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Corrigendum
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 Metab J. 2020;44(5):783-783.   Published online October 21, 2020
DOI: https://doi.org/10.4093/dmj.2020.0245
Corrects: Diabetes Metab J 2020;44(4):592
  • 3,954 View
  • 94 Download
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Original Article
Clinical Complications
Incidence and Risk Factors for Dementia in Type 2 Diabetes Mellitus: A Nationwide Population-Based Study in Korea
Ji Hee Yu, Kyungdo Han, Sanghyun Park, Hanna Cho, Da Young Lee, Jin-Wook Kim, Ji A Seo, Sin Gon Kim, Sei Hyun Baik, Yong Gyu Park, Kyung Mook Choi, Seon Mee Kim, Nan Hee Kim
Diabetes Metab J. 2020;44(1):113-124.   Published online November 12, 2019
DOI: https://doi.org/10.4093/dmj.2018.0216
  • 7,897 View
  • 199 Download
  • 31 Web of Science
  • 32 Crossref
AbstractAbstract PDFSupplementary MaterialPubReader   
Background

Diabetes mellitus is associated with an increased risk of dementia. We aimed to comprehensively analyze the incidence and risk factors for dementia and young-onset dementia (YOD) in diabetic patients in Korea using the National Health Insurance Service data.

Methods

Between January 1, 2009 and December 31, 2012, a total of 1,917,702 participants with diabetes were included and followed until the date of dementia diagnosis or until December 31, 2015. We evaluated the incidence and risk factors for all dementia, Alzheimer's disease (AD), and vascular dementia (VaD) by Cox proportional hazards analyses. We also compared the impact of risk factors on the occurrence of YOD and late-onset dementia (LOD).

Results

During an average of 5.1 years of follow-up, the incidence of all types of dementia, AD, or VaD was 9.5, 6.8, and 1.3/1,000 person-years, respectively, in participants with diabetes. YOD comprised 4.8% of all dementia occurrence, and the ratio of AD/VaD was 2.1 for YOD compared with 5.5 for LOD. Current smokers and subjects with lower income, plasma glucose levels, body mass index (BMI), and subjects with hypertension, dyslipidemia, vascular complications, depression, and insulin treatment developed dementia more frequently. Vascular risk factors such as smoking, hypertension, and previous cardiovascular diseases were more strongly associated with the development of VaD than AD. Low BMI and a history of stroke or depression had a stronger influence on the development of YOD than LOD.

Conclusion

The optimal management of modifiable risk factors may be important for preventing dementia in subjects with diabetes mellitus.

