Elsevier

Clinical Nutrition

Volume 38, Issue 5, October 2019, Pages 2175-2179
Clinical Nutrition

Original article
Body composition using bioelectrical impedance: Development and validation of a predictive equation for fat-free mass in a middle-income country

https://doi.org/10.1016/j.clnu.2018.09.012Get rights and content

Summary

Objective

We developed and described a new equation to estimate fat-free mass derived from BIA using a sample population from Brazil and having Dual-energy X-ray absorptiometry (DXA) as the reference method. We also compared this new equation with two published and widely used equations developed in high-income countries.

Methods

Cross-sectional study with 294 healthy adults from Pelotas, Brazil. DXA was used to assess total fat mass and fat-free mass aiming to obtain reference measures for the development of the new BIA equation. Multivariable linear regression models including fractional polynomials were used to find the best predictive model for FFM, using resistance, reactance, age, weight and height as the independent variables. Models were developed separately for men and women. The bootstrapping method was used to test the validity of the new equation. Finally, the Bland-Altman approach was used to assess the agreement of our equations and the two others widely used equations with the FFM measured by DXA.

Results

The new equations explained more than 80% of the variation in fat-free mass percentage from DXA. In the bootstrapping analysis, the new equations presented good validity, as the corrected RMSE was similar to those found in regression analysis. Finally, the new equations presented a better concordance when compared to two validated equations from US and Switzerland.

Conclusion

The new developed equations appear to be the best options to predict fat-free mass percentage in Brazilian adults by bioelectrical impedance and appear to fit well in all Brazilian population due to the good validity presented.

Section snippets

Background

Obesity is a major public health problem and very high levels of body fat play a significant role in the development of non-communicable diseases and mortality [1], [2]. Obesity traditionally has been assessed using body mass index (BMI) but the accuracy of this approach has been questioned because it does not distinguish fat mass (FM) from fat-free mass (FFM) [3].

Despite the good accuracy of some body composition methods, such as the four-compartment model, their complexity along with

Subjects

Cross-sectional study carried out between August 2007 and December 2008 with 302 healthy individuals aged 20–79 years from Pelotas, Brazil. Pelotas is a city located in Southern Brazil with 330,000 inhabitants, according to the last Brazilian census. For this study, a sample with 302 individuals was considered enough to allow the development of a predictive equation to assess adult body composition using BIA parameters. To guarantee that different age groups were equally represented, 50

Results

We included 294 individuals (47.3% men) who average aged 46.3 years. Eight individuals were excluded due to inability to perform DXA exams (presence of prosthesis or BMI ≥40 kg/m2). Regarding anthropometric characteristics, the mean weight was 72 ± 13.4 kg while the mean height was 164 ± 9.3 cm. When the results were stratified by age and sex, we observed that both men and women ≥60 years of age presented higher BMI and waist circumference and lower height. There was no difference in mean

Discussion

BIA is an alternative method to estimate body composition and has been used in several investigations [14], [15], [16], [17], [18], since it is less invasive and less expensive than other techniques like DXA, computerized tomography, and magnetic resonance imaging. Bioelectrical impedance analysis is an easy-to-use and low-cost method for the estimation of fat-free mass (FFM) in healthy individuals and in physiological and pathological conditions [19], [20], [21]. However, the BIA equation's

Conflict of interest

The authors declare no conflict of interest related to this study.

Acknowledgements

This study was conducted by MCG, SPO, LPS and AJDB. MCG designed and conducted the research, helped in analyzing data and in drafting the manuscript. SPO helped in data collection, in analyzing data and drafted the manuscript. LPS performed the statistical analyses and drafted the manuscript. AJDB designed and conducted the research, helped in analyzing data and reviewed the final version of the manuscript.

This study was supported by the Brazilian Research Council (CNPq) through the grant

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