The Effect of Konjac Glucomannan Fibre Gel on Satiety and Energy Intake

Home , Glucomannan, Konjac, Shirataki noodles

Fei Au-Yeung

A thesis submitted in conformity with the requirements for the degree of Master of Science Department of Nutritional Sciences University of Toronto

THE EFFECT OF KONJAC GLUCOMANNAN FIBRE GEL ON SATIETY AND FOOD INTAKE

Fei Au-Yeung Master of Science, 2016 Department of Nutritional Sciences University of Toronto

ABSTRACT

Konjac glucomannan (KGM) is a viscous dietary fibre that forms a firm, low-energy gel (KGM- gel) with shapes resembling common food staples. Despite a history of use in Asia, no study to date as assessed the effect of replacing energy-dense foods with KGM-gel foods. Therefore, we conducted two acute, randomized, controlled, crossover trials in healthy individuals to assess

KGM-gel food substitution at a moderate and high level in single and repeated meals on appetite and energy intake. In both studies, KGM-gel substitution proportionally reduced the energy content of test meals compared to control. While high substitution lowered satiety, moderate substitution did not reduce satiety and cumulative energy intake was inversely proportional

KGM-gel substitution. KGM-gel foods may assist in reducing energy intake without increasing appetite when replacing a modest amount of energy-rich foods. These results may have relevance in weight loss regimes and should be evaluated in overweight or obese populations.

ACKNOWLEDGEMENTS

To begin, I would like to thank my supervisor, Dr. Vladimir Vuksan, for providing me with an opportunity to pursue a Master’s degree and build a foundation in the area of nutrition research.

Your support and guidance has been immeasurable since I began my journey at the Risk Factor

Modification Centre in 2012 and you have been an invaluable mentor in all aspects of my life.

You provided me with the model for research excellence and have set the standard for my expectations. While every journey has oscillating moments, you were always patient and flexible. Your enthusiasm for research is infectious and I have always taken away valuable life lessons with all of the stories you share. The experiences you have provided me will be carried throughout my career, so I am thankful for the faith and passion you have placed in me.

I would also like to thank Dr. Alexandra Jenkins for her support and guidance throughout my journey. The opportunity you have provided me to apply the skills that I have acquired throughout my Master’s degree has immensely contributed to my growth and development. I would also like to thank my supervisory committee members, Dr. Thomas Wolever and Dr.

Harvey Anderson. Your questions and insights regarding my research have been stimulating and have driven me to seek out answers in uncharted waters. It has undoubtedly shaped my approach to research, and I am thankful for experiences you have shared with me.

I am also thankful for the colleagues and staff that I have had the pleasure of working with.

Thank you, Elena Jovanovski, for the countless hours of guidance and assistance you have provided me when I am met with a crossroad. I once heard the phrase “linchpin of sanity”, and I

iii feel it suits you in more ways than one. Thank you, Andreea Zurbau and Thanh Ho, for lending an ear in my times of need and for making my cloudless days just a little bit brighter. There is always more to say about everyone, but this should suffice for the sake of brevity. While the roles you’ve played in my professional and personal development have been different, know that the value of your friendship weighs equally to me. Thank you for always having patience with me and thank you for your unwavering support, even when my resolve falters.

Another sizeable thank you goes out to all of our research volunteers and study participants I have met throughout my time at the RFMC. The work done here would not be possible without you, and it is your interest and passion that drives our research.

Lastly, I would like to thank my family for putting a roof over my head and my friends for their support during this time. To my friends that have journeyed alongside me, it has been a blast.

Thank you for being an outlet of comfort and R&R in an everlasting vortex of work and deadlines.

I have been humbled by everyone I have met and the days will never be quite the same without everyone. However, with the end of one journey marks the beginning of another. Thank you for the memories and I hope we all cross paths in the future.

Table of Contents

CHAPTER 1. INTRODUCTION ...... 1

CHAPTER 2. LITERATURE REVIEW ...... 4

2.1. Obesity ...... 5

2.2. Weight Loss ...... 6

2.3. Surgical Approaches to Weight Loss ...... 6

2.4. Pharmacological Approaches to Weight Loss ...... 8

2.5. Dietary and Lifestyle Approaches to Weight Loss ...... 9

2.6. Appetite and Satiety Regulation for Weight Loss ...... 12

2.7. Dietary Fibres for Weight Loss and Appetite Regulation ...... 17

2.8. Glucomannan Fibre ...... 19

2.9. Characterization of Konjac Glucomannan Fibre...... 20

2.10. Physicochemical Properties of Konjac Glucomannan ...... 22

2.11. Macronutrient and Sensory Properties of Konjac Glucomannan ...... 23

2.12. History, Use, and Safety of Konjac Glucomannan ...... 25

2.13. Health Benefits of Konjac Glucomannan ...... 27

2.14. Potential of Konjac Glucomannan Gel for Energy Regulation ...... 28

CHAPTER 3. RATIONALE, OBJECTIVES, AND HYPOTHESES ...... 31

3.1. Rationale ...... 32

3.2. Objectives ...... 34

3.3. Hypothesis...... 35

CHAPTER 4. INVESTIGATION OF AN ISOVOLUMETRIC PRELOAD OF KGM-GEL ON

APPETITE AND ENERGY INTAKE ...... 36

4.1. ABSTRACT ...... 37

4.2. INTRODUCTION ...... 38

4.3. METHODS ...... 40

4.3.1. Participants ...... 40

4.3.2. Design ...... 40

4.3.3. Study Materials ...... 41

4.3.4. Measurements ...... 42

4.3.5. Statistical Analysis ...... 44

4.4. RESULTS ...... 46

4.4.1. Participants ...... 46

4.4.2. Energy Intake ...... 46

4.4.3. Appetite Sensations ...... 48

4.4.4. Other Measures ...... 50

4.5. DISCUSSION ...... 52

CHAPTER 5. KONJAC GLUCOMANNA GEL SUBSTITUTION OVER A DAY ON APPETITE

AND SUBSEQUENT ENERGY INTAKE ...... 58

5.1. ABSTRACT ...... 59

5.2. INTRODUCTION ...... 60

5.3. METHODS ...... 62

5.3.1. Participants ...... 62

5.3.2. Design ...... 62

5.3.3. Interventions ...... 63

5.3.4. Procedures ...... 66

5.3.5. Measurements ...... 67

5.3.6. Statistical Analyses ...... 69

5.4. RESULTS ...... 72

5.4.1. Participants ...... 72

5.4.2. Appetite ...... 73

5.4.3. Subsequent Food Intake ...... 77

5.4.4. Blood Glucose ...... 78

5.4.5. Blood Pressure ...... 80

5.4.6. Palatability, Time to Eat, and Symptoms ...... 81

5.5. DISCUSSION ...... 83

CHAPTER 6. DISCUSSION, LIMITATIONS, FUTURE DIRECTIONS, CONCLUSION...... 88

6.1. MAIN FINDINGS ...... 89

6.2. OVERALL DISCUSSION ...... 90

6.3. LIMITATIONS ...... 92

6.4. FUTURE DIRECTIONS ...... 94

6.5. CONCLUSIONS ...... 97

CHAPTER 7. REFERENCES ...... 98

CHAPTER 8. APPENDIX ...... 114

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LIST OF TABLES

Table 1 – Grades of konjac glucomannan preparations...... 22

Table 2 – Nutrient composition of konjac glucomannan preparations...... 24

Table 3 – Composition and characteristics of the preloads...... 42

Table 4 – Mean ratings of appetite measurements over 90 min in 16 healthy participants...... 50

Table 5 – Mean palatability and time to consume preload in 16 healthy individuals...... 50

Table 6 – Presence of symptoms during preloading in 16 healthy individuals...... 51

Table 7 – Composition of intervention meals...... 65

Table 8 – Nutrient composition of intervention meals...... 66

Table 9 – Participant characteristics at baseline...... 72

Table 10 – Mean 12 hour appetite measurements in 20 healthy individuals...... 76

Table 11 – Mean 12 hour ambulatory blood pressure...... 80

Table 12 – Mean palatability and time taken to consume meals in 20 individuals...... 81

Table 13 – Presences of symptoms over 12 hours in 20 individuals...... 82

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LIST OF FIGURES

Figure 1 – Amorphophallus konjac K. Koch plant...... 20

Figure 2 – Konjac glucomannan gel foods...... 27

Figure 3 – Subsequent energy intake at 90 min after preload administration...... 47

Figure 4 – Mean appetite ratings over 90 min...... 49

Figure 5 – Mean appetite ratings over 12 hours...... 74

Figure 6 – Mean 120 min AUC for appetite after each meal...... 75

Figure 7 – Subsequent and cumulative energy intake in 20 healthy individuals...... 77

Figure 8 – Postprandial blood glucose response over 6 hours in 20 healthy individuals...... 79

Figure 9 – Hourly ambulatory blood pressure measurements in 20 healthy individuals...... 80

LIST OF APPENDICIES

Appendix 1 – Study 1 Clinical Assessment Form 106

Appendix 2 – Study 1 Subject Information Form 107

Appendix 3 – Study 1 Ad Libitum Food Form 108

Appendix 4 – Study 1 Palatability Questionnaire 109

Appendix 5 – Study 2 Clinical Assessment Form 110

Appendix 6 – Study 1 & 2 Preclinical Information 111

Appendix 7 – Study 1 & 2 Satiety Questionnaire 112

Appendix 8 – Study 1 & 2 Symptoms Questionnaire 113

Appendix 9 – Study 2 Palatability Questionnaire 114

Appendix 10 – Study 2 Medical History Questionnaire 115

LIST OF ABBREVIATIONS

ADF Alternate day fasting

AHA American Heart Association

ANOVA Analysis of Variance

AUC Area Under the Curve

BMI Body Mass Index

BP Blood Pressure

CCK Cholecystokinin

CI Confidence Interval

CNF Canadian Nutrient File

CS Composite Score

CVD Cardiovascular Disease

DASH Dietary Approaches to Stop Hypertension

DBP Diastolic Blood Pressure

ED Energy Densioty

EFSA European Food Safety Authority

FDA Food and Drug Administration

GI Gastrointestinal

GLP-1 Glucagon-Like Peptide 1 iAUC Incremental Area Under the Curve

IF Intermittent Fasting

KGM Konjac Glucomannan

LDL Low Density Lipoprotein

MRI Magnetic Resonance Imaging

PYY Peptide Tyrosine Tyrosine

RCTs Randomized Controlled Trials

RR Relative Risk

RYGB Roux-en-Y Gastriic Bypass

SBP Systolic Blood Pressure

SCFA Short Chain Fatty Acid

SQ Satiety Quotient

T2DM Type 2 Diabetes Mellitus

TFEQ Three Factors Eating Questionnaire

USDA United States Department of Agriculture

VAS Visual Analogue Scale

WHO World Health Organization

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CHAPTER 1. INTRODUCTION

The prevalence of obesity continues to rise worldwide [1]. Overweight or obese individuals are at a greater risk of developing comorbidities such as type 2 diabetes and cardiovascular disease, placing a significant burden on the health care system [2]. Strategies to manage or prevent obesity often focus on body weight regulation by pharmacological or dietary approaches. However, pharmacological interventions are often unsuccessful as currently prescribed agents are limited in efficacy and hindered by significant adverse effects [3-5].

Surgical approaches can be taken, and have been met with great success in the reduction of mortality, but serious adverse effects limit this option to the morbidly obese [6].

Hence, dietary approaches to manage body weight are often recommended. These recommendations typically introduce a 500-1000 kcal deficit in daily energy intakes through changes in dietary habits, with the goal of achieving negative energy balance to promote weight loss [7]. Unfortunately, weight loss programs are met with poor compliance, as the changes in lifestyle are often too difficult for individuals to adhere [8]. Causes for poor compliance are often due to intolerable hunger as a result of portion control and dietary modification to achieve hypocaloric conditions [8-10]. The low satiating quality of the diet will contribute to increased food intake during meals and increased meal frequency, likely resulting in the consumption of energy greater than the deficit introduced.

Studies have suggested that viscous dietary fibres promote satiety and may modestly reduce body weight [11]. However, the health benefits of viscous fibres rely largely on their physicochemical properties, where fibres with the greatest viscosity appear to be the most beneficial [12]. In particular, certain viscous fibres are capable of forming solid gels after hydration, and have been shown to increase satiety to a greater extent than the same type of fibre administered in a non-gel form [13,14]. These fibre-gels are often low in energy, as the primary

2 composition is water and fibre, and may act as a potential tool in weight management if it can provide feelings of satiety comparable to or greater than typically consumed foods.

One type of fibre-gel food products that is commercially available is derived from konjac glucomannan (KGM). KGM-gel is a traditional food that originates from China and Japan, and is popularly consumed in Japan [15,16]. It can be commonly purchased as “shirataki noodles” which is KGM-gel extruded into strands with a similar diameter to spaghetti. This KGM-gel is very low in energy content and may introduce an energy deficit in the diet when substituted as a replacement for typical caloric food items, such as pasta. However, little is known about the effects of KGM-gel on appetite and energy intake in a clinical setting.

CHAPTER 2. LITERATURE REVIEW

2.1. Obesity

The prevalence of overweight and obesity continues to rise across the world. The most commonly reported measure for overweight and obesity is the body mass index (BMI), which is a function of an individual’s weight divided by their height squared. Based on the classification from various health agencies, overweight is defined as a BMI between 25.0-29.9 kg/m2 and obese is defined as a BMI equal to or greater than 30.0 kg/m2. Data from the World Health

Organization (WHO) in 2014 reports that more than 1.9 billion adults (39%) are overweight or obese, with more than 600 million adults (13%) being obese [17]. Data from Statistics Canada in

2014 reported that over 14 million (54%) Canadian adults are overweight or obese, where approximately 5.3 million (20%) Canadian adults are obese [18]. These rates are higher than those reported by the WHO for the world population and are in agreement with the prevailing notion that developed countries experience a higher prevalence of obesity.

Overweight and obesity has been linked with increased risk for developing various chronic conditions, such as cardiovascular disease (CVD), type 2 diabetes mellitus (T2DM), arthritis, various common and less common cancers, and is linked with increased all-cause mortality

[2,19,20]. Data from 97 prospective studies indicates that every 5 kg/m2 increase in body mass index (BMI) above 20 kg/m2 is associated with a 27% higher risk of coronary heart disease and

18% risk of stroke [21]. Data from 141 studies reported significantly higher relative risk (RR) of

1.51 for oesophageal adenocarcinoma, a RR of 1.24 for colon cancer in men, and a RR of 1.24-

1.34 for renal cancer among several cancer types [22].

2.2. Weight Loss

Current recommendations from various health agencies suggest aiming for a reduction of 5-10% from initial body weight as a clinically meaningful weight loss goal [7,23]. Such reductions have been linked to improvements in CVD outcomes and reduced incidence of T2DM [24-26]. While the regulation of body weight can be simplified to a problem of energy balance, where energy intake is exceeding energy expenditure, the most common challenge for individuals undergoing weight loss is not the process of losing weight, but is in the attempt to maintain the weight lost

[27]. Weight reduction from weight loss therapies tend to plateau after 6 months of intervention

[23]. After this period, focus is shifted to maintaining the weight that has been lost, instead of attempting to lose more weight. The difficulty in maintaining the lost weight is due to the homeostatic response to maintain body weight, leading to a production of counter-regulatory hormones that drive overconsumption [28,29]. Several strategies are currently available for promoting weight loss and maintenance, and are often prescribed based on the severity of obesity. The line of treatment for overweight or obese individuals is lifestyle intervention, which can include behavioural therapies and dietary and physical activity programs. For more severe cases of obesity, pharmacological approaches are available, and for extreme cases, surgical intervention is considered in conjunction with lifestyle interventions [7,23].

2.3. Surgical Approaches to Weight Loss

Bariatric surgery is a term describing a number of elective procedures performed on the stomach and lower gastrointestinal (GI) tract to promote weight loss. These procedures often act by restrict the amount of food the stomach can handle or reduce the absorption of nutrients in the

6 intestinal tract. Clinical studies have shown that bariatric surgery for long-term weight loss is more effective than lifestyle or pharmacological interventions alone when promoting and maintaining weight loss in severely obese individuals (BMI > 40 kg.m2) [30-32]. Current available options for bariatric surgery are laparoscopic adjustable gastric banding, laparoscopic

Roux-en-Y gastric bypass (RYGB), open RYGB, biliopancreatic diversion with and without duodenal switch, and sleeve gastrectomy.

Research has shown that up to 60% of excess weight can be reduced by bariatric surgery, depending on individual factors such as the presence of comorbidities, initial body weight, and other factors [23]. Beyond weight loss, many studies have reported improvements in quality of life and obesity associated comorbidities after bariatric surgery. In some cases, individuals have shown resolution of comorbidities such as T2DM and hypertension [32,33].

