Causes of maternal mortality in Sub-Saharan Africa: A systematic review of studies published from 2015 to 2020

Journal of global health, Volume 11, Year 2021

Interprétation

Background: Maternal deaths remain high in Sub-Saharan Africa (SSA) and their causes of maternal death must be analysed frequently in this region to guide interventions. Methods: We conducted a systematic review of studies published from 2015 to 2020 that reported the causes of maternal deaths in 57 SSA countries. The objective was to identify the leading causes of maternal deaths using the international classification of disease – 10th revision, for maternal mortality (ICD-MM). We searched PubMed, WorldCat Discovery Libraries Worldwide (including Medline, Web of Science, LISTA and CNHAL databases), and Google Scholar databases and citations, using the search words “maternal mortality”, “maternal death”, “pregnancy-related death”, “reproductive age mortality” and “causes” as MeSH terms or keywords. The last date of search from all databases was 21 May 2021. We included original research articles published in English and excluded articles that mentioned SSA country names without study results for those countries, studies that reported death from a single cause or assigned causes of death using computer models or incompletely broke down the causes of death. We exported, de-duplicated and screened the searches electronically in EndNote version 20. We selected the final articles by reading the titles, abstracts and full texts. Two authors searched the articles and assessed the risk of bias using a tool adapted from Montoya and others. Data from the articles were extracted onto an Excel worksheet and the deaths classified into ICD-MM groups. Proportions were calculated with 95% confidence intervals and compared for deaths attributed to each cause and ICD-MM group. We compared the results with WHO and Global Burden of Disease (GDB) estimates. Results: We identified 38 studies that reported 11 427 maternal and four incidental deaths. Twenty-one of the third-eight studies were retrospective record reviews. The leading causes of death (proportions and 95% confidence intervals (CI)) were obstetric hemorrhage: 28.8% (95% CI = 26.5%-31.2%), hypertensive disorders in pregnancy: 22.1% (95% CI = 19.9%-24.2%), non-obstetric complications: 18.8% (95% CI = 16.4%-21.2%) and pregnancy-related infections: 11.5% (95% CI = 9.8%-13.2%). The studies reported few deaths of unknown/undetermined and incidental causes. Conclusions: Limitations of this review were the failure to access more data from government reports, but the study results compared well with WHO and GDB estimates. Obstetric hemorrhage, hypertensive disorders in pregnancy, non-obstetric complications, and pregnancy-related infections are the leading causes of maternal deaths in SSA. However, deaths from incidental causes are likely under-reported in this region. SSA countries must continue to invest in health information systems that collect and publishes comprehensive, quality, maternal death causes data. A publicly accessible repository of data sets and government reports for causes of maternal death will be helpful in future reviews. This review received no specific funding and was not registered. We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) 2020 guidelines in conducting this systematic review. Guided by the stated objective, we built search strategies using the words “maternal mortality”, “reproductive age mortality”, “pregnancy-related deaths”, “causes” and SSA country names. We searched PubMed, WorldCat Discovery Libraries Worldwide (including Medline, Web of Science, LISTA and CNHAL databases), and Google Scholar (last searched 21/05/2021) for studies that reported causes of maternal deaths in SSA, published from 2015 to 2020. We used “include related terms” options in the searches and combined the search terms using Boolean operators “OR” and “AND”. We used MeSH terms in PubMed search and Keywords expanded to “related terms” in World Cat Discovery and Google Scholar searches. Additional searches were done using citations and “similar” or “related articles” options for included articles. The search period started from 2015 to limit the review to studies containing data collected from 2010 onwards, which would have used the ICD-MM. We performed the search from 16 December 2020 to 21 March 2021 and repeated it from 13 to 21 May 2021. For the detailed strategy for each search see Table S1 in the Online Supplementary Document. We included original research articles published in English that reported causes of maternal deaths and mentioned SSA countries. We excluded articles without study results for the SSA countries mentioned in them, studies that evaluated interventions, studied a single cause of death, assigned death causes using computer models, incompletely broke down the causes of death (less than 75% of total deaths identified), without full articles or reported data collected before 2010 (before the introduction of ICD-MM) or reported results contained in other selected studies. Unpublished government reports for Zimbabwe and South Africa, which the authors managed to access, were also included. We searched for a central repository of government reports but found none. We could not find additional government reports from the databases’ and open internet searches, and enquiries with relevant UN agencies. Two authors searched for and screened the articles independently, and discussed and agreed on the selected articles. Differences were resolved by the last author, who verified the eligibility of the selected articles and the assigning of the causes of death into ICD-MM