Skip to content

Advertisement

  • Research
  • Open Access

Postpartum depressive symptoms in the context of high social adversity and reproductive health threats: a population-based study

International Journal of Mental Health Systems201812:42

https://doi.org/10.1186/s13033-018-0219-x

  • Received: 19 February 2018
  • Accepted: 14 July 2018
  • Published:

Abstract

Background

Postpartum depression is an important but neglected public health issue in low- and middle-income countries. The aim of this study was to assess postpartum depressive (PPD) symptoms and associated factors in a rural Ethiopian setting characterized by high social adversity and reproductive health threats. We hypothesized that infant gender preference would be associated with PPD symptoms.

Methods

A cross-sectional, population-based study was conducted in Sodo district, southern Ethiopia, between March and June 2014. A total of 3147 postpartum women (one to 12 months after delivery) were recruited and interviewed in their homes. The questionnaire included demographic, reproductive health and psychosocial factors in addition to a culturally validated measure of depressive symptoms, the Patient Health Questionnaire. Scores of 5 or more were indicative of high levels of PPD symptoms.

Results

The prevalence of high PPD symptoms was 12.2%, with 95% confidence interval (CI) between 11.1 and 13.4. Of these, 12.0% of the study participants had suicidal ideation. Preference of the husband for a boy baby was associated with PPD symptoms in univariate analysis (crude odds ratio 1.43: 95% CI 1.04, 1.91) but became non-significant after adjusting for confounders. In the final multivariable analysis, rural residence [adjusted odds ratio (aOR) 2.56: 95% CI 2.56, 4.19], grand multiparity (aOR 2.00: 1.22, 3.26), perinatal complications (aOR: 2.55: 1.89, 3.44), a past history of abortion (aOR 1.50: 1.07, 2.11), experiencing hunger in the preceding 1 month (aOR 2.38: 1.75, 3.23), lower perceived wealth (aOR 2.11: 1.19, 3.76), poor marital relationship (aOR 2.47: 1.79, 3.42), and one or more stressful events in the preceding 6 months (aOR 2.36: 1.82, 3.06) were associated significantly with high PPD symptoms.

Conclusion

PPD symptoms affected more than one in 10 women in this Ethiopian community setting. Social adversity and reproductive health threats were associated with poorer mental health. Interventions focusing on poor rural women with low access to care are necessary. This research can serve as an entry point for the adaptation of a psychosocial intervention.

Keywords

  • Postpartum depression
  • Social determinants
  • Developing countries
  • Ethiopia

Background

Postpartum depression (PPD) is a pressing but largely neglected public health concern in low- and middle-income countries (LMICs) [1]. The symptoms of PPD are the same as depressive symptoms at any other time in a person’s life [2]. The prevalence of PPD in LMICs is as high as, if not higher than, the prevalence seen in high-income countries [3]. Recent evidence on the prevalence of PPD was only available from 15% of LMICs [3] and indicated a weighted mean prevalence of perinatal common mental disorders (including depressive symptoms) of 19.8% [3]. In sub-Saharan Africa, many studies of PPD are facility-based or restricted to high risk populations, for example women with HIV, and are not representative of the general population of postpartum women. More representative community-based studies have mostly been conducted in Ethiopia and South Africa (Table 1). Most studies indicate a high burden of PPD symptoms, measured using validated depression screening scales, but with substantial variation in the estimated prevalence of PPD [47].
Table 1

Prevalence of postpartum depression in community-based studies from sub-Saharan Africa

Author, year

Country

Sample

Prevalence (%)

Measurement

Setting

Tsai et al. [76], (2016)

South Africa

1238

39.5

EPDS ≥ 13

Urban

Stellenberg et al. [6], (2015)

South Africa

159

50.3

EPDS ≥ 13

Rural

Hung et al. [77], (2014); Dewing et al. [68], (2013)

South Africa

249

31.7

EPDS ≥ 13

Urban

Cooper et al. [78], (1991)

South Africa

184

34.7

DSM-IV

Peri-urban

Ramchandani et al. [79], (2009)

South Africa

1035

16.0

PDQ ≥ 20

Urban

Tomlinson et al. [80], (2004)

South Africa

147

35.0

DSM-IV

Urban

Tefera et al. [4], (2015)

Ethiopia

340

31.5

SRQ ≥ 6

Urban

Baumgartner et al. [5], (2014)

Ethiopia

1319

32.8

SRQ ≥ 5

Rural and urban

Hanlon et al. [81], (2008)

Ethiopia

954

4.6

SRQ ≥ 6

Rural

Harpham et al. [82], (2005)

Ethiopia

1772

33

SRQ ≥ 6

Rural

Weobong et al. [7], (2015)

Ghana

13,360

3.8

PHQ ≥ 5

Rural

DSM-IV  Diagnostic and Statistical Manual of mental disorders fourth edition, EPDS Edinburgh Postnatal Depression Scale, PDQ Pitt Depression Questionnaire, PHQ Patient Health Questionnaire, SCID Structured Clinical Interview for DSM Disorders, SRQ Self-Reporting Questionnaire

PPD is likely to be an important factor contributing to elevated mortality in women in LMICs, through increasing the risk of suicide [8, 9]. There are several studies from LMICs which show a substantial burden of suicide in the perinatal period, for which unrecognized and untreated PPD is likely to have made an important contribution although information on the woman’s mental health prior to death is not known [1012]. An estimated 20% of deaths among women in the postpartum period in India are classified as suicide or accidental burns [12]. In a hospital-based retrospective study from Mozambique, 33% of deaths during the early postpartum period were from suicide [10]. In Nepal, suicide was the leading cause of maternal death, accounting for 16% [11]. Similarly, 13% of maternal deaths were attributed to suicide in Sri Lanka [13]. PPD also has implications for the child and has been linked to higher rates of stunting, diarrheal diseases, lower completion of recommended schedules of immunization, lower rate of exclusive breast feeding and poorer cognitive and social-emotional development among children in LMICs [1419].

