Abstract
Background
Little research has been conducted on the association between pregnant specific stress and depressive symptoms, and whether family relationship and leisure hobbies moderate the association.
Methods
A cross-sectional survey of 647 pregnant women was conducted in Shenyang City, Liaoning Province of China. Pregnancy Pressure Scale (PPS), Edinburgh Postnatal Depression Scale (EPDS) and two single items were used to assess stress, perinatal depressive symptoms, family relationship and leisure hobbies, respectively. The analysis included χ2-test, Fisher’s exact test, and binary logistic regression.
Results
The prevalence of perinatal depressive symptoms was 22.9% among the participants. After adjustment, four dimensions of pregnancy stress were found to increase the risk of depressive symptoms, and odds ratios (ORs) were 4.175 (95% confidence interval (CI) = 2.240, 7.779), 5.947 (95% CI = 2.624, 13.478), 3.907 (95% CI = 2.375, 6.425), and 8.534 (95% CI = 4.588, 15.873) for factors 1, 2, 3, and 4 (recognition of the role of parents, worrying about maternal and child health and safety, the changes in body shape and physical activity level, as well as child care and marriage), respectively. In addition, significant interactions were found between factor 2, factor 4 and family relationship, leisure hobbies with depressive symptoms, respectively (interaction P < 0.10).
Conclusion
Tailored stress-overcoming programs, as well as health services, are needed to relieve women’s pregnancy stress and prevent them from depressive symptoms. Clinical practice should conduct family relationship-oriented interventions and women themselves can cultivate extensive leisure hobbies in the period of pregnancy preparation.
Keywords: Depressive symptoms, Pregnant women, Stress, Family relationship, Leisure hobbies, China
Introduction
In the lives of women, pregnancy is seen as a special period accompanied by biological, physiological, psychological, and social changes, which may develop from the start of pregnancy and even to the postpartum period (Bjelica et al. 2018). Around the world, 11.9% of women suffer from perinatal depression, and women in low- and middle- income countries have a higher prevalence of perinatal depression than those in high-income ones (Woody et al. 2017). Severe perinatal depression is considered to be the third leading cause of years lived with disability in Chinese people (Vos et al. 2016). Perinatal depression is likely to result in miscarriage, premature delivery, low birth weight and Apgar scores (indicating the maladaptation of newborns to the intrauterine environment) as well as delayed emotional and language development in offspring (Fredriksen et al. 2019). In addition, pregnant women have a higher possibility of developing postnatal depression if they experience depression in the prenatal period (Martinez-Borba et al. 2020; Pampaka et al. 2019). Moreover, the general population is faced with an increase in the risk of suffering from stress, anxiety, and depression during the coronavirus disease 2019 (COVID-19) pandemic (Salari et al. 2020). Because of social isolation, pregnant women have some difficulty interacting with family members and friends; whose mental health is challenged by restrictions on hospital visitation (Ostacoli et al. 2020) and they also worry about the possible intrauterine transmission of COVID-19 to fetuses (Mazur-Bialy et al. 2020).
The possible mechanisms explaining maternal depression are of two types: biological and psychosocial. From a psychosocial perspective, the strongest predicting factors are severe life stress, certain forms of chronic tension, the quality of spousal relationship and the support of her partner (Yim et al. 2015). A broad variety of studies carried out on pregnant women have observed a negative relationship between perceived stress and mental health (Staneva et al. 2015; Zhang et al. 2022). As a common phenomenon, pregnancy stress refers to “the imbalance felt by a pregnant woman in the case of being unable to cope with demands, which is expressed in both a behavioral and physiological way”. Research shows that the stress of pregnant women comes from physical symptoms and changes, body image changes, physiological (gestation reaction including nausea and vomiting (Rodriguez-Ayllon et al. 2021)), social (disruptions with work and fetus nourishment) and emotional changes, parenting concerns, medical issues, anxiety about childbirth, concerns about delivery and babies’ health, and other various pregnancy-specific problems (Bjelica et al. 2018). For pregnant women, a high level of stress may give rise to adverse maternity outcomes and the development of behavioral, cognitive, and emotional problems in their children (Magnus et al. 2021; Staneva et al. 2015). Additionally, the stress of pregnant women has a positive correlation with stress and the negative emotions of their spouses (Nie et al. 2017). In China, the prevalence of antenatal stress is approximately 90% (Tang et al. 2019). Pregnancy stress exists in most pregnant women during their pregnancy, indicating that it is of great importance to find ways to regulate stress and prevent depressive symptoms.
