Drugs and Accident Risk in Fatally-Injured Drivers
Olaf H. Drummer, Ph.D.
Victorian Institute of Forensic Pathology, Department of Forensic Medicine, Monash University, 57-83 Kavanagh Street, South Melbourne 3205, Australia
Risk analysis studies to investigate the contribution of drugs to accident causation are limited. We have used a method based on establishing the responsibility of a driver to investigate the involvement of drugs other than alcohol in 1052 fatally injured drivers. The proportion of drivers deemed to be responsible in a drug-free group were compared to drivers with target drugs found in their blood stream.
Drugs (including alcohol) were detected in 49% of the drivers. Alcohol was detected in 36% of the cases, whilst drugs were detected in 22%. 13% had only drugs detected. The remaining 9% of the population involved a combination of drugs and alcohol. The order of prevalence of drugs were marijuana (112 cases), amphetamines and related stimulants (35), benzodiazepines (34) and opiates (34).
Drivers in whom only opiates were detected had an odd's ratio of 2.4, whilst marijuana cases provided a relative risk of 0.6. Drivers in whom stimulants were detected gave an odd's ratio of 1.4 whilst benzodiazepines gave an odd's ratio of 1.0. By contrast the odd's ratio for alcohol was 6.8.
Drivers with higher than therapeutic concentrations detected represented 22 drivers (2.1%). Most of these drivers were found to be culpable. Multiple drug cases also tended to be culpable. The culpability rate in this group was 89% compared to 70% in drug-free drivers.
These data show that only a small proportion of impaired drivers are drug effected, the remainder being impaired by alcohol. The relative risk for psychoactive drugs is also not uniform, with marijuana use providing the least effect on risk, whilst opiate use seems to provide the largest increase in risk compared to the other drug groups studied.
While certain psychoactive drugs other than alcohol can adversely affect driving skills in simulated studies, epidemiological risk analysis data which provides an assessment of the contribution, of specific drugs or drug classes to accident causation is limited. The effect of benzodiazepines and minor tranquillisers on accident risk are uncertain [Skegg et al, 1979; Jick et al, 1981; Lagier et al, 1993], while the effects of THC appears to be slight or even protective [Terhune et al, 1992; Williams et al, 1985]. Assessment of risk for other drugs or drug groups has not been studied in any detail.
We have used a method based on establishing the responsibility of a driver using strict scoring guidelines [Robertson & Drummer, 1994]. We have used this approach to investigate the involvement of drugs in over 1000 fatal accidents.
Information of drivers killed in motor vehicle accidents were obtained from records kept either at the Victorian Institute of Forensic Pathology and the State Coroner's Office (Victoria), numerous Coroner's courts in NSW or the Western Australian Police (WA). Accidents occurred from January 1990 to December 1993.
Drivers were scored for responsibility as described by Robertson and Drummer . Cases in which insufficient information was available to allow an assessment of culpability were omitted from the analysis. Toxicology data relating to drivers scored for responsibility were only assessed after the responsibility analysis was conducted.
Toxicological analysis was conducted for a large range of drugs including the drugs of abuse, the benzodiazepines and other prescription drugs. Drugs administered in hospital were excluded. Only cases which had both alcohol and a full range of drug tests were used in the study.
The proportion of drivers deemed to be responsible in a drug-free group were compared to drivers with target drugs found in their blood stream. Accident risk is defined as the odd's ratio of a drug group over the drug-free control group.
Means and 95% confidence intervals are shown in the text and Tables. Data were analysed by smoothed logistic regression. Odd's ratios were adjusted for age and sex [Schleselman, 1982]. EGRET statistical software was used to evaluate these data.
Drugs (including alcohol) were detected in 49% of the drivers. Alcohol was detected in 36% of the cases, whilst drugs were detected in 22%. 13% had only drugs detected. The remaining 9% of the population involved a combination of drugs and alcohol.
The most common drugs detected are shown in Table 1. Over forty drugs were represented in these cases. Illegal drugs were found in 12.9% of the drivers. The most common illegal drugs were marijuana and the stimulants (This group represents the amphetamines, the ephedrines and the slimming drugs such as phentermine etc). However four cases involved heroin and only one case involved cocaine.
