A Subjective Assessment of the Prevalence and Factors Associated with Poor Sleep Quality Amongst Elite Japanese Athletes
Hoshikawa et al. Sports Medicine - Open
A Subjective Assessment of the Prevalence and Factors Associated with Poor Sleep Quality Amongst Elite Japanese Athletes
Masako Hoshikawa 0
Sunao Uchida 2
Yuichi Hirano 1
0 Department of Sport Research, Japan Institute of Sport Sciences , 3-15-1 Nishigaoka, Kita-ku, Tokyo 115-0056 , Japan
1 Faculty of Sports and Health Studies, Hosei University , 4342 Aihara-Cho, Machida, Tokyo 194-0298 , Japan
2 Faculty of Sport Sciences, Waseda University , Mitakajima, Tokorozawa, Saitama , Japan
Background: The amount, quality, and timing of sleep are considered important for athletes' ability to train, maximize training responses, and recover. However, some research has shown that elite athletes do not obtain sufficient sleep. Based on this background, researchers recently started to assess and manage sleep in elite athletes. The purpose of this study was to clarify the prevalence of poor sleep quality and its associated factors amongst elite Japanese athletes. Methods: Eight hundred and ninety-one candidates for the 17th Asian Games Incheon 2014, who were over 20 years old, participated in this study. They completed a questionnaire that included the Pittsburgh Sleep Quality Index (PSQI), Epworth Sleepiness Scale, two-question case-finding instruments, and a checklist for sleep hygiene. Data from 817 of the 891 athletes (91.7%) with no missing values were analyzed. Results: The mean time in bed was 7 h and 29 min. Two hundred and twenty-nine (28.0%) athletes showed a PSQI global score above the clinical criteria. A multiple logistic analysis revealed that sleep quality was significantly associated with five factors: “time in bed,” “eating breakfast every morning,” “avoiding the use of electronic devices (PC, smartphone, etc.) just before bedtime,” “depressive mood”, and “not thinking about troubles while in bed.” Forty percent of athletes reported they had been informed by someone about “snoring loudly” and/or “leg twitching or jerking during sleep.” Conclusions: The results of this study demonstrate that 28% of the athletes showed the PSQI score above the cutoff for poor sleep quality (> 5.5), which suggests that there may be a high prevalence of poor sleep quality in this population of athletes. To improve athletes' sleep, the five factors associated with sleep quality should be emphasized in athletes' sleep education. Furthermore, in medical evaluations of athletes, it may be desirable to include screening for sleep disorders.
Elite athletes; Sleep quality; Questionnaire study
Twenty-eight percent of elite Japanese athletes
showed a PSQI global score above the cutoff for poor
The PSQI global score above the cutoff for poor sleep
quality was associated with five factors: “time in bed,”
“eating breakfast every morning,” “avoiding the use of
electronic devices (PC, smartphone, etc.) just before
bedtime,” “depressive mood,” and “not thinking about
troubles in bed.”
Forty percent of the athletes had been informed by
someone about “snoring loudly” and/or “leg
twitching or jerking during sleep.”
increase in the training load is often successful, and their
performance improves. Since the training load will be
compromised during periods of fatigue, fatigue
management is very important for a successful increase in the
]. If athletes cannot maintain a favorable
condition, it may be difficult to train as scheduled and to
achieve good results.
Sleep is arguably one of the forms of recovery and
regeneration available to elite athletes. The amount,
quality, and timing of sleep are important for athletes’
ability to train, maximize training responses, and
recover. However, some research has shown that elite
athletes do not obtain an adequate amount of sleep and
that the prevalence of poor sleep quality is high (> 20%)
]. Based on this background, researchers recently
started to assess and manage sleep in elite athletes [
The amount, quality, and timing of sleep in elite athletes
may be affected by many factors, such as training-practice
], training or exercise volumes [
3, 10, 11
], nervousness due to competitions
], and sleep disorders [
]. Inappropriate sleep
] is also known to influence the amount and
quality of sleep; however, the present status of sleep hygiene
in elite athletes has not been studied extensively.
Strictly speaking, factors that affect sleep quality may
depend on the individual athletes. However, clarifying
general factors correlated with sleep quality may be
helpful for the sleep education of athletes.
The Pittsburgh Sleep Quality Index (PSQI) is a widely
used standardized measure to assess subjective sleep
]. The PSQI has been applied to both athletes
and general populations. Fietze et al. reported that 12 of
24 German ballet dancers showed PSQI global scores
above the cutoff level (> 5.5) [
]. In the Netherlands,
Knufinke et al. reported that the mean PSQI global score
in athletes was 4.61 and that 40 of 98 athletes showed a
PSQI global score above the cutoff level [
]. In Japan,
we studied 310 elite Japanese athletes and reported that
the mean PSQI global score was 4.8, and 95 of the 310
athletes showed global scores above the cutoff level [
In this study, we defined sleep quality as being poor if the
PSQI global score was above the cutoff level. A logistic
regression analysis was performed to examine relevant
factors, such as body mass index (BMI), some clinical
information, mood, training-practice schedules, frequencies of
overseas trips, sleep schedule, and sleep hygiene, and their
association with poor sleep quality. The purpose of this
study was to clarify the prevalence of poor sleep quality and
its associated factors amongst elite Japanese athletes.
A total of 891 candidates for the 17th Asian games
Incheon 2014, who were over 20 years old, participated
in this study. The survey started on February 20 and
ended on July 15, 2014. (The 17th Asian games Incheon
2014 was held between September 19 and October 4).
