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Article

Relationships between Depression, Fear of Childbirth, and Obsessive-Compulsive Symptoms among Pregnant Women under the COVID-19 Pandemic in Japan

by
Yuriko Usui
1,*,
Mizuki Takegata
2,
Satoru Takeda
3,4 and
Toshinori Kitamura
2,5,6,7
1
Department of Midwifery and Women’s Health, Division of Health Sciences and Nursing, Graduate School of Medicine, The University of Tokyo, Tokyo 113-0033, Japan
2
Kitamura Institute of Mental Health Tokyo, Tokyo 151-0063, Japan
3
Department of Obstetrics & Gynecology, Faculty of Medicine, Juntendo University, Tokyo 113-8421, Japan
4
Aiiku Research Institute for Maternal, Child Health and Welfare, Imperial Gift Foundation Boshi-Aiiku-Kai, Tokyo 106-0047, Japan
5
Kitamura KOKORO Clinic Mental Health, Tokyo 151-0063, Japan
6
T. and F. Kitamura Foundation for Studies and Skill Advancement in Mental Health, Tokyo 151-0063, Japan
7
Department of Psychiatry, Graduate School of Medicine, Nagoya University, Nagoya 464-0814, Japan
*
Author to whom correspondence should be addressed.
Healthcare 2023, 11(3), 361; https://doi.org/10.3390/healthcare11030361
Submission received: 3 December 2022 / Revised: 17 January 2023 / Accepted: 24 January 2023 / Published: 27 January 2023
(This article belongs to the Special Issue Perinatal Mental Health and Care)
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Abstract

:
Little is known about the causality of antenatal depression (AND). We focused on the causal relationships between AND, fear of childbirth (FOC), and obsessive-compulsive symptoms (OCS) during the COVID-19 pandemic in Japan. We also examined whether the perceived threat of COVID-19 is associated with AND. Participants were recruited for an Internet survey conducted in December 2020. A total of 245 pregnant women completed the online survey at 12 to 15 weeks’ gestational age (Time 1) and approximately 10 weeks later (Time 2). AND was estimated using the first two diagnostic items of Major Depressive Episode. The estimated prevalence of AND was 4.5% and 2.9% at Time 1 and Time 2, respectively. At both time points, no association was found between AND and the perception of COVID-19 threat. Structural equation modeling showed that AND predicted OCS (β = 0.16, p < 0.001), which, in turn, predicted FOC (β = 0.09, p = 0.042); FOC, in turn, predicted AND (β = 0.23, p < 0.001). AND, OCS, and FOC were predicted by borderline personality traits. Insecure adult attachment influenced AND and FOC via the perceived negative impact of the current pregnancy. Perinatal care providers should assess the personality and perception of pregnancy to prevent depression and pay attention to symptoms such as FOC and OCS in addition to those of depression.

1. Introduction

Depression often occurs among pregnant women. The pooled prevalence of AND identified by a meta-analysis was 20.7%, and that of major depression was 15% [1]. Several correlates of AND in previous studies were identified: primiparity, single motherhood, history of mental illness, unplanned and/or unwanted pregnancy, pregnancy complications, past history of abortion, early life experience such as loss of father, vulnerable personality such as neuroticism and anxiety traits, being exposed to domestic violence, lack of social support, and poor intimacy with the husband [2,3,4,5]. It is of note that these variables are not mutually independent.
Out of the correlates, poor relationship with the partner or being exposed to domestic violence would be strongly contributing to the onset of perinatal depression [2,3]. Considering pregnancy is a life stage in which interpersonal relationships, particularly with a partner, play a critical role preparing for childbirth and child rearing [6]. The person whom pregnant women seek support the most is her partner [7], and the partner’s support contributes to the mental health of pregnant women [8]. Although poor interrelationship is caused by the malfunctional interaction between individuals with different personality [9], it is speculated that a woman with an insecure attachment style would underlie the poor relationship among the couple, leading to the occurrence of AND.
Furthermore, insecure attachment to a partner may be associated with maladaptive personality traits. Special attention may be necessary for individuals with borderline personality traits. Borderline personality disorder, which occurs in approximately 1.4% of the general population [10], is one of the most prevalent personality disorders [11]. People with borderline personality disorder are often accompanied by a variety of mood and anxiety disorders. Hence, there may be a strong association between insecure adult attachment to a partner, borderline personality, and AND.
Recent research indicates that fear of childbirth (FOC) is frequently observed among pregnant women. Reportedly, 6–14% of pregnant women expressed severe FOC [12]. Women with FOC are afraid of pain, unpredicted complications such as bleeding, and uncontrollable situations [13,14] (Nilsson & Lundgren, 2009; Takegata et al., 2018). Studies have reported that FOC and depression coexist [15,16,17]; hence, FOC should not be dismissed when considering the correlates of AND.
Furthermore, a recent systematic review and meta-analysis reported that the onset of obsessive-compulsive disorders (OCDs) during pregnancy is not uncommon, and that 13–39% of women with OCD develop the disorder during their pregnancy [18]. Depression frequently accompanies obsessive-compulsive symptoms (OCS) [19,20]. The coronavirus 2019 (COVID-19) pandemic may worsen these fears and obsessions in pregnant women who are already affected by FOC or OCS, and their aggravation may affect AND. Hence, our primary interest was to investigate the causal relationships between AND, FOC, and OCS among pregnant women. We were also interested in the effects of adult attachment style and borderline personality traits on the above relationships.
The COVID-19 outbreak began worldwide in February 2020. In Japan, most obstetric facilities canceled or restricted perinatal classes with the COVID-19 pandemic; thus, pregnant women were less likely to obtain support from healthcare providers. Since the outbreak of COVID-19, reports have been inconsistent in terms of the prevalence of perinatal depression during the pandemic: some have shown an increased prevalence of perinatal depression [21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40], whereas others have refuted this or have reported a decrease in depression [41,42,43,44,45]. Disastrous events, such as the COVID-19 pandemic, are often followed by psychological maladjustment of individuals exposed to them (e.g., [46]). A risk factor related to disaster-induced psychological maladjustment is perceiving the event as having adversely affected one’s health. Residents in an area near a nuclear power plant accident (Three Mile Island; TMI) showed no increase in episodes of depression or anxiety as compared with those living in an area near a nuclear plant without an accident. However, those who manifested an episode of depression or anxiety, as compared with those who did not, were more likely to view the situation at TMI as currently dangerous, believe that living near a nuclear facility was unsafe, and had young children in the house [47]. Hence, another research question was whether the perceived threat of COVID-19 is associated with AND among the Japanese population.

