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The present study examined the impact of breakfast and exercise on postprandial metabolism, appetite and macronutrient balance. A sample of twelve (blood variables n 11) physically active males completed four trials in a randomised, crossover design comprising a continued overnight fast followed by: (1) rest without breakfast (FR); (2) exercise without breakfast (FE); (3) breakfast consumption (1859 kJ) followed by rest (BR); (4) breakfast consumption followed by exercise (BE). Exercise was continuous, moderate-intensity running (expending approximately 2·9 MJ of energy). The equivalent time was spent sitting during resting trials. A test drink (1500 kJ) was ingested on all trials followed 90 min later by an ad libitum lunch. The difference between the BR and FR trials in blood glucose time-averaged AUC following test drink consumption approached significance (BR: 4·33 (sem 0·14) v. FR: 4·75 (sem 0·16) mmol/l; P= 0·08); but it was not different between FR and FE (FE: 4·77 (sem 0·14) mmol/l; P= 0·65); and was greater in BE (BE: 4·97 (sem 0·13) mmol/l) v. BR (P= 0·012). Appetite following the test drink was reduced in BR v. FR (P= 0·006) and in BE v. FE (P= 0·029). Following lunch, the most positive energy balance was observed in BR and least positive in FE. Regardless of breakfast, acute exercise produced a less positive energy balance following ad libitum lunch consumption. Energy and fat balance is further reduced with breakfast omission. Breakfast improved the overall appetite responses to foods consumed later in the day, but abrogated the appetite-suppressive effect of exercise.
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Breakfast and exercise contingently affect postprandial metabolism and
energy balance in physically active males
Javier T. Gonzalez
1
*, Rachel C. Veasey
1
, Penny L. S. Rumbold
2
and Emma J. Stevenson
1
1
Brain, Performance and Nutrition Research Centre, School of Life Sciences, Northumbria University, Northumberland
Building, Newcastle upon Tyne NE1 8ST, UK
2
Department of Sport and Exercise Sciences, School of Life Sciences, Northumbria University, Northumberland Building,
Newcastle upon Tyne NE1 8ST, UK
(Submitted 30 July 2012 – Final revision received 4 October 2012 – Accepted 14 November 2012)
Abstract
The present study examined the impact of breakfast and exercise on postprandial metabolism, appetite and macronutrient balance.
A sample of twelve (blood variables n11) physically active males completed four trials in a randomised, crossover design comprising a
continued overnight fast followed by: (1) rest without breakfast (FR); (2) exercise without breakfast (FE); (3) breakfast consumption
(1859 kJ) followed by rest (BR); (4) breakfast consumption followed by exercise (BE). Exercise was continuous, moderate-intensity running
(expending approximately 2·9 MJ of energy). The equivalent time was spent sitting during resting trials. A test drink (1500 kJ) was ingested
on all trials followed 90 min later by an ad libitum lunch. The difference between the BR and FR trials in blood glucose time-averaged
AUC following test drink consumption approached significance (BR: 4·33 (SEM 0·14) v. FR: 4·75 (SEM 0·16) mmol/l; P¼0·08); but it
was not different between FR and FE (FE: 4·77 (SEM 0·14) mmol/l; P¼0·65); and was greater in BE (BE: 4·97 (SEM 0·13) mmol/l) v.BR
(P¼0·012). Appetite following the test drink was reduced in BR v.FR(P¼0·006) and in BE v.FE(P¼0·029). Following lunch, the most
positive energy balance was observed in BR and least positive in FE. Regardless of breakfast, acute exercise produced a less positive
energy balance following ad libitum lunch consumption. Energy and fat balance is further reduced with breakfast omission. Breakfast
improved the overall appetite responses to foods consumed later in the day, but abrogated the appetite-suppressive effect of exercise.
Key words: Appetite: Fasted state: Glycaemia: Fat oxidation
Regular breakfast consumption has been inversely associated
with BMI
(1)
, yet it is not clear whether this association is due
to differences in energy expenditure, metabolism or energy
intake. Although the ostensible benefits of regular breakfast
consumption could be due to improved diet composition
with breakfast cereals
(1)
, rather than meal pattern per se,
acute consumption of breakfast can enhance glucose
tolerance, insulin sensitivity and subjective and physiological
satiety responses to a test drink
(2)
.
A recent position statement concluded that further research
is required in regular exercisers with regards to meal pattern,
metabolism and appetite regulation
(3)
, as research in exercis-
ing individuals in this area is sparse. However, this population
do use diet/exercise strategies, such as training in the fasted
state, to control body fat/mass and improve metabolic
adaptations to training
(4)
. Exercise attenuates adverse dietary
outcomes such as fat-induced glucose intolerance
(5)
, and the
nutritional state in which exercise is performed can modulate
the magnitude of these improvements
(5)
. Exercise in the fasted
state results in a greater reliance on fat as a substrate
(6)
and
has led to its use as a tool to reduce body fat by athletes
(4)
.
Training in the fasted state also leads to enhanced fat transpor-
ter protein mRNA content
(5)
, mitochondrial enzyme activity
and maximal aerobic capacity
(7)
, making exercise in the
fasted state an attractive proposition for both recreational
and elite athletes. On the other hand, high carbohydrate avail-
ability during exercise training may result in improved body
composition, as gains in fat-free mass are amplified, whilst
fat loss is similar
(8)
. Hence, although there is a suggestion
that exercise in the fasted state can maximise some benefits
already associated with exercise, ensuing effects on appetite
and metabolism are not entirely clear.
The regulation of acute energy balance involves (not
exclusively) the exposure and sensitivity to the circulating
*Corresponding author: J. T. Gonzalez, fax þ44 191 243 7012, email javier.gonzalez@northumbria.ac.uk
Abbreviations: AUC
INS/GLU
, serum insulin AUC to blood glucose AUC ratio; BE, overnight fast followed by breakfast and exercise; BR, overnight fast
followed by breakfast and rest; FE, overnight fast followed by exercise without breakfast; FR, overnight fast followed by rest without breakfast; GLP-1,
glucagon-like peptide 1; ISI
Matsuda
, Matsuda insulin sensitivity index; VAS, visual analogue scale.
British Journal of Nutrition, page 1 of 12 doi:10.1017/S0007114512005582
qThe Authors 2013
British Journal of Nutrition
hormonal and metabolic milieu
(9)
, which underscores the
importance of determining these changes concomitant with
measuring energy balance. Exercise training improves glucose
tolerance
(5)
, yet acute exercise effects are less lucid
(10 – 13)
.
Muscle glucose uptake is increased after exercise
(14)
,as
assessed in rat hindlimb muscle. However, both this method
and the most commonly used technique for assessing insulin
sensitivity in human subjects (the euglycaemic hyperinsuli-
naemic clamp) possess some caveats. First, they ignore the
gastrointestinal response to food ingestion. Direct contact of
nutrients with L-cells in the intestine stimulates secretion of
glucagon-like peptide 1 (GLP-1), which potentiates insulin
secretion and sensitivity and reduces food intake
(9)
. GLP-1
exists in two active forms; in human subjects, the primary
circulating form is GLP-1
7–36(9)
. Acute exercise has been
shown to increase GLP-1 concentrations in the fed state
(15)
.
Therefore, GLP-1 may be an important mediator in the
acute regulation of energy homeostasis regarding breakfast
consumption and exercise.
Second, provision of nutrients other than glucose can
influence glucose tolerance and insulin sensitivity. Protein,
for example, stimulates insulin and/or incretin hormone
secretion
(16)
. Flavoured milk providing mixed macronutrients
is an increasingly consumed post-exercise drink due to its
recovery-enhancing potential
(17)
. Therefore, assessing the
whole-body metabolic and endocrine response to an orally
ingested mixed-nutrient load provides more applicable
findings to regular exercisers. Acute exercise can transiently
suppress hunger
(15,18)
, possibly via changes in appetite-related
hormones
(15,18,19)
. Subsequent relative energy intake is usually
also reduced
(18,19)
. The influence of nutritional status on
appetite regulation and energy intake following exercise is
not entirely understood. Of the studies investigating appetite
responses to fasted v. fed exercise, one used a high-fat
(70 %) meal
(20)
, which is not representative of a typical break-
fast, and another compared meal-exercise sequence rather
than omission of breakfast per se
(21)
.
Accordingly, the aim of the present study was to explore
the interaction of breakfast consumption and exercise on the
metabolic, endocrine and appetite responses to a commonly
consumed post-exercise drink, and to assess subsequent
energy intake and macronutrient balance in physically
active males.
Materials and methods
Participants
A group of twelve healthy males was recruited from the
student and staff population at Northumbria University
between December 2010 and April 2011. All participants
gave informed written consent and completed the entire
study. Participants who self-reported as physically inactive,
defined by less than 30 min of moderate activity, five times
per week by the International Physical Activity Question-
naire
(22)
; restrained eaters, defined by a score of .11 on
the Three Factor Eating Questionnaire
(23)
; or those with
any metabolic disorders or on medications were omitted.
The protocol was approved by the School of Life Sciences
Ethics Committee at Northumbria University.
Preliminary measurements
Participants undertook preliminary tests to establish: (1) the
relationship between O
2
uptake and running speed on a flat
treadmill (Woodway ELG, Woodway) using a four-stage,
16 min test; (2) their V
O2peak
using an incremental treadmill
test, whereby the gradient was increased by 1 %/min to
exhaustion, as described previously in detail
(24)
. The duration
of the exercise period in the main trials was calculated from
submaximal O
2
uptake and CO
2
values in order to expend
2·9 MJ (693 kcal) of energy whilst running at a speed estimated
to elicit 60 % V
O2peak
. This value was chosen to equate to
approximately 1 h on average, whilst maintaining similar
energy expenditure across participants. On the same day, par-
ticipants were familiarised with the visual analogue scales
(VAS) to assess subjective appetite sensations in main trials,
and it was verbally confirmed that participants did not have
any particular disliking of foods contained in the test meals.