Written informed consent was obtained after explaining
the purpose, procedure, and possible risks of this study.
This study was approved by the Japan Institute of Sports
Sciences Ethics Committee.
Data from 817 (449 males and 368 females) of the 891
athletes (91.7%) with no missing data were analyzed.
The athletes were asked to complete the questionnaire
after measuring their heights and weights. The
questionnaire consisted of questions to obtain general information,
the PSQI [
], the Epworth Sleepiness Scale (ESS) [
two-question case-finding instruments [
], and a
checklist for sleep hygiene. The general information included
sex, age, sport, training-practice schedules, napping habits,
and frequency of overseas trips in the past 6 months.
Training-practice schedules were ascertained on each day
of the week. Training-practice times per week were
calculated from the training-practice times on each day.
The PSQI consists of 19 self-rated questions. The
athletes were asked about their bed time, sleep latency,
and getting-up time, and the time in bed and sleep
efficiency were calculated as part of the PSQI. Subjective
sleep quality was evaluated based on the global score of
the PSQI. In the Japanese version, a PSQI global score
higher than 5.5 is considered to indicate poor sleep
]. The PSQI contains five other questions that
are not reflected in the global score and are rated by a
bed partner or roommate [
]. Since the athletes
were not accompanied by a bed partner or roommate at
the time of completing the questionnaire, the latter five
questions were modified to be answered by the athletes
themselves in this study as follows:
Has any of your family, people living with you, or
people who have stayed in the same room as you
during a tour or other occasions made the following
remarks to you?
(A) You snore loudly
(B) You take long pauses between breaths while asleep
(C) Your legs twitch or jerk while asleep
(D) You show episodes of disorientation or
confusion during sleep
(E) You show other types of restlessness while asleep
For each of the five items, athletes selected an
appropriate answer from the following: “Not at all,” “Yes,
sometimes,” and “Yes, frequently.” For the logistic regression
analyses, “Yes, sometimes” and “Yes, frequently” were
defined as “the athlete has the symptom.” For the logistic
regression analyses, “the athlete has the symptom” was
assigned the dummy variable “1,” and the absence of the
symptom was assigned “0.”
Napping habits were clarified by asking three
questions. Firstly, the athletes stated their frequency of
napping by selecting one of five choices: no napping
habits, less than once per week, 1–2 times per week,
3–5 times per week, and almost every day. Athletes
with napping habits were requested to answer the
second and third questions. In the second question,
athletes stated their timing of starting to nap by
selecting one of nine choices: before noon, eight time bands
of every 1 hour from 12:00 to 19:00, and depends on
case. Thirdly, athletes stated their duration of napping
by selecting one of five choices: 30 min or less, 31 to
60 min, 61 to 90 min, more than 90 min, and depends
on case. For the logistic regression analyses, “no
napping habit” and “within 30 min” were assigned the
dummy variable “0,” and the others were assigned “1.”
Daytime sleepiness was evaluated by the ESS score
(Japanese version). An ESS score higher than 10.5 is
considered to indicate excessive daytime sleepiness [
Two-question case-finding instruments for depression
were used to evaluate each athlete’s mood [
instruments consisted of two questions: (1) “During the past
month, have you often been bothered by feeling down,
depressed, or hopeless?” and (2) “During the past month,
have you often been bothered by little interest or pleasure
in doing things?” Athletes were requested to answer “yes”
or “no” to each question. For Japanese adults, a sensitivity
of 99% and a specificity of 60.5% have been reported if the
respondent answers “yes” to either of the two questions. If
the respondent answers “yes” to both questions, a
sensitivity of 87.9% and a specificity of 81.4% have been reported
]. For the logistic regression analyses, the answer “yes”
to both questions was considered “the athlete feels a
depressive mood.” For the logistic regression analyses,
“the athlete feels a depressive mood” was assigned the
dummy variable “1,” and its absence was assigned “0.”
Sleep hygiene was assessed using the modified checklist
reported by Tamura and Tanaka [
Being bathed in sunlight after getting up
Eating breakfast every morning
Not taking a nap after 15:00
Not going out to bright places after 21:00
Avoiding the use of electronic devices just before bed time
Not drinking alcohol to induce sleep
Not thinking about troubles in bed
Keeping the bedroom quiet and comfortable
Using a comfortable mattress and bedclothing
Preventing an irregular getting up time (within 2 h)
Each question had three possible replies: “I already do
so,” “I may be able to, but do not already do so,” and “I
think it is difficult to do so.” For the logistic regression
analyses, “I may be able to, but do not already do so” and
“I think it is difficult to do so” were defined as “the athlete
does not already do so.” For the logistic regression
analyses, “the athlete does not already do so” was assigned
the dummy variable “1,” and the other was assigned “0.”
The athletes were asked about the frequency of
overseas trips in the past 6 months.
The questionnaire took approximately 10 min to
For describing general information, data are expressed
as the mean ± SD. Statistical comparisons between sexes
were conducted by the independent t test for continuous
variables and by chi-square tests and residual analyses
for discrete variables.
