Prevalence and determinants of hypertension among urban slum dwellers in Bangladesh
Bibliographic record
Abstract
BACKGROUND: In low- and middle- income countries such as Bangladesh, urban slum dwellers are particualry vulnerable to hypertension due to inadequate facilities for screening and management, as well as inadequate health literacy among them. However, there is scarcity of evidence on hypertension among the urban slum dwellers in Bangladesh. The present study aimed to determine the prevalence and factors associated with hypertension among urban slum dwellers in Bangladesh. METHODS: Data were collected as part of a large-scale cross-sectional survey conducted by Building Resources Across Communities (BRAC) between October 2015 and January 2016. The present analysis was performed among 1155 urban slum dwellers aged 35 years or above. A structured questionnaire was adminstered to collect data electronically and blood pressure measurements were taken using standardised procedures. Binary logistic regression with generalized estimating equation modelling was performed to estimate the factors associated with hypertension. RESULTS: The prevalence of hypertension was 28.3% among urban slum dwellers aged 35 years and above. In adjusted analysis, urban slum dwellers aged 45-54 years (AOR: 1.64, 95% CI: 1.17-2.28), 55-64 years (AOR: 2.47, 95% CI: 1.73-3.53) and ≥ 65 years (AOR: 2.34, 95% CI: 1.47-3.72), from wealthier households (AOR: 1.94, 95% CI: 1.18-3.20), sleeping < 7 h per day (AOR: 1.87, 95% CI: 1.39-2.51), who were overweight (AOR: 1.53, 95% CI: 1.09-2.14) or obese (AOR: 2.34, 95% CI: 1.71-3.20), and having self-reported diabetes (AOR: 3.08, 95% CI: 1.88-5.04) had an increased risk of hypertension. Moreover, 51.0% of the participants were taking anti-hypertensive medications and 26.4% of them had their hypertension in control. CONCLUSIONS: The findings highlight a high burden of hypertension and poor management of it among the slum dwellers in Bangladesh requiring a novel approach to improve care. It is integral to effectively implement the available national non-communicable disease (NCD) control guidelines and redesign the current urban primary health care system to have better coordination.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".