Effects of sleep quality, anxiety, and depression on miscarriage among pregnant women during the COVID-19 pandemic: Prospective Observational Study

Effects of sleep quality, anxiety, and depression on miscarriage among pregnant women during the COVID-19 pandemic: Prospective Observational Study | 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 Help Center Sign In Submit a Preprint Cite Share Download PDF Article Effects of sleep quality, anxiety, and depression on miscarriage among pregnant women during the COVID-19 pandemic: Prospective Observational Study Tianan Jiang, Jinhua Pan, Xiaodan Zhu, Linyu Zhou, Shanyu Yin, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3336014/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Importance: Sleep quality is related to miscarriage of pregnant women, which can also lead to depression and anxiety. Currently, there is no research revealing the role of anxiety and depression in the relationship between sleep quality and miscarriage among pregnant women and their interacting mechanism. Objective This study aims to uncover the mechanisms and quantitative dose response relationships among these factors, as well as develop a predictive model for the miscarriage rate. Methods In this study, 1,058 pregnant women in mainland China were recruited. All of them met inclusion criteria. Sleep quality was assessed subjectively using the Pittsburgh Sleep Quality Index questionnaire (PSQI). Anxiety was assessed subjectively using the Self-Rating Anxiety Scale questionnaire (SAS). Depression was assessed subjectively using the Self-Rating Depression Scale questionnaire (SDS). We used mediation analysis to explore how anxiety and depression mediate the relationship between sleep quality and miscarriage. We employed restricted cubic spline (RCS) combined with logistic regression to examine the dose-response relationship between these variables. Additionally, a directed acyclic graph was used to reveal their interactions. Furthermore, we constructed a nomogram model for predicting the occurrence of unexpected miscarriages in pregnant and postpartum women. Results During our investigation, 16.4% of the participant pregnant women had a miscarriage. Our results showed a significant association between sleep quality, anxiety, depression, pregnant age and miscarriage both unadjusted and multivariable multinomial logistic regression. Dose-response relationships showed that the miscarriage rate slowly increases with increasing PSQI, SAS and SDS score at first. However, when a certain threshold is reached, even slight increases in the scores of SAS, SDS, and PSQI will lead to a sharp rise in the miscarriage rate. The threshold for PSQI, SAS and SDS is 15, 60, and 65, respectively. Anxiety mediated the effect of sleep quality on miscarriage by 55.88% (95% CI 41.18,69.12) and depression had a similar mediation effect (16.18% [95% CI 7.35,27.94]). Conclusions and Relevance: The quantitative dose response relationships between PSQI, SAS, SDS, and the miscarriage rate among pregnant women are all positive. In the impact of sleep quality on the miscarriage rate, anxiety and depression also play significant mediating roles. By revealing high-risk pregnant women, early intervention can be provided, aiming to reduce the miscarriage rate among pregnant women during the COVID-19 pandemic. Health sciences/Health care/Public health/Epidemiology Health sciences/Medical research/Epidemiology Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Miscarriage is generally defined as the loss of a pregnancy before viability. In recent years, with the rapid development of society, increasing life pressures, worsening environmental pollution, and the rise in the number of advanced maternal age pregnancies, the incidence of miscarriage has been on the rise. An estimated 23 million miscarriages occur every year worldwide, translating to 44 pregnancy losses each minute. The pooled risk of miscarriage is 15.3% (95% CI 12.5–18.7%) of all recognised pregnancies [ 1 ] . Many factors can contribute to the occurrence of miscarriage in pregnant women, sleep quality has been proven to be a risk factor for unexpected miscarriage during the perinatal period in women [ 2 ] . Research has also confirmed the impact of poor sleep quality on spontaneous miscarriage at the genetic level [ 3 ] . Sleep is a fundamental physiological need for humans, which helps alleviate fatigue and restore energy. Sufficient sleep aids in the clearance of neurotoxic waste accumulated during wakefulness [ 4 ] . Sleep deprivation often leads to fatigue, lack of concentration, delayed reaction time, and impaired judgment [ 5 ] . In experimental settings, sleep quality is causally associated with two recognized causes of miscarriage: anxiety and depression. Pregnant and postpartum women, as a special population, often experience significant changes in reproductive hormone levels such as estrogen and progesterone during the perinatal period. Physiological changes, such as increased frequency of urination and difficulty finding a comfortable sleeping position, as well as psychological turmoil, can lead to poor sleep quality, anxiety, and depression. On average, approximately 45% of pregnant women experience sleep disturbances [ 6 ] . It has been reported that poor sleep quality is associated with perinatal anxiety and depression (OR = 1.56–6.83) [ 2 ] . Now, with the added impact of the COVID-19 pandemic, the situation is even more challenging. Prior to the pandemic, the reported prevalence of perinatal depression among women was around 15–20% [ 7 , 8 ] . However, among women surveyed during the pandemic, over a third (36.4%) were found to have clinically significant levels of depression [ 7 ] . Participants reported feeling intense sadness, loss, disappointment, and worry due to the pandemic [ 9 ] . Some women have been unable to access expected support from family members or have had to rely only on their partners or peer groups for help due to concerns about COVID-19 [ 10 ] . Therefore, it is of utmost importance to observe the modifiable factors (such as sleep quality, anxiety, and depressive symptoms) affecting the miscarriage rate among pregnant and postpartum women during the pandemic, and to implement early prevention and intervention measures. Several studies have already explored and investigated the sleep quality, anxiety, depression, and miscarriage rates among pregnant and postpartum women during the pandemic [ 11 , 12 ] . However, these studies often provide only simple descriptions of the sleep patterns, anxiety, depression levels, miscarriage rate, and analysis of influencing factors. They have not explored how anxiety and depression impact miscarriages in the context of sleep quality, the extent of their influence, and the mechanisms of interaction between these factors. Additionally, there is limited research on establishing predictive models for miscarriages during the COVID-19 pandemic based on variables such as anxiety, depression, and sleep quality. We aimed to characterize the prevalence, type, and clinical consequences of sleep quality in a broad cohort of pregnant women who had been admitted to hospital during COVID-19 pandemic period using a multimodal approach. We hypothesized that sleep quality would be associated with miscarriage and that relationship would be mediated by anxiety and depression. Based on this, we utilized mediation analysis to explore how anxiety and depression mediate the relationship between sleep quality and miscarriage. We employed restricted cubic spline (RCS) combined with logistic regression to examine the dose-response relationship between these variables. Additionally, a directed acyclic graph was used to reveal their interactions. Furthermore, we constructed a nomogram model for predicting the occurrence of unexpected miscarriages in pregnant and postpartum women under different circumstances. This model serves to better alert pregnant and postpartum women, highlighting the importance of improving sleep quality and reducing anxiety and depression. This, in turn, facilitates early prevention of miscarriages and reduces the miscarriage rate. Methods Study design This was a prospective cohort study conducted in the First Affiliated Hospital, Zhejiang University School of Medicine. The primary aim of this cohort study is to investigate the short- and long-term health effects of prenatal exposures (eg, poor sleep quality, anxiety and depression) on mothers and their children. Baseline recruitment was conducted in May 2022, and pregnant women who visited the outpatient clinic for the first prenatal examination at First Affiliated Hospital, Zhejiang University School of Medicine were recruited when they met the following inclusion criteria: <14 gestational weeks, singleton pregnancy, plan to have antenatal care and delivery in First Affiliated Hospital, Zhejiang University School of Medicine, and resided in Hangzhou during the past half year and have no plan to move out after delivery. The study was approved by the institutional review boards at the First Affiliated Hospital of Zhejiang University School of Medicine, and all participants gave written informed consent at the enrollment. This study conforms to the ethical guidelines of the 1975 Declaration of Helsinki (6th revision, 2008) as reflected in a priori approval by the institution's human research committee. Follow-up for Pregnancy Outcomes The follow-up of the pregnancy outcomes was carried out by local healthcare personnel. Pregnant women receive regular antenatal care and give birth in the hospital. Information on pregnancy outcomes is obtained through the hospital's medical electronic information system, which automatically records information during each antenatal care and delivery. Miscarriage is defined as the loss of pregnancy that occurs before