2. Methods

2.1. Study Procedure and Participants

This Internet survey was conducted with pregnant women at 12–15 weeks’ gestational age (Time 1: T1). No exclusion criteria were used except for a lack of command on Japanese reading. The T1 survey was conducted for two weeks, from 7 to 21 December 2020, via the Internet applications called Luna Luna and Luna Luna Baby (MTI Ltd., Tokyo, Japan). Anonymity was assured, and participation was voluntary. The main questionnaire was preceded by an information page, with the aims of the study, affiliations, information about informed consent, and the address of the consultation desk for the research. Participants were asked to enter their email address after completing the survey to merge the data of T1 and T2 only by means of mail address. The participants were incentivized with electronic money points usable for Amazon shopping via the MTI Ltd (MTI Ltd., Tokyo, Japan).
The same participants were invited to participate in the Time 2 (T2) study approximately 10 weeks later (22–35 gestational weeks) in March 2021. As compared with the women who declined to participate in the T2 survey, those who participated in the T2 survey were slightly but significantly older (32.2 vs. 31.4 years, p < 0.05), and their gestational age was less advanced (13.2 vs. 13.4, p < 0.05). The two groups of women did not significantly differ otherwise. The period was at the beginning of the fourth wave of the COVID-19 pandemic. The same questionnaires were used, except for basic demographic and obstetric variables. Because this Internet survey set the items as forced questions, there was no missing value.

2.2. Measurements

Depression: The first two symptoms of Major Depressive Episode (MDE)―depressed mood and lack of interest—were observed to detect depression. Each item was rated on a 4-point scale: 0 = none, 1 = a few days a week, 2 = more than half a week, and 3 = almost every day. This was based on research showing that the set of two questions would predict MDE reasonably well [48,49,50,51,52,53,54,55]. As a rough indicator of MDE, we defined MDE at both time periods if either or both of the two items (depressed mood and lack of interest) were rated as present almost every day for the previous 2 weeks. In this study, Cronbach’s α coefficients were 0.83 at T1 and 0.79 at T2.
Borderline personality traits: The participant’s borderline personality trait was rated on the short version (IPO-SV) [56] of the Personality Organisation Inventory (IPO) [57]. The IPO-SV has nine items on a 7-point scale with three subscales: primitive defense (PD), identity diffusion (ID), and reality testing (RT) disturbance. In this study, Cronbach’s α coefficients of the PD, ID, and RT subscales were 0.71, 0.78, and 0.87, respectively.
Adult attachment: The participants’ attachment toward their partners was rated using the Japanese version [58] of the Relationship Questionnaire (RQ) [59]. The RQ has four items answered on a 7-point scale. The four items describe different styles of adult attachment: Secure, Fearful, Preoccupied, and Dismissing. The total score was calculated by adding the scores of Fearful, Preoccupied, and Dismissing, which was then subtracted by the score of Secure. A higher score indicates a more insecure attachment style. In this study, Cronbach’s α coefficient was 0.65.
Perceived impact of pregnancy: The participants’ perception of the impact of the current pregnancy was rated by a single ad hoc item; ‘Mark a point for the influence of the current pregnancy upon you from −100 to 100.’ and ‘Mark positive points if it is good, joyful, and happy, whereas mark negative points if it is awful, perplexing, and unhappy.’
Demographic and obstetric variables: We asked the participant’s age, number of past pregnancies, number of past deliveries, infertility treatment, and marital status (single/married).
Antenatal fear of childbirth: We used the Japanese version [60] of the Wijma Delivery Expectancy/Experience Questionnaire [61]. It consists of 33 items rated on a 5-point scale. A higher score indicates more severe FOC. Item 31 was erroneously deleted in the present study. In this study, Cronbach’s α coefficients were 0.91 at T1 and 0.91 at T2.
Obsessive-compulsive symptoms: Obsessive and compulsive symptoms were rated using the Japanese version [62] of the Obsessive-Compulsive Inventory—Revised (OCI-R) [63]. The OCI-R comprises 18 items with a 5-point scale. In this study, we changed the grading from 5-point to 7-point. In this study, Cronbach’s α coefficients were 0.89 at T1 and 0.90 at T2.
Perceived threat of COVID-19: We used ad hoc questions. This was rated using three items on a 7-point Likert scale from not at all true = 0 to very much true = 6: “potentially dangerous”, “not serious unless aged or with choric disease (reverse)”, and “OK because I am immune (reverse)”. In this study, Cronbach’s α coefficient was 0.67.

