Analysis Of The Influence Of Environmental Factors On Respiratory Diseases

In recent years,extreme weather changes in Changchun have been increasing,air pollution in spring and winter is serious,and the number of patients suffering from respiratory tract has increased significantly compared with the same period of the previous year.In view of this phenomenon,this paper mainly studies the relationship between air pollutants（SO₂、NO₂、CO、O₃、PM2.5 and PM10）,meteorological related indicators（average pressure,average humidity,etc.）in Changchun City and hospitalizations in respiratory diseases.Collecting hospitalized cases,air pollutants and related meteorological indicators for respiratory diseases in Jilin Province General Hospital of Jilin First Hospital from 2013 to 2017.Firstly,gender and age differential analysis is performed on the collected patient data,and statistical analysis such as correlation analysis and significance test are performed on the collected data.Then,after selecting the PM2.5 and the air pressure as independent variables through the LASSO algorithm,the multivariate linear model,the ARIMAX model and the machine learning model（decision tree,support vector regression）for the number of hospitalized patients with weekly respiratory disease are respectively established,according to the AIC information minimum criterion and standardization and the minimum normal-mean-square error（NMSE）selects the optimal model—ARIMAX model,and gives 1 week prediction,and finally draws conclusions and gives appropriate suggestions.