Zhang Jian, Zhang Jingwei, Li Pengfei, Xu Yandan, Zhou Xuesong, Qiu Jia, Tang Xiuli, Ding Zhongao, Xu Mingjia, Wang Chongjian
Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, China.
Department of Environmental and Occupational Health, Jinshan District Center for Disease Control and Prevention, Shanghai, China.
Prev Med. 2025 Feb;191:108217. doi: 10.1016/j.ypmed.2024.108217. Epub 2024 Dec 30.
This study aimed to explore the associations between short-term air pollution exposure and acute exacerbation of chronic bronchitis (AECB).
AECB data were collected from hospital surveillance systems in Shanghai, China, during 2018-2022. Exposure pollution data were obtained from China high resolution high quality near-surface air pollution datasets and assigned to individuals based on their residential addresses. The time-stratified case crossover design combined with the conditional logistic regression model were used to estimate the associations between air pollution and AECB. Weighted quantile sum regression evaluated combined pollution effects and key pollutants.
A total of 2202 hospitalized cases with AECB were included. On day 7 of the average lag (lag 07-day), the odds ratios (OR) of air pollution (Particulate matter with aerodynamic diameters of ≤2.5 μm (PM), 2.5-10 μm (PM), and ≤ 10 μm (PM), Ozone (O), Sulfur dioxide (SO), Nitrogen dioxide (NO)) with AECB increased by 10 μg/m were 1.07 (95 % confidence interval (CI): 1.02-1.12), 1.13 (1.06, 1.21), 1.06 (1.03-1.09), 1.03 (1.01-1.06), 2.05 (1.51-2.80) and 1.11 (1.05-1.18), respectively. Combined exposure was also positively associated with the risk of AECB (OR 1.04, 95 % CI 1.00-1.08), with O being the most significant.
This study demonstrates that short-term exposure to air pollution was significantly associated with higher risk of AECB. O might contribute the most to AECB. Policymakers should pay more attention to air pollution control.
本研究旨在探讨短期空气污染暴露与慢性支气管炎急性加重（AECB）之间的关联。
收集了2018 - 2022年期间中国上海医院监测系统的AECB数据。暴露污染数据来自中国高分辨率高质量近地面空气污染数据集，并根据个体的居住地址分配给他们。采用时间分层病例交叉设计结合条件逻辑回归模型来估计空气污染与AECB之间的关联。加权分位数和回归评估了综合污染效应和关键污染物。
共纳入2202例AECB住院病例。在平均滞后的第7天（滞后07天），空气污染（空气动力学直径≤2.5μm的颗粒物（PM）、2.5 - 10μm的颗粒物（PM）、≤10μm的颗粒物（PM）、臭氧（O）、二氧化硫（SO）、二氧化氮（NO））每增加10μg/m³，与AECB的比值比（OR）分别为1.07（95%置信区间（CI）：1.02 - 1.12）、1.13（1.06，1.21）、1.06（1.03 - 1.09）、1.03（1.01 - 1.06）、2.05（1.51 - 2.80）和1.11（1.05 - 1.18）。综合暴露也与AECB风险呈正相关（OR 1.04，95% CI 1.00 - 1.08），其中O最为显著。
本研究表明，短期暴露于空气污染与AECB的较高风险显著相关。O可能对AECB的影响最大。政策制定者应更加关注空气污染控制。
