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The acute effects of a pulse-containing meal on glycaemic responses and measures of satiety and satiation within and at a later meal

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Pulses are low glycaemic foods; however, their effect on satiation is unknown. The objective was to determine the effects of an ad libitum pulse meal on food intake (FI), appetite and blood glucose (BG) before and after a test meal (4 h later) and on FI at the test meal. Males (n 24, 22·8 kg/m2) received one of four treatments or control. The pulse treatments contained pasta and tomato sauce and 44 % of energy from: (1) chickpeas, (2) lentils, (3) navy beans or (4) yellow peas. The control was pasta and tomato sauce (pasta and sauce). FI (satiation) was measured at the treatment meal (0-20 min) and at an ad libitum pizza meal 4 h later. BG and appetite were measured from 0 to 340 min. At the treatment meal, lentils led to lower FI compared to chickpeas and pasta and sauce, whereas navy beans led to lower FI compared to chickpeas. Also, lentils led to lower cumulative FI compared to pasta and sauce. All pulses led to lower BG peak and cumulative area under the curve (AUC; 0-340 min); however, only chickpeas, lentils and navy beans reduced pre-pizza meal BG AUC (0-260 min) relative to pasta and sauce. Chickpeas led to lower post-pizza meal BG AUC (260-340 min) compared to navy beans and yellow peas. Consumption of pulses in a high-glycaemic meal contributes to earlier satiation, lower BG following the meal and after a later meal, but these effects are specific to pulse type and cannot be explained by their glycaemic properties alone.
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The acute effects of a pulse-containing meal on glycaemic responses and
measures of satiety and satiation within and at a later meal
R. C. Mollard, A. Zykus, B. L. Luhovyy, M. F. Nunez, C. L. Wong and G. H. Anderson*
Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, 150 College Street, Toronto, ON,
Canada M5S 3E2
(Submitted 2 February 2011 – Final revision received 8 August 2011 – Accepted 26 September 2011 – First published online 7 November 2011)
Abstract
Pulses are low glycaemic foods; however, their effect on satiation is unknown. The objective was to determine the effects of an ad libitum
pulse meal on food intake (FI), appetite and blood glucose (BG) before and after a test meal (4 h later) and on FI at the test meal. Males
(n24, 22·8 kg/m
2
) received one of four treatments or control. The pulse treatments contained pasta and tomato sauce and 44 % of energy
from: (1) chickpeas, (2) lentils, (3) navy beans or (4) yellow peas. The control was pasta and tomato sauce (pasta and sauce). FI (satiation)
was measured at the treatment meal (020 min) and at an ad libitum pizza meal 4 h later. BG and appetite were measured from 0 to
340 min. At the treatment meal, lentils led to lower FI compared to chickpeas and pasta and sauce, whereas navy beans led to lower FI
compared to chickpeas. Also, lentils led to lower cumulative FI compared to pasta and sauce. All pulses led to lower BG peak and cumu-
lative area under the curve (AUC; 0 –340 min); however, only chickpeas, lentils and navy beans reduced pre-pizza meal BG AUC
(0260 min) relative to pasta and sauce. Chickpeas led to lower post-pizza meal BG AUC (260– 340 min) compared to navy beans and
yellow peas. Consumption of pulses in a high-glycaemic meal contributes to earlier satiation, lower BG following the meal and after a
later meal, but these effects are specific to pulse type and cannot be explained by their glycaemic properties alone.
Key words: Pulses: Food intake: Blood glucose: Satiation
Pulses are the edible seeds of legumes or pod-bearing plants
and include beans, chickpeas, yellow peas and lentils. Regular
consumption of pulses (half cup per d) has been related to
higher-quality diets, including higher intakes of fibre, protein,
folate, Zn, Fe and Mg, and lower intakes of saturated fat and
total fat
(1)
. Bean consumption is also associated in epidemio-
logical studies with reduced body weight, waist circumference
and risk of overweight and obesity
(2)
.
Currently, the world is experiencing an obesity epidemic
and a rapid increase in prevalence of chronic diseases such
as type 2 diabetes. Overweight and obesity characteristically
result when energy intake exceeds energy expenditure. One
potential countermeasure to the current obesity epidemic is
to identify and recommend foods that reduce energy intake
by inducing satiation and increasing satiety. Satiation and
satiety are complementary events related to the sensation of
fullness, but differ in timing and outcome. Satiation is the ter-
mination of food intake (FI) during a meal due to fullness
(3)
.
Thus, satiation can reduce hunger and limit energy intake
at that meal
(4)
. Satiety is a postprandial sensation of fullness
that can delay the onset and/or reduce energy intake of
a second meal
(4)
. Consequently, identifying foods that are
satiating (eat less at that meal) and prolong satiety (extend
the time to the next meal and reduce FI at that next meal)
would be beneficial in the prevention and treatment of
obesity.
Pulses are possible foods that could be used in dietary strat-
egies for the control of body weight as well as blood glucose
(BG). Short-term studies have shown that pulses, when con-
sumed alone, are high satiety
(5)
low glycaemic
(5 – 7)
foods
that have the ability to lower the BG response to a later
meal
(8)
. This effect on postprandial BG following a later
meal has been termed the ‘second meal effect’
(9)
.
Pulses are commonly consumed with high-carbohydrate
foods such as pasta, rice and bread, and eaten to satiation
(until full). However, it is unclear whether the incorporation
of pulses into a high-carbohydrate meal affects how much is
eaten at that meal (satiation). It is also unknown how consum-
ing a pulse meal to satiation would affect FI at a subsequent
meal, as well as the first and second meal effects of pulses
on appetite and BG. It was hypothesised that pulses would
reduce FI at the treatment meal and at the later meal, while
maintaining their first and second meal effects on appetite
and BG. Therefore, the objective of this study was to examine
*Corresponding author: G. H. Anderson, fax þ1 416 978 5882, email harvey.anderson@utoronto.ca
Abbreviations: AUC, area under the curve; BG, blood glucose; FI, food intake; GI, glycaemic index.
British Journal of Nutrition (2012), 108, 509–517 doi:10.1017/S0007114511005836
qThe Authors 2011
British Journal of Nutrition
the effects of ad libitum pulse meals (lentils, navy beans,
chickpeas and yellow peas) compared to a non-pulse meal
on treatment meal FI (satiation), FI at a second ad libitum
pizza meal, as well as appetite (satiety) and BG responses fol-
lowing both meals.
Methods
Subjects
Healthy males aged 2030 years with a BMI of 20 24·9 kg/m
2
were recruited through advertisements around the University
of Toronto (Toronto, ON, Canada) campus. Females, smokers,
breakfast skippers, individuals with diabetes or other meta-
bolic diseases and those scoring $11 on an Eating Habit
Questionnaire
(10)
were excluded from the study. A total of
twenty-seven subjects began the study and twenty-four com-
pleted all sessions. In all, three subjects did not complete all
five sessions because of reasons unrelated to the study.
