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The Effects of Substrate Oxidation on Post-Exercise Food Intake in
Pre-pubertal, Normal-weight Boys and Men.
By
Sascha Hunschede
A thesis submitted in conformity with the requirements
for the degree of Masters of Science
Graduate Department of Nutritional Sciences
University of Toronto
© Copyright by Sascha Hunschede 2013
ii
The Effects of Substrate Oxidation on Post-Exercise Food Intake in
Pre-pubertal, Normal-weight Boys and Men.
Master of Science, 2013
Sascha Hunschede
Graduate Department of Nutritional Sciences
University of Toronto
ABSTRACT
The relationship between substrate oxidation (RER) and food intake (FI) is undefined. This study
examined the effects of RER modified by a glucose pre-load (GL), exercise (EX) and GL with EX
on, FI and energy balance (NEB) in normal-weight boys (9-12 y) and men (20-30 y). Subjects (15
boys, 15 men) were randomized with treatments of either water or GL followed by either EX or
rest. Measures included RER, energy expenditure (EE)(kcal/kg), subjective appetite, FI(kcal/kg)
measured at a pizza lunch and NEB (kcal/kg). FI(kcal/kg) was reduced by GL(p < 0.0001), and
further decreased with GL ingested prior to EX(p = 0.0254). RER was increased with GL(p <
0.0001) and EX(p = 0.0043), and was higher in men compared to boys (p = 0.007). There was no
association between RER and FI(kcal/kg). In conclusion, there was no relationship between RER
and FI, suggesting that FI is not affected by substrate oxidation.
iii
ACKNOWLEDGEMENTS
I would like to express my gratitude to my supervisor, Dr. Harvey Anderson, whose
expertise, understanding, and patience, added extensively to my graduate experience. His vast
knowledge in many areas (e.g., nutrition, exercise and the interaction of food intake and energy
expenditure), without whose assistance and motivation and encouragement I would not have
considered pursuing further steps in nutritionals sciences. It was under his guidance that I
developed a greater focus and became more interested in obesity and the prevention of it.
A very special thanks goes out to Dr. Scott Thomas, who encouraged and assisted me with
the design and practical implementation of the project and he was always available to exchange
concepts, knowledge, skills, and helped me venting of frustration during my graduate program,
which helped to enrich the experience. He provided me with direction, technical support and
became more of a mentor and friend, than a professor. It was through his, persistence,
understanding and kindness that I completed this project and applied for the Ph.D. program. I doubt
that I will ever be able to convey my appreciation fully, but I owe him my highest gratitude. I
would like to thank Dr. Thomas Wolever who is the third member of my committee, for taking
time out from his busy schedule and providing assistance at all levels of the research project.
I must also acknowledge Dr. Sophie Antoine-Jonville who joined the Department of
Nutritional Sciences, University of Toronto on her sabbatical, Dr. Antoine-Jonville supported me
with her understanding and the clinical applications of the substrate measurements and the
metabolic cart. Further thanks goes to Dr. Dalia El Khoury who was always available to discuss
ideas and give me feedback and suggestions for my graduate work.
iv
I would also like to thank my family for the support they provided me through my entire
life and in particular the last two years, I must acknowledge my significant other and best friend,
Katherine, without whose love, encouragement and editing assistance, I would not have finished
this thesis.
In conclusion, I recognize that this research would not have been possible without the
financial assistance of CIHR and the University of Toronto, Department of Nutritional Sciences,
which I would like to express my gratitude.
v
TABLE OF CONTENTS
ABSTRACT ................................................................................................................................... ii
ACKNOWLEDGEMENTS ........................................................................................................ iii
TABLE OF CONTENTS ............................................................................................................. v
LIST OF TABLES ........................................................................................................................ x
LIST OF FIGURES .................................................................................................................... xii
LIST OF EQUATIONS ............................................................................................................. xiii
LIST OF ABBREVATIONS ..................................................................................................... xiv
1. INTRODUCTION......................................................................................................... 1
2. LITERATURE REVIEW ............................................................................................ 3
2.1 Overweight and Obesity .............................................................................. 3
2.2 Physical Activity and Obesity ..................................................................... 4
2.3 Physical Activity and Food Intake Regulation .......................................... 6
2.3.1. Physical Activity and Food Intake Regulation in Adults .................. 8
2.3.2 Physical Activity and Food Intake Regulation in Children .............. 9
2.4. Energy Balance and Obesity ..................................................................... 10
2.4.1. Carbohydrate Balance ....................................................................... 11
2.4.2. Fat Balance .......................................................................................... 12
2.4.3. Protein Balance ................................................................................... 12
vi
2.5. Energy Balance and Substrate Oxidation................................................ 13
2.6. Metabolic Flexibility and Obesity............................................................. 15
2.7. Metabolic Flexibility and Physical (In)Activity ...................................... 16
2.8. Physical Activity, Substrate Utilization and Food Intake Regulation .. 17
3. SUMMARY AND STUDY RATIONALE ................................................................ 19
4. HYPOTHESIS............................................................................................................. 20
4.1. Primary Hypothesis ................................................................................... 20
5. OBJECTIVES ....................................................................................................................... 20
5.1. Overall Objective ....................................................................................... 20
5.2. Specific Objective ....................................................................................... 20
6. MATERIALS AND METHODS ....................................................................................... 21
6.1 Experimental Design .................................................................................. 21
6.2 Participants ................................................................................................. 23
6.3 Screening Session ....................................................................................... 23
6.4 Experimental Sessions ............................................................................... 25
6.5 Preload Treatment ..................................................................................... 26
6.6. Exercise Treatment .................................................................................... 26
6.6.1. Exercise Protocol for Children .......................................................... 27
6.6.2. Exercise Protocol for Adults .............................................................. 28
6.6.3. Resting Protocol .................................................................................. 28
vii
7. MEASURES AND DATA ANALYSIS ............................................................................ 29
7.1. Food Intake ................................................................................................. 29
7.2. Blood Glucose Measurements ................................................................... 30
7.3. Collection of Ventilatory Gases ................................................................ 30
7.4. Measurement of Physical Fitness ............................................................. 31
7.5. Maximum Oxygen Consumption.............................................................. 31
7.6. Ventilation Threshold ................................................................................ 32
7.7. Substrate Oxidation and Energy Expenditure ........................................ 34
7.8. Assessment of Body Fat Percentage ......................................................... 37
7.9. Estimation of Percentage of Maximum Heart Rate................................ 38
7.10. Visual Analog Scales .................................................................................. 38
7.10.1. Subjective Appetite ............................................................................. 38
7.10.2. Subjective Physical Comfort ............................................................. 39
7.10.3. Subjective Energy/Fatigue and Stress .............................................. 40
7.10.4. Subjective Palatability ....................................................................... 40
7.10.5. Subjective Sweetness .......................................................................... 41
7.11. Statistical Analysis ..................................................................................... 41
8. RESULTS ............................................................................................................................... 42
8.1. Descriptive Measures ................................................................................. 42
8.2. Food Intake ................................................................................................. 46
viii
8.3. Energy Expenditure ................................................................................... 47
8.4. Net Energy Balance.................................................................................... 48
8.5. Substrate Oxidation ................................................................................... 49
8.6. Carbohydrate Oxidation ........................................................................... 50
8.7. Fat Oxidation .............................................................................................. 51
8.8. Heart Rate................................................................................................... 52
8.9. Water Consumption................................................................................... 53
8.10. Net Area Under the Curve Blood Glucose Measurements..................... 54
8.11. Blood Glucose Measurements ................................................................... 55
8.12. Visual Analog Scale Analysis .................................................................... 57
8.12.1. Subjective Appetite ............................................................................. 57
8.12.2. Thirst ................................................................................................... 59
8.12.3. Physical Comfort in Boys ................................................................... 61
8.12.4. Physical Comfort in Men ................................................................... 63
8.12.5. Preload Palatability in Boys .............................................................. 65
8.12.6. Preload Palatability in Men ............................................................... 66
8.12.7. Pizza Meal Palatability in Boys ......................................................... 67
8.12.8. Pizza Meal Palatability in Men ......................................................... 68
8.13. Correlation Analysis .................................................................................. 69
8.13.1. Correlations with Food Intake .......................................................... 69
ix
8.13.2. Associations with Net Energy Balance ............................................. 71
9. DISCUSSION .............................................................................................................. 73
10. FUTURE DIRECTIONS ............................................................................................ 82
10.1. Metabolic Flexibility and Food Intake Regulation in Obesity ............... 82
10.2. Explore the Effects of Exogenous and Endogenous Carbohydrate
Oxidation on Food Intake Regulation ...................................................... 83
10.3. Control for Appetite Hormones in Lean and Obese Subjects ............... 84
10.4. Standardization of the Time to Meal ....................................................... 84
10.5. Control for Daily Physical Activity Levels and Diet ............................... 85
10.6. Long-term Intervention Study .................................................................. 85
11. SUMMARY & CONCLUSIONS............................................................................... 86
SUMMARY .............................................................................................................. 86
CONCLUSION ........................................................................................................ 86
REFERENCES ............................................................................................................................ 87
APPENDENCIES ................................................................................................................................... 114
x
LIST OF TABLES
Table 7-1 Thermal equivalents of oxygen for the non-protein respiratory exchange ratio . 36
Table 8-1 1Mean subject characteristics of boys and men ...................................................... 43
Table 8-2 Baseline characteristics for 15 boys1 ........................................................................ 44
Table 8-3 Baseline characteristics for 15 men1......................................................................... 45
Table 8-4 1Food intake (kcal/kg) in boys and men ................................................................... 46
Table 8-5 1Energy expenditure (kcal/kg) in boys and men ..................................................... 47
Table 8-6 1Net energy balance (kcal/kg) in boys and men ...................................................... 48
Table 8-7 1Respiratory exchange ratio in boys and men ......................................................... 49
Table 8-8 1 Carbohydrate oxidation (kcal/kg) in boys and men ............................................. 50
Table 8-9 1Fat oxidation (kcal/kg) in boys and men ................................................................ 51
Table 8-10 1Heart rate (bpm) in boys and men ........................................................................ 52
Table 8-11 1Water consumption (kg/ml) in boys and men ..................................................... 53
Table 8-12 1 nAUC blood glucose levels (min*mmol/l) in boys and men ............................... 54
Table 8-131 Average Blood Glucose Concentrations (mmol/l) for boys and men ................. 55
Table 8-14 1Average appetite ratings (mm) in boys and men ................................................. 57
Table 8-15 1Average thirst ratings (mm) in boys and men ..................................................... 59
Table 8-16 1 Average physical comfort (mm) in boys .............................................................. 61
Table 8-17 1Average physical comfort (mm) in men. .............................................................. 63
xi
Table 8-18 1Average preload palatability (mm) in boys .......................................................... 65
Table 8-19 1Average preload palatability (mm) in men .......................................................... 66
Table 8-20 1Average pizza palatability (mm) in boys .............................................................. 67
Table 8-211 Average pizza palatability (mm) in men ............................................................... 68
Table 8-221Associations with food intake (kcal/kg) ................................................................. 69
Table 8-23 Associations with net energy balance (kcal/kg) ..................................................... 72
xii
LIST OF FIGURES
Figure 6-1 Study design .............................................................................................................. 22
Figure 7-1 VET (arrow) of an adult subject identified by the VE/VO2 (solid line) over
VE/VCO2 (dashed line) method. ........................................................................................ 33
Figure 7-2 VET (arrow) of an adult subject identified by the “V-Slope” method. ............... 33
xiii
LIST OF EQUATIONS
Equation 6-1 ASCM running equation for the determination of VO2 in boys and men ...... 27
Equation 6-2 Converted ASCM running equation for the determination of grade (%) in
boys and men ....................................................................................................................... 27
Equation 7-1 RQ equation for glucose and fat ......................................................................... 35
Equation 7-2 Energy expenditure for 40 minutes of gas exchange measurements ............... 35
Equation 7-3 Equations to calculate CHOox and FATox .......................................................... 35
Equation 7-4 Durnin and Womersley equations for body density ......................................... 37
Equation 7-5 Siri equation for prediction of fat mass ............................................................. 37
xiv
LIST OF ABBREVATIONS
ANOVA - Analysis of Variance
AUC - Area under the Curve
ASCM - American College of Sports Medicine
BF - Body Fat
BG - Blood Glucose
BPM - Beats per Minute
BIA - Body Impedance Analysis
BMI - Body Mass Index
BW - Body-weight
CDC - Centre for Disease Control
CHOox - Carbohydrate Oxidation
CO2 - Carbon Dioxide
CON - Control
DEV - Physical Development
EB - Energy Balance
EE - Energy Expenditure
EI - Energy Intake
EX - Exercise
EXCN - Exercise with Control
EXGL - Exercise with Glucose
FATox - Fat Oxidation
FI - Food Intake
xv
FQ - Food Quotient
FP - Food Palatability
GL - Glucose
GLT-4 - Glut 4 Transporter
GLP-1 - Glucagon-like-peptide 1
HR - Heart Rate
HRmax - Maximum Heart Rate
LD - Long Duration
MTE - Motivation To Eat
NEB - Net Energy Balance
NW - Normal-weight
OB - Obese
OW - Overweight
OXM - Oxyntomodulin
PA - Physical Activity
PAL - Physical Activity Level
PC - Physical Comfort
PS - Preload Sweetness
PP - Preload Palatability
PP - Pancreatic Polypeptide
PYY - Peptide YY
RER - Respiratory Exchange Ratio
RQ - Respiratory Quotient
xvi
RO - Resting Oxygen Consumption
ROb - Resting Oxygen Consumption Boys
ROm - Resting Oxygen Consumption Men
SECN - Sedentary Condition with Water
SEGL - Sedentary Condition with Glucose
SED - Sedentary Behaviour/Rest
SD - Short Duration
SEM - Standard Error of the Mean
SKF - Skinfold
SI - Suprailiac
Speedb - Running Speed Boys
Speedm - Running Speed Men
SS - Subscapular
TRT - Treatment
TVV - Television Viewing
VAS - Visual Analog Scale
VE - Ventilatory Equivalent
VET - Ventilatory Threshold
VO2 - Oxygen Consumption
VCO2 - Carbon Dioxide Consumption
VO2peak - Peak Oxygen Consumption
WHO - World Health Organisation
1
1. INTRODUCTION
The World Health Organisation (WHO) defines obesity as, “abnormal or excessive fat
accumulation that presents a risk to health.” It is caused by a disturbance in the equilibrium of
energy intake (EI) and energy expenditure (EE) and obesity is one of the top ten preventable global
diseases [1]. From 1978 to 2004, the number of obese Canadian adults has more than doubled and
childhood obesity has tripled [2]. In particular, class III obesity, which is defined with a body mass
index (BMI) of greater than 40, has witnessed an increase from 0.4% to 1.3% from 1990 to 2003
in Canada [3]. Overweight and obesity now characterize 31 % of children and adolescents in the
US and Canada [4]. Additionally, obese children and adolescents are at a greater risk of staying
overweight throughout maturation and developing severe forms of obesity into adulthood [5]. This
rapid increase is predicting enormous public health costs due to the potential long-term health
impacts of obesity.
The increased consumption of high-caloric foods and decrease of EE has been associated
with the increased phenomenon of obesity, which now characterizes more than half of the
Canadian population [6-9]. Obesity plays an essential role in the pathophysiology of
cardiovascular diseases such as hypertension, atherosclerosis [10] and metabolic impairments such
as insulin resistance, dyslipidemia, and type 2 diabetes mellitus [11]. As part of the metabolic
syndrome, obesity is highly correlated with greater mortality [12], and an increased risk for liver,
intestinal, pulmonary, endocrine and reproductive dysfunctions. The annual cost of obesity related
conditions has been estimated to be at 4.6 billion dollars in Canada alone. [13, 14].
2
Countless physical activity (PA) and dietary programs have been designed to counteract
this epidemic by creating a behavioural change without much success. Less attention has been
given to understanding of physiological relationships of EE, energy balance (EB), food intake (FI),
appetite regulation and their impact on obesity. Therefore the focus of this research is on the
physiology of appetite regulation.
The following sections provide a brief description of the obesity epidemic, followed by a
discussion of the physiological interrelationship of PA, EB, and substrate oxidation on FI
regulation.
3
2. LITERATURE REVIEW
2.1 Overweight and Obesity
Obesity is a chronic medical condition characterized by an accumulation of excess body
fat is presented with pathophysiologic consequences. A person with a BMI ≥ 25 kg/m2 is
considered overweight; a person with a BMI of ≥ 30 kg/m2 is considered obese. Those classified
as class I obesity have a BMI of 30-34.9, class II a BMI of 35-39.9 and class III a BMI of ≥ 40
[15]. In children, the diagnosis of obesity is based on percentile charts established by the CDC
BMI-for-age growth charts [16]. It is the standard method to classify obesity and overweight for
children and adolescents from 2 to 20 years of age. A child is considered overweight if he/she is
above the 85th percentile and obese if above the 95th percentile for the age specific BMI [17].
In 1997, the WHO officially named obesity as a worldwide epidemic [18]. As of 2005, the
WHO estimated that at least 400 million adults are obese, and obesity rates are increasing [18].
Particularly, Canada, United States and Australia show a greater increase in obesity when
compared with the global rate. Research conducted in the 2009-2011 Canadian Community Health
Survey reported that 61.1 % of Canadians older than 18 years were overweight, of which 23 %
were obese. In children and adolescents aged 5 to 17 years of age, 31.5 % were overweight, of
which 11.7% were classified as obese [19]. It is of concern that these proportions have tripled over
the past 25 years in children and adolescents [20].
