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2 "Ji-Won Lee"
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Lifestyle and Behavioral Interventions
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Assessing Nutritional Factors for Metabolic Dysfunction-Associated Steatotic Liver Disease via Diverse Statistical Tools
Yea-Chan Lee, Hye Sun Lee, Soyoung Jeon, Yae-Ji Lee, Yu-Jin Kwon, Ji-Won Lee
Diabetes Metab J. 2026;50(1):178-189.   Published online June 9, 2025
DOI: https://doi.org/10.4093/dmj.2025.0026
  • 3,203 View
  • 94 Download
AbstractAbstract PDFSupplementary MaterialPubReader   ePub   
Background
Lifestyle modifications are critical in addressing metabolic dysfunction-associated steatotic liver disease (MASLD); however, the specific macronutrients that most significantly influence the disease’s progression are uncertain. In this study, we aimed to explore the role of carbohydrate, fat, and protein intake in MASLD development using decision trees, random forest models, and cluster analysis.
Methods
Participants (n=3,951) from the Korean Genome and Epidemiology Study were included. We used the classification and regression tree analysis to classify participants into subgroups based on variables associated with the incidence of new-onset MASLD. Random forest analyses were used to assess the relative importance of each variable. Participants were grouped into homogeneous clusters based on carbohydrate, protein, fat, and total caloric intake using hierarchical cluster analysis. Subsequently, we used the Cox proportional hazards regression models to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for MASLD risk across the clusters.
Results
Carbohydrate intake was identified as the most significant predictor of new-onset MASLD, followed by fat, protein, and total caloric intake. Participants in cluster 3, who consumed a lower proportion of carbohydrate but had higher total caloric, protein, and fat intake, had a lower risk of new-onset MASLD than those in cluster 1 after adjusting for confounders (cluster 1 as a reference; cluster 3: HR, 0.90; 95% CI, 0.82 to 0.99).
Conclusion
The study’s results highlight the critical role of macronutrient composition, particularly carbohydrate intake, in MASLD development. The findings suggest that dietary strategies focusing on optimizing macronutrients, rather than simply reducing caloric intake, may be more effective in preventing MASLD.
Metabolic Risk/Epidemiology
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Comparison of SPISE and METS-IR and Other Markers to Predict Insulin Resistance and Elevated Liver Transaminases in Children and Adolescents
Kyungchul Song, Eunju Lee, Hye Sun Lee, Hana Lee, Ji-Won Lee, Hyun Wook Chae, Yu-Jin Kwon
Diabetes Metab J. 2025;49(2):264-274.   Published online October 29, 2024
DOI: https://doi.org/10.4093/dmj.2024.0302
  • 7,099 View
  • 239 Download
  • 13 Web of Science
  • 12 Crossref
AbstractAbstract PDFSupplementary MaterialPubReader   ePub   
Background
Studies on predictive markers of insulin resistance (IR) and elevated liver transaminases in children and adolescents are limited. We evaluated the predictive capabilities of the single-point insulin sensitivity estimator (SPISE) index, metabolic score for insulin resistance (METS-IR), homeostasis model assessment of insulin resistance (HOMA-IR), the triglyceride (TG)/ high-density lipoprotein cholesterol (HDL-C) ratio, and the triglyceride-glucose index (TyG) for IR and alanine aminotransferase (ALT) elevation in this population.
Methods
Data from 1,593 participants aged 10 to 18 years were analyzed using a nationwide survey. Logistic regression analysis was performed with IR and ALT elevation as dependent variables. Receiver operating characteristic (ROC) curves were generated to assess predictive capability. Proportions of IR and ALT elevation were compared after dividing participants based on parameter cutoff points.
Results
All parameters were significantly associated with IR and ALT elevation, even after adjusting for age and sex, and predicted IR and ALT elevation in ROC curves (all P<0.001). The areas under the ROC curve of SPISE and METS-IR were higher than those of TyG and TG/HDL-C for predicting IR and were higher than those of HOMA-IR, TyG, and TG/HDL-C for predicting ALT elevation. The proportions of individuals with IR and ALT elevation were higher among those with METS-IR, TyG, and TG/ HDL-C values higher than the cutoff points, whereas they were lower among those with SPISE higher than the cutoff point.
Conclusion
SPISE and METS-IR are superior to TG/HDL-C and TyG in predicting IR and ALT elevation. Thus, this study identified valuable predictive markers for young individuals.