reaching 20 completed weeks of gestation [ 13 ] . The prevalence of miscarriage was defined as the proportion of participants who had a miscarriage to all participants. Covariates Covariates were collected at the first prenatal visit, including age, educational level, occupation, history of cesarean section, history of preterm birth, history of miscarriage, history of pregnancy, history of operation, gravidity, number of children, pre-pregnancy weight, basic disease, bad habits (Smoking or drinking during pregnancy), COVID-19 infection, COVID-19 infection symptom temperature and history of antipyretic drug use, vaccination history of COVID-19 and flu, anxiety, depression, sleep quality and so on. Pre-pregnancy BMI was calculated using weight (in kilograms) divided by the square of height (in meters). Anxiety symptoms was assessed using the Zung Self-Rating Anxiety Scale developed by Zung [ 14 ] . It consists of 20 questions. Responses are scored on a four-point scale, ranging from 1 (no or very little time) to 2 (sometimes), to 3 (most of the time) and 4 (most or all of the time). The raw score is the sum of all responses. The standard score is calculated as 1.25 times the original score. The current study used an index score cutoff of ≥ 50 to diagnose anxiety. Depression symptoms was assessed using the Zung Self-Rating Depression Scale developed by Zung [ 15 ] . It consists of 20 questions. Responses are scored on a four-point scale, ranging from 1 (no or very little time) to 2 (sometimes), to 3 (most of the time) and 4 (most or all of the time). The raw score is the sum of all responses. The standard score is calculated as 1.25 times the original score. The current study used an index score cutoff of ≥ 53 to diagnose depression. Sleep quality was assessed using the Pittsburgh Sleep Quality Index, a self-report scale used to assess respondents' sleep quality over a 2-week period [ 16 ] . PSQI consists mainly of 18 items with 7 components, which represent sleep quality, time to fall asleep, sleep duration, sleep efficiency, sleep disorders, hypnotic drugs, and daytime dysfunction. Each question is rated on a scale of 0 to 3. The sum of the 7 component scores is the total score of PSQI. The higher the score, the worse the sleep. The total score ranged from 0 to 21, with a score of > 5 indicating poor sleep quality (sleep disturbance) in pregnant women, with 98% high sensitivity and 90% specificity (kappa = 0.89, p < 0.01), suitable for Chinese [ 16 ] . Statistical analysis Mean (SD) values and proportions of baseline characteristics were calculated. Prevalence and 95%CI of miscarriage was calculated. Miscarriage prevalence in women with different characteristics were also compared using chi-square test or Wilcoxon rank sum test. Multivariable logistic regression models were used to estimate the adjusted risk ratios (RRs) and their 95% CIs of miscarriage for women with different exposures. We combined logistic model and RCS methods to describe the stoichiometric response relationship with anxiety, depression, sleep quality, age and miscarriage (RCS details seen appendix pp1). We used nomogram model to predict the probability of miscarriage (nomogram details seen appendix pp1&pp2). Mediation was evaluated with linear regression with the product of coefficients method to estimate the direct and indirect effects of the relationship (mediation analysis details seen appendix pp2) and draw their directed acyclic graph (appendix pp 8), done with the R package lavaan version 0.6–12 (appendix pp 2). All data were analysed with R (version 4.2.0). A p value less than 0.05 was considered significant. Results Participant recruitment A total of 1,058 participants were enrolled, of whom 997 participants attended. Subjective sleep quality was measured with the PSQI questionnaire. Depression and anxiety status were measured with SD and SAS questionnaires, respectively. 801 of 997 (80.3%) participants attended follow-up offering the above three questionnaire (Figure S1 ). Of these, 357 participants lost to follow-up or went to other hospital or did not submit the complete questionnaire, 444 participants entered the final analysis of anxiety, depression and sleep quality. 942 of 997 (94.5%) participants have complete clinical information. Of these, 665 participants complete the follow-up and included in the final analysis (Figure S1 ). Basic Characteristic Among all the 665 pregnant women included, 10.4% (n = 69) were unemployed, 91.3% (n = 607) had bachelor or above degree, 32.7% (n = 217) were overweight or obese, 8.9% (n = 59) had basic diseases, 69.0% (n = 459) were having their first pregnancy, 28.6% (n = 190) had a history of cesarean section, 28.9% (n = 180) had a history of abortion, 19.8% (n = 132) had a history of operation. The mean age at baseline was 30.1 (SD: 3.4) (Table 1 ). The results for each variable grouped by miscarriage are shown in Table S1 (appendix pp3-pp5). Table 1 Demographics, anxiety, depression and sleep quality of the study participants Overall n 665 Age (mean (SD)) 30.1 (3.4) Education (%) Bachelor's degree 502 (75.5) Master degree or above 105 (15.8) Senior high school and below 58 (8.7) Prepregnant BMI Underweight 35 (5.3) Normal weight 412 (62.0) Overweight 196 (29.5) Obese 21 (3.2) Occupation = unemployed (%) 69 (10.4) COVID-19 (%) Yes 525 (78.9) No 125 (18.8) Unclear 15 (2.3) Symptom (%) Asymptomatic 232 (43.0) Ordinary 284 (52.6) Other 22 (4.1) severe 2 (0.4) Temperature (%) Normal a 53 (9.8) 37 ~ 38℃ 143 (26.5) 38 ~ 39℃ 302 (55.9) ≥ 39℃ 42 (7.8) Febrifuge = Yes (%) 168 (34.5) Previous infection (%) Yes 359 (54.0) No 287 (43.2) Unclear 19 (2.9) Basic disease = Yes (%) 59 (8.9) Hospital = No (%) 637 (95.8) COVID-19 vaccine (%) No 73 (11.0) Thrice or more 264 (39.7) Twice or less 328 (49.3) Flu vaccine (%) Yes 41 (6.2) No 592 (89.0) Unclear 32 (4.8) Bad habits = Yes (%) 6 (0.9) First pregnancy = Yes (%) 459 (69.0) History of cesarean section (%) Reject to answer 144 (21.7) Yes 190 (28.6) No 331 (49.8) Miscarriage = Yes (%) 109 (16.4) Number of full-term births (%) 0 475 (76.1) 1 145 (23.2) 2 4 (0.6) Number of premature births (%) 0 619 (99.4) 1 3 (0.5) 2 1 (0.2) Number of abortions (%) No 442 (71.1) Once 132 (21.2) Twice or more 48 (7.7) Number of children = One or more (%) 149 (24.0) Operation = Yes (%) 132 (19.8) Gestational hypertension = No (%) 493 (99.6) Gestational diabetes = No (%) 453 (89.5) Pregnancy with thrombocytopenia = No (%) 471 (99.4) Embolism = No (%) 425 (89.9) Antiphospholipid syndrome = No (%) 456 (97.2) Hypoproteinemia = No (%) 460 (99.4) Anemia = No (%) 373 (74.7) Iron deficiency = No (%) 382 (78.1) Factor1 (mean (SD)) 2.3 (0.7) Factor2 (mean (SD)) 2.3 (0.6) Factor3 (mean (SD)) 1.3 (1.2) Factor4 (mean (SD)) 1.9 (0.9) Factor5 (mean (SD)) 2.5 (0.5) Factor6 (mean (SD)) 1.7 (0.9) Factor7 (mean (SD)) 2.1 (0.8) PSQI (mean (SD)) 13.9 (2.8) Poor sleep quality (PSQI score ≥ 5) No 0 (0%) Yes 444 (100%) SAS (mean (SD)) 38.4 (6.0) SAS standard score (mean (SD)) 48.0 (7.5) Anxiety (SAS standard score ≥ 50) No 293 (66.0%) Yes 151 (34.0%) SDS (mean (SD)) 44.2 (6.3) SDS standard score (mean (SD)) 55.3 (7.8) Depression (SDS standard score ≥ 53) No 164 (36.9%) Yes 280 (63.1%) a: The normal body temperature of the armpit is used (36–37℃) . COVID-19 infection Among all the 665 pregnant women included, 78.9% (n = 525) were infected with COVID-19 while under investigation (of these, 43.0% were asymptomatic, 52.6% were ordinary), 90.2% (n = 487) had a fever. Of these, 34.5% (n = 168) took antipyretic medicine (155 took P-acetylamino acid, 4 took ibuprofen, 1 took lianhua Qingwen, 8 took other medicine). Of all the participants, 54.0% (n = 359) had infected with COVID-19 before, 89.0% (n = 592) had vaccinated COVID-19 vaccine and 6.2% (n = 41) had vaccinated flu vaccine within three years (Table 1 ). The results for each variable grouped by miscarriage are shown in Table S1 (appendix pp3-pp5). Sleep quality, anxiety and depression During the COVID-19 period, the average global PSQI score was 13.9 (SD: 2.8) of the pregnant women participated in this study, 100% (n = 444) of them had poor sleep quality. The average SAS standard score were 48.0 (SD: 7.5), 34.0% (n = 151) were anxiety. The average SDS standard score were 55.3 (SD: 7.8), 63.1% (n = 280) were depression (Table 1 ). The results for each variable grouped by miscarriage are shown in Table S1 (appendix pp3-pp5). Prevalence of miscarriage in populations with different characteristics Out of 665 pregnant women, 109 (16.4%, 95%CI:[13.8%-19.4%]) had a miscarriage. Compared with women who did not miscarriage, participants who had a miscarriage tend to have significantly higer SAS scores (P < 0.05) (Fig. 1 A). Similarly, SDS and PSQI scores tend to have higher values in those women who had a miscarriaged (Fig. 1 B&C). While BMI, age and number of abortions did not have a relationship with miscarriage of participant pregnant women (Fig. 1 D,E &F). Education, COVID-19 infection, occupation, first pregnancy, history of cesarean section and basic disease did not have relationship with miscarriage of participant pregnant women either (Figure S2). Association between sleep quality, anxiety, depression and miscarriage The relationship between sleep quality and miscarriage was assessed. Participants with poor sleep quality (assessed by the Pittsburgh Sleep Quality Index) were more likely to have a miscarriage compared to participants who reported lower PSQI values (Figure S3). A similar association was observed between anxiety, depression and miscarriage. Participants who reported higher SAS and SDS value were more likely to have a miscarriage compared to participants who reported lower SAS and SDS values (Figure S3). Those pregnant women who were older are more likely to have a miscarriage (Figure S3). Dose-response relationships between miscarriage rate and