School nutrition policy and diet quality of children and youth: a quasi-experimental study from Canada
Bibliographic record
Abstract
OBJECTIVE: We investigated the impact of mandatory school nutrition policy on diet quality of Canadian school children using a quasi-experimental study design. METHODS: Using 24-h dietary recall data from the 2004 Canadian Community Health Survey (CCHS) Cycle 2.2 and 2015 CCHS - Nutrition, we constructed the Diet Quality Index (DQI). We used multivariable difference-in-differences regressions to quantify the DQI scores associated with school nutrition policy. We conducted stratified analyses by sex, school grade, household income, and food security status to gain additional insights into the impact of nutrition policy. RESULTS: We found that mandatory school nutrition policy was associated with an increased DQI score by 3.44 points (95% CI: 1.1, 5.8) during school-hours in intervention provinces relative to control provinces. DQI score was higher among males (3.8 points, 95% CI: 0.6, 7.1) than among females (2.9 points, 95% CI: -0.5, 6.3), and the score among students in elementary schools was higher (5.1 points, 95% CI: 2.3, 8.0) than that among high school students (0.4 points, 95% CI: -3.6, 4.5). We also found that DQI scores were higher for middle-high income and food secure households. CONCLUSION: Provincial mandatory school nutrition policy was associated with better diet quality among children and youth in Canada. Our findings suggest that other jurisdictions may consider implementing mandatory school nutrition policy.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.015 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| 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".