Sleep Quality in a Nigerian Community: Prevalence of Poor Sleep Quality, Risk Factors and Health-Related Quality of Life

Abstract

Background:
A review of the literature shows there is a dearth of community-based studies that evaluated the prevalence of poor sleep quality and its psychosocial correlates among Nigerians. This study was conducted to determine the prevalence of poor sleep quality and its psychosocial correlates in a Nigerian community.

Methods:
The data presented here is an extract from the IlisanRemo Functional Bowel Disorder Project, a cross-sectional community-based study of 515 adults aged 18-70 years. The aspects of the research instrument relevant to this study include the sociodemographic data, Pittsburgh Sleep Quality Index (PSQI), Beck Anxiety and Depression Inventories, and Short Form 12, version 2 Health Survey (SF-12v2) questionnaire. An overall PSQI score of >5 was defined as poor sleep quality. Data analysis was conducted with appropriate statistical instruments. P-value < 0.05 was considered significant.

Results:
There were adequate data for statistical analysis for 505 participants. The participants' mean age was 32.73±12.93 years. A total of 212 (42.0%) participants had poor sleep quality. Poor sleep quality was associated with attainment of at least secondary schooleducation [AOR = 2.27 (95% CI, 1.17 - 4.41), p = 0.016], increased waist circumference [AOR = 1.03 (95% CI, 1.01 - 1.04), p < 0.001], coffee consumption [AOR = 2.57 (95% CI, 1.66 - 3.99), p < 0.001], anxiety [AOR = 1.06 (95% CI, 1.03 - 1.09), p < 0.001], and depression [AOR = 1.05 (95% CI, 1.03 - 1.08), p < 0.001]. Participants with poor sleep quality had poorer mean SF-12v2 sub-scales scores compared with those with good sleep quality in Bodily Pain, General Health, Vitality and Mental Health with statistical significance (p < 0.001).

Conclusion:
Poor sleep quality is common in our study population and needs to be holistically addressed.

Full text

West African Journal of Medicine Vol. 39, No. 7, July, 2022
RÉSUMÉ
CONTEXTE: Une revue de la littérature montre qu’il existe une
pénurie d’études communautaires qui ont évalué la prévalence de la
mauvaise qualité du sommeil et ses corrélats psychosociaux chez les
Nigérians. Cette étude a été menée pour déterminer la prévalence de
la mauvaise qualité du sommeil et ses corrélats psychosociaux dans
une communauté nigériane.
MÉTHODES: Les données présentées ici sont extraites du projet
Ilisan-Remo sur les troubles fonctionnels intestinaux, une étude
transversale communautaire portant sur 515 adultes âgés de 18 à
70 ans. Les aspects de l’instrument de recherche pertinents pour
cette étude comprennent les données sociodémographiques, l’indice
de qualité du sommeil de Pittsburgh (PSQI), les inventaires de l’anxiété
et de la dépression de Beck et le questionnaire Short Form 12, version
2 Health Survey (SF-12v2). Un score PSQI global e”5 a été défini
comme une mauvaise qualité du sommeil. L’analyse des données a
été effectuée avec des instruments statistiques appropriés. La va P <
0,05 était considérée comme significative.
RÉSULTATS: Il y avait des données adéquates po ur l’analyse
statistique pour 505 participants. L’âge moyen des participants était
de 32,73 ± 12,93 ans. Un total de 212 [4 2,0 % (IC à 95 % = 38 % –
46,0 %)] participants avaient une mauvaise qualité de sommeil. Le
Mauvaise qualité du sommeil était associé à l’obtention d’au moins
un diplôme d’études secondaires [AOR = 2,27 (IC à 95 %, 1,17 –
4,41), p = 0,016], à une augmentation du tour de taille [AOR = 1,03
(IC à 95 %, 1,01 – 1,04), p < 0,001], consommation de café [AOR =
2,57 (IC à 95 %, 1,66 – 3,99), p < 0,001], anxiété [AOR = 1,06 (IC à
95 %, 1,03 – 1,09), p < 0,001] et dépression [AOR = 1,05 (IC à 95 %,
1,03 – 1,08), p < 0,001]. Les participants avec Mauvaise qualité du
sommeil avaient des scores moyens inférieurs aux so us-échelles SF-
12v2 par rapport à ceux avec une bonne qualité de sommeil dans la
douleur corporelle, la santé générale, la vitalité et la santé mentale
avec une signification statistique (p< 0,001).
CONCLUSION: La mauvaise qualité du sommeil est courante dans
notre population d’étude et doit être traitée de manière holistique.
WAJM 2022; 39(7): 729–736.
Mots clés: Qualité du sommeil, Anxiété, Dépression, Qualité de vie,
Santé mentale.
WEST AFRICAN JOURNAL OF MEDICINE
Sleep Quality in a Nigerian Community: Prevalence of Poor Sleep Quality,
Risk Factors and Health-Related Quality of Life
La Qualité du Sommeil dans une Communauté Nigériane : Prévalence de la Mauvaise Qualité du
Sommeil, Facteurs de Risque et Qualité de Vie Liée à la Santé
1*A. C. Jemilohun, 2O. A. Fasesan, 3T. O. Ajiro, 4K. O. Akande, 5C. J. Elikwu, 6O. O. Adeleye
ABSTRACT
BACKGROUND: A review of the literatur e shows there is a dearth
of community-based studies that evaluated the prevalence of poor
sleep quality and its psychosocial correlates among Nigerians. This
study was conducted to determine the prevalence of poor sleep quality
and its psychosocial correlates in a Nigerian community.
METHODS: The data presented here is an extract from the Ilisan-
Remo Fun ctio na l Bo we l Di so rd er Pr oj ec t, a cro ss -s ec ti on al
community-based study of 515 adults aged 18–70 years. The aspects
of the research instrument relevant to this study include the socio-
demographic data, Pittsburgh Sleep Quality Index (PSQI), Beck
Anxiety and Depression Inventories, and Short Form 12, version 2
Health Survey (SF-12v2) questionnaire. An overall PSQI score of >5
was defined as poor sleep quality. Data analysis was conducted with
appropriate statistical instruments. P-value < 0.05 was considered
significant.
RESULTS: There were adequate data for statistical analysis for 505
participants. The participants’ mean age was 32.73±12.93 years. A
total of 212 (42.0%) participants had poor sleep quality. Poor sleep
quality was associated with attainment of at least secondary school
education [AOR = 2.27 (95% CI, 1.17 – 4.41), p = 0.016], increased
waist circumference [AOR = 1.03 (95% CI, 1.01 – 1.04), p < 0.001],
coffee consumption [AOR = 2.57 (95% CI, 1.66 – 3.99), p < 0.001],
anxiety [AOR = 1.06 (95% CI, 1.03 – 1.09), p < 0.001], and depression
[AOR = 1.05 (95% CI, 1.03 – 1.08), p < 0.001]. Participants with
poor sleep quality had poo rer mean SF-12v2 sub-scales scores
compared with those with good sleep quality in Bodily Pain, General
Health, Vitality and Mental Health with statistical significance (p <
0.001).