Factors associated with PPD in LMICs include younger age [3, 20, 21], rural residence [3, 22], low income [3, 20, 23, 24], lack of social support [3, 24, 25], pregnancy and birth complications [3, 7, 22, 23, 26], unplanned pregnancy [3, 22, 27, 28], intimate partner violence [20, 22, 27] and non-adherence with perinatal sociocultural practices [29]. Gender preference has been frequently cited as a risk factor for PPD in Asian culture, but has not been adequately investigated in Africa [22, 23, 3033]. In Ethiopia and other sub-Saharan African countries, studies indicate that gender preference affects the decision to use family planning [34, 35]. Couples have been found to postpone the use of family planning if their live children are female, reflecting a desire for a male child. In a previous qualitative study from Ethiopia, there was a strong preference for boy babies [36], but in a subsequent quantitative study no association was found between giving birth to a boy when the husband preferred a boy and onset of PPD, but this study was under-powered [37].

Inconsistencies in the prevalence of PPD and associated factors are likely to be explained by use of different measures of depressive symptoms and associated factors, differing cut-off scores on self-report measures of PPD, differing definitions of the perinatal period, variation in sample size, the nature of the sample (rural, periurban or urban) and differences in the variables included in multivariable models.

There is a need for rigorously conducted, contextually sensitive and adequately powered studies to investigate the distribution of perinatal depressive symptoms in rural sub-Saharan African country settings. The information obtained will help to inform appropriate intervention strategies at both the individual and community level. The aim of this study was to assess the prevalence of high levels of PPD symptoms and associated factors in a setting of high social adversity and reproductive health threats in Ethiopia. We tested the hypothesis that infant gender preference would be associated with PPD in rural Ethiopia.

Methods

Study design: a population-based cross-sectional survey

Study setting

The study was conducted in Sodo district, of the Gurage zone, Southern Nations, Nationalities and Peoples’ Region (SNNPR) of Ethiopia. SNNPR is one of the largest regions in Ethiopia, accounting for more than 10 percent of the country’s land area. The SNNPR is an extremely ethnically diverse region of Ethiopia. These ethnic groups are distinguished by different languages, cultures and socioeconomic organizations. The Gurage zone has 15 districts. Sodo district is the second largest in terms of population (161,952 persons; 79,356 men and 82,596 women), with 88% of the population residing in rural areas [38] and comprises 58 sub-districts. It is located about 100 km south of the capital city, Addis Ababa.

In Sodo district, there are eight health centers, each linked to five health posts served by health extension workers. There is a general hospital 30 km away from the district town, Buee, which has an outpatient psychiatric service provided by a psychiatric nurse. However, at the time of the study there was no specialist mental health professional located within the district and no health care personnel trained in mental health care. As part of the Program for Improving Mental health carE (PRIME), plans were being made to integrate mental health care into primary care and maternal health care settings across the district [39]. PRIME is a multi-country implementation research project involving five LMICs (Ethiopia, India, Nepal, South Africa and Uganda) [40]. The analyses presented in this paper were from a formative study which was conducted to identify the treatment gap for women with post-partum depression and their preferred help-seeking [41] and coping strategies [42] in order to inform service development. In this paper we focus on the identification of risk factors for development of PPD.

Recruitment

We attempted to identify and recruit all women between one and 12 months postpartum with live infants who were residing in Sodo district. A total of 3147 women were recruited from the 58 sub-districts of the study district, identified by locators in a house-to-house census triangulated with the list of infants from the PRIME census [43] and immunization reports for the whole district obtained from the district health office. Further details of the sample identification have been described previously [41]. The eligibility criteria included being a resident of the study district for 1 year or more, having a live infant, being between one and 12 months postpartum and not exhibiting overt behavioral disturbance indicative of severe mental illness. Each household containing an eligible woman was visited by a data collector who then explained the purpose of the research and gave the woman an information sheet or read the information aloud for those who were unable to read. Women who consented to participate were interviewed at a time and place that was convenient for them, but for the most part the interview took place within their homes. The interviews took approximately 1 hour to complete.

Measures

PPD symptoms were measured using the Patient Health Questionnaire (PHQ-9). The PHQ-9 was developed originally to measure depression in primary care settings [44]. The PHQ-9 has been culturally validated for use in several African country settings [3, 29, 4547] including in postpartum women in rural Ghana [48] and in the primary health care and antenatal care settings in the neighbouring district to this study [49, 50]. In the Ethiopia primary care validation, a score of 5 or more was found to have a sensitivity of 83% and specificity of 75% for the detection of major depressive disorder. In antenatal women, the validated cut-off was four and above, giving a sensitivity of 86.7% and a specificity of 80.4%.

Gender preference was measured by asking the woman whether she was happy with her child’s gender (yes/no) and whether she perceived that her husband was happy with the child’s gender (yes/no).

Potential confounders/explanatory variables

Social support was assessed using the Oslo Social Support Scale (OSSS-3). The total score as well as the individual items of the OSSS-3 may be used. A total score ranging between 3 and 8 is classified as poor social support, a score between 9 and 11 as intermediate support, and a score between 12 and 14 as strong support [51]. The OSSS-3 has been used in Ethiopia in various settings, including the community for this study [43, 5254].

Stressful events were measured by the list of threatening experiences (LTE-12) [55]. The LTE has been found to have convergent validity in various studies in Ethiopia [43, 53, 54]. Alcohol use disorder was indicated using the Fast Alcohol Screening Test [56], a four item questionnaire that has been adapted and used in the study site previously [43]. A score of 3 or more indicates probable hazardous or harmful drinking. Perinatal complications were assessed by asking the woman “Have you had pregnancy, or birth-related difficulties? If yes, what were they?” (coded as haemorrhage, prolonged labour or high blood pressure).

Data collection and quality assurance

A total of 36 data collectors and four supervisors, who were recruited from the district by the PRIME project and had experience of data collection, were trained for 9 days. The educational levels of the data collectors ranged from tenth grade completed to first degree. They were supervised by four supervisors who were also trained and assisted by the investigators. The supervisors were diploma or degree graduates. A pre-test was conducted in three sub-districts near the study area. Data were collected between April and June 2014.

Data management and analysis

Data were double entered into EpiData version 3.1 and exported to the Statistical Packages for Social Sciences, version 20 (SPSS-20) for analysis. Frequencies, percentages, and mean values were used to describe the categorical and continuous variables. Bivariate analyses were carried out to investigate the association between symptoms of PPD and several demographic, obstetric, and psychosocial variables. The hypothesis that the woman’s perception that her husband was unhappy with the gender of the baby would be associated with PPD was tested by controlling for demographic and obstetric factors in the multivariable analysis. All variables with a p-value < 0.2 were included in the multivariable model. Adjusted odds ratios with associated 95% confidence intervals were reported in the final multiple logistic regression model.

