ORIGINAL RESEARCH
published: 10 May 2022
doi: 10.3389/fpsyt.2022.792460
Poor Sleep in Community-Dwelling
Polysubstance Users: Association
With Khat Dependence,
Metacognition, and
Socio-Demographic Factors
Md Dilshad Manzar 1 , Ahmad H. Alghadir 2 , Masood Khan 2*, Mohammed Salahuddin 3,4 ,
Hamid Yimam Hassen 5 , Ahmed M. Almansour 1 , Dejen Nureye 3 , Eyob Tekalign 6 ,
Showkat Ahmad Shah 7 , Seithikurippu R. Pandi-Perumal 8,9 and Ahmed S. Bahammam 10,11
Edited by:
Sairam Parthasarathy,
University of Arizona, United States
Reviewed by:
Constance Fung,
VA Greater Los Angeles Healthcare
System, United States
Axel Steiger,
Ludwig Maximilian University of
Munich, Germany
*Correspondence:
Masood Khan
raomasood22@gmail.com;
mkhan4.c@ksu.edu.sa
Specialty section:
This article was submitted to
Sleep Disorders,
a section of the journal
Frontiers in Psychiatry
Received: 10 October 2021
Accepted: 14 February 2022
Published: 10 May 2022
Citation:
Manzar MD, Alghadir AH, Khan M,
Salahuddin M, Hassen HY,
Almansour AM, Nureye D, Tekalign E,
Shah SA, Pandi-Perumal SR and
Bahammam AS (2022) Poor Sleep in
Community-Dwelling Polysubstance
Users: Association With Khat
Dependence, Metacognition, and
Socio-Demographic Factors.
Front. Psychiatry 13:792460.
doi: 10.3389/fpsyt.2022.792460
Frontiers in Psychiatry | www.frontiersin.org
1
Department of Nursing, College of Applied Medical Sciences, Majmaah University, Al Majmaah, Saudi Arabia, 2 Department
of Rehabilitation Sciences, College of Applied Medical Sciences, King Saud University, Riyadh, Saudi Arabia, 3 Department of
Pharmacy, College of Medicine and Health Sciences, Mizan-Tepi University (Mizan), Mizan-Aman, Ethiopia, 4 Pharmacology
Division, Department of BioMolecular Sciences, University of Mississippi, Oxford, MS, United States, 5 Department of Public
Health, College of Medicine and Health Sciences, Mizan-Tepi University, Mizan-Aman, Ethiopia, 6 Department of Medical
Laboratory Sciences, College of Medicine and Health Sciences, Mizan-Tepi University, Mizan-Aman, Ethiopia, 7 Department
of Economics, College of Business and Economics, Mizan-Tepi University (Mizan), Mizan-Aman, Ethiopia, 8 Somnogen
Canada Inc., Toronto, ON, Canada, 9 Saveetha Medical College and Hospitals, Saveetha Institute of Medical and Technical
Sciences, Saveetha University, Chennai, India, 10 The University Sleep Disorders Center, College of Medicine, King Saud
University, Riyadh, Saudi Arabia, 11 National Plan for Science and Technology, College of Medicine, King Saud University,
Riyadh, Saudi Arabia
Purpose: Poor sleep and cognitive deficits are often associated with increased drug
use. However, no study has addressed the relationship between poor sleep, substance
dependence, and metacognitive deficit in polysubstance users.
Methods: This was a cross-sectional study with a simple random sampling involving
community-dwelling polysubstance users (n = 326, age = 18–43 years) in Mizan,
Ethiopia. Participants completed a brief sleep questionnaire, severity of dependence on
khat (SDS-Khat), a brief meta-cognition questionnaire, and a socio-demographic survey.
Results: Majority (56.4%) of the polysubstance users had sleep disturbance. Chronic
health conditions [adjusted odds ratio (AOR) = 2.52, 95% confidence interval (CI) 1.31–
4.85], chronic conditions in the family (AOR = 2.69, 95% CI 1.40–5.20), illiterate-primary
level of educational status (AOR = 2.40, 95% CI 1.30–4.04), higher SDS-Khat score (AOR
= 1.39, 95% CI 1.13–1.72), and lower meta-cognition score (AOR = 0.90, 95% CI 0.84–
0.97) predicted poor sleep in the polysubstance users. Moreover, low metacognition
score and high SDS score also predicted additional sleep disturbances like chronic
sleep insufficiency, lethargy and restlessness after nighttime sleep, socio-occupational
dysfunctions, and daytime disturbances in polysubstance users.