Obesity is related to a number of complex and multifactorial diseases. It can lead to
ischemic heart disease [21], congestive heart failure and high blood pressure [22]. Endocrinologic
and reproductive conditions associated with obesity include diabetes mellitus type II, infertility
4
and birth defects [22] and various types of cancer such as breast, ovarian, liver, pancreatic, prostate
and colorectal cancers [23]. Gastrointestinal and respiratory disorders involve sleep apnea, asthma
[24], gastrointestinal reflux disease [25], fatty liver disease and cholelithiasis [22]. Additionally,
obese and overweight individuals often suffer from depression and/or social stigmata [22].
An imbalance between EI and EE is thought to play a key role in the development of
obesity. The over-consumption of calories combined with decreases in PA are considered essential
underlying causes for the development of obesity. Therefore, the interaction of PA and appetite
regulation is explored in the following sections.
2.2 Physical Activity and Obesity
In recent decades, there has been a large shift towards a decrease in PA and an increase in
EI and fat intake [26-28]. In adults, PA has declined due to less physical demanding work and a
greater use of modern conveyance [26, 29, 30].
PA is defined as any movement that results in an increase of EE when compared to resting
conditions. PA occurs in daily life and includes occupational, sports, conditioning, household and
other activities. Exercise (EX), as a subgroup of PA is defined as a planned form of PA, which
incorporates structured body movements designed to enhance physical fitness [31]. EX includes
occupational sports, conditioning and recreational activities. Evidence that highlights the
significance of PA and EX in maintaining cardiovascular health and preventing diseases has been
increasing over the past decades [32]. It shows that physically active individuals are less likely to
develop stroke [33], some forms of cancer [34], type 2 diabetes [35] and obesity [36]. Conversely,
a decrease in PA is strongly correlated with an increase in body mass index (BMI) and waist-hip
5
ratio and waist circumference [37, 38], which is accompanied by a loss of aerobic performance
[39]. The decrease in PA is also directly linked with increased occurrence of various risk factors
related to metabolic syndrome and cardiovascular diseases [40]. Some research suggests that
sedentary (SED) behaviour is an independent predictor of metabolic risk, even if the individual’s
PA meets current guidelines [41].
The WHO recommends that adults aged 18 or older, participate in at least 150 minutes of
moderate to vigorous activity a week or the equivalent of 30 minutes of daily activity [42].
Currently, just over 15% of Canadian adults are meeting the PA guidelines. In obese populations,
these numbers are even lower [43]. Obese men in Canada only achieve 19 minutes of daily activity.
Daily physical activity levels (PAL) are evaluated by a person’s daily energy expenditure divided
by his or her basic metabolic rate [44]. Some studies of PALs in sedentary and obese individuals
found that they have PALs, of 1.4-1.5 which is comparable to PALs in bed resting individuals [45,
46]. Bed resting and low PALs increase ectopic fat storage, impair lipid trafficking, increase
insulin resistance and decrease fat oxidation (FATOX) [45].
Following a similar trend, the decrease in PA is associated with weight gain in children
[47]. According to the current Canadian PA guidelines, 50% of boys and 68% of girls are
categorised as inactive. Children participating in organized sports are unlikely to meet current PA
recommendations of 16,500 steps a day [48]. To achieve this, PA equivalent of at least 60 minutes
of moderate to vigorous PA per day is suggested for healthy development during childhood [48].
The decline in PA among children has been attributed primarily to decreased time walking and
increased time spent playing video games and television viewing (TVV) [49, 50]. In Canada in
2004, 36% of all children aged 6-11 spent more than two hours per day in front of a screen. Obesity
6
rates in children with two or more hours of screen time per day are doubled compared to those
who were exposed to screen time for one hour or less [20].
The contribution of reduced PA to obesity pathophysiology has been suggested to occur
via two pathways: firstly through decreasing EE, and secondly by a failure to compensate in EI.
2.3 Physical Activity and Food Intake Regulation
The interaction between PA, EX and FI regulation is multifactorial and very complex.
Factors such as age, caloric intake, obesity, metabolic function and physical fitness are all involved
in regulation of FI. Additional difficulties in interpreting and finding consistency in the literature
occur because of the different study treatments prior to measuring FI, including variations in
composition and quantity of the preload, time to next meal, control of FI prior to study sessions,
the EX mode, intensity, duration, frequency and the individual’s training status.
It is generally accepted that habitual PA counteracts obesity and helps to maintain a healthy
body weight in children and adults. In a 12 month study of the effects of military training,
substantial improvements were found in body weight, waist circumference, BMI, body
composition measured by bioelectrical impedance analysis (BIA) and aerobic performance [51].
Similarly, in a longitudinal study in the eating routines of 5-year-old children (e.g. eating together
as a family, having the TV on during meals, duration of meals, etc.), PA and TVV behaviour with
weight status development until age 8 were studied. Both TVV and SED patterns significantly
increased the risk for becoming overweight at an early age and more physically active children
7
were less prone to develop obesity [52]. A review of key factors reducing abdominal fat also found
that regular EX reduces body adipose tissue deposits both in obese and overweight subjects [53].
PA and EX exert a beneficial impact on body weight beyond what can be attributed to their
energy cost alone. Studies as early as the 1930s found an increase in energy metabolism that
persists for many hours following EX [54, 55]. Decades later, studies demonstrated that the resting
metabolic rate was greater in endurance-trained individuals than that predicted by their body
weight [56]. Therefore, it would be expected that the energy cost of PA and the related increase in
post-EX metabolic rate would induce body weight loss if no compensation in EI occurred over
time. Consequently, there has been considerable investigation of the impact of both short- and
long-term effects of PA and EX on the regulation of EI and EB.
PA has been associated with a more accurate regulation of FI and equilibrium in EB [57].
One of the earliest reported studies on this effect was conducted in an Indian male population
which measured FI in workers carrying out SED and medium to hard work [58]. The study found
that EI and EE were mismatched in individuals carrying out SED work. EI and body-weight were
higher in workers performing SED work when compared to workers with medium to high
demanding occupations. The matching homeostasis between EI and EE in SED individuals
compared to individuals who are active, is in accordance with findings from other studies [59, 60].
One other study showed improvements in FI regulation after an EX intervention. SED adults who
exercised for six weeks, were given either a high- or a low-caloric drink followed by an ad libitum
buffet meal 60 minutes following EX [61]. After the EX intervention, the participants showed a
greater average compensation of FI (79.5%) for the caloric content of the drinks when compared
with their SED response (8.9 %) [61].
8
2.3.1. Physical Activity and Food Intake Regulation in Adults
Most studies in adults show that in the short-term, large energy deficits, due to high levels
of PA, lead to increased FI and are tolerated in part by decreasing other daily activities. No change
in EI at a subsequent meal was reported when lean men exercised once at 70% of their maximum
oxygen uptake (VO2peak) for 50 minutes, expending an average of 1191 kcal [62]. Even exercising
for seven days did not increase EI in men who increased EE by 765 kcal/day by completing three
40 minute period of cycling per day [63]. The lack of adjustment in FI was explained by a decrease
in non-structured daily activities, such as taking the elevator instead of stairs. This compensational
decrease in EE accounted for 25 - 30% of the EE induced by EX [63]. Similarly, females failed to
compensate for the EE of EX. When women expended an additional 453 kcal/day or 812 kcal/day
by cycling for seven days, total daily EE decreased over time during their EX interventions. This
is likely due to the same behaviour changes that were observed in men [64]. Partial compensation
of only 30% of the EE was accounted for by the reduction of non-structured PA [64]. However,
another study with a similar approach found that women tolerated an EE of 907 kcal per day for
14 days but compensated only partially (30%) by increasing FI [65].
This responsiveness in FI regulation to PA may depend on habitual PAL and weight status.
Woo et al. conducted two similar studies which investigated the effect of 19 days of a SED, mild
EX and moderate EX condition on FI regulation and found that lean active women match EE by
increasing EI and maintained a stable EB for all three treatments [66]. However, obese women did
not [67].
9
2.3.2 Physical Activity and Food Intake Regulation in Children
As noted previously, low levels of PA may desensitize FI regulatory mechanisms and
precede weight gain. However, it is unclear if EB is primarily determined by EE or FI in children
[68]. Based on PA information collected twice a year by accelerometer studies in children, the
children with the highest PA had significantly lower BMIs and sum of skinfolds (SKF) than the
low or moderate activity groups [68]. Shorter studies modified PA patterns in children for three
weeks by increasing sedentary behaviours, such as the time spent watching TV and playing video
games, found increased EIs [69-72]. Conversely, a reduction of SED activities (TV viewing, video
games) resulted in lower EI and higher PA in healthy body weight boys when compared to boys
with lower BMI Z scores [69-72]. In obese boys, PA decreased when SED activities decreased
[71]. An elevation of daily EB was observed with increase in SED behaviours (350 kcal), leading
to an increase of BW of 0.32 Kg per week [72].
One study did show differences in EI but induced a significant negative EB after EX [73].
The study of 19 girls assessed differences in EI following one SED and two equicaloric EX
protocols performed one week apart. The EX protocols consisted of cycling at a low (50%
VO2peak) and high (75% VO2peak) intensity until an EE of 360 kcal was reached [73]. The
sessions lasted between 38 and 56 minutes according to the intensity. FI, measured at an ad libitum
lunch and dinner, either 75 or 105 minutes after the completion of the EX or SED session, did not
differ between the different intensities. Showing that FI may not be responsive to EX in children
[73].
Other acute short-duration studies have also failed to show an effect of EX on FI. When 9
to 14 year old boys were asked to EX at their ventilatory threshold (VET) for 12 minutes, expending
10
50 kcal, an increase in appetite was found. However, FI was not measured [74]. A follow up study
of moderate short (15 minutes) and long-duration EX (45 minutes) on post-EX FI in 9 to 14 year
old boys and girls found no effect on FI [75]. Similarly, a third study failed to detect increases in
post-EX FI in either lean or obese boys who exercised for either 15 minutes at their individual
ventilatory threshold (VET) or 25% above. When the boys received either a non-caloric sweetened
control or GL drink in random order 5 minutes after EX or an SED activity, it was found that FI
decreased after the GL preload, but was not affected by EX [76]. As a result, EX reduced EB over
the duration of the experiments in overweight/obese but not in normal-weight boys. This suggests
the regulation of FI in overweight/obese boys in response to a GL drink is similar to normal-weight
boys, but it may be less responsive to EX, resulting in an improved EB [76].
In summary, it is clear that increased PA increases EE but its mechanisms on FI regulation
are unresolved. One reason may be due to the adaptations that occur in substrate oxidation with
PA and the variability induced by body fat. It is well known that each of the macronutrients
contributes to intake regulation through different mechanisms. However, the primary sources of
energy during EX are glucose and fatty acids; how their oxidation impacts the effects on FI
regulation has received little attention. The following section gives a description of the effects of
macronutrients (protein, carbohydrate and fat) on FI and EB, and is followed by an evaluation of
the role of substrate oxidation in regulation of FI.
2.4. Energy Balance and Obesity
Individuals with low EE, low levels of PA and excess levels of EI are particularly
vulnerable to weight gain. This can be explained in part by the utilization and storage of energy
11
from macronutrients and their effect on FI. Carbohydrates, fat and protein contribute to intake
regulation through the glucostatic, lipostatic and aminostatic mechanisms, respectively.
2.4.1. Carbohydrate Balance
Carbohydrates are stored as glycogen [77]. Daily EI in form of carbohydrates accounts for
up to 50–100 % of the total energy stored as glycogen. Therefore carbohydrate oxidation (CHOOX)
is decreased or increased, in order to keep the energy stored as glycogen in balance [78]. However,
an individual’s energy storage of glycogen is limited to a range of 2.000 – 4.000 kcal [79], and
shows much greater fluctuations within the day and from day-to-day than energy storage of fat and
protein. In humans, a conversion of carbohydrate to fat in the liver occurs exclusively when daily
carbohydrate intake exceeds total daily energy expenditure [80]. Carbohydrates provide signals to
FI regulatory systems by several mechanisms including their stimulation of gut peptides and
endocrine signals [81]. Their effects are highly correlated with blood glucose which led to the
glucostatic theory of appetite control more than 50 years ago. This theory states that decreased
glucose utilization or ‘metabolic hypoglycemia’ occurs at the point where the peripheral
arteriovenous difference in blood glucose becomes negligible. As a result, glucose entering
‘metabolizing cells’ and conversion to energy is decreasing, signalling hunger. This signalling
process is thought to account for the short term control of hunger, satiety and satiation [81].
12
2.4.2. Fat Balance
Compared with other macronutrients, fat is the largest energy store in the body. In healthy
individuals, energy stored as fat is approximately 140,000 kcal and six times larger than the energy
stored as protein. In obese individuals, it can be several times larger than that [82].
Adaptations in substrate utilization in response to dietary fat intake are slow to take place.
In conditions of overfeeding fat intake is readily stored as body fat since FATOX does not adjust
rapidly to the dietary intake [82] and increased FATOX may take up to 7 days [83]. As a result, fat
balance is virtually equal to total EB [82].
The lipostatic feedback theory of FI regulation, proposed by Kennedy in 1953, is based on
the idea that fatty acids signal the amount of body fat to the brain. In return, the brain compares
the current level with a desired target level (the set-point), regulating FI and EE according to body
fat stores [84]. FATOX is believed to play a primary role in long-term but not short-term regulation
of FI [81].
2.4.3. Protein Balance
Protein balance is tightly controlled, and is achieved on a day-to-day basis [77]. The total
energy derived from energy stored as protein represents about 24.000 kcal [82]. Unlike energy
stored as fat, higher protein intake than required does not increase the amount of energy stored as
protein. Only growth stimuli, such as growth hormone, androgens, physical training and weight
gain will increase storage of energy as protein [85].
13
The aminostatic theory of FI regulation, as first proposed by Mellinkoff in 1956 [86], is
based on appetite suppression that is triggered due to a rise of serum amino acid levels. In the past
few decades, the regulation of FI based on amino acid sensing systems in the brain has been
investigated [87]. Many studies have focused on the role of amino acids such as tryptophan,
tyrosine and BCAAs as hypothalamic signals controlling satiety and satiation [88].
In more recent years, it has become apparent that these theories do not fully explain the
complexity of FI regulation. However, the principle that they are different in the way they stimulate
FI regulatory mechanisms and that metabolism affects EI and EB remains fundamentally sound.
Of interest to the present research is that while the role of substrate oxidation has been explored as
a factor in physical performance, its role in FI regulation has received little attention. The
interaction of EB with substrate oxidation is discussed in the following sections, followed by a
description of disturbances in substrate oxidation and metabolic flexibility in obesity and the role
of PA in their modulation.
2.5. Energy Balance and Substrate Oxidation
Although obesity is a complex and multifactorial problem in origin, a decreased ability of
obese and overweight individuals to adequately oxidize substrates may also contribute to obesity
[89-91]. The role of fuel utilization in the control of FI was of interest in the 1990s. However, the
focus subsequently shifted towards the study of pre-absorptive hormones and brain mechanisms
in response to macronutrient ingestion as the primary factors in control of FI, as a more promising
cause of obesity than the role of fuel utilization [92]. Although the interest in the role of fuel
utilization has declined, the issue was never resolved [93].
14
Substrate oxidation in humans as measured by the respiratory quotient (RQ) or the
respiratory exchange ratio (RER), was described as early as the 1930s [94]. The RQ (RER) is
usually measured by indirect calorimetry and calculated as the ratio of carbon dioxide production
to oxygen consumption. Depending on the net metabolic needs of the body at a given moment, the
ratio ranges from 0.7 to 1. The ratio is determined by the composition of substrates that are utilized:
1.0 for 100% CHOOX and 0.7 for 100% FATOX. With normal activity levels, the ratio ranges
between 0.80 and 0.85. In conditions that elicit a high production of CO2, such as overfeeding, it
can be as high as 1.0–1.3 and indicates lipogenesis [95].
In the 1980s, the RQ : Food Quotient (FQ) concept was proposed. The concept was based
on the hypothesis that under normal conditions, the body matches substrate oxidation to the
macronutrient composition of the ingested food [89, 96], thus describing the variations in EB and
its correlation to variations in macronutrient balance [56]. Due to the daily variation of EE and EI,
changes in substrate homeostasis occur constantly. In response to an increased carbohydrate
intake, the oxidation of carbohydrates may shift rapidly towards an increased CHOOX while FATOX
is decreased, resulting in an increased RER [89, 97]. In very low carbohydrate diets, CHOOX will
decrease while FATOX is increased [98]. Fat utilization responds relatively slowly to dietary fat
and is therefore stored directly as adipose tissue [83, 89]. These changes in substrate utilization
are reflected by the RER [97].
Substrate utilization during EX can vary greatly and is determined by many factors
including intensity, type, duration, fitness levels, body weight, whether the person is exercising in
a fasted state and whether carbohydrates are ingested during the EX. Additionally, the ability to
utilize GL during EX is not based on insulin secretion but rather on muscle contraction itself [99],
15
resulting in an intact CHOOX even if metabolic impairments such as insulin resistance are present
[100].
In healthy individuals at low EX intensities (25% VO2peak), almost all energy is derived
from plasma fatty acids [101]. When EX intensity increases to moderate intensity (50-60%
VO2peak), total FATOX increases to its peak [101]. Above this crossover point, energy
requirements reach levels where FATOX cannot meet them and approximately half of the energy
is provided by carbohydrates [101]. In healthy individuals, the aerobic/anaerobic threshold occurs
approximately at this crossover point [102]. At EX intensities > 85% VO2peak, the energy is
predominately supplied by muscle glycogen and CHOOX. As soon as energy stored as carbohydrate
depletes, FATOX cannot supply energy at rates sufficient for high EX intensities [101].
