Tove Hels

Risk of severe driver injury by driving with psychoactive substances

Driving with alcohol and other psychoactive substances imposes an increased risk of severe injury accidents. In a population-based case-control design, the relative risks of severe driver injury (MAIS≥2) by driving with ten substance groups were approximated by odds ratios (alcohol, amphetamines, benzoylecgonine, cocaine, cannabis, illicit opiates, benzodiazepines and Z-drugs, i.e. zolpidem and zopiclone, medicinal opioids, alcohol-drug combinations and drug-drug combinations). Data from six countries were included in the study: Belgium, Denmark, Finland, Italy, Lithuania and the Netherlands. Case samples (N=2490) were collected from severely injured drivers of passenger cars or vans in selected hospitals in various regions of the countries. Control samples (N=15,832) were sampled in a uniform sampling scheme stratified according to country, time, road type and season. Relative risks were approximated by odds ratios and calculated by logistic regression. The estimates were adjusted for age, gender and country. The highest risk of the driver being severely injured was associated with driving positive for high concentrations of alcohol (≥0.8 g/L), alone or in combination with other psychoactive substances. For alcohol, risk increased exponentially with blood alcohol concentration (BAC). The second most risky category contained various drug-drug combinations, amphetamines and medicinal opioids. Medium increased risk was associated with medium sized BACs (at or above 0.5 g/L, below 0.8 g/L) and benzoylecgonine. The least risky drug seemed to be cannabis and benzodiazepines and Z-drugs. For male drivers, the risk of being severely injured by driving with any of the psychoactive substances was about 65% of that of female drivers. For each of the substance groups there was a decrease in the risk of severe driver injury with increasing age. It is concluded that among psychoactive substances alcohol still poses the largest problem in terms of driver risk of getting injured.

Alcohol and drugs in seriously injured drivers in six European countries

The objective of this study was to determine the presence of alcohol and drugs in drivers severely injured in traffic crashes in six European countries. Data were collected from 2492 seriously injured drivers of cars and vans in Belgium, Denmark, Finland, Italy, Lithuania, and the Netherlands, between 2007 and 2010. Toxicological analysis was performed with chromatographic techniques on whole blood for 23 substances. The percentage of drivers positive for at least one psychoactive substance ranged between 28% (Lithuania) and 53% (Belgium). Alcohol (≥0.1 g/L) was the most common finding with the highest percentage in Belgium (42.5%). Among the alcohol-positive drivers, 90.5% had a blood alcohol count (BAC) ≥0.5 g/L and 65.7% had a BAC ≥1.3 g/L. Benzodiazepines (0.0-10.2%) and medicinal opioids (0.5-7.8%) were the most prevailing medicinal drugs, but half of the concentrations were lower than therapeutic. Cannabis (0.5-7.6%) was the most prevailing illicit drug. Alcohol was found in combination with drugs in 2.3-13.2% of the drivers. Drug combinations were found in 0.5-4.3% of the drivers. This study confirms the high prevalence of psychoactive substances in injured drivers, but we observed large differences between the participating countries. Alcohol was the most common finding, followed by cannabis and benzodiazepines. Notable are the many drivers having a BAC ≥ 1.3 g/L. The majority of the substances were found in combination with another psychoactive substance, mostly alcohol. The high prevalence of high BACs and combinations (compared to roadside surveys) suggest that those drivers are most at risk and that preventive actions should target them preferentially.