CONCLUSION: Poor sl ee p quality is common in our st udy
population and needs to be holistically addressed. WAJM 2022;
39(7): 729–736.
Keywords: Sleep quality, Anxiety, Depression, Quality of Life,
Mental health.
1Department of Medicine, Benjamin Carson Snr. Col le ge of He alth a nd Med ic al Sciences, Babcock Un iversity, Ilisan-R emo, Ogun
State, Nigeri a. 2Department of Medicine, Psychiatr y Unit, Ben jamin Carson Snr. Co llege of Health and Medi cal Science s, Babcock
Uni versity, Ilisan-R emo, Ogun State, Nige ri a. 3Depart ment of Medicine , Babcock University Teaching Hos pital, Ilis an Remo , Ogun
State, Nigeria. 4De pa rtment of Me di ci ne, College of Medicine/University Col lege Hospi tal, Ibad an, Oy o Sate, Niger ia .
5Depar tment of Medi cal Micr obiolo gy, Benjamin Car so n Snr. College of Health and Me dica l Sciences, Babcock Univ er sity, Ilisan-
Remo, Ogun State, Nigeria. 6Department of Medicine, Olabisi Onab anjo University Teaching Hos pital, Sagamu, Ogun State, Nigeria.
*Corr esp ond en ce: Dr. A. C. Jemilo hun, Depar tment of Internal Medi cin e, Benja min C arson Snr. College of Hea lth and Medical Scien ces ,
Bab cock Univer sity, Ilisa n-Remo, Ogun State, Nigeri a. Email: chris lohu n20 10@ hot mail.com
Abbr eviations: PSQI, Pittsburgh Sle ep Qua lity Index.

West African Journal of Medicine Vol. 39, No. 7, July, 2022
A. C. Jemilohun and Associates Sleep Quality in a Nigerian Community
730
INTRODUCTION
Sleep, a necessity for survival, is a
state of unaware ness of the external
environment which is characterized by the
revitalization of the body and conserva-
tion of energy.1 The proper maintenance
of ca r dio vas c ul a r and met abol ic
homeostasis, along with the process of
committing information to memory, occur
in the context of proper sleep.2–4
Sleep quality is a widely used but
lo o sel y de fin ed t e rm. It h as b e en
previously described as how well an
individual is satisfied with his sleep
experience, which encompasses the stage
of initiation and maintenance, and feeling
on waking up from sleep.5 However,
unlik e sleep qua nti ty th at ca n b e
objectively assessed, subjective feed-
back on certain sleep parameters is the
only available modality to describe the
quality of sleep.6 The usage of standar-
dize d asses smen t to ols such as the
Pittsburgh Sleep Quality Index (PSQI)
with a multi-item list provides a robust
an d pra cti cal a sse ssm ent o f sl eep
quality.7
Poor sleep quality (PSQ), which is
the principal feature of sleep disorders,6
is a problem that currently affe cts a
si gni fic ant num ber of th e wo r ld
population cutting across gender, race,
age, social status and geograp hi cal
location.8 A multinational study showed
the burden of PSQ to be 17% in the
developing countries as against 20% in
the developed world.8 Older people have
been shown to have a higher prevalence
of poor sleep compared to the younger
age-groups.9 About 22.8% of women
have trouble sleeping in comparison to
14% of men.10
Factors implicated in the growing
burden of impaired sleep quality include
smoki ng, p oor ex e rci se, f a ti g ue ,
depression, anxiety, old age, female
gender a nd co mor bid conditions.11–14
Also, it has been shown that chronic PSQ
leads to cardiovascular disease, mental
he alt h p r obl e ms , unpro d uct ivi ty,
impaired cognition and motor vehicle
accident.15,16
A review of the literature shows that
several studies to determine sleep quality
among various population groups in
Ni geri a have be en cond uct ed. 1 7– 24
However, the majority of these studies
were conducted among patients with a
particular disease condition or a small
segment of the general populace. There
is paucity of community-based data on
sleep quality and its association with
quality of life in Nigeria, in particular, and
sub-Saharan Africa in general. Given that
find ing s of st ud ies co nd uct ed in a
sp e cific s ett i ng a re us ual ly no t
generalizable to the whole community
due to default selection bias, the present
study was conducted to determine the
prevalence of PSQ, its risk factors and
association with the quality of life of the
people in a Nigerian community.
METHODOLOGY
Study Design
Thi s wa s a cro s s- s ec tion al
community-based study. It is a secondary
analysis of the relevant aspects of the
Ilisan-Remo Functional Bowel Disorder
Projec t data. The study protocol has
been described in detail and published
elsewhere.25
Study Population and Sampling
The study population consisted of
a cohort of adults aged 18 to 70 years
living in Ilisan-Remo, a sub-urban town
in Ogun State, Southwest Nigeria. The
community hosts the Babcock University
and the Babcock University Teaching
Hospital. The town is centrally located
between Ibadan and Lagos and has a
population of about 10,000 people.26,27 The
population comprises a mixture of well-
educated civil servants and Babcock
University/Babcock University Teaching
Ho spit al st aff w ho re sid e in the
community on one hand, and the low
cadre workers, petty traders, artisans and
subsistent farmers on the other hand.
We w ere u nab le to f ind a ny
community-based study on sleep quality
in Nigeria whose prevalence could be
used to determine the sample size. Using
50% proportio n and the Leslie Kish
formula (n = Z2pq/d2, at 95% confidence
interval, p = proportion, q = 1.0–p, normal
deviat e Z = 1.96 and d = 0. 05), the
minimum sample size required was 384.
Adjusting for missing or incomplete data
entry with an expected response rate of
90%, the sample size required for the
study was 427.
There were 51 major streets in the
community from which 10 streets were
selected randomly by ballot, initially. Two
ad dit ional stre ets were select ed to
complete the sample size. Adults living
in the households on each of the selected
streets who consented to participate in
the study we re inte rviewe d by well-
trained res ea rc h assistants until the
sample was completed. The research
instrument was translated to Yoruba
language for the sake of participants who
did not understand English language.
The data collection took about 8 weeks,
from 2nd February to 29th March 2019. A
total of 515 participants were recruited
for the study.
Survey Instrument
The relevant aspects of the research
instrument regarding this study comprise
the de mog raphi c i nformat ion (age,
gender, level of education and marital
st atu s), li fes tyl e fac tors (c iga ret te
smoking, alcohol consumption, coffee
intake and regularity of physical exercise);
waist circumference; the Pittsburgh Sleep
Quality Index (PSQI) for assessing sleep
quality, the Beck Anxiety and Depression
Inventories for assessing anxiety and
depressio n, and the Short Form 12,
version 2 Hea lth Survey ( SF -1 2v2)
questionnaire for the assessme nt of
Health-Related Quality of Life (HRQoL).
