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通过开放环境数据平台促进人口健康。

Advancing Population Health Through Open Environmental Data Platforms.

机构信息

Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.

Respiratory Epidemiology and Clinical Research Unit, Research Institute of the McGill University Health Centre, Montréal, QC, Canada.

出版信息

Curr Top Behav Neurosci. 2024;68:297-323. doi: 10.1007/7854_2024_512.


DOI:10.1007/7854_2024_512
PMID:39112811
Abstract

Data stand as the foundation for studying, evaluating, and addressing the multifaceted challenges within environmental health research. This chapter highlights the contributions of the Canadian Urban Environmental Health Research Consortium (CANUE) in generating and democratizing access to environmental exposure data across Canada. Through a consortium-driven approach, CANUE standardizes a variety of datasets - including air quality, greenness, neighborhood characteristics, and weather and climatic factors - into a centralized, analysis-ready, postal code-indexed database. CANUE's mandate extends beyond data integration, encompassing the design and development of environmental health-related web applications, facilitating the linkage of data to a wide range of health databases and sociodemographic data, and providing educational training and events such as webinars, summits, and workshops. The operational and technical aspects of CANUE are explored in this chapter, detailing its human resources, data sources, computational infrastructure, and data management practices. These efforts collectively enhance research capabilities and public awareness, fostering strategic collaboration and generating actionable insights that promote physical and mental health and well-being.

摘要

数据是研究、评估和应对环境健康研究中多方面挑战的基础。本章重点介绍了加拿大城市环境健康研究联盟(CANUE)在加拿大各地生成和普及环境暴露数据方面的贡献。通过联盟驱动的方法,CANUE 将各种数据集(包括空气质量、绿化、邻里特征以及天气和气候因素)标准化为一个集中的、可分析的、邮政编码索引的数据库。CANUE 的任务不仅限于数据集成,还包括设计和开发与环境健康相关的网络应用程序,促进将数据与广泛的健康数据库和社会人口数据进行链接,并提供教育培训和活动,如网络研讨会、峰会和研讨会。本章探讨了 CANUE 的运营和技术方面,详细介绍了其人力资源、数据源、计算基础设施和数据管理实践。这些努力共同增强了研究能力和公众意识,促进了战略合作,并产生了可操作的见解,以促进身心健康和幸福感。

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[2]
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本文引用的文献

[1]
Tree-Based Machine Learning to Identify Predictors of Psoriasis Incidence at the Neighborhood Level: A Populational Study from Quebec, Canada.

Am J Clin Dermatol. 2024-5

[2]
Systemic health effects of noise exposure.

J Toxicol Environ Health B Crit Rev. 2024-1-2

[3]
Impact of ultraviolet radiation on cardiovascular and metabolic disorders: The role of nitric oxide and vitamin D.

Photodermatol Photoimmunol Photomed. 2023-11

[4]
Green space and the health of the older adult during pandemics: a narrative review on the experience of COVID-19.

Front Public Health. 2023

[5]
Comparison of Particulate Air Pollution From Different Emission Sources and Incident Dementia in the US.

JAMA Intern Med. 2023-10-1

[6]
Foundation models for generalist medical artificial intelligence.

Nature. 2023-4

[7]
Particulate matter air pollution and COVID-19 infection, severity, and mortality: A systematic review and meta-analysis.

Sci Total Environ. 2023-7-1

[8]
Impacts of COVID-19 pandemic on environment, society, and food security.

Environ Sci Pollut Res Int. 2023-9

[9]
Food security and food access during the COVID-19 pandemic: Impacts, adaptations, and looking ahead.

JPEN J Parenter Enteral Nutr. 2023-2

[10]
The impact of air pollution on COVID-19 incidence, severity, and mortality: A systematic review of studies in Europe and North America.

Environ Res. 2022-12

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