Triglyceride-glucose index and its combination with anthropometric obesity indicators are significant predictors of visceral obesity among the Newfoundland population
Bibliographic record
Abstract
Visceral obesity (VO) is a critical risk factor for metabolic disorders and cardiovascular diseases. Although DXA, CT, or MRI are reliable tools for measuring visceral adiposity, their routine use is limited by cost and accessibility. The triglyceride-glucose (TyG) index, a surrogate marker of insulin resistance, has shown potential as a cost-effective predictor of VO in type 2 diabetes mellitus (T2DM). However, its relationship with visceral adiposity in generally healthy populations remains unclear. A total of 2921 healthy adults (825 males, 2096 females) without serious metabolic, cardiovascular, or endocrine diseases were included. Anthropometric measurements (including body mass index (BMI), waist circumference (WC), and waist-to-height ratio (WHtR)) and blood analyses (fasting plasma glucose, triglycerides) were performed. Visceral adipose tissue (VAT) mass and volume were measured using DXA. Logistic regression identified independent factors of VO, defined as VAT mass or volume ≥ 85th percentile by sex. ROC curve analyses assessed the predictive ability of TyG and its related indices. Visceral adiposity increased with ascending TyG quartiles in both sexes, showing a dose-dependent manner. Individuals with VO exhibited higher TyG than those without VO in males (8.95 vs. 8.39) and females (8.81 vs. 8.20). TyG was positively correlated with visceral adiposity and identified as an independent risk factor of VO, with stronger associations in females (OR = 3.512, 95%CI: 2.538-4.861) compared to males (OR = 1.575, 95%CI: 1.002-2.477). ROC analyses showed TyG index had a significant predictive value for VO in males (AUC = 0.733) and females (AUC = 0.791). Combining TyG with BMI, WC, and WHtR, further improved predictive accuracy for VO in females (AUC = 0.930 for TyG-BMI, AUC = 0.929 for TyG-WC, and AUC = 0.926 for TyG-WHtR). TyG index is a significant predictor of VO, particularly in females. Combining TyG with BMI, WC, or WHtR enhances its predictive accuracy, making it a simple, low-cost and valuable screening tool for early identification of individuals at risk of VO.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".