Skip to main content
Download PDF
  • Research article
  • Open access
  • Published:

Maternal multimorbidity during pregnancy and after childbirth in women in low- and middle-income countries: a systematic literature review

BMC Pregnancy and Childbirth volume 20, Article number: 637 (2020) Cite this article

Abstract

Background

For every maternal death, 20 to 30 women are estimated to have morbidities related to pregnancy or childbirth. Much of this burden of disease is in women in low- and middle-income countries. Maternal multimorbidity can include physical, psychological and social ill-health. Limited data exist about the associations between these morbidities. In order to address all health needs that women may have when attending for maternity care, it is important to be able to identify all types of morbidities and understand how each morbidity influences other aspects of women’s health and wellbeing during pregnancy and after childbirth.

Methods

We systematically reviewed published literature in English, describing measurement of two or more types of maternal morbidity and/or associations between morbidities during pregnancy or after childbirth for women in low- and middle-income countries. CINAHL plus, Global Health, Medline and Web of Science databases were searched from 2007 to 2018. Outcomes were descriptions, occurrence of all maternal morbidities and associations between these morbidities. Narrative analysis was conducted.

Results

Included were 38 papers reporting about 36 studies (71,229 women; 60,911 during pregnancy and 10,318 after childbirth in 17 countries). Most studies (26/36) were cross-sectional surveys. Self-reported physical ill-health was documented in 26 studies, but no standardised data collection tools were used. In total, physical morbidities were included in 28 studies, psychological morbidities in 32 studies and social morbidities in 27 studies with three studies assessing associations between all three types of morbidity and 30 studies assessing associations between two types of morbidity. In four studies, clinical examination and/or basic laboratory investigations were also conducted. Associations between physical and psychological morbidities were reported in four studies and between psychological and social morbidities in six. Domestic violence increased risks of physical ill-health in two studies.

Conclusions

There is a lack of standardised, comprehensive and routine measurements and tools to assess the burden of maternal multimorbidity in women during pregnancy and after childbirth. Emerging data suggest significant associations between the different types of morbidity.

Systematic review registration number

PROSPERO CRD42018079526.

Peer Review reports

Background

Maternal multimorbidities affect millions of women during pregnancy and after childbirth and the burden of ill-health is expected to be highest in women in low-and middle-income countries (LMIC) [1]. For every maternal death, 20 to 30 women have morbidities related to pregnancy or childbirth [2, 3]. More recent studies using new and comprehensive assessment tools suggest that the magnitude of maternal multimorbidity is much larger than previously estimated [4,5,6]. International targets and the Sustainable Development Goals have a new focus; in addition to preventing maternal mortality, improving health and well-being, as well as “survive and thrive” are the new goals [7]. There is international agreement that all women have the right to the highest attainable standard of health and well-being, also during pregnancy and after childbirth [7, 8]. Estimates of morbidity have until now largely focused on acute and/or severe complications such as haemorrhage, sepsis and eclampsia [9]. The current definition of health is “a state of complete physical, mental, and social well-being and not merely the absence of disease or infirmity” [10]. There are arguments that this definition needs to be re-formulated to consider health in a context of functionality, capacity, adaptability and the ability to perform activities of daily living despite having an illness or disability; but with a continued emphasis on the importance of the three domains of health: physical, psychological and social [11]. There is also debate that current definitions, measurements and timeframes for “multimorbidity”, “co-morbidity”, “morbidity burden” and related constructs are not well conceptualized [11, 12].

Regarding maternal morbidity, a suggested definition is “any health condition attributed to and/or aggravated by pregnancy and childbirth that has a negative impact on women’s well-being” [13]. In order to address all health needs that women may have when attending for maternity care, it is important to be able to identify all types of morbidities and understand how each morbidity influences other aspects of women’s health and wellbeing during pregnancy and after childbirth. To date, lack of data exist regarding measurement and burden of disease described as “maternal morbidity”, “maternal multimorbidity”, or “maternal co-morbidity”; these terms are often used interchangeably; and there is uncertainty regarding the timeframe over which maternal morbidity impacts a woman’s health and wellbeing. Additionally, there is limited understanding of best practices to measure different components of maternal ill-health and descriptions of morbidities, and if and how different types of morbidities are interlinked and associated.

Objective

A systematic review of the literature was conducted for studies from LMIC that measured two or more different types of maternal morbidity and/or associations with and between morbidities.

Methods

We included studies which assessed two or more types of maternal morbidity in women during and/or after pregnancy. For the purposes of this study we categorised maternal multimorbidity as physical (such as but not limited to medical, infectious, obstetric), psychological (such as but not limited to depression, suicidal ideation) and social co-morbidities (such as but not limited to domestic violence, substance misuse) [5]. We assessed tools that were used to collect data, including self-reported subjective measures; and/or objective measures such as clinical examination; and/or use of investigations for different types of maternal multimorbidity as reported by authors. We described how and what different types of maternal multimorbidity (physical, psychological, social) were measured and if there were any reported associations between these.

