Crash Risk of Alcohol Impaired Driving

In order to determine the relative crash risk of drivers at various blood alcohol concentration (BAC) levels a case-control study was conducted in Long Beach, CA and Fort Lauderdale, FL. Data was collected on 4,919 drivers involved in 2,871 crashes of all severities. In addition, two drivers at the same location, day of week and time of day were sampled a week after a crash, which produced 10,066 control drivers. Thus, a total of 14,985 drivers were included in the study. Relative risk models were generated using logistic regression techniques with and without covariates such as driver age, gender, marital status, drinking frequency and ethnicity. The overall result was in agreement with previous studies in showing increasing relative risk as BAC increases, with an accelerated rise at BACs in excess of .10 BAC. After adjustments for missing data (hit-and-run drivers, refusals, etc.) the result was an even more dramatic rise in risk, with increasing BAC that began at lower BACs (above .03 BAC). Introduction The role of alcohol in motor vehicle crashes, which was identified as a traffic safety problem by the first decade of this century, remains a major highway safety problem. For example, in the U.S. in 2000, there were 16,653 alcohol-related fatalities, 40% of all traffic fatalities (1). NHTSA defines an alcohol-related fatal crash as one involving either a driver or non-occupant (e.g., pedestrian) who had a BAC of 0.01 grams per deciliter (g/dl) or greater in a police reported crash. While this represents a 25% decline from the 22,084 alcohol-related fatalities reported in 1990 (50% of the toal), it is still an unacceptably large number. Moreover, in 2000, some 31% of all traffic fatalities occurred in crashes in which at least one driver or non-occupant had a BAC of 0.10 or greater. The mechanisms by which alcohol affects individual skills related to safe driving have been studied using well-controlled laboratory experimentation. These laboratory experiments have examined a wide range of BACs from low to relatively high and have found that numerous driving-related skills are degraded beginning at low BACs. The assessment of the risk of crash involvement by drivers at various BACs has been carried out using epidemiological research methods in which a comparison is made of the BACs of crash-involved drivers and similarly atrisk, non-crash-involved drivers. Perhaps the most widely cited epidemiological study of the crash risk produced by alcohol is the Borkenstein Grand Rapids Study (2). In this, and other similar studies, a relative risk function is determined that indicates the likelihood of a driver at a specified BAC becoming involved in a crash compared to similar drivers under the same conditions at 0.00 BAC. These relative risk functions have been widely used to set the legal limits for driving under the influence of alcohol. The emphasis of much of this early research on the role of alcohol in contributing to traffic crashes focused on establishing a causal connection between use of alcohol and crash involvement. With the role of alcohol in causing crashes firmly established, attention has shifted to the issue of at what BAC level elevated risk first occurs. While the Grand Rapids study, and other similar epidemiological studies, contributed greatly to our understanding of the role of alcohol in crashes, it is possible to gain an improved understanding of the relative risk at various BACs through more robust research designs and multivariate analytic techniques. For example, in the Grand Rapids study the control drivers were not matched to the time and location or direction of travel of the specific crash-involved drivers. Also, the measurement of BAC level has improved greatly over the last 30+ years, statistical techniques have become much more sophisticated in their ability to take into account potentially confounding variables, and many of the previous studies failed to collect or to include in their analyses of relative risk many key covariates such as age, gender, alcohol consumption patterns and measures of fatigue known or assumed to be related to the use or effects of alcohol. Finally, the extended time since these earlier studies raises the possibility that a change in the driving and/or drinking environments may have influenced relative risk. Thus, the availability of significantly improved breath alcohol measuring equipment, the possibility of improving the case/control design (based on insights gained over the years), and the potential advantages of modern analytic techniques provided the impetus for the present study. The study was designed to determine the relative risk of crash involvement by BAC level (controlling for other factors like age, gender, alcohol consumption, etc.) and the relative risk for major groups of drivers (e.g., gender and age). Methods A case-control study was conducted in Long Beach, CA and Fort Lauderdale, FL in which data was collected on drivers involved in crashes of all severities. Two drivers at the same location, day of week and time of day were sampled a week after the crash to constitute a control group. Relative risk models were generated using logistic regression techniques with and without the inclusion of covariates such as driver age, gender, marital status and alcohol consumption. Sampling Procedures Data from crash-involved drivers and matched non-crash-involved (control) drivers was collected in Long Beach, CA from June 1997 through September 1998 and in Fort Lauderdale, FL from September 1998 through September 1999. The collection protocol specified crashes were to be sampled during the late afternoon, evening and nighttime hours (4 PM to 2 AM in Long Beach and 5 PM to 3 AM in Fort Lauderdale) when drinking and driving is most prevalent. Two matched control drivers for each crash-involved driver were sampled by returning to the crash scene one week later at the same time as the crash, and stopping at random drivers on the same roadway, traveling in the same direction as the crash involved driver. Drivers were first asked to answer a few survey questions (on drinking habits, prior DUI arrests, use of medicines, mileage, fatigue, trip origin, and demographics) and then were asked to provide a breath sample.