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Analyses of inequalities in RMNCH: rising to the challenge of the SDGs
  1. Cesar Victora1,2,
  2. Ties Boerma3,
  3. Jennifer Requejo4,
  4. Marilia Arndt Mesenburg2,
  5. Gary Joseph2,
  6. Janaína Calu Costa2,
  7. Luis Paulo Vidaletti2,
  8. Leonardo Zanini Ferreira2,
  9. Ahmad Reza Hosseinpoor5,
  10. Aluisio J D Barros2
  1. 1Postgraduate Program in Epidemiology, Federal University of Pelotas, Pelotas, Brazil
  2. 2International Center for Equity in Health, Federal University of Pelotas, Pelotas, Brazil
  3. 3Department of Community Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
  4. 4UNICEF USA, New York City, New York, USA
  5. 5Partnership for Maternal, Newborn & Child Health, World Health Organization, Geneva, Switzerland
  1. Correspondence to Professor Aluisio J D Barros; abarros{at}equidade.org

Abstract

The Sustainable Development Goal (SDG) 17.18 recommends efforts to increase the availability of data disaggregated by income, gender, age, race, ethnicity, migratory status, disability and geographic location in developing countries. Surveys will continue to be the leading data source for disaggregated data for most dimensions of inequality. We discuss potential advances in the disaggregation of data from national surveys, with a focus on the coverage of reproductive, maternal, newborn and child health indicators (RMNCH). Even though the Millennium Development Goals were focused on national-level progress, monitoring initiatives such as Countdown to 2015 reported on progress in RMNCH coverage according to wealth quintiles, sex of the child, women’s education and age, urban/rural residence and subnational geographic regions. We describe how the granularity of equity analyses may be increased by including additional stratification variables such as wealth deciles, estimated absolute income, ethnicity, migratory status and disability. We also provide examples of analyses of intersectionality between wealth and urban/rural residence (also known as double stratification), sex of the child and age of the woman. Based on these examples, we describe the advantages and limitations of stratified analyses of survey data, including sample size issues and lack of information on the necessary variables in some surveys. We conclude by recommending that, whenever possible, stratified analyses should go beyond the traditional breakdowns by wealth quintiles, sex and residence, to also incorporate the wider dimensions of inequality. Greater granularity of equity analyses will contribute to identify subgroups of women and children who are being left behind and monitor the impact of efforts to reduce inequalities in order to achieve the health SDGs.

  • equity health
  • health systems evaluation
  • maternal health
  • child health
  • health services research

This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/.

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Footnotes

  • Handling editor Seye Abimbola

  • Presented at This article is part of a Series addressing the challenges in measurement and monitoring women’s, children’s and adolescents’ health in the context of the Sustainable Development Goals. The series includes improved ways to measure and monitor inequalities, drivers of women’s, children’s and adolescents’ health especially governance, early childhood development, reproductive maternal and child health in conflict settings, nutrition intervention coverage and effective coverage of interventions. These articles were prepared as part of an initiative of the Countdown to 2030 for Women’s, Children’s and Adolescents’ Health, presented at a Countdown measurement conference 31 January to 1 February 2018 in South Africa and reviewed by members of the Countdown working groups.

  • Contributors CV and TB conceptualised the manuscript. MAM, GJ, JCC, LPV and LZF conducted the analyses. CV drafted the manuscript, JR, ARH and AJDB contributed to the writing, interpretation and refining of figures. All authors read and approved the final manuscript.

  • Funding Our work was financially supported by the Bill & Melinda Gates Foundation through a grant to the Countdown to 2030 for women’s, children’s and adolescents’ health.

  • Competing interests None declared.

  • Patient consent for publication Not required.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Data sharing statement All the analyses of this manuscript were based on publicly available national health survey data obtainable from the DHS and MICS websites.

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