A sample size of twenty-six was determined by a power
analysis for a within-subject design from previous studies
(5,11)
to be sufficient to detect a treatment effect on FI of 628·0 kJ,
with a power of 0·80 and an
a
of ,0·05. This study was
conducted according to the guidelines laid down in the
Declaration of Helsinki, and all procedures involving human
subjects were approved by the University of Toronto Health
Sciences Research Ethics Board. Written informed consent
was obtained from all subjects.
Study design
A within-subject, balanced, repeated-measures design was fol-
lowed in which subjects received four treatments or control
over 5 weeks, approximately 1 week apart. The pulse treat-
ments contained: (1) chickpeas (Primo, Toronto, ON,
Canada); (2) lentils (Primo); (3) navy beans/haricot beans
(Ferma, Toronto, ON, Canada); or (4) yellow peas (Nupak,
Toronto, ON, Canada). The pulse treatments and control
were made the day before the session and the recipe was cal-
culated to provide 6280·2 kJ at each session. All meals had the
same energy density (approximately 322·4 kJ/100 g) to control
for differences in FI due to variations in energy or weight
among treatments. Energy derived from pulses was consistent
among all pulse treatments (44 %). The pulse treatments
and control all contained macaroni pasta and homemade
tomato sauce. To account for the energy from pulses, the
control contained more pasta (138·0 v. 323·4 g per 6280·2 kJ
portion; Kraft Canada, Inc., Donmills, ON, Canada). The
tomato sauce was made on the premises and contained
diced tomatoes (433·9 g, no salt added, President’s Choice,
Loblaws, Toronto, ON, Canada), parmesan cheese (33·3 g, La
Lila, Silani Brand, Schomberg, ON, Canada), garlic (5·4 g),
onion (119·7 g), chili powder (3·0 g, Selection, Metro, Toronto,
ON, Canada), salt (4·28 –8·17 g; Sifto Canada, Inc., Mississauga,
ON, Canada) and rapeseed oil (11·4 g, Canola Harvest,
Richardson Oilseed Limited, Lethbridge, AB, Canada) per
6280·2 kJ portion. Garlic and onions were bought fresh
from a local supermarket. The tomato sauce was prepared
as follows. Onions and garlic were cooked for 3 min over
medium heat in rapeseed oil and then the additional tomato
sauce ingredients and water were added. Water was added
(50300 ml) to account for differences in weight to ensure
that they were matched for energy density. For the treatments,
pulses were then added and then the mixture was left to
simmer on low heat for 20 min. The macaroni was cooked
separately in boiling water for 8 min and then drained. Varying
amounts of salt were added to match the Na content among
the treatments and the control to ensure that they were
equally palatable. All meals were homogenised with a food
processor to make them similar in texture and prevent partici-
pants from selecting specific contents within the treatment
meal, as this would obscure energy intake based on weight
and confound the effects of treatments on dependent vari-
ables. Pulses were analysed for nutritional composition by
proximate analysis. Proximate analysis was conducted by
Maxxam Analytics (Mississauga, ON, Canada) using standard
methodology (Food Core analysis). Only one sample was ana-
lysed for each pulse. However, there were multiple steps
taken to ensure that the results were accurate, including run-
ning blanks, checking the instrument calibration daily using
EDTA, verifying that results are consistent by running a con-
tinuous calibration verification several times a day, monitoring
the results of an standard reference material by daily control
charting and analysing one duplicate per batch of twenty
samples (the duplicate sample is chosen at random). If any
of the above quality controls are outside the tolerance quality
control range, Maxxam Analytics re-runs the whole batch
after identifying and fixing the root cause. Composition of
non-pulse ingredients were provided by the manufacturer.
Pulse treatments and control were served as an ad libitum
meal during which subjects were instructed to eat until
comfortably full. The nutritional composition of the treatments
and control is shown in Table 1.
Protocol
Before each session, subjects were instructed to refrain
from alcohol and unusual physical activity. As previously
reported
(12 – 15)
, following a 10 –12 h overnight fast, subjects
were asked to consume a standardised breakfast (1256·0 kJ) in
the morning (06.00 09.00 hours) and arrive at the laboratory
4 h later (10.00 – 13.00 hours) to start the session. The standar-
dised breakfast included 26 g of Cheerios (General Mills,
Mississauga, ON, Canada), 250 ml of Beatrice 2 % milk (Parmalat
Canada, Toronto, ON, Canada) and 250 ml of Tropicana
orange juice (Tropicana Products, Inc., Bradenton, FL, USA)
and, if desired, either tea or coffee without additions. In
addition, 500 ml of Canadian Spring water (Canadian Springs,
Mississauga, ON, Canada) was provided to consume between
breakfast and 1 h before commencing the session.
BG concentrations were measured by a glucose meter
(Accu-check Compact-Plus glucose monitor; Roche Diagnos-
tics Canada, Laval, QC, Canada) and blood samples were
obtained by finger prick by a Monojector Lancet Device (Sher-
wood Medical, St Louis, MO, USA), as previously described
(14)
.
The first drop of blood was wiped due to contamination with
R. C. Mollard et al.510
British Journal of Nutrition
alcohol and interstitial fluid and the second drop was placed
on the testing strip. Each subject used the same glucometer
throughout the study to minimise intra-subject variation.
On arrival for the sessions, subjects completed question-
naires assessing their sleep, stress and compliance with fasting
and pattern of activity. If they reported significant deviations
from their usual pattern, they were asked to reschedule. The
session protocol is presented in Fig. 1. Before treatment con-
sumption, subjects completed Motivation to Eat visual ana-
logue scales questionnaire to measure subjective appetite
(16)
,
as used in previous studies
(5,11,12,17)
. A baseline BG measure-
ment was then taken. A value .5·5 mMwas interpreted to
suggest that the subject had not fasted and the session was
rescheduled. After taking the baseline measures (0 min), sub-
jects were given either one of the treatment or control meals
in random order. Subjects ate in isolation in the feeding
room and were instructed to eat until comfortably full and to
pace themselves over 18 min. Pulse/control meals were served
in excess to enable subjects to reach satiation. Previous studies
have also measured satiation by determining ad libitum FI at
one meal
(18,19)
and across the day at multiple meals
(20 – 22)
.
Three portions of the meal (2093·4 kJ per bowl) were served
fresh in 6-min intervals. Additionally, 250 ml of water was
provided, which subjects had to consume within the 18 min.