However, despite the effectiveness of bariatric surgeries, the potential for complications limit the procedure to those that are severely obese, as defined as a BMI > 40 kg/m2 or a BMI > 35 kg/m2 with the presence obesity-related comorbidities. Firstly, post-surgical mortality rates have been reported to range from 0.1-2.0%, depending on various factors such as the type of surgery, the surgeon, and other factors [34,35]. Secondly, individuals can also experience short or long term complications including, but not limited to, bowel obstruction, GI discomfort, ulcers, gallstones, deep vein thrombosis, and need for reoperation. While effective in weight management, bariatric surgery represents a last resort for individuals to aid in weight management. Appropriate modifications to lifestyle and diet continue to be a necessity to prevent weight regain.

2.4. Pharmacological Approaches to Weight Loss

Pharmacological options for weight loss are available and prescribed in conjunction with an energy restricted diet. In Canada, two pharmacological options have been approved for the medical treatment of obesity: orlistat which is a lipase inhibitor and liraglutide which is a glucagon-like peptide 1 (GLP-1) agonist. In the United States, three additional pharmacological interventions for obesity treatment have been approved by the Food and Drug Administration

(FDA): lorcaserin, phentermine-topiramate combination, and naltrexone-bupropion combination, which are drugs that act on the central nervous system to promote appetite suppression.

A network meta-analysis of 28 randomized controlled trials (RCTs) reported a weighted mean reduction in body weight when comparing the drug to the placebo of 2.6 kg (95% CI, 2.3-2.9 kg) with orlistat, 3.2 kg (95% CI, 3.0-3.6 kg) with lorcaserin, 5.0 kg (95% CI, 4.4-5.5 kg) with naltrexone-bupropion, 8.8 kg (95% CI, 8.0-9.6 kg) with phentermine-topiramate, and 5.2 kg

(95% CI, 4.9-5.6 kg) with liraglutide [36]. While all pharmacological interventions resulted in significant weight reduction, pharmacological treatments are often associated with adverse events that limit the effectiveness in dieting individuals. Adverse events that are commonly reported among all the pharmacotherapies include headaches, dizziness, and nausea.

Accordingly, the present meta-analysis identified significantly higher rates of withdrawal due to adverse events in all pharmacotherapies when compared to the placebo control. This limits the acceptance of many pharmacological approaches for many individuals when used over an extended period of time.

2.5. Dietary and Lifestyle Approaches to Weight Loss

Dietary and lifestyle modifications to maintain a healthy body weight remains to be the first line of treatment as obesity is a condition heavily influenced by environmental factors. These approaches to weight loss remain to be the safest and most widely recommended method to achieve a healthy body weight when properly implemented [7,23]. Emphasis on this approach focuses on achieving a negative energy balance to mobilize adipose tissue by decreasing energy intake through dietary restriction, increasing energy expenditure through exercise, or a combination of both. While exercise has been shown to be effective in improving satiety and promoting weight loss in the absence of caloric restriction, exercise programs can be difficult for individuals due to physical limitations, joint pain, and increased risk of injury due to high body weight and deconditioning from the existing physical inactivity [37,38].

Dietary approaches to weight management are vast and numerous, but generally have an element of energy restriction. Current guidelines recommend promoting a daily energy deficit of 500-

1000 kcal to achieve a healthful rate of weight loss (0.5-1.0 kg/week) in free-living individuals to reach a goal of 5-10% reduction in initial body weight [7]. Such reductions have been observed in various dietary approaches, but a commonality between most weight loss diets is that the relative success of weight loss is closely associated with the adherence to the prescribed diet

[29,39,40].

Numerous clinical trials for weight loss with lifestyle interventions have found that selecting a specific type of weight loss diet or adjusting the relative macronutrient distribution within the weight loss diet does not confer additional weight loss. Data of 713 individuals from the

PREMIER trial after 6 months found that an energy restricted lifestyle intervention with or without advice on following a DASH (Dietary Approaches to Stop Hypertension) diet observed greater weight loss compared to an advice only control (-4.9 kg and -5.8 kg, respectively), with no differences between the intervention groups [41]. Similarly, the POUNDS Lost study with data from 811 overweight individuals evaluated the effects of 4 diets with different macronutrient distributions: low-fat average-protein, low-fat high-protein, high-fat average protein, and high-fat high-protein [10]. Weight change from baseline at 6 months and 24 months were similar between all groups, with weight loss being greater at 6 months (approximately -6 kg) then at 24 months (approximately -3.5 kg). The results from these trials are consistent with current meta-analyses on dietary approaches to weight loss that reach similar conclusions that energy restricted diets result in clinically meaningful weight loss regardless of the macronutrient distribution emphasized [42].

Another dietary approach to weight management that has received considerable scientific attention is intermittent fasting (IF) and alternate day fasting (ADF) [43]. IF is a dietary weight loss therapy where an individual cycle between periods of usual food intake and a fasting period where individuals do not consume any calories. One popular IF method is the “5:2”, where individuals choose 5 days in a week to eat normally and 2 days in the week to fast (consume no calories) [44]. While fasting for a full day in the IF approach can be difficult, ADF is a modified regime where individuals restrict the caloric intake to < 500 kcal per day (600 kcal for men) on alternating days in place of fasting. Recent research has reported that ADF is a safe and tolerable method to weight management that produces similar changes in body weight, body composition and some CVD risk factors when compared to a traditional 500-1000 kcal energy restricted

10 approach [45,46]. The weight lost is within the range of 5-6 kg in ADF studies over a 12 week period with high adherence rates [47-49]. While the results suggest efficacy and are promising, the lack of long term data calls for additional, higher quality studies to be conducted before IF or

ADF can be recommended to the general population as weight loss therapies.

Commercial or proprietary weight loss programs are also popular treatment options for obesity despite their subscription costs or lack of clinical evidence evaluating their efficacy. Among the most popular are Weight Watchers, Nutrisystem and Jenny Craig [50]. The costs of these diets can vary between monthly subscription fees of $20-30 excluding the foods that need to be purchased. The attraction of commercial weight loss programs may stem from their popularity, ease of use, or both. For example, the Nutrisystem is a low-calorie meal replacement plan where individuals buy frozen, prepackaged meals that are delivered to the individual. These commercial programs can offer a simple approach to weight loss that is not focused on the restriction of any particular food group or macronutrient. The Jenny Craig program is similar, but offers weekly consultations with a counselor at an increased subscription fee. The efficacy of these commercial weight loss programs, while limited in clinical evidence, have been summarized in a recent review [50,51]. The Weight Watchers program reported in a minimum of 2.6% reduction in body weight over 12 months in 6 trials, the Nutrisystem program reported a minimum of 3.8% reduction in body weight compared over 3 months in 3 trial, and Jenny Craig system reported a minimum of 4.9% body weight reduction over 12 months in 3 trials when compared to an advice only control. The primary limitation of these studies are the short duration of trials, most lasting less than 12 months, and large rates of dropouts. The modest reduction in weight observed does not reach the goal of 5%, which is associated with improvements to obesity-related CVD risk

11 factors. Despite the lack of efficacy and incomplete clinical evidence, the popularity of these commercial weight loss programs may be explained by their low level of participant burden.

Many factors predicting dietary weight loss success beyond adherence have identified, such as initial starting weight, amount of weight loss within the first 1-3 months, dietary disinhibition, and others [39,40]. However, one factor that may be limiting dieting success is the amount of participant burden that is placed on the dieter. A study on 240 individuals with metabolic syndrome investigating weight change following 1 of 2 diets [52]. The first diet was an energy restricted diet based on the American Heart Association (AHA) guidelines that recommended various dietary goals such as consuming a diet with an energy distribution of 50-55% from carbohydrates, 15-20% from protein, and 30-35% from fat where less than 7% of total energy intake is from saturated fat, while increasing the consumption of fruits, vegetables, dietary fibre, plant protein, and reducing sugary foods. The other diet was simply to increase dietary fibre consumption to more than 30 g per day with no advice for energy restriction. Unexpectedly, the increased fibre group reported a 12 month weight loss of 2.1 kg, which is comparable to the 2.7 kg weight loss in the energy restricted AHA diet group. These results suggest that simple dietary changes may be more effective at promoting weight loss when compared to complex dietary advice and may indicate a desire for interventions that require minimal change.

2.6. Appetite and Satiety Regulation for Weight Loss

Identifying foods that improve the regulation of appetite and satiety sensations may assist in the management of food intake and body weight. Appetite is commonly defined as the sensation that

12 motivates food intake, selection, and preference. In contrast, satiety is the process that regulates food intake after the consumption of food leading to the next eating episode. These sensations can be a result of environmental stimulation, food sensory aspects, energy imbalance, and other factors that encompass physiological and psychological stimuli.

Changes in appetite and satiety from and eating episode are often depicted by four phases: sensory, cognitive, pre-absorptive and post-absorptive effects [53]. The sensory phase often begins prior to, during, and shortly after food intake. During this phase, appetite is associated with olfactory and oro-sensory cues such as smell, taste, and texture, appearance, and auditory cues. The cognitive phase can overlap the sensory phase and is influenced by socio-cultural, preconceived, and personal beliefs held about food. Aspects of the pre-absorptive is described by the physiological processes that occur prior to the absorption of nutrients in the GI (GI) tract, such as gastric distention and emptying rate, which occurs during and shortly after food ingestion. In contrast, the post-absorptive phase occurs during the latter phase of digestion and relates to the influence of the presence and absorption of nutrients and their metabolites in the blood and GI tract, such as blood glucose, fatty acids, and amino acids that influence satiety- related hormones.

One of the most common forms of appetite measurement is through self-reported visual analogue scales (VAS) due to their low cost and ease of use. The VAS is a straight, horizontal line with no notches or markers other than indicators that are anchored at the end of each scale. The current standard questionnaire for appetite measurements consists of 4 questions, each on a separate 100 or 150 mm VAS reflecting different aspects of the motivation to eat [53,54]. The 4 questions

13 reflect the desire to eat, hunger, fullness, and prospective food consumption. Each scale is anchors with the phrase “very weak” on the left end and “very strong” on the right end. While the VAS scores are subjective measures of appetite, studies have demonstrated that appetite measurements from VAS are reliable and reproducible within the individual on different test days in healthy, overweight, and obese individuals [54,55]. These individual questions have been accepted for the quantification of health claims for satiety by the European Food Safety

Authority (EFSA) and are being considered in the Health Canada draft guidance document for appetite and satiety health claims [56,57]. A composite score, which is computed as the average of the 4 appetite questions, have also been suggested as a representation for the overall motivation to eat and is acceptable as evidence for appetite and satiety health claims, although current health claims only support the 4 VAS measured appetite ratings.

While the collection of VAS ratings of appetite are similar across most studies, the way in which they are reported and represented have been met with heterogeneity, leading to difficulties in interpretation. Attempts to standardize the reporting methods were made recently, suggesting that researchers avoid assessing appetite ratings at individual time points, but instead use a method that accounts for changes in time to assess the overall appetite sensation [53]. The most frequently suggested approach is to use the absolute Area Under the Curve (AUC) over the testing period for all appetite measurements, with a statistical adjusted for baseline appetite ratings to account for variations between testing days and individuals. This is currently accepted by EFSA and Health Canada for health claim quantifications [56,57]. Other measurements, such as the mean appetite ratings over the testing period, are also acceptable as it provides an

14 assessment over time, although the AUC method accounts for differences in the delay between measurements [56].

Other methods that have also been used is the satiety quotient, which is a measure of the satiating efficiency of a food based the amount or energy consumed over a period of time, which is expressed as the appetite rating per gram or kilocalorie of food consumed [58]. This assessment may be useful when interventions differ in volume or calories consumed, as the satiating efficiency of foods can be due to factors beyond amount and energy content consumed. The SQ for fullness has been shown to be predictive of acute ad libitum energy intake and in dieting women [59,60]. The SQ can be used as supporting evidence for an appetite and satiety health claim, although there is a need to validate this measurement in different populations as few studies utilize this assessment [56].

Appetite and satiety has been suggested to curb overconsumption and assist in compliance to energy deficient diets to help increase adherence during weight loss. While expert opinions suggest that a 10% difference in appetite measurements from VAS represent a clinically meaningful outcome [53], a recent review of 23 studies involving 549 individuals suggests that a difference of at least 15% is needed to alter subsequent energy intake [61]. Additionally, it was suggested that the question that best predicted subsequent energy intake was hunger. Based on current recommendations, a 10% reduction in hunger was associated with a 5.3% reduction in energy intake based on the conclusions of the review, although this value can changing depending on the factors initial hunger rating and the magnitude of change. Subjective appetite

15 ratings have been shown to have predictive value for weight loss success and may be a useful target to improve adherence to energy restricted diets [60,62].

Other measurements of appetite involve the assessment of satiety-related hormones. These are biomarkers that can be assessed and are known to influence feels of appetite and food intake

[63]. These include hormones that promote hunger such as ghrelin, or hormones that promote satiety such as cholecystokinin (CCK), peptide YY (PYY), GLP-1, and over extended periods of time, leptin. These have all been shown to be regulators of appetite and have a blunted response in obese individuals [64].

The other most common method to assess appetite in the context of weight loss is through ad libitum food consumption [53,65]. In this method, participants are told to consume as much food as they desire until they feel moderately full. The amount of food consumed and the energy content is then calculated and used to assess the effectiveness between treatments. In this case, the treatment manipulation can occur as a preload, a meal that occurs prior to ad libitum food intake, or the manipulation occurs with the ad libitum food itself. This method provides the most direct method of assessing an efficacy of weight loss tool, as the result is directly related to energy balance [66]. However, there are several limitations to this method that should be addressed. The amount of food consumed through ad libitum food intake has been shown to be affected by design factors. An example is where ad libitum food intake increases when the variety of food available is increased [67-69]. Similarly, when the food is presented in a set portion, individuals tend to consume the entire portion, regardless of the energy content [70-72].

In addition, the time between the previous meal and the next meal can greatly affect ad libitum

16 intakes. A recent systematic review of 61 preloading studies reported that increased delay between meals lowers the sensitivity of compensation, leading to overconsumption [65]. Due to these limitations, studies of different design measuring appetite should be interpreted with caution.

2.7. Dietary Fibres for Weight Loss and Appetite Regulation

Dietary fibres have long been suggested to have a potential weight reducing effect in addition to their established metabolic health benefits. Evidence from large epidemiological studies have reported a reduced risk of developing obesity with increasing dietary fibre intake [12,73,74], in addition to having an inverse relationship to the risk of developing CVD, T2DM, and colon cancer [75-79]. Mechanisms for weight reduction with dietary fibres are proposed to act by reducing dietary ED, modifying oro-sensory exposure, promoting gastric distention, and delaying gastric emptying to modify nutrient absorption [80]. However, few RCTs have studied the independent effects of dietary fibres for weight loss over durations beyond 12 months [11].

Data from RCTS have estimated that a 14g increase in dietary fibre intake over the duration of

3.8 months can result in an estimated weight reduction of 1.8 kg [80]. More recent investigations have only reported modest weight reducing (~2 kg) effects of increase fibre supplementation and these studies are often less than 6 months in duration, suggesting a need for higher quality RCTs

[52,81,82].

One explanation for the modest weight effect is that, while the majority of epidemiological evidence has associated fibre intakes with cereal and whole grain fibres, acute and RCTs of up to

12 weeks have demonstrated that soluble viscous dietary fibres have the greatest propensity to attenuate appetite, reduce daily energy intake, and body weight [11]. Viscous fibres are believed to act on appetite by increasing the viscosity of the digesta in the GI tract after ingestion, delaying gastric emptying and nutrient absorption [83,84]. This delay results in greater volumes in the antrum of the stomach, and has shown to be positively correlated with sensations of fullness [85,86]. However, the effects of viscosity on appetite control are dependent upon multiple factors and may not translate to reductions in energy intake. Differences in viscosity for a cellulose or glucomannan drink did not result in significant differences in energy intake from pizza at the subsequent meal [87]. In addition, the development of viscosity can be influenced by gastric conditions such as pH or dilution, greatly reducing the often reported and measured in vitro levels of viscosity. Indeed, viscous fibres appear to beneficially influence hunger and appetite, but the effect on subsequent energy intake remains unclear [11,13,88,89]. However, reductions in body weight have been well documented in viscous fibres such as KGM and in gel- forming fibres such as alginates, although these studies are limited by a short intervention period

[81,90-92].

Emerging evidence suggests that dietary fibre-gels may have a similar effect on appetite to viscous dietary fibres [93,94]. Dietary fibre-gels are derived from gel-forming fibres, which is a term often used as a synonym for viscous fibre, but holds distinct differences. Viscosity is often related to the ability of the dietary fibre to thicken or form a gel when mixed with fluids.

However, only certain fibres exhibit changes in the molecular interactions that result in the transition of a thick liquid to a solid, self-standing form [95]. As the fibres are often dispersed into water for hydration, the energy content of the fibre-gel belongs solely to the fibre content

18 and liquid medium used. These fibre-gels are believed to be efficacious due to the fact that solid foods are typically more satiating than liquid foods [65]. Indeed, it has been shown that dietary fibre-gels are more satiating than their non-gelled counterparts [13,14,88,96-98]. This effect may be due to delays in gastric emptying, increased activation of mechanical stretch receptors in the stomach, or increased oro-sensory exposure time, leading to prolonged meal time as postulated in the previous studies. Known gel-forming fibres are pectin, agar, alginate under acidic conditions, and KGM.

