Longitudinal Drinking Patterns and Their Clinical Correlates in Million Veteran Program Participants

Abstract

BACKGROUND\nA 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.\n\n\nMETHODS\nUsing 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.\n\n\nRESULTS\nOf 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\xa0=\xa00.94). 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.\n\n\nCONCLUSIONS\nTrajectories 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.