The weight of each treatment portion before and after con-
sumption was measured to calculate FI. Pleasantness, taste
and texture of the treatment were measured using a Palatabil-
ity visual analogue scales
(5,11,12,17)
questionnaire to ensure that
the subject’s FI and appetite were not affected by treatment
fondness or dislike.
Following treatment meal consumption, BG and appetite
were measured at 20, 40, 60, 110, 140, 200 and 260 min and are
reported as pre-pizza meal (before pizza) values. At 140 min,
subjects were provided with 250 ml water to drink within 5 min
to compensate for physical discomfort arising from thirst.
FI was measured at an ad libitum pizza test meal provided
at 260 min in isolation in our feeding room. Subjects
were instructed to eat until they were ‘comfortably full’.
Three varieties (Pepperoni, Deluxe and Three Cheese) of
Deep ‘N Delicious pizza (McCain Foods, Florenceville, NB,
Canada) were offered to subjects according to their preference
determined at screening, and the same choices were provided
at all sessions. The pizzas averaged 10·0 g of protein, 7·6 g of
fat, 26·6 g of carbohydrate and 946·2 kJ/100 g. Each cooked
pizza (8 min at 2278C and cut in quarters) was weighed
before serving. Fresh pizza trays replaced the previous tray
at 8-min intervals until the subjects declined further trays.
Each tray contained two pizzas of their first choice and one
each of their second and third choices. Following the pizza
meal, palatability of the pizza was assessed by visual analogue
scales questionnaire.
Following the pizza meal, BG and appetite were measured
at 280, 300, 320 and 340 min and are reported as post-pizza
meal (after pizza) values.
Statistical analysis
The average subjective appetite score was calculated from the
Motivation to Eat visual analogue scales questionnaire as fol-
lows: appetite score ¼(desire to eat þhunger þ(100
fullness) þprospective consumption)/4
(14,16,23 – 26)
. Energy
intake at the satiation treatment meal and pizza meal was cal-
culated based on weight consumed and compositional infor-
mation obtained by either proximate analysis or provided by
the manufacturer. Cumulative, pre- and post-pizza meal net
incremental area under the curve (AUC) for BG and cumulat-
ive, pre- and post-pizza meal net area above the curve for
average appetite were calculated for 0340 min, 0260 min
and 260 –340 min, respectively.
SAS version 9.2 (Statistical Analysis Systems; SAS Institute,
Cary, NC, USA) was used for statistical analysis. All ANOVA
included session as a repeated measure to control for
within-subject variability. Three-way (time, treatment and ses-
sion) repeated measures ANOVA determined the effects of
treatments, time and the time £treatment interaction on BG
and average appetite scores over the session. A statistically sig-
nificant interaction between time and treatment was followed
by two-way (treatment and session) repeated measures
ANOVA at the individual time points. The effect of treatments
on FI at the meal and on BG AUC and average appetite area
above the curve were determined by two-way (treatment
and session) repeated measures ANOVA. TukeyKramer post
hoc test was used to describe mean differences among treat-
ments. All results are presented as mean values with their stan-
dard errors of the mean. The statistical significance was
concluded with the Pvalue ,0·05.
Results
Subject characteristics
Subjects had a mean age of 24·3 (SEM 3·6) years, weight of 72·4
(SEM7·8) kg and BMI of 22·8 (SEM1·4) kg/m
2
.
0 20 40 60 80 110 140 200 260 280 300 320 340
min
Pizza
meal
Treatment
Pre-pizza meal blood glucose and appetite
Post-pizza meal
blood glucose
and appetite
Fig. 1. Session protocol. Both the treatment and the pizza meals were ad libitum.
Pulses, satiation and blood glucose 511
British Journal of Nutrition
Food intake and palatability
There was an effect of treatment on FI at the treatment meal
(P,0·0001; Table 2), with lentils exhibiting the strongest
satiating properties. The lentil treatment led to lower FI com-
pared to chickpeas and pasta and sauce, whereas navy beans
led to lower FI compared only to chickpeas. Despite no sig-
nificant differences in FI at the pizza meal 4 h following ad
libitum treatment consumption (P¼0·13), lentils reduced
cumulative FI compared to pasta and sauce (P¼0·02). There
were no significant differences observed in palatability ratings
among treatment meals (P¼0·28). Palatability ratings for the
control and treatment meals were as follows: 53·8 (SEM 4·8),
61·7 (SEM3·4), 58·1 (SEM3·8), 58·5 (SEM3·5) and 57·0
(SEM4·0) mm for the pasta and sauce, chickpeas, lentils, navy
beans and yellow peas, respectively. There was also no differ-
ence in palatability ratings of the pizza among the five sessions
(P¼0·50; data not shown).
Subjective appetite
Pre-pizza meal appetite was affected by time (P,0·001), but
there was no effect of treatment (P¼0·23) and no time £
treatment interaction (P¼0·59; Fig. 2). Regardless of treatment,
appetite was highest when subjects first arrived (72·5 (SEM
1·7) mm), but immediately decreased at 20 min on completion
of the treatment meal (17·4 (SEM 1·3) mm) and gradually
returned to baseline levels by 260 min (68·5 (SEM 1·6) mm).
Average appetite scores over the pre-pizza meal period for
the control and treatment groups were as follows: 40·4 (SEM
1·7), 38·6 (SEM 1·6), 39·6 (SEM 1·7), 39·0 (SEM 1·6) and 36·5
(SEM 1·6) mm for the pasta and sauce, chickpeas, lentils,
navy beans and yellow peas, respectively.
Similarly, post-pizza meal appetite was affected by time
(P,0·001), but there was no effect of treatment (P¼0·23)
and no time £treatment interaction (P¼0·11; Fig. 2). Immedi-
ately after the pizza meal, regardless of treatment, appetite
sharply decreased to 16·0 (SEM 1·3) mm and gradually
increased over the next hour to 27·4 (SEM 1·8) mm. Average
appetite scores over the post-pizza meal period for the control
and treatments were as follows: 32·6 (SEM 2·2), 34·3 (SEM 2·3),
34·3 (SEM 2·5), 34·1 (SEM 2·4) and 35·3 (SEM 2·3) mm for the
pasta and sauce, chickpeas, lentils, navy beans and yellow
peas, respectively. There was no effect of treatment on cumu-
lative (P¼0·82), pre-pizza meal (P¼0·81) or post-pizza meal
(P¼0·78) appetite area above the curve (Table 3).