Experimental design
All participants completed four trials in a randomised
(performed by J. T. G with Research Randomizer version 3.0;
http://www.randomizer.org/), crossover design separated by
$7 d comprising a continued overnight fast followed by:
(1) rest without breakfast (FR); (2) exercise without breakfast
(FE); (3) breakfast consumption (1859 kJ) followed by rest
(BR); and (4) breakfast consumption followed by exercise
(BE). By necessity of the design (food intake and exercise),
the intervention was not blinded. All trials were performed
under similar laboratory conditions (ambient temperature,
humidity and pressure; all P.0·05; data not shown). Food and
fluid diaries were kept for the day preceding the first trial and
participants were instructed to replicate this for all subsequent
trials. Alcohol, caffeine and vigorous activity were prohibited
for 24 h prior to trials.
On trial days, participants arrived in the laboratory at 07.30
hours after a 1014 h fast and a cannula was inserted into an
antecubital vein for blood sampling. After baseline samples of
expired gas and VAS were taken, in breakfast trials (BE and
BR), participants consumed a porridge breakfast. In fasting
trials (FE and FR), participants were permitted to consume
water only, which was consumed ad libitum on the first
exercise and non-exercise trials, and water consumption was
replicated for the following exercise and non-exercise trials
(Fig. 1). Following 120 min of rest, during exercise trials (BE
and FE), participants ran on a treadmill at 61·1 (SEM 0·6) %
V
O2peak
for 59 (SEM 2) min based on the a priori estimated
energy expenditure. Treadmill speed was adjusted accordingly
on the first trial to obtain the appropriate V
O2
. Changes in
speed were noted for duplication in subsequent exercise
trials. In resting trials (BR and FR), participants rested for the
equivalent amount of time as the exercise trials.
Within 20 min of exercise termination, participants ingested
a chocolate milk test drink. Following a 90 min postprandial
J. T. Gonzalez et al.2
British Journal of Nutrition
period, a homogeneous ad libitum test lunch was provided.
Participants were provided with an initial 430 g (3694 kJ;
882 kcal) portion of the test meal, which was replaced upon
completion. The test meal was terminated when the partici-
pant instructed that they felt ‘comfortably full’. Participants
were constantly reminded to follow this instruction and
were always presented with fresh, warmed portions before
participant-induced termination to ensure that the end of a
portion was not the reason for meal termination. Remaining
food was then removed and weighed out of the sight of the
participants to determine energy intake.
Anthropometric measurements
Body mass was determined to the nearest 0·1 kg using balance
scales (Seca) upon arrival at the laboratory, immediately prior
to and following exercise, where participants wore only light
clothing. Height was measured to the nearest 0·1 cm using a
stadiometer (Seca).
Test meals
The breakfast consisted of 72 g oats (Oatso Simple Golden
Syrup, Quaker Oats) and 360 ml semi-skimmed milk (Tesco)
and provided 1859 kJ of energy (444 kcal; 17 % protein, 60 %
carbohydrate and 23 % fat). The test drink was 500 ml of
chocolate milk (Yazoo, Campina Limited) and contained
1500 kJ of energy (358; 18 % protein, 63 % carbohydrate and
19 % fat). The test lunch comprised pasta (Tesco), tomato
sauce (Tesco), cheddar cheese (Tesco) and olive oil (Tesco)
and provided 859 kJ of energy per 100 g of food (205 kcal;
14 % protein, 52 % carbohydrate and 34 % fat).
Blood sampling and analysis
Blood samples, 10 ml, were collected at baseline, immediately
prior to and following exercise (or the equivalent points in
resting trials) at 15, 30, 50, 70 and 90 min following consump-
tion of the test drink (immediately prior to the test meal). All
samples were obtained whilst participants were seated upright
to control for postural changes in plasma volume. Additional
5 ml samples were collected at 5, 10, 20 and 25 min following
test drink ingestion, where blood glucose was determined
immediately by a glucose analyser (Biosen C_line, EKF
Diagnostics). From the 10 ml samples, a 20 ml capillary tube
was filled with whole blood to determine blood glucose
concentrations, 4 ml was dispensed into an EDTA vacutainer
containing 100 ml aprotinin and immediately centrifuged
at 3000 rpm at 48C for 10 min. Plasma was stored for later
determination of GLP-1
7–36
using an immunoassay (Phoenix
Pharmaceuticals, Inc.). Remaining whole blood from 10 ml
samples was allowed to stand for 30 min in a non-anticoagulant
tube before being centrifuged at 3000 rpm at 48C for 10 min.
Aliquots of serum were then stored for later determination of
NEFA (WAKO Diagnostics) and insulin (DIAsource Immuno-
Assays S.A.) concentrations in duplicate. All plasma/serum
samples were stored at 2808C. The intra-assay CV were 5·6
and 7·2 % for NEFA and insulin, respectively. Inter-assay CV
were 8·1, 3·6 and 18·5 % for NEFA, insulin and GLP-1
7–36
,
respectively. In order to reduce the inter-assay variation,
samples from each participant were analysed during the same
run where possible. It was decided that it was unnecessary to
adjust analyte concentrations to account for plasma volume
changes, as exercise of a similar and greater intensity and
duration does not result in changes in plasma volume
(15,25)
.
Energy expenditure and substrate oxidation
Expired gas samples were collected using an online gas
analysis system (Metalyzer 3B, Cortex) calibrated using gases
of known concentrations and a 3 l syringe. Participants wore a
facemask and after a 2 min stabilisation phase, 5 min samples
were obtained and averaged at baseline, at every 30 min after
breakfast consumption (or equivalent time in breakfast omis-
sion trials) and at 5, 15, 30, 50, 70 and 90 min following consump-
tion of the test drink. Expired gas was continuously sampled
throughout the exercise and averaged over each 5 min period,
ignoring the first 5 min to allow for steady-state values.
Substrate metabolism was calculated, assuming negligible
protein oxidation, with V
O2
and CO
2
production values using
stoichiometric equations and was adjusted during exercise to
account for the contribution of glycogen to metabolism
(26)
:
Rate of fat oxidation at rest and during exercise ðg=minÞ
¼ð1:695 £VO2 Þ2ð1:701 £VCO2Þ:
Rate of carbohydrate oxidation at rest ðg=minÞ
¼ð4:585 £VCO2 Þ2ð3:226 £VO2Þ:
Rate of carbohydrate oxidation during exercise ðg=minÞ
¼ð4:210 £VCO2Þ2ð2:962 £VO2Þ:
V
O2
and V
CO2
are measured in litres/min.
Energy expenditure was calculated based on fat, glucose
and glycogen concentrations providing 40·81, 15·64 and
17·36 kJ/g of energy, respectively. At rest, calculations were
based on glucose providing all of the carbohydrate for
metabolism, whereas during moderate-intensity exercise,
Visual analogue scales and expired
gas sample
Test
drink
Exercise
2 h rest
or
60 % VO2peak
2·9 MJ or
rest
15 30
Time (min)
50 70 90
Ad libitum
lunch
Fig. 1. Schematic representation of trials. , Breakfast consumption; , blood sample.
Integrated effects of breakfast and exercise 3
British Journal of Nutrition
carbohydrate oxidation is met by both glucose and glycogen
providing a 20 and 80 % contribution, respectively
(26)
.
Subjective ratings
Paper-based 100 mm VAS were completed at baseline, prior to
and immediately following breakfast and at every 30 min
thereafter until exercise (or equivalent time points in breakfast
omission trials); further, VAS were completed immediately
following exercise and after test drink consumption and at
30 min intervals thereafter. Final VAS were completed follow-
ing termination of the test meal. Questions asked were used
to determine hunger, fullness, satisfaction and prospective
food consumption. An overall appetite score was calculated
using the following formula, as previously used
(27)
:
Overall appetite
¼ðhunger þprospective food consumption
þð100 – fullnessÞþð100 – satisfactionÞÞ=4:
Statistical analysis
Due to difficulties associated with blood collection, data for
GLP-1
7–36
are presented from ten participants and, for all
other blood analytes, from eleven participants. After the
consumption of the test drink, glucose, insulin, GLP-1
7–36
and NEFA concentrations and appetite sensations were con-
verted into AUC using the trapezoidal rule. Indices of insulin
secretion and sensitivity, post-test drink serum insulin AUC
to blood glucose AUC ratio (AUC
INS/GLU
) and Matsuda insulin
sensitivity index (ISI
Matsuda
) were calculated as described pre-
viously
(28,29)
. Unless otherwise stated, all data are presented as
mean values with their standard errors. One-way, repeated
measures ANOVA was used to determine differences at base-
line, between all AUC values and total fat and carbohydrate
oxidation and energy expenditure between trials. Two-way
repeated measures ANOVA (trial £time) was used to detect
differences for all variables, and following a significant inter-
action effect, simple main effects analyses were employed.
This approach allowed for a comparison between the four
conditions (FR, FE, BR and BE) across time to determine
the most appropriate diet/exercise strategy. The Holm
Bonferroni step-wise post hoc test was utilised to determine
the location of the variance, and all Pvalues reported have
already been adjusted for multiple comparisons. Differences
were considered significant at P,0·05.
Results
The participants’ age, height, body mass, BMI and peak O
2
uptake (V
O2peak
) were 23·2 (SD 4·3) years, 178·0 (SD 7·0) cm,
77·2 (SD 5·3) kg, 24·5 (SD 2·0) kg/m
2
and 53·1 (SD 5·5) ml/kg
per min, respectively.
Blood glucose
Blood glucose concentration displayed a trial £time inter-
action effect (Fig. 2(A); P,0·001). Breakfast consumption
reduced time to reach peak blood glucose concentration
following test drink ingestion by 10 and 4 min during rest
and exercise trials, respectively (P¼0·012 and P¼0·02,
respectively). Peak blood glucose concentration was unaf-
fected by breakfast consumption during resting trials (FR:
5·95 (SEM 0·20) mmol/l, BR: 5·75 ( SEM 0·14) mmol/l; P¼0·20).
