Moderate Weight Loss Improves Body Composition and Metabolic Function in Metabolically Unhealthy Lean Subjects
Bibliographic record
Abstract
Objective Individuals who have “metabolically obese normal weight” (MONW) have an increased risk for cardiometabolic disease. Moderate weight loss has multiple benefits in people with obesity, but its effects in lean people are unknown. Thus, the effects of diet‐induced 5% weight loss on body composition and metabolic function in MONW subjects were evaluated. Methods Total body fat, visceral adipose tissue (VAT) and subcutaneous abdominal adipose tissue (SAT) volumes, intrahepatic and intramyocellular lipid contents, insulin sensitivity (hyperinsulinemic‐euglycemic clamp), glucose tolerance, and postprandial insulin secretion and clearance rates (mixed meal with minimal modeling) were measured before and after 4.8% ± 0.5% weight loss in 11 MONW Asians (48 ± 3 years old, six men and five women, BMI 22.7 ± 0.4 kg/m 2 ). Results Weight loss decreased total fat mass by ∼9%, VAT and SAT volumes by ∼11% and ∼17%, respectively, and intrahepatic fat by ∼50% (all P < 0.05). Fasting plasma insulin, triglyceride, and total low‐ and high‐density lipoprotein cholesterol concentrations were also reduced ( P < 0.05). Insulin sensitivity indexes (M‐value and M/I ratio) increased by 21% to 26% (both P < 0.05); β‐cell responsivity and postprandial insulin secretion rate did not change, but insulin clearance rate increased by 16% ( P < 0.05). Conclusions Diet‐induced moderate weight loss improves body composition, lipid profile, and insulin sensitivity and thereby reduces cardiometabolic risk in MONW Asians.
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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 | 0.001 | 0.000 |
| 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 | 0.000 |
| 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 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".