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Shinje Moon  (Moon S) 3 Articles
Metabolic Risk/Epidemiology
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Effect of Sarcopenia and Body Shape on Cardiovascular Disease According to Obesity Phenotypes
Hyun-Woong Cho, Wankyo Chung, Shinje Moon, Ohk-Hyun Ryu, Min Kyung Kim, Jun Goo Kang
Diabetes Metab J. 2021;45(2):209-218.   Published online July 10, 2020
DOI: https://doi.org/10.4093/dmj.2019.0223
  • 8,943 View
  • 217 Download
  • 22 Web of Science
  • 20 Crossref
AbstractAbstract PDFSupplementary MaterialPubReader   ePub   
Background

This study aimed to assess the effects of sarcopenia and A Body Shape Index (ABSI) on cardiovascular disease (CVD) risk according to obesity phenotypes.

Methods

We used data from the National Health and Nutrition Examination Survey 1999 to 2012. A total of 25,270 adults were included and classified into the following groups: metabolically healthy normal weight (MHNW), metabolically healthy overweight/obese (MHO), metabolically unhealthy normal weight (MUNW), and metabolically unhealthy overweight/obese (MUO). Sarcopenia was defined as the appendicular skeletal mass index <7 kg/m2 in men and <5.5kg/m2 in women. A multivariate logistic regression analysis was performed to evaluate the odds ratio (OR) of sarcopenia and ABSI for CVD events according to the obesity phenotype.

Results

The MHNW participants with sarcopenia had higher risk for CVD than those without sarcopenia (OR, 2.69; 95% confidence interval [CI], 1.56 to 4.64). In the analysis with MHNW participants without sarcopenia as a reference, the participants with sarcopenia showed a higher OR for CVD than those without sarcopenia in both MHO (OR in participants without sarcopenia, 3.31; 95% CI, 1.94 to 5.64) (OR in participants with sarcopenia, 8.59; 95% CI, 2.63 to 28.04) and MUO participants (OR in participants without sarcopenia, 5.11; 95% CI, 3.21 to 8.15) (OR in participants with sarcopenia, 8.12; 95% CI, 4.04 to 16.32). Participants within the second and third tertiles of ABSI had higher ORs for CVDs than the counterpart of obesity phenotypes within the first tertile.

Conclusion

These results suggest that clinical approaches that consider muscle and body shape are required.

