Associations between long-term exposures to airborne PM2.5 components and mortality in Massachusetts: mixture analysis exploration
Abstract Background: Numerous studies have documented PM2.5’s links with adverse health outcomes. Comparatively fewer studies have evaluated specific PM2.5 components. The lack of exposure measurements and high correlation among different PM2.5 components are two limitations. Methods: We applied a n...
| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
BMC
2022-10-01
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| Series: | Environmental Health |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12940-022-00907-2 |
| _version_ | 1798029984408797184 |
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| author | Tingfan Jin Heresh Amini Anna Kosheleva Mahdieh Danesh Yazdi Yaguang Wei Edgar Castro Qian Di Liuhua Shi Joel Schwartz |
| author_facet | Tingfan Jin Heresh Amini Anna Kosheleva Mahdieh Danesh Yazdi Yaguang Wei Edgar Castro Qian Di Liuhua Shi Joel Schwartz |
| author_sort | Tingfan Jin |
| collection | DOAJ |
| description | Abstract Background: Numerous studies have documented PM2.5’s links with adverse health outcomes. Comparatively fewer studies have evaluated specific PM2.5 components. The lack of exposure measurements and high correlation among different PM2.5 components are two limitations. Methods: We applied a novel exposure prediction model to obtain annual Census tract-level concentrations of 15 PM2.5 components (Zn, V, Si, Pb, Ni, K, Fe, Cu, Ca, Br, SO4 2−, NO3 −, NH4 +, OC, EC) in Massachusetts from 2000 to 2015, to which we matched geocoded deaths. All non-accidental mortality, cardiovascular mortality, and respiratory mortality were examined for the population aged 18 or over. Weighted quantile sum (WQS) regression models were used to examine the cumulative associations between PM2.5 components mixture and outcomes and each component’s contributions to the cumulative associations. We have fit WQS models on 15 PM2.5 components and a priori identified source groups (heavy fuel oil combustion, biomass burning, crustal matter, non-tailpipe traffic source, tailpipe traffic source, secondary particles from power plants, secondary particles from agriculture, unclear source) for the 15 PM2.5 components. Total PM2.5 mass analysis and single component associations were also conducted through quasi-Poisson regression models. Results: Positive cumulative associations between the components mixture and all three outcomes were observed from the WQS models. Components with large contribution to the cumulative associations included K, OC, and Fe. Biomass burning, traffic emissions, and secondary particles from power plants were identified as important source contributing to the cumulative associations. Mortality rate ratios for cardiovascular mortality were of greater magnitude than all non-accidental mortality and respiratory mortality, which is also observed in cumulative associations estimated from WQS, total PM2.5 mass analysis, and single component associations. Conclusion: We have found positive associations between the mixture of 15 PM2.5 components and all non-accidental mortality, cardiovascular mortality, and respiratory mortality. Among these components, Fe, K, and OC have been identified as having important contribution to the cumulative associations. The WQS results also suggests potential source effects from biomass burning, traffic emissions, and secondary particles from power plants. |
| first_indexed | 2024-04-11T19:33:05Z |
| format | Article |
| id | doaj.art-8a45c54345a04ac095a14df3cd67c2d7 |
| institution | Directory Open Access Journal |
| issn | 1476-069X |
| language | English |
| last_indexed | 2024-04-11T19:33:05Z |
| publishDate | 2022-10-01 |
| publisher | BMC |
| record_format | Article |
| series | Environmental Health |
