Exercise Improves Sleep Quality in Pregnant Women: A Meta-Analysis with Exploratory Dose–Response Analysis

Exercise Improves Sleep Quality in Pregnant Women: A Meta-Analysis with Exploratory Dose–Response Analysis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Exercise Improves Sleep Quality in Pregnant Women: A Meta-Analysis with Exploratory Dose–Response Analysis Endong Qiao, Anping Chen This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9453570/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract Objective To systematically evaluate the effects of exercise interventions on sleep quality in pregnant women and to explore the dose–response relationship between intervention duration, exercise frequency, and duration of individual exercise sessions and sleep improvement. Methods Conducted in accordance with PRISMA guidelines and pre-registered (PROSPERO ID: CRD420261350741), we searched PubMed, Embase, CNKI, Scopus, and Web of Science from inception to March 2026. Randomized controlled trials (RCTs) and controlled clinical trials examining exercise and sleep quality (measured by validated scales like PSQI) were included. Standardized mean differences (SMD) with 95% confidence intervals (CI) were pooled using random-effects models. Heterogeneity was explored via meta-regression and predefined subgroup analyses to identify optimal exercise "dosages." Results Twenty studies involving 2,204 participants (1,136 exercise; 1,068 control) were included. Meta-analysis demonstrated that exercise significantly improved sleep quality in pregnant women (SMD = − 0.82; 95% CI [− 1.19, − 0.45]; P < 0.00001), despite substantial heterogeneity (I² = 93.3%). Subgroup analyses suggested that interventions lasting 9–12 weeks, a frequency of 3 sessions/week, and a session duration exceeding 60 minutes yielded the most pronounced improvements. While exploratory meta-regression did not confirm a linear dose–response relationship (P > 0.05), a trend toward greater efficacy with increased session duration was observed. No exercise-related adverse maternal or fetal events were reported in the included trials. Conclusion Exercise is a safe and effective non-pharmacological intervention for enhancing sleep quality during pregnancy. While the dose–response relationship remains non-linear, structured programs exceeding 60 minutes per session appear particularly beneficial. Clinicians should consider these parameters when prescribing prenatal exercise, although high heterogeneity across studies warrants a personalized approach and further high-quality, large-scale RCTs to refine these recommendations. Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 1. Introduction In recent years, increasing attention has been paid to women’s health, particularly during pregnancy, which represents a unique and physiologically demanding period in a woman’s life. Hormonal fluctuations and anatomical changes during pregnancy are associated with a range of adverse conditions, including depression, anxiety, elevated blood pressure, and impaired sleep quality, all of which can negatively affect overall well-being [ 1 ]. Among these, sleep disturbances are especially prevalent. Data from the 2007 Sleep in America Poll indicated that up to 78% of women reported sleep disruption during late pregnancy [ 2 ]. Sleep disturbances during pregnancy are multifactorial, often resulting from hormonal changes, increased nocturia due to uterine enlargement, and fetal movements at night [ 3 ]. Previous meta-analyses have demonstrated that many pregnant women experience reductions in sleep quality, sleep duration, and sleep depth due to these factors [ 4 ]. The overall prevalence of insomnia symptoms during pregnancy has been estimated at 38.2%, with even higher rates reported in the third trimester [ 5 ]. Importantly, a growing body of evidence suggests that sleep disturbances during pregnancy are associated with a wide range of adverse maternal and fetal outcomes, including gestational diabetes, hypertensive disorders, perinatal mental health problems, prolonged labor, cesarean delivery, preterm birth, and stillbirth [6 7 8]. Several treatment approaches have been proposed to improve sleep during pregnancy, including pharmacological therapy, acupuncture, cognitive behavioral therapy (CBT), yoga, and mindfulness-based interventions [ 9 ]. Pharmacological treatments, such as hypnotics and sedatives, have demonstrated efficacy in the general population[ 10 ]. However, their use during pregnancy remains controversial due to potential adverse effects. For example, benzodiazepines and benzodiazepine receptor agonists have been associated with increased risks of preterm birth, low birth weight, and small-for-gestational-age infants [ 11 ]. CBT is recommended as a first-line treatment for insomnia in both American and European clinical guidelines [12 13]. Nevertheless, its implementation in pregnant populations may be limited by requirements for patient education, structured training, and ongoing supervision, which can reduce adherence and effectiveness in real-world settings [ 14 ]. Therefore, there is a clear need to identify alternative interventions that are safe, accessible, and feasible for improving sleep during pregnancy. Exercise and physical activity have emerged as promising non-pharmacological strategies for improving sleep quality. In the general population, a substantial body of evidence supports the beneficial effects of exercise on sleep[15 16]. In pregnant women, several meta-analyses have also reported positive effects. For example, Choong (2022) pooled data from seven randomized controlled trials and found that exercise interventions significantly improved sleep among perinatal women [ 17 ]. Similarly, Yang (2020) reported beneficial effects of exercise on sleep quality in pregnant women, although its impact on insomnia symptoms remained unclear [ 18 ]. Despite these encouraging findings, important limitations remain. Most existing studies have focused primarily on the overall effectiveness of exercise, with limited attention given to specific characteristics of exercise interventions, such as session duration, frequency, intervention cycle, and exercise type. As a result, current evidence provides limited guidance for clinical practice, particularly in terms of how exercise should be prescribed. A recent meta-analysis attempted to address some of these issues by examining intervention characteristics and suggested that the effects of physical activity may vary according to participant characteristics, intervention duration, delivery mode, and activity type [ 19 ]. However, this study did not explore dose–response relationships, and thus its implications for optimizing exercise prescriptions remain limited. Therefore, the optimal “dose” of exercise for improving sleep quality during pregnancy remains unclear. Given the unique physiological context of pregnancy, it is possible that the relationship between exercise and sleep differs from that observed in non-pregnant populations. A more detailed understanding of how intervention parameters influence outcomes is essential for developing evidence-based and clinically applicable exercise recommendations. Accordingly, the present study aimed to systematically evaluate the effects of exercise on sleep quality in pregnant women through a comprehensive systematic review and meta-analysis. In addition, we explored potential dose–response relationships between exercise characteristics (including intervention cycle, frequency, and session duration) and sleep outcomes, with the goal of providing more precise and practical guidance for clinical and public health applications. 2. Methods 2.1 Protocol and Registration This systematic review and meta-analysis was conducted in accordance with the PRISMA 2020 guidelines. Our systematic review and meta-analysis has been registered on the PROSPERO website (CRD420261350741) and strictly adheres to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. 2.2 Eligibility Criteria The eligibility criteria for the study were based on the PICOS framework (i.e., participants, intervention, comparators, outcomes, and study design). There were no restrictions on the date of inclusion, and the languages accepted were English and Chinese. 2.3 Information Sources An initial search was conducted on December 10, 2025, followed by an updated search on March 25, 2026, in the electronic databases PubMed, Embase, CNKI, Scopus, and Web of Science (Core Collection). Studies published from the start of each database up to the time of manuscript preparation were considered for inclusion in this study. 2.4 Search Strategy Keywords were identified through expert consultation and systematic reviews of previous studies on pregnancy and exercise (e.g., Medical Subject Headings: MeSH). Table 1 outlines the search strategies for specific databases. In addition, reference lists from previous systematic reviews were manually screened to identify additional studies. Finally, errata or retractions of included studies were retrieved and considered (where applicable). Table 1 Retrieval strategy in PubMed. Search number Query 1 "Pregnancy"[Mesh] 2 (Pregnancies[Title/Abstract]) OR (Gestation[Title/Abstract]) 3 1 AND 2 4 "Exercise"[Mesh] 5 ((((Resistance exercise[Title/Abstract]) OR (Aerobic Exercise[Title/Abstract])) OR (Mind-body exercise[Title/Abstract])) OR (TaiChi[Title/Abstract])) OR (Baduanjin[Title/Abstract]) 6 4 AND 5 7 "Sleep"[Mesh] 8 ((((Sleep quality[Title/Abstract]) OR (Sleep disorder[Title/Abstract])) OR (Sleep Wake Disorders[Title/Abstract])) OR (Sleep apnea[Title/Abstract])) OR (Duration of sleep[Title/Abstract]) 9 7 AND 8 10 3 AND 6 AND 9 2.5 Selection Process An initial search of all databases was conducted on December 10, 2025; studies were eligible for inclusion only if they were published prior to March 25, 2026, when the manuscript revision began. Subsequently, two authors (Q.E.D. and C.A.P.) independently screened the provisionally included studies using a two-stage approach based on the eligibility criteria. The first stage involved screening articles based on their titles and abstracts. The second stage involved a full-text analysis of the remaining articles. Any discrepancies between the two authors were resolved through consensus-building discussions. 2.6 Data Collection Process The mean and standard deviation of outcome variables before and after the intervention were extracted from the included studies and recorded in Microsoft Excel (Microsoft Corporation, Redmond, WA, USA). For outcome variables assessed at different time points (e.g., pre-, mid-, and post-intervention), only pre- and post-intervention data were recorded. Follow-up data were not considered. Apply transformations as previously recommended for reporting values other than means and standard deviations (e.g., interquartile range, median, range, and standard error). When authors did not provide numerical data as required and the data were presented graphically, numerical data were extracted from the individual graphs using validated (r = 0.99, p < 0.001) software (Web Plot Digitizer, version 4.6; https://apps.automeris.io/wpd/ ) to extract numerical data from the figures. One author (Q.E.D.) performed the data extraction, and the second author (C.A.P.) provided verification; any discrepancies between authors were resolved through consensus by negotiation. 2.7 Data Items Data extraction was performed independently by two researchers (Q.E.D. and C.A.P.) and included the following: basic study characteristics (first author’s name, year of publication, country); characteristics of the intervention group (sample size, age); characteristics of the intervention (type of exercise, duration, frequency, and cycle); and target outcome measures (sleep quality, duration, number of awakenings, etc.). These data were extracted using a table developed by the researchers. The final list depended on the number of existing studies reporting specific outcome data. Due to the lack of standardized reporting on exercise intensity, interventions were categorized into three groups based on exercise type: mind-body exercises (yoga, tai chi, progressive muscle relaxation training, etc.), aerobic exercises (aerobic exercise, walking, aquatic physical activity, etc.), and structured/combined training (Pilates, aerobic combined with strength training, diet combined with exercise). 2.8 Risk of Bias Assessments The Cochrane Risk of Bias in Randomized Trials Tool, Version 2 (RoB-2) was used to assess the risk of bias at the study level [ 20 ]. For non-randomized studies, the Risk of Bias in Non-randomized Studies—Interventions (ROBINS-I) tool was used [ 21 ]. Two authors (Q.E.D. and C.A.P.) independently assessed the risk of bias for each included study; any discrepancies were resolved through consensus reached by the two reviewers. 2.9 Synthesis Methods Data were analyzed, combined, and visualized using Revman 5.4 and Stata 17. Revman 5.4 was employed for assessing the quality and risk of bias in the literature, while Stata 17 was used for data integration, analysis, and visualization. Data were pooled using the difference between the mean and standard deviation values before and after intervention across all groups, and the outcome variable was expressed as the standardized mean difference (SMD). SMD values are presented with 95% confidence intervals (95% CI). The calculated SMD values were interpreted using the following scale: 0.6–1.2 moderate, > 1.2–2.0 large, > 2.0–4.0 very large, > 4.0 extremely large [ 22 ]. However, since outliers in meta-analyses can affect their validity and robustness [ 23 ], as well as the interpretations, conclusions, and inferences drawn from them, a search for outliers was conducted [ 24 ]. We considered recommendations from previous studies on exercise interventions: it is unlikely that most interventions would yield a standardized effect size ≥ 3.0 (an improvement of ≥ 3 standard deviations relative to the mean or an increase in the interquartile range of more than 1.5 times relative to the median), and thus such results may be considered outliers. Based on this outlier analysis, a sensitivity analysis was conducted by excluding studies with outlier data, thereby presenting both the overall analysis and the results of the sensitivity analysis. In addition, the I² statistic is used to assess the impact of study heterogeneity, with values of 75% representing low, moderate, and high levels of heterogeneity, respectively [ 25 ]. The risk of publication bias for continuous variables (with ≥ 10 studies per outcome) was examined using the extended Egger test [ 26 ] [ 27 ] and interpreted according to the recommendations of Afonso et al. [ 28 ]. To account for the risk of publication bias, sensitivity analyses were conducted using the trimming-and-filling method [ 29 ], with L0 as the default estimate for the number of missing studies [ 30 ]. 3. Results 3.1 Study Selection After searching five databases, a total of 523 studies were identified. After removing duplicates, 422 studies remained. Following a review of abstracts and titles, 52 studies were selected for full-text analysis. Ultimately, 17 studies were selected for systematic review and meta-analysis. Additionally, we searched for previously published systematic reviews and meta-analyses, assessed the eligibility of 14 additional studies, and ultimately included 3 of them. Therefore, a total of 20 studies[ 31 ][ 32 ][ 33 ][ 34 ][ 35 ][ 36 ][ 37 ][ 38 ][ 39 ][ 40 ][ 41 ][[ 42 ][ 43 ][ 44 ][ 45 ][ 46 ][ 47 ][ 48 ][ 49 ][ 50 ] were included. The specific screening process is shown in Fig. 1 . 3.2 Risk of Bias of Included Studies The risk of bias in the randomized controlled trials is shown in Fig. 2 . A total of 17 randomized controlled trials were included. One study was identified as having a high risk of bias, six studies were found to have some issues, and the remaining 10 studies had a low risk of bias. When assessing bias criteria, it was found that the majority (> 80%) of studies raised concerns regarding three criteria: (i) bias arising from the randomization process (e.g., lack of concealment of the allocation sequence), (ii) selection bias in the trial (e.g., lack of double-blinding of patients and physicians), and (iii) bias in the reporting of results (e.g., lack of prior registration of the study protocol). The risk of bias assessment for non-randomized studies is shown in Fig. 3 . This included 3 non-randomized controlled trials; the ROBINS-I assessment results (Fig. 3 ) indicated that 2 of these studies had a moderate risk of bias, while 1 had a high risk of bias. 3.3 Study Characteristics All included studies were from 9 different countries and regions and were published between 2013 and 2025. A total of 7 types of exercise were included: Pilates (k = 6), progressive muscle relaxation (k = 4), aerobic exercise (k = 3), aerobic and strength training (k = 2), aquatic exercise (k = 1), yoga (k = 2), and physical activity (k = 2). The total sample size for the exercise intervention groups was 1,136, and for the control groups, 1,068. The intervention frequency ranged from 1 to 7 days per week, the intervention duration ranged from 4 to 24 weeks, and the duration of a single session ranged from 20 to 180 minutes. 