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Original Paper
Neuroepidemiology
Prevalence and Predictors of Restless Leg
Syndrome in Adolescents and Young Adults of
Bengaluru City, India: A Cross-Sectional Study
Shreyas Bellur
a Suraj Samuel Thota
a Jeffrey Pradeep Raj
b Tomy K. Kallarakal
c
Raghunandan Nadig
d
aSt. John’s Medical College, Bengaluru, India; bDepartment of Pharmacology, St. John’s Medical College
Hospital, Bengaluru, India; cSchool of Commerce, Finance and Accountancy, Christ University, Bengaluru, India;
dDepartment of Neurology, St. John’s Medical College Hospital, Bengaluru, India
Received: May 2, 2022
Accepted: May 31, 2022
Published online: June 7, 2022
Correspondence to:
Raghunandan Nadig, docnadig @ rediffmail.com
© 2022 S. Karger AG, Basel
Karger@karger.com
www.karger.com/ned
DOI: 10.1159/000525336
Keywords
Restless leg syndrome · Excessive daytime sleepiness ·
Pittsburgh Sleep Quality Index · Sleep · Epworth sleepiness
scale
Abstract
Introduction: Restless leg syndrome (RLS) is a sensorimotor
disease characterized by an urge to move the legs, often
caused by uncomfortable and unpleasant sensations in the
legs. It affects the quality of sleep which in turn affects scho-
lastic performance in children and predisposes them to car-
diovascular diseases in the long run. Hence, the primary aim
of this study was to assess the prevalence and predictors of
RLS, poor sleep quality, and excessive daytime sleepiness
(EDS). Methods: This was a cross-sectional observational
study conducted between September 2017 and March 2020
in Bengaluru, India, including all consenting PreUniversity
College, Degree College, and Higher Secondary school stu-
dents. After parental consent and assent (if applicable) was
obtained, a semi-structured standardized pilot-tested ques-
tionnaire consisting of the RLS diagnostic criteria, Pittsburgh
Sleep Quality Index (PSQI), Epworth sleepiness scale, and
questions on sleep hygiene was administered. The preva-
lence was expressed as proportions and 95% confidence in-
tervals (95% CI). Regression analysis was done to determine
the predictors. Results: The overall prevalence (95% CI; fre-
quency) of students with RLS, poor sleep quality, and EDS in
our study population was 8.36% (7.54, 9.24; n = 1,544/4,211),
36.67% (35.21, 38.14; n = 1,544/4,211), and 39.87% (38.39,
41.37; n = 1,679/4,211), respectively. PSQI and Epworth score
were the significant predictors of RLS. Age, Epworth score,
knowledge score, and the number of unacceptable sleep
habits were the significant predictors of sleep quality. Fe-
male gender, PSQI, RLS, knowledge score, and the number
of unacceptable sleep habits were the significant predictors
of EDS. Conclusions: The prevalence of RLS, those with poor
sleep quality and EDS among adolescents and young adults
was higher when compared to the historical data of general
population in the same city. © 2022 S. Karger AG, Basel
Introduction
Restless leg syndrome (RLS) is a type of sleep disorder
that is not very well recognized in clinical practice. RLS is
a sensorimotor disease that affects the quality of life. As
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DOI: 10.1159/000525336
per the International Restless Legs Syndrome Study
Group (IRLSSG) diagnostic criteria, RLS is characterized
by an urge to move the legs, often caused by uncomfort-
able and unpleasant sensations in the legs after having
ruled out other medical or behavioral causes. The symp-
toms usually begin or worsen during rest, particularly in
the evening, and are partially or totally relieved by move-
ment [1]. Globally, the prevalence of RLS is reported to
be anywhere between 3.9% and 15% [2], and in an Indian
urban population, Rangarajan et al. [3] have reported it
to be 2.1%.
RLS impairs the quality of sleep which is an important
entity for adequate health and is one of the least reported
sleep disorders that can affect the quality of sleep [4].
Chronic impaired sleep translates into deranged meta-
bolic parameters which predispose the person to cardio-
vascular diseases [5]. The possible mechanism underlying
the association between RLS and cardiovascular disease is
sympathetic hyperactivity due to insufficient inhibition
of sympathetic preganglionic neurons [6].
