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Predictive ability of traditional and novel anthropometric measurement indices for cardio-metabolic diseases in Chinese adults: China Health and Nutrition Survey (CHNS) cohort study

医学 人体测量学 体质指数 肥胖 腹部肥胖 队列 入射(几何) 代谢综合征 内科学 腰围 数学 几何学
作者
Ke Wang,Ying Li,Wanqing Ye,Bo Chen,Jingjing Zeng,Shaoyong Xu
出处
期刊:Nutrition Metabolism and Cardiovascular Diseases [Elsevier BV]
卷期号:33 (4): 737-748 被引量:1
标识
DOI:10.1016/j.numecd.2022.12.025
摘要

Cardio-metabolic diseases has been shown to be strongly associated with obesity. The aim of this study was to compare the predictive value of traditional and novel anthropometric measurement indices for cardio-metabolic diseases risk and evaluate whether new indicators can provide important information in addition to traditional indicators.China Health and Nutrition Survey (CHNS) data were obtained for this study. Baseline information for healthy participants was gathered from 1997 to 2004. The incidence of cardio-metabolic diseases was collected from 2009 to 2015 for cohort analysis. The predictive ability of each index for the risk of cardio-metabolic diseases was evaluated with time-dependent ROC analysis. Body mass index (BMI) showed the greatest predictive ability for cardio-metabolic disease incidence among all traditional and novel indices (Harrell's C statistic (95% CI): 0.7386 (0.7266-0.7507) for hypertension, 0.7496 (0.7285-0.7706) for diabetes, 0.7895 (0.7593-0.8196) for stroke and 0.7581 (0.7193-0.7969) for myocardial infarction). The addition of novel indices separately into the BMI model did not improve the predictive ability. Novel anthropometric measurement indices such as a body shape index (ABSI), abdominal volume index (AVI) and triponderal mass index (TMI), had a certain prediction ability for adults with BMI <24 kg/m2 compared to those with BMI ≥24 kg/m2.No strong evidence supports novel anthropometric measurement indices were better than BMI in the prediction of cardio-metabolic diseases incidence among Chinese adults. Novel anthropometric measurement indices, mainly for abdominal obesity, may have a high predictive effect for adults with BMI <24 kg/m2.
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