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

We aimed to analyse the yet unclear correlation between air pollutant concentrations and out-of-hospital cardiac arrest (OHCA) in Shenzhen, China.

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 (PM_2.5), 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 PM_2.5 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 PM_2.5 and OHCA varied by gender and arrest rhythm. A reduction in the average daily PM_2.5 concentration by 1 µg/m³ could decrease the incidence of OHCA attributable to PM_2.5 exposure by 4.60%, while a reduction by 3 µg/m³ could decrease it by 18.41% on lag Day 1. PM_2.5 was significantly associated with the occurrence of OHCA on lag Day 1. This association was modulated by gender and arrest rhythm.

Improving the levels of PM_2.5, NO₂, and O₃ could decrease the risk of OHCA and the demand for emergency medical service related to PM_2.5 exposure.