Time series analysis of low-concentration air pollution and hospital respiratory disease outpatient visits

低浓度空气污染与医院呼吸系统疾病门诊就诊量的时间序列分析

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Abstract

OBJECTIVE: The aim of this study was to analyze the effects of short-term exposure to low concentrations of air pollutants on the volume of respiratory outpatient visits in hospitals and their lagged effects. METHODS: The study collected outpatient data from seven hospitals in Fuzhou City, air pollution data provided by the Fuzhou Environmental Monitoring Center Station, and meteorological data from the Fuzhou Meteorological Bureau for analysis from 2019 to 2022. Time series analysis was used to explore the relationship between air pollutants and meteorological factors and daily outpatient visits for respiratory diseases by constructing a generalized linear model (GLM). RESULTS: From 2019 to 2022, the total outpatient volume of respiratory diseases in 7 hospitals in Fuzhou was 1,530,000, with pediatrics accounting for 72.44% and internal medicine accounting for 27.56%. Air pollutants such as PM(2.5), PM(10), NO(2), and SO(2) all had significant impacts on the total respiratory and pediatric respiratory outpatient volumes. NO(2) and PM(10) had the greatest impact on respiratory diseases on the day of pollution exposure or 1 day later, while SO(2) and PM(2.5) exhibited longer lag effects, with the most significant impact occurring at a lag period of 4-6 days. The impact of air pollution on pediatric respiratory disease outpatient visits was generally more significant than that on adult. CONCLUSION: Low concentrations of air pollution significantly impacted respiratory outpatient visits in Fuzhou, especially in children. Despite relatively good air quality, air pollution in low-pollution areas poses a public health risk, highlighting the need for targeted pollution control policies.

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