Lifestyle Variables, Non‐traditional Cardiovascular Risk Factors, and the Metabolic Syndrome in an Aboriginal Canadian Population
Bibliographic record
Abstract
OBJECTIVE: To examine lifestyle factors associated with metabolic syndrome (MetS) and to explore the relationships between MetS and non-traditional cardiovascular disease risk factors [adiponectin, leptin, C-reactive protein (CRP), interleukin-6 (IL-6), and serum amyloid A (SAA)] in an isolated Aboriginal Canadian community. RESEARCH METHODS AND PROCEDURES: Data were obtained from 360 non-diabetic adults participating in a population-based study of Aboriginal Canadians. Fasting samples were drawn for glucose, insulin, lipids, adiponectin, leptin, CRP, IL-6, and SAA. Percentage body fat was measured using bioelectrical impedance analysis. Past year physical activity and fitness level were assessed. MetS was diagnosed according to the criteria of the National Cholesterol Education Program, the World Health Organization, and the International Diabetes Federation. RESULTS: The results showed that older age, higher percentage body fat, and lower fitness levels were associated with increased odds of MetS regardless of MetS definition and subject gender. Past year physical activity was independently related with the World Health Organization-MetS in male subjects. Subjects with MetS had significantly higher leptin, CRP, IL-6, and SAA levels and lower adiponectin levels; however, only adiponectin remained significantly low after adjustment for age and percentage body fat. DISCUSSION: The study showed that higher percentage body fat and lower physical activity and fitness were associated with a higher prevalence of MetS in this Aboriginal community and that hypoadiponectinemia was independently associated with MetS.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".