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Pharmacoepidemiol Drug Saf. Author manuscript; available in PMC 2009 Nov 23.
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PMCID: PMC2780583
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The impact of medicinal drugs on traffic safety: a systematic review of epidemiological studies



To evaluate the quality of epidemiological research into effects of medicinal drugs on traffic safety and the current knowledge in this area.

Data sources

The bibliographic search was done in Medline electronic database using the keywords: ((accident* or crash*) and traffic and drug*) leading to 1141 references. Additional references were retrieved from the Safetylit website and the reference lists of selected studies. Original articles published in English or French, between April 1st, 1979 and July 31st, 2008, were considered for inclusion. We excluded descriptive studies, studies limited to alcohol or illicit drug involvement, and investigations of injuries other than from traffic crashes. Studies based on laboratory tests, driving simulators or on-the-road driving tests were also excluded. Eligible studies had to evaluate the causal relationship between the use of medicinal drugs and the risk of traffic crashes. Study quality was assessed by two independent experts, according to a grid adapted from the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement.


22 studies of variable methodological quality were included. Definition of drug exposure varied across studies and depended on the data sources. Potential confounding due to the interaction between the effects of the medicinal drug and disease-related symptoms was often not controlled. The risk of motor-vehicle crashes related to benzodiazepines has been amply studied and demonstrated. Results for other medicinal drugs remain controversial.


There is a need for large studies, investigating the role of individual substances in the risk of road traffic crashes.

Keywords: Accidents, Traffic; statistics & numerical data; Benzodiazepines; adverse effects; Bias (Epidemiology); Epidemiologic Research Design; Humans; Odds Ratio; Pharmaceutical Preparations; adverse effects; Risk Assessment; Risk Factors
Keywords: traffic crashes, medicinal drugs, methodology


Traffic crashes are a common cause of death in many countries. Among the numerous risk factors (eg, speed, alcohol, talking on cell phones, road infrastructures), the effect of medicinal drugs has not received sufficient attention. Assessment of effects of medicinal drugs on driving ability by laboratory tests, driving simulators or on-the-road driving tests provides helpful insights on potential impact, but only partially assesses the impact in “real life” conditions where driver behaviour, health status, and road traffic environment interact. Reports on the state of knowledge about drugs and driving were published in 1999 1 and 2003 2, showing an increase concern about the role medicinal drug use may play in road traffic crashes. In 2003, a European Safety Action program was set up to encourage research on the effects of medicinal drugs, in order to establish a European classification regarding road safety 3. Two literature reviews, focusing on a few medicinal drugs (benzodiazepines, opioids, antihistamines and antidepressants), concluded that benzodiazepines represent a major traffic safety problem but remained cautious about other medicinal drugs 4 5. The aim of this article is to review available epidemiological studies, their results and methodological issues, in order to make recommendations for further research.


Search strategy

The bibliographic search was done in Medline electronic database using the keywords: ((accident* or crash*) and traffic and drug*). We updated the search using the Safetylit website which provides an updated literature on injury prevention with a special section on “alcohol and other drugs”. The reference lists of papers considered for inclusion were scanned for any further potentially eligible studies. Original articles published in English or French, between April 1st 1979 (oldest article we included) and July 31st, 2008 (end of inclusion period), were considered for inclusion. We excluded descriptive studies, studies limited to involvement of alcohol or illicit drugs, and studies of injury risk other than in traffic crashes. Studies based on laboratory tests, driving simulators or on-the-road driving tests were also excluded. Eligible studies were those that evaluated the causal relationship between the use of medicinal drugs and the risk of traffic crashes.

Quality assessment

A reading grid was adapted from the STROBE statement (Strengthening the Reporting of Observational Studies in Epidemiology) 6 and from the quality assessment checklists published by Salmi 7 (see Appendix 1). Criteria covered methods of selecting participants, data collection regarding outcomes, exposures and potential confounders, statistical methods and reported results, as well as discussion content.

Participant selection was evaluated according to the relevance of eligibility and exclusion criteria to reflect a general population of drivers, the choice of sources, the independence of selection from the event or the drug exposure, and the comparability of the reference group. We considered the way medicinal drug exposure was assessed. In studies on medicinal drug consumption and crash risk, several potential confounders should be measured and controlled in analyses. Apart from subjects’ age and gender, interaction between disease-related symptoms and the effects of the medicinal drug used to treat the disease, which can both modulate the risk of crash, should be addressed. Other important variables to be measured are the number of kilometres driven in each group and the consumption of alcohol or other drugs. We assessed the relevance of statistical methods and results presentation and discussion. Two authors (EL and LO) reviewed the selected studies independently according to the grid criteria. Disagreements were referred to a third reviewer (LRS) and resolved by discussion.