3.4 Results of the Meta-Analysis 3.4.1 The Effect of Exercise on Sleep Quality Among the included studies, 15 used the PSQI to assess sleep quality, while 5 used other sleep quality assessment scales. Because various tools were used to measure each outcome, standardized mean differences (SMD) adjusted for small-sample bias were calculated as summary statistics. Data were first pooled using a fixed-effects model, which showed that the exercise intervention group had a significant effect on sleep quality in pregnant women compared to the control group (SMD = − 0.65, 95% CI = − 0.74, − 0.56, P < 0.00001). A heterogeneity test revealed I² = 93%, indicating high heterogeneity; therefore, a random-effects model was used for analysis. The results were similar(Fig. 4 ), with the intervention group still showing a significant improvement in sleep quality (SMD = − 0.82, 95% CI = − 1.19, − 0.45, P < 0.00001). However, heterogeneity remained high (I² = 93%). The Galbraith plot (Fig. 5 ) showed that several studies deviated significantly, which may be a source of heterogeneity; further heterogeneity analysis is required. First, a funnel plot was constructed to assess for publication bias. The funnel plot (Fig. 6 ) showed a relatively symmetrical distribution of studies, all concentrated in the upper and middle portions of the funnel. The Egger test revealed a statistically significant small-sample effect (β₁ = −3.58, P = 0.023), suggesting the possible presence of publication bias. However, the trim-and-fill analysis did not identify any studies requiring inclusion, and the pooled effect size remained unchanged before and after adjustment. Furthermore, significant heterogeneity was observed in this study (I² = 93%), suggesting that the asymmetry in the funnel plot may be primarily due to differences among studies rather than publication bias. We then conducted a sensitivity analysis by sequentially excluding studies from the included literature and found that the heterogeneity index I² did not change significantly after excluding any single study. Next, we excluded non-randomized controlled trials, and the results showed that I² remained unchanged, indicating that the findings were independent of whether the studies were randomized controlled trials. Concurrently, we conducted a meta-regression analysis, incorporating variables such as the average age of pregnant women, total number of participants, duration of a single intervention, frequency of interventions, and intervention cycle. The results (Table 2 ) showed that none of these factors had a significant effect on study heterogeneity (P > 0.05). Table 2 Meta-regression analysis. Factors Coefficient Std. err z P >|z| [95% conf. interval] age 0.0656468 0.0653828 1.00 0.315 -0.0625 00.1937 Intervention cycle 0.0539063 0.0518955 1.04 0.299 -0.478 0.1556 Single duration -0.0048199 0.0055378 -0.87 0.384 -0.0156 0.0060 Number of sample 0013532 0.0032086 0.42 0.673 -0.0049 0.0076 Intervention frequency -0.0120615 0.1102792 -0.11 0.913 -0.2282 0.2040 3.4.2 An Exploration of the Dose-Response Relationship Between Exercise and Sleep Quality First, a dose-response analysis of the intervention cycle was conducted. A univariate regression analysis of the intervention duration was performed, yielding a p-value of 0.34, indicating that there was no linear relationship between intervention duration and effect size. Subsequently, a nonlinear relationship was explored; the results of the nonlinear meta-regression analysis showed a p-value of 0.59, indicating that no significant nonlinear dose-response relationship was observed. Finally, a subgroup analysis was performed after grouping the intervention duration. This study divided the intervention cycle into four groups: 0–4 weeks, 5–8 weeks, 9–12 weeks, and 12 weeks or longer, with five studies included in each group. The pooled analysis results (Fig. 7 ) showed small differences between groups (I² = 31.7%). Specifically, when the intervention cycle was 0–4 weeks (SMD = − 1.06, 95% CI = − 2.65, 0.53, p = 0.19) or greater than 12 weeks (SMD = − 0.53, 95% CI = − 1.10, 0.04, p = 0.07), the results showed that, compared with the control group, exercise intervention had no significant effect on improving sleep quality. Analysis of the remaining two groups (5–8 weeks and 9–12 weeks) showed that exercise intervention significantly improved sleep quality in pregnant women, with a larger effect size observed when the intervention cycle was 5–8 weeks (SMD = − 1.32, 95% CI = − 1.95, − 0.69, p < 0.0001). An analysis of the dose-response relationship for intervention frequency was conducted; a total of 19 studies reported exercise frequency. Nonlinear meta-regression analysis showed that neither the first-order term (P = 0.735) nor the second-order term (P = 0.632) of intervention frequency was significantly associated with the effect size, suggesting that no significant linear or nonlinear dose-response relationship was observed. Furthermore, the model failed to account for heterogeneity among studies (R² = 0%). Exercise frequency was then categorized into three groups: 0–2 days per week, 3–4 days per week, and 5–7 days per week. Subgroup analysis results (Fig. 8 ) showed almost no differences between groups (I² = 0%). Specifically, when the intervention frequency was 0–2 days per week or 3–4 days per week, exercise significantly improved sleep quality in pregnant women compared to the control group, with the 3–4 days per week intervention yielding better results (SMD = − 0.97, 95% CI = − 1.48, − 0.45, p = 0.0003). However, when the intervention frequency was increased to 5–7 days per week, the exercise intervention lost its statistical significance compared to the control group (SMD = − 0.69, 95% CI = − 1.99, 0.61, p = 0.3). Next, we explored the dose-response relationship for the duration of a single intervention; a total of 18 studies reported the duration of a single intervention. Nonlinear meta-regression analysis revealed that neither the first-order term (p = 0.564) nor the second-order term (p = 0.353) of single-session duration was significantly associated with effect size, suggesting that no significant linear or nonlinear dose-response relationship was observed, and that the model had limited ability to explain heterogeneity (R² = 4.64%). A bubble plot with a fitted regression line (Fig. 9 ) suggests a possible nonlinear relationship between single-session duration and effect size; however, this trend did not reach statistical significance. Subgroup analysis was conducted by dividing the 18 studies into three groups based on single-session duration: 0–30 minutes, 31–60 minutes, and 60 minutes or longer. The results showed that the 0–30-minute group included 4 studies, the 31–60-minute group included 10 studies, and the 60-minute-or-longer group included 4 studies. The results of the meta-analysis (Fig. 10 ) showed significant differences between groups (I² = 68.4%, p = 0.04). When the duration of a single exercise session was 0–30 minutes or exceeded 60 minutes, exercise significantly improved sleep quality in pregnant women compared with the control group, and exercise lasting 60 minutes or longer may have been more effective (SMD = − 1.34, 95% CI = − 2.01, − 0.67, p < 0.0001). However, when the intervention duration was 31–60 minutes, the exercise intervention was less effective and did not reach statistical significance (SMD = − 0.39, 95% CI = − 0.87, 0.09, p = 0.11). In summary, the dose-response relationship for intervention duration may exhibit a bimodal pattern, but this requires verification with a larger sample size. Finally, this study also categorized different types of exercise into three groups: mind-body exercises (such as yoga, tai chi, and progressive muscle relaxation), aerobic exercises (such as cardio, walking, and aquatic physical activities), and combined training (such as Pilates, cardio combined with strength training, and diet combined with exercise). Among these, 5 studies involved aerobic exercise, 6 involved mind-body exercises, and 9 involved combined training. A meta-regression analysis treating exercise type as a categorical variable showed no significant association between exercise type and effect size (P = 0.64). Compared with mind-body interventions, neither aerobic exercise (β = 0.38, P = 0.54) nor combined training (β = −0.16, P = 0.77) showed a significant difference in their effects on sleep quality. Furthermore, exercise type could not explain the heterogeneity among the studies (R² = 0%). Subgroup analysis also showed that there was virtually no heterogeneity between groups (I² = 0%, p = 0.45). The pooled results within each group (Fig. 11 ) show that the aerobic exercise group and the mind-body exercise group exhibited substantial heterogeneity (I² = 95% and I² = 97%), respectively. Furthermore, compared with the control group, neither of these two exercise types significantly improved sleep quality in pregnant women (p = 0.1 and p = 0.14). In contrast, the mixed exercise group showed slightly lower heterogeneity than the previous two groups (I² = 76%). At the same time, compared with the control group, mixed exercise significantly improved sleep quality in pregnant women (SMD = − 0.95, 95% CI = − 1.33, − 0.57, p < 0.00001). 4. Discussion This systematic review and meta-analysis aimed to evaluate the effects of exercise on sleep quality in pregnant women and to explore potential dose-response relationships associated with the duration, frequency, and duration of the intervention. Twenty studies were synthesized to examine the effectiveness of exercise interventions on sleep quality in pregnant women. The main findings indicate that exercise interventions can significantly improve sleep quality during pregnancy. However, high heterogeneity was observed across all studies, and no clear linear or nonlinear dose-response relationship was identified. Notably, subgroup analyses suggest that a mixed exercise regimen combined with moderate intervention parameters—specifically, exercise programs lasting 5–8 weeks, performed 3–4 times per week, with each session lasting more than 60 minutes—may yield more pronounced effects. These findings collectively indicate that, during pregnancy, increased exercise volume is not necessarily associated with improved sleep quality. The beneficial effects of exercise on sleep quality observed in this study are consistent with the findings of previous systematic reviews and meta-analyses conducted on the general population and pregnant women[ 51 ]. Previous studies have shown that physical activity can alleviate sleep disturbances and improve overall sleep quality, particularly when compared to sedentary control groups[ 52 ]. However, most early meta-analyses focused primarily on the overall effects of exercise without examining specific components of exercise prescriptions. In contrast, this study expands upon the existing literature by incorporating detailed dose-response analyses, including intervention duration, frequency, and duration per training session. This approach provides more nuanced insights into how different exercise characteristics influence sleep outcomes during pregnancy. Although the mechanisms by which exercise improves sleep quality during pregnancy are not yet fully understood, several factors may play a significant role. First, exercise alters the concentrations of signaling molecules in the blood; for example, it can increase levels of brain-derived neurotrophic factor (BDNF), which influences neural centers in the brain and thereby regulates sleep[ 53 ]. Second, exercise may modulate neuroendocrine function, including lowering cortisol levels and improving melatonin secretion, thereby helping to stabilize the circadian rhythm [ 54 ]. Given the significant fluctuations in hormone levels during pregnancy, this regulatory effect may be particularly important for maintaining sleep quality. Additionally, exercise may improve sleep by increasing homeostatic sleep pressure. Moderate physical activity promotes physiological fatigue, which aids in the onset and maintenance of sleep. However, excessive exercise may activate the sympathetic nervous system and disrupt the recovery process[ 55 ], which may be one reason why higher exercise frequencies (e.g., 5 to 7 times per week) were not associated with significant improvements in sleep quality in this study. Third, psychological factors: psychological states such as anxiety and depression can severely impact pregnant women’s sleep quality and quality of life. Previously published meta-analyses indicate that prenatal exercise can effectively prevent and treat prenatal depression and anxiety, as well as prevent postpartum depression [ 56 ]. This suggests that exercise may improve sleep quality by enhancing the psychological well-being of pregnant women. A key contribution of this study is the identification of a potential “optimal” exercise range, although no statistically significant dose-response relationship was found. The finding that interventions lasting 5–8 weeks were associated with greater improvements may reflect a balance between sufficient exercise and the avoidance of cumulative fatigue. Similarly, an exercise frequency of 3–4 times per week may ensure adequate recovery while maintaining regular stimulation. The observed patterns regarding exercise duration are particularly noteworthy. Both shorter and longer exercise durations appear to be beneficial, while intermediate durations showed no statistical significance. One possible explanation is that shorter exercise durations may primarily serve a relaxation function, whereas longer durations may induce sufficient physiological fatigue to promote sleep. In contrast, intermediate durations may not consistently achieve either of these effects. However, this apparent bimodal pattern should be interpreted with caution, as it is based on a limited number of studies. 4.1 Probable source of high heterogeneity The substantial heterogeneity observed in this meta-analysis (I²=93%) requires careful consideration, particularly in the context of behavioral and lifestyle interventions, where variability is often inherent. Although meta-regression analyses were performed to explore potential moderators, none of the examined variables significantly accounted for the between-study variability. Furthermore, the absence of evidence for publication bias, as indicated by Egger’s test and the trim-and-fill method, suggests that the heterogeneity is unlikely to be driven by small-study effects or selective reporting. Rather, it appears to reflect genuine clinical and methodological diversity across the included studies. From a broader perspective, exercise interventions during pregnancy can be conceptualized as complex interventions, characterized by multiple interacting components, context dependency, and variability in implementation. Within this framework, heterogeneity is not merely a statistical artifact but an expected feature arising from differences in population characteristics, intervention delivery, and contextual factors. Several specific sources of heterogeneity can be identified. First, variation in gestational age at study inclusion is likely to be a major contributor. The included studies encompassed participants at different stages of pregnancy, ranging from early second trimester[ 43 ] to late third trimester[ 31 ], while some studies did not clearly report gestational timing[ 49 ]. Given that pregnancy is associated with dynamic physiological, hormonal, and sleep-related changes, the baseline severity of sleep disturbances and the responsiveness to exercise may differ substantially across gestational stages. This temporal variability may therefore introduce meaningful differences in intervention effects. Second, heterogeneity in intervention delivery—including exercise setting, supervision, and implementation fidelity—may have further contributed to the observed variability. Interventions conducted in controlled clinical environments with direct supervision[ 35 ] are likely to ensure higher adherence and more consistent exercise intensity, whereas remotely supervised[ 34 ] or hybrid interventions[ 48 ] may introduce greater variability in participant engagement and execution. Such differences are particularly relevant in exercise-based interventions, where adherence and correct performance are critical determinants of effectiveness. Third, differences in participant health status represent another important source of heterogeneity. While the majority of studies targeted generally healthy pregnant women, some included populations with specific conditions, such as restless legs syndrome[ 31 ], depressive symptoms, or pre-existing sleep disorders[ 33 ]. These conditions may not only affect baseline sleep quality but also modify the physiological and psychological response to exercise, thereby leading to heterogeneous treatment effects. Importantly, the inability of meta-regression to identify significant moderators may reflect limited statistical power, collinearity among variables, or insufficient reporting of key intervention characteristics—particularly exercise intensity, which is a central dimension of exercise prescription but was inconsistently described across studies. The absence of standardized reporting limits the ability to fully disentangle the relative contributions of different factors to heterogeneity. Taken together, the high heterogeneity observed in this analysis likely reflects the combined influence of multiple interacting factors rather than a single dominant source. This underscores the need to interpret pooled estimates with caution, while also recognizing that such variability is characteristic of real-world interventions. Future studies would benefit from more standardized and detailed reporting, as well as from designs that allow for better isolation of individual components within multifactorial exercise interventions. 