Spatial Association between Speciated Fine Particles and Mortality
Particulate matter (PM) has been linked to a range of serious cardiovascular and respiratory health problems, including premature mortality. The main objective of our research is to quantify uncertainties about the impacts of fine PM exposure on mortality. We develop a multivariate spatial regressio...
Gespeichert in:
| Veröffentlicht in: | Biometrics 2006-09, Vol.62 (3), p.855-863 |
|---|---|
| Hauptverfasser: | , , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 863 |
|---|---|
| container_issue | 3 |
| container_start_page | 855 |
| container_title | Biometrics |
| container_volume | 62 |
| creator | Fuentes, Montserrat Song, Hae‐Ryoung Ghosh, Sujit K Holland, David M Davis, Jerry M |
| description | Particulate matter (PM) has been linked to a range of serious cardiovascular and respiratory health problems, including premature mortality. The main objective of our research is to quantify uncertainties about the impacts of fine PM exposure on mortality. We develop a multivariate spatial regression model for the estimation of the risk of mortality associated with fine PM and its components across all counties in the conterminous United States. We characterize different sources of uncertainty in the data and model the spatial structure of the mortality data and the speciated fine PM. We consider a flexible Bayesian hierarchical model for a space‐time series of counts (mortality) by constructing a likelihood‐based version of a generalized Poisson regression model that combines methods for point‐level misaligned data and change of support regression. Our results seem to suggest an increase by a factor of two in the risk of mortality due to fine particles with respect to coarse particles. Our study also shows that in the Western United States, the nitrate and crustal components of the speciated fine PM seem to have more impact on mortality than the other components. On the other hand, in the Eastern United States, sulfate and ammonium explain most of the fine PM effect. |
| doi_str_mv | 10.1111/j.1541-0420.2006.00526.x |
| format | Article |
| fullrecord | <record><control><sourceid>jstor_proqu</sourceid><recordid>TN_cdi_proquest_miscellaneous_33525126</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><jstor_id>4124596</jstor_id><sourcerecordid>4124596</sourcerecordid><originalsourceid>FETCH-LOGICAL-c5746-2b459d65246b3ac3aaec54c9688fc81b23e97ef11584fefae3260d0a4ebd01523</originalsourceid><addsrcrecordid>eNqNkktv1DAURi0EokPhHyCIWLBL8DvJgkVb0VLRUqRpBermyklukEMmHuyMOvPvcZrRILHCGz--c6_sIxOSMJqxOD50GVOSpVRymnFKdUap4jrbPiGLQ_CULGiMUiHZjyPyIoQubktF-XNyxHRZSMHLBTldrs1oTZ-chOBqG9duSCocHxCHZLnG6Qib5NwOmHwzfrR1jyExQ5NcOz-a3o67l-RZa_qAr_bzMbk7_3R79jm9urm4PDu5SmuVS53ySqqy0YpLXQlTC2OwVrIudVG0dcEqLrDMsWVMFbLF1qDgmjbUSKwayhQXx-T93Hft3e8NhhFWNtTY92ZAtwkghOKKcR3Bd_-Andv4Id4NOBOFUFKqCBUzVHsXgscW1t6ujN8BozBJhg4mlzC5hEkyPEqGbSx9s--_qVbY_C3cW43Axxl4sD3u_rsxnF7eXKvHB7ye67swOn-ol4xHhVOczrENI24PsfG_QOciV_D96wVILe_LL_oW7iP_duZb48D89DbA3ZJHp9P_yCll4g8WeKsK</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>213835445</pqid></control><display><type>article</type><title>Spatial Association between Speciated Fine Particles and Mortality</title><source>Jstor Complete Legacy</source><source>Oxford University Press Journals All Titles (1996-Current)</source><source>MEDLINE</source><source>Wiley Online Library Journals Frontfile Complete</source><source>JSTOR Mathematics & Statistics</source><creator>Fuentes, Montserrat ; Song, Hae‐Ryoung ; Ghosh, Sujit K ; Holland, David M ; Davis, Jerry M</creator><creatorcontrib>Fuentes, Montserrat ; Song, Hae‐Ryoung ; Ghosh, Sujit K ; Holland, David M ; Davis, Jerry M</creatorcontrib><description>Particulate matter (PM) has been linked to a range of serious cardiovascular and respiratory health problems, including premature mortality. The main objective of our research is to quantify uncertainties about the impacts of fine PM exposure on mortality. We develop a multivariate spatial regression model for the estimation of the risk of mortality associated with fine PM and its components across all counties in the conterminous United States. We characterize different sources of uncertainty in the data and model the spatial structure of the mortality data and the speciated fine PM. We consider a flexible Bayesian hierarchical model for a space‐time series of counts (mortality) by constructing a likelihood‐based version of a generalized Poisson regression model that combines methods for point‐level misaligned data and change of support regression. Our results seem to suggest an increase by a factor of two in the risk of mortality due to fine particles with respect to coarse particles. Our study also shows that in the Western United States, the nitrate and crustal components of the speciated fine PM seem to have more impact on mortality than the other components. On the other hand, in the Eastern United States, sulfate and ammonium explain most of the fine PM effect.