Because of this complex interplay between sleep and
cardiovascular function and limited data available, this
study was proposed to primarily estimate the prevalence
of RLS in adolescent and young adult age group. The sec-
ondary objectives were to assess their quality of sleep so
that early intervention can be made to curb poor sleep as
a risk factor for cardiovascular dysfunction; estimate the
prevalence of excessive daytime sleepiness (EDS); assess
the risk factors for RLS, sleep quality, and EDS. We also
aimed to describe the knowledge, attitude, and practices
of sleep hygiene and evaluate their knowledge with re-
gards to right sleep hygiene practices.
Materials and Methods
Ethics
The study was approved by the Institutional Ethics Committee
vide study reference number 57/2017. Written informed consent
was taken from one of the parents or the legal guardian, and writ-
ten informed assent was obtained from the students. The study was
conducted in accordance with the Declaration of Helsinki (For-
taleza, 2013) and the National Ethical Guidelines for Biomedical
and Health Research Involving Human Participants (Indian
Council of Medical Research, 2017).
Study Design and Eligibility Criteria
This was a cross-sectional observational study conducted dur-
ing a 2.5-year period from September 2017 to March 2020 in Ben-
galuru, India. All consenting Pre-University College, Degree Col-
lege, and Higher Secondary school (11th and 12th Grade) students
were enrolled in the study. Students who were absent on the day of
administering the questionnaire were excluded.
Sample Size Estimation
The prevalence of RLS among general population was assumed
to be 10% (p) based on the review by Ohayon et al. [2]. Using Co-
chran’s formula [n = Zα2 × p (100 − p)/d2] [7] for calculation of
sample size from a single proportion with 95% confidence and a
relative precision of 20% (d), the calculated sample size was 3,600.
However, to account for the clustering effect of students belonging
to the same class, a design effect (DE) was calculated using the for-
mula DE = 1 + ρ (cluster size 1) where cluster size was taken as 40
and ρ arbitrarily taken as 0.01. The DE thus calculated was 1.4, and
the new sample size taking into effect the clustering was 5,040. Ac-
counting for approximately 10% nonresponders, the sample size
was increased to 5,500.
Sampling Strategy
A multistage sampling strategy was used. Initially, institutions
were randomly chosen from a list obtained by the authors from the
State Government of Karnataka, and permission was sought from
the head of the institute to conduct the study. A cluster random
sampling was done to identify a few classrooms, and all students
in the selected classrooms were briefed about the procedure by the
institutional faculty.
Study Procedure
Parental consent forms were sent home through the students
before the proposed date of study assessment. A mutually conve-
nient day was chosen to meet the students in the selected class-
rooms, and the assent form was administered by the research team.
Once assent was obtained, a pilot-tested semi-structured standard-
ized questionnaire was administered to the students. Pilot testing
was done among 20 participants, and the questionnaire needed no
modification. The data from the pilot test were not included in the
analysis. The questionnaire comprised various sections including
basic demographic details; IRLSSG consensus diagnostic criteria;
Pittsburgh Sleep Quality index (PSQI); Epworth sleepiness scale
(ESS); knowledge, attitude, and practices questionnaire on sleep
hygiene. Those who fulfilled the diagnostic criteria for RLS were
re-evaluated by the study investigators to rule out other primary
conditions that may mimic RLS to avoid misdiagnosis.
The IRLSSG consensus diagnostic criteria [1] have a sensitivity
of 87.2% and a specificity of 94.4% to diagnose RLS. The PSQI is a
validated scale which has nineteen questions that ultimately give a
global PSQI score between zero and twenty-one. A score >5 has a
diagnostic sensitivity of 89.6% and a specificity of 86.5% in distin-
guishing good and poor sleepers [8]. The ESS is an eight-item scale
that measures EDS. An ESS score of ≥10 is considered a clinically
relevant EDS with a specificity of 79.3% and a positive predictive
value of 88.0% [9]. Both PSQI [10] and ESS [11] have been vali-
dated for use in India. The knowledge and practice questions were
ten in number each and were framed by the study team from the
standard sleep hygiene practices available in literature [12, 13]. Six
experts from the field of sleep medicine, neurology, epidemiology,
psychological medicine, pediatrics, and internal medicine re-
viewed the questionnaire for face and content validity.
