Sleep accounts for one third of the average human lifetime. It is a basic human need and as important to good health as diet and exercise (Krishnan & Collop, 2006; National Sleep Foundation, 2013). For pregnant women, adequate sleep is essential not only to restore physical and mental agility but also to facilitate fetal–placental growth and health (Chang, Pien, Duntley, & Macones, 2010; Lee & Gay, 2004). However, sleep disturbances are a common complaint among pregnant women (Tsai, Kuo, Lai, & Lee, 2011). Studies have found that sleep disturbance prevalence during pregnancy ranges between 26% and 78% (Facco, Kramer, Ho, Zee, & Grobmanl, 2010b; Ko, Chang, & Chen, 2010; National Sleep Foundation, 2013). The prevalence of sleep disturbance gradually increases with pregnancy duration (Hung, Tsai, Ko, & Chen, 2013). Pregnancy-associated sleep disorders are a widely recognized health issue (American Academy of Sleep Medicine, 2005) because of pregnancy-related physical discomforts (e.g., nausea, lower back pain, leg cramps, and fetal movement); frequent micturation; and potential influences of psychosocial factors such as depressed states, inadequate social support, higher stress, and anxiety related to fetal integrity or labor pain (Ko et al., 2010; Lee, Baker, Newton, & Ancoli-Israel, 2008; Lee, Lam, & Lau, 2007; Swanson, Pickett, Flynn, & Armitage, 2011).
Sleep disturbance has been defined as any change or variation in an individual’s normal sleep pattern because of difficulties falling asleep, midsleep interruptions, or early awakenings (Evans, Dick, & Cark, 1995; Lee & Dejoseph, 1992). Continual disturbance of sleeping patterns may negatively impact maternal and fetal health (Chang et al., 2010; Lee et al., 2008). Sleep disturbances have been positively correlated with norepinephrine and cortisol levels during the second and third trimesters (Field et al., 2007). Furthermore, maternal norepinephrine and cortisol levels have been negatively correlated with fetal weight; both biomarkers are significant determinants of fetal weight, which means that elevated norepinephrine/cortisol levels in an expecting mother correlate with an elevated risk of giving birth to a low-birth-weight infant (Diego et al., 2006). Possible pathophysiological mechanisms linking sleep disturbances and adverse pregnancy outcomes have also been discussed by Okun, Hall, and Coussons-Read (2007). They examined the association between interleukin-6 (IL-6) and sleep disturbances in 19 women during the midstage and late stage of pregnancy. Using the Pittsburgh Sleep Quality Index and sleep diaries to measure sleep disturbances, the study reported a positive correlation between sleep disturbance frequency and IL-6 levels. IL-6 is an inflammatory cytokine linked to labor preceding preterm births (Chang et al., 2010). It is possible that sleep disturbances increase systemic inflammation and decrease placental perfusion, which has been linked to adverse pregnancy outcomes such as preeclampsia, intrauterine growth retardation, and preterm delivery (Okun, Roberts, Marsland, & Hall, 2009). Furthermore, Okun et al. (2012) reported that, although poor sleep quality may contribute to the risk of preterm birth, the effects of this factor were attenuated after controlling for traditional risk factors. It has also been evidenced that short sleep duration (nighttime sleep < 7 hours) and frequent snoring (≥3 times per night) increase maternal glucose intolerance, associated with a higher incidence of gestational diabetes (Facco, Grobman, Kramer, Ho, & Zee, 2010a). Similar findings have been reported by Micheli et al. (2011), who assessed the sleep habits of 1,091 women with singleton pregnancies during their third trimester as well as their birth outcomes. They found that sleep-deprived women (≤5 hours of sleep) were at a higher risk of preterm births (<37 gestational weeks). Moreover, obstructive sleep apnea has been found to predispose pregnant women to increased risks of low birth weight, preterm birth, small-for-gestational-age infants, cesarean section, and preeclampsia (Chen et al., 2012).