Ethical considerations

Ethical approval was obtained from the Institutional Review Board of the College of Health Sciences, Addis Ababa University. Permission was also obtained from the Sodo District Health Office and administration. Women who agreed to participate gave written consent. For those who were not literate, independent witnesses were invited to sign to indicate that the information had been read out correctly. Non-literate participants then gave a finger print to indicate consent. Women who endorsed the PHQ item indicating suicidal ideation and those with higher than or equal to 10 in the PHQ were linked to the Butajira hospital psychiatric nurse-led outpatient clinic.

Results

A total of 3147 women between one and 12 months postpartum (mean 5.89 months postpartum; standard deviation (SD) 3.42) were included in the study. One woman was excluded and referred for specialist mental health care with probable psychotic symptoms. No women refused to participate in the study.

The mean age of the respondents was 27.9 years (SD 5.3). Concerning the gender of the baby, 8.8% (n = 276) of the women and 11.6% (n = 366) of their husbands reported being unhappy. More husbands were happy about the baby’s gender if the baby was male (55.9% for male vs. 44.1% for female) (Table 2).
Table 2

Socio-demographic, obstetric, and psychosocial characteristics of postpartum women in Sodo district, Ethiopia (n = 3147)

Characteristics of participants

Frequency

Percent

Age (years)

 Less than 20

107

3.4

 20–29

1754

55.7

 30–39

1217

38.7

 40 or more

69

2.2

Marital status

 Not currently married

51

1.6

 Married

3096

98.4

Residence

 Rural

2788

88.6

 Urban

359

11.4

Education attended

 No formal education

2212

70.3

 Primary education

802

25.5

 Secondary and above

133

4.2

Occupational status

 Housewife

2722

86.5

 Government or private employee

351

11.2

 No job or daily laborer

74

2.4

Religion

 Orthodox Christian

2931

93.1

 Protestant, Muslim, Catholic or other

216

6.9

Ethnicity

 Gurage

2856

90.8

 Amhara, oromo or other

291

9.2

Baby gender

 Male

1607

51.1

 Female

1540

48.9

Happy about baby gender

 Yes

2871

91.2

 No

276

8.8

Husband happy about baby gender

 Yes

2781

88.4

 No

366

11.6

Perinatal complicationa

 Yes

346

11.0

 No

2801

89.0

History of stillbirth

 Yes

162

5.1

 No

2985

94.9

History of abortion

 Yes

296

9.4

 No

2851

90.6

Parity of women

 Primipara

504

16.0

 Multipara

1393

44.3

 Grand multipara

1250

39.7

Experienced hunger in the past 1 month

 Yes

434

13.8

 No

2713

86.2

Relative wealth

 Less

800

25.4

 Same

2083

66.2

 Better

264

8.4

Level of social support

 Poor support

569

18.1

 Intermediate support

1565

49.7

 Strong support

1013

32.2

Stressful event in the past 6 months

 No

1621

51.5

 1 stressful event

715

22.7

 2 or more stressful events

811

25.8

Husband drinks too much alcohol

 No

2450

77.9

 Yes

697

22.1

Marital relationship

 Poor

291

9.2

 Good

2856

90.8

Problem drinking (≥ 3 on the FAST)

 No

3121

99.2

 Yes

26

0.8

FAST Fast Alcohol Screening Test

aBleeding in pregnancy or post-partum period, prolonged labour or high blood pressure

The prevalence of high PPD symptoms (PHQ-9 score of 5 or more) was 12.2% (385/3147) with 95% confidence interval 11.1–13.4. The prevalence estimates for PPD symptoms did not differ across the postpartum period: 1–3 months postpartum 12.7% (129/1012), 4–6 months 11.1% (80/723) and 7–12 months 12.5% (176/1412).

Factors associated with PPD symptoms

In the bivariate analysis, the odds of having PPD symptoms were 1.43 times higher in women whose husbands were not happy about the baby gender: 95% confidence interval (CI) 1.04–1.91. However, the association became non-significant in the multivariable model. In the multivariable analysis, the following were associated significantly with PPD symptoms: rural residence, grand multi-parity, history of complication during pregnancy of the index child, past history of abortion, experiencing hunger in the preceding month due to lack of food, perceived wealth less than the neighbors, poor marital relationship, and having had one or more negative events during the preceding 6 months (Table 3).
Table 3

Crude and adjusted odds ratios for factors associated with postpartum depressive symptoms in women from Sodo district, Ethiopia

Characteristic

Postpartum depressive symptoms (Patient Health Questionnaire-9 ≥ 5) N = 3147

Crude odds ratio (95% confidence interval)

Adjusted Odds ratio (95% confidence interval) (n = 3147)

Yes 385 (12.2)

No 2762 (88.8)

Age (years)

 < 20

11 (10.3)

96 (89.7)

Reference

Reference

 20–29

191 (10.9)

1563 (89.1)

1.06 (0.56, 2.02)

2.38 (0.76, 7.39)

 30–39

175 (14.4)

1042 (85.6)

1.46 (0.77, 2.79)

1.90 (0.82, 4.38)

 40 or more

8 (11.6)

61 (88.4)

1.14 (0.43, 3.00)

1.87 (0.83, 4.20)

Not currently married

11 (21.6)

40 (78.4)

2.00 (1.01, 3.93)

1.05 (0.46, 2.40)

Rural residence

363 (13.0)

2425 (87.0)

2.93 (1.46, 3.57)

2.60 (1.58, 4.27)

No formal education

308 (13.9)

1904 (86.1)

1.80 (1.38, 2.34)

1.31 (0.96, 1.80)

Husband unhappy about baby gender

58 (15.8)

308 (84.2)

1.43 (1.04, 1.91)

1.20 (0.77, 1.85)

Perinatal complication

86 (24.9)

260 (75.1)

2.76 (2.10, 3.63)

2.43 (1.80, 3.29)

History of stillbirth

37 (22.8)

125 (77.2)

2.24 (1.52, 3.29)

1.42 (0.92, 2.19)

History of abortion

61 (20.6)

235 (79.4)

2.02 (1.49, 2.74)

1.45 (1.03, 2.04)

Parity

 Primiparous

40 (7.9)

464 (92.1)

Reference

Reference

 2–4 live births

149 (10.7)

1244 (89.3)

1.38 (0.96, 2.00)

1.43 (0.91, 2.23)

 Five or more

196 (15.7)

1054 (84.3)

2.15 (1.50, 3.08)

