Association between air pollutants and out-of-hospital cardiac arrest: a 5-year time series analysis

Abstract Aims We aimed to analyse the yet unclear correlation between air pollutant concentrations and out-of-hospital cardiac arrest (OHCA) in Shenzhen, China. Methods and results A 5-year time series analysis of all OHCA events reported to the Shenzhen Emergency Center was conducted. Quasi-Poisson regression, controlling for meteorological variables (daily mean relative temperature and humidity) with multivariable fractional polynomial and using Fourier series to adjust for long-term trends and account for periodic patterns, was used to assess the association among particulate matter of 2.5 μm (PM2.5), ozone (O3), particulate matter of ≥10 μm (PM10), carbon monoxide (CO), nitrogen dioxide (NO2), sulfur dioxide (SO2), and OHCA. Data from 16 769 patients who experienced OHCA were analysed. An increase of 10 μg/m3 in PM2.5 was associated with a higher risk of OHCA (relative risk (RR): 1.026 [95% confidence interval [CI]: 1.001–1.053]) on lag Day 1. A similar increase in PM10 was linked to an immediate risk of OHCA on the onset day (RR: 1.02 [95% CI: 1.005–1.036]) and a cumulative risk on lag Day 1 (RR: 1.021 [95% CI: 1.003–1.039]). An increased risk of OHCA was associated with NO2 and O3 exposure, while a reduced risk of OHCA was associated with SO2 and CO exposure in the subsequent 5 days. The relationship between PM2.5 and OHCA varied by gender and arrest rhythm. A reduction in the average daily PM2.5 concentration by 1 µg/m³ could decrease the incidence of OHCA attributable to PM2.5 exposure by 4.60%, while a reduction by 3 µg/m³ could decrease it by 18.41% on lag Day 1. PM2.5 was significantly associated with the occurrence of OHCA on lag Day 1. This association was modulated by gender and arrest rhythm. Conclusion Improving the levels of PM2.5, NO2, and O3 could decrease the risk of OHCA and the demand for emergency medical service related to PM2.5 exposure.