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[目的]探讨武汉市不同粒径颗粒物数浓度(PNCs)对市民呼吸系统疾病日门诊量的短期影响。[方法]收集2014年武汉市不同粒径颗粒物的日均数浓度、同期气象参数资料以及部分市级医院呼吸系统疾病日门诊量数据。采用时间序列的半参数广义相加模型分析颗粒物数浓度对呼吸道疾病日门诊量影响的最佳滞后时间及暴露-反应关系。[结果]单污染物模型结果显示,在最佳滞后条件下,PNC0.25-0.5每升高一个四分位间距值时,全人群和男性呼吸系统疾病日门诊量分别增加5.60%(RR=1.056 0,95%CI:1.004 5~1.110 2)和8.63%(RR=1.086 3,95%CI:1.027 0~1.148 9);PNC0.5-1.0每升高一个四分位间距值时,全人群和男性呼吸系统疾病日门诊量分别增加2.42%(RR=1.024 2,95%CI:1.006 7~1.042 1)和3.29%(RR=1.032 9,95%CI:1.013 4~1.052 8);PNC1.0-2.5每升高一个四分位间距值时,全人群和男性的呼吸系统疾病日门诊量分别增加4.45%(RR=1.044 5,95%CI:1.013 4~1.076 5)和3.89%(RR=1.038 9,95%CI:1.003 6~1.075 4)。双污染物模型结果显示,当分别调整可吸入颗粒物、细颗粒物、二氧化硫、二氧化氮、一氧化碳和臭氧质量浓度后,PNC0.5-1.0与全人群及男性的呼吸系统疾病日门诊量仍呈正相关关系(P<0.05),但PNC0.25-0.5仅与男性呼吸系统疾病日门诊量的相关性稳健(P<0.05)。[结论]当调整了颗粒物及气态污染物的质量浓度后,粒径<1.0μm颗粒物数浓度对全人群和男性呼吸系统疾病日门诊量的影响较明显。
[Objective] To explore the short-term effect of different particle size concentration (PNCs) in Wuhan on daily outpatient respiratory diseases. [Method] The daily mean concentration of particulate matter of different particle size, meteorological parameter data of the same period and the daily outpatient data of respiratory diseases in municipal hospitals were collected in 2014. The time series of semi-parametric generalized additive model was used to analyze the best lag time and exposure-response relationship between the concentration of particulate matter and the daily outpatient volume of respiratory diseases. [Results] The results of single-pollutant model showed that at the best lag condition, the daily outpatient visits of respiratory diseases increased by 5.60% (PNR = 1.056 0,95% CI: 1.004 5 ~ 1.110 2) and 8.63% (RR = 1.086 3,95% CI: 1.027 0 ~ 1.148 9). When PNC 0.5-1.0 was increased by one interquartile range, The daily outpatient visits for both the population and the male respiratory system increased by 2.42% (RR = 1.024 2, 95% CI: 1.006 7 to 1.042 1) and 3.29% (RR = 1.032 9, 95% CI: 1.013 4 to 1.052 8) .0-2.5 Daily outpatient visits increased 4.45% (RR = 1.044 5,95% CI: 1.013 4 ~ 1.076 5) and 3.89% (% RR = 1.038 9,95% CI: 1.003 6-1.075 4). The results of the double-pollutant model showed that PNC0.5-1.0 still had a positive respiratory disease outbreak with both the whole population and males when the respirable particulate matter, fine particulate matter, sulfur dioxide, nitrogen dioxide, carbon monoxide and ozone concentrations were separately adjusted (P <0.05). However, the correlation between PNC0.25-0.5 and the daily outpatient respiratory disease was steady (P <0.05). [Conclusion] When the mass concentration of particulate matter and gaseous pollutants was adjusted, the effect of particle number of particles with particle size <1.0μm on the daily outpatient volume of respiratory diseases was more obvious.