Hypertension among Rural Population in Four States: Sudan 2012
Bibliographic record
Abstract
BACKGROUND: Hypertension is emerging as an alarming public-health problem causes organ damage. OBJECTIVES: To identify prevalence of hypertension and predictor factors among rural population in four states in Sudan. METHODS: A community based cross-sectional study was conducted in sixteen rural areas in Sudan during April 2012. A total of 3020 adult were interviewed using structured questionnaire and blood pressure was measured before and after the interview. Hypertension was taken as ≥140 mmHg and ≥90 mmHg for systole and diastole respectively. ANALYSIS: Descriptive statistic was presented; Sex and mean of systolic and diastolic blood pressure were tested using ANOVA for individuals on antihypertensive medication. Predictor factors to hypertension were tested by logistic regression. RESULTS: Prevalence of hypertension among rural population was 15.8%. Overall means of systolic and diastolic blood pressure were 128.6 ± 17.7 and 81.5 ± 11.6 respectively while the means among hypertensive individuals was 154.74 ±14.4 and 97.98±8.4 respectively Known hypertensive individuals were 20.1%; out of whom 71.7% were hypertensive and 22.4% have Target Organ Damage. Those on anti-hypertensive medications were 76.4% and normotensive were 55.1%. Individuals having both diabetes and hypertension were 3.3% and 80.2% were hypertensive. Log regression model showed age, smoking, diabetes and family hypertension were predictors of hypertension by 3.6%, 34.9%, 49.7% and 56.8% respectively (P-value < 0.05). CONCLUSION: Prevalence of hypertension among rural Sudan was 15.8%. Family history was the strongest predictor of hypertension.
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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 | 0.002 | 0.000 |
| 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 | 0.000 |
| 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".