Abstract
Background
Postpartum depression (PPD) and postpartum anxiety (PPA) are common perinatal mental disorders affecting maternal and infant health. However, the epidemiological characteristics and risk factors of PPD, PPA, and the comorbidity of both disorders remain inadequately investigated.
Methods
The cohort of this cross-sectional study included 2,152 postpartum women. The Patient Health Questionnaire-9 (PHQ-9), Edinburgh Postnatal Depression Scale (EPDS), and Generalized Anxiety Disorder-7 were used to assess symptoms of PPD and PPA.
Results
The self-reported point prevalence rates of PPD, PPA, and their comorbidity were 12.9%, 20.8%, and 9.4%, respectively. Among the participants, 12.9% and 8.4% experienced moderate-to-severe symptoms of PPD and PPA, respectively. Spearman’s correlation analysis revealed a correlation between the total PHQ-9 and EPDS scores (r = 0.404, p < 0.001). Sleep duration < 6 h was associated with increased risks of symptoms of PPD (RR = 1.862, p < 0.001), while sleep duration > 8 h was a protective factor for PPA symptoms (RR = 0.795, p = 0.024). A low annual household income was significantly correlated with higher risks for symptoms of PPD (RR = 3.369, p < 0.001) and PPA (RR = 2.148, p < 0.001).
Conclusion
This study revealed high prevalence rates of PPD and PPA, with frequent comorbidity. These findings suggest the importance of combined screening of women for both PPD and PPA, with particular attention to sleep quality and economic status.
Keywords: Postpartum depression, Postpartum anxiety, Comorbidity, Prevalence, Risk factors
Introduction
Depression and anxiety are among the most common mental health disorders globally. According to the World Health Organization, approximately 280 million people worldwide suffer from depression and 260 million from anxiety disorders [1]. Depression and anxiety disorders rank first and second, respectively, in terms of disability-adjusted life years among mental disorders, thereby imposing a substantial economic burden globally [2]. The postpartum period represents a high-risk phase for depression and anxiety among women [3]. The comorbidity of postpartum depression (PPD) and anxiety is increasingly recognized, often resulting in more severe symptoms and greater treatment complexity [4, 5]. Studies have demonstrated that the prevalence of postpartum depression varies considerably across countries, ranging from 5% to 25%, with even higher rates reported in low- and middle-income countries [6–8]. The prevalence of postpartum anxiety (PPA) is equally significant, affecting approximately 6% to 26% of mothers globally [5, 7, 9]. A recent study conducted in Shanghai, China, reported prevalence rates for PPD and PPA of 23.2% and 15.2%, respectively [10]. PPD not only affects maternal physical and mental health but also has long-term negative impacts on infant cognitive development, emotional attachment, and behavioral outcomes [11–13]. Additionally, PPA may lead to excessive maternal worry and reduced sleep quality, compromising breastfeeding practices and childcare quality [14]. Evidence suggests that early detection and intervention of postpartum mental health issues are crucial for both maternal and infant well-being [15, 16].
Previous studies have identified multiple risk factors associated with PPD and PPA, including biological factors (such as hormonal changes and sleep quality), psychological factors (such as prenatal mental state and stress coping ability), and social factors (such as economic status and social support) [13, 17–19]. However, the manifestation of these risk factors varies substantially across different ethnic groups, regions, and periods [20–22]. Against the backdrop of rapid social development and cultural transformation [23], the risk factors affecting postpartum women continue to evolve. Conducting new epidemiological surveys in specific populations and regions is essential not only to understand the current prevalence of PPD and PPA but also to provide evidence for developing targeted preventive measures.
Based on these considerations, this study aims to investigate the prevalence of PPD and PPA and identify potential influencing factors. This investigation encompasses multiple dimensions, including demographic characteristics (such as age and residential area), obstetric variables (such as parity), physical conditions (such as sleep quality and comorbidities), and socioeconomic parameters. We hypothesize that these elements influence maternal psychological well-being through different pathways, with some variables potentially contributing to both PPD and PPA. The findings derived from this study will help identify key determinants of postpartum mental health conditions, thereby providing evidence for developing targeted preventive and intervention strategies to improve the psychological well-being of postpartum women. This study was conducted in Lianyungang, a developing coastal city in eastern China, during 2023–2024. Unlike previous studies predominantly conducted in first-tier cities, our research provides epidemiological evidence from an understudied region and is the first in this area to employ dual screening tools for PPD validation.
