Body composition measures assessed by bioelectrical impedance analysis and dual-energy X-ray absorptiometry in a sample of Brazilian adults and older adults

Vivian Wahrlich¹Agnes Ciafrino²Amina Chain Costa³Francine Moreira Bossan²Valéria Troncoso Baltar⁴Luiz Antonio dos Anjos^1*

• ¹Laboratório de Avaliação Nutricional e Funcional, Departamento de Nutrição Social, Programa de Pós-Graduação em Ciências da Nutrição, Universidade Federal Fluminense, Niterói, Brazil
• ²Laboratório de Avaliação Nutricional e Funcional, Departamento de Nutrição Social, Universidade Federal Fluminense, Niterói, Brazil
• ³Laboratório de Avaliação Nutricional e Funcional, Departamento de Nutrição Social, Programa de Pós-Graduação em Ciências da Nutrição and Programa de Pós-Graduação em Saúde Coletiva, Universidade Federal Fluminense, Niterói, Brazil
• ⁴3Departamento de Epidemiologia e Bioestatística, Instituto de Saúde Coletiva, Programa de Pós-Graduação em Saúde Coletiva and Programa de Pós-Graduação em Ciências da Nutrição, Universidade Federal Fluminense, Niterói, Brazil

Introduction: Bioelectrical impedance analysis (BIA) is a common technique for assessing body composition in clinical and epidemiological settings. However, its accuracy is limited compared to reference methods like dual-energy X-ray absorptiometry (DXA). Purpose: This study aimed to evaluate the agreement between fat-free mass (FFM) and fat mass (FM) measured by BIA (Tanita BC-418) and DXA, and to develop a calibration model to correct BIA estimates in a heterogeneous sample of Brazilian adults and older adults. Methods: We analyzed data from 945 participants (aged≥18 years; 611 women) who underwent both BIA and DXA assessments across multiple cross-sectional research projects. Agreement between BIA and DXA measures of FFM (BIAFFM and DXAFFM) and fat mass (FM) was assessed using Pearson correlation coefficients (r) for precision and Lin's concordance correlation coefficients (CCC) for accuracy. Mean absolute and relative differences were evaluated with paired t-tests or Anova for sex, age and nutritional status based on body mass index (BMI). Linear regression was employed to calibrate BIAFFM against DXAFFM. A multivariate prediction model for DXAFFM was developed using BIA-derived resistance, stature, body mass, and age in a randomly selected subsample (70%, n=659) and validated in the remaining 30% (n=286). Results: BIA and DXA measures were highly correlated for both FFM and FM (r=0.97) and demonstrated moderate to high accuracy (CCC≥0.93). For the entire sample, BIA overestimated FFM by 3.1 kg (SD=2.4; +7.2%) and underestimated FM by 2.9 kg (2.3; - 13.0%) compared to DXA (both p<0.0001). The resulting calibration equation for FFM was DXAFFM=0.94420×BIAFFM)–(0.01128xAge)+0.20516. The multivariate prediction equation derived from the development group was: FFM (kg)=(Sex×4.1797)+(Stature [cm]×0.1062)+(Resistance Index [cm²/Ω]×0.5289)+(Body Mass [kg]×0.1797)-(Age [yrs]×0.0705)-5.4286 (women=0, men=1). In the validation group, both the calibrated BIAFFM and the value from the predicted by the new multivariate equation showed no statistically significant difference from the actual DXAFFM measurement. Conclusion: Significant discrepancies exist between the BIA-and DXA-derived body composition measures in this heterogeneous sample of Brazilians. The developed prediction equations effectively calibrated BIAFFM estimates to align with DXA values, providing a practical method to enhance the accuracy of the BIA system in body composition estimates in this population.