Metabolic Syndrome, Obesity, and Mortality
Bibliographic record
Abstract
OBJECTIVE: To determine in normal weight, overweight, and obese men the risk of all-cause and cardiovascular disease (CVD) mortality associated with the metabolic syndrome (MetS) and the influence of cardiorespiratory fitness (CRF). RESEARCH DESIGN AND METHODS: This observational cohort study included 19,173 men who underwent a clinical examination, including a maximal exercise test. MetS was defined according to National Cholesterol Education Program guidelines. RESULTS: At baseline 19.5% of the men had MetS. The ORs of the metabolic syndrome at baseline were 4.7 (95% CI 4.2-5.3) in overweight and 30.6 (26.7-35.0) in obese men compared with normal weight men. A total of 477 deaths (160 CVD) occurred in 10.2 years of follow-up. The risks of all-cause mortality were 1.11 (0.75-1.17) in normal weight, 1.09 (0.82-1.47) in overweight, and 1.55 (1.14-2.11) in obese men with MetS compared with normal weight healthy men. The corresponding risks for CVD mortality were 2.06 (0.92-4.63) in normal weight, 1.80 (1.10-2.97) in overweight, and 2.83 (1.70-4.72) in obese men with the MetS compared with normal weight healthy men. After the inclusion of CRF in the model, the risks associated with obesity and MetS were no longer significant. CONCLUSIONS: Obesity and MetS are associated with an increased risk of all-cause and CVD mortality; however; these risks were largely explained by CRF.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".