RGUHS Nat. J. Pub. Heal. Sci Vol No: 9 Issue No: 1 eISSN: 2584-0460 pISSN:
Prafulla shriyan1 , Giridhara R Babu2 , Sanjay Pattanshetty1 , Srikumaran Nair3
1. Department of Public Health, Manipal University, Manipal, Karnataka 2. Professor and Head, Life course Epidemiology, Public Health Foundation of India, Bengaluru Karnataka 3. Head of the Department, Dept. of Statistics, Manipal University, Manipal, Karnataka
Address for correspondence:
Dr. Giridhara R. Babu
Indian Institute of Public Health-Bangalore, Public Health Foundation of India (PHFI), Besides Leprosy Hospital, 1st Cross, Magadi Road Bangalore, India.
E-mail:giridhar@iiphh.org
Date of Received: 30/07/2020 Date of Acceptance:29/08/2020
Abstract
Background: Globally about 10% of pregnant women suffer from mental illness, primarily depression. The prevalence is higher in developing countries ranging from 15 – 65% whereas in developed countries it is 17%. Depression is associated with lower quality of life during pregnancy. This study was done to estimate the antenatal depression and its association with quality of life.
Methodology: A community-based cross-sectional study was conducted among 352 pregnant women. The study was conducted in Udupi District, Karnataka,. Depression scores were assessed using inventory for depressive symptom (IDS-SR) questionnaire and Quality of life was measured using the World Health Organization Quality of Life-BREF scale, which measures the domains such as physical health, psychological health, social relationship and environment.
Results: The study sample was 81.9% from rural and 18.1% from the urban area. The majority were housewives and living in a joint family. The mean age of the participants was 26(±3.5 SD) years. Nearly 65% of the participants were in the age group of 25-29 years. The prevalence of depressive symptoms was 44.2%. An unadjusted estimate showed women with depression had significantly lower quality of life domains except social. After adjusting for confounders, we did not find a significant association between depressive symptoms with quality of life scores.
Conclusion: The study found a high prevalence of prenatal depression. The presence of symptoms of depression is an important public health concern. The focus should be on evaluating the mental health of pregnant women and supporting successful strategies to prevent and manage maternal depression
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Introduction
Globally over 264 million people are estimated of having depression. Depression is a major cause of disability, which contributes greatly to the global burden of disease.1 Depression is a psychological health condition that causes low mood, loss of interest or happiness, feelings of hopelessness, disrupted sleep or appetite , low energy and concentration difficulties.2 Most frequently depression appears with the symptoms of anxiety. Such problems can become persistent and lead to a substantial deterioration in an individual's ability to carry out their responsibilities. Depression of the worst kind can lead to suicide.3
About 10% of pregnant women worldwide suffer from mental illness, primarily depression.4 The prevalence is higher in developing countries, it ranges from 15 – 65% 5-7 whereas in developed countries it is 17%.8 Problems of mental wellbeing remain undiagnosed because many of the signs were generally associated with motherhood itself.9 Depressed women have increased risk of obstetric complications such as preterm birth, Intra Uterine Growth restriction (IUGR) and low birth weight.10-13 Pregnant women with mental health issues are less likely to take good care of their own needs, seek antenatal care or take prescribed treatment.
One out of seven Indians suffered from mental disorders of varying severities. In 2017, mental illnesses contributed 4.7 percent of India’s overall Disability Adjusted Life Years and accounting for 14.5 % of total years of life lost due to deaths.14 Studies done in India estimated that the prevalence rate of depression during pregnancy was 25-45%.15 Many studies in India are hospital based and thus limited from generalization. Despite documentation of prevalence of depression only a few studies have examined the association of depression during pregnancy with quality of life. The study objective was to estimate the prevalence of depression and assessment of the quality of life among antenatal women. We also aimed to explore the association between prenatal depression and quality of life.
Materials and methods
A cross-sectional study was conducted among 352 pregnant women in the Udupi district of Karnataka. The study was approved by the Institutional Ethical Committee of Kasturba Medical Hospital. The study was done in Kundapura Taluk of Udupi District. The designated taluk has 387 Anganwadi centers. The estimated sample size was 350. The anganwadi centers are stratified as urban and rural anganwadi. There are 17 anganwadis in the urban area and 370 were in rural area. Participants were selected according to the proportion of the population in each area. It was calculated that 64 participants to be included from urban area and 288 from rural area. The average pregnant women registered in AWC were about 5, so limiting the number of eight pregnant women recruited from each centers the number of anganwadi selected includes 8 from urban and 36 centres from rural areas. The list of existing anganwadi centers with the coordinating person had been obtained from Child Development Project Officer and later centers were selected randomly. The participants who were present on the day of the field visit were interviewed after obtaining their written informed consent. All pregnant women who had completed their first trimester of pregnancy were eligible to participate in the study and the pregnant women with a history of depression were excluded. Study was conducted from February 2014 to July 2014.
