The relation of body mass index and abdominal adiposity with dyslipidemia in 27 general populations of the WHO MONICA Project
Bibliographic record
Abstract
Abstract Background and aims The association between adiposity measures and dyslipidemia has seldom been assessed in a multipopulational setting. Methods and results 27 populations from Europe, Australia, New Zealand and Canada (WHO MONICA project) using health surveys conducted between 1990 and 1997 in adults aged 35–64 years ( n = 40,480). Dyslipidemia was defined as the total/HDL cholesterol ratio >6 (men) and >5 (women). Overall prevalence of dyslipidemia was 25% in men and 23% in women. Logistic regression showed that dyslipidemia was strongly associated with body mass index (BMI) in men and with waist circumference (WC) in women, after adjusting for region, age and smoking. Among normal-weight men and women (BMI 2 ), an increase in the odds for being dyslipidemic was observed between lowest and highest WC quartiles (OR = 3.6, p p = 0.036). A similar weakening was observed among women. Classification tree analysis was performed to assign subjects into classes of risk for dyslipidemia. BMI thresholds (25.4 and 29.2 kg/m 2 ) in men and WC thresholds (81.7 and 92.6 cm) in women came out at first stages. High WC (>84.8 cm) in normal-weight men, menopause in women and regular smoking further defined subgroups at increased risk. Conclusion standard categories of BMI and WC, or their combinations, do not lead to optimal risk stratification for dyslipidemia in middle-age adults. Sex-specific adaptations are necessary, in particular by taking into account abdominal obesity in normal-weight men, post-menopausal age in women and regular smoking in both sexes.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".