Skip to main content
Erschienen in: BMC Pregnancy and Childbirth 1/2020

Open Access 01.12.2020 | Research article

Human Development Index of the maternal country of origin and its relationship with maternal near miss: A systematic review of the literature

verfasst von: Santiago García-Tizón Larroca, Francisco Amor Valera, Esther Ayuso Herrera, Ignacio Cueto Hernandez, Yolanda Cuñarro Lopez, Juan De Leon-Luis

Erschienen in: BMC Pregnancy and Childbirth | Ausgabe 1/2020

Abstract

Background

The reduction in maternal mortality worldwide has increased the interest in studying more frequent severe events such as maternal near miss. The Human Development Index is a sociodemographic country-specific variable that includes key human development indicators such as living a long and healthy life, acquiring knowledge, and enjoying a decent standard of living, allowing differentiation between countries. In a globalised environment, it is necessary to study whether the Human Development Index of each patient's country of origin can be associated with the maternal near-miss rate and thus classify the risk of maternal morbidity and mortality.

Methods

A systematic review of the literature published between 2008 and 2019 was conducted, including all articles that reported data about maternal near miss in their sample of pregnant women, in addition to describing the study countries of their sample population. The Human Development Index of the study country, the maternal near-miss rate, the maternal mortality rate, and other maternal-perinatal variables related to morbidity and mortality were used.

Results

After the systematic review, eighty two articles from over thirty countries were included, for a total of 3,699,697 live births, 37,191 near miss cases, and 4029 mortality cases. A statistically significant (p <0.05) inversely proportional relationship was observed between the Human Development Index of the study country and the maternal near-miss and mortality rates. The most common cause of maternal near miss was haemorrhage, with an overall rate of 38.5%, followed by hypertensive disorders of pregnancy (34.2%), sepsis (7.5%), and other undefined causes (20.9%).

Conclusions

The Human Development Index of the maternal country of origin is a sociodemographic variable allowing differentiation and classification of the risk of maternal mortality and near miss in pregnant women. The most common cause of maternal near miss published in the literature was haemorrhage.

Trial registration

PROSPERO ID: CRD 42019133464
Hinweise

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Abkürzungen
MM
Maternal mortality
MNM
Maternal near miss
HDI
Human development index
WHO
World Health Organization
GNI
Gross national income
UNDP
United Nations Development Programme
LB
Live births
NR
Non reported
GBD
Global Burden of Disease
BMI
Body mass index

Background

Worldwide, over 1500 women die every day due to complications of pregnancy or childbirth. It is possible that most of these deaths could be prevented if the women were in countries other than their countries of origin. Although the Millennium Development Goal of reducing maternal mortality (MM) by 75% between 1990 and 2015 has not been achieved globally, significant progress has been made; in many countries, maternal health has improved significantly, and the goals for 2030 are to achieve MM rates of less than 70 per 100,000 live births and to increase the proportion of births attended by skilled health personnel [1]. One of the Millennium Development Goals set in 2000 by the member countries of the United Nations is to improve the health of women through multiple interventions, such as promoting access to family planning services and emergency obstetric care by qualified and trained personnel. In this respect, women in low-income countries are especially vulnerable to dying from obstetric causes. The World Health Organization, through its “Global Strategy for Women´s, Children´s and Adolescents´ Health (2016-2030),” is analysing relevant indicators and scores to improve the survival of newborns and pregnant women. Although the world has made substantial progress on these two issues, the decline in maternal and neonatal mortality has recently slowed down. Moreover, in 2017-2019, the Quality of Care Network group supported by the WHO included more countries – such as Ethiopia, Ghana, India, Malawi, Nigeria, Tanzania and Uganda – on its agenda to complete the following tasks:
  • Accelerate action by adapting the WHO’s standards for improving the quality of maternal and newborn care in health facilities at the country level.
  • Foster learning and generate evidence on quality of care through a learning platform.
  • Develop and support institutions and mechanisms that will ensure accountability for quality of care by designing a national accountability framework.
Traditionally, the analysis of maternal deaths has been the approach of choice for evaluating women's health and the quality of obstetric care. However, due to the success of modern medicine, such deaths have become very rare in developed countries, which has led to an increased interest in analysing so-called “near miss” events. The World Health Organization defines a maternal near miss (MNM) as “a woman who nearly died but survived a complication that occurred during pregnancy, childbirth or within forty-two days of termination of pregnancy”. A MNM is also assumed to be a better indicator than MM alone when designing, monitoring, following-up and evaluating safe motherhood programmes [2]. Year after year, increasingly more authors are interested in publishing MNM events that occur in their countries, and it is necessary to analyse morbidity and mortality data over the past decade to compare situations in different countries.
Haemorrhage, hypertensive disorders of pregnancy, and infections stand out as the direct causes of more than 70% of both MNM and mortality. In all these cases, the lack of care or access to care, the high cost of health care or its poor quality, and the variation among different countries results in 1 million maternal orphans every year, and these children are also more likely to die during the years following their mother's death.
For years, gross national income per capita has been used to weigh differences among countries; however, in the 1990s, the WHO introduced the Human Development Index (HDI) as a sociodemographic variable to help differentiate countries, thus avoiding reliance on the purely economic value of each nation and trying to classify the world population in homogeneous groups through more comprehensive indicators.
This index has helped the WHO to establish different strategies to end preventable maternal morbidity and mortality; its use is increasingly widespread in the medical literature, where a very high HDI is typical of countries with more resources. Tuncalp is the first author to relate the HDI of the maternal country of origin to severe maternal outcomes such as MNM and MM with data from countries in Africa, Asia, Latin America, and the Middle East. That author describes a significant relationship between mothers from countries with medium and low HDIs; women in those countries are shown to have a risk of maternal complications that is 2-3 times higher than for women from countries with high HDIs [3].
Using the HDI of pregnant women from other countries and assessing the influence of HDI on maternal-perinatal health in our country, Spain, a previous study conducted by our team [4] observed an increased risk of adverse maternal-perinatal events in pregnant women from low-HDI countries compared to women originating from countries with higher HDIs. Similarly, Luque-Fernandez et al. [5], analysing the trend of stillbirth in Spain, showed an increased risk of stillbirth, approximately three times higher, in pregnant women from low-HDI countries. For both authors, incorporating HDI improves the characterisation of the maternal socio-economic level by introducing the HDI of the maternal country of origin and maternal educational attainment to population analysis, producing a fuller analysis compared to those studies that only include the country of origin of immigrant pregnant women.
In this study, we will consider the HDI of the place of publication (as a proxy measure like that used in the study on immigration) and determine the relationship with adverse maternal-perinatal outcomes.
The aim of this study is to conduct a systematic review of the articles published over the last decade reporting severe acute maternal morbidity. We use as a reference the HDI of the country where the study was conducted—which directly reflects the HDI of its population of pregnant women—to analyse its relationship with relevant adverse maternal-perinatal outcomes during pregnancy, childbirth, and the postpartum period, such as MNM and MM.

Methods

Protocol, eligibility criteria, information sources and search strategies

This review was performed according to an a-priori-designed protocol recommended for systematic reviews. PRISMA [6] and MOOSE guidelines were followed [7]. The study was registered in the PROSPERO database (registration number: CRD 42019133464). The systematic literature search was conducted in two electronic databases, PubMed/MEDLINE and EMBASE, utilising combinations of the relevant medical subjects by MeSH terms with the following keywords: “near miss” or “morbidity” and “pregnancy” or “mothers” or “pregnancy outcome”. The search period was between 17/02/2008 and 17/02/2019. A reference database (EndNote X7, Thomson Reuters) was used to incorporate all references.
The inclusion criteria were as follows:
  • studies published between 17/02/2008 and 17/02/2019;
  • studies conducted with humans;
  • studies in English, both the abstract and the main text; and
  • studies that included MNM analysis in their study population.
The exclusion criteria were as follows:
  • studies with scarce information about the study population, such as country of origin, or studies investigating specific ethnic, racial, or immigrant groups;
  • published articles that did not report data on MNM or those on maternal morbidity events not meeting MNM criteria according to the WHO;
  • systematic reviews, expert opinions, and intervention studies without quantitative data about the MNM rate; and
  • studies conducted on the same patient cohort. In these cases, we selected the most up-to-date patient cohorts and excluded secondary analysis studies on the same sample.

Study selection

Titles and abstracts of the search results were screened by two researchers independently (SGTL and FAV). If the title and abstract did not provide useful information for the review or was irrelevant, the articles were eliminated from the analysis. Potentially eligible studies were assessed in full-text format. Any disagreement on the eligibility of studies was resolved through discussion and joint assessment until consensus was reached between the two researchers.

Data collection and data items

Data were extracted using an appraised extraction form. Each reviewer collected the data independently, and discrepancies between them were resolved by the two authors checking the study against the form. The review authors were not blinded to the journal or author details. Extracted data included the name of the first author and year of publication, first and last year of the study, study period, country or countries where the study was conducted, HDI group to which the study country belongs, and the HDI score of the study country.
The HDI is a summary measure of a country’s average level of achievement in the following major dimensions of human development: living a long and healthy life, being educated, and having a decent standard of living. Life expectancy serves as an indicator of the health dimension; standard of living is measured in terms of gross national income per capita; and education level is evaluated as the average number of years of schooling among adults aged twenty-five years and older and expected number of years of schooling among children [8].
A country obtains a higher HDI score when its population has a higher life expectancy, education level, and gross national income (GNI) per capita; these scores are reported within the annual Human Development Report published by the United Nations Development Programme (UNDP) [9]. The UNDP divides countries into four broad categories of human development: group 1 (very high HDI), group 2 (high HDI), group 3 (medium HDI), and group 4 (low HDI) based on the numerical score obtained, with a minimum of 0 and a maximum of 1.
Other maternal-perinatal variables included in the study were type of study (single- or multi-centre), study design, total number of live births (LBs), number of MNM events in the study, rate of MNM/1000 LBs, number of maternal mortality events, rate of MM/100,000 LBs, percentage of MNM due to haemorrhage, percentage of MNM due to hypertensive disorders of pregnancy, percentage of MNM due to sepsis, percentage of MNM due to other causes, MNM in the immigrant population, MNM by ethnic group, maternal age at MNM, percentage of primiparous mothers in the MNM group, parity in MNM, percentage of births <37 weeks gestation in the MNM group, caesarean section rate in the MNM group, and neonatal near miss.
In the case of multicountry studies, the average HDI score given by the HDI scores of all included countries was calculated.
After data collection, the data were ordered according to the publication year.

Risk of bias assessment and statistical analysis

The risk of bias was assessed independently by both authors, who determined the adequacy of compliance with the inclusion criteria. The items assessed were correct description of MNM cases, complete reporting of proportion and type of near miss in the case group, and adequate description of the country or countries where the study was carried out. We tried to choose strict eligibility criteria to achieve a good number of studies that were as homogeneous as possible and thereby extract concrete and valid conclusions.
The quality of the evidence of the studies included was assessed according to the Grade of Evidence Working Group Criteria [10].
Statistical analyses were carried out using STATA, version 13.1 (Stata Corp., College Station, TX, USA) in its default settings. The results are expressed as rates (%) for dichotomous variables, and we calculated 95% confidence intervals (95% CIs). We tried to perform a quantitative synthesis with pooled relative risks and 95% confidence intervals (95% CI), but a meta-analysis was not feasible given the lack of a control group and the heterogeneity of the available studies.

Results

Figure 1 describes the workflow process. As shown, the initial search identified 4842 articles in the databases. After screening and applying the eligibility and exclusion criteria in the final phase of the records, eighty-two articles were selected. A total of 3,699,697 LBs, 37,191 near miss cases and 4029 mortality cases were reported, representing the population analysed in this systematic review.
Table 1 describes the results obtained in each study for the different variables analysed in the review. Over 90% of the studies were led by different authors; among those who led in publishing, the author who published the most studies in the period included in this analysis of MNM was Jayaratnam, with four. Of all the articles, sixty-two (75.6%) have been published since 2014, and the study by Okusanya et al. [53] (reference) included the longest period of data collection, at twenty years. Over 70% of the studies had a follow-up design with retrospective data collection/analysis.
Table 1
Summary of all the studies included in the review with their results
Authors
Publication Year
First Year
Last Year
Period Years
Country
HDI Group
HDI score
Study Type
Study Design
Total live births
MNM cases
MNM rate
MM cases
MM rate
MNM Haemorrhage %
MNM Hypertension %
MNM Sepsis %
MNM Others %
MNM immigrants
MNM ethnicity
MNM Maternal age
G1 in MNM %
Parity in MNM
GA < 37 weeks in MNM %
Caesarean rate in MNM %
Neonatal near miss
Adisasmita et al. [11]
2008
2003
2004
1
Indonesia
3
0.694
multi-centre
Retrospective longitudinal
5669
763
134.6
127
2240
40.6
32.3
NR
16.3
NR
NR
NR
NR
NR
NR
NR
NR
Driul et al. [12]
2008
1998
2008
10
Italy
1
0.88
single-centre
Retrospective longitudinal
18936
95
5.0
1
5.4
NR
NR
NR
NR
NR
NR
NR
NR
 
NR
NR
NR
Roost et al. [13]
2009
2006
2007
1
Bolivia
3
0.693
single-centre
Retrospective longitudinal
8136
401
49.3
15
187.0
48
46
NR
NR
NR
NR
NR
NR
 