2.8. Glucomannan Fibre

Glucomannan is a neutral viscous dietary fibre derived from the root tubers of perennial plants indigenous to Asia belonging to the Amorphophallus genus [99]. There are over 170 species belonging to this genus, but less than 10 are known to be used as a food source [100]. The physical appearance of the plant typically consist of a stem that extends into a corm that is underground and a highly dissected umbrella-shaped leaf blade that extends on the other end of the stem above ground (Figure 1). The corms are brown in colour and are harvested and milled as a flour to produce foodstuffs. These plants have a long history of use in Asia as a food source and traditional medicine for over a thousand years [16]. In recent years, interest in KGM has grown as it possesses unique physicochemical properties that can be applied in industrial and biomedical applications [101,102].

2.9. Characterization of Konjac Glucomannan Fibre

The most commonly produced crop is Amorphophallus konjac K. Koch, which contains one of the largest yields of glucomannan (w/w) [103]. KGM has a naturally occurring molecular weight between 200,000 – 2,000,000 Da. KGM primarily consists of a linear backbone of β-1,4 linkages of D-mannopyranose and D-glucopyranose sugars in a 1.6:1 ratio that occur in a random order, with three to five block repeats of mannopyranose sugars being common [104]. The side chains consists of 5 to 10% acetyl groups occurring every 10-19 units on the glucomannan backbone in

β-1,6 linkages, that provides KGM with its soluble properties in aqueous solutions [105].

Figure 1 – Amorphophallus konjac K. Koch plant. The upper stem and leaf (left) and harvested corm that contains the konjac glucomannan fibre (right).

Konjac plants are typically milled after harvesting to form crude flour that can be used immediately or refined for various uses. The corms of A. konjac contain 49-60% (w/w) glucomannan, 10-30% starch, 3-7% in inorganic elements (aluminum, calcium, chromium, cobalt, iron, magnesium, manganese, phosphorus, potassium, selenium, silicon, sodium, tin, and zinc), 5-14% in crude protein, 3-5% in sugars, 3-5% ash, and a small amount of alkaloids and saponins [106], as well as other trace elements of organic compounds. The refining process uses a dry or wet processing method and results in various grades of KGM material to be used [107].

Different grades have been defined by the European Commission and Chinese Ministry of

Agriculture (presented in Table 1), drawing a distinction in KGM material for labeling purposes

[108,109]. Konjac material produced by dry processing is refined mechanically and then wind- sifted, resulting in a relatively low purity of konjac flour containing less than 75% glucomannan

[103,110]. This konjac flour is typically sold as a food commodity. Wet refining processes refers to glucomannan extracted typically through chemical means such as lead acetate, salts, enzymes, ethanol, or a combination of these methods that are more costly than dry processing [111-114].

The benefit of wet processing is a material of higher purity containing glucomannan concentrations of 75-99%, which are more effective in industrial and biomedical applications.

This method is also used to produce pharmaceutical grades of KGM, which has a purity of more than 95% glucomannan, except for the lead acetate extraction which yields inedible KGM.

Table 1 – Grades of konjac glucomannan preparations.

Specifications Konjac Flour Konjac Glucomannan Chinese Ministry European Chinese Ministry European of Agriculture Commission of Agriculture Commission Glucomannan (%) >70 >75 >90 >95 Sulphur dioxide (g/kg) <1.6 – <0.3 <0.004 Loss on drying (%) <11.0 <12 <10 <8 Total ash <4.5 <5 <3 <2 Arsenic (mg/kg) <3 <3 <2 – Lead (mg/kg) <1 <2 <1 <1 Starch (%) – <3 – <1 Protein (%) – <3 – <1.5 Ether-soluble material – <0.1 – <0.5% Chloride – – – <0.02% Salmonella spp. – Absent in 12.5 g – Absent in 12.5 g E. coli – Absent in 5 g – Absent in 5 g Viscosity 22000 mPa/s >3 kg/m/s 32000 mPa/s >20 kg/m/s (1% solution) (1% solution)

2.10. Physicochemical Properties of Konjac Glucomannan

KGM is available in two general forms: as a powder and as a gel. In the powdered form, KGM is a high viscous soluble dietary fibre. KGM has a very high water holding capacity, where studies have reported retention of water up to 50-100 times its weight [103]. At concentrations below 7 to 8% w/w, KGM powder hydrated in an aqueous solution exhibits pseudoplastic or non-

Newtonian behaviour and is likely due to the formation of junction zones from hyper- entanglement of the KGM backbone [99,115]. The viscosity developed in 1-7% KGM solution exceeds other commonly known viscous fibres at similar concentrations such as xanthan gum and guar gum [103]. However, at concentrations below 0.55%, KGM solutions exhibit near-

Newtonian flow, which is not indicative of the viscous, gel-forming properties of KGM. These rheological properties, however, are dependent on the purity, concentration, and source of KGM

22 material. One study investigated the viscosity formation of 4 samples of KGM that were milled into different particle sizes this affects the hydration of the fibres [106]. The authors reported a faster time to reach peak viscosity with decreasing particle size.

The alternate form of KGM is in the form of a gel, which appears to have different physicochemical properties than the KGM powder. The characteristics of KGM-gels formed have been extensively studied in industrial and pharmacological applications [116-118]. Various methods can be used to achieve gelation, however, most methods rely on removing the acetyl groups that are present on the glucomannan chain [119]. Deacetylation occurs through changes in pH, either by the addition of an alkali (i.e. CaOH) or acidic coagulant, although alkali coagulants are preferred as acids can results in hydrolysis of the KGM chain [103]. Removal of the acetyl groups produces areas on the KGM chain free of steric hindrance, promoting hydrogen bonding, Coulombic forces, and many other hydrophobic interactions to form junction zones, establishing a rigid scaffolding for the KGM-gel that entraps water [120]. This method of gelation results in a thermo-irreversible gel that has been shown to be resistant to digestive enzymes. At concentrations greater than 8%, solutions of KGM will also form a solid gel due to hyper-entanglement, however, the resultant gel is thermo-reversible [103].

2.11. Macronutrient and Sensory Properties of Konjac Glucomannan

While both preparations of KGM exhibit different physicochemical properties, both KGM powder and KGM-gel have the same nutrient profile, containing only dietary fibre and trace amounts of carbohydrates and protein (Table 2). When fibre is matched, the energy content of is

23 the same for powder and KGM-gel, but the energy density (ED) would be different due to the gelation process entrapping water within the KGM-gel.

Sensory properties of KGM can depend on the purity. Unrefined KGM contains traces of protein and sulphurous compounds that give KGM an unpleasant, fish-like smell [16]. With refined samples with more than 95% KGM, the powder and resulting gel is odorless. Both forms are also tasteless and the KGM-gel has been described to have a firm and elastic texture. Refined KGM powder is white in colour and results in the formation of white, semi-translucent gels. Unrefined

KGM powder can range from yellow to grey in colour and can produce a dark grey or light brown gel.

Table 2 – Nutrient composition of konjac glucomannan preparations.

Nutrient Composition KGM Powder 3% KGM-Gel

Energy Content (kcal) 12.0 12.0

Available Carbohydrates (g) 0.0 0.0

Protein (g) 0.0 0.0

Fat (g) 0.0 0.0

Dietary Fibre (g)* 3.0 3.0

Weight (g) 3.0 100.0

Energy Density (kcal/g) 4.0 0.12

*Energy contribution of fibre was calculated as 4 kcal per gram.

2.12. History, Use, and Safety of Konjac Glucomannan

The discovery of KGM dates back to 206 BC in China, where it was later introduced to Korea by monks in 550 AD and then to Japan in 950 AD [121]. Production and trade of KGM became widespread in the 19th century and is now predominantly consumed in Japan and certain regions of China. With over a thousand years of traditional consumption, KGM is most commonly found in Japanese cuisine in the form of KGM-gel foods known in Japanese as “konnyaku”. Konnyaku foods can take on many different shapes, such as noodles (also known as “shirataki”) or cakes, and are often prepared in dishes such as sukiyaki and gyudon [122-124].

In North America and Europe, KGM was first introduced as a food additive. KGM received the

Generally Recognized as Safe (GRAS) status and was approved for use in the United States by the FDA in 1997. Approval was shortly followed by Canada and Europe in 1998. Since its approval, the unique rheological and gelling properties of KGM have been utilized as a binding agent and texture enhancer in the food industry for meat and seafood [118,125,126], as a controlled drug delivery system [102], and as a nutraceutical product in the form of encapsulated supplements [91,92]. In the food form, regulations for KGM as an additive have been extended to KGM-gel foods. However, the Food Standards Australia New Zealand has recognized KGM- gel as a traditional, non-novel food [127].

The consumption of KGM-gel foods have been gaining popularity among North American and

European consumers. KGM-gel foods have been featured in popular media outlets such as The

Huffington Post and the Daily Mail U.K [128,129]. Many commercial KGM-gel food products

25 reference the low energy and high fibre content of the KGM-gels, implicating its use as a weight management tool. The available shapes and variations in KGM-gel foods have also expanded.

Currently available forms of KGM-gel foods include imitation pastas of various shapes (shells, penne, and fettuccine), rice, imitation meats (pork, chicken, and sausages), imitation seafoods

(shrimps and scallops), and vegetables (peas, corn, and carrots). Other forms of KGM-gel foods have added tofu, soy, or oat based fibres to KGM to change the oro-sensory attributes of the

KGM-gel. These forms of KGM-gel foods are intended to be consumed in place of usual foods, which can lead to reductions in energy intake given the low energy content of KGM-gels.

Despite the long history of use in Asia, safety concerns have arisen regarding KGM-gel foods.

Case reports of esophageal and GI obstruction due to rapid hydration of KGM tablets have led to a recall of KGM powdered tablets on the market [130,131]. Additionally, reports of esophageal obstruction in children and the elderly were reported from the consumption of KGM-gel fruit flavoured snack [132]. Due to the small size of approximately 2 x 2 cm and the method of consumption, it posed a choking risk and has been banned in Europe, the United States, and

Canada. Other concerns regarding mild GI side effects have been reported due to the soluble fibre content, but most RCTs have reported that KGM is well tolerated [91].

Figure 2 – Konjac glucomannan gel foods. Unrefined konjac glucomannan gel cake (left) and unrefined konjac glucomannan gel shirataki noodles (right) prepared in a sukiyaki dish.

2.13. Health Benefits of Konjac Glucomannan

The majority of evidence on KGM and health are based on studies utilizing KGM powder. To our knowledge, no study to date has investigated the properties of KGM-gel on metabolic health.

Studies investigating KGM supplementation have reported various clinical benefits including improvements in obesity, hyperglycemia, hyperlipidemia, laxation, colonic health, and inflammatory outcomes [16]. A recent meta-analysis of 14 randomized clinical trials found that the use of KGM significantly improved total cholesterol by 0.50 mmol/L (95% CI: -0.63, -0.37),

LDL cholesterol by 0.41 mmol/L (95% CI: -0.55, -0.28), triglycerides by 0.13 mmol/L (95% CI:

-0.25, -0.01), body weight by 0.79 kg (95% CI: -1.53, -0.05), and fasting blood glucose by 0.41 mmol/L (95% CI: -0.79, -0.04) [91].

In line with the findings of the meta-analysis, the EFSA has approved two health claims for the use of KGM powder for health management. The expert panel concluded that there was enough evidence to support a cause and effect relationship between KGM powder and cholesterol

27 lowering (2009) and body weight regulation (2010) [133,134]. The panel concluded that there was insufficient evidence to support claims for improvements in triglycerides and fasting blood glucose. No health claims have been approved for use in Canada and the United States.

However, a recent meta-analysis of 8 RCTs on KGM powder supplementation and weight loss only in overweight or obese populations found non-significant results for weight loss, challenging the efficacy of KGM powder for weight loss [92]. Likewise, weight reduction of

0.79 kg in the previous meta-analyses, while statistically significant, may not be clinically meaningful given the modest weight reduction. Nevertheless, it is clear from the meta-analyses

[92] that there is a need for longer and higher quality KGM powder RCTs. The ineffectiveness of

KGM powder may be a shortcoming of viscous fibres when applied to a weight loss setting.

Viscous fibres rely on increasing intraluminal viscosity, decreasing gastric emptying and nutrient absorption rate, to increase satiety and alter the energy balance [12]. However, studies investigating viscous fibres in energy matched preloads have yielding conflicting results when assessing subsequent energy intake despite reducing appetite [135]. This may hinder the effectiveness of viscous fibres for weight loss. Additionally, the doses administered and recommended by EFSA for weight management are small (3 g per day). Larger intakes and direct methods to reduce energy intake may be more effective in achieving weight loss.

2.14. Potential of Konjac Glucomannan Gel for Energy Regulation

In contrast, KGM-gel exhibits different physicochemical properties than KGM powder and emerging evidence suggests that gelled dietary fibres may be more effective for reducing

28 appetite responses compared to powdered viscous fibres. This response has been demonstrated for pectin and agar, two gel-forming fibres that have a greater satiety value when administered as a gel [13,88,98]. The differences in appetite responses may be the result of differences in food form and its impact on satiety. It has been previous shown that apples in different forms, given with the same macronutrient profile and same volume, differentially affects satiety such that consuming the solid apple provided the greatest reduction in appetite response [136].

This effect of solid foods may be due to the antral forces exerted by the stomach during digestion. Studies using echo-planar magnetic resonance imaging (MRI) using agar gel beads of different fracture strengths found that gel beads with a higher firmness tends to induce greater satiety relative to fibre-gels with less strength, where the critical fracture strength resides > 0.65

N [96]. Gel beads requiring a force greater than 0.65 N to deform results in incomplete digestion and remains in the stomach longer due the sieving functions of the pyloric sphincter that restricts the passage of foods > 2 mm into the duodenum [96,137]. Thus, consuming a modest amount of high fracture strength foods may result in greater satiety than other foods by prolonged occupancy in the stomach. Studies investigating different preparation methods of commercial

KGM-gel foods found that a 3% w/w KGM-gel has a deformation or fracture strength between

0.8-1.6 N, well beyond the threshold of 0.65 N necessary to induce increased satiety [101].

In addition, the low energy content of KGM-gel and availability in various food forms will allow for discrete manipulations of meals to reduce the energy content while maintaining the amount of food consumed. Clinical investigations have shown that healthy, overweight, and obese individuals consume a consistent amount of food daily [138,139]. Reduction in the energy

29 content, thereby reducing ED, can reduce overall energy intake without increasing appetite ratings [140,141]. While many of these studies reduce the ED of meals by 20-30 % by discretely adding water, vegetables, or reducing the fat content in mixed meals, the addition of KGM-gel can greatly reduce ED with minimal effort if replacing a food such as noodles or rice [141].

Reduction in dietary ED has been shown to be an effective method in restricting energy intake and can predict weight loss [142].

CHAPTER 3. RATIONALE, OBJECTIVES, AND HYPOTHESES

3.1. Rationale

An effective and simple method to reduce energy intake in weight loss diets is needed. Dietary fibre-gels are emerging as a potential tool to assist in appetite regulation. Among different gel- forming fibres, KGM may have the greatest potential to suppress appetite given its unique physicochemical characteristics. While the physiological effects of KGM in the powdered form have been well characterized, little is known about KGM-gel despite its long history of consumption in China and Japan [16]. Available evidence suggests that fibre-gels made from

KGM may have strong satiating capacities due to its high firmness. This has been shown to delay gastric emptying and is correlated with sensations of fullness [96]. In addition, KGM-gels are very low in ED, possessing an ED of ~0.10 kcal/g. Low ED foods have been shown to promote satiety and reduce subsequent food intake during ad libitum meals [141]. However, unlike most strategies with low ED foods, KGM-gel can displace energy dense foods in large amounts, such as pasta and rice, without significantly altering the composition of the meal. This offers a simple and discrete method of reducing energy intake with minimal participant burden. However, no

RCT to our knowledge has quantified the appetite and subsequent energy response to consumption of KGM-gel foods. Given the very low energy content of the gel, overconsumption of KGM-gel may lead to unbearable hunger that limits the efficacy of KGM-gel foods or have adverse effects on the individual. Therefore, there is a need to characterize the acute appetite and energy responses to KGM-gel foods and assess the efficacy and safety of KGM-gel foods over single and repeated administrations.

Additionally, KGM-gels may achieve very low energy contents in meals without changing meal palatability or amount consumed. To investigate this, 3 levels of KGM-gel substitution will be

32 utilized based on the energy content: 0% energy reduction (control), 40% energy reduction with

KGM-gel foods, and 80% energy reduction with KGM-gel foods. This will allow observations of acute moderate to high energy restriction and characterize their effects on appetite and subsequent energy intake.

3.2. Objectives

The overall objective was to characterize the appetite and subsequent energy intake responses to single or repeated administration of KGM-gel foods in the context of low energy, volume controlled meals.

Study 1: To determine the effect of three levels of isovolumetric substitution of KGM-gel noodles on subsequent energy intake, cumulative energy intake, and appetite in healthy individuals.

Study 2: To determine the effect of three levels of KGM-gel substitution in a controlled diet over the course of a day on subsequent energy intake, cumulative energy intake, overall appetite, blood glucose, and blood pressure (BP) in healthy individuals.