groups. Two authors screened the articles using titles and abstracts, and reading full-text versions when abstracts indicated that the study reported the causes of maternal death. All articles identified from the searches were exported to EndNote version 20, and duplicates removed electronically. The articles were initially screened electronically using keywords “maternal”, “death”, “mortality” and “causes,” combining the search terms using the Boolean Operators “AND” and “OR”. The remaining articles were screened manually using study titles and abstracts. The verification of eligibility of the selected articles was done using the study titles and abstracts. The first author extracted the data from the included articles onto an adapted Critical Appraisal Skills Programme (CASP) form in Microsoft Excel (Microsoft Inc, Seattle, USA), recording the article’s first author name, year published, study description or title, study implementer (study group or government), the period covered by the data, study design, study setting, source of maternal death data, the definition of maternal death used, whether the study included community deaths, the method used to assign the causes of death, country and SSA region where the study was done, the total number of maternal deaths reported and breakdown of maternal deaths by cause of death – categorised into ICD-MM groups (Table S2 in the Online Supplementary Document). The primary study outcome was the number of deaths attributed to each cause of maternal death. The number of deaths for each cause was identified from the results section of the articles and not abstracts. For the PRISMA diagram with the search method and results see Figure S1 in the Online Supplementary Document. We synthesised the data in an Excel data extraction worksheet. As data were extracted from each selected article, the different causes of death reported in the studies were added to the data extraction template. In the process, each cause of death was assigned to the relevant cause of death group, using the ICD-MM manual. Each eligible study was recorded on the datasheet with the number of deaths recorded under the applicable cause of death. When the breakdown of causes of death was given in percentages, we calculated the number of deaths using the percentages and total deaths reported in the study. No studies were excluded at the synthesis stage. Standard risk-of-bias assessment tools such as the Risk of Bias in randomised trials (RoB 2 tool), Risk Of Bias in Non-randomised Studies (ROBINS-I tool) and Risk of Bias due to Missing Evidence in synthesis (ROB_ME) were considered but deemed inapplicable for this review. They are designed for systematic review of studies measuring intervention effects. Instead, the risk of bias was assessed using a tool adapted from Montoya and others’ study, which reviewed hospital maternal mortality levels in SSA. This tool assesses different types of bias, depending on the kind of studies reviewed and the biases that affect them [11]. In their review, Montoya and others assessed four types of bias as follows: selection bias from the definition of maternal death used in the studies, information bias from the sources of data, selection bias from the length of follow up of the women, and selection bias from inclusion or exclusion of deaths in early pregnancy. We adapted the tool to four criteria that suited our review. Using the adapted tool, we assessed: information bias from the source of maternal death data used in the studies, missing data bias from the completeness of the cause-of-death data against total deaths reported, selection bias from the use or non-use of ICD-MM in assigning causes of death in the study, measurement bias from competence levels of persons who assigned the causes of death. Under each criterion, the risk of bias was rated and scored as low (1), medium (2), or high (3) (Table 1). We assigned the overall risk of bias rating for each study as low (average score less than 1.5), medium (average score ranging 1.5 to less than 2), and low (average score ranging from 2 to 3) (See Table S3 in the Online Supplementary Document). Studies with a high risk of bias were to be excluded from analysis. Risk of bias assessment criteria VA – verbal autopsy, CEMD/MDSR – confidential enquiry into maternal deaths/maternal death surveillance and response We calculated the total number of deaths reported in all the studies, total number of deaths belonging to each ICD-MM group and the total number of deaths reported under each specific cause of death. Proportions of deaths attributed to each ICD-MM group and specific causes for all SSA and sub-regions (East and Central, Southern and West Africa) were calculated. The leading causes of death in SSA and its sub-regions were identified by ranking the proportions of deaths. The leading causes of death from this study were compared with WHO and Global Burden of Disease (GBD) cause-of-death estimates, using the rankings of the causes of death from each study. Meta-analysis was not performed because this review assessed all causes of maternal deaths reported in the studies and not one cause. Heterogeneity and sensitivity analysis was not performed as these apply to meta-analysis. The risk of bias from missing results was assessed using completeness of reporting the causes of death. The robustness of the synthesised results was assessed using 95% confidence intervals for the proportions of deaths. The systematic review was not registered, but conducted under a study protocol approved by the Medical Research Council of Zimbabwe (MRCZ/A/2613) and the University of Pretoria Faculty of Science Research Ethics Committee (339/2019).