Using a longitudinal study on 35 nulliparous women at or after 38 weeks of gestation, Beebe and Lee (2007) evaluated the association between self-reported pain and fatigue in early labor before admission using wrist actigraphy monitors. They found that women with less nighttime sleep before hospitalization reported a higher perception of pain in early labor. According to some previous studies, women who sleep less than 6 hours at night during the last month of pregnancy have significantly longer average labor durations (29 vs. <21 hours, p = .001) and a higher incidence of cesarean delivery (<6 hours, 36.8%; 6–6.9 hours, 34.2%; and ≥7 hours, 10.8%; p = .014; Lee & Gay, 2004), whereas sleeping more than 8 hours or having self-perceived “refreshing” sleep have been associated with shorter labor durations (Zafarghandi et al., 2012). However, Evans et al. (1995) reported finding no relationship between sleep quality 2 weeks before the onset of labor and length of labor, type of delivery, or maternal perceptions of labor.
Polysomnography (PSG) is generally regarded as the gold standard for accurately and objectively measuring sleep quality, and actigraphy is regarded as the next-best measure (de Souza et al., 2003). Although several studies have used these methods to monitor sleep disturbances during pregnancy, their small sample sizes limit generalizability. In the absence of PSG or actigraphy data, self-reported data have been the most widely used approach to measuring sleep disturbance (Okun et al., 2009). Postsleep questionnaires are a potentially more accurate instrument for detecting transient and persistent sleep disturbances. The Pittsburgh Sleep Quality Index (PSQI) is a postsleep instrument that has shown high reliability for evaluating sleep quality and sleep disturbance (Buysse, Reynolds, Monk, Berman, & Kupfer, 1989). Questionnaires represent a cost-effective, easy-to-implement alternative to PSG and actigraphy instruments.
This study uses a model of disrupted sleep (Okun et al., 2012) that presumes sleep disturbances may result in adverse obstetric outcomes. Our prior study (Hung et al., 2013) found sleep disturbance to be prevalent among Taiwanese pregnant women and that the influences of these disturbances on maternal and neonatal health require further research. Therefore, this study was designed to determine whether prenatal sleep disturbance is associated with adverse obstetric outcomes in Taiwan. We conducted a follow-up study of a cohort of 248 Taiwanese pregnant women screened using the PSQI to examine the possible effects of poor sleep quality on obstetric outcomes.
This study used a prospective design to examine the association between poor sleep quality during the second or third trimester of pregnancy and obstetric–neonatal outcomes.
Setting and Samples
Participants in this study were women receiving prenatal care at two teaching hospital clinics in southern and central Taiwan between October 2007 and June 2008. Participant inclusion criteria included (a) over 20 years old, (b) in the 13th–38th weeks of a singleton gestation, and (c) willing to participate.
A demographic data form addressed demographic and obstetric variables. Socioeconomic status was estimated using the index of status position, which integrates education and occupation information to classify the socioeconomic status of nuclear families into five levels (Lin, 1978). In this study, levels 1 and 2 were categorized as upper class, level 3 was categorized as middle class, and levels 4 and 5 were categorized as lower class. Participants rated their level of marital satisfaction as satisfied (1), acceptable (2), or dissatisfied (3). Gestational age was divided by trimester based on participants’ last menses: ≤12 weeks (first trimester), 13–28 weeks (second trimester), and ≥29 weeks (third trimester).
Sleep quality was quantified using the seven-component PSQI (Buysse et al., 1989). Each PSQI item was scored using a whole number from 0 (better) to 3 (worse); summed scores for the seven components provided the global PSQI score (range = 0–21), with higher scores indicating poorer sleep quality. A global score above 5 yielded a diagnostic sensitivity of 90% and specificity of 87% in distinguishing good sleepers from poor sleepers (Buysse et al., 1989). Jomeen and Martin (2007) tested the PSQI on 148 pregnant women to determine the usefulness of this measure and found internal consistency and convergent/divergent validities to be good. The Cronbach’s α for the Chinese version PSQI was .73 (Lee et al., 2008). In this study, internal consistency for the Chinese PSQI was adequate, with a Cronbach’s α of .75. Medical records containing information on the obstetric outcome (type of delivery, use of epidural anesthesia, or instrument-assisted delivery) and the neonatal outcome (incidence of prematurity, birth weight, and Apgar score) were obtained from participating hospitals.
