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Association of long-term exposure to ambient air pollution with the number of tuberculosis cases notified: a time-series study in Hong Kong
Xu, Man Hu, Ping Chen, Ruoling Liu, Bing Chen, Hongying Hou, Jian Ke, Li Huang, Jiao Ren, Hairong Hu, Hui
Xu, Man
Hu, Ping
Chen, Ruoling
Liu, Bing
Chen, Hongying
Hou, Jian
Ke, Li
Huang, Jiao
Ren, Hairong
Hu, Hui
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2021-11-12
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Abstract
To analyze the association of long-term exposure to air pollution and its attributable risks with the number of tuberculosis (TB) cases notified, a quasi-Poisson regression model combined with a distributed lag nonlinear model (DLNM) was constructed using monthly data on air pollution and TB cases notified in Hong Kong from 1999 to 2018. Nonlinear relationships between PM10, PM2.5, and CO and TB cases notified were identified. The concentrations of PM10, PM2.5, and CO corresponding to the minimum numbers of TB cases notified (the minimum TB notification concentrations, MTNCs) were 58.3 μg/m3, 41.7 μg/m3, and 0.1 mg/m3, respectively. Compared with the MTNCs, the overall cumulative numbers of TB cases notified increased by 76.93% (95% CI: 13.08%, 176.83%), 88.81% (95% CI: 26.09%, 182.71%), and 233.43% (95% CI: 13.56%, 879.03%) for the 95th percentiles of PM10 and PM2.5 and for the 97.5th percentiles of CO, respectively. The TB notification rate attributed to concentration ranges above the 97.5th percentile of PM10, PM2.5, and CO was 3.38% (95% empirical confidence intervals [eCI]: 0.93%, 5.61%), 4.73% (95% eCI: 1.87%, 7.15%), and 3.34% (95% eCI: 0.29%, 5.83%), respectively. Long-term exposure to high concentrations of air pollution in Hong Kong may be associated with increases in the number of TB cases notified for this area.
Citation
Xu, M., Hu, P., Chen, R. et al. (2022) Association of long-term exposure to ambient air pollution with the number of tuberculosis cases notified: a time-series study in Hong Kong. Environmental Science and Pollution Research, 29, pp. 21621–21633. https://doi.org/10.1007/s11356-021-17082-5
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34767173 (pubmed)
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Journal article
Language
en
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This is an accepted manuscript of a paper published by Springer on 12/11/2021, available online at: https://doi.org/10.1007/s11356-021-17082-5. The accepted manuscript of the publication may differ from the final published version. For re-use please see the publisher's terms and conditions.
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ISSN
0944-1344
EISSN
1614-7499