Chinese visceral adiposity index outperforms insulin resistance indices in predicting cardiovascular disease risk: a
Weiyan Tu1, Rongdi Xu2, Na Luo3
1Shanghai Key Laboratory of Maternal-Fetal Medicine, Shanghai Institute of Maternal-Fetal Medicine and Gynecologic Oncology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai, China.
Aims:
This study investigated and compared the abilities of seven insulin resistance (IR) indices, including the triglyceride-glucose index (TyG), TyG-waist circumference (TyG-WC), TyG-waist-to-hip ratio (TyG-WHtR), lipid accumulation product (LAP), visceral adiposity index (VAI), Chinese visceral adiposity index (CVAI), and metabolic score for insulin resistance (METS-IR) to predict cardiovascular disease (CVD) among participants without a history of CVD.
Methods:
The population was recruited from the prospective Asymptomatic Polyvascular Abnormalities Community (APAC) Study in Hebei. This prospective study included 5,194 individuals without history of CVD who were stratified into CVD group and non-CVD group. The seven IR indices (TyG, TyG-WC, TyG-WHtR, LAP, VAI, CVAI, and METS-IR) were calculated. The primary endpoint was CVD.
Results:
Over a 12-year follow-up period, 373(7.2%) CVD were documented. The seven IR indices were strongly positively associated with CVD risk. Compare to other IR indices, CVAI was the strongest predictor for CVD (HR:1.84 95% CI: 1.45-2.35; p < 0.001) and showed the highest diagnostic value for CVD (AUC: 0.654 95% CI: 0.640-0.666; p < 0.001). Adding CVAI to the based model exhibited the maximum increased on incremental risk stratification for CVD (NRI: 0.355; IDI: 0.010; all p < 0.001). Moreover, there was a non-linear association between CVAI and CVD, with a threshold point of 96.21. The association between CVAI and CVD risk was more prominent among individuals aged<65 years, female, and non-hypertension (all P interaction<0.001).
Conclusion:
Compared to the other six tested IR indices, CVAI might be the most valuable index to predict and stratify CVD risk, with enhanced prediction in women under 65 years of age. This suggests that strategies aimed at improving risk stratification should incorporate CVAI into risk algorithms.
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