In addition, the results of training-practice schedules,
sleep schedule, the PSQI, the ESS, and clinical
information were categorized within each variable, and then the
number and percentages of athletes were described in
To explore factors associated with poor sleep quality
(PSQI global score > 5.5), logistic regression analyses were
performed using the following independent variables: age,
sex, BMI, frequency of overseas expeditions,
trainingpractice schedules, sleep schedules, clinical information,
depressive mood, and sleep hygiene. Initially, we examined
these variables using a univariate analysis. Then, a
multiple logistic regression analysis was performed using the
variables showing significant correlations in the univariate
analysis (p < 0.05). For the continuous variables, the
results were used for the logistic regression analyses. For the
variables regarding clinical information, depressive mood,
and sleep hygiene, dummy variables were used for the
logistic regression analysis. Wald statistics were used to
examine the significant odds ratios generated by the
regression analyses. All analyses were performed using IBM
SPSS 22 for windows. Significance was set at p < 0.05.
The athletes’ heights, body weights, and BMIs were as
follows: 177.5 ± 8.7 cm, 76.7 ± 12.9 kg, and 24.2 ± 3.0 kg/
m2 for males, and 165.0 ± 7.7 cm, 59.9 ± 8.7 kg, and 22.1
± 2.6 kg/m2 for females, respectively (p < 0.001). The
BMIs in 296 males (65.9%) were less than 25 kg/m2, and
those in 153 males (34.1%) were equal to or greater than
25 kg/m2. The indexes in 333 females (90.5%) were less
than 25 kg/m2, and those in 35 females (9.5%) were
equal to or greater than 25 kg/m2.
The characteristics of the athletes’ daily schedules are
presented in Table 1. If the athletes have several types of
training-practice schedules, the earliest start and latest
end times were adopted as representative. The statistical
analysis revealed significant differences between the
sexes in the latest training-practice end time (18:20 ±
2:00 for males and 18:36 ± 2:00 for females, p < 0.01) and
the hours of training-practice per week (22 h 30 min ±
10 h 12 min for males and 24 h 36 min ± 12 h for
females, p < 0.05), but not in the earliest
trainingpractice start time (9:48 ± 2:42 for males and 9:30 ± 2:42
for females). The mean time in bed was 7 h and 29 min
in total: 7 h and 37 min for males and 7 h and 20 min
for females (p < 0.001). Two point four percent of males
and 6.3% of females were considered short sleepers (time
in bed < 6 h). For both males and females, more than
half of the athletes have napping habits of once or more
than once per week. Additionally, both males and
females tend to prefer a nap duration of 31–60 min.
Table 2 describes the mean time in bed in athletes
specialized in each sport. Each mean value was
calculated when the values were obtained from more
than four athletes. The results show a time in bed of less
than 7 h in males from five sports and in females from
The results of the PSQI and the ESS are presented in
Table 3. Two-hundred and twenty-nine (28.0%) athletes,
111 (24.7%) males and 118 (32.1%) females, showed a
PSQI global score above 5.5. The mean and SD of the
PSQI global scores were 4.2 ± 2.1 for males and 4.7 ± 2.2
for females (p < 0.01). The PSQI sub-category scores
indicated the presence of 34 (4.2%) athletes with a long
sleep latency. The sub-category scores also indicated that
76 (9.3%) athletes had difficulty maintaining their sleep.
Fifty (11.1%) males and 51 (13.9%) females showed a
sleep efficiency lower than 85%. Two-hundred and
sixtyfive (32.4%) athletes, 112 (24.9%) males and 153 (41.6%)
females, showed an ESS score above the cutoff level.
The mean and SD of the ESS scores were 8.2 ± 4.0 for
males and 9.7 ± 4.1 for females (p < 0.001). Overall, both
the PSQI global and ESS scores were below the cutoff
for 417 (51.0%) athletes. For 91 (11.1%) athletes, both
scores were above the cutoff.
Regarding clinical information, approximately 40% of
the athletes had been informed by someone about
“snoring loudly” and/or “leg twitching or jerking during
sleep” (Table 4). Males were frequently described as loud
snorers (p < 0.001) and taking long pauses between
breaths (p < 0.01, Table 4). According to BMI, 4.7% of
males and 1.2% of females in the categories with a BMI
below 25 kg/m2 had been informed of long pauses
between breaths, whereas those values were 12.3 and
11.4% in the categories with a BMI at or above 25 kg/
m2, respectively. Leg twitching or jerking during sleep
was remarked in 55.5% of females (p < 0.01).
Regarding the results of the two-question case-finding
instruments for depression, 141 (17.3%) athletes in total,
58 (12.9%) males and 83 (22.6%) females, replied “yes” to
both questions (p < 0.01).
The results of sleep hygiene are shown in Fig. 1. For
both males and females, less than 20% of the athletes
replied “I already do so” to the items “avoiding the use
of electronic devices (PC, smartphone) just before
bedtime” and/or “not thinking about troubles in bed.”
Table 5 describes the results of the univariate and
multiple logistic regression analyses. The univariate
logistic regression analysis revealed that sex, bed time,
time in bed, depressive mood, and eight of ten sleep
hygiene-factors were significantly correlated with poor
sleep quality (PSQI global score > 5.5). In a multiple
logistic regression analysis using the above variables, time
in bed, depressive mood, and three sleep hygiene-factors
were significantly correlated with poor sleep quality.
The results of the univariate and multiple logistic
regression analyses for males and females are described in
Tables 6 and 7. For males, time in bed, depressive mood,
and the hygiene-factor “not thinking about troubles” were
significantly correlated with poor sleep quality (Table 6).
For females, getting up time, depressive mood, the
hygiene-factors “not thinking about troubles in bed” and
“preventing an irregular getting up time (within 2 h)” were
significantly correlated with poor sleep quality (Table 7).