3.3. Hypothesis

The overall hypothesis of the two studies was that all interventions would result in similar appetite and energy intake responses, leading to a reduction in total cumulative energy intake.

Study 1: It was hypothesized that isovolumetric substitution of energy dense pasta with energy sparse KGM-gel noodles will invoke a similar satiety response in subjective appetite ratings and subsequent energy intake in an ad libitum setting.

Study 2: It was hypothesized that replacement of energy dense foods in 4 meals over the course of a day with energy sparse KGM-gel foods will not increase the subjective appetite responses of each meal or subsequent energy intake post-visit. Cumulative energy intake would be lowest for the highest level of substitution.

CHAPTER 4. INVESTIGATION OF AN ISOVOLUMETRIC PRELOAD OF KGM-GEL

ON APPETITE AND ENERGY INTAKE

4.1. ABSTRACT

BACKGROUND: Konjac glucomannan (KGM) is a viscous dietary fibre that forms a solid, low energy gel when hydrated, commonly consumed in a noodle form. Recent studies have reported greater satiating effects when viscous fibres are consumed as a solid gel, but no studies to date have reported the appetite effect of a KGM fibre-gel when used to replace caloric foods.

OBJECTIVE: To primary objective was to evaluate cumulative energy intake after 90 min after replacing a high carbohydrate preload with KGM-gel noodles. Secondary outcomes were subsequent food intake and appetite sensations.

DESIGN: In a randomized, controlled, crossover design, 16 healthy individuals (12F/4M; age:

26±12 years; BMI: 23±3 kg/m2) were enrolled and received a 325 mL volume-matched preload of pasta (442 kcal, control), half pasta and half KGM (259 kcal, 50-KGM), or only KGM noodles (77 kcal, 100-KGM). Appetite over 90 min and ad libitum food intake was assessed.

RESULTS: Hunger was significantly higher for 100-KGM compared to control. Fullness was lower and prospective consumption was higher for 100-KGM compared to 50-KGM. Food and energy intake across all preloads were similar, resulting in a net caloric deficit of 201 and 421 kcal in cumulative energy intake for 50-KGM and 100-KGM, respectively. Palatability was similar across all treatments.

CONCLUSION: Replacement of a high carbohydrate preload with a very low energy KGM-gel did not promote food intake in healthy individuals at a subsequent meal. The caloric deficit incurred from the volume-matched preloads may have relevance in weight loss regimes and further studies should evaluate whether the effects of KGM-gel extend beyond the healthy population.

ClinicalTrials.gov identifier: NCT01875627

4.2. INTRODUCTION

Sustained overeating and physical inactivity often leads to increased body weight. Despite numerous advances in dietary and lifestyle approaches, body weight regulation remains challenging. One major obstacle when adhering to a calorie-restricted diet is to endure hunger, a predictor of success for long term weight loss and maintenance [60,143].

Several promising approaches for appetite regulation have emerged, including the consumption of low ED foods, increased intake of dietary fibre, and taking advantage of the food matrix, such as the physical form or viscosity of the meal [65,94,141]. While several foods have been identified to possess some of these characteristics, few alternatives are available when replacing high energy foods in the diet without any major dietary or meal sensory modifications. An emerging novel food that embodies all three approaches is fibre-based gel food analogues, in particular, those made from KGM.

KGM is a highly viscous dietary fibre derived from Amorphophallus konjac, with a long history of use as a traditional food and industrial additive in Eastern Asia [16]. At low concentrations,

KGM is capable of forming a strong gel that is over 95% water with the rest being fibre, representing one of the lowest ED foods available [103]. The gel can be formed into various shapes such as long strands popularly known as “shirataki noodles”, which can be used to replace starchy noodle-like foods to reduce calories in a meal without changing the volume of food consumed. In addition, KGM is a neutral fibre that has been shown to be resistant to acid degradation while the gel possesses a firmness exceeding the strength typically exerted by the

38 stomach during digestion [96,144,145]. This additional property may independently attenuate appetite responses.

Despite these promising characteristics, no study to date has investigated the role of KGM-gel foods on appetite and satiety regulation in a controlled clinical setting. It is also unclear whether the caloric deficit incurred from substituting caloric foods with KGM foods will be compensated at a subsequent meal, abolishing its effectiveness as a potential weight management tool.

Therefore, we sought to evaluate the effects of substituting KGM-based shirataki noodles in place of a high carbohydrate, caloric preload of equal volume on subjective satiety and subsequent food intake in healthy individuals

4.3. METHODS

4.3.1. Participants

Healthy participants were recruited into the study by advertisement flyers placed on the campus of the University of Toronto and in St. Michael’s Hospital, Toronto, Canada. Individuals who responded to the advertisements were interviewed by telephone to ensure they met the initial criteria for inclusion into the study: age 18 to 65 years, body mass index (BMI) between 18 to 30 kg/m2, no presence or known history of major diseases, not using prescription medication and/or natural health products during the study period, not pregnant or lactating, no known food allergies and weight stable for the past 2 months.

Potential participants meeting the initial criteria were invited to the clinic, where anthropometrics

(height, weight, % body fat) were taken, and several questionnaires were completed regarding dietary and lifestyle regimens. All participants gave informed written consent before participating. The study was approved by the St. Michael’s Hospital Research Ethics Board and was conducted at the Risk Factor Modification Centre, St. Michael’s Hospital (Toronto, Canada).

The trial protocol was registered with ClinicalTrials.gov, identifier NCT01875627.

4.3.2. Design

In a randomized, controlled, crossover design, participants were administered 1 of 3 intervention preloads in a randomized sequence determined by a random number table generated by a

40 statistician. Participants visited the clinic between 8:00 am to 10:00 am after a 10-12 hour overnight fast on three separate occasions separated by a washout period of at least two days.

Upon arrival at the clinic, participants were seated in a quiet, isolated area for the remainder of the visit. Participants were told to maintain their usual dietary and lifestyle regimens during the study period and this was assessed by a questionnaire. Baseline (0 min) appetite and symptoms were recorded and the preloads were served subsequently. Participants rated the palatability of the preload immediately after finishing and appetite and symptoms questionnaires were completed at 15, 30, 45, 60, 75, and 90 min after the first bite of the preload. Participants were given 15 min to consume the preload and water served. Participants were only allowed to consume the foods given to them at the clinic. Immediately after completing the appetite and symptoms questionnaires at 90 min, participants were offered an ad libitum dessert. Dessert was served in 150 g portions and participants were told to consume as much of the dessert as they desired until they felt comfortably full. Preload and dessert meals were served with ad libitum water in portions of 240 g and the same amount of water was served with the respective meal during subsequent visits for each participant. All food and drinks served were weighed using a digital scale to the nearest 0.1 g before and after serving to determine the intake of food.

4.3.3. Study Materials

Macronutrient composition and characteristics of the preloads are described in Table 1. The intervention preloads were the following: 1) cooked pasta noodles (control); 2) volume matched substitution of half (50-KGM) cooked pasta noodles with KGM-gel noodles; 3) complete volume matched substitution (100-KGM) of cooked pasta noodles with KGM-gel noodles. This resulted

41 in an energy reduction of 40% and 80% in the 50-KGM and 100-KGM preloads compared to the control, respectively. Preloads were matched for volume and food form and were mixed with rosèe pasta sauce prior to serving. All preloads were cooked and prepared on the same day as the clinical visit. The ad libitum dessert consisted of bite-sized (~1 inch) pieces of hazelnut- flavoured wafer cookies (Quadratini Wafer Cookies, Loaker ©, Italy). All study materials were commercially available food products purchased from a local supermarket and were prepared according to the instructions found on the manufacturer’s label.

Table 3 – Composition and characteristics of the preloads.

Preloads Control 50-KGM 100-KGM Ingredients Cooked Pasta Noodles1 (g) 220.0 110.0 0.0 Konjac-gel Noodles2 (g) 0.0 122.5 245.0 Pasta Sauce3 (g) 80.0 80.0 80.0 Nutrients* Energy Content (kcal) 441.5 259.2 76.8 Energy Density (kcal/100g) 147.2 82.9 23.6 Available Carbohydrates (g) 80.5 43.5 6.4 Protein (g) 14.9 8.4 1.9 Fat (g) 6.9 6.0 5.1 Dietary Fibre (g) 6.5 7.3 8.0 Weight (g) 300.0 312.5 325.0 Volume (mL) 325.0 325.0 325.0 *Adapted from the nutrition facts table presented on the manufacturer’s packaging.

1Spaghetti, Barilla America Inc., Illinois, USA.

2Shirataki, Ontario, Canada.

3Irresistibles ©, Montreal, Quebec, Canada.

4.3.4. Measurements

Participants completed appetite questionnaires in the form of 100mm visual analogue scales

(VAS) assessing four subjective appetite sensations: desire to eat, hunger, fullness and 42 prospective consumption. Each VAS were anchored on both sides with descriptors adapted from

Blundell et al [53]. The appetite sensations recorded prior to serving the preload were used as baseline (0 min) measurements and appetite sensations after the first bite of the preload were recorded every 15 min thereafter until 90 min. Response of the appetite sensations to the preloads were evaluated by calculating the AUC after 90 min using the trapezoid method [146].

To investigate the efficiency and capacity of the preload to influence appetite sensations, the satiety quotient (SQ) was calculated for each appetite sensation, except for sensations of fullness, at each postprandial time measured following the equation adapted from Green et al [58]:

푏푎푠푒푙𝑖푛푒 푎푝푝푒푡𝑖푡푒 (푚푚) − 푝표푠푡푝푟푎푛푑𝑖푎푙 푎푝푝푒푡𝑖푡푒(푚푚) 푆푄(푚푚/푘푐푎푙) = 푒푛푒푟푔푦 푐표푛푡푒푛푡 표푓 푡ℎ푒 푝푟푒푙표푎푑(푘푐푎푙)

The appetite sensation of fullness used a reversed SQ where [postprandial appetite (mm) – baseline appetite (mm)] was used instead to facilitate the comparison between the other appetite sensations. A higher SQ for each appetite sensation would represent a greater satiety response and a lower SQ would represent a weaker satiety response because the SQ accounts for baseline appetite sensations and the energy content of the preload.

GI symptoms of bloating, belching, diarrhea, flatulence and nausea were reported using a

100mm VAS at each time interval appetite sensations were measured. VAS were anchored with the descriptors “low” and “high” on the left and right ends of the VAS, respectively.

Preload palatability was measured using a 100mm VAS immediately after consumption of the preload anchored with the phrases “very unpalatable” to “very palatable” on the left and right ends of the VAS, respectively.

4.3.5. Statistical Analysis

The primary outcome measured was energy compensation defined as the energy intake 90 min after preload administration. Total food intake (g and kcal), appetite sensations (baseline, 90 min

AUC and SQ), palatability ratings and GI symptoms were evaluated as secondary outcomes. A composite score for appetite (CS) adapted from a previous study [87] was calculated to reflect the overall effect of the preload on satiety using each appetite sensation based on the following:

ℎ푢푛푔푒푟 + 푑푒푠𝑖푟푒 푡표 푒푎푡 + (100 − 푓푢푙푙푛푒푠푠) + 푝푟표푠푝푒푐푡𝑖푣푒 푐표푛푠푢푚푝푡𝑖표푛 퐶푆 = 4

Data are presented as means and SEM. All statistical procedures were performed using the

Statistical Analysis System software package, University Edition (SAS Institute Inc., Cary, NC,

USA). Results were considered significant at p < 0.05. Data normality was assessed visually and using the Shapiro-Wilk procedure. The effect of the interventions on appetite was assessed using a mixed model ANOVA (proc mixed, SAS) with preload, time, and time*preload interaction as fixed factors and participants as the repeated factor. Pairwise analyses were conducted to assess the differences between interventions and adjusted for multiple comparisons using the Tukey-

Kramer method for multiple comparisons. Mean appetite, AUC for appetite, mean SQ, time to eat, palatability, subsequent energy intake and cumulative energy intake were assessed with a

44 similar procedure without time and its interactive factor. For all appetite measures, baseline fasting (0 min) values were included as a covariate to adjust for the variability between intervention days and individuals. For symptoms, data were grouped by presence and assessed using a chi square test.

In order to detect a significant difference in subsequent food intake of 120 kcal between a single pairwise comparison, 16 subjects were required to detect differences in subsequent energy intake with 80% power and a 2-tailed level of significance at a level of p< 0.05 (α=0.05 and 1-β=0.8) based on a power and reproducibility study of ad libitum energy intake in healthy individuals

[147].

4.4. RESULTS

4.4.1. Participants

Sixteen participants (12F: 4M; age: 26.0 ± 11.8 years; BMI: 23.1 ± 3.2 kg/m2) were enrolled in the study. All participants completed the study and were compliant with the study protocols. No significant changes in body weight or body fat occurred over the duration of the study (data not shown). Participants did not report any significant changes to diet or physical activity levels during the study period.

4.4.2. Energy Intake

Despite significant energy differences of the preloads, energy intakes during dessert 90 min later were similar between interventions (Figure 3, effect of treatment: p = 0.71). Subsequent energy intake was 366.8 ± 34 kcal for control, 390.1 ± 34 kcal for 50-KGM and 394.9 ± 34.3 kcal for

100-KGM. No differences in food intake was observed (100-KGM: 75.7 ± 7 g, 50-KGM: 74.7 ±

7 g, and Control: 70.3 ± 7 g). Cumulative energy intake across the two meals (preload and dessert) remained significantly different for 50-KGM (-201 ± 142 kcal, p < 0.001) and 100-KGM

(-421 ± 150 kcal, p < 0.001) relative to control.

Subsequent Intake Cumulative Intake 1000 a

b 800 Preload c 600 Dessert

400 Energy Energy Intake (kcal) 200

0 Control 50-KGM 100-KGM Control 50-KGM 100-KGM

Preload

Figure 3 – Subsequent energy intake at 90 min after preload administration. Cumulative intake was defined as the total energy intake from the preload and the subsequent meal. Data are expressed as mean and SEM. Preloads with different letters are significantly different (p < 0.05, Tukey adjusted).

4.4.3. Appetite Sensations

Appetite sensations at individual time points are presented in Figure 4 and mean appetite sensations are presented in Table 4. A significant effect of time (p < 0.001) and preload (p <

0.001) was observed for all appetite measures, but no interaction effect was observed. Mean ratings for hunger was significantly higher when comparing 100-KGM to control (10 ± 4 mm, p

= 0.04). Mean ratings for prospective food consumption was significantly lower when comparing

50-KGM to 100-KGM (9 ± 3 mm, p = 0.03). When comparing the AUC for appetite measurements, 100-KGM increased hunger (% difference from control: 31%, p = 0.035) compared to control and 100-KGM decreased fullness (% difference from 50-KGM: 19%, p =

0.042) and increased prospective food consumption (% difference from 50-KGM: 28%, p =

0.031) when compared to 50-KGM. No other significant differences were detected.

The satiating capacity of each preload was also assessed with the SQ, where changes in appetite ratings were expressed as a factor of energy intake in Table 4. The mean SQ was significantly higher for 100-KGM for all appetite measurements when compared to both 50-KGM and control preloads (p < 0.0001) and no differences were detected among other preloads.

48 a) Control b) 80 50-KGM § 80 § 100-KGM * * 70 70 * * 60 60 § 50 50 40 40

30 30 Hunger Hunger (mm)

20 20 Desire Desire to eat (mm) 10 10 0 0 0 15 30 45 60 75 90 0 15 30 45 60 75 90 Time Time c) d) § 90 80 * 80 70 § 70 60 § 60 50 50 40 40 30 30 Fullness(mm) 20 20 10 10 0 0 0 15 30 45 60 75 90 Prospective consumption (mm) 0 15 30 45 60 75 90 Time Time e) 90

80 § * 70 60 § 50 40 30 20 Composite Composite score (mm) 10 0 0 15 30 45 60 75 90 Time

Figure 4 – Mean appetite ratings over 90 min. Data presented are means and SEM on a) desire to eat, b) hunger, c) fullness, d) prospective consumption, and e) composite score in 16 healthy individuals. Significance is denoted by * between 100-KGM vs. control and § between 50-KGM vs.100-KGM (p<0.05).

Table 4 – Mean ratings of appetite measurements over 90 min in 16 healthy participants.

Appetite Sensation Control 50-KGM 100-KGM Mean Appetite (mm) Desire to Eat 39 ± 4 39 ± 4 47 ± 4 Hunger 37 ± 4a 38 ± 4ab 47 ± 4b Fullness 55 ± 5 56 ± 5 46 ± 5 Prospective Consumption 39 ± 4ab 38 ± 4a 47 ± 4b Composite Score 40 ± 4 40 ± 4 49 ± 4 Mean Satiety Quotient (mm/kcal) Desire to Eat 0.092 ± 0.03a 0.148 ± 0.03a 0.616 ± 0.03b Hunger 0.093 ± 0.03a 0.147 ± 0.03a 0.619 ± 0.03b Fullness 0.123 ± 0.04a 0.214 ± 0.04a 0.595 ± 0.04b Prospective Consumption 0.092 ± 0.03a 0.144 ± 0.03a 0.608 ± 0.03b Composite Score 0.096 ± 0.03a 0.153 ± 0.03a 0.636 ± 0.03b AUC after 90 min (mm x min) Desire to Eat 3123 ± 376 3113 ± 375 3909 ± 375 Hunger 3009 ± 394a 3109 ± 389ab 3954 ± 393b Fullness 5257 ± 452ab 5429 ± 454a 4423 ± 455b Prospective Consumption 3229 ± 374ab 3046 ± 374a 3909 ± 373b Composite Score 3284 ± 386 3234 ± 384 4054 ± 386 Data presented as mean and SEM. AUC – Area under the curve. Different letters within each row are significantly different (p < 0.05).