Bibliographic search retrieved 1141 references from which 16 eligible studies were selected on the basis of their title and abstract. An additional six studies were found either from a Safetylit website search or from the reference lists of the initial 16 studies. This process led us to select 22 epidemiological studies of the impact of medicinal drugs on the risk of traffic crashes 829. Their methodology and main results are presented in Table 1.

Table 1
Epidemiological studies of traffic crash risk and medicinal drug consumption: methodology and main results

Quality of available research

Two sources for the outcome variable (the crash) are described in these studies. In eight studies, case selection was based on emergency admission to hospital for injuries related to the crash 16 18 20 21 23 2628. Accident record databases represented the most frequent source for identification of subjects involved in traffic crashes 815 17 19 22 25 29. Drummer et al 11 focused on fatal crashes while two other studies only considered non-fatally injured drivers 18 27. Case-control was the most frequent design 10 13 1517 20 2325 27. Two strategies were used to select an appropriate control group, composed of drivers who have not been involved in a crash. The first method consisted of random selection from moving traffic or at petrol stations 16 20. Selection was therefore done on a voluntary basis, which can lead to a selection bias. In the second method, control subjects were selected from the source of case data, such as health insurance records 17, driver licence records 10 13 15 19 25, general practitioner records 23 or hospital admissions 27. Depending on the characteristics of the source population, extrapolation to the general driver population must be done with caution, especially if there is no indication that these controls actually drive.

Among selected epidemiological studies, five were responsibility studies 11 18 19 24 26 which can be viewed as a particular case-control study. The main principle is that if a medicinal drug contributes to crash causation, it would be over-represented in drivers whose responsibility in the crash was demonstrated compared to non-responsible drivers. Responsibility analysis, based on police records, must be objective and independent of data related to medicinal drug consumption. A standardized method to determine the level of driver responsibility was described by Robertson and Drummer 30 and applied in studies by Drummer et al 11 and Longo et al 18. The responsibility determination criteria were not described precisely in the other three studies 19 24 26.

Barbone et al 8 and Ray et al 22 used a case-crossover design, where the exposure risk to a given medicinal drug in a period immediately before the crash was compared with the exposure risk in an earlier period. Each subject was his own control and confounding due to all fixed characteristics was therefore eliminated, including genetics, personality, education, lifestyle and chronic diseases. This design, appropriate to study the effects of episodic exposure on the risk of acute events 31, is not adapted to chronic exposure.

Exposed/non-exposed studies have also been conducted, in which users and non-users are followed up for subsequent road traffic crashes 9 12 14 21 22 28 29. Unlike case-crossover designs, these studies ensure independence of subject selection from outcome and can address chronic consumption. This is not always true in case-control studies.

Available data about medicinal drug prescription (eg, dose, treatment duration) depended on national records. The link between prescription and actual consumption is estimated in various ways. Exposure periods can be estimated according to the date of dispensation and the number of defined daily doses (DDDs) dispensed 9 12 25 29 or according to the prescribed duration of treatment when known 8 15. Sensitivity to definition of consumption period has been tested, comparing the results obtained for a presumed exposure of seven days with fourteen days, starting the day after dispensing 9 12 14. Incident use was defined as exposure after a non-use period to assess the effect of treatment initiation 9 14 15 21 25 28 29, as opposed to chronic consumption defined by repeated exposure 10 13 28.

Drug exposure assessment was performed by the analysis of urine or blood samples in six studies 11 16 18 20 24 27. This method measures actual use and offers the advantage of accounting for non-prescribed medicinal drugs. The main limits are the small number of substances tested and the time period between crash and sampling which may be critical for some medicinal drugs.

McGwin et al 19 collected medicinal drug exposure data during a telephone interview, leading to possible bias due to self-reporting. Indeed, Honkanen et al 16 showed that only half of the patients in whom benzodiazepines were detected by serum analysis reported having taken these medicinal drugs.

Another issue relates to the grouping of drugs according to therapeutic class, often for reasons of statistical power. As an example, all benzodiazepines were assessed as a single class of exposure 8 11 1720 22 27, whereas, in this class, drugs can have different pharmacokinetic properties: benzodiazepines with longer half-lives are probably more likely to be associated with an associated risk of road traffic crash 15.

Concomitant consumption of non-medicinal psychoactive substances was sometimes controlled in the analysis: illicit drugs in two studies 11 18, alcohol in five studies 11 18 20 21 24. The frequency of driving was measured and accounted for in statistical models in only two studies 17 19. A few studies considered the potential interaction with medical conditions 10 13 15 17 19 25. McGwin et al 19 estimated the risk for angiotensin-converting enzyme inhibitors and anticoagulants adjusted for the conditions for which they are prescribed, and the same strategy was used for nonsteroidal anti-inflammatory drugsand arthritis. In the study of the effect of warfarin, adjustment was made for cardiovascular events and strokes 10. Other studies adjusted for a summary chronic disease score based on selected prescription medications used in the management of chronic conditions 13 15 17 25.