World Health Organization Quality of Life-BREF (WHOQOL-BREF): Quality of life was measured using this scale. This scale has 26 items, which measure the domains such as physical health, psychological health, social relationship and environment.16 The instrument was validated in Indian setting.17
Inventory for Depressive Symptoms – Self Reported-30 (IDS-SR30): The 30 item IDS scale is designed to assess the severity of depressive symptoms. It has been used to screen for depression. The symptoms over the last seven days are assessed.18 The study participants were screened by using inventory for depressive symptoms by conducting face to face interviews. The total scores ranged from 0 – 84. The severity of the symptoms was defined as per the score cut – off, 0-13 as no depressive symptoms, 14-25 as mild, 26 -38 as moderate, 39-48 as severe and 49-84 as very severe. IDS-SR30 score of 18 or above as a cutoff was used to classify the depressive symptoms.
Socioeconomic status of the family was assessed by using a simplified scale developed by Agarwal et al19 for both urban and rural areas, which was validated against Kuppuswamy’s modified scale.
This instrument has 22 items; suitable weightage was given to each item. The score ranges from 3-9; the maximum aggregate score is 100. Based on the final score the SES of the family is divided into six categories, upper high (>=76), High (61-75), upper middle (46-60), lower middle (31-45), poor (16-30) and very poor (<=15). The study tools were pre tested before starting a study to test the validity of the study tool and the feasibility of conducting research.
Statistical analysis
Analysis was done using SPSS statistical software version 15. Descriptive statistics were reported. The linear regression model was used to evaluate the association between depression and QOL. Regression coefficients and 95%confidence intervals and p- value has been reported
Results
A total of 352 participants were included in this study, 44.2% (156) were found to be having depressive symptoms. Of the totals who were depressed, we observed that majority (74.4%) had mild depressive symptoms followed by moderate (24.4%) and severe (1.3%) level of depressive symptoms according to the severity threshold. (Table No.1)
Socio-demographic characteristics, obstetric factors and social support variables were compared between depressed and non-depressed pregnant women. The mean age of the participants was 26.8±3.6 years among non- depressed and 26.5±3.3years among depressed participants. The majority belonged to the age group of 24-29 years. Most of them were housewives and 60% of the participants were from the lower middle class family followed by upper middle. (Table 2)
Participants who were in the third trimester of pregnancy have higher depressive symptoms compared to the second trimester .Among depressed, the majority were primigravida. Of the total participants, 17.6% had a previous history of abortion and from these 43.5% of them were found to have depressive symptoms.
Women with depressive symptoms showed statistically significant lower scores in physical, psychological and environmental domains except in the social domain. (Table no 3) Scores of social domains were the same for both women who were depressed and non-depressed. The mean and CI for both depressed and non-depressed participants after adjusting for an area of living, education, spacing between two deliveries and hospitalization during pregnancy. We observed that the QOL score was the same across the two groups after adjusting for covariates and conclude that there is no independent association between depressive symptoms and quality of life.
Discussion
Our study provides a comprehensive analysis of the magnitude of the association between depressive symptoms during pregnancy on all four domains of quality of life. We assessed the depression during pregnancy and found that there is no significant difference in the quality of life according to the presence of depressive symptoms. The prevalence of depression in this study is somewhat higher than the earlier reported rates at similar points in pregnancy. There have been previous studies done in India examining the depression during pregnancy. Chandra et al reported the prevalence of antenatal depression among pregnant women in Tamil Nadu was 16.2%.20 and Patel V et al reported the depression status in Goa was of 23%21 and Savarimuthu RJS et al reported the prevalence of 26.3% in rural south India.22 The studies done in Northern India reported lesser depression level, 6.0% 23 9.18%24, 11.5%25. The reported prevalence in Western countries ranged from 11.7% to 40%.26-29 Possible explanations for depression during pregnancy may be because pregnant women experience a lot of physical distress, such as nausea and sleep disturbances, which increase in the second trimester and can worsen at this period. Our findings illustrate the importance of monitoring women during their routine pregnancy checks for symptoms of distress by health care providers and being particularly cautious in the second trimester when symptoms might get worse.
Our findings on estimating the association between depressive symptoms and quality of life were not consistent with the prior study findings by Nicholson et al28 who reported women in early pregnancy with depressive symptoms to have a poor health-related quality of life. Li Jie et al29 reported that Antenatal depression has negative effects on the quality of life linked to health. The limitations of our study are the lack of sufficient sample size; women may expect healthrelated symptoms or physical discomfort during pregnancy, which does not affect their perception of health-related quality of life; another limitation of this study is that we did not collect information on history of domestic violence which is a major determinant of antenatal depression and quality of life. We suggest additional prospective study to evaluate whether depressive symptoms in pregnancy can impact the quality of life.
Conclusion
The study found a high prevalence of prenatal depression. The presence of symptoms of depression is an important public health concern. We hope that the results of the study will aid policy makers to address mental wellbeing in pregnant women. The focus should be given on evaluating the mental health of pregnant women and supporting successful strategies to prevent and manage maternal depression.
Contribution to Authorship
PS designed the research and collected data. SN contributed in designing, data analysis and interpretation of data. SP and GRB have contributed in preparing the draft and revision of Manuscript.'
Details of Ethics approval
Ethical approval was taken from the Institutional Ethical Committee Manipal.
Funding: No funding was received for the study.
Supporting Files
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