Antenatal depression in coastal South India: Prevalence and risk factors in the community

Abstract

Background:

Antenatal depression is a highly prevalent disorder with serious implications on maternal and child outcomes. There are few studies examining this in low-middle-income community settings.

Aims:

To determine the prevalence of antenatal depression in women from a coastal rural background in Kerala and Tamil Nadu and to determine its associated factors.

Materials and methods:

In this cross-sectional community-based study, in 202 antenatal women, standard interview and diagnostic criteria (Clinical Interview Schedule–Revised (CIS-R)) were employed for identifying depression and examining a wide range of putative clinical and sociocultural risk factors including domestic violence.

Results:

There was a 16.3% prevalence of depression among the 202 women sampled. The possible risk factors after stepwise backward regression were pressure to have a male child, 11.48 (2.36–55.78); financial difficulties, 8.23 (2.49–27.22); non-arranged marriage, 6.05 (1.72–21.23); history of miscarriage–still birth, 5.77 (1.55–21.43) and marital conflict, 9.55 (2.34–38.98).

Conclusion:

There is a need to develop strategies for recognition and appropriate intervention for antenatal depression, in the context of locally relevant risk factors, so as to improve both maternal and child outcomes.

Keywords

Antenatal depression community prevalence risk factors

Background

While pregnancy is a time of emotional wellbeing for many women, conferring ‘protection’ against psychiatric disorders, a meta-analysis of 21 studies suggests the mean prevalence rate of depression across the antenatal period is 10.70%, ranging from 7.4% in the first trimester to a high of 12.80% in the second trimester (Bennett, Einarson, Taddio, Koren, & Einarson, 2004). It has also been shown that antenatal depression is highly prevalent in low-income settings, such as the South East Asian countries (Chandran, Tharyan, Muliyil, & Abraham, 2002; Rahman, Iqbal, & Harrington, 2003), with a prevalence of up to 20%–30% (Fisher, Mello, Izutsu, & Tran, 2011; Yingchun, Ying, & Jie, 2015). Depression in pregnant women is associated with underutilization of antenatal care, intrauterine growth retardation, low birth weight and preterm delivery (Grote et al., 2010; Hadegaard, Henriksen, Sabroe, & Secher, 1993). Depression during the antenatal period is the strongest predictor of postnatal depression (Chandran et al., 2002), which has a negative impact on child outcomes even in low-income countries (Patel, DeSouza, & Rodrigues, 2003; Rahman, Lovel, Bunn, Iqbal, & Harrington, 2004; Verkuijl et al., 2014). Depression during the antenatal period is often not recognized and treatment rates are lower in pregnant than in non-pregnant women (Vesga-López et al., 2008).

Risk factors for antenatal depression include past history of depression, presence of anxiety, marital difficulties or lack of a partner, low levels of social support and recent major life events (Pereira, Lovisi, Pilowsky, Lima, & Legay, 2009; Senturk, Abas, Berksun, & Stewart, 2011). Other factors include poverty (Patel, Rodrigues, & DeSouza, 2002), substance abuse, previous abortion, unplanned pregnancy, family violence, ambivalence towards the pregnancy and history of abuse (Jesse, Walcott-McQuigg, Mariella, & Swanson, 2005; Leigh & Milgrom, 2008). In a study on 292 women, in China, a history of miscarriage, irregular menstrual history, financial worries, psychoticism and neuroticism personality traits, and pregnancy pressures were the risk factors (Yingchun et al., 2015). In addition, women in Asia are socialized into patriarchal societies (Rahman et al., 2004) potentially creating a sense of poor self-esteem and negative cognitive style. This scenario highlights the need for a universal screening programme and treatment strategies for antenatal depression. But there is a paucity of studies in India on antenatal depression in rural and population-based settings, with the majority of studies being from clinic-based samples. The purpose of the study was to determine the prevalence of antenatal depression in women from a coastal rural background in Kerala and Tamil Nadu and to determine its associated factors.