4.4.4. Other Measures

Palatability ratings between the preloads and the time taken to consume the preloads were not significantly different (Table 5). All preload interventions were well tolerated. The frequency of GI symptoms was not statistically different between preloads (

Table 6).

Table 5 – Mean palatability and time to consume preload in 16 healthy individuals.

Other Measurements Control 50-KGM 100-KGM

Palatability (mm) 71.5 ± 7 62.9 ± 7 56.7 ± 7

Time to Consume Preload (min) 13.2 ± 1 11 ± 1 11.9 ± 1

Data are expressed as mean and SEM.

Table 6 – Presence of symptoms during preloading in 16 healthy individuals.

Symptoms Control 50-KGM 100-KGM Anxiety 0 0 0 Belching 1 3 2 Bloating 3 2 5 Cold Hands and Feet 0 0 0 Poor Wound Healing 0 0 0 Diarrhea 0 0 0 Disorientation 0 0 0 Dizziness 0 0 1 Flatulence 0 2 3 Headache 0 0 0 Nausea 0 0 1 Excessive Urination 0 0 0 Other 0 0 0 Data are presented as frequency of presence during the clinical visit.

4.5. DISCUSSION

To our knowledge, the present study is the first to investigate substituting KGM-gel food analogues into a meal on appetite sensations and subsequent food intake. KGM-gels are made by dispersing a small amount of KGM fibre into water and adding a mild alkalizing agent to induce gelation. As a result, the composition of KGM-gels is over 95% water, giving it a very low ED.

We hypothesized that substituting energy dense pasta with KGM-gel noodles would lead to greater hunger sensations and caloric compensation at the subsequent meal due to the large differences in caloric and macronutrient content between the preloads. Appetite sensations were not different between the control and 50-KGM, but sensations of hunger were higher and fullness was lower when compared to the 100-KGM preload, respectively. However, no differences in subsequent food intake at 90 minutes were detected amongst all preloads. This led to an overall reduction in cumulative energy intake across the treatment period.

One possible explanation for the comparable subsequent energy intake between preloads is the different amounts and types of dietary fibre present among the preloads. Several reviews have suggested that increased fibre intake is associated with greater satiety and reduced energy intake when provided in an isocaloric setting [11,12,80,135]. In particular, viscous soluble fibres appear to be the most effective as they can increase the viscosity of the digestive contents to promote satiety by lowering the gastric emptying rate and modifying nutrient kinetics [94]. The KGM fibre used in the present study is known to be one of the most viscous plant derived fibres [144], while the fibre content present in the control is non-viscous. In a previous study using a similar preloading design, we demonstrated that a 5 g mixture of fibres containing KGM in a powdered

52 form that has been shown to maximize its viscosity did not affect satiety, but reduced food intake at 90 minutes compared to an insoluble fibre control [87]. While the effect of satiety was poor at the highest level of KGM-gel substitution, likely due to the large deficit in calories, the 8 g of viscous fibre in the 100-KGM preload may have reduced subsequent food intake to a comparable amount similar to the previous study. However, given that the KGM-gel develops its viscosity and forms a gel outside of the stomach, it is unclear if it continues to act as a viscous fibre upon ingestion as the literature investigating the metabolic effects of KGM-gels is sparse. Evidence from other gel-forming fibres, such as pectin and agar, suggest that fibre-gels can increase subjective ratings of fullness without reductions in caloric intake [13,88]. However, the preloads used in other fibre-gel studies are often energy-matched, thus an energy-deficient fibre-gel similar to those used presently may not produce the same satiety effect.

Matching for volume between the preloads may have also contributed to comparable energy intakes during the subsequent meal. Food volume has been observed to be an independent predictor of short-term energy intake in acute studies of similar design. Increasing meal volume leads to greater gastric distention that triggers afferent vagal signals that promote satiety [140].

This claim is supported by studies investigating satiety and food intake after ED manipulations in energy-matched preloads and from intragastric infusion studies that bypass oro-sensory cues of satiety [148-150]. While this may explain the comparable energy intakes, it is insufficient to explain the differences in appetite sensations observed after 100-KGM.

Investigations utilizing MRI have reported greater delays in gastric emptying by increasing the energy content of a meal by as little as 100 kcal, regardless of the volume administered [151].

Delays in gastric emptying are consistently associated with increased satiety and suggest that the appetite response presently observed is driven by the presence of macronutrients rather than the volume of the meal. In this context, it would be more appropriate to assess the satiating capacity of the preloads than the absolute effect on satiety, as energy intake is the primary concern for weight management [58]. The present study showed that the SQ, which assesses the change in appetite sensations per kcal consumed, was significantly higher for 100-KGM than control or 50-

KGM. This suggests that satiety increases at a faster rate for 100-KGM than the other preloads when energy intake is matched. While the evidence on the clinical importance of the SQ is sparse, the SQ for fullness has been suggested to predict energy intake in free-living individuals

[60,152].

It has also been proposed that fibre-gels, such as KGM-gel, may possess unique properties that can assist in appetite and energy regulation. Marciani et al. [96] used magnetic resonance imaging on agar fibre-gels of varying strengths and found that a firm gel exceeding 0.65 N in facture strength were retained in the stomach longer and was correlated with a greater feeling of fullness compared to fibre-gels of a lower strength. The authors concluded that 0.65 N likely exceed the force exerted during mechanical digestion, leading to incomplete gel digestion and greater retention within the stomach. This can increase gastric distention and is likely a unique property of certain fibre-gels as most foods are susceptible to acidic degradation, reducing firmness. While the strength of the KGM-gels in the present study were not directly measured, commercially prepared KGM-gels report a strength ranging between 0.8-1.6 N, which may explain the lack of energy compensation [101,153]. Alternatively, this high gel strength may have altered the oro-sensory attributes between the preloads, leading to greater oral exposure that

54 affects satiety and food intake [135,154]. However, this effect in the present study may be small as palatability and mean eating time between preloads were not significantly different.

Since the energy intakes at the subsequent meal were similar, the caloric deficit between the preloads was maintained when the cumulative energy intake was calculated (~201 kcal for 50-

KGM and ~421 kcal for 100-KGM). Comparing across various preloading methods, the cumulative reductions observed between 100-KGM and control preloads were higher than those seen with viscous dietary fibre supplementation of higher meal volumes, or preloads with a similar volume and ED (~0.3 kcal/g in ~300 mL) achieved through fat reduction or increased vegetable consumption [87,155]. In the form currently administered in the study, the noodle shape allows for discretionary replacement of a commonly consumed high carbohydrate food to decrease mealtime energy intake. Taking into consideration that palatability was not significantly different between the preloads, KGM-gels may potentially be a dietary tool to reduce daily caloric intake without affecting the type or amount of food consumed, increasing compliance to weight management diets.

Based on the present results, it is unclear whether the caloric deficit introduced from the preloads will be sustained beyond the subsequent meal. A reduction in caloric intake introduced by low

ED foods have been shown to be sustained over several days in healthy individuals [156].

Repeated consumption of fibre-gels may have a similar effect but available clinical evidence is sparse. One study supplemented pectin fibre-gels for 15 days and only observed a modest increase in fullness with no reduction in overall energy intake [14]. However, the pectin gel were calorie matched with the control and was likely more susceptible to mechanical digestion, as

55 indicated by the gel strength of ~0.36 N reported in the study. Alternatively, the dietary fibres found in fibre-gels may increase production of short chain fatty acids through fermentation by the gut microbiota, which can influence satiety hormones such as PYY and GLP-1 [157]. As

KGM-gels have been shown to be fermentable in vitro with a profile similar to the un-gelled form, KGM-gels have the potential for long term caloric management given the fermentation profile and high gel strength [158-160]. Additional benefits of extended KGM consumption may include reductions in LDL cholesterol, systolic BP, and improvements in glycemic control in individuals with T2DM, metabolic syndrome and healthy individuals [161-164]. However, these metabolic benefits have only been attributed to the viscous, powdered form and future studies should investigate whether these benefits extend to KGM-gels.

Several limitations to the present study should be acknowledged. Firstly, a negative control was not used to determine ad libitum food intake in the absence of a preload [53]. While several studies have reported reduced ad libitum food intake after preloading, the addition of the preload calories resulted in higher caloric intake than the no preload condition. However, as the KGM- gel contributes negligible calories to the preload, the total caloric intake of the 100-KGM condition is unlikely to exceed a negative control. Secondly, the use of a dessert to assess ad libitum food intake may have masked true differences in energy intake as sweet foods are high in

ED and are associated with overconsumption. While this is a concern, the susceptibility to overconsume appears to be more associated with sweetened beverages [165]. In equally palatable meals, difference in ad libitum energy intake between sweet and savoury foods appears to be negligible in healthy individuals [166].

In conclusion, KGM-gel noodle substitution resulted in a reduction of cumulative caloric intake without altering meal palatability. Due to the soluble fibre content, very low ED, and its ability to replace common high carbohydrate foods such as pasta without changing meal volume, KGM- gels hold great promise for appetite and food intake regulation and may potentially introduce a new tool for body weight regulation.

CHAPTER 5. KONJAC GLUCOMANNA GEL SUBSTITUTION OVER A DAY ON

APPETITE AND SUBSEQUENT ENERGY INTAKE

5.1. ABSTRACT

Introduction: Konjac glucomannan (KGM) is a viscous dietary fibre that has the capacity to form a high fibre, firm gel (KGM-gel) with a very low ED. The resultant gel can be molded into various food shapes and be discretely incorporated into meals to promote satiety and reduce energy intake.

Objective: The primary objective was to assess three substitution levels of KGM-gel foods into meals over the course of a day on cumulative appetite ratings. Secondary outcomes include cumulative energy intake, palatability, blood glucose, and BP.

Methods: In a randomized, crossover, controlled design, 20 participants (age: 31.6±12.0, M/F:

9/11, BMI: 25.4±4.7) completed the study. The intervention assessed three levels of KGM-gel substitution, each consisting of 4 meals over 12 hours: a control with no KGM-gel substitution

(1859 kcal), energy reduction by 40% (40-KGM) and 80% (80-KGM) with KGM-gel substitution. Appetite measurements were collected and subsequent energy intake was recorded for 12 hours post-visit.

Results: Appetite suppression was ~25% greater after control intervention than 80-KGM over

12h (p<0.01) with no differences observed for 40-KGM. However, KGM interventions were more efficient at suppressing appetite per calorie or gram of food intake. Despite a 1480 kcal energy deficit between 80-KGM and control, incomplete compensation post-visit occurred for all

KGM interventions, leading to a cumulative reduction in overall caloric intake for 40-KGM and

80-KGM of 625 and 1129 kcal from control (p<0.001).

Conclusions: KGM-gel foods may assist in reducing daily energy intake by substituting for energy dense foods without altering palatability despite modest increases in appetite.

ClinicalTrials.gov Identifier: NCT02134938.

5.2. INTRODUCTION

The prevalence of overweight and obesity continues to rise worldwide. The first line of treatment recommended for weight management is a dietary approach to maintain or promote a negative energy balance [23]. While no dietary pattern has been met with wide success for weight loss, several promising strategies have been suggested to reduce food intake and promote satiety

[135,167,168].

Increasing the intake of dietary fibres is among one of many suggested methods to promote weight loss. It has been proposed that increasing the intake of dietary fibre by 14 g per day is associated with a 10% reduction in energy intake and a weight loss of 1.9 kg over 4 months [80].

Acute reductions in energy intake through fibre consumption have been well documented and appear to be most effective with viscous soluble dietary fibres [83]. However, a recent study investigating the satiating properties of a gel-forming fibre found that satiety was greatest when the fibre was administered as a solid gel when compared to a mildly viscous or a highly viscous, but non-gelled form [13]. While no differences in energy intake was observed, a stronger gel- forming fibre may have a greater satiating effect, reducing energy intake.

Konjac glucomannan (KGM) is a highly viscous, gel-forming soluble fibre derived from a perennial Asian plant. Under alkali conditions after being dissolved in water, KGM forms a gel that is stronger than most other gel-forming fibres [16]. As only a small amount of KGM is needed to make the KGM-gel, the resulting gel consists of ~97% water and the rest as KGM fibre, yielding a very low ED of ~0.10 kcal/g. The KGM-gel is odourless and tasteless and can be molded into various food shapes such as pastas and rice to be discretely incorporated into

60 typical meals. This can displace the energy content of common food staples, reducing the ED of the diet, which assists in the suppression of appetite and overconsumption [141].

Despite the potential to greatly reduce the energy content of the diet, few clinical studies have evaluated KGM-gel for its role on appetite and food consumption. Additionally, as KGM-gels are most commonly available as noodles or rice, individuals that choose to replace all their typical foods with KGM-gel foods would greatly reduce the energy content of their diet with small changes to the portions consumed. However, the appetite, food intake, and potential adverse effects for extreme levels of KGM-gel substitution are unknown. Therefore, we aimed to assess the effect of KGM-gel substitution into a metabolically controlled diet on parameters of appetite and food intake in healthy individuals over the course of a day.

5.3. METHODS

5.3.1. Participants

Twenty two healthy individuals were recruited by paper and online advertisements in the city of

Toronto, Canada. The criteria for inclusion into the study included age between 18 to 70 years, body mass index (BMI) between 18 to 29.9 kg/m2, unrestrained eaters as identified by a score less than or equal to 10 on the Three Factors Eating Questionnaire (TFEQ) [169], and were willing to consume the foods served in the study. Potential participants were excluded if they have a known presence or history of major diseases, are using prescription medication and/or natural health products that may impact appetite during the study period, pregnancy or lactating, have known food allergies to study products or has experienced a weight change > 3 kg within the past 2 months. All participants gave informed written consent before participating. The study was approved by the St. Michael’s Hospital Research Ethics Board and was conducted at the

Risk Factor Modification Centre, St. Michael’s Hospital (Toronto, Canada). The trial protocol was registered with ClinicalTrials.gov, identifier NCT02134938.

5.3.2. Design

This study followed a randomized, controlled, crossover design with repeated measures within participants with 3 treatment arms. The order of administration was randomized by a random number table generated by a statistician and each participant was allocated to one sequence.

Participants attended the clinic between 8:00 AM to 10:00 AM after a 10-12 hour overnight fast on 3 separate occasions with a minimum of 2 days separating clinical visits to minimize potential

62 carry over effects. Upon arrival at the clinic, participants were seated in a quiet isolated area for the remainder of the visit. Participants were asked to maintain their usual dietary and lifestyle habits between visits and to refrain from conducting any vigorous exercise prior to the study visit, which was assessed by a self-administered questionnaire. On each test day, participants were provided with all their food and beverages over a 12 hour period. For the duration of the study, participants were asked to remain within the clinic. Participants were allowed to do light deskwork and browse the internet.

At each clinical visit, an intervention arm was administered consisting of 4 meals: a breakfast, lunch, snack, and dinner. The breakfast and the lunch were separated by 4 hours apart and the remaining meals were each separated by 3 hours apart. During the first visit, participants were allowed to have a beverage of their choice in the form of water, coffee, or tea with the option of

30 mL of milk and a non-caloric sweetener up to 45 min prior to the lunch, snack or dinner meal.

If the participants chose to have a beverage, the same beverage was administered during subsequent visits at the time. After consumption of the dinner meal, participants were allowed to depart from the clinic, but were instructed to not consume any additional foods until 2 hours after the dinner meal. After the study visit, participants were issued a 12 hour food record to record any energy intake post-visit.

5.3.3. Interventions

Estimates of typical daily caloric intake for each individual were collected by a 3-day food record prior to the first study visit. Intakes from individual days were averaged to provide an

63 estimate of daily caloric intake. These values were used to adjust to each intervention arm to account for differences in habitual eating.

The meal composition of the interventions is presented in Table 7 and the nutrient composition presented shown in Table 8. Three interventions were evaluated: a control where individuals consumed their usual daily caloric intake, a similar intervention where some of the foods were replaced with KGM-gel foods (40-KGM), and a similar intervention with a high level of replacement with KGM-gel foods (80-KGM). KGM-gel foods used in the intervention were

KGM-gel cubes to replace rice, KGM-gel noodles to replace pasta, and KGM-gel shrimp to replace the vegetarian chicken. The aim of the intervention levels was to reduce the overall caloric intake during the meals by 40% with 40-KGM and by 80% with 80-KGM. However, due to the potential GI side effects with the high amounts of dietary fibre administered in the 80-

KGM intervention (46 g), KGM-gel substitution was limited. This led to a reduction in the amount of food served by 16% in 40-KGM and 40% in 80-KGM when compared to control.

