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dc.contributor.authorTonne, Cathryn
dc.contributor.authorYanosky, Jeffrey
dc.contributor.authorGryparis, Alexandros
dc.contributor.authorMelly, Steven J.
dc.contributor.authorMittleman, Murray A.
dc.contributor.authorGoldberg, Robert J.
dc.contributor.authorvon Klot, Stephanie
dc.contributor.authorSchwartz, Joel
dc.date2022-08-11T08:10:39.000
dc.date.accessioned2022-08-23T17:15:39Z
dc.date.available2022-08-23T17:15:39Z
dc.date.issued2009-06-26
dc.date.submitted2010-05-27
dc.identifier.citationOccup Environ Med. 2009 Dec;66(12):797-804. Epub 2009 Jun 23. <a href="http://dx.doi.org/10.1136/oem.2008.045047">Link to article on publisher's site</a>
dc.identifier.issn1351-0711 (Linking)
dc.identifier.doi10.1136/oem.2008.045047
dc.identifier.pmid19553228
dc.identifier.urihttp://hdl.handle.net/20.500.14038/47216
dc.description.abstractOBJECTIVES: We modelled exposure to traffic particles using a latent variable approach and investigated whether long-term exposure to traffic particles is associated with an increase in the occurrence of acute myocardial infarction (AMI) using data from a population-based coronary disease registry. METHODS: Cases of individually validated AMI were identified between 1995 and 2003 as part of the Worcester Heart Attack Study. Population controls were selected from Massachusetts, USA, resident lists. NO(2) and PM(2.5) filter absorbance were measured at 36 locations throughout the study area. The air pollution data were used to estimate exposure to traffic particles using a semiparametric latent variable regression model. Conditional logistic models were used to estimate the association between exposure to traffic particles and occurrence of AMI. RESULTS: Modelled exposure to traffic particles was highest near the city of Worcester. Cases of AMI were more exposed to traffic and traffic particles compared to controls. An interquartile range increase in modelled traffic particles was associated with a 10% (95% CI 4% to 16%) increase in the odds of AMI. Accounting for spatial dependence at the census tract, but not block group, scale substantially attenuated this association. CONCLUSIONS: These results provide some support for an association between long-term exposure to traffic particles and risk of AMI. The results were sensitive to the scale selected for the analysis of spatial dependence, an issue that requires further investigation. The latent variable model captured variation in exposure, although on a relatively large spatial scale.
dc.language.isoen_US
dc.relation<a href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=pubmed&cmd=Retrieve&list_uids=19553228&dopt=Abstract">Link to Article in PubMed</a>
dc.relation.urlhttp://dx.doi.org/10.1136/oem.2008.045047
dc.subjectAged
dc.subjectAged, 80 and over
dc.subjectAir Pollutants
dc.subjectCase-Control Studies
dc.subjectEnvironmental Exposure
dc.subjectEnvironmental Monitoring
dc.subjectFemale
dc.subjectHumans
dc.subjectMale
dc.subjectMassachusetts
dc.subjectMiddle Aged
dc.subjectMyocardial Infarction
dc.subjectSensitivity and Specificity
dc.subjectSocioeconomic Factors
dc.subjectUrban Health
dc.subjectVehicle Emissions
dc.subjectBioinformatics
dc.subjectBiostatistics
dc.subjectEpidemiology
dc.subjectHealth Services Research
dc.titleTraffic particles and occurrence of acute myocardial infarction: a case-control analysis
dc.typeJournal Article
dc.source.journaltitleOccupational and environmental medicine
dc.source.volume66
dc.source.issue12
dc.identifier.legacycoverpagehttps://escholarship.umassmed.edu/qhs_pp/360
dc.identifier.contextkey1333114
html.description.abstract<p>OBJECTIVES: We modelled exposure to traffic particles using a latent variable approach and investigated whether long-term exposure to traffic particles is associated with an increase in the occurrence of acute myocardial infarction (AMI) using data from a population-based coronary disease registry.</p> <p>METHODS: Cases of individually validated AMI were identified between 1995 and 2003 as part of the Worcester Heart Attack Study. Population controls were selected from Massachusetts, USA, resident lists. NO(2) and PM(2.5) filter absorbance were measured at 36 locations throughout the study area. The air pollution data were used to estimate exposure to traffic particles using a semiparametric latent variable regression model. Conditional logistic models were used to estimate the association between exposure to traffic particles and occurrence of AMI.</p> <p>RESULTS: Modelled exposure to traffic particles was highest near the city of Worcester. Cases of AMI were more exposed to traffic and traffic particles compared to controls. An interquartile range increase in modelled traffic particles was associated with a 10% (95% CI 4% to 16%) increase in the odds of AMI. Accounting for spatial dependence at the census tract, but not block group, scale substantially attenuated this association.</p> <p>CONCLUSIONS: These results provide some support for an association between long-term exposure to traffic particles and risk of AMI. The results were sensitive to the scale selected for the analysis of spatial dependence, an issue that requires further investigation. The latent variable model captured variation in exposure, although on a relatively large spatial scale.</p>
dc.identifier.submissionpathqhs_pp/360
dc.contributor.departmentDepartment of Medicine, Division of Cardiovascular Medicine
dc.source.pages797-804


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