Psychoactive substances in seriously injured drivers in Denmark

This study assesses the presence of a number of psychoactive substances, including alcohol, based on blood samples from 840 seriously injured drivers admitted to five selected hospitals located in five different regions of Denmark. The study was a part of the EU 6th framework program DRUID (Driving Under the Influence of Drugs, Alcohol and Medicines). Blood samples were screened for 30 illegal and legal psychoactive substances and metabolites as well as ethanol. Danish legal limits were used to evaluate the frequency of drivers violating the Danish legislation while limit of quantification (LOQ) was used for monitoring positive drivers. Tramadol is not included in the Danish legislation therefore the general cut off, as decided in the DRUID project was used. Overall, ethanol (18%) was the most frequently identified compound (alone or in combination with other drugs) exceeding the legal limit, which is 0.53g/l in Denmark. The percentage of seriously injured drivers testing positive for medicinal drugs at levels above the Danish legal limit was 6.8%. Benzodiazepines and Z-drugs (6.4%) comprised the majority of this group. One or more illegal drugs (primarily amphetamines and cannabis) were found to be above the Danish legal limit in 4.9% of injured drivers. Young men (median age 31 years) were over-represented among injured drivers who violated Danish law for alcohol and drugs. Diazepam (4.4%), tramadol (3.2%), and clonazepam (3.0%) were the medicinal drugs most frequently detected at levels above LOQ, whereas amphetamines (5.4%) (amphetamine [5.2%] and methamphetamine [1.5%]), tetrahydrocannabinol (3.7%), and cocaine (3.3%), including the metabolite benzoylecgonine, were the most frequently detected illegal drugs. A driver could be positive for more than one substance; therefore, percentages are not mutually exclusive. Poly-drug use was observed in 112 (13%) seriously injured drivers. Tramadol was detected above DRUID cutoffs in 2.1% of seriously injured drivers. This is 3.5 times that observed in a Danish survey of randomly selected drivers. Moreover, illegal and medicinal drug levels above the Danish legal limit were present more than 10 times as frequently as in injured drivers, whereas ethanol was present more than 30 times as frequently than in randomly selected drivers. The results indicate that there is an increased risk in traffic when driving under the influence of psychoactive drugs, especially alcohol in young male drivers.

Presence of psychoactive substances in oral fluid from randomly selected drivers in Denmark.

This roadside study is the Danish part of the EU-project DRUID (Driving under the Influence of Drugs, Alcohol, and Medicines) and included three representative regions in Denmark. Oral fluid samples (n=3002) were collected randomly from drivers using a sampling scheme stratified by time, season, and road type. The oral fluid samples were screened for 29 illegal and legal psychoactive substances and metabolites as well as ethanol. Fourteen (0.5%) drivers were positive for ethanol (alone or in combination with drugs) at concentrations above 0.53g/l, which is the Danish legal limit. The percentage of drivers positive for medicinal drugs above the Danish legal concentration limit was 0.4%; while, 0.3% of the drivers tested positive for one or more illicit drug at concentrations exceeding the Danish legal limit. Tetrahydrocannabinol, cocaine, and amphetamine were the most frequent illicit drugs detected above the limit of quantitation (LOQ); while, codeine, tramadol, zopiclone, and benzodiazepines were the most frequent legal drugs. Middle aged men (median age 47.5 years) dominated the drunk driving group, while the drivers positive for illegal drugs consisted mainly of young men (median age 26 years). Middle aged women (median age 44.5 years) often tested positive for benzodiazepines at concentrations exceeding the legal limits. Interestingly, 0.6% of drivers tested positive for tramadol, at concentrations above the DRUID cut off; although, tramadol is not included in the Danish list of narcotic drugs. It can be concluded that driving under the influence of drugs is as serious a road safety problem as drunk driving.

Understanding traffic crash under-reporting: Linking police and medical records to individual and crash characteristics

ABSTRACT Objective: This study aligns to the body of research dedicated to estimating the underreporting of road crash injuries and adds the perspective of understanding individual and crash factors contributing to the decision to report a crash to the police, the hospital, or both. Method: This study focuses on road crash injuries that occurred in the province of Funen, Denmark, between 2003 and 2007 and were registered in the police, the hospital, or both authorities. Underreporting rates are computed with the capture–recapture method, and the probability for road crash injuries in police records to appear in hospital records (and vice versa) is estimated with joint binary logit models. Results: The capture–recapture analysis shows high underreporting rates of road crash injuries in Denmark and the growth of underreporting not only with the decrease in injury severity but also with the involvement of cyclists (reporting rates of about 14% for serious injuries and 7% for slight injuries) and motorcyclists (reporting rates of about 35% for serious injuries and 10% for slight injuries). Model estimates show that the likelihood of appearing in both data sets is positively related to helmet and seat belt use, number of motor vehicles involved, alcohol involvement, higher speed limit, and females being injured. Conclusions: This study adds significantly to the literature about underreporting by recognizing that understanding the heterogeneity in the reporting rate of road crashes may lead to devising policy measures aimed at increasing the reporting rate by targeting specific road user groups (e.g., males, young road users) or specific situational factors (e.g., slight injuries, arm injuries, leg injuries, weekend).

