The Influence of Physical and Social Contexts of Eating on Lunch-Time Food Intake Among Southern Ontario, Canada, Middle School Students
Bibliographic record
Abstract
BACKGROUND: Among students, little is known about the physical and social context of eating lunch. The objective of this study was to determine if food intake (including the type of food and beverages and portion sizes) was associated with specific aspects of the physical and social lunch environment (location, with whom lunch was consumed, who prepared the food, and where the food was originally purchased). METHODS: A total of 1236 participants (males = 659, females = 566) in grades 6 (n = 359), 7 (n = 409), and 8 (n = 463) from southern Ontario, Canada, completed the Food Behavior Questionnaire during the 2005-2006 academic year. RESULTS: A total of 8159 foods and 2200 beverages were consumed during the lunch meal, which contributed to 552 kcal (SD = 429) or 30% (SD = 16) of total daily energy intake (kcal/day). Higher amounts of energy, meats and alternatives, other foods, fried foods, and pizza were consumed when participants ate in between places or at a restaurant/fast food outlet (compared with at home or school, p < 0.05) and/or when prepared by friends or others (compared with themselves or family members, p < 0.05). A large number of participants (46%) reported consuming sugar-sweetened beverages during lunch, despite a school board-level policy restricting the sales of "junk food," which appears to be brought from home. CONCLUSIONS: Our findings support schools in policy efforts that restrict fast food access (by leaving school grounds, preventing fast food companies from coming onto school grounds, or restricting sugar-sweetened beverage sales in vending machines) and that eating in between places should be discouraged.
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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 | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".