The obesogenic environment around elementary schools: food and beverage marketing to children in two Mexican cities
Bibliographic record
Abstract
BACKGROUND: Unhealthy environments and food advertisements are major determinants of childhood obesity. Recent regulation has banned unhealthy foods from schools in Mexico. However, currently there is no regulation limiting exposure to food marketing around schools. Thus, our objective was to analyze the characteristics of food advertising practices around 60 elementary schools in two cities and to evaluate compliance with the Pan American Health Organization (PAHO) recommendations and the local food industry self-regulatory marketing code. METHODS: Data were collected during the period of October 2012 to March 2013. A random sample of elementary schools was selected from two Mexican cities. Using geographic information systems, we drew a 100-m-diameter buffer around each school. Trained personnel obtained photographs to assess the locations and types of food advertisements. Our results were stratified by school type and by indicators of compliance with the PAHO and industry recommendations. We developed a multivariate negative binomial regression model to determine factors predicting the number of advertisements around schools. RESULTS: The number of advertisements was significantly higher around public schools than around private schools (6.5 ± 5.6 vs. 2.4 ± 3.5, p < 0.05). Printed posters were the most common type of marketing medium (97%), showing mostly sugar-sweetened beverages, sweet breads, candies, and bottled water. Promotions, such as special prices or gifts, were included on 30% of printed posters. Food advertising practices were often in compliance with industry recommendations (83%) but not with those from the PAHO (32%) (p < 0.001). CONCLUSION: Our results support the importance of monitoring the obesogenic environment and identifying policy tools to protect children from food marketing not only inside schools but also around them, particularly in lower income communities.
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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 | 0.002 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".