A Longitudinal Study from Early Pregnancy to Postpartum: The Moderating Effect of Marital Support on the Development of Perinatal Depression and the Construction of a Risk Prediction Model

A Longitudinal Study from Early Pregnancy to Postpartum: The Moderating Effect of Marital Support on the Development of Perinatal Depression and the Construction of a Risk Prediction Model | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article A Longitudinal Study from Early Pregnancy to Postpartum: The Moderating Effect of Marital Support on the Development of Perinatal Depression and the Construction of a Risk Prediction Model Yu Gan, Shu juan Liao, Jing Chen, Xiujing Guo This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7555596/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Objective To investigate the moderating effect of marital support on the development of perinatal depression and to construct a risk prediction model for perinatal depression, providing important references for clinical practice. Methods This study adopted a longitudinal design, including 1,520 pregnant women who visited West China Second University Hospital, Sichuan University between January 2023 and December 2024. Data were collected at three time points: early pregnancy (T1), late pregnancy (T2), and postpartum (T3). The Dyadic Adjustment Scale (DAS) was used to assess marital support, and the Edinburgh Postnatal Depression Scale (EPDS) was used to assess depressive symptoms. Data analysis methods included univariate analysis, logistic regression, cross-lagged models, and prediction model construction. Results The mean EPDS scores at early pregnancy, late pregnancy, and postpartum were 7.45 ± 3.57, 7.02 ± 3.51, and 7.99 ± 4.17, respectively. The prevalence of depression showed a U-shaped trend, with 16.5% in early pregnancy, 15.0% in late pregnancy, and 18.5% postpartum. The results of the univariate analysis indicated that the marital support scores (including consensus, positive interaction, marital satisfaction, and total marital score) in the depressed group were all significantly lower than those in the non-depressed group ( P < 0.05 ), while the conflict score was significantly higher than that in the non-depressed group ( P < 0.05 ). Cross-lagged model analysis indicated that marital support in early pregnancy significantly reduced the risk of depression in late pregnancy ( β=-0.24, P = 0.003 ), while depression in late pregnancy significantly reduced marital support postpartum ( β=-0.18, P = 0.020 ). Multivariate logistic regression analysis showed that three dimensions of marital support (including consensus, positive interaction, marital satisfaction) were protective factors ( OR < 1, P 1, P < 0.05 ). The performance of the postpartum depression prediction model based on marital support was the highest ( AUC = 0.82 ), indicating its excellent performance. Conclusion Marital support plays a significant moderating role in the development of perinatal depression. High marital support reduces the risk of depression, while low support increases the risk. The postpartum depression prediction model based on marital support performs well, providing important references for clinical interventions in perinatal depression. Pregnant women Depression Marital support Prediction model Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 1. Introduction Perinatal period is a special stage in a woman's life, filled with physiological and psychological changes. Accompanied by dramatic fluctuations in hormone levels, changes in body morphology, and adaptation to the role of becoming a mother, women face numerous challenges during this period. Perinatal depression, as a common mental health issue, has a global prevalence rate of approximately 10%-20%, highlighting its universality and severity[ 1 , 2 ]. In China, although the specific prevalence rate may vary due to regional, cultural, and methodological differences, its prevalence is also not negligible[ 3 , 4 ]. Perinatal depression not only has profound impacts on the physical and mental health of pregnant women, such as causing emotional distress, anxiety, and sleep disorders[ 5 ], but may also indirectly affect fetal development through its impact on the physiological state of pregnant women[ 6 , 7 ]. Furthermore, it may hinder the establishment and development of parent-child relationships after the birth of the baby[ 8 – 10 ]. In recent years, with the increasing emphasis on the mental health of pregnant women in society, the prevention and intervention of perinatal depression have become a research hotspot in public health. Marriage, as an indispensable part of the social support system, plays a crucial role in regulating individual mental health[ 11 ], particularly during the perinatal period, where the quality of marital support may directly relate to the psychological state and developmental trajectory of depressive symptoms in pregnant women[ 12 , 13 ]. Numerous studies have shown that a good marital relationship can provide pregnant women with a solid emotional support system, offering them emotional comfort and support[ 14 , 15 ]. Meanwhile, partners in marriage can also provide practical assistance in daily life, alleviating the burden on pregnant women. Additionally, mutual understanding and encouragement in marriage can instill confidence and courage in pregnant women to better cope with psychological stress and effectively reduce the risk of depression[ 16 , 17 ]. However, despite the widespread recognition of the importance of marital support in preventing perinatal depression[ 18 ], there is a lack of in-depth research on how marital support specifically affects the developmental trajectory of perinatal depression and how to accurately utilize this relationship to construct an effective risk prediction model. Therefore, this study aims to conduct a systematic longitudinal study to deeply explore the moderating effect of marital support on the development of perinatal depression and to attempt to construct a scientific and effective risk prediction model for perinatal depression, with the aim of providing strong support for clinical practice, improving the mental health level of pregnant women, and reducing the incidence of perinatal depression. 2. Methods 2.1 Study Design This study adopted a longitudinal design to systematically track pregnant women from early pregnancy to postpartum. A total of 1,520 eligible pregnant women who visited West China Second University Hospital, Sichuan University between January 2023 and December 2024 were included as research subjects. All pregnant women underwent regular prenatal examinations and deliveries at this hospital. The study was divided into three key time points for data collection: early pregnancy (T1, within 12 weeks of gestation), late pregnancy (T2, from 28 weeks of gestation to delivery), and postpartum (T3, within 6 weeks after delivery). This design allows for dynamic observation of changes in marital support and depressive symptoms over time, as well as their interactions. 2.2 Study Subjects The inclusion criteria strictly limited subjects to pregnant women aged between 18 and 45 years old, with singleton pregnancies, no severe physical diseases or history of mental disorders, and who voluntarily participated in the study and signed informed consent forms. All participants fully understood the study purpose, procedures, and possible risks before signing the informed consent forms. This study has been reviewed and approved by the ethics committee to ensure that all research activities comply with ethical norms. 2.3 Measurement Tools Dyadic Adjustment Scale (DAS): This study used the DAS scale to assess the marital support status of pregnant women at different time points (early pregnancy, late pregnancy, and postpartum). The DAS scale, compiled by Spanier in 1976, is a widely used standardized tool in marital relationship research. The scale consists of 32 items and four subscales: Affectional Expression (AE), Dyadic Consensus (DC), Dyadic Cohesion (AC), and Dyadic Satisfaction (DS). The total score range of the DAS scale is 0 to 151. Through this scale, detailed data on the marital support status of pregnant women can be obtained, including the specific content and scoring of the four subscales. Additionally, marital support scores in this study were mainly considered from four dimensions: consensus, conflict, positive interaction, and marital satisfaction. (1) Consensus: corresponds to the scores of the Dyadic Consensus subscale, with higher scores indicating greater ease in reaching consensus on important matters between husband and wife, and easier formation of unified opinions and actions in the face of various problems in marriage. (2) Conflict: Although the DAS scale does not directly name a "conflict" subscale, marital conflict can be reflected through relevant items in each subscale, such as the frequency of arguments during disagreements and ways of handling conflicts. Higher conflict levels may indicate poorer marital support. (3) Positive interaction: Related to the Affectional Expression and Dyadic Cohesion subscales, higher scores in positive interaction reflect more emotional expression, joint activities, and good communication between husband and wife, indicating a more harmonious and intimate relationship. (4) Marital satisfaction: Corresponds to the scores of the Dyadic Satisfaction subscale, directly reflecting the overall satisfaction level of pregnant women with their marital relationship, and is an important indicator for measuring the quality of marital support. This study strictly followed the guidance principles of the DAS scale for administration and scoring to ensure the accuracy and reliability of the assessment results. Edinburgh Postnatal Depression Scale (EPDS) This scale is a widely used self-rating scale specifically designed for pregnant and postnatal women, used to comprehensively and meticulously assess depressive symptoms. The EPDS scale consists of 10 carefully designed items that comprehensively cover possible depression-related symptoms, such as emotional distress, loss of interest, self-blame and guilt, sleep disorders, appetite changes, loss of energy, anxiety, and lack of confidence in the future. In terms of scoring rules, each item is assigned different scoring levels based on the severity of symptoms, usually adopting a four-point scoring method from 0 to 3, where 0 points represent almost no symptoms and 3 points represent very severe symptoms. Pregnant women choose the option that best matches their symptom severity based on their actual situation in the past week. The scoring method is to sum the scores of the 10 items to obtain the total score. Higher total scores indicate more severe depressive symptoms in pregnant women. Generally, the EPDS scale has a specific critical value (≥ 13 points). When the total score reaches or exceeds this critical value, it suggests that the pregnant woman may have depressive emotions. 