徐志伟, 童世庐, 胡文彪, 程健, 黄存瑞, 郑浩. 热浪定义对其健康效应评估的影响:以泰国为例[J]. 环境与职业医学, 2020, 37(1): 3-8. DOI: 10.13213/j.cnki.jeom.2020.19500
引用本文: 徐志伟, 童世庐, 胡文彪, 程健, 黄存瑞, 郑浩. 热浪定义对其健康效应评估的影响:以泰国为例[J]. 环境与职业医学, 2020, 37(1): 3-8. DOI: 10.13213/j.cnki.jeom.2020.19500
XU Zhiwei, TONG Shi-lu, HU Wen-biao, CHENG Jian, HUANG Cun-rui, ZHENG Hao. Impact of heatwave definition on health effect assessment: Evidence from Thailand[J]. Journal of Environmental and Occupational Medicine, 2020, 37(1): 3-8. DOI: 10.13213/j.cnki.jeom.2020.19500
Citation: XU Zhiwei, TONG Shi-lu, HU Wen-biao, CHENG Jian, HUANG Cun-rui, ZHENG Hao. Impact of heatwave definition on health effect assessment: Evidence from Thailand[J]. Journal of Environmental and Occupational Medicine, 2020, 37(1): 3-8. DOI: 10.13213/j.cnki.jeom.2020.19500

热浪定义对其健康效应评估的影响:以泰国为例

Impact of heatwave definition on health effect assessment: Evidence from Thailand

  • 摘要: 背景

    热浪在全球很多国家都是高致死率的自然灾害,对公众健康造成严重威胁。但目前在全球范围内,对于如何定义热浪,尚无共识。

    目的

    探讨热浪定义对其健康效应评估的影响,为热浪预警系统的建立提供依据。

    方法

    收集泰国60个省1999年1月1日-2008年12月31日的气象与各死因死亡数据。气象数据具体包括每日最高气温、最低气温、平均气温、相对湿度。各死因包括总死亡和因缺血性心脏病、肺炎、糖尿病引起的死亡,具体死因根据国际疾病伤害及死因分类标准第十版(ICD10)编码。采用准泊松非线性分布滞后模型来评估热浪对泰国人群死亡风险的短期影响,并比较热浪期间总死亡和各死因的死亡风险在不同热浪定义(强度和持续时间)下的变化。其中,热浪强度定义分别为每日平均气温的第90百分位数(P90)和P95P97P98;持续时间包括≥ 2 d、≥ 3 d、≥ 4 d。采用随机效应meta分析定量合并60个省的结果,计算热浪对泰国人群各疾病死亡的总效应值,即以相对危险度(RR)及其95%可信区间(CI)的大小衡量人群对热浪敏感性的高低。

    结果

    相比于非热浪期间,热浪期间人群总死亡和各死因死亡风险均升高。在低强度的热浪期间(平均气温> P90且持续≥ 2 d),总死亡的风险增高12.8%(95% CI:10.6%~15.1%)。热浪期间人群死亡的RR,并非完全随着热浪强度或持续时间的增加而增加。在持续≥ 2 d时,肺炎引起的死亡RR(95% CI)为1.42(1.27~1.59)和糖尿病引起的死亡RR(95% CI)为1.34(1.17~1.52),对以P97定义的热浪最敏感;而总死亡(RR:1.16,95% CI:1.13~1.20)和缺血性心脏病引起的死亡(RR:1.35,95% CI:1.24~1.48),对以P95定义的热浪最敏感。而以P98定义时为例,糖尿病引起的死亡风险随着热浪持续时间的增加而增加,但总死亡和肺炎引起的死亡风险随着热浪持续时间的增加而降低。

    结论

    本研究提示,不同强度和持续时间定义模式下的热浪,对疾病死亡风险的影响有差异。因此在热浪预警系统和其他热浪适应性政策的制定中,根据各地区人群的热浪易感性特点,量体裁衣式地使用热浪定义,可能更有利于保障人群健康。

     

    Abstract: Background

    Heatwaves are a lethal natural disaster in many countries, posing a big threat to population health. However, there is no international consensus on how to properly define a heatwave.

    Objective

    This study aims to understand the impact of heatwave definition on the assessment of the health effects of heatwaves, and to provide evidence for the development of heatwave early warning systems.

    Methods

    Data on climatic variables and cause-specific deaths in 60 provinces of Thailand from 1st January 1999 to 31st December 2008 were collected. Climatic variables included daily maximum temperature, minimum temperature, mean temperature, and relative humidity. Deaths included total deaths and deaths from ischemic heart disease, pneumonia, and diabetes. Cause of death was classified according to the International Classification of Diseases, Tenth Version (ICD10). Quasi-Poisson regression combined with distributed lag non-linear model was used to assess the short-term effect of heatwaves on deaths in Thailand, and compare the risks of total and causespecific deaths under different heatwave definitions (intensity and duration). The cut-off percentiles used for heatwave definitions were the 90th, 95th, 97th, and 98th percentiles of daily mean temperature; the durations were ≥ 2 d, ≥ 3 d, and ≥ 4 d, respectively. The total effects of heatwaves on cause-specific deathsrelative risks (RR) and corresponding 95% confidence intervals (CI) were estimated by random-effect meta-analysis that combined the results of the 60 provinces.

    Results

    The risks of total and cause-specific deaths increased significantly during heatwave periods, compared with non-heatwave periods. During mild heatwaves (> the 90th percentile of mean temperature and ≥ 2 d), the risk of total deaths increased by 12.8% (95% CI:10.6%-15.1%). The RR of deaths during heatwaves did not consistently increase with the increase of heatwave intensity or duration. When the heatwave duration was ≥ 2 d, deaths due to pneumoniaRR:1.42, 95% CI:1.27-1.59 and deaths due to diabetes (RR:1.34, 95% CI:1.17-1.52) were most vulnerable to the heatwaves defined using the 97th percentile of mean temperature distribution as the threshold; total deaths (RR:1.16, 95% CI:1.13-1.20) as well as deaths due to ischemic heart disease (RR:1.35, 95% CI:1.24-1.48) were most vulnerable to the heatwaves defined using the 95th percentile of mean temperature distribution as the threshold. When the heatwave cut-off percentile was the 98th percentile, with the extension of heatwave duration, the risk of deaths from diabetes increased, but the risks of total deaths and deaths due to pneumonia decreased.

    Conclusion

    This study suggests that the impact of heatwaves on death risks changes under different intensity and duration definitions. Therefore, in the development of heatwave warning systems and other heat adaptation strategies, incorporating the characteristics of heatwave vulnerability of local population and adopting an optimal local heatwave definition may more effectively protect public health in the face of heatwaves.

     

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