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Association between Particulate Matter Pollution Concentration and Hospital Admissions for Hypertension in Ganzhou, China
Fine particulate matter (PM(2.5)) and respirable particulate matter (PM(10)) are two major air pollutants with toxic effects on the cardiovascular system. Hypertension, as a chronic noncommunicable cardiovascular disease, is also a risk factor for several diseases. We applied generalized linear mode...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Hindawi
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8872648/ https://www.ncbi.nlm.nih.gov/pubmed/35223092 http://dx.doi.org/10.1155/2022/7413115 |
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author | Li, Chenwei Zhou, Xinye Huang, Kun Zhang, Xiaokang Gao, Yanfang |
author_facet | Li, Chenwei Zhou, Xinye Huang, Kun Zhang, Xiaokang Gao, Yanfang |
author_sort | Li, Chenwei |
collection | PubMed |
description | Fine particulate matter (PM(2.5)) and respirable particulate matter (PM(10)) are two major air pollutants with toxic effects on the cardiovascular system. Hypertension, as a chronic noncommunicable cardiovascular disease, is also a risk factor for several diseases. We applied generalized linear models with a quasi-Poisson link to assess the effect of air pollution exposure on the number of daily admissions for patients with hypertension. In addition, we established a two-pollutant model to evaluate PM(2.5) and PM(10) hazard effect stability by adjusting the other gaseous pollutants. Results showed that during the study period, 24 h mean concentrations of ambient PM(2.5) and PM(10) at 38.17 and 59.84 μg/m(3), respectively, and a total of 2,611 hypertension hospital admissions were recorded. Air pollution concentrations significantly affected the number of hospitalizations for hypertension approximately 2 months after exposure. For each 10 μg/m(3) increase in PM(2.5) and PM(10) in single-pollutant models, the number of hospitalizations for hypertension increased by 7.92% (95% CI: 5.48% to 10.42%) and 4.46% (95% CI: 2.86% to 5.65%), respectively, at the lag day with the strongest effect. NO(2), O(3), CO, and SO(2) had different significant effects on the number of hospitalizations over the same time period, and PM(2.5) and PM(10) still showed robust significant effects after adjustment of gas pollutants through a two-pollutant model. These findings may contribute to a better understanding of the health effects of ambient particulate matter. |
format | Online Article Text |
id | pubmed-8872648 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-88726482022-02-25 Association between Particulate Matter Pollution Concentration and Hospital Admissions for Hypertension in Ganzhou, China Li, Chenwei Zhou, Xinye Huang, Kun Zhang, Xiaokang Gao, Yanfang Int J Hypertens Research Article Fine particulate matter (PM(2.5)) and respirable particulate matter (PM(10)) are two major air pollutants with toxic effects on the cardiovascular system. Hypertension, as a chronic noncommunicable cardiovascular disease, is also a risk factor for several diseases. We applied generalized linear models with a quasi-Poisson link to assess the effect of air pollution exposure on the number of daily admissions for patients with hypertension. In addition, we established a two-pollutant model to evaluate PM(2.5) and PM(10) hazard effect stability by adjusting the other gaseous pollutants. Results showed that during the study period, 24 h mean concentrations of ambient PM(2.5) and PM(10) at 38.17 and 59.84 μg/m(3), respectively, and a total of 2,611 hypertension hospital admissions were recorded. Air pollution concentrations significantly affected the number of hospitalizations for hypertension approximately 2 months after exposure. For each 10 μg/m(3) increase in PM(2.5) and PM(10) in single-pollutant models, the number of hospitalizations for hypertension increased by 7.92% (95% CI: 5.48% to 10.42%) and 4.46% (95% CI: 2.86% to 5.65%), respectively, at the lag day with the strongest effect. NO(2), O(3), CO, and SO(2) had different significant effects on the number of hospitalizations over the same time period, and PM(2.5) and PM(10) still showed robust significant effects after adjustment of gas pollutants through a two-pollutant model. These findings may contribute to a better understanding of the health effects of ambient particulate matter. Hindawi 2022-02-17 /pmc/articles/PMC8872648/ /pubmed/35223092 http://dx.doi.org/10.1155/2022/7413115 Text en Copyright © 2022 Chenwei Li et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Li, Chenwei Zhou, Xinye Huang, Kun Zhang, Xiaokang Gao, Yanfang Association between Particulate Matter Pollution Concentration and Hospital Admissions for Hypertension in Ganzhou, China |
title | Association between Particulate Matter Pollution Concentration and Hospital Admissions for Hypertension in Ganzhou, China |
title_full | Association between Particulate Matter Pollution Concentration and Hospital Admissions for Hypertension in Ganzhou, China |
title_fullStr | Association between Particulate Matter Pollution Concentration and Hospital Admissions for Hypertension in Ganzhou, China |
title_full_unstemmed | Association between Particulate Matter Pollution Concentration and Hospital Admissions for Hypertension in Ganzhou, China |
title_short | Association between Particulate Matter Pollution Concentration and Hospital Admissions for Hypertension in Ganzhou, China |
title_sort | association between particulate matter pollution concentration and hospital admissions for hypertension in ganzhou, china |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8872648/ https://www.ncbi.nlm.nih.gov/pubmed/35223092 http://dx.doi.org/10.1155/2022/7413115 |
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