is short-term high-intensity interval training effective at

IS SHORT-TERM HIGH-INTENSITY INTERVAL TRAINING EFFECTIVE AT IMPROVING INFLAMMATION, VISCERAL ADIPOSITY, AND ADIPONECTIN?

DANIEL HINCHLIFFE

LEEDS BECKETT UNIVERSITY CARNEGIE FACULTY

MSc. SPORT AND EXERCISE PHYSIOLOGY 2016

IS SHORT-TERM HIGH-INTENSITY INTERVAL TRAINING EFFECTIVE AT IMPROVING INFLAMMATION, VISCERAL ADIPOSITY, AND ADIPONECTIN?

DANIEL HINCHLIFFE

LEEDS BECKETT UNIVERSITY CARNEGIE FACULTY

MSc. SPORT AND EXERCISE PHYSIOLOGY 2016

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This Major Independent Study constitutes my own work and all material that is not my own is fully acknowledged. No part of this work has been submitted for assessment elsewhere.

Student: …………………………….

Supervisor: …………………………

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Contents Page Number Abbreviations…………………………………………………….…………..…ix Abstract…………………………………………………………..…….……….xi Chapter 1: Background 1.1

Introduction………………………………….…………………..…….1

1.2

Aim.………………………………………………….……………..….6

1.3

Objectives…………………………………………………….………..6

1.4

Research Question……………………………………………..………7

Chapter 2: Review of Literature 2.1

Inflammation

2.1.1

General Overview……………………………………………….….…8

2.1.2

Chronic Low-Grade Inflammation………………………………..…..9

2.2

Obesity

2.2.1

Prevalence of Obesity……………………………………….……..…11

2.2.2

Visceral Adipose Tissue………………………………………………13

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2.2.3

Pathophysiology of Visceral Adipose Tissue…………..…….…….…14

2.2.4

Adipokines (Adiponectin)………………………………………….…16

2.3

Exercise, Inflammation and Visceral Adipose Tissue……….…..……18

2.3.1

Exercise as a means to reduce Visceral Adipose Tissue……..….…….19

2.3.2

Low-Volume High-Intensity Interval Training……………….……….26

Chapter 3: Methodology 3.1

Research Design………………………………………………………29

3.2

Validity…………………………………………………….……….…29

3.3

Ethics

3.3.1

Research ethics………………………………………………………..32

3.3.2

Ethical approval………………………………………….………..…..33

3.3.3

Consent………………………………………………………………..33

3.3.4

Security of data………………………………………….………….…34

3.4

Sampling strategy

3.4.1

Sampling method…………………………………………………..….35

3.4.2

Recruitment………………………………….………………………..37

3.4.3

Participants………………………………………………………..…..37

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3.5

Data Collection

3.5.1

Preliminary Screening…………………………….…………………..38

3.5.2

Maximal Exercise Test…………………………………………….….40

3.5.3

Visceral Adipose Tissue Assessment……………………………….…42

3.5.4

Blood Sampling and Analysis……………………………………..….44

3.5.5

High Intensity Interval Training Group…………………….…………46

3.6

Data analysis………………………………………………………….48

Chapter 4: Results 4.1

Baseline Characteristics………………………………………………49

4.2

Visceral Fat Mass (Arithmetic means)………………………………..50

4.3

hsCRP (Geometric means)……………………………………………51

4.4

Total Adiponectin (Arithmetic means)………………………………..51

Chapter 5: Discussion…………………………………………………………53

Chapter 6: Conclusions………………………………………………………..62

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References…………………………………………………………….………..63

List of Tables Table 1

DETAILS OF EXERCISE INTERVENTION………………………47

Table 2

BASELINE CHARACTERISTICS OF THE PARTICIPANTS…….49

Table 3

DEPENDENT VARIABLES BEFORE AND AFTER SIX WEEKS OF

HIIT……………………………………………………………………………..50

List of Figures Figure 1

FLOWCHART OF RECRUITMENT PROCESS……………….38

Figure 2

ERROR BAR GRAPH (95% CONFIDENCE INTERVALS) FOR

VISCERAL FAT MASS…………………………………………..……….……51 Figure 3 ERROR BAR GRAPH (95% CONFIDENCE INTERVALS) FOR TOTAL ADIPONECTIN………………………………………………………..……….52

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Appendices Appendix A LITERATURE REVIEW OF EXPERIMENTAL STUDIES EXAMINING THE EFFECTS OF EXERCISE ON INFLAMMATION/BODY COMPOSITION…………………………………………………………………89 Appendix B FACULTY RESEARCH ETHICS COMMITTEE APPROVAL…97 Appendix C PARTICIPANT INFORMATION SHEET………………………..98 Appendix D INFORMED CONSENT FORM………………………………….104 Appendix E SCREENING QUESTIONNAIRE………………………………..108 Appendix F RECRUITMENT POSTER………………………………………..113 Appendix G

DETERMINING THE RAMP SLOPE………………………….114

Appendix H

MIS SUPERVISORY MEETING FORMS (6)………………….115

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Acknowledgements I would like to thank all those who supported this study, especially Mr C. Tsakirides for his support and guidance throughout the last year (the coffee breaks kept me going through those tedious data collection periods). I would also like to thank all the learning support staff that helped out with calibrating the equipment and ensuring that the laboratory bookings ran smoothly; my parents for their continued support through tough times and their countless efforts at proof-reading my work; my friends for being so patient on the ‘lost weekends’ when I was working. Finally I would like to thank all the participants that took part in the study, without those willing volunteers this study would not have been possible!

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Abbreviations

The following table provides a key to the abbreviations used within the thesis.

Abbreviation

Description

ACSM

American College of Sports Medicine

BMI

Body Mass Index

CON

Control Group

CRP

C-Reactive Protein

CT

Computed Tomography

CV

Coefficient of Variation

DXA

Dual Energy X-ray Absorptiometry

ECG

Electrocardiogram

ELISA

Enzyme Linked Immunosorbent Assay

EU

European Union

FFA

Free Fatty Acid

GH

Growth Hormone

HIIT

High-Intensity Interval Training

HMW

High Molecular Weight

hsCRP

High sensitivity C-Reactive Protein

ICRP

International Commission of Radiological Protection

IL

Interleukin

LDL

Low Density Lipoprotein ix

LMW

Low Molecular Weight

LT

Lactate Threshold

MICT

Moderate-Intensity Continuous Training

MRI

Magnetic Resonance Imaging

n

Sample Size

OECD

Organisation for Economic Cooperation and Development

PPAR-y

Peroxisome Proliferator - Activated Receptor Gamma

SAT

Subcutaneous Adipose Tissue

TNF-a

Tumour Necrosis Factor Alpha

VAT

Visceral Adipose Tissue

VLDL

Very Low Density Lipoproteins

VO2peak

Peak Oxygen Uptake

VO2

Oxygen Uptake

VT

Ventilatory Threshold

WHO

World Health Organisation

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Abstract Research has identified that visceral adiposity is a significant risk factor in debilitating diseases through secretion of proinflammatory cytokines. As an active endocrine organ, adipose tissue manipulates many reactions within the body and secretes proteins that affect homeostasis thus leading to metabolic dysregulation. Exercise attenuates inflammation and reduces visceral adiposity. Exercise intensity has been postulated to effect visceral adipose tissue lipolysis, whereby increased exercise intensity is suggested to have an increased reduction in visceral adiposity. The aim of the study was to investigate whether a low-volume high-intensity interval training intervention (HIIT) was effective at improving inflammation, visceral adiposity, and adiponectin. A pre-experimental research design was adopted, 14 healthy mixed gender adults [mean (SD): age 41.3 (9.5) yr, body mass 72.4 (13.7) kg, body mass index 21.2 (3.5) kg.m-2] were recruited and underwent a six week exercise intervention on a cycle ergometer. Prior to and post intervention, measurements were collected; serum was analysed for TNF-a, hsCRP and adiponectin via enzyme linked immunosorbent assay whereas visceral adiposity was estimated using Dual-energy X-Ray absorptiometry. Dependent t-tests revealed no significant differences between pre and post values for visceral adiposity (P=0.746) and adiponectin (P=0.246). There was a significant decrease in hsCRP (P=0.025) in post-training.

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The present investigation suggests six weeks of HIIT is not sufficient to induce beneficial alterations in visceral adiposity and adiponectin, yet it has been demonstrated that significant reductions in CRP are evident in a heterogenous cohort.

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Chapter 1: Background

Word Count: 13597

1.1 Introduction Obesity has been evident in the global population for decades, yet in the twenty first century it has reached epidemic proportions, with at least 2.8 million people dying each year due to being overweight (World Health Organisation, 2014). The financial strain of treating obesity-related problems burdens economies (Grieve et al, 2013), yet contemporary research has provided evidence that simple lifestyle changes can have a profound impact on obesity related health (Stewart et al, 2014). The use of pharmacological interventions to combat the accumulation of excess fat is not a viable option, whereas a combination of consuming a healthy diet and participating in regular physical activity has been shown to induce beneficial effects for a variety of health outcomes (Dâmaso et al, 2014).

Various physiological mechanisms exist in the link between obesity and mortality yet it is not the total amount of body fat per se that seems to be problematic but the distribution of body fat that is closely linked to metabolic dysfunction (Bastard et al, 2006). In a broad sense, the principal depots of adipose tissue include visceral adipose tissue (VAT), which is located centrally within the abdominal cavity and enclosed by the peritoneum, subcutaneous adipose tissue (SAT) (which is located directly under the skin) and ectopic adipose tissue which is found in localities not directly associated with storage. The mechanisms that aim to explain the reason for ectopic and visceral fat storage are beyond the scope of this thesis, but one hypothesis is that these depots occur as a result of the inability for SAT to store excess lipids as a metabolic ‘sink’,

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therefore resulting in a spillover from SAT to VAT and eventually to other organs and tissues (Britton and Fox, 2011). VAT has been demonstrated to be an independent risk factor for obesity related metabolic and cardiovascular diseases (Hocking et al, 2013), with animal studies highlighting an improvement in insulin sensitivity in rats following the surgical removal of VAT (Gabriely et al, 2002). The Health ABC study measured VAT by Computed Tomography (CT) in 3000 adults, and demonstrated that VAT is associated with metabolic syndrome in both normal weight and obese cohorts (Goodpaster et al, 2005), which reinforces the concept that the accumulation of VAT could possibly lead to metabolic disturbances.

Various mechanisms have been hypothesised to explain the roles of VAT in health and disease: lipolysis and increased sensitivity to catecholamines, the flow of free fatty acids (FFA) to the liver through the portal vein, secretion of proinflammatory cytokines, dysfunction of anti-inflammatory substances (adiponectin) and in the function of Peroxisome Proliferator-Activated Receptor Gamma (PPAR-y) signalling and a lower angiogenic capability and hypoxia (Walker et al, 2014). The focus of the current thesis is centred around the secretion of proinflammatory cytokines and the dysregulation of adiponectin via systemic concentrations.

