Abstract 4189: Gender Difference in Inflammatory Markers: What is the Contribution of Visceral Adiposity?
Bibliographic record
Abstract
Several studies have reported a gender difference in inflammatory markers associated with obesity. Indeed, whereas C-reactive protein (CRP) concentrations have been found to be higher in pre-menopausal women compared to men, interleukin (IL)-6 and tumor necrosis factor (TNF)-α levels have been found to be lower in women than in men because of the inhibitory effect of estrogens on the expression of inflammatory genes. Since body fat distribution is very different between men and pre-menopausal women, the contribution of visceral adipose tissue (VAT) to the gender difference in inflammatory markers is a question of clinical relevance. To examine this issue, plasma CRP, IL-6 and TNF-α levels were measured in a sample of 195 healthy men (age: 41.7±14.9 years) and 139 healthy women (age: 36.6±11.2 years). Pre-menopausal women were characterized by lower plasma TNF-α levels (1.57±0.59 pg/mL vs.1.85±0.99 pg/mL, p=0.001) and higher CRP concentrations (1.91±1.77 mg/L vs. 1.65±1.78 mg/L, p=0.04) than men whereas the IL-6 levels did not differ between genders. Significant positive relationships were observed between VAT accumulation and CRP concentrations in men (r=0.43, p<0.0001) and in women (r=0.42, p<0.0001), or IL-6 in men (r=0.42, p<0.0001) and in women (r=0.51, p<0.0001). Regression analyses showed that gender did affect the associations between VAT and CRP. In order to investigate the contribution of visceral adiposity to the gender variation in inflammatory markers, 85 men and 85 pre-menopausal women were individually matched on the basis of similar VAT accumulation. After such matching procedure, women still had significantly higher CRP levels than men (2.07±1.88 and 1.57±1.84 mg/L, p=.01) whereas no differences were observed in IL-6 and TNF-α concentrations. Thus, these results suggest that the gender difference in CRP levels is not entirely explained by the greater amount of VAT generally observed in men.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".