1.94 (1.18, 3.20)

Hunger in the previous month

126 (29.0)

308 (71.0)

3.87 (3.03, 4.94)

1.95 (1.43, 2.67)

Relative wealth

 Less

171 (21.4)

629 (78.6)

4.21 (2.47, 7.18)

1.84 (1.03, 3.29)

 Same

198 (9.5)

1885 (90.5)

1.62 (0.96, 2.75)

1.34 (0.77, 2.31)

 Better

16 (6.1)

248 (93.9)

Reference

Reference

Social support

 Poor

104 (18.3)

465 (81.7)

2.18 (1.61, 2.95)

0.89 (0.66, 1.19)

 Intermediate

187 (11.9)

1378 (88.1)

1.32 (1.02, 1.72)

0.81 (0.58, 1.14)

 Strong

94 (9.3)

919 (90.7)

Reference

Reference

Husband does not live in the same house

70 (18.0)

319 (82.0)

1.70 (1.28, 2.26)

1.31 (0.93, 1.83)

Husband drinks too much alcohol

95 (13.6)

602 (86.4)

1.17 (0.91, 1.50)

0.79 (0.60, 1.04)

Poor marital relationship

80 (27.5)

211 (72.5)

3.17 (2.38, 4.21)

2.13 (1.53, 2.97)

Reference category

The variables with statistically significant association (p < 0.05) are written in italics

Discussion

In this paper we report findings from a large population-based study of PPD symptoms in a rural Ethiopian setting, using a culturally validated measure of depression and a wide range of potentially relevant associated factors measured using standardized instruments. The hypothesis that unhappiness of the father about the baby’s gender would be associated with PPD symptoms was rejected.

The prevalence of high PPD symptoms in our study was 12.2%. Although this is in the range of the prevalence reports from community studies from LMICs (ranging from 4.9 to 59.4%) [3], it is much higher than a previous study conducted in a neighboring district 10 years ago where the prevalence was 5% [57]. Apart from the difference in the measurement instruments (the Self-Reporting Questionnaire was used in the previous study), it is possible that psychosocial and socio-cultural protective factors might be declining in the society. Socio-cultural practices that provide emotional and material support to women following birth are hypothesized to be protective against PPD or may be risk factors when people fail to comply with them [36].

In the same sample of women, we have shown previously that the treatment gap for PPD is very high [41], with most women not seeking any help for their symptoms and not receiving any evidence-based care. Nonetheless, around half of women were receptive to receiving treatment in the primary healthcare setting as well as from religious to traditional healers.

Gender preference, social adversity and PPD

Symptoms of PPD were higher among women whose husbands were not happy about the baby gender (15.8% vs. 11.8%), p-value < 0.05. However, this association became non-significant after adjusting for potential confounders. Gender preference has been reported as independent predictor of PPD in Asian countries [33, 5861]. In most of the studies conducted in LMICs, male gender was preferred to female especially among people with low income and education [58, 62, 63]. Although there is some evidence of gender preference in the Ethiopian setting [34], this does not appear to translate into a threat to the mental health of perinatal women.

The association between depression and disadvantage in women, including gender inequality, intimate partner violence and low maternal education, has been reported by many studies in LMICs, including Ethiopia [64, 65]. In this study, women living in the rural area had about twice the odds of having PPD. Rural living is associated with lower socioeconomic status, lower empowerment of women and poorer access to healthcare in Ethiopia. Unemployment and poverty are well known risk factors for PPD [3, 20, 23, 24, 66, 67]. Dimensions of poverty include food and financial insecurity. In this study, women who had experienced hunger in the preceding month and who perceived their socio-economic status to be lower than others were more likely to have PPD. This is consistent with findings in other LMICs [66, 68, 69]. Those women who reported a poor relationship with their husband were also more likely to have PPD. The question of whether poor marital relationships cause PPD or PPD leads to problems in the marital relationship remains unanswered given the cross-sectional nature of our study. Nearly half of women in our study had experienced at least one stressful life event, ranging from loss of a loved one to being the victim of theft, and this was associated significantly with PPD.

The importance of social determinants of PPD in this rural Ethiopian setting is also reflected in our previous finding of attribution of PPD symptoms to social rather than psychological causes [36, 41]. Any intervention for PPD will need to consider social determinants in order to effectively address the underlying cause of depression, as well as to be acceptable for women in this context. Poverty reduction interventions or interventions to address intimate partner violence would be expected to improve mental health in women in this setting at the population level, although a review indicated that micro-finance initiatives may actually increase mental distress [70]. Nonetheless, alongside such initiatives, it is likely that individually-focused psychosocial interventions will also be needed for a sub-group of women. In a systematic review of psychosocial interventions for women with perinatal depression, there was preliminary evidence that purely social interventions were less effective than psychological interventions [71].

Reproductive health threats

Women who had given birth to five or more children had two-fold increased odds of experiencing PPD compared to first time mothers. This is in keeping with previous studies from LMICs [3, 69, 72]. The unmet need for family planning is very high in many LMICs and women with high fertility are more likely to be uneducated, poor and in poorer health, all of which are associated with PPD [73]. Past adverse pregnancy outcomes such as abortion and perinatal complications were found to have significant association with PPD in this study, as with many other studies in other LMICs [3, 7, 22, 23, 26, 69]. Despite recent reductions, maternal mortality remains high in rural Ethiopian settings. As a consequence, any medical complications during pregnancy are likely to be perceived as potentially life-threatening and a potent threat to mental health [74]. Loss of a previous pregnancy has been associated with increased risk of mental health problems in the subsequent pregnancy in high-income country settings [75] but has been little-investigated in LMICs. Improving the reproductive health of women would be expected to improve their mental as well as their physical health. Nonetheless, for women who do experience complications, improved psychological support may reduce the risk of developing future mental health problems.

Limitations

This is a cross-sectional study it is difficult to determine temporal relationship between exposure and outcome variables, for example between PPD and poverty. Reliance on self-report for the measurement of factors such as wealth, marital relationship and husbands’ substance use may have led to under-reporting of the true extent of the problem. Although women were asked specifically about symptoms for PPD in the preceding 2 weeks, some might have also reported symptoms present during or before pregnancy due to difficulty defining the recall period in this rural setting with low levels of literacy. Some depressive symptoms, such as weakness, may have been the result of the demands of the postpartum period rather than depression. We did not conduct physical examinations and may have missed underlying physical health problems.