Conclusion: Poor sleep, severe khat dependence, and metacognitive deficits are
common in community polysubstance users. Moreover, poor sleep is associated with
higher khat dependence, lower metacognitive ability, lower educational status, and the
presence of chronic conditions in polysubstance users or their families.
Keywords: polydrug use, khat, alcohol, nicotine, sleep problems, metacognition
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Sleep Correlates in Polysubstance Users
INTRODUCTION
attempted to assess sleep, sleep-related symptoms, and their
predictors in community-dwelling polysubstance users. There is
a paucity of studies regarding these factors among polysubstance
users. Therefore, this study explored the prevalence of poor sleep,
poor sleep-related symptoms, severe dependence on khat, and
level of metacognitive deficits in polysubstance-using community
adults. We hypothesized that history of chronic conditions
in polysubstance users/family members, lower metacognitive
ability, and higher level of dependence on substance use may
predict poor sleep outcome.
Polysubstance use (PSU) implies using more than one drug
of abuse either simultaneously or sequentially within a defined
timeframe. PSU is common among illicit drug users with the
desire to (1) obtain greater effects compared to use of either drug
alone, (2) acquire a notable increase in the subjective response to
a drug, or (3) alleviate the adverse side effects of one substance by
the other (1). Most substance use research (including preclinical
research) has not accounted for PSU as a variable.
Globally, sleep disturbances have become one of the
commonly prevalent mental health disorders, wherein onethird of general adult individuals suffer from sleep problems
(2). Estimates vary, but a large proportion of communitydwelling adults show sleep disturbances ranging from ∼16 to
65.4% (3–5). Poor sleep and related sleep disturbances may
lead to physiological, psychological, and social disturbances (6).
For example, individuals with poor sleep have been associated
with treatment-resistant hypertension (7), suicidal ideation
(8), dysregulated circulating cholesterol and triglyceride levels
(9), and diabetes mellitus (10). Moreover, individuals with
poor sleep quality were more susceptible to neuropsychiatric
complications, especially substance use and affective and
cognitive disorders (11–15). Intriguingly, the relationship
between sleep disturbances and substance use disorders may
be bidirectional, wherein sleep disturbances increase the risk of
substance misuse (11, 12), and substance use may trigger sleep
complications (16).
Substance-using populations in Ethiopian demographics have
pronounced sleep problems (16–20). Habitual khat (Catha edulis)
is a plausible explanation for changes in sleep patterns. Khat
has two important alkaloids, cathinone and cathine, that possess
stimulant-like activity similar to amphetamines (17, 21, 22).
Central nervous complications are associated with khat use,
including deficits in memory, concentration, sleep, headache,
migraine, motor coordination, and stereotypical behavior (21,
22). Alcohol is often concurrently misused in the Ethiopian
population (17, 18). The effect of alcohol on sleep continuity
is dose-dependent, with low dose increasing the sleep time
and high dose leading to short-term withdrawal state, increased
sympathetic activity, and sleep disruption, mainly in the second
phase of the night (23). Smoking tobacco is associated with
a constellation of sleep complications, including difficulty
initiating sleep, staying asleep, daytime sleepiness, and affective
dysregulation, including anxiety and depression (24, 25).
Metacognitive abilities do vary among insomnia patients in
comparison to healthy people (26). Some of the identifiable
features of circadian rhythm (a component in sleep regulation)
are associated with dysfunctional metacognition and neuroticism
(27). Sleep quality characteristics, and metacognition mediate
between chorotype measures and poor well-being (27). These
pieces of evidence do imply that PSU disorder is a comorbid
disorder commonly associated with numerous influences such
as poor sleep, stress, and other factors. However, no study has
MATERIALS AND METHODS
Participants and Procedure
A cross-sectional study was performed on community-dwelling
habitual polysubstance users living in Mizan-Aman, Bench Maji
Zone, Ethiopia. Houses were earmarked using simple random
sampling (lottery method) from the list of houses provided by
health post professionals. All households with a minimum of one
adult member were the source population. Adults with habitual
use of more than one substance for at least 6 months composed
the study population. PSU was defined as the habitual use of
two or more of these substances: khat, alcohol, smoking, and
caffeinated drinks. Those having memory problems or on neuropsychotic medications based on self-report or on account of
information given by the family members were excluded to avoid
memory-related bias. A final sample (n = 326) with certain
age (range: 18–43 years; mean: 27.1 ± 3.7 years) completed
this study involving a brief sleep questionnaire (BSQ), severity
of dependence on khat (SDS-Khat), a brief metacognition
questionnaire, and a socio-demographics tool (19, 28). A brief
and precise summary of the objectives and methods to be
followed in the study were given to the participants. Participation
was voluntary and involved no risks or rewards. The participants
gave informed written consent for participation and publication.