Each intervention consists of 4 meals: a breakfast, lunch, snack, and dinner. The same meal served for the breakfast was served as the snack meal and the same meal served as the lunch was served as the dinner meal to observe potential repeated effects of consumption. All study materials were commercially available food products purchased from local supermarkets and were prepared according to the instructions found on the manufacturer’s label. All interventions were cooked and prepared on the same day 30 min prior to each meal, except for the rice, which was prepared the night prior and refrigerated at 4oC until use. All meals were served with 250

64 mL of water. All food and drinks served were weighed using a digital scale to the nearest 0.1 g before and after serving to determine the intake of food.

Table 7 – Composition of intervention meals.

Control 40-KGM 80-KGM Breakfast/Snack Ingredients (g) Mixed Berry Puree1 153.3 106.7 60.0 Mixed Berries1 97.6 73.8 50.0 Evapourated Milk2 83.6 56.8 30.0 Instant Rice3 116.2 58.1 0.0 Konjac Gel4 0.0 35.0 70.0 Total Served (g) 450.7 330.4 210.0

Lunch/Dinner Ingredients (g) Cooked Pasta5 92.9 46.5 0.0 Vegeterian Chicken Breast6 45.5 22.8 0.0 Mixed Vegetables7 192.4 140.2 0.0 Konjac Noodles8 0.0 77.0 154.0 Konjac Shrimp9 0.0 53.0 105.0 Pasta Sauce10 185.9 142.9 100.0 Total Served (g) 516.7 482.4 359.0 1President’s Choice 4-Berry Blend (Loblaws Inc., Ontario, Canada)

2Carnation (Smucker Foods of Canada Corp., Ontario, Canada)

3President’s Choice 5 Minute Enriched Long Grain Instant Rice (Loblaws Inc., Ontario, Canada)

4Shirataki (Ontario, Canada)

5Spaghetti (Barilla America Inc., Illinois, USA.)

6President’s Choice Blue Menu Vegetarian Chicken Breast (Loblaws Inc., Ontario, Canada)

7President’s Choice Frozen California Mix (Loblaws Inc., Ontario, Canada)

8Shirataki Noodles (Wellbond Import Export Inc., Ontario, Canada)

9Sophie’s Kitchen Vegan Prawns (Sophie’s Kitchen Inc., California, USA)

10Victoria Marinara Sauce (Victoria Fine Foods, New York, USA.)

Table 8 – Nutrient composition of intervention meals.

Control 40-KGM 80-KGM Breakfast/Snack Energy (kcal) 389.9 251.0 110.0 Total Carbohydrate (g) 72.4 44.8 18.3 Fat (g) 6.3 4.7 2.5 Protein (g) 10.9 7.5 3.6 Dietary Fibre (g) 9.0 7.5 7.8 Total Served (g) 450.7 330.4 210.0 Energy Density (kcal/g) 0.86 0.76 0.52

Lunch/Dinner Energy (kcal) 557.7 277.1 113.0 Total Carbohydrate (g) 84.5 43.7 19.9 Fat (g) 12.7 6.6 3.1 Protein (g) 26.4 10.7 1.5 Dietary Fibre (g) 10.6 10.7 12.2 Total Served (g) 516.7 482.4 359.0 Energy Density (kcal/g) 1.08 0.57 0.31

Overall Intake Energy (kcal) 1895.6 1057 447.2 Total Carbohydrate (g) 313.8 177 76.4 Fat (g) 38 22.6 11.2 Protein (g) 74.6 36.4 10.2 Dietary Fibre (g) 39.2 36.4 40 Total Served (g) 1935 1625 1138 Energy Density (kcal/g) 0.98 0.65 0.39 Nutrient information adapted from manufacturer’s packaging.

5.3.4. Procedures

During all meals, baseline (0 min for each respective meal) blood glucose, appetite, and symptoms were recorded and the meal was served immediately thereafter. The only except was during breakfast, where participants were additionally equipped with an ambulatory BP device prior all baseline measurements and BP was recorded. To minimize the effect of collecting study measurements on the study outcomes, the order of measurement collection was identical across all individuals and intervention arms. Participants were given 15 min to consume the preload and water served. Participants rated the palatability of the preload immediately after finishing and appetite and symptoms questionnaires were completed at 15, 30, 45, 60, 90, and 120 min after

66 the first bite of the respective meals. Blood glucose samples were only collected after breakfast and lunch meals at 30, 60, 90 and 120 min of the respective meals.

5.3.5. Measurements

Anthropometric measurements of height, weight, and body fat percentage were collected at screening and each visit. Height was measured with a wall-mounted stadiometer (Perspective

Enterprises, Portage, MI, USA) with the head in the Frankfort plane position. Body weight and body fat composition measured by bioelectrical impedance was assessed by the TANITA BC-

418 Segmental Body Composition Analyzer (Arlington Heights, Illinois, USA) after voiding the bladder and removing any excess clothing and shoes.

BP at screening was measured in triplicates using an automated device (OMRON Intellisense

HEM-907, Kyoto, Japan), each measurement taken one minute apart, and averaged. During each visit, BP was monitored using an ambulatory device using a portable Spacelabs 90207 monitoring device (Spacelabs, Bellevue, WA, USA). Measurements were taken prior to the start of the first meal and were taken every 30 minutes thereafter for 12 hours.

Capillary blood samples were collected by finger-pricks in tubes containing fluoride-oxalate and were immediately frozen at -20°C pending analysis. Blood glucose concentrations were determined using the glucose oxidase method within 48 hours of collection (YSI 2300 STAT

Analyzer, Yellow Springs, OH, USA).

Appetite was measured using 100mm visual analogue scales (VAS) on the subjective ratings of desire to eat, hunger, fullness, and prospective food consumption. The ends of each VAS were anchored with the phrases “not very much at all” and “extremely” on the left and right sides, respectively, as recommended [53]. An overall appetite composite score was calculated by adding desire to eat + hunger + (100 – fullness) + prospective food consumption and dividing the value by 4 to reflect average satiety [87]. Appetite measurements using 100mm VAS have been shown to be reproducible between study visits within healthy individuals [54]. Appetite measurements after each time point were folded out of view upon completion to minimize the influence of previous responses during subsequent measurements. To investigate the efficiency and capacity of the preload to influence appetite sensations, the satiety quotient (SQ) was calculated for each appetite sensation, except for sensations of fullness, at each postprandial time measured following the equation adapted from Green et al [58]:

푏푎푠푒푙𝑖푛푒 푎푝푝푒푡𝑖푡푒 (푚푚) − 푝표푠푡푝푟푎푛푑𝑖푎푙 푎푝푝푒푡𝑖푡푒(푚푚) 푆푄 = 푒푛푒푟푔푦 푐표푛푡푒푛푡 (푘푐푎푙) 표푟 푤푒𝑖푔ℎ푡 (푔) 표푓 푡ℎ푒 푝푟푒푙표푎푑

Dietary food records were analyzed using the ESHA (Food Processor SQL, Version 10.9) program using nutrient data based on the Canadian Nutrient Database File (CNF), the United

States Department of Agriculture (USDA) database if data was not available from the CNF, or from the nutrition facts table if information was available for individual food items. For mixed meals, the individual components were estimated based on descriptions provided by the participants. Participants were provided with information to estimate serving sizes on typically consumed foods and how to complete foods records. Diets were analyzed for total energy and macronutrient content.

Palatability scores and symptoms were collected using a 7-point rating scale representing low (1) to high (7) rating. Symptoms assessed include bloating, belching, diarrhea, flatulence, excessive urination, nausea, headache, dizziness, disorientation, anxiety, stomach cramps, and cold hands and feet.

5.3.6. Statistical Analyses

The primary outcome of the present study was the average appetite rating over 12 hours. Starting times were adjusted to 9:00 AM to standardize comparisons at each time point. Secondary outcomes include appetite ratings, SQ, blood glucose, subsequent energy and food intake, total energy intake, ambulatory BP, and symptoms over the 12 hours and at each individual meal.

Ambulatory BP was analyzed as hourly averages and the mean ambulatory BP was analyzed as the mean of the hourly averages. For appetite and glucose measurements, total area under the curve (AUC) was calculated geometrically using the trapezoid rule for each participant and meal and incremental area under the curve (iAUC) were calculated geometrically using the trapezoid rule ignoring areas below the fasting blood glucose value [170].

Data are presented as means and SEM. All statistical procedures were performed using the

Statistical Analysis System software package, University Edition (SAS Institute Inc., Cary, NC,

USA). Results were considered significant at p<0.05. Data normality was assessed visually and using the Shapiro-Wilk procedure. The effect of the interventions on blood glucose, appetite and ambulatory BP was analyzed using a mixed model ANOVA (proc mixed, SAS) with intervention, time, and time*intervention interaction as fixed factors and participants as the repeated factor for each meal and for the overall 12 hour duration. When a statistically significant interactive effect of intervention and time was observed, pairwise analyses were conducted to assess the differences between interventions and adjusted for multiple comparisons using the Tukey-Kramer method for multiple comparisons. AUC for appetite, mean appetite, mean SQ, iAUC for blood glucose, time to eat, palatability, subsequent energy intake and total energy intake were assessed with a similar procedure without time and its interactive factor. For all glucose, appetite and BP measures over the 12 hour duration, baseline fasting (0 min) values were included as a covariate to adjust for the variability between intervention days and individuals. For glucose and appetite measures at each meal, the baseline measurement, as defined as the value measured immediately prior to meal consumption, was included as a covariate to adjust for the variability between individuals and intervention meals. For symptoms, data were grouped by presence and assessed using a chi square test.

Based on a previously conducted study evaluating the reproducibility of VAS for appetite measurements, the authors concluded that 18 individuals in a crossover design would have 80% power and a 2-tailed level of significance at p < 0.05 (=0.05 and 1-=0.8) for detect a 10%

70 change in subjective appetite ratings between two groups [54]. Accounting for an attrition rate of

15%, 22 individuals were to be recruited into the study.

5.4. RESULTS

5.4.1. Participants

Twenty two (22) participants met the recruitment criteria and were enrolled into the study. Two participants withdrew from the study due to time constraints after attending the first clinical visit.

A total of 20 participants completed the study and were included in the final analysis. All participants completing the study complied with the study protocols. Participant characteristics are presented in Table 9. The participants had a mean age of 31.6 ± 12.0 years, BMI of 25.4 ±

4.7 kg/m2, SBP of 117.1 ± 9.6 mmHg, DBP of 72.6 ± 10.3 mmHg, an average dietary restraint score of 6.2, disinhibition score of 4.7, hunger score of 4.2, and an average energy intake of

1858.6 ± 456.4 kcal as assessed by a 3 day food record. Participants did not report any significant changes to diet or physical activity levels during the study period and complied with the study protocols.

Table 9 – Participant characteristics at baseline.

Characteristic Completers (n=20) Age (years) 31.6 ± 12.0 Female (%) 11 (55) Weight (kg) 72.0 ± 16.0 BMI (kg/m2) 25.4 ± 4.7 SBP (mmHg) 117.1 ± 9.6 DBP (mmHg) 72.6 ± 10.3 Three Factors Eating Questionnaire Restraint 6.2 ± 2.7 Disinhibition 4.7 ± 3.1 Hunger 4.2 ± 3.1 Average 3-Day Energy Intake (kcal) 1858.6 ± 456.4 Data expressed as mean and SD. Average energy intake was assessed by self-reported food record.

5.4.2. Appetite

A significant effect of intervention (p=0.001) and time (p<0.0001) was detected but no interaction effect was detected on all appetite ratings over 12 hours. Appetite ratings over the 12 hours, SQ by kcal or gram, and mean ratings are presented in Table 10. The AUC for the 12 hour appetite measurements was significantly reduced for desire to eat, hunger, prospective consumption, and composite score, and was significantly higher for fullness when comparing the control to the 80-KGM intervention. No significant differences were observed for all appetite measurements between the 40-KGM and all other interventions. A similar pattern was observed for mean 12 hour appetite rating. For the SQ, SQ per kcal consumed was significantly higher for all KGM interventions compared to control, with no differences between the KGM interventions.

When evaluating the SQ per gram, a similar pattern was observed, however, the value for fullness on 40-KGM was not significantly different from the control or 80-KGM intervention.

Appetite sensations at each measured time point are presented in Figure 5 and AUC for appetite over 2 hours for each meal of each intervention are presented in Figure 6. There was a trend for greater appetite sensations after KGM-gel substitution when compared to the control, however, this was only significant in the 80-KGM intervention at lunch for all appetite ratings, at the snack for ratings of desire to eat, fullness, prospective consumption, and composite score, and for fullness at the dinner meal.

a) 80 Control 40-KGM 80-KGM * 60 * * * * * * 40

b) 80

60 * § * * † * * 40 *

0 † * * * * * c) * * * * 80 * * *

40 (mm)

20 Mean Appetite Mean Appetite 0

d) 80

60 * † * * * * * 40

e) 80 * 60 * † * * * * * * * * 40

9:00

19:00 10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00 18:00 20:00 21:00

Time

Figure 5 – Mean appetite ratings over 12 hours. Data presented are means and SEM on a) desire to eat, b) hunger, c) fullness, d) prospective consumption, and e) composite score in 20 healthy individuals. Significance is denoted by

* between 80-KGM vs. control, † between 40-KGM vs. control, and § between 40-KGM vs.80-KGM (p<0.05). 74

b b a) 5000 ab ab Control 40-KGM 80-KGM a a

2500

0 b b) ab a 4000

2000

min)

× 0 a ab a a ab c) b ab b 8000 b

6000

4000

2000

0 b d) 6000 b ab a ab

120 min 120 AUC for min Appetite (mm a 4000

2000

0 6000 b b e) ab ab a a 4000

2000

0 Breakfast Lunch Snack Dinner (9:00 AM) (1:00 PM) (4:00 PM) (7:00 PM) Meal (Time)

Figure 6 – Mean 120 min AUC for appetite after each meal. Data presented are means and SEM on a) desire to eat, b) hunger, c) fullness, d) prospective consumption, and e) composite score in 20 healthy individuals. Different letters within each meal are significantly different (p<0.05).

Table 10 – Mean 12 hour appetite measurements in 20 healthy individuals.

Appetite Measure Control 40-KGM 80-KGM 12 Hour AUC Desire to Eat 24876 ± 2667a 29547 ± 2663ab 32144 ± 2667b Hunger 25431 ± 2535 a 29445 ± 2527 ab 32217 ± 2536 b Fullness 41443 ± 2605 a 37340 ± 2599 ab 34577 ± 2587 b Prospective Food Consumption 26829 ± 2652 a 31129 ± 2642 ab 33346 ± 2638 b Composite Score 26963 ± 2464 a 31202 ± 2454 ab 33736 ± 2455 b Mean Appetite Rating Desire to Eat 29 ± 3.7 a 35 ± 3.6 ab 39 ± 3.7 b Hunger 30 ± 3.5 a 35 ± 3.5 ab 39 ± 3.5 b Fullness 63 ± 3.7 a 57 ± 3.7 ab 53 ± 3.7 b Prospective Food Consumption 32 ± 3.8 a 38 ± 3.7 ab 41 ± 3.7 b Composite Score 32 ± 3.5 a 38 ± 3.5 ab 42 ± 3.5 b Mean Satiety Quotient per kcal of food intake (mm/kcal) Desire to Eat 0.099 ± 0.023 a 0.149 ± 0.023b 0.308 ± 0.023 b Hunger 0.099 ± 0.023 a 0.151 ± 0.023 b 0.314 ± 0.023 b Fullness -0.098 ± 0.026 a -0.138 ± 0.026 b -0.286 ± 0.026 b Prospective Food Consumption 0.098 ± 0.024 a 0.147 ± 0.024 b 0.297 ± 0.024 b Composite Score 0.099 ± 0.023 a 0.145 ± 0.023 b 0.301 ± 0.023 b Mean Satiety Quotient per g of food intake (mm/g) Desire to Eat 0.092 ± 0.012 a 0.099 ± 0.012b 0.128 ± 0.012 b Hunger 0.093 ± 0.012 a 0.101 ± 0.012 b 0.132 ± 0.012 b Fullness -0.089 ± 0.013 a -0.094 ± 0.013ab -0.12 ± 0.013 b Prospective Food Consumption 0.091 ± 0.013 a 0.098 ± 0.013 b 0.124 ± 0.013 b Composite Score 0.091 ± 0.012 a 0.097 ± 0.012 b 0.126 ± 0.012 b Data presented as mean and SEM. AUC – Area under the curve. Different letters within each row are significantly different (p < 0.05).

5.4.3. Subsequent and Cumulative Energy Intake

Mean subsequent food intake and total caloric intake are presented in Figure 7. Participants in the control intervention consumed significantly less food during the subsequent 12 hours when compared to the 80-KGM intervention. No significant differences were detected when comparing the 40-KGM intervention to all other interventions. Cumulative energy intake was significantly different among all interventions, with the control intervention being the highest and the 80-KGM intervention being the lowest.

