Reserch On The Relationship Between Respiratory Diseases And Meteorological Factors And Air Quality In Beijing

Respiratory diseases are common to people.Weather events can directly or indirectly lead to respiratory diseases.The close relationship between climate change,air quality and respiratory diseases has become a problem that people must pay attention to and need to be deeply understood.Based on the daily meteorological data,air quality data and the data of a Grade-A tertiary hospital in Beijing from 2013 to 2016,this paper studied the variation of meteorological factors,air quality and the number of patients with respiratory diseases by descriptive analysis,correlation analysis and stepwise regression,and analyzed the correlation between meteorological factors,air quality and the number of patients with respiratory diseases month by month,with consideration of the hysteresis.The monthly prediction equation of respiratory diseases is established as a result.The data from 2013 to 2016 are used for back generation test.The data of 2017 are used for prediction test.The results are as following:(1)The mean air pressure and temperature(including mean,maximum and minimum temperature)in Beijing were increasing year by year,while the mean wind speed,precipitation and relative humidity were decreasing yearly,especially the precipitation.The average wind speed in April was the highest and the lowest in August;the precipitation in July was the heaviest and the least in December;the relative humidity in August was the highest and the lowest in January;the mean pressure in January was the highest and the lowest in July;the temperature in July was the highest and the lowest in January.The seasonal variations of meteorological factors were basically consistent with monthly variations.(2)The air quality of Beijing had shown a trend of improvement year by year.The air quality of Beijing in 2016 was the best and the worst in 2013 and 2014.As the seasonal variations of air quality,air quality was the worst in winter,and the difference was not significant among spring,summer and autumn.(3)The number of patients with respiratory diseases in a Grade-A tertiary hospital in Beijing decreased significantly from 2013 to 2014,and the number increased year by year from 2014 to 2016.From the seasonal variation of the number of visits to hospital,autumn and winter were more frequent,and less in spring and summer.From 2013 to 2016,the proportion of male patients with respiratory diseases was higher than that of female patients.The proportion of elderly and young patients was higher than that of adult and middle-aged patients.The elderly group had the largest share of patients.(4)The correlation analysis of meteorological factors and air quality with the number of patients with respiratory diseases showed that air temperature(mean,maximum,and minimum temperature)had a significant impact on the number of patients almost throughout the year.Daily temperature range had a significant impact on the number of patients in February-June and August;mean air pressure had a significant impact on the number of patients in January,May-October and December;mean wind speed had a significant impact on the number of patients only in February,April,June and December;relative humility had a significant impact throughout of the year;precipitation had a significant impact on the number of patients in January-March,May-July,and November.The number of patients was significantly affected in January-March,May-July and November,and Air Quality Index(AQI)significantly affected the number of patients in January-February,April-July and November-December.The influence of temperature(average,maximum,and minimum)and relative humidity on the number of patients was more significant than that of other meteorological factors and air quality.(5)Using multiple stepwise regression method,the prediction equation of respiratory diseases from January to December was established,and the regression test showed that the accuracy of the monthly prediction equation was above 67% except for February and October.If the difference of the number was 30%,the prediction formula would be accurate.Through forecasting test,except for February and October,the accuracy rate of the course reached more than 66%,and the monthly forecast error rate of January-December was less than 17% according to the monthly number of patients.According to the long-term trend of substitution test,forecasting test and the number of patients,the results of the forecasting equation is still satisfactory.This study has a certain reference value for guiding the health care of the population.The results of this study mainly provide scientific basis for the meteorological factors and the influence of air quality on respiratory diseases,as well as for the prevention of respiratory diseases.