Diabetes & Metabolism Journal

Hong-Yup Ahn (Ahn HY)

3 Articles

Metabolic Risk/Epidemiology
Metabolic Dysfunction-Associated Fatty Liver Disease and Mortality: A Population-Based Cohort Study: Kyung-Soo Kim, Sangmo Hong, Hong-Yup Ahn, Cheol-Young Park; Diabetes Metab J. 2023;47(2):220-231. Published online January 12, 2023; DOI: https://doi.org/10.4093/dmj.2021.0327

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Background
We investigated whether metabolic dysfunction-associated fatty liver disease (MAFLD) is associated with an elevated risk of all-cause and cardiovascular mortality using a large-scale health examination cohort.
Methods
A total of 394,835 subjects in the Kangbuk Samsung Health Study cohort were enrolled from 2002 to 2012. Participants were categorized by the presence of nonalcoholic fatty liver disease (NAFLD) and MAFLD as follows: normal subjects; patients with both NAFLD and MAFLD; patients with NAFLD only; and patients with MAFLD only. Cox proportional hazards models were used to analyze the risk of mortality.
Results
During a median 5.7 years of follow-up, 20.69% was patients with both NAFLD and MAFLD, 1.51% was patients with NAFLD only, and 4.29% was patients with MAFLD only. All-cause and cardiovascular death was higher in patients with MAFLD than those without MAFLD (P<0.001, respectively). In patients with MAFLD only, the hazard ratio (HR) of all-cause and cardiovascular death was 1.35 (95% confidence interval [CI], 1.13 to 1.60) and 1.90 (95% CI, 1.26 to 2.88) after adjusting for age, which lost its statistical significance by multivariable adjustments. Compared to patients with less than two components of metabolic dysfunction, patients with more than two components of metabolic dysfunction were a higher risk of cardiovascular death (HR, 2.05; 95% CI, 1.25 to 3.38) and only women with more than two components of metabolic dysfunction were a higher risk of all-cause death (HR, 1.44; 95% CI, 1.02 to 2.03).
Conclusion
MAFLD criteria could identify a high-risk group for all-cause and cardiovascular death.

