Associations between socio-economic status and school-day dietary intake in a sample of grade 5–8 students in Vancouver, Canada
Bibliographic record
Abstract
OBJECTIVE: To examine associations between students' socio-economic status (SES) and school-day dietary intake, and the roles of parents and peers in shaping these associations. DESIGN: A cross-sectional survey measured school-day intake of vegetables, whole grains, low-fat milk, packaged snack foods and sugar-sweetened beverages. Logistic regression models examined associations between SES (parental education and food insecurity status) and dietary outcomes during or en route to or from school, and examined whether peer modelling or parental norms potentially mediated the associations between SES and dietary outcomes. SETTING: Twenty-six public schools in Vancouver, Canada in 2012. SUBJECTS: Nine hundred and fifty students in grades 5-8. RESULTS: Students whose parents completed some college, compared with those completing high school or less, were significantly more likely to consume vegetables daily (unadjusted OR = 1.85; 95 % CI 1.06, 3.22) and students whose parents completed college or university were significantly less likely to consume sugar-sweetened beverages daily (unadjusted OR = 0.67; 95 % CI 0.47, 0.94). Food secure students were also significantly less likely to consume sugar-sweetened beverages daily compared with food insecure students (unadjusted OR = 0.52; 95 % CI 0.29, 0.92). Parental norms, but not peer modelling, emerged as a potential mediator of the association between SES and vegetable intake. SES was not significantly associated with the remaining dietary outcomes. CONCLUSIONS: Higher SES was significantly associated with two of five school-day dietary outcomes and predicted higher likelihood of daily nutritious food choices at school. The present study suggests that there is room for improvement in school-day dietary quality for students from all SES backgrounds in Vancouver.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".