The present systematic review and meta-analysis of 10 observational studies demonstrated that short sleep duration and poor sleep quality were associated with a significantly increased risk of preterm birth. This association highlights the vital significance of pregnant women to reduce the risk of premature birth.
In regard to sleep duration and quality, the inconsistent findings of previous studies might be attributed to differences in the trimester examined and geographical location. For instance, Micheli et al. [13] conducted a cohort study (n = 1091), in which 23% of pregnant women reported a sleep duration of ≤5 h in the third trimester. However, Reutrakul et al. [31] reported that about 56% of pregnant women experienced sleep deprivation in the second trimester, but this study had a relatively small cohort (n = 116). Meanwhile, Li et al. [32] enrolled participants with a similar proportion of short sleepers in all trimesters and the results were similar with the main findings. One study [31] reported that about 50% of pregnant women experienced sleep deprivation, but the sleep durations differed (< 7 and < 8 h/night, respectively). Furthermore, preterm birth rates vary among countries, even different regions in the same country. Also, income and education differences may affect sleep duration and preterm birth rates [37, 38]. Warland et al. [15] speculated that African Americans may exhibit heightened sensitivity to the adverse physiological sequelae of poor sleep quality. Two other studies indicated that pregnant women with clinically disturbed sleep (PSQI > 5) accounted for a similar proportion (about 60%), despite the study being conducted in various regions within the USA [31, 36], while a study conducted in Japan included a lower proportion of poor sleepers at the initial examination and gestational weeks 16, 24, and 32 (27%, 34%, 37%, and 41% of the samples, respectively) [35]. In addition, a study conducted in the USA reported that pregnant women at gestational week 14–16 accounted for 36.4% (n = 48) of the sample [14].
The findings of the current study raise questions about the potential mechanisms underlying the increased risk of preterm birth due to sleep disorders. Sleep deprivation partially accounts for the proinflammatory cytokine response [39-41], immune changes [42], and greater susceptibility to infections [43]. It is well established that inflammation and infection are highly significant risk factors for preterm birth [44, 45]. Additionally, a short sleep duration and poor sleep quality may result from stress and as a physiological stressor per se, stress “overload” and activation of the stress system may lead to prematurity through impairment of the hypothalamus-pituitary-adrenal axis and activation of the proinflammatory system [46]. On the other hand, physiological and hormonal changes also affect sleep practices. For instance, higher levels of estrogen and progesterone during pregnancy contribute to poor sleep quality and also influence the secretion of other hormones, such as cortisol and melatonin, which can increase arousal [47, 48]. Lastly, because disturbed sleep may disrupt normal remodeling of the maternal blood vessels and increased sympathetic activity, placental blood flow was decreased [49, 50], which may be a mechanism underlying preterm birth.
The strengths of the present meta-analysis lie in its quantitative analysis of the association of sleep duration and quality with the risk of prematurity using a large number of participants (n = 5693) and instances of preterm birth associated with sleep duration (n = 1248) and sleep quality (n = 156). The large sample size of this meta-analysis provide strong power for the main analyses and the conclusions derived. Furthermore, numerous sensitivity analyses showed that the main findings were robust. Of note, quality assessment showed that all of the included studies were at a low risk of bias.
Findings from the present meta-analysis should be interpreted in light of several limitations. First, the present meta-analysis was prone to inherent recall and selection bias due to the inclusion of original observational studies. Although case-control studies are more susceptible to bias than cohort studies, the results were robust after exclusion of the only case-control study from the analyses. Furthermore, the PSQI is an important clinical and research tool to gauge sleep quality [51]. However, the PSQI includes sleep duration, thus short sleep duration was included as an outcome of "sleep quality." Consistently, the pooled effect size for poor sleep quality (RR = 1.54) was similar to that for a shorter duration (RR = 1.32), as determined by the meta-analysis. Moreover, in consideration of the variation of the study populations, geographical location likely contributed to the heterogeneity of effect estimates. Furthermore, since all of the included studies measured sleep quality and sleep duration with the use of questionnaires, self-reported sleep quality and duration are not always perfectly aligned with objective sleep quality and duration. Third, because the pooled effect estimates were mostly derived from observational studies, susceptibility to confounding factors remain a concern.
Some common chronic diseases, as mediators between short sleep duration and preterm birth, such as diabetes [31, 52], hypertension [53, 54], and obesity [55], have been correlated with prematurity. Of note, self-reported sleep disturbances are predictive of the incidence of major depression and strongly precede a series of symptoms of depression [56, 57]. The association between depression syndrome and the risk of preterm delivery has been reported [58]. Thus, early intervention to prevent poor sleep quality and a short sleep duration, which may be indicators of early depression, can reduce the risk of preterm birth. However, the observational studies included in this meta-analysis were restricted by the lack of controls for these potentially relevant confounders. Hence, further studies are warranted with better designs to take these confounders or mediators into account or fully adjust for these confounders in order to better rule out the potential effects of residual confounding. Fourth, as the comparison of sleep duration differed considerably among the included studies, dose–response analysis was not conducted. Notably, several of the included studies suggested a potential U-shaped association between sleep duration and preterm birth. Additionally, one of the included studies suggested a potential non-linear (U-shaped) association between sleep duration and preterm birth [33]. However, since a limited number of the included studies met the criteria of linear/non-linear dose-response analysis, such analysis was not conducted in the present study. Also, although seven studies were excluded due to the lack of risk estimates for the association between sleep quantity/quality and preterm birth [10, 24-29], findings of three of these studies support the main findings of the present meta-analysis [10, 27, 28]. Of note, although the power of the main analysis suggested that the statistical power of this meta-analysis was greater than 80% to identify sleep duration/quality for preterm birth with minimum OR values of 1.20 (risk factor for sleep duration) and 1.5 (risk factor for sleep quality), limited sample sizes restricted subgroup analyses stratified by study characteristics and potential confounders. Therefore, on the basis of these limitations, priority should be given to large, adequately powered, cohort studies using standard definitions of maternal sleep duration and quality with effective data analyses. Furthermore, more comparison groups in the primary studies are needed to evaluate the possible non-linear aforementioned association.