Citations

Citations to this article as recorded by  
  • Unlocking the Protective Potential of Upper Respiratory Infection Treatment Histories against Alzheimer’s Disease: A Korean Adult Population Study
    Ho Suk Kang, Ji Hee Kim, Joo-Hee Kim, Woo Jin Bang, Hyo Geun Choi, Nan Young Kim, Ha Young Park, Mi Jung Kwon
    Journal of Clinical Medicine.2024; 13(1): 260.     CrossRef
  • Hepatopancreatic metabolic disorders and their implications in the development of Alzheimer's disease and vascular dementia
    Francisco I. Pinheiro, Irami Araújo-Filho, Amália C.M. do Rego, Eduardo P. de Azevedo, Ricardo N. Cobucci, Fausto P. Guzen
    Ageing Research Reviews.2024; 96: 102250.     CrossRef
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    Juhyun Song
    Biomedicine & Pharmacotherapy.2023; 162: 114647.     CrossRef
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    Sunyoung Cho, Choon Ok Kim, Bong-soo Cha, Eosu Kim, Chung Mo Nam, Min-Gul Kim, Min Soo Park
    Diabetes Research and Clinical Practice.2023; 201: 110721.     CrossRef
  • Association of triglyceride/high-density lipoprotein cholesterol ratio with severe complications of COVID-19
    Yoonkyung Chang, Jimin Jeon, Tae-Jin Song, Jinkwon Kim
    Heliyon.2023; 9(6): e17428.     CrossRef
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    Wenhui Lei, Yiwen Cheng, Jie Gao, Xia Liu, Li Shao, Qingming Kong, Nengneng Zheng, Zongxin Ling, Weiming Hu
    Frontiers in Cellular and Infection Microbiology.2023;[Epub]     CrossRef
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    Jiayi Feng, Cuihong Huang, Lei Liang, Chuang Li, Xiaojie Wang, Jianping Ma, Xinhui Guan, Bin Jiang, Shaofen Huang, Pei Qin
    Journal of the American Medical Directors Association.2023; 24(9): 1363.     CrossRef
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    Hee-Cheol Kim, Ho-Jun Lee, Yang-Tae Kim, Byeong-Churl Jang, Asirvatham Alwin Robert
    Journal of Diabetes Research.2023; 2023: 1.     CrossRef
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    Gratianne Rabiller, Zachary Ip, Shahram Zarrabian, Hongxia Zhang, Yoshimichi Sato, Azadeh Yazdan-Shahmorad, Jialing Liu
    Aging and disease.2023;[Epub]     CrossRef
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    Mingyang Sun, Zhongyuan Lu, Wan-Ming Chen, Szu-Yuan Wu, Jiaqiang Zhang
    Brain Communications.2023;[Epub]     CrossRef
  • Association of periodontitis with microvascular complications of diabetes mellitus: A nationwide cohort study
    Moo-Seok Park, Jimin Jeon, Tae-Jin Song, Jinkwon Kim
    Journal of Diabetes and its Complications.2022; 36(2): 108107.     CrossRef
  • Association between oral health and cardiovascular outcomes in patients with hypertension: a nationwide cohort study
    Jinkwon Kim, Hyung Jun Kim, Jimin Jeon, Tae-Jin Song
    Journal of Hypertension.2022; 40(2): 374.     CrossRef
  • Diabetic retinopathy and cognitive dysfunction: a systematic review and meta-analysis
    Mei Wu, Fan Mei, Kaiyan Hu, Liyuan Feng, Zhe Wang, Qianqian Gao, Fei Chen, Li Zhao, Xiaohui Li, Bin Ma
    Acta Diabetologica.2022; 59(4): 443.     CrossRef
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    Yeng Yan Chow, Milou Verdonschot, Claire T. McEvoy, Geeske Peeters
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  • Diabetes Mellitus: A Path to Amnesia, Personality, and Behavior Change
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    Hee Kyung Kim, Juhyun Song
    International Journal of Molecular Sciences.2022; 23(6): 2982.     CrossRef
  • Type 2 Diabetes Mellitus as a Risk Factor for Alzheimer’s Disease: Review and Meta-Analysis
    Athanasia Athanasaki, Konstantinos Melanis, Ioanna Tsantzali, Maria Ioanna Stefanou, Sofia Ntymenou, Sotirios G. Paraskevas, Theodosis Kalamatianos, Eleni Boutati, Vaia Lambadiari, Konstantinos I. Voumvourakis, George Stranjalis, Sotirios Giannopoulos, Ge
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  • Cumulative Exposure to Metabolic Syndrome Components and the Risk of Dementia: A Nationwide Population-Based Study
    Yunjung Cho, Kyungdo Han, Da Hye Kim, Yong-Moon Park, Kun-Ho Yoon, Mee Kyoung Kim, Seung-Hwan Lee
    Endocrinology and Metabolism.2021; 36(2): 424.     CrossRef
  • Cardiovascular risks of periodontitis and oral hygiene indicators in patients with diabetes mellitus
    Tae-Jin Song, Jimin Jeon, Jinkwon Kim
    Diabetes & Metabolism.2021; 47(6): 101252.     CrossRef
  • Association Between Diabetic Retinopathy and Cognitive Impairment: A Systematic Review and Meta-Analysis
    Dihe Cheng, Xue Zhao, Shuo Yang, Guixia Wang, Guang Ning
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  • Letter: Hypoglycemia and Dementia Risk in Older Patients with Type 2 Diabetes Mellitus: A Propensity-Score Matched Analysis of a Population-Based Cohort Study (Diabetes Metab J 2020;44:125–33)
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Short Communication
Epidemiology
Associations between Breastfeeding and Type 2 Diabetes Mellitus and Glycemic Control in Parous Women: A Nationwide, Population-Based Study
Ga Eun Nam, Kyungdo Han, Do-Hoon Kim, Youn Huh, Byoungduck Han, Sung Jung Cho, Yong Gyu Park, Yong-Moon Park
Diabetes Metab J. 2019;43(2):236-241.   Published online December 21, 2018
DOI: https://doi.org/10.4093/dmj.2018.0044
  • 4,047 View
  • 45 Download
  • 3 Web of Science
  • 3 Crossref
AbstractAbstract PDFPubReader   

We investigated associations between breastfeeding duration and number of children breastfed and type 2 diabetes mellitus (T2DM) and glycemic control among parous women. We performed a cross-sectional analysis of data for 9,960 parous women from the Korea National Health and Nutritional Examination Survey (2010 to 2013). Having ever breastfed was inversely associated with prevalent T2DM (adjusted odds ratio [OR], 0.60; 95% confidence interval [CI], 0.42 to 0.87). All ranges of total and average breastfeeding duration showed inverse associations with T2DM. Even short periods of breastfeeding were inversely associated with T2DM (adjusted OR, 0.61; 95% CI, 0.38 to 0.99 for a total breastfeeding duration ≤12 months; adjusted OR, 0.65; 95% CI, 0.42 to 0.99 for an average breastfeeding duration per child ≤6 months). A longer duration of breastfeeding was associated with better glycemic control in parous women with T2DM (P trend=0.004 for total breastfeeding duration; P trend <0.001 for average breastfeeding duration per child). Breastfeeding may be associated with a lower risk of T2DM and good glycemic control in parous women with T2DM. Breastfeeding may be a feasible method to prevent T2DM and improve glycemic control.