NR
NR
NR
Almerie et al. [14]
2010
2006
2008
2
Syria
4
0.536
single-centre
Retrospective case-control
28025
901
32.1
15
54.8
34
52
2.8
NR
NR
NR
Mean 28.4 years
28
P0 28%; P1-3 40.8%; P≥4 (31.1%) in NM
NR
54%
NR
Shrestha et al. [15]
2010
2009
2009
1
Nepal
3
0.574
single-centre
Retrospective longitudinal
1562
36
23.0
5
324.0
41.6
27.7
19.4
8.3
NR
NR
Mean 27 years
30.5
G1 NM= 30.5%
NR
NR
2.77% shoulder dystocia
Souza et al. [16]
2010
2005
2005
1
Multicountry
 
0.745
multi-centre
Retrospective longitudinal
97095
2964
34.0
25
26
NR
NR
NR
NR
NR
NR
NR
NR
 
NR
NR
NR
Ali et al. [17]
2011
2008
2010
2
Sudan
4
0.502
single-centre
Retrospective cohort
9578
205
21.4
41
432.0
40.8
18
21.5
NR
NR
NR
Mean 25.5 years
NR
Mean 3.01 in NM
NR
NR
NR
Amaral et al. [18]
2011
2005
2005
1
Brazil
2
0.759
single-centre
Retrospective longitudinal
4491
95
21.1
4
89
17.9
57.8
14.3
17.8
NR
NR
NR
NR
 
NR
NR
60 perinatal deaths
Donati et al. [19]
2011
2004
2005
1
Italy
1
0.88
multi-centre
Retrospective longitudinal
539382
1259
2.3
NR
NR
40
29
3
25
Immigrants OR 3
NR
≥ 35 years 2.8/1000
NR
Not specified
NR
70%
NR
Jayaratnam et al. [20]
2011
2009
2010
1
Australia
1
0.939
single-centre
Prospective longitudinal
NR
17
6.0
NR
NR
40
12
NR
NR
NR
NR
NR
NR
Not specified
NR
NR
NR
Kaye et al. [21]
2011
2010
2010
1
Uganda
4
0.516
single-centre
Prospective cohort
140
21
150.0
NR
NR
NR
NR
NR
NR
NR
NR
NR
NR
Mean 3.3
NR
67.90%
NR
Lobato et al. [22]
2012
2008
2008
1
Brazil
2
0.759
single-centre
Retrospective review
1163
27
23.2
NR
NR
4
80
NR
NR
NR
NR
NR
NR
Not specified
NR
NR
NR
Souza et al. [23]
2012
2009
2010
1
Brazil
2
0.759
multi-centre
Retrospective longitudinal
82388
770
9.3
140
170.0
NR
NR
NR
NR
NR
NR
NR
NR
Not specified
NR
NR
NR
Adeoye et al. [24]
2013
2006
2007
1
Nigeria
4
0.532
multi-centre
Prospective case-control
375
75
200.0
NR
NR
45.3
37.3
18.6
NR
NR
NR
>40 years 5.3%
NR
1-2 (61.3%); 3-4 (25.3%); 5 or more (13.4%) in NM
NR
NR
NR
Jabir et al. [25]
2013
2010
2010
1
Iraq
3
0.685
multi-centre
Cross-sectional
25472
129
5.1
16
62.8
65.9
21
NR
NR
NR
NR
NR
NR
Not specified
NR
67.83%
NR
Karolinski et al. [26]
2013
2008
2009
1
Argentina
1
0.825
multi-centre
Cross-sectional
65033
518
8.0
34
52.3
36.7
31.1
4.4
15.3
NR
NR
>35 years in 21.8%, <20 years in 16.1%
26.6
26.6% P0; 37.5% >P3 in NM
NR
80.1
NR
Nelissen et al. [27]
2013
2009
2011
2
Tanzania
4
0.538
single-centre
Prospective longitudinal
9136
216
23.6
32
350.3
NR
NR
NR
NR
NR
NR
NR
NR
Not specified
NR
NR
NR
Roopa et al. [28]
2013
2011
2012
1
India
3
0.64
single-centre
Retrospective longitudinal
7390
131
17.8
23
313.0
44.2
23.6
16
NR
NR
NR
NR
58
 
NR
NR
NR
Shen et al. [29]
2013
2008
2012
4
China
2
0.752
single-centre
Retrospective longitudinal
18104
69
3.8
3
16.0
36.1
31.7
NR
NR
aOR in Immigrants 2.34 (95% CI, 0.45–24.9)
NR
Mean 28 ± 5 years
76.8
G1 76.8% in NM
NR
89.9
40% admission to neonatal ICU
Tuncalp et al. [3]
2013
2010
2011
1
Multicountry
 
0.649
multi-centre
Retrospective longitudinal
314623
1667
5.3
360
114.4
NR
NR
NR
NR
MNM by groups: 0.8% HDI 1-2, 0.5% HDI 3, 1.1% HDI 4
NR
≥35 years 10.6%
NR
G1 37.3% of the total
NR
NR
NR
Wahlberg et al. [30]
2013
1998
2007
9
Sweden
1
0.933
multi-centre
Retrospective longitudinal
914474
2655
2.9
22
2.4
NR
NR
NR
NR
Specified by groups of origin
NR
Specified by groups of origin
NR
Specified by groups of origin
NR
NR
NR
Abalos et al. [31]
2014
2004
2008
4
Multicountry
 
0.655
multi-centre
Cross-sectional
313030
1227
3.9
204
65.2
NR
NR
NR
NR
NR
NR
NR
NR
P2-4 51.9% in no preeclampsia group; 45.6 % in preeclampsia; P1 61.6% in eclampsia group
NR
NR
NR
David et al. [32]
2014
2008
2008
1
Mozambique
4
0.437
multi-centre
Cross-sectional
27916
564
20.2
71
254.0
58
35.5
3.9
NR
NR
NR
14-19 (23.6%), 20-24 (27%), 25-29 (26.2%), 30-34 (16.7%), ≥35 (6.6%)
33.9
0 (33.9%); 1 (20.47%); 2-4 (40.6%); ≥5 (4.8%) in NM
NR
56.6
NR
Galvao et al. [33]
2014
2011
2012
1
Brazil
2
0.759
multi-centre
Cross-sectional/Nested case-control
16243
77
4.7
NR
NR
NR
NR
NR
NR
NR
84.4% non white; 15.6% white
< 35 years 73.9%; ≥35 years 26.1%
NR
Not specified
NR
74.5
NR
Litorp et al. [34]
2014
2012
2012
1
Tanzania
4
0.538
multi-centre
Cross-sectional
13121
467
35.6
77
587.0
13
42
NR
NR
NR
NR
Mean 26 years
43
P0 (43%); 1-4 (50%); >4(3.9%); in NM
NR
35
NR
Luexay et al. [35]
2014
2011
2011
1
Laos
3
0.601
multi-centre
Retrospective longitudinal
1215
11
9.1
2
178.0
NR
NR
NR
NR
NR
Lao (70.6%); tribes (18.3%)
Mean 24.4 years
43
G1 43% of the total
12.8
NR
NR
Lumbiganon et al. [36]
2014
2015
2011
1
Multicountry
 
-
multi-centre
Cross-sectional
314623
2365
7.5
NR
NR
NR
8.1
28.1
NR
NR
NR
NR
NR
Not specified
NR
NR
NR
Mazhar et al. [37]
2014
2011
2011
1
Pakistan
4
0.562
multi-centre
Retrospective longitudinal
13175
94
7.1
38
299.0
48.5
25.8
NR
NR
NR
NR
20-40 years 96.2 %
37
G1 37% in NM
47
49
NR
Pacheco et al. [38]
2014
2011
2011
1
Brazil
2
0.759
single-centre
Retrospective longitudinal
2291
24
10.5
3
130.9
NR
NR
NR
NR
NR
NR
NR
NR
Not specified
NR
29.7
NR
Pandey et al. [39]
2014
2011
2012
1
India
3
0.64
single-centre
Retrospective longitudinal
6357
633
120.0
247
4684.0
45.6
24.2
7.5
8.7
NR
NR
NR
NR
 
NR
NR
NR
Rocha Filho et al. [40]
2014
2009
2010
1
Brazil
2
0.759
multi-centre
Retrospective longitudinal
82144
770
9.4
140
170.4
43.5
NR
NR
56.5
NR
43.1% white; 56.9% non white
≥40 years 7%
38.9
G1 38.9% in NM
72.3
89.5
NR
Assarag et al. [41]
2015
2012
2012
1
Morocco
3
0.667
multi-centre
Retrospective case-control
299
80
267.6
NR
NR
39
45
10
5
NR
NR
Mean 29.2 years
50
P1 (50%); 2-3 (39%); ≥4 (11%) in NM
NR
66
NR
Bashour et al. [42]
2015
2011
2015
4
Multicountry (Egypt, Lebanon, Palestine and Syria)
 
0.616
multi-centre
Cross-sectional
9063
71
7.8
6
66.2
100
15.4
NR
30.9
NR
NR
NR
NR
(Egypt 40.7%) 3-4; (Lebanon 60%) 0; (Palestine 43.8%) >5; (Syria 27.8%) 0, 1-2, 3-4
NR
Egypt 65.6%; Lebanon 100%; Palestine 50%; Syria 61.1%
NR
Cecatti et al. [43]
2015
2009
2010
1
Brazil
2
0.759
multi-centre
Cross-sectional
9555
770
80.6
16
170.0
40.5
45.3
5.7
NR
NR
NR
NR
NR
Not specified
NR
NR
NR
Hassan et al. [44]
2015
2011
2012
1
Palestine
 
-
single-centre
Prospective longitudinal
1558
15
9.6
NR
NR
16.4
4.2
2.5
26.9
NR
NR
NR
16.2
G1= 253 (16.2%) of the total
NR
2420.00%
0.6% admision UCI, 14 perinatal deaths
Kulkarni et al. [45]
2015
2012
2013
1
India
3
0.64
multi-centre
Prospective longitudinal
19176
884
46.1
94
490.2
7.7
53.4
NR
NR
NR
NR
Mean 25.8 years
41
41% G1 in NM
NR
NR
NR
Madeiro et al. [46]
2015
2012
2013
1
Brazil
2
0.759
single-centre
Cross-sectional / Prospective longitudinal
5841
56
9.6
10
171.2
100
86.1
NR
NR
NR
NR
<20 years 25.8%
NR
≥4 13.6% in NM
54.8
87.5
NR
Naderi et al. [47]
2015
2013
2013
1
Iran
2
0.798
multi-centre
Retrospective longitudinal
19908
501
25.2
2
10
46.1
31.9
NR
15.2
NR
NR
NR
41.5
 
NR
54.2
NR
Oladapo et al. [48]
2015
2012
2013
1
Nigeria
4
0.532
multi-centre
Prospective longitudinal
91724
1451
15.8
998
1088.0
49
20.5
2.5
NR
NR
NR
NR
NR
Not specified
NR
NR
perinatal deaths 60.5/1000 live births
Oliveira et al. [49]
2015
2006
2007
1
Brazil
2
0.759
single-centre
Retrospective longitudinal
19940
255
12.8
56
280.8
53.7
62.7
NR
NR
NR
57.3% mixed, 17.6% white, 7.1% black
≥35 years 11.8%
44.7
G1 44.7% in NM
54.5
76.4
NR
Rulisa et al. [50]
2015
2011
2012
1
Rwanda
4
0.524
single-centre
Retrospective longitudinal
1739
192
110.4
50
2875.2
19.3
28.6
30.2
NR
NR
NR
≥35 years 15.6%
NR
Not specified
45
45.5
NR
Sangeeta et al. [51]
2015
2012
2013
1
India
3
0.64
single-centre
Retrospective longitudinal
6892
27
4.0
8
116
40.7
26
7.4
NR
NR
NR
NR
NR
 
NR
NR
NR
Soma-Pillay et al. [52]
2015
2013
2014
1
South Africa
3
0.699
multi-centre
Retrospective longitudinal
26614
136
5.1
19
71.4
37.5
32.4
10.3
NR
NR
NR
NR
29
 
NR
NR
NR
Okusanya et al. [53]
2016
1993
2013
20
Nigeria
4
0.532
single-centre
Retrospective cross-sectional
30553
116
3.8
NR
NR
NR
NR
NR
NR
NR
NR
20-24 n=3; 25-29 n=31; 30-34 n=40; 35-39 n=33; 40-44 n=9
NR
0 n=6; 1 n=20 ; 2 n=27; 3 n=35; 4 n=14; 5 n=14
NR
NR
NR
de Mucio et al. [54]
2016
2013
2013
1
Latin America (12 countries)
 
