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Stroiney, Debra A.

Mayo Clinic

George Mason University

Citations 4

Influence of Individual Traits on Measurement Differences in Percent Body Fat
Magee, Meghan K., Miller, Angela D. , Fields, Jennifer B, Lockard, B , Stroiney, Debra A., Jones, Margaret T, Jones, Margaret T , Jagim, Andrew R.

International Journal of Sports Medicine | March 12, 2026 | Volume: 47 | Issue: 08 | Pages: 599-604

10.1055/a-2785-7668 Get It

Abstract The purpose of the current study was to identify the influence of individual characteristics on differences in body fat percentage between air displacement plethysmography and dual-energy X-ray absorptiometry (change in body fat percentage) in 360 collegiate student-athletes. Body fat percentage was obtained from air displacement plethysmography and dual-energy X-ray absorptiometry. A 2 (sex)×3 (Brozek body fat percentage, Siri body fat percentage, and dual-energy x-ray absorptiometry body fat percentage) analysis of variance was used to evaluate the difference between the body fat percentages obtained from air displacement plethysmography and dual-energy x-ray absorptiometry in men and women. The agreement between air displacement plethysmography and dual-energy X-ray absorptiometry was evaluated via Bland–Altman plot and linear regression. Multiple linear regression was used to identify the influence of sex, race, height, and body mass on the change in body fat percentages. Dual-energy X-ray absorptiometry yielded greater body fat percentages in both men (4.8±2.8; p < 0.001) and women (2.2±2.9; p < 0.001) compared to air displacement plethysmography measurements. Proportional and systematic biases were observed between air displacement plethysmography and dual-energy X-ray absorptiometry. Race, height, and mass were significant predictors of the body fat percentage difference between air displacement plethysmography and dual-energy X-ray absorptiometry (R 2=0.445, p<0.001, and standard error of the estimate=2.527). The present study suggests that air displacement plethysmography underestimates body fat percentages when compared to dual-energy X-ray absorptiometry and this underestimation may not be the same for every athlete due to their individual characteristics.
Estimation of Whole-Body Bone Mineral Density Through Air Displacement Plethysmography in a Large Sample of Elite Athletes
Magee, Meghan K., Fields, Jennifer B. , Lockard, B , Miller, Angela D. , Stroiney, Debra A., Jones, Margaret T. , Jagim, Andrew, Jones, Margaret T , Jagim, Andrew R.

Journal of Strength & Conditioning Research | September 10, 2025 | Volume: 39 | Issue: 4 | Pages: 427-432

10.1519/jsc.0000000000005024 Get It

Abstract Magee, MK, Fields, JB, Jagim, A, Lockard, B, Miller, A, Stroiney, D, and Jones, MT. Estimation of whole-body bone mineral density through air displacement plethysmography in a large sample of elite athletes. J Strength Cond Res 39(4): 427–432, 2025—Dual-energy x-ray absorptiometry (DXA) is used to determine bone mineral density (BMD) and body composition. Regulations and cost may limit DXA's utility in some athletic settings. Air displacement plethysmography (ADP), while able to measure body composition, does not measure BMD. The purpose was to evaluate the influence of body composition parameters obtained from ADP on BMD. Collegiate athletes (males, n = 153; females, n = 208) underwent ADP and DXA assessments. For ADP testing, the Brozek equation was used to estimate body fat percent (BF%) and fat-free mass (FFM) from body density. Dual-energy x-ray absorptiometry tests were completed to obtain BMD using the whole-body scan mode. Stepwise regression was conducted using age, body mass, height, sex, race, FFM (ADP), BF% (ADP), and sport type as independent variables. Total BMD (DXA) was the dependent variable. Accuracy and precision of the final equation were evaluated through Bland–Altman and linear regression. The final regression equation yielded an R 2 of 0.691 with race, mass, BF%, age, and sport type as significant predictors ( p < 0.05) of BMD. Bland–Altman and linear regression showed systematic {95% confidence interval [CI] (−0.619 to −0.360)} and proportional bias (95% CI [0.173–0.374]). Although an ADP-derived regression equation may not provide a precise prediction of BMD, it may be useful to establish risk for low BMD if DXA is unavailable. Dual-energy x-ray absorptiometry may not be feasible for some athletic programs; therefore, an estimation equation for BMD derived from ADP values is advantageous for practitioners. This equation may assist in screening athletes for risk of low BMD.
A new estimation equation to assess body composition in an athletic population
Magee, Meghan K., Miller, Angela D. , Stroiney, Debra A., Lockard, B , Jones, Margaret T. , Jagim, Andrew R , Jones, Margaret T , Jagim, Andrew R.

Journal of the International Society of Sports Nutrition | May 28, 2025 | Volume: 22 | Issue: 1 | Pages: No page available

10.1080/15502783.2025.2504578 Get It

Differences In BMD Z-scores Of Athletes Participating In Difference Sports Types
Magee, Meghan K., Fields, Jennifer B. , Lockard, B , Stroiney, Debra A., Jones, Margaret T. , Jagim, Andrew R.

Medicine & Science in Sports & Exercise | September 16, 2024 | Volume: 56 | Issue: 10S | Pages: 71-72

10.1249/01.mss.0001053104.98165.bd Get It