COMBATTING DIET RELATED NON-COMMUNICABLE DISEASE THROUGH ENHANCED SURVEILLANCE (CoDiet)
COMBATTING DIET RELATED NON-COMMUNICABLE DISEASE THROUGH ENHANCED SURVEILLANCE (CoDiet)
批准号:
10060437
负责人:
金额:
$454.4万
依托单位:
依托单位国家:
英国
项目类别:
EU-Funded
财政年份:
2023
资助国家:
英国
项目状态:
未结题
起止时间:
2023 至 --
中文摘要
我们目前对饮食与非传染性疾病(NCD)发展之间关系的理解受到许多因素的限制。这些问题包括缺乏对推动非传染性疾病的饮食机制的了解,收集饮食信息的工具不准确,对个性化营养的作用的认识尚不成熟,以及缺乏非传染性疾病往往过高的弱势群体的数据。CoDiet的总体目标是开发一系列工具(通过八个工作包),这些工具将解决我们目前在知识方面的差距,并导致开发一种评估饮食引起的非传染性疾病风险的工具。我们将通过六个目标来实现这一目标,这些目标将回答工作计划的挑战1:开发人工智能驱动的文献检索工具-使人们清楚地了解饮食与非传染性疾病之间的生理和代谢联系领域的大型全球文献2:加强对非传染性疾病风险因素的理解-我们将带来一系列超越技术状态的技术,以获得机制见解3:了解饮食对非传染性疾病风险的个体差异的重要性——这将有助于深入了解膳食非传染性疾病建议的目标4:利用机器学习技术开发一种增强的饮食评估方法——解决缺乏准确饮食工具的营养基本问题5:开发一种增强的饮食-非传染性疾病监测工具——使非传染性疾病因饮食而发生的变化能够在人口水平上得到监测6:在饮食与非传染性疾病风险因素监测和政策之间建立动态接口——确保CoDiet在人口水平上适用。对这些目标的调查及其提供的答案将为在人口水平上加强非传染性疾病保护饮食的吸收开辟一条途径。
英文摘要
Our current understanding of the relationship between diet and the development of non-communicable disease (NCD) is limited by a number of factors. These include a lack of understanding of dietary mechanisms that drive NCD, inaccurate tools to collect dietary information, a nascent understanding of the role of personalised nutrition, and the lack of data in vulnerable groups where NCDs are often over-represented. The overarching aim of CoDiet is to develop a series of tools (through eight work packages) which will address the current gaps in our knowledge and lead to the development of a tool that will assess dietary-induced NCD risk. We will achieve this through the six objectives which will answer the challenges of the work programme 1: Development of AI-driven literature searching tools - bring clear understanding of large global literature in the field of physiological and metabolic links between diet and NCD 2: Enhance the understanding of NCD risk factors - we will bring a series of beyond the state of the technics to gain mechanistic insight 3: Understanding of the importance individual variation in response to diet to risk of NCD - this will give insight into the targeting of dietary NCD advice 4: Develop an enhanced method of dietary assessment using machine learning technologies - solving a fundamental problem in nutrition of lack of an accurate dietary tool 5: Develop an enhance diet-NCD monitoring tool - enabling change in NCD in response to diet to be monitored at the population level 6: Develop a dynamic interface between diet and NCD risk factor monitoring and policy - Ensuring CoDiet is applicable at a population level The investigation of these objectives and the answers they provide will open a pathway to enhancing the uptake of NCD protective diet at a population level.
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