4.2 Clinical and public health implications From a clinical perspective, the study findings suggest that moderate, structured exercise programs may offer greater benefits than either minimal or excessive exercise. In particular, exercise interventions of moderate duration and frequency appear to strike a balance between effectiveness and feasibility, which is especially meaningful for pregnant women who may experience fatigue, discomfort, or time constraints. However, due to the absence of a statistically significant dose-response relationship, these findings should not be interpreted as prescriptive thresholds but rather as indicative ranges to guide individualized exercise plans. Therefore, clinicians should consider patient-specific factors, including baseline health status, stage of pregnancy, and comorbidities, when recommending exercise programs. From a public health perspective, these findings highlight the importance of incorporating exercise-based interventions into routine prenatal care and health promotion programs. Compared to pharmacological treatments, exercise is a low-cost, low-risk, and widely accessible strategy that can be implemented at the community level. Public health initiatives should promote regular moderate-intensity physical activity as part of comprehensive maternal health programs, while also addressing common barriers such as a lack of guidance, safety concerns, and a shortage of supervised exercise resources. 4.3 Limitations and Future Directions This study should acknowledge several limitations. First, the high degree of heterogeneity limits the precision of the pooled estimates. Second, reporting on exercise interventions is often incomplete, particularly regarding intensity, which hinders a more comprehensive dose-response analysis. Third, some subgroup results are based on a relatively small number of studies and should therefore be interpreted with caution. Finally, although most of the included studies were randomized controlled trials, the inclusion of a small number of non-randomized studies may introduce additional bias. Despite these limitations, the current findings remain clinically relevant. They suggest that moderate, structured exercise during pregnancy may be more beneficial for improving sleep than either insufficient or excessive physical activity. In particular, exercise programs of moderate duration and frequency appear to strike a favorable balance between effectiveness and feasibility. However, given the variability across studies, these observations should be viewed as indicative rather than prescriptive. Future research would benefit greatly from more standardized reporting of exercise interventions, particularly regarding intensity and adherence. Well-designed randomized controlled trials are needed to further clarify dose-response relationships and identify factors that may influence the effects of exercise on sleep. A deeper understanding of these mechanisms could support the development of more targeted and effective exercise recommendations for pregnant women. 5. Conclusion This systematic review and meta-analysis indicates that exercise interventions can significantly improve sleep quality in pregnant women. Although no statistically significant linear or nonlinear dose-response relationship was observed, the results of the subgroup analysis provide important guidance for optimizing exercise prescriptions during pregnancy: A mixed exercise regimen (such as Pilates or a combination of aerobic and strength training) lasting 5–8 weeks, performed 3–4 times per week, with each session exceeding 60 minutes, may yield better intervention outcomes. This suggests that during the unique physiological phase of pregnancy, the sleep-improving effects of exercise do not simply increase with higher “dose”; rather, moderate exercise frequency and duration play a key role in balancing physiological fatigue and avoiding excessive fatigue accumulation. From both clinical and public health perspectives, exercise—as a safe, low-cost, and easily accessible non-pharmacological intervention—should be actively incorporated into routine prenatal care. When formulating exercise recommendations, clinicians should refer to the aforementioned “optimal” ranges while fully considering the pregnant woman’s gestational stage, health status, and individual adherence to provide personalized exercise plans. Although this study is limited by the high heterogeneity of the included literature and the incompleteness of reported exercise intensity, it still provides empirical evidence for precise interventions in this field. Future research should focus on standardized measurement of exercise intensity and monitoring of adherence, and through the design of more rigorous randomized controlled trials, further validate the interactions among different exercise parameters to develop more scientific and precise guidelines for exercise during pregnancy. Disclosure statement No potential conflict of interest was reported by the author(s). Declarations Disclosure statement No potential conflict of interest was reported by the author(s). Funding The research was not funded by any institution. Author contributions Endong Qiao and Anping Chen contributed to the conceptualization and design of the study, and data analysis, and original manuscript draft and revision; Endong Qiao contributed to the data collection and interpretation of data; Anping Chen contributed to the supervision and reviewed/edited the manuscript; All authors have read and approved the final manuscript. Ethics approval This article does not contain any studies with human participants or animals performed by any of the authors. Consent to Participate Not applicable. This study is a systematic review and meta-analysis based on previously published studies; therefore, ethical approval and individual consent to participate are not required. Consent to Publish declaration Not applicable Data Availability Statement All relevant data are within the manuscript and its additional file. The data are available from the corresponding author on reasonable request. References Haas JS, Rebecca A, Jackson E, Fuentes-Afflick, et al. Changes in the Health Status of Women during and after Pregnancy. J Gen Intern Med. 2005;20(1):45–51. https://doi.org/10.1111/j.1525-1497.2004.40097.x . National Sleep Foundation. Summary of findings of the 2007 Sleep in America Poll. Available at: http://sleepfoundation.org/media-center/pressrelease/sleep-america-poll-summary-findings Lamberg L. Sleeping Poorly While Pregnant May Not Be ‘Normal’. JAMA. 2006;295(12):1357–61. https://doi.org/10.1001/jama.295.12.1357 . Sedov ID, Emily E, Cameron S, Madigan, Lianne M, Tomfohr-Madsen. Sleep Quality during Pregnancy: A Meta-Analysis. Sleep Med Rev. 2018;38(April):168–76. https://doi.org/10.1016/j.smrv.2017.06.005 . Sedov ID, Nina J, Anderson AK, Dhillon, Tomfohr-Madsen LM. Insomnia Symptoms during Pregnancy: A Meta-Analysis. J Sleep Res. 2021;30(1):e13207. https://doi.org/10.1111/jsr.13207 . Pien GW, and Richard J. Schwab. Sleep Disorders during Pregnancy. Sleep. 2004;27(7):1405–17. https://doi.org/10.1093/sleep/27.7.1405 . Palagini L, Cipriani E, Caruso V, et al. Insomnia during the Perinatal Period and Its Association with Maternal and Infant Psychopathology: A Systematic Review and Meta-Analysis. Curr Psychiatry Rep. 2023;25(11):617–41. https://doi.org/10.1007/s11920-023-01463-3 . Baattaiah BA, Mutasim D, Alharbi NM, Babteen, Haneen M, Al-Maqbool FA, Babgi, Albatati AA. The Relationship between Fatigue, Sleep Quality, Resilience, and the Risk of Postpartum Depression: An Emphasis on Maternal Mental Health. BMC Psychol. 2023;11(1):10. https://doi.org/10.1186/s40359-023-01043-3 . Bacaro V, Benz F, Pappaccogli A, et al. Interventions for Sleep Problems during Pregnancy: A Systematic Review. Sleep Med Rev. 2020;50:101234. https://doi.org/10.1016/j.smrv.2019.101234 . Feren S, Katyal A, Walsh JK. Efficacy of Hypnotic Medications and Other Medications Used for Insomnia. Sleep Med Clin. 2006;1(3):387–97. https://doi.org/10.1016/j.jsmc.2006.06.011 . Insomnia. Okun ML. A Review of Sleep-Promoting Medications Used in Pregnancy. Am J Obstet Gynecol. 2015;212(4):428–41. https://doi.org/10.1016/j.ajog.2014.10.1106 . Riemann D, Baglioni C, Bassetti C, et al. European Guideline for the Diagnosis and Treatment of Insomnia. J Sleep Res. 2017;26(6):675–700. https://doi.org/10.1111/jsr.12594 . Qaseem A, Kansagara D, Forciea MA, et al. Management of Chronic Insomnia Disorder in Adults: A Clinical Practice Guideline from the American College of Physicians. Ann Intern Med. 2016;165(2):125–33. https://doi.org/10.7326/M15-2175 . Tolin DF. Is Cognitive–Behavioral Therapy More Effective than Other Therapies? A Meta-Analytic Review. Clin Psychol Rev. 2010;30(6):710–20. https://doi.org/10.1016/j.cpr.2010.05.003 . Jurado-Fasoli L, Molina-Hidalgo AD-la-OC, Migueles JH, Manuel J, Castillo, Francisco J, Amaro-Gahete. Exercise Training Improves Sleep Quality: A Randomized Controlled Trial. Eur J Clin Invest. 2020;50(3):e13202. https://doi.org/10.1111/eci.13202 . Yang P-Y, Ho K-H, Chen H-C, Meng-Yueh C. Exercise Training Improves Sleep Quality in Middle-Aged and Older Adults with Sleep Problems: A Systematic Review. J Physiotherapy. 2012;58(3):157–63. https://doi.org/10.1016/S1836-9553(12)70106-6 . Choong SY, Xin XYJ, Tan LJ, Cheng, and Ying Lau. Effectiveness of Exercise in Improving Sleep Outcomes among Perinatal Women: A Systematic Review and Meta-Analysis of Randomised Controlled Trials. Behav sleep Med. 2022;20(4):410–28. https://doi.org/10.1080/15402002.2021.1931221 . Yang S-Y, Lan S-J, Yen Y-Y, Hsieh Y-P, Kung P-T, and Shao-Huan Lan. Effects of Exercise on Sleep Quality in Pregnant Women: A Systematic Review and Meta-Analysis of Randomized Controlled Trials. Asian Nurs Res. 2020;14(1):1–10. https://doi.org/10.1016/j.anr.2020.01.003 . Liu D, Liu K, Xie L, He M, and Xiangping Liu. The Effect of Physical Activity on Sleep Disorders in Pregnant People: A Meta-Analysis of Randomized Controlled Trials. BMC Pregnancy Childbirth. 2025;25(1):139. https://doi.org/10.1186/s12884-024-07129-z . Sterne JAC, Jelena Savović MJ, Page et al. 2019. RoB 2: A Revised Tool for Assessing Risk of Bias in Randomised Trials. Research Methods & Reporting. BMJ 366 (August): l4898. https://doi.org/10.1136/bmj.l4898 Sterne JAC, Miguel A, Hernán BC, Reeves, et al. ROBINS-I: A Tool for Assessing Risk of Bias in Non-Randomised Studies of Interventions. Res Methods Report BMJ. 2016;355(October):i4919. https://doi.org/10.1136/bmj.i4919 . Hopkins WG, Stephen W, Marshall AM, Batterham, and Juri Hanin. Progressive Statistics for Studies in Sports Medicine and Exercise Science. Med Sci Sports Exerc. 2009;41(1):3. https://doi.org/10.1249/MSS.0b013e31818cb278 . Viechtbauer W, Mike WL, Cheung. Outlier and Influence Diagnostics for Meta-Analysis. Res Synthesis Methods. 2010;1(2):112–25. https://doi.org/10.1002/jrsm.11 . Kadlec D, Sainani KL, and Sophia Nimphius. With Great Power Comes Great Responsibility: Common Errors in Meta-Analyses and Meta-Regressions in Strength & Conditioning Research. Sports Medicine . N Z). 2023;53(2):313–25. https://doi.org/10.1007/s40279-022-01766-0 . Auckland. Higgins JPT, Thompson SG. Quantifying Heterogeneity in a Meta-Analysis. Stat Med. 2002;21(11):1539–58. https://doi.org/10.1002/sim.1186 . Egger M, Smith GD, Schneider M, Minder C. Bias in Meta-Analysis Detected by a Simple. Graphical Test Paper BMJ. 1997;315(7109):629–34. https://doi.org/10.1136/bmj.315.7109.629 . Higgins TJ, Chandler J, Cumpston M, Li T, Page MJ et al. Assessing risk of bias due to missing results in a synthesis. In: Cochrane handbook for systematic reviews of interventions. Second edition. Chichester (UK): John Wiley & Sons; 2019, pp 365. Afonso José, Clemente RR-CFM, Fionn Cléirigh Büttner, and Renato Andrade. 2024. The Perils of Misinterpreting and Misusing ‘Publication Bias’ in Meta-Analyses: An Education Review on Funnel Plot-Based Methods. Sports Medicine (Auckland, N.Z.) 54 (2): 257–69. https://doi.org/10.1007/s40279-023-01927-9 Duval S, Tweedie R. Trim and Fill: A Simple Funnel-Plot-Based Method of Testing and Adjusting for Publication Bias in Meta-Analysis. Biometrics. 2000;56(2):455–63. https://doi.org/10.1111/j.0006-341x.2000.00455.x . Shi L, and Lifeng Lin. The Trim-and-Fill Method for Publication Bias: Practical Guidelines and Recommendations Based on a Large Database of Meta-Analyses. Medicine. 2019;98(23):e15987. https://doi.org/10.1097/MD.0000000000015987 . Akbaş Pınar, Şengül YSözbir. The Effect of Progressive Muscle Relaxation Exercise on the Intensity of Symptoms and Quality of Sleep and Quality of Life in Pregnant Women with Restless Leg Syndrome. Patient Educ Couns. 2023;113(August):107768. https://doi.org/10.1016/j.pec.2023.107768 . Rashed AA, Bekhatro A, Khalil AK, and Hanaa Mohamed Abo Shereda. Effect of Non-Pharmacological Interventions on Sleep Quality during Pregnancy among Primigravida. South Asian Res J Nurs Healthc. 2019;01(01):8–17. https://doi.org/10.36346/sarjnhc.2019.v01i01.002 . Batool A, Kousar Z, Tariq M, Saleem M, Anwer N, and Javeria Aslam. Comparison of Aerobic and Pilates Exercises on Depression and Sleep Quality in Primigravida Females. Pakistan J Med Health Sci. 2024;17(11):27–30. https://doi.org/10.53350/pjmhs02023171127 . Benito-Villena R, Naveiro-Fuentes IG-M et al. 2022. Walking Promotion in Pregnancy and Its Effects on Insomnia: Results of Walking_Preg Project (WPP) Clinical Trial. International Journal of Environmental Research and Public Health 19 (16): 10012. https://doi.org/10.3390/ijerph191610012 Broberg L, Damm P, Frokjaer VG, et al. Evaluation of the Effect of Supervised Group Exercise on Self-Reported Sleep Quality in Pregnant Women with or at High Risk of Depression: A Secondary Analysis of a Randomized Controlled Trial. Int J Environ Res Public Health. 2022;19(10):5954. https://doi.org/10.3390/ijerph19105954 . Chen C, Jinguo Zhai, Shuiwang Hu, et al. Effects of Different Physical Exercise Types on Health Outcomes of Individuals with Hypertensive Disorders of Pregnancy: A Prospective Randomized Controlled Clinical Study. J Maternal-Fetal Neonatal Medicine: Official J Eur Association Perinat Med Federation Asia Ocean Perinat Soc Int Soc Perinat Obstetricians. 2024;37(1):2421278. https://doi.org/10.1080/14767058.2024.2421278 . Field T, Diego M, Delgado J, and Lissette Medina. Tai Chi/Yoga Reduces Prenatal Depression, Anxiety and Sleep Disturbances. Complement Ther Clin Pract. 2013;19(1):6–10. https://doi.org/10.1016/j.ctcp.2012.10.001 . Golmakani. Nahid, and Negar Asghari Pour. n.d. Comparing the Effects of Progressive Muscle Relaxation and Guided Imagery on Sleep Quality in Primigravida Women Referring to Mashhad Health Care Centers – 1393 . Hawkins M, Marcus B, Pekow P, et al. The Impact of a Randomized Controlled Trial of a Lifestyle Intervention on Sleep among Latina Postpartum Women. Annals Behav Medicine: Publication Soc Behav Med. 2021;55(9):892–903. https://doi.org/10.1093/abm/kaaa118 . Huang Wenyu L, Yonghan, Xiaoying X. 2020. A Study on the Effects of Moderate-to-Low-Intensity Aerobic Exercise During the Second and Third Trimesters on the Prenatal Quality of Life and Maternal-Fetal Outcomes in Advanced-Age Pregnant Women. Guangzhou Med 51 (5). https://kns.cnki.net/KCMS/detail/detail.aspx?dbcode=CJFQ &dbname=CJFDLAST2020&filename=GZYY202005015. Hyun A-H, Cho J-Y, Jung-Hoon Koo. Effect of Home-Based Tele-Pilates Intervention on Pregnant Women: A Pilot Study. Healthcare (Basel Switzerland). 