Abstract

Introduction: There is limited research examining dietary changes in adults with prediabetes who are following a diet personalized to predict postprandial glycemic response (PPGR). Objective: We compared dietary changes in subjects randomized to a low-fat, one-size-fits-all diet ( Standardized ) or to a diet personalized to minimize PPGR ( Personalized ). Methods: Dietary data collected to-date were analyzed from the Personal Diet study, a clinical trial to compare two behavioral weight loss interventions in adults with prediabetes or early-stage type 2 diabetes. All subjects had resting energy expenditure (REE) measured at baseline using indirect calorimetry. Both arms were instructed to restrict energy intake (-500 kcal/day, based on REE and a physical activity factor of 1.4), log daily dietary intake with a smartphone app, and attend scheduled behavioral counseling sessions. The Standardized arm received app feedback about energy and fat intake, while the Personalized arm received app feedback about energy intake and meal specific predicted PPGR determined from a gut microbiome-based machine learning algorithm. At baseline, 3 months, and 6 months, subjects completed one 24-hour dietary recall using the Automated Self-Administered 24-hour Dietary Assessment Tool. Total energy, total carbohydrate, total sugars, fiber, total fat, saturated fat, monounsaturated fat, polyunsaturated fat, and protein were measured using the USDA Food and Nutrient Database for Dietary Studies 2011-2012. Macronutrient intakes were analyzed as percentage of energy (%E). Linear mixed modelling, with random intercepts and slopes and an unstructured covariance pattern, was used to analyze dietary changes within- and between-arms from baseline to 3 and 6 months. Fixed effects were included for study arm, time period, and interaction of study arm and time period. A random effect was included for subjects. Models were adjusted for age and sex. Results: Dietary assessments were completed at baseline (n=66 Personalized ; n=65 Standardized ), 3 months (n=50 Personalized ; n=36 Standardized ), and 6 months (n=47 Personalized ; n=39 Standardized ). The Personalized arm had a greater reduction than the Standardized arm in energy (β: -342 kcal; 95% CI: -672, -12) and %E from carbohydrate (β: -6.2; 95% CI: -11.7, -0.6) and sugars (β: -4.9; 95% CI: -8.8, -1.0) from baseline to 3 months, but there were no between-arm differences in dietary measures at 6 months. Within-arm, Personalized had decreases in energy (β: -327 kcal; 95% CI: -546, -108) and %E from carbohydrate (β: -4.6; 95% CI: -8.2, -0.9) from baseline to 3 months. In the Standardized arm, %E from sugars increased from baseline to 3 months (β: 3.0; 95% CI: 0.02, 5.9). Conclusions: Personalized had greater reductions than Standardized in energy and %E from carbohydrate and sugars over the first 3 months of the intervention, but dietary changes were similar by 6 months.

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