2.6. Metabolic Flexibility and Obesity
Metabolism and the utilization of substrates is generally determined by an individual’s
demand to generate adenosine triphosphate to maintain body temperature and movement. The
adjustment of substrate utilization is called “substrate shift” or “substrate choice”. The term
metabolic inflexibility as first proposed by Kelley et al., defined a “metabolic deregulation that
impairs the capacity to increase FATOX when fatty acid availability is increased and to switch from
fat to GL as primary fuel source after a meal” [103, 104]. It has also been defined as “the
incapability of the body or cells to match fuel oxidation to fuel availability and the endocrine
environment.” [85]. Impairments such as insulin resistance, hyperinsulinaemia, reduced lipid
trafficking and hyperlipidemia, increased RER during EX, shift in muscle fibre type and ectopic
fat storages are also often stated as characteristics of metabolic inflexibility [105].
16
In inactive and especially inactive obese and overweight individuals, impairments of the
ability to shift substrates seem to be present [45, 105-108]. This is described by a heavy reliance
upon carbohydrates under fasted conditions [109] and an inability to increase CHOOX under
insulin-stimulated conditions [110].
The capability to appropriately shift substrates is reduced in obese individuals and a
consistently high fasting RER has been associated with weight gain [98, 111-113]. Formerly obese
individuals have a higher RQ than never-obese individuals and experience greater weight regain
following weight loss [114-117]. Obese and formerly obese individuals also display a blunted
increase in FATOX following weight loss [109], potentially contributing to an individual's
susceptibility to overconsumption and weight gain [114-117].
2.7. Metabolic Flexibility and Physical (In)Activity
Some studies suggest that SED behaviour is an autonomous contributor to metabolic
inflexibility, even if the current guidelines for PA have been met [118]. Physical inactivity is one
of the primary augmenters in the progress of developing metabolic inflexibility [105]. Individuals
who follow SED daily lifestyle patterns are more likely to develop obesity and insulin resistance
[119, 120]. One study showed an increase in insulin resistance in healthy individuals after 1-3
weeks of bed rest [121]. Studies investigating three months of bed rest have also shown decreases
in FATox of up to 37% and increases in CHOOX of 21% [106]. Other studies that investigated bed
rest have discovered an increased RER of 4-14% [106, 107, 122]. This increase was inversely
correlated with metabolic flexibility [123], which is further aggravated by excess adipose tissue
[124].
17
In contrast, high PALs improve outcomes related to metabolic inflexibility. Several studies
have shown beneficial effects, of PA and EX on metabolic flexibility and substrate utilization, in
children and adults. Trained men have significantly higher aerobic capacities when compared to
untrained men [125]. This indicates that trained individuals are more reliant on FATOX and are
therefore more metabolically flexible. In children, Bell et al., showed that an 8 week EX program,
consisting of 3 x 1 hours sessions per week improved cardiorespiratory fitness, insulin sensitivity
and the lipid profile of obese children [126]. Schmitz et al., observed similar findings during a
hyperinsulemic clamp study in 357 non-diabetic children. He found a strong positive correlation
of PALs with insulin sensitivity and lipid profiles [110]. Another study has shown that pubescent
boys display significantly higher rates of FATOX during EX when compared with their obese
counterparts [127].
To summarize, PA contributes to metabolic flexibility because of an increased ability to
oxidize fat. Individuals with impaired capacity to up-regulate FATOX may also signal a promotion
of FI. Although it is known that EX improves insulin resistance, no study has investigated the
benefits of EX intervention programs on metabolic flexibility and FI regulation.
2.8. Physical Activity, Substrate Utilization and Food Intake Regulation
Substrate metabolism may also act as a biological determinant of eating behavior, rather
than being a response to EX or FI. Although there have been few studies, substrate metabolism
has been attributed to post-EX compensatory eating. Although no mean increase in EI was reported
in 11 lean men following 90 minutes of cycling (60% VO2peak), when participants were
retrospectively divided into 'high' or 'low' fat oxidizers based on their RQ, post-EX EI was
18
significantly lower in the high-fat oxidizers. EX induced a -406 kcal net energy deficit in the high-
fat oxidizers, but a net positive EB of a similar order in the low-fat oxidizers [48]. The group
suggested that a low RQ attenuates EX-induced glycogen depletion and therefore decreases EI in
the high-fat oxidizers [48]. Other studies also have reported similar results [49, 50, [128].
Obesity has been proposed to modify the metabolic control of EI due to body- and skeletal
muscle-related impairments in FATOX associated with adiposity [92, 129]. As a result,
metabolically inflexible individuals who display a blunted ability to up-regulate FATOX during EX
may be more susceptible to compensatory eating. In addition, enhanced reliance upon CHOOX
during EX could induce reductions in stored glycogen, blood glucose and consequently enhance
the drive to restore availability via feeding as proposed by the glucostatic hypothesis of FI
regulation.
In summary, the role of substrate oxidation as influenced by metabolic flexibility and/or
PA, on FI regulation has not been reprised. The objective of this thesis research is to begin to
examine these relationships.
19
3. SUMMARY AND STUDY RATIONALE
The relationship between substrate oxidation and FI has not been investigated. It is well
accepted that habitual EX can help to improve metabolic flexibility [125, 130] as well as FI
regulation [61, 129]. Obese and SED populations often display signs of metabolic inflexibility
when compared to lean individuals such as a lower RER and the impaired ability to oxidize fat
[105]. Similar to the comparison of lean and obese individuals, pre-pubertal boys have been shown
to have a better metabolic flexibility and therefore lower RER values and higher rates of FATOX
when compared to adults [131]. The study, as part of this thesis, will examine substrate oxidation
and its relationship with FI. The study will examine RER in normal weight boys and young men,
without confounders of insulin resistance and hyperinsulinaemia which are present in obese
populations [105, 132]. This research will also aid in the understanding of the general effects of
RER on post-EX FI.
20
4. HYPOTHESIS
4.1. Primary Hypothesis
An elevated RER, indicating an increased carbohydrate relative to fat oxidation, is
associated with an increased FI at a later meal.
5. OBJECTIVES
5.1. Overall Objective
To examine the relationship between substrate oxidation and short-term FI in normal-
weight pre-pubertal boys and young adult men.
5.2. Specific Objective
To describe the effects of a GL preload, EX, and GL with EX combined, on substrate
oxidation and FI in normal-weight pre-pubertal boys and young adult men.
21
6. MATERIALS AND METHODS
6.1 Experimental Design
Fifteen normal-weight boys and fifteen normal-weight male adults were recruited through
posters at the University of Toronto Athletic Centre and recruitment letters which were sent to
local sports clubs (Appendix 4A + 4B + 8A +8B). The experiment followed a 2 x 2 x 2 factorial
repeated measures randomized design, generated with a random generator script in SAS version
9.2, with four experimental sessions separated by one week. For each session, including the
screening session, subjects arrived after a 12-hour overnight fast. Subjects received four
treatments, which included: 1) Water preload in a SED condition (control), 2) GL in a SED
condition, 3) Water in an EX condition (control), 4) GL in an EX condition. Participants were
blinded about the type of treatment. Heart rate (HR), gas exchange, subjective appetite and blood
glucose (BG) were measured throughout the session. Five minutes after the completion of the SED
or EX, the participants were provided with an ad libitum pizza meal. Short-term FI reflected each
individual’s net energy pizza consumption.
22
Figure 6-1 Study design
Visual Analog Scale Legend 1 1.0 g kg-1 bodyweight GL (adults) or 1.2 g kg-1 bodyweight GL (children) preload was given in an opaque covered
mug with a straw and consumed within 5 min
2 250ml (children) or 350 ml (adults) water control was given in an opaque covered mug with a straw and consumed
within 5 min
3 Pizza lunch and a 500 ml bottle of spring water was presented with the test meal at 85 minutes for children and 95
minutes in adults
4A was presented with the test meal at 85 minutes for children and 95 minutes in adults
5Motivation-to-Eat (MTE) VAS administered to determine subjective appetite and thirst
6Physical Comfort (PC) VAS was administered to determine subjective physical well-being
7Drink Sweetness (PS) VAS was administered to determine subjective sweetness of the preload
8Drink Palatability (PP) VAS was administered to determine subjective palatability of the preload
9Food Palatability (FP) VAS was administered to determine subjective palatability of the test meal
10Energy Fatigue (EF) VAS was administered to determine subjective energy/fatigue ratings in adults
GL/CON1,2
EX/SED EX/SED
Pizza lunch3
Time (min): -1 0 5 15 35 40 60 65 85/953
MTE4 MTE4 MTE4 MTE4 MTE4 MTE4
PC5 PC5 PC5 PC5 PC5 PC5
EF9 PS6 EF9 EF9 EF9 FP
PP7 EF9
EF9
23
6.2 Participants
Participants born at full-term and with normal birth weight were included in the study.
Those taking any medications that could interfere with study outcomes, with significant learning,
behavioural, injuries or emotional difficulties were excluded. Participants who volunteered to
partake in this study were first tested for eligibility using a telephone questionnaire (Appendix 2A
+ 2B). Participants were also asked to select the type of pizza they would eat during the test visits.
All study sessions took place on weekend mornings for children at either 9:00 am or 10:00 am and
weekday mornings at either 8:00 am or 9:00 am for adults. Participants were asked to arrive at the
same day and time for each of the following sessions. If subjects arrived more than 30 minutes
late, the session was postponed to another day. Prior to the first study visit, the parents and child
were given a tour of the facility to familiarize the child with the study rooms and minimize his
apprehension during the first test visit.
6.3 Screening Session
If the initial inclusion criteria were met, the adults or the children along with their parents
attended a screening session at the University of Toronto Athletic Centre, where the study was
explained to them. An informed written consent was obtained from the adults or the parents and
their children (Appendix 5A + 5B). The BG measurements were voluntary for children. Parents as
well as the child had to give their consent. Participants were asked to fill out questionnaires about
food acceptability, food preference, sleep habits and previous PALs. Children additionally filled
out questions about their Tanner staging (Appendix 3A).
24
After that, height, weight and body composition by SKF calipers were assessed (Appendix
3A + 3B). Physical fitness was measured by VO2peak and VET.
To evaluate EX intensity and physical fitness, a continuous incremental walking protocol
on a motorized treadmill was utilized. A continuous and progressive walking protocol based on a
VO2peak of 65 ml·kg-1·min-1 was employed on a motorized Trackmaster TMX 425 CP treadmill
(Full Vision, Newton, KS, USA) to determine the slope and speed to maintain the EX intensity at
a RER of 0.82. The measurement of ventilatory gases identified the VET and VO2peak as well as
the RER of 0.82, which translates into an approximate CHOOX of 40% and FATOX of 60%. The
identified slope and speed was then employed during the experimental EX sessions. It required a
fast walk during all stages of the protocol, but depending on participants’ height and running
mechanics, some were more comfortable running than walking to achieve the target speed. The
final stage was determined by the participants’ fitness and effort. To allow collection of ventilatory
gases, they were fitted with a Hans-Rudolph mouthpiece/facemask with a Hans Rudolph two-way
non-rebreathing valve (Hans Rudolph, Inc., Shawnee, KS, USA). A Polar Monitor was used to
detect HR (Polar Electro Inc. Lake Success, NY, USA). Participants were asked to refrain from
eating before the screening session.
The participants were able to stop the treadmill at any time if they were uncomfortable with
the protocol or the measurements. The accuracy of speed and incline of the treadmill were verified
before the start of the study. The test was performed at the Human Physiology and Performance
Laboratory (University of Toronto - Athletic Centre, Toronto, ON, Canada) after an overnight fast.
Subjects that met the eligibility criteria were scheduled for the experimental sessions.
25
6.4 Experimental Sessions
Adults started the session on a weekday morning at either 8:00 am or 9:00 am and children
started their sessions on a weekend morning at either 9:00 am or 10:00 am, following an overnight
fast. Subjects were allowed to consume water until one hour before each session. Each subject
arrived at the same chosen time for each session. Subjects were instructed to refrain from any
unusual EX and activity the day before the study sessions.
Upon their arrival to the University of Toronto Athletic Centre, participants were asked to
change into EX clothing so they could not anticipate the treatment. A fasting BG sample was
obtained and recorded in the session sheet (Appendix 7), prior to the completion of the first visual
analog scale (VAS) questionnaires assessing their “Sleep Habits”, “Stress Factors”, “Food Intake
and Activity Level” and “Feelings of Fatigue”. If subjects reported significant deviations from
their usual patterns, they were asked to reschedule. In this study, six participants had to reschedule
due to not arriving in a fasted state and/or showing elevated fasting BG levels.
Fifteen minutes before the start of the EX or SED sessions, participants consumed the
preload treatment consisting of a GL solution or a water control. Subjects were then prepared for
the gas exchange measurement for another 10 minutes and started exercising at 15 minutes.
Participants exercised for 45 minutes in 2 x 20 minute periods with a 5-minute break at an intensity
following an RER of 0.82. A Polar HR monitor was used to measure HR during the 2 x 20 minute
time periods. BG was measured four times via finger-pricks at 0, 15, 35 and 60 minutes. FI was
measured at an ad libitum lunch meal (pizza), served 5 min after the end of the EX or SED session,
and the subject was instructed to eat until he is comfortably full. “Deep and Delicious” pizzas
(McCain Foods Ltd, Florenceville, NB, Canada) were served up to 30 minutes. Subjects had a
26
choice between varieties of pizza, including Three Cheese, Pepperoni and Deluxe. EI from the
pizza meal was calculated based on the weight consumed and the compositional information
provided by the manufacturer, whereas water intake was measured by weight.
6.5 Preload Treatment
Treatments consisted of either a GL preload or water (control). In adults, the preload
contained 1.0 g per kg body weight of 1.125 g per kg body weight GL monohydrate (Grain Process
Enterprises, Toronto, ON Canada) and 1.6 g of aspartame-sweetened orange flavored crystals
(Sugar Free Kool-Aid, Kraft Canada Inc., Don Mills, ON Canada) in 350 ml water. In boys, 1.2 g
per kg body weight of 1.31 g per kg body weight GL monohydrate and 1.1g of aspartame-
sweetened orange flavored crystals were added to 250 ml water. In adults, the amount of GL and
water was altered to avoid nausea. The control consisted of 250 ml water (children) or 350 ml
water (adults). Subjects were asked to consume the beverage within a period of 5 minutes.
6.6. Exercise Treatment
The EX intensity was estimated based on a VO2peak of 65 ml.kg-1.min-1 and a resting
oxygen consumption (RO) of 4.5 ml.kg-1.min-1 in boys (ROb) and 3.5 ml.kg-1.min-1 in men (ROm)
[133]. The American College of Sports Medicine (ASCM) running formula was used to calculate
the 9-2 minutes continuous stages (Equation 6-1) [134, 135]. To ensure the safety of the
participants, the running speed for the final stage of the protocol was fixed at 150 m/min for boys
(Speedb) and 250 m/min for men (Speedm). This speed was determined with a preliminary testing
27
at the University of Toronto Athletic centre. The formula was converted for the determination of
the grade incline for the final stage of the protocol. The speed and grade incline of the final stage
were partitioned to each of the nine stages to guarantee a steady incline within each stage. To
prevent an overshoot of RER, both children and adults were asked to EX at 0 % incline and a speed
of 3 km/h to warm up and become familiar with the treadmill prior to the start of the protocol.
Equation 6-1 ASCM running equation for the determination of VO2 in boys and men
VO2peak (ml/kg/min) = 0.2 × Speedb (m/min) + 0.9 × Speedb (m/min) × Grade (%) + ROb
VO2peak (ml/kg/min) = 0.2 × Speedm (m/min) + 0.9 × Speedm(m/min) × Grade (%) + ROm
Equation 6-2 Converted ASCM running equation for the determination of grade (%) in boys
and men
Grade boys (%) = [65 ml ∙ kg−1 ∙ min−1 − 4.5 ml ∙ kg−1 ∙ min−1
150 m ∙ min−1 ] − 0.2
0.9
Grade men (%) = [65 ml ∙ kg−1 ∙ min−1 − 3.5 ml ∙ kg−1 ∙ min−1
250 m ∙ min−1 ] − 0.2
0.9
6.6.1. Exercise Protocol for Children
The protocol for children started with 2-minute warm-up followed by a 2-minute rest
period. After the warm-up and rest period the treadmill started at 4.5% incline and a speed of 3
km/h. Speed and incline increased every 2 minutes by 1.5% in incline and 1 km/h in speed.
Children were asked to EX on the treadmill until a RER >1.15, a HR of > 205 BPM or a voluntary
exhaustion was achieved.
28
6.6.2. Exercise Protocol for Adults
The protocol was designed similar to that for children, based on a different resting oxygen
consumption. The protocol started at a speed of 5 km/h. Adult men were also asked to EX on the
treadmill until a RER >1.15, a HR >195 BPM or a voluntary exhaustion was achieved.
6.6.3. Resting Protocol
During resting periods participants remained sedentary and engaged in quiet games
(Sudoku, word puzzles, reading, Jenga, Dominoes, and Checkers) or reading. However, they were
allowed to get up to use the washroom. Participants were monitored by a volunteer or a research
assistant at all times who avoided the topic of food.
29
7. MEASURES AND DATA ANALYSIS
7.1. Food Intake
Two varieties of five-inch diameter pizza (McCain Foods Ltd, Florenceville, NB, Canada)
were offered for the test meal. Boys were served a total of nine pizzas with three pizzas per tray in
regular 10-minute intervals. Men were served a total of 12 pizzas with four pizzas per tray in 6:30
minute-intervals. The intervals and numbers of pizza were determined in previous studies in our
lab on adults and children. “Deep and Delicious” pizzas were selected due to their lack of crust
and uniform composition. The boys had the option of choosing between Three Cheese, Pepperoni
or a combination of both pizzas, while adults had an additional choice of Deluxe. Each pizza
contained on average 180 kcal. The energy content and macronutrient information is provided by
the manufacturer (Appendix 12).