Data sources and search strategy

This protocol is registered in PROSPERO (CRD42018079526). Relevant articles published between January 2007 and December 2018 were identified using a structured search strategy in four electronic databases: CINAHL Plus, Global Health, Medline, and Web of Science. A search strategy was developed using thesaurus (including MeSH) and free-text terms for “maternal morbidity” and associated keywords, were used as main search terms. For each aspect of maternal morbidity (“physical”, “psychological” and “social”) search terms and related keywords were selected (Supplementary Table 1). Reference lists and bibliographies of key topic articles were also searched and any additional papers that met the inclusion criteria were obtained.

Inclusion and exclusion criteria

The study population was limited to women during pregnancy, childbirth or up to 12 weeks postnatal. Studies were excluded if: (i) they reported one type of maternal morbidity only, (ii) examined trend, risk factors or associations only without estimates of prevalence of types of morbidity, or (iii) reported severe or life-threatening complications of pregnancy or childbirth that would require emergency obstetric care. The review was limited to studies from LMIC as defined by the World Bank. Language was limited to English.

Selection and data extraction

One researcher screened all titles and abstracts (MMc). A sub-sample (20%) was double screened by the second researcher (SZ). Evaluation of full-text papers was done independently by these two researchers with reasons for exclusion recorded and any discrepancies were discussed with a third researcher (NvdB). Information was extracted into a pre-designed summary table and included data on location of study, study dates, study design, study population, types of maternal morbidity, methods of measurement, timing (pregnancy phase) of the assessment and whether or not associations were reported (Supplementary Table 2). Throughout the review and extraction process, articles where uncertainty existed were discussed by all researchers to reach consensus.

Quality assessment

Appraisal of the quality of studies was conducted based on descriptions of maternal morbidities, sampling methods and completeness of data. Quality of evidence for each study was assessed using the Grading of Recommendations, Assessment Development and Evaluation (GRADE) tool adapted from the Critical Analysis Skills Programme (CASP) tool [14].

Data synthesis

A narrative synthesis approach was used to describe outcomes including: types of maternal morbidity categorised as physical (such as medical, infectious, obstetric), psychological (such as depression, suicidal ideation) and social (such as domestic violence, substance misuse); approaches used to collect data (self-reported or determined by healthcare providers); data collection tools used (standardised validated tool, or study specific); measurements of maternal morbidities; and reported associations (if any) between different types of maternal morbidities.

Results

By combining the search terms, 2840 studies were identified from the four databases and after screening for relevance, 58 were retrieved for full text review (Fig. 1). Upon applying the eligibility criteria, 38 articles met the inclusion criteria. Two studies were conducted by the same group of authors [15,16,17,18]. In these publications, the same methodology was reported in two papers, but there was a different emphasis on the results and outcomes reported per publication. For the purposes of this review, the first publication is referenced in the methodology section [15, 17]. Both publications were included in the summary tables and measurements and/or associations for each publication are described in the results section. Most studies (92%; 33/36) were of medium quality, and the rest low quality (8%, 3/36).

Fig. 1
figure 1

PRISMA diagram for article selection process

Full size image

Characteristics of studies

The 36 studies were from 17 different countries, with 15 from sub-Saharan Africa. Eleven were conducted in low-income countries and six in middle-income countries (four lower-middle and two upper-middle income countries).

Study design, source of data, data collection method and sample size

Twenty-six studies used cross-sectional survey study designs. Four were observational prospective cohort studies [15, 19,20,21]. One study was a case control [22]. Twenty five studies used face-to-face interviews or consultations to collect self-reported primary data from women using questionnaires. Most studies that collected primary data relied on women’s self-reported symptoms (n = 28). In four studies, clinical examination and/or laboratory tests were also conducted [6, 20, 23, 24]. Three studies extracted data using secondary data analysis of large databases of hospital admissions, discharges or birth registers [25,26,27]. In these secondary data analyses authors used their own data collection tools with little details of the variables extracted. One study extracted data from medical case notes [28] (Supplementary Table 2). A total number of 71,229 women were assessed in the 36 studies: 60,911 during pregnancy and 10,318 after childbirth. In nine studies less than 500 women were assessed [24,25,26,27,28,29,30,31,32,33]; thirteen assessed 500–999 women each [15, 18, 20, 21, 34,35,36,37,38,39,40,41,42,43]. In nine studies 1000–1999 women were assessed [19, 22, 27, 28, 44,45,46,47,48]; and five had sample sizes of ≥2000 women (Supplementary Table 2) [6, 25, 26, 49, 50].

Stages of pregnancy assessed

A total of 23 studies collected data from women during pregnancy: in the second trimester [16, 19, 32, 40, 47]; in the third trimester [20, 24, 37]; or at any time during pregnancy [19, 29, 32, 33]. In 11 of those, gestational age was not given [32, 36, 38,39,40,41,42,43,44,45, 48, 49]. Seven studies assessed women within 12 weeks of childbirth [18, 22, 29, 30, 32, 46, 50]. In one study, data was collected during three stages after childbirth: at 4–12 weeks; at 12–24 weeks; and at 24–56 weeks [23]. Zafar et al. collected data at three different assessment stages, during early and late antenatal period and after childbirth (Supplementary Table 2) [6].

