KMID : 1039620170070010110
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Korean Journal of Family Practice 2017 Volume.7 No. 1 p.110 ~ p.115
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A Comparison of Predictability of Physician-Diagnosed Diabetes according to Metabolic Syndrome Components: A Nationwide Population-Based Retrospective Cohort Study
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Sang Jung-Eun
Lee Jong-Eun Choi Jun-Seok Huh Youn Nam Hyo-Yun Nam Ga-Eun Kim Do-Hoon Han Kyung-Do
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Abstract
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Background: Metabolic syndrome is associated with an increased risk of cardiovascular disease and diabetes. However, in Korea, the association between metabolic syndrome components and diabetes has been examined only by cross-sectional survey. This study aimed to identify the association between metabolic syndrome components and risk of developing diabetes of diabetes in the National Health Insurance Service-National Sample Cohort (NHIS-NSC).
Methods: Data were obtained from the NHIS-NSC between 2010 and 2013. Out of a total of 211,541 eligible individuals, the following were excluded: 25,133 under the age of 30 years; 180 with incomplete information; and 19 with diabetes at baseline. Finally, 166,257 subjects were included in the study. Statistical analysis was performed using the independent t-test and chi-square test. The association between metabolic syndrome and the risk of developing diabetes was estimated by using Cox multivariable regression analysis.
Results: During the follow-up, 4,405 were diagnosed with diabetes among total 166,257 participants.
Conclusion: Metabolic syndrome as well as the individual components is associated with an increased risk of diabetes after adjusting for age and sex, body mass index, smoking status, alcohol intake, and physical activity. During the 4-year follow up, the risk for incident rate of diabetes increased with the number of metabolic syndrome components. It has been also suggested that the metabolic syndrome component most strongly associated with incident diabetes was high fasting blood glucose.
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KEYWORD
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Metabolic Syndrome X, Diabetes Mellitus, Impaired Fasting Glucose, National Health Insurance Service-National Sample Cohort
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