Analyses of Inequalities in RMNCH: Rising to the Challenge of the Sdgs

Analysis BMJ Glob Health: first published as 10.1136/bmjgh-2018-001295 on 24 June 2019. Downloaded from Analyses of inequalities in RMNCH: rising to the challenge of the SDGs 1,2 3 4 2 To cite: Victora C, Boerma T, Cesar Victora, Ties Boerma, Jennifer Requejo, Marilia Arndt Mesenburg, 2 2 2 Requejo J, et al. Analyses Gary Joseph, Janaína Calu Costa, Luis Paulo Vidaletti, of inequalities in RMNCH: Leonardo Zanini Ferreira, 2 Ahmad Reza Hosseinpoor,5 Aluisio J D Barros 2 rising to the challenge of the SDGs. BMJ Glob Health 2019;4:e001295. doi:10.1136/ bmjgh-2018-001295 ABSTRACT Summary box Handling editor Seye Abimbola The Sustainable Development Goal (SDG) 17.18 recommends efforts to increase the availability of data Additional material is ► The Sustainable Development Goals (SDGs) call for ► disaggregated by income, gender, age, race, ethnicity, published online only. To view better and more finely grained analyses on health migratory status, disability and geographic location in please visit the journal online equity, presenting a challenge to researchers and developing countries. Surveys will continue to be the (http:// dx. doi. org/ 10. 1136/ designers of health surveys. bmjgh- 2018- 001295). leading data source for disaggregated data for most ► With currently available data, it is possible to further dimensions of inequality. We discuss potential advances equity analyses, and we present innovative ways in the disaggregation of data from national surveys, with a This article is part of a Series to deal with equity analysis to incorporate absolute focus on the coverage of reproductive, maternal, newborn addressing the challenges in wealth, ethnicity and intersectionality between dif- and child health indicators (RMNCH). Even though the measurement and monitoring ferent dimensions of inequalities. women’s, children’s and Millennium Development Goals were focused on national- ► The analytical examples provided here show how adolescents’ health in the level progress, monitoring initiatives such as Countdown new approaches may lead to deeper understanding context of the Sustainable to 2015 reported on progress in RMNCH coverage of patterns of inequality and thus help health man- Development Goals. The according to wealth quintiles, sex of the child, women’s agers and policy makers fine-tune their policies and series includes improved education and age, urban/rural residence and subnational programmes. ways to measure and monitor geographic regions. We describe how the granularity of inequalities, drivers of women’s, ► The challenges presented here will need to be tack- equity analyses may be increased by including additional children’s and adolescents’ led by survey designers and implementers, data stratification variables such as wealth deciles, estimated health especially governance, analysts and all those involved in capacity strength- absolute income, ethnicity, migratory status and disability. early childhood development, ening towards the achievement of SDG 17.18. reproductive maternal and We also provide examples of analyses of intersectionality child health in conflict settings, between wealth and urban/rural residence (also known nutrition intervention coverage as double stratification), sex of the child and age of the http://gh.bmj.com/ and effective coverage of woman. Based on these examples, we describe the from 2005 the Countdown to 2015 initiative interventions. These articles advantages and limitations of stratified analyses of survey provided regular reports on within-country were prepared as part of an data, including sample size issues and lack of information initiative of the Countdown to health inequalities according to wealth, on the necessary variables in some surveys. We conclude 3 2030 for Women’s, Children’s education, gender and place of residence. by recommending that, whenever possible, stratified and Adolescents’ Health, Starting with the World Bank,4 equity analyses analyses should go beyond the traditional breakdowns by presented at a Countdown on September 23, 2021 by guest. Protected copyright. wealth quintiles, sex and residence, to also incorporate have permeated the documents and websites measurement conference 31 of international organisations. The WHO’s January to 1 February 2018 in the wider dimensions of inequality. Greater granularity of South Africa and reviewed by equity analyses will contribute to identify subgroups of Health Equity Monitor (http://www. who. int/ members of the Countdown women and children who are being left behind and monitor gho/ health_ equity/ en/) and its publication working groups. the impact of efforts to reduce inequalities in order to on the State of Inequality,5 and analyses by achieve the health SDGs. Unicef6 7 have contributed to