According to the stress-buffering model, environmental coping resources (i.e., social support), and personal coping resources, or particular behavioral and/or cognitive strategies in coping are possibly important to reduce the impact of exposure to stressors on depression (Wheaton 1985). The arrival of a child brings about dynamic changes in the family, which can be a source of physical and emotional vulnerability for all family members, especially mothers (Nomaguchi and Milkie 2020). Moreover, late pregnancy women are out of daily work and most of them stay with their family all the time. Therefore, family relationships have a great influence on their psychological and emotional state. A good family relationship is the foundation of healthy family function and sufficient and effective intra-family social support (Lei and Kantor 2021). Families with healthy functions can cope with negative emotional states in conflicts and critical situations. However, families with low family functionality may not have the competence to overcome the problems brought about by various life periods (Thomas et al. 2017). A study conducted in rural areas of Southwest China among 490 women has revealed that family function had a direct negative correlation with perinatal depression (Huang et al. 2021). Moreover, a study conducted in China with 1821 undergraduates indicated that the association between the uncertainty stress and depressive symptoms was significantly moderated by family relationships (Zhang et al. 2021). However, whether family relationship plays a moderate role between pregnancy specific stress and depressive symptoms has not been explored.
In addition, due to the normalization of the COVID-19 situation and restrictions related to social distance, patients in hospital are only accompanied by one family member, and other relatives or friends are not allowed to visit at will. Therefore, self-regulation is also particularly necessary. Scholars in the domain of leisure science have long agreed with the crucial role of leisure in buffering stress and facilitating overall well-being (Iwasaki et al. 2006). These benefits may be attributed to leisure stimulating positive feelings and augmenting means of capitalizing on social and physical resources, ultimately refreshing individuals and enabling them to better cope with a variety of stressors (Iwasaki and Mannell 2000; Iwasaki and Schneider 2003). Existing studies suggest that leisure activities are beneficial to alleviating stress and restoring psychosocial wellness (Lee et al. 2020). However, the role of leisure hobbies in the relationship between stress and depression remains unclear.
In the context of the normalization of the epidemic of COVID-19, the mental health of hospitalized late pregnancy women deserves more attention. Considering the difference between stress during pregnancy and in daily life, it is meaningful to investigate the association between stress and depressive symptoms from different dimensions. The present study was aimed at analyzing the relationship between pregnant specific stress and depressive symptoms in the late pregnancy of Chinese women, and whether leisure hobbies play a moderate role in the relationship.
Methods
Data sources and sample composition
Conducted between May and November 2021 in Shenyang City, Liaoning Province of China, this cross-sectional study aimed to investigate pregnant women who were hospitalized for pending delivery with a gestation period of 36 weeks or more. The participants provided their demographic information, maternity characteristics, physiological conditions, lifestyle, folic acid, drug consumption, and leisure hobbies. First, survey time, place, and participants were determined through the discussion of the researcher with the management in the hospital. During this study, the investigators explained the objectives and importance of the questionnaire survey to all the participants who provided their written informed consent. Then, questionnaires were distributed to the participants who completed them completely according to their own opinions. A total of 656 late pregnancy women participated in this study and completed the entire questionnaire. After excluding nine pregnant women with twins or multiple fetuses, this study had a final sample size of 647. Based on the bioethics principles mentioned in the Declaration of Helsinki, the current study also gained the approval of the Ethics Committee.
Measures
Pregnancy pressure
Pregnancy specific stress status was assessed using the Pregnancy Pressure Scale (PPS), which is a validated tool for pregnant women in China (Tang et al. 2019). The PPS consists of 4-factors, with 30 items in total: Factor 1 (include 15 items) – stress comes from recognition of the role of parents; Factor 2 (include 8 items) – stress comes from worrying about maternal and child health and safety; Factor 3 (include 4 items) – stress comes from worrying about the changes in body shape and physical activity level; Factor 4 (include 3 items) – stress comes from worrying about child care and marriage. Each factor score is equal to the factor’s total score divided by the number of items contained in that factor. The total scale score is classified into no and has stress (0, and > 0). In this study, the Cronbach’s α coefficient of the total scale was 0.947, and the Cronbach’s α coefficients of the four dimensions were 0.897, 0.899, 0.921, and 0.800, respectively.
Prenatal depression
Prenatal depression status was assessed using the Edinburgh Postnatal Depression Scale (EPDS) in accordance with previous studies (Bergink et al. 2011). The EPDS is a structured 10-item self-report measurement of depression during post-pregnancy. It is also validated for screening depression during pregnancy. Each item is scored with a value from 0 to 3, which give a sum score of 0 to 30. The cut-off point of an EPDS standardized score ≥ 9.5 reflects depressive symptomatology in the Chinese population (Wang et al. 2009). In the present study, the Cronbach’s α of EPDS was 0.872.
