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Sleep Pattern of Adolescents in a School in Delhi, India: Impact on their Mood and Academic Performance. Indian J Pediatr. 2018 Indian J Pediatr. 2018 Oct;85(10):841-848. doi: 10.1007/s12098-018-2647-7.



OBJECTIVES: To examine the sleep pattern and observe differences in sleep routines, phase preferences, mood, attendance, and academic performance among different adolescent age students. Secondly, to observe the age at which sleep phase transition and changes in sleep requirement become evident. METHODS: A cross-sectional study was conducted among 501 students (aged 11-15 y) of a school in Delhi, India. Students were evaluated for their sleep patterns, sleep duration, habits of napping, quality of sleep, sleepiness, depression, phase preferences by self-reported school sleep habits survey questionnaire along with school performance and attendance. RESULTS: Significant differences were found in sleep pattern of students aged 11-12 y and 13-15 y. Bedtime shifted to a later time with increasing age but early morning schools kept the wake time same, leading to a decline in total sleep duration of older adolescents. Older adolescents had higher depression but poor attendance and academic performance. Prevalence of sleep deprivation increased with age, from 83.7% to 87.1% in 11-12 y to 90.5% to 92.5% in 13-15 y. CONCLUSIONS: The study clearly identifies 12-13 y as age of transition of sleep pattern among adolescents. Though significant differences were found in the academic performance, mood and attendance among preteens and teens but no direct association was seen between academic performances and sleep pattern. A complex multifactorial association between sleep patterns, attendance, mood and academic performance which may change over days, months, or years should be explored further in a longitudinal follow up study.
Sleep Pattern of Adolescents in a School in Delhi, India: Impact on their
Mood and Academic Performance
Ruchi Singh
&Jagdish C. Suri
&Renuka Sharma
&Tejas Suri
&Tulsi Adhikari
Received: 21 September 2017 / Accepted: 15 February 2018
#Dr. K C Chaudhuri Foundation 2018
Objectives To examine the sleep pattern and observe differences in sleep routines, phase preferences, mood, attendance, and
academic performance among different adolescent age students. Secondly, to observe the age at which sleep phase transition and
changes in sleep requirement become evident.
Methods A cross-sectional study was conducted among 501 students (aged 1115 y) of a school in Delhi, India. Students were
evaluated for their sleep patterns, sleep duration, habits of napping, quality of sleep, sleepiness, depression, phase preferences by
self-reported school sleep habits survey questionnaire along with school performance and attendance.
Results Significant differences were found in sleep pattern of students aged 1112 y and 1315 y. Bedtime shifted to a later time
with increasing age but early morning schools kept the wake time same, leading to a decline in total sleep duration of older
adolescents. Older adolescents had higher depression but poor attendance and academic performance. Prevalence of sleep
deprivation increased with age, from 83.7% to 87.1% in 1112 y to 90.5% to 92.5% in 1315 y.
Conclusions The study clearly identifies 1213 y as age of transition of sleep pattern among adolescents. Though significant
differences were found in the academic performance, mood and attendance among preteens and teens but no direct association
was seen between academic performances and sleep pattern. A complex multifactorial association between sleep patterns,
attendance, mood and academic performance which may change over days, months, or years should be explored further in a
longitudinal follow up study.
Keywords Sleep deprivation .Depression .Sleep .Students .Adolescents .Mood .School performance
Sleep is a biological necessity for regeneration of mind and
body. Unfortunately, it is an easily compromised part in daily
routine. Students between ages, 10 to 19 y who are in stage of
transition from childhood to adulthood, are especially
vulnerable to sleep loss [1]. Researchers have shown that there
is a sleep phase shift during adolescence [2]. Total sleep re-
quirement remains between 8.25 to 9.2 h/night for optimal
daytime alertness but sleep onset time is delayed [3,4].
Inconsistency between sleep pattern, i.e., sleeping and waking
routines on weekdays and weekends increases as one grows to
an adolescent [58]. Adequate sleep is essential for normal
daytime functioning, learning, cognition, physical and
psychological well-being [9]. In spite of increased sleep
requirements, adolescents experience sleep debt and suffer
unknowingly from its consequences i.e., daytime sleepi-
ness, mood changes and poor school attendance [4,10,
11]. Poor sleep badly impacts attention, memory and ac-
ademic performance [1214].
Various cultural, social, environmental, and family factors
are responsible for changes in sleep patterns [15]. Hence this
study was undertaken to examine these changes in sleep pat-
tern and observe differences in sleep routines, phase prefer-
ences, mood change, attendance, and academic performance
*Jagdish C. Suri
Department of Physiology, VMMC and Safdarjung Hospital,
Delhi, India
Department of Pulmonary, Critical Care and Sleep Medicine,
Safdarjung Hospital, New Delhi 110029, India
Department of Medicine, All IndiaInstitute ofMedical Science, New
Delhi, India
National Institute of Medical Statistics (ICMR), Ansari Nagar, New
Delhi, India
The Indian Journal of Pediatrics
among different adolescent age students in a school of Delhi,
India which still is unexplored. The authors also endeavored
to know the age when sleep phase transition and changes in
sleep requirement become evident.
