Pregnancy and childbirth constitute crucial phases in the life cycle of a woman, yet these phases also present numerous physical and psychological challenges [1]. The occurrence of depression during pregnancy has been reported to be as high as 20.70% in 2020 [2], a rate significantly above that of the general population. According to the 2018 American College of Obstetricians and Gynecologists (ACOG) consensus, depressive episodes experienced by pregnant women, ranging from mild to severe, can be diagnosed as perinatal depression [3]. This condition not only poses risks for adverse pregnancy outcomes, such as fetal growth restriction, preterm labor, and increased cesarean section rates, but also elevates the likelihood of postpartum depression [4]. Furthermore, perinatal depression can impact the day-to-day functioning and overall quality of life for pregnant women and new mothers [5]. Research by Lebel et al. [6] has shown that maternal depression during mid-pregnancy can have lasting effects on neonatal brain structure and long-term emotional, behavioral, cognitive, physiological, and neurological development. Meanwhile, psychological factors play a significant role in labor and delivery, with approximately 10% of cesarean sections being attributed to elevated levels of maternal anxiety [7]. Notably, compared to postpartum mental health, mental health during pregnancy has not been adequately addressed in clinical practice. Moreover, depression screening is not routinely included in obstetric examinations, even though depression during pregnancy can lead to adverse birth outcomes such as smaller gestational age babies and reduced head circumference [8, 9, 10]. The reported detection rate of depression during pregnancy is 20.00% [11]. Research indicates that depression and anxiety during pregnancy cannot only affect the health of the pregnant woman and fetus but also impact family dynamics and impose a significant economic burden on both the family and society [12]. Mellor et al. [13] highlighted that risk factors such as fear of childbirth, self-perceived stress, and exposure to stressful or negative events during pregnancy can contribute to the development of depressive symptoms in pregnant women. Thus, as the medical field transitions from the traditional biomedical model to the biopsychosocial medical model, there is a growing emphasis on recognizing and addressing the somatization of psychosocial stress symptoms in patients with mental illnesses stemming from psychosocial disorders.

Therefore, perinatal depression can result in a series of physical and psychological disorders in both mothers and children, imposing a certain burden on families and society. Australia recommends the application of the Prenatal Risk Factor Questionnaire (PRFQ) and the Postnatal Risk Questionnaire (PRQ) for maternal screening [14]. In the United States, it is recommended to ask about psychiatric history, medication use, and the presence of anxiety and depression at 6, 8, and 28 weeks of pregnancy and postpartum, and to use the Edinburgh Postnatal Depression Scale (EPDS) for screening [15]. Given the high prevalence of prenatal depression among perinatal women, coupled with the severity of adverse outcomes and low rates of mental health visits, the implementation of a rapid and convenient screening method could significantly enhance the mental well-being of perinatal women [16]. However, the current tools have limitations: The PRFQ and PRQ focus on risk factor questioning and lack consideration of complex multifactorial interactions; the EPDS is primarily used for postnatal depression screening and is not sufficiently targeted in the prediction of depression during pregnancy. Various risk factors contribute to depression during pregnancy, yet there remains a scarcity of studies examining the present state of depression and its risk factors in pregnant women [17, 18, 19]. Thus, this study aimed to explore the risk factors associated with the occurrence of depression in pregnant women, starting with the construction of a maternal handbook in mid-pregnancy. A column-line diagram model was constructed to quickly assess the risk of depression in pregnancy based on multidimensional information of pregnant women, which improved the diagnostic efficiency and made the operation more convenient. This study aimed to identify and explore risk factors associated with depression in pregnant women, focusing on the development of a maternity booklet during mid-pregnancy to enhance the detection and screening of prenatal depression.

