Shenzhen Longhua District Central Hospital, 187 Guanlan Avenue, Longhua District, Shenzhen, 518110, China.
School of Public Health, Sun Yat-sen University, Zhongshan Road #2, Guangzhou, 510080, China.
Int J Biometeorol. 2021 Nov;65(11):1871-1880. doi: 10.1007/s00484-021-02143-8. Epub 2021 May 8.
Current development of temperature-related health early warning systems mainly arises from knowledge of temperature-related mortality or hospital-based morbidity. However, due to the delay in data reporting and limits in hospital capacity, these indicators cannot be used in health risk assessments timely. In this study, we examine temperature impacts on emergency ambulance and discuss the benefits of using this near real-time indicator for risk assessment and early warning. We collected ambulance dispatch data recording individual characteristics and preliminary diagnoses between 2015 and 2016 in Shenzhen, China. Distributed lag nonlinear model was used to examine the effects of high and low temperatures on ambulance dispatches during warm and cold seasons. Lag effects were also assessed to evaluate the sensitivity of ambulance dispatches in reflecting immediate health reactions. Stratified analyses by gender, age, and a wide range of diagnoses were performed to identify vulnerable subgroups. Disease-specific numbers of ambulance dispatches attributable to non-optimal temperature were calculated to determine the related medical burdens. Effects of temperature on ambulance dispatches appeared to be acute on the current day. Males, people aged 18-44 years, were more susceptible to non-optimal temperatures. Highest RR during heat exposure by far was for urinary disease, alcohol intoxication, and traumatic injury, while alcohol intoxication and cardiovascular disease were especially sensitive to cold exposure, causing the main part of health burden. The development of local health surveillance systems by utilizing ambulance dispatch data are important for temperature impact assessments and medical resource reallocation.
目前,与温度相关的健康预警系统的发展主要源于与温度相关的死亡率或基于医院的发病率方面的知识。然而,由于数据报告的延迟和医院容量的限制,这些指标不能及时用于健康风险评估。在本研究中,我们研究了温度对急诊救护车的影响,并讨论了利用这一接近实时的指标进行风险评估和预警的好处。我们收集了 2015 年至 2016 年期间中国深圳的救护车派遣数据,记录了个体特征和初步诊断。分布式滞后非线性模型用于检验高温和低温对温暖和寒冷季节救护车派遣的影响。还评估了滞后效应,以评估救护车派遣反映即时健康反应的敏感性。按性别、年龄和广泛的诊断进行分层分析,以确定脆弱亚组。计算了因非最佳温度而导致的特定疾病的救护车派遣数量,以确定相关的医疗负担。温度对救护车派遣的影响似乎是当天急性的。男性和 18-44 岁的人群对非最佳温度更敏感。在高温暴露期间,最高 RR 远高于尿路疾病、酒精中毒和创伤性损伤,而酒精中毒和心血管疾病对寒冷暴露特别敏感,导致了主要的健康负担。利用救护车派遣数据开发当地健康监测系统对于温度影响评估和医疗资源重新分配非常重要。