Enhancing the accuracy of dietary assessment
Modern medical technology can do a lot. It can track the way we move, analyse our genetic composition, even predict the likelihood of developing certain diseases. But one thing it cannot do is accurately assess what we eat. In fact, the difficulty of accurately assessing dietary intake is one of the major roadblocks to being able to assess the link between diet and metabolic health or disease. “Current approaches to assessing dietary intake have a number of well-documented limitations,” says Lorraine Brennan, a professor of Human Nutrition at University College Dublin. “For example, people have difficulty accurately recalling what they ate and estimating correct portion sizes.” With the support of the EU-funded A-DIET project, Brennan and her colleagues aim to overcome these limitations by developing new strategies for enhancing the accuracy of dietary assessment. “Being able to accurately assess what people are actually eating – as opposed to what they say they are eating – could prove vital to understanding how diet impacts disease development,” adds Brennan.
Objective measures of dietary intake
At the heart of this European Research Council supported project is a nutritype, a rather novel concept used to express dietary intake via a metabolomics profile. As Brennan explains, metabolomics is the study of small molecules called metabolites that can be derived from our foods and are intermediates and products of cell metabolism. These metabolites can be biomarkers of diet. “This approach was chosen because it offers the possibility of getting objective measures of dietary intake,” explains Brennan. For instance, prior research demonstrated that urinary biomarkers can be used to estimate specific foods people are eating, such as citrus fruits, apples or chicken. “Building on this, we developed a model that lets us classify people into dietary patterns using only urinary biomarker data,” adds Brennan. “This removes the need for self-reported dietary data – a major roadblock to accurately assessing dietary intake.”
Overcoming obstacles
This is just one example of how the project used biomarkers to assess food intake. Other examples include developing approaches and tools to combine dietary data with self-reported data, thus correcting the self-reported data for errors. “By advancing the use of biomarkers as a means of assessing what people are eating, our research laid the foundation to the future development of biomarker-based approaches,” she remarks. Needless to say, achieving these results during the COVID-19 pandemic was anything but easy. “Overnight we had to close our lab, stop our experiments and work from home,” recalls Brennan. “It was a major and stressful upheaval to our progress, one that required us to readjust our focus to concentrate more on data analysis and manuscript writing.” Yet despite this setback, the project still succeeded at making significant advancements in the field. According to Brennan, this was the result of having a motivated, multidisciplinary team. “I am very proud of how, as a team of nutritionists, food scientists, analytical chemists, and statisticians, we were able to work together – even when doing so remotely – to develop new approaches for assessing what people are eating,” she says. Researchers are currently putting some of the biomarker-based approaches developed during the A-DIET project into action to study the relationship between diet and disease.
Keywords
A-DIET, dietary assessment, biomarkers, diet, disease, dietary intake, health, nutrition, nutritype, metabolic
