Metabolic Syndrome and Its Components Predict the Risk of Type 2 Diabetes Mellitus in the Mainland Chinese: A 3-Year Cohort Study. (13th December 2018)

• Record Type: Journal Article
• Authors: Wang, Kun; Yang, Qun-Fang; Chen, Xing-Lin; Liu, Yu-Wei; Shan, Sheng-Shuai; Zheng, Hua-Bo; Zhao, Xiao-Fang; Chen, Chang-Zhong; Liu, Cheng-Yun
• Other Names: Laganà Antonio Simone Academic Editor.
• Is Part Of: International journal of endocrinology. Volume 2018(2018)
• Publication Date: 2018-12-13
• Subjects: Endocrinology -- Periodicals; Endocrinology; Endocrinology -- Periodicals; Endocrine System Diseases -- Periodicals; Periodicals; 616.4
• DOI: 10.1155/2018/9376179
• Languages: English
• ISSNs: 1687-8337

Abstract

Abstract : Introduction . It has well established that metabolic syndrome (MetS) can predict the risk of type 2 diabetes mellitus (T2DM) in some population groups. However, limited evidence is available regarding the predictive effect of MetS for incident T2DM in mainland Chinese population. Methods . A 3-year cohort study was performed for 9735 Chinese without diabetes at baseline. MetS and its components were assessed by multivariable analysis using Cox regression. Prediction models were developed. Discrimination was assessed with area under the receiver operating characteristic curves (AUCs), and performance was assessed by a calibration curve. Results . The 3-year cumulative incidence of T2DM was 11.29%. Baseline MetS was associated with an increased risk of T2DM after adjusting for age (HR = 2.68, 95% CI, 2.27–3.17 in males; HR = 2.59, 95% CI, 1.83–3.65 in females). Baseline MetS exhibited relatively high specificity (88% in males, 94% in females) and high negative predictive value (90% in males, 94% in females) but low sensitivity (36% in males, 23% in females) and low positive predictive value (31% in males and females) for predicting the 3-year risk of T2DM. AUCs, including age and components of MetS, for the prediction model were 0.779 (95% CI: 0.759–0.799) in males and 0.860 (95% CI: 0.836–0.883) in females. Calibration curves revealed good agreement between prediction and observation results in males; however, the model could overestimate the risk when the predicted probability is >40% in females. Conclusions . MetS predicts the risk of T2DM. The quantitative MetS-based prediction model for T2DM risk may improve preventive strategies for T2DM and present considerable public health benefits for the people in mainland China.