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Cohort study evaluation of New Chinese Diabetes Risk Score: A new non-invasive indicator for predicting metabolic syndrome
Primary Care Diabetes ( IF 2.6 ) Pub Date : 2021-05-21 , DOI: 10.1016/j.pcd.2021.05.005
Yifei Feng 1 , Xingjin Yang 1 , Yang Li 2 , Minghui Han 1 , Ranran Qie 1 , Shengbing Huang 1 , Xiaoyan Wu 2 , Yanyan Zhang 2 , Yuying Wu 2 , Dechen Liu 3 , Fulan Hu 2 , Ming Zhang 2 , Yongli Yang 1 , Xuezhong Shi 1 , Jie Lu 1 , Sun Liang 4 , Dongsheng Hu 1 , Yang Zhao 1
Affiliation  

Objectives

To investigate the association of the baseline New Chinese Diabetes Risk Score (NCDRS) with metabolic syndrome (MetS) risk and to evaluate the power of the baseline NCDRS to predict MetS based on the rural Chinese cohort study.

Methods

Study participants were classified by baseline quartiles of NCDRS by gender. Multivariable logistic regression was used to calculate odds ratios (ORs) and 95% confidence intervals (CIs) for risk of MetS according to different diagnostic criteria. The receiver operating characteristic curve (ROC) and area under the ROC curve (AUC) were used to evaluate the power of the baseline NCDRS for predicting MetS according to different diagnostic criteria.

Results

We included 7,133 participants, and 1,651 MetS cases were identified after 6 years follow-up. After adjusting for multivariable confounding factors and with NCDRS quartile 1 as the reference, with quartile 4, the risk of MetS was increased for all participants, men and women: ORs (95% CIs) 4.03 (3.23−5.02), 3.59 (2.56−5.05) and 5.71 (4.23−7.70), respectively. Similar results were found on sensitivity analysis. The baseline NCDRS was a good predictor of MetS for all participants, men and women with MetS defined according to the diagnostic criteria of the Chinese Joint Committee on the Development of Guidelines for the Prevention and Treatment of Dyslipidemia in Adults (JCDCG).

Conclusions

Our study, based on the cohort study, found that the baseline NCDRS was positively associated with risk of MetS. Furthermore, our study might provide suggestions for developing a useful and inexpensive tool for predicting MetS in the Chinese population.

更新日期:2021-05-21
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