The relationship between cardiovascular risk factors and knowledge of cardiovascular disease in African men in the North-West Province
Bibliographic record
Abstract
Background: South Africa has an established high prevalence of cardiovascular disease(CVD), particularly amongst urban African communities. However, it was unknown whether African men's CVD knowledge was associated with their CV health profiles.Objective: To investigate the possible relationships between CV risk factors and CVD knowledge in a group of African men.Method: Questionnaires were completed by 118 African men from the North-West Province, South Africa, and health screening, including anthropometry, blood pressure, fasting blood sugar and cholesterol measurements, were done.Results: The mean CVD knowledge score was 75%. Participants' mean BP was 146/92 mmHg, falling within hypertensive ranges. Their mean fasting blood glucose of 5.8 ± 2.0 mmol/L exceeded the normal cut-off value of 5.6 mmol/L. There was a lack of association between CV risk factors and CVD knowledge, except for a borderline significant association between triglycerides and CVD knowledge (r ¼ 0.167; p ¼ 0.071), implying that men with higher CVD knowledge had higher levels of triglycerides.Conclusion: Despite African men's high CV risk and a relatively good understanding of CVD risk factors, there was no significant correlation between their CV risk factors and CVD knowledge.
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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 | 0.001 | 0.003 |
| 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) | 0.002 | 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".