Diabetes & Metabolism Journal

Original Articles

Lifesytle
Changes in the Quality of Life in Patients with Type 2 Diabetes Mellitus According to Physician and Patient Behaviors: Young-Joo Kim, In-Kyung Jeong, Sin-Gon Kim, Dong Hyeok Cho, Chong-Hwa Kim, Chul-Sik Kim, Won-Young Lee, Kyu-Chang Won, Jin-Hye Cha, Juneyoung Lee, Doo-Man Kim; Diabetes Metab J. 2020;44(1):91-102. Published online October 23, 2019; DOI: https://doi.org/10.4093/dmj.2018.0251

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Background

Diabetes mellitus (DM) is the most common chronic metabolic disorder with an increasing prevalence worldwide. According to a previous study, physicians' treatment patterns or patients' behaviors change when they become aware of the risk for cardiovascular (CV) disease in patients with DM. However, there exist controversial reports from previous studies in the impact of physicians' behaviors on the patients' quality of life (QoL) improvements. So we investigate the changes in QoL according to physicians and patients' behavioral changes after the awareness of CV risks in patients with type 2 DM.

Methods

Data were obtained from a prospective, observational study where 799 patients aged ≥40 years with type 2 DM were recruited at 24 tertiary hospitals in Korea. Changes in physicians' behaviors were defined as changes in the dose/type of antihypertensive, lipid-lowering, and anti-platelet therapies within 6-month after the awareness of CV risks in patients. Changes in patients' behaviors were based on lifestyle modifications. Audit of Diabetes Dependent Quality of Life comprising 19-life-domains was used.

Results

The weighted impact score change for local or long-distance journey (P=0.0049), holidays (P=0.0364), and physical health (P=0.0451) domains significantly differed between the two groups; patients whose physician's behaviors changed showed greater improvement than those whose physician's behaviors did not change.

Conclusion

This study demonstrates that changes in physicians' behaviors, as a result of perceiving CV risks, improve QoL in some domains of life in DM patients. Physicians should recognize the importance of understanding CV risks and implement appropriate management.

Citations

Citations to this article as recorded by

Spline Longitudinal Multi-response Model for the Detection of Lifestyle- Based Changes in Blood Glucose of Diabetic Patients
Anna Islamiyati
Current Diabetes Reviews.2022;[Epub] CrossRef
Characteristics of Glycemic Control and Long-Term Complications in Patients with Young-Onset Type 2 Diabetes
Han-sang Baek, Ji-Yeon Park, Jin Yu, Joonyub Lee, Yeoree Yang, Jeonghoon Ha, Seung Hwan Lee, Jae Hyoung Cho, Dong-Jun Lim, Hun-Sung Kim
Endocrinology and Metabolism.2022; 37(4): 641. CrossRef
Agriophyllum Oligosaccharides Ameliorate Diabetic Insulin Resistance Through INS-R/IRS/Glut4-Mediated Insulin Pathway in db/db Mice and MIN6 Cells
Shuyin Bao, Xiuzhi Wang, Sung Bo Cho, Yan-Ling Wu, Chengxi Wei, Shuying Han, Liming Bao, Qiong Wu, Wuliji Ao, Ji-Xing Nan
Frontiers in Pharmacology.2021;[Epub] CrossRef
Glycolipid metabolism and liver transcriptomic analysis of the therapeutic effects of pressed degreased walnut meal extracts on type 2 diabetes mellitus rats
Yulan Li, Dan Chen, Chengmei Xu, Qingyujing Zhao, Yage Ma, Shenglan Zhao, Chaoyin Chen
Food & Function.2020; 11(6): 5538. CrossRef
Cause-of-death statistics in 2018 in the Republic of Korea
Hyun-Young Shin, Jin Kim, Seokmin Lee, Min Sim Park, Sanghee Park, Sun Huh
Journal of the Korean Medical Association.2020; 63(5): 286. CrossRef

Is A1C Variability an Independent Predictor for the Progression of Atherosclerosis in Type 2 Diabetic Patients?: Chul Sik Kim, So Young Park, Sung Hoon Yu, Jun Goo Kang, Ohk Hyun Ryu, Seong Jin Lee, Eun Gyung Hong, Hyeon Kyu Kim, Doo-Man Kim, Jae Myung Yoo, Sung Hee Ihm, Moon Gi Choi, Hyung Joon Yoo; Korean Diabetes J. 2010;34(3):174-181. Published online June 30, 2010; DOI: https://doi.org/10.4093/kdj.2010.34.3.174

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Background

Little is known about the relative contribution of long-term glycemic variability to the risk of macrovascular complications in type 2 diabetes. This study was conducted to evaluate the effect of A1C variability on the progression of carotid artery intima-media thickness (IMT) in type 2 diabetic patients.

