Abstract
BACKGROUND: The prevalence of metabolic syndrome varies widely by ethnicity and by the criteria used in its definition. OBJECTIVE: To identify the optimal cutoff values for waist circumference (WC), waist-to-hip ratio (WHR) and body mass index (BMI) for identifying metabolic syndrome among the Saudi population. DESIGN: Nationwide household cross-sectional population-based survey. SETTING: Thirteen health sectors in Saudi Arabia. SUBJECTS AND METHODS: We used data for subjects in the Saudi Abnormal Glucose Metabolism and Diabetes Impact Study (SAUDI-DM), which was conducted from 2007 to 2009. Using International Diabetes Federation (IDF) criteria, metabolic syndrome and its different components were assessed using anthropometric measurements, blood pressure, fasting plasma glucose, triglycerides and HDL cholesterol. Receiver operating characteristic (ROC) curves were generated to assess sensitivity and specificity for different cutoff values of WC, WHR, and BMI. The Youden index was used to calculate the optimal cutoff value for each anthropometric measurement. MAIN OUTCOME MEASURE(S): Optimal cutoff value for WC, WHR, and BMI for identifying the risk of metabolic syndrome. RESULTS: The prevalence of two or more risk factors for metabolic syndrome was observed in 43.42% of the total cohort of 12126 study participants >=18 years of age. The presence of two or more risk factors were significantly higher among men (46.81%) than women (40.53%) (P < .001). The optimal cutoff values for WC, WHR, and BMI were 92 cm, 0.89, and 25 kg/m2 for men and 87 cm, 0.81 and 28 kg/m2 for women for identifying the risk of metabolic syndrome. The prevalence of elevated triglycerides, blood pressure, and fasting plasma glucose significantly increased with age for both genders. CONCLUSIONS: The proposed WC cutoff values were better than WHR and BMI in predicting metabolic syndrome and could be used for screening people at high risk for metabolic syndrome in the Saudi population. LIMITATIONS: No direct measure of body fatness and fat distribution, cross-sectional design.