摘要
目的 了解广东省深圳市极端气温对孕妇120急救量的影响,为孕妇采取防范措施以抵御极端气温所带来的不利影响提供合理建议。方法 收集深圳市急救指挥中心2013年1月1日-2022年12月31日孕妇120救护车调度数据以及深圳市同期气象数据资料,应用分布滞后非线性模型分析极端气温对孕妇120急救量的单日滞后效应和累积滞后效应。结果 深圳市2013-2022年孕妇总急救量为61 270例次,2013、2014、2015、2016、2017、2018、2019、2020、2021和2022年分别为4 968、5 589、5 057、5 595、5 668、4 887、6 384、6 179、6 846和10 097例次,孕妇120急救量呈逐年上升趋势(rs=0.794,P=0.006)。日均气温与孕妇120急救量呈非线性趋势,总体效应呈“U”型,较高的日均气温和较低的日均气温均可增加孕妇的120急救量。分布滞后非线性模型分析结果显示,极端低温的单日滞后效应值在Lag3 d~Lag7 d时均有统计学意义(均P <0.05),其中在Lag4 d时效应值最大(RR=1.015,95%CI=1.004~1.024),极端高温的单日滞后效应值仅在Lag6 d时有统计学意义(RR=1.017,95%CI=1.000~1.034);极端低温和极端高温的累积滞后效应值均随着滞后天数的增加而变大,极端低温累积滞后效应值在Lag0~13 d时最大(RR=1.071,95%CI=1.002~1.145),随后效应值降低且无统计学意义;极端高温累积滞后效应值则在Lag0~11 d时最大(RR=1.192,95%CI=1.033~1.377),随后效应值逐渐降低,在Lag0~14 d时无统计学意义。结论 深圳市孕妇120急救量呈逐年上升趋势,极端高温和极端低温对孕妇120急救量有均有影响,其中极端高温带来的累计滞后效应更加显著。
Objective To 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.Methods The 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.Results The total number of medical emergency ambulance dispatches for pregnant women was 61270 during 2013-2022 in the city and the annual figures ranged from 4968 to 10097,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 temperatur
作者
郑建辉
周丽
程锦泉
ZHENG Jianhui;ZHOU Li;CHENG Jinquan(School of Public Health,Zhengzhou University,Zhengzhou 450001,China;Shenzhen Center for Disease Control and Prevention,Shenzhen 518055,China)
出处
《中国公共卫生》
CAS
CSCD
北大核心
2024年第3期371-374,共4页
Chinese Journal of Public Health
关键词
孕妇
120急救
极端气温
分布滞后非线性模型
pregnant women
medical emergency service
extreme temperature
distributed lag non-linear model
