The influence of perinatal depression on marital relationships in high-risk pregnant women: A parallel process latent growth model

The influence of perinatal depression on marital relationships in high-risk pregnant women: A parallel process latent growth 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 The influence of perinatal depression on marital relationships in high-risk pregnant women: A parallel process latent growth model FEIYAN YI, Liping Ren, SUKHEE AHN This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6730714/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 6 You are reading this latest preprint version Abstract Background Perinatal depression and marital satisfaction are key factors in pregnant women's successful adaptation to parenthood and the maternal role. However, most existing studies have primarily used cross-sectional data to explain the relationship between depression and marital satisfaction, lacking a longitudinal perspective to capture their dynamic changes from pregnancy through the postpartum period. Methods Therefore, this study aimed to explore how depressive symptoms over time influence marital satisfaction in 157 high-risk perinatal women in South Korea, using a parallel latent growth model. Depression levels were assessed at 24–32 weeks of gestation (T1), 6 weeks postpartum (T2), and 12 weeks postpartum (T3). Results The results showed a significant negative correlation between depression and marital satisfaction (r = -0.17 to -0.32, p < .05). The parallel latent growth model revealed that a faster decrease in depressive symptoms was associated with greater improvements in marital satisfaction (β = -0.54, p < .001). Although baseline depression did not significantly predict initial marital satisfaction, its declining trend over time was meaningful. Conclusions These findings highlight the importance of early depression screening and timely intervention during pregnancy, particularly for high-risk women, to support their maternal role adaptation and facilitate a positive transition into this new life stage. High-risk Pregnant Women Parallel Process Latent Growth Model Perinatal Depression Perinatal Marital Relationships Figures Figure 1 Background Perinatal depression (PND) is a prevalent and serious public health problem [ 8 , 9 ] that negatively affects infant care and adjustment to the family-level adjustment [ 26 ]. Women with high-risk pregnancies are more likely than women with low-risk pregnancies to experience psychological distress about their own and their baby's health from the time of pregnancy through to the postpartum period. For example, mothers with gestational hypertension were 5 times more likely to be in the increased group of depression [ 18 ]. The prevalence of perinatal depression among high-risk pregnant women has been reported as 39–52% [ 17 , 21 , 25 , 28 , 32 , 39 ], compared to 9–32%% in low-risk pregnancies [ 11 , 16 , 35 , 38 ]. Even after experiencing a high-risk pregnancy, the risk of depression is even higher, as the burden of the baby's health risks adds to the stress of parenting [ 12 ]. While mother-father relationship quality is one of the key factors in the adjustment to parenthood and the child's development [ 29 ], many parents reported a decline in their couple's relationship during the postpartum period than during pregnancy [ 4 ]. Furthermore, parents suffering from stress and depression were more likely to feel inadequate spousal support and less satisfied with their relationship [ 2 , 25 , 27 ]. In particular, maternal postpartum depression is a key factor that negatively affects marital satisfaction, leading to lower levels of parenting competence and infant attachment in mothers who had high-risk pregnancies [ 25 ]. Therefore, perinatal depression and marital satisfaction seem to be essential factors for a successful adjustment to parenthood in these mothers who had a high-risk pregnancy, so it is important to look at how postpartum depression affects marital satisfaction over time. Pregnancy and childbirth represent a critical period of psychological and relational adjustment for women. As women transition from mid to late pregnancy, they encounter challenges not only in preparing for their new parenting role but also in restructuring marital relationships to accommodate the arrival of a newborn and the evolving needs of the family [ 1 ]. The transition to parenthood requires families to adjust to new family structures and functions for the overall family's well-being. Maternal depression during pregnancy and postpartum periods significantly influences women's ability to adapt to these changes, potentially impacting marital relationship quality [ 4 ]. Gaining insights into how individuals adjust during this period can help healthcare providers offer more tailored and practical support. However, these studies were mainly elucidated by providing cross-sectional data. There is a lack of a longitudinal description of maternal dynamics from pregnancy to postpartum regarding development and change. Latent growth modeling is a useful statistical tool in developmental change research and has been successfully applied to studies of maternal depression for up to 8 years [ 1 , 18 , 23 ]. These studies reported different development trajectories of depressive symptoms of women during the perinatal period: low stable, moderately stable, and increasing or decreasing patterns [ 1 , 18 , 23 ]. The other study found that maternal depression trajectories over time had a significant negative impact on marital relationships within 8 years postpartum in mothers who had low-risk pregnancies [ 23 ]. Therefore, in describing the relationship between the level of maternal depression and marital relationship during the perinatal period using dynamics, latent growth modeling with longitudinal data is necessary. The purpose of this study was 1) to identify how maternal depression and marital relationships change from mid-pregnancy to 12 weeks postpartum and 2) to explore how these changes in depression continue to affect their marital relationships. Methods Study Design and participants This study utilized a longitudinal survey design to explore the change trajectories and their relationships between maternal depression and marital relationship from mid-pregnancy to 12 weeks postpartum in Korean women who had high-risk pregnancies. We recruited 157 pregnant women in South Korea who met the criteria for this study. The inclusion criteria for the study participants were pregnant women who were married and living with their husbands; pregnant women diagnosed with high-risk pregnancies, including 19 diagnoses designated by the National Health Insurance Service of Korea, such as preterm labor, premature rupture of membranes, and cervical incompetence; willing to participate in follow-up cohort study during three-time points of data collection: 24–32 weeks of pregnancy (T1), 6 weeks postpartum(T2), and 12 weeks postpartum (T3). Exclusion Criteria were as follows: single mothers, women separated from their spouses, and their infants are admitted to the hospital at 6 weeks and 3 months postpartum so that childrearing has not yet started. Based on the complexity of modeling structural equations and the expected effect size, a minimum of 100 or 200 participants was required to obtain sufficient statistical power [ 40 ]. A total of 157 valid data were obtained in this study. Measurements Perinatal depression was measured by using the Korean version of the Edinburgh Postnatal Depression Scale (EPDS) [ 7 , 22 ]. The EPDS consists of 10 self-reported questions on depression, anxiety and fear, guilt, and self-harm thoughts and is scored on a 4-point scale ranging from 0–3, with a total score ranging from 0–30. Cox et al. reported the tool's reliability at the time of development as Cronbach's α = .87. In this study, it was .84, .88, and .89 at three measurement time points. The marital relationship was measured by using the simplified Korean version of DAS-10 [ 6 ] based on 32 questions of the Dyadic Adjustment Scale (DAS) [ 33 ]. Questions 1–9 are on a 5-point scale, including marital conflicts, satisfaction, and cohesion. Finally, question 10 is based on a 6-point scale regarding plans or resolutions for future marital life. The higher the score, the higher the marital relationships. The reliability of this Korean version is Cronbach's alpha=. 