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Prevalence and determinants of maternal near miss in Ethiopia: a systematic review and meta-analysis, 2015–2023

BMC Women's Health volume 23, Article number: 380 (2023) Cite this article

A Correction to this article was published on 01 August 2023

This article has been updated

Abstract

Background

One of the most challenging problems in developing countries including Ethiopia is improving maternal health. About 303,000 mothers die globally, and one in every 180 is at risk from maternal causes. Developing regions account for 99% of maternal deaths. Maternal near miss (MNM) resulted in long-term consequences. A systematic review and meta-analysis was performed to assess the prevalence and predictors of maternal near miss in Ethiopia from January 2015 to March 2023.

Methods

A systematic review and meta-analysis cover both published and unpublished studies from different databases (PubMed, CINHAL, Scopus, Science Direct, and the Cochrane Library) to search for published studies whilst searches for unpublished studies were conducted using Google Scholar and Google searches. Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were used. Duplicated studies were removed using Endnote X8. The paper quality was also assessed based on the JBI checklist. Finally, 21 studies were included in the study. Data synthesis and statistical analysis were conducted using STATA Version 17 software. Forest plots were used to present the pooled prevalence using the random effect model. Heterogeneity and publication bias was evaluated using Cochran’s Q test, (Q) and I squared test (I2). Subgroup analysis based on study region and year of publication was performed.

Result

From a total of 705 obtained studies, twenty-one studies involving 701,997 pregnant or postpartum mothers were included in the final analysis. The national pooled prevalence of MNM in Ethiopia was 140/1000 [95% CI: 80, 190]. Lack of formal education [AOR = 2.10, 95% CI: 1.09, 3.10], Lack of antenatal care [AOR = 2.18, 95% CI: 1.33, 3.03], history of cesarean section [AOR = 4.07, 95% CI: 2.91, 5.24], anemia [AOR = 4.86, 95% CI: 3.24, 6.47], and having chronic medical disorder [AOR = 2.41, 95% CI: 1.53, 3.29] were among the predictors of maternal near misses from the pooled estimate.

Conclusion

The national prevalence of maternal near miss was still substantial. Antenatal care is found to be protective against maternal near miss. Emphasizing antenatal care to prevent anemia and modifying other chronic medical conditions is recommended as prevention strategies. Avoiding primary cesarean section is recommended unless a clear indication is present. Finally, the country should place more emphasis on strategies for reducing MNM and its consequences, with the hope of improving women's health.

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Background

Globally, 303 000 mothers die each year from maternal causes, with one in every 180 at risk; developing regions account for 99% of maternal deaths [1]. Millions of women suffered from pregnancy and its complications, including death, and the majority (94%) of these deaths occurred in low- and middle-income countries [2]. Sub-Saharan African countries continue to share the largest portion of maternal mortality [3]; about 66% of global MMR accounts for sub-Saharan Africa alone [4]. However, it is rare in absolute numbers in the community, possibly due to underreporting by healthcare providers and managers [5].

Direct obstetric causes like hemorrhage, hypertensive disorder of pregnancy (pre-eclampsia, eclampsia), postpartum sepsis, obstructed labor, uterine rupture, and abortion-related death are among the most common causes of maternal morbidity and mortality [2, 6, 7].

For every woman who dies from pregnancy or childbirth-related causes, about twenty more experienced maternal near miss [8]. World Health Organization (WHO) defines a maternal near-miss (MNM) as a woman who nearly died but survived a complication that occurred during pregnancy, childbirth, or within 42 days of termination of pregnancy [9, 10].

The national annual incidence of maternal near miss was 7.2 per 1,000 live births in Kenya [11], 22.1 per 1000 live births in Sudan [12], and 23.6 per 1,000 live births in Tanzania [13]. In Uganda, the MNM rate was 287.7/1000 pregnancies [14]. Maternal near miss in Ethiopia ranges from 4.97% to 29.7% [15, 16], one study reported a 50.4 per 1000 live births ratio [17].

Studying MNM is very important, as maternal mortality is more likely to be underreported by healthcare providers and managers, especially in low-income countries [18]. MNM shows the quality of obstetric intervention to save the lives of mothers and also provides the chance of interviewing the mother [19].

All countries must contribute to achieve the global target of MMR of less than 70 per 1,000 live births, and no country should have MMR of more than 140 per 1,000 live births by 2030 [20, 21]. Ethiopia is one of the countries that strive to reduce maternal mortality through different strategies, such as the promotion of maternal health, the provision of free maternity services and the provision of supplies [22]; however maternal mortality remains a public concern [10, 23, 24].

MNM is associated with life-threatening pregnancy outcomes like stillbirth, birth asphyxia, and low birth weight [25,26,27,28]. This bad pregnancy outcome can be reduced by identifying predictors, implementing intervention for context-specific quality improvement [29], and addressing modifiable risk factors accordingly [30].

Different predictors that were associated with maternal near misses in Ethiopia include, delay to seek health care, referred from the health facility, history of cesarean Section. [31,32,33], no formal education [28, 32], travelling greater than 60 min to reach the place of final care [15, 32, 33], induction of labor [15, 32, 33], age less than 16 [32], history of chronic medical disorders [28, 32, 33], lack of ANC [15, 33], lack of birth preparedness and complication readiness plan [33], less monthly income, and rural residence [28].

Understanding the estimated national burden of MNM and its predictors is very important. This will enable policymakers and anyone else who wants to take action to reduce maternal morbidity and mortality to do so based on evidence. Apart from different studies across the countries that are inconsistent and make generalizability difficult, there is a paucity of pooled national evidence on the burden of MNM and its predictors. Therefore, this study aimed to determine the pooled prevalence of maternal near-miss and its determinants among women in Ethiopia by including a study published after 2015, as it was a turning point from millennium development goals to sustainable development goals.