Site of data collection

In studies that collected primary data (n = 30), data collection took place during visits for routine antenatal or postnatal care in outpatient departments of healthcare facilities: tertiary/provincial hospitals [23, 31, 35, 38, 41, 44, 46]; secondary level or district hospitals [32, 43, 51], and primary healthcare facility level [15, 18, 36, 39, 47]. For four studies the site was unclear [29, 33, 34, 42]. In 12 studies, this took place in the community or in women’s homes (Supplementary Table 2) [6, 19, 20, 22, 24, 30, 42, 45, 49,50,51].

Maternal multimorbidity

All three types of maternal morbidity including physical, psychological and social ill-health were assessed in 12 studies [6, 15, 16, 20, 39, 41,42,43, 46, 48]; psychological and social ill-health were assessed in nine studies [18, 25, 29, 31, 32, 34, 35, 39, 42]; physical and psychological ill-health in 11 [6, 18, 19, 21, 22, 24, 27, 29, 32, 33, 49]; and physical and social ill-health in six [17, 26, 44, 45, 47, 50] (Supplementary Table 2).

Physical morbidity

Twenty-nine studies reported on different types of physical morbidity; three of which assessed pre-selected populations including women with HIV [35, 42] or women with gestational diabetes [38]. A variety of data collection tools were used, but generally not well described. No study used validated questionnaires or international disease classifications. The most commonly reported physical morbidities were anaemia in six studies (prevalence range 5.0–57.7%) [6, 20, 22, 23, 32, 49], and HIV in nine (prevalence range 3.0–16.0%) [6, 16, 29, 33, 35, 36, 43, 48, 50]. There was a variety of other types of physical morbidities, with wide ranges for some conditions such as antepartum haemorrhage; nausea and vomiting; preterm birth; malaria; reproductive or sexually transmitted infection; urinary tract infection (Supplementary Table 3). Some authors used summative aggregated measures, for example “gynaecological and obstetric problems” as occurring in 10–22% of women; “multiple morbidities” in 60% of women or “at least one reported symptom” (44% occurrence) [22, 46, 49]. One study used antenatal hospitalisation as a “proxy” for physical morbidities (55.4% of women) [45] (Supplementary Table 3).

Psychological morbidity

Of the 32 studies that report psychological morbidities, the most common condition was depression with a prevalence range of 13.5–39.5% across 21 studies [18, 20,21,22,23,24, 27,28,29,30,31,32,33,34,35, 38, 41, 49, 51]. Twelve studies described more than one psychological condition [15, 16, 19, 25, 34, 37, 42, 43, 46,47,48,49]. Some authors described aggregates or a summative psychological condition; for example, “common mental disorders” and “symptoms of any mental distress” [15, 16]. There was a range of other types of psychological morbidity described, such as anxiety; suicidal ideation; and distress (Supplementary Table 4). Fourteen different data collection tools were used either alone or in combination (Table 1). The commonest tool was the Edinburgh Postnatal Depression Score (EPDS) questionnaire, used in fourteen studies [6, 18, 20, 28,29,30,31, 34,35,36, 38, 41, 49]. However, different studies used various cut-off scores (from ≥4 to ≥13) for the EPDS questionnaire and the Kessler scale (from > 15 to > 30) [6, 18, 20, 28,29,30,31, 34,35,36, 38, 41, 49, 54, 56].

Table 1 Description of data collection tools used to assess psychological and social morbidity
Full size table

Social morbidity

In total, 27 studies assessed social morbidity; the most commonly reported type of social morbidity was domestic violence in 14 studies [17, 18, 23, 25, 28, 31, 35, 38, 39, 43, 45, 47, 48, 50]. Substance abuse was assessed in nine studies (Supplementary Table 4) [16, 34, 39, 40, 42, 44,45,46, 50]. Three studies assessed both domestic violence and substance abuse [26, 37, 46]. Eight studies assessed other aspects of social health including husband’s alcohol intake, poor social support, food insecurity and unplanned pregnancy [20, 21, 30, 36, 41, 42, 46, 51].

In the 14 studies assessing domestic violence, a variety of data collection tools were used and most authors used their own definitions and questionnaires to screen for domestic violence. Five publications used all or part of internationally recognised questionnaires (Table 1) [17, 18, 39, 45, 47]. Different types of domestic violence included: disrespect, forced sex, intimate partner violence, physical assault, severe emotional and verbal abuse. Other authors used descriptions of domestic violence as aggregates or summative measures, for example, terms such as “multiple acts of physical violence” and “physical and/or sexual abuse” [38]. Nine studies assessed one or more forms of substance abuse [16, 34, 39, 40, 42, 44,45,46, 50], and two of these used validated questionnaires [34, 40]. In general, substance abuse related to alcohol (9 studies; prevalence range 0–49.5%) [16, 34, 39,40,41, 44,45,46, 50].

