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A LITERATURE OVERVIEW OF THE RELATIONSHIP BETWEEN LIFE-EVENTS AND ALCOHOL USE IN THE GENERAL POPULATION
Ist Teil von
Alcohol and alcoholism (Oxford), 2006-07, Vol.41 (4), p.455-463
Ort / Verlag
Oxford: Oxford University Press
Erscheinungsjahr
2006
Quelle
Oxford Journals 2020 Medicine
Beschreibungen/Notizen
Aims: A critical review of the evidence of effects of stressful life-events on alcohol use in the general population, with a particular focus on study design. Methods: A literature search in Medline was conducted, covering the period from 1990 to 2005, to identify articles in which the relationship between life-events and alcohol use in the general population (i.e. non-problem drinking population) was investigated. Samples with a limited age range (e.g. college students) were excluded. Twelve studies with a cross-sectional design, and four articles with a longitudinal design were included in this review. Results: Four cross-sectional studies found evidence that experiencing life-events is related to higher alcohol use, three other studies, however, found no such association. The relationship between specific life-events and alcohol use in the five remaining cross-sectional studies is less clear-cut. Being a victim of crime was associated with higher alcohol use, but divorce and financial problems were related to both higher and lower alcohol use. Health-related life-events were found to be associated with lower alcohol use. In studies with a longitudinal design, it was found that health-related life-events and financial problems caused a decrease in alcohol use, and life-events related to spouse, friends and relatives, and retiring led to an increase in alcohol use. Conclusions: Evidence points towards a relationship between the occurrence of life-events and alcohol use in the general population. The direction of the effect is, however, not unequivocal. When life-events are operationalized or categorized separately they are not only related to an increased alcohol use but also to a decreased alcohol use. Specification of the model to be tested, including buffering factors such as gender, social support, coping resources, as well as baseline consumption, is important for a correct estimation of the effect of negative life-events.