Abstract
Bone mineral content (BMC) serves as an important indicator of osteoporosis risk. Traditional methods of BMC estimation include using demographic information within prediction equations, which draw from population trends but may not reflect individual variance in BMC. Dual-energy X-ray absorptiometry (DXA) provides a more accurate assessment of BMC but may pose challenges in clinical settings due to certification requirements, cost, and space requirements. Bioelectrical impedance analysis (BIA) has shown promise in correlating with BMC and may offer an intriguing alternative due to its accessibility, but its efficacy compared to traditional methods remains largely unexplored. PURPOSE: Quantify the contribution of BIA assessment on accuracy of BMC estimations compared to the traditional demographic information alone. METHODS: Three-hundred and twelve adults (n=193 F, n=119 M; [mean ± SD] age: 30.2 ± 13.0 y; body mass: 71.2 ± 14.7 kg; height: 169.6 ± 9.1 cm; body fat: 27.8 ± 8.7%) completed DXA and standing multi-frequency bioelectrical impedance analysis (MFBIA) assessments in a single laboratory visit. Two multiple linear regression models were fit to predict DXA BMC. The demographic model included age, sex, weight, and height as predictors, while the demographic + bioimpedance model additionally included total body bioelectrical resistance at the 50 kHz frequency. Regression model performance was quantified by the R2, root mean square error (RMSE), and Akaike information criterion (AIC). RESULTS: In both models, weight, height and the male sex were positively related to BMC, while age was negatively related to BMC (p<0.01 for all). Although bioelectrical resistance was negatively related to DXA BMC (p<0.01), it exerted a minimal improvement in the overall regression model performance (demographic model: R2: 0.79, RMSE: 241 g, AIC: 4321; demographic + bioimpedance model: R2: 0.82, RMSE: 225 g, AIC: 4280). CONCLUSIONS: The inclusion of bioelectrical impedance analysis (BIA) resulted in only a modest improvement in model performance compared to the demographic model. These findings suggest that BIA-derived BMC estimations may not provide clinically significant benefit, nor should the BMC estimation provided by BIA hold substantially greater weight in the minds of clinicians and patients alike. Though this study did not indicate the need for widespread implementation of BIA-derived BMC assessments, further experimentation involving a more diverse population, particularly for those at greater risk of osteoporosis, could offer valuable insight into the potential of BIA in accurate monitoring and detection.
Recommended Citation
Whitson, Julia A.; Rodriguez, Christian; Florez, Christine M.; Tinoco, Ethan; Cardoso, Joao P.; Rasco, Jaylynn; Francis, Sieneh; and Tinsley, Grant M.
(2025)
"Bioimpedance Minimally Improves Prediction of Bone Mineral Density Beyond Demographic Information Alone,"
International Journal of Exercise Science: Conference Proceedings: Vol. 2:
Iss.
17, Article 20.
Available at:
https://digitalcommons.wku.edu/ijesab/vol2/iss17/20