The underlying effects of inflammatory cytokines can predispose individuals to chronic long-term illnesses through concomitant metabolic alterations. In an acute immune response, the recruitment of T-cells and the development of an antigen specific immune response is assisted by the proinflammatory cytokines Tumour Necrosis Factor Alpha (TNF-a) and Interleukin 1 Beta (IL-1b). These acute phase 2

reactants have a negative effect on metabolism during acute illness, leading to alterations in glucose homeostasis (hyperglycaemia) and insulin resistance. Although the context is specific to acute illness (Gruys et al, 2005), low-grade chronic inflammation is strongly associated with increasing age, lifestyle factors and obesity resulting in an increased risk of disease progression (Beavers et al, 2010).

C-Reactive Protein (CRP) is the most frequently studied inflammatory biomarker for disease progression in clinical studies, with previous literature providing evidence for its strong independent association with cardiovascular disease (Ridker, 2004). CRP has been linked with various other diseases such as diabetes (Duncan and Schmidt, 2006), dementia (Kuo et al, 2005) and chronic heart failure (Yin et al, 2004). It appears that the primary function of CRP is to stimulate the synthesis of tissue factor production, and to activate complement when aggregated. Aggregated CRP binds to Low Density Lipoproteins (LDL) and Very Low Density Lipoproteins (VLDL) in vitro, leading to the activation of complement and initiation of coagulation (Puglisi and Fernandez, 2008), thus partly explaining its link with cardiovascular disease. Reduced CRP is associated with weight loss and high adiponectin levels (Ouchi et al, 2003).

TNF-a is a pleiotropic cytokine with a complex role in the inflammatory process. In combination with other immune cells, TNF-a is a crucial contributor to the development of atherosclerotic lesions by the initiation of the inflammatory cascade inside the arterial wall (Popa et al, 2007), thus making TNF-a a vital element in the pathogenesis of cardiovascular disease. Both CRP and TNF-a are important 3

biomarkers in underlying inflammation due to their pivotal roles in the inflammatory cascade, therefore warranting the measurement of these cytokines in the assessment of chronic low-grade inflammation.

Adiponectin is a protein hormone that is secreted exclusively from adipocytes and has been considered an anti-inflammatory and anti-oxidative adipokine that protects against cardiovascular disease (Antoniades et al, 2009). Adiponectin is found abundantly in circulation with concentrations ranging from between 2 to 20 µg.mL-1 (Lihn et al, 2005), with lower levels associated with obesity and metabolic dysfunction (Weyer et al, 2001). A negative relationship exists between adiponectin and visceral fat (Ryan et al, 2003) with the causative mechanism unclear, yet some authors speculate that TNF-a might be suppressing adiponectin levels when fat mass is increased.

The real challenge that our governments face is incentivising the public to modify their sedentary lifestyles. The thought of regular physical activity might be perceived as an arduous task for inactive individuals due to the World Health Organisation (WHO) (2010) recommended guidelines of 150 minutes of moderate intensity aerobic physical activity, or 75 minutes of vigorous physical activity per week. This requires a significant time commitment which is difficult to adhere to due to busy lifestyles. In the past decade, researchers have focused on a new and exciting method of exercise that addresses the time commitment issue, high-intensity interval training (HIIT).

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HIIT is characterised by brief periods of high-intensity exercise (30-60 seconds) often performed at > 90% peak oxygen uptake (VO2peak) interspersed with short recovery periods at a lower intensity and is generally performed on a cycle ergometer (Gibala et al, 2006). It has been established that HIIT provides a sufficient stimulus for the improvement of a number of physiological adaptations (Laursen et al, 2005), as well as being superior to more traditional forms of exercise such as moderate-intensity continuous training (MICT) (Gaesser and Angadi, 2011).

Gibala and colleagues developed a low-volume model of HIIT using slightly lower intensities (90-100% VO2peak) than previous protocols. Low-volume HIIT refers to exercise sessions that are brief in duration (< 10 minutes of intense exercise) with a training session lasting approximately 30 minutes with the inclusion of warm-ups, cool-downs and recovery periods. This addresses the common time commitment excuse many individuals cite as being the reason why they fail to comply with the WHO guidelines for physical activity.

Weston et al (2014) completed a meta-analysis on the effects of low-volume HIIT on fitness in adults and concluded that this type of exercise elicits substantial improvements in VO2peak in sedentary and non-athletic participants, however to date there is little research conducted on the effects of low-volume HIIT on VAT, inflammation and adiponectin. The effects of MICT on VAT have been reviewed with subsequent meta-analyses providing a more detailed interpretation of the literature (Chaston and Dixon, 2008; Ismail et al, 2012; Vissers et al, 2013) although the 5

majority of studies included in the analyses consisted of overweight/obese adults. All three meta-analyses had similar conclusions; aerobic exercise training was central to exercise-induced VAT modification with the intensity of exercise playing an important role in the amount of VAT loss. The application of a low-volume model of HIIT to the general population might induce superior VAT loss, with a possible concomitant reduction in chronic low-grade inflammation through systemic concentrations of TNF-a, CRP and adiponectin.

1.2 Aim The aim of this study was to investigate whether or not a six week exercise intervention altered systemic inflammation (via TNF-a and CRP), adiponectin and visceral adiposity in a heterogeneous group of individuals.

1.3 Objectives I.

A group of heterogenous individuals underwent baseline testing: Assessment of Visceral adiposity via Dual Energy X-ray Absorptiometry (DXA), TNF-a, hsCRP and Adiponectin via Enzyme Linked Immunosorbent Assay (ELISA).

II. The participants completed six weeks of low-volume HIIT training three times per week. The first training session took place the week after baseline measurements, and the last training session occurred the week before the ‘post’ measurements. III. The participants underwent the same initial tests completed at baseline.

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IV. An appropriate statistical model was fitted to the data to assess if there were any significant differences between pre and post values for the four dependent variables.

1.4 Research Question Is short term high-intensity interval training effective at improving inflammation, visceral adiposity, and adiponectin?

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Chapter 2: Review of Literature 2.1 Inflammation 2.1.1 General Overview The inflammatory process is an essential response to illness or infection. Inflammation mediates internal homeostasis, and acts to protect the body’s internal environment from foreign substances, as well as to clear cellular debris and prevent the spread of infection. Cytokines are intercellular signalling polypeptides produced by a variety of activated cells and tissue types, such as leukocytes and skeletal muscle. These proteins are produced at the site of inflammation in response to the aforementioned factors, this is known as the local response. An influx of a variety of cells including neutrophils, monocytes and lymphocytes are facilitated by cytokines, and are responsible for the clearance of the antigen and to initiate the healing process. The local inflammatory response is followed by a systemic reaction which is also known as the acute phase response. Inflammatory cells and the vascular system are activated by the release of proinflammatory cytokines, this is then followed by an increase in other inflammatory mediators which are diffused in to the extracellular compartment and circulate in the blood. Proinflammatory cytokines stimulate an increase in hepatocyte derived acute phase proteins which are released from the liver, and act as key regulators of the inflammatory cascade (Gruys et al, 2005).

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2.1.2 Chronic Low-Grade Inflammation Chronic low-grade inflammation is a prominent contributor to a vast amount of chronic health conditions affecting various bodily systems: cardiovascular (atherosclerosis, coronary heart disease), endocrine (diabetes, insulin resistance) and neurological (dementia, depression). Common inflammatory and immune processes act on different cell types leading to different disease manifestations. The function of various types of epithelial cells can be altered by inflammatory processes which subsequently lead to different disease states. For example, altered endothelial cells can lead to atherosclerosis, synoviocytes lead to arthritis, enterocytes lead to inflammatory bowel disease, glomerular/tubular epithelial cells lead to kidney disease and bronchoalveolar cells lead to lung disease (Libby, 2007). Therefore it seems plausible that at the cellular level, inflammation underpins a wide variety of disease states, and is a major player in the development of chronic health conditions associated with high mortality rates.

Chronic low-grade systemic inflammation can be a prospective risk factor for many chronic health conditions. Petersen and Pedersen (2005) highlighted that chronic lowgrade inflammation can be classed as a typical 2/3 fold increase in the systemic concentrations of several proinflammatory and anti-inflammatory cytokines (TNF-a, IL-1, IL-6, IL-1ra, sTNF-R and CRP). Although the inflammatory response is essential for the mediation of trauma or infection, persistent low-grade inflammation can disrupt cellular homeostasis and predispose individuals to chronic long-term health issues. 9

TNF-a is an up streaming proinflammatory cytokine that plays a pivotal role in the innate and adaptive immunity, cell proliferation and apoptotic processes (Popa et al, 2007). TNF-a is produced by a number of cells including activated immune T-cells, macrophages, monocytes and adipocytes. This proinflammatory cytokine alongside interleukin 6 (IL-6) is strongly associated with an increased risk for several diseases including cardiovascular disease, cancer and diabetes, thus making it an important cytokine to consider in the risk assessment of individuals. TNF-a is also crucial for the induction of other cytokines (IL-6 and IL-8) which leads to the production of a large number of hepatocyte derived acute phase proteins such as CRP.

CRP is the first described acute phase protein (Tillett and Francis, 1930) involved within the immune systems systemic response. CRP is a prominent marker of chronic low-grade inflammation, and has been linked to several pathological disease states. Ridker et al (2000) demonstrated that CRP was the strongest predictor of cardiovascular events, therefore supporting the notion that the acute phase reactant should be considered in studies focused around long-term health and inflammation. CRP has demonstrated a dose-response relationship to coronary heart disease independent of other risk factors (Pearson et al, 2003), suggesting that the acute phase reactant plays a pivotal role in the development of chronic illnesses, which is consistent with previous research (Ridker et al, 2000).

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Inflammatory cytokines such as TNF-a and CRP are increased in obesity due to the increased adipocytes that house macrophages/monocytes that secrete such cytokines. Compared with normal weight adults, those who are obese have a 50% to 75% increased risk of cardiovascular diseases over 3-4 year periods (Wilson et al, 2002). The cellular composition of adipocytes changes in obese states, favouring a harmful environment resulting in a prolonged inflammatory state. This physiological phenomenon partly explains the increased mortality of overweight individuals, and provides a platform to base research studies on for investigating the relationship between obesity and inflammation.

2.2 Obesity 2.2.1 Prevalence of Obesity Obesity is a 21st century global epidemic, affecting more than 1.9 billion adults worldwide

with the prevalence of obesity increasing more than twofold between

1980 and 2014 (World Health Organisation, 2015). In accordance with the Organisation for Economic Cooperation and Development (OECD) survey data, over half (52.6%) of the adult population in the European Union (EU) are overweight (Walker et al, 2014). These statistics pose a genuine threat to the sustainability of global healthcare systems due to the financial strain of obesity. The increasing rates of obesity are a cause for concern due to direct links between obese individuals and mortality (Lau et al, 2007), morbidity (Mitchell et al, 2011) and healthcare costs.