Methods

Systematic review registration and reporting of findings

The protocol for this study has been registered on the International Prospective Register of Systematic Review (PROSPERO), the University of York Center for Reviews and Dissemination (https://www.crd.york.ac.uk/) with registration number CRD42023393803. The finding of the study was reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA 2020) [34] guidelines.

Eligibility criteria and study selection

The systematic review and meta-analysis were designed to determine the magnitude of MNM and its determinants among pregnant and postpartum women in Ethiopia. A maternal near miss is a woman who nearly died but survived a complication that occurred during pregnancy, childbirth or within 42 days of termination of pregnancy [10].

This study included all published studies (cross-sectional, case–control, and cohort) that reported the magnitude and/or determinants of a maternal near-miss in Ethiopia, with full text and written in English. However, studies that only included abstracts, case reports and written in languages other than English were excluded. End note X8 was used to remove the duplicated result. Three authors (AN, ML, TB), screened the article by reading the title and abstract based on predefined inclusion and exclusion criteria.

Sources and search strategy

The systematic review took into account English-language studies that were published between January 2015 and March 2023. Searches for published research were conducted using electronic databases like PubMed/Medline, Scopus, CINHAL, Science Direct, and the Cochrane Library, whilst searches for unpublished studies were conducted using Google Scholar, Advanced Google Search and Google. Keywords and medical subject heading terms were used to search an electronic data repository. The discovered PECO components were connected using Boolean operators.

The search strategy for advanced PubMed includes: ((((("epidemiology"[Subheading] OR "epidemiology"[All Fields] OR "prevalence"[All Fields] OR "prevalence"[MeSH Terms]) OR determinants[All Fields]) OR burden[All Fields]) AND ("mothers"[MeSH Terms] OR "mothers"[All Fields] OR "maternal"[All Fields]) AND "near miss"[All Fields]) AND (("mothers"[MeSH Terms] OR "mothers"[All Fields] OR "maternal"[All Fields]) AND near[All Fields] AND miss[All Fields])) AND Ethiopia[Title].

For scopus search

Aditional searching (ALL (prevalence) AND ALL(maternal AND nearmiss) OR TITLE-ABS-KEY ( maternal AND near-miss) AND TITLE-ABS-KEY ( predictors) OR ALL (associated AND factors) AND TITLE-ABS-KEY (Ethiopia)) were used. Then all identified keywords and index terms were checked across all databases. Finally the reference lists of all identified articles were searched for further articles.

Quality assessment and data extraction

Data extraction was done by five authors (ML, AN, AS, HD and FT) by using an extraction format prepared on Microsoft Excel. The extracted data were first author name, publication year, publication place, study design, sample size, sampling method, maternal near miss, determinants with odd ratio, and causes that resulted in maternal near miss.

Each screened article was evaluated by five authors (AN, ML, AS, AB, and DA) for quality assurance using standardized critical evaluation tools, Joanna Briggs Institute (JBI) Critical Appraisal tools [35]. Then the quality of each included article was classified as high (80% or above), moderate (65%–80%), or low (less than 65%). The final inclusion was determined by reading the full text of the articles by five authors (AS, EY, KN, Til. B and AT). Finally, the included article was verified by (MD, DA, HF and GD). Any disagreement was resolved by the discussion after the same procedure was repeated.

Outcome of interest

The primary outcome of this systematic review is the magnitude of maternal near miss in Ethiopia. The secondary outcome is determinants of maternal near miss.

Statistical analysis and publication bias

Data synthesis and statistical analysis were conducted using STATA version 17. The random effect model of analysis was used as a method of meta-analysis to reduce the heterogeneity of included studies. Subgroup meta-analysis was done by study setting, sample size and year of publication. A forest plot was used to present the result of the meta-analysis. Heterogeneity among included articles was evaluated using Cochran’s Q test, (Q) and I squared test (I2). I2 test statistics of 25%, 50% and 75% were declared as low, moderate and high heterogeneity, respectively. The effect of factors associated with maternal near misses was pooled. The investigators checked for potential publication bias through visual inspection of a funnel plot and Egger’s Regression Test. A p-value of less than 0.05 was used as statistical evidence of publication bias. Finally, the findings of the included studies were first presented using a narrative synthesis and followed by a meta-analysis chart.

Result

Study identification

Initially, 705 studies were retrieved from electronic databases like PubMed/Midline, Scopus, CINHAL and Science Direct. Unpublished studies were searched from Google Scholar and advanced Google search and Google. The major reason for exclusion was duplication and mismatch. 105 duplicate was found and removed. 599 studies were screened by title and abstract 541 of them were removed due to mismatch. 58 studies were sought for retrieval and 11 were not retrieved. A full text was assessed for illegibility (English language, report prevalence of MNM and/or its predictors, present in full text, a study done in Ethiopia after 2015 and moderate and above in quality) and finally, 21 studies were included in a systematic review and meta-analysis (Fig. 1).