Methods and subjects
Procedures and subjects
A cross-sectional survey was conducted from October 2023 to October 2024 in Lianyungang, Jiangsu Province, China. Data were collected through an online questionnaire distributed via the Wenjuanxing platform (https://www.wjx.cn/app/survey.aspx). A QR code for the questionnaire was disseminated to healthcare institutions across six administrative districts in Lianyungang, targeting women within 6 weeks postpartum. Inclusion criteria included the ability to understand the questionnaire content and voluntary participation, and completion of the questionnaire via online platform. Exclusion criteria included incomplete questionnaire information (missing key information such as age, address, or health status), history of diagnosed psychiatric disorders with ongoing treatment, severe obstetric complications requiring hospitalization, and inability to complete the questionnaire independently. Participation in the study was voluntary. All participants were informed about the purpose, content, and procedures of the study, with confidentiality assured for all collected data. Participants had the option to withdraw from the survey at any point, and informed consent was obtained online. The study protocol was approved by the Ethics Committee of the Fourth People’s Hospital of Lianyungang.
A total of 2,425 postpartum women participated in the survey. Due to incomplete information, such as missing age, address, or health status, 273 participants were excluded, resulting in a final sample size of 2,152 women included in the study. A flowchart of the participant selection process is presented in Fig. 1.
Fig. 1.
Flow chart of the participant selection process
Socio-demographic information
The authors designed a semi-structured sociodemographic questionnaire that included the following elements: age, living region (urban/suburban), parity (primiparous/multiparous), presence of somatic diseases (yes/no), and sleep duration (< 6 h/6–8 h/> 8 h). Somatic diseases/complications refer to prenatal complications, including gestational hypertension, gestational diabetes mellitus, thyroid disorders, postpartum hemorrhage, and puerperal infections, which participants could report by referring to their prenatal examination records or medical history. Annual household income was categorized into four levels: >200,000 RMB as “high,” 100,000–200,000 RMB as “above average,” 60,000–100,000 RMB as “average,” and < 60,000 RMB as “low.”
Patient Health Questionnaire-9 (PHQ-9)
The PHQ-9 was used to assess symptoms of PPD [24]. The PHQ-9 is a widely used self-reporting tool designed to screen for the presence and severity of depression symptoms that comprises nine items, each aligning with the nine diagnostic criteria for major depression as outlined in the fourth edition of the Diagnostic and Statistical Manual of Mental Disorders. Participants evaluated their emotions and symptoms over the past two weeks using a 4-point Likert scale, where 0 = “not at all”, 1 = “several days”, 2 = “more than half the days”, and 3 = “nearly every day”. The total score ranged from 0 to 27, with higher scores indicating more severe PPD symptoms. In this study, a score of ≥ 10 was considered to reflect the presence of PPD symptoms, while a score < 10 suggested the absence of such symptoms [25]. The severity of PPD was further categorized as mild (score, 5–9), moderate (score, 10–14), or severe (score, ≥ 15). The PHQ-9 has been validated for good reliability and validity in the Chinese population and various fields [25, 26], including screening of PPD [27].
Edinburgh postnatal depression scale (EPDS)
The EPDS was utilized to assess symptoms of PPD [28]. The EPDS is a self-reporting tool consisting of 10 items, each primarily focusing on postpartum emotional states, including but not limited to sadness, self-blame, anxiety, and sleep disturbances. Participants rated each item based on their feelings over the past week using a 4-point scale, where 0 = “never”, 1 = “sometimes”, 2 = “often”, and 3 = “almost always” [29]. The total score ranged from 0 to 30. The EPDS has good reliability and validity in the Chinese population [30].
Generalized Anxiety Disorder scale (GAD-7)
The GAD-7 was used to assess symptoms of PPA. The GAD-7 is a brief self-reporting tool designed to screen for generalized anxiety disorder and evaluate the severity of symptoms [31]. The scale consisted of 7 items, primarily assessing PPA symptoms experienced over the past two weeks. Each item described a common PPA symptom and the participants rated each item based on how they felt over the past two weeks using a 4-point scale, where 0 = “not at all”, 1 = “several days”, 2 = “more than half the days”, and 3 = “nearly every day”. The total score ranged from 0 to 21. PPA severity was categorized a mild (score, 5–9), moderate (score, 10–14), or severe (score, ≥ 15). Total scores of ≥ 7 and < 7 indicated the presence and absence of PPA symptoms, respectively [32]. The GAD-7 showed good reliability and validity in the Chinese population [33].
