Optimal Cut-Points of Different Anthropometric Indices and Their Joint Effect in Prediction of Type 2 Diabetes: Results of a Cohort Study

Optimal Cut-Points of Different Anthropometric Indices and Their Joint Effect in Prediction of Type 2 Diabetes: Results of a Cohort Study Publisher Pubmed

Zafari N¹ ; Lotfaliany M^{1, 2} ; Mansournia MA³ ; Khalili D¹ ; Azizi F⁴ ; Hadaegh F¹

Show Affiliations

1. Prevention of Metabolic Disorders Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
2. Non-Communicable Disease Control, School of Population and Global Health, University of Melbourne, Melbourne, VIC, Australia
3. Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
4. Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran

Source: BMC Public Health Published:2018

Abstract

Background: To determine the anthropometric indices that would predict type 2 diabetes (T2D) and delineate their optimal cut-points. Methods: In a cohort study, 7017 Iranian adults, aged 20-60 years, free of T2D at baseline were investigated. Using Cox proportional hazard models, hazard ratios (HRs) for incident T2D per 1 SD change in body mass index (BMI), waist circumference (WC), waist to height ratio (WHtR), waist to hip ratio (WHR), and hip circumference (HC) were calculated. The area under the receiver operating characteristics (ROC) curves (AUC) was calculated to compare the discriminative power of anthropometric variables for incident T2D. Cut-points of each index were estimated by the maximum value of Youden's index and fixing the sensitivity at 75%. Using the derived cut-points, joint effects of BMI and other obesity indices on T2D hazard were assessed. Results: During a median follow-up of 12 years, 354 men, and 490 women developed T2D. In both sexes, 1 SD increase in anthropometric variables showed significant association with incident T2D, except for HC in multivariate adjusted model in men. In both sexes, WHtR had the highest discriminatory power while HC had the lowest. The derived cut-points for BMI, WC, WHtR, WHR, and HC were 25.56 kg/m2, 89 cm, 0.52, 0.91, and 96 cm in men and 27.12 kg/m2, 87 cm, 0.56, 0.83, and 103 cm in women, respectively. Assessing joint effects of BMI and each of the obesity measures in the prediction of incident T2D showed that among both sexes, combined high values of obesity indices increase the specificity for the price of reduced sensitivity and positive predictive value. Conclusions: Our derived cut-points differ between both sexes and are different from other ethnicities. © 2018 The Author(s).

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Style	Citing Format
MLA	Zafari N, et al.. "Optimal Cut-Points of Different Anthropometric Indices and Their Joint Effect in Prediction of Type 2 Diabetes: Results of a Cohort Study." BMC Public Health, vol. 18, no. 1, 2018, pp. -.
APA	Zafari N, Lotfaliany M, Mansournia MA, Khalili D, Azizi F, Hadaegh F (2018). Optimal Cut-Points of Different Anthropometric Indices and Their Joint Effect in Prediction of Type 2 Diabetes: Results of a Cohort Study. BMC Public Health, 18(1), -.
Chicago	Zafari N, Lotfaliany M, Mansournia MA, Khalili D, Azizi F, Hadaegh F. "Optimal Cut-Points of Different Anthropometric Indices and Their Joint Effect in Prediction of Type 2 Diabetes: Results of a Cohort Study." BMC Public Health 18, no. 1 (2018): -.
Harvard	Zafari N et al. (2018) 'Optimal Cut-Points of Different Anthropometric Indices and Their Joint Effect in Prediction of Type 2 Diabetes: Results of a Cohort Study', BMC Public Health, 18(1), pp. -.
Vancouver	Zafari N, Lotfaliany M, Mansournia MA, Khalili D, Azizi F, Hadaegh F. Optimal Cut-Points of Different Anthropometric Indices and Their Joint Effect in Prediction of Type 2 Diabetes: Results of a Cohort Study. BMC Public Health. 2018;18(1):-.
BibTex	@article{ author = {Zafari N and Lotfaliany M and Mansournia MA and Khalili D and Azizi F and Hadaegh F}, title = {Optimal Cut-Points of Different Anthropometric Indices and Their Joint Effect in Prediction of Type 2 Diabetes: Results of a Cohort Study}, journal = {BMC Public Health}, volume = {18}, number = {1}, pages = {-}, year = {2018} }
RIS	TY - JOUR AU - Zafari N AU - Lotfaliany M AU - Mansournia MA AU - Khalili D AU - Azizi F AU - Hadaegh F TI - Optimal Cut-Points of Different Anthropometric Indices and Their Joint Effect in Prediction of Type 2 Diabetes: Results of a Cohort Study JO - BMC Public Health VL - 18 IS - 1 SP - EP - PY - 2018 ER -

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