Evidence mapPaperPMID 40197277Full record

ArticleDiabetology & metabolic syndrome2025

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

Peizhen Zhou, Wei Liu, Kangning Sun, Zekun Zhao, Wenqian Zhu, Jing Zhang, Wenjun Wang

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Article in Diabetology & metabolic syndrome, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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7 authors.

Peizhen ZhouDepartment of Epidemiology and Health Statistics, School of Public Health, North China University of Science and Technology, No. 21 Bohai Avenue, Caofeidian New Town, Tangshan, 063210, China.
Wei LiuJining Center for Disease Control And Prevention, No.26 Yingcui Road, High-Tech Zone, Jining, 272000, China.
Kangning SunWeifang Nursing Vocational College, No. 9966 Yunmenshan South Road, Qingzhou, 262500, China.
Zekun ZhaoWeifang Nursing Vocational College, No. 9966 Yunmenshan South Road, Qingzhou, 262500, China.
Wenqian ZhuWeifang Nursing Vocational College, No. 9966 Yunmenshan South Road, Qingzhou, 262500, China.
Jing ZhangJining Medical University, No.133 Hehua Road, Taibai Lake New District, Jining, 272067, China. zhangj1976@163.com.
Wenjun WangWeifang Nursing Vocational College, No. 9966 Yunmenshan South Road, Qingzhou, 262500, China. wwjun1973@163.com.

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6 · The paper itself

Abstract

backgroundMetabolic 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.

methodsThis 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.

resultsThe 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.

conclusionsTyG-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.

Indexed as

Anthropometric indicesMetabolic syndromeMETS-VFTyG-WC

Identifiers

PMID40197277
PMCPMC11974144

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