title: Aggregating dimensions of alcohol consumption to predict medical and social consequences.
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.
authors: Addiction Research Foundation Division, Centre for Addictions and Mental Health (CAMH), Toronto, Canada. jurgen_rehm@camh.net
authors: J
authors: J
authors: Rehm
authors: G
authors: G
authors: Gmel
mesh_terms: D000428:Alcohol Drinking / Q000009:adverse effects / Q000453:epidemiology*; D019973:Alcohol-Related Disorders / Q000453:epidemiology*; D003430:Cross-Sectional Studies; D003625:Data Collection / Q000706:statistics & numerical data; D006306:Health Surveys; D006801:Humans; D015233:Models, Statistical; D012940:Social Problems / Q000706:statistics & numerical data*