The dynamics in food selection stemming from price awareness and perceived income adequacy: a cross-sectional study using 1-year loyalty card data
Bibliographic record
Abstract
BACKGROUND: Higher cost of healthy foods may explain unhealthy dietary patterns in lower-income households. Unfortunately, combining food selection and nutrient intake data to price and expenditure is challenging. Food retailer's customer loyalty card data, linked to nutrient composition database, is a novel method for simultaneous exploration of food purchases, price, and nutrition. OBJECTIVES: We studied the associations between perceived income adequacy (PIA) as a grouping variable with price (per kilogram or megajoule) and the volume of purchases (percentage of expenditure or energy) simultaneously as outcome variables for 17 most purchased food groups. METHODS: We used 1-year (2018) loyalty card data from the largest grocery chain in Finland. Participants were 28,783 loyalty cardholders who made ≥41% of food purchases from the retailer and answered an online questionnaire at the midpoint of data collection. The 5-level PIA described the perceived financial situation in the household. Energy and nutrient content of foods purchased were from the Finnish Food Composition Database Fineli. We calculated the Nutrient Rich Food Index per 100 g food using 11 nutrients. Trends in prices and expenditures between PIA levels were analyzed using 2-sided Jonckheere-Terpstra tests, with false discovery rate control (Benjamini-Hochberg method) and confounder adjustments (inverse probability weighting). RESULTS: Lower PIA participants selected cheaper foods per kilogram and megajoule within most food groups. They also favored unhealthy food groups cheap in energy [<1 € (USD 1.18)/MJ]. Despite lower purchase price, the expenditure (%) among lower PIA was higher on alcohol, snacks, sugar-sweetened beverages, and sweets and chocolates. CONCLUSIONS: Participants with lower PIA showed stronger price awareness. It is crucial to consider the pricing of competing alternative food groups, when steering toward environmentally sustainable and healthier food purchases. Package labeling might also direct the selection of healthier choices among the less expensive items within a food group.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".