Blood glucose
Pre-pizza meal BG was affected by time (P,0·0001) and treat-
ment (P,0·0001), with a time £treatment interaction
(P,0·0001) that was explained by variation in the response
to treatments over time. Thus, to further investigate the
response to the treatments over time, the effect of treatment
was assessed at each time measurement. There was a signifi-
cant effect of treatment on all pre-pizza meal BG time points
over the 260-min period (Fig. 3). Immediately following
Table 1. Nutritional composition of treatments and control*
Energy
(kJ/100 g) Fat (g/100 g)
Available carbohydrate
(g/100 g)
Fibre
(g/100 g)
Protein
(g/100 g)
Pasta and sauce 322·0 1·3 13·7 0·9 2·6
Chickpeas 324·5 1·7 12·0 2·1 3·5
Lentils 323·2 1·3 12·6 2·5 3·9
Navy beans 324·1 1·4 12·0 3·2 4·2
Yellow peas 327·4 1·2 12·9 2·0 3·9
* Composition of the pulses were determined by proximate analysis. The composition of the non-pulse ingredients were provided
by the manufacturers.
Table 2. Treatment meal, pizza meal and cumulative food intake*
(Mean values with their standard errors)
Treatment
meal† (kJ)
Pizza
meal‡ (kJ) Cumulative§ (kJ)
Mean SEM Mean SEM Mean SEM
Pasta and sauce 2916·1
a,b
212·3 6090·5 321·6 9006·6
a
435·9
Chickpeas 2970·1
a
188·8 5715·4 304·4 8685·9
a,b
430·0
Lentils 2613·4
c
190·9 5672·7 283·0 8286·1
b
432·9
Navy beans 2691·7
b,c
218·6 5859·0 327·0 8550·7
a,b
469·8
Yellow peas 2949·6
a,b
229·4 5794·5 331·2 8744·1
a,b
491·5
Pk,0·0001 0·13 0·02
a,b,c
Mean values within a column with unlike superscript letters are significantly different (P,0·05).
* Two-way ANOVA, followed by Tukey –Kramer post hoc test (n24).
† Measured at an ad libitum treatment meal consumed following baseline measures (0 –20 min).
‡ Measured at an ad libitum pizza meal 260 min following the consumption of the treatment meals.
§ Cumulative equals the amount consumed at the treatment meal plus the pizza meal.
kPvalue for the effect of treatment on study outcomes.
R. C. Mollard et al.512
British Journal of Nutrition
their consumption (20 min), all treatments resulted in a lower
BG response compared with pasta and sauce; also, navy beans
led to lower BG relative to chickpeas. At 40 min, all treatments
led to lower BG compared to pasta and sauce. At 60 min, len-
tils and navy beans resulted in lower BG concentrations com-
pared to the yellow peas. At 80 min, chickpeas and lentils led
to lower BG compared to yellow peas and pasta and sauce,
whereas navy beans led to lower BG compared only to
yellow peas. At 110 min, navy beans led to lower BG com-
pared to pasta and sauce. At 140 min, although there was a sig-
nificant effect of treatment, the post hoc test was unable to
identify differences between the treatments and control. At
200 min, lentils and navy beans led to lower BG compared
to pasta and sauce, whereas at 260 min, only navy meals led
to lower BG concentrations compared to chickpeas and
pasta and sauce.
Post-pizza meal BG was affected by time (P,0·0001), but
not by treatment (P¼0·31). However, there was a time £
treatment interaction (P¼0·03). Although there was a time £
treatment interaction on post-pizza meal BG, there was only
a significant effect of treatment at 300 min and the post hoc
test did not identify differences between the treatments and/
or control (Fig. 3).
There was an effect of treatment on cumulative (P¼0·0002),
pre-pizza meal (P,0·0001) and post-pizza meal (P¼0·01) BG
AUC (Table 4). Cumulative BG AUC was lower following all
80
70
60
50
Average appetite (mm)
40
30
20
10
0
0 20 40 60 80 110 140 200 260 280 300 320 340
Time (min)
Pizza
meal
Treatment
meal
Fig. 2. The effect of pulses consumed to satiation on appetite ratings over time. Treatments were pasta and sauce ( ), chickpeas ( ), lentils ( ), navy
beans ( ) and yellow peas ( ). Effects were identified for time (pre-pizza meal: P,0·0001; post-pizza meal: P,0·0001), treatment (pre-pizza meal: P¼0·23;
post-pizza meal: P¼0·23) and time £treatment interaction (pre-pizza meal: P¼0·59; post-pizza meal: P¼0·11) using three-way ANOVA, n24.
Table 3. Pre- and post-meal average appetite area above the curve (AAC)*
(Mean values with their standard errors)
Average appetite AAC† (mm £min)
Cumulative Pre-pizza meal Post-pizza meal
Mean SEM Mean SEM Mean SEM
Pasta and sauce 211 185·3 1325·2 26791·0 822·6 23378·8 281·2
Chickpeas 211 533·4 1105·9 27080·0 942·9 23393·4 292·7
Lentils 212 269·8 1064·4 27521·2 792·9 23145·7 294·8
Navy beans 211 576 ·3 1370·2 27237·7 925·9 23268·6 264·1
Yellow peas 212 681·8 1284·8 27965·0 904·4 23207·1 331·8
P 0·82 0·81 0·78
* Two-way ANOVA (n24).
Cumulative: 0 340 min; pre-pizza meal: 0 260 min; post-pizza meal: 260 340 min.
Pvalue for the effect of treatment on study outcomes.
Pulses, satiation and blood glucose 513
British Journal of Nutrition
the treatments compared to pasta and sauce. Chickpeas, lentils
and navy beans reduced pre-pizza meal BG AUC relative to
pasta and sauce, whereas yellow peas led to intermediate con-
centrations. Despite no effect on the post-pizza meal BG
identified by three-way ANOVA, chickpeas led to lower
post-pizza meal BG AUC compared to navy beans and
yellow peas, whereas lentils and pasta and sauce led to inter-
mediate values.
Discussion
This study shows that incorporating pulses into a high-
glycaemic meal results in lower FI at that meal and lowers
the BG response. However, the effects on satiation at the treat-
ment meal and BG after the second meal were dependent on
pulse type. Specifically, at the treatment meal, lentils exhibited
the strongest satiating properties, resulting in lower FI com-
pared to chickpeas and pasta and sauce, whereas navy
beans also resulted in lower FI compared to chickpeas.
Despite no differences in FI at the pizza meal 4 h later, lentils
were the only pulse to significantly reduce cumulative FI
(treatment plus pizza meal) compared to pasta and sauce.