The effects of medicinal drugs on road safety


The impact of benzodiazepines on the risk of car crashes has been extensively considered in several studies 8 11 12 1424 2628. The strength of the associations and the consistency between studies indicate that benzodiazepines are a cause of car crash risk, although part of the effect could result from the indication of benzodiazepines (sleep problems). The effects of benzodiazepines on the risk of crash have been demonstrated in the elderly 15 22, but also among younger drivers 8 14 21 28. The effects of treatment initiation have been explored 14 15 21 28. A cohort study about the risk of hospitalisation for traffic crash injuries showed a diminished risk with elapsed time from the new prescription fill-date 21, probably reflecting tolerance to medicinal drug effects or decreasing doses or use over time. In the case-crossover study, a dose-response relationship between benzodiazepine consumption and crash risk was described 8. Benzodiazepine hypnotics and anxiolytics have been studied separately 8 12 21, as well as long and short half-life benzodiazepines 15 and individual drugs (eg, zopiclone, zolpidem, diazepam, lorazepam) 14 28. Four studies did not find any significant relationship. Two of them lacked sufficient statistical power 11 17, and in the third information was obtained via self-report 19. In the last study, the authors note that the assay used to detect blood benzodiazepines measures certain benzodiazepines poorly, especially triazolam 24.


Two studies conducted in older drivers found a significant association between the risk of being involved in a car crash and the consumption of tricyclic antidepressants (relative risk=2.2 [1.3–3.5] 22 and odds ratio=2.3 [1.1–4.8] 17). Bramness et al found an increased risk for drivers who had received a prescription for any antidepressant, slightly higher for young drivers (18–34 years old), but without adjusting for the use of other narcotics and without being able to distinguish between the effects of the medicinal drugs and depression 29. Two other studies showed no association, probably because of insufficient statistical power 19 20. However, despite a study population of 410 306 people aged at least 18 years, Barbone et al 8 found no relationship with the risk of traffic crash, for selective serotonin-receptor inhibitors or for tricyclic antidepressants, suggesting the risk to be specific to older drivers.


In a nested case-control study, the risk of being involved in an injurious motor vehicle crash for elderly people who use lithium was found to be increased two-fold. Carbamazepine, another common mood stabiliser, also used in epilepsy, was not associated with the risk of traffic crashes 13.


Engeland et al 12 found that the risk of road traffic crashes was increased in users of natural opium alkaloids such as codeine, morphine and oxycodone (SIR=2 [1.7–2.4]), and that the risk was higher in the 18–54 age group. In the case-control study by Leveille et al 17, opioid analgesic use was also associated with an elevated crash risk in older drivers (OR=1.8 [1–3.4]). Mura et al 27 also found the association significant, but no distinction was made between licit and illicit use of opiates as only biological samples were used for their detection. No significant association was found by three studies which may have lacked statistical power 11 20 23, and by Ray et al 22. A longitudinal study from a cohort of 13 548 French workers suggested that pain and pain treatment could be associated with the risk of crash. The authors noted, however, that severe pain is more likely to be treated and may itself be associated with poorer driving performance 32.

H1 antihistamines

A few studies explored the association between H1 antihistamines and car crashes. Skegg et al identified only 3 antihistamine users (5.3%) among a small sample of 57 cases 23. In the studies by Leveille et al 17 and by Ray et al 22, both conducted in the elderly, the association was not significant. Nevertheless, Howard et al 33 showed that histaminergic consumption was associated with the risk of traffic crashes in professional drivers. There is a lack of epidemiological data on impact of the different generations of antihistamines which have different ability to cross the blood-brain barrier and induce sedation.

Diabetic treatment

The risk of crashes for diabetic drivers is linked to degenerative complications and to hypoglycaemic seizures related to treatment. Inconsistent results have been published about the role of diabetes and its treatment in causing traffic crashes, probably because of the heterogeneity in treatment regimes 3437. A responsibility study conducted in the elderly did not find any association between diabetes and at-fault crash involvement and no interaction with treatment type 19 36. Traffic injury risk has been reported to be 2.6-fold higher in older diabetic drivers, especially those treated with insulin (OR=5.8 [1.2–28.7]) but not in those using oral hypoglycaemic agents 35. Hemmelgarn et al 25 found the rate ratios for current users of insulin monotherapy were 1.4 [1.0–2.0] and 1.3 [1.0–1.7] for sulfonylurea and metformin combined. The authors note the difficulty of distinguishing between medicinal drug effects and diabetes-related complications since treatment is strongly correlated with disease progression.

