ABSTRACT
Objective To explore the effects of atmospheric haze and air pollutants(PM10, PM2.5), SO2, NO2 on hospital visits for cardiovascular diseases. Methods The relationship among atmospheric haze, air pollution and the outpatients data of Guangzhou for cardiovascular disease had been investigated by collecting the air pollution data, the meteorological data and cardiovascular diseases’ outpatients data in Guangzhou city from January 1, 2006 to December 31,2008 . The time-series analysis by auto-regression model was used, controlling for long -term trends, seasonal patterns and meteorological variables. Results Auto-regression model showed that the number of outpatients in 2008 was higher than that in 2006.The number was larger in April and December compared with that in January, and it was higher on Monday, Tuesday, Wednesday, Thursday and Friday than on Saturday, Sunday. There was a positive correlation between the haze level and cardiovascular outpatients. The number of hospital outpatients increased by 2.12 units with each additional day of the atmospheric haze. The haze level (lag2) of the former second day had a negative impact on the intraday data of outpatients. The residual parts showed that outpatients’ residual data (AR1, AR3) of the former first and third day had a positive effect on intraday outpatients’ residual data (increased by 52.25%, 26.1%), while the outpatients’ residual data of the former second day (AR2) had a negative effect on outpatients’ residual data of the present day (decreased by 17%). In addition, a variety of air pollutants (PM10, PM2.5, SO2, and NO2) showed some positive correlation, and had hysteresis. Conclusion The atmospheric haze, generated from suspended particulate, meteorological factor and gaseous pollutants, is the environmental pathogenic factor for the cardiovascular diseases, while the effects of single air pollutant on the hospital visit for cardiovascular diseases can be weakened by the haze pollution.
ABSTRACT
Objective To know the relationship between air pollutants and daily hospital visits for respiratory diseases in Guangzhou. Methods The data of daily hospital visits for respiratory diseases in a hospital in Guangzhou during 2006 to 2008, along with the daily meteorological factors, air pollutants concentration (NO2, PM10,PM2.5 and SO2) were collected. The time series analysis auto-regression model was used, considering the potential confounding factors such as seasonal and meteorological factors. Results Daily hospital visits for respiratory diseases presented a significant week effect, the time of higher daily hospital visits for respiratory diseases was the same of higher concentration of pollutants. When SO2 and NO2 increased by 10 ?g/m3, the daily hospital visits increased by 3%(P