Resistance training and maintenance of a higher protein diet have been recommended to help older individuals maintain muscle mass. This study examined whether adherence to a higher protein diet while participating in a resistance-based exercise program promoted more favorable changes in body composition, markers of health, and/or functional capacity in older females in comparison to following a traditional higher carbohydrate diet or exercise training alone with no diet intervention. In total, 54 overweight and obese females (65.9 ± 4.7 years; 78.7 ± 11 kg, 30.5 ± 4.1 kg/m2, 43.5 ± 3.6% fat) were randomly assigned to an exercise-only group (E), an exercise plus hypo-energetic higher carbohydrate (HC) diet, or a higher protein diet (HP) diet. Participants followed their respective diet plans and performed a supervised 30-min circuit-style resistance exercise program 3 d/wk. Participants were tested at 0, 10, and 14 weeks. Data were analyzed using univariate, multivariate, and repeated measures general linear model (GLM) statistics as well as one-way analysis of variance (ANOVA) of changes from baseline with [95% confidence intervals]. Results revealed that after 14 weeks, participants in the HP group experienced significantly greater reductions in weight (E −1.3 ± 2.3, [−2.4, −0.2]; HC −3.0 ± 3.1 [−4.5, −1.5]; HP −4.8 ± 3.2, [−6.4, −3.1]%, p = 0.003), fat mass (E −2.7 ± 3.8, [−4.6, −0.9]; HC −5.9 ± 4.2 [−8.0, −3.9]; HP −10.2 ± 5.8 [−13.2, –7.2%], p < 0.001), and body fat percentage (E −2.0 ± 3.5 [−3.7, −0.3]; HC −4.3 ± 3.2 [−5.9, −2.8]; HP −6.3 ± 3.5 [−8.1, −4.5] %, p = 0.002) with no significant reductions in fat-free mass or resting energy expenditure over time or among groups. Significant differences were observed in leptin (E −1.8 ± 34 [−18, 14]; HC 43.8 ± 55 [CI 16, 71]; HP −26.5 ± 70 [−63, −9.6] ng/mL, p = 0.001) and adiponectin (E 43.1 ± 76.2 [6.3, 79.8]; HC −27.9 ± 33.4 [−44.5, −11.3]; HP 52.3 ± 79 [11.9, 92.8] µg/mL, p = 0.001). All groups experienced significant improvements in muscular strength, muscular endurance, aerobic capacity, markers of balance and functional capacity, and several markers of health. These findings indicate that a higher protein diet while participating in a resistance-based exercise program promoted more favorable changes in body composition compared to a higher carbohydrate diet in older females.

Vitamin D and calcium supplementation have been posited to improve body composition and different formulations of calcium may impact bioavailability. However, data are lacking regarding the combinatorial effects of exercise, diet, and calcium and/or vitamin D supplementation on body composition changes in post-menopausal women. Herein, 128 post-menopausal women (51.3 ± 4.5 years, 36.4 ± 5.7 kg/m2, 46.2 ± 4.5% fat) were assigned to diet and supplement groups while participating in a supervised circuit-style resistance-training program (3 d/week) over a 14-week period. Diet groups included: (1) normal diet (CTL), (2) a low-calorie, higher protein diet (LCHP; 1600 kcal/day, 15% carbohydrates, 55% protein, 30% fat), and (3) a low-calorie, higher carbohydrate diet (LCHC; 1600 kcal/day, 55% carbohydrates, 15% protein, 30% fat). Supplement groups consisted of: (1) maltodextrin (PLA), (2) 800 mg/day of calcium carbonate (Ca), and (3) 800 mg/day of calcium citrate and malate and 400 IU/day of vitamin D (Ca+D). Fasting blood samples, body composition, resting energy expenditure, aerobic capacity, muscular strength and endurance measures were assessed. Data were analyzed by mixed factorial ANOVA with repeated measures and presented as mean change from baseline [95% CI]. Exercise training promoted significant improvements in strength, peak aerobic capacity, and blood lipids. Dieting resulted in greater losses of body mass (CTL −0.4 ± 2.4; LCHC −5.1 ± 4.2; LCHP −3.8 ± 4.2 kg) and fat mass (CTL −1.4 ± 1.8; LCHC −3.7 ± 3.7; LCHP −3.4 ± 3.4 kg). When compared to LCHC-PLA, the LCHC + Ca combination led to greater losses in body mass (PLA −4.1 [−6.1, −2.1], Ca −6.4 [−8.1, −4.7], Ca+D −4.4 [−6.4, −2.5] kg). In comparison to LCHC-Ca, the LCHC-Ca+D led to an improved maintenance of fat-free mass (PLA −0.3 [−1.4, 0.7], Ca −1.4 [−2.3, −0.5], Ca+D 0.4 [−0.6, 1.5] kg) and a greater loss of body fat (PLA −2.3 [−3.4, −1.1], Ca −1.3 [−2.3, −0.3], Ca+D −3.6 [−4.8, −2.5]%). Alternatively, no significant differences in weight loss or body composition resulted when adding Ca or Ca+D to the LCHP regimen in comparison to when PLA was added to the LCHP diet. When combined with an energy-restricted, higher carbohydrate diet, adding 800 mg of Ca carbonate stimulated greater body mass loss compared to when a PLA was added. Alternatively, adding Ca+D to the LCHC diet promoted greater% fat changes and attenuation of fat-free mass loss. Our results expand upon current literature regarding the impact of calcium supplementation with dieting and regular exercise. This data highlights that different forms of calcium in combination with an energy restricted, higher carbohydrate diet may trigger changes in body mass or body composition while no impact of calcium supplementation was observed when participants followed an energy restricted, higher protein diet.