Fig. 1
figure 1

PRISMA flow diagram of the studies included in final systematic review and meta-analysis of maternal near miss in Ethiopia, 2023 [36]

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Study characteristics

A total of 701,997 pregnant or postpartum mothers who visited the health facility for Obstetrics or Gynecologic services from 21 studies were included. A study published from January 2015 to March 2023 in Ethiopia, of which 5 studies were from the Amhara region, 5 from the Oromia region, 4 studies were from the Southern Nation Nationalities and Peoples (SNNP) region, 1 study from the Harar region, 2 studies from the Tigray region, 3 studies from Addis Abeba city, and another study that was done nationally, were included. Eight of them were published before 2020, while the rest were published after 2020. Regarding the quality of included studies 10 were moderate while the rest 11 were high quality based on JBI (Additional file 1). 12 of 22 studies used a cross-sectional study design, while the rest used a case–control, except for one study that used a survey from national data. From the total included studies 8 used record review for data collection, while 12 studies used interviews supported by chart review. The sample size ranges from 296 to 78,195 (Table 1).

Table 1 Characteristics of studies included in systematic review and meta-analysis of maternal near miss in Ethiopia, 2023
Full size table

Prevalence of maternal near miss

The pooled prevalence of maternal near misses from 13 studies indicated 14% [95% CI: 8, 19]. Considerable heterogeneity was observed across the included studies [I2 = 99.98, p < 0.001] (Fig. 2).

Fig. 2
figure 2

Forest plot indicating a pooled prevalence of maternal near misses in Ethiopia, 2023

Full size image

Subgroup analysis

Subgroup analysis based on the study setting (region) didn’t show any significant variation. Based on the subgroup analysis result, the highest prevalence (20%, 95% CI: 14, 26) I2 = 99.92%) was seen in the Amhara region, and the lowest prevalence (3%, 95% CI: 2, 4), I2 = . %) was seen in the Tigray region (Fig. 3).

Fig. 3
figure 3

Subgroup analysis based on study area showing the pooled prevalence of maternal near miss in Ethiopia, 2023

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There is no significant variation between studies published before and after 2020 (Fig. 4).

Fig. 4
figure 4

Subgroup analysis based on year of publication

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Sensitivity analysis

The result of the sensitivity analysis done by dropping large and small sample sizes alternatively indicated there was no significant difference (Table 2).

Table 2 Sensitivity analysis to see the effect of sample size on outcome
Full size table

Factors associated with maternal near misses

Nine studies were included to assess the relationship between residence and MNM [31, 32, 36, 38, 43, 47, 49,50,51]. From the pooled estimate, there is no association between rural residence and maternal near misses [AOR 0.98, 95% CI, 0.66, 1.30]. Ten studies were included to evaluate the association between ANC and MNM [15, 31, 36, 43, 44, 47,48,49,50,51]. From pooled estimates, mothers who have no ANC were 2.18 times more likely to develop MNM when compared to those who have ANC [AOR = 2.18, 95% CI: 1.33, 3.03] (Fig. 5).

Fig. 5
figure 5

Association between lack of antenatal care and maternal near miss in Ethiopia 2023

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The association between cesarean section (CS) and maternal near-miss was also assessed by 7 studies [31, 32, 36, 37, 47, 49, 51]. A pooled estimate revealed that a mother who has a history of cesarean section is 4.07 times more likely to develop MNM when compared to those who have no history of CS [AOR = 4.07, 95% CI: 2.91, 5.24]. There is no observed heterogeneity (I2 = 0) (Fig. 6).

Fig. 6
figure 6

Association between history cesarean section and maternal near miss in Ethiopia 2023

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Three studies were pooled to assess the association between anemia in index pregnancy and MNM [36, 37, 50]. Those who had anemia were 4.86 times more likely to develop MNM when compared to those who had no anemia [AOR = 4.86; 95% CI: 3.24, 6.47]. There is no heterogeneity in the study [I2 = 0.00%]. The effect of chronic medical disorders on MNM was assessed by a pooled estimate of five studies [32, 37, 47, 49, 51]. Those who have had a history of chronic medical disorders were 2.41 times more likely to develop MNM when compared to their counterparts [AOR = 2.41; 95% CI: 1.53, 3.29]. There is no variability among the included studies [I2 = 0.00%]. Four studies were included to evaluate the effect of educational level on MNM [32, 48, 49, 51]. The pooled estimate indicated that those who have no formal education were 2.10 times more likely to develop MNM when compared to the educated group [AOR = 2.10; 95% CI: 1.09, 3.10].

Additionally, factors like grand multiparty, residence, and a delay of 60 min were pooled to look at their effects. Even though those predictors were significantly associated in some studies, the pooled estimate fails to indicate a significant association.

Discussion

The prevalence and factors associated with maternal near miss in Ethiopia were assessed and analyzed. From the 21 studies included in this systematic review and meta-analysis, 13 were used to compute the pooled prevalence, while 14 studies were used to assess factors associated with maternal near miss.

The pooled prevalence of maternal near miss from 13 studies (about 378,173 study participants) indicated 14% [95% CI: 8, 19]. This finding was greater than the global weighted pooled burden of maternal near misses [52], a study done in sub-Saharan Africa, Europe and Northern America [53], a study done in Tanzania [13], Latin America [54], Kenya [11], Harare, Namibia [55], Zimbabwe [56], South Africa [57], Eastern India [58] and Rwanda [59]. The reason for this variation could be the scope of the study, the year of publication, and the nature of the variation of MNM among high and low-income countries.

This finding is consistent with a systematic review and meta-analysis conducted in Ethiopia [19], a study conducted in Rwanda [60], Ghana [61], Indonesia and Western Pacific [62]. This could be because they belong to countries classified by the World Bank as developing countries and have high maternal morbidity and mortality rates.

The finding of this study was lower than those of the studies done in Uganda [14], and Uganda [63]. The difference between these findings may be because of variation between studies (systematic vs single study) and the difference in socio-demographics and health care systems of the study population.

