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We also observed no differences in COVID-19 prevalence for athletes I P i = 0.970), staff ( I P i = 0.976), or combined Team USA delegation members ( I P i = 0.962) between the Olympic and Paralympic Games. 2 International Olympic Committee, International Paralympic Committee, Tokyo 2020 Organising Committee and Tokyo Metropolitan Government announce new dates for the Olympic and Paralympic Games Tokyo 2020 - Olympic News. No differences in average days in quarantine were observed between Team USA Olympic athletes and all other Olympic athletes or Team USA staff (all I P i > 0.05). No differences in COVID-19 prevalence between Team USA athletes and staff at the Olympic ( I P i = 0.628) or Paralympic Games ( I P i = 0.784) were observed. [Extracted from the article]

Coppus, TA, Anderson, T, Hurley, E, Gill, DL, and Brown, PK. The practical utility of objective training load indices in Division I college soccer players. J Strength Cond Res 36(4): 1026-1030, 2022-The aim of this study was to investigate the association of subjective session rating of perceived exertion with objective training load measures and explored data reduction approaches for 26 commonly measured objective load metrics. One National Collegiate Athletic Association Division I male soccer team (N = 28) provided 26 objective measures via a global positioning system and heart rate monitor system and self-report rating of perceived exertion measures for all team activities through the 12-week 2019 fall championship season. The singular associations between session rating of perceived exertion (sRPE) and objective load metrics were assessed via repeated-measures correlation and collectively assessed via elastic net regression. Principal components analysis was then used to reduce the dimensionality of objective load variables. Level of significance for the study was [alpha] <= 0.05. The training load variable had the highest correlation with sRPE (r = 0.85) among the 26 metrics. Twenty variables were retained in the elastic-net regression and demonstrated an R 2 of 0.76. The principal components analysis demonstrated a 4-component solution. The components were qualitatively described as "moderate- or high-intensity external load," "low-intensity load," "high-intensity internal load," and "average internal load" and accounted for 46, 32, 16, and 6% of the variance, respectively. The sRPE metric had strong correlations with multiple objective measures, demonstrating its utility for practitioners monitoring training load in collegiate soccer with limited resources. Furthermore, the consolidation of 26 metrics into 4 components while retaining data variability allows coaches to focus on a small number of metrics and employ a data-driven approach to training. /p> [ABSTRACT FROM AUTHOR]

Objective: The primary aim of this study was to assess the efficacy of the weight, urine, thirst (WUT) framework in predicting dehydration after a body water manipulation protocol, while concurrently determining the individual and interactive contributions of the model components., Methods: The total study sample was 93 participants (female, n = 47), recruited from two institutions. Phase 1 involved collecting daily hydration measures from free-living participants (Study 1, 58 participants for 3 days; Study 2, 35 participants for 7 days). Phase 2 entailed a two-hour passive heating protocol, where participants from Study 2 were randomly assigned to one of three groups that manipulated total body water over 24-hours using passive heating and fluid restriction. During each Phase, participants provided urine samples, underwent body mass measurements, and completed questionnaires pertaining to thirst perception. Morning and 24-hour urine samples were assessed for color, osmolality, and specific gravity. Differences between intervention groups, based on the probability of hydration status, were examined (ANOVA) and ridge regression analysis assessed the relative importance of variables within the WUT model., Results: The study revealed significant differences among the intervention groups for predicted probability of dehydration, as determined by changes in body mass (p = 0.001), urine color (p = 0.044), and thirst perception (p < 0.001). Binomial ridge regression indicated that change in body mass (58%) and thirst perception (26%) were the most influential predictors of dehydration., Conclusions: These data support use of an enhanced version of the WUT model, underscoring the significance of changes in body mass and thirst perception in the assessment of hydration status., Competing Interests: Conflict of Interest and Funding Source: This study was funded in part by a Faculty Grant awarded by the School of Health and Human Sciences as the University of North Carolina at Greensboro and the Biotechnology High Performance Computing Software Applications Institute (BHSAI). WMA declares the following conflicts of interest: he serves on the advisory boards for My Normative and Emerja Corporation, the Medical and Science Advisory Board for the Korey Stringer Institute, and the Sport Advisory Council for the Wu Tsai Human Performance Alliance where he has received compensation either as part of his role on the respective boards, or as a consultant. WMA has previously received consulting fees/honoraria/compensation/grant funding/travel support from the following entities that is related to the submitted work: Gatorade, Samsung, BSX, QKC LLC, Clif Bar & Company, Danone Research Nutricia, Nobo Inc, and Onda Vision. WMA is also the owner of Adams Sports Medicine Consulting LLC with clients on topics related to the submitted work., (Copyright © 2024 by the American College of Sports Medicine.)