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

TY - JOUR

T1 - Determining the sex-specific distributions of average daily alcohol consumption using cluster analysis. Is there a separate distribution for people with alcohol dependence?

AU - Jiang, Huan

AU - Lange, Shannon

AU - Tran, Alexander

AU - Imtiaz, Sameer

AU - Rehm, Jürgen

PY - 2021/6/7

Y1 - 2021/6/7

N2 - BACKGROUND: It 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.METHODS: Data 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.RESULTS: Modeling 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.CONCLUSIONS: Overall, 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.

AB - BACKGROUND: It 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.METHODS: Data 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.RESULTS: Modeling 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.CONCLUSIONS: Overall, 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.

KW - Alcohol Drinking/epidemiology

KW - Alcoholism/epidemiology

KW - Cluster Analysis

KW - Ethanol

KW - Female

KW - Humans

KW - Male

KW - Sex Distribution

U2 - 10.1186/s12963-021-00261-4

DO - 10.1186/s12963-021-00261-4

M3 - SCORING: Journal article

C2 - 34098997

VL - 19

JO - POPUL HEALTH METR

JF - POPUL HEALTH METR

SN - 1478-7954

IS - 1

M1 - 28

ER -