Impact of extreme ambient temperatures on medical emergency service for pregnant women in Shenzhen city: an analysis based on ambulance dispatch records from 2013 to 2022

Abstract

ObjectiveTo examine the impact of extreme temperatures on daily number of medical emergency calls from pregnant women in Shenzhen, Guangdong province for providing evidence-based recommendations to the women to mitigate the health effects associated with adverse weather conditions. MethodsThe study collected the data on daily medical ambulance dispatches for pregnant women from 2013 through 2022 from Shenzhen Emergency Command Center and corresponding meteorological data for the same period in Shenzhen city were also collected. A distributed lag nonlinear model was employed to analyze both the single-day and cumulative effects of extreme temperature on daily number of medical emergency services to pregnant women. ResultsThe total number of medical emergency ambulance dispatches for pregnant women was 61 270 during 2013 – 2022 in the city and the annual figures ranged from 4 968 to 10 097, demonstrating a significant increasing trend over the years (rs = 0.794, P = 0.006). A nonlinear correlation was observed between the daily mean temperature and the number of medical emergency calls from pregnant women. Both high and low daily mean temperatures exhibited an approximate 'U' shaped effect, leading to an increase in the quantity of the emergency calls. The results of the lag nonlinear model analysis revealed statistically significant single-day lag effects of extreme low temperatures at lag day 3 – lag day 7 (all P < 0.05), with the strongest effect observed at lag day 4 (relative risk [RR] = 1.015, 95% confidence interval [95%CI]: 1.004 – 1.024). The single-day lag effect of extreme high temperatures was only statistically significant at lag day 6 (RR = 1.017, 95%CI: 1.000 – 1.034). The cumulative lag effects of extreme low and high temperatures exhibited an increasing trend with the number of lag days, reaching its peak for extreme low temperatures at lag day 0 – 13 (RR = 1.071, 95%CI: 1.002 – 1.145), followed by a subsequent decreasing trend without statistical significance observed thereafter. Similarly, the strongest cumulative lag effect for extreme high temperatures occurred at lag day 0 – 11 (RR = 1.192, 95%CI: 1.033 – 1.377), followed by a gradual decrease without statistical significance up to lag day 0 – 14. ConclusionThe number of medical emergency calls from pregnant women in Shenzhen city has been steadily increasing year by year from 2013 to 2022. Both extremely high and low temperatures have a significant impact on the daily volume of emergency calls, with the cumulative lag effect of extreme high temperatures being more pronounced.

Keywords

• pregnant women
• medical emergency service
• extreme temperature
• distributed lag non-linear model