2022;10(1):125. https://doi.org/10.3390/healthcare10010125 . Kim H-B, and Ah-Hyun Hyun. Psychological and Biochemical Effects of an Online Pilates Intervention in Pregnant Women during COVID-19: A Randomized Pilot Study. Int J Environ Res Public Health. 2022;19(17):10931. https://doi.org/10.3390/ijerph191710931 . Navas A, Carrascosa MaríaDC, Artigues C, et al. Effectiveness of Moderate-Intensity Aerobic Water Exercise during Pregnancy on Quality of Life and Postpartum Depression: A Multi-Center, Randomized Controlled Trial. J Clin Med. 2021;10(11):2432. https://doi.org/10.3390/jcm10112432 . Özkan S, Aydın, and Gülay Rathfisch. The Effect of Relaxation Exercises on Sleep Quality in Pregnant Women in the Third Trimester: A Randomized Controlled Trial. Complement Ther Clin Pract. 2018;32(August):79–84. https://doi.org/10.1016/j.ctcp.2018.05.008 . Rodriguez-Blanque R, Sánchez-García JC, Sánchez-López AM, Mur-Villar N, Aguilar-Cordero MJ. The Influence of Physical Activity in Water on Sleep Quality in Pregnant Women: A Randomised Trial. Women Birth: J Australian Coll Midwives. 2018;31(1):e51–58. https://doi.org/10.1016/j.wombi.2017.06.018 . Shen W-C, and Chung-Hey Chen. Effects of Non-Supervised Aerobic Exercise on Sleep Quality and Maternal-Fetal Attachment in Pregnant Women: A Randomized Controlled Trial. Complement Ther Med. 2021;57:102671. https://doi.org/10.1016/j.ctim.2021.102671 . Sonmezer E, Özköslü MA, Hayri Baran Yosmaoğlu. The Effects of Clinical Pilates Exercises on Functional Disability, Pain, Quality of Life and Lumbopelvic Stabilization in Pregnant Women with Low Back Pain: A Randomized Controlled Study. J Back Musculoskelet Rehabil. 2021;34(1):69–76. https://doi.org/10.3233/BMR-191810 . Shu Ling X, Mingxia W, Chuanfang Z, Wei T, Chuang. and Chen Dan. 2018. The Effects of Mindfulness Yoga Training on Sleep Quality, Anxiety, and Fear of Childbirth Among Pregnant Women. Chin J Nurs Manage 18 (10). https://kns.cnki.net/KCMS/detail/detail.aspx?dbcode=CJFQ &dbname=CJFDLAST2018&filename=GLHL201810034. Tayhan F, and Aysenur Karakus. Effect of Pilates on Sleep Quality, Eating Disorders and Occupational Balance in Pregnant Women. Arch Gynecol Obstet. 2025;312(6):2187–98. https://doi.org/10.1007/s00404-025-08202-4 . Yıldırım P, Basol G, and Ali Yavuz Karahan. Pilates-Based Therapeutic Exercise for Pregnancy-Related Low Back and Pelvic Pain: A Prospective, Randomized, Controlled Trial. Turkish J Phys Med Rehabilitation. 2023;69(2):207–15. https://doi.org/10.5606/tftrd.2023.11054 . Liu D, Liu K, Xie L, He M, and Xiangping Liu. The Effect of Physical Activity on Sleep Disorders in Pregnant People: A Meta-Analysis of Randomized Controlled Trials. BMC Pregnancy Childbirth. 2025;25(1):139. https://doi.org/10.1186/s12884-024-07129-z . Huang H-H, Stubbs B, Chen L-J, et al. The Effect of Physical Activity on Sleep Disturbance in Various Populations: A Scoping Review of Randomized Clinical Trials. Int J Behav Nutr Phys Activity. 2023;20(1):44. https://doi.org/10.1186/s12966-023-01449-7 . Tan X, Lieve T, van Egmond JC, and Christian Benedict. The Role of Exercise-Induced Peripheral Factors in Sleep Regulation. Mol Metabolism. 2020;42:101096. https://doi.org/10.1016/j.molmet.2020.101096 . Mennitti C, Farina G, Antonio Imperatore, et al. How Does Physical Activity Modulate Hormone Responses? Biomolecules. 2024;14(11):1418. https://doi.org/10.3390/biom14111418 . Chiang J-K, Lin Y-C, Hung T-Y, Kao H-H, and Yee-Hsin Kao. The Impact on Autonomic Nervous System Activity during and Following Exercise in Adults: A Meta-Regression Study and Trial Sequential Analysis. Medicina. 2024;60(8):1223. https://doi.org/10.3390/medicina60081223 . Dong J, Chi J, Fung-Chua E, Lei. Effects of Prenatal Exercise on Prenatal and Postpartum Depression and Anxiety Symptoms: A Systematic Review and Network Meta-Analysis. J Affect Disord. 2026;393(January):120438. https://doi.org/10.1016/j.jad.2025.120438 . Additional Declarations No competing interests reported. Supplementary Files PRISMAchecklist.docx Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 18 May, 2026 Reviewers agreed at journal 08 May, 2026 Reviewers invited by journal 30 Apr, 2026 Editor invited by journal 23 Apr, 2026 Editor assigned by journal 20 Apr, 2026 Submission checks completed at journal 20 Apr, 2026 First submitted to journal 17 Apr, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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intervention and the magnitude of the effect. The size of each circle represents the weight of the corresponding study. The solid line represents the fitted regression line.\u003c/p\u003e","description":"","filename":"image9.png","url":"https://assets-eu.researchsquare.com/files/rs-9453570/v1/739ba4ed97229f88127eabf7.png"},{"id":108972192,"identity":"ee99e1af-0b41-4347-8884-728e84dd842e","added_by":"auto","created_at":"2026-05-11 10:34:52","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":185831,"visible":true,"origin":"","legend":"\u003cp\u003eForest plot of subgroup analysis by duration of a single intervention.\u003c/p\u003e","description":"","filename":"image10.png","url":"https://assets-eu.researchsquare.com/files/rs-9453570/v1/b059099418af7a7ac96ad5f6.png"},{"id":108972190,"identity":"2dcc0ce8-552d-4a10-a245-cb04f80ffde3","added_by":"auto","created_at":"2026-05-11 10:34:52","extension":"png","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":196529,"visible":true,"origin":"","legend":"\u003cp\u003eForest plot of subgroup analysis by exercise type.\u003c/p\u003e","description":"","filename":"image11.png","url":"https://assets-eu.researchsquare.com/files/rs-9453570/v1/4c38df9907168a0b3efa0973.png"},{"id":108972181,"identity":"9eb81f8f-8cc1-4357-a3d2-52e633dc838a","added_by":"auto","created_at":"2026-05-11 10:34:52","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":33527,"visible":true,"origin":"","legend":"","description":"","filename":"PRISMAchecklist.docx","url":"https://assets-eu.researchsquare.com/files/rs-9453570/v1/9c2da11409da8339930d629d.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eExercise Improves Sleep Quality in Pregnant Women: A Meta-Analysis with Exploratory Dose–Response Analysis\u003c/p\u003e","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eIn recent years, increasing attention has been paid to women\u0026rsquo;s health, particularly during pregnancy, which represents a unique and physiologically demanding period in a woman\u0026rsquo;s life. Hormonal fluctuations and anatomical changes during pregnancy are associated with a range of adverse conditions, including depression, anxiety, elevated blood pressure, and impaired sleep quality, all of which can negatively affect overall well-being [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Among these, sleep disturbances are especially prevalent. Data from the 2007 Sleep in America Poll indicated that up to 78% of women reported sleep disruption during late pregnancy [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSleep disturbances during pregnancy are multifactorial, often resulting from hormonal changes, increased nocturia due to uterine enlargement, and fetal movements at night [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Previous meta-analyses have demonstrated that many pregnant women experience reductions in sleep quality, sleep duration, and sleep depth due to these factors [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. The overall prevalence of insomnia symptoms during pregnancy has been estimated at 38.2%, with even higher rates reported in the third trimester [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Importantly, a growing body of evidence suggests that sleep disturbances during pregnancy are associated with a wide range of adverse maternal and fetal outcomes, including gestational diabetes, hypertensive disorders, perinatal mental health problems, prolonged labor, cesarean delivery, preterm birth, and stillbirth [6 7 8].\u003c/p\u003e \u003cp\u003eSeveral treatment approaches have been proposed to improve sleep during pregnancy, including pharmacological therapy, acupuncture, cognitive behavioral therapy (CBT), yoga, and mindfulness-based interventions [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Pharmacological treatments, such as hypnotics and sedatives, have demonstrated efficacy in the general population[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. However, their use during pregnancy remains controversial due to potential adverse effects. For example, benzodiazepines and benzodiazepine receptor agonists have been associated with increased risks of preterm birth, low birth weight, and small-for-gestational-age infants [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. CBT is recommended as a first-line treatment for insomnia in both American and European clinical guidelines [12 13]. Nevertheless, its implementation in pregnant populations may be limited by requirements for patient education, structured training, and ongoing supervision, which can reduce adherence and effectiveness in real-world settings [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Therefore, there is a clear need to identify alternative interventions that are safe, accessible, and feasible for improving sleep during pregnancy.\u003c/p\u003e \u003cp\u003eExercise and physical activity have emerged as promising non-pharmacological strategies for improving sleep quality. In the general population, a substantial body of evidence supports the beneficial effects of exercise on sleep[15 16]. In pregnant women, several meta-analyses have also reported positive effects. For example, Choong (2022) pooled data from seven randomized controlled trials and found that exercise interventions significantly improved sleep among perinatal women [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Similarly, Yang (2020) reported beneficial effects of exercise on sleep quality in pregnant women, although its impact on insomnia symptoms remained unclear [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDespite these encouraging findings, important limitations remain. Most existing studies have focused primarily on the overall effectiveness of exercise, with limited attention given to specific characteristics of exercise interventions, such as session duration, frequency, intervention cycle, and exercise type. As a result, current evidence provides limited guidance for clinical practice, particularly in terms of how exercise should be prescribed. A recent meta-analysis attempted to address some of these issues by examining intervention characteristics and suggested that the effects of physical activity may vary according to participant characteristics, intervention duration, delivery mode, and activity type [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. However, this study did not explore dose\u0026ndash;response relationships, and thus its implications for optimizing exercise prescriptions remain limited.\u003c/p\u003e \u003cp\u003eTherefore, the optimal \u0026ldquo;dose\u0026rdquo; of exercise for improving sleep quality during pregnancy remains unclear. Given the unique physiological context of pregnancy, it is possible that the relationship between exercise and sleep differs from that observed in non-pregnant populations. A more detailed understanding of how intervention parameters influence outcomes is essential for developing evidence-based and clinically applicable exercise recommendations.\u003c/p\u003e \u003cp\u003eAccordingly, the present study aimed to systematically evaluate the effects of exercise on sleep quality in pregnant women through a comprehensive systematic review and meta-analysis. In addition, we explored potential dose\u0026ndash;response relationships between exercise characteristics (including intervention cycle, frequency, and session duration) and sleep outcomes, with the goal of providing more precise and practical guidance for clinical and public health applications.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Protocol and Registration\u003c/h2\u003e \u003cp\u003e This systematic review and meta-analysis was conducted in accordance with the PRISMA 2020 guidelines. Our systematic review and meta-analysis has been registered on the PROSPERO website (CRD420261350741) and strictly adheres to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Eligibility Criteria\u003c/h2\u003e \u003cp\u003eThe eligibility criteria for the study were based on the PICOS framework (i.e., participants, intervention, comparators, outcomes, and study design). There were no restrictions on the date of inclusion, and the languages accepted were English and Chinese.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Information Sources\u003c/h2\u003e \u003cp\u003eAn initial search was conducted on December 10, 2025, followed by an updated search on March 25, 2026, in the electronic databases PubMed, Embase, CNKI, Scopus, and Web of Science (Core Collection). Studies published from the start of each database up to the time of manuscript preparation were considered for inclusion in this study.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Search Strategy\u003c/h2\u003e \u003cp\u003eKeywords were identified through expert consultation and systematic reviews of previous studies on pregnancy and exercise (e.g., Medical Subject Headings: MeSH). Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e outlines the search strategies for specific databases. In addition, reference lists from previous systematic reviews were manually screened to identify additional studies. Finally, errata or retractions of included studies were retrieved and considered (where applicable).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRetrieval strategy in PubMed.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSearch number\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQuery\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\"Pregnancy\"[Mesh]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(Pregnancies[Title/Abstract]) OR (Gestation[Title/Abstract])\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 AND 2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\"Exercise\"[Mesh]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e((((Resistance exercise[Title/Abstract]) OR (Aerobic Exercise[Title/Abstract])) OR (Mind-body exercise[Title/Abstract])) OR (TaiChi[Title/Abstract])) OR (Baduanjin[Title/Abstract])\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 AND 5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\"Sleep\"[Mesh]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e((((Sleep quality[Title/Abstract]) OR (Sleep disorder[Title/Abstract])) OR (Sleep Wake Disorders[Title/Abstract])) OR (Sleep apnea[Title/Abstract])) OR (Duration of sleep[Title/Abstract])\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 AND 8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 AND 6 AND 9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Selection Process\u003c/h2\u003e \u003cp\u003eAn initial search of all databases was conducted on December 10, 2025; studies were eligible for inclusion only if they were published prior to March 25, 2026, when the manuscript revision began. Subsequently, two authors (Q.E.D. and C.A.P.) independently screened the provisionally included studies using a two-stage approach based on the eligibility criteria. The first stage involved screening articles based on their titles and abstracts. The second stage involved a full-text analysis of the remaining articles. Any discrepancies between the two authors were resolved through consensus-building discussions.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6 Data Collection Process\u003c/h2\u003e \u003cp\u003eThe mean and standard deviation of outcome variables before and after the intervention were extracted from the included studies and recorded in Microsoft Excel (Microsoft Corporation, Redmond, WA, USA). For outcome variables assessed at different time points (e.g., pre-, mid-, and post-intervention), only pre- and post-intervention data were recorded. Follow-up data were not considered. Apply transformations as previously recommended for reporting values other than means and standard deviations (e.g., interquartile range, median, range, and standard error). When authors did not provide numerical data as required and the data were presented graphically, numerical data were extracted from the individual graphs using validated (r\u0026thinsp;=\u0026thinsp;0.99, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) software (Web Plot Digitizer, version 4.6; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://apps.automeris.io/wpd/\u003c/span\u003e\u003cspan address=\"https://apps.automeris.io/wpd/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) to extract numerical data from the figures. One author (Q.E.D.) performed the data extraction, and the second author (C.A.P.) provided verification; any discrepancies between authors were resolved through consensus by negotiation.