Data Management
Data were collected through printed questionnaires and trans-
ferred to an electronic database using Microsoft Excel (Microsoft,
USA, 2016). Data were saved in password-protected computers
accessible only to researchers or researchers’ authorized study per-
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DOI: 10.1159/000525336
sonnel. Statistical analyses were performed with Statistical Package
for Social Sciences (SPSS) for Windows, Version 20.0 (IBM Corp.,
USA, 2011).
Statistical Analysis Plan
The socio-demographic characteristics were summarized us-
ing descriptive statistics such as median and interquartile range
(IQR). Normality was assessed using Kolmogorov-Smirnov test. A
knowledge score of ≤5 out of 10 was arbitrarily chosen as the cut-
off point to define participants with poor knowledge regarding
sleep hygiene. The prevalence was expressed in proportions and
95% confidence intervals (CI). The predictors of PSQI and EDS
were subject to univariate and multivariate analysis using linear
regression, whereas the predictors of RLS were subject to logistic
regression. Only those predictors that had a p value less than 0.2 in
the univariate analysis were subject to multivariate analysis. The
differences between male and female gender with regards to sleep
habits and knowledge regarding sleep hygiene were assessed using
χ2 test and odds ratio (OR). Statistical significance was set at p <
0.05 for all the analyses.
Results
Baseline Demographic Characteristics
The number of institutions that were approached was
13, out of which 5 institutions granted permission to con-
duct the study. In these 5 institutions, 5,145 students were
approached and 4,714 students had parental/legal guard-
ian consent for participation. Among the 4,714 students,
182 students were on leave on the day of data collection
and 321 pro formas were either incomplete or did not sign
the assent form. Thus, the final number analyzed was
N = 4,211. The median (IQR) age of the participants was
18 (17, 19) years, and the proportion of male and female
students was 54.55% (n = 2,293/4,211) and 45.45% (n =
1,918/4,211), respectively.
Prevalence of RLS, Poor Sleepers, and EDS
The overall prevalence (95% CI; frequency) of students
with RLS, poor sleepers, and EDS in our study population
was 8.36% (7.54, 9.24; n = 1,544/4,211), 36.67% (35.21,
38.14; n = 1,544/4,211), and 39.87% (38.39, 41.37; n =
1,679/4,211), respectively. The gender-wise prevalence is
summarized in Table1. There was no significant differ-
ence in the prevalence between the two genders for all
three conditions.
Predictors of RLS, Sleep Quality, and EDS
The details of the univariate and multivariate analysis
to identify the predictors of RLS are summarized in Ta-
Table 1. Prevalence of RLS, poor sleep quality, and EDS
Condition Overall prevalence (N = 4,211) Prevalence in men (n = 2,293) Prevalence in women
(n = 1,918)
Difference in prevalence
between genders
% 95% CI n% 95% CI N% 95% CI n p value OR 95% CI
RLS 8.36 7.54, 9.24 1,511 7.89 6.82, 9.07 181 8.92 7.68, 10.28 171 0.233 0.88 0.70, 1.09
Poor sleep quality 36.67 35.21, 38.14 1,544 36.50 34.53, 38.51 837 36.86 34.70, 39.07 707 0.810 1.02 0.90, 1.15
EDS 39.87 38.39, 41.37 1,679 39.21 37.20, 41.24 899 40.67 38.46, 42.90 780 0.335 1.06 0.94, 1.20
CI, confidence intervals; OR, odds ratio.
Table 2. Predictors of RLS
Predictor Univariate analysis Multivariate analysis
OR p value Adjusted OR 95% CI p value
Age 1.053 0.099 0.971 0.878 1.075
Gender* 0.876 0.233 Not included in the analysis
PSQI 1.620 <0.001 1.393 1.289, 1.507 <0.001
Epworth score 1.359 <0.001 1.201 1.142, 1.263 <0.001
Knowledge score 0.928 0.023 0.963 0.868, 1.069 0.481
Unacceptable sleep habits, n1.127 0.002 1.031 0.909, 1.168 0.637
Nagelkerke R2 = 0.291. PSQI, Pittsburgh Sleep Quality Index. * Female gender, absence of RLS considered as 0.