Material and Methods
This was a cross-sectional study enrolling 501 urban students of
a school in Delhi, India. The study was conducted after getting
prerequisite permission from the school administration and eth-
ical clearance from ethics committee of the Institution. Data
was collected in the month of OctoberNovember from stu-
dents of 6th9th grades. Rationale of study was explained to
ticipate in the study. Consent forms were distributed for the
parents of these students. Of 575 forms distributed, consent
was received from 545 parents. Further data was collected only
from these students. School sleep habits survey questionnaire,
which is a comprehensive instrument including items about
sleep habits during the previous 2 wk as well as daytime func-
tioning, was used in this survey; Available at http://www. [4].Itwasinaneasylanguageand
individual items were explained to the participants. They were
clearly instructed not to fill the response without understanding
or if unsure. A total of 501 completely filled forms were
received back and were included for further evaluation.
The questionnaire evaluated the students for their sleep
patterns, napping, quality of sleep, and sleep awakenings sep-
arately on weekdays and weekends for the past 2 wk along
with their mood, academic performance, and attendance. The
authors took weekly total sleep duration <58:10 hh:mm (at
least 8.30 h of daily night sleep for 7 d in a week) as a cutoff
for considering sleep deprivation [16]. It was used to estimate
the prevalence of sleep deprivation among adolescents.
Daytime Sleepiness For assessing daytime sleepiness a self-
reported question was asked about the extent of problem the
subject has with sleepiness during his/her daytime activities
whichrangedbetween1and5fromBno problem at all^to Ba
big problem^[4].
Quality of Sleep The questionnaire consisted of total responses
to two self-reported items questioning how often the subject
had Bfelt satisfied with your (his/her) sleep^and Bhad good
nightssleep^over the last 2 wk [17]. Another question exam-
ining whether sleep duration was considered sufficient by the
respondent, added to the information on quality of sleep [18].
Phase Delay A scale consisting of responses to six self-
reported items, attempted to reveal about the frequency of
behaviors presumed to be related to a phase delay of sleep
and included questions such as Bstayed up all night,^and
Bstayed up till 3 a.m.^for the past 2 wk [17].
Morningness/Eveningness A 10-item morningness/eveningness
scale is a validated adaptation of the composite scale of
morningnessusedtoassessME orientation in adolescents
indicative of greater morningness [5]. Morning/evening types
refer to the circadian typesclassification that the morning types
(M-types) prefer day activity whereas evening types (E-types)
prefer night activity.
Depression The students were assessed by a self-reported
measure for depression that Bhow often they were troubled
by certain situations in the last 2 wk^by using depressive
mood scale [20].
Attendance and Performance Attendance was calculated as
the percentage of total number of presents in an academic
session. Academic performance was calculated from their per-
centages in respective subjects during that academic session.
Data analysis was carried out using SPSS, version 11.5
(SPSS Inc., Chicago, IL). Normality of data was tested using
ShapiroWilk test. Statistical descriptions were made using
mean, standard deviation for continuous variables and percent-
age for categorical variables. Independent-sample t-test, univar-
iate analysis of variance with post hoc GamesHowell test, and
chi-square test were used to compare the differences between
groups, where appropriate. Correlation analysis was performed
using Pearsons correlation coefficient. A two-tailed (α=2),
probability (p) value less than 0.05 (p< 0.05) was considered
to be statistically significant for all statistical tests applied.
A total of 501 school children (295 male and 206 female stu-
dents) aged 1115 y participated in this study. Students were
comparable in their baseline characters with a mean age of 12.9
± 1.2 y, height 150 ± 13.8 cm, and weight 42.09 ± 9.7 kg.
Analysis of variance of sleep routines of various age groups
(1115 y) revealed no difference between students aged 11
there were significant differences between the sleep routines of
preteens (1112 y) and teenagers (1315 y) (Tables 1and 2).
Sleep Pattern on Weekdays and Weekends Preteens had rel-
atively early time to bed compared to teenagers. On weekends,
time to bed of all students was delayed, with teenagers having
considerably delayed bed time (p= 0.0001). Female students
had greatly delayed rise time (p= 0.0001) on weekends
and thus had significantly more total sleep time (p=
0.004) on weekends as compared to males students
Indian J Pediatr
Table 1 An age-wise and gender wise comparison of sleep routine of the subjects
Variables 11 years (N=85)
(Boys-51, Girls-34)
12 years (N= 98)
(Boys-60, Girls-38)
13 years (N=126)
(Boys-73, Girls-53)
14 years (N= 125)