Family relationship
Family relationship was evaluated by asking the respondents to evaluate their family relationship and select from “very good, good, fair, poor, and very poor (1–5),” and their answers were divided into good (1–2) and fair or poor (3–5).
Leisure hobbies
Regarding Leisure hobbies, the participants gave answers to the question “Do you have extensive hobbies or leisure activities?” on a scale ranging from 1 to 5, representing “not extensive,” “not very extensive,” “fair,” “extensive,” and “very extensive,” respectively. Then, it was divided into extensive (4–5) and not extensive (1–3).
Covariate assessment
Demographic characteristics included age, educational level, only child, residence, per capita household income monthly, and family relationship. Age was segmented into 20–24, 25–29, 30–34 and ≥ 35. Educational level was classified according to the setting of China’s education system: (1) middle school or below, (2) high school, (3) college, (4) undergraduate, (5) postgraduate, and above. Only child was assessed by asking the respondents whether they were the only child in their families.
Maternity characteristics included the method of conception, the number of antenatal examinations, and parity. The method of conception contained natural conception and assisted reproduction. The number of antenatal examinations was assessed by asking the participants the number of examinations from the beginning of pregnancy to the present. In this study, the answers were divided into 1–10, 11–15, and ≥16. Parity was assessed by asking the participants whether they were primiparas.
Three physiological health factors were considered in this study: pre-pregnancy body mass index (BMI), pregnancy weight gain, and self-rated health. According to the revised Asia-Pacific BMI criteria by the World Health Organization (World Health Organization 2004), BMI < 18.5, 18.5 ≤ BMI < 24.0, 24.0 ≤ BMI < 28.0, BMI ≥ 28.0 were defined as underweight, normal, overweight, and obesity, respectively. According to the guidelines of American Institute of Medicine (Institute of Medicine 2009), pregnancy weight gain criteria vary based on pre-pregnancy weight. It is recommended that pregnant women with normal weight, low weight, overweight, and obesity increase 11.5–16, 12.5–18, 7–11.5, and 5–9 kg, respectively, during the whole pregnancy. In this study, body weight gain during pregnancy was divided into in normal range, under minimum, and over the maximum. Self-rated health was measured by asking the respondents how they evaluated their health status on a 5-point scale, which was categorized into good and fair or poor.
Life style included smoking and drinking before conception, reducing the use of household appliances during pregnancy, and the frequency of passive smoking and exercise during pregnancy. Passive smoking refers to the inhalation of smoke generated by the smoking of others, whose cumulative time is more than 15 minutes. Alternative answers included every day, often, occasionally, and never. Regular exercise means exercising three or more times a week. The frequency of folic acid consumption and whether the respondents were at risk of drug use were also taken into consideration. The period of folic acid consumption included before and during pregnancy, during pregnancy as well as before pregnancy, and neither.
Statistical analyses
Statistical Product and Service Solutions (SPSS) 24 (IBM, Armonk, NY, USA) was used to manage and analyze data. First, whether each factor had a statistically significant association with pregnancy depression was explored by using χ2-test and Fisher’s exact test. Then, the use of binary logistic regression models analyzed the relationships between pregnancy stress in all dimensions and depressive symptoms in the whole participants, extensive and not extensive leisure hobbies, respectively. Odds ratios (ORs) and 95% confidence intervals (CIs) were adjusted for potential confounding factors. Two-sided P values were statistically significant when lower than 0.05 in univariate and binary analysis logistic regression, while 0.10 in the interaction analysis.
Results
Basic socio-demographic factors and perinatal depressive symptoms
The results revealed that 22.9% (148/647) of Chinese adults suffered from perinatal depressive symptoms. Of all the participants, the number of those aged 20–24, 25–29, 30–34, and ≥35 was 57 (8.8%), 277 (42.8%), 235 (36.3%), and 78 (12.1%), respectively.
Six factors, including residence, per capita household income monthly, family relationship, self-rated health, reducing the use of household appliances during pregnancy, and leisure hobbies, were associated with perinatal depressive symptoms (P < 0.05). The associations are described in detail, as shown in Table 1.
Table 1.
