Body Composition Assessment by Bioelectrical Impedance  Analysis in Prediction of Cardio-Metabolic Risk Factors: Tehran Lipid and Glucose Study (TLGS)

Minoo  Heidari Almasi; Maryam  Barzin; Sara  Serahati; Majid  Valizadeh; Amirabbas Momenan; Feridoun  Azizi; Farhad  Hosseinpanah

doi:10.18502/ijph.v51i4.9246

Minoo Heidari Almasi Obesity Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
Maryam Barzin Obesity Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
Sara Serahati Department of Public Health, University of Saskatchewan, Saskatoon, SK, Canada
Majid Valizadeh Obesity Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
Amirabbas Momenan Prevention of Metabolic Disorders Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
Feridoun Azizi Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Science, Tehran, Iran
Farhad Hosseinpanah Obesity Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran

DOI: https://doi.org/10.18502/ijph.v51i4.9246

Keywords: Body composition; Bioelectrical impedance analysis (BIA); Cardio-metabolic risk factor

Abstract

Background: We aimed at evaluating the best body mass index (BMI) and percent body fat (PBF) cutoffs related to cardio-metabolic risk factors and comparing the discriminative power of PBF and BMI for predicting these risk factors.

Methods: In this cross-sectional study in phase V (2012-2015), 1271 participants (age ≥ 20 yr; 54.3% women) were enrolled. Bioelectrical impedance analysis (BIA) was used to estimate PBF. Joint Interim Statement criteria were used for defining metabolic syndrome (MetS). We compared PBF with BMI through logistic regression and area under the curve of the receiver operating characteristic (ROC) curve. Percent body fat cutoff points were > 25 in men and >35 in women.

Results: Percent body fat and BMI cutoff points for predicting MetS were 25.6% and 27.2 kg/m² in men and 36.2% and 27.5 kg/m² in women, respectively. There were no significant differences between BMI and PBF area under the ROC curves for predicting MetS and its components, except for abdominal obesity in men and low high-density lipoprotein (HDL) in women in favor of BMI. Logistic regression analysis indicated that BMI in women was better for predicting MetS and its components, except for abdominal obesity. Moreover, BMI was equal or superior to PBF in men, except for low HDL and high triglyceride levels.

Conclusion: Comparison of PBF with BMI showed that the use of PBF is not significantly better than BMI in predicting cardio-metabolic risks in the general population.