In recent years, the conversation surrounding processed foods has intensified, driven by mounting public concern about their potential health effects. Despite widespread interest, the scientific community has faced significant challenges in precisely defining which aspects of food processing most directly influence health outcomes. Traditional classification systems have offered broad categories but often lack nuance, making it difficult to provide actionable guidance to consumers and manufacturers alike. Addressing this gap, a team of scientists has unveiled a novel system designed to classify processed foods based on a refined analysis of ingredients with established health impacts.
This breakthrough was spearheaded by WISEcode, an organization known for developing advanced tools like a consumer-facing app that deciphers complex ingredient lists found in packaged foods. The new classification framework aims to bring unprecedented specificity to the evaluation of processed foods, moving beyond the limitations of existing approaches. Dr. Richard Black, the Chief Scientific Officer at WISEcode and adjoint professor at Tufts University, emphasizes that their method introduces a more objective and granular perspective. He explains that this system not only aids consumers in making healthier selections within highly processed categories but also enables manufacturers to benchmark their products more precisely against competitors based on ingredient composition and associated health risks.
Traditionally, the Nova classification system, established in 2009, has been the dominant model in nutrition science to categorize foods based on processing levels. Nova groups foods into four distinct categories, culminating in a notion known as “ultra-processed” foods, which have been epidemiologically linked to heightened risks of obesity, cardiovascular disease, and other chronic illnesses. However, the broad nature of Nova’s ultra-processed category has drawn criticism for lumping nutritionally diverse foods together—for instance, treating a sugary candy bar on par with fortified, sugar-free whole grain cereals. Such generalization obscures meaningful differences in health impact, complicating efforts to formulate precise dietary guidelines.
Dr. Black and his team criticize this “one-size-fits-all” paradigm as insufficient to capture the complexities of contemporary food formulations. They argue that equating all ultra-processed foods under a single risk umbrella ignores the heterogeneity in ingredients and their varied physiological effects. There exists a subset of processed foods that may indeed contribute to adverse health outcomes when consumed over the long term, but other products, similarly labeled by Nova, might play constructive roles in a balanced diet. Recognizing this nuance, the WISEcode classification system endeavors to untangle these disparities by quantifying the health implications of specific ingredients.
The newly developed scoring system incorporates three core components to evaluate processed foods more precisely. First, it assesses individual ingredients, assigning weighted scores reflecting the latest scientific insights into their health risks. This ingredient-level scrutiny allows for a more refined differentiation than broad processing categories alone. Second, the system integrates the proportion of calories derived from added sugars, a well-established marker of dietary quality linked to metabolic and cardiovascular health. Third, it incorporates considerations for ingredients with known health concerns, encompassing emerging evidence about additives and processing agents that may influence long-term outcomes.
Applying this methodology, WISEcode researchers analyzed an extensive food database encompassing over 650,000 products and a comprehensive ingredient catalog exceeding 5,500 items. The comparative analysis with the Nova system yielded remarkable findings: the new system demonstrated finer gradations among foods previously grouped together as ultra-processed. This enhanced resolution reveals critical subtleties in product healthfulness that Nova’s broader framework cannot detect. Conversely, for foods with minimal processing, both systems exhibited similar categorizations, reinforcing the notion that the greatest differentiation is required among highly processed products.
The WISEcode classification scheme categorizes foods across five processing levels: minimal, light, moderate, ultra, and super-ultra. Distribution analyses indicate that foods—whether classified broadly as ultra-processed under Nova or across the entire database—are relatively evenly spread across these gradations, with each category comprising approximately 16 to 23 percent of foods. This balanced dispersion underscores the system’s ability to parse foods in a way that reflects the spectrum of processing intensity and ingredient profiles, thereby offering consumers and producers a more actionable framework.
A pivotal aspect of WISEcode’s innovation lies in its dynamic nature. Dr. Black underscores that this classification model is not a static endpoint but an iterative platform designed to evolve alongside advancements in nutritional science. As novel research elucidates the health effects of specific ingredients or processing techniques, the framework will be updated accordingly. This commitment to continuous refinement ensures that the system remains scientifically credible, transparent, and aligned with the most current evidence, thereby maximizing its utility and trustworthiness.
Beyond consumer guidance and industry benchmarking, the WISEcode system opens new avenues for research. By enabling granular analysis of ingredient occurrences and their combinations within the food supply, scientists are better equipped to investigate the differential health impacts of food components. This capability can facilitate epidemiological and mechanistic studies aimed at identifying which ingredients or combinations thereof are associated with increased or decreased health risks, ultimately informing public health policies and regulatory standards.
The research underpinning this system was scheduled for presentation by Dr. Black at the upcoming NUTRITION 2025 meeting, the premier annual event organized by the American Society for Nutrition. The presentation is set within the Food Science and Nutrition session on June 3rd in Orlando, Florida. Attendees of this session will gain insights into the methodology, validation, and implications of the WISEcode classification system, as well as opportunities to engage with the research team regarding future directions.
It is important to note that, while the preliminary findings showcased at NUTRITION 2025 have been rigorously evaluated by expert committees, they have yet to undergo the peer-review process customary for scientific publications. Consequently, these results should be viewed as an initial step towards evolving understanding rather than definitive conclusions. The scientific community and industry stakeholders will be watching closely as further validation studies and peer-reviewed articles emerge from this research trajectory.
The impetus behind this work reflects a growing consensus that nutrition science must incorporate the complexities of modern food processing. With global dietary patterns increasingly reliant on packaged and processed foods, a more sophisticated understanding of how processing relates to nutrition and health is essential. The WISEcode system represents a milestone in this endeavor, offering a framework that bridges scientific precision with practical application in consumer health and food industry innovation.
In summary, the WISEcode classification system represents an important advancement in the nuanced evaluation of processed foods. By focusing on ingredient-specific health impacts and integrating added sugar content, it transcends existing categorical limitations. Its dynamic, evidence-based approach promises not only to empower consumers with clearer information but also to enhance research capabilities and industry transparency. As the system continues to evolve with emerging scientific knowledge, it stands to reshape how nutrition experts, policymakers, and the public conceptualize and manage the complex landscape of processed foods in the modern diet.
Subject of Research: Development of a nuanced classification system for processed foods based on ingredient-specific health impacts.
Article Title: [Not provided]
News Publication Date: [Not provided]
Web References:
- WISEcode abstract and presentation details at NUTRITION 2025.
References:
- Nova classification system (2009) as the prevailing model for food processing categorization.
Image Credits: [Not provided]
Keywords: Foods, Food additives, Food safety, Food production, Food chemistry, Diets, Nutrition