Perinatal depression, also referred to as maternal depression, encompasses depressive symptoms that emerge during pregnancy, following childbirth, or after an abortion. Perinatal depression includes prenatal depression (PD) and postpartum depression (PPD), and is a prevalent complication during pregnancy and the postpartum period [24]. The various stressors experienced during pregnancy can have adverse effects on the mental health of women, potentially increasing the risk of depression due to hormonal changes and physical transformations [25]. Prior research has indicated that perinatal depression not only impacts the health and well-being of women but also extends to the entire family, influencing the emotional and psychological state of the mother, her ability to care for the baby, and the bonding process [26]. Moreover, perinatal depression can promote a significant decline in the mother’s quality of life, an economic strain on the family, and may even result in family discord, self-harm, suicide, and other negative outcomes [27]. A study has shown a clear link between postpartum depression and depression during pregnancy, with approximately one-third of postpartum depression patients experiencing depression during or before pregnancy [28]. Postpartum depression is characterized by persistent low mood, diminished self-esteem, lack of confidence in daily life, and heightened levels of anxiety or hypervigilance [29].

The current study found that 19.37% of pregnant women experienced mid-pregnancy depression. Meanwhile, general demographic and clinical data analysis revealed no statistically significant differences between the two groups of patients in terms of age, gravidity, parity, pre-pregnancy BMI, education level, smoking or alcohol consumption, and work cessation due to pregnancy (p $>$ 0.05). However, factors such as family income, spousal disharmony, disharmony in relationships with parents, change in sleep and diet, work-study stress, adverse maternal history, low satisfaction with living environment, assisted reproduction, unplanned pregnancy, interference from adverse life events, and lack of maternal knowledge were identified as independent risk factors for depression during pregnancy (OR $>$1). Divney et al. [30] demonstrated that social support, family functioning, and intimate relationships can help mitigate the impact of stressful events on the mental health of pregnant women. Nonetheless, pregnant women with low marital satisfaction [31], poor interpersonal relationships, exposure to spousal physical violence [32], and high levels of social distrust [33] are more likely to experience depression or anxiety. Conflicts between the mother-in-law and daughter-in-law, as well as other family conflicts, are common during pregnancy and significantly increase the risk of developing depression [34]. Previous research has shown that low socioeconomic status is linked to prenatal depression [35], and unemployment may lead to a decrease in family income [36], particularly for low-income families [1].

Adverse pregnancy outcomes and insomnia can result in negative maternal emotions such as self-blame, guilt, and distress, and are significant risk factors for postpartum depression, as noted by Chung et al. [37]. Pregnant women who have experienced adverse pregnancy events, including miscarriage, preterm delivery, stillbirth, and other challenging experiences, are more prone to psychological issues during the next pregnancy. Gong et al. [38] found that pregnant women who had a history of miscarriage and short intervals between pregnancies were at a higher risk of experiencing depression and anxiety in early pregnancy compared to those without such a history. Additionally, Meijer et al. [39] discovered that life events during pregnancy were linked to prenatal depression and anxiety symptoms, with pregnancy-related events notably increasing the likelihood of anxiety symptoms.

In addition to social support and stressful life events, various social factors such as economic level, social status, marital status, non-native speakers, and housing status also play a role in the prenatal psychological state of pregnant women [40]. Morylowska-Topolska et al. [41] discovered that economic level and housing situations consistently impact the psychological well-being of pregnant women. Previous research [42] has indicated that favorable living conditions significantly contribute to enhancing maternal psychological recovery. Conversely, this study revealed that poor living conditions can be a risk factor for developing depression during pregnancy. Furthermore, women with lower marital satisfaction were more likely to experience heightened levels of stress during pregnancy [43]. The physiological changes and psychological needs that accompany pregnancy necessitate support and understanding within the marital relationship; thus, women with higher levels of marital satisfaction are less likely to experience postpartum depression [44].