Associations between different types of morbidity

For physical morbidity, there was an association between increased psychological morbidity in women with obstetric complications (haemorrhage, infections, incontinence, prolonged labour, caesarean birth, low birthweight, stillbirth, neonatal death) (Table 2) [6, 26, 41, 45, 50]. Women with gestational diabetes were not more likely to have psychological morbidity (depression) [38], but women with HIV were more likely to have social morbidity (domestic violence) [18]. Psychological morbidity was more common in younger women [40] and among women with social morbidities such as domestic violence [25, 35], unwanted pregnancy [19, 41, 50] and poor social support (Table 2) [41]. For social morbidity, there was an association between women with substance abuse (alcohol) and domestic violence [48]; and domestic violence was also associated with neonatal death [48] and maternal complications (Table 2) [46]. Due to heterogeneity, meta-analysis of associations was not possible.

Table 2 Associations between types of maternal morbidity
Full size table

Discussion

Main findings

There is emerging evidence of a high burden of multimorbidity in women living in LMIC during pregnancy and after childbirth, as well as emerging evidence of associations between physical, psychological and social morbidities, suggesting that maternal morbidities are inter-linked. There is, however, still limited data about the strengths and direction of the associations between the different types of morbidities.

There was an apparent lack of standardisation of definitions and data collection tools used to measure maternal multimorbidities. The EPDS was the most common validated data collection tool to assess psychological morbidity in the studies, but with different cut-off scores to determine the risk of “depression” (ranging from 4 to 13) making comparisons difficult. Similarly, a variety of different validated data collection tools were used to assess domestic violence and/or substance abuse as components of social morbidity. Physical, psychological and social morbidities were often described as aggregates or summative measures, limiting comparability of findings.

Strengths and limitations

To the best of our knowledge, this is the first systematic review to assess maternal multimorbidities and types and levels of association between the different types. Many studies relied on recall of experience of morbidity and many primary data were symptom-based rather than “diagnosed”. Only four studies triangulated self-reported symptoms with findings from clinical examination and/or basic laboratory investigations. Assessments of measurements of ill-health based on self-reporting may be valid regarding ill-health as experienced by women, but do not provide accurate burden of disease estimates. No study described or used internationally recognised disease classifications to assess physical morbidity. Internationally recognised data collection tools were used to assess psychological and social morbidity, but these often used different cut-off scores making comparisons difficult. A limitation of this review is that studies that explored maternal multimorbidity using qualitative methodology were excluded.

Interpretation

Valid comparable measurements of maternal multimorbidity are limited to date, and this study confirms the need for a new approach and focus [70,71,72]. It will be important for future healthcare practice and research to agree and apply: (a) common identification criteria for maternal multimorbidity taking into account the different types of physical, psychological and social morbidity; (b) standardised and validated data collection tools that can be used in different languages and at all levels of healthcare; with, (c) validation of self-reported measurements of maternal morbidity compared to clinical assessment, investigations and diagnosis determined by healthcare providers [6, 70,71,72]. More recognition must be given that maternal morbidity is a complex concept with important associations between different morbidities. This has implications for screening and management of all different types of ill-health during pregnancy and after childbirth. There is a need to incorporate women’s understanding, perceptions and lived experience of maternal multimorbidity into public health approaches to improve maternal health and wellbeing during pregnancy and after childbirth in LMIC [73, 74].

Conclusion

To date a range of methods and tools have been used to assess maternal multimorbidity. Maternal multimorbidity estimates using these methodologies and tools, while useful as a guide, cannot be considered truly representative of the burden and range of maternal multimorbidity that have negative impact on women’s wellbeing during pregnancy and after childbirth. The suggested WHO definition of maternal morbidity provides such a framework in principle, but challenges remain to map out comprehensive, feasible and acceptable assessment tools, approaches and timeframes [11]. Comprehensive and routine measurements of maternal multimorbidity are necessary to inform policy and program decisions and for resource allocation for antenatal and postnatal care [5]. Improved standardised measurements of maternal multimorbidity will also allow for comparison of the burden of disease across settings within and between countries. There is a need for a sustainable way to provide good baseline maternity care for all and targeted individualised care for women who need extra care to prevent development and progression of maternal multimorbidity.

Availability of data and materials

All the sources of data are publicly available and referenced in the document.

Abbreviations

EPDS:

Edinburgh Postnatal Depression Score

CASP:

Critical Analysis Skills Programme

GRADE:

Grading of Recommendations, Assessment, Development and Evaluation

LMIC:

Low- and middle-income countries

MeSH:

Medical Subject Headings

PRISMA:

Preferred Reporting Items for Systematic Reviews and Meta-Analyses

WHO:

World Health Organization

References

  1. Graham W, Woodd S, Byass P, Fillipi V, Gon G, Virgo S, et al. Diversity and divergence: the dynamic burden of poor maternal health. Lancet. 2016;388(10056):2164–75. https://doi.org/10.1016/S0140-6736(16)31533-1.

    Article  PubMed  Google Scholar 

  2. Ashford L. Hidden suffering: disabilities from pregnancy and childbirth in less developed countries. Washington, DC: Population Reference Bureau, MEASURE Communication; 2002.

