Patterns of alcohol consumption and related behaviour in Great Britain: A latent class analysis of the alcohol use disorder identification test (AUDIT)

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Abstract

Aims: Attempts have been made to develop typologies to classify different types of alcoholism. However, limited research has focused on classifications to describe general patterns of alcohol use in general population samples. Methods: Latent class analysis was used to create empirically derived behaviour clusters of alcohol consumption and related problems from the Alcohol Use Disorder Identification Test (AUDIT) based on data from a large stratified multi-stage random sample of the population of Great Britain. Multinomial logistic regression was performed to describe these resultant classes using both demographic variables and mental health outcomes. Results: Six classes best described responses in the sample data. Three were heavy consumption groups, one with multiple negative consequences, one experiencing alcohol-related injury and social pressures to cut down and an additional class with memory loss. There was one moderate class with few negative consequences, and finally two mild consumption groups, one with alcohol-related injury and social pressure to cut down and one with no associated problems. Conclusions: Alcohol use in Great Britain can be hypothesized as reflecting six distinct classes, four of which follow a continuum of increased consumption leading to increased dependence and related problems and two that do not. Differences between alcohol use classes are apparent with reduced risk of depressive episode in moderate classes and an increased risk of anxiety disorders for the highest consumers of alcohol. © The Author 2008. Published by Oxford University Press on behalf of the Medical Council on Alcohol. All rights reserved.

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APA

Smith, G. W., & Shevlin, M. (2008). Patterns of alcohol consumption and related behaviour in Great Britain: A latent class analysis of the alcohol use disorder identification test (AUDIT). Alcohol and Alcoholism, 43(5), 590–594. https://doi.org/10.1093/alcalc/agn041

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