Evaluation of Sleep Quality and Its Socio-demographic Predictors in Three Trimesters of Pregnancy among Women Referring to Health Centers in Tabriz, Iran: A Cross-sectional Study

Document Type: Short Report

Authors

1 Instructor, Reproductive Health Research Center, Midwifery Department, Faculty of Nursing and Midwifery, Urmia University of Medical Sciences, Urmia, Iran

2 Professor, Midwifery Department, Faculty of Nursing and Midwifery, Social Determinants of Health Research Center, Tabriz University of Medical Sciences, Tabriz, Iran.

3 Instructor, Midwifery Department, Saveh Faculty of Medical Sciences, Saveh, Iran

4 MSc at Midwifery, Shohadaye Qom Hospital, Qom University of Medical Sciences, Qom, Iran

5 Associate Professor, Social Determinants of Health Research Center, Tabriz University of Medical Sciences, Tabriz, Iran

Abstract

This study aimed to determine sleep quality and its socio-demographic predictors regarding three trimesters of pregnancy. This cross-sectional study was conducted on 605 pregnant women referred to health centers in Tabriz, Iran, using a two-stage cluster sampling method. Data were collected using socio-demographic characteristics questionnaire and the Pittsburgh Sleep Quality Index. The mean±SD of the total sleep quality scores were estimated at 5.22±2.52, 5.82±3.07, 8.60±3.03, and 6.56±3.24 in the first, second, and third trimester, and during the whole pregnancy, respectively. Moreover, the study results showed that 81 (40.1%), 105 (53.0%), 172 (83.9%), and 358 (59.2%) mothers experienced sleep disorder in the first, second, and third trimester, and during the whole pregnancy, respectively. According to the results of this study, sleep quality predictors may help health providers identify high-risk pregnant women in terms of sleep disorder to provide them with appropriate interventional programs.

Keywords

Main Subjects


Introduction

Pregnancy is a joyful event generally. Nevertheless, remarkable physical and emotional changes occur during pregnancy (1). Even in uncomplicated pregnancies, physical and psychological changes associated with pregnancy can change women’s ability and function in their various roles and ultimately affect their quality of life (2).

Sleep disorder is a common complaint during pregnancy that can affect physiological, hormonal, vascular, and metabolic changes, including endocrine changes, such as increased progesterone, prolactin levels, and fetal size and movements, bladder distension, aperture rise, stomach discomfort, nausea, and temperature fluctuations (3). In addition, pregnant women reported that sleep disorders, especially in the third trimester, was caused by nausea, back pain, frequent urination, heartburn, leg cramps, shortness of breath, too much thinking, sadness, anxiety, and fear (4).

Studies showed that 25% and 75% of women in the first and third trimester of pregnancy experience sleep disorder, respectively (5). Despite the presence of low-cost and safe treatments (6), the prevalence of sleep disorder is probably high. The reason is that it is often considered a natural change in pregnancy or it is believed that there is no treatment for it; therefore, its treatment is not considered to be important (7).

The effect of sleep deprivation on women’s function during pregnancy is widely varied. Sleep disorders affect some women catastrophically, whereas it has no significant influences on others (8). Poor sleep quality during pregnancy may increase the symptoms of depression in the last weeks of pregnancy (9). There are also reports on poor sleep quality and its association with adverse pregnancy outcomes, including preterm labor, labor length, and birth weight (10).

In several studies, many factors are reported as predictors of sleep quality, including gestational age (11), education and economic level, number of pregnancies, number of children, different pregnancy trimesters, age of mother (12), occupational status of pregnant mothers (13), acceptance of fetal gender by the family (14), husband’s job (9) and residency in a rental home (9). These studies have often been conducted in other countries; however, a review of the medical database shows that no study has been conducted on sleep quality anddifferent trimesters of pregnancy in Iran. Moreover, there is no exact statistics on the prevalence of sleep disorders and the predictors of sleep quality during different trimesters of pregnancy in Iran. A meta-analysis suggests future research should examine various factors underlying poor sleep quality during this period (15).