In this meta-analysis, women who lack ANC follow-up were more likely to have maternal near miss. This finding was supported by a systematic review and meta-analysis (SRMA) in Ethiopia [19, 64]. This could be because lack of ANC is many things in obstetrics. It is a lack of screening, diagnosis and management, supplementation, health education [65] and a lack of birth preparedness complication readiness plan which resulted in poor pregnancy outcomes [66]. Also, those who have a history of cesarean section (CS) were 4.07 times more likely to have MNM. This finding was supported by a systematic review and meta-analysis study [67]. This is because the presence of a uterine scar could be one factor in the occurrence of complications like uterine rupture and hemorrhage [68]. Additionally, different complications can occur intraoperatively and can result in maternal near miss.

Another predictor was anemia, which increased 4.86 times the odds of having MNM among those who have anemia when compared to those who do not have anemia. Furthermore, those who had chronic medical disorders were 2.41 times more likely to have MNM when compared to their counterparts. This could be because medical disorders, including anemia, can be exacerbated by the physiologic nature of pregnancy and contribute to maternal MNM [69,70,71,72]. Educational status is another factor that affects maternal near miss. From the pooled estimate, participants who have no formal education were 2.10 times more likely to develop MNM when compared to the educated group. This could be because uneducated women may be less knowledgeable, limited awareness of their health and pregnancy danger signs, and are less likely to utilise maternity healthcare services [73,74,75,76,77].

This finding has considerable heterogeneity and should be interpreted with some limitations. The highest heterogeneity may be explained by the difference in study design or characteristics of the study population.

Conclusion

The national prevalence of maternal near misses was still substantial. Lack of formal education, lack of ANC, history of cesarean section, anemia, and chronic medical disorders were among the predictors of maternal near miss. Antenatal care is found to be a special opportunity and area to intervene. More ANC contact as recommended by WHO should be practised. Avoiding primary cesarean section is recommended unless a clear indication is present. The country should give more emphasis on strategies for reducing MNM and its consequence, with the hope of improving women's health.

Strengths and limitations of the study

The study provided pooled prevalence of maternal near misses which is more representative than a single study and is strong evidence. There is considerable heterogeneity across the study. This could be due to different study populations, study designs, data collection methods and sample sizes. Also, the funnel plot is asymmetric indicating publication bias, as any significant finding with maternal near-miss is more likely to be published. Therefore the interpretation of the finding should be cautious.

Availability of data and materials

Additional data can be available from the corresponding author upon reasonable request.

Change history

References

  1. Organization WH. Trends in maternal mortality: 1990–2015: estimates from WHO, UNICEF, UNFPA, World Bank Group and the United Nations population division: World Health Organization; 2015 : https://reliefweb.int/report/world/trends-maternal-mortality-1990-2015-estimates-who-unicef-unfpa-world-bank-group-and?gclid=Cj0KCQjw1rqkBhCTARIsAAHz7K2huQJWiRD1Ypc1BQd9M54sHar6d8YNbILy-8kpLtKAfsiCboS-JX8aAg__EALw_wcB.

  2. Organization WH. Maternal mortality: evidence brief. World Health Organization; 2019:https://apps.who.int/iris/handle/10665/329886.

  3. Batist J. An intersectional analysis of maternal mortality in Sub-Saharan Africa: a human rights issue. J Glob Health. 2019;9(1):010320. https://doi.org/10.7189/jogh.09.010320.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Organization WH. Trends in maternal mortality 2000 to 2017: estimates by WHO, UNICEF, UNFPA, World Bank Group and the United Nations population division. 2019: https://www.unfpa.org/featured-publication/trends-maternal-mortality-2000-2017.

  5. Kalhan M, Singh S, Punia A, Prakash J. Maternal near-miss audit: Lessons to be learnt. Int J Appl Basic Med Res. 2017;7(2):85–7. https://doi.org/10.4103/2229-516X.205815.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Neal S, Mahendra S, Bose K, Camacho AV, Mathai M, Nove A, et al. The causes of maternal mortality in adolescents in low and middle income countries: a systematic review of the literature. BMC Pregnancy Childbirth. 2016;16(1):352. https://doi.org/10.1186/s12884-016-1120-8.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Van Den Broek NR, Falconer AD. Maternal mortality and millennium development goal 5. Br Med Bull. 2011;99(1):25–38. https://doi.org/10.1093/bmb/ldr033.

    Article  PubMed  Google Scholar 

  8. Kalhan M, Singh S, Punia A, Prakash J. Maternal near-miss audit: lessons to be learnt. Int J Appl Basic Med Res. 2017;7(2):85.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Pattinson R, Say L, Souza JP, Broek N, Rooney C,mortalityWHOwgom, et al. WHO maternal death and near-miss classifications. Bull World Health Organ. 2009;87(10):734. https://doi.org/10.2471/blt.09.071001.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Say L, Souza JP, Pattinson RC. Maternal near miss–towards a standard tool for monitoring quality of maternal health care. Best Pract Res Clin Obstet Gynaecol. 2009;23(3):287–96.

    Article  PubMed  Google Scholar 

  11. Owolabi O, Riley T, Juma K, Mutua M, Pleasure ZH, Amo-Adjei J, et al. Incidence of maternal near-miss in Kenya in 2018: findings from a nationally representative cross-sectional study in 54 referral hospitals. Sci Rep. 2020;10(1):15181.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Ali AA, Khojali A, Okud A, Adam GK, Adam I. Maternal near-miss in a rural hospital in Sudan. BMC Pregnancy Childbirth. 2011;11(1):48. https://doi.org/10.1186/471-2393-11-48.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Nelissen EJ, Mduma E, Ersdal HL, Evjen-Olsen B, van Roosmalen JJ, Stekelenburg J. Maternal near miss and mortality in a rural referral hospital in northern Tanzania: a cross-sectional study. BMC Pregnancy Childbirth. 2013;13(1):141.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Nansubuga E, Ayiga N, Moyer CA. Prevalence of maternal near miss and community-based risk factors in Central Uganda. Int J Gynaecol Obstet. 2016;135(2):214–20.

