Reducing maternal mortality is a global health priority. The Sustainable Development Goals (SDGs) aim for a reduction of the maternal mortality ratio (MMR) to below 70 per 100,000 live births by 2030. If the SDGs are met by 2030, the lives of an estimated 1.6 million mothers will be saved. Maternal mortality is not only a health indicator, but also a key indicator of country development because maternal deaths have an important social and economic impact. Maternal mortality disproportionately affects women in low and lower-middle income countries (LMICs) where most of the maternal deaths are from preventable causes.
Despite the majority of maternal deaths occurring in LMICs (MMR of 479 for low income countries compared to 41 in high income countries), robust systems for data collection and health indicator tracking are lacking. This makes reliable tracking of MMRs difficult, despite global attention to the problem. Also, controversy still exists regarding the optimal way to monitor maternal mortality. In areas where health registries are lacking, the MMR can be estimated through a series of modelling strategies which rely on local data sources. When data are sparse, such as in LMICs, these strategies rely on complex models with several poorly defined variables and weakly justified assumptions that lead to low precision in the final results. Therefore, primary datasets that reliably track the MMR in LMICs are urgently needed to provide a more robust evidence base for evaluating and tracking maternal mortality.
In this manuscript, we describe maternal mortality in 6 LMICs from a defined geographic, community-based, prospectively collected maternal health registry that captures data on all women delivering within or outside of facilities. This longitudinal dataset describes maternal deaths over a 9-year period. We examine maternal characteristics associated with maternal deaths, causes of maternal death and evaluate site specific trends in the MMR over time.
By: Bauserman M, Thorsten V, Nolen T, Patel A, Patterson J, Lokangaka A et al.