Physical activity and the metabolic syndrome in Canada
Bibliographic record
Abstract
The metabolic syndrome (MetS) is a cluster of risk factors that predispose individuals to cardiovascular disease. Therapeutic lifestyle changes, including increased physical activity, are recommended for the prevention and treatment of MetS. The purpose of this study was to examine the relationship between physical activity and MetS in Canada. The sample included 6406 men and 6475 women aged 18-64 y who were participants in the Canadian Heart Health Surveys (1986-1992). MetS was classified using criteria modified from the US National Cholesterol Education Program. Participants were deemed physically active if they were active at least once each week for at least 30 min, engaging in strenuous activity some of the time. The relationship between physical activity and MetS was assessed using logistic regression, with age, smoking, alcohol consumption, and income adequacy as covariates. A total of 14.4% of Canadians had MetS and 33.6% were physically active. The odds ratio for MetS was 0.73 (95% confidence interval (CI): 0.54-0.98; p < 0.05) for physically active vs. physically inactive participants. The corresponding odds ratios were 0.45 (95% CI: 0.29-0.69; p < 0.001) and 0.67 (95% CI: 0.44-1.02; p = 0.06) for men and women, respectively. In summary, physical activity was associated with lower odds of MetS, particularly in men. Further research is required to determine the effectiveness of physical activity in the treatment of 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".