anxiety, sleep quality, depression, age Using multivariable logistic regression model combined with RCS method, the dose-response relationships between SAS score, PSQI score, SDS score, age, and miscarriage were analyzed separately (Fig. 2 ). The overall relationship between PSQI score and miscarriage rate indicates that higher PSQI scores are associated with higher miscarriage rates. Initially, the miscarriage rate slowly increases with increasing PSQI score. However, after PSQI > 15, even slight increases in PSQI have a significant impact on the miscarriage rate. The overall relationship between SDS score and miscarriage rate is also positive. When SDS score increases, the abortion rate initially remains stable. However, after SDS > 60, the miscarriage rate increases slowly at first and then sharply with increasing SDS score. A similar pattern is observed for SAS score. When SAS score 65, the abortion rate sharply increases with increasing SAS score. Age shows a clear negative correlation with abortion rate, indicating that the abortion rate decreases as age increases (Fig. 2 ). Prediction the probability of miscarriage based on nomogram model Based on the logistic regression model, a nomogram model was constructed to predict the probability of abortion occurrence (Fig. 3 ). By combining significant variables from logistic regression: age, SAS score, SDS score, and PSQI score, the corresponding scores for each indicator are given on the point scale axis. The total score is obtained by adding the score values for each indicator. The probability of miscarriage in pregnant women is then determined based on the total score, with higher scores indicating a greater likelihood of miscarriage. The discriminative power of this nomogram prediction model is shown in Figure S4, with an AUC of 99.8%, corrected pAUC of 99.0%, indicating excellent predictive performance. Mediation analysis Given that anxiety and depression are recognised causes of miscarriage, mediation analysis was done to investigate the contribution of anxiety and depression in mediating the effect between sleep and miscarriage during COVID-19 period (Fig. 4 A). Anxiety following discharge from hospital mediated the effect of sleep quality on miscarriage by 55.88% (95% CI 41.18, 69.12) and depression had a similar mediation effect (16.18% [95% CI 7.35,27.94]; Fig. 4 B; Table S2, appendix p8), and their directed acyclic graph are shown in the appendix (appendix pp 8) Discussions To our knowledge, this is the first study exploring the mediating role of anxiety and depression in the relationship between sleep quality and the miscarriage rate, and their dose response relationship and interaction relationship. In our study, most of the participant pregnant women (78.9%) were infected with COVID-19 while under investigation. All of them had poor sleep quality, 34.0% were anxiety and 63.1% were depression. During our investigation, 16.4% of the participant pregnant women had a miscarriage. Our results showed a significant association between sleep quality, anxiety, depression, pregnant age and miscarriage both unadjusted and multivariable multinomial logistic regression. RCS results showed that the miscarriage rate slowly increases with increasing PSQI, SAS and SDS score at first. However, when a certain threshold is reached, even slight increases in the scores of SAS, SDS, and PSQI will lead to a sharp rise in the miscarriage rate. The threshold for PSQI, SAS and SDS is 15, 60, and 65, respectively. Age displays a clear negative correlation with abortion rate, indicating a decrease as age increases, which is inconsistent with previous research findings [ 17 ] , which may be attributed to the relatively narrow age range included in this study or to the fact that older pregnant women tend to have a more stable mindset during the COVID-19 pandemic, enabling them to better adjust their mindset and cope with anxiety and depression. Other studies have indicated a potential link between COVID-19 infection and miscarriage in pregnant women [ 18 ] . However, this study did not find any significant relationship between the miscarriage rate of pregnant women and COVID-19 infection. This may be due to the milder symptoms of COVID-19 and its diminishing impact on pregnant women, or it could be attributed to a growing understanding of COVID-19, resulting in reduced fear and improved anxiety, depression, and sleep quality. This study used nomogram model to identify high-risk pregnant women, necessary interventions and treatments can be initiated in advance, providing personalized care and support such as psychological counseling, support, cognitive behavioral therapy, and sleep management, which can alleviate the adverse effects of insufficient sleep, anxiety, and depression on maternal health and reduce the risk of miscarriage. It can also help healthcare institutions and government departments optimize resource allocation. By identifying high-risk groups, limited resources can be prioritized for pregnant women in need of greater attention and intervention, thus improving resource efficiency. Additionally, it contributes to raising public awareness of maternal health, promoting overall societal health consciousness, and increasing happiness indices. The prospective cohort study design, controlling various risk factors related with miscarriage, and the first insight into the association and mediation effect of anxiety, depression on the relationship between sleep quality and miscarriage and uncovered the dose-relationship of them are the strengths of this study. However, there are several limitations in this study. First, genetic and psychological factors associated with miscarriage were not investigated in this study. The results need to be interpreted with caution. The potential intermediation role of psychological factors on the association between sleep quality and miscarriage needs to be explored in further studies. Second, this study was a single-center cohort conducted in China. A multicenter cohort study is needed to verify the findings in this study. Third, quantification of sleep quality, anxiety, depression based on questionnaires relied upon participant recall and therefore could be affected by recall bias. Last, selection bias could also affect the results. Despite these limitations, our findings are helpful to better understand the role of anxiety, depression and sleep quality on health among pregnant women during the COVID-19 pandemic. In conclusion, anxiety and depression and poor sleep quality were associated with a higher risk of miscarriage. Anxiety and depression also play a significant role in the impact of sleep quality on the miscarriage rate. By revealing high-risk pregnant women through the nomogram model, early intervention and personalized care and support can be provided, aiming to reduce the miscarriage rate among pregnant women. Our findings highlight the importance of healthy mental state of pregnant women during the COVID-19 pandemic. Declarations Authors’ contributions JHP and XDZ conceptualized this Article and wrote the original draft of the manuscript. JHP, XDZ, SYY, JJ, QL, PPZ, LYZ, XJQ, DLL contributed to the study design, data collection, methodology, data analysis, and data interpretation. SYY, JJ, QL, PPZ, and TAJ reviewed and edited the manuscript. TAJ supervised the study group. All authors had full access to all the data in the study and had final responsibility for the decision to submit for publication. All authors read and approved the final version of the manuscript. Funding This work is funded by National Key Scientific Instrument and Equipment Development Projects of China (82027803), National Natural Science Foundation of China (81971623). Availability of data and materials The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation. Ethics approval and consent to participate The studies involving human participants were reviewed and approved by First Affiliated Hospital of Zhejiang University. 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Jiang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9UlEQVRIiWNgGAWjYDACZjDJxgMkGB8wgCiGBPw6eJC0MBsQpwWJzSYBoQlosWdnfvbg5w4+Gf7Z7dcqf8gcZuBnzzFg+LkDn8PYzA17z7DxSNw5U3ZDgucwg2TPGwPG3jN4/WImwdsG9MuNnLQbBkAtBjdyDJgZ2/BpYf8m+ReoRR6opSABqMWesBYeM2mQLQY30o8xHADZIkFIy2GeMmlZoBbDGznMkg086TwSZ54VHOzFo4W9//g2ybdtx+zlbqQ//Pizx1qOvz1544OfeLRAwTGQhQYMjD2QiDpAUAMDQw3IwgcMDD+IUDsKRsEoGAUjDgAAFChGy6T5Te0AAAAASUVORK5CYII=","orcid":"","institution":"Zhejiang University School of Medicine","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Tianan","middleName":"","lastName":"Jiang","suffix":""},{"id":236966217,"identity":"90ba78ea-44cd-4032-b1f6-fbfce829bb16","order_by":1,"name":"Jinhua Pan","email":"","orcid":"","institution":"The First Affiliated Hospital, Zhejiang University School of Medicine","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Jinhua","middleName":"","lastName":"Pan","suffix":""},{"id":236966218,"identity":"32fe8ea3-4df5-4de2-b163-a29e182dd0ff","order_by":2,"name":"Xiaodan Zhu","email":"","orcid":"","institution":"Zhejiang University School of Medicine","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Xiaodan","middleName":"","lastName":"Zhu","suffix":""},{"id":236966219,"identity":"07c2b6af-1488-4d29-bff8-785530af0e05","order_by":3,"name":"Linyu Zhou","email":"","orcid":"","institution":"Zhejiang University School of Medicine","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Linyu","middleName":"","lastName":"Zhou","suffix":""},{"id":236966220,"identity":"c5fe3e19-5343-4e5f-94e3-c85801089d3e","order_by":4,"name":"Shanyu Yin","email":"","orcid":"","institution":"Zhejiang University School of Medicine","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Shanyu","middleName":"","lastName":"Yin","suffix":""},{"id":236966221,"identity":"32ac0f72-3a09-4f23-84a6-39c65f864fdb","order_by":5,"name":"Qiang