Citations

Citations to this article as recorded by  
  • Association between the single-point insulin sensitivity estimator and cardiovascular disease incidence: A prospective nationwide cohort study involving two cohorts
    Xiaotong Yao, Lina Liu, Lifen Zhao, Nianzhu Zhang
    Atherosclerosis.2026; 412: 120591.     CrossRef
  • Purpose in Life and Insulin Resistance in a Large Occupational Cohort: Cross-Sectional Associations Using TyG, SPISE-IR, and METS-IR Indices
    Pilar García Pertegaz, Pedro Juan Tárraga López, Irene Coll Campayo, Carla Busquets-Cortés, Ángel Arturo López-González, José Ignacio Ramírez-Manent
    Diabetology.2026; 7(1): 16.     CrossRef
  • Utility of the MetS-IR and SPISE indices for identifying insulin resistance in Mexican children
    Edmundo Gutiérrez-Rosas, Marco A. Morales-Pérez, Mayra Cristina Torres-Castañeda, Lorena Lizárraga-Paulín, Rita A. Gómez-Díaz, Adriana L. Valdez-González, Niels H. Wacher
    Obesity Research & Clinical Practice.2026; 20(1): 29.     CrossRef
  • How Emerging Digital Health Technologies Based on Dietary and Physical Activity Regulation Improve Metabolic Syndrome-Related Outcomes in Adolescents: A Systematic Review
    Ruida Yu, Angkun Li, Yufei Qi, Jianhong Hu, Fei Peng, Shengrui Cao, Siyu Rong, Hao Zhang
    Metabolites.2026; 16(2): 106.     CrossRef
  • The Prognostic Significance of the Metabolic Score for Insulin Resistance and Subclinical Myocardial Injury for Cardiovascular Mortality in the General Population
    Patrick Cheon, Shannon O’Connor, Saeid Mirzai, Mohamed A. Mostafa, Chuka B. Ononye, Elsayed Z. Soliman, Richard Kazibwe
    Journal of Clinical Medicine.2026; 15(3): 1141.     CrossRef
  • Is Measuring BMI and Waist Circumference as Good in Assessing Insulin Resistance as Using Bioelectrical Impedance to Measure Total Body Fat and Visceral Fat?
    María Gordito Soler, Pedro Juan Tárraga López, Ángel Arturo López-González, Hernán Paublini, Emilio Martínez-Almoyna Rifá, María Teófila Vicente-Herrero, José Ignacio Ramírez-Manent
    Diabetology.2025; 6(4): 32.     CrossRef
  • Association between cardiometabolic index and postmenopausal stress urinary incontinence: a cross-sectional study from NHANES 2013 to 2018
    Ting Yin, Yue He, Huifang Cong
    Lipids in Health and Disease.2025;[Epub]     CrossRef
  • Identification of pediatric MASLD using insulin resistance indices
    Kyungchul Song, Eunju Lee, Hye Sun Lee, Young Hoon Youn, Su Jung Baik, Hyun Joo Shin, Hyun Wook Chae, Ji-Won Lee, Yu-Jin Kwon
    JHEP Reports.2025; 7(7): 101419.     CrossRef
  • Screening accuracy of Single-Point Insulin Sensitivity Estimator (SPISE) for metabolic syndrome: a systematic review and meta-analysis
    Alireza Azarboo, Parisa Fallahtafti, Sayeh Jalali, Amirhossein Shirinezhad, Ramin Assempoor, Amirhossein Ghaseminejad-Raeini
    BMC Endocrine Disorders.2025;[Epub]     CrossRef
  • Associations of triglyceride-glucose index and metabolic score for insulin resistance with various hypertension phenotypes in children and adolescents: results from the 2017 China nutrition and health surveillance
    Haiyuan Zhu, Lianlong Yu, Qiqi Wu, Runquan Zhang, Zebang Zhang, Yumei Feng, Tao Liu, Dan Liu, Jiewen Peng, Xiongfei Chen, Xiaomei Dong
    Frontiers in Endocrinology.2025;[Epub]     CrossRef
  • Associations between the METS-IR index and cognitive function in community-dwelling Chinese middle-aged and older adult individuals: a cross-sectional study
    Nian Jiang, Chenlu Ma, Zhenning Feng, Yongjun Tang, Xiaolong Chen, Yingxu He, Weiyi Pang
    Frontiers in Public Health.2025;[Epub]     CrossRef
  • Comparison of single-point insulin sensitivity estimator and other markers to predict metabolic syndrome in children and adolescents
    Kyungchul Song, Eunju Lee, Hye Sun Lee, Hana Lee, Hyun Wook Chae, Yu-Jin Kwon
    Obesity Research & Clinical Practice.2025; 19(5): 427.     CrossRef

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