2.4 Statistical Analysis Univariate analysis was initially conducted to explore the associations between marital support, depressive symptoms, and other relevant variables of pregnant women at different time points. Descriptive statistics were calculated for each variable, including means, standard deviations, frequency distributions, etc. For continuous variables conforming to a normal distribution, means (standard deviations) were used for description; for non-normally distributed continuous variables, medians (interquartile ranges) were used to describe their central tendency and dispersion; for categorical variables, frequencies (percentages) were presented. Additionally, preliminary comparisons were made between the depression group and the non-depression group in terms of marital support scores in each dimension. Cross-lagged models were used to test the bidirectional relationships between marital support and depressive symptoms. To more deeply explore the impact of different dimensions of marital support on the risk of perinatal depression, binary logistic regression analysis was conducted in this study, with different dimensions of marital support (such as consensus, conflict, positive interaction, marital satisfaction) as independent variables and the depressive status of pregnant women as the dependent variable for regression analysis. The odds ratio (OR) and confidence interval (CI) were calculated to assess the impact of each marital dimension on the risk of depression. Meanwhile, a risk prediction model for perinatal depression in pregnant women based on marital support was constructed. Cross-validation and performance evaluation were used to verify the stability and generalization ability of the model on different datasets. 3. Results 3.1 General Information of Pregnant Women The general information of pregnant women showed that the average age of the research subjects was 28.5 ± 4.2 years old, with the majority being married (98.3%), having a college/university education (54.8%), medium income (45.2% with a monthly family income of 5000–10000 yuan), and first-time mothers (76.5%). The gestational weeks at each stage met the requirements of the study design(as shown in Table 3.1 ). . Table 3.1 General Information of Pregnant Women (N = 1520) Variable Category Mean ± SD / (%) Age (years) – 28.5 ± 4.2 Gestational weeks Early pregnancy (T1) 8.2 ± 1.5 Late pregnancy (T2) 34.6 ± 2.8 Postpartum (T3) 6.0 ± 1.2 Marital status Married 98.3 Unmarried/Divorced 1.7 Education level High school or below 32.6 College/University 54.8 Master's degree or above 12.6 Monthly family income 10000 yuan 36.4 Parity First-time mothers 76.5 Experienced mothers 23.5 3.2 U-shaped Trend of Perinatal Depression and Significantly Lower Marital Support in the Depression Group The EPDS scores and prevalence rates of depression in all pregnant women were statistically analyzed. The results showed that the mean EPDS scores at early pregnancy, late pregnancy, and postpartum were 7.45 ± 3.57, 7.02 ± 3.51, and 7.99 ± 4.17, respectively. The prevalence rates of depression showed a U-shaped trend, with 16.5% in early pregnancy, 15.0% in late pregnancy, and 18.5% postpartum (as shown in Table 3.2 and Fig. 3.1 ). Pregnant women were divided into a depression group (EPDS score > 13) and a non-depression group based on EPDS scores. The results showed that there were significant differences in marital support scores (consensus, conflict, positive interaction, marital satisfaction, and total marital score) at each stage between the two groups ( P < 0.05 ). The conflict scores in the depression group were significantly higher than those in the non-depression group, while the consensus, positive interaction, marital satisfaction, and total marital scores were significantly lower than those in the non-depression group. The total marital support scores at early pregnancy, late pregnancy, and postpartum in the depression group were significantly lower than those in the non-depression group ( P < 0.05 ) (as shown in Table 3.3 and Fig. 3.2 ). Table 3.2 EPDS Scores and Prevalence Rates of Depression at Each Stage of Pregnancy Stage Variable Mean ± SD / (%) Early pregnancy (n = 1520) EPDS score 7.45 ± 3.57 Prevalence rate of depression 16.5% Late pregnancy (n = 1520) EPDS score 7.02 ± 3.51 Prevalence rate of depression 15.0% Postpartum (n = 1520) EPDS score 7.99 ± 4.17 Prevalence rate of depression 18.5% Table 3.3 Marital Support Scores in the Depression Group and Non-depression Group at Each Stage of Pregnancy Variable Depression status n Mean ± SD t-value P-value Early pregnancy Consensus score Yes 250 48.65 ± 9.25 8.521 < 0.001 No 1270 43.72 ± 8.14 – – Conflict score Yes 250 19.37 ± 3.17 -11.688 < 0.001 No 1270 21.34 ± 2.26 – – Positive interaction score Yes 250 13.81 ± 4.75 -6.110 < 0.001 No 1270 15.64 ± 4.27 – – Marital satisfaction score Yes 250 16.64 ± 3.59 -7.950 < 0.001 No 1270 18.28 ± 2.85 – – Total marital score Yes 250 107.39 ± 15.61 -3.747 0.002 No 1270 117.54 ± 15.24 – – Late pregnancy Consensus score Yes 229 49.75 ± 8.89 6.377 < 0.001 No 1291 44.88 ± 8.38 – – Conflict score Yes 229 19.04 ± 2.83 -9.170 < 0.001 No 1291 21.11 ± 2.45 – – Positive interaction score Yes 229 12.94 ± 4.49 -5.450 < 0.001 No 1291 15.15 ± 4.51 – – Marital satisfaction score Yes 229 16.48 ± 3.19 -4.539 < 0.001 No 1291 17.71 ± 3.97 – – Total marital score Yes 229 115.94 ± 14.64 -2.247 0.028 No 1291 124.58 ± 14.97 – – Postpartum Consensus score Yes 281 50.87 ± 10.01 6.359 < 0.001 No 1239 44.62 ± 8.69 – – Conflict score Yes 281 18.54 ± 4.12 -6.503 < 0.001 No 1239 20.83 ± 3.06 – – Positive interaction score Yes 281 11.42 ± 5.14 -5.757 < 0.001 No 1239 14.47 ± 4.85 – – Marital satisfaction score Yes 281 15.37 ± 3.83 -5.148 < 0.001 No 1239 17.26 ± 3.31 – – Total marital score Yes 281 104.56 ± 17.15 -2.813 0.006 No 1239 115.70 ± 17.10 – – Note A: Early pregnancy,B: Late pregnancy, C: Postpartum, *: P < 0.05 ,**: P < 0.01,***: P < 0.001 3.3 Marital Support in Early Pregnancy Reduces the Risk of Depression in Late Pregnancy, While Depression in Late Pregnancy Weakens Marital Support Postpartum The results of the cross-lagged model analysis of marital support and depression are shown in Table 3.4 . Marital support in early pregnancy significantly reduces the risk of depression in late pregnancy ( β=-0.24, P = 0.003 ). Depression in late pregnancy significantly reduces marital support postpartum ( β=-0.18, P = 0.020 ); the predictive effect of marital support in late pregnancy on postpartum depression is not significant ( β=-0.10, P = 0.125 ). Table 3.4 Cross-lagged Model of Marital Support and Depression Path β (SE) P-value Marital support in early pregnancy → Depression in late pregnancy -0.24 (0.07) 0.003 Marital support in late pregnancy → Depression postpartum -0.10 (0.06) 0.125 Depression in early pregnancy → Marital support in late pregnancy -0.08 (0.05) 0.112 Depression in late pregnancy → Marital support postpartum -0.18 (0.07) 0.020 3.4 Consensus, Positive Interaction, and Marital Satisfaction are Protective Factors for Depression, While Conflict is a Risk Factor Binary logistic regression analysis was conducted with marital support (consensus, conflict, positive interaction, marital satisfaction) as influencing factors for the risk of depression. The results showed that in early pregnancy, the total consensus score ( OR = 0.975, P = 0.002 ), total positive interaction score ( OR = 0.966, P = 0.020 ), and total marital satisfaction score ( OR = 0.946, P = 0.012 ) were protective factors; the total conflict score ( OR = 1.162, P < 0.001 ) was a risk factor. In late pregnancy, the total consensus score ( OR = 0.970, P = 0.003 ), total positive interaction score (OR = 0.961, P = 0.026), and total marital satisfaction score ( OR = 0.951, P = 0.046 ) were protective factors; the total conflict score ( OR = 1.197, P < 0.001 ) was a risk factor. In the postpartum period, the total consensus score ( OR = 0.972, P = 0.020 ), total positive interaction score ( OR = 0.963, P = 0.037 ), and total marital satisfaction score ( OR = 0.959, P = 0.036 ) were protective factors; the total conflict score ( OR = 1.128, P < 0.001 ) was a risk factor (as shown in Table 3.5 and Fig. 3.3 ). Table 3.5 Binary Logistic Regression Analysis of Depression in Pregnant Women Stage Variable β SE Wald P-value OR 95% CI T1 Consensus score -0.025 0.008 9.752 0.002 0.975 0.96–0.99 Conflict score 0.150 0.025 36.00 < 0.001 1.162 1.16–1.22 Positive interaction score -0.035 0.015 5.444 0.020 0.966 0.93–0.99 Marital satisfaction score -0.055 0.022 6.250 0.012 0.946 0.90–0.98 T2 Consensus score -0.030 0.010 9.000 0.003 0.970 0.95–0.99 Conflict score 0.180 0.030 36.00 < 0.001 1.197 1.12–1.27 Positive interaction score -0.040 0.018 4.938 0.026 0.961 0.92–0.99 Marital satisfaction score -0.050 0.025 4.000 0.046 0.951 0.90–0.99 T3 Consensus score -0.028 0.012 5.444 0.020 0.972 0.95–0.99 Conflict score 0.120 0.028 18.367 < 0.001 1.128 1.06–1.19 Positive interaction score -0.038 0.020 3.610 0.037 0.963 0.92-1.00 Marital satisfaction score -0.042 0.020 4.410 0.036 0.959 0.92–0.99 3.5 The Postpartum Depression Prediction Model Based on Marital Support Performs the Best, Outperforming the Early Pregnancy and Late Pregnancy Prediction Models The influencing factors obtained from binary logistic regression analysis (including consensus, conflict, positive interaction, marital satisfaction) were used as predictive variables to predict the risk of depression in pregnant women. The ROC curve was used to evaluate the model's ability to distinguish between depressed and non-depressed pregnant women. The closer the area under the curve (AUC) is to 1, the higher the prediction accuracy of the model. The results showed that the AUC values of the early pregnancy model, late pregnancy model, and postpartum model were 0.756, 0.608, and 0.82, respectively. The AUC value of the postpartum model was the highest, indicating the best prediction effect of the postpartum depression prediction model based on marital support (as shown in Fig. 3.4 ). The calibration curve results showed that for the early pregnancy model, the predicted probability was basically consistent with the actual probability, but it may slightly overestimate the risk in the high-risk population (predicted probability > 30%). For the late pregnancy model, the predicted probability in the 10%-20% range was slightly lower than the actual value; for the postpartum model, the calibration performance was the best, indicating that the model's prediction of postpartum depression was relatively accurate (as shown in Fig. 3.5 ). 