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Metabolic syndrome as a predictor of type 2 diabetes, and its clinical interpretations and usefulness.

Authors :
Shin, Jeong‐Ah
Lee, Jin‐Hee
Lim, Sun‐Young
Ha, Hee‐Sung
Kwon, Hyuk‐Sang
Park, Yong‐Moon
Lee, Won‐Chul
Kang, Moo‐Il
Yim, Hyeon‐Woo
Yoon, Kun‐Ho
Son, Ho‐Young
Source :
Journal of Diabetes Investigation. Jul2013, Vol. 4 Issue 4, p334-343. 10p.
Publication Year :
2013

Abstract

Metabolic syndrome is defined as a cluster of glucose intolerance, hypertension, dyslipidemia and central obesity with insulin resistance as the source of pathogenesis. Although several different combinations of criteria have been used to define metabolic syndrome, a recently published consensus recommends the use of ethnic-specific criteria, including waist circumference as an indicator of central obesity, triglyceride and high-density lipoprotein ( HDL) cholesterol as indicators of dyslipidemia, and blood pressure greater than 130/85 mmHg. The definition of dysglycemia, and whether central obesity and insulin resistance are essential components remain controversial. Regardless of the definition, the prevalence of metabolic syndrome is increasing in Western and Asian countries, particularly in developing areas undergoing rapid socioenvironmental changes. Numerous clinical trials have shown that metabolic syndrome is an important risk factor for cardiovascular disease ( CVD), type 2 diabetes mellitus and all-cause mortality. Therefore, metabolic syndrome might be useful as a practical tool to predict these two major metabolic disorders. Comprehensive management of risk factors is very important to the improvement of personal and public health. However, recent studies have focused on the role metabolic syndrome plays as a risk factor for CVD; its importance in the prediction of incident diabetes is frequently overlooked. In the present review, we summarize the known evidence supporting metabolic syndrome as a predictor for type 2 diabetes mellitus and CVD. Additionally, we suggest how metabolic syndrome might be useful in clinical practice, especially for the prediction of diabetes. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20401116
Volume :
4
Issue :
4
Database :
Academic Search Index
Journal :
Journal of Diabetes Investigation
Publication Type :
Academic Journal
Accession number :
88930931
Full Text :
https://doi.org/10.1111/jdi.12075