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Background: For countries to contribute to Sustainable Development Goal 3.1 of reducing the global maternal mortality ratio (MMR) to less than 70 per 100,000 live births by 2030, identifying the drivers of maternal mortality is critically important. The ability of countries to identify the key drivers is however hampered by the lack of data sources with sufficient observations of maternal death to allow a rigorous analysis of its determinants. This paper overcomes this problem by utilising census data. In the context of Indonesia, we merge individual-level data on pregnancy-related deaths and households’ socio-economic status from the 2010 Indonesian population census with detailed data on the availability and quality of local health services from the Village Census. We use these data to test the hypothesis that health service access and quality are important determinants of maternal death and explain the differences between high maternal mortality and low maternal mortality provinces. Methods: The 2010 Indonesian Population Census identifies 8075 pregnancy-related deaths and 5,866,791 live births. Multilevel logistic regression is used to analyse the impacts of demographic characteristics and the existence of, distance to and quality of health services on the likelihood of maternal death. Decomposition analysis quantifies the extent to which the difference in maternal mortality ratios between high and low performing provinces can be explained by demographic and health service characteristics. Findings: Health service access and characteristics account for 23% (CI: 17.2% to 28.5%) of the difference in maternal mortality ratios between high and low-performing provinces. The most important contributors are the number of doctors working at the community health centre (8.6%), the number of doctors in the village (6.9%) and distance to the nearest hospital (5.9%). Distance to health clinics and the number of midwives at community health centres and village health posts are not significant contributors, nor is socio-economic status. If the same level of access to doctors and hospitals in lower maternal mortality Java-Bali was provided to the higher maternal mortality Outer Islands of Indonesia, our model predicts 44 deaths would be averted per 100,000 pregnancies. Conclusion: Indonesia has employed a strategy over the past several decades of increasing the supply of midwives as a way of decreasing maternal mortality. While there is evidence of reductions in maternal mortality continuing to accrue from the provision of midwife services at village health posts, our findings suggest that further reductions in maternal mortality in Indonesia may require a change of focus to increasing the supply of doctors and access to hospitals. If data on maternal death is collected in a subsequent census, future research using two waves of census data would prove a useful validation of the results found here. Similar research using census data from other countries is also likely to be fruitful. [ABSTRACT FROM AUTHOR]

Background: Inadequate water and sanitation during childbirth are likely to lead to poor maternal and newborn outcomes. This paper uses existing data sources to assess the water and sanitation (WATSAN) environment surrounding births in Tanzania in order to interrogate whether such estimates could be useful for guiding research, policy and monitoring initiatives. Methods: We used the most recent Tanzania Demographic and Health Survey (DHS) to characterise the delivery location of births occurring between 2005 and 2010. Births occurring in domestic environments were characterised as WATSAN-safe if the home fulfilled international definitions of improved water and improved sanitation access. We used the 2006 Service Provision Assessment survey to characterise the WATSAN environment of facilities that conduct deliveries. We combined estimates from both surveys to describe the proportion of all births occurring in WATSAN-safe environments and conducted an equity analysis based on DHS wealth quintiles and eight geographic zones. Results: 42.9% (95% confidence interval: 41.6%–44.2%) of all births occurred in the woman's home. Among these, only 1.5% (95% confidence interval: 1.2%–2.0%) were estimated to have taken place in WATSAN-safe conditions. 74% of all health facilities conducted deliveries. Among these, only 44% of facilities overall and 24% of facility delivery rooms were WATSAN-safe. Combining the estimates, we showed that 30.5% of all births in Tanzania took place in a WATSAN-safe environment (range of uncertainty 25%–42%). Large wealth-based inequalities existed in the proportion of births occurring in domestic environments based on wealth quintile and geographical zone. Conclusion: Existing data sources can be useful in national monitoring and prioritisation of interventions to improve poor WATSAN environments during childbirth. However, a better conceptual understanding of potentially harmful exposures and better data are needed in order to devise and apply more empirical definitions of WATSAN-safe environments, both at home and in facilities. [ABSTRACT FROM AUTHOR]