As expected, all pulse treatments lowered BG following the
treatment meal compared to pasta and sauce, but in contrast
to the hypothesis, not after the pizza meal. Following the
pizza meal, only differences among the pulse treatments
8·5
8·0
Treatment
meal
a
a
b
a
aa
aa
aa
b
b
a,b
a,b a,b
b
a,b
a,b a,b
a,b
a,b
a,b
b,c
c
c
a,b
b
b
b,c
b,c
c
b
b
b
b
Pizza
meal
7·5
7·0
6·5
Blood glucose (mmol/l)
6·0
5·5
5·0
4·0 0 20406080110140
Time (min)
200 260 280 300 320 340
4·5
Fig. 3. The effect of pulses consumed to satiation on blood glucose concentrations over time. Treatments were pasta and sauce ( ), chickpeas ( ), lentils
(), navy beans ( ) and yellow peas ( ). Effects were identified for time (pre-pizza meal: P,0·0001; post-pizza meal: P,0·0001), treatment (pre-pizza
meal: P,0·0001; post-pizza meal: P¼0·31) and time £treatment interaction (pre-pizza meal: P,0·0001; post-pizza meal: P¼0·03) using three-way ANOVA fol-
lowed by a two-way ANOVA; Tukey Kramer post hoc test indentified differences among treatments (P,0·05).
a,b,c
Values with unlike letters are significantly
different at each time point (a .b.c), n24.
Table 4. Pre- and post-test meal blood glucose (BG) area under the curve (AUC)*
(Mean values with their standard errors)
BG AUC† (mmol £min/l)
Cumulative Pre-pizza meal Post-pizza meal
Mean SEM Mean SEM Mean SEM
Pasta and sauce 462·7
a
43·6 340·8
a
35·7 92·2
a,b
13·2
Chickpeas 321·6
b
29·5 220·0
b
27·5 74·5
b
10·7
Lentils 334·6
b
33·4 231·7
b
26·9 89·0
a,b
13·6
Navy beans 324·2
b
34·6 213·0
b
26·0 104·0
a
12·5
Yellow peas 390·8
b
33·2 275·7
a,b
28·0 106·1
a
11·5
P 0·0002 ,0·0001 0·01
a,b,c
Mean values within a column with unlike superscript letters are significantly different
(P,0·05).
* Two-way ANOVA, followed by Tukey –Kramer post hoc test (n24).
† Cumulative: 0– 340 min; pre-pizza meal: 0 –260 min; post-pizza meal: 260– 340min.
Pvalue for the effect of treatment on study outcomes.
R. C. Mollard et al.514
British Journal of Nutrition
were observed. Chickpeas lowered the post-pizza meal BG
AUC response compared to navy beans and yellow peas.
To our knowledge, this is the first report on the effects of
different pulse type consumed within a meal on satiation
and how eating to satiation affects first and second meal BG
and appetite responses and FI at a subsequent meal. In this
trial, pulses were added to a meal with another carbohydrate
source (pasta) because they are usually consumed with
high-glycaemic index (GI) foods and thus would reflect a typi-
cal pulse meal. Also, pulses accounted for 44 % of the energy
in the meal and contributed approximately half of the avail-
able carbohydrate. The average amount of pulses consumed
at the treatment meal was 1235·1 kJ, which is approximately
two cups and provides an average of 44·5 g of available carbo-
hydrate. This amount is similar to the quantity provided in
previous studies (1046·7 kJ) investigating the effects of pulses
consumed alone on BG, appetite and FI control
(5)
. The
pulse treatments and control were provided ad libitum in
the first meal to allow for measurement of their effects on
satiation within the meal and an ad libitum pizza meal was
provided 4 h later to determine if the content of the first
meal impacted FI at a subsequent pizza meal and BG follow-
ing the meal. Both meals were provided ad libitum to reflect
normal eating conditions and because a previous study found
that the incorporation of one cup of pulses into the daily diet
five times a week for 8 weeks resulted in lower daily energy
intake and improved glycaemic control in overweight/obese
subjects
(27)
. The time between treatment meal consumption
and the subsequent ad libitum test meal was based on pre-
vious studies that investigated the second meal effects of
foods or food components on BG
(8,28,29)
.
Neither palatability nor composition was responsible for the
satiating effects of the navy beans and lentils at the treatment
meal. Lentils and navy beans led to the lowest FI and chick-
peas and yellow peas led to the highest during the treatment
meal, yet the pulse treatments and control were found to be
equally palatable (P¼0·28). In addition, there was no relation-
ship between the palatability of the treatment and control
meals and the amount eaten at either the treatment meal (r
0·12, P¼0·20) or the pizza meal (r0·11, P¼0·21). Also, all
the pulse treatments tended to contain more protein, fibre
and less available carbohydrate compared to the control; how-
ever, the macronutrient content among the pulse treatments
were similar.
Additional observations within the present study demon-
strate that pulses are satiating foods. First, despite not statisti-
cally significantly lowering FI at the pizza meal, lentils led to
8 % (720·1 kJ) lower cumulative intake compared to pasta
and sauce. Second, subjects ate the most during the chickpea
and yellow pea treatments, but these treatments did not lead
to higher cumulative FI and, thus, subjects compensated for
those extra energy at the pizza meal. Lastly, despite eating
less at the treatment meals containing lentils and navy
beans, there were no differences in appetite ratings over the
session, indicating that they are high-satiety foods.
When consumed to satiation within a meal containing high-
glycaemic carbohydrate, pulses maintain their low glycaemic
properties. It was expected that the amount eaten at the
treatment meal would be associated with BG AUC response
(r0·42, P,0·0001) over the 4 h preceding the pizza meal, indi-
cating that greater FI at the meal results in a higher BG
response to the meal. However, the BG responses immedi-
ately following pulse consumption (20 min), at peak (40 min)
and cumulative AUC were lower following all the pulse treat-
ments compared with pasta and sauce, indicating that meal
size alone was not the only determinant of BG.
As expected, replacing 44 % of energy from high-GI pasta
with low-GI pulses lowered the pre-pizza meal BG AUC
(19 –37·5 %) and cumulative BG AUC (15 –30·5 %). Pulses
consumed alone are known to be low-GI foods
(30)
and their
consumption has been suggested for improving BG
control
(31)
; however, this study shows that pulse type is a
factor, with yellow peas being the least effective.
Differences in macronutrient content between the pulse
treatments and pasta and sauce may provide an explanation
of the differences in pre-pizza BG responses. The pulse treat-
ments tended to be higher in protein and fibre and lower in
available carbohydrate content compared to pasta and
sauce, components involved in BG control. However, unlike
the other pulses, yellow peas did not lower pre-pizza meal
BG AUC relative to pasta and sauce and this lack of an
effect was observed at all time points during the pre-pizza
meal period following BG peak (60 –260 min). This is most
likely due to the fact that yellow peas are the highest in avail-
able carbohydrate and lowest in fibre among the pulses.
The present study, supports the hypothesis that lower FI
within the pulse meals is associated with a lower glycaemic
response
(32)
, but found that FI intake at a later meal was not
predicted from the glycaemic response to foods in the earlier
meal. BG immediately before the pizza meal (260 min; r0·17,
P¼0·07) and pre-pizza meal BG AUC (r0·23, P¼0·01) were
positively associated with amount eaten at the pizza meal,
which indicates that a higher and not lower BG response fol-
lowing a previous meal and BG concentrations immediately
before eating are associated with higher FI at the meal.