Pizzas were cooked and then weighed and cut into four equal pieces. Pizzas were then
served and the amount left over after the meal was subtracted from the initial weight of the pizza
to determine the net weight consumed in grams. Different varieties of pizza were weighed
separately. The energy consumed (kcal) was calculated by converting the consumed net weight of
the pizza (grams) using information provided by the manufacturer. During feeding period,
participants were escorted and seated in a feeding room to minimize distractions and maintain
consistent conditions. A 500 mL bottle of spring water (Danone Crystal Springs, Quebec City, QC,
Canada) was served along with the pizza meal. The bottle was weighed before and after the meal
to determine water intake (grams). Subjects were provided with a second bottle if they finished the
first.
30
7.2. Blood Glucose Measurements
Fifteen adults and six children gave their consent and completed the BG measurements.
Each session, four finger-pricks were taken for a total of 16 throughout the study for each
individual. Finger-prick blood samples were obtained using a Monojector Lancet Device
(Sherwood Medical, St. Louis, MO, U.S.A.). One drop of blood was placed on an Accu-Chek test
strip for immediate reading of the GL concentration with the Accu-chek GL meter (Accu-Chek
Compact and Compact-Plus, Roche Diagnostics Canada, Laval, Quebec). The meters and test
strips were standardized against Assayed Human Multi-sera (Randox Laboratories LTD, Antrim,
UK). Proper procedure for obtaining blood sample was demonstrated to participants, prior to the
first session during the screening interview. The adult subjects pricked their own fingers while
supervised by the investigator. Children had their fingers pricked by the supervisor. Each subject
was assigned the same GL meter throughout the study. There was no risk of contamination because
the lancet needles were discarded after each use and each subject was provided with a sterilized
monojector device (immersed overnight in ethanol, 70%) at each session. Moreover, the
monojector device was wiped with an antiseptic isopropyl alcohol pad before inserting the
disposable sterile lancet needle. Subjects cleaned their fingers with antiseptic isopropyl alcohol
pads before pricking and were seated at a safe distance from each other to prevent cross-
contamination.
7.3. Collection of Ventilatory Gases
Ventilatory gases were collected using a Moxus metabolic cart (AEI Technologies, Inc.,
300 William Pitt Way, Pittsburgh, PA 15238, USA), a facemask and a two-way non-rebreathing
31
valve (Hans Rudolph, Inc., 8325 Cole Parkway Shawnee, KS 66227, USA). A pneumotachometer
measured inspiratory ventilation and gas analyzers measured the mixed expired gas. The O2
content was analyzed by S-3A Oxygen Analyzer and a CD-3A Carbon Dioxide Analyzer (AEI
Technologies, Inc., 300 William Pitt Way, Pittsburgh, PA 15238) measured the CO2 content of the
expired air. Known gas concentrations of 16.04% O2 and 4.06% CO2 and 20% O2 and 0.03% CO2,
were used to calibrate the metabolic cart, prior to each test.
7.4. Measurement of Physical Fitness
Physical fitness was determined by measuring the VO2peak and the VET. VO2peak is the
maximum capacity of an individual's body to transport and use oxygen during incremental
exercise, which reflects the physical fitness of the individual. The VET roughly corresponds to
lactic acid threshold, at which plasma lactic acid builds at a rate faster than that at which the body
clears lactate from circulation. The VET is a submaximal marker of aerobic fitness, which is used
clinically to monitor patients.
7.5. Maximum Oxygen Consumption
The VO2peak requires the individual to reach a maximum physical effort in order to
achieve a plateau of oxygen consumption with no further increase of the workload. These tests are
usually performed on a treadmill or a cycle ergometer. The measurement of VO2max is regarded
as the gold standard for determining cardiovascular fitness of an individual [136]. A VO2max at
plateau occurs in approximately 50% of all tests, and when not achieved the peak value is then
called VO2peak [136]. The measurement of VO2peak can be affected by a number of factors like
32
age, gender, training state, altitude changes and the action of ventilatory muscles [137]. Further
criteria, such as RER or HR, are used to indicate if an individual reached their VO2max. The
average of six breaths of the highest achieved values is usually used to identify the plateau. There
is limited evidence regarding the most appropriate oxygen uptake data averaging interval;
nonetheless, the averaging interval does not seem to affect the reproducibility of VO2peak
measurements [138].
7.6. Ventilation Threshold
The VET is an indicator of aerobic fitness. It represents a practical and non-invasive method
to approximate an individual’s lactic acid threshold [139, 140]. Intensities above the VET indicate
a more fatiguing less sustainable level of EX, causing an individual to switch from fat to
carbohydrates as predominant fuel source.
The VET of healthy untrained individuals averages at 45-65% of their individual VO2peak
[141]. It can be increased with habitual EX, as a study in marathon runners reported VET values
as high as 76% [142].
This study used the two most common methods to determine the VET. The first method
used the ratio of pulmonary ventilation (VE) divided by VO2 and VCO2. This method, identifies
the VET when there is a rise of VE/VO2 without a significant increase in VE/VCO2 [143] (Figure
7-1). The second method, the “V-Slope” method, is used if the increase in VE/VO2 over VE/VCO2
is not conclusive. In the second method, the VET is described as the point at which a change in
slope occurs if VCO2 is plotted over VO2 [144] (Figure 7-2).
33
0
525
30
35
40
45
VE/VO2
VE/VCO2
0 10 20 30 40 50 60 70 80 90 100
Percentage VO2peak
Ventila
tory
Equiv
ale
nts
(m
l·m
in-1
) VET
Figure 7-1 VET (arrow) of an adult subject identified by the VE/VO2 (solid line) over
VE/VCO2 (dashed line) method.
0 500 1000 1500 2000 2500 3000 35000
500
1000
1500
2000
2500
3000
3500
VET
VO2(ml)
VC
O2
(ml)
Figure 7-2 VET (arrow) of an adult subject identified by the “V-Slope” method.
34
7.7. Substrate Oxidation and Energy Expenditure
The RER is sometimes referred to the RQ. The difference is that RER is measured at the
mouth and is VCO2/VO2, whereas the RQ is the ratio of CO2 produced to O2 consumed at the
cellular level. Thus, RQ is dependent on the type or types of fuel substrates being used by the cell.
The measurement of RER provides a means of estimating the composition of the fuels oxidized
and represents the ratio of carbon dioxide exhaled to the amount of oxygen consumed by the
individual (VCO2/VO2). Generally RER = RQ but if the subject is hyperventilating, has an acid-
base disturbance, or is performing intense EX with an RER < 1.0, extra CO2 can result from
buffering. Thus CO2 production, measured at the level of the mouth, may not accurately reflect
CO2 production at the cellular level [145]. Furthermore, RER is a non-protein measurement
because proteins cannot be completely oxidized into CO2 and H2O and nitrogen is additionally
present. O2 consumption needed for oxidizing a protein and the resulting CO2 production could be
measured, but it would not accurately reflect protein use by the body because nitrogen cannot be
measured by RER. Furthermore, under normal circumstances in humans, less than 5% of the
energy production comes from protein oxidation and is therefore neglected in this measurement.
Although fat contains more potential chemical energy on a per unit-weight basis, carbohydrates
due to their oxygen content give more energy for a given volume of O2. A RER of 0.7 indicates
that only fat is being used as a substrate whereas a RER of 1.0 indicates that only carbohydrates
are being used, as showing in the following equations (Equation 7-1).
35
Equation 7-1 RQ equation for glucose and fat
a) Glucose
C6H12O6 + 6 O2 6 CO2 + 6 H2O
RQ = 6 CO2 produced / 6 O2 consumed = 1.0
b) Fat
C57H104O6 + 80 O2 57 CO2 + 52 H2O
RQ = 57/80 = 0.71
RER is also useful in interpreting EE, which was measured indirectly with a metabolic cart
by analyzing respired gases such as O2 and CO2. The volume of air passing through the lungs was
assessed by a pneumotachometer placed on the inspiratory side. From this value the amount of
inspired and expired VO2 and VCO2 was extracted and the RER was calculated. The measurements
of RER helped to calculate the EE (kcal) and the ratio of CHOOX and FATOX. The Weir equation
was used to calculate EE for 40 minutes of EX or SED as shown in the following example
(Equation 7-) [146].
Equation 7-2 Energy expenditure for 40 minutes of gas exchange measurements
EE (kcal) = ((1.1 × RQ) + 3.9) × VO2) × 40 minutes
The percent of CHOOX and FATOX were derived from the non-protein RER table (Table
7-1) [147] and their amount contributing to EE was calculated as in Equation 7-1.
Equation 7-3 Equations to calculate CHOox and FATox
CHOox (kcal) = EE × % kcal derived from CHO
FATox (kcal) = EE × % kcal derived from FAT
36
Table 7-1 Thermal equivalents of oxygen for the non-protein respiratory exchange ratio
RER kcal per Liter
O2 Uptake
% kcal Derived
from CHO
% kcal Derived
From FAT
Grams per
Liter O2 CHO
Grams per
Liter O2 FAT
0.7 4.686 0.0 100.0 0.000 0.496
0.71 4.69 0.1 98.9 0.120 0.491
0.72 4.702 4.8 95.2 0.510 0.476
0.73 4.714 8.4 91.6 0.900 0.460
0.74 4.727 12.0 88.0 0.130 0.444
0.75 4.739 15.6 84.4 0.170 0.428
0.76 4.75 19.2 80.8 0.211 0.412
0.77 4.764 22.8 77.2 0.250 0.396
0.78 4.776 26.3 73.7 0.290 0.380
0.79 4.788 29.9 70.1 0.330 0.363
0.8 4.801 33.4 66.6 0.371 0.347
0.81 4.813 36.9 63.1 0.413 0.330
0.82 4.825 40.3 59.7 0.454 0.313
0.83 4.838 43.8 56.2 0.496 0.297
0.84 4.85 47.2 52.8 0.537 0.280
0.85 4.862 50.7 49.3 0.579 0.263
0.86 4.875 54.1 45.9 0.621 0.247
0.87 4.887 57.5 42.5 0.663 0.230
0.88 4.889 60.8 39.2 0.705 0.213
0.89 4.911 64.2 35.8 0.749 0.195
0.9 4.924 67.5 32.5 0.791 0.178
0.91 4.936 70.8 29.2 0.834 0.160
0.92 4.948 74.1 25.9 0.877 0.143
0.93 4.961 77.4 22.6 0.921 0.125
0.94 4.973 80.7 19.3 0.964 0.108
0.95 4.985 84.0 16.0 1.008 0.090
0.96 4.998 87.2 12.8 1.052 0.072
0.97 5.01 90.4 9.6 1.097 0.054
0.98 5.022 93.6 6.4 1.142 0.036
0.99 5.035 96.8 3.2 1.186 0.018
1 5.047 100.0 0.0 1.231 0.000
37
7.8. Assessment of Body Fat Percentage
A Harpenden SKF caliper was used to measure SKFs at four sites (biceps, triceps,
subscapular and suprailiac crest) and recorded to 0.2 mm. The mean SKF of three measurements
at each site was used to estimate body fat percentage. The typical standard error of estimate for
SKF measurements in healthy individuals was previously determined at 3-5% and was also
reported to be higher in younger individuals [148]. Age specific regression equations from Durnin
and Womersley were used to determine percent body fat in boys and adults, as shown in
Equation7-4 [149]. Body fat measurements with the SKF method are considered an inexpensive
and direct procedure to assess body fat in children and adults. The density value can then be
converted to percent body fat (%BF) using the Siri Equation (Equation 5) [150].
Equation 7-4 Durnin and Womersley equations for body density
a) Boys
Body density boys = (1.1533 – 0.0643) x log (SKF biceps + SKF triceps + SKF
Subscapular + SKF Suprailiac Crest)
b) Men
Body density boys = (1.1631 – 0.0632) x log (SKF biceps + SKF triceps + SKF
Subscapular + SKF Suprailiac Crest)
Equation 7-5 Siri equation for prediction of fat mass
% BF = {4.95
body density− 4.5} × 100
38
7.9. Estimation of Percentage of Maximum Heart Rate
The maximum HR, which was measured during the screening session, was compared with
each subject’s estimated maximum HR (HRest), to determine if the subjects reached their
VO2peak. The HR was estimated according to the formula of Mahon et al. [151], in boys (HRmax
boys = 208 – age × 0.7) and the formula of Robergs et al., in men (HRmax men = 205 – age ×
0.685) [152].
7.10. Visual Analog Scales
Standardized VASs questionnaires were used to measure subjective appetite, physical
comfort, and energy/fatigue and stress as well as treatment and pizza meal palatability and
sweetness. Different questionnaire versions were used for children and adults for the assessment
of physical comfort and food/preload palatability and questionnaires on subjective sweetness were
only administered in children, whereas energy fatigue VASs were only used for adults.
7.10.1. Subjective Appetite
Motivation-to-eat VAS (Appendix 9A), which consisted of five questions, was used to
assess subjective appetite and thirst. Each question was followed by a 100 mm line with opposing
statements at either end. Subjective appetite questionnaires were asked at 0, 5, 15, 35, 60 and 85
in adults and 95 minutes in children. Subjects pencilled an “X” mark on the line to indicate their
subjective perception regarding the question. Scores were assessed by measuring the distance in
mm from the left of the line to the “X” mark. The five questions of the VAS are:
How strong is your desire to eat? (‘Very weak’ to ‘Very strong’)
How hungry do you feel? (‘Not hungry at all’ to ‘As hungry as I’ve ever felt’)
39
How full do you feel? (‘Not full at all’ to ‘Very full’)
How much food do you think you could eat? (‘Nothing at all’ to ‘A large amount’)
How thirsty do you feel? (‘Not thirsty at all’ to ‘As thirsty as I have ever felt’)
Subjective average appetite scores were determined by adding the scores of desire to eat, hunger
and how much food do you think you can eat and 100 minus fullness and dividing them by four
[average appetite (mm) = (desire to eat + hunger + (100 – fullness) + how much food do you think
you can eat)/4] [153]. Appetite scores have been calculated in previous studies [153-155]
7.10.2. Subjective Physical Comfort
Visual Analog Scales for physical comfort were assessed by ‘How well do you feel?’ with
a range of ‘Not well at all’ to ‘Very well’ in children (Appendix 9B). Physical comfort in adults
was assessed by a number of questions such as ‘Do you feel nauseous?’ with a range of ‘Not at
all’ to ‘Very much’, ‘Does your stomach hurt?’ with a range of ‘Not at all’ to ‘Very much’, ‘How
well do you feel?’ with a range of ‘Not well at all’ to ‘Very well’, ‘Do you feel like you have gas?’
with a range of ‘Not at all’ to ‘Very much’ and ‘Do you feel like you have diarrhea?’ with a range
of ‘Not at all’ to ‘Very much’(Appendix 10B). Subjective physical comfort was assessed in
children and adults at 0, 5, 15, 35, 60 and 85 in adults and 95 minutes in children. Subjective
average physical comfort scores were determined by adding the scores of ‘do you feel nauseous’,
‘does your stomach hurt’, ‘how do you feel like having diarrhea’, ‘do you feel like having gas’ as
well as 100 minus ‘how well do you feel’, and dividing them by five [physical comfort (mm) =
(do you feel nauseous + does your stomach hurt + how do you feel like having diarrhea + do you
feel like having gas + (100 – how well do you feel))/5].
40
7.10.3. Subjective Energy/Fatigue and Stress
. Subjective energy/fatigue and stress was assessed only in adults. Subjects’ subjective
energy perception was assessed by the question ‘How energetic do you feel right now? with a
range of ‘Not at all’ to ‘Very energetic’, ‘How tired do you feel right now?’ with a range of ‘Not
at all ‘ to ‘Very tired’ and ‘How anxious do you feel right now?’ with a range of ‘Not at all anxious’
to ‘Very anxious’(Appendix 10C). Subjective energy/fatigue and stress scores were assessed at 0,
5, 15, 35, 60 and 85 minutes.
7.10.4. Subjective Palatability
The enjoyment of the beverage/meal was assessed by the VAS palatability score by asking
questions such as ‘How pleasant have you found the food?’ with a range of very pleasant to ‘Not
pleasant at all’ (Appendix 9D). Adults were asked questions such as ‘How pleasant have you found
the beverage/food?’ with a range of ‘Not at all pleasant’ to ‘Very pleasant’, ‘How tasty have you
found the beverage/food?’ with a range of ‘Not at all tasty’ to ‘Very tasty’ and ‘How did you like
the texture of the beverage/food?’ with a range of ‘Not at all’ to ‘Very much’. Subjective
palatability was only assessed after the preload and the pizza lunch at 5 minutes in children and
adults and 85 minutes in adults and 95 minutes in children. Palatability scores for adults were
determined by adding the scores of ‘how pleasant have you found the beverage/food’, ‘does your
stomach hurt’, ‘how tasty have you found the beverage/food’ and ‘how did you like the texture of
the beverage/food’ and dividing them by four [Subjective palatability (mm) = (How pleasant have
you found the beverage/food + does your stomach hurt + How tasty have you found the
beverage/food + How did you like the texture of the beverage/food)/4] (Appendix 10D).
41
7.10.5. Subjective Sweetness
The sweetness VAS was only assessed in children at 5 minutes. Subjects’ subjective
sweetness perception was assessed by the question ‘How sweet have you found the beverage?’
with a range of ‘Extremely sweet’ to ‘Not sweet at all’(Appendix 9C).