Since both PHQ-9 and GAD-7 assess symptoms over the two weeks preceding survey completion, the prevalence rates reported in this study represent point prevalence. The PHQ-9 was designated as the primary measure for assessing PPD, and the EPDS was included as a supplementary validation tool.
Statistical analysis
Statistical analysis was conducted using IBM SPSS Statistics for Windows (version 23.0; IBM Corporation, Armonk, NY, USA). The required sample size was calculated using G*Power 3.1 software (https://www.psychologie.hhu.de/arbeitsgruppen/allgemeine-psychologie-und-arbeitspsychologie/gpower). Comprehensive exploratory analysis of the descriptive data was performed, which included the mean, median, standard deviation (SD), minimum values, and maximum values. For continuous variables, an independent samples t-test was used to compare mean differences between groups. For categorical variables, the chi-square test was used to examine the distribution differences between groups. Spearman’s correlation analysis was used to assess the correlation between the PHQ-9 and EPDS scores. The presence or absence of PPD or PPA symptoms was treated as a binary variable, and the modified Poisson regression model was employed to analyze potential risk factors associated with these symptoms. A two-tailed probability (p) value < 0.05 was considered statistically significant.
Results
Sociodemographic characteristic of participants
The mean age of the participants was 30.10 ± 4.53 (range, 18–42) years. The average total EPDS score was 8.28 ± 5.17. Among the participants, 62.2% lived in urban areas, while 37.8% resided in suburban areas. Regarding parity, 48% of the women were primiparous, while 52% had two or more children. Additionally, 79 participants had comorbid somatic diseases. The proportions of individuals with sleep durations of < 6, 6–8 h, and > 8 h were 44.2%, 33.4%, and 22.4%, respectively. In regard to annual household income, 11.3% were classified as high, 14.5% as above average, 71.2% as average, and 3.0% as low (Table 1).
Table 1.
Sociodemographic and clinical characteristics of postpartum women (N = 2152)
| PPD symptoms | PPA symptoms | |||||
|---|---|---|---|---|---|---|
| With (n = 278) | Without (n = 1874) | p | With (n = 448) | Without (n = 1704) | p | |
| Age (years), mean (SD) | 29.92 (4.75) | 30.13 (4.50) | 0.482a | 29.64 (4.53) | 30.23 (4.53) | 0.014a |
| EPDS, mean (SD) | 13.87 (4.99) | 7.45 (4.66) | < 0.001a | 12.50 (4.83) | 7.17 (4.67) | < 0.001a |
| Region, n (%) | 0.892b | 0.067b | ||||
| Urban | 104 (12.8) | 709 (87.2) | 262 (19.6) | 1077 (80.4) | ||
| Suburban | 174 (13.0) | 1165 (87.0) | 186 (22.9) | 627 (77.1) | ||
| Parity, n (%) | 0.670b | 0.447b | ||||
| Primiparous | 130 (12.6) | 902 (87.4) | 222 (21.5) | 810 (78.5) | ||
| Multiparous | 148 (13.2) | 972 (86.8) | 226 (20.2) | 894 (79.8) | ||
| Complications, n (%) | 0.195b | 0.003b | ||||
| Yes | 14 (17.7) | 65 (82.3) | 27 (34.2) | 52 (65.8) | ||
| No | 264 (12.7) | 1809 (87.3) | 421 (20.3) | 1652 (79.7) | ||
| Sleep duration, n (%) | < 0.001b | < 0.001b | ||||
| < 6 h | 95 (19.7) | 387 (80.3) | 135 (28.0) | 347 (72.0) | ||
| 6–8 h | 106 (11.1) | 846 (88.9) | 202 (21.2) | 750 (78.8) | ||
| > 8 h | 77 (10.7) | 641 (89.3) | 111 (15.5) | 607 (84.5) | ||
| Annual household income, n (%) | < 0.001b | < 0.001b | ||||
| High | 22 (9.0) | 222 (91.0) | 34 (13.9) | 210 (86.1) | ||
| Above average | 23 (7.4) | 289 (92.6) | 40 (12.8) | 272 (87.2) | ||
| Average | 212 (13.8) | 1320 (86.2) | 347 (22.7) | 1185 (77.3) | ||
| Low | 21 (32.8) | 43 (67.2) | 27 (42.2) | 37 (57.8) | ||
aIndependent samples; t-test; bχ2 test; SD standard deviation
Prevalence of PPD and PPA symptoms
The overall prevalence of PPD symptoms, PPA symptoms, and the co-occurrence of both were 12.9%, 20.8%, and 9.4%, respectively. In postpartum women with and without PPD symptoms, there were significant differences in sleep duration and annual household income. The prevalence of PPD symptoms was higher among women who slept < 6 h (χ2 = 25.527, P < 0.001), as well as those with low economic status (χ2 = 35.503, p < 0.001). However, there were no significant differences in age, living region, parity, or the presence of somatic diseases between postpartum women with and without PPD symptoms (all, p > 0.05).
