Aggregating dimensions of alcohol consumption to predict medical and social consequences

Details

Serval ID
serval:BIB_A2AEA23480FC
Type
Article: article from journal or magazin.
Publication sub-type
Review (review): journal as complete as possible of one specific subject, written based on exhaustive analyses from published work.
Collection
Publications
Title
Aggregating dimensions of alcohol consumption to predict medical and social consequences
Journal
Journal of Substance Abuse
Author(s)
Rehm  J., Gmel  G.
ISSN
0899-3289 (Print)
Publication state
Published
Issued date
2000
Volume
12
Number
1-2
Pages
155-68
Notes
Journal Article
Review
Abstract
BACKGROUND: Alcohol consumption has many different dimensions. For each potential medical or social outcome, different dimensions of consumption may have different relationships. However, these relationships are not independent of each other and this multidimensionality is often mishandled or not taken into consideration at all in current alcohol epidemiology. OBJECTIVE: To give recommendations on how to aggregate dimensions of alcohol consumption to predict social and medical consequences. METHODS: Based on a review of relevant papers, different statistical methods to deal with aggregating dimensions of alcohol consumption in predicting outcomes are compared and discussed. RESULTS: Regression approaches may be used to aggregate different dimensions of alcohol consumption to predict medical and social outcomes. However, the substantive interpretation of regression in general has to be taken into consideration. CONCLUSIONS: Future research in alcohol epidemiology should incorporate different dimensions of consumption and should analyze them by regression approaches either using the dummy variable approach or using suitable interaction terms.
Keywords
Alcohol Drinking/adverse effects/*epidemiology Alcohol-Related Disorders/*epidemiology Cross-Sectional Studies Data Collection/statistics & numerical data *Health Surveys Humans Models, Statistical Social Problems/*statistics & numerical data
Pubmed
Web of science
Create date
25/01/2008 17:15
Last modification date
20/08/2019 15:08
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