The study was conducted to explore the effects of atmospheric pollutants on allergic skin diseases, combining principal component analysis and multiple linear regression modeling to statistically analyze the data of atmospheric pollutants (PM2.5, PM10, etc.) and outpatient cases of allergic skin diseases in hospitals in Nanchong City from 2020 to 2024. The main components of air pollutants were extracted by dimensionality reduction using principal component analysis to solve the problem of multicollinearity among variables. Regression models were also constructed to analyze the association between principal components and the incidence of allergic skin diseases. The results showed that the principal component analysis extracted three principal components in the atmospheric pollutants with a cumulative variance contribution of 91.97%. The annual average concentrations of the atmospheric pollutants PM2.5, PM10, NO₂, SO₂, CO, and O₃ were 31.267 µg/m³, 51.109 µg/m³, and 24.252 µg/m³, respectively, from 2020 to 2024, 7.765 µg/m³, 0.951 mg/m³, and 131.452 µg/m³. The regression model showed that a 1-unit increase in atmospheric CO concentration was associated with a significant increase in the risk of allergic skin visits by 6.22. The regression model provided a good fit with errors between the predicted and true values of the number of visits for urticaria, eczema, and contact dermatitis in 2 general hospitals ranging between 0 and 1. The study confirmed that atmospheric oxidizing pollutants are the main environmental risk factors for allergic skin diseases in Nanchong City.
