@article{ref1,
title="Estimating long-term drinking patterns for people with lifetime alcohol use disorder",
journal="Medical decision making",
year="2019",
author="Barbosa, Carolina and Dowd, William N. and Aldridge, Arnie P. and Timko, Christine and Zarkin, Gary A.",
volume="ePub",
number="ePub",
pages="ePub-ePub",
abstract="<b>Background.</b> There is a lack of data on alcohol consumption over time. This study characterizes the long-term drinking patterns of people with lifetime alcohol use disorders who have engaged in treatment or informal care. <b>Methods.</b> We developed multinomial logit models using the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC) to estimate short-term transition probabilities (TPs) among the 4 World Health Organization drinking risk levels (low, medium, high, and very high risk) and abstinence by age, sex, and race/ethnicity. We applied an optimization algorithm to convert 3-year TPs from NESARC to 1-year TPs, then used simulated annealing to calibrate TPs to a propensity-scored matched set of participants derived from a separate 16-year study of alcohol consumption. We validated the resulting long-term TPs using NESARC-III, a cross-sectional study conducted on a different cohort. <b>Results.</b> Across 24 demographic groups, the 1-year probability of remaining in the same state averaged 0.93, 0.81, 0.49, 0.51, and 0.63 for abstinent, low, medium, high, and very high-risk states, respectively. After calibration to the 16-year study data (<i>N</i> = 420), resulting TPs produced state distributions that hit the calibration target. We find that the abstinent or low-risk states are very stable, and the annual probability of leaving the very high-risk state increases by about 20 percentage points beyond 8 years. <b>Limitations.</b> TPs for some demographic groups had small cell sizes. The data used to calibrate long-term TPs are based on a geographically narrow study. <b>Conclusions.</b> This study is the first to characterize long-term drinking patterns by combining short-term representative data with long-term data on drinking behaviors. Current research is using these patterns to estimate the long-term cost effectiveness of alcohol treatment.<p /> <p>Language: en</p>",
language="en",
issn="0272-989X",
doi="10.1177/0272989X19873627",
url="http://dx.doi.org/10.1177/0272989X19873627"
}