MIND THE GAP: CLINICAL CAUTION IN USING MFBIA FOR BODY FAT ASSESSMENT

MR QURESHI; SHS MOHAMMED; MM ALAM; F ASHRAF; SR UMRAO; Z PASCUAL; FU AMIN; MM KHAN

doi:10.64013/bbasr.v2026i1.126

Authors

MR QURESHI Life Core Private Clinic LLC, Royal Group Headquarters (7th Floor), Al Salam Street, PO Box 63811, Abu Dhabi, United Arab Emirates
SHS MOHAMMED Life Core Private Clinic LLC, Royal Group Headquarters (7th Floor), Al Salam Street, PO Box 63811, Abu Dhabi, United Arab Emirates
MM ALAM Life Core Private Clinic LLC, Royal Group Headquarters (7th Floor), Al Salam Street, PO Box 63811, Abu Dhabi, United Arab Emirates
F ASHRAF Life Core Private Clinic LLC, Royal Group Headquarters (7th Floor), Al Salam Street, PO Box 63811, Abu Dhabi, United Arab Emirates
SR UMRAO Life Core Private Clinic LLC, Royal Group Headquarters (7th Floor), Al Salam Street, PO Box 63811, Abu Dhabi, United Arab Emirates
Z PASCUAL Life Core Private Clinic LLC, Royal Group Headquarters (7th Floor), Al Salam Street, PO Box 63811, Abu Dhabi, United Arab Emirates
FU AMIN Life Core Private Clinic LLC, Royal Group Headquarters (7th Floor), Al Salam Street, PO Box 63811, Abu Dhabi, United Arab Emirates
MM KHAN Life Core Private Clinic LLC, Royal Group Headquarters (7th Floor), Al Salam Street, PO Box 63811, Abu Dhabi, United Arab Emirates

DOI:

https://doi.org/10.64013/bbasr.v2026i1.126

Keywords:

impedance-based body composition analysis, dual-energy X-ray absorptiometry, adiposity percentage, body composition measurement, agreement analysis, comparative validation study

Abstract

Impedance-based body composition assessment is commonly used because it is quick, noninvasive, and practical in clinical and field settings. However, its accuracy compared with reference methods can vary across different populations. The current study examined how well multi-frequency bioelectrical impedance analysis (MFBIA; seca mBCA 514) agreed with dual-energy X-ray absorptiometry (DXA) in estimating body fat percentage (BF%) and fat mass in adults. In this agreement study, 45 adults received the same-day body composition measurements using MFBIA and DXA. Agreement between the two methods was evaluated using Bland-Altman analysis, paired statistical tests, effect sizes, and root mean square error (RMSE). Correlation and linear regression analyses were also performed to assess the strength of association and predictive relationship between the methods. The results showed that MFBIA and DXA produced similar estimates for body weight and body mass index (BMI). However, MFBIA consistently underestimated body fat-related measures. Mean BF% was 30.32 ± 8.08% with MFBIA compared with 33.86 ± 7.79% with DXA, resulting in a mean bias of -3.54 percentage points (95% CI: -4.34 to -2.74; p < 0.001; Cohen’s d = -1.33). Bland-Altman analysis demonstrated limits of agreement ranging from -8.75 to +1.67 percentage points for BF% and from -8.41 to +3.40 kg for fat mass, with no evidence of proportional bias. Although BF% estimates from the two methods were strongly correlated (r = 0.945; R² = 0.892), the RMSE of 4.41 percentage points indicated considerable variation at the individual level. Overall, MFBIA showed a strong relationship with DXA measurements but systematically underestimated BF% and fat mass. While the two methods were closely associated, the observed bias and relatively wide limits of agreement suggest that MFBIA should not be used interchangeably with DXA when precise individual-level estimates of body fat percentage are required.

Downloads

Download data is not yet available.

References

Bennett, J. P., and Lim, S. (2025). The critical role of body composition assessment in advancing research and clinical health risk assessment across the lifespan. Journal of Obesity and Metabolic Syndrome34, 120-137. DOI: https://doi.org/10.7570/jomes25010

Bosy-Westphal, A., Later, W., Hitze, B., et al. (2008). Accuracy of bioelectrical impedance consumer devices for measurement of body composition in comparison to whole body magnetic resonance imaging and dual X-ray absorptiometry. Obesity Facts1, 319-324. DOI: https://doi.org/10.1159/000176061

Bosy-Westphal, A., Schautz, B., Later, W., et al. (2013). What makes a BIA equation unique? Validity of eight-electrode multifrequency BIA to estimate body composition in a healthy adult population. European Journal of Clinical Nutrition67 Suppl 1, S14-S21. DOI: https://doi.org/10.1038/ejcn.2012.160