Li","email":"","orcid":"","institution":"Zhejiang University School of Medicine","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Qiang","middleName":"","lastName":"Li","suffix":""},{"id":236966222,"identity":"f88aa2dc-31f6-474e-8b3c-9c7a847f95c2","order_by":6,"name":"Danlei Lu","email":"","orcid":"","institution":"Zhejiang University School of Medicine","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Danlei","middleName":"","lastName":"Lu","suffix":""},{"id":236966223,"identity":"33089b22-585a-4ae6-af56-dc2fdd0f6adf","order_by":7,"name":"Zihang Xu","email":"","orcid":"","institution":"Zhejiang University School of Medicine","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Zihang","middleName":"","lastName":"Xu","suffix":""},{"id":236966224,"identity":"33f38b9b-412d-4bea-98c0-21d5654cc5f9","order_by":8,"name":"Pingping Zhou","email":"","orcid":"","institution":"Zhejiang University School of Medicine","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Pingping","middleName":"","lastName":"Zhou","suffix":""},{"id":236966225,"identity":"cbe296c1-f8cd-4a14-bfdb-f440ecff0e47","order_by":9,"name":"Jian Jiang","email":"","orcid":"","institution":"Zhejiang University School of Medicine","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Jian","middleName":"","lastName":"Jiang","suffix":""},{"id":236966226,"identity":"dae01f7b-38e3-4b55-bbf6-81cabccdc9ff","order_by":10,"name":"Xiaoyu Lin","email":"","orcid":"","institution":"Zhejiang University School of Medicine","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Xiaoyu","middleName":"","lastName":"Lin","suffix":""}],"badges":[],"createdAt":"2023-09-08 02:35:33","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false,"coiExplicitlySet":false},"doi":"10.21203/rs.3.rs-3336014/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3336014/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":43988233,"identity":"7e5d99b9-6af3-401a-83b6-0e9f40938119","added_by":"auto","created_at":"2023-10-02 22:27:06","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":918133,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe association between SAS scores, SDS scores, PSQI scores, prepregnant BMI, age and number of abortions and miscarriage.\u003c/strong\u003e (A) The distribution of SAS standard score between those participants who had a miscarriage or not. (B) The distribution of SDS standard score between those participants who had a miscarriage or not. (C) The distribution of PSQI scores between those participants who had a miscarriage or not. (D) The distribution of prepregnant BMI values between those participants who had a miscarriage or not. (E) The association between age and miscarriage. (F) The association between the number of abortions and miscarriage.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-3336014/v1/67152a0e7ab40cbd1f66657c.png"},{"id":43988594,"identity":"22a7471d-7cb3-4c30-8d50-f1f2bc244c64","added_by":"auto","created_at":"2023-10-02 22:35:06","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":442104,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDose-response relationships between miscarriage rate and PSQI scores, SAS scores, SDS scores, age. \u003c/strong\u003eWe combined multivariable multinomial logistic regression models and RCS methods, the association was adjusted for age, BMI, basic disease, COVID-19 infection, occupation, education, first pregnancy, history of cesarean section and operation. The red lines represent the changes in the odds ratio (OR) with respect to SAS, SDS, PSQI, and age. The red shaded area represents the 95% confidence interval (CI). The black horizontal dashed line represents the reference line Y=1.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-3336014/v1/c07f7e489c638803aaf6900b.png"},{"id":43988228,"identity":"25f5a588-cdee-4be2-b0ca-d0ad56bf9620","added_by":"auto","created_at":"2023-10-02 22:27:06","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":342850,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eNomogram model to predict the probability\u003c/strong\u003e. The values below the first four graduated axes in the predictive model for miscarriage in pregnant women correspond to the actual values of the indicators. The corresponding score values for each variable are indicated by the colors in the legend on the right side. The sum of the score values for the four variables yields the score value above the final graduated axis. Each score value corresponds to a different miscarriage risk below the final graduated axis.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-3336014/v1/fca04595e1a34def5b2b488d.png"},{"id":43988595,"identity":"7a378650-98eb-4b1f-83e0-05d7d346cda7","added_by":"auto","created_at":"2023-10-02 22:35:06","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":298306,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe effect of anxiety or depression in mediating the effect of sleep on miscarriage.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Mediation model frame: Mediation models investigated the association between sleep quality and miscarriage to investigate whether anxiety and depression could be considered mediators in the relationship. The detail results are reported in Supplementary Table S2 (appendix pp8). The pathway labelled 𝒄′ represents the direct effect of sleep quality on miscarriage. The pathways labelled 𝒂\u003csub\u003e𝒊\u003c/sub\u003e represent the effect of sleep quality on the hypothesis mediators (Anxiety and Depression). Lastly, the pathways labelled 𝒃\u003csub\u003e𝒊\u003c/sub\u003e represent the effect of the mediators on miscarriage and are calculated whilst controlling for sleep quality\u003cstrong\u003e. \u003c/strong\u003e(B) The results of mediation models. Mediation models were used to investigate the effects of depression or anxiety, recognised causes of miscarriage, in mediating the association between sleep disturbance and miscarriage.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-3336014/v1/d57f20b6a449d2d2a0b9aa7b.png"},{"id":50358057,"identity":"739840f4-5557-442e-99fc-701854891a37","added_by":"auto","created_at":"2024-01-30 09:30:50","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1667639,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3336014/v1/5e81a834-13e8-466d-870e-f8f9bbb836c7.pdf"},{"id":43988230,"identity":"bb14004e-6e04-48a7-8eac-258c15a3f7ec","added_by":"auto","created_at":"2023-10-02 22:27:06","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":632528,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary information\u003c/p\u003e","description":"","filename":"Supplementaryinformation.docx","url":"https://assets-eu.researchsquare.com/files/rs-3336014/v1/b9855a77f3b61c0cf2e2ddb4.docx"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Effects of sleep quality, anxiety, and depression on miscarriage among pregnant women during the COVID-19 pandemic: Prospective Observational Study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eMiscarriage is generally defined as the loss of a pregnancy before viability. In recent years, with the rapid development of society, increasing life pressures, worsening environmental pollution, and the rise in the number of advanced maternal age pregnancies, the incidence of miscarriage has been on the rise. An estimated 23\u0026nbsp;million miscarriages occur every year worldwide, translating to 44 pregnancy losses each minute. The pooled risk of miscarriage is 15.3% (95% CI 12.5\u0026ndash;18.7%) of all recognised pregnancies\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e. Many factors can contribute to the occurrence of miscarriage in pregnant women, sleep quality has been proven to be a risk factor for unexpected miscarriage during the perinatal period in women\u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e. Research has also confirmed the impact of poor sleep quality on spontaneous miscarriage at the genetic level\u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eSleep is a fundamental physiological need for humans, which helps alleviate fatigue and restore energy. Sufficient sleep aids in the clearance of neurotoxic waste accumulated during wakefulness\u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e. Sleep deprivation often leads to fatigue, lack of concentration, delayed reaction time, and impaired judgment\u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e. In experimental settings, sleep quality is causally associated with two recognized causes of miscarriage: anxiety and depression. Pregnant and postpartum women, as a special population, often experience significant changes in reproductive hormone levels such as estrogen and progesterone during the perinatal period. Physiological changes, such as increased frequency of urination and difficulty finding a comfortable sleeping position, as well as psychological turmoil, can lead to poor sleep quality, anxiety, and depression. On average, approximately 45% of pregnant women experience sleep disturbances\u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e. It has been reported that poor sleep quality is associated with perinatal anxiety and depression (OR\u0026thinsp;=\u0026thinsp;1.56\u0026ndash;6.83) \u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eNow, with the added impact of the COVID-19 pandemic, the situation is even more challenging. Prior to the pandemic, the reported prevalence of perinatal depression among women was around 15\u0026ndash;20%\u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e. However, among women surveyed during the pandemic, over a third (36.4%) were found to have clinically significant levels of depression\u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e. Participants reported feeling intense sadness, loss, disappointment, and worry due to the pandemic\u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e. Some women have been unable to access expected support from family members or have had to rely only on their partners or peer groups for help due to concerns about COVID-19\u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e. Therefore, it is of utmost importance to observe the modifiable factors (such as sleep quality, anxiety, and depressive symptoms) affecting the miscarriage rate among pregnant and postpartum women during the pandemic, and to implement early prevention and intervention measures.