2.3. Data Analysis

After examining the means, standard deviations (SDs), skewness, and kurtosis of all the variables studied in the present investigation, we correlated the T1 and T2 depression scores with the scores of the other explanatory variables. We set the alpha value to p < 0.001 due to multiple comparisons. Then, using the variables that were significantly correlated with T1 and T2 depression scores, we set a non-recursive structural regression model in the framework of structural equation modeling (SEM) (Figure 1). Here, we posited four latent variables: borderline personality traits, adult attachment, and two depressions at T1 and T2. We hypothesized that OCS, FOC, and depression at T1 were all predicted by borderline personality traits and adult attachment that were mediated by the perceived impact of the present pregnancy. Borderline personality traits and adult attachment were correlated. OCS, FOC, and depression at T1 were correlated with each other, and all predicted their own scores at T2. At T2, OCS, FOC, and depression predicted each other, making a non-recursive loop (Figure 1). The goodness of fit of this model was rated by χ2, comparative fit index (CFI), and root mean square error appropriation (RMSEA). A good fit was defined as χ2/df < 2, CFI > 0.97, and RMSEA < 0.05. An acceptable fit was defined as χ2/df < 3, CFI > 0.95, and RMSEA < 0.08 [64,65]. After confirming that the model fit was good, we performed model trimming in which the least significant path was deleted one by one until (a) no non-significant path remained to be deleted, (b) the model’s solution was inappropriate, or (c) the model fit was no longer good. Statistical analyses were performed using IBM SPSS version 28.0 and Amos version 28.0 software for Windows (IBM Japan, Tokyo, Japan).

2.4. Ethical Considerations

This study was approved by the Institutional Review Board (IRB) of the Kitamura Institute of Mental Health, Tokyo (No. 2020101501). All participants provided electrical informed consent after understanding the study rationale and procedure. The authors assert that all procedures that contributed to this study complied with the ethical standards of the National and Institutional Committees on Human Experimentation and with the 1975 Declaration of Helsinki as revised in 2008.

3. Results

Of the 696 pregnant women who participated in T1, data from 245 (35.2%) who participated in T2 were used in the analysis.
Although AND, FOC, and OCS were correlated with each other at both T1 and T2, none of them were correlated with the perceived threat of COVID-19 (Table 1).
The prevalence of MDE was 4.5% and 2.9% at T1 and T2, respectively. Of the 11 women identified as having MDE at T1, 9 (82%) still had MDE at T2. Of the 234 women who did not have MDE at T1, 5 (2.1%) had MDE at T2. T1 and T2 depression scores were both significantly correlated with borderline personality traits, insecure adult attachment, perceived impact of the current pregnancy, and T1 and T2 W-DEQ and OCI-R (Table 2).
The initial model showed a good fit: χ2/df = 1.351, CFI = 0.984, and RMSEA = 0.038. This persisted after model trimming: χ2/df = 1.337, CFI = 0.983, and RMSEA = 0.037 (Figure 2). The trimmed SEM model showed that T1 OCS, FOC, and depression were predicted by borderline personality traits. T1 FOC and depression were predicted by (insecure) adult attachment and mediated only by the (negative) perceived impact of the present pregnancy. At T2, depression was predicted using FOC. Depression then predicted OCS, which, in turn, predicted FOC. Hence, a circuit of prediction appeared. The direction of prediction was not found the other way round.

4. Discussion

The use of a non-recursive model in which OCS, FOC, and depression were set to statistically predict each other was unique to this study. It is of note that our study examined the correlations between the target variables at one time point as well as between the two time points; we used "influence" and "predict" only as statistical terms but did not necessarily indicate real causality. We cannot be more cautious about unseen confounders and mediators. We found relationships from FOC to depression, depression to OCS, and OCS to FOC. The directions the other way round were not significant. The W-DEQ comprises four components, one of which is isolation. Isolation is a risk factor for depression, especially during the COVID-19 pandemic, where it is difficult to have contact with other people [66]. Care for women with FOC, including pregnant women who have feelings of isolation, may prevent depression. Additionally, the SEM showed that depression predicted OCS. Since OCS at T2 was strongly influenced by T1 OCS, we interpret that persistent OCS stems from the first trimester, which is further aggravated by depression. Therefore, this result suggests that healthcare providers should carefully assess depression together with FOC and OCS, and consider how to approach expectant women with them taking into account the directions in which they affect each other.
Our results showed that borderline personality traits directly predicted AND. A recent meta-analysis estimated the prevalence of borderline personality traits during pregnancy in non-clinical samples to be 6.9–26.7% [67]. The existence of borderline personality is not rare among pregnant women, indicating the importance of identifying women with borderline personality before and early in pregnancy, and of preventing and caring for depression. Furthermore, borderline personality predicted not only depression but also FOC. A previous study reported that pregnant women with borderline personality traits expected childbirth to be traumatic and requested to give birth early [68]. In the perinatal period, it is important to care for women for not only depression but also FOC and OCS; for this, it is essential to assess their personality.
Although previous studies have reported that insecure attachment styles influence depression [69,70], this study found that insecure attachment styles are associated with more negative perceptions of pregnancy, which is more likely to lead to depression. In Japan, a birth debriefing generally provides women with an opportunity to talk about their birth experience with the midwife who assisted in the delivery to promote a positive perception of birth, but there are no routine opportunities to review the perception of pregnancy. Providing care that involves listening carefully to pregnant women about their perception of the current pregnancy is needed.
In this study, the prevalence of MDE was 4.5% and 2.9% at T1 and T2, respectively. Kitamura et al. (2006) conducted an epidemiological survey of 290 Japanese pregnant women using a structured diagnostic interview and reported a 5.9% incidence of Diagnostic and Statistical Manual of Mental Disorders—III-R (DSM-III-R) MDE in early pregnancy [71]. Considering that the current study relied only on the presence of two core symptoms of MDE at the time of investigation for diagnosing MDE, we assume that the prevalence of perinatal depression remained unchanged before and after COVID-19 or at least did not increase, as reported in other studies. Matsushima et al. (2022) reported that the point prevalence of AND was 17% among 1777 Japanese pregnant women [33]. The discrepancy between the study and our study may be due to the use of different scales used for identifying depression (the core two symptoms of DSM-5 and the Edinburgh Postnatal Depression Scale; EPDS). The EPDS comprises three factors: anhedonia, anxiety, and depression [72,73]. Therefore, it is likely that the pregnant women in the previous study scored high only on anxiety. A second reason may be the differences in assessment points; the research period of our study was in the middle of the second wave of the COVID-19 pandemic, whereas Matsushima et al.’s (2022) study was after the first wave. Therefore, perceived psychological stress/threats may have been desensitized during the pandemic period.
AND was not predicted by the perceived threat of COVID-19 in our study. Although in disastrous events such as a nuclear power station meltdown, the perceived threat is a predictor of psychological maladjustment, our expectant women seemed to be immune to the threat of infection. This may be due to the fact that the magnitude of the infection was much lower in Japan than in other countries.
There were limitations to this study. First, the scale to assess the threat of COVID-19 was ad hoc, and its validity and reliability have not yet been confirmed. Second, as this was an online study design, the response rate was low, and the characteristics of the sample might not be representative of all Japanese pregnant women. The incidence of AND was based on the presence or absence of the two core MDE symptoms. A more detailed assessment of all MDE symptoms is desirable. Regardless, the current study is the first to identify the circular causality between AND, FOC, and OCS, as well as the effects of borderline personality traits and insecure adult attachment on them among the Japanese population. This implies the importance of a full understanding of women’s personality traits, which precede the occurrence of mental disorders during pregnancy.