4. Discussion Through longitudinal of pregnant women from early pregnancy to postpartum, this study deeply explored the moderating effect of marital support on the development of perinatal depression and the construction of a risk prediction model. The research results not only reveal the important role of marital support in the occurrence and development of perinatal depression but also provide intervention strategies and risk prediction indicators, which are of great significance for clinical practice and theoretical development. This study found that marital support shows significant dynamic moderating effects in the development of perinatal depression. The depressive symptoms of the high marital support group remained stable, while those of the low support group showed a significant upward trend. This finding is consistent with Brazeau Hr et al.'s (2020) research on the buffering effect of marital quality on psychological stress, which found that high marital support can reduce cortisol levels and thus alleviate emotional disorders[ 19 ]. This study not only verified the buffering effect of marital support on depression but also revealed the dynamic changes of this effect in different perinatal stages through longitudinal, providing a new perspective for understanding the complex relationship between marital support and depression. The analysis of the cross-lagged model further revealed the bidirectional predictive relationship between marital support and depression. Marital support in early pregnancy can significantly reduce the risk of depression in late pregnancy, but this effect weakens in the postpartum period. Conversely, depression in late pregnancy can adversely damage the quality of marital support postpartum, forming a vicious cycle. This result supports Kiecolt-Glaser JK et al.'s (2019) "depression-marital quality negative feedback cycle" theory[ 20 ], and through longitudinal and cross-lagged analysis, it more clearly reveals the dynamic changes and stage characteristics of this bidirectional relationship. This study further explored the impact of different marital dimensions in early pregnancy, late pregnancy, and postpartum on the risk of depression. The results showed that different dimensions of marital support have significant impacts on the risk of depression in all three stages; in the perinatal period, conflict frequency is positively correlated with the risk of depression, while consensus, positive interaction, and marital satisfaction are negatively correlated with the risk of depression, consistent with Werner-Bierwisch T's (2018) marital protection model[ 21 – 25 ]. This indicates that in the perinatal period, the higher the consensus and marital satisfaction between husband and wife, the lower the risk of depression[ 26 , 27 ]; the more conflicts and the less positive interaction, the higher the risk of depression[ 28 ]. Furthermore, by incorporating the above indicators into predictive variables and constructing depression prediction models for each stage of the perinatal period, all models showed relatively high prediction performance, with the postpartum depression prediction model performing the best. These results indicate that by comprehensively considering multiple indicators such as consensus, conflict, positive interaction, and marital satisfaction in marital support during the perinatal period, the risk of depression can be accurately predicted, providing strong support for clinical interventions. In conclusion, through longitudinal and cross-lagged analysis, this study deeply explored the moderating effect of marital support on the development of perinatal depression and the construction of a risk prediction model. The research results not only provide strong support for clinical practice but also offer new perspectives and ideas for theoretical development. However, this study also has certain limitations. For example, the limited sample size may affect the generalization of the model; future research can further expand the sample size, incorporate multi-modal data such as biological indicators and psychosocial factors to more comprehensively reveal the occurrence mechanism and intervention strategies of perinatal depression. Declarations Funding This study was supported by the Natural Science Foundation of Sichuan Province, China (Grant No. 2022NSFSC1371). Ethical Approval This study was conducted in accordance with the principles outlined in the Helsinki Declaration and received ethical approval from the Ethics Committee of West China Second Hospital of Sichuan University (Ethics Number: 2019(002)). Consent for publication Not applicable. Consent to Participate Written informed consent was obtained from all participants prior to the study. Data Availability Not applicable for that section. Clinical Trial Registration Not applicable for that section. Competing Interests The authors declare no competing financial interests or personal relationships that could have influenced this study. References Woody CA, Ferrari AJ, Siskind DJ, Whiteford HA, Harris MG. A systematic review and meta-regression of the prevalence and incidence of perinatal depression. J Affect Disord. 2017 Sep;219:86-92. Al-Abri K, Edge D, Armitage CJ. Prevalence and correlates of perinatal depression. Soc Psychiatry Psychiatr Epidemiol. 2023 Nov;58(11):1581-1590. 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Bull World Health Organ. 2017 Oct 1;95(10):706-717C. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviewers invited by journal 16 Oct, 2025 Editor assigned by journal 13 Oct, 2025 Editor invited by journal 23 Sep, 2025 Submission checks completed at journal 21 Sep, 2025 First submitted to journal 21 Sep, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7555596","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":535547569,"identity":"7ef9a199-599b-4fed-823d-bd4443578d71","order_by":0,"name":"Yu Gan","email":"","orcid":"","institution":"West China Second University Hospital of Sichuan University","correspondingAuthor":false,"prefix":"","firstName":"Yu","middleName":"","lastName":"Gan","suffix":""},{"id":535547570,"identity":"dd799094-29bb-4331-ada3-4ea37ac09c22","order_by":1,"name":"Shu juan Liao","email":"","orcid":"","institution":"West China Second University Hospital of Sichuan University","correspondingAuthor":false,"prefix":"","firstName":"Shu","middleName":"juan","lastName":"Liao","suffix":""},{"id":535547571,"identity":"8d6a9f03-443f-4660-b37d-4c20d7b5036c","order_by":2,"name":"Jing Chen","email":"","orcid":"","institution":"West China Second University Hospital of Sichuan University","correspondingAuthor":false,"prefix":"","firstName":"Jing","middleName":"","lastName":"Chen","suffix":""},{"id":535547572,"identity":"c765f851-1130-42fc-94f8-4fdf7e7fe3ed","order_by":3,"name":"Xiujing Guo","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAxklEQVRIiWNgGAWjYBACeWb+7x8/GNTw2B9vIFKLYTuDGbNEwTE5hjMHiLXmPIMZA88HZmOGGwlE6mBsZkh7IGHAltg48/HGGww1NtEEtbAzMxw3KDCQSWyWTiu2YDiWlttA2BbGBgmQLW3SOWYSjA2HCWthOMzMIMFjwJzYI3mGaC1sbCAtxhISPERqMWzmASo3OCZnwAP0SwIxfpHnP8P48MOfGh4D9sMbb3yosSHCYUjAQCKBFOUQLaTqGAWjYBSMgpEBAK1LOLLkGQGsAAAAAElFTkSuQmCC","orcid":"","institution":"West China Second 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06:44:44","extension":"xml","order_by":13,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":107767,"visible":true,"origin":"","legend":"","description":"","filename":"08690417d1c54a068d12fb18f50826351structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7555596/v1/f2da0c22b700f428246cd9fe.xml"},{"id":94732264,"identity":"4d1d786c-5caa-4538-b67a-688e3ef49a70","added_by":"auto","created_at":"2025-10-30 07:09:07","extension":"html","order_by":14,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":116205,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7555596/v1/a08d0e53435a922a5f0f97b7.html"},{"id":94732151,"identity":"f6ace2e9-3e29-41d3-99c5-e50b58d9d418","added_by":"auto","created_at":"2025-10-30 07:09:06","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":69083,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure 3.1 EPDS Scores and Prevalence Rates of Depression at Each Stage of Pregnancy\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7555596/v1/473a021a5f9c891300b2a845.png"},{"id":94732280,"identity":"48c651d6-848c-46e3-8f8e-188e54ca22a5","added_by":"auto","created_at":"2025-10-30 07:09:07","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":193918,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure 3.2 Comparison of Marital Support Scores in the Depression Group and Non-depression Group at Each Stage of Pregnancy\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNote: A: Early pregnancy,B: Late pregnancy, C: Postpartum,\u003cem\u003e*: P \u0026lt; 0.05 ,**: P \u0026lt; 0.01,***: P \u0026lt; 