The school environment and sugar-sweetened beverage consumption among Guatemalan adolescents
Bibliographic record
Abstract
OBJECTIVE: The current study sought to examine Guatemalan adolescents' consumption of sugar-sweetened beverages (SSB), identify which individual-level characteristics are associated with SSB consumption and describe school characteristics that may influence students' SSB consumption. DESIGN: Within this observational pilot study, a questionnaire was used to assess students' consumption of three varieties of SSB (soft drinks, energy drinks, sweetened coffees/teas), as well as a variety of sociodemographic and behavioural characteristics. We collected built environment data to examine aspects of the school food environment. We developed Poisson regression models for each SSB variety and used descriptive analyses to characterize the sample. SETTING: Guatemala City, Guatemala. SUBJECTS: Guatemalan adolescents (n 1042) from four (two public, two private) secondary schools. RESULTS: Built environment data revealed that students from the two public schools lacked access to water fountains/coolers. The SSB industry had a presence in the schools through advertisements, sponsored food kiosks and products available for sale. Common correlates of SSB consumption included school type, sedentary behaviour, frequency of purchasing lunch in the cafeteria, and frequency of purchasing snacks from vending machines in school and off school property. CONCLUSIONS: Guatemalan adolescents frequently consume SSB, which may be encouraged by aspects of the school environment. Schools represent a viable setting for equitable population health interventions designed to reduce SSB consumption, including increasing access to clean drinking-water, reducing access to SSB, restricting SSB marketing and greater enforcement of existing food policies.
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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 | 0.001 | 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 | 0.001 | 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".