7.11. Statistical Analysis
Statistical analyses were conducted using SAS version 9.2 (Statistical Analysis Systems,
SAS Institute Inc., Carey, NC). All results are presented as mean ± standard error of the mean
(SEM). Statistical significance was concluded with a 2-tail p-value less than 0.05. Repeated
measures ANOVA analysis were conducted with the “Proc Mixed” procedure.
A 3-factor ANOVA was used to determine the effects of GL, EX and age (AGE) on FI, NEB,
RER, EE, and HR. The effect of AGE and AGE interaction with GL, EX and GL with EX was
used to identify different FI and NEB responses between groups. Separate ANOVA analysis for
boys and men were conducted if there was an interaction for AGE*GL, AGE*EX or
AGE*GL*EX.
A 4-factor ANOVA was used to determine the effect of GL, EX, TIME and AGE on
average BG and VAS scores for pre-meal subjective feelings of appetite, thirst and physical
comfort. The pre-meal results for the 15 – 50 min times are expressed as change from baseline,
and represent the time between completion of either the SED or EX condition and the the test meal.
Pearson correlation coefficients were calculated to identify associations between FI, NEB
and RER, HR, CHOOX, FATOX and EE.
42
8. RESULTS
8.1. Descriptive Measures
The study was completed with 30 participants, with 36 being initially recruited. Pooled
values for subject characteristics of the 15 boys and 15 men are shown in Table 8-1. These
characteristics are shown for each of the 30 participants in Table 8-2 for boys and Table 8-3 for
men. The average age of boys and men was 10.9 ± 0.3 and 23.5 ± 0.8 years respectively. Baseline
BMI and BMI percentile classified both age groups as normal weight, according to the CDC BMI
and BMI for age guidelines (Appendix 1A + 1B).
VO2peak was similar in both groups (43.5 ± 2.0 ml·kg-1·min-1 in boys vs. 43.5 ± 1.2 ml·kg-
1·min-1 in adults). However, VO2peaks indicated higher absolute fitness levels in adults when
compared to children relative to their age specific norms [156, 157]. The VETs at 29.2 ± 1.6 ml·kg-
1·min-1 in boys and 25.7 ± 0.9 ml·kg-1·min-1 in men were not significantly different. The VET as a
relative percentage of the VO2peak in children (67.6 ± 1.9 %) may indicate that they had a better
ability to rely on fats during EX when compared to adults (59.2 ± 2.0 %), but adults had less body
fat (13.5 ± 0.9 %) when compared with children (17.6 ± 1.0 %). HRmax and %HRest were not
significantly different between boys and men
43
Table 8-1 1Mean subject characteristics of boys and men
Subject Characteristics Children Adults P-value
Age (years)1 10.9 ± 0.3 23.5 ± 0.8 <0.0001
Weight (kg)1 36.0 ± 1.3 70.5 ± 2.4 <0.0001
Height (cm) 1 144.9 ± 2.5 174.3 ± 1.5 <0.0001
BMI2 (kg/m2) 17.1 ± 0.4 23.1 ± 0.6 <0.0001
BMI2 percentile 50.2 ± 5.6
SKF body fat3 (%)1 17.6 ± 1.0 13.5 ± 0.9 .0052
VET4 (ml·kg-1·min-1) 1 29.2 ± 1.6 25.7 ± 0.9 n.s.
%VET of VO2peak 67.6 ± 1.9 58.2 ± 2.0 0.0056
VO2peak5 (ml·kg-1·min-1) 43.5 ± 2.0 43.5 ± 1.2 n.s.
HRmax6 (bpm) 183 ± 3.5 181 ± 3.2 n.s.
%HRest7 93 ± 1.8 96 ± 1.7 n.s.
1 Means ± SEM; n=30. A student’s t-test was used to determine differences between boys and men.
2BMI = Body mass index
3VET = Ventilation threshold (ml·min-1·kg-1)
4VET = percentage VET of Vo2peak
5VO2peak = maximum oxygen consumption (ml·min-1·kg-1)
6HRmax = maximum heart rate (bpm)
7%HRest = percentage of estimated HRmax
44
Table 8-2 Baseline characteristics for 15 boys1
1 Means ± SEM; n=15
2BMI = Body mass index
3VET = Ventilation threshold (ml·min-1·kg-1)
4VET = percentage VET of Vo2peak
5VO2peak = maximum oxygen consumption (ml·min-1·kg-1)
6HRmax = maximum heart rate (bpm)
7%HRest = percentage of estimated HRmax
8SKF BF = Percent body fat by SKF analysis (%)
ID
Age
(year
s)
Weigh
t (kg)
Heigh
t (cm)
BMI2
(kg/m2
)
BMI2
percentil
e
VET3
(ml·mi
n-1·kg-1)
VET4 %
of
VO2pea
k
VO2peak5
(ml·min-
1·kg-1)
HR
max6
(bpm
)
HRes
t
(%)7
SKF
body
fat(%)8
Tanne
r
Stage
1 11.5 35.3 147.0 16.5 30.5 26.2 59.1 44.2 167.0 84 15.9 1
2 11.6 38.6 150.5 17.0 44.4 40.1 72.0 56.4 198.0 99 13.7 2
3 10.9 35.4 144.0 17.1 65.2 32.6 68.1 47.9 191.0 95 17.9 1
4 10.0 31.1 135.0 17.1 61.8 39.9 75.3 53.0 191.0 95 15.0 1
5 10.8 37.5 144.0 18.1 62.9 24.0 60.7 39.6 202.0 101 13.6 1
6 11.7 38.9 163.0 14.6 14.5 28.6 78.7 36.8 199.0 100 11.8 2
7 12.3 39.6 155.0 16.5 25.8 25.9 72.5 35.8 168.0 84 23.8 2
8 11.8 40.5 152.0 17.5 44.8 36.6 72.5 50.5 196.0 98 18.5 2
9 11.7 39.0 147.0 18.0 64.1 33.3 63.6 52.3 201.0 101 15.9 1
10 10.8 38.5 150.0 17.1 51.2 29.4 59.8 49.4 180.0 90 17.0 1
11 9.7 32.3 133.0 18.3 78.8 27.8 66.4 41.8 180.0 89 22.6 1
12 11.5 32.3 140.0 16.5 54.4 27.8 65.0 42.8 170.0 85 16.3 1
13 10.4 36.3 145.0 17.3 59.1 22.2 62.3 35.6 186.0 93 21.0 1
14 8.4 21.7 123.0 14.1 12.1 23.4 79.8 29.6 166.0 82 15.8 1
15 12.0 43.5 145.5 20.7 83.9 20.8 57.6 36.1 200.0 100 25.8 2
Mean 11.0 36.0 144.9 17.1 50.2 29.2 67.6 43.5 186.3 93 17.6 1.3
SEM 0.3 1.3 2.5 0.4 5.6 1.6 1.9 2.0 3.5 1.8 1.0 0.1
45
Table 8-3 Baseline characteristics for 15 men1
1 Means ± SEM; n=15
2BMI = Body mass index
3VET = Ventilation threshold (ml·min-1·kg-1)
4VET = percentage VET of Vo2peak
5VO2peak = maximum oxygen consumption (ml·min-1·kg-1)
6HRmax = maximum heart rate (bpm)
7%HRest = percentage of estimated HRmax
8SKF BF = Percent body fat by SKF analysis (%)
ID
Age
(year
s)
Weig
ht
(kg)
Heigh
t (cm)
BMI2
(kg/m2
)
VET3
(ml·min-
1·kg-1)
VET4 % of
VO2peak
VO2peak5
(ml·min-
1·kg-1)
HR
max6
(bpm)
HRe
st
(%)7
SKF
BF
(%)8
1 27 88.0 180.2 27.1 20.7 42.7 48.5 182 98 11.8
2 26 77.3 181.0 23.6 24.8 60.2 42.2 160 85 9.0
3 20 70.2 177.2 22.3 26.2 61.5 42.6 187 99 23.0
4 22 61.0 176.4 19.6 24.9 60.9 40.8 196 102 12.8
5 24 85.0 176.5 27.3 30.5 60.5 50.4 193 104 17.4
6 27 64.2 168.5 22.6 27.3 63.1 43.2 165 87 12.3
7 28 72.5 172.5 24.4 26.4 50.5 52.3 182 97 11.6
8 23 60.6 162.0 23.1 28.5 57.3 49.8 183 97 13.0
9 20 58.8 172.0 19.9 25.3 63.0 40.2 177 92 13.3
10 19 82.3 183.0 24.6 25.6 67.2 38.1 163 87 17.6
11 23 66.3 172.0 22.4 19.5 49.2 39.6 193 102 11.4
12 24 74.2 176.0 24.0 32.5 72.6 44.8 181 96 12.6
13 20 59.6 165.5 21.8 27.0 65.5 41.2 198 104 12.3
14 22 71.5 177.5 22.7 19.3 50.9 38.0 193 102 13.8
15 28 65.5 175.0 21.4 26.4 63.7 41.5 172 90 10.4
M
ea
n
23.5 70.5 174.4 23.1 25.7 58.2 43.5 181.7 96 13.5
SE
M 0.8 2.4 1.5 0.6 0.9 2.0 1.2 3.2 1.7 0.9
46
8.2. Food Intake
Compared to CON, FI (kcal/kg) was lower after GL (p < 0.0001), but not affected by EX.
FI (kcal/kg) was higher in boys when compared to men (AGE, p = 0.0001). A significant
interaction was found for GL*EX (p = 0.0254), showing an additional suppression of FI (kcal/kg)
by GL combined with EX. No other significant interactions were found (Table 8-4).
Table 8-4 1Food intake (kcal/kg) in boys and men
Activity: Sedentary Exercise Pooled
Drink: Control Glucose Control Glucose
Boys 24.4 ± 1.6 22.5 ± 1.6 25.0 ± 1.7 19.9 ± 1.6 22.9 ± 0.8
Men 16.7 ± 1.1 14.5 ± 1.4 17.1 ± 1.3 13.6 ± 1.3 15.5 ± 0.7
Pooled 20.6 ± 1.3 18.5 ± 1.2 21.0 ± 1.3 16.7 ± 1.2
1Mean ± SEM (kcal/kg); pooled n=30. ANOVA analysis (GL, p < 0.0001; EX, p = 0.2250;
GL*EX, p = 0.0254; AGE, p = 0.0001; AGE*EX, p = 0.4655; AGE*GL, p = 0.5329;
AGE*EX*GL, p = 0.3557).
47
8.3. Energy Expenditure
Compared to CON, EE (kcal/kg) was increased by GL (p = 0.0098) and EX (p < 0.0001).
EE (kcal/kg) was higher in boys when compared to men (AGE, p = 0.0008). AGE*EX did show
a trend without reaching statistical significance (p = 0.087). No other significant interactions were
found (Table 8-5).
Table 8-5 1Energy expenditure (kcal/kg) in boys and men
Activity: Sedentary Exercise Pooled
Drink: Water Glucose Water Glucose
Boys 1.21 ± 0.08 1.39 ± 0.07 4.12 ± 0.17 4.20 ± 0.17 2.73 ± 0.20
Men 0.85 ± 0.04 0.87 ± 0.03 3.55 ± 0.22 3.72 ± 0.21 2.25 ± 0.20
Pooled 1.03 ± 0.05 1.13 ± 0.06 3.83 ± 0.14 3.96 ± 0.14
1Mean ± SEM (kcal/kg); pooled n=30. ANOVA analysis (GL, p = 0.0098; EX, p < 0.0001;
GL*EX, p = 0.7951; AGE, p = 0.0008; AGE*EX, p = 0.7415; AGE*GL, p = 0.6669;
AGE*EX*GL, p = 0.2597).
48
8.4. Net Energy Balance
Compared to CON, NEB (kcal/kg) was increased by GL (p = 0.0307) and decreased by
EX (p < 0.0001). NEB (kcal/kg) was higher in boys when compared to men (AGE, p = 0.0002).
GL*EX showed a trend, but no significant interaction was found (p = 0.0734). No other significant
interactions were found (Table 8-6).
Table 8-6 1Net energy balance (kcal/kg) in boys and men
1Mean ± SEM (kcal/kg); pooled n=30. ANOVA analysis (GL, p = 0.0307; EX, p < 0.0001;
GL*EX, p = 0.0734; AGE, p = 0.0002; AGE*EX, p = 0.2547; AGE*GL, p = 0.6176;
AGE*EX*GL, p = 0.2319).
Activity: Sedentary Exercise Pooled
Drink: Water Glucose Water Glucose
Boys 23.6 ± 1.6 26.0 ± 1.6 20.8 ± 1.7 20.6 ± 1.7 22.7 ± 0.8
Men 15.8 ± 1.1 17.8 ± 1.4 13.3 ± 1.3 14.7 ± 1.5 15.4 ± 0.7
Pooled 19.7 ± 1.2 21.9 ± 1.3 17.1 ± 1.3 17.6 ± 1.2
49
8.5. Substrate Oxidation
Compared to CON, RER was increased by GL (p < 0.0001) and by EX (p = 0.0043). RER
was lower in boys compared to men (AGE, p = 0.0002). AGE*EX showed a trend towards
statistical significance (p = 0.087). No significant interactions were found (Table 8-7).
Table 8-7 1Respiratory exchange ratio in boys and men
Activity: Sedentary Exercise Pooled
Drink: Water Glucose Water Glucose
Boys 0.85 ± 0.01 0.89 ± 0.02 0.86 ± 0.01 0.90 ± 0.02 0.88 ± 0.01
Men 0.87 ± 0.01 0.92 ± 0.04 0.91 ± 0.03 0.95 ± 0.04 0.91 ± 0.01
Pooled 0.86 ± 0.01 0.90 ± 0.01 0.89 ± 0.01 0.93 ± 0.01
1Mean ± SEM; pooled n=30. ANOVA analysis (GL, p < 0.0001; EX, p = 0.0043; GL*EX, p =
0.6951; AGE, p = 0.007; AGE*EX, p = 0.087; AGE*GL, p = 0.8738; AGE*EX*GL, p = 0.3348).
50
8.6. Carbohydrate Oxidation
Compared to CON, CHOOX (kcal/kg) was increased by GL (p < 0.0001) and EX (p <
0.0001). A significant interaction was found for GL*EX (p = 0.0031), showing an additional
increase in CHOOX (kcal/kg) with GL and EX. AGE*EX did show a trend to be statistically
significant (p = 0.0561). No other significant interactions were found (Table 8-8).
Table 8-8 1 Carbohydrate oxidation (kcal/kg) in boys and men
Activity: Sedentary Exercise Pooled
Drink: Water Glucose Water Glucose
Boys 0.61 ± 0.06 0.88 ± 0.10 2.15 ± 0.18 2.83 ± 0.22 1.62 ± 0.14
Men 0.48 ± 0.04 0.62 ± 0.04 2.51 ± 0.18 3.06 ± 0.22 1.67 ± 0.17
Pooled 0.54 ±0.04 0.75 ± 0.06 2.34 ± 0.13 2.95 ± 0.15
1Mean ± SEM (kcal/kg) pooled n=30. ANOVA analysis (GL, p < 0.0001; EX, p < 0.0001;
GL*EX, p = 0.0031; AGE, p = 0.724; AGE*EX, p = 0.0561; AGE*GL, p = 0.3479;
AGE*EX*GL, p = 0.9880).
51
8.7. Fat Oxidation
Compared to CON, FATOX (kcal/kg) was decreased by GL (p < 0.0001) and increased with
EX (p < 0.0001). FATOX (kcal/kg) was higher in boys when compared to men (AGE p < 0.0001).
A significant interaction was found for GL*EX (p = 0.0031), showing increased FATOX (kcal/kg)
with GL and EX when compared with CON. Moreover, AGE*EX interaction reached statistical
significance (p = 0.0104). No other significant interactions were found (Table 8-9). AGE-specific
analysis found GL (p < 0.0001) to decrease and EX (p < 0.0001) to increase FATOX (kcal/kg) in
boys. A significant interaction was also found for GL*EX (p = 0.004) in boys, revealing increased
FATOX (kcal/kg) with GL and EX. In men, GL (p < 0.0001) decreased and EX (p < 0.0001)
increased FATOX (kcal/kg). GL*EX did not interact significantly in men.
Table 8-9 1Fat oxidation (kcal/kg) in boys and men
Activity: Sedentary Exercise Pooled
Drink: Water Glucose Water Glucose
Boys2 0.60 ± 0.08 0.51 ± 0.09 1.96 ± 0.22 1.36 ± 0.22 1.11 ± 0.11
Men3 0.37 ± 0.03 0.25 ± 0.03 1.03 ± 0.10 0.65 ± 0.14 0.58 ± 0.06
Pooled 0.49 ± 0.05 0.38 ± 0.05 1.50 ± 0.15 1.01 ± 0.14
1 Mean± SEM (kcal/kg); pooled n=30. ANOVA analysis (GL, p < 0.0001; EX, p < 0.0001;
GL*EX, p = 0.0021; AGE, p < 0.0001; AGE*EX, p = 0.0104; AGE*GL, p = 0.4829;
AGE*EX*GL, p = 0.2738).
2 Mean± SEM (kcal/kg); n=15. ANOVA analysis for boys (GL, p = 0.0009; EX, p < 0.0001;
EX*GL, p = 0.004).
3 Mean ± SEM (kcal/kg); n=15. ANOVA analysis for men (GL, p = 0.0103; EX, p < 0.0001;
EX*GL, p = 0.1515).
52
8.8. Heart Rate
Compared to CON, HR (bpm) was increased by GL (p < 0.0001) and EX (p < 0.0001).