83. In this study, it was .87, .84, and .86 at 3 measurement time points. Characteristics include maternal age, education, marital duration, and planned pregnancy. Ethical approval All procedures were performed in compliance with the Helsinki Declaration and according to the relevant laws and institutional guidelines. This study was approved by the Institutional Review Board of XX University (N202007-SB-094-01). Statistical analysis Data were analyzed using SPSS 29.0 for reliability, descriptive, and correlation analysis. We used the Mplus 8.3 version for latent growth modeling (LGM) and simultaneously analyzed the potential growth trajectories of these two variables. To address the issue of missing values in data, the maximum likelihood (ML) method is first used to process the missing data on SPSS data to maximize the utilization of all available data to handle missing values [3]. Two potential factors were evaluated, one indicating the initial values of depression and marital relationships (i.e., intercept) and the other indicating the changes in these variables over time (i.e., slope). First, two separate univariate latent growth models (LGMs) were conducted for depression and marital relationship, respectively. In each model, intercept factors were fixed at loadings of 1, and residual variances of observed variables were freely estimated. For slope factors, we examined two alternative specifications: fixed slope loadings of (0, 1, 2), indicative of linear change, and partially fixed slope loadings of (0, 1, *), consistent with a latent nonlinear growth model. The model fit indices and parameter stability of these two approaches were compared to select the optimal parameterization [14, 30]. And unconditional parallel process models were tested to determine the effect of the initial level of perinatal depression to on the initial level of marital relationships, as well as the effect of change in perinatal depression on change in marital relationships. A bootstrap procedure was used to test and validate a final model's statistical significance of the path and indirect effects. Model fit was assessed by comparing the fit index (CFI), Tucker Lewis index (TLI), root mean square error of approximation (RMSEA), and standardized root mean square residual (SRMR), following the growth model criteria. Model fit was considered good when CFI and TLI ≥ 0.90, RMSEA ≤ 0.10, and SRMR ≤ 0.08 [19]. Results Participant Demographics The average age of high-risk pregnant women was 35.91 years old, with 85 (65.9%) over 35 years old, 122 (94.6%) a college graduate and above, and the average length of marriage was 3.54 years. Most (76.0%) had a planned pregnancy (Table 1). Descriptive statistics and correlation Maternal depression levels increased from 7.96 ± 5.17 during mid-pregnancy (T1) to 10.62 ± 6.38 at 6 weeks postpartum (T2) and slightly decreased to 9.23 ± 6.07 at 12 weeks postpartum (T3). The level of marital relationship showed a slight decline over time, starting at 38.46 ± 6.64 during mid-pregnancy, decreasing to 36.93 ± 6.74 at 6 weeks postpartum, and further dropping to 35.35 ± 7.88 at 12 weeks postpartum. The association of depression with marital relationship at mid-pregnancy, 6 weeks postpartum, and 12 weeks postpartum were found. Significant positive correlations were found among depression (r = 0.24 to 0.61, p < .05) and among marital relationships (r = 0.61 to 0.77, p < .001) over time. Several negative correlations were found between perinatal depression and marital relationships over time (r = -0.17 to -0.32, p < .05) over time (Table 2). Univariate growth models To determine whether the changes in maternal depression and marital relationship followed linear or nonlinear trajectories during the perinatal period, we fitted two unconditional latent growth models for each variable: a linear model with fixed slope loadings (0, 1, 2) and a nonlinear latent basis model with partially fixed loadings (0, 1, *). Model fit indices indicated that the nonlinear unconditional latent growth model better fit the data compared to the linear model (Table 3). In the nonlinear unconditional growth model for maternal depression, the estimated mean of the intercept, representing the initial level of depression, was 8.14 ( p < .001), significantly greater than zero. Maternal depression showed a significant increase over the three measurement occasions (slope = 2.83, p < .001). The intercept variance (σ² = 11.11, p = .045) and the slope variance (σ² = 15.24, p = .154) indicated substantial interindividual variability in baseline levels of maternal depression. However, variability in rates of change over time was not statistically significant between individuals. Furthermore, a positive correlation was observed between the intercept and slope (r = .30, p = .624), suggesting that women with higher initial levels of maternal depression experienced more rapid increases in depression over time. In the nonlinear unconditional growth model for marital relationships, the estimated mean of the intercept was 38.07 ( p < .001), indicating that, on average, participants initially reported high levels of perceived relationship quality with their partners. The slope was negative and statistically significant (-1.44, p < .001), suggesting a steady decline in marital relationships over the three measurement occasions. Significant variance in the intercept (σ² = 40.73, p < .001) indicated considerable individual differences in initial relationship quality. In contrast, the variance in the slope (σ² = 3.08, p = .135) was not statistically significant, reflecting limited variation in trajectories of change. A negative correlation was also found between the intercept and slope (r = − .20, p = .211), indicating that participants who initially reported higher levels of marital relationship tended to experience a steeper decline over time. Parallel process latent growth model for depression and marital relationships This study established a parallel process latent growth model to examine the direct effects of depression's initial level on marital relationships and to explore the co-varying trajectories of these two variables. The model fit results were as follows: χ² = 20.51 ( p = .002), CFI = 0.97, TLI = 0.92, RMSEA = 0.12, SRMR = 0.04, indicating that the model's overall fit was good (Table 4). In a parallel process latent growth model examining depression and marital relationships among older adults, the intercept of depression was a significant predictor of the intercept of marital relationships (β = -0.43, p < .001). This finding indicates that participants with lower initial levels of depression tended to have higher initial levels of marital relationships. Additionally, the intercept of depression showed a negative association with the slope (rate of change) of marital relationships (β = -0.002, p = .998). Although not statistically significant, the direction of this effect suggests that participants with lower baseline depression tended to experience a faster increase in marital relationships over time. Finally, the slope of depression was negatively associated with the slope of marital relationship (β = -0.54, p < .001). This significant negative association indicates that the faster the decline in depression over time, the faster the increase in marital relationships. In other words, women who showed a more rapid reduction in depression symptoms tended to exhibit correspondingly faster growth in their marital relationships (Fig. 1). Discussion The findings of this study indicate that among high-risk pregnant women in South Korea who participated in the study, more than 50% were of advanced maternal age (> 35 years), and less than a quarter experienced unintended pregnancies. Change trajectories of maternal depression and marital relationships Maternal depression levels at mid-pregnancy (T1) had a mean score of 7.96, indicating that most mothers were below the depression risk threshold of 10 on the EPDS scores. However, at 6 weeks postpartum (T2), the mean score increased to 10.62, crossing the threshold and suggesting an elevated risk of depression during this period. By 12 weeks postpartum (T3), the mean score slightly decreased to 9.23, falling below the cut point but still reflecting higher levels than during pregnancy. Mothers who have given birth following high-risk pregnancies—resulting in preterm infants, low-birth-weight babies, or infants with health concerns, temperamental difficulties, or other issues—often feel a lack of parenting confidence. This, in turn, contributes to heightened parenting stress and an increased risk of postpartum depression [ 12 ]. It is crucial to assess the risk of postpartum depression among mothers who visit hospitals for postpartum health check-ups within six weeks after delivery. Moreover, there is a need to implement interventions aimed at addressing and mitigating depression in these individuals while providing a holistic approach to understanding women and their high-risk journey. Additionally, mothers who have undergone high-risk pregnancies often go through a range of emotional and psychological experiences and remain concerned about their own and their infant’s health and well-being after birth [ 20 ]. Therefore, providing comprehensive health evaluations and precise and detailed information is paramount. Since maternal depression levels often do not return to pre-pregnancy levels even at 12 weeks postpartum, it is essential to implement both short-term and medium-term strategies. These strategies should include informational support, emotional counseling, and advisory services, such as phone consultations or open chat platforms, throughout the perinatal period to address maternal health and infant care issues [ 24 ]. The marital relationships of the study participants showed a declining trend as time progressed postpartum, compared to the levels observed during pregnancy. This aligns with previous research