Time-series analysis of pollen concentration effects on allergic conjunctivitis healthcare visits in Beijing, 2023–2024

Objective: To analyze the lagged effects of pollen concentration on allergic conjunctivitis (AC) healthcare visits and investigate the influence of environmental factors and pathogen infections on AC risk. Methods: Daily AC outpatient and emergency cases from Beijing Shijitan Hospital, along with concurrent meteorological and pollen concentration data from March 1 to October 31 in 2023-2024, were collected. Spearman rank correlation analysis, generalized additive models (GAM), and distributed lag non-linear models (DLNM) were employed to plot lag-response curves for specific cumulative effects and incremental cumulative effects of relative risks. Results: = 0.637), while meteorological factors (including temperature, air pressure, etc.) showed weaker correlations. Lagged effect analysis demonstrated that the AC lag effect associated with pollen exposure in 2024 was significantly stronger than in 2023, displaying a strict dose-response relationship with pollen concentration levels. The peak value increase from baseline in relative risk (RR) for specific cumulative effects was 2.6 times higher (0.0018 in 2024 vs. 0.0007 in 2023), with a 1.9-fold longer lag duration (28 days vs. 15 days). For incremental cumulative effects, the time to peak doubled (day 28 in 2024 vs. day 15 in 2023), and the lag duration exceeded 50 days in 2024 (vs. 27 days in 2023). The lag-response curve exhibited biphasic peaks in 2024, contrasting with the unimodal pattern in 2023. Conclusion: This study confirms that pollen concentration is the dominant factor affecting the lagged effects of AC visits, with a clear dose-response relationship. The findings provide a scientific basis for AC prevention strategies and public health early-warning systems.