The association between ambient temperature and out-of-hospital cardiac arrest in Guangzhou, China

Abstract

Out-of-hospital cardiac arrest (OHCA) is becoming a considerable public health burden worldwide. The seasonal variation of OHCA has been observed, but the potential effects of ambient temperature on OHCA were rarely investigated. We, therefore, aimed to evaluate the association between ambient temperature and OHCA in Guangzhou, China. We collected daily emergency ambulance dispatches for OHCA from the Guangzhou Emergency Center from January 1, 2008 to December 31, 2012. We analyzed the associations using the time-series method. We applied the generalized linear model combined with the distributed lag non-linear model to estimate the potentially non-linear and lagged effects of temperature on OHCA. Time trends, day of the week, and air pollutants were controlled as covariates. We identified a total of 4369 cases of OHCD. The associations between daily mean temperature and OHCA were generally J-shaped. Both low and high temperatures could increase the risk of OHCA. The effects were strongest on the concurrent day (lag 0) and lasted for 6 or 7days. The cumulative risks of extreme cold (1st percentile of temperature) and extreme heat (99th percentile of temperature) over lags 0-21days were 3.75 (95% confidence interval [CI]: 1.63, 8.63) and 2.45 (95%CI: 1.15, 5.33), respectively, compared with the referent temperature (28°C)·This study suggested that both cold and hot temperatures could significantly increase the risk of OHCA in Guangzhou, China. Our results might have important public health implications for the prevention of OHCA.

Keywords: Epidemiology; Out-of-hospital cardiac arrest; Temperature; Time series.