Relationship between the percentage of predicted cardiorespiratory fitness and cardiovascular disease risk factors in premenopausal women: a MONET study
Bibliographic record
Abstract
OBJECTIVE: To determine the relationships between the percentage predicted cardiorespiratory fitness (%CRF) and the anthropometric and metabolic cardiovascular disease risk factors in asymptomatic, premenopausal women. METHODS: Data are baseline values obtained in 97 healthy premenopausal women (age 49.9 +/- 1.9 years; body mass index 23.2 +/- 2.2 kg/m(2)) participating in a longitudinal study from 2004 to 2009. The outcome measures were peak oxygen consumption (VO(2) peak), body mass index, body composition (percentage fat, fat mass, fat-free mass), waist circumference, abdominal subcutaneous fat, visceral fat, resting blood pressure and fasting lipids, glucose and insulin levels. RESULTS: The %CRF was negatively associated with body mass index, fat mass, percentage fat, waist circumference, abdominal subcutaneous fat, visceral fat, triglycerides, triglyceride/high density lipoprotein cholesterol, total cholesterol, total cholesterol/high density lipoprotein cholesterol, fasting insulin levels and HOMA-IR (- 0.59 < or = r < or = - 0.20; 0.01 < p < 0.05) and positively associated with insulin sensitivity index (r = 0.23; p < 0.05). VO(2) peak was associated with the same variables; however, correlations were slightly better (- 0.70 < or = r < or = 0.30; 0.01 < p < 0.05). Stepwise multiple regression analysis showed that %CRF was only independently correlated with plasma triglyceride levels. CONCLUSION: The results of this study suggest that %CRF was not a major predictor of anthropometric and metabolic variables associated with an increased risk of cardiovascular disease in asymptomatic premenopausal women. Finally, the VO(2) peak is a better predictor than the %CRF to assess the risk of cardiovascular disease in asymptomatic premenopausal women.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".