scholarly journals Effects of Protein Source and Quantity on Appetite Control, Satiety and Subsequent Food Intake in Healthy Adults

2021 ◽  
Vol 5 (Supplement_2) ◽  
pp. 409-409
Author(s):  
Charlotte Griffith ◽  
Kamille Piacquadio ◽  
Morgan Braden ◽  
Heather Leidy
Keyword(s):  
Food Intake ◽  
Energy Intake ◽  
Food Consumption ◽  
Repeated Measures ◽  
Healthy Adults ◽  
Protein Source ◽  
Pea Protein ◽  
Desire To Eat ◽  
Main Effects ◽  
Eating Initiation

Abstract Objectives To examine whether consumption of breakfast preloads varying in protein source and quantity affect measures of appetite, satiety and subsequent energy intake in healthy adults. Methods Thirty-seven healthy adults (Age: 26 ± 4; BMI: 23 ± 2) participated in this randomized crossover design study. On 3 consecutive days, participants consumed 325 kcal preload breakfast yogurts, varying in protein quality (Whey vs. Pea) and quantity (20, 30, 40 g) vs. an isocaloric carbohydrate preload (Control). On day 4, participants completed a 5-hr in clinic testing day. At baseline time -15 min, questionnaires assessing hunger, fullness, desire to eat, prospective food consumption, and eating initiation, were completed. At time 0 min, the respective preload was provided, and palatability assessed. At time 15 min, after consumption, similar questionnaires were completed every 30 min during the 4-h postprandial period followed by an ad libitum pizza lunch. There was a 3–7 day washout period between testing days. To assess main effects of protein source, paired sample t-tests of incremental area under the curve (iAUC) were computed for 20g Pea vs. 20g Whey preloads on 4-h hunger, fullness, desire to eat, prospective food consumption, eating initiation and lunch energy intake. To assess main effects of protein quantity, repeated measures ANOVA was computed between control and pea protein preloads of 20g, 30g, and 40g on 4-h hunger, fullness, desire to eat, and prospective food consumption niAUC, eating initiation, and lunch energy intake. P < 0.05 was considered statistically significant. Statistical analyses were performed using The R Foundation (R; version 4.0.3). Results No main effects of protein source or quantities were detected for 4-h postprandial hunger, fullness, desire to eat, and prospective food consumption niAUC. On average, participants requested to eat again 2-h after breakfast (134 ± 12 min) and consumed on average 830 ± 10 kcals at lunch with no differences between protein sources or quantities. Conclusions In the context of an acute feeding study, no differences in postprandial appetite, satiety, and subsequent food intake were detected when comparing protein preloads varying in source and quantity. These data suggest that 20 g pea protein is sufficient to elicit satiety effects and can be used as a plant-based alternative for whey protein. Funding Sources Roquette.

scholarly journals Acute Effects of Protein Source on Appetite and Subsequent Food Intake in Healthy Adults (P08-066-19)

2019 ◽  
Vol 3 (Supplement_1) ◽  
Author(s):  
Jess Gwin ◽  
Heather Leidy
Keyword(s):  
Food Intake ◽  
Soy Protein Isolate ◽  
Protein Isolate ◽  
Healthy Adults ◽  
Blood Sampling ◽  
Protein Source ◽  
Reduce Food Intake ◽  
Acute Effects ◽  
Ad Libitum ◽  
Desire To Eat

