AN INVESTIGATION INTO THE SLEEPING PATTERNS OF YOUTH SOCCER PLAYERS DURING THE COMPETITIVE SEASON
Sleep is a recurring state that is considered a critical process in the optimal attainment of daily functions and recovery in athletes. However individuals from elite sports, such as soccer, may be exposed to a number of situations that may impact sleep within the competitive season (such as inconsistent schedules and travel), which may result in sub-optimal sleeping patterns. However, research documenting the sleep of soccer players is at present limited. Therefore it would seem important to investigate how soccer players sleep to further the understanding of how sleep may be impacted. On this basis, the aim of the current thesis was to examine the typical sleeping patterns of youth soccer players and the factors effecting sleep. This was completed through a series of investigations conducted during the competitive youth soccer season. The aim of the first study (Chapter 3) was to validate a commercially available wireless sleep-monitoring device (WS). This was done in an attempt to provide a viable methodology to measure sleep within the habitual environment of soccer players. Nine randomly selected male participants were monitored over 3 nights and comparisons were made between the WS and other established field measures of sleep (Wristwatch actigraphy, sleep diary and Firstbeat bodyguard heart rate system). The relationships between the WS and the other sleep devices, indicated strong to very strong correlations (r > 0.6) and no significant differences between a range of outputs; total sleep time (Actigraphy assumed sleep time [0.97] & Sleep Diary [0.87] p > 0.05), sleep onset latency (Actigraphy [0.69] p > 0.05) and number of awakenings (Sleep Diary [0.69], p > 0.05). There were also low bias and narrow limits of agreement (LOA) within the comparison of mean differences with the WS for assumed sleep time (2 ± 17 min 95% LOA: -30 to 34 min [Actigraphy]), sleep onset latency (7 ± 17 min, 95% LOA -28 to 40 min [Actigraphy]), and number of awakenings (0.05 ± 1, 95% LOA -3 to 3 [Sleep Diary]). These results suggested that the WS is a viable device for the detection of these selected sleep variables. Chapter 4 looked to provide a comparison of sleep measures between a sample of youth soccer players (N=8) and non-athletes (N=8). Both groups were monitored over a period of 6 days within the habitual setting using the WS. The findings showed the soccer player group attained greater amounts of sleep quantity in comparison to the non-athlete group (504 ± 22 vs. 433 ± 46 min [+71 min] total sleep time, ES: 2.0, Large, p < 0.01). This may have been as a result of a later time of final awakening (08:54 ± 00:14 vs. 07:34 ± 00:46 [+77 min], ES: 1.7, Large, p < 0.01). Such an observation suggested that the soccer players were afforded greater time in bed as a result of the imposed soccer schedule. The soccer players also displayed a statistically greater time spent in wake (13(13) vs. 3(5) min [+10 min], PS: 0.86 ES: 1.5, Large, p < 0.05) on average each night. This data suggested that the sleep of the youth soccer players might be less efficient (as a consequence of greater levels of disturbance), despite desirable quantities of sleep being attained than non-athlete controls. Chapter 5 provided a daily comparison of sleep measures conducted over a 14-day assessment period. It is apparent that youth soccer players attained more sleep quantity in the nights preceding the match day (M-2: 488 ± 53 min [ES: 0.91, Moderate; p = 0.06] & M-1: 486 ± 64 min [ES: 0.84, Moderate; p = 0.02] respectively) in comparison to the night of the day after the match day (M+1: 422 ± 61 min). Such a finding suggested that youth soccer players adopt behaviours that reduce their sleep quantity on the designated recovery day (M+1) by >60 min, which may impact the recovery processes associated to this day. Relationships between sleep parameters and training and match load indicated a 100 au rise in RPELOAD (RPE * Duration) increased the time spent in wake (42 s [90% CI: 0 to 84 s]; ES: 0.36, Small; p = 0.098). It was also observed that an increase of 1000 m total distance increased the time spent in wake (40 s [90% CI: 5 to 75 s]; ES: 0.33, small; p = 0.06) A 100 m rise in high-speed running distance increased the number of awakenings observed (0.14 [90% CI: 0.03 to 0.25]; ES: 0.28, p =0.04) and the time spent in wake on average each night (1.5 min [90% CI: 0.78 to 2.3 min]; ES: 0.57, Small; p = 0.04). A similar outcome was observed in Chapter 6 were a 100 m rise in average high-speed running distance across three different 14-day training periods during the youth soccer season showed a 5 min increase in the time spent in wake on average (ES: 0.88, moderate; p = 0.04). Such outcomes provided a potential link between increases in training intensity (i.e. high-speed running distance) and sleep disturbances within youth soccer players. Increases in high-speed running distance also related to an increase of 24 min (90% CI: 12 to 36 min) on average for total sleep time (ES: 1.3, large; p < 0.01). Similarly increased high intensity heart rate (>85% max HR) was shown to effect total sleep time +20 min (90% CI: 6 to 32 min; ES: 0.87, moderate; p = 0.035). This may suggest that increases in intensity also may impact the amount of sleep quantity within youth soccer players. At present the mechanism for this response largely remains unknown. Within Chapter 7, a practical sleep hygiene strategy (10 min showering at ~40 °C, 20 min before time of lights out) was investigated. A group of ten youth soccer players were evaluated under normal sleeping conditions (control) and a shower intervention period, each consisting of three days within a randomized cross over trial design. Sleep information was collected using the WS. In addition to skin temperature, which was evaluated using iButton skin thermistors. The iButtons were used to establish both distal and proximal skin temperatures. This data was also used to create the distal to proximal gradient (average of distal measures – average of proximal measures = DPG). The data demonstrated that the shower intervention elevated distal skin temperature by (+1.1 °C [95% CI: 0.1 to 2.1 °C]; ES: 0.44, Small; p = 0.04) on average during a 10-minute period prior to lights out in comparison to the control condition. This elevation was also present during the first 30 minutes following lights out (1.0 °C [95% CI: 0.4 to 1.6 °C]; ES: 0.65, Moderate; p < 0.01), which was also accompanied by an increased DPG between conditions (0.7 °C [95% CI: 0.3 to 1.2 °C]; ES: 0.45, Small; p < 0.01). Additionally it was observed that on average the sleep onset latency of the youth soccer players was lower in the shower intervention condition (-7min [95% CI: -13 to -2 min]; ES -0.55, Moderate; p = 0.007). However no other sleep variable was affected as a result of the intervention. These findings demonstrate that a warm shower performed before lights out may offer a practical strategy to alter the thermoregulatory properties of distal skin temperature, which may advance sleep onset latency within youth soccer players.
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