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The purpose of this study was to compare the accuracy of commercially-available physical activity devices when walking and running at various treadmill speeds using CTA 2056: Physical Activity Monitoring for Fitness Wearables: Step Counting, standard by the Consumer Technology Association (CTA). Twenty participants (10 males and 10 females) completed self-paced walking and running protocols on the treadmill for five minutes each. Eight devices (Apple iWatch series 1, Fitbit Surge, Garmin 235, Moto 360, Polar A360, Suunto Spartan Sport, Suunto Spartan Trainer, and TomTom Spark 3) were tested two at a time, one per wrist. Manual step counts were obtained from video to serve as the benchmark. The mean absolute percent error (MAPE) was calculated during walking and running. During walking, three devices: Fitbit Surge (11.20%), Suunto Sport (22.93%), and TomTom (10.11%) and during running, one device, Polar (10.66%), exceeded the CTA suggestion of a MAPE < 10%. The Moto 360 had the lowest MAPE of all devices for both walking and running. The devices tested had higher step accuracy with running than walking, except for the Polar. Overall, the Apple iWatch series 1, Moto 360, Garmin, and Suunto Spartan Trainer met the CTA standard for both walking and running.

The purpose of this study was to retrospectively assess relationships between strength and conditioning (SC) measures and game performance in Division I volleyball. Five years of SC and game data were collected from one women's Division I collegiate team, n = 76. SC measures included: T-drill, 18.3 m sprint, back squat, hang clean, vertical jump, and broad jump. All game and SC stats were normalized to Z-scores. Analyses included assessing SC differences by position, and multiple stepwise regression to assess relationships between game and SC stats. There was a significant difference by position for broad jump (p =.002), 18.3 m sprint (p =.036), vertical (p <.001), and total strength (p =.019). Overall, game performance and SC measures were significantly correlated (r = .439, p <.001). Multiple regression analyses indicated significant relationships (p < .05) between SC measures and game success by position as follows: defensive specialist stats with squat and total strength; setters game stats with hang cleans, T-drill, and broad jump; pin hitter game stats with vertical, squat, and total strength; middle blockers game stats with broad jump. These data indicate that SC measures correlate well with game performance and are specific by position. These data could help SC coaches create a more precise training approach to focus on improving specific measures by position, which could then translate to improved game performance. These data could also help coaches with talent identification to determine playing time and rotations to maximize player ability and achieve success.

Objective. To determine if supplementation of protein and amino acids (PAA) decreases skeletal muscle expression of atrophy-related genes, muscle mass, and strength during immobilization in humans. Methods. Twenty males wore a lower-limb immobilization boot for 28 days and consumed either a PAA supplement (28 g protein) or carbohydrate placebo (28 g maltodextrose), while consuming their normal daily diet. Testing sessions included dietary analysis, lower-leg girth and body composition measurements, strength testing, and gastrocnemius muscle biopsies. Muscle was analyzed for mRNA expression of markers in the ubiquitin and calpain systems, myostatin, TNF-α, and NF-κB. Results. All genes of interest increased over time (P < .05), but there was no difference between groups. Lower-leg girth decreased over time (P = 0.02); however, there were no significant changes in body composition or strength. Conclusion. Short-term lower-limb disuse, despite the absence of significant muscle atrophy, is associated with increases in skeletal muscle gene expression of several proteolysis-related genes. These changes do not appear to be altered by oral PAA supplementation.

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Purpose: To statistically evaluate the internal and external load metrics in different types of lacrosse drills. Methods: A total of 25 Division I collegiate female lacrosse players wore a heart rate monitor and a global positioning system during preseason training sessions. Seven measures determined training load, 2 internal measures and 5 external measures, across 5 different types of drills: stickwork, small-sided games, individual skills, conditioning, and team drills. Principal component analysis was used to determine which internal and external load variables were most associated with each drill type. Results: Stickwork extracted 2 principal components, explaining 45% and 17% of the variance. Small-sided games extracted 1 principal component, explaining 51% of the variance. Individual skills extracted 2 components, explaining 39% and 22% of the variance. Conditioning extracted 2 components, explaining 44% and 24% of the variance. Team drills extracted 2 components, explaining 52% and 18% of the variance. Conclusions: In 4 out of 5 training modes, the inclusion of both internal and external training-load measures was necessary to accurately decipher training load. For most drills, the first component is related to measures of external load, and the second component described the balance between internal and external load measures. Small-sided games extracted only external measures including the following: accelerations, total distance, and average speed. These results show that a combination of internal and external load measures is required to determine training load during certain training modes. This information can help coaches make decisions about desired training load for practice sessions.