County-level air quality and the prevalence of diagnosed chronic kidney disease in the US Medicare population
Considerable geographic variation exists in the prevalence of chronic kidney disease across the United States. While some of this variability can be explained by differences in patient-level risk factors, substantial variability still exists. We hypothesize this may be due to understudied environmen...
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| description | Considerable geographic variation exists in the prevalence of chronic kidney disease across the United States. While some of this variability can be explained by differences in patient-level risk factors, substantial variability still exists. We hypothesize this may be due to understudied environmental exposures such as air pollution.
Using data on 1.1 million persons from the 2010 5% Medicare sample and Environmental Protection Agency air-quality measures, we examined the association between county-level particulate matter ≤2.5 μm (PM2.5) and the prevalence of diagnosed CKD, based on claims. Modified Poisson regression was used to estimate associations (prevalence ratios [PR]) between county PM2.5 concentration and individual-level diagnosis of CKD, adjusting for age, sex, race/ethnicity, hypertension, diabetes, and urban/rural status.
Prevalence of diagnosed CKD ranged from 0% to 60% by county (median = 16%). As a continuous variable, PM2.5 concentration shows adjusted PR of diagnosed CKD = 1.03 (95% CI: 1.02-1.05; p |
| doi_str_mv | 10.1371/journal.pone.0200612 |
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Using data on 1.1 million persons from the 2010 5% Medicare sample and Environmental Protection Agency air-quality measures, we examined the association between county-level particulate matter ≤2.5 μm (PM2.5) and the prevalence of diagnosed CKD, based on claims. Modified Poisson regression was used to estimate associations (prevalence ratios [PR]) between county PM2.5 concentration and individual-level diagnosis of CKD, adjusting for age, sex, race/ethnicity, hypertension, diabetes, and urban/rural status.
Prevalence of diagnosed CKD ranged from 0% to 60% by county (median = 16%). As a continuous variable, PM2.5 concentration shows adjusted PR of diagnosed CKD = 1.03 (95% CI: 1.02-1.05; p<0.001) for an increase of 4 μg/m3 in PM2.5. Investigation by quartiles shows an elevated prevalence of diagnosed CKD for mean PM2.5 levels ≥14 μg/m3 (highest quartile: PR = 1.05, 95% CI: 1.03-1.07), which is consistent with current ambient air quality standard of 12 μg/m3, but much lower than the level typically considered healthy for sensitive groups (~40 μg/m3).
A positive association was observed between county-level PM2.5 concentration and diagnosed CKD. The reliance on CKD diagnostic codes likely identified associations with the most severe CKD cases. These results can be strengthened by exploring laboratory-based diagnosis of CKD, individual measures of exposure to multiple pollutants, and more control of confounding.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0200612</identifier><identifier>PMID: 30063741</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Aged ; Aged, 80 and over ; Air Pollutants - toxicity ; Air pollution ; Air Pollution - statistics & numerical data ; Air pollution measurements ; Air quality ; Air quality measurements ; Airborne particulates ; Atherosclerosis ; Biology and Life Sciences ; Cardiovascular disease ; Chan, Priscilla ; Continuity (mathematics) ; Cross-Sectional Studies ; Diabetes ; Diabetes mellitus ; Diagnosis ; Diagnostic systems ; Disease control ; Disease prevention ; Engineering and Technology ; Environmental Exposure - adverse effects ; Environmental protection ; Epidemiology ; Exposure ; Female ; Government programs ; Health care ; Health surveillance ; Hospitals ; Humans ; Hypertension ; Influence ; Internal medicine ; Kidney diseases ; Kidneys ; Male ; Medicare - statistics & numerical data ; Medicine ; Medicine and Health Sciences ; Metabolism ; Minority & ethnic groups ; Mortality ; Nephrology ; Outdoor air quality ; Particulate matter ; Particulate Matter - toxicity ; People and places ; Physical Sciences ; Poisson density functions ; Pollutants ; Pollution control ; Prevalence ; Prevalence studies (Epidemiology) ; Public health ; Quality standards ; Quartiles ; Renal Insufficiency, Chronic - epidemiology ; Renal Insufficiency, Chronic - etiology ; Risk analysis ; Risk Assessment ; Risk factors ; Social Sciences ; Statistical analysis ; United States ; United States Environmental Protection Agency - statistics & numerical data ; Variability ; Zuckerberg, Mark</subject><ispartof>PloS one, 2018-07, Vol.13 (7), p.e0200612</ispartof><rights>COPYRIGHT 2018 Public Library of Science</rights><rights>This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication: https://creativecommons.org/publicdomain/zero/1.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c692t-3b65f0b322cbcf24b022b6be4272f555e73fcf01fb16398090a6396cf8ebc4583</citedby><cites>FETCH-LOGICAL-c692t-3b65f0b322cbcf24b022b6be4272f555e73fcf01fb16398090a6396cf8ebc4583</cites><orcidid>0000-0002-9069-9489</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC6067706/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC6067706/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,2096,2915,23845,27901,27902,53766,53768,79343,79344</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/30063741$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Bragg-Gresham, Jennifer</creatorcontrib><creatorcontrib>Morgenstern, Hal</creatorcontrib><creatorcontrib>McClellan, William</creatorcontrib><creatorcontrib>Saydah, Sharon</creatorcontrib><creatorcontrib>Pavkov, Meda</creatorcontrib><creatorcontrib>Williams, Desmond</creatorcontrib><creatorcontrib>Powe, Neil</creatorcontrib><creatorcontrib>Tuot, Delphine</creatorcontrib><creatorcontrib>Hsu, Raymond</creatorcontrib><creatorcontrib>Saran, Rajiv</creatorcontrib><creatorcontrib>Centers for Disease Control and Prevention CKD Surveillance System</creatorcontrib><creatorcontrib>for the Centers for Disease Control and Prevention CKD Surveillance System</creatorcontrib><title>County-level air quality and the prevalence of diagnosed chronic kidney disease in the US Medicare population</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>Considerable geographic variation exists in the prevalence of chronic kidney disease across the United States. While some of this variability can be explained by differences in patient-level risk factors, substantial variability still exists. We hypothesize this may be due to understudied environmental exposures such as air pollution.
Using data on 1.1 million persons from the 2010 5% Medicare sample and Environmental Protection Agency air-quality measures, we examined the association between county-level particulate matter ≤2.5 μm (PM2.5) and the prevalence of diagnosed CKD, based on claims. Modified Poisson regression was used to estimate associations (prevalence ratios [PR]) between county PM2.5 concentration and individual-level diagnosis of CKD, adjusting for age, sex, race/ethnicity, hypertension, diabetes, and urban/rural status.
Prevalence of diagnosed CKD ranged from 0% to 60% by county (median = 16%). As a continuous variable, PM2.5 concentration shows adjusted PR of diagnosed CKD = 1.03 (95% CI: 1.02-1.05; p<0.001) for an increase of 4 μg/m3 in PM2.5. Investigation by quartiles shows an elevated prevalence of diagnosed CKD for mean PM2.5 levels ≥14 μg/m3 (highest quartile: PR = 1.05, 95% CI: 1.03-1.07), which is consistent with current ambient air quality standard of 12 μg/m3, but much lower than the level typically considered healthy for sensitive groups (~40 μg/m3).
