Evidence map›Paper›PMID 40888934›Full record

ArticleSocial psychiatry and psychiatric epidemiology2025

The interplay of alcohol use symptoms and sociodemographic factors in the HELIUS study: A network perspective.

Karoline B S Huth, Orestis Zavlis, Judy Luigjes, Henrike Galenkamp, Anja Lok, Karien Stronks, Claudi L H Bockting, Anneke Goudriaan, Maarten Marsman, Ruth J van Holst

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Article in Social psychiatry and psychiatric epidemiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Karoline B S HuthDepartment of Psychology, University of Amsterdam, Amsterdam, the Netherlands. k.huth@uva.nl.ORCID http://orcid.org/0000-0002-0662-1591
Orestis ZavlisDepartment of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands.
Judy LuigjesDepartment of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands.
Henrike GalenkampDepartment of Public and Occupational Health, University of Amsterdam, Amsterdam, the Netherlands.
Anja LokDepartment of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands.
Karien StronksCentre for Urban Mental Health, University of Amsterdam, Amsterdam, the Netherlands.
Claudi L H BocktingDepartment of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands.
Anneke GoudriaanDepartment of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands.
Maarten MarsmanDepartment of Psychology, University of Amsterdam, Amsterdam, the Netherlands.
Ruth J van HolstDepartment of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeResearch on alcohol use disorder has exclusively focused on either its symptom-level mechanisms-the network perspective or sociodemographic determinants-epidemiological research. Moreover, such research failed to stratify analyses for important person-level factors (e.g., sex or ethnicity). Here, we combine network and epidemiological research and stratify analyses by person-level factors.

methodUsing Bayesian inference, we estimated (1) a logistic regression model predicting past-year alcohol consumption from various sociodemographic factors within a large, multiethnic, urban sample in the Netherlands (complete sample: N = 22,164), (2) a cross-sectional network model of alcohol use symptoms and sociodemographic factors among alcohol drinkers of the same sample (drinkers: N = 10,877), and (3) stratified networks at the sex- and ethnic- levels in the same drinkers subsample.

resultsAll of our examined sociodemographic factors predicted past-year alcohol consumption (in order of magnitude: religion, sex, education, employment, perceived ethnic discrimination, and age). Our Bayesian analysis of networks revealed three notable patterns. First, religion was uniquely and negatively related to adverse alcohol use problems (such as having an injury due to drinking). Second, socioeconomic proxies (education and employment) were positively related to binge drinking, but negatively related to its adverse effects (such as 'needing a drink in the morning'). Finally, employment and education were particularly negatively related to alcohol use symptoms within male and female networks, respectively.

conclusionOur results suggest that alcohol use symptoms are differentially related to sociodemographic factors and that these effects are moderated by sex and ethnicity. Our highlighted network links and Bayesian methodologies could prove useful for future research and prevention and intervention efforts on alcohol use disorders.Word count: 4198 words.

Indexed as

Alcohol DrinkingAlcoholismEthnicityAdultAgedBayes TheoremCross-Sectional StudiesFemaleHumansLogistic ModelsMaleMiddle AgedNetherlandsSociodemographic FactorsSocioeconomic FactorsYoung AdultAlcohol useBayesianHELIUS studyNetwork analysisSociodemographic factors

Identifiers

PMID40888934
PMCPMC12572036

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.