Data-driven integration of emerging technologies to generate a Standardised and Objective Dietary Intake Assessment Tool

数据驱动的新兴技术集成，生成标准化、客观的膳食摄入评估工具

• 批准号: MR/W028336/1
• 负责人: John Draper
• 金额: $ 323.71万
• 依托单位: Aberystwyth University
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=MR%2FW028336%2F1
• 关键词: Data; driven; integration; emerging; technologies

Nutrition surveys aim to understand how usual diets impact health. The problem with this is that we don't have an accurate tool to assess diet. We rely on people telling us what they have eaten in the last day or month. However, it is difficult to remember what and how much we have eaten. The surveys used also struggle to capture the range of diets in the UK. Often, people we want to talk to about their diets find these methods unsuitable.There are lots of emerging ways in which we can assess diet. We can use urine and finger-prick blood samples to test for 'markers' of food and drinks. The benefit of these is that they give us objective data. We can also use wearable cameras to assess foods and diets. Artificial intelligence software is used to determine the type and amount of food eaten. Additionally, new online tools are making it easier for us to self-report. However, no single tool can accurately measure all aspects of the diet. The aim of this project is to develop a combined tool to accurately assess diet. To do so, we will determine the optimal combination(s) of these emerging methods. The final tool will be easy-to-use and low cost. The combined tool will capture all aspects of the diet.This project involves four expert teams. Our expertise spans each of the emerging tools. This includes nutrition studies, bio-sampling, chemical analysis, wearable camera technology and web-based diet assessment. First, we will assess the performance of each tool in a small group of people (~ 30). Volunteers will attend a clinical unit 2 times for 4 days to eat standard meals. The meals will represent foods eaten in the UK. Blood, urine, self-reported diet, and food images will be captured. This trial will guide the running of a longer remote trial. The larger trial will involve around 120 people and test habitual diet. We will validate the use of the tools in a home setting. The data will then be analysed to identify which food components are measured accurately by each different tool. This will enable us to determine the optimal combination of measurement techniques to enable comprehesive coverage of the UK diet. We will test use of the combined tool in a final remote trial. This study will involve people often excluded from research. For example, we will engage people from disadvantaged backgrounds and minority ethnic groups. This will help us ensure the tool is not only accurate but suitable for the wider UK population. Throughout the project, we will talk to members of the public to ensure the trials are easy to follow. To ensure uptake of the combined tool, we will hold workshops with key stakeholders. This will include representatives of the nutrition research community and government departments.

营养调查的目的是了解日常饮食对健康的影响。这样做的问题是我们没有一个准确的工具来评估饮食。我们依赖于人们告诉我们他们在过去的一天或一个月里吃了什么。然而，我们很难记住我们吃了什么，吃了多少。这些调查也很难捕捉到英国的饮食范围。通常，我们想要谈论他们的饮食的人会发现这些方法是不合适的。我们可以用很多新兴的方法来评估饮食。我们可以用尿液和手指抽血样本来检测食物和饮料的“标记物”。这些方法的好处是它们为我们提供了客观的数据。我们还可以使用可穿戴式相机来评估食物和饮食。人工智能软件被用来确定食物的类型和数量。此外，新的在线工具使我们更容易进行自我报告。然而，没有一个单一的工具可以准确地测量饮食的所有方面。该项目的目的是开发一种组合工具来准确评估饮食。为此，我们将确定这些新兴方法的最佳组合(S)。最终的工具将是易于使用和低成本的。这个组合的工具将捕捉饮食的方方面面。这个项目涉及四个专家团队。我们的专业知识涵盖了每一种新兴工具。这包括营养研究、生物采样、化学分析、可穿戴相机技术和基于网络的饮食评估。首先，我们将在一小群人(~30人)中评估每个工具的性能。志愿者将在一个临床单元就诊2次，为期4天，吃标准的饭菜。这些食物将代表在英国吃过的食物。血液、尿液、自我报告的饮食和食物图像将被捕获。该试验将指导更长时间的远程试验的运行。这项规模更大的试验将涉及约120人，并测试习惯饮食。我们将在家庭环境中验证这些工具的使用。然后将对数据进行分析，以确定每种不同工具准确测量了哪些食物成分。这将使我们能够确定测量技术的最佳组合，从而能够全面覆盖英国的饮食。我们将在最终的远程试验中测试组合工具的使用。这项研究将涉及经常被排除在研究之外的人。例如，我们将吸纳弱势群体和少数民族。这将帮助我们确保该工具不仅准确，而且适用于更广泛的英国人口。在整个项目中，我们将与公众交谈，以确保试验容易进行。为确保采用综合工具，我们将与主要利益攸关方举行研讨会。这将包括营养研究界和政府部门的代表。