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Short-term effects of ambient pm 2.5 and pm 2.5-10 on mortality in major cities of korea

DC Field Value Language
dc.contributor.authorKim, Tae-Young-
dc.contributor.authorKim, Ho-
dc.contributor.authorYi, Seung-Muk-
dc.contributor.authorCheong, Jang-Pyo-
dc.contributor.authorHeo, Jongbae-
dc.creator김호-
dc.date.accessioned2019-04-25T01:56:22Z-
dc.date.available2020-04-05T01:56:22Z-
dc.date.created2019-06-21-
dc.date.issued2018-07-
dc.identifier.citationAerosol and Air Quality Research, Vol.18 No.7, pp.1853-1862-
dc.identifier.issn1680-8584-
dc.identifier.urihttps://hdl.handle.net/10371/149971-
dc.description.abstractWhile many epidemiological studies have examined the health effects of different sizes of ambient particulate matter (PM), the findings have been mixed. PM is a heterogeneous mixture, and its chemical components differ by size, with more combustion related materials in the fine mode and more crustal materials in the coarse mode. This study estimates the risk of mortality associated with exposure to PM2.5 (particulate matter less than 2.5 mu m in aerodynamic diameter) and PM2.5-10 (particulate matter less than 10 mu m and greater than 2.5 mu m in aerodynamic diameter). Long-term measurements of PM2.5 and PM2.5-10 were compared with the all-cause, cardiovascular, and respiratory mortality observed from January 2006 till December 2012 in three large cities in Korea (viz., Seoul, Busan, and Incheon). A time-series analysis based on a quasi-Poisson distribution was used to evaluate the associations of PM2.5 and PM2.5-10 with mortality. A 10 mu g m(-3) increase in PM2.5 (lag01) was associated with an increase of 1.18% (95% CI: 0.64, 1.72), 0.34% (95% CI: 0.03, 0.64), and 0.43% (90% CI: 0.02, 0.95) in the all-cause mortality in Busan, Seoul, and Incheon, respectively, during the study period. An increase in respiratory mortality of 0.52% (95% CI: 0.09, 0.96) and 2.25% (95% CI: 0.38, 4.15) was associated with a 10 mu g m(-3) increase in PM2.5 (lag01) in Seoul and Busan, respectively. Overall, the strongest associations were observed in Busan as well as among the elderly population. Statistically significant associations between ambient PM2.5 and PM2.5-10, and mortality were observed in this study. Exposure to fine particles, which mostly originate in combustion and mobile emissions, showed stronger effects on human health than coarse particles, which mostly originate in natural sources such as soil and mechanical processes.-
dc.language영어-
dc.language.isoenen
dc.publisherChinese Association for Aerosol Research in Taiwan-
dc.titleShort-term effects of ambient pm 2.5 and pm 2.5-10 on mortality in major cities of korea-
dc.typeArticle-
dc.identifier.doi10.4209/aaqr.2017.11.0490-
dc.citation.journaltitleAerosol and Air Quality Research-
dc.identifier.wosid000435943400026-
dc.identifier.scopusid2-s2.0-85055059663-
dc.description.srndOAIID:RECH_ACHV_DSTSH_NO:T201821025-
dc.description.srndRECH_ACHV_FG:RR00200001-
dc.description.srndADJUST_YN:-
dc.description.srndEMP_ID:A001370-
dc.description.srndCITE_RATE:2.589-
dc.description.srndFILENAME:2018_26_AAQR.pdf-
dc.description.srndDEPT_NM:보건학과-
dc.description.srndEMAIL:hokim@snu.ac.kr-
dc.description.srndSCOPUS_YN:Y-
dc.description.srndFILEURL:https://srnd.snu.ac.kr/eXrepEIR/fws/file/c2c5bcc7-ec4a-4ba3-83f0-1304b951b651/link-
dc.citation.endpage1862-
dc.citation.number7-
dc.citation.startpage1853-
dc.citation.volume18-
dc.description.isOpenAccessY-
dc.contributor.affiliatedAuthorKim, Ho-
dc.contributor.affiliatedAuthorYi, Seung-Muk-
dc.identifier.srndT201821025-
dc.type.docTypeArticle-
dc.description.journalClass1-
dc.subject.keywordPlusPARTICULATE AIR-POLLUTION-
dc.subject.keywordPlusMULTICITY TIME-SERIES-
dc.subject.keywordPlusCOARSE PARTICLES-
dc.subject.keywordPlusSOURCE APPORTIONMENT-
dc.subject.keywordPlusSEASONAL-VARIATION-
dc.subject.keywordPlusCHINESE CITIES-
dc.subject.keywordPlusFINE-
dc.subject.keywordPlusMATTER-
dc.subject.keywordPlusASSOCIATIONS-
dc.subject.keywordPlusSEOUL-
dc.subject.keywordAuthorCoarse particles-
dc.subject.keywordAuthorFine particles-
dc.subject.keywordAuthorHealth effects-
dc.subject.keywordAuthorTime-series analysis-
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