Yahya Pasdar - Research Canter for Environmental Determinants of Health, Kermanshah University of Medical Sciences,Kermanshah, Iran
Farid Najafi - Research Canter for Environmental Determinants of Health, Kermanshah University of Medical Sciences,Kermanshah, Iran
Behrooz Hamzeh - Research Canter for Environmental Determinants of Health, Kermanshah University of Medical Sciences,Kermanshah, Iran
Mitra Darbandi - Research Canter for Environmental Determinants of Health, Kermanshah University of Medical Sciences,Kermanshah, Iran

Background and Aim: High body fat is related to metabolic syndrome in all ethnic groups. We aimed to determine the optimal cutoff points for the Fat Mass Index (FMI) and Body Fat Percentage (BFP) in the prediction of metabolic syndrome diseases.Methods: This cross-sectional study was performed on 10063 individuals, aged between 35-65 years, recruited in Ravansar Non-Communicable Diseases (RaNCD) cohort. The anthropometric indices were measured using a body analyzer. The receiver operating characteristic curve analysis was employed to determine the optimal cutoff points for the indices.Results: In males, the optimal cutoff point for FMI and PBF to the prediction of metabolic syndrome was 8 kg/m2 and 29, respectively. In females, the optimal cutoff point for FMI and PBF was 11.7 kg/m2 and 40, respectively. In the rural population, the cut-off points were lower than the urban population. The risk of metabolic syndrome diseases in males and females with a FMI higher than the optimal cutoff point was respectively 6.10 and 2.25 times higher than that in those with a FMI lower than the cutoff point. The risk in males and females with a PBF higher than the optimal cutoff point was respectively 4.7 and 2 times higher than that in those with a PBF lower than the cutoff point.Conclusion: This study revealed that the indices of FMI and BFP are appropriate predictors of the risk of metabolic syndrome diseases. The diagnostic power of these indicators was better in men and villagers.

Metabolic syndrome, Cut-point, Fat Mass Index, Body Fat Percentage