Lockard, B

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.

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.

Aim: To compare the efficacy of two popular weight loss approaches on weight loss, body composition, and markers of health in sedentary obese women. Methods: In total, 51 sedentary women (age 34.5 ± 7.7 yrs.; weight 90.0 ± 14.5 kg; BMI 34.0 ± 5.1 kg/m2; 46.5 ± 7.0% fat) were matched and randomized to participate in the Weight Watchers® Momentum™ (WW) or Curves® (CV) Fitness and Weight Management program for 16 weeks. Participants in the WW group (n = 27) were provided a point-based diet program, received weekly progress checks and counseling, and were encouraged to exercise. Participants in the CV group (n = 24) followed a menu-based higher protein/low-fat diet (1200 kcal/d) for 1 week; 1500 kcal/d diet for 3 weeks; and 2000–2500 kcals/d for 2 weeks that was repeated three times (except the last segment) while participating in a supervised circuit-style resistance training program (3 d/wk). A general linear model (GLM) with repeated measures was used to analyze data and are presented as mean changes from baseline (mean [UL, LL]). Results: Supervised CV training resulted in greater amounts of vigorous and total physical activity. After 16 weeks, both groups lost weight (WW −6.1 [−7.8, −4.6], CV −4.9 [−6.2, −3.2] kg, p = 0.264). Participants in the CV group observed greater reductions in fat mass (WW −2.9 [−6.7, −0.2], CV −6.4 [−9.2, −3.6] kg, p = 0.081) and increases in lean mass (WW −2.5 [−4.3, −0.7], CV 1.3 [−0.6, 3.2] kg, p = 0.005) resulting in more favorable changes in percent body fat (WW −1.4 [−4.1, 1.2], CV −4.7 [−7.5, −1.8]%, p = 0.098). Both groups observed improvements in peak aerobic capacity and muscular endurance, although bench press lifting volume was greater in the CV group. Those in the CV group experienced a greater increase in HDLc and reduction in the CHL–HDLc ratio and triglycerides. Conclusion: Both interventions promoted weight loss and improvements in fitness and markers of health. The CV program, which included supervised resistance training and higher protein diet menus, promoted greater fat loss, increases in lean mass, and improvements in percent body fat and blood lipids. Trial Registration: clinicaltrials.gov, #NCT04372771, registered retrospectively 1 May 2020.

(1) Background: Limited information exists on the prevalence of low energy availability (LEA) in collegiate team sports. The purpose of this study was to examine the prevalence of LEA in collegiate women soccer players. (2) Methods: Collegiate women soccer athletes (n = 18, height: 1.67 ± 0.05 m; body mass: 65.3 ± 7.9 kg; body fat %: 24.9 ± 5.6%) had their body composition and sport nutrition knowledge assessed in the pre-season. Energy availability was assessed mid-season using a 4-day dietary log and activity energy expenditure values from a team-based monitoring system. A validated screening tool was used to screen for LEA. (3) Results: The screening tool classified 56.3% of athletes as at risk of LEA (<30 kcal/kg of FFM); however, the actual dietary intake identified 67% as LEA. Athletes identified as non-LEA consumed significantly more absolute (p = 0.040) and relative (p = 0.004) energy than LEA athletes. (4) Conclusions: There was a high prevalence of LEA among collegiate women soccer athletes. Although previously validated in women endurance athletes, the LEA screening tool was not effective in identifying those at risk of LEA in this sample of athletes.