Comparison of the predictive value of 17 anthropometric in-dices for the prevalence of metabolic syndrome among Chinese residents: a cross-sectional study.

Background: Metabolic syndrome (MetS) is increasingly viewed as a pressing concern for public health globally. The objective of this study was to compare the predictive ability of 17 anthropometric indices for the risk of MetS in Chinese residents, to explore the differences in the predictive effect of the indices between different sexes, and to identify the optimal predictive indices of MetS for men and women.

Methods: This research utilized a cross-sectional study involving 5479 residents in Shandong Province, China. According to the subjects' working curve (ROC), TyG-WHtR, TyG-WC, METS-VF, CVAI, and LAP with the area under the curve (AUC) greater than 0.850 were included in the follow-up. To explore the associations between indices and the prevalence of MetS, three logistic regression models were employed. The dose-response relationship between the indices and the risk of MetS was performed by the Restricted cubic spline (RCS) curves.

Results: The prevalence of MetS in this study is approximately 45.56%. The multivariate logistic regression showed the predictive capacity of the TyG-WC and METS-VF for MetS was superior in males, while only METS-VF in females. Furthermore, there is a non-linear relationship between MTES-VF and MetS risk both in men and women (non-linearity p < 0.001). The potential for the risk of MetS increased when the METS-VF exceeded 6.67 in males or 6.30 in females. In addition, in the male population, TyG-WC is non-linearly related to MetS risk (non-linear p < 0.001), and the risk of MetS may increase when TyG-WC is higher than 750.40.

Conclusions: TyG-WC and METS-VF have a good predictive value for the risk of MetS in the Chinese male population, with TyG-WC being better than METS-VF. For females, METS-VF could be regarded as the most reliable indicator.