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A multi-country analysis of temperature-mortality associations from a climate change perspective

A multi-country analysis of temperature-mortality associations from a climate change perspective
从气候变化角度对温度与死亡率关联进行多国分析
批准号:
MR/M022625/1
负责人:
Antonio Gasparrini
金额:
$57.77万
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2015
资助国家:
英国
项目状态:
已结题
起止时间:
2015 至 --

项目摘要

项目成果

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中文摘要
翻译
非最佳室外温度是人类健康的已知风险因素,高暴露和低暴露都会增加死亡风险。考虑到平均气温和极端天气事件的预计上升,几项研究试图量化气候变化的相关影响。然而,温度与死亡率之间的关系显示出巨大的地理和时间异质性,这种异质性在很大程度上仍未得到解释,人们对决定人口对温度影响的脆弱性或复原力的因素知之甚少。这些信息对于在气候变化下产生可靠的影响预测以及制定有效的公共卫生政策以减轻健康负担至关重要。该项目旨在通过对温度对具有明显不同特征的人群的死亡率的关联和未来影响的系统评估,来弥补这些研究差距。该项目受益于为此目的收集的最大数据集,包括1972年至2012年期间13个国家384个地点的数据。分析将基于最近为模拟复杂的温度-健康关系而开发的灵活的分析方法。第一次评估将探讨气候、人口、社会经济和基础设施特征在改变温度造成的死亡风险方面的作用。这些信息将用于第二次评估,以预测综合情景下的影响,考虑到长期趋势以及缓解和适应战略的实施可能导致的敏感性变化。该项目将全面描述气温对健康的影响以及相关的气候变化影响,并提供一个平台,以定量评估替代公共卫生政策和适应措施的益处。
英文摘要
Non-optimal outdoor temperature is a known risk factor for human health, with increased mortality risk associated with both high and low exposures. Several studies have attempted to quantify the related impact in a changing climate, considering the predicted increase in average temperature and extreme weather events. However, temperature-mortality associations show a substantial geographical and temporal heterogeneity that is still largely unexplained, and little is known about the factors determining vulnerability or resilience of populations to the effects of temperature. This information is critical to produce reliable impact projections under climate change, and to develop effective public health policies to attenuate the health burden. This project aims to address these research gaps by offering a systematic evaluation of the association and future impact of temperature on mortality across populations with markedly different characteristics. This project benefits from the availability of the largest data set ever collected for this purpose, including data from 384 locations within 13 countries between 1972 and 2012. Analyses will be based on flexible analytical methods recently developed for modelling complex temperature-health relationships. A first assessment will explore the role of climatological, demographic, socio-economic and infrastructural characteristics in modifying the mortality risk of temperature. This information will be used in second assessment to project the impact under composite scenarios accounting for potential changes in susceptibility due to secular trends and implementation of mitigation and adaptation strategies. This project will provide a comprehensive characterization of the health effects of temperature and the related climate change impact, and a platform to quantitatively evaluate the benefits of alternative public health policies and adaptation measures.
期刊论文(10)
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会议论文
DOI: 10.1289/ehp1756
发表时间: 2017-10-27
期刊: Environmental health perspectives
影响因子: 10.4
作者: [Armstrong B, Bell ML, de Sousa Zanotti Stagliorio Coelho M, Leon Guo YL, Guo Y, Goodman P, Hashizume M, Honda Y, Kim H, Lavigne E, Michelozzi P, Hilario Nascimento Saldiva P, Schwartz J, Scortichini M, Sera F, Tobias A, Tong S, Wu CF, Zanobetti A, Zeka A, Gasparrini A]
通讯作者: Gasparrini A
Additional file 1 of Sample size issues in time series regressions of counts on environmental exposures
环境暴露计数时间序列回归中的样本大小问题的附加文件 1
DOI: 10.6084/m9.figshare.11759541
发表时间: 2020
期刊:
影响因子: --
作者: [Armstrong B]
通讯作者: Armstrong B
Additional file 3 of Sample size issues in time series regressions of counts on environmental exposures
环境暴露计数时间序列回归中的样本大小问题的附加文件 3
DOI: 10.6084/m9.figshare.11759553
发表时间: 2020
期刊:
影响因子: --
作者: [Armstrong B]
通讯作者: Armstrong B
Additional file 4 of Sample size issues in time series regressions of counts on environmental exposures
环境暴露计数时间序列回归中的样本大小问题的附加文件 4
DOI: 10.6084/m9.figshare.11759559
发表时间: 2020
期刊:
影响因子: --
作者: [Armstrong B]
通讯作者: Armstrong B
Investigating health risks of environmental stressors in the UK Biobank cohort
Current and future temperature-related mortality and morbidity in the UK: a public health and climate change perspective
Half a degree Additional warming: Prognosis and Projected Impacts on Health (HAPPI-Health)
The case time series design: a new tool for big data analysis
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