1874-9445/20
Send Orders for Reprints to reprints@benthamscience.net
388
The Open Public Health Journal
Content list available at: https://openpublichealthjournal.com
RESEARCH ARTICLE
The Development of a New Understanding of Symptom Cluster During Pregnancy Using the Mediation Model
1,*
Khaled Suleiman
, Mahmoud Al Kalaldeh1
and Loai Abu Sharour1
1
School of Nursing, Al-Zaytoonah University, Amman, Jordan
Abstract:
Background:
Fatigue, depression and sleep disturbance are regarded as a symptom cluster associated with pregnancy. The mediation effect of sleep disturbance
on the relationship between depression on fatigue is still unclear.
Objective:
To assess the mediation effect of sleep disturbance on the established relationship between depression and fatigue among pregnant women.
Methods:
This study used a cross-sectional design. Pregnant women (n = 130) at a private gynecology and obstetrics outpatient clinic in Amman, Jordan.
Participants were recruited to complete the Brief Fatigue Inventory, the Insomnia Severity Index, and the Zung depression scale, in addition to the
demographic questionnaire. The mediation effect was examined through a Hierarchal Multiple Regression model.
Results:
A total of 130 pregnant women participated (mean of ages= 27.3). Of those, 41.5% were in the first trimester, while the rest were in their second
and the third trimesters (27.7%, and 30.8%, respectively). Regression analysis indicated that about 23% of the variation of fatigue was explained
by depression. Nonetheless, 47% of the variance of fatigue was explained by depression after identifying the mediation effect of sleep disturbance.
Conclusion:
The mediation role of sleep disturbance between depression and fatigue added a new approach to the assessment and prognosis of fatigue during
pregnancy.
Keywords: Depression, Fatigue, Mediation model, Pregnancy, Sleep disturbance, Pregnant women.
Article History
Received: March 21, 2020
1. INTRODUCTION AND BACKGROUND
A number of symptoms experienced by pregnant women
affect their quality of life including their energy, appetite, and
weight balance [1 - 3]. Fatigue scored the highest incidence
among pregnant women of more than 90% [2, 4, 5]. Studies
that examined symptoms experienced by pregnant women
reported that fatigue is often associated with other symptoms
such as sleep disturbances and depression [6 - 8]. The latter
symptoms have recently gained greater popularity during
pregnancy. Studies found that more than 75% of pregnant
* Address correspondence to this author at the School of Nursing, Al-Zaytoonah
University, P.O.Box 130, Amman 11733, Jordan; Tel: + 962 6 4291511;
Fax; + 962 6 4291432; E-mail: khaledsuleiman@yahoo.com
Revised: June 08, 2020
Accepted: June 17, 2020
women complained of sleep disturbances [9 - 13]. Other
studies revealed that more than 57% of pregnant women
reported depression during pregnancy and in the postpartum
period [5, 14]. In Jordan, minimal research attention has been
given to the study of symptoms among Jordanian pregnant
women. A previous study, nonetheless, reported that Jordanian
pregnant women experience low social support and symptoms
such as depression that interfere with life satisfaction [14].
The existence of these symptoms may warrant symptom
cluster [5, 15 - 18]. Because the majority of the previous
studies examined the incidence of each symptom individually,
the association between these symptoms is still controversial.
However, the relationship between fatigue, depression and
DOI: 10.2174/1874944502013010388, 2020, 13, 388-394
The Open Public Health Journal, 2020, Volume 13 389
Symptom Cluster During Pregnancy
sleep disturbances was identified in some other studies. For
instance, a significant negative correlation was found between
fatigue and sleep hours in which less sleeping hours were
correlated with more fatigue [15, 17, 19 - 22]. Sleep
disturbance was also correlated with depression across the
three pregnancy trimesters [17, 23, 24]. However, inconsistent
relationship was suggested between fatigue and depression
among pregnant women, as one study confirmed this
significant correlation (r=0.24, p=0.01) [22], while another
rejected this supposition in late pregnancy and postpartum
period [6]. Despite the existence of these associations,
understanding the extent of how depression may influence
fatigue, excluding the effect of sleep disturbances, is still not
clear. The need for understanding these relationships within a
conceptual model becomes a necessity.