(Boys-65, Girls-60)
15 years (N= 67)
(Boys-46, Girls-21)
Gender Age Age and Gender
WD 22:00 ± 00:32
22:00 ± 00:38
22:17 ± 00:45
22:26 ± 00:46
22:33 ± 00:50
0.344 (p= 0.558) 10.607 (p= 0.0001)** 0.297 (p= 0.880)
Boys 22:01 ± 00:36 22:00 ± 00:40 22:16 ± 00:45 22:26 ± 00:44 22:29 ± 00:52
Girls 21:57 ± 00:26 22:00 ± 00:37 22:19 ± 00:45 22:27 ± 00:48 22:41 ± 00:47
WE 22:29 ± 00:40
22:32 ± 00:42
22:47 ± 00:49
22:53 ± 00:43
23:07 ± 00:50
1.689 (p= 0.194) 10.994 (p= 0.0001)** 1.176 (p= 0.320)
Boys 22:27 ± 00:42 22:31 ± 00:44 22:42 ± 00:52 22:52 ± 00:43 22:58 ± 00:39
Girls 22:33 ± 00:37 22:32 ± 00:40 22:55 ± 00:42 22:56 ± 00:43 22:35 ± 01:06
Rise-up time
WD 5:36 ± 00:27 5:34 ± 00:26 5:32 ± 00:29 5:36 ± 00:31 05:42 ± 00:31 0.071 (p= 0.790) 0.861 (p= 0.487) 1.366 (p= 0.245)
Boys 5:37 ± 00:26 5:31 ± 00:25 5:33 ± 00:29 5:32 ± 00:30 5:45 ± 00:31
Girls 5:33 ± 00:29 5:39 ± 00:27 5:32 ± 00:29 5:41 ± 00:31 5:37 ± 00:32
WE 07:51 ± 1:25 7:53 ± 1:21 8:07 ± 1:12 8:05 ± 1:30 08:07 ± 1:25 14.856 (p= 0.0001)** 1.156 (p= 0.329) 1.418 (p= 0.227)
Boys 7:51 ± 01:33 7:36 ± 1:14 7:58 ± 1:08 7:55 ± 1:45 7:48 ± 1:20
Girls 7:52 ± 1:14 8:20 ± 1:25 8:20 ± 1:16 8:17 ± 1:09 8:48 ± 1:23
Total sleep time
WD 7:21 ± 00:48
7:16 ± 00:57
6:56 ± 00:49
6:52 ± 00:54
6:48 ± 00:46
0.000 (p= 0.988) 7.212 (p= 0.0001)** 0.371 (p= 0.830)
Boys 7:18 ± 00:49 7:19 ± 00:56 6:56 ± 00:49 6:51 ± 00:55 6:50 ± 00:41
Girls 7:27 ± 00:46 7:11 ± 00:59 6:56 ± 00:50 6:55 ± 00:54 6:44 ± 00:57
WE 8:59 ± 1:19 8:56 ± 1:21 8:50 ± 1:18 8:51 ± 1:12 8:35 ± 1:16 8.197 (p= 0.004)** 0.441 (p= 0.779) 4.009 (p= 0.003)**
Boys 8:57 ± 1:22 8:49 ± 1:22 8:57 ± 1:15 8:42 ± 1:21 8:11 ± 1:07
Girls 9:02 ± 1:16 9:09 ± 1:19 8:40 ± 1:21 9:00 ± 1:01 9:30 ± 1:08
Data presented as hh:mm (mean) ± SD. Analysis of variance with post hoc Games Howell was carried out. WD Weekday; WE Weekend, F-value F-test of equality of variances.
Significant difference in
the bedtime, on weekdays and weekend, between 11 and 12 y children and 13,14, and 15 y adolescents.
Significant difference in the total sleep time on weekdays between 11 and 12 y children and 14 and
15 y adolescents. *p-value <0.05 was considered significant and **p< 0.001 as highly significant
Indian J Pediatr
(Table 1). This difference in wake up time was there for
all ages but it increased more with age in female students as
compared to the male student of corresponding age (Table 1).
Thus, total sleep of preteens was more both on weekdays (p=
0.0001) and weekends (p= 0.064) as there was not much dif-
ference in awakening time of two groups (Table 2).
Remarkable differences (p= 0.0001) were observed on
intragroup comparison of sleep routines of preteens and teen-
agers on weekdays and weekends. Bedtime shift, calculated as
bedtime difference on weekdays and weekends was 00:30 ±
00:41 h in preteens and 00:30 ± 00:50 h in teenagers (p=
0.0001); wake time shift i.e., difference between weekend
and weekday wakeup time was 2:17 ± 1:26 h in preteens and
2:30 ± 1:29 h in teenagers (p= 0.0001). Weekends oversleep
i.e. the difference between total sleep on weekend and a week-
day was 1:39 ± 1:20 h in preteens and 01:53 ± 1:23 h in teen-
agers (p= 0.0001). Proportion of adolescents falling asleep
when they felt sleepy, due to the circadian and homeostatic
balance was increased on weekends in both groups (Fig. 1).
Lesser number of teenagers went to bed on their own but their
bedtime was considerably delayed both on weekday and
weekend (Table 2, Fig. 1). Students reported that parents con-
trolled their bedtime especially on weekdays while socializing
and electronic media usage was increased on weekends (Fig.
1). Students were also maximally dependent on their parents
forwakingupinmorning;67.8%(n= 124) preteens and
54.6% (n= 174) teens on weekdays and 59.4% (n=109)pre-
teens and 50% (n= 159) teens on weekends next to alarm
clocks 26.2% (n= 48) preteens and 15.3% (n= 49) teens on
weekdays and 32.4% (n= 59) preteens and 21.4% (n= 68)
teens on weekends.
Comparisons of Various Behaviors Related to Napping,
Quality of Sleep, Sleepiness, Tiredness, Attendance, Phase
Preferences, and Phase Delays among Preteens and
Teenagers 39.6% (n= 126) of teenagers reported taking naps
4 times/week compared to only 26.2% (n = 48) preteens who
had lesser frequency of tiredness, 8.21 ± 2.92 compared to
Fig. 1 Causes for the following
bed times schedule among
preteens and teenagers. Reasons
for bedtime on weekdays (a)and
weekends (b) for preteens.
Reasons for bedtime on weekdays
(c) and weekends (d)for
Table 2 Comparison of sleep pattern between preteens and teenagers
Variables Preteens (N= 183) Teenagers (N=318) pvalue
WD 22.00 ± 00:35 22:24 ± 00:47 0.0001**
WE 22:31 ± 00:41 22:54 ± 00:47 0.0001**
Rise up
WD 05:35 ± 00:26 5:36 ± 00:36 0.631
WE 07:52 ± 1:23 08:06 ± 1:22 0.064
Total sleep time (h)
WD 7:19 ± 00:53 06:53 ± 00:51 0.0001**
WE 8:58 ± 1:20 8:47 ± 1:15 0.064
Weekly Sleep loss
Weekly loss 6:41 ± 5:13 8:05 ± 5:34 0.005*
Total weekly night sleep duration <58:10 in hh:mm was considered as
Weekly sleep loss (deprivation). Data presented as hh:mm (mean) ± SD.
