Record for a UF thesis. Title & abstract won't display until thesis is accessible after 2014-08-31.

Permanent Link: http://ufdc.ufl.edu/UFE0044748/00001

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Title: Record for a UF thesis. Title & abstract won't display until thesis is accessible after 2014-08-31.
Physical Description: Book
Language: english
Creator: Wright, Arnelle Renee
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2012


Subjects / Keywords: Food Science and Human Nutrition -- Dissertations, Academic -- UF
Genre: Food Science and Human Nutrition thesis, M.S.
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Statement of Responsibility: by Arnelle Renee Wright.
Thesis: Thesis (M.S.)--University of Florida, 2012.
Local: Adviser: Dahl, Wendy Joanne.
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Classification: lcc - LD1780 2012
System ID: UFE0044748:00001

Permanent Link: http://ufdc.ufl.edu/UFE0044748/00001

Material Information

Title: Record for a UF thesis. Title & abstract won't display until thesis is accessible after 2014-08-31.
Physical Description: Book
Language: english
Creator: Wright, Arnelle Renee
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2012


Subjects / Keywords: Food Science and Human Nutrition -- Dissertations, Academic -- UF
Genre: Food Science and Human Nutrition thesis, M.S.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation


Statement of Responsibility: by Arnelle Renee Wright.
Thesis: Thesis (M.S.)--University of Florida, 2012.
Local: Adviser: Dahl, Wendy Joanne.
Electronic Access: INACCESSIBLE UNTIL 2014-08-31

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2012
System ID: UFE0044748:00001

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2 2012 ArNelle R Wright


3 To my family


4 ACKNOWLEDGMENTS I thank my supervisory committe e members Dr. Dahl, Dr. Mathews, Dr. Henke n and Dr. Janicke for all of the guidance provided to me over the past two years. The knowledge I have gained from this experience will aid me in the next phase of my life. I thank all the graduate and undergraduate students for their help in the success ful execution of th e study. Lastly, I thank my family and close friends for their encouragement and support during this process.


5 TABLE OF CONTENTS page ACKNOWLEDGMENTS ................................ ................................ ................................ .. 4 LIST OF TABLES ................................ ................................ ................................ ............ 7 LIST OF FIGURES ................................ ................................ ................................ .......... 8 LIST OF ABBREVIATIONS ................................ ................................ ............................. 9 ABSTRACT ................................ ................................ ................................ ................... 11 CHAPTER 1 LITERATURE REVIEW ................................ ................................ .......................... 13 Obesity ................................ ................................ ................................ .................... 13 Obesity Trends and Health Risks ................................ ................................ ..... 13 Prevention and Treatment Methods ................................ ................................ 15 Fiber ................................ ................................ ................................ ........................ 17 Definition ................................ ................................ ................................ .......... 17 Fiber Recommendations and United States Intakes ................................ ........ 19 Sources and Classification of Fiber ................................ ................................ .. 19 Fermentable Carbohydrates ................................ ................................ ............. 22 Health Benefits of Adequate Fiber Intake ................................ ......................... 23 Fiber and diabetes ................................ ................................ ..................... 24 Fiber and cardiovascular disease ................................ .............................. 25 Fiber and cancer ................................ ................................ ........................ 26 Fiber and obesity ................................ ................................ ....................... 29 Fiber and satiety ................................ ................................ ........................ 30 Assessing Energy Intake ................................ ................................ ........................ 33 Diet Records ................................ ................................ ................................ ..... 33 Food Frequency Questionnaires ................................ ................................ ...... 34 24 Hour Diet Recalls ................................ ................................ ........................ 34 2 PURPOSE ................................ ................................ ................................ .............. 38 3 METHODS ................................ ................................ ................................ .............. 39 Participants ................................ ................................ ................................ ............. 39 Experimental Design ................................ ................................ ............................... 40 Pre Baseline and Baseline ................................ ................................ ...................... 40 Randomization ................................ ................................ ................................ ........ 42 Intervention ................................ ................................ ................................ ............. 43 Daily and Weekly Measures ................................ ................................ ................... 44 Final Study Week ................................ ................................ ................................ .... 47


6 Incentives ................................ ................................ ................................ ................ 47 Statistical Analyses ................................ ................................ ................................ 47 4 RESULTS ................................ ................................ ................................ ............... 52 Participant Demographics and Characteristics ................................ ....................... 52 Diet Recalls Obtained ................................ ................................ ............................. 53 Fiber Intake ................................ ................................ ................................ ............. 53 Energy Intake ................................ ................................ ................................ .......... 54 Body Weight Changes ................................ ................................ ............................ 54 5 DISCUSSION AND CONCLUSION ................................ ................................ ........ 62 Fiber Intake ................................ ................................ ................................ ............. 62 Energy Intake ................................ ................................ ................................ .......... 64 Body Weight ................................ ................................ ................................ ........... 65 Limitations and Future Directions ................................ ................................ ........... 66 APPENDIX A INSTITUTIONAL REVIEW BOARD APPROVAL LETTER ................................ ..... 69 B INSTITUTIONAL RE VIEW BOARD INFORMED CONSENT ................................ .. 71 C RECRUITMENT MATERIALS AND QUESTIONNAIRES ................................ ....... 83 LIST OF REFERENCES ................................ ................................ ............................. 100 BIOGRAPHICAL SKETCH ................................ ................................ .......................... 105


7 LIST OF TABLES Table page 3 1 Caloric and nutrient content of snack bars provided to parti cipants during study ................................ ................................ ................................ ................... 51 3 2 Caloric and nutrient content of yogurt study food provided to participants during study ................................ ................................ ................................ ........ 51 4 1 Chara cteristics of ITT participants at baseline and study completion. ................ 56 4 2 The average number of 24 hour diet recalls obtained from ITT participants per week, at baseline and during each week of data collection. ......................... 57 4 3 Mean macronutrient intake at baseline and during each week of data collection ................................ ................................ ................................ ............ 60


8 LIST OF FIGURES Figure page 1 1 Adapted from Viuda ................................ ................................ .......................... 37 1 2 The structure of an oligofructose mo lecule ................................ ......................... 37 3 1 Study design ................................ ................................ ................................ ....... 50 4 1 Participant flow from screening to randomization. ................................ .............. 55 4 2 Mean total fiber intake of ITT participants at baseline and during each week of data collection.. ................................ ................................ ............................... 58 4 3 Mean energy intake of ITT participants at baseline and durin g each week of data collection. Data are statistically significant at P value < 0.05, and are expressed as meanSEM. ................................ ................................ .................. 59 4 4 Final body weight expressed as a percent of baseline body weight. Da ta were obtained by calculating the mean percentage of baseline weight at the end of the study. ................................ ................................ ................................ 61


9 LIST OF ABBREVIATION S AI Adequate Intake AMPM Automated Multiple Pass Method ANOVA Analysis of Variance ASA 24 Automated Self Administered 24 hour Die t Recall BMI Body Mass Index CHD Coronary Heart Disease CVD Cardiovascular Disease DRI Dietary Reference Intake s DP Degree of Polymerization DPP Diabetes Prevention Program EFSA European Food Safety Authority FFQ Food Frequency Questionnaire FOS Fructoolig osaccharide FSHN Food S cience H uman N utrition GERD Gastroesophageal Reflux Disease GLP 1 Glucagon Like Peptide 1 GOS Galactooligosaccharide I Interaction ITT Intent to Treat MRP Meal Replacement Program NCI National Cancer Institute NHANES National Health and Nutrition Examination Survey NHLBI National Heart Lung and Blood Institute NS Not Significant


10 NSP Non Starch Polysaccharides OF Oligofructose PRO Protein PYY Peptide YY QOL Quality of Life RM Repeated Measures SCFA Short Chain Fatty Acids SDE Structure d Diet and Exercise Program SEM Standard Error of the Mean T1D Type 1 Diabetes T2D Type 2 Diabetes TX Treatment Group USDA United States Department of Agriculture WK Week


11 Abstract of Thesis Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science THE EFFECT OF SNACK FOODS WITH ADDED OLIGOFRUCTOSE ON ENERGY INTAKE IN HEALTHY ADULTS By ArNelle R. Wright August 2012 Chair: Wendy Dahl Major: Food Science a nd Human Nutrition Previous epidemiological research has shown that there is an inverse association between fiber consumption and energy intake over time. Based on recommended energy intake, the Dietary Reference Intakes suggests that adults consume 14 g dietary fiber per 1000 kcal, or 25 g for adult women and 38 g for adult men. However, current usual intakes in the United States are only about 15 g/day. The effect of increasing fiber intake on body weight, specifically oligofructose, has been examined in various animal trials; however, few human studies have investigated the same outcomes. In 2009, Parnell and Reimer specifically investigated the effect of oligofructose supplementation on weight loss in overweight and obese adults. These authors saw a red uction in the body weights of the oligofructose supplemented group in comparison to the increased body weights of the control group. The aim of the present study was to determine the effect of the daily consumption of yogurt and snack bars, containing 16 g oligofructose, a fermentable fiber, on average daily energy intake and body weight compared to daily consumption of similar control foods. Ninety eight healthy individuals, 18 to 50 years of age, with a BMI between 23.0 29.9 kg/m 2 were recruited from the University of Florida campus, Gainesville, FL for a 10 week randomized, double blind, controlled study.


12 P articipants completed seven consecutive automated 24 hour recalls at four different time points throughout the study, baseline, and weeks 4, 6, and 8 t o assess energy intake. Body composition assessments were obtained at both baseline and study completion. There were no significant differences in energy intake amongst participants of the control and oligofructose group. Additionally, t here were no effe cts on body weight observed in participants These results suggest that despite the study group, participants were successful at substituting the study foods into their diets, to maintain energy intake, as counseled Future research should explore whether the snack foods containing the oligofructose may impact energy intake and body weight when counseled for energy reduction.


