Association between the food retail environment surrounding schools and overweight in Canadian youth
Bibliographic record
Abstract
INTRODUCTION: There is growing interest in how the physical environment influences obesity. Few studies have considered how the food retail environment surrounding schools influences overweight in students. OBJECTIVE: To determine whether there is a relationship between food retailers surrounding schools and overweight among Canadian youth. DESIGN: Cross-sectional study. SETTING/METHODS/SUBJECTS: The number of food retailers was obtained within a 1 km and 5 km radius around 178 schools in Canada. Retailers included full-service restaurants, fast-food restaurants, sub/sandwich retailers, doughnut/coffee shops, convenience stores and grocery stores. An index of total food retailer exposure was also created. Multilevel analyses were used to control for individual- and area-level covariates. RESULTS: None of the individual food retailers was associated with an increased likelihood of overweight. The total food retailer index was most strongly related to overweight, but in the opposite direction to that hypothesized. At 1 km, students attending schools with at least one food retailer had a lower relative odds of overweight (OR = 0.70, 95% CI 0.61, 0.81). At 5 km, students attending schools with the highest exposure to the total food retailer index had a lower relative odds of overweight (OR = 0.56, 95% CI 0.47, 0.68) compared with students attending schools with no exposure. CONCLUSIONS: Exposure to various types of food retailers in school neighbourhoods was not associated with an increased likelihood of overweight in Canadian school-aged youth. The opportunity to make healthy choices from a variety of options and the unique Canadian context may explain the findings.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".