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Obesity can be defined as abnormal or excessive fat accumulation (World Health Organisation, 2015) and is usually classified using body mass index (BMI). BMI is a simple anthropometric measurement of overall adiposity, and is used globally to categorise individuals based on specific cut off points. The determination of overweight and obese individuals based on BMI have been previously established over a decade ago (National Institutes of Health, 1998), with overweight classed as between 25 kg.m-2 to 29.9 kg.m-2, and obese counterparts being classed as > 30 kg.m-2. Although BMI can be perceived as a useful surrogate measure for distinguishing between a healthy weight and an unhealthy weight, it fails to account for important confounding factors such as ethnicity, muscle mass, gender and age. BMI is also ignorant to adipose tissue distribution, which is a crucial determinant of metabolic disease and negative health issues, thus rendering this simplistic measurement as obsolete in terms of assessing the amount of visceral and subcutaneous fat. Therefore the use of BMI is somewhat tainted by its failure to control for variables that will have a considerable effect on the outcome. Due to the simplistic nature of calculating BMI, it is still used world wide by healthcare professionals though substantial individual variability exists in the correlation between excess body fat and pathologic consequences (Bays, 2011). Research is ongoing with regards to using blood biomarkers in combination with anthropometric measurements for stratifying individuals that are at high risk of chronic health conditions (Lemieux et al, 2007; Sam et al, 2009; Lim et al, 2012). 


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2.2.2 Visceral Adipose Tissue Obesity holds strong links with many debilitating diseases including type 2 diabetes mellitus, cardiovascular diseases, dyslipidemia and insulin resistance. Due to the fact that obesity is driving the global healthcare systems out of pocket with the ever increasing numbers of individuals seeking medical treatment, it is important to discuss how excess adiposity is closely associated with such comorbidities. Originally adipose tissue was viewed as an inactive storage depot, yet it is now known to be an active endocrine organ, both vascularised and innervated, with a clear anatomy and a high degree of plasticity responding to both corporeal and environmental changes (Walker et al, 2014). In the 1950’s, Vague eluded to the concept that the distribution of adipose tissue was closely linked with metabolic complications such as diabetes and cardiovascular disease. Vague (1956) postulated that android obesity, elective localisation of fat on the upper part of the body, led to metabolic disturbances. Within the scientific community it is known that the term android fat is associated with VAT which surrounds the inner organs in the abdominal cavity. Intra-abdominal VAT accounts for between 10% to 20% of total body fat yet has been revealed to be strongly associated with adverse metabolic complications (Fox et al, 2007), more so than SAT. The reasons why increased VAT seems to be a positive risk factor for many disease states are multifaceted, yet there is one hypothesis that seems to be common in the literature; secretion of proinflammatory cytokines.

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2.2.3 Pathophysiology of Visceral Adipose Tissue Matsuzawa (2008) studied the molecular characteristics of VAT and adipocytes through gene expression and discovered that visceral adipocytes secrete a variety of bioactive substances, known as adipokines. Adipokines can be subdivided into adipokines adipose tissue specific bioactive substances (i.e. leptin and adiponectin), and adipokines abundantly secreted from adipose tissue which are nonspecific for visceral adipocytes (TNF-a, interleukins etc.).

When an individual has a significant accumulation of VAT, hypersecretion of proinflammatory cytokines ensues which can encourage chronic low-grade inflammation. The hypersecretion of proinflammatory cytokines may be one mechanism that offers to explain the positive relationship between VAT accumulation and the development of multiple risk factors for metabolic/cardiovascular diseases, yet other explanations aim to elucidate the intricate nature between VAT and pathological disease. Increased influxes of FFA’s from VAT to the liver could be a precursor for metabolic complications as suggested by Matsuzawa (2008). VAT is characterised by enhanced lipolysis, and an increased flux of FFA’s to the portal circulation which is directly linked to the liver. Previous research in animal models proposed that increased FFA influx to the liver from VAT may contribute increased VLDL formation and secretion, which could subsequently result in hyperlipidemia (Kuriyama et al, 1998). Moreover FFA’s stimulate cytokine production of macrophages (Suganami et al, 2005) thus modulating underlying inflammation within the adipose tissue. 14

It is important to be aware that it is not the adipocyte per se that evokes the secretion of proinflammatory cytokines, it is the macrophage content of the adipose tissue that dictates the release of cytokines (Weisberg et al, 2003). Obesity switches the phenotypic state of the cells from an anti-inflammatory M2 polarisation state to a proinflammatory M1 polarisation state. The increase in M1 activated macrophages has been shown to secrete a variety of proinflammatory cytokines, that might contribute to obesity-related metabolic complications (Xu et al, 2003).

It is hypothesised that the primary mechanism responsible for the association between increased VAT accumulation and increased risk of disease is the secretion of bioactive substances from VAT which is then drained by the portal circulation. This has been demonstrated in obese cohorts by Fontana et al (2007). The authors concluded that VAT is an important site for cytokine secretion, therefore postulating a mechanistic link between VAT and systemic inflammation. Fox et al (2007) demonstrated through a large observational study (n=3001) that VAT remains more strongly correlated to an adverse metabolic risk profile more so than SAT. In a smaller scale observational study, Kuk et al (2006) reported that VAT was a strong independent predictor of allcause mortality in a male cohort. Correlation does not imply causation, yet it highlights an important area of research in relation to the link between VAT and negative pathophysiological consequences. Research suggests that VAT accumulation is associated with metabolic complications through the secretion of bioactive substances (Dusserre et al, 2000; Arner, 2001; Giusti et al, 2004) thus suggesting that

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VAT is an important contributor to the underlying inflammatory responses involved in adverse metabolic complications.

2.2.4 Adipokines (Adiponectin) Although it has been established that adipose tissue secretes proinflammatory cytokines, there are several adipokines that have demonstrated anti-inflammatory properties. Adiponectin was first identified over two decades ago (Scherer et al, 1995) as a serum protein hormone secreted from adipose tissue. Adiponectin exists in at least two isoforms within the circulation, low molecular weight (LMW) oligomers and as high molecular weight (HMW) oligomers (Pajvani et al, 2003). The various isoforms of adiponectin activate different signalling pathways, that exert different effects on various tissues, therefore it is important to justify which isoform will be measured in an inflammatory context in relation to exercise. Previous research shows that total adiponectin decreases with an increase in visceral fat (Indulekha et al, 2011), yet HMW adiponectin has been shown to be the most biologically active form when compared with its counterparts (Baumann et al, 2009). Bluher et al (2007) compared total adiponectin to HMW adiponectin as predictors of metabolic variables at both baseline and after an exercise intervention, and concluded that HMW adiponectin was not superior to total adiponectin, thus suggesting that the use of total adiponectin in similar contextual studies does not appear to put the research at a disadvantage. In contrast, Hara et al (2006) discovered that when compared with total adiponectin, the HMW isoform shows better predictive power for the prediction of insulin resistance and metabolic syndrome. Wang et al (2014) found that the HMW isoform showed a 16

stronger association with the severity of coronary atherosclerosis when compared with total adiponectin. The evidence with regards to which adiponectin isoform should be used remains equivocal. Within the present study total adiponectin in serum was measured via ELISA.

This novel adipokine is involved in numerous metabolic and inflammatory functions primarily related to the promotion of insulin sensitivity, endothelial function and the inhibition of inflammatory mediators (Berg and Scherer, 2005), the current study focused on the latter. Ouchi et al (1999) tested the interaction effects between TNF-a and adiponectin in-vitro, and discovered that concentrations of adiponectin dosedependently inhibited TNF-a induced THP-1 adhesion. The authors also demonstrated that adiponectin reduced the expression of adhesion molecules in endothelial cells, and elicited anti-inflammatory properties by decreasing proinflammatory cytokine production in macrophages. Salmenniemi et al (2004) suggested that low levels of adiponectin were responsible for endothelial damage, and a chronic low-grade inflammatory state. Past research supports the association between lower than normal circulating adiponectin and type 2 diabetes (Hotta et al, 2000) and dyslipidemia (LaraCastro et al, 2006). It is clear that reduced levels of adiponectin disrupts internal homeostasis of the cell by having direct effects on monocytes/macrophages, leading to a constant proinflammatory state.

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The link between VAT, inflammation and adipokines is complicated and the intricate nature of the underlying mechanisms involved seems to be a grey area within the literature. As discussed previously an increase in the accumulation of VAT leads to increased proinflammatory cytokines such as CRP and TNF-a, and the attenuation of protective adipokines such as adiponectin. TNF-a is interlinked with adiponectin with research suggesting that TNF-a reduces secretion of adiponectin from adipose tissue fragments (Lihn et al, 2003). In vivo studies have shown negative associations between TNF-a and adiponectin. From reviewing the literature it appears that both TNF-a and adiponectin antagonise each other by regulating the expression of one another. Lihn et al (2005) speculated that increased levels of TNF-a in metabolic disorders such as obesity, might be involved with down-regulating adiponectin. Therefore it is postulated that a reduction in VAT will lead to reduced proinflammatory cytokines thus increasing circulating adiponectin.

2.3 Exercise, Inflammation and Visceral Adipose Tissue In order to tackle obesity and more importantly VAT accumulation and chronic lowgrade inflammation, modifiable lifestyle changes must be encouraged. Bays et al (2013) describes the common causes of increased VAT as a positive caloric balance, sedentary lifestyle, genetic predisposition and environmental causes. A sedentary lifestyle leads to a positive caloric balance through lack of physical activity, thus it seems plausible that increasing physical activity might stimulate an increase in VAT loss, which might have concomitant effects on the inflammatory state.

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Physical activity exhibits an anti-inflammatory effect which serves to reduce the secretion of proinflammatory cytokines, and restore the homeostatic balance of the body’s internal environment. Gleeson et al (2011) highlighted three possible mechanisms that are thought to be responsible for the anti-inflammatory effects of exercise: Reduction in VAT, release of IL-6 from contracting skeletal muscle and increased levels of adrenal hormones and catecholamines. Also within animal models, the immunological effects of exercise provides further mechanisms that are involved, such as the phenotypic switching of macrophages within adipocytes, and the inhibition of macrophage and monocyte infiltration into adipose tissue (Kawanishi et al, 2010). For the purpose of the current study, the reduction of VAT will provide the focal point, as visceral adiposity can be considered to be the driver of inflammation. As Walker et al (2014) suggested, what remains to be understood is how we can control the key features of adipose tissue depots to reduce the development of metabolic dysfunctions. One way of exploring this area would be to prescribe structured physical activity with the aim of reducing VAT.

2.3.1 Exercise as a Means to Reduce Visceral Adipose Tissue/Inflammation A negative energy balance is needed to reduce weight and total fat mass, which can be achieved through dieting alone or in combination with exercise. However exercise alone has been shown to significantly decrease VAT even without changes in body mass (Lee et al, 2005). A possible explanation for the decrease in VAT is that exercise might provide the stimulus that increases sympathetic activity, thereby stimulating

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lipolysis which would have concomitant effects on reducing fat mass (Mourier et al, 1997).

It is evident in the literature that obese individuals are more prone to weight loss when compared with their lean counterparts. This is consistently reflected in previous research by the relationship between fat loss and initial fat mass using behavioural therapy (Teixeira et al, 2004), bariatric surgery (Valera-Mora et al, 2005) and exercise without caloric restriction (Trapp et al, 2008). Although the sample used in the current study consisted of a heterogenous group and not exclusively obese individuals, the concept of VAT loss is still crucial for reducing the risk of mortality even in lean individuals. It has been demonstrated that lean individuals with a higher proportion of VAT are at a higher risk of negative health outcomes, when compared with their obese counterparts carrying a lower proportion of VAT (Ruderman et al, 1981).

