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Bulletin of the World Health Organization logoLink to Bulletin of the World Health Organization
. 2017 Sep 5;95(10):706–717C. doi: 10.2471/BLT.17.192237

Postpartum depression in India: a systematic review and meta-analysis

Dépression post-partum en Inde: revue systématique et méta-analyse

Depresión posparto en India: una revisión sistemática y un metaanálisis

اكتئاب ما بعد الولادة في الهند: مراجعة منهجية وتحليل تَلوي ملخص

印度产后抑郁症: 系统评价和元分析

Послеродовая депрессия в Индии: систематический обзор и метаанализ

Ravi Prakash Upadhyay a,, Ranadip Chowdhury b, Aslyeh Salehi c, Kaushik Sarkar d, Sunil Kumar Singh a, Bireshwar Sinha e, Aditya Pawar f, Aarya Krishnan Rajalakshmi f, Amardeep Kumar g
PMCID: PMC5689195  PMID: 29147043

Abstract

Objective

To provide an estimate of the burden of postpartum depression in Indian mothers and investigate some risk factors for the condition.

Methods

We searched PubMed®, Google Scholar and Embase® databases for articles published from year 2000 up to 31 March 2016 on the prevalence of postpartum depression in Indian mothers. The search used subject headings and keywords with no language restrictions. Quality was assessed via the Newcastle–Ottawa quality assessment scale. We performed the meta-analysis using a random effects model. Subgroup analysis and meta-regression was done for heterogeneity and the Egger test was used to assess publication bias.

Findings

Thirty-eight studies involving 20 043 women were analysed. Studies had a high degree of heterogeneity (I2 = 96.8%) and there was evidence of publication bias (Egger bias = 2.58; 95% confidence interval, CI: 0.83–4.33). The overall pooled estimate of the prevalence of postpartum depression was 22% (95% CI: 19–25). The pooled prevalence was 19% (95% CI: 17–22) when excluding 8 studies reporting postpartum depression within 2 weeks of delivery. Small, but non-significant differences in pooled prevalence were found by mother’s age, geographical location and study setting. Reported risk factors for postpartum depression included financial difficulties, presence of domestic violence, past history of psychiatric illness in mother, marital conflict, lack of support from husband and birth of a female baby.

Conclusion

The review shows a high prevalence of postpartum depression in Indian mothers. More resources need to be allocated for capacity-building in maternal mental health care in India.

Introduction

Postpartum psychiatric disorders can be divided into three categories: postpartum blues; postpartum psychosis and postpartum depression.1,2 Postpartum blues, with an incidence of 300‒750 per 1000 mothers globally, may resolve in a few days to a week, has few negative sequelae and usually requires only reassurance.1 Postpartum psychosis, which has a global prevalence ranging from 0.89 to 2.6 per 1000 births, is a severe disorder that begins within four weeks postpartum and requires hospitalization.3 Postpartum depression can start soon after childbirth or as a continuation of antenatal depression and needs to be treated.1 The global prevalence of postpartum depression has been estimated as 100‒150 per 1000 births.4

Postpartum depression can predispose to chronic or recurrent depression, which may affect the mother‒infant relationship and child growth and development.1,57 Children of mothers with postpartum depression have greater cognitive, behavioural and interpersonal problems compared with the children of non-depressed mothers.5,6 A meta-analysis in developing countries showed that the children of mothers with postpartum depression are at greater risk of being underweight and stunted.6 Moreover, mothers who are depressed are more likely not to breastfeed their babies and not seek health care appropriately.5 A longitudinal study in a low- and middle-income country documented that maternal postpartum depression is associated with adverse psychological outcomes in children up to 10 years later.8 While postpartum depression is a considerable health issue for many women, the disorder often remains undiagnosed and hence untreated.1,9

The current literature suggests that the burden of perinatal mental health disorders, including postpartum depression, is high in low- and lower-middle-income countries. A systematic review of 47 studies in 18 countries reported a prevalence of 18.6% (95% confidence interval, CI: 18.0‒19.2).10 Scarcity of available mental health resources,11 inequities in their distribution and inefficiencies in their utilization are key obstacles to optimal mental health, especially in lower resource countries. Addressing these issues is therefore a priority for national governments and their international partners. The impetus for this will come from reliable scientific evidence of the burden of mental health problems and their adverse consequences.

Despite the launch of India’s national mental health programme in 1982, maternal mental health is still not a prominent component of the programme. Dedicated maternal mental health services are largely deficient in health-care facilities, and health workers lack mental health training. The availability of mental health specialists is limited or non-existent in peripheral health-care facilities.12 Furthermore, there is currently no screening tool designated for use in clinical practice and no data are routinely collected on the proportion of perinatal women with postpartum depression.12

India is experiencing a steady decline in maternal mortality,13 which means that the focus of care in the future will shift towards reducing maternal morbidity, including mental health disorders. Despite the growing number of empirical studies on postpartum depression in India, there is a lack of robust systematic evidence that looks not only at the overall burden of postpartum depression, but also its associated risk factors. Our current understanding of the epidemiology of postpartum depression is largely dependent on a few regional studies, with very few nationwide data. The current review was done to fill this gap, by providing an updated estimate of the burden of postpartum depression in India, to synthesize the important risk factors and to provide evidence-based data for prioritization of maternal mental health care.

Methods

Data sources and search strategy

Two authors (RPU and AP) independently searched PubMed®, Google Scholar and Embase® databases for articles on the prevalence of postpartum depression in India, published until 31 March 2016. The search strategy (Box 1) used subject headings and keywords with no language restrictions. Any discrepancy in the search results was planned to be discussed with a third author (AKR). We also searched the bibliographies of included articles and government reports on government websites to identify relevant primary literature to be included in the final analysis. For studies with missing data or requiring clarification, we contacted the principal investigators.

Box 1. Search keywords used for identification of articles for the review of the prevalence of postpartum depression, India, 2000–2015.