Measures
Brief Sleep Questionnaire
A BSQ with four dichotomous items (yes/no) was used to assess
the presence of poor sleep and poor sleep-related symptoms. The
BSQ items recorded responses to determine these: (i) subjective
report of sleep disturbances; (ii) duration of sleep complaints
(3 or more months); (iii) daytime restlessness, irritability, and
tiredness; and (iv) report of social and occupational disruptions
related to sleep disturbances. The respondents were identified as
having poor sleep if they had any one of the first two symptoms,
i.e., (i) or (ii) along with complaints of both (iii) and (iv) (20).
Similarly, a clinical interview using slightly modified criteria
based on the International Classification of Sleep Disorders,
Revised (ICSD-R) has been used in previous sleep research in
similar settings (4, 29). The BSQ was found to have an excellent
level of internal consistency, as shown by a McDonald’s Omega
of 0.88 and the greatest lower bound to reliability of 0.92 in this
study sample (30). All the four items loaded on a common factor,
“poor sleep,” with a cumulative variance of 72. 30%. Further, a
goodness of fit index (GFI) = 0.994 and weighted root mean
Abbreviations: SDS-Khat, severity of dependence on khat; PSU, polysubstance
use; BSQ, brief sleep questionnaire.
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Sleep Correlates in Polysubstance Users
univariate outlier in the age but was retained after verifying
the correctness of the information. There was no issue of
multicollinearity and singularity; all predictor variables were
significantly correlated with poor sleep except athletic activity: β
= −1.71 to 8.7 (unadjusted odds ratio). All predictor variables
had linear relation with their log odds; there were no significant
p-values for the interaction terms between continuous predictor
variables and their natural logs in the model. Factor 10.10.03 for
Windows was used to perform a factor analysis of the BSQ scores
using categorical data assumptions (34, 35).
square residual (WRMR) = 0.024 of the BSQ supported its
unidimensional factor structure.
The Severity of Dependence on Khat
SDS-Khat has been found to have a moderate internal
consistency, adequate internal homogeneity, convergent validity,
and factorial validity in polysubstance-using adults (19). SDSKhat is a brief measure to assess dependence on khat with five
items each scored on the ordinal scale from 0 to 3. The least score
of 0 is indicated for a frequency of never to almost never for khat
use-related behavior, while a response of 3 indicates a frequency
of always or nearly always for khat use-related behavior. Scores
for all individual items are added to obtain SDS-Khat total score;
a higher score indicates increasing severity of dependence (19).
SDS-Khat is a valid and reliable tool for khat-chewing substance
users (19). A cutoff score of 6 and above has been used to indicate
severe psychological dependence on khat (31).
RESULTS
Participants’ Characteristics
More than 90% of the polysubstance users participating in
this study were men (Table 1). The prevalence of poor sleep,
chronic conditions in the participants, and chronic conditions
in the participants’ family members was 56.4, 60.4, and 61.3%,
respectively (Table 1). Most of the polysubstance users (69.9%)
were found to have a more severe psychological dependence on
khat. The majority of the study population (53.1%) were illiterate
or primary-educated. More than half of the polysubstance users
(60.4%) in this study were married or stayed with their partners
(Table 1). The range of monthly income (in Birr), SDS-Khat total
score, meta-cognition total score, and athletic activity every day
(min) were 1,500–5,000, 2–12, 16–36, and 0–105, respectively
(Table 1). Khat-chewing polysubstance users were the largest
group among the polysubstance-using adults (Table 1).
