Physical Examination Center, Xuanwu Hospital, Capital Medical University, Beijing, China.
Department of Epidemiology and Biostatistics, School of Public Health, Capital Medical University, Beijing, China.
Public Health. 2016 Feb;131:3-10. doi: 10.1016/j.puhe.2015.08.001. Epub 2015 Nov 11.
Obesity has become a major health problem in contemporary society and it is closely related to many chronic diseases, so it is an important issue for measuring adiposity accurately and predicting its future. Prevention and treatment of overweight and obesity has become one of the key prevention and treatment of metabolic disorders.
In this study, we compared the ability of the four anthropometric indicators (body mass index, waist circumstance, waist-height ratio, waist-to-hip ratio) to identify metabolic disorders (hypertension, hyperlipidaemia, hyperglycemia and hyperuricemia) by receiver operating characteristic (ROC) curve analyses and to provide evidence for clinical practice.
In this large scale cross-sectional study, 13,275 Han adults (including 7595 males and 5680 females) received physical examination between January, 2009 and January, 2010 in Xuanwu Hospital of Capital Medical University were investigated by the means of questionnaire, Meanwhile, the physical examination and serological results were recorded. A package known as Statistical Package for Social Scientist (SPSS) was employed to analyse the responses while t-test, one-way analysis of variance (ANOVA), ROC analysis and chi-square statistical methods were used to test the hypotheses.
WC, WHtR, WHR and BMI were all significantly (P < 0.001) correlated with all metabolic risk factors regardless of gender. And the area under the curve (AUC) of WHtR was significantly greater than that of WC, BMI or WHR in the prediction of hypertension, hyperlipidaemia, hyperglycemia and hyperuricemia.
Our data show that WHtR was the best predictor of various metabolic disorders. The diagnostic value in descending order was WHtR > WHR > WC > BMI. Therefore we recommend WHtR in assessment of obese patients, in order to better assess the risks of their metabolic diseases.
肥胖已成为当代社会的一个主要健康问题,与许多慢性疾病密切相关,因此准确测量肥胖并预测其未来是一个重要问题。超重和肥胖的预防和治疗已成为代谢紊乱的关键预防和治疗措施之一。
本研究通过受试者工作特征(ROC)曲线分析比较了四种人体测量指标(体重指数、腰围、腰高比、腰臀比)识别代谢紊乱(高血压、高脂血症、高血糖和高尿酸血症)的能力,为临床实践提供证据。
在这项大规模横断面研究中,2009 年 1 月至 2010 年 1 月,首都医科大学宣武医院对 13275 名汉族成年人(包括 7595 名男性和 5680 名女性)进行了体检,采用问卷调查的方式进行调查,同时记录体检和血清学结果。使用称为社会科学家统计软件包(SPSS)的软件包来分析响应,使用 t 检验、单因素方差分析(ANOVA)、ROC 分析和卡方统计方法来检验假设。
无论性别如何,WC、WHtR、WHR 和 BMI 均与所有代谢危险因素显著相关(P<0.001)。WHtR 在预测高血压、高脂血症、高血糖和高尿酸血症方面的曲线下面积(AUC)明显大于 WC、BMI 或 WHR。
我们的数据表明,WHtR 是预测各种代谢紊乱的最佳指标。诊断价值依次为 WHtR>WHR>WC>BMI。因此,我们建议在评估肥胖患者时使用 WHtR,以更好地评估其代谢疾病的风险。