{"title":"Association between eGDR and MASLD and liver fibrosis: a cross-sectional study based on NHANES 2017-2023.","authors":"Wenjing Peng, Zeyu Li, Nian Fu","doi":"10.3389/fmed.2025.1579879","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>This study aimed to investigate the association between estimated glucose disposal rate (eGDR) and metabolic dysfunction-associated steatotic liver disease (MASLD), as well as liver fibrosis, using data from the National Health and Nutrition Examination Survey (NHANES) 2017-2023 dataset.</p><p><strong>Methods: </strong>Data from 7,855 participants in the NHANES 2017-2023 dataset were analyzed. Multivariable logistic regression models were constructed to assess the association between eGDR (both continuous and quartiles) and MASLD, as well as liver fibrosis, adjusting for potential confounders. Generalized additive models (GAM) were used to explore non-linear relationships, stratified by age, hypertension, diabetes, cardiovascular disease (CVD), and body mass index (BMI). A two-piecewise linear regression model was used to examine threshold effects. Subgroup analyses were conducted to assess effect modification. Mediation analysis was performed to determine the role of the atherogenic index of plasma (AIP). Sensitivity analysis was performed to test the robustness of the results.</p><p><strong>Results: </strong>In the fully adjusted model, higher eGDR was inversely associated with both MASLD and liver fibrosis (MASLD: OR = 0.62, 95% CI: 0.53-0.72, <i>p</i> < 0.0001; liver fibrosis: OR = 0.50, 95% CI: 0.42-0.58, <i>p</i> < 0.0001). Participants in higher eGDR quartiles (Q2, Q3, and Q4) had progressively lower odds of both MASLD and liver fibrosis compared to those in Q1 (MASLD: Q2: OR = 0.56, 95% CI: 0.37-0.84, <i>p</i> = 0.0047; Q3: OR = 0.25, 95% CI: 0.12-0.50, <i>p</i> = 0.0001; Q4: OR = 0.13, 95% CI: 0.05-0.31, <i>p</i> < 0.0001; liver fibrosis: Q2: OR = 0.24, 95% CI: 0.13-0.44, <i>p</i> < 0.0001; Q3: OR = 0.06, 95% CI: 0.02-0.16, <i>p</i> < 0.0001; Q4: OR = 0.05, 95% CI: 0.01-0.19, <i>p</i> < 0.0001). A non-linear relationship with threshold effects at an eGDR value of 3.25 was observed for MASLD. Subgroup analyses revealed that the inverse association between eGDR and MASLD was more pronounced in individuals without diabetes. Additionally, smoothing curve fitting showed that the dose-response relationship between eGDR and both MASLD and liver fibrosis differed by metabolic and clinical status. Mediation analysis suggested that AIP partially mediated the association between eGDR and MASLD, accounting for approximately 10.6% of the total effect. Sensitivity analyses excluding extreme eGDR values confirmed the robust inverse associations with MASLD and liver fibrosis.</p><p><strong>Conclusion: </strong>This study found a significant non-linear inverse association between eGDR and both MASLD and liver fibrosis, with a threshold effect observed for MASLD. The association was stronger in non-diabetic individuals and partially mediated by AIP. Moreover, the dose-response relationships varied across metabolic and clinical subgroups.</p>","PeriodicalId":12488,"journal":{"name":"Frontiers in Medicine","volume":"12 ","pages":"1579879"},"PeriodicalIF":3.1000,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12162473/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers in Medicine","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.3389/fmed.2025.1579879","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q1","JCRName":"MEDICINE, GENERAL & INTERNAL","Score":null,"Total":0}
引用次数: 0
Abstract
Background: This study aimed to investigate the association between estimated glucose disposal rate (eGDR) and metabolic dysfunction-associated steatotic liver disease (MASLD), as well as liver fibrosis, using data from the National Health and Nutrition Examination Survey (NHANES) 2017-2023 dataset.
Methods: Data from 7,855 participants in the NHANES 2017-2023 dataset were analyzed. Multivariable logistic regression models were constructed to assess the association between eGDR (both continuous and quartiles) and MASLD, as well as liver fibrosis, adjusting for potential confounders. Generalized additive models (GAM) were used to explore non-linear relationships, stratified by age, hypertension, diabetes, cardiovascular disease (CVD), and body mass index (BMI). A two-piecewise linear regression model was used to examine threshold effects. Subgroup analyses were conducted to assess effect modification. Mediation analysis was performed to determine the role of the atherogenic index of plasma (AIP). Sensitivity analysis was performed to test the robustness of the results.