The Prevalence and Factors Associated with Poor Sleep
In the present study, we described the characteristics of
the sleeping habits of elite Japanese athletes, investigated
the prevalence of poor sleep quality on the PSQI global
score, and explored its associated factors. Based on our
knowledge, this is the first study to examine a large
number of elite athletes (n = 817).
Our results using the PSQI global score indicated that
sleep quality is poor in 28% of elite Japanese athletes. A
previous study [
] that examined general populations
in Japan reported that the PSQI global scores were 4.51
± 2.14 for males in their 20s and 5.30 ± 2.48 for females
in their 20s. This study also reported that 30.1% of
males in their 20s and 36.4% for females in their 20s
scored above the cutoff for poor sleep quality on the
PSQI. Our results of the mean PSQI global scores and
prevalence of poor sleep quality for both males and
females were slightly better than those of age-matched
general populations in Japan. The differences between
sexes observed in the sleep schedules, PSQI global, and
ESS scores in this study were in line with those in
previous studies [
The multiple logistic analysis revealed that athletes’
sleep quality was significantly associated with five
factors: “time in bed,” “depressive mood,” “eating
breakfast every morning,” “avoiding the use of electronic
devices (PC, smartphone) just before bedtime,” and “not
thinking about troubles in bed.” Regarding excessive
daytime sleepiness, Doi and Minowa examined 4722
Japanese and reported that insufficient nocturnal sleep,
an irregular sleep-wake schedule, and depression were
associated risk factors [
]. Although the evaluated
parameters differed between the latter research and ours
(PSQI global and ESS scores), common
backgroundrelated factors may exist.
Time in Bed
Our study shows that the mean time in bed was 7 h and
29 min in total, corresponding to 7 h and 37 min for
males and 7 h and 20 min for females. As shown in Table
2, males from five sports and females from nine sports
showed a mean time in bed of less than 7 h. The 2015
NHK Japanese Time Use Survey revealed that the sleep
duration was 7 h and 27 min for males in their 20s
(n = 424) and 7 h and 18 min for females in their 20s
(n = 437) [
]. Since sleep duration is generally
shorter than time in bed, our results may suggest that
time in bed of Japanese athletes was not as long as
those of age-matched general populations. At present,
it is unclear and debatable whether a time in bed that
is the same as the general population is sufficient for
athletes. However, some researchers recommend a
longer nocturnal sleep, i.e., 8–10 h [
] for athletes.
Samuels and Alexander [
] recommend 8–10 h of
nocturnal sleep plus a 30-min nap between 2 and
4 pm for athletes. Bompa and Haff [
] reported that
athletes require 9 to 10 h of sleep, 80–90% of it during the
night. Rountree [
] recommends sleep extension with a
longer training-practice time. Our results suggest that the
time in bed of elite Japanese athletes is inconsistent with
Our study revealed that 34 (4.2%) athletes were
considered short sleepers (time in bed < 6 h). Seventeen
of the 34 short sleepers get up earlier than 6:00.
However, only 4 of the 17 short sleepers reported that
their training-practice starts before 8:00. Sargent et al.
] reported that early-morning training markedly
restricts the time in bed of swimmers. Our results differ
from theirs. For an example, all of our kabaddi players
reported that their training-practice starts around 19:00
and ends at 21:00. Twelve of 20 kabaddi players get up
at 7:00 or earlier because of their jobs. For them, the
schedules of both training-practice and their job may be
the reasons for their short time in bed.
Use of Electronic Devices
In this study, more than 80% of the athletes replied
that they use electronic devices (PC, smartphone)
just before bedtime. The Ministry of Posts and
Telecommunications (Japan) reported that 53.7% of
Internet users in Japan had delayed bedtimes, and
45.4% of them had a shortened sleep duration as a
result of internet use [
]. It is also known that
lights from electronic devices reduce melatonin
levels, increase alertness at night, delay the circadian
clock, and decrease alertness the next morning [
Thus, using electronic devices just before bedtime
may lead to a shortened sleep duration and poor
sleep quality [
It is already known that skipping breakfast is associated
with poor sleep quality [
]. Previous researchers have
stated that busy lifestyles cause some people to skip
breakfast, but some also suggested that skipping
breakfast affects circadian rhythms. For example, in the
liver, breakfast promotes food-induced entrainment of
the circadian clock [
]. In addition, some researchers
suggest that dietary components influence the synthesis
of serotonin and melatonin, and this contributes to a
good sleep quality [
]. Skipping breakfast may lead to
the loss of these effects.
Hammond et al. reported that 26% of athletes showed
self-reported mild to moderate symptoms of depression
]. In their study, they demonstrated that in elite
athletes, negative changes in their performances were
correlated with depression. Guilliver et al. examined 224 elite
Australian athletes and reported that 27.2% of them
displayed depressive symptoms [
]. Yang et al. examined
257 collegiate athletes and reported that 21% of their
athletes showed depression, and anxiety and pain were
related to that depression [
]. Other factors such as
sports injuries, career termination, and performance
outcomes that are below expectations are also risk
factors of depression [
]. It is also well-known that a
depressive mood is one of the symptoms of
overtraining or overreaching [
]. Although it was unclear
whether our athletes were suffering from overtraining
or overreaching, such risks may arise during periods
of high training loads [
Although sleep disturbance is known as one of the
symptoms of depression, sleep deprivation lowers the
psychological threshold for the perception of stress [
In addition, there is a report that individuals with short
(< 7 h/night) and long (≧ 9 h/night) sleep durations
show an increased genetic influence for depression [
Thus, sleep quantity and quality are associated with
depression and vice versa.