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.7 Data Items\u003c/h2\u003e \u003cp\u003eData extraction was performed independently by two researchers (Q.E.D. and C.A.P.) and included the following: basic study characteristics (first author\u0026rsquo;s name, year of publication, country); characteristics of the intervention group (sample size, age); characteristics of the intervention (type of exercise, duration, frequency, and cycle); and target outcome measures (sleep quality, duration, number of awakenings, etc.). These data were extracted using a table developed by the researchers. The final list depended on the number of existing studies reporting specific outcome data. Due to the lack of standardized reporting on exercise intensity, interventions were categorized into three groups based on exercise type: mind-body exercises (yoga, tai chi, progressive muscle relaxation training, etc.), aerobic exercises (aerobic exercise, walking, aquatic physical activity, etc.), and structured/combined training (Pilates, aerobic combined with strength training, diet combined with exercise).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e2.8 Risk of Bias Assessments\u003c/h2\u003e \u003cp\u003eThe Cochrane Risk of Bias in Randomized Trials Tool, Version 2 (RoB-2) was used to assess the risk of bias at the study level [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. For non-randomized studies, the Risk of Bias in Non-randomized Studies\u0026mdash;Interventions (ROBINS-I) tool was used [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Two authors (Q.E.D. and C.A.P.) independently assessed the risk of bias for each included study; any discrepancies were resolved through consensus reached by the two reviewers.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e2.9 Synthesis Methods\u003c/h2\u003e \u003cp\u003eData were analyzed, combined, and visualized using Revman 5.4 and Stata 17. Revman 5.4 was employed for assessing the quality and risk of bias in the literature, while Stata 17 was used for data integration, analysis, and visualization. Data were pooled using the difference between the mean and standard deviation values before and after intervention across all groups, and the outcome variable was expressed as the standardized mean difference (SMD). SMD values are presented with 95% confidence intervals (95% CI). The calculated SMD values were interpreted using the following scale: \u0026lt; 0.2 trivial, 0.2\u0026ndash;0.6 small, \u0026gt; 0.6\u0026ndash;1.2 moderate, \u0026gt; 1.2\u0026ndash;2.0 large, \u0026gt; 2.0\u0026ndash;4.0 very large, \u0026gt; 4.0 extremely large [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. However, since outliers in meta-analyses can affect their validity and robustness [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e], as well as the interpretations, conclusions, and inferences drawn from them, a search for outliers was conducted [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. We considered recommendations from previous studies on exercise interventions: it is unlikely that most interventions would yield a standardized effect size\u0026thinsp;\u0026ge;\u0026thinsp;3.0 (an improvement of \u0026ge;\u0026thinsp;3 standard deviations relative to the mean or an increase in the interquartile range of more than 1.5 times relative to the median), and thus such results may be considered outliers. Based on this outlier analysis, a sensitivity analysis was conducted by excluding studies with outlier data, thereby presenting both the overall analysis and the results of the sensitivity analysis. In addition, the I\u0026sup2; statistic is used to assess the impact of study heterogeneity, with values of \u0026lt;\u0026thinsp;25%, 25\u0026ndash;75%, and \u0026gt;\u0026thinsp;75% representing low, moderate, and high levels of heterogeneity, respectively [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. The risk of publication bias for continuous variables (with \u0026ge;\u0026thinsp;10 studies per outcome) was examined using the extended Egger test [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e] [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] and interpreted according to the recommendations of Afonso et al. [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. To account for the risk of publication bias, sensitivity analyses were conducted using the trimming-and-filling method [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e], with L0 as the default estimate for the number of missing studies [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Study Selection\u003c/h2\u003e \u003cp\u003eAfter searching five databases, a total of 523 studies were identified. After removing duplicates, 422 studies remained. Following a review of abstracts and titles, 52 studies were selected for full-text analysis. Ultimately, 17 studies were selected for systematic review and meta-analysis. Additionally, we searched for previously published systematic reviews and meta-analyses, assessed the eligibility of 14 additional studies, and ultimately included 3 of them. Therefore, a total of 20 studies[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e][\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e][\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e][\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e][\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e][\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e][\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e][\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e][\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e][\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e][\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e][[\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e][\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e][\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e][\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e][\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e][\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e][\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e][\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e][\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e] were included. The specific screening process is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Risk of Bias of Included Studies\u003c/h2\u003e \u003cp\u003eThe risk of bias in the randomized controlled trials is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. A total of 17 randomized controlled trials were included. One study was identified as having a high risk of bias, six studies were found to have some issues, and the remaining 10 studies had a low risk of bias. When assessing bias criteria, it was found that the majority (\u0026gt;\u0026thinsp;80%) of studies raised concerns regarding three criteria: (i) bias arising from the randomization process (e.g., lack of concealment of the allocation sequence), (ii) selection bias in the trial (e.g., lack of double-blinding of patients and physicians), and (iii) bias in the reporting of results (e.g., lack of prior registration of the study protocol). The risk of bias assessment for non-randomized studies is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. This included 3 non-randomized controlled trials; the ROBINS-I assessment results (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) indicated that 2 of these studies had a moderate risk of bias, while 1 had a high risk of bias.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Study Characteristics\u003c/h2\u003e \u003cp\u003eAll included studies were from 9 different countries and regions and were published between 2013 and 2025. A total of 7 types of exercise were included: Pilates (k\u0026thinsp;=\u0026thinsp;6), progressive muscle relaxation (k\u0026thinsp;=\u0026thinsp;4), aerobic exercise (k\u0026thinsp;=\u0026thinsp;3), aerobic and strength training (k\u0026thinsp;=\u0026thinsp;2), aquatic exercise (k\u0026thinsp;=\u0026thinsp;1), yoga (k\u0026thinsp;=\u0026thinsp;2), and physical activity (k\u0026thinsp;=\u0026thinsp;2). The total sample size for the exercise intervention groups was 1,136, and for the control groups, 1,068. The intervention frequency ranged from 1 to 7 days per week, the intervention duration ranged from 4 to 24 weeks, and the duration of a single session ranged from 20 to 180 minutes.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Results of the Meta-Analysis\u003c/h2\u003e \u003cdiv id=\"Sec17\" class=\"Section3\"\u003e \u003ch2\u003e3.4.1 The Effect of Exercise on Sleep Quality\u003c/h2\u003e \u003cp\u003eAmong the included studies, 15 used the PSQI to assess sleep quality, while 5 used other sleep quality assessment scales. Because various tools were used to measure each outcome, standardized mean differences (SMD) adjusted for small-sample bias were calculated as summary statistics. Data were first pooled using a fixed-effects model, which showed that the exercise intervention group had a significant effect on sleep quality in pregnant women compared to the control group (SMD\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;0.65, 95% CI\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;0.74, \u0026minus;\u0026thinsp;0.56, P\u0026thinsp;\u0026lt;\u0026thinsp;0.00001). A heterogeneity test revealed I\u0026sup2; = 93%, indicating high heterogeneity; therefore, a random-effects model was used for analysis. The results were similar(Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e), with the intervention group still showing a significant improvement in sleep quality (SMD\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;0.82, 95% CI\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;1.19, \u0026minus;\u0026thinsp;0.45, P\u0026thinsp;\u0026lt;\u0026thinsp;0.00001). However, heterogeneity remained high (I\u0026sup2; = 93%). The Galbraith plot (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e) showed that several studies deviated significantly, which may be a source of heterogeneity; further heterogeneity analysis is required.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFirst, a funnel plot was constructed to assess for publication bias. The funnel plot (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e) showed a relatively symmetrical distribution of studies, all concentrated in the upper and middle portions of the funnel. The Egger test revealed a statistically significant small-sample effect (β₁ = \u0026minus;3.58, P\u0026thinsp;=\u0026thinsp;0.023), suggesting the possible presence of publication bias. However, the trim-and-fill analysis did not identify any studies requiring inclusion, and the pooled effect size remained unchanged before and after adjustment. Furthermore, significant heterogeneity was observed in this study (I\u0026sup2; = 93%), suggesting that the asymmetry in the funnel plot may be primarily due to differences among studies rather than publication bias.\u003c/p\u003e \u003cp\u003eWe then conducted a sensitivity analysis by sequentially excluding studies from the included literature and found that the heterogeneity index I\u0026sup2; did not change significantly after excluding any single study. Next, we excluded non-randomized controlled trials, and the results showed that I\u0026sup2; remained unchanged, indicating that the findings were independent of whether the studies were randomized controlled trials.\u003c/p\u003e \u003cp\u003eConcurrently, we conducted a meta-regression analysis, incorporating variables such as the average age of pregnant women, total number of participants, duration of a single intervention, frequency of interventions, and intervention cycle. The results (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) showed that none of these factors had a significant effect on study heterogeneity (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMeta-regression analysis.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFactors\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCoefficient\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStd. err\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ez\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP \u0026gt;|z|\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003e[95% conf. interval]\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0656468\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0653828\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e0.315\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.0625\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e00.1937\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntervention cycle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0539063\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0518955\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e0.299\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.478\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.1556\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSingle duration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.0048199\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0055378\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e0.384\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.0156\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.0060\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of sample\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0013532\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0032086\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e0.673\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.0049\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.0076\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntervention frequency\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.0120615\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.1102792\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e0.913\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.2282\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.2040\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section3\"\u003e \u003ch2\u003e3.4.2 An Exploration of the Dose-Response Relationship Between Exercise and Sleep Quality\u003c/h2\u003e \u003cp\u003eFirst, a dose-response analysis of the intervention cycle was conducted. A univariate regression analysis of the intervention duration was performed, yielding a p-value of 0.34, indicating that there was no linear relationship between intervention duration and effect size. Subsequently, a nonlinear relationship was explored; the results of the nonlinear meta-regression analysis showed a p-value of 0.59, indicating that no significant nonlinear dose-response relationship was observed. Finally, a subgroup analysis was performed after grouping the intervention duration. This study divided the intervention cycle into four groups: 0\u0026ndash;4 weeks, 5\u0026ndash;8 weeks, 9\u0026ndash;12 weeks, and 12 weeks or longer, with five studies included in each group. The pooled analysis results (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e) showed small differences between groups (I\u0026sup2; = 31.7%). Specifically, when the intervention cycle was 0\u0026ndash;4 weeks (SMD\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;1.06, 95% CI\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;2.65, 0.53, p\u0026thinsp;=\u0026thinsp;0.19) or greater than 12 weeks (SMD\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;0.53, 95% CI\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;1.10, 0.04, p\u0026thinsp;=\u0026thinsp;0.07), the results showed that, compared with the control group, exercise intervention had no significant effect on improving sleep quality. Analysis of the remaining two groups (5\u0026ndash;8 weeks and 9\u0026ndash;12 weeks) showed that exercise intervention significantly improved sleep quality in pregnant women, with a larger effect size observed when the intervention cycle was 5\u0026ndash;8 weeks (SMD\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;1.32, 95% CI\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;1.95, \u0026minus;\u0026thinsp;0.69, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAn analysis of the dose-response relationship for intervention frequency was conducted; a total of 19 studies reported exercise frequency. Nonlinear meta-regression analysis showed that neither the first-order term (P\u0026thinsp;=\u0026thinsp;0.735) nor the second-order term (P\u0026thinsp;=\u0026thinsp;0.632) of intervention frequency was significantly associated with the effect size, suggesting that no significant linear or nonlinear dose-response relationship was observed. Furthermore, the model failed to account for heterogeneity among studies (R\u0026sup2; = 0%). Exercise frequency was then categorized into three groups: 0\u0026ndash;2 days per week, 3\u0026ndash;4 days per week, and 5\u0026ndash;7 days per week. Subgroup analysis results (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e) showed almost no differences between groups (I\u0026sup2; = 0%). Specifically, when the intervention frequency was 0\u0026ndash;2 days per week or 3\u0026ndash;4 days per week, exercise significantly improved sleep quality in pregnant women compared to the control group, with the 3\u0026ndash;4 days per week intervention yielding better results (SMD\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;0.97, 95% CI\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;1.48, \u0026minus;\u0026thinsp;0.45, p\u0026thinsp;=\u0026thinsp;0.0003). However, when the intervention frequency was increased to 5\u0026ndash;7 days per week, the exercise intervention lost its statistical significance compared to the control group (SMD\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;0.69, 95% CI\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;1.99, 0.61, p\u0026thinsp;=\u0026thinsp;0.3).