This study successfully constructed a risk prediction model for depression during pregnancy. The mean absolute error of the calibration curve of the model was verified as 0.011, demonstrating good predictive accuracy, and the area under the working characteristic curve of the subjects reached 0.806, with a sensitivity of 66.4% and specificity of 83.5%. Compared with existing diagnostic methods and scales, the EPDS focuses on postnatal depression screening, and this model can integrate multidimensional risk factors at the stage of pregnancy to assess the risk of disease in pregnant women in advance; moreover, this model is more advantageous in terms of accuracy. Some traditional screening questionnaires focus on a single dimension of risk, whereas this model incorporates a combination of factors, which greatly improves the comprehensiveness of the prediction.

Compared with the existing literature, the advantage of this model is that it integrates multiple social, psychological, and physiological factors and is presented in the form of a visualized column-line graph, which facilitates clinicians in calculating the risk probability and identifying high-risk pregnant women quickly. However, the fact that the sample was from a single center may limit the generalizability of the model.

To summarize, the independent risk factors for depression during pregnancy include spousal disharmony, discordant parental relationships, changes in sleep and diet, work-study stress, adverse maternal history, dissatisfactory living environment, assisted reproduction, unplanned pregnancy, interference from adverse life events, and lack of maternal knowledge. The prediction model presented in this study can effectively calculate the occurrence of depression during pregnancy, which is helpful for clinical staff to identify high-risk groups, strengthen pregnancy health care for pregnant women with multiple risk factors, and conduct prenatal health education to alleviate nervousness and fear. Meanwhile, individualized psychological guidance and family intervention can be provided for depressed pregnant women to reduce the occurrence of depression during pregnancy, ensure that pregnant women receive sufficient social support, and minimize the probability of depression during pregnancy.

This study also has some limitations. First, this was a single-center retrospective study with a relatively small sample size (n = 630), and the subjects were all from the same region, which may result in an under-representative sample and affect the generalizability of the model. Second, although the EPDS and GAD-7 scales employed in the study are commonly used screening tools, these scales are mainly used for postpartum depression assessment, and their specificity in predicting depression during pregnancy still needs to be validated further. In addition, this study only explored the correlates of depression during pregnancy; thus, it did not clarify the causal relationships or consider potential influences such as cultural differences and social support systems. Future studies are needed to expand the sample size, conduct multicenter prospective studies, and include more dimensional assessment indicators to enhance the credibility of the research and the applicability of the model.

In addition, the model in this study was constructed and internally validated only on single-center data, meaning the model has not been externally validated, which limits its diagnostic generalizability. The follow-up study will expand the sample range, conduct a multicenter study, collect data from pregnant women in different regions, and externally validate the model by applying the same assessment scales and statistical methods to test the accuracy and applicability of the model further.

This study clarified the independent risk factors for depression during pregnancy through multifactorial analyses, including multidimensional indicators, such as spousal relationships, familial environments, changes in living habits, work-study stress, and pregnancy and childbirth history. The column-line graph prediction model constructed based on these factors had good predictive efficacy (AUC = 0.806) and effectively identified a group of high-risk pregnant women. This study provides a visual and easy-to-use risk assessment tool for the clinic, which can help early intervention and personalized management to reduce the incidence of depression during pregnancy. Future multicenter studies are needed to validate the generalizability of the model further and explore its application value in different cultural contexts.

Original data in this study are available from the corresponding author according to reasonable request.

HQ and YZ designed the research study. HQ and YZ performed the research. YY performed verification and formal analysis. HQ analyzed the data. All authors contributed to editorial changes in the manuscript. All authors read and approved the final manuscript. All authors have participated sufficiently in the work and agreed to be accountable for all aspects of the work.

The study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee of Jinshan Central Hospital Affiliated to Shanghai University of Medicine & Health Sciences (Code number: jszxyy202129; Approval date: November 3, 2020). All subjects gave their informed consent for inclusion before they participated in the study.

This research is supported by Jinshan District Medical and Health Science and Technology Innovation Fund Project (Grant No. 2020-3-31) and Shanghai University of Medicine & Health Sciences Affiliated Hospital Faculty Talent Hundred People Talent Program (Grant No. 2023-1).

The authors declare no conflict of interest.