Arizona State Scientists Build 96%-Accurate Calorie Model, Beating 130-Year-Old Atwater Formula
Updated
Updated · studyfinds.com · May 29
Arizona State Scientists Build 96%-Accurate Calorie Model, Beating 130-Year-Old Atwater Formula
1 articles · Updated · studyfinds.com · May 29
DAMM, a new calorie-absorption model from Arizona State University and AdventHealth, matched measured energy absorption with 96% accuracy in a controlled trial, versus 88% for the Atwater formula used on U.S. nutrition labels.
The model tracks digestion, absorption and microbial metabolism, capturing energy from gut bacteria that Atwater treats as fixed; on a low-fiber Western diet, the older method consistently underestimated absorbed calories.
Data from 17 healthy adults showed Atwater missed by about 22 gCOD per day on average, while DAMM was off by roughly 2.5, after participants completed tightly controlled whole-food and Western diet phases.
Methane-producing microbes also appeared undercounted in stool tests: DAMM initially predicted methane output at least 10 times too low, but improved to a 76% fit when researchers assumed larger biofilm-linked populations near the gut lining.
The findings suggest microbiome differences may help explain why identical diets affect people differently, though the authors say DAMM still needs validation in larger studies and in weight-loss or metabolic-disease settings.
Could hidden gut microbes be the real reason why the same diet affects people so differently?
With food labels underestimating calories, how will this change the billion-dollar weight loss and food industries?
The End of Atwater? DAMM Model and the Microbiome Redefine How We Measure Food Calories
Overview
For over a century, the Atwater system has been the standard for calculating food calories, but modern nutritional science now shows it is outdated. The system was built on direct measurements of energy from food, using calorimetry to estimate average energy values for macronutrients. However, it fails to account for how gut bacteria affect the calories our bodies actually absorb, leading to inaccuracies in calorie labeling. These limitations have important consequences for public health and dietary advice, highlighting the need for more precise models that reflect the real complexity of human digestion and metabolism.