Adherence to Dietary Recommendations Supports Canadian Children’s Academic Achievement
Bibliographic record
Abstract
PURPOSE: We aimed to determine if adherence to established Canadian, American, and WHO-developed nutrition recommendations supported children's academic achievement. METHODS: Data from a health survey of 1595 grade 5 students in Alberta, Canada, was used. Dietary intake was assessed using a validated food frequency questionnaire. Adherence to recommendations for food group servings, saturated fat intake, and free sugars intake was assessed. Survey data were linked to grade 6 standardized exam results. Multivariable mixed effects linear regression models were employed to assess the association between adherence to recommendations and academic achievement. RESULTS: Boys who met current recommendations for free sugars scored on average 5.67% better on exams (β: 5.67; 95% CI: 3.14, 8.29). Boys who met recommendations for milk and alternatives scored 3.45% better on exams (β: 3.45; 95% CI: 0.67, 6.23). Though results indicated that adhering to dietary recommendations was beneficial for girls' academic achievement, no result was statistically significant. CONCLUSIONS: Adherence to current dietary recommendations has benefits for children's academic achievement. This evidence may be used to inform continued development and promotion of dietary recommendations and to support school-based nutrition initiatives.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".