    Google Scholar 

  3. Datta KK, Sharma RS, Razack PMA, Ghosh TK, Arora RR. Morbidity pattern among rural women in Alwar-Rajasthan - a cohort study. Health Popul Perspect Issues. 1980;3(4):282–92.

    Google Scholar 

  4. Barreix M, Barbour K, McCaw-Binns A, Chou D, Petzold M, Gichuhi G, et al. Standardizing the measurement of maternal morbidity: pilot study results. Int J Gynecol Obstet. 2018;141(Supp 1):10–9. https://doi.org/10.1002/ijgo.12464.

    Article  Google Scholar 

  5. McCauley M, Madaj B, White SA, Dickinson F, Bar-Zeev S, Aminu M, et al. Burden of physical, psychological and social ill-health during and after pregnancy among women in India, Pakistan, Kenya and Malawi. BMJ Glob Health. 2018;3(3):e000625. https://doi.org/10.1136/bmjgh-2017-000625.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Zafar S, Jean-Baptiste R, Rahman A, Neilson JP, van den Broek NR. Non-life threatening maternal morbidity: cross sectional surveys from Malawi and Pakistan. PLoS One. 2015;10(9):e0138026.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  7. United Nations. Transforming our world: the 2030 Agenda for Sustainable Development. New York: World Health Organization; 2015. Accessed 17th November 2017. Available from: https://sustainabledevelopment.un.org/post2015/transformingourworld.

    Google Scholar 

  8. United Nations. Every Woman, Every Child: Global Strategy; 2015. Accessed 17th November 2017. Available from: http://www.everywomaneverychild.org/global-strategy-2.

    Google Scholar 

  9. Vos T, Barber RM, Bell B, et al. Global, regional, and national incidence, prevalence, and years lived with disability for 301 acute and chronic diseases and injuries in 188 countries, 1990–2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet. 2015;386:743–800. https://doi.org/10.1016/S0140-6736(15)60692-4.

    Article  Google Scholar 

  10. World Health Organization. Constitution of the World Health Organization. Geneva: World Health Organization; 1948.

    Google Scholar 

  11. Huber M, Knottnerus JA, Green L, et al. How should we define health? BMJ. 2011;343:d416.

    Article  Google Scholar 

  12. Valderas JM, Starfield B, Sibbald B, Salisbury C, Roland M. Defining comorbidity: implications for understanding health and health services. Ann Fam Med. 2009;7(4):357–63. https://doi.org/10.1370/afm.983.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Firoz T, Chou D, von Dadelszen P, Agrawal P, Vanderkruik R, Tunçalp Ö, et al. Measuring maternal health: focus on maternal morbidity. Bull World Health Organ. 2013;91(10):794–6.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Atkins D, Eccles M, Flottorp S, Guyatt GH, Henry D, Hill S, et al. Systems for grading the quality of evidence and the strength of recommendations I: critical appraisal of existing approaches. The GRADE Working Group. BMC Health Serv Res. 2004;4(1):38.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Faisal-Cury A, Araya R, Marcelo Z, Menezes P. Common mental disorders during pregnancy and adverse obstetric outcomes. J Psychosom Obstet Gynecol. 2010;31(4):229–35.

    Article  Google Scholar 

  16. Faisal-Cury A, Menezes P, Araya R, Zugaib M. Common mental disorders during pregnancy: prevalence and associated factors among low-income women in São Paulo, Brazil. Arch Womens Ment Health. 2009;12(5):335.

    Article  PubMed  Google Scholar 

  17. Shamu S, Zarowsky C, Roelens K, Temmerman M, Abrahams K. High-frequency intimate partner violence during pregnancy, postnatal depression and suicidal tendencies in Harare, Zimbabwe. Gen Hosp Psychiatry. 2016;38(Jan-Feb):109–14.

    Article  PubMed  Google Scholar 

  18. Shamu S, Zarowsky C, Shefer T, Temmerman M, Abrahams N. Intimate partner violence after disclosure of HIV test results among pregnant women in Harare, Zimbabwe. PLoS One. 2014;9(10):e109447.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  19. Karmaliani R, Asad N, Bann CM, Moss N, McClure EM, Pasha O, et al. Prevalence of anxiety, depression and associated factors among pregnant women of Hyderabad. Pakistan Int J Soc Psychiatry. 2009;55(5):10.

    Google Scholar 

  20. Tran TD, Biggs B-A, Tran T, Casey GJ, Hanieh S, Simpson JA, et al. Psychological and social factors associated with late pregnancy iron deficiency anaemia in rural Viet Nam: A population-based prospective study. PLoS One. 2013;8(10):e78162 19.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Wado YD, Afework MF, Hindin MJ. Effects of maternal pregnancy intention, depressive symptoms and social support on risk of low birth weight: a prospective study from southwestern Ethiopia. PLoS One. 2014;9(5):e96304.20.