Résumé de l’IA

Study Justification:

– Maternal deaths remain high in Sub-Saharan Africa (SSA).
– Frequent analysis of the causes of maternal death is necessary to guide interventions.
– This systematic review aims to identify the leading causes of maternal deaths in SSA.

Highlights:

– The study conducted a systematic review of studies published from 2015 to 2020.
– 38 studies were identified, reporting 11,427 maternal deaths and four incidental deaths.
– The leading causes of maternal deaths in SSA were identified as obstetric hemorrhage (28.8%), hypertensive disorders in pregnancy (22.1%), non-obstetric complications (18.8%), and pregnancy-related infections (11.5%).
– Limitations of the review include the failure to access more data from government reports, but the results compared well with WHO and Global Burden of Disease estimates.

Recommendations:

– SSA countries should continue to invest in health information systems that collect and publish comprehensive, quality data on the causes of maternal death.
– A publicly accessible repository of data sets and government reports for causes of maternal death would be helpful for future reviews.

Key Role Players:

– Researchers and academics in the field of maternal health
– Government health departments and ministries
– Non-governmental organizations (NGOs) working in maternal health
– International organizations such as the World Health Organization (WHO) and United Nations agencies

Cost Items for Planning Recommendations:

– Development and maintenance of health information systems
– Training and capacity building for data collection and analysis
– Research funding for further studies and reviews
– Development and maintenance of a publicly accessible data repository

Force de la preuve

The strength of evidence for this abstract is 8 out of 10.
The evidence in the abstract is strong, but there are some areas for improvement. The systematic review included a comprehensive search strategy and followed the PRISMA guidelines. The authors conducted a thorough assessment of bias and provided a clear description of the methods used. The results are presented with proportions and confidence intervals, and comparisons were made with WHO and Global Burden of Disease estimates. However, the limitations of the review, such as the failure to access more data from government reports, should be addressed in future studies. Additionally, the inclusion of a publicly accessible repository of data sets and government reports would enhance the transparency and reproducibility of the review.