0.001\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7555596/v1/eb1030d1c24aa53802e2a7fd.png"},{"id":94731987,"identity":"8f053e00-f1f0-46b8-8bd9-08839276bbe5","added_by":"auto","created_at":"2025-10-30 07:09:02","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":87077,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure 3.3 Forest Plot of Binary Logistic Regression Analysis of Depression in Pregnant Women\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7555596/v1/320ecdf491242bdfeccd7cc7.png"},{"id":94732080,"identity":"74948877-c18c-4cec-ae3d-f1326621db3a","added_by":"auto","created_at":"2025-10-30 07:09:05","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":90413,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure 3.4 Depression Prediction Models for Pregnant Women at Each Stage\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNote: T1: Early pregnancy, T2: Late pregnancy, T3: Postpartum\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7555596/v1/b78dae537098a2827450b05b.png"},{"id":94732187,"identity":"1df3976d-66d3-49b6-8a99-93289a26df10","added_by":"auto","created_at":"2025-10-30 07:09:06","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":97078,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure 3.5 Calibration Curves of Depression Prediction Models for Pregnant Women at Each Stage\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNote: T1: Early pregnancy, T2: Late pregnancy, T3: Postpartum, n: Sample size\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-7555596/v1/8d59006688497a9754d8807a.png"},{"id":94827166,"identity":"4507f731-4cd4-4d0b-aa38-0775a037a2ce","added_by":"auto","created_at":"2025-10-31 06:55:14","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1785265,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7555596/v1/5a380184-ffc0-446b-8dd5-31ea5153a365.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"A Longitudinal Study from Early Pregnancy to Postpartum: The Moderating Effect of Marital Support on the Development of Perinatal Depression and the Construction of a Risk Prediction Model","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003ePerinatal period is a special stage in a woman's life, filled with physiological and psychological changes. Accompanied by dramatic fluctuations in hormone levels, changes in body morphology, and adaptation to the role of becoming a mother, women face numerous challenges during this period. Perinatal depression, as a common mental health issue, has a global prevalence rate of approximately 10%-20%, highlighting its universality and severity[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. In China, although the specific prevalence rate may vary due to regional, cultural, and methodological differences, its prevalence is also not negligible[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Perinatal depression not only has profound impacts on the physical and mental health of pregnant women, such as causing emotional distress, anxiety, and sleep disorders[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], but may also indirectly affect fetal development through its impact on the physiological state of pregnant women[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Furthermore, it may hinder the establishment and development of parent-child relationships after the birth of the baby[\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. In recent years, with the increasing emphasis on the mental health of pregnant women in society, the prevention and intervention of perinatal depression have become a research hotspot in public health. Marriage, as an indispensable part of the social support system, plays a crucial role in regulating individual mental health[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], particularly during the perinatal period, where the quality of marital support may directly relate to the psychological state and developmental trajectory of depressive symptoms in pregnant women[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Numerous studies have shown that a good marital relationship can provide pregnant women with a solid emotional support system, offering them emotional comfort and support[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Meanwhile, partners in marriage can also provide practical assistance in daily life, alleviating the burden on pregnant women. Additionally, mutual understanding and encouragement in marriage can instill confidence and courage in pregnant women to better cope with psychological stress and effectively reduce the risk of depression[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eHowever, despite the widespread recognition of the importance of marital support in preventing perinatal depression[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], there is a lack of in-depth research on how marital support specifically affects the developmental trajectory of perinatal depression and how to accurately utilize this relationship to construct an effective risk prediction model. Therefore, this study aims to conduct a systematic longitudinal study to deeply explore the moderating effect of marital support on the development of perinatal depression and to attempt to construct a scientific and effective risk prediction model for perinatal depression, with the aim of providing strong support for clinical practice, improving the mental health level of pregnant women, and reducing the incidence of perinatal depression.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Study Design\u003c/h2\u003e\u003cp\u003eThis study adopted a longitudinal design to systematically track pregnant women from early pregnancy to postpartum. A total of 1,520 eligible pregnant women who visited West China Second University Hospital, Sichuan University between January 2023 and December 2024 were included as research subjects. All pregnant women underwent regular prenatal examinations and deliveries at this hospital. The study was divided into three key time points for data collection: early pregnancy (T1, within 12 weeks of gestation), late pregnancy (T2, from 28 weeks of gestation to delivery), and postpartum (T3, within 6 weeks after delivery). This design allows for dynamic observation of changes in marital support and depressive symptoms over time, as well as their interactions.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Study Subjects\u003c/h2\u003e\u003cp\u003eThe inclusion criteria strictly limited subjects to pregnant women aged between 18 and 45 years old, with singleton pregnancies, no severe physical diseases or history of mental disorders, and who voluntarily participated in the study and signed informed consent forms. All participants fully understood the study purpose, procedures, and possible risks before signing the informed consent forms. This study has been reviewed and approved by the ethics committee to ensure that all research activities comply with ethical norms.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Measurement Tools\u003c/h2\u003e\u003cp\u003eDyadic Adjustment Scale (DAS): This study used the DAS scale to assess the marital support status of pregnant women at different time points (early pregnancy, late pregnancy, and postpartum). The DAS scale, compiled by Spanier in 1976, is a widely used standardized tool in marital relationship research. The scale consists of 32 items and four subscales: Affectional Expression (AE), Dyadic Consensus (DC), Dyadic Cohesion (AC), and Dyadic Satisfaction (DS). The total score range of the DAS scale is 0 to 151. Through this scale, detailed data on the marital support status of pregnant women can be obtained, including the specific content and scoring of the four subscales. Additionally, marital support scores in this study were mainly considered from four dimensions: consensus, conflict, positive interaction, and marital satisfaction. (1) Consensus: corresponds to the scores of the Dyadic Consensus subscale, with higher scores indicating greater ease in reaching consensus on important matters between husband and wife, and easier formation of unified opinions and actions in the face of various problems in marriage. (2) Conflict: Although the DAS scale does not directly name a \"conflict\" subscale, marital conflict can be reflected through relevant items in each subscale, such as the frequency of arguments during disagreements and ways of handling conflicts. Higher conflict levels may indicate poorer marital support. (3) Positive interaction: Related to the Affectional Expression and Dyadic Cohesion subscales, higher scores in positive interaction reflect more emotional expression, joint activities, and good communication between husband and wife, indicating a more harmonious and intimate relationship. (4) Marital satisfaction: Corresponds to the scores of the Dyadic Satisfaction subscale, directly reflecting the overall satisfaction level of pregnant women with their marital relationship, and is an important indicator for measuring the quality of marital support. This study strictly followed the guidance principles of the DAS scale for administration and scoring to ensure the accuracy and reliability of the assessment results.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eEdinburgh Postnatal Depression Scale (EPDS)\u003c/strong\u003e\u003cp\u003eThis scale is a widely used self-rating scale specifically designed for pregnant and postnatal women, used to comprehensively and meticulously assess depressive symptoms. The EPDS scale consists of 10 carefully designed items that comprehensively cover possible depression-related symptoms, such as emotional distress, loss of interest, self-blame and guilt, sleep disorders, appetite changes, loss of energy, anxiety, and lack of confidence in the future. In terms of scoring rules, each item is assigned different scoring levels based on the severity of symptoms, usually adopting a four-point scoring method from 0 to 3, where 0 points represent almost no symptoms and 3 points represent very severe symptoms. Pregnant women choose the option that best matches their symptom severity based on their actual situation in the past week. The scoring method is to sum the scores of the 10 items to obtain the total score. Higher total scores indicate more severe depressive symptoms in pregnant women. Generally, the EPDS scale has a specific critical value (\u0026ge;\u0026thinsp;13 points). When the total score reaches or exceeds this critical value, it suggests that the pregnant woman may have depressive emotions.