Post-Visit 12h Intake Cumulative Intake a 2000

In-Clinic Intake b 1500 c 1000

ab b

Energy Energy Intake (kcal) 500 a

0 Control 40-KGM 80-KGM Control 40-KGM 80-KGM

Intervention

Figure 7 – Subsequent and cumulative energy intake in 20 healthy individuals. Cumulative intake was defined as the total energy intake from the intervention and foods consumed 12h post-visit. Data are expressed as mean and

SEM. Interventions with different letters are significantly different (p < 0.05, Tukey adjusted).

5.4.4. Blood Glucose

Postprandial blood glucose measurements are presented in Figure 8. A significant two-way interaction for intervention and time was observed after breakfast (p<0.0001), but not after lunch.

At individual time points, a significant reduction in blood glucose was observed for 80-KGM when compared to the control intervention at 30, 60, 90, and 120 min after breakfast and after 90 and 120 min after lunch. A significant reduction in blood glucose was observed when comparing the 80-KGM to the 40-KGM intervention at 30 and 60 min after breakfast. No differences were observed between the control and 40-KGM intervention. The area under the curve for blood glucose was significantly different among all interventions after breakfast and was significantly lower at the lunch meal for 80-KGM when compared to control.

Control a) 7.00 40-KGM a 80-KGM a 6.00 a a a a a b a ab ab ab ab 5.00 b

b b b b

4.00 Blood Glucose(mmol/L) 9:00 10:00 11:00 12:00 13:00 14:00 15:00

Time

200 b) a Control 40-KGM b 80-KGM 150 c a ab b 100

0 Blood Glucose(mmol/L x min) Breakfast Lunch (9:00) (13:00)

Meal (Time)

Figure 8 – Postprandial blood glucose response over 6 hours in 20 healthy individuals. Data are presented as mean and SEM on a) absolute blood glucose over 2 hours and b) incremental area under the curve for blood glucose over

2 hours after breakfast (9:00) and lunch (13:00). Interventions with different letters at each point are significantly different (p < 0.05, Tukey adjusted).

5.4.5. Blood Pressure

Hourly systolic and diastolic BP values are presented in Figure 9. No intervention or interactive effect with time was observed. No significant differences were observed at individual time points in SBP and DBP. The mean 12 hour systolic and diastolic BP was not significantly different among interventions.

a) 135 Control 40-KGM

130 80-KGM

125

120

Pressure Pressure (mmHg) 115 b)

85 Blood

70 9:00 10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00 18:00 19:00 20:00 21:00 Time

Figure 9 – Hourly ambulatory blood pressure measurements in 20 healthy individuals. Data are presented as mean and SEM on a) systolic blood pressure and b) diastolic blood pressure.

Table 11 – Mean 12 hour ambulatory blood pressure.

Vascular Measure Control 40-KGM 80-KGM Mean 12h Systolic Blood Pressure (mmHg) 123.0 ± 1.2 124.2 ± 1.2 123.6 ± 1.2 Mean 12h Diastolic Blood Pressure (mmHg) 78.0 ± 1.4 78.7 ± 1.4 78.5 ± 1.4 Mean 12h Mean Arterial Pressure (mmHg) 92.8 ± 1.4 93.4 ± 1.4 93.8 ± 1.4 Data are expressed as mean and SEM.

5.4.6. Palatability, Time to Eat, and Symptoms

Mean palatability ratings and time to eat the meals are presented in Table 12. Palatability was significantly higher for control when compared to the 100-KGM intervention after the consumption of the lunch meal (0.59 ± 0.2, p = 0.016) and palatability was significantly lower for the control meal when compared to the 100-KGM intervention at the snack meal (-0.59 ± 0.2, p = 0.010). Participants took a significantly longer time to consume the control intervention meal during breakfast (4.14 ± 1.1 min, p = 0.002), lunch (1.50 ± 0.6 min, p = 0.045), and snack (3.01

± 0.8 min, p = 0.001) when compared to 100-KGM and for the snack when compared to the 50-

KGM intervention (2.02 ± 0.8 min, p = 0.031). No significant differences in individual symptoms were observed as presented in Table 13. When assessing total symptoms, the control intervention reported significantly less symptoms than either KGM intervention, with no difference among the KGM intervention.

Table 12 – Mean palatability and time taken to consume meals in 20 individuals.

Measure Control 40-KGM 80-KGM Palatability Breakfast 5.0 ± 0.2 5.0 ± 0.2 5.4 ± 0.2 Lunch 5.8 ± 0.2a 5.4 ± 0.2ab 5.2 ± 0.2b Snack 4.9 ± 0.2 a 5.2 ± 0.2 ab 5.4 ± 0.2 b Dinner 5.3 ± 0.2 5.1 ± 0.2 4.8 ± 0.2 Time to Eat (min) Breakfast 11.5 ± 1.0a 9.4 ± 1.0ab 7.1 ± 1.0b Lunch 11 ± 0.6 a 10.9 ± 0.6a 9.2 ± 0.6 b Snack 10 ± 0.7 a 7.8 ± 0.7b 6.9 ± 0.7 b Dinner 10.3 ± 0.7 10.8 ± 0.7 9.3 ± 0.7 Data are expressed as mean and SEM. Palatability rating ranges from 1 (minimum) to 7 (maximum). Different letters within a row are significantly different (p < 0.05).

Table 13 – Presences of symptoms over 12 hours in 20 individuals.

Symptom Control 40-KGM 80-KGM Anxiety 0 0 0 Belching 2 2 2 Bloating 2 2 2 Cold Hands and Feet 2 2 4 Stomach Cramps 1 2 2 Diarrhea 0 0 1 Disorientation 0 2 1 Dizziness 0 1 2 Flatulence 1 2 2 Headache 0 4 0 Nausea 0 2 1 Excessive Urination 0 2 1 Other 0 0 0 Total 8a 21b 18b Data are presented as a frequency of individuals indicating the presence of a symptom during the intervention.

Different letters in each row are significantly different (p < 0.05)

5.5. DISCUSSION

The present study is the first to administer KGM-gels into meals over the course of a day to assess the impact on appetite and subsequent energy intake. Due to the high fibre content of the

KGM interventions, it was not possible to match the volume of the interventions while achieving the same degree of caloric restriction. As a result, the 40-KGM and 80-KGM interventions differed from control in energy content by approximately 40% and 75% and differed in weight by approximately 16% and 40%, respectively. The present results demonstrate that appetite ratings and subsequent energy intakes were significant higher following 80-KGM intervention when compared to the control. This was in contrast to our hypothesis, where appetite ratings were expected to be similar despite the deficit in energy. This may be explained by the differences in the volume of food consumed, which was approximately 25 and 50% lower in the

40-KGM and 80-KGM interventions, respectively. However, no significant differences were observed between the 40-KGM and all other interventions.

Although the energy content and volume were not matched across interventions, the present findings suggest that small changes in ED of ~0.25 kcal/g had a small, but non-significant effect on appetite and subsequent energy intake. Larger changes in ED, such as a difference of 0.5 kcal/g shown between 80-KGM and control, resulted in significantly poorer appetite responses for 80-KGM. These results were consistent across the different appetite ratings throughout the day and when assessed at individual meals. These findings are in contrast to a majority of clinical evidence that support ED reduction for decreasing energy consumption and increasing satiety [141,167]. Reduced ED of 20-25% in ad libitum meals has demonstrated reductions in overall energy intake and comparable appetite responses to a usual ED diet [155,171]. In these

83 studies and others, healthy individuals have been observed to consume a consistent quantity of food over the course of a day, irrespective of the energy content or testing conditions [172,173].

This indicates that food quantity is the primary determinant of postprandial appetite and subsequent food intake. However, other studies have also demonstrated that large differences in energy content of ~500 kcal in a single meal can independently drive appetite responses and suppress energy intake despite being matched for volume [174]. Given the reduction in calories and food quantity with increasing KGM substitution was concomitant, the comparisons of absolute appetite ratings may not be representative of any satiating capacities the low ED KGM- gels may possess.

To further investigate the potential satiety effect of KGM interventions, appetite responses were assessed using the satiety quotient, which is a measure that considers the satiating capacity of foods by their energy content or quantity [58]. With this assessment, both 40-KGM and 80-KGM demonstrated a significantly higher satiating capacity when compared to control, indicating that appetite suppression was greater per calorie or gram of food consumed. The SQ for fullness has been shown to be predictive of subsequent energy intake in dieting women [60,152]. However, more research is required to investigate the impact and reproducibility of SQ on appetite and food intake in different populations.

Subsequent energy intake followed a similar pattern to subjective appetite, where energy intake was significantly higher after the 80-KGM intervention when compared to the control.

Interestingly, the mean subsequent energy intake after the 80-KGM was 330 kcal, compensating for less than 25% of the 1330 kcal deficit between the 80-KGM and the control. When the

84 cumulative 24 hour energy intake was assessed, the energy deficit introduced by the interventions was maintained, leading to significantly lower intakes for KGM interventions.

Evidence for the incomplete compensation observed have been reported in acute studies of severe energy restriction or complete fasting where intake was similar or lower than the 450 kcal provided in the 80-KGM intervention. Acute energy restriction led to a net energy deficit that is sustained post-intervention and without increased appetite sensations [175,176]. Similarly, evidence suggests that energy is only partially compensated when an energy reduced meal is administered and that compensation only occurs at the subsequent meal [177,178]. While the current study does not continue to follow individuals after the clinical visit to track energy compensation into the next day, current evidence using dietary energy restrictions ranging from

25-75% in an acute setting does not appear to invoke a homeostatic response to regain the lost calories.

Additional factors may have also contributed to the appetite and energy intake response.

Individuals in the present study reported a significantly lower time taken to consume the meals in the KGM interventions, likely due to the smaller volume consumed. The rate of consumption was also significantly lower for 80-KGM during the breakfast and snack meals. Duration and rate of food consumption has been reported to impact the cephalic phase of digestion, increasing signals of satiety through prolonged oral exposure and increased mastication [179,180].

However, sham feeding studies in humans dissociating the oral act of food consumption to the rating of food entry into the stomach has reported conflicting evidence to the existing hypothesis of satiety and eating duration [181,182].

The postprandial glucose response was reduced following 80-KGM and 40-KGM compared to control after breakfast. This was expected as the available carbohydrate content of the meals was different: 63 g for control, 37 g for 40-KGM, and 10 g for 80-KGM. However, differences after lunch intake were only detected between the control and 80-KGM, indicating an overall lower glycemic response. This is likely due to the reduction in available carbohydrate in the lunch meal, the lower glycemic index value of pasta compared to rice, and higher sensitivity of the endocrine system due to an earlier carbohydrate load from the breakfast meal [183,184].

Presently, no acute effect of KGM-gel substitution was observed on ambulatory BP. Previous investigations of KGM have reported significant reductions in systolic BP, however those studies differed by administration methods, duration, and study population [91,161]. There is evidence to suggest that a high carbohydrate load will lead to reduced BP as the secretion of insulin in response to the carbohydrate load will affect BP [185]. In the present study, changes in BP would not be expected as this effect is more often attributed to an older or at risk population [186].

Nevertheless, soluble fibres do appear to have an inverse association with cardiovascular risk.

Given that previous studies with KGM powder significantly improved cardiovascular risk factors

[161,162], future studies should assess whether the benefits of KGM in the powder form are present in the gel form when consumed over an extended period of time.

There are several limitations to the present study. Firstly, the recruitment criteria for the present study encompassed a wide range of healthy individuals. Presently, more than half the sample size is overweight and this may have contributed to the appetite response as overweight individuals have been shown to have a blunted appetite response to foods, leading to greater hunger and

86 subsequent food intake [187]. The present study is underpowered to undergo sub-analyses by the presence of overweight, but inclusion of BMI or overweight status did not significantly change the results. Secondly, the present study was a metabolically controlled feeding trial that restricted the consumption of foods to those administered during the 12 hour clinic duration. This limits the interpretation of the present results to the general population and future studies should address the efficacy and effectiveness of KGM-gel substitution for reducing daily energy intake in a free- living or ad libitum dietary pattern.

In conclusion, moderate incorporation of KGM-gel over the course of a day did not result in increased appetite or subsequent energy intake despite reductions in the energy content and quantity consumed. Greater appetite and subsequent intake was only triggered when KGM-gel replaced a majority of the study foods. Given the incomplete compensation observed in the

KGM-gel interventions, the results from this study add to the body of literature that indicates individuals are unable to fully compensate for missing calories incurred over the course of a day.

Due to the very low ED and resemblance of KGM-gels food to common food staples, future studies should evaluate the effectiveness of KGM-gels as a weight management aid.

CHAPTER 6. DISCUSSION, LIMITATIONS, FUTURE DIRECTIONS, CONCLUSION

6.1. MAIN FINDINGS

Study 1: The objective of the first study was to determine if isovolumetric substitution of KGM- gel noodles for a high carbohydrate pasta at two levels (50% and 100% of pasta for KGM-gel) in a preload would result in decreased food intake during a subsequent meal without changing palatability in 16 healthy individuals. The control contained 442 kcal, the 50% replacement (50-

KGM) contained 259 kcal, and the 100% replacement (100-KGM) contained 77 kcal. Hunger was significantly higher for 100-KGM compared to control. Fullness was lower and prospective consumption was higher for 100-KGM compared to 50-KGM. Energy intake and palatability was similar across all preloads, resulting in a net caloric deficit of 201 kcal for 50-KGM and 421 kcal for 100-KGM in cumulative energy intake.

Study 2: The objective was to assess two substitution levels of KGM-gel foods into 4 meals over

12 hours on appetite scores, energy intake, and palatability compared to a control diet in 20 healthy individuals. Three levels of KGM-gel substitution were employed: none (control, 1935 kcal), 40% energy reduction (40-KGM) and 80% energy reduction (80-KGM) with KGM-gel food substitution. Appetite suppression was ~25% higher for control than 80-KGM over 12h

(p<0.01), KGM interventions were more efficient at suppressing appetite by calorie or amount consumed. Despite large energy deficits between interventions, energy compensation post-visit was small, leading to a cumulative reduction in overall caloric intake for 40-KGM and 80-KGM of 625 and 1129 kcal from control (p<0.001).

6.2. OVERALL DISCUSSION

To our knowledge, these two studies are among the first to clinically investigate the appetite response to a very low energy fibre-gel when consumed as a food. The results partially support the hypothesis, where both studies showed that substituting a modest portion of a meal with

KGM-gel foods to lower the intake of calories resulted in comparable appetite ratings when compared to a control. In contrast to the hypothesis, large substitutions increased appetite ratings and suppressed satiety when compared to an energy dense control. However, despite the higher appetite ratings, KGM-gel substitution at all levels resulted in significantly lower cumulative energy intakes across each clinical visit. This effect was consistent in both studies, despite the lower amount of food served in Study 2, and has strong implications for dietary strategies in body weight management.

Long term success of weight management therapies are determined by individual adherence to the prescription of lifestyle and dietary modifications that include energy restriction. While various factors can influence adherence, common barriers to success include excess hunger from insufficient food intake that lead to overconsumption and difficulty adhering to changes in individual dietary patterns [39]. Despite the higher appetite ratings observed in the highest level of KGM-gel substitution in both studies (~23% in study 1 and ~25% in study 2 compared to controls), results from both trials demonstrated that a cumulative energy deficit can be accrued by using KGM-gel foods as a food substitute. This may be due to the fact that the satiating capacity of KGM-gel is very high when satiety is a factor of calories consumed. When observing the SQ, the SQ per energy intake from Study 1 is nearly 2 times the SQ calculated in Study 2 for

90 the highest level of substitution (~0.6 mm/kcal for 100-KGM vs. ~0.3 mm/kcal for 80-KGM, respectively). This difference may be explained by the reduced volume in Study 2, where SQ by gram of food intake was also significantly higher for 80-KGM compared to control. Since the amount of the food in Study 2 was reduced by nearly 50% for 80-KGM compared to the control, these results indicate that half of the high satiating capacity of KGM-gel can be attributed to changes in the amount consumed. Nevertheless, both studies demonstrated a high satiating capacity, which has implications for weight management as low energy, highly satiating foods can assist in adherence to energy restricted diets [60,152].

While an extensive investigation on the oro-sensory properties and acceptability of KGM-gel foods was not in the scope of the two studies, the palatability assessments and methods of incorporation can be used as indicators for the applicability of KGM-gels in a free-living population. In study 1, replacing 1.5 cup of pasta (~220 g) with KGM-gel noodles resulted in an energy reduction of approximately 350 kcal in a single meal. Additionally, KGM-gels may be discretely incorporated into meals without adversely affecting sensory characteristics as commercially produced forms of KGM-gels that can be purchased from local supermarkets as noodles, various pasta shapes, and rice. The similar palatability responses between meals and their respective controls in both studies suggest that KGM-gel foods have a minimal impact on the general oro-sensory characteristics of the meals utilized. As the foods used in the present studies were pasta and rice, these KGM-gels are food analogues of common food staples in the

North American diet and will minimizing the need to change habitually consumed dishes. Based on the current guidelines on energy restricted diets to achieve a minimum daily energy reduction of 500 kcal, this can be achieved by replacing 2 cups of cooked pasta or medium-grain white

91 rice. This replacement will not change the amount of food consumed and will lower the dietary

ED, which has been shown to be a strong predictor of energy intake and weight loss

[141,142,167].

