Skip Navigation
Skip to contents

Diabetes Metab J : Diabetes & Metabolism Journal

Search
OPEN ACCESS

Previous issues

Page Path
HOME > Browse > Previous issues
12 Previous issues
Filter
Filter
Article category
Keywords
Authors
Funded articles
Volume 42(5); October 2018
Prev issue Next issue
Reviews
Clinical Diabetes & Therapeutics
Diabetes and Subclinical Coronary Atherosclerosis
Chang Hoon Lee, Seung-Whan Lee, Seong-Wook Park
Diabetes Metab J. 2018;42(5):355-363.   Published online October 22, 2018
DOI: https://doi.org/10.4093/dmj.2018.0041
  • 4,722 View
  • 58 Download
  • 13 Web of Science
  • 11 Crossref
AbstractAbstract PDFPubReader   

It is well known that diabetic patients have a high risk of cardiovascular events, and although there has been a tremendous effort to reduce these cardiovascular risks, the incidence of cardiovascular morbidity and mortality in diabetic patients remains high. Therefore, the early detection of coronary artery disease (CAD) is necessary in those diabetic patients who are at risk of cardiovascular events. Significant medical and radiological advancements, including coronary computed tomography angiography (CCTA), mean that it is now possible to investigate the characteristics of plaques, instead of solely evaluating the calcium level of the coronary artery. Recently, several studies reported that the prevalence of subclinical coronary atherosclerosis (SCA) is higher than expected, and this could impact on CAD progression in asymptomatic diabetic patients. In addition, several reports suggest the potential benefit of using CCTA for screening for SCA in asymptomatic diabetic patients, which might dramatically decrease the incidence of cardiovascular events. For these reasons, the medical interest in SCA in diabetic patients is increasing. In this article, we sought to review the results of studies on CAD in asymptomatic diabetic patients and discuss the clinical significance and possibility of using CCTA to screen for SCA.

Citations

Citations to this article as recorded by  
  • Coronary Artery Calcium Score directed risk stratification of patients with Type-2 diabetes mellitus
    Mahmoud Nassar, Nso Nso, Kelechi Emmanuel, Mohsen Alshamam, Most Sirajum Munira, Anoop Misra
    Diabetes & Metabolic Syndrome: Clinical Research & Reviews.2022; 16(6): 102503.     CrossRef
  • Association between carotid atherosclerosis and presence of intracranial atherosclerosis using three-dimensional high-resolution vessel wall magnetic resonance imaging in asymptomatic patients with type 2 diabetes
    Ji Eun Jun, You-Cheol Hwang, Kyu Jeong Ahn, Ho Yeon Chung, Geon-Ho Jahng, Soonchan Park, In-Kyung Jeong, Chang-Woo Ryu
    Diabetes Research and Clinical Practice.2022; 191: 110067.     CrossRef
  • Serum metabolic signatures of subclinical atherosclerosis in patients with type 2 diabetes mellitus: a preliminary study
    Jiaorong Su, Qing Zhao, Aihua Zhao, Wei Jia, Wei Zhu, Jingyi Lu, Xiaojing Ma
    Acta Diabetologica.2021; 58(9): 1217.     CrossRef
  • Atherogenic Index of Plasma, Triglyceride-Glucose Index and Monocyte-to-Lymphocyte Ratio for Predicting Subclinical Coronary Artery Disease
    Yueqiao Si, Wenjun Fan, Chao Han, Jingyi Liu, Lixian Sun
    The American Journal of the Medical Sciences.2021; 362(3): 285.     CrossRef
  • Cardiologist's approach to the diabetic patient: No further delay for a paradigm shift
    Francesco Maranta, Lorenzo Cianfanelli, Carlo Gaspardone, Vincenzo Rizza, Rocco Grippo, Marco Ambrosetti, Domenico Cianflone
    International Journal of Cardiology.2021; 338: 248.     CrossRef
  • Co‐expression of glycosylated aquaporin‐1 and transcription factor NFAT5 contributes to aortic stiffness in diabetic and atherosclerosis‐prone mice
    Rosalinda Madonna, Vanessa Doria, Anikó Görbe, Nino Cocco, Péter Ferdinandy, Yong‐Jian Geng, Sante Donato Pierdomenico, Raffaele De Caterina
    Journal of Cellular and Molecular Medicine.2020; 24(5): 2857.     CrossRef
  • Recent Updates on Vascular Complications in Patients with Type 2 Diabetes Mellitus
    Chan-Hee Jung, Ji-Oh Mok
    Endocrinology and Metabolism.2020; 35(2): 260.     CrossRef
  • Quantitative measure of asymptomatic cardiovascular disease risk in Type 2 diabetes: Evidence from Indian outpatient setting
    Samit Ghosal, Binayak Sinha, Jignesh Ved, Mansij Biswas
    Indian Heart Journal.2020; 72(2): 119.     CrossRef
  • Role of pregnancy hormones and hormonal interaction on the maternal cardiovascular system: a literature review
    Vitaris Kodogo, Feriel Azibani, Karen Sliwa
    Clinical Research in Cardiology.2019; 108(8): 831.     CrossRef
  • Letter: Comparison of the Efficacy of Rosuvastatin Monotherapy 20 mg with Rosuvastatin 5 mg and Ezetimibe 10 mg Combination Therapy on Lipid Parameters in Patients with Type 2 Diabetes Mellitus (Diabetes Metab J2019;43:582–9)
    Tae Seo Sohn
    Diabetes & Metabolism Journal.2019; 43(6): 909.     CrossRef
  • Effects of Diabetes on Motor Recovery After Cerebral Infarct: A Diffusion Tensor Imaging Study
    Jun Sung Moon, Seung Min Chung, Sung Ho Jang, Kyu Chang Won, Min Cheol Chang
    The Journal of Clinical Endocrinology & Metabolism.2019; 104(9): 3851.     CrossRef
Complications
Pathophysiology of Diabetic Retinopathy: The Old and the New
Sentaro Kusuhara, Yoko Fukushima, Shuntaro Ogura, Naomi Inoue, Akiyoshi Uemura
Diabetes Metab J. 2018;42(5):364-376.   Published online October 22, 2018
DOI: https://doi.org/10.4093/dmj.2018.0182
  • 13,564 View
  • 472 Download
  • 114 Web of Science
  • 108 Crossref
AbstractAbstract PDFPubReader   

Vision loss in diabetic retinopathy (DR) is ascribed primarily to retinal vascular abnormalities—including hyperpermeability, hypoperfusion, and neoangiogenesis—that eventually lead to anatomical and functional alterations in retinal neurons and glial cells. Recent advances in retinal imaging systems using optical coherence tomography technologies and pharmacological treatments using anti-vascular endothelial growth factor drugs and corticosteroids have revolutionized the clinical management of DR. However, the cellular and molecular mechanisms underlying the pathophysiology of DR are not fully determined, largely because hyperglycemic animal models only reproduce limited aspects of subclinical and early DR. Conversely, non-diabetic mouse models that represent the hallmark vascular disorders in DR, such as pericyte deficiency and retinal ischemia, have provided clues toward an understanding of the sequential events that are responsible for vision-impairing conditions. In this review, we summarize the clinical manifestations and treatment modalities of DR, discuss current and emerging concepts with regard to the pathophysiology of DR, and introduce perspectives on the development of new drugs, emphasizing the breakdown of the blood-retina barrier and retinal neovascularization.