asserting that the transition to parenthood often leads to weakened marital relationships due to physical challenges, the burden of acquiring new roles, shifts in family priorities, and a lack of shared time between spouses [ 4 , 10 ]. Mothers who have undergone the challenging process from high-risk pregnancies to childbirth often experience a weakening of the marital bond during the transition to motherhood. This transition highlights the potential instability in the relationship, which was initially strengthened by shared expectations of a healthy delivery and the birth of their babies during pregnancy, suggesting an increased risk of relationship discord during the postpartum period [ 10 ]. Particularly following high-risk pregnancies, mothers who spend significant time and effort caring for themselves and their children postpartum may experience physical and mental exhaustion. If they perceive insufficient support from their spouse, this can lead to emotional distancing in the marital relationship and, consequently, a decline in marital satisfaction [ 2 , 27 ]. Parallel Trajectories of Perinatal Depression and Marital Relationship This study investigated the parallel development of perinatal depression and marital relationship quality among high-risk pregnant women in South Korea using a parallel process latent growth model. The findings revealed a significant negative association between the initial levels of depression and marital relationship quality. Specifically, during the initial stage of pregnancy (gestational weeks 24–32), women who reported higher levels of depressive symptoms also tended to report lower levels of marital satisfaction (β = -0.43). This result is consistent with previous studies indicating that antenatal depression can undermine emotional connection and perceived partner support during pregnancy [ 2 , 23 ]. This may be related to the inability of partners or husbands to provide sufficient security and emotional support to women experiencing high-risk pregnancies. In marital relationships, mutual dependence and trust between partners contribute to a healthy psychological state, which serves as a protective factor against anxiety and depression in women [ 5 ]. Furthermore, the results revealed a significant negative association between the slopes of depression and marital relationship quality (β = -0.54), suggesting that a faster decline in depressive symptoms over time was associated with a more rapid improvement in marital relationships. This finding aligns with previous research showing that maternal emotional recovery is often accompanied by improved interpersonal functioning and relational well-being [ 36 ]. In this study, women who exhibited a more pronounced reduction in depression from mid-pregnancy through the postpartum period also tended to experience strengthening of their marital bonds. These results highlight the dynamic interplay between psychological health and relational outcomes during the perinatal period. However, the effect of the initial level of depression on the rate of change in marital relationship quality was not statistically significant (β = -0.002, p = .998). While the direction of the association suggests that women with lower initial depression levels may experience slightly more significant improvements in marital relationships over time, the effect size was negligible. This finding implies that baseline depressive symptoms alone may not be sufficient to predict future changes in relationship dynamics and that other factors, such as perceived partner support, coping mechanisms, or socioeconomic status, may play a moderating or mediating role [ 31 , 37 ]. Finally, the transition to parenthood often shifts attention from spousal interaction to infant care, which may reduce emotional communication between partners [ 13 ]. This shift can increase the emotional vulnerability of postpartum women, notably when relational support is lacking. Previous research has shown that insufficient partner involvement and communication during this period may exacerbate maternal distress and reduce marital satisfaction [ 1 , 15 ]. Nonetheless, women with higher levels of education generally demonstrate better coping mechanisms and adaptive strategies when managing depressive emotions and marital conflicts [ 34 ], underscoring the importance of targeted interventions for at-risk groups. Limitations This study employed a parallel latent growth model, and the model fit was generally acceptable based on the evaluation of various indicators. However, the model did not reach an optimal fit. One possible limitation is the absence of specific covariates that were not included in the study, such as maternal economic status, which may influence both depression and marital relationships. These missing factors could have impacted the construction of an optimal model. Additionally, the study had limitations related to sample size, as the number of participants was not sufficiently large. Future research should address these limitations by utilizing a larger sample size and incorporating additional covariates for a more comprehensive analysis. Conclusion The relationship between depression and marital quality among high-risk pregnant women in South Korea persists during the perinatal period, specifically from 24–32 weeks of pregnancy to 12 weeks postpartum. Notably, the initial level of depression during pregnancy plays a crucial role in later marital satisfaction. Therefore, we recommend that healthcare professionals conduct early depression screenings and interventions for high-risk pregnant women as early as possible during pregnancy. The transition to parenthood exerts a profound influence on the prevalence of depression and the dynamics of marital relationships. These women require more understanding and support to help them better adapt to their new maternal role and transition into this new life stage with a positive mindset. Their partners should pay greater attention to the emotional and relational needs of postpartum women, particularly those with high-risk pregnancies. The healthcare team should deliver multidimensional support to equip mothers and fathers for relationship transitions during the perinatal period and employ structured interventions to identify and address potential challenges effectively. Declarations All procedures were performed in compliance with the Helsinki Declaration and according to the relevant laws and institutional guidelines. Ethics approval and consent to participate This study was approved by the Institutional Review Board of Chungnam National University (No.202007-SB-094-01). Written informed consent was obtained from all participants prior to their enrollment in the study. Participant confidentiality and privacy were strictly maintained throughout the research process. Consent for publication Not applicable. Availability of data and materials The data that support the findings of this study are available from the corresponding author upon reasonable request. Competing interests The authors have no conflicts of interest to disclose. Funding This research received funding from the National Research Foundation of Korea (NRF No. 2020R1A2C201086511). Author ’s contributions FY: Formal analysis, Methodology, Writing – original draft, Writing – review & editing. LR: Conceptualization, Formal analysis, Methodology, Writing – original draft, Writing – review & editing.SA: Conceptualization, Data curation, Supervision, Writing – original draft, Writing – review & editing. Acknowledgements None. References Ahmad HA, Alkhatib A, Luo J. Prevalence and risk factors of postpartum depression in the Middle East: A systematic review and meta-analysis. BMC Pregnancy Childbirth. 2021;21:1–12. https://doi.org/10.1186/s12884-021-03613-4. Baldoni F, Giannotti M, Casu G, Luperini V, Spelzini F. A dyadic study on perceived stress and marital adjustment during pregnancy: The mediating role of depression. J Fam Issues. 2020;41(11):1935–1955. https://doi.org/10.1177/0192513X19898498. Baraldi AN, Enders CK. An introduction to modern missing data analyses. J Sch Psychol. 2010;48(1):5–37. https://doi.org/10.1016/j.jsp.2009.10.001. 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Korean J Women Health Nurs. 2021;27(4):326-336. https://doi.org/10.4069/kjwhn.2021.27.4.326. Yu M, Gong W, Taylor B, Cai Y, Xu D. Coping styles in pregnancy, their demographic and psychological influences, and their association with postpartum depression: A longitudinal study of women in China. Int J Environ Res Public Health. 2020;17(10):3654. https://doi.org/10.3390/ijerph17103654. Yu M, Li H, Xu DR, Wu Y, Liu H, Gong W. Trajectories of perinatal depression from early pregnancy to six weeks postpartum and their risk factors—a longitudinal study. J Affect Disord. 2020;275:149-156. https://doi.org/10.1016/j.jad.2020.06.005. Wallwiener S, Goetz M, Lanfer A, Gillessen A, Suling M, Feisst M, et al. Epidemiology of mental disorders during pregnancy and link to birth outcome: A large-scale retrospective observational database study including 38,000 pregnancies. Arch Gynecol Obstet. 