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巴西的热舒适条件与死亡率。

Thermal Comfort Conditions and Mortality in Brazil.

机构信息

Center for Environment and Public Health Studies, School of Public Policy and Government, Fundação Getulio Vargas, Brasilia 72125590, Brazil.

Sanitary and Enviromental Engineering Department, Universidade Federal de Santa Catarina, Florianópolis 88040600, Brazil.

出版信息

Int J Environ Res Public Health. 2024 Sep 20;21(9):1248. doi: 10.3390/ijerph21091248.

DOI:10.3390/ijerph21091248
PMID:39338131
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11431699/
Abstract

Conventional temperature-based approaches often overlook the intricate nature of thermal stress experienced by individuals. To address this limitation, climatologists have developed thermal indices-composite measures designed to reflect the complex interaction of meteorological factors influencing human perception of temperature. Our study focuses on Brazil, estimating the association between thermal comfort conditions and mortality related to respiratory and circulatory diseases. We examined four distinct thermal indices: the discomfort index (DI), net effective temperature (NET), humidex (H), and heat index (HI). Analyzing a comprehensive dataset of 2,872,084 deaths from 2003 to 2017, we found significant variation in relative risk (RR) based on health outcomes, exposure lag, percentile of exposure, sex/age groups, and specific thermal indices. For example, under high exposure conditions (99th percentile), we observed that the shorter lags (3, 5, 7, and 10) had the most robust effects on all-cause mortality. For example, under lag 3, the pooled national results for the overall population (all ages and sexes) indicate an increased risk of all-cause mortality, with an RR of 1.17 (95% CI: 1.13; 1.122) for DI, 1.15 (95% CI: 1.12; 1.17) for H, 1.15 (95% CI: 1.09; 1.21) for HI, and 1.18 (95% CI: 1.13; 1.22) for NET. At low exposure levels (1st percentile), all four distinct thermal indices were linked to an increase in all-cause mortality across most sex and age subgroups. Specifically, for lag 20, we observed an estimated RR of 1.19 (95% CI: 1.14; 1.23) for DI, 1.12 (95% CI: 1.08; 1.16) for H, 1.17 (95% CI: 1.12; 1.22) for HI, and 1.18 (95% CI: 1.14; 1.23) for NET. These findings have important implications for policymakers, guiding the development of measures to minimize climate change's impact on public health in Brazil.

摘要

传统的基于温度的方法往往忽略了个体所经历的热应激的复杂性质。为了解决这一局限性,气候学家开发了热指数——综合指标,旨在反映影响人体对温度感知的气象因素的复杂相互作用。我们的研究关注巴西,估计热舒适条件与与呼吸和循环系统疾病相关的死亡率之间的关联。我们研究了四个不同的热指数:不适指数(DI)、有效净温度(NET)、湿球黑球温度(H)和热指数(HI)。我们分析了 2003 年至 2017 年期间 2872084 例死亡的综合数据集,发现健康结果、暴露滞后、暴露百分位数、性别/年龄组和特定热指数的相对风险(RR)存在显著差异。例如,在高暴露条件下(第 99 百分位),我们观察到较短的滞后时间(3、5、7 和 10)对所有原因死亡率的影响最大。例如,在滞后 3 时,全国总人口(所有年龄和性别)的综合结果表明,所有原因死亡率的风险增加,不适指数(DI)的 RR 为 1.17(95%CI:1.13;1.122),湿球黑球温度(H)为 1.15(95%CI:1.12;1.17),热指数(HI)为 1.15(95%CI:1.09;1.21),有效净温度(NET)为 1.18(95%CI:1.13;1.22)。在低暴露水平(第 1 百分位)下,四个不同的热指数都与大多数性别和年龄组的所有原因死亡率增加有关。具体来说,对于滞后 20,我们观察到不适指数(DI)的估计 RR 为 1.19(95%CI:1.14;1.23),湿球黑球温度(H)为 1.12(95%CI:1.08;1.16),热指数(HI)为 1.17(95%CI:1.12;1.22),有效净温度(NET)为 1.18(95%CI:1.14;1.23)。这些发现对决策者具有重要意义,指导制定措施以尽量减少气候变化对巴西公共卫生的影响。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d21/11431699/461156af8200/ijerph-21-01248-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d21/11431699/a33c09457b1a/ijerph-21-01248-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d21/11431699/7fea8bda98fb/ijerph-21-01248-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d21/11431699/0d2ce199bd5a/ijerph-21-01248-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d21/11431699/39cc13dbf738/ijerph-21-01248-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d21/11431699/40a097a04567/ijerph-21-01248-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d21/11431699/e374e799d9f9/ijerph-21-01248-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d21/11431699/461156af8200/ijerph-21-01248-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d21/11431699/a33c09457b1a/ijerph-21-01248-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d21/11431699/7fea8bda98fb/ijerph-21-01248-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d21/11431699/0d2ce199bd5a/ijerph-21-01248-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d21/11431699/39cc13dbf738/ijerph-21-01248-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d21/11431699/40a097a04567/ijerph-21-01248-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d21/11431699/e374e799d9f9/ijerph-21-01248-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d21/11431699/461156af8200/ijerph-21-01248-g007.jpg

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