The institutional review boards of participating hospitals approved the study protocol. Two research assistants were trained on required data collection techniques. Pregnant women were approached in the prenatal clinics of participating institutions. Research assistants explained the study’s objectives to each woman, assured participants of anonymity, and guaranteed that all personal information would remain confidential. Two hundred ninety-eight women meeting the study criteria agreed to participate and completed the demographic data form and PSQI. Two hundred forty-eight (83.2%) participants delivered their babies at the participating hospitals, and their medical records containing obstetric data were obtained and reviewed.
The SPSS software for Windows 17.0 (SPSS, Inc., Chicago, IL, USA) was used for all descriptive and inferential statistical analyses. The χ2, Fisher’s exact, and independent t tests were used to examine differences between the two study groups with respect to participant characteristics and obstetric data. A value of p < .05 was considered statistically significant.
Childbirth data were obtained from a valid sample of 248 pregnant women between 21 and 41 years (mean = 31.6 years, SD = 3.6 years), with 128 (51.6%) in the second (13–28 gestational weeks) trimester and 120 (48.4%) in the third (≥29 gestational weeks) trimester. The PSQI score was used to assign each participant into one of the two groups: the good-sleep-quality group (PSQI ≤ 5) and the poor-sleep-quality group (PSQI > 5). Table 1 shows the incidence of poor sleep quality as significantly higher among unemployed participants than among currently employed participants, regardless of pregnant trimester (second trimester, χ2 = 7.888, p = .005; third trimester, χ2 = 4.611, p = .032). Second-trimester participants with poor sleep quality reported significantly lower marital satisfaction than those with good sleep quality (t = −2.356, p = .020). No other significant difference was found in the distribution of demographic variables.
Overall, 153 participants (61.69%) self-reported as poor sleepers: 74 of 128 (57.8%) in the second trimester and 79 of 120 (65.8%) in the third trimester. Obstetric data from medical records during the immediate postpartum period pertaining to the general health of the mother–infant dyads were reviewed. As shown in Table 2, second-trimester poor sleep quality was not significantly associated with any obstetric or neonatal outcome studied. However, third-trimester poor sleep quality was significantly associated with vacuum-assisted delivery (χ2 = 4.789, p = .029) and not significantly associated with the other observed obstetric and neonatal outcomes.
In the current study, 62% of participants experienced some form of sleep disturbance. Unemployed women reported experiencing significantly more sleep disturbance than those working full time. This result supports the findings of a nationwide survey in the United Kingdom, which found that women not engaged in paid employment had poorer sleep quality than their employed peers (American Academy of Sleep Medicine, 2005). This finding partially echoes the result of Matsuaki, Haruna, Ota, Murayama, and Murashima (2011), who reported that pregnant Japanese women who stopped working during their pregnancy had lower mental health scores than those who continued to work. There are several potential explanations for the association between women’s sleep quality and employment. First, low socioeconomic status is commonly linked to poor health and living in disadvantaged socioeconomic circumstances (Arber, Bote, & Meadows, 2009). Therefore, women who are unemployed and economically inactive may be more likely to report sleep problems. Second, occupation-related networks potentially provide a forum for pregnant women to share sleep disturbance experiences with female colleagues and receive information, emotional support, and resources to help deal with the problem. Our study did not examine the proposition by Arber et al. that higher prevalence of sleep disturbance among unemployed women may be confounded by poor physical and mental health. On the basis of the identified positive correlation between nonemployment and sleep disturbance, we suggest that healthcare providers assess the sleep patterns and health status of prenatal women who are economically disadvantaged and tailor appropriate interventions/education programs.
In this study, second-trimester participants with poor sleep quality perceived lower marital satisfaction than those with good sleep quality. During pregnancy, poor sleepers were more likely to be less happy with their husbands than good sleepers, which may or may not be related to pregnancy itself. The husbands of pregnant women with poor sleep quality were not able to play a supportive role during this unique role transition stage. Emotional and instrumental supports are particularly important during the prenatal period because of the physical and emotional demands of pregnancy. Our study echoes the finding of a previous report that lack of meaningful support from one’s spouse may relate to prenatal sleep disturbance (Nomura, Yamaoka, Nakaoa, & Yano, 2010). Of note, husbands/partners are the primary sources of instrumental and emotional support for prenatal women (Warren, 2005), whereas nurses are the primary sources of professional health information. On the basis of this finding, a supportive model of prenatal care that includes reinforcing/enhancing spousal support is needed.