2019;299:755-763. https://doi.org/10.1007/s00404-018-5022-5. Wang X, Zhang L, Lin X, Nian S, Wang X, Lu Y. Prevalence and risk factors of postpartum depression at 42 days among 2462 women in China. J Affect Disord. 2024;350:706-712. https://doi.org/10.1016/j.jad.2023.12.061. Wolf EJ, Harrington KM, Clark SL, Miller MW. Sample size requirements for structural equation models: An evaluation of power, bias, and solution propriety. Educ Psychol Meas. 2013;73(6):913-934. https://doi.org/10.1177/0013164413495237. Tables Table 1. Subjects’ Characteristics of Women with High-risk Pregnancies (N=157) Variables Category n(%) M±SD Maternal age (years) <35 44 (34.1) 35.91±3.81 ≥35 85 (65.9) Maternal education ≤High School 7 (5.4) ≥College 122 (94.6) Marital duration (years) 3.54±2.48 Planned pregnancy Yes 98 (76.0) No 31 (24.0) M±SD, mean±standard deviation Table 2. Descriptive Statistics and Correlation between Depression and Marital Relationships during Mid-pregnancy, 6-week Postpartum, and 12-week Postpartum (N=157) Variables Dep T1 Dep T2 Dep T3 MR T1 MR T2 MR T3 Dep T1 1 Dep T2 .258(.003) 1 Dep T3 .244(.005) .616(<.001) 1 MR T1 -.343(<.001) .012(.894) -.113(.200) 1 MR T2 -.183(.038) -.104(.241) -.174(.049) .775(<.001) 1 MR T3 -.235(.007) -.169(.056) -.326(<.001) .616(<.001) .716(<.001) 1 M(SD) 7.96(5.17) 10.62(6.38) 9.23(6.07) 38.46(6.64) 36.93(6.74) 35.35(7.88) Note. Dep = Depression, MR = Marital Relationship T1 indicates at mid-pregnancy; T2 at 6 weeks postpartum; T3 at 12 weeks postpartum. Table 3. Model Fit and Growth Trajectories of Depression and Marital Relationships: Unconditional and Nonlinear Unconditional Models. Variable CFI TLI RMSEA SRMR Intercept Mean/Var (p) Slope Mean/Var (p) Unconditional Latent Growth Models Depression 0.82 0.47 .384 .114 8.66(<.001)/ 14.80(.002) 0.59(.025)/ 0.72(.004) Marital relationships 1.00 1.00 <.001 .005 38.10(<.001)/ 41.11(<.001) -1.54(<.001)/ 3.52(.097) Nonlinear Unconditional Latent Growth Models Depression 1.00 1.00 <.001 <.001 8.14(<.001)/ 11.11(.045) 2.83(<.001)/ 15.24(.154) Marital relationships 1.00 1.00 <.001 <.001 38.07(<.001)/ 40.73(<.001) -1.44(<.001)/ 3.08(.135) Note. CFI = Comparative Fit Index; TLI = Tucker Lewis index; RMSEA = Root Mean Square Error of Approximation; SRMR = Standardized Rroot Mean Square Residual. Table 4. Multivariate Latent Growth Model Analysis between Depression and Marital Relationships of Women with High-risk Pregnancies during the Perinatal Period. χ² (p) CFI TLI RMSEA SRMR Depression M arital r elationships Intercept (I1) Slope (S1) Intercepts (I2) Slope (S2) Mean/Var (p) Mean/Var (p) Mean/Var (p) Mean/Var (p) 20.51 (.002) 0.97 0.92 0.12 0.04 8.12(<.001)/21.83(.001) 2.58(<.001)/ 23.73(<.001) 43.10(<.001)/ 36.51(<.001) -0.92(.203)/ 3.96(.151) Note. CFI = Comparative Fit Index; TLI = Tucker Lewis index; RMSEA = Root Mean Square Error of Approximation; SRMR = Standardized Rroot Mean Square Residual. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editor invited by journal 05 Aug, 2025 Reviewers agreed at journal 09 Jul, 2025 Reviewers invited by journal 09 Jul, 2025 Editor assigned by journal 29 May, 2025 Submission checks completed at journal 29 May, 2025 First submitted to journal 23 May, 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-6730714","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":482991036,"identity":"f40f5ad7-f417-41e4-939c-446df3907feb","order_by":0,"name":"FEIYAN YI","email":"","orcid":"","institution":"Chungnam National University","correspondingAuthor":false,"prefix":"","firstName":"FEIYAN","middleName":"","lastName":"YI","suffix":""},{"id":482991037,"identity":"1b110a8a-82bb-48aa-b7ce-ea9f6fbbe23a","order_by":1,"name":"Liping Ren","email":"","orcid":"","institution":"SHANDONG SECOND MEDIAL UNIVERSITY","correspondingAuthor":false,"prefix":"","firstName":"Liping","middleName":"","lastName":"Ren","suffix":""},{"id":482991038,"identity":"86ecb24d-e116-46f5-8f63-596b51009cd9","order_by":2,"name":"SUKHEE AHN","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA00lEQVRIiWNgGAWjYFACNjYQmcDA3gAV4CFaC88BkrVIJBCpRX5GWtqDDxV2eeaSj5895mGwk2fgOfsArxaDG2nHDWecSS62nJ1mbszDkGzYwNtugF+LRHqbNG8bc+KG2zls0jwMzAkM/GyEHAbU8vdffeKGm2dAWuoJa2G4kXZMmrHhcOKGGzwgLYcTGHjb8OswOPMsTbLn2PHEDWfSzCTnGBw3bOM5RsBh7WlmEj9qqhM3HD/8TOJNRbU8P08aAYehWQqMJ5I0jIJRMApGwSjACgBCkzzeHktyqQAAAABJRU5ErkJggg==","orcid":"","institution":"Chungnam National University","correspondingAuthor":true,"prefix":"","firstName":"SUKHEE","middleName":"","lastName":"AHN","suffix":""}],"badges":[],"createdAt":"2025-05-23 08:08:13","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6730714/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6730714/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":86524669,"identity":"139d735e-da76-45f4-93d8-30c68a170f68","added_by":"auto","created_at":"2025-07-11 15:38:46","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":54855,"visible":true,"origin":"","legend":"\u003cp\u003ePath coefficients of a parallel process latent growth model.\u003c/p\u003e\n\u003cp\u003eNote. Dep = Depression, MR = Marital Relationships\u003c/p\u003e\n\u003cp\u003eTime 1 indicates at mid-pregnancy; 2 at 6 weeks postpartum; 3 at 12 weeks postpartum.\u003c/p\u003e\n\u003cp\u003e**p\u0026lt;0.01, ***p\u0026lt;0.001\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-6730714/v1/4d1197ff107c8c0fbac06414.png"},{"id":86525309,"identity":"3b62f75a-aefd-4f1e-be81-61759e84b01c","added_by":"auto","created_at":"2025-07-11 15:46:51","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":722146,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6730714/v1/1d37530d-33db-418b-a177-63b84a32f52f.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The influence of perinatal depression on marital relationships in high-risk pregnant women: A parallel process latent growth model","fulltext":[{"header":"Background","content":"\u003cp\u003ePerinatal depression (PND) is a prevalent and serious public health problem [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] that negatively affects infant care and adjustment to the family-level adjustment [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Women with high-risk pregnancies are more likely than women with low-risk pregnancies to experience psychological distress about their own and their baby's health from the time of pregnancy through to the postpartum period. For example, mothers with gestational hypertension were 5 times more likely to be in the increased group of depression [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. The prevalence of perinatal depression among high-risk pregnant women has been reported as 39\u0026ndash;52% [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e], compared to 9\u0026ndash;32%% in low-risk pregnancies [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Even after experiencing a high-risk pregnancy, the risk of depression is even higher, as the burden of the baby's health risks adds to the stress of parenting [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eWhile mother-father relationship quality is one of the key factors in the adjustment to parenthood and the child's development [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e], many parents reported a decline in their couple's relationship during the postpartum period than during pregnancy [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Furthermore, parents suffering from stress and depression were more likely to feel inadequate spousal support and less satisfied with their relationship [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. In particular, maternal postpartum depression is a key factor that negatively affects marital satisfaction, leading to lower levels of parenting competence and infant attachment in mothers who had high-risk pregnancies [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Therefore, perinatal depression and marital satisfaction seem to be essential factors for a successful adjustment to parenthood in these mothers who had a high-risk pregnancy, so it is important to look at how postpartum depression affects marital satisfaction over time.\u003c/p\u003e\u003cp\u003ePregnancy and childbirth represent a critical period of psychological and relational adjustment for women. As women transition from mid to late pregnancy, they encounter challenges not only in preparing for their new parenting role but also in restructuring marital relationships to accommodate the arrival of a newborn and the evolving needs of the family [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. The transition to parenthood requires families to adjust to new family structures and functions for the overall family's well-being. Maternal depression during pregnancy and postpartum periods significantly influences women's ability to adapt to these changes, potentially impacting marital relationship quality [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Gaining insights into how individuals adjust during this period can help healthcare providers offer more tailored and practical support. However, these studies were mainly elucidated by providing cross-sectional data. There is a lack of a longitudinal description of maternal dynamics from pregnancy to postpartum regarding development and change.