  1. (“depression” OR “depressive disorder” OR “blues” OR “distress” OR “bipolar” OR “bi-polar” OR “mood disorder” OR “anxiety disorder”)

  2. (“postpartum” OR “postnatal” OR “perinatal” OR “post birth” OR “after delivery” OR “after birth” OR “puerperium” OR “puerperal”)

  3. (“prevalence” OR “incidence” OR “burden” OR “estimate” OR “epidemiology”)

  4. (“India” OR “South East Asia”)

  5. (#1 AND #2 AND #3 AND #4)

  6. (Addresses[ptyp] OR Autobiography[ptyp] OR Bibliography[ptyp] OR Biography[ptyp] OR pubmed books[filter] OR Case Reports[ptyp] OR Congresses[ptyp] OR Consensus Development Conference[ptyp] OR Directory[ptyp] OR Duplicate Publication[ptyp] OR Editorial[ptyp] OR Systematic reviews OR Meta analysis OR Festschrift[ptyp] OR Guideline[ptyp] OR In Vitro[ptyp] OR Interview[ptyp] OR Lectures [ptyp] OR Legal Cases[ptyp] OR News[ptyp] OR Newspaper Article[ptyp] OR Personal Narratives [ptyp] OR Portraits[ptyp] OR Retracted Publication[ ptyp] OR Twin Study[ptyp] OR Video-Audio Media[ptyp])

  7. (#5 NOT #6) Filters: Original research; published in the past 15 years; humans

Study selection and data extraction

For a study to be included in the systematic review, it had to be original research done in India, within a cross-sectional framework of a few weeks to 1 year post-birth. We excluded research done in a specific population, such as mothers living with human immunodeficiency virus; research including mothers with any current chronic disease. To have a fairly recent estimate of the burden of postpartum depression, we considered only studies published from the year 2000 and later. After initial screening of titles and abstracts, we reviewed the full text of eligible publications. Decisions about inclusion of studies and interpretation of data were resolved by discussion among the reviewers. Data from all studies meeting the inclusion criteria were extracted and tabulated.

Study quality assessment

We used the Newcastle‒Ottawa quality assessment scale adapted for cross-sectional studies.14,15 The scale is used to score the articles under three categories: (i) selection (score 0‒5); (ii) comparability (score 0‒2 ); and (iii) outcome (score 0‒3); total score range 0‒10. The selection category consists of parameters, such as representativeness of the sample, adequacy of the sample size, non-response rate and use of a validated measurement tool to gather data on exposure. The comparability category examines whether subjects in different outcome groups are comparable based on the study design and analysis and whether confounding factors were controlled for or not. The outcome category includes whether data on outcome(s) were collected by independent blind assessment, through records or by self-reporting. The outcome category also includes whether the statistical tests used to analyse data were clearly described and whether these tests were appropriate or not. Two authors (RPU and KS) made separate quality assessments of the included studies. In case of any discrepancy, a third author (AP) was consulted. We grouped the studies into those with quality scores ≤ 5 and > 5.

Data analysis

We did a meta-analysis of the reported prevalence of postpartum depression in the included studies. Heterogeneity between studies was quantified by the I2 statistic. We considered I2 values > 50% to represent substantial heterogeneity.16 The degree of heterogeneity among the studies was high (> 95%), and thus we used a random effects model to derive the pooled estimate for postpartum depression in mothers. The final estimates of prevalence were reported as percentages with 95% CI.

We did a subgroup analysis by excluding articles in which depression was assessed within 2 weeks postpartum,1,17,18 since some researchers argue that it is difficult to differentiate postpartum depression from postpartum blues within 2 weeks of birth. In addition, the Edinburgh postnatal depression scale, which was used in the majority of studies we identified, can give false-positive results in the early postpartum period.

We also did separate subgroup analyses on each of the following factors: place of study (geographical location; rural or urban; hospital or community); study instrument used; quality score of the articles; time of publication; and age of mothers. Not all the studies provided data on the mean age of the study participants that was required for subgroup analysis; however, the proportion of mothers in specific age ranges were available. Using this information, we estimated the mean age of the study participants. For studies that reported the prevalence of postpartum depression in mothers at different time points, we used the prevalence reported in the earliest time point to reduce the effect of lost to follow-up. We used meta-regression analysis to identify factors contributing to the heterogeneity in effect size, i.e. the pooled proportion of mothers with postpartum depression.

We assessed publication bias with the Egger test and used a funnel plot to graphically represent the bias. Finally, we listed the risk factors for postpartum depression. We used Stata software, version 14 (StataCorp. LLC, College Station, United States of America) for all analyses.

Results

Characteristics of the studies

Of the 1285 articles we identified in our search, we screened 1248 titles of unique articles. Out of these, we reviewed 211 relevant abstracts, assessed 62 full-text articles for eligibility and included 38 articles in our final analysis.1956 (Fig 1). These 38 studies included data from 20 043 mothers in total. More of the articles (26 studies) were published in the most recent five-year period 2011‒2015 than in the earlier periods 2000–2005 (6) and 2006–2010 (6). The majority of studies were from south India (16 studies), followed the western (9) and northern regions (7) of the country; 24 studies were done in an urban setting and 29 in hospitals (Table 1; available at: http://www.who.int/bulletin/volumes/94/10/17-192237). In 19 studies, the mean age of the study mothers was ≤ 25 years. The Edinburgh postnatal depression scale was the most commonly used study instrument (29 studies). The median quality score for the studies was 5 (21 articles had a score of ≤ 5 and 17 had a score >  5).

Fig. 1.

Fig. 1

Flowchart showing the selection of studies for the systematic review of the prevalence of postpartum depression, India, 2000–2015

Table 1. Characteristics of the studies identified in the systematic review of the prevalence of postpartum depression in mothers, India, 2000–2015.

