Suppr超能文献

极端高温事件的发生频率作为一种替代暴露指标,用于研究气候变化对人类健康的影响。

Frequency of Extreme Heat Event as a Surrogate Exposure Metric for Examining the Human Health Effects of Climate Change.

作者信息

Romeo Upperman Crystal, Parker Jennifer, Jiang Chengsheng, He Xin, Murtugudde Raghuram, Sapkota Amir

机构信息

Maryland Institute for Applied Environmental Health, University of Maryland School of Public Health, College Park, Maryland, United States of America.

Marine Estuarine Environmental Science Program, University of Maryland, College Park, Maryland, United States of America.

出版信息

PLoS One. 2015 Dec 7;10(12):e0144202. doi: 10.1371/journal.pone.0144202. eCollection 2015.

Abstract

Epidemiological investigation of the impact of climate change on human health, particularly chronic diseases, is hindered by the lack of exposure metrics that can be used as a marker of climate change that are compatible with health data. Here, we present a surrogate exposure metric created using a 30-year baseline (1960-1989) that allows users to quantify long-term changes in exposure to frequency of extreme heat events with near unabridged spatial coverage in a scale that is compatible with national/state health outcome data. We evaluate the exposure metric by decade, seasonality, area of the country, and its ability to capture long-term changes in weather (climate), including natural climate modes. Our findings show that this generic exposure metric is potentially useful to monitor trends in the frequency of extreme heat events across varying regions because it captures long-term changes; is sensitive to the natural climate modes (ENSO events); responds well to spatial variability, and; is amenable to spatial/temporal aggregation, making it useful for epidemiological studies.

摘要

气候变化对人类健康,尤其是慢性病的影响的流行病学调查,因缺乏可作为与健康数据兼容的气候变化标志物的暴露指标而受阻。在此,我们提出一种使用30年基线(1960 - 1989年)创建的替代暴露指标,该指标允许用户在与国家/州健康结果数据兼容的尺度上,以近乎完整的空间覆盖范围量化暴露于极端高温事件频率的长期变化。我们按十年、季节、国家区域以及其捕捉天气(气候)长期变化(包括自然气候模式)的能力来评估该暴露指标。我们的研究结果表明,这种通用暴露指标对于监测不同地区极端高温事件频率的趋势可能有用,因为它能捕捉长期变化;对自然气候模式(厄尔尼诺 - 南方涛动事件)敏感;对空间变异性反应良好,并且;适合进行空间/时间汇总,使其对流行病学研究有用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d633/4671592/4061fcf8f005/pone.0144202.g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验