For the first time, researchers can estimate ultra-processed food intake using objective blood and urine markers—no diet diaries required.
NIH scientists have unveiled poly-metabolite scores that signal a breakthrough in nutrition research and open the door to more reliable links between diet and disease.
A New Chapter in Dietary Measurement
In May 2025, the National Institutes of Health (NIH) published a study in PLOS Medicine introducing a novel way to assess consumption of ultra-processed foods.
By identifying metabolite patterns in blood and urine, researchers developed a poly-metabolite score that removes the need for self-reported diet data.
This advancement could transform population health studies and deepen our understanding of nutrition-related diseases.
Why Ultra-Processed Foods Matter
Ultra-processed foods—industrial, ready-to-eat or ready-to-heat products—are typically high in calories, added sugars, and preservatives, yet low in essential nutrients.
These foods have been strongly linked to increased risks of:
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Obesity
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Type 2 diabetes
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Cardiovascular disease
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Certain cancers
Until now, studies exploring these links have relied on food diaries or questionnaires, both of which are prone to bias and misreporting.
Poly-Metabolite Scores: A Scientific Leap Forward
What Are Metabolites?
Metabolites are chemical by-products created when the body processes food. By studying these compounds, scientists can trace patterns that reveal what kinds of foods were consumed—without needing personal accounts.
How the Scores Work
NIH researchers used machine learning to evaluate hundreds of metabolites from:
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A year-long observational study of 718 older U.S. adults
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A tightly controlled feeding trial involving 20 participants
Participants in the clinical trial consumed both a diet made up of 80% ultra-processed foods and a diet containing 0%, in random order. Blood and urine samples were collected for analysis.
Core Findings from the NIH Study
Researchers successfully identified metabolic signatures that correlated with the percentage of ultra-processed food energy in participants’ diets.
These signatures were then converted into poly-metabolite scores.
Accuracy Rates
| Metric | Observed Outcome |
|---|---|
| Differentiation between diet types | High |
| Blood-based score effectiveness | Strong |
| Urine-based score effectiveness | Strong |
| Consistency across individual responses | Reliable |
These scores accurately distinguished between the two dietary phases of each trial subject, affirming their validity as objective biomarkers.
Why This Matters for Public Health
This scoring system provides a scalable, evidence-based method for measuring food intake—critical for large-scale studies. Advantages include:
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Eliminating bias from self-reported data
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Detecting nuanced dietary changes over time
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Applying consistent metrics across diverse populations
As lead researcher Dr. Erikka Loftfield from NIH’s National Cancer Institute noted,
“Metabolomics allows us to improve the way we measure diet, which is central to understanding its role in health.”
Considerations and Future Directions
Limitations of the Study
The participants in this study were mostly older adults from the U.S., which may affect generalizability. Researchers should conduct further studies to validate scores across age groups, ethnic backgrounds, and dietary cultures.
What’s Next?
Researchers plan to refine the poly-metabolite scores and explore how these biomarkers correlate with long-term health risks, particularly:
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Cancer development
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Onset of type 2 diabetes
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Cardiovascular outcomes
Implications for Diet and Disease Research
This study marks a shift toward more precise, science-driven dietary tracking. For public health experts and clinicians, it introduces a new tool for identifying at-risk individuals and understanding how diet affects chronic disease development over time.
Want to Learn More?
NIH’s breakthrough in using poly-metabolite scores offers a compelling new direction for nutritional science. As this research progresses, its impact on healthcare, dietary policy, and personalized nutrition could be profound.
To follow future developments, keep an eye on publications from PLOS Medicine and NIH nutrition research updates.
Sources: National Institutes of Health.
Prepared by Ivan Alexander Golden, Founder of THX News™, an independent news organization delivering timely insights from global official sources. Combines AI-analyzed research with human-edited accuracy and context.