Study Place of study (region) Study setting Study design Study instrument Mean age of participants, years (SD) Timing of data collection postpartum No. of women No. of mothers with depression Quality scorea
Affonso et al., 200056 Kolkata (east) NR Cross-sectional EPDS > 25b At 1-2 weeks 110 39 6
At 4-6 weeks 102 33
BDI At 1-2 weeks 106 35
At 4-6 weeks 101 25
Patel et al., 200255 Goa (south-west) Urban hospital Cohort EPDS 26 (4) At 6–8 weeks 252 59 8
At 6 months 235 51
Chandran et al., 200254 Tamil Nadu (south) Rural community Cohort CIS-R 22.8 (3.7) At 6–12 weeks 301 33 8
Patel et al., 200353 Goa (south-west) Urban hospital Cohort EPDS 26 (NR) At 6–8 weeks 171 37 7
Sood & Sood, 200352 Uttar Pradesh (north) Urban hospital Cohort BDI 24 (3) At 3–7 days 75 15 4
At 4–6 weeks 70 9
Prabhu et al., 200551 Tamil Nadu (south) Not clearly defined Cross-sectional EPDS NR At 3–4 weeks 478 28 5
Kalita et al., 200850 Assam (North east) Urban hospital Cross-sectional EPDS 25.1 (4.7) At 6 weeks 100 18 4
Nagpal et al., 200849 Delhi (north) Urban community Cross-sectional EPDS 27 (25.8–28.2)c Within 6 months 172 63 8
Mariam & Srinivasan, 200948 Karnataka (south) Urban hospital Cohort EPDS 23.9 (3.6) Within 6–10 weeks 132 39 3
Ghosh & Goswami, 200947 Kolkata (east) Urban hospital Cross-sectional EPDS 25.3 (NR) At 4–7 days 6000 1505 2
Savarimuthu et al., 201046 Tamil Nadu (south) Rural community Cross-sectional EPDS 23.6 (3.4) At 2–10 weeks 137 36 7
Sankapithilu et al., 201045 Mysore (south) Urban hospital Cross-sectional EPDS 23.8 (NR) Within 3 months 100 30 5
Manjunath et al., 201144 Karnataka (south) Urban hospital Cross-sectional EPDS 18–45d Within 2 weeks 123 72 5
Iyengar et al., 201243 Rajasthan (west) Rural community Cohort EPDS 26.4 (NR) At 6–8 weeks 430 87 9
At 12 months 275 32
Prost et al., 201242 Jharkand; Orrisa (east) Rural community Control arm of a clustered RCT Kessler 10--item scale 25.5 (5.3) At 6 weeks 5801 669 9
Dubey et al., 201241 Delhi (north) Urban hospital Cross-sectional EPDS 24.3 (3.2) Day 1 to week 1 293 18 3
Hegde et al. 201240 Karnataka (south) Urban hospital Cross-sectional MINI with DSM-IV criteria 24.3 (7.9) At 2–3 days 150 17 9
At 6 weeks 139 22
At 14 weeks 129 20
Desai et al., 201239 Gujarat (west) Urban hospital Cross-sectional Semi-structured interview based on DSM-IV-TR criteria 23.8 (NR) Up to 1 year 200 25 4
Gokhale et al., 201338 Gujarat (west) Urban hospital Cross-sectional EPDS 25.2 (NR) At day 1 200 22 3
At day 6 108 8
At week 6 62 2
Sudeepa et al., 201337 Bangalore (south) Rural hospital Cross-sectional EPDS 22.6 (2.4) At 6–8 weeks 244 28 3
Prakash et al., 201336 Gujarat (west) Urban hospital Cross-sectional EPDS NR Within 24 hours 155 50 2
Gupta et al., 201335 Delhi (north) Urban hospital Cross-sectional PRIME-MD 24.6 (3.7) At 6 weeks 202 32 9
Dhiman et al., 201434 Puducherry (south) Urban hospital Cross-sectional EPDS NR At 24–48 hours 103 58 2
Jain et al., 201433 Delhi (north) Urban hospital Cross-sectional EPDS 26.3 (NR) Within 1 week 1537 105 7
Saldanha et al., 201432 Maharashtra (west) Urban hospital Cross-sectional EPDS 24.9 (NR) At 6 weeks 186 40 5
Dhande et al., 201431 Wardha (west) Rural hospital Cross-sectional EPDS 24.3 (NR) Within 6 months 67 16 5
Poomalar & Arounassalame, 201430 Puducherry (south) Urban hospital Cross-sectional EPDS 25.6 (NR) Within 1 week 254 26 6
Johnson et al., 201529 Karnataka (south) Rural hospital Cross-sectional EPDS 23.2 (NR) Within 1 week 74 33 7
At 6–8 weeks 49 23
Patel et al., 201528 Gujarat (west) Urban hospital Cross-sectional EPDS 25.2 (4.2) Within 1 week 134 65 3
Hiremath et al., 201527 Maharashtra (west) Urban hospital Cross-sectional EPDS 29.3 (NR) Within 6 weeks 80 13 4
Hirani & Bala, 201526 Gujarat (West) Rural community Cross-sectional EPDS 23.3 (NR) At 1–6 weeks 516 62 4
Bodhare et al., 201525 Telengana (south) Urban hospital Cross-sectional PHQ-9 23.2 (3.2) At 6–8 weeks 274 109 8
Kolisetty & Jyothi, 201524 Karnataka (south) Urban hospital Cross-sectional DSM-IV 28.2 (NR) Within 6 weeks 100 22 6
Srivastava et al. 201523 Uttar Pradesh (north) Urban hospital Cross-sectional DSM-IV-TR 25.1 (NR) Within 4 weeks 100 16 1
Kumar et al., 201522 Karnataka (south) Rural hospital Cross-sectional EPDS 22.7 (3.3) At 6−8 weeks 310 43 8
Suguna et al., 201521 Bangalore (south) Rural hospital Cross-sectional EPDS 23.6 (NR) Within 6 weeks 180 32 1
Shrestha et al., 201520 Haryana (north) Rural community Cross-sectional EPDS 22.6 (NR) At 6 weeks 200 24 5
Shivalli & Gururaj, 201519 Karnataka (south) Rural hospital Cross-sectional EPDS 23.1 (2.9) At 4–10 weeks 102 32 9

BDI: Beck depression inventory; CIS-R: clinical interview schedule-revised; DSM-IV: diagnostic and statistical manual of mental disorders 4th edition; DSM-IV-TR: “text revision” of diagnostic and statistical manual of mental disorders 4th edition; EPDS: Edinburgh postnatal depression scale; MINI: M.I.N.I. international neuropsychiatric interview; NR: not reported; PHQ-9: 9-item patient health questionnaire; PRIME-MD: primary care evaluation of mental disorders; RCT: randomized controlled trial; SD: standard deviation.

a We used the Newcastle–Ottawa quality assessment scale with a maximum score of 10.14

b Reported average age of participants > 25 years.

c Range is 95% confidence interval.

d Range of ages.

Prevalence of postpartum depression

Based on the random effects model, the overall pooled estimate of the prevalence of postpartum depression in Indian mothers was 22% (95% CI: 19–25; Fig. 2). Eight studies included women reporting depression within 2 weeks of delivery. After excluding these, the pooled prevalence for the remaining 30 studies (11 257 women) was 19% (95% CI: 17–22; Fig. 3).

Fig. 2.

Estimated prevalence of postpartum depression, pooling all selected studies (n = 38), India, 2000–2015

CI: confidence interval.

Notes: Results from random effect analysis. Studies included a total of 20 043 women. The dashed line passing through the midpoint of the diamond denotes the point estimate of the overall pooled effect size and the lateral tips of the diamond represent 95% confidence intervals.

Fig. 2

Fig. 3.

Estimated prevalence of postpartum depression after excluding studies reporting depression within 2 weeks postpartum (n=30), India, 2000-2015

CI: confidence interval.

Notes: Results from random effect analysis. Studies included a total of 11 257 women. The dashed line passing through the midpoint of the diamond denotes the point estimate of the overall pooled effect size and the lateral tips of the diamond represent 95% confidence intervals.

Fig. 3

The estimated overall pooled prevalence was highest in the southern region of the country (26%; 95% CI: 19–32), followed by eastern (23%; 95% CI: 12-35), south-western (23%; 95% CI: 19–27) and western regions (21%; 95% CI: 15–28; Table 2). The northern region of India had the lowest prevalence (15%; 95% CI: 10–21). The pooled prevalence was higher, but not significantly so, for studies conducted in hospital settings (23%; 95% CI: 19–28) than in community settings (17%; 95% CI: 13–22); Fig. 4; Table 2) and in urban versus rural areas (24%; 95% CI: 19–29 versus 17%; 95% CI: 14–21). Prevalence was 20% (95% CI: 16–24) and 21% (95% CI: 16–26) when studies with mean maternal age of ≤ 25 years and > 25 years were pooled respectively.