WD Wee k day; WE We e k en d . * pvalue <0.05 was considered significant
and **p< 0.001 as highly significant
Indian J Pediatr
teenagers 9.11 ± 3.20 (p= 0.002). Sleepiness was a problem in
59.1% (n= 188) teens compared to 44.9% (n= 82) preteens.
Self-reported quality of sleep was poor among teenagers who
had higher frequency of behaviors related to phase delay and
scored low on MEscale(P> 0.05). Higher ME scores was
found to correlate with less tiredness (r = 0.157, p=0.0001),
reduced phase-delay behaviors (r = 0.198, p=0.0001), and
better sleep quality (r = 0.165, p= 0.0001). M/E scores had
negative correlation with depression (r = 0.175**, p=
0.0001) i.e., higher eveningness lead to greater depression.
Prevalence and Correlates of Sleep Deprivation Through the
Week Adolescents were considered as sleep deprived if week-
ly total night sleep was less than 58:10 (hh:mm) i.e., their
weekend oversleep was unable to rectify their sleep debt.
Prevalence of sleep deprivation increased from approximately
8387% in preteens to more than 92% in teenagers (Table 3).
Sleep deprivation had positive correlation with behaviors re-
lated to phase delay on weekdays (r = 0.119; p=0.008) anda
negative correlation with attendance (r = 0.138; p=0.002)as
well as performance in various subjects (p>0.05).
Differences in the Academic Performance and Mood of
Preteens and Teenagers There were significant differences
in the mood as well as the academic performance of preteens
and teens. The preteens were significantly better in English
(p= 0.0001) and mathematics (p= 0.0001) compared to the
teenagers, 50% (n= 158) of whom took external tuition clas-
ses compared to 41.5% (n= 76) of the preteens (Table 4).
Only 6% (n= 11) of preteens had <80% attendance compared
to 11.9% (n= 38) of teenagers (p= 0.031) who had signifi-
cantly higher depression (p=0.025).
Association of Sleep Pattern with Academic Performance,
Mood Disorder, and Attendance Significant correlation was
observed between sleep patterns and attendance. Bedtime had
a negative correlation with attendance whereas total sleep time
had a positive correlation. Thus if bedtime were delayed, atten-
dance was poor (Table 5). Performance in science, social stud-
ies and mathshad positive correlation (p= 0.002, p=0.011,
p= 0.0001 respectively) with attendance i.e., higher the atten-
dance, better was the performance (Table 5). Mood too
showed positive correlations with bedtime; later bedtime
led to higher depression. Delayed wake up time on week-
ends also led to significantly low attendance. Performance
in English was better if total sleep duration was more on
weekdays and there was negative correlation of wakeup
time on weekends with academic performance (p> 0.05).
Changes in sleep patterns are observed across all ages, from
infancy to adulthood. But variations during adolescence are crit-
ical as it is the time in life, for establishing foundation of a
successful future [9,21]. Shift in sleep-wake pattern towards
eveningness along with a rise in prevalence of sleep deprivation
on transition from preteens to teenage at age between 12 and 13
y in Indian adolescents was remarkable. More than 80% stu-
dents of all ages were sleep deprived (Total nocturnal sleep
<58:10 hh:mm per week) (Tables 1and 3). Sleep deprivation
leading to poor attendance and eveningness was associated with
higher depression, which again was associated with poor atten-
dance. Attendance had a positive correlation with performance.
Sleep pattern along with culmination of other associated factors
Table 4 Comparison of the
academic performance, mood and
attendance of preteens and
Variables Preteens (N= 183) Teenagers (N=318) pvalue
English marks 53.55 ± 17.9 45.91 ± 10.41 0.0001**
Science marks 62.19 ± 17.2 59.5 ± 17.83 0.112
Social studies marks 64.62 ± 17.9 61.3 ± 19.23 0.062
Maths marks 64.22 ± 16.54 58.18 ± 17.22 0.0001**
Educational help 41.5% (76) 49.7% (158) 0.078
Depression 9.05 ± 2.68 9.57 ± 2.40 0.025*
Attendance (<80%) 6% (11) 11.9% (38) 0.031*
Data presented as mean ± SD and percentage (N). *pvalue <0.05 was considered significant and **p<0.001as
highly significant
Table 3 Prevalence of sleep
deprivation among adolescents
through the week
Prevalence of sleep deprivation
(through the week)
11 years
12 years
13 years
14 years
(N= 125)
15 years
Weekly sleep loss 87.1% (74) 83.7% (82) 90.5% (114) 90.4% (113) 92.5% (62)
Total weekly night sleep duration <58:10 (hh:mm) was considered as weekly sleep deprivation. Data presented as
Indian J Pediatr
like mood and sleepiness indirectly affected academic perfor-
mance which was poorer among teenagers who were signifi-
cantly more sleep deprived (p= 0.005), depressed (p= 0.025),
sleepy 59.1% (n= 188) and had poor attendance (p=0.031).
General Sleep Pattern and Its Determinants Sleep patterns
were remarkably irregular both on weekdays and weekends.