Citations

Citations to this article as recorded by

Mortality in metabolic dysfunction-associated steatotic liver disease: A nationwide population-based cohort study
Eugene Han, Byung-Wan Lee, Eun Seok Kang, Bong-Soo Cha, Sang Hoon Ahn, Yong-ho Lee, Seung Up Kim
Metabolism.2024; 152: 155789. CrossRef
Association of non-alcoholic fatty liver disease with cardiovascular disease and all cause death in patients with type 2 diabetes mellitus: nationwide population based study
Kyung-Soo Kim, Sangmo Hong, Kyungdo Han, Cheol-Young Park
BMJ.2024; : e076388. CrossRef
Sex differences in mortality and liver‐related events in non‐alcoholic fatty liver disease: A systematic review and meta‐analysis
Huimin Zhou, Haiyan Chen, Hanxiao Lu, Bo Wu, Shuo Zhang, Yuanlong Gu, Guangwen Zhou, Jie Xiang, Jun Yang
Liver International.2024; 44(7): 1600. CrossRef
Association between dietary carbohydrate to fiber ratio and metabolic dysfunction associated fatty liver disease in adults: evidence from the NHANES 2017–2020
Zhenmin Liu, Taiyong Fang
Journal of Health, Population and Nutrition.2024;[Epub] CrossRef
NAFLD and MAFLD independently increase the risk of major adverse cardiovascular events (MACE): a 20-year longitudinal follow-up study from regional Australia
Karl Vaz, William Kemp, Ammar Majeed, John Lubel, Dianna J. Magliano, Kristen M. Glenister, Lisa Bourke, David Simmons, Stuart K. Roberts
Hepatology International.2024; 18(4): 1135. CrossRef
Clinical outcomes of MAFLD versus NAFLD: A meta‐analysis of observational studies
Grazia Pennisi, Giuseppe Infantino, Ciro Celsa, Gabriele Di Maria, Marco Enea, Marco Vaccaro, Roberto Cannella, Carlo Ciccioli, Claudia La Mantia, Alessandro Mantovani, Francesco Mercurio, Herbert Tilg, Giovanni Targher, Vito Di Marco, Calogero Cammà, Sal
Liver International.2024; 44(11): 2939. CrossRef
Racial and ethnic disparities in metabolic dysfunction-associated steatotic liver disease outcomes: A call for culturally sensitive interventions: Editorial on “Differences in liver and mortality outcomes of non-alcoholic fatty liver disease by race and e
Jae Hyun Bae
Clinical and Molecular Hepatology.2024; 30(4): 665. CrossRef
Comparison of Outcomes Between Metabolic Dysfunction-Associated Fatty Liver Disease and Non-alcoholic Fatty Liver Disease: A Meta-Analysis
Ghazala S Virk, Jaahnavi Vajje, Nausheen K Virk, Raam Mannam, Wajeeh Rehman, Naglaa G Ghobriel , Irfan-ud-din Mian, Muhammad Usama
Cureus.2023;[Epub] CrossRef
Trends in prevalence and all-cause mortality of metabolic dysfunction-associated fatty liver disease among adults in the past three decades: Results from the NHANES study
Zhi-Qin Xie, Hong-Xia Li, Bing-Kun Wang, Zhao-Ming Yang, Zi-Yu Zhang, Wen-Liang Tan, Wen-Xin Li, Qing-Bin Wang, Lei Yang, Hong-Kai Zhuang, Chen-Wei Tang, Chang-Zhen Shang, Ya-Jin Chen
European Journal of Internal Medicine.2023; 110: 62. CrossRef
Comparing the Mortality Risk between Metabolic Dysfunction-Associated Fatty Liver Disease and Non-Alcoholic Fatty Liver Disease
Han Na Jung, Chang Hee Jung
Diabetes & Metabolism Journal.2023; 47(2): 198. CrossRef
Increased expression of sodium-glucose cotransporter 2 and O-GlcNAcylation in hepatocytes drives non-alcoholic steatohepatitis
Hye Jin Chun, Eun Ran Kim, Minyoung Lee, Da Hyun Choi, Soo Hyun Kim, Eugene Shin, Jin-Hong Kim, Jin Won Cho, Dai Hoon Han, Bong-Soo Cha, Yong-ho Lee
Metabolism.2023; 145: 155612. CrossRef
Current understanding and future perspectives on the impact of changing NAFLD to MAFLD on global epidemiology and clinical outcomes
Karl Vaz, Daniel Clayton-Chubb, Ammar Majeed, John Lubel, David Simmons, William Kemp, Stuart K. Roberts
Hepatology International.2023; 17(5): 1082. CrossRef
Mitochondrial Quality Control: Its Role in Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD)
Soyeon Shin, Jaeyoung Kim, Ju Yeon Lee, Jun Kim, Chang-Myung Oh
Journal of Obesity & Metabolic Syndrome.2023; 32(4): 289. CrossRef

Metabolic Risk/Epidemiology
Trends in the Prevalence of Obesity and Its Phenotypes Based on the Korea National Health and Nutrition Examination Survey from 2007 to 2017 in Korea: Sang Ouk Chin, You-Cheol Hwang, Hong-Yup Ahn, Ji Eun Jun, In-Kyung Jeong, Kyu Jeung Ahn, Ho Yeon Chung; Diabetes Metab J. 2022;46(5):808-812. Published online March 8, 2022; DOI: https://doi.org/10.4093/dmj.2021.0226

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This study used data from the Korea National Health and Nutrition Examination Survey IV–VII from 2007 to identify the prevalence of obesity and its phenotypes (metabolically unhealthy obesity [MUO] and metabolically healthy obesity [MHO]) and their secular changes. The prevalence of obesity in Korea increased with significant secular changes observed (β=0.326, P trend <0.01) between 2007 and 2017, and especially in men (β=0.682, P trend <0.001) but not in women. The changes in the prevalence of obesity during the study period were different between men and women (P=0.001). The prevalence of MUO significantly increased only in men (β=0.565, P trend <0.01), while that of MHO increased only in women (β=0.179, P<0.05), especially in the younger age group (β=0.308, P<0.01).