    Article  CAS  Google Scholar 

  22. Assarag B, Dubourg D, Maaroufi A, Dujardin B, De Brouwere V. Maternal postpartum morbidity in Marrakech: what women feel what doctors diagnose? BMC Pregnancy Childbirth. 2013;13:225.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Chersich MF, Kley N, Luchters SMF, Njeru C, Yard E, Othigo MJ, et al. Maternal morbidity in the first year after childbirth in Mombasa Kenya; a needs assessment. BMC Pregnancy Childbirth. 2009;9:51.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Rahman A, Bunn J, Lovel H, Creed F. Association between antenatal depression and low birthweight in a developing country. Acta Psychiatr Scand. 2007;115(6):481–6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Isaksen AB, Østbye T, Mmbaga BT, Daltveit AK. Alcohol consumption among pregnant women in northern Tanzania 2000–2010: a registry-based study. BMC Pregnancy Childbirth. 2015;15:205.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  26. Surkan PJ, Sakyi KS, Christian P, Mehra S, Labrique A, Ali H, et al. Risk of depressive symptoms associated with morbidity in postpartum women in rural Bangladesh. Matern Child Health J. 2017;21(10):1890–900.

    Article  PubMed  PubMed Central  Google Scholar 

  27. 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.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Ukachukwu V, Unger H, Onoka C, Nduka C, Maina S, Ngugi N. Maternal morbidity and mortality in peri-urban Kenya-assessing progress in improving maternal healthcare. East Afr J Public Health. 2009;6(2):112–8.

    CAS  PubMed  Google Scholar 

  29. Chibanda D, Mangezi W, Tshimanga M, Woelk G, Rusakaniko S, Stranix-Chibanda L, et al. Postnatal depression by HIV status among women in Zimbabwe. J Women's Health. 2010;19(11):2071–7.

    Article  Google Scholar 

  30. Dewing S, Tomlinson M, Le Roux 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.

    Article  PubMed  PubMed Central  Google Scholar 

  31. Khalifa DS, Glavin K, Bjertness E, Lien L. Determinants of postnatal depression in Sudanese women at 3 months postpartum: a cross-sectional study. BMJ Open. 2016;6:e009443.

    Article  PubMed  PubMed Central  Google Scholar 

  32. Lukose A, Ramthal A, Thomas T, Bosch R, Kurpad AV, Duggan C, et al. Nutritional factors associated with antenatal depressive symptoms in the early stage of pregnancy among urban south Indian women. Matern Child Health J. 2014;18(1):161–70.

    Article  PubMed  Google Scholar 

  33. Natamba BK, Achan J, Arbach A, Oyok TO, Ghosh S, Mehta S, et al. Reliability and validity of the Center for Epidemiologic Studies Depression Scale in screening for depression among HIV-infected and uninfected pregnant women attending antenatal Services in Northern Uganda: a cross-sectional study. BMC Psychiatr. 2014;14:2197.

    Article  Google Scholar 

  34. Vythilingum B, Roos A, Faure SC, Geerts L, Stein DJ. Risk factors for substance use in pregnant women in South Africa. S Afr Med J. 2012;102(11 Pt 1):851–4.

    Article  PubMed  Google Scholar 

  35. Yator O, Mathai M, Vander Stoep A, Rao D, Kumar M. Risk factors for postpartum depression for women living with HIV attending the prevention of mother to child transmission clinic at Kenyatta National Hospital at Nairobi, Kenya. AIDS Care. 2016;28(7):884–9.

    Article  PubMed  PubMed Central  Google Scholar 

  36. Brittain K, Mellins CA, Phillips T, Zerbe A, Abrams EJ, Myer L, et al. Social support, stigma and antenatal depression among HIV-infected pregnant women in South Africa. AIDS Behavior. 2017;21(1):274–82.

    Article  PubMed  Google Scholar 

  37. Nasreen HE, Kabir ZN, Forsell Y, Edhborg M. Prevalence and associated factors of depressive and anxiety symptoms during pregnancy: a population based study in rural Bangladesh. BMC Womens Health. 2011;11:22.

    Article  PubMed  PubMed Central  Google Scholar 

  38. Natasha K, Hussain A, Khan AKA. Prevalence of depression among subjects with and without gestational diabetes mellitus in Bangladesh: a hospital based study. J Diabetes Metab Disord. 2015;14:64.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  39. Ntaganira J, Muula AS, Masaisa F, Dusabeyezu F, Siziya S, Rudatskikira E. Intimate partner violence among pregnant women in Rwanda. BMC Womens Health. 2008;8:17.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Tran TD, Tran T, Wynter K, Fisher J. Interactions among alcohol dependence, perinatal common mental disorders and violence in couples in rural Vietnam: a cross-sectional study using structural equation modeling. BMC Psychiatry. 2012;12:148.

    Article  PubMed  PubMed Central  Google Scholar 

  41. 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.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  42. Wong M, Myer L, Zerbe A, Phillips T, Petro G, Mellins CA, et al. Depression, alcohol use, and stigma in younger versus older HIV-infected pregnant women initiating antiretroviral therapy in Cape Town, South Africa. Arch Womens Ment Health. 2017;20(1):149–59.

    Article  PubMed  Google Scholar 

  43. Stewart RC, Umar E, Tomenson B, Creed F. A cross-sectional study of antenatal depression and associated factors in Malawi. Arch Womens Ment Health. 2014;17(2):145–54.