0.723
multi-centre
Cross-sectional
3196
37
11.6
NR
NR
NR
NR
NR
NR
NR
NR
NR
NR
Not specified
13.3
NR
NR
Domingues et al. [55]
2016
2011
2012
1
Brazil
2
0.759
multi-centre
Retrospective case-control
23984
244
10.2
NR
NR
NR
NR
NR
NR
NR
56.1% mixed; 33.8% white; 8.6% black; 1.1% asian; 0.4% indigenous of the total
NR
46.9
P0 46.9%; P1 29.4%; 2-3 18.8%; >4 4.9%
NR
43.7
NR
El Ghardallou et al. [56]
2016
2012
2012
1
Tunisia
2
0.735
single-centre
Retrospective longitudinal
9957
58
5.8
1
10.0
74.1
20.7
NR
25.9
NR
NR
Mean 32 ± 5.2 years, >39 years 12.1%
36.2
G1= 36.2% in NM
NR
66.7
15.4% neonatal death, 48.5% (n=16) ICU admission
Jayaratnam et al. [57]
2016
2014
2015
1
Australia
1
0.939
single-centre
Prospective longitudinal
2080
10
4.8
NR
4.8
NR
NR
NR
NR
NR
NR
NR
NR
Not specified
NR
NR
No
Kalisa et al. [58]
2016
2014
2014
1
Rwanda
4
0.524
single-centre
Prospective cohort
3979
86
21.6
13
325.0
57
31.4
NR
NR
NR
NR
NR
NR
Not specified
NR
43
No
Lima et al. [59]
2016
2009
2010
1
Brazil
2
0.759
multi-centre
Retrospective longitudinal
4617
50
10.8
10
216
NR
NR
NR
NR
NR
NR
NR
54.3
 
NR
NR
NR
Mohammadi et al. [60]
2016
2012
2014
2
Iran
2
0.798
multi-centre
Retrospective case-control
12965
82
6.3
12
92.6
35
32
7
NR
NR
NR
≥35 years n=124
23
G1 n=495 (23% G1 in NM)
48
81
204 perinatal deaths
Nakimuli et al. [61]
2016
2013
2014
1
Uganda
4
0.516
multi-centre
Prospective cohort
NR
695
8.4
130
503.0
26.5
22
11.8
NR
NR
NR
≥25 years 55.7%
26.5
G1 n=184 (26.5%) of NM
NR
78%
NR
Nansubuga et al. [62]
2016
2013
2013
1
Uganda
4
0.516
single-centre
Retrospective longitudinal
1557
434
278.7
NR
NR
55
0.2
3.5
4.1
NR
NR
NR
NR
Not specified
NR
NR
NR
Norhayati et al. [63]
2016
2014
2014
1
Malaysia
2
0.802
multi-centre
Retrospective longitudinal
21579
47
2.2
2
9.3
80.9
21.3
NR
38.3
NR
NR
Mean 33.2(6.03) years, >35years 42.6%
NR
Not specified
NR
63.80%
19.1% perinatal death , 63.2% admitted to neonatal ICU
Parmar et al. [64]
2016
2012
2012
1
India
3
0.64
single-centre
Retrospective longitudinal
1929
46
23.9
18
933.0
NR
NR
NR
NR
NR
NR
NR
NR
 
42
NR
39% perinatal death
Rathod et al. [65]
2016
2011
2013
2
India
3
0.64
multi-centre
Retrospective longitudinal
21992
161
7.6
66
300
26.7
11.8
11.5
NR
NR
NR
NR
NR
 
NR
NR
NR
Tanimia et al. [66]
2016
2012
2013
1
Papua New Guinea
4
0.544
single-centre
Prospective longitudinal
13338
122
9.1
9
67.5
38
32
7.4
NR
NR
NR
NR
NR
NR
NR
NR
NR
Bolnga et al. [67]
2017
2014
2016
2
Papua New Guinea
4
0.544
single-centre
Prospective longitudinal
6019
153
25.4
10
166.0
42.5
22.2
16.3
3.3
NR
NR
NR
NR
NR
NR
26.80%
NR
Goldenberg et al. [68]
2017
2014
2016
2
Multicountry (Congo, Guatemala, India, Kenia, Pakistan and Zambia)
 
0.593
multi-centre
Prospective longitudinal
122707
4866
39.7
190
155.0
79
42
75
NR
NR
NR
NR
NR
NR
NR
NR
NR
Herklots et al. [69]
2017
2016
2016
1
Tanzania
4
0.538
single-centre
Cross-sectional
4125
37
6.7
28
678.8
29.7
24.3
10.8
2.7
NR
NR
<20 years 12.3%; 20-35 years 66.2%; >35 years 21.5%
20
P0 20%; P1-4 60%; P>4 20%
NR
63
NR
Khan et al. [70]
2017
2009
2011
2
India
3
0.64
single-centre
Retrospective cross-sectional
20556
302
14.7
67
325.0
63.6
20.5
2.6
NR
NR
NR
Mean 26.7 years
36.4
G1 (36.4%); G2-3 (50%); G4-6 (13.6%)
NR
64.2
NR
Kiruja et al. [71]
2017
2015
2015
1
Somalia
4
-
single-centre
Retrospective longitudinal
1385
120
86.6
18
1328.0
36.7
55
2.5
1.7
NR
NR
Mean 29.5 years
2.5
≥ 7 (29.2%); 5-6 (10.8%); 2-4 (29.2%); 1 (28.3%); 0 (2.5%)
NR
NR
21.7% perinatal death
Liyew et al. [72]
2017
2015
2016
1
Ethiopia
4
0.463
multi-centre
Cross-sectional
29697
238
8.0
NR
NR
38
53
1
NR
NR
NR
NR
NR
NR
NR
NR
NR
Mawarti et al. [73]
2017
2011
2012
1
Indonesia
3
0.694
single-centre
Retrospective longitudinal
3300
86
26.0
29
879
5.81
95
4.5
NR
NR
NR
NR
50
NR
NR
NR
NR
Mbachu et al. [74]
2017
2015
2015
1
Nigeria
4
0.532
single-centre
Retrospective longitudinal
262
52
198.5
5
1908.0
24.6
28.1
1.8
NR
NR
NR
NR
NR
NR
NR
NR
NR
Mekango et al. [75]
2017
2016
2016
1
Ethiopia
4
0.463
multi-centre
Retrospective longitudinal
308
103
334.4
NR
NR
44.7
38.8
9.7
NR
NR
NR
≥40 years n=88
NR
G1 N=5
54.4
NR
NR
Sayinzoga et al. [76]
2017
2016
2016
1
Rwanda
4
0.524
multi-centre
Prospective case-control
5577
201
36.0
13
233.1
22.9
8.5
7.5
5
NR
NR
≥35 years 60%
60
G1 60%
34
52
46.1% perinatal death
Witteveen et al. [77]
2017
   
Multicountry (Netherlands, Tanzania, Malawi)
 
0.648
multi-centre
Prospective cohort
NR
2308
NR
126
NR
NR
NR
NR
NR
MNM% specified by country of origin
NR
Specified by country
NR
Specified by country
NR
NR
NR
Awowole et al. [78]
2018
2007
2016
9
Nigeria
4
0.532
single-centre
Retrospective longitudinal
11242
43
3.8
NR
NR
18
40
12
NR
NR
NR
Mean 29.2 years
NR
Mean 2
NR
NR
NR
Benimana et al. [79]
2018
2015
2015
1
Rwanda
4
0.524
single-centre
Retrospective longitudinal
NR
98
NR
NR
NR
23.1
21.5
27.3
NR
NR
NR
16-24years (28.9%); 25-34 years (52.1%); ≥35 years (19%)
17.4
0 (17.4%); 1-2 (53.7%); ≥3 (28.9%)
NR
NR
NR
Chikadaya et al. [80]
2018
2016
2016
1
Zimbabwe
4
0.535
single-centre
Prospective longitudinal
11871
110
9.3
13
109.5
31.8
28.2
NR
20
NR
NR
NR
NR
NR
NR
NR
NR
Iwuh et al. [81]
2018
2014
2014
1
South Africa
3
0.699
multi-centre
Retrospective longitudinal
19222
112
5.8
13
67.6
33.9
44.6
11.6
NR
NR
NR
<18 years 3.6%; 18-34 years 84.8%; ≥35 years 11.6%
41.1
P0 41.1%; P1-4 58%; P5 0.9%
NR
NR
NR
Jayaratnam et al. [82]
2018
2014
2015
1
Australia
1
0.939
single-centre
Prospective longitudinal
2773
19
7.0
NR
NR
NR
NR
NR
NR
NR
NR
NR
NR
NR
NR
NR
NR
Liyew et al. [83]
2018
2015
2016
1
Ethiopia
4
0.463
multi-centre
Prospective cohort
828
207
250.0
NR
NR
NR
NR
NR
NR
NR
NR
NR
NR
P 0-2 (79.2%); P3-4 (15.5%); P>5 (5.3%)
40.6
NR
29.5% perinatal death
Oliveira Neto et al. [84]
2018
2013
2015
2
Brazil
2
0.759
single-centre
Retrospective longitudinal
8065
60
7.4
5
62
64.5
25.8
6.5
NR
NR
NR
>35 years 75%
NR
NR
NR
74
NR
Tura et al. [85]
2018
2016
2017
1
Ethiopia
4
0.463
single-centre
Retrospective longitudinal
7404
594
80.2
28
378
36
45.6
21.2
NR
NR
NR
NR
NR
NR
 
NR
NR
Woldeyes et al. [86]
2018
2015
2015
1
Ethiopia
4
0.463
single-centre
Retrospective longitudinal
2737
138
50.4
24
877.0
22.5
21
10.1
5.8
NR
NR
NR
41.6
NR
NR
25.7
NR
Yang et al. [87]
2018
2012
2015
3
China
2
0.752
single-centre
Retrospective longitudinal
14105
265
18.8
10
70.9
36.9
49
NR
NR
NR
NR
≥35 years 2.54%
22.3
G1-2 2.33%
5.36
NR
35 perinatal deaths
Herklots et al. [88]
2019
2017
2018
1
Tanzania
4
0.538
single-centre
Prospective longitudinal
26842
256
9.5
79
294
NR
NR
NR
NR
NR
NR
NR
NR
NR
NR
NR
NR
Jayaratnam et al. [89]
2019
2015
2016
1
Timor
3
0.625
single-centre
Prospective longitudinal
4529
39
8.0
30
662
25
25
NR
NR
NR
NR
NR
50
NR
NR
NR
NR
Oppong et al. [90]
2019
2015
2015
1
Ghana
3
0.592
multi-centre
Retrospective longitudinal
8433
288
34.2
62
735
12.2
41
11.1
NR
NR
NR
NR
NR
NR
NR
NR
NR
Zanardi et al. [91]
2019
2009
2010
1
Brazil
2
0.759
multi-centre
Retrospective longitudinal
82388
624
7.6
113
137.1
NR
NR
NR
NR
NR
NR
NR
37
NR
63%
73.9
14.2% perinatal death
Looking at single-country studies, over thirty-three countries were represented, and seven studies were conducted with populations from several countries; Brazil published more studies than any other country, with thirteen (15.4%), followed by India, with six (7.1%), and Nigeria and Ethiopia, with five each (6%). Regarding the number of studies classified by HDI group, seven belonged to group 1, nineteen to group 2, eighteen to group 3, and twenty-nine to group 4. In only three studies, the HDI score could not be obtained because of the lack of data provided regarding the study country.
Regarding the MM rate, the median was 175 deaths per 100,000/LBs, with six studies reporting a rate above 1000; in relation to the MNM rate, the median was 11 events per 1000 LBs, with nine studies reporting a rate above 100. Regarding MNM, the average of the overall percentage of publications reported the cause to be haemorrhage (38.5%), hypertensive disorders of pregnancy (34.2%), sepsis (7.5%), and other causes (20.9%).
In relation to gestational data, the mean percentage of primiparous women in the total cases of MNM published was 37%. The mean percentage of premature births in the MNM cases was 38%. The mean percentage of caesarean sections in the MNM cases reported in the twenty-eight articles that reported these data was 57.2%.
Of all the articles included in the review, only sixteen presented data on adverse neonatal outcomes; the most commonly described complication was perinatal death, reported in twelve articles.
Finally, 4/82 articles referred to the differential analysis of near-miss ratios in immigrants, and 16/82 provided data on perinatal mortality or morbidity (near miss) in their results.
Figures 2 and 3 show the exponential trend relationship between the HDI score of the study population and the MNM and MM rates. In both, an inversely proportional relationship between the two variables was shown; higher MNM rates and higher MM rates were observed for study countries with lower HDI scores, significantly in both cases:
  • Average rate of MNM/country = 331.71e-4.572country HDI per 1000 live births (R2 = 0.2251; p = 0.001)
  • Average rate of MM/country = 47290e-8.663country HDI n per 100,000 live births (R2 = 0.4304; p = 0.038)
In addition, to provide more detail in these figures, Tables 2 and 3 show the MNM and MM rates, respectively, weighted by the number of LBs according to the HDI group of the study population. The articles whose study population belonged to HDI group 1 showed the lowest MNM and MM rates compared to the rest of the groups. Those whose study population belonged to HDI group 3 had the highest MNM rate, 7.6 times higher than that of HDI group 1. Studies whose population was classified as HDI group 4 had the highest MM rate, 98.4 times higher than that of HDI group 1. It should be noted in these tables that the MNM rate for group 4 was lower than that for HDI group 3.
Table 2
MNM rate weighted by the number of LBs according to the HDI group
HDI group
Sum of MNM
Sum of livebirths
MNM rate per 1000 livebirths
1
4556
1542678
2.95
2
4844
439728
11.01
3
4265
188743
22.59
4
7196
352653
20.40
Total
20861
2523802
8.26
Table 3
MM rate weighted by the number of LBs according to the HDI group
HDI group
Sum of MM
Sum of livebirths
MM rate per 100,000 live births
1
57
998443
5.7
2
527
398338
132.4
3
841
188444
446.3
4
1563
277953
562.2
Total
2988
1863178
160.4
The proportion of each cause of MNM published in each study is shown in Figure 4. This same figure reflects the overall proportions of each type of MNM. The most common cause of MNM in the set of studies selected in this review was haemorrhage, occurring in 38.5% (95% CI, 37.7-39.2) of all cases.
Concerning haemorrhagic causes of MNM, the study by Lobato et al. [22] reported the lowest proportion of this complication, with 3.7%, compared to the study by Madeiro et al. [46], which reported the highest percentage of haemorrhagic causes of MNM, 100% of total cases in their sample.
Regarding hypertensive disorders as a cause of MNM, the studies by Lobato et al. [22], Madeiro et al. [46], and Mawarti et al. [73] predominantly include populations of pregnant women from countries in HDI groups 2 and 3, with proportions of MNM greater than 80% out of all cases in their respective samples.
Overall, the less common cause of MNM was infection/sepsis, at 7.5%, although the studies by Rulisa et al. [50] and Benimana et al. [79] observed this cause to be responsible for 30.2% and 27.6%, respectively, of total MNM cases. Both studies were conducted in countries belonging to HDI group 4. A total of 83.7% of studies that reported infectious causes of MNM were conducted in countries classified as HDI groups 3 and 4.

