The Metabolically Healthy but Obese Individual Presents a Favorable Inflammation Profile
Bibliographic record
Abstract
OBJECTIVE: The purpose of this study was to investigate the inflammatory state in obese women displaying the "metabolically healthy but obese" (MHO) phenotype. DESIGN: We examined the metabolic characteristics of 88 obese, sedentary postmenopausal women. Subjects were classified as MHO or as "at risk" based on the upper and lower quartiles of insulin sensitivity as measured by the hyperinsulinemic-euglycemic clamp technique. Thereafter, we determined 1) body composition, 2) body fat distribution, 3) plasma lipid and lipoprotein levels, 4) glucose homeostasis, 5) resting blood pressure, 6) peak oxygen consumption, and 7) inflammation markers as potential modulators of differences in the coronary risk profile. RESULTS: Twenty-two MHO women displayed high insulin sensitivity (15.35 +/- 2.3 mg/min.kg fat-free mass), and 22 at risk subjects with low insulin sensitivity (7.98 +/- 1.4 mg/min.kg fat-free mass) were identified. Despite comparable total body fatness between groups (47.7 +/- 4.8 vs. 45.5 +/- 4.4%; not significant), MHO individuals had significantly lower levels of visceral fat, fasting insulin, plasma triglycerides, high-sensitivity C-reactive protein (CRP), and alpha-1 antitrypsin levels and higher levels of high-density lipoprotein cholesterol than at risk individuals (P < 0.05). Stepwise regression analysis showed that CRP, fasting triglycerides, and the lean body mass index explained 19.5, 8.5, and 4.0%, respectively, of the variance observed in glucose disposal (total r(2) = 0.320; P < 0.001). CONCLUSION: Results of the present study indicate that postmenopausal women displaying the MHO phenotype also have a favorable inflammation profile as shown by lower CRP and alpha-1 antitrypsin levels compared with insulin-resistant women. This suggests that a lower inflammation state, as attested by low CRP levels, could play a role in the protective profile of the MHO individual, and this may be associated metabolically to a lower risk for cardiovascular disease.
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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".