Analyzing the Effect of Selected Control Policy Measures and SocioDemographic Factors on Alcoholic Beverage Consumption in Europe within the AMPHORA Project: Statistical Methods

Abstract

This paper describes the methods used to investigate variations in total alcoholic beverage consumption as related to selected control intervention policies and other socioeconomic factors (unplanned factors) within 12 European countries involved in the AMPHORA project. The analysis presented several critical points: presence of missing values, strong correlation among the unplanned factors, long-term waves or trends in both the time series of alcohol consumption and the time series of the main explanatory variables. These difficulties were addressed by implementing a multiple imputation procedure for filling in missing values, then specifying for each country a multiple regression model which accounted for time trend, policy measures and a limited set of unplanned factors, selected in advance on the basis of sociological and statistical considerations are addressed. This approach allowed estimating the “net” effect of the selected control policies on alcohol consumption, but not the association between each unplanned factor and the outcome.

Keywords :

• multiple imputation
• multiple regression
• time series
• alcoholic beverage consumption

THE AUTHORS

Michela Baccini, Ph.D., is researcher in medical statistics at the University of Florence. Author of several papers in the field of environmental epidemiology and biostatistics, she worked on time series analysis, meta-analysis, health impact assessment, and multiple imputation.

Giulia Carreras, Ph.D., is a statistician at the Cancer Prevention and Research Institute in Florence. She is author of several papers in the field of primary prevention and environmental epidemiology. Her key research areas are Markov models and dynamic models for decision making, analysis of prevention studies, and health impact assessment.

Notes

2 The reader is referred to Hills's criteria for causation which were developed in order to help assist researchers and clinicians determine if risk factors were causes of a particular disease or outcomes or merely associated. [Hill, A. B. (1965). The environment and disease: associations or causation? Proceedings of the Royal Society of Medicine 58: 295–300.]. Editor's note.