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Background: Alcohol consumption is a significant cause of disease, death and social harm, and it clusters with smoking tobacco and an unhealthy diet. Using automatically registered retail data for research purposes is a novel approach, which is not subject to underreporting bias. Based on loyalty card data (LoCard) obtained by a major Finnish retailer holding a market share of 47%, we examined alcohol expenditure and their associations with food and tobacco expenditures.

Methods: The data consisted of 1,527,217 shopping events in 2016 among 13,274 loyalty card holders from southern Finland. A K-means cluster analysis was applied to group the shopping baskets according to their content of alcoholic beverages. The differences in the absolute and relative means of food and tobacco between the clusters were tested by linear mixed models with the loyalty card holder as the random factor.

Results: By far, the most common basket type contained no alcoholic beverages, followed by baskets containing a small number of beers or ciders. The expenditure on food increased along with the expenditure on alcoholic beverages. The foods most consistently associated with alcohol purchases were sausages, soft drinks and snacks. The expenditure on cigarettes relative to total basket price peaked in the mid-price alcohol baskets.

Conclusion: Clustering of unhealthy choices occurred on the level of individual shopping events. People who bought many alcoholic beverages did not trim their food budget. Automatically registered purchase data provide valuable insight into the health behaviours of individuals and the population.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6587280PMC
http://dx.doi.org/10.1186/s12889-019-7096-3DOI Listing

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