\u003c/p\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.4 Statistical Analysis\u003c/h2\u003e\u003cp\u003eUnivariate analysis was initially conducted to explore the associations between marital support, depressive symptoms, and other relevant variables of pregnant women at different time points. Descriptive statistics were calculated for each variable, including means, standard deviations, frequency distributions, etc. For continuous variables conforming to a normal distribution, means (standard deviations) were used for description; for non-normally distributed continuous variables, medians (interquartile ranges) were used to describe their central tendency and dispersion; for categorical variables, frequencies (percentages) were presented. Additionally, preliminary comparisons were made between the depression group and the non-depression group in terms of marital support scores in each dimension. Cross-lagged models were used to test the bidirectional relationships between marital support and depressive symptoms. To more deeply explore the impact of different dimensions of marital support on the risk of perinatal depression, binary logistic regression analysis was conducted in this study, with different dimensions of marital support (such as consensus, conflict, positive interaction, marital satisfaction) as independent variables and the depressive status of pregnant women as the dependent variable for regression analysis. The odds ratio (OR) and confidence interval (CI) were calculated to assess the impact of each marital dimension on the risk of depression. Meanwhile, a risk prediction model for perinatal depression in pregnant women based on marital support was constructed. Cross-validation and performance evaluation were used to verify the stability and generalization ability of the model on different datasets.\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e3.1 General Information of Pregnant Women\u003c/h2\u003e\u003cp\u003eThe general information of pregnant women showed that the average age of the research subjects was 28.5\u0026thinsp;\u0026plusmn;\u0026thinsp;4.2 years old, with the majority being married (98.3%), having a college/university education (54.8%), medium income (45.2% with a monthly family income of 5000\u0026ndash;10000 yuan), and first-time mothers (76.5%). The gestational weeks at each stage met the requirements of the study design(as shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e3.1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e.\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 3.1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eGeneral Information of Pregnant Women (N\u0026thinsp;=\u0026thinsp;1520)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCategory\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD / (%)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge (years)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e28.5\u0026thinsp;\u0026plusmn;\u0026thinsp;4.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGestational weeks\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEarly pregnancy (T1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8.2\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLate pregnancy (T2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e34.6\u0026thinsp;\u0026plusmn;\u0026thinsp;2.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePostpartum (T3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.0\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMarital status\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMarried\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e98.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUnmarried/Divorced\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEducation level\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHigh school or below\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e32.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCollege/University\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e54.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMaster's degree or above\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e12.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMonthly family income\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;5000 yuan\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e18.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5000\u0026ndash;10000 yuan\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e45.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;10000 yuan\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e36.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFirst-time mothers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e76.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eExperienced mothers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e23.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e3.2 U-shaped Trend of Perinatal Depression and Significantly Lower Marital Support in the Depression Group\u003c/h2\u003e\u003cp\u003eThe EPDS scores and prevalence rates of depression in all pregnant women were statistically analyzed. The results showed that the mean EPDS scores at early pregnancy, late pregnancy, and postpartum were 7.45\u0026thinsp;\u0026plusmn;\u0026thinsp;3.57, 7.02\u0026thinsp;\u0026plusmn;\u0026thinsp;3.51, and 7.99\u0026thinsp;\u0026plusmn;\u0026thinsp;4.17, respectively. The prevalence rates of depression showed a U-shaped trend, with 16.5% in early pregnancy, 15.0% in late pregnancy, and 18.5% postpartum (as shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e3.2\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e3.1\u003c/span\u003e). Pregnant women were divided into a depression group (EPDS score\u0026thinsp;\u0026gt;\u0026thinsp;13) and a non-depression group based on EPDS scores. The results showed that there were significant differences in marital support scores (consensus, conflict, positive interaction, marital satisfaction, and total marital score) at each stage between the two groups (\u003cem\u003eP\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/em\u003e). The conflict scores in the depression group were significantly higher than those in the non-depression group, while the consensus, positive interaction, marital satisfaction, and total marital scores were significantly lower than those in the non-depression group. The total marital support scores at early pregnancy, late pregnancy, and postpartum in the depression group were significantly lower than those in the non-depression group (\u003cem\u003eP\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/em\u003e) (as shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3.3\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3.2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3.2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eEPDS Scores and Prevalence Rates of Depression at Each Stage of Pregnancy\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eStage\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD / (%)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEarly pregnancy (n\u0026thinsp;=\u0026thinsp;1520)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEPDS score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7.45\u0026thinsp;\u0026plusmn;\u0026thinsp;3.57\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePrevalence rate of depression\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e16.5%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLate pregnancy (n\u0026thinsp;=\u0026thinsp;1520)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEPDS score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7.02\u0026thinsp;\u0026plusmn;\u0026thinsp;3.51\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePrevalence rate of depression\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e15.0%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePostpartum (n\u0026thinsp;=\u0026thinsp;1520)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEPDS score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7.99\u0026thinsp;\u0026plusmn;\u0026thinsp;4.17\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePrevalence rate of depression\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e18.5%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3.3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eMarital Support Scores in the Depression Group and Non-depression Group at Each Stage of Pregnancy\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDepression status\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003en\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003et-value\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cem\u003eP-value\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEarly pregnancy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eConsensus score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e250\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e48.65\u0026thinsp;\u0026plusmn;\u0026thinsp;9.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e8.521\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1270\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e43.72\u0026thinsp;\u0026plusmn;\u0026thinsp;8.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eConflict score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e250\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e19.37\u0026thinsp;\u0026plusmn;\u0026thinsp;3.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-11.688\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1270\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e21.34\u0026thinsp;\u0026plusmn;\u0026thinsp;2.26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePositive interaction score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e250\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e13.81\u0026thinsp;\u0026plusmn;\u0026thinsp;4.75\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-6.110\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1270\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e15.64\u0026thinsp;\u0026plusmn;\u0026thinsp;4.