Citations

Citations to this article as recorded by  
  • Recent Insights into the Etiopathogenesis of Diabetic Retinopathy and Its Management
    Arpon Biswas, Abhijit Deb Choudhury, Sristi Agrawal, Amol Chhatrapati Bisen, Sachin Nashik Sanap, Sarvesh Kumar Verma, Mukesh Kumar, Anjali Mishra, Shivansh Kumar, Mridula Chauhan, Rabi Sankar Bhatta
    Journal of Ocular Pharmacology and Therapeutics.2024; 40(1): 13.     CrossRef
  • GMFB/AKT/TGF‐β3 in Müller cells mediated early retinal degeneration in a streptozotocin‐induced rat diabetes model
    Tong Zhu, Yingao Li, Lilin Zhu, Jinyuan Xu, Zijun Feng, Hao Chen, Si Shi, Caiying Liu, Qingjian Ou, Furong Gao, Jieping Zhang, Caixia Jin, Jingying Xu, Jiao Li, Jingfa Zhang, Yanlong Bi, Guo‐tong Xu, Juan Wang, Haibin Tian, Lixia Lu
    Glia.2024; 72(3): 504.     CrossRef
  • The significance of glutaredoxins for diabetes mellitus and its complications
    Mengmeng Zhou, Eva-Maria Hanschmann, Axel Römer, Thomas Linn, Sebastian Friedrich Petry
    Redox Biology.2024; 71: 103043.     CrossRef
  • Proteomic analysis of diabetic retinopathy identifies potential plasma-protein biomarkers for diagnosis and prognosis
    Bent Honoré, Javad Nouri Hajari, Tobias Torp Pedersen, Tomas Ilginis, Hajer Ahmad Al-Abaiji, Claes Sepstrup Lønkvist, Jon Peiter Saunte, Dorte Aalund Olsen, Ivan Brandslund, Henrik Vorum, Carina Slidsborg
    Clinical Chemistry and Laboratory Medicine (CCLM).2024;[Epub]     CrossRef
  • Next generation therapeutics for retinal neurodegenerative diseases
    Matthew B. Appell, Jahnavi Pejavar, Ashwin Pasupathy, Sri Vishnu Kiran Rompicharla, Saed Abbasi, Kiersten Malmberg, Patricia Kolodziejski, Laura M. Ensign
    Journal of Controlled Release.2024; 367: 708.     CrossRef
  • Modeling early pathophysiological phenotypes of diabetic retinopathy in a human inner blood-retinal barrier-on-a-chip
    Thomas L. Maurissen, Alena J. Spielmann, Gabriella Schellenberg, Marc Bickle, Jose Ricardo Vieira, Si Ying Lai, Georgios Pavlou, Sascha Fauser, Peter D. Westenskow, Roger D. Kamm, Héloïse Ragelle
    Nature Communications.2024;[Epub]     CrossRef
  • Emerging role of ferroptosis in diabetic retinopathy: a review
    Ruohong Wang, Suyun Rao, Zheng Zhong, Ke Xiao, Xuhui Chen, Xufang Sun
    Journal of Drug Targeting.2024; 32(4): 393.     CrossRef
  • Serum vitamin D is substantially reduced and predicts flares in diabetic retinopathy patients
    Yong Zhuang, Zihao Zhuang, Qingyan Cai, Xin Hu, Huibin Huang
    Journal of Diabetes Investigation.2024;[Epub]     CrossRef
  • Ocular pharmacological and biochemical profiles of 6-thioguanine: a drug repurposing study
    Maria Consiglia Trotta, Carlo Gesualdo, Caterina Claudia Lepre, Marina Russo, Franca Ferraraccio, Iacopo Panarese, Ernesto Marano, Paolo Grieco, Francesco Petrillo, Anca Hermenean, Francesca Simonelli, Michele D’Amico, Claudio Bucolo, Francesca Lazzara, F
    Frontiers in Pharmacology.2024;[Epub]     CrossRef
  • Pharmacological mechanism and clinical study of Qiming granules in treating diabetic retinopathy based on network pharmacology and literature review
    Yuxia Huang, Jia Wang, Yu Wang, Wei Kuang, Mengjun Xie, Mei Zhang
    Journal of Ethnopharmacology.2023; 302: 115861.     CrossRef
  • Vitreous humor proteome: unraveling the molecular mechanisms underlying proliferative and neovascular vitreoretinal diseases
    Fátima Milhano dos Santos, Sergio Ciordia, Joana Mesquita, João Paulo Castro de Sousa, Alberto Paradela, Cândida Teixeira Tomaz, Luís António Paulino Passarinha
    Cellular and Molecular Life Sciences.2023;[Epub]     CrossRef
  • Protective Effects of Human Pericyte-like Adipose-Derived Mesenchymal Stem Cells on Human Retinal Endothelial Cells in an In Vitro Model of Diabetic Retinopathy: Evidence for Autologous Cell Therapy
    Gabriella Lupo, Aleksandra Agafonova, Alessia Cosentino, Giovanni Giurdanella, Giuliana Mannino, Debora Lo Furno, Ivana Roberta Romano, Rosario Giuffrida, Floriana D’Angeli, Carmelina Daniela Anfuso
    International Journal of Molecular Sciences.2023; 24(2): 913.     CrossRef
  • Predictive factors for microvascular recovery after treatments for diabetic retinopathy
    Junyeop Lee, Yoon-Jeon Kim, Joo-Yong Lee, Young Hee Yoon, June-Gone Kim
    BMC Ophthalmology.2023;[Epub]     CrossRef
  • Pathophysiology and diagnosis of diabetic retinopathy: a narrative review
    Mohadese Estaji, Bita Hosseini, Saeed Bozorg-Qomi, Babak Ebrahimi
    Journal of Investigative Medicine.2023; 71(3): 265.     CrossRef
  • Proteomics profiling of vitreous humor reveals complement and coagulation components, adhesion factors, and neurodegeneration markers as discriminatory biomarkers of vitreoretinal eye diseases
    Fátima M. Santos, Sergio Ciordia, Joana Mesquita, Carla Cruz, João Paulo Castro e Sousa, Luís A. Passarinha, Cândida T. Tomaz, Alberto Paradela
    Frontiers in Immunology.2023;[Epub]     CrossRef
  • Hypoxia-induced transcriptional differences in African and Asian versus European diabetic cybrids
    Andrew H. Dolinko, Marilyn Chwa, Kevin Schneider, Mithalesh K. Singh, Shari Atilano, Jie Wu, M. Cristina Kenney
    Scientific Reports.2023;[Epub]     CrossRef
  • Downregulation of plasma microRNA-29c-3p expression may be a new risk factor for diabetic retinopathy
    Bora TORUS, Hakan KORKMAZ, Kuyaş H. OZTURK, Fevziye B. ŞİRİN, Mehmet ARGUN, Sonmez ŞEVİK, Levent TÖK
    Minerva Endocrinology.2023;[Epub]     CrossRef
  • Short-Term Outcomes of Intravitreal Faricimab Injection for Diabetic Macular Edema
    Sentaro Kusuhara, Maya Kishimoto-Kishi, Wataru Matsumiya, Akiko Miki, Hisanori Imai, Makoto Nakamura
    Medicina.2023; 59(4): 665.     CrossRef
  • L-type calcium channel blocker increases VEGF concentrations in retinal cells and human serum
    Anmol Kumar, Stefan Mutter, Erika B. Parente, Valma Harjutsalo, Raija Lithovius, Sinnakaruppan Mathavan, Markku Lehto, Timo P. Hiltunen, Kimmo K. Kontula, Per-Henrik Groop, Satyajit Mohapatra
    PLOS ONE.2023; 18(4): e0284364.     CrossRef
  • Efficacy and safety of curcumin in diabetic retinopathy: A protocol for systematic review and meta-analysis
    Liyuan Wang, Jiayu Xu, Tianyang Yu, Hanli Wang, Xiaojun Cai, He Sun, Godwin Ovenseri-Ogbomo
    PLOS ONE.2023; 18(4): e0282866.     CrossRef
  • Highly water-soluble diacetyl chrysin ameliorates diabetes-associated renal fibrosis and retinal microvascular abnormality in db/db mice
    Young-Hee Kang, Sin-Hye Park, Young Eun Sim, Moon-Sik Oh, Hong Won Suh, Jae-Yong Lee, Soon Sung Lim
    Nutrition Research and Practice.2023; 17(3): 421.     CrossRef
  • Preventive and management approach of triptonide, a diterpenoid compound against streptozotocin-induced diabetic retinopathy in Wistar rat model
    Chandramohan Govindasamy, Khalid S. Al-Numair, Jun Li, Weibai Chen, Guoqiang Wu
    Arabian Journal of Chemistry.2023; 16(9): 105034.     CrossRef
  • New Insights on Dietary Polyphenols for the Management of Oxidative Stress and Neuroinflammation in Diabetic Retinopathy
    Gustavo Bernardes Fanaro, Marcelo Rodrigues Marques, Karin da Costa Calaza, Rafael Brito, André Moreira Pessoni, Henrique Rocha Mendonça, Deborah Emanuelle de Albuquerque Lemos, José Luiz de Brito Alves, Evandro Leite de Souza, Marinaldo Pacífico Cavalcan
    Antioxidants.2023; 12(6): 1237.     CrossRef
  • Evaluation of Social Platform-Based Continuity of Care in Improving Cognitive and Prognostic Effects of Young Patients with Diabetic Retinopathy
    Guo-lan Cao, Ke-jian Chen
    Diabetes, Metabolic Syndrome and Obesity.2023; Volume 16: 1931.     CrossRef
  • Role of vascular endothelial growth factor B in nonalcoholic fatty liver disease and its potential value
    Yu-Qi Li, Lei Xin, Yu-Chi Zhao, Shang-Qi Li, Ya-Nuo Li
    World Journal of Hepatology.2023; 15(6): 786.     CrossRef
  • The rs1800469 T/T and rs1800470 C/C genotypes of the TGFB1 gene confer protection against diabetic retinopathy in a Southern Brazilian population
    Aline Rodrigues Costa, Cristine Dieter, Luís Henrique Canani, Taís Silveira Assmann, Daisy Crispim
    Genetics and Molecular Biology.2023;[Epub]     CrossRef
  • Evaluation of Self-Care in Patients with Diabetic Retinopathy
    Songül BİLTEKİN, Züleyha KILIÇ, Şefika Dilek GÜVEN
    Turkish Journal of Diabetes and Obesity.2023; 7(3): 214.     CrossRef
  • Diabetes mellitus and its influence on the incidence and process of diabetic retinopathy
    Janka Poráčová, Melinda Nagy, Marta Mydlárová Blaščáková, Mária Konečná, Vincent Sedlák, Mária Zahatňanská, Tatiana Kimáková, Hedviga Vašková, Viktória Rybárová, Mária Majherová, Ivan Uher
    Central European Journal of Public Health.2023; 31(Suppl 1): S4.     CrossRef
  • Dysregulation of the NLRP3 Inflammasome in Diabetic Retinopathy and Potential Therapeutic Targets
    Karanvir S. Raman, Joanne A. Matsubara
    Ocular Immunology and Inflammation.2022; 30(2): 470.     CrossRef
  • Adult-induced genetic ablation distinguishes PDGFB roles in blood-brain barrier maintenance and development
    Elisa Vazquez-Liebanas, Khayrun Nahar, Giacomo Bertuzzi, Annika Keller, Christer Betsholtz, Maarja Andaloussi Mäe
    Journal of Cerebral Blood Flow & Metabolism.2022; 42(2): 264.     CrossRef
  • Investigation on the Q-markers of Bushen Huoxue Prescriptions for DR treatment based on chemometric methods and spectrum-effect relationship
    Yueting Yu, Ziyu Zhu, Mengjun Xie, Liping Deng, Xuejun Xie, Mei Zhang
    Journal of Ethnopharmacology.2022; 285: 114800.     CrossRef
  • Corneal Confocal Microscopy in Type 1 Diabetes Mellitus: A Six-Year Longitudinal Study
    Stuti L. Misra, James A. Slater, Charles N. J. McGhee, Monika Pradhan, Geoffrey D. Braatvedt
    Translational Vision Science & Technology.2022; 11(1): 17.     CrossRef
  • Microphysiological Neurovascular Barriers to Model the Inner Retinal Microvasculature
    Thomas L. Maurissen, Georgios Pavlou, Colette Bichsel, Roberto Villaseñor, Roger D. Kamm, Héloïse Ragelle
    Journal of Personalized Medicine.2022; 12(2): 148.     CrossRef
  • Long-Term Oral Administration of Salidroside Alleviates Diabetic Retinopathy in db/db Mice
    Fei Yao, Xinyi Jiang, Ling Qiu, Zixuan Peng, Wei Zheng, Lexi Ding, Xiaobo Xia
    Frontiers in Endocrinology.2022;[Epub]     CrossRef
  • Classification of macular abnormalities using a lightweight CNN-SVM framework
    Xuqian Wang, Yu Gu
    Measurement Science and Technology.2022; 33(6): 065702.     CrossRef
  • Chorioretinal Hypoxia Detection Using Lipid-Polymer Hybrid Organic Room-Temperature Phosphorescent Nanoparticles
    Yingying Zeng, Van Phuc Nguyen, Yanxiu Li, Do Hyun Kang, Yannis M. Paulus, Jinsang Kim
    ACS Applied Materials & Interfaces.2022; 14(16): 18182.     CrossRef
  • LncRNA FLG-AS1 Mitigates Diabetic Retinopathy by Regulating Retinal Epithelial Cell Inflammation, Oxidative Stress, and Apoptosis via miR-380-3p/SOCS6 Axis
    Rong Luo, Lan Li, Fan Xiao, Jinsong Fu
    Inflammation.2022; 45(5): 1936.     CrossRef
  • Correlation between the progression of diabetic retinopathy and inflammasome biomarkers in vitreous and serum – a systematic review
    Charisse Y. J. Kuo, Rinki Murphy, Ilva D. Rupenthal, Odunayo O. Mugisho
    BMC Ophthalmology.2022;[Epub]     CrossRef
  • The relationship between the neutrophil-to-lymphocyte ratio and diabetic retinopathy in adults from the United States: results from the National Health and nutrition examination survey
    Xiaojie He, Shanshan Qi, Xi Zhang, Jiandong Pan
    BMC Ophthalmology.2022;[Epub]     CrossRef
  • Th22 cells induce Müller cell activation via the Act1/TRAF6 pathway in diabetic retinopathy
    Yufei Wang, Hongdan Yu, Jing Li, Wenqiang Liu, Shengxue Yu, Pan Lv, Lipan Zhao, Xiaobai Wang, Zhongfu Zuo, Xuezheng Liu
    Cell and Tissue Research.2022; 390(3): 367.     CrossRef
  • Prevalence and Factors Associated with Diabetic Retinopathy among Adult Diabetes Patients in Southeast Ethiopia: A Hospital-Based Cross-Sectional Study
    Biniyam Sahiledengle, Tesfaye Assefa, Wogene Negash, Anwar Tahir, Tadele Regasa, Yohannes Tekalegn, Ayele Mamo, Zinash Teferu, Damtew Solomon, Habtamu Gezahegn, Kebebe Bekele, Demisu Zenbaba, Alelign Tasew, Fikreab Desta, Zegeye Regassa, Zegeye Feleke, Ch
    Clinical Ophthalmology.2022; Volume 16: 3527.     CrossRef
  • Diabetic Retinopathy: Are lncRNAs New Molecular Players and Targets?
    Simona Cataldi, Mariagiovanna Tramontano, Valerio Costa, Marianna Aprile, Alfredo Ciccodicola
    Antioxidants.2022; 11(10): 2021.     CrossRef
  • Diosgenin protects retinal pigment epithelial cells from inflammatory damage and oxidative stress induced by high glucose by activating AMPK/Nrf2/HO‐1 pathway
    Yang Hao, Xuefeng Gao
    Immunity, Inflammation and Disease.2022;[Epub]     CrossRef
  • Selective Activation of the Wnt-Signaling Pathway as a Novel Therapy for the Treatment of Diabetic Retinopathy and Other Retinal Vascular Diseases
    Huy Nguyen, Sung-Jin Lee, Yang Li
    Pharmaceutics.2022; 14(11): 2476.     CrossRef
  • Development and validation of a predictive risk model based on retinal geometry for an early assessment of diabetic retinopathy
    Minglan Wang, Xiyuan Zhou, Dan Ning Liu, Jieru Chen, Zheng Zheng, Saiguang Ling
    Frontiers in Endocrinology.2022;[Epub]     CrossRef
  • Characterization of NLRP3 Inflammasome Activation in the Onset of Diabetic Retinopathy
    Charisse Y-J. Kuo, Jack J. Maran, Emma G. Jamieson, Ilva D. Rupenthal, Rinki Murphy, Odunayo O. Mugisho
    International Journal of Molecular Sciences.2022; 23(22): 14471.     CrossRef
  • VEGF Gene Polymorphism Among Diabetes Mellitus and Diabetic Retinopathy
    Samra Anees, Saima Shareef, Muhammad Roman, Shah Jahan
    Futuristic Biotechnology.2022; : 02.     CrossRef
  • Th22 Cells Induce Müller Cells Activation Via the Act1/Traf6 Pathway in Diabetic Retinopathy
    YuFei Wang, Hongdan Yu, Jing Li, Wenqiang Liu, Shengxue Yu, Pan Lv, Lipan Zhao, Xiaobai Wang, Zhongfu Zuo, Xuezheng Liu
    SSRN Electronic Journal .2022;[Epub]     CrossRef
  • Pathogenesis of diabetic macular edema: the role of pro-inflammatory and vascular factors. Aliterature review
    M.L. Kyryliuk, S.A. Suk
    INTERNATIONAL JOURNAL OF ENDOCRINOLOGY (Ukraine).2022; 18(3): 180.     CrossRef
  • Effects of emixustat hydrochloride in patients with proliferative diabetic retinopathy: a randomized, placebo-controlled phase 2 study
    Ryo Kubota, Chirag Jhaveri, John M. Koester, Jeffrey K. Gregory
    Graefe's Archive for Clinical and Experimental Ophthalmology.2021; 259(2): 369.     CrossRef
  • Transient receptor potential vanilloid 4 channel deletion regulates pathological but not developmental retinal angiogenesis
    Holly C. Cappelli, Brianna D. Guarino, Anantha K. Kanugula, Ravi K. Adapala, Vidushani Perera, Matthew A. Smith, Sailaja Paruchuri, Charles K. Thodeti
    Journal of Cellular Physiology.2021; 236(5): 3770.     CrossRef
  • Involvement of miR‐126 rs4636297 and miR‐146a rs2910164 polymorphisms in the susceptibility for diabetic retinopathy: a case–control study in a type 1 diabetes population
    Eloísa Toscan Massignam, Cristine Dieter, Felipe Mateus Pellenz, Taís Silveira Assmann, Daisy Crispim
    Acta Ophthalmologica.2021;[Epub]     CrossRef
  • Retinal Vascular Endothelial Cell Dysfunction and Neuroretinal Degeneration in Diabetic Patients
    Malgorzata Mrugacz, Anna Bryl, Katarzyna Zorena
    Journal of Clinical Medicine.2021; 10(3): 458.     CrossRef
  • Factors based on optical coherence tomography correlated with vision impairment in diabetic patients
