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Spatiotemporal variations of asthma admission rates and their relationship with environmental factors in Guangxi, China
OBJECTIVE: The study aimed to determine if and how environmental factors correlated with asthma admission rates in geographically different parts of Guangxi province in China. SETTING: Guangxi, China. PARTICIPANTS: This study was done among 7804 asthma patients. PRIMARY AND SECONDARY OUTCOME MEASURE...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7542934/ https://www.ncbi.nlm.nih.gov/pubmed/33033020 http://dx.doi.org/10.1136/bmjopen-2020-038117 |
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author | Ma, Rui Liang, Lizhong Kong, Yunfeng Chen, Mingyang Zhai, Shiyan Song, Hongquan Hou, Yane Zhang, Guangli |
author_facet | Ma, Rui Liang, Lizhong Kong, Yunfeng Chen, Mingyang Zhai, Shiyan Song, Hongquan Hou, Yane Zhang, Guangli |
author_sort | Ma, Rui |
collection | PubMed |
description | OBJECTIVE: The study aimed to determine if and how environmental factors correlated with asthma admission rates in geographically different parts of Guangxi province in China. SETTING: Guangxi, China. PARTICIPANTS: This study was done among 7804 asthma patients. PRIMARY AND SECONDARY OUTCOME MEASURES: Spearman correlation coefficient was used to estimate correlation between environmental factors and asthma hospitalisation rates in multiple regions. Generalised additive model (GAM) with Poisson regression was used to estimate effects of environmental factors on asthma hospitalisation rates in 14 regions of Guangxi. RESULTS: The strongest effect of carbon monoxide (CO) was found on lag1 in Hechi, and every 10 µg/m(3) increase of CO caused an increase of 25.6% in asthma hospitalisation rate (RR 1.26, 95% CI 1.02 to 1.55). According to the correlation analysis, asthma hospitalisations were related to the daily temperature, daily range of temperature, CO, nitrogen dioxide (NO(2)) and particulate matter (PM(2.5)) in multiple regions. According to the result of GAM, the adjusted R(2) was high in Beihai and Nanning, with values of 0.29 and 0.21, which means that environmental factors are powerful in explaining changes of asthma hospitalisation rates in Beihai and Nanning. CONCLUSION: Asthma hospitalisation rate was significantly and more strongly associated with CO than with NO(2), SO(2) or PM(2.5) in Guangxi. The risk factors of asthma exacerbations were not consistent in different regions, indicating that targeted measures should differ between regions. |
format | Online Article Text |
id | pubmed-7542934 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-75429342020-10-19 Spatiotemporal variations of asthma admission rates and their relationship with environmental factors in Guangxi, China Ma, Rui Liang, Lizhong Kong, Yunfeng Chen, Mingyang Zhai, Shiyan Song, Hongquan Hou, Yane Zhang, Guangli BMJ Open Public Health OBJECTIVE: The study aimed to determine if and how environmental factors correlated with asthma admission rates in geographically different parts of Guangxi province in China. SETTING: Guangxi, China. PARTICIPANTS: This study was done among 7804 asthma patients. PRIMARY AND SECONDARY OUTCOME MEASURES: Spearman correlation coefficient was used to estimate correlation between environmental factors and asthma hospitalisation rates in multiple regions. Generalised additive model (GAM) with Poisson regression was used to estimate effects of environmental factors on asthma hospitalisation rates in 14 regions of Guangxi. RESULTS: The strongest effect of carbon monoxide (CO) was found on lag1 in Hechi, and every 10 µg/m(3) increase of CO caused an increase of 25.6% in asthma hospitalisation rate (RR 1.26, 95% CI 1.02 to 1.55). According to the correlation analysis, asthma hospitalisations were related to the daily temperature, daily range of temperature, CO, nitrogen dioxide (NO(2)) and particulate matter (PM(2.5)) in multiple regions. According to the result of GAM, the adjusted R(2) was high in Beihai and Nanning, with values of 0.29 and 0.21, which means that environmental factors are powerful in explaining changes of asthma hospitalisation rates in Beihai and Nanning. CONCLUSION: Asthma hospitalisation rate was significantly and more strongly associated with CO than with NO(2), SO(2) or PM(2.5) in Guangxi. The risk factors of asthma exacerbations were not consistent in different regions, indicating that targeted measures should differ between regions. BMJ Publishing Group 2020-10-07 /pmc/articles/PMC7542934/ /pubmed/33033020 http://dx.doi.org/10.1136/bmjopen-2020-038117 Text en © Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. http://creativecommons.org/licenses/by-nc/4.0/ http://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/. |
spellingShingle | Public Health Ma, Rui Liang, Lizhong Kong, Yunfeng Chen, Mingyang Zhai, Shiyan Song, Hongquan Hou, Yane Zhang, Guangli Spatiotemporal variations of asthma admission rates and their relationship with environmental factors in Guangxi, China |
title | Spatiotemporal variations of asthma admission rates and their relationship with environmental factors in Guangxi, China |
title_full | Spatiotemporal variations of asthma admission rates and their relationship with environmental factors in Guangxi, China |
title_fullStr | Spatiotemporal variations of asthma admission rates and their relationship with environmental factors in Guangxi, China |
title_full_unstemmed | Spatiotemporal variations of asthma admission rates and their relationship with environmental factors in Guangxi, China |
title_short | Spatiotemporal variations of asthma admission rates and their relationship with environmental factors in Guangxi, China |
title_sort | spatiotemporal variations of asthma admission rates and their relationship with environmental factors in guangxi, china |
topic | Public Health |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7542934/ https://www.ncbi.nlm.nih.gov/pubmed/33033020 http://dx.doi.org/10.1136/bmjopen-2020-038117 |
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