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eNext, we explored the dose-response relationship for the duration of a single intervention; a total of 18 studies reported the duration of a single intervention. Nonlinear meta-regression analysis revealed that neither the first-order term (p\u0026thinsp;=\u0026thinsp;0.564) nor the second-order term (p\u0026thinsp;=\u0026thinsp;0.353) of single-session duration was significantly associated with effect size, suggesting that no significant linear or nonlinear dose-response relationship was observed, and that the model had limited ability to explain heterogeneity (R\u0026sup2; = 4.64%). A bubble plot with a fitted regression line (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e) suggests a possible nonlinear relationship between single-session duration and effect size; however, this trend did not reach statistical significance. Subgroup analysis was conducted by dividing the 18 studies into three groups based on single-session duration: 0\u0026ndash;30 minutes, 31\u0026ndash;60 minutes, and 60 minutes or longer. The results showed that the 0\u0026ndash;30-minute group included 4 studies, the 31\u0026ndash;60-minute group included 10 studies, and the 60-minute-or-longer group included 4 studies. The results of the meta-analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003e) showed significant differences between groups (I\u0026sup2; = 68.4%, p\u0026thinsp;=\u0026thinsp;0.04). When the duration of a single exercise session was 0\u0026ndash;30 minutes or exceeded 60 minutes, exercise significantly improved sleep quality in pregnant women compared with the control group, and exercise lasting 60 minutes or longer may have been more effective (SMD\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;1.34, 95% CI\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;2.01, \u0026minus;\u0026thinsp;0.67, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). However, when the intervention duration was 31\u0026ndash;60 minutes, the exercise intervention was less effective and did not reach statistical significance (SMD\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;0.39, 95% CI\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;0.87, 0.09, p\u0026thinsp;=\u0026thinsp;0.11). In summary, the dose-response relationship for intervention duration may exhibit a bimodal pattern, but this requires verification with a larger sample size.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFinally, this study also categorized different types of exercise into three groups: mind-body exercises (such as yoga, tai chi, and progressive muscle relaxation), aerobic exercises (such as cardio, walking, and aquatic physical activities), and combined training (such as Pilates, cardio combined with strength training, and diet combined with exercise). Among these, 5 studies involved aerobic exercise, 6 involved mind-body exercises, and 9 involved combined training. A meta-regression analysis treating exercise type as a categorical variable showed no significant association between exercise type and effect size (P\u0026thinsp;=\u0026thinsp;0.64). Compared with mind-body interventions, neither aerobic exercise (β\u0026thinsp;=\u0026thinsp;0.38, P\u0026thinsp;=\u0026thinsp;0.54) nor combined training (β = \u0026minus;0.16, P\u0026thinsp;=\u0026thinsp;0.77) showed a significant difference in their effects on sleep quality. Furthermore, exercise type could not explain the heterogeneity among the studies (R\u0026sup2; = 0%). Subgroup analysis also showed that there was virtually no heterogeneity between groups (I\u0026sup2; = 0%, p\u0026thinsp;=\u0026thinsp;0.45). The pooled results within each group (Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e11\u003c/span\u003e) show that the aerobic exercise group and the mind-body exercise group exhibited substantial heterogeneity (I\u0026sup2; = 95% and I\u0026sup2; = 97%), respectively. Furthermore, compared with the control group, neither of these two exercise types significantly improved sleep quality in pregnant women (p\u0026thinsp;=\u0026thinsp;0.1 and p\u0026thinsp;=\u0026thinsp;0.14). In contrast, the mixed exercise group showed slightly lower heterogeneity than the previous two groups (I\u0026sup2; = 76%). At the same time, compared with the control group, mixed exercise significantly improved sleep quality in pregnant women (SMD\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;0.95, 95% CI\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;1.33, \u0026minus;\u0026thinsp;0.57, p\u0026thinsp;\u0026lt;\u0026thinsp;0.00001).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThis systematic review and meta-analysis aimed to evaluate the effects of exercise on sleep quality in pregnant women and to explore potential dose-response relationships associated with the duration, frequency, and duration of the intervention. Twenty studies were synthesized to examine the effectiveness of exercise interventions on sleep quality in pregnant women. The main findings indicate that exercise interventions can significantly improve sleep quality during pregnancy. However, high heterogeneity was observed across all studies, and no clear linear or nonlinear dose-response relationship was identified. Notably, subgroup analyses suggest that a mixed exercise regimen combined with moderate intervention parameters\u0026mdash;specifically, exercise programs lasting 5\u0026ndash;8 weeks, performed 3\u0026ndash;4 times per week, with each session lasting more than 60 minutes\u0026mdash;may yield more pronounced effects. These findings collectively indicate that, during pregnancy, increased exercise volume is not necessarily associated with improved sleep quality.\u003c/p\u003e \u003cp\u003eThe beneficial effects of exercise on sleep quality observed in this study are consistent with the findings of previous systematic reviews and meta-analyses conducted on the general population and pregnant women[\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. Previous studies have shown that physical activity can alleviate sleep disturbances and improve overall sleep quality, particularly when compared to sedentary control groups[\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. However, most early meta-analyses focused primarily on the overall effects of exercise without examining specific components of exercise prescriptions. In contrast, this study expands upon the existing literature by incorporating detailed dose-response analyses, including intervention duration, frequency, and duration per training session. This approach provides more nuanced insights into how different exercise characteristics influence sleep outcomes during pregnancy.\u003c/p\u003e \u003cp\u003eAlthough the mechanisms by which exercise improves sleep quality during pregnancy are not yet fully understood, several factors may play a significant role. First, exercise alters the concentrations of signaling molecules in the blood; for example, it can increase levels of brain-derived neurotrophic factor (BDNF), which influences neural centers in the brain and thereby regulates sleep[\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. Second, exercise may modulate neuroendocrine function, including lowering cortisol levels and improving melatonin secretion, thereby helping to stabilize the circadian rhythm [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. Given the significant fluctuations in hormone levels during pregnancy, this regulatory effect may be particularly important for maintaining sleep quality. Additionally, exercise may improve sleep by increasing homeostatic sleep pressure. Moderate physical activity promotes physiological fatigue, which aids in the onset and maintenance of sleep. However, excessive exercise may activate the sympathetic nervous system and disrupt the recovery process[\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e], which may be one reason why higher exercise frequencies (e.g., 5 to 7 times per week) were not associated with significant improvements in sleep quality in this study. Third, psychological factors: psychological states such as anxiety and depression can severely impact pregnant women\u0026rsquo;s sleep quality and quality of life. Previously published meta-analyses indicate that prenatal exercise can effectively prevent and treat prenatal depression and anxiety, as well as prevent postpartum depression [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. This suggests that exercise may improve sleep quality by enhancing the psychological well-being of pregnant women.\u003c/p\u003e \u003cp\u003eA key contribution of this study is the identification of a potential \u0026ldquo;optimal\u0026rdquo; exercise range, although no statistically significant dose-response relationship was found. The finding that interventions lasting 5\u0026ndash;8 weeks were associated with greater improvements may reflect a balance between sufficient exercise and the avoidance of cumulative fatigue. Similarly, an exercise frequency of 3\u0026ndash;4 times per week may ensure adequate recovery while maintaining regular stimulation. The observed patterns regarding exercise duration are particularly noteworthy. Both shorter and longer exercise durations appear to be beneficial, while intermediate durations showed no statistical significance. One possible explanation is that shorter exercise durations may primarily serve a relaxation function, whereas longer durations may induce sufficient physiological fatigue to promote sleep. In contrast, intermediate durations may not consistently achieve either of these effects. However, this apparent bimodal pattern should be interpreted with caution, as it is based on a limited number of studies.\u003c/p\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Probable source of high heterogeneity\u003c/h2\u003e \u003cp\u003eThe substantial heterogeneity observed in this meta-analysis (I\u0026sup2;=93%) requires careful consideration, particularly in the context of behavioral and lifestyle interventions, where variability is often inherent. Although meta-regression analyses were performed to explore potential moderators, none of the examined variables significantly accounted for the between-study variability. Furthermore, the absence of evidence for publication bias, as indicated by Egger\u0026rsquo;s test and the trim-and-fill method, suggests that the heterogeneity is unlikely to be driven by small-study effects or selective reporting. Rather, it appears to reflect genuine clinical and methodological diversity across the included studies.\u003c/p\u003e \u003cp\u003eFrom a broader perspective, exercise interventions during pregnancy can be conceptualized as complex interventions, characterized by multiple interacting components, context dependency, and variability in implementation. Within this framework, heterogeneity is not merely a statistical artifact but an expected feature arising from differences in population characteristics, intervention delivery, and contextual factors.\u003c/p\u003e \u003cp\u003eSeveral specific sources of heterogeneity can be identified. First, variation in gestational age at study inclusion is likely to be a major contributor. The included studies encompassed participants at different stages of pregnancy, ranging from early second trimester[\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e] to late third trimester[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e], while some studies did not clearly report gestational timing[\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. Given that pregnancy is associated with dynamic physiological, hormonal, and sleep-related changes, the baseline severity of sleep disturbances and the responsiveness to exercise may differ substantially across gestational stages. This temporal variability may therefore introduce meaningful differences in intervention effects.\u003c/p\u003e \u003cp\u003eSecond, heterogeneity in intervention delivery\u0026mdash;including exercise setting, supervision, and implementation fidelity\u0026mdash;may have further contributed to the observed variability. Interventions conducted in controlled clinical environments with direct supervision[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e] are likely to ensure higher adherence and more consistent exercise intensity, whereas remotely supervised[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e] or hybrid interventions[\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e] may introduce greater variability in participant engagement and execution. Such differences are particularly relevant in exercise-based interventions, where adherence and correct performance are critical determinants of effectiveness.\u003c/p\u003e \u003cp\u003eThird, differences in participant health status represent another important source of heterogeneity. While the majority of studies targeted generally healthy pregnant women, some included populations with specific conditions, such as restless legs syndrome[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e], depressive symptoms, or pre-existing sleep disorders[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. These conditions may not only affect baseline sleep quality but also modify the physiological and psychological response to exercise, thereby leading to heterogeneous treatment effects.\u003c/p\u003e \u003cp\u003eImportantly, the inability of meta-regression to identify significant moderators may reflect limited statistical power, collinearity among variables, or insufficient reporting of key intervention characteristics\u0026mdash;particularly exercise intensity, which is a central dimension of exercise prescription but was inconsistently described across studies. The absence of standardized reporting limits the ability to fully disentangle the relative contributions of different factors to heterogeneity.\u003c/p\u003e \u003cp\u003eTaken together, the high heterogeneity observed in this analysis likely reflects the combined influence of multiple interacting factors rather than a single dominant source. This underscores the need to interpret pooled estimates with caution, while also recognizing that such variability is characteristic of real-world interventions. Future studies would benefit from more standardized and detailed reporting, as well as from designs that allow for better isolation of individual components within multifactorial exercise interventions.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Clinical and public health implications\u003c/h2\u003e \u003cp\u003eFrom a clinical perspective, the study findings suggest that moderate, structured exercise programs may offer greater benefits than either minimal or excessive exercise. In particular, exercise interventions of moderate duration and frequency appear to strike a balance between effectiveness and feasibility, which is especially meaningful for pregnant women who may experience fatigue, discomfort, or time constraints. However, due to the absence of a statistically significant dose-response relationship, these findings should not be interpreted as prescriptive thresholds but rather as indicative ranges to guide individualized exercise plans. Therefore, clinicians should consider patient-specific factors, including baseline health status, stage of pregnancy, and comorbidities, when recommending exercise programs.