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. 2025 Jul 2:12:1621074.
doi: 10.3389/fnut.2025.1621074. eCollection 2025.

Association between estimated glucose disposal rate and metabolic dysfunction-associated steatotic liver disease and dyslipidemia in US adults: a cross-sectional study

Deliang Liu #  1   2 , Xiaojun Lv #  1   2 , Wenwen Li  1   2 , Hongsheng Dai  1   2 , Yang Tan  1   2 , Dandan Yang  1   2 , Xiaoqian Zhang  1   2
Affiliations

Association between estimated glucose disposal rate and metabolic dysfunction-associated steatotic liver disease and dyslipidemia in US adults: a cross-sectional study

Deliang Liu et al. Front Nutr. .

Abstract

Background: Metabolic dysfunction-associated steatotic liver disease (MASLD) is strongly associated with insulin resistance (IR). This study examined the relationship between estimated glucose disposal rate (eGDR), a simple IR indicator, and MASLD risk.

Methods: Using NHANES 2017-2018 data (n = 3,957), MASLD was diagnosed by CAP ≥285 dB/m. eGDR was calculated from waist circumference, hypertension, and HbA1c.

Results: Lower eGDR significantly predicted higher MASLD risk (OR = 0.396, p < 0.01) and elevated CAp values (b = -21.375, p < 0.01). It also correlated with unfavorable lipid profiles (lower HDL, higher triglycerides). Subgroup analyses showed consistent associations across age, sex, and diabetes status.

Conclusion: Estimated glucose disposal rate was significantly associated with both MASLD and dyslipidemia. eGDR may serve as a useful indicator for identifying risk factors related to these metabolic disorders. Mediation analysis revealed that relative fat mass (RFM), (high-density lipoprotein cholesterol) HDL, triglyceride (TG), visceral adiposity index (VAI), and uric acid to HDL ratio (UHR) mediated the association between eGDR and MASLD, with respective proportions of 61.09, 6.79, 6.53, 9.85, and 12.9%.

Keywords: IR; MASLD; NHANES; eGDR; lipid.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
The flow chart of participant selection in the first part of the study.
Figure 2
Figure 2
The flow chart of participant selection in the second part of the study.
Figure 3
Figure 3
Smooth curve fitting between eGDR and MASLD.
Figure 4
Figure 4
Smooth curve fitting between eGDR and CAP.
See this image and copyright information in PMC

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