Boys had higher HR than men AGE (p < 0.0001). No other significant interactions were found
(Table 8-10).
Table 8-10 1Heart rate (bpm) in boys and men
Activity: Sedentary Exercise Pooled
Drink: Water Glucose Water Glucose
Boys 81 ± 2 80 ± 2 123 ± 3 132 ± 2 104 ± 3
Men 62 ± 2 67 ± 3 110 ± 5 115 ± 4 89 ± 4
Pooled 71 ± 2 74 ± 3 116 ± 3 123 ± 3
1Means ± SEM (bpm); n=30. ANOVA analysis (GL, p = 0.0014; EX, p < 0.0001; GL*EX, p =
0.1118; AGE, p < 0.0001; AGE*EX, p = 0.8703; AGE*GL, p = 0.7612; AGE*EX*GL, p =
0.0839).
53
8.9. Water Consumption
Water consumption (ml/kg) was similar in boys and men. Neither EX nor GL affected water
consumption in boys and men. No interactions were found (Table 8-11).
Table 8-11 1Water consumption (kg/ml) in boys and men
Activity: Sedentary Exercise Pooled
Drink: Water Glucose Water Glucose
Boys 5.7 ± 4.7 5.5 ± 4.3 5.3 ± 6.3 6.8 ± 7.0 5.8 ± 5.8
Men 3.3 ± 3.9 4.3 ± 5.7 4.7 ± 4.8 5.1 ± 6.2 4.4 ± 5.2
Pooled 4.5 ± 4.1 4.9 ± 4.9 5.0 ± 5.5 6.0 ± 6.2
1Means ± SEM (ml/kg); n=30. ANOVA analysis (GL, p = 0.1414; EX, p = 0.1461; GL*EX, p =
0.6274; AGE, p = 0.2049; AGE*EX, p = 0.5014; AGE*GL, p = 0.9991; AGE*EX*GL, p =
0.3185).
54
8.10. Net Area Under the Curve Blood Glucose Measurements
Compared to CON, BG nAUC was increased by GL (p < 0.0001) and decreased by EX (p
< 0.0011). BG measured by nAUC BG was not different between boys and men. A significant
interaction was found for GL*EX (p < 0.0001), showing lower BG AUC responses when GL was
combined with EX. No other significant interactions were found (table 8-12).
Table 8-12 1 nAUC blood glucose levels (min*mmol/l) in boys and men
Activity: Sedentary Exercise Pooled
Drink: Control Glucose Control Glucose
Boys -15 ± 5 159 ± 23 15 ± 6 87 ±17 61.8 ± 15.7
Men -4 ± 3 182 ± 18 -9 ± 6 93 ± 16 65.7 ± 16.6
Pooled -7 ± 3 175 ± 14 -2 ± 5 90 ± 12
1Means ± SEM (min*mmol/l); n = 6 boys and n = 15 men. ANOVA analysis (EX p = 0.0011; GL
p < 0.0001; GL*EX p < 0.0001; AGE p = 0.7702; AGE*EX p = 0.1960; AGE*GL p = 0.2808;
AGE*EX*GL, p = 0.6603).
55
8.11. Blood Glucose Measurements
Compared to CON, average BG levels were higher after the GL (p < 0.0001), lower after
EX compared to SED (p < 0.0001), increased over TIME (p < 0.001) and were not affected by
AGE. AGE*GL interaction showed a trend for statistical significance (p = 0.0863), with higher
BG levels reported in adults. Significant interactions were found for EX*TIME (p < 0.0001) and
GL*TIME (p = 0.0034), reflecting higher BG with GL and lower BG with EX over time, when
compared with the CON sessions. EX*GL*TIME interaction showed a reduction of BG over
TIME with GL with EX when compared to GL alone (p < 0.0001). No other significant
interactions were found (table 8-13).
Table 8-131 Average Blood Glucose Concentrations (mmol/l) for boys and men
Time
Activity: Sedentary Exercise
Drink: Control Glucose Control Glucose
Boys
02
5.2 ± 0.07 4.9 ± 0.1 4.9 ± 0.13 5.07 ± 0.14
Men 4.95 ± 0.08 4.95 ± 0.09 4.96 ± 0.11 4.82 ± 0.14
Boys
153
5.02 ± 0.06 7.3 ± 0.37 5.07 ± 0.1 7.1 ± 0.42
Men 4.87 ± 0.07 7.37 ± 0.36 4.73 ± 0.13 6.78 ± 0.3
Boys
35
4.88 ± 0.07 8.92 ± 0.45 5.23 ± 0.11 6.7 ± 0.53
Men 4.9 ± 0.08 9.41 ± 0.49 4.81 ± 0.87 6.67 ± 0.36
Boys
604
4.87 ± 0.04 7.0 ± 0.8 5.28 ± 0.11 6.37 ± 0.21
Men 4.84 ± 0.08 8.08 ± 0.58 4.85 ± 0.11 6.21 ± 0.28
56
1Mean SEM (mmol/l) n = 6 boys and n = 15 men. ANOVA analysis change from baseline (0
min) average BG measurements. EX conducted between 15 and 60 minutes and GL administered
at 0 min; (GL p < 0.0001; EX p < 0.0001; TIME p < 0.0001; AGE p = 0.8018; EX*GL p <
0.0001; EX*AGE p = 0.1765; GL*AGE p < 0.0863; EX*TIME p < 0.0001; GL*TIME p =
0.0034; AGE*TIME p = 0.8073; EX*GL*AGE p = 0.3593; EX*GL*TIME p < 0.0001;
EX*AGE*TIME p = 0.6979; GL*AGE*TIME p = 0.6386; EX*GL*AGE*TIME p = 0.9250)
2 Preload provided
3 Start of Exercise
4 End of Exercise
57
8.12. Visual Analog Scale Analysis
8.12.1. Subjective Appetite
Pre-meal ratings of appetite were affected by the GL (p = 0.0446), and (AGE, p = 0.0301),
and increased over TIME (p < 0.0001). EX had no effect on subjective appetite. The interaction
of TIME*AGE (p < 0.0001), is explained by the suppression of appetite by GL in men but not in
boys. No other interactions were found. Post-meal minus pre-meal ratings were less in men (AGE,
p = 0.0283) indicating less suppression of appetite following the meal than in boys, but were not
affected by either GL or EX. No other significant interactions were found (Table 8-14).
Table 8-14 1Average appetite (mm) in boys and men
Time
Activity Sedentary Exercise
Drink: Control Glucose Control Glucose
Pre-meal appetite scores
Boys2
04
0 ± 0 0 ± 0 0 ± 0 0 ± 0
Men3 0 ± 0 0 ± 0 0 ± 0 0 ± 0
Boys2
5
-1.3 ± 2.1 0.9 ± 4.0 3.2 ± 3.3 -3.8 ± 5.4
Men3 -4.6 ± 2.4 -6.9 ± 2.5 -6.1 ± 2.8 -14.1 ± 3.0
Boys2
155
1.2 ± 2.1 4.2 ± 3.1 -0.6 ± 3.2 7.1 ± 0.4
Men3 -3.7 ± 2.8 -4.4 ± 2.6 -3.4 ± 2.4 -6.8 ± 2.2
Boys2 35 6.6± 3.2 9.0 ± 3.3 4.3 ± 3.8 6.3 ± 5.8
58
Men3 -1.3 ± 2.5 -3.07 ± 1.8 1.3 ± 3.7 -5.4 ± 3.9
Boys2
606
12.4 ± 2.9 11.9 ± 4.0 12.3 ± 3.6 4.2 ± 6.2
Men3 1.9 ± 3.1 -3.4 ± 2.4 0.9 ± 3.5 -4.3 ± 4.3
Boys
852,7/953,7
-63.8 ± 6.9 -65.8 ± 5.9 -67.7 ± 6.8 -51.6 ± 7.6
Men -54.8 ± 4.7 -54.3 ± 6.5 -53.1 ± 5.3 -56.1 ± 6.0
Post meal minus pre-meal scores
Boys2
-76.1 ± 9.0 -77.6 ± 8.3 -79.9 ± 9.5 -55.8 ± 12.4
Men3 -56.7 ± 5.3 -50.9 ± 5.5 -60.25 ± 7.44 -49.4 ± 6.4
1Mean SEM (mm) n = 15 boys and n = 15 men. Pre-meal (0-60 minutes) ANOVA analysis
change from baseline (0 min) average appetite measurements. EX conducted between 15 and 60
minutes and GL administered at 0 min; (GL p = 0.0446; EX p = 0.1094; TIME p < 0.0001; AGE
p = 0.0008; EX*GL p = 0.1097; EX*TIME p =0.7734; GL*TIME p = 0.4102; AGE*TIME p =
0.0013; EX*GL*AGE p = 0.8907; EX*GL*TIME p = 0.9008; EX*AGE*TIME p = 0.8852;
GL*AGE*TIME p = 0.7787; EX*GL*AGE*TIME p = 0.8736)
Post-meal minus pre-meal ANOVA analysis 852/953 – 60 minutes (GL p = 0.0712; EX p = 0.2218;
AGE p = 0.0283; EX*GL p = 0.1773; EX*AGE p = 0.4524; GL*AGE p = 0.5002; EX*GL*AGE
p = 0.1385)
4 Preload provided at 0 minutes
5 Start of Exercise at 15 minutes
6 End of Exercise at 60 minutes
7Termination of Meal
59
8.12.2. Thirst
Pre-meal ratings of thirst were not affect by GL, EX, AGE or TIME. Post-meal minus
pre-meal scores were also not affected by GL, EX, AGE or Time. No interactions were found
(Table 8-15).
Table 8-15 1Average thirst (mm) in boys and men
Time
Activity Sedentary Exercise
Drink: Control Glucose Control Glucose
Pre-meal appetite scores
Boys2
04
0 ± 0 0 ± 0 0 ± 0 0 ± 0
Men3 0 ± 0 0 ± 0 0 ± 0 0 ± 0
Boys2
5
-34.7 ± 6.1 -28.6 ± 6.5 -32.6 ± 5.9 -31.6 ± 7.0
Men3 0.1 ± 1.9 -1.4 ± 2.0 2.2 ± 2.5 3.0 ± 2.1
Boys2
155
-23.4 ± 6.6 -17.9 ± 6.1 -23.2 ± 8.1 -20.0 ± 6.9
Men3 -1.8 ± 2.5 -0.4 ± 1.9 0.9 ± 1.4 1.2 ± 1.6
Boys2
35
-11.7 ± 5.7 -6.7 ± 6.8 -1.4 ± 8.0 -4.0 ± 8.3
Men3 0.3 ± 1.9 -4.8 ± 2.4 -1.4 ± 1.9 5.1 ± 3.3
Boys2
606
-3.9 ± 6.9 -2.1 ± 8.4 11.7 ± 8.4 -2.1 ± 8.4
Men3 -6.3 ± 3.2 -3.8 ± 1.8 -0.4 ± 2.5 0.5 ± 3.6
Boys 852,7/953,7 -6.5 ± 7.5 0.9 ± 9.0 10.6 ± 10.3 -5.7 ± 7.2
60
Men -7.4 ± 8.6 -11.2 ± 5.9 0.7 ± 11.4 -1.1 ± 9.6
Post meal minus pre-meal scores
Boys2
-2.6 ± 7.2 3 ± 8.7 1.2 ± 9.4 -3.6 ± 7.8
Men3 -0.2 ± 5.9 -7.4 ± 3.9 1.1 ± 7.0 -1.6 ± 6.6
1Mean SEM (mm) n = 15 boys and n = 15 men. Pre-meal (0-60 minutes) ANOVA analysis
change from baseline (0 min) thirst measurements. EX conducted between 15 and 60 minutes and
GL administered at 0 min; (GL p = 0.6868; EX p = 0.9152; TIME p = 0.9980; AGE p = 0.9936;
EX*GL p = 0.8572; EX*TIME p = 0.7236; GL*TIME p = 0.9896; AGE*TIME p = 0.3918;
EX*GL*AGE p = 0.8907; EX*GL*TIME p = 0.9977; EX*AGE*TIME p = 0.9028;
GL*AGE*TIME p = 0.8482; EX*GL*AGE*TIME p = 0.5434)
Post-meal minus pre-meal ANOVA analysis 852/953 – 60 minutes (GL p = 0.3655; EX p = 0.4027;
AGE p = 0.3822; EX*GL p = 0.9520; EX*AGE p = 0.6154; GL*AGE p = 0.8030; EX*GL*AGE
p = 0.3296)
4 Preload provided at 0 minutes
5 Start of Exercise at 15 minutes
6 End of Exercise at 60 minutes
7Termination of Meal
61
8.12.3. Physical Comfort in Boys
Pre-meal ratings in boys were decreased over TIME (p = 0.0323). GL and EX did not
affect physical comfort in boys. No interactions were found. Physical comfort post-meal minus
pre-meal ratings were not affected by neither GL nor EX. No further interactions were found
(Table 8-16).
Table 8-16 1 Average physical comfort (mm) in boys
Activity: Sedentary Exercise
Drink: Control Glucose Control Glucose
Time (min)
Pre-meal scores
02 0 0 0 0
53 -2.7 ± 4.0 -2.3 ± 1.0 2.2 ± 1.3 2.5 ± 3.2
15 -5.6 ± 4.9 -0.8 ± 4.1 -0.6 ± 2.6 -6.7 ± 3.2
35 -10.3 ± 4.9 -1.5 ± 2.0 -5.2 ± 5.1 -6.8 ± 2.4
604 -2.0 ± 4.9 -4.1 ± 5.0 -4.9 ± 3.6 -5.3 ± 4.9
855 -8.3 ± 7.4 -9.0 ± 7.5 -9.6 ± 11.5 -17.7 ± 9.8
Post-meal minus pre-meal scores5
60-85 -6.3 ± 3.1 -5.0 ± 5.0 -4.7 ± 6.4 -12.4 ± 5.6
1Mean SEM (mm) n = 15 boys. Pre-meal ANOVA analysis change from baseline (0 min) average
physical comfort measurements. EX conducted between 15 and 60 minutes and GL administered
62
at 0 min; (GL p = 0.7783; EX p = 0.7560; TIME p = 0.0323; EX*GL p = 0.1680; EX*TIME p
=0.6147; GL*TIME p = 0.8313; EX*GL*TIME p = 0.5552).
Post-meal minus pre-meal ANOVA analysis 852/953 – 60 minutes (GL p = 0.5260; EX p = 0.5768;
EX*GL p = 0.6419)
2 Preload provided
3 Preload terminated
4Test meal provided
5Test meal terminated
63
8.12.4. Physical Comfort in Men
Pre-meal ratings in men were decreased due to the GL (p = 0.0027). EX did not affect
physical comfort in men. No interactions were found. Physical comfort post-meal minus pre-meal
ratings were not affected by neither GL nor EX. No further interactions were found (Table 8-17).
Table 8-17 1Average physical comfort (mm) in men.
Activity: Sedentary Exercise
Drink: Control Glucose Control Glucose
Time (min)
Pre-meal scores
02 0 0 0 0
53 0.9 ± 0.8 -3.7 ± 1.0 -0.9 ± 1.3 -1.7 ± 1.6
15 0.4 ± 0.8 -4.3 ± 2.5 -0.5 ± 1.2 -1.7 ± 1.7
35 0.6 ± 0.6 -2.4 ± 2.8 -0.3 ± 1.5 -3.0 ± 1.5
604 6.3 ± 3.5 -1.2 ± 4.1 -0.1 ± 1.7 -1.0 ± 3.3
855 -0.3 ± 0.7 -2.4 ± 3.5 -1.6 ± 1.9 -3.9 ± 1.6
Post-meal minus pre-meal5
60-85 -6.6 ± 3.2 -1.2 ± 2.3 -1.5 ± 1.4 -2.9 ± 3.4
1Mean SEM (mm) n = 15 men. Pre-meal ANOVA analysis change from baseline (0 min) average
physical comfort measurements. EX conducted between 15 and 60 minutes and GL administered
64
at 0 min; (GL p = 0.0027; EX p = 0.4967; TIME p = 0.2520; EX*GL p = 0.0935; EX*TIME p
=0.6411; GL*TIME p = 0.6035; EX*GL*TIME p = 0.7142).
Post-meal minus pre-meal ANOVA analysis 852/953 – 60 minutes (GL p = 0.1793; EX p = 0.6821;
EX*GL p = 0.8350)
2 Preload provided
3 Preload terminated
4Test meal provided
5Test meal terminated
65
8.12.5. Preload Palatability in Boys
Boys found the GL drink significantly more pleasing compared with water (p = 0.0003)
(Table 8-18).
Table 8-181Average preload palatability (mm) in boys
Activity: Control Glucose p-value
(DRINK)
26.9 ± 6.0 57.2 ± 5.2 0.0003
1Mean± SEM (mm); n=30. A student’s t-test was used to determine the difference in drink
palatability (5 min). GL (p = 0.0003)
66
8.12.6. Preload Palatability in Men
Men found the GL drink more palatable than water (p = 0.0237) (Table 8-19).
Table 8-19 1Average preload palatability (mm) in men
Activity: Control Glucose p-value
(DRINK)
56.3 ± 3.9 68.9 ± 3.7 0.0237
1 Mean ± SEM (mm); n=30. A student’s t-test was used to determine the difference in drink
palatability (5 min). GL (p = 0.0237)
67
8.12.7. Pizza Meal Palatability in Boys
Neither EX nor GL had an effect on pizza palatability in boys. No interactions were found
(Table 8-20).
