Influence of a walking program on the metabolic risk profile of obese postmenopausal women
Bibliographic record
Abstract
OBJECTIVE: Menopause transition is associated with an increased prevalence of metabolic syndrome (MS), which may partly explain the higher coronary heart disease risk. The aim of this study was to examine the impact of a 16-week walking program on the metabolic risk profile of women 50 to 65 years old whose body mass index ranged from 29 to 35 kg/m. METHODS: A total of 153 postmenopausal women were subjected to three sessions per week of 45-minutes of walking at 60% of their heart rate reserve. At baseline, 46 and 84 women were characterized by one and two or more determinants of MS, respectively, whereas 23 women did not show this condition. Body composition, resting blood pressure, fasting lipid-lipoprotein profile, and cardiorespiratory fitness (CRF) were measured before and after exercise. RESULTS: In the whole sample of 153 women, CRF estimated by V(O2max) increased in response to walking (P < 0.0001). Endurance training promoted body weight and fat mass losses and reduced waist girth and blood pressure, whereas it decreased plasma triglyceride, cholesterol, and low-density lipoprotein cholesterol levels and increased high-density lipoprotein cholesterol concentrations (P < 0.0001). Improvements in lipid-lipoprotein levels were not associated with increases in CRF but seemed to be dependent on reduced body fatness. However, the greatest ameliorations in metabolic risk profile were found in women characterized by two or more determinants of MS at baseline than in the two other groups (0.05 < P < 0.0001). CONCLUSION: A moderate-intensity physical activity is thus sufficient to reduce the metabolic risk profile of postmenopausal women characterized by the presence of one or several clinical features of MS but without overt coronary heart disease.
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How this classification was reachedexpand
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".