Meta-Cognition Questionnaire
Metacognition is a person’s awareness about his own cognitive
and emotive abilities (28). A brief measure of metacognition
with nine items was developed and validated by Klusmann et
al. (28). This structured questionnaire assesses two important
aspects of metacognitive ability, namely, metamemory and
metaconcentration (20, 28, 32, 33). An adapted version had been
found to have adequate psychometric validity in collegiate young
adults (32). Each of these nine items is scored on an ordinal
scale of 1 (absolutely wrong) to 5 (absolutely true). Metacognition
total score (range: 9–45) is obtained by adding scores for all the
nine items. Lower scores indicate poor metacognitive ability in
the respondent (28, 32). A similar and adapted meta-cognition
questionnaire has been found to have robust psychometric
validity measures in substance users, university students, and
nurses (20, 32, 33).
Associated Factors of Poor Sleep in
Polysubstance Users
Associated factors of poor sleep in the polysubstance users
are shown in Table 2. A binary regression prediction model
was adjusted for age (years) and gender. The prediction model
explained 47.8% (Nagelkerke R2 ) of the variance in classifying
poor sleepers among polysubstance users (36). This model was
significant compared to a model with only intercepts as indicated
by χ2 (10, N = 326) = 143.58, p < 0.001 with 79.4% accuracy
in classifying those with poor sleep. The presence of chronic
conditions [adjusted odds ratio (AOR = 2.52, 95% confidence
interval CI 1.31–4.85), the presence of chronic conditions in the
family (AOR = 2.69, 95% CI 1.40–5.20), illiterate to primary level
of educational status (AOR = 2.40, 95% CI 1.30–4.04), higher
SDS total score (AOR = 1.39, 95% CI 1.13–1.72), and lower metacognition total score (AOR = 0.90, 95% CI 0.84–0.97) predicted
poor sleep in the polysubstance users (Table 2).
Socio-Demographic Information
Information related to socio-demographic characteristics—
age, gender, presence of chronic conditions, presence of
chronic conditions in the family, educational status, marital
status, monthly income (in Birr), and duration of athletic
activity every day (min)—were collected. Self-reported accounts
from respondents for the presence of medication of AIDS,
cardiovascular complications, diabetes, epilepsy, hypertension,
tuberculosis, and any other chronic diseases including mental
health issues were recorded.
Statistical Analysis
All the statistical analysis was performed by SPSS-26.0 version
and Factor 10.10.03 for Windows. Participants’ characteristics are
presented using mean ± SD, range, frequency, and percentage.
Binary logistics regression was employed to identify associated
factors of poor sleep and related sleep disturbances after
verifying the assumptions. Dichotomized measures—(i) presence
or absence of poor sleep based on BSQ and (ii) presence or
absence of related sleep disturbances—were outcome variables.
There were no multivariate outliers as determined by the
Mahalanobis criteria: X2 (10) = 29.59, p < 0.001. There was one
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Associated Factors of Poor Sleep-Related
Symptoms in Polysubstance Users
Associated factors of poor sleep-related symptoms in the
polysubstance users are shown in Table 3. All four models were
adjusted for age and gender. Based on the criteria of Nagelkerke
R2 , the prediction models explained 54.9, 69.8, 58.0, and 19.3% of
the variance in classifying polysubstance users with a subjective
report of sleep disturbances, duration of sleep complaints (3 or
more months), daytime restlessness, irritability, and tiredness,
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TABLE 2 | Logistic regression predicting poor sleep in polysubstance users.
TABLE 1 | Participants’ characteristics.
Characteristics
(N = 326)
Age
Range; mean ± SD/
Predictors
Female
AOR
(95% CI of AOR)
18–43; 27.1 ± 3.7
Presence of chronic conditions
Gender
Male
p-value
frequency (percentage)
No
294 (90.2)
1
Yes
32 (9.8)
<.01
2.52 (1.31–4.85)
<0.01
2.69 (1.40–5.20)
<0.01
2.40 (1.30–4.44)
Presence of chronic conditions in the family
Poor sleep
No
No
142 (43.6)
Yes
Yes
184 (56.4)
Educational status
No
129 (39.6)
Secondary to higher level
Yes
197 (60.4)
Marital status
Illiterate to primary level
Presence of chronic conditions
1
1
Single/divorced/widowed
Presence of chronic conditions in the family
No
126 (38.7)
Double/married
Yes
200 (61.3)
Monthly income
SDS-Khat total score
Educational status
1
0.09
1.72 (0.93–3.20)
0.10
1.06 (0.98–1.15)
<0.01
1.39 (1.13–1.72)
Illiterate to primary level
173 (53.1)
Meta-cognition total score
0.01
0.90 (0.84–0.97)
Secondary to higher level
153 (46.9)
Athletic activity everyday (min)
0.10
1.01 (1.00–1.02)
Marital status
Unmarried/divorced/widowed
Double/married
Monthly income (In Birr)a
SDS-Khat total score
Poor sleep was evaluated by a brief structured questionnaire; the presence of chronic
conditions was based on self-reported presence of diabetes, hypertension, epilepsy,
tuberculosis, AIDS, other cardiovascular complications, and any other chronic diseases.