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ble2. PSQI and Epworth score were the significant pre-
dictors of RLS.
The details of the univariate and multivariate analysis
to identify the predictors of sleep quality are summarized
in Table3. Age, Epworth score, knowledge score, and the
number of unacceptable sleep habits were the significant
predictors of sleep quality.
The details of the univariate and multivariate analysis
to identify the predictors of EDS are summarized in Ta-
ble4. Female gender, PSQI, RLS, knowledge score, and
the number of unacceptable sleep habits were the signifi-
cant predictors of EDS.
Practices with Regards to Sleep Hygiene
Various practices regarding sleep hygiene that are
followed by the students in this study are tabulated in
Table5. On a weekday, the most common methods of
waking up in the morning were by using an alarm clock,
followed by parents waking up, whereas on a holiday,
the most common mode of walking up was by self, fol-
lowed by parents waking up. With regards to naps, n =
2,316/4,211 (55.0%) reported taking a nap at least once
on a weekday when compared to n = 2,646/4,211 (62.8%)
on a holiday. (χ2 = 53.4208; p < 0.00001) The median
(IQR) duration of naps on a weekday was 60 min (30,
100) and that on a weekend or holiday was 60 min (60,
120).
The comparisons between men and women on various
sleep hygiene-related habits are summarized in Table5.
Men tend to use bed more for activities other than sleep-
ing (OR [95% CI] = 1.188 [1.009, 1.399]) and stay awake
longer than usual when compared to women (OR [95%
CI] = 1.191 [1.029, 1.377]).
Knowledge Regarding Good Sleep Hygiene
The median (IQR) of knowledge score among all the
students was 6.00 (5.00, 7.00). It was the same for both
genders individually. The overall prevalence (95% CI;
frequency) of students with poor knowledge of sleep
hygiene practices (score < 5/10) was 12.94% (11.94,
13.99; n = 545/4,211). The prevalence (95% CI; frequen-
cy) of students with poor knowledge of sleep hygiene
practices among men and women was 12.08% (10.77,
13.48; n = 277/2,293) and 13.97% (12.45, 15.61; n =
Table 3. Predictors of sleep quality (PSQI)
Predictor Univariate analysis Multivariate analysis
B-coefficient p value B-coefficient 95% CI p value
Age 0.105 <0.001 0.059 0.026, 0.092 <0.001
Gender* −0.007 0.914 Not included in the analysis
Epworth score 0.284 <0.001 0.236 0.221, 0.251 <0.001
Restless legs syndrome* 2.982 <0.001 1.764 1.549, 1.980 <0.001
Knowledge score −0.007 0.934 Not included in the analysis
Unacceptable sleep habits, n0.251 <0.001 0.147 0.106, 0.188 <0.001
R2 = 0.317. * Female gender, absence of RLS considered as 0.
Table 4. Predictors of EDS
Predictor Univariate analysis Multivariate analysis
B-coefficient p value B-coefficient 95% CI p value
Age 0.134 <0.001 0.015 −0.046, 0.076 0.639
Gender* −0.308 0.014 −0.264 −0.474, −0.054 0.014
PSQI 0.929 <0.001 0.797 0.747, 0.847 <0.001
Restless legs syndrome* 4.969 <0.001 2.533 2.132, 2.934 <0.001
Knowledge score −0.214 <0.001 −0.107 −0.169, −0.044 0.001
Unacceptable sleep habits, n0.354 <0.001 0.111 0.035, 0.187 0.004
R2 = 0.295. PSQI, Pittsburgh Sleep Quality Index. * Female gender, absence of RLS considered as 0.
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268/1,918), respectively (p = 0.238; OR [95% CI] = 1.09
[0/94, 1.27]).
The correct responses to various questions assessing
the knowledge of participants in good sleep hygiene
practices are summarized in Table6. There was no sig-
nificant difference between men and women with re-
gards to the proportion of participants who made correct
responses for all questions except for two, namely, no
sleeping with lights on and no drinking coffee within 4 h
prior to sleep.