    Hiroaki Endo, Satoru Kase, Hikari Tanaka, Mitsuo Takahashi, Satoshi Katsuta, Yasuo Suzuki, Minako Fujii, Susumu Ishida, Manabu Kase
    Scientific Reports.2021;[Epub]     CrossRef
  • Class-3 semaphorins: Potent multifunctional modulators for angiogenesis-associated diseases
    Bo Jiao, Shiyang Liu, Xi Tan, Pei Lu, Danning Wang, Hui Xu
    Biomedicine & Pharmacotherapy.2021; 137: 111329.     CrossRef
  • Single-Cell Analysis of Blood-Brain Barrier Response to Pericyte Loss
    Maarja A. Mäe, Liqun He, Sofia Nordling, Elisa Vazquez-Liebanas, Khayrun Nahar, Bongnam Jung, Xidan Li, Bryan C. Tan, Juat Chin Foo, Amaury Cazenave-Gassiot, Markus R. Wenk, Yvette Zarb, Barbara Lavina, Susan E. Quaggin, Marie Jeansson, Chengua Gu, David
    Circulation Research.2021;[Epub]     CrossRef
  • VEGFR1 signaling in retinal angiogenesis and microinflammation
    Akiyoshi Uemura, Marcus Fruttiger, Patricia A. D'Amore, Sandro De Falco, Antonia M. Joussen, Florian Sennlaub, Lynne R. Brunck, Kristian T. Johnson, George N. Lambrou, Kay D. Rittenhouse, Thomas Langmann
    Progress in Retinal and Eye Research.2021; 84: 100954.     CrossRef
  • Changes in Gene Expression Profiling and Phenotype in Aged Multidrug Resistance Protein 4-Deficient Mouse Retinas
    Kyung Woo Kim, Sentaro Kusuhara, Atsuko Katsuyama-Yoshikawa, Sho Nobuyoshi, Megumi Kitamura, Sotaro Mori, Noriyuki Sotani, Kaori Ueda, Wataru Matsumiya, Akiko Miki, Takuji Kurimoto, Hisanori Imai, Makoto Nakamura
    Antioxidants.2021; 10(3): 455.     CrossRef
  • Circular RNAs: Novel target of diabetic retinopathy
    Huan-ran Zhou, Hong-yu Kuang
    Reviews in Endocrine and Metabolic Disorders.2021; 22(2): 205.     CrossRef
  • MicroRNA-431-5p encapsulated in serum extracellular vesicles as a biomarker for proliferative diabetic retinopathy
    Bo Yu, Mengran Xiao, Fuhua Yang, Jing Xiao, Hui Zhang, Lin Su, Xiaomin Zhang, Xiaorong Li
    The International Journal of Biochemistry & Cell Biology.2021; 135: 105975.     CrossRef
  • EndMT Regulation by Small RNAs in Diabetes-Associated Fibrotic Conditions: Potential Link With Oxidative Stress
    Roberta Giordo, Yusra M. A. Ahmed, Hilda Allam, Salah Abusnana, Lucia Pappalardo, Gheyath K. Nasrallah, Arduino Aleksander Mangoni, Gianfranco Pintus
    Frontiers in Cell and Developmental Biology.2021;[Epub]     CrossRef
  • Pharmacokinetics of genistein distribution in blood and retinas of diabetic and non-diabetic rats
    T. Hakami, M.I. Mahmoud, E. de Juan, M. Cooney
    Drug Metabolism and Pharmacokinetics.2021; 39: 100404.     CrossRef
  • Nimbolide ameliorates the streptozotocin-induced diabetic retinopathy in rats through the inhibition of TLR4/NF-κB signaling pathway
    Xiangwen Shu, Yali Hu, Chao Huang, Ning Wei
    Saudi Journal of Biological Sciences.2021; 28(8): 4255.     CrossRef
  • Basic regulatory effects and clinical value of metalloproteinase-14 and extracellular matrix metalloproteinase inducer in diabetic retinopathy
    Shuyan Li, Shiheng Lu, Lei Zhang, Shasha Liu, Lei Wang, Kai Lin, Jialun Du, Meixia Song
    Materials Express.2021; 11(6): 873.     CrossRef
  • Reduced Acrolein Detoxification in akr1a1a Zebrafish Mutants Causes Impaired Insulin Receptor Signaling and Microvascular Alterations
    Haozhe Qi, Felix Schmöhl, Xiaogang Li, Xin Qian, Christoph T. Tabler, Katrin Bennewitz, Carsten Sticht, Jakob Morgenstern, Thomas Fleming, Nadine Volk, Ingrid Hausser, Elena Heidenreich, Rüdiger Hell, Peter Paul Nawroth, Jens Kroll
    Advanced Science.2021;[Epub]     CrossRef
  • The Metaflammatory and Immunometabolic Role of Macrophages and Microglia in Diabetic Retinopathy
    Honglian Wu, Mengqi Wang, Xiaorong Li, Yan Shao
    Human Cell.2021; 34(6): 1617.     CrossRef
  • Inflammatory resolution and vascular barrier restoration after retinal ischemia reperfusion injury
    Steven F. Abcouwer, Sumathi Shanmugam, Arivalagan Muthusamy, Cheng-mao Lin, Dejuan Kong, Heather Hager, Xuwen Liu, David A. Antonetti
    Journal of Neuroinflammation.2021;[Epub]     CrossRef
  • Diferenças de mensuração de acuidade visual e velocidade de leitura para perto entre pacientes com retinopatia diabética. Repercussão entre conceitos de deficiência visual parcial e cegueira legal
    Roberta Freitas Momenté, Isabella Couto Amaral, Luiz Guilherme Coimbra de Brito, João Gabriel Volpato Ferraresi, Maria Luisa Gois da Fonsêca, Nadyr Antônia Damasceno, Luiz Claudio Santos de Souza Lima, Mauricio Bastos Pereira, Eduardo de França Damasceno
    Revista Brasileira de Oftalmologia.2021;[Epub]     CrossRef
  • Maintaining blood retinal barrier homeostasis to attenuate retinal ischemia-reperfusion injury by targeting the KEAP1/NRF2/ARE pathway with lycopene
    Hao Huang, Xielan Kuang, Xiaobo Zhu, Hao Cheng, Yuxiu Zou, Han Du, Han Tang, Linbin Zhou, Jingshu Zeng, Huijun Liu, Jianhua Yan, Chongde Long, Huangxuan Shen
    Cellular Signalling.2021; 88: 110153.     CrossRef
  • Luteolin, an aryl hydrocarbon receptor antagonist, alleviates diabetic retinopathy by regulating the NLRP/NOX4 signalling pathway: Experimental and molecular docking study
    Y. Yang, M. Zhou, H. Liu
    Physiology International.2021; 108(2): 172.     CrossRef
  • ALDH2/SIRT1 Contributes to Type 1 and Type 2 Diabetes-Induced Retinopathy through Depressing Oxidative Stress
    Mengshan He, Pan Long, Tao Chen, Kaifeng Li, Dongyu Wei, Yufei Zhang, Wenjun Wang, Yonghe Hu, Yi Ding, Aidong Wen, Daniela Ribeiro
    Oxidative Medicine and Cellular Longevity.2021; 2021: 1.     CrossRef
  • Looking Ahead: Visual and Anatomical Endpoints in Future Trials of Diabetic Macular Ischemia
    Chui Ming Gemmy Cheung, Elizabeth Pearce, Beau Fenner, Piyali Sen, Victor Chong, Sobha Sivaprasad
    Ophthalmologica.2021; 244(5): 451.     CrossRef
  • The effect of psychotherapy on anxiety, depression, and quality of life in patients with diabetic retinopathy
    Suiping Li, Hong Liu, Xian Zhu
    Medicine.2021; 100(51): e28386.     CrossRef
  • Changes in Ocular Blood Flow after Ranibizumab Intravitreal Injection for Diabetic Macular Edema Measured Using Laser Speckle Flowgraphy
    Lisa Toto, Federica Evangelista, Pasquale Viggiano, Emanuele Erroi, Giada D’Onofrio, Daniele Libertini, Annamaria Porreca, Rossella D’Aloisio, Parravano Mariacristina, Luca Di Antonio, Marta Di Nicola, Rodolfo Mastropasqua
    BioMed Research International.2020; 2020: 1.     CrossRef
  • microRNA Expression Profile in the Vitreous of Proliferative Diabetic Retinopathy Patients and Differences from Patients Treated with Anti-VEGF Therapy
    Julian Friedrich, David H. W. Steel, Reinier O. Schlingemann, Michael J. Koss, Hans-Peter Hammes, Guido Krenning, Ingeborg Klaassen
    Translational Vision Science & Technology.2020; 9(6): 16.     CrossRef
  • Update on the Effects of Antioxidants on Diabetic Retinopathy: In Vitro Experiments, Animal Studies and Clinical Trials
    Jose Javier Garcia-Medina, Elena Rubio-Velazquez, Elisa Foulquie-Moreno, Ricardo P Casaroli-Marano, Maria Dolores Pinazo-Duran, Vicente Zanon-Moreno, Monica del-Rio-Vellosillo
    Antioxidants.2020; 9(6): 561.     CrossRef
  • Methylglyoxal, a Highly Reactive Dicarbonyl Compound, in Diabetes, Its Vascular Complications, and Other Age-Related Diseases
    C. G. Schalkwijk, C. D. A. Stehouwer
    Physiological Reviews.2020; 100(1): 407.     CrossRef
  • Pericytes, inflammation, and diabetic retinopathy
    Benjamin G. Spencer, Jose J. Estevez, Ebony Liu, Jamie E. Craig, John W. Finnie
    Inflammopharmacology.2020; 28(3): 697.     CrossRef
  • Eye hemodynamic data and biochemical parameters of the lacrimal fluid of patients with non-proliferative diabetic retinopathy
    Guzal Kangilbaeva, Fazilat Bakhritdinova, Iroda Nabieva, Aziza Jurabekova
    Data in Brief.2020; 32: 106237.     CrossRef
  • Endocannabinoids in aqueous humour of patients with or without diabetes
    Patrick Richardson, Catherine Ortori, Dave Barrett, Saoirse O'Sullivan, Iskandar Idris
    BMJ Open Ophthalmology.2020; 5(1): e000425.     CrossRef
  • A pyruvate dehydrogenase kinase inhibitor prevents retinal cell death and improves energy metabolism in rat retinas after ischemia/reperfusion injury
    Kota Sato, Seiya Mochida, Daisuke Tomimoto, Takahiro Konuma, Naoki Kiyota, Satoru Tsuda, Yukihiro Shiga, Kazuko Omodaka, Toru Nakazawa
    Experimental Eye Research.2020; 193: 107997.     CrossRef
  • The Role of Bone Morphogenetic Proteins in Diabetic Complications
    Nimna Perera, Rebecca H. Ritchie, Mitchel Tate
    ACS Pharmacology & Translational Science.2020; 3(1): 11.     CrossRef
  • Increased Ephrin-B2 expression in pericytes contributes to retinal vascular death in rodents
    Maha Coucha, Amy C. Barrett, Joseph Bailey, Maryam Abdelghani, Mohammed Abdelsaid
    Vascular Pharmacology.2020; 131: 106761.     CrossRef
  • Mitochondrial Defects Drive Degenerative Retinal Diseases
    Deborah A. Ferrington, Cody R. Fisher, Renu A. Kowluru
    Trends in Molecular Medicine.2020; 26(1): 105.     CrossRef
  • Fli1 deficiency induces endothelial adipsin expression, contributing to the onset of pulmonary arterial hypertension in systemic sclerosis
    Takuya Miyagawa, Takashi Taniguchi, Ryosuke Saigusa, Maiko Fukayama, Takehiro Takahashi, Takashi Yamashita, Megumi Hirabayashi, Shunsuke Miura, Kouki Nakamura, Ayumi Yoshizaki, Shinichi Sato, Yoshihide Asano
    Rheumatology.2020; 59(8): 2005.     CrossRef
  • Natriuretic Peptides Attenuate Retinal Pathological Neovascularization Via Cyclic Guanosine Monophosphate Signaling in Pericytes and Astrocytes
    Katarina Špiranec Spes, Sabrina Hupp, Franziska Werner, Franziska Koch, Katharina Völker, Lisa Krebes, Ulrike Kämmerer, Katrin G. Heinze, Barbara M. Braunger, Michaela Kuhn
    Arteriosclerosis, Thrombosis, and Vascular Biology.2020; 40(1): 159.     CrossRef
  • Therapeutic investigation of quercetin nanomedicine in a zebrafish model of diabetic retinopathy
    Shuai Wang, Shanshan Du, Wenzhan Wang, Fengyan Zhang
    Biomedicine & Pharmacotherapy.2020; 130: 110573.     CrossRef
  • The role of CD44 in pathological angiogenesis
    Li Chen, Chenying Fu, Qing Zhang, Chengqi He, Feng Zhang, Quan Wei
    The FASEB Journal.2020; 34(10): 13125.     CrossRef
  • Associations between alcohol intake and diabetic retinopathy risk: a systematic review and meta-analysis
    Chen Chen, Zhaojun Sun, Weigang Xu, Jun Tan, Dan Li, Yiting Wu, Ting Zheng, Derong Peng
    BMC Endocrine Disorders.2020;[Epub]     CrossRef
  • Alpha-Smooth Muscle Actin-Positive Perivascular Cells in Diabetic Retina and Choroid
    Soo Jin Kim, Sang A. Kim, Yeong A. Choi, Do Young Park, Junyeop Lee
    International Journal of Molecular Sciences.2020; 21(6): 2158.     CrossRef
  • The G‐protein‐coupled chemoattractant receptor Fpr2 exacerbates neuroglial dysfunction and angiogenesis in diabetic retinopathy
    Ying Yu, Shengding Xue, Keqiang Chen, Yingying Le, Rongrong Zhu, Shiyi Wang, Shuang Liu, Xinliang Cheng, Huaijin Guan, Ji Ming Wang, Hui Chen
    FASEB BioAdvances.2020; 2(10): 613.     CrossRef
  • Dual-Acting Antiangiogenic Gene Therapy Reduces Inflammation and Regresses Neovascularization in Diabetic Mouse Retina
    Rute S. Araújo, Diogo B. Bitoque, Gabriela A. Silva
    Molecular Therapy - Nucleic Acids.2020; 22: 329.     CrossRef
  • The cells involved in the pathological process of diabetic retinopathy
    Songtao Yang, Jiaoyue Zhang, Lulu Chen
    Biomedicine & Pharmacotherapy.2020; 132: 110818.     CrossRef
  • The Role of Transforming Growth Factor-Beta in Retinal Ganglion Cells with Hyperglycemia and Oxidative Stress
    Hsin-Yi Chen, Yi-Jung Ho, Hsiu-Chuan Chou, En-Chi Liao, Yi-Ting Tsai, Yu-Shan Wei, Li-Hsun Lin, Meng-Wei Lin, Yi-Shiuan Wang, Mei-Lan Ko, Hong-Lin Chan
    International Journal of Molecular Sciences.2020; 21(18): 6482.     CrossRef
  • Circadian rhythms in diabetic retinopathy: an overview of pathogenesis and investigational drugs
    Ashay D. Bhatwadekar, Varun Rameswara
    Expert Opinion on Investigational Drugs.2020; 29(12): 1431.     CrossRef
  • Blood-retinal barrier as a converging pivot in understanding the initiation and development of retinal diseases
    Xue Yang, Xiao-Wei Yu, Dan-Dan Zhang, Zhi-Gang Fan
    Chinese Medical Journal.2020; 133(21): 2586.     CrossRef
  • Immunosubunit β5i Knockout Suppresses Neovascularization and Restores Autophagy in Retinal Neovascularization by Targeting ATG5 for Degradation
    Liyang Ji, Li Li, Ying Zhao, Shengqiang Liu, Jingmin Li, Jinsong Zhang, Qi Zhao, Shuai Wang
    Investigative Opthalmology & Visual Science.2020; 61(14): 30.     CrossRef
  • Dipeptidyl Peptidase-4 Inhibitors versus Other Antidiabetic Drugs Added to Metformin Monotherapy in Diabetic Retinopathy Progression: A Real World-Based Cohort Study
    Yoo-Ri Chung, Kyoung Hwa Ha, Hyeon Chang Kim, Sang Jun Park, Kihwang Lee, Dae Jung Kim
    Diabetes & Metabolism Journal.2019; 43(5): 640.     CrossRef
  • Age-related changes of the human retinal vessels: Possible involvement of lipid peroxidation
    Tapas Chandra Nag, Meenakshi Maurya, Tara Sankar Roy
    Annals of Anatomy - Anatomischer Anzeiger.2019; 226: 35.     CrossRef
  • Human iPSCs-Derived Endothelial Cells with Mutation in HNF1A as a Model of Maturity-Onset Diabetes of the Young
    Kachamakova-Trojanowska, Stepniewski, Dulak
    Cells.2019; 8(11): 1440.     CrossRef
  • Diabetic Retinopathy–An Underdiagnosed and Undertreated Inflammatory, Neuro-Vascular Complication of Diabetes
    Stephen H. Sinclair, Stanley S. Schwartz
    Frontiers in Endocrinology.2019;[Epub]     CrossRef
  • Identification of Diagnostic and Prognostic microRNAs for Recurrent Vitreous Hemorrhage in Patients with Proliferative Diabetic Retinopathy
    Parviz Mammadzada, Juliette Bayle, Johann Gudmundsson, Anders Kvanta, Helder André
    Journal of Clinical Medicine.2019; 8(12): 2217.     CrossRef
  • RANKL blockade suppresses pathological angiogenesis and vascular leakage in ischemic retinopathy
    Sangmi Ock, Soyoung Park, Junyeop Lee, Jaetaek Kim
    Biochemical and Biophysical Research Communications.2019; 516(2): 350.     CrossRef
  • EndogenousClostridium perfringensPanophthalmitis with Potential Entry Port from Diverticulitis Exacerbated by Proliferative Diabetic Retinopathy
    Vamsee Neerukonda, Anny M. S. Cheng, Swetha Dhanireddy, Samuel Alpert, Han Y. Yin
    Case Reports in Ophthalmological Medicine.2019; 2019: 1.     CrossRef
  • Attenuation of Retinal Endothelial Vasodilator Function in a Rat Model of Retinopathy of Prematurity
    Ayuki Nakano, Asami Mori, Shiho Arima, Daiki Asano, Akane Morita, Kenji Sakamoto, Tohru Nagamitsu, Tsutomu Nakahara
    Current Eye Research.2019; 44(12): 1360.     CrossRef
  • Efficacy of fenofibrate for diabetic retinopathy
    Xing-jie Su, Lin Han, Yan-Xiu Qi, Hong-wei Liu
    Medicine.2019; 98(14): e14999.     CrossRef
  • Nutraceuticals for the Treatment of Diabetic Retinopathy
    Maria Grazia Rossino, Giovanni Casini
    Nutrients.2019; 11(4): 771.     CrossRef
  • Efficacy of ranibizumab for the treatment of diabetic retinopathy
    Yong-bo Ren, Xing-jie Su, Yan-xiu Qi, He-qun Luan, Qi Sun
    Medicine.2019; 98(17): e15409.     CrossRef
Editorial
Epidemiology
Trends of Diabetes Epidemic in Korea
Ji Cheol Bae
Diabetes Metab J. 2018;42(5):377-379.   Published online October 22, 2018
DOI: https://doi.org/10.4093/dmj.2018.0194
  • 3,431 View
  • 37 Download
  • 22 Web of Science
  • 21 Crossref
PDFPubReader   

