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The impact of long-term PM(2.5) exposure on specific causes of death: exposure-response curves and effect modification among 53 million U.S. Medicare beneficiaries

BACKGROUND: The shape of the exposure-response curve for long-term ambient fine particulate (PM(2.5)) exposure and cause-specific mortality is poorly understood, especially for rural populations and underrepresented minorities. METHODS: We used hybrid machine learning and Cox proportional hazard mod...

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Autores principales: Wang, Bingyu, Eum, Ki-Do, Kazemiparkouhi, Fatemeh, Li, Cheng, Manjourides, Justin, Pavlu, Virgil, Suh, Helen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7026980/
https://www.ncbi.nlm.nih.gov/pubmed/32066433
http://dx.doi.org/10.1186/s12940-020-00575-0
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author Wang, Bingyu
Eum, Ki-Do
Kazemiparkouhi, Fatemeh
Li, Cheng
Manjourides, Justin
Pavlu, Virgil
Suh, Helen
author_facet Wang, Bingyu
Eum, Ki-Do
Kazemiparkouhi, Fatemeh
Li, Cheng
Manjourides, Justin
Pavlu, Virgil
Suh, Helen
author_sort Wang, Bingyu
collection PubMed
description BACKGROUND: The shape of the exposure-response curve for long-term ambient fine particulate (PM(2.5)) exposure and cause-specific mortality is poorly understood, especially for rural populations and underrepresented minorities. METHODS: We used hybrid machine learning and Cox proportional hazard models to assess the association of long-term PM(2.5) exposures on specific causes of death for 53 million U.S. Medicare beneficiaries (aged ≥65) from 2000 to 2008. Models included strata for age, sex, race, and ZIP code and controlled for neighborhood socio-economic status (SES) in our main analyses, with approximately 4 billion person-months of follow-up, and additionally for warm season average of 1-h daily maximum ozone exposures in a sensitivity analysis. The impact of non-traffic PM(2.5) on mortality was examined using two stage models of PM(2.5) and nitrogen dioxide (NO(2)). RESULTS: A 10 μg /m(3) increase in 12-month average PM(2.5) prior to death was associated with a 5% increase in all-cause mortality, as well as an 8.8, 5.6, and 2.5% increase in all cardiovascular disease (CVD)-, all respiratory-, and all cancer deaths, respectively, in age, gender, race, ZIP code, and SES-adjusted models. PM(2.5) exposures, however, were not associated with lung cancer mortality. Results were not sensitive to control for ozone exposures. PM(2.5)-mortality associations for CVD- and respiratory-related causes were positive and significant for beneficiaries irrespective of their sex, race, age, SES and urbanicity, with no evidence of a lower threshold for response or of lower Risk Ratios (RRs) at low PM(2.5) levels. Associations between PM(2.5) and CVD and respiratory mortality were linear and were higher for younger, Black and urban beneficiaries, but were largely similar by SES. Risks associated with non-traffic PM(2.5) were lower than that for all PM(2.5) and were null for respiratory and lung cancer-related deaths. CONCLUSIONS: PM(2.5) was associated with mortality from CVD, respiratory, and all cancer, but not lung cancer. PM(2.5)-associated risks of CVD and respiratory mortality were similar across PM(2.5) levels, with no evidence of a threshold. Blacks, urban, and younger beneficiaries were most vulnerable to the long-term impacts of PM(2.5) on mortality.
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spelling pubmed-70269802020-02-24 The impact of long-term PM(2.5) exposure on specific causes of death: exposure-response curves and effect modification among 53 million U.S. Medicare beneficiaries Wang, Bingyu Eum, Ki-Do Kazemiparkouhi, Fatemeh Li, Cheng Manjourides, Justin Pavlu, Virgil Suh, Helen Environ Health Research BACKGROUND: The shape of the exposure-response curve for long-term ambient fine particulate (PM(2.5)) exposure and cause-specific mortality is poorly understood, especially for rural populations and underrepresented minorities. METHODS: We used hybrid machine learning and Cox proportional hazard models to assess the association of long-term PM(2.5) exposures on specific causes of death for 53 million U.S. Medicare beneficiaries (aged ≥65) from 2000 to 2008. Models included strata for age, sex, race, and ZIP code and controlled for neighborhood socio-economic status (SES) in our main analyses, with approximately 4 billion person-months of follow-up, and additionally for warm season average of 1-h daily maximum ozone exposures in a sensitivity analysis. The impact of non-traffic PM(2.5) on mortality was examined using two stage models of PM(2.5) and nitrogen dioxide (NO(2)). RESULTS: A 10 μg /m(3) increase in 12-month average PM(2.5) prior to death was associated with a 5% increase in all-cause mortality, as well as an 8.8, 5.6, and 2.5% increase in all cardiovascular disease (CVD)-, all respiratory-, and all cancer deaths, respectively, in age, gender, race, ZIP code, and SES-adjusted models. PM(2.5) exposures, however, were not associated with lung cancer mortality. Results were not sensitive to control for ozone exposures. PM(2.5)-mortality associations for CVD- and respiratory-related causes were positive and significant for beneficiaries irrespective of their sex, race, age, SES and urbanicity, with no evidence of a lower threshold for response or of lower Risk Ratios (RRs) at low PM(2.5) levels. Associations between PM(2.5) and CVD and respiratory mortality were linear and were higher for younger, Black and urban beneficiaries, but were largely similar by SES. Risks associated with non-traffic PM(2.5) were lower than that for all PM(2.5) and were null for respiratory and lung cancer-related deaths. CONCLUSIONS: PM(2.5) was associated with mortality from CVD, respiratory, and all cancer, but not lung cancer. PM(2.5)-associated risks of CVD and respiratory mortality were similar across PM(2.5) levels, with no evidence of a threshold. Blacks, urban, and younger beneficiaries were most vulnerable to the long-term impacts of PM(2.5) on mortality. BioMed Central 2020-02-17 /pmc/articles/PMC7026980/ /pubmed/32066433 http://dx.doi.org/10.1186/s12940-020-00575-0 Text en © The Author(s) 2020 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Wang, Bingyu
Eum, Ki-Do
Kazemiparkouhi, Fatemeh
Li, Cheng
Manjourides, Justin
Pavlu, Virgil
Suh, Helen
The impact of long-term PM(2.5) exposure on specific causes of death: exposure-response curves and effect modification among 53 million U.S. Medicare beneficiaries
title The impact of long-term PM(2.5) exposure on specific causes of death: exposure-response curves and effect modification among 53 million U.S. Medicare beneficiaries
title_full The impact of long-term PM(2.5) exposure on specific causes of death: exposure-response curves and effect modification among 53 million U.S. Medicare beneficiaries
title_fullStr The impact of long-term PM(2.5) exposure on specific causes of death: exposure-response curves and effect modification among 53 million U.S. Medicare beneficiaries
title_full_unstemmed The impact of long-term PM(2.5) exposure on specific causes of death: exposure-response curves and effect modification among 53 million U.S. Medicare beneficiaries
title_short The impact of long-term PM(2.5) exposure on specific causes of death: exposure-response curves and effect modification among 53 million U.S. Medicare beneficiaries
title_sort impact of long-term pm(2.5) exposure on specific causes of death: exposure-response curves and effect modification among 53 million u.s. medicare beneficiaries
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7026980/
https://www.ncbi.nlm.nih.gov/pubmed/32066433
http://dx.doi.org/10.1186/s12940-020-00575-0
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