    Article  PubMed  Google Scholar 

  15. Kumela L, Tilahun T, Kifle D. Determinants of maternal near miss in western Ethiopia. Ethiop J Health Sci. 2020;30(2):161–8. https://doi.org/10.4314/ejhs.v30i2.3.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Gedefaw M, Gebrehana H, Gizachew A, Taddess F. Assessment of maternal near miss at Debre Markos referral hospital, Northwest Ethiopia: five years experience. Open Journal of Epidemiology. 2014;4(04):199. https://doi.org/10.4236/ojepi.2014.44026.

    Article  Google Scholar 

  17. Woldeyes WS, Asefa D, Muleta G. Incidence and determinants of severe maternal outcome in Jimma University teaching hospital, south-West Ethiopia: a prospective cross-sectional study. BMC Pregnancy Childbirth. 2018;18(1):255. https://doi.org/10.1186/s12884-018-1879-x.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Melberg A, Mirkuzie AH, Sisay TA, Sisay MM, Moland KM. ‘Maternal deaths should simply be 0’: politicization of maternal death reporting and review processes in Ethiopia. Health Policy and Planning. 2019;34(7):492–8. https://doi.org/10.1093/heapol/czz075.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Mengist B, Desta M, Tura AK, Habtewold TD, Abajobir A. Maternal near miss in Ethiopia: Protective role of antenatal care and disparity in socioeconomic inequities: A systematic review and meta-analysis. International Journal of Africa Nursing Sciences. 2021;15:100332.

    Article  Google Scholar 

  20. Organization WH. Strategies towards ending preventable maternal mortality (EPMM). 2015: https://apps.who.int/iris/handle/10665/153544.

  21. Nations U. Sustainable Development Goals. Geneva World Health Organization, 2015.:https://sdgs.un.org/goals.

  22. Liyew EF, Yalew AW, Afework MF, Essen B. Incidence and causes of maternal near-miss in selected hospitals of Addis Ababa, Ethiopia. PLoS One. 2017;12(6):e0179013. https://doi.org/10.1371/journal.pone.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Organization WH. Beyond the numbers: reviewing maternal deaths and complications to make pregnancy safer: World Health Organization; 2004. https://doi.org/10.1093/bmb/ldg009 p.

  24. Pattinson RC, Hall M. Near misses: a useful adjunct to maternal death enquiries. Br Med Bull. 2003;67(1):231–43. https://doi.org/10.1093/bmb/ldg007.

    Article  CAS  PubMed  Google Scholar 

  25. Adeoye IA, Onayade AA, Fatusi AO. Incidence, determinants and perinatal outcomes of near miss maternal morbidity in Ile-Ife Nigeria: a prospective case control study. BMC Pregnancy Childbirth. 2013;13(1):93. https://doi.org/10.1186/471-2393-13-93.

    Article  PubMed  PubMed Central  Google Scholar 

  26. Agarwal N, Jain V, Bagga R, Sikka P, Chopra S, Jain K. Near miss: determinants of maternal near miss and perinatal outcomes: a prospective case control study from a tertiary care center of India. J matern fetal neonatal med. 2022;35(25):5909–16. https://doi.org/10.1080/14767058.2021.1902497.

    Article  PubMed  Google Scholar 

  27. Tura AK, Scherjon S, van Roosmalen J, Zwart J, Stekelenburg J, van den Akker T. Surviving mothers and lost babies–burden of stillbirths and neonatal deaths among women with maternal near miss in eastern Ethiopia: a prospective cohort study. J Glob Health. 2020;10(1):01041310. https://doi.org/10.7189/jogh.10.010413.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Liyew EF, Yalew AW, Afework MF, Essen B. Maternal near-miss and the risk of adverse perinatal outcomes: a prospective cohort study in selected public hospitals of Addis Ababa, Ethiopia. BMC Pregnancy Childbirth. 2018;18(1):345. https://doi.org/10.1186/s12884-018-1983-y.

    Article  PubMed  PubMed Central  Google Scholar 

  29. Gebrehiwot Y, Tewolde BT. Improving maternity care in Ethiopia through facility based review of maternal deaths and near misses. Int J Gynecol Obstet. 2014;127:S29–34. https://doi.org/10.1016/j.ijgo.2014.08.003.

    Article  Google Scholar 

  30. Goffman D, Madden RC, Harrison EA, Merkatz IR, Chazotte C. Predictors of maternal mortality and near-miss maternal morbidity. J Perinatol. 2007;27(10):597–601. https://doi.org/10.1038/sj.jp.7211810.

    Article  CAS  PubMed  Google Scholar 

  31. Kasahun AW, Wako WG. Predictors of maternal near miss among women admitted in Gurage zone hospitals, South Ethiopia, 2017: a case control study. BMC Pregnancy Childbirth. 2018;18(1):1–9. https://doi.org/10.1186/s12884-018-1903-1.