Thinking About Troubles in Bed
Symptoms of chronic stress, burnout, anxiety, and
nervousness are prevalent amongst athletes [
Erlacher et al. studied 632 German athletes and
reported that 65.8% of them experienced poor sleep
during nights before important competitions [
Romyn et al. demonstrated strong negative associations
between state anxiety and sleep quality in athletes
]. Kashani et al. reported a significant correlation
between perceived stress and the PSQI global score
]. In non-pharmacologic treatment of insomnia,
Lande and Gragnani recommend trying to resolve
problems prior to bedtime or to make resolution a
priority the following day [
]. Siebern et al.
recommends relaxation techniques including progressive
muscle relaxation, deep breathing techniques, body
scanning, and autogenic training [
Although the logistic regression analysis did not reveal a
significant association with sleep quality, 40% of the
athletes had been informed by someone about “snoring
loudly” and/or “leg twitching or jerking during sleep”
(Table 5). Similarly, Swinbourne et al. examined 175
athletes in New Zealand and demonstrated that 38% of
them were defined as snorers and 8% reported having
apnoeic episodes [
]. Tuomilehto et al. examined 107
professional ice-hockey players and found that 14 of
them had obstructive sleep apnoea [
]. In our studies,
loud snoring and a long pause between breaths were
widely distributed in many BMI categories, and higher
percentages of athletes were found in larger BMI
categories. Emsellem and Murtagh said that a BMI
above 28.0 kg/m2 and a neck circumference greater than
40.0 cm are risk factors for obstructive sleep apnoea
]. However, this BMI criterion might be
too high for the Japanese. Itasaka et al. divided 257
Japanese subjects into three groups: normal weight (BMI
under 24.0 kg/m2), mildly obese (BMI 24.0–26.4 kg/m2),
and obese (BMI 26.4 kg/m2 or higher), and showed that
the apnoea-hypopnea index, intraoesophageal pressure,
and lowest oxygen saturation became significantly worse
according to the degree of obesity [
]. In this study, the
athletes with a BMI at or above 25 kg/m2 showed a
higher frequency of being informed about long pauses
between breaths. However, some athletes with a BMI
below 25 kg/m2 were also similarly informed. Other
factors, such as microgenia, retrognathia, rhinostenosis,
and enlarged tonsils, should also be examined to identify
causes of apnoea/hypopnea. Regarding leg twitching or
jerking, there are both physiological and pathological
causes. If the leg twitching or jerking is physiological
and does not fragment sleep, treatment is rarely
]. For pathological forms, sleep-related
movement disorders, such as periodic limb movement
disorder and restless legs syndrome, may be related. A
low ferritin level (> 50 μg/L) is one of the risk factors of
restless leg syndrome [
]. Koehler et al. reported that
31% of male athletes and 57% of female athletes showed
serum ferritin levels below 35 μg/L [
]. Checking blood
profiles might be recommended if sleep is disturbed by
frequent limb movements. In a study on 107
professional ice hockey players, Tuomilehto et al. found 14
with obstructive sleep apnoea, 13 with insomnia, 4 with
restless legs syndrome and periodic leg movements, 1
with parasomnia, and 1 with delayed sleep-wake
]. We should keep in mind that factors not
showing an association in our logistic analysis may also
affect individual athlete’s sleep quality.
For both males and females, depressive mood and the
hygiene-factor “not thinking about troubles in bed” were
correlated with poor sleep quality (Tables 6 and 7). Time
in bed for males and getting up time and the
hygienefactor “preventing an irregular getting up time (within
2 h)” for females were also correlated with poor sleep
quality. These results suggest that psychological factors
and sleep schedules are common factors that affect poor
Firstly, we investigated Japanese athletes’ sleeping habits
using a questionnaire and not by actual measurements.
If applicable, it would be desirable to evaluate sleep
schedules with equipment such as actigraphy [
2–4, 8, 9,
]. Secondly, Samuels et al. developed a new
athlete-specific sleep-screening questionnaire because
they felt that the PSQI classified a higher than expected
number of athletes as poor sleepers [
]. For example,
24.7% of males and 32.1% of females showed a PSQI
global score above 5.5, whereas our PSQI subcategory
scores indicated that the number of athletes with
insomnia seems to be small. It is debatable whether the PSQI
is the most suitable sleep-screening questionnaire for
athletes. Thirdly, athletes younger than 20 years old were
excluded from this study. Since many of them spend the
daytime at high school or junior high school, their
training schedules and sleeping habits may be different from
those shown by our results. Fourthly, we could not
evaluate athletes’ performance in this research. Further
studies are necessary to verify that an improvement in
sleep leads to enhanced sport performance.
In conclusion, 229 (28.0%) athletes had a PSQI global
score showing poor sleep quality. Compared to the
results in a previous study [
], our results suggest that
the prevalence of poor sleep quality in athletes is slightly
lower than that in age-matched general populations. The
multiple logistic analysis in our study revealed that poor
sleep quality on the PSQI global score is related to five
factors: “time in bed,” “depressive mood,” “eating
breakfast every morning,” “avoiding the use of electronic
devices (PC, smartphone) just before bedtime,” and “not
thinking about troubles in bed.” Forty percent of athletes
reported they had been informed by someone about
“snoring loudly” and/or “leg twitching or jerking during
sleep,” which would suggest that sleep quality would be
poor; however, this finding was not significantly
associated with poor sleep quality on the PSQI global score. In
the medical check for athletes, it may be desirable to
include screening for sleep disorders.