No difference was observed in peak or in time to peak
blood glucose concentrations in FR v. FE trials (P¼0·73 and
P¼0·28, respectively). However, in BE, blood glucose concen-
tration reached 6·66 (SEM 0·24) mmol/l, significantly greater
than FE (5·89 (SEM 0·17) mmol/l; P¼0·06) and BR (P¼0·030).
The difference between the BR and FR trials in AUC for
blood glucose approached statistical significance (Fig. 2(B);
P¼0·09); but it was not significantly different between
the FR and FE trials (P¼0·65); and was greater in BE v.BR
trials (P¼0·012).
FR BR FE BE
Trial
3·0
3·5
4·0
Time-averaged blood
glucose AUC (mmol/l)
Blood glucose
concentration (mmol/l)
4·5
5·0
(B)
(A)
3·0
BLPE 0 102030405060708090
Time post-drink (min)
*
*†§||
a,b,c
‡¶
*‡¶
‡||¶ ||
||
*
§
EX
b,c
b
a
3·5
4·0
4·5
5·0
5·5
6·0
6·5
Fig. 2. (A) Blood glucose concentration in response to test drink consumption
in the overnight fast followed by rest without breakfast (FR, W), overnight fast
followed by breakfast and rest (BR, X), overnight fast followed by exercise
(EX) without breakfast (FE, D) and overnight fast followed by breakfast and
EX (BE, O) trials. BL, baseline; PE, pre-EX. Values are means, with their
standard errors represented by vertical bars. * Mean value for the FE trial
was significantly different from that of BR trial (P,0·05). † Mean value for the
FR trial was significantly different from that of FE trial (P,0·05). ‡ Mean
value for the FR trial was significantly different from that of BE trial (P,0·05).
§ Mean value for the BR trial was significantly different from that of FE trial
(P,0·05). kMean value for the BR trial was significantly different from that of
BE trial (P,0·05). {Mean value for the FE trial was significantly different
from that of BE trial (P,0·05). (B) Time-averaged blood glucose AUC follow-
ing test drink consumption.
a,b,c
Values with unlike letters were significantly
different (P,0·05).
J. T. Gonzalez et al.4
British Journal of Nutrition
Serum insulin
A trial £time interaction effect was observed for serum
insulin concentrations (P,0·001), where peak concentrations
occurred at 37 (SEM 3) min in the FR trial, and the delay
compared with BR (29 (SEM 1) min; P¼0·09) and FE
(30 (SEM 4) min; P¼0·10) approached statistical significance.
Serum insulin concentrations rose after test drink consump-
tion (Fig. 3(A)) to a similar peak between trials (FR: 682
(SEM 71), BR: 607 (SEM 46), FE: 570 (SEM 72) and BE: 586 (SEM
64) pmol/l; P¼0·21). The greater AUC for serum insulin in FR
v. all other trials approached statistical significance (Fig. 3(B);
P¼0·07, P¼0·12 and P¼0·09 for BR, FE and BE, respectively).
Indices of insulin secretion and sensitivity
The AUC
INS/GLU
was similar between FR and BR trials (82
(SEM 7) and 80 (SEM 6) pmol/mmol; P¼0·45), but was reduced
by exercise compared with the FR trial (FE: 70 (SEM 7) and BE:
67 (SEM 6) pmol/mmol; P¼0·03 and P¼0·04 for FE and BE
trials, respectively). ISI
Matsuda
was similar between the trials
(12 (SEM 4), 12 (SEM 4), 12 (SEM 4) and 13 (SEM5) arbitrary units
for FR, BR, FE and BE respectively; all P.0·05).
Serum NEFA
Test drink consumption transiently suppressed NEFA concen-
trations and a significant trial £time interaction effect was
observed (Fig. 4(A); P,0·001). The time at which the nadir of
NEFA concentrations was reached was delayed in the FR trial (81
(SEM 3) min) compared with all other trials (BR: 65 (SEM 3) min,
P¼0·019; FE: 57 (SEM 3) min, P,0·001; and BE: 55 (SEM 6) min,
P¼0·007). The AUC for BR was lower than that for FR and
BE trials (Fig. 4(B); P¼0·019 and P¼0·004, respectively).
Plasma glucagon-like peptide 1
7–36
There was no trial £time interaction effect or main effects of
trial on GLP-1
7–36
concentrations (Fig. 5(A); both P.0·05).
FR BR FE BE
Trial
0·0
0·1
Time-averaged serum
NEFA AUC (mmol/l)
Serum NEFA
concentration (mmol/l)
0·2
0·3
0·4(B)
(A)
0·0
BLPE 0 102030405060708090
Time post-drink (min)
*
§
*§||
*|| ‡||
a
EX
a,b,c a,c
b
0·1
0·2
0·3
0·4
0·5
0·6
0·7
Fig. 4. (A) Serum NEFA concentration in response to test drink consumption
in the overnight fast followed by rest without breakfast (FR, W), overnight fast
followed by breakfast and rest (BR, X), overnight fast followed by exercise
(EX) without breakfast (FE, D) and overnight fast followed by breakfast and
EX (BE, O) trials. BL, baseline; PE, pre-EX. Values are means, with standard
errors represented by vertical bars. * Mean value for the FE trial was signifi-
cantly different from that of BR trial (P,0·05). † Mean value for the FR trial
was significantly different from that of FE trial (P,0·05). ‡ Mean value for the FR
trial was significantly different from that of BE trial (P,0·05). § Mean value for
the BR trial was significantly different from that of FE trial (P,0·05). kMean
value for the BR trial was significantly different from that of BE trial (P,0·05).
{Mean value for the FE trial was significantly different from that of BE trial
(P,0·05). (B) Time-averaged serum NEFA AUC following test-drink consump-
tion.
a,b,c
Values with unlike letters were significantly different (P,0·05).
FR BR FE BE
Trial
BLPE 0 102030405060708090
Time post-drink (min)
*
§
§
||
EX
*‡
*
*‡§
*द
Time-averaged serum
insulin AUC (pmol/l)
Serum insulin
concentration (pmol/l)
0
100
200
300
400
0
100
200
300
400
500
600
700
(B)
(A)
Fig. 3. (A) Serum insulin concentration in response to test drink consumption
in the overnight fast followed by rest without breakfast (FR, W), overnight fast
followed by breakfast and rest (BR, X), overnight fast followed by exercise
(EX) without breakfast (FE, D) and overnight fast followed by breakfast and
EX (BE, O) trials. BL, baseline; PE, pre-EX. Values are means, with standard
errors represented by vertical bars. * Mean value for the FE trial was signifi-
cantly different from that of BR trial (P,0·05). † Mean value for the FR trial
was significantly different from that of FE trial (P,0·05). ‡ Mean value for the
FR trial was significantly different from that of BE trial (P,0·05). § Mean
value for the BR trial was significantly different from that of FE trial (P,0·05).
kMean value for the BR trial was significantly different from that of BE trial
(P,0·05). {Mean value for the FE trial was significantly different from that of
BE trial (P,0·05). (B) Time-averaged serum insulin AUC following test-drink
consumption.
Integrated effects of breakfast and exercise 5
British Journal of Nutrition
There was also no difference in AUC (Fig. 5(B)), peak or
time to peak GLP-1
7–36
concentrations (P¼0·17, P¼0·27 and
P¼0·45, respectively).
Energy intake, metabolism and balance
Energy expenditure, fat oxidation and carbohydrate oxidation
did not differ at baseline (P¼0·43, P¼0·13 and P¼0·57,
respectively).
In the breakfast postprandial period, energy expenditure
was not significantly different between the trials (Table 1).
Less fat and more carbohydrate were utilised during the break-
fast postprandial period in the breakfast trials (i.e. BE and BR)
v. fasting trials (i.e. FE and FR) (Table 1; P¼0·005 and
P,0·001, respectively).
The exercise bout lasted for 59 (SEM 2) min and mean O
2
uptake was similar between the FE and BE trials during
this period (2·52 (SEM 0·11) and 2·50 (SEM 0·11) litres/min;
P¼0·54). In spite of the equivalent amount of external work
performed, exercise increased energy expenditure more
during the breakfast trials (3279 (SEM 50) kJ) compared
with that during the fasting trials (2627 (SEM 43) kJ; P,0·01).
Breakfast consumption reduced the reliance on fat as a
substrate and subsequently raised carbohydrate metabolism
in the exercise period, an effect which was independent of
exercise/rest (Table 1). This resulted in similar carbohydrate
balance (intake minus oxidation) post-exercise between FE
and BE, in spite of a large difference in carbohydrate balance
prior to exercise (pre-exercise: 217 (SEM 2) and 43 (SEM 2) g,
P,0·001; post-exercise: 2108 (SEM 7) and 2102 (SEM 8) g,
P¼0·38 for FE and BE trials, respectively). Following con-
sumption of the test drink, energy expenditure and fat
oxidation were greater in both exercise trials compared with
rest trials, yet carbohydrate oxidation was similar (Table 1).
There was no detectable difference in ad libitum energy
intake at lunch (Fig. 6; P¼0·78). Hence, when energy intakes
from the breakfast and the test drink are taken into consider-
ation, breakfast trials produced a greater total energy intake
(Fig. 6; P,0·001). The variation in the compensation of
energy intake to account for the increase in energy expenditure
(energy intake on exercise trials minus energy intake on resting
trials) ranged from 21916 to 3749 kJ (2458 to 895 kcal) in the
fasting trials and from 21447 to 3683 kJ (2346 to 880 kcal) in
the breakfast trials. A total of seven individuals consumed
less in the FE v. FR trial, four individuals partially compensated
for exercise, consuming more in the FE v. FR trial, but not
enough to overcome the exercise-induced energy expenditure.
Only one participant over-compensated for exercise, consum-
ing more than the exercise-induced energy expenditure in
the FE v. FR trial. In breakfast trials, six individuals consumed
less in the BE v. BR trial, five partially compensated and only
one over-compensated for the exercise-induced energy expen-
diture. No significant relationship was present between the
compensation on fast days and the compensation on breakfast
days (r20·07, P.0·05).