Discussion

This systematic review of the literature selected eighty-two studies that included over three million live births, over 37,000 MNM cases, and just over 4,000 MM events over the past eleven years, representing over fifty countries.
To our knowledge, this is the most up-to-date review of MNM as an adverse perinatal outcome, and the only one in which the country of origin of the study population has been analysed. In addition, it is the first review that analyses these results in relation to the HDI of each country of publication.
As shown in Table 1, increasingly more studies are publishing MNM results as an indicator for monitoring the quality of maternal health and maternal care. These data will be a valuable contribution to taking necessary action to improve the quality of maternal care.

MNM as an analysis variable of maternal morbidity and mortality and the importance of the country of origin

Despite the differences in MM between countries, these events are increasingly infrequent and related to an LB rate on the order of 100,000. As stated above, MNM data collection is increasingly necessary; most of the studies included have been published since 2014, showing the growing interest in considering this variable.
Brazil published the most studies in this period, followed by India, Nigeria and Ethiopia; most studies were published in low-HDI countries, leading to publication bias because, as this study shows, cases of severe maternal morbidity are more prevalent in more disadvantaged countries.
As highlighted in Table 1, only four studies underline the relationship between MNM and migration when analysing maternal origin, where perinatal outcomes were more unfavourable in immigrant groups. However, many studies analysed this variable for MM. In a systematic review that included thirteen studies involving over forty-two million women and 4995 maternal deaths, immigrant women had twice the risk of this complication over native women in Western Europe [92].
As in the results obtained in those four studies regarding both MNM and MM, our results highlight a significant relationship between the HDI of the place of publication and adverse maternal-perinatal outcomes. These results are in line with previous studies by Tuncalp et al. [3] and Luque-Fernandez et al. [5] and those reported previously by our team.
These studies highlight the importance of classifying maternal risk by considering not only economic data but also other relevant aspects of human development and capacity for survival in each country, or, in the case of immigrants, their country of origin, specifically in the case of pregnant women from low-income countries where monitoring of pregnancy and childbirth occurs in their countries of origin and when a pregnant woman becomes an immigrant in a country with higher resources. Wahlberg et al. [30] observed, in a study conducted in Sweden that included 914,474 births and 2655 MNM cases, that women from low-income countries had a significant 2.3 times greater risk than native women of suffering from severe morbidity events. This study revealed some hypotheses about plausible mechanisms by which this relationship occurred, such as a breach of previous social networks among immigrant women, low socio-economic status, poor access to health and prenatal care, and communication problems resulting from suboptimal language acquisition.
Urquia et al. [93] analysed 1,252,543 births in Ontario hospitals between 2002 and 2012 and observed heterogeneity that included severe maternal morbidity rates according to the world regions of origin of pregnant women. Overall, they found no significant differences in the risk of such pregnancy complications between native and immigrant women; however, in women from East Asia, such as Vietnam and the Philippines, an increased risk of severe maternal morbidity was observed among these patients in Canadian hospitals.
Finally, it is necessary to highlight the data from Table 1, which show that only a minority of the authors reported maternal morbidity data, such as MNM, and neonatal morbidity results. Less than 20% of these publications considered adverse perinatal outcomes in newborns, reporting neonatal mortality as the most common complication but poorly describing very important information such as pH at birth, Apgar score, need for neonatal resuscitation manoeuvres, or admission to the neonatal intensive care unit.

Main findings

The present study shows that MNM and MM rates have a significant relationship with maternal country of origin. Specifically, the HDI of the maternal country of origin where the different studies were conducted was significantly related to MNM and MM rates. Thus, we have observed that the lower the HDI score of the maternal country of origin, the greater the risk is of suffering from these 2 severe pregnancy complications.
We must emphasise that HDI group 3 had the highest MNM rate compared to the other groups even though group 4 would be expected to have the worst results for this complication. The reason for this is not explained in our review, although a possible cause could be that HDI group 4 had lower MNM ratios compared to group 3 because cases of severe morbidity in these countries more frequently caused maternal deaths. This hypothesis would explain why HDI group 4 had an overall MM rate higher than Group 3 and other groups.
Thus, the present study allows calculation of the average expected MNM ratios based on the country's HDI score, as shown in the following examples:
- Average MNM rate in Sweden = 331.71e-4.572x0.933 = 4.69 per 1000 LBs
- Average MNM rate in Brazil = 331.71e-4.572x0.759 = 10.38 per 1000 LBs
- Average MNM rate in Uganda = 331.71e-4.572x0.516 = 31.54 per 1000 LBs
In the same way, if we wanted to calculate the average expected MM rate in a country based on its HDI, we could apply the following formula presented in the results section:
- Average MM rate in Sweden = 47290e-8.663x0.933 = 15.02 per 100,000 LBs
- Average MM rate in Brazil = 47290e-8.663x0.759 = 67.46 per 100,000 LBs
- Average MM rate in Uganda = 47290e-8.663x0.516 = 549.73 per 100,000 LBs
We can observe how the MNM and MM rates increase as the HDI score of the reference country decreases. On the other hand, we see rates of these complications similar to those published by the authors of the studies included in this review. The calculation of these rates is limited by the use of a single explanatory variable such as the HDI score of the country in which the adverse event occurs in the study; therefore, we can observe differences in the results published by other authors, such as the study by Vangen et al. [94] in Norway, which presented an HDI score similar to that of Sweden and a MM rate of 7.2 per 100,000 LBs, half of what was anticipated from our equation.
Estimating these two severe adverse events of pregnancy, childbirth, and the postpartum period can be important for clinicians, enabling them to classify the risk of such events according to the place of maternal origin. Considering previous calculations, a clinician in Sweden can expect that near-miss and mortality rates for a patient attending their hospital from Uganda may be higher than those of a patient from Brazil (if we consider the rates of these countries and how to discriminate between Uganda and Brazil), even if both are immigrants. Obviously, this hypothesis must be confirmed by more studies; surely, the near-miss rate of an immigrant patient in Sweden is lower than that corresponding to their country of origin, but according to our results, it is possible that HDI can help estimate the risk with more accuracy.
The HDI simplifies and captures major socio-demographic characteristics and encompasses various aspects of human development across countries in the form of a common score, as explained above. Therefore, using the HDI, maternal origin can be categorised not only by race and ethnicity but also by income and educational level, which provide accurate information regarding poverty and inequality worldwide. According to our systematic review, the excess risk of MNM and MM seems to depend not only on the maternal birthplace but also on the region where the prenatal checkups and delivery took place, other maternal characteristics and the presence of comorbidities. Therefore, taking into account that a significant proportion of MNM and MM cases are avoidable, there should be an initiative to develop and implement epidemiological analysis systems in host countries to identify socio-demographic risk factors – such as indicators of poverty and social impairment – that have a significant impact on the perinatal outcomes of pregnant immigrant women.
This proposal to use HDI as a parameter related to morbidity and mortality rates is another step in calculating these risks by analysing other aspects than just the average income of the maternal country of origin or immigrant status. Previously, other authors showed an increased risk of severe maternal morbidity events during pregnancy, childbirth, and the postpartum period in women from low-income countries, such as those in sub-Saharan Africa and the Caribbean [9597]. The study published by Blagoeva Atanasova et al. [98] in Spain showed a significantly increased MM risk (four times higher) in immigrant women from South American countries. Similarly, this study highlighted important inequalities in the rate of this complication depending on the place of maternal origin.

Near-miss types by HDI group (Figure 4)

Our review showed that the most common cause of MNM was haemorrhage (38.5% of cases), followed closely by hypertensive disorders of pregnancy.
Overall, we did not observe significant differences in the proportions of MNM types according to the HDI or maternal HDI groups. Thus, although the absolute number and MNM rate are higher in low-HDI countries compared to countries with higher HDI, the proportion of causes of these maternal morbidity events does not differ substantially from one country to another for reasons that are not clear in the literature.
Published studies reflect heterogeneous results in the proportions of MNM, as in a recent multi-centre analysis published by Oppong et al. [90] conducted in Ghana with 8,433 LBs and 288 MNM cases. In this study, the most common cause of MNM was preeclampsia/eclampsia, at 41%, compared to haemorrhage, which was observed in 12.2% of cases. The identification and classification of near-miss cases were performed in this group using the WHO Maternal Near Miss Tool [23].
Tanimia et al. [66], however, in a study conducted in Papua New Guinea with 13,338 LBs and 122 near-miss cases, identified, using the same tool and WHO criteria, haemorrhage as the most common cause of maternal near miss (38%), followed by hypertensive disorders of pregnancy (32%).
The main cause of MM identified by the Global Burden of Disease (GBD) study, which conducted a global and regional review of data from 186 countries during the period of 1990–2015, was obstetric haemorrhage. Other relevant causes of MM were hypertensive disorders of pregnancy, maternal sepsis, obstructed labour, and uterine rupture [99].
There are several reasons why the proportion of MNM causes may differ from one study to another even among countries with similar socio-economic development levels as defined by the HDI. On the one hand, the method used in the collection, definition, and classification of MNM varies from one study to another in both the sources and classification systems of these pregnancy complications. There are several cases in which patients may suffer from several types of near-miss incidents, or one cause of near miss may trigger another, but these situations may not be revealed in the results of the studies included in this review. Furthermore, the description of the study population and hospitals where the conditions were treated in the various studies were not always sufficiently detailed to identify the reason why, in some studies, one cause of near miss was more prevalent than another. In this regard, the maternal HDI given by the country of origin where each study was conducted does not explain the differences found between the studies in the proportion of each type of MNM.

Strengths of the review

This is the most recent and up-to-date systematic review that addresses the importance of characterising pregnant women by their country of origin and investigates a relevant sociodemographic variable, HDI, and its relationship with adverse events such as MNM and MM. From what has been published over the course of a decade, eighty-two articles were collected, describing results from over forty countries, including a large number of patients and maternal morbidity and mortality events.

Limitations of the review

Several limitations are worth considering when interpreting the results of this review. However, there is a lack of uniform criteria for the identification of cases of severe obstetric morbidity or MNM. The identification of cases is complex and varies across studies. Three major criteria have been mentioned in a review conducted by the WHO [100]. The review suggested the use of organ system dysfunction-based criteria supplemented with compatible clinical markers of organ system dysfunction that are feasible for collection in the absence of higher-level amenities-based criteria for identifying all severe morbidity and investigating the cause as the most reproducible one across similar areas.
Population characteristics in case-control groups were not always well described; in several studies, relevant adjustment variables of perinatal outcomes were not used, such as maternal comorbidities, maternal age, parity, maternal body mass index (BMI), or belonging to ethnic or sociodemographic groups that are more vulnerable to pregnancy complications.
As we have described, very few studies refer to immigrant pregnant women or maternal HDI influencing adverse events during pregnancy, childbirth, and the postpartum period.
To address these limitations, Mengistu et al. [101] have recently published a protocol for the systematic review and meta-analysis of severe maternal morbidity events and MNM, at least in high-income countries.
Finally, we must note the limitations of the HDI. On the one hand, the population in the study country is not homogeneous with regard to origin, education level, or income; these factors are not always perfectly described in national epidemiological publications or data. On the other hand, migration flows are very diverse from one country to another depending on economic, social, political, and geographical factors; therefore, the quantity and characteristics of the immigrant population of a nation can be more or less heterogeneous even within similar territories, as in the European Union. We attempted to divide the patients into groups in a simple manner that was based on maternal HDI; additionally, we obtained as much information as we could regarding the mothers’ social situation, as indicated by their country of origin but this might not be entirely informative.

Conclusions

In summary, this review of the literature highlights the usefulness of identifying the HDI of the maternal country of origin through the HDI of the country of publication. Based on eighty-two articles, the review includes a great variety of countries, patients, and maternal morbidity and mortality events. This variety has allowed us to study the inverse and significant relationship between maternal morbidity and mortality and the HDI of the countries included. This relationship is maintained according to the HDI groups.
The most common causes of MNM described were haemorrhage and hypertensive disorders of pregnancy and, less frequently, infectious complications and sepsis. Overall, there were no significant differences in the proportion of each cause of MNM, the HDI, and HDI groups.

