Estimated effects of the implementation of the Mexican warning labels regulation on the use of health and nutrition claims on packaged foods
Bibliographic record
Abstract
BACKGROUND: The use of health and nutrition claims on front-of-pack labels may impact consumers' food choices; therefore, many countries have established regulations to avoid misinformation. This study describes the prevalence of health and nutrition claims on the front-of-pack of food products in retail stores in Mexico and estimate the potential effects of the Official Mexican Standards 051 (new regulation that includes specifications for implementing warning labels and other packaging elements such as health and nutrition claims on less healthy foods) on the prevalence of these claims. METHODS: This is a cross-sectional study in which health and nutrition claims, nutrition information panels, and the list of ingredients of all foods and beverages available in the main retail stores in Mexico City were collected. The products were grouped by level of processing according to the NOVA food system classification. Claims were classified using the internationally harmonized INFORMAS taxonomy. According to the criteria of the new Mexican front-of-pack labelling regulation, the effect on the reduction on the prevalence of health and nutrition claims was estimated by type of food and by energy and nutrients of concern thresholds. RESULTS: Of 17,264 products, 33.8% displayed nutrition claims and 3.4% health claims. In total, 80.8% of all products in the Mexican market were classified as "less healthy"; 48.2% of products had excess calories, 44.6% had excess sodium, and 40.7% excess free sugars. The new regulation would prevent 39.4% of products with claims from displaying health and nutrition claims (P < 0.001); the largest reduction is observed for ultra-processed foods (51.1%, P < 0.001). The regulation thresholds that resulted in the largest reduction of claims were calories (OR 0.62, P < 0.001) and non-sugar sweeteners (OR 0.54, P < 0.001). CONCLUSIONS: The new Mexican front-of-pack labelling regulation will prevent most processed and ultra-processed foods from displaying health and nutrition claims and will potentially improve information on packaging for consumers.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".