Shift of about 1.5 h seen in total sleep duration on weekends
appears to be a compensation for the sleep debt accumulated
during weekdays [9]. Similar patterns have been reported among
Chinese, Swedish, South African, Japanese and Canadian ado-
lescents [9,2224]. Several factors including biological (puber-
tal changes), environmental (parents and siblings schedule, same
bed etc), social (electronic media usage-internet, television) and
emotional (mood changes and academic stress) influence sleep
[9,25]. Sleep induction is a balance of circadian and homeostat-
ic drive. Older adolescents build up slower homeostatic sleep
pressure compared to younger ones due to biological sleep
phase shift as proposed by Carskadon et al. [5]. Present study
also shows that this homeostatic /circadian drive balance is max-
imally responsible for deciding adolescence bed time (Fig. 1).
But percentage of teenagers falling asleep primarily due to this
balance was less, as considerable number of teenagers were
involved in socializing [6% (n= 19) on weekdays increasing
to 15% (n= 48) on weekends] (Fig. 1). As reported by stu-
dents, parents were also less strict regarding time to bed
on weekends 18% (n= 57) compared to weekdays 24%
(n= 76). Delayed wakeup time and thus prolonged total
sleep time on weekends among girls which increased with
age (p= 0.0001) could be due to early onset of puberty
among them as suggested by Carskadon et al. [5].
Sleep Deprivation and Its Correlates Delayed bedtime and
early awakening on weekdays due to schools, leads to weekly
sleep loss which was not rectified even by sleeping for long
durations on weekends. Both preteens and teenagers were
sleep deprived, with teenagers having significantly more sleep
deprivation (p= 0.005). This may be either because of circa-
dian sleep delays or increased academic and social demand on
weekdays. A unique feature of Indian students is their high
dependency on supplemental coaching programs after school
hours, owing to the high value placed on professional courses
like Medicine and Engineering from early classes like seventh
standard onwards. The extra workload and time spent attend-
ing these classes further curtails their sleep. A study showed
that 63.9% of Chinese high school students attended extra
learning classes and it was considered as one of the reasons
for their sleep deprivation [9]. In the present study, 41.5% (n=
76) preteens and 49% (n= 156) teenagers reported taking an
educational help. Teenagers showed higher frequency of
phase delay behaviors and more eveningness on M/E scores.
Insufficient night sleep leads to sleep deprivation, increases
daytime sleepiness and napping [26]. Consequently, teenagers
were more tired, sleepier and probably as they failed to wake
up on time on weekdays, had poor attendance and academic
performance at schools (Table 4).
Academic Performance and Mood of Preteens and Teenagers
and Its Association with Their Sleep Pattern Academic perfor-
mance had a positive correlation with attendance, which was
significantly low if total sleep duration was less and/or bed-
time was delayed (Table 5). Also, depression was high if bed
times were delayed. Greater the total sleep duration on week-
days, better was the performance in English and also delayed
wake up time on weekend negatively affected performance
(Table 5). Thus irregular sleep routines on weekdays and
weekend had deleterious effect on attendance and perfor-
mance. Studies have shown association of poor performance
Table 5 Correlation of sleep pattern with academic performance, mood, and attendance among all the students (N=501)
Sleep pattern Time to bed
(WD) r(p)
Time to wake
up (WD) r(p)
Total sleep time
(WD) r(p)
Time to bed
(WE) r(p)
Time to wake
up (WE) r(p)
Tot al sl e ep tim e
(WE) r(p)
Va r i ab l e s
English marks 0.008
Science marks 0.011
S. studies marks 0.002
Maths marks 0.001
Depression score 0.130*
Attendance 0.089*
rpearsons correlation coefficient; pp-value. *pvalue <0.05 was considered significant and **p< 0.001 as highly significant
Indian J Pediatr
with short sleep duration while others have drawn attention
towards the association of short sleep duration with depression
in adolescents [4,2729]. Poor sleep is not only a symptom of
mood disturbance but is also a likely cause for it [30].
Strength and Limitations This is first study that tells the prev-
alence of sleep deprivation among adolescents of different
ages of a school of Delhi, India. It suggests us to examine
adolescents who are poor academically, for their sleep pattern
and mood. We should change our focus from effect i.e., poor
academic performance to the cause which may be their poor
sleep hygiene practices. Certain limitations are, as it was a
cross-sectional study, sleep diary records of sleep routines or
polysomnography were not included which could have given
us an objective measure for changes observed through preteen
to teenage. Puberty scales could not be included thus the as-
sociation of these sleepwake transitions with pubertal chang-
es was not seen. Also, the data was collected only over a
months duration (between OctoberNovember), thus the re-
sults could have been influenced by seasonal variations in
sleep patterns.
The study identifies 1213 y of age as an age of sleep phase
transition in Indian adolescents. With transition from pre-
teens to teenage, there was a rise in prevalence of sleep
deprivation, mood changes and poor attendance at school.
Sleep pattern did not have any direct impact on academic
performances but it did affect the mood, attendance and
alertness of adolescents. Shorter sleep duration can both be
a cause and effect of depression. Thus multiple factors with
a complex relationship along with sleep pattern might be
influencing academic performances and warrants further
Acknowledgements The authors thank the school administration and all
the students who participated in the study, which helped in smooth con-
duction of the survey. They also thank Dr. Shobha Das and Dr. Raj
Kapoor for their constant support and encouragement that led them to
the completion of the study. They would also like to acknowledge the
financial support provided by the Indian Sleep Disorder Association
(ISDA) for this study.