Abstract Objectives The purpose of this study was to examine the acute effects of consuming isocaloric, higher-protein breakfast shakes varying in protein source on appetite, satiety, and subsequent breakfast and lunch food intake in healthy adults. Methods Thirty-two adults (Age: 25 ± 1y; BMI: 24.2 ± 0.5 kg/m2) randomly consumed 250 kcal higher-protein breakfast shakes (24 g total protein; 17 g CHO; 9 g fat), varying only in protein source (whey protein isolate, WHEY; soy protein isolate, SOY; Micellar Casein, CAS; pea protein isolate, PEA; and milk protein isolate; MILK) for 3 days/shake. On day 4, the participants completed a 4-h testing day that included the consumption of the respective shake followed by blood sampling and questionnaires taken every 30 min to assess appetite and satiety. At the end of the testing day, an ad libitum lunch was provided. In addition, we sought to assess whether the study shakes consumed as breakfast preloads reduce food intake within the breakfast eating occasion. Thus, on day 5, the respective shake was consumed 30 min before an ad libitum breakfast. Results Postprandial differences in morning fullness and desire to eat were detected between protein shakes. Specifically, MILK led to greater 4-h fullness vs. WHEY, SOY, and PEA (all, P < 0.05) but not vs. CAS. CAS led to greater fullness vs. SOY (P < 0.05). In addition, MILK, CAS, and PEA led to greater decreases in 4-h desire to eat vs. SOY (all, P < 0.05). No differences in hunger, prospective food consumption, or food cravings were detected. At the subsequent lunch meal, the participants consumed on average 750 ± 70 kcal with no differences observed between shakes. Lastly, regardless of the protein source within the preloads, the participants consumed an additional +280 ± 50 kcal from other breakfast foods. Blood sampling analyses of metabolic analytes and appetite hormones are on-going. Conclusions Although protein source differences within isocaloric, higher-protein breakfast shakes influenced appetite responses throughout the morning, subsequent breakfast and lunch intake was not modified. Funding Sources Leprino Foods.

scholarly journals Effect of Chia (Salvia hispanica L.) Flour on Glycemic Response and Energy Intake in Healthy Adults (P06-099-19)

2019 ◽  
Vol 3 (Supplement_1) ◽  
Author(s):  
Olivia Coelho ◽  
Daniela Rocha ◽  
Barbara Pereira da Silva ◽  
Alessandra Silva ◽  
Ana Paula Caldas ◽  
...  
Keyword(s):  
Blood Glucose ◽  
Food Intake ◽  
Dietary Intake ◽  
Energy Intake ◽  
Repeated Measures ◽  
Normal Weight ◽  
Healthy Adults ◽  
Glycemic Response ◽  
Repeated Measures Anova ◽  
Anova Test

Abstract Objectives Postprandial glycemic control is essential in both healthy and diabetic people, as hyperglycemia predisposes to complications associated with diabetes. The consumption of fiber-rich meals help to prevent and control undesirable glycemic changes. This study aimed to evaluate the effect of one-day consumption of chia on glycemic response and energy intake in healthy adults. Methods Single-blind, randomized, crossover design study involving healthy adults, normal weight (BMI 18.5–24.9 kg/m2), euglycemic (100 mg/dL), with no diabetes family history. They attended to the laboratory after 10–12 h fasting and received either 350 ml of a shake containing 10 g of chia flour (4.44 g of fiber) or 350 ml of a control shake (1.1 g of fiber)- similar in calories and macronutrients, containing 51 g of available carbohydrate - on two non-consecutive days (washout period). At each testing day, 60 minutes after shake intake a glucose solution (25 g) was provided. Capillary blood glucose was measured in fasting state (−60 min), immediately before (0 min), and 15, 30, 45, 60, 90, 120 minutes after glucose load. In addition, food intake was assessed 24-hour dietary recall was performed after each testing day. Habitual dietary intake was estimated using the semi-quantitative QFCA. The study was approved by the Local Ethics Committee. Repeated-measures ANOVA test was used to compare habitual dietary intake and consumption after shake. Two-way repeated measures ANOVA test followed by Bonferroni's post-hoc was used to assess the differences in postprandial blood glucose. Incremental area under the curve (AUC) of postprandial glycemia was calculated using the trapezoidal rule and paired sample t-test was used to compare them. All analyses were conducted using SPSS software. Statistical significance was set as p < 0.05. Results Fifteen subjects completed the study (14 female and 1 male). Consumption of chia (10 g of chia flour) did not change the blood glucose (p > 0.05) nor food intake (p > 0.05) among adults (25 ± 1 years), euglycemic (87.88 ± 1.21 mg/dL), normal weight (21.06 ± 0.28 kg/m2 and 23.23 ± 1.19% body fat percentual). Conclusions The one-day consumption of chia flour did not affect the glycemic response and did not interfere in energy intake in healthy individuals. The long-term effect of chia should be assessed. Funding Sources CNPq, CAPES, FAPEMIG, FUNARBE, DNS-UFV. Supporting Tables, Images and/or Graphs

