Estimation of ultra-processed food intake and associations with molecular measures in IDATA
Principal Investigator
Name
Erikka Cronin
Degrees
Ph.D., M.P.H.
Institution
NCI
Position Title
Investigator
Email
erikka.loftfield@nih.gov
About this CDAS Project
Study
IDATA
(Learn more about this study)
Project ID
IDATA-96
Initial CDAS Request Approval
Dec 9, 2025
Title
Estimation of ultra-processed food intake and associations with molecular measures in IDATA
Summary
Ultra-processed food intake accounts for a majority calories consumed in the United States and has been associated with obesity, mortality, and several chronic diseases, including certain types of cancer. We previously estimated ultra-processed, processed, and minimally processed food intake using the Nova classification system in 718 IDATA participants with metabolomics data. This project seeks to expand the creation of Nova group and subgroup intake variables to the full IDATA population with dietary data (e.g., ASA24, DHQ, 4DFR) and to explore associations with previously measured recovery biomarkers for dietary intake, blood metabolic and inflammatory markers (e.g., fasting glucose, lipids, IL-6), and the oral microbiome.
Aims
Specific Aim 1: Estimate intake of ultra-processed food (Nova group 4), processed food (Nova group 3), culinary ingredients (Nova group 2) and minimally processed food (Nova group 1) as well as Nova subgroups, in both grams and calories, according to the Nova classification from ASA24, DHQ, and 4DFR.
Specific Aim 2: Evaluate the performance of DHQ using a measurement error model and ASA24 as the reference instrument.
Specific Aim 3: Characterize the relationship between ultra-processed food intake and dietary reference biomarkers for energy, sodium, potassium, and protein.
Specific Aim 4: Characterize the relationship between ultra-processed food intake and blood metabolic and inflammatory markers (e.g., fasting glucose, lipids, IL-6).
Specific Aim 5: Characterize the relationship between ultra-processed food intake and the oral microbiome including alpha and beta diversity.
Collaborators
Erikka Cronin NCI
Emily Vogtmann NCI
Yukiko Yano NCI
Kaelyn Burns NCI
Lisa Kahle IMS