The mediation model developed by Baron and Kenny [23]
was previously used to explain the relationship between
fatigue, depression, and sleep disturbance in cancer patients
[24, 25]. Huang and Lin [25] found a complete mediated effect
of depression between sleep disturbances and fatigue, as
depression led to sleep disturbances which, in turn, led to
fatigue. Similarly, Beck et al. [24] showed a partially mediated
effect of sleep disturbances between pain and fatigue in which
pain led to sleep disturbances that, in turn, led to fatigue. Thus,
the mediation model can be employed to enhance a better
understanding of how this symptom cluster interacts with each
other and its impact on pregnant women.
The study aims to achieve the following objectives:
1. To examine the relationship between fatigue, depression,
and sleep disturbance, on pregnant women in Jordan.
2. To explain the mediation effect of sleep disturbance on
depression that induces fatigue in pregnancy.
2. METHODS
This study employed a cross-sectional correlational design
through recruiting pregnant women from a private gynecology
and obstetrics outpatient clinic located in Amman, Jordan. A
non-probability convenient sampling technique was used to
recruit the study sample. A pregnant woman was eligible to
participate in the study if she was pregnant regardless of her
trimester and able to read and write in Arabic. Women were
excluded if they suffered from any comorbid disease such as
diabetes mellitus, hypertension, heart failure, chronic kidney
diseases, chronic obstructive pulmonary disease, asthma and
migraine. Women who had the psychiatric disease were also
excluded from the study. All previous illnesses had to be
declared in the informed consents and the researchers had to be
assured that none of the participants had a disease that may
induce fatigue or sleep disturbances. The preliminary sample
size calculation revealed the need for at least 120 participants.
However, 150 questionnaires were distributed.
2.1. Instruments
A self-administered questionnaire was used in this study
and included a demographic sheet and four self-report
instruments to assess the symptoms. Although the instruments
are self-reported tools, they are valid and reliable tools that
have been used widely in the literature to assess the symptoms
in different clinical populations.
2.2. Demographic Part
This section contains questions about age, trimester,
number of children, educational level, any health problems,
and employment status.
2.3. The Brief Fatigue Inventory (BFI)
The BFI [26] is a self-report questionnaire that assesses the
severity of fatigue and its interference with life in 9 items. The
total BFI score ranges from 0 to 10, with a higher score
indicating more fatigue and more fatigue interference with life
[26]. The severity of fatigue can be obtained from the average
of the first three items, while the interference with participants’
life is obtained from other items such as general activity, mood,
walking ability, and relationships with others. Mendoza et al.
[26] set up cut-off points for fatigue severity in two categories:
a score of 0-6 indicating non-severe fatigue, and a score >7
indicating severe fatigue. The BFI demonstrated high internal
consistency coefficient of 0.96, and good validity as supported
by significant correlations with both the Functional Assessment
of Cancer Therapy-Fatigue scale (r= -0.88, p<.001) and the
Profile of Mood States-Vigor (r= -0.84, p<.001) [26]. Suleiman
et al. [27] reported high internal consistency (α= 0.93) of the
Arabic version of the BFI.
2.4. The Insomnia Severity Index (ISI)
The ISI [28] is a self-report questionnaire that assesses the
severity of insomnia for the preceding two weeks. It consists of
9 items rated from 0 (not at all severe) to 4 (very severe) with
the total score ranges from 0 to 28. Higher scores indicate
greater insomnia severity. Morin [28] defined four categories
of insomnia scores as follows: 0 to 7 indicating no clinically
significant insomnia, 8 to 14 indicating subthreshold insomnia,
15 to 21 indicating moderate clinical insomnia, and 22 to 28
indicating severe clinical insomnia. Morin [28] reported that
ISI had a high internal consistency of 0.88. The convergent
validity of the ISI with sleep diary indicated significant
correlations (0.32-0.91, p<.05) [29]. Good internal consistency
(α=0.84) was also demonstrated in the Arabic version of the ISI
[30].
2.5. The Zung Depression Scale (ZDS)
The ZDS [31] is a self-report tool that assesses depression
for the previous week. This 20-item scale has a rating system
of 5-point (0-4) and its total scores ranged from 0 to 80. A cutoff point for depression was established by the original authors
as follows: 20-49 indicating a normal range, 50-59 indicating
mild depression, 60-69 indicating moderate depression, and 70
and above indicating severe depression. The validity and
reliability of the scale have been established [32]. Regarding
the Arabic version of the ZDS, Kirkby et al. [33] reported a
higher agreement with the original English versions as
indicated by the kappa K measurement (0.65, CI: 0.57-0.73).