5. Conclusions

By means of a non-recursive SEM among Japanese pregnant women, we aimed to understand the causal relationships between borderline personality traits and adult attachment with FOC, OCS, and AND, as well as circular influences from AND through OCS to FOC and, in turn, predicting AND. However, no association was found between AND and the perception of COVID-19 threat.

Author Contributions

Conceptualization, T.K.; Methodology, S.T. and T.K.; Formal analysis, Y.U. and T.K.; Investigation, T.K.; Writing – original draft, Y.U., M.T. and T.K. All authors have read and agreed to the published version of the manuscript.

Funding

The present study was funded by Health, Labour and Welfare Policy Research Grants: Special research: The Effects of Self-Restraint under the Novel Coronavirus Infection (COVID-19) Epidemic: A Survey on Unexpected Pregnancy, etc. and Research to Establish an Appropriate Support System for Women’s Health (20CA2062; Principal Researcher-Tomoko Adachi).

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki, and approved by the Institutional Review Board of the Kitamura Institute of Mental Health Tokyo (No. 2020101501).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The datasets used and analyzed in this study are available from the corresponding author upon reasonable request.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Yin, X.; Sun, N.; Jiang, N.; Xu, X.; Gan, Y.; Zhang, J.; Qiu, L.; Yang, C.; Shi, X.; Chang, J.; et al. Prevalence and associated factors of antenatal depression: Systematic reviews and meta-analyses. Clin. Psychol. Rev. 2021, 83, 101932. [Google Scholar] [CrossRef]
  2. Biaggi, A.; Conroy, S.; Pawlby, S.; Pariante, C.M. Identifying the women at risk of antenatal anxiety and depression: A systematic review. J. Affect. Disord. 2016, 191, 62–77. [Google Scholar] [CrossRef] [Green Version]
  3. Orsolini, L.; Valchera, A.; Vecchiotti, R.; Tomasetti, C.; Iasevoli, F.; Fornaro, M.; Berardis, D.; de Perna, G.; Pompili, M.; Bellantuono, C. Suicide during perinatal period: Epidemiology, risk factors, and clinical correlates. Front. Psychiatry 2016, 7, 1–6. [Google Scholar] [CrossRef] [Green Version]
  4. Kitamura, T.; Shima, S.; Sugawara, M.; Toda, M.A. Clinical and psychosocial correlates of antenatal depression: A review. Psychother. Psychosom. 1996, 65, 117–123. [Google Scholar] [CrossRef]
  5. Minatani, M.; Kita, S.; Ohashi, Y.; Kitamura, T.; Haruna, M.; Sakanashi, K.; Tanaka, T. Temperament, character, and depressive symptoms during pregnancy: A study of a Japanese population. Depress. Res. Treat. 2013, 140169. [Google Scholar] [CrossRef] [Green Version]
  6. Takegata, M.; Ohashi, Y.; Haruna, M.; Kitamura, T. Theoretical framework for interper-sonal psychotherapy in the prevention of post-partum depression: A commentary. Int. J. Nurs. Sci. 2014, 1, 37–40. [Google Scholar]
  7. Kitamura, T.; Toda, M.A.; Shima, S.; Sugawara, K.; Sugawara, M. Social support and pregnancy: I. Factorial structure and psychosocial correlates of perceived social support. Psychiatry Clin. Neurosci. 1998, 52, 29–36. [Google Scholar] [CrossRef]
  8. Kitamura, T.; Toda, M.A.; Shima, S.; Sugawara, K.; Sugawara, M. Social support and pregnancy: II. Its relationship with depressive symptoms among Japanese women. Psychiatry Clin. Neurosci. 1998, 52, 37–45. [Google Scholar] [CrossRef]
  9. Chen, Z.; Tanaka, N.; Uji, M.; Hiramura, H.; Shikai, N.; Fujihara, S.; Kitamura, T. The role of personality for marital adjustment of Japanese couples. Soc. Behav. Pers. 2007, 35, 561–572. [Google Scholar] [CrossRef]
  10. Quirk, S.E.; Berk, M.; Pasco, J.A.; Brennan-Olsen, S.L.; Chanen, A.M.; Koivumaa-Honkanen, H.; Burke, L.M.; Jackson, H.J.; Hulbert, C.; Olsson, C.A.; et al. The prevalence, age distribution and comorbidity of personality disorders in Australian women. Aust. N. Z. J. Psychiatry 2017, 51, 141–150. [Google Scholar] [CrossRef] [Green Version]
  11. Lenzenweger, M.F.; Lane, M.C.; Loranger, A.W.; Kessler, R.C. DSM-IV Personality Disorders in the National Comorbidity Survey Replication. Biol. Psychiatry 2007, 62, 553–564. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  12. Nilsson, C.; Hessman, E.; Sjöblom, H.; Dencker, A.; Jangsten, E.; Mollberg, M.; Patel, H.; Sparud-Lundin, C.; Wigert, H.; Begley, C. Definitions, measurements and prevalence of fear of childbirth: A systematic review. BMC Pregnancy Childbirth 2018, 18, 28. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  13. Nilsson, C.; Lundgren, I. Women’s lived experience of fear of childbirth. Midwifery 2009, 25, e1–e9. [Google Scholar] [CrossRef] [PubMed]
