Associations between postmenopausal endogenous sex hormones and C-reactive protein: a clearer picture with regional adiposity adjustment?
Bibliographic record
Abstract
OBJECTIVE: To better understand the pathogenesis of inflammatory-related diseases after menopause, we studied the adiposity-independent association between endogenous sex hormones and C-reactive protein (CRP), a biomarker of inflammation. METHODS: We conducted a secondary, cross-sectional analysis of baseline data from the Alberta Physical Activity and Breast Cancer Prevention Trial (2003-2007), including 319 healthy, postmenopausal women not using hormone therapy. Multivariable linear regression models related serum CRP levels to estrogens, androgens, and sex hormone-binding globulin (SHBG), all on the natural logarithmic scale. Models were adjusted for age, lipids, medication, and former menopausal hormone therapy use, and also for adiposity (body mass index [BMI], per cent body fat [via whole-body dual x-ray absorptiometry], or intra-abdominal fat area [via computed tomography]). RESULTS: Without adiposity adjustment, estrone, total estradiol, and free estradiol were significantly positively associated with CRP, whereas SHBG was significantly inversely associated with CRP. Of all adiposity measures, adjustment for BMI caused the greatest attenuation of CRP-estrogen associations; only free estradiol (β = 0.24, 95% confidence interval [CI] 0.06, 0.43) and SHBG (β = -0.37, 95% CI -0.60, -0.13) associations remained significant. Inverse associations between CRP-total testosterone became stronger with BMI adjustment (β = -0.20, 95% CI -0.40, -0.01). Differential associations across categories of BMI, former hormone therapy use, and years since menopause were suggestive, but not statistically significant (Pheterogeneity > 0.05). CONCLUSIONS: Prospective and systems epidemiological studies are needed to understand whether or not the cross-sectional associations we observed, independent of adiposity, between CRP-SHBG, CRP-total testosterone, and CRP-free estradiol, are causal.
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".