Cardiovascular drugs

Among the medicinal drugs considered in epidemiological studies, calcium channel blockers were not associated with an increased risk of crashes 12, and were associated with a reduced risk of at-fault crash involvement, as well as vasodilators 19. In the latter study, anticoagulants and angiotensin-converting enzyme inhibitors were positively associated with being at-fault for a crash but the odds ratios were no longer significant after adjustment for concomitant diseases 19. In a recent case-control study, the use of warfarin, an anticoagulant, was not associated with an elevated rate of injurious motor vehicle crash 10.


Carisoprodol, a muscle relaxing drug, has been considered in a pharmacoepidemiological study because of its central nervous system depressant potential. The standardised incidence ratio for being involved in a crash having been prescribed carisoprodol was 3.7 [2.9–4.8] 9.

Nonsteroidal anti-inflammatory drugs

Recently, Engeland et al 12 raised the question of nonsteroidal anti-inflammatory drug (NSAID) effects in the central nervous system, as they found a significant association with the risk of traffic crash (OR=1.5 [1.3–1.9]). This result could be an indicator of clinical disability in some arthritic conditions. McGwin et al found that NSAID association with an increased risk of at-fault involvement in crashes persisted after adjustment for arthritis which was also independently associated with crash risk in females. The authors note however that some NSAID users may be undiagnosed for musculoskeletal impairments 19.


The 22 studies included in this systematic review were of variable methodological quality. Several different research methods were used, leading to difficulties to compare them. The sample populations were different, ranging from victims of road traffic crashes with personal injury, victims hospitalized for road traffic crash injury to fatally injured drivers. Drug exposure assessment was heterogeneous, mostly depending on available retrospective data or on the molecule selection for biological testing.

Another identified issue was related to potential confounding. Particularly, alcohol or illicit drugs interact with medicinal drugs in impairing driving abilities and were not always taken into account. Driving conditions such as weekday, time of the day, road environment are important factors too, so is the number of miles driven. These latter factors were rarely assessed and included in risk modelling. Finally, the main issue of confounding by indication is addressed in a few studies only. Consequently, it often remains unclear whether crashes occur as a result of medicinal drug consumption or of the underlying disease, a concern highlighted in a literature review on benzodiazepines and driving 38.

This systematic review highlights several fields where more epidemiological data are needed. There is a need for large studies, investigating the individual and combined role of substances in the risk of road traffic crashes. The differential effect of the older generations of medicinal drugs versus newer ones must be compared to adapt patient care. The impact on crash risk of dose changes, beginning or end of treatment, must be further investigated. As described above, some non-psychoactive medicinal drugs may alter driving abilities due to their action on physiological functions or regarding central side effects. The impact of these medicinal drugs on road traffic crash risk has hardly been assessed in epidemiological studies so far. Other studies should also be designed to assess the relative roles of disease and medication in the risk of road traffic crashes. Quantifying the risk in patients who may be under-represented in the general driving population is also of interest as they may be at high risk due to the disease itself, and to the medicinal drugs used to treat the condition (eg Parkinson’s disease and dopamine agonists 39).

Key points

  • Taking benzodiazepines has been identified as a risk for road traffic crashes in several epidemiological studies. However, data are missing for other medicinal drugs.
  • Main methodological issues are confounding by indication and grouping of drugs with different properties.
  • Exposure assessment methods are heterogeneous, partly explaining the inconsistent literature results.

Appendix 1: Reading grid

Study design
Objectives are clearly stated
Key elements of study design are provided
Location and dates are specified
Cohort study
Eligibility criteria are defined and appropriate
Exclusion criteria are defined and appropriate
Sources are described and appropriate
Selection method is described and appropriate
Selection is independent from risk of collision
Follow-up period is defined and long enough
Compared exposures are described
Reference group is appropriate
Selection procedures are identical in all exposure groups
Case-control study
Eligibility criteria are defined and appropriate
Exclusion criteria are defined and appropriate
Sources are described and appropriate
Selection is independent of drug exposure
Definition of cases is appropriate
Controls are selected from same population as cases
Control group is appropriate
Selection procedures are identical in cases and controls
Matching is appropriate
Drug exposure
Data sources are described and appropriate
Choice of studied drugs is justified
Drug exposure assessment method is described and justified
Case/control status is masked when assessing exposure
Collision data
Data sources are described and appropriate
Collision characteristics are accounted for
Accounting for potential confounders
Associated diseases
Number of kilometres/miles driven
Alcohol and other drugs
Statistical methods
Sample size calculation
Appropriate estimates and models
Control for confounding
Sensitivity analysis
Number of subjects reported
Number of refusals reported
Description of all groups
Reported confidence intervals or p
Key results/study objective
Limitations and possible biases discussed

(Y=Yes, I=Incomplete, N=No, NA= Not Applicable, DNK=Do Not Know)



Conflicts of interest

The authors declare that they have no conflicts of interest.


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