Which measure of BG is more predictive of meal intake is
uncertain, but may mediate pre-meal concentrations because,
although the pulse treatment meals led to a lower pre-pizza
meal BG AUC of 19 –34 %, they did not reduce FI at the
pizza meal compared with the pasta and sauce meal.
Despite the lack of a suppression of FI after the treatment
with chickpeas, it led to lower post-pizza meal BG AUC com-
pared to navy beans and yellow peas, whereas lentils and
pasta and sauce led to intermediate values. These second
meal effects of chickpeas on BG were not in response to a
higher FI at the pizza meal. Chickpeas resulted in higher FI
at the treatment meal compared to lentils and navy beans,
but did not reduce FI at the pizza meal. In support of this
interpretation, higher FI at the treatment (r20·45,
P,0·0001) and pizza meals (r20·23, P¼0·01) were associ-
ated with lower post-pizza meal BG AUC, suggesting that
when subjects ate more at the treatment and pizza meals,
there was a lower second meal BG response. Whether this
association is due to the amount eaten at the meals or is in
response to components having opposing effects on FI and
second meal BG responses requires investigation.
Pulses, satiation and blood glucose 515
British Journal of Nutrition
The post-pizza meal BG effects are not in response to a
lower pre-meal BG response observed after the pulse meals.
It has been proposed that the second meal effect on BG
occurs in response to the lente carbohydrate features of
low-GI foods
(8,28,29)
. On the basis of the higher pre-meal BG
response and the fact that pulses are a source of lente carbo-
hydrate, it was expected that the pasta and sauce would lead
to the highest post-pizza meal BG response and the response
among the pulse treatments would be similar. However, it was
navy beans and yellow peas that led to the highest post-pizza
meal BG AUC, which was significantly higher compared to
chickpeas. In support of our conclusions, pre-pizza meal BG
AUC was not associated with post-pizza meal BG (r0·04,
P¼0·65). In contrast, BG immediately before consumption of
the pizza meal (260 min) was negatively associated with
post-pizza meal BG (r20·66, P,0·0001), suggesting that a
higher pre-pizza meal BG is a predictor of a lower BG
response to a meal. The current literature is limited beyond
the lente carbohydrate hypothesis, and thus, an explanation
for the second meal effect of chickpeas requires further
investigation.
In conclusion, when incorporated into a meal with high gly-
caemic carbohydrates, pulses maintain their low glycaemic
properties, indicating that regular inclusion in the diet can
be beneficial for BG control. In addition, meals with pulses
can lead to greater satiation, lower cumulative FI and lower
post-pizza meal BG responses compared to a pulse-free
meal, but these effects are dependent on pulse type. Thus,
the addition of pulses to a high-glycaemic meal contributes
to earlier satiation, the reduction of BG both following the
meal and again after a later meal, but these effects are specific
to pulse type.
Acknowledgements
This study was funded by Agriculture and Agri-Food Canada
under the Pulse Research Network. The authors would also
like to acknowledge the assistance of Yudan Liu and Chris
Smith. R. C. M. was involved in the design of the study and
treatments, coordination of the study, and was also respon-
sible for data analysis and writing of the manuscript. A. Z.
was responsible for treatment development, subject recruit-
ment, running sessions, data collection and reviewing of the
manuscript. B. L. L. was involved in design of the study and
responsible for managing students and research assistants,
communication with the funding agency and reviewing the
manuscript. M. F. N. was involved in managing students and
research assistants, data analysis and reviewing of the manu-
script. C. L. W. was responsible for design of the study and
reviewing of the manuscript. G. H. A. was the principal inves-
tigator responsible for conceptualisation and design of the
study, coordination of the research team and reviewing of
the manuscript. The authors declare no conflict of interest.
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Pulses, satiation and blood glucose 517
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Background: Practical risk reduction strategies are needed to address cardiovascular disease. Beans can decrease LDL cholesterol; however, research into different daily amounts and varieties is warranted. Objectives: To examine the effects of canned beans (daily rotation of black, navy, pinto, dark red kidney, white kidney) in 1-cup (1CB, 180 g) and ½-cup (½CB, 90 g) daily amounts compared with a 1-cup white rice (WR) control on serum lipid and glycemic biomarkers in adults with elevated LDL cholesterol. Methods: Adults [n = 73, mean ± SD age: 48.1 ± 14.2 y; BMI (in kg/m2): 25.9 ± 4.22; fasting serum LDL cholesterol: 3.0-5.0 mmol/L] consumed 1CB, ½CB, and WR for 4-wk treatment periods separated by ≥4-wk washouts in a multicenter, randomized, crossover study. Fasting serum LDL cholesterol (primary outcome) and other lipids and glycemic biomarkers (secondary outcomes) were measured on study days 1 and 29 of each treatment period with study day 29 values compared using repeated-measures ANCOVA, including study day 1 values as covariates. Results: Treatment completion was n = 66 for 1CB, n = 68 for ½CB, and n = 64 for WR. Total cholesterol on study day 29 was lower for 1CB (P = 0.04) but not ½CB (P = 0.77) compared with WR (-5.46%, -2.74%, -0.65% changes from study day 1, respectively) and did not differ between 1CB and ½CB (P = 0.17). LDL cholesterol on study day 29 was also lower for 1CB (P = 0.002) but not ½CB (P = 0.30) compared with WR (-8.08%, -3.84%, +0.49% changes from study day 1, respectively) and did not differ between 1CB and ½CB (P = 0.11). Other lipids and glycemic biomarkers did not differ among treatments. Conclusions: Consumption of 1 cup (180 g) of canned beans of multiple varieties decreased total and LDL cholesterol in adults with elevated LDL cholesterol, supporting a practical strategy for cardiovascular disease risk reduction. This trial was registered at clinicaltrials.gov as NCT03830970.
