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This study aimed to evaluate the superiority of anthropometric indices compared to others for predicting ischemic heart disease (IHD) or cardiometabolic risk factors. This study was a cross-sectional analysis of the Pars Cohort Study data. In total, 9229 Valashahr inhabitants aged 40–75 were included in the analysis. The area under the receiver operating characteristic curve (AUC) analyses was used to compare the predictive accuracy of four anthropometric measures, including body mass index, waist to height ratio (WHtR), waist to hip ratio (WHR), and waist circumference (WC). IHD prevalence was 10.4% in our sample. The prevalence of diabetes mellitus (DM), hypertension, dyslipidemia, and metabolic syndrome was 12.7%, 29.2%, 58.4%, and 22.3%, respectively. All anthropometric indices had poor to good accuracy in predicting IHD risk factors, with AUCs ranging between 0.580 and 0.818. WHR was the most accurate measure for predicting IHD in both genders. All indexes had a better accuracy for predicting DM, dyslipidemia, and metabolic syndrome (MetS) in males than in females. To conclude, anthropometric measures, especially WC and WHtR, are recommended for predicting metabolic syndrome in primary prevention settings. These simple indices could help physicians find those who need further evaluation for MetS.
Nakhostin-Ansari et al. (Thu,) studied this question.