13 CHAPTER 1 LITERATURE REVIEW Obesity Obesity Trends and Health Risks Obesity and overweight are usually expressed in terms of body mass index (BMI) in epidemiological studies height in meters squared (kg/m 2 ) (1) The World Health Organization classifies adults with a BMI of greater than or equal to 30 kg/m 2 as obese, and overweight as a BMI of 25 29.9 kg/m 2 (2) Although BMI is a functional tool for expressing overweight and obesity population wise, its use regarding children is more controversial than with adults (3) Nevertheless, children can be defined as being obese or overweight if their weight to he ight ratio exceeds a certain age and sex specific interval (1) yet fully understood. In general though, the development of overweight and obesity occurs as a result of an energy imbalance, specifically when caloric intake chronically exceeds ene rgy expenditure. behind this global epidemic, no sole cause of obesity has been identified. Instead, there exists a complex and multi factorial blend of genetic, psychological, environmental, social, economic, and physiological factors, occurring at varying quantities tha t may also contribute to the development of obesity (4) More specifically, environmental changes (1) including the steady decline in physical activity, in creased consumption of fast food, excessive sugar intake from soft drink s (5) the numerous advances in technology includi ng: social networking, gaming, television watching, and other sedentary behaviors, contribute primarily to the onset and progression of obesity (4)


14 Obesity is not limited to one particular demo graphic. Instead, it affects people of all ages, racial and ethnic groups. Prior to the 1980s, reports of obesity rates were below 10% in many developed countries (6) Now, however obesity rates have reached rampant proportions, in the United States especially where 32% of adults are reported clinically obese and an additional 68% are considered overweight (7) Reports of childhood obesity in the United States have more than doubled, since the 1970s when it was estimated to be 5% among preschool children, 6.5% a mong children aged 6 11, and 5 % amongst adolescents (8) T he most recent U.S report however, estimates that the prevalence of obesity between 2009 and 2010 in both children and adolescents aged 2 through 19 years, was 1 8 4 % (9) which correlates directly to the upward trend seen in adults Obesity is not a benign condition. As the incidence of obesity across various age groups has increased the co morbidities associated with obesity have escalated as well (10) O besity is a key risk factor for the development of diabetes, hypertension, stroke, cardiovascular di sease, certain cancers, liver disease, and musculoskeletal disease (11, 12) Previous studies have shown that a modest decrease in body weight is associated with a significant decrease in the risk for chronic diseas es. For instance, a 58% reduction in the incidence of diabetes occurred in participants of the Diabetes Prevention Program (DPP), lifestyle intervention (13) In this study, 3, 234 non diabetic individuals with eleva ted fasting and post load plasma glucose concentrations were rand omized to one of three groups to receive either the placebo metformin or a lifestyle modification program and were followed for approximately 3 years. After implementation of specific beha vior modifications to achieve weight loss, the lifestyle


15 intervention was shown to be more effective than metformin treatment for reducing the incidence of diabetes in participants at high risk (13) T hus t reatment plans for overweight and obese adults are essential to the restoration of the health status for the U.S population. Prevention and Treatment Methods With the considerable increase in the prevalence of obesity across various demographics, there has been a joint increase in the demand for treatment and prevention options (14) However, it is important to consider the fact that excessive adiposity is harder to regulate once it has been established. Several large, randomized, clinical trials have compared the efficacy of a variety of nutritional approaches for decreasing overweight and obesity, al though few stu dies have followed participants for more than two years. Several large trials have also sought to determine whether t a rgeting s pecific macronutrient s or macronutrient combinations are best for weight loss and weight maintenance (15) For instance, a low carbohydrate diet was shown to be an effective alternative to a low fat diet for achievi ng weight loss in 32 2 moderately obese individuals. In this study, participants were randomized to one of three diets: low fat, restricted calorie, Mediterranean diet, restricted calorie, or low carbohydrate, non restricted calorie (16) The mean weight loss for the low fat group was 2.9 kg, 4.4 for the Mediterranean diet group, and 4.7 kg for the low carbohydrate group (P <0.001 for the interaction between diet group and time) (16) While a lower carbohydrate eating plan produces weight loss more rapidly and to a greater extent, over time the targeted macronutrient or macronutrient combination diets are of less importance than ad herence to the study protocol. T h erefor e behavi oral aspects are most closely asso ciated with long term success (15)


16 Additional treatment methods exist and encompass behavior modification. R educing dietary fat intake, calorie restriction plan s, portion control, and increasing physical activity levels have been methods explored by clinicians in attempts to reduce body weight in o verweight and o bese p articipants According to data from the National Weight Control Registry, restricting certain foods, limiting quanti ties, and counting calories were the three most commonly reported strategies manipulated to achieve weight loss (17) In a meta analysis of low fat diets, weight gain was prevented in normal weight participants who restricted dietary fat intakes, and weight loss actually occurr ed in the overweight participants (18) Additionally, energy density and portion sizes were suggested to influence satiety and energy intake synergistically. In a 2004 trial, Rolls et al. showed that high consumption of low energy dense foods, like salads, reduced energy intake and participants reported feelings of fullness (19) Another study comparing the effect of a structured diet and exerc ise program (SDE) to a basic meal replacement program (MRP), found that a combination of diet and exercise in sedentary, obese women was significantly effective in the promotion and maintenance of weight loss (20) Although positive effects have been shown through these findings, adherence to such dietary changes and creating a sustainable energy deficit is challenging, and many regain weight that was lost. As a result the development of a treatment program for both adults and children should consider a variety of factors influencing obesity, including changes individually, nationally, environmentally, and could also encompass state and national policy. As mentioned, previous approaches have included a focus on macro nutrients, such as combination of low fat, low carbohydrate and/or high protein diets. More


17 recently though much attention has been given to dietary fiber as a potential approach for reducing energy intake (21, 22 ) The effect of increased dietary fiber consumption on energy intake, has been researched in various animal trials (23) however, large, randomized, controlled trials have not yet investigated its impact on overal l energy intake and body weight in humans. Previous epidemiological research (24) has shown that there is an inverse association between fiber consumption and energy intake over time. In 2009, Parnell and Reimer specifically investigated the effect of oligofructose supplementation on weight loss in overweight and obese adults (25) These authors saw a reduction in the body weights of the oligofructose supplemented group in comparison to the increased body weights of the control group. High fiber d iets high are known to provide bulk, and are believed to contribute to satiety. Therefore, increasing dietary fiber in take may be an additional way to assist with susta ining a negative energy balance, without one experiencing feelings of hunger and deprivation, thereby result ing in significant weight loss. Fiber Definition Dietary fiber is defined physiologically rather than by its chemical composition, unlike the definition of various micronutrients, such as vitamins and minerals. Non digestibility in the small intestine is the most important property mentioned when defining dietary fiber, meaning that, upon consumption the food item reaches the large intestine intact. In 1976, Hugh Trowell defined dietary fiber as the residue of plant cell walls that is resistant to hydrolysis by human digestive enzymes (26) Following Trowell, dietary fiber was defined differently by various chemists, researchers, and scientific organizations. However, four main definitions formulated by the American Association of


18 Cereal Chemists (AACC), the Institute of Medicine (IOM), the European Union (EU), and the Codex Alimentarius Commission (Codex) ar e commonly mentioned when discussing dietary fiber. analogous carbohydrates that are resistant to digestion and absorption in the human small intestine, with complete or partial fer mentation in the large intestine and includes (27) In digestible (27) Another derivation of the definition came about in 2008 by the EU, describing as polymers with 3 monomeric units, which are neither digested nor absorbed in the human small intestine and belong to the following categories: (i) edible carbohydrate polymers naturally occurring in the food consumed; (ii) edible carbohydrate polymers that have been obtained from food raw materials by physical, enzymatic, or chemical means and that have a b eneficial physiological effect as demonstrated by generally accepted scientific evidence; and (iii) edible synthetic carbohydrate polymers which have a beneficial physiological effect as demonstrated by generally accepted scientific (27) Although the above definitions regarding dietary fiber exist, prior to 2009, an accepted, uniform definition of the term d id not. In June 2009, at the Codex Alimentarius Commission on Nutrition and Foods for Special Dietary Uses meeting in South Africa, a consensus was reached regarding a universal definition of fiber. Both the W orld Health Organization (W HO ) and the Food and Agriculture Organization (FAO) defined fiber as carbohydrate polymers with 10 monomeric units which are not


19 hydrolyzed by the endogenous enzymes in the small intestine of humans and belong to the following categories: (i) edible carbohydrate polymers naturally occurring in the food as consumed; (ii) carbohydrate polymers, which have been obtained from food raw materials by physical, enzymatic or chemical means and which have been shown to have a physiological effect of benefit to health as demonstrated by generally accepted scientific evidence to competent authorities; and (iii) synthetic carbohydrate polymers which have been shown to have a physiological effect of benefit to health as (27) This accepted definition is nearly identical to the previous definition developed by the EU. Fiber Recommendations and U nited States Intakes Adequate Intake levels for fiber are related to recommended energy intake. Based on various epidemiological studies, Dietary Reference Intakes (DRI) recommends the consumption of 14 g dietary fiber per 1000 kcal or 25 g/day for adult women consuming 2000 kcal/day, and 38 g/day for adult men consuming 2600 kcal/day In contrast to the se recommendations, the intake of dietary fiber in the United States has declined over the past decade, and is estimated to be well below the recommendation, at approximately 15 g/day (28) Sources and Classification of Fiber An e ducational e mphasis has been placed on the consumption of foods that are rich in nutrients and provide increased amounts of dietary fiber. F ruit, vegetables, whole grains legumes, and nuts are common sources of natural fiber. However, servings of these occasionally consumed foods provide small amounts of dietary fiber to the diet (1 3 g), whereas, food such as white flour and/or white potatoes add dietary fiber in greater


20 quantities, d ue to higher consumption d espite their nutritional value (29) Dietary fiber can also be provided in the diet by supplements, including psyllium, wheat de xtrin, inulin, guar gum, and methylcellulose. Although supplementary options exist as a means to adding fiber to the diet, use of fiber su pplements are not highly recommended Instead, dietary fiber is encouraged to be obtained naturally via the consumption of fiber containing foods (30) D ietary fibers are categorized as one of two ways, on the basis of water solubility, and both fiber types can be consumed simultaneously in the daily diet (Figure 1 1) They are also distinguished by their viscous or non viscous properties Viscosity may be incorporated in examples of both types. Soluble fiber, consists of the components that are water soluble and includes pectic substances (31) which are polysaccharides comprising galacturonic acid, a sugar acid, and a variety of other sugars. Mucilages, which are present in the cells of the outer layers of seeds of the plantain family, also belong to the soluble fiber classification. Other relatives of pectins and mucilages include some hemicelluloses, storage polysaccharides, such as guar gum, beta glucan s, and resistant starches (30) H emicelluloses are polysaccharides containing suga rs other than glucose that are associated with cellulose in cell walls and are present in both water soluble and insoluble forms (32) Gums also known as hydrocolloids are derived from plant exudates such as agar. Both gums and pectins are used as gelling agents, thickeners, and emulsifying agents, h ence their viscous properties B eta glucans are glucose polymers that are branched in structure, unlike cellulose, which enables them to form viscous solutions (32) Finally, the term Resistant Starch (RS), refers to the fraction of