    Article  Google Scholar 

  32. Mekango DE, Alemayehu M, Gebregergs GB, Medhanyie AA, Goba G. Determinants of maternal near miss among women in public hospital maternity wards in northern Ethiopia: a facility based case-control study. PLoS One. 2017;12(9):e0183886. https://doi.org/10.1371/journal.pone.0183886.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Habte A, Wondimu M. Determinants of maternal near miss among women admitted to maternity wards of tertiary hospitals in Southern Ethiopia, 2020: A hospital-based case-control study. PLoS ONE. 2021;16(5):e0251826.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. Systematic reviews. 2021;10(1):1–11. https://doi.org/10.1016/j.ijsu.2021.105906.

    Article  Google Scholar 

  35. Institute JB. Critical appraisal tools for use in the JBI systematic reviews checklist for prevalence studies. University of Adelaide, Adelaide, Australia2019. p. https://jbi.global/sites/default/files/2019-05/JBI_Critical_Appraisal-Checklist_for_Prevalence_Studies7_0.pdf.

  36. Geze Tenaw S, Girma Fage S, Assefa N, Kenay Tura A. Determinants of maternal near-miss in private hospitals in eastern Ethiopia: A nested case-control study. Womens Health (Lond). 2021;17:17455065211061949. https://doi.org/10.1177/17455065211061949.

  37. Tenaw SG, Assefa N, Mulatu T, Tura AK. Maternal near miss among women admitted in major private hospitals in eastern Ethiopia: a retrospective study. BMC Pregnancy Childbirth. 2021;21(1):181. https://doi.org/10.1186/s12884-021-03677-w.

    Article  PubMed  PubMed Central  Google Scholar 

  38. Mekonnen A, Fikadu G, Seyoum K, Ganfure G, Degno S, Lencha B. Factors associated with maternal near-miss at public hospitals of South-East Ethiopia: An institutional-based cross-sectional study. Womens Health (Lond). 2021;17:17455065211060617. https://doi.org/10.1177/17455065211060617.

  39. Teka H, Yemane A, Berhe Zelelow Y, Tadesse H, Hagos H. Maternal near-miss and mortality in a teaching hospital in Tigray region, Northern Ethiopia. Womens Health (Lond). 2022;18:17455057221078739.

  40. Gebremariam TB, Demie TG, Derseh BT, Mruts KB. Trends of and factors associated with maternal near-miss in selected hospitals in North Shewa Zone, Central Ethiopia. J Pregnancy. 2022;2022:2023652.

  41. Geleto A, Chojenta C, Taddele T, Loxton D. Incidence of maternal near miss among women in labour admitted to hospitals in Ethiopia. Midwifery. 2020;82:102597.

  42. Wakgar N, Dulla D, Daka D. Maternal near misses and death in southern Ethiopia: a retrospective study. Ethiop J Reprod Health. 2019;11(2):9.

  43. Yemane Y, Tiruneh F. Incidence-proportion of maternal near-misses and associated Factors in Southwest Ethiopia: a prospective cross-sectional study. Int J Womens Health. 2020;12:1125–34. https://doi.org/10.2147/IJWH.S283122.

    Article  PubMed  PubMed Central  Google Scholar 

  44. Worke MD, Enyew HD, Dagnew MM. Magnitude of maternal near misses and the role of delays in Ethiopia: a hospital based cross-sectional study. BMC Res Notes. 2019;12(1):585. https://doi.org/10.1186/s13104-019-4628-y.

    Article  PubMed  PubMed Central  Google Scholar 

  45. Asaye MM. Proportion of maternal near-miss and its determinants among northwest Ethiopian women: a cross-sectional study. Int J Reprod Med. 2020;2020.

  46. Dile M, Seyum T. Proportion of maternal near misses and associated factors in referral hospitals of Amhara regional state, Northwest Ethiopia: institution based cross sectional study. Gynecol Obstet (Sunnyvale). 2015;5(308):2161-0932.1000.

  47. Teshome HN, Ayele ET, Hailemeskel S, Yimer O, Mulu GB, Tadese M. Determinants of maternal near-miss among women admitted to public hospitals in North Shewa Zone, Ethiopia: A case-control study. Front Public Health. 2022;10:996885. https://doi.org/10.3389/fpubh.2022.996885.

  48. Danusa KT, Debelo BT, Wakgari N, Seifu B, Kenasa K, Daba G, et al. Predictors of maternal near miss in public hospitals of West Shoa zone, central Ethiopia: A case-control study. Front Med (Lausanne). 2022;9:868992. https://doi.org/10.3389/fmed.2022.868992.

    Article  PubMed  Google Scholar 

  49. Habte A, Wondimu M. Determinants of maternal near miss among women admitted to maternity wards of tertiary hospitals in Southern Ethiopia, 2020: A hospital-based case-control study. PLoS One. 2021;16(5):e0251826. https://doi.org/10.1371/journal.pone.0251826.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Liyew EF, Yalew AW, Afework MF, Essen B. Distant and proximate factors associated with maternal near-miss: a nested case-control study in selected public hospitals of Addis Ababa, Ethiopia. BMC Womens Health. 2018;18(1):28. https://doi.org/10.1186/s12905-018-0519-y.

    Article  PubMed  PubMed Central  Google Scholar 

  51. Dessalegn FN, Astawesegn FH, Hankalo NC. Factors associated with maternal near miss among women admitted in west Arsi zone public hospitals, Ethiopia: unmatched case-control study. J Pregnancy. 2020;2020:6029160. https://doi.org/10.1155/2020/6029160.

  52. Abdollahpour S, Heidarian Miri H, Khadivzadeh T. The global prevalence of maternal near miss: a systematic review and meta-analysis. Health Promot Perspect. 2019;9(4):255–62. https://doi.org/10.15171/hpp.2019.35.

