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Investigating health risks of environmental stressors in the UK Biobank cohort

Investigating health risks of environmental stressors in the UK Biobank cohort
调查英国生物银行队列中环境压力​​因素的健康风险
批准号:
MR/Y003330/1
负责人:
Antonio Gasparrini
金额:
$104.14万
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2023
资助国家:
英国
项目状态:
未结题
起止时间:
2023 至 --

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中文摘要
翻译
在过去的几十年里,人们对暴露于环境压力源的健康风险进行了广泛的研究。最近的全球评估发现,空气污染和非最佳室外温度这两个最重要的风险因素分别占全球死亡人数的7.6%和9.4%。然而,虽然有证据表明它们与健康风险增加有关,但在知识方面仍然存在重大差距。该项目说明了一个雄心勃勃的研究计划,利用英国生物银行(UKB)调查与环境压力相关的健康风险,这是一项队列研究,预计将有50多万参与者参与。这项研究工作涉及来自伦敦卫生与热带医学学院、美国凯斯西储大学和伦敦帝国理工学院的国际研究人员团队,他们在研究领域具有多学科专业知识和丰富的经验。研究计划分为不同的步骤。首先,研究小组将开发基于机器学习的复杂时空模型,以制作空气污染和温度等环境压力源的高分辨率地图。输出将用于重建每个UKB参与者的详细暴露概况。然后,该小组将开发创新的方法来分析如此丰富的数据集,并评估环境压力因素对健康的影响。这些数据资源和分析方法将用于一系列流行病学研究,这些研究将调查与空气污染和温度有关的一系列不同风险。这些将包括对呼吸事件(如哮喘加重)的短期影响,与心血管结局(如心肌梗死)的长期关联,以及与已有临床状况、药物、生活习惯、社会经济特征和社区特征相关的个体易感性。最后,接触数据将永久地与UKB数据库联系起来,为研究界提供充分记录的资源和易于使用的工具,以解决关于环境压力因素与人类健康之间联系的进一步研究问题。该项目将有助于提高我们对与暴露于环境压力源有关的健康风险的认识,并提高我们对社会经济、生活方式、临床和环境因素决定的个人易感性的理解。向UKB数据库提供详细的暴露信息将为研究人员提供独特的资源,以提高我们对环境、气候和健康之间复杂关系的理解。
英文摘要
Over the past decades, there has been extensive research on the health risks associated with exposure to environmental stressors. Recent global assessments have found that air pollution and non-optimal outdoor temperature, two of the most important risk factors, are responsible for 7.6% and 9.4% of global deaths, respectively. However, while the evidence of their association with increased health risks is established, major gaps in knowledge still remain.This project illustrates an ambitious research programme for investigating health risks associated with environmental stressors using the UK Biobank (UKB), a cohort study that follows prospectively more than half a million participants. The research endeavour involves an international team of researchers from the London School of Hygiene & Tropical Medicine, Case Western Reserve University in the USA, and Imperial College London, with multidisciplinary expertise and established experience in the research area.The research plan is structured in different steps. First, the research team will develop sophisticated spatio-temporal models based on machine learning to produce high-resolution maps of environmental stressors such as air pollution and temperature. The output will be used to reconstruct detailed exposure profiles for each UKB participant. The team will then develop innovative methodologies to analyse such a rich set of data and assess the health impacts of environmental stressors. These data resources and analytical methods will be used in a series of epidemiological studies that will investigate a range of different risks related to air pollution and temperature. These will include short-term effects on respiratory events such as asthma exacerbations, long-term associations with cardiovascular outcomes such as myocardial infarction, and individual susceptibility linked to pre-existing clinical conditions, medications, lifestyle habits, socio-economic characteristics, and neighbourhood features. Finally, the exposure data will be permanently linked to the UKB database, making available to the research community fully documented resources and easy-to-use tools to address further research questions on links between environmental stressors on human health.This project will contribute to advancing our knowledge of the health risks associated with exposure to environmental stressors, and improve our understanding of individual susceptibilities determined by socio-economic, lifestyle, clinical, and contextual factors. The provision of detailed exposure information to the UKB database will provide researchers with unique resources to improve our understanding of the complex relationships between environment, climate, and health.
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会议论文
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
A multi-country analysis of temperature-mortality associations from a climate change perspective
国内基金
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