基于室内WBGT的中暑发病率预测模型  

Prediction Model for Heatstroke Incidence Based on Indoor WBGT

作　　者：王若睿 刘书晓 邹钺[1] 刘赟 Wang Ruorui;Liu Shuxiao;Zou Yue;Liu Yun(College of Environmental Science and Engineering,Donghua University,Shanghai,201620;Dianwei Science Co.,Ltd,Shanghai,201602)

机构地区：[1]东华大学环境科学与工程学院,上海201620 [2]典唯科技股份有限公司,上海201602

出　　处：《制冷与空调(四川)》2025年第1期115-120,共6页Refrigeration and Air Conditioning

摘　　要：近年来,随着全球变暖的加剧,高温中暑的发病率越来越普遍。利用日本四个地区六年间6月-9月的救护车每日中暑运输记录和气象数据,确定中暑的潜在危险因素,建立可靠的中暑发病率预测模型。结果表明,室内湿球黑球温度(WBGT)每日温度最高五小时的平均温度与中暑发病率相关性最佳;连续高温天数对中暑发生过程中人体热适应的作用规律在预测中暑患者数量的高峰期和夏末患者数量方面表现优异。该预测模型可为相关人员制定减少中暑患者和保障应急运输安全的策略提供可靠依据。In recent years,with the intensification of global warming,the incidence of heatstroke in high temperatures has become increasingly common.This article utilizes the daily records of heatstroke transports by ambulances and meteorological data from four regions in Japan over six years(June to September)to identify potential risk factors for heatstroke and establish a reliable prediction model for its occurrence.The results show that the average temperature of the indoor wet bulb globe temperature(WBGT)during the five hottest hours of the day has the strongest correlation with the incidence of heatstroke.The effect of consecutive hot days on the process of heat adaptation in the human body performs exceptionally well in predicting the peak period of heatstroke cases and the number of patients towards the end of summer.This prediction model can provide reliable evidence for relevant personnel to develop strategies to reduce heatstroke cases and ensure the safety of emergency transportation.

关 键 词：中暑发病率 室内WBGT 连续高温天数 热适应 

分 类 号：R594.1[医药卫生—内科学]