Energy balance post-lunch was most positive with BR and
least positive with FE trials (Fig. 7). There was no detectable
difference in carbohydrate balance when breakfast was omitted
v. consumed, although the difference at rest approached
significance (FR v. BR, P¼0·06; FE v. BE, P¼0·95; Fig. 7). Yet,
fat balance was significantly different between all trials, apart
from the FR v. BE trial, albeit in BE, a reduction which
approached statistical significance was observed (P¼0·06).
Subjective ratings
Feelings of hunger during the exercise period were
suppressed in FE v.FR(P¼0·015) and BE v. BR trials
(P¼0·016). This was still the case immediately post-exercise
in the FE v. FR trial (P¼0·002), yet, in the BE v. BR trial,
there was no detectable difference (P¼0·45). FE also reduced
ratings of prospective consumption during and after exercise
v.FR(P¼0·028 and P¼0·032, respectively), whereas BE did
not significantly affect prospective consumption ratings com-
pared with BR (P¼0·67 and P¼0·15, respectively). Overall
appetite rating showed similar findings (Fig. 8(A)), where
the change from pre- to during the exercise period was signifi-
cantly different between the FR and the FE trials (2 (SEM 1) v.
211 (SEM 4); P¼0·048), but not between the BR and BE trials
(6 (SEM 2) v.0(SEM 4); P¼0·21).
Breakfast did not influence hunger immediately pre-
lunch during exercise trials (P¼0·11), but did reduce hunger
FR BR FE BE
Trial
Time post-drink (min)
BLPE 0 102030405060708090
EX
Time-averaged plasma
GLP-17–36 AUC (pmol/l)
Plasma GLP-17–36
concentration (pmol/l)
0
20
15
10
5
0
15
10
5
(B)
(A)
Fig. 5. (A) Plasma glucagon-like peptide-1
7–36
(GLP-1
7–36
) concentration
in response to test drink consumption in the overnight fast followed by rest
without breakfast (FR, W), overnight fast followed by breakfast and rest
(BR, X), overnight fast followed by exercise (EX) without breakfast (FE, D)and
overnight fast followed by breakfast and EX (BE, O) trials. BL, baseline; PE,
pre-EX. (B) Time-averaged GLP-1
7–36
AUC following test drink consumption.
Values are means, with standard errors represented by vertical bars.
J. T. Gonzalez et al.6
British Journal of Nutrition
in resting trials (P¼0·006). The same pattern was
observed with prospective consumption (FR v. BR: P¼0·005;
BR v. FE: P¼0·005; FE v. BE: P¼0·10). However, immediately
prior to lunch, overall appetite was suppressed in the BR
trial compared with that in both fasting trials (i.e. FE
and FR) (P¼0·001 and P¼0·005, for rest and exercise, respect-
ively; Fig. 8(B)).
There was no detectable difference in AUC for hunger
between exercise and rest (P¼0·47 and P¼0·71 for FR v.FE
and BR v. BE trials, respectively). The AUC for overall appetite
following consumption of the test drink was greater in the FR
trial v. the BR trial (Table 2; P¼0·006), and this pattern was
still apparent, although it was attenuated when exercise was
performed (Table 2; P¼0·029). Similar patterns were shown
for hunger and prospective consumption AUC and mirrored
by fullness and satisfaction AUC (Table 2).
Discussion
The present study attempted to examine the cumulative effects
of breakfast consumption and exercise on the metabolic and
appetite responses to foods consumed later in the day and on
subsequent energy and macronutrient balance. The main find-
ings were that acute breakfast consumption is likely to reduce
postprandial glycaemia and insulinaemia at rest. Acute exercise
did not affect glucose tolerance when breakfast was omitted,
but reduced glucose tolerance when breakfast was consumed;
the pertinence of this chronically should be noted with cau-
tion, given the benefits of exercise training. Exercise in the
fasted state led to a greater transitory reduction in appetite
compared with exercise in the fed state. Energy and fat bal-
ance were least positive following exercise in the fasted state.
Acute breakfast consumption has been shown to improve
glucose tolerance
(2)
. The present findings in physically active
males somewhat support the previous data, although the
effect may be more trivial in these aerobically fit individuals,
with magnitude-based inferences
(30)
indicating 41 and 59 %
likelihoods of beneficial and negligible effects, respectively,
on glucose tolerance. This could be due to the fact that
subjects in the present study are regular exercisers and therefore
displaying better basal glucose tolerance
(5)
. Lower fasting blood
glucose concentrations (approximately 4·5 v. 4·8 mmol/l)
support this proposition. Lower NEFA exposure prior to con-
sumption of the test drink in the BR trial compared with the
FR trial is a possible cause of the potential improvement
in glucose tolerance, as prolonged NEFA elevations reduce
insulin-stimulated glucose disposal by inhibiting insulin signal-
ling
(31)
. The (non-significant) increase in insulinemia and delay
in peak insulin concentrations do support this proposition.
Muscle contraction stimulates insulin-independent glucose
uptake
(14)
, and thus explains why glucose uptake is augmen-
ted following an acute bout of exercise in spite of increased
NEFA concentrations, which was observed in the FE and
BE trials. Increased glucose uptake is a well-established
observation at the muscle
(14)
and whole-body level
(32)
. Thus,
based on insulin clamp studies, it may seem surprising
that there was no difference in glucose tolerance between
the fasted rest and exercise trials, but this does, in fact,
Table 1. Energy expenditure and substrate metabolism during the breakfast postprandial period, exercise or the equivalent rest period and the recovery period following test drink consumption
(Mean values with their standard errors)
Breakfast period (120 min) Exercise period (about 60 min) Recovery period (90 min)
EE (kJ) FO (g) CO (g) EE (kJ) FO (g) CO (g) EE (kJ) FO (g) CO (g)
Trial Mean SEM Mean SEM Mean SEM Mean SEM Mean SEM Mean SEM Mean SEM Mean SEM Mean SEM
FR 919 90 17·4 1·9 13·5 2·8 377 25 7·3 0·8 5·0 0·9 754 4 12·6 1·6 15·5 2·0
BR 922 61 12·4* 1·5 26·6* 2·5 376 20 5·9* 0·8 8·6* 1·1 775 47 11·1 1·2 20·5 2·1
FE 875 46 15·0 1·4 16·8† 1·8 3003*† 43 35·3*† 3·1 91·7*† 7·0 831* 37 15·3† 1·2 13·2 1·8
BE 946 60 13·8* 1·8 24·3a 2·4 3655*†‡ 47 29·3*†‡ 3·2 144·6*†‡ 7·6 832* 37 14·7† 1·5 14·9 2·2
EE, energy expenditure; FO, fat oxidation; CO, carbohydrate oxidation; FR, overnight fast followed by rest without breakfast; BR, overnight fast followed by breakfast and rest; FE, overnight fast followed by exercise without
breakfast; BE, overnight fast followed by breakfast and exercise.
* Mean value was significantly different from FR (P,0·05).
Mean value was significantly different from BR (P,0·05).
Mean value was significantly different from FE (P,0·05).
Integrated effects of breakfast and exercise 7
British Journal of Nutrition
corroborate with studies using oral glucose tolerance tests.
Until now, studies in healthy participants have shown either
decreases
(10,11,33 – 37)
or no difference
(12,13,38)
in glucose toler-
ance following acute endurance exercise. In those displaying
no difference, the tests were either performed in the fasted
state
(13,38)
or glucose tolerance was assessed more than 2 h
after exercise
(12)
. The present study is the first to demonstrate
that when nutrients are ingested immediately post-exercise,
the effect on acute postprandial glucose kinetics may
depend on the nutritional state (fasted or fed) prior to exercise.
It may be the accrual of this acute effect that contributes to the
attenuated improvements in glucose tolerance seen during
exercise training when carbohydrate availability is high
(5)
.
Regarding the effects of exercise when fasted, endurance
exercise increases the rate of appearance of endogenous
glucose
(37)
. Therefore, the increase in muscle glucose uptake
after exercise
(14)
(affecting rate of disappearance) could
ostensibly be offset by the increase in splanchnic glucose
output (affecting rate of appearance) and, hence, result in
an increase in flux, but there was no difference in the systemic
concentrations of glucose after exercise compared with that
after rest when fasted. Future studies are needed to address
whether this is indeed the mechanism at play.
Food consumption prior to exercise also increases splanch-
nic blood flow during exercise
(6)
. As mesenteric blood flow
is positively associated with intestinal glucose absorption
(39)
,
it can be speculated that the increase in blood flow (from
breakfast consumption), combined with increased passive
absorption (from exercise), results in the greater peak blood
glucose concentration in the BE trial compared with the FE
trial. However, recent evidence associates the increase in
intestinal absorption with reduced gut blood flow occurring
during intense exercise and may result in intestinal
damage
(40)
, indicating faster entry of glucose into the circula-
tion when gut blood flow is reduced (which occurs when
exercising after fasting compared with after feeding
(6)
).
This adds to the confusion in the previous conjecture, as the
putative increase in splanchnic blood flow in BE would
result in less intestinal cell damage and reduced passive
absorption, leading to a lower blood glucose AUC (assuming
that endogenous glucose production and glucose disappear-
ance remain constant, which can be presumed due to similar
carbohydrate balance post-exercise and thus similar whole-
body glycogen concentrations).
The present study used an exercise intensity that was lower
(61 % V
O2peak
v. 70 % of maximum power output) than that of
van Wijck et al.
(40)
. At lower intensities (55 % V
O2peak
), the
exercise-induced reduction in splanchnic blood flow is abol-
ished
(6)
. This makes it tempting to presume that other factors,
such as heat or mechanical stresses or changes in hormone
concentrations, contribute to the increase in intestinal glucose
absorption following exercise
(41)
. Another factor at play could
be reductions in insulin sensitivity of non-exercised (upper
limb) muscle following exercise
(42)
. Clearly, this area has
great scope for future work, pertinent to the understanding
of the impact of food intake and exercise on subsequent
whole-body glucose tolerance.
