(P17-014-25) Associations of the Discretionary Food Score With Cardiometabolic Risk Factors in a Representative Sample of U.S. Adults

Objectives: To examine associations of a novel measure of discretionary food intake with cardiometabolic risk factors.

Methods: This study used cross-sectional data from adults ≥20 years (n=6576) in the NHANES 2017-2020 pre-pandemic data, including dietary recalls, anthropometrics, and biomarkers. Foods meeting any of the following criteria were classified as discretionary: added sugar >20% of energy; sodium >460mg per serving; refined grain >50% of total grains and >10:1 carbohydrate: fiber ratio; saturated fat >20% of energy (excluding vegetables); and total fat >9% by weight (applied only to vegetables, sweets, and snacks), and all alcoholic beverages. A Discretionary Food Score was calculated as the percent of total energy intake across all recalls from foods meeting the above criteria. Separate linear regression models examined associations of the Discretionary Food Score with BMI, waist circumference, blood pressure (SBP, DBP), total cholesterol (TC), low-density lipoprotein (LDL), triglycerides (TG), high density lipoprotein (HDL), glycohemoglobin (A1C), fasting glucose, insulin, and c-reactive protein (CRP). Models adjusted for age, sex, race/ethnicity, physical activity metabolic equivalents, and supplement use.

Results: Mean Discretionary Food Score was 75% (SE: 0.52) of total energy. The Discretionary Food Score was positively associated with BMI (B=0.04, p< 0.001), waist circumference (B=0.11, p< 0.001), CRP (B=0.04, p=0.003), insulin (B=0.07, p=0.018), TG (B=0.30, p=0.014), DBP (B=0.05, p=0.002) and SBP (B=0.05, p=0.01). The Discretionary Food Score was negatively associated with HDL (B=-0.04, p=0.02) and was not associated with TC, LDL, A1C, or fasting glucose.

Conclusions: A higher Discretionary Food Score, reflecting percent of energy from discretionary foods, is consistently associated with worse cardiometabolic risk factors in U.S. adults and may represent a useful behavioral target for nutrition interventions.

Funding Sources: This research was supported in part by the Intramural Research Program of the Eunice Kennedy Shriver National Institute of Child Health and Human Development.