Among women with and without PPA symptoms, significant differences were observed in age, accompanying somatic diseases, sleep duration, and annual household income. Women with PPA symptoms tended to be younger (t = -2.452, p = 0.014), have accompanying somatic diseases (χ2 = 8.879, p = 0.003), slept < 6 h (χ2 = 27.716, p < 0.001), and have a low annual household income (χ2 = 39.969, p < 0.001). In contrast, there were no significant differences in living region and parity in women with and without PPA symptoms (all, p > 0.05). The EPDS scores were higher for women with symptoms of PPD (t = 21.213, p < 0.001) and PPA (t = 21.325, p < 0.001) than without.
The percentages of women with mild, moderate, severe, and moderate-to-severe PPD symptoms were 26.3%, 7.7%, 5.2%, and 12.9%, respectively. Meanwhile, the percentages of women with mild, moderate, severe, and moderate-to-severe PPA symptoms were 20.4%, 5.9%, 2.5%, and 8.4%, respectively. Table 2 presents the mean scores of PPD and PPA symptoms of varying severity, along with the corresponding EPDS mean scores. Spearman’s correlation analysis revealed a correlation between the total PHQ-9 and EPDS scores (r = 0.404, p < 0.001).
Table 2.
Percentage of postpartum women with various severities of PPD and PPA symptoms (N = 2152)
| PPD symptoms | EPDS | PPA symptoms | EPDS | |||
|---|---|---|---|---|---|---|
| n (%) | Mean (SD) | Mean (SD) | n (%) | Mean (SD) | Mean (SD) | |
| Minimal | 1308 (60.8) | 1.16 (1.43) | 6.62 (4.35) | 1533 (71.2) | 0.68 (1.21) | 6.86 (4.58) |
| Mild | 566 (26.3) | 7.03 (1.47) | 9.39 (4.79) | 438 (20.4) | 6.67 (1.07) | 10.6 (4.46) |
| Moderate | 166 (7.7) | 11.66 (1.38) | 13.02 (4.96) | 127 (5.9) | 12.17 (1.52) | 14.38 (3.72) |
| Moderate to severe | 278 (12.9) | 14.51 (4.40) | 13.87 (5.0) | 181 (8.4) | 14.07 (3.42) | 14.71 (4.57) |
| Severe | 112 (5.2) | 18.72 (3.93) | 15.12 (4.81) | 54 (2.5) | 18.56 (2.27) | 15.48 (6.10) |
SD standard deviation
Risk factors for PPD and PPA symptoms
Although no significant differences were observed in age, residential region, parity, and comorbid somatic diseases of women with and without PPD symptoms, these variables were included in the modified Poisson regression due to the large sample size. The results showed that as compared to sleep durations of 6–8 and < 8 h, a sleep duration of < 6 h (B = 0.621, RR = 1.862, 95%CI = 1.439–2.408, p < 0.001) was a risk factor for PPD symptoms. Similarly, as compared to households with high, and above average, average annual household incomes (B = 0.442, RR = 1.555, 95% CI = 1.027–2.355, p = 0.037), and low annual household income (B = 1.215, RR = 3.369, 95% CI = 1.981–5.730, p < 0.001) was also identified as a risk factor for PPD (Table 3). Nonetheless, parity, comorbid somatic diseases, region of living, and age were not risk factors for PPD (all, p > 0.05).
Table 3.