The AUC
INS/GLU
was lower in both exercise trials com-
pared with the FR trial, whereas ISI
Matsuda
was similar between
trials, suggesting that postprandial insulin secretion is reduced
immediately following exercise, but insulin sensitivity is
unaffected
(28,29)
. This strengthens the assumption that the
change in glucose kinetics seen in the present study is due
to a difference in the glucose rate of appearance.
The finding that GLP-1
7–36
concentrations were not differ-
ent between trials is in accordance with the proposition that
glucose entered the circulation via passive absorption. Intrave-
nous infusion of glucose mirroring the plasma glucose profile
to oral ingestion does not augment GLP-1 concentrations
(43)
.
Therefore, as GLP-1
7–36
concentrations were not different
between trials, this provides support for elevated glucose
appearance from passive absorption, as greater GLP-1
7–36
secretion would not occur. GLP-1
7–36
is also a potent incretin
a
a
a
a
b
b
c
c
b
a
d
7000
6000
5000
4000
3000
2000
1000
0
FR
Substrate balance (kJ)
BR FE BE
Trial
b
Fig. 7. Substrate balance. Carbohydrate ( ), fat ( ) and energy ( and
combined) balance at the end of the trial. FR, overnight fast followed by rest
without breakfast; BR, overnight fast followed by breakfast and rest; FE,
overnight fast followed by exercise without breakfast; BE, overnight fast fol-
lowed by breakfast and exercise. Values are means, with standard errors
represented by vertical bars.
a,b,c,d
Values with unlike letters were significantly
different (P,0·05).
10 000
a
b
a
b
8000
6000
4000
2000
0FR
Energy intake (kJ)
BR FE BE
Trial
Fig. 6. Energy intake. Energy intake at lunch ( ) and throughout the whole
trial ( ). FR, overnight fast followed by rest without breakfast; BR, overnight
fast followed by breakfast and rest; FE, overnight fast followed by exercise
without breakfast; BE, overnight fast followed by breakfast and exercise.
Values are means, with standard errors represented by vertical bars.
a,b
Values with unlike letters were significantly different (P,0·05).
J. T. Gonzalez et al.8
British Journal of Nutrition
hormone, stimulating insulin secretion and also suppressing
appetite
(9)
. Thus, as GLP-1
7–36
concentration did not differ
between trials, it would seem that other factors are playing a
role in enhanced insulin action and appetite suppression with
breakfast consumption. It should be noted that GLP-1
7–36
may interact with neurons expressed locally in L-cells, prior
to being rapidly degraded on entry into the circulation,
where its clearance can exceed cardiac output by two to
three times
(44)
. Hence, GLP-1
7–36
can still influence appetite
in spite of no detectable rise in its plasma concentrations.
There was evidence of delayed suppression of NEFA follow-
ing consumption of the test drink in the FR trial compared
with the BR trial, suggestive of metabolic inflexibility, again
associated with insulin resistance. Exercise uncoupled the
link between breakfast, NEFA and insulin concentrations,
whereby, in both the FE and BE trials, insulin and NEFA con-
centrations were similar prior to and following consumption
of the test drink. Increased NEFA availability during and
following exercise is required to support higher rates of fat
oxidation by skeletal muscle as carbohydrate is used to
replenish glycogen stores
(11)
. As such, NEFA flux is raised,
and, as insulin-resisting effects of NEFA on muscle seem to
be time dependent
(31)
, turnover may be more important
than NEFA concentrations for insulin sensitivity.
Exercise transiently suppressed hunger and overall appetite.
This is a common phenomenon
(15,18,45)
, yet less is known
about the effect of nutritional status on the ability of exercise
to influence appetite. The present study found that, compared
with rest, exercise suppressed hunger and overall appetite
to a greater extent when fasted compared with the fed state
(approximately 17 v. 9 %, respectively). Nevertheless, it
should be noted that appetite was higher in the fasting state
prior to exercise. To our knowledge, this is the first crossover
study to demonstrate the effect of exercise in fasted and fed
conditions on appetite sensations compared with resting
trials in the equivalent nutritional state.
Harmonious with preceding research
(15,18)
, the exercise-
induced suppression of appetite was abolished within
30 min of exercise termination and appetite was subsequently
similar between exercise and rest trials until lunch. Breakfast
consumption, however, reduced overall appetite following
test drink consumption by approximately 17 and 14 % in the
rest and exercise trials, respectively. Despite a 10 % reduction
in appetite ratings with breakfast consumption, no detectable
difference in energy intake between trials was observed at
lunch. This occurred regardless of the additional 1859 kJ
of energy consumed during breakfast and approximately
2423 kJ of energy expended during exercise. Subsequently,
energy intake was higher in breakfast trials. Observational
data corroborate the present findings with daily energy
intake increase in regular breakfast consumers compared
with omitters
(1)
. Yet, when BMI was measured, it was still
inversely associated with breakfast consumption
(1)
, suggesting
that it may be the increased energy expenditure and the
improved metabolic responses to food consumption that
result in better weight maintenance.
The outcome that exercise did not influence subsequent
energy intake is in accord with most of the prior research in
this area, although some have found an increase in immediate
energy intake
(46)
. It may be that individual variation exists,
whereby some individuals’ drive to eat following exercise is
dominated by hedonic processes
(47)
. This leads to a diver-
gence between those who compensate for extra energy
expenditure by increasing intake and non-compensators,
who fail to increase intake in the face of an increase in expen-
diture. In the present study, the range of compensation for
exercise-induced energy expenditure was large (5665 kJ of
energy separated the individual who over-compensated and
the individual who under-compensated the greatest). This
variation in the compensation of energy expenditure is likely
to account for the variation seen in body fat changes in an
exercise intervention (reviewed by Caudwell et al.
(48)
). It is
interesting to note that there was no significant relationship
between the degree of compensation to exercise on fasted
trials and breakfast trials, suggesting that those who over-
compensate during exercise in one nutritional state (i.e. the
100 *द
*†‡
§¶ *‡§
80
60
40
20
0
0 20406080100
Time post-drink (min)
Overall appetite (mm)
**‡§
Time (min)
(A)
100
80
60
40
20
0
Overall appetite (mm)
(A)
BL 0 30 60 90 120 DE EE
EX
Breakfast postprandial period
*
Fig. 8. Overall appetite. Overall appetite sensations during (A) the breakfast
postprandial and exercise (EX) periods and (B) following test drink consump-
tion in the overnight fast followed by rest without breakfast (FR, W), overnight
fast followed by breakfast and rest (BR, X), overnight fast followed by EX
without breakfast (FE, D) and overnight fast followed by breakfast and EX
(BE, O) trials. BL, baseline; DE, during EX; EE, end of EX; PL, post-lunch.
Values are means, with standard errors represented by vertical bars. * Mean
value for the FE trial was significantly different from that of BR trial (P,0·05).
† Mean value for the FR trial was significantly different from that of FE trial
(P,0·05). ‡ Mean value for the FR trial was significantly different from that of
BE trial (P,0·05). § Mean value for the BR trial was significantly different
from that of FE trial (P,0·05). {Mean value for the FE trial was significantly
different from that of BE trial (P,0·05).
Integrated effects of breakfast and exercise 9
British Journal of Nutrition
fasted/fed state) may not over-compensate in the opposing
circumstance. Another possibility is that exercise energy
expenditure is gradually compensated for by energy intake,
which is likely to require a period of several weeks, and
even then is not likely to be fully compensated for
(49)
.
The higher total energy intake with breakfast trials and the
exercise-induced energy expenditure led to energy balance
being most positive in the BR trial and least positive in the FE
trial. BE resulted in an approximately 1110 kJ reduction in
energy balance compared with FR. When taken in concert
with the similar appetite sensations to resting trials, exercise
may provide a more attractive option for restricting energy avail-
ability compared with omitting breakfast. Interestingly, in spite
of differing quantities of carbohydrate and fat oxidised with all
trials, carbohydrate balance was remarkably similar between
the FE and BE trials, whereas fat balance was 3-fold more posi-
tive in the BE trial. This may not be as clear at rest, as the differ-
ence between the FR and BR trials in carbohydrate balance did
approach a statistically significant difference (Fig. 7), but was
higher than that in exercise trials. At least in the short term,
the regulation of carbohydrate stores is more tightly regulated
than fat stores
(19)
. The findings of the present study add that
consumption/omission of breakfast will not alter carbohydrate
balance, whereas exercise can reduce carbohydrate balance.
The increased energy expenditure observed during
exercise with breakfast consumption was provided by a
higher rate of carbohydrate oxidation, this has previously
been reported
(50 – 52)
and may be magnified during running
due to the weight-bearing component
(53)
. The relevance of
this with respect to energy balance was, however, trivial,
as energy balance was lower in the FE trial compared with
the BE trial.
This controlled experimental study involved the provision
of a popular breakfast food consumed prior to a bout of exer-
cise or rest in physically active males, with a structure similar
to the eating patterns in Western society. It could be viewed
that a caveat with the present study is that the participants
were physically active and that a sedentary population
would benefit more from exercise/diet-induced improvements
in metabolism and appetite. However, those who regularly
exercise still utilise energy/carbohydrate restriction in order
to regulate body composition
(4)
. Therefore, the results are
pertinent to these populations; yet, it would undoubtedly be
of virtue to investigate these responses in other populations
(females, sedentary and obese) to extrapolate findings to a
wider population. Moreover, future work should examine
whether there is a difference in energy intake in subsequently
consumed meals over a longer duration.
It is also of merit to recognise that the environmental
conditions were similar between trials, which is important
due to the potential effect of temperature on appetite and
energy intake
(46)
.
The findings of the present investigation suggest that in
an acute setting, energy intake from breakfast and energy
expenditure from exercise are not compensated for at lunch.
