Aerobic Exercise And Insulin Sensitivity In Postmenopausal Women: Is Body Composition Implicated?
Bibliographic record
Abstract
Until now, it is accepted in the scientific literature that insulin sensitivity is related to body fat and muscle mass. However, we have shown in previous studies that the relationship between insulin sensitivity and body composition seems to be associated with substrate oxidation and energy metabolism. To the best of our knowledge there are no studies showing that low muscle mass (sarcopenia) is associated with insulin sensitivity. In turn, glucose can be oxidized to produce energy. Resting metabolic rate (RMR) decreases with age, potentially leading to changes in substrate oxidation. There are numerous studies indicating that lipid metabolism and more specifically lipid oxidation, decreases with age, which affects glucose metabolism. It is still unclear, however, if it occurs simultaneously with the increase in glucose oxidation or the oxidation of lipids and glucose are also reduced. On the other hand, changes in insulin sensitivity that occur after an exercise program has long been regarded as the result of changes in muscle mass and body fat. However, the impact of exercise on insulin sensitivity may actually be the result of changes in substrate oxidation and energy metabolism. PURPOSE: We will study the mechanisms explaining changes in insulin sensitivity (glucose oxidation, lipid oxidation (RQ) and energy metabolism (RMR)) following a program of aerobic exercise in postmenopausal women. METHODS: Fifty-eight postmenopausal women (average age: 57.7 years, mean BMI: 31.4 kg/m2) participated in a 6-month aerobic training program at moderate intensity, 3 times per week. RMR, insulin sensitivity (QUICKI), RQ and body composition (DXA) were measured before and after 6 months of exercise. RESULTS: While insulin sensitivity increased significantly (p <0.01), there was no significant change in RQ, RMR.or body composition. In addition, regression model demonstrated that the change in insulin sensitivity was not explained by measures of body composition or metabolism. CONCLUSION: Our results show that aerobic exercise can significantly increase insulin sensitivity, even if it is an unstructured program. Our results also show that the improved insulin sensitivity occurs even if there is no improvement in body composition or energy metabolism.
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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 | 0.001 |
| 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".