Association between the abdominal obesity anthropometric indicators and metabolic disorders in a Chinese population

J Dong, Y-Q Ni, X Chu, Y-Q Liu, G-X Liu, J Zhao, Y-B Yang, Y-X Yan
Public Health 2016, 131: 3-10

BACKGROUND: 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.

OBJECTIVE: 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.

METHODS: 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.

RESULTS: 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.

CONCLUSION: 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.

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