A positive association was observed between county-level PM2.5 concentration and diagnosed CKD. The reliance on CKD diagnostic codes likely identified associations with the most severe CKD cases. These results can be strengthened by exploring laboratory-based diagnosis of CKD, individual measures of exposure to multiple pollutants, and more control of confounding.</description><subject>Aged</subject><subject>Aged, 80 and over</subject><subject>Air Pollutants - toxicity</subject><subject>Air pollution</subject><subject>Air Pollution - statistics & numerical data</subject><subject>Air pollution measurements</subject><subject>Air quality</subject><subject>Air quality measurements</subject><subject>Airborne particulates</subject><subject>Atherosclerosis</subject><subject>Biology and Life Sciences</subject><subject>Cardiovascular disease</subject><subject>Chan, Priscilla</subject><subject>Continuity (mathematics)</subject><subject>Cross-Sectional Studies</subject><subject>Diabetes</subject><subject>Diabetes mellitus</subject><subject>Diagnosis</subject><subject>Diagnostic systems</subject><subject>Disease control</subject><subject>Disease prevention</subject><subject>Engineering and Technology</subject><subject>Environmental Exposure - adverse effects</subject><subject>Environmental protection</subject><subject>Epidemiology</subject><subject>Exposure</subject><subject>Female</subject><subject>Government programs</subject><subject>Health care</subject><subject>Health surveillance</subject><subject>Hospitals</subject><subject>Humans</subject><subject>Hypertension</subject><subject>Influence</subject><subject>Internal medicine</subject><subject>Kidney diseases</subject><subject>Kidneys</subject><subject>Male</subject><subject>Medicare - statistics & numerical data</subject><subject>Medicine</subject><subject>Medicine and Health Sciences</subject><subject>Metabolism</subject><subject>Minority & ethnic groups</subject><subject>Mortality</subject><subject>Nephrology</subject><subject>Outdoor air quality</subject><subject>Particulate matter</subject><subject>Particulate Matter - toxicity</subject><subject>People and places</subject><subject>Physical Sciences</subject><subject>Poisson density functions</subject><subject>Pollutants</subject><subject>Pollution control</subject><subject>Prevalence</subject><subject>Prevalence studies (Epidemiology)</subject><subject>Public health</subject><subject>Quality standards</subject><subject>Quartiles</subject><subject>Renal Insufficiency, Chronic - epidemiology</subject><subject>Renal Insufficiency, Chronic - etiology</subject><subject>Risk analysis</subject><subject>Risk Assessment</subject><subject>Risk factors</subject><subject>Social Sciences</subject><subject>Statistical analysis</subject><subject>United States</subject><subject>United States Environmental Protection Agency - statistics & numerical data</subject><subject>Variability</subject><subject>Zuckerberg, Mark</subject><issn>1932-6203</issn><issn>1932-6203</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>BENPR</sourceid><sourceid>DOA</sourceid><recordid>eNqNkl2LEzEYhQdR3LX6D0QDguBFaz5mMjM3C0vxo7Cy4LrehkzmTZuaJt1kpth_b7qdXTqgILlISJ5zEk5Olr0meEZYST6ufR-ctLOtdzDDFGNO6JPsnNSMTjnF7OnJ-ix7EeMa44JVnD_PzliiWZmT82wz973r9lMLO7BImoDuemlNt0fStahbAdoG2EkLTgHyGrVGLp2P0CK1Ct4ZhX6Z1sE-HUSQEZBx96rbG_QNWqNkSA5-21vZGe9eZs-0tBFeDfMku_386cf86_Tq-stifnk1Vbym3ZQ1vNC4YZSqRmmaN5jShjeQ05LqoiigZFppTHRDOKsrXGOZZq50BY3Ki4pNsrdH3631UQxJRUFxhUte8bxIxOJItF6uxTaYjQx74aUR9xs-LIUMnVEWhGIVtLxiuuZFXpVt3VBaVZyBVAXBlCWvi-G2vtlAq8B1QdqR6fjEmZVY-p3gmJdl-olJ9m4wCP6uh9j948kDtUzfIYzTPpmpjYlKXKaHpSAIPXjN_kKl0cLGqNQVbdL-SPBhJEhMB7-7pexjFIub7__PXv8cs-9P2BVI262it_2hB3EM5kdQBR9jAP2YHMHiUPWHNMSh6mKoepK9OU39UfTQbfYHNFT5PQ</recordid><startdate>20180731</startdate><enddate>20180731</enddate><creator>Bragg-Gresham, Jennifer</creator><creator>Morgenstern, Hal</creator><creator>McClellan, William</creator><creator>Saydah, Sharon</creator><creator>Pavkov, Meda</creator><creator>Williams, Desmond</creator><creator>Powe, Neil</creator><creator>Tuot, Delphine</creator><creator>Hsu, Raymond</creator><creator>Saran, Rajiv</creator><general>Public Library of Science</general><general>Public Library of Science (PLoS)</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>IOV</scope><scope>ISR</scope><scope>3V.