Results: In the fully adjusted model, higher eGDR was inversely associated with both MASLD and liver fibrosis (MASLD: OR = 0.62, 95% CI: 0.53-0.72, p < 0.0001; liver fibrosis: OR = 0.50, 95% CI: 0.42-0.58, p < 0.0001). Participants in higher eGDR quartiles (Q2, Q3, and Q4) had progressively lower odds of both MASLD and liver fibrosis compared to those in Q1 (MASLD: Q2: OR = 0.56, 95% CI: 0.37-0.84, p = 0.0047; Q3: OR = 0.25, 95% CI: 0.12-0.50, p = 0.0001; Q4: OR = 0.13, 95% CI: 0.05-0.31, p < 0.0001; liver fibrosis: Q2: OR = 0.24, 95% CI: 0.13-0.44, p < 0.0001; Q3: OR = 0.06, 95% CI: 0.02-0.16, p < 0.0001; Q4: OR = 0.05, 95% CI: 0.01-0.19, p < 0.0001). A non-linear relationship with threshold effects at an eGDR value of 3.25 was observed for MASLD. Subgroup analyses revealed that the inverse association between eGDR and MASLD was more pronounced in individuals without diabetes. Additionally, smoothing curve fitting showed that the dose-response relationship between eGDR and both MASLD and liver fibrosis differed by metabolic and clinical status. Mediation analysis suggested that AIP partially mediated the association between eGDR and MASLD, accounting for approximately 10.6% of the total effect. Sensitivity analyses excluding extreme eGDR values confirmed the robust inverse associations with MASLD and liver fibrosis.
Conclusion: This study found a significant non-linear inverse association between eGDR and both MASLD and liver fibrosis, with a threshold effect observed for MASLD. The association was stronger in non-diabetic individuals and partially mediated by AIP. Moreover, the dose-response relationships varied across metabolic and clinical subgroups.
背景:本研究旨在研究估计葡萄糖处置率(eGDR)与代谢功能障碍相关的脂肪变性肝病(MASLD)以及肝纤维化之间的关系,使用的数据来自2017-2023年国家健康与营养检查调查(NHANES)数据集。方法:分析NHANES 2017-2023数据集中7855名参与者的数据。构建多变量logistic回归模型来评估eGDR(包括连续和四分位数)与MASLD以及肝纤维化之间的关系,并对潜在的混杂因素进行调整。使用广义加性模型(GAM)来探索按年龄、高血压、糖尿病、心血管疾病(CVD)和体重指数(BMI)分层的非线性关系。采用两分段线性回归模型检验阈值效应。进行亚组分析以评估效果的改变。通过中介分析确定血浆动脉粥样硬化指数(AIP)的作用。进行敏感性分析以检验结果的稳健性。结果:在完全调整模型中,较高的eGDR与MASLD和肝纤维化均呈负相关(MASLD: OR = 0.62,95% CI: 0.53-0.72, p p p = 0.0047;Q3: OR = 0.25,95% CI: 0.12-0.50, p = 0.0001;Q4: OR = 0.13,95% CI: 0.05-0.31, p p p p 结论:本研究发现eGDR与MASLD和肝纤维化之间存在显著的非线性负相关,且MASLD存在阈值效应。非糖尿病患者的相关性更强,部分由AIP介导。此外,剂量-反应关系在代谢亚组和临床亚组中有所不同。
期刊介绍:
Frontiers in Medicine publishes rigorously peer-reviewed research linking basic research to clinical practice and patient care, as well as translating scientific advances into new therapies and diagnostic tools. Led by an outstanding Editorial Board of international experts, this multidisciplinary open-access journal is at the forefront of disseminating and communicating scientific knowledge and impactful discoveries to researchers, academics, clinicians and the public worldwide.
In addition to papers that provide a link between basic research and clinical practice, a particular emphasis is given to studies that are directly relevant to patient care. In this spirit, the journal publishes the latest research results and medical knowledge that facilitate the translation of scientific advances into new therapies or diagnostic tools. The full listing of the Specialty Sections represented by Frontiers in Medicine is as listed below. As well as the established medical disciplines, Frontiers in Medicine is launching new sections that together will facilitate
- the use of patient-reported outcomes under real world conditions
- the exploitation of big data and the use of novel information and communication tools in the assessment of new medicines
- the scientific bases for guidelines and decisions from regulatory authorities
- access to medicinal products and medical devices worldwide
- addressing the grand health challenges around the world