Methods

Setting

The study was set within a population served by a community programme attached to the SMCSI Medical College in the coastal belts of Trivandrum and Kanyakumari districts in South India. The female literacy rates in the districts are 90.89% and 90.45%, respectively (Provisional Population Totals Paper 1 of 2011: Kerala, n.d.; Provisional Population Totals Paper 2 of 2011: Tamil Nadu, n.d.) and health indices are favourable compared to most other districts in India. However, the coastal population in India with fishing as their principle livelihood means have higher number of individuals below the poverty line and lower literacy rates compared to general populations (George & Domi, 2002) possibly due to disguised unemployment, seasonal variations in income, dwindling means of livelihood and high density of housing (Sathiadas, 2005). Coastal dwellers have also traditionally been isolated from the rest of the population. Women are financially disadvantaged and are dependent on their menfolk and families with daughters further burdened by high amounts of marital dowry.

The community programme covers 85 km² in Trivandrum and Kanyakumari districts with a target population of approximately 80,000. The programme has strong links to the hospital with promotion, prevention, treatment and advocacy components. The programme employs trained community lay workers enabled with various skills including screening and case identification (Cohen et al., 2011).

Design

A cross-sectional design was employed for determining the prevalence, while a case control frame work was used for the risk factor analysis.

Sample

All pregnant women registered at primary care facilities in the area were eligible for inclusion in the study. A household survey of the area identified a total of 698 women were eligible for inclusion in the study.

Procedure

The study protocol was approved by the Institutional Review Board of the institution. From the sampling frame of 698 women, 202 women were included for the study employing computer-generated random numbers. Those who gave written consent and were available for subsequent assessment were recruited. In all, 11 women refused consent and were replaced using predetermined rules. The subjects were interviewed and assessed for depression and risk factors in their homes, ensuring privacy. Those individuals who were detected to have depression were referred to the community programme for further management.

Study assessments

Diagnosis of antenatal depression

The Edinburgh Postnatal Depression Scale (EPDS) was employed to screen for depression. It has 10 items; each item is scored on a 4-point scale (0–3), the minimum and maximum score ranging from 0 to 30, respectively. It takes less than 5 minutes to administer. It has been used widely in various cultures (Vivilaki et al., 2009; Zubaran, Schumacher, Roxo, & Foresti, 2010), including India (Benjamin, Chandramohan, Annie, Prasad, & Jacob, 2005) to screen for antenatal depression. It was administered by trained community workers. Subjects with a score of above 10 were taken as having screened positive and were interviewed using the Clinical Interview Schedule–Revised (CIS-R).

The CIS-R (Lewis, Pelosi, Araya, & Dunn, 1992) was employed to diagnose depression. The CIS is a standardized interview for the diagnosis of common mental disorders in the community. The interview consists of 14 sections, each covering specific symptoms such as anxiety, depression, irritability, fatigue, obsessions, compulsions and panic. The CIS-R generates International Classification of Diseases (ICD-10) diagnosis (World Health Organization, 1992) and was employed to diagnose depression. The Tamil version of the instrument has been previously validated (Kuruvilla et al., 1999). This interview was conducted by consultant psychiatrists.

Assessment of associated factors

(a) We constructed a questionnaire for the assessment of associated factors based on previously reported risk factors and factors identified as possibly significant from a pilot study. The questionnaire covered the following areas:

Past and family history of psychiatric disorder.

Obstetric history: number of children; whether pregnancy planned or not; trimester of pregnancy, history of miscarriages or stillbirths; pregnancy-related complications.

Environmental and relational problems: financial difficulties, family structure (joint or nuclear); quality of marital relationship; problem drinking in husband; difficult relationship with mother in law

Adverse life events in the year before delivery.

Fears and expectations: desired gender of child; pressure to have a male child.

(b) Low self-esteem was measured employing the Rosenberg’s self-esteem scale (Rosenberg, 1965). There are 10 statements, and respondents are asked to circle whether they strongly agree (SA), agree (A), disagree (D) or strongly disagree (SD) with each one. This is the most commonly used scale for estimating self-esteem in young people.

(c) Intimate partner violence was measured with the Domestic Violence Questionnaire (Indu, Remadevi, Vidhukumar, Anilkumar, & Subha, 2011). The questionnaire has 20 items – 13 items for psychological and 7 items for physical violence. A cut-off score of 5 has been found to have a sensitivity of 89.5% and specificity 87.2% for detecting domestic violence. It has been validated for use in the Kerala population.

