Regional Patterns and Association Between Obesity and Hypertension in Africa
Bibliographic record
Abstract
Hypertension and obesity are the most important modifiable risk factors for cardiovascular diseases, but their association is not well characterized in Africa. We investigated regional patterns and association of obesity with hypertension among 30 044 continental Africans. We harmonized data on hypertension (defined as previous diagnosis/use of antihypertensive drugs or blood pressure [BP]≥140/90 mmHg/BP≥130/80 mmHg) and obesity from 30 044 individuals in the Cardiovascular H3Africa Innovation Resource across 13 African countries. We analyzed data from population-based controls and the Entire Harmonized Dataset. Age-adjusted and crude proportions of hypertension were compared regionally, across sex, and between hypertension definitions. Logit generalized estimating equation was used to determine the independent association of obesity with hypertension ( P value <5%). Participants were 56% women; with mean age 48.5±12.0 years. Crude proportions of hypertension (at BP≥140/90 mmHg) were 47.9% (95% CI, 47.4–48.5) for Entire Harmonized Dataset and 42.0% (41.1–42.7) for population-based controls and were significantly higher for the 130/80 mm Hg threshold at 59.3% (58.7–59.9) in population-based controls. The age-adjusted proportion of hypertension at BP≥140/90 mmHg was the highest among men (33.8% [32.1–35.6]), in western Africa (34.7% [33.3–36.2]), and in obese individuals (43.6%; 40.3–47.2). Obesity was independently associated with hypertension in population-based controls (adjusted odds ratio, 2.5 [2.3–2.7]) and odds of hypertension in obesity increased with increasing age from 2.0 (1.7–2.3) in younger age to 8.8 (7.4–10.3) in older age. Hypertension is common across multiple countries in Africa with 11.9% to 51.7% having BP≥140/90 mmHg and 39.5% to 69.4% with BP≥130/80 mmHg. Obese Africans were more than twice as likely to be hypertensive and the odds increased with increasing age.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".