Sample characteristics of late pregnancy women and univariate analysis of depressive symptoms
| Variables | Sample n (%) |
Depressive symptoms | χ2 | P | |
|---|---|---|---|---|---|
| No (n = 499) | Yes (n = 148) | ||||
| Demography characteristics | |||||
| Age (year) | 0.758 | 0.859 | |||
| 20–24 | 57 (8.8) | 42 (73.7) | 15 (26.3) | ||
| 25–29 | 277 (42.8) | 212 (76.5) | 65 (23.5) | ||
| 30–34 | 235 (36.3) | 183 (77.9) | 52 (22.1) | ||
| ≥35 | 78 (12.1) | 62 (79.5) | 16 (20.5) | ||
| Educational level | 6.760 | 0.149 | |||
| Middle school and below | 67 (10.4) | 48 (71.6) | 19 (28.4) | ||
| High school | 87 (13.4) | 60 (69.0) | 27 (31.0) | ||
| College | 192 (29.7) | 150 (78.1) | 42 (21.9) | ||
| Undergraduate | 266 (41.1) | 215 (80.8) | 51 (19.2) | ||
| Postgraduate and above | 35 (5.4) | 26 (74.3) | 9 (25.7) | ||
| Only child | 0.877 | 0.349 | |||
| Yes | 284 (43.9) | 224 (78.9) | 60 (21.1) | ||
| No | 363 (56.1) | 275 (75.8) | 88 (24.2) | ||
| Residence | 4.709 | 0.030 | |||
| Urban | 587 (90.7) | 446 (76.0) | 141 (24.0) | ||
| Rural | 60 (9.3) | 53 (88.3) | 7 (11.7) | ||
| Per capita household income monthly (yuan) | 13.683 | 0.003 | |||
| ≤5000 | 230 (35.5) | 173 (75.2) | 57 (24.8) | ||
| 5001–7000 | 124 (19.2) | 84 (67.7) | 40 (32.3) | ||
| 7001–10000 | 166 (25.7) | 132 (79.5) | 34 (20.5) | ||
| ≥10001 | 127 (19.6) | 110 (86.6) | 17 (13.4) | ||
| Family relationship | 16.459 | <0.001 | |||
| Good | 542 (83.8) | 434 (80.1) | 108 (19.9) | ||
| Fair/ poor | 105 (16.2) | 65 (61.9) | 40 (38.1) | ||
| Maternity characteristics | |||||
| Method of conception | 0.559 | 0.455 | |||
| Natural conception | 623 (96.3) | 482 (77.4) | 141 (22.6) | ||
| Assisted reproduction | 24 (3.7) | 17 (70.8) | 7 (29.2) | ||
| Number of antenatal examination | 0.247 | 0.884 | |||
| 1–10 | 63 (9.7) | 50 (79.4) | 13 (20.6) | ||
| 11–15 | 285 (44.0) | 218 (76.5) | 67 (23.5) | ||
| ≥16 | 299 (46.2) | 231 (77.3) | 68 (22.7) | ||
| Parity | 0.014 | 0.905 | |||
| 0 (primiparity) | 518 (80.1) | 399 (77.0) | 119 (23.0) | ||
| 1 | 129 (19.9) | 100 (77.5) | 29 (22.5) | ||
| Physiological factors | |||||
| Pre-pregnancy BMI | 2.577 | 0.461 | |||
| Underweight | 71 (11.0) | 55 (77.5) | 16 (22.5) | ||
| Normal weight | 388 (60.0) | 299 (77.1) | 89 (22.9) | ||
| Overweight | 130 (20.1) | 96 (73.8) | 34 (26.2) | ||
| Obesity | 58 (9.0) | 49 (84.5) | 9 (15.5) | ||
| Weight gain during pregnancy | 0.788 | 0.674 | |||
| In normal range | 220 (34.0) | 173 (78.6) | 47 (21.4) | ||
| Under minimum | 98 (15.1) | 77 (78.6) | 21 (21.4) | ||
| Over maximum | 329 (50.9) | 249 (75.7) | 80 (24.3) | ||
| Self-rated health | 14.004 | <0.001 | |||
| Good | 440 (68.0) | 358 (81.4) | 82 (18.6) | ||
| Fair/ poor | 207 (32.0) | 141 (68.1) | 66 (31.9) | ||
| Life style and consumption | |||||
| Smoking before conception | 1.747 | 0.186 | |||
| Yes | 27 (4.2) | 18 (66.7) | 9 (33.3) | ||
| No | 620 (95.8) | 481 (77.6) | 139 (22.4) | ||
| Passive smoking during pregnancy | 4.782 | 0.189 | |||
| Everyday | 8 (1.2) | 6 (75.0) | 2 (25.0) | ||
| Often | 24 (3.7) | 15 (62.5) | 9 (37.5) | ||
| Occasionally | 235 (36.3) | 176 (74.9) | 59 (25.1) | ||
| Never | 380 (58.7) | 302 (79.5) | 78 (20.5) | ||
| Drinking before conception | 0.068 | 0.795 | |||
| Yes | 62 (9.6) | 47 (75.8) | 15 (24.2) | ||
| No | 585 (90.4) | 452 (77.3) | 133 (22.7) | ||