Consequently, energy balance was most positive following
breakfast and rest and least positive following breakfast
omission and exercise. When exercise is performed, it may
be more pertinent to omit breakfast if a negative fat balance
is desirable, although the findings of the present study are
unable to predict the longer-term outcomes of energy and
fat balance due to the single-meal design, and as such this
conclusion should be interpreted with caution.
The present study aimed to explore the effect of breakfast
and exercise on the metabolic and appetite responses to
subsequent food consumption. The findings indicate that
breakfast ingestion may improve the metabolic and appetite
responses to subsequently consumed foods when sedentary.
When breakfast is consumed, subsequent postprandial
glycaemia is higher following exercise, yet care should
be taken during the interpretation for chronic effects, as
exercise training almost always confers a benefit for glucose
tolerance and insulin sensitivity. Exercise also resulted in
an ephemeral reduction in appetite, which is greater when
performed fasted.
Acknowledgements
We gratefully thank the volunteers for their participation and
A. Wilde for technical assistance. This project received no
external funding. J. T. G. and E. J. S. designed the study, J. T.
G. and R. C. V. performed the data collection and all authors
contributed to data analysis and interpretation and writing of
the manuscript. The authors declare no conflicts of interest.
Table 2. Time-averaged AUC values for subjective appetite responses to consumption of the test drink
(Mean values with their standard errors)
Hunger (mm) Fullness (mm)
Satisfaction
(mm)
Prospective
consumption
(mm)
Overall appe-
tite (mm)
Trial Mean SEM Mean SEM Mean SEM Mean SEM Mean SEM
FR 65 4 30 4 27 2 72 3 70 2
BR 54* 4 40 4 40* 3 58* 4 58* 3
FE 63 3 28† 4 29† 3 68† 4 67† 3
BE 55 4 40 4 40*‡ 3 62* 4 59*‡ 4
FR, overnight fast followed by rest without breakfast; BR, overnight fast followed by breakfast and rest; FE, overnight fast
followed by exercise without breakfast; BE, overnight fast followed by breakfast and exercise.
* Mean value was significantly different from FR (P,0·05).
Mean value was significantly different from BR (P,0·05).
Mean value was significantly different from FE (P,0·05).
J. T. Gonzalez et al.10
British Journal of Nutrition
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J. T. Gonzalez et al.12
British Journal of Nutrition
... The timing of exercise in conjunction with breakfast has demonstrated an ability to affect 24 h energy balance as well. More specifically, previous investigations have examined the impact of morning exercise with or without breakfast consumption on 24 h energy balance [101][102][103]. All three prior investigations found that morning moderate-intensity (50-60% VO 2 max) endurance exercise, in conjunction with breakfast omission, resulted in a negative energy balance over a 24 h period. ...
... Furthermore, the exercise respiratory quotient was lowered in the breakfast omission group (0.90 versus 0.86). However, the average relative VO 2 max in this investigation was 59.1 mlO 2 /kg/min, and the mean VO 2 max across all three studies was 55 mL of O 2 /kg/min (53, 59.1, and 53.1) [101][102][103], indicating that these findings might not extend to lesser-trained or clinical populations. ...
Article
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Background: Breakfast is often termed the most important meal of the day. However, its importance to acute and chronic adaptations to exercise is currently not well summarized throughout the literature. Methods: A narrative review of the experimental literature regarding breakfast consumption’s impact on acute and chronic exercise performance and alterations in body composition prior to November 2024 was conducted. To be included in this review, the selected investigations needed to include some aspect of either endurance or resistance training performance and be conducted in humans. Results: These findings suggest that breakfast consumption may benefit acute long-duration (>60 min) but not short-duration (<60 min) morning endurance exercise. Evening time trial performance was consistently inhibited following breakfast omission despite the resumption of eating midday. No or minimal impact of breakfast consumption was found when examining acute morning or afternoon resistance training or the longitudinal adaptations to either resistance or endurance training. Favorable changes in body composition were often noted following the omission of breakfast. However, this was primarily driven by the concomitant reduced kilocalorie intake. Conclusions: Consuming breakfast may aid endurance athletes regularly performing exercise lasting >60 min in length. However, the morning meal’s impact on resistance training and changes in body composition appears to be minimal. Although, as the body of literature is limited, future investigations are needed to truly ascertain the dietary practice’s impact.
... Human beings exhibit circadian rhythms and diurnal variations in their physiology and the time of day they exercise, typically identifying as either morning or evening chronotypes [1]. There is still controversy regarding training timing; some authors have observed improvements in muscular adaptations and energy utilization during morning exercise [2][3][4][5][6], while muscular function has been favoured in other studies when exercise is performed in the afternoon or evening [7][8][9][10]. In this regard, research exploring the potential effects of Exercise Timing of the Day (ETOD) on the body composition and diet of young athletes is not fully documented across multiple domains of applicability in daily life, justifying its assessment. ...
... (www.preprints.org) | NOT PEER-REVIEWED | Posted: 6 September 2024 doi:10.20944/preprints202409.0524.v14 ...
Preprint
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Training schedule is a factor that influences sports performance optimization. In a sport like soccer, there is often significant disparity in training schedules among different teams within the same club, without considering whether this may affect players' performance. The aim of this study was to describe differences in nutrient intake and body composition in elite youth soccer players from the Spanish league with different training schedules (morning and evening). A cross-sectional study was conducted to determine differences in anthropometric variables and dietary assessment in a sample of Spanish young soccer players. A total of 41 players participated in this study. After comparing the groups according to their training schedule, no differences were observed in body composition between both groups; the evening-night training group showed higher consumption of lipids and saturated fats. In summary, more experimental studies are needed to determine the effects on various health and performance parameters of different training schedules in young population.
... It was reported that there was evidence for true inter-individual differences in the responses of peak glucose concentrations and hunger ratings in response to a breakfast [9]. However, since blood sampling finished at 60 min after the meal, it is not known whether reactive hypoglycaemia, which typically occurs between 1 and 3 h postprandially [4,10], displays true interindividual variability in response to a meal. We previously reported on a study examining the interactive effects of breakfast and exercise on mean changes in postprandial metabolism later in the day. ...
... The original study design was a randomised crossover with 4 conditions, fasted prior to rest, fasted prior to exercise, breakfast prior to rest and breakfast prior to exercise and is available open access [10]. Up to the exercise period (and parallel period in control), these conditions provided, essentially, a replicate crossover with two control and two breakfast conditions. ...
Article
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Background Following consumption of a meal, circulating glucose concentrations can rise and then fall briefly below the basal/fasting concentrations. This phenomenon is known as reactive hypoglycaemia but to date no researcher has explored potential inter-individual differences in response to meal consumption. Objective We conducted a secondary analysis of existing data to examine inter-individual variability of reactive hypoglycaemia in response to breakfast consumption. Methods Using a replicate crossover design, 12 healthy, physically active men (age: 18–30 y, body mass index: 22.1 to 28.0 kg⋅m− 2) completed two identical control (continued overnight fasting) and two breakfast (444 kcal; 60% carbohydrate, 17% protein, 23% fat) conditions in randomised sequences. Blood glucose and lactate concentrations, serum insulin and non-esterified fatty acid concentrations, whole-body energy expenditure, carbohydrate and fat oxidation rates, and appetite ratings were determined before and 2 h after the interventions. Inter-individual differences were explored using Pearson’s product-moment correlations between the first and second replicates of the fasting-adjusted breakfast response. Within-participant covariate-adjusted linear mixed models and a random-effects meta-analytical approach were used to quantify participant-by-condition interactions. Results Breakfast consumption lowered 2-h blood glucose by 0.44 mmol/L (95%CI: 0.76 to 0.12 mmol/L) and serum NEFA concentrations, whilst increasing blood lactate and serum insulin concentrations (all p < 0.01). Large, positive correlations were observed between the first and second replicates of the fasting-adjusted insulin, lactate, hunger, and satisfaction responses to breakfast consumption (all r > 0.5, 90%CI ranged from 0.03 to 0.91). The participant-by-condition interaction response variability (SD) for serum insulin concentration was 11 pmol/L (95%CI: 5 to 16 pmol/L), which was consistent with the τ-statistic from the random-effects meta-analysis (11.7 pmol/L, 95%CI 7.0 to 22.2 pmol/L) whereas effects were unclear for other outcome variables (e.g., τ-statistic value for glucose: 0 mmol/L, 95%CI 0.0 to 0.5 mmol/L). Conclusions Despite observing reactive hypoglycaemia at the group level, we were unable to detect any meaningful inter-individual variability of the reactive hypoglycaemia response to breakfast. There was, however, evidence that 2-h insulin responses to breakfast display meaningful inter-individual variability, which may be explained by relative carbohydrate dose ingested and variation in insulin sensitivity of participants.
... It was reported that there was evidence for true inter-individual differences in the responses of peak glucose concentrations and hunger ratings in response to a breakfast(8). However, since blood sampling nished at 60 min after the meal, it is not known whether reactive hypoglycaemia, which typically occurs between 1-3 h postprandially (4,9), displays true interindividual variability in response to a meal. We previously reported on a study examining the interactive effects of breakfast and exercise on mean changes in postprandial metabolism later in the day. ...
... The original study design was a randomised crossover with 4 conditions, fasted prior to rest, fasted prior to exercise, breakfast prior to rest and breakfast prior to exercise and is available open access (9). Up to the exercise period (and parallel period in control), these conditions provided, essentially, a replicate crossover with two control and two breakfast conditions. ...
