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Pre-exercise hypohydration prevalence in soccer players: A quantitative systematic review.

L ChapelleBruno TassignonNikki RommersE MertensP MulliePeter Clarys
Published in: European journal of sport science (2019)
Pre-exercise hypohydration can impair soccer performance and has been extensively studied in different soccer populations. Therefore, the aim of this systematic review was to report hypohydration prevalence, measured by blood or urine samples, in different soccer populations based on sex (males and females), performance level (professional and recreational players) and context (training sessions and games). The Pubmed, Web of Science and SPORTDiscus databases were systematically searched until November 2018. Data were pooled to compare hypohydration prevalence between the different subgroups. Following the systematic search selection process, 24 studies were included. The results indicated that overall pre-exercise hypohydration prevalence was 63.3%, 37.4% and 58.8% for urine specific gravity (USG), urine osmolality (U Osm) and urine colour, respectively. Furthermore, no study implemented blood samples to examine hypohydration prevalence in soccer players. The subgroup analyses using USG data indicated that pre-exercise hypohydration prevalence was significantly higher amongst males (66.0%; p = 0.001), professional soccer players (66.2%; p = 0.020) and before a training session (79.6%; p < 0.001). Pre-exercise hypohydration prevalence was 46.8% among female soccer players, 55.6% in recreational soccer players and 41,3% before a game. The subgroup analyses using U Osm data indicated that hypohydration prevalence was significantly higher before a training session (52.6%; p = 0.023). Based on these results, it can be concluded that hypohydration prevalence in soccer players is of major concern. Future research should explore how pre-exercise hydration status can be improved in a sustainable way.
Keyphrases
  • risk factors
  • systematic review
  • high intensity
  • physical activity
  • public health
  • big data
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