Table 1. Specifications of studies about prevalence Maternal Near Miss based on the WHO approach in world .
| Author | Year | Country | Continent | Design | Sample (LB) | MNM | MD | MNM/1000 | JBI Score |
| Souza9 | 2012 | Brazil | South America | Cross-sectional | 82 388 | 770 | 140 | 9/34 | 17 |
| Jabir10 | 2013 | Iraq | Asia | Cross-sectional | 25 472 | 129 | 16 | 5/06 | 16 |
| Nelissen11 | 2013 | Tanzania | Africa | Cross-sectional | 9152 | 216 | 32 | 23/6 | 17 |
| Ps12 | 2013 | India | Asia | Cross-sectional | 7390 | 131 | 17/80 | 18 | |
| Rana13 | 2013 | Nepal | Asia | Cohort | 41 676 | 157 | 3/80 | 15 | |
| Tunçalp14 | 2013 | Ghana | Africa | Cohort | 3438 | 94 | 37 | 28/60 | 17 |
| Setia15 | 2013 | Indonesia | Asia | Cross-sectional | 14 559 | 341 | 23/42 | 16 | |
| Dias16 | 2014 | Brazil | South America | Cross-sectional | 2 300 000 | 10/21 | 16 | ||
| Galvão17 | 2014 | Brazil | South America | Cross-sectional | 16243 | 77 | 17 | 5/80 | 15 |
| Luexay18 | 2014 | Laos | Asia | Cohort | 1215 | 11 | 2 | 9/80 | 15 |
| Pandey19 | 2014 | India | Asia | Case-control | 5273 | 633 | 247 | 120/04 | 14 |
| Tahira20 | 2014 | Pakistan | Asia | Cross-sectional | 1000 | 67 | 67 | 17 | |
| Bakshi21 | 2015 | India | Asia | Cross-sectional | 688 | 51 | 10 | 5/12 | 18 |
| Bashour22 | 2015 | Egypt* | Africa | Cross-sectional | 9063 | 71 | 6 | 7/83 | 17 |
| Madeiro23 | 2015 | Brazil | South America | Cohort | 5841 | 56 | 10 | 9/60 | 18 |
| Mazhar24 | 2015 | Pakistan | Asia | Cross-sectional | 13 175 | 94 | 38 | 7/13 | 15 |
| Menezes25 | 2015 | Brazil | South America | Cross-sectional | 20 435 | 77 | 17 | 3/76 | 16 |
| Oliveira26 | 2015 | Brazil | South America | Cross-sectional | 2055 | . | 12/8 | 17 | |
| Rulisa27 | 2015 | Rwanda | Africa | Cross-sectional | 1739 | 13 | 8 | 14 | |
| Tan28 | 2015 | China | Asia | Cross-sectional | 34 547 | 8 | 5 | 2/3 | 15 |
| Abha29 | 2016 | India | Asia | Cohort | 13 895 | 211 | 102 | 15/18 | 17 |
| Cecatti20 | 2016 | Brazil | South America | Cross-sectional | 82 388 | 770 | 140 | 9/34 | 17 |
| De Mucio31 | 2016 | Latin America | South America | Cross-sectional | 3196 | 37 | 12/3 | 16 | |
| Ghazivakili32 | 2016 | Iran | Asia | Cross-sectional | 38 663 | 192 | 7 | 4/97 | 16 |
| Kalisa33 | 2016 | Rwanda | Africa | Cohort | 3994 | 86 | 13 | 21/51 | 16 |
| Mohammadi34 | 2016 | Iran | Asia | Case-control | 12 965 | 82 | 12 | 6/30 | 15 |
| Nakimuli35 | 2016 | Uganda | Africa | Cohort | 25 840 | 695 | 130 | 8/42 | 15 |
| Nansubuga36 | 2016 | Uganda | Africa | Cross-sectional | 1557 | 434 | 287/70 | 18 | |
| Norhayati37 | 2016 | Malaysia | Asia | Cross-sectional | 21 579 | 395 | 2 | 2/20 | 15 |
| Oladapo38 | 2016 | Nigeria | Africa | Cross-sectional | 91 724 | 1451 | 998 | 15/81 | 16 |
| O'Malley39 | 2016 | Ireland | Europe | Cross-sectional | 4502 | 16 | 0 | 3/55 | 17 |
| Parmar40 | 2016 | India | Asia | Cross-sectional | 1929 | 46 | 18 | 23/85 | 18 |
| Rathod41 | 2016 | India | Asia | Cohort | 21 992 | 161 | 66 | 7/56 | 17 |
| Ray42 | 2016 | India | Asia | Cross-sectional | 4800 | 220 | 17 | 45/83 | 16 |
| Tanimia43 | 2016 | Papua New Guinea | Oceania | Cross-sectional | 13 338 | 122 | 9 | 9/1 | 16 |
| Witteveen44 | 2016 | Netherlands | Europe | Cross-sectional | 371 623 | 1179 | 3/17 | 15 | |
| Bolnga45 | 2017 | Papua New Guinea | Oceania | Cohort | 6019 | 153 | 10 | 25/4 | 16 |
| Chandak46 | 2017 | India | Asia | Cross-sectional | 13 186 | 137 | 10/38 | 16 | |
| Goldenberg47 | 2017 | Zambia** | Africa | Cross-sectional | 122 707 | 4866 | 39/65 | 15 | |
| Liyew48 | 2017 | Ethiopia | Africa | Cross-sectional | 29 697 | 238 | 8/01 | 15 | |
| Mbachu49 | 2017 | Nigeria | Africa | Cross-sectional | 262 | 52 | 5 | 198 | 15 |
| Serruya50 | 2017 | Latin America | South America | Cross-sectional | 712 081 | 21985 | 1028 | 31/50 | 16 |
| Awowole51 | 2018 | Nigeria | Africa | Case-control | 11 242 | . | 3/8 | 15 | |
| Chikadaya52 | 2018 | Zimbabwe | Africa | Cohort | 11 871 | 110 | 13 | 9/3 | 16 |
| Iwuh53 | 2018 | South Africa | Africa | Case-control | 19 222 | 112 | 13 | 5/83 | 17 |
| Oppong54 | 2018 | Ghana | Africa | Cross-sectional | 8433 | 288 | 62 | 34/2 | 17 |
| Woldeyes55 | 2018 | Ethiopia | Africa | Cross-sectional | 2737 | 138 | 24 | 50/42 | 16 |
| Yang56 | 2018 | China | Asia | Cohort | 14 014 | 265 | 18/90 | 17 | |
| Deepti Gupta57 | 2018 | India | Asia | Cohort | 4533 | 74 | 15 | 16/32 | 16 |