Determining the sex-specific distributions of average daily alcohol consumption using cluster analysis: is there a separate distribution for people with alcohol dependence?

Huan Jiang,Sameer Imtiaz,Alexander Tran,Shannon Lange,Jürgen Rehm

doi:10.1186/s12963-021-00261-4

Abstract

BackgroundIt remains unclear whether alcohol use disorders (AUDs) can be characterized by specific levels of average daily alcohol consumption. The aim of the current study was to model the distributions of average daily alcohol consumption among those who consume alcohol and those with alcohol dependence, the most severe AUD, using various clustering techniques.MethodsData from Wave 1 and Wave 2 of the National Epidemiologic Survey on Alcohol and Related Conditions were used in the current analyses. Clustering algorithms were applied in order to group a set of data points that represent the average daily amount of alcohol consumed. Gaussian Mixture Models (GMMs) were then used to estimate the likelihood of a data point belonging to one of the mixture distributions. Individuals were assigned to the clusters which had the highest posterior probabilities from the GMMs, and their treatment utilization rate was examined for each of the clusters.ResultsModeling alcohol consumption via clustering techniques was feasible. The clusters identified did not point to alcohol dependence as a separate cluster characterized by a higher level of alcohol consumption. Among both females and males with alcohol dependence, daily alcohol consumption was relatively low.ConclusionsOverall, we found little evidence for clusters of people with the same drinking distribution, which could be characterized as clinically relevant for people with alcohol use disorders as currently defined.

Highlights

Alcohol use is a major risk factor for burden of disease [1], and alcohol use disorders (AUDs) comprise a substantial part of the alcohol-attributable disease burden globally [2]
While it is obvious that an individual who completely abstains from consuming alcohol would not be diagnosed with an AUD—i.e., such use is, by definition, a necessary and sufficient cause, there is a great deal of debate in the literature regarding whether or not these conditions can be characterized by specific levels of daily alcohol consumption
Statistical analysis As an exploratory analysis, following traditional fitting of distributions for alcohol use [27, 28], we evaluated the fit of the Log-Normal, Gamma, and Weibull distributions to determine if the distribution of daily alcohol consumption could be appropriately described as unimodal, using the Wave 1 survey

Summary

Introduction

Alcohol use is a major risk factor for burden of disease [1], and alcohol use disorders (AUDs) comprise a substantial part of the alcohol-attributable disease burden globally [2]. While it is obvious that an individual who completely abstains from consuming alcohol would not be diagnosed with an AUD—i.e., such use is, by definition, a necessary and sufficient cause (see [3, 4] for further discussion), there is a great deal of debate in the literature regarding whether or not these conditions can be characterized by specific levels of daily alcohol consumption In both the Diagnostic and Statistical Manual of Mental Disorders, 5th edition (DSM-5) and the International Classification of Diseases, 11th revision (ICD11) [5, 6], AUDs are defined without any reference to the level of drinking, but rather, are based on a nonspecific set of behavioral, social, psychological, and physiological criteria [7, 8]—e.g., continuing to drink even though it is causing trouble with friends/family, and giving up or cutting back on activities that were once important or interesting in order to drink. The aim of the current study was to model the distributions of average daily alcohol consumption among those who consume alcohol and those with alcohol dependence, the most severe AUD, using various clustering techniques

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Conclusion