Search

Impedance (Z), resistance (R), reactance (Xc), and phase angle (PhA) are sensitive to shifts in fluid between intra- and extracellular compartments, as would occur with nutrient uptake into skeletal muscle, but remains largely unexplored. To explore the sensitivity of whole-body and segmental (arms, legs, trunk) bioimpedance to acute feeding, 27 young adults completed three feeding conditions on separate occasions in randomized, cross-over design [high-carbohydrate (CHO), high-protein (PRO), fasted (FAST); standardized for fluid]. Bioimpedance was completed one-hour post-meal. Differences between feeding conditions at 5, 50, 250 kHz were evaluated. At 5 kHz, whole-body Xc and PhA were significantly different with CHO (p = 0.017), but not PRO (p = 0.152), compared to FAST; there were no significant differences at 50 or 250 kHz (p > 0.05). Segmental bioimpedance was significantly different with CHO and PRO compared to FAST [5 kHz: (Arms: Z, R, Xc,PhA; Trunk: Z, R; p = 0.002), 50 kHz:(Arms: Z, R, Xc; Trunk: Z, R, Xc; p < 0.02), 250 kHz:(Arms: Z, R; Trunk: Z, R; Legs: PhA; p = 0.009)]. Results suggest segmental bioimpedance at 5 kHz is sensitive to acute nutrition. Further exploration is warranted.

Recent concerns have been raised regarding the ethical considerations of conducting body composition assessments in sports. Specific apprehensions pertain to the inappropriate use of percent body fat and the limited application of the results to performance and recovery. Fat-free mass index (FFMI), a height-adjusted assessment of FFM, can serve as an alternative body composition metric to focus on in sports. Fat-free mass index provides valuable context regarding an optimal amount of FFM, accounting for skeletal frame and height while helping to qualify an athlete's FFM as low, moderate, or high. This review posits that shifting the focus of body composition measures to FFM can support more ideal targets across athletic seasons, careers, and the return to play after injury. In addition, a FFM focus may help change the perception of body composition assessment and how athletes perceive their current body because of the increased focus on the FFM compartment and the goal of maximizing tissue accrual, rather than focusing on fat loss. Fat-free mass index is calculated by dividing FFM (kg) by height (m²) and can serve to normalize FFM, relative to height, and enable comparisons across athletes, sport types, and sex. Previous research has identified differences in FFMI across sex and among sport categories. Still, there is a need for more published data to develop optimal ranges for FFMI across sex, sports, and positions. As more data become available, FFMI has the potential to provide normative guidelines for optimal FFM development, performance, and injury risk reduction. The purpose of the current review was to summarize FFMI values across collegiate sport categories and competitive status to provide normative profiles, according to sex and sport type. [ABSTRACT FROM AUTHOR]

The effects of female sex hormones on optimal performance have been increasingly recognized as an important consideration in exercise and sport science research. This narrative review explores the findings of studies evaluating the effects of menstrual cycle phase in eumenorrheic women and the use of hormonal contraception (oral contraceptives and hormonal intrauterine devices) on metabolism, muscular strength, and recovery in active females. Ovarian hormones are known to influence metabolism because estrogen is a master regulator of bioenergetics. Importantly, the menstrual cycle may impact protein synthesis, impacting skeletal muscle quality and strength. Studies investigating muscular strength in eumenorrheic women report equivocal findings between the follicular phase and luteal phase with no differences compared to oral contraceptive users. Studies examining recovery measures (using biomarkers, blood lactate, and blood flow) do not report clear or consistent effects of the impact of the menstrual cycle or hormonal contraception use on recovery. Overall, the current literature may be limited by the evaluation of only one menstrual cycle and the use of group means for statistical significance. Hence, to optimize training and performance in females, regardless of hormonal contraception use, there is a need for future research to quantify the intra-individual impact of the menstrual cycle phases and hormonal contraceptive use in active females. [ABSTRACT FROM AUTHOR]

Aim: Secondary analyses were conducted from a randomized trial of an adaptive behavioural intervention to assess the relationship between protein intake (g and g/kg) consumed within 4 h before moderate‐to‐vigorous physical activity (MVPA) bouts and glycaemia during and following MVPA bouts among adolescents with type 1 diabetes (T1D). Materials and Methods: Adolescents (n = 112) with T1D, 14.5 (13.8, 15.7) years of age and 36.6% overweight/obese, provided measures of glycaemia using continuous glucose monitoring [percentage of time above range (>180 mg/dl), time in range (70‐180 mg/dl), time below range (TBR; <70 mg/dl)], self‐reported physical activity (previous day physical activity recalls), and 24 h dietary recall data at baseline and 6 months post‐intervention. Mixed effects regression models adjusted for design (randomization assignment, study site), demographic, clinical, anthropometric, dietary, physical activity and timing covariates estimated the association between pre‐exercise protein intake on percentage of time above range, time in range and TBR during and following MVPA. Results: Pre‐exercise protein intakes of 10‐19.9 g and >20 g were associated with an absolute reduction of −4.41% (p =.04) and −4.83% (p =.02) TBR during physical activity compared with those who did not consume protein before MVPA. Similarly, relative protein intakes of 0.125‐0.249 g/kg and ≥0.25 g/kg were associated with −5.38% (p =.01) and −4.32% (p =.03) absolute reductions in TBR during physical activity. We did not observe a significant association between protein intake and measures of glycaemia following bouts of MVPA. Conclusions: Among adolescents with T1D, a dose of ≥10 g or ≥0.125 g/kg of protein within 4 h before MVPA may promote reduced time in hypoglycaemia during, but not following, physical activity. [ABSTRACT FROM AUTHOR]