Clinical significant of predicting the risk of dysglycemia and dyslipidemia based on body mass index,waist circumference and waist-to-hip ratio
10.3760/cma.j.issn.1008-6315.2015.01.017
- VernacularTitle:体质量指数、腰围与腰臀比预测糖脂代谢异常的临床价值
- Author:
Shuangtao HE
;
Jinan ZHANG
;
Jun LIU
- Publication Type:Journal Article
- Keywords:
Body mass index;
Waist circumference;
Waist-to-hip ratio;
Dysglycemia;
Dyslipidemia
- From:
Clinical Medicine of China
2015;31(1):54-56
- CountryChina
- Language:Chinese
-
Abstract:
Objective To investigate the clinical significant and the difference of predicting the risk of dysglycemia and dyslipidemia by body mass index (BMI),waist circumference (WC) and waist-to-hip ratio (WHR) in order to look for the best predicting index.Methods Five thousand and thirty residents were participated to this study who were from Jinshan New Area and nearby of Jinshan,Shanghai,including 2004 males and 3026 females.They were divided into obesity group and non-obesity group based on the index of BMI,WC and WHR respectively.The ROC was made based on the above indies in different gender groups.Results The ROC area of BMI was the biggest with 0.641 (P ＜0.05) for male and 0.617(P ＜0.05) for female.The cut off value was 24.67 or 23.88 based on the male or the female.The same trend was seen in terms of WC with 88.5 cm for the male and 84.5 cm for the female.The small cut off value was seen in terms of WHR and there was no significant between male and female.Among male people,the cut off values was 26.01 in terms of BMI and 88.5 cm in terms of WC,0.89 cm in terms of WHR.Among the female people,there was the less predicting significant in terms of WC or WHR.The area under the curve had no significant differences,and the BMI predicted abnormal blood glucose of no value,the area under the curve is only 0.513 (P ＞ 0.05).Conclusion BMI is proved the best predictor for the risk of dyslipidemia.There are significant among BMI,WC and WHR in terms of predicting dysglycemia in different gender.BMI is proved without significant regarding of predicting dysglycemia in females.