    Article  PubMed  PubMed Central  Google Scholar 

  53. Firoz T, Romero CLT, Leung C, Souza JP, Tunçalp Ö. Global and regional estimates of maternal near miss: a systematic review, meta-analysis and experiences with application. BMJ Global Health. 2022;7(4):e007077. https://doi.org/10.1136/bmjgh-2021-007077.

    Article  PubMed  PubMed Central  Google Scholar 

  54. De Mucio B, Abalos E, Cuesta C, Carroli G, Serruya S, Giordano D, et al. Maternal near miss and predictive ability of potentially life-threatening conditions at selected maternity hospitals in Latin America. Reprod Health. 2016;13(1):134. https://doi.org/10.1186/s12978-016-0250-9.

    Article  PubMed  PubMed Central  Google Scholar 

  55. Heemelaar S, Josef M, Diener Z, Chipeio M, Stekelenburg J, van den Akker T, et al. Maternal near-miss surveillance, Namibia. Bull World Health Organ. 2020;98(8):548–57. https://doi.org/10.2471/BLT.20.251371.

    Article  PubMed  PubMed Central  Google Scholar 

  56. Chikadaya H, Madziyire MG, Munjanja SP. Incidence of maternal near miss in the public health sector of Harare, Zimbabwe: a prospective descriptive study. BMC Pregnancy Childbirth. 2018;18(1):458. https://doi.org/10.1186/s12884-018-2092-7.

    Article  PubMed  PubMed Central  Google Scholar 

  57. Heitkamp A, Vollmer L, van den Akker T, Gebhardt GS, Sandberg EM, van Roosmalen J, et al. Great saves or near misses? Severe maternal outcome in Metro East, South Africa: A region-wide population-based case-control study. Int J Gynecol Obstet. 2022;157(1):173–80. https://doi.org/10.1002/ijgo.13739.

    Article  Google Scholar 

  58. Singh V, Barik A. Maternal Near-Miss as a Surrogate indicator of the quality of obstetric care: a study in a tertiary care hospital in Eastern India. Cureus. 2021;13(1):e12548. https://doi.org/10.7759/cureus.12548.

    Article  PubMed  PubMed Central  Google Scholar 

  59. Kalisa R, Rulisa S, van den Akker T, van Roosmalen J. Maternal near miss and quality of care in a rural Rwandan hospital. BMC Pregnancy Childbirth. 2016;16(1):324. https://doi.org/10.1186/s12884-016-1119-1.

    Article  PubMed  PubMed Central  Google Scholar 

  60. Rulisa S, Umuziranenge I, Small M, van Roosmalen J. Maternal near miss and mortality in a tertiary care hospital in Rwanda. BMC Pregnancy Childbirth. 2015;15:203. https://doi.org/10.1186/s12884-015-0619-8.

    Article  PubMed  PubMed Central  Google Scholar 

  61. Oppong SA, Bakari A, Bell AJ, Bockarie Y, Adu JA, Turpin CA, et al. Incidence, causes and correlates of maternal near-miss morbidity: a multi-centre cross-sectional study. BJOG. 2019;126(6):755–62. https://doi.org/10.1111/471-0528.15578.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. De Silva M, Panisi L, Lindquist A, Cluver C, Middleton A, Koete B, et al. Severe maternal morbidity in the Asia Pacific: a systematic review and meta-analysis. Lancet Reg Health-West Pac. 2021;14:100217. https://doi.org/10.1016/j.lanwpc.2021.100217.

    Article  PubMed  PubMed Central  Google Scholar 

  63. Nakimuli A, Nakubulwa S, Kakaire O, Osinde MO, Mbalinda SN, Nabirye RC, et al. Maternal near misses from two referral hospitals in Uganda: a prospective cohort study on incidence, determinants and prognostic factors. BMC Pregnancy Childbirth. 2016;16:24. https://doi.org/10.1186/s12884-016-0811-5t.

    Article  PubMed  PubMed Central  Google Scholar 

  64. Turi E, Fekadu G, Taye B, Kejela G, Desalegn M, Mosisa G, et al. The impact of antenatal care on maternal near-miss events in Ethiopia: a systematic review and meta-analysis. International Journal of Africa Nursing Sciences. 2020;13: https://doi.org/10.1016/j.ijans.2020.100246.

  65. Geltore TE, Anore DL. The impact of antenatal care in maternal and perinatal health. Empowering Midwives and Obstetric Nurses. 2021;107:https://books.google.com/books?hl=en&lr=&id=R7daEAAAQBAJ&oi=fnd&pg=PA107&dq=The+impact+of+antenatal+care+in+maternal+and+perinatal+health&ots=KggCsr-6W8&sig=YTRQNZV1SlKsHmYwCND0wCW6Piw.

  66. Asrat T, Baraki N, Assefa N, Alemkere G. Birth preparedness among women who gave birth in the last twelve months in Jardega Jarte District, Western Ethiopia. Journal of Pregnancy. 2019;2019.

  67. Nik Hazlina NH, Norhayati MN, Shaiful Bahari I, Mohamed Kamil HR. The prevalence and risk factors for severe maternal morbidities: a systematic review and meta-analysis. Front Med (Lausanne). 2022;9:861028. https://doi.org/10.3389/fmed.2022.861028.

    Article  PubMed  PubMed Central  Google Scholar 

  68. Biswas J, Datta M, Kar K, Mitra D, Reddy P, Biswas A. Retrospective analysis of maternal near miss and the applicability of previous caesarean section delivery as a predictor of risk at a tertiary level hospital of India. Hamdan Med J. 2023;16(1):14. https://doi.org/10.4103/hmj.hmj_69_22.