Contributions JCS and RS conceived the idea; JCS, RS and RenukaS
designed the study; RS, RenukaS, TS, JCS and TA contributed for acqui-
sition, analysis, or interpretation of data. RS, JCS and TA contributed in
analysis tools; RS and RenukaS drafted the paper and JCS, TS and TA
substantively revised the paper. All authors gave approval for the submit-
ted version. JCS will act as guarantor for this paper.
Compliance with Ethical Standards
Conflict of Interest None.
Source of Funding The authors would also like to acknowledge the
financial support provided by the Indian Sleep Disorder Association
(ISDA) for this study.
1. Carskadon MA, Wolfson AR, Acebo C, Tzischinsky O, Seifer R.
Adolescent sleep patterns, circadian timing, and sleepiness at a
transition to early school days. Sleep. 1998;21:87181.
2. John B. Sleep-patterns, sleep hygiene behaviors and parental mon-
itoring among Bahrain-based Indian adolescents. J Family Med
Prim Care. 2015;4:2327.
3. Brand S, Kirov R. Sleep and its importance in adolescence and in
common adolescent somatic and psychiatric conditions. Int J Gen
Med. 2011;4:42542.
4. Wolfson AR, Carskadon MA. Sleep schedules and daytime func-
tioning in adolescents. Child Dev. 1998;69:87587.
5. Carskadon MA, Vieira C, Acebo C. Association between puberty
and delayed phase preference. Sleep. 1993;16:25862.
6. Carskadon MA, Acebo C. Regulation of sleepiness in adolescents:
update, insights and speculation. Sleep. 2002;25:60614.
7. Carskadon MA. Patterns of sleep and sleepiness in adolescents.
Pediatrician. 1990;17:512.
8. Hansen MI, Schiff A, Zee PC, Dubocovich ML. The impact of
school daily schedule on adolescent sleep. Pediatrics. 2005;115:
9. Chen T, Wu Z, Shen Z, Zhang J, Shen X, Li S. Sleep duration in
Chinese adolescents: biological, environmental, and behavioral pre-
dictors. Sleep Med. 2014;15:134553.
10. Danner FW. Adolescent sleep and daytime functioning: a national
study. Sleep. 2000;23:A199.
11. Liu X, Buysse DJ, Gentzler AL, et al. Insomnia and hypersomnia
associated with depressive phenomenology and comorbidity in
childhood depression. Sleep. 2007;30:8390.
12. Kjeldsen JS, Hjorth MF, Andersen R,et al. Short sleep durationand
large variability in sleep duration are independently associated with
dietary risk factors for obesity in Danish school children. Int J Obes
(Lond.). 2014;38:329.
13. Sivertsen B, Harvey AG, Pallesen S, Hysing M. Mental health prob-
lems in adolescents with delayed sleep phase: results from a large
population-based study in Norway. J Sleep Res. 2015;24:118.
14. Lee YJ, Park J, Kim S, Cho SJ, Kim SJ. Academic performance
among adolescents with behaviorally induced insufficient sleep
syndrome. J Clin Sleep Med. 2015;11:618.
15. Yang CK, Kim JK, Patel SR, Lee JH. Age-related changes in sleep/
wake patterns among Korean teenagers. Pediatrics. 2005;115:2506.
16. Moore M, Meltzer LJ. The sleepy adolescent: causes and conse-
quences of sleepiness in teens. Paediatr Respir Rev. 2008;9:11421.
17. Acebo C, Carskadon MA. Influence of irregular sleep patterns on
waking behavior. In: Carskadon MA, editor. Adolescent sleep pat-
terns: biological, social, and psychological influences. Cambridge:
Cambridge University Press; 2002. p. 22035.
18. Ficca G, Conte F, De Padova V, Zilli I. Good and bad sleep in
childhood: a questionnaire survey amongst school children in
southern Italy. Sleep Disord. 2011;2011:825981.
19. Smith CS, Reilly C, Midkiff K. Evaluation of three circadian
rhythm questionnaires with suggestions for an improved measure
of morningness. J Appl Psychol. 1989;74:72838.
20. Kandel DB, Davies M. Epidemiology of depressive mood in
adolescents: an empirical study. Arch Gen Psychiatry.
21. Titova OE, Hogenkamp PS, Jacobsson JA, Feldman I, Schiöth HB,
Benedict C. Associations of self-reported sleep disturbance and
Indian J Pediatr
duration with academic failure in community-dwelling Swedish
adolescents: sleep and academic performance at school. Sleep
Med. 2015;16:8793.
22. Reid A, Maldonado CC, Baker FC. Sleep behavior of south African
adolescents. Sleep. 2002;25:4237.
23. Takemura T, Funaki K, Kanbayashi T, et al. Sleep habits of stu-
dents attending elementary schools, and junior and senior high
schools in Akita prefecture. Psychiatry Clin Neurosci. 2002;56:
24. Gibson ES, Powles AC, Thabane L, et al. BSleepiness^is serious in
adolescence: two surveys of 3235 Canadian students. BMC Public
Health. 2006;6:116.
25. Tikotzky L, Sadeh A. Sleep problems during adolescence: links
with daytime functioning. In: Latzer Y, Tzischinsky O, editors.
The dance of sleeping and eating in adolescents: normal and
pathological perspective. New York: Nova Science Publishers;
2012. p. 10927.
26. Noland H, Price JH, Dake J, Telljohann SK. Adolescents' sleep
behaviors and perceptions of sleep. J Sch Health. 2009;79:22430.
27. Curcio G, Ferrara M, De Gennaro L. Sleep loss, learning capacity
and academic performance. Sleep Med Rev. 2006;10:32337.