2.6. Procedure
Approval to conduct the study was granted by the manager
390 The Open Public Health Journal, 2020, Volume 13
of the clinic where the study was conducted. An IRB approval
was obtained from Al-Zaytoonah University of Jordan. At the
clinic waiting room, participants were invited directly by the
researchers to participate in the study. Invitation to the study
included a verbal description of the study's purpose, benefits,
and participants’ rights. Participants were assured that their
contribution was totally anonymous, voluntary, and
confidential, in addition to the right to withdraw or participate.
Eligible participants were informed to complete the
questionnaires with signed consent. They were given a choice
to complete the questionnaire during their current visit or take
it home and return it back in their next visit. In the latter case,
participants' contact information (i.e., telephone number) was
required to allow for follow-up. The estimated time to
complete the whole questionnaire was 15-30 minutes.
2.7. Data Analysis
The collected data were entered into the Statistical Package
for Social Sciences software (SPSS) version 23. It was checked
for missing and outliers through visualizing the frequency
distributions of each variable and treated by re-checking the
original papers. Descriptive statistics included frequencies,
percentages, means, and standard deviations. Bivariate
correlation coefficient was used to evaluate the relationship
between symptoms. The mediation model developed as
proposed by Baron and Kenny [23] was implemented to
examine the effect of sleep disturbances on fatigue and
depression using the Hierarchical Multiple Regression as
follows:
1. Sleep disturbances (the mediator) is regressed on
depression (the independent variable).
2. Fatigue (the dependent variable) is regressed on
depression (the independent variable).
3. Fatigue (the dependent variable) is regressed on sleep
disturbances (the mediator) and depression (the independent
variable).
It was assumed that significant mediation occurs if
depression (independent variable) has no effect (not
significant) when the mediator (sleep disturbances) is
controlled.
3. RESULTS
3.1. Participants Characteristics
Of the 150 questionnaires distributed, 130 returned their
forms representing 86% response rate. Table 1 shows the
demographic characteristics of the participants. The
participants' average age was 27.33 years. Most of the
participants (70.3%) held high school degrees, unemployed
(86.2%), had kids (73.8%). While 41.5% of the participants
were in their first trimester, the rest were in their second and
third trimester (27.7% and 30.8%, respectively) (Table 1).
3.2. Fatigue, Depression and Sleep Disturbance Among
Pregnant Women
Descriptive statistics of the three symptoms (fatigue,
depression, and sleep disturbance) are as follows. The pregnant
women reported an average BFI of 5.43 (SD= 1.92), indicating
Suleiman et al.
non-severe fatigue. The majority of the women (67.7%) had
non-severe fatigue. The BFI severity mean score was 5.23,
while the BFI interference mean score was 5.61 (SD= 2.44).
The mean of the total ISI scores was 13.41 indicating subthreshold insomnia. The mean of the total ZDS scores was
50.09 indicating mild depression (Table 2).
Table 1. Demographic characteristics of the sample.
Variable
Total (N= 130)
Mean
SD
Age
27.33
5.93
Number of kids
2.64
0.97
-
-
-
-
n
%
Have kids
-
-
Yes
96
73.8
No
34
26.2
Education
-
-
Secondary School
90
70.3
Primary education
38
29.7
Employment
-
-
Employed
18
13.8
Unemployed
112
86.2
Trimester
-
-
First
54
41.5
Second
36
27.7
Third
40
30.8
N: Total sample, n: frequency, SD: Standard Deviation.
3.3. Associations Between Symptoms
The Pearson correlations coefficient was used to evaluate
the relationships between fatigue, depression, and sleep
disturbance as shown in Table 2. A significant positive
correlation was found between fatigue and depression, fatigue
and sleep disturbances, and between depression and sleep
disturbances. All correlations were statically significant at α:
0.01 and ranged from 0.48 to 0.68. (Table 3).
Table 2. Fatigue, depression and sleep disturbance levels.
Symptom
Mean
Total BFI
5.43
SD
1.9
Fatigue severity items total
5.61
2.44
Fatigue interference items total
5.2
2.21
Total ISI
13.41
5.3
Total ZDS
50.09
7.3
SD: Standard Deviation, BFI: Brief Fatigue Inventory, ISI: Insomnia Severity
Index, ZDS: Zung Depression Scale.
