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Published on: January 7, 2018
Association between insulin resistance and multiple chronic diseases: a cross-sectional study from CHARLS
Wen-Ze Jiang1, Zhen-Liang Fan2, Meng-Li Xu1
1The Third Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, China.
Background:
Chronic disease is a global public health problem. This study aimed to explore the association between insulin resistance (IR)-related indices and various chronic diseases, and to evaluate the predictive capacity of IR-related indices for these diseases.
Methods:
The data used in this study came from CHARLS. Binary logistic regression analysis and RCS were used to analyze the relationship between IR-related indices, including TyG, TyG-BMI, TyG-WHtR, METS-IR and eGDR, with nine chronic diseases. Subgroup analysis was performed to test the stability of the results. Finally, the predictive power of IR-related indices for chronic diseases was tested by ROC curve.
Results:
A total of 8,177 participants were included in this study. The study found that elevated prevalence of multiple chronic diseases is positively associated with increases in TyG, TyG-BMI, TyG-WHtR, and METS-IR, and negatively associated with eGDR. ROC analysis revealed that IR-related indices had the best accuracy in predicting dyslipidemia compared to other diseases, with TyG being the best predictor.
Conclusions:
IR-related indices were positively associated with the prevalence of multiple chronic diseases. The burden of chronic diseases can be reduced by improving IR in middle-aged and older people.
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