Preprint
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Background Following consumption of a meal, circulating glucose concentrations can rise and then fall briefly below the basal/fasting concentrations. This phenomenon is known as reactive hypoglycaemia but to date no study explored potential inter-individual differences in response to meal consumption. Objective We conducted a secondary analysis of existing data to examine inter-individual variability of reactive hypoglycaemia in response to breakfast consumption. Methods Using a replicate crossover design, 12 healthy men completed two identical control (continued overnight fasting) and two breakfast (444 kcal) conditions in randomised sequences. Blood glucose and lactate concentrations, serum insulin and non-esterified fatty acid concentrations, whole-body energy expenditure, carbohydrate and fat oxidation rates, and appetite ratings were determined before and 2 hours after the interventions. Inter-individual differences were explored using Pearson’s product-moment correlations between the first and second replicates of the control-adjusted breakfast response. Within-participant covariate-adjusted linear mixed models and a random-effects meta-analytical approach were used to quantify participant-by-condition interactions. Results Breakfast consumption lowered 2-h blood glucose 0.44 mmol/L (95%CI: 0.76 to 0.12 mmol/L) and serum NEFA concentrations, whilst increasing blood lactate and serum insulin concentrations (all p < 0.01). Large, positive correlations were observed between the first and second replicates of the control-adjusted insulin, lactate, hunger, and satisfaction responses to breakfast consumption (all r > 0.5, 90%CI ranged from 0.03 to 0.91). The participant-by-condition interaction response variability (SD) for serum insulin concentration was 11 pmol/L (95%CI: 5 to 16 pmol/L), which was consistent with the τ-statistic from the random-effects meta-analysis (11.7 pmol/L, 95%CI 7.0 to 22.2 pmol/L) whereas effects were unclear for other outcome variables (e.g., τ-statistic value for glucose: 0 mmol/L, 95%CI 0.0 to 0.5 mmol/L). Conclusions Despite observing reactive hypoglycaemia at the group level, we were unable to detect any meaningful inter-individual variability of the reactive hypoglycaemia response to breakfast. There was, however, evidence that 2-h insulin responses to breakfast display meaningful inter-individual variability, which may be explained by relative carbohydrate dose ingested and variation in insulin sensitivity of participants.
... It was reported that there was evidence for true inter-individual differences in the responses of peak glucose concentrations and hunger ratings in response to a breakfast(8). However, since blood sampling nished at 60 min after the meal, it is not known whether reactive hypoglycaemia, which typically occurs between 1-3 h postprandially (4,9), displays true interindividual variability in response to a meal. We previously reported on a study examining the interactive effects of breakfast and exercise on mean changes in postprandial metabolism later in the day. ...
... The original study design was a randomised crossover with 4 conditions, fasted prior to rest, fasted prior to exercise, breakfast prior to rest and breakfast prior to exercise and is available open access (9). Up to the exercise period (and parallel period in control), these conditions provided, essentially, a replicate crossover with two control and two breakfast conditions. ...
Preprint
Full-text available
Background Following consumption of a meal, circulating glucose concentrations can rise and then fall briefly below the basal/fasting concentrations. This phenomenon is known as reactive hypoglycaemia but to date no study explored potential inter-individual differences in response to meal consumption. Objective We conducted a secondary analysis of existing data to examine inter-individual variability of reactive hypoglycaemia in response to breakfast consumption. Methods Using a replicate crossover design, 12 healthy men completed two identical control (continued overnight fasting) and two breakfast (444 kcal) conditions in randomised sequences. Blood glucose and lactate concentrations, serum insulin and non-esterified fatty acid concentrations, whole-body energy expenditure, carbohydrate and fat oxidation rates, and appetite ratings were determined before and 2 hours after the interventions. Inter-individual differences were explored using Pearson’s product-moment correlations between the first and second replicates of the control-adjusted breakfast response. Within-participant covariate-adjusted linear mixed models and a random-effects meta-analytical approach were used to quantify participant-by-condition interactions. Results Breakfast consumption lowered 2-h blood glucose 0.44 mmol/L (95%CI: 0.76 to 0.12 mmol/L) and serum NEFA concentrations, whilst increasing blood lactate and serum insulin concentrations (all p < 0.01). Large, positive correlations were observed between the first and second replicates of the control-adjusted insulin, lactate, hunger, and satisfaction responses to breakfast consumption (all r > 0.5, 90%CI ranged from 0.03 to 0.91). The participant-by-condition interaction response variability (SD) for serum insulin concentration was 11 pmol/L (95%CI: 5 to 16 pmol/L), which was consistent with the τ-statistic from the random-effects meta-analysis (11.7 pmol/L, 95%CI 7.0 to 22.2 pmol/L) whereas effects were unclear for other outcome variables (e.g., τ-statistic value for glucose: 0 mmol/L, 95%CI 0.0 to 0.5 mmol/L). Conclusions Despite observing reactive hypoglycaemia at the group level, we were unable to detect any meaningful inter-individual variability of the reactive hypoglycaemia response to breakfast. There was, however, evidence that 2-h insulin responses to breakfast display meaningful inter-individual variability, which may be explained by relative carbohydrate dose ingested and variation in insulin sensitivity of participants.
... Exercise in a fasted state leads to higher fat oxidation during exercise (Bachman et al., 2016;Gonzalez et al., 2013) and a greater caloric deficit for the day (Bachman et al., 2016;Edinburgh et al., 2019). In the current study, fat oxidation was highest during exercise in the NON-CAL (fasted) trial (0.57 g·min −1 , 95% CI: 0.43-0.69 ...
... In the current study, fat oxidation was highest during exercise in the NON-CAL (fasted) trial (0.57 g·min −1 , 95% CI: 0.43-0.69 g·min −1 ) with similar levels of fat oxidation between PRO and CHO (0.50 vs. 0.48 g·min −1 ) in line with previous research (Bachman et al., 2016;Gonzalez et al., 2013;Rothschild et al., 2021). While not statistically significant, carbohydrate oxidation was approximately 0.2 g·min −1 greater during exercise in PRO and CHO compared to the fasted trial. ...
Article
Background: Manipulation of macronutrient intake and exercise can alter overall energy consumption and potentially body composition. Aim: The purpose of this study was to manipulate the macronutrient content of breakfast before exercise to investigate the impact on exercise energy expenditure and postexercise energy intake (EI). Methods: Twelve active men were recruited, 11 finished the study protocol (age: 28 ± 9 years; VO 2 max: 56 ± 5 ml·kg ⁻¹ ·min ⁻¹ ). In a randomized crossover design, each participant completed 4 trials, 3 consisting of a specific breakfast (protein, PRO; carbohydrate, CHO; noncaloric; NON-CAL) followed in 1 h by a 45 minutes moderate intensity treadmill exercise protocol. The fourth trial consisted of breakfast and no exercise (CON). An ad-libitum lunch and food for the rest of the day were provided and assessed for EI. Measures included resting metabolic rate pre- and postbreakfast along with oxygen uptake (VO 2 ) during and after exercise, along with hunger scales, and blood measures of glucose, insulin and plasma-PYY prebreakfast, pre-exercise, postexercise, and 60 minutes postexercise. Results: Fat oxidation was highest during exercise in the NON-CAL (0.57 g·min ⁻¹ ) trial with similar levels of fat oxidation between PRO (0.50 g·min ⁻¹ ) and CHO trials (0.48 g·min ⁻¹ ). Hunger was not affected by PRO intake or exercise, nor was appetite hormones and glucose. EI at lunch and dinner was not significantly different between trials. Conclusion: Pre-exercise PRO intake did not modify fat oxidation during exercise, did not lead to a larger VO 2 versus CHO, nor did it attenuate EI postexercise.
... Human beings exhibit circadian rhythms and diurnal variations in their physiology and the time of day they exercise, typically identifying as either morning or evening chronotypes [1]. There is still controversy regarding training timing; some authors have observed improvements in muscular adaptations and energy utilization during morning exercise [2][3][4][5][6], while muscular function has been favored in other studies when exercise is performed in the afternoon or evening [7][8][9][10]. In this regard, research exploring the potential effects of Exercise Timing of the Day (ETOD) on the body composition and diet of young athletes is not fully documented across multiple domains of applicability in daily life, justifying its assessment. ...
Article
Full-text available
The training schedule is a factor that influences sports performance optimization. In a sport like soccer, there is often significant disparity in training schedules among different teams within the same club, without considering whether this may affect players’ performance. The aim of this study was to describe differences in nutrient intake and body composition in elite youth soccer players from the Spanish league with different training schedules (morning and evening). A cross-sectional study was conducted to determine differences in anthropometric variables and dietary assessment in a sample of Spanish young soccer players. A total of 41 players participated in this study. After comparing the groups according to their training schedule, no differences were observed in body composition between both groups; the evening-night training group showed higher consumption of lipids and saturated fats. In summary, more experimental studies are needed to determine the effects on various health and performance parameters of different training schedules in young population.
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The environment comprises both living and nonliving components, and their interplay dictates the health and sustenance of the environment. Emergent properties from this interaction, various by-products are released directly or indirectly into the environment. Water environments are very dynamic, and their composition is based on the inputs they receive from the land which may be directly or indirectly discharged into it. These pollutants may be in various forms such as solid, liquid, and gases and may be composed of chemicals or from biological processes. They are capable of imposing stress on the water environment thereby affecting ubiquitous and migratory organisms dwelling in it. Organisms have different tolerable ranges to these pollutants as some may migrate or die in extreme cases. Some of these pollutants are capable of bio-accumulating in water organisms, thereby causing health issues along the higher levels in the food chain. Approaches such as biomarkers and the use of molecular approaches can be used for the detection of these pollutants in water. Some of the biomarker approaches include the use of macrophytes, plankton, fishes, aquatic reptiles, amphibians, arthropods, benthic organisms, aquatic mammals, aquatic reptiles, and micro-organisms. Similarly, the biomarker responses to stress such as the responses to chemical, nonchemical, histological, and Histopathological approaches are processes that can be used in pollution detection in water environments. The use of biomarkers has numerous importance, and its prospects are enormous. It can be applied in ecotoxicology and molecular biology, in the proteogenomic approach as the coming biomarker, in genotoxicity (DNA damage and micronucleus formation), and reproductive impairments. Despite these advantages, there are several limitations associated with biomarkers in pollution detection in the aquatic environment, and the issue of sustainable use of biomarkers for the detection of pollutants in the freshwater and marine ecosystem is crucial. To this end, this paper reviews the use of biomarkers for pollution detection in water environments, stress responses, biomarker tools, perspectives, and the limitations in the use and sustainable use of biomarkers in pollution detection in water environments.