Contrary to the findings of Lee and Gay (2004), we found no association between prenatal sleep disturbance and mode of delivery. That previous study had collected objective data on weekday sleep quantity using 48-hour wrist actigraphy and subjective data on sleep quality using sleep logs and a general sleep disturbance scale from 131 primiparous prenatal women. They found a positive correlation between sleep disruption and the incidence of cesarean delivery. This contradictory finding may be because of significant differences between the studies in terms of participants’ parity, gestational age, and sleep assessment timing.
The findings of the current study partially concur with those of Evans et al. (1995), who investigated the sleep quality of 99 pregnant women 2 weeks before the onset of labor and reported no correlation between poor sleep quality and length of labor, type of delivery, or maternal perceptions of labor. The negative findings led the authors to question the impact of prenatal sleep disturbances on the progress of labor and elevated numbers of cesarean sections. Furthermore, the lack of significant correlation between sleep quality and labor outcomes may be because of the low variance on questions concerning sleep quality and overall expectations of labor. Our study extended these findings by examining sleep quality in a different trimester and studying additional outcome indicators. Although poor sleep quality detected during the second trimester was not associated with any obstetric outcomes, a positive association between poor sleep quality detected during the third trimester and vacuum-assisted delivery was identified.
Notably, we found that poor sleep quality during the third trimester may be associated with an increased risk of vacuum-assisted delivery. We further examined and found no significant difference in newborn birth weight between the vacuum-assisted delivery group and the vaginal delivery group (t = 0.385, p = .701). Therefore, it is reasonable to suppose that maternal exhaustion was more important than large fetus size as an indicator for vacuum-extractor use in this study. Disturbed sleep reduces the ability of the body to reach and maintain deeper levels of rest and recovery, leading to increased fatigue and decreased energy (Beebe & Lee, 2007). Fatigue may influence a woman’s ability to endure labor pain and sustain the intraabdominal force necessary for maternal pushing and bearing down to supplement uterine contractions and successfully deliver the fetus. We partially echo the argument that many pregnancy-related complications become manifest during the latter half of pregnancy, at which prolonged or worsened sleep disturbances may impact obstetric outcomes (Facco et al., 2010b). Women experiencing sleep disturbances later in their pregnancy may be more fatigued and thus require vacuum-assisted delivery, a potentially dangerous procedure for both mothers and neonates. Maternal risks include perineal laceration and anal sphincter damage; fetal risks include caput succedaneum, neonatal intracranial trauma, retinal hemorrhaging, jaundice, cephalhematoma, and subarachnoid hemorrhaging (Simonson et al., 2007; Wen et al., 2001). Thus, health professionals should focus greater attention on improving sleep quality in prenatal women as early as possible to further reduce the incidence of vacuum-assisted delivery and improve maternal and infant health-related quality of life.
Study rigor was enhanced by our review of medical record data on obstetric outcomes. Self-report measures of sleep are useful for obtaining perceptions of sleep quality and quantity and are retrospective in nature. However, the use of a convenience sample in this study limited the generalizability of findings. In addition, the cross-sectional approach used was unable to detect changes in sleep quality over time.
To our knowledge, this is the first study reporting the finding that women’s poor sleep quality during the third trimester is a risk factor for vacuum-assisted delivery. The findings of this study contribute to our understanding of the impact of prenatal poor sleep quality on birth outcomes. Interestingly, employed women in this study had a lower prevalence of prenatal sleep disturbance than unemployed women. There appears to be a relationship between sleep disturbance during the third trimester and vacuum-assisted delivery. It is important to detect sleep disturbances and provide proactive sleep counseling to help pregnant women adjust to the psychosocial and physiological transitions of motherhood. Further research is recommended that uses a longitudinal study design and a larger sample size to follow up on postpartum health status and changes in sleep quality over each trimester and then test for further significant relationships with obstetric outcome variables.
American Academy of Sleep Medicine. (2005). International classification of sleep disorders, revised: Diagnostic and coding manual. Chicago, IL: Author.