\u003c/p\u003e\u003cp\u003eLatent growth modeling is a useful statistical tool in developmental change research and has been successfully applied to studies of maternal depression for up to 8 years [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. These studies reported different development trajectories of depressive symptoms of women during the perinatal period: low stable, moderately stable, and increasing or decreasing patterns [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. The other study found that maternal depression trajectories over time had a significant negative impact on marital relationships within 8 years postpartum in mothers who had low-risk pregnancies [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Therefore, in describing the relationship between the level of maternal depression and marital relationship during the perinatal period using dynamics, latent growth modeling with longitudinal data is necessary.\u003c/p\u003e\u003cp\u003eThe purpose of this study was 1) to identify how maternal depression and marital relationships change from mid-pregnancy to 12 weeks postpartum and 2) to explore how these changes in depression continue to affect their marital relationships.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy Design and participants\u003c/h2\u003e\u003cp\u003eThis study utilized a longitudinal survey design to explore the change trajectories and their relationships between maternal depression and marital relationship from mid-pregnancy to 12 weeks postpartum in Korean women who had high-risk pregnancies.\u003c/p\u003e\u003cp\u003eWe recruited 157 pregnant women in South Korea who met the criteria for this study. The inclusion criteria for the study participants were pregnant women who were married and living with their husbands; pregnant women diagnosed with high-risk pregnancies, including 19 diagnoses designated by the National Health Insurance Service of Korea, such as preterm labor, premature rupture of membranes, and cervical incompetence; willing to participate in follow-up cohort study during three-time points of data collection: 24\u0026ndash;32 weeks of pregnancy (T1), 6 weeks postpartum(T2), and 12 weeks postpartum (T3). Exclusion Criteria were as follows: single mothers, women separated from their spouses, and their infants are admitted to the hospital at 6 weeks and 3 months postpartum so that childrearing has not yet started. Based on the complexity of modeling structural equations and the expected effect size, a minimum of 100 or 200 participants was required to obtain sufficient statistical power [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. A total of 157 valid data were obtained in this study.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eMeasurements\u003c/h3\u003e\n\u003cp\u003ePerinatal depression was measured by using the Korean version of the Edinburgh Postnatal Depression Scale (EPDS) [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. The EPDS consists of 10 self-reported questions on depression, anxiety and fear, guilt, and self-harm thoughts and is scored on a 4-point scale ranging from 0\u0026ndash;3, with a total score ranging from 0\u0026ndash;30. Cox et al. reported the tool's reliability at the time of development as Cronbach's α\u0026thinsp;=\u0026thinsp;.87. In this study, it was .84, .88, and .89 at three measurement time points.\u003c/p\u003e\u003cp\u003eThe marital relationship was measured by using the simplified Korean version of DAS-10 [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] based on 32 questions of the Dyadic Adjustment Scale (DAS) [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Questions 1\u0026ndash;9 are on a 5-point scale, including marital conflicts, satisfaction, and cohesion. Finally, question 10 is based on a 6-point scale regarding plans or resolutions for future marital life. The higher the score, the higher the marital relationships. The reliability of this Korean version is Cronbach's alpha=. 83. In this study, it was .87, .84, and .86 at 3 measurement time points.\u003c/p\u003e\u003cp\u003eCharacteristics include maternal age, education, marital duration, and planned pregnancy.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eEthical approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll procedures were performed in compliance with the Helsinki Declaration and according to the relevant laws and institutional guidelines.\u0026nbsp;This study was approved by the Institutional Review Board of XX University (N202007-SB-094-01).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData were analyzed using SPSS 29.0 for reliability, descriptive, and correlation analysis. We used the Mplus 8.3 version for latent growth modeling (LGM) and simultaneously analyzed the potential growth trajectories of these two variables. To address the issue of missing values in data, the maximum likelihood (ML) method is first used to process the missing data on SPSS data to maximize the utilization of all available data to handle missing values [3]. Two potential factors were evaluated, one indicating the initial values of depression and marital relationships (i.e., intercept) and the other indicating the changes in these variables over time (i.e., slope). First, two separate univariate latent growth models (LGMs) were conducted for depression and marital relationship, respectively. In each model, intercept factors were fixed at loadings of 1, and residual variances of observed variables were freely estimated. For slope factors, we examined two alternative specifications: fixed slope loadings of (0, 1, 2), indicative of linear change, and partially fixed slope loadings of (0, 1, *), consistent with a latent nonlinear growth model. The model fit indices and parameter stability of these two approaches were compared to select the optimal parameterization [14, 30]. And unconditional parallel process models were tested to determine the effect of the initial level of perinatal depression to on the initial level of marital relationships, as well as the effect of change in perinatal depression on change in marital relationships. A bootstrap procedure was used to test and validate a final model\u0026apos;s statistical significance of the path and indirect effects. Model fit was assessed by comparing the fit index (CFI), Tucker Lewis index (TLI), root mean square error of approximation (RMSEA), and standardized root mean square residual (SRMR), following the growth model criteria. Model fit was considered good when CFI \u0026nbsp;and TLI \u0026ge; 0.90, RMSEA \u0026le; 0.10, and SRMR \u0026le; 0.08 [19].\u0026nbsp;\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eParticipant Demographics\u003c/strong\u003e\u003c/p\u003e\u003cp\u003eThe average age of high-risk pregnant women was 35.91 years old, with 85 (65.9%) over 35 years old, 122 (94.6%) a college graduate and above, and the average length of marriage was 3.54 years. Most (76.0%) had a planned pregnancy (Table\u0026nbsp;1).\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eDescriptive statistics and correlation\u003c/strong\u003e\u003c/p\u003e\u003cp\u003eMaternal depression levels increased from 7.96 ± 5.17 during mid-pregnancy (T1) to 10.62 ± 6.38 at 6 weeks postpartum (T2) and slightly decreased to 9.23 ± 6.07 at 12 weeks postpartum (T3). The level of marital relationship showed a slight decline over time, starting at 38.46 ± 6.64 during mid-pregnancy, decreasing to 36.93 ± 6.74 at 6 weeks postpartum, and further dropping to 35.35 ± 7.88 at 12 weeks postpartum.\u003c/p\u003e\u003cp\u003eThe association of depression with marital relationship at mid-pregnancy, 6 weeks postpartum, and 12 weeks postpartum were found. Significant positive correlations were found among depression (r = 0.24 to 0.61, \u003cem\u003ep\u003c/em\u003e \u0026lt; .05) and among marital relationships (r = 0.61 to 0.77, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001) over time. Several negative correlations were found between perinatal depression and marital relationships over time (r = -0.17 to -0.32, \u003cem\u003ep\u003c/em\u003e \u0026lt; .05) over time (Table\u0026nbsp;2).\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eUnivariate growth models\u003c/strong\u003e\u003c/p\u003e\u003cp\u003e To determine whether the changes in maternal depression and marital relationship followed linear or nonlinear trajectories during the perinatal period, we fitted two unconditional latent growth models for each variable: a linear model with fixed slope loadings (0, 1, 2) and a nonlinear latent basis model with partially fixed loadings (0, 1, *). Model fit indices indicated that the nonlinear unconditional latent growth model better fit the data compared to the linear model (Table\u0026nbsp;3).