Table 3. Inter-Correlation matrix of pregnancy symptoms.
Symptom
BFI
ISI
ZDS
BFI
1
0.68**
0.48**
ISI
-
1
0.59**
ZDS
-
-
1
BFI: Brief Fatigue Inventory, ISI: Insomnia Severity Index, ZDS: Zung
Depression Scale.
**p<0.01
The Open Public Health Journal, 2020, Volume 13 391
Symptom Cluster During Pregnancy
β = 0.59, p < 0.001
Sleep
disturbance
s
Depression
β = 0.61, p < 0.001
β = 0.12, p = 0.13
Fatigue
β = 0.48, p < 0.001
Fig. (1). The mediation model.
3.4. The Mediation Effect of Sleep Disturbances
4. DISCUSSION
Based on the mediation steps mentioned earlier, the
regression model is presented in Table 4. The first step was
regressing sleep disturbances (the mediator) on depression (the
independent variable). Results revealed a significant
association between depression and sleep disturbances (β=
0.59, p< 0.001). The second step was regressing fatigue (the
outcome variable) on sleep disturbances (the mediator). Results
revealed a significant association between fatigue and sleep
disturbances (β = 0.68, p< 0.001). The third step was regressing
fatigue (the outcome variable) on depression (the independent
variable). Results revealed a significant association between
fatigue and depression (β = 0.48, p< 0.001). The final step was
regressing fatigue on both depression (the independent
variable) and sleep disturbances (the mediator). When sleep
disturbance was controlled, this association between the
dependent and the independent variable became no longer
significant (β = 0.12, p= 0.13). Fig. (1) shows the mediation
model of all symptoms based on the regression results. The
results indicated that sleep disturbance completely mediated
the effect of depression on fatigue. In other words, concurrent
experience of depression, fatigue and sleep disturbances by
pregnant women can be attributed to the effect of sleep
disturbances that induce depression, which in turn, induces
fatigue.
Pregnancy induces many bothersome symptoms as
experienced by pregnant women. Fatigue, depression and sleep
disturbance are commonly reported symptoms associated with
pregnancy. The experience of pregnant women of more than
one symptom together may be explained by the sickness
behavior model which suggests that the difference in symptom
experiences by pregnant women may result from the woman
ability to respond to physical and psychological stressors
exhibited as symptoms through changes in pro-and-antiinflammatory cytokines during pregnancy period [34]. The
results of this study can also be explained by the idea that
getting married and pregnant may induce a big change in the
social class of the woman. Specifically, the pregnant woman
transitioning from one social class to another is likely to
generate status-based identity uncertainty, helplessness, and
lack of freedom. This uncertainty increases the woman’s
allostatic load and induces a range of negative physical health
outcomes [35]. Allostatic load theory may explain the stressors
that pregnant women may experience and how to accommodate
them [36]. Symptom cluster experience during pregnancy may
be examined as a stressor that affects the women’s social life.
During marriage, women may move from one social class to
another which may induce stressors that are exhibited as a
cluster of symptoms affecting their quality of life [37].
Table 4. The mediation model of the symptoms.
The current study investigated three common symptoms of
pregnancy (fatigue, depression and sleep disturbances
altogether) from within the Jordanian context. The study
supports previous evidence about the influence of one
symptom on the others. However, integrating these three
symptoms has not been studied before in pregnant women,
especially when the implementation of a mediation model is
integrated. The results found strong correlations between
fatigue, depression and sleep disturbances and confirmed that
sleep disturbances had a significant mediation effect on
depression which, in turn, induces fatigue.
Model
Variables
Adjusted SE t test Standardized
R Square
value Coefficient
Sig*
Bata
Model Depression
1
0.23
0.020 6.33
0.48
Model Depression
2
Sleep
disturbance
0.47
0.021 1.51
0.12
0.13
0.29 7.71
0.61
<0.001
<0.001
SE: Standard Error.
*Significant value was drawn from the coefficients table indicating that the two
models were statistically significant (Sig<0.001) in F change and ANOVA
results.