BMI: Body mass index; ESS: Epworth Sleepiness Scale; PSQI: Pittsburgh Sleep
We thank the Japanese Olympic Committee and the athletes who
participated in this study. This study was carried out as part of the Research
Projects of Japan Institute of Sports Sciences.
This study was partially supported by JSPS KAKENHI Grant Number 26350827.
Availability of Data and Materials
MH was involved in the design, data collection, analysis, and article writing. SU
supervised the research design. YH managed the conduction of the research
and revised the manuscript. All authors read and approved the final manuscript.
Ethics Approval and Consent to Participate
All procedures performed involving human participants were conducted in
accordance with the ethical standards of the institutional and/or national
research committee and with the 1964 Helsinki declaration and its later
amendments or comparable ethical standards. Informed consent was
obtained from all individual participants included in the study.
Consent for Publication
Consent to publish was obtained from all the participants.
Masako Hoshikawa, Sunao Uchida, and Yuichi Hirano declare no conflicts
Springer Nature remains neutral with regard to jurisdictional claims in
published maps and institutional affiliations.
1. Robson-Ansley P , Gleeson M , Ansley L . Fatigue management in the preparation of Olympic athletes . J Sports Sci . 2009 ; 27 : 1409 - 20 .
2. Leeder J , Glaister M , Pizzoferro K , Dawson J , Pedlar C . Sleep duration and quality in elite athletes measured using wristwatch actigraphy . J Sports Sci . 2012 ; 30 ( 6 ): 541 - 5 .
3. Sargent C , Halson S , Roach GD . Sleep or swim? Early-morning training severely restricts the amount of sleep obtained by elite swimmers . Eur J Sports Sci . 2014 ; 14 ( S1 ): S310 - 5 .
4. Sargent C , Lastella M , Halson SL , Roach GD . The impact of training schedules on the sleep and fatigue of elite athletes . Chronobiol Int . 2014 ; 31 : 1160 - 8 .
5. Shapiro CM , Bortz R , Mitchell D. Slow-wave sleep: a recovery period after exercise . Science . 1981 ; 214 ( 11 ): 1253 - 4 .
6. Taylor SR , Rogers GG , Driver HS . Effects of training volume on sleep, psychological, and selected physiological profiles of profiles of elite female swimmers . Med Sci Sports Exerc . 1997 ; 29 ( 5 ): 688 - 93 .
7. Hague JFE , Gilbert SS , Burgess HJ , Ferguson SA , Dawson D. A sedentary day: effects on subsequent sleep and body temperatures in trained athletes . Physiol Behav . 2003 ; 78 : 261 - 7 .
8. Kolling S , Wiewelhove T , Raeder C , Endler S , Ferrauti A , Meyer T , et al. Sleep monitoring of a six-day macrocycle in strength and high-intensity training . Eur J Sport Sci . 2016 ; 16 ( 5 ): 507 - 15 .
9. Killer SC , Svendsen IS , Jeukendrup AE , Gleeson M. Evidence of disturbed sleep and mood state in well-trained athletes during short-term intensified training with and without a high carbohydrate nutritional intervention . J Sports Sci . 2017 ; 35 ( 14 ): 1402 - 10 .
10. Fullagar HHK , Skorski S , Duffield R , Julian R , Bartlett J , Meyer T. Impaired sleep and recovery after night matches in elite football players . J Sports Sci . 2016 ; 34 ( 14 ): 1333 - 9 .
11. Staunton C , Gordon B , Custovic E , Stanger J , Kingsley M. Sleep patterns and match performance in elite Australian basketball players . J Sci Med Sport . https://doi.org/10.1016/j.jsams. 2016 . 11 .016.
12. Lastella M , Roach GD , Halson SL , Martin DT , West NP , Sargent C . Sleep/wake behavior of endurance cyclists before and during competition . J Sports Sci . 2015 ; 33 ( 3 ): 293 - 9 .
13. Erlacher D , Ehrlenspiel F , Adegbesan OA , El-Din HG . Sleep habits in German athletes before important competitions or games . J Sports Sci . 2011 ; 29 ( 8 ): 859 - 66 .
14. Juliff LE , Halson SL , Peiffer JJ . Understanding sleep disturbance in athletes prior to important competitions . J Sci Med Sport 2015 ; 18 ( 1 ): 13 - 18 .
15. Lastella M , Lovell GP , Sargent C . Athletes' precompetitive sleep behavior and its relationship with subsequent precompetitive mood and performance . Eur J Sport Sci . 2014 ; 14 ( S1 ): S123 - 30 .
16. Emsellem HA , Murtagh KE . Sleep apnea and sports performance . Clin Sports Med . 2005 ; 24 : 329 - 41 .
17. Rice TB , Dunn RE , Lincoln AE , Tucker AM , Vogel RA , Heyer RA , et al. Sleepdisordered breathing in the national football league . Sleep . 2010 ; 33 ( 6 ): 819 - 24 .
18. Swinbourne R , Gill N , Vaile J , Smart D. Prevalence of poor sleep quality, sleepiness and obstructive sleep apnoea risk factors in athletes . Eur J Sport Sci . 2016 ; 16 ( 7 ): 850 - 8 .
