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