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Geospatial Analysis of Dental Access and Workforce Distribution in Kenya
BACKGROUND AND OBJECTIVE: One of the major factors affecting access to quality oral healthcare in low- and middle-income countries is the under-supply of the dental workforce. The aim of this study was to use Geographical Information System (GIS) to analyse the distribution and accessibility of the...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Ubiquity Press
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9695222/ https://www.ncbi.nlm.nih.gov/pubmed/36474897 http://dx.doi.org/10.5334/aogh.3903 |
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author | Okumu, Brenda A. Tennant, Marc Kruger, Estie Kemoli, Arthur M. Roberts, Frank A. Seminario, Ana L. |
author_facet | Okumu, Brenda A. Tennant, Marc Kruger, Estie Kemoli, Arthur M. Roberts, Frank A. Seminario, Ana L. |
author_sort | Okumu, Brenda A. |
collection | PubMed |
description | BACKGROUND AND OBJECTIVE: One of the major factors affecting access to quality oral healthcare in low- and middle-income countries is the under-supply of the dental workforce. The aim of this study was to use Geographical Information System (GIS) to analyse the distribution and accessibility of the dental workforce and facilities across the Kenyan counties. METHODS: This was a cross-sectional study targeting dental professionals and their practices in Kenya in 2013. Using QGIS 3.16, these data were overlaid with data on population size and urbanization levels. For access measurement, buffers were drawn around each clinic at distances of 2.5, 5, 10 and 20 km, and the population within each determined. FINDINGS: Nine hundred six dental professionals in 337 dental clinic locations were included in the study. Dentists, community oral health officers (equivalent to dental therapists) and dental technologists comprised 72%, 15% and 12%, respectively. Nairobi county with 100% urbanization and >4000 people/km(2) had 43% of the workforce and a dentist to population ratio of 1:9,018. Wajir with an urbanization level of 15% and 12 people/km(2) had no dental facility. Overall, 11%, 19%, 35% and 58% of the Kenyan population were within 2.5, 5, 10 and 20 km radius of a dental clinic respectively. CONCLUSION: Maldistribution of dental workforce in Kenya persists, particularly in less urbanized and sparsely populated areas. GIS map production give health planners a better visual picture of areas that are most in need of health care services based on population profiles. |
format | Online Article Text |
id | pubmed-9695222 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Ubiquity Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-96952222022-12-05 Geospatial Analysis of Dental Access and Workforce Distribution in Kenya Okumu, Brenda A. Tennant, Marc Kruger, Estie Kemoli, Arthur M. Roberts, Frank A. Seminario, Ana L. Ann Glob Health Original Research BACKGROUND AND OBJECTIVE: One of the major factors affecting access to quality oral healthcare in low- and middle-income countries is the under-supply of the dental workforce. The aim of this study was to use Geographical Information System (GIS) to analyse the distribution and accessibility of the dental workforce and facilities across the Kenyan counties. METHODS: This was a cross-sectional study targeting dental professionals and their practices in Kenya in 2013. Using QGIS 3.16, these data were overlaid with data on population size and urbanization levels. For access measurement, buffers were drawn around each clinic at distances of 2.5, 5, 10 and 20 km, and the population within each determined. FINDINGS: Nine hundred six dental professionals in 337 dental clinic locations were included in the study. Dentists, community oral health officers (equivalent to dental therapists) and dental technologists comprised 72%, 15% and 12%, respectively. Nairobi county with 100% urbanization and >4000 people/km(2) had 43% of the workforce and a dentist to population ratio of 1:9,018. Wajir with an urbanization level of 15% and 12 people/km(2) had no dental facility. Overall, 11%, 19%, 35% and 58% of the Kenyan population were within 2.5, 5, 10 and 20 km radius of a dental clinic respectively. CONCLUSION: Maldistribution of dental workforce in Kenya persists, particularly in less urbanized and sparsely populated areas. GIS map production give health planners a better visual picture of areas that are most in need of health care services based on population profiles. Ubiquity Press 2022-11-21 /pmc/articles/PMC9695222/ /pubmed/36474897 http://dx.doi.org/10.5334/aogh.3903 Text en Copyright: © 2022 The Author(s) https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License (CC-BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. See http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Original Research Okumu, Brenda A. Tennant, Marc Kruger, Estie Kemoli, Arthur M. Roberts, Frank A. Seminario, Ana L. Geospatial Analysis of Dental Access and Workforce Distribution in Kenya |
title | Geospatial Analysis of Dental Access and Workforce Distribution in Kenya |
title_full | Geospatial Analysis of Dental Access and Workforce Distribution in Kenya |
title_fullStr | Geospatial Analysis of Dental Access and Workforce Distribution in Kenya |
title_full_unstemmed | Geospatial Analysis of Dental Access and Workforce Distribution in Kenya |
title_short | Geospatial Analysis of Dental Access and Workforce Distribution in Kenya |
title_sort | geospatial analysis of dental access and workforce distribution in kenya |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9695222/ https://www.ncbi.nlm.nih.gov/pubmed/36474897 http://dx.doi.org/10.5334/aogh.3903 |
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