28. Fredriksen K, Rhodes J, Reddy R, Way N. Sleepless in Chicago:
tracking the effects of adolescent sleep loss during the middle
school years. Child Dev. 2004;75:8495.
29. NSF (2006). 2006 Sleep in America Poll. Available at: http://www.
August 2016.
30. Johnson EO, Roth T, Breslau N. The association of insomnia with
anxiety disorders and depression: exploration of the direction of
risk. J Psychiatr Res. 2006;40:700-8.
Indian J Pediatr
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Objective: To examine associations of self-reported sleep disturbance and short sleep duration with the risk for academic failure. Methods: A cohort of ~40,000 adolescents (age range: 12–19 years) who were attending high school grades 7, 9, and 2nd year of upper secondary school in the Swedish Uppsala County were invited to participate in the Life and Health Young Survey (conducted between 2005 and 2011 in Uppsala County, Sweden). In addition to the question how many subjects they failed during the school year (outcome variable), subsamples of adolescents also answered questions related to subjective sleep disturbance (n = 20,026) and habitual sleep duration (n = 4736) (exposure variables). Binary logistic regression analysis was utilized to explore if self-reported sleep disturbances and habitual short sleep duration (defined as less than 7–8 h sleep per night) increase the relative risk to fail subjects during the school year (controlled for possible confounders, e.g. body-mass-index). Results: Adolescents with self-reported sleep disturbances had an increased risk for academic failure (i.e., they failed at least one subject during the school year; OR: boys, 1.68; girls, 2.05, both P < 0.001), compared to adolescents without self-reported sleep disturbances. In addition, adolescents who reported short sleep duration on both working and weekend days were more likely to fail at least one subject at school than those who slept at least 7–8 h per night (OR: boys, 4.1; girls, 5.0, both P < 0.001). Conclusion: Our findings indicate that reports of sleep disturbance and short sleep duration are linked to academic failure in adolescents. Based on our data, causality cannot be established.
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Objective To examine sleep-duration-related risk factors from multidimensional domains among Chinese adolescents. Methods A random sample of 4801 adolescents aged 11–20 years participated in a cross-sectional survey. A self-reported questionnaire was used to collect information about adolescents' sleep behaviors and possible related factors from eight domains. Results In all, 51.0% and 9.8% of adolescents did not achieve optimal sleep duration (defined as <8.0 h per day) on weekdays and on weekends, respectively. According to multivariate logistic regression models, after adjusting for all possible confounders, 17 factors were associated with sleep duration <8 h. Specifically, 13 factors from five domains were linked to physical and psychosocial condition, environment, and behaviors. These factors were overweight/obesity, chronic pain, bedtime anxiety/excitement/depression, bed/room sharing, school starting time earlier than 07:00, cram school learning, more time spent on homework on weekdays, television viewing ≥2 h/day, physical activity <1 h/day, irregular bedtime, and shorter sleep duration of father. Conclusion Biological and psychosocial conditions, sleep environments, school schedules, daily activity and behaviors, and parents' sleep habits significantly affect adolescents' sleep duration, indicating that the existing chronic sleep loss in adolescents could be, at least partly, intervened by improving adolescents' physical and psychosocial conditions, by controlling visual screen exposure, by regulating school schedules, by improving sleep hygiene and daytime behaviors, and by changing parents' sleep habits.
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Despite its clinical importance, the issue of subjective sleep quality in children remains unexplored. Here we investigate, in school-aged children, the prevalence of bad sleep perception and its relationships with sleep habits and daytime functioning, to provide hints on its possible determinants. Subjective sleep perception, sleep habits, and daytime functioning were studied through a questionnaire survey in a sample of 482 children (6–12 yrs.). Being “bad sleeper” was reported by 6.9% of the sample. Compared to the “good sleepers”, these subjects displayed shorter sleep duration on schooldays, longer sleep latencies, and a more pronounced evening preference, beyond more frequent insufficient sleep. Though no differences emerged in sleepiness, bad sleepers showed higher impairments in daytime functioning, indicated by more frequent depressed mood and impulsivity. These distinctive features might be very important to precociously detect those children who are possibly more vulnerable to sleep disturbances and whose sleep-wake rhythms evolution should be paid particular attention thereafter. “The good people sleep much better at night than the bad people.Of course, the bad people enjoy the waking hours much more”Woody Allen
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Restoring sleep is strongly associated with a better physical, cognitive, and psychological well-being. By contrast, poor or disordered sleep is related to impairment of cognitive and psychological functioning and worsened physical health. These associations are well documented not only in adults but also in children and adolescents. Importantly, adolescence is hallmarked by dramatic maturational changes in sleep and its neurobiological regulation, hormonal status, and many psychosocial and physical processes. Thus, the role of sleep in mental and physical health during adolescence and in adolescent patients is complex. However, it has so far received little attention. This review first presents contemporary views about the complex neurobiology of sleep and its functions with important implications for adolescence. Second, existing complex relationships between common adolescent somatic/organic, sleep-related, and psychiatric disorders and certain sleep alterations are discussed. It is concluded that poor or altered sleep in adolescent patients may trigger and maintain many psychiatric and physical disorders or combinations of these conditions, which presumably hinder recovery and may cross into later stages of life. Therefore, timely diagnosis and management of sleep problems appear critical for growth and development in adolescent patients.