The CIS-R and EPDS are validated for the Tamil population (Benjamin et al., 2005; Kuruvilla et al., 1999), while the Domestic Violence Questionnaire is for the Kerala population (Indu et al., 2011). The instruments were adapted where necessary, after key-informant interviews with the target population and translation and back-translation by a panel of experts.

Statistical analysis

Mean, standard deviation and range were employed to describe continuous variables, while frequency distributions were obtained for categorical variables. The chi-squared and fisher’s exact tests were used to assess the significance of associations between categorical variables. Multivariate analysis was performed using stepwise backward logistic regression models. Associations are expressed as odds ratios (ORs) with 95% confidence intervals (95% CIs). The Hosmer-Lemeshow goodness-of-fit statistic was used to evaluate calibration of the predictive model. Variables with significance <.05 on univariate analysis were employed in the multivariate model.

The sample size obtained was 177 using the following assumptions: prevalence of antenatal depression to be 25% (Rahman et al., 2003), power of 80% with an alpha error of 5%. Data were analysed using the Statistical Package for the Social Sciences, version 16.00 (SPSS Inc.)

Results

We recruited 202 pregnant women. Overall, 33 (16.3%) of the women fulfilled ICD-10 criteria for depression. Table 1 documents the socio-demographic characteristics of the sample. The mean age of the women was 24.7(±3.4) yrs. The majority were married housewives, who had received high school education, had arranged marriages, lived in joint families and were married to husbands who were employed as fishermen. A significant proportion reported financial stress.

Table 1.

Socio-demographic and obstetric variables of antenatal women (n = 202).

Variables		Frequency (%)
Marital status	Married	202 (100)
Family structure	Joint	142 (70.3)
Educational status	High school and above	156 (77.2)
Arranged marriage	Yes	178 (88.1)
Occupation	Home maker	194 (96.0)
Husbands occupation	Fisherman	170 (84.2)
Poor support from husband	Present	5 (2.5)
Alcohol use in husband	Present	45 (22.3)
Marital conflict	Present	15 (7.4)
Dowry problems	Present	15 (7.4)
Problems with in-laws	Present	32 (15.8)
Environmental/financial problems	Present	95 (47.0)
Adverse life events in last 1 year	Present	49 (24.3)
Domestic violence	Present	15 (7.4)
Current gravida	First	91 (45.0)
Unplanned pregnancy	Yes	21 (10.4)
Trimester of pregnancy	First	58 (28.7)
Desired gender of child	Male child	37 (18.3)
Pressure for a male child	Present	18 (8.9)
Health worker home visit	Absent	176 (87.1)
H/o miscarriage/still birth	Present	15 (7.4)
Family h/o psychiatric illness	Yes	16 (7.9)

A small proportion of women had difficulties in their relationship with spouse, while more had problems with their mother-in-law. The mean Rosenberg’s self-esteem scale score was 19.64±2.41, only five of the sample had scores less than 15 indicating low self-esteem.

Table 2 shows the factors significantly associated with antenatal depression on univariate analysis. These included marital discord, intimate partner violence, discord with mother-in-law, non-arranged marriage, financial stress, history of miscarriage, complications in current pregnancy and pressure to have a male child. Educational level, dowry-related problems, employment status, low self-esteem, husband’s occupation, past and family history of psychiatry disorder, family structure, alcohol abuse in husband, adverse events in the last 1 year and unplanned pregnancy were not significantly associated with antenatal depression.

Table 2.

Variables significantly associated with depression in pregnant women – univariate analysis.

