Socioeconomic status (SES) of individuals or families is a composite measure of an individual’s and community’s access to resources, that accounts for economic and social position in relation to others. SES is an important determinant of health in high and middle- and low-income countries (LMIC) across a wide range of health conditions and diseases. In general, the lower an individual’s socioeconomic position the worse their health. The importance of SES is highlighted in one of the United Nations’ Sustainable Development Goals, to reduce income inequality (Goal 10), which has increased by 11 percent in developing countries in recent years. The role of SES in maternal and child health outcomes in LMIC has therefore become a focus in the 2000s.
One of the reasons for the delays in recognition of the role of SES in health outcomes in LMIC has been determining the optimal way to measure SES. Income and consumption expenditures are widely used in high income countries to measure SES but these concepts do not translate easily to many LMIC settings, particularly rural settings where the economy is often informal and difficult to track, and expenditures on health care may not be accurately recorded. Alternative approaches include using household assets as a proxy for income.
Several SES indices have been developed; however, each has limitations for use in predicting child outcomes in LMIC. The Demographic and Health Surveys (DHS), which have been conducted in more than 90 countries since 1994, are one of the most commonly referenced sources of information on SES based on asset ownership as a proxy for wealth. Wealth is considered as an underlying unobserved variable. DHS developed country-specific indices which categorize the household’s economic status in five wealth categories and allow for comparisons of wealth among individuals within the country. However, these indices were not designed for comparisons between countries. A comparative wealth index score that allows for measurement of variation in wealth among individuals within a country while also allowing for differentiation in wealth across countries is needed for a globally pooled data set.
To address multi-country comparisons, the United Nations Development Programme introduced the Multidimensional Poverty Index in 2010 as a new multi-country approach to understand how people experience poverty in multiple and simultaneous ways. An indicator of acute multidimensional deprivation, it identifies a state of poverty through three equally weighted dimensions: education (number of years of schooling), health (child mortality, nutritional status), and standard of living (household attributes/asset ownership). However, including health measures, such as child mortality, in the index itself restricts its suitability for predicting health-related outcomes. In addition, the index does not evaluate SES on a continuum score but rather categorizes households as poor, severe poverty and vulnerable. Therefore, it is not able to discriminate across a range of SES, limiting its sensitivity.
Some recent studies (such as the 8 Country MAL-ED (Etiology, Risk Factors and Interactions of Enteric Infections and Malnutrition and the Consequences for Child Health and Development) study and the single country SHINE (Sanitation, Hygiene, Infant Nutrition, Efficacy) Trial have developed new SES indicators based on the DHS and the UN index, respectively, that appear to be valid and robust. However, both of these studies designed the SES measures to optimize prediction of a specific outcome (e.g., child’s height-for-age Z-score), limiting their generalizability. Another measure, the International Wealth Index, was developed to allow for comparisons across countries; however, it uses the same set of items and scoring algorithm for all countries and therefore, cannot account for country-level differences in item functioning.
Since 2009, The Eunice Kennedy Shriver National Institute of Child Health and Human Development’s (NICHD’s) Global Network (GN) for Women and Children’s Health Research has supported a population-based Maternal and Newborn Health Registry (MNHR) of pregnant women and their babies living in rural communities in LMIC. The MNHR has focused on documentation of maternal mortality, fetal loss after week 20 of pregnancy, accurate and timely measurement of birth weight, and early and late neonatal outcomes. The GN has used the number years of maternal education as a proxy for SES since 2009. In 2016, the GN revisited this approach and adapted the multipoverty index to create a simple index of SES.
The objective of this study is to use item response theory to develop and evaluate an index to assess the SES of the communities in LMICs participating GN’s MNHR which can both differentiate among participants within a country as well as permit comparisons across countries. The justification for this approach are the challenges and complexity of addressing SES in multi-country studies, including our network that is used to evaluate multiple interventions to improve maternal and neonatal mortality and to study trends of these outcomes over time.
By: Patel AB, Bann CM, Garces AL, Krebs NF, Lakangaka A, Tshefu A et al.