Abstract
Background
The increasing recognition of antenatal depression is an emerging area of concern in developing countries. We conducted a study to estimate the prevalence of antenatal mental distress and its relation with sociodemographic factors, obstetric factors, and physiological wellbeing in pregnant women attending public health facilities in Bengaluru, South India.
Methods
Nested within a cohort study, we assessed the mental status in 823 pregnant women in two public referral hospitals. Kessler Psychological Distress Scale (K-10 scale) was used to assess maternal depression. We collected information related to social-demographic characteristics and recent medical complaints. Descriptive statistics and odds ratios were calculated using SPSS version 20.
Results
Results show that 8.7% of the women exhibited symptoms of antenatal depression. Sociodemographic characteristics, such as respondent occupation, husband education, husband’s occupation, total family income showed significance. First time pregnancy, anemia, and high blood pressure were also associated with mental distress.
Conclusion
Our study has demonstrated feasibility of screening for mental health problems in public hospitals. Early detection of mental distress during pregnancy is crucial as it has a direct impact on the fetus. The public health facilities in low- and middle-income countries such as India should consider piloting and scaling up screening services for mental health conditions for pregnant women.
Keywords: pregnancy, mental distress, antenatal, stress, cohort, public hospital
Introduction
The increasing recognition of antenatal depression is an emerging area of concern. In contrast to affecting 7–20% of pregnant women in high-income countries, the estimates from lower and lower-middle-income countries report to be ranging from 5.2 to 32.9% (1). The pregnant women with symptoms suggestive of depression can have sudden exacerbation of existing medical disorders (2, 3). Poor mental health in pregnancy may lead to adverse pregnancy outcomes such as physical defects, low birth weight, emotional problems, preterm birth, and postnatal depression (4–6). Studies also attribute the association of behavioral, cognitive, and linguistic problems in children born to mothers suffering from depressive symptoms (7). Depression during pregnancy and the postpartum period is a major risk factor for suicidal ideation. There is sparse evidence regarding mortality associated with suicides during pregnancy in developing countries. However, the prevalence of antenatal suicidal ideation is reported in 6.3–14% of pregnant women from low-income households (8, 9). Therefore, screening for mental health disorders is vital during pregnancy, as it offers opportunities for early intervention to prevent adverse pregnancy outcomes. During the antenatal period, usually, greater importance is given in screening physical health and mental health of the pregnant woman tends to remain an area of neglect. Data from four low- and middle-income countries (LMICs) verifies that none of the countries have reported a dedicated maternal mental health service (10).
Previous studies in India have reported a wide-ranging prevalence of antenatal depression between 9.8 and 36.75% (11–13). The presence of depression among women presenting with medical complaints could be of significant importance. While there is sufficient evidence on the association of psychosocial and environmental risk factors; the association of antenatal depression with medical symptoms in LMICs including India is limited. An understanding of the sociodemographic and medical factors associated with the occurrence of depression during pregnancy could enhance better monitoring of women who are prone to develop a disorder such as this.
The present study was conducted with the objective of estimating the prevalence of symptoms of depression and its relation to sociodemographic and obstetric factors and physiological well-being in pregnant women attending public health facilities in Bengaluru, South India.
Materials and Methods
The current study is nested within an existing cohort of 823 women, the detailed protocol of which has been published elsewhere (14). The field centers comprise two public health facilities in the city of Bengaluru. Each of these facilities registers approximately 80–120 pregnant women for antenatal care every month; recruitment was conducted from November 2013 to June 2015.
The recruitment was done after obtaining informed consent. A pre-designed approved questionnaire was used to record relevant sociodemographic details and obstetric history. Women were also asked to recall and report any medical symptoms experienced by them over the past month. Physiologic measurements included body mass index, blood pressure, and hemoglobin estimation.
The Kessler Psychological Distress Scale (K-10 scale) (15) (Appendix S1 in Supplementary Material), a well-structured questionnaire, was administered by trained research assistants (RAs). The K-10 scale is observed to be a reliable measure to screen for depression among pregnant women in developing countries (16). The WHO-issued English language version of the K10 questionnaire was translated into the local language of “Kannada” using the standardized WHO translation and back-translation protocol (WHO) and pretested before being finalized. The Cronbach’s Alpha score was 0.843 for all the items on K-10 scale. Privacy and confidentiality of the study participants were ensured during the study process. The K-10 has five psychological distress response categories ranked on a five-point scale (1. All the time, 2. Most of the time, 3. Some of the time, 4. A little of the time, 5. None of the time), with the score being the sum of these responses (details given in Appendix S1 in Supplementary Material).
