Overweight and obesity among school-going adolescents in Bengaluru, South India
Bibliographic record
Abstract
Introduction: Adolescent obesity is an emerging public health problem in urban India. This study assessed the prevalence of overweight and obesity and its associated factors among school-going adolescents in Bengaluru, India.Material and Methods: Cross-sectional study of 734 male and female students aged 10 years and older from two private schools in Bengaluru city, India. Students were administered a questionnaire that recorded socioeconomic, and family-related factors and lifestyle behaviors. Anthropometric measurements done to determine overweight and obesity using the WHO body mass index for age charts. Nominal variables were described in terms of frequency and proportion, and odd's ratio (OR) (with 95% confidence interval) as test of association.Results: The prevalence of overweight and obesity among adolescents was 21.7% and 6.1% respectively. Age, gender, religion, education level of parents, mother working outside the home, participation in vigorous physical activities, vegetarian diet, and consumption of junk foods as snacks were not found to be significantly associated with overweight/obesity.Conclusion: The prevalence of overweight/obesity among school-going adolescents in Bengaluru, India was 27.8%. Adolescents from the higher income families, OR = 2.35 (1.43–3.85) as well as students who indicated a family history of obesity, OR = 2.4 (1.72–3.33) were more likely to be overweight or obese. Since young adolescents spend a significant portion of their day in school, a comprehensive school health service including growth monitoring, nutrition education, and exercise programs remains one of the most cost-effective public health measures.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".