In the current study, the pregnant women in all pregnancy
trimesters revealed a significant relationship between fatigue
and depression. Although a previous study found a weak
392 The Open Public Health Journal, 2020, Volume 13
Suleiman et al.
relationship between fatigue and depression in 113 pregnant
women in the early pregnancy period [22], pregnant women in
the majority of studies experience more fatigue and depression
levels while advancing in the pregnancy trimesters [6]. The
current study also reported a strong correlation between fatigue
and sleep disturbances. This conforms to a previous study
conducted on 650 pregnant women and indicated a significant
negative relationship between sleeping hours and fatigue [19].
Another study by Tsai et al. [7] found that naps were
significantly associated with fatigue, suggesting that longer
sleeping was associated with less fatigue. It was evident that
depression in the current study was strongly correlated with
sleep disturbance. This result is consistent with Reshadat et al.
[16], who also suggested a higher correlation (r=0.48).
Similarly, Shariat et al. [17] who used Cramer's correlation
coefficient to examine the relationship between sleep
disturbance and depression, found that depression was
significantly correlated with sleep quality in all pregnancy
trimesters. Further, another study by Nylen et al. [38]
confirmed the relationship between depression and sleep
disturbances among pregnant women which are in line with the
findings of the current study.
implementing counseling or strategies such as sole reflexology
[3]. Nursing administrators could also develop and implement
continuing education programs about symptom management to
improve sleep quality and decrease fatigue and depression
levels to improve the quality of life among pregnant women.
The mediation effect of sleep disturbance indicated that
depression could directly affect fatigue, but its impact can be
influenced by sleep disturbances. The direct effect of
depression on fatigue, however, became insignificant when the
role of sleep disturbance was added to the model. Thus, the
effect of depression on fatigue should not be justified without
understanding the effect of sleep disturbances. This suggests
that both depression and sleep disturbances can affect each
other and trigger fatigue. Therefore, sleep disturbance plays a
pivotal role in both depression and fatigue among pregnant
women. The results of this mediation model are consistent with
previous studies that reported a positive relationship between
the three symptoms of which sleep disturbance had the most
substantial contribution to fatigue development [25]. Since the
three symptoms may need to be managed simultaneously,
discovering the impact of one symptom on the others may
expedite the effectiveness of the therapeutic management and
mitigate the complexity resulting from using various modalities
in those delicate individuals.
5. LIMITATIONS
4.1. Application to Nursing
Understanding the relationship among these symptoms will
provide direction to future intervention studies to know which
symptom to focus on specifically in a symptom-management
intervention. According to the results of this study, a complete
mediation relationship of sleep disturbances on the relationship
between fatigue and depression is shown to exist. In Jordan,
there is a lack of research related to symptoms management
among pregnant women. More research is needed to fill this
gap. The current study may serve as a baseline for further
studies in the Jordanian context. Given the centrality of
pregnant women, as well as the role of sleep effect on fatigue
and depression relationship in the management of symptoms
among pregnant women in Jordan, future researchers may
conduct interventional studies using behavioral therapies to
reduce sleep disturbances and consequently reduce fatigue and
depression levels.
*The current study implemented a cross-sectional design
which is carried out at a one-time point and does not allow for
inferences over time, so the results cannot be generalized
unlike that of a longitudinal design. With cross-sectional
design, it is not possible to establish a true cause and effect
relationship in longitudinal studies considering several
demographic and sociocultural variations.
*The current study implemented a non-probability
convenience sample. The sample was pulled out from pregnant
women who were willing to participate in the study. Voluntary
participation meant that it was possible that pregnant women
who did not choose to participate differed from those who did
participate. The voluntary sampling methodology may limit the
generalizability of the findings.
*The important role of hormones on pregnant women and
the influence of hormones such as HCG, E2, PRL on
depression and fatigue was not assessed through this study as
thus, the current study recommends examining these important
variables in the future research.
Symptom cluster indicates that symptoms may occur
simultaneously with other symptoms and consequently interact
with each other; that is, two or more symptoms may occur at
the same time and serve as catalysts for each other. Pregnant
women experience more than one symptom, such as fatigue,
depression and sleep disturbances. For example, fatigue seems
considerably worse when pregnant women also have
depression or sleep disturbances.
*Further, this study has been conducted in a single setting
with minimal variation with respect to socioeconomic and
cultural properties. Future research is encouraged to evaluate
the impact of other important factors such as women’s
husbands, family members, economical situation, hygiene
factors, and security on symptom experience among pregnant
women.