Citations

Citations to this article as recorded by  
  • Dynamic changes in prevalence of type 2 diabetes along with associated factors in Bangladesh: Evidence from two national cross-sectional surveys (BDHS 2011 and BDHS 2017–18)
    Sabiha Shirin Sara, Ashis Talukder, Ka Yiu Lee, Nayan Basak, Shaharior Rahman Razu, Iqramul Haq, Chuton Deb Nath
    Diabetes & Metabolic Syndrome: Clinical Research & Reviews.2023; 17(2): 102706.     CrossRef
  • Inverse Association between Oxidative Balance Score and Incident Type 2 Diabetes Mellitus
    Yu-Jin Kwon, Hye-Min Park, Jun-Hyuk Lee
    Nutrients.2023; 15(11): 2497.     CrossRef
  • Non-HDL cholesterol as a predictor for incident type 2 diabetes in community-dwelling adults: longitudinal findings over 12 years
    In-Ho Seo, Da-Hye Son, Hye Sun Lee, Yong-Jae Lee
    Translational Research.2022; 243: 52.     CrossRef
  • Severe Hypoglycemia Increases Dementia Risk and Related Mortality: A Nationwide, Population-based Cohort Study
    Eugene Han, Kyung-do Han, Byung-Wan Lee, Eun Seok Kang, Bong-Soo Cha, Seung-Hyun Ko, Yong-ho Lee
    The Journal of Clinical Endocrinology & Metabolism.2022; 107(5): e1976.     CrossRef
  • Effects of Teneligliptin on HbA1c levels, Continuous Glucose Monitoring-Derived Time in Range and Glycemic Variability in Elderly Patients with T2DM (TEDDY Study)
    Ji Cheol Bae, Soo Heon Kwak, Hyun Jin Kim, Sang-Yong Kim, You-Cheol Hwang, Sunghwan Suh, Bok Jin Hyun, Ji Eun Cha, Jong Chul Won, Jae Hyeon Kim
    Diabetes & Metabolism Journal.2022; 46(1): 81.     CrossRef
  • Fatty liver index as a predictor for incident type 2 diabetes in community-dwelling adults: longitudinal findings over 12 years
    In-Ho Seo, Hye Sun Lee, Yong-Jae Lee
    Cardiovascular Diabetology.2022;[Epub]     CrossRef
  • Triglyceride glucose (TyG) index as a predictor of incident type 2 diabetes among nonobese adults: a 12-year longitudinal study of the Korean Genome and Epidemiology Study cohort
    Byoungjin Park, Hye Sun Lee, Yong-Jae Lee
    Translational Research.2021; 228: 42.     CrossRef
  • Leukocyte count, C-reactive protein level and incidence risk of type 2 diabetes among non-smoking adults: A longitudinal finding over 12 years from the Korean Genome and Epidemiology Study
    A-Ra Cho, Jun-Hyuk Lee, Hye Sun Lee, Yong-Jae Lee
    Primary Care Diabetes.2021; 15(2): 385.     CrossRef
  • White Blood Cell Count as a Predictor of Incident Type 2 Diabetes Mellitus Among Non-Obese Adults: A Longitudinal 10-Year Analysis of the Korean Genome and Epidemiology Study
    Jae-Min Park, Hye Sun Lee, Ju-Young Park, Dong-Hyuk Jung, Ji-Won Lee
    Journal of Inflammation Research.2021; Volume 14: 1235.     CrossRef
  • C-reactive protein-to-albumin ratio and 8‐year incidence of type 2 diabetes: the Korean genome and epidemiology study
    A.-Ra Cho, Sung‐Bum Lee, Kyung-Won Hong, Dong‐Hyuk Jung
    Acta Diabetologica.2021; 58(11): 1525.     CrossRef
  • Comparison of fracture risk between type 1 and type 2 diabetes: a comprehensive real-world data
    J. Ha, C. Jeong, K.-D. Han, Y. Lim, M.K. Kim, H.-S. Kwon, K.-H. Song, M.I. Kang, K.-H. Baek
    Osteoporosis International.2021; 32(12): 2543.     CrossRef
  • Lung function as a predictor of incident type 2 diabetes in community-dwelling adults: A longitudinal finding over 12 years from the Korean Genome and Epidemiology Study
    J.H. Lee, H.S. Lee, Y.J. Lee
    Diabetes & Metabolism.2020; 46(5): 392.     CrossRef
  • Metformin Treatment for Patients with Diabetes and Chronic Kidney Disease: A Korean Diabetes Association and Korean Society of Nephrology Consensus Statement
    Kyu Yeon Hur, Mee Kyoung Kim, Seung Hyun Ko, Miyeun Han, Dong Won Lee, Hyuk-Sang Kwon
    Diabetes & Metabolism Journal.2020; 44(1): 3.     CrossRef
  • Serum γ-glutamyltransferase as an independent predictor for incident type 2 diabetes in middle-aged and older adults: Findings from the KoGES over 12 years of follow-up
    Jun-Hyuk Lee, Hye Sun Lee, Yong-Jae Lee
    Nutrition, Metabolism and Cardiovascular Diseases.2020; 30(9): 1484.     CrossRef
  • Metformin treatment for patients with diabetes and chronic kidney disease: A Korean Diabetes Association and Korean Society of Nephrology consensus statement
    Kyu Yeon Hur, Mee Kyoung Kim, Seung Hyun Ko, Miyeun Han, Dong Won Lee, Hyuk-Sang Kwon
    Kidney Research and Clinical Practice.2020; 39(1): 32.     CrossRef
  • The incidence and seasonal variation of necrotizing fasciitis in Korea: a nationwide cross-sectional study
    H.K. Choi, G.H. Seo, E. Han
    Clinical Microbiology and Infection.2020; 26(8): 1090.e1.     CrossRef
  • Triglyceride to HDL-cholesterol ratio and the incidence risk of type 2 diabetes in community dwelling adults: A longitudinal 12-year analysis of the Korean Genome and Epidemiology Study
    Tae-Kyeong Lim, Hye Sun Lee, Yong-Jae Lee
    Diabetes Research and Clinical Practice.2020; 163: 108150.     CrossRef
  • Diabetic Retinopathy and Related Clinical Practice for People with Diabetes in Korea: A 10-Year Trend Analysis
    Yoo-Ri Chung, Kyoung Hwa Ha, Kihwang Lee, Dae Jung Kim
    Diabetes & Metabolism Journal.2020; 44(6): 928.     CrossRef
  • Elderly Hepatocellular Carcinoma Patients: Open or Laparoscopic Approach?
    Jong Man Kim, Sangjin Kim, Jinsoo Rhu, Gyu-Seong Choi, Choon Hyuck David Kwon, Jae-Won Joh
    Cancers.2020; 12(8): 2281.     CrossRef
  • Diabetes and the Risk of Infection: A National Cohort Study
    Eun Jin Kim, Kyoung Hwa Ha, Dae Jung Kim, Young Hwa Choi
    Diabetes & Metabolism Journal.2019; 43(6): 804.     CrossRef
  • Premeal Consumption of a Protein-Enriched, Dietary Fiber-Fortified Bar Decreases Total Energy Intake in Healthy Individuals
    Chang Ho Ahn, Jae Hyun Bae, Young Min Cho
    Diabetes & Metabolism Journal.2019; 43(6): 879.     CrossRef
Original Articles
Clinical Care/Education
Impact of Socioeconomic Status on Health Behaviors, Metabolic Control, and Chronic Complications in Type 2 Diabetes Mellitus
So Hun Kim, Seung Youn Lee, Chei Won Kim, Young Ju Suh, Seongbin Hong, Seong Hee Ahn, Da Hae Seo, Moon-Suk Nam, Suk Chon, Jeong-Taek Woo, Sei Hyun Baik, Yongsoo Park, Kwan Woo Lee, Young Seol Kim
Diabetes Metab J. 2018;42(5):380-393.   Published online June 29, 2018
DOI: https://doi.org/10.4093/dmj.2017.0102
  • 4,835 View
  • 67 Download
  • 11 Web of Science
  • 15 Crossref
AbstractAbstract PDFSupplementary MaterialPubReader   
Background

The aim of the study was to assess the impact of socioeconomic status (SES) on health behaviors, metabolic control, and chronic complications in people with type 2 diabetes mellitus (T2DM) from South Korea, a country with universal health insurance coverage and that has experienced rapid economic and social transition.

Methods

A total of 3,294 Korean men and women with T2DM aged 30 to 65 years, participating in the Korean National Diabetes Program (KNDP) cohort who reported their SES and had baseline clinical evaluation were included in the current cross-sectional analysis. SES included the level of education and monthly household income.

Results

Lower education level and lower income level were closely related, and both were associated with older age in men and women. Women and men with lower income and education level had higher carbohydrate and lower fat intake. After adjustment for possible confounding factors, higher education in men significantly lowered the odds of having uncontrolled hyperglycemia (glycosylated hemoglobin ≥7.5%) (odds ratio [OR], 0.63; 95% confidence interval [CI], 0.43 to 0.91 for highest education; Ptrend=0.048), while higher household income in men significantly lowered the odds of having diabetic retinopathy (OR, 0.59; 95% CI, 0.37 to 0.95 for highest income level; Ptrend=0.048). In women, lower income was associated with a higher stress level.

Conclusion

Men with lower SES had higher odds of having diabetic retinopathy and uncontrolled hyperglycemia, showing the need to improve care targeted to this population.

Citations

Citations to this article as recorded by  
  • A Scoping Review of Possible Solutions for Decreasing Socioeconomic Inequalities in Type 2 Diabetes Mellitus
    Laleh Gharacheh, Mostafa Amini-Rarani, Amin Torabipour, Saeed Karimi
    International Journal of Preventive Medicine.2024;[Epub]     CrossRef
  • Socioeconomic status and the effect of prolonged pandemic confinement on anthropometric and glycaemic outcomes in adults with type 2 diabetes mellitus
    Chandana Wijeweera, Ummul Muhfaza, Reginald V. Lord, Peter Petocz, Juliana Chen, Veronica Preda
    Primary Care Diabetes.2024;[Epub]     CrossRef
  • Income variability and incident cardiovascular disease in diabetes: a population-based cohort study
    Yong-Moon Mark Park, Jong-Ha Baek, Hong Seok Lee, Tali Elfassy, Clare C Brown, Mario Schootman, Marie-Rachelle Narcisse, Seung-Hyun Ko, Pearl A McElfish, Michael R Thomsen, Benjamin C Amick, Seong-Su Lee, Kyungdo Han
    European Heart Journal.2024;[Epub]     CrossRef
  • Association of diet quality with glycemia, insulinemia, and insulin resistance in families at high risk for type 2 diabetes mellitus in Europe: Feel4 Diabetes Study
    Botsi E, Karatzi K, Mavrogianni C, Kaloyan Tsochev, Esther M González-Gil, Radó S, Kivelä J, Wikström K, Cardon G, Rurik I, Liatis S, Tsvetalina Tankova, Violeta Iotova, Luis A. Moreno, Makrillakis K, Manios Y, Tsigos C
    Nutrition.2023; 105: 111805.     CrossRef
  • Sustained Low Income, Income Changes, and Risk of All-Cause Mortality in Individuals With Type 2 Diabetes: A Nationwide Population-Based Cohort Study
    Hong Seok Lee, Jimin Clara Park, Inkwan Chung, Junxiu Liu, Seong-Su Lee, Kyungdo Han
    Diabetes Care.2023; 46(1): 92.     CrossRef
  • Association of birth weight with risk of diabetes mellitus in adolescence and early adulthood: analysis of the Indonesian Family Life Survey
    Ratu Ayu Dewi Sartika, Fathimah Sulistyowati Sigit, Edy Purwanto, Norliyana Aris, Avliya Quratul Marjan, Wahyu Kurnia Yusrin Putra, Sutanto Priyo Hastono
    Annals of Pediatric Endocrinology & Metabolism.2023; 28(4): 267.     CrossRef
  • Effects of Diabetes Quality Assessment on Diabetes Management Behaviors Based on a Nationwide Survey
    Chang Kyun Choi, Jungho Yang, Ji-An Jeong, Min-Ho Shin
    International Journal of Environmental Research and Public Health.2022; 19(23): 15781.     CrossRef
  • FOLLOW-UP ADHERENCE IN PATIENTS WITH NONPROLIFERATIVE DIABETIC RETINOPATHY PRESENTING TO AN OPHTHALMIC EMERGENCY DEPARTMENT
    Arjun Watane, Meghana Kalavar, Elizabeth A. Vanner, Kara Cavuoto, Jayanth Sridhar
    Retina.2021; 41(6): 1293.     CrossRef
  • Socioeconomic disparity in global vision loss burden due to diabetic retinopathy: an analysis on time trends from 1990 to 2017
    Yi Shan, Yufeng Xu, Lingxia Ye, Xiling Lin, Yaoyao Chen, Qi Miao, Juan Ye
    Endocrine.2021; 73(2): 316.     CrossRef
  • Tip 2 Diyabetli Bireylerin Hastalık Yönetiminde Karşılaştıkları Engellerin Değerlendirilmesi
    Şuheda ÜSTÜNDAĞ, Nuray DAYAPOĞLU
    Adnan Menderes Üniversitesi Sağlık Bilimleri Fakültesi Dergisi.2021; 5(3): 514.     CrossRef
  • Socioeconomic inequalities in type 2 diabetes in employed individuals, nonworking spouses and pensioners
    Batoul Safieddine, Stefanie Sperlich, Johannes Beller, Karin Lange, Jelena Epping, Juliane Tetzlaff, Fabian Tetzlaff, Siegfried Geyer
    SSM - Population Health.2020; 11: 100596.     CrossRef
  • Thirteen-year trends in the prevalence of diabetes according to socioeconomic condition and cardiovascular risk factors in a Swiss population
    Carlos de Mestral, Silvia Stringhini, Idris Guessous, François R Jornayvaz
    BMJ Open Diabetes Research & Care.2020; 8(1): e001273.     CrossRef
  • Dietary Habits and Dietary Antioxidant Intake Are Related to Socioeconomic Status in Polish Adults: A Nationwide Study
    Małgorzata Elżbieta Zujko, Anna Waśkiewicz, Wojciech Drygas, Alicja Cicha-Mikołajczyk, Kinga Zujko, Danuta Szcześniewska, Krystyna Kozakiewicz, Anna Maria Witkowska
    Nutrients.2020; 12(2): 518.     CrossRef
  • Diabetes Fact Sheets in Korea, 2018: An Appraisal of Current Status
    Bo-Yeon Kim, Jong Chul Won, Jae Hyuk Lee, Hun-Sung Kim, Jung Hwan Park, Kyoung Hwa Ha, Kyu Chang Won, Dae Jung Kim, Kyong Soo Park
    Diabetes & Metabolism Journal.2019; 43(4): 487.     CrossRef
  • Gender in Endocrine Diseases: Role of Sex Gonadal Hormones
    R. Lauretta, M. Sansone, A. Sansone, F. Romanelli, M. Appetecchia
    International Journal of Endocrinology.2018; 2018: 1.     CrossRef
Epidemiology
Ten-Year Mortality Trends for Adults with and without Diabetes Mellitus in South Korea, 2003 to 2013
Kyeong Jin Kim, Tae Yeon Kwon, Sungwook Yu, Ji A Seo, Nan Hee Kim, Kyung Mook Choi, Sei Hyun Baik, Dong Seop Choi, Sin Gon Kim, Yousung Park, Nam Hoon Kim
Diabetes Metab J. 2018;42(5):394-401.   Published online April 26, 2018
DOI: https://doi.org/10.4093/dmj.2017.0088
  • 4,865 View
  • 58 Download
  • 25 Web of Science
  • 30 Crossref
AbstractAbstract PDFPubReader   
Background

To estimate and compare the trends of all-cause and cause-specific mortality rates for subjects with and without diabetes in South Korea, from 2003 to 2013.

