Role of hypertension in the association of overweight and obesity with diabetes among adults in Bangladesh: a population-based, cross-sectional nationally representative survey
Bibliographic record
Abstract
AIMS: Overweight and obesity (OWOB) is a modifiable risk factor for both hypertension and diabetes. However, the association between OWOB and diabetes among Bangladeshi adults and how hypertension may mediate this relationship are not well explored. This study aimed to examine (1) whether OWOB is independently associated with diabetes among Bangladeshi adults, (2) whether this association is mediated by hypertension, and (3) the effect modification by wealth status and place of residence in the relationships. RESEARCH DESIGN AND METHODS: We used data of 9305 adults aged ≥18 years from the most recent nationally representative cross-sectional study of Bangladesh Demographic and Health Survey 2017-2018. Design-based logistic regression was used to assess the association between OWOB and diabetes, and counterfactual framework-based weighting approach was used to evaluate the mediation effect of hypertension in the OWOB-diabetes relationship. We used stratified analyses for the effect modifications. RESULTS: The prevalence of OWOB, diabetes and hypertension was 48.5%, 11.7% and 30.3%, respectively. We observed a significant association between OWOB and diabetes and a mediating role of hypertension in the OWOB-diabetes association. The odds of diabetes was 51% higher among adults with OWOB than those without OWOB (adjusted OR: 1.51, 95% CI 1.29 to 1.77). We observed that 18.64% (95% CI 9.84% to 34.07%) of the total effect of OWOB on the higher odds of diabetes was mediated through hypertension, and the mediation effect was higher among adults from non-poor households and from both rural and urban areas. CONCLUSIONS: Adult OWOB status is independently associated with diabetes in Bangladesh, and hypertension mediates this association. Therefore, prevention policies should target adults with both OWOB and hypertension, particularly those from non-poor households and from both rural and urban areas, to reduce the growing burden of diabetes and its associated risk.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".