The results of this study provide basic information for
nurses and midwives regarding symptom experience among
pregnant women in Jordan. Hence, nurses and midwives should
monitor pregnant women who demonstrate fatigue and
depression which may affect the women's quality of life.
Nurses may adopt standard assessment tools to assess the
symptoms and reduce the women's symptoms experience by
CONCLUSION
*Future studies should also develop a unique framework of
symptom cluster for each individual trimester rather than
generating inferences to the whole pregnancy period.
Symptom cluster is an imminent phenomenon experienced
by pregnant women. Fatigue, depression and sleep disturbances
are common symptoms that should not be understood or treated
The Open Public Health Journal, 2020, Volume 13 393
Symptom Cluster During Pregnancy
as discrete, individual, separate symptoms. Rather, each
individual symptom has a unique contribution to the other
symptoms, something that should be clinically undertaken. The
mediation role of sleep disturbance between depression and
fatigue added a new approach to the assessment and prognosis
of fatigue during pregnancy. Depression, which is viewed as
one of the main precursors for fatigue, can be heavily
influenced by sleep disturbance. Therefore, surveying sleep
disturbances can be an integral part of the routine pregnancy
follow-ups, and its impact should be investigated further in
future prospective studies.
ETHICS APPROVAL AND CONSENT TO PARTICIPATE
[6]
[7]
[8]
[9]
[10]
An IRB approval was obtained from Al-Zaytoonah
University of Jordan (IRB approval number is
2017-2016/602/11).
[11]
HUMAN AND ANIMAL RIGHTS
[12]
Not applicable.
CONSENT FOR PUBLICATION
[13]
All patients participated on a voluntary basis and gave their
informed consent.
[14]
AVAILABILITY OF DATA AND MATERIALS
The authors confirm that the data supporting the findings
of this study are available within the article.
FUNDING
[15]
[16]
None
CONFLICT OF INTEREST
The author declares no conflict of interest, financial or
otherwise.
ACKNOWLEDGEMENTS
[17]
[18]
[19]
The authors would like to acknowledge Dr Mustafa Harb
for his guidance and advice.
REFERENCES
[1]
[2]
[3]
[4]
[5]
Bai G, Korfage IJ, Groen EH, Jaddoe VW, Mautner E, Raat H.
Associations between nausea, vomiting, fatigue and health-related
quality of life of women in early pregnancy: the generation r study.
PLoS One 2016; 11(11)e0166133
[http://dx.doi.org/10.1371/journal.pone.0166133] [PMID: 27814390]
Bossuah K. Fatigue in Pregnancy. Int J Childbirth Educ 2017; 32(1):
10-2.
Shobeiri F, Manoucheri B, Parsa P, Roshanaei G. Effects of
Counselling and Sole Reflexology on Fatigue in Pregnant Women: A
Randomized Clinical Trial. J Clin Diagn Res 2017; 11(6): QC01-4.
[http://dx.doi.org/10.7860/JCDR/2017/22681.9972]
[PMID:
28764252]
Chen TY, Chou YC, Tzeng NS, et al. Effects of a selective educational
system on fatigue, sleep problems, daytime sleepiness, and depression
among senior high school adolescents in Taiwan. Neuropsychiatr Dis
Treat 2015; 11(March): 741-50.
[PMID: 25834449]
Thomas KA, Spieker S. Sleep, depression, and fatigue in late
postpartum. MCN Am J Matern Child Nurs 2016; 41(2): 104-9.
[PMID:
[http://dx.doi.org/10.1097/NMC.0000000000000213]
26909724]
[20]
[21]
[22]
[23]
[24]
[25]
Cheng C, Pickler R. Perinatal stress, fatigue, depressive symptoms,
and immune modulation in late pregnancy and one month postpartum.
Sci World J 2014; 22 (January):eCollection 2014
[http://dx.doi.org/10.1155/2014/652630]
Tsai SY, Kuo LT, Lee CN, Lee YL, Landis CA. Reduced sleep
duration and daytime naps in pregnant women in Taiwan. Nurs Res
2013; 62(2): 99-105.
[PMID:
[http://dx.doi.org/10.1097/NNR.0b013e3182830d87]
23458907]
Tsai SY, Lin JW, Wu WW, Lee CN, Lee PL. Sleep disturbances and
symptoms of depression and daytime sleepiness in pregnant women.
Birth 2016; 43(2): 176-83.