21 starch resistant to digestion by human enzymes in the small intestine and reaches the colon for fermentation by colonic microbio ta (33, 34) RS1, the type most closely related to dietar y fiber, is starch that is physically inaccessible to digestion, and is found in whole or partly milled grains, seeds, legumes, and pasta (35) Sources include oat bran, psyllium, some fruits and vegetables, legumes, barley, and soybeans In contrast, insoluble dietary fibers are those components that are not water soluble, r esistant to digestion by human enzymes (32) and include lignin and non star ch polysaccharides such as cellulose and some hemicelluloses (31) Cellulose is the main structural component of plants that provides strength and stability (36) It is described as a polysaccharide comprising up to 10,000 closely packed gl ucose units arranged linearly (32) Lignin on the other hand, is not described as a polysaccharide, but bound chemically to previously mentioned hemicelluloses, like a glue, in plant cell wa lls, instead (32) Good sources of insoluble fibers are vegetables and whole grains, such as wheat bran, cereal grains, oat hull brown rice, and whole wheat breads (29) Previous methods for fiber analysis underestimate d the amount of fiber present in foods according to the newly developed dietary fiber definitions. The Association of Official Analytical Chemists International (AOAC International) procedure for analyzing fiber components dates back as early as 1976. The Official Method of Analysis (OMA) 985.29 in conjunction with other methods, used enzymes to remove the majority of starch and protein from dietary fiber (37) However, specific types of fibers, other than non starch polysaccharides ( NS P) and lignin, were not recovered using this method (27) ; probably because of the use of multiple methods allowing analysis overlap (32) Despite the previous lack of an accepted fiber analysis method, in 2008, the AOAC


22 In ternational began the development of a revised method that would allow measurement of all fiber types using a single AOAC International method (32) Fermentable Carbohydrates Carbohydrate fermentation is a break down and energy acquisition process that occurs by anaerobic bacteria and yeasts. The ener gy that is obtained during this process is necessary for growth of colonic bacteria, maintenance of cellular function, and overall gastrointestinal health (37) Many of the dietary fiber examples mentioned abov e will undergo fermentation in the large intestine, upon consumption. Resistant starch, for example, is considered one of many fermentable carbohydrates, because it passes through the small intestine undigested. Carbohydrates as such are desired substrates for colonic microbiota. Substrate interaction with colonic microbiota produces short chain fatty acid s (SCFA) such as butyrate, propionate, and acetate B utyrate however, is favored for use as fuel for colonic mucosal cells (21) and is essential to the maintenance of epithelial health (35) Although not previously mentioned, some oligosaccharides such as f ructooligosaccharides (FOS) and galactooligosaccharides (GOS), are also fermentable carbohydrates that influence the activity of the colonic microbiota. Oligosaccharides consist of linked monosaccharide units (38) The generic terms have been used by researchers inconsistently throughout the years to describe these fructans Howev er properties, such as structure manufacturing method, and degree of polymerization (chain length) of these oligosaccharides do vary (39) Inulin, f or example, is used as a generic term used to collectively refer to all lin ear fructans with (2 1) fructosyl fructo se glycosidic bonds (40) When described, fructooligosaccharide and oligofructose, sound fairly similar, and are sometimes used


23 interchangeably However, DP is the differentiating factor between the two and the description of inulin. Whereas, inulin has a DP ranging from 3 60, short chain fructans with a DP of < 10 are termed oligofructose (27) (Figure 1 2) Nevertheless, inulin type fructans are found both naturally in foods, primarily fruits, vegetables, and grains or extracted from its natural food sources, the chicory root, and added to food products (39, 41) T hey are also widely accepted a s dietary fibers because of fe rmentation and bulking capabilities (27) Health Benefits of Adequate Fiber Intake Di etary fiber is considered a functional food because of the health benefits it provides upon consumption (28) The ecological observations of Burkitt et al. (42) first interests in the cause of chronic diseases were heightened as he observed reduced occurrences of certain diseases in Afric a, opposite of the observations seen in Western civilization. In a study where the diets and disease patterns of both Westernized and non Westernized cultures were evaluated, Burkitt and colleagues theorized that similar diseases and incidences in populati ons may stem from similar causes. From the work of may underlie development of many chara cteristically Western diseases (43) The association between fiber intake and chronic disease has gained more at tention as data has accumulated. Several investigations have identified specific types of fiber mediating this correlation. Although the exact mechanism(s) have yet to be understood entirely, dietary fiber has been shown to play a protective role against t he development of obesity and associated diseases, including diabetes, cardiovascular disease, gastrointestinal diseases, and certain cancers (11)


24 Fiber and d iabetes Type 1 diabetes (T1D) is considered to be an aut o immune disease, whereas type 2 diabetes (T2D) is referred to primarily as a metabolic disease. Obesity is common in T2D, and is rarely seen in those with T1D. Similar to increases in obesity rates, diabetes rates have also reached dramatic levels. For instance, in 1997, 124 million people worldwide were estimated to be diagnosed with diabetes, and 97% of t hat population was likely to have Type 2 diabetes m ellitus (formerly non insulin dependent diabetes mellitus) (44) According to statistics provided by the American Diabetes Association, 25.8 million (8.3%) children and adults in the United States currently have diabetes. Additionally in 2010, another 1.9 million new cases of diabetes were reported in individ uals who were at least 20 year of age and older. The risk for diabetes and the effects of fiber consumption, specifically from whole grain cereals, have also been reported in several investigations. In the Framingham Offspring Study II, a cross sectional study of 2,941 participants, whole grain intake and metabolic risk markers were assessed. Investigators were able to show that the intake of dietary fiber of whole meal bread and whole grain cereals was inversely related to the following indicators: BMI, w aist to hip ratios, total cholesterol, l ow densi ty lipoprotein cholesterol, and fasting insulin levels. It was concluded that a reduction of diabetes risk may occur by the favorable influences on metabolic risk factors, as a result of increasing the intake of whole grains (45, 46) Improvement of beta cell function led to increased insulin secretion in male and female participants of a randomized crossover study. Juntunen et al. (2002) investigated the factors of grains that affect post prandial glucose and insulin responses by examining markers for gastric emptying and fasting and postprandial blood samples (46, 47) In another study conducted in men from the Health


25 Professionals Follow up Study, refined and whole grain intakes were measured every 4 years via food frequency questionnaires, by Fung et al ( 2002) which subsequently predicted T2D risk (48) Investigators of this study showed a reduction in the risk for diabetes by 30%, a decrease mediated again by cereal fibers. Although these investig ations suggest whole grains specifically decreasing the risk for diabetes, other studies have shown protective effects against diabetes with the consumption of soluble fibers further perpetuating the benefit of f iber intake, overall Fiber and c ardiovascular d isease The strong relationship between dietary fiber and its protection against CVD, and the basis for the current DRI recommendations, was established using data from epidemiologic, cohort studies (29) These studies used food frequency reports to assess dietary fiber intakes and followed participants prospectively until CVD was detected (29) Since the intake of dietary fiber displayed protective effects against CVD, an Adequate Intake (AI) for fiber has been determined. S oluble fiber is thought to affect several cardiovascular disease (CVD) risk factors. While soluble fiber has affected risk factors for CVD positively, food sources of insoluble fibers, primarily from cereal products, have been associated most consistently with reduced in cidence rates of CVD (49) Although a clear inconsistency exists between the effects of soluble versus insoluble fiber types, there is evidence promoting a nutritional regime that provides a combination of fiber types for CVD prevention, such as a diet com prised of fruit, whole grain cereals, and vegetables. An increasing number of findings from observational studies have illustrated lower incidences of coronary heart disease in participants reporting the consumption of diets


26 high in fiber. In a recent pool ed analysis of 10 cohort studies, Pereira et al. showed a direct inverse relationship between dietary fiber consumption and the risk for coronary heart disease, in all but one of them (50) In a large, prospective cohort study conducted strictly in US women, Wolk et a l. examined the association between long term int ake of total dietary fiber, as well as fiber from other sources and the risk of coronary heart disease ( C HD ) (51) A significant inverse association was observed between intake of dietary fiber and risk of CHD, particularly confined to cereal fiber sources. In another q uintile of fiber intake (median 22.9 g/day) had an age adjusted relative risk for major coronary events that was 47% lower than women in the lowest quintile (11.5 g/day) (52) Furthermore, in a 2004 longitudinal study (the HALE project) it was demonstrated that the men and women adhering to a particularly high fiber diet, such as the Mediterranean diet, experienced a 29% reduction in CVD mortality over a 10 year period (53) In addition to the findings of observational and cohort studies, randomized clinical trials have also reported associations between high fiber intake and CVD risk. For instance, w hen comparing the effects of soluble fiber (P. ovata husk) with those of insoluble fiber (P. ovata seeds) in men with ischemic heart disease, Sol et al. demonstrated that intake of the soluble fiber induced a more ben eficial effect on the cardiovascular lipid risk factor profile than does an equivalent intake of insoluble fiber (54) Fiber and c ancer The effects of increase d in dietary fiber consumption has supported existing hy potheses regarding a range of diseases. Participants that were given specific fiber


27 sources saw decreases in either weight, risks for diabetes, cardiovascular disease, and/or gastrointestinal diseases. Although fiber is being considered to play a role in t he protection against certain cancers, experimental studies have shown that excessive energy intake predisposes to tumor development (55) In a prospective study among women that examined fiber intake and the risk of colon cancer, evidence for the above hypothesis was supported. Willett et al (1990 ) concluded that a high intake of animal fat increases the risk for colon cancer (56, 57) during his observation of the effect of fiber on diverticular disease, which was said to occur as a result of fiber lacking in the diet (55) Burkitt advertised the hypothesis that the refining of grains and the lack of dietary fiber in the diet may be implicated in colorectal cancer. F urthermore, he suggested that large bowel fermentation, increased stool bulk, and high fecal output that occurs from consumption of insoluble fibers consequently relates to colorectal cancer rates. Since this observation, dietary fiber has been postulated to play a preventative role in colorectal carcinogenesis (58) For instance, in an observati onal study Cassidy et al (1994) determined inverse epidemiological relationship between total star ch intakes, RS, and NSPs and large bowel cancer risks (59) Although the molecular mechanism has yet to be elucidated, one mechanism Burkitt and colleagues suggests relates to the bacteria proliferation that occurs upon fiber consumption. The effect of dietary fiber specifically on colorectal cancer risk and protection has been documented in some studies. However, although a large body of evidence exists from epidemiologic, clinical, and experimental studies (60)


28 regarding the assumed role of fib er in cancers, the theory remains inconclusive, and therefore needs further study. In one study conducted in a cohort of 60,000 women (Swedish Mammography Cohort), Larsson et al (2005) prospectively examined the association between the consumption of whole grains and colorectal cancer risk, and concluded that a high consumption of whole grains, such as rye bread, may decrease the risk of colon cancer in women (61) Similarly, i n a l arge, prospective cohort study the N ational Institute s of Health A merican A ssociation of R etired P ersons D iet and H ealth S tudy total dietary fiber and whole grain consumption were examined in 291,988 men and 197,623 women aged 50 71 years old Total dietary fiber intake was found to not have an association with colorectal cancer risk, while whole grain intake was associated with a reduced risk, although statistically insignificant (62) The relationship between dietary fiber and the risk of colorectal cancer and adenoma in women only wa s examined by another group who found no significant association between fiber intake and the risk of colorectal adenoma found (58) An identical conclusion was drawn by Michels et al in 2004 after the prospective investigation of the association of fiber intake with the incidence of colon Professionals Follow up Study) was examined (63) The data compiled from the above cohorts did not indicate a significant association between fiber intake and colorectal cancer. As previously stated, various research e xist throughout the literature concerning the relationship of fiber and cancers. Findings from animal studies and some clinical trials have suggested that wheat bran cereals may consist of substances that may lower t he risk for colorectal cancers (64) Nevertheless, although few reports have illustrated


