Impact of extreme temperatures on ambulance dispatches in London, UK
Impact of extreme temperatures on ambulance dispatches in London, UK
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DOI：
10.1016/j.envres.2019.109100
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发表时间：
2020-03-01
影响因子：
8.3
通讯作者：
Pope, Francis D.
中科院分区：
文献类型：
--
作者：
Sangkharat, Kamolrat;Mahmood, Marliyyah A.;Pope, Francis D.
背景：极端温度与健康结果（如死亡率和发病率）之间的关联经常被观察到。然而，相对较少的研究已经调查了极端温度对救护车dispatches.Methods的作用：使用伦敦救护车服务（LAS）的事件数据（2010-2014年），包括5,252,375调度进行了时间序列分析。应用广义线性模型（GLM）与准似然泊松回归分析救护车调度和温度之间的关联。第99度（22.8摄氏度）和第1度（0.0摄氏度）的温度被定义为极端高温和低温。14类救护车调度进行了调查，分为“呼吸”（哮喘，呼吸困难，呼吸道胸部感染，呼吸停止和慢性阻塞性肺病），“心血管”（心脏骤停，胸痛，心脏胸痛RCI，心律失常和其他心脏问题）和“其他”非心肺（头晕，酒精相关，呕吐和“一般不适”）类别。长期趋势、季节性、一周中的某一天、公共假日和空气污染的影响在GLM中得到了控制。还研究了温度的滞后效应。每个类别的阈值温度进行了确定和分布滞后非线性模型（DLNM）报告使用相对风险（RR）值在95%的置信区间。来自999调度和“一般不适”调度类别的总呼叫在低温和高温下都显示出显著的RR。大多数呼吸系统类别（哮喘、呼吸困难和RCI）在低温下具有显著RR，估计RR范围为哮喘的1.392（95%CI：1.161-1.699）至RCI的2.075（95%CI：1.673-2.574）。对于高温，所有其他非心肺功能派遣的RR通常是显著的，范围从“一般不适”的1.280（95%CI：1.128-1.454）到酒精相关的1.985（95%CI：1.422-2.773）。对于心血管组，只有胸痛调度报告一个显着的RR在hightemperature.Conclusions：救护车调度可以与极端温度，依赖于调度类别。建议将气象因素纳入救护车预测模型和预警系统，以提高救护车和一般卫生服务的效率。
Background: Associations between extreme temperatures and health outcomes, such as mortality and morbidity, are often observed. However, relatively little research has investigated the role of extreme temperatures upon ambulance dispatches.Methods: A time series analysis using London Ambulance Service (LAS) incident data (2010-2014), consisting of 5,252,375 dispatches was conducted. A generalized linear model (GLM) with a quasi-likelihood Poisson regression was applied to analyse the associations between ambulance dispatches and temperature. The 99th (22.8 degrees C) and 1st (0.0 degrees C) percentiles of temperature were defined as extreme high and low temperature. Fourteen categories of ambulance dispatches were investigated, grouped into 'respiratory' (asthma, dyspnoea, respiratory chest infection, respiratory arrest and chronic obstructive pulmonary disease), 'cardiovascular' (cardiac arrest, chest pain, cardiac chest pain RCI, cardiac arrhythmia and other cardiac problems) and 'other' non-cardiorespiratory (dizzy, alcohol related, vomiting and 'generally unwell') categories. The effects of long-term trends, seasonality, day of the week, public holidays and air pollution were controlled for in the GLM. The lag effect of temperature was also investigated. The threshold temperatures for each category were identified and a distributed lag non-linear model (DLNM) was reported using relative risk (RR) values at 95% confidence intervals.Results: Many dispatch categories show significant associations with extreme temperature. Total calls from 999 dispatches and 'generally unwell' dispatch category show significant RRs at both low and high temperatures. Most respiratory categories (asthma, dyspnoea and RCI) have significant RRs at low temperatures represented by with estimated RRs ranging from 1.392 (95%CI: 1.161-1.699) for asthma to 2.075 (95%CI: 1.673-2.574) for RCI. The RRs for all other non-cardiorespiratory dispatches were often significant for high temperatures ranging from 1.280 (95% CI: 1.128-1.454) for 'generally unwell' to 1.985 (95%CI: 1.422-2.773) for alcohol-related. For the cardiovascular group, only chest pain dispatches reported a significant RR at high temperatures.Conclusions: Ambulance dispatches can be associated with extreme temperatures, dependent on the dispatch category. It is recommended that meteorological factors are factored into ambulance forecast models and warning systems, allowing for improvements in ambulance and general health service efficiency.