19. Tuomilehto H , Vuorinen VP , Penttilä E , Kivimäki M , Vuorenmaa M , Venojärvi M , et al. Sleep of professional athletes: underexploited potential to improve health and performance . J Sports Sci . 2017 ; 35 ( 7 ): 704 - 10 .
20. Samuels C , James L , Lawson D , Meeuwisse W. The athlete sleep screening questionnaire: a new tool for assessing and managing sleep in elite athletes . Br J Sport Med . 2016 ; 50 ( 7 ): 418 - 22 .
21. Munezawa T , Kaneita Y , Osaki Y , Kanda H , Minowa M , Suzuki K , et al. The association between use of mobile phones after lights out and sleep disturbances among Japanese adolescents: a nationwide cross-sectional survey . Sleep . 2011 ; 34 ( 8 ): 1013 - 20 .
22. Chang AM , Aeschbach D , Duffy JF , Czeisler CA . Evening use of lightemitting eReaders negatively affects sleep, circadian timing, and nextmorning alertness . Proc Natl Acad Sci U S A . 2015 ; 112 ( 4 ): 1232 - 7 .
23. White AG , Biboltz W , Igou F. Mobile phone use and sleep quality and length in college students . Int J Humanities Soc Sci . 2011 ; 1 ( 18 ): 51 - 8 .
24. Mastin DF , Bryson J , Corwyn R . Assessment of sleep hygiene using the Sleep Hygiene Index . J Behav Med . 2006 ; 29 ( 3 ): 223 - 7 .
25. Kang JH , Chen SC . Effects of irregular bedtime schedule on sleep quality, daytime sleepiness, and fatigue among university students in Taiwan . BMC Public Health . 2009 ; 9 : 248 . https://www.ncbi.nlm.nih.gov/pmc/articles/ PMC2718885/. accessed 31 July 2017
26. Buysse DJ , Reynolds CF 3rd, Monk TH , Berman SR , Kupfer DJ . The Pittsburgh sleep quality index: a new instrument for psychiatric practice and research . Psychiatry Res . 1989 ; 28 ( 2 ): 193 - 213 .
27. Fietze I , Strauch J , Holzhausen M , Glos M , Theobald C , Lehnkerning H , et al. Sleep quality in professional ballet dancers . Chronobiol Internat . 2009 ; 26 ( 6 ): 1249 - 62 .
28. Knufinke M , Nieuwenhuys A , SAE G , AML C , MAJ K. Self reported sleep quantity, quality and sleep hygiene in elite athletes . J Sleep Res . 2017 ; http://onlinelibrary.wiley.com/doi/10.1111/jsr.12509/epdf. accessed 31 July 2017
29. Hoshikawa M , Uchida S , Fujita Y . Questionnaire study of the sleeping habits of elite Japanese athletes . Jpn J Clin Sports Med . 2015 ; 23 ( 1 ): 74 - 87 .
30. Doi Y , Minowa M , Uchiyama M , Okawa M. Development of the Pittsburgh sleep quality index Japanese version . Jpn J Psychiatry Treat . 1998 ; 13 ( 6 ): 755 - 63 .
31. Takegami M , Suzukamo Y , Wakita T , Noguchi H , Chin K , Kadotani H , et al. Development of a Japanese version of the Epworth Sleepiness Scale (JESS) based on item response theory . Sleep Med . 2009 ; 10 : 556 - 65 .
32. Whooley MA , Avins AL , Miranda J , Miranda J , Browner WS . Case finding instruments for depression. Two questions are good as many . J Gen Intern Med . 1997 ; 12 : 439 - 45 .
33. Doi Y , Minowa M , Uchiyama M , Okawa M , Kim K , Shibui K , et al. Psychometric assessment of subjective sleep quality using the Japanese version of the Pittsburgh Sleep quality index (PSQI-J) in psychiatric disordered and control subjects . Psychiatry Res . 2000 ; 97 ( 2 ): 165 - 72 .
34. Suzuki T , Nobata R , Kim N , Hane Y , Narita T , Iwata N , et al. Evaluation of questionnaire (Two-question case-finding instrument and Beck depression inventory) as a tool for screening and intervention of depression in work place . Seishin Igaku (Clinical Psychiatry) . 2003 ; 45 : 699 - 708 .
35. Tamura N , Tanaka H. Effects of sleep education with self-help treatment for elementary schoolchild with nocturnal lifestyle . Sleep Biol Rhythms . 2014 ; 12 : 169 - 79 .
36. Doi Y , Minowa M , Uchiyama M , Okawa M. Subjective sleep quality and sleep problems in the general Japanese adult population . Psychiat and Clin Neurosci . 2001 ; 55 : 213 - 5 .
37. Doi Y , Minowa M. Gender differences in excessive daytime sleepiness among Japanese workers . Soc Sci Med . 2003 ; 56 ( 4 ): 883 - 94 .
38. Sekine C , Watanabe Y , Hayashida M. No more decline in sleeping time, more time now spent on necessary activities from the 2015 NHK Japanese time use survey . The NHK monthly report on broadcast research , 2016 May, 2 - 27 . http://www.nhk.or.jp/bunken/english/reports/pdf /report_16071301.pdf 8. accessed on 1 May 2017 .
39. Mah CD , Mah KE , Kezirian EJ , Dement WC . The effects of sleep extension on the athletic performance of collegiate basketball players . Sleep . 2011 ; 34 ( 7 ): 943 - 50 .