Article
Context How pre-exercise meal composition influences metabolic and health responses to exercise later in the day is currently unclear. Objective Examine the effects of substituting carbohydrate for protein at lunch on subsequent exercise metabolism, appetite, and energy intake. Methods Twelve healthy males completed three trials in randomized, counterbalanced order. Following a standardized breakfast (779 ± 66 kcal; ∼08:15), participants consumed a lunch (1186 ± 140 kcal; ∼13:15) containing either 0.2 g·kg-1 carbohydrate and ∼2 g·kg-1 protein (LO-CARB), 2 g·kg-1 carbohydrate and ∼0.4 g·kg-1 protein (HI-CARB), or fasted (FAST). Participants later cycled at ∼60% V̇O2peak for 1 h (∼16:15) and post-exercise ad-libitum energy intake was measured (∼18:30). Substrate oxidation, subjective appetite, and plasma concentrations of glucose, insulin, non-esterified fatty acids (NEFA), peptide YY (PYY), glucagon-like peptide-1 (GLP-1), and acylated ghrelin (AG) were measured for 5 h post-lunch. Results Fat oxidation was greater during FAST (+11.66 ± 6.63 g) and LO-CARB (+8.00 ± 3.83 g) than HI-CARB (p < 0.001), with FAST greater than LO-CARB (+3.67 ± 5.07 g; p < 0.05). NEFA were lowest in HI-CARB and highest in FAST, with insulin demonstrating the inverse response (all p < 0.01). PYY and GLP-1 demonstrated a stepwise pattern, with LO-CARB greatest and FAST lowest (all p < 0.01). AG was lower during HI-CARB and LO-CARB versus FAST (p < 0.01). Energy intake in LO-CARB was lower than FAST (-383 ± 233 kcal; p < 0.001) and HI-CARB (-313 ± 284 kcal; p < 0.001). Conclusion Substituting carbohydrate for protein in a pre-exercise lunch increased fat oxidation, suppressed subjective and hormonal appetite, and reduced post-exercise energy intake.
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The performance of exercise while immersed in cold water has been shown to influence energy intake in the subsequent meal. However, the effect of ambient temperature during land-based exercise is not known. Our aims were to investigate the effect of exercise performed in the heat on energy intake in the subsequent meal and to determine concentrations of circulating appetite-related hormones. In a randomized, counterbalanced design, 11 active male participants completed 3 experimental trials in a fasted state: exercise in the heat (36 degrees C), exercise in a neutral temperature (25 degrees C), and a resting control (25 degrees C). The exercise trials consisted of treadmill running for 40 min at 70% VO(2peak). After each trial, participants were presented with a buffet-type breakfast of precisely known quantity and nutrient composition, which they could consume ad libitum. Energy intake was greater after exercise in the neutral temperature compared with the control (P = 0.021) but was similar between exercise in the heat and the control and between the 2 exercise trials. When accounting for the excess energy expended during exercise, relative energy intake during exercise in the heat was lower than the control (P = 0.002) but was similar between exercise in the neutral temperature and the control and between exercise in the heat and in the neutral temperature. The lower relative energy intake after exercise in the heat was associated with an elevated tympanic temperature and circulating concentrations of peptide YY (P < 0.05). Exercise in a neutral environmental temperature is associated with higher energy intake in the subsequent meal compared with a control, whereas exercise in the heat is not.
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We investigated the relationship between mechanical and energy cost of transport and body mass in running humans. Ten severely obese (body mass ranging from 108.5 to 172.0 kg) and 15 normal-weighted (52.0-89.0 kg) boys and men, aged 16.0-45.8 years, participated in this study. The rate of O(2) consumption was measured and the subjects were filmed with four cameras for kinematic analysis, while running on a treadmill at 8 km h(-1). Mass specific energy cost (C (r)) and external mechanical work (W (ext)) per unit distance were calculated and expressed in joules per kilogram per meter, efficiency (η) was then calculated as W (ext) × C (r) (-1) × 100. Both mass-specific C (r) and W (ext) were found to be independent of body mass (M) (C (r) = 0.002 M + 3.729, n = 25, R (2) = 0.05; W (ext) = -0.001 M + 1.963, n = 25, R (2) = 0.01). It necessarily follows that the efficiency is also independent of M (η = -0.062 M + 53.3298, n = 25, R (2) = 0.05). The results strongly suggest that the elastic tissues of obese subjects can adapt (e.g., thickening) to the increased mass of the body thus maintaining their ability to store elastic energy, at least at 8 km h(-1) speed, at the same level as the normal-weighted subjects.
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This study investigated the effect of fasted and postprandial exercise on appetite, energy intake and resting metabolic responses. Twelve healthy males (mean±SD: age 23±3 years, body mass index 22.9±2.1 kg m(-2), maximum oxygen uptake 57.5±9.7 mL kg(-1) min(-1)) performed three 10 h experimental trials (control, fasted exercise and postprandial exercise) in a Latin Square design. Trials commenced at 8 am after an overnight fast. Sixty min of treadmill running at ∼70% of maximum oxygen uptake was performed at 0-1 h in the fasted exercise trial and 4-5 h in the postprandial exercise trial. A standardised breakfast was provided at 1.5 h and ad libitum buffet meals at 5.5 and 9.5 h. Appetite ratings and resting expired air samples were collected throughout each trial. Postprandial exercise suppressed appetite to a greater extent than fasted exercise. Ad libitum energy intake was not different between trials, resulting in a negative energy balance in exercise trials relative to control after accounting for differences in energy expenditure (control: 9774±2694 kJ; fasted exercise: 6481±2318 kJ; postprandial exercise: 6017±3050 kJ). These findings suggest that 60 min treadmill running induces a negative daily energy balance relative to a sedentary day but is no more effective when performed before or after breakfast.
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Splanchnic hypoperfusion is common in various pathophysiological conditions and often considered to lead to gut dysfunction. While it is known that physiological situations such as physical exercise also result in splanchnic hypoperfusion, the consequences of flow redistribution at the expense of abdominal organs remained to be determined. This study focuses on the effects of splanchnic hypoperfusion on the gut, and the relationship between hypoperfusion, intestinal injury and permeability during physical exercise in healthy men. Healthy men cycled for 60 minutes at 70% of maximum workload capacity. Splanchnic hypoperfusion was assessed using gastric tonometry. Blood, sampled every 10 minutes, was analyzed for enterocyte damage parameters (intestinal fatty acid binding protein (I-FABP) and ileal bile acid binding protein (I-BABP)). Changes in intestinal permeability were assessed using sugar probes. Furthermore, liver and renal parameters were assessed. Splanchnic perfusion rapidly decreased during exercise, reflected by increased gap(g-a)pCO(2) from -0.85±0.15 to 0.85±0.42 kPa (p<0.001). Hypoperfusion increased plasma I-FABP (615±118 vs. 309±46 pg/ml, p<0.001) and I-BABP (14.30±2.20 vs. 5.06±1.27 ng/ml, p<0.001), and hypoperfusion correlated significantly with this small intestinal damage (r(S) = 0.59; p<0.001). Last of all, plasma analysis revealed an increase in small intestinal permeability after exercise (p<0.001), which correlated with intestinal injury (r(S) = 0.50; p<0.001). Liver parameters, but not renal parameters were elevated. Exercise-induced splanchnic hypoperfusion results in quantifiable small intestinal injury. Importantly, the extent of intestinal injury correlates with transiently increased small intestinal permeability, indicating gut barrier dysfunction in healthy individuals. These physiological observations increase our knowledge of splanchnic hypoperfusion sequelae, and may help to understand and prevent these phenomena in patients.
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Position Statement: Admittedly, research to date examining the physiological effects of meal frequency in humans is somewhat limited. More specifically, data that has specifically examined the impact of meal frequency on body composition, training adaptations, and performance in physically active individuals and athletes is scant. Until more research is available in the physically active and athletic populations, definitive conclusions cannot be made. However, within the confines of the current scientific literature, we assert that: 1. Increasing meal frequency does not appear to favorably change body composition in sedentary populations. 2. If protein levels are adequate, increasing meal frequency during periods of hypoenergetic dieting may preserve lean body mass in athletic populations. 3. Increased meal frequency appears to have a positive effect on various blood markers of health, particularly LDL cholesterol, total cholesterol, and insulin. 4. Increased meal frequency does not appear to significantly enhance diet induced thermogenesis, total energy expenditure or resting metabolic rate. 5. Increasing meal frequency appears to help decrease hunger and improve appetite control. The following literature review has been prepared by the authors in support of the aforementioned position statement.
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Investigations of the impact of physical activity on appetite control have the potential to throw light on the understanding of energy balance and therefore, upon body weight regulation and the development of obesity. Given the complexity of the landscape influencing weight regulation,research strategies should reflect this complexity. We have developed a research approach based on the concept of the psychobiological system (multi-level measurement and analysis) and an experimental platform that respects the operations of an adaptive regulating biological system. It is important that both sides of the energy balance equation (activity and diet) receive similar detailed levels of analysis. The experimental platform uses realistic and fully supervised levels of physical activity, medium-term (not acute) interventions, measurement of body composition, energy metabolism (indirect calorimetry), satiety physiology(gut peptides), homeostatic and hedonic processes of appetite control, non-exercise activity, obese adult participants and both genders. This research approach has shown that the impact of physical activity on appetite control is characterised by large individual differences. Changes in body composition, waist circumference and health benefits are more meaningful than changes in weight. Further, we are realising that the acute effects do not predict what will happen in the longer term. The psychobiological systems approach offers a strategy for simultaneously investigating biological and behavioural processes relevant to understanding obese people and how obesity can be managed. This experimental platform provides opportunities for industry to examine the impact of foods under scientifically controlled conditions relevant to the real world.
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