\u003c/p\u003e \u003cp\u003eSeveral studies have already explored and investigated the sleep quality, anxiety, depression, and miscarriage rates among pregnant and postpartum women during the pandemic\u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e. However, these studies often provide only simple descriptions of the sleep patterns, anxiety, depression levels, miscarriage rate, and analysis of influencing factors. They have not explored how anxiety and depression impact miscarriages in the context of sleep quality, the extent of their influence, and the mechanisms of interaction between these factors. Additionally, there is limited research on establishing predictive models for miscarriages during the COVID-19 pandemic based on variables such as anxiety, depression, and sleep quality.\u003c/p\u003e \u003cp\u003eWe aimed to characterize the prevalence, type, and clinical consequences of sleep quality in a broad cohort of pregnant women who had been admitted to hospital during COVID-19 pandemic period using a multimodal approach. We hypothesized that sleep quality would be associated with miscarriage and that relationship would be mediated by anxiety and depression. Based on this, we utilized mediation analysis to explore how anxiety and depression mediate the relationship between sleep quality and miscarriage. We employed restricted cubic spline (RCS) combined with logistic regression to examine the dose-response relationship between these variables. Additionally, a directed acyclic graph was used to reveal their interactions. Furthermore, we constructed a nomogram model for predicting the occurrence of unexpected miscarriages in pregnant and postpartum women under different circumstances. This model serves to better alert pregnant and postpartum women, highlighting the importance of improving sleep quality and reducing anxiety and depression. This, in turn, facilitates early prevention of miscarriages and reduces the miscarriage rate.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design\u003c/h2\u003e \u003cp\u003eThis was a prospective cohort study conducted in the First Affiliated Hospital, Zhejiang University School of Medicine. The primary aim of this cohort study is to investigate the short- and long-term health effects of prenatal exposures (eg, poor sleep quality, anxiety and depression) on mothers and their children. Baseline recruitment was conducted in May 2022, and pregnant women who visited the outpatient clinic for the first prenatal examination at First Affiliated Hospital, Zhejiang University School of Medicine were recruited when they met the following inclusion criteria: \u0026lt;14 gestational weeks, singleton pregnancy, plan to have antenatal care and delivery in First Affiliated Hospital, Zhejiang University School of Medicine, and resided in Hangzhou during the past half year and have no plan to move out after delivery. The study was approved by the institutional review boards at the First Affiliated Hospital of Zhejiang University School of Medicine, and all participants gave written informed consent at the enrollment. This study conforms to the ethical guidelines of the 1975 Declaration of Helsinki (6th revision, 2008) as reflected in a priori approval by the institution's human research committee.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eFollow-up for Pregnancy Outcomes\u003c/h2\u003e \u003cp\u003eThe follow-up of the pregnancy outcomes was carried out by local healthcare personnel. Pregnant women receive regular antenatal care and give birth in the hospital. Information on pregnancy outcomes is obtained through the hospital's medical electronic information system, which automatically records information during each antenatal care and delivery. Miscarriage is defined as the loss of pregnancy that occurs before reaching 20 completed weeks of gestation\u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/sup\u003e. The prevalence of miscarriage was defined as the proportion of participants who had a miscarriage to all participants.\u003c/p\u003e\u003cp\u003e\u003cb\u003eCovariates\u003c/b\u003e\u003c/p\u003e \u003cp\u003eCovariates were collected at the first prenatal visit, including age, educational level, occupation, history of cesarean section, history of preterm birth, history of miscarriage, history of pregnancy, history of operation, gravidity, number of children, pre-pregnancy weight, basic disease, bad habits (Smoking or drinking during pregnancy), COVID-19 infection, COVID-19 infection symptom temperature and history of antipyretic drug use, vaccination history of COVID-19 and flu, anxiety, depression, sleep quality and so on. Pre-pregnancy BMI was calculated using weight (in kilograms) divided by the square of height (in meters).\u003c/p\u003e \u003cp\u003eAnxiety symptoms was assessed using the Zung Self-Rating Anxiety Scale developed by Zung\u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e. It consists of 20 questions. Responses are scored on a four-point scale, ranging from 1 (no or very little time) to 2 (sometimes), to 3 (most of the time) and 4 (most or all of the time). The raw score is the sum of all responses. The standard score is calculated as 1.25 times the original score. The current study used an index score cutoff of \u0026ge;\u0026thinsp;50 to diagnose anxiety.\u003c/p\u003e \u003cp\u003eDepression symptoms was assessed using the Zung Self-Rating Depression Scale developed by Zung\u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e. It consists of 20 questions. Responses are scored on a four-point scale, ranging from 1 (no or very little time) to 2 (sometimes), to 3 (most of the time) and 4 (most or all of the time). The raw score is the sum of all responses. The standard score is calculated as 1.25 times the original score. The current study used an index score cutoff of \u0026ge;\u0026thinsp;53 to diagnose depression.\u003c/p\u003e \u003cp\u003eSleep quality was assessed using the Pittsburgh Sleep Quality Index, a self-report scale used to assess respondents' sleep quality over a 2-week period\u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e. PSQI consists mainly of 18 items with 7 components, which represent sleep quality, time to fall asleep, sleep duration, sleep efficiency, sleep disorders, hypnotic drugs, and daytime dysfunction. Each question is rated on a scale of 0 to 3. The sum of the 7 component scores is the total score of PSQI. The higher the score, the worse the sleep. The total score ranged from 0 to 21, with a score of \u0026gt;\u0026thinsp;5 indicating poor sleep quality (sleep disturbance) in pregnant women, with 98% high sensitivity and 90% specificity (kappa\u0026thinsp;=\u0026thinsp;0.89, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), suitable for Chinese\u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eMean (SD) values and proportions of baseline characteristics were calculated. Prevalence and 95%CI of miscarriage was calculated. Miscarriage prevalence in women with different characteristics were also compared using chi-square test or Wilcoxon rank sum test. Multivariable logistic regression models were used to estimate the adjusted risk ratios (RRs) and their 95% CIs of miscarriage for women with different exposures. We combined logistic model and RCS methods to describe the stoichiometric response relationship with anxiety, depression, sleep quality, age and miscarriage (RCS details seen appendix pp1). We used nomogram model to predict the probability of miscarriage (nomogram details seen appendix pp1\u0026amp;pp2). Mediation was evaluated with linear regression with the product of coefficients method to estimate the direct and indirect effects of the relationship (mediation analysis details seen appendix pp2) and draw their directed acyclic graph (appendix pp 8), done with the R package lavaan version 0.6\u0026ndash;12 (appendix pp 2). All data were analysed with R (version 4.2.0). A p value less than 0.05 was considered significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eParticipant recruitment\u003c/h2\u003e \u003cp\u003eA total of 1,058 participants were enrolled, of whom 997 participants attended. Subjective sleep quality was measured with the PSQI questionnaire. Depression and anxiety status were measured with SD and SAS questionnaires, respectively. 801 of 997 (80.3%) participants attended follow-up offering the above three questionnaire (Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). Of these, 357 participants lost to follow-up or went to other hospital or did not submit the complete questionnaire, 444 participants entered the final analysis of anxiety, depression and sleep quality. 942 of 997 (94.5%) participants have complete clinical information. Of these, 665 participants complete the follow-up and included in the final analysis (Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eBasic Characteristic\u003c/h2\u003e \u003cp\u003eAmong all the 665 pregnant women included, 10.4% (n\u0026thinsp;=\u0026thinsp;69) were unemployed, 91.3% (n\u0026thinsp;=\u0026thinsp;607) had bachelor or above degree, 32.7% (n\u0026thinsp;=\u0026thinsp;217) were overweight or obese, 8.9% (n\u0026thinsp;=\u0026thinsp;59) had basic diseases, 69.0% (n\u0026thinsp;=\u0026thinsp;459) were having their first pregnancy, 28.6% (n\u0026thinsp;=\u0026thinsp;190) had a history of cesarean section, 28.9% (n\u0026thinsp;=\u0026thinsp;180) had a history of abortion, 19.8% (n\u0026thinsp;=\u0026thinsp;132) had a history of operation. The mean age at baseline was 30.1 (SD: 3.4) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The results for each variable grouped by miscarriage are shown in Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e (appendix pp3-pp5).