Association of hypertension and hyperglycaemia with socioeconomic contexts in resource-poor settings: the Bangladesh Demographic and Health Survey
Bibliographic record
Abstract
BACKGROUND: Cardiovascular diseases and risk factors are disproportionally concentrated among the socioeconomically disadvantaged in high-income countries; however, this relationship is not well-understood or documented in resource-limited countries. METHODS: We analysed data from the 2011 Bangladesh Demographic and Health Survey to estimate age-, sex- and location-adjusted differences in blood pressure and blood glucose outcomes by categories of a standardized wealth index and education levels. Body mass index (BMI) was examined as a secondary outcome and also assessed as a potential confounder. RESULTS: There was strong evidence that the prevalence of hypertension was higher among Bangladeshi women than among men (33.6% vs 19.6%, P < 0.001), whereas the overall prevalence of hyperglycaemia was 7.1% with no evidence of sex differences. The likelihood of having hypertension was more than double for individuals in the highest vs lowest wealth quintile [odds ratio (OR) for men: 2.82, 95% confidence interval (CI): 2.32-3.44; OR for women: 2.25, 95% CI: 1.90-2.67], and for individuals with the highest level of education attained vs those with no education (OR for men: 2.55, 95% CI: 2.06-3.16; OR for women: 1.42, 95% CI: 0.99-2.03). Likewise, the likelihood of having hyperglycaemia was more than four times higher in the wealthiest compared with the poorest individuals (OR for men: 6.48, 95% CI: 5.11-8.22; OR for women: 4.77, 95% CI: 3.72-6.12), and in individuals with the highest level of education attained vs those with no education (OR for men: 4.68, 95% CI: 3.56-6.15; OR for women: 5.02, 95% CI: 3.30-7.64). There were no appreciable differences in these trends when stratified by geographical location. BMI did not attenuate these associations and exhibited similarly positive associations with education and wealth. CONCLUSIONS: Increasing levels of wealth and educational attainment were associated with an increased likelihood of having hypertension and hyperglycaemia in Bangladesh.
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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 | 0.013 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".