Estimating the intake of moderation foods and evaluating associations with risk of cancer and mortality
Principal Investigator
Name
Kaelyn Burns
Degrees
Ph.D., M.S.
Institution
National Cancer Institute
Position Title
Postdoctoral Fellow
Email
kaelyn.burns@nih.gov
About this CDAS Project
Study
PLCO
(Learn more about this study)
Project ID
PLCO-2045
Initial CDAS Request Approval
May 4, 2026
Title
Estimating the intake of moderation foods and evaluating associations with risk of cancer and mortality
Summary
Ultra-processed foods (UPF) are defined by the Nova classification system, which classifies foods by their extent and purpose of industrial processing [1]. Current evidence for the association between UPF and cancer risk is weak, with inconsistency across studies [2]. Potentially contributing to this inconsistency is that Nova is agnostic to the nutrient content of foods, resulting in a heterogenous mix of foods with various nutrient profiles. For example, some UPF are nutrient-poor and high in sugar, fat, and sodium while others are nutrient-dense and may be low in sugar, fat, and sodium such as unsweetened whole grain cereal and fruited yogurt [3,4].
Conversely, the moderation food classification system is a novel method that classifies foods and beverages based on the amount of added sugar, saturated fat, sodium, and refined grains in the item [5]. These are dietary components that should be limited according to the Dietary Guidelines for Americans due to associations between overconsumption of these nutrients with adverse health outcomes. Associations between moderation food intake and cancer risk have not been evaluated.
References
1. Monteiro CA, Cannon G, Levy RB, et al. Ultra-processed foods: what they are and how to identify them. Public Health Nutr. Apr 2019;22(5):936–941. doi:10.1017/S1368980018003762
2. Lane MM, Gamage E, Du S, et al. Ultra-processed food exposure and adverse health outcomes: umbrella review of epidemiological meta-analyses. BMJ. Feb 28 2024;384:e077310. doi:10.1136/bmj-2023-077310
3. Poti JM, Mendez MA, Ng SW, Popkin BM. Is the degree of food processing and convenience linked with the nutritional quality of foods purchased by US households? Am J Clin Nutr. Jun 2015;101(6):1251–62. doi:10.3945/ajcn.114.100925
4. Hess JM, Comeau ME, Casperson S, et al. Dietary Guidelines Meet NOVA: Developing a Menu for A Healthy Dietary Pattern Using Ultra-Processed Foods. J Nutr. Aug 2023;153(8):2472–2481. doi:10.1016/j.tjnut.2023.06.028
5. Channell Doig AJ, Lipsky LM, Choe A, Nansel TR. Development and evaluation of a nutrient-based method of classifying moderation foods. medRxiv. 2025:2025.03.20.25324317. doi:10.1101/2025.03.20.25324317
Aims
Aim 1: Estimate the intake of moderation foods and non-moderation foods, in grams and calories, using food-code level data from the DHQ.
Aim 2: Evaluate associations between moderation food and non-moderation food intake with all-cause and cause-specific mortality risk.
Cox proportional hazards models will be used to estimate hazards ratios (HRs) and 95% confidence intervals for moderation food intake with all-cause and cause-specific mortality risk. The model will use age as the underlying time metric and will be adjusted for potential confounders, including sex, race/ethnicity, smoking status, and physical activity.
Aim 3: Evaluate associations between moderation food and non-moderation food intake with overall cancer and cancer-specific risk.
Cox proportional hazards models will be used to estimate hazards ratios (HRs) and 95% confidence intervals for moderation food intake with overall cancer and cancer-specific risk.
Collaborators
Lisa Kahle IMS
Kaelyn Burns National Cancer Institute
Emily Vogtmann National Cancer Institute
Erikka Loftfield National Cancer Institute