Assessment of Sleep Quality
Sleep quality was assessed with the
PSQI. The PSQI is a self-rated question-
naire used to measure the quality and
patterns of sleep in adults.7 It differen-
tiates “poor” from “good” sleep quality.
It was designed by Buysse, et al in 1989.
It has nineteen individual items which
ge ner a te sev en co mponent sc ore s:
subjective sleep quality, sleep latency,
sleep duration, habitual sleep efficiency,
sleep di st ur bance s, use of sl ee ping
medications, and daytime dysfunction
over the last month.7 Each of the seven
components is weighted on a scale of
0–3. The seven component scores are
summed to a global score which ranges
from 0–21. The higher the score the worse
the sleep quality. Generally, an overall
score of >5 indicates PSQ.7
Reg ardin g the 7 c ompon ents of
sleep qualit y, the par ti cipants were

West African Journal of Medicine Vol. 39, No. 7, July, 2022
A. C. Jemilohun and Associates Sleep Quality in a Nigerian Community
731
categorized into those with problem and
those without problem based on their
sc o res or res pons e. T he p rob l ems
included short sleep duration (<7 hours
of actual sleep), sleep latency problem
(>1), sleep disturbance (>1), poor sleep
efficiency (<85%), daytime dysfunction
(>1), bad subjective sleep quality (> fairly
bad) and sleep medication use (at least
once in the past month).
Assessment of Anxiety
Anxiety symptoms were assessed
in the participants with the Beck Anxiety
Inventory (BAI). The BAI was designed
by Beck, et al in 1988 as a screening tool
for anxiety.28 It is a valid and reliable29–32
21-item self-report questionnaire with
st ate men ts d e scr ipti ve o f anxiet y
symptoms experienced by the subjects
during the last month of their lives, rated
on a scale of 0 – 3. The 21 items’ scores
are added up to a global score which
ranges from 0 to 63. It is also graded into
low anxiety (0–21), moderate anxiety
(22–35) and severe anxiety (36 – 63).
Assessment of Depression
Symptoms of depress io n in the
participants were assessed with the Beck
Depression Inventory (BDI). The BDI was
developed in 1961 by Beck, et al as a
scree ning too l for depr essive symp-
toms.33 It also measures the severity of
the symptoms. It is a 21-item self-report
questionnaire with statements descrip-
tive of depressive symptoms experienced
by the subjects during the past 2 weeks
of their lives, rated on a scale of 0–3. The
21-items’ scores are added up to a global
score which ranges from 0–63 . The
inventory has been revised twice since
its creation: the original version (BDI)
was published in 1961; the first revision
(BDI- 1A) was published in 1978; and the
second revision (BDI-II) was published
in 1996. The BDI is a valid and reliable
instrument which has been used widely
by b oth res earcher s an d he al thcare
professionals in a variety of settings,
including Nigeria.34–39 It is graded into
minimal dep res sion ( 0–13 ) , mil d
depression (14–19), moderate depression
(20–28), and severe depression (29–63).
The BSI-II was used in the conduct of
this study.
Assessment of Health-related Quality of
Life
Participants’ HRQoL was assessed
with SF-12v2. The SF-12v2 is a generic
HRQoL instrument designed to measure
th e Physic al Compon ent Summar y
(PCS12 ) and the Mental Component
Summary (MCS12) of subjects.40,41 It also
measures the subject’s profile across 8
subscales: Physical Functioning (PF),
Role Physical (RP), Bodily Pain (BP)
General Health (GH), Vitality (VT), Social
Functioning (SF), Role Emotional (RE),
Mental Health (ME). The components are
scored on a scale of 0 to 100 with a mean
of 50 and a standard deviation of 10. The
higher the score, the better the health
quality. The SF-36 family of instruments
has been proven to be a valid and reliable
measure of quality of life among several
cultures.42
Statistical Analysis
Data analysis was conducted with
the IB M- Statistical Package for Social
Sciences (SPSS), version 22. Summary
statistics for continuous variables were
mean and range. Means comparison was
conducted with the Independent Student
t-te st whe re a ppr opr iat e. Summar y
st ati sti c s for ca teg oric al var iab l es
included frequency and percentage. The
unadjusted odds ratios (OR) of the risk
facto rs of po or sl eep qual ity wer e
calculated by univariate analysis. Binary
lo gis tic regres sio n a nal ysi s wa s
conducte d to eliminate the effect o f
potential confounders on the risk factors
that were noted to be significant during
the univariate analysi s to obtain the
adjusted odds ratios (AOR). Only the risk
factors that were significant during the
univariate analysis were included in the
fina l mod el. Th e cut -off va lue for
statistical significance was p-value < 0.05.
Ethical Consideration
Ethical approval was obtained from
the Ethics Review Board of Babcock
University, Ilisan-Remo (BUHREC044/
19). Writt en informed con se nt was
obtained from all the participants. Strict
confidentiality was maintained through-
out the conduct of the research.
RESULTS
A t o tal o f 5 15 su bjec t s were
interviewed but 10 (1.9%) of them were
excluded from the data analysis due to
inadequate information supply. Among
the remaini ng 5 05 partic ipants, 212
(42.0%) had PSQ while the remaining had
good sleep quality (GSQ) [Table 1]. The
participants’ mean age was 32.73 ± 12.93
ye ars . The re wa s no s tati stical ly
significant difference between the mean
age of the participants with PSQ and
those with GSQ. Participants who were
in their third decade of life were the most
represented [210 (41.6%)] while those in
th eir fif th d e cad e we re t he l e ast
represented [50 (9.95%)]. There was a
significant difference in age distribution
between the subjects with PSQ and those
with GSQ (p = 0.048) with 43.2% having
PSQ compared with 56.8% with GSQ
among those who were 21 to 30 years
old. T here were more females [260
(51.5%)] than males [245 (48.5%)] among
th e par tici pan ts bu t th e re was no
signifi cant diff er en ce in the gend er
distribution between PSQ and GSQ.
The majority of the participants had
at least secondary school education [444
(88.7%)] while the remaining had primary
or no formal education [57 (11.3%)] [Table
1]. The educational attainment difference
between PSQ and GSQ was significant
(p = 0.007) with 34.9% having PSQ
compared with 42.3% with GSQ among
pa rtici pants wit h se conda ry scho ol
education. Regarding the marital status
of the participants, the single category
was the most represented [269 (53.3%)]
while the widowed category was the least
represented [5 (1.0%)]. The marital status
deference between PSQ and GSQ was
also significant (p = 0.035) with 50.0%
having PSQ compared with 55.6% with
GSQ among participants who were single.
A minority of the pa rti cip ants
smoked cigarettes [50 (9.9%)] without a
significant difference between PSQ and
GSQ [Table 1]. This was also true for
alcohol consumption [139 (27.5%)].