\u003c/p\u003e \u003cp\u003eFrom a public health perspective, these findings highlight the importance of incorporating exercise-based interventions into routine prenatal care and health promotion programs. Compared to pharmacological treatments, exercise is a low-cost, low-risk, and widely accessible strategy that can be implemented at the community level. Public health initiatives should promote regular moderate-intensity physical activity as part of comprehensive maternal health programs, while also addressing common barriers such as a lack of guidance, safety concerns, and a shortage of supervised exercise resources.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003e4.3 Limitations and Future Directions\u003c/h2\u003e \u003cp\u003eThis study should acknowledge several limitations. First, the high degree of heterogeneity limits the precision of the pooled estimates. Second, reporting on exercise interventions is often incomplete, particularly regarding intensity, which hinders a more comprehensive dose-response analysis. Third, some subgroup results are based on a relatively small number of studies and should therefore be interpreted with caution. Finally, although most of the included studies were randomized controlled trials, the inclusion of a small number of non-randomized studies may introduce additional bias.\u003c/p\u003e \u003cp\u003eDespite these limitations, the current findings remain clinically relevant. They suggest that moderate, structured exercise during pregnancy may be more beneficial for improving sleep than either insufficient or excessive physical activity. In particular, exercise programs of moderate duration and frequency appear to strike a favorable balance between effectiveness and feasibility. However, given the variability across studies, these observations should be viewed as indicative rather than prescriptive.\u003c/p\u003e \u003cp\u003eFuture research would benefit greatly from more standardized reporting of exercise interventions, particularly regarding intensity and adherence. Well-designed randomized controlled trials are needed to further clarify dose-response relationships and identify factors that may influence the effects of exercise on sleep. A deeper understanding of these mechanisms could support the development of more targeted and effective exercise recommendations for pregnant women.\u003c/p\u003e \u003c/div\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThis systematic review and meta-analysis indicates that exercise interventions can significantly improve sleep quality in pregnant women. Although no statistically significant linear or nonlinear dose-response relationship was observed, the results of the subgroup analysis provide important guidance for optimizing exercise prescriptions during pregnancy: A mixed exercise regimen (such as Pilates or a combination of aerobic and strength training) lasting 5\u0026ndash;8 weeks, performed 3\u0026ndash;4 times per week, with each session exceeding 60 minutes, may yield better intervention outcomes. This suggests that during the unique physiological phase of pregnancy, the sleep-improving effects of exercise do not simply increase with higher \u0026ldquo;dose\u0026rdquo;; rather, moderate exercise frequency and duration play a key role in balancing physiological fatigue and avoiding excessive fatigue accumulation.\u003c/p\u003e \u003cp\u003eFrom both clinical and public health perspectives, exercise\u0026mdash;as a safe, low-cost, and easily accessible non-pharmacological intervention\u0026mdash;should be actively incorporated into routine prenatal care. When formulating exercise recommendations, clinicians should refer to the aforementioned \u0026ldquo;optimal\u0026rdquo; ranges while fully considering the pregnant woman\u0026rsquo;s gestational stage, health status, and individual adherence to provide personalized exercise plans.\u003c/p\u003e \u003cp\u003eAlthough this study is limited by the high heterogeneity of the included literature and the incompleteness of reported exercise intensity, it still provides empirical evidence for precise interventions in this field. Future research should focus on standardized measurement of exercise intensity and monitoring of adherence, and through the design of more rigorous randomized controlled trials, further validate the interactions among different exercise parameters to develop more scientific and precise guidelines for exercise during pregnancy.\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eDisclosure\u003c/strong\u003e \u003cp\u003e \u003cb\u003estatement\u003c/b\u003e \u003c/p\u003e \u003c/p\u003e \u003cp\u003eNo potential conflict of interest was reported by the author(s).\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eDisclosure statement\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo potential conflict of interest was reported by the author(s).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe research was not funded by any institution.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eEndong Qiao and Anping Chen contributed to the conceptualization and design of the study, and data analysis, and original manuscript draft and revision; Endong Qiao contributed to the data collection and interpretation of data; Anping Chen contributed to the supervision and reviewed/edited the manuscript; All authors have read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis article does not contain any studies with human participants or animals performed by any of the authors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable. This study is a systematic review and meta-analysis based on previously published studies; therefore, ethical approval and individual consent to participate are not required.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Publish declaration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll relevant data are within the manuscript and its additional file. The data are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eHaas JS, Rebecca A, Jackson E, Fuentes-Afflick, et al. Changes in the Health Status of Women during and after Pregnancy. J Gen Intern Med. 2005;20(1):45\u0026ndash;51. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/j.1525-1497.2004.40097.x\u003c/span\u003e\u003cspan address=\"10.1111/j.1525-1497.2004.40097.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNational Sleep Foundation. Summary of findings of the 2007 Sleep in America Poll. Available at: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://sleepfoundation.org/media-center/pressrelease/sleep-america-poll-summary-findings\u003c/span\u003e\u003cspan address=\"http://sleepfoundation.org/media-center/pressrelease/sleep-america-poll-summary-findings\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLamberg L. Sleeping Poorly While Pregnant May Not Be \u0026lsquo;Normal\u0026rsquo;. JAMA. 2006;295(12):1357\u0026ndash;61. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1001/jama.295.12.1357\u003c/span\u003e\u003cspan address=\"10.1001/jama.295.12.1357\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSedov ID, Emily E, Cameron S, Madigan, Lianne M, Tomfohr-Madsen. Sleep Quality during Pregnancy: A Meta-Analysis. Sleep Med Rev. 2018;38(April):168\u0026ndash;76. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.smrv.2017.06.005\u003c/span\u003e\u003cspan address=\"10.1016/j.smrv.2017.06.005\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSedov ID, Nina J, Anderson AK, Dhillon, Tomfohr-Madsen LM. Insomnia Symptoms during Pregnancy: A Meta-Analysis. J Sleep Res. 2021;30(1):e13207. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/jsr.13207\u003c/span\u003e\u003cspan address=\"10.1111/jsr.13207\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePien GW, and Richard J. Schwab. Sleep Disorders during Pregnancy. Sleep. 2004;27(7):1405\u0026ndash;17. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/sleep/27.7.1405\u003c/span\u003e\u003cspan address=\"10.1093/sleep/27.7.1405\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePalagini L, Cipriani E, Caruso V, et al. Insomnia during the Perinatal Period and Its Association with Maternal and Infant Psychopathology: A Systematic Review and Meta-Analysis. Curr Psychiatry Rep. 2023;25(11):617\u0026ndash;41. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s11920-023-01463-3\u003c/span\u003e\u003cspan address=\"10.1007/s11920-023-01463-3\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBaattaiah BA, Mutasim D, Alharbi NM, Babteen, Haneen M, Al-Maqbool FA, Babgi, Albatati AA. The Relationship between Fatigue, Sleep Quality, Resilience, and the Risk of Postpartum Depression: An Emphasis on Maternal Mental Health. BMC Psychol. 2023;11(1):10. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s40359-023-01043-3\u003c/span\u003e\u003cspan address=\"10.1186/s40359-023-01043-3\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBacaro V, Benz F, Pappaccogli A, et al. Interventions for Sleep Problems during Pregnancy: A Systematic Review. Sleep Med Rev. 2020;50:101234. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.smrv.2019.101234\u003c/span\u003e\u003cspan address=\"10.1016/j.smrv.2019.101234\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFeren S, Katyal A, Walsh JK. Efficacy of Hypnotic Medications and Other Medications Used for Insomnia. Sleep Med Clin. 2006;1(3):387\u0026ndash;97. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.jsmc.2006.06.011\u003c/span\u003e\u003cspan address=\"10.1016/j.jsmc.2006.06.011\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Insomnia.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOkun ML. A Review of Sleep-Promoting Medications Used in Pregnancy. Am J Obstet Gynecol. 2015;212(4):428\u0026ndash;41. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.ajog.2014.10.1106\u003c/span\u003e\u003cspan address=\"10.1016/j.ajog.2014.10.1106\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRiemann D, Baglioni C, Bassetti C, et al. European Guideline for the Diagnosis and Treatment of Insomnia. J Sleep Res. 2017;26(6):675\u0026ndash;700. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/jsr.12594\u003c/span\u003e\u003cspan address=\"10.1111/jsr.12594\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eQaseem A, Kansagara D, Forciea MA, et al. Management of Chronic Insomnia Disorder in Adults: A Clinical Practice Guideline from the American College of Physicians. Ann Intern Med. 2016;165(2):125\u0026ndash;33. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.7326/M15-2175\u003c/span\u003e\u003cspan address=\"10.7326/M15-2175\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTolin DF. Is Cognitive\u0026ndash;Behavioral Therapy More Effective than Other Therapies? A Meta-Analytic Review. Clin Psychol Rev. 2010;30(6):710\u0026ndash;20. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.cpr.2010.05.003\u003c/span\u003e\u003cspan address=\"10.1016/j.cpr.2010.05.003\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJurado-Fasoli L, Molina-Hidalgo AD-la-OC, Migueles JH, Manuel J, Castillo, Francisco J, Amaro-Gahete. Exercise Training Improves Sleep Quality: A Randomized Controlled Trial. Eur J Clin Invest. 2020;50(3):e13202. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/eci.13202\u003c/span\u003e\u003cspan address=\"10.1111/eci.13202\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYang P-Y, Ho K-H, Chen H-C, Meng-Yueh C. Exercise Training Improves Sleep Quality in Middle-Aged and Older Adults with Sleep Problems: A Systematic Review. J Physiotherapy. 2012;58(3):157\u0026ndash;63. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/S1836-9553(12)70106-6\u003c/span\u003e\u003cspan address=\"10.1016/S1836-9553(12)70106-6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChoong SY, Xin XYJ, Tan LJ, Cheng, and Ying Lau. Effectiveness of Exercise in Improving Sleep Outcomes among Perinatal Women: A Systematic Review and Meta-Analysis of Randomised Controlled Trials. Behav sleep Med. 2022;20(4):410\u0026ndash;28. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/15402002.2021.1931221\u003c/span\u003e\u003cspan address=\"10.1080/15402002.2021.1931221\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYang S-Y, Lan S-J, Yen Y-Y, Hsieh Y-P, Kung P-T, and Shao-Huan Lan. Effects of Exercise on Sleep Quality in Pregnant Women: A Systematic Review and Meta-Analysis of Randomized Controlled Trials. Asian Nurs Res. 2020;14(1):1\u0026ndash;10. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.anr.2020.01.003\u003c/span\u003e\u003cspan address=\"10.1016/j.anr.2020.01.003\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu D, Liu K, Xie L, He M, and Xiangping Liu. The Effect of Physical Activity on Sleep Disorders in Pregnant People: A Meta-Analysis of Randomized Controlled Trials. BMC Pregnancy Childbirth. 2025;25(1):139. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s12884-024-07129-z\u003c/span\u003e\u003cspan address=\"10.1186/s12884-024-07129-z\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSterne JAC, Jelena Savović MJ, Page et al. 2019. RoB 2: A Revised Tool for Assessing Risk of Bias in Randomised Trials. Research Methods \u0026amp; Reporting. \u003cem\u003eBMJ\u003c/em\u003e 366 (August): l4898. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1136/bmj.l4898\u003c/span\u003e\u003cspan address=\"10.1136/bmj.l4898\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSterne JAC, Miguel A, Hern\u0026aacute;n BC, Reeves, et al. ROBINS-I: A Tool for Assessing Risk of Bias in Non-Randomised Studies of Interventions. Res Methods Report BMJ. 2016;355(October):i4919. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1136/bmj.i4919\u003c/span\u003e\u003cspan address=\"10.1136/bmj.i4919\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHopkins WG, Stephen W, Marshall AM, Batterham, and Juri Hanin. Progressive Statistics for Studies in Sports Medicine and Exercise Science. Med Sci Sports Exerc. 2009;41(1):3. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1249/MSS.0b013e31818cb278\u003c/span\u003e\u003cspan address=\"10.1249/MSS.0b013e31818cb278\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eViechtbauer W, Mike WL, Cheung. Outlier and Influence Diagnostics for Meta-Analysis. Res Synthesis Methods. 2010;1(2):112\u0026ndash;25. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/jrsm.11\u003c/span\u003e\u003cspan address=\"10.1002/jrsm.11\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKadlec D, Sainani KL, and Sophia Nimphius. With Great Power Comes Great Responsibility: Common Errors in Meta-Analyses and Meta-Regressions in Strength \u0026amp; Conditioning Research. \u003cem\u003eSports Medicine\u003c/em\u003e. N Z). 2023;53(2):313\u0026ndash;25. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s40279-022-01766-0\u003c/span\u003e\u003cspan address=\"10.1007/s40279-022-01766-0\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Auckland.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHiggins JPT, Thompson SG. Quantifying Heterogeneity in a Meta-Analysis. Stat Med. 2002;21(11):1539\u0026ndash;58. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/sim.1186\u003c/span\u003e\u003cspan address=\"10.1002/sim.1186\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEgger M, Smith GD, Schneider M, Minder C. Bias in Meta-Analysis Detected by a Simple. Graphical Test Paper BMJ. 1997;315(7109):629\u0026ndash;34. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1136/bmj.315.7109.629\u003c/span\u003e\u003cspan address=\"10.1136/bmj.315.7109.629\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHiggins TJ, Chandler J, Cumpston M, Li T, Page MJ et al. Assessing risk of bias due to missing results in a synthesis. In: Cochrane handbook for systematic reviews of interventions. Second edition. Chichester (UK): John Wiley \u0026amp; Sons; 2019, pp 365.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAfonso Jos\u0026eacute;, Clemente RR-CFM, Fionn Cl\u0026eacute;irigh B\u0026uuml;ttner, and Renato Andrade. 2024. The Perils of Misinterpreting and Misusing \u0026lsquo;Publication Bias\u0026rsquo; in Meta-Analyses: An Education Review on Funnel Plot-Based Methods. \u003cem\u003eSports Medicine\u003c/em\u003e (Auckland, N.Z.) 54 (2): 257\u0026ndash;69. