Background and Objective: Hospital readmission among respiratory patients is an important indicator for evaluating the quality of healthcare services and for assessing the burden of chronic diseases. This study aimed to examine the cumulative effects of PM2.5 and to estimate the attributable risk of respiratory-related readmissions in Sanandaj.
Materials and Methods: In this study, datasets from the Meteorological Organization, hospital readmission records of respiratory patients, along with integrated data from environmental monitoring stations and satellite remote sensing, were utilized. The association between PM2.5 and readmissions was assessed using a semi-parametric regression model with nonlinear functions to control for known and unknown confounders. Based on the model outputs, cumulative effects up to 21 days post-exposure and the attributable risk were estimated, stratified by age and sex.
Results: High concentrations of PM2.5 were significantly associated with cumulative increases in readmissions, particularly among men and individuals under 65 years old. In younger patients (<65 years), there were delayed effects, while in older adults the highest risk occurred during the initial days following exposure. The attributable risk analysis indicated that approximately 3500 readmissions during the study period were attributed to PM2.5 exposure, with the largest proportion observed within the 0–15 μg/m³ concentration range.
Conclusion: This study demonstrated that PM2.5 contributes substantially to respiratory-related hospital readmissions, with effects that were both cumulative and delayed. These findings highlight the need to revise air quality standards, design preventive interventions tailored to age and sex groups, and strengthen early-warning and monitoring systems to reduce the burden of respiratory diseases and healthcare costs.