[http://dx.doi.org/10.1111/birt.12215] [PMID: 26776559]
Mindell JA, Cook RA, Nikolovski J. Sleep patterns and sleep
disturbances across pregnancy. Sleep Med 2015; 16(4): 483-8.
[http://dx.doi.org/10.1016/j.sleep.2014.12.006] [PMID: 25666847]
Rezaei E, Moghadam ZB, Nejat S, Dehghannayeri N. The impact of
sleep healthy behavior education on the quality of life in the pregnant
women with sleep disorder: A randomized control trial in the year
2012. Iran J Nurs Midwifery Res 2014; 19(5): 508-16.
[PMID: 25400680]
Rezaei E, Moghadam ZB, Saraylu K. Quality of life in pregnant
women with sleep disorder. J Family Reprod Health 2013; 7(2): 87-93.
[PMID: 24971108]
Xu X, Liu D, Zhang Z, Sharma M, Zhao Y. Sleep duration and quality
in pregnant women: a cross-sectional survey in china. Int J Environ
Res Public Health 2017; 14(7): 817.
[http://dx.doi.org/10.3390/ijerph14070817] [PMID: 28726747]
Yucel S, Yucel U, Gulhan I, Ozeren M. Sleep quality and related
factors in pregnant women. J Med Med Sci 2012; 3(7): 459-63.
Abujilban SK, Abuidhail J, Al-Modallal H, Hamaideh S, Mosemli O.
Predictors of antenatal depression among Jordanian pregnant women
in their third trimester. Health Care Women Int 2014; 35(2): 200-15.
[http://dx.doi.org/10.1080/07399332.2013.817411] [PMID: 24020729]
D’Anna-Hernandez KL, Garcia E, Coussons-Read M, Laudenslager
ML, Ross RG. Sleep moderates and mediates the relationship between
acculturation and depressive symptoms in pregnant mexican-american
women. Matern Child Health J 2016; 20(2): 422-33.
[http://dx.doi.org/10.1007/s10995-015-1840-9] [PMID: 26728897]
Reshadat S, Zakiei A, Karami J, Ahmadi E. A study of the
psychological and family factors associated with sleep quality among
pregnant women. Harv Rev Psychiatry 2018; 20(1): 17-24.
Shariat M, Abedinia N, Noorbala A, Raznahan M. The relationship
between sleep quality, depression, and anxiety in pregnant women: A
cohort study. J Sleep Sci 2018; 2(1): 20-7.
Yu Y, Li M, Pu L, et al. Sleep was associated with depression and
anxiety status during pregnancy: a prospective longitudinal study.
Arch Women Ment Health 2017; 20(5): 695-701.
[http://dx.doi.org/10.1007/s00737-017-0754-5] [PMID: 28685391]
Hall WA, Hauck YL, Carty EM, Hutton EK, Fenwick J, Stoll K.
Childbirth fear, anxiety, fatigue, and sleep deprivation in pregnant
women. J Obstet Gynecol Neonatal Nurs 2009; 38(5): 567-76.
[http://dx.doi.org/10.1111/j.1552-6909.2009.01054.x]
[PMID:
19883478]
Tsai SY, Lin JW, Kuo LT, Thomas KA. Daily sleep and fatigue
characteristics in nulliparous women during the third trimester of
pregnancy. Sleep (Basel) 2012; 35(2): 257-62.
[http://dx.doi.org/10.5665/sleep.1634] [PMID: 22294816]
Chung TC, Chung CH, Peng HJ, Tsao CH, Chien WC, Sun HF. An
analysis of whether sleep disorder will result in postpartum depression.
Oncotarget 2018; 9(38): 25304-14.
[http://dx.doi.org/10.18632/oncotarget.25219] [PMID: 29861873]
Chou FH, Lin LL, Cooney AT, Walker LO, Riggs MW. Psychosocial
factors related to nausea, vomiting, and fatigue in early pregnancy. J
Nurs Scholarsh 2003; 35(2): 119-25.
[PMID:
[http://dx.doi.org/10.1111/j.1547-5069.2003.00119.x]
12854291]
Baron RM, Kenny DA. The moderator-mediator variable distinction in
social psychological research: conceptual, strategic, and statistical
considerations. J Pers Soc Psychol 1986; 51(6): 1173-82.
