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The association between fine particulate matter (PM(2.5)) and chronic kidney disease using electronic health record data in urban Minnesota

BACKGROUND: Recent evidence has shown that fine particulate matter (PM(2.5)) may be an important environmental risk factor for chronic kidney disease (CKD), but few studies have examined this association for individual patients using fine spatial data. OBJECTIVE: To investigate the association betwe...

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Autores principales: Ghazi, Lama, Drawz, Paul E., Berman, Jesse D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group US 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8202050/
https://www.ncbi.nlm.nih.gov/pubmed/34127789
http://dx.doi.org/10.1038/s41370-021-00351-3
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author Ghazi, Lama
Drawz, Paul E.
Berman, Jesse D.
author_facet Ghazi, Lama
Drawz, Paul E.
Berman, Jesse D.
author_sort Ghazi, Lama
collection PubMed
description BACKGROUND: Recent evidence has shown that fine particulate matter (PM(2.5)) may be an important environmental risk factor for chronic kidney disease (CKD), but few studies have examined this association for individual patients using fine spatial data. OBJECTIVE: To investigate the association between PM(2.5) and CKD (estimated glomerular filtration rate [eGFR]<45 ml/min/1.73 m(2)) in the Twin-Cities area in Minnesota using a large electronic health care database (2012–2019). METHODS: We estimated the previous 1-year average PM(2.5) from the first eGFR (measured with the CKD Epidemiology Collaboration equation using the first available creatinine measure during the baseline period [2012–2014]) using Environmental Protection Agency downscaler modeling data at the census tract level. We evaluated the spatial relative risk and clustering of CKD prevalence using a K-function test statistic. We assessed the prevalence ratio of the PM(2.5) association with CKD incidence using a mixed effect Cox model, respectively. RESULTS: Patients (n = 20,289) in the fourth (PM(2.5) > 10.4), third (10.3 < PM(2.5) < 10.8) and second quartile (9.9 < PM(2.5) < 10.3) vs. the first quartile (<9.9 μg/m(3)) had a 2.52[2.21, 2.87], 2.18[1.95, 2.45], and 1.72[1.52, 1.97] hazard rate of developing CKD in the fully adjusted models, respectively. We identified spatial heterogeneities and evidence of CKD clustering across our study region, but this spatial variation was accounted for by air pollution and individual covariates. SIGNIFICANCE: Exposure to higher PM(2.5) is associated with a greater risk for incident CKD. Improvements in air quality, specifically at hotspots, may reduce CKD.
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spelling pubmed-82020502021-06-15 The association between fine particulate matter (PM(2.5)) and chronic kidney disease using electronic health record data in urban Minnesota Ghazi, Lama Drawz, Paul E. Berman, Jesse D. J Expo Sci Environ Epidemiol Article BACKGROUND: Recent evidence has shown that fine particulate matter (PM(2.5)) may be an important environmental risk factor for chronic kidney disease (CKD), but few studies have examined this association for individual patients using fine spatial data. OBJECTIVE: To investigate the association between PM(2.5) and CKD (estimated glomerular filtration rate [eGFR]<45 ml/min/1.73 m(2)) in the Twin-Cities area in Minnesota using a large electronic health care database (2012–2019). METHODS: We estimated the previous 1-year average PM(2.5) from the first eGFR (measured with the CKD Epidemiology Collaboration equation using the first available creatinine measure during the baseline period [2012–2014]) using Environmental Protection Agency downscaler modeling data at the census tract level. We evaluated the spatial relative risk and clustering of CKD prevalence using a K-function test statistic. We assessed the prevalence ratio of the PM(2.5) association with CKD incidence using a mixed effect Cox model, respectively. RESULTS: Patients (n = 20,289) in the fourth (PM(2.5) > 10.4), third (10.3 < PM(2.5) < 10.8) and second quartile (9.9 < PM(2.5) < 10.3) vs. the first quartile (<9.9 μg/m(3)) had a 2.52[2.21, 2.87], 2.18[1.95, 2.45], and 1.72[1.52, 1.97] hazard rate of developing CKD in the fully adjusted models, respectively. We identified spatial heterogeneities and evidence of CKD clustering across our study region, but this spatial variation was accounted for by air pollution and individual covariates. SIGNIFICANCE: Exposure to higher PM(2.5) is associated with a greater risk for incident CKD. Improvements in air quality, specifically at hotspots, may reduce CKD. Nature Publishing Group US 2021-06-14 2022 /pmc/articles/PMC8202050/ /pubmed/34127789 http://dx.doi.org/10.1038/s41370-021-00351-3 Text en © The Author(s), under exclusive licence to Springer Nature America, Inc. 2021 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Article
Ghazi, Lama
Drawz, Paul E.
Berman, Jesse D.
The association between fine particulate matter (PM(2.5)) and chronic kidney disease using electronic health record data in urban Minnesota
title The association between fine particulate matter (PM(2.5)) and chronic kidney disease using electronic health record data in urban Minnesota
title_full The association between fine particulate matter (PM(2.5)) and chronic kidney disease using electronic health record data in urban Minnesota
title_fullStr The association between fine particulate matter (PM(2.5)) and chronic kidney disease using electronic health record data in urban Minnesota
title_full_unstemmed The association between fine particulate matter (PM(2.5)) and chronic kidney disease using electronic health record data in urban Minnesota
title_short The association between fine particulate matter (PM(2.5)) and chronic kidney disease using electronic health record data in urban Minnesota
title_sort association between fine particulate matter (pm(2.5)) and chronic kidney disease using electronic health record data in urban minnesota
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8202050/
https://www.ncbi.nlm.nih.gov/pubmed/34127789
http://dx.doi.org/10.1038/s41370-021-00351-3
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