Implications for clinical practice

This study shows that the use of maternal sociodemographic variables, including the HDI, may be useful to categorise the risk of maternal morbidity and mortality. In addition to economic value, the HDI weighs education level and life expectancy – as health and social parameters of pregnant women – according to their origin. The HDI is a variable that is easily accessible and calculated, although it may have limitations influenced by other factors, for example, in the immigrant population, such as time spent in the destination country, baseline health state, or the degree of social integration and family income. More studies are needed to determine the discriminatory value of risk in the immigrant population treated in different countries.

Acknowledgements

The authors are grateful to Mr Jose María Bellon for statistical assistance.
This is a systematic review of the literature so consent to participate was not required. Ethical approval was not required either.
Not Applicable

Competing interests

The authors declare that they have no competing interests.
Open AccessThis 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.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Literatur
1.
Zurück zum Zitat GBD 2015 DALYs and HALE Collaborators. Global, regional, and national disability-adjusted life-years (DALYs) for 315 diseases and injuries and healthy life expectancy (HALE), 1990-2015: a systematic analysis for the global burden of disease study 2015. Lancet. 2016;388:1603–58.CrossRef GBD 2015 DALYs and HALE Collaborators. Global, regional, and national disability-adjusted life-years (DALYs) for 315 diseases and injuries and healthy life expectancy (HALE), 1990-2015: a systematic analysis for the global burden of disease study 2015. Lancet. 2016;388:1603–58.CrossRef
2.
Zurück zum Zitat 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;23:287–96.PubMedCrossRef 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;23:287–96.PubMedCrossRef
3.
Zurück zum Zitat Tuncalp O, Hindin MJ, Adu-Bonsaffoh K, Adanu RM. Assessment of maternal near-miss and quality of care in a hospital-based study in Accra, Ghana. Int J Gynaecol Obstet. 2013;123:58–63.PubMedCrossRef Tuncalp O, Hindin MJ, Adu-Bonsaffoh K, Adanu RM. Assessment of maternal near-miss and quality of care in a hospital-based study in Accra, Ghana. Int J Gynaecol Obstet. 2013;123:58–63.PubMedCrossRef
4.
Zurück zum Zitat Garcia-Tizon Larroca S, Arevalo-Serrano J, Duran Vila A, Pintado Recarte MP, Cueto Hernandez I, Solis Pierna A, et al. Human Development Index (HDI) of the maternal country of origin as a predictor of perinatal outcomes - a longitudinal study conducted in Spain. BMC Pregnancy Childbirth. 2017;17:314.PubMedPubMedCentralCrossRef Garcia-Tizon Larroca S, Arevalo-Serrano J, Duran Vila A, Pintado Recarte MP, Cueto Hernandez I, Solis Pierna A, et al. Human Development Index (HDI) of the maternal country of origin as a predictor of perinatal outcomes - a longitudinal study conducted in Spain. BMC Pregnancy Childbirth. 2017;17:314.PubMedPubMedCentralCrossRef
5.
Zurück zum Zitat Luque-Fernandez MA, Thomas A, Gelaye B, Racape J, Sanchez MJ, Williams MA. Secular trends in stillbirth by maternal socioeconomic status in Spain 2007-15: a population-based study of 4 million births. Eur J Pub Health. 2019. https://doi.org/10.1093/eurpub/ckz086. Luque-Fernandez MA, Thomas A, Gelaye B, Racape J, Sanchez MJ, Williams MA. Secular trends in stillbirth by maternal socioeconomic status in Spain 2007-15: a population-based study of 4 million births. Eur J Pub Health. 2019. https://​doi.​org/​10.​1093/​eurpub/​ckz086.
6.
Zurück zum Zitat Liberati A, Altman DG, Tetzlaff J, Mulrow C, Gotzsche PC, Ioannidis JP, et al. The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration. PLoS Med. 2009;6:e1000100.PubMedPubMedCentralCrossRef Liberati A, Altman DG, Tetzlaff J, Mulrow C, Gotzsche PC, Ioannidis JP, et al. The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration. PLoS Med. 2009;6:e1000100.PubMedPubMedCentralCrossRef
7.
Zurück zum Zitat Stroup DF, Berlin JA, Morton SC, Olkin I, Williamson GD, Rennie D, et al. Meta-analysis of observational studies in epidemiology: a proposal for reporting. Meta-analysis of Observational Studies in Epidemiology (MOOSE) group. JAMA. 2000;283:2008–12.PubMedCrossRef Stroup DF, Berlin JA, Morton SC, Olkin I, Williamson GD, Rennie D, et al. Meta-analysis of observational studies in epidemiology: a proposal for reporting. Meta-analysis of Observational Studies in Epidemiology (MOOSE) group. JAMA. 2000;283:2008–12.PubMedCrossRef
8.
Zurück zum Zitat United Nations Development Programme (UNDP). Summary human development report 2013. New York: United Nations Development Programme (UNDP); 2013.CrossRef United Nations Development Programme (UNDP). Summary human development report 2013. New York: United Nations Development Programme (UNDP); 2013.CrossRef
9.
Zurück zum Zitat United Nations Development Programme (UNDP). Reports (1990–2013) Human Development Reports (HDR). New York: United Nations Development Programme (UNDP); 2013. United Nations Development Programme (UNDP). Reports (1990–2013) Human Development Reports (HDR). New York: United Nations Development Programme (UNDP); 2013.
10.
Zurück zum Zitat Guyatt GH, Oxman AD, Vist GE, Kunz R, Falck-Ytter Y, Alonso-Coello P, et al. GRADE: an emerging consensus on rating quality of evidence and strength of recommendations. BMJ. 2008;336:924–6.PubMedPubMedCentralCrossRef Guyatt GH, Oxman AD, Vist GE, Kunz R, Falck-Ytter Y, Alonso-Coello P, et al. GRADE: an emerging consensus on rating quality of evidence and strength of recommendations. BMJ. 2008;336:924–6.PubMedPubMedCentralCrossRef
11.
Zurück zum Zitat Adisasmita A, Deviany PE, Nandiaty F, Stanton C, Ronsmans C. Obstetric near miss and deaths in public and private hospitals in Indonesia. BMC Pregnancy Childbirth. 2008;8:10.PubMedPubMedCentralCrossRef Adisasmita A, Deviany PE, Nandiaty F, Stanton C, Ronsmans C. Obstetric near miss and deaths in public and private hospitals in Indonesia. BMC Pregnancy Childbirth. 2008;8:10.PubMedPubMedCentralCrossRef
12.
Zurück zum Zitat Driul L, Cacciaguerra G, Citossi A, Martina MD, Peressini L, Marchesoni D. Prepregnancy body mass index and adverse pregnancy outcomes. Arch Gynecol Obstet. 2008;278:23–6.PubMedCrossRef Driul L, Cacciaguerra G, Citossi A, Martina MD, Peressini L, Marchesoni D. Prepregnancy body mass index and adverse pregnancy outcomes. Arch Gynecol Obstet. 2008;278:23–6.PubMedCrossRef
13.
Zurück zum Zitat Roost M, Altamirano VC, Liljestrand J, Essen B. Priorities in emergency obstetric care in Bolivia--maternal mortality and near-miss morbidity in metropolitan La Paz. Bjog. 2009;116:1210–7.PubMedCrossRef Roost M, Altamirano VC, Liljestrand J, Essen B. Priorities in emergency obstetric care in Bolivia--maternal mortality and near-miss morbidity in metropolitan La Paz. Bjog. 2009;116:1210–7.PubMedCrossRef
14.
Zurück zum Zitat Almerie Y, Almerie MQ, Matar HE, Shahrour Y, Al Chamat AA, Abdulsalam A. Obstetric near-miss and maternal mortality in maternity university hospital, Damascus, Syria: a retrospective study. BMC Pregnancy Childbirth. 2010;10:–65. Almerie Y, Almerie MQ, Matar HE, Shahrour Y, Al Chamat AA, Abdulsalam A. Obstetric near-miss and maternal mortality in maternity university hospital, Damascus, Syria: a retrospective study. BMC Pregnancy Childbirth. 2010;10:–65.
15.
Zurück zum Zitat Shrestha NS, Saha R, Karki C. Near miss maternal morbidity and maternal mortality at Kathmandu medical college teaching hospital. Kathmandu Univ Med J (KUMJ). 2010;8:222–6.CrossRef Shrestha NS, Saha R, Karki C. Near miss maternal morbidity and maternal mortality at Kathmandu medical college teaching hospital. Kathmandu Univ Med J (KUMJ). 2010;8:222–6.CrossRef
16.
Zurück zum Zitat Souza JP, Cecatti JG, Faundes A, Morais SS, Villar J, Carroli G, et al. Maternal near miss and maternal death in the World Health Organization's 2005 global survey on maternal and perinatal health. Bull World Health Organ. 2010;88:113–9.PubMedCrossRef Souza JP, Cecatti JG, Faundes A, Morais SS, Villar J, Carroli G, et al. Maternal near miss and maternal death in the World Health Organization's 2005 global survey on maternal and perinatal health. Bull World Health Organ. 2010;88:113–9.PubMedCrossRef
18.
Zurück zum Zitat Amaral E, Souza JP, Surita F, Luz AG, Sousa MH, Cecatti JG, et al. A population-based surveillance study on severe acute maternal morbidity (near-miss) and adverse perinatal outcomes in Campinas, Brazil: the Vigimoma project. BMC Pregnancy Childbirth. 2011;11:9.PubMedPubMedCentralCrossRef Amaral E, Souza JP, Surita F, Luz AG, Sousa MH, Cecatti JG, et al. A population-based surveillance study on severe acute maternal morbidity (near-miss) and adverse perinatal outcomes in Campinas, Brazil: the Vigimoma project. BMC Pregnancy Childbirth. 2011;11:9.PubMedPubMedCentralCrossRef
19.
Zurück zum Zitat Donati S, Senatore S, Ronconi A. Obstetric near-miss cases among women admitted to intensive care units in Italy. Acta Obstet Gynecol Scand. 2012;91:452–7.PubMedCrossRef Donati S, Senatore S, Ronconi A. Obstetric near-miss cases among women admitted to intensive care units in Italy. Acta Obstet Gynecol Scand. 2012;91:452–7.PubMedCrossRef
20.
Zurück zum Zitat Jayaratnam S, de Costa C, Howat P. Developing an assessment tool for maternal morbidity 'near-miss'- a prospective study in a large Australian regional hospital. Aust N Z J Obstet Gynaecol. 2011;51:421–5.PubMedCrossRef Jayaratnam S, de Costa C, Howat P. Developing an assessment tool for maternal morbidity 'near-miss'- a prospective study in a large Australian regional hospital. Aust N Z J Obstet Gynaecol. 2011;51:421–5.PubMedCrossRef
21.
Zurück zum Zitat Kaye DK, Kakaire O, Osinde MO. Maternal morbidity and near-miss mortality among women referred for emergency obstetric care in rural Uganda. Int J Gynaecol Obstet. 2011;114:84–5.PubMedCrossRef Kaye DK, Kakaire O, Osinde MO. Maternal morbidity and near-miss mortality among women referred for emergency obstetric care in rural Uganda. Int J Gynaecol Obstet. 2011;114:84–5.PubMedCrossRef
22.
Zurück zum Zitat Lobato G, Nakamura-Pereira M, Mendes-Silva W, Dias MA, Reichenheim ME. Comparing different diagnostic approaches to severe maternal morbidity and near-miss: a pilot study in a Brazilian tertiary hospital. Eur J Obstet Gynecol Reprod Biol. 2013;167:24–8.PubMedCrossRef Lobato G, Nakamura-Pereira M, Mendes-Silva W, Dias MA, Reichenheim ME. Comparing different diagnostic approaches to severe maternal morbidity and near-miss: a pilot study in a Brazilian tertiary hospital. Eur J Obstet Gynecol Reprod Biol. 2013;167:24–8.PubMedCrossRef
23.
Zurück zum Zitat Souza JP, Cecatti JG, Haddad SM, Parpinelli MA, Costa ML, Katz L, et al. The WHO maternal near-miss approach and the maternal severity index model (MSI): tools for assessing the management of severe maternal morbidity. PLoS One. 2012;7:e44129.PubMedPubMedCentralCrossRef Souza JP, Cecatti JG, Haddad SM, Parpinelli MA, Costa ML, Katz L, et al. The WHO maternal near-miss approach and the maternal severity index model (MSI): tools for assessing the management of severe maternal morbidity. PLoS One. 2012;7:e44129.PubMedPubMedCentralCrossRef
24.
Zurück zum Zitat 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;13:93.PubMedPubMedCentralCrossRef 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;13:93.PubMedPubMedCentralCrossRef
25.
Zurück zum Zitat Jabir M, Abdul-Salam I, Suheil DM, Al-Hilli W, Abul-Hassan S, Al-Zuheiri A, et al. Maternal near miss and quality of maternal health care in Baghdad, Iraq. BMC Pregnancy Childbirth. 2013;13:11.PubMedPubMedCentralCrossRef Jabir M, Abdul-Salam I, Suheil DM, Al-Hilli W, Abul-Hassan S, Al-Zuheiri A, et al. Maternal near miss and quality of maternal health care in Baghdad, Iraq. BMC Pregnancy Childbirth. 2013;13:11.PubMedPubMedCentralCrossRef
26.
Zurück zum Zitat Karolinski A, Mercer R, Micone P, Ocampo C, Mazzoni A, Fontana O, et al. The epidemiology of life-threatening complications associated with reproductive process in public hospitals in Argentina. BJOG. 2013;120:1685–94.PubMedCrossRef Karolinski A, Mercer R, Micone P, Ocampo C, Mazzoni A, Fontana O, et al. The epidemiology of life-threatening complications associated with reproductive process in public hospitals in Argentina. BJOG. 2013;120:1685–94.PubMedCrossRef
27.
Zurück zum Zitat Nelissen EJT, Mduma E, Ersdal HL, Evjen-Olsen B, van Roosmalen JJM, Stekelenburg J. Maternal near miss and mortality in a rural referral hospital in northern Tanzania: a cross-sectional study. BMC Pregnancy Childbirth. 2013;13:141.PubMedPubMedCentralCrossRef Nelissen EJT, Mduma E, Ersdal HL, Evjen-Olsen B, van Roosmalen JJM, Stekelenburg J. Maternal near miss and mortality in a rural referral hospital in northern Tanzania: a cross-sectional study. BMC Pregnancy Childbirth. 2013;13:141.PubMedPubMedCentralCrossRef
28.
Zurück zum Zitat Roopa PS, Verma S, Rai L, Kumar P, Pai MV, Shetty J. “Near miss” obstetric events and maternal deaths in a tertiary care hospital: an audit. J Pregnancy. 2013;2013:393758. Roopa PS, Verma S, Rai L, Kumar P, Pai MV, Shetty J. “Near miss” obstetric events and maternal deaths in a tertiary care hospital: an audit. J Pregnancy. 2013;2013:393758.
29.
Zurück zum Zitat Shen FR, Liu M, Zhang X, Yang W, Chen YG. Factors associated with maternal near-miss morbidity and mortality in Kowloon Hospital, Suzhou, China. Int J Gynaecol Obstet. 2013;123:64–7.PubMedCrossRef Shen FR, Liu M, Zhang X, Yang W, Chen YG. Factors associated with maternal near-miss morbidity and mortality in Kowloon Hospital, Suzhou, China. Int J Gynaecol Obstet. 2013;123:64–7.PubMedCrossRef
30.
Zurück zum Zitat Wahlberg A, Roost M, Haglund B, Hogberg U, Essen B. Increased risk of severe maternal morbidity (near-miss) among immigrant women in Sweden: a population register-based study. BJOG. 2013;120:1605–11 discussion 12.PubMedCrossRef Wahlberg A, Roost M, Haglund B, Hogberg U, Essen B. Increased risk of severe maternal morbidity (near-miss) among immigrant women in Sweden: a population register-based study. BJOG. 2013;120:1605–11 discussion 12.PubMedCrossRef
31.
Zurück zum Zitat Abalos E, Cuesta C, Carroli G, Qureshi Z, Widmer M, Vogel JP, et al. Pre-eclampsia, eclampsia and adverse maternal and perinatal outcomes: a secondary analysis of the world health organization multicountry survey on maternal and Newborn health. BJOG. 2014;121(Suppl 1):14–24.PubMedCrossRef Abalos E, Cuesta C, Carroli G, Qureshi Z, Widmer M, Vogel JP, et al. Pre-eclampsia, eclampsia and adverse maternal and perinatal outcomes: a secondary analysis of the world health organization multicountry survey on maternal and Newborn health. BJOG. 2014;121(Suppl 1):14–24.PubMedCrossRef
32.