Conclusion

Postpartum depression affected at least one in ten women in this Ethiopian community. Social adversity and reproductive threats were high and associated with PPD. Improving reproductive healthcare, addressing social determinants of PPD and creating access to mental health care through integration into existing primary care-based maternal health care may reduce the burden.

Abbreviations

DSM-IV: 

Diagnostic and Statistical Manual of mental disorders fourth edition

EPDS: 

Edinburgh Postnatal Depression Scale

LMIC: 

low- and middle-income country

LTE: 

list of threatening experiences

OSSS: 

Oslo Social Support Scale

PDQ: 

Pitt Depression Questionnaire

PHQ: 

Patient Health Questionnaire

PRIME: 

Programme for Improving Mental health carE

SCID: 

Structured Clinical Interview for DSM Disorders

SNNPR: 

Southern Nations, Nationalities and People’s Region

SRQ: 

Self-Reporting Questionnaire

Declarations

Authors’ contributions

TA developed the proposal, supervised the data collection process, developed the data entry template, checked the data entry periodically, analyzed the data, and prepared the draft manuscript. CH: supported development of the proposal, analyzed the data and contributed to interpretation of the findings, as well as commenting on the manuscript. AF participated in the translation of the instruments, helped in interpretation of the results and commented on the manuscript. All authors read and approved the final manuscript.

Acknowledgements

We are grateful to the study participants for giving their time and energy to respond to the interview questions. The authors acknowledge the PRIME project for funding the research. The district health office, administrative office and the respective sub-districts are highly acknowledged for their cooperation in the process of the research. We also thank the data collectors, supervisors, and other members of the research team for their commitment to the study.

Competing interests

The authors declare that they have no competing interests.

Availability of data and materials

The data for this study are part of a PhD thesis for Telake Azale and therefore cannot be made publicly available at the present time. Through the PRIME consortium, data will be made publicly available in due course via applications through the PRIME website: https://www.prime.uct.za. The data are available on request from the corresponding author (CH) for replication of the findings presented in this paper.

Consent for publication

Not applicable.

Ethics approval and consent to participate

Ethical approval was obtained from the Institutional Review Board (IRB) of the College of Health Sciences, Addis Ababa University. Permission to conduct the research was received from the district Health and Administrative offices. Only women who gave written, informed consent to participate were included in the study.

Funding

This study is an output of the PRogramme for Improving Mental health carE (PRIME). This work was supported by the UK Department for International Development [201446]. The views expressed do not necessarily reflect the UK Government’s official policies.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors’ Affiliations

(1)
Department of Health Education and Behavioral Sciences, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia
(2)
Centre for Global Mental Health, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
(3)
Center for Innovative Drug Development and Therapeutic Trials for Africa, Addis Ababa University, Addis Ababa, Ethiopia
(4)
Centre for Affective Disorders, Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
(5)
Department of Psychiatry, School of Medicine, College of Health Sciences, Addis Ababa University, Addis Ababa, Ethiopia