    Article  PubMed  Google Scholar 

  44. Hassan M, Kashanian M, Hassan M, Roohi M, Yousefi H. Maternal outcomes of intimate partner violence during pregnancy: study in Iran. Public Health. 2014;128(5):410–5.

    Article  CAS  PubMed  Google Scholar 

  45. Hanlon C, Medhin G, Alem A, Tesfaye F, Lakew Z, Worku B, et al. Impact of antenatal common mental disorders upon perinatal outcomes in Ethiopia: the P-MaMiE population-based cohort study. Tropical Med Int Health. 2009;14:156–66.

    Article  Google Scholar 

  46. Romero-Gutiérrez G, Cruz-Arvizu VH, Regalado-Cedillo CA. Ponce-Ponce de Leon AL. Prevalence of violence against pregnant women and associated maternal and neonatal complications in Leon, Mexico. Midwifery. 2011;27(5):750–3.

    Article  PubMed  Google Scholar 

  47. Rees SJ, Tol W, Mohammad M, Tay AK, Tam N, dos Reis N, et al. A high-risk group of pregnant women with elevated levels of conflict-related trauma, intimate partner violence, symptoms of depression and other forms of mental distress in post-conflict Timor-Leste. Transl Psychiatry. 2016;6:e725.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Stöckl H, Watts C, Kilonzo Mbwambo JK. Physical violence by a partner during pregnancy in Tanzania: prevalence and risk factors. Reprod Health Matters. 2010;18(36):171–80.

    Article  PubMed  Google Scholar 

  49. Hamadani JD, Tofail F, Hilaly A, Mehrin F, Shiraji S, Banu S, et al. An association of postpartum maternal morbidities with children's mental, psychomotor and language development in rural Bangladesh. J Health Popul Nutr. 2012;30(2):193–204.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. 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;138(3):277–86.

    Article  PubMed  PubMed Central  Google Scholar 

  51. Rwakarema M, Premji SS, Nyanza EC, Riziki P, Palacios-Derflingher L. Antenatal depression is associated with pregnancy-related anxiety, partner relations, and wealth in women in northern Tanzania: a cross-sectional study. BMC Womens Health. 2015;15:68.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  52. Ali BS, Reza H, Khan MM, Jehan I. Development of an indigenous screening instrument in Pakistan: the Aga Khan University anxiety and depression scale. J Pak Med Assoc. 1998;48(9):261–5.

    CAS  PubMed  Google Scholar 

  53. Lewis G, Pelosi AJ, Araya R, Dunn G. Measuring psychiatric disorder in the community: a standardized assessment for use by lay interviewers. Psychol Med. 1992;22(2):465–86.

    Article  CAS  PubMed  Google Scholar 

  54. Cox JL, Holden JM, Sagovsky R. Detection of postnatal depression. Development of the 10-item Edinburgh postnatal depression scale. Brit J Psychiatry. 1987;150(6):782–6.

    Article  CAS  Google Scholar 

  55. Mollica RF, Caspi-Yavin Y, Bollini P, Truong T, Tor S, Lavelle J. The Harvard Trauma Questionnaire. Validating a cross-cultural instrument for measuring torture, trauma, and posttraumatic stress disorder in Indochinese refugees. J Nerv Ment Dis. 1992;180(2):111–6.

    Article  CAS  PubMed  Google Scholar 

  56. Kessler RC, Andrews G, Colpe LJ, Hiripi E, Mroczek DK, Normand SL, et al. Short screening scales to monitor population prevalence and trends in non-specific psychological distress. Psychol Med. 2002;32(6):959–76.

    Article  CAS  PubMed  Google Scholar 

  57. 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.

    Article  CAS  PubMed  Google Scholar 

  58. Montgomery SA, Asberg M. A new depression scale designed to be sensitive to change. Brit J Psychiatry. 1979;134:382–9.

    Article  CAS  Google Scholar 

  59. Spitzer RL, Williams JBW, Gibbon M, First MB. The structured clinical interview for DSM-III-R (SCID). Arch Gen Psychiatry. 1992;49:624–9.

    Article  CAS  PubMed  Google Scholar 

  60. Beusenberg M, Orley JH. A User's guide to the self-reporting questionnaire Geneva: World Health Organization, Division of Mental Health;1994. Available from: http://www.who.int/iris/handle/10665/61113.

    Google Scholar 

  61. Spielberger CD. State-trait anxiety inventory STAI. Palo Alto: Consulting Psychologists Press; 1983.

    Google Scholar 

  62. American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders 4. Washington, DC: American Psychiatric Association; 1994.

    Google Scholar 

  63. Radloff LS. The CES-D scale: a self-report depression scale for research in the general population. Appl Psychol Meas. 1977;1(3):385–401.

    Article  Google Scholar 

  64. Sheehan DV, Lecrubier Y, Sheehan KH, Anorm P, Janavs J, Weiller E, et al. The Mini-international neuropsychiatric interview (M.I.N.I.): the development and validation of a structured diagnostic psychiatric interview for DSM-IV and ICD-10. J Clin Psychiatry. 1998;59(Supp 20):22–57.