</description><identifier>ISSN: 0006-341X</identifier><identifier>EISSN: 1541-0420</identifier><identifier>DOI: 10.1111/j.1541-0420.2006.00526.x</identifier><identifier>PMID: 16984329</identifier><identifier>CODEN: BIOMA5</identifier><language>eng</language><publisher>Malden, USA: Blackwell Publishing Inc</publisher><subject>Air Pollutants - toxicity ; air pollution ; Airborne particulates ; Ambient air pollution ; Ammonia ; ammonium nitrogen ; Bayes Theorem ; Bayesian analysis ; Bayesian hierarchical models ; Bayesian theory ; Biometrics ; Biometry ; Cardiovascular Diseases - etiology ; Cardiovascular Diseases - mortality ; Conditional autoregressive models ; Environmental agencies ; Environmental epidemiology ; Geographic regions ; Health risk assessment ; Human exposure ; Humans ; Modeling ; Models, Biological ; Models, Statistical ; Mortality ; nitrate nitrogen ; Nitrates ; Ozone ; Particle Size ; Particulate matter ; particulates ; Poisson distribution ; Quantum statistics ; Regression Analysis ; Respiratory Tract Diseases - etiology ; Respiratory Tract Diseases - mortality ; Risk ; risk estimate ; Spatial models ; Spatial statistics ; sulfates ; Sulfur ; Time series ; uncertainty ; United States - epidemiology ; Weather</subject><ispartof>Biometrics, 2006-09, Vol.62 (3), p.855-863</ispartof><rights>Copyright 2006 The International Biometric Society</rights><rights>2006, The International Biometric Society</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c5746-2b459d65246b3ac3aaec54c9688fc81b23e97ef11584fefae3260d0a4ebd01523</citedby><cites>FETCH-LOGICAL-c5746-2b459d65246b3ac3aaec54c9688fc81b23e97ef11584fefae3260d0a4ebd01523</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.jstor.org/stable/pdf/4124596$$EPDF$$P50$$Gjstor$$H</linktopdf><linktohtml>$$Uhttps://www.jstor.org/stable/4124596$$EHTML$$P50$$Gjstor$$H</linktohtml><link.rule.ids>314,776,780,799,828,1411,27903,27904,45552,45553,57994,57998,58227,58231</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/16984329$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Fuentes, Montserrat</creatorcontrib><creatorcontrib>Song, Hae‐Ryoung</creatorcontrib><creatorcontrib>Ghosh, Sujit K</creatorcontrib><creatorcontrib>Holland, David M</creatorcontrib><creatorcontrib>Davis, Jerry M</creatorcontrib><title>Spatial Association between Speciated Fine Particles and Mortality</title><title>Biometrics</title><addtitle>Biometrics</addtitle><description>Particulate matter (PM) has been linked to a range of serious cardiovascular and respiratory health problems, including premature mortality. The main objective of our research is to quantify uncertainties about the impacts of fine PM exposure on mortality. We develop a multivariate spatial regression model for the estimation of the risk of mortality associated with fine PM and its components across all counties in the conterminous United States. We characterize different sources of uncertainty in the data and model the spatial structure of the mortality data and the speciated fine PM. We consider a flexible Bayesian hierarchical model for a space‐time series of counts (mortality) by constructing a likelihood‐based version of a generalized Poisson regression model that combines methods for point‐level misaligned data and change of support regression. Our results seem to suggest an increase by a factor of two in the risk of mortality due to fine particles with respect to coarse particles. Our study also shows that in the Western United States, the nitrate and crustal components of the speciated fine PM seem to have more impact on mortality than the other components. On the other hand, in the Eastern United States, sulfate and ammonium explain most of the fine PM effect.