Please use this identifier to cite or link to this item: https://doi.org/10.1371/journal.pone.0207339
DC FieldValue
dc.titleAccess to environmental health assets across wealth strata: Evidence from 41 low- and middle-income countries
dc.contributor.authorGraham J.P.
dc.contributor.authorKaur M.
dc.contributor.authorJeuland M.A.
dc.date.accessioned2019-11-01T08:11:25Z
dc.date.available2019-11-01T08:11:25Z
dc.date.issued2018
dc.identifier.citationGraham J.P., Kaur M., Jeuland M.A. (2018). Access to environmental health assets across wealth strata: Evidence from 41 low- and middle-income countries. PLoS ONE 13 (11) : e0207339. ScholarBank@NUS Repository. https://doi.org/10.1371/journal.pone.0207339
dc.identifier.issn19326203
dc.identifier.urihttps://scholarbank.nus.edu.sg/handle/10635/161209
dc.description.abstractIntroduction Low levels of household access to basic environmental health assets (EHAs)–including technologies such as clean cookstoves and bed nets or infrastructure such as piped water and electricity–in low- and middle-income countries (LMICs) are known to contribute significantly to the global burden of disease. This low access persists despite decades of promotion of many low-cost, life-saving technologies, and is particularly pronounced among poor households. This study aims to characterize variation in access to EHAs among LMIC households as a function of wealth, as defined by ownership of various assets. Methods Demographic and Health Survey (DHS) data from 41 low- and middle-income countries were used to assess household-level access to the following EHAs: 1) improved water supply; 2) piped water supply; 3) improved sanitation; 4) modern cooking fuels; 5) electricity; and 6) bed nets. For comparison, we included access to mobile phones, which is considered a highly successful technology in terms of its penetration into poor households within LMICs. Ownership levels were compared across country-specific wealth quintiles constructed from household assets using bivariate analysis and multivariable linear regression models. Results Access to EHAs was low among the households in the bottom three quintiles of wealth. Access to piped water, modern cooking fuels, electricity and improved sanitation, for example, were all below 50% for households in the bottom three wealth quintiles. Access to certain EHAs such as improved water supply and bed nets increased only slowly with concomitant increases in wealth, while gaps in access to other EHAs varied to a greater degree by wealth quintile. For example, disparities in access between the richest and poorest quintiles were greatest for electricity and improved sanitation. Rural households in all wealth quintiles had much lower levels of access to EHAs, except for bed nets, relative to urban households. Conclusions The findings of this study provide a basis for understanding how EHAs are distributed among poor households in LMICs, elucidate where inequalities in access are particularly pronounced, and point to a need for strategies that better reach the poor, if the global environmental burden of disease is to be reduced. © 2018 Graham et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
dc.rightsAttribution 4.0 International
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.sourceUnpaywall 20191101
dc.subjectdrinking water
dc.subjectAfrica south of the Sahara
dc.subjectArticle
dc.subjectbivariate analysis
dc.subjectcontrolled study
dc.subjectdemography
dc.subjectelectricity
dc.subjectenvironmental health
dc.subjecthealth care access
dc.subjecthealth care disparity
dc.subjecthuman
dc.subjectlinear regression analysis
dc.subjectlow income country
dc.subjectmiddle income country
dc.subjectorganization and management
dc.subjectquality of life
dc.subjectsanitation
dc.subjectwater supply
dc.subjectwater treatment
dc.subjectadult
dc.subjectdeveloping country
dc.subjectenvironment
dc.subjectfamily size
dc.subjectfemale
dc.subjecthealth status
dc.subjectincome
dc.subjectmale
dc.subjectmiddle aged
dc.subjectpoverty
dc.subjectAdult
dc.subjectDeveloping Countries
dc.subjectEnvironment
dc.subjectFamily Characteristics
dc.subjectFemale
dc.subjectHealth Status
dc.subjectHumans
dc.subjectIncome
dc.subjectMale
dc.subjectMiddle Aged
dc.subjectPoverty
dc.typeArticle
dc.contributor.departmentDEAN'S OFFICE (LKY SCH OF PUBLIC POLICY)
dc.contributor.departmentLEE KUAN YEW SCHOOL OF PUBLIC POLICY
dc.description.doi10.1371/journal.pone.0207339
dc.description.sourcetitlePLoS ONE
dc.description.volume13
dc.description.issue11
dc.description.pagee0207339
Appears in Collections:Staff Publications
Elements

Show simple item record
Files in This Item:
File Description SizeFormatAccess SettingsVersion 
10_1371_journal_pone_0207339.pdf937.73 kBAdobe PDF

OPEN

NoneView/Download

SCOPUSTM   
Citations

6
checked on Jan 22, 2022

WEB OF SCIENCETM
Citations

5
checked on Oct 6, 2021

Page view(s)

183
checked on Jan 27, 2022

Download(s)

1
checked on Jan 27, 2022

Google ScholarTM

Check

Altmetric


This item is licensed under a Creative Commons License Creative Commons