Metacognition was assessed by a brief measure developed by Klusmann et al. Sample
size (N = 326).
SDS-Khat, severity of dependence on khat scale; CI, confidence interval; AOR, adjusted
odds ratio, adjusted for age (year) and gender.
129 (39.6)
197 (60.4)
1,500–5,000; 3,647.8 ± 707.1
2–12; 6.5 ± 1.3
Dependence on khat
Less psychological dependence
98 (30.1)
More or severe psychological dependence
228 (69.9)
Meta-cognition total score
16–36; 26.6 ± 4.1
Athletic activity everyday (min)
0–105; 15.0 ± 24.4
Polysubstance use with khat chewing
318 (97.5%)b
Polysubstance use with alcohol
230 (70.6%)b
Polysubstance use with smoking
221 (67.8%)b
a model having only intercept χ2 (10, N = 326) = 26.74,
p < 0.01, which had an accuracy of 92.6% in classifying
complaints of social and occupational disruptions related to
sleep disturbances.
Low metacognition score predicted the presence of all the four
sleep complaints: subjective report of sleep disturbances (AOR =
0.91, 95% CI 0.84–0.98), 3 or more months of complaints about
sleep duration (AOR = 0.86, 95% CI 0.78–0.95), complaints
of daytime restlessness, irritability, and tiredness (AOR = 0.85,
95% CI 0.78–0.92), and complaints of social and occupational
disruptions related to sleep disturbances (AOR = 0.85, 95%
CI 0.75–0.97; Table 3). Illiterate to primary level of educational
status predicted the presence of all the four sleep complaints:
subjective report of sleep disturbances (AOR = 3.30, 95%
CI 1.71–6.36), 3 or more months of complaints about sleep
duration (AOR = 2.57, 95% CI 1.22–5.40), complaints of daytime
restlessness, irritability, and tiredness (AOR = 2.22, 95% CI 1.06–
4.64), and complaints of social and occupational disruptions
related to sleep disturbances (AOR = 0.36, 95% CI 0.13–0.97;
Table 3).
A high SDS total score predicted the presence of the three
sleep complaints: subjective report of sleep disturbances (AOR =
1.53, 95% CI 1.22–1.93), 3 or more months of complaints about
sleep duration (AOR = 1.52, 95% CI 1.18–1.97), and complaints
of daytime restlessness, irritability, and tiredness (AOR = 1.87,
95% CI 1.43–2.43; Table 3). The presence of chronic conditions
in the family predicted the presence of the three sleep complaints:
subjective report of sleep disturbances (AOR = 4.27, 95% CI
SD, standard deviation; SDS-Khat, severity of dependence on khat scale.
The presence of chronic conditions was based on self-reported presence of diabetes,
hypertension, epilepsy, tuberculosis, AIDS, other cardiovascular complications, and any
other chronic diseases. Poor sleep was evaluated by a brief questionnaire; metacognition
was assessed by a brief measure developed by Klusmann et al.
a One hundred Birr was approximately equal to 2.01 USD on January 23, 2022.
b Groups were not exclusive.
and report of social and occupational disruptions related to sleep
disturbances, respectively.
The model with correlates was significant compared with a
model having only intercept χ2 (10, N = 326) = 169.50, p < 0.001,
which had an accuracy of 80.4% in classifying polysubstance
users with a subjective report of sleep disturbances. The model
with correlates was significant compared with a model having
only intercept χ2 (10, N = 326) = 241.61, p < 0.001, which
had an accuracy of 87.7% in classifying polysubstance users
with 3 or more months of complaints about sleep duration.
The model with correlates was significant compared with a
model having only intercept χ2 (10, N = 326) = 173.13,
p < 0.001, which had an accuracy of 83.4% in classifying
complaints of daytime restlessness, irritability, and tiredness.
The model with correlates was significant when compared with
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Sleep Correlates in Polysubstance Users
TABLE 3 | Logistic regression predicting poor sleep-related symptoms in polysubstance users.