The pregnant women were administered Kessler’s Psychological Distress Scale by the RAs during their antenatal visit to the hospital; the questionnaire was administered to all pregnant women irrespective of their gestational age.
The institutional review board at The Indian Institute of Public Health-H, Public Health Foundation of India has approved the protocol. All the analyses were carried out in SPSS version 20.
Statistical Analysis
The main outcome variable, mental distress was dichotomized into a binary variable using a cutoff score from the K-10 scale; women with a cutoff score of ≥20 to the K10 scale are reported to be having symptoms of mental distress. Bivariate analysis of the association of sociodemographic characteristics, obstetric history, and medical symptoms with mental distress was evaluated by chi-square or fisher exact test (for cell values less than 5). Logistic regression was conducted to estimate the association between different factors and mental distress adjusting for known and unknown confounders. All those variables with a p-value < 0.25 on bivariate analysis were entered in the logistic regression model, even those variables with a p-value > 0.25 but which were known to have significant associations in previous studies were included (age, abortion, parity). More traditional levels such as 0.05 can fail in identifying variables known to be important (17, 18).
Results
Prevalence of Symptoms of Mental Distress
The sociodemographic characteristics of respondents with and without mental distress are displayed in Table 1. Gestational age and total household income were found to be significant and had small effect size.
Table 1.
Sociodemographic factors and mental distress in pregnancy (N = 823).
| Background characteristics | Mental distress |
p-Value | Effect | Degrees of Freedom | |
|---|---|---|---|---|---|
| Present (N = 72) | Absent (N = 751) | ||||
| Gestational age | |||||
| First trimester (less than 12 week) | 2 (11.8) | 15 (88.2) | 0.001 | 0.134 | 2 |
| Second trimester (12–28 week) | 52 (12.3) | 370 (87.7) | |||
| Third trimester (greater than 28 week) | 18 (4.7) | 366 (95.3) | |||
| Age | |||||
| 18–25 | 52 (9.5) | 495 (90.5) | 0.279 | 0.038 | 1 |
| >25 | 20 (7.2) | 256 (92.8) | |||
| Religion | |||||
| Hindu | 42 (7.7) | 500 (92.3) | 0.159 | 0.049 | 1 |
| Non-Hindu | 30 (11.3) | 251 (88.7) | |||
| Respondent’s education | |||||
| Illiterate | 7 (10.0) | 63 (90.0) | 0.366 | 0.049 | 2 |
| School | 19 (11.2) | 150 (88.8) | |||
| College | 46 (7.9) | 538 (92.0) | |||
| Husband’s education | |||||
| Illiterate | 18 (13.2) | 118 (86.8) | 0.249 | 0.072 | 3 |
| Middle school | 1 (5.9) | 16 (94.1) | |||
| High school | 13 (7.3) | 164 (92.7) | |||
| College | 40 (8.1) | 453 (91.7) | |||
| Subject’s occupation | |||||
| Unemployed | 64 (8.3) | 706 (91.7) | 0.124 | 0.059 | 1 |
| Working | 8 (15.1) | 45 (84.9) | |||
| Husband’s Occupation | |||||
| Unemployed | 2 (25.0) | 6 (75.0) | 0.132 | 0.066 | 2 |
| Unskilled worker | 35 (7.7) | 418 (92.3) | |||
| Skilled worker | 35 (9.7) | 327 (90.3) | |||
| Total household income (in rupees) | |||||
| ≤6000 | 29 (13.2) | 190 (86.8) | 0.047 | 0.098 | 3 |
| 7000–10,000 | 17 (6.3) | 251 (93.7) | |||
| 11,000–15,000 | 13 (8.1) | 148 (91.9) | |||
| >15,000 | 13 (7.4) | 162 (92.6) | |||
Statisttically significant results are in bold.
Table 2 shows the obstetric and medical characteristics of respondents with and without mental distress. Anemia and past month medical symptoms like nausea, vomiting, cough/cold, tiredness, abdominal pain, heartburn, giddiness, Ear pain, headache, and backache were found to be significant. BMI of respondent, parity, abortion, and blood pressure did not show any significance.
Table 2.