  14. Takegata, M.; Haruna, M.; Morikawa, M.; Yonezawa, K.; Komada, M.; Severinsson, E. Qualitative exploration of fear of childbirth and preferences for mode of birth among Japanese primiparas. Nurs. Health Sci. 2018, 20, 338–345. [Google Scholar] [CrossRef]
  15. Pettersson, F.D.; Hellgren, C.; Nyberg, F.; Åkerud, H.; Sundström-Poromaa, I. Depressed mood, anxiety, and the use of labor analgesia. Arch. Womens Ment. Health 2016, 19, 11–16. [Google Scholar] [CrossRef]
  16. Rondung, E.; Thomtén, J.; Sundin, Ö. Psychological perspectives on fear of childbirth. J. Anxiety Disord. 2016, 44, 80–91. [Google Scholar] [CrossRef] [Green Version]
  17. Storksen, H.T.; Eberhard-Gran, M.; Garthus-Niegel, S.; Eskild, A. Fear of childbirth; The relation to anxiety and depression. Acta Obstet. Gynecol. Scand. 2012, 91, 237–242. [Google Scholar] [CrossRef]
  18. Viswasam, K.; Eslick, G.D.; Starcevic, V. Prevalence, onset and course of anxiety disorders during pregnancy: A systematic review and meta analysis. J. Anxiety Disord. 2019, 255, 27–40. [Google Scholar] [CrossRef]
  19. Miller, E.S.; Hoxha, D.; Wisner, K.L.; Gossett, D.R. The impact of perinatal depression on the evolution of anxiety and obsessive-compulsive symptoms. Arch. Womens Ment. Health 2015, 18, 457–461. [Google Scholar] [CrossRef]
  20. Wisner, K.L.; Sit, D.K.Y.; McShea, M.C.; Rizzo, D.M.; Zoretich, R.A.; Hughes, C.L.; Eng, H.F.; Luther, J.F.; Wisniewski, S.R.; Costantino, M.L.; et al. Onset timing, thoughts of self-harm, and diagnoses in postpartum women with screen-positive depression findings. JAMA Psychiatry 2013, 70, 490–498. [Google Scholar] [CrossRef]
  21. Ayaz, R.; Hocaoǧlu, M.; Günay, T.; Yardlmcl, O.D.; Turgut, A.; Karateke, A. Anxiety and depression symptoms in the same pregnant women before and during the COVID-19 pandemic. J. Perinat. Med. 2020, 48, 965–970. [Google Scholar] [CrossRef] [PubMed]
  22. Berthelot, N.; Lemieux, R.; Garon-Bissonnette, J.; Drouin-Maziade, C.; Martel, É.; Maziade, M. Uptrend in distress and psychiatric symptomatology in pregnant women during the coronavirus disease 2019 pandemic. Acta Obstet. Gynecol. Scand. 2020, 99, 848–855. [Google Scholar] [CrossRef] [PubMed]
  23. Ceulemans, M.; Hompes, T.; Foulon, V. Mental health status of pregnant and breastfeeding women during the COVID-19 pandemic: A call for action. Int. J. Gynecol. Obstet. 2020, 151, 146–147. [Google Scholar] [CrossRef]
  24. Dagklis, T.; Tsakiridis, I.; Mamopoulos, A.; Athanasiadis, A.; Pearson, R.; Papazisis, G. Impact of the COVID-19 lockdown on antenatal mental health in Greece. Psychiatry Clin. Neurosci. 2020, 74, 616–617. [Google Scholar] [CrossRef] [PubMed]
  25. Dib, S.; Rougeaux, E.; Vázquez-Vázquez, A.; Wells, J.C.K.; Fewtrell, M. Maternal mental health and coping during the COVID-19 lockdown in the UK: Data from the COVID-19 New Mum Study. Int. J. Gynecol. Obstet. 2020, 151, 407–414. [Google Scholar] [CrossRef]
  26. Farewell, C.V.; Jewell, J.; Walls, J.; Leiferman, J.A. A Mixed-Methods Pilot Study of Perinatal Risk and Resilience During COVID-19. J. Prim. Care Community Health 2020, 11. [Google Scholar] [CrossRef]
  27. Farrell, T.; Reagu, S.; Mohan, S.; Elmidany, R.; Qaddoura, F.; Ahmed, E.E.; Corbett, G.; Lindow, S.; Abuyaqoub, S.M.; Alabdulla, M.A. The impact of the COVID-19 pandemic on the perinatal mental health of women. J. Perinat. Med. 2020, 48, 971–976. [Google Scholar] [CrossRef]
  28. Fukase, Y.; Ichikura, K.; Murase, H.; Tagaya, H. Depression, risk factors, and coping strategies in the context of social dislocations resulting from the second wave of COVID-19 in Japan. BMC Psychiatry 2021, 21, 33. [Google Scholar] [CrossRef]
  29. Gur, R.E.; White, L.K.; Waller, R.; Barzilay, R.; Moore, T.M.; Kornfield, S.; Njoroge, W.F.M.; Duncan, A.F.; Chaiyachati, B.H.; Parish-Morris, J.; et al. The Disproportionate Burden of the COVID-19 Pandemic Among Pregnant Black Women. Psychiatry Res. 2020, 293, 113475. [Google Scholar] [CrossRef]
  30. Liang, P.; Wang, Y.; Shi, S.; Liu, Y.; Xiong, R. Prevalence and factors associated with postpartum depression during the COVID-19 pandemic among women in Guangzhou, China: A cross-sectional study. BMC Psychiatry 2020, 20, 557. [Google Scholar] [CrossRef]
  31. Liu, C.H.; Erdei, C.; Mittal, L. Risk factors for depression, anxiety, and PTSD symptoms in perinatal women during the COVID-19 Pandemic. Psychiatry Res. 2021, 295, 113552. [Google Scholar] [CrossRef] [PubMed]
  32. López-Morales, H.; del Valle, M.V.; Canet-Juric, L.; Andrés, M.L.; Galli, J.I.; Poó, F.; Urquijo, S. Mental health of pregnant women during the COVID-19 pandemic: A longitudinal study. Psychiatry Res. 2021, 295, 113567. [Google Scholar] [CrossRef] [PubMed]
