UNSTRUCTURED
Respiratory infectious diseases are closely related to meteorological conditions and pollutants, and the changes of their epidemiological characteristics rarely explored in recent 10 years. We aimed to assess the incidence and mortality trends for respiratory infectious diseases from 2004 to 2018, and examine the associations between air pollution (PM2.5, PM10, SO2, NO2, O3 and CO exposure and meteorological conditions [mean temperature, relative humidity, air pressure, precipitation, wind speed, and sunlight hours] and respiratory infectious diseases. Data were collected from China’s notifiable infectious disease report database. Joinpoint regression models were used to examine changes in incidence and mortality for each respiratory infectious disease and to estimate average annual percentage changes (AAPCs). We used Pearson’s correlation coefficient to examine the associations between air pollution exposure and meteorological conditions. A Distributed Lag Non-Linear Model (DLNM) with relative risk was applied to analyze the impact of meteorological conditions and air pollutants on respiratory infectious diseases. We also applied a time-series decomposition approach based on LOESS (locally weighted regression) to present the seasonality of seven respiratory infectious diseases. A total of 23,444,640 cases and 45,291 deaths caused by seven respiratory infectious diseases were recorded in China, and the national mean age-standardized incidence and mortality were 115.87/100,000 and 0.23/100,000, respectively. The AAPC of age-adjusted incidence was 0.23 but was -2.11 for age-adjusted mortality; change of incidence and mortality differed by age groups. SO2 and PM10 in air pollutants and relative humidity and air pressure in climatic factors had significant effects on most respiratory diseases in this study. Based on DLNM results, meteorological factors had a stronger impact on respiratory infectious diseases with an acute and short-term lag effect compared with air pollutants.