Risk factors correlated with the prevalence of PPD and PPA symptoms
| PPD symptoms | PPA symptoms | |||||
|---|---|---|---|---|---|---|
| RR | 95% CI | p | RR | 95% CI | p | |
| Age | 0.980 | 0.953−1.007 | 0.150 | 0.983 | 0.966–1.001 | 0.064 |
| EPDS total score | - | - | - | 1.134 | 1.120–1.148 | < 0.001 |
| Region | ||||||
| Suburban | 1 | 1 | ||||
| Urban | 1.080 | 0.855–1.363 | 0.519 | 0.934 | 0.795–1.098 | 0.409 |
| Parity | ||||||
| Primiparous | 1 | 1 | ||||
| Multiparous | 1.167 | 0.917–1.485 | 0.209 | 1.029 | 0.869–1.219 | 0.738 |
| Complications | ||||||
| No | 1 | 1 | ||||
| Yes | 1.280 | 0.786–2.084 | 0.320 | 1.298 | 0.961–1.753 | 0.089 |
| Sleep duration | ||||||
| 6–8 h | 1 | 1 | ||||
| >8 h | 0.965 | 0.730–1.276 | 0.803 | 0.795 | 0.652–0.970 | 0.024 |
| < 6 h | 1.862 | 1.439–2.408 | < 0.001 | 1.060 | 0.883–1.273 | 0.533 |
| Annual household income | ||||||
| High | 1 | 1 | ||||
| Above average | 0.771 | 0.436–1.362 | 0.370 | 0.848 | 0.564–1.275 | 0.429 |
| Average | 1.555 | 1.027–2.355 | 0.037 | 1.438 | 1.063–1.945 | 0.018 |
| Low | 3.369 | 1.981–5.730 | < 0.001 | 2.148 | 1.449–3.184 | < 0.001 |
Regarding PPA symptoms, modified Poisson regression showed that sleep duration > 8 h (B = -0.229, RR = 0.795, 95% CI = 0.652–0.970, p = 0.024) was a protective factor for PPA symptoms. In contrast, sleep duration < 6 h (B = 0.058, RR = 1.060, 95% CI = 0.883–1.273, p = 0.533) showed no significant association with PPA symptoms. Additionally, a household annual income classified as average (B = 0.363, RR = 1.438, 95% CI = 1.063–1.945) or low (BB = 0.764, RR = 2.148, 95% CI = 1.449–3.184) was also identified as a risk factor for PPA. PPA symptoms were correlated to higher EPDS scores (B = 0.126, RR = 1.134, 95% CI = 1.120–1.148). Although age (p = 0.064) and comorbid somatic diseases (p = 0.089) did not reach statistical significance, the results suggested a potential trend, warranting further attention. In contrast, residential region and parity were not risk factors for PPA (all, p > 0.05) (Table 3).
Discussion
In this study, the self-reported prevalence rates of PPD, PPA, and comorbidity of both disorders were 12.9%, 20.8%, and 9.4%, respectively. Further, among these women, 12.9% and 8.4% experienced moderate-to-severe PPD and PPA symptoms, respectively. Women with moderate-to-severe PPD had similar PHQ-9 and EPDS scores. The results revealed that low economic status was a common risk factor for both PPD and PPA, while sleep duration showed differential effects on these two conditions. Additionally, the risks of PPD and PPA increased significantly with higher EPDS scores. To the best of our knowledge, this is the first study to simultaneously use both the PHQ-9 and EPDS to assess PPD symptoms among postpartum women residing in the eastern coastal region of China.
The self-reported prevalence rates for PPD and PPA symptoms were 12.9% and 20.8%, respectively. These findings align with recent research, as a systematic review across 56 countries revealed an average PPD rate of 17.7% [34], while a Chinese study reported rates ranging from 10% to 15% [35]. Notably, the prevalence of PPA symptoms reached 20.8%, substantially exceeding the 12.9% rate observed for PPD symptoms. This pattern might reflect the psychological challenges during the postpartum period, where the responsibilities of newborn care, breastfeeding pressure, and concerns about infant health may particularly contribute to elevated PPA levels [36]. Furthermore, previous literature suggests that the proliferation of parenting information on social media and increasingly demanding standards of childrearing may contribute to elevated anxiety levels among postpartum mothers [37], though this hypothesis warrants further investigation.