References

  1. Shidhaye P, Giri P. Maternal depression: a hidden burden in developing countries. Ann Med Health Sci Res. 2014;4(4):463–5.View ArticlePubMedPubMed CentralGoogle Scholar
  2. Cox JL, Connor YM, Kendell RE. Prospective study of the psychiatric disorders of childbirth. Br J Psychiatry. 1982;140:111–7.View ArticlePubMedGoogle Scholar
  3. Fisher J, de Cabral Mello M, Patel V, Rahman A, Tran T, Holton S, Holmes W. 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;90(2):139G–49G.View ArticlePubMedGoogle Scholar
  4. Tefera TB, Erena AN, Kuti KA, Hussen MA. Perinatal depression and associated factors among reproductive aged group women at Goba and Robe Town of Bale Zone, Oromia Region, South East Ethiopia. Matern Health Neonatol Perinatol. 2015;1:12.View ArticlePubMedPubMed CentralGoogle Scholar
  5. Baumgartner JN, Parcesepe A, Mekuria YG, Abitew DB, Gebeyehu W, Okello F, Shattuck D. Maternal mental health in Amhara region, Ethiopia: a cross-sectional survey. Glob Health Sci Pract. 2014;2(4):482–6.View ArticlePubMedPubMed CentralGoogle Scholar
  6. Stellenberg EL, Abrahams JM. Prevalence of and factors influencing postnatal depression in a rural community in South Africa. Afr J Primary Health Care Fam Med. 2015;7(1):874.Google Scholar
  7. Weobong B, Ten Asbroek AH, Soremekun S, Danso S, Owusu-Agyei S, Prince M, Kirkwood BR. Determinants of postnatal depression in rural ghana: findings from the don population based cohort study. Depress Anxiety. 2015;32(2):108–19.View ArticlePubMedGoogle Scholar
  8. Tavares D, Quevedo L, Jansen K, Souza L, Pinheiro R, Silva R. Prevalence of suicide risk and comorbidities in postpartum women in Pelotas. Rev Bras Psiquiatr. 2012;34(3):270–6.View ArticlePubMedGoogle Scholar
  9. Conner KR, Bridge JA, Davidson DJ, Pilcher C, Brent DA. Metaanalysis of mood and substance use disorders in proximal risk for suicide deaths. Suicide Life Threat Behav. 2017. https://doi.org/10.1111/sltb.12422.PubMedView ArticleGoogle Scholar
  10. Granja AC, Zacarias E, Bergström S. Violent deaths: the hidden face of maternal mortality. BJOG. 2002;109(1):5–8.View ArticlePubMedGoogle Scholar
  11. Karki C. Suicide: leading cause of death among women in Nepal. Kathmandu Univ Med J. 2011;9(3):157–8.Google Scholar
  12. Lal S, Satpathy S, Khanna P, Vashisht BM, Punia MS, Kumar S. Problem of mortality in women of reproductive age in rural area of Haryana. Indian J Matern Child Health. 1995;6(1):17–21.PubMedGoogle Scholar
  13. Agampodi S, Wickramage K, Agampodi T, Thennakoon T, Jayathilaka N, Karunarathna D, Alagiyawanna S. Maternal mortality revisited: the application of the new ICD-MM classification system in reference to maternal deaths in Sri Lanka. Reprod Health. 2014;11:17.View ArticlePubMedPubMed CentralGoogle Scholar
  14. 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;89:608–15.View ArticlePubMedGoogle Scholar
  15. Ejaz MS, Sarwat A, Aisha T. Maternal psychiatric morbidity and childhood malnutrition. Pak J Med Sci. 2012;28(5):874–8.Google Scholar
  16. Shapiro M, Murray-Kolb L, Chang S, Hamadani J, El Arifeen S, Baqui A, Black R. Maternal depressive symptoms and infant diarrhea in Bangladesh. FASEB J. 2011;25:780.Google Scholar
  17. Rahman A, Hafeez A, Bilal R, Sikander S, Malik A, Minhas F, Tomenson B, Creed F. The impact of perinatal depression on exclusive breastfeeding: a cohort study. Matern Child Nutr. 2016;12(3):452–62.View ArticlePubMedGoogle Scholar
  18. Rahman A, Iqbal Z, Bunn J, Lovel H, Harrington R. Impact of maternal depression on infant nutritional status and illness: a cohort study. Arch Gen Psychiatry. 2004;61(9):946–52.View ArticlePubMedGoogle Scholar
  19. Tran TD, Biggs BA, Tran T, Simpson JA, de Mello MC, Hanieh S, Nguyen TT, Dwyer T, Fisher J. Perinatal common mental disorders among women and the social and emotional development of their infants in rural Vietnam. J Affect Disord. 2014;160:104–12.View ArticlePubMedGoogle Scholar
  20. 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;61(5):364–9.View ArticlePubMedGoogle Scholar
  21. Giri RK, Khatri RB, Mishra SR, Khanal V, Sharma VD, Gartoula RP. Prevalence and factors associated with depressive symptoms among post-partum mothers in Nepal. BMC Res Notes. 2015;8:111.View ArticlePubMedPubMed CentralGoogle Scholar
  22. Waqas A, Raza N, Lodhi HW, Muhammad Z, Jamal M, Rehman A. Psychosocial factors of antenatal anxiety and depression in Pakistan: is social support a mediator? PLoS ONE. 2015;10(1):e0116510.View ArticlePubMedPubMed CentralGoogle Scholar
  23. 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;10(4):e0122079.View ArticlePubMedPubMed CentralGoogle Scholar
  24. Al Hinai FI, Al Hinai SS. Prospective study on prevalence and risk factors of postpartum depression in Al-dakhliya governorate in oman. Oman Med J. 2014;29(3):198–202.View ArticlePubMedPubMed CentralGoogle Scholar
  25. Yim IS, Tanner Stapleton LR, Guardino CM, Hahn-Holbrook J, Dunkel Schetter C. Biological and psychosocial predictors of postpartum depression: systematic review and call for integration. Annu Rev Clin Psychol. 2015;11:99–137.View ArticlePubMedPubMed CentralGoogle Scholar
  26. Gulamani SS, Premji SS, Kanji Z, Azam SI. A review of postpartum depression, preterm birth, and culture. J Perinat Neonatal Nurs. 2013;27(1):52–9 (quiz 60-51).View ArticlePubMedGoogle Scholar
  27. Turkcapar AF, Kadioglu N, Aslan E, Tunc S, Zayifoglu M, Mollamahmutoglu L. Sociodemographic and clinical features of postpartum depression among Turkish women: a prospective study. BMC Pregnancy Childbirth. 2015;15:108.View ArticlePubMedPubMed CentralGoogle Scholar
  28. Stellenberg EL, Abrahams JM. Prevalence of and factors influencing postnatal depression in a rural community in South Africa. Afr J Prim Health Care Fam Med. 2015;7(1):1–8.Google Scholar
  29. Hanlon C, Medhin G, Alem A, Tesfaye F, Lakew Z, Worku B, Dewey M, Araya M, Abdulahi A, Hughes M, et al. Impact of antenatal common mental disorders upon perinatal outcomes in Ethiopia: the P-MaMiE population-based cohort study. Trop Med Int Health. 2009;14(2):156–66.View ArticlePubMedGoogle Scholar
  30. Deng AW, Xiong RB, Jiang TT, Luo YP, Chen WZ. Prevalence and risk factors of postpartum depression in a population-based sample of women in Tangxia Community, Guangzhou. Asian Pac J Trop Med. 2014;7(3):244–9.View ArticlePubMedGoogle Scholar
