Preschool Children in Childcare Settings Do Not Consume a Healthy Diet Despite Menus that Meet Recommended Dietary Standards
Bibliographic record
Abstract
Purpose/Objective: To compare preschool lunch menus that meet dietary guidelines to what is actually served and consumed. Methods: Fifty-two preschool children (mean±SD, age 3y and 10m ± 8m) from a university early childhood center participated in the 10-week study. Dietary intake was measured by a registered dietitian using direct observation for pre and post meal analysis. Energy and nutrient content was completed using Food Processor Nutrition Analysis by ESHA. Results: There was a significant (p<0.05) difference for total kilocalories (kcals) between what was on the menu (448 ± 130) and to what was served to the children (523 ± 148) compared to what was consumed (361 ± 178) by the children. There was a significant (p<0.05) difference for grams of fat between what food was listed on the menu (16.0 ± 8.7g), the food served to the children (21.2 ± 9.7g), and the food consumed (14.5 ± 10.0g) by the children. There was a significant (p<0.05) difference for grams of carbohydrate between what food was listed on the menu (55.3 ± 18.9g) and the food served to the children (56.5 ± 20.5g) compared to what was consumed (38.5 ± 21.7g) by the children. Children consumed only 46.9% of the vegetables, 88.9% of dairy products, 82.0% of fruits, 81.8% of grains and 72.8% of meats served, and 77.9% of all fats/sweets served to them at lunch. Conclusion: The results indicated that menus that meet recommended dietary standards do not translate into what children are served or consumed, in particular, for vegetables.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".