Prevalence and awareness of hypertension among Sudanese rural population, Sinnar State, Sudan, 2016
Bibliographic record
Abstract
Objective: The aim of this study to estimate the prevalence of hypertension and determine awareness among rural population.Methods: Cross-sectional community based study, conducted in rural community. Population was the resident citizens in age of 25-64 years. A cluster sampling technique was used and total sample size mounted to 341 subjects. The collected data was cleaned, edited and analyzed using SPSS program.Results: Prevalence of hypertension was 21.1%, systolic was 5.9% and diastolic hypertension was 10.0% with no significant differences among gender (p-value .409). About 59.7% of hypertensive subjects were unaware with their diagnosis, men were more awareness than women with proportion of 62.0% in men and 38.0% in women. Awareness with hypertension diagnosed was increased by increasing age, income and education. Most of known hypertensive subjects (86.20%) were on treatment. Approximately 80% of known hypertensive subjects were complained of signs and symptoms and 31.0% with complications. Also controlled blood pressure was 34.0% with proportion of 36.4% among women and 33.3% among men.Conclusions: The study reflected high prevalence of hypertension, systolic and diastolic among rural population, also the level of awareness among hypertensive subjects generally was low; however the level of awareness among elder, educated was better and females were more control 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".