Arber S., Bote M., Meadows R. (2009). Gender and socio-economic patterning of self-reported sleep problems in Britain. Social Science & Medicine, 68 (2), 281–289. doi:10.1016/j.socscimed.2008.10.016
Beebe K. R., Lee K. A. (2007). Sleep disturbance in late pregnancy
and early labor. Journal of Perinatal & Neonatal Nursing, 21 (2), 103–108. doi:10.1097/01.JPN.0000270626.66369.26
Buysse D. J., Reynolds C. F. III, Monk T. H., Berman S. R., Kupfer D. J. (1989). The Pittsburgh sleep quality
index: A new instrument for psychiatric practice and research. Psychiatry Research, 28 (2), 193–213.
Chang J. J., Pien G. W., Duntley S. P., Macones G. A. (2010). Sleep deprivation during pregnancy
and maternal and fetal outcomes: Is there a relationship? Sleep Medicine Review, 14 (2), 107–114. doi:10.1111/j.1365-2702.2007.02064.x
Chen Y. H., Kang J. H., Lin C. C., Wang I. T., Keller J. J., Lin H. C. (2012). Obstructive sleep apnea and the risk of adverse pregnancy
outcomes. American Journal of Obstetrics & Gynecology, 206 (2), 136e1–136e5. doi:10.1016/j.ajog.2011.09.006
de Souza L., Benedito-Silva A. A., Pires M. L., Poyares D., Tufik S., Calil H. M. (2003). Further validation of actigraphy for sleep studies. Sleep, 26 (1), 81–85.
Diego M. A., Jones N. A., Field T., Hernandez-Reif M., Schanberg S., Kuhn C., Gonzalez-Garcia A. (2006). Maternal psychological distress, prenatal cortisol, and fetal weight. Psychosomatic Medicine, 68 (5), 747–753. doi:10.1097/01.psy.0000238212.21598.7b
Evans M. L., Dick M. J., Cark A. S. (1995). Sleep during the week before labor: Relationship to labor outcomes. Clinical Nursing Research, 4 (3), 238–252.
Facco F. L., Grobman W. A., Kramer J., Ho K. H., Zee P. C. (2010a). Self-reported short sleep duration and frequent snoring in pregnancy
: Impact on glucose metabolism. American Journal of Obstetrics & Gynecology, 203 (2), 142e1–142e5. doi:10.1016/j.ajog.2010.03.041
Facco F. L., Kramer J., Ho K. H., Zee P. C., Grobman W. A. (2010b). Sleep disturbances in pregnancy
. Obstetrics & Gynecology, 115 (1), 77–83. doi:10.1097/AOG.0b013e3181c4f8ec
Field T., Diego M., Hernandez-Reif M., Figueiredo B., Schanberg S., Kuhn C. (2007). Sleep disturbances in depressed pregnant women and their newborns. Infant Behavior & Development, 30 (1), 127–133. doi:10.1016/j.infbeh.2006.08
Hung H. M., Tsai P. S., Ko S. H., Chen C. H. (2013). Patterns and predictors of sleep quality
in Taiwanese pregnant women. The American Journal of Maternal/Child Nursing, 38 (2), 95–101. doi:10.1097/NMC.0b013e3182659345
Jomeen J., Martin C. R. (2007). Assessment and relationship of sleep quality
to depression in early pregnancy
. Journal of Reproductive and Infant Psychology, 25 (1), 87–99. doi:10.1080/02646830601117308
Ko S. H., Chang S. C., Chen C. H. (2010). A comparative study of sleep quality
between pregnant and non-pregnant Taiwanese women. Journal of Nursing Scholarship, 42 (1), 23–30. doi:10.1111/j.1547-5069.2009.01326.x
Krishnan V., Collop N. A. (2006). Gender differences in sleep disorders. Current Opinion Pulmonary Medicine, 12 (6), 383–389. doi:10.1097/01.mcp.0000245705.69440.6a
Lee A. M., Lam S. K., Lau S. M. (2007). Prevalence, course, and risk factors for antenatal anxiety and depression. Obstetrics and Gynecology, 110 (5), 1102–1112. doi:10.1097/01.AOG.0000287065.59491.70
Lee K. A., Baker F. C., Newton K. M., Ancoli-Israel S. (2008). The influence of reproductive status and age on women’s sleep. Journal of Women’s Health, 17 (7), 1209–1214. doi:10.1089/jwh.2007.0562
Lee K. A., Dejoseph J. F. (1992). Sleep disturbances, vitality, and fatigue among a select group of employed childbearing women. Birth, 19 (4), 208–213.