Table 2. Subgroup analysis in the systematic review of the prevalence of postpartum depression, India, 2000–2015.

Study characteristic No. of women No. of studies Pooled prevalence, % (95% CI) P P for meta-regression
All 20 043 38 22 (19–25)    
Region
East 11911 3 23 (12-35) < 0.05 0.63
West 1 968 9 21 (15–28) 0.66
North 2 579 7 15 (10–21) 0.20
South 3 062 16 26 (19–32) Ref.
North-east 100 1 18 (10–26) 0.81
South-west 423 2 23 (19–27) 0.70
Settinga
Hospital 11 898 29 23 (19–28) < 0.05 Ref.
Community 7 557 7 17 (13–22) 0.41
Areaa
Urban 11 093 24 24 (19–29) < 0.05 Ref.
Rural 8 362 12 17 (14–21) 0.16
Study instrument
EPDS 12 840 29 24 (20–28) < 0.05 Ref.
Othersb 7 203 9 17 (13–22) 0.22
Weeks postpartum
≥ 2 11 257 30 19 (17–22) < 0.05 Ref.
< 2 8 599c 8 30 (20–39) 0.29
Age of participants, yearsd
≤ 25 3 743 19 20 (16–24) < 0.05 Ref.
> 25 15 441 15 21 (16–26) 0.25
Study quality score
≤ 5 9 666 21 22 (18–27) < 0.05 Ref.
> 5 10 377 17 21 (18–25) 0.59
Publication year
2000–2005 1 387 6 19 (11–27) < 0.05 0.91
2006–2010 6 641 6 27 (23–32) 0.89
2011–2015 12 015 26 21 (18–24) Ref.

CI: confidence interval; EPDS: Edinburgh postnatal depression scale; Ref.: reference category.

a Prabhu51 et al. and Affonso et al.56 did not provide information on study setting.

b Includes diagnostic and statistical manual of mental disorders 4th edition (DSM-IV); 9-item patient health questionnaire; primary care evaluation of mental disorders; Beck depression inventory; M.I.N.I. international neuropsychiatric interview plus DSM-IV; Kessler 10-item scale; and clinical interview schedule‒revised.

c Numbers do not total 20 043 as the number of women varies according to the time of assessment postpartum.

d Dhiman et al.,34 Prakash et al.,36 Manjunath et al.44 and Prabhu et al.51 either did not provide the age of mothers or sufficient data for the analysis.

Fig. 4.

Estimated prevalence of postpartum depression from hospital- and community-based studies (n = 36), India, 2000–2015

CI: confidence interval.

Notes: Results from random effect analysis. Studies included a total of 19 455 women (11 898 in hospital-based studies and 7557 in community-based studies). Two studies (Prabhu51 et al. and Affonso et al.56) did not provide information on study setting. The dashed line passing through the midpoint of the diamond denotes the point estimate of the overall pooled effect size and the lateral tips of the diamond represent 95% confidence intervals. The three diamonds from the top represent the pooled estimate for hospital-based studies, community-based studies and overall pooled estimate respectively.

Fig. 4

Pooling of studies that used the Edinburgh postnatal depression scale as the study instrument produced a prevalence of 24% (95% CI: 20–28) compared with 17% (95% CI: 13–22) in those that used other study instruments (Table 2).

Studies with a quality score ≤ 5 had a pooled prevalence of 22% (95% CI: 18–27) and those with a score > 5 had a prevalence of 21% (95% CI: 18–25).

The studies had a high degree of heterogeneity (I2 = 96.8%). Both the Egger plot (Egger bias = 2.58; 95% CI: 0.83–4.33; Fig. 5) and the funnel plot (Fig. 6) showed evidence of publication bias.

Fig. 5.

Fig. 5

Egger plot for publication bias in the meta-analysis of studies (n = 38) on the prevalence of postpartum depression, India, 2000–2015

Fig. 6.

Funnel plot of publication bias in the meta-analysis of studies (n = 38) on the prevalence of postpartum depression, India, 2000–2015.

Notes: The outer dashed lines indicate the triangular region within which 95% of studies are expected to lie in the absence of both biases and heterogeneity. The solid line represents the log of the total overall estimate of the meta-analysis.

Fig. 6

Risk factors

A total of 32 studies reported risk factors for postpartum depression. The risk factors most commonly reported were financial difficulties (in 19 out of 21 studies that included this variable), domestic violence (6/8 studies), past history of psychiatric illness in the mother (8/11 studies), marital conflict (10/14 studies), lack of support from the husband (7/11 studies) and birth of a female baby (16/25 studies). Other commonly reported risk factors were lack of support from the family network (8/14 studies), recent stressful life event (6/11 studies), family history of psychiatric illness (7/13 studies), sick baby or death of the baby (6/13 studies) and substance abuse by the husband (4/9 studies). Preterm or low birth-weight baby, high parity, low maternal education, current medical illness, complication in current pregnancy and unwanted or unplanned pregnancy and previous female child, were some of the other reported risk factors (Table 3).

Table 3. Risk factors for postpartum depression reported by studies included in the systematic review, India, 2000–2015.

Variable No. of studies
Total Reporting risk for postpartum depression
Individual factors
High maternal agea 28b 4
Low maternal agea 28b 3
Low maternal education  27c 10
Current medical illness  6 2
Past history of psychiatric illness, anxiety or low mood 11 8
Family history of psychiatric illness 13 7
Recent stressful life event 11 6
Low self-esteem 4 2
Husband & marital relationship factors
Marital conflict  14  10
Domestic violence  8 6
Lack of support from husband  11 7
Addiction in husband  9 4
Financial difficulties 21 19
Pregnancy-related factors
Unplanned or unwanted pregnancy 14  4
Past history of obstetric complication  18 3
Complicated or eventful current pregnancy  22 8
Female child born in the current pregnancy  25 16
Previous female child  14 4
Primigravida 23 4
High parity 23 9
Mood swings during pregnancy  12 4
Caesarean section  15 5
Preterm or low-birth-weight baby  16 5
Sickness or death of baby 13 6
Other psychological factors
Conflict with in-laws 11 3
Lack of support from family networks  14 8
Lack of confidant/close friend 12 2

a High maternal age reported as > 30–35 years. Low maternal age reported as < 25 years.

b Total number of studies that analysed maternal age as a risk factor for postpartum depression.

c Studies that analysed maternal education as a risk factor for postpartum depression.