</scope><scope>7QG</scope><scope>7QL</scope><scope>7QO</scope><scope>7RV</scope><scope>7SN</scope><scope>7SS</scope><scope>7T5</scope><scope>7TG</scope><scope>7TM</scope><scope>7U9</scope><scope>7X2</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>D1I</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>H94</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>KB.</scope><scope>KB0</scope><scope>KL.</scope><scope>L6V</scope><scope>LK8</scope><scope>M0K</scope><scope>M0S</scope><scope>M1P</scope><scope>M7N</scope><scope>M7P</scope><scope>M7S</scope><scope>NAPCQ</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PATMY</scope><scope>PDBOC</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope><scope>PYCSY</scope><scope>RC3</scope><scope>5PM</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0002-9069-9489</orcidid></search><sort><creationdate>20180731</creationdate><title>County-level air quality and the prevalence of diagnosed chronic kidney disease in the US Medicare population</title><author>Bragg-Gresham, Jennifer ; Morgenstern, Hal ; McClellan, William ; Saydah, Sharon ; Pavkov, Meda ; Williams, Desmond ; Powe, Neil ; Tuot, Delphine ; Hsu, Raymond ; Saran, Rajiv</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c692t-3b65f0b322cbcf24b022b6be4272f555e73fcf01fb16398090a6396cf8ebc4583</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Aged</topic><topic>Aged, 80 and over</topic><topic>Air Pollutants - toxicity</topic><topic>Air pollution</topic><topic>Air Pollution - statistics & numerical data</topic><topic>Air pollution measurements</topic><topic>Air quality</topic><topic>Air quality measurements</topic><topic>Airborne particulates</topic><topic>Atherosclerosis</topic><topic>Biology and Life Sciences</topic><topic>Cardiovascular disease</topic><topic>Chan, Priscilla</topic><topic>Continuity (mathematics)</topic><topic>Cross-Sectional Studies</topic><topic>Diabetes</topic><topic>Diabetes mellitus</topic><topic>Diagnosis</topic><topic>Diagnostic systems</topic><topic>Disease control</topic><topic>Disease prevention</topic><topic>Engineering and Technology</topic><topic>Environmental Exposure - adverse effects</topic><topic>Environmental protection</topic><topic>Epidemiology</topic><topic>Exposure</topic><topic>Female</topic><topic>Government programs</topic><topic>Health care</topic><topic>Health surveillance</topic><topic>Hospitals</topic><topic>Humans</topic><topic>Hypertension</topic><topic>Influence</topic><topic>Internal medicine</topic><topic>Kidney diseases</topic><topic>Kidneys</topic><topic>Male</topic><topic>Medicare - 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While some of this variability can be explained by differences in patient-level risk factors, substantial variability still exists. We hypothesize this may be due to understudied environmental exposures such as air pollution.
Using data on 1.1 million persons from the 2010 5% Medicare sample and Environmental Protection Agency air-quality measures, we examined the association between county-level particulate matter ≤2.5 μm (PM2.5) and the prevalence of diagnosed CKD, based on claims. Modified Poisson regression was used to estimate associations (prevalence ratios [PR]) between county PM2.5 concentration and individual-level diagnosis of CKD, adjusting for age, sex, race/ethnicity, hypertension, diabetes, and urban/rural status.
