Muscle mass and insulin sensitivity in postmenopausal women after 6-month exercise training
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVE: The common belief that high muscle mass improves insulin sensitivity is controversial and even recent studies have established that larger muscle mass is associated with insulin resistance in sedentary postmenopausal women. Physical activity induces a beneficial effect in muscle size and its metabolic properties. Hence, larger muscle mass induced by exercise training should ameliorate insulin sensitivity and the negative relationship between larger muscle mass and insulin sensitivity should disappear. This study examined the induced changes in muscle mass and insulin sensitivity in postmenopausal women after 6-month exercise training along with their possible correlations. METHODS: Forty-eight sedentary, overweight-to-obese postmenopausal women followed a 6-month mixed exercise training (three sessions/week; endurance and resistance). Lean body mass (LBM) and fat mass (FM) were measured by DXA, then the muscle mass index (MMI) was calculated (MMI = LBM (kg)/height (m(2))). Fasting glucose and insulin measurements were obtained and insulin resistance (IR) was estimated by the HOMA-IR formula. RESULTS: Baseline MMI was correlated with IR (r = 0.219, p = 0.015). After intervention, significant differences were observed in body weight, FM%, MMI, and glycemia, and changes in MMI were significantly correlated with changes in IR (r = 0.345, p = 0.016). Also linear regression showed that the increase in MMI explained 28% of the deterioration in insulin sensitivity (p = 0.001). CONCLUSIONS: After 6 months of mixed training, changes in muscle mass remained correlated with changes in insulin resistance, overweight-to-obese women with large muscle gains being more insulin-resistant. This supports that muscle quality and functionality, and the loss of fat mass, should be targeted rather than muscle mass gains in postmenopausal women, especially in a context of no energy restriction.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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) | 0.000 | 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 it