\u003c/p\u003e\u003cp\u003eIn the nonlinear unconditional growth model for maternal depression, the estimated mean of the intercept, representing the initial level of depression, was 8.14 (\u003cem\u003ep\u003c/em\u003e \u0026lt; .001), significantly greater than zero. Maternal depression showed a significant increase over the three measurement occasions (slope = 2.83, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001). The intercept variance (σ² = 11.11, \u003cem\u003ep\u003c/em\u003e = .045) and the slope variance (σ² = 15.24, \u003cem\u003ep\u003c/em\u003e = .154) indicated substantial interindividual variability in baseline levels of maternal depression. However, variability in rates of change over time was not statistically significant between individuals. Furthermore, a positive correlation was observed between the intercept and slope (r = .30, \u003cem\u003ep\u003c/em\u003e = .624), suggesting that women with higher initial levels of maternal depression experienced more rapid increases in depression over time.\u003c/p\u003e\u003cp\u003eIn the nonlinear unconditional growth model for marital relationships, the estimated mean of the intercept was 38.07 (\u003cem\u003ep\u003c/em\u003e \u0026lt; .001), indicating that, on average, participants initially reported high levels of perceived relationship quality with their partners. The slope was negative and statistically significant (-1.44, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001), suggesting a steady decline in marital relationships over the three measurement occasions. Significant variance in the intercept (σ² = 40.73, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001) indicated considerable individual differences in initial relationship quality. In contrast, the variance in the slope (σ² = 3.08, \u003cem\u003ep\u003c/em\u003e = .135) was not statistically significant, reflecting limited variation in trajectories of change. A negative correlation was also found between the intercept and slope (r = − .20, \u003cem\u003ep\u003c/em\u003e = .211), indicating that participants who initially reported higher levels of marital relationship tended to experience a steeper decline over time.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eParallel process latent growth model for depression and marital relationships\u003c/strong\u003e\u003c/p\u003e\u003cp\u003eThis study established a parallel process latent growth model to examine the direct effects of depression's initial level on marital relationships and to explore the co-varying trajectories of these two variables. The model fit results were as follows: χ² = 20.51 (\u003cem\u003ep\u003c/em\u003e = .002), CFI = 0.97, TLI = 0.92, RMSEA = 0.12, SRMR = 0.04, indicating that the model's overall fit was good (Table\u0026nbsp;4).\u003c/p\u003e\u003cp\u003eIn a parallel process latent growth model examining depression and marital relationships among older adults, the intercept of depression was a significant predictor of the intercept of marital relationships (β = -0.43, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001). This finding indicates that participants with lower initial levels of depression tended to have higher initial levels of marital relationships. Additionally, the intercept of depression showed a negative association with the slope (rate of change) of marital relationships (β = -0.002, \u003cem\u003ep\u003c/em\u003e = .998). Although not statistically significant, the direction of this effect suggests that participants with lower baseline depression tended to experience a faster increase in marital relationships over time. Finally, the slope of depression was negatively associated with the slope of marital relationship (β = -0.54, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001). This significant negative association indicates that the faster the decline in depression over time, the faster the increase in marital relationships. In other words, women who showed a more rapid reduction in depression symptoms tended to exhibit correspondingly faster growth in their marital relationships (Fig.\u0026nbsp;1).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe findings of this study indicate that among high-risk pregnant women in South Korea who participated in the study, more than 50% were of advanced maternal age (\u0026gt; 35 years), and less than a quarter experienced unintended pregnancies.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eChange trajectories of maternal depression and marital relationships\u003c/strong\u003e\u003c/p\u003e\u003cp\u003eMaternal depression levels at mid-pregnancy (T1) had a mean score of 7.96, indicating that most mothers were below the depression risk threshold of 10 on the EPDS scores. However, at 6 weeks postpartum (T2), the mean score increased to 10.62, crossing the threshold and suggesting an elevated risk of depression during this period. By 12 weeks postpartum (T3), the mean score slightly decreased to 9.23, falling below the cut point but still reflecting higher levels than during pregnancy. Mothers who have given birth following high-risk pregnancies—resulting in preterm infants, low-birth-weight babies, or infants with health concerns, temperamental difficulties, or other issues—often feel a lack of parenting confidence. This, in turn, contributes to heightened parenting stress and an increased risk of postpartum depression [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. It is crucial to assess the risk of postpartum depression among mothers who visit hospitals for postpartum health check-ups within six weeks after delivery.\u003c/p\u003e\u003cp\u003eMoreover, there is a need to implement interventions aimed at addressing and mitigating depression in these individuals while providing a holistic approach to understanding women and their high-risk journey. Additionally, mothers who have undergone high-risk pregnancies often go through a range of emotional and psychological experiences and remain concerned about their own and their infant’s health and well-being after birth [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Therefore, providing comprehensive health evaluations and precise and detailed information is paramount. Since maternal depression levels often do not return to pre-pregnancy levels even at 12 weeks postpartum, it is essential to implement both short-term and medium-term strategies. These strategies should include informational support, emotional counseling, and advisory services, such as phone consultations or open chat platforms, throughout the perinatal period to address maternal health and infant care issues [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe marital relationships of the study participants showed a declining trend as time progressed postpartum, compared to the levels observed during pregnancy. This aligns with previous research asserting that the transition to parenthood often leads to weakened marital relationships due to physical challenges, the burden of acquiring new roles, shifts in family priorities, and a lack of shared time between spouses [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Mothers who have undergone the challenging process from high-risk pregnancies to childbirth often experience a weakening of the marital bond during the transition to motherhood. This transition highlights the potential instability in the relationship, which was initially strengthened by shared expectations of a healthy delivery and the birth of their babies during pregnancy, suggesting an increased risk of relationship discord during the postpartum period [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Particularly following high-risk pregnancies, mothers who spend significant time and effort caring for themselves and their children postpartum may experience physical and mental exhaustion. If they perceive insufficient support from their spouse, this can lead to emotional distancing in the marital relationship and, consequently, a decline in marital satisfaction [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eParallel Trajectories of Perinatal Depression and Marital Relationship\u003c/strong\u003e\u003c/p\u003e\u003cp\u003eThis study investigated the parallel development of perinatal depression and marital relationship quality among high-risk pregnant women in South Korea using a parallel process latent growth model. The findings revealed a significant negative association between the initial levels of depression and marital relationship quality. Specifically, during the initial stage of pregnancy (gestational weeks 24–32), women who reported higher levels of depressive symptoms also tended to report lower levels of marital satisfaction (β = -0.43). This result is consistent with previous studies indicating that antenatal depression can undermine emotional connection and perceived partner support during pregnancy [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. This may be related to the inability of partners or husbands to provide sufficient security and emotional support to women experiencing high-risk pregnancies. In marital relationships, mutual dependence and trust between partners contribute to a healthy psychological state, which serves as a protective factor against anxiety and depression in women [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eFurthermore, the results revealed a significant negative association between the slopes of depression and marital relationship quality (β = -0.54), suggesting that a faster decline in depressive symptoms over time was associated with a more rapid improvement in marital relationships. This finding aligns with previous research showing that maternal emotional recovery is often accompanied by improved interpersonal functioning and relational well-being [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. In this study, women who exhibited a more pronounced reduction in depression from mid-pregnancy through the postpartum period also tended to experience strengthening of their marital bonds. These results highlight the dynamic interplay between psychological health and relational outcomes during the perinatal period.