Abstrait

We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) 2020 guidelines in conducting this systematic review. Guided by the stated objective, we built search strategies using the words “maternal mortality”, “reproductive age mortality”, “pregnancy-related deaths”, “causes” and SSA country names. We searched PubMed, WorldCat Discovery Libraries Worldwide (including Medline, Web of Science, LISTA and CNHAL databases), and Google Scholar (last searched 21/05/2021) for studies that reported causes of maternal deaths in SSA, published from 2015 to 2020. We used “include related terms” options in the searches and combined the search terms using Boolean operators “OR” and “AND”. We used MeSH terms in PubMed search and Keywords expanded to “related terms” in World Cat Discovery and Google Scholar searches. Additional searches were done using citations and “similar” or “related articles” options for included articles. The search period started from 2015 to limit the review to studies containing data collected from 2010 onwards, which would have used the ICD-MM. We performed the search from 16 December 2020 to 21 March 2021 and repeated it from 13 to 21 May 2021. For the detailed strategy for each search see Table S1 in the Online Supplementary Document. We included original research articles published in English that reported causes of maternal deaths and mentioned SSA countries. We excluded articles without study results for the SSA countries mentioned in them, studies that evaluated interventions, studied a single cause of death, assigned death causes using computer models, incompletely broke down the causes of death (less than 75% of total deaths identified), without full articles or reported data collected before 2010 (before the introduction of ICD-MM) or reported results contained in other selected studies. Unpublished government reports for Zimbabwe and South Africa, which the authors managed to access, were also included. We searched for a central repository of government reports but found none. We could not find additional government reports from the databases’ and open internet searches, and enquiries with relevant UN agencies. Two authors searched for and screened the articles independently, and discussed and agreed on the selected articles. Differences were resolved by the last author, who verified the eligibility of the selected articles and the assigning of the causes of death into ICD-MM groups. Two authors screened the articles using titles and abstracts, and reading full-text versions when abstracts indicated that the study reported the causes of maternal death. All articles identified from the searches were exported to EndNote version 20, and duplicates removed electronically. The articles were initially screened electronically using keywords “maternal”, “death”, “mortality” and “causes,” combining the search terms using the Boolean Operators “AND” and “OR”. The remaining articles were screened manually using study titles and abstracts. The verification of eligibility of the selected articles was done using the study titles and abstracts. The first author extracted the data from the included articles onto an adapted Critical Appraisal Skills Programme (CASP) form in Microsoft Excel (Microsoft Inc, Seattle, USA), recording the article’s first author name, year published, study description or title, study implementer (study group or government), the period covered by the data, study design, study setting, source of maternal death data, the definition of maternal death used, whether the study included community deaths, the method used to assign the causes of death, country and SSA region where the study was done, the total number of maternal deaths reported and breakdown of maternal deaths by cause of death – categorised into ICD-MM groups (Table S2 in the Online Supplementary Document). The primary study outcome was the number of deaths attributed to each cause of maternal death. The number of deaths for each cause was identified from the results section of the articles and not abstracts. For the PRISMA diagram with the search method and results see Figure S1 in the Online Supplementary Document. We synthesised the data in an Excel data extraction worksheet. As data were extracted from each selected article, the different causes of death reported in the studies were added to the data extraction template. In the process, each cause of death was assigned to the relevant cause of death group, using the ICD-MM manual. Each eligible study was recorded on the datasheet with the number of deaths recorded under the applicable cause of death. When the breakdown of causes of death was given in percentages, we calculated the number of deaths using the percentages and total deaths reported in the study. No studies were excluded at the synthesis stage. Standard risk-of-bias assessment tools such as the Risk of Bias in randomised trials (RoB 2 tool), Risk Of Bias in Non-randomised Studies (ROBINS-I tool) and Risk of Bias due to Missing Evidence in synthesis (ROB_ME) were considered but deemed inapplicable for this review. They are designed for systematic review of studies measuring intervention effects. Instead, the risk of bias was assessed using a tool adapted from Montoya and others’ study, which reviewed hospital maternal mortality levels in SSA. This tool assesses different types of bias, depending on the kind of studies reviewed and the biases that affect them [11]. In their review, Montoya and others assessed four types of bias as follows: selection bias from the definition of maternal death used in the studies, information bias from the sources of data, selection bias from the length of follow up of the women, and selection bias from inclusion or exclusion of deaths in early pregnancy. We adapted the tool to four criteria that suited our review. Using the adapted tool, we assessed: information bias from the source of maternal death data used in the studies, missing data bias from the completeness of the cause-of-death data against total deaths reported, selection bias from the use or non-use of ICD-MM in assigning causes of death in the study, measurement bias from competence levels of persons who assigned the causes of death. Under each criterion, the risk of bias was rated and scored as low (1), medium (2), or high (3) (Table 1). We assigned the overall risk of bias rating for each study as low (average score less than 1.5), medium (average score ranging 1.5 to less than 2), and low (average score ranging from 2 to 3) (See Table S3 in the Online Supplementary Document). Studies with a high risk of bias were to be excluded from analysis. Risk of bias assessment criteria VA – verbal autopsy, CEMD/MDSR – confidential enquiry into maternal deaths/maternal death surveillance and response We calculated the total number of deaths reported in all the studies, total number of deaths belonging to each ICD-MM group and the total number of deaths reported under each specific cause of death. Proportions of deaths attributed to each ICD-MM group and specific causes for all SSA and sub-regions (East and Central, Southern and West Africa) were calculated. The leading causes of death in SSA and its sub-regions were identified by ranking the proportions of deaths. The leading causes of death from this study were compared with WHO and Global Burden of Disease (GBD) cause-of-death estimates, using the rankings of the causes of death from each study. Meta-analysis was not performed because this review assessed all causes of maternal deaths reported in the studies and not one cause. Heterogeneity and sensitivity analysis was not performed as these apply to meta-analysis. The risk of bias from missing results was assessed using completeness of reporting the causes of death. The robustness of the synthesised results was assessed using 95% confidence intervals for the proportions of deaths. The systematic review was not registered, but conducted under a study protocol approved by the Medical Research Council of Zimbabwe (MRCZ/A/2613) and the University of Pretoria Faculty of Science Research Ethics Committee (339/2019).