Day, K., Kwok, A., Evans, A., et al. (2018). Comparison of a bioelectrical impedance device against the reference method dual energy X-ray absorptiometry and anthropometry for the evaluation of body composition in adults. Nutrients10, 1469. DOI: https://doi.org/10.3390/nu10101469

Dehghan, M., and Merchant, A. T. (2008). Is bioelectrical impedance accurate for use in large epidemiological studies? Nutrition Journal7, 26. DOI: https://doi.org/10.1186/1475-2891-7-26

Feng, Q., Bešević, J., Conroy, M., et al. (2024). Comparison of body composition measures assessed by bioelectrical impedance analysis versus dual-energy X-ray absorptiometry in the United Kingdom Biobank. Clinical Nutrition ESPEN63, 214-225. DOI: https://doi.org/10.1016/j.clnesp.2024.06.040

Genton, L., Hans, D., Kyle, U. G., and Pichard, C. (2002). Dual-energy X-ray absorptiometry and body composition: differences between devices and comparison with reference methods. Nutrition18, 66-70. DOI: https://doi.org/10.1016/S0899-9007(01)00700-6

Goldfield, G. S., Cloutier, P., Mallory, R., et al. (2006). Validity of foot-to-foot bioelectrical impedance analysis in overweight and obese children and parents. Journal of Sports Medicine and Physical Fitness46, 447-453.

Heymsfield, S. B., and Wadden, T. A. (2017). Mechanisms, pathophysiology, and management of obesity. New England Journal of Medicine376, 254-266. DOI: https://doi.org/10.1056/NEJMra1514009

Kabiri, L. S., Hernandez, D. C., and Mitchell, K. (2015). Reliability, validity, and diagnostic value of a pediatric bioelectrical impedance analysis scale. Childhood Obesity11, 650-655. DOI: https://doi.org/10.1089/chi.2014.0156

Kyle, U. G., Earthman, C. P., Pichard, C., and Coss-Bu, J. A. (2015). Body composition during growth in children: limitations and perspectives of bioelectrical impedance analysis. European Journal of Clinical Nutrition69, 1298-1305. DOI: https://doi.org/10.1038/ejcn.2015.86

Lahav, Y., Goldstein, N., and Gepner, Y. (2021). Comparison of body composition assessment across body mass index categories by two multifrequency bioelectrical impedance analysis devices and dual-energy X-ray absorptiometry in clinical settings. European Journal of Clinical Nutrition75, 1275-1282. DOI: https://doi.org/10.1038/s41430-020-00839-5

Ling, C. H., de Craen, A. J., Slagboom, P. E., et al. (2011). Accuracy of direct segmental multi-frequency bioimpedance analysis in the assessment of total body and segmental body composition in middle-aged adults’ population. Clinical Nutrition30, 610-615. DOI: https://doi.org/10.1016/j.clnu.2011.04.001

Nathan, B. M., and Moran, A. (2008). Metabolic complications of obesity in childhood and adolescence: more than just diabetes. Current Opinion in Endocrinology, Diabetes and Obesity15, 21-29. DOI: https://doi.org/10.1097/MED.0b013e3282f43d19

Sim, P. Y., Su, T. T., Abd, M. H., et al. (2014). A comparison study of portable foot-to-foot bioelectrical impedance scale to measure body fat percentage in Asian adults and children. BioMed Research International2014, 475659. DOI: https://doi.org/10.1155/2014/475659

Sun, G., French, C. R., Martin, G. R., et al. (2005). Comparison of multifrequency bioelectrical impedance analysis with dual-energy X-ray absorptiometry for assessment of percentage body fat in a large, healthy population. American Journal of Clinical Nutrition81, 74-78. DOI: https://doi.org/10.1093/ajcn/81.1.74

Talma, H., Chinapaw, M. J., Bakker, B., et al. (2013). Bioelectrical impedance analysis to estimate body composition in children and adolescents: a systematic review and evidence appraisal of validity, responsiveness, reliability and measurement error. Obesity Reviews14, 895-905. DOI: https://doi.org/10.1111/obr.12061

Wells, J. C., and Fewtrell, M. S. (2006). Measuring body composition. Archives of Disease in Childhood91, 612-617. DOI: https://doi.org/10.1136/adc.2005.085522

Wells, J. C., Fuller, N. J., Dewit, O., et al. (1999). Four-component model of body composition in children: density and hydration of fat-free mass and comparison with simpler models. American Journal of Clinical Nutrition69, 904-912. DOI: https://doi.org/10.1093/ajcn/69.5.904

Zeng, Q., Dong, S. Y., Sun, X. N., Xie, J., and Cui, Y. (2012). Percent body fat is a better predictor of cardiovascular risk factors than body mass index. Brazilian Journal of Medical and Biological Research45, 591-600. DOI: https://doi.org/10.1590/S0100-879X2012007500059