Predictors
Subjective
report of sleep
disturbances
Duration of sleep
complaints
Daytime
restlessness,
irritability, and
tiredness
Social and
occupational
disruptions related
to sleep
disturbances
AOR
(95% CI of AOR)
AOR
(95% CI of AOR)
AOR
(95% CI of AOR)
AOR
(95% CI of AOR)
Presence of chronic conditions
No
1
1
1
1
Yes
1.62 (0.80–3.30)
0.98 (0.41–2.38)
1.42 (0.66–3.02)
4.30 (1.47–12.54)**
Presence of chronic conditions in the family
No
1
1
1
1
Yes
4.27 (2.10–8.68)**
14.40 (5.73–36.20)**
5.61 (2.59–12.15)**
0.34 (0.11–1.09)
3.30 (1.71–6.36)**
2.57 (1.22–5.40)**
2.22 (1.06–4.64)*
0.36 (0.13–0.97)*
1
1
1
1
Educational status
Illiterate to primary level
Secondary to higher level
Marital status
Single/divorced/widowed
Double/married
1
1
1
1
1.17 (0.60–2.29)
3.65 (1.69–7.90)**
2.14 (1.05–4.36)*
2.20 (0.80–5.99)
0.99 (0.98–1.00)
Monthly income
0.99 (0.98–1.00)**
0.99 (0.98–1.00)
0.99 (0.98–1.00)**
SDS-Khat total score
1.53 (1.22–1.93)**
1.52 (1.18–1.97)**
1.87 (1.43–2.43)**
0.90 (0.63–1.29)
Meta-cognition total score
0.91 (0.84–0.98)*
0.86 (0.78–0.95)**
0.85 (0.78–0.92)**
0.85 (0.75–0.97)*
Athletic activity everyday (min)
1.02 (1.00–1.03)*
1.03 (1.02–1.05)**
1.00 (0.99–1.02)
0.99 (0.97–1.01)
*p
< 0.05; ** p < 0.01; sample size (N = 326).
Poor sleep was evaluated by a brief sleep questionnaire; subjective report of sleep disturbances, duration of sleep complaints (3 or more months), daytime restlessness, irritability,
and tiredness; and report of social and occupational disruptions related to sleep disturbances. The presence of chronic conditions was based on self-reported presence of diabetes,
hypertension, epilepsy, tuberculosis, AIDS, other cardiovascular complications, and any other chronic diseases.
SDS-Khat, severity of dependence on khat scale; CI, confidence interval; AOR, adjusted odds ratio, adjusted for age (year) and gender.
khat and nicotine-induced stimulants effects like anxiety and
impulsive behavior (37, 38). Given that the half-life of cathinone
is 1.5 h (39), this combination may be worse, as the effects of khat
may wear off quicker than alcohol (half-life is 4–5 h), triggering
individuals to consume khat repeatedly. This may lead to a fatal
inhibited state in these individuals when the effects of alcohol
are felt in isolation. Indeed, polysubstance users have poor health
outcomes than single-drug users (38). As such, the present study
revealed that PSU of khat, alcohol, and nicotine significantly
correlated with poor sleep, poor sleep-related disturbances, and
metacognitive deficits.
This study showed that among polysubstance users, the
majority of users chewed khat (97.5%), and ∼56% of the
total population showed poor sleep. This PSU behavior among
khat users is similar to the findings of prior studies, which
also reported that khat users often use other substances
(19, 40). Neurobiological mechanisms of khat which mimic
amphetamine-like effects on the sleep circadian system are
just beginning to be understood. Dopamine is an important
neurotransmitter that modulates the reward circuitry and
regulates alertness, thus implicated in the sleep–wake cycle.
It has been demonstrated that repeated use of amphetaminelike drugs led to increased sleep latency and a decrease in
the total sleep time and slow-wave and rapid eye movement
(REM) sleep (41). Sleep changes may further downregulate
2.10–8.68), 3 or more months of complaints about sleep duration
(AOR = 14.40, 95% CI 5.73–36.20), and complaints of daytime
restlessness, irritability, and tiredness (AOR = 5.61, 95% CI 2.59–
12.15; Table 3). The presence of chronic conditions predicted the
presence of social and occupational disruptions related to sleep
disturbances (AOR = 4.30, 95% CI 1.47–12.54; Table 3).