The present study investigated academic performance among adolescents with behaviorally induced insufficient sleep syndrome (BISS) and attempted to identify independent predictors of academic performance among BISS-related factors. A total of 51 students with BISS and 50 without BISS were recruited from high schools in South Korea based on self-reported weekday sleep durations, weekend oversleep, and the Epworth Sleepiness Scale (ESS). Participants reported their academic performance in the form of class quartile ranking. The Korean version of the Composite Scale (KtCS) for morningness/ eveningness, the Beck Depression Inventory (BDI) for depression, and the Barratt Impulsiveness Scale-II (BIS-II) for impulsivity were administered. Adolescents with BISS reported poorer academic performance than adolescents without BISS (p = 0.02). Adolescents with BISS also exhibited greater levels of eveningness (p < 0.001), depressive symptoms (p < 0.001), and impulsiveness (p < 0.01). Longer weekend oversleep predicted poorer academic performance among adolescents with BISS even after controlling for ESS, KtCS, BDI, and BIS-II (β = 0.42, p < 0.01). BISS among adolescents is associated with poor academic performance and that sleep debt, as represented by weekend oversleep, predicts poorer academic performance independent of depression, impulsiveness, weekday sleep duration, daytime sleepiness, and morningness/ eveningness among adolescents with BISS. © 2014 American Academy of Sleep Medicine.
The aim of the current study was to compare mental health problems, resilience and family characteristics in adolescents with and without delayed sleep phase (DSP) in a population-based sample. Data were taken from the youth@hordaland-survey, a large population-based study in Hordaland County in Norway conducted in 2012. In all, 9338 adolescents aged 16–19 years (53.5% girls) provided self-reported data on a wide range of instruments assessing mental health symptoms, including depression, anxiety, obsessive–compulsive behaviours, attention deficit hyperactive disorder (ADHD) symptoms, perfectionism, resilience and sleep. Measures of socioeconomic status were also included. Three hundred and six adolescents (prevalence 3.3%) were classified as having DSP [according to the International Classification of Sleep Disorders-2 (ICSD-2)] criteria. Adolescents with DSP reported higher levels of depression, anxiety and ADHD symptoms. Adolescents with DSP also exhibited significantly lower levels of resilience. The Cohen's d effect sizes ranged from small [obsessive–compulsive disorder (OCD): d = 0.15] to moderate (inattention: d = 0.71). In the fully adjusted model, the significant predictors of DSP included inattention [odds ratio (OR): 2.11], lack of personal structure (OR: 2.07), low (OR: 1.85) and high (OR: 1.91) paternal education, parents not living together (OR: 1.81), hyperactivity/inattention (OR: 1.71) and poorer family economy (OR: 1.59). In conclusion, the high symptom load across a range of mental health measures suggests that a broad and thorough clinical approach is warranted when adolescents present with DSP.
Background: Lack of sleep and increased consumption of energy-dense foods and sugar-sweetened beverages (SSBs) have all been suggested as factors contributing to the increased prevalence of overweight and obesity. Objective: To evaluate whether objectively measured sleep duration (average and day-to-day variability) as well as parent-reported sleep problems are independently associated with proposed dietary risk factors for overweight and obesity in 8-11-year-old children. Design: In this cross-sectional study, data on sleep duration and day-to-day variability in sleep duration were measured in 676 Danish, apparently healthy children by an objective measure (actigraphy) for 8 nights, and the Children's Sleep Habits Questionnaire (CSHQ) was filled out by the parents. Diet was recorded using a web-based food record for 7 consecutive days. Fasting blood samples were obtained for measurements of plasma leptin and ghrelin levels. Results: Sleep duration (h per night) was negatively associated with energy density (ED) of the diet (β = -0.32 kJ g(-1)), added sugar (β = -1.50 E%) and SSBs (β = -1.07 E%) (all P ≤ 0.003). Furthermore, variability in sleep duration (10-min per night) was positively associated with SSBs (β = 0.20 E%, P = 0.03), independent of sleep duration, and CSHQ score was positively associated with ED (β = 0.16 kJ g(-1), P = 0.04). All of these associations were independent of potential confounders (age, sex, pubertal status, height, weight, screen time, moderate-to-vigorous physical activity and parental education and ethnicity). Conclusion: Our study suggests that short sleep duration, high sleep duration variability and experiencing sleep problems are all associated with a poor, obesity-promoting diet in children.
Sleep duration affects the health of children and adolescents. Shorter sleep durations have been associated with poorer academic performance, unintentional injuries, and obesity in adolescents. This study extends our understanding of how adolescents perceive and deal with their sleep issues. General education classes were randomly selected from a convenience sample of three high schools in the Midwest. Three hundred eighty-four ninth- to twelfth-grade students (57%) completed a self-administered valid and reliable questionnaire on sleep behaviors and perceptions of sleep. Most respondents (91.9%) obtained inadequate sleep (<or= 9 hours) on most school nights of the week, with 10% reporting less than 6 hours of sleep each week night. The majority indicated that not getting enough sleep had the following effects on them: being more tired during the day (93.7%), having difficulty paying attention (83.6%), lower grades (60.8%), increase in stress (59.0%), and having difficulty getting along with others (57.7%). Some students reported engaging in harmful behaviors to help them sleep: taking sleeping pills (6.0%), smoking a cigarette to relax (5.7%), and drinking alcohol in the evening (2.9%). Students who received fewer hours of sleep were significantly more likely to report being stressed (p = .02) and were more likely to be overweight (p = .04). Inadequate sleep time may be contributing to adolescent health problems such as increased stress and obesity. Findings indicate a need for sleep hygiene education for adolescents and their parents. A long-term solution to chronic sleep deprivation among high school students could include delaying high school start times, such as was done successfully in the Minneapolis Public School District.