Increased body fat mass explains the positive association between circulating estradiol and insulin resistance in postmenopausal women
Bibliographic record
Abstract
The relationship between circulating estrogen levels and cardiometabolic risk factors such as insulin resistance is unclear in postmenopausal women. High estradiol (E2) levels have been reported to predict increased risk of type 2 diabetes in this population. We aimed to examine associations among estrogen levels, adiposity measurements, and cardiometabolic risk variables including insulin resistance in postmenopausal women. One hundred-one healthy participants (mean ± SD: age 57 ± 4 yr, BMI 27.9 ± 4.8 kg/m2) were included in the analysis. Fifteen plasma steroids or metabolites were measured by liquid chromatography-tandem mass spectrometry. Insulin sensitivity was assessed with a hyperinsulinemic-euglycemic clamp. Body composition and fat distribution were determined with hydrostatic weighing and computed tomography, respectively. Blood lipids and circulating cytokines were also measured. Circulating E2was positively correlated with all adiposity indexes ( r = 0.62 to 0.42, P < 0.0001) except waist-to-hip ratio. E2was positively correlated with VLDL-cholesterol, plasma-, VLDL-, and HDL-triglyceride levels ( r = 0.31 to 0.24, P < 0.02) as well as with hs-CRP and IL-6 ( r = 0.52 and 0.29, P < 0.005) and negatively with HDL-cholesterol, adiponectin, and insulin sensitivity ( r = −0.36 to −0.20, P < 0.02). With adjustments for percent body fat, correlations between E2and metabolic risk variables were no longer significant. Similar results were observed for circulating estrone (E1) and estrone-sulfate (E1-S) levels. In conclusion, circulating estrogen concentrations are proportional to adipose mass in postmenopausal women, although they remain in the low range. Insulin resistance as well as altered blood lipids and cytokines are observed when circulating estrogen levels are high within that range, but these differences are explained by concomitant variation in total adiposity.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".