Discussion

The pooled prevalence of postpartum depression in India in our meta-analysis was 22% (95% CI: 19–25). A systematic review of studies in 11 high-income countries showed that, based on point prevalence estimates, around 12.9% (95% CI: 10.6–15.8) of mothers were depressed at three months postpartum.57 Data from 23 studies conducted in low- and middle-income countries, which included 38 142 women, was 19.2% (95% CI: 15.5–23.0).58 Another systematic review from 34 studies found that the prevalence of common mental disorders in the postpartum period in low- and lower-middle income countries was 19.8% (95% CI: 19.2–20.6).10 These estimates in low- and middle-income countries are similar to ours and, taken together, they support an argument for placing greater importance on maternal mental health as part of overall efforts to improve maternal and child health.

Although facility-based deliveries are increasing in many low- and middle-income countries, a high proportion of pregnant mothers still deliver at home.59 Beyond the lack of awareness of postpartum depression by health professionals, there are issues that may be barriers to prompt recognition and management of the illness.6062 In India, women who deliver at a health facility often stay for less than 48 hours after delivery.63 This leaves little opportunity for health personnel to counsel the mother and family members on the signs and symptoms of postpartum depression and when to seek care. In low- and middle-income countries, the proportion of women who visit the health facility for postpartum visits is generally low and consequently mental disorders often remain undetected and unmanaged, especially for those delivering at home.64 Analysis of demographic and health survey data from 75 countdown countries showed that postnatal care visits for mothers have low coverage among interventions on the continuum of maternal and child care65 Postnatal traditions, such as the period of seclusion at home observed in many cultures, can negatively affect care-seeking behaviour in the postpartum period. Furthermore, mothers may be reluctant to admit their suffering either because of social taboos associated with depression or concerns about being labelled as a mother who failed to deliver the responsibilities of child care. In the current public health system in most low- and middle-income countries, including India, primary-care workers are supposed to be in regular contact with recently delivered mothers. However, at postnatal visits community health workers tend to focus on promoting essential infant care practices, with lower priority given to the mother’s health.63,66 These factors might explain, to some extent, the lack of availability of reliable, routine data on the burden of postpartum depression in low- and middle-income countries.

A strength of our study is the large sample of recently delivered mothers included in the review. This is probably the first review that documents the overall estimated prevalence of postpartum depression in India. The study has its limitations as well. Most of the studies included in the review did not provide effect sizes against the risk factors for postpartum depression and this precluded pooling of risk factors to provide an estimate. Most of the studies included in the review used the Edinburgh postnatal depression scale and the cut-offs used to label postpartum depression varied among studies. This could limit the internal validity of our findings. We observed significant heterogeneity in the results and performed subgroup analysis and meta-regression. The meta-regression analysis was able to explain < 10% of the heterogeneity and suggests that unidentified factors were causing such heterogeneity.

Among the studies included in our review, risk factors for postpartum depression included financial difficulties, birth of a female child, marital conflict, lack of support from the family, past history of psychiatric illness, high parity, complications during pregnancy and low maternal education. Previous studies from low- and middle-income countries report similar risk factors.58,67

We found relatively higher pooled proportion of postpartum depression in mothers residing in urban than in rural areas. This may be due to factors such as overcrowding, inadequate housing, breakdown of traditional family structures leading to fragmented social support systems, increased work pressure, high cost of living and increased out-of-pocket expenditure on health care.68 Pooling of hospital-based studies found comparatively higher estimates of postpartum depression than studies in community settings. It is likely that mothers suffering from any illness during the postnatal period, including postnatal depression, will seek care at a health facility, compared to physically healthy mothers and babies who may not visit a facility at all. Moreover, being in a hospital environment provides an opportunity for the mother to express her concerns and problems to the health personnel, but when interviewed at her home she may not admit to having depressive symptoms, owing to the presence of other family members or neighbours and the social stigma attached to mental health conditions.

On subgroup analysis, we found a slightly higher proportion of postpartum depression in mothers who were aged > 25 years compared with those aged ≤ 25 years. Moreover, high maternal age emerged as a risk factor for depression in 4/28 studies which included this variable compared with 3/28 studies reporting low maternal age as a risk. Older mothers may suffer more from depression because they lack peer support or because they have more obstetric complications and multiple births or greater use of assisted reproductive technologies.6971 On the other hand, it is possible that depression among older mothers is simply a biological phenomenon.

In our meta-analysis, geographical variation in the prevalence of postpartum depression was observed, with the highest prevalence in the southern regions. The observed differences in prevalence were not statistically significant on meta-regression and therefore more data are needed to document any significant geographical variations. The southern parts of the country have high literacy rates, which could lead to increased awareness about this health issue and therefore increased care-seeking.72 Moreover, the health system in southern India is more organized and there is comparatively better primary health-care provision than in other parts of the country and this could be a factor in greater care-seeking.73 South India also has a higher proportion of people living in urban slums compared with the northern parts of the country and greater rates of intimate partner violence.74,75

We found that the number of studies on postpartum depression has seen an upward trend in the last five years. There were 26 published studies between 2011‒2016, compared with six each in the periods 2000‒2005 and 2006‒2010. This reflects a recent interest of the medical research community towards this important issue.

There are a lack of data on perinatal mental health problems from low- and middle-income countries76 and this gap in the evidence hinders the process of establishing interventions to promote maternal psychosocial health. Gathering data on perinatal mental health issues will be essential in these countries, not only to gauge the magnitude of the problem, but also to inform policy-makers. Such evidence can stimulate governments to allocate resources for capacity-building in maternal mental health care, such as developing and implementing guidelines and protocols for screening and treatment, and setting targets for reducing the burden of postpartum depression.

Acknowledgements

We thank Mary V. Seeman (Department of Psychiatry, University of Toronto, Canada) and Meenakshi Bhilwar (Department of Community Medicine, Vardhman Mahavir Medical College and Safdarjung Hospital, New Delhi). Aslyeh Salehi is also affiliated with the Menzies Health Institute, Queensland, Australia.

Competing interests:

None declared.

