Adolescent football players’ sleep,wellness and school physical activity over different phases of the year

Introduction

Sleep is an actively regulated process that can affect adolescents academic performance, mental, cardiometabolic and emotional health, as well as athletes’ recovery and performance. ¹ The recommended sleep duration for adolescents is 8–10 h, ² a standard which is endorsed for long-term health. ³ This may be particularly pertinent for adolescent athletes, who require sufficient sleep to perform optimally, as well as to recover from their physical activity (PA). ⁴ Although the importance of sleep to adolescent athletes’ health, wellness and athletic performance is evident, their normative behaviours across different phases of the year are unknown.

Adolescents face risks to achieving sufficient sleep in part due to a misalignment between their biological and social sleep schedules. ⁵ Delays in adolescent’s circadian rhythm and build-up of homeostatic drive for sleep result in a delayed sleep phase (i.e. extended evening wakefulness ⁶ ). Thus, incurred later bedtimes followed by waking early for school and extracurricular activities such as sports training, often results in adolescents accumulating a “sleep debt” on school nights which is “recovered” by longer sleep durations on weekends, ⁵ also known as social jetlag. ⁵ In addition to adolescent-related challenges to sleep, adolescent athletes (i.e. academy football [soccer] players) experience competition stress and anxiety, as well as psychosocial pressure from coaches, parents and competitors, ⁷ which may negatively affect their sleep. However, whether or not differences in sleep parameters in school nights compared to weekends also exists between school and holidays, and in elite adolescent athlete populations, is unclear. For example, a study on 20 adolescent athletes found no difference in sleep duration between two weeks of school term and two weeks of holidays. ⁸ However, large studies in non-athletic adolescent populations have reported significantly greater holiday sleep durations compared to school term. ⁹ Conflicting results may be due to differences in methodologies (i.e. actigraphy compared to self-reports), or adolescent athletes demonstrating differing sleep patterns to non-athletic adolescents. Additionally, whilst research has assessed youth athletes’ sleep and wellness across whole seasons, focus has largely been on the association between these variables and changes in training load or injury risk,^10–12 rarely considering the seasonal impact or comparing time-points. For instance, to the authors knowledge there is just one study showing declines in youth academy football players’ perceptions of sleep quality and wellness throughout a season, ¹³ necessitating further research.

Within elite football, there are many sporting organisations which nurture the development of adolescent athletes including clubs, academies and “sport high schools” (SHS). Sport high schools foster the development of athletic success and ensure students meet their academic requirements, whilst football academies mainly aim to produce professional players. ¹⁴ Therefore, academy football players who also attend SHS are exposed to a high level of PA in the form of coaching hours, demanding training and competition schedules. ¹⁴ Since PA can vary across individuals with differing sleep behaviours, it would seem beneficial to further our understanding of these factors in elite football academy settings where high training loads, fixture congestion and athlete associated stressors are encountered (i.e. sleep decrements and reduced wellness ¹⁵ ). For instance, in a Norwegian study comparing adolescent athlete club teammates from SHS and regular high schools (RHS), higher training loads and a higher prevalence of injuries were observed in the SHS group. ¹⁶ However, whether those who attend SHS are at increased risk of poor sleep quantity or quality, and subsequent relationships with wellness, remains unknown in an academy setting.

Taken collectively, our current understanding of adolescent athletes’ sleep quantity and quality, wellness and level of school PA (s-PA) remains equivocal. Therefore, the purpose of this study is to examine the differences in sleep, perceived wellness and s-PA in adolescent academy football players during different phases of the year. Additionally, the impact of school type (SHS vs. RHS) on these variables is explored.

Methods

Experimental approach to the problem

The study followed a longitudinal observational design where subjective sleep, perceived wellness variables and hours of s-PA were collected in two blocks of two weeks, three months apart. Each block consisted of one week of school and one week of holidays in all participants (Figure 1). All participants were assigned randomised identification numbers. Participants completed a daily sleep and wellness questionnaire and a weekly s-PA survey for the duration of the study (four weeks in total). Within each block, one week of school term and holidays was collected. As part of standard academy procedures, height (cm) and body mass (kg) were measured every month by a qualified member of staff.

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Figure 1.

Overview of study design and timeline.

The questionnaire and survey were piloted for one week prior to the commencement of the first block of data collection. Ten players from the academy volunteered to take part in the pilot testing. Pilot testing was conducted to refine the construction, timing and verbiage of questions, as well as increase face validity. All players were familiarised with procedures by the head researcher who explained the online questionnaires to players in small groups at training prior to data collection commencing.