| Folic acid consumption | –– | 0.175b | |||
| Before and during pregnancy | 279 (43.1) | 226 (81.0) | 53 (19.0) | ||
| During pregnancy | 336 (51.9) | 250 (74.4) | 86 (25.6) | ||
| Before pregnancy | 19 (2.9) | 13 (68.4) | 6 (31.6) | ||
| Neither | 13 (2.0) | 10 (76.9) | 3 (23.1) | ||
| At-risk drug use | 0.047a | 0.828 | |||
| Yes | 18 (2.8) | 13 (72.2) | 5 (27.8) | ||
| No | 629 (97.2) | 486 (77.3) | 143 (22.7) | ||
| Reduce the use of household appliances during pregnancy | 9.715 | 0.002 | |||
| Yes | 291 (45.0) | 241 (82.8) | 50 (17.2) | ||
| No | 356 (55.0) | 258 (72.5) | 98 (27.5) | ||
| Exercise regularly during pregnancy | 2.202 | 0.138 | |||
| Yes | 109 (16.8) | 90 (82.6) | 19 (17.4) | ||
| No | 538 (83.2) | 409 (76.0) | 129 (24.0) | ||
| Leisure hobbies | 12.048 | 0.001 | |||
| Not extensive | 511 (79.0) | 379 (74.2) | 132 (25.8) | ||
| Extensive | 136 (21.0) | 120 (88.2) | 16 (11.8) | ||
Values were shown as the number (proportions). P-values were calculated by χ2 tests.
a: χ2 was calculated by correction for continuity.
b: P was calculated by Fisher’s exact test
Pregnancy stress and depressive symptoms
Pregnancy stress from the recognition of the role of parents (OR = 4.679, 95% CI = 2.568, 8.525), worrying about maternal and child health and safety (OR = 5.763, 95% CI = 2.621, 12.668), worrying about the changes in body shape and physical activity level (OR = 3.663, 95% CI = 2.285, 5.872) and worrying about child care and marriage (OR = 8.390, 95% CI = 4.624, 15.226) could increase the risk of depressive symptoms among late pregnancy Chinese women. The adjustment of potential confounders showed that OR values turned into 4.175 (95% CI = 2.240, 7.779), 5.947 (95% CI = 2.624, 13.478), 3.907 (95% CI = 2.375, 6.425), and 8.534 (95% CI = 4.588, 15.873), respectively. Data are shown in Table 2.
Table 2.
Pregnancy stress as predictors for depressive symptoms
| Pregnancy stress | Total (n=647) |
Depression symptoms | Unadjusted OR (95%CI) |
Adjusted ORa (95%CI) |
|
|---|---|---|---|---|---|
| No (n = 499) | Yes (n = 148) | ||||
| Recognition of the role of parents | |||||
| No | 168 (26.0) | 155 (92.3) | 13 (7.7) | 1 | 1 |
| Yes | 479 (74.0) | 344 (71.8) | 135 (28.2) | 4.679 (2.568, 8.525)*** | 4.175 (2.240, 7.779) *** |
| Worried about maternal and child health and safety | |||||
| No | 118 (18.2) | 111 (94.1) | 7 (5.9) | 1 | 1 |
| Yes | 529 (81.8) | 388 (73.3) | 141 (26.7) | 5.763 (2.621, 12.668)*** | 5.947 (2.624, 13.478) *** |
| Worried about the changes in body shape and physical activity level | |||||
| No | 231 (35.7) | 207 (89.6) | 24 (10.4) | 1 | 1 |
| Yes | 416 (64.3) | 292 (70.2) | 124 (29.8) | 3.663 (2.285, 5.872) *** | 3.907 (2.375, 6.425) *** |
| Worried about child care and marriage | |||||
| No | 236 (36.5) | 223 (94.5) | 13 (5.5) | 1 | 1 |
| Yes | 411 (63.5) | 276 (67.2) | 135 (32.8) | 8.390 (4.624, 15.226) *** | 8.534 (4.588, 15.873) *** |
Values were shown as the number (proportions).
No depressive symptoms (EPDS < 9.5) is the reference category for the outcome variable. OR represents the odds ratio; 95% CI represents 95% confidence intervals.
aAdjusted for age, residence, per capita household income monthly (yuan), self-rated health, family relationship, reduce the use of household appliances during pregnancy, and leisure hobbies.
