Cargando…

High-Resolution Spatial Distribution and Estimation of Access to Improved Sanitation in Kenya

BACKGROUND: Access to sanitation facilities is imperative in reducing the risk of multiple adverse health outcomes. A distinct disparity in sanitation exists among different wealth levels in many low-income countries, which may hinder the progress across each of the Millennium Development Goals. MET...

Descripción completa

Detalles Bibliográficos
Autores principales: Jia, Peng, Anderson, John D., Leitner, Michael, Rheingans, Richard
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4942115/
https://www.ncbi.nlm.nih.gov/pubmed/27404271
http://dx.doi.org/10.1371/journal.pone.0158490
_version_ 1782442384256139264
author Jia, Peng
Anderson, John D.
Leitner, Michael
Rheingans, Richard
author_facet Jia, Peng
Anderson, John D.
Leitner, Michael
Rheingans, Richard
author_sort Jia, Peng
collection PubMed
description BACKGROUND: Access to sanitation facilities is imperative in reducing the risk of multiple adverse health outcomes. A distinct disparity in sanitation exists among different wealth levels in many low-income countries, which may hinder the progress across each of the Millennium Development Goals. METHODS: The surveyed households in 397 clusters from 2008–2009 Kenya Demographic and Health Surveys were divided into five wealth quintiles based on their national asset scores. A series of spatial analysis methods including excess risk, local spatial autocorrelation, and spatial interpolation were applied to observe disparities in coverage of improved sanitation among different wealth categories. The total number of the population with improved sanitation was estimated by interpolating, time-adjusting, and multiplying the surveyed coverage rates by high-resolution population grids. A comparison was then made with the annual estimates from United Nations Population Division and World Health Organization /United Nations Children's Fund Joint Monitoring Program for Water Supply and Sanitation. RESULTS: The Empirical Bayesian Kriging interpolation produced minimal root mean squared error for all clusters and five quintiles while predicting the raw and spatial coverage rates of improved sanitation. The coverage in southern regions was generally higher than in the north and east, and the coverage in the south decreased from Nairobi in all directions, while Nyanza and North Eastern Province had relatively poor coverage. The general clustering trend of high and low sanitation improvement among surveyed clusters was confirmed after spatial smoothing. CONCLUSIONS: There exists an apparent disparity in sanitation among different wealth categories across Kenya and spatially smoothed coverage rates resulted in a closer estimation of the available statistics than raw coverage rates. Future intervention activities need to be tailored for both different wealth categories and nationally where there are areas of greater needs when resources are limited.
format Online
Article
Text
id pubmed-4942115
institution National Center for Biotechnology Information
language English
publishDate 2016
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-49421152016-08-01 High-Resolution Spatial Distribution and Estimation of Access to Improved Sanitation in Kenya Jia, Peng Anderson, John D. Leitner, Michael Rheingans, Richard PLoS One Research Article BACKGROUND: Access to sanitation facilities is imperative in reducing the risk of multiple adverse health outcomes. A distinct disparity in sanitation exists among different wealth levels in many low-income countries, which may hinder the progress across each of the Millennium Development Goals. METHODS: The surveyed households in 397 clusters from 2008–2009 Kenya Demographic and Health Surveys were divided into five wealth quintiles based on their national asset scores. A series of spatial analysis methods including excess risk, local spatial autocorrelation, and spatial interpolation were applied to observe disparities in coverage of improved sanitation among different wealth categories. The total number of the population with improved sanitation was estimated by interpolating, time-adjusting, and multiplying the surveyed coverage rates by high-resolution population grids. A comparison was then made with the annual estimates from United Nations Population Division and World Health Organization /United Nations Children's Fund Joint Monitoring Program for Water Supply and Sanitation. RESULTS: The Empirical Bayesian Kriging interpolation produced minimal root mean squared error for all clusters and five quintiles while predicting the raw and spatial coverage rates of improved sanitation. The coverage in southern regions was generally higher than in the north and east, and the coverage in the south decreased from Nairobi in all directions, while Nyanza and North Eastern Province had relatively poor coverage. The general clustering trend of high and low sanitation improvement among surveyed clusters was confirmed after spatial smoothing. CONCLUSIONS: There exists an apparent disparity in sanitation among different wealth categories across Kenya and spatially smoothed coverage rates resulted in a closer estimation of the available statistics than raw coverage rates. Future intervention activities need to be tailored for both different wealth categories and nationally where there are areas of greater needs when resources are limited. Public Library of Science 2016-07-12 /pmc/articles/PMC4942115/ /pubmed/27404271 http://dx.doi.org/10.1371/journal.pone.0158490 Text en © 2016 Jia et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Jia, Peng
Anderson, John D.
Leitner, Michael
Rheingans, Richard
High-Resolution Spatial Distribution and Estimation of Access to Improved Sanitation in Kenya
title High-Resolution Spatial Distribution and Estimation of Access to Improved Sanitation in Kenya
title_full High-Resolution Spatial Distribution and Estimation of Access to Improved Sanitation in Kenya
title_fullStr High-Resolution Spatial Distribution and Estimation of Access to Improved Sanitation in Kenya
title_full_unstemmed High-Resolution Spatial Distribution and Estimation of Access to Improved Sanitation in Kenya
title_short High-Resolution Spatial Distribution and Estimation of Access to Improved Sanitation in Kenya
title_sort high-resolution spatial distribution and estimation of access to improved sanitation in kenya
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4942115/
https://www.ncbi.nlm.nih.gov/pubmed/27404271
http://dx.doi.org/10.1371/journal.pone.0158490
work_keys_str_mv AT jiapeng highresolutionspatialdistributionandestimationofaccesstoimprovedsanitationinkenya
AT andersonjohnd highresolutionspatialdistributionandestimationofaccesstoimprovedsanitationinkenya
AT leitnermichael highresolutionspatialdistributionandestimationofaccesstoimprovedsanitationinkenya
AT rheingansrichard highresolutionspatialdistributionandestimationofaccesstoimprovedsanitationinkenya