Methods

Among type 2 diabetic patients who visited Hallym University Sacred Heart Hospital from March 2007 to September 2009, 120 patients who had carotid artery IMT measured annually and A1C checked every three months for at least one year were analyzed. Individual A1C variability was defined as the standard deviation (SD) of five A1C levels taken every three months for approximately one year. Change in IMT was defined as an increase in IMT on follow-up measurement. The association between the SD of A1C and changes in IMT was evaluated.

Results

With greater A1C variability, there was a greater increase in the mean IMT (r = 0.350, P < 0.001) of the carotid artery. After adjusting for confounding factors that may influence IMT, A1C variability was significantly associated with the progression of IMT (r = 0.222, P = 0.034). However, the SD of A1C was not a significant independent risk factor for the progression of IMT in multiple regression analysis (β = 0.158, P = 0.093).

Conclusion

Higher A1C variability is associated with IMT progression in type 2 diabetic patients; however, it is not an independent predictor of IMT progression. Overall glycemic control is the most important factor in the progression of IMT.

Citations

Citations to this article as recorded by

Long-Term Risk of Cardiovascular Disease Among Type 2 Diabetes Patients According to Average and Visit-to-Visit Variations of HbA1c Levels During the First 3 Years of Diabetes Diagnosis
Hyunah Kim, Da Young Jung, Seung-Hwan Lee, Jae-Hyoung Cho, Hyeon Woo Yim, Hun-Sung Kim
Journal of Korean Medical Science.2023;[Epub] CrossRef
Association Between Long-Term Visit-to-Visit Hemoglobin A1c and Cardiovascular Risk in Type 2 Diabetes: The ACCORD Trial
Dan Huang, Yong-Quan Huang, Qun-Ying Zhang, Yan Cui, Tian-Yi Mu, Yin Huang
Frontiers in Cardiovascular Medicine.2021;[Epub] CrossRef
Association of Longitudinal Values of Glycated Hemoglobin With Cardiovascular Events in Patients With Type 2 Diabetes and Multivessel Coronary Artery Disease
Paulo Cury Rezende, Mark Andrew Hlatky, Whady Hueb, Rosa Maria Rahmi Garcia, Luciano da Silva Selistre, Eduardo Gomes Lima, Cibele Larrosa Garzillo, Thiago Luis Scudeler, Gustavo Andre Boeing Boros, Fernando Faglioni Ribas, Carlos Vicente Serrano, Jose An
JAMA Network Open.2020; 3(1): e1919666. CrossRef
Haemoglobin A1c variability as an independent correlate of atherosclerosis and cardiovascular disease in Chinese type 2 diabetes
Yifei Mo, Jian Zhou, Xiaojing Ma, Wei Zhu, Lei Zhang, Jie Li, Jingyi Lu, Cheng Hu, Yuqian Bao, Weiping Jia
Diabetes and Vascular Disease Research.2018; 15(5): 402. CrossRef
Relationship of HbA1c variability, absolute changes in HbA1c, and all-cause mortality in type 2 diabetes: a Danish population-based prospective observational study
Mette V Skriver, Annelli Sandbæk, Jette K Kristensen, Henrik Støvring
BMJ Open Diabetes Research & Care.2015; 3(1): e000060. CrossRef
Association between hemoglobin A1c variability and subclinical coronary atherosclerosis in subjects with type 2 diabetes
Hae Kyung Yang, Borami Kang, Seung-Hwan Lee, Kun-Ho Yoon, Byung-Hee Hwang, Kiyuk Chang, Kyungdo Han, Gunseog Kang, Jae Hyoung Cho
Journal of Diabetes and its Complications.2015; 29(6): 776. CrossRef
Glycated hemoglobin as a marker of subclinical atherosclerosis and cardiac remodeling among non-diabetic adults from the general population
Robin Haring, Sebastian E. Baumeister, Wolfgang Lieb, Bettina von Sarnowski, Henry Völzke, Stephan B. Felix, Matthias Nauck, Henri Wallaschofski
Diabetes Research and Clinical Practice.2014; 105(3): 416. CrossRef
HbA1c Variability and Micro- and Macrovascular Complications of Diabetes
Hae Kyung Yang, Seung-Hwan Lee
The Journal of Korean Diabetes.2014; 15(4): 202. CrossRef
HbA1c variability and the development of microalbuminuria in type 2 diabetes: Tsukuba Kawai Diabetes Registry 2
A. Sugawara, K. Kawai, S. Motohashi, K. Saito, S. Kodama, Y. Yachi, R. Hirasawa, H. Shimano, K. Yamazaki, H. Sone
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