Chaston and Dixon (2008) reviewed VAT reduction through exercise and found that loss of VAT was associated with modest weight loss. This finding is inconsistent with other studies in that significant VAT reduction was present without changes in body mass (Ross et al, 2000; Ross et al, 2004; Giannopoulou et al, 2005; Keating et al, 2015). Although the evidence seems to be conflicting, from reviewing the literature it is apparent that significant reductions in VAT can occur with negligible changes in weight loss. The mechanisms responsible for this physiological anomaly are unclear and therefore warrant further investigation.

20

Ismail et al (2012) completed a meta-analysis with a number of randomised control trials on the effects of aerobic exercise on VAT in adults and found a significant pooled effect size using 29 studies. Even though the majority of studies used overweight cohorts (which were predominantly female), the meta-analysis revealed that aerobic exercise can be an effective method for reducing VAT. Although previous research suggests that a dose-response relationship exists between volume of exercise and VAT loss (Ohkawara et al, 2007), Ismail et al (2012) failed to find a relationship between weekly exercise volume and the reduction of VAT. It has been postulated that a greater amount of energy expenditure results in greater weight loss, yet VAT has been shown to be significantly reduced in the absence of weight loss (Ross et al, 2004; Slentz et al, 2005; Johnson et al, 2009). Therefore it seems that the volume of exercise does not necessarily influence the amount of VAT loss, which contrasts with the concept that high volumes of exercise are more beneficial for decreasing risk of adverse health conditions when compared with low-volume exercise by means of increased energy expenditure.

However the intensity of exercise has been shown to effect reductions in VAT with higher intensities resulting in more favourable VAT loss (Slentz et al, 2005; Irving et al, 2008; Coker et al, 2009; Zhang et al, 2015). In a recent meta-analysis examining the effects of exercise on VAT in overweight adults, Vissers et al (2013) discovered that there seems to be a threshold for intensity in order to have an effect on VAT reduction. Studies using moderate intensities (45-55% VO2peak) revealed a significant effect on VAT loss (Hedge’s g=-0.473, 95% CI: -0.140 to -0.806, P=0.005) whereas 21

higher intensities (>55% VO2peak) resulted in slightly higher effect sizes with increased significance (Hedge’s g=-0.588, 95% CI: -0.336 to -0.840, P 2 risk factors) (ACSM, 2014). The target population was a heterogeneous group, therefore making the results applicable to a general population as opposed to a specific set of individuals.

There are two categories of sample design in social science research; probability sampling and non-probability sampling. Probability sampling is classified by its ability to specify the probability at which each sampling unit of the population will be included in the sample. This tends to be the gold standard within research as only probability sampling can be used in representative sampling designs. When using non-probability sampling there is no way of specifying the probability of each unit’s inclusion in the sample. In other words non-probability samples are not fully representative of the sampling population. Due to convenience and time constraints, non-probability sampling was used for the current study. This sampling design seemed to outweigh the advantages of using a probability sampling design, due to the study being a small scale University research project. This presented itself as one limitation to the current study in that randomisation was not present, which had an effect on the internal validity of the study design as previously mentioned.

36

In terms of sample size due to the sample design, a prospective power analysis was not completed. The aim was to recruit enough individuals to produce the necessary statistical power for identifying significant changes within the dependent variables, and to provide a meaningful effect and error variance (Atkinson and Nevill, 2001). This was informed by previous literature with similar study aims and objectives (Keating et al, 2014).

3.4.2 Recruitment The various methods of recruitment that were used included electronic bulletins, University noticeboards, word of mouth and email (Appendix F). The sample included students and staff from Leeds Beckett University and members of the public.

3.4.3 Participants A total of 29 participants expressed an interest in taking part in the study through email replies. 29 eligible participants were invited to the laboratory to complete ACSM screening procedures. Two participants were excluded from the study due to risk stratification, having over two cardiovascular risk factors. 12 participants completed a cross-sectional part of a wider study whereas 15 participants began the interventional study. One participant dropped out due to time/availability issues therefore resulting in 14 participants completing the six week intervention. Due to mechanical breakdown of the DXA scanner and therefore missing data values, only

37

six participants data were included in the data analysis. Figure 1 shows a flowchart of the recruitment process. Responded to advertisement: n=29

Cross-sectional study: n=12

Responders potentially

Excluded from

eligible and screened:

study due to >2

n=29

risk factors: n=2

HIIT n=15 Dropped out: n=1 (time/availability) Final completers: n=14 Excluded: n=8 (missing data)

Figure 1. Flowchart of recruitment process

3.5 Data Collection 3.5.1 Preliminary screening Initially all participants visited the laboratory to complete preliminary screening based on ACSM guidelines. The participants were asked to complete a 12 hour fast prior to their first visit. If the participants satisfied the low risk criteria during the screening 38

process, visceral adiposity was quantified using DXA (Section 2.5.4.3) and venous blood samples were taken through phlebotomy (Section 2.5.4.4). Low-risk participants underwent a maximal exercise test to establish the appropriate load for the training programme (Section 2.5.4.2).

During the visit, a 30 minute consultation was completed, verbally informing the participants about the nature of the study including the aims and objectives. All participants were provided with an information sheet that detailed the procedures of the study. Written informed consent was provided by each participant in accordance with Leeds Beckett University’s ethical procedures.

Participants were screened in accordance with the ACSM pre-participation screening guidelines (American College of Sports Medicine, 2014). This included their medical history and an assessment of cardiovascular risk factors (See Appendix D). The screening was used to identify individuals with medical contraindications that would exclude them from taking part in supervised exercise. Individuals at high risk with two or more cardiovascular risk factors were excluded from the study. Stature was measured to the nearest 0.1 cm by stadiometer (Seca, Birmingham, UK), body mass was measured using a digital electronic scale (Tanita, 330ST, Netherlands) with the initial weight pre-set at -0.5 kg to account for light clothing. Resting blood pressure was assessed in duplicate and recorded using an electronic sphygmomanometer (Accoson, Greenlight 300, England), with participants seated in

39

a relaxed position. Resting heart rate was measured using a radio telemetry heart rate monitor (Polar, FS1, Finland), which was placed just below the pectoral muscles and just above the xiphisternal joint on the sternum. The participants had been resting in a supine position for 5 minutes prior to measurements being taken to ensure a true resting value. A resting Electrocardiogram (ECG) was also recorded and assessed as part of the pre-participation screening. The ECG was assessed by a competent exercise physiologist, with borderline cases referred to a cardiologist.

3.5.2 Maximal Exercise Test Participants that satisfied the inclusion criteria were invited back to the laboratory to undergo a maximal exercise test to volitional exhaustion using a RAMP protocol on an electromagnetically braked cycle ergometer (Lode, Corival, Netherlands). Each participant completed a submaximal familiarisation ride for 12 minutes prior to the maximal exercise test, to allow habituation to the laboratory equipment and procedures employed within the study. The online gas analysis system was connected to the cycle ergometer thus a pre-programmed RAMP protocol (Wasserman et al, 2011) with an individualised slope for each participant was calculated and applied by the researcher. The Wasserman equation was used to calculate the progressive load increment using anthropometric measurements on a Microsoft Excel spreadsheet (Appendix G).

40

Expired respiratory gases were collected continuously via an online gas analysis system (Metalyser, Cortex 3B, Germany). The digital tripleV volume transducer was calibrated using a 3-litre syringe (Hans Rudolph Inc, USA). The gas analysers were calibrated using room air, and a mass standard gas mixture (Alpha Gravimetric standard, BOC gases, Guildford, UK) of oxygen and carbon dioxide in nitrogen equivalent to expired air (15% O2 and 5% CO2).

The World Health Organisation’s guidelines (World Health Organisation, 1971) specify that the following supplementary criteria should be coincided with a plateau in VO2 for a valid approximation of an individual’s ‘true’ VO2peak: 1) Heart rate within 10 beats.min-1 of Astrands’ ‘age related maximum’ (220-age) 2) Lactate blood > 8 mmol.litre-1 3) Respiratory exchange ratio (RER) > 1.15 The criteria have been heavily criticised due to the variance of the attainable values between subjects and across exercise modes and protocols (Duncan et al, 1997). Poole et al (2008) highlighted that the proposed criteria were surpassed prior to attainment of VO2peak and exercise intolerance, therefore suggesting a fundamental flaw with the use of such measurements in the recognition of VO2peak. However, no suitable alternative methods have been evidenced in the literature, therefore peak VO2 values were ascertained using the above criteria (with the exception of blood lactate values

41

due to the absence of such measurements). VO2peak was calculated as the highest 30 second average of VO2 observed in the last two minutes of the exercise test. Blood pressure was monitored throughout the test at two minute intervals, whereas heart rate was monitored continuously to ensure participant safety.

Each participant completed a two minute active cool-down at 25 W followed by a passive cool-down and observation for a further three minutes. This recovery period aimed to minimise the precipitous fall in blood pressure, often experienced with the abrupt decrease in venous return due to lower extremity vasodilatation, that may occur when vigorous exercise is terminated (Wasserman et al, 2011).

3.5.3 Visceral Adipose Tissue Assessment Dual-energy X-ray absorptiometry (DXA) is an advanced, cost-effective method for measuring body composition (Lohman and Zhao, 2005). DXA measures the attenuation of two energies emitted from the modality to distinguish fat, lean and bone mineral content measures, however it is important to note that the quantification of VAT is still only an estimation as it cannot distinguish between subcutaneous and visceral adiposity. Previous research highlights the usefulness of such technology for identifying VAT, with studies validating its use with the gold standard CT in a healthy mixed gender population (Kaul et al, 2012), therefore the use of DXA seemed appropriate for the given research study. Although DXA has been validated against

42

gold standard techniques, Rothney et al (2013) makes the point that due to the visceral region being relatively small, the mathematical algorithms to distinguish between visceral adiposity and subcutaneous adiposity might lead to greater precision error. Mellis et al (2014) dichotomised a heterogeneous group of mixed gender individuals based on BMI (16.7-24.9 kg.m-2, 25.5-42.4 kg.m-2) and calculated precision error between two measurements and the percentage of coefficient of variability (%CV). Although the majority of the sample were female, the results indicated that the CoreScan software for iDXA provided good precision for VAT measurements for obese individuals. The authors concluded that the %CV value for precision should be interpreted with caution for subjects with a normal BMI, thus in the current study careful considerations will be made with regards to the %CV. Shuster et al (2012) summarised the different methods for measuring visceral adiposity and concluded that even though DXA provides an estimation of visceral adiposity, the reproducibility in terms of %CV varies between < 1% to 4% (Stewart et al, 2003; Lane et al, 2005; Bosy-Westphal et al, 2008) which are acceptable limits for the current research.

