Association Between Sulfur Dioxide and Daily Inpatient Visits With Respiratory Diseases in Ganzhou, China: A Time Series Study Based on Hospital Data

Abstract

Background: Sulfur dioxide (SO₂) has been reported to be related to the mortality of respiratory diseases, but the relationship between SO₂ and hospital inpatient visits with respiratory diseases and the potential impact of different seasons on this relationship is still unclear.

Methods: The daily average concentrations of air pollutants, including SO₂ and meteorological data in Ganzhou, China, from 2017 to 2019 were collected. The data on daily hospitalization for respiratory diseases from the biggest hospital in the city were extracted. The generalized additive models (GAM) and the distributed lag non-linear model (DLNM) were employed to evaluate the association between ambient SO₂ and daily inpatient visits for respiratory diseases. Stratified analyses by gender, age, and season were performed to find their potential effects on this association.

Results: There is a positive exposure-response relationship between SO₂ concentration and relative risk of respiratory inpatient visits. Every 10 μg/m³ increase in SO₂ was related to a 3.2% (95% CI: 0.6-6.7%) exaltation in daily respiratory inpatient visits at lag3. In addition, SO₂ had a stronger association with respiratory inpatient visits in women, older adults (≥65 years), and warmer season (May-Oct) subgroups. The relationship between SO₂ and inpatient visits for respiratory diseases was robust after adjusting for other air pollutants, including PM₁₀, NO₂, O₃, and CO.

Conclusion: This time-series study showed that there is a positive association between short-term SO₂ exposure and daily respiratory inpatient visits. These results are important for local administrators to formulate environmental public health policies.

Keywords: air pollution; distributed lag non-linear models; generalized additive models; inpatient visits; respiratory disease; sulfur dioxide; time-series analysis.