Social inequality in infant mortality: What explains variation across low and middle income countries?
Introduction
Improving the health outcomes of children has been the central focus of many public health programs (Simon et al, 2001) in the world over the last three decades. To date, there have been several international goals set out to improve child health. The Declaration of Alma Ata (1978) aimed to reduce infant mortality rates (IMR) to less than 50 death per 1000 live-births through a global strategy for "Health for All" by the Year 2000 (World Health Organization, 1981). Subsequently, the 1990 World Summit for Children Programme of Action and the Programme of Action of the 1994 International Conference on Population and Development (ICPD) encouraged countries to reduce infant mortality. Another international effort targeting infant mortality is the fourth goal of the United Nations Millennium Development Goals (MDG 4). The MDG 4 is set to reduce IMRs between 1990 and 2015 by two thirds.
Despite the remarkable improvement in child health over the past three decades, infant mortality still remains a central issue in the global health agenda. There is extremely uneven progress towards reducing infant mortality across countries and regions (World Bank, 2012a, You et al., 2011), Furthermore, there is a growing body of global research demonstrating a social gradient in children's health outcome within countries: children belonging to lower compared to higher socioeconomic status (SES) households have a lower probability of surviving to their first birthday (Adler and Ostrove, 1999, Adler et al., 1994, Arntzen and Nybo Andersen, 2004, Bakketeig et al., 1993, Finch, 2003, Hobcraft et al., 1984, Hosseinpoor et al., 2006). The vast majority of these deaths are preventable and inequitable (Hosseinpoor et al., 2006, WHO/UNICEF, 2012, WHO/World Bank, 2002).
The monitoring of socioeconomic inequalities in child health within and among countries has an important role in gauging progress toward the commitments made by decision makers to reduce inequalities in infant mortality (Victora et al, 2003). However, measuring socioeconomic inequalities alone is not enough to secure sustainable changes. Identifying the factors explaining the concentration of infant mortality among children born into lower SES households is essential to implementing effective policies to redress these inequalities (Hosseinpoor et al., 2006, Victora et al., 2003).
Although inequalities in health have recently received substantial attention in the economics and public health literature (Costa-Font and Hernández-Quevedo, 2012, Gwatkin, 2000, Kawachi et al., 2002, Marmot and Wilkinson, 2006, O'Donnell et al., 2008, Wagstaff et al., 1991), few studies (Hosseinpoor et al., 2006, Monteiro et al., 2010, Pradhan and Arokiasamy, 2010, Vapattanawong et al., 2007, Wang, 2003, Zere et al., 2007) have measured socioeconomic inequalities in infant mortality using a summary measure such as the concentration index, which accounts for inequality across the entire socioeconomic distribution. Therefore, this study aimed to provide a comprehensive and comparative analysis of social inequality in infant mortality across 53 low-and-middle-income countries (LMICs) using the most recent nationally representative samples of live births collected through the Demographic Health Surveys (DHS). In addition, following the conceptual framework developed by Houweling and Kunst (2010) we used meta-regression to analyze whether inequalities in proximate risk factors for infant mortality were associated with the magnitude of social inequality in infant mortality across countries.
Section snippets
Data
The data for this study were obtained from the Demographic Health Surveys (DHS). The DHS typically are cross-sectional surveys of nationally representative household samples for selected LMICs (Corsi, Neuman, Finlay, & Subramanian, 2012). The DHS surveys collect comparable information concerning a wide range of topics, with a special focus on maternal and child health (Rutstein & Rojas, 2006). These surveys are an important source of comparative population health data in LMICs due to their data
Infant mortality
Table 2 reports the sample size, GDP per capita, and overall and gender-specific IMRs for each county. Rates of infant mortality ranged from less than 20 deaths per 1000 births in Moldova, Armenia, Ukraine and Colombia to greater than 100/1000 births in some sub-Saharan African countries, including Chad, Guinea, Mozambique and Mali. Gender differentials in infant mortality varied widely across countries, with rates generally higher for males than females. As illustrated in Fig. 2, there were
Discussion and conclusion
We measured social inequalities in infant health by estimating wealth-based relative and absolute concentration indices for infant mortality using the most recent nationally representative data from 53 LMICs that participated in the Demographic and Health Surveys. Analyses showed that infant mortality was consistently concentrated among poorer households within countries and, furthermore, that there was substantial variation across countries and regions in the magnitude of these social
Acknowledgments
Mohammad Hajizadeh is funded by the Strategic Training Program in Global Health Research, a partnership of the Canadian Institutes of Health Research (CIHR) and the Québec Population Health Research Network (QPHRN). Arijit Nandi and Jody Heymann acknowledge the support of the Canada Research Chairs Program and the Canadian Institutes of Health Research Operating Grant: Examining the impact of social policies on health equity (ROH-115209).
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