![]() Start times were categorised as afternoon, twilight, or night. Twelve out of 13 were found to have a significant effect of chronotypes on athletic performance.Įxamine Australian Football League (AFL) results for evidence that game-day circadian misalignment or environmental temperature influence games with competing teams from each of Western Australia (WA) and Victoria (VIC).ĭata were obtained for games (n = 791) contested by WA and VIC teams including game location, start time, and outcome. The present systematic review demonstrates that chronotypes affect the athletic performance. Most of the studies (12 out of 13) demonstrated a significant influence of chronotype over athletic performance based on outcomes of the various physical performance test.Conclusion thesis and duplicates were excluded.ResultInitially 936 articles were identified from electronic search and out of the 13 studies (PEDro score = 7.8) meet the inclusion criteria. Randomized controlled trials and crossover studies consisting of the effect of chronotype on athletic performance in athletes irrespective of age and gender and having full text available in the English language were included while unpublished, Ph.D. The literature search for this review was carried out till 30th June 2021 from the following electronic databases-PubMed and Scopus about PRISMA guidelines. This systematic review aims to investigate the effect of chronotypes on athletic performance in the athletic population.Method The chronotypes reflect innate variation, which is essential to consider for obtaining significant outcomes in sports competitions and optimizing adequate recovery during rehabilitation following an injury. IntroductionThe individual differences in exogenous and endogenous factors influence the various physiological and psychological processes related to athletic performance. ECTs slept for 7.66 ± 0.12 h on weekdays and 7.70 ± 0.22 h on weekends, ICTs for an average of 8.24 ± 0.11 h on weekdays and 8.97 ± 0.12 h on weekends, and LCTs for 8.70 ± 0.17 h on weekdays and 9.25 ± 0.17 h on weekends ( Figures. LCT average sleep onset was 24.27 ± 0.13 h on weekdays and 01.66 ± 0.16 h on weekends (Figures 1C,D). ECT sleep onset was 23.23 ± 0.13 h on weekdays and 23.84 ± 0.17 h on weekends, whilst ICT sleep onset was 23.53 ± 0.08 h on week- days and 24.32 ± 0.10 h on weekends. Significant differences were also seen in sleep-onset times (Kruskal-Wallis, p < 0.001) and sleep duration times (Kruskal-Wallis, p < 0.001). ![]() Average wake-up times dif- fered significantly between circadian phenotypes (Kruskal-Wallis, p < 0.001) being 6.90 ± 0.11 h for ECTs on weekdays as compared to 7.55 ± 0.11 h on weekends, for ICTs 7.77 ± 0.08 h at weekdays and 9.29 ± 0.06 h on weekends, and for LCTs 8.98 ± 0.14 h on week- days and 10.91 ± 0.10 h on weekends ( Figures 1A,B). The circadian phenotyping methodology proved consistent with relevant circadian parameters, such as wake-up times, sleep-onset times, and sleep durations (Figure 1). In total, we identified 15% early circadian phenotypes (ECT n = 32), 51% intermediate circadian phenotypes (ICT n = 111), and 34% late circadian phenotypes (LCT n = 73). comprehensive analysis and consideration of specific sleep/wake-related criteria, including wake-up times on week- days, weekends, and training-free days, sleep onset on weekdays, weekends, and training-free days, sleep durations, periods of high and low activity, sleep inertia, and meal times, as previously described (25), all participants could be categorized into "circadian phenotypes" (CT).
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