Does hourly variation in ambient nitrogen dioxide increase the risk of acute asthma hospitalisations? A time-series study of Birmingham and Solihull, UK.

Abstract

This study aims to investigate the association between hourly nitrogen dioxide (NO₂) concentrations and emergency hospital admissions for adult patients with asthma in the Birmingham-Solihull metropolitan area, West Midlands, UK. A time-series study. The study was conducted in the Birmingham-Solihull metropolitan area, West Midlands, UK. Adult patients with asthma (aged ≥16 years at the time of admission) from 1 June 2016 to 31 May 2022 residing in Birmingham and Solihull, West Midlands. We analysed the hourly rate of emergency hospital admissions for acute asthma. A Poisson generalised additive model combined with the distributed lag non-linear model was applied to assess the association between hourly NO₂ concentrations and hourly counts of hospital admissions for acute asthma. Furthermore, the effect modification of the NO₂-asthma association in specific participant groups, such as sex, deprivation index and ethnicity, was explored in stratified analyses. The study included 18 943 adults with asthma exacerbations who attended the four acute hospitals in the study area during the study period. The study observed a significant positive association between hospital admissions for acute asthma and hourly NO₂ concentrations. The mean NO₂ exposure (18 µg/m³) over a lag of 0-24 hours was associated with a 13% (RR=1.13, 95% CI 1.01 to 1.26) increase in the risk of daytime emergency hospital admissions for acute asthma in comparison with no exposure. The results show a significant association between NO₂ exposure and hospital admissions for a lag of 3-6 hours. Furthermore, subgroup-specific analysis indicated a higher positive risk associated with hourly NO₂ among patients living in the most deprived areas. This study strengthens the evidence for the importance of using high-temporal resolution air pollution data to examine impacts on health, particularly where there are marked temporal patterns in exposure. Understanding these exposure-response relationships will improve healthcare preparedness and resource allocation in relation to air pollution levels.