DISCUSSION
In the present study, an association was observed between
poor sleep and increasing severity of khat dependence, lower
metacognition ability, the presence of chronic conditions, the
presence of chronic conditions of a family member, and lower
educational status. Moreover, a high proportion of polysubstance
users had sleep disturbances and severe dependence on khat.
Consistent with the crosstalk between substance use and poor
sleep, this is the first study to demonstrate further that
polysubstance users have sleep complaints such as subjective
sleep disturbances, short sleep duration, daytime complaints, and
occupational problems related to sleep disturbances.
Mostly, psychostimulants like khat and nicotine are taken
along with central nervous system (CNS) depressants like
alcohol: either (a) to obtain greater subjective effects when using
these drugs together or (b) administration of khat or nicotine
may offset alcohol’s depressant effects. Alcohol may temper
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alone did not impair the spatial memory, suggesting synergistic
effects when these drugs were combined (58). Furthermore, when
rat hippocampus was assessed for markers of oxidative stress,
the use of alcohol and METH showed a synergistic increase
in reactive oxygen species, which are detrimental for the cell
compared to the use of either drug alone. Hence, concurrent use
of drugs may cause the drugs to interact with each other and may
have additive or synergistic effects on the physiological system.
Consistent with the predisposition to sleep changes, cognitive
deficits may also interplay, albeit concurrently, following
substance use (59, 60). In the present study lower metacognition
score predicted the presence of all four sleep complaints in
polydrug users. This is in line with previous preclinical and
clinical neuroimaging studies, which showed that differential
substance users have differential changes in the gray matter
volume that are associated with psychomotor, affective, and
cognitive deficits (22, 61–64). Furthermore, long-term use of
drugs with abuse potential may produce excitotoxicity by
over-activation of glutamatergic and dopaminergic synapses,
thus leading to neuronal damage and associated behavioral
changes (65–67).
In the present study increasing severity of khat dependence
was significantly associated with sleep complaints, namely,
subjective reports of sleep disturbances, sleep duration
complaints (3 or more months), daytime restlessness,
irritability, and tiredness. This is in line with other studies,
which demonstrated that drug users struggle with internalizing
and externalizing problems including difficulty in sleep
maintenance, sleep efficiency, and sleep duration (46, 68). Family
social support buffers the effects of internalizing problems
observed in substance users. Therefore, family involvement may
moderate the risk factors associated with substance use and
related emotional and behavioral challenges (69). However, if
family members of substance users have chronic conditions, then
they are less likely to buffer the effects of internalizing problems.
This possibly explains the relationship of chronic conditions in
family members with various sleep complaints and overall poor
sleep because family members with chronic conditions may be
less likely to constructively contribute to moderate the effects of
internalizing problems (69).
dopamine receptors, thereby increasing vulnerability to drug
misuse (42). Indeed, PSU may elevate the risk of comorbid
psychopathology and cognitive dysfunction (13). In support,
we and others have previously demonstrated that concurrent
use of khat and tobacco smoking (43) and concurrent use of
alcohol, khat, and tobacco smoking were associated with poor
sleep (18). In animal models of behavioral sensitization, which is
a model of drug addiction, nicotine potentiated the amphetamine
behavioral response and dopaminergic efflux in rats (44); in the
drug reinforcement animal model, nicotine enhanced incentive
motivational effects of amphetamine (45). In the light of the
dynamic interaction effects between nicotine, amphetamine, and
alcohol on hypocretin/orexin, GABAergic, dopaminergic, and
cholinergic neurotransmission, it is imperative to systematically
study the neurological comorbidities in polydrug users to reveal
new insights into the management of these addicts (41).
The present study also identified poor sleep-related
disturbances in polysubstance users with the binary logistic
regression models that were significantly associated with a
subjective report of sleep disturbances and three and more
months of sleep complaints. These findings are consistent
with a previous study, which demonstrated that adolescents’
substance use is significantly associated with sleep disturbances,
especially in maintaining sleep regularity, timing, efficiency,
and duration (46). Recent evidence support changes in the gene
expression level of Per2 with heavy drinking in alcoholics (47).
These changes are modulated by the dopaminergic transmission
between the ventral tegmental area and nucleus accumbens
involving melatonin hormone, levels of which promote circadian
rhythm, or via gene expression by the CLOCK protein (48, 49).
