Department of Food and Nutrition, FIN-00014 University of Helsinki, P.O. Box 66, Agnes Sjöbergin katu 2, Helsinki, Finland.
The Finnish Foundation for Alcohol Studies, c/o THL, P.O. Box 30, FIN-00271, Helsinki, Finland.
BMC Public Health. 2019 Jun 20;19(1):787. doi: 10.1186/s12889-019-7096-3.
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.
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.
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.
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.
饮酒是导致疾病、死亡和社会危害的重要原因,它与吸烟和不健康饮食交织在一起。使用自动注册的零售数据进行研究是一种新颖的方法,不会受到报告偏差的影响。基于芬兰一家主要零售商的忠诚度卡数据(LoCard),该零售商的市场份额为 47%,我们研究了酒精支出及其与食品和烟草支出的关系。
数据包括 2016 年来自芬兰南部的 13274 名忠诚度卡持有者的 1527217 次购物活动。采用 K-均值聚类分析根据购物篮中含酒精饮料的内容对其进行分组。通过线性混合模型测试了不同聚类之间食物和烟草的绝对和相对平均值的差异,其中忠诚度卡持有者为随机因素。
迄今为止,最常见的购物篮类型不含酒精饮料,其次是含有少量啤酒或苹果酒的购物篮。随着酒精饮料支出的增加,食品支出也随之增加。与酒类购买最一致相关的食物是香肠、软饮料和小吃。相对于总篮子价格,香烟支出在中价位酒精篮子中达到峰值。
不健康选择的聚类发生在个体购物事件的层面上。购买大量酒精饮料的人并没有削减他们的食品预算。自动注册的购买数据为个人和人群的健康行为提供了有价值的见解。