Obstetric cum medical factors and mental distress in pregnancy (N = 823).
| Background characteristics | Mental distress |
p-Value | Effect | Degrees of freedom | |
|---|---|---|---|---|---|
| Present (N = 72) | Absent (N = 751) | ||||
| BMI | |||||
| Normal weight | 32 (9.9) | 401 (92.6) | 0.23 | 0.057 | 2 |
| Under weight | 5 (13.5) | 32 (86.5) | |||
| Over weight | 35 (9.9) | 318 (90.1) | |||
| Blood pressurea | |||||
| High blood pressure | 2 (3.7) | 52 (6.3) | 0.218 | 0.047 | 1 |
| Normal blood pressure | 70 (9.1) | 699 (90.9) | |||
| Anemia | |||||
| Anemic (Hb < 11) | 33 (6.8) | 455 (93.2) | 0.017 | 0.085 | 1 |
| Non-anemic | 39 (11.6) | 296 (88.4) | |||
| Gravida | |||||
| Primigravida | 26 (7.9) | 302 (92.1) | 0.531 | 0.024 | 1 |
| Multigravida | 46 (9.3) | 449 (90.5) | |||
| Ever had an abortion | |||||
| Yes | 17 (11.2) | 134 (88.8) | 0.263 | 0.042 | 1 |
| No | 55 (8.2) | 617 (91.8) | |||
| Past month medical symptoms | |||||
| Nausea | 14 (25.5) | 41 (74.5) | >0.001 | 0.158 | 1 |
| Vomiting | 36 (19.1) | 152 (80.9) | >0.001 | 0.200 | 1 |
| Cough/cold | 32 (13.9) | 198 (86.1) | >0.001 | 0.114 | 1 |
| Giddiness | 38 (18.4) | 168 (81.6) | >0.001 | 0.198 | 1 |
| Tiredness | 49 (12.3) | 349 (87.7) | >0.001 | 0.122 | 1 |
| Abdominal pain | 27 (14.6) | 158 (85.4) | 0.002 | 0.111 | 1 |
| Ear pain | 7 (29.2) | 17 (70.8) | 0.003 | 0.125 | 1 |
| Heartburn | 19 (20.7) | 73 (79.3) | 0.001 | 0.149 | 1 |
| Constipation | 7 (21.9) | 25 (78.1) | 0.017 | 0.093 | 1 |
| Headache | 31 (16.5) | 157 (83.5) | >0.001 | 0.149 | 1 |
| Backache | 35 (11.4) | 271 (88.6) | >0.04 | 0.073 | 1 |
Statisttically significant results are in bold.
aHigh Blood pressure is Systolic BP of >130 mmHg and diastolic BP of >80 mmHg.
In Table 3, the sociodemographic factors of women were adjusted for age, gestational age, total income, respondent education, occupation, and husband’s occupation. Women in third trimester were more likely to be stressed (OR 2.67, CI 0.55–12.9) than women in early or second trimester. Women who were older than 25 years had greater risks for having mental distress than women younger than 25 years (OR 1.34, CI 0.78–2.30). Unemployed women seemed to have more mental distress than working women (OR 2.27, CI 0.98–5.26). However, the association was statistically not significant. Similarly respondents with unemployed husbands or unskilled workers had higher odds (1.34 CI 0.81–2.24) than women with husbands who were skilled workers or professionals. Women with household income less than Rs. 10,000 ($150) were at higher risk of mental distress compared to women with household income greater than Rs. 10,000.
Table 3.
Multivariate analysis of sociodemographic risk factors and mental distress in pregnancy.
| Factor | Unadjusted odds ratio (95% CI) | Adjusted odds ratio (95% CI) |
|---|---|---|
| Trimester | ||
| I Trimester | 1 | 1 |
| II Trimester | 0.94 (0.21–4.26) | 1.04 (0.22–4.83) |
| III Trimester | 2.71 (0.57–12.76) | 2.67 (0.55–12.9) |
| Age (older than 25 vs. less than 25 years) | 1.34 (0.78–2.30) | 0.73 (0.42–1.27) |
| Religion: Hindu vs. non-Hindu | 1.42 (0.87–2.32) | 1.57 (0.93–2.64) |
| Respondent’s education (did not attend college vs. attended college) | 0.70 (0.42–1.16) | 0.81 (0.46–1.42) |
| Respondent’s occupation (unemployed vs. working) | 1.96 (0.88–4.34) | 2.27 (0.98–5.26) |
| Husband’s Occupation (unemployed and unskilled vs. skilled worker) | 1.22 (0.75–1.99) | 1.34 (0.81–2.24) |
| Total income (in rupees) | ||
| >15,000 | 1 | 1 |
| 10,001–15,000 | 0.91 (0.41–2.03) | 0.88 (0.39–2.00) |
| 6001–10,000 | 1.18 (0.56–2.50) | 1.02 (0.47–2.20) |
| ≤6000 | 0.52 (0.26–1.04) | 0.49 (0.23–1.04) |
In Table 4, women’s medical and obstetric factors have been adjusted for age, gestational age, and parity. Anemic women had higher odds of having mental distress than non-anemic women (1.92 CI 1.17–3.15). Similarly first time mothers too had greater odds for mental distress (1.23 CI 0.73–2.07). Women with hypertension had a higher risk of mental distress than normotensive women (2.1 CI 0.49–8.93). None of the other medical symptoms reported by respondents were associated with mental distress.
