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

Marques, Paul ; Tippetts, Scott ; Allen, John ; Javors, Martin ; Alling, Christer LU ; Yegles, Michel ; Pragst, Fritz and Wurst, Friedrich (2010) In Addiction 105(2). p.226-239
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... (More)
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. (Less)
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author
; ; ; ; ; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
ignition interlock, DUI, driver, biomarkers, Alcohol, assessment, phosphatidyl ethanol (PETH)
in
Addiction
volume
105
issue
2
pages
226 - 239
publisher
Wiley-Blackwell
external identifiers
  • wos:000273546100012
  • scopus:74249123871
  • pmid:19922520
ISSN
1360-0443
DOI
10.1111/j.1360-0443.2009.02738.x
language
English
LU publication?
yes
id
5fbd6c8f-6e9f-40e9-bded-cc1edefe22ff (old id 1547720)
date added to LUP
2016-04-01 10:16:49
date last changed
2022-03-27 06:47:46
@article{5fbd6c8f-6e9f-40e9-bded-cc1edefe22ff,
  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.}},
  author       = {{Marques, Paul and Tippetts, Scott and Allen, John and Javors, Martin and Alling, Christer and Yegles, Michel and Pragst, Fritz and Wurst, Friedrich}},
  issn         = {{1360-0443}},
  keywords     = {{ignition interlock; DUI; driver; biomarkers; Alcohol; assessment; phosphatidyl ethanol (PETH)}},
  language     = {{eng}},
  number       = {{2}},
  pages        = {{226--239}},
  publisher    = {{Wiley-Blackwell}},
  series       = {{Addiction}},
  title        = {{Estimating driver risk using alcohol biomarkers, interlock blood alcohol concentration tests and psychometric assessments: initial descriptives}},
  url          = {{http://dx.doi.org/10.1111/j.1360-0443.2009.02738.x}},
  doi          = {{10.1111/j.1360-0443.2009.02738.x}},
  volume       = {{105}},
  year         = {{2010}},
}