This study revealed a self-reported comorbidity rate of 9.4% for PPD and PPA symptoms, indicating that a considerable proportion of mothers experience both conditions simultaneously. This finding diverges from previous research, as Dennis et al. reported a comorbidity rate of 21.9% [38], while a meta-analysis by Falah-Hassani et al. documented rates ranging from 1.7% to 8.2% [39]. Such discrepancies might reflect variations in sociocultural contexts and assessment tools across different study populations. Terrone et al. demonstrated that perinatal depression comorbidity patterns vary by onset timing (pregnancy versus postpartum), suggesting that methodological differences and assessment windows contribute to reported variations [40]. Clinically, the substantial comorbidity rate underscores the necessity of routine dual screening for both depression and anxiety in postpartum care.
With PPD symptoms affecting 12.9% of the study population and a comorbidity rate of 9.4%, our findings suggest that a substantial proportion of mothers with PPD also experience concurrent PPA symptoms. Previous studies have demonstrated that mothers with such comorbid conditions often exhibit increased ruminative thinking and avoidance behaviors, which not only affect their willingness to seek social support but also interfere with early mother-infant interactions [41, 42]. Moreover, as compared to those with isolated PPD or PPA, mothers with comorbid symptoms demonstrate more pronounced sleep disturbances and somatic complaints, making it particularly challenging for them to benefit from conventional social support systems [43, 44]. This study provides data from a developing coastal region during 2023–2024. The observed prevalence rates and strong economic associations reflect the specific context of areas undergoing rapid socioeconomic change in post-pandemic China.
The results revealed differential effects of sleep duration on PPD versus PPA. Insufficient sleep was identified as a risk factor for PPD, whereas longer sleep duration emerged as a protective factor for PPA. Interestingly, insufficient sleep showed no significant association with PPA symptoms. This finding partially corroborates previous research demonstrating the association between poor sleep quality and postpartum depression [45, 46]. The differential effects of sleep on PPD versus PPA may reflect distinct underlying pathophysiological mechanisms. Sleep deprivation may primarily affect depressive symptoms through dysregulation of the neuroendocrine system, particularly the hypothalamic-pituitary-adrenal axis [47, 48]. Moreover, impaired sleep has been shown to compromise glymphatic clearance, enhance neuroinflammatory processes, and reduce neuroplasticity [49], providing additional neurobiological pathways linking insufficient sleep to PPD risk. In contrast, adequate or extended sleep may buffer against anxiety symptoms by allowing for better stress recovery and emotional regulation [50].
Low economic status was identified as a shared risk factor for both PPD and PPA. Persistent economic stress not only directly affects maternal quality of life and healthcare-seeking behaviors but also indirectly impacts mental health through increased family conflicts and diminished perceived social support [51]. These risk factors demonstrate a synergistic interaction, whereby financial hardship may lead to suboptimal living conditions and insufficient childcare support, subsequently compromising sleep quality, while sleep deprivation may impair work performance and income-earning capacity during the postpartum period [52]. Targeted interventions combining sleep management strategies with financial assistance programs have been shown to significantly improve maternal mental health outcomes, encompassing professional sleep guidance and flexible financial support schemes [53].
Interestingly, several variables traditionally considered risk factors for postpartum mental health, including parity, maternal age, residential region, and comorbid somatic diseases, did not demonstrate significant associations with PPD or PPA in our study, which may be attributed to the relatively homogeneous sample characteristics, the cultural context of strong family support systems in China, the uniform healthcare infrastructure in our study region, and limited sample representation of certain comorbidities [54–57].
This study employed the PHQ-9 and GAD-7 as primary assessment tools, while incorporating the EPDS for evaluation. The PHQ-9 was selected based on the direct correspondence with the DSM diagnostic criteria and compatibility with the GAD-7, which enables concurrent assessment of PPD and PPA comorbidity. A moderate-to-low correlation was observed between the total scores of these two scales, which could be attributed to the distinct design characteristics. Furthermore, the PHQ-9 assesses general PPD symptoms (including somatic symptoms) over a two-week period, whereas the EPDS focuses on postpartum-specific emotional changes, while deliberately avoiding the influence of physiological changes during the postpartum period, with a seven-day assessment window. The decision to calculate prevalence rates using the PHQ-9 was primarily driven by alignment with the DSM diagnostic criteria, facilitating comparison with other clinical studies.
