Objective To explore the interaction effects between air temperature and fine particulate matter (PM2.5) on population's respiratory system diseases in four cities of Shandong province, China.
Methods The daily data on meteorological factors, PM2.5 mass concentrations and the number of visits for respiratory diseases to departments of internal medicine in some hospitals were collected in the four cities from 2019 to 2021. Pearson correlation analysis was performed to analyze the relationship between meteorological factors, PM2.5 mass concentrations and the number of visits for respiratory diseases. The distributed lag nonlinear model was used to estimate the effects of air temperature on visit for respiratory diseases. The potential interaction between PM2.5 and air temperature was evaluated using the relative excess risk due to interaction (RERI).
Results The average daily temperature was negatively correlated with PM2.5, mass concentrations with correlation coefficient being -0.471(P < 0.01). The number of visits for respiratory diseases was negatively correlated with the average daily temperature (r =-0.059, P < 0.01) and average relative humidity (r =-0.056, P < 0.01), while positively correlated with PM2.5 mass concentrations (r =0.10, P < 0.01). The average daily temperature and PM2.5 mass concentrations showed antagonistic interaction in Jinan RERI =-0.11, 95%confidence interval (CI): -0.15, -0.08), and synergistic interaction between average daily temperature and PM2.5 mass concentrations in Zibo (RERI =0.04, 95%CI: 0.04, 0.04, Binzhou (RERI =0.10, 95%CI: 0.10 to 0.11) and Heze (RERI =0.03, 95%CI: 0.02, 0.05), all with statistical significance (P < 0.05).
Conclusion Daily average air temperature might modify the effects of PM2.5 on the number of visits for respiratory diseases, and their interaction effect might have regional differences.
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