Determination of the Optimal Cut-Off Point of Anthropometric Indices to Predict the Risk of Metabolic Syndrome in Iranian Adult Population With Type 2 Diabetes Mellitus: A Cross-Sectional-Analytical Study

Abstract

Aims Metabolic syndrome (MetS) and type 2 diabetes mellitus (T2DM) are two diseases that are related to each other and the presence of both can increase the risk of heart attack and death. The present study aimed to assess the efficacy of anthropometric indices in predicting the risk of MetS among T2DM patients in Iran. Materials and Methods In this study, 400 T2DM subjects were included via convenience sampling. Some anthropometric information, such as weight, height, waist circumference, and hip circumference along with biochemical data including fasting blood sugar, lipid profile components, systolic and diastolic blood pressure, were collected. The performance of the anthropometric indices in predicting MetS was evaluated using receiver operating characteristic (ROC) curve analysis and estimation of the area under the curve (AUC) values. Results Abdominal volume index (AVI) had the largest AUC in the total population. Although this result was also obtained in females, the highest value of AUC was related to vaisceral adiposity index (VAI) in males. All of the anthropometric indices increased the odds of MetS significantly, with p < 0.001 in all crude and adjusted models. Although AVI had the highest odds ratio in the crude model (21.28, 95 CI 12.26-36.92), the highest odds ratio belonged to Relative fat mass (RFM) in the adjusted models. Conclusions All anthropometric indices used in the study were effective in predicting the odds of MetS. AVI and VAI showed the strongest associations with MetS in both genders. Given the cross-sectional design of the study, these results should be interpreted as associations rather than causal or predictive relationships.