Prevalence of diagnosed CKD ranged from 0% to 60% by county (median = 16%). As a continuous variable, PM2.5 concentration shows adjusted PR of diagnosed CKD = 1.03 (95% CI: 1.02-1.05; p<0.001) for an increase of 4 μg/m3 in PM2.5. Investigation by quartiles shows an elevated prevalence of diagnosed CKD for mean PM2.5 levels ≥14 μg/m3 (highest quartile: PR = 1.05, 95% CI: 1.03-1.07), which is consistent with current ambient air quality standard of 12 μg/m3, but much lower than the level typically considered healthy for sensitive groups (~40 μg/m3).
A positive association was observed between county-level PM2.5 concentration and diagnosed CKD. The reliance on CKD diagnostic codes likely identified associations with the most severe CKD cases. These results can be strengthened by exploring laboratory-based diagnosis of CKD, individual measures of exposure to multiple pollutants, and more control of confounding.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>30063741</pmid><doi>10.1371/journal.pone.0200612</doi><orcidid>https://orcid.org/0000-0002-9069-9489</orcidid><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1932-6203 |
| ispartof | PloS one, 2018-07, Vol.13 (7), p.e0200612 |
| issn | 1932-6203 1932-6203 |
| language | eng |
| recordid | cdi_plos_journals_2080768645 |
| source | MEDLINE; DOAJ Directory of Open Access Journals; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; PubMed Central; Free Full-Text Journals in Chemistry; Public Library of Science (PLoS) |
| subjects | Aged Aged, 80 and over Air Pollutants - toxicity Air pollution Air Pollution - statistics & numerical data Air pollution measurements Air quality Air quality measurements Airborne particulates Atherosclerosis Biology and Life Sciences Cardiovascular disease Chan, Priscilla Continuity (mathematics) Cross-Sectional Studies Diabetes Diabetes mellitus Diagnosis Diagnostic systems Disease control Disease prevention Engineering and Technology Environmental Exposure - adverse effects Environmental protection Epidemiology Exposure Female Government programs Health care Health surveillance Hospitals Humans Hypertension Influence Internal medicine Kidney diseases Kidneys Male Medicare - statistics & numerical data Medicine Medicine and Health Sciences Metabolism Minority & ethnic groups Mortality Nephrology Outdoor air quality Particulate matter Particulate Matter - toxicity People and places Physical Sciences Poisson density functions Pollutants Pollution control Prevalence Prevalence studies (Epidemiology) Public health Quality standards Quartiles Renal Insufficiency, Chronic - epidemiology Renal Insufficiency, Chronic - etiology Risk analysis Risk Assessment Risk factors Social Sciences Statistical analysis United States United States Environmental Protection Agency - statistics & numerical data Variability Zuckerberg, Mark |
| title | County-level air quality and the prevalence of diagnosed chronic kidney disease in the US Medicare population |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-02T22%3A01%3A41IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_plos_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=County-level%20air%20quality%20and%20the%20prevalence%20of%20diagnosed%20chronic%20kidney%20disease%20in%20the%20US%20Medicare%20population&rft.jtitle=PloS%20one&rft.au=Bragg-Gresham,%20Jennifer&rft.aucorp=Centers%20for%20Disease%20Control%20and%20Prevention%20CKD%20Surveillance%20System&rft.date=2018-07-31&rft.volume=13&rft.issue=7&rft.spage=e0200612&rft.pages=e0200612-&rft.issn=1932-6203&rft.eissn=1932-6203&rft_id=info:doi/10.1371/journal.pone.0200612&rft_dat=%3Cgale_plos_%3EA548398126%3C/gale_plos_%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2080768645&rft_id=info:pmid/30063741&rft_galeid=A548398126&rft_doaj_id=oai_doaj_org_article_c38ed683f965487d9b228863eac51023&rfr_iscdi=true |