scholarly journals Effect of ultraprocessed food intake on cardiometabolic risk is mediated by diet quality: a cross-sectional study

2021 ◽  
pp. bmjnph-2020-000225
Author(s):  
Jennifer Griffin ◽  
Anwar Albaloul ◽  
Alexandra Kopytek ◽  
Paul Elliott ◽  
Gary Frost
Keyword(s):  
Food Intake ◽  
Energy Intake ◽  
Food Consumption ◽  
Outcome Measures ◽  
Diet Quality ◽  
Cardiometabolic Risk ◽  
Saturated Fat ◽  
Secondary Outcome ◽  
Cross Sectional ◽  
Occupational Cohort

ObjectiveTo examine the effect of the consumption of ultraprocessed food on diet quality, and cardiometabolic risk (CMR) in an occupational cohort.DesignCross-sectional.SettingOccupational cohort.Participants53 163 British police force employees enrolled (2004–2012) into the Airwave Health Monitoring Study. A total of 28 forces across the UK agreed to participate. 9009 participants with available 7-day diet record data and complete co-variate data are reported in this study.Main outcome measuresA CMR and Dietary Approaches to Stop Hypertension score were treated as continuous variables and used to generate measures of cardiometabolic health and diet quality. Secondary outcome measures include percentage of energy from fat, saturated fat, carbohydrate, protein and non-milk extrinsic sugars (NMES) and fibre grams per 1000 kcal of energy intake.ResultsIn this cohort, 58.3%±11.6 of total energy intake was derived from ultraprocessed (NOVA 4) foods. Ultraprocessed food intake was negatively correlated with diet quality (r=−0.32, p<0.001), fibre (r=−0.20, p<0.001) and protein (r = −0.40, p<0.001) and positively correlated with fat (r=0.18, p<0.001), saturated fat (r=0.14, p<0.001) and nmes (r=0.10, p<0.001) intake . Multivariable analysis suggests a positive association between ultraprocessed food (NOVA 4) consumption and CMR. However, this main effect was no longer observed after adjustment for diet quality (p=0.209). Findings from mediation analysis indicate that the effect of ultraprocessed food (NOVA 4) intake on CMR is mediated by diet quality (p<0.001).ConclusionsUltraprocessed food consumption is associated with a deterioration in diet quality and positively associated with CMR, although this association is mediated by and dependent on the quality of the diet. The negative impact of ultraprocessed food consumption on diet quality needs to be addressed and controlled studies are needed to fully comprehend whether the relationship between ultraprocessed food consumption and health is independent to its relationship with poor diet quality.

scholarly journals Fecal Bacteria as Biomarkers for Predicting Food Intake in Healthy Adults

2020 ◽  
Author(s):  
Leila M Shinn ◽  
Yutong Li ◽  
Aditya Mansharamani ◽  
Loretta S Auvil ◽  
Michael E Welge ◽  
...  
Keyword(s):  
Food Intake ◽  
Food Consumption ◽  
Healthy Adults ◽  
Compact Set ◽  
Fecal Bacteria ◽  
Whole Grain ◽  
Gastrointestinal Microbiota ◽  
Model Accuracy ◽  
Microbial Biomarkers ◽  
The Impact