Lee K. A., Gay C. L. (2004). Sleep in late pregnancy
predicts length of labor and type of delivery. American Journal of Obstetrics and Gynecology, 191 (6), 2041–2046. doi:10.1016/j.ajog.2004.05.086
Lin T. (1978). Psychiatry and society. Taipei City, Taiwan, ROC: Chi-Tsung. (Original work published in Chinese)
Matsuaki M., Haruna M., Ota E., Murayama R., Murashima S. (2011). Factors related to the continuation of employment during pregnancy
among Japanese women. Japan Journal of Nursing Science, 8 (2), 153–162. doi:10.1111/j.1742-7924.2010.00169.x
Micheli K., Ioannis K., Emmanouel B., Theano R., Antonis K., Manolis K., Leda C. (2011). Sleep patterns in late pregnancy
and risk of preterm birth and fetal growth restriction. Epidemiology, 22 (5), 738–744. doi:10.1097/EDE.0b013e31822546fd
National Sleep Foundation. (2013). Women and sleep. Retrieved from http://www.sleepfoundation.org/article/sleep-topics/women-and-sleep
Nomura K., Yamaoka K., Nakaoa M., Yano E. (2010). Social determinants of self-reported sleep problems in South Korea and Taiwan. Journal of Psychosomatic Research, 69 (5), 435–440. doi:10.1016/j.jpsychores.2010.04.014
Okun M. L., Hall M., Coussons-Read M. E. (2007). Sleep disturbances increase interleukin-6 production during pregnancy
: Implications for pregnancy
complication. Reproductive Sciences, 14 (6), 560–567. doi:10.1177/1933719107307647
Okun M. L., Luther J. F., Wisniewski S. R., Sit D., Prairie B. A., Wisner K. L. (2012). Disturbed sleep, a novel risk factor for preterm birth? Journal of Women’s Health, 21 (1), 54–60. doi:10.1089/jwh.2010.2670
Okun M. L., Roberts J. M., Marsland A. L., Hall M. (2009). How disturbed sleep may be a risk for adverse pregnancy
outcomes: A hypothesis. Obstetrical & Gynecological Survey, 64 (4), 273–280. doi:10.1080/15402000902762394
Simonson C., Barlow P., Dehennin N., Sphel M., Toppet V., Murillo D., Rozenberg S. (2007). Neonatal complications of vacuum-assisted delivery. Obstetrics & Gynecology, 109 (3), 626–633.
Swanson L. M., Pickett S. M., Flynn H., Armitage R. (2011). Relationships among depression, anxiety, and insomnia symptoms in perinatal women seeking mental health treatment. Journal of Women’s Health, 20 (4), 553–558. doi:10.1089/jwh.2010.2371
Tsai S. Y., Kuo L. T., Lai Y. H., Lee C. N. (2011). Factors associated with sleep quality
in pregnant women. Nursing Research, 60 (6), 405–412. doi:10.1097/NNR.0b013e3182346249
Warren P. L. (2005). First-time mothers: Social support and confidence in infant care. Journal of Advanced Nursing, 50 (5), 479–488. doi:10.1111/j.1365-2648.2005.03425.x
Wen S. W., Liu S., Kramer M. S., Marcoux S., Ohlsson A., Sauvé R., Liston R. (2001). Comparison of maternal and infant outcomes between vacuum extraction and forceps deliveries. American Journal of Epidemiology, 153 (2), 103–107. doi:10.1093/aje/153.2.103
Zafarghandi N., Hadavand S., Davati A., Mohsen S. M., Kimiaiimoghadam F., Torkestani F. (2012). The effects of sleep quality
and duration in late pregnancy
on labor and fetal outcome. The Journal of Maternal-Fetal and Neonatal Medicine, 25 (5), 535–537. doi:10.3109/14767058.2011.600370