Differences in MetS marker prevalence between black African and Caucasian teachers from the North West Province: Sympathetic Activity and Ambulatory Blood Pressure in Africans (SABPA) Study
Bibliographic record
Abstract
Background: The aim of this study was to compare metabolic syndrome (MetS) prevalence between black and Caucasian Africans using different definitions, and secondly, to determine the association between MetS, anthropometric markers and the albumin: creatinine ratio using the new joint statement criteria. This was a target population study. It included 409 urban African and Caucasian men and women (aged 25–65 years) from the North West Province, who were stratified into gender and ethnic groups.Method: We obtained anthropometric measurements, levels of microalbuminuria, and other markers of MetS (systolic and diastolic blood pressure, glucose, triglycerides and high-density lipoprotein).Results: The joint statement criteria included more persons with MetS than the other definitions, and Africans presented with more cases of MetS than the Caucasians. The most prevalent risk factors were blood pressure among men, and waist circumference (WC) and glucose among women. African men, as a group, presented with more risk factors than the other groups. African women, although obese, seem to have few cardiovascular risk factors, while all groups presented with an unhealthy WC according to European cut-points. Multiple linear regression analysis, independent of covariates, showed that the albumin: creatinine ratio is explained only by glucose in Africans.Conclusion: African women, as a group, present with few MetS risk factors, and glucose is associated with renal function risk in Africans.
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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) | 0.002 | 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".