6.3. LIMITATIONS

Several methodological limitations are present in the two studies and may improve future studies if they are addressed.

A limitation that is inherent to this study and other similar studies is the acute, single- administration design that limits the interpretation of effects after repeated consumption. Acute measurements does not allow for the assessment of habituation or ability to adhere to the interventions, which are key factors for weight loss success. Additionally, in the present studies, appetite responses were higher after KGM-gel consumption, although total energy intake was reduced. Over an extended period, the appetite responses may increase due to the habitual deficit of calories and individuals may compensate by increasing food intake, reducing the effectiveness of KGM-gel substitution. Extended studies of repeated and prolonged consumption of KGM-gel are needed to assess the appetite and energy intake if KGM-gels are to be used as a weight loss aid.

A key limitation of the two studies is the small sample size. While the two studies have appropriate power analyses to support the conclusions made about the primary outcomes, the determined sample size may not be large enough for some of the secondary analyses. This is

92 particularly relevant when assessing appetite measurements, as the recommended method of measurement involves 4 independent questions that reflect the motivation to eat, increasing the likelihood of a type 2 statistical error. This limitation affects the second study more than the first study, as the primary outcome was based on appetite measurements, and several additional secondary outcomes were measured, including blood glucose and BP. One method to address the

4 appetite questions was to use a composite score that was calculated using all 4 appetite questions as the primary outcome. While the primary outcomes were adequately powered, all secondary outcomes should be considered as exploratory and evaluated independently in future studies.

The outcomes collected also have inherent limitations in both studies. VAS are self-reported measurements of appetite that have the potential for reporting error. While VAS have been shown to be reproducible in healthy adults, they do not always correlated with subsequent energy intake [54,87]. Thus, changes in subjective appetite may not be predictive of potential changes in energy intake or potential weight loss. Methods to address this can involve using biomarkers of satiety, such as ghrelin, PYY, CCK, and GLP-1 for short term satiety, or leptin for long-term measurements.

While many efforts were made to minimize factors that could influence appetite and energy intake, potential environmental factors may have affected the study results. In particular, individuals were allowed to browse the internet in Study 2, which may have exposed individuals to visual food cues that can influence appetite ratings. Depending on the individual, these auditory or visual cues could have triggered before, during, or after a meal. However, the

93 participants were asked to maintain the same routines during clinical visits in an attempt to minimize this influence.

Most importantly, a major limitation to the present studies is that both studies enrolled individuals that were healthy with a BMI between 18.0-29.9 kg/m2. While the average BMI in

Study 2 was 25.4 kg/m2, indicating the sample was modestly overweight, these results may not be applicable to obese individuals who in the most need of effective dietary therapies for weight management. Obese individuals have been reported to respond more strongly to food cues than lean individuals after being satiated, indicating differences in the cognitive control of appetite

[188,189]. For satiety related hormones, obese individuals appear to experience suppressed ghrelin clearance, and reduced GLP-1 and PYY production after meal consumption [137,187].

As obese individuals appear to have a blunted appetite response to food, KGM-gels may allow for increased food consumption without increasing energy intake. Thus, the results from the present studies need to be confirmed in an obese population.

6.4. FUTURE DIRECTIONS

The present studies utilizing KGM-gel foods have provided preliminary observations on the physiological effects of fibre-gels on appetite control. Due to the lack of available research on fibre-gels and KGM-gels on appetite and energy regulation, future search should focus on elucidating the mechanisms of action, efficacy for weight loss in overweight or obese individuals, and potential metabolic health benefits in the general population.

The incomplete compensation of energy with KGM-gel incorporation and the commercial availability in various food forms suggests that KGM-gel foods may be highly accessible and effective in popular weight loss therapies beyond standard care. Low-carbohydrate or ketogenic diets for weight loss may be especially applicable for KGM-gel foods as the majority of the foods they can replace are carbohydrate-rich foods. There is evidence to support a strong weight loss effect and while following a ketogenic diet, which appears to promote satiety to a greater extent than a standard energy-restricted diet [190,191]. Other dietary methods that may benefit with KGM-gel inclusion would be very low-energy diets (daily energy intake < 500 kcal) or

ADF diets where the fasting days aim to consume < 500 kcal per day [49]. Given that KGM-gel foods contain approximately 6-20 kcal per 100 g, the very low energy goal of 500 kcal can be maintained while consuming a large amount of KGM-gel foods, promoting greater adherence to these dietary restriction methods through appetite suppression.

It is currently unclear how KGM-gels are metabolized. When consumed in a meal, the KGM-gel may be interacting with the nutrients in various ways to augment the satiety signal. It is possible that this can occur in two ways. As previously discussed, KGM-gel possesses a high firmness that can stimulate satiety by promoting gastric distention. Alternatively, it is possible that KGM- gel continues to act like a viscous soluble fibre upon ingestion. Formation of the gel is a result of deacetylation, which leaves the fibre chains exposed to hydrolysis within the stomach [103]. The loss of the gel integrity may promote mild viscosity development, which can provide some of the health benefits that are associated with the KGM powder. In Study 1, the fully KGM preload contained 8 g of dietary fibre and in Study 2, the total intake of dietary fibre at the high KGM substitution level was 31 g. These amounts are far higher than those used as capsules, and it is

95 possible that extended consumption of KGM-gel in this quantity may confer the cardiovascular health benefits of the powdered form, such as reductions in LDL-cholesterol, postprandial glycemia, systolic BP, and modest weight management [91].

Another aspect that should be elucidated is the role of KGM-gel within the gut microbiota and whether it has any prebiotic potential. The accessibility of the KGM-gel may have implications for long term weight management as the production of SCFA is linked with reduced appetite and weight loss [157]. In vitro comparisons, both KGM powder and gel reported similar fermentation profiles, indicating the gel is fermentable [160]. This is somewhat seen in the present results, where KGM-gel administration resulted in slightly elevated overall GI symptoms than control, as shown in Study 2.

Future studies should build upon the present design for elucidating acute appetite and food intake. The present studies did not have a comprehensive measure of the oro-sensory attributes, such as taste and texture, and attitudes individuals felt towards KGM-gel foods [154]. The KGM- gels used presently were also only in the form of noodles and small cubes. KGM-gels are available in various pasta shapes, rice, and as other food analogues such as vegan seafood to increase variety. Modifying these factors may influence appetite and food intake and help in the formulation of intervention products that can be effectively utilized in a long term weight loss setting.

6.5. CONCLUSIONS

In conclusion, the substitution of KGM-gel foods for energy dense foods reduced the energy content of the meals without adversely affecting meal palatability. The appetite response was inconsistent with our hypothesis, showing that the highest level of KGM-gel substitution resulted in significantly lower satiety. Despite this difference, subsequent energy intake was moderately affected by differences in appetite and cumulative energy intakes were reduced with increasing

KGM-gel substitution, supporting the hypothesis. Thus, substitution of KGM-gel foods for energy dense foods may assist in reducing energy intake without increasing appetite when replacing a modest amount. The reductions in cumulative energy intake are congruent with energy reductions recommended for dietary weight management therapies and may have relevance in weight loss regimes. Future studies should evaluate the efficacy of KGM-gel foods for energy and weight management of an extended duration in an overweight or obese population.

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CHAPTER 8. APPENDIX

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APPENDIX 1 – Study 1 Clinical Assessment Form

In-Meal Gel Study

CLINICAL ASSESSMENT FORM Participant ID:______

Date: ______Visit #: 1 / 2 / 3

TREATMENT CODE: ______

Anthropometry Meal Start/Finish Time

Ht (cm):______START TIME:______

Wt (kg):______FINISH TIME:______

BF (%): ______Time taken to consume meal:______

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APPENDIX 2 – Study 1 Subject Information Form

In-Meal Gel Study

SUBJECT INFORMATION FORM Participant ID:______

All information provided in this questionnaire will be kept confidential and is only for the purpose of the present study.

Gender:  Male  Female  Less Active: You average less than 30 minutes of physical activity a day. Physical Activity  Moderately active: You average 30 to 60 minutes of physical activity a day. Level:  Active: You average more than 60 minutes of physical activity a day.

 Non-smoker Smoking:  Casual (less than 1 cigarette/day)  Moderate (1 or more cigarette(s)/day but less than 1 pack)  Frequent (1 pack or more/day) Average number of alcoholic drinks/week: ______Alcohol: (1 serving of wine is 5 oz, 1 serving of beer is 12 oz, 1 serving of malt liquor is 8 oz and 1 serving of distilled spirits (80 proof) is 1.5 oz)

Illnesses/Diseases (if any): (please list)

Allergies: (please list all of your known allergies)

Medications Type(s): Dosage(s): (please list any medications you are currently taking, and their dosages)

Supplements Type(s): Amount(s): (please list any supplements you are currently taking, and their amounts)

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APPENDIX 3 – Study 1 Ad Libitum Food Form

In-Meal Gel Study

AD LIBITUM FOOD FORM Participant ID:______

Date: ______Visit: 1 2 3 (circle)

Treatment Code: ______

Quantity of Wafer Cookies snack given (g)

Amount of Wafer cookies snacks remaining (g)

Amount of water drink on Visit 1 (mL)

Quantity of Wafer cookies consumed (g)

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APPENDIX 4 – Study 1 Palatability Questionnaire In-Meal Gel Study

Participant ID:______

Palatability Questionnaire

Please draw a vertical line across the line at the point to indicate meal palatability.

Very Very Palatable Unpalatable ______

(Not acceptable or (Acceptable or Not agreeable to the agreeable to the Palate or taste) palate or taste)

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APPENDIX 5 – STUDY 2 Clinical Assessment Form

KJM Satiety Study

CLINICAL ASSESSMENT FORM Participant ID:______

Date: ______Visit #: 1 / 2 / 3

INTERVENTION CODE: ______MEAL TYPE: BREAKFAST LUNCH SNACK DINNER

Anthropometry Meal Start/Finish Time

Ht (cm):______START TIME:______

Wt (kg):______FINISH TIME:______

BF (%): ______Time taken to consume meal:______

Ambulatory Blood Pressure Setup :

Yes / No

0’ 30’ 60’ 90’ 120’ (Pre- meal) Blood Glucose*

PART A: To be completed by INVESTIGATOR

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APPENDIX 6 – STUDY 1 & 2 Preclinical Information

PART B: To be completed by PARTICIPANT

Preclinical information Did you consume at least 150g (6oz.) of carbohydrate on Time Food item Quantity each of the three days previous to this test? This amount is equivalent to 3 servings of any of the following alone ______or in combination: 2 slices of bread, 1 cup of cooked rice/pasta, 1 medium potato, 1 bowl of cereal with milk, 1 ______glass of juice/soft-drink, 3 oranges/apples, or 1 bowl of ice cream. ______ Yes  No ______Have you been fasting for 10-12 hours?  Yes  No Please describe the last meal you consumed before the test.

Did you take any medications (prescription, OTC, etc.), remedies, or supplements last night or this morning? If Type: ______Dose:______Time:______yes, then please describe.  Yes  No How long ago did you last (1) empty your bladder and/or (1) Last urination:______hours ago (2) have a bowel movement? (2) Last Bowel movement:_____hours ago

Did you do anything last night that is not part of your regular routine? This may include social activities, exercise, or use of alcohol, medications, or supplements. ______If yes, then please describe.  Yes  No How many hours of sleep did you have last night? Does this represent a typical amount? ______hours  Yes  No Did you do anything before the test this morning that is not part of your regular routine? This may include exercise or use of alcohol, medications, or supplements. ______If yes, then please describe.  Yes  No What was your mode of transportation to the clinic this morning? Is this different from other clinic mornings? ______ Yes  No How would you rate your current level of health/well- being. Please comment on anything unusual. ______ Excellent  Good  Fair  Poor

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APPENDIX 7 – STUDY 1 & 2 Satiety Questionnaire

Subject ID: Time: Pre Test Meal (0 min) SATIETY QUESTIONNAIRE

These questions relate to your physical assessment at this time. Please rate your feelings by placing a vertical line across the line at the point which best reflects your present feelings.

1. How strong is your desire to eat?

Very weak ______Very strong

2. How hungry do you feel?

Not hungry ______As hungry at all as I have ever felt

3. How full do you feel?

Not full at all ______As full as I have ever felt 4. How much do you think you could eat now?

Nothing at all ______A large amount

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APPENDIX 8 – STUDY 1 & 2 Symptoms Questionnaire

SYMPTOMS PRESENCE SEVERITY Comment

Bloating  Yes  No Low 1------2------3------4------5------6------7 High

Belching  Yes  No Low 1------2------3------4------5------6------7 High

Diarrhoea  Yes  No Low 1------2------3------4------5------6------7 High

Flatulence  Yes  No Low 1------2------3------4------5------6------7 High

Excessive urination  Yes  No Low 1------2------3------4------5------6------7 High

Nausea  Yes  No Low 1------2------3------4------5------6------7 High

Headache  Yes  No Low 1------2------3------4------5------6------7 High

Dizziness  Yes  No Low 1------2------3------4------5------6------7 High

Disorientation  Yes  No Low 1------2------3------4------5------6------7 High

Anxiety  Yes  No Low 1------2------3------4------5------6------7 High

Poor wound healing  Yes  No Low 1------2------3------4------5------6------7 High

Excessive bleeding after cuts  Yes  No Low 1------2------3------4------5------6------7 High

Other (specify): ______ Yes  No Low 1------2------3------4------5------6------7 High

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APPENDIX 9 – STUDY 2 Palatability Questionnaire

PALATABILITY QUESTIONNAIRE

Please indicate meal palatability.

Like Like Like Neither Dislike Dislike Dislike extremely very much moderately like or moderately very much extremely dislike

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APPENDIX 10 – STUDY 2 Medical History Questionnaire

KJM Satiety Study

MEDICAL HISTORY FORM Participant ID:______

Date: ______

Last name:

First name and initials:

Mailing address:

Telephone:

Fax:

E-mail:

Gender:  Male  Female

Age: (18-70)

Family Physician:

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Part 2: Anthropometry and BP Measurements

Ht (cm) ______Brachial blood pressure (mmHg):

Wt (kg) ______1. ______/ ______

BMI (kg/m2) ______(18-27) 2. ______/ ______

Waist circumference (cm) ______3. ______/ ______

Body Fat (%) ______AVG: ______/______

Part 3: Medical History

Have you been diagnosed with any of the following?

Previously Condition Onset date Present status Diagnosed  Yes  Recovered Liver disease/Infectious Hepatitis  No  Active  Yes  Recovered Kidney disease  No  Active  Yes  Recovered Diabetes  No  Active  Yes  Recovered Hypertension  No  Active Heart disease  Yes  Recovered

(Stroke, myocardial infarctions)  No  Active  Yes  Recovered Thyroid disease  No  Active  Yes  Recovered Celiac disease  No  Active Gastrointestinal disease (Crohn’s disease, Malabsorption syndrome, Ulcerative colitis, Stomach  Yes  Recovered

(gastric) ulcer, Duodenal ulcer,  No  Active Intestinal parasites, Diarrhea, Constipation)  Yes  Recovered Pancreatic disease  No  Active  Yes  Recovered Cancer  No  Active  Yes  Recovered HIV/AIDS  No  Active

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 Yes Please list: Any food allergies  No  Yes Any food intolerance Please list:  No

Did you experience any of the following symptoms in the past 2 weeks?

Severity Onset (mild/moderate/severe) Symptom Presence Frequency Duration date

Bloating  Yes  No  Yes Belching  No  Yes Flatulence (gas)  No Diarrhoea  Yes  No  Yes Excessive urination  No  Yes Nausea  No Headache  Yes  No  Yes Dizziness  No  Yes Insomnia  No Anxiety  Yes  No  Yes Disorientation  No  Yes Poor wound healing  No Excessive bleeding after  Yes

cuts  No  Yes Impaired vision  No  Yes Heart flutters  No Joint pain  Yes  No  Yes Numbness  No

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Do you have any other health problems besides the above mentioned ones?

 No  Yes (please describe):

______

Part 4: Lifestyle and diet

1. Did your weight increase or decrease by 3kg or 6.6 lbs within the last 2 months?  Yes  No 2. Are you following a special diet?  Yes (please describe)  No

______

Are there any food you do not eat?  Yes (please describe)  No

______

3. Do you take medications, herbs or supplements?  Yes  No

If yes, please describe indicating types, brand names, doses and time

______

4. Do you smoke?  Yes  No

If yes, how many cigarettes per day?  < 10 cigarettes/ day  > 10 cigarettes /day

If you are a past smoker, how many cigarettes did you smoke per day and when did you quit?

______

5. Please list type, duration and frequency of any regular exercise (including walking): ______

6. Please indicate the number of alcoholic beverages (spirit 1.5 oz, beer 1 bottle, wine 1 200 ml glass) consumed per day:

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 0/day  1-2/day  > 2/ day (exclusion)

7. Please indicate the number of coffee drinks per day (1 cup = 1.5 fl.oz.)

 0/day  1-5 cups/ day  5-8 cups/day   9 cups/ day

8. Are you currently participating in another clinical trial?  Yes  No

Have you participated in a clinical trial within the last month?  Yes  No

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