Past research confirms that the radiation dose to individuals from DXA scans is relatively low when compared with other radiological investigations involving ionising radiation (Huda and Morin, 1996). The International Commission of Radiological Protection (1991) defines the effective dose as the sum of absorbed doses to each irradiated organ weighted for the radiation type, and the radio sensitivity of that organ. Albanese et al (2003) reviewed the use of DXA for body composition 43

and concluded that the radiation exposure from whole body DXA is low when compared with the annual dose equivalent from natural background radiation. Also due to the available equipment, the DXA scanner at Leeds Beckett University uses a fan beam as opposed to a pencil beam. The advantage of this technique is the improved scanning time of 3-4 minutes and a higher quality image. All DXA scans completed at the University were in accordance with the Standard Operating Procedures under Ionising Radiation (Medical Exposure) Regulations 2000 IR(ME)R.

The same technician calibrated the equipment at baseline and at the end of the experimental period. All participants wore a standard hospital gown during the DXA scan. Participants were asked to remove any metal piercings prior to the scan to ensure accuracy of the measurement. Regional fat distributions were measured on a fan-beam GE Lunar iDXA using standard (153mm/sec) or thick (80mm/sec) mode depending on body stature. CoreScan software provided quantifications of VAT. The technician followed the DXA manual operating procedures to ensure the correct positioning of the participant, thus reducing error and maintaining participant safety.

3.5.4 Blood Sampling and Analysis Venous blood samples (17 ml) were obtained after an overnight fast (12 hours) by a trained individual. The participant adopted a seated position for five minutes prior to the sample being taken via venipuncture from an antecubital vein. After selection of the most prominent vein, a sterilised pre-injection swab was used to cleanse the

44

surrounding area of skin and a tourniquet was placed around the arm to increase pressure. A butterfly needle 0.80mm x 19mm x 305mm (BD Vacutainer Systems, Preanalytical Solutions, UK) was then inserted inside the selected vein. The holder was stabilised, and then in succession two Gold 8.5ml (16 x 100mm) BD SST II Vacutainers (BD Vacutainer Systems, Preanalytical Solutions, UK) were attached to the holder until each was full. Standard procedures were followed and minimal stasis was ensured by removing the tourniquet at the appropriate time.

The whole blood sample was left to coagulate for 30 minutes at room temperature immediately after the sample was taken. The tubes were then centrifuged (< 5˚C) at 3000 rpm for 15 minutes and the serum removed, aliquoted, and stored at -80˚C for subsequent analysis.

Analysis was performed at the end of the six week intervention by trained individuals. Commercially available enzyme linked immunosorbent assay kits (ELISA) were used to measure high-sensitivity C-reactive protein (hsCRP), tumour necrosis factor alpha (TNF-a) and total adiponectin according to manufacturer’s specifications (Quantikine; R & D systems, Abingdon, UK). The intra-assay % coefficient of variation (%CV) of samples was: hsCRP=4.7%, TNF-a=5.9% and total adiponectin=3.2%. The interassay %CV of samples was: hsCRP=6.2%, TNF-a=13.1% and total adiponectin=9.3%.

45

3.5.5 High Intensity Interval Training Group The work rate for each participant was calculated from their maximal exercise test using an individualised linear regression equation. Past research uses maximal/ supramaximal intensities for HIIT, yet this can be challenging for sedentary individuals that are just starting to become active. Little et al (2010) developed a more appropriate low-volume model of HIIT which differed from previous protocols in that the intensity was not ‘all out’. Interventional studies have demonstrated that lowvolume models of HIIT have elicited similar favourable physiological adaptations when compared with endurance type training (Burgomaster et al, 2008; Babraj et al, 2009). Considering the minimal time commitment associated with HIIT and the reduced volume compared with more traditional types of training, past research highlights the potent capability of HIIT to induce skeletal muscle adaptations and aerobic exercise capacity.

Six male and eight female participants (n=14) underwent a low-volume HIIT protocol consisting of five 30 second intervals at 92.5% VO2peak interspersed with 30 seconds active recovery at 50 W. Overload was applied with the addition of one extra interval per week to a total of 10 intervals by week six (Table 1). The participants completed a standardised warm-up for four minutes at 60 W, and a standardised cool-down for four minutes at 50 W. The total training time (including warm-up and cool-down) per week per session started at 13 minutes in week one progressing to 18 minutes in week six. This reduced time commitment is significantly lower than the World Health

46

Organisation national guidelines of 150 minutes of moderate intensity exercise or 75 minutes of vigorous intensity exercise per week (World Health Organisation, 2010). This low-volume model of HIIT will challenge the concept of how much aerobic exercise is necessary to induce the physiological benefits, in terms of lowering systemic inflammation and decreasing visceral adiposity. Table 1: Description of exercise intervention. Week Frequency

Intensity

Session duration W:R no. of intervals (seconds)

Total weekly training time (excluding warm up and cool down, min)

1

3

92.5% VO2peak : 50 W

30 : 30

5

15

2

3

92.5% VO2peak : 50 W

30 : 30

6

18

3

3

92.5% VO2peak : 50 W

30 : 30

7

21

4

3

92.5% VO2peak : 50 W

30 : 30

8

24

5

3

92.5% VO2peak : 50 W

30 : 30

9

27

6

3

92.5% VO2peak : 50 W

30 : 30

10

30

Abbreviations: W=Watts; VO2peak =Peak oxygen uptake; W:R=Work to rest period.

The HIIT group completed their training on a cycle ergometer (Monark, 894E, Sweden) three times per week for six weeks. The training was completed on Mondays, Wednesdays and Fridays. The exercise training sessions were supervised by the researcher(s).

47

3.6 Data analysis Conventional statistical software was used to analyse the data (IBM SPSS Statistics for Windows, version 22, Chicago, IL, USA). Data normality was assessed for the differences between the pre-test and post-test values using a Shapiro-Wilk test (Ghasemi and Zahediasl, 2012). Where parameters were not normally distributed the data were log transformed. Transforming non-normal data increases the validity of the associated statistical analyses, yet the author must be cautious when interpreting the outcome (Feng et al, 2014). Due to the small sample size and the fact that Cohen’s d often overestimates the magnitude of the effect when using data from a dependent ttest, a modified formula has been used to calculate the effect size (Dunlap et al, 1996, cited in Dunst et al, 2004, pp. 5-6). hsCRP, adiponectin and visceral fat were analysed using dependent t-tests to determine if significant differences existed prior to and post six weeks of training. TNF-a values were omitted due to a lack of sensitivity of the biochemical assay, resulting in some values being undetectable. All data are reported as Mean ± SD (standard deviation) except for hsCRP which has been reported as a geometric mean with 95% confidence intervals. An arbitrary level of 5% statistical significance was used throughout (two-tailed).

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Chapter 4: Results 4.1 Baseline characteristics 14 participants successfully finished the study. Due to missing data values, six participants data are presented in Table 2 and used in the statistical analysis.

Table 2: Baseline characteristics of the participants. High Intensity Interval Training n= 6 Gender

2 male, 4 female

Age (years)

41.3 ± 9.5

Stature (cm)

170.9 ± 10

Body Mass (kg)

72.42 ± 13.7

BMI (kg.m2)☨

21.15 ± 3.47

Abbreviations: BMI=Body Mass Index. Note: All variables presented as mean ± SD. ☨

Calculated as weight in kilograms divided by height in meters squared.

Visceral fat mass and total adiponectin were normally distributed (both P>0.05). However, hsCRP was not normally distributed (P 10 mg.L whereas all other values were < 3 mg.L. Although this anomaly was considered as an outlier it would be irrational to exclude the participant from the data set thereby reducing the sample size even more.

The findings from the current study disagree with similar research (Campbell et al, 2008; Church et al, 2010; Hovanloo et al, 2013) in that exercise fails to attenuate CRP. Hovanloo et al (2013) found non-significant differences in pre and post CRP values after a two week exercise intervention in healthy adults although there was a slight trend towards a decrease in CRP. Two weeks is probably not long enough to induce beneficial reductions in inflammation as evidenced by Zwetsloot et al (2014). Beavers et al (2010) speculated that in order to find meaningful differences in inflammatory markers following an exercise intervention participants usually had elevated baseline values, yet Campbell et al (2008) and Church et al (2010) used sedentary participants with elevated baseline CRP values and failed to find significant differences. Methodological heterogeneity in terms of exercise intensity and volume might partly explain the discrepancy in the data.

Due to the fact that the data for CRP was log transformed thereby adding an arbitrary constant to each value, this attempt at reducing the skewness and normalising the distribution might have had misleading implications for the current results. Feng et al (2014) used simulated data to highlight the effect of adding a positive constant in order for log transformation to be effective and concluded that the P-value of the test depends on what value is added to the data before applying a log transformation. 60

Admittedly this point was overlooked by the author in the current study therefore making inferences from the CRP data must be done cautiously.

Limitations of the current study include but are not limited to the research design whereby factors relating to internal and external validity have been compromised (See methodology section). Due to the established sexual dimorphism with regards to the dependent variables and the fact that the sample consisted of predominantly female participants, the generalisation of the results are limited. The small sample size would have a considerable impact on the results of the study leading to increased sampling error and reduced statistical power whereby a larger sample would provide better approximations of the population. The failure to control/monitor for calorie intake or dietary composition presents itself as a limitation in that the amount of weight loss and subsequent visceral fat loss can be affected by diet (Boutcher and Dunn, 2009) thereby having a knock-on effect on adiponectin and inflammation as weight loss affects both of these.

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Chapter 6: Conclusions

In summary, the results of this study suggest that a six week low-volume HIIT protocol induces negligible effects on visceral fat mass and adiponectin. Furthermore, inflammation through systemic concentrations of CRP were significantly reduced therefore providing evidence that short term HIIT has beneficial effects on inflammation yet it is important to note that due to the statistical procedures utilised, the results should be interpreted with caution. Taken together, the findings from the current study provides a starting point and a platform for future research investigating the effects of low-volume HIIT on visceral adiposity, adiponectin and inflammation. Future research utilising low-volume HIIT protocols should investigate the differences between MICT and HIIT in terms of alterations in visceral adiposity, inflammatory biomarkers and adiponectin.

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reversal of comorbidities in malabsorptive bariatric surgery. American Journal of Clinical Nutrition. 81 (6), pp. 1292-1297. Vissers, D., Hens, W., Taeymans, J., Baeyens, JP., Poortmans, J. and Gaal, L.V. (2013) The Effect of Exercise on Visceral Adipose Tissue in Overweight Adults: A Systematic Review and Meta-Analysis. PLoS One. 8 (2), pp. e56415. Vu,V., Riddell, M.C. and Sweeney, G. (2007) Circulating adiponectin and adiponectin receptor expression in skeletal muscle: Effects of Exercise. Diabetes/Metabolism Research and Reviews. 23 (8), pp. 600-611. Walker, G.E., Marzullo, P., Ricotti, R., Bona, G. and Prodam, F. (2014) The pathophysiology of abdominal adipose tissue depots in health and disease. Hormone Molecular Biology and Clinical Investigation. 19 (1), pp. 57-74. Wang, Y., Zheng, A., Yan, Y., Song, F., Kong, Q., Qin, S. and Zhang, D. (2014) Association between HMW adiponectin, HMW-total adiponectin ratio and early-onset coronary artery disease in Chinese population. Atherosclerosis. 235 (2), pp. 392-397. Wasserman, K., Hansen, J.E., Sue, D.Y., Stringer, W.W., Sietsema, K.E., Sun, XG. and Whipp, B.J. (2011) Principles of Exercise Testing and Interpretation including Pathophysiology and Clinical Applications. 5th Ed. Philadelphia: Lippincott Williams & Wilkins. Weisberg, S.P., McCann, D., Desai, M., Rosenbaum, M., Leibel, R.L. and Ferrante, A.W. (2003) Obesity is associated with macrophage accumulation in adipose tissue. Journal of Clinical Investigation. 112 (12), pp. 1796-1808.