  33. Matsushima, M.; Horiguchi, H. The COVID-19 pandemic and mental well-being of pregnant women in Japan: Need for Economic and Social Policy interventions. Disaster Med. Public Health Prep. 2022, 16, 449–454. [Google Scholar] [CrossRef] [PubMed]
  34. Molgora, S.; Accordini, M. Motherhood in the Time of Coronavirus: The Impact of the Pandemic Emergency on Expectant and Postpartum Women’s Psychological Well-Being. Front. Psychol. 2020, 11, 1–16. [Google Scholar] [CrossRef]
  35. Parra-Saavedra, M.; Villa-Villa, I.; Pérez-Olivo, J.; Guzman-Polania, L.; Galvis-Centurion, P.; Cumplido-Romero, Á.; Santacruz-Vargas, D.; Rivera-Moreno, E.; Molina-Giraldo, S.; Guillen-Burgos, H.; et al. Attitudes and collateral psychological effects of COVID-19 in pregnant women in Colombia. Int. J. Gynecol. Obstet. 2020, 151, 203–208. [Google Scholar] [CrossRef] [PubMed]
  36. Qi, M.; Li, X.; Liu, S.; Li, Y.; Huang, W. Impact of the COVID-19 epidemic on patterns of pregnant women’s perception of threat and its relationship to mental state: A latent class analysis. PLoS ONE 2020, 15, e0239697. [Google Scholar] [CrossRef] [PubMed]
  37. Ravaldi, C.; Ricca, V.; Wilson, A.; Homer, C.; Vannacci, A. Previous psychopathology predicted severe COVID-19 concern, anxiety, and PTSD symptoms in pregnant women during “lockdown” in Italy. Arch. Womens Ment. Health 2020, 23, 783–786. [Google Scholar] [CrossRef]
  38. Spinola, O.; Liotti, M.; Speranza, A.M.; Tambelli, R. Effects of COVID-19 Epidemic Lockdown on Postpartum Depressive Symptoms in a Sample of Italian Mothers. Front. Psychiatry 2020, 11, 1–10. [Google Scholar] [CrossRef]
  39. Wang, Y.; Chen, L.; Wu, T.; Shi, H.; Li, Q.; Jiang, H.; Zheng, D.; Wang, X.; Wei, Y.; Zhao, Y.; et al. Impact of Covid-19 in pregnancy on mother’s psychological status and infant’s neurobehavioral development: A longitudinal cohort study in China. BMC Med. 2020, 18, 347. [Google Scholar] [CrossRef]
  40. Wu, Y.; Zhang, C.; Liu, H.; Duan, C.; Li, C.; Fan, J.; Li, H.; Chen, L.; Xu, H.; Li, X.; et al. Perinatal depressive and anxiety symptoms of pregnant women during the coronavirus disease 2019 outbreak in China. Am. J. Obstet. Gynecol. 2020, 223, 240.e1–240.e9. [Google Scholar] [CrossRef]
  41. Hessami, K.; Romanelli, C.; Chiurazzi, M.; Cozzolino, M. COVID-19 pandemic and maternal mental health: A systematic review and meta-analysis. J. Matern. Neonatal Med. 2020, 35, 4014–4021. [Google Scholar] [CrossRef]
  42. Sade, S.; Sheiner, E.; Wainstock, T.; Hermon, N.; Salem, S.Y.; Kosef, T.; Battat, T.L.; Oron, S.; Pariente, G. Risk for depressive symptoms among hospitalized women in high-risk pregnancy units during the COVID-19 pandemic. J. Clin. Med. 2020, 9, 2449. [Google Scholar] [CrossRef]
  43. Silverman, M.E.; Medeiros, C.; Burgos, L. Early pregnancy mood before and during COVID-19 community restrictions among women of low socioeconomic status in New York City: A preliminary study. Arch. Womens Ment. Health 2020, 23, 779–782. [Google Scholar] [CrossRef]
  44. Yan, H.; Ding, Y.; Guo, W. Mental Health of Pregnant and Postpartum Women During the Coronavirus Disease 2019 Pandemic: A Systematic Review and Meta-Analysis. Front. Psychol. 2020, 11, 1–12. [Google Scholar] [CrossRef]
  45. Zhou, Y.; Shi, H.; Liu, Z.; Peng, S.; Wang, R.; Qi, L.; Li, Z.; Yang, J.; Ren, Y.; Song, X.; et al. The prevalence of psychiatric symptoms of pregnant and non-pregnant women during the COVID-19 epidemic. Transl. Psychiatry 2020, 10, 319. [Google Scholar] [CrossRef] [PubMed]
  46. Bromet, E.J.; Havenaar, J.M. Psychological and perceived health effects of the chernobyl disaster: A 20-year review. Health Phys. 2007, 93, 516–521. [Google Scholar] [CrossRef]
  47. Bromet, E.; Schulberg, H.C.; Dunn, L. Reactions of Psychiatric Patients to the Three Mile Island Nuclear Accident. Arch. Gen. Psychiatry 1982, 39, 725–730. [Google Scholar] [CrossRef]
  48. Bowling, A. Just one question: If one question works, why ask several? J. Epidemiol. Community Health 2005, 59, 342–345. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  49. Chochinov, H.M.; Wilson, K.G.; Enns, M.; Lander, S. “Are you depressed?” Screening for depression in the terminally ill. Am. J. Psychiatry 1997, 154, 674–676. [Google Scholar] [CrossRef]
  50. Cutler, C.B.; Legano, L.A.; Dreyer, B.P.; Fierman, A.H.; Berkule, S.B.; Lusskin, S.I.; Tomopoulos, S.; Roth, M.; Mendelsohn, A.L. Screening for maternal depression in a low education population using a two item questionnaire. Arch. Womens Ment. Health 2007, 10, 277–283. [Google Scholar] [CrossRef]
