Examining school-day dietary intakes among Canadian children
Bibliographic record
Abstract
Understanding how dietary intakes vary over the course of the school day can help inform targeted school-based interventions, but little is known about the distribution or determinants of school-day dietary intakes in Canada. This study examined differences between school-hour and non–school-hour dietary intakes and assessed demographic and socioeconomic correlates of school-hour diet quality among Canadian children. Nationally representative data from the Canadian Community Health Survey were analyzed using 24-h dietary recalls falling on school days in 2004 (n = 4827). Differences in nutrient and food-group densities during and outside of school hours and differences in School Heathy Eating Index (School-HEI) scores across sociodemographic characteristics were examined using survey-weighted, linear regression models. Children reported consuming, on average, 746 kcal during school hours (one-third of their daily energy intakes). Vitamins A, D, B12, calcium, and dairy products densities were at least 20% lower during school hours compared with non-school hours. Differences in School-HEI scores were poorly explained by sociodemographic factors, although age and province of residence emerged as significant correlates. The school context provides an important opportunity to promote healthy eating, particularly among adolescents who have the poorest school-hour dietary practices. The nutritional profile of foods consumed at school could be potentially improved with increased intake of dairy products, thereby increasing intakes of protein, vitamin A, vitamin D, calcium, and magnesium.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".