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Weston, M., Taylor, K.L., Batterham, A.M. and Hopkins, W.G. (2014) Effects of LowVolume High-Intensity Interval Training (HIT) on Fitness in Adults: A Meta-Analysis of Controlled and Non-Controlled Trials. Sports Medicine. 44, pp. 1005-1017. Weyer, C., Funahashi, T., Tanaka, S., Hotta, K., Matsuzawa, Y., Pratley, R.E. and Tataranni, P.A. (2001) Hypoadiponectinemia in obesity and type 2 diabetes: close association with insluin resistance and hyperinsulinemia. Journal of Clinical Endocrinology and Metabolism. 86 (5), pp. 1930-1935. Whitehead, J.P., Richards, A.A., Hickman, I.J., Macdonald, G.A. and Prins, J.B. (2006) Adiponectin - a key adipokine in the metabolic syndrome. Diabetes, Obesity and Metabolism. 8, pp. 264-280. Wilson, P.W., D’Agostino, R.B., Sullivan, L., Parise, H. and Kannel, W.B. (2002) Overweight and obesity as determinants of cardiovascular risk: the Framingham experience. Archives of Internal Medicine. 162 (16), pp. 1867-1872. Wisløff, U., Støylen, A., Loennechen, J.P., Bruvold, M., Rognmo, Ø., Haram, P.M., Tjønna, A.E., Helgerud, J., Slørdahl, S.A., Lee, S.J., Videm, V., Bye, A., Smith, G.L., Najjar, S.M., Ellingsen, Ø. and Skjaerpe, T. (2007) Superior cardiovascular effect of aerobic interval training versus moderate continuous training in heart failure patients: a randomized study. Circulation. 115 (24), pp. 3086-3094. World Health Organisation. (1971) Fundamentals of exercise testing. Geneva: WHO Press.

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World Health Organisation. (2010) Global Recommendations on Physical Activity for Health. [Online]. Geneva: WHO Press. Available from: [Accessed 29th June 2015]. World Health Organisation. (2014) 10 facts on obesity. [Online]. Geneva: WHO Press. Available from: [Accessed 26th June 2015]. World Health Organisation. (2015) Obesity and overweight: Fact sheet No311. [Online]. Geneva: WHO Press. Available from: [Accessed 18th June 2015]. World Medical Association. (2008) Declaration of Helsinki-ethical principles for medical research involving human subjects. World medical association Inc. Xu, H., Barnes, G.T., Yang, Q., Tan, G., Yang, D., Chou, C.J., Sole, J., Nichols, A., Ross, J.S., Tartaglia, L.A. and Chen, H. (2003) Chronic inflammation in fat plays a crucial role in the development of obesity-related insulin resistance. Journal of Clinical Investigation. 112 (12), pp. 1821-1830. Yang, WS., Lee, WJ., Funahashi, T., Tanaka, S., Matsuzawa, Y., Chao, CL., Chen, CL., Tai, TY. and Chuang, LM. (2001) Wright Reduction Increases Plasma Levels of an Adipose-Derived Anti-Inflammatory Protein, Adiponectin. Journal of Clinical Endocrinology and Metabolism. 86 (8), pp. 3815-3819. Yin, WH., Chen, JW., Jen, HL. and Lin, S.J. (2004) Independent prognostic value of elevated high-sensitivity C-reactive protein in chronic heart failure. American Heart Journal. 147 (5), pp. 931-938. 87

Zhang, H., Tong, T.K., Qiu, W., Wang, J., Nie, J. and He, Y. (2015) Effect of HighIntensity Interval Training Protocol on Abdominal Fat Reduction in Overweight Chinese Women: A Randomized Controlled Trial. Kinesiology. 47, pp. 57-66. Zwetsloot, K.A., John, C.S., Lawrence, M.M., Battista, R.A. and Shanely, R.A. (2014) High-intensity interval training induces a modest systemic inflammatory response in active, young men. Journal of Inflammation Research. 7, pp. 9-17.

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Appendices Appendix A: LITERATURE REVIEW OF EXPERIMENTAL STUDIES EXAMINING THE EFFECTS OF EXERCISE ON INFLAMMATION/BODY COMPOSITION

Study

Boudou et al, 2003

Participa Study Sampl nt design e size character (n) istics

Intensity/ duration of exercise

Body Inflammat compositi ory on measurem measurem ents ents

Conclusions

16 middle aged adults with diabetes

EXE: 2x continuous exercise at 75% V02peak for 45min and 1x intermittent at 85% V02peak

Body mass(kg) EXE # 2.2% CON # 1.8%

Adiponect in (µg.mL) EXE # 4.8% CON # 3.4%

An eight week intensive training program inducing a marked reduction in abdominal fat and increase in insulin sensitivity does not affect adiponectin and leptin levels in men with type 2 diabetes

EXE: continuous exercise at LT for 60min

Body Adiponect mass (kg) in EXE # (µg.mL) EXE # 17.7%

Exercise training induced increase in insulin sensitivity is not dependent on the increase in adiponectine mia

Bike 3d.wk for 8 weeks

CON (8) EXE (8)

♂

Yatagai et al, 2003

12 Bike sedentary adults 5d.wk for 6 ♂ weeks

EXE (12)

89

Visceral fat (MRI cm2) EXE # 45.1% CON # 4.1%

Body Slentz et 175 Tread CON HVHI: mass (kg) al, 2005 sedentary millsB (47) 65-80% overweig ikes HVHI V02peak CON # ht adults Ellipti (42) (Equivalent 1% with mild cal LVHI to jogging HVHI # to trainer (46) 20miles/ 2.6% moderate s LVMI wk) LVHI # dyslipide (40) 0.8% mia 32 LVHI: weeks LVMI # 65-80% ♀/♂ 0.7% V02peak (Equivalent to jogging 12miles/ wk) LVMI: 40-55% V02peak (Equivalent to walking 12miles/ wk) Campbel 202 Tread l et al, sedentary mill 2008 middle aged 6d.wk adults for 1 year ♀/♂

CON (102) EXE (100)

EXE: 60-85% HRM for 60min

N/A

Visceral fat (CT) CON # 8.6% HVHI # 6.9% LVHI # 2.5% LVMI # 1.7% Body mass (kg) CON EXE

CRP (mg.L) EXE Men: # 5.7% Women: # 10.1% CON Men:# 12.9% Women: #

90

A modest exercise program, consistent with ACSM exercise guidelines, prevented significant increases in visceral fat. A modest increase over the ACSM exercise guidelines resulted in significant decreases in visceral fat without changes in caloric intake A 12-month moderate to vigorous aerobic exercise intervention did not affect CRP levels in previously sedentary men or women with average risk CRP values at baseline

Irving et al, 2008

27 middle aged obese adults with metaboli c syndrom e

Body CON Low: >LT, (7) 300-400kca mass (kg) LOW l (EE) CON # 5d.wk (11) 1% for 16 HIGH High: LTLOW # weeks (9) V02peak, 2.2% 300-400kca HIGH # l (EE) 3.7% Tread mill

AVF(cm2 ) CON # 1.3% LOW # 4.6% HIGH # 14.5%

♀

Trapp et al, 2008

45 healthy adults ♀

N/A

Body composition changes are affected by exercise intensity with high intensity exercise training more effective at reducing total abdominal fat, subcutaneou s abdominal fat, and abdominal visceral fat

Body Adiponect CON HIIT: High mass (kg) in (?) >0.5kg intensity (µg.mL) 3d.wk HIIT resistance interval CON # for 15 (?) 60 x 8s training three 2.1% CON # weeks SS (?) sprints with times per 11.9% HIIT # 12s week for 15 2.4% HIIT # recovery weeks 1.5% SS # 0.2% compared to SS # SS: the same Central 27.7% continuous frequency of exercise at abdomina steady state l fat 60% exercise was V02peak for HIIT led associated to a with 20-40min significan significant t decrease reductions in in central total body abdomina fat, l fat subcutaneou (-9.5%) s leg and whereas trunk fat, and there insulin were resistance minor increases in SSE (+10.5%) and CON Bike

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Coker et 18 Bike CON MI: al, 2009 overweig (6) continuous ht elderly 4-5d. MI (6) exercise at adults wk for HI (6) 50% 12 V02peak ♀/♂ weeks (1000kcal/ wk)

Visceral fat (CT cm2) CON ? MI ? HI: ∆ of −39 ± 11 cm2

HI: continuous exercise at 75% V02peak (1000kcal/ wk) Body mass (kg) CON # EXE #

Johnson 19 Bike et al, sedentary 2009 obese 3d.wk adults for 4 weeks ♀/♂

CON (7) EXE (12)

Church et al, 2010

CON (82) EXE (80)

Body EXE: mass (kg) Continuous CON # exercise EXE # between 60-80% Visceral V02peak to fat (CT) expend CON # 16Kcal/wk EXE #

EXE (25) DEX (25) DIO (29)

Body Adiponect EXE: EE of Aerobic mass (kg) in 500-600kca exercise for l per 12 weeks EXE # EXE # session for was found to 3.5% 5.4% 60-75min have no DEX # DEX # effects on 11.6% 17.9% circulating DIO # DIO # inflammator 11.4% 20.3% y markers in an obese cohort

162 sedentary adults with elevated CRP ♀/♂

Christia nsen et al, 2010

Bike and tread mill 3-5d. wk for 16 weeks

79 obese adults

Aerob ic

♀/♂

3d.wk for 12 weeks

CON: Stretching

Adiponect The direct in comparison (ng.mL) of exercise CON ? intensity MI ∆ of without +1.6 ± 2.2 weight loss ng/mL promotes the efficacy of HI: ∆ of + high 2.5 ± 1.5 intensity ng.mL exercise in the reduction of visceral fat, even without changes in adiponectin

EXE: continuous cycling at 50-70% VO2peak for 30-45 min

92

Average VAT (MRI cm3) CON # 1% EXE # 11.6%

N/A

CRP (mg.L) CON # EXE #

Regular aerobic exercise reduces hepatic and visceral lipids in obesity

Exercise without weight loss in not associated with a reduction in CRP

Heydari 46 Bike et al, sedentary 2012 overweig 3d.wk ht young for 12 adults weeks

CON (21) HIIT (25)

♂

Leggate et al, 2012

12 obese adults ♂

HIIT: 8sec sprints at 80-90% HRM with 12sec recovery

Body mass (kg) CON # HIIT # 1.7%

N/A

Visceral fat (CT g) CON # 3.4% HIIT # 17.3%

Bike 3d.wk for 2 weeks

HIIT (12)