Discussion/Conclusion
We conducted a cross-sectional study among Pre-
University College, Degree College, and Higher Second-
ary school students of Bengaluru city, primarily to esti-
mate the prevalence of RLS and evaluate their quality of
sleep. We report that the overall prevalence of RLS was
8.36% (7.54% among male and 9.24% among female stu-
dents). The overall prevalence of students with poor sleep
quality in our study population was 36.67% (36.50%
among male and 36.86% among women students).
Table 6. Proportion of participants who made correct responses with regards to sleep hygiene practices
Habit Overall
(N = 4,211)
Men
(n = 2,293)
Women
(n = 1,918)
p value
n%n%n%
Watch TV/use laptop/read in bed prior to sleep 2,196 52.1 1,183 51.6 1,013 52.8 0.429
No drinking alcohol prior to bedtime 2,631 62.5 1,426 62.2 1,205 62.8 0.671
No smoke prior to bedtime or when awaken during the night 3,303 78.4 1,804 78.7 1,499 78.2 0.683
Afternoon nap is acceptable 1,809 43.0 995 43.4 814 42.4 0.534
Napping >60 min is unacceptable 2,788 66.2 1,506 65.7 1,282 66.8 0.427
No sleeping with night lights/room lights on 2,857 67.8 1,606 70.0 1,251 65.2 0.001*
Bedroom should be absolutely silent without TV or road noise 2,819 66.9 1,550 67.6 1,269 66.2 0.324
No sleeping longer into the morning than usual on holidays and weekends 1,126 26.7 588 25.6 538 28.1 0.079
No going to bed and trying to sleep even if not feeling sleepy 2,013 47.8 1,114 48.6 899 46.9 0.268
No drinking coffee or other caffeinated drink (within 4 h) prior to sleep 2,948 70.0 1,639 71.5 1,309 68.2 0.023#
* Odds ratio (95% confidence intervals) = 1.246 (1.095, 1.419). # Odds ratio (95% Confidence intervals) = 1.166 (1.022, 1.331).
Table 5. Sleep habits
Habit Overall (N = 4,211) Men (n = 2,293) Women (n = 1,918) p value
n%n%N%
Watch TV/use laptop/read in bed prior to sleep 3,519 83.6 1,941 84.6 1,578 82.3 0.038*
Drink alcohol prior to bedtime 120 2.8 73 3.2 47 2.5 0.154
Smoke prior to bedtime or when I awaken during the night 146 3.5 88 3.8 58 3.0 0.151
Eat a snack at bedtime 1,395 33.1 731 31.9 664 34.6 0.060
Sleep with night lights/room lights on 820 19.5 425 18.5 395 20.6 0.093
Bedroom is not completely silent while sleeping 1,124 26.7 616 26.9 508 26.5 0.782
Staying awake longer than usual the night before a holiday 3,279 77.9 1,817 79.2 1,462 76.2 0.019#
Sleep longer into the morning than usual on holidays and weekends$3,297 78.3 1,800 78.5 1,497 78.1 0.724
Exercise in the night (within 4 h) prior to sleep 824 19.6 459 20.0 365 19.0 0.421
Drink coffee or other caffeinated drink (within 4 h) prior to sleep 875 20.8 464 20.2 411 21.4 0.342
* Odds ratio (95% confidence intervals) = 1.188 (1.009, 1.399). #Odds ratio (95% Confidence intervals) = 1.191 (1.029, 1.377). $ Mode of awakening on a
weekday: alarm clock, n = 2,240/4,211 (53.2%); parents waking up n = 1,105/4,211 (26.2%); waking up by themselves, n = 822/4,211 (19.5%); and by other
miscellaneous methods, n = 44/4,211 (1.0). Mode of awakening on a weekend/holiday: by self, n = 2,974/4,211 (70.6%); parents waking up, n = 845/4,211
(20.1); using alarm clock, n = 326/4,211 (7.7%); and by other miscellaneous modes, n = 66/4,211 (1.6%).
