Nutritional quality of foods and beverages on child-care centre menus in Mexico
Bibliographic record
Abstract
OBJECTIVE: The purpose of the present study was to assess the nutritional quality of foods and beverages listed on menus serving children in government-sponsored child-care centres throughout Mexico. DESIGN: For this cross-sectional menu assessment, we compared (i) food groups and portion sizes of foods and beverages on the menus with MyPlate recommendations and (ii) macronutrients, sugar and fibre with Daily Reference Intake standards. SETTING: Menus reflected foods and beverages served to children attending one of 142 government-sponsored child-care centres throughout Mexico. SUBJECTS: There were fifty-four distinct menus for children aged 4–6 months, 7–9 months, 10–12 months, 13–23 months, 24–47 months and 48–72 months. RESULTS: Menus included a variety of foods meeting minimum MyPlate recommendations for each food category except whole grains for children aged 48–72 months. Menus listed excessive amounts of high-energy beverages, including full-fat milk, fruit juice and sugar-sweetened beverages for children of all ages. The mean daily energy content of menu items yielded an average of 2?76 MJ for infants, 4.77 MJ for children aged 13–23 months, 5.36 MJ for children aged 24–47 months and 5.87 MJ for children aged 48–72 months. Foods and beverages on menus provided sufficient grams of carbohydrate and fat, but excessive protein. CONCLUSIONS: Menus provided a variety of foods but excessive energy. Whole grains were limited, and high-energy beverages were prevalent. Both may be appropriate targets for nutrition intervention. Future studies should move beyond menus and assess what children actually consume in child care.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".