• Bmc Public Health · Jun 2018

    Optimal cut-points of different anthropometric indices and their joint effect in prediction of type 2 diabetes: results of a cohort study.

    • Neda Zafari, Mojtaba Lotfaliany, Mohammad Ali Mansournia, Davood Khalili, Fereidoun Azizi, and Farzad Hadaegh.
    • Prevention of Metabolic Disorders Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
    • Bmc Public Health. 2018 Jun 5; 18 (1): 691.

    BackgroundTo determine the anthropometric indices that would predict type 2 diabetes (T2D) and delineate their optimal cut-points.MethodsIn 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.ResultsDuring 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.ConclusionsOur derived cut-points differ between both sexes and are different from other ethnicities.

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