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Income disparities in driving distance to health care infrastructure in the United States: a geographic information systems analysis
OBJECTIVE: Inequities in access to health care contribute to persisting disparities in health care outcomes. We constructed a geographic information systems analysis to test the association between income and access to the existing health care infrastructure in a nationally representative sample of...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9235217/ https://www.ncbi.nlm.nih.gov/pubmed/35761413 http://dx.doi.org/10.1186/s13104-022-06117-w |
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author | Guo, Jingchuan Hernandez, Inmaculada Dickson, Sean Tang, Shangbin Essien, Utibe R. Mair, Christina Berenbrok, Lucas A. |
author_facet | Guo, Jingchuan Hernandez, Inmaculada Dickson, Sean Tang, Shangbin Essien, Utibe R. Mair, Christina Berenbrok, Lucas A. |
author_sort | Guo, Jingchuan |
collection | PubMed |
description | OBJECTIVE: Inequities in access to health care contribute to persisting disparities in health care outcomes. We constructed a geographic information systems analysis to test the association between income and access to the existing health care infrastructure in a nationally representative sample of US residents. Using income and household size data, we calculated the odds ratio of having a distance > 10 miles in nonmetropolitan counties or > 1 mile in metropolitan counties to the closest facility for low-income residents (i.e., < 200% Federal Poverty Level), compared to non-low-income residents. RESULTS: We identified that in 954 counties (207 metropolitan counties and 747 nonmetropolitan counties) representing over 14% of the US population, low-income residents have poorer access to health care facilities. Our analyses demonstrate the high prevalence of structural disparities in health care access across the entire US, which contribute to the perpetuation of disparities in health care outcomes. |
format | Online Article Text |
id | pubmed-9235217 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-92352172022-06-28 Income disparities in driving distance to health care infrastructure in the United States: a geographic information systems analysis Guo, Jingchuan Hernandez, Inmaculada Dickson, Sean Tang, Shangbin Essien, Utibe R. Mair, Christina Berenbrok, Lucas A. BMC Res Notes Research Note OBJECTIVE: Inequities in access to health care contribute to persisting disparities in health care outcomes. We constructed a geographic information systems analysis to test the association between income and access to the existing health care infrastructure in a nationally representative sample of US residents. Using income and household size data, we calculated the odds ratio of having a distance > 10 miles in nonmetropolitan counties or > 1 mile in metropolitan counties to the closest facility for low-income residents (i.e., < 200% Federal Poverty Level), compared to non-low-income residents. RESULTS: We identified that in 954 counties (207 metropolitan counties and 747 nonmetropolitan counties) representing over 14% of the US population, low-income residents have poorer access to health care facilities. Our analyses demonstrate the high prevalence of structural disparities in health care access across the entire US, which contribute to the perpetuation of disparities in health care outcomes. BioMed Central 2022-06-27 /pmc/articles/PMC9235217/ /pubmed/35761413 http://dx.doi.org/10.1186/s13104-022-06117-w Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Note Guo, Jingchuan Hernandez, Inmaculada Dickson, Sean Tang, Shangbin Essien, Utibe R. Mair, Christina Berenbrok, Lucas A. Income disparities in driving distance to health care infrastructure in the United States: a geographic information systems analysis |
title | Income disparities in driving distance to health care infrastructure in the United States: a geographic information systems analysis |
title_full | Income disparities in driving distance to health care infrastructure in the United States: a geographic information systems analysis |
title_fullStr | Income disparities in driving distance to health care infrastructure in the United States: a geographic information systems analysis |
title_full_unstemmed | Income disparities in driving distance to health care infrastructure in the United States: a geographic information systems analysis |
title_short | Income disparities in driving distance to health care infrastructure in the United States: a geographic information systems analysis |
title_sort | income disparities in driving distance to health care infrastructure in the united states: a geographic information systems analysis |
topic | Research Note |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9235217/ https://www.ncbi.nlm.nih.gov/pubmed/35761413 http://dx.doi.org/10.1186/s13104-022-06117-w |
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