Objective: To estimate the influence of the ambient PM(l0) and PM(2.5) pollution on the hospital outpatient department visit due to respiratory diseases in local residents in Jinan quantitatively. Methods: Time serial analysis using generalized addictive model (GAM) was conducted. After controlling the confounding factors, such as long term trend, weekly pattern and meteorological factors, considering lag effect and the influence of other air pollutants, the excess relative risks of daily hospital visits associated with increased ambient PM(10) and PM(2.5) levels were estimated by fitting a Poisson regression model. Results: A 10 μg/m(3) increase of PM(10) and PM(2.5) levels was associated with an increase of 0.36%(95%CI: 0.30%-0.43%) and 0.50%(95%CI: 0.30%-0.70%) respectively for hospital visits due to respiratory diseases. Lag effect of 6 days was strongest, the excess relative risks were 0.65% (95% CI: 0.58% -0.71% ) and 0.54% (95% CI: 0.42%-0.67%) respectively. When NO(2) concentration was introduced, the daily hospital visits due to respiratory disease increased by 0.83% as a 10 μg/m(3) increase of PM(10) concentration (95% CI: 0.76%-0.91%). Conclusion: The ambient PM(l0) and PM(2.5) pollution was positively associated with daily hospital visits due to respiratory disease in Jinan, and ambient NO(2) concentration would have the synergistic effect.
Objective: To estimate the influence of the ambient PM(l0) and PM(2.5) pollution on the hospital outpatient department visit due to respiratory diseases in local residents in Jinan quantitatively. Methods: Time serial analysis using generalized addictive model (GAM) was conducted. After controlling the confounding factors, such as long term trend, weekly pattern and meteorological factors, considering lag effect and the influence of other air pollutants, the excess relative risks of daily hospital visits associated with increased ambient PM(10) and PM(2.5) levels were estimated by fitting a Poisson regression model. Results: A 10 μg/m(3) increase of PM(10) and PM(2.5) levels was associated with an increase of 0.36%(95%CI: 0.30%-0.43%) and 0.50%(95%CI: 0.30%-0.70%) respectively for hospital visits due to respiratory diseases. Lag effect of 6 days was strongest, the excess relative risks were 0.65% (95% CI: 0.58% -0.71% ) and 0.54% (95% CI: 0.42%-0.67%) respectively. When NO(2) concentration was introduced, the daily hospital visits due to respiratory disease increased by 0.83% as a 10 μg/m(3) increase of PM(10) concentration (95% CI: 0.76%-0.91%). Conclusion: The ambient PM(l0) and PM(2.5) pollution was positively associated with daily hospital visits due to respiratory disease in Jinan, and ambient NO(2) concentration would have the synergistic effect.
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Keywords:
Daily hospital visit; Generalized addictive model; Inhalable particulates; Respiratory disease; Time series analysis