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We report that the prevalence of RLS in adolescents is
higher than the prevalence in the general population of
Bengaluru city [3]. This could probably be due to the ex-
cessive emphasis on the 10th and 12th board exams and
the resultant psychological stress and anxiety [14]. Many
epidemiological studies have already proved the associa-
tion between RLS, stress, and mood disorders [15]. RLS
is now widely recognized as a disease of altered iron-do-
pamine interaction wherein brain iron deficiency leads to
dysfunction of cortico-striatal-thalamic-cortical circuits
leading to an enhanced arousal state [16]. Mood disorders
also affect the brain neurotransmitter levels and enhance
the arousal state in susceptible individuals [15]. We hy-
pothesize that the scenario would be no different in the
rest of the country as Bengaluru is a city with a population
comprising multiethnic and multicultural cosmopolitan
background wherein more than 50% is migrant popula-
tion [17] thereby giving us an insight about the entire
country. This hypothesis could further be corroborated
by the fact that the prevalence of RLS among adolescent
population from other developed countries such as the
USA [18] is less when compared to India probably due to
the differences in the educational system. We found that
a higher PSQI score (denoting poor sleep quality) and a
higher ESS score (denoting EDS) were significant predic-
tors of RLS. For every unit rise in the PSQI and ESS, the
odds of having RLS increased by approximately 40% and
20%, respectively.
We found that almost every third student had poor
quality sleep and a similar number had EDS. Sleep qual-
ity and EDS are interdependent. Poor sleep quality leads
to EDS and vice versa. These were once again much
higher than what was reported from the general popula-
tion of Bengaluru city. Panda et al. [19] have concluded
that the prevalence of people with poor sleep quality
(PSQI score <5) in Bengaluru was 6.2%. On a similar
note, Mathew et al. [20] have reported that the preva-
lence of EDS among 318 hospital workers in Bengaluru
city who have shift duties was 19.8%, which was still low-
er than the prevalence reported in our study. However,
this was similar to those reported from the same age
group in other countries [20]. For instance, Oginska et
al. [21] from Poland have shown that EDS is seen in 36%
of the adolescents. Thus, this increased prevalence in the
adolescents when compared to the adults cannot be at-
tributed merely to the exam stress but also due to other
factors such as utilization of screens, anxiety due to
bodily pubertal changes, loneliness due to physical dis-
tance from family, romantic interests, stronger peer re-
lationships, etc. [22]. This poor sleep quality not only
affects the scholastic performance but also has an impact
on the long-term health of an individual, especially non-
communicable diseases [21]. Therefore, as a method of
primordial prevention, importance to adequate and
good quality sleep must be stressed upon right from the
school days.
The predictors of poor sleep quality identified in our
study were age, ESS, presence of RLS, and increasing
number of unacceptable sleep habits. As age increases by
1 year, the mean PSQI score is predicted to increase by
0.059 units. Similarly, for every unit increase in ESS or the
number of unacceptable sleep habits, the mean PSQI
score is expected to increase by 0.236 and 0.147 units, re-
spectively. On a similar note, in the event that a person
has RLS, he/she is likely to have a mean PSQI higher by
1.764 units when compared to the ones who do not have
RLS. With regards to the predictors of EDS, gender, PSQI,
RLS, knowledge score, and number of unacceptable sleep
habits have turned out to be significant. Male students are
likely to have a mean ESS score less than the female stu-
dent by 0.264 units suggesting that female gender is at
higher risk of experiencing EDS and those with RLS are
likely to have a mean ESS score higher by 2.533 units
when compared to those without RLS. Likewise, for every
unit increase in PSQI or the number of unacceptable sleep
habits, the mean ESS score is predicted to increase by
0.797 and 0.111 units, respectively. On the flip side, for
every unit increase in knowledge score, there is an antici-
pated fall in the mean ESS by 0.107 units thereby proving
the fact that increasing awareness about good sleep prac-
tices would go a long way in preventing EDS. All of these
findings suggest that PSQI, ESS, number of unacceptable
sleep habits, and the knowledge regarding sleep hygiene
go hand in hand.
With regards to the various sleep habits assessed, men
in significant numbers over women were reported to have
been doing activities other than sleeping on the bed and
staying longer in the night. There was no difference be-
tween male and female students on other sleep habits.