Variables		Antenatal depression		Odds ratio (95% CI)	Significance on univariate analysis
		Absent (n = 169)	Present (n = 33)	Odds ratio (95% CI)	Significance on univariate analysis
Intimate partner violence	Present	8	7	7.4 (2.46–22.21)	χ² = 16.23; p = .000*
Marital conflict	Present	11	4	2.08 (1.3–7.14)	χ² = 38.51; p = .000*
Difficult relationship with mother-in-law	Present	13	19	5.13 (2.20–11.9)	χ² = 16.41; p = .000*
Financial stress	Present	26	69	5.38 (2.22–13.16)	χ² = 15.97; p = .000*
Pressure to have a male child	Present	8	10	5.08 (1.83–14.08)	χ² = 11.42; p = .001*
Complications in present pregnancy	Present	5	6	4.85 (1.39–16.95)	χ² = 7.22; p = .007*
Non-arranged marriage	Present	8	16	3.06 (1.19–7.87)	χ² = 5.76; p = .016*
History of miscarriage/still birth	Present	7	8	5.41 (1.81–16.13)	χ² = 10.91; p = .001*
Trimester of pregnancy	First	13	45	**	χ² = 6.43; p = .040

CI: confidence interval.

p < .05; **not computed.

Marital conflict (χ² = 11.6; p = .00) was significantly associated with problems in relations with mother-in-law as well as having had a non-arranged or ‘love’ marriage (χ² = 7.12; p = .01), while dowry-related problems were elevated (20% vs 6.4%), but missed statistical significant relationship with the presence of marital conflict (Fischer’s exact test = .08).

Significant intimate partner violence was reported in 15 (7.4%) with at least one form of physical violence being present in 21 (10.4%) marriages. Intimate partner violence was significantly associated with pressure to have a male child (χ² = 19.2; p = .00) and problems in relationship with mother-in-law (χ² = 23.9; p = .00).

A multivariate analysis was conducted entering variables with significance <.05 (financial difficulties, violence by intimate partner, presence of complications in the current pregnancy, history of miscarriage/still birth, history of marital conflict, difficult relationship with mother in law, being in a non-arranged marriage, current trimester of pregnancy and pressure to have a male child) into the stepwise logistic regression model. Of these, pressure to have a male child, history of miscarriage–still birth, non-arranged marriage, financial difficulties and marital conflict had significant association with antenatal depression (Table 3).

Table 3.

Multivariate model for depression in pregnant women.

Risk factors	Odds ratio (adjusted)	95% CI	Significancep value
Pressure to have a male child	11.48	2.36–55.78	.002
History of miscarriage–still birth	5.77	1.55–21.43	.009
Non-arranged marriage	6.05	1.72–21.23	.005
Financial difficulties	8.23	2.49–27.22	.001
Marital conflict	9.55	2.34–38.98	.002

Discussion

Perinatal mental health has not been a priority in low- and low-middle-income countries. The sample studied had a 16.3% prevalence of depression. These findings are similar to those from systematic reviews involving samples from higher and lower income countries (Fisher et al., 2012) although some studies have higher rates ranging from 18% to 39.4% (Karmaliani et al., 2009; Rahman et al., 2003).

Sampling and assessment

In a review (Fisher et al., 2012) on studies from low-middle-income countries, 11 out of 13 samples were recruited from health facilities. The recruitment method in the present investigation included both accessing lists of women from primary care antenatal services and recruiting women through household visits, ensuring a representative population sample. Unlike most published studies (Ajinkya, Jadhav, & Srivastava, 2013; Karmaliani et al., 2009; Lau, Yin, & Wang, 2011), which employed screening tools to diagnose depression, we used a standardized interview schedule (CIS-R) and generated ICD-10 diagnosis, leading to more reliable diagnosis and more accurate estimates of depression.

Risk factors

Psychosocial factors

Evidence from communities, such as rural India, shows that difficulties in relationship with in-laws is a risk factor (Gupta, Kishore, Mala, Ramji, & Aggarwal, 2013; Lau et al., 2011) unlike this investigation, while marital conflict and financial difficulties emerged as risk factors consistent with extant literature (Patel, Kirkwood, Pednekar, & Pereira, 2006; Patel et al., 2002; Rahman et al., 2003; Senturk et al., 2011). Potential indicators of gender disadvantage evidenced by prevalent dowry practices and value attached to the male child exist within the Indian society (Chandran et al., 2002). In this sample, pressure to have a male child was associated with domestic violence and predictive of depression in keeping with literature from the country (Chandran et al., 2002).

Having a ‘love’ marriage was associated with reported marital conflict, both of which were associated with depression. A study from India showed that non-traditional life styles were associated with depression (Pillai et al., 2008). It may be postulated that women who choose their own partner, while living in traditional societies, may possibly be exposed to downstream untoward psychosocial effects that mediate the development of depression.

