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Factors Contributing to Maternal and Child Mortality Reductions in 146 Low- and Middle-Income Countries between 1990 and 2010

Monday, 25th of January 2016

“Economic growth and good governance, while valuable ends in themselves, were only part of a broad area of health determinants whose progress improved child health. Improvements in factors from diverse sectors as the environment, education, the health system, fertility, and women´s empowerment all contributed significantly to mortality reductions. These results point to the importance of a multi-sector approach to improving child health and thus aligns with the findings of country case studies, qualitative analysis, and literature review from the larger MDGs 4 and 5 Success Factors Study.”

Factors Contributing to Maternal and Child Mortality Reductions in 146 Low- and Middle-Income Countries between 1990 and 2010

• David M. Bishai, 
• Robert Cohen, 
• Y. Natalia Alfonso, 
• Taghreed Adam, 
• Shyama Kuruvilla, 
• Julian Schweitzer

Abstract

Introduction

From 1990–2010, worldwide child mortality declined by 43%, and maternal mortality declined by 40%. This paper compares two sources of progress: improvements in societal coverage of health determinants versus improvements in the impact of health determinants as a result of technical change.

Methods

This paper decomposes the progress made by 146 low- and middle-income countries (LMICs) in lowering childhood and maternal mortality into one component due to better health determinants like literacy, income, and health coverage and a second component due to changes in the impact of these health determinants. Health determinants were selected from eight distinct health-impacting sectors. Health determinants were selected from eight distinct health-impacting sectors. Regression models are used to estimate impact size in 1990 and again in 2010. Changes in the levels of health determinants were measured using secondary data.

Findings

The model shows that respectively 100% and 89% of the reductions in maternal and child mortality since 1990 were due to improvements in nationwide coverage of health determinants. The relative share of overall improvement attributable to any single determinant varies by country and by model specification. However, in aggregate, approximately 50% of the mortality reductions were due to improvements in the health sector, and the other 50% of the mortality reductions were due to gains outside the health sector.

Conclusions

Overall, countries improved maternal and child health (MCH) from 1990 to 2010 mainly through improvements in the societal coverage of a broad array of health system, social, economic and environmental determinants of child health. These findings vindicate efforts by the global community to obtain such improvements, and align with the post-2015 development agenda that builds on the lessons from the MDGs and highlights the importance of promoting health and sustainable development in a more integrated manner across sectors.

 

Citation: Bishai DM, Cohen R, Alfonso YN, Adam T, Kuruvilla S, Schweitzer J (2016) Factors Contributing to Maternal and Child Mortality Reductions in 146 Low- and Middle-Income Countries between 1990 and 2010. PLoS ONE 11(1): e0144908. doi:10.1371/journal.pone.0144908

Introduction

Millennium Development Goal (MDG) 4 was to reduce child mortality by two thirds from 1990–2015 and MDG5 was to reduce maternal mortality by three quarters over the same time period. Child mortality has decreased by 49% and maternal mortality has decreased 45% worldwide since 1990, but the pace of reduction has varied across countries and 6.6 million children and 300,000 mothers continue to die every year from preventable causes [1–6]. The pace of mortality decline is not constant and its relationship to economic progress, political progress, and health system progress has varied over time and from place to place. Countries with similar geography, wealth, U5MR and MMR levels have shown wide differences in health progress over the last 40 years[7]. Several studies have been devoted to systematically accounting for past progress [8–11]. The direct relationship from maternal and child health (MCH) improvements to the alleviation of poverty has long been recognized [12]. Other key social determinants of health include better schooling [11], good governance [9], clean water [13], and less social inequality [14].

Health policy obviously involves scaling up of health sector based interventions, but health policy also involves policies to improve education, governance, the economy, the environment, and other social determinants of health. The impact of health interventions and social and environmental determinants (health determinants) on mortality has been known to change over time [15]. Preston´s seminal paper showed that changes in public health technologies between 1965 and 1975 made each dollar of national income growth a more important contributor to infant mortality over the decade. That particular decade of time passage from 1965 to 1975 was shown to have a particularly large effect on changing the β coefficient on GDP in determining child mortality. Obviously, it was not ten orbits around the sun that made economic growth more likely to lower mortality than before. Rather, this decade was marked by low income countries´ adoption of recent fruits of new scientific progress in sanitation, antibiotics, vaccines, and modern obstetrics. Public health progress in the 1960s made it possible to use new income in ways that were not present a decade earlier and made GDP a more impactful social determinant of health. Since Preston´s seminal paper, there has been little systematic study of whether the impact factors of macro health determinants is changing.

It is a good time to raise the question because the last 25 years of mortality declines have been paralleled by progress in coverage of most health determinants as well as progress in health technology (e.g. new treatments for AIDS, malaria, new vaccines, etc.). So it is difficult to know whether mortality declines are due primarily to higher coverage of health determinants or to improvements in the impact of health determinants. We focus on two co-contributing explanations for the decline in maternal and child mortality: 1) improvements in the absolute levels of key health determinants; 2) improvements in the impact of each health determinant since 1990, which includes secular progress due to time and diffusion of best practices. Health policies have focused on increasing the levels of social and intervention-based health determinants as well as getting more from each health determinant. Doing both is important. This paper asks how much of past improvements are due to higher levels of health determinants vs. improvements in the health impact per unit of change in a health determinant.

