Time series analysis on atmospheric particulate matter and daily outpatient visits of internal medicine in Heze from 2019-2021
Objective To investigate the effect of atmospheric particulate matter exposure on daily outpatient visits of internal medicine in Heze City,aiming to provide scientific basis for effective health risk assessment of air pollution and effective intervention measures to improve population health.Methods The daily outpatient data from 2019 to 2021 were collected,and daily air pollutant data and meteorological data were also collected.The generalized additive model with time-series Poisson distribution was used to investigate the relationship between atmospheric particulate matter and the daily outpatient volume of internal medicine,the daily outpatient volume of respiratory system diseases,and the daily outpatient volume of circulatory system diseases in this city.The influence of atmospheric particulate matter concentration on the outpatient volume of these three diseases after the introduction of other pollutants was analyzed.Results There was a correlation between the concentration of air pollutants and the daily outpatient volume of internal medicine in Heze City.For every 10 μg/m3 increase in PM2.5,the effect value of daily outpatient volume of internal medicine,daily outpatient volume of respiratory diseases and daily outpatient volume of circulatory system diseases reached the strongest effect at Lag09,Lag0 10,Lag0 days,respectively,with ER(95%CI)of 1.05%(0.44%-1.66%),2.15%(1.48%-2.83%),0.68%(0.33%-1.02%).Every 10 μg/m3 increase in PM10 had the strongest effect on the total volume of internal medicine,the daily outpatient volume of respiratory system and the daily outpatient volume of circulatory system at Lag02,Lag09 and Lag01 days,respectively,with ER(95%CI)of 0.21%(0.05%-0.38%),0.80%(0.48%-1.12%)and 0.21%(0.04%-0.37%).Conclusion The increase of PM2.5 and PM10 concentration in Heze City may increase the number of internal medicine outpatient visits,and there is a certain hysteresis.
Atmospheric particulate matterRespiratory diseasesCirculatory diseasesTime series analysis