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探索短期空气污染与过敏性鼻炎每日门诊之间的关联
Authors Tang W, Sun L, Wang J, Li K, Liu S, Wang M, Cheng Y, Dai L
Received 4 May 2023
Accepted for publication 25 July 2023
Published 7 August 2023 Volume 2023:16 Pages 1455—1465
DOI https://doi.org/10.2147/RMHP.S416365
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 2
Editor who approved publication: Dr Jongwha Chang
Purpose: Many studies have reported that exposure to air pollution increases the likelihood of acquiring allergic rhinitis (AR). This study investigated associations between short-term air pollution exposure and AR outpatient visits.
Patients and Methods: The Department of Otorhinolaryngology, Affiliated Hospital of Hangzhou Normal University provided AR outpatient data from January 1, 2019 to December 31, 2021. Daily air quality information for that period was gathered from the Hangzhou Air Quality Inspection Station. We used the Poisson’s generalized additive model (GAM) to investigate relationships between daily outpatient AR visits and air pollution, and investigated lag-exposure relationships across days. Subgroup analyses were performed by age (adult (> 18 years) and non-adult (< 18 years)) and sex (male and female).
Results: We recorded 20,653 instances of AR during the study period. Each 10 g/m3 increase in fine particulate matter (PM10 and PM2.5) and carbon monoxide (CO) concentrations was associated with significant increases in AR outpatient Visits. The relative risks (RR) were: 1.007 (95% confidence interval (CI): 1.001– 1.013), 1.026 (95% CI: 1.008– 1.413), and 1.019 (95% CI: 1.008– 1.047). AR visits were more likely due to elevated PM2.5, PM10, and CO levels. Additionally, children were more affected than adults.
Conclusion: To better understand the possible effects of air pollution on AR, short-term exposure to ambient air pollution (PM2.5, PM10, and CO) may be linked to increased daily outpatient AR visits.
Keywords: air pollution, daily outpatient visits, allergic rhinitis, the Poisson’s generalized additive model, GAM, PM10, PM2.5