New concentration-response functions for seven morbidity endpoints associated with short-term PM2.5 exposure and their implications for health impact assessment
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 PM2.5 assume...
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| Format: | Article |
| Language: | English |
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Elsevier
2023-09-01
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| Series: | Environment International |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S0160412023003951 |
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| author | Muye Ru Drew Shindell Joseph V. Spadaro Jean-François Lamarque Ariyani Challapalli Fabian Wagner Gregor Kiesewetter |
| author_facet | Muye Ru Drew Shindell Joseph V. Spadaro Jean-François Lamarque Ariyani Challapalli Fabian Wagner Gregor Kiesewetter |
| author_sort | Muye Ru |
| collection | DOAJ |
| description | 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 PM2.5 assume a fixed risk estimate as a log-linear function over an extrapolated exposure range, based on evidence primarily from Europe and North America. 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 PM2.5 and morbidity outcomes. |
| first_indexed | 2024-03-12T00:11:09Z |
| format | Article |
| id | doaj.art-6f7a9ab9afea4245bbc838b621f11cd0 |
| institution | Directory Open Access Journal |
| issn | 0160-4120 |
| language | English |
| last_indexed | 2024-03-12T00:11:09Z |
| publishDate | 2023-09-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Environment International |
| spelling | doaj.art-6f7a9ab9afea4245bbc838b621f11cd02023-09-16T05:28:39ZengElsevierEnvironment International0160-41202023-09-01179108122New concentration-response functions for seven morbidity endpoints associated with short-term PM2.5 exposure and their implications for health impact assessmentMuye Ru0Drew Shindell1Joseph V. Spadaro2Jean-François Lamarque3Ariyani Challapalli4Fabian Wagner5Gregor Kiesewetter6Nicholas School of the Environment, Duke University, Durham, NC, USA; Now at The Earth Institute, Columbia University, New York, NY, USA; Corresponding author at: The Earth Institute, Columbia University, New York City, NY, USA.Nicholas School of the Environment, Duke University, Durham, NC, USA; Porter School of the Environment and Earth Sciences, Tel Aviv University, Tel Aviv, IsraelSpadaro Environmental Research Consultants, Philadelphia, PA, USANational Center for Atmospheric Research, Boulder, CO, USANicholas School of the Environment, Duke University, Durham, NC, USAInternational Institute for Applied Systems Analysis, Laxenburg, AustriaInternational Institute for Applied Systems Analysis, Laxenburg, AustriaBackground: 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 PM2.5 assume a fixed risk estimate as a log-linear function over an extrapolated exposure range, based on evidence primarily from Europe and North America. 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 PM2.5 and morbidity outcomes.http://www.sciencedirect.com/science/article/pii/S0160412023003951MorbidityConcentration–response functionsAir pollutionNonlinearityHealth-impact assessmentMeta-analysis |
| spellingShingle | Muye Ru Drew Shindell Joseph V. Spadaro Jean-François Lamarque Ariyani Challapalli Fabian Wagner Gregor Kiesewetter New concentration-response functions for seven morbidity endpoints associated with short-term PM2.5 exposure and their implications for health impact assessment Environment International Morbidity Concentration–response functions Air pollution Nonlinearity Health-impact assessment Meta-analysis |
| title | New concentration-response functions for seven morbidity endpoints associated with short-term PM2.5 exposure and their implications for health impact assessment |
| title_full | New concentration-response functions for seven morbidity endpoints associated with short-term PM2.5 exposure and their implications for health impact assessment |
| title_fullStr | New concentration-response functions for seven morbidity endpoints associated with short-term PM2.5 exposure and their implications for health impact assessment |
| title_full_unstemmed | New concentration-response functions for seven morbidity endpoints associated with short-term PM2.5 exposure and their implications for health impact assessment |
| title_short | New concentration-response functions for seven morbidity endpoints associated with short-term PM2.5 exposure and their implications for health impact assessment |
| title_sort | new concentration response functions for seven morbidity endpoints associated with short term pm2 5 exposure and their implications for health impact assessment |
| topic | Morbidity Concentration–response functions Air pollution Nonlinearity Health-impact assessment Meta-analysis |
| url | http://www.sciencedirect.com/science/article/pii/S0160412023003951 |
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