Effect of atmospheric pollen concentration on daily visits of allergic rhinitis in Beijing: a distributed lag nonlinear model analysis

• Published in: International journal of biometeorology 2023-11, Vol.67 (11), p.1723-1732
• Main Authors: Liu, Aizhu, Sheng, Weixuan, Tang, Xianshi, Yin, Jinshu
• Format: Article
• Language: English
• Subjects: Allergic rhinitis; Animal Physiology; Atmospheric effects; Biological and Medical Physics; Biophysics; Correlation coefficient; Correlation coefficients; Earth and Environmental Science; Emergency medical care; Emergency medical services; Environment; Environmental Health; Hay fever; Meteorology; Original Paper; Plant Physiology; Pollen; Rhinitis
• ISSN: 0020-7128; 1432-1254
• DOI: 10.1007/s00484-023-02533-0

To investigate the influence and lag effect of atmospheric pollen concentration on daily visits of patients with allergic rhinitis (AR), we collected the AR data during the pollen seasons from 2018 to 2019 from the outpatient and emergency department of Beijing Shijitan Hospital. The distributed lag non-linear model (DLNM) was used to analyze the correlation and the lag effect between pollen concentration and the incidence of AR. R4.1.2 was used to generate the Spearman correlation coefficients and plot the lag response curves of relative risk specific and incremental cumulative effects. In 2018 and 2019, the number of AR visits was moderately positively correlated with pollen concentration. The peak value of the overall specific cumulative effect for every 10 grains/1000 mm 2 increase in atmospheric pollen concentration occurred on day 0 (2018, 2019), and the lag disappearance time was day 6 (2018) and day 7 (2019), and the specific cumulative effect duration was respectively 6 days (2018) and 7 days (2019), with the curve showing a downward trend with time increase. In 2018, the peak value of the overall incremental cumulative effect was on day 7, the lag disappearance time was day 13, and the duration of the incremental cumulative effect was 13 days, forming a curve pattern of rising first and then falling. In 2019, the peak value time of the overall incremental cumulative effect was on day 8, and the curve went down afterwards until it showed the trend of ascending again after day26.