Body composition, cardiometabolic risk factors, physical activity, and inflammatory markers in premenopausal women after a 10-year follow-up: a MONET study
Bibliographic record
Abstract
OBJECTIVE: Menopausal transition and postmenopause are usually associated with changes in body composition and a decrease in physical activity energy expenditure (PAEE). This study investigated body composition, cardiometabolic risk factors, PAEE, and inflammatory markers in premenopausal women after a 10-year follow-up. METHODS: In all, 102 premenopausal women participated in the 5-year observational longitudinal Montreal Ottawa New Emerging Team (MONET) study. This present substudy included 48 participants (age: 60.0 ± 1.7 years; body mass index: 23.2 ± 2.2 kg/m) 6.0 ± 0.3 years after completion of the initial MONET study. Measures included body composition, waist circumference (WC), fasting glucose and insulin levels, insulin sensitivity (QUICKI model), plasma lipid levels, PAEE, and inflammatory markers. RESULTS: Compared with baseline measures of the MONET study, analyses revealed no significant increase in body weight, although there were significant increases in WC, fat mass (FM), % FM, total cholesterol, low-density lipoprotein cholesterol and high-density lipoprotein cholesterol, haptoglobin, apolipoprotein B, ferritin, adiponectin, and soluble cluster of differentiation 14 (all P < 0.001) after the 10-year follow-up. However, significant decreases were observed for fat-free mass, PAEE, fasting glucose levels, interleukin-8 levels, and soluble tumor necrosis factor receptors 1 and 2 (sTNFR-1 and sTNFR-2) levels (all P < 0.05). To determine the effect of postmenopausal years, data were restructured based on final menstrual period (FMP), and one-way analyses of variance were performed.Waist circumference, % FM, total cholesterol, high-density lipoprotein cholesterol, apolipoprotein B, ferritin, adiponectin, and soluble cluster of differentiation 14 were higher in early and late postmenopausal periods in these women. sTNFR-1 and sTNFR-2 levels were higher at the FMP and early postmenopausal years as compared with the late postmenopausal periods. Finally, interleukin-8 levels were lower in years after FMP. CONCLUSION: The number of years elapsed since the FMP can affect body composition, cardiometabolic risk factors, and inflammatory markers in healthy premenopausal women going through menopausal transition and postmenopausal periods.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".