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Article: How to determine life expectancy change of air pollution mortality: A time series study

TitleHow to determine life expectancy change of air pollution mortality: A time series study
Authors
Issue Date2011
PublisherBioMed Central Ltd. The Journal's web site is located at http://www.ehjournal.net
Citation
Environmental Health: A Global Access Science Source, 2011, v. 10, article no. 25 How to Cite?
AbstractBackground: Information on life expectancy (LE) change is of great concern for policy makers, as evidenced by discussions of the "harvesting" (or "mortality displacement") issue, i.e. how large an LE loss corresponds to the mortality results of time series (TS) studies. Whereas loss of LE attributable to chronic air pollution exposure can be determined from cohort studies, using life table methods, conventional TS studies have identified only deaths due to acute exposure, during the immediate past (typically the preceding one to five days), and they provide no information about the LE loss per death. Methods. We show how to obtain information on population-average LE loss by extending the observation window (largest "lag") of TS to include a sufficient number of "impact coefficients" for past exposures ("lags"). We test several methods for determining these coefficients. Once all of the coefficients have been determined, the LE change is calculated as time integral of the relative risk change after a permanent step change in exposure. Results: The method is illustrated with results for daily data of non-accidental mortality from Hong Kong for 1985 - 2005, regressed against PM10and SO2with observation windows up to 5 years. The majority of the coefficients is statistically significant. The magnitude of the SO2coefficients is comparable to those for PM10. But a window of 5 years is not sufficient and the results for LE change are only a lower bound; it is consistent with what is implied by other studies of long term impacts. Conclusions: A TS analysis can determine the LE loss, but if the observation window is shorter than the relevant exposures one obtains only a lower bound. © 2011 Rabl et al; licensee BioMed Central Ltd.
Persistent Identifierhttp://hdl.handle.net/10722/151736
ISSN
2015 Impact Factor: 3.453
2015 SCImago Journal Rankings: 1.898
ISI Accession Number ID
Funding AgencyGrant Number
Health Effects Institute, Boston, MA4744-RFA04-4/06-5
EC
Funding Information:

This work has been supported by a grant from the Health Effects Institute, Boston, MA (Agreement number #4744-RFA04-4/06-5). Ari Rabl also acknowledges support by the ExternE project series of the EC DG Research. We thank the reviewers (Richard Burnett and Denis Zmirou) for very perceptive and helpful comments.

References

 

DC FieldValueLanguage
dc.contributor.authorRabl, Aen_US
dc.contributor.authorThach, TQen_US
dc.contributor.authorChau, PYKen_US
dc.contributor.authorWong, CMen_US
dc.date.accessioned2012-06-26T06:27:42Z-
dc.date.available2012-06-26T06:27:42Z-
dc.date.issued2011en_US
dc.identifier.citationEnvironmental Health: A Global Access Science Source, 2011, v. 10, article no. 25en_US
dc.identifier.issn1476-069Xen_US
dc.identifier.urihttp://hdl.handle.net/10722/151736-
dc.description.abstractBackground: Information on life expectancy (LE) change is of great concern for policy makers, as evidenced by discussions of the "harvesting" (or "mortality displacement") issue, i.e. how large an LE loss corresponds to the mortality results of time series (TS) studies. Whereas loss of LE attributable to chronic air pollution exposure can be determined from cohort studies, using life table methods, conventional TS studies have identified only deaths due to acute exposure, during the immediate past (typically the preceding one to five days), and they provide no information about the LE loss per death. Methods. We show how to obtain information on population-average LE loss by extending the observation window (largest "lag") of TS to include a sufficient number of "impact coefficients" for past exposures ("lags"). We test several methods for determining these coefficients. Once all of the coefficients have been determined, the LE change is calculated as time integral of the relative risk change after a permanent step change in exposure. Results: The method is illustrated with results for daily data of non-accidental mortality from Hong Kong for 1985 - 2005, regressed against PM10and SO2with observation windows up to 5 years. The majority of the coefficients is statistically significant. The magnitude of the SO2coefficients is comparable to those for PM10. But a window of 5 years is not sufficient and the results for LE change are only a lower bound; it is consistent with what is implied by other studies of long term impacts. Conclusions: A TS analysis can determine the LE loss, but if the observation window is shorter than the relevant exposures one obtains only a lower bound. © 2011 Rabl et al; licensee BioMed Central Ltd.en_US
dc.languageengen_US
dc.publisherBioMed Central Ltd. The Journal's web site is located at http://www.ehjournal.neten_US
dc.relation.ispartofEnvironmental Health: A Global Access Science Sourceen_US
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.subject.meshAir Pollution - Analysis - Statistics & Numerical Dataen_US
dc.subject.meshCohort Studiesen_US
dc.subject.meshHong Kongen_US
dc.subject.meshHumansen_US
dc.subject.meshLife Expectancyen_US
dc.subject.meshLife Tablesen_US
dc.subject.meshModels, Statisticalen_US
dc.subject.meshMortality - Trendsen_US
dc.subject.meshParticulate Matter - Analysis - Toxicityen_US
dc.subject.meshResearch Designen_US
dc.subject.meshSulfur Dioxide - Analysis - Toxicityen_US
dc.subject.meshTime Factorsen_US
dc.titleHow to determine life expectancy change of air pollution mortality: A time series studyen_US
dc.typeArticleen_US
dc.identifier.emailThach, TQ:thach@hku.hken_US
dc.identifier.authorityThach, TQ=rp00450en_US
dc.description.naturepublished_or_final_versionen_US
dc.identifier.doi10.1186/1476-069X-10-25en_US
dc.identifier.pmid21450107en_US
dc.identifier.scopuseid_2-s2.0-79955060310en_US
dc.identifier.hkuros185525-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-79955060310&selection=ref&src=s&origin=recordpageen_US
dc.identifier.volume10en_US
dc.identifier.issue1en_US
dc.identifier.isiWOS:000289682800001-
dc.publisher.placeUnited Kingdomen_US
dc.identifier.scopusauthoridRabl, A=7004462093en_US
dc.identifier.scopusauthoridThach, TQ=6602850066en_US
dc.identifier.scopusauthoridChau, PYK=34876162600en_US
dc.identifier.scopusauthoridWong, CM=37100635000en_US

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