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Avoidable mortality due to long-term exposure to PM(2.5) in Colombia 2014–2019

OBJECTIVE: To compare estimates of spatiotemporal variations of surface PM(2.5) concentrations in Colombia from 2014 to 2019 derived from two global air quality models, as well as to quantify the avoidable deaths attributable to the long-term exposure to concentrations above the current and projecte...

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Autores principales: Rodriguez-Villamizar, Laura A., Belalcazar-Ceron, Luis Carlos, Castillo, María Paula, Sanchez, Edwin Ricardo, Herrera, Víctor, Agudelo-Castañeda, Dayana Milena
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9789551/
https://www.ncbi.nlm.nih.gov/pubmed/36564760
http://dx.doi.org/10.1186/s12940-022-00947-8
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author Rodriguez-Villamizar, Laura A.
Belalcazar-Ceron, Luis Carlos
Castillo, María Paula
Sanchez, Edwin Ricardo
Herrera, Víctor
Agudelo-Castañeda, Dayana Milena
author_facet Rodriguez-Villamizar, Laura A.
Belalcazar-Ceron, Luis Carlos
Castillo, María Paula
Sanchez, Edwin Ricardo
Herrera, Víctor
Agudelo-Castañeda, Dayana Milena
author_sort Rodriguez-Villamizar, Laura A.
collection PubMed
description OBJECTIVE: To compare estimates of spatiotemporal variations of surface PM(2.5) concentrations in Colombia from 2014 to 2019 derived from two global air quality models, as well as to quantify the avoidable deaths attributable to the long-term exposure to concentrations above the current and projected Colombian standard for PM(2.5) annual mean at municipality level. METHODS: We retrieved PM(2.5) concentrations at the surface level from the ACAG and CAMSRA global air quality models for all 1,122 municipalities, and compare 28 of them with available concentrations from monitor stations. Annual mortality data 2014–2019 by municipality of residence and pooled effect measures for total, natural and specific causes of mortality were used to calculate the number of annual avoidable deaths and years of potential life lost (YPLL) related to the excess of PM(2.5) concentration over the current mean annual national standard of 25 µg/m(3) and projected standard of 15 µg/m(3). RESULTS: Compared to surface data from 28 municipalities with monitoring stations in 2019, ACAG and CAMSRA models under or overestimated annual mean PM(2.5) concentrations. Estimations from ACAG model had a mean bias 1,7 µg/m(3) compared to a mean bias of 4,7 µg/m(3) from CAMSRA model. Using ACAG model, estimations of total nationally attributable deaths to PM(2.5) exposure over 25 and 15 µg/m(3) were 142 and 34,341, respectively. Cardiopulmonary diseases accounted for most of the attributable deaths due to PM(2.5) excess of exposure (38%). Estimates of YPLL due to all-cause mortality for exceeding the national standard of 25 µg/m(3) were 2,381 years. CONCLUSION: Comparison of two global air quality models for estimating surface PM(2.5) concentrations during 2014–2019 at municipality scale in Colombia showed important differences. Avoidable deaths estimations represent the total number of deaths that could be avoided if the current and projected national standard for PM(2.5) annual mean have been met, and show the health-benefit of the implementation of more restrictive air quality standards. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12940-022-00947-8.
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spelling pubmed-97895512022-12-25 Avoidable mortality due to long-term exposure to PM(2.5) in Colombia 2014–2019 Rodriguez-Villamizar, Laura A. Belalcazar-Ceron, Luis Carlos Castillo, María Paula Sanchez, Edwin Ricardo Herrera, Víctor Agudelo-Castañeda, Dayana Milena Environ Health Research OBJECTIVE: To compare estimates of spatiotemporal variations of surface PM(2.5) concentrations in Colombia from 2014 to 2019 derived from two global air quality models, as well as to quantify the avoidable deaths attributable to the long-term exposure to concentrations above the current and projected Colombian standard for PM(2.5) annual mean at municipality level. METHODS: We retrieved PM(2.5) concentrations at the surface level from the ACAG and CAMSRA global air quality models for all 1,122 municipalities, and compare 28 of them with available concentrations from monitor stations. Annual mortality data 2014–2019 by municipality of residence and pooled effect measures for total, natural and specific causes of mortality were used to calculate the number of annual avoidable deaths and years of potential life lost (YPLL) related to the excess of PM(2.5) concentration over the current mean annual national standard of 25 µg/m(3) and projected standard of 15 µg/m(3). RESULTS: Compared to surface data from 28 municipalities with monitoring stations in 2019, ACAG and CAMSRA models under or overestimated annual mean PM(2.5) concentrations. Estimations from ACAG model had a mean bias 1,7 µg/m(3) compared to a mean bias of 4,7 µg/m(3) from CAMSRA model. Using ACAG model, estimations of total nationally attributable deaths to PM(2.5) exposure over 25 and 15 µg/m(3) were 142 and 34,341, respectively. Cardiopulmonary diseases accounted for most of the attributable deaths due to PM(2.5) excess of exposure (38%). Estimates of YPLL due to all-cause mortality for exceeding the national standard of 25 µg/m(3) were 2,381 years. CONCLUSION: Comparison of two global air quality models for estimating surface PM(2.5) concentrations during 2014–2019 at municipality scale in Colombia showed important differences. Avoidable deaths estimations represent the total number of deaths that could be avoided if the current and projected national standard for PM(2.5) annual mean have been met, and show the health-benefit of the implementation of more restrictive air quality standards. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12940-022-00947-8. BioMed Central 2022-12-24 /pmc/articles/PMC9789551/ /pubmed/36564760 http://dx.doi.org/10.1186/s12940-022-00947-8 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Rodriguez-Villamizar, Laura A.
Belalcazar-Ceron, Luis Carlos
Castillo, María Paula
Sanchez, Edwin Ricardo
Herrera, Víctor
Agudelo-Castañeda, Dayana Milena
Avoidable mortality due to long-term exposure to PM(2.5) in Colombia 2014–2019
title Avoidable mortality due to long-term exposure to PM(2.5) in Colombia 2014–2019
title_full Avoidable mortality due to long-term exposure to PM(2.5) in Colombia 2014–2019
title_fullStr Avoidable mortality due to long-term exposure to PM(2.5) in Colombia 2014–2019
title_full_unstemmed Avoidable mortality due to long-term exposure to PM(2.5) in Colombia 2014–2019
title_short Avoidable mortality due to long-term exposure to PM(2.5) in Colombia 2014–2019
title_sort avoidable mortality due to long-term exposure to pm(2.5) in colombia 2014–2019
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9789551/
https://www.ncbi.nlm.nih.gov/pubmed/36564760
http://dx.doi.org/10.1186/s12940-022-00947-8
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