长期暴露于空气污染对SARS-CoV-2突破性感染中疾病结局和混合免疫反应的影响：中国宜昌COVID-19抗体纵向调查（YC-CALS）研究
Effects of Long-Term Air Pollution Exposure on Disease Outcomes and Hybrid Immune Responses in SARS-CoV-2 Breakthrough Infections: A Study of the Yichang COVID-19 Antibody Longitudinal Survey (YC-CALS) in China.
作者信息
Yan Xiaolong, Du Yin, Li Ke, Zhao Xin, Wang Hao, Liu Li, Wang Qi, Liu Jianhua, Wei Sheng
机构信息
School of Public Health and Emergency Management, Southern University of Science and Technology, Shenzhen, China.
School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
出版信息
Environ Health Perspect. 2025 May;133(5):57022. doi: 10.1289/EHP15660. Epub 2025 May 27.
BACKGROUND
As immunity wanes and viral mutations continue, the risk of endemic SARS-CoV-2 breakthrough infections (BTIs) remains. Air pollution is considered a risk factor for respiratory infection, but evidence of its association with SARS-CoV-2 BTIs is limited.
OBJECTIVES
We aimed to examine the effects of long-term exposure to air pollution on disease outcomes, immune responses, and antibody dynamics of SARS-CoV-2 BTIs.
METHODS
We gathered data on self-reported SARS-CoV-2 infections through questionnaires and measured IgG antibody levels using serological assays from a total of 6,875 participants from the Yichang COVID-19 Antibody Longitudinal Survey cohort in China. Air pollutant exposure [particulate matter (PM) with an aerodynamic diameter (), PM with an aerodynamic diameter (), PM with an aerodynamic diameter (), , , , and CO] was quantified using validated models for the past 5 y (2018-2022). Logistic and linear regression models were applied to analyze the associations between air pollutant levels and SARS-CoV-2 BTIs, Long COVID, COVID-19 hospitalization, and antibody responses. Quantile g-computation was used to assess the combined effects of pollutant mixtures. A linear mixed model was used to evaluate the effect of air pollution on antibody dynamics.
RESULTS
Per interquartile range (IQR) increase in , , , and CO, the adjusted odds ratios (ORs) for SARS-CoV-2 BTIs were 1.65 [95% confidence interval (CI): 1.30, 2.08], 1.30 (95% CI: 1.12, 1.50), 1.63 (95% CI: 1.20, 2.20), and 1.24 (95% CI: 1.06, 1.45). The ORs for were 1.78 (95% CI: 1.07, 3.02) and 2.02 (95% CI: 1.18, 3.54) for Long COVID and hospitalization. Per IQR increase in and , IgG antibody percentages decreased by (95% CI: , ) and (95% CI: , ). Effects were stronger in older adults, those with comorbidities, and the undervaccinated. The combined effect on SARS-CoV-2 BTIs was mainly driven by (59.4%), and the impact on IgG response was largely attributed to (63.7%). Exposure to the highest levels of (), (), and () was associated with a faster IgG decline than the lowest.
DISCUSSION
Long-term exposure to air pollution increases the risk of SARS-CoV-2 BTIs and disease severity while weakening the immune response, particularly for vulnerable populations. https://doi.org/10.1289/EHP15660.
背景
随着免疫力下降和病毒突变持续存在，SARS-CoV-2突破性感染（BTIs）的流行风险依然存在。空气污染被认为是呼吸道感染的一个风险因素，但其与SARS-CoV-2 BTIs关联的证据有限。
目的
我们旨在研究长期暴露于空气污染对SARS-CoV-2 BTIs的疾病结局、免疫反应和抗体动态的影响。
方法
我们通过问卷调查收集了自我报告的SARS-CoV-2感染数据，并使用血清学检测方法测量了来自中国宜昌COVID-19抗体纵向调查队列的6875名参与者的IgG抗体水平。使用经过验证的模型对过去5年（2018 - 2022年）的空气污染物暴露情况进行量化，这些空气污染物包括空气动力学直径小于等于10μm的颗粒物（PM10）、空气动力学直径小于等于2.5μm的颗粒物（PM2.5）、空气动力学直径小于等于1μm的颗粒物（PM1）、二氧化氮（NO₂）、二氧化硫（SO₂）、臭氧（O₃）和一氧化碳（CO）。应用逻辑回归和线性回归模型分析空气污染物水平与SARS-CoV-2 BTIs、长期新冠、COVID-19住院以及抗体反应之间的关联。使用分位数g计算来评估污染物混合物的综合影响。使用线性混合模型评估空气污染对抗体动态的影响。
结果
PM10、PM2.5、PM1和CO每增加一个四分位数间距（IQR），SARS-CoV-2 BTIs的调整比值比（OR）分别为1.65 [95%置信区间（CI）：1.30, 2.08]、1.30（95% CI：1.12, 1.50）、1.63（95% CI：1.20, 2.20）和1.24（95% CI：1.06, 1.45）。长期新冠和住院的OR分别为1.78（95% CI：1.07, 3.02）和2.02（95% CI：1.18, 3.54）。PM2.5和PM1每增加一个IQR，IgG抗体百分比分别下降（95% CI：, ）和（95% CI：, ）。在老年人、患有合并症的人群以及未充分接种疫苗的人群中，影响更为强烈。对SARS-CoV-2 BTIs的综合影响主要由PM2.5（59.4%）驱动，对IgG反应的影响主要归因于PM1（63.7%）。暴露于最高水平的PM2.5（）、PM1（）和O₃（）与IgG下降速度比最低水平更快有关。
讨论
长期暴露于空气污染会增加SARS-CoV-2 BTIs的风险和疾病严重程度，同时削弱免疫反应，特别是对脆弱人群。https://doi.org/10.1289/EHP15660 。
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