[http://dx.doi.org/10.1037/0022-3514.51.6.1173] [PMID: 3806354]
Beck SL, Dudley WN, Barsevick A. Pain, sleep disturbance, and
fatigue in patients with cancer: using a mediation model to test a
symptom cluster. Oncol Nurs Forum 2005; 32(3): 542.
[http://dx.doi.org/10.1188/05.ONF.E48-E55] [PMID: 15897927]
Huang TW, Lin CC. The mediating effects of depression on sleep
disturbance and fatigue: symptom clusters in patients with
394 The Open Public Health Journal, 2020, Volume 13
[26]
[27]
[28]
[29]
[30]
[31]
[32]
hepatocellular carcinoma. Cancer Nurs 2009; 32(5): 398-403.
[http://dx.doi.org/10.1097/NCC.0b013e3181ac6248]
[PMID:
19661795]
Mendoza TR, Wang XS, Cleeland CS, et al. The rapid assessment of
fatigue severity in cancer patients: use of the Brief Fatigue Inventory.
Cancer 1999; 85(5): 1186-96.
[http://dx.doi.org/10.1002/(SICI)1097-0142(19990301)85:5<1186::AI
D-CNCR24>3.0.CO;2-N] [PMID: 10091805]
Suleiman K, Al Kalaldeh M, AbuSharour L, Yates B, Berger A,
Mendoza T, et al. Validation study of the arabic version of the brief
fatigue inventory (BFI-A). E Mediterr Health J 2019; 25(11): 784-90.
Morin C. Insomnia: Psychological assessment and management. 1st
edition ed. New York: Guilford Press 1993.
Bastien CH, Vallières A, Morin CM. Validation of the Insomnia
Severity Index as an outcome measure for insomnia research. Sleep
Med 2001; 2(4): 297-307.
[http://dx.doi.org/10.1016/S1389-9457(00)00065-4]
[PMID:
11438246]
Suleiman KH, Yates BC. Translating the insomnia severity index into
Arabic. J Nurs Scholarsh 2011; 43(1): 49-53.
[http://dx.doi.org/10.1111/j.1547-5069.2010.01374.x]
[PMID:
21342424]
Zung WW. A self-rating depression scale. Arch Gen Psychiatry 1965;
12(1): 63-70.
[http://dx.doi.org/10.1001/archpsyc.1965.01720310065008] [PMID:
14221692]
De Jonghe J, Baneke J. The Zung self-rating depression scale: a
Suleiman et al.
[33]
[34]
[35]
[36]
[37]
[38]
replication study on reliability, validity and prediction. J Psychological
Reports 1989; 64(3): 833-4.
[http://dx.doi.org/10.2466/pr0.1989.64.3.833]
Kirkby R, Al Saif A, el-din Mohamed G. Validation of an arabic
translation of the zung self-rating depression scale. Ann Saudi Med
2005; 25(3): 205-8.
[http://dx.doi.org/10.5144/0256-4947.2005.205] [PMID: 16119520]
Illi J, Miaskowski C, Cooper B, et al. Association between pro- and
anti-inflammatory cytokine genes and a symptom cluster of pain,
fatigue, sleep disturbance, and depression. Cytokine 2012; 58(3):
437-47.
[http://dx.doi.org/10.1016/j.cyto.2012.02.015] [PMID: 22450224]
Simandan D. Rethinking the health consequences of social class and
social mobility. Soc Sci Med 2018; 200(March): 258-61.
[http://dx.doi.org/10.1016/j.socscimed.2017.11.037]
[PMID:
29301638]
Simandan D. Beware of Contingency. EnvironPlan D. Environ Plann
D Soc Space 2010; 28(3): 388-96.
[http://dx.doi.org/10.1068/d2310]
Simandan D. On how much one can take: relocating exploitation and
exclusion within the broader framework of allostatic load theory.
Health Place 2010; 16(6): 1291-3.
[http://dx.doi.org/10.1016/j.healthplace.2010.08.009]
[PMID:
20813575]
Nylen KJ, Williamson JA, O’Hara MW, Watson D, Engeldinger J.
Validity of somatic symptoms as indicators of depression in
pregnancy. Arch Women Ment Health 2013; 16(3): 203-10.
[http://dx.doi.org/10.1007/s00737-013-0334-2] [PMID: 23456541]
© 2020 Suleiman et al.
This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is
available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the
original author and source are credited.