Zurück zum Zitat David E, Machungo F, Zanconato G, Cavaliere E, Fiosse S, Sululu C, et al. Maternal near miss and maternal deaths in Mozambique: a cross-sectional, region-wide study of 635 consecutive cases assisted in health facilities of Maputo province. BMC Pregnancy Childbirth. 2014;14:401.PubMedPubMedCentralCrossRef David E, Machungo F, Zanconato G, Cavaliere E, Fiosse S, Sululu C, et al. Maternal near miss and maternal deaths in Mozambique: a cross-sectional, region-wide study of 635 consecutive cases assisted in health facilities of Maputo province. BMC Pregnancy Childbirth. 2014;14:401.PubMedPubMedCentralCrossRef
33.
Zurück zum Zitat Galvao LP, Alvim-Pereira F, de Mendonca CM, Menezes FE, Gois KA, Ribeiro RF Jr, et al. The prevalence of severe maternal morbidity and near miss and associated factors in Sergipe, Northeast Brazil. BMC Pregnancy Childbirth. 2014;14:25.PubMedPubMedCentralCrossRef Galvao LP, Alvim-Pereira F, de Mendonca CM, Menezes FE, Gois KA, Ribeiro RF Jr, et al. The prevalence of severe maternal morbidity and near miss and associated factors in Sergipe, Northeast Brazil. BMC Pregnancy Childbirth. 2014;14:25.PubMedPubMedCentralCrossRef
34.
Zurück zum Zitat Litorp H, Kidanto HL, Roost M, Abeid M, Nystrom L, Essen B. Maternal near-miss and death and their association with caesarean section complications: a cross-sectional study at a university hospital and a regional hospital in Tanzania. BMC Pregnancy Childbirth. 2014;14:244.PubMedPubMedCentralCrossRef Litorp H, Kidanto HL, Roost M, Abeid M, Nystrom L, Essen B. Maternal near-miss and death and their association with caesarean section complications: a cross-sectional study at a university hospital and a regional hospital in Tanzania. BMC Pregnancy Childbirth. 2014;14:244.PubMedPubMedCentralCrossRef
35.
Zurück zum Zitat Luexay P, Malinee L, Pisake L, Marie-Helene BC. Maternal near-miss and mortality in Sayaboury province. Lao PDR BMC Public Health. 2014;14:945.PubMedCrossRef Luexay P, Malinee L, Pisake L, Marie-Helene BC. Maternal near-miss and mortality in Sayaboury province. Lao PDR BMC Public Health. 2014;14:945.PubMedCrossRef
36.
Zurück zum Zitat Lumbiganon P, Laopaiboon M, Intarut N, Vogel JP, Souza JP, Gulmezoglu AM, et al. Indirect causes of severe adverse maternal outcomes: a secondary analysis of the WHO multicountry survey on maternal and newborn health. BJOG. 2014;121(Suppl 1):32–9.PubMedCrossRef Lumbiganon P, Laopaiboon M, Intarut N, Vogel JP, Souza JP, Gulmezoglu AM, et al. Indirect causes of severe adverse maternal outcomes: a secondary analysis of the WHO multicountry survey on maternal and newborn health. BJOG. 2014;121(Suppl 1):32–9.PubMedCrossRef
37.
Zurück zum Zitat Mazhar SB, Batool A, Emanuel A, Khan AT, Bhutta S. Severe maternal outcomes and their predictors among Pakistani women in the WHO Multicountry Survey on Maternal and Newborn Health. Int J Gynaecol Obstet. 2015;129:30–3.PubMedCrossRef Mazhar SB, Batool A, Emanuel A, Khan AT, Bhutta S. Severe maternal outcomes and their predictors among Pakistani women in the WHO Multicountry Survey on Maternal and Newborn Health. Int J Gynaecol Obstet. 2015;129:30–3.PubMedCrossRef
38.
Zurück zum Zitat Pacheco AJ, Katz L, Souza AS, de Amorim MM. Factors associated with severe maternal morbidity and near miss in the Sao Francisco Valley, Brazil: a retrospective, cohort study. BMC Pregnancy Childbirth. 2014;14:91.PubMedPubMedCentralCrossRef Pacheco AJ, Katz L, Souza AS, de Amorim MM. Factors associated with severe maternal morbidity and near miss in the Sao Francisco Valley, Brazil: a retrospective, cohort study. BMC Pregnancy Childbirth. 2014;14:91.PubMedPubMedCentralCrossRef
39.
Zurück zum Zitat Pandey A, Das V, Agarwal A, Agrawal S, Misra D, Jaiswal N. Evaluation of obstetric near miss and maternal deaths in a tertiary care hospital in north India: shifting focus from mortality to morbidity. J Obstet Gynaecol India. 2014;64:394–9.PubMedPubMedCentralCrossRef Pandey A, Das V, Agarwal A, Agrawal S, Misra D, Jaiswal N. Evaluation of obstetric near miss and maternal deaths in a tertiary care hospital in north India: shifting focus from mortality to morbidity. J Obstet Gynaecol India. 2014;64:394–9.PubMedPubMedCentralCrossRef
40.
Zurück zum Zitat Rocha Filho EA, Costa ML, Cecatti JG, Parpinelli MA, Haddad SM, Sousa MH, et al. Contribution of antepartum and intrapartum hemorrhage to the burden of maternal near miss and death in a national surveillance study. Acta Obstet Gynecol Scand. 2015;94:50–8.PubMedCrossRef Rocha Filho EA, Costa ML, Cecatti JG, Parpinelli MA, Haddad SM, Sousa MH, et al. Contribution of antepartum and intrapartum hemorrhage to the burden of maternal near miss and death in a national surveillance study. Acta Obstet Gynecol Scand. 2015;94:50–8.PubMedCrossRef
41.
Zurück zum Zitat Assarag B, Dujardin B, Delamou A, Meski FZ, de Brouwere V. Determinants of maternal near-miss in Morocco: too late, too far, too sloppy? PLoS One. 2015;10:e0116675.PubMedPubMedCentralCrossRef Assarag B, Dujardin B, Delamou A, Meski FZ, de Brouwere V. Determinants of maternal near-miss in Morocco: too late, too far, too sloppy? PLoS One. 2015;10:e0116675.PubMedPubMedCentralCrossRef
42.
Zurück zum Zitat Bashour H, Saad-Haddad G, DeJong J, Ramadan MC, Hassan S, Breebaart M, et al. A cross sectional study of maternal ‘near-miss’ cases in major public hospitals in Egypt, Lebanon. Palestine and Syria BMC Pregnancy Childbirth. 2015;15:296.PubMedCrossRef Bashour H, Saad-Haddad G, DeJong J, Ramadan MC, Hassan S, Breebaart M, et al. A cross sectional study of maternal ‘near-miss’ cases in major public hospitals in Egypt, Lebanon. Palestine and Syria BMC Pregnancy Childbirth. 2015;15:296.PubMedCrossRef
43.
Zurück zum Zitat Cecatti JG, Souza RT, Pacagnella RC, Leal MC, Moura EC, Santos LM. Maternal near miss among women using the public health system in the Amazon and Northeast regions of Brazil. Rev Panam Salud Publica. 2015;37:232–8.PubMed Cecatti JG, Souza RT, Pacagnella RC, Leal MC, Moura EC, Santos LM. Maternal near miss among women using the public health system in the Amazon and Northeast regions of Brazil. Rev Panam Salud Publica. 2015;37:232–8.PubMed
44.
Zurück zum Zitat Hassan SJ, Wick L, DeJong J. A glance into the hidden burden of maternal morbidity and patterns of management in a Palestinian governmental referral hospital. Women Birth. 2015;28:e148–56.PubMedCrossRef Hassan SJ, Wick L, DeJong J. A glance into the hidden burden of maternal morbidity and patterns of management in a Palestinian governmental referral hospital. Women Birth. 2015;28:e148–56.PubMedCrossRef
45.
Zurück zum Zitat Kulkarni R, Chauhan S, Daver R, Nandanwar Y, Patil A, Bhosale A. Prospective observational study of near-miss obstetric events at two tertiary hospitals in Mumbai, Maharashtra. India Int J Gynaecol Obstet. 2016;132:170–3.PubMedCrossRef Kulkarni R, Chauhan S, Daver R, Nandanwar Y, Patil A, Bhosale A. Prospective observational study of near-miss obstetric events at two tertiary hospitals in Mumbai, Maharashtra. India Int J Gynaecol Obstet. 2016;132:170–3.PubMedCrossRef
46.
Zurück zum Zitat Madeiro AP, Rufino AC, Lacerda EZ, Brasil LG. Incidence and determinants of severe maternal morbidity: a transversal study in a referral hospital in Teresina, Piaui, Brazil. BMC Pregnancy Childbirth. 2015;15:210.PubMedPubMedCentralCrossRef Madeiro AP, Rufino AC, Lacerda EZ, Brasil LG. Incidence and determinants of severe maternal morbidity: a transversal study in a referral hospital in Teresina, Piaui, Brazil. BMC Pregnancy Childbirth. 2015;15:210.PubMedPubMedCentralCrossRef
47.
Zurück zum Zitat Naderi T, Foroodnia S, Omidi S, Samadani F, Nakhaee N. Incidence and correlates of maternal near miss in southeast Iran. Int J Reprod Med. 2015;2015:914713.PubMedPubMedCentralCrossRef Naderi T, Foroodnia S, Omidi S, Samadani F, Nakhaee N. Incidence and correlates of maternal near miss in southeast Iran. Int J Reprod Med. 2015;2015:914713.PubMedPubMedCentralCrossRef
48.
Zurück zum Zitat Oladapo OT, Adetoro OO, Ekele BA, Chama C, Etuk SJ, Aboyeji AP, et al. When getting there is not enough: a nationwide cross-sectional study of 998 maternal deaths and 1451 near-misses in public tertiary hospitals in a low-income country. BJOG. 2016;123:928–38.PubMedCrossRef Oladapo OT, Adetoro OO, Ekele BA, Chama C, Etuk SJ, Aboyeji AP, et al. When getting there is not enough: a nationwide cross-sectional study of 998 maternal deaths and 1451 near-misses in public tertiary hospitals in a low-income country. BJOG. 2016;123:928–38.PubMedCrossRef
49.
Zurück zum Zitat Oliveira LC, da Costa AA. Maternal near miss in the intensive care unit: clinical and epidemiological aspects. Rev Bras Ter Intensiva. 2015;27:220–7.PubMedPubMedCentral Oliveira LC, da Costa AA. Maternal near miss in the intensive care unit: clinical and epidemiological aspects. Rev Bras Ter Intensiva. 2015;27:220–7.PubMedPubMedCentral
50.
Zurück zum Zitat 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.PubMedPubMedCentralCrossRef 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.PubMedPubMedCentralCrossRef
51.
Zurück zum Zitat Sangeeta G, Leena W, Taru G, Sushma K, Nupur G, Amrita P. Evaluation of severe maternal outcomes to assess quality of maternal health care at a tertiary center. J Obstet Gynaecol India. 2015;65:23–7.PubMedCrossRef Sangeeta G, Leena W, Taru G, Sushma K, Nupur G, Amrita P. Evaluation of severe maternal outcomes to assess quality of maternal health care at a tertiary center. J Obstet Gynaecol India. 2015;65:23–7.PubMedCrossRef
52.
Zurück zum Zitat Soma-Pillay P, Pattinson RC, Langa-Mlambo L, Nkosi BS, Macdonald AP. Maternal near miss and maternal death in the Pretoria academic complex, South Africa: a population-based study. S Afr Med J. 2015;105:578–63.PubMedCrossRef Soma-Pillay P, Pattinson RC, Langa-Mlambo L, Nkosi BS, Macdonald AP. Maternal near miss and maternal death in the Pretoria academic complex, South Africa: a population-based study. S Afr Med J. 2015;105:578–63.PubMedCrossRef
53.
Zurück zum Zitat Okusanya BO, Sajo AE, Osanyin GE, Okojie OE, Abodunrin ON. Peripartum hysterectomy in a Nigerian university hospital: an assessment of severe maternal outcomes with the maternal severity index model. Niger Postgrad Med J. 2016;23:62–6.PubMedCrossRef Okusanya BO, Sajo AE, Osanyin GE, Okojie OE, Abodunrin ON. Peripartum hysterectomy in a Nigerian university hospital: an assessment of severe maternal outcomes with the maternal severity index model. Niger Postgrad Med J. 2016;23:62–6.PubMedCrossRef
54.
Zurück zum Zitat 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;13:134.PubMedPubMedCentralCrossRef 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;13:134.PubMedPubMedCentralCrossRef
55.
Zurück zum Zitat Domingues RM, Dias MA, Schilithz AO, Leal MD. Factors associated with maternal near miss in childbirth and the postpartum period: findings from the birth in Brazil national survey, 2011-2012. Reprod Health. 2016;13:115.PubMedPubMedCentralCrossRef Domingues RM, Dias MA, Schilithz AO, Leal MD. Factors associated with maternal near miss in childbirth and the postpartum period: findings from the birth in Brazil national survey, 2011-2012. Reprod Health. 2016;13:115.PubMedPubMedCentralCrossRef
56.
Zurück zum Zitat El Ghardallou M, Nabli Ajmi T, Mkhazni A, Zedini C, Meddeb S, Khairi H, et al. Maternal near miss and quality of obstetric care in a Tunisian tertiary level maternity. Afr J Reprod Health. 2016;20:44–50.PubMedCrossRef El Ghardallou M, Nabli Ajmi T, Mkhazni A, Zedini C, Meddeb S, Khairi H, et al. Maternal near miss and quality of obstetric care in a Tunisian tertiary level maternity. Afr J Reprod Health. 2016;20:44–50.PubMedCrossRef
57.
Zurück zum Zitat Jayaratnam S, Burton A, Connan KF, de Costa C. Maternal 'near miss' at Royal Darwin hospital: an analysis of severe maternal morbidity at an Australian regional tertiary maternity unit. Aust N Z J Obstet Gynaecol. 2016;56:381–6.PubMedCrossRef Jayaratnam S, Burton A, Connan KF, de Costa C. Maternal 'near miss' at Royal Darwin hospital: an analysis of severe maternal morbidity at an Australian regional tertiary maternity unit. Aust N Z J Obstet Gynaecol. 2016;56:381–6.PubMedCrossRef
58.
Zurück zum Zitat 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;16:324.PubMedPubMedCentralCrossRef 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;16:324.PubMedPubMedCentralCrossRef
59.
Zurück zum Zitat Lima HM, Carvalho FH, Feitosa FE, Nunes GC. Factors associated with maternal mortality among patients meeting criteria of severe maternal morbidity and near miss. Int J Gynaecol Obstet. 2017;136:337–43.PubMedCrossRef Lima HM, Carvalho FH, Feitosa FE, Nunes GC. Factors associated with maternal mortality among patients meeting criteria of severe maternal morbidity and near miss. Int J Gynaecol Obstet. 2017;136:337–43.PubMedCrossRef
60.
Zurück zum Zitat Mohammadi S, Essen B, Fallahian M, Taheripanah R, Saleh Gargari S, Kallestal C. Maternal near-miss at university hospitals with cesarean overuse: an incident case-control study. Acta Obstet Gynecol Scand. 2016;95:777–86.PubMedCrossRef Mohammadi S, Essen B, Fallahian M, Taheripanah R, Saleh Gargari S, Kallestal C. Maternal near-miss at university hospitals with cesarean overuse: an incident case-control study. Acta Obstet Gynecol Scand. 2016;95:777–86.PubMedCrossRef
61.
Zurück zum Zitat 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.PubMedPubMedCentralCrossRef 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.PubMedPubMedCentralCrossRef
62.
Zurück zum Zitat Nansubuga E, Ayiga N, Moyer CA. Prevalence of maternal near miss and community-based risk factors in Central Uganda. Int J Gynaecol Obstet. 2016;135:214–20.PubMedCrossRef Nansubuga E, Ayiga N, Moyer CA. Prevalence of maternal near miss and community-based risk factors in Central Uganda. Int J Gynaecol Obstet. 2016;135:214–20.PubMedCrossRef
63.
Zurück zum Zitat Norhayati MN, Nik Hazlina NH, Sulaiman Z, Azman MY. Severe maternal morbidity and near misses in tertiary hospitals, Kelantan. Malaysia: a cross-sectional study BMC Public Health. 2016;16:229.PubMed Norhayati MN, Nik Hazlina NH, Sulaiman Z, Azman MY. Severe maternal morbidity and near misses in tertiary hospitals, Kelantan. Malaysia: a cross-sectional study BMC Public Health. 2016;16:229.PubMed
64.
Zurück zum Zitat Parmar NT, Parmar AG, Mazumdar VS. Incidence of maternal "Near-Miss" events in a tertiary care hospital of central Gujarat. India J Obstet Gynaecol India. 2016;66:315–20.PubMedCrossRef Parmar NT, Parmar AG, Mazumdar VS. Incidence of maternal "Near-Miss" events in a tertiary care hospital of central Gujarat. India J Obstet Gynaecol India. 2016;66:315–20.PubMedCrossRef
65.
Zurück zum Zitat Rathod AD, Chavan RP, Bhagat V, Pajai S, Padmawar A, Thool P. Analysis of near-miss and maternal mortality at tertiary referral centre of rural India. J Obstet Gynaecol India. 2016;66:295–300.PubMedPubMedCentralCrossRef Rathod AD, Chavan RP, Bhagat V, Pajai S, Padmawar A, Thool P. Analysis of near-miss and maternal mortality at tertiary referral centre of rural India. J Obstet Gynaecol India. 2016;66:295–300.PubMedPubMedCentralCrossRef
66.
Zurück zum Zitat Tanimia H, Jayaratnam S, Mola GL, Amoa AB, de Costa C. Near-misses at the port moresby general hospital: a descriptive study. Aust N Z J Obstet Gynaecol. 2016;56:148–53.PubMedCrossRef Tanimia H, Jayaratnam S, Mola GL, Amoa AB, de Costa C. Near-misses at the port moresby general hospital: a descriptive study. Aust N Z J Obstet Gynaecol. 2016;56:148–53.PubMedCrossRef