Citations

Citations to this article as recorded by  
  • Association of low muscle mass and obesity with increased all‐cause and cardiovascular disease mortality in US adults
    Donghyun Kim, Junghoon Lee, Raekil Park, Chang‐Myung Oh, Shinje Moon
    Journal of Cachexia, Sarcopenia and Muscle.2024; 15(1): 240.     CrossRef
  • Metabolic-associated fatty liver disease and sarcopenia: A double whammy
    Aditya Viswanath, Sherouk Fouda, Cornelius James Fernandez, Joseph M Pappachan
    World Journal of Hepatology.2024; 16(2): 152.     CrossRef
  • Association of Myosteatosis with Nonalcoholic Fatty Liver Disease, Severity, and Liver Fibrosis Using Visual Muscular Quality Map in Computed Tomography
    Hwi Seung Kim, Jiwoo Lee, Eun Hee Kim, Min Jung Lee, In Young Bae, Woo Je Lee, Joong-Yeol Park, Hong-Kyu Kim, Chang Hee Jung
    Diabetes & Metabolism Journal.2023; 47(1): 104.     CrossRef
  • Additive impact of diabetes and sarcopenia on all-cause and cardiovascular mortality: A longitudinal nationwide population-based study
    Eyun Song, Soon Young Hwang, Min Jeong Park, Ahreum Jang, Kyeong Jin Kim, Ji Hee Yu, Nam Hoon Kim, Hye Jin Yoo, Ji A. Seo, Sin Gon Kim, Nan Hee Kim, Sei Hyun Baik, Kyung Mook Choi
    Metabolism.2023; 148: 155678.     CrossRef
  • Association between a body shape index and abdominal aortic calcification in general population: A cross-sectional study
    Wei Li, Zhenwei Wang, Min Li, Jing Xie, Jing Gong, Naifeng Liu
    Frontiers in Cardiovascular Medicine.2023;[Epub]     CrossRef
  • Metabolic Impact of Frailty Changes Diabetes Trajectory
    Alan J. Sinclair, Ahmed H. Abdelhafiz
    Metabolites.2023; 13(2): 295.     CrossRef
  • Association between sarcopenic obesity and poor muscle quality based on muscle quality map and abdominal computed tomography
    Yun Kyung Cho, Han Na Jung, Eun Hee Kim, Min Jung Lee, Joong‐Yeol Park, Woo Je Lee, Hong‐Kyu Kim, Chang Hee Jung
    Obesity.2023; 31(6): 1547.     CrossRef
  • Metabolic Characteristics of Frail Older People with Diabetes Mellitus—A Systematic Search for Phenotypes
    Ahmed H. Abdelhafiz, Grace L. Keegan, Alan J. Sinclair
    Metabolites.2023; 13(6): 705.     CrossRef
  • Risk of Cardiovascular Diseases Among Different Metabolic Obesity Phenotypes: A Prospective Observational Study
    Xiaowei Liu, Chan Yang, Yuanyuan Dang, Zhenqi Chang, Juan Li, Yi Zhao, Yuhong Zhang
    Metabolic Syndrome and Related Disorders.2023; 21(6): 306.     CrossRef
  • Effect of Hypoxia Conditioning on Body Composition in Middle-Aged and Older Adults: A Systematic Review and Meta-Analysis
    Zhijian He, Lijun Qiang, Yusheng Liu, Wenfeng Gao, Tao Feng, Yang Li, Bing Yan, Olivier Girard
    Sports Medicine - Open.2023;[Epub]     CrossRef
  • Association Between a Body Shape Index and Subclinical Carotid Atherosclerosis in Population Free of Cardiovascular and Cerebrovascular Diseases
    Xiaotian Ma, Lihong Chen, Wenchao Hu, Lanjie He
    Journal of Atherosclerosis and Thrombosis.2022; 29(8): 1140.     CrossRef
  • Impact of Sarcopenia on the Severity of the Liver Damage in Patients With Non-alcoholic Fatty Liver Disease
    Vittoria Zambon Azevedo, Cristina Alina Silaghi, Thomas Maurel, Horatiu Silaghi, Vlad Ratziu, Raluca Pais
    Frontiers in Nutrition.2022;[Epub]     CrossRef
  • Identification of sarcopenic obesity in adults undergoing orthopaedic surgery: Relationship between “a body shape index” (ABSI) and fat-free mass. A cross -sectional study
    Ana Tomažič, Boštjan Žvanut, Lilijana Vouk Grbac, Mihaela Jurdana, Fatih Özden
    PLOS ONE.2022; 17(6): e0269956.     CrossRef
  • Associations of Dynapenic Obesity and Sarcopenic Obesity with the Risk of Complications in COVID-19
    Laura Pérez-Campos Mayoral, Carlos Alberto Matias-Cervantes, Eduardo Pérez-Campos, Carlos Romero Díaz, Luis Ángel Laguna Barrios, María del Socorro Pina Canseco, Margarito Martínez Cruz, Eduardo Pérez-Campos Mayoral, Carlos Josué Solórzano Mata, Francisco
    International Journal of Molecular Sciences.2022; 23(15): 8277.     CrossRef
  • Sex Differences in Adiposity and Cardiovascular Diseases
    Haoyun Li, Daniels Konja, Luyao Wang, Yu Wang
    International Journal of Molecular Sciences.2022; 23(16): 9338.     CrossRef
  • The Applicability of the ESPEN and EASO-Defined Diagnostic Criteria for Sarcopenic Obesity in Japanese Patients after Stroke: Prevalence and Association with Outcomes
    Yoshihiro Yoshimura, Hidetaka Wakabayashi, Fumihiko Nagano, Ayaka Matsumoto, Sayuri Shimazu, Ai Shiraishi, Yoshifumi Kido, Takahiro Bise
    Nutrients.2022; 14(19): 4205.     CrossRef
  • The value of combining the simple anthropometric obesity parameters, Body Mass Index (BMI) and a Body Shape Index (ABSI), to assess the risk of non-alcoholic fatty liver disease
    Maobin Kuang, Guotai Sheng, Chong Hu, Song Lu, Nan Peng, Yang Zou
    Lipids in Health and Disease.2022;[Epub]     CrossRef
  • Sarcopenia and cardiovascular disease in patients with and without kidney disease: what do we know?
    Ozkan Gungor, Mustafa Sevinc, Sena Ulu, Ismail Kocyigit
    International Urology and Nephrology.2022; 55(5): 1161.     CrossRef
  • Skeletal Muscle Should Not Be Overlooked
    Ji A Seo
    Diabetes & Metabolism Journal.2021; 45(2): 173.     CrossRef
  • The Role of Sarcopenic Obesity in Cancer and Cardiovascular Disease: A Synthesis of the Evidence on Pathophysiological Aspects and Clinical Implications
    Erika Aparecida Silveira, Rômulo Roosevelt da Silva Filho, Maria Claudia Bernardes Spexoto, Fahimeh Haghighatdoost, Nizal Sarrafzadegan, Cesar de Oliveira
    International Journal of Molecular Sciences.2021; 22(9): 4339.     CrossRef
Obesity and Metabolic Syndrome
The Association between Z-Score of Log-Transformed A Body Shape Index and Cardiovascular Disease in Korea
Wankyo Chung, Jung Hwan Park, Hye Soo Chung, Jae Myung Yu, Shinje Moon, Dong Sun Kim
Diabetes Metab J. 2019;43(5):675-682.   Published online April 26, 2019
DOI: https://doi.org/10.4093/dmj.2018.0169
  • 8,067 View
  • 59 Download
  • 3 Web of Science
  • 3 Crossref
AbstractAbstract PDFSupplementary MaterialPubReader   
Background

In order to overcome the limitations of body mass index (BMI) and waist circumference (WC), the z-score of the log-transformed A Body Shape Index (LBSIZ) has recently been introduced. In this study, we analyzed the relationship between the LBSIZ and cardiovascular disease (CVD) in a Korean representative sample.