Table 4.
Multivariate analysis of medical and obstetric risk factors and mental distress in pregnancy.
| Factor | Unadjusted odds ratio | Adjusted odds ratio |
|---|---|---|
| BMI | 0.77 (0.47–1.26) | 0.661 (0.40–1.08) |
| Hypertension | 2.60 (0.62–10.91) | 2.1 (0.49–8.93) |
| Primigravida vs. Multigravida | 1.19 (0.72–1.96) | 1.23 (0.73–2.07) |
| Anemia | 1.81 (1.11–2.95) | 1.92 (1.17–3.15) |
| Nausea | 0.23 (0.12–0.46) | 0.25 (0.12–0.50) |
| Vomiting | 0.25 (0.15–0.41) | 0.26 (0.16–0.46) |
| Cough/cold | 0.44 (0.27–0.73) | 0.51 (0.31–0.84) |
| Giddiness | 0.25 (0.15–0.42) | 0.28 (0.17–0.46) |
| Ear pain | 0.21 (0.86–0.53) | 0.22 (0.08–0.57) |
| Tiredness | 0.40 (0.24–0.68) | 0.47 (0.28–0.80) |
| Abdominal pain | 0.44 (0.26–0.73) | 0.50 (0.30–0.85) |
| Heartburn | 0.30 (0.16–0.53) | 0.26 (0.14–0.48) |
| Constipation | 0.32 (0.13–0.76) | 0.30 (0.12–0.75) |
| Headache | 0.35 (0.21–0.57) | 0.38 (0.23–0.64) |
| Backache | 0.59 (0.36–0.97) | 0.66 (0.40–1.09) |
Statisttically significant results are in bold.
Discussion
Mental health problems during the pregnancy have harmful effect on both the fetus and the mother. The results of this study suggest that symptoms of antenatal mental distress are associated with medical symptoms and other sociodemographic correlates (19). Also, there is a higher probability of depression in women post-delivery and the children are at higher risk of depression during adolescence (20). Out of 823 pregnant women, 8.7% reported having symptoms of mental distress, indicating that the antenatal depression poses a significant health issue in the study population. Previous studies in India have reported a prevalence of antenatal depression to be 9.8–36.75% (10–13). However, systematic reviews of prevalence of depression in pregnancy across the globe range from 6 to 25% (21, 22).
We found higher mental distress among women in their third trimester. This concurs with earlier evidence suggestive of progressive increase in the plasma concentration of total and free cortisol, peaking during the third trimester (23–25). Unemployed women were at a higher risk of mental distress as compared to working women. Similarly women with employed husbands appeared to have significantly lesser symptoms of mental distress compared to the women with husbands with no employment. Studies have shown excessive risk of preterm delivery in unemployed pregnant women (26). Earlier studies indicate that the fetal growth restriction (SGA) is associated with employment status of parents (27). Also, our results concur with studies reporting higher symptoms of mental distress in respondents whose total family monthly income was considerably lower (28–31).
First time mothers were more prone to mental distress in our study population; this resonates with the findings of several other studies (32, 33). It is possible that the fears associated with delivery such as losing control, something being wrong with the baby or painful contractions are more common in nulliparous women (34). However, Saisto and Halmesmäki suggest that fear of childbirth is common in nulliparous as well as in parous women. They further explain that the woman’s personal characteristics, mainly general anxiety, low self-esteem, depression, dissatisfaction with their partnership, and lack of support are important factors irrespective of parity (35).
