Texture-based differences in eating rate influence energy intake for minimally processed and ultra-processed meals.

BACKGROUND: Consumption of ultra-processed foods has been linked with higher energy intakes. Food texture is known to influence eating rate (ER) and energy intake to satiation, yet it remains unclear whether food texture influences energy intakes from minimally processed and ultra-processed meals. OBJECTIVES: We examined the independent and combined effects of food texture and degree of processing on ad libitum food intake. We also investigated whether differences in energy intake during lunch influenced postmeal feelings of satiety and later food intake. METHODS: In this crossover study, 50 healthy-weight participants [n = 50 (24 men); mean ± SD age: 24.4 ± 3.1 y; BMI: 21.3 ± 1.9 kg/m2] consumed 4 ad libitum lunch meals consisting of "soft minimally processed," "hard minimally processed," "soft ultra-processed," and "hard ultra-processed" components. Meals were matched for total energy served, with some variation in meal energy density (±0.20 kcal/g). Ad libitum food intake (kcal and g) was measured and ER derived using behavioral coding of videos. Subsequent food intake was self-reported by food diary. RESULTS: There was a main effect of food texture on intake, whereby "hard minimally processed" and "hard ultra-processed" meals were consumed slower overall, produced a 21% and 26% reduction in food weight (g) and energy (kcal) consumed, respectively. Intakes were higher for "soft ultra-processed" and "soft minimally processed" meals (P < 0.001), after correcting for meal pleasantness. The effect of texture on food weight consumed was not influenced by processing levels (weight of food: texture*processing-effect, P = 0.376), but the effect of food texture on energy intake was (energy consumed: texture*processing-effect, P = 0.015). The least energy was consumed from the "hard minimally processed" meal (482.9 kcal; 95% CI: 431.9, 531.0 kcal) and the most from the "soft ultra-processed" meal (789.4 kcal; 95% CI: 725.9, 852.8 kcal; Δ=↓∼300 kcal). Energy intake was lowest when harder texture was combined with the "minimally processed" meals. Total energy intake across the day varied directly with energy intakes of the test meals (Δ15%, P < 0.001). CONCLUSIONS: Findings suggest that food texture-based differences in ER and meal energy density contribute to observed differences in energy intake between minimally processed and ultra-processed meals.This trial was registered at clinicaltrials.gov as NCT04589221.

Increased oral processing and a slower eating rate increase glycaemic, insulin and satiety responses to a mixed meal tolerance test.

PURPOSE: Variations in specific oral processing behaviours may contribute to differences in glucose, insulin and satiety responses to a standardised test meal. This study tested how natural variations in oral processing between slower and faster eaters contribute to differences in post-prandial glucose (PP glucose), insulin response (PP insulin) and post-meal satiety for a standardised test meal. METHODS: Thirty-three participants with higher risk for type 2 diabetes consumed a standardised test-meal while being video recorded to derive specific oral processing behaviours. Plasma glucose, insulin and satiety measures were collected at baseline, during and post meal. Participants were split into slower and faster eaters using median split based on their eating rates and individual bolus properties were analysed at the point of swallow. RESULTS: There were large variations in eating rate (p < 0.001). While there was no significant difference in PP glucose response (p > 0.05), slower eaters showed significantly higher PP insulin between 45 and 60 min (p < 0.001). Slower eaters had longer oro-sensory exposure and increased bolus saliva uptake which was associated with higher PP glucose iAUC. Faster eating rate and larger bolus particle size at swallow correlated with lower PP glucose iAUC. A slower eating rate with greater chews per bite significantly increased insulin iAUC. Faster eaters also consistently rated their hunger and desire to eat higher than slower eaters (p < 0.05). CONCLUSIONS: Natural variations in eating rate and the associated oral processing contributed to differences in PP glucose, PP insulin and satiety responses. Encouraging increased chewing and longer oral-exposure time during consumption, may promote early glucose absorption and greater insulin and satiety responses, and help support euglycaemia. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT04522063.