Table 8-20 1Average pizza palatability (mm) in boys
Activity:
Drink: Water Glucose Pooled
Sedentary 73 ± 9 81 ± 7 77 ± 5
Exercise 89 ± 3 82 ± 5 86 ± 3
Pooled 81 ± 5 81 ± 4
1Means ± SEM (mm); n = 15 boys. ANOVA analysis (85 min) (EX p = 0.9291; GL p = 0.1735;
GL*EX p = 0.1577).
68
8.12.8. Pizza Meal Palatability in Men
Neither EX nor GL had an effect on pizza palatability in men. No interactions were found
(Table 8-21).
Table 8-21 1Average pizza palatability (mm) in men
Activity:
Drink: Water Glucose Pooled
Sedentary 64.2 ± 5.3 66.1 ± 5.1 65.1 ± 3.6
Exercise 65.1 ± 4.7 64.2 ± 5.5 64.7 ± 3.6
Pooled 64.6 ± 3.5 65.2 ± 3.7
1Mean ± SEM (mm); n = 15 men. ANOVA analysis (95 min) (EX p = 0.9003; GL p = 0.8861;
GL*EX p = 0.7027).
69
8.13. Correlation Analysis
Correlation analysis were conducted to investigate the relationship between FI, NEB and
RER, EE, HR. FATOX, CHOOX and BG levels. All measurements, except for HR, RER and BG
levels were adjusted for body-weight.
8.13.1. Correlations with Food Intake
Subjective appetite, expressed was correlated with FI (kcal/kg) in boys but not men (r =
0.297; p = 0.0213). No significant correlations were found for EE, Net AUC BG, HR, CHOOX and
FATOX (Table 8-22).
Table 8-221Associations with food intake (kcal/kg)
Boys Men
r p r p
EE (kcal/kg)1 -0.069 0.5991 -0.061 0.6428
RER1 -0.049 0.7447 -0.041 0.7545
HR (bpm)1 -0.156 0.2335 0.065 0.6241
Net AUC BG (min*mmol/l)2 -0.246 0.2588 -0.191 0.1437
CHOox (kcal/kg)1 -0.072 0.5859 -0.056 0.6726
FATox (kcal/kg)1 -0.031 0.8112 -0.048 0.7116
Water consumption (ml/kg)1 0.132 0.3116 0.116 0.3787
70
nAUC Appetite (mm*min)1 0.297 0.0213 -0.077 0.5613
nAUC Physical Comfort (mm*min)1 0.148 0.2619 -0.139 0.2888
nAUC Thrist (mm*min)1 0.098 0.4542 -0.145 0.2698
Food Palatability at 85/95 min (mm)1 -0.032 0.8029 0.068 0.6072
Preload Palatability at 5 min (mm)1 -0.127 0.3333 0.233 0.0731
Preload Sweetness at 5 min(mm)1 -0.077 0.5604 Not assessed
1Pearson correlation coefficients; n = 15 boys and 15 men
2 Pearson correlation coefficients; n = 6 boys and 15 men
71
8.13.2. Associations with Net Energy Balance
A correlation was found for NEB and EE in boys (r = -0.299; p = 0.0201) and men (r = -
0.304; p = 0.018). Subjective appetite was also correlated with NEB in boys (r = 0.277; p =
0.0322) but not men. FATOX was correlated with NEB in both boys (r = -0.278; p = 0.0314) and
men (r = -0.379; p = 0.0028). No correlations were found for FI and EE, HR, BG levels, FATOX
and CHOOX (Table 8-23).
Table 8-23 Associations with net energy balance (kcal/kg)
Boys Men
r p r p
EE (kcal/kg)1 -0.299 0.0201 -0.304 0.0180
RER1 0.063 0.635 0.074 0.5697
HR (bpm)1 -0.34 0.0082 -0.153 0.2487
CHOox (kcal/kg)1 -0.195 0.1363 -0.228 0.0794
FATox (kcal/kg)1 -0.278 0.0314 -0.379 0.0028
nAUC BG (min*mmol/l)2 0.089 0.6785 0.252 0.0528
Water consumption (ml/kg)1 0.118 0.3701 0.093 0.4795
nAUC Appetite (mm*min)1 0.277 0.0322 -0.171 0.1918
nAUC Physical Comfort (mm*min)1 0.127 0.3377 -0.119 0.364
nAUC Thrist (mm*min)1 0.126 0.3467 -0.124 0.3436
Food Palatability at 85/95 min (mm)1 0.053 0.6856 0.096 0.4667
72
Preload Palatability at 5 min (mm)1 0.033 0.8017 -0.009 0.9421
Preload Sweetness at 5 min(mm)1 -0.039 0.7676 Not assessed
1Pearson correlation coefficients; n = 15 boys and 15 men
2 Pearson correlation coefficients; n = 6 boys and 15 men
73
9. DISCUSSION
The results of this study do not support our hypothesis. In contrast, several lines of evidence
show that substrate oxidation was not a factor determining FI. First, RER was higher after GL,
showing increased CHOOX and decreased FI. Second, EX increased RER as well but did not
stimulate FI. Third, GL combined with EX did not increase RER and resulted in the greatest
decrease in FI. Last, boys had a lower RER than men, but had higher FI/kg body weight.
This is the first study to assess the effects of substrate oxidation on short-term FI in boys
and men using a unique design to examine the links among metabolic flexibility and substrate
oxidation with FI. Substrate oxidation was modified with EX, GL and their combination in two
age groups because metabolic flexibility is known to decline with age [131]. This study was
stimulated by former studies, investigating the effects of obesity on FI regulation [76, 153, 158]
and metabolic flexibility [127, 158-160]. However, these studies did not report if the metabolic
impairments of obese populations, characterized by an increased proportion of CHOOX relative to
FATOX, are related to an increased FI that perpetuates a positive energy balance.
A reduction in FI with GL but no effect of EX on FI in boys and men is consistent with
previous studies of the effects of GL [74, 76, 153, 155] and EX at similar EE [73, 161-165].
However, the measures of RER allowed an examination of the relationship between substrate
oxidation and FI. GL increased RER by 12 % (Table 8-7), consistent with other studies showing
that carbohydrate ingestion increases RER by triggering the release of insulin, which stimulates
splanchnic and peripheral glucose uptake and CHOOX [166-168]. However, the interpretation of
the relationship between RER and FI may be confounded by a suppression of appetite and FI that
74
has been found after EX. This “EX-induced anorexia” describes a brief suppression of appetite
after long and/or high intensity EX [73, 169-171]. Therefore, a modest level and medium duration
of EX, standardized for an individual RER value below the VET, was chosen to increase RER
above resting values [172] without affecting FI [75, 76]. As noted in Table 8-7, EX alone increased
RER by an average of 10 % which is consistent with the literature of EX at similar intensities
[173]. RER was not further increased by combining EX with GL (Table 8-7). This can be explained
by the reduction of endogenous CHOOX while utilizing more exogenous carbohydrates derived
from plasma [166]. FI was additionally suppressed by GL in combination with EX, showing an
additional effect of EX on FI suppression when compared with GL alone, without increasing RER.
Therefore, these findings did not provide evidence for an association between RER and FI (Table
8-4, Table 8-7). In support of this, we did not find any correlations between FI and RER (Table 8-
22).
The comparison of metabolic flexibility in boys with men provides firmer support against
the hypothesis that a higher RER leads to increased FI. Men had a 13 % higher RER, indicating
higher reliance on carbohydrates across all conditions, but a lower FI/kg body weight when
compared with boys (Table 8-4, Table 8-7). EX showed a trend for RER to be further increased,
but did not stimulate additional differences in FI between men and boys (Table8-4). The decreased
RER in boys is caused mainly by their increased ability to oxidize fat (Table 8-9). Associations
between RER and FATOX showed that Boys (r = -0.584; p < 0.0001) reached higher levels of
FATOX, which were additionally increased with EX (Table 8-9), by having lower levels of RER
when compared with men (r = -0.31; p = 0.0162). Other studies have similarly shown higher rates
of FATOX in boys compared to men [131, 174].
75
Why children oxidize more fat is currently not clear. Based on limited biopsy data collected
from 6-yr-old children, pre-pubertal children may have an enhanced ability to oxidize fat due to
higher intramuscular triglyceride stores and higher overall fat stores [175]. In support to this
hypothesis, boys had a higher body fat content compared to men (Table 8-1). Higher rates of
FATOX in children might also be a consequence of underdeveloped glycogenolytic and/or
glycolytic systems [176-178]. Children have lower lactate levels during exercise [179, 180],
perhaps due to decreased capacity to utilize glucose, resulting in increased rates of FATOX. Other
studies that investigated FATOX in children and adults also found lower RQ and higher rates of
FATOX, but did not analyze FI behaviour [131, 174].
Data on FATOX as a major component of substrate oxidation, also confirms our conclusion
that RER is not linked to FI in boys and men. First, FATOX strongly correlated with RER (Figure
8.1), but did not associate with FI in the present study. Second, FATOX was decreased with GL
(Table 8-9), and this did not translate into an increase but instead a decrease in FI. GL has
previously been shown to limit lipolysis to an extent that can significantly lower overall FATOX
[181]. Last, EX expectedly increased FATOX (Table 8-9) but did not affect FI.
CHOOX, another determinant of RER, increased with both GL and EX (Table 8-8) but did,
not translate into increases in FI, as was similar to FATOX. CHOOX was positively associated with
RER in boys (r = 0.553; p < 0.0001) and men (r = 0.55; p < 0.0001) but did not associate with FI
in either boys or men. EX increased CHOOX to meet the increased EE of EX [182], and CHOOX
increased with GL in order to keep the energy stored as carbohydrates stable [78]. In contrast to
FATOX, CHOOX was not increased in boys when compared to men, reflecting the lower RER values
in boys (Table 8-7, Table 8-8, Table 8-9). Expectedly, BG circulating levels showed response
patterns parallel to those of CHOOX as they reflect readily available carbohydrate sources for
76
CHOOX [183] (Table 8-8). GL increased nAUC BG levels because it is readily absorbed [183]
(table 8-12). EX, on the other hand, reduced nAUC BG (table 8-12) by utilizing available plasma
GL in circulation to meet the increased energy demands of EX [158].
NEB regulation by substrate oxidation was another objective of the current study. NEB
was calculated in this study based on EI from the GL preload and the ad libitum pizza lunch, in
addition to the energy expended during EX and SED sessions. Unlike FI, EE is directly linked to
substrate oxidation, and it was found to be positively correlated to CHOOX in boys (r = 0.825; p <
0.0001) and men (r = 0.963; p < 0.0001) and FATOX in boys (r = 0.708; p < 0.0001) and men (r =
0.65; p < 0.0001) in the present study. GL and EX are known to modulate EE [75, 76, 131, 153,
158, 164, 168, 184-188]. In the current study, EX increased EE by an average of 360 % when
compared to the resting condition, while GL increased EE by only 4% when compared to the water
control (Table 8-5). The increased EE with GL intake has been previously described as “glucose-
induced thermogenesis”, with an average increased EE of 1-3 % with 50 g of GL [187]. The
thermic effect in the current study reached 4 % with an average GL load of 58 g. Boys had higher
EE across all conditions (Table 8-5), attributed mainly to their higher resting metabolic rates per
kg body weight when compared to men [189]. In support of the higher EE in children, we found
higher levels of HR in boys than men (table 8-10). The relationship between HR and EE has
previously been established [190, 191], and this correlation was confirmed in the current study, in
boys (r = 0.875; p < 0.0001) and men (r = 0.853; p < 0.0001). Decreased stroke volume and
increased oxygen demand generally cause HR to be higher in children [192].
This is the first study to investigate the effects of substrate oxidation on NEB. Similar to
FI, we did not find an association between NEB and RER, suggesting that NEB is also not affected
by substrate oxidation. NEB in this study was increased by 7 % with GL intake (Table 8-6), which
77
resulted in higher RER values (Table 8-7). Consistent with other studies, GL ingestion was found
to increase NEB [76]. Conversely, EX decreased NEB but increased RER (Table 8-7), showing
that RER is not related to NEB. EE was negatively correlated with NEB in boys (r = -0.299; p =
0.0201) and men (r = -0.304; p = 0.0180), which is consistent with the literature on children [193,
194] and adults [62, 195-197] (Table 8-23). This observation may not be applicable in the long
term, as other studies have shown a decrease of daily non-structured activities to compensate for
the increased EE with EX [198, 199].
Data on metabolic flexibility in our two age groups also support our conclusion that
substrate oxidation is not linked to NEB. Boys had a greater NEB across all conditions compared
to men, although they displayed lower relative RER values (Table 8-7). The greater NEB in boys
compared to men was mainly caused by their higher FI (Table 8-4, Table 8-6). It is unlikely that
pre-meal anticipation of pizza induced a greater FI/kg body weight in boys and consequently
higher NEB values, because palatability ratings in boys and men were similar despite being
assessed with different questionnaires (Table 8-20, Table 8-21). Increased palatability of food
significantly promotes FI [200-202]. The mechanisms underlying age-related differences in NEB
have never been studied and need to be further investigated.
EX alone reduced NEB but did not affect subjective appetite and FI, therefore, findings of
this study do not support the concept of EX-induced anorexia. Although the concept recently
received more attention as a potential modulator for NEB [203], it is difficult to discuss EX-
induced anorexia with confidence, especially if other parameters such as appetite-regulating
hormones were not measured. EX-induced anorexia was suggested to be the result of alterations
of the circulating levels of appetite-stimulating and suppressing hormones [203-207]. Two studies
reported reductions in the appetite stimulating hormone acylated ghrelin and increases in the
78
appetite suppressing hormone peptide YY, after 60 minutes of high intensity EX, but did not
measure FI [204, 205]. Another study showed increases of the appetite-suppressing hormone
glucagon-like-peptide-1, after medium and high intensity EX, and increases of peptide YY only
appeared after high intensity EX associated with decreases in appetite ratings and EI only after
high intensity EX [206]. Stensel et al., concluded that EX-induced anorexia is mainly promoted
by high but not low intensity levels of EX [203]. Although appetite hormones were not measured,
the lack of effect on FI and subjective appetite scores support the notion that EX-induced anorexia
was not present in the current study. This is further supported by the low-to-moderate intensity
and the medium duration of our EX sessions, which were considerably below the EX intensity
and/or duration of studies reporting significant changes in appetite hormone concentrations and/or
FI [185, 203-207].
Appetite has been reported to strongly predict subsequent FI in several studies [74]. Despite
the limitations of VAS questionnaires, we measured subjective appetite in boys and men using
similar questionnaires [208, 209]. We found positive associations of appetite with FI (r = 0.297; p
= 0.0213) and NEB (r = 0.277; p = 0.0322) in boys but not men, which may have been caused by
differences in sensory-specific satiety systems between children and adults (Table 8-14) [210].
However, we found a suppression of pre-meal subjective appetite with GL in both groups, which
is consistent with other studies from this lab (Table 8-14) [76, 153]. The palatability of the GL
preload reported to be more pleasant by boys than men (Table 8-18, Table 8-19) and may have
promoted the suppression of pre-meal appetite [211] consequently leading to a lower FI with GL
ingestion (Table 8-4). Preload palatability was positively correlated with appetite in men (r =
0.359; p = 0.0049) but not boys. A role of palatability has been described in appetite and FI
regulation, despite controversial findings [202, 212]. EX did not affect pre-meal satiety ratings
79
(Table 8-14). The low-to-moderate EX intensity in our study may not have been high enough to
affect appetite significantly. Other studies investigating the effect of EX intensity have found
reductions in appetite only after medium- to high- intensities [170, 213]. Conversely, post-meal
appetite scores decreased during all conditions being affected mainly by the large caloric
consumption from the pizza meal; a finding consistent with other studies conducted on children
[75, 76, 214] and adults [87, 215] (table 8-15).
Palatability of the pizza meal was also assessed because it can affect the amount of food
eaten at a meal [200-202]. Adults are known to reward themselves for physical activity by eating
more of preferred foods, which tend to be high in fat [216]. Although we used different
questionnaires in boys and men, we did not find any effects of either GL or EX (Table 8-20, Table
8-21) on food palatability. FI and appetite were not correlated with food palatability in either
children or adults. Thus, palatability of pizza meal did not affect FI responses to either GL and/or
EX in the current study.
Thirst and water intake have been strongly correlated with FI, and might also provide
explanation to our observations on FI in boys and men. In both animals [217] and humans [218],
FI and water intake at a meal were consistently found to be correlated [219]. FI was shown to be
reduced when water intake was restricted in healthy volunteers [218]. The analysis of thirst and
water consumption in the present study showed that neither thirst nor water consumption were
affected by GL or EX (Table 8-15). Moreover, we did not observe any association between water
intake and FI. This is inconsistent with previous studies who have found increased thirst ratings
with both EX and GL [76]. Larger volumes of preloads, 250 ml for boys and 350 ml for adults,
may have acted as a positive control in our study and suppressed water intake and thirst in a
80
confounding manner [220], likely hindering expected increases of thirst and water intake with EX
and/or GL.
This study has several limitations. First, only lean individuals were assessed in this study.
Obese and SED individuals were not included. As a consequence of insulin resistance, obese and
SED populations generally display higher levels of insulin (hyperinsulinaemia) [221], which in
turn may disrupt the metabolic flexibility of insulin responsive (hepatic, muscular and fat) tissues
[222]. Accordingly, higher levels of insulin may prevent lipolysis and therefore hinder FATOX
[223]. Recent studies provided evidence that insulin can also have a direct effect on feeding
behavior [224]. In obese and hyperinsulinemic individuals, increased insulin levels were
associated with altered appetite regulation and increased FI when compared to lean individuals
[225]. In the present study, although we did not measure insulin, we hypothesized that the cause
of lower metabolic flexibility in adults compared to children is not related to differences in insulin
levels as they were all healthy. Healthy children and adults have been previously described with
similar insulin levels [132]. Therefore, the relationship between FI regulation and metabolic
flexibility, involving substrate oxidation impaired by insulin, may be different in obese compared
to lean individuals. Our study solely assessed metabolic flexibility by substrate oxidation on FI
without insulin as a potential confounder. Nonetheless, the concept of an impaired FI regulation
and substrate oxidation in obese, involving insulin resistance and hyperinsulinaemia as an
underlying mechanism, needs further investigation.
