Abstract
BackgroundAlthough most of maternal deaths are preventable, maternal mortality reduction programs have not been completely successful. As targeting individuals alone does not seem to be an effective strategy to reduce maternal mortality (Millennium Development Goal 5), the present study sought to reveal the role of many distant macrostructural factors affecting maternal mortality at the global level.MethodsAfter preparing a global dataset, 439 indicators were selected from nearly 1800 indicators based on their relevance and the application of proper inclusion and exclusion criteria. Then Pearson correlation coefficients were computed to assess the relationship between these indicators and maternal mortality. Only indicators with statistically significant correlation more than 0.2, and missing values less than 20% were maintained. Due to the high multicollinearity among the remaining indicators, after missing values analysis and imputation, factor analysis was performed with principal component analysis as the method of extraction. Ten factors were finally extracted and entered into a multiple regression analysis.ResultsThe findings of this study not only consolidated the results of earlier studies about maternal mortality, but also added new evidence. Education (std. B = −0.442), private sector and trade (std. B = −0.316), and governance (std. B = −0.280) were found to be the most important macrostructural factors associated with maternal mortality. Employment and labor structure, economic policy and debt, agriculture and food production, private sector infrastructure investment, and health finance were also some other critical factors. These distal factors explained about 65% of the variability in maternal mortality between different countries.ConclusionDecreasing maternal mortality requires dealing with various factors other than individual determinants including political will, reallocation of national resources (especially health resources) in the governmental sector, education, attention to the expansion of the private sector trade and improving spectrums of governance. In other words, sustainable reduction in maternal mortality (as a development indicator) will depend on long-term planning for multi-faceted development. Moreover, trade, debt, political stability, and strength of legal rights can be affected by elements outside the borders of countries and global determinants. These findings are believed to be beneficial for sustainable development in Post-2015 Development Agenda.Electronic supplementary materialThe online version of this article (doi:10.1186/s12992-015-0087-y) contains supplementary material, which is available to authorized users.
Highlights
Most of maternal deaths are preventable, maternal mortality reduction programs have not been completely successful
As the above-mentioned systematic review highlighted the need for knowledge about the macrostructural causes of maternal mortality [7], the present study investigated the relationship between some macrostructural factors and maternal mortality at the global level in 2010
In order to obtain global data, we selected the following databases based on their data availability and relation to our research topic: 1- World Development Indicators (WDI): It is the primary World Bank collection of development indicators gathered from officially recognized international sources
Summary
Most of maternal deaths are preventable, maternal mortality reduction programs have not been completely successful. Maternal mortality is widely accepted as a key indicator of health and socioeconomic development [1]. It is a reflection of the whole national health system and represents the outcome of its cons and pros along with its other characteristics such as intersectoral collaboration, transparency and disparities. Beyond these, it can illustrate even the sociocultural, political and economic philosophy of a society. Improving maternal health and reducing maternal mortality ratio (MMR) by 75% between 1990 and 2015 have been defined as the Millennium Development Goal 5 (MDG 5A) [2]. The MDGs cannot be successfully practiced due to data gaps, inconsistent indicators, and frequent revisions [5]
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