29 an inverse correlation between dietary fiber intake and colorectal cancer risk, the inconsistency of finding s justifies the need for clinical trials examining this relationship on both a molecular and physiological level. Fiber and o besity Because of the known physiologic effects, high fiber consumption has been proposed to potentially effect energy regulation, and promote weight loss Various studies examining energy intake during the consumption of high or low fiber diets observed a decrease in intake in the p articipants consuming a higher fiber regimen (65) For example, I n a randomized, double blind controlled trial, participants consuming 21 g oligofructose per day experienced a 1.03 0.43 kg reduction in body weight, whereas the body weight of the control group increased by 0.45 0 .31 kg over a 12 week period (25) association between changes in whole grain consumption and weight gain over 12 year s, Liu et al. (2003 ) showed that body weight gain was inversely associated with whole grain intake (23) Participants consuming greater intakes of whole grains experienced less weight gain than those consuming refin ed grains. In contrast, Gropper et al. (1987) reported in a 4 week, childhood obesity related study, using 15 g dietary fiber supplements per day, that there was no statistically significant mean weight loss in the fiber supplemented children compared to p lacebo supplementation (66) However, the weight loss that occurred was greater in the fiber su pplemented children (67) Al though the primary aims and methodologies differ amongst the said studies, they ha ve all come to a related conclusion: an inverse relationship exists between the consumption of dietary fiber and weight loss.


30 Participants in the above studies were more like ly lose weight when consuming a high fiber diet than the low or non fiber consuming counterparts. Developing countries that report high fiber consumption also report lower rates of obesity (21) Because dietary fiber intakes in the United States are currently less than half of the recommen dation, while obesity rates are colossal, increasing dietary fiber in the diet, at least to the recommended amount, may be one strategy used to reduce the prevalence of obesity. Currently, intervention studies assessing these potential beneficial effects h ave not been tested with all types of fi bers, including oligofructose. However, most studies focus consistently on increased intake of whole grains, fruits and vegetables. Fiber and s atiety Gut microbiota. T he human large intestine is diversely inhabited b y populations of microorganisms that respond to dietary changes, particularly the quantity and type of dietary carbohydrate consumed (68) Proliferation of specific gut microbiota, such as bifidobacteria and lactobacilli species, ultimately benefits the host through the process of selective fermentation. Benefits of bacterial enhancement include the production of short chain fatty acids (S CFA), such as butyrate, which provides an improved resistance to gut infections (39) a nd reduces the pH of the colon. Oligofructose is a fermentable fiber known to initiate a prebiotic response upon consumption All fermentab le carbohydrates are not classified as prebiotics The its origination, and is constantly expanding. In 1995, Gibson and Roberfroid digestible food ingredient s that beneficially affect the host by selectively stimulating the growth and/or activity of one or a limited number of bacteria in the colon, and thus


31 that allows spe cific changes, both in the composition and/or activity in gastrointestinal microflora that confers benefits upon host well being and h (69) The abundance of gut mic robiota as a result of inulin type fructan ingestion has been demonstrated in a range of studies, and at varying doses. Menne and Guggenbuhl (2000) saw a significant increase in bifidobacteria compared to baseline when particpants (n=8) were fed 8g /day fru ctooligosaccharides for five weeks (70) Similarly, significant increases in bifidobacteria were shown in 12 healthy adults given 4 g/day short chain fructooligosaccharides in a controlled diet, for 25 days (71) Forty healthy volunteers experienced significant increased bifidobacteria dose dependently, over the course of 7 days when fed between 2.5 and 10 g short chain fructooligosaccharides (72) Lastly, Kleessen et al. (1997 ) also observed a significant increase in bifidobacteria, in addition to decreases in enterococci and enterobacteria in 35 constipated elderly individuals for a period of 19 days (73) Participa nts in this trial were either lactose or fed 20 g/day inulin fo r the first 8 days, and the dose was increased to 40 g/day gradually for the remaining 11 days of the study (73) Gut hormones The molecular mechanism of oligofructose action still requires additional study H owever, as a substrate for colonic bacteria it plays a role in gene regulation (68, 74) Additionally, the inverse association of oligofructose consumption and energy intake over time may be due to effects of gut hormones. There are several candidate gut hormones that may have involvement in increased satiety and decreased energy intake, such as glucagon like peptide 1 ( GLP 1 ) and peptide YY (PYY). As previo usly mentioned, colonic fermentation provides energy for beneficial gut bacteria. It


32 is suggested that the products of fermentation trigger an increase in gut hormone GLP 1, leading to an increase in satiety signals in the brain, and ultimately triggering a reduction in energy intake. Since GLP 1 functions to inhibit gastric acid secretion and emptying, it is believed to be the key hormone regulating the effect of fermentable fibers on energy intake (41) Contrary to the function of GLP 1, gut hormone PYY, which is released into circulation shortly after food intake, is believed to be the chief contributor to the feelings of fullness and satiety (75) The hypothesis that oligofructose consumption may decrease energy intake is based primarily on results derived from rodent studies (76) In a recent study using rats, both energy intake and satiety were shown to be positively influenced over time by the administration of oligofructose to a high fat diet (77) In this study oligofructose f ermentation led to an increase in pro glucagon mRNA in the cecum and the colon, and an increase in glucagon like peptides, GLP 1 and GLP 2 contents in the proximal colon. GLP 1 is released from the enteroendocrine L cells in response to nutrient ingestion Consequently, the fermentation of oligofructose into SCFA in the gut has been shown to promote enteroendocrine L cell differentiation by up regulating differentiation factors (neurogenin 3 and NeuroD), thus contributing to higher endogenous GLP 1 levels (76) that the rats were protected against the promotion of energy intake, body weight gain, and fat mass development. Fermenta ble fibers may also affect hormones such as ghrelin, which is the oligofructose fed rats, ghrelin level s were positively modulated (41) Throughout the


33 experiment researchers saw that dietary energy intake was significantly lower in oligofructose fed rats compared to control rats. They concluded that the low dietary energy intake led to a significant decrease in epidydimal fat m ass at the end of the treatment period. Ghrelin is an important hormone to consider when examining obesity cases molecularly, because active ghrelin concentration in plasma normally increases during food deprivation and falls rapidly during a meal. However food intake fails to suppress it in the obese, which could explain overeating (75) In this study after eight hours of food deprivation, active ghrelin in the plasma remained significantly lower in the oligofructose fed rats compared to control rats, suggesting that oligofructose consumption somehow mediates the reduced signals of the hunger hor mone. Assessing Energy Intake The 2010 Dietary Guidelines for Americans was developed using data from previous dietary assessments. Various methods exist to assess both the quality and quantity of individual diet or energy intakes. These tools are commonl y employed in research settings, especially clinical intervention studies. However, the accuracy and validity of these tools is strongly debated amongst researchers Despite the debate, three w idely used dietary assessment examples include diet records, fo od frequency questionnaires (FFQs) and 24 hour diet recalls (78) Diet Records As the name suggests, diet records food and beverage intakes, generall y collected over 3 to 4 days, ideally at the time of consump tion (79) Study participants are usually trained thoroughly by study personnel on how to properly complete the food record. One major training point involves capturing accurate measurements of the amounts of foods/drinks consumed in a 24


34 hour period. However, there are instances in which over or underreporting takes place, which has been iden tified as major disadvantage s to this dietary assessment tool. Other disadvantages regarding food records includ e high personnel costs, incomplete reports over time, and respondent burden, to name a few (79) Advantages for using diet records include altered dietary behaviors and effectiveness as a weight loss tool (79) both of which c ould be due to the awareness created when self monitoring Advantages and disadvantages of diet r ecord use should encompass the aim of the particular study in which the method is being integrated Food Frequency Questionnaires F ood F requency Questionnaires (FFQs) are another method by which clinical researchers assess dietary intakes in research T he content of typical FFQs is usually 100 items and completion time requires between 30 to 60 minutes (79) They hav e been (80 ) t o dietary assessment because of low cost and lack of respondent burden (79) Research ers at the National Cancer Institute (NCI) primarily developed FFQs to determine usual intakes from food lists (80) They can also be used to target specific groups of people by their long term intake of various nutrients for epidemiological studies (78) The fact that FFQs are usually completed by a study participant is believed to discred it the validity of this method in addition to measurement error (79) As seen with the us e of diet records, underreporting by study participants has also been shown to occur with the completion of FFQs. 24 Hour Diet Recalls Twenty four hour diet recalls may be conducted in a number of ways, including personal or telephone interview, computer p rograms, or via paper and pencil. When


35 completing a 24 hour recall, participants are prompted to report all food and beverages consumed in the previous (79) In an interview, specific questions and statements are used by the interviewer to help the respondent recall their consumption history. This requires that inter viewe rs are well trained in their understanding of food s, beverages, and measurements A major advantage of diet recalls as opposed to record methods, necessarily influenced because reporting occurs after consumption o f food items (79) I naccurate reporting may still occur for several reasons, especially be cause participants are reporting from memory, though. This method is said to be the very useful in population based studies, because of its ability to reveal dietary patterns of particular samples (81) Limitations of conducting 24 hour recalls include the time and labor demand to co Various online self administered dietary interviews have been developed and used in population studies however only one cur rently utilizes the U nited States Department of Agriculture (USDA) Automated Multiple Pass Method (AMPM) as the source of the interview questions (82) The Automated Self Administered 24 hour recall (ASA 24) d eveloped by the National Cancer Institute (NCI) in 2009, is the first system allowing for collection and automatic coding based on the AMPM, and is an example of a web based method by which individual dietary intake data is collected and assessed. The mult iple pass method is a 5 pass National Health and Nutrition Examination Survey (NHANES) (83)


36 The ASA 24 interview database compiles approximately 7000 Food List Terms into 24 food groups and 243 food subgroups. Additionally more than 1100 different probes are available for respondents to provide details about foods consumed. Lastly, photographs are available in the ASA 24 system to represent portion sizes of consu med foods (82) (APPENDIX C) The amount of food consumed, description, additions to the food, time and place obtained and eaten, and name of eating occasion are all recorded for each recall (82)


37 Figure 1 1. Adapted from Viuda Role of Fiber in Cardiovascular Figure 1 2. The structure of an oligofructose molecule


38 CHAPTER 2 PURPOSE High fiber intake is commonly ass ociated with a lower body weight. The effect of increasing dietary fiber intake on body weight, specifically oligofructose, has been examined in various animal trials, however, research investigating the same outcomes is lacking in human studies. Although previous epidemiological research (24) has shown that there is an inverse association between fiber consumption and energy intake over time, the execution of large, randomized, clinical trials have not been undertaken to determine whether an increase in oligofructose impacts the overall energy intake and body weight over time. Therefore the specific aims of this study are to determine the effect of yogurt and snack b ars containing 16 g oligofructose compared to the control, on average daily energy intake and body weight over eight weeks of supplementation We hypothesize that both average energy intake and body weights will decrease in those consuming the study foods with the added oligofructose. Positive results from this study could not only benefit study participants, bu t could also be used as a broad tool in weight management.