    PubMed  Google Scholar 

  65. Babor TF, Biddle-Higgins JC, Saunders JB, Monteiro MG. AUDIT: the alcohol use disorders identification test: guidelines for use in primary health care. Geneva: World Health Organization; 2001.

    Google Scholar 

  66. Ewing J, Rouse BA. Identifying the hidden alcoholic. Paper presented at: the 29th International Congress on Alcohol and Drug Dependence, 1970; Sydney Australia; 1970.

    Google Scholar 

  67. Pascoe JM, Ialongo NS, Horn WF, Reinhart MA, Perradatto D. The reliability and validity of the maternal social support index. Fam Med. 1988;20(4):271–6.

    CAS  PubMed  Google Scholar 

  68. Cutrona CE, Russell DW. The provisions of social relationships and adaptation to stress In: Jones WH, Perlman D. Advances in Personal Relationships. Greenwich: JAI Press;1987. pp. 37–67.

    Google Scholar 

  69. Holzemer WL, Uys LR, Chirwa ML, Greeff M, Makoae LN, Kohi TW. Validation of the HIV/AIDS stigma instrument - PLWA (HASI-P). AIDS Care. 2007;19(8):1002–12.

    Article  PubMed  Google Scholar 

  70. Chou D, Tunçalp Ö, Firoz T, Barreix M, Filippi V, von Dadelszen P, et al. Constructing maternal morbidity – towards a standard tool to measure and monitor maternal health beyond mortality. BMC Pregnancy Childbirth. 2016;16:45.

    Article  PubMed  PubMed Central  Google Scholar 

  71. Say L, Chou D, Barbour K, Barreix M, Cecatti J, Costa M, et al. Maternal morbidity: time for reflection, recognition, and action. Int J Gynecol Obstet. 2018;141(S1):1–3.

    Article  Google Scholar 

  72. Vanderkruik RC, Tunçalp Ö, Chou D, Say L. Framing maternal morbidity: WHO scoping exercise. BMC Pregnancy Childbirth. 2013;13:213.

    Article  PubMed  PubMed Central  Google Scholar 

  73. Lange IL, Gherissi A, Chou D, Say L, Filippi V. What maternal morbidities are and what they mean for women: A thematic analysis of twenty years of qualitative research in low and lower-middle income countries. PLoS One. 2019;14(4):e0214199. Published 2019 Apr 11. https://doi.org/10.1371/journal.pone.0214199.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  74. McCauley M, Avais A, Agrawal R, Saleem S, Zafar S, van den Broek N. “Good health means being mentally, socially, emotionally and physically fit”: Women’s understanding of health and ill-health during and after pregnancy. BMJ Open. 2020;10:e028760. https://doi.org/10.1136/bmjopen-2018-028760.

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

Not applicable.

Funding

This study was funded by a grant from the Department of International Development, London UK, under the Making it Happen programme (202945–101) and Global Fund (20168770) and the EGA Hospital Charity Travelling Fellowship in Memory of Anne Boutwood from the Royal College of Obstetricians and Gynaecologists. The funders played no role in the writing of the manuscript or the decision to submit it for publication.

Author information

Authors and Affiliations

  1. Centre for Maternal and Newborn Health, Liverpool School of Tropical Medicine, Pembroke Place, Liverpool, L3 5QA, UK

    Mary McCauley & Nynke van den Broek

  2. Fazaia Medical College, Air University, Islamabad, Pakistan

    Shamsa Zafar

Authors
  1. Mary McCauley
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Shamsa Zafar
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Nynke van den Broek
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

MMc and NvdB were responsible for the study inception and design. MMc and SZ performed the data extraction. MMc and NvdB interpreted the data and wrote the manuscript. All authors have read, critiqued and approved the final manuscript.

Corresponding author

Correspondence to Mary McCauley.

Ethics declarations

Ethics approval and consent to participate

This systematic review did not involve contact with any human participants, and therefore no ethical approval was needed. This study was conducted in compliance with the established ethical guidelines of the Declaration of Helsinki.

Consent for publication

Not applicable.

Competing interests

The authors have no competing interests to declare.

Additional information

Publisher’s Note

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

Supplementary information

Additional file 1: Supplementary Table 1.

MeSH terms and keywords used in the search.

Additional file 2: Supplementary Table 2.

Summary table for studies reporting maternal multimorbidity during pregnancy and after childbirth and /or associations between the multimorbidities.

Additional file 3: Supplementary Table 3.

Summary table of types of physical morbidity reported in included studies.

Additional file 4: Supplementary Table 4.

Summary table of measurements of psychological and social morbidities reported.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. 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 in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

McCauley, M., Zafar, S. & van den Broek, N. Maternal multimorbidity during pregnancy and after childbirth in women in low- and middle-income countries: a systematic literature review. BMC Pregnancy Childbirth 20, 637 (2020). https://doi.org/10.1186/s12884-020-03303-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12884-020-03303-1

Keywords

BMC Pregnancy and Childbirth

ISSN: 1471-2393

Contact us