Building nutritionally meaningful product groups for loyalty card data: the LoCard Food Classification process

Abstract Analysing customer loyalty card data is a novel method for assessing dietary 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 into appropriate categories suitable for the use of nutrition and health research. This paper depicts how such a classification is compiled and how it reflects the nutritional quality of the food classes. Healthfulness was considered the main criterion guiding the reclassification of the 3574 grocery product groups. In addition, the main ingredient of the product group, type of food and purpose of use, and carbon footprint were considered in the reclassification process. The classified food groups were linked with the national food composition database, and the nutrient profile was assessed by calculating the Nutrient Rich Food Index (NRFI) for each product group. Our four-level classification hierarchy had 38 food groups at its broadest level (Class 1). Only 1% (n=38) of the grocery product groups were left unclassified. Standard deviation in NRFI decreased from 0.21 to 0.08 from the broadest to the finest level of classification. We conclude it is possible to assign a great majority of the grocery product groups to classes based on their nutritional quality. However, the challenge is classification of product groups that lack detailed information on their contents or include main ingredients that have opposite health effects, such as products including both plant- and animal-based proteins.