Ho wev er, ther e wer e 141 (27. 0%)
participants who consumed coffee and
th ere wa s a s ign ifi can t di ffe renc e
between PSQ and QSP with 39.2% of
th ose with PSQ co nsu ming cof fee
compared with 19.8% of participants with
GSQ consuming coffee (p <0.001).
The majority of the participants [419
(83.0%)] did not exercise regularly and
there was no s igni ficant di ff erence

West African Journal of Medicine Vol. 39, No. 7, July, 2022
A. C. Jemilohun and Associates Sleep Quality in a Nigerian Community
732
be t we en PS Q and GSQ. Ho we ver,
participants with PSQ had a higher mean
waist circumference than the participants
with GSQ (84.48 ± 17.32 vs 80.28 ± 12.03,
p = 0.003).
Re gar d ing the p syc hol ogic al
factors, participants with PSQ had a
higher mean anxiety score than those
with GSQ (11.59 ± 8.84 vs 6.35 ± 6.94, p
<0.001) [Table 1]. In the same token,
participants with PSQ had higher mean
depression scores than those with GSQ
(p < 0.001).
Within the month preceding the
study, 350 (69.3%) of the participants
went to bed between 8:00 pm and 10.00
pm, followed by 115 (22.8%) who went to
bed between 10:00 pm and 12:00 midnight
while the others reclined at other times.
The majority of the participants [338
(66.9%)] woke up between 4:00 am and
6:00 am, followed by 113 (22.3%) who
woke up between 6:00 am and 7:00 am
while the others woke up at other times.
The mean night sleep duration was 7.2 ±
1.9 hours while the average sleep latency
was 38.1 ± 53.2 minutes.
The char acteristics of the seven
components of sleep quality evaluated
in the study are highlighted in Table 2. A
total of 275 (54.5%) participants had <7
hours of night sleep (poor sleepers) while
346 (68.5%) of the participants had sleep
latency problem. The majority of the
participants [421 (83.4%)] had sleep
disturbance while 154 (30 .5 %) had
daytime dysfunction within the period
under consideration. Again, 138 (27.3%)
participants reported that they had < 85%
sleep efficiency while 28 (5.6%) reported
that their subjective sleep quality was
ba d . Co ncer nin g the use o f sl eep
medication, 100 (19.8%) reported that
they used such medications within the
past month.
On univariate analysis, PSQ was
positively associated with attainment of
at least secondary education [OR = 1.99
(95% CI, 1.09 – 3.66), p = 0.026], increased
waist circumference [OR = 1.02 (95% CI,
1.00–1.03), p = 0.002], coffee consumption
[OR = 2.61 (95% CI, 1.75 – 3.88), p < 0.001],
anxiety [OR = 1.09 (95% CI, 1.06–1.12), p
<0.001] and depression [OR = 1.07 (95%
CI, 1.05–1.09), p < 0.001] [Table 2]. After
adjustment for potential confounders was
made with multivariate analysis, all the
factors that had positive association with
PSQ initially retained the association:
at tainme nt of a t l east se cond ary
education [AOR = 2.27 (95% CI, 1.17–
4. 41) , p = 0. 016 ], in cre ase d wai st
circumference [AOR = 1.03 (95% CI, 1.01–
1.04), p < 0.001], coffee consumption
[AOR = 2.57 (95% CI, 1.66 – 3.99), p <
0.001], anxiety [AOR = 1.06 (95% CI, 1.03
– 1.09), p < 0.001], and depression [AOR
= 1.05 (95% CI, 1.03 – 1.08), p <0.001].
Table 1: Demographic and psychosocial characteristics of participants (n = 505)
Variables Total (n) PSQ (n, %) GSQ (n, %) p-value
Age in years [Mean ±SD] 32.73±12.93 33.73±13.92 32.00 ±12.13 0.148
Age group in years [n (%)] 0.048
< 20 79 32 (40.5) 47 (59.5)
21 – 30 210 92 (43.8) 118 (56.2)
31 – 40 100 69 (69.0) 31 (31.0)
41 – 50 50 21 (42.0) 29 (58.0)
> 51 66 36 (54.6) 30 (45.5)
Gender 0.267
Male 245 109 (51.4) 136 (45.4)
Female 260 103 (48.6) 157 (53.6)
Education [n (%)] 0.007
Nil 17 3 (1.4) 14 (4.8)
Primary 40 13 (6.1) 27 (9.2)
Secondary 196 74 (34.9) 124 (42.3)
Tertiary 248 122 (57.5) 128 (43.7)
Marital Status [n (%)] 0.035
Married 211 93 (43.9) 118 (40.3)
Single 269 106 (50.0) 163 (55.6)
Separated 10 5 (2.4) 5 (1.7)
Divorced 10 6 (2.8) 4 (1.4)
Widowed 5 2 (0.9) 3 (1.0)
Cigarette Smoking [n (%)] 0.765
No 455 192 (90.6) 263 (89.8)
Yes 50 20 (9.4) 30 (10.2)
Alcohol Intake [n (%)] 0.123
No 366 146 (68.9) 220 (75.1)
Yes 139 66 (31.1) 73 (24.9)
Coffee Intake [n (%)] <0.001
No 364 129 (60.8) 235 (80.2)
Yes 141 83 (39.2) 58 (19.8)
Physical Exercise 0.240
No or < once a week 419 171 (80.7) 248 (84.6)
> once a week 86 41 (19.3) 45 (15.4)
Waist Circumference 82.04±14.62 84.48±17.32 80.28±12.03 0.003
BAI [Mean ± SD] 8.55±8.21 11.59±8.84 6.35±6.94 <0.001
Anxiety Level [n (%)] <0.001
Low (0 – 21) 457 180 (84.9) 277 (94.5)
Moderate (22 -35) 45 30 (14.2) 15 (5.1)
High (> 36) 3 2 (0.9) 1 (0.3)
BDI-II [Mean ± SD] 8.34±9.57 11.67±11.06 5.9±7.47 <0.001
Depression Level [n (%)] <0.001
Minimal (0 – 13) 392 138 (65.1) 254 (86.7)
Mild (14 – 19) 42 21 (9.9) 21 (7.1)
Moderate (20 – 28) 42 30 (14.2) 12 (4.1)
Severe (29 – 63) 29 23 (10.8) 17 (2.0)
Total [n (%)] 505 212 (42.0) 293 (58.0)
PSQ, Poor sleep quality; GSQ, Good sleep quality; BAI, Beck Anxiety Inventory; BDI, Beck
Depression Inventory; SD, Standard deviation.

West African Journal of Medicine Vol. 39, No. 7, July, 2022
A. C. Jemilohun and Associates Sleep Quality in a Nigerian Community
733
The means of SF-12v2 subscales
scores for participants with PSQ were
compared with those with GSQ [Table 4].