ABSTRACT Background Diet affects the human gastrointestinal microbiota. Blood and urine samples have been used to determine nutritional biomarkers. However, there is a dearth of knowledge on the utility of fecal biomarkers, including microbes, as biomarkers of food intake. Objectives This study aimed to identify a compact set of fecal microbial biomarkers of food intake with high predictive accuracy. Methods Data were aggregated from 5 controlled feeding studies in metabolically healthy adults (n = 285; 21–75 y; BMI 19–59 kg/m2; 340 data observations) that studied the impact of specific foods (almonds, avocados, broccoli, walnuts, and whole-grain barley and whole-grain oats) on the human gastrointestinal microbiota. Fecal DNA was sequenced using 16S ribosomal RNA gene sequencing. Marginal screening was performed on all species-level taxa to examine the differences between the 6 foods and their respective controls. The top 20 species were selected and pooled together to predict study food consumption using a random forest model and out-of-bag estimation. The number of taxa was further decreased based on variable importance scores to determine the most compact, yet accurate feature set. Results Using the change in relative abundance of the 22 taxa remaining after feature selection, the overall model classification accuracy of all 6 foods was 70%. Collapsing barley and oats into 1 grains category increased the model accuracy to 77% with 23 unique taxa. Overall model accuracy was 85% using 15 unique taxa when classifying almonds (76% accurate), avocados (88% accurate), walnuts (72% accurate), and whole grains (96% accurate). Additional statistical validation was conducted to confirm that the model was predictive of specific food intake and not the studies themselves. Conclusions Food consumption by healthy adults can be predicted using fecal bacteria as biomarkers. The fecal microbiota may provide useful fidelity measures to ascertain nutrition study compliance.

scholarly journals Stevia Beverage Consumption prior to Lunch Reduces Appetite and Total Energy Intake without Affecting Glycemia or Attentional Bias to Food Cues: A Double-Blind Randomized Controlled Trial in Healthy Adults

2020 ◽  
Vol 150 (5) ◽  
pp. 1126-1134 ◽  
Author(s):  
Nikoleta S Stamataki ◽  
Corey Scott ◽  
Rebecca Elliott ◽  
Shane McKie ◽  
Douwina Bosscher ◽  
...  
Keyword(s):  
Blood Glucose ◽  
Food Intake ◽  
Total Energy ◽  
Attentional Bias ◽  
Energy Intake ◽  
Sweet Taste ◽  
Healthy Adults ◽  
Food Cues ◽  
Double Blind ◽  
Randomized Controlled

ABSTRACT Background Stevia is a zero-calorie alternative to caloric sugars. Substituting caloric sweeteners with noncaloric sweeteners reduces available energy, but their effects on appetite, subsequent food intake, and neurocognitive responses are still unclear. Objective The aim was to examine whether sweetness with or without calories influences food intake, appetite, blood glucose concentrations, and attentional bias (AB) to food cues. Methods This was a randomized, controlled, double-blind crossover study. Healthy participants [n = 20; aged 27 ± 5 y,  55% female; BMI (kg/m2): 21.8 ± 1.5] completed 5 visits, consuming 5 study beverages: 330 mL water (control, no sweet taste, no calories) and either 330 mL water containing 40 g glucose or sucrose (sweet taste; calories, both 160 kcal), maltodextrin (no sweet taste; calories, 160 kcal), or 240 ppm stevia (sweet taste, no calories). Glucose and stevia beverages were matched for sweetness. Subjective appetite ratings and blood glucose were measured at baseline and at 15, 30, and 60 min postprandially. At 15 min participants performed a visual-dot probe task to assess AB to food cues; at 30 min, participants were offered an ad libitum lunch; food intake was measured. Results Subjective appetite ratings showed that preload sweetness and calorie content both affected appetite. The total AUC for glycemia was significantly higher after the caloric beverages (mean ± SD: maltodextrin, 441 ± 57.6;  glucose, 462 ± 68.1;  sucrose, 425 ± 53.6 mmol × min × L−1 ) compared with both stevia (320 ± 34.2 mmol × min × L−1) and water (304 ± 32.0 mmol × min × L−1) (all P &lt; 0.001). Total energy intake (beverage and meal) was significantly lower after the stevia beverage (727 ± 239 kcal) compared with water (832 ± 198 kcal,  P = 0.013), with no significant difference between the water and caloric beverages (P = 1.00 for water vs. maltodextrin, glucose, and sucrose). However, food-related AB did not differ across conditions (P = 0.140). Conclusions This study found a beneficial and specific effect of a stevia beverage consumed prior to a meal on appetite and energy intake in healthy adults. This trial is registered at clinicaltrials.gov as NCT03711084.