In this investigation, the reported rates of domestic violence are lower than those in general populations (Yoshikawa, Agrawal, Poudel, & Jimba, 2012), but are similar to those reported from a South Indian hospital-based antenatal sample (Nongrum, Thomas, Lionel, & Jacob, 2014) at 7.4%. Domestic violence was not independently associated with antenatal depression, in contrast to other investigations showing such a link (Jesse et al., 2005). This study also supported evidence that gender-based violence was associated with the preference for boy babies (Nongrum et al., 2014).

Prior history of mental illness was not associated with antenatal depression, unlike other studies (Pereira et al., 2009), possibly explained by the high rates of non-recognition of common mental disorders (Davidson & Meltzer-Brody, 1999) in the community.

Obstetric risk factors

This study adds to the evidence that a history of previous pregnancy loss is associated with antenatal depression (Weobong et al., 2014), probably related to the fear of another loss. While unplanned pregnancy, complications in current pregnancy and trimester of pregnancy were not risk factors, unlike other studies (Leigh et al., 2008; Pereira et al., 2009).

Strengths and limitations

The strengths of this study are that, the sample is drawn from the community, a structured clinical interview was employed for assessment of depression, a wide range of putative risk factors were examined and multivariate statistics was used. However, the cross-sectional nature of the study precludes conclusions regarding causality of possible risk factors.

Conclusion

Given its varied public health implications, there is a need for policy makers to prioritize the need to address emotional disorders within programmes which seem to focus preferentially on reducing perinatal and infant mortality rates.

Strategies for developing feasible community-level screening in pregnant high-risk women are probably likely to be effective in reducing morbidity (Patel, Simon, Chowdhary, Kaaya, & Araya, 2009). Shorter, time efficient and accurate screening methods that can be employed by health care workers at the primary level or community, while screening for obstetric and infant-related adversities (Smith, Gotman, Haiqun, & Yonkers, 2010) need to be developed.

There is evidence that management of depression among women in low-income settings may require a stepped care approach with counselling techniques such as support and psycho-education being effective for mild–moderate depression, while antidepressants may be reserved for individuals with severe depression (Araya et al., 2003). Given the putative risk factors for poor maternal mental health in such low-income settings, experts have opined that improvements in maternal mental health require a multi-sectoral response addressing poverty reduction, social protection, violence prevention, education and gender disadvantage. The findings of this study reiterate the need for a social response with, or even above, health responses to maternal issues.

Footnotes

Acknowledgements

We would like to acknowledge Mr. Ani Abraham, Mr. Godwin and Ms. Anitha A.S. for their help with the data collection. We thank CBM international for supporting the community outreach programme.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship and/or publication of this article.

References

Ajinkya

Jadhav

P. R.

Srivastava

N. N.

(2013). Depression during pregnancy: Prevalence and obstetric risk factors among pregnant women attending a tertiary care hospital in Navi Mumbai. Industrial Psychiatry Journal, 22, 37–40.

Araya

Rojas

Fritsch

Gaete

Rojas

Simon

Peter

T. J.

(2003). Treating depression in primary care in low-income women in Santiago, Chile: A randomised controlled trial. The Lancet, 361, 995–1000.

Benjamin

Chandramohan

Annie

I. K.

Prasad

Jacob

K. S.

(2005). Validation of the Tamil version of Edinburgh post-partum depression scale. The Journal of Obstetrics and Gynecology of India, 55, 241–243.

Bennett

H. A.

Einarson

Taddio

Koren

Einarson

T. R.

(2004). Prevalence of depression during pregnancy: Systematic review. Obstetrics & Gynecology, 103, 698–709.

Chandran

Tharyan

Muliyil

Abraham

(2002). Post-partum depression in a cohort of women from a rural area of Tamil Nadu, India: Incidence and risk factors. British Journal of Psychiatry, 181, 499–504.

Cohen

Eaton

Radtke

George

Manuel

De Silva

Patel

(2011). Three models of community mental health services in low-income countries. International Journal of Mental Health Systems, 5, Article 3.

