Estimating driver risk using alcohol biomarkers, interlock blood alcohol concentration tests and psychometric assessments: initial descriptives

Authors


Paul R. Marques, Pacific Institute for Research and Evaluation, 11720 Beltsville Drive, Suite 900, Calverton, MD 20705-3111, USA. E-mail: marques@pire.org

ABSTRACT

Aim  To identify alcohol biomarker and psychometric measures that relate to drivers' blood alcohol concentration (BAC) patterns from ignition interlock devices (IIDs).

Design, setting, participants, measurements  In Alberta, Canada, 534 drivers, convicted of driving under the influence of alcohol (DUI), installed IIDs and agreed to participate in a research study. IID BAC tests are an established proxy for predicting future DUI convictions. Three risk groups were defined by rates of failed BAC tests. Program entry and follow-up blood samples (n = 302, 171) were used to measure phosphatidyl ethanol (PETH), carbohydrate deficient transferrin (%CDT), gamma glutamyltransferase (GGT) and other biomarkers. Program entry urine (n = 130) was analyzed for ethyl glucuronide (ETG) and ethyl sulphate (ETS). Entry hair samples were tested for fatty acid ethyl esters (FAEE) (n = 92) and ETG (n = 146). Psychometric measures included the DSM-4 Diagnostic Interview Schedule Alcohol Module, Alcohol Use Disorders Identification Test (AUDIT), the time-line follow-back (TLFB), the Drinker Inventory of Consequences (DRINC) and the Temptation and Restraint Inventory (TRI).

Findings  Except for FAEE, all alcohol biomarkers were related significantly to the interlock BAC test profiles; higher marker levels predicted higher rates of interlock BAC test failures. PETH, the strongest with an overall analysis of variance F ratio of 35.5, had significant correlations with all nine of the other alcohol biomarkers and with 16 of 19 psychometric variables. Urine ETG and ETS were correlated strongly with the IID BAC tests.

Conclusions  The findings suggest that several alcohol biomarkers and assessments could play an important role in the prediction and control of driver alcohol risk when re-licensing.

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