The mean scores of the subscales were
lower in subjects with PSQ than those
with GSQ except for Physical Functioning
and Social Functioning. The relationship
was statistically significant (p < 0.001) in
Bodily Pain, General Health, Vitality and
Me nt al Heal th . The mea n Physica l
Component Summary (PCS) and Mental
Health Summary (MCS) scores were also
less in participants with PSQ than in those
with GS Q. MCS wa s sta tis t ic a lly
significant (p < 0.001) while PCS was near
significant (p = 0.052).
DISCUSSION
Although sleep quality has been
studied in various population groups in
Nigeria,17–24 this study appears to be the
fir st community- ba sed sleep qual ity
study in the country. The 42% prevalence
of participants who had PSQ in the
present study is similar to the prevalence
of 38.2% obtained in a Spanish adult
popu la ti on.43 Two popula tion-bas ed
studies with a similar age distribution
from Ethiopia12 and Chin a44 s howed
divergent prevalence rates of 64.5% and
8. 3% res pec tiv e ly, t hou gh o t her
population-based studies from China
amo ng the middle-aged and elderly
Table 3: Unadjusted and Adjusted Odds Ratios of Risk Factors for PSQ (n =505)
Variable Total PSQ (n = 212) GSQ (n = 293) UOR (90% CI) p-value AOR (90% CI) p-value
Age [Mean ± SD] 32.73±12.93 33.73±13.92 32.00 ±12.13 1.01 (1.0 – 1.02) 0.140
Gender [n (%)] 0.268
Male 245 109 (44.5) 136 (55.5) 1(Reference)
Female 260 103 (39.6) 157 (60.4) 0.82 (0.58–1.17)
Level of Education [n (%)] 0.026 0.016
Nil/Primary 57 (11.3) 16 (28.1) 41 (71.9) 1 (Reference) 1 (Reference)
Secondary/Tertiary 448 (88.7) 196(43.8) 252 (56.3) 1.99 (1.09 – 3.66) 2.27 (1.17– 4.41)
Waist circumference
[Mean ±SD] 82.04±14.62 84.48±17.32 80.28±12.03 1.02 (1.00 – 1.03) 0.002 1.03 (1.01 – 1.04) < 0.001
Coffee intake [n (%)] <0.001 < 0.001
No 364 129 (35.4) 235 (64.6) 1 (Reference) 1 (Reference)
Yes 141 83 (58.9) 58 (41.1) 2.61 (1.75 – 3.88) 2.57 (1.66 – 3.99)
Marital Status 0.345
Married 211 93 (44.1) 118 (55.9) 1 (Reference)
Single 269 106 (39.4) 163 (60.6) 0.83(0.57 – 1.19) 0.303
D/W/S* 25 13 (52.0) 12 (48.0) 1.38 (0.60 – 3.15) 0.453
Anxiety [Mean ± SD] 8.55±8.21 11.59±8.84 6.35±6.94 1.09 (1.06 – 1.12) <0.0001 1.06 (1.03 – 1.09) < 0.001
Depression [Mean ± SD] 8.34±9.57 11.67±11.06 5.9±7.47 1.07 (1.05 – 1.09) < 0.0001 1.05 (1.03 – 1.08) < 0.001
PSQ, Poor sleep quality; GSQ, Good sleep quality; SD, Standard deviation; UOR, Unadjusted odds ratio; AOR, Adjusted odds ratio;
CI, Confidence interval; *D/W/S = Divorced/Widowed/Separated.
Table 2: Components of Sleep Quality and Corresponding Score among Participants
(n = 505)
Variables Values Frequency (%)
Sleep duration (hours) >7 226 (44.8)
6 – 7 113 (22.4)
5 – 6 121 (24.0)
<5 45 (8.9)
Sleep latency 0 152 (31.5)
1 231 (45.7)
2 100 (19.8)
3 15 (3.0)
Daytime dysfunction 0 351 (69.5)
1 119 (23.6)
2 30 (5.9)
3 5 (1.0)
Sleep efficiency >85% 367 (72.7)
75 – 84% 49 (9.7)
65 – 75% 26 (5.1)
<65% 63 (12.5)
Subjective sleep quality Very good 338 (66.9)
Fairly good 139 (27.5)
Fairly bad 17 (3.4)
Very bad 11 (2.2)
Sleep disturbance 0 84 (16.6)
1 362 (71.7)
2 57 (11.3)
3 2 (0.4)
Use of sleep medications Not during the past month 405 (80.2)
Less than once a week 64 (12.7)
Once or twice a week 24 (4.8)
Three or more times a week 12 (2.4)

West African Journal of Medicine Vol. 39, No. 7, July, 2022
showed higher prevalence rates (27.7%–
33.8%) .11 ,45 The reason for this wide
prevalence disparity is not immediately
known but a variety of reasons may be
responsible. These include differences in
the sociodemographic characteristics
and cultural habits of the participants,
and the locations of the studies, whether
rural or urban.
Coffee, which is a rich source of
ca ffe ine , is a well -kn own psyc ho-
st imula nt use d by ma n y peo ple to
ma int ain al e rtn ess , a ttentio n a nd
concentratio n. Ho wever, its negative
impact on sleep quality in regular drinkers
has been previously described in the
literature.46,47 This was further corro-
bo rat ed by our st ud y in whic h the
prevalence of PSQ was much higher in
coffee-drinkers than non-coffee drinkers
(58.9% vs 39.4%, p < 0.001). A systematic
review of randomized controlled trials
and epidemiological studies conducted
by Cla rk and Lan dolt47 sho wed that
consump ti on of caffeine co nt ai ni ng
subst ances pr olo ngs slee p latenc y,
decreases sleep efficiency and total sleep
ti me , a nd wo rsens perc eiv ed sl eep
quality. Human and animal studies have
established a role for adenosine in sleep
and aro us al regulation.48 Adeno sine
receptor agonists promote sleep. It is
be l iev ed t hat caf fe i ne e nha nce s
wakefulness by antagonizing adenosine
A1 and A2A receptors in the brain.49
In the present study, a higher level
of educational attainment was associated
with PSQ . The a ss oc ia tion between
educational attainment with PSQ has not
be e n con sis ten t. W h ile P SQ wa s
positively associated with a low-level
of educ a tio nal atta inment in some
st udi es, 50 –5 2 it sho wed a p osi tiv e
association with a higher educational
attainment in a study.53 In another study,
it had no association with the level of
education.54 It is not immediately clear
why a higher educational attainment was
associated with PSQ in the present study.
Waist circumference is a measure of
abdominal fat deposit such that persons
with higher waist circumference also have
higher abdo minal fat . The re was a
positive association between PSQ and
increased waist circumference in the
presen t study. Knowing that persons
with higher waist circumference tend to
also have excess body weight (over-
weight and obesity),55,56 this finding is
consistent with previous studies that
showed a positive association between
PSQ and excess body weight.57,58 The link
between PSQ and excess body weight
could be sleep-disordered breat hi ng
(apnea and hypopnea) that is common in
those with excess body weight.59–61
Anxiety and depression arise from
perturbation in the normal psychological
state. We found that the sleep quality in
the participants with these conditions
was largely poor. PSQ prevalence has
been shown to be higher in patients with
symp toms o f anx iet y and de pres -
sion,13,14,51,62 and this relationship could
be bidirectional.63
For participants with impaired sleep
quality, the most affected areas include
sleep latency, duration, and disturbance.