\u003c/p\u003e\u003cp\u003eHowever, the effect of the initial level of depression on the rate of change in marital relationship quality was not statistically significant (β = -0.002, \u003cem\u003ep\u003c/em\u003e = .998). While the direction of the association suggests that women with lower initial depression levels may experience slightly more significant improvements in marital relationships over time, the effect size was negligible. This finding implies that baseline depressive symptoms alone may not be sufficient to predict future changes in relationship dynamics and that other factors, such as perceived partner support, coping mechanisms, or socioeconomic status, may play a moderating or mediating role [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eFinally, the transition to parenthood often shifts attention from spousal interaction to infant care, which may reduce emotional communication between partners [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. This shift can increase the emotional vulnerability of postpartum women, notably when relational support is lacking. Previous research has shown that insufficient partner involvement and communication during this period may exacerbate maternal distress and reduce marital satisfaction [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Nonetheless, women with higher levels of education generally demonstrate better coping mechanisms and adaptive strategies when managing depressive emotions and marital conflicts [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e], underscoring the importance of targeted interventions for at-risk groups.\u003c/p\u003e\n\u003ch3\u003eLimitations\u003c/h3\u003e\n\u003cp\u003eThis study employed a parallel latent growth model, and the model fit was generally acceptable based on the evaluation of various indicators. However, the model did not reach an optimal fit. One possible limitation is the absence of specific covariates that were not included in the study, such as maternal economic status, which may influence both depression and marital relationships. These missing factors could have impacted the construction of an optimal model. Additionally, the study had limitations related to sample size, as the number of participants was not sufficiently large. Future research should address these limitations by utilizing a larger sample size and incorporating additional covariates for a more comprehensive analysis.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe relationship between depression and marital quality among high-risk pregnant women in South Korea persists during the perinatal period, specifically from 24–32 weeks of pregnancy to 12 weeks postpartum. Notably, the initial level of depression during pregnancy plays a crucial role in later marital satisfaction. Therefore, we recommend that healthcare professionals conduct early depression screenings and interventions for high-risk pregnant women as early as possible during pregnancy. The transition to parenthood exerts a profound influence on the prevalence of depression and the dynamics of marital relationships. These women require more understanding and support to help them better adapt to their new maternal role and transition into this new life stage with a positive mindset. Their partners should pay greater attention to the emotional and relational needs of postpartum women, particularly those with high-risk pregnancies. The healthcare team should deliver multidimensional support to equip mothers and fathers for relationship transitions during the perinatal period and employ structured interventions to identify and address potential challenges effectively.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eAll procedures were performed in compliance with the Helsinki Declaration and according to the relevant laws and institutional guidelines.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by\u0026nbsp;the Institutional Review Board of Chungnam National University\u0026nbsp;(No.202007-SB-094-01). Written informed consent was obtained from all participants prior to their enrollment in the study. Participant confidentiality and privacy were strictly maintained throughout the research process.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data that support the findings of this study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no conflicts of interest to disclose.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research received funding from the National Research Foundation of Korea (NRF No. 2020R1A2C201086511).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor\u003c/strong\u003e\u003cstrong\u003e’s\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFY: Formal analysis, Methodology, Writing – original draft, Writing – review \u0026amp; editing. LR: Conceptualization, Formal analysis, Methodology, Writing – original draft, Writing – review \u0026amp; editing.SA: Conceptualization, Data curation, Supervision, Writing – original draft, Writing – review \u0026amp; editing.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAhmad HA, Alkhatib A, Luo J. Prevalence and risk factors of postpartum depression in the Middle East: A systematic review and meta-analysis. BMC Pregnancy Childbirth. 2021;21:1–12. https://doi.org/10.1186/s12884-021-03613-4.\u003c/li\u003e\n\u003cli\u003eBaldoni F, Giannotti M, Casu G, Luperini V, Spelzini F. A dyadic study on perceived stress and marital adjustment during pregnancy: The mediating role of depression. J Fam Issues. 2020;41(11):1935–1955. https://doi.org/10.1177/0192513X19898498.\u003c/li\u003e\n\u003cli\u003eBaraldi AN, Enders CK. 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Educ Psychol Meas. 2013;73(6):913-934. https://doi.org/10.1177/0013164413495237.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1. Subjects’ Characteristics of Women with High-risk Pregnancies (N=157)\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"579\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCategory\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003en(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eM±SD\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eMaternal age (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;35 \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e44 (34.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e35.91±3.81\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e≥35 \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e85 (65.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eMaternal education\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e≤High School \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7 (5.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e≥College \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e122 (94.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMarital duration (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.54±2.48\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003ePlanned pregnancy \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e98 (76.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e31 (24.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eM±SD, mean±standard deviation\u003c/p\u003e\n\u003cp\u003eTable 2. Descriptive Statistics and Correlation between Depression and Marital Relationships during Mid-pregnancy, 6-week Postpartum, and 12-week Postpartum (N=157)\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"671\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDep T1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDep T2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDep T3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMR T1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMR T2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMR T3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDep T1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDep T2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.258(.003)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDep T3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.244(.005)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.616(\u0026lt;.001)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMR T1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-.343(\u0026lt;.001)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.012(.894)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-.113(.200)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMR T2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-.183(.038)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-.104(.241)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-.174(.049)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.775(\u0026lt;.001)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMR T3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-.235(.007)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-.169(.056)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-.326(\u0026lt;.001)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.616(\u0026lt;.001)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.716(\u0026lt;.001)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eM(SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7.96(5.