【摘要】 目的探讨石家庄市大气颗粒物对暴露人群下呼吸道感染住院的影响。方法收集石家庄市大气污染资料、气象资料及因下呼吸道感染入院患者的资料,应用Pearson相关分析研究大气颗粒物与气象因素的相关性。采用双向病例交叉研究,条件logistic回归对数据进行分析,应用单污染物模型,探究各颗粒物浓度对下呼吸道感染住院风险的影响及滞后效应。应用多污染物模型,探究各颗粒物浓度对下呼吸道感染住院风险的影响。在多污染物模型的基础上,采用分层分析控制性别、年龄、合并症及季节等潜在混杂因素,分析大气颗粒物对暴露人群呼吸道感染的影响。结果 Pearson相关分析表明,大气污染物PM_2.5、PM₁₀、SO₂、NO₂、CO之间存在正相关,这些污染物与日均气温及O₃呈负相关。在单污染物模型中,当日PM_2.5浓度及滞后5d的PM₁₀浓度每增加10μg/m³,对应OR值（95%CI）分别为1.010（1.005¹.015）、1.006（1.003¹.009）,即当日PM_2.5浓度及滞后5d的PM₁₀浓度每增加10μg/m³,下呼吸道感染的住院风险分别增加1.0%（0.5%¹.5%）、0.6%（0.3%⁰.9%）。在多污染物模型中,PM_2.5仍然会增加下呼吸道感染住院的风险。分层分析结果显示,与女性、≥60岁和有合并症患者相比,PM_2.5暴露会增加男性、<60岁和无合并症患者下呼吸道感染住院的风险,且该效应在冷季节中更为明显;而与男性、<60岁和无合并症者比较,PM₁₀暴露会增加女性、≥60岁及存在合并症者下呼吸道感染住院的风险,且该效应在冷季节中更为明显。结论石家庄市大气颗粒物(PM₁₀/PM_2.5)浓度的升高可导致下呼吸道感染患者住院增加。更多还原

【Abstract】 Objective To explore the association between atmospheric particulate matter(PM₁₀/PM_2.5) levels and hospital admissions due to lower respiratory tract infection in Shijiazhuang. Methods Data of air pollution, meteorologic data, and the data of patients admitted to hospital due to lower respiratory tract infection were retrospectively analyzed. Pearson’s correlation coefficients were calculated to analyze correlations between atmospheric particulate matter and meteorologic factors. Data of hospital admission due to lower respiratory tract infection and of atmospheric air pollution levels in Shijiazhuang were obtained, a bidirectional case-crossover design was used to investigate the association between hospital admissions due to lower respiratory tract infection and levels of atmospheric particles. Stratified analyses of exposure based on age, gender, complications and season were performed to evaluate the effect. Results Pearson’s correlation analysis showed positive correlations among PM_2.5, PM₁₀, SO₂, NO₂ and CO. The concentration of all these five pollutants were negatively correlated with O3 and daily mean temperature, while a positive correlation was found between concentrations of the 5 pollutants and daily average temperature and O₃. In single-pollutant model, every 10μg/m³ increase in PM_2.5 and PM₁₀ at lag5 brought the corresponding OR values（95%CI） up to 1.010（1.005-1.015） and 1.006（1.003-1.009） respectively. In the multi-pollutant models, the observed effects of PM_2.5 remained significant. Stratified analysis based on gender, age, season and comorbidities showed that the effect of PM_2.5 exposure on lower respiratory tract infection admissions was stronger in males, persons younger than 60 years of age and persons without comorbidities, and even more stronger in cold season. The effect of PM₁₀ exposure on lower respiratory tract infection admissions was stronger in females, persons older than 60 years of age and persons with comorbidities, and even more stronger in cold season. Conclusion Our study demonstrates that higher levels of atmospheric particulate matter(PM₁₀/PM_2.5) may increase the risk of hospital admissions due to lower respiratory tract infection.更多还原