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Cross-Sectional and Longitudinal Validity of Automated Body Composition Methods in U.S. Air Force Reserve Officers'
Austin J Graybeal1, Sheena Puleali'i2, Christian Rodriguez3
1Department of Kinesiology, Harris College of Nursing and Health Sciences, Texas Christian University, Fort Worth, TX 76129, United States.
New body fat percentage (BF%) assessment technologies, near-infrared spectroscopy (NIRS), smartwatch bioelectrical impedance analysis (SWBIA), and 3D optical scanning (3DO), accurately estimate body composition in U.S. Air Force Reserve Officers' Training Corps (AFROTC) cadets compared to dual-energy X-ray absorptiometry (DXA). These portable methods offer a viable alternative to less accurate traditional circumference-based measurements for military readiness assessments.
Area of Science:
- Military health and fitness
- Body composition analysis
- Biomedical engineering
Background:
- Accurate body composition assessment is critical for U.S. Air Force Reserve Officers' Training Corps (AFROTC) cadet military readiness.
- Current methods like Body Mass Index (BMI) and circumference-based measurements often misclassify body fat percentage (BF%).
- Laboratory methods (e.g., DXA) are accurate but impractical for field use due to cost and portability limitations.
Purpose of the Study:
- To evaluate the cross-sectional and longitudinal accuracy of emerging field-based body fat percentage (BF%) technologies.
- To compare these technologies against dual-energy X-ray absorptiometry (DXA) and current AFROTC circumference-based methods.
- To assess the classification accuracy of these methods against established AFROTC BF% standards.
Main Methods:
- Fifty-seven AFROTC cadets underwent baseline body composition assessments using DXA, circumference equations, bioelectrical impedance spectroscopy (BIS), near-infrared spectroscopy (NIRS), smartwatch bioelectrical impedance analysis (SWBIA), and 3D optical scanning (3DO).
- A subset of 50 cadets were reassessed after a 12-week training program to evaluate longitudinal validity.
- Statistical analyses included equivalence testing, concordance correlation coefficients, Bland-Altman analyses, and Deming regression; sensitivity and specificity were used for classification accuracy.
Main Results:
- Most cadets met BMI standards (57.9%), but only one-third met DXA-derived BF% standards (33.3%), highlighting BMI's limitations.
- Cross-sectionally, NIRS and SWBIA showed the lowest measurement error and highest accuracy for classifying cadets according to AFROTC BF% guidelines.
- Longitudinally, BF% changes from 3DO and NIRS demonstrated the strongest agreement with DXA; NIRS, SWBIA, and 3DO provided the most accurate BF% estimates overall, outperforming traditional methods.
Conclusions:
- Near-infrared spectroscopy (NIRS), smartwatch bioelectrical impedance analysis (SWBIA), and 3D optical scanning (3DO) offer accurate and portable alternatives to DXA for assessing body fat percentage in AFROTC cadets.
- Traditional circumference-based equations demonstrated the largest errors, and the majority of cadets exceeded DXA-derived BF% standards, underscoring the inadequacy of current assessment practices.
- These accessible technologies should be integrated into military health and fitness assessments, with further research in diverse cohorts and settings recommended.