The academy training schedule during the late season holidays (Week 3) occurred in the morning rather than evening, differing to all other weeks and adding a potential for confounding results. Therefore, to assess differences in school vs. holidays, data from Weeks 1 and 2 only were used, and to assess differences in early season vs. late season, data from Weeks 1 and 4 only were used.

Results

Table 1 provides a descriptive overview of the players sleep and wellness during school term and the holidays. There was a large significant main effect of week (school vs. holidays) on the sleep variables (F_(2,40) = 5.631, p = 0.007, η² = 0.22) with subsequent univariate analysis revealing an increased TST in the holidays compared to school term (F_(1,41) = 10.946, p = .002, η² = 0.21; Table 1). In addition, there was a large significant main effect of school type (SHS vs. RHS) on the wellness variables (F_(2,40) = 4.369, p = 0.019, η² = 0.18) with players at RHS reporting significantly higher levels of fatigue (F_(1,41) = 5.481, p = .024, η²= 0.12; Table 1).

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Table 1.

Descriptive overview of sleep and wellness between players at regular high schools and sport high schools over school term and holidays.

	School term						Holidays
	RHS		SHS		All players		RHS		SHS		All players
	Mean ± SD	95% CI	Mean ± SD	95% CI	Mean ± SD	95% CI	Mean ± SD	95% CI	Mean ± SD	95% CI	Mean ± SD	95% CI
TST (h:min)	8:51 ± 0:31	8:38–9:05	8:43 ± 0:40	8:25–9:01	8:47 ± 0:35	8:36–8:58	9:10 ± 0:39	8:53–9:28	9:22 ± 0:63	8:53–9:50	9:16 ± 0:52*,a	9:00–9:32
Sleep quality	61 ± 12	56–67	64 ± 18	56–72	63 ± 15	58–67	61 ± 12	56–67	65 ± 19	57–74	63 ± 15	59–68
Muscle pain	2.4 ± 1.7	1.7–3.2	1.8 ± 2.0	0.9–2.7	2.1 ± 1.9	1.6–2.7	2.4 ± 2.0	1.5–3.2	1.6 ± 1.9	0.8–2.4	2.0 ± 1.9	1.4–2.6
Fatigue	3.1 ± 1.7#, b	2.4–3.8	1.8 ± 2.1	0.9–2.7	2.5 ± 2.0	1.9–3.0	2.7 ± 1.6# ,b	2.0–3.4	1.6 ± 1.9	0.8–2.4	2.1 ± 1.9	1.6–2.7

TST, total sleep time; RHS, regular high school; SHS, sport high school; CI, confidence interval.

*Significantly differently to school term (p < .05).

^#Significantly different to sport high school group (p < .05) .

^aLarge effect of week.

^bModerate effect of group.

Table 2 provides a descriptive overview of sleep and wellness between players at RHS and SHS during early and late season. No significant interaction effect of week*school type on the combined sleep variables (combined TST and sleep quality) were found, although a large effect size was reported (F_(2,32) = 2.501, p = 0.098, η² = 0.14). A significant interaction effect of week*school type was only observed for TST (F_(1,33) = 4.98, p = 0.03, η²= 0.13), with those in RHS and during Week 1 (end of school Term) shown to incur higher TST than SHS players, and during Week 4 (start of school Term) SHS players incurred higher TST than RHS players (Table 2). No significant effect of week (early season vs. late season) or school (SHS vs. RHS) on the wellness variables were found (p > 0.05).

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Table 2.

Descriptive overview of sleep and wellness between players at regular high schools and sport high schools over early and late season.

	Early season						Late season
	RHS		SHS		All players		RHS		SHS		All players
	Mean ± SD	95% CI	Mean ± SD	95% CI	Mean ± SD	95% CI	Mean ± SD	95% CI	Mean ± SD	95% CI	Mean ± SD	95% CI
TST (h:min)	9:05 ± 31	8:50–9:23	8:54 ± 33	8:38–9:11	9:00 ± 32	8:49–9:11	8:57 ± 22	8:45–9:10	9:05 ± 30	8:50–9:20	9:02 ± 26	8:53–9:11
Sleep quality	65 ± 14	57–72	64 ± 13	57–70	64 ± 13	60–69	63 ± 13	56–70	65 ± 14	59–72	64 ± 13	59–69
Muscle pain	2.3 ± 1.8	1.5–3.3	1.6 ± 1.9	0.6–2.5	1.9 ± 1.8	1.3–2.5	2.1 ± 1.9	1.2–3.2	1.6 ± 1.5	0.9–2.4	1.9 ± 1.7	1.3–2.5
Fatigue	2.8 ± 1.5	57.4–72.4	1.8 ± 1.9	0.9–2.7	2.3 ± 1.7	1.9–2.9	2.4 ± 2.1	1.4–3.6	1.9 ± 1.7	1.1–2.8	2.2 ± 1.9	1.5–2.8

TST, total sleep time; RHS, regular high school; SHS, sport high school; CI, confidence interval.

