Literature DB >> 19395203

AUDIT and its abbreviated versions in detecting heavy and binge drinking in a general population survey.

Mauri Aalto1, Hannu Alho, Jukka T Halme, Kaija Seppä.   

Abstract

BACKGROUND: The aim of this study was to define optimal cut points for the Alcohol Use Disorders Identification Test (AUDIT) and its abbreviated versions (AUDIT-C, AUDIT-QF, and AUDIT-3), and to evaluate how effectively these questionnaires detect heavy drinking in the general population.
METHODS: The study population consisted of a sub-sample of the National FINRISK Study. A stratified random sample of 3216 Finns, aged 25-64, was invited to a health check. Of these, 1851 (57.6%) completed the AUDIT and participated in person in the Timeline Followback (TLFB) interview regarding their alcohol consumption. The TLFB-based definition of heavy drinking was used as a primary gold standard (for males > or =16 standard drinks average in a week or > or =7 drinks at least once a month; for females, respectively, > or =10 and > or =5 drinks). Areas under receiving operating characteristics curves (AUROCs), sensitivities and specificities were used to compare the performance of the tests. RESULTS AND
CONCLUSIONS: The AUDIT and its abbreviated versions are valid for detecting heavy drinking also in a general population sample. However, performance seems to vary between the different versions and accuracy of each test is achieved only by using tailored cut points according to gender. The AUDIT and AUDIT-C are effective for both males and females. The optimal cut points for males were found to be >/=7 or 8 for AUDIT and > or =6 for AUDIT-C. Among females the optimal cut points were found to be > or =5 for AUDIT and > or =4 for AUDIT-C. The study also indicates that AUDIT-QF among females and AUDIT-3 among males are relatively effective. The cut points for detecting all heavy drinkers (including binge drinkers without exceeding weekly thresholds) were lower than for detecting heavy drinkers excluding those who are only binge drinkers.

Entities:  

Mesh:

Year:  2009        PMID: 19395203     DOI: 10.1016/j.drugalcdep.2009.02.013

Source DB:  PubMed          Journal:  Drug Alcohol Depend        ISSN: 0376-8716            Impact factor:   4.492


  45 in total

1.  Gender differences in the factor structure of the Alcohol Use Disorders Identification Test in multinational general population surveys.

Authors:  Chun-Zi Peng; Richard W Wilsnack; Arlinda F Kristjanson; Perry Benson; Sharon C Wilsnack
Journal:  Drug Alcohol Depend       Date:  2012-01-10       Impact factor: 4.492

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5.  Social network characteristics and heavy episodic drinking among women at risk for HIV/sexually transmitted infections.

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7.  Phosphatidylethanol (PEth) as a biomarker of alcohol consumption in HIV-positive patients in sub-Saharan Africa.

Authors:  Judith A Hahn; Loren M Dobkin; Bernard Mayanja; Nneka I Emenyonu; Isaac M Kigozi; Stephen Shiboski; David R Bangsberg; Heike Gnann; Wolfgang Weinmann; Friedrich M Wurst
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8.  Hazardous Drinking Prevalence and Correlates in Older New Zealanders: A Comparison of the AUDIT-C and the CARET.

Authors:  Andy Towers; Ágnes Szabó; David A L Newcombe; Janie Sheridan; Allison A Moore; Martin Hyde; Annie Britton; Priscilla Martinez; Nadia Minicuci; Paul Kowal; Thomas Clausen; Christine L Savage
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9.  Correlates of HIV infection among people visiting public HIV counseling and testing clinics in Mpumalanga, South Africa.

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Journal:  Afr Health Sci       Date:  2012-03       Impact factor: 0.927

10.  Screening Caregivers of Children for Risky Drinking in KwaZulu-Natal, South Africa.

Authors:  Myra Taylor; Justin Knox; Meera K Chhagan; Shuaib Kauchali; Jane Kvalsvig; Claude Ann Mellins; Stephen M Arpadi; Murray H Craib; Leslie L Davidson
Journal:  Matern Child Health J       Date:  2016-11
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