67.
Zurück zum Zitat Bolnga JW, Morris M, Totona C, Laman M. Maternal near-misses at a provincial hospital in Papua New Guinea: a prospective observational study. Aust N Z J Obstet Gynaecol. 2017;57:624–9.PubMedCrossRef Bolnga JW, Morris M, Totona C, Laman M. Maternal near-misses at a provincial hospital in Papua New Guinea: a prospective observational study. Aust N Z J Obstet Gynaecol. 2017;57:624–9.PubMedCrossRef
68.
Zurück zum Zitat Goldenberg RL, Saleem S, Ali S, Moore JL, Lokangako A, Tshefu A, et al. Maternal near miss in low-resource areas. Int J Gynaecol Obstet. 2017;138:347–55.PubMedPubMedCentralCrossRef Goldenberg RL, Saleem S, Ali S, Moore JL, Lokangako A, Tshefu A, et al. Maternal near miss in low-resource areas. Int J Gynaecol Obstet. 2017;138:347–55.PubMedPubMedCentralCrossRef
69.
Zurück zum Zitat Herklots T, van Acht L, Meguid T, Franx A, Jacod B. Severe maternal morbidity in Zanzibar’s referral hospital: measuring the impact of in-hospital care. PLoS One. 2017;12:e0181470.PubMedPubMedCentralCrossRef Herklots T, van Acht L, Meguid T, Franx A, Jacod B. Severe maternal morbidity in Zanzibar’s referral hospital: measuring the impact of in-hospital care. PLoS One. 2017;12:e0181470.PubMedPubMedCentralCrossRef
70.
Zurück zum Zitat Khan T, Laul P, Laul A, Ramzan M. Prognostic factors of maternal near miss events and maternal deaths in a tertiary healthcare facility in India. Int J Gynaecol Obstet. 2017;138:171–6.PubMedCrossRef Khan T, Laul P, Laul A, Ramzan M. Prognostic factors of maternal near miss events and maternal deaths in a tertiary healthcare facility in India. Int J Gynaecol Obstet. 2017;138:171–6.PubMedCrossRef
71.
Zurück zum Zitat Kiruja J, Osman F, Egal JA, Essen B, Klingberg-Allvin M, Erlandsson K. Maternal near-miss and death incidences - frequencies, causes and the referral chain in Somaliland: a pilot study using the WHO near-miss approach. Sex Reprod Healthc. 2017;12:30–6.PubMedCrossRef Kiruja J, Osman F, Egal JA, Essen B, Klingberg-Allvin M, Erlandsson K. Maternal near-miss and death incidences - frequencies, causes and the referral chain in Somaliland: a pilot study using the WHO near-miss approach. Sex Reprod Healthc. 2017;12:30–6.PubMedCrossRef
72.
Zurück zum Zitat 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:e0179013.PubMedCrossRef 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:e0179013.PubMedCrossRef
73.
Zurück zum Zitat Mawarti Y, Utarini A, Hakimi M. Maternal care quality in near miss and maternal mortality in an academic public tertiary hospital in Yogyakarta, Indonesia: a retrospective cohort study. BMC Pregnancy Childbirth. 2017;17:149.PubMedPubMedCentralCrossRef Mawarti Y, Utarini A, Hakimi M. Maternal care quality in near miss and maternal mortality in an academic public tertiary hospital in Yogyakarta, Indonesia: a retrospective cohort study. BMC Pregnancy Childbirth. 2017;17:149.PubMedPubMedCentralCrossRef
74.
Zurück zum Zitat Mbachu II, Ezeama C, Osuagwu K, Umeononihu OS, Obiannika C, Ezeama N. A cross sectional study of maternal near miss and mortality at a rural tertiary centre in southern Nigeria. BMC Pregnancy Childbirth. 2017;17:251.PubMedPubMedCentralCrossRef Mbachu II, Ezeama C, Osuagwu K, Umeononihu OS, Obiannika C, Ezeama N. A cross sectional study of maternal near miss and mortality at a rural tertiary centre in southern Nigeria. BMC Pregnancy Childbirth. 2017;17:251.PubMedPubMedCentralCrossRef
75.
Zurück zum Zitat 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:e0183886.PubMedPubMedCentralCrossRef 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:e0183886.PubMedPubMedCentralCrossRef
76.
Zurück zum Zitat Sayinzoga F, Bijlmakers L, van der Velden K, van Dillen J. Severe maternal outcomes and quality of care at district hospitals in Rwanda- a multicentre prospective case-control study. BMC Pregnancy Childbirth. 2017;17:394.PubMedPubMedCentralCrossRef Sayinzoga F, Bijlmakers L, van der Velden K, van Dillen J. Severe maternal outcomes and quality of care at district hospitals in Rwanda- a multicentre prospective case-control study. BMC Pregnancy Childbirth. 2017;17:394.PubMedPubMedCentralCrossRef
77.
Zurück zum Zitat Witteveen T, Bezstarosti H, de Koning I, Nelissen E, Bloemenkamp KW, van Roosmalen J, et al. Validating the WHO maternal near miss tool: comparing high- and low-resource settings. BMC Pregnancy Childbirth. 2017;17:194.PubMedPubMedCentralCrossRef Witteveen T, Bezstarosti H, de Koning I, Nelissen E, Bloemenkamp KW, van Roosmalen J, et al. Validating the WHO maternal near miss tool: comparing high- and low-resource settings. BMC Pregnancy Childbirth. 2017;17:194.PubMedPubMedCentralCrossRef
78.
Zurück zum Zitat Awowole IO, Omitinde OS, Arogundade FA, Bola-Oyebamiji SB, Adeniyi OA. Pregnancy-related acute kidney injury requiring dialysis as an indicator of severe adverse maternal morbidity at a tertiary center in Southwest Nigeria. Eur J Obstet Gynecol Reprod Biol. 2018;225:205–9.PubMedCrossRef Awowole IO, Omitinde OS, Arogundade FA, Bola-Oyebamiji SB, Adeniyi OA. Pregnancy-related acute kidney injury requiring dialysis as an indicator of severe adverse maternal morbidity at a tertiary center in Southwest Nigeria. Eur J Obstet Gynecol Reprod Biol. 2018;225:205–9.PubMedCrossRef
79.
Zurück zum Zitat Benimana C, Small M, Rulisa S. Preventability of maternal near miss and mortality in Rwanda: a case series from the university teaching hospital of Kigali (CHUK). PLoS One. 2018;13:e0195711.PubMedPubMedCentralCrossRef Benimana C, Small M, Rulisa S. Preventability of maternal near miss and mortality in Rwanda: a case series from the university teaching hospital of Kigali (CHUK). PLoS One. 2018;13:e0195711.PubMedPubMedCentralCrossRef
80.
Zurück zum Zitat 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;18:458.PubMedPubMedCentralCrossRef 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;18:458.PubMedPubMedCentralCrossRef
81.
Zurück zum Zitat Iwuh IA, Fawcus S, Schoeman L. Maternal near-miss audit in the Metro West maternity service, Cape town, South Africa: a retrospective observational study. S Afr Med J. 2018;108:171–5.PubMedCrossRef Iwuh IA, Fawcus S, Schoeman L. Maternal near-miss audit in the Metro West maternity service, Cape town, South Africa: a retrospective observational study. S Afr Med J. 2018;108:171–5.PubMedCrossRef
82.
Zurück zum Zitat Jayaratnam S, Kua S, deCosta C, Franklin R. Maternal 'near miss' collection at an Australian tertiary maternity hospital. BMC Pregnancy Childbirth. 2018;18:221.PubMedPubMedCentralCrossRef Jayaratnam S, Kua S, deCosta C, Franklin R. Maternal 'near miss' collection at an Australian tertiary maternity hospital. BMC Pregnancy Childbirth. 2018;18:221.PubMedPubMedCentralCrossRef
83.
Zurück zum Zitat Liyew EF, Yalew AW, Afework MF, Essén 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;18:345.PubMedPubMedCentralCrossRef Liyew EF, Yalew AW, Afework MF, Essén 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;18:345.PubMedPubMedCentralCrossRef
84.
Zurück zum Zitat Oliveira Neto AF, Parpinelli MA, Costa ML, Souza R, Ribeiro do Valle C, Cecatti JG. Exploring epidemiological aspects, distribution of WHO maternal near Miss Criteria, and organ dysfunction defined by SOFA in cases of severe maternal outcome admitted to obstetric ICU: a cross-sectional study. Biomed Res Int. 2018;2018:5714890.PubMedPubMedCentralCrossRef Oliveira Neto AF, Parpinelli MA, Costa ML, Souza R, Ribeiro do Valle C, Cecatti JG. Exploring epidemiological aspects, distribution of WHO maternal near Miss Criteria, and organ dysfunction defined by SOFA in cases of severe maternal outcome admitted to obstetric ICU: a cross-sectional study. Biomed Res Int. 2018;2018:5714890.PubMedPubMedCentralCrossRef
85.
Zurück zum Zitat Tura AK, Zwart J, van Roosmalen J, Stekelenburg J, van den Akker T, Scherjon S. Severe maternal outcomes in eastern Ethiopia: application of the adapted maternal near miss tool. PLoS One. 2018;13:e0207350.PubMedPubMedCentralCrossRef Tura AK, Zwart J, van Roosmalen J, Stekelenburg J, van den Akker T, Scherjon S. Severe maternal outcomes in eastern Ethiopia: application of the adapted maternal near miss tool. PLoS One. 2018;13:e0207350.PubMedPubMedCentralCrossRef
86.
Zurück zum Zitat 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;18:255.PubMedPubMedCentralCrossRef 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;18:255.PubMedPubMedCentralCrossRef
87.
Zurück zum Zitat Yang YY, Fang YH, Wang X, Zhang Y, Liu XJ, Yin ZZ. A retrospective cohort study of risk factors and pregnancy outcomes in 14,014 Chinese pregnant women. Medicine (Baltimore). 2018;97:e11748.CrossRef Yang YY, Fang YH, Wang X, Zhang Y, Liu XJ, Yin ZZ. A retrospective cohort study of risk factors and pregnancy outcomes in 14,014 Chinese pregnant women. Medicine (Baltimore). 2018;97:e11748.CrossRef
88.
Zurück zum Zitat Herklots T, van Acht L, Khamis RS, Meguid T, Franx A, et al. Validity of WHO’s near-miss approach in a high maternal mortality setting. PLoS One. 2019;14:e0217135.PubMedPubMedCentralCrossRef Herklots T, van Acht L, Khamis RS, Meguid T, Franx A, et al. Validity of WHO’s near-miss approach in a high maternal mortality setting. PLoS One. 2019;14:e0217135.PubMedPubMedCentralCrossRef
89.
Zurück zum Zitat Jayaratnam S, Soares M, Jennings B, Thapa AP, Woods C. Maternal mortality and 'near miss' morbidity at a tertiary hospital in Timor-Leste. Aust N Z J Obstet Gynaecol. 2019;59:567–72.PubMedCrossRef Jayaratnam S, Soares M, Jennings B, Thapa AP, Woods C. Maternal mortality and 'near miss' morbidity at a tertiary hospital in Timor-Leste. Aust N Z J Obstet Gynaecol. 2019;59:567–72.PubMedCrossRef
90.
Zurück zum Zitat 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;126:755–62.PubMedCrossRefPubMedCentral 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;126:755–62.PubMedCrossRefPubMedCentral
91.
Zurück zum Zitat Zanardi DM, Parpinelli MA, Haddad SM, Costa ML, Sousa MH, Leite DFB, et al. Adverse perinatal outcomes are associated with severe maternal morbidity and mortality: evidence from a national multicentre cross-sectional study. Arch Gynecol Obstet. 2019;299:645–54.PubMedCrossRef Zanardi DM, Parpinelli MA, Haddad SM, Costa ML, Sousa MH, Leite DFB, et al. Adverse perinatal outcomes are associated with severe maternal morbidity and mortality: evidence from a national multicentre cross-sectional study. Arch Gynecol Obstet. 2019;299:645–54.PubMedCrossRef
92.
Zurück zum Zitat Pedersen GS, Grontved A, Mortensen LH, Andersen AM, Rich-Edwards J. Maternal mortality among migrants in Western Europe: a meta-analysis. Matern Child Health J. 2014;18:1628–38.PubMedCrossRef Pedersen GS, Grontved A, Mortensen LH, Andersen AM, Rich-Edwards J. Maternal mortality among migrants in Western Europe: a meta-analysis. Matern Child Health J. 2014;18:1628–38.PubMedCrossRef
93.
Zurück zum Zitat Urquia ML, Wanigaratne S, Ray JG, Joseph KS. Severe maternal morbidity associated with maternal birthplace: a population-based register study. J Obstet Gynaecol Can. 2017;39:978–87.PubMedCrossRef Urquia ML, Wanigaratne S, Ray JG, Joseph KS. Severe maternal morbidity associated with maternal birthplace: a population-based register study. J Obstet Gynaecol Can. 2017;39:978–87.PubMedCrossRef
94.
Zurück zum Zitat Vangen S, Bodker B, Ellingsen L, Saltvedt S, Gissler M, Geirsson RT, et al. Maternal deaths in the Nordic countries. Acta Obstet Gynecol Scand. 2017;96:1112–9.PubMedCrossRef Vangen S, Bodker B, Ellingsen L, Saltvedt S, Gissler M, Geirsson RT, et al. Maternal deaths in the Nordic countries. Acta Obstet Gynecol Scand. 2017;96:1112–9.PubMedCrossRef
95.
Zurück zum Zitat Knight M, Kurinczuk JJ, Spark P, Brocklehurst P. Inequalities in maternal health: national cohort study of ethnic variation in severe maternal morbidities. BMJ. 2009;338:b542.PubMedPubMedCentralCrossRef Knight M, Kurinczuk JJ, Spark P, Brocklehurst P. Inequalities in maternal health: national cohort study of ethnic variation in severe maternal morbidities. BMJ. 2009;338:b542.PubMedPubMedCentralCrossRef
96.
Zurück zum Zitat Urquia ML, Glazier RH, Mortensen L, Nybo-Andersen AM, Small R, Davey MA, et al. Severe maternal morbidity associated with maternal birthplace in three high-immigration settings. Eur J Pub Health. 2015;25:620–5.CrossRef Urquia ML, Glazier RH, Mortensen L, Nybo-Andersen AM, Small R, Davey MA, et al. Severe maternal morbidity associated with maternal birthplace in three high-immigration settings. Eur J Pub Health. 2015;25:620–5.CrossRef
97.
Zurück zum Zitat Zwart JJ, Jonkers MD, Richters A, Ory F, Bloemenkamp KW, Duvekot JJ, et al. Ethnic disparity in severe acute maternal morbidity: a nationwide cohort study in the Netherlands. Eur J Pub Health. 2011;21:229–34.CrossRef Zwart JJ, Jonkers MD, Richters A, Ory F, Bloemenkamp KW, Duvekot JJ, et al. Ethnic disparity in severe acute maternal morbidity: a nationwide cohort study in the Netherlands. Eur J Pub Health. 2011;21:229–34.CrossRef
98.
Zurück zum Zitat Blagoeva Atanasova V, Arevalo-Serrano J, Antolin Alvarado E, Garcia-Tizon LS. Maternal mortality in Spain and its association with country of origin: cross-sectional study during the period 1999-2015. BMC Public Health. 2018;18:1171.PubMedPubMedCentralCrossRef Blagoeva Atanasova V, Arevalo-Serrano J, Antolin Alvarado E, Garcia-Tizon LS. Maternal mortality in Spain and its association with country of origin: cross-sectional study during the period 1999-2015. BMC Public Health. 2018;18:1171.PubMedPubMedCentralCrossRef
99.
Zurück zum Zitat GBD 2015 Maternal Mortality Collaborators. Global, regional, and national levels of maternal mortality, 1990-2015: a systematic analysis for the global burden of disease study 2015. Lancet. 2016;388:1775–812. GBD 2015 Maternal Mortality Collaborators. Global, regional, and national levels of maternal mortality, 1990-2015: a systematic analysis for the global burden of disease study 2015. Lancet. 2016;388:1775–812.
101.
Zurück zum Zitat Mengistu TS, Turner J, Flatley C, Fox J, Kumar S. Impact of severe maternal morbidity on adverse perinatal outcomes in high-income countries: systematic review and meta-analysis protocol. BMJ Open. 2019;9:e027100.PubMedPubMedCentralCrossRef Mengistu TS, Turner J, Flatley C, Fox J, Kumar S. Impact of severe maternal morbidity on adverse perinatal outcomes in high-income countries: systematic review and meta-analysis protocol. BMJ Open. 2019;9:e027100.PubMedPubMedCentralCrossRef
Metadaten
Titel
Human Development Index of the maternal country of origin and its relationship with maternal near miss: A systematic review of the literature
verfasst von
Santiago García-Tizón Larroca
Francisco Amor Valera
Esther Ayuso Herrera
Ignacio Cueto Hernandez
Yolanda Cuñarro Lopez
Juan De Leon-Luis
Publikationsdatum
01.12.2020
Verlag
BioMed Central
Erschienen in
BMC Pregnancy and Childbirth / Ausgabe 1/2020
Elektronische ISSN: 1471-2393
DOI
https://doi.org/10.1186/s12884-020-02901-3

