Predictors and prevalence of hazardous alcohol use in middle-late to late adulthood in Europe

Abstract

Objectives: Even low to moderate levels of alcohol consumption can have detrimental health consequences, especially in older adults (OA). Although many studies report an increase in the proportion of drinkers among OA, there are regional variations. Therefore, we examined alcohol consumption and the prevalence of hazardous alcohol use (HAU) among men and women aged 50+ years in four European regions and investigated predictors of HAU.

Methods: We analyzed data of N = 35,042 participants of the European SHARE study. We investigated differences in alcohol consumption (units last week) according to gender, age and EU-region using ANOVAs. Furthermore, logistic regression models were used to examine the effect of income, education, marital status, history of a low-quality parent–child relationship and smoking on HAU, also stratified for gender and EU-region. HAU was operationalized as binge drinking or risky drinking (<12.5 units of 10 ml alcohol/week).

Results: Overall, past week alcohol consumption was 5.0 units (±7.8), prevalence of HAU was 25.4% within our sample of European adults aged 50+ years. Male gender, younger age and living in Western Europe were linked to both higher alcohol consumption and higher risks of HAU. Income, education, smoking, a low-quality parent–child relationship, living in Northern and especially Eastern Europe were positively associated with HAU. Stratified analyses revealed differences by region and gender.

Conclusions: HAU was highly prevalent within this European sample of OA. Alcohol consumption and determinants of HAU differed between EU-regions, hinting to a necessity of risk-stratified population-level strategies to prevent HAU and subsequent alcohol use disorders.

Keywords:

• Hazardous alcohol use
• older adults
• middle-aged adults
• Europe
• alcohol
• drug and alcohol abuse
• cross-national/international studies
• environmental factors/housing/rural-urban factors
• epidemiology (mental health)

Acknowledgement

This paper uses data from SHARE Waves 6 and 7 (DOIs: 10.6103/SHARE.w6.710, 10.6103/SHARE.w7.711), see Börsch-Supan et al. (2013) for methodological details.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the German Ministry of Education and Research (Forschungsnetz AERIAL 01EE1406A, 01EE1406B, 01EE1406I) and the Deutsche Forschungsgemeinschaft DFG (SFB 940). The SHARE data collection has been funded by the European Commission, DG RTD through FP5 (QLK6-CT-2001-00360), FP6 (SHARE-I3: RII-CT-2006-062193, COMPARE: CIT5-CT-2005-028857, SHARELIFE: CIT4-CT-2006-028812), FP7 (SHARE-PREP: GA No. 211909, SHARE-LEAP: GA No. 227822, SHARE M4: GA No. 261982, DASISH: GA No. 283646) and Horizon 2020 (SHARE-DEV3: GA No. 676536, SHARE-COHESION: GA No. 870628, SERISS: GA No. 654221, SSHOC: GA No. 823782) and by DG Employment, Social Affairs & Inclusion through VS 2015/0195, VS 2016/0135, VS 2018/0285, VS 2019/0332, and VS 2020/0313. Additional funding from the German Ministry of Education and Research, the Max Planck Society for the Advancement of Science, the U.S. National Institute on Aging (U01_AG09740-13S2, P01_AG005842, P01_AG08291, P30_AG12815, R21_AG025169, Y1-AG-4553-01, IAG_BSR06-11, OGHA_04-064, HHSN271201300071C, RAG052527A) and from various national funding sources is gratefully acknowledged (see www.share-project.org).