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COMBATTING DIET RELATED NON-COMMUNICABLE DISEASE THROUGH ENHANCED SURVEILLANCE

COMBATTING DIET RELATED NON-COMMUNICABLE DISEASE THROUGH ENHANCED SURVEILLANCE
通过加强监测来对抗与饮食相关的非传染性疾病
批准号:
10058081
负责人:
金额:
$27.35万
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 --

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中文摘要
翻译
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。这些问题包括对导致非传染性疾病的饮食机制缺乏了解,收集饮食信息的工具不准确,对个性化营养作用的认识尚处于起步阶段,以及缺乏非传染性疾病往往过多的弱势群体的数据。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的知识差距,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-清楚地了解饮食和NCD之间生理和代谢联系领域的大型全球文献2:加强对NCD风险因素的理解-我们将带来一系列超越技术状态的技术,以获得机械见解3:了解个体差异对饮食对NCD风险的重要性-这将深入了解饮食NCD建议的目标4:使用机器学习技术开发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:开发一个强化的饮食-非传染性疾病监测工具-使非传染性疾病的变化能够在人群层面上对饮食作出反应,以进行监测6:在饮食和非传染性疾病风险因素监测与政策之间建立动态接口-对这些目标及其提供的答案的调查将为在人口水平上加强非传染性疾病保护性饮食的摄入开辟一条途径
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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