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e10.62(6.38)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e9.23(6.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e38.46(6.64)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e36.93(6.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e35.35(7.88)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote. Dep = Depression, MR = Marital Relationship\u003c/p\u003e\n\u003cp\u003eT1 indicates at mid-pregnancy; T2 at 6 weeks postpartum; T3 at 12 weeks postpartum.\u003c/p\u003e\n\u003cp\u003eTable 3. Model Fit and Growth Trajectories of Depression and Marital Relationships: Unconditional and Nonlinear Unconditional Models.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCFI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eTLI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eRMSEA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eSRMR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eIntercept\u003c/p\u003e\n \u003cp\u003eMean/Var (p)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003eSlope\u003c/p\u003e\n \u003cp\u003eMean/Var (p)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"13\" valign=\"top\"\u003e\n \u003cp\u003eUnconditional Latent Growth Models\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDepression\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e0.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e.384\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e.114\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e8.66(\u0026lt;.001)/\u003c/p\u003e\n \u003cp\u003e14.80(.002)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e0.59(.025)/\u003c/p\u003e\n \u003cp\u003e0.72(.004)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMarital relationships\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e38.10(\u0026lt;.001)/\u003c/p\u003e\n \u003cp\u003e41.11(\u0026lt;.001)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e-1.54(\u0026lt;.001)/\u003c/p\u003e\n \u003cp\u003e3.52(.097)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"12\" valign=\"top\"\u003e\n \u003cp\u003eNonlinear Unconditional Latent Growth Models\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDepression\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e8.14(\u0026lt;.001)/\u003c/p\u003e\n \u003cp\u003e11.11(.045)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.83(\u0026lt;.001)/\u003c/p\u003e\n \u003cp\u003e15.24(.154)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMarital relationships\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e38.07(\u0026lt;.001)/\u003c/p\u003e\n \u003cp\u003e40.73(\u0026lt;.001)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-1.44(\u0026lt;.001)/\u003c/p\u003e\n \u003cp\u003e3.08(.135)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote. CFI = Comparative Fit Index; TLI = Tucker Lewis index; RMSEA = Root Mean Square Error of Approximation; SRMR = Standardized Rroot Mean Square Residual.\u003c/p\u003e\n\u003cp\u003eTable 4. Multivariate Latent Growth Model Analysis between Depression and Marital Relationships of Women with High-risk Pregnancies during the Perinatal Period. \u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"690\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003eχ²\u003c/p\u003e\n \u003cp\u003e(p)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003eCFI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003eTLI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003eRMSEA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003eSRMR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cu\u003eDepression\u003c/u\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cu\u003eM\u003c/u\u003e\u003cu\u003earital\u003c/u\u003e\u003cu\u003e \u003c/u\u003e\u003cu\u003er\u003c/u\u003e\u003cu\u003eelationships\u003c/u\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eIntercept\u003c/p\u003e\n \u003cp\u003e(I1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSlope\u003c/p\u003e\n \u003cp\u003e(S1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eIntercepts\u003c/p\u003e\n \u003cp\u003e(I2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSlope\u003c/p\u003e\n \u003cp\u003e(S2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMean/Var (p)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMean/Var (p)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMean/Var (p)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMean/Var (p)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e20.51\u003c/p\u003e\n \u003cp\u003e(.002)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8.12(\u0026lt;.001)/21.83(.001)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.58(\u0026lt;.001)/\u003c/p\u003e\n \u003cp\u003e23.73(\u0026lt;.001)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e43.10(\u0026lt;.001)/\u003c/p\u003e\n \u003cp\u003e36.51(\u0026lt;.001)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.92(.203)/\u003c/p\u003e\n \u003cp\u003e3.96(.151)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote. CFI = Comparative Fit Index; TLI = Tucker Lewis index; RMSEA = Root Mean Square Error of Approximation; SRMR = Standardized Rroot Mean Square Residual.\u003c/p\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":"High-risk Pregnant Women, Parallel Process Latent Growth Model, Perinatal Depression, Perinatal Marital Relationships","lastPublishedDoi":"10.21203/rs.3.rs-6730714/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6730714/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003ePerinatal depression and marital satisfaction are key factors in pregnant women's successful adaptation to parenthood and the maternal role. However, most existing studies have primarily used cross-sectional data to explain the relationship between depression and marital satisfaction, lacking a longitudinal perspective to capture their dynamic changes from pregnancy through the postpartum period.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eTherefore, this study aimed to explore how depressive symptoms over time influence marital satisfaction in 157 high-risk perinatal women in South Korea, using a parallel latent growth model. Depression levels were assessed at 24\u0026ndash;32 weeks of gestation (T1), 6 weeks postpartum (T2), and 12 weeks postpartum (T3).\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eThe results showed a significant negative correlation between depression and marital satisfaction (r = -0.17 to -0.32, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.05). The parallel latent growth model revealed that a faster decrease in depressive symptoms was associated with greater improvements in marital satisfaction (β = -0.54, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001). Although baseline depression did not significantly predict initial marital satisfaction, its declining trend over time was meaningful.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eThese findings highlight the importance of early depression screening and timely intervention during pregnancy, particularly for high-risk women, to support their maternal role adaptation and facilitate a positive transition into this new life stage.\u003c/p\u003e","manuscriptTitle":"The influence of perinatal depression on marital relationships in high-risk pregnant women: A parallel process latent growth model","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-11 15:38:31","doi":"10.21203/rs.3.rs-6730714/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvited","content":"","date":"2025-08-05T17:40:57+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"114902117320215423886427978947296301948","date":"2025-07-09T13:41:39+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-07-09T07:14:24+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-05-29T11:09:41+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-05-29T11:07:17+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Pregnancy and Childbirth","date":"2025-05-23T07:56:11+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":"80042d7a-9652-473c-b385-d3907479b100","owner":[],"postedDate":"July 11th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-07-11T15:38:31+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-11 15:38:31","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6730714","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6730714","identity":"rs-6730714","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}