Ultra-Processed Foods and Continuous Glucose Monitoring Metrics in Adults With Type 2 Diabetes
TL;DR
Higher UPF energy content at the food level was associated with poorer CGM-derived glycemic outcomes, suggesting food-level UPF measures may more closely reflect CGM-derived glycemic metrics than individual-level measures.
Abstract
Aim: We examined associations between ultra-processed foods (UPFs) consumption and continuous glucose monitoring (CGM)-derived metrics using individual- and food-level measures of UPFs in adults with T2D. Methods: Adults with T2D (n=190) completed two 24-hour dietary recalls and wore blinded CGM devices for 14 days. Foods were classified by the NOVA system. Individual-level UPF intake was defined as the proportion of total energy or grams derived from UPFs (energy-weighted). Food-level intake was assessed as Mean UPF Energy (%) and Mean UPF Gram (%) across all reported food items (item-weighted). CGM outcomes included time in range (TIR), time above range (TAR), glucose management indicator (GMI), and coefficient of variation. Multivariable logistic regression models were adjusted for demographic, lifestyle, and clinical factors. Results: After adjustment, higher Mean UPF Energy (%) was associated with lower odds of achieving TIR >70% (OR=0.59, 95% CI: 0.38–0.92) and higher odds of TAR ≥ 25% (OR=1.62, 95% CI: 1.06–2.47) and GMI ≥7% (OR=1.56, 95% CI: 1.03–2.35). Individual-level UPF intake was not significantly associated with CGM-derived outcomes. Conclusions: Higher UPF energy content at the food level was associated with poorer CGM-derived glycemic outcomes. Food-level UPF measures may more closely reflect CGM-derived glycemic metrics than individual-level measures.