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

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.