Comparison of anthropometric indices for predicting the risk of metabolic syndrome and its components in Chinese adults: A prospective, longitudinal study

Haoyu Wang, Aihua Liu, Tong Zhao, Xun Gong, Tianxiao Pang, Yingying Zhou, Yue Xiao, Yumeng Yan, Chenling Fan, Weiping Teng, Yaxin Lai*, Zhongyan Shan

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review


Objectives Our study aimed to distinguish the ability of anthropometric indices to assess the risk of metabolic syndrome (MetS). Design Prospective cohort study. Setting Shenyang, China. Participants A total of 379 residents aged between 40 and 65 were enrolled. 253 of them were free of MetS and had been followed up for 4.5 years. Methods At baseline, all the participants underwent a thorough medical examination. A variety of anthropometric parameters were measured and calculated, including waist circumference (WC), body mass index (BMI), a body shape index (ABSI), abdominal volume index (AVI), body adiposity index, body roundness index, conicity index, waist-to-hip ratio and visceral adiposity index (VAI). After 4.5 year follow-up, we re-examined whether participants were suffering from MetS. A receiver operating characteristic (ROC) curve was applied to examine the potential of the above indices to identify the status and risk of MetS. Outcomes Occurrence of MetS. Results At baseline, 33.2% participants suffered from MetS. All of the anthropometric indices showed clinical significance, and VAI was superior to the other indices as it was found to have the largest area under the ROC curve. After a 4.5 year follow-up, 37.8% of men and 23.9% of women developed MetS. ROC curve analysis suggested that baseline BMI was the strongest predictor of MetS for men (0.77 (0.68-0.85)), and AVI was the strongest for women (0.72 (0.64-0.79)). However, no significant difference was observed between WC and both indices. In contrast, the baseline ABSI did not predict MetS in both genders. Conclusions The present study indicated that these different indices derived from anthropometric parameters have different discriminatory abilities for MetS. Although WC did not have the largest area under the ROC curve for diagnosing and predicting MetS, it may remain a better index of MetS status and risk because of its simplicity and wide use.

Original languageEnglish
Article numbere016062
JournalBMJ Open
Issue number9
Publication statusPublished - 1 Sep 2017
Externally publishedYes

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