Random and systematic errors in case-control studies calculating the injury risk of driving under the influence of psychoactive substances

Between 2006 and 2010, six population based case-control studies were conducted as part of the European research-project DRUID (DRiving Under the Influence of Drugs, alcohol and medicines). The aim of these case-control studies was to calculate odds ratios indicating the relative risk of serious injury in car crashes. The calculated odds ratios in these studies showed large variations, despite the use of uniform guidelines for the study designs. The main objective of the present article is to provide insight into the presence of random and systematic errors in the six DRUID case-control studies. Relevant information was gathered from the DRUID-reports for eleven indicators for errors. The results showed that differences between the odds ratios in the DRUID case-control studies may indeed be (partially) explained by random and systematic errors. Selection bias and errors due to small sample sizes and cell counts were the most frequently observed errors in the six DRUID case-control studies. Therefore, it is recommended that epidemiological studies that assess the risk of psychoactive substances in traffic pay specific attention to avoid these potential sources of random and systematic errors. The list of indicators that was identified in this study is useful both as guidance for systematic reviews and meta-analyses and for future epidemiological studies in the field of driving under the influence to minimize sources of errors already at the start of the study.

Effectiveness of Electronic Stability Control on Single-Vehicle Accidents

Objective: This study aims at evaluating the effectiveness of electronic stability control (ESC) on single-vehicle injury accidents while controlling for a number of confounders influencing the accident risk. Methods: Using police-registered injury accidents from 2004 to 2011 in Denmark with cars manufactured in the period 1998 to 2011 and the principle of induced exposure, 2 measures of the effectiveness of ESC were calculated: The crude odds ratio and the adjusted odds ratio, the latter by means of logistic regression. The logistic regression controlled for a number of confounding factors, of which the following were significant. For the driver: Age, gender, driving experience, valid driving license, and seat belt use. For the vehicle: Year of registration, weight, and ESC. For the accident surroundings: Visibility, light, and location. Finally, for the road: Speed limit, surface, and section characteristics. Results: The present study calculated the crude odds ratio for ESC-equipped cars of getting in a single-vehicle injury accident as 0.40 (95% confidence interval [CI], 0.34–0.47) and the adjusted odds ratio as 0.69 (95% CI, 0.54–0.88). No difference was found in the effectiveness of ESC across the injury severity categories (slight, severe, and fatal). Conclusions: In line with previous results, this study concludes that ESC reduces the risk for single-vehicle injury accidents by 31% when controlling for various confounding factors related to the driver, the car, and the accident surroundings. Furthermore, it is concluded that it is important to control for human factors (at a minimum age and gender) in analyses where evaluations of this type are performed.

Infrastructure and spatial effects on the frequency of cyclist-motorist collisions in the Copenhagen Region

ABSTRACT Promoting cycling aims at reducing congestion and pollution as well as encouraging healthy and sustainable lifestyles but generally clashes with the perception of crash risk while riding a bicycle that is still the most significant disincentive to cycling. This study sheds light on the factors affecting the probability of cyclist–motorist collisions while accounting for heterogeneity and spatial correlation. The current study analyzed the factors contributing to increase crash risk while riding a bicycle by focusing on 5,349 cyclist–motorist collisions within 269 traffic zones in the Copenhagen Region. The model controlled for traffic exposure for bicycles and motorized transport modes, evaluated the effects of infrastructure and socioeconomic characteristics of the zones, and accounted for heterogeneity and spatial correlation across the zones. A Poisson-lognormal model with second-order conditional autoregressive (CAR) priors confirmed the existence of the safety in numbers phenomenon, contradicted previous literature about bicycle facilities not being helpful in reducing crash risk, highlighted the need for Copenhagen-style bicycle paths especially in suburban areas, and emphasized how heterogeneity and spatial correlation play a significant role in explaining the probability of cyclist-motorist crash occurrence.