References

  • 1.Stewart DE, Robertson E, Dennis CL, Grace SL, Wallington T. Postpartum depression: literature review of risk factors and interventions. Toronto: University Health Network Women’s Health Program; 2003. Available from: http://www.who.int/mental_health/prevention/suicide/lit_review_postpartum_depression.pdf [cited 2017 May 16].
  • 2.Di Florio A, Smith S, Jones I. Postpartum psychosis. The Obstetrician & Gynaecologist. 2013;15(3):145–50. 10.1111/tog.12041 [DOI] [Google Scholar]
  • 3.VanderKruik R, Barreix M, Chou D, Allen T, Say L, Cohen LS; Maternal Morbidity Working Group. The global prevalence of postpartum psychosis: a systematic review. BMC Psychiatry. 2017. July 28;17(1):272. 10.1186/s12888-017-1427-7 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.O’hara MW, Swain AM. Rates and risk of postpartum depression –a meta-analysis. Int Rev Psychiatry. 1996;8(1):37–54. 10.3109/09540269609037816 [DOI] [Google Scholar]
  • 5.Field T. Postpartum depression effects on early interactions, parenting, and safety practices: a review. Infant Behav Dev. 2010. February;33(1):1–6. 10.1016/j.infbeh.2009.10.005 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Surkan PJ, Kennedy CE, Hurley KM, Black MM. Maternal depression and early childhood growth in developing countries: systematic review and meta-analysis. Bull World Health Organ. 2011. August 1;89(8):608–15D. 10.2471/BLT.11.088187 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Sohr-Preston SL, Scaramella LV. Implications of timing of maternal depressive symptoms for early cognitive and language development. Clin Child Fam Psychol Rev. 2006. March;9(1):65–83. 10.1007/s10567-006-0004-2 [DOI] [PubMed] [Google Scholar]
  • 8.Verkuijl NE, Richter L, Norris SA, Stein A, Avan B, Ramchandani PG. Postnatal depressive symptoms and child psychological development at 10 years: a prospective study of longitudinal data from the South African Birth to Twenty cohort. Lancet Psychiatry. 2014. November;1(6):454–60. 10.1016/S2215-0366(14)70361-X [DOI] [PubMed] [Google Scholar]
  • 9.Dennis CL, Stewart DE. Treatment of postpartum depression, part 1: a critical review of biological interventions. J Clin Psychiatry. 2004. September;65(9):1242–51. 10.4088/JCP.v65n0914 [DOI] [PubMed] [Google Scholar]
  • 10.Fisher J, Cabral de Mello M, Patel V, Rahman A, Tran T, Holton S, et al. Prevalence and determinants of common perinatal mental disorders in women in low- and lower-middle-income countries: a systematic review. Bull World Health Organ. 2012. February 1;90(2):139–49G. 10.2471/BLT.11.091850 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Saxena S, Thornicroft G, Knapp M, Whiteford H. Resources for mental health: scarcity, inequity, and inefficiency. Lancet. 2007. September 8;370(9590):878–89. 10.1016/S0140-6736(07)61239-2 [DOI] [PubMed] [Google Scholar]
  • 12.Baron EC, Hanlon C, Mall S, Honikman S, Breuer E, Kathree T, et al. Maternal mental health in primary care in five low- and middle-income countries: a situational analysis. BMC Health Serv Res. 2016. February 16;16(1):53. 10.1186/s12913-016-1291-z [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Trends in maternal mortality: 1990 to 2015: estimates by WHO, UNICEF, UNFPA, World Bank Group and the United Nations Population Division. Geneva: World Health Organization; 2015. Available from: http://apps.who.int/iris/bitstream/10665/194254/1/9789241565141_eng.pdf?ua=1 [cited 2017 Aug 25].
  • 14.Herzog R, Álvarez-Pasquin MJ, Díaz C, Del Barrio JL, Estrada JM, Gil Á. Are healthcare workers’ intentions to vaccinate related to their knowledge, beliefs and attitudes? A systematic review. BMC Public Health. 2013. February 19;13(1):154. 10.1186/1471-2458-13-154 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Wells G, Shea B, O’Connell D, Peterson J, Welch V, Losos M, et al. The Newcastle-Ottawa (NOS) for assessing the quality of nonrandomized studies in meta-analysis. Ottawa: Ottawa Hospital Research Institute. Available from: http://www.ohri.ca/programs/clinical_epidemiology/oxford.asp [cited 2017 Aug 25].
  • 16.Higgins JPT, Green S, editors. Cochrane handbook for systematic reviews of interventions. London: The Cochrane Collaboration; 2008 . Available from: https://dhosth.files.wordpress.com/2011/12/cochrane-handbook-for-systematic-reviews-of-interventions.pdfhttp://[cited 2017 Aug 25].
  • 17.Lee DT, Yip AS, Chan SS, Tsui MH, Wong WS, Chung TK. Postdelivery screening for postpartum depression. Psychosom Med. 2003. May-Jun;65(3):357–61. 10.1097/01.PSY.0000035718.37593.87 [DOI] [PubMed] [Google Scholar]
  • 18.Dennis CL, Ross LE. Depressive symptomatology in the immediate postnatal period: identifying maternal characteristics related to true- and false-positive screening scores. Can J Psychiatry. 2006. April;51(5):265–73. 10.1177/070674370605100501 [DOI] [PubMed] [Google Scholar]
  • 19.Shivalli S, Gururaj N. Postnatal depression among rural women in South India: do socio-demographic, obstetric and pregnancy outcome have a role to play? PLoS One. 2015. April 7;10(4):e0122079. 10.1371/journal.pone.0122079 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Shrestha N, Hazrah P, Sagar R. Incidence and prevalence of postpartum depression in a rural community of India. J Chitwan Med Coll. 2015;5(2):11–9. 10.3126/jcmc.v5i2.13149 [DOI] [Google Scholar]
  • 21.Suguna A, Naveen R, Surekha A. Postnatal depression among women attending a rural maternity hospital in south India. Ntl J Community Med. 2015;6(3):297–301. Available from: www.njcmindia.org/home/download/689 [cited 2017 Jul 19].
  • 22.Kumar P, Krishna A, Sanjay SC, Revathy R, Nagendra K, Thippeswamy NR, et al. Determinants of postnatal depression among mothers in a rural setting in Shimoga District, Karnataka. A cross-sectional descriptive study. Int J Preven Curat Comm Med. 2015;1(4):74–9. [Google Scholar]
  • 23.Srivastava AS, Mara B, Pandey S, Tripathi MN, Pandit B, Yadav JS. Psychiatric morbidities in postpartum females: a prospective follow-up during puerperium. Open J Psychiatry Allied Sci. 2015;6(2):101–5. 10.5958/2394-2061.2015.00005.1 [DOI] [Google Scholar]
  • 24.Kolisetty R, Jyothi NU. Postpartum depression- a study from a tertiary care hospital. Indian J Basic Appl Med Res. 2015;4(4):277–81. [Google Scholar]