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMarital satisfaction score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e250\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e16.64\u0026thinsp;\u0026plusmn;\u0026thinsp;3.59\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-7.950\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1270\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e18.28\u0026thinsp;\u0026plusmn;\u0026thinsp;2.85\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal marital score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e250\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e107.39\u0026thinsp;\u0026plusmn;\u0026thinsp;15.61\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-3.747\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.002\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1270\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e117.54\u0026thinsp;\u0026plusmn;\u0026thinsp;15.24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLate pregnancy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eConsensus score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e229\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e49.75\u0026thinsp;\u0026plusmn;\u0026thinsp;8.89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e6.377\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1291\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e44.88\u0026thinsp;\u0026plusmn;\u0026thinsp;8.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eConflict score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e229\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e19.04\u0026thinsp;\u0026plusmn;\u0026thinsp;2.83\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-9.170\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1291\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e21.11\u0026thinsp;\u0026plusmn;\u0026thinsp;2.45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePositive interaction score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e229\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e12.94\u0026thinsp;\u0026plusmn;\u0026thinsp;4.49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-5.450\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1291\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e15.15\u0026thinsp;\u0026plusmn;\u0026thinsp;4.51\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMarital satisfaction score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e229\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e16.48\u0026thinsp;\u0026plusmn;\u0026thinsp;3.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-4.539\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1291\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e17.71\u0026thinsp;\u0026plusmn;\u0026thinsp;3.97\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal marital score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e229\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e115.94\u0026thinsp;\u0026plusmn;\u0026thinsp;14.64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-2.247\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.028\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1291\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e124.58\u0026thinsp;\u0026plusmn;\u0026thinsp;14.97\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePostpartum\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eConsensus score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e281\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e50.87\u0026thinsp;\u0026plusmn;\u0026thinsp;10.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e6.359\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1239\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e44.62\u0026thinsp;\u0026plusmn;\u0026thinsp;8.69\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eConflict score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e281\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e18.54\u0026thinsp;\u0026plusmn;\u0026thinsp;4.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-6.503\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1239\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e20.83\u0026thinsp;\u0026plusmn;\u0026thinsp;3.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePositive interaction score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e281\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e11.42\u0026thinsp;\u0026plusmn;\u0026thinsp;5.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-5.757\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1239\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e14.47\u0026thinsp;\u0026plusmn;\u0026thinsp;4.85\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMarital satisfaction score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e281\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e15.37\u0026thinsp;\u0026plusmn;\u0026thinsp;3.83\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-5.148\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1239\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e17.26\u0026thinsp;\u0026plusmn;\u0026thinsp;3.31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal marital score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e281\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e104.56\u0026thinsp;\u0026plusmn;\u0026thinsp;17.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-2.813\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.006\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1239\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e115.70\u0026thinsp;\u0026plusmn;\u0026thinsp;17.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eNote\u003c/strong\u003e\u003cp\u003eA: Early pregnancy,B: Late pregnancy, C: Postpartum,\u003cem\u003e*: P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 ,**: P\u0026thinsp;\u0026lt;\u0026thinsp;0.01,***: P\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/em\u003e\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003e3.3 Marital Support in Early Pregnancy Reduces the Risk of Depression in Late Pregnancy, While Depression in Late Pregnancy Weakens Marital Support Postpartum\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe results of the cross-lagged model analysis of marital support and depression are shown in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e3.4\u003c/span\u003e. Marital support in early pregnancy significantly reduces the risk of depression in late pregnancy (\u003cem\u003eβ=-0.24, P\u0026thinsp;=\u0026thinsp;0.003\u003c/em\u003e). Depression in late pregnancy significantly reduces marital support postpartum (\u003cem\u003eβ=-0.18, P\u0026thinsp;=\u0026thinsp;0.020\u003c/em\u003e); the predictive effect of marital support in late pregnancy on postpartum depression is not significant (\u003cem\u003eβ=-0.10, P\u0026thinsp;=\u0026thinsp;0.125\u003c/em\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3.4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eCross-lagged Model of Marital Support and Depression\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePath\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eβ (SE)\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eP-value\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMarital support in early pregnancy \u0026rarr; Depression in late pregnancy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.24 (0.07)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.003\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMarital support in late pregnancy \u0026rarr; Depression postpartum\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.10 (0.06)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.125\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDepression in early pregnancy \u0026rarr; Marital support in late pregnancy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.08 (0.05)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.112\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDepression in late pregnancy \u0026rarr; Marital support postpartum\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.18 (0.07)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.020\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003e3.4 Consensus, Positive Interaction, and Marital Satisfaction are Protective Factors for Depression, While Conflict is a Risk Factor\u003c/b\u003e\u003c/p\u003e\u003cp\u003eBinary logistic regression analysis was conducted with marital support (consensus, conflict, positive interaction, marital satisfaction) as influencing factors for the risk of depression. The results showed that in early pregnancy, the total consensus score (\u003cem\u003eOR\u0026thinsp;=\u0026thinsp;0.975, P\u0026thinsp;=\u0026thinsp;0.002\u003c/em\u003e), total positive interaction score (\u003cem\u003eOR\u0026thinsp;=\u0026thinsp;0.966, P\u0026thinsp;=\u0026thinsp;0.020\u003c/em\u003e), and total marital satisfaction score (\u003cem\u003eOR\u0026thinsp;=\u0026thinsp;0.946, P\u0026thinsp;=\u0026thinsp;0.012\u003c/em\u003e) were protective factors; the total conflict score (\u003cem\u003eOR\u0026thinsp;=\u0026thinsp;1.162, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/em\u003e) was a risk factor. In late pregnancy, the total consensus score (\u003cem\u003eOR\u0026thinsp;=\u0026thinsp;0.970, P\u0026thinsp;=\u0026thinsp;0.003\u003c/em\u003e), total positive interaction score (OR\u0026thinsp;=\u0026thinsp;0.961, P\u0026thinsp;=\u0026thinsp;0.026), and total marital satisfaction score (\u003cem\u003eOR\u0026thinsp;=\u0026thinsp;0.951, P\u0026thinsp;=\u0026thinsp;0.046\u003c/em\u003e) were protective factors; the total conflict score (\u003cem\u003eOR\u0026thinsp;=\u0026thinsp;1.197, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/em\u003e) was