Prevalence of Hypertension and Its Associated Factors among Adults in Selected Areas of Bangladesh: A Community Based Cross-sectional Study
Bibliographic record
Abstract
Background: Hypertension is a silent killer and an overwhelming global public health challenge. This study aimed to determine the prevalence and associated factors of hypertension among adults in Bangladesh. Methods: A community-based cross-sectional study design was conducted among 400 adults who lived in Dhaka, Mymensing, Sylhet and Khulna District. Data were collected using a structured questionnaire that is adapted from the WHO Stepwise approach. Data was analyzed by SPSS version 25. Descriptive statistics and bivariate logistic regression analysis were conducted and statistical significance was declared at a p-value ≤0.05. Results: This study identified a high prevalence of hypertension in the study area and it was 39.75%. Among the male the prevalence was 23.5% and the prevalence was 16.5% among female. In this study hypertension was significantly associated with the age group 51-65 years (OR=1.02; CI 0.557-1.862) , ever smoking (OR= 2.59; CI 1.718-3.917) consume less fruits (OR=3.125; CI 0.839-11.632) and vegetable (OR=2.25; CI 1.364-3.725), physically inactive (OR=1.48;CI 0.973-2.252) overweight (OR=7.98; CI 4.612-13.793) and had diabetes mellitus (0R=2.38; CI 1.213-4.659). Conclusion: The prevalence of hypertension was considerably higher in this study area. Hence, the health care system needs to establish strategies to improve the diagnostic and screening services. Community-level intervention and regular assessment, screening, and diagnosis of behavioral, socio-demographic, and physiological risk factors, screening, should be institutionalized to address the occult burden of hypertension.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".