HIIT: 10 x 4min at 85% V02peak

Body Adiponect mass (kg) in (µg.mL) HIIT # 0.3% HIIT # 10.7% TNF-a (pg/ml) HIIT #

Hovanlo o et al, 2013 


16 active students ♀/♂

Bike 3d.wk for 2 weeks

CET (8) SIT (8)

CET: 90-120min at 65% V02peak SIT: 4-6 30s wingates with 4min recovery

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N/A

CRP (ng.mL) CET # 27.8% SIT # 8.5%

12 weeks of HIIT resulted in significant reductions in total, abdominal, trunk, and visceral fat and significant increases in fat free mass and aerobic power Two weeks of high intensity interval training induces beneficial alterations in the resting inflammator y profile and adipose tissue proteome of an obese cohort

Both forms of exercise induced similar effects on inflammator y markers. There were no significant improvement s in inflammator y markers

Keating et al, 2014

33 inactive overweig ht adults ♀/♂

Zwetslo ot et al, 2014

8 active adults ♂

Body hsCRP(m CON HIIT: 4-6 x mass (kg) g/L) (11) 30s at 3d.wk HIIT 120% HIIT # MICT # for 12 (11) V02peak, 0.3% 27.5% weeks MICT 180s MICT # HIIT # (11) recovery at 1% 5.9% 30W %android MICT: fat (DXA) continuous exercise at HIIT # 50-65% MICT # V02peak for 2.4% 30-45min Bike

Bike 3d.wk for 2 weeks

HIIT (8)

HIIT: 8-12 x 60s at 100% V02peak with 75s at 50W recovery

94

TNF-a (pg.mL) N/A N/A

High intensity interval training might be advocated eliciting comparable fitness benefits to traditional continuous exercise in inactive, overweight adults High intensity interval training induces a small inflammator y response; however two weeks of HIIT does not alter this response

Keating et al, 2015

48 Bike CON overweig (12) ht 3-4d. HILV inactive wk for (12) adults 8 LIHV weeks (12) ♀/♂ LILV (12)

HILV: 60-70% VO2peak continuous cycling 2d.wk + brisk walking at same intensity 1d.wk LIHV: 50% VO2peak continuous cycling 3d.wk + brisk walking at same intensity 1d.wk LILV: 50% VO2peak continuous cycling 2d.wk + brisk walking at same intensity 1d.wk

95

Body mass (kg) CON # HILV # 1.3% LIHV # 1.5% LILV # VAT (MRI, cm3) CON # 3.3% HiLo # 7.2% LIHV # 11% LILV # 6.7%

hsCRP (mg.L) CON # 2.1% HILV # 5.5% LIHV # 1.8% LILV # 19.4 %

All of the aerobic exercise regimens employed educed liver fat and VAT by a small amount without clinically significant weight loss

Zhang et al, 2015

35 obese adults ♀

Body CON MICT: (11) Continuous mass (kg) MICT exercise at CON # 4d.wk (12) 60-70% MICT # for 12 HIIT HRM 6.9% weeks (12) HIIT # HIIT: 4 x 7.8% 4min at 85-95%HR Visceral M with fat (CT3min cm2) recovery at 50-60% CON # HRM 4.2% MICT # (Matched 7.9% oxygen HIIT # costs of 18.2% HIIT to MICT) Tread mill

96

N/A

12 week of high intensity interval training and moderate intensity continuous training with equivalent oxygen cost resulted in similar whole body fat loss. HIIT appears to be more effective than MICT for controlling abdominal visceral and subcutaneou s fat

Appendix B: FACULTY RESEARCH ETHICS COMMITTEE APPROVAL



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Appendix C: PARTICIPANT INFORMATION SHEET

! Information for Participants Title of the study: Heart rate variability and other cardio-metabolic and respiratory variables at rest and in response to high intensity interval training (HIIT). Introduction We are inviting you to take part in a research study. Before you decide whether you would like to take part, it is important for you to understand why the research is being done and what it will involve. Please take the time to read the following information carefully and discuss it with friends and/or relatives if you wish. Ask us if there is anything that is not clear, or if you would like more information (contact numbers and addresses are at the end of this information sheet). Please take your time to decide whether or not you wish to take part. Background to and purpose of the study HIIT is a modern exercise training approach that is made up of a short bout of exercise at a high intensity, followed by a short rest period, which is then repeated a number of times during the exercise session. The purpose of this research is to add to our knowledge of heart rate, blood sugar and respiratory activity at rest, and in response to interval training. HIIT has been shown to improve blood pressure and fitness to name a few. Due to the short amount of time required for the exercise, interval training could promote physical activity in individuals who typically struggle to find the time to meet the recommended guidelines of 150 minutes of moderate exercise or 75 minutes of vigorous physical activity per week. Am I a suitable participant for the study? We are recruiting men and women over 18 years old. This study is in two parts - anyone can participate in part A, even if you have been diagnosed with a medical condition. Part B involves a maximal exercise test and the HIIT intervention. Based on your results in part A we will advise if you are eligible for part B. If you are eligible for part B you can decide if you would like to participate or not. If you do not want to participate in training sessions, you will have the option for all tests to be repeated a few weeks later. This will help us with statistical analysis. Do I have to take part? It is your decision whether or not to take part. If you decide to take part, you will be given this information sheet to keep and be asked to sign a consent form. If you decide to take part you are still free to withdraw at any time and without giving reason. If you decide to withdraw from the study before participating in all parts of data collection, your data may be included up to that time point of the study. If you are eligible for part B it remains your decision if you want to continue taking part in the study. What will happen if I take part? The first assessment will be taken over 2 days, which will be carried out in the Fairfax Laboratories. Based on results you may be invited to volunteer for part B. Table 1 outlines what will happen. After looking at this, if you are keen to participate then please read the information on pages 3 and 4.

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Table 1: Overview of the study

Visit

Study

number

Week

Purpose of Visit

Duration of Visit

Pre-testing day 1: PART A Screening and resting ECG 1

0

Blood samples Body composition: DXA, height, weight, waist

1.5 hours

circumference, hip circumference. Resting heart rate variability. Pre-testing day 2: PART B 2

0

Submaximal cycling exercise test

30 minutes

Maximal exercise test 3

1 (Monday)

4

1

•

3 sessions per week

(Wednesday)

•

5 minutes HIIT per session (5 x

Training sessions (Part B):

30seconds intervals with 30 seconds rest)

5

1 (Friday)

6

2 (Monday)

•

3 sessions per week

2

•

6 minutes HIIT per session (6 x

7

30seconds intervals with 30 seconds rest)

(Wednesday) 8

2 (Friday)

9

3 (Monday)

•

3 sessions per week

10

3(Wednesda

•

7 minutes HIIT per session (7 x

11

3 (Friday)

12

4 (Monday)

•

3 sessions per week

4

•

8 minutes HIIT per session (8 x

14

4 (Friday)

15

5 (Monday)

•

3 sessions per week

16

5

•

9 minutes HIIT per session (9 x 30seconds intervals with 30 seconds rest)

(Wednesday) 17

5 (Friday)

18

6 (Monday)

•

3 sessions per week

6

•

10 minutes HIIT per session (10 x

(Wednesday) 20

15 minutes

16 minutes

30seconds intervals with 30 seconds rest)

(Wednesday)

19

14 minutes

30seconds intervals with 30 seconds rest)

y)

13

13 minutes

30seconds intervals with 30 seconds rest)

6 (Friday)

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17 minutes

18 minutes

21

7

Re-testing day 1: PART A Screening and resting ECG Blood samples Body composition: DXA, height, weight, waist

1.5 hours

circumference, hip circumference Resting heart rate variability. 22

7

Submaximal cycling exercise test Maximal exercise test

30 minutes

Screening Before testing and once you have given consent, you will be screened by the researchers by use of a questionnaire. You will be asked to disclose lifestyle information (alcohol, smoking, physical activity – through a physical activity recall questionnaire), diagnosed conditions and medications, plus family history of medical conditions. You will also have your height, weight, waist circumference, hip circumference and blood pressure (BP) measured. In addition a resting ECG will be recorded. Dual energy X-ray absorptiometry (DXA) scans DXA is a gold standard method for assessing body composition (bone, fat and muscle mass). You will receive two DXA scans. Your first scan will be on pre-testing day. A second scan will take place if you complete part B at the end of the 6-week training. For the scans you will be asked to lie on a couch, wearing clothes that do not contain any metal or plastic fastenings, whilst the DXA scanner arm moves over your body (without touching it). The complete procedure will take about 10 minutes. The dose of radiation that you will receive will be small; much less than a standard X-ray. This has been assessed and approved by an external Medical Physics Expert and Clinical Radiation Expert. The information picked up by the scanner is analysed by a computer to provide images and a measurement of your bone and body composition. You will be given a copy of your results to take home with you. All DXA’s will be performed by a trained DXA operator, and will be interpreted by a certified DXA specialist. Pre-Testing Day 1- Part A You will be asked to arrive in a fasted state, this means you should eat no food for 12 hours prior to the session but you can drink water. The first tests will involve taking some blood samples. We will take one or two fingertip and venous blood samples to measure your cholesterol and glucose levels as well as your haemoglobin and haematocrit. Please see ‘blood sampling’ section below. We will also record your resting heart rate variability for 25 minutes, which just requires you to lie down whilst heart rate (HR) is monitored. Blood Sampling A venous sample will be taken, which is very similar to a blood test you would have at GP surgery, or when giving blood and is relatively pain free. All personnel who will draw blood samples are fully qualified and authorised practitioners. We will ask you to cycle for 12 minutes at a moderate intensity. Your heart rate will be monitored using a heart rate monitor (placed on your chest). We will obtain resting measurements (HR and BP) and during the bike test you will wear a face mask so that expired air can be collected and measured at regular time intervals using a computerised system. Pre Testing Day 2 – Part B

