Department of Food and Nutrition, University of Helsinki, PO Box 66, 00014Helsinki, Finland.
Faculty of Social Sciences (Health Sciences), Tampere University, Kanslerinrinne 1, 33100Tampere, Finland.
Br J Nutr. 2024 Sep 28;132(6):770-781. doi: 10.1017/S0007114524000710. Epub 2024 Apr 18.
Analysing customer loyalty card data is a novel method for assessing nutritional quality and changes in a population's food consumption. However, prior to its use, the thousands of grocery products available in stores must be reclassified from the retailer's original hierarchical structure into a structure that is suitable for the use of nutrition and health research. We created LoCard Food Classification (LCFC) and examined how it reflects the nutritional quality of the grocery product groups. Nutritional quality was considered the main criterion guiding the reclassification of the 3574 grocery product groups. Information on the main ingredient of the product group, purpose of use and carbon footprint was also used at the more granular levels of LCFC. The main challenge in the reclassification was a lack of detailed information on the type of products included in each group, and some of the groups included products that have opposite health effects. The final LCFC has four hierarchical levels, and it is openly available online. After reclassification, the product groups were linked with the Finnish food composition database, and the nutrient profile was assessed by calculating the Nutrient-Rich Food Index (NRFI) for each product group. sd in NRFI decreased from 0·21 of the least granular level to 0·08 of the most granular level of LCFC indicating that the most granular level of LCFC has more homogeneous nutritional quality. Studies that apply LCFC to examine loyalty card data with health and environmental outcomes are needed to further demonstrate its validity.
分析客户忠诚度卡数据是评估人群食物消费的营养质量和变化的一种新方法。然而,在使用之前,必须将商店中数千种杂货产品从零售商的原始层次结构重新分类为适合营养和健康研究使用的结构。我们创建了 LoCard Food Classification(LCFC),并研究了它如何反映杂货产品组的营养质量。营养质量被认为是指导 3574 个杂货产品组重新分类的主要标准。在 LCFC 的更细粒度级别上,还使用了关于产品组主要成分、用途和碳足迹的信息。重新分类的主要挑战是缺乏每个组中包含的产品类型的详细信息,并且一些组中包含的产品具有相反的健康影响。最终的 LCFC 有四个层次结构,并且可以在线公开获得。重新分类后,将产品组与芬兰食物成分数据库链接,并通过计算每个产品组的营养丰富食物指数(NRFI)来评估营养状况。NRFI 中的 sd 从 LCFC 最细粒度级别的 0·21 降低到最粗粒度级别的 0·08,表明 LCFC 的最粗粒度级别的营养质量更加均匀。需要应用 LCFC 来研究与健康和环境结果相关的忠诚度卡数据的研究,以进一步证明其有效性。