40. Samuels CH , Alxander BN . Sleep, recovery, and human performance. A comprehensive strategy for long-term athlete development. Sport for life . http://www.swimsask.ca/pdf/Sleep-and-Recovery. pdf. accessed 1 May 2017 .
41. Bompa TO , Haff GG . Periodization: theory and methocology of training . 5th ed. Champaign: Human Kinetics Pub; 2009 . p. 97 - 122 .
42. Rountree S. The athlete's recovery: rest, relax, and restore for peak performance . Boulder: Velopress; 2011 .
43. Ministry of Post and Telcomminications (Japan) . White paper communications in Japan 1998 . Gyosei; 1998 . p. 10 - 6 . (in Japanese). http:// www.soumu.go.jp/johotsusintokei/whitepaper/ja/h10/pdf/index.html. accessed on 1 May 2017 .
44. Wang L , Qin P , Zhao Y , Duan S , Zhang Q , Liu Y , et al. Prevalence and risk factors of poor sleep quality among inner Mongolia medical university students: a cross-sectional survey . Psychiatry Res . 2016 ; 244 : 243 - 8 .
45. Hirao A , Nagahama H , Tsuboi T , Hirao M , Tahara Y , Shibata S . Combination of starvation interval and food volume determines the phase of liver circadian rhythm in Per2: Luc knock-in mice under two meals per day feeding . Am J Physiol Gastrointest Liver Physiol . 2010 ; 299 : G1045 - 53 .
46. Halson SI . Sleep in elite athletes and nutritional interventions to enhance sleep . Sports Med . 2014 ; 44 ( Suppl ): S13 - 23 .
47. Hammond T , Gialloreto C , Kubas H , Hap Davis H IV. The prevalence of failure-based depression among elite athletes . Clin J Sports Med . 2013 ; 23 : 273 - 7 .
48. Guilliver A , Griffiths K , Mackinnon A , Batterham PJ , Stanimirovic R. The mental health of Australian elite athletes . J Sci Med Sport . 2015 ; 18 ( 3 ): 255 - 61 .
49. Yang J , Peek-Asa C , Corlette JD , Cheng G , Foster DT , Albright J . Prevalence of and risk factors associated with symptoms of depression in competitive collegiate student athletes . Clin J Sports Med . 2007 ; 17 : 481 - 7 .
50. Wolanin A , Gross M , Hong E. Depression in athletes: prevalence and risk factors . Cur Sports Med Reports . 2015 ; 14 ( 1 ): 56 - 60 .
51. Urhausen A , Kindermann W . Diagnosis of overtraining. What tools do we have? Sports Med . 2002 ; 32 ( 2 ): 95 - 102 .
52. Hausswrth C , Louis J , Aubry A , Bonnet G , Duffield R , Meur YL . Evidence disturbed sleep and increased illness in overreached endurance athletes . Med Sci Sports Exerc . 2014 ; 46 ( 5 ): 1036 - 45 .
53. Minkel JD , Banks S , Htaik O , Moreta MC , Jones CW , McGlinchey EL , et al. Sleep deprivation and stressors: evidence for elevated negative affect in response to mild stressors when sleep deprived . Emotion . 2012 ; 12 ( 5 ): 1015 - 20 .
54. Watson NF , Harden KP , Buchwald D , Vitello MV , Pack AI , Strachan E , et al. Sleep duration and depressive symptoms: a gene-environment interaction . Sleep . 2014 ; 37 : 351 - 8 .
55. Demarzo MMP , Stein PK . Mental stress and exercise training response: stress-sleep connection may be involved . Front Physiol . 2012 ; 3 : 51 . https:// doi.org/10.3389/fphys. 2012 . 00051 . accessed 2 May 2017
56. Romyn G , Robey E , Dimmock JA , Halson SL , Peeling P. Sleep , anxiety, and electronic device use by athletes in the training and competition environment . Eur J Sports Sci . 2016 ; 16 ( 3 ): 301 - 8 .
57. Kashani M , Eliasson A , Vernalis M. Perceived stress correlates with disturbed sleep: a link connecting stress and cardiovascular disease . Stress . 2012 ; 15 ( 1 ): 45 - 51 .
58. Lande RG , Gragnani C . Nonpharmacologic approaches to the management of insomnia . J Am Osteopath Assoc . 2010 ; 110 ( 12 ): 695 - 701 .
59. Seibern AT , Suh S , Nowakowski S . Non-pharmacological treatment of insomnia . Neurotherapeutics . 2012 ; 9 : 717 - 27 .
60. Itasaka Y , Miyazaki S , Ishikawa K , Togawa K. The influence of sleep position and obesity on sleep apnea . Psychirat Clin Neurosci . 2000 ; 54 : 340 - 1 .
61. Iber C , Ancoli-Israel S , Chesson A , Quan SF , for the American Academy of Sleep Medicine. The AASM manual for the scoring of sleep and associated events: rules, terminology and technical specifications . 1st ed. Westcher: American Academy of Sleep Medicine; 2007 . p. 41 - 3 .
62. O 'Keeffe ST . Iron deficiency with normal ferritin levels in restless legs syndrome . Sleep Med . 2005 ; 6 : 281 - 2 .
63. Koehler K , Braun H , Achtzehn S , Hildebrand U , Predel HG , Schänzer W. Iron status in elite young athletes: gender-dependent influences of diet and exercise . Eur J Appl Physiol . 2012 ; 112 : 513 - 23 .