School Food Environment, Food Consumption, and Indicators of Adiposity Among Students 7‐14 Years in Bogotá, Colombia
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: In Colombia, the prevalence of overweight/obesity in children has increased by 26% in the past 5 years. School food environment may be an important contributor and offers opportunities for effective intervention. METHODS: We conducted a cross-sectional study among 7- to 14-year-old schoolchildren from 10 schools in Bogotá, Colombia. We examined the school food environment and the relationship of individual-level consumption, and physical activity with overweight/obesity, measured by body mass index and percentage body fat. RESULTS: Schools with a restaurant/store were characterized as having excessive unhealthy foods. In the sample of 714 schoolchildren, 17.5% were overweight and 10.5% were obese. In multivariate models, boys had significantly increased odds of being overweight/obese (odds ratio [OR]: 1.53; p = .01) as compared to girls. Schoolchildren who consumed a greater number of energy drinks (OR = 1.82; p = .04), and those who spent more than 3 hours per schoolday watching TV (OR = 1.53; p < .01) had increased odds of being overweight/obese. CONCLUSIONS: Approximately 1 in 4 schoolchildren were overweight/obese, with boys, energy drink consumers, and those with low physical activity having increased risk. School-based interventions focused on improving food options and providing health behavior education may be effective to reduce overweight among children in Bogotá and similar settings.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 it