Short term effects of changes in air pollutant concentrations during peaks traffic hours on hospitalization for respiratory diseases

Abstract

Abstract Research on the impact of changes in air pollutant concentrations during peak traffic hours on hospital admissions for respiratory diseases (RD) is limited. This study utilized a distributed lag nonlinear model (DLNM) to investigate this effect. Between 2014 and 2019, a total of 109,419 RD patients were hospitalized across seven hospitals in Lanzhou, China. Except for ozone (O3), fine particulate matter (PM2.5), inhalable particulate matter (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2) and carbon monoxide (CO), which increased by 10 µg/m3 (1 mg/m3 for CO), the relative risk (RR) values of hospitalization for RD were 1.0211 [95% confidence interval (CI) 1.0090, 1.0333] (lag0-7), 1.0026 ( 95% CI 1.0010, 1.0043) (lag0), 1.0615 (95% CI 1.0355, 1.0882) (lag0-7), 1.0650 (95% CI 1.0478, 1.0824) (lag0-7) and 1.1229 (95% CI 1.0686, 1.1800) ( lag0-7), respectively. The stratified analyses revealed that air pollutants, except for O3, affected both males and females. PM2.5, PM10, NO2, and CO had a greater impact on individuals aged < 15 years, while SO2 had a more pronounced effect on those aged ≥ 65 years. The impact of air pollutants on RD hospitalizations was more significant during the cold season. It was recommended that people reduce short-term outdoor exposure during peak traffic hours.

Keywords

• Atmospheric pollution
• Heavy traffic hours
• Respiratory diseases
• Hospitalization
• Relative risk