Exposure-response functions of the correlated environmental exposures green space, noise, and air pollution for quantifying mortality burden in health impact assessment

Objective: Environmental health impact assessments (HIA)on green space, air pollution (fine particulate matter (PM2.5) or nitrogen dioxide (NO2)), and noise use exposure-response functions (ERF) based on single-exposure models from epidemiological studies, not accounting for potential confounding by...

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Autores: Chen, Xuan, Gehring, Ulrike, Dyer, Georgia M. C., de Hoogh, Kees, Khomenko, Sasha, Khreis, Haneen, Mueller, Natalie, 1988-, Vermeulen, Roel, Williams, Harry, Zapata-Diomedi, Belén, Nieuwenhuijsen, Mark J., Hoek, Gerard
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2025
País:España
Institución:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repositorio:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:10230/71218
Acceso en línea:http://hdl.handle.net/10230/71218
http://dx.doi.org/10.1016/j.envint.2025.109645
Access Level:acceso abierto
Palabra clave:Air pollution
Exposure–response functions
Green space
Health impact assessment
Noise
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network_name_str España
repository_id_str
dc.title.none.fl_str_mv Exposure-response functions of the correlated environmental exposures green space, noise, and air pollution for quantifying mortality burden in health impact assessment
title Exposure-response functions of the correlated environmental exposures green space, noise, and air pollution for quantifying mortality burden in health impact assessment
spellingShingle Exposure-response functions of the correlated environmental exposures green space, noise, and air pollution for quantifying mortality burden in health impact assessment
Chen, Xuan
Air pollution
Exposure–response functions
Green space
Health impact assessment
Noise
title_short Exposure-response functions of the correlated environmental exposures green space, noise, and air pollution for quantifying mortality burden in health impact assessment
title_full Exposure-response functions of the correlated environmental exposures green space, noise, and air pollution for quantifying mortality burden in health impact assessment
title_fullStr Exposure-response functions of the correlated environmental exposures green space, noise, and air pollution for quantifying mortality burden in health impact assessment
title_full_unstemmed Exposure-response functions of the correlated environmental exposures green space, noise, and air pollution for quantifying mortality burden in health impact assessment
title_sort Exposure-response functions of the correlated environmental exposures green space, noise, and air pollution for quantifying mortality burden in health impact assessment
dc.creator.none.fl_str_mv Chen, Xuan
Gehring, Ulrike
Dyer, Georgia M. C.
de Hoogh, Kees
Khomenko, Sasha
Khreis, Haneen
Mueller, Natalie, 1988-
Vermeulen, Roel
Williams, Harry
Zapata-Diomedi, Belén
Nieuwenhuijsen, Mark J.
Hoek, Gerard
author Chen, Xuan
author_facet Chen, Xuan
Gehring, Ulrike
Dyer, Georgia M. C.
de Hoogh, Kees
Khomenko, Sasha
Khreis, Haneen
Mueller, Natalie, 1988-
Vermeulen, Roel
Williams, Harry
Zapata-Diomedi, Belén
Nieuwenhuijsen, Mark J.
Hoek, Gerard
author_role author
author2 Gehring, Ulrike
Dyer, Georgia M. C.
de Hoogh, Kees
Khomenko, Sasha
Khreis, Haneen
Mueller, Natalie, 1988-
Vermeulen, Roel
Williams, Harry
Zapata-Diomedi, Belén
Nieuwenhuijsen, Mark J.
Hoek, Gerard
author2_role author
author
author
author
author
author
author
author
author
author
author
dc.subject.none.fl_str_mv Air pollution
Exposure–response functions
Green space
Health impact assessment
Noise
topic Air pollution
Exposure–response functions
Green space
Health impact assessment
Noise
description Objective: Environmental health impact assessments (HIA)on green space, air pollution (fine particulate matter (PM2.5) or nitrogen dioxide (NO2)), and noise use exposure-response functions (ERF) based on single-exposure models from epidemiological studies, not accounting for potential confounding by other commonly correlated exposures. We assessed differences in ERFs between single- and multi-exposure models for calculation of joint health impacts in HIA. Methods: We systematically searched cohort studies that reported both single- and multi-exposure models for associations of long-term exposure to any combination of the following exposures green space, PM2.5, NO2, and noise, with all-cause mortality. For each exposure, pooled hazard ratios (HRs) were calculated by meta-analyses and compared between single- and two-exposure models. The joint effects of two exposures in each exposure pair were expressed as joint HRs calculated by multiplying the individual HRs. Coefficient differences were calculated, and population attributable fractions (PAF) were used to estimate joint health impacts. Results: Eleven studies were identified, examining associations between multiple exposures and mortality in the general population. The studies show substantial variability in exposure levels and correlations between exposures. For most exposure pairs, adjusting for a second exposure resulted in moderately attenuated HRs compared to single-exposure models. The mortality PAFs estimated from joint single-exposure model HRs were higher than those from two-exposure models, indicating an overestimation of mortality burden when not accounting for other co-exposures. For example, when adjusted for green space or noise, the mortality HRs for PM2.5 were attenuated from 1.071 to 1.061 and 1.072 to 1.055, respectively. As for PAFs, for the green space-PM2.5 pair, the single-exposure model PAF (0.090) was 18.4% higher than the two-exposure model (0.076). For all exposure pairs, the joint PAFs of two-exposure models were higher than the PAFs from the single-exposure models for each exposure individually. Conclusion: The pooled coefficient differences from this study can be used to adjust single-exposure ERFs from meta-analyses and allow the calculation of combined impacts from multiple environmental exposures, making HIA estimates more robust and realistic.
