High prevalence of hypertension in an agricultural village in Madagascar
Bibliographic record
Abstract
Elevated blood pressure presents a global health threat, with rates of hypertension increasing in low and middle-income countries. Lifestyle changes may be an important driver of these increases in blood pressure. Hypertension is particularly prevalent in African countries, though the majority of studies have focused on mainland Africa. We collected demographic and health data from 513 adults living in a community in rural Madagascar. We used generalized linear mixed models to assess body mass index (BMI), age, sex, and attributes related to household composition and lifestyle as predictors of blood pressure and hypertension. The prevalence of hypertension in this cohort was 49.1% (both sexes combined: N = 513; females: 50.3%, N = 290; males: 47.5%, N = 223). Blood pressure, as well as hypertensive state, was positively associated with age and BMI. Lifestyle and household factors had no significant relationships with blood pressure. The prevalence of hypertension was similar to that found in urban centers of other African countries, yet almost double what has been previously found in Madagascar. Future research should investigate the drivers of hypertension in rural communities worldwide, as well as the lifestyle, cultural, and genetic factors that underlie variation in hypertension across space and time.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".