Methods

Using a population-based cohort (2003 to 2013), we evaluated annual mortality rates in adults (≥30 years) with and without diabetes. The number of subjects in this analysis ranged from 585,795 in 2003 to 670,020 in 2013.

Results

Age- and sex-adjusted all-cause mortality rates decreased consistently in both groups from 2003 to 2013 (from 14.4 to 9.3/1,000 persons in subjects with diabetes and from 7.9 to 4.4/1,000 persons in those without diabetes). The difference in mortality rates between groups also decreased (6.61 per 1,000 persons in 2003 to 4.98 per 1,000 persons in 2013). The slope associated with the mortality rate exhibited a steeper decrease in subjects with diabetes than those without diabetes (regression coefficients of time: −0.50 and −0.33, respectively; P=0.004). In subjects with diabetes, the mortality rate from cardiovascular disease decreased by 53.5% (from 2.73 to 1.27 per 1,000 persons, P for trend <0.001). Notably, the decrease in mortality from ischemic stroke (79.2%, from 1.20 to 0.25 per 1,000 persowns) was more profound than that from ischemic heart disease (28.3%, from 0.60 to 0.43 per 1,000 persons).

Conclusion

All-cause and cardiovascular mortality rates decreased substantially from 2003 to 2013, and the decline in ischemic stroke mortality mainly contributed to the decreased cardiovascular mortality in Korean people with diabetes.

Citations

Citations to this article as recorded by  
  • Green tea consumption and incidence of cardiovascular disease in type 2 diabetic patients with overweight/obesity: a community-based cohort study
    Bingyue Liu, Shujun Gu, Jin Zhang, Hui Zhou, Jian Su, Sudan Wang, Qian Sun, Zhengyuan Zhou, Jinyi Zhou, Chen Dong
    Archives of Public Health.2024;[Epub]     CrossRef
  • Trends in all-cause and cause-specific mortality in older adults with and without diabetes: A territory-wide analysis in one million older adults in Hong Kong
    Aimin Yang, Tingting Chen, Mai Shi, Eric Lau, Raymond SM Wong, Jones Chan, Juliana CN Chan, Elaine Chow
    Diabetes Research and Clinical Practice.2024; 210: 111618.     CrossRef
  • Lipid Management in Korean People With Type 2 Diabetes Mellitus: Korean Diabetes Association and Korean Society of Lipid and Atherosclerosis Consensus Statement
    Ye Seul Yang, Hack-Lyoung Kim, Sang-Hyun Kim, Min Kyong Moon
    Journal of Lipid and Atherosclerosis.2023; 12(1): 12.     CrossRef
  • Lipid Management in Korean People with Type 2 Diabetes Mellitus: Korean Diabetes Association and Korean Society of Lipid and Atherosclerosis Consensus Statement
    Ye Seul Yang, Hack-Lyoung Kim, Sang-Hyun Kim, Min Kyong Moon
    Diabetes & Metabolism Journal.2023; 47(1): 1.     CrossRef
  • Letter: Triglyceride-Glucose Index Predicts Cardiovascular Outcome in Metabolically Unhealthy Obese Population: A Nationwide Population-Based Cohort Study (J Obes Metab Syndr 2022;31:178-86)
    Gwanpyo Koh
    Journal of Obesity & Metabolic Syndrome.2023; 32(2): 179.     CrossRef
  • Management of Dyslipidemia in Patients with Diabetes Mellitus
    Kyung Ae Lee
    The Journal of Korean Diabetes.2023; 24(3): 111.     CrossRef
  • 2023 Clinical Practice Guidelines for Diabetes: Management of Cardiovascular Risk Factors
    Ye Seul Yang
    The Journal of Korean Diabetes.2023; 24(3): 135.     CrossRef
  • The Characteristics and Risk of Mortality in the Elderly Korean Population
    Sunghwan Suh
    Endocrinology and Metabolism.2023; 38(5): 522.     CrossRef
  • Current Status of Low-Density Lipoprotein Cholesterol Target Achievement in Patients with Type 2 Diabetes Mellitus in Korea Compared with Recent Guidelines
    Soo Jin Yun, In-Kyung Jeong, Jin-Hye Cha, Juneyoung Lee, Ho Chan Cho, Sung Hee Choi, SungWan Chun, Hyun Jeong Jeon, Ho-Cheol Kang, Sang Soo Kim, Seung-Hyun Ko, Gwanpyo Koh, Su Kyoung Kwon, Jae Hyuk Lee, Min Kyong Moon, Junghyun Noh, Cheol-Young Park, Sung
    Diabetes & Metabolism Journal.2022; 46(3): 464.     CrossRef
  • Health-related Quality of Life Instrument With 8 Items for Use in Patients With Type 2 Diabetes Mellitus: A Validation Study in Korea
    Juyoung Kim, Hyeon-Jeong Lee, Min-Woo Jo
    Journal of Preventive Medicine and Public Health.2022; 55(3): 234.     CrossRef
  • Improvement in Age at Mortality and Changes in Causes of Death in the Population with Diabetes: An Analysis of Data from the Korean National Health Insurance and Statistical Information Service, 2006 to 2018
    Eugene Han, Sun Ok Song, Hye Soon Kim, Kang Ju Son, Sun Ha Jee, Bong-Soo Cha, Byung-Wan Lee
    Endocrinology and Metabolism.2022; 37(3): 466.     CrossRef
  • Renoprotective Mechanism of Sodium-Glucose Cotransporter 2 Inhibitors: Focusing on Renal Hemodynamics
    Nam Hoon Kim, Nan Hee Kim
    Diabetes & Metabolism Journal.2022; 46(4): 543.     CrossRef
  • Diabetic Ketoacidosis and COVID-19: A Retrospective Observational Study
    Govind Nagdev, Gajanan Chavan, Charuta Gadkari, Gaurav Sahu
    Cureus.2022;[Epub]     CrossRef
  • Trends in the effects of pre‐transplant diabetes on mortality and cardiovascular events after kidney transplantation
    Ja Young Jeon, Soo Jung Kim, Kyoung Hwa Ha, Ji Hyun Park, Bumhee Park, Chang‐Kwon Oh, Seung Jin Han
    Journal of Diabetes Investigation.2021; 12(5): 811.     CrossRef
  • Acute Hyperglycemic Crises with Coronavirus Disease-19: Case Reports
    Na-young Kim, Eunyeong Ha, Jun Sung Moon, Yong-Hoon Lee, Eun Young Choi
    Diabetes & Metabolism Journal.2020; 44(2): 349.     CrossRef
  • Polysomnographic phenotyping of obstructive sleep apnea and its implications in mortality in Korea
    Jeong-Whun Kim, Tae-Bin Won, Chae-Seo Rhee, Young Mi Park, In-Young Yoon, Sung-Woo Cho
    Scientific Reports.2020;[Epub]     CrossRef
  • Peripheral arterial endothelial dysfunction predicts future cardiovascular events in diabetic patients with albuminuria: a prospective cohort study
    Bo Kyung Koo, Woo-Young Chung, Min Kyong Moon
    Cardiovascular Diabetology.2020;[Epub]     CrossRef
  • Metformin treatment for patients with diabetes and chronic kidney disease: A Korean Diabetes Association and Korean Society of Nephrology consensus statement
    Kyu Yeon Hur, Mee Kyoung Kim, Seung Hyun Ko, Miyeun Han, Dong Won Lee, Hyuk-Sang Kwon
    Kidney Research and Clinical Practice.2020; 39(1): 32.     CrossRef
  • Outcomes for Inappropriate Renal Dose Adjustment of Dipeptidyl Peptidase-4 Inhibitors in Patients With Type 2 Diabetes Mellitus: Population-Based Study
    Sangmo Hong, Kyungdo Han, Cheol-Young Park
    Mayo Clinic Proceedings.2020; 95(1): 101.     CrossRef
  • Metformin Treatment for Patients with Diabetes and Chronic Kidney Disease: A Korean Diabetes Association and Korean Society of Nephrology Consensus Statement
    Kyu Yeon Hur, Mee Kyoung Kim, Seung Hyun Ko, Miyeun Han, Dong Won Lee, Hyuk-Sang Kwon
    Diabetes & Metabolism Journal.2020; 44(1): 3.     CrossRef
  • A systematic review of trends in all-cause mortality among people with diabetes
    Lei Chen, Rakibul M. Islam, Joanna Wang, Thomas R. Hird, Meda E. Pavkov, Edward W. Gregg, Agus Salim, Maryam Tabesh, Digsu N. Koye, Jessica L. Harding, Julian W. Sacre, Elizabeth L. M. Barr, Dianna J. Magliano, Jonathan E. Shaw
    Diabetologia.2020; 63(9): 1718.     CrossRef
  • Diabetic ketoacidosis precipitated by COVID-19: A report of two cases and review of literature
    Pavan Kumar Reddy, Mohammad Shafi Kuchay, Yatin Mehta, Sunil Kumar Mishra
    Diabetes & Metabolic Syndrome: Clinical Research & Reviews.2020; 14(5): 1459.     CrossRef
  • Prognostic value of long-term gamma-glutamyl transferase variability in individuals with diabetes: a nationwide population-based study
    Da Young Lee, Kyungdo Han, Ji Hee Yu, Sanghyun Park, Ji A Seo, Nam Hoon Kim, Hye Jin Yoo, Sin Gon Kim, Seon Mee Kim, Kyung Mook Choi, Sei Hyun Baik, Yong Gyu Park, Nan Hee Kim
    Scientific Reports.2020;[Epub]     CrossRef
  • Arterial stiffness is an independent predictor for risk of mortality in patients with type 2 diabetes mellitus: the REBOUND study
    Jeong Mi Kim, Sang Soo Kim, In Joo Kim, Jong Ho Kim, Bo Hyun Kim, Mi Kyung Kim, Soon Hee Lee, Chang Won Lee, Min Chul Kim, Jun Hyeob Ahn, Jinmi Kim
    Cardiovascular Diabetology.2020;[Epub]     CrossRef
  • The triglyceride glucose index is a simple and low-cost marker associated with atherosclerotic cardiovascular disease: a population-based study
    Sangmo Hong, Kyungdo Han, Cheol-Young Park
    BMC Medicine.2020;[Epub]     CrossRef
  • Increased Age of Death and Change in Causes of Death Among Persons With Diabetes Mellitus From the Korean National Health Insurance and Statistical Information Service, 2006 to 2018
    Eugene Han, Sun Ok Song, Hye Soon Kim, Kang Ju Son, Sun Ha Jee, Bong-Soo Cha, Byung-Wan Lee
    SSRN Electronic Journal .2020;[Epub]     CrossRef
  • Letter: Comparison of the Efficacy of Rosuvastatin Monotherapy 20 mg with Rosuvastatin 5 mg and Ezetimibe 10 mg Combination Therapy on Lipid Parameters in Patients with Type 2 Diabetes Mellitus (Diabetes Metab J2019;43:582–9)
    Tae Seo Sohn
    Diabetes & Metabolism Journal.2019; 43(6): 909.     CrossRef
  • Diabetes Mellitus, Still Major Threat to Mortality from Various Causes
    Nam Hoon Kim
    Diabetes & Metabolism Journal.2019; 43(3): 273.     CrossRef
  • Diabetes and Cancer: Cancer Should Be Screened in Routine Diabetes Assessment
    Sunghwan Suh, Kwang-Won Kim
    Diabetes & Metabolism Journal.2019; 43(6): 733.     CrossRef
  • Trends of Diabetes Epidemic in Korea
    Ji Cheol Bae
    Diabetes & Metabolism Journal.2018; 42(5): 377.     CrossRef
Epidemiology
Development and Validation of the Korean Diabetes Risk Score: A 10-Year National Cohort Study
Kyoung Hwa Ha, Yong-ho Lee, Sun Ok Song, Jae-woo Lee, Dong Wook Kim, Kyung-hee Cho, Dae Jung Kim
Diabetes Metab J. 2018;42(5):402-414.   Published online July 6, 2018
DOI: https://doi.org/10.4093/dmj.2018.0014
  • 5,834 View
  • 114 Download
  • 22 Web of Science
  • 21 Crossref
AbstractAbstract PDFSupplementary MaterialPubReader   
Background

A diabetes risk score in Korean adults was developed and validated.

Methods

This study used the National Health Insurance Service-National Health Screening Cohort (NHIS-HEALS) of 359,349 people without diabetes at baseline to derive an equation for predicting the risk of developing diabetes, using Cox proportional hazards regression models. External validation was conducted using data from the Korean Genome and Epidemiology Study. Calibration and discrimination analyses were performed separately for men and women in the development and validation datasets.

Results

During a median follow-up of 10.8 years, 37,678 cases (event rate=10.4 per 1,000 person-years) of diabetes were identified in the development cohort. The risk score included age, family history of diabetes, alcohol intake (only in men), smoking status, physical activity, use of antihypertensive therapy, use of statin therapy, body mass index, systolic blood pressure, total cholesterol, fasting glucose, and γ glutamyl transferase (only in women). The C-statistics for the models for risk at 10 years were 0.71 (95% confidence interval [CI], 0.70 to 0.73) for the men and 0.76 (95% CI, 0.75 to 0.78) for the women in the development dataset. In the validation dataset, the C-statistics were 0.63 (95% CI, 0.53 to 0.73) for men and 0.66 (95% CI, 0.55 to 0.76) for women.

Conclusion

The Korean Diabetes Risk Score may identify people at high risk of developing diabetes and may be an effective tool for delaying or preventing the onset of condition as risk management strategies involving modifiable risk factors can be recommended to those identified as at high risk.