scholarly journals The Short-Term Effect of Whey Compared with Pea Protein on Appetite, Food Intake, and Energy Expenditure in Young and Older Men

2020 ◽  
Vol 4 (2) ◽  
Author(s):  
Aubree L Hawley ◽  
Edward Gbur ◽  
Angela M Tacinelli ◽  
Sam Walker ◽  
Allie Murphy ◽  
...  
Keyword(s):  
Food Intake ◽  
Energy Expenditure ◽  
Fat Oxidation ◽  
Older Men ◽  
Protein Isolate ◽  
High Protein ◽  
Protein Source ◽  
Pea Protein ◽  
Age Related ◽  
Source Markers

ABSTRACT Background Diets higher in protein have been reported to improve age-related changes in body composition via increased energy expenditure, shifts in substrate oxidation (SO), and decreased appetite. However, how protein source (e.g., animal compared with plant protein) affects energy expenditure, appetite, and food intake as we age is unknown. Objectives The objective of this study was to evaluate the effect of protein source as part of a high-protein breakfast on appetite, food intake, energy expenditure, and fat oxidation in young men (YM) compared with older men (OM). Methods This study used a randomized, single-blinded crossover design, with a 1-wk washout period between testing days. Fifteen YM (mean ± SD age: 25.2 ± 2.8 y) and 15 OM (67.7 ± 4.5 y), healthy adults, participated in the study. Participants arrived fasted and consumed an isocaloric, volume-matched, high-protein (40-g) test beverage made with either an animal [whey protein isolate (WPI)] or plant [pea protein isolate (PPI)] protein isolate source. Markers of appetite and energy expenditure were determined at baseline and over 4 h postprandial. Results There was a significant effect of time, age, and protein source on appetite (P &lt; 0.05). There was no effect of protein source on plasma markers of appetite, food intake, energy expenditure, and SO. After controlling for body weight, OM had decreased energy expenditure (P &lt; 0.05) and lower fat oxidation (P &lt; 0.001) compared with YM. Conclusions This study indicates that a high-protein breakfast containing WPI or PPI exerts comparable effects on appetite, energy expenditure, and 24-h energy intake in both young and older healthy adult men. This trial was registered at clinicaltrials.gov as NCT03399812.

scholarly journals Acute Effects of an Afternoon Hummus-containing Snack on Appetite, Mood, and Food Intake in Healthy Adults (P08-009-19)

2019 ◽  
Vol 3 (Supplement_1) ◽  
Author(s):  
Heather Leidy ◽  
Evan Reister
Keyword(s):  
Food Intake ◽  
Glucose Monitoring ◽  
Healthy Adults ◽  
Funding Sources ◽  
Fat Consumption ◽  
Daily Food ◽  
Testing Facility ◽  
Desire To Eat ◽  
At Home

