Healthiness, processing, and price discounts of foods advertised in supermarket flyers in Buenos Aires, Argentina
Bibliographic record
Abstract
Introduction: The food environment, encompassing factors such as food availability, advertising, and promotions, can significantly impact dietary choices. The main objective of this study was to characterize the profile of the advertised products in relation to the food groups defined by the Dietary Guidelines for the Argentine Population (GAPA), the degree of processing and their price discounts. Methods: This cross-sectional study analyzed 4355 promotions of foods and beverages in supermarket circulars from seven supermarket chains over an 8-week period in Buenos Aires. Foods were classified into four categories based on the GAPA: 1) core food groups and water, 2) "optional" products (those to be limited), 3) alcoholic beverages, and 4) other foods. Additionally, NOVA classification was used to assess the degree and purpose of processing. The minimum purchase amount required for the discount and the unit price discount were analyzed by food group and degree of processing. Results: Only 37.0% of advertised food products were from the core recommended food groups, while 45.3% and 11.7% were "optional/discretionary" products and alcoholic beverages. In addition, 56% of the food and non-alcoholic beverage promotions included ultra-processed (UP) products. The minimum purchase amount to obtain a discount and relative discounts were higher for "optional" products (p<0.001) and UP (p<0.001) compared to staple food groups and unprocessed or minimally processed foods, respectively. Conclusions: Most advertisements and price promotions found in supermarket circulars were for UP and items that the GAPA recommend limiting, suggesting an environment that is conducive to promoting unhealthy eating behaviors. Funding: International Development Research Center (IDRC; grant Number IDRC 108643-001).
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".