In one study, it is concluded that a better understanding of the sleep quality predictors among pregnant women helps identify high-risk groups. In addition, it focused on interventional programs to be applied to these groups (16).

Given the high prevalence of sleep disorder and its adverse effects on pregnancy and childbirth process, this study aimed to determine sleep quality and its socio-demographic predictors regarding three trimesters of pregnancy among pregnant women referring to health centers in Tabriz, Iran. In this regard, healthcare professionals, such as midwives, should provide pregnant women with appropriate sleep counseling and incorporate a supportive model of sleep-related prenatal care during the whole pregnancy. In doing so, they prevent and treat sleep disorders regarding the date of pregnancy.

 

Methods

This cross-sectional study was conducted on 605 pregnant women referred to health centers and bases in Tabriz, Iran, between February 2015 and May 2016. The sample size was determined based on the following criteria: the confidence interval of 95%, prevalence rates of 25%, 50%, and 75% for sleep disorder in the first, second, and third trimester, respectively (5), error accepted around the ratio (d) of 0.1, and the design effect of 2. As a result, the estimated sample sizes for the first and third trimester were 145 and 193 for the second trimester.

The inclusion criteria in the study were: 1) residency in Tabriz, 2) low-risk singleton pregnancy, 3) living with husband at the time of the study, 4) access to phone calls, and 5) no night shift.

The data were collected using a socio-demographic characteristics questionnaire and the Pittsburgh Sleep Quality Index (PSQI). Socio-demographic characteristics questionnaire includes items on the mother’s age (17), height, weight (18), education level (12), and occupational status  (13). Moreover, it elicited information about husband’s education level, job, income adequacy (12), along with abortion history, fetal gender based on ultrasound, and the parent’s interest in the fetal gender (14). The validity of this questionnaire was confirmed through the face and content validity.

The PSQI is a self-report questionnaire that assesses sleep quality during the last 4 weeks. This questionnaire investigates seven components, including subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbances, use of sleeping medications, and daytime dysfunction. The scores for each scale in this questionnaire range from 0 to 3. The sum of the mean scores for these seven components makes the total score of the questionnaire ranging from 0 to 21. The higher the score is, the lower the sleep quality will be. A total score above 5 indicates poor sleep quality.

The reliability of this questionnaire was estimated at 0.83 and the questionnaire developers confirmed the appropriate level of this instrument with a sensitivity and specificity of 89.6% and 86.5%, respectively, in the experimental group, compared to the control one (19). In addition, this questionnaire was employed in a study conducted on pregnant women in Tabriz, Iran (920).

In this study, the reliability was confirmed through the internal consistency, and Cronbach’s alpha was estimated at 0.84. The sampling was performed through a two-stage cluster sampling method. At first, one-third of all 60 health centers and 25 health bases were randomly selected using the website www.random.org. Then, the list of eligible pregnant women was prepared for each selected center or bases.

Subsequently, a relative number of samples for each center and bases was calculated and randomly determined. The selected pregnant women were contacted by phone and invited to participate in the study. After the visit, the participants were first evaluated in terms of demographic information and inclusion and exclusion criteria. If the participants met the inclusion criteria, they would be provided with comprehensive information about the reasons to conduct the research, the research benefits and results, the confidentiality of the information, and the research process. 