  51. De Boer, A.G.E.M.; van Lanschot, J.J.B.; Stalmeier, P.F.M.; van Sandick, J.W.; Hulscher, J.B.F.; de Haes, J.C.J.M.; Sprangers, M.A.G. Is a single-item visual analogue scale as valid, reliable and responsive as multi-item scales in measuring quality of life? Qual. Life Res. 2004, 13, 311–320. [Google Scholar] [CrossRef]
  52. Mitchell, A.J. Are one or two simple questions sufficient to detect depression in cancer and palliative care? A Bayesian meta-analysis. Br. J. Cancer 2008, 98, 1934–1943. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  53. Mishina, H.; Hayashino, Y.; Fukuhara, S. Test performance of two-question screening for postpartum depressive symptoms. Pediatr. Int. 2009, 51, 48–53. [Google Scholar] [CrossRef]
  54. Mitchell, A.J.; Coyne, J.C. Do ultra-short screening instruments accurately detect depression in primary care? A pooled analysis and meta- analysis of 22 studies. Br. J. Gen. Pract. 2007, 57, 144–151. [Google Scholar]
  55. Richardson, L.P.; Rockhill, C.; Russo, J.E.; Grossman, D.C.; Richards, J.; McCarty, C.; McCauley, E.; Katon, W. Evaluation of the PHQ-2 as a brief screen for detecting major depression among adolescents. Pediatrics 2010, 125, e1097–e1103. [Google Scholar] [CrossRef] [Green Version]
  56. Yamada, F.; Kataoka, Y.; Kitamura, T. Development and Validation of a Short Version of the Primary Scales of the Inventory of Personality Organization: A Study among Japanese University Students. Psychology 2022, 13, 872–890. [Google Scholar] [CrossRef]
  57. Kernberg, O.F.; Clarkin, J.F. The Inventory of Personality Organization; The New York Hospital Cornell Medical Center: New York, NY, USA, 1995. [Google Scholar]
  58. Matsuoka, N.; Uji, M.; Hiramura, H.; Chen, Z.; Shikai, N.; Kishida, Y.; Kitamura, T. Adolescents’ attachment style and early experiences: A gender difference. Arch. Womens Ment. Health 2006, 9, 23–29. [Google Scholar] [CrossRef]
  59. Bartholomew, K.; Horowitz, L.M. Attachment Styles Among Young Adults: A Test of a Four-Category Model. J. Pers. Soc. Psychol. 1991, 61, 226–244. [Google Scholar] [CrossRef]
  60. Takegata, M.; Haruna, M.; Matsuzaki, M.; Shiraishi, M.; Murayama, R.; Okano, T.; Severinsson, E. Translation and validation of the Japanese version of the Wijma Delivery Expectancy/Experience Questionnaire version A. Nurs. Health Sci. 2013, 15, 326–332. [Google Scholar] [CrossRef]
  61. Wijma, K.; Wijma, B.; Zar, M. Psychometric aspects of the W-DEQ; A new questionnaire for the measurement of fear of childbirth. J. Psychosom. Obstet. Gynaecol. 1998, 19, 84–97. [Google Scholar] [CrossRef]
  62. Koike, H.; Tsuchiyagaito, A.; Hirano, Y.; Oshima, F.; Asano, K.; Sugiura, Y.; Kobori, O.; Ishikawa, R.; Nishinaka, H.; Shimizu, E.; et al. Reliability and validity of the Japanese version of the Obsessive-Compulsive Inventory-Revised (OCI-R). Curr. Psychol. 2020, 39, 89–95. [Google Scholar] [CrossRef]
  63. Foa, E.B.; Huppert, J.D.; Leiberg, S.; Langner, R.; Kichic, R.; Hajcak, G.; Salkovskis, P.M. The obsessive-compulsive inventory: Development and validation of a short version. Psychol. Assess. 2020, 14, 485–496. [Google Scholar] [CrossRef]
  64. Bentler, P.M. Comparative fit indexes in structural models. Psychol. Bull. 1990, 107, 238–246. [Google Scholar] [CrossRef] [PubMed]
  65. Schermelleh-Engel, K.; Moosbrugger, H.; Müller, H. Evaluating the fit of structural equation models: Tests of significance and descriptive goodness-of-fit measures. Methods Psychol. Res. Online 2003, 8, 23–74. [Google Scholar]
  66. Lebel, C.; Mackinnon, A.; Bagshawe, M.; Anna, M. Elevated depression and anxiety symptoms among pregnant individuals during the COVID-19 pandemic. J. Affect. Disord. 2020, 277, 5–13. [Google Scholar] [CrossRef]
  67. Prasad, D.; Kuhathasan, N.; de Azevedo Cardoso, T.; Suh, J.S.; Frey, B.N. The prevalence of borderline personality features and borderline personality disorder during the perinatal period: A systematic review and meta-analysis. Arch. Womens Ment. Health 2020, 25, 227–289. [Google Scholar] [CrossRef]
  68. Blankley, G.; Galbally, M.; Snellen, M.; Power, J.; Lewis, A.J. Borderline Personality Disorder in the perinatal period: Early infant and maternal outcomes. Australas. Psychiatry 2015, 23, 688–692. [Google Scholar] [CrossRef]
  69. Monk, C.; Leight, K.L.; Fang, Y. The relationship between women’s attachment style and perinatal mood disturbance: Implications for screening and treatment. Arch. Womens Ment. Health 2008, 11, 117–129. [Google Scholar] [CrossRef] [Green Version]
