Synergic effect of phytoestrogens and exercise training on cardiovascular risk profile in exercise-responder postmenopausal women
Bibliographic record
Abstract
OBJECTIVE: We showed that isoflavones and exercise improve total and abdominal fat mass (FM) to a greater extent than does exercise alone in postmenopausal women, but not other cardiovascular disease (CVD) risk factors. Fat-free mass (FFM) showed a wide variability of responses, with 60% of women having increased FFM and 40% having decreased FFM. We thus wondered if women who had decreased FFM could be considered as nonresponders (NRs) to exercise and if this masked a potential synergistic effect of phytoestrogens (PHY) and exercise. The aim of this study was to verify if PHYs enhance the response obtained after aerobic and resistance exercises in CVD risk profile in exercise responders. METHODS: Among 21 women who participated in a 6-month exercise program and received PHY or placebo (PLA), 14 were exercise responders (PHY, n = 8; PLA, n = 6) whereas 7 were NRs. Body weight, waist circumference, FM, and FFM were assessed (dual-energy x-ray absorptiometry). Plasma glucose, insulin, sex hormone-binding globulin, and testosterone levels were obtained after a 12-hour overnight fast. Total energy intake was measured with a 3-day dietary record. All measurements were performed before and after the intervention. RESULTS: After exercise training, the PHY and PLA groups, but not the NR group, had increased FFM (0.01 < P < 0.03). On the other hand, body weight, FM, and systolic and diastolic blood pressure (0.01 < P < 0.05) decreased in the PHY group only. Furthermore, plasma insulin level (P = 0.04) and homeostasis model assessment significantly decreased (P = 0.03) while plasma sex hormone-binding globulin increased (P = 0.04) after training in the PHY group, whereas energy intake remained unchanged in both groups (0.10 < P < 0.59) after the intervention. CONCLUSION: PHYs combined with exercise compared with exercise alone seem to improve body composition and CVD risk profile in exercise-responder 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 | 0.000 | 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) | 0.001 | 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".