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All Journal Bioscientia Medicina : Journal of Biomedicine and Translational Research
Surya Darma
Division of Rheumatology, Department of Internal Medicine, Faculty of Medicine, Universitas Sriwijaya/Dr. Mohammad Hoesin General Hospital, Palembang, Indonesia
Biochemistry, Genetics & Molecular Biology Immunology & microbiology Medicine & Pharmacology Neuroscience

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Accuracy of Fat Mass and Muscle Mass Measured by Bioelectrical Impedance Analysis in Predicting Osteoporosis in Older Adults Nur Riviati; Ari Dwi Prasetyo; Rizki Bastari; Surya Darma; Erial Bahar
Bioscientia Medicina : Journal of Biomedicine and Translational Research Vol. 9 No. 2 (2025): Bioscientia Medicina: Journal of Biomedicine & Translational Research
Publisher : HM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37275/bsm.v9i2.1191

Abstract

Background: Osteoporosis is a prevalent bone disease characterized by reduced bone mineral density (BMD) and increased fracture risk. This study aimed to evaluate the accuracy of fat mass (FM) and muscle mass measured by bioelectrical impedance analysis (BIA) in predicting osteoporosis in older adults. Methods: A cross-sectional study was conducted on 109 outpatients aged 60 years and older. FM parameters (total fat mass, visceral fat level, and fat mass index [FMI]) and muscle mass parameters (total muscle mass, appendicular skeletal muscle mass [ASM], and appendicular skeletal muscle mass index [ASMI]) were measured using BIA. Osteoporosis was diagnosed based on BMD measurements using dual-energy X-ray absorptiometry (DXA). Receiver operating characteristic (ROC) curves were used to determine cut-off points and assess the accuracy of BIA parameters in predicting osteoporosis. Results: The prevalence of osteoporosis was 52.3% (n=57). The optimal cut-off points for predicting osteoporosis were: total fat mass >36.25%, visceral fat level >12.05, FMI >7.82 kg/m2, total muscle mass <37.82 kg, ASM <16.795 kg, and ASMI <6.895 kg/m2. Among the FM parameters, visceral fat level had the highest accuracy (AUC = 60.9%, sensitivity = 64.9%, specificity = 78.8%) while FMI had the lowest (AUC = 53.5%, sensitivity = 56.1%, specificity = 57.7%). For muscle mass parameters, ASM showed the highest accuracy (AUC = 74.0%, sensitivity = 70.2%, specificity = 76.9%). Conclusion: BIA-derived FM and muscle mass parameters, particularly visceral fat level and ASM can be used to predict osteoporosis in older adults with good accuracy. This non-invasive and accessible method may be useful as a screening tool for osteoporosis, especially in settings where DXA is unavailable.
Co-Authors Ari Dwi Prasetyo Erial Bahar Nur Riviati, Nur Rizki Bastari