Methods

Data were collected from the Korea National Health and Nutrition Examination VI to V. The association between CVD and obesity indices was analyzed using a receiver operating characteristic curve. The cut-off value for the LBSIZ was estimated using the Youden index, and the odds ratio (OR) for CVD was determined via multivariate logistic regression analysis. ORs according to the LBSIZ value were analyzed using restricted cubic spline regression plots.

Results

A total of 31,227 Korean healthy adults were analyzed. Area under the curve (AUC) of LBSIZ against CVD was 0.686 (95% confidence interval [CI], 0.671 to 0.702), which was significantly higher than the AUC of BMI (0.583; 95% CI, 0.567 to 0.599) or WC (0.646; 95% CI, 0.631 to 0.661) (P<0.001). Similar results were observed for stroke and coronary artery diseases. The cut-off value for the LBSIZ was 0.35 (sensitivity, 64.5%; specificity, 64%; OR, 1.29, 95% CI, 1.12 to 1.49). Under restricted cubic spline regression, LBSIZ demonstrated that OR started to increase past the median value.

Conclusion

The findings of this study suggest that the LBSIZ might be more strongly associated with CVD risks compared to BMI or WC. These outcomes would be helpful for CVD risk assessment in clinical settings, especially the cut-off value of the LBSIZ suggested in this study.

Citations

Citations to this article as recorded by  
  • Body Shape Index and Cardiovascular Risk in Individuals With Obesity
    Nazlı Hacıağaoğlu, Can Öner, Hüseyin Çetin, Engin Ersin Şimşek
    Cureus.2022;[Epub]     CrossRef
  • Association between body shape index and risk of mortality in the United States
    Heysoo Lee, Hye Soo Chung, Yoon Jung Kim, Min Kyu Choi, Yong Kyun Roh, Wankyo Chung, Jae Myung Yu, Chang-Myung Oh, Shinje Moon
    Scientific Reports.2022;[Epub]     CrossRef
  • Utility of the Z-score of log-transformed A Body Shape Index (LBSIZ) in the assessment for sarcopenic obesity and cardiovascular disease risk in the United States
    Wankyo Chung, Jung Hwan Park, Hye Soo Chung, Jae Myung Yu, Dong Sun Kim, Shinje Moon
    Scientific Reports.2019;[Epub]     CrossRef
Clinical Diabetes & Therapeutics
Association between Serum Selenium Level and the Presence of Diabetes Mellitus: A Meta-Analysis of Observational Studies
Juno Kim, Hye Soo Chung, Min-Kyu Choi, Yong Kyun Roh, Hyung Joon Yoo, Jung Hwan Park, Dong Sun Kim, Jae Myung Yu, Shinje Moon
Diabetes Metab J. 2019;43(4):447-460.   Published online January 2, 2019
DOI: https://doi.org/10.4093/dmj.2018.0123
  • 6,699 View
  • 103 Download
  • 35 Web of Science
  • 35 Crossref
AbstractAbstract PDFSupplementary MaterialPubReader   
Background

Epidemiological studies have suggested an association between selenium (Se) and diabetes mellitus (DM). However, different studies have reported conflicting results. Therefore, we performed a comprehensive meta-analysis to clarify the impact of Se on DM.

Methods

We searched the PubMed database for studies on the association between Se and DM from inception to June 2018.

Results

Twenty articles evaluating 47,930 participants were included in the analysis. The meta-analysis found that high levels of Se were significantly associated with the presence of DM (pooled odds ratios [ORs], 1.88; 95% confidence interval [CI], 1.44 to 2.45). However, significant heterogeneity was found (I2=82%). Subgroup analyses were performed based on the Se measurement methods used in each study. A significant association was found between high Se levels and the presence of DM in the studies that used blood (OR, 2.17; 95% CI, 1.60 to 2.93; I2=77%), diet (OR, 1.61; 95% CI, 1.10 to 2.36; I2=0%), and urine (OR, 1.49; 95% CI, 1.02 to 2.17; I2=0%) as samples to estimate Se levels, but not in studies on nails (OR, 1.24; 95% CI, 0.52 to 2.98; I2=91%). Because of significant heterogeneity in the studies with blood, we conducted a sensitivity analysis and tested the publication bias. The results were consistent after adjustment based on the sensitivity analysis as well as the trim and fill analysis for publication bias.

Conclusion

This meta-analysis demonstrates that high levels of Se are associated with the presence of DM. Further prospective and randomized controlled trials are warranted to elucidate the link better.

Citations

Citations to this article as recorded by  
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    Krystyna Pyrzynska, Aleksandra Sentkowska
    Biological Trace Element Research.2024; 202(7): 2993.     CrossRef
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