Bullying victimization and obesogenic behaviour among adolescents aged 12 to 15 years from 54 low‐ and middle‐income countries
Bibliographic record
Abstract
BACKGROUND: Data on the association between obesogenic behaviours and bullying victimization among adolescents are scarce from low- and middle-income countries. OBJECTIVES: To assess the associations between obesogenic behaviours and bullying victimization in 54 low- and middle-income countries. METHODS: Cross-sectional data from the global school-based student health survey were analyzed. Data on bullying victimization and obesogenic behaviours were collected. The association between bullying victimization and the different types of obesogenic behaviour (anxiety-induced insomnia, fast-food consumption, carbonated soft-drink consumption, no physical activity and sedentary behaviour) were assessed by country-wise multivariable logistic regression analysis adjusting for age, sex, food insecurity and obesity with obesogenic behaviours being the outcome. RESULT: The sample consisted of 153 929 students aged 12 to 15 years [mean (SD) age 13.8 (1.0) years; 49.3% girls]. Overall, bullying victimization (vs no bullying victimization) was significantly associated with greater odds for all types of obesogenic behaviour with the exception of physical activity, which showed an inverse association. Specifically, the ORs (95% CIs) were: anxiety-induced sleep problems 2.65 (2.43-2.88); fast-food consumption 1.36 (1.27-1.44); carbonated soft-drink consumption 1.14 (1.08-1.21); no physical activity 0.84 (0.79-0.89); and sedentary behaviour 1.34 (1.25-1.43). CONCLUSION: In this large representative sample of adolescents from low- and middle-income countries, bullying victimization was found to be associated with several, but not all, obesogenic behaviours.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".