Second, children exhibited lower fitness levels relative to their age-specific norms and
when compared with adults [157, 226] (Table 8-1). Aerobic fitness is known to affect metabolic
flexibility [130], therefore, differences in metabolic flexibility between boys and men could have
been altered. However, it is difficult to compare metabolic flexibility of our participants to those
81
of other studies due to the variety of assessment methods and study methodologies that are being
used. The assessment of aerobic fitness levels and metabolic flexibility is often based on VET,
FATOX and RER, as practiced in the current study, but varies greatly in units and assessment
methods among studies [127, 131, 158, 186, 188, 227-229] which makes comparison challenging.
Third, the GL preload differed between 1.0 g/kg bodyweight in adults and 1.2 g/kg
bodyweight in children; however, this difference was a major part of the study design in order to
reduce the risk of nausea in men with a greater preload [230]. We chose these numbers based on a
pre-testing where the GL load for our average adult participant would have resulted in a total GL
intake of 84.6 g if the per kg values would have been the same in boys and men. We found that
GL intake decreased physical comfort in men, while it did not affect boys (Table 8-16, Table 8-
17). This finding suggests that men cannot tolerate GL loads on a per kg basis to the same extent
as boys. Furthermore, with the small difference of 0.2g/kg GL intake averaging 10.6 g in total for
our participants, we minimized the possibility that differences in GL intake between boys and men
may have contributed to differences in CHOOX and consequently RER. Significant increases of 29
% in CHOOX were reported with total GL doses of 100 g compared to 50 g [231].
Fourth, we compared appetite and thirst responses of boys and men using similar VAS
questionnaires. A number of studies have shown that children aged 7 years and younger do not
have the cognitive ability to use VAS [232, 233]. However, questions regarding appetite and thirst
were simple and easy to understand for children in our age group.
In conclusion, there was no relationship between RER and FI in either age group,
suggesting that FI regulation, in the short term, is not affected by substrate oxidation as modified
by GL, EX , GL with EX or age.
82
10. FUTURE DIRECTIONS
This research provides evidence that substrate oxidation is not affecting short-term FI
regulation. However, a role of substrate oxidation as a short- and long-term modulator for FI
regulation has been hypothesized since the early 1950’s by the glucostatic and lipostatic theory of
appetite control. Although this study did not report a relationship between RER and FI regulation,
it is important to investigate these theories with respect to different EX durations, intensities,
modes and study populations to understand the full picture of how the oxidation of substrates is
involved in linking metabolic flexibility to appetite and FI regulation and EB. Linking newer
approaches based on appetite hormones with the traditional ones of the lipo- and glucostatic
theories may provide useful data to develop a better understanding of FI and NEB regulation
during EX [81, 84].
Additional research is required to explore the effects of EX modalities and intensities,
fitness and body fat levels of individuals, and time to the next meal under both short-term and
long-term conditions to better comprehend the benefits of EX interventions on FI and body
composition regulation.
10.1. Metabolic Flexibility and Food Intake Regulation in Obesity
It is important to assess the effects of substrate oxidation on FI behaviour among obese and
SED participants. Studies that have investigated habitual activity levels in active and obese/SED
individuals found that active individuals exhibit better aerobic fitness levels, a better metabolic
flexibility [125, 234] and a better regulation of FI and body weight when compared with obese
83
individuals [129, 185, 235]. As previously described, those impairments in metabolic flexibility
and FI regulation are often accompanied with higher levels of insulin in obese individuals [221,
225]. Therefore, it is important to investigate these relationships in obese and SED individuals to
gain a better understanding of the mechanisms involving increased FI and metabolic inflexibility
including insulin resistance and hyperinsulinaemia.
10.2. Explore the Effects of Exogenous and Endogenous Carbohydrate Oxidation
on Food Intake Regulation
Previous studies have shown that total as well as endogenous and exogenous CHOOX
differs with EX intensity and GL intake [166, 182]. When carbohydrates are ingested, energy
derived from exogenous carbohydrates was found to meet a greater proportion of the EE during
rest and EX [182]. Although we did not measure exogenous and endogenous CHOOX, our study
has shown a suppression of FI with GL ingestion and an even greater suppression with GL ingested
prior to EX. These findings suggest that CHOOX was based mainly on the oxidation of exogenous
rather than endogenous carbohydrate sources, which may have been involved in regulating FI
responses.
In this context, it is also important to explore various intensities of EX and their relationship
with endogenous, exogenous, and total CHOOX. High intensity EX was reported to increase the
amount of endogenous CHOOX compared to low intensity EX [182]. Some studies have shown a
reduction of FI after high intensity EX [73, 169-171]. Although we did not find a relationship
between total CHOOX and FI regulation, it is unclear whether higher rates of endogenous and/or
exogenous CHOOX promoted by higher intensity EX could have caused alterations in FI behavior.
84
Therefore, it is important to measure rates of endogenous and exogenous CHOOX with stable
isotope tracers, in addition to total CHOOX. Future studies should investigate the components of
CHOOX in response to higher EX intensities to better understand whether any of these is more
involved than others in FI regulation.
10.3. Control for Appetite Hormones in Lean and Obese Subjects
Knowing that appetite hormones are important modulators of food-intake regulating
systems, it is critical to understand how appetite-related hormones respond to EX generally, and
to compare these responses between normal-weight and overweight/obese individuals. There
should be special focus on children because literature investigating the effects of EX on appetite
hormones in children is scarce. The link between appetite hormone responses, substrate oxidation
and habitual EX and the understanding of the underlying mechanisms of action should also be
investigated as it would be a major asset to the formation and utilization of successful obesity
prevention and treatment EX regimens.
10.4. Standardization of the Time to Meal
Some studies reported a time dependent effect of EX on FI. The lack of effect of EX on FI
in the present study may be due to the time interval between EX bout and test meal [185]. It is
possible that there would have been an increase in FI after EX if the meal had been further
distanced from the end of the EX session. This suggestion is secondary to the findings of studies
that found decreased suppression of post-EX appetite 60 minutes later [73], and studies that
showed no effect of EX on FI within 30 minutes [75, 76]. Rather than a fixed length of time to the
85
next meal post exercise, participants in future studies could be fed at several time points or given
the option to snack or choose when they would like to have a meal. In the literature, the time to
the next meal ranged from 30 min [75, 76] to 4 hours [163].
10.5. Control for Daily Physical Activity Levels and Diet
The measures of VO2peak and VET reflect overall habitual activity levels, but activity
levels may differ on the day before the experimental sessions. Studies have shown higher rates of
glycogen depletion with vigorous activity when compared to resting [236, 237]. In the same way,
high caloric diets can result in more replenished glycogen stores relative to [238]. Glycogen stores
have been proposed to affect the regulation of FI [239, 240]. Thus, future studies should take into
account the level of physical activity and the dietary habits of participants in the days preceding
the measurements. Accelerometers and HR monitors could quantify the duration and intensity of
the habitual activity performed before the measurements [241].
10.6. Long-term Intervention Study
The most important issue is to identify and create effective long-term EX programs which
guarantee ongoing weight loss and weight maintenance. This study assessed only short-term
subjective appetite, FI, NEB and substrate oxidation after acute exercise sessions, which may not
reflect the relationship between substrate oxidation and FI in the long-term [240]. Future studies
should investigate the effects of long-term substrate oxidation on overall FI and NEB regulation
using activity patterns typical to individuals’ real life, such as in schools and with typical feeding
times such as after recess or gym class.
86
11. SUMMARY & CONCLUSIONS
SUMMARY
1. GL increased RER and decreased FI, while EX increased RER but had no effect on FI. GL
with EX combined decreased FI but did not affect RER. Boys had higher FI than men,
despite lower values of RER across all conditions.
2. GL suppressed FATOX and increased CHOOX in boys and men. Boys had a lower RER and
a stronger preference for FATOX across all conditions and especially during EX when
compared to men.
3. NEB was increased by GL preloads, lowered by EX and showed a trend to be decreased
when GL was combined with EX.
CONCLUSION
In conclusion, there was no relationship between RER and FI in either age group, suggesting
that FI regulation, in the short term, is not affected by substrate oxidation as modified by GL, EX,
GL with EX or age.
87
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12. APPENDENCIES
12.1. Appendix 1 Supplemental Data
12.1.1. Food Intake (Not adjusted for kg body-weight)
Compared to CON, FI was lower with GL (p < 0.0001), but not affected by EX. FI was higher
in men when compared to boys AGE (p = 0.0068). GL*EX showed trend for a significant
interaction GL*EX (p = 0.0557). No significant interactions were found.
1Food Intake (kcal) in boys and men
Activity: Sedentary Exercise Pooled
Drink: Water Glucose Water Glucose
Boys 880 ± 66 798 ± 52 895 ± 69 715 ± 64 822 ± 32
Men 1174 ± 88 1007 ± 90 1181 ± 79 936 ± 79 1074 ± 43
Pooled 1027 ± 60 902 ± 55 1037 ± 58 825 ± 54
1Means ± SEM (kcal); n=30. ANOVA analysis (GL, p < 0.0001; EX, p = 0.3227; GL*EX, p =
0.0557; AGE, p = 0.0068; AGE*EX, p = 0.9656; AGE*GL, p = 0.2709; AGE*EX*GL, p =
0.8282).
115
12.1.2. Net Energy Balance (Not adjusted for kg body-weight)
Compared to CON, NEB was decreased by EX (p < 0.0001). GL (p = 0.0543) showed a trend
to increased NEB. NEB was higher in men when compared to boys AGE (p = 0.0074). No
significant interactions were found.
1Net energy balance (kcal) in boys and men
Activity: Sedentary Exercise Pooled
Drink: Water Glucose Water Glucose
Boys 848 ± 64 924 ± 54 746 ± 67 739 ± 65 724 ± 33
Men 1114 ± 88 1234 ± 92 920 ± 80 1006 ± 87 917 ± 47
Pooled 981 ± 59 1079 ± 60 833 ± 55 872 ± 54
1Values are means ± SEM (kcal); n=30. ANOVA analysis (GL, p = 0.0543; EX, p < 0.0001;
GL*EX, p = 0.1371; AGE, p = 0.0074; AGE*EX, p = 0.3579; AGE*GL, p = 0.3316;
AGE*EX*GL, p = 0.5248).
116
12.1.3. Energy Expenditure (Not adjusted for kg body-weight)
Compared to CON, EE was increased by GL (p = 0.0101), decreased by EX (p < 0.0001).
EE was higher in men when compared to boys AGE (p < 0.0001). There was a significant
interaction for AGE*EX (p < 0.001). No other significant interactions were found (. AGE specific
analysis showed that EX (p < 0.0001) increased and GL (p = 0.0742) showed a trend to lower
FATOX in boys. No other significant interaction was found. In men, EX (p < 0.0001) increased
and GL (p =0.0619) increased EE. No other significant interaction was found.
1Energy Expenditure (kcal) in boys and men
Activity: Sedentary Exercise Pooled
Drink: Water Glucose Water Glucose
Boys2 43 ± 3 50 ± 3 148 ± 7 152 ± 9 98 ± 7
Men3 60 ± 3 61 ± 3 248 ± 18 261 ± 18 157 ± 14
Pooled 52 ± 3 55 ± 2 198 ± 13 206 ± 14
1Values are means ± SEM (kcal); n=15. ANOVA analysis (GL, p = 0.0101; EX, p < 0.0001;
GL*EX, p = 0.3778; AGE, p < 0.0001; AGE*EX, p < 0.0001; AGE*GL, p = 0.6669;
AGE*EX*GL, p = 0.1636).
2 Values are means ± SEM; n=15. ANOVA analysis for boys (GL, p = 0.0742; EX, p < 0.0001;
GL*EX, P = 0.7102).
3 Values are means ± SEM; n=15. ANOVA analysis for men (GL, p = 0.0619; EX, p < 0.0001;
GL*EX, p = 0.1165).
117
12.1.4. Carbohydrate Oxidation (Not adjusted for kg body-weight)
Compared to CON, CHOOX was increased by GL (p < 0.0001) and EX (p < 0.0001). A
significant interaction was found for GL*EX (p = 0.0061), showing an additional increase in
CHOOX. Men had higher CHOOX when compared to boys AGE (p < 0.0001). There was an
interaction for AGE*EX (p < 0.0001). No other significant interactions were found. AGE specific
analysis showed that EX (p < 0.0001) and GL (p = 0.0009) increased CHOOX in boys. There was
a significant interaction for GL*EX (p = 0.0323) in boys. In men, EX (p < 0.0001) and GL (p <
0.0001) increased CHOOX. GL*EX (p = 0.0519) interaction showed a trend but did not reach
significance.
1Carbohydrate oxidation (kcal) in boys and men
Activity: Sedentary Exercise Pooled
Drink: Water Glucose Water Glucose
Boys 22 ± 2 30 ± 3 77 ± 7 102 ± 9 58 ± 5
Men 33 ± 3 43 ± 3 177 ± 15 214± 17 117 ± 12
Pooled 27 ± 2 37 ± 2 127 ± 12 158 ± 14
1Values are means ± SEM (kcal); n=30. ANOVA analysis (GL, p < 0.0001; EX, p < 0.0001;
GL*EX, p = 0.0061; AGE, p < 0.0001; AGE*EX, p < 0.0001; AGE*GL, p = 0.3706;
AGE*EX*GL, p = 0.9880).
2 Values are means ± SEM; n=15. ANOVA analysis for boys (GL, p = 0.0009; EX, p < 0.0001;
GL*EX, p = 0.0323).
3 Values are means ± SEM; n=15. ANOVA analysis for men (GL, p < 0.0001; EX, p < 0.0001;
GL*EX, p = 0.0519).
118
12.1.5. Fat Oxidation (Not adjusted for kg body-weight)
Compared to CON, FATOX was decreased by GL (p = 0.0002) and increased with EX (p
< 0.0001). FATOX was similar in boys and men. No other significant interactions were found.
1Fat oxidation (kcal) in boys and men
Activity: Sedentary Exercise Pooled
Drink: Water Glucose Water Glucose
Boys 22 ± 3 19 ± 4 71 ± 9 50 ± 8 40 ± 4
Men 27 ± 3 17 ± 2 71 ± 7 47 ± 10 40 ± 4
Pooled 24 ± 2 18 ± 2 71 ± 5 48 ± 7
21Values are means ± SEM (kcal); n=30. ANOVA analysis (GL, p = 0.0002; EX, p < 0.0001;
GL*EX, p = 0.0161; DEV, p = 0.9737; DEV*EX, p = 0.7786; DEV*GL, p = 0.5051;
DEV*EX*GL, p = 0.7907)
119
12.1.6. Water Consumption (Not adjusted for kg body-weight)
EX (p = 0.0858) showed a trend for water consumption to be increased. GL had no effect
on water consumption. No significant interactions were found.
1Water consumption (ml) in boys and men
Activity: Sedentary Exercise Pooled
Drink: Water Glucose Water Glucose
Boys 206 ± 46 203 ± 50 190 ± 39 255 ± 45 213 ± 22
Men 232 ± 55 303 ± 55 331 ± 56 355 ± 51 349 ± 27
Pooled 219 ± 35 254 ± 38 260 ± 36 304 ± 35
1Values are means ± SEM (kcal); n=30. ANOVA analysis (GL, p = 0.1196; EX, p = 0.0858;
GL*EX, p = 0.8445; DEV, p = 0.0936; DEV*EX, p = 0.2839; DEV*GL, p = 0.7418;
DEV*EX*GL, p = 0.2787).
120
12.2. Appendix 1A BMI for Age Percentile Charts in Boys
121
12.3. Appendix 1B CDC BMI Chart for men
122
12.4. Appendix 2A Telephone Screening Questionnaire Boys
123
12.5. Appendix 2B Telephone Screening Questionnaire Men
124
12.6. Appendix 3A Screening Questionnaire Boys
125
126
127
128
129
130
131
12.7. Appendix 3B Screening Questionnaire Men
132
133
134
135
136
137
12.8. Appendix 4A Recruitment Letter Boys
138
12.9. Appendix 4B Recruitment Letter Men
139
12.10. Appendix 5A Study information sheet and consent form boys
140
141
142
143
144
12.11. Appendix 5B Study Information Sheet and Consent Form Boys
145
146
147
148
12.12. Appendix 6 Pizza Form
149
12.13. Appendix 7 Session Sheet
150
12.14. Appendix 8A Recruitment poster boys
151
12.15. Appendix 8B Recruitment poster men
152
12.16. Visual Analog Scale Questionnaires
12.16.1. Appendix 9A VAS Motivation to Eat Boys
153
12.16.2. Appendix 9B VAS Physical Comfort Boys
154
12.16.3. Appendix 9C VAS Preload Sweetness Boys
155
12.16.4. Appendix 9D VAS Preload and Pizza Palatability Boys
156
12.16.5. Appendix 10A VAS Motivation to Eat Men
157
12.16.6. Appendix 10B Physical Comfort Men
158
12.16.7. Appendix 10C Energy/Fatigue and Stress Men
159
12.16.8. Appendix 10D Pizza and Preload Palatability Men
160
12.16.9. Appendix 11 Nutritional Information Pizza
3 - Cheese Pepperoni
Deluxe