</description><subject>Air Pollutants - toxicity</subject><subject>air pollution</subject><subject>Airborne particulates</subject><subject>Ambient air pollution</subject><subject>Ammonia</subject><subject>ammonium nitrogen</subject><subject>Bayes Theorem</subject><subject>Bayesian analysis</subject><subject>Bayesian hierarchical models</subject><subject>Bayesian theory</subject><subject>Biometrics</subject><subject>Biometry</subject><subject>Cardiovascular Diseases - etiology</subject><subject>Cardiovascular Diseases - mortality</subject><subject>Conditional autoregressive models</subject><subject>Environmental agencies</subject><subject>Environmental epidemiology</subject><subject>Geographic regions</subject><subject>Health risk assessment</subject><subject>Human exposure</subject><subject>Humans</subject><subject>Modeling</subject><subject>Models, Biological</subject><subject>Models, Statistical</subject><subject>Mortality</subject><subject>nitrate nitrogen</subject><subject>Nitrates</subject><subject>Ozone</subject><subject>Particle Size</subject><subject>Particulate matter</subject><subject>particulates</subject><subject>Poisson distribution</subject><subject>Quantum statistics</subject><subject>Regression Analysis</subject><subject>Respiratory Tract Diseases - etiology</subject><subject>Respiratory Tract Diseases - mortality</subject><subject>Risk</subject><subject>risk estimate</subject><subject>Spatial models</subject><subject>Spatial statistics</subject><subject>sulfates</subject><subject>Sulfur</subject><subject>Time series</subject><subject>uncertainty</subject><subject>United States - epidemiology</subject><subject>Weather</subject><issn>0006-341X</issn><issn>1541-0420</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2006</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqNkktv1DAURi0EokPhHyCIWLBL8DvJgkVb0VLRUqRpBermyklukEMmHuyMOvPvcZrRILHCGz--c6_sIxOSMJqxOD50GVOSpVRymnFKdUap4jrbPiGLQ_CULGiMUiHZjyPyIoQubktF-XNyxHRZSMHLBTldrs1oTZ-chOBqG9duSCocHxCHZLnG6Qib5NwOmHwzfrR1jyExQ5NcOz-a3o67l-RZa_qAr_bzMbk7_3R79jm9urm4PDu5SmuVS53ySqqy0YpLXQlTC2OwVrIudVG0dcEqLrDMsWVMFbLF1qDgmjbUSKwayhQXx-T93Hft3e8NhhFWNtTY92ZAtwkghOKKcR3Bd_-Andv4Id4NOBOFUFKqCBUzVHsXgscW1t6ujN8BozBJhg4mlzC5hEkyPEqGbSx9s--_qVbY_C3cW43Axxl4sD3u_rsxnF7eXKvHB7ye67swOn-ol4xHhVOczrENI24PsfG_QOciV_D96wVILe_LL_oW7iP_duZb48D89DbA3ZJHp9P_yCll4g8WeKsK</recordid><startdate>200609</startdate><enddate>200609</enddate><creator>Fuentes, Montserrat</creator><creator>Song, Hae‐Ryoung</creator><creator>Ghosh, Sujit K</creator><creator>Holland, David M</creator><creator>Davis, Jerry M</creator><general>Blackwell Publishing Inc</general><general>International Biometric Society</general><general>Blackwell Publishing Ltd</general><scope>FBQ</scope><scope>BSCLL</scope><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>JQ2</scope><scope>7SC</scope><scope>8FD</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope></search><sort><creationdate>200609</creationdate><title>Spatial Association between Speciated Fine Particles and Mortality</title><author>Fuentes, Montserrat ; Song, Hae‐Ryoung ; Ghosh, Sujit K ; Holland, David M ; Davis, Jerry M</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c5746-2b459d65246b3ac3aaec54c9688fc81b23e97ef11584fefae3260d0a4ebd01523</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2006</creationdate><topic>Air Pollutants - toxicity</topic><topic>air pollution</topic><topic>Airborne particulates</topic><topic>Ambient air pollution</topic><topic>Ammonia</topic><topic>ammonium nitrogen</topic><topic>Bayes Theorem</topic><topic>Bayesian analysis</topic><topic>Bayesian hierarchical models</topic><topic>Bayesian theory</topic><topic>Biometrics</topic><topic>Biometry</topic><topic>Cardiovascular Diseases - etiology</topic><topic>Cardiovascular Diseases - mortality</topic><topic>Conditional autoregressive models</topic><topic>Environmental agencies</topic><topic>Environmental epidemiology</topic><topic>Geographic regions</topic><topic>Health risk assessment</topic><topic>Human exposure</topic><topic>Humans</topic><topic>Modeling</topic><topic>Models, Biological</topic><topic>Models, Statistical</topic><topic>Mortality</topic><topic>nitrate nitrogen</topic><topic>Nitrates</topic><topic>Ozone</topic><topic>Particle Size</topic><topic>Particulate matter</topic><topic>particulates</topic><topic>Poisson distribution</topic><topic>Quantum statistics</topic><topic>Regression Analysis</topic><topic>Respiratory Tract Diseases - etiology</topic><topic>Respiratory Tract Diseases - mortality</topic><topic>Risk</topic><topic>risk estimate</topic><topic>Spatial models</topic><topic>Spatial statistics</topic><topic>sulfates</topic><topic>Sulfur</topic><topic>Time series</topic><topic>uncertainty</topic><topic>United States - epidemiology</topic><topic>Weather</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Fuentes, Montserrat</creatorcontrib><creatorcontrib>Song, Hae‐Ryoung</creatorcontrib><creatorcontrib>Ghosh, Sujit