Active Psychology & Behaviour Public Health & Healthcare

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

In plain English

AI plain-English summary

Every time someone fills out a food diary or recalls what they ate yesterday, the data is flawed—people forget, misjudge portions, or skip details. This project aims to replace those unreliable self-reports with a single, objective tool that combines urine and blood tests, wearable cameras, and online questionnaires to measure what people actually eat. The problem is that current diet surveys cannot accurately capture the full range of UK diets, especially among groups often excluded from research, such as people from disadvantaged backgrounds or minority ethnic groups. Without accurate intake data, researchers cannot link diet to health outcomes with confidence. If successful, the tool will give nutrition scientists and government departments a low-cost, standardised way to assess diet objectively. This could improve the quality of large-scale nutrition surveys that underpin public health policy—from dietary guidelines to food fortification programmes. The tool will be tested in a small clinical trial (30 people) and a larger home-based trial (120 people), with final validation in groups typically left out of research.

View original technical description
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.

View the original record at the funder ↗

Researchers

Albert Koulman (Co-Investigator)Benny Lo (Co-Investigator)Faustina Hwang (Co-Investigator)Gary Frost (Co-Investigator)John Draper (Principal Investigator)Julie Lovegrove (Co-Investigator)Manfred Beckmann (Principal Investigator)Rosalind Fallaize (Co-Investigator)

Related Research

Grants with similar aims, by meaning.

A UK on-line 24h dietary recall tool for population studies: development, validation and practical application
MICA: Partnership for Improvement and Innovation in Dietary Assessment Technology (PIIDAT)
SoDIAT study: Data-driven integration of emerging technologies to generate a Standardized and Objective Dietary Intake Assessment Tool
Making the best use of new technologies in the National Diet and Nutrition Survey: A Review
Modelling individual responses to healthier diets: new ways to quantify the importance of physiology and behaviour for successful dietary changes

Original classification

Research Grant

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