Davidson

J. R.

Meltzer-Brody

S. E.

(1999). The underrecognition and undertreatment of depression: What is the breadth and depth of the problem? Journal of Clinical Psychiatry, 60(Suppl. 7), 4–9.

Fisher

J. R.

Mello

M. C.

Izutsu

Tran

(2011). The Ha Noi Expert Statement: Recognition of maternal mental health in resource-constrained settings is essential for achieving the Millennium Development Goals. International Journal of Mental Health Systems, 5, Article 2.

Fisher

J. R.

Mello

M. C.

Patel

Rahman

Tran

Holton

Holmes

(2012). Prevalence and determinants of common perinatal mental disorders in women in low- and lower-middle-income countries: A systematic review. Bulletin of the World Health Organization, 90, 139G–149G.

10.

George

M. K.

Domi

(2002). Residual literacy in a coastal village: Poovar village of Thiruvananthapuram district. Retrieved from http://www.cds.ac.in/krpcds/publication/downloads/w45.pdf

11.

Grote

N. K.

Bridge

J. A.

Gavin

A. R.

Melville

J. L.

Iyengar

Katon

W. J.

(2010). A meta-analysis of depression during pregnancy and the risk of preterm birth, low birth weight, and intrauterine growth restriction. Archives of General Psychiatry, 67, 1012–1024.

12.

Gupta

Kishore

Mala

Y. M.

Ramji

Aggarwal

(2013). Postpartum depression in North Indian women: Prevalence and risk factors. The Journal of Obstetrics and Gynecology of India, 63, 223–229.

13.

Hadegaard

Henriksen

T. B.

Sabroe

Secher

N. J.

(1993). Psychological distress in pregnancy and preterm delivery. British Medical Journal, 307, 234–239.

14.

Indu

P. V.

Remadevi

Vidhukumar

Anilkumar

T. V.

Subha

(2011). Development and validation of the domestic violence questionnaire in married women aged 18–55 years. Indian Journal of Psychiatry, 53, 218–223.

15.

Jesse

D. E.

Walcott-McQuigg

Mariella

Swanson

M. S.

(2005). Risks and protective factors associated with symptoms of depression in low-income African American and Caucasian women during pregnancy. Journal of Midwifery & Women’s Health, 50, 405–410.

16.

Karmaliani

Asad

Bann

C. M.

Moss

McClure

E. M.

Pasha

… Goldenberg

R. L.

(2009). Prevalence of anxiety, depression and associated factors among pregnant women of Hyderabad, Pakistan. International Journal of Social Psychology, 55, 414–424.

17.

Kuruvilla

Pothen

Philip

Braganza

Joseph

Jacob

K. S.

(1999). The validation of the Tamil version of the 12 item General health Questionnaire. Indian Journal of Psychiatry, 41, 217–221.

18.

Lau

Yin

Wang

(2011). Antenatal depressive symptomatology, family conflict and social support among Chengdu Chinese women. Maternal and Child Health Journal, 15, 1416–1426.

19.

Leigh

Milgrom

(2008). Risk factors for antenatal depression, postnatal depression and parenting stress. BMC Psychiatry, 8, Article 24.

20.

Lewis

Pelosi

A. J.

Araya

Dunn

(1992). Measuring psychiatric disorder in the community: A standardised assessment for use by lay interviewers. Psychological Medicine, 22, 465–486.

21.

Nongrum

Thomas

Lionel

Jacob

K. S.

(2014). Domestic violence as a risk factor for maternal depression and neonatal outcomes: A hospital-based cohort study. Indian Journal of Psychological Medicine, 36, 179–181.

22.

Patel

DeSouza

Rodrigues

(2003). Postnatal depression and infant growth and development in low income countries: A cohort study from Goa, India. Archives of Disease in Childhood, 88, 34–37.

23.

Patel

Kirkwood

B. R.

Pednekar

Pereira

(2006). Gender disadvantage and reproductive health risk factors for common mental disorders in women: A community survey in India. Archives of General Psychiatry, 63, 404–413.

24.

Patel

Rodrigues

DeSouza

(2002). Gender, poverty, and postnatal depression: A study of mothers in Goa, India. American Journal of Psychiatry, 159, 43–47.

25.

