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3
The Impact of Extreme Heat Exposure on Pregnant People and Neonates: A State of the Science Review.极端高温暴露对孕妇和新生儿的影响:科学综述。
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A Multistate Study on Housing Factors Influential to Heat-Related Illness in the United States.一项有关影响美国热相关疾病的住房因素的多州研究。
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How humans adapt to hot climates learned from the recent research on tropical indigenes.人类如何适应炎热气候,可以从最近对热带土着居民的研究中了解到。
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9
Assessment of Regional Health Vulnerability to Extreme Heat - China, 2019.2019年中国区域对极端高温的健康脆弱性评估
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10
Heat waves: a hot topic in climate change research.热浪:气候变化研究中的一个热门话题。
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应用主成分分析法(PCA)评估雪兰莪谷弱势群体在室内环境中受热压力的影响因素。

Assessment of heat stress contributing factors in the indoor environment among vulnerable populations in Klang Valley using principal component analysis (PCA).

机构信息

Department of Environmental and Occupational Health, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, Serdang, Selangor, Malaysia.

Department of Environmental Engineering, Faculty of Engineering and Green Technology (FEGT), Universiti Tunku Abdul Rahman, Kampar, Perak, Malaysia.

出版信息

Sci Rep. 2024 Jul 15;14(1):16265. doi: 10.1038/s41598-024-67110-w.

DOI:10.1038/s41598-024-67110-w
PMID:39009671
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11251149/
Abstract

Rising global temperatures can lead to heat waves, which in turn can pose health risks to the community. However, a notable gap remains in highlighting the primary contributing factors that amplify heat-health risk among vulnerable populations. This study aims to evaluate the precedence of heat stress contributing factors in urban and rural vulnerable populations living in hot and humid tropical regions. A comparative cross-sectional study was conducted, involving 108 respondents from urban and rural areas in Klang Valley, Malaysia, using a face-to-face interview and a validated questionnaire. Data was analyzed using the principal component analysis, categorizing factors into exposure, sensitivity, and adaptive capacity indicators. In urban areas, five principal components (PCs) explained 64.3% of variability, with primary factors being sensitivity (health morbidity, medicine intake, increased age), adaptive capacity (outdoor occupation type, lack of ceiling, longer residency duration), and exposure (lower ceiling height, increased building age). In rural, five PCs explained 71.5% of variability, with primary factors being exposure (lack of ceiling, high thermal conductivity roof material, increased building age, shorter residency duration), sensitivity (health morbidity, medicine intake, increased age), and adaptive capacity (female, non-smoking, higher BMI). The order of heat-health vulnerability indicators was sensitivity > adaptive capacity > exposure for urban areas, and exposure > sensitivity > adaptive capacity for rural areas. This study demonstrated a different pattern of leading contributors to heat stress between urban and rural vulnerable populations.

摘要

全球气温上升会导致热浪,进而给社区带来健康风险。然而,在强调加剧脆弱人群热健康风险的主要因素方面,仍存在明显差距。本研究旨在评估生活在炎热潮湿的热带地区的城市和农村脆弱人群中热应激因素的优先顺序。采用面对面访谈和经过验证的问卷,对马来西亚雪兰莪州巴生谷的 108 名城市和农村居民进行了一项比较性横断面研究。使用主成分分析对数据进行分析,将因素分为暴露、敏感性和适应能力指标。在城市地区,五个主成分(PCs)解释了 64.3%的变异性,主要因素是敏感性(健康发病率、药物摄入、年龄增长)、适应能力(户外职业类型、无天花板、居住时间延长)和暴露(较低的天花板高度、建筑物较老)。在农村地区,五个 PCs 解释了 71.5%的变异性,主要因素是暴露(无天花板、热导率高的屋顶材料、建筑物较老、居住时间较短)、敏感性(健康发病率、药物摄入、年龄增长)和适应能力(女性、不吸烟、更高的 BMI)。城市地区的热健康脆弱性指标的顺序是敏感性>适应能力>暴露,而农村地区的顺序是暴露>敏感性>适应能力。本研究表明,城市和农村脆弱人群中导致热应激的主要因素存在不同的模式。