39 CHAPTER 3 METHODS Participants Participants were recruited from the University of Flori da campus via flyers, posters, and announcements in the early fall of 2011. They were eligible to participate in the study if the y: were b etween the ages of 18 and 50 ; were w illing to co nsume yogurt and a snack bar daily for eight weeks ; h ad I nternet acces s for the du ration of the study (~10 weeks); h ad a BMI of 23.0 to <30 kg/ m 2 ; were w eight stable (5 lbs. last 3 months) ; were w illing to complete daily questionnaires and 28 dietary reca lls over approximately 10 weeks; and w ere habitual breakfast consumers which was defined as eating breakfast (any food within 2 hours of waking) 5 or more days a week Potential p articipants were ineligible for this study if they: h ad any disordered eating habits as the restraint construct of the Eating Inventory questionnaire ; w ere post menopausal (self reported no menstrual period for one year) ; were current smoker s or tobacco user s; c ontinued using any prebiotic and fiber supplements, or probiotic supplement ; c ontinued antibiotic use within 2 mo nths prior to study start ; h ad any known food allergies ; h ad a physician diagnosed gastrointestinal disease or condition other than Gastroesophageal Reflux Disease ( GERD ) constipation, or peptic ulce r disease, Celiac disease, short bowel disease, ileostomy, colostomy) ; w ere taking prescribed medications other than oral contraceptives, seasonal allergy medications, cholesterol or blood pressure lowering medications, vitamins or minerals, baby aspirin ; h ad an intake of >2 alcoholic drinks per day on average ; p articipated in purposeful exercise of >300 minutes (5 hours) per week on average or was a lactating


40 or pregnant female. Approval from the University of Florida Institutional Review Board 01 (IRB 01 ) was obtained (Appendix A) and written informed consent was obtained from all study participants (Appendix B ). Experimental Design A ten week, randomized, double blind, controlled, parallel arm study was completed with 98 healthy adults, ages 18 50 years old (Figure 3 1) Un blinding of researchers occurred after all statistical analyses were performed. Participants began the protocol in a rolling start manner, in seven waves referred to as sections P articipant s in their respective section s consumed one study food (snack bar) for the first seven days of the study, in order to become acclimated to the fiber in the event that they were randomized to the oligofructose group On the eight h day from randomization each participant was instructed to begin cons uming both study foods (snack bar and yogurt) and to continue consuming them for the duration of the study. Section 1 (n = 7) was randomized on September 14, 2011, Section 2 (n = 6) was randomized on September 15, 2011, Section 3 (n = 15) was randomized o n September 20, 2011, Section 4 (n = 12) was randomized on September 21, 2011, Section 5 (n = 22) was randomized on September 22, 2011, Section 6 (n = 24) was randomized on Septem ber 23, and Section 7 (n = 11) was ra ndomized on September 27, 2011. Pre Base line and Baseline Eligible participants were consented over the course of seven days. At the height, weight, and BMI which was calculated by inputting the screening height/w eight into the BMI calculator on the National Heart Lung and Blood Institute website ( http://www.nhlbisupport.com/bmi/ ), and study coordinators completed the p re baseline


41 data collection sheet with participants The p re baseline data collection sheet consisted of demographic questions incl uding date of birth gender, ethnicity (Hispanic or non Hispanic), race (American Indian or Alaska native, Asian, Black or African American, N ative Hawaiian or other Pacific Islander, and/or White) Of the five categories listed (American Indian or Alaska Native, Asian, Black or African American, Native Hawaiian or other Pacific Islander, and/or White), the choices were narrowed down to four categories: White, Black, Asian, and Other Participants reporting that they were White only, American Indian and W hite, or Native Hawaiian and White were classified as White. Participants reporting that they were black only, American Indian and Black, or Native Hawaiian and Black were classified as Black. Participants reporting that they were Asian only, American Indi an and Asian, or Native Hawaiian and Asian were classified as Asian. Lastly, those who reported that they were Black and White, Black and Asian, or White and As Additionally p articipants were asked to complete a series of el igibility questionnaires/surveys including: Fruit/Vegetable/Fiber screener ( NutritionQuest Copyright 2009, Berkeley, CA), the Global Physical Activity Questionnaire (World Health Organization Version 2.0, Geneva, Switzerland), and the dietary r estraint co nstruct of the Eating Inventory, formerly known as the Three Factor Eating Questionnaire (Pearson, Inc., Copyright 1988). Participants could have scored a maximum score of 21 on the restraint portion of the Eating Inventory; however, a score of 14 was us ed as the cutoff. Each participant was trained on how to complete the online daily questionnaires and the online 24 hour diet recall, using the beta version of the Automated Self Administered 24 hour Diet Recall (National Cancer Institute, 2009).


42 Participa nts began submitting 24 hour diet recalls on the day of consent receipt, and were instructed to continue for a total of seven days prior to randomization. The seven days of pre b aseline 24 hour diet recalls were requested for the following reasons: i) to d etermine the amount of k cal being consumed, ii) to randomize in blocks by kcal consumption and lastly, iii) to ensure that participants were consuming additional high fiber foods that may have been overlooked by the fiber screener All participants wer e given a three month calendar, with i nstructions regarding what was required of the participants each day unt il the last day of the study. Once who was responsible f or monitoring the progress of each partici pant assigned to their section. They also kept a record of completed and uncompleted tasks. This responsibility also included reminding participants when they were required to submit seven days of 24 hour diet reca lls, daily questionnaires, food pick up appointments, and answering any questi ons presented by a participant. Randomization Similar to the informed consent phase, th e randomization process occurred over the course of seven days, consistent with the seven s ections. Each participant was scheduled for randomization exactly one week from their initial consenting appointment. Participants were randomized in one of six blocks based on gender and the average pre baseline energy intake that was reported in the 24 hour diet recalls. A Registered Dietiti an evaluated each diet, from the reported 24 hour diet recalls, and drafted diet counseling sheets with specific recommendations. From the diet counseling sheets s tudy coordinators provided dietary couns eling to each participant on how to properly incorporate the study foods into their diet, without increasing their usual calori c


43 e diet to maintain energy balance, instead of adding them on top of usual intakes Also as part of the dietary counseling, food models were used to demonstrate examples of portion sizes, a nd a variety of ingredients lists were used to educate participants on the products to avoid wh ile participating in the study The calorie ranges for males were: 1500 2000 kcal/day (low), 2001 2600 kcal/day (medium), and >2600 kcal/day (high), and for females they were: 1200 1800 kcal/day (low), 1801 2400 kcal/day (medium), and >2400 kcal/day (high). These energy stratification and randomization pattern s were generated in sealed envelopes by the study statistician, who was blinded and had no direct contact with any participants. composition by air displacement plethysmography ( BodPod, Cosmed, Inc. 1996 2012 ), and distributed the first supply of study foods to participants. The first supply of study snack bars only, to serve as an acclimation period. Following the first week of study food c onsumption, participants were instructed to return to the clinical lab in the U niversity of F lorida food science and human nutrition (FSHN) building, retrieve a two week supply of study foods, including both the yogurt and bars, and begin consume one of ea ch daily. Lastly, participants were either reminded about the calendars previously issued to them or given another calendar to further remind them of upcoming events such as when to complete the next set 24 hour diet recalls, or when to retrieve the next supply of study foods. Intervention Both study foods were provided in coded packaging that was identical in size and shape. Neither participants nor study personnel were able to distinguish between the


44 controls versus fiber supplemented foods. Nutritional information regarding both the yogurt and the snack bars was provided by General Mills The macronutrient content of the study foods was similar, with the exception of the added fiber. Neither the control yogurt nor snack bar contain ed any oligofructose However the control snack bar contained 0.5 g fiber while the yogurt contained only 0.05 g fiber The treatment yogurt contained 7.2 g of oligofructose while the treatment snack bar contained 8. 4 g oligofructose. The nutrient information for both the con trol and oligofructose snack bar and yogurt is listed in T able 3 1 and Table 3 2 respectively. Study foods were provided to the participants in two week increments for the duration of the study. Each participant arrived between the hours of 3 :00 p m and 6 :00 p m to retrieve their study foods from the FSHN building on the day ind icated in their study calendar. two study coordinators, were asked for their study ID number, were given thei r pre packaged yogurts and snack bars and was encouraged to consume one yogurt and same day in which start the seven days of 24 hour diet recalls, using the ASA 24 system. Study coordinators also Study coordinators were available at the FSHN building, or via email and telephone, throughout the study to accommodate those participants. Daily and Weekly Measures For the duration of the study, all participants were expected to complete a 10 item on line questionnaire daily. Online daily questionnaires asked a variety of que stions (Appendix C ), including whether participants visited a doctor or consumed antibiotics,


45 and the number of bowel movements (i.e., stools) they had on a scale from 0 to >10. The quantity of study foods consumed on a scale from 0 to 2, and the number of hours of sleep they acquired the night before, on a scale of <5 to >9, was also included in the questionnaire. When answering the question about sleep they were asked not to include the time it took for them to fall asleep, or anytime they were awakened d uring the night. Finally, participants were asked to rate gastrointestinal side effects experienced in the last 24 hours from consuming the study food on a scale from 0 to 6 (0=none, 3=moderate, 6=very severe) for bloating, flatulence, abdominal cramping, and stomach noises. When rating symptom intensity experience, females were asked to not rate menstrual cramping and bloating. Daily questionnaires were automatically emailed to the email address on file, by 6 :00 p m. At times when the daily q uestionnaires were not received by a participant, they were able to contact their re sent manually. Lastly, participants who were unable to consume both study foods on a particular day were asked to consume the left over foods on the following day, and were asked to report that consumption on the daily questionnaire. Participants were discouraged from consuming more than two worth o f study foods on any given day. P articipants were required to complete seven con secutive days of online 24 hr diet recalls using the ASA 24 system at baseline weeks 4, 6, and 8, for a total of 28 days of the study t o assess energy intake To log into the online questionnaire system, participants used their assigned study numbers as the username and a password provided during the informed consent phase. In the event that participants forgot or misplaced their log in information, paper records were retained by study coordinators