Matériaux

https://efashare.b-cdn.net/materials/7a23bfb5a06abd95a49e52b405e985cb9c038062a85cd27b6b6dda1093220518/jogh-11-04048-s001.pdf

Innovations

Based on the provided information, it seems that you are looking for innovations to improve access to maternal health in Sub-Saharan Africa. While the text you provided is a detailed description of a systematic review on the causes of maternal mortality in the region, it does not explicitly mention any innovations or recommendations. However, based on the findings of the review, here are some potential innovations that could be considered to improve access to maternal health:

1. Telemedicine and mobile health (mHealth) solutions: Implementing telemedicine and mHealth technologies can help overcome geographical barriers and improve access to healthcare services for pregnant women in remote areas. This can include remote consultations, prenatal care monitoring, and health education through mobile apps or telecommunication platforms.

2. Community-based interventions: Engaging and training community health workers to provide essential maternal health services, such as antenatal care, postnatal care, and health education, can help reach women in underserved areas where healthcare facilities are limited.

3. Transportation solutions: Improving transportation infrastructure and implementing innovative transportation solutions, such as ambulances or mobile clinics, can ensure timely access to emergency obstetric care for women in need.

4. Maternal waiting homes: Establishing maternal waiting homes near healthcare facilities can provide a safe and supportive environment for pregnant women who live far away, allowing them to stay closer to the facility as they approach their due dates.

5. Task-shifting and skill enhancement: Training and empowering midwives and other healthcare providers with the necessary skills and competencies to handle complications during pregnancy and childbirth can help bridge the gap in skilled birth attendance and emergency obstetric care.

6. Strengthening health information systems: Investing in robust health information systems that collect and analyze data on maternal health outcomes can help identify trends, monitor progress, and inform evidence-based interventions.

It’s important to note that these recommendations are based on the general need to improve access to maternal health and may not directly address the specific causes of maternal mortality identified in the systematic review. Further research and context-specific analysis would be needed to tailor these innovations to the specific challenges and needs of Sub-Saharan Africa.

AI Innovations Description

Based on the information provided, the recommendation to improve access to maternal health based on the systematic review is to invest in health information systems that collect and publish comprehensive, quality data on the causes of maternal death in Sub-Saharan Africa (SSA). This includes:

1. Strengthening Health Information Systems: SSA countries should prioritize the development and implementation of robust health information systems that capture accurate and comprehensive data on maternal deaths. This includes improving data collection methods, standardizing reporting mechanisms, and ensuring data quality and completeness.

2. Enhancing Data Sharing and Accessibility: Governments and relevant stakeholders should establish a publicly accessible repository of data sets and government reports on the causes of maternal death. This will facilitate transparency, accountability, and enable researchers, policymakers, and healthcare providers to access and utilize the data for evidence-based decision-making.

