Search resultsModelling over week patterns of alcohol consumption
Title
Modelling over week patterns of alcohol consumption
Publication type
Journal Article
Year of Publication
2008
Authors
Journal
Alcohol and Alcoholism
Volume
43
Issue
2
Pagination
215 - 222
Date published
2008
ISBN
07350414 (ISSN)
Keywords
Adult, Aged, Aged, 80 and over, alcohol consumption, Alcohol Drinking, Alcoholic Beverages, Alcoholism, article, Bayes theorem, controlled study, dietary intake, drinking behavior, education, Female, Health Surveys, human, Humans, major clinical study, male, methodology, Middle Aged, Models, Biological, Portugal, priority journal, risk assessment, Risk Factors, Socioeconomic Factors, statistical model, Time Factors
Abstract
Aims: This study aims to analyze alcohol consumption patterns throughout a week, controlled by socio-demographic characteristics, and to discuss the adequacy of the complex models employed. Methods: The sample included 496 participants, from both sexes, ≥40 years old and with 7-day dietary records. Bayesian generalized additive mixed models (GAMM) were applied using two approaches: a multinomial model, with three categories of alcohol consumption behaviour including; non-drinkers, alcohol during meals only and alcohol at any time; and a gamma model for drinkers which considered the total amount of alcohol ingested per day. Results: The multinomial model captured two different patterns of alcohol consumption: a sharp increase in consumption on weekends for mealtime only drinkers, the dominant behaviour among drinkers and a linear increase from Monday towards Sunday for those who drank at anytime. The effect of higher education changed from slightly protective for mealtime only drinkers to risky for anytime drinkers. The amount of alcohol consumed presents a pattern similar to the meals-only drinking. Conclusions: Alcohol consumption increased during the week. Two different alcohol consumption patterns were identified according to drinking behaviours. The methodological approach utilized was essential in uncovering these patterns.