Abstract Objectives The purpose of this study was to determine whether the consumption of afternoon snacks containing lower-sugar hummus/pretzels vs. higher-sugar granola bars improve appetite, mood, and eating behavior throughout the day compared to no afternoon snacking in healthy adults. Methods Thirty-two adults (age: 24.3 ± 0.9 y; BMI: 24.2 ± 0.6 kg/m2) randomly completed the following afternoon snack patterns for 6 days/pattern: consumption of hummus & pretzels (HUMMUS; 240 kcals; 6 g PRO/31 g CHO(2 g sugar)/11 g FAT); consumption of granola bars (BARS; 240 kcals; 4 g PRO/38 g CHO(16 g sugar)/9 g FAT); or no afternoon snacking (NO SNACK). On day 7 of each pattern, a standardized breakfast was provided at home and the participants arrived at the testing facility to consume a standardized lunch. The respective snack was provided to participants three hours after lunch. Appetite, mood, and satiety questionnaires were completed throughout the afternoon. Three hours after the snack, a standardized dinner was consumed, and an evening snack packout was provided, ad libitum at home, throughout the remainder of the day. Continuous glucose monitoring (CGM) was also completed from days 3–8 of each snack pattern. Results The HUMMUS snack led to lower hunger, desire to eat, and prospective food consumption throughout the afternoon vs. NO SNACK (all, P < 0.01), whereas the BARS did not. When directly comparing the snacks, HUMMUS tended to elicit lower hunger (P = 0.06) and desire to eat (P = 0.09) vs. BARS (all, P < 0.100). Fullness was not different between patterns. The HUMMUS snack also led to smaller reductions in afternoon alertness vs. NO SNACK (P < 0.01) and vs. BARS (P = 0.05); no difference in alertness was detected when comparing BARS vs. NO SNACK. Afternoon snacking delayed subsequent eating initiation by + 80 min compared to NO SNACK (both, P < 0.05) with no differences between snacks. Although afternoon snacking on either HUMMUS or BARS reduced subsequent (evening) snack intake vs. NO SNACK (both, P < 0.01), daily energy intake was not different. CGM analyses are on-going. Conclusions The acute consumption of an afternoon snack, particularly containing lower-sugar hummus, improved select indices of appetite and mood but had minimal effects on daily food intake in healthy adults. Long-term trials assessing the effects of lower-sugar snacks on health outcomes are warranted. Funding Sources Sabra Dipping Company.

Ankle and Midfoot Power During Walking and Stair Ascent in Healthy Adults

2018 ◽  
Vol 34 (4) ◽  
pp. 262-269 ◽  
Author(s):  
Frank E. DiLiberto ◽  
Deborah A. Nawoczenski ◽  
Jeff Houck
Keyword(s):  
Power Generation ◽  
Repeated Measures ◽  
Peak Power ◽  
Healthy Adults ◽  
Total Power ◽  
Foot Motion ◽  
Reaction Forces ◽  
Foot Function ◽  
Main Effects ◽  
External Loads

Ankle power dominates forward propulsion of gait, but midfoot power generation is also important for successful push-off. However, it is unclear if midfoot power generation increases or stays the same in response to propulsive activities that induce larger external loads and require greater ankle power. The purpose of this study was to examine ankle and midfoot power in healthy adults during progressively more demanding functional tasks. Multisegment foot motion (tibia, calcaneus, and forefoot) and ground reaction forces were recorded as participants (N = 12) walked, ascended a standard step, and ascended a high step. Ankle and midfoot positive peak power and positive total power, and the proportion of midfoot to ankle positive total power were calculated. One-way repeated-measures analyses of variance were conducted to evaluate differences across tasks. Main effects were found for ankle and midfoot peak and total powers (all Ps < .01), but not for the proportion of midfoot-to-ankle total power (P = .33). Ankle and midfoot power significantly increased across each task. Midfoot power increased in proportion to ankle power and in congruence to the external load of a task. Study findings may serve to inform multisegment foot modeling applications and internal mechanistic theories of normal and pathological foot function.