46 and were available for r etrieval throughout the study. De spite the study group, a ll p articipant s were asked to enter the study snack bar as an G rain bar, and the study yogurt was to be entered as 6 oz, non fat, non frozen yogurt. Because the ASA 24 system did not reflect the added oligofructose from the study foods, mean total fiber intake was manually determined prior to statistical analysis. An excel spreadsheet containing every 24 hour diet recall from each participant was created from the ASA 24 output. The fiber content of for each diet rec all was then adjusted based on the treatment group in which each participant was enrolled and the week of data collection (baseline versus weeks 4, 6, and 8). The amount of fiber actually contained in the model study foods was subtracted from the total fib er provided by the ASA 24 output for each participant and all recalls, and was replaced with the actual amount of fiber found in both the control and oligofructose study foods (th G rain bar actually contained 3 g fiber, and the 6 oz, non fat, non frozen yogurt contained no fiber). For example, after the 3 g fiber found in th ri G rain bar was subtracted from the total fiber, 8.4g (oligofructose snack bar) and 7.2 g (oligofructose yogurt) was then added to the fiber content fo r oligofructose participants. The same procedure was used to adjust for the amount of fiber actually consumed by control group participants. However, only 0.5 g fiber (control snack bar) and 0.05 g fiber (control yogurt) were added back to the total fiber content for participants in the control group. Participant questionnaires were incomplete, either by ph one or email. Twenty four hour diet recalls were no longer available to p articipants once missed or if completed.


47 Final Study Week During the last week of the study intervention, the final seven diet r ecalls were obtained. On the last day of the study, bod y compositions and waist circumferences were obtained as described for baseline collections. Both the eating inventory and the global physical activity questionnaire were also reas sessed and the participants completed a final questionnaire The final quest ionnaire asked about any sicknesses, antibiotic use, pregnancies, and/or symptoms experienced during the study (Appendix C ) It also as ked them to explain the group they believed they were in and why. Any uneaten study foods were also obtained at that time Lastly, participants were offered a generic version of their body composition results in sealed envelopes containing their initial and final body fat percent and kcal intakes. Compensation was also provided for participating in the study. Incentives In addition to eight weeks of study foods, participants also received two complementary body composition assessments, and monetary compensation for completion of the study The participants who were employees of the University of Florida received their $300.0 0 compensation via direct deposit and those who were not employees of the University of Florida received it in the form of a check on the final day of the study, unles s other arrangements were made. Statistical Analyses Differences in mean energy in take mean number diet recalls obtained from participants, and mean macronutrient intake between the control and oligofructose groups were analyzed using a two way, repeated measures analysis of variance model ( ANOVA ) with the following main effects: treatment group, week of da ta collection, and


48 a treatment x week interaction. Pairwise comparisons of differences in the mean number of diet reca lls obtained from participants, and the mean macronutrient intake were completed using the Holm Sidak method Both treatment and week of d ata collection factors were compared to the control group. As previously mentioned, all participants were asked to enter the study snack bar as an utri G rain bar, and the study yogurt as 6 oz, non fat, non frozen yogurt, despite study group. Upon adjustment of fiber content for each participant over the duration of the study, averages of each week of data collection were then calculated, including baseline. Once an average was obtained for each participant, the data was then analyzed also usin g a two way, repeated measures ANOVA model, with the following main effects: treatment group, week of data collection, and a treatment x week interaction. Pairwise comparisons of differences in the mean total fiber consumption, was also completed using the Holm Sidak method. Both treatment and week of data collection factors were compared to the control group. Body weight data is expressed as mean final body weight as a percentage of baseline body weight. The Mann Whitney Rank Sum T test was used to analyze differences between the two study groups regarding any changes in body weight. Data were analyzed on the basis of intent to treat (ITT) ( Table 4 1 ) and compliance ( Data not shown) The ITT analysis included all participants that were randomized and enrol led in the study (n=98). Compliance was defined as 1) the reported consum ption of 1.5 or more servings of study foods per day on average throughout the 8 week intervention period, equivalent to 12 g of fiber per day 2) no reported used of antibiotics thro ughout the intervention period, and 3) the complet ion of


49 at least three 24 hour diet recalls during each of the 4 period s If participants failed to complete 3 or more diet recalls in a given treatment period, their data was not included in the c ompliant s tatistical analysis. Similarly, i f participants expressed the use of antibiotics during the study, the respective data was included in the analyses until the reported starting point. All data were analyzed using SigmaPlot 12 Exact Graphs and Data Analysi s Program (Systat Software Inc., San Jose, CA). Significance was set at a p value <0.05. Data are presented as mean SEM, unless specified otherwise.


50 Figure 3 1. Study design


51 Table 3 1 Energy and nutrient content of snack bars provided to participant s d uring study Description Prototype Bar Weight Target Energy Carbohydrates Protein Total Fat Fiber (g) Control 38 g 2 g 143 kcal 31.8 g 1.5 g 1.0 g 0.5 g (0 g OF ) Oligofructose 40 g 2 g 148 kcal 32.6 g 1.5 g 1.4 g 8. 8 g (8.4 g OF ) T able 3 2. Energy and nutrient content of yogurt study food provided to participants during study Serving size Oligofructose 6 oz Control 6 oz Energy 110 kcal 107 kcal Fat 0.2 g 0.2 g Carbohydrates 24.2 g 19.5 g Sugar 12.1 g 14.9 g Fi ber 7.2 g (OF ) 0.0 5 g Protein 6.7 g 6. 8 g


52 CHAPTER 4 RESULTS Participant D emographics and Characteristics Four hundred and sixty eight candidates were screened for this study. From that population, 207 were consented and completed various eligibili ty assessments for further inclusion into the study ( Figure 4 1 ). One hundred and nine of these potential p articipants were excluded. The reasons for excluding participants (n=73) prior to randomization included: use of antibiotics, BMI outside the allowab le range ( 23.0 to <30 kg/m 2 ) a high degree of dietary restraint as determined by the Eating Inventory ( ), reported food allergies, fiber intake > 20 grams per day, as estimated by the Fruit/Vegetable/Fiber Screener, and > 300 minutes of physical activity per week reported in the GPAQ. During the pre baseline period, participants were instructed to compl ete seven consecutive days of 24 hour diet recalls. An additional 31 participants were excluded post consent due to reported fiber and energy intakes above or below the allowable limits. One participant was withdrawn by the Principal Investigator due to in complete diet recalls reported during the pre baseline week and 4 participants declined further participation for reasons including workload, diet, and lack of interest. Of the 98 participants, the control group consisted of 48 p articipants and the fiber supplemented group consisted of 50 However, o ne p articipant withdrew from the oligofructose group post randomization due to gastrointestinal discomfort, which left a total of 97 enrolled participants at study completion. The randomization schemes produce d an even distribution of the two groups, as there were no differences between subject characteristics at baseline and study completion, r egarding gende r, age, ethnicity, race, weight in kg height in cm, BMI, waist circumference in cm, percent body


53 fat, m inutes of physical activity as estimated by the Global Physical Activity Questionnaire, and dietary restraint as determined by the Eating Inventory ( Table 4 1 ). As previously mentioned, ITT data were analyzed from the 98 participants randomized and enrolle d in the trial P articipants were encouraged to retrieve their study foods according to their assigned day H owever, there were times throughout the study when arrang ements were made for earlier, later, or completely different retrieval days and times. Add itionally, although participants were encouraged to consume one yogurt and one bar daily, four participants requested approval to consume either two bars or two yogurts only. A ccommodations for those participants were also made accordingly. Diet Recalls Ob tained The mean number of diet recalls completed at baseline was significantly different from the mean number of diet recalls completed during each week of data collection for both the control and oligofructose group (P < 0.001 ) (Table 4 2 ) The average nu mber of diet recalls completed and submitted by participants did not vary amongst the two groups, except for one time point At the completion of the study (week 8) the average number of diet recalls completed was significantly different between the two gr oups, where the oligofructose group completed less diet recalls ( 4.7 0.2 ) than the control group ( 5.5 0.2 ). Fiber Intake Mean total fiber intakes were not significantly different between the control and oligofructose group at baseline ( Figure 4 2 ). How ever, when comparing mean total fiber intake between the two groups during the intervention period (weeks 4, 6, and 8) the oligofructose group consumed considerably more fiber over time than the control group,


54 as expected ( P < 0.001 ) While the oligofruct ose group increased their total fiber intake over the duration of the study, the total fiber intake of the control group were consistently lower from baseline to study completion. Additionally, the total fiber intake of the oligofructose participants in we eks 4 an d 6 were significantly higher from total fiber consumption at week 8 (P< 0.05). Energy Intake Mean energy intakes were not significantly different between the control and oligofructose group at baseline (Figure 4 3). W hen comparing mean energy inta ke between the two groups during the intervention period (weeks 4, 6, and 8) t here was also no change in energy intake observed in either group. Regarding macronutrient intake, significance was found for the study week main effect when evaluating carbohyd rate intake ( Table 4 3). More specifically, when mean baseline carbohydrate intake was compared to that of weeks 4, 6, and 8 of data collection, week 4 ( P = 0.002) and week 6 (P < 0.001) were found to be significantly higher from baseline. There were no ot her significant differences observed in mean macronutrient intake otherwise, including mean fat and protein intake. Body W eight Changes Final body weight is expressed as a percent of baseline body weight for both study groups (Figure 4 4). T here was no sig nificant difference observed in the final body weight s of individual participants in either the control or the oligofructose group (Data not shown). W hen comparing the final body weight data between the control and oligofructose group there are also no dif ferences, as expected.