***: P < 0.001
Pregnancy stress and depressive symptoms in the group of different family relationship
The interactions of pregnancy stress and family relationship with depressive symptoms are presented in Fig. 1. The interaction P values of four factors of pregnancy stress and family relationship with depressive symptoms were 0.546, 0.081, 0.131, and 0.060, respectively. After controlling for confounders, higher significant associations were found between pregnancy stress and depressive symptoms in the group of poor/fair family relationship, and ORs were 27.097 (95% CI = 3.987, 184.166), and 14.376 (95% CI = 3.737, 55.301) for worrying about maternal and child health and safety as well as worrying about child care and marriage, respectively. Lower significant associations were found between pregnancy stress and depressive symptoms in the group of good family relationship, and ORs were 4.691 (95% CI = 1.820, 12.089) and 8.254 (95% CI = 3.980, 17.116) (Table 3).
Fig. 1.
The interactions between pregnancy stress and family relationship on depressive symptoms among late pregnancy women. The interaction P values between four factors of pregnancy stress and family relationship on perinatal depressive symptoms were 0.546, 0.081, 0.131, and 0.060, respectively. Note: Factor 1: stress comes from recognition of the role of parents; Factor 2: stress comes from worrying about maternal and child health and safety; Factor 3: stress comes from worrying about the changes in body shape and physical activity level; Factor 4: stress comes from worrying about child care and marriage
Table 3.
Family relationship – stratified analysis on the association between pregnancy stress and depressive symptoms
| Pregnancy stress | Good family relationship | Poor/fair family relationship | ||
|---|---|---|---|---|
| Unadjusted OR (95%CI) |
Adjusted ORa (95%CI) |
Unadjusted OR (95%CI) |
Adjusted ORa (95%CI) |
|
| Worried about maternal and child health and safety | ||||
| No | 1 | 1 | 1 | 1 |
| Yes | 5.465 (2.163, 13.808)*** | 4.691 (1.820, 12.089)*** | 8.444 (1.854, 38.468)** | 27.097 (3.987, 184.166) *** |
| Worried about child care and marriage | ||||
| No | 1 | 1 | 1 | 1 |
| Yes | 8.646 (4.258, 17.555)*** | 8.254 (3.980, 17.116)*** | 8.727 (2.786, 27.335) *** | 14.376 (3.737, 55.301) *** |
No depressive symptoms (EPDS < 9.5) is the reference category for the outcome variable. OR represents the odds ratio; 95% CI represents 95% confidence intervals.
aAdjusted for age, residence, per capita household income monthly (yuan), self-rated health, leisure hobbies, and reduce the use of household appliances during pregnancy.
** P < 0.05
*** P < 0.001
Pregnancy stress and depressive symptoms in the group of different leisure hobbies
The interactions of pregnancy stress and leisure hobbies with depressive symptoms are presented in Fig. 2. The interaction P values of four factors of pregnancy stress and leisure hobbies with depressive symptoms were 0.135, 0.062, 0.377, and 0.039, respectively. After controlling for confounders, significant associations were found between pregnancy stress and depressive symptoms in the group of not extensive leisure hobbies, and ORs were 7.480 (95% CI = 2.896, 19.322), and 8.815 (95% CI = 4.522, 17.183) for worrying about maternal and child health and safety as well as worrying about child care and marriage, respectively.
Fig. 2.
The interactions between pregnancy stress and leisure hobbies on depressive symptoms among late pregnancy women. The interaction P values between four factors of pregnancy stress and leisure hobbies on perinatal depressive symptoms were 0.135, 0.062, 0.377, and 0.039, respectively. Note: Factor 1: stress comes from recognition of the role of parents; Factor 2: stress comes from worrying about maternal and child health and safety; Factor 3: stress comes from worrying about the changes in body shape and physical activity level; Factor 4: stress comes from worrying about child care and marriage
However, no significant associations were found between pregnancy stress and depressive symptoms in the group of extensive leisure hobbies (P > 0.05) after controlling for confounders (Table 4).
Table 4.
Leisure hobbies – stratified analysis on the association between pregnancy stress and depressive symptoms
| Pregnancy stress | Extensive leisure hobbies | Not extensive leisure hobbies | ||
|---|---|---|---|---|
| Unadjusted OR (95%CI) |
Adjusted ORa (95%CI) |
Unadjusted OR (95%CI) |
Adjusted ORa (95%CI) |
|
| Worried about maternal and child health and safety | ||||
| No | 1 | 1 | 1 | 1 |
| Yes | 2.032 (0.435, 9.502) | 3.109 (0.390, 24.777) | 7.233 (2.865, 18.256)*** | 7.480 (2.896, 19.322) *** |
| Worried about child care and marriage | ||||
| No | 1 | 1 | 1 | 1 |
| Yes | 5.923 (1.290, 27.203)** | 6.226 (0.965, 40.168) | 8.758 (4.574, 16.771) *** | 8.815 (4.522, 17.183) *** |
No depressive symptoms (EPDS < 9.5) is the reference category for the outcome variable. OR represents the odds ratio; 95% CI represents 95% confidence intervals.
aAdjusted for age, residence, per capita household income monthly (yuan), self-rated health, family relationship and reduce the use of household appliances during pregnancy.