Food Type and Lentil Variety Affect Satiety Responses but Not Food Intake in Healthy Adults When Lentils Are Substituted for Commonly Consumed Carbohydrates

2019 ◽  
Vol 149 (7) ◽  
pp. 1180-1188
Author(s):  
Sandra L Clark ◽  
D Dan Ramdath ◽  
Brittany V King ◽  
Katherine E O'Connor ◽  
Michel Aliani ◽  
...  
Keyword(s):  
Body Weight ◽  
Food Intake ◽  
Weight Management ◽  
Energy Intake ◽  
Test Meal ◽  
Food Products ◽  
Healthy Adults ◽  
Food Type ◽  
Food Ingredients ◽  
Decrease Food Intake

ABSTRACT Background Lentils have potential to increase satiety and may contribute to a body weight management strategy; however, the effects on satiety of replacing common food ingredients with lentils within food products remain largely unknown. Objective The aim of this study was to determine the effects of replacing wheat and rice with 2 lentil varieties within muffins and chilies on satiety, test-meal food intake, and 24-h energy intake. Methods Healthy adults consumed muffins or chilies in which wheat or rice was substituted with green (61.8 g) or red (54 g) lentils in 2 randomized crossover studies (muffin study: n = 24, mean ± SE age: 25.4 ± 0.9 y, BMI (in kg/m2): 23.2 ± 0.5; chili study: n = 24, age: 25.7 ± 1.0 y, BMI: 23.2 ± 0.5), with ≥1-wk washout periods between study visits and studies. Subjective appetite sensations measured over 180 min were summarized with total area under the curve (AUC), food intake was measured at an ad libitum test meal, and 24-h energy intake was measured using weighed food records. Treatment effects were compared within each study using repeated-measures ANCOVA (subjective appetite sensations) and ANOVA (food intake, 24-h energy intake). Results Green, but not red, lentil chili significantly increased fullness AUC (17.5%, P = 0.02) and decreased desire to eat AUC (20.1%, P = 0.02) and prospective food consumption AUC (16.7%, P = 0.04) compared with rice chili, with no significant differences between chili treatments for test-meal food intake or 24-h energy intake. Muffin treatments did not significantly differ for any outcomes. Conclusions Replacing rice with green, but not red lentils within chili increases satiety but does not decrease food intake, whereas replacing wheat with lentils within muffins does not increase satiety or decrease food intake in healthy adults. Further study of the role of lentil replacement in food products in body weight management is warranted. This trial was registered at clinicaltrials.gov as NCT03128684.

Acute effects of pea protein and hull fibre alone and combined on blood glucose, appetite, and food intake in healthy young men – a randomized crossover trial

2014 ◽  
Vol 39 (12) ◽  
pp. 1360-1365 ◽  
Author(s):  
Rebecca C. Mollard ◽  
Bohdan L. Luhovyy ◽  
Christopher Smith ◽  
G. Harvey Anderson
Keyword(s):  
Blood Glucose ◽  
Food Intake ◽  
Repeated Measures ◽  
Crossover Trial ◽  
Value Added ◽  
Tomato Sauce ◽  
Pea Protein ◽  
Yellow Peas ◽  
Hull Fibre ◽  
And Control

Whether pulse components can be used as value-added ingredients in foods formulated for blood glucose (BG) and food intake (FI) control requires investigation. The objective of this study was to examine of the effects of pea components on FI at an ad libitum meal, as well as appetite and BG responses before and after the meal. In a repeated-measures crossover trial, men (n = 15) randomly consumed (i) pea hull fibre (7 g), (ii) pea protein (10 g), (iii) pea protein (10 g) plus hull fibre (7 g), (iv) yellow peas (406 g), and (v) control. Pea hull fibre and protein were served with tomato sauce and noodles, while yellow peas were served with tomato sauce. Control was noodles and tomato sauce. FI was measured at a pizza meal (135 min). Appetite and BG were measured pre-pizza (0–135 min) and post-pizza (155–215 min). Protein plus fibre and yellow peas led to lower pre-pizza BG area under the curve compared with fibre and control. At 30 min, BG was lower after protein plus fibre and yellow peas compared with fibre and control, whereas at 45 and 75 min, protein plus fibre and yellow peas led to lower BG compared with fibre (p < 0.05). Following the pizza meal (155 min), yellow peas led to lower BG compared with fibre (p < 0.05). No differences were observed in FI or appetite. This trial supports the use of pea components as value-added ingredients in foods designed to improve glycemic control.

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