a risk factor. In the postpartum period, the total consensus score (\u003cem\u003eOR\u0026thinsp;=\u0026thinsp;0.972, P\u0026thinsp;=\u0026thinsp;0.020\u003c/em\u003e), total positive interaction score (\u003cem\u003eOR\u0026thinsp;=\u0026thinsp;0.963, P\u0026thinsp;=\u0026thinsp;0.037\u003c/em\u003e), and total marital satisfaction score (\u003cem\u003eOR\u0026thinsp;=\u0026thinsp;0.959, P\u0026thinsp;=\u0026thinsp;0.036\u003c/em\u003e) were protective factors; the total conflict score (\u003cem\u003eOR\u0026thinsp;=\u0026thinsp;1.128, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/em\u003e) was a risk factor (as shown in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e3.5\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3.3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3.5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eBinary Logistic Regression Analysis of Depression in Pregnant Women\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"8\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eStage\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eβ\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eSE\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eWald\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cem\u003eP-value\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cem\u003eOR\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u003cem\u003e95% CI\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eT1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eConsensus score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-0.025\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.008\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e9.752\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.002\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.975\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.96\u0026ndash;0.99\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eConflict score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.150\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.025\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e36.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1.162\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e1.16\u0026ndash;1.22\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePositive interaction score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-0.035\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.015\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e5.444\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.020\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.966\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.93\u0026ndash;0.99\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMarital satisfaction score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-0.055\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.022\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e6.250\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.012\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.946\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.90\u0026ndash;0.98\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eT2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eConsensus score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-0.030\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.010\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e9.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.003\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.970\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.95\u0026ndash;0.99\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eConflict score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.180\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.030\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e36.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1.197\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e1.12\u0026ndash;1.27\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePositive interaction score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-0.040\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.018\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e4.938\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.026\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.961\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.92\u0026ndash;0.99\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMarital satisfaction score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-0.050\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.025\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e4.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.046\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.951\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.90\u0026ndash;0.99\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eT3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eConsensus score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-0.028\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.012\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e5.444\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.020\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.972\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.95\u0026ndash;0.99\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eConflict score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.120\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.028\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e18.367\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1.128\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e1.06\u0026ndash;1.19\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePositive interaction score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-0.038\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.020\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e3.610\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.037\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.963\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.92-1.00\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMarital satisfaction score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-0.042\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.020\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e4.410\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.036\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.959\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.92\u0026ndash;0.99\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003e3.5 The Postpartum Depression Prediction Model Based on Marital Support Performs the Best, Outperforming the Early Pregnancy and Late Pregnancy Prediction Models\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe influencing factors obtained from binary logistic regression analysis (including consensus, conflict, positive interaction, marital satisfaction) were used as predictive variables to predict the risk of depression in pregnant women. The ROC curve was used to evaluate the model's ability to distinguish between depressed and non-depressed pregnant women. The closer the area under the curve (AUC) is to 1, the higher the prediction accuracy of the model. The results showed that the AUC values of the early pregnancy model, late pregnancy model, and postpartum model were 0.756, 0.608, and 0.82, respectively. The AUC value of the postpartum model was the highest, indicating the best prediction effect of the postpartum depression prediction model based on marital support (as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3.4\u003c/span\u003e). The calibration curve results showed that for the early pregnancy model, the predicted probability was basically consistent with the actual probability, but it may slightly overestimate the risk in the high-risk population (predicted probability\u0026thinsp;\u0026gt;\u0026thinsp;30%). For the late pregnancy model, the predicted probability in the 10%-20% range was slightly lower than the actual value; for the postpartum model, the calibration performance was the best, indicating that the model's prediction of postpartum depression was relatively accurate (as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e3.5\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThrough longitudinal of pregnant women from early pregnancy to postpartum, this study deeply explored the moderating effect of marital support on the development of perinatal depression and the construction of a risk prediction model. The research results not only reveal the important role of marital support in the occurrence and development of perinatal depression but also provide intervention strategies and risk prediction indicators, which are of great significance for clinical practice and theoretical development.\u003c/p\u003e\u003cp\u003eThis study found that marital support shows significant dynamic moderating effects in the development of perinatal depression. The depressive symptoms of the high marital support group remained stable, while those of the low support group showed a significant upward trend. This finding is consistent with Brazeau Hr et al.'s (2020) research on the buffering effect of marital quality on psychological stress, which found that high marital support can reduce cortisol levels and thus alleviate emotional disorders[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. This study not only verified the buffering effect of marital support on depression but also revealed the dynamic changes of this effect in different perinatal stages through longitudinal, providing a new perspective for understanding the complex relationship between marital support and depression. The analysis of the cross-lagged model further revealed the bidirectional predictive relationship between marital support and depression. Marital support in early pregnancy can significantly reduce the risk of depression in late pregnancy, but this effect weakens in the postpartum period. Conversely, depression in late pregnancy can adversely damage the quality of marital support postpartum, forming a vicious cycle. This result supports Kiecolt-Glaser JK et al.'s (2019) \"depression-marital quality negative feedback cycle\" theory[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], and through longitudinal and cross-lagged analysis, it more clearly reveals the dynamic changes and stage characteristics of this bidirectional relationship.