Finally, 202, 198, and 205 pregnant women completed the questionnaire during the first, second, and third trimester of pregnancy, respectively. The study protocol was approved by the Ethics Committee of Tabriz University of Medical Sciences, Tabriz, Iran (Code: Tbzmed.Rec.1392.244). Informed written consent was obtained from all participants. Moreover, the confidentiality of the data and their anonymity, along with the objectives of the study and the way to access the results were emphasized within this

Data were analyzed in SPSS software (Version 21) through descriptive statistics including frequency, percentage, mean, and standard deviation, to describe the participants’ socio-demographic characteristics and sleep quality. Normality of quantitative data was measured using Skewness and Kurtosis. Furthermore, one-way ANOVA was utilized to compare the total sleep quality score regarding three trimesters of pregnancy. Furthermore, bivariate tests, including independent t-test, and one-way ANOVA were used to determine the relationship between sleep quality and socio-demographic characteristics. Finally, the independent variables with a p-value of less than 0.05 in bivariate tests were entered into the multiple linear regression model.

 

Results

In total, 605 pregnant women were studied from February 2015 to May 2016. The mean±SD age and BMI of the participants were 27.08±5.18 years and 23.89±4.04 kg/m2, respectively. With regard to the education level, about half of the participants (47.4%, n=287) were under diploma and the other half (52.6%, n=318) had a diploma and academic degree. In terms of the occupational status, about 90% of the respondents were housewives (n=547). About half of the participants' spouses (47.3%, n=286) were under diploma and the rest (52.7%, n=319) had a diploma and academic degree.

In terms of the residency status, about one-third of the participants (30.4%, n=184) lived in their personal home and 39 % of them (n=236) lived in a rental home. About two thirds (60.3%, n=125) reported earning relatively adequate family income. According to ultrasound scans, 45% (n=272) of the fetuses were male and 90.6% of the mothers (n=548) and 88.9% of the fathers (n=538) were satisfied with the fetal gender (Table 1).

 

 

 

 

Table 1. Socio-demographic characteristics of the participants (n= 605)

 

Characteristic

First

trimester

* Number (%)

Second trimester

* Number (%)

Third

trimester

* Number (%)

Characteristic

First

trimester

* Number (%)

Second trimester

* Number (%)

Third trimester

* Number (%)

n= 202

n=198

n=205

n= 202

n=198

n=205

Age (years)

 

 

 

Body mass index (kg/m2)

 

 

Mean±SD**

27.86±(5.15)

27.20±(5.68)

26.18±(4.54)

Mean±SD**

24.87±4.33

23.89±4.01

22.91±3.51

Gravid

 

 

 

Pregnancy status

1

87 (43.1)

94 (47.5)

123 (60.0)

Wanted pregnancy

173 (85.6)

179 (90.4)

186 (90.7)

2

43 (21.3)

60 (30.3)

62 (30.2)

Unwanted pregnancy

29 (14.4)

19 (9.6)

19 (9.3)

≥3

72 (35.6)

44 (22.2)

20 (9.8)

Husband’s Education level

 

 

Education level

 

 

 

Illiterate

---

---

---

Illiterate

---

4 (2.00)

---

Elementary school

33 (16.3)

24 (12.1)

29 (14.1)

Elementary school

32 (15.8)

28 (14.1)

32 (15.6)

Secondary school

49 (24.3)

47 (23.7)

48 (23.4)

Secondary school

28 (13.9)

39 (19.7)

37 (18.0)

High school

12 (5.9)

25 (12.6)

19 (9.3)

High school

31 (15.3)

21 (10.6)

35 (17.1)

Diploma

45 (22.3)

50 (25.3)

68 (33.2)

Diploma

61 (30.2)

54 (27.3)

42 (20.5)

University

63 (31.2)

52 (26.3)

41 (20.0)

University

50 (24.8)

52 (26.3)

59 (28.8)

Husband’s Job

 

 

 

Job

 

 

 

Clerk

51 (25.2)

49 (24.7)

25 (12.2)

Housewife

183 (90.6)

169 (85.4)

195 (95.1)

Worker

40 (19.8)

63 (31.8)

67 (32.7)

Employed

11 (5.4)

23 (11.6)

---

Shopkeeper

18 (8.9)

20 (10.1)

34 (16.6)

Work at ome

8 (4.0)

6 (3.0)

10 (4.9)