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If you are eligible and willing to participate in the training study, you will be asked to visit us again to perform an exercise test. If you do not want to participate in the training study, you will still be invited to be part of a control group, which means have all your tests repeated 6 weeks later but without taking part in any of the training sessions. You will perform a maximal exercise test, which will last 8-12 minutes. The intensity will increase progressively up to a maximal level which will only be sustained for a few seconds. As well as HR and BP, the electrical activity of your heart may also be monitored (ECG) and expired air will be collected via the face mask. Training Intervention Sessions (Part B) In addition to the initial visits, you will be required to visit the exercise lab in Fairfax Hall at Leeds Metropolitan University 3 times per week (Mondays, Wednesdays and Fridays) for 6 weeks. You will have 1-2 rest days between each session, and the sessions will run early in the morning (8am) or after work (5.30pm Mondays and Wednesday and 4.30pm on Friday) for 6 consecutive weeks. On the designated exercise days, you can eat as usual but ensure you are well hydrated. What do I have to do? Before each training session you will be required to not drink caffeine for a couple of hours and avoid participating in any strenuous exercise for at least 24 hours as this could affect your responses. We do ask you to not alter your current diet and activity habits over the duration of the intervention. This gives us more confidence that any changes are a result of the training. During each training session you will be using the bike and the intensity of exercise will have been determined by your exercise test performance on ‘Pre-Testing Day 2’. You will do a 4minute warm up prior to each session. You will then cycle at a high intensity for 30-seconds, followed by 30 seconds of light cycling or complete rest. This will be repeated 5 times in week one, progressing by one interval each week. You will finish with a 4-minute cool down. This training programme is equal to 5-10 minutes of high intensity exercise per session, and 15-30 minutes per week. Including warm-up, recovery and cool-down, each training session will last 13-18 minutes for a total of 39-54 minutes of exercise per week. This equates to 4.65 hours over the whole 6 weeks! What are the possible benefits of taking part in this study? The study is being undertaken for research purposes and to advance our understanding of resting cardiovascular and metabolic risk factors, and the use of a short HIIT on fitness and risk. You may benefit from participating in the study by understanding more about your individual fitness and cardio-metabolic status, as well as possibly improving these factors over the training period (if eligible for part B). The primary benefit to you will be the opportunity to have a state of the art tests to determine your current fitness status and to assess your risk factors for cardio-metabolic disease. In addition, an introduction to a form of exercise training that could potentially be effective at improving your fitness and health, and it will take less than 20 minutes per session. This way, we hope it would encourage you to continue with an active lifestyle. What happens if something goes wrong? All of the experimental procedures that will be used in this study have been rigorously tested to ensure that they meet health and safety standards. These tests are all routinely and regularly performed on patients and healthy volunteers alike. The researchers who perform the tests are all trained and skilled to do so. If you show signs of illness which may cause you harm, you will be informed and withdrawn immediately from the study. Should there be any issues you experience in this study please can you inform one of the investigators (contact details are at the end of this sheet) and we will do our utmost to address these. Should you be harmed in any way whilst participating in this study, the University maintains clinical trial Indemnity insurance. The clinical trial indemnity insurance will only

101

respond in the event that the University is deemed to be legally liable for incidents that occur, as a direct result of the study. Will taking part in this study be kept confidential? All information collected about you will be kept strictly confidential, other than to those of us who are involved directly with the study. Any information that leaves Leeds Metropolitan University will have your name and address removed so that you cannot be recognised from it. As a group of participants you will receive feedback, but all names will be removed from the individual data set. Who will be working on the study? The researcher in charge is Mr Costas Tsakirides assisted by Dr Michelle Mellis (both Senior Lecturers in Exercise Physiology). At all times, there will be appropriately qualified personnel present during testing sessions. What will happen to the results of the study? Once the study has been completed all data will be anonymised and stored as per current data protection laws. The results will be written up for publication in academic journals and possibly used at academic conferences. Some of the data will be used by the students attached to this study, to inform their dissertations. The students will only receive anonymised data sets. Anything with your personal details (name, DOB, contact details etc.) will be kept securely in a locked filing cabinet by the Principal Investigator. Results will also be made available to you (the participants) on request at any time throughout the study.

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Contact for further information If you require further advice about this study, at any time during participation, you may contact Mr Costas Tsakirides or Mr Daniel Hinchliffe at Leeds Metropolitan University who are organising and working on the study. You may also contact Dr Karen Hind who is independent of the study for advice. Independent Contact Dr Karen Hind Senior Research Fellow and Radiation Protection Supervisor Carnegie Faculty of Sport and Education Leeds Metropolitan University Fairfax Hall 115 Headingley Campus Telephone: 0113 81 26244 Leeds LS6 3QS E-mail: [email protected] Study Team Contact Details Carnegie Faculty of Sport and Education Fairfax Hall, Headingley Campus Leeds, LS6 3QS Principal Investigator: Mr Costas Tsakirides E-mail: [email protected] Investigator: Mr Daniel Hinchliffe E-mail: [email protected]

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Appendix D: INFORMED CONSENT FORM

Participation Identification Number for this Trial:

! CONSENT FORM A

STUDY: HEART RATE VARIABILITY AND OTHER CARDIO-METABOLIC AND RESPIRATORY VARIABLES AT REST AND IN RESPONSE TO HIGH-INTENSITY INTERVAL TRAINING Name of Researcher(s): Mr Costas Tsakirides, Mr Daniel Hinchliffe.

Please initial box: 1. I confirm that I have read and understand the information sheet for the above study and I have had the opportunity to ask questions. I agree to participate in Part A of this study and understand all responsibilities and requirements that are necessary for the study. 2. I understand that my eligibility for Part B will be determined by the researchers based on information collected in Part A. If I am eligible, I will be asked to complete part B of this consent form and the researchers will advise me accordingly. 3. I understand that my participation is voluntary and that I am free to withdraw at any time, without giving any reason and without my legal rights being affected. 4. I understand that the researchers and technicians from Leeds Metropolitan University are fully-trained and skilled to perform all of the tests within this study. 5. I consent to blood samples (venous and finger tip). I will notify the researchers if I have a needle phobia or I am susceptible to fainting prior to the procedure. 6. I consent to having the required number of DXA scans and confirm that I have not had more than 3 scans or X-rays in the past 12 months 7. I understand that in the event of any findings being indicative of a possible medical condition (e.g. diabetes, high blood pressure), the researchers will inform me. 8. I consent to my GP being contacted if any of my results are out of recommended ranges e.g. cholesterol, glucose, blood pressure, insulin, bone mineral density. 9. I understand that if I show any signs of illness which may cause harm, the researchers will inform me and I will be withdrawn from the study. 10. I agree that any personal information about me will remain locked in a filling cabinet by the principal investigator and to be destroyed after 10 years of the conclusion of the study. 11. I consent to the use of my results for statistical analyses, which will form the basis for a number of research communications (abstracts, papers, presentations etc.), and to provide undergraduate and postgraduate students with data for their dissertation. I give permission for these individuals to have access to my results because I will remain anonymous.

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12. I agree to take part in the above study.

_______________________ _________________________ Name of Participant

__________________________ ____________________________ Signature


___________ Date _____________ Name of Researcher

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Signature

Date

Participation Identification Number for this Trial:

! CONSENT FORM B STUDY: HEART RATE VARIABILITY AND OTHER CARDIO-METABOLIC AND RESPIRATORY VARIABLES AT REST AND IN RESPONSE TO HIGH-INTENSITY INTERVAL TRAINING Following the information collected in Part A, you are invited to take part in the exercise training study (Part B). Please indicate your intention to do so by placing your initials in the box by the appropriate response below: Please initial box: Yes, I would like to take part in the training study. I understand I will undergo maximal exercise testing on two occasions and will need to comply with a training programme for 6 weeks (refer to Table 1 on the information sheet). No, I would not like to take part in the training study but I would like to be part of the control group and have a second test in a few weeks. No, I would not like to take part in the training study or the control group.

_______________________ _________________________

___________

__________________________ ____________________________ Name of Researcher

_____________

Name of Participant

Date

Date

Signature

Signature

Personal information: Name:

Study ID:

Email address: Mobile:

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GP details: Surgery name: Address:

Telephone:

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Appendix E: SCREENING QUESTIONNAIRE HRV/HIIT STUDY SCREENING QUESTIONNAIRE (for use prior to exercise testing or training) Study ID: Sex: Occupation: Date of birth: Age: years Date of test: Time: Pre-test screening questionnaire 1. Do you suffer/have you suffered from any CVD (e.g. heart disease, vascular disease, stroke etc.)? Y / N If yes, please specify: 2.

Do you suffer from diabetes? Y / N If yes please give more information:

3.

Do you suffer from any of the following:
 thyroid disorders Y / N kidney disease Y / N liver disease Y / N
 If yes please give more information:

4.

Have you ever suffered from or do you suffer from: asthma Y / N bronchitis Y / N emphysema Y / N Have you ever had an epileptic episode? Y / N
 If yes please give more information:

5.

COPD Y / N

6.

Do you suffer from any muscular or joint problems? Y / N If yes, please specify:

7.

Are you presently taking any medication or receiving medical treatment? Y / N If yes, please specify:

8.

Have you ever felt a pain in your chest or the surrounding areas? Y / N If yes, was it during exercise or exertion? Y / N Please explain:

9.

Have you ever felt breathless or fatigued with mild exertion/exercise that should not normally make you breathless? Y / N







Explain: 10.

Have you ever felt dizzy or lost consciousness (passed out)? Y / N If yes, was it during or after exercise? Y / N

11.

Do you ever find it difficult to breathe at night to the extent that you have to sit up in order to recover? Y/N
 
 If yes, please explain: 


12. 13.

Have you ever had badly swollen ankles without an injury? Y / N Do you frequently get palpitations or tachycardia? Y / N

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14.

Have you ever felt a severe pain in your legs during light exercise (e.g. walking)? Y / N
 


If yes, please explain: 
 15.

Has your doctor ever mentioned you have heart murmurs? Y / N

Coronary risk profile (answer the following questions to the best of your knowledge) 1. Are you or have you ever been on medication for high blood pressure? Y / N If yes, please specify: 2. Have you had your cholesterol tested? Y / N If yes, do you remember the result? 3. Do you smoke cigarettes? Y / N If yes, how many per day? If not, have you ever smoked? Y / N If yes, how long ago did you stop? How many years did you smoke for? 4.

How many cig. did you smoke per day?

Have any of your immediate family suffered from any serious CVD (e.g. heart attack, stroke, cardiac arrest)? Y / N
 If yes, please answer the following questions about the person(s) who suffered from CVD:
 Father or other first degree male relative? Y / N (was it before the age of 55yrs Y / N)
 Mother or other first degree female relative? Y / N (was it before the age of 65yrs Y / N)
 Did this condition result in death or significant disability? Y / N
 Please explain: 5. Do you drink alcoholic drinks? Y / N How many alcohol-free days have you got each week? How much do you drink? (average weekly units): (1 unit of alcohol = 1/2 pint of normal strength beer, 1 pub measure of spirits, 1 glass of wine) 6. Physical activity: do you take part in moderate intensity activity for at least 30min, at least 3 times each week? Y / N
 If has, have you done this for at least three months? Y / N 7. (Females only) Which of the following describes you? Still Menstrual Menopausal Post Menopausal

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PLEASE TICK NEXT TO EACH ITEM WHICH APPLIES TO THIS PARTICIPANT Low Risk Client who qualifies for a maximal test without medical supervision • No Known CV - Pulmonary - Metabolic Disease • CV: cardiac, peripheral vascular, or cerebrovascular • Pulmonary: COPD, asthma, interstitial lung disease, cystic fibrosis • Metabolic: Diabetes (type 1 or 2), thyroid disorders, renal, or liver disease • No signs or symptoms of CV, Pulmonary, Metabolic disease • Pain, discomfort in the chest, neck, jaw, arms, or other areas, that may result from ischaemia. • Shortness of breath at rest or with mild exertion. • Dizziness or syncope. • Orthopnoea or Paroxysmal nocturnal dyspnoea. • Ankle oedema. • Palpitations or tachycardia. • Intermittent claudication. • Known heart murmur. • Unusual fatigue or shortness of breath with usual activities. • No more than 1 CVD risk factor • (If HDL ≥ 1.55 mmol.L-1 then subtract 1 from the sum of the CVD risk factors) • Age: M≥45 or F≥55 • Family history: MI, revascularisation, sudden death in father or male 1st degree relative