Type and Abundance of Drugs
|Drug/th>||Abundance (%) /th>|
|Anti-depressant drugs/td>||1.0 /td>|
|Anti-convulsant drugs/td>||0.6 /td>|
|Anti-inflammatory drugs/td>||0.6 /td>|
Odd's ratios and statistical significance for drug groups are shown in Table 2. Drivers in whom opiates, stimulants or benzodiazepines were detected gave odd's ratio of 2.0 compared to an age and sex matched drug free group, but neither drug group were significant statistically. Marijuana cases provided an odd's ratio of 0.6, but again this was not significant statistically. By contrast the odd's ratio for alcohol was 7.6.
Adjusted Odd's Ratios for Selected Drugs
|Drug/th>||Odd's Ratio*/th>||P-value /th>|
|Alcohol/td>||7.6 (4.6-12)/td>||<0.001 /td>|
|Any Drug/td>||1.4 (0.9-2.2)/td>||0.130 /td>|
|Cannabis/td>||0.6 (0.3-1.0)/td>||0.065 /td>|
|Stimulants/td>||2.0 (0.7-5.6)/td>||0.217 /td>|
|Benzodiazepines/td>||2.0 (0.6-7.0)/td>||0.295 /td>|
|Opiates/td>||2.0 (0.7-6.3)/td>||0.220 /td>|
|Misc. Drugs/td>||2.8 (1.1-7.3)/td>||0.040 /td>|
* 95% confidence interval in parentheses
Drivers with higher than therapeutic concentrations detected represented 22 drivers (2.1%). Most of these drivers were found to be responsible. Multiple drug cases (alcohol excluded) were found in 24 cases (2.3%). Most of these cases were responsible. For example, of the 24 drivers in whom more than one psychoactive drug was detected (alcohol excluded), 22 were deemed culpable, 2 were contributory and 2 were not culpable.
The use of responsibility rates of drivers has been used to establish that alcohol increases accident risk [Terhune et al, 1992; Williams et al, 1985]. This is again confirmed in this study. The prevalence of alcohol at over 30% in the Australian fatally-injured driver population reinforces the magnitude of alcohol-related trauma which still exist on Australian roads.
The contribution of drug use on road trauma and accident risk is less well defined. While most common drug type detected were the illegal drugs, marijuana, certain stimulants and certain opiates, their effect individually and collectively were small compared to alcohol.
Drivers with higher than therapeutic drug concentrations and drivers involving multiple drug use tended to be responsible. If cases involving alcohol were excluded, then such cases represented 2.6% of the driving population. This contrasts to ~30% of the population involving alcohol over 0.05 gram/100 mL (general legal limit in Australia).
It was of some interest that cannabis tended to show a negative effect on relative risk when other drug groups showed an increase. This phenomenon has also been seen elsewhere [Terhune et al, 1992; Williams et al, 1985]. The most likley reason probably relates to the over compensation of marijuana-using drivers on their driving skills. Over compensation may be caused simply by slowing down and avoiding adverse driving situations. These observations do not seem to be related to whether delta-9-THC or 11-carboxy-THC are measured in blood [Terhune et al, 1992; Williams et al, 1985].
In conclusion, these findings show that the contribution of drugs to accident causation is much lower than for alcohol. While more cases are required before any definitive conclusions can be made on the effect of specific drug types on driving risk, cases involving multiple drug use and higher than therapeutic drug concentrations tended to be culpable in fatal accidents.
There were many persons and/or organisations who provided valuable assistance to various parts of this project;. Ms. Lynette Kornmehl; Ms Maryanne Maisey; the staff of the Victorian Institute of Forensic Pathology and the State Coroners Office; Dr. Phillip Swann of Vic Roads; members of the Advisory Group on Drugs and Driving (AGODD); Dr. Peter Vulcan of the Accident Research Centre, Monash University; NSW State Coroners; staff of the NSW Institute of Forensic Medicine; staff of the NSW Division of Analytical Laboratories; Dr. David Saffron of the Road Safety Unit of the NSW Roads and Traffic Authority; the Federal Office of Road Safety; WA Police; the WA Coroner; staff of the Toxicology Section of the Western Australian Department of Mines, and Professor John McNeil and Dr. Andrew Forbes of the Department of Social and Preventative Medicine, Monash University.
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