prescriptions for medications of interest versus drivers without prescriptions. To explore whether risk of collision responsibility was related to medication effect or driver factors, we compared risk in current medication users versus past users. To study whether drivers developed tolerance to medication effects, we compared risk in new (first 30 days of a prescription) versus established users.
During the study period, 4 906 925 drivers had their driving licence linked to health records; of these drivers, 747 662 unique drivers were involved in 837 919 incident collisions between Jan 1, 2000, and Dec 31, 2016. 382 685 drivers responsible for the collision (cases) and 332 259 drivers not responsible (controls) were included in the final analysis; 122 975 drivers with indeterminate responsibility were excluded. We found increased risk of collision responsibility in drivers prescribed sedating antipsychotics (adjusted odds ratio [aOR] 1·35 [98·75% CI 1·25-1·46]), long-acting benzodiazepines (aOR 1·30 [1·22-1·38]), short-acting benzodiazepines (aOR 1·25 [1·20-1·31]), and high-potency opioids (aOR 1·24 [1·17-1·30]). Among medications used for medical indications, the highest risk was seen in drivers prescribed neurological medications: cholinergic drugs (aOR 1·83 [1·39-2·40]), anticholinergic agents for Parkinson\'s disease (aOR 1·45 [1·08-1·96]), dopaminergic agents (aOR 1·20 [1·04-1·38]), and anticonvulsants (aOR 1·20 [1·14-1·26]). People currently taking benzodiazepines, non-sedating antidepressants, high-potency opioids, and anticonvulsants had increased risk compared with past users, and we did not find increased risk in new compared with established users of these drugs.
Drivers prescribed benzodiazepines or high-potency opioids are at increased risk of being responsible for collisions and this risk does not decrease over time. Several other classes of medications are associated with increased risk, but this association might be independent of medication effect. These findings can guide medication warnings and prescription choices and inform public education campaigns targeting impaired driving.
Canadian Institutes of Health Research.

5F-MDMB-PICA has been detected in products sold on the internet as well as in biological samples since 2016. It is associated with serious adverse health and behavioral effects and even death. Herein we report on twelve cases with proven 5F-MDMB-PICA consumption, including three fatalities, four cases of driving under the influence of drugs and five other criminal acts. In these cases, 5F-MDMB-PICA was detected in postmortem blood or serum. Concentrations ranged from 0.1-16ng/mL. In some blood (serum) and urine samples, the hydrolysis metabolite of 5F-MDMB-PICA (M12) could also be detected. In this case series, co-consumption with other drugs occurred in 9 of 12 cases, most commonly alcohol, cannabis and other contemporary SCs. In five cases, 4F-MDMB-BINACA was also detected. The described cases demonstrate various adverse effects that might be associated with 5F-MDMB-PICA. Observed physical adverse effects were mainly balance deficiencies and ocular effects such as reddened conjunctivae, glassy eyes and delayed or unresponsive pupil light reactions. Observed mental and behavioral effects were mainly changing moods, aggression, confusion, erratic behavior, mental leaps, disorientation, slowed reaction, logorrhea and slurred speech. Due to the fast changing market of synthetic cannabinoids, data on such new appearing substances are basically scarce. Because of the limited number of studies on pharmacological properties of synthetic cannabinoids, reports of findings in human samples along with corresponding case history descriptions can be valuable for the interpretation of upcoming routine cases.

Although only 2 % of crashes are head-on crashes in the United States, they account for over 10 % of all crash-related fatalities. This study aims to investigate the contributing factors that affect the injury severity of head-on crashes and develop appropriate countermeasures. Due to the unobserved heterogeneity inherent in the crash data, a latent class clustering analysis is firstly conducted to segment the head-on crashes into relatively homogeneous clusters. Then, mixed logit models are developed to further explore the unobserved heterogeneity within each cluster. Analyses are performed based on the data collected from the Highway Safety Information System (HSIS) from 2005 to 2013 in North Carolina. The estimated parameters and associated marginal effects are combined to interpret significant variables of the developed models. The proposed method is able to uncover the heterogeneity within the whole dataset and the homogeneous clusters. Results of this research can provide more reliable and insightful information to engineers and policy makers regarding the contributing factors to head-on crashes.

There are more than 2000 pedestrians reported to be involved in traffic crashes with vehicles in North Carolina every year. 10%-20% of them are killed or severely injured. Research studies need to be conducted in order to identify the contributing factors and develop countermeasures to improve safety for pedestrians. However, due to the heterogeneity inherent in crash data, which arises from unobservable factors that are not reported by law enforcement agencies and/or cannot be collected from state crash records, it is not easy to identify and evaluate factors that affect the injury severity of pedestrians in such crashes. By taking advantage of the latent class clustering (LCC), this research firstly applies the LCC approach to identify the latent classes and classify the crashes with different distribution characteristics of contributing factors to the pedestrian-vehicle crashes. By considering the inherent ordered nature of the traffic crash severity data, a partial proportional odds (PPO) model is then developed and utilized to explore the major factors that significantly affect the pedestrian injury severities resulting from pedestrian-vehicle crashes for each latent class previously obtained in the LCC. This study uses police reported pedestrian crash data collected from 2007 to 2014 in North Carolina, containing a variety of features of motorist, pedestrian, environmental, roadway characteristics. Parameter estimates and associated marginal effects are mainly used to interpret the models and evaluate the significance of each independent variable. Lastly, policy recommendations are made and future research directions are also given.

Experimental, epidemiological, and real-case studies have different advantages and limitations when used to study the effect of substance use on the risk for involvement in a road traffic crash. It is easier to perform well-controlled experimental studies than well-controlled epidemiological studies due to difficulties related to selection bias, information bias, and confounding. On the other hand, it is difficult or impossible to perform experimental studies using single and repeated substance doses similar to those used by drivers and problematic drugs users. Real-case studies indicate which substances may cause observed impairment and involvement in road traffic crashes and at which concentrations; however, those studies cannot be used to quantify crash risks or determine causality. All three types of studies are needed to obtain a broad and complete picture as they may complement each other when assessing the effects of substance use on road traffic safety.

Objective: The purpose of this study is to provide an overview of the prevalence of driving under the influence of alcohol (DUI) according to day of the week, specific roads (urban/rural), daytime or nighttime, and vehicle category. In addition, this study examines how the prohibition of selling alcoholic drinks in shops and supermarkets (not in restaurants) after 10 p.m. has affected the prevalence of DUI. Method: Breath alcohol concentration (BrAC) was collected from all drivers through police checkpoints at 54 locations in Serbia. In this study, 17,945 drivers were tested in urban areas and 19,507 in rural areas. The relationship between DUI during the prohibition on alcohol sales in Belgrade and other large cities in Serbia was determined using logistic regression. Results: On average, every 100th driver in traffic in Serbia was DUI (0.99%). This study shows that the 0 blood alcohol concentration (BAC) limit for motorcyclists does not have an influence on DUI. Moreover, motorcyclists represent the category with the highest share of DUI, with a statistically significantly larger difference compared to drivers of other vehicle categories. These results may be a consequence of the fact that a large number of drivers drive both motorcycles and other vehicle categories (cars or mopeds), so the different BAC limits for nonprofessional drivers may create confusion about the legal BAC limit. Conclusions: This study suggests that the required legal BAC limit for nonprofessional drivers should be the same. The prohibition of selling alcoholic drinks in Belgrade after 10 p.m. does not decrease the prevalence of DUI.