3. Capacity Building: Efforts should be made to enhance the capacity of healthcare providers, researchers, and data managers in SSA countries to effectively collect, analyze, and interpret data on maternal deaths. This can be achieved through training programs, workshops, and collaborations with international partners.

4. Collaboration and Knowledge Sharing: SSA countries should collaborate with regional and international organizations, such as the World Health Organization (WHO), to share best practices, experiences, and lessons learned in improving maternal health data collection and analysis. This can help accelerate progress and avoid duplication of efforts.

5. Advocacy and Resource Mobilization: Governments, civil society organizations, and international partners should advocate for increased funding and resources to support the development and implementation of robust health information systems. This includes allocating adequate budgetary resources, leveraging partnerships, and engaging in advocacy efforts to prioritize maternal health data collection and analysis.

By implementing these recommendations, SSA countries can improve their understanding of the leading causes of maternal deaths and develop targeted interventions to address them. This will ultimately contribute to reducing maternal mortality rates and improving access to maternal health services in the region.

AI Innovations Methodology

Based on the provided description, the systematic review aimed to identify the leading causes of maternal deaths in Sub-Saharan Africa (SSA) by analyzing studies published from 2015 to 2020. The methodology followed the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) 2020 guidelines. Here is a brief summary of the methodology:

1. Search Strategy: The researchers conducted a comprehensive search using databases such as PubMed, WorldCat Discovery Libraries Worldwide, and Google Scholar. They used specific search terms related to maternal mortality, reproductive age mortality, pregnancy-related deaths, causes, and SSA country names. The search period was from 2015 to 2020.

2. Study Selection: The researchers included original research articles published in English that reported causes of maternal deaths in SSA countries. They excluded studies that did not provide study results for the mentioned countries, evaluated interventions, focused on a single cause of death, used computer models to assign causes of death, or had incomplete breakdowns of causes of death. Government reports for Zimbabwe and South Africa were also included.

3. Data Extraction: Two authors independently screened the articles based on titles, abstracts, and full texts. They used an adapted Critical Appraisal Skills Programme (CASP) form in Microsoft Excel to extract data from the selected articles. The data included study details, study design, source of maternal death data, causes of death, and the number of deaths attributed to each cause.

4. Risk of Bias Assessment: The researchers assessed the risk of bias using a tool adapted from a previous study. The tool assessed information bias, missing data bias, selection bias, and measurement bias. Each criterion was rated as low, medium, or high risk of bias. The overall risk of bias for each study was determined based on the average scores.

5. Data Synthesis: The researchers calculated the total number of deaths reported in all the studies and the proportions of deaths attributed to each cause of death and International Classification of Disease – 10th revision for maternal mortality (ICD-MM) group. The leading causes of death in SSA and its sub-regions were identified by ranking the proportions of deaths. The results were compared with WHO and Global Burden of Disease (GBD) estimates.

6. Limitations: The review acknowledged limitations such as the failure to access more data from government reports and the under-reporting of deaths from incidental causes in the region. The researchers recommended the continued investment in health information systems and the establishment of a publicly accessible repository of data sets and government reports for causes of maternal death.

In summary, the methodology involved a systematic search, study selection, data extraction, risk of bias assessment, data synthesis, and comparison with existing estimates. The review aimed to identify the leading causes of maternal deaths in SSA and provide insights for interventions and improvements in maternal health.

Auteur

Dima Health

Statistics:

Citations: 16

Identifiers:

DOI: 10.7189/jogh.11.04048

Research Areas:

Community Interventions, Genetics and Genomics, Health System and Policy, Maternal and Child Health, Noncommunicable Diseases, Quality of Care, Sexual and Reproductive Health, Social Determinants

Study Countries:

Multi-Countries, South Africa, Zimbabwe

Study Design:

Cohort Study, randomised-control-trial

Study Approach:

Systematic Review

Participants Gender:

Female

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