Others****

91 (45.0)

63 (31.8)

79 (38.5)

Residence

 

 

 

Abortion history

47 (23.3)

41 (20.7)

24 (11.7)

Personal

63 (31.2)

62 (31.3)

59 (28.8)

Sufficiency of income for expenses

Rental

74 (36.6)

71 (35.9)

91 (44.4)

Completely   Sufficient

44 (21.8)

49 (24.7)

32 (15.6)

Father’s parent’s home

63 (31.2)

55 (27.8)

53 (25.9)

Fairy sufficient

119 (58.9)

112 (56.6)

134 (65.4)

Mother’s parent’s home

---

5 (2.5)

1 (0.5)

Insufficient

39 (19.3)

37 (18.7)

39 (19.0)

Others***

2 (1.0)

5 (2.5)

1 (0.5)

Fetal gender

 

 

 

Woman’s interest in fetal gender

Female

43 (21.3)

71 (35.9)

105 (51.2)

Yes

178 (88.1)

185 (93.4)

185 (90.2)

Male

61 (30.2)

111 (56.1)

100 (48.8)

No

24 (11.9)

13 (6.6)

20 (9.8)

Unknown

98 (48.5)

16 (8.1)

---

Spouse’s interest in fetal gender

---

---

---

---

Yes

171 (84.8)

181 (91.4)

186 (90.7)

---

---

---

---

No

31(15.3)

17 (8.6)

19 (9.3)

---

---

---

---

*Valid percent has been reported in all the variables because of missed data.

**All data indicate the number (percent) unless they have been specified.

*** Others indicate residence in the relative house and corporate house.

**** Other includes occupations, such as building painter and farmer.

The mean±standard deviation of the total sleep quality scores were 5.22±2.52, 5.82±3.07, 8.60±3.03, and 6.56±3.24 in the first, second, and third trimester, and during the whole pregnancy ranged from 0 to 21, respectively. According to the results obtained from one-way ANOVA, there was also a significant difference between the different trimesters and total sleep quality scores (P<0.001). Moreover, in the first, second, and third trimester, and during the whole pregnancy, the mean±SD scores of the component of subjective sleep quality were 0.84±0.69, 0.94±0.79, 1.88±0.79, and 1.23±0.89, respectively.

 In addition, with regard to the same period, the mean±SD scores of the component of sleep latency were 1.22±0.94, 1.32±0.96, 1.93±0.96, and 1.50±0.96. In addition, the mean±SD scores of the component of sleep duration were 0.33±0.72, 0.36±0.75, 0.34±0.74, and 0.35±0.74. The mean±SD scores of the component of sleep disturbances were estimated at 1.21±0.56, 1.33±0.56, 1.91±0.5,1 and 1.49±0.62. The mean±SD scores of the component of the use of sleeping medications were obtained at 0.02±0.14, 0.04±0.18, 0.00±0.00, and 0.02±0.13. The mean±SD scores of the component of daytime dysfunction were 1.10±0.74, 1.27±0.73, 1.98±0.78, and 1.46±0.84.

The study results also showed that  81 (40.1%), 105 (53.0%), and 358 (59.2%), 172 (83.9%) of mothers had sleep disorders in the first, second, and third trimester, and during the whole pregnancy, respectively.

According to the bivariate test results, there was a significant correlation between the total sleep quality scores in the first trimester and the mother's age (P=0.007), education level (P=0.008), occupational status and interest in current pregnancy (P=0.001), and fetal gender on the basis of ultrasound scans (P=0.04).

With respect to the multiple linear regression model by adjusting the other variables, a significant association was observed between total sleep quality scores and variables, such as mother's age, education level, job and interest in the current pregnancy, and fetal gender in the first trimester. This association was able to predict 19.5% of sleep quality variance among pregnant women in the first trimester.