\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\u003eDemographics, anxiety, depression and sleep quality of the study participants\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\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOverall\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e665\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (mean (SD))\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30.1 (3.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBachelor's degree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e502 (75.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaster degree or above\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e105 (15.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSenior high school and below\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e58 (8.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrepregnant BMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnderweight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35 (5.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNormal weight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e412 (62.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOverweight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e196 (29.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObese\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21 (3.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOccupation\u0026thinsp;=\u0026thinsp;unemployed (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e69 (10.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCOVID-19 (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e525 (78.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e125 (18.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnclear\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15 (2.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSymptom (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAsymptomatic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e232 (43.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOrdinary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e284 (52.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22 (4.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003esevere\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (0.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTemperature (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNormal \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e53 (9.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e37\u0026thinsp;~\u0026thinsp;38℃\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e143 (26.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e38\u0026thinsp;~\u0026thinsp;39℃\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e302 (55.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;39℃\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e42 (7.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFebrifuge\u0026thinsp;=\u0026thinsp;Yes (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e168 (34.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrevious infection (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e359 (54.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e287 (43.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnclear\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19 (2.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBasic disease\u0026thinsp;=\u0026thinsp;Yes (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e59 (8.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHospital\u0026thinsp;=\u0026thinsp;No (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e637 (95.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCOVID-19 vaccine (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e73 (11.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThrice or more\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e264 (39.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTwice or less\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e328 (49.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFlu vaccine (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e41 (6.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e592 (89.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnclear\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e32 (4.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBad habits\u0026thinsp;=\u0026thinsp;Yes (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (0.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFirst pregnancy\u0026thinsp;=\u0026thinsp;Yes (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e459 (69.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHistory of cesarean section (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eReject to answer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e144 (21.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e190 (28.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e331 (49.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMiscarriage\u0026thinsp;=\u0026thinsp;Yes (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e109 (16.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of full-term births (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e475 (76.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e145 (23.2)\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\u003e4 (0.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of premature births (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e619 (99.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (0.5)\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\u003e1 (0.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of abortions (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e442 (71.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOnce\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e132 (21.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTwice or more\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e48 (7.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of children\u0026thinsp;=\u0026thinsp;One or more (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e149 (24.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOperation\u0026thinsp;=\u0026thinsp;Yes (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e132 (19.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGestational hypertension\u0026thinsp;=\u0026thinsp;No (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e493 (99.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGestational diabetes\u0026thinsp;=\u0026thinsp;No (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e453 (89.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePregnancy with thrombocytopenia\u0026thinsp;=\u0026thinsp;No (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e471 (99.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEmbolism\u0026thinsp;=\u0026thinsp;No (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e425 (89.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAntiphospholipid syndrome\u0026thinsp;=\u0026thinsp;No (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e456 (97.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypoproteinemia\u0026thinsp;=\u0026thinsp;No (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e460 (99.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnemia\u0026thinsp;=\u0026thinsp;No (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e373 (74.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIron deficiency\u0026thinsp;=\u0026thinsp;No (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e382 (78.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFactor1 (mean (SD))\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.3 (0.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFactor2 (mean (SD))\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.3 (0.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFactor3 (mean (SD))\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.3 (1.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFactor4 (mean (SD))\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.9 (0.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFactor5 (mean (SD))\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.5 (0.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFactor6 (mean (SD))\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.7 (0.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFactor7 (mean (SD))\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.1 (0.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePSQI (mean (SD))\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13.9 (2.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoor sleep quality (PSQI score\u0026thinsp;\u0026ge;\u0026thinsp;5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e444 (100%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSAS (mean (SD))\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38.4 (6.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSAS standard score (mean (SD))\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e48.0 (7.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnxiety (SAS standard score\u0026thinsp;\u0026ge;\u0026thinsp;50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e293 (66.