    Article  Google Scholar 

  69. Garzon S, Cacciato PM, Certelli C, Salvaggio C, Magliarditi M, Rizzo G. Iron deficiency anemia in pregnancy: novel approaches for an old problem. Oman Med J. 2020;35(5):e166. https://doi.org/10.5001/omj.2020.108.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. Beckert RH, Baer RJ, Anderson JG, Jelliffe-Pawlowski LL, Rogers EE. Maternal anemia and pregnancy outcomes: a population-based study. J Perinatol. 2019;39(7):911–9. https://doi.org/10.1038/s41372-019-0375-0.

    Article  PubMed  Google Scholar 

  71. Ramlakhan KP, Johnson MR, Roos-Hesselink JW. Pregnancy and cardiovascular disease. Nat Rev Cardiol. 2020;17(11):718–31. https://doi.org/10.1038/s41569-020-0390-z.

    Article  PubMed  Google Scholar 

  72. Tavera G, Dongarwar D, Salemi JL, Akindela O, Osazuwa I, Akpan EB, et al. Diabetes in pregnancy and risk of near-miss, maternal mortality and foetal outcomes in the USA: a retrospective cross-sectional analysis. J Public Health (Oxf). 2022;44(3):549–57. https://doi.org/10.1093/pubmed/fdab117.

    Article  PubMed  Google Scholar 

  73. Tekelab T, Chojenta C, Smith R, Loxton D. Factors affecting utilization of antenatal care in Ethiopia: A systematic review and meta-analysis. PLoS One. 2019;14(4):e0214848. https://doi.org/10.1371/journal.pone.0214848.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  74. Saaka M, Alhassan L. Prevalence and predictors of birth preparedness and complication readiness in the Kassena-Nankana district of Ghana: an analytical cross-sectional study. BMJ Open. 2021;11(3):e042906. https://doi.org/10.1136/bmjopen-2020-042906.

    Article  PubMed  PubMed Central  Google Scholar 

  75. Ketema DB, Leshargie CT, Kibret GD, Assemie MA, Petrucka P, Alebel A. Effects of maternal education on birth preparedness and complication readiness among Ethiopian pregnant women: a systematic review and meta-analysis. BMC Pregnancy Childbirth. 2020;20(1):1–9. https://doi.org/10.1186/s12884-020-2812-7.

    Article  Google Scholar 

  76. Geleto A, Chojenta C, Musa A, Loxton D. Barriers to access and utilization of emergency obstetric care at health facilities in sub-Saharan Africa: a systematic review of literature. Syst Rev. 2018;7(1):1–14. https://doi.org/10.1186/s13643-018-0842-2.

    Article  Google Scholar 

  77. Moinuddin M, Christou A, Hoque DME, Tahsina T, Salam SS, Billah SM, et al. Birth preparedness and complication readiness among pregnant women in hard-to-reach areas in Bangladesh. PloS one. 2017;12(12):e0189365. https://doi.org/10.1371/journal.pone.0189365.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

We would like to thank all authors of studies included in the review

Funding

This study received no specific financing from governmental, private, or non-profit funding bodies.

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Authors and Affiliations

  1. School of Nursing and Midwifery, College of Health and Medical Sciences, Haramaya University, Harar, Ethiopia

    Abraham Negash, Addisu Sertsu, Kabtamu Nigussie, Tilahun Bete, Elias Yadeta, Tegenu Balcha, Deribe Bekele Dechasa, Jerman Dereje & Magarsa Lami

  2. School of Environmental Health, College of Health and Medical Sciences, Haramaya University, Harar, Ethiopia

    Dechasa Adare Mengistu

  3. School of Public Health, College of Health and Medical Sciences, Haramaya University, Harar, Ethiopia

    Aklilu Tamire, Adisu Birhanu Weldesenbet & Hamdi Fekredin

  4. School of Pharmacy, College of Health and Medical Sciences, Haramaya University, Harar, Ethiopia

    Mesay Dechasa

  5. College of Health Sciences, Mattu University, Mattu, Ethiopia

    Gebiso Roba Debele

  6. College of Health Sciences, Oda Bultum University, Chiro, Ethiopia

    Habtamu Geremew

  7. College of Health Sciences, Salale University, Fitche, Ethiopia

    Fikadu Tolesa

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Contributions

Abraham Negash is a principal investigator. All authors contributed to the work equally whether it is at conception (A.N, ML), screening (AN, ML, TB), evaluation of finally included article (AS, EY, KN, Til. B and AT), verification of included article (MD, HF and GD), data extraction (ML, AN, AS, HD and FT), evaluation for quality assurance (AN, AS, and DA). Analysis (AN, DA and AB), and drafting (AN, DB and ML). All authors participated in critically reviewing the final draft and agreed to be accountable for all aspects of the work.

Corresponding author

Correspondence to Abraham Negash.

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The study was carried out following relevant guidelines and regulations of the Helsinki Declaration of medical research ethics as it included ethically approved articles only. Ethical approval for each included individual article works for this systematic review and meta-analysis.

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Supplementary Information

Additional file 1

: Table. Critical appraisal check list of quantitative studies of maternal near miss in Ethiopia 2023.

Additional file 2

: Sample of searching engines.

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Negash, A., Sertsu, A., Mengistu, D.A. et al. Prevalence and determinants of maternal near miss in Ethiopia: a systematic review and meta-analysis, 2015–2023. BMC Women's Health 23, 380 (2023). https://doi.org/10.1186/s12905-023-02523-9

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