How the data was compiled: The grocery purchase data including 3574 product groups was received from the retailer for research purposes. The data was reclassified into appropriate categories suitable for the use of nutrition and health research. How the data has been handled: A four-level hierarchical classification of product groups was used. Each class on the broadest level of hierarchy (Class 1) was subsequently divided into a reasonable number of finer sub-classes starting with Class level 2, followed by Class 3, and finally, Class 4, which was the most detailed level of hierarchy. The main ingredient of the product group, type of the food and purpose of use, nutritional content, and carbon footprint were considered in the reclassification process. The classified food groups were linked with Finnish food composition database. How the data can be used for research: The re-classified data can be used to measure can be used to infer and describe food purchase patterns, monitor of the nutrition composition of food purchases, monitoring and evaluating dietary environmental and economic sustainability, and deriving consumer segments based on the re-classification. The authors strongly recommend reading the detailed description of the classification is published in https://doi.org/10.21203/rs.3.rs-2826970/v1.

{"references": ["More information of the Locard project and list of publications can be found in https://locard.fi/julkaisut/", "https://doi.org/10.21203/rs.3.rs-2826970/v1"]}