Nutrient Declarations and Nutritional Quality of Processed and Ultra‐processed Foods Sold in Guatemala
Bibliographic record
Abstract
Background Obesity and high blood pressure are major risk factors for diet‐related chronic diseases (DRCD), such as diabetes, in Guatemala. High consumption of critical nutrients (energy, saturated fat, trans fat, total sugar, added sugar and sodium) is linked to DRCD. Guatemala's current food labelling regulation mandates nutrient declarations only if healthy or nutrient claims are made. Objective To assess, for the first time, the nutritional information available on packaged foods in Guatemala and to evaluate differences in the nutritional quality of processed (P) and ultra‐processed (UP) foods according to the Nutrient Profile model of the Pan American Health Organization (PAHO). Methods Two major supermarkets in Guatemala City were selected. All packaged foods (excluding baby foods, coffee, tea, sugar, herbs and spices) were photographed to extract nutritional information if available. Declaration of critical nutrients was determined. Nutritional quality was assessed according to the Nutrient Profile model of PAHO. Results We extracted nutritional information from 3463 food products. Out of these, 7% were classified as P, and 83% as UP. The remainder 10% were unprocessed/minimally processed foods or culinary ingredients. Energy content was not declared on 16% and 10% [p= 0.005]; total fat on 17% and 10% [p=0.001]; saturated fat on 25% and 15% [p<0.0001]; trans fat on58% and 48% [p=0.002]; total sugar on 39% and 26%; [p<0.0001] added sugar on 100% and 99% [p=0.214]; and sodium or salt on 17% and 11% [p=0.004] of P and UP products, respectively. Only 38% of P and 39% of UP foods had all the nutritional information required for classification with the PAHO nutrient profile model [p=0.720]. We found excessive amounts of at least one critical nutrient in and 84% of P and 89% of UP [p=0.219] and artificial sweeteners in 9% UP products. The food group with the lowest number of nutrient declarations was processed meat and meat products. Conclusion Both processed and ultra‐processed products contain excessive amounts of critical nutrients. Several critical nutrients associated with chronic diseases are not consistently reported in labels of processed and ultra‐processed foods in Guatemala. Nutritional information is limited, and the use of a nutrient profiling system to evaluate nutritional quality is difficult due to missing information. Current regulation concerning food labelling should be revised and enforced to improve the nutritional information available to consumers in order to create healthier food environments and to stimulate the food industry to reformulate their products towards healthier alternatives. Support or Funding Information International Development Research Centre (IDRC), Canada
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".