Adiponectinemia in Visceral Obesity: Impact on Glucose Tolerance and Plasma Lipoprotein and Lipid Levels in Men
Bibliographic record
Abstract
The present study examined the associations between a major adipokine, adiponectin, and adiposity indices as well as metabolic risk variables in a sample of 190 untreated asymptomatic men. Anthropometric measurements and a complete fasting plasma lipoprotein and lipid profile were obtained, and subjects underwent an oral glucose tolerance test. Fasting plasma adiponectin concentrations were determined by an ELISA. Although all adiposity and adipose tissue (AT) distribution indices were negatively correlated with plasma adiponectin levels (-0.14 </= r </= -0.32; P < 0.04), multiple regression analyses revealed that visceral AT accumulation was the only independent predictor of adiponectin levels, with 10% of its variance explained by visceral AT (P < 0.0001). Comparison of obese men with similar body mass index values (>/=30 kg/m(2)) but who markedly differed in their level of visceral AT (< vs. >/=130 cm(2); n = 15) revealed significant differences in adiponectin levels (7.0 +/- 3.0 vs. 11.1 +/- 4.9 microg/ml; P < 0.02 for men with high vs. low visceral AT, respectively). Finally, when men were stratified into tertiles of visceral AT and further classified on the basis of the 50th percentile of adiponectin levels (</= vs. >8.8 microg/ml), a 3 x 2 ANOVA revealed an independent contribution of adiponectin on the variation of high-density lipoprotein cholesterol levels (P < 0.002) and of the glucose area (P < 0.02). These results support the notion that adiponectin concentration is influenced to a greater extent by visceral than sc obesity. Furthermore, adiponectin predicts glucose tolerance and plasma high-density lipoprotein cholesterol levels in a manner that is partly independent from the contribution of visceral adiposity.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".