Meanwhile, based on the bivariate test results, there was no significant difference between the total sleep quality scores and socio-demographic characteristics in the second trimester (P<0.05). Furthermore, a significant correlation was observed between the total sleep quality scores and body mass index (P<0.001), education (P=0.004), husband’s occupation (P=0.01), and the number of pregnancy (P=0.007) in the third trimester.

With regard to the multiple linear regression model by adjusting the other variables, there was a significant relationship between the total sleep quality scores and the variables, such as BMI, and husband’s education level and occupation. This relationship was able to predict 19.1% of sleep quality variance among pregnant women in the third trimester.

According to the bivariate test results, the total sleep quality scores were significantly correlated with gestational age (P<0.001), place of residence (P=0.01), and fetal gender based on ultrasound scans (P<0.001) during the whole pregnancy, regardless of the pregnancy trimesters. With regard to the

 

Table 2. Relationship of socio-demographic characteristics with sleep quality in pregnant women based on the bivariate test and multiple linear regression model

Variables

Bivariate test results

 

 

Multivariate linear regression results

Mean ±SD

P

 

 

β (95% CI)

P

 

First trimester) n= 202(

 

Age

 

0.007

 

Age

 

 

 

<18

3.0±0.6

 

 

<18

0.3 (-2.6 to 3.1)

0.80

 

18-25

4.8±2.5

 

18-25

0.9 (-0.4 to 2.3)

0.18

 

25-30

5.7±2.5

 

25-30

1.9 (0.6 to 3.2)

0.005

 

>30

4.2±2.3

 

>30

Reference

 

 

Education level

0.008

 

Education level

Elementary school

5.8±2.8

 

 

Elementary school

-0.2 (-1.4 to 0.9)

0.66

 

Secondary school

5.7±2.3

 

Secondary school

-1.7 (-2.9 to -0.6)

0.002

 

High school

3.9±2.8

 

High school

-0.6 (-1.5 to 0.3)

0.19

 

Diploma

5.0±2.1

 

Diploma

0.3 (-1.6 to 1.2)

0.89

 

University

5.7±2.4

 

University

Reference

 

 

Job

 

0.005

 

Job

 

Housewife

5.2±2.5

 

 

Housewife

1.8 (0.3 to 3.3)

0.01

 

Employed

7.0±3.2

 

Employed

3.3 (1.1 to 5.5)

0.004

 

Work at home

11.0±4.2

 

Work at home

Reference

 

 

Pregnancy status                          0.001

 

Pregnancy status

 

Wanted pregnancy

5.4±2.6

 

 

Wanted pregnancy

1.8 (0.9 to 2.8)

<0.001

 

Unwanted pregnancy

4.0±1.8

 

Unwanted pregnancy

Reference

 

 

Fetal gender

0.04

 

Fetal gender

 

Male

5.6±2.5

 

 

Male

0.7 (-0.2 to 1.5)

0.11

 

Female

5.7±3.0

 

Female

1.6 (0.7 to 2.4)

<0.001

 

Unknown

4.8±2.2

 

Unknown

Reference

 

 

Third trimester (n=205)

 

Body Mass Index (kg/m2)

<0.001

 

Body Mass Index (kg/m2)

 

<19.8

7.1±1.7

 

 

<19.8

-3.0 (-4.8 to -1.1)

0.001

 

19.8-26

8.4±3.1

 

19.8-26

-1.5 (-3.2 to 0.1)

0.06

 

26-29

11.0±3.1

 

26-29

0.8 (-1.2 to 2.8)

0.41

 

>30

10.6±1.7

 

>30

Reference

 

 

Education level

0.004

 

Education level

 

Elementary school

9.5±3.0

 

 

Elementary school

1.0 (-0.4 to 2.4)

0.16

 

Secondary school

7.7±3.1

 

Secondary school

-0.5 (-1.8 to 0.7 )

0.39

 

High school

9.2±2.4

 

High school

0.7 (-0.5 to 2.0)

0.26

 