  31. Klainin P, Arthur DG. Postpartum depression in Asian cultures: a literature review. Int J Nurs Stud. 2009;46(10):1355–73.View ArticlePubMedGoogle Scholar
  32. Loo KK, Li Y, Tan Y, Luo X, Presson A, Shih W. Prenatal anxiety associated with male child preference among expectant mothers at 10–20 weeks of pregnancy in Xiangyun County, China. Int J Gynaecol Obstet. 2010;111(3):229–32.View ArticlePubMedPubMed CentralGoogle Scholar
  33. Chandran M, Tharyan P, Muliyil J, Abraham S. Post-partum depression in a cohort of women froma rural area of Tamil Nadu, India: incidence and risk factors. Br J Psychiatry. 2002;181:499–504.View ArticlePubMedGoogle Scholar
  34. Tilahun T, Coene G, Temmerman M, Degomme O. Spousal discordance on fertility preference and its effect on contraceptive practice among married couples in Jimma zone, Ethiopia. Reprod Health. 2014;11:27.View ArticlePubMedPubMed CentralGoogle Scholar
  35. Adebowale SA, Palamuleni ME. Influence of gender preference and sex composition of surviving children on childbearing intention among high fertility married women in stable union in Malawi. Afr Health Sci. 2015;15(1):150–60.View ArticlePubMedPubMed CentralGoogle Scholar
  36. Hanlon C, Whitley R, Wondimagegn D, Alem A, Prince M. Postnatal mental distress in relation to the sociocultural practices of childbirth: an exploratory qualitative study from Ethiopia. Soc Sci Med. 2009;69(69):1211–9.View ArticlePubMedPubMed CentralGoogle Scholar
  37. Hanlon C. Perinatal common mental disorders in Ethiopia: Sociocultural factors in onset, remission and maintenance London. UK: University of London; 2009.Google Scholar
  38. FDRE, PCC. Summary and statistical report of the 2007 population and housing census. In: Ethiopia FDRo, editor. Population size by age and sex. Addis Ababa: Population Census Policy; 2008.Google Scholar
  39. Fekadu A, Hanlon C, Medhin G, Alem A, Selamu M, Giorgis TW, Shibre T, Teferra S, Tegegn T, Breuer E, et al. Development of a scalable mental healthcare plan for a rural district in Ethiopia. Br J Psychiatry. 2016;208(Suppl 56):s4–12.View ArticlePubMedPubMed CentralGoogle Scholar
  40. Lund C, Tomlinson M, De Silva M, Fekadu A, Shidhaye R, Jordans M, Petersen I, Bhana A, Kigozi F, Prince M, et al. PRIME: a programme to reduce the treatment gap for mental disorders in five low- and middle-income countries. PLoS Med. 2012;9(12):e1001359.View ArticlePubMedPubMed CentralGoogle Scholar
  41. Azale T, Fekadu A, Hanlon C. Treatment gap and help-seeking for postpartum depression in a rural African setting. BMC Psychiatry. 2016;16:196.View ArticlePubMedPubMed CentralGoogle Scholar
  42. Azale T, Fekadu A, Medhin G, Hanlon C. Coping strategies of women with postpartum depression symptoms in rural Ethiopia: a cross-sectional community study. BMC Psychiatry. 2018;18:41.View ArticlePubMedPubMed CentralGoogle Scholar
  43. Fekadu A, Medhin G, Selamu M, Hailemariam M, Alem A, Giorgis TW, Breuer E, Lund C, Prince M, Hanlon C. Population level mental distress in rural Ethiopia. BMC Psychiatry. 2014;14:194.View ArticlePubMedPubMed CentralGoogle Scholar
  44. Kroenke K, Spitzer RL, Williams JBW. The PHQ-9: validity of a brief depression severity measure. J Gen Intern Med. 2001;16(9):606–13.View ArticlePubMedPubMed CentralGoogle Scholar
  45. Shrestha SD, Pradhan R, Tran TD, Gualano RC, Fisher JR. Reliability and validity of the Edinburgh Postnatal Depression Scale (EPDS) for detecting perinatal common mental disorders (PCMDs) among women in low-and lower-middle-income countries: a systematic review. BMC Pregnancy Childbirth. 2016;16:72.View ArticlePubMedPubMed CentralGoogle Scholar
  46. Rowe H, Wynter K, Lorgelly P, Amir LH, Ranasinha S, Proimos J, Cann W, Hiscock H, Bayer J, Burns J, et al. A cluster randomised controlled trial of a brief couple-focused psychoeducational intervention to prevent common postnatal mental disorders among women: study protocol. BMJ Open. 2014;4(9):e006436.View ArticlePubMedPubMed CentralGoogle Scholar
  47. Gjerdingen D, Crow S, McGovern P, Miner M, Center B. Postpartum depression screening at well-child visits: validity of a 2-question screen and the PHQ-9. Ann Fam Med. 2009;7(1):63–70.View ArticlePubMedPubMed CentralGoogle Scholar
  48. Weobong B, Akpalu B, Doku V, Owusu-Agyei S, Hurt L, Kirkwood B. M. P: the comparative validity of screening scales for postnatal common mental disorder in Kintampo, Ghana. J Affect Disord. 2009;113(1–2):109–17.View ArticlePubMedGoogle Scholar
  49. Hanlon C, Medhin G, Selamu M, Breuer E, Worku B, Hailemariam M, Lund C, Prince M, Fekadu A. Validity of brief screening questionnaires to detect depression in primary care in Ethiopia. J Affect Disord. 2015;186:32–9.View ArticlePubMedGoogle Scholar
  50. Girma F. Detecting depression during pregnancy: validation of PHQ-9, Kessler-10, Kessler-6 and SRQ-20 in Butajira health center antenatal care clinics, Ethiopia. Addis Ababa: Addis Ababa University; 2013.Google Scholar
  51. Dalgard OS, Bjork S, Tambs K. Social support, negative life events and mental health—a longitudinal study. Br J Psychiatry. 1995;166:29–34.View ArticlePubMedGoogle Scholar
  52. Sintayehu M, Mulat H, Yohannis Z, Adera T, Fekade M. Prevalence of mental distress and associated factors among caregivers of patients with severe mental illness in the outpatient unit of Amanuel Hospital, Addis Ababa, Ethiopia, 2013: cross-sectional study. J Mol Psychiatry. 2015;3:9.View ArticlePubMedPubMed CentralGoogle Scholar
  53. Duko B, Gebeyehu A, Ayano G. Prevalence and correlates of depression and anxiety among patients with tuberculosis at WolaitaSodo University Hospital and Sodo Health Center, WolaitaSodo, South Ethiopia, Cross sectional study. BMC Psychiatry. 2015;15:214.View ArticlePubMedPubMed CentralGoogle Scholar
  54. Habtewold TD, Alemu SM, Haile YG. Sociodemographic, clinical, and psychosocial factors associated with depression among type 2 diabetic outpatients in Black Lion General Specialized Hospital, Addis Ababa, Ethiopia: a cross-sectional study. BMC Psychiatry. 2016;16(1):103.View ArticlePubMedPubMed CentralGoogle Scholar
  55. Brugha T, Bebbington P, Tennant C, Hurry J. The list of threatening experiences: a subset of 12 life event categories with considerable long-term contextual threat. Psychol Med. 1985;15(1):189–94.View ArticlePubMedGoogle Scholar
  56. Hodgson R, Alwyn T, John B, Thom B, Smith A. The FAST Alcohol Screening Test. Alcohol Alcohol. 2002;37(1):61–6.View ArticlePubMedGoogle Scholar