  • 25.Bodhare TN, Sethi P, Bele SD, Gayatri D, Vivekanand A. Postnatal quality of life, depressive symptoms, and social support among women in southern India. Women Health. 2015;55(3):353–65. 10.1080/03630242.2014.996722 [DOI] [PubMed] [Google Scholar]
  • 26.Hirani D, Bala DV. A study of postnatal depression and its determinants in postnatal women residing in rural areas of Ahemdabad district, Gujarat, India. IOSR-JDMS. 2015;14(7):10–5. [Google Scholar]
  • 27.Hiremath P, Mohite VR, Naregal P, Chendake M, Gholap MC. A study to determine the prevalence of postnatal depression among primigravida mothers in Krishna hospital Karad. Int J Sci Res. 2015;4(2):247–9. [Google Scholar]
  • 28.Patel HL, Ganjiwale JD, Nimbalkar AS, Vani SN, Vasa R, Nimbalkar SM. Characteristics of postpartum depression in Anand District, Gujarat, India. J Trop Pediatr. 2015. October;61(5):364–9. 10.1093/tropej/fmv046 [DOI] [PubMed] [Google Scholar]
  • 29.Johnson AR, Edwin S, Joachim N, Mathew G, Ajay S, Joseph B. Postnatal depression among women availing maternal health services in a rural hospital in South India. Pak J Med Sci. 2015. Mar-Apr;31(2):408–13. 10.12669/pjms.312.6702 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Poomalar GK, Arounassalame B. Impact of socio-cultural factors on postpartum depression in South Indian women. Int J Reprod Contracept Obstet Gynecol. 2014;3(2):338–43. [Google Scholar]
  • 31.Dhande N, Khapre M, Nayak S, Mudey A. Assessment of postnatal depression among mothers following delivery in rural area of Wardha District: a cross sectional study. Innov J Med Health Sci. 2014;4(2):53–5. [Google Scholar]
  • 32.Saldanha D, Rathi N, Bal H, Chaudhari B. Incidence and evaluation of factors contributing towards postpartum depression. Med J D Y Patil Univ. 2014;7(3):309–16. 10.4103/0975-2870.128972 [DOI] [Google Scholar]
  • 33.Jain A, Tyagi P, Kaur P, Puliyel J, Sreenivas V. Association of birth of girls with postnatal depression and exclusive breastfeeding: an observational study. BMJ Open. 2014. June 9;4(6):e003545. 10.1136/bmjopen-2013-003545 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34.Dhiman P, Say A, Rajendiren S, Kattimani S, Sagili H. Association of foetal APGAR and maternal brain derived neurotropic factor levels in postpartum depression. Asian J Psychiatr. 2014. October;11:82–3. 10.1016/j.ajp.2014.06.022 [DOI] [PubMed] [Google Scholar]
  • 35.Gupta S, Kishore J, Mala YM, Ramji S, Aggarwal R. Postpartum depression in north Indian women: prevalence and risk factors. J Obstet Gynaecol India. 2013. August;63(4):223–9. 10.1007/s13224-013-0399-x [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 36.Prakash M, Komal PT, Pragna S. Sociocultural bias about female child and its influences on postpartum depressive features. Int J Sci Res. 2013;2(12):462–3. [Google Scholar]
  • 37.Sudeepa D, Madhukumar S, Gaikwad V. A study on postnatal depression of women in rural Bangalore. Int J Health Sci Res. 2013;3(1):1–6. [Google Scholar]
  • 38.Gokhale AV, Vaja A. Screening for postpartum depression. Gujarat Med J. 2013;68(2):46–51. [Google Scholar]
  • 39.Desai N, Mehta R, Ganjiwale J. Study of prevalence and risk factors of postpartum depression. Natl J Med Res. 2012;2(2):194–8. [Google Scholar]
  • 40.Hegde S, Latha KS, Bhat SM, Sharma PSVN, Kamath A, Shetty AK. Postpartum depression: prevalence and associated factors among women in India. J Womens Health Issues Care. 2012;1(1):1–7. [Google Scholar]
  • 41.Dubey C, Gupta N, Bhasin S, Muthal RA, Arora R. Prevalence and associated risk factors for postpartum depression in women attending a tertiary hospital, Delhi, India. Int J Soc Psychiatry. 2012. November;58(6):577–80. 10.1177/0020764011415210 [DOI] [PubMed] [Google Scholar]
  • 42.Prost A, Lakshminarayana R, Nair N, Tripathy P, Copas A, Mahapatra R, et al. Predictors of maternal psychological distress in rural India: a cross-sectional community-based study. J Affect Disord. 2012. May;138(3):277–86. 10.1016/j.jad.2012.01.029 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 43.Iyengar K, Yadav R, Sen S. Consequences of maternal complications in women’s lives in the first postpartum year: a prospective cohort study. J Health Popul Nutr. 2012. June;30(2):226–40. 10.3329/jhpn.v30i2.11318 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 44.Manjunath NG, Venkatesh G, Rajanna. Postpartum blue is common in socially and economically insecure mothers. Indian J Community Med. 2011. July;36(3):231–3. 10.4103/0970-0218.86527 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 45.Sankapithilu GJ, Nagaraj AKM, Bhat SU, Raveesh BN, Nagaraja V. A comparative study of frequency of postnatal depression among subjects with normal and caesarean deliveries. Online J Health Allied Sci. 2010;9(2): 1–5. [Google Scholar]
  • 46.Savarimuthu RJ, Ezhilarasu P, Charles H, Antonisamy B, Kurian S, Jacob KS. Post-partum depression in the community: a qualitative study from rural South India. Int J Soc Psychiatry. 2010. January;56(1):94–102. 10.1177/0020764008097756 [DOI] [PubMed] [Google Scholar]
  • 47.Ghosh A, Goswami S. Evaluation of post partum depression in a tertiary hospital. J Obstet Gynaecol India. 2011. October;61(5):528–30. 10.1007/s13224-011-0077-9 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 48.Mariam KA, Srinivasan K. Antenatal psychological distress and postnatal depression: A prospective study from an urban clinic. Asian J Psychiatr. 2009. June;2(2):71–3. 10.1016/j.ajp.2009.04.002 [DOI] [PubMed] [Google Scholar]
  • 49.Nagpal J, Dhar RS, Sinha S, Bhargava V, Sachdeva A, Bhartia A. An exploratory study to evaluate the utility of an adapted Mother Generated Index (MGI) in assessment of postpartum quality of life in India. Health Qual Life Outcomes. 2008. December 2;6(1):107. 10.1186/1477-7525-6-107 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 50.Kalita KN, Phookun HR, Das GC. A clinical study of postpartum depression: validation of the Edinburgh postnatal depression scale (Assamese version). Eastern J Psychiatry. 2014;11(1):14–8. [Google Scholar]
  • 51.Prabhu TR, Asokan TV, Rajeswari A. Postpartum psychiatric illness. J Obstet Gynaecol India. 2005;55(4):329–32. [Google Scholar]
  • 52.Sood M, Sood AK. Depression in pregnancy and postpartum period. Indian J Psychiatry. 2003. January;45(1):48–51. [PMC free article] [PubMed] [Google Scholar]