However, we still see a large number of female students
indulge in the same bad sleep practices when compared
to the other ill practices of sleep. Additionally, a little
more than three-fourths of all students have reported
sleeping longer into the morning than usual on holidays
and weekends. These findings are similar to other such
studies reported in literature. Molla and Wondie [23]
have reported that the most common bad practice docu-
mented among medical students at a college in Ethiopia
was using their beds for activities other than for sleeping.
Likewise, Hershner, and Chervin [24] have recorded that
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DOI: 10.1159/000525336
sleeping longer over the weekend is a common practice
among school- and college-going students. Mathew et al.
[25] from Kerala too have reported that adolescent school-
going children sleep significantly longer duration in the
weekends than during the weekdays (9.03 ± 1.4 h vs. 7.4
± 1.2 h; p < 0.0001).
We report that the prevalence of students with poor
knowledge of sleep hygiene practices was approximately
13%. This was comparable to other similar studies, al-
though the tools used to measure knowledge and catego-
rize were different. For instance, Sivagnanam et al. [26]
have reported that the proportion of final-year medical
students at a college in Tamil Nadu with good knowledge
about sleep practices was 63.9%. However, our findings
were slightly better than what was reported by Raj and
Ramesh [27], who conducted a study among 206 tuber-
culosis patients in Bengaluru city wherein 33% were cat-
egorized as having poor knowledge. This is probably be-
cause of the disparity in the educational qualifications of
study participants between the two studies.
Our study has a few limitations. Even though the PQSI
is a validated scale, polysomnography is the gold standard
to assess the quality of sleep and this could not be per-
formed due to financial constraints. Objective measures
such as the multiple suggested immobilization test were
not used to confirm RLS due to logistical reasons [28].
The knowledge and practices were assessed only using a
standardized pilot-tested questionnaire and not using a
validated one. On the other hand, the strength of our
study is that it is one of the very few studies that have been
done exclusively among adolescents in India. As dis-
cussed earlier, yet another strength is that Bengaluru be-
ing a cosmopolitan city, our study possibly reflects the
situation across the whole of India with its diverse cul-
tures.
In conclusion, the prevalence of RLS among adoles-
cents and young adults was higher (8.4%) when com-
pared to the historical data of general population in the
same city as well as in the same age group in other coun-
tries. PQSI and ESS were significant predictors for those
at risk of RLS. Although those with poor knowledge of
sleep hygiene were very less, probably owing to their life-
style, adolescents and young adults who slept poorly
(36.67%) or during the day (38.87%) were higher. Given
the magnitude of this issue, in order to curb the effects of
sleep deprivation and prevent the development of cardio-
vascular disease, we recommend creating awareness
among school/college authorities on this topic and advo-
cate the need for routine screening of RLS, EDS, and sleep
quality among adolescents and young adults.
Acknowledgment
We would like to thank Mr. Jaisheel Rao, clinical research co-
ordinator, St. John’s Medical College, Bengaluru, for his support
in data collection and data entry.
Statement of Ethics
This study protocol was reviewed and approved by the Institu-
tional Ethics Committee, St. John’s Medical College, vide study
reference number 57/2017. Written informed consent was ob-
tained from one of the parents, and written informed assent was
obtained from the participating students if they were less than 18
years of age. Written informed consent was obtained from the stu-
dents who were 18 years and above.
Conflict of Interest Statement
The authors declare no conflicts of interest.
Funding Sources
The study was partially funded by the Research Society, St.
Johns Medical College and Hospital, vide Grant No. RS/1/1749/18.
Author Contributions
S.B.: concept, data acquisition, drafting manuscript, and final
approval of the manuscript. J.P.R.: concept and design, data acqui-
sition, statistical analysis and interpretation, drafting manuscript,
and drafting final report. S.T. and T.K.K.: data acquisition, critical
review of manuscript, and final approval of manuscript. R.N.: de-
sign, interpretation of data, critical review of manuscript, and final
approval of the manuscript. All authors agree to be accountable for
all aspects of the work in ensuring that questions related to the ac-
curacy or integrity of any part of the work are appropriately inves-
tigated and resolved.
Data Availability Statement
The data that support the findings of this study are available
from the corresponding author upon reasonable request.
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Bellur/Thota/Raj/Kallarakal/Nadig
Neuroepidemiology
8
DOI: 10.1159/000525336
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