Table 1 General study characteristics
No | Study author & year of publication | Country | Income | Data collection period | Coverage | Study design | Comparator | Method of identifying maternal deaths | Study risk of bias | Meta analysise |
|---|---|---|---|---|---|---|---|---|---|---|
1 | (AIHWs, 2020) [4] | Australia | High | 2018 | National – population based | Cross-sectional | CRVS | CEMDa | Low | A, F |
2 | (Berdzuli et al., 2020) [7] | Georgia | High | 2012 | National – population based | Cross-sectional | CRVS | Triangulation of data from different sources | Low | A, E, F |
3 | (Baeva et al., 2018) [6] | USA | High | 2012 | Subnational – population based | Cross-sectional | CRVS | Review of death records and data linkage | Medium | NA |
4 | (Boutin et al., 2021) [9] | Canada | High | 2013—2017 | Subnational – facility based | Cross-sectional | FBSS | Review of electronic medical records | Medium | NA |
5 | (Catalano et al., 2021) [11] | USA | High | 2016 | Subnational – population based | Cross-sectional | Pregnancy checkbox on death certificates | Data linkages (birth and foetal death registers) | Medium | NA |
6 | (Davis et al., 2017) [12] | USA | High | 1987—2012 | National – facility based | Cross-sectional | MMR in 1978 to 2008 (before introduction of pregnancy checkbox) | Review of national statistics records of mortality and natality files | High | NA |
7 | (Deneux-Tharaux et al., 2005) [13] | USA, Finland and France | High | 1999—2000 | Subnational – population based | Cross-sectional | CRVS | Data linkage (birth and foetal death registers) | Low | F |
8 | (Donati et al., 2018) [15] | Italy | High | 2006—2012 | Subnational—facility based | Cross-sectional | CRVS | Data linkages (pregnancy or pregnancy-related hospitalizations records) | Medium | NA |
9 | (Horon, 2005) [19] | USA | High | 1993—2001 | Subnational – population based | Nested case–control | CRVS | Data linkages (birth and foetal death registers) | Low | A, D, F |
10 | (Laura et al., 2020) [24] | Switzerland | High | 2005—2014 | Subnational – population based | Cross-sectional | CRVS | Data linkages (birth and foetal death registers) | Low | A, B, F |
11 | (MBRRACE-UK, 2020) [26] | United Kingdom | High | 2016—2018 | National – population based | Cross-sectional | CRVS | CEMD | Low | A, F |
12 | (Sesmero et al., 2016) [34] | Spain | High | 2012 | Subnational—facility based | Cross-sectional | FBSS | Questionnaire filled by heads of hospitals asking about maternal deaths information | Medium | NA |
13 | (O’Hare et al., 2020) [30] | Ireland | High | 2016—2018 | National – population based | Cross-sectional | CRVS | CEMD | Low | NA |
14 | (Vangen et al., 2017) [37] | Denmark, Norway, Finland, Iceland, Sweden | High | 2005—2013 | National – population based | Cross-sectional | CRVS | Triangulating data from different sources | Low | A, F |
15 | (Abalos et al., 2019) d [1] | Argentina | Upper-Middle | 2014 | National – facility based | Cross-sectional | CRVS | Review of clinical records | Medium | A, B, E, F |
16 | (Bess Constantén et al., 2018) d [8] | Cuba | Upper-Middle | 2013 | national – population-based | Cross-sectional | CRVS | Review of clinical records | Low | A, B, F |
17 | (Kodan et al., 2017) [21] | Suriname | Upper-Middle | 2010–2014 | National – population based | Cross-sectional | CRVS | RAMOSb | Low | A, E, F |
18 | (Lin et al., 2019a) [25] | China, Taiwan Province of China | Upper-Middle | 2010—2017 | Subnational – population based | Cross-sectional | Pregnancy checkbox on death certificates | Review of pregnancy checkbox field on death certificate | Medium | NA |
19 | (Wu et al., 2015) [47] | China, Taiwan Province of China | Upper-Middle | 2000—2009 | Subnational – population based | Cross-sectional | CRVS | Data linkage of CRVS with insurance claims data | Medium | A, E, F |
20 | (Abouchadi et al., 2018) [2] | Morocco | Lower-Middle | Jan 2013 – Sept 2014 | Subnational – population based | Cross-sectional | CRVS | RAMOS | Low | A, B, C, D, F |
21 | (Anwar et al., 2018) [5] | Pakistan | Lower-Middle | Jun 2015 – May 2016 | Subnational – population based | Cross-sectional | MMR from the 1.5 years before the study | follow up of pregnant women until 42 days post termination of pregnancy | High | NA |
22 | (Boyd et al., 2017) [10] | Haiti | Low | 2014—2015 | Subnational – facility based | Cross-sectional | FBSS | Review of clinical records and dossiers | High | A, F |
23 | (Garces et al., 2012) [16] | Philippines | Lower-Middle | 2008 | Subnational – population based | Cross-sectional | CRVS | RAMOS | Low | A, B, F |
24 | (Kodio et al., 2002) [22] | Senegal | Lower-Middle | 1984—1995 | Subnational – population based | Cross-sectional | HDSS | HDSS | Low | A, F |
25 | (Mswia et al., 2003) [27] | Tanzania | Lower-Middle | July 1993 – Dec 1999 | Subnational – population based | Cross-sectional | HDSS | An active reporting system based on a network of respected individuals within each community | Medium | A, F |
26 | (Mwaniki et al., 2020) [29] | Kenya | Lower-Middle | Jan 2015 – June 2018 | Subnational – facility based | Cross-sectional | FBSS | MDSRc | High | A, F |
27 | (Qomariyah et al., 2020) [32] | Indonesia | Lower-Middle | 2016 | Subnational – population based | Cross-sectional | DHIS | review of routine HIS in addition to asking village informants | Low | A, B, C, D, F |
28 | (Songane & Bergström, 2002) [35] | Mozambique | Lower-Middle | Aug 1996 – July 1997 | Subnational – population based | Cross-sectional | DHIS | Triangulation from different data sources | Low | A, F |
29 | (Zakariah et al., 2009) [48] | Ghana | Lower-Middle | 2002 | Subnational – population based | Cross-sectional | DHIS | RAMOS | Low | A, C, F |