Citations

Citations to this article as recorded by  
  • Alanine to glycine ratio is a novel predictive biomarker for type 2 diabetes mellitus
    Kwang Seob Lee, Yong‐ho Lee, Sang‐Guk Lee
    Diabetes, Obesity and Metabolism.2024; 26(3): 980.     CrossRef
  • Associations of updated cardiovascular health metrics, including sleep health, with incident diabetes and cardiovascular events in older adults with prediabetes: A nationwide population-based cohort study
    Kyoung Hwa Ha, Dae Jung Kim, Seung Jin Han
    Diabetes Research and Clinical Practice.2023; 203: 110820.     CrossRef
  • Comparisons of the prediction models for undiagnosed diabetes between machine learning versus traditional statistical methods
    Seong Gyu Choi, Minsuk Oh, Dong–Hyuk Park, Byeongchan Lee, Yong-ho Lee, Sun Ha Jee, Justin Y. Jeon
    Scientific Reports.2023;[Epub]     CrossRef
  • Risk prediction models for incident type 2 diabetes in Chinese people with intermediate hyperglycemia: a systematic literature review and external validation study
    Shishi Xu, Ruth L. Coleman, Qin Wan, Yeqing Gu, Ge Meng, Kun Song, Zumin Shi, Qian Xie, Jaakko Tuomilehto, Rury R. Holman, Kaijun Niu, Nanwei Tong
    Cardiovascular Diabetology.2022;[Epub]     CrossRef
  • Gamma-glutamyl transferase to high-density lipoprotein cholesterol ratio: A valuable predictor of type 2 diabetes mellitus incidence
    Wangcheng Xie, Bin Liu, Yansong Tang, Tingsong Yang, Zhenshun Song
    Frontiers in Endocrinology.2022;[Epub]     CrossRef
  • Low aspartate aminotransferase/alanine aminotransferase (DeRitis) ratio assists in predicting diabetes in Chinese population
    Wangcheng Xie, Weidi Yu, Shanshan Chen, Zhilong Ma, Tingsong Yang, Zhenshun Song
    Frontiers in Public Health.2022;[Epub]     CrossRef
  • Prediction Models for Type 2 Diabetes Risk in the General Population: A Systematic Review of Observational Studies
    Samaneh Asgari, Davood Khalili, Farhad Hosseinpanah, Farzad Hadaegh
    International Journal of Endocrinology and Metabolism.2021;[Epub]     CrossRef
  • Development of a clinical risk score for incident diabetes: A 10‐year prospective cohort study
    Tae Jung Oh, Jae Hoon Moon, Sung Hee Choi, Young Min Cho, Kyong Soo Park, Nam H Cho, Hak Chul Jang
    Journal of Diabetes Investigation.2021; 12(4): 610.     CrossRef
  • Association between longitudinal blood pressure and prognosis after treatment of cerebral aneurysm: A nationwide population-based cohort study
    Jinkwon Kim, Jang Hoon Kim, Hye Sun Lee, Sang Hyun Suh, Kyung-Yul Lee, Yan Li
    PLOS ONE.2021; 16(5): e0252042.     CrossRef
  • Development of a predictive risk model for all-cause mortality in patients with diabetes in Hong Kong
    Sharen Lee, Jiandong Zhou, Keith Sai Kit Leung, William Ka Kei Wu, Wing Tak Wong, Tong Liu, Ian Chi Kei Wong, Kamalan Jeevaratnam, Qingpeng Zhang, Gary Tse
    BMJ Open Diabetes Research & Care.2021; 9(1): e001950.     CrossRef
  • Development and Validation of a Deep Learning Based Diabetes Prediction System Using a Nationwide Population-Based Cohort
    Sang Youl Rhee, Ji Min Sung, Sunhee Kim, In-Jeong Cho, Sang-Eun Lee, Hyuk-Jae Chang
    Diabetes & Metabolism Journal.2021; 45(4): 515.     CrossRef
  • Development and validation of a new diabetes index for the risk classification of present and new-onset diabetes: multicohort study
    Shinje Moon, Ji-Yong Jang, Yumin Kim, Chang-Myung Oh
    Scientific Reports.2021;[Epub]     CrossRef
  • New risk score model for identifying individuals at risk for diabetes in southwest China
    Liying Li, Ziqiong Wang, Muxin Zhang, Haiyan Ruan, Linxia Zhou, Xin Wei, Ye Zhu, Jiafu Wei, Sen He
    Preventive Medicine Reports.2021; 24: 101618.     CrossRef
  • Multiple Biomarkers Improved Prediction for the Risk of Type 2 Diabetes Mellitus in Singapore Chinese Men and Women
    Yeli Wang, Woon-Puay Koh, Xueling Sim, Jian-Min Yuan, An Pan
    Diabetes & Metabolism Journal.2020; 44(2): 295.     CrossRef
  • Smoking as a Target for Prevention of Diabetes
    Ye Seul Yang, Tae Seo Sohn
    Diabetes & Metabolism Journal.2020; 44(3): 402.     CrossRef
  • Middle-aged men with type 2 diabetes as potential candidates for pancreatic cancer screening: a 10-year nationwide population-based cohort study
    Dong-Hoe Koo, Kyung-Do Han, Hong Joo Kim, Cheol-Young Park
    Acta Diabetologica.2020; 57(2): 197.     CrossRef
  • Systematic review with meta-analysis of the epidemiological evidence relating smoking to type 2 diabetes
    Peter N Lee, Katharine J Coombs
    World Journal of Meta-Analysis.2020; 8(2): 119.     CrossRef
  • Biomarker Score in Risk Prediction: Beyond Scientific Evidence and Statistical Performance
    Heejung Bang
    Diabetes & Metabolism Journal.2020; 44(2): 245.     CrossRef
  • Research progress on Traditional Chinese Medicine syndromes of diabetes mellitus
    Jingkang Wang, Quantao Ma, Yaqi Li, Pengfei Li, Min Wang, Tieshan Wang, Chunguo Wang, Ting Wang, Baosheng Zhao
    Biomedicine & Pharmacotherapy.2020; 121: 109565.     CrossRef
  • Cardiometabolic risk prediction algorithms for young people with psychosis: a systematic review and exploratory analysis
    B. I. Perry, R. Upthegrove, O. Crawford, S. Jang, E. Lau, I. McGill, E. Carver, P. B. Jones, G. M. Khandaker
    Acta Psychiatrica Scandinavica.2020; 142(3): 215.     CrossRef
  • Impact of obesity, fasting plasma glucose level, blood pressure, and renal function on the severity of COVID-19: A matter of sexual dimorphism?
    Kyungmin Huh, Rugyeom Lee, Wonjun Ji, Minsun Kang, In Cheol Hwang, Dae Ho Lee, Jaehun Jung
    Diabetes Research and Clinical Practice.2020; 170: 108515.     CrossRef
Epidemiology
Diabetes Fact Sheet in Korea, 2016: An Appraisal of Current Status
Jong Chul Won, Jae Hyuk Lee, Jae Hyeon Kim, Eun Seok Kang, Kyu Chang Won, Dae Jung Kim, Moon-Kyu Lee
Diabetes Metab J. 2018;42(5):415-424.   Published online August 9, 2018
DOI: https://doi.org/10.4093/dmj.2018.0017
  • 8,883 View
  • 89 Download
  • 72 Web of Science
  • 72 Crossref
AbstractAbstract PDFSupplementary MaterialPubReader   
Background

This report presents the recent prevalence and comorbidities related to diabetes in Korea by analyzing the nationally representative data.

Methods

Using data from the Korea National Health and Nutrition Examination Survey for 2013 to 2014, the percentages and the total number of subjects over the age of 30 years with diabetes and prediabetes were estimated and applied to the National Population Census in 2014. Diagnosis of diabetes was based on fasting plasma glucose (≥126 mg/dL), current taking of antidiabetic medication, history of previous diabetes, or glycosylated hemoglobin (HbA1c) ≥6.5%. Impaired fasting glucose (IFG) was defined by fasting plasma glucose in the range of 100 to 125 mg/dL among those without diabetes.

Results

About 4.8 million (13.7%) Korean adults (≥30 years old) had diabetes, and about 8.3 million (24.8%) Korean adults had IFG. However, 29.3% of the subjects with diabetes are not aware of their condition. Of the subjects with diabetes, 48.6% and 54.7% were obese and hypertensive, respectively, and 31.6% had hypercholesterolemia. Although most subjects with diabetes (89.1%) were under medical treatment, and mostly being treated with oral hypoglycemic agents (80.2%), 10.8% have remained untreated. With respect to overall glycemic control, 43.5% reached the target of HbA1c <7%, whereas 23.3% reached the target when the standard was set to HbA1c <6.5%, according to the Korean Diabetes Association guideline.

Conclusion

Diabetes is a major public health threat in Korea, but a significant proportion of adults were not controlling their illness. We need comprehensive approaches to overcome the upcoming diabetes-related disease burden in Korea.

Citations

Citations to this article as recorded by  
  • Impact of anaerobic zone on biodegradation of micropollutants: Comparison of micropollutants’ removal efficiencies in lab-scale anaerobic bioreactor and in full-scale anaerobic zone
    Jingyeong Shin, Sungman Lee, Jihea Lee, Heejong Son, Yunho Lee, Young Mo Kim
    Chemical Engineering Journal.2024; 481: 148356.     CrossRef
  • Clinical traits and systemic risks of familial diabetes mellitus according to age of onset and quantity: an analysis of data from the community-based KoGES cohort study
    Ju-Yeun Lee, Kyungsik Kim, Sangjun Lee, Woo Ju An, Sue K. Park
    Epidemiology and Health.2023; 45: e2023029.     CrossRef
  • The prevalence and predictors of pre-diabetes and diabetes among adults 40–70 years in Kharameh cohort study: A population-based study in Fars province, south of Iran
    Masoumeh Ghoddusi Johari, Kimia Jokari, Alireza Mirahmadizadeh, Mozhgan Seif, Abbas Rezaianzadeh
    Journal of Diabetes & Metabolic Disorders.2022; 21(1): 85.     CrossRef
  • Concept and Proof of the Lifelog Bigdata Platform for Digital Healthcare and Precision Medicine on the Cloud
    Kyu Hee Lee, Erdenebayar Urtnasan, Sangwon Hwang, Hee Young Lee, Jung Hun Lee, Sang Baek Koh, Hyun Youk
    Yonsei Medical Journal.2022; 63(Suppl): S84.     CrossRef
  • The Impact of Diabetes on Vascular Disease: Progress from the Perspective of Epidemics and Treatments
    Runyang Liu, Lihua Li, Chen Shao, Honghua Cai, Zhongqun Wang, Pawel Kleczynski
    Journal of Diabetes Research.2022; 2022: 1.     CrossRef
  • Incidence and Predisposing Factors of Postoperative Infection after Rhinoplasty: A Single Surgeon’s 16-Year Experience with 2630 Cases in an East Asian Population
    Khanh Ngoc Tran, Yong Ju Jang
    Plastic & Reconstructive Surgery.2022; 150(1): 51e.     CrossRef
  • Predictors for successful weight reduction during treatment with Dapagliflozin among patients with type 2 diabetes mellitus in primary care
    Youn Huh, Young Sik Kim
    BMC Primary Care.2022;[Epub]     CrossRef
  • Skin accumulation of advanced glycation end products and cardiovascular risk in Korean patients with type 2 diabetes mellitus
    Lee-Seoul Choi, Kainat Ahmed, Young-Seol Kim, Jung-Eun Yim
    Heliyon.2022; 8(6): e09571.     CrossRef
  • Health-related Quality of Life Instrument With 8 Items for Use in Patients With Type 2 Diabetes Mellitus: A Validation Study in Korea
    Juyoung Kim, Hyeon-Jeong Lee, Min-Woo Jo
    Journal of Preventive Medicine and Public Health.2022; 55(3): 234.     CrossRef
  • Factors Influencing the Utilization of Diabetes Complication Tests Under the COVID-19 Pandemic: Machine Learning Approach
    Haewon Byeon
    Frontiers in Endocrinology.2022;[Epub]     CrossRef
  • Prevalence and risk of diabetic complications in young-onset versus late-onset type 2 diabetes mellitus
    Yongin Cho, Hye-Sun Park, Byung Wook Huh, Seong Ha Seo, Da Hea Seo, Seong Hee Ahn, Seongbin Hong, Young Ju Suh, So Hun Kim
    Diabetes & Metabolism.2022; 48(6): 101389.     CrossRef
  • Prevalence and Early Prediction of Diabetes Using Machine Learning in North Kashmir: A Case Study of District Bandipora
    Salliah Shafi Bhat, Venkatesan Selvam, Gufran Ahmad Ansari, Mohd Dilshad Ansari, Md Habibur Rahman, Mamoon Rashid
    Computational Intelligence and Neuroscience.2022; 2022: 1.     CrossRef
  • Association between Nighttime Work and HbA1c Levels in South Korea
    Yeon-Suk Lee, Jae Hong Joo, Eun-Cheol Park
    Healthcare.2022; 10(10): 1977.     CrossRef
  • Differences in health behavior and nutrient intake status between diabetes-aware and unaware Korean adults based on the Korea national health and nutrition examination survey 2016–18 data: A cross-sectional study
    Anshul Sharma, Chen Lulu, Kee-Ho Song, Hae-Jeung Lee
    Frontiers in Public Health.2022;[Epub]     CrossRef
  • Screening for Prediabetes and Diabetes in Korean Nonpregnant Adults: A Position Statement of the Korean Diabetes Association, 2022
    Kyung Ae Lee, Dae Jung Kim, Kyungdo Han, Suk Chon, Min Kyong Moon
    Diabetes & Metabolism Journal.2022; 46(6): 819.     CrossRef
  • Sex differences in sarcopenia and frailty among community‐dwelling Korean older adults with diabetes: The Korean Frailty and Aging Cohort Study
    Sunyoung Kang, Tae Jung Oh, Be Long Cho, Yong Soon Park, Eun Roh, Hyeon Ju Kim, Sam‐Gyu Lee, Bong Jo Kim, Miji Kim, Chang Won Won, Hak Chul Jang
    Journal of Diabetes Investigation.2021; 12(2): 155.     CrossRef
  • Umbilical Cord-Mesenchymal Stem Cell-Conditioned Medium Improves Insulin Resistance in C2C12 Cell
    Kyung-Soo Kim, Yeon Kyung Choi, Mi Jin Kim, Jung Wook Hwang, Kyunghoon Min, Sang Youn Jung, Soo-Kyung Kim, Yong-Soo Choi, Yong-Wook Cho
    Diabetes & Metabolism Journal.2021; 45(2): 260.     CrossRef
  • Hemoglobin glycation index is associated with incident chronic kidney disease in subjects with impaired glucose metabolism: A 10-year longitudinal cohort study
    Wonjin Kim, Taehwa Go, Dae Ryong Kang, Eun Jig Lee, Ji Hye Huh
    Journal of Diabetes and its Complications.2021; 35(1): 107760.     CrossRef
  • East Asian diet‐mimicking diet plan based on the Mediterranean diet and the Dietary Approaches to Stop Hypertension diet in adults with type 2 diabetes: A randomized controlled trial
    Sang‐Man Jin, Jiyeon Ahn, Jiyun Park, Kyu Yeon Hur, Jae Hyeon Kim, Moon‐Kyu Lee
    Journal of Diabetes Investigation.2021; 12(3): 357.     CrossRef
  • Status of Diabetic Neuropathy in Korea: A National Health Insurance Service-National Sample Cohort Analysis (2006 to 2015)
    Seong-Su Moon, Chong Hwa Kim, Seon Mee Kang, Eun Sook Kim, Tae Jung Oh, Jae-Seung Yun, Ho Chan Cho, Dae Jung Kim, Tae Sun Park
    Diabetes & Metabolism Journal.2021; 45(1): 115.     CrossRef
  • Diabetes Fact Sheets in Korea, 2020: An Appraisal of Current Status
    Chan-Hee Jung, Jang Won Son, Shinae Kang, Won Jun Kim, Hun-Sung Kim, Hae Soon Kim, Mihae Seo, Hye-Jung Shin, Seong-Su Lee, Su Jin Jeong, Yongin Cho, Seung Jin Han, Hyang Mi Jang, Mira Rho, Shinbi Lee, Mihyun Koo, Been Yoo, Jung-Wha Moon, Hye Young Lee, Ja
    Diabetes & Metabolism Journal.2021; 45(1): 1.     CrossRef
  • Considering serum alanine aminotransferase and gamma-glutamyltransferase levels together strengthen the prediction of impaired fasting glucose risk: a cross-sectional and longitudinal study
    Ji Hye Jeong, Susie Jung, Kyu-Nam Kim
    Scientific Reports.2021;[Epub]     CrossRef
  • The Associations Between Vitamin D Receptor BsmI and ApaI Polymorphisms and Obesity in Korean Patients with Type 2 Diabetes Mellitus
    Sang Won Nam, Jinwoo Choi, Hyun Jeong Jeon, Tae Keun Oh, Dong-Hwa Lee
    Diabetes, Metabolic Syndrome and Obesity: Targets and Therapy.2021; Volume 14: 557.     CrossRef
  • Association between living alone and incident type 2 diabetes among middle-aged individuals in Korea: a nationwide cohort study
    Ga Eun Nam, Wonsock Kim, Kyungdo Han, Jin-Hyung Jung, Byoungduck Han, Jinwook Kim, Nan Hee Kim, Kyung Mook Choi, Kyung Hwan Cho, Yong Gyu Park, Seon Mee Kim
    Scientific Reports.2021;[Epub]     CrossRef
  • Retracted: Western pacific consensus proposals for management of prediabetes

