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Education and adult mortality in middle-income countries: Surprising gradients in six nationally-representative longitudinal surveys

dc.contributor.authorSudharsanan, Nikkil
dc.contributor.authorZhang, Yuan
dc.contributor.authorPayne, Collin
dc.contributor.authorDow, William
dc.contributor.authorCrimmins, Eileen
dc.date.accessioned2022-02-03T01:01:27Z
dc.date.available2022-02-03T01:01:27Z
dc.date.issued2020
dc.date.updated2020-12-13T07:19:28Z
dc.description.abstractBackground: There are large differences in adult mortality across schooling groups in many high-income countries (HICs). An important open question is whether there are similar gradients in adult mortality in middle-income countries (MICs), where schooling and healthcare quality tends to be lower and health-related behaviors are often not strongly patterned by schooling. Methods: We present one of the first international-comparative studies on schooling differences in adult mortality across MICs using harmonizedlongitudinal data on adults ages 50+from China, Costa Rica, Indonesia, Mexico, South Africa, and South Korea. We use Cox proportional hazards models to estimate differences in the hazard of mortality across schooling groups overall and separately by sex and broad age groups. We also estimate schooling gradients in smoking and body mass index to determine whether risk factor gradients potentially explain mor-tality patterns. Results: Only adults with tertiary schooling have a consistent adult mortality advantage compared to those with no schooling. We do not find evidence that individuals with primary schooling have a lower hazard of mortality compared to individuals with no schooling in five of the six countries. The mortality advantage for individuals with secondary schooling is mixed, with evidence of lower mortality relative to those with no schooling in Mexico, South Africa, and South Korea. Gradients in BMI and smoking are inconsistent across countries and unlikely to explain mortality differences. Conclusions: We find that adult mortality and risk factor gradients in MICs can be much different than the established patterns seen in modern HICs. Our results highlight that adult mortality gradients are not an inev-itability and are not found in all populations. Understanding what factors give rise to inequalities in adult mortality and what can be done to minimize gradients while still ensuring continued mortality improvements in MICs is a crucial focus for research and policy.en_AU
dc.format.mimetypeapplication/pdfen_AU
dc.identifier.issn2352-8273en_AU
dc.identifier.urihttp://hdl.handle.net/1885/259043
dc.language.isoen_AUen_AU
dc.provenanceThis is an open access article under the CC BY-NC-ND licenseen_AU
dc.publisherElsevier Ltd.en_AU
dc.rights© 2020 The Authors. Published by Elsevier Ltd.en_AU
dc.rights.licenseCC BY-NC-ND licenseen_AU
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/en_AU
dc.sourceSSM - Population Healthen_AU
dc.subjectAdult mortalityen_AU
dc.subjectLongevityen_AU
dc.subjectSchoolingen_AU
dc.subjectEducationen_AU
dc.subjectMiddle-income countriesen_AU
dc.subjectDeveloping countriesen_AU
dc.titleEducation and adult mortality in middle-income countries: Surprising gradients in six nationally-representative longitudinal surveysen_AU
dc.typeJournal articleen_AU
dcterms.accessRightsOpen Accessen_AU
local.bibliographicCitation.lastpage19en_AU
local.bibliographicCitation.startpage1en_AU
local.contributor.affiliationSudharsanan, Nikkil, Heidelberg Universityen_AU
local.contributor.affiliationZhang, Yuan, Carolina Population Centeren_AU
local.contributor.affiliationPayne, Collin, College of Arts and Social Sciences, ANUen_AU
local.contributor.affiliationDow, William , Department of Demography, University of Californiaen_AU
local.contributor.affiliationCrimmins, Eileen, Leonard Davis School of Gerontology, University of Southern Californiaen_AU
local.contributor.authoruidPayne, Collin, u1057660en_AU
local.description.notesImported from ARIESen_AU
local.identifier.absfor160304 - Mortalityen_AU
local.identifier.ariespublicationa383154xPUB14552en_AU
local.identifier.citationvolume12en_AU
local.identifier.doi10.1016/j.ssmph.2020.100649en_AU
local.publisher.urlhttps://www.elsevier.com/en-auen_AU
local.type.statusPublished Versionen_AU

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