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s40279-023-01927-9\u003c/span\u003e\u003cspan address=\"10.1007/s40279-023-01927-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDuval S, Tweedie R. Trim and Fill: A Simple Funnel-Plot-Based Method of Testing and Adjusting for Publication Bias in Meta-Analysis. Biometrics. 2000;56(2):455\u0026ndash;63. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/j.0006-341x.2000.00455.x\u003c/span\u003e\u003cspan address=\"10.1111/j.0006-341x.2000.00455.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShi L, and Lifeng Lin. The Trim-and-Fill Method for Publication Bias: Practical Guidelines and Recommendations Based on a Large Database of Meta-Analyses. Medicine. 2019;98(23):e15987. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1097/MD.0000000000015987\u003c/span\u003e\u003cspan address=\"10.1097/MD.0000000000015987\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAkbaş Pınar, Şeng\u0026uuml;l YS\u0026ouml;zbir. The Effect of Progressive Muscle Relaxation Exercise on the Intensity of Symptoms and Quality of Sleep and Quality of Life in Pregnant Women with Restless Leg Syndrome. Patient Educ Couns. 2023;113(August):107768. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.pec.2023.107768\u003c/span\u003e\u003cspan address=\"10.1016/j.pec.2023.107768\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRashed AA, Bekhatro A, Khalil AK, and Hanaa Mohamed Abo Shereda. Effect of Non-Pharmacological Interventions on Sleep Quality during Pregnancy among Primigravida. South Asian Res J Nurs Healthc. 2019;01(01):8\u0026ndash;17. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.36346/sarjnhc.2019.v01i01.002\u003c/span\u003e\u003cspan address=\"10.36346/sarjnhc.2019.v01i01.002\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBatool A, Kousar Z, Tariq M, Saleem M, Anwer N, and Javeria Aslam. Comparison of Aerobic and Pilates Exercises on Depression and Sleep Quality in Primigravida Females. Pakistan J Med Health Sci. 2024;17(11):27\u0026ndash;30. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.53350/pjmhs02023171127\u003c/span\u003e\u003cspan address=\"10.53350/pjmhs02023171127\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBenito-Villena R, Naveiro-Fuentes IG-M et al. 2022. Walking Promotion in Pregnancy and Its Effects on Insomnia: Results of Walking_Preg Project (WPP) Clinical Trial. \u003cem\u003eInternational Journal of Environmental Research and Public Health\u003c/em\u003e 19 (16): 10012. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/ijerph191610012\u003c/span\u003e\u003cspan address=\"10.3390/ijerph191610012\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBroberg L, Damm P, Frokjaer VG, et al. Evaluation of the Effect of Supervised Group Exercise on Self-Reported Sleep Quality in Pregnant Women with or at High Risk of Depression: A Secondary Analysis of a Randomized Controlled Trial. Int J Environ Res Public Health. 2022;19(10):5954. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/ijerph19105954\u003c/span\u003e\u003cspan address=\"10.3390/ijerph19105954\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen C, Jinguo Zhai, Shuiwang Hu, et al. Effects of Different Physical Exercise Types on Health Outcomes of Individuals with Hypertensive Disorders of Pregnancy: A Prospective Randomized Controlled Clinical Study. J Maternal-Fetal Neonatal Medicine: Official J Eur Association Perinat Med Federation Asia Ocean Perinat Soc Int Soc Perinat Obstetricians. 2024;37(1):2421278. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/14767058.2024.2421278\u003c/span\u003e\u003cspan address=\"10.1080/14767058.2024.2421278\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eField T, Diego M, Delgado J, and Lissette Medina. Tai Chi/Yoga Reduces Prenatal Depression, Anxiety and Sleep Disturbances. Complement Ther Clin Pract. 2013;19(1):6\u0026ndash;10. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.ctcp.2012.10.001\u003c/span\u003e\u003cspan address=\"10.1016/j.ctcp.2012.10.001\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGolmakani. Nahid, and Negar Asghari Pour. n.d. \u003cem\u003eComparing the Effects of Progressive Muscle Relaxation and Guided Imagery on Sleep Quality in Primigravida Women Referring to Mashhad Health Care Centers\u0026thinsp;\u0026ndash;\u0026thinsp;1393\u003c/em\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHawkins M, Marcus B, Pekow P, et al. The Impact of a Randomized Controlled Trial of a Lifestyle Intervention on Sleep among Latina Postpartum Women. Annals Behav Medicine: Publication Soc Behav Med. 2021;55(9):892\u0026ndash;903. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/abm/kaaa118\u003c/span\u003e\u003cspan address=\"10.1093/abm/kaaa118\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHuang Wenyu L, Yonghan, Xiaoying X. 2020. A Study on the Effects of Moderate-to-Low-Intensity Aerobic Exercise During the Second and Third Trimesters on the Prenatal Quality of Life and Maternal-Fetal Outcomes in Advanced-Age Pregnant Women. Guangzhou Med 51 (5). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://kns.cnki.net/KCMS/detail/detail.aspx?dbcode=CJFQ\u003c/span\u003e\u003cspan address=\"https://kns.cnki.net/KCMS/detail/detail.aspx?dbcode=CJFQ\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u0026amp;dbname=CJFDLAST2020\u0026amp;filename=GZYY202005015.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHyun A-H, Cho J-Y, Jung-Hoon Koo. Effect of Home-Based Tele-Pilates Intervention on Pregnant Women: A Pilot Study. Healthcare (Basel Switzerland). 2022;10(1):125. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/healthcare10010125\u003c/span\u003e\u003cspan address=\"10.3390/healthcare10010125\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKim H-B, and Ah-Hyun Hyun. Psychological and Biochemical Effects of an Online Pilates Intervention in Pregnant Women during COVID-19: A Randomized Pilot Study. Int J Environ Res Public Health. 2022;19(17):10931. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/ijerph191710931\u003c/span\u003e\u003cspan address=\"10.3390/ijerph191710931\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNavas A, Carrascosa Mar\u0026iacute;aDC, Artigues C, et al. Effectiveness of Moderate-Intensity Aerobic Water Exercise during Pregnancy on Quality of Life and Postpartum Depression: A Multi-Center, Randomized Controlled Trial. J Clin Med. 2021;10(11):2432. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/jcm10112432\u003c/span\u003e\u003cspan address=\"10.3390/jcm10112432\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e\u0026Ouml;zkan S, Aydın, and G\u0026uuml;lay Rathfisch. The Effect of Relaxation Exercises on Sleep Quality in Pregnant Women in the Third Trimester: A Randomized Controlled Trial. Complement Ther Clin Pract. 2018;32(August):79\u0026ndash;84. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.ctcp.2018.05.008\u003c/span\u003e\u003cspan address=\"10.1016/j.ctcp.2018.05.008\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRodriguez-Blanque R, S\u0026aacute;nchez-Garc\u0026iacute;a JC, S\u0026aacute;nchez-L\u0026oacute;pez AM, Mur-Villar N, Aguilar-Cordero MJ. The Influence of Physical Activity in Water on Sleep Quality in Pregnant Women: A Randomised Trial. Women Birth: J Australian Coll Midwives. 2018;31(1):e51\u0026ndash;58. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.wombi.2017.06.018\u003c/span\u003e\u003cspan address=\"10.1016/j.wombi.2017.06.018\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShen W-C, and Chung-Hey Chen. Effects of Non-Supervised Aerobic Exercise on Sleep Quality and Maternal-Fetal Attachment in Pregnant Women: A Randomized Controlled Trial. Complement Ther Med. 2021;57:102671. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.ctim.2021.102671\u003c/span\u003e\u003cspan address=\"10.1016/j.ctim.2021.102671\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSonmezer E, \u0026Ouml;zk\u0026ouml;sl\u0026uuml; MA, Hayri Baran Yosmaoğlu. The Effects of Clinical Pilates Exercises on Functional Disability, Pain, Quality of Life and Lumbopelvic Stabilization in Pregnant Women with Low Back Pain: A Randomized Controlled Study. J Back Musculoskelet Rehabil. 2021;34(1):69\u0026ndash;76. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3233/BMR-191810\u003c/span\u003e\u003cspan address=\"10.3233/BMR-191810\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShu Ling X, Mingxia W, Chuanfang Z, Wei T, Chuang. and Chen Dan. 2018. The Effects of Mindfulness Yoga Training on Sleep Quality, Anxiety, and Fear of Childbirth Among Pregnant Women. Chin J Nurs Manage 18 (10). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://kns.cnki.net/KCMS/detail/detail.aspx?dbcode=CJFQ\u003c/span\u003e\u003cspan address=\"https://kns.cnki.net/KCMS/detail/detail.aspx?dbcode=CJFQ\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u0026amp;dbname=CJFDLAST2018\u0026amp;filename=GLHL201810034.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTayhan F, and Aysenur Karakus. Effect of Pilates on Sleep Quality, Eating Disorders and Occupational Balance in Pregnant Women. Arch Gynecol Obstet. 2025;312(6):2187\u0026ndash;98. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s00404-025-08202-4\u003c/span\u003e\u003cspan address=\"10.1007/s00404-025-08202-4\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYıldırım P, Basol G, and Ali Yavuz Karahan. Pilates-Based Therapeutic Exercise for Pregnancy-Related Low Back and Pelvic Pain: A Prospective, Randomized, Controlled Trial. Turkish J Phys Med Rehabilitation. 2023;69(2):207\u0026ndash;15. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.5606/tftrd.2023.11054\u003c/span\u003e\u003cspan address=\"10.5606/tftrd.2023.11054\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu D, Liu K, Xie L, He M, and Xiangping Liu. The Effect of Physical Activity on Sleep Disorders in Pregnant People: A Meta-Analysis of Randomized Controlled Trials. BMC Pregnancy Childbirth. 2025;25(1):139. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s12884-024-07129-z\u003c/span\u003e\u003cspan address=\"10.1186/s12884-024-07129-z\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHuang H-H, Stubbs B, Chen L-J, et al. The Effect of Physical Activity on Sleep Disturbance in Various Populations: A Scoping Review of Randomized Clinical Trials. Int J Behav Nutr Phys Activity. 2023;20(1):44. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s12966-023-01449-7\u003c/span\u003e\u003cspan address=\"10.1186/s12966-023-01449-7\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTan X, Lieve T, van Egmond JC, and Christian Benedict. The Role of Exercise-Induced Peripheral Factors in Sleep Regulation. Mol Metabolism. 2020;42:101096. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.molmet.2020.101096\u003c/span\u003e\u003cspan address=\"10.1016/j.molmet.2020.101096\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMennitti C, Farina G, Antonio Imperatore, et al. How Does Physical Activity Modulate Hormone Responses? Biomolecules. 2024;14(11):1418. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/biom14111418\u003c/span\u003e\u003cspan address=\"10.3390/biom14111418\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChiang J-K, Lin Y-C, Hung T-Y, Kao H-H, and Yee-Hsin Kao. The Impact on Autonomic Nervous System Activity during and Following Exercise in Adults: A Meta-Regression Study and Trial Sequential Analysis. Medicina. 2024;60(8):1223. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/medicina60081223\u003c/span\u003e\u003cspan address=\"10.3390/medicina60081223\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDong J, Chi J, Fung-Chua E, Lei. Effects of Prenatal Exercise on Prenatal and Postpartum Depression and Anxiety Symptoms: A Systematic Review and Network Meta-Analysis. J Affect Disord. 2026;393(January):120438. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.jad.2025.120438\u003c/span\u003e\u003cspan address=\"10.1016/j.jad.2025.120438\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-pregnancy-and-childbirth","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"prch","sideBox":"Learn more about [BMC Pregnancy and Childbirth](http://bmcpregnancychildbirth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/prch/default.aspx","title":"BMC Pregnancy and Childbirth","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-9453570/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9453570/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eTo systematically evaluate the effects of exercise interventions on sleep quality in pregnant women and to explore the dose\u0026ndash;response relationship between intervention duration, exercise frequency, and duration of individual exercise sessions and sleep improvement.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003e Conducted in accordance with PRISMA guidelines and pre-registered (PROSPERO ID: CRD420261350741), we searched PubMed, Embase, CNKI, Scopus, and Web of Science from inception to March 2026. Randomized controlled trials (RCTs) and controlled clinical trials examining exercise and sleep quality (measured by validated scales like PSQI) were included. Standardized mean differences (SMD) with 95% confidence intervals (CI) were pooled using random-effects models. Heterogeneity was explored via meta-regression and predefined subgroup analyses to identify optimal exercise \"dosages.\"\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eTwenty studies involving 2,204 participants (1,136 exercise; 1,068 control) were included. Meta-analysis demonstrated that exercise significantly improved sleep quality in pregnant women (SMD\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;0.82; 95% CI [\u0026minus;\u0026thinsp;1.19, \u0026minus;\u0026thinsp;0.45]; P\u0026thinsp;\u0026lt;\u0026thinsp;0.00001), despite substantial heterogeneity (I\u0026sup2; = 93.3%). Subgroup analyses suggested that interventions lasting 9\u0026ndash;12 weeks, a frequency of 3 sessions/week, and a session duration exceeding 60 minutes yielded the most pronounced improvements. While exploratory meta-regression did not confirm a linear dose\u0026ndash;response relationship (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05), a trend toward greater efficacy with increased session duration was observed. No exercise-related adverse maternal or fetal events were reported in the included trials.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eExercise is a safe and effective non-pharmacological intervention for enhancing sleep quality during pregnancy. While the dose\u0026ndash;response relationship remains non-linear, structured programs exceeding 60 minutes per session appear particularly beneficial. Clinicians should consider these parameters when prescribing prenatal exercise, although high heterogeneity across studies warrants a personalized approach and further high-quality, large-scale RCTs to refine these recommendations.\u003c/p\u003e","manuscriptTitle":"Exercise Improves Sleep Quality in Pregnant Women: A Meta-Analysis with Exploratory Dose–Response Analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-11 10:34:41","doi":"10.21203/rs.3.rs-9453570/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-05-18T21:26:18+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"89937040266045308611360974778806220734","date":"2026-05-08T22:42:33+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-30T15:56:13+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-04-23T06:58:32+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-21T00:26:02+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-21T00:25:08+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Pregnancy and Childbirth","date":"2026-04-18T02:30:21+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-pregnancy-and-childbirth","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"prch","sideBox":"Learn more about [BMC Pregnancy and Childbirth](http://bmcpregnancychildbirth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/prch/default.aspx","title":"BMC Pregnancy and Childbirth","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"52cc6571-fc95-4376-afb9-ceea64276515","owner":[],"postedDate":"May 11th, 2026","published":true,"recentEditorialEvents":[{"type":"editorInvitedReview","content":"","date":"2026-05-18T21:26:18+00:00","index":40,"fulltext":""},{"type":"reviewerAgreed","content":"89937040266045308611360974778806220734","date":"2026-05-08T22:42:33+00:00","index":39,"fulltext":""},{"type":"reviewersInvited","content":"16","date":"2026-04-30T15:56:13+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-11T10:34:41+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-11 10:34:41","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9453570","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9453570","identity":"rs-9453570","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}