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Do we eat what we buy? Relative validity of grocery purchase data as an indicator of food consumption in the LoCard study.

Henna VepsäläinenJaakko NevalainenSatu KinnunenSuvi T ItkonenJelena MeiniläSatu MännistöLiisa UusitaloMikael FogelholmMaijaliisa Erkkola
Published in: The British journal of nutrition (2021)
The validity of grocery purchase data as an indicator of food consumption is uncertain. This paper investigated 1) the associations between food consumption and grocery purchases using automatically accumulated purchase data, and 2) whether the strength of the associations differed in certain sub-populations. The participants filled in a food frequency questionnaire (FFQ), and a major Finnish retailer issued us with their loyalty-card holders grocery purchase data covering the 1- and 12-month periods preceding the FFQ. We used gamma statistics to study the association between thirds/quarters of FFQ and grocery purchase data (frequency/amount) separately for 18 food groups among the 11,983 participants. Stratified analyses were conducted for subgroups based on gender, family structure, educational level, household income and self-estimated share of purchases from the retailer. We also examined the proportion of participants classified into the same, adjacent, subsequent and opposite categories using the FFQ and purchase data. The gammas ranged from 0.12 (cooked vegetables) to 0.75 (margarines). Single households had stronger gammas than two-adult families, and participants with >60% of purchases from the retailer had stronger gammas. For most food groups, the proportion of participants classified into the same or adjacent category was >70%. Most discrepancies were observed for fresh/cooked vegetables, berries, and vegetable oils. Even though the two methods did not categorize all food groups similarly, we conclude that grocery purchase data are able to describe food consumption in an adult population, and future studies should consider purchase data as a resource-saving and moderately valid measure in large samples.
Keyphrases
  • electronic health record
  • big data
  • human health
  • risk assessment
  • physical activity
  • young adults
  • climate change
  • mass spectrometry
  • childhood cancer