Citations

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Link between obesity and growth in children and adolescents
Hae Sang Lee
Journal of the Korean Medical Association.2024; 67(5): 330. CrossRef
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Eun Roh, Kyung Mook Choi
International Journal of Molecular Sciences.2023; 24(4): 3384. CrossRef
Differences of Regional Fat Distribution Measured by Magnetic Resonance Imaging According to Obese Phenotype in Koreans
Ha-Neul Choi, Hyunjung Lim, Young-Seol Kim, Sang-Youl Rhee, Jung-Eun Yim
Metabolic Syndrome and Related Disorders.2022; 20(10): 551. CrossRef

Others
Comparison of the Usefulness of the Updated Homeostasis Model Assessment (HOMA2) with the Original HOMA1 in the Prediction of Type 2 Diabetes Mellitus in Koreans: Young Seok Song, You-Cheol Hwang, Hong-Yup Ahn, Cheol-Young Park; Diabetes Metab J. 2016;40(4):318-325. Published online May 27, 2016; DOI: https://doi.org/10.4093/dmj.2016.40.4.318

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103 Download
43 Web of Science
46 Crossref

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Background

The original homeostasis model assessment (HOMA1) and the updated HOMA model (HOMA2) have been used to evaluate insulin resistance (IR) and β-cell function, but little is known about the usefulness of HOMA2 for the prediction of diabetes in Koreans. The aim of this study was to demonstrate the usefulness of HOMA2 as a predictor of type 2 diabetes mellitus in Koreans without diabetes.

Methods

The study population consisted of 104,694 Koreans enrolled at a health checkup program and followed up from 2001 to 2012. Participants were divided into a normal glucose tolerance (NGT) group and a pre-diabetes group according to fasting glucose and glycosylated hemoglobin levels. Anthropometric and laboratory data were measured at the baseline checkup, and HOMA values were calculated at the baseline and follow-up checkups. The hazard ratios (HRs) of the HOMA1 and HOMA2 values and the prevalence of diabetes at follow-up were evaluated using a multivariable Cox proportional hazards model and Kaplan-Meier analysis.

Results

After adjusting for several diabetes risk factors, all of the HOMA values except 1/HOMA1-β and 1/HOMA2-β in the NGT group were significant predictors of the progression to diabetes. In the NGT group, there was no significant difference in HOMA1-IR (HR, 1.09; 95% confidence interval [CI], 1.04 to 1.14) and HOMA2-IR (HR, 1.11; 95% CI, 1.04 to 1.19). However, in the pre-diabetes group, 1/HOMA2-β was a more powerful marker (HR, 1.29; 95% CI, 1.26 to 1.31) than HOMA1-IR (HR, 1.23; 95% CI, 1.19 to 1.28) or 1/HOMA1-β (HR, 1.14; 95% CI, 1.12 to 1.16). In the non-diabetic group (NGT+pre-diabetes), 1/HOMA2-β was also a stronger predictor of diabetes (HR, 1.27; 95% CI, 1.25 to 1.29) than HOMA1-IR (HR, 1.14; 95% CI, 1.12 to 1.15) or 1/HOMA1-β (HR, 1.13; 95% CI, 1.11 to 1.14).

Conclusion

HOMA2 is more predictive than HOMA1 for the progression to diabetes in pre-diabetes or non-diabetic Koreans.

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