By examining country performance in MCH over the past twenty years we can assess some of the major factors responsible for the observed progress. A similar analysis was undertaken which found that maternal education, HIV, fertility, income and time accounted for 99% of the decline in child mortality [1]. Our study expands this analysis by examining a greater variety of health determinants and also assessing maternal mortality. Our goal in this paper is to assess how much of the world´s progress on MDG 4 and 5 has been due to increases in well-known determinants of MCH and how much progress has been due to changes in the impact of these determinants from 1990–2010. We decompose the magnitude of the observed improvement due to each of these possible explanations. The results can help policy-makers prioritize between strategies that make the levels of things like schooling, health spending, and good governance increase versus strategies that make schooling more likely to impact health, that make health spending more efficient, and that make governance improvements affect the health sector more positively.

. . .

Discussion

In the period after World War II, low and middle income countries had the luxury of facing a world of technical progress. Mortality rates could fall substantially without the need for economic growth because the impact factor of GDP on mortality was dramatically improving thanks to new discoveries in public health. Just riding on technology could save more of the people who were already covered by the modern social system without the necessity and expense of expanding the umbrella. The twenty years between 1990 and 2010 brought even more wonderful new discoveries in treatments for HIV, new vaccines, and new innovations in sanitation and health communication, but there has also been basic progress in expanding the umbrella of coverage in this period. This paper has measured the relative contributions of expanding basic factors that lead to health vs. progress in making those factors more impactful. There is a decisive answer. Improvement in the levels of health determinants explains nearly all of the progress on U5MR and MMR. For MMR the impact factors for social determinants have gotten smaller between 1990 and 2010. For U5MR, impact factor improvement accounts for only 11% of the reductions between 1990 and 2010.

No single health input dominated as the cause of mortality decline. Rather, the summation of improvements in many different policy areas is what saved lives. Economic growth and good governance, while valuable ends in themselves, were only part of a broad area of health determinants whose progress improved child health. Improvements in factors from diverse sectors as the environment, education, the health system, fertility, and women´s empowerment all contributed significantly to mortality reductions. These results point to the importance of a multi-sector approach to improving child health and thus aligns with the findings of country case studies, qualitative analysis, and literature review from the larger MDGs 4 and 5 Success Factors Study [23]. They also suggest that the eight policy areas included in our model—the same ones emphasized by successful LMICs and development partners—are those of great importance to MCH. Our findings vindicate efforts to address a multisectoral set of key health determinants as a path to reach the health MDGs.

We considered whether what we interpreted as “multi-sectoral” progress was really just a proxy for economic growth and good or improved governance driving progress across all other sectors. We find that these two factors by themselves were only minor predictors of either gains in child health or in the other factor levels that drove child health. As a second test of this finding, the OB decomposition similarly showed that economic growth accounted for an average of 20% of child health gains and 31% of maternal health gains across all models tested.

All models are subject to limitations. Concerns about endogeneity and unobservable confounders are unavoidable in cross-country regressions. There are limitations related to the errors induced in the way MMR and U5MR have been constructed based on models. However, we attempt to mitigate these concerns by testing over 1000 models, including both unimputed data and imputed data. The findings for each policy area were similar whether missing data was filled in by imputation or not, with the largest differences noted for highly imputed variables. Many cross-country regressions are of dubious value because their results hinge on model specification—on the particular combination of included variables. Our findings were robust across 600 combinations of health determinants.

Still, the findings should be interpreted with care. Variables within and even between policy areas are highly correlated, and interchanging one for another usually did not alter significantly the contribution of that policy area. Thus, readers should not examine the results to find support for any single particular factor as being able to deliver health gains. We refrain from drawing specific conclusions about the causal significance of individual coefficients on individual health determinants. It is also possible that the contribution of different health determinants to MCH varies by region, and we did not test for that here because the sample size is only 146 countries.

The main conclusions that can be drawn from this analysis are that 1) it is the improved levels more so than improvements in the impact per unit of a combination of proven health determinants that contributed to declining mortality, 2) mortality decline was not solely due to GDP growth, but was independently lifted by multisectoral progress. This analysis should not be taken to discount the importance of improvements in specific health conditions. Our analytical approach used U5MR and MMR as summary indicators of health. Progress on these specific health conditions obviously matters substantially for U5MR and MMR, but decomposing that progress would require a separate analysis that is out of our scope.

Looking ahead to a post-2015 agenda for Sustainable Development Goals these results indicate that progress on the health of mothers and children will depend on multiple underlying determinants improving at the same time. Countries and donors must invest in a multi-faceted approach across multiple policy areas to improve MCH. Countries cannot count on technical progress to make existing levels of health determinants more impactful on human health. A broad array of both health sector interventions and social determinants of health need to improve together. The post-2015 development agenda with an emerging emphasis on multi-sector collaboration offers an unprecedented opportunity to build on the lessons from the MDGs and to promote health and sustainable development in a more integrated manner.

Supporting Information

S1 Appendix. Supporting Information.

Addition details about the methods (Methods A). Sensitivity analysis to show how results change for birth weighting vs. population weighting (Table A) and for imputation vs. no imputation (Tables B and C) and to models using zero-inflated Poisson models (Table D). Additional detailed results about how much each variable changed between 1990 and 2010 (Figures A and B). Stata code used in the analysis (Text A).

doi:10.1371/journal.pone.0144908.s001

(DOCX)

Acknowledgments

This analysis is part of the Success Factors for Women´s and Children´s Health Study supported by the Partnership for Maternal, Newborn & Child Health (PMNCH), Alliance for Health Policy and Systems Research (AHPSR), the World Bank, and the World Health Organization.

Author Contributions

Conceived and designed the experiments: DMB. Analyzed the data: DMB RC YNA. Wrote the paper: DMB RC YNA TA SK JS. Obtained the statistical data: DMB RC YNA.

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