Predictive Values of Anthropometric Measurements for Cardiometabolic Risk Factors and Cardiovascular Diseases Among 44 048 Chinese

Jia Liu(Chinese Academy of Medical Sciences & Peking Union Medical College), Lap Ah Tse(Chinese University of Hong Kong), Zhiguang Liu(Chinese University of Hong Kong), Sumathy Rangarajan(Population Health Research Institute), Bo Hu(Chinese Academy of Medical Sciences & Peking Union Medical College), Yin Lu(Chinese Academy of Medical Sciences & Peking Union Medical College), Darryl P. Leong(Population Health Research Institute), Wei Li(Chinese University of Hong Kong), Bing Liu(Chinese University of Hong Kong), Chun‐Ming Chen, Jin Guo, Hongye Zhang, Hui Chen, Jian Bo(Chinese Academy of Medical Sciences & Peking Union Medical College), Jian Li(Chinese University of Hong Kong), Juan Li(Chinese University of Hong Kong), Jun Yang, Kean Wang, Li Zhang(Chinese University of Hong Kong), Qing Deng, Ren Bing, Tao Chen, Tao Xu, Wei Wang(Chinese University of Hong Kong), Wenhua Zhao, Xiaohong Chang, Xiaoru Cheng, Xinye He, Xixin Hou, Xingyu Wang, Xiulin Bai, Zhao Xiuwen, Xu Liu(Chinese University of Hong Kong), Xuan Jia(Chinese Academy of Medical Sciences & Peking Union Medical College), Yang Wang, Yi Sun(Chinese Academy of Medical Sciences & Peking Union Medical College), Yi Zhai(Chinese Academy of Medical Sciences & Peking Union Medical College), Di Chen, Hui Jin, Jiwen Tian, Yumin Ma(Population Health Research Institute), Yindong Li(Chinese University of Hong Kong), Chao He, Kai You, Songjian Zhang, Xiuzhen Tian, Xu Xu, Jinling Di, Jianquan Wu, Mei Wang, Qiang Zhou, Aiying Han, Minzhi Cao, Weiping Jiang, Deren Qiang, Jing Qin, Shan Qian, Suyi Shi, Yihong Zhou, Zhengrong Liu(Chinese University of Hong Kong), Ming Wan, Jinhua Tang, Yongzhen Mo, Rongwen Bian, Qinglin Lou, Lihua Hu(Chinese Academy of Medical Sciences & Peking Union Medical College), Shuwei Xiong, Yan Zhong, Ning Li(Chinese University of Hong Kong), Xincheng Tang, Shuli Ye, Chunyi Li(Chinese University of Hong Kong), Yujin Li(Chinese University of Hong Kong), Qiuyang Wang, Xiaoli Fu, Baoxia Guo, Huilian Feng, Lihui Xu, Haibin Ma(Population Health Research Institute), Ruiqi Wu, Yali Wang, Hongze Liu(Chinese University of Hong Kong), Yurong Ma(Population Health Research Institute), Bo Yuan(Chinese Academy of Medical Sciences & Peking Union Medical College), Qian Zhao, Guofan Xu, Hui He, Jiankang Liu(Chinese University of Hong Kong), Xin Wang, Ming Chen, Wenqing Deng, Zhendong Liu(Chinese University of Hong Kong), Hua Zhang, Shangwen Sun, Shujian Wang, Yingkin Zhao, Yutao Diao, Xuezheng Shi, Chuanrui Wei(Chinese University of Hong Kong), Jufang Wang, Guoqin Liu(Chinese University of Hong Kong), Cuiying Wu, Guilan Ma(Population Health Research Institute), Wei Hua(Chinese University of Hong Kong), Junying Wang, Xiongfei Bao, Yue Tang, Yahong Zhi(Chinese University of Hong Kong), Ailing Wang, Huijuan Wang, Jianna Liu(Chinese University of Hong Kong), Q H Liu(Chinese University of Hong Kong), Rong Wang, Aideer Aili, Ayoufumiti Wula, A Bu-la, Dongmei Yang, Wen Qian, Yize Xiao, Qingping Shi, Ying Shao, Kehua Li(Chinese University of Hong Kong), Wuba Bai, Jinkui Yang, Huaxing Liu(Chinese University of Hong Kong), Shunyun Yang
Journal of the American Heart Association
August 9, 2019
10.1161/jaha.118.010870
Cited by 115Open Access
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Abstract

Background The predictive value of adiposity indices and the newly developed index for cardiometabolic risk factors and cardiovascular diseases (CVDs) remains unclear in the Chinese population. This study aimed to compare the predictive value of A Body Shape Index with other 5 conventional obesity-related anthropometric indices (body mass index, waist circumference, hip circumference, waist-to-hip ratio, waist-to-height ratio) in Chinese population. Methods and Results A total of 44 048 participants in the study were derived from the baseline data of the PURE-China (Prospective Urban and Rural Epidemiology) study in China. All participants' anthropometric parameters, CVDs, and risk factors (dyslipidemia, abnormal blood pressure, and hyperglycemia) were collected by standard procedures. Multivariable logistic regression models and receiver operator characteristic curve analysis were used to evaluate the predictive values of obesity-related anthropometric indices to the cardiometabolic risk factors and CVDs. A positive association was observed between each anthropometric index and cardiometabolic risk factors and CVDs in all models (P<0.001). Compared with other anthropometric indices (body mass index, waist circumference, hip circumference, waist-to-hip ratio, and A Body Shape Index), waist-to-height ratio had significantly higher areas under the curve (AUCs) for predicting dyslipidemia (AUCs: 0.646, sensitivity: 65%, specificity: 44%), hyperglycemia (AUCs: 0.595, sensitivity: 60%, specificity: 45%), and CVDs (AUCs: 0.619, sensitivity: 59%, specificity: 41%). Waist circumference showed the best prediction for abnormal blood pressure (AUCs: 0.671, sensitivity: 66%, specificity: 40%) compared with other anthropometric indices. However, the new body shape index did not show a better prediction to either cardiometabolic risk factors or CVDs than that of any other traditional obesity-related indices. Conclusions Waist-to-height ratio appeared to be the best indicator for dyslipidemia, hyperglycemia, and CVDs, while waist circumference had a better prediction for abnormal blood pressure.

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