  57. Medhin G, Hanlon C, Dewey M, Alem A, Tesfaye F, Lakew Z, Worku B, Aray M, Abdulahi A, Tomlinson M, et al. The effect of maternal common mental disorders on infant undernutrition in Butajira, Ethiopia: the P-MaMiE study. BMC Psychiatry. 2010;10:32.View ArticlePubMedPubMed CentralGoogle Scholar
  58. Qadir F, Khan MM, Medhin G, Prince M. Male gender preference, female gender disadvantage as risk factors for psychological morbidity in Pakistani women of childbearing age—a life course perspective. BMC Public Health. 2011;11:745.View ArticlePubMedPubMed CentralGoogle Scholar
  59. Dhillon N, Macarthur C. Antenatal depression and male gender preference in Asian women in the UK. Midwifery. 2010;26(3):286–93.View ArticlePubMedGoogle Scholar
  60. Loo KK, Luo X, Su H, Presson A, Li Y. Dreams of tigers and flowers: child gender predictions and preference in an urban mainland Chinese sample during pregnancy. Women Health. 2009;49(1):50–65.View ArticlePubMedPubMed CentralGoogle Scholar
  61. Patel V, Rodrigues M, DeSouza N. Gender, poverty, and postnatal depression: a study of mothers in Goa, India. Am J Psychiatry. 2002;159(1):43–7.View ArticlePubMedGoogle Scholar
  62. Yasmin S, Mukherjee A, Manna N, Baur B, Datta M, Sau M, Roy M, Dasgupta S. Gender preference and awareness regarding sex determination among antenatal mothers attending a medical college of eastern India. Scand J Public Health. 2013;41(4):344–50.View ArticlePubMedGoogle Scholar
  63. Rai P, Paudel IS, Ghimire A, Pokharel PK, Rijal R, Niraula SR. Effect of gender preference on fertility: cross-sectional study among women of Tharu community from rural area of eastern region of Nepal. Reprod Health. 2014;11(1):15.View ArticlePubMedPubMed CentralGoogle Scholar
  64. Deyessa N, Berhane Y, Emmelin M, Ellsberg MC, Kullgren G, Hogberg U. Joint effect of maternal depression and intimate partner violence on increased risk of child death in rural Ethiopia. Arch Dis Child. 2010;95(10):771–5.View ArticlePubMedGoogle Scholar
  65. Deyessa N, Berhane Y, Alem A, Ellsberg M, Emmelin M, Hogberg U, Kullgren G. Intimate partner violence and depression among women in rural Ethiopia: a cross-sectional study. Clin Pract Epidemiol Ment Health. 2009;5:8.View ArticlePubMedPubMed CentralGoogle Scholar
  66. Kathree T, Selohilwe OM, Bhana A, Petersen I. Perceptions of postnatal depression and health care needs in a South African sample: the “mental” in maternal health care. BMC Womens Health. 2014;14:140.View ArticlePubMedPubMed CentralGoogle Scholar
  67. Adama ND, Foumane P, Olen JPK, Dohbit JS, Meka ENU, Mboudou E. Prevalence and risk factors of postpartum depression in Yaounde, Cameroon. Open J Obstet Gynecol. 2015;5(11):608.View ArticleGoogle Scholar
  68. Dewinga S, Tomlinsonb M, le Rouxd IM, Chopra M, Tsai AC. Food insecurity and its association with co-occurring postnatal depression, hazardous drinking, and suicidality among women in peri-urban South Africa. J Affect Disord. 2013;150(2):460–5.View ArticleGoogle Scholar
  69. Roomruangwong C, Eppersonb N. Perinatal depression in Asian women: prevalence, associated factors, and cultural aspects. Asian Biomed. 2011;5(2):179–93.View ArticleGoogle Scholar
  70. Lund C, De Silva M, Plagerson S, Cooper S, Chisholm D, Das J. Poverty and mental disorders: breaking the cycle in low-income and middle-income countries. Lancet. 2011;378:1505–14.View ArticleGoogle Scholar
  71. Clarke K, King M, Prost A. Psychosocial interventions for perinatal common mental disorders delivered by providers who are not mental health specialists in low- and middle-income countries: a systematic review and meta-analysis. PLoS Med. 2013;10(10):e1001541.View ArticlePubMedPubMed CentralGoogle Scholar
  72. Mathisen SE, Glavin K, Lien L, Lagerløv P. Prevalence and risk factors for postpartum depressive symptoms in Argentina: a cross-sectional study. Int J Womens Health. 2013;5:787–93.View ArticlePubMedPubMed CentralGoogle Scholar
  73. Ayele W, Tesfaye H, Gebreyes R, Gebreselassie T. Trends and determinants of unmet need for family planning and programme options, Ethiopia. In: DHS, editor. Further analysis of the 2000, 2005 and 2011 Demographic and Health Surveys. 81st ed. Calverton: ICF International; 2013. p. 31.Google Scholar
  74. Hanlon C, Whitley R, Wondimagegn D, Alem A, Prince M. Between life and death: exploring the sociocultural context of antenatal mental distress in rural Ethiopia. Arch womens Ment Health. 2010;13(5):385–93.View ArticlePubMedPubMed CentralGoogle Scholar
  75. Giannandrea SAM, Cerulli C, Anson E, Chaudron LH. Increased risk for postpartum psychiatric disorders among women with past pregnancy loss. J Womens Health. 2013;22(9):760–8.View ArticleGoogle Scholar
  76. Tsai AC, Tomlinson M, Comulada WS, Rotheram-Borus MJ. intimate partner violence and depression symptom severity among South African women during pregnancy and postpartum: population-based prospective cohort study. PLoS Med. 2016;13(1):e1001943.View ArticlePubMedPubMed CentralGoogle Scholar
  77. Hung KJ, Tomlinson M, le Roux IM, Dewing S, Chopra M, Tsai AC. Community-based prenatal screening for postpartum depression in a South African township. Int J Gynaecol Obstet. 2014;126(1):74–7.View ArticlePubMedPubMed CentralGoogle Scholar
  78. Cooper PJ, Tomlinson M, Swartz L, Woolgar M, Murray L, Molteno C. Posbpartum depression and the mother–infant relationship in a South African peri-urban settlement. Br J Psychiatry. 1999;175:554–8.View ArticlePubMedGoogle Scholar
  79. Ramchandani PG, Richter LM, Stein A, Norris SA. Predictors of postnatal depression in an urban South African cohort. J Affect Disord. 2009;113(3):279–84.View ArticlePubMedGoogle Scholar
  80. Tomlinson M, Swartz L, Cooper PJ, Molteno C. Social factors and postpartum depression in Khayelitsha, Cape Town. South Afr J Psychol. 2004;34:409–90.View ArticleGoogle Scholar
  81. Hanlon C, Medhin G, Alem A, Araya M, Abdulahi A, Hughes M, Tesfaye M, Wondimagegn D, Patel V, Prince M. Detecting perinatal common mental disorders in Ethiopia: validation of the self-reporting questionnaire and Edinburgh Postnatal Depression Scale. J Affect Disord. 2008;108(3):251–62.View ArticlePubMedGoogle Scholar
  82. Harpham T, Huttly S, De Silva MJ, Abramsky T. Maternal mental health and infant nutrition in four developing countries. J Epidemiol Community Health. 2005;59:1060–4.View ArticlePubMedPubMed CentralGoogle Scholar

Copyright

© The Author(s) 2018

Advertisement