Evidence map›Paper›PMID 29493588›Full record

ArticleNature2018

Mapping local variation in educational attainment across Africa.

Nicholas Graetz, Joseph Friedman, Aaron Osgood-Zimmerman, Roy Burstein, Molly H Biehl, Chloe Shields, Jonathan F Mosser, Daniel C Casey, Aniruddha Deshpande, Lucas Earl and 16 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Nature, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
45citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

45 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
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  15. The Transformation of Polygyny in Sub-Saharan Africa.Population and development review · 2022
    Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

26 authors.

Nicholas GraetzInstitute for Health Metrics and Evaluation, University of Washington, Seattle, Washington 98121, USA.
Joseph FriedmanInstitute for Health Metrics and Evaluation, University of Washington, Seattle, Washington 98121, USA.
Aaron Osgood-ZimmermanInstitute for Health Metrics and Evaluation, University of Washington, Seattle, Washington 98121, USA.
Roy BursteinInstitute for Health Metrics and Evaluation, University of Washington, Seattle, Washington 98121, USA.
Molly H BiehlInstitute for Health Metrics and Evaluation, University of Washington, Seattle, Washington 98121, USA.
Chloe ShieldsInstitute for Health Metrics and Evaluation, University of Washington, Seattle, Washington 98121, USA.
Jonathan F MosserInstitute for Health Metrics and Evaluation, University of Washington, Seattle, Washington 98121, USA.
Daniel C CaseyInstitute for Health Metrics and Evaluation, University of Washington, Seattle, Washington 98121, USA.
Aniruddha DeshpandeInstitute for Health Metrics and Evaluation, University of Washington, Seattle, Washington 98121, USA.
Lucas EarlInstitute for Health Metrics and Evaluation, University of Washington, Seattle, Washington 98121, USA.
Robert C ReinerInstitute for Health Metrics and Evaluation, University of Washington, Seattle, Washington 98121, USA.
Sarah E RayInstitute for Health Metrics and Evaluation, University of Washington, Seattle, Washington 98121, USA.
Nancy FullmanInstitute for Health Metrics and Evaluation, University of Washington, Seattle, Washington 98121, USA.
Aubrey J LevineInstitute for Health Metrics and Evaluation, University of Washington, Seattle, Washington 98121, USA.
Rebecca W StubbsInstitute for Health Metrics and Evaluation, University of Washington, Seattle, Washington 98121, USA.
Benjamin K MayalaInstitute for Health Metrics and Evaluation, University of Washington, Seattle, Washington 98121, USA.
Joshua LongbottomBig Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7FZ, UK.
Annie J BrowneBig Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7FZ, UK.
Samir BhattDepartment of Infectious Disease Epidemiology, Imperial College London, London SW7 2AZ, UK.
Daniel J WeissBig Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7FZ, UK.
Peter W GethingBig Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7FZ, UK.
Ali H MokdadInstitute for Health Metrics and Evaluation, University of Washington, Seattle, Washington 98121, USA.
Stephen S LimInstitute for Health Metrics and Evaluation, University of Washington, Seattle, Washington 98121, USA.
Christopher J L MurrayInstitute for Health Metrics and Evaluation, University of Washington, Seattle, Washington 98121, USA.
Emmanuela GakidouInstitute for Health Metrics and Evaluation, University of Washington, Seattle, Washington 98121, USA.
Simon I HayInstitute for Health Metrics and Evaluation, University of Washington, Seattle, Washington 98121, USA.

Funding

GRADUATE TRAINING IN DEMOGRAPHYT32HD007242 · NICHD · UNIVERSITY OF PENNSYLVANIA · PI MICHEL GUILLOT · 1985 to 2026
$6.6M
Medical Research Council MR/R015600/1NICHD NIH HHS T32 HD007242
6 · The paper itself

Abstract

Educational attainment for women of reproductive age is linked to reduced child and maternal mortality, lower fertility and improved reproductive health. Comparable analyses of attainment exist only at the national level, potentially obscuring patterns in subnational inequality. Evidence suggests that wide disparities between urban and rural populations exist, raising questions about where the majority of progress towards the education targets of the Sustainable Development Goals is occurring in African countries. Here we explore within-country inequalities by predicting years of schooling across five by five kilometre grids, generating estimates of average educational attainment by age and sex at subnational levels. Despite marked progress in attainment from 2000 to 2015 across Africa, substantial differences persist between locations and sexes. These differences have widened in many countries, particularly across the Sahel. These high-resolution, comparable estimates improve the ability of decision-makers to plan the precisely targeted interventions that will be necessary to deliver progress during the era of the Sustainable Development Goals.

Indexed as

Educational StatusAdolescentAdultAfricaFemaleGoalsHumansInternationalityMaleMiddle AgedProbabilitySex FactorsWorld Health OrganizationYoung Adult

Identifiers

PMID29493588
PMCPMC6346272

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.