Identifying Metabolically Healthy but Obese Individuals in Sedentary Postmenopausal Women
Bibliographic record
Abstract
The purpose of this study was to compare different methods to identify metabolically healthy but obese (MHO) individuals in a cohort of obese postmenopausal women. We examined the anthropometric and metabolic characteristics of 113 obese (age: 57.3 +/- 4.8 years; BMI: 34.2 +/- 2.7 kg/m(2)), sedentary postmenopausal women. The following methods were used to identify MHO subjects: the hyperinsulinemic-euglycemic clamp (MHO: upper quartile of glucose disposal rates); the Matsuda index (MHO: upper quartile of the Matsuda index); the homeostasis model assessment (HOMA) index (MHO: lower quartile of the HOMA index); having 0-1 cardiometabolic abnormalities (systolic/diastolic blood pressure > or =130/85 mm Hg, triglycerides (TG) > or =1.7 mmol/l, glucose > or =5.6 mmol/l, HOMA >5.13, high-sensitive C-reactive protein (hsCRP) >0.1 mg/l, high-density lipoprotein-cholesterol (HDL-C) <1.3 mmol/l); and meeting four out of five metabolic factors (HOMA < or =2.7, TG < or =1.7 mmol/l, HDL-C > or =1.3 mmol/l, low-density lipoprotein-cholesterol < or =2.6 mmol/l, hsCRP < or =3.0 mg/l). Thereafter, we measured insulin sensitivity, body composition (dual-energy X-ray absorptiometry), body fat distribution (computed tomography scan), energy expenditure, plasma lipids, inflammation markers, resting blood pressure, and cardiorespiratory fitness. We found significant differences in body composition (i.e., peripheral fat mass, central lean body mass (LBM)) and metabolic risk factors (i.e., HDL-C, hsCRP) between MHO and at risk individuals using the different methods to identify both groups. In addition, significant differences between MHO subjects using the different methods to identify MHO individuals were observed such as age, TG/HDL, hsCRP, and fasting insulin. However, independently of the methods used, we noted some recurrent characteristics that identify MHO subjects such as TG, apolipoprotein B, and ferritin. In conclusion, the present study shows variations in body composition and metabolic profile based on the methods studied to define the MHO phenotype. Therefore, an expert consensus may be needed to standardize the identification of MHO individuals.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".