  70. Zhang, L.; Wang, L.; Yuan, Q.; Huang, C.; Cui, S.; Zhang, K.; Zhou, X. The mediating role of prenatal depression in adult attachment and maternal-fetal attachment in primigravida in the third trimester. BMC Pregnancy Childbirth 2021, 21, 307. [Google Scholar] [CrossRef]
  71. Kitamura, T.; Yoshida, K.; Okano, T.; Kinoshita, K.; Hayashi, M.; Toyoda, N.; Ito, M.; Kudo, N.; Tada, K.; Kanazawa, K.; et al. Multicentre prospective study of perinatal depression in Japan: Incidence and correlates of antenatal and postnatal depression. Arch. Womens Ment. Health 2006, 9, 121–130. [Google Scholar] [CrossRef]
  72. Hada, A.; Kubota, C.; Imura, M.; Takauma, F.; Tada, K.; Kitamura, T. The Edinburgh Postnatal Depression Scale: Model Comparison of Factor Structure and its Psychosocial Correlates Among Mothers at One Month After Childbirth in Japan. Open Fam. Stud. J. 2019, 11, 1–17. [Google Scholar] [CrossRef]
  73. Kubota, C.; Okada, T.; Aleksic, B.; Nakamura, Y.; Kunimoto, S.; Morikawa, M.; Shiino, T.; Tamaji, A.; Ohoka, H.; Banno, N.; et al. Factor structure of the Japanese version of the Edinburgh postnatal depression scale in the postpartum period. PLoS ONE 2014, 9, e103941. [Google Scholar] [CrossRef] [PubMed] [Green Version]
Healthcare 11 00361 g001 550
Figure 1. Conceptual model of causal relationships between antenatal depression.
Figure 1. Conceptual model of causal relationships between antenatal depression.
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Figure 2. Final model after trimming.
Figure 2. Final model after trimming.
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Table
Table 1. Correlations of T1 and T2 depression (N = 245).
Table 1. Correlations of T1 and T2 depression (N = 245).
Mean (SD) or N (%)T1 DepressionT2 Depression
Demographic and obstetric variables
Age32.2 (4.2)0.013−0.009
Gestational age13.2 (1.1)−0.0420.112
Gravidity1.8 (1.1)−0.175 *−0.087
Primipara131 (53.5)------
Infertility treatment85 (34.7)------
Have a partner243 (99.2)------
Borderline personality traits
T1 Primitive defense4.44 (3.66)0.403 *0.352 *
T1 Identity diffusion7.34 (4.73)0.428 *0.355 *
T1 Reality testing1.58 (2.64)0.231 *0.332 *
T1 Total13.4 (9.3)0.440 *0.412 *
Adult attachment
T1 Total−2.3 (3.9)0.306 *0.271 *
Perception of the impact of the current pregnancy
Perceived impact of pregnancy84.0 (27.7)−0.452 *−0.364 *
Fear of child birth
T1 Total62.0 (20.3)0.428 *0.395 *
T2 Total66.0 (21.4)0.358 *0.425 *
Obsessive-compulsive symptoms
T1 Total27.4 (16.8)0.448 *0.366 *
T2 Total28.1 (17.6)0.399 *0.427 *
Perceived threat of COVID-19
T1 Perceived threat13.1 (3.6)−0.048−0.091
* p < 0.001. Time 1: 12–15 gestational weeks; Time 2: 22–35 gestational weeks.
Table
Table 2. Correlations between the variables used in this study.
Table 2. Correlations between the variables used in this study.
1. Depression2. Borderline Personality Traits 3. Adult Attachment 4. Perceived Impact
of Pregnancy		5. W-DEQ6. OCI-R7. Perceived Threat
1.---0.412 *0.271 *−0.364 *0.425 *0.427 *−0.174 *
2.0.440 *------------------
3.0.306 *0.431 *---------------
4.−0.452 *−0.314 *−0.278 *------------
5.0.428 *0.453 *0.302 *−0.465 *---0.427 *0.023
6.0.448 *0.621 *0.318 *−0.240 *0.465 *---0.009
7.−0.094−0.0070.1010.042−0.0030.061---
* p < 0.001. Correlations at Time 1 are under the diagonal, whereas those at Time 2 are above the diagonal. Abbreviations: W-DEQ; Wijma Delivery Expectancy/Experience Questionnaire, OCI-R; Obsessive-Compulsive Inventory—Revised.
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Usui, Y.; Takegata, M.; Takeda, S.; Kitamura, T. Relationships between Depression, Fear of Childbirth, and Obsessive-Compulsive Symptoms among Pregnant Women under the COVID-19 Pandemic in Japan. Healthcare 2023, 11, 361. https://doi.org/10.3390/healthcare11030361

AMA Style

Usui Y, Takegata M, Takeda S, Kitamura T. Relationships between Depression, Fear of Childbirth, and Obsessive-Compulsive Symptoms among Pregnant Women under the COVID-19 Pandemic in Japan. Healthcare. 2023; 11(3):361. https://doi.org/10.3390/healthcare11030361

Chicago/Turabian Style

Usui, Yuriko, Mizuki Takegata, Satoru Takeda, and Toshinori Kitamura. 2023. "Relationships between Depression, Fear of Childbirth, and Obsessive-Compulsive Symptoms among Pregnant Women under the COVID-19 Pandemic in Japan" Healthcare 11, no. 3: 361. https://doi.org/10.3390/healthcare11030361

APA Style

Usui, Y., Takegata, M., Takeda, S., & Kitamura, T. (2023). Relationships between Depression, Fear of Childbirth, and Obsessive-Compulsive Symptoms among Pregnant Women under the COVID-19 Pandemic in Japan. Healthcare, 11(3), 361. https://doi.org/10.3390/healthcare11030361

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