Prevalence, inequality and associated factors of overweight/obesity among Bangladeshi adolescents aged 15–19 years
Bibliographic record
Abstract
BACKGROUND: The objective of the current study was to estimate the prevalence and associated factors of overweight/obesity among Bangladeshi adolescents aged 15-19 y and to identify whether wealth-related inequality exists for overweight/obesity among Bangladeshi older adolescents. METHODS: We analyzed publicly available national representative secondary data from the 2019-2020 Bangladesh Adolescent Health and Wellbeing Survey. This cross-sectional survey was carried out among 18 249 adolescents aged 15-19 y regardless of their marital status using a two-stage stratified sampling technique (the data of 9128 eligible adolescents were included in this analysis). The WHO reference population for body mass index-for-age (1+Z score) was considered as overweight/obesity. RESULTS: We found that girls had significantly (p<0.05) higher prevalence of overweight/obesity (11.63%) than boys (8.25%); however, their biological sex as well their age were not significantly associated with higher odds of overweight/obesity. Those who were in their higher grade (grade 11 and higher) in the school and had been exposed to media were more likely (1.67 and 1.39 times, respectively) to be overweight/obesity compared with primary grade (0-5) and those who experienced no media exposure, respectively. Inequality analysis revealed that adolescents belonging to wealthy households had significantly higher rates of overweight/obesity than those in poorer households (concentration index=0.093). CONCLUSIONS: The study exhibited the multifaceted nature of overweight/obesity among Bangladeshi older teenagers, revealing that their school grade, exposure to media content and wealth-related inequality emerged as significant contributing factors. The findings underscore the urgent need for targeted interventions and public health strategies to address the escalating burden of overweight and obesity in this age group.
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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 | 0.000 | 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".