Awareness of and Participation in School Food Programs Among Youth From Six Countries
Bibliographic record
Abstract
\n\t\t\t\t\t<jats:title>Abstract</jats:title>\n <jats:sec>\n <jats:title>Background</jats:title>\n <jats:p>School-based meal programs may promote healthy dietary intake among youth. However, limited data exist regarding the impact of income-targeted school meal programs across countries, particularly among food insecure youth.</jats:p>\n </jats:sec>\n <jats:sec>\n <jats:title>Objectives</jats:title>\n <jats:p>To examine self-reported awareness of and participation in free school meal programs, and associations with dietary intake among youth from six countries with differing national school meal policies.</jats:p>\n </jats:sec>\n <jats:sec>\n <jats:title>Methods</jats:title>\n <jats:p>Data were collected through the 2019 International Food Policy Study (IFPS) Youth Survey, a cross-sectional survey of 10,565 youth aged 10–17 y from Australia, Canada, Chile, Mexico, the United Kingdom (UK), and the United States (US). Regression models examined: 1) country differences in awareness of and participation in breakfast and lunch programs; and 2) associations between lunch program participation and intake of fruit and vegetables, and ‘less healthy’ foods during the previous school lunch day.</jats:p>\n </jats:sec>\n <jats:sec>\n <jats:title>Results</jats:title>\n <jats:p>Awareness of and participation in free breakfast and lunch programs varied across countries. Approximately half of US and Chilean students participated in school lunch programs—the countries with the most comprehensive national policies—compared to one fifth of students in the UK, and approximately 5% in Australia, Canada, and Mexico (P &amp;lt; 0.001 for all contrasts). In the US and Chile, more than two thirds of youth with the highest level of food insecurity participated in lunch programs, compared to 45% in the UK, 27% in Canada, and 20% or less in Australia and Mexico. In all countries, youth reporting school lunch program participation were more likely to report fruit and vegetable intake during their previous school lunch (P &amp;lt; 0.001), and higher intake of ‘less healthy’ food in all countries except the US and Chile.</jats:p>\n </jats:sec>\n <jats:sec>\n <jats:title>Conclusions</jats:title>\n <jats:p>More comprehensive national policies were associated with greater participation in school meals programs, particularly among youth at greatest risk of food insecurity, as well as healthier dietary intake from school lunch.</jats:p>\n </jats:sec>\n\t\t\t\t
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".