Women with anemia had higher risk of mental distress than other women with normal hemoglobin levels. Nevertheless, few studies do not support the association between anemia and depression (36, 37). Women with higher blood pressure (systolic >130 mmHg and diastolic >80 mmHg) were at greater risk of mental distress; however, there may be temporal ambiguity of this association. Leeners et al. found emotional stress during pregnancy was associated with a 1.6-fold increased risk for hypertensive diseases in pregnancy (38).
We did not find any significant links between mental distress and any pregnancy loss. This is in concurrence with other studies, a review of articles from 1980 through 2008 to evaluate risk factors for antepartum depressive symptoms did not show obstetric history (i.e., spontaneous abortions, elective abortions, and fetal deaths in utero) to be significantly associated with depressive symptoms in bivariate or multivariate analyses (39).
Postpartum depression results in poorer cognitive development (40) and behavioral/emotional problems in infants (5). The main limitations of the study were the use of the Kessler’s scale as the measure of mental distress symptoms rather than a clinical diagnosis. The second limitation is to not have a homogenous population of pregnant women in terms of gestational age; the study included pregnant women from 14 week of pregnancy until 38 weeks. We believe that a longitudinal analysis of risk factors across different stages of pregnancy is required.
Early detection of mental distress during pregnancy is crucial as it has a direct impact on the fetus (41). Our study has demonstrated feasibility of screening for mental health problems in public hospitals; the pregnant women can be screened in antenatal clinics. Evidence suggests that educational interventions comprising of counseling can be successful in decreased adverse effects in pregnant women. Considering the scalability, the patient counseling by nurses and trainings for doctors can be done at all primary health centers. In addition, auxiliary nurse midwives/accredited social health activist can also be trained and skilled to assist the pregnant women about the need of screening for mental health problems and treatment. The health workers can also circulate information, education, and communication materials and motivate people as a regular activity and contribute toward efficient, empathetic management of mental health problems in pregnant women.
Conclusion
Mental status of pregnant women play critical role in pregnancy and birth outcomes. The public health facilities in LMICs such as India should consider piloting and scaling up screening services for mental health conditions for pregnant women. Women with mental distress must be referred for further diagnostic assessment and therapy.
Ethics Approval and Consent to Participate
The study was reviewed and approved by the institutional ethical review board (IEC) at Bangalore campus of IIPH-H. Only participants willing to participate voluntarily and those who have provided written informed consent are enrolled.
Consent for Publication
Informed consent has been obtained from all the enrolled participants of the study.
Availability of Data and Material
Requests for the datasets generated during and/or analyzed during the current study can be directed to the corresponding author. The Institutional ethics committee reviewing at IIPH-Bangalore will decide on providing the data.
Ethics Statement
This study was carried out in accordance with the recommendations of “IEC Guidelines, Institutional Ethics Committee, PHFI” with written informed consent from all subjects. All subjects gave written informed consent in accordance with the Declaration of Helsinki. The protocol was approved by the “Institutional ethical Committee (IEC) at Bangalore campus of IIPH-H.”
Author Contributions
GB has conceptualized, written, and has taken the lead in completing manuscript through all stages of preparation and submission till publication and is the first author. GM has reviewed the application from the conceptualization stage and has contributed to each version of the manuscript. AN has written and reviewed the study paper and contributed to the manuscript. MR has reviewed the application from the conceptualization stage and has contributed to the manuscript. NSingh and NSaldanha were involved in writing and analyzing the pilot data. RD was involved in writing and revising the manuscript. SK has reviewed the application from the conceptualization stage and has contributed to the manuscript. All authors have contributed to the article critically for important intellectual content and final approval of the version to be published.
Conflict of Interest Statement
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Acknowledgments
The authors thank Dr. Saraswati, Superintendent, H Siddhiah Road Referral Hospital and Dr. Shivakumar, Superintendent, Banashankari Referral Hospital for the support extended in conducting the pilot study. The authors thank Ms. Maithili Karthik and Ms. Keerti Deshapande for managing the fieldwork. The authors are grateful to Dr. Suresh Shapeti and T. S. Ramesh for facilitating administrative approvals and coordination.
Footnotes
Funding. The study was funded by an intermediate fellowship by the Wellcome Trust Department of Biotechnology India Alliance Clinical and Public Health research Fellowship (Grant No. IA/CPHI/14/1/501499).
Supplementary Material
The Supplementary Material for this article can be found online at https://www.frontiersin.org/articles/10.3389/fpubh.2018.00127/full#supplementary-material.
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