Effect of the menopausal transition and physical activity energy expenditure on inflammatory markers: a MONET group study
Bibliographic record
Abstract
OBJECTIVE: Menopausal transition is usually associated with changes in body composition and a decrease in physical activity energy expenditure. Adipose tissue, especially visceral fat, is an important source of inflammatory markers, which contributes to the development of a proinflammatory state. Conversely, high levels of physical activity and exercise have an anti-inflammatory effect. This study aimed to investigate the impact of menopausal transition and physical activity on inflammatory makers. METHODS: One hundred two healthy premenopausal women participated in a 5-year longitudinal study. The present secondary analyses were performed on 58 participants with a full set of data (age: 49.6 ± 1.7 y; body mass index: 23.3 ± 2.4 kg/m). Measures included body composition, waist circumference, fasting glucose and insulin levels, insulin sensitivity, plasma lipid levels, cardiorespiratory fitness, physical activity energy expenditure, and inflammatory markers. RESULTS: Repeated measure analyses revealed, after the 5-year follow-up, significant increases in ferritin, interleukin-8 (IL-8), and soluble tumor necrosis factor-α receptor 1 and 2 (sTNFR1 and sTNFR2) (P < 0.001), and a significant decrease in serum high-sensitive C-reactive protein (P < 0.05). Positive correlations were observed between change (year 5 to baseline) in waist circumference and changes in high-sensitive C-reactive protein, orosomucoid (ORM), haptoglobin, and apolipoprotein B (ApoB) levels (0.26 ≤ r ≤ 0.34; P < 0.05), and between change in peripheral fat and changes in ORM, ApoB, sTNFR2 (0.28 ≤ r ≤ 0.39; P < 0.05). On the contrary, negative correlations were found between change in physical activity energy expenditure and changes in ORM as well as ApoB (r = -0.35 and r = -0.36, respectively; P < 0.05). No significant correlations were found between change in cardiorespiratory fitness, glucose, insulin, insulin sensitivity and changes in inflammatory markers. Multiple regression analyses showed that changes in physical activity energy expenditure and waist circumference together explained 23% of the individual variance of change in ORM (P < 0.05). Also, change in physical activity energy expenditure explained 15% (P < 0.05) of the variance of change in ApoB. Fat mass change explained 15% (P < 0.05) of the variance of change in IL-8, and finally change in peripheral fat explained 15% of variance of change in sTNFR2 (P < 0.05). CONCLUSIONS: The present study indicates that the menopausal transition is accompanied by an increase in inflammatory markers, namely ferritin, IL-8, sTNFR1, and sTNFR2. The increase in IL-8 and sTNFR2 with menopause could be explained, in part, by changes in fat mass and peripheral fat, respectively.
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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) | 0.001 | 0.000 |
| 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 | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".