Accuracy of Fat Mass and Muscle Mass Measured by Bioelectrical Impedance Analysis in Predicting Osteoporosis in Older Adults

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.

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Journal
Bioscientia Medicina Journal of Biomedicine and Translational Research
Published
2024-11-25
DOI
https://doi.org/10.37275/bsm.v9i2.1191
Citations
1
Primary Topic
Body Composition Measurement Techniques
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article
Field-Weighted Citation Impact
0.33
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article

Accuracy of Fat Mass and Muscle Mass Measured by Bioelectrical Impedance Analysis in Predicting Osteoporosis in Older Adults

Andika Prasetyo, Surya Darma, Erial Bahar, Rizki Bastari et al.
1 citations
Bioscientia Medicina Journal of Biomedicine and Translational Research
Body Composition Measurement Techniques
0.33
article

Accuracy of Fat Mass and Muscle Mass Measured by Bioelectrical Impedance Analysis in Predicting Osteoporosis in Older Adults

Andika Prasetyo, Surya Darma, Erial Bahar, Rizki Bastari, Nur Riviati
article en
1 citations

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.

Bioscientia Medicina Journal of Biomedicine and Translational ResearchVol. 9(2)
Sriwijaya University (ID)
Affordable and clean energy
Openalex Percentile: Top 36%
Body Composition Measurement Techniques
0.33
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