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Research investigating hemp protein consumption on glycemic response is limited. The effects of hemp protein consumption on blood glucose (BG), insulin, and satiety compared with soybean protein and a carbohydrate control were examined. Two acute randomized repeated-measures crossover experiments were conducted. In both, participants consumed the following isocaloric treatments: 40 g of hemp protein (hemp40), 20 g of hemp protein (hemp20), 40 g of soybean protein (soy40), 20 g of soybean protein (soy20), and a carbohydrate control. In experiments 1 (n = 27) and 2 (n = 16), appetite and BG were measured before (0–60 min, pre-pizza) and after a pizza meal (80–200 min, post-pizza). In experiment 1, food intake was measured at 60 min by ad libitum meal; in experiment 2 a fixed meal was provided (based on body weight) and insulin was measured pre-pizza and post-pizza. In both experiments, BG response was affected by treatment (p < 0.01), time (p < 0.001) and time-by-treatment (p < 0.001) from 0–200 min. Protein treatments lowered 0–60-min BG overall mean and area under the curve compared with control (p < 0.05) dose-dependently. In experiment 2, hemp40 and soy40 lowered (p < 0.05) overall mean insulin concentrations compared with hemp20, soy20, and control pre-meal. Results suggest that hemp protein, like soybean, dose-dependently lowers postprandial BG and insulin concentrations compared with a carbohydrate control. Clinical trial registry: NCT02366598 (experiment 1) and NCT02458027 (experiment 2). Novelty: Hemp protein concentrate dose-dependently leads to lower postprandial BG response compared with a carbohydrate control. No differences were seen between hemp and soy protein.
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Pulses are low in energy density, supporting their inclusion in the diet for the management of risk factors of the metabolic syndrome (MetSyn). The aim of the present study was to describe the effects of frequent consumption (five cups/week over 8 weeks) of pulses (yellow peas, chickpeas, navy beans and lentils), compared with counselling to reduce energy intake by 2093 kJ/d (500 kcal/d), on risk factors of the MetSyn in two groups (nineteen and twenty-one subjects, respectively) of overweight or obese (mean BMI 32·8 kg/m2) adults. Body weight, waist circumference, blood pressure, fasting blood parameters and 24 h food intakes were measured at weeks 1, 4 and 8. Blood glucose, insulin, C-peptide, glucagon-like peptide-1 (GLP-1) and ghrelin were measured after a 75 g oral glucose load at weeks 1 and 8. At week 8, both groups reported reductions in energy intake, waist circumference, systolic blood pressure, glycosylated Hb (HbA1c) and glucose AUC and homeostasis model of insulin resistance (HOMA-IR) following the glucose load (P < 0·05). However, HDL, fasting C-peptide and insulin AUC responses were dependent on diet (P < 0·05). HDL and C-peptide increased by 4·5 and 12·3 %, respectively, in the pulse group, but decreased by 0·8 and 7·6 %, respectively, in the energy-restricted group. Insulin AUC decreased in both females and males on the energy-restricted diet by 24·2 and 4·8 %, respectively, but on the pulse diet it decreased by 13·9 % in females and increased by 27·3 % in males (P < 0·05). In conclusion, frequent consumption of pulses in an ad libitum diet reduced risk factors of the MetSyn and these effects were equivalent, and in some instances stronger, than counselling for dietary energy reduction.
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Diets containing beans have been associated with a lower risk of obesity and overweight in several dietary surveys. These results suggest a benefit might be derived from beans and other pulses, possibly due to improved satiety or satiation and therefore lowering energy intake. Such a hypothesis has not been tested. To investigate the effect of processing, recipe, and pulse variety on short-term food intake (FI), subjective appetite, and glycemic response after pulse consumption in healthy young men. Three experiments were conducted. In a randomized repeated-measures design, young men aged 18-35 years with a body mass index of 20-25 kg/m(2) were fed the test treatments. In experiment 1 (n = 14), navy beans canned in Canada or in the United Kingdom were compared with homemade navy beans and 300 ml of glucose drink, each containing 50 g of available carbohydrate. In experiment 2 (n = 14), canned navy beans in tomato sauce, maple style, with pork and molasses, and homemade navy beans with pork and molasses were compared with white bread, each containing 50 g of available carbohydrate. In experiment 3 (n = 15), 4 equicaloric (300-kcal) treatments of pulses were compared with both a white bread and water control. Blood glucose and subjective appetite were measured from immediately before consumption of the treatment to 120 minutes later when FI from a pizza meal was measured. All caloric treatments decreased subjective appetite. In no experiment did any pulse treatment lower FI at 120 minutes compared with white bread or result in lower cumulative FI (sum of calories from treatment and pizza meal) compared with either 50 g of available carbohydrate as a glucose drink (experiment 1) or from white bread (experiment 2) or compared with equal food energy from white bread (experiment 3). Glycemic response to navy beans was affected by recipe, but not processing, and as with the other pulses, it was lower than with white bread. An inverse relationship was observed between glycemic response and both subjective appetite and FI at 120 minutes in experiment 3 (r = -0.4, p = 0.001) but not in experiments 1 (r = 0.1, p = 0.62) and 2 (r = 0.2, p = 0.10). The short-term effect of pulse consumption on subjective appetite and FI at a meal 120 minutes later and in cumulative food intake was determined primarily by energy content and was little influenced by composition, processing, recipe, or variety. Thus, the epidemiological associations between frequent pulse consumption and lower risk of obesity and overweight are not explained by short-term effect of pulses on satiety and FI.
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Starch composition and rate of digestion are determinants of blood glucose concentrations and food intake (FI). Our objective was to describe relations between estimates of digestibility of starches by the in vitro Englyst method and their effect on blood glucose concentrations, subjective appetite, and FI in young men. Subjects consumed 5 soups containing 50 g maltodextrin, whole-grain, high-amylose, regular cornstarch, or no added starch at 1-wk intervals. Ad libitum FI was measured at 30 min (experiment 1) or 120 min (experiment 2) later, which were the estimated times of digestion of a rapidly digestible starch (RDS) and slowly digestible starch, respectively. Blood glucose concentrations and appetite were measured pre- and postmeal. At 30 min, FI was reduced by maltodextrin only [86% RDS, 12% resistant starch (RS); P < 0.05], but at 120 min FI was reduced by whole-grain (24% RDS, 66% RS), high-amylose corn (40% RDS, 48% RS), and regular corn (27% RDS, 39% RS) (P < 0.0001). The premeal blood glucose concentration at 30 and 120 min was highest and lowest after maltodextrin treatment, respectively (P < 0.0001). After the meal, the blood glucose area under the curve at 30 min was lower after all starch treatments (P < 0.05), but at 120 min the blood glucose area under the curve was lower only after the regular cornstarch treatment (P < 0.05). Premeal appetite decreased by all treatments (P < 0.05). The in vitro estimates of starch digestibility by the Englyst method predicted the effects of starch composition on blood glucose concentrations and FI in young men 30 and 120 min after consumption. This trial was registered at clinicaltrials.gov as NCT00980941 for experiment 1 and NCT00988689 for experiment 2.
