The Association between Peptide Hormones with Obesity and Insulin Resistance Markers in Lean and Obese Individuals in the United Arab Emirates
Bibliographic record
Abstract
Peptide hormones play a crucial role in body weight and glucose homeostasis. In this study, we aimed to explore this association and recruited 43 obese and 31 age- and sex-matched lean participants. We assessed their body mass index (BMI), waist circumference (WC), waist-to-height ratio (WtHR), percentage body fat (PBF), fasting blood levels of peptide hormones (GLP-1, GLP-2, insulin, leptin, ghrelin, CCK, and PYY), fasting blood sugar (FBS), and Homeostatic Model Assessment of Insulin Resistance (HOMA-IR). We tested the associations between peptide hormones and markers of obesity and insulin resistance (IR) by using the Independent-Samples t-test and Mann-Whitney U test, partial correlation, and logistic regression. FBS, insulin, HOMA-IR, GLP-1, GLP-2, and leptin were significantly higher in the obese group; ghrelin and CCK were significantly higher in lean participants, and no difference was seen for PYY. Controlling for BMI, GLP-1 was positively correlated with WtHR, while ghrelin was inversely correlated with WtHR. GLP-1 was correlated with HOMA-IR. GLP-1 was associated with obesity and IR markers in the regression model. Our results show that obese and lean adults display significant differences in plasma peptide hormone levels. GLP-1 levels were independently associated with markers of obesity and IR. Restoring the appetite hormone balance in obesity may represent a potential therapeutic target.
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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 | 0.001 | 0.001 |
| 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".