    International Journal of Clinical Practice.2021;[Epub]     CrossRef
  • Blood glucose levels and bodyweight change after dapagliflozin administration
    Hyunah Kim, Seung‐Hwan Lee, Hyunyong Lee, Hyeon Woo Yim, Jae‐Hyoung Cho, Kun‐Ho Yoon, Hun‐Sung Kim
    Journal of Diabetes Investigation.2021; 12(9): 1594.     CrossRef
  • Prevalence and socioeconomic burden of diabetes mellitus in South Korean adults: a population-based study using administrative data
    Sung-Hee Oh, Hyemin Ku, Kang Seo Park
    BMC Public Health.2021;[Epub]     CrossRef
  • Prediction of Type 2 Diabetes Based on Machine Learning Algorithm
    Henock M. Deberneh, Intaek Kim
    International Journal of Environmental Research and Public Health.2021; 18(6): 3317.     CrossRef
  • Development of a clinical risk score for incident diabetes: A 10‐year prospective cohort study
    Tae Jung Oh, Jae Hoon Moon, Sung Hee Choi, Young Min Cho, Kyong Soo Park, Nam H Cho, Hak Chul Jang
    Journal of Diabetes Investigation.2021; 12(4): 610.     CrossRef
  • New Era for Renal-Protective Therapy in Type 2 Diabetes: Better Renal Outcomes in Patients with Type 2 Diabetes Taking Sodium-Glucose Cotransporter 2 Inhibitors versus Dipeptidyl Peptidase-4 Inhibitors
    Chan-Hee Jung
    Endocrinology and Metabolism.2021; 36(2): 339.     CrossRef
  • Treatment Patterns of Type 2 Diabetes Assessed Using a Common Data Model Based on Electronic Health Records of 2000–2019
    Kyung Ae Lee, Heung Yong Jin, Yu Ji Kim, Yong-Jin Im, Eun-Young Kim, Tae Sun Park
    Journal of Korean Medical Science.2021;[Epub]     CrossRef
  • No influence of hepatic steatosis on the 3‐year outcomes of patients with quiescent chronic hepatitis B
    Jin Won Chang, Jae Seung Lee, Hye Won Lee, Beom Kyung Kim, Jun Yong Park, Do Young Kim, Sang Hoon Ahn, Seung Up Kim
    Journal of Viral Hepatitis.2021; 28(11): 1545.     CrossRef
  • Occupational Noise Exposure and Incidence of High Fasting Blood Glucose: A 3-Year, Multicenter, Retrospective Study
    Seunghan Kim, Byungyoon Yun, Seunghyun Lee, Changyoung Kim, Juho Sim, Ara Cho, Yeonsuh Oh, Jiho Lee, Jinha Yoon
    International Journal of Environmental Research and Public Health.2021; 18(17): 9388.     CrossRef
  • Young-onset type 2 diabetes in South Korea: a review of the current status and unmet need
    Ye Seul Yang, Kyungdo Han, Tae Seo Sohn, Nam Hoon Kim
    The Korean Journal of Internal Medicine.2021; 36(5): 1049.     CrossRef
  • Blood Pressure and Cardiovascular Disease in Older Patients With Diabetes: Retrospective Cohort Study
    Sangmo Hong, Jung Hwan Park, Kyungdo Han, Chang Beom Lee, Dong Sun Kim, Sung Hoon Yu
    Journal of the American Heart Association.2021;[Epub]     CrossRef
  • Prevalence of significant hepatic fibrosis using magnetic resonance elastography in a health check‐up clinic population
    Kyung A Kang, Dae Won Jun, Mi Sung Kim, Heon‐Ju Kwon, Mindie H. Nguyen
    Alimentary Pharmacology & Therapeutics.2020; 51(3): 388.     CrossRef
  • The Effects of Bariatric Surgery on Type 2 Diabetes in Asian Populations: a Meta-analysis of Randomized Controlled Trials
    Jin Hwa Kim, Jung-Soo Pyo, Won Jin Cho, Sang Yong Kim
    Obesity Surgery.2020; 30(3): 910.     CrossRef
  • Opposite Effects of Work-Related Physical Activity and Leisure-Time Physical Activity on the Risk of Diabetes in Korean Adults
    Hyun Sook Oh
    International Journal of Environmental Research and Public Health.2020; 17(16): 5812.     CrossRef
  • Middle-aged men with type 2 diabetes as potential candidates for pancreatic cancer screening: a 10-year nationwide population-based cohort study
    Dong-Hoe Koo, Kyung-Do Han, Hong Joo Kim, Cheol-Young Park
    Acta Diabetologica.2020; 57(2): 197.     CrossRef
  • Efficacy and safety of insulin glargine 300 U/mL versus insulin glargine 100 U/mL in Asia Pacific insulin‐naïve people with type 2 diabetes: The EDITION AP randomized controlled trial
    Linong Ji, Eun Seok Kang, XiaoLin Dong, Ling Li, GuoYue Yuan, Shuhua Shang, Elisabeth Niemoeller
    Diabetes, Obesity and Metabolism.2020; 22(4): 612.     CrossRef
  • Non-Exercise Based Estimation of Cardiorespiratory Fitness Mediates Associations between Comorbidities and Health-Related Quality of Life in Older Korean Adults with Diabetes
    Inhwan Lee, Shinuk Kim, Hyunsik Kang
    International Journal of Environmental Research and Public Health.2020; 17(4): 1164.     CrossRef
  • γ-Linolenic Acid versus α-Lipoic Acid for Treating Painful Diabetic Neuropathy in Adults: A 12-Week, Double-Placebo, Randomized, Noninferiority Trial
    Jong Chul Won, Hyuk-Sang Kwon, Seong-Su Moon, Sung Wan Chun, Chong Hwa Kim, Ie Byung Park, In Joo Kim, Jihyun Lee, Bong Yun Cha, Tae Sun Park
    Diabetes & Metabolism Journal.2020; 44(4): 542.     CrossRef
  • Circulating myokine levels in different stages of glucose intolerance
    Kahui Park, Chul Woo Ahn, Jong Suk Park, YuSik Kim, Ji Sun Nam
    Medicine.2020; 99(8): e19235.     CrossRef
  • Associations among Obesity Degree, Glycemic Status, and Risk of Heart Failure in 9,720,220 Korean Adults
    Eun-Jung Rhee, Hyemi Kwon, Se Eun Park, Kyung-Do Han, Yong-Gyu Park, Yang-Hyun Kim, Won-Young Lee
    Diabetes & Metabolism Journal.2020; 44(4): 592.     CrossRef
  • The sweet spot: fasting glucose, cardiovascular disease, and mortality in older adults with diabetes: a nationwide population-based study
    Ji Hyun Lee, Kyungdo Han, Ji Hye Huh
    Cardiovascular Diabetology.2020;[Epub]     CrossRef
  • Glucose-Lowering Effect of Home-Delivered Therapeutic Meals in Patients with Type 2 Diabetes
    Jong Han Choi, Se Hee Min, Kyeong Hye Lim, Uoon Jeong Shin, Min-Seon Kim
    The Journal of Korean Diabetes.2020; 21(1): 46.     CrossRef
  • Fasting Plasma Glucose Level Independently Predicts the Mortality of Patients with Coronavirus Disease 2019 Infection: A Multicenter, Retrospective Cohort Study
    Min Cheol Chang, Jong-Moon Hwang, Jae-Han Jeon, Sang Gyu Kwak, Donghwi Park, Jun Sung Moon
    Endocrinology and Metabolism.2020; 35(3): 595.     CrossRef
  • Gender differences in adverse event reports associated with antidiabetic drugs
    Kyung-In Joung, Gyu-Won Jung, Han-Heui Park, Hyesung Lee, So-Hee Park, Ju-Young Shin
    Scientific Reports.2020;[Epub]     CrossRef
  • Relative fat mass at baseline and its early change may be a predictor of incident nonalcoholic fatty liver disease
    Hwi Young Kim, Su Jung Baik, Hye Ah Lee, Byoung Kwon Lee, Hye Sun Lee, Tae Hun Kim, Kwon Yoo
    Scientific Reports.2020;[Epub]     CrossRef
  • Peripheral Arterial Stiffness Increases the Risk of Progression of Renal Disease in Type 2 Diabetic Patients
    Tae Hoon Lim, Seung Min Chung, Dong Sung Lee, Se Ra Choi, Jun Sung Moon, Ji Sung Yoon, Kyu Chang Won, Hyoung Woo Lee
    Frontiers in Medicine.2020;[Epub]     CrossRef
  • Association of Urinary Polycyclic Aromatic Hydrocarbons and Diabetes in Korean Adults: Data from the Korean National Environmental Health Survey Cycle 2 (2012–2014)


    Yon Ju Nam, Shin-Hye Kim
    Diabetes, Metabolic Syndrome and Obesity: Targets and Therapy.2020; Volume 13: 3993.     CrossRef
  • Present and Future of Digital Health in Diabetes and Metabolic Disease
    Sang Youl Rhee, Chiweon Kim, Dong Wook Shin, Steven R. Steinhubl
    Diabetes & Metabolism Journal.2020; 44(6): 819.     CrossRef
  • Trends in the Incidence, Prevalence, and Mortality of End-Stage Kidney Disease in South Korea
    Min-Jeong Lee, Kyoung Hwa Ha, Dae Jung Kim, Inwhee Park
    Diabetes & Metabolism Journal.2020; 44(6): 933.     CrossRef
  • An evaluation of the impact of aggressive diabetes and hypertension management on chronic kidney diseases at the population level: a simulation analysis
    John Pastor Ansah, Shawn Tan Yi Wei, Tessa Lui Shi Min
    System Dynamics Review.2020; 36(4): 497.     CrossRef
  • Nationwide Trends in Pancreatitis and Pancreatic Cancer Risk Among Patients With Newly Diagnosed Type 2 Diabetes Receiving Dipeptidyl Peptidase 4 Inhibitors
    Minyoung Lee, Jiyu Sun, Minkyung Han, Yongin Cho, Ji-Yeon Lee, Chung Mo Nam, Eun Seok Kang
    Diabetes Care.2019; 42(11): 2057.     CrossRef
  • Clinical Efficacy and Parameters Affecting the Response to Dulaglutide Treatment in Patients with Type 2 Diabetes: A Retrospective, Real-World Data Study
    Jee Hee Yoo, Yun Kyung Cho, Jiwoo Lee, Hwi Seung Kim, Yu Mi Kang, Chang Hee Jung, Joong-Yeol Park, Woo Je Lee
    Diabetes Therapy.2019; 10(4): 1453.     CrossRef
  • Diabetes and the Risk of Infection: A National Cohort Study
    Eun Jin Kim, Kyoung Hwa Ha, Dae Jung Kim, Young Hwa Choi
    Diabetes & Metabolism Journal.2019; 43(6): 804.     CrossRef
  • Current Management of Type 2 Diabetes Mellitus in Primary Care Clinics in Korea
    Da Hea Seo, Shinae Kang, Yong-ho Lee, Jung Yoon Ha, Jong Suk Park, Byoung-Wan Lee, Eun Seok Kang, Chul Woo Ahn, Bong-Soo Cha
    Endocrinology and Metabolism.2019; 34(3): 282.     CrossRef
  • Effects of Blood Pressure and Glucose Levels on Visual Acuity
    Dae-Jong Kim
    Journal of Korean Ophthalmic Optics Society.2019; 24(2): 181.     CrossRef
  • An evaluation of the impact of aggressive hypertension, diabetes and smoking cessation management on CVD outcomes at the population level: a dynamic simulation analysis
    John Pastor Ansah, Ryan Leung Hoe Inn, Salman Ahmad
    BMC Public Health.2019;[Epub]     CrossRef
  • Retracted : Angelica polysaccharide alleviates TNF‐α‐induced MIN6 cell damage a through the up‐regulation microRNA‐143
    Yingying Zhao, Chuanqian Liu, Xueting Zhang, Xipeng Yan
    BioFactors.2019;[Epub]     CrossRef
  • Poor Control of Blood Glucose, Lifestyle, and Cardiometabolic Parameters in Younger Adult Patients with Type 2 Diabetes Mellitus
    Nam, Han, Joo, Kang, Lim, Kim, Park
    Journal of Clinical Medicine.2019; 8(9): 1405.     CrossRef
  • Frailty and Disability in Diabetes
    Sol-Ji Yoon, Kwang-il Kim
    Annals of Geriatric Medicine and Research.2019; 23(4): 165.     CrossRef
  • A Case Report of Increased Blood Sugar in a Diabetic Patient Treated with Socheongryong-tang
    Youngji Kim, Juyeon Song, Seungcheol Hong, Song-won Park, Hakkyeom Kim, Lib Ahn, Dong-jun Choi
    The Journal of Internal Korean Medicine.2019; 40(5): 929.     CrossRef
  • A comparison of sotagliflozin therapy for diabetes mellitus between week 24 with week 52
    Nie Zhang, Zhi-Qun Gu, Yun-Long Ding, Liu Yang, Mao-Bing Chen, Qi-Han Zheng
    Medicine.2019; 98(47): e17976.     CrossRef
  • 2019 Clinical Practice Guidelines for Type 2 Diabetes Mellitus in Korea
    Mee Kyoung Kim, Seung-Hyun Ko, Bo-Yeon Kim, Eun Seok Kang, Junghyun Noh, Soo-Kyung Kim, Seok-O Park, Kyu Yeon Hur, Suk Chon, Min Kyong Moon, Nan-Hee Kim, Sang Yong Kim, Sang Youl Rhee, Kang-Woo Lee, Jae Hyeon Kim, Eun-Jung Rhee, SungWan Chun, Sung Hoon Yu
    Diabetes & Metabolism Journal.2019; 43(4): 398.     CrossRef
  • Letter: Comparison of the Efficacy of Rosuvastatin Monotherapy 20 mg with Rosuvastatin 5 mg and Ezetimibe 10 mg Combination Therapy on Lipid Parameters in Patients with Type 2 Diabetes Mellitus (Diabetes Metab J2019;43:582–9)
    Tae Seo Sohn
    Diabetes & Metabolism Journal.2019; 43(6): 909.     CrossRef
  • The Need to Improve the Quality of Diabetes Care in Korea
    Seung Jin Han, Dae Jung Kim
    Journal of Korean Medical Science.2019;[Epub]     CrossRef
  • Letter: Projection of Diabetes Prevalence in Korean Adults for the Year 2030 Using Risk Factors Identified from National Data (Diabetes Metab J 2019;43:90–6)
    Bo Kyung Koo
    Diabetes & Metabolism Journal.2019; 43(2): 242.     CrossRef
  • Letter: Efficacy and Safety of Voglibose Plus Metformin in Patients with Type 2 Diabetes Mellitus: A Randomized Controlled Trial (Diabetes Metab J 2019;43;276-86)
    Hannah Seok, Tae Seo Sohn
    Diabetes & Metabolism Journal.2019; 43(4): 545.     CrossRef
  • Teneligliptin versus sitagliptin in Korean patients with type 2 diabetes inadequately controlled with metformin and glimepiride: A randomized, double‐blind, non‐inferiority trial
    Yonghyun Kim, Eun Seok Kang, Hak Chul Jang, Dong Jun Kim, Taekeun Oh, Eun Sook Kim, Nan‐Hee Kim, Kyung Mook Choi, Sung‐Rae Kim, JiYoung You, Se‐Jin Kim, Moon‐Kyu Lee
    Diabetes, Obesity and Metabolism.2019; 21(3): 631.     CrossRef
  • Fifty Years of Compassionate Care and Harmonious Collaboration of the Korean Diabetes Association: The 50th Anniversary of Korean Diabetes Association
    Jong Chul Won, Eun-Jung Rhee, Hyung Joon Yoo
    Diabetes & Metabolism Journal.2018; 42(6): 475.     CrossRef
Complications
The Association between Pancreatic Steatosis and Diabetic Retinopathy in Type 2 Diabetes Mellitus Patients
Jee Sun Jeong, Mee Kyung Kim, Kyung Do Han, Oak Kee Hong, Ki-Hyun Baek, Ki-Ho Song, Dong Jin Chung, Jung-Min Lee, Hyuk-Sang Kwon
Diabetes Metab J. 2018;42(5):425-432.   Published online August 9, 2018
DOI: https://doi.org/10.4093/dmj.2017.0107
  • 4,122 View
  • 43 Download
  • 5 Web of Science
  • 4 Crossref
AbstractAbstract PDFPubReader   
Background