These findings have significant clinical and policy implications. We recommend integrating systematic mental health screening into postpartum care to promptly identify mothers exhibiting symptoms of PPD and PPA, particularly those experiencing sleep deprivation and financial hardship. Additionally, establishing dedicated postpartum mental health support networks is crucial to provide counseling and support services to aid mothers in addressing potential mental health challenges. There is also a need to enhance social welfare and financial assistance for economically disadvantaged families to alleviate the financial stress on postpartum women, thereby reducing the risk of mental health issues. Furthermore, increasing public awareness of PPD and PPA is vital to combat stigma and misconceptions. In postpartum care and family education, it is important to emphasize and promote good sleep hygiene practices to help women and families understand the crucial role of sleep in mental health, and offer practical advice to improve sleep quality.
There were some limitations to this study that warrant attention. First, our study relied on self-administered questionnaires (PHQ-9, GAD-7, and EPDS) may introduce social desirability and reporting biases, potentially affecting the accuracy and objectivity of the findings. Second, as participants were primarily recruited from hospitals, selection bias may exist, which limits the generalizability of our results to postpartum women who do not utilize hospital-based maternity care. Third, the cross-sectional design of this study precludes the determination of causality and makes it impossible to distinguish between transient and persistent postpartum affective disorders. Fourth, our analysis focused exclusively on risk factors, and we did not explicitly examine protective variables. This omission was primarily due to the design of our data collection instruments, most of which were structured to identify risk exposures rather than protective elements. Fifth, we were unable to include important psychosocial variables such as family support, marital relationship quality, and recent stressful life events, which are known to play critical roles in perinatal mental health. Future research should examine protective factors and key psychosocial variables, adopt longitudinal designs, and employ broader recruitment strategies for a more comprehensive understanding of postpartum affective disorders.
This study revealed a significant presence of PPD and PPA among women, with a substantial proportion experiencing moderate-to-severe symptoms. Insufficient sleep and low economic status emerged as significant risk factors for both conditions, with EPDS scores demonstrating an important predictive value. These findings highlight the potential impact of sleep management and economic support to reduce postpartum mental health issues. In conclusion, early identification and management of PPD and PPA are crucial. Healthcare providers should develop targeted intervention strategies that address multiple risk factors, with particular emphasis on improving sleep quality and providing socioeconomic support to enhance the mental well-being of postpartum women.
Acknowledgements
We would like to express our sincere gratitude to all study participants and colleagues involved in data collection.
Authors’ contributions
Zhen Qin, Yangyang Pan, and Haidong Yang wrote the manuscript; Xiaobin Zhang and Chunlin Zhu were responsible for study design; Zhen Qin and Haidong Yang performed the statistical analysis; Yangyang Pan and Lingshu Luan were responsible for collecting the data, coordinating with schools, and maintaining the online survey platform. All authors have contributed to and approved the final manuscript.
Funding
We are grateful to the funders of this study. The study was supported by the Suzhou Key Technologies Program (SKY2021063), Suzhou Clinical Medical Center for Mood Disorders (Szlcyxzx202109), Suzhou Clinical Key Disciplines for Geriatric Psychiatry (SZXK202116), Suzhou Key Laboratory (SZS2024016), General Program of Lianyungang Health Committee (NO.202336), and Lianyungang Maternal and Child Health Research Project (No. F202506). The funding sources of this study had no role in the study design, data collection and analysis, decision to publish, or preparation of the article.
Data availability
The data that support the findings of this study are available from the corresponding author upon reasonable request.
Declarations
Ethics approval and consent to participate
We declare that all experiments on human subjects were conducted in accordance with the Declaration of Helsinki and that all procedures were carried out with the adequate understanding and written consent of the subjects. We also certify that formal approval to conduct the experiments described has been obtained from the human subject review board of our institution. All experimental protocols were approved by the Ethics Committee of Lian Yun Gang Fourth People’s Hospital. Informed consent was obtained from all subjects or their guardian. All methods were carried out in accordance with relevant guidelines and regulations.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Zhen Qin, Yangyang Pan, and Haidong Yang contributed equally to this work. They should be regarded as joint first authors.
Contributor Information
Xiaobin Zhang, Email: zhangxiaobim@163.com.
Chunlin Zhu, Email: zcllyg6619@163.com.
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Associated Data
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Data Availability Statement
The data that support the findings of this study are available from the corresponding author upon reasonable request.