ArticleAlcoholism, clinical and experimental research2019
Longitudinal Drinking Patterns and Their Clinical Correlates in Million Veteran Program Participants.
Article in Alcoholism, clinical and experimental research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 5 citations in OpenAlex.
- Patterns of Cannabis Use among Women With HIV in the United States.AIDS and behavior · 2025Article
- Racial and Ethnic Bias in the Diagnosis of Alcohol Use Disorder in Veterans.The American journal of psychiatry · 2023Article
- COVID-19 and liver injury: Pathophysiology, risk factors, outcome and management in special populations.World journal of hepatology · 2023Review
- Covid-19 and alcohol associated liver disease.Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver · 2022Review
- Predictors of early and sustained cessation of heavy drinking over 5 years among adult primary care patients.Addiction (Abingdon, England) · 2022Article
Corrections and comments
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Authors and funding
5 authors at 3 institutions in 1 country.
Funding
Abstract
backgroundA variety of measures have been developed to screen for hazardous or harmful drinking. The Alcohol Use Disorders Identification Test-Consumption (AUDIT-C) is one of the screening measures recommended by the U.S. Preventive Services Task Force. Annual administration of the AUDIT-C to all primary care patients is required by the U.S. Veterans Affairs Health System. The availability of data from the repeated administration of this instrument over time in a large patient population provides an opportunity to evaluate the utility of the AUDIT-C for identifying distinct drinking groups.
methodsUsing data from the Million Veteran Program cohort, we modeled group-based drinking trajectories using 2,833,189 AUDIT-C scores from 495,178 Veterans across an average 6-year time period. We also calculated patients' age-adjusted mean AUDIT-C scores to compare to the drinking trajectories. Finally, we extracted data on selected clinical diagnoses from the electronic health record and assessed their associations with the drinking trajectories.
resultsOf the trajectory models, the 4-group model demonstrated the best fit to the data. AUDIT-C trajectories were highly correlated with the age-adjusted mean AUDIT-C scores (rs = 0.94). Those with an alcohol use disorder diagnosis had 10 times the odds of being in the highest trajectory group (consistently hazardous/harmful) compared to the lowest drinking trajectory group (infrequent). Those with hepatitis C, posttraumatic stress disorder, liver cirrhosis, and delirium had 10, 7, 21, and 34%, respectively, higher odds of being classified in the highest drinking trajectory group versus the lowest drinking trajectory group.
conclusionsTrajectories and age-adjusted mean scores are potentially useful approaches to optimize the information provided by the AUDIT-C. In contrast to trajectories, age-adjusted mean AUDIT-C scores also have clinical relevance for real-time identification of individuals for whom an intervention may be warranted.
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