55 Figure 4 1. Participant flow from screening to randomization


56 Table 4 1 C haracteristics of ITT participants a t baseline and study completion Control (n=48) Oligofructose (n=50) Gender (M/F) 17/31 20/30 Age in years 24.5 1.1 23.9 0.8 Ethnicity (n [%]) 1 Hispanic Non Hispanic 7 (14.5%) 41 (85.4%) 8 (16%) 41 (82%) Race (n[%]) White Black Asian Other 2 No Response 31 (65%) 6 (12.5%) 7 (14.5%) 3 (6.25%) 1 (2.1%) 32 (64%) 11 (22%) 5 (10%) 1 (2%) 1 (2%) BMI (kg/m 2 ) Initial Final 25.4 0.3 25.6 0.3 25.7 0.3 25.7 0.4 Height ( cm ) 167.5 1.4 169.2 1.2 Body Fat (%) Initial Final 29.2 1.2 29.1 1.4 28.4 1.3 27.5 1.4 Physical Activity Initial (min/week) 139.6 14.0 125.9 12.0 Physical Activity Final (min/week) 104.6 14.7 145.9 21.2 Weight (kg) Initial Final 71.5 1.5 72.2 1.6 73.9 1.4 74.2 1.5 Dietary Restraint Initial Final 6.8 0.5 6.2 0.6 7.1 0.5 7.5 0.7 Waist Circumference (cm) Initial Final 87.0 1.0 87.2 1.1 87.6 0.9 88.1 1.0 1 One participant in the o ligofructose group did not indicate their ethnicity 2 P articipants indicating mixed race were classified as All percent age s of ethnicity and race categories do not add to 100%, due to rounding. All data is presented as mean SEM unless otherwi se indicated


57 Table 4 2. The average number of 24 hour diet recalls obtained from ITT participants per week, at baseline and during each week of data collection Control (n=48) Oligofructose (n=50) P value a Baseline 6.6 0.2 6.3 0.2 Tx: NS Wk : < 0.0 01 b I: NS Week 4 5.8 0.2 5.7 0.2 Week 6 5.4 0.2 5.2 0.2 Week 8 5.5 0.2 4.7 0.2 a Data are statistically significant at P value < 0.05. b T he mean number of diet recalls completed at baseline was significantly different from the mean number of diet recalls completed during each week of data collection for both the control and oligofructose group (P < 0.001). Data are expressed as meanSEM. Abbreviations: Tx, treatment group; Wk week ; I, interaction ; NS, not significant


58 Figure 4 2 Mean total fiber intake of ITT participants at baseline and during each week of data collection Data are statistically significant at P value < 0.05. is indicative of significant differences in the total fiber intake between the respective weeks and baselin e (P < 0.05). is indicative of significant differences in the total fiber intake between the control and oligofructose group during the same week (P < 0.001). is indicative of significant differences in the total fiber intake of the oligofructose group at weeks 4 and 6 compared to week 8 (P < 0.05) Data are expressed as meanSEM.


59 Figure 4 3 Mean energy intake of ITT participants at baseline and during each week of data collection Data are statistically significant at P value < 0.05, and are express ed as meanSEM.


60 Table 4 3 Mean macronutrient intake at baseline and during each week of data collection Control (n=48) Oligofructose (n=50) P value a Carbohydrate (g) Baseline Week 4 Week 6 Week 8 210.4 5.5 23 8.3 6. 0 23 9.9 6.2 221. 2 6.3 22 7 .2 5.5 23 6.5 5.8 243 .2 6.0 23 7. 9 6 4 Tx: NS Wk : <0.001 b I: NS Protein (g) Baseline Week 4 Week 6 Week 8 79. 1 2. 4 8 6.5 2.6 84.3 2.7 83.0 2.8 7 8.4 2.4 76. 9 2.5 83.6 2. 6 78.8 2.8 Tx: NS Wk : NS I: NS Fat (g) Baseline W eek 4 Week 6 Week 8 74.7 2. 5 72. 9 2.7 72.3 2.8 69.2 2.9 74. 5 2.5 6 9.2 2. 6 72.8 2. 7 68. 1 2. 9 Tx: NS Wk : NS I: NS A two way, repeated measure s (RM) ANOVA model was used with the following main effects: t reatment group, week and a trea tment* week interaction. a Data are statistically significant at P value < 0.05. b The RM ANOVA found significance for the week main effect when evaluating the carbohydrate intake. Therefore, the Holm Sidak test was used to compare baseline carbohydrate inta ke to that of each week of data collection Week 4 ( P = 0.002) and week 6 (P < 0.001) were significantly different from baseline. Data are expressed as meanSEM. Abbreviations: Tx, treatment group; Wk week ; I, interaction.


61 Figure 4 4 Final b ody w eight expressed as a percent of baseline body weight. Data were obtained by calculating the mean percent age of baseline weight at the end of the study The Mann Whitney Rank Sum Test was used to evaluate difference between the two groups. Six participants enrolled in the control group, and four participants enrolled in the oligofructose group did not have final body weight measurements.


62 CHAPTER 5 DISCUSSION AND CONCL USION Fiber Intake This study provides additional information concerning the effect of pr oviding yogurt and snack bars with added oligofructose on fiber intake in high normal weight to overweight adults. Previous work suggests that U.S. adults are not consuming the recommended amount of fiber per day (29) In fact, U.S. adults are currently consuming approximately half of the recommendation, 15 g per day (29) In this study, healthy adults were randomized to receive yogurt and snack bars with or without approximately 16 g of oligofructose. Twenty four hour diet recalls were obtained from all participants at baseline and durin g the treatment period (weeks 4, 6, and 8), in order to assess energy intake and t otal f iber consumption Consum ption of yogurt and snack bars with app roximately 16 g oligofructose resulted in an average total fiber intake of 24.3 g which is close to the recommende d intake of 25 g for females. Participant adherence was calculated to be 81%. Aside from the completion of 28 total diet recalls, participants were required to complete a 10 question daily questionnaire over the course of th e study, which recorded the number of study foods consumed. Participants of both the control and oligofructose group completed significantly less mean diet recalls at week s 4, 6, and 8 compared to baseline (Table 4 2) A lthough the mean number of diet reca ll s decreased as the study progressed, the reported energy intake remained fairly consistent. Although there was a significant difference between the average number of diet r ecalls complete d between the two study groups over the duration of the trial compa red to baseline, the difference is unlikely to have an effect on our findings


63 In terms of fiber consumption, participants in the control group decreased their mean total fiber intake from baseline, over the treatment period compared to those in the oligo fructose group (Figure 4 2) This outcome in the control group participants is not entirely unexpected, given that prior to study enrollment all participants were encouraged to exchange the study yogurt and snack bars for similar snacks normally consumed Part icipants ma y have replaced a fiber containing food with the control study foods devoid of fiber. T here was no difference in mean total fiber consumption between the two study groups at baseline. However, mean total fiber intake was increased significantly in the p articipants of the oligofructose group, during the treatment period (weeks 4, 6, and 8) compared to baseline, as well as compared to controls. Unlike the decrease in mean total fiber intake that occurred over time in control participants, this was an entirely expected outcome. Not only did the mean total fiber intake increase during the trea tment period versus baseline in those consuming the oligofructose snack foods, but the rise was significantly different than that of control group individuals at respective time points. In addition, mean total fiber intake at week 4 and 6 was significantly higher from week 8 in oligofructose participants (P < 0.05) These results are also indicative of adherence to study protocol. Furthermore, because the participants in the oligofructose group easily doubled their fiber from the oligofructose study foods it is safe to conclude that U.S. adults could possibly meet the current recommendations for daily fiber consumption from commonly co nsumed foods (yogurt and snack bars) in addition consuming foods with dietary fiber With this in mind, a future study coul d also


64 encompass a follow fiber consumption was increased to meet the recommendations. Energy Intake In rodents, b oth energy intake and satiety have been shown to be positively influenced o ver time by oligofructose consumption (77) Other studies in rodents ha ve also shown that the consumption of oligofructose promoted weight loss, stimulated hormone secretion, reduced energy intake, and improved lipi d profiles collectively at varying amounts (25) In a study conducted by Cani et al. (2004), gastrointestinal peptides involved in appetite regulation were modulated by oligofructose consumption aft er three weeks of supplementation (41) Rats were fed 100 g/kg oligofructose throughout the study and their energy intakes were significantly lower than control rats, which led to significant decreases in epididymal fat mass. The energy intake results of this clinical trial do not confirm the findings of animal studies, because energy intake was not decrease d in our participants it was maintained, instead. T here was no change in energy intake observed in either stu dy group when all seven consecutive days of 24 hour diet recalls were analyzed across the four data collection weeks (Figure 4 3) All participants, despite their study group, maintained energy intake by incorporating the study foods into their usual diets as counseled Additionally, energy intake between data collection weeks did vary compared to baseline, however the changes we re not significantly different. For example, p articipants in the oligofructose group reported decrease d energy intake at week 4 c ompared to baseline. To our knowledge this is the large st randomized controlled trial, to examine the effects of oligofructose consum ption Previously, Parnell and Reimer (2009) examined


65 21 g oligofructose supplementation in 48 men and women, and saw wei ght gain (0.45 0.31) in the control group. The oligofructose group, however, experienced significant reduction in body weight (1.03 0.43), which was believed to be instigated by suppressed ghrelin and enhanced PYY (25) More recently, in the Netherlands, Verhoef et al. (2011) examined a similar effect of oligofructose in 31 healthy men and women. These participants were fed 10 g oligofructose, 16 g oligofructose, or placebo for 13 days. The author s concluded that a higher dose of oligofructose may be an effective in reduc ing energy intake, since energy intake was decreased by 11% with the 16 g d ose compared to the 10 g dose. Cani et al. (2006) assessed the effect of 16 g/day oligofructose or placeb o on energy intake, hunger, and satiety over a 2 week period in 10 participants, and found total energy intake in the oligofructose group to be 5% lower than the placebo group (84) In view of this, a future study cou ld aim to decrease energy intake and encompass appetite and satiety hormone measurement on a molecular level in normal weight, overweight, and obese individuals. Furthermore, the difference in mean energy intake between males and females of both study grou ps, if any, could be compared, as well as determining whether there are differences in caloric consumption on specific days of the week, such as weekends versus weekdays. Body Weight There were no changes in body weight observed in the participants of eit her study group. Because energy intake was maintained over the course of the study, we would not expect for there to be a change in body weight. Energy intake would have needed to be reduced significantly, as well as an increase in energy expenditure, in o rder for there to be significant changes in weight.


