Scientists at VTC’s Fralin Biomedical Research Institute who study ultra-processed foods have created a new tool to evaluate the rewarding and strengthening properties of foods that make up 58 percent of the calories consumed in the United States. Foods have been linked to a wide range of negative health outcomes.
The research, which was published in April in the journal Appetiteprovides a collection of carefully curated images of minimally and ultra-processed foods that combine 26 characteristics, including macronutrients, sodium, dietary fiber, calories, price, and visual characteristics such as color and serving size.
The work was based on the NOVA classification system (“nova” means new in Portuguese) which groups foods into four categories according to their level of processing. Nutrition researchers at the University of São Paulo in Brazil developed the scale while studying the sharp rise in obesity rates in the country.
The scale has its detractors.
“One of the main criticisms of the NOVA scale is that it is difficult to use or that people rate foods differently,” said Alexandra DiFeliceantonio, corresponding author and assistant professor at the Fralin Biomedical Research Institute. “We found that people with nutrition education generally agreed with the food classifications, which provides some data that might not be valid criticism.”
What did you do
The NOVA system assigns foods to four categories: unprocessed or minimally processed, such as fresh fruit, legumes or plain yogurt; processed culinary ingredients, such as cooking oils, butter and salt; processed foods, which combine the previous two through simple methods such as cheese, canned vegetables or freshly baked bread; and ultra-processed foods, such as soft drinks, flavored yogurts, processed meat, and most packaged breads, made through industrial processing and additives rarely found in the home pantry.
To develop the image set, a team of psychologists, neuroscientists, and registered dietitians selected foods that represented minimally or ultra-processed foods.
The foods were prepared in a laboratory, visually represented using professional photographs, and checked for consistency. The researchers also collected prices, food weights, and nutritional information (calories, macronutrients, sodium, and dietary fiber) for the foods in each image.
Study participants rated the images on a variety of qualities to generate a final set of 28 images that matched 26 characteristics. To objectively measure NOVA classification, researchers recruited 67 nutrition professionals and asked them to classify foods as minimally or ultra-processed.
“With this set of food images we can begin to infer that any differences between the food images are due to the degree of processing of the food, and not all of these other factors that we know have a potential impact,” said Zach Hutelin, lead author of the study and Fralin Biomedical Research Institute graduate student pursuing a PhD in translational biology, medicine and health. program.
Why this matters
Ultra-processed foods are linked to an increased risk of developing obesity, type 2 diabetes, heart disease and cancer. They account for more than half of the calories consumed in the United States, Canada and the United Kingdom and have been identified as a global threat to public health.
“There is very little experimental research on ultra-processed foods, and part of what has been holding us back is better tools to measure and evaluate their effects,” said DiFeliceantonio, who is also associate director of the Center for Health Behaviors at the Fralin Biomedical Research Institute. . Investigation. “The more tools we can provide, the more we can learn.”
The Virginia Tech team is making the images and associated data accessible through the Virginia Tech University Libraries’ Virginia Tech Data Repository. This will allow scientists to test hypotheses in neuroimaging and behavioral economics studies.
In DiFeliceantonio’s lab, photographs are used with fMRI to reveal associated brain activity, and the images isolate the effects of food processing from other characteristics.
The study was funded by a graduate research fellowship from the National Science Foundation, the National Institute of Diabetes and Digestive and Kidney Diseases of the National Institutes of Health, and a grant from the Seale Innovation Fund, which supports pilot research projects. innovators at Fralin Biomedical Research. Institute. DiFeliceantonio received a grant from the fund to investigate metabolic, neural, and behavioral data to better understand how our brain processes nutrient availability and food preference.