The Impact of School Nutrition Policy on Diet Quality of Children and Youth in Canada
Bibliographic record
Abstract
Improving diet quality is an important public policy initiative targeted to enhance population health worldwide. In this regard, school nutrition policy is an important means to promote healthy diet among children and youth. In Canada, six provinces implemented mandatory school nutrition policies at different times between 2005 and 2011. We investigated the impact of mandatory school nutrition policy on diet quality of Canadian children and youth using a quasi- experimental study design. Using 24-hour 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 regression models to quantify the effect of school nutrition policy on diet quality. We conducted stratified analyses by sex, school grade, and household income to gain additional insights into the effect of nutrition policy. We found that the effect of mandatory school nutrition policy on diet quality, measured by DQI, increased by 4.34 points (95% CI: 1.83 - 6.85) per child during school-hours in provinces with mandatory nutrition policy compared to control provinces. Although the confidence intervals overlap, the effect was higher among males (6.51 points, 95% CI: 2.93 - 10.09) compared to females (2.14 points, 95% CI: -1.25 - 5.52), and the effect among children in elementary schools was higher (4.82 points, 95% CI: 1.97 - 7.67) compared to those in high schools (3.37 points, 95% CI: -1.22 - 7.95). 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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".