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Abstract
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AIMS: Harmful drinking patterns are shaped by a broad complex interaction of factors, societal and individual, psychological and behavioral. Although previous studies have focused on a few variables at a time, the current study simultaneously examines a large number of variables in order to create a comprehensive view (i.e. phenotype) of harmful drinking, and to rank the main predictors of harmful and non-harmful drinking by order of importance.
METHODS: We surveyed a large sample of Dutch adults about their habitual drinking characteristics and attitudes, perceptions and motives for drinking. We fed 45 variables into a random forest machine learning model to identify predictors for (1) drinking within and in excess of Dutch guideline recommendations and (2) harmful and non-harmful drinking.
RESULTS: In both models, respondents' subjective perceptions of 'responsible drinking', both per occasion and per week, showed the strongest predictive potential for different drinking phenotypes. The next strongest factors were respondents' reason for drinking, motives for drinking and age. Other variables, such as drinking location, knowledge about alcohol-related health risks and consumption of different beverage types, were not strong predictors of drinking phenotypes.
CONCLUSIONS: Although the direction of the relationship is unclear from the findings, they suggest that interventions and policy measures aimed at individuals and social norms around drinking may offer promise for reducing harmful drinking. Messaging and promotion of drinking guidelines should be tailored with this in mind.
Language: en |