Weitere Artikel der Ausgabe 1/2020

BMC Pregnancy and Childbirth 1/2020 Zur Ausgabe

Hirsutismus bei PCOS: Laser- und Lichttherapien helfen

26.04.2024 Hirsutismus Nachrichten

Laser- und Lichtbehandlungen können bei Frauen mit polyzystischem Ovarialsyndrom (PCOS) den übermäßigen Haarwuchs verringern und das Wohlbefinden verbessern – bei alleiniger Anwendung oder in Kombination mit Medikamenten.

ICI-Therapie in der Schwangerschaft wird gut toleriert

Müssen sich Schwangere einer Krebstherapie unterziehen, rufen Immuncheckpointinhibitoren offenbar nicht mehr unerwünschte Wirkungen hervor als andere Mittel gegen Krebs.

Weniger postpartale Depressionen nach Esketamin-Einmalgabe

Bislang gibt es kein Medikament zur Prävention von Wochenbettdepressionen. Das Injektionsanästhetikum Esketamin könnte womöglich diese Lücke füllen.

Bei RSV-Impfung vor 60. Lebensjahr über Off-Label-Gebrauch aufklären!

22.04.2024 DGIM 2024 Kongressbericht

Durch die Häufung nach der COVID-19-Pandemie sind Infektionen mit dem Respiratorischen Synzytial-Virus (RSV) in den Fokus gerückt. Fachgesellschaften empfehlen eine Impfung inzwischen nicht nur für Säuglinge und Kleinkinder.

Update Gynäkologie

Bestellen Sie unseren Fach-Newsletter und bleiben Sie gut informiert – ganz bequem per eMail.