Promoting healthy school food environments and nutrition in Canada: a systematic review of interventions, policies, and programs
Bibliographic record
Abstract
CONTEXT: The school food environment is a critical interface for child and adolescent nutrition, and there is a need to understand existing literature on Canadian school food environments to identify equity gaps and opportunities, and empower decision-makers to plan for future action. OBJECTIVE: Literature on Canadian school food and nutrition interventions, policies, programs, and their effects on diets and nutritional status are synthesized and appraised in this systematic review. DATA SOURCES: A search strategy was developed for each database used (Medline, Embase, PsycINFO, ERIC, Cochrane Collaboration, Canadian Electronic Library, BiblioMap), with a combination of free text and controlled vocabulary, for articles published from 1990 to 2021. Unpublished data and grey literature were also searched. DATA EXTRACTION: Quantitative and qualitative studies with an observational or intervention study design, reviews, or program evaluations conducted in Canadian schools with participants aged 5-19.9 years were included. Key study characteristics and risk of bias were extracted independently by 2 investigators using a standardized tool. DATA ANALYSIS: A total of 298 articles were included (n = 192 peer reviewed and 106 from the grey literature), which were mostly conducted in Ontario (n = 52), British Columbia (n = 43), and Nova Scotia (n = 28). Twenty-four interventions, 5 nonevaluated programs, and 1 policy involved Indigenous populations. Overall, 86 articles measured and reported on effectiveness outcomes, including dietary intake; anthropometry; knowledge, attitudes, and practices; and physical activity. The literature remains largely heterogenous and primarily focused on nutrition education programs that use subjective assessments to infer changes in nutrition. A key facilitator to implementation and sustainability was community engagement, whereas key barriers were staff capacity, access to resources and funding, and consistent leadership. CONCLUSIONS: This review provides insight into Canadian school food and nutrition interventions, programs, and policies and uncovers important evidence gaps that require careful examination for future evaluations. Governments must create supportive environments that optimize nutrition for children and adolescents through equitable policies and programs. SYSTEMATIC REVIEW REGISTRATION: PROSPERO registration no. CRD42022303255.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".