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Mapping disparities in education across low- and middle-income countries

  • N. Graetz
  • , L. Woyczynski
  • , K.F. Wilson
  • , J.B. Hall
  • , K.H. Abate
  • , F. Abd-Allah
  • , O.M. Adebayo
  • , V. Adekanmbi
  • , M. Afshari
  • , O. Ajumobi
  • , T. Akinyemiju
  • , F. Alahdab
  • , Z. Al-Aly
  • , J.E.A. Rabanal
  • , M. Alijanzadeh
  • , V. Alipour
  • , K. Altirkawi
  • , M. Amiresmaili
  • , N.H. Anber
  • , C.L. Andrei
  • M. Anjomshoa, C.A.T. Antonio, J. Arabloo, O. Aremu, K.K. Aryal, M. Asadi-Aliabadi, S. Atique, M. Ausloos, A. Awasthi, B.P.A. Quintanilla, S. Azari, A. Badawi, J.A.M. Banoub, S.L. Barker-Collo, A. Barnett, N. Bedi, D.A. Bennett, N.V. Bhattacharjee, K. Bhattacharyya, S. Bhattarai, Z.A. Bhutta, A. Bijani, B. Bikbov, G. Britton, R. Burstein, Z.A. Butt, R. Cárdenas, F. Carvalho, C.A. Castañeda-Orjuela, F. Castro, E. Cerin, Felix Akpojene Ogbo, Andre M. N. Renzaho

Research output: Contribution to journalArticlepeer-review

103 Citations (Scopus)
3 Downloads (Pure)

Abstract

Educational attainment is an important social determinant of maternal, newborn, and child health1–3. As a tool for promoting gender equity, it has gained increasing traction in popular media, international aid strategies, and global agenda-setting4–6. The global health agenda is increasingly focused on evidence of precision public health, which illustrates the subnational distribution of disease and illness7,8; however, an agenda focused on future equity must integrate comparable evidence on the distribution of social determinants of health9–11. Here we expand on the available precision SDG evidence by estimating the subnational distribution of educational attainment, including the proportions of individuals who have completed key levels of schooling, across all low- and middle-income countries from 2000 to 2017. Previous analyses have focused on geographical disparities in average attainment across Africa or for specific countries, but—to our knowledge—no analysis has examined the subnational proportions of individuals who completed specific levels of education across all low- and middle-income countries12–14. By geolocating subnational data for more than 184 million person-years across 528 data sources, we precisely identify inequalities across geography as well as within populations.

Original languageEnglish
Pages (from-to)235-238
Number of pages4
JournalNature
Volume577
Issue number7789
DOIs
Publication statusPublished - 9 Jan 2020

Bibliographical note

Publisher Copyright:
© 2019, The Author(s).

Open Access - Access Right Statement

This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. http://creativecommons.org/licenses/by/4.0/

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 5 - Gender Equality
    SDG 5 Gender Equality
  2. SDG 10 - Reduced Inequalities
    SDG 10 Reduced Inequalities

Keywords

  • detection method; education; educational attainment; equity; gender; international aid; mapping method; public health; spatiotemporal analysis; Africa; Article; clinical outcome; educational status; evidence based practice; geographic distribution; global health; health care disparity; health care policy; health equity; human; low income country; middle income country; priority journal; public health; sex ratio; social determinants of health; Bayes theorem; developing country; education; female; health status; male; socioeconomics; Africa; Bayes Theorem; Developing Countries; Education; Female; Health Status; Humans; Male; Socioeconomic Factors

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