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A cross-sectional analysis of associations between environmental indices and asthma in U.S. counties from 2003 to 2012

BACKGROUND: To capture the impacts of environmental stressors, environmental indices like the Air Quality Index, Toxic Release Inventory and Environmental Quality Index have been used to investigate environmental quality and its association with public health issues. However, past studies often rely...

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Autores principales: Hurbain, Patrick, Liu, Yan, Strickland, Matthew J., Li, Dingsheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8542056/
https://www.ncbi.nlm.nih.gov/pubmed/33895778
http://dx.doi.org/10.1038/s41370-021-00326-4
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author Hurbain, Patrick
Liu, Yan
Strickland, Matthew J.
Li, Dingsheng
author_facet Hurbain, Patrick
Liu, Yan
Strickland, Matthew J.
Li, Dingsheng
author_sort Hurbain, Patrick
collection PubMed
description BACKGROUND: To capture the impacts of environmental stressors, environmental indices like the Air Quality Index, Toxic Release Inventory and Environmental Quality Index have been used to investigate environmental quality and its association with public health issues. However, past studies often rely on relatively small sample sizes, and they have typically not adjusted for important individual-level disease risk factors. OBJECTIVE: We aim to estimate associations between existing environmental indices and asthma prevalence over a large population and multiple years. METHODS: Based on data availability, we assessed the predictive capability of these indices for prevalent asthma across U.S. counties from 2003 to 2012. We gathered asthma data from the U.S. CDC Behavioral Risk Factor Surveillance System by county and used multivariable weighted logistic regression models to estimate the associations between the environmental indices and asthma, adjusting for individual factors such as smoking, income level, and obesity. RESULTS: Environmental indices showed little to no correlation with one another and with prevalent asthma over time. Associations of environmental indices with prevalent asthma were very weak; whereas individual factors were more substantially associated with prevalent asthma. SIGNIFICANCE: Our study suggests that an improved environmental index is needed to predict population-level asthma prevalence.
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spelling pubmed-85420562022-03-17 A cross-sectional analysis of associations between environmental indices and asthma in U.S. counties from 2003 to 2012 Hurbain, Patrick Liu, Yan Strickland, Matthew J. Li, Dingsheng J Expo Sci Environ Epidemiol Article BACKGROUND: To capture the impacts of environmental stressors, environmental indices like the Air Quality Index, Toxic Release Inventory and Environmental Quality Index have been used to investigate environmental quality and its association with public health issues. However, past studies often rely on relatively small sample sizes, and they have typically not adjusted for important individual-level disease risk factors. OBJECTIVE: We aim to estimate associations between existing environmental indices and asthma prevalence over a large population and multiple years. METHODS: Based on data availability, we assessed the predictive capability of these indices for prevalent asthma across U.S. counties from 2003 to 2012. We gathered asthma data from the U.S. CDC Behavioral Risk Factor Surveillance System by county and used multivariable weighted logistic regression models to estimate the associations between the environmental indices and asthma, adjusting for individual factors such as smoking, income level, and obesity. RESULTS: Environmental indices showed little to no correlation with one another and with prevalent asthma over time. Associations of environmental indices with prevalent asthma were very weak; whereas individual factors were more substantially associated with prevalent asthma. SIGNIFICANCE: Our study suggests that an improved environmental index is needed to predict population-level asthma prevalence. 2022-03 2021-04-24 /pmc/articles/PMC8542056/ /pubmed/33895778 http://dx.doi.org/10.1038/s41370-021-00326-4 Text en http://www.nature.com/authors/editorial_policies/license.html#termsUsers may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use:http://www.nature.com/authors/editorial_policies/license.html#terms
spellingShingle Article
Hurbain, Patrick
Liu, Yan
Strickland, Matthew J.
Li, Dingsheng
A cross-sectional analysis of associations between environmental indices and asthma in U.S. counties from 2003 to 2012
title A cross-sectional analysis of associations between environmental indices and asthma in U.S. counties from 2003 to 2012
title_full A cross-sectional analysis of associations between environmental indices and asthma in U.S. counties from 2003 to 2012
title_fullStr A cross-sectional analysis of associations between environmental indices and asthma in U.S. counties from 2003 to 2012
title_full_unstemmed A cross-sectional analysis of associations between environmental indices and asthma in U.S. counties from 2003 to 2012
title_short A cross-sectional analysis of associations between environmental indices and asthma in U.S. counties from 2003 to 2012
title_sort cross-sectional analysis of associations between environmental indices and asthma in u.s. counties from 2003 to 2012
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8542056/
https://www.ncbi.nlm.nih.gov/pubmed/33895778
http://dx.doi.org/10.1038/s41370-021-00326-4
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