The mean HRQoL subscales values were
significantly lower for the participants
with PSQ compared with those with GSQ.
There were significant impairments in
their General Health, Vitality, Bodily Pain
and Mental Health. Other studies have
found a similar lowering of health-related
quality of life in people with PSQ.62,64,65
The major limitation in this study is
the use of self-reported questionnaires
that depends on accurate recollections
of past events, and which cannot be
insulated from personal bias. Though
the perfo rmance of sleep study using
polysomnography to determine sleep
quality would have been a more objective
approach, this was not feasible due to
funding limitation. Nevertheless, all the
instruments we used in the conduct of
the study have been severally validated
in different populations and found to be
reliable. Also, the sampling method is not
error-proof because there was no strict
ad her e nc e to prob abil ity samp li ng
pr inci ple s . Co mor b idi tie s suc h as
cardiovascular disease, arthritic pain,
chronic obstructive pulmonary disease
etc., especially in the elderly, which are
confounders of disordered sleep were
not considered in the study.
The findings of the present study
may not represent what obtains in all parts
of Nigeria because it was conducted in a
single community. Ther ef or e, lager
prospective population-ba sed studies
are needed to examine these factors in
greater detail.
CONCLUSION
Thi s stu dy sho ws that the
prevalence of PSQ is high in the study
population and that those with PSQ tend
to have poorer HRQ oL. A ho li sti c
approa ch that addresses the related
ps yc hos oci al an d other mo d if iab le
factors identified by this study is much
de s ira ble in t he man age men t of
disordered sleep.
REFERENCES
1. Eve rs o n CA , B erg ma n n B M,
Rechtschaffen A. Sleep deprivation in
the rat: III. Total sleep deprivation.
Sleep. 1989; 12: 13–21.
2. Frank E, Sidor MM, Gamble KL, Cirelli
C, Sh ark ey KM , Ho yl e N, et al .
Circadian clocks, brain function, and
development. Ann N Y Acad Sci. 2013;
1306: 43–67.
3. Xie L, Kang H, Xu Q, Chen MJ, Liao Y,
Thiyagarajan M, et al. Sleep drives
A. C. Jemilohun and Associates Sleep Quality in a Nigerian Community
Table 4: Health-Related Quality of Life in Participants (n=505)
Variables Total PSQ (n=212) GSQ (n=293) p-value
Physical Functioning 72.9 ± 32.1 74.1 ± 30.4 72.0 ± 33.3 0.474
Role Physical 74.0 ± 29.9 73.1 ± 29.8 74.7 ± 30.1 0.531
Bodily Pain 75.7 ± 24.9 69.1 ± 26.3 80.6 ± 22.6 < 0.001
General Health 84.8 ± 15.7 80.4 ± 17.3 88.0 ± 13.7 < 0.001
Vitality 58.0 ± 35.4 42.5 ± 36.5 69.3 ± 30.1 < 0.001
Social Functioning 69.7 ± 30.2 70.9 ± 27.3 68.8 ± 32.1 0.428
Role Emotional 74.9 ± 29.5 73.5 ± 29.8 75.9 ± 29.3 0.372
Mental Health 64.5 ±19.4 59.4 ± 17.7 68.2 ± 19.9 < 0.001
PCS 50.2 ± 7.7 49.4 ± 8.5 50.8 ± 7.0 0.052
MCS 46.2 ± 8.9 43.7 ± 9.0 48.1 ± 8.0 <0.001
PSQ, Poor sleep quality; GSQ, Good sleep quality; PCS, Physical Component Summary;
MCS, Mental Component Summary.
734

West African Journal of Medicine Vol. 39, No. 7, July, 2022
metabolite clearance from the adult
brain. Science. 2013; 342: 373–377.
4. Ci nc in A, Sari I, Oðu z M, Sert S,
Bozbay M, Ataþ H, et al. Effect of acute
sleep deprivation on heart rate recovery
in healthy young adults. Sleep Breath.
2015; 19: 631–636.
5. Kline C. Sleep Quality. In: Gellman
MD, Turner JR, editors. Encyclopedia
of Behavioral Medicine. New York, NY:
Springer; 2013 [Accessed 2020 Oct 15].
p. 1811–3. Availab le from: https: //
doi.org/10.100 7/ 97 8- 1- 44 19 -1 005-
9_849.
6. Harvey AG, Stinson K, Whitaker KL,
Moskovitz D, Virk H. The Subjective
Meaning of Sleep Quality: A Com-
parison of Individuals with and without
Insomnia. Sleep. 2008; 31: 383–393.
7. Buysse DJ, Reynolds CF, Monk TH,
Berman SR, Kupfer DJ. The Pittsburgh
Sleep Quality Index: a new instrument
for psychiatric practice and research.
Psychiatry Res. 1989; 28: 193–213.
8. Stranges S, Tigbe W, Gómez-Olivé FX,
Thorogood M, Kandala N-B. Sleep
problems: an emerging global epidemic?
Findings from the INDEPTH WHO-
SAGE study among more than 40,000
older adults from 8 countries across
Africa and Asia. Sleep. 2012; 35: 1173–
1181.
9. Luo J, Zhu G, Zhao Q, Guo Q, Meng
H, Hong Z, et al. Prevalence and Risk
Factors of Poor Sleep Quality among
Ch i nes e E lde r ly in a n U rba n
Community: Results from the Shanghai
Aging Study. PLoS One. 2013: 8.
10. Leger D, Guilleminault C, Dreyfus JP,
Delahaye C, Paillard M. Prevalence of
insomnia in a survey of 12,778 adults
in France. J Sleep Res. 2000; 9: 35–42.
11. Wang P, Song L, Wang K, Han X, Cong
L, Wan g Y, et al. Preval en ce an d
associated factors of poor sleep quality
among Chinese older adults living in a
rural area: a population-based study.
Aging Clin Exp Res. 2020; 32: 125–131.
12. Berhanu H, Mossie A, Tadesse S, Geleta
D. Prevalence and Associated Factors
of Sleep Qual it y amon g Adults in
Jimma Town, Southwest Ethiopia: A
Community- Ba sed Cro ss -S ectional
Stud y. Sl ee p Disord . 201 8; 20 18 :
8342328.
13. Bouloukaki I, Stathakis G, Koloi A,
Bakiri E, Moudatsaki M, Pouladaki E,
et al. Prevalence and risk factors of poor
sleep quality and fatigue during exam
period s in university stude nts. ERJ
Open Research. 2017; 3.