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Background: Glucose meters are convenient for measuring postprandial glycemic responses. However, their performance for this purpose has not been evaluated. Methods: Glucose responses of 7 potato meals were measured using the One Touch Ultra((R)) (OTU) glucose meter and a reference method (Yellow Springs Instruments Glucose Analyzer, YSI) and the incremental areas under the curves (AUC) and glycemic index (GI) values compared. Results: Mean AUC(OTU) was greater than AUC(YSI) (192 +/- 8 vs. 175 +/- 7 mmol x min/l, p=0.001), but GI(OTU) tended to be less than Glys, (69 +/- 3 vs. 74 +/- 3, p =0.052). Bland-Altman difference plots showed wide 95% limits of agreement for AUC (-84 to 119 mmol x min/1) and GI (-21 to 26) values of individual subjects, and for the mean GI values of the 7 foods (- 11 to 21). Total and error variance of AUC and GI values were greater for OTU than YSI, and food means differed significantly for YSI (p < 0.01) but not OTU (p=0.11). Conclusion: AUC and GI values determined by OTU are more variable and do not agree well with those obtained by YSL Thus, the OTU is not recommended for determining AUC or GI in normal subjects. This conclusion does not necessarily apply to other glucose meters whose performance should be evaluated. (c) 2005 Elsevier B.V. All rights reserved.
Article
High-protein preloads have been shown to enhance satiety, but little is known about the satiating effects of protein in more typical situations when meals are consumed ad libitum. To investigate the effects of protein in amounts commonly consumed over a day, a crossover study was conducted in 2008. In this experiment, 18 normal-weight women consumed ad libitum lunch and dinner entrées 1 day a week that were covertly varied in protein content (10%, 15%, 20%, 25%, or 30% energy). Entrées were manipulated by substituting animal protein for starchy ingredients and were matched for energy density, fat content, palatability, and appearance. Unmanipulated breakfasts and evening snacks were consumed ad libitum. Participants rated their hunger and fullness before and after meals as well as the taste and appearance of entrées. Data were analyzed using a mixed linear model. Results showed that mean 24-hour protein intake increased significantly across conditions, from 44±2 g/day in the 10% protein condition to 82±6 g/day in the 30% condition. Daily energy intake did not differ significantly across the 10% to 30% protein conditions (means 1,870±93, 1,887±93, 1,848±111, 1,876±100, and 1,807±98 kcal in the 10%, 15%, 20%, 25%, and 30% energy groups, respectively). There were no significant differences in hunger and fullness ratings across conditions or in taste and appearance ratings of the manipulated entrées. This study showed that varying the protein content of several entrées consumed ad libitum did not differentially influence daily energy intake or affect ratings of satiety.
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It is hypothesized that a solid form of food or food components suppresses subjective appetite and short-term food intake (FI) more than a liquid form. To compare the effect of eating solid vs drinking liquid forms of gelatin, sucrose and its component mixtures, and whey protein, on subjective appetite and FI in young men. A randomized crossover design was used in three experiments in which the subjects were healthy males of normal weight. Solid and liquid forms of gelatin (6 g) (experiment 1, n=14), sucrose (75 g) and a mixture of 50% glucose/50% fructose (G50:F50) (experiment 2, n=15), and acid and sweet whey protein (50 g) (experiment 3, n=14) were compared. The controls were water (experiments 1 and 3) and calorie-free sweetened water with gelatin (sweet gelatin, experiment 1) or calorie-free sweetened water (sweet control, experiment 2). Subjective average appetite was measured by visual analog scales over 1 h and ad libitum FI was measured 1 h after treatment consumption. Average appetite area under the curve was not different between solid and liquid forms of sugars, but was larger, indicating greater satiety for solid compared with liquid forms of gelatin and sweet, but not acid whey protein. The FI was not different from that of control because of solid or liquid sugars or gelatin treatments. However, both solid and liquid forms of whey protein, with no difference among them, suppressed FI compared with control (P<0.05). Macronutrient composition is more important than physical state of foods in determining subjective appetite and FI.
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Phenylketonuria (PKU) requires a lifelong low-phenylalanine (phe) diet where protein needs are met by consumption of a phe-free amino acid (AA) formula; complaints of persistent hunger are common. Foods made with glycomacropeptide (GMP), an intact protein that contains minimal phe and may promote satiety, provide an alternative to AA formula. The objective was to assess the ability of a GMP breakfast to promote satiety and affect plasma concentrations of AAs, insulin, and the appetite stimulating hormone ghrelin in those with PKU, when compared to an AA-based breakfast. Eleven PKU subjects (8 adults and 3 boys ages 11-14) served as their own controls in an inpatient metabolic study with two 4-day treatments: an AA-based diet followed by a diet replacing all AA formula with GMP foods. Plasma concentrations of AAs, insulin and ghrelin were obtained before and/or 180 min after breakfast. Satiety was assessed using a visual analog scale before, immediately after and 150 min after breakfast. Postprandial ghrelin concentration was significantly lower (p=0.03) with GMP compared to an AA-based breakfast, with no difference in fasting ghrelin. Lower postprandial ghrelin concentrations were associated with greater feelings of fullness after breakfast suggesting greater satiety with GMP compared to AAs. Postprandial concentrations of insulin and total plasma AAs were higher after a GMP breakfast compared to an AA-based breakfast consistent with slower absorption and less degradation of AAs from GMP. These results show sustained ghrelin suppression, and suggest greater satiety with ingestion of a meal containing GMP compared with AAs.
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Dairy protein ingestion before a meal reduces food intake and, when consumed with carbohydrate, reduces blood glucose. The objective was to describe the effect of whey protein (WP) or its hydrolysate (WPH) when consumed before a meal on food intake, pre- and postmeal satiety, and concentrations of blood glucose and insulin in healthy young adults. Two randomized crossover studies were conducted. WP (10-40 g) in 300 mL water was provided in experiment 1, and WP (5-40 g) and WPH (10 g) in 300 mL water were provided in experiment 2. At 30 min after consumption, the subjects were fed an ad libitum pizza meal (experiment 1) or a preset pizza meal (12 kcal/kg, experiment 2). Satiety, blood glucose, and insulin were measured at baseline and at intervals both before and after the meals. In experiment 1, 20-40 g WP suppressed food intake (P < 0.0001) and 10-40 g WP reduced postmeal blood glucose concentrations and the area under the curve (AUC) (P < 0.05). In experiment 2, 10-40 g WP, but not WPH, reduced postmeal blood glucose AUC and insulin AUC in a dose-dependent manner (P < 0.05). The ratio of cumulative blood glucose to insulin AUCs (0-170 min) was reduced by > or =10 g WP but not by 10 g WPH. WP consumed before a meal reduces food intake, postmeal blood glucose and insulin, and the ratio of cumulative blood glucose to insulin AUCs in a dose-dependent manner. Intact WP, but not WPH, contributes to blood glucose control by both insulin-dependent and insulin-independent mechanisms. This trial was registered at clinicaltrials.gov as NCT00988377 and NCT00988182.