Figure 2 depicts the hours of s-PA and TST for all players during Weeks 1 and 4. No significant effect of hours of s-PA on TST in Week 4 was reported, despite a large effect size (F_(5,32) = 1.394, p = .253, η² = 0.18). There were no significant findings or associations between the different hours of s-PA that players participated in (0 h, 1–2 h, 2–3 h, 3–4 h, 4–5 h, 5+ h) and their TST.

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Figure 2.

Hours of physical activity players performed at school and total sleep time during Week 1 (end of school term) and Week 4 (start of school term).

In terms of compliance, the mean individual response rate for the daily sleep and wellness questionnaires was 22.0/28, 95% CI 20.5 – 23.4, and for the weekly s-PA survey was 3.5/4, 95% CI 3.3 – 3.7.

Discussion

The present study aimed to assess the sleep, wellness and s-PA parameters of adolescent academy football players during different phases of the year. In addition, these parameters were compared between two groups of players within the academy; those attending RHS and SHS. The main findings included that reported sleep durations were within recommended guidelines for adolescents (8–10 h²), and that there were no differences evident between groups (SHS vs. RHS). Furthermore, extended sleep duration was observed during holidays compared to school term, whereas no effect of week (school vs. holidays, early season vs. late season) on the wellness variables (fatigue, general muscle pain) was found. Lastly, no significant effect of hours of s-PA on sleep duration was evident; although a large effect size was found at the beginning of term. The overall positive findings indicate the adolescent academy football players’ sleep and wellness was fairly resilient to the contextual factors (school vs holidays, seasonal effect, school type) examined across the football season.

Sleep duration across all conditions (school term, holidays, early season, late season) was within the National Sleep Foundations guidelines for adolescents (8–10 h per night ² ). Athletes are a population group who require substantial sleep quantity and quality for physical and cognitive restoration, in order to recover and perform optimally. ⁴ The sleep duration observed in our cohort (mean TST across conditions 8 h 47 min – 9 h 16 min) may be attributed to the players’ knowledge and value placed on the importance of sleep as a recovery tool and the consistency in Academy training schedule for all RHS and SHS players across the season (17:30 – 19:30 h Monday, Tuesday and Thursday, except Week 3 of the study which was not assessed) given irregular bedtime schedules may be associated with decreases in sleep duration. ²⁵ In comparison to previous studies using subjective methods to assess sleep in adolescent athletes (i.e. questionnaire, diary or log), our mean school night sleep duration (8 h 47 min) was similar to a previous study of adolescent football players, ²⁴ but was longer than others. ²⁶ The difference in results to the latter study may be attributed to the differences in age (i.e. mean age of 16–17 y compared to 14 y in our study), as older adolescents have been demonstrated to incur truncated sleep durations on school days, ²⁷ attributed to psychosocial and biological factors. ⁶

This is only the second observational study to our knowledge to compare adolescent athletes sleep during school term and holidays. On weekday nights, adolescent athletes reported an additional 29 min of sleep duration during the holidays (9 h 16 min ± 52 min) compared to school term (8 h 47 min ± 35 min). Skein et al. ⁸ compared two weeks during the holidays to two weeks during school term (inclusive of weekends) and found no significant difference in adolescent athletes sleep duration as assessed by actigraphy. The inclusion of weekend sleep in the Skein et al. ⁸ study could have reduced the difference between holiday and school term mean weekly sleep duration. ²⁸ Nonetheless, our findings are in agreeance with previous research in non-athletic adolescent Australian populations, ⁹ which reported increases in sleep duration of 36 min to 1 h 17 min in the holidays. Previous research has suggested that holiday sleep durations are more indicative of adolescents natural (i.e. biological) sleep requirement. ⁹ This is concerning as in our study the players are sleeping approximately 2 h less during each school week compared to during the holidays (29 min * 5 nights) and may therefore be presenting in a state of sleep debt during the school term.