\u003c/p\u003e\u003cp\u003eThis study further explored the impact of different marital dimensions in early pregnancy, late pregnancy, and postpartum on the risk of depression. The results showed that different dimensions of marital support have significant impacts on the risk of depression in all three stages; in the perinatal period, conflict frequency is positively correlated with the risk of depression, while consensus, positive interaction, and marital satisfaction are negatively correlated with the risk of depression, consistent with Werner-Bierwisch T's (2018) marital protection model[\u003cspan additionalcitationids=\"CR22 CR23 CR24\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. This indicates that in the perinatal period, the higher the consensus and marital satisfaction between husband and wife, the lower the risk of depression[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]; the more conflicts and the less positive interaction, the higher the risk of depression[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Furthermore, by incorporating the above indicators into predictive variables and constructing depression prediction models for each stage of the perinatal period, all models showed relatively high prediction performance, with the postpartum depression prediction model performing the best. These results indicate that by comprehensively considering multiple indicators such as consensus, conflict, positive interaction, and marital satisfaction in marital support during the perinatal period, the risk of depression can be accurately predicted, providing strong support for clinical interventions.\u003c/p\u003e\u003cp\u003eIn conclusion, through longitudinal and cross-lagged analysis, this study deeply explored the moderating effect of marital support on the development of perinatal depression and the construction of a risk prediction model. The research results not only provide strong support for clinical practice but also offer new perspectives and ideas for theoretical development. However, this study also has certain limitations. For example, the limited sample size may affect the generalization of the model; future research can further expand the sample size, incorporate multi-modal data such as biological indicators and psychosocial factors to more comprehensively reveal the occurrence mechanism and intervention strategies of perinatal depression.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by the Natural Science Foundation of Sichuan Province, China (Grant No. 2022NSFSC1371).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical Approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was conducted in accordance with the principles outlined in the Helsinki Declaration and received ethical approval from the Ethics Committee of West China Second Hospital of Sichuan University (Ethics Number: 2019(002)).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWritten informed consent was obtained from all participants prior to the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable for that section.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical Trial Registration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable for that section.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing financial interests or personal relationships that could have influenced this study.\u003cstrong\u003e\u003c/strong\u003e\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWoody CA, Ferrari AJ, Siskind DJ, Whiteford HA, Harris MG. 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BMC Pregnancy Childbirth. 2018 Dec 4;18(1):473.\u003c/li\u003e\n\u003cli\u003eKasalova P, Prasko J, Holubova M, Vrbova K, Zmeskalova D, Slepecky M, Grambal A. Anxiety disorders and marital satisfaction. Neuro Endocrinol Lett. 2018 Feb;38(8):555-564. \u003c/li\u003e\n\u003cli\u003eWhisman MA, Sbarra DA, Beach SRH. Intimate Relationships and Depression: Searching for Causation in the Sea of Association. Annu Rev Clin Psychol. 2021 May 7;17:233-258. \u003c/li\u003e\n\u003cli\u003eUpadhyay RP, Chowdhury R, Aslyeh Salehi, Sarkar K, Singh SK, Sinha B, Pawar A, Rajalakshmi AK, Kumar A. Postpartum depression in India: a systematic review and meta-analysis. Bull World Health Organ. 2017 Oct 1;95(10):706-717C. \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-pregnancy-and-childbirth","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"prch","sideBox":"Learn more about [BMC Pregnancy and Childbirth](http://bmcpregnancychildbirth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/prch/default.aspx","title":"BMC Pregnancy and Childbirth","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Pregnant women, Depression, Marital support, Prediction model","lastPublishedDoi":"10.21203/rs.3.rs-7555596/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7555596/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjective\u003c/h2\u003e\u003cp\u003eTo investigate the moderating effect of marital support on the development of perinatal depression and to construct a risk prediction model for perinatal depression, providing important references for clinical practice.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eThis study adopted a longitudinal design, including 1,520 pregnant women who visited West China Second University Hospital, Sichuan University between January 2023 and December 2024. Data were collected at three time points: early pregnancy (T1), late pregnancy (T2), and postpartum (T3). The Dyadic Adjustment Scale (DAS) was used to assess marital support, and the Edinburgh Postnatal Depression Scale (EPDS) was used to assess depressive symptoms. Data analysis methods included univariate analysis, logistic regression, cross-lagged models, and prediction model construction.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eThe mean EPDS scores at early pregnancy, late pregnancy, and postpartum were 7.45\u0026thinsp;\u0026plusmn;\u0026thinsp;3.57, 7.02\u0026thinsp;\u0026plusmn;\u0026thinsp;3.51, and 7.99\u0026thinsp;\u0026plusmn;\u0026thinsp;4.17, respectively. The prevalence of depression showed a U-shaped trend, with 16.5% in early pregnancy, 15.0% in late pregnancy, and 18.5% postpartum. The results of the univariate analysis indicated that the marital support scores (including consensus, positive interaction, marital satisfaction, and total marital score) in the depressed group were all significantly lower than those in the non-depressed group (\u003cem\u003eP\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/em\u003e), while the conflict score was significantly higher than that in the non-depressed group (\u003cem\u003eP\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/em\u003e). Cross-lagged model analysis indicated that marital support in early pregnancy significantly reduced the risk of depression in late pregnancy (\u003cem\u003eβ=-0.24, P\u0026thinsp;=\u0026thinsp;0.003\u003c/em\u003e), while depression in late pregnancy significantly reduced marital support postpartum (\u003cem\u003eβ=-0.18, P\u0026thinsp;=\u0026thinsp;0.020\u003c/em\u003e). Multivariate logistic regression analysis showed that three dimensions of marital support (including consensus, positive interaction, marital satisfaction) were protective factors (\u003cem\u003eOR\u0026thinsp;\u0026lt;\u0026thinsp;1, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/em\u003e) in all three stages, whereas conflict was a risk factor (\u003cem\u003eOR\u0026thinsp;\u0026gt;\u0026thinsp;1, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/em\u003e). The performance of the postpartum depression prediction model based on marital support was the highest (\u003cem\u003eAUC\u0026thinsp;=\u0026thinsp;0.82\u003c/em\u003e), indicating its excellent performance.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eMarital support plays a significant moderating role in the development of perinatal depression. High marital support reduces the risk of depression, while low support increases the risk. The postpartum depression prediction model based on marital support performs well, providing important references for clinical interventions in perinatal depression.\u003c/p\u003e","manuscriptTitle":"A Longitudinal Study from Early Pregnancy to Postpartum: The Moderating Effect of Marital Support on the Development of Perinatal Depression and the Construction of a Risk Prediction Model","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-30 07:04:32","doi":"10.21203/rs.3.rs-7555596/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewersInvited","content":"","date":"2025-10-16T07:17:36+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-10-14T03:12:35+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-09-23T16:05:19+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-09-21T13:36:03+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Pregnancy and Childbirth","date":"2025-09-21T13:33:04+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-pregnancy-and-childbirth","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"prch","sideBox":"Learn more about [BMC Pregnancy and Childbirth](http://bmcpregnancychildbirth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/prch/default.aspx","title":"BMC Pregnancy and Childbirth","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"baf6cdb2-98a6-4326-a6ce-7956de08e8c0","owner":[],"postedDate":"October 30th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-10-30T07:04:32+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-30 07:04:32","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7555596","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7555596","identity":"rs-7555596","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}