Comparison between Several Muscle Strength and Cardiorespiratory Fitness Indices with Body Composition and Energy Expenditure in Obese Postmenopausal Women
Bibliographic record
Abstract
The purpose of this study was to compare the relationship of several muscle strength and cardiorespiratory fitness indices with body composition and energy expenditure in obese postmenopausal women. This was a cross-sectional study involving 72 obese postmenopausal women (age: 60.0±4.8 years; body mass index: 34.1±3.5 kg/m²). Muscle strength was determined by hand dynamometer and cardiorespiratory fitness was measured by indirect calorimetry. Muscle strength and cardiorespiratory fitness were expressed in absolute (kg and L/min, respectively) and in relative values (kg/body weight (BW) and kg/lean body mass (LBM) for muscle strength and ml/min/kg BW and ml/min kg LBM for cardiorespiratory fitness). Body composition was measured using dual energy x-ray absorptiometry. Anthropometric (waist and thigh circumference), physical activity energy expenditure and daily number of steps (SenseWear armband) as well as blood pressure were also assessed. Correlations of muscle strength and cardiorespiratory fitness indices with body composition and energy expenditure showed several similarities, however, several variations were also observed. Furthermore, our results showed that age and waist circumference were the primary independent predictors for the muscle strength indices, explaining 22-37% of the variance and % body fat and age were the primary predictors for the cardiorespiratory fitness indices, explaining 18-40% of the variance. In conclusion, the present study indicates that the different methods of expressing muscle strength and cardiorespiratory fitness may display several variations and similarities with body composition and energy expenditure associations. Therefore, interpretations of relationships between muscle strength and cardiorespiratory indices with body composition and energy expenditure factors should take in account the method used to express them.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".