K</creatorcontrib><creatorcontrib>Holland, David M</creatorcontrib><creatorcontrib>Davis, Jerry M</creatorcontrib><collection>AGRIS</collection><collection>Istex</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Computer Science Collection</collection><collection>Computer and Information Systems Abstracts</collection><collection>Technology Research Database</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>Biometrics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Fuentes, Montserrat</au><au>Song, Hae‐Ryoung</au><au>Ghosh, Sujit K</au><au>Holland, David M</au><au>Davis, Jerry M</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Spatial Association between Speciated Fine Particles and Mortality</atitle><jtitle>Biometrics</jtitle><addtitle>Biometrics</addtitle><date>2006-09</date><risdate>2006</risdate><volume>62</volume><issue>3</issue><spage>855</spage><epage>863</epage><pages>855-863</pages><issn>0006-341X</issn><eissn>1541-0420</eissn><coden>BIOMA5</coden><abstract>Particulate matter (PM) has been linked to a range of serious cardiovascular and respiratory health problems, including premature mortality. The main objective of our research is to quantify uncertainties about the impacts of fine PM exposure on mortality. We develop a multivariate spatial regression model for the estimation of the risk of mortality associated with fine PM and its components across all counties in the conterminous United States. We characterize different sources of uncertainty in the data and model the spatial structure of the mortality data and the speciated fine PM. We consider a flexible Bayesian hierarchical model for a space‐time series of counts (mortality) by constructing a likelihood‐based version of a generalized Poisson regression model that combines methods for point‐level misaligned data and change of support regression. Our results seem to suggest an increase by a factor of two in the risk of mortality due to fine particles with respect to coarse particles. Our study also shows that in the Western United States, the nitrate and crustal components of the speciated fine PM seem to have more impact on mortality than the other components. On the other hand, in the Eastern United States, sulfate and ammonium explain most of the fine PM effect.</abstract><cop>Malden, USA</cop><pub>Blackwell Publishing Inc</pub><pmid>16984329</pmid><doi>10.1111/j.1541-0420.2006.00526.x</doi><tpages>9</tpages></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0006-341X |
| ispartof | Biometrics, 2006-09, Vol.62 (3), p.855-863 |
| issn | 0006-341X 1541-0420 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_33525126 |
| source | Jstor Complete Legacy; Oxford University Press Journals All Titles (1996-Current); MEDLINE; Wiley Online Library Journals Frontfile Complete; JSTOR Mathematics & Statistics |
| subjects | Air Pollutants - toxicity air pollution Airborne particulates Ambient air pollution Ammonia ammonium nitrogen Bayes Theorem Bayesian analysis Bayesian hierarchical models Bayesian theory Biometrics Biometry Cardiovascular Diseases - etiology Cardiovascular Diseases - mortality Conditional autoregressive models Environmental agencies Environmental epidemiology Geographic regions Health risk assessment Human exposure Humans Modeling Models, Biological Models, Statistical Mortality nitrate nitrogen Nitrates Ozone Particle Size Particulate matter particulates Poisson distribution Quantum statistics Regression Analysis Respiratory Tract Diseases - etiology Respiratory Tract Diseases - mortality Risk risk estimate Spatial models Spatial statistics sulfates Sulfur Time series uncertainty United States - epidemiology Weather |
| title | Spatial Association between Speciated Fine Particles and Mortality |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-28T07%3A45%3A19IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-jstor_proqu&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Spatial%20Association%20between%20Speciated%20Fine%20Particles%20and%20Mortality&rft.jtitle=Biometrics&rft.au=Fuentes,%20Montserrat&rft.date=2006-09&rft.volume=62&rft.issue=3&rft.spage=855&rft.epage=863&rft.pages=855-863&rft.issn=0006-341X&rft.eissn=1541-0420&rft.coden=BIOMA5&rft_id=info:doi/10.1111/j.1541-0420.2006.00526.x&rft_dat=%3Cjstor_proqu%3E4124596%3C/jstor_proqu%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=213835445&rft_id=info:pmid/16984329&rft_jstor_id=4124596&rfr_iscdi=true |