mainstreaming Received 16 November 2018 equity considerations. In many developing Revised 19 February 2019 Accepted 25 February 2019 countries, however, the extent to which disaggregated analyses are presented and used for BACKGROUND policies and programmes is still quite limited. The Millennium Development Goals (MDGs, The launch of the Sustainable Development © Author(s) (or their employer(s)) 2019. Re-use 1990–2015 failed to address within-country Goals (SDGs) in 2015 more clearly brought permitted under CC BY. health inequalities (http://www. un. org/ equity to the forefront (https://sust aina bled Published by BMJ. millenniumgoals/), with country perfor- evelopment. un. org). The third SDG (‘ensure For numbered affiliations see mance being solely assessed according to healthy lives and promote well-being for all at end of article. national level progress on health goals all ages’) has an intrinsic equity component, 1 Correspondence to (MDGs 4, 5 and 6). Nevertheless, the litera- and the tenth goal (‘reduce inequality within Professor Aluisio J D Barros; ture on socioeconomic inequalities in health and among countries’), although focused abarros@ equidade. org increased rapidly during the MDG era2 and on economic inequality, also highlights the Victora C, et al. BMJ Glob Health 2019;4:e001295. doi:10.1136/bmjgh-2018-001295 1 BMJ Global Health BMJ Glob Health: first published as 10.1136/bmjgh-2018-001295 on 24 June 2019. Downloaded from importance of reducing disparities. SDG 17.18 on data, PANEL 1. SAMPLE SIZES FOR DISAGGREGatED ANALYSES monitoring and accountability specifically addresses the RMNCH survey sample sizes have increased over time need to increase ‘the availability of high-quality, timely due to the growing interest in disaggregated analyses. and reliable data disaggregated by income, gender, age, The median number of children aged less than 5 years in race, ethnicity, migratory status, disability, geographic the surveys included in the Pelotas database (DHS, MICS location and other characteristics relevant in national and RHS) increased from 4523 in the 1991–1999 period contexts’. to 5140 after 2010 (The mean sample size increased from In this paper, we address the challenges presented by 4827 in 1990-99 to 7321 in 2010 or later, an increase that SDG 17.18, with examples from coverage of reproduc- was driven by some large recent surveys). tive, maternal, newborn and child health (RMNCH) Table 1 shows the median denominators for key interventions in low-income and middle-income coun- RMNCH coverage indicators, by wealth quintiles. The tries (LMICs). We focus on data from national surveys, median provides a more realistic picture of the sample which provide the most comprehensive and comparable sizes available for analyses than the means, which are assessments of intervention coverage, while noting that distorted by a few very large surveys, such as the recently administrative data from health information systems released 2015 India DHS. The median numbers of house- are also useful for demonstrating some dimensions of holds and of women are similar in all quintiles, but due inequalities, particularly geographic. We report on the to higher birth rates the number of under-five children experience of the Countdown to 2030 Equity Tech- in the poorest quintile is almost twice as large as in the nical Working Group, based at the Federal University of richest quintile. Even larger imbalances are observed for Pelotas, Brazil, in exploring new ways of analysing and case-management indicators, given the much higher inci- presenting health inequalities according to a wide range dence of diarrhoea and suspected pneumonia among the of dimensions. poor. Indicators of exclusive breastfeeding and immuni- sations, which are based on restricted age ranges, also have relatively small denominators. DATA SOURCES Data for the present analyses were retrieved from publicly INCOME, WEalth AND SOCIOECONOMIC POSITION available nationally representative health surveys carried Potential indicators for assessing socioeconomic posi- out from 1991 to 2016, including the Demographic and tion through surveys in LMICs include household assets, Health Surveys (DHS), Multiple Indicator Cluster Surveys consumption expenditure, income, education, occupa- (MICS) and Reproductive Health Surveys (RHS). Our tion and subjective measures such as participatory wealth analyses relied on data from up to 349 surveys carried rankings and self-rating.10 Each approach has strengths out in 113 countries ( www. equidade. org/ surveys), hence- and limitations. Education of the woman or mother and forth referred to as the Pelotas database. All surveys used occupation of the father were the most frequently used http://gh.bmj.com/ multistage cluster sampling designs

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