Citations

Citations to this article as recorded by  
  • Integration of nutrigenomics, melatonin, serotonin and inflammatory cytokines in the pathophysiology of pregnancy-specific urinary incontinence in women with gestational diabetes mellitus
    Danielle Cristina Honorio França, Eduardo Luzía França, Luis Sobrevia, Angélica Mércia Pascon Barbosa, Adenilda Cristina Honorio-França, Marilza Vieira Cunha Rudge
    Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease.2023; 1869(6): 166737.     CrossRef
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    Ana‐Catarina Pinho‐Gomes, Georgia Morelli, Alexandra Jones, Mark Woodward
    Diabetes, Obesity and Metabolism.2021; 23(8): 1902.     CrossRef
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    Laura T. Dickens, Celeste C. Thomas
    Current Diabetes Reports.2019;[Epub]     CrossRef
Original Article
Clustering Characteristics of Risk Variables of Metabolic Syndrome in Korean Rural Populations.
Yong Moon Park, Hyuk Sang Kwon, Sun Young Lim, Jin Hee Lee, Sung Rae Kim, Kun Ho Yoon, Bong Yun Cha, Ho Young Son, Yong Gyu Park, Dong Suk Kim, Kwang ho Meng, Won Chul Lee
Korean Diabetes J. 2006;30(3):177-189.   Published online May 1, 2006
DOI: https://doi.org/10.4093/jkda.2006.30.3.177
  • 2,236 View
  • 17 Download
  • 4 Crossref
AbstractAbstract PDF
BACKGROUND
The risks of both type 2 diabetes mellitus and cardiovascular disease are mainly associated with the metabolic syndrome which is characterized by clustering of metabolic risk factors, including abdominal obesity, glucose intolerance, hypertension, and dyslipidemia. This study aimed to examine the relations among metabolic risk variables and the underlying structure of the metabolic syndrome that unites related components. METHODS: Subjects were selected by stratified random cluster sampling among persons aged over 40 years from a rural area. Waist circumference, BMI, fasting glucose, fasting insulin, triglycerides, HDL cholesterol, systolic blood pressure, and diastolic blood pressure were used as risk variables of metabolic syndrome. Factor analysis, a multivariate correlation statistical technique, was performed on a dataset from nondiabetic 3,443 men and women without history of coronary heart disease. RESULTS: Exploratory factor analysis identified three factors in both gender (obesity, hypertension, and dyslipidemia-insulin resistance in men; obesity-insulin resistance, hypertension, and dyslipidemia in women). Fasting insulin was a common contributor to the structure of metabolic syndrome in male subjects, smokers and alcohol drinking group. Confirmatory factor analysis based on the results of exploratory factor analysis revealed that metabolic syndrome was represented primarily by obesity factor in men, obesity-insulin resistance factor in women, and that dyslipidemia factor was highly correlated with obesity factor in men, with insulin resistance factor in women. CONCLUSION: Underlying structure of metabolic syndrome was different between men and women, and obesity might be a primary target for prevention of both type 2 diabetes mellitus and cardiovascular disease in Korea.

Citations

Citations to this article as recorded by  
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    Maurizio Vichi
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  • Optimal Waist Circumference Cutoff Value Reflecting Insulin Resistance as a Diagnostic Criterion of Metabolic Syndrome in a Nondiabetic Korean Population Aged 40 Years and Over: The Chungju Metabolic Disease Cohort (CMC) Study
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  • Prevalence, Awareness, Treatment, and Control of Hypertension Among People Over 40 Years Old in a Rural Area of South Korea: The Chungju Metabolic Disease Cohort (CMC) Study
    Hong-Seok Lee, Yong-Moon Park, Hyuk-Sang Kwon, Jin-Hee Lee, Young Joon Park, Sun Young Lim, Seung-Hwan Lee, Kun-Ho Yoon, Ho-Young Son, Dong Suk Kim, Hyeon Woo Yim, Won-Chul Lee
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Diabetes Metab J : Diabetes & Metabolism Journal