Visceral Adipocyte Hypertrophy is Associated With Dyslipidemia Independent of Body Composition and Fat Distribution in Women
Bibliographic record
Abstract
OBJECTIVE: We assessed whether subcutaneous and omental adipocyte hypertrophy are related to metabolic alterations independent of body composition and fat distribution in women. RESEARCH DESIGN AND METHODS: Mean adipocyte diameter of paired subcutaneous and omental adipose tissue samples was obtained in lean to obese women. Linear regression models predicting adipocyte size in both adipose tissue depots were computed using body composition and fat distribution measures (n = 150). In a given depot, women with larger adipocytes than predicted by the regression were considered as having adipocyte hypertrophy, whereas women with smaller adipocytes than predicted were considered as having adipocyte hyperplasia. RESULTS: Women characterized by omental adipocyte hypertrophy had higher plasma and VLDL triglyceride levels as well as a higher total-to-HDL cholesterol ratio compared with women characterized by omental adipocyte hyperplasia (P < 0.05). Conversely, women characterized by subcutaneous adipocyte hypertrophy or hyperplasia showed a similar lipid profile. In logistic regression analyses, a 10% enlargement of omental adipocytes increased the risk of hypertriglyceridemia (adjusted odds ratio [OR] 4.06, P < 0.001) independent of body composition and fat distribution measures. A 10% increase in visceral adipocyte number also raised the risk of hypertriglyceridemia (adjusted OR 1.55, P < 0.02). Associations between adipocyte size and homeostasis model assessment of insulin resistance were not significant once adjusted for adiposity and body fat distribution. CONCLUSIONS: These results suggest that omental, but not subcutaneous, adipocyte hypertrophy is associated with an altered lipid profile independent of body composition and fat distribution in women.
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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 | 0.000 | 0.001 |
| 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) | 0.001 | 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".