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e151 (34.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSDS (mean (SD))\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e44.2 (6.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSDS standard score (mean (SD))\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e55.3 (7.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDepression (SDS standard score\u0026thinsp;\u0026ge;\u0026thinsp;53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e164 (36.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e280 (63.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003e\u003csup\u003ea: The normal body temperature of the armpit is used (36\u0026ndash;37℃)\u003c/sup\u003e.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eCOVID-19 infection\u003c/h2\u003e \u003cp\u003eAmong all the 665 pregnant women included, 78.9% (n\u0026thinsp;=\u0026thinsp;525) were infected with COVID-19 while under investigation (of these, 43.0% were asymptomatic, 52.6% were ordinary), 90.2% (n\u0026thinsp;=\u0026thinsp;487) had a fever. Of these, 34.5% (n\u0026thinsp;=\u0026thinsp;168) took antipyretic medicine (155 took P-acetylamino acid, 4 took ibuprofen, 1 took lianhua Qingwen, 8 took other medicine). Of all the participants, 54.0% (n\u0026thinsp;=\u0026thinsp;359) had infected with COVID-19 before, 89.0% (n\u0026thinsp;=\u0026thinsp;592) had vaccinated COVID-19 vaccine and 6.2% (n\u0026thinsp;=\u0026thinsp;41) had vaccinated flu vaccine within three years (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The results for each variable grouped by miscarriage are shown in Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e (appendix pp3-pp5).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eSleep quality, anxiety and depression\u003c/h2\u003e \u003cp\u003eDuring the COVID-19 period, the average global PSQI score was 13.9 (SD: 2.8) of the pregnant women participated in this study, 100% (n\u0026thinsp;=\u0026thinsp;444) of them had poor sleep quality. The average SAS standard score were 48.0 (SD: 7.5), 34.0% (n\u0026thinsp;=\u0026thinsp;151) were anxiety. The average SDS standard score were 55.3 (SD: 7.8), 63.1% (n\u0026thinsp;=\u0026thinsp;280) were depression (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The results for each variable grouped by miscarriage are shown in Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e (appendix pp3-pp5).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003ePrevalence of miscarriage in populations with different characteristics\u003c/h2\u003e \u003cp\u003eOut of 665 pregnant women, 109 (16.4%, 95%CI:[13.8%-19.4%]) had a miscarriage. Compared with women who did not miscarriage, participants who had a miscarriage tend to have significantly higer SAS scores (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). Similarly, SDS and PSQI scores tend to have higher values in those women who had a miscarriaged (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB\u0026amp;C). While BMI, age and number of abortions did not have a relationship with miscarriage of participant pregnant women (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD,E \u0026amp;F). Education, COVID-19 infection, occupation, first pregnancy, history of cesarean section and basic disease did not have relationship with miscarriage of participant pregnant women either (Figure S2).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eAssociation between sleep quality, anxiety, depression and miscarriage\u003c/h2\u003e \u003cp\u003eThe relationship between sleep quality and miscarriage was assessed. Participants with poor sleep quality (assessed by the Pittsburgh Sleep Quality Index) were more likely to have a miscarriage compared to participants who reported lower PSQI values (Figure S3). A similar association was observed between anxiety, depression and miscarriage. Participants who reported higher SAS and SDS value were more likely to have a miscarriage compared to participants who reported lower SAS and SDS values (Figure S3). Those pregnant women who were older are more likely to have a miscarriage (Figure S3).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eDose-response relationships between miscarriage rate and anxiety, sleep quality, depression, age\u003c/h2\u003e \u003cp\u003eUsing multivariable logistic regression model combined with RCS method, the dose-response relationships between SAS score, PSQI score, SDS score, age, and miscarriage were analyzed separately (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The overall relationship between PSQI score and miscarriage rate indicates that higher PSQI scores are associated with higher miscarriage rates. Initially, the miscarriage rate slowly increases with increasing PSQI score. However, after PSQI\u0026thinsp;\u0026gt;\u0026thinsp;15, even slight increases in PSQI have a significant impact on the miscarriage rate. The overall relationship between SDS score and miscarriage rate is also positive. When SDS score increases, the abortion rate initially remains stable. However, after SDS\u0026thinsp;\u0026gt;\u0026thinsp;60, the miscarriage rate increases slowly at first and then sharply with increasing SDS score. A similar pattern is observed for SAS score. When SAS score\u0026thinsp;\u0026lt;\u0026thinsp;65, it has no effect on the miscarriage rate. However, when SAS score\u0026thinsp;\u0026gt;\u0026thinsp;65, the abortion rate sharply increases with increasing SAS score. Age shows a clear negative correlation with abortion rate, indicating that the abortion rate decreases as age increases (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003ePrediction the probability of miscarriage based on nomogram model\u003c/h2\u003e \u003cp\u003eBased on the logistic regression model, a nomogram model was constructed to predict the probability of abortion occurrence (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). By combining significant variables from logistic regression: age, SAS score, SDS score, and PSQI score, the corresponding scores for each indicator are given on the point scale axis. The total score is obtained by adding the score values for each indicator. The probability of miscarriage in pregnant women is then determined based on the total score, with higher scores indicating a greater likelihood of miscarriage. The discriminative power of this nomogram prediction model is shown in Figure S4, with an AUC of 99.8%, corrected pAUC of 99.0%, indicating excellent predictive performance.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eMediation analysis\u003c/h2\u003e \u003cp\u003eGiven that anxiety and depression are recognised causes of miscarriage, mediation analysis was done to investigate the contribution of anxiety and depression in mediating the effect between sleep and miscarriage during COVID-19 period (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). Anxiety following discharge from hospital mediated the effect of sleep quality on miscarriage by 55.88% (95% CI 41.18, 69.12) and depression had a similar mediation effect (16.18% [95% CI 7.35,27.94]; Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB; Table S2, appendix p8), and their directed acyclic graph are shown in the appendix (appendix pp 8)\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussions","content":"\u003cp\u003eTo our knowledge, this is the first study exploring the mediating role of anxiety and depression in the relationship between sleep quality and the miscarriage rate, and their dose response relationship and interaction relationship. In our study, most of the participant pregnant women (78.9%) were infected with COVID-19 while under investigation. All of them had poor sleep quality, 34.0% were anxiety and 63.1% were depression. During our investigation, 16.4% of the participant pregnant women had a miscarriage. Our results showed a significant association between sleep quality, anxiety, depression, pregnant age and miscarriage both unadjusted and multivariable multinomial logistic regression. RCS results showed that the miscarriage rate slowly increases with increasing PSQI, SAS and SDS score at first. However, when a certain threshold is reached, even slight increases in the scores of SAS, SDS, and PSQI will lead to a sharp rise in the miscarriage rate. The threshold for PSQI, SAS and SDS is 15, 60, and 65, respectively. Age displays a clear negative correlation with abortion rate, indicating a decrease as age increases, which is inconsistent with previous research findings\u003csup\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e, which may be attributed to the relatively narrow age range included in this study or to the fact that older pregnant women tend to have a more stable mindset during the COVID-19 pandemic, enabling them to better adjust their mindset and cope with anxiety and depression.\u003c/p\u003e \u003cp\u003eOther studies have indicated a potential link between COVID-19 infection and miscarriage in pregnant women\u003csup\u003e[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/sup\u003e. However, this study did not find any significant relationship between the miscarriage rate of pregnant women and COVID-19 infection. This may be due to the milder symptoms of COVID-19 and its diminishing impact on pregnant women, or it could be attributed to a growing understanding of COVID-19, resulting in reduced fear and improved anxiety, depression, and sleep quality.