Optimal Cut-off Points of BMI WC and WHR for Screening of Pre-Diabetes and Diabetes Over 35 Years Old People
World Journal of Public Health
Volume 4, Issue 1, March 2019, Pages: 1-9
Received: Dec. 6, 2018;
Accepted: Dec. 20, 2018;
Published: Jan. 29, 2019
Views 683 Downloads 104
Anle Li, Jiading District Center for Disease Control and Prevention, Shanghai, China
Yanyun Li, Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China
Fang Xiang, Jiading District Center for Disease Control and Prevention, Shanghai, China
Yiying Zhang, Jiading District Center for Disease Control and Prevention, Shanghai, China
Qinping Yang, Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China
Zhihao Hu, Jiading District Center for Disease Control and Prevention, Shanghai, China
Qian Peng, Jiading District Center for Disease Control and Prevention, Shanghai, China
Using BMI, WC and WHR to investigate and compare these screening tool for IFG, IGT and diabetes subjects in Shanghai China; and to identify the optimal cut-off points of BMI, WC and WHR for screening pre-diabetes (Pre-DM) and diabetes (DM) over 35 years old people. Totally 3,195 aged 35 years old and above people who attended community epidemiological survey of diabetes mellitus. Using ADA criteria (2010), the participants were classified as normal, Pre-DM or DM according to test results of blood glucose. The area under ROC curve (AUROC) for BMI, WC and WHR were calculated; as well as the sensitivity, specificity and Youden index under different BMI or WHR cut-off points. Among these people, age is (61.07±10.08), and BMI and WHR are respectively (25.12±3.29) and (0.87±0.06). The positive rate of screening of DM is 11.36% and that of Pre-DM is 38.57%. There are correlation between blood glucose and BMI or WHR (p<0.05). With the increase of BMI or WHR cut-off point, the screening sensitivity (YI, Sp and Se) for DM or pre-DM are decreasing; but the area under ROC (AUROC) increases firstly and then decreases (inflection point: WHR≥0.8~0.9 and BMI≥23 for pre-DM, WHR≥0.9 and BMI≥24 for DM). The combined screening efficacy of BMI merged WHR is the best combination choice (cut-off point of BMI and WHR are respectively 23 and 0.8), and YI is the highest. Using HbA1C as standard of judgment seems to be better than blood glucose in screening for DM. BMI≥23, WC≥90 cm or WHR≥0.8 is the optimal cut-off point for screening DM and pre-DM, and the screening efficacy of BMI is better than WC and WHR. BMI merged WHR is the best combination choice (cut-off point of BMI and WHR are respectively 23 and 0.8). HbA1C is better than FBG and OGTT as standard of judgment in screening.
Optimal Cut-off Points of BMI WC and WHR for Screening of Pre-Diabetes and Diabetes Over 35 Years Old People, World Journal of Public Health.
Vol. 4, No. 1,
2019, pp. 1-9.
World Health Organization. The Asia-Pacific perspective: redefining obesity and its treatment [M]. Sydney: Health Communications, 2000:20-21.
Diabetes Sciences of Chinese Medical Association. Guidelines for the prevention and treatment of type 2 diabetes mellitus in China (2013 edition) [J]. Chinese Journal of diabetes; 2014,6(7): 447-498.
Ashwell M, Gunn P, Gibson S. Waist-to-height ratio is a better screening tool than waist circumference and BMI for adult cardiometabolic risk factors: systematic review and meta-analysis [J]. Obes Rev; 2012, 13(3):275-286.
Browning LM, Shiun Dong H, Margaret A. A systematic review of waist-to-height ratio as a screening tool for the prediction of cardiovascular disease and diabetes: 0•5 could be a suitable global boundary value [J]. Nutr Res Rev, 2010, 23(23):247-269.
LI MZ, SU L, LIANG B Y, et al. Trends in prevalence, awareness, treatment, and control of diabetes mellitus in mainland china from 1979 to 2012 [J]. Int J Endocrinol, 2013, 2013(4): 7531-50.
XU Y. Prevalence and control of diabetes in chinese adults [J]. JAMA, 2013, 310(9): 948-958.
CHIU M, AUSTIN P C, MANUEL D G, et al. Deriving ethnic-specific BMI cutoff points for assessing diabetes risk [J]. Diabetes Care, 2011, 34(8): 1741-1748.
LI S, XIAO J, JI L, et al. BMI and waist circumference are associated with impaired glucose metabolism and type 2 diabetes in normal weight Chinese adults [J]. J Diabetes Complications, 2014, 28(4): 470-476.
HSU W C, ARANETA M R, KANAYA A M, et al. BMI cut points to identify at-risk Asian Americans for type 2 diabetes screening [J]. Diabetes Care, 2015, 38(1): 150-158.
China Obesity Task Force data summary analysis collaboration group. Predictive value of body mass index and waist circumference for abnormal risk factors of related diseases in Chinese adults: A study of appropriate body mass index and waist circumference cut points [J]. Chinese Journal of Epidemiology; 2002, 23(1): 10-15.
ZENG Q, HE Y, DONG S, et al. Optimal cut-off values of BMI, waist circumference and waist height ratio for defining obesity in Chinese adults [J]. Br J Nutr; 2014, 112(10): 1735-1744.
CHU F L, HSU C H, JENG C. Lowered cutoff points of obesity indicators are better predictors of hypertension and diabetes mellitus in premenopausal Taiwanese women [J]. Obes Res Clin Pract, 2015, 9(4): 328-335.
Xi Chen, Xiao lei Guo, Ji xiang Ma, etc. Appropriate cut-off point analysis of anthropometric parameters for diabetes screening in Shandong residents aged 18~69 [J]. Journal of Shandong University (Medical Science), 2012,50(4): 19-23.
JIA Z, ZHOU Y, LIU X, et al. Comparison of different anthropometric measures as predictors of diabetes incidence in a Chinese population [J]. Diabetes Res Clin Pract, 2011, 92(2): 265-271.
Introduction: Standards of medical care in diabetes-2018 [J]. Diabetes care, 2018;41(suppl):s1.
Marathe PH, Gao HX, Close KL. American Diabetes Association Standards of medical care in diabetes 2017 [J]. Journal of Diabetes. 2017;9(4):320.
Tsuyoshi Okura, Risa Nakamura, Yohei Fujioka, etc. Body mass index ≥23 is a risk factor for insulin resistance and diabetes in Japanese people: A brief report [J]. PLoS One. 2018; 13(7): e0201052.
Yiu-Hua Cheng, Yu-Chung Tsao, I-Shiang Tzeng, etc. Body mass index and waist circumference are better predictors of insulin resistance than total body fat percentage in middle-aged and elderly Taiwanese [J]. Medicine (Baltimore); 2017; 96(39): e8126.
Group IDFGD. Global guideline for type 2 diabetes [J]. Diabetes Res Clin Pract, 2014, 104(1):1-52.
Schneider HJ, Klotsche J, Silber S, et al. Measuring abdominal obesity: effects of height on distribution of cardio-metabolic risk factors risk using waist circumference and waist-to-height ratio[J]. Diabetes Care, 2011, 34(1):e7.
Shimajiri T, Imagawa M, Kokawa M, et al. Revised optimal cut-off point of waist circumference for the diagnosis of metabolic syndrome in Japanese women and the influence of height [J]. J Atheroscler Thromb; 2008,15(2):94-99.
Yang Qundi, Li Rui, Ruan Ye, et al. Optimal screening tool for prediabetes and undiagnosed diabetes using waist circumstance and waist-to-height ratio [J]. Chin J Diabetes Mellitus，2016; 8 ( 9): 554-558.