Patel

Simon

Chowdhary

Kaaya

Araya

(2009). Packages of care for depression in low- and middle-income countries. PLoS Medicine, 6(10), e1000159.

26.

Pereira

P. K.

Lovisi

G. M.

Pilowsky

D. L.

Lima

L. A.

Legay

L. F.

(2009). Depression during pregnancy: Prevalence and risk factors. Cadernos de Saúde Pública, 25, 2725–2736.

27.

Pillai

Patel

Cardozo

Goodman

Weiss

H. A.

Andrew

(2008). Non-traditional lifestyles and prevalence of mental disorders in adolescents in Goa, India. British Journal of Psychiatry, 192, 45–51.

28.

Provisional Population Totals Paper 1 of 2011: Kerala. (n.d.). Retrieved from http://censusindia.gov.in/2011-prov-results/prov_data_products_kerala_.html

29.

Provisional Population Totals Paper 2 of 2011: Tamil Nadu. (n.d.). Retrieved from http://censusindia.gov.in/2011-prov-results/prov_data_products_tamilnadu.html

30.

Rahman

Iqbal

Harrington

(2003). Life events, social support and depression in childbirth: Perspectives from a rural community in the developing world. Psychological Medicine, 33, 1161–1167.

31.

Rahman

Lovel

Bunn

Iqbal

Harrington

(2004). ‘Mothers’ mental health and infant growth: A case-control study from Rawalpindi, Pakistan. Child: Care, Health and Development, 30, 21–27.

32.

Rosenberg

(1965). Society and the adolescent self-image. Princeton, NJ: Princeton University Press.

33.

Sathiadas

(2005). Socio economic scenario of marine fisheries in Kerala. Retrieved from http://eprints.cmfri.org.in/5649/1/

34.

Senturk

Abas

Berksun

Stewart

(2011). Social support and antenatal depression in extended and nuclear family environments in Turkey: A cross-sectional survey. BMC Psychiatry, 11, Article 48.

35.

Smith

Gotman

Haiqun

Yonkers

(2010). Do the PHQ-8 and the PHQ-2 accurately screen for depressive disorders in a sample of pregnant women? General Hospital Psychiatry, 32, 544–548.

36.

Verkuijl

N. E.

Richter

Norris

S. A.

Stein

Avan

Ramchandani

P. G.

Nienke

(2014). Postnatal depressive symptoms and child psychological development at 10 years: A prospective study of longitudinal data from the South African Birth to Twenty Cohort. The Lancet Psychiatry, 1, 454–460.

37.

Vesga-López

Blanco

Keyes

Olfson

Grant

B. F.

Hasin

D. S.

(2008). Psychiatric disorders in pregnant and postpartum women in the United States. Archives of General Psychiatry, 65, 805–815.

38.

Vivilaki

V. G.

Dafermos

Kogevinas

Bitsios

Lionis

Vivilaki

L. C.

(2009). The Edinburgh Postnatal Depression Scale: Translation and validation for a Greek sample. BMC Public Health, 9, Article 329.

39.

Weobong

Soremekun

Ten Asbroek

A. H.

Amenga-Etego

Danso

Owusu-Agyei

… Kirkwood

B. R.

(2014). Prevalence and determinants of antenatal depression among pregnant women in a predominantly rural population in Ghana: The DON population-based study. Journal of Affective Disorders, 165, 1–7.

40.

World Health Organization. (1992). The ICD-10 classification of mental and behavioural disorders: Clinical descriptions and diagnostic guidelines. Geneva, Switzerland: Author.

41.

Yingchun

Ying

Jie

(2015). Prevalence and predictors of antenatal depressive symptoms among Chinese women in their third trimester: A cross-sectional survey. BMC Psychiatry, 15, Article 66.

42.

Yoshikawa

Agrawal

N. R.

Poudel

K. C.

Jimba

(2012). A lifetime experience of violence and adverse reproductive outcomes: Findings from population surveys in India. Bioscience Trends, 6, 115–121.

43.

Zubaran

Schumacher

Roxo

M. R.

Foresti

(2010). Screening tools for postpartum depression: Validity and cultural dimensions. African Journal of Psychiatry, 13, 357–365.