Whether pancreatic steatosis has a local or systemic effect, like ectopic fat of other major organs, remains unknown. Data on the influence of pancreatic steatosis on microvascular complication are rare. Therefore, we investigated the relationship between pancreatic steatosis and diabetic retinopathy (DR) in patients with type 2 diabetes mellitus (T2DM).

Methods

The attenuation of three pancreatic regions (head, body, and tail) and the spleen (S) in 186 patients with T2DM was measured using non-enhanced computed tomography imaging. We used three parameters for the assessment of pancreatic steatosis (‘P’ mean: mean attenuation of three pancreatic regions; P–S: difference between ‘P’ mean and ‘S’; P/S: the ‘P’ mean to ‘S’ ratio). The presence of DR was assessed by an expert ophthalmologist using dilated fundoscopy.

Results

The average P mean was 29.02 Hounsfield units (HU), P–S was −18.20 HU, and P/S was 0.61. The three pancreatic steatosis parameters were significantly associated with the prevalence of DR in non-obese T2DM patients. In the non-obese group, the odds ratios of P mean, P–S, and P/S for the prevalence of DR, after adjustment for age, sex, and glycosylated hemoglobin level, were 2.449 (P=0.07), 2.639 (P=0.04), and 2.043 (P=0.02), respectively.

Conclusion

In this study, pancreatic steatosis was significantly associated with DR in non-obese patients with T2DM. Further studies are necessary to clarify the causal relationship between pancreatic steatosis and the development of DR.

Citations

Citations to this article as recorded by  
  • Intra‐pancreatic fat is associated with continuous glucose monitoring metrics
    Yutong Liu, Wandia Kimita, Xiatiguli Shamaitijiang, Loren Skudder‐Hill, Ivana R. Sequeira‐Bisson, Maxim S. Petrov
    Diabetes, Obesity and Metabolism.2024;[Epub]     CrossRef
  • Association between Intrapancreatic Fat Deposition and Lower High-Density Lipoprotein Cholesterol in Individuals with Newly Diagnosed T2DM
    Jianliang Wang, Qingyun Cai, Xiaojuan Wu, Jiaxuan Wang, Xiaona Chang, Xiaoyu Ding, Jia Liu, Guang Wang, Muhittin Yurekli
    International Journal of Endocrinology.2023; 2023: 1.     CrossRef
  • The comparison of pancreatic and hepatic steatosis in healthy liver donor candidates
    Bedriye Koyuncu Sokmen, Tolga Sahin, Alihan Oral, Erdem Kocak, Nagihan Inan
    Scientific Reports.2021;[Epub]     CrossRef
  • Computed Tomography-Estimated Pancreatic Steatosis is Associated with Carotid Plaque in Type 2 Diabetes Mellitus Patients: A Cross-Sectional Study from China
    Pengtao Sun, Chunzhi Fan, Rengui Wang, Tongwei Chu, Xiaoli Sun, Dongxue Zhang, Xuechao Du
    Diabetes, Metabolic Syndrome and Obesity: Targets and Therapy.2021; Volume 14: 1329.     CrossRef
Obesity and Metabolic Syndrome
Comparison of Competitive Models of Metabolic Syndrome Using Structural Equation Modeling: A Confirmatory Factor Analysis
Karimollah Hajian-Tilaki
Diabetes Metab J. 2018;42(5):433-441.   Published online October 22, 2018
DOI: https://doi.org/10.4093/dmj.2018.0010
  • 3,230 View
  • 41 Download
  • 4 Web of Science
  • 4 Crossref
AbstractAbstract PDFPubReader   
Background

The purpose of this study was to apply the structural equation modeling (SEM) to compare the fitness of different competing models (one, two, and three factors) of the metabolic syndrome (MetS) in Iranian adult population.

Methods

Data are given on the cardiometabolic risk factors of 841 individuals with nondiabetic adults from a cross-sectional population-based study of glucose, lipids, and MetS in the north of Iran. The three conceptual hypothesized models (single factor, two correlated factors, and three correlated latent factors) were evaluated by using confirmatory factor analysis with the SEM approach. The summary statistics of correlation coefficients and the model summary fitting indexes were calculated.

Results

The findings show that a single-factor model and a two-correlated factor model had a poorer summary fitting index compared with a three-correlated factor model. All fitting criteria met the conceptual hypothesized three-correlated factor model for both sexes. However, the correlation structure between the three underlying constructs designating the MetS was higher in women than in men.

Conclusion

These results indicate the plausibility of the pathophysiology and etiology of MetS being multifactorial, rather than a single factor, in a nondiabetic Iranian adult population.

Citations

Citations to this article as recorded by  
  • Structural Equation Modelling for Predicting the Relative Contribution of Each Component in the Metabolic Syndrome Status Change
    José E. Teixeira, José A. Bragada, João P. Bragada, Joana P. Coelho, Isabel G. Pinto, Luís P. Reis, Paula O. Fernandes, Jorge E. Morais, Pedro M. Magalhães
    International Journal of Environmental Research and Public Health.2022; 19(6): 3384.     CrossRef
  • New risk score model for identifying individuals at risk for diabetes in southwest China
    Liying Li, Ziqiong Wang, Muxin Zhang, Haiyan Ruan, Linxia Zhou, Xin Wei, Ye Zhu, Jiafu Wei, Sen He
    Preventive Medicine Reports.2021; 24: 101618.     CrossRef
  • Definition and early diagnosis of metabolic syndrome in children
    Gunter Matthias Christian Flemming, Sarah Bussler, Antje Körner, Wieland Kiess
    Journal of Pediatric Endocrinology and Metabolism.2020; 33(7): 821.     CrossRef
  • Calcium-Sensing Receptor in Adipose Tissue: Possible Association with Obesity-Related Elevated Autophagy
    Pamela Mattar, Sofía Sanhueza, Gabriela Yuri, Lautaro Briones, Claudio Perez-Leighton, Assaf Rudich, Sergio Lavandero, Mariana Cifuentes
    International Journal of Molecular Sciences.2020; 21(20): 7617.     CrossRef
Brief Report
Complications
The Necessity of the Simple Tests for Diabetic Peripheral Neuropathy in Type 2 Diabetes Mellitus Patients without Neuropathic Symptoms in Clinical Practice
Jung Hwan Park, Dong Sun Kim
Diabetes Metab J. 2018;42(5):442-446.   Published online October 22, 2018
DOI: https://doi.org/10.4093/dmj.2017.0090
  • 4,355 View
  • 67 Download
  • 15 Web of Science
  • 13 Crossref
AbstractAbstract PDFPubReader   

Early recognition and appropriate management of diabetic peripheral polyneuropathy (DPNP) is important. We evaluated the necessity of simple, non-invasive tests for DPNP detection in clinical practice. We enrolled 136 randomly-chosen patients with type 2 diabetes mellitus and examined them with the 10-g Semmes-Weinstein monofilament examination, the 128-Hz tuning-fork, ankle-reflex, and pinprick tests; the Total Symptom Score and the 15-item self-administered questionnaire of the Michigan Neuropathy Screening Instrument. Among 136 patients, 48 had subjective neuropathic symptoms and 88 did not. The abnormal-response rates varied depending on the methods used according to the presence of subjective neuropathic symptoms (18.8% vs. 5.7%, P<0.05; 58.3% vs. 28.4%, P<0.005; 81.3% vs. 54.5%, P<0.005; 12.5% vs. 5.7%, P=0.195; 41.7% vs. 2.3%, P<0.001; and 77.1% vs. 9.1%, P<0.001; respectively). The largest abnormal response was derived by combining all methods. Moreover, these tests should be implemented more extensively in diabetic patients without neuropathic symptoms to detect DPNP early.

Citations

Citations to this article as recorded by  
  • A Machine Learning-Based Severity Prediction Tool for the Michigan Neuropathy Screening Instrument
    Fahmida Haque, Mamun B. I. Reaz, Muhammad E. H. Chowdhury, Mohd Ibrahim bin Shapiai, Rayaz A. Malik, Mohammed Alhatou, Syoji Kobashi, Iffat Ara, Sawal H. M. Ali, Ahmad A. A. Bakar, Mohammad Arif Sobhan Bhuiyan
    Diagnostics.2023; 13(2): 264.     CrossRef
  • Effect of Diabetic Neuropathy on Reparative Ability and Immune Response System
    Emina Karahmet Sher, Besim Prnjavorac, Esma Karahmet Farhat, Benjamin Palić, Sabah Ansar, Farooq Sher
    Molecular Biotechnology.2023;[Epub]     CrossRef
  • Novel therapeutical approaches based on neurobiological and genetic strategies for diabetic polyneuropathy – A review
    Emina Karahmet Sher, Amina Džidić-Krivić, Alma Karahmet, Merima Beća-Zećo, Esma Karahmet Farhat, Adaleta Softić, Farooq Sher
    Diabetes & Metabolic Syndrome: Clinical Research & Reviews.2023; 17(11): 102901.     CrossRef
  • SUDOSCAN in Combination with the Michigan Neuropathy Screening Instrument Is an Effective Tool for Screening Diabetic Peripheral Neuropathy
    Tae Jung Oh, Yoojung Song, Hak Chul Jang, Sung Hee Choi
    Diabetes & Metabolism Journal.2022; 46(2): 319.     CrossRef
  • Detection of diabetic polyneuropathy in a family medicine clinic by using monofilament
    Biljana Lakic, Verica Petrovic, Maja Racic, Kosana Stanetic
    Vojnosanitetski pregled.2022; 79(4): 383.     CrossRef
  • Association between Sleep Quality and Painless Diabetic Peripheral Neuropathy Assessed by Current Perception Threshold in Type 2 Diabetes Mellitus
    Dughyun Choi, Bo-Yeon Kim, Chan-Hee Jung, Chul-Hee Kim, Ji-Oh Mok
    Diabetes & Metabolism Journal.2021; 45(3): 358.     CrossRef
  • Diabetic neuropathies
    Kamakshi Patel, Holli Horak, Ezgi Tiryaki
    Muscle & Nerve.2021; 63(1): 22.     CrossRef
  • Diabetic peripheral neuropathy
    Joyce K. Anastasi, Chloe Klug
    Nursing.2021; 51(4): 34.     CrossRef
  • A nomogram-based diabetic sensorimotor polyneuropathy severity prediction using Michigan neuropathy screening instrumentations
    Fahmida Haque, Mamun Bin Ibne Reaz, Muhammad E.H. Chowdhury, Sawal Hamid Md Ali, Ahmad Ashrif A Bakar, Tawsifur Rahman, Syoji Kobashi, Chitra A. Dhawale, Mohammad Arif Sobhan Bhuiyan
    Computers in Biology and Medicine.2021; 139: 104954.     CrossRef
  • Diabetic Peripheral Neuropathy: Is it Underdiagnosed?
    Rizaldy T. Pinzon, M. Kes, Rosa De Lima R. Sa
    Asian Journal of Biological Sciences.2020; 13(2): 168.     CrossRef
  • Risk factors associated with the progression of overactive bladder among patients with type 2 diabetes
    Yiyi Zhu, Zaisheng Zhu, Jiajun Chen
    International Journal of Clinical Practice.2019;[Epub]     CrossRef
  • Response: The Necessity of the Simple Tests for Diabetic Peripheral Neuropathy in Type 2 Diabetes Mellitus Patients without Neuropathic Symptoms in Clinical Practice (Diabetes Metab J 2018;42:442–6)
    Jung Hwan Park, Dong Sun Kim
    Diabetes & Metabolism Journal.2018; 42(6): 546.     CrossRef
  • Letter: The Necessity of the Simple Tests for Diabetic Peripheral Neuropathy in Type 2 Diabetes Mellitus Patients without Neuropathic Symptoms in Clinical Practice (Diabetes Metab J 2018;42:442-6)
    Jun Hwa Hong
    Diabetes & Metabolism Journal.2018; 42(6): 544.     CrossRef
Letter
Letter: Cardio-Ankle Vascular Index as a Surrogate Marker of Early Atherosclerotic Cardiovascular Disease in Koreans with Type 2 Diabetes Mellitus (Diabetes Metab J 2018;42:285-95)
Dongwon Yi
Diabetes Metab J. 2018;42(5):447-448.   Published online October 22, 2018
DOI: https://doi.org/10.4093/dmj.2018.0185
  • 2,515 View
  • 31 Download
  • 1 Crossref
PDFPubReader   

Citations

Citations to this article as recorded by  
  • M2AI-CVD: Multi-modal AI approach cardiovascular risk prediction system using fundus images
    Premalatha Gurumurthy, Manjunathan Alagarsamy, Sangeetha Kuppusamy, Niranjana Chitra Ponnusamy
    Network: Computation in Neural Systems.2024; : 1.     CrossRef
Response

Diabetes Metab J : Diabetes & Metabolism Journal