Cross-Sectional and Longitudinal Validity of Automated Body Composition Methods in U.S. Air Force Reserve Officers'...

Accurate assessment of body composition is essential for evaluating and maintaining military readiness among U.S. Air Force Reserve Officers' Training Corps (AFROTC) cadets, who must meet the same standards as active-duty personnel. Current reliance on BMI and circumference-based methods often leads to misclassification because of measurement variability and the inability to distinguish between lean and fat mass. Although laboratory methods like dual-energy X-ray absorptiometry (DXA) are ideal, their high cost, limited portability, and the need for trained personnel make them impractical for field use. During training or deployment, these limitations also hinder consistent monitoring when access to fitness and nutrition resources is most restricted. Therefore, this study examined the cross-sectional and longitudinal accuracy of body fat percentage (BF%) estimates obtained from the following emerging, field-based technologies compared with DXA and current AFROTC circumference-based methods in AFROTC cadets assessed before and after a 12-week training program: bioelectrical impedance spectroscopy (BIS), near-infrared spectroscopy (NIRS), smartwatch bioelectrical impedance analysis (SWBIA), and smartphone-based three-dimensional optical scanning (3DO).

At baseline before the 12-week training program, 57 cadets (26 F, 31 M; BF%: 27.2 ± 9.5%) underwent body composition assessments using DXA, circumference-based equations, BIS, NIRS, SWBIA, and 3DO to assess cross-sectional validity. 3DO-derived circumferences were also substituted for manual measures in circumference-based equations. A subset of 50 cadets returned after the program to assess longitudinal validity, defined as the agreement between the change in the BF% from DXA and those produced by each field method. Cross-sectional and longitudinal validity were assessed using null-hypothesis significance and equivalence testing, coefficients of determination, concordance correlation coefficients, root mean square error, Bland-Altman analyses, and Deming regression. Classification accuracy based on AFROTC BF% standards was assessed at baseline using sensitivity and specificity analyses. The University Institutional Review Board approved the study, and informed consent was obtained before participation.

Although most cadets met the AFROTC BMI standards (57.9%), only one-third met the DXA-derived BF% standards (33.3%), indicating false compliance when using BMI alone. Cross-sectionally, NIRS and SWBIA demonstrated the lowest measurement error and the highest accuracy for classifying cadets according the AFROTC BF% guidelines. Longitudinally, changes in BF% from 3DO and NIRS demonstrated the strongest agreement with DXA. Overall performance comparisons indicated that NIRS, SWBIA, and 3DO provided the most accurate and consistent BF% estimates relative to DXA, while traditional circumference-based equations produced the largest errors.

NIRS, SWBIA, and 3DO provide accurate, portable alternatives to DXA for assessing BF% in AFROTC cadets. Despite most cadets meeting BMI standards and the widespread use of circumference-based equations in practice, our findings that the majority of cadets exceeded DXA-derived BF% standards, and that circumference-based estimates were the least accurate, highlight the limitations of current assessment methods. Strengths include direct comparison with DXA and both cross-sectional and longitudinal assessments, although limitations include reliance on a single cohort and modest BF% changes. Overall, these findings support integrating these accessible, user-friendly technologies into military health and fitness assessments, with future studies warranted in larger cohorts undergoing differential training programs across varied settings.