New concentration-response functions for seven morbidity endpoints associated with short-term PM

Air pollution Concentration–response functions Health-impact assessment Meta-analysis Morbidity Nonlinearity

Journal

Environment international
ISSN: 1873-6750
Titre abrégé: Environ Int
Pays: Netherlands
ID NLM: 7807270

Informations de publication

Date de publication:
09 2023
Historique:
received: 12 03 2023
revised: 26 07 2023
accepted: 28 07 2023
medline: 18 9 2023
pubmed: 3 9 2023
entrez: 2 9 2023
Statut: ppublish

Résumé

Morbidity burdens from ambient air pollution are associated with market and non-market costs and are therefore important for policymaking. The estimation of morbidity burdens is based on concentration-response functions (CRFs). Most existing CRFs for short-term exposures to PM We revisit these CRFs by performing a systematic review for seven morbidity endpoints previously assessed by the World Health Organization, including data from all available regions. These endpoints include all cardiovascular hospital admission, all respiratory hospital admission, asthma hospital admission and emergency room visit, along with the outcomes that stem from morbidity, such as lost work days, respiratory restricted activity days, and child bronchitis symptom days. We estimate CRFs for each endpoint, using both a log-linear model and a nonlinear model that includes additional parameters to better fit evidence from high-exposure regions. We quantify uncertainties associated with these CRFs through randomization and Monte Carlo simulations. The CRFs in this study show reduced model uncertainty compared with previous CRFs in all endpoints. The nonlinear CRFs produce more than doubled global estimates on average, depending on the endpoint. Overall, we assess that our CRFs can be used to provide policy analysis of air pollution impacts at the global scale. It is however important to note that improvement of CRFs requires observations over a wide range of conditions, and current available literature is still limited. The higher estimates produced by the nonlinear CRFs indicates the possibility of a large underestimation in current assessments of the morbidity impacts attributable to air pollution. Further studies should be pursued to better constrain the CRFs studied here, and to better characterize the causal relationship between exposures to PM

Sections du résumé

BACKGROUND
Morbidity burdens from ambient air pollution are associated with market and non-market costs and are therefore important for policymaking. The estimation of morbidity burdens is based on concentration-response functions (CRFs). Most existing CRFs for short-term exposures to PM
OBJECTIVES
We revisit these CRFs by performing a systematic review for seven morbidity endpoints previously assessed by the World Health Organization, including data from all available regions. These endpoints include all cardiovascular hospital admission, all respiratory hospital admission, asthma hospital admission and emergency room visit, along with the outcomes that stem from morbidity, such as lost work days, respiratory restricted activity days, and child bronchitis symptom days.
METHODS
We estimate CRFs for each endpoint, using both a log-linear model and a nonlinear model that includes additional parameters to better fit evidence from high-exposure regions. We quantify uncertainties associated with these CRFs through randomization and Monte Carlo simulations.
RESULTS
The CRFs in this study show reduced model uncertainty compared with previous CRFs in all endpoints. The nonlinear CRFs produce more than doubled global estimates on average, depending on the endpoint. Overall, we assess that our CRFs can be used to provide policy analysis of air pollution impacts at the global scale. It is however important to note that improvement of CRFs requires observations over a wide range of conditions, and current available literature is still limited.
DISCUSSION
The higher estimates produced by the nonlinear CRFs indicates the possibility of a large underestimation in current assessments of the morbidity impacts attributable to air pollution. Further studies should be pursued to better constrain the CRFs studied here, and to better characterize the causal relationship between exposures to PM

Identifiants

pubmed: 37659174
pii: S0160-4120(23)00395-1
doi: 10.1016/j.envint.2023.108122
pii:
doi:

Substances chimiques

Particulate Matter 0

Types de publication

Systematic Review Journal Article Research Support, U.S. Gov't, Non-P.H.S.

Langues

eng

Sous-ensembles de citation

IM

Pagination

108122

Informations de copyright

Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

Muye Ru (M)

Nicholas School of the Environment, Duke University, Durham, NC, USA; Now at The Earth Institute, Columbia University, New York, NY, USA. Electronic address: muye.ru.work@gmail.com.

Drew Shindell (D)

Nicholas School of the Environment, Duke University, Durham, NC, USA; Porter School of the Environment and Earth Sciences, Tel Aviv University, Tel Aviv, Israel.

Joseph V Spadaro (JV)

Spadaro Environmental Research Consultants, Philadelphia, PA, USA.

Jean-François Lamarque (JF)

National Center for Atmospheric Research, Boulder, CO, USA.

Ariyani Challapalli (A)

Nicholas School of the Environment, Duke University, Durham, NC, USA.

Fabian Wagner (F)

International Institute for Applied Systems Analysis, Laxenburg, Austria.

Gregor Kiesewetter (G)

International Institute for Applied Systems Analysis, Laxenburg, Austria.

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Classifications MeSH