Diploma

9.4±3.8

 

Diploma

1.3 (0.1 to 2.4)

0.03

 

University

7.8±2.4

 

University

Reference

 

 

Husband’s Job

0.01

 

Husband’s Job

 

Clerk

8.8±3.1

 

 

Clerk

0.5 (-0.7 to 1.8)

0.41

 

Worker

9.5±2.9

 

Worker

1.5 (0.5 to 2.4)

0.003

 

Shopkeeper

7.8±2.7

 

Shopkeeper

0.1 (-1.1 to 1.2)

0.92

 

Others*

8.1±3.1

 

Others*

Reference

 

 

Parity

 

0.007

 

Parity

 

 

 

1

8.2±2.9

 

 

1

-1.0 (-2.4 to 0.5)

0.19

 

2

9.0±3.2

 

2

-1.2 (-2.7 to 0.3)

0.12

 

≥3

11.2±2.0

 

≥3

Reference

 

 

Whole pregnancy (n= 605)

 

Gestational age

<0.001

 

Gestational age

 

 

First trimester

5.2±2.5

 

 

First trimester

-3.0 (-3.6 to -2.3)

<0.001

 

Second trimester

5.8±3.1

 

Second trimester

-2.8 (-3.3 to -2.2)

<0.001

 

Third trimester

8.6±3.0

 

Third trimester

Reference

 

 

Residence

0.01

 

Residence

 

 

Personal

6.5±3.5

 

 

Personal

-3.6 (-5.6 to -1.5)

0.001

 

Rental

6.8±3.2

 

Rental

-3.5 (-5.5 to -1.4)

0.001

 

Mother’s parent’s home

8.2±3.0

 

Mother’s parent’s home

-1.6 (-4.7 to 1.4)

0.28

 

Father's parent's home

6.1±3.0

 

Father's parent's home

-3.9 (-6.0 to -1.9)

<0.001

 

Others**

9.4±2.3

 

Others**

Reference

 

 

Fetal gender

 

<0.001

 

Fetal gender

 

 

 

Male

6.6±3.3

 

 

Male

0.451 (-0.3 to 1.2)

0.22

 

Female

7.3±3.2

 

Female

0.9 (0.2 to 1.7)

0.01

 

Unknown

5.0±3.2

 

Unknown

Reference

 

 

*Others include residence in relative’s home and corporate houses.

** Others include jobs, such as building painter and farmer.

First trimester: Adjusted R2= 0.195; Third trimester: Adjusted R2= 0.191; Whole of pregnancy: Adjusted R2= 0.228

 One-way ANOVA  T-test

multiple linear regression model by adjusting the other variables, a significant relationship was observed between the total sleep quality scores and all three variables. This association was able to predict 22.8% of sleep quality variance among pregnant women during the pregnancy (Table 2).

 

Implications for practice       

According to the results of this study, it is concluded that women suffer from high rates of sleep disorder during pregnancy. Moreover, the factors predicting the quality of sleep in pregnant women include some variables, such as age, education level, women’s and husband’s job, pregnancy status, fetal gender, BMI, gestational age, and place of residence. These results may help health providers identify high-risk pregnancy for a sleep disorder and provide appropriate interventional programs for them. It seems that paying more attention to these factors and not ensuring the routine care running in health centers can improve the quality of sleep as an important factor in predicting pregnancy outcomes. Early diagnosis and treatment of sleep disorders can help reduce complications during pregnancy, increase postpartum maternal health, and improve the short-term and long-term outcomes for infants and children.

 

Acknowledgment

This article is extracted from a part of a research project (ethics code: ir.tbzmed.rec.1392.244). Hereby, the authors express their gratitude to the Research Deputy of Tabriz University of Medical Sciences, Tabriz, Iran, for funding. The authors would also like to sincerely thank all the pregnant women who patiently took part in this study.

 

Conflict of Interest

The authors declare that there is no conflict of interest.

 

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