publishDate 2025
dc.date.none.fl_str_mv 2025
2025
2025
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10230/71218
http://dx.doi.org/10.1016/j.envint.2025.109645
http://hdl.handle.net/10230/71218
url http://hdl.handle.net/10230/71218
http://dx.doi.org/10.1016/j.envint.2025.109645
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Environ Int. 2025 Aug;202:109645
info:eu-repo/grantAgreement/EC/HE/101094639
info:eu-repo/grantAgreement/ES/2PE/CEX2018-000806-S
dc.rights.none.fl_str_mv http://creativecommons.org/licenses/by/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:Recercat. Dipósit de la Recerca de Catalunya
instname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
instname_str Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
reponame_str Recercat. Dipósit de la Recerca de Catalunya
collection Recercat. Dipósit de la Recerca de Catalunya
repository.name.fl_str_mv
repository.mail.fl_str_mv
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spelling Exposure-response functions of the correlated environmental exposures green space, noise, and air pollution for quantifying mortality burden in health impact assessmentChen, XuanGehring, UlrikeDyer, Georgia M. C.de Hoogh, KeesKhomenko, SashaKhreis, HaneenMueller, Natalie, 1988-Vermeulen, RoelWilliams, HarryZapata-Diomedi, BelénNieuwenhuijsen, Mark J.Hoek, GerardAir pollutionExposure–response functionsGreen spaceHealth impact assessmentNoiseObjective: Environmental health impact assessments (HIA)on green space, air pollution (fine particulate matter (PM2.5) or nitrogen dioxide (NO2)), and noise use exposure-response functions (ERF) based on single-exposure models from epidemiological studies, not accounting for potential confounding by other commonly correlated exposures. We assessed differences in ERFs between single- and multi-exposure models for calculation of joint health impacts in HIA. Methods: We systematically searched cohort studies that reported both single- and multi-exposure models for associations of long-term exposure to any combination of the following exposures green space, PM2.5, NO2, and noise, with all-cause mortality. For each exposure, pooled hazard ratios (HRs) were calculated by meta-analyses and compared between single- and two-exposure models. The joint effects of two exposures in each exposure pair were expressed as joint HRs calculated by multiplying the individual HRs. Coefficient differences were calculated, and population attributable fractions (PAF) were used to estimate joint health impacts. Results: Eleven studies were identified, examining associations between multiple exposures and mortality in the general population. The studies show substantial variability in exposure levels and correlations between exposures. For most exposure pairs, adjusting for a second exposure resulted in moderately attenuated HRs compared to single-exposure models. The mortality PAFs estimated from joint single-exposure model HRs were higher than those from two-exposure models, indicating an overestimation of mortality burden when not accounting for other co-exposures. For example, when adjusted for green space or noise, the mortality HRs for PM2.5 were attenuated from 1.071 to 1.061 and 1.072 to 1.055, respectively. As for PAFs, for the green space-PM2.5 pair, the single-exposure model PAF (0.090) was 18.4% higher than the two-exposure model (0.076). For all exposure pairs, the joint PAFs of two-exposure models were higher than the PAFs from the single-exposure models for each exposure individually. Conclusion: The pooled coefficient differences from this study can be used to adjust single-exposure ERFs from meta-analyses and allow the calculation of combined impacts from multiple environmental exposures, making HIA estimates more robust and realistic.This project has received funding from the European Union's, Horizon Europe Framework Programme (HORIZON) under GA No 101094639 – THE URBAN BURDEN OF DISEASE ESTIMATION FOR POLICY MAKING (UBDPolicy). We also acknowledge support from the Spanish Ministry of Science, Innovation and Universities and State Research Agency through the grant CEX2018-000806-S funded by MCIN/AEI/10.13039/501100011033; support from the Generalitat de Catalunya through the Centres de Recerca de Catalunya (CERCA) programme; support from Centro de Investigacioń Bioḿedica en red Epidemiología y Salud Pública (CIBERESP).Elsevier202520252025info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfapplication/pdfhttp://hdl.handle.net/10230/71218http://dx.doi.org/10.1016/j.envint.2025.109645http://hdl.handle.net/10230/71218reponame:Recercat. Dipósit de la Recerca de Catalunyainstname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)InglésEnviron Int. 2025 Aug;202:109645info:eu-repo/grantAgreement/EC/HE/101094639info:eu-repo/grantAgreement/ES/2PE/CEX2018-000806-S© 2025 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).http://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:recercat.cat:10230/712182026-05-29T05:05:01Z
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