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Relative Energy Deficiency in Sport (RED-S) characterizes a range of negative health and performance outcomes that result from chronically low energy availability. RED-S concerns high performance junior and senior athletes across Canada and has a prevalence rate of 3-60%. Our ability to assess and diagnose RED-S remains poor. Accordingly, we aim to create the best parameters to diagnose and manage RED-S; along with information of the prevalence and severity across Canada and globally. These outcomes are expected to have a significant positive impact on the health and performance of Canadian athletes in preparation for the Olympic Games in 2022 and beyond.
Full description
Purpose:
Our aim is to improve our understanding of the prevalence and symptoms of RED-S in international and Canadian athletes and para-athletes, along with developing screening tools and treatment protocols to manage RED-S in order to improve athlete health, availability and performance.
Objectives:
Justification:
This study will be the first to systematically assess the prevalence and severity of outcomes of RED-S in a large group of international and Canadian athletes and para-athletes (A), and within the COPSI network (B,C), utilising physiological and performance tests and training metrics for a more holistic assessment of potential outcomes (B,C,). This study will also aim to strengthen the literature regarding to the time-course of changes in these outcomes (B,C,D) and the efficacy of a simple nutritional intervention arm on these changes (D). Finally, this multicentre project will be the largest to date in Canada and globally, and the first to produce data on the prevalence of RED-S within the COPSI network (across A,B,C,D).
Research Design:
This is an observational study including online survey and physiological testing with potential for follow-up in a subset of athletes. A separate study arm (study D) will be an intervention arm with follow-up.
Statistical analysis:
Analysis will be a combination of basic statistics such as t-tests and ANOVA's, as well as more advanced statistical modelling (e.g. stepwise regression modelling, with first identifying collinearity among independent variables via the implementation of variance inflation factors (VIFs)) as well as questionnaire-based statistics and potentially principal components analysis (PCA) will be implemented.
Physiological data will be plotted against survey data to create links between RED-S symptoms among various athlete groups (female vs male, able bodied vs disabled, sports groups, age categories, etc.)
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2,000 participants in 4 patient groups
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Central trial contact
Ida A Heikura, Ph.D.; Trent Stellingwerff, Ph.D.
Data sourced from clinicaltrials.gov
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