Sleep quality has been demonstrated to be a better predictor of daily wellness than sleep duration ²⁹ and may have contributed to why no differences were observed in the wellness variables in our study between school and holidays given no significant differences in sleep quality were observed despite the extended sleep duration. Indeed, no seasonal effects were seen for the sleep measures or wellness variables. In contrast, previous research in youth academy football players have shown perceptions of sleep quality, fatigue and muscle soreness to decline throughout a season. ¹³ It is possible that given the participants in the Noon et al. study ¹³ were at a critical age (17 ± 1 y) for their football careers (Category 2 Premier League Academy), they may have faced greater psychosocial stressors as they neared their professional careers (e.g. pressure to earn a contract, conflicts with study commitments and concerns regarding their performance). Indeed, such stressors may have contributed to their reduced wellness. Of further note, Noon et al. ¹³ also reported higher training exposure (approximately 10 h per week, compared to 6 h per week in our study), which could explain the decreases in perceptions of recovery throughout the season. ³⁰ Although speculative, this may have disrupted the balance between stress and recovery, thus, increasing the likelihood of accumulating stress and therefore a decline in wellness. ³⁰

No difference in general muscle pain was found between the groups, whereas the RHS group reported higher levels of fatigue. It could be speculated that players from RHS are less accustomed to the high academy training loads that SHS players are more consistently exposed to, and as such players from SHS may have a ‘higher resiliency’ per se, and subsequently lower levels of fatigue. However, this remains hypothetical and the underlying reasons or mechanisms for this difference are unknown. The presence of early morning activities and training may also play a role, as training schedules have been shown to influence athletes’ sleep and fatigue. ³¹ An alternate hypothesis is that players from RHS may experience greater academic pressure at school and from their parents, possibly due to a higher academic focus at RHS. Players from RHS may therefore experience higher levels of overall stress, given the stress-fatigue state is affected by individuals psychological, social and physiological capacities. ³² Since such influences were not assessed in our study, this could become a focus of future research. Indeed, future studies may wish to assess a range of psychosocial stressors (e.g. school, sport, family and friend related factors) in addition to physical stress (training loads) when assessing the stress-fatigue state in adolescent athletes.

Hours of s-PA had no effect on sleep duration, and no significant differences in sleep duration or quality were found between players attending SHS and players attending RHS. Although a large effect size for hours of s-PA on sleep duration was demonstrated at the beginning of term, no trend was reported. Differences in total weekly PA (i.e. inclusive of PA inside and outside of school and the academy) may explain why hours of s-PA had little effect on sleep duration. Personal communication with SHS players and academy staff indicated SHS players attended early morning school football training and reported increased frequency of tiredness compared to RHS players. Although players from SHS may have early morning football trainings (anecdotal evidence), players from RHS may also have other before school activities (e.g. swimming training), as such a lack of transparency regarding morning schedules is a limitation of this study. Collectively, these results would suggest players’ sleep may also be more susceptible to other mediums such as training schedules, ³¹ technology screen time, socialising and academic pressure ³³ or competition anxiety and stress, ¹ which weren’t collected in our study.

Certain limitations should be acknowledged within this study. Firstly, our sample size may be considered small, although we were limited by the number of players in the academy. Secondly, while objective measures of sleep, such as the “gold standard” polysomnography or wrist watch actigraphy are preferred due to their superior accuracy, validity and reliability, ³⁴ subjective measures were chosen due to equipment availability, cost and ease of application. Nevertheless, players may have over-estimated their sleep duration. ³⁵ Compliance was less than expected, in part due to selected players departing for international tournaments coinciding with the study period and some results from the online questionnaire/survey were received with partial answers, and therefore not included in the analysis. Attempts were made to maximise response rates through daily reminders to players, in addition to weekly email reminders to parents. The school term weeks were dissimilar across the two study periods (last week of term in Block 1 vs first week of term in Block 2) which may have introduced further uncontrolled variance. Additionally, although total PA levels may have a larger impact on sleep than s-PA, concerns regarding the players interpretation of PA outside of the academy/school question presented, thereby preventing an accurate calculation of total PA (previously demonstrated elsewhere). ³⁶ Lastly, daily schedules (i.e. early morning activities) were not directly assessed and as such players could have been exposed to a number of daily schedules that compromised sleep opportunities, however from a subgroup of this cohort, ³⁷ it should be acknowledged there was minimal differences between early morning and evening training sessions in this group.

In conclusion, it was found that adolescent academy football players reported sleep quantities within recommended ranges, with the greatest sleep durations observed during holidays. Time of season, and school compared to holidays, had no effect on the wellness variables or sleep quality. In addition, attending a SHS did not negatively affect players sleep quantity or quality, or perceived muscle pain or fatigue. Furthermore, s-PA had limited effect on sleep duration. As such, the football players in our study appeared to manage their sleep well throughout the year. Alternative factors not assessed in this study (e.g. competition stress, academic pressure, electronic media device use, training schedule) may have a more influential effect on adolescent football players’ sleep and wellness. Future research may wish to assess the influence of the aforementioned alternative factors on the relationship between adolescent athletes’ total PA levels, measures of sleep and wellness, as well as the direct effect of school morning trainings on adolescent athletes’ sleep.

Practical applications

Adolescent athletes who attend football academies reported sufficient sleep durations as well as levels of PA and wellness, regardless of the school type (SHS vs. RHS) they attended.