  • 53.Patel V, DeSouza N, Rodrigues M. Postnatal depression and infant growth and development in low income countries: a cohort study from Goa, India. Arch Dis Child. 2003. January;88(1):34–7. 10.1136/adc.88.1.34 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 54.Chandran M, Tharyan P, Muliyil J, Abraham S. Post-partum depression in a cohort of women from a rural area of Tamil Nadu, India. Incidence and risk factors. Br J Psychiatry. 2002. December;181(6):499–504. 10.1192/bjp.181.6.499 [DOI] [PubMed] [Google Scholar]
  • 55.Patel V, Rodrigues M, DeSouza N. Gender, poverty, and postnatal depression: a study of mothers in Goa, India. Am J Psychiatry. 2002. January;159(1):43–7. 10.1176/appi.ajp.159.1.43 [DOI] [PubMed] [Google Scholar]
  • 56.Affonso DD, De AK, Horowitz JA, Mayberry LJ. An international study exploring levels of postpartum depressive symptomatology. J Psychosom Res. 2000. September;49(3):207–16. 10.1016/S0022-3999(00)00176-8 [DOI] [PubMed] [Google Scholar]
  • 57.Gavin NI, Gaynes BN, Lohr KN, Meltzer-Brody S, Gartlehner G, Swinson T. Perinatal depression: a systematic review of prevalence and incidence. Obstet Gynecol. 2005. November;106(5 Pt 1):1071–83. 10.1097/01.AOG.0000183597.31630.db [DOI] [PubMed] [Google Scholar]
  • 58.Gelaye B, Rondon MB, Araya R, Williams MA. Epidemiology of maternal depression, risk factors, and child outcomes in low-income and middle-income countries. Lancet Psychiatry. 2016. October;3(10):973–82. 10.1016/S2215-0366(16)30284-X [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 59.Joseph G, da Silva IC, Wehrmeister FC, Barros AJ, Victora CG. Inequalities in the coverage of place of delivery and skilled birth attendance: analyses of cross-sectional surveys in 80 low and middle-income countries. Reprod Health. 2016. June 17;13(1):77. 10.1186/s12978-016-0192-2 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 60.Mannava P, Durrant K, Fisher J, Chersich M, Luchters S. Attitudes and behaviours of maternal health care providers in interactions with clients: a systematic review. Global Health. 2015. August 15;11(1):36. 10.1186/s12992-015-0117-9 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 61.Keng SL. Malaysian midwives’ views on postnatal depression. Br J Midwifery. 2005;13(2):78–86. 10.12968/bjom.2005.13.2.17465 [DOI] [Google Scholar]
  • 62.Goldsmith ME. Postpartum depression screening by family nurse practitioners. J Am Acad Nurse Pract. 2007. June;19(6):321–7. 10.1111/j.1745-7599.2007.00232.x [DOI] [PubMed] [Google Scholar]
  • 63.Home based newborn care operational guidelines (revised 2014). New Delhi: Ministry of Health and Family Welfare; 2014. Available from: http://nhm.gov.in/images/pdf/programmes/child-health/guidelines/Revised_Home_Based_New_Born_Care_Operational_Guidelines_2014.pdf [cited 2017 May 28].
  • 64.Langlois ÉV, Miszkurka M, Zunzunegui MV, Ghaffar A, Ziegler D, Karp I. Inequities in postnatal care in low- and middle-income countries: a systematic review and meta-analysis. Bull World Health Organ. 2015. April 1;93(4):259–270G. 10.2471/BLT.14.140996 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 65.Victora CG, Requejo JH, Barros AJ, Berman P, Bhutta Z, Boerma T, et al. Countdown to 2015: a decade of tracking progress for maternal, newborn, and child survival. Lancet. 2016. May 14;387(10032):2049–59. 10.1016/S0140-6736(15)00519-X [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 66.Tripathi A, Kabra SK, Sachdev HP, Lodha R. Home visits by community health workers to improve identification of serious illness and care seeking in newborns and young infants from low- and middle-income countries. J Perinatol. 2016. May;36 Suppl 1:S74–82. 10.1038/jp.2016.34 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 67.Shidhaye P, Giri P. Maternal depression: a hidden burden in developing countries. Ann Med Health Sci Res. 2014. July;4(4):463–5. 10.4103/2141-9248.139268 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 68.Lund C, Breen A, Flisher AJ, Kakuma R, Corrigall J, Joska JA, et al. Poverty and common mental disorders in low and middle income countries: A systematic review. Soc Sci Med. 2010. August;71(3):517–28. 10.1016/j.socscimed.2010.04.027 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 69.Bayrampour H, Heaman M, Duncan KA, Tough S. Advanced maternal age and risk perception: a qualitative study. BMC Pregnancy Childbirth. 2012. September 19;12(1):100. 10.1186/1471-2393-12-100 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 70.McMahon CA, Boivin J, Gibson FL, Fisher JRW, Hammarberg K, Wynter K, et al. Older first-time mothers and early postpartum depression: a prospective cohort study of women conceiving spontaneously or with assisted reproductive technologies. Fertil Steril. 2011. November;96(5):1218–24. 10.1016/j.fertnstert.2011.08.037 [DOI] [PubMed] [Google Scholar]
  • 71.Carlson DL. Explaining the curvilinear relationship between age at first birth and depression among women. Soc Sci Med. 2011. February;72(4):494–503. 10.1016/j.socscimed.2010.12.001 [DOI] [PubMed] [Google Scholar]
  • 72.Office of the Registrar General and Census Commissioner. State of literacy. Chapter 6. In: Provisional population totals – India. New Delhi: Ministry of Home Affairs, 2011. Available from: http://censusindia.gov.in/2011-prov-results/data_files/india/Final_PPT_2011_chapter6.pdf [cited 2017 Aug 18]. India
  • 73.Parthasarathi R, Sinha SP. Towards a better health care delivery system: the Tamil Nadu model. Indian J Community Med. 2016. Oct-Dec;41(4):302–4. 10.4103/0970-0218.193344 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 74.Slums in India: a statistical compendium (2015). New Delhi: Ministry of Housing and Urban Poverty Alleviation; 2015. Available from: http://nbo.nic.in/Images/PDF/SLUMS_IN_INDIA_Slum_Compendium_2015_English.pdf [cited 2017 Aug 18].
  • 75.National family health survey (NFHS-4) 2015–16. Mumbai: International Institute for Population Sciences (IIPS) and Macro International; 2016.
  • 76.Maternal mental health and child health and development in low and middle income countries: report of the meeting held in Geneva, Switzerland, 30 January–1 February, 2008. Geneva: World Health Organization; 2008. Available from: http://www.who.int/mental_health/prevention/suicide/mmh_jan08_meeting_report.pdf [cited 2017 May 22].

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