Moreover, drugs of abuse mediate direct changes in the circadian
rhythm independent of suprachiasmatic nucleus (SCN) or
light/dark cycle (50, 51) and also changes the sensitivity of
various drugs of abuse like opiates, nicotine, stimulants, and
alcohol based on the diurnal cycle (51).
As most study participants were khat users, it is possible
to speculate that repeated use of khat, alcohol, and tobacco
may have adverse consequences on attention and psychomotor
function. Chronic amphetamine use promoted deficits in
psychomotor functioning, attention, and sleep disruption (52,
53). Moreover, the concurrent use of nicotine and amphetamine
in female rats demonstrated potentiation of behavioral response
with an increase in the dopamine concentrations in the striatal
slices rich in dopaminergic receptors (44).
Alcohol, on the other hand, is a cytochrome p450 inhibitor;
chronic alcohol use may downregulate GABAergic receptors
and stimulate the glutamatergic receptors, thereby leading to
hyperarousal impulsive behavior state and further increase
vulnerability to affective and substance use disorders
(54, 55). Sleep disorders may confer vulnerability to future
neuropsychiatric complications and cognitive dysfunction (56).
Concurrent use of alcohol and methamphetamine (METH)
showed impairment of learning and memory compared
to METH alone in rats (57). Additional evidence in rats
demonstrated that the use of alcohol and METH produced
synergy to impair hippocampal-mediated spatial memory
compared to using METH alone (58). Alcohol administration
Frontiers in Psychiatry | www.frontiersin.org
LIMITATIONS OF THE STUDY
The current study’s results must be viewed in light of the study’s
cross-sectional nature. Also, the present study only focused on
poor sleep and associated sleep disturbances and metacognition.
Other factors that may impact sleep were not considered. The
collection of data was done by using a validated questionnaire,
which lacked objective sleep metrics. Also, illicit drug users were
questioned about their drug use (duration in months) with a
recall period of 1 month which may be associated with recall
bias. Future studies should explore longitudinal study design
in a cohort group of individuals who may use CNS stimulants
and depressants together and compare to single-drug users or
normal subjects. Nevertheless, our study is the first to report
a high prevalence of sleep complaints and their association
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Manzar et al.
Sleep Correlates in Polysubstance Users
The patients/participants provided their written informed
consent to participate in this study.
with dependence, metacognitive deficit, and socio-demographic
factors in polysubstance users. From the data presented in this
study, it is not possible to discern differences in associated
factors of poor sleep/poor sleep-related symptoms in discrete
groups of polysubstance users. Future studies with case–control
designs involving distinct groups of polysubstance users with
longitudinal data collection may help in identifying relationships
between sub-groups of polysubstance users and sleep.
AUTHOR CONTRIBUTIONS
MM, MS, HH, AMA, DN, ET, SS, SRP, and AB conceptualized the
study and its methodology and were involved in data collection
and curation also. MM and MK did the data analysis and wrote
and edited the manuscript. AHA, MS, HH, AMA, and AB were
involved in supervision. All authors reviewed and approved
the manuscript.
CONCLUSION
This study demonstrates that poor sleep, khat dependence,
and metacognitive deficits are highly prevalent in community
polysubstance users. Moreover, poor sleep is associated with
higher khat dependence, lower metacognitive ability, lower
educational status, and the presence of chronic conditions in
polysubstance users or their families.
FUNDING
DATA AVAILABILITY STATEMENT
Researchers Supporting Project number (RSP-2021/382), King
Saud University, Riyadh, Saudi Arabia. The authors extend their
appreciation to the Deanship of Scientific Research at Majmaah
University for funding this work under Project Number (R-2022113).
The raw data supporting the conclusions of this article will be
made available by the authors, without undue reservation.
ACKNOWLEDGMENTS
The authors are grateful to the Researchers Supporting Project
number (RSP-2021/382), King Saud University, Riyadh, Saudi
Arabia for funding this research. The authors are grateful to
the Deanship of Scientific Research, Majmaah University, for
funding the research (R-2022-113).
ETHICS STATEMENT
The studies involving human participants were reviewed and
approved by Human Institutional Ethics Committee, College of
Health Sciences, Mizan-Tepi University, Mizan-Aman, Ethiopia.
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Conflict of Interest: SRP is employed by Somnogen Canada Inc.
The remaining authors declare that the research was conducted in the absence of
any commercial or financial relationships that could be construed as a potential
conflict of interest.
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