ArticleFrontiers in nutrition2026
Exploratory mediation analysis of body roundness index in the nonlinear association between CHG index and metabolic dysfunction-associated steatotic liver disease among non-diabetic adults.
Article in Frontiers in nutrition, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Metabolic dysfunction-associated steatotic liver disease (MASLD) is the most prevalent chronic liver disease worldwide, highlighting an urgent need for non-invasive early biomarkers. The cholesterol, high-density lipoprotein, and glucose index (CHG) is a novel composite marker reflecting disturbances in glucose and lipid metabolism. However, the independent association between CHG and MASLD, and the potential statistical mediating effect of visceral adiposity, as represented by the body roundness index (BRI), remains unclear, especially in non-diabetic individuals. Methods: This cross-sectional study included 13,682 non-diabetic Japanese adults. Multivariable logistic regression, generalized additive models, and two-piecewise linear regression were used to explore the association, nonlinear relationship, and threshold effect between CHG and MASLD. Receiver operating characteristic (ROC) curve analysis was performed to evaluate CHG's discriminatory performance. Exploratory mediation analysis was performed to statistically decompose the association between CHG and MASLD via BRI. Results: The prevalence of MASLD was 15.25%. After full adjustment, each 1-unit increase in CHG was independently associated with a higher risk of MASLD (OR = 4.46, 95% CI: 3.00-6.64). A significant dose-response trend was observed across CHG quartiles (Q4 vs. Q1: OR = 4.09, 95% CI: 2.83-5.91). A nonlinear threshold effect was identified at CHG = 5.52. CHG showed excellent discriminatory performance (AUC = 0.84), with an optimal cutoff at 5.23 (sensitivity = 0.81, specificity = 0.73), and retained robust discriminatory capacity in non-obese and young individuals. BRI showed a significant statistical mediating effect in the CHG-MASLD association, accounting for 46.15% of the total observed association. Subgroup mediation analyses revealed that this mediating effect was more pronounced in non-obese and normotriglyceridemic individuals. Conclusion: In non-diabetic Japanese adults, CHG is independently and nonlinearly associated with MASLD risk, with BRI as a potential statistical mediator. This mediating effect exhibits heterogeneity and is more pronounced in non-obese individuals. The causal direction of this pathway remains to be verified in prospective studies. CHG shows potential as a low-cost indicator for early MASLD risk stratification, especially in non-obese and younger populations who are often missed by conventional screening.
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.