**: P < 0.05
***: P < 0.001
Discussion
Depressive symptoms are common in the prenatal period but are often overlooked by medical institutions in China. In this study conducted in Shenyang City in northeast China, 22.9% of late pregnancy women developed depressive symptoms. The China Center for Disease Control and Prevention (CDC) included the data of six provinces and cities in the mainland of China, turning it into a better representative sample than other research carried out in only one province or city. The result of the China CDC (10.8%) is lower than that of this study (Hu et al. 2017), indicating that the prevalence of late pregnancy depressive symptoms in Shenyang City is probably higher than China’s average level. It may be due to assessment time, assessment methods and/or cutoffs, the sample size of the present study, the clinical status, and socio-economic backgrounds of the participants. Notably, COVID-19 may also increase the depression level of pregnant women (Lebel et al. 2020). An Italian study revealed that women giving birth during the period of compulsory quarantine developed significantly higher-level depressive disorders compared with those giving birth in 2019 (Zanardo et al. 2020). In the context of the COVID-19 epidemic, medical resources are relatively scarce, and depressive symptoms in pregnant women are more likely to be higher but ignored. All the departments of society should pay attention to the late pregnancy depressive symptoms of women in China.
In consideration of previously published studies, few studies investigated the association between pregnancy stress and depressive symptoms of Chinese pregnant women from different stress sources. Previous research has mainly evaluated the stress during pregnancy as a whole, and perceived psychological variables to explore its influencing factors (Tang et al. 2019) or relationship with other psychological variables (Kolomanska-Bogucka et al. 2022; Zhang et al. 2019). However, this study focused on the specific sources of stress and explored the relationship between stress and depressive symptoms from different dimensions. Relatively, factor 4 (worried about child care and marriage) and factor 2 (worried about maternal and child health and safety) were the top two factors associated with depressive symptoms. The participants in this study were expectant mothers with a gestation period of 36 weeks or more, and consideration might be given to a series of stress caused by the changes in their marital life as well as the safety of maternal and child health when and after the babies were born. A meta study on perinatal depression in the mainland of China also indicated that “the lack of confidence in child-care abilities” was related with perinatal depression (Nisar et al. 2020). Furthermore, COVID-19 is likely to increase the anxiety, insecurity, and stress levels of pregnant women (The American College of Obstetricians & Gynaecologists 2021). The main reason for the increased stress level was the concern about the underlying intrauterine transmission of COVID-19 to fetuses (Saccone et al. 2020). Generally, if the stress is not timely and effectively alleviated, which may lead to depressive symptoms (Nisar et al. 2020; Zhang et al. 2019). Such depressive symptoms may be alleviated after newborns are confirmed to be healthy and mothers feel able to take good care of their babies. However, it may affect the confidence of mothers in taking care of children and being eligible parents, cause other adverse consequences such as postpartum depression (Martinez-Borba et al. 2020), and affect the growth and development of children (Fredriksen et al. 2019).
Existing studies have not revealed that family relationships play a significant moderate role in the relationship between pregnancy stress (worried about maternal and child health and safety, child care and marriage) and depression symptoms. According to the stress-buffering model, environmental coping resources (i.e., social support) is important to reduce the correlation between stress and depression (Wheaton 1985). Family is one of the most important resources of social support (Lei and Kantor 2021) and family resilience (Simpkin et al. 2018), a better family relationship often represents higher family social support and family resilience. The attachment theory indicated that one’s emotional needs can be satisfied by warm and supportive parenting and a positive family atmosphere, leading to less preoccupation with one’s negative mental problems (Heard 1978). In accord with the attachment theory, a better family relationship may shape women’s beliefs about the acceptability and expression of emotions when they encounter pregnancy stress, at least stress from worrying about maternal and child health and safety, as well as child care and marriage, preventing the pregnancy stress switch to depressive symptoms. Therefore, it suggests that clinical practice should conduct family relationship-oriented interventions to facilitate family resilience and intra-family social support among pregnant females regulating their stress during pregnancy, with the goal to reduce depressive symptoms.