\u003c/p\u003e \u003cp\u003eThis study used nomogram model to identify high-risk pregnant women, necessary interventions and treatments can be initiated in advance, providing personalized care and support such as psychological counseling, support, cognitive behavioral therapy, and sleep management, which can alleviate the adverse effects of insufficient sleep, anxiety, and depression on maternal health and reduce the risk of miscarriage. It can also help healthcare institutions and government departments optimize resource allocation. By identifying high-risk groups, limited resources can be prioritized for pregnant women in need of greater attention and intervention, thus improving resource efficiency. Additionally, it contributes to raising public awareness of maternal health, promoting overall societal health consciousness, and increasing happiness indices.\u003c/p\u003e \u003cp\u003eThe prospective cohort study design, controlling various risk factors related with miscarriage, and the first insight into the association and mediation effect of anxiety, depression on the relationship between sleep quality and miscarriage and uncovered the dose-relationship of them are the strengths of this study. However, there are several limitations in this study. First, genetic and psychological factors associated with miscarriage were not investigated in this study. The results need to be interpreted with caution. The potential intermediation role of psychological factors on the association between sleep quality and miscarriage needs to be explored in further studies. Second, this study was a single-center cohort conducted in China. A multicenter cohort study is needed to verify the findings in this study. Third, quantification of sleep quality, anxiety, depression based on questionnaires relied upon participant recall and therefore could be affected by recall bias. Last, selection bias could also affect the results. Despite these limitations, our findings are helpful to better understand the role of anxiety, depression and sleep quality on health among pregnant women during the COVID-19 pandemic.\u003c/p\u003e \u003cp\u003eIn conclusion, anxiety and depression and poor sleep quality were associated with a higher risk of miscarriage. Anxiety and depression also play a significant role in the impact of sleep quality on the miscarriage rate. By revealing high-risk pregnant women through the nomogram model, early intervention and personalized care and support can be provided, aiming to reduce the miscarriage rate among pregnant women. Our findings highlight the importance of healthy mental state of pregnant women during the COVID-19 pandemic.\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJHP and XDZ conceptualized this Article and wrote the original draft of the manuscript. JHP, XDZ, SYY, JJ, QL, PPZ, LYZ, XJQ, DLL contributed to the study design, data collection, methodology, data analysis, and data interpretation. SYY, JJ, QL, PPZ, and TAJ reviewed and edited the manuscript. TAJ supervised the study group. All authors had full access to all the data in the study and had final responsibility for the decision to submit for publication. All authors read and approved the final version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work is funded by National Key Scientific Instrument and Equipment Development Projects of China (82027803), National Natural Science Foundation of China (81971623).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe studies involving human participants were reviewed and approved by First Affiliated Hospital of Zhejiang University. The participants provided their oral informed consent to participate in this study. Consent for publication was obtained from all participants.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eQuenby S, Gallos I D, Dhillon-Smith R K, Podesek M, Stephenson M D, Fisher J, Brosens J J, Brewin J, Ramhorst R, Lucas E S, Mccoy R C, Anderson R, Daher S, Regan L, Al-Memar M, Bourne T, Macintyre D A, Rai R, Christiansen O B, Sugiura-Ogasawara M, Odendaal J, Devall A J, Bennett P R, Petrou S, Coomarasamy A. Miscarriage matters: the epidemiological, physical, psychological, and economic costs of early pregnancy loss [J]. Lancet, 2021, 397(10285): 1658\u0026ndash;1667.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePietikainen J T, Polo-Kantola P, Polkki P, Saarenpaa-Heikkila O, Paunio T, Paavonen E J. 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Sleep heterogeneity in the third trimester of pregnancy: Correlations with depression, memory impairment, and fatigue [J]. Psychiatry Res, 2021, 303(114075).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLin W, Wu B, Chen B, Zhong C, Huang W, Yuan S, Zhao X, Wang Y. Associations of COVID-19 related experiences with maternal anxiety and depression: implications for mental health management of pregnant women in the post-pandemic era [J]. Psychiatry Res, 2021, 304(114115.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLin W, Wu B, Chen B, Lai G, Huang S, Li S, Liu K, Zhong C, Huang W, Yuan S, Wang Y. Sleep Conditions Associate with Anxiety and Depression Symptoms among Pregnant Women during the Epidemic of COVID-19 in Shenzhen [J]. J Affect Disord, 2021, 281(567\u0026ndash;573).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVan P, Gay C L, Lee K A. Prior pregnancy loss and sleep experience during subsequent pregnancy [J]. 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Arch Gen Psychiatry, 1965, 12(63\u0026ndash;70.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBuysse D J, Reynolds C F, 3rd, Monk T H, Berman S R, Kupfer D J. The Pittsburgh Sleep Quality Index: a new instrument for psychiatric practice and research [J]. Psychiatry Res, 1989, 28(2): 193\u0026ndash;213.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMagnus M C, Wilcox A J, Morken N H, Weinberg C R, Haberg S E. Role of maternal age and pregnancy history in risk of miscarriage: prospective register based study [J]. BMJ, 2019, 364(l869.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCavalcante M B, De Melo Bezerra Cavalcante C T, Cavalcante A N M, Sarno M, Barini R, Kwak-Kim J. COVID-19 and miscarriage: From immunopathological mechanisms to actual clinical evidence [J]. J Reprod Immunol, 2021, 148(103382).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-3336014/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3336014/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eImportance:\u003c/h2\u003e \u003cp\u003eSleep quality is related to miscarriage of pregnant women, which can also lead to depression and anxiety. Currently, there is no research revealing the role of anxiety and depression in the relationship between sleep quality and miscarriage among pregnant women and their interacting mechanism.\u003c/p\u003e\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eThis study aims to uncover the mechanisms and quantitative dose response relationships among these factors, as well as develop a predictive model for the miscarriage rate.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eIn this study, 1,058 pregnant women in mainland China were recruited. All of them met inclusion criteria. Sleep quality was assessed subjectively using the Pittsburgh Sleep Quality Index questionnaire (PSQI). Anxiety was assessed subjectively using the Self-Rating Anxiety Scale questionnaire (SAS). Depression was assessed subjectively using the Self-Rating Depression Scale questionnaire (SDS). We used mediation analysis to explore how anxiety and depression mediate the relationship between sleep quality and miscarriage. We employed restricted cubic spline (RCS) combined with logistic regression to examine the dose-response relationship between these variables. Additionally, a directed acyclic graph was used to reveal their interactions. Furthermore, we constructed a nomogram model for predicting the occurrence of unexpected miscarriages in pregnant and postpartum women.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eDuring our investigation, 16.4% of the participant pregnant women had a miscarriage. Our results showed a significant association between sleep quality, anxiety, depression, pregnant age and miscarriage both unadjusted and multivariable multinomial logistic regression. Dose-response relationships showed that the miscarriage rate slowly increases with increasing PSQI, SAS and SDS score at first. However, when a certain threshold is reached, even slight increases in the scores of SAS, SDS, and PSQI will lead to a sharp rise in the miscarriage rate. The threshold for PSQI, SAS and SDS is 15, 60, and 65, respectively. Anxiety mediated the effect of sleep quality on miscarriage by 55.88% (95% CI 41.18,69.12) and depression had a similar mediation effect (16.18% [95% CI 7.35,27.94]).\u003c/p\u003e\u003ch2\u003eConclusions and Relevance:\u003c/h2\u003e \u003cp\u003eThe quantitative dose response relationships between PSQI, SAS, SDS, and the miscarriage rate among pregnant women are all positive. In the impact of sleep quality on the miscarriage rate, anxiety and depression also play significant mediating roles. By revealing high-risk pregnant women, early intervention can be provided, aiming to reduce the miscarriage rate among pregnant women during the COVID-19 pandemic.\u003c/p\u003e","manuscriptTitle":"Effects of sleep quality, anxiety, and depression on miscarriage among pregnant women during the COVID-19 pandemic: Prospective Observational Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-10-02 22:27:01","doi":"10.21203/rs.3.rs-3336014/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"aad1edcb-ef2c-4245-b780-c5d939996686","owner":[],"postedDate":"October 2nd, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":25089496,"name":"Health sciences/Health care/Public health/Epidemiology"},{"id":25089497,"name":"Health sciences/Medical research/Epidemiology"}],"tags":[],"updatedAt":"2024-01-30T09:22:43+00:00","versionOfRecord":[],"versionCreatedAt":"2023-10-02 22:27:01","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3336014","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3336014","identity":"rs-3336014","version":["v1"]},"buildId":"GqpaHPwrfC8PjnIFayRh5","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}