Validation and diagnostic accuracy of a multi-frequency bioelectrical impedance analysis device with dual-energy X-ray absorptiometry (DXA) for estimating body composition among healthy Malaysian adults

Background: Precise assessment of body composition is critical for managing obesity and sarcopenia, both of which are rising health concerns around the globe. While dual-energy X-ray absorptiometry (DXA) remains the gold standard, its high cost and limited accessibility hinder large-scale application. Multi-frequency bioelectrical impedance analysis (MF-BIA) shows promise as an alternative method, but validation in specific populations remains necessary.Objectives: This study aimed to validate and evaluate the diagnostic accuracy of the InBody 970S MF-BIA device in estimating body composition parameters against DXA among healthy Malaysian adults.Methods: A prospective validation study was conducted among 148 healthy adults aged 20–45 years. Participants underwent standardised assessments using MF-BIA (InBody 970S) and full-body DXA. Linear regression, paired t-tests, Bland–Altman plots, and diagnostic performance indices (sensitivity, specificity, PPV, NPV) were used to evaluate the agreement between methods for fat mass (BFM), lean body mass (LBM), fat-free mass (FFM), percent body fat (PBF), bone mineral content (BMC), and skeletal muscle mass index (SMI).Results: MF-BIA showed strong correlations with DXA across all parameters (R2 = 0.72–0.97). The predictive models for BFM, LBM, and PBF demonstrated high accuracy (e.g., BFM: R2 = 0.96; LBM: R2 = 0.96; FFM: R2 = 0.97). Diagnostic agreement was particularly strong for sarcopenia (sensitivity = 95.1%, NPV = 98.0%) and obesity classification (specificity and PPV = 100%), though obesity sensitivity was lower (75.2%). Bland–Altman analysis confirmed acceptable limits of agreement.Conclusion: MF-BIA offers a clinically valid, non-invasive, and accessible method for body composition assessment in Malaysian adults. Its utility in identifying obesity and sarcopenia risk supports its integration into routine clinical practice and public health screening, especially in resource-limited settings. Future work should explore ethnic-specific calibration to enhance its diagnostic precision across diverse populations.