| spelling | doaj.art-8a45c54345a04ac095a14df3cd67c2d72022-12-22T04:06:56ZengBMCEnvironmental Health1476-069X2022-10-0121111310.1186/s12940-022-00907-2Associations between long-term exposures to airborne PM2.5 components and mortality in Massachusetts: mixture analysis explorationTingfan Jin0Heresh Amini1Anna Kosheleva2Mahdieh Danesh Yazdi3Yaguang Wei4Edgar Castro5Qian Di6Liuhua Shi7Joel Schwartz8Department of Environmental Health, Harvard T.H. Chan School of Public HealthDepartment of Public Health, University of CopenhagenDepartment of Environmental Health, Harvard T.H. Chan School of Public HealthDepartment of Family, Population, & Preventive Medicine, Program in Public Health, Stony Brook UniversityDepartment of Environmental Health, Harvard T.H. Chan School of Public HealthDepartment of Environmental Health, Harvard T.H. Chan School of Public HealthVanke School of Public Health, Tsinghua UniversityGangarosa Department of Environmental Health, Rollins School of Public Health, Emory UniversityDepartment of Environmental Health, Harvard T.H. Chan School of Public HealthAbstract Background: Numerous studies have documented PM2.5’s links with adverse health outcomes. Comparatively fewer studies have evaluated specific PM2.5 components. The lack of exposure measurements and high correlation among different PM2.5 components are two limitations. Methods: We applied a novel exposure prediction model to obtain annual Census tract-level concentrations of 15 PM2.5 components (Zn, V, Si, Pb, Ni, K, Fe, Cu, Ca, Br, SO4 2−, NO3 −, NH4 +, OC, EC) in Massachusetts from 2000 to 2015, to which we matched geocoded deaths. All non-accidental mortality, cardiovascular mortality, and respiratory mortality were examined for the population aged 18 or over. Weighted quantile sum (WQS) regression models were used to examine the cumulative associations between PM2.5 components mixture and outcomes and each component’s contributions to the cumulative associations. We have fit WQS models on 15 PM2.5 components and a priori identified source groups (heavy fuel oil combustion, biomass burning, crustal matter, non-tailpipe traffic source, tailpipe traffic source, secondary particles from power plants, secondary particles from agriculture, unclear source) for the 15 PM2.5 components. Total PM2.5 mass analysis and single component associations were also conducted through quasi-Poisson regression models. Results: Positive cumulative associations between the components mixture and all three outcomes were observed from the WQS models. Components with large contribution to the cumulative associations included K, OC, and Fe. Biomass burning, traffic emissions, and secondary particles from power plants were identified as important source contributing to the cumulative associations. Mortality rate ratios for cardiovascular mortality were of greater magnitude than all non-accidental mortality and respiratory mortality, which is also observed in cumulative associations estimated from WQS, total PM2.5 mass analysis, and single component associations. Conclusion: We have found positive associations between the mixture of 15 PM2.5 components and all non-accidental mortality, cardiovascular mortality, and respiratory mortality. Among these components, Fe, K, and OC have been identified as having important contribution to the cumulative associations. The WQS results also suggests potential source effects from biomass burning, traffic emissions, and secondary particles from power plants.https://doi.org/10.1186/s12940-022-00907-2Air pollutionParticle componentsWeighted quantile sum regression |
| spellingShingle | Tingfan Jin Heresh Amini Anna Kosheleva Mahdieh Danesh Yazdi Yaguang Wei Edgar Castro Qian Di Liuhua Shi Joel Schwartz Associations between long-term exposures to airborne PM2.5 components and mortality in Massachusetts: mixture analysis exploration Environmental Health Air pollution Particle components Weighted quantile sum regression |
| title | Associations between long-term exposures to airborne PM2.5 components and mortality in Massachusetts: mixture analysis exploration |
| title_full | Associations between long-term exposures to airborne PM2.5 components and mortality in Massachusetts: mixture analysis exploration |
| title_fullStr | Associations between long-term exposures to airborne PM2.5 components and mortality in Massachusetts: mixture analysis exploration |
| title_full_unstemmed | Associations between long-term exposures to airborne PM2.5 components and mortality in Massachusetts: mixture analysis exploration |
| title_short | Associations between long-term exposures to airborne PM2.5 components and mortality in Massachusetts: mixture analysis exploration |
| title_sort | associations between long term exposures to airborne pm2 5 components and mortality in massachusetts mixture analysis exploration |
| topic | Air pollution Particle components Weighted quantile sum regression |
| url | https://doi.org/10.1186/s12940-022-00907-2 |
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