14. Zhu X, Hu Z, Nie Y, Zhu T, Chiwanda
Kaminga A, Yu Y, et al. The prevalence
A. C. Jemilohun and Associates Sleep Quality in a Nigerian Community
of poor sleep quality and associated risk
factors among Chinese elderly adults in
nursing homes: A cross-sectional study.
PLoS One. 2020: 15.
15. Kim JY, Kim JH, Lee HW, Choi KG.
Prevalence of Shift work sleep disorder
and its impact on health and working.
Jou rn al of Korean Slee p Resea rch
Society. 2005; 2: 39–46.
16. P lan t in g a L . Pr eva len ce o f S elf -
Re por ted Sl eep Pr ob lem s Amon g
People With Diabetes in the United
States, 2005–2008. Prev Chronic Dis.
2012: 9.
17. Nuhu FT, Yusuf AJ, Adeyemi SO, Kalu
AO. Sleep quality among primary care
attendees in Kaduna, Northern Nigeria:
a case-control study. Int J Psychiatry
Med. 2013; 46: 291–301.
18. Aliyu I, Mohamme d II, Lawal TO,
Gudaji M, Garba N, Monsudi KF, et al.
Assessment of Sleep Quality among
Medical Doctors in a Tertiary Hospital
in a Semi-Rural Setting. J Neurosci Rural
Pract. 201 8; 9: 535–540.
19. Fawale MB, Ismaila IA , Musta pha
AF, Ko mo laf e MA, Ib igb ami O .
Correlates of sleep quality and sleep
duration in a sample of urban-dwelling
elderly Nigerian women. Sleep Health.
2017; 3: 257–262.
20. Oshinaike O, Akinbami A, Ojelabi O,
Da da A, D o sun mu A , O lab ode S J.
Quality of Sleep in an HIV Population
on Antiretroviral Therapy at an Urban
Tert iary Cent re in Lagos , Ni ge ria.
Neurol Res Int. 2014: 298703.
21. Alebiosu OC, Ogunsemi OO, Familoni
OB, Adebayo PB, Ayosele EO. Quality
of sleep among hypertensive patients
in a semi-urban Nigerian community: a
prospective study. Postgrad Med. 2009;
121: 166–172.
22. Seun-Fadipe CT, Mosaku KS. Sleep
qu al it y and psych ological distress
among und erg rad uate studen ts of a
Nigerian university. Sleep Health. 2017;
3: 190–194.
23. A kin tay o R O, Yer im a A,
Uh un mwangho C, Olaosebikan H,
Akpabio AA. Tossing and turning with
degenerat ive arthropathy: an assess-
ment of poor sleep quality in knee
osteoarthritis. Reumatologia. 2019; 57:
207–213.
24. Adetiloye AO, Erhabor GE, Obaseki
DO , Ad e wa le OO , Awo p et u O F.
Impact of Sleep Quality on the Health-
Related Quality of Life of Patients with
Ch ron ic Ob str u ct i ve P u lm o nar y
Disease. West Afr J Med. 2018; 35: 173–
179.
25. Jemilohun AC, Akande KO, Elikwu CJ,
Fasesan OA, Adeleye O, Ajiro TO.
Functional Bowel Disorders, Psycho-
social Correlates and Health -related
Qu ali ty o f Lif e in a N ig eri an
Community: Ilisan-Remo Functional
Bowel Disorders Project Protocol. Int
Res J Gastroenterol & Hepatol. 2020;
3: 1–9.
26. Towns of the world. Information on
Ilishan, Ogun, Nigeria. [Accessed 2020
Se p 28 ]. Avai lab le fr o m: ht t ps: //
www.to wns oft heworld.c om/ Nig eria/
Ogun/Ilishan/Information.
27. E zekiel CN, Oyeyemi OT, Oyedele
OA, Ayeni KI, Oyeyemi IT, Nabofa W,
et al. Ur i na ry af la tox in ex pos ure
monitoring in rural an d semi-urban
pop ulatio ns in Ogun state , Nigeria.
Food Addit Contam Part A Chem Anal
Control Expo Risk Assess. 2018; 35:
1565–1572.
28. Beck AT, Epstein N, Brown G, Steer
RA. An inventory for measuring clinical
an xi ety: ps ychom etric pr op ert ie s.
J Consult Clin Psychol. 1988; 56: 893–
897.
29. L eyfer OT, Ru berg JL, Wood ru ff-
Borden J. Examination of the utility of
the Beck Anxiety Inventory and its
fa ct o rs as a scre ene r for a nxi ety
disorders. J Anxiety Disord. 2006; 20:
444–58.
30. O sman A, Hoff man J, Bar rios FX,
Kopper BA, Breitenstein JL, Hahn SK.
Factor structure, reliability, and validity
of the Beck An xiety Inven tor y in
adolescent psychiatric inpatients. J Clin
Psychol. 2002; 58: 443–456.
31. Muntingh ADT, van der Feltz-Cornelis
CM, van Marwijk HWJ, Spinhoven P,
Penninx BWJH, van Balkom AJLM. Is
the Beck Anxiety Inventory a good tool
to assess the severity of anxiety? A
primary care study in the Netherlands
Stud y of De pr ess io n and Anxie ty
(NESDA). BMC Family Practice. 2011;
12: 66.
32. Wetherell JL, Areán PA. Psychometric
ev alu ati on o f th e B eck Anxi ety
Inventory with older medical patients.
Psycholo gical Assessment. 1997; 9:
136–144.
33. Beck AT, Ward CH, Mendelson M,
Mock J, Erbaugh J. An inventory for
me as u rin g de pre ssi o n. Arc h Gen
Psychiatry. 1961; 4: 561–571.
34. Adewuya AO , Ola BA, Aloba OO.
Prevalence of major depressive disorders
and a validation of the Beck Depression
Inventory among Nigerian adolescents.
Eur Child Adolesc Psychiatry. 2007; 16:
287–292.
735

West African Journal of Medicine Vol. 39, No. 7, July, 2022
A. C. Jemilohun and Associates Sleep Quality in a Nigerian Community
35. C h ukw uje kwu D C, Oke afo r C U,
On ifade PO. Val idi ty of Bec k’s
depression inventory and alcohol use
disorders identification test in Nigeria’s
Nig er Delta regi on . Port Harco urt
Medical Journal. 2016; 10: 50–54.
36. Mostafa Alim AH, Ahmed N, Mullick
MSI, Chowdhury NF, Akhter F, Alam
S. Validation of the Bangla version of
Beck Depression Inventory-II. Brain
and behavior. Brain Behav. 2020; 10:
e01563.
37. Park K, Jaekal E, Yoon S, Lee S-H, Choi
K-H. Diagnostic Utility and Psycho-
me tri c P rope rti es o f t he Bec k
De pre ssi o n I n ven tor y-I I Amo ng
Korean Adults. Front Psychol. 2019; 10:
2934.