Extensive leisure hobbies play a significant moderate role in the relationship between pregnancy stress (worried about maternal and child health and safety, child care and marriage) and depression symptoms, which was not mentioned in previous studies. According to the stress-buffering model, personal coping resources or particular behavioral and/or cognitive strategies in coping is also of great importance to reducing the impact of exposure to stressors on depression (Wheaton 1985). In the context of the normalization of COVID-19 epidemic prevention and control, hospitalized pregnant women waiting for delivery may be required to stay in the hospital either with no accompanying family members or only one. At this point, it is very important for them to adjust to the stress by themselves. The restorative value of leisure hobbies is related to enhanced joyfulness and reduced emotional exhaustion and depression (Chiu et al. 2020). It has been indicated that leisure engagement could act on psychological pathways, including detachment and recovery, autonomy, mastery, meaning, and affiliation (Newman et al. 2014). In this study, when pregnant women are immersed in leisure activities, they may temporarily forget the various sources of stress during pregnancy, including a series of stress due to worrying about maternal and child health and safety as well as the marital life, which thus can restore their poor emotional state and refresh them through the restorative effect of leisure activities. In addition, leisure activities offer the perception of freedom and a sense of achievement by acquiring skills or overcoming challenges, which may be important for hospitalized expectant mothers who are briefly separated from society. Moreover, individuals can feel relaxed and happy in leisure activities while releasing dopamine, which is of importance to reduce the risk of depressive symptoms (Malhi and Berk 2007). Therefore, stress can be relieved and the risk of perinatal depressive symptoms can be decreased if women not only adjust their physical conditions during the pregnancy preparation period but also cultivate extensive leisure interests and hobbies, especially leisure activities conveniently done in late pregnancy, like calligraphy and reading.
What is already known on this topic
Women in low- and middle-income countries have a higher prevalence of perinatal depression than those in high-income ones. In the context of the normalization of the COVID-19 epidemic, the mental health of hospitalized late pregnancy women deserves more attention. In China, the prevalence of antenatal stress is approximately 90%. The relationship of higher level of stress and increased risk of depressive symptoms in the general population has been confirmed.
What this study adds
Four dimensions of pregnancy stress was found to increase the risk of depressive symptoms, respectively. Family relationship and leisure hobbies play a moderate role in associations of factor 2 (worried about maternal and child health and safety) and factor 4 (worried about child care and marriage) with depressive symptoms, respectively. In the context of the normalization of the COVID-19 epidemic, the mental health of hospitalized late pregnancy women deserves more attention. This study elucidates that pregnant specific stresses are common in late pregnancy women but are often overlooked by medical institutions in China. Family relationship and leisure hobbies play a moderate role in the associations of main stress with depressive symptoms, respectively. Therefore, mental health nursing should conduct family relationship-oriented interventions and women themselves can cultivate extensive leisure hobbies in the period of pregnancy preparation, which can relieve pregnancy stress and decrease the risk of perinatal depressive symptoms.
Study limitations
The major limitation of this study is the nature of the cross-sectional study, making it difficult to correlate causes with effects from the findings. In addition, the data were collected through self-reporting, which could yield recall biases as well.
Conclusions
Depressive symptoms in the late pregnancy of Chinese women remain to be improved. Pregnancy stress was associated with the increased risk of depressive symptoms in all dimensions. Family relationship and leisure hobbies play a moderate role in associations of factor 2 (worried about maternal and child health and safety) and factor 4 (worried about child care and marriage) with depressive symptoms, respectively. Therefore, family members should build and maintain good family relationships together to facilitate family resilience and intra-family social support. In addition, women themselves can cultivate extensive leisure hobbies during the period of pregnancy preparation, especially leisure activities conveniently done in late pregnancy, which can relieve pregnancy stress and decrease the risk of perinatal depressive symptoms.
Acknowledgements
The authors would like to acknowledge investigators, hospital leaders, and nurses for their support in the data collection. This study was supported by Science and Technology Department of Jilin Province, China (Grant Number: 20200101133FG). We also want to express our gratitude to the funder. The funder had no role in the study design, data collection or preparation of the manuscript.
Author’s contributions
Conceptualisation and study design: XMZ and HJL; data acquisition and management:
HFZ, HS, CC, ZR, XRL, YYL, YJP, LC, SXW, and JYZ; statistical analysis and data analysis: HFZ, HS, MFH, and XRL; manuscript drafting: HFZ; manuscript revision: XMZ, HJL, and MFH; final approval: all authors.
Funding
This study was supported by Science and Technology Department of Jilin Province, China (Grant Number: 20200101133FG).
Data availability
The datasets analyzed during the current study are available from the corresponding author on reasonable request.
Code availability
The code analyzed during the current study are available from the corresponding author on reasonable request.
Declarations
Ethics approval
This study gained the approval of the Research Ethical Committee of Jilin University School of Public Health. (Approval number: 2021-05-08). The date of approval was May 25, 2021.
Consent to participate
Informed consent was obtained from the participants.
Conflict of interest
The authors have no conflicts of interest to disclose.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The datasets analyzed during the current study are available from the corresponding author on reasonable request.
The code analyzed during the current study are available from the corresponding author on reasonable request.