Heat health assessment and risk simulation prediction in eastern China: a geospatial analysis.

IF 3.4 3区 医学 Q2 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH Frontiers in Public Health Pub Date : 2025-03-07 eCollection Date: 2025-01-01 DOI:10.3389/fpubh.2025.1521997
Ming Li, Jiaying Xu
{"title":"Heat health assessment and risk simulation prediction in eastern China: a geospatial analysis.","authors":"Ming Li, Jiaying Xu","doi":"10.3389/fpubh.2025.1521997","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>High temperatures pose significant health risks and societal challenges in China, with spatial variations in heat health risks. Furthermore, due to the constraint imposed by heat health risk assessment on the construction of the public health security framework, it is necessary to explore the heat health risk pattern of spatial distribution and the trend of future risk development in eastern China.</p><p><strong>Methods: </strong>Based on the Intergovernmental Panel on Climate Change (IPCC) and Risk Triangle framework which is combined with natural and socio-economic factors, the heat health risk assessment index system of eastern China is established in this paper. This paper enhances the accuracy of risk maps with the aid of high-resolution imagery. It also focuses specifically on the exposure of construction workers in urban areas and agricultural workers in rural areas. This paper also evaluates the heat health risk of eastern China from 2010 to 2019 by using ArcGIS and the CA-Markov model.</p><p><strong>Results: </strong>The heat health risk in most areas of eastern China is predominantly highest risk, with the proportion of highest and medium risk areas increasing steadily from 2010 to 2019. The spatial distribution pattern reveals that high-risk areas are concentrated in the central urban areas, while low-risk areas are primarily in the mountainous regions, suburbs, rural areas, and water source areas. The conversion of heat health risk areas mainly occurs between adjacent levels, with no mutation process. From 2010 to 2025, the heat health risk of eastern China has been improving, and the overall distribution pattern of risk levels remains consistent.</p><p><strong>Conclusion: </strong>The research findings provide a basis for us to gain a deeper understanding of the vulnerability of different groups. This study not only presents spatial distribution maps of health risks, but offers a new perspective for us to comprehend the complexity and diversity of these risks. The research findings also establish a foundation for optimizing monitoring and warning systems. Furthermore, this study provides scientific evidence for policymakers to develop comprehensive heatwave mitigation plans. Nevertheless, we must acknowledge the limitations of the research and recognize that there is room for improvement in the future.</p>","PeriodicalId":12548,"journal":{"name":"Frontiers in Public Health","volume":"13 ","pages":"1521997"},"PeriodicalIF":3.4000,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11925918/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers in Public Health","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.3389/fpubh.2025.1521997","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH","Score":null,"Total":0}
引用次数: 0

Abstract

Background: High temperatures pose significant health risks and societal challenges in China, with spatial variations in heat health risks. Furthermore, due to the constraint imposed by heat health risk assessment on the construction of the public health security framework, it is necessary to explore the heat health risk pattern of spatial distribution and the trend of future risk development in eastern China.

Methods: Based on the Intergovernmental Panel on Climate Change (IPCC) and Risk Triangle framework which is combined with natural and socio-economic factors, the heat health risk assessment index system of eastern China is established in this paper. This paper enhances the accuracy of risk maps with the aid of high-resolution imagery. It also focuses specifically on the exposure of construction workers in urban areas and agricultural workers in rural areas. This paper also evaluates the heat health risk of eastern China from 2010 to 2019 by using ArcGIS and the CA-Markov model.

Results: The heat health risk in most areas of eastern China is predominantly highest risk, with the proportion of highest and medium risk areas increasing steadily from 2010 to 2019. The spatial distribution pattern reveals that high-risk areas are concentrated in the central urban areas, while low-risk areas are primarily in the mountainous regions, suburbs, rural areas, and water source areas. The conversion of heat health risk areas mainly occurs between adjacent levels, with no mutation process. From 2010 to 2025, the heat health risk of eastern China has been improving, and the overall distribution pattern of risk levels remains consistent.

Conclusion: The research findings provide a basis for us to gain a deeper understanding of the vulnerability of different groups. This study not only presents spatial distribution maps of health risks, but offers a new perspective for us to comprehend the complexity and diversity of these risks. The research findings also establish a foundation for optimizing monitoring and warning systems. Furthermore, this study provides scientific evidence for policymakers to develop comprehensive heatwave mitigation plans. Nevertheless, we must acknowledge the limitations of the research and recognize that there is room for improvement in the future.

Abstract Image

Abstract Image

Abstract Image

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
中国东部地区热健康评估和风险模拟预测:地理空间分析。
背景:高温给中国带来了重大的健康风险和社会挑战,且热健康风险存在空间差异。此外,由于热健康风险评价对公共卫生安全框架构建的约束,有必要探讨中国东部地区热健康风险空间分布格局和未来风险发展趋势。方法:基于政府间气候变化专门委员会(IPCC)和风险三角框架,结合自然因素和社会经济因素,建立中国东部地区热健康风险评价指标体系。本文利用高分辨率图像提高了风险图的精度。它还特别侧重于城市地区的建筑工人和农村地区的农业工人的接触情况。利用ArcGIS和CA-Markov模型对2010 - 2019年中国东部地区的热健康风险进行了评价。结果:2010 - 2019年,中国东部大部分地区的热健康风险以高风险区为主,高风险区和中风险区所占比例稳步上升。空间分布格局显示,高风险区主要集中在中心城区,低风险区主要分布在山区、郊区、农村和水源地。热健康危险区的转换主要发生在相邻层之间,不存在突变过程。2010 - 2025年,东部地区热健康风险总体呈改善趋势,风险等级分布格局保持一致。结论:研究结果为我们更深入地了解不同群体的脆弱性提供了依据。本研究不仅提供了健康风险的空间分布图,而且为我们理解这些风险的复杂性和多样性提供了一个新的视角。研究结果也为优化监测预警系统奠定了基础。此外,本研究为决策者制定全面的热浪缓解计划提供了科学依据。然而,我们必须承认研究的局限性,并认识到未来还有改进的余地。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Frontiers in Public Health
Frontiers in Public Health Medicine-Public Health, Environmental and Occupational Health
CiteScore
4.80
自引率
7.70%
发文量
4469
审稿时长
14 weeks
期刊介绍: Frontiers in Public Health is a multidisciplinary open-access journal which publishes rigorously peer-reviewed research and is at the forefront of disseminating and communicating scientific knowledge and impactful discoveries to researchers, academics, clinicians, policy makers and the public worldwide. The journal aims at overcoming current fragmentation in research and publication, promoting consistency in pursuing relevant scientific themes, and supporting finding dissemination and translation into practice. Frontiers in Public Health is organized into Specialty Sections that cover different areas of research in the field. Please refer to the author guidelines for details on article types and the submission process.
期刊最新文献
Comparative study: mapping treatment costs, best practices, and challenges across Africa. Socioeconomic disparities and its association with food security, diet quality, and growth among Malaysian children aged 6 months to 12.9 years. Dilemmas in the usage of community-based home care and smart home care services for older adults among family caregivers of older adults with mild cognitive impairment (MCI): a qualitative study. Environmental determinants of cerebral haemorrhage in older adults: behavioural pathways and population health implications. PRAYAS: individual patient data meta-analysis database for Pooled Research and Analysis for Yielding Anemia-free Solutions in India.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1