38. Wiglusz MS, Landowski J, Michalak
L, Cubała WJ. Validation of the Polish
ve rsi on of th e Beck De pre ssi on
Inventory in pati ent s with epilepsy.
Epilepsy Behav. 2017; 77: 58–61.
39. Luty J, O’Gara C. Validation of the 13-
Item Beck Dep ression Inve nto ry in
alcohol-dependent people. Int J Psy-
chiatry Clin Pract. 2006; 10: 45–51.
40. B han da ri NR, Ka th e N, Hayes C,
Payakachat N. Reliability and validity
of SF-12 v2 among adults with self-
reported cancer. Res Social Adm Pharm.
2018; 14: 1080–1084.
41. H ayes CJ, Bhanda ri NR, Ka the N,
Payakachat N. Reliability and Validity
of the Medical Outcomes Study Short
Form-12 Version 2 (SF-12v2) in Adults
with Non-C ancer Pain . Hea lthcare
(Basel). 201 7; 5: 22.
42. I n ter nat ion a l Qual ity o f L ife
As ses sm ent – IQ OLA Co u ntr ies .
[Accessed 2020 Jan 9]. Available from:
http://www.iqola.org/countries.aspx.
43. Madrid-Valero JJ, Martínez-Selva JM,
Ribeiro do Couto B, Sánchez-Romera
JF, Ordoñana JR. Age and gender effects
on the prevalence of poor sleep quality
in the adult population. Gac Sanit. 2017;
31: 18–22.
44. Wu W, Jiang Y, Wang N, Zhu M, Liu X,
Jiang F, et al. Sleep quality of Sh anghai
residents: pop ul at io n- based c ro ss -
sectional study. Qual Life Res. 2020;
29: 1055–1064.
45. Dong X, Wang Y, Chen Y, Wang X, Zhu
J, Wang N, et al. Poor sleep quality and
influencing factors among rural adults
in Deqing, China. Sleep Breath. 2018;
22: 1213–1220.
46. Watson EJ, Coat es AM, Ko hler M,
Banks S. Caffeine Consumption and
Sleep Quality in Australian Adult s.
Nutrients. 2016; 8: 479.
47. Clark I, Landolt HP. Coffee, caffeine,
and sleep: A systemat ic review of
epidemiological studies and randomized
controlled trials. Sleep Med Rev. 2017;
31: 70–78.
48. P orkka-Heiskanen T, Kalinchuk AV.
Adenosine, energy metabolism and sleep
homeostasis. Sleep Med Rev. 2011; 15:
123–135.
49. Nehlig A, Daval JL, Debry G. Caffeine
an d t he ce ntr al ne rvo us sy st e m:
mechanisms of action, biochemical,
metabolic and psychostimulant effects.
Brain Res Brain Res Rev. 1992; 17:
139–170.
50. Getachew Y, Azale T, Necho M. Poor
slee p quality and ass ociated factors
amon g pri so ne rs of the Di re dawa
correctional facility in eastern Ethiopia.
Ann Gen Psychiatry. 2020; 19: 40.
51. Vézina-Im L-A, Lebel A, Gagnon P,
Nicklas TA, Baranowski T. Individual
Correlates of Sleep Among Childbearing
Age Women in Canada. Behav Sleep
Med. 2019; 17: 634–645.
52. Xiang Y-T, Ma X, Cai Z-J, Li S-R, Xiang
Y-Q, Guo H-L, et al. The prevalence of
insomnia, its sociodemographic and
clinical correlates, and treatment in rural
and urban regions of Beijing, China: a
general population-based survey. Sleep.
2008; 31: 1655–1662.
53. Tang J, Liao Y, Kelly BC, Xie L, Xiang
Y-T, Qi C, et al. Gender and Regional
Di ff ere nc es in Sl eep Qual it y and
Insomnia: A General Population-based
Study in Hunan Province of China. Sci
Rep. 2017 6; 7: 43690.
54. Kang J-M, Lee JA, Jang J-W, Kim YS,
Sun woo S. Factors Associated with
Poor Sleep Quality in Primary Care.
Korean Journal of Family Medicine.
2013; 34: 107.
55. Chinedu SN, Ogunlana OO, Azuh DE,
Iweala EEJ, Afolabi IS, Uhuegbu CC,
et al. Correlation Between Body Mass
Index and Wa is t Cir cumference in
Ni ger ian Ad ult s: I mpl ica tio n as
Indicators of Health Status. J Public
Health Res. 2013; 2: e16.
56. Gierach M, Gierach J, Ewertowska M,
Arndt A, Junik R. Correlation between
Bo d y M as s I n de x a nd Wais t
Ci rcu mfe re n ce in P ati ent s w ith
Metabolic Syndrome. ISRN Endocrinol.
2014: 514589.
57. Hung HC, Yang YC, Ou HY, Wu JS, Lu
FH, Chang CJ. The association between
se lf- re por ted s lee p q ual ity a nd
overweight in a Chinese population.
Obesity. 2013; 21: 486–492.
58. Chen DR, Ku an PY. Gender, sl eep
problems, and obesity in Ta iwan: a
propensity-score-match ing approach.
Women Health. 2015; 55: 119–133.
59. Young T, Peppard PE, Taheri S. Excess
weight and sleep-disordered breathing.
J Appl Physiol (1985). 2005; 99: 1592–
1599.
60. Senaratna CV, Perret JL. Lodge CJ,
Lowe AJ, Campbell BE, Matheson MC,
et al. Prevalence of obstructive sleep
apn ea in th e general popu latio n: A
sys tematic review. Sleep medi ci ne
reviews . Sleep Med Rev. 20 17; 34:
70–81.
61. L iu C , C hen M-S , Yu H . T he
relationship between obstructive sleep
apnea and obe sity hypo ventilation
syndro me: a systematic review and
meta-a nal ysi s. Oncotarget. 201; 8:
93168–93178.
62. P otter MN, Howell DR, Dahab KS,
Sweeney EA, Albright JC, Provance AJ.
Sleep Quality and Quali ty of Lif e
Among Healthy High School Athletes.
Clin Pediatr (Phila). 2020; 59: 170–177.
63. Dinis J, Bragança M. Quality of Sleep
and Depression in College Students:
A Systematic Review. Sleep Sci. 2018;
11: 290–301.
64. Mariani D, Muzasti RA, Thamrin A.
The Relationship Between Quality of
Sleep and Quality of Life of Patients in
Medan, Indonesia. Open Access Maced
J Med Sci. 2019; 7: 1794–1797.
65. Ghasemi S-R, Khezeli M, Rajabi-Gilan
N, Koulani M, Moloudi-Safa N, Hemati
A, et al. Sleep Qualit y and Health-
Related Quality of Life in Workers of
Ke rma nsh ah Ind ust ria l Town: A
Corre latio n Stu dy. Indian J Occup
Environ Med. 2020; 24: 72–77.
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