66 B ecause this study took place during football season at the University of Florida, it is possible that distinctive eating behaviors existed amongst participants of the two groups According to Woods et al., (2000), eating occurs most when environmental conditions are optimal, instead of in response to hunger cues (85) In a study that sought to determine whether macronutrient consumption for the U.S. population is greater on weekend days compared to weekdays, Haines et al. (2003) observed greater increases in dietary intake for adults between 19 and 50 years old on the weekends than weekdays (86) This population of participants consumed high proportions of energy from fat and alcohol (86) With this in mind, alco hol intake throughout the study may have compensated for any changes in caloric consumption experienced thus maintenance of body weight throughout the study. Further research is needed to determ ine why a decrease in energy intake and body weight was not observed in this clinical trial. Limitations and Future Directions T he participants in this study were not representative of the U nited S tates population as they were mostly young adults high n ormal weight to overweight, non restrictive eating individuals. Future studies regarding the effect of oligofructose supplementation on energy intake and weight loss should consider assessing this relationship amongst p articipants who have different demogr aphic characteristics For example, c onsidering the fact that childhood obesity rates have risen exponentially since the 1970s, future studies should also assess the effect oligofructose on this population, and could be included in the strategy for preven tion. T he elderly were also not well represented in this study. Although this population may not be direct targets for obesity treatment, they may benefit in other ways fr om fiber


67 consumption, such as gastrointestinal health and absorption of micronutrient s Holloway et al. (2007) treated 15 post menopausal women with Synergy1 (a long chain inulin) for 6 weeks, which resulted in the significant increase in calcium absorption (87) A similar effect occurred when post menopausal women were treated with 20 g/d transgalacto oligosaccharides for 9 days (88) In a recent study conducted in iron deficient rats, inulin and oligofructose increased the intest inal absorption of iron (89) The impact of daily consumption of 15 g ch icory root inulin was documented in a more recent randomized, double blind, controlled trial. Marteau et al. (2011) showed significant improvements in constipation and quality of life (QOL) with inulin supplementation in 25 elderly individuals (90) Inulin supplementation also led to expected significant increases in total fecal bacteria and bifidobacteria concent rations after 28 days of consumption. Knowing this, the elderly are another likely targeted group that could benefit positi vely from oligofructose intake for the improvement of mineral absorption to play an important role in osteoporosis prevention, and g astrointestinal health. There were four major race categories identified in this study however that category was also not very representative of the United States population. Race and ethnicity consideration is pertinen t to any treatment plan, as individ uals of distinct backgrounds may respond differently to interventions Flegal et al (2010) showed that obesity rates are elevated primarily in Non Hispanic Blacks than Mexican Americans, Non Hispanic Whites, and Hispanics (7) The increase, identified by BMI, was also higher in Non Hispanic Blacks than all of the previously mentioned demographics. In the future it is import ant to recruit so that the demographics are well balanced between the


68 groups, especially the African American category. In doing so we could possibly see that race has an effect on the treatment At the time of randomization, participants were counseled t o substitute the study foods into their diet without increasing usual en ergy intake. A ll participants adhered to such counseling instructions by maintaining caloric consumption. Because weight loss was not our primary aim, participants were not counseled i n a way that would lead to weight reduction behaviors. However, in order to contribute to the theory drawn from previous energy intake studies, a future study should anticipate weight loss following reduced energy intake, and could possibly be implemented in long term obesity prevention and treatment programs In conclusion, f uture studies should plan to control the diet of both study groups so that investigators are well aware of energy and external fiber sources. Secondly, providing a higher dosage of th e oligofructose perhaps may ensure that participants will meet the current fiber recommendations. Lastly participants should be counseled for weight loss specifically, as these factors may be widely pertinent to weight reduction strategies since we are a ware that energy intake and body weight were maintained from maintenance counseling.














































91 Eating Inventory (previously known as the TFEQ). Note: this is the scoring key for this questionnaire. Clean (i.e., unchecked) copies will be purchased from the copyright holder. The actual questionnaire does not list t he category of each question (i.e., dietary disinhibition, dietary hunger, etc.)














98 ASA24 Diet Recalls Dietary intake will be assessed using the ASA24. The ASA24 is a web based 24 hour dietary recall hosted by the National Cancer Institute. The investigators will provide Participant study numbers (i.e., not names or other identifying information) to the ASA24 developers. The developers will then assign a password for each study number. Participants will access the ASA24 using their study number and password. The investigators can monitor Participant progress and download nutrient intake estimates. Questions on the ASA24 include when did you eat, what did you eat, and how much did you eat.



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100 LIST OF REFERENCES 1. Anderson PM, Butcher KE. Childhood obesity: trends and potential causes. Future Child. 2006;16:19 45. 2. Obesity and Overweight fact sheet, 2010. World Health Organization; 2010. 3. Daniels SR, Arnett DK, Eckel RH, Gidding SS, Hayman LL, Kumanyika S, Robin son TN, Scott BJ, St Jeor S, Williams CL. Overweight in children and adolescents: pathophysiology, consequences, prevention, and treatment. Circulation. 2005 ;111:1999 2012. 4. Wright SM, Aronne LJ. Causes of obesity. Abdom Imaging. 2012 5. Dehghan M, Akhtar Danesh N, Merchant AT. Childhood obesity, prevalence and prevention. Nutr J. 2005;4:24. 6. Conterno L, Fava F, Viola R, Tuohy KM. Obesity and the gut microbiota: does up regulating colonic fermentation protect against obesity and metabolic disea se? Genes Nutr. 2011 ;6:241 60. 7. Flegal KM, Carroll MD, Ogden CL, Curtin LR. Prevalence and trends in obesity among US adults, 1999 2008. JAMA. 2010 ;303:235 41. 8. Ogden CL, Carroll MD, Curtin LR, Lamb MM, Flegal KM. Prevalence of high body mass i ndex in US children and adolescents, 2007 2008. JAMA. 2010 ;303:242 9. 9. Ogden CL, Carroll MD, Kit BK, Flegal KM. Prevalence of obesity and trends in body mass index among US children and adolescents, 1999 2010. JAMA. 2012 ;307:483 90. 10. James PT, Leach R, Kalamara E, Shayeghi M. The worldwide obesity epidemic. Obes Res. 2001 ;9 Suppl 4:228S 33S. 11. Billington C, Epstein L, Goodwin N. Overweight, obesity, and health risk. arch intern med. 2000;160:898 904. 12. Malnick SD, Knobler H. The medical complications of obesity. QJM. 2006 ;99:565 79. 13. Knowler WC, Barrett Connor E, Fowler SE, Hamman RF, Lachin JM, Walker EA, Nathan DM, Group DPPR. Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin. N Engl J Med. 2 002 ;346:393 403. 14. Koplan JP, Liverman CT, Kraak VI, Youth CoPoOiCa. Preventing childhood obesity: health in the balance: executive summary. J Am Diet Assoc. 2005 ;105:131 8. 15. Sacks FM, Bray GA, Carey VJ, Smith SR, Ryan DH, Anton SD, McManus K, Champagne CM, Bishop LM, et al. Comparison of weight loss diets with different compositions of fat, protein, and carbohydrates. N Engl J Med. 2009 ;360:859 73. 16. Shai I, Schwarzfuchs D, Henkin Y, Shahar DR, Witkow S, Greenberg I, Golan R, Fraser D, B olotin A, et al. Weight loss with a low carbohydrate, Mediterranean, or low fat diet. N Engl J Med. 2008 ;359:229 41. 17. Wing RR, Phelan S. Long term weight loss maintenance. Am J Clin Nutr. 2005 ;82:222S 5S. 18. Astrup A, Grunwald GK, Melanson EL, Saris WH, Hill JO. The role of low fat diets in body weight control: a meta analysis of ad libitum dietary intervention studies. Int J Obes Relat Metab Disord. 2000 ;24:1545 52. 19. Rolls BJ, Roe LS, Meengs JS. Salad and satiety: energy density and port ion size of a first course salad affect energy intake at lunch. J Am Diet Assoc. 2004 ;104:1570 6.

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101 20. Kreider RB, Serra M, Beavers KM, Moreillon J, Kresta JY, Byrd M, Oliver JM, Gutierrez J, Hudson G, et al. A structured diet and exercise program promo tes favorable changes in weight loss, body composition, and weight maintenance. J Am Diet Assoc. 2011 ;111:828 43. 21. Slavin JL. Dietary fiber and body weight. Nutrition. 2005 ;21:411 8. 22. Burton Freeman B. Dietary fiber and energy regulation. J N utr. 2000 ;130:272S 5S. 23. Liu S, Willett WC, Manson JE, Hu FB, Rosner B, Colditz G. Relation between changes in intakes of dietary fiber and grain products and changes in weight and development of obesity among middle aged women. Am J Clin Nutr. 2003 ;78:920 7. 24. Freeland KR, Anderson GH, Wolever TM. Acute effects of dietary fibre and glycaemic carbohydrate on appetite and food intake in healthy males. Appetite. 2009 ;52:58 64. 25. Parnell JA, Reimer RA. Weight loss during oligofructose supplem entation is associated with decreased ghrelin and increased peptide YY in overweight and obese adults. Am J Clin Nutr. 2009 ;89:1751 9. 26. Trowell H. Definition of dietary fiber and hypotheses that it is a protective factor in certain diseases. Am J Cl in Nutr. 1976 ;29:417 27. 27. Raninen K, Lappi J, Mykkanen H, Poutanen K. Dietary Fiber type reflects physiological functionality: comparison of grain fiber, inulin, and polydextrose. Nutrition Reviews. 2010;69:9 21. 28. Anderson JW, Baird P, Davis RH, Ferreri S, Knudtson M, Koraym A, Waters V, Williams CL. Health benefits of dietary fiber. Nutr Rev. 2009 ;67:188 205. 29. Slavin JL. Position of the American Dietetic Association: health implications of dietary fiber. J Am Diet Assoc. 2008 ;108:1716 31. 30. Galisteo M, Duarte J, Zarzuelo A. Effects of dietary fibers on disturbances clustered in the metabolic syndrome. J Nutr Biochem. 2008 ;19:71 84. 31. McKee LH, Latner TA. Underutilized sources of dietary fiber: a review. Plant Foods Hum Nutr. 20 00;55:285 304. 32. Buttriss JL, Stokes CS. Dietary fibre and health: an overview. British Nutrition Foundation. 2008;33:186 200. 33. Rastall RA. Functional oligosaccharides: application and manufacture. Annu Rev Food Sci Technol. 2010;1:305 39. 34. Chawla R, Patil GR. Soluble Dietary Fiber. Comprehensive Reviews In Food Science And Food Safety. 2010;9:178 96. 35. Jonnalagadda SS, Harnack L, Liu RH, McKeown N, Seal C, Liu S, Fahey GC. Putting the whole grain puzzle together: health benefits associated with w hole grains -summary of American Society for Nutrition 2010 Satellite Symposium. J Nutr. 2011 ;141:1011S 22S. 36. Viuda Martos M, Lopez Marcos MC, Fernandez Lopez J, Sendra E, Lopez Vargas JH, Perez Alvarez JA. Role of fiber in cardiovascular diseases: a review. comprehensive reviews in food science and food safety. 2010;9:240 58. 37. Cummings JH, Englyst HN. Fermentation in the human large intestine and the available substrates. Am J Clin Nutr. 1987 ;45:1243 55. 38. Cummings JH, Stephen AM. Carbohydr ate terminology and classification. Eur J Clin Nutr. 2007 ;61 Suppl 1:S5 18.

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102 39. Macfarlane S, Macfarlane GT, Cummings JH. Review article: prebiotics in the gastrointestinal tract. Aliment Pharmacol Ther. 2006 ;24:701 14. 40. Kelly G. Inulin type pre biotics -a review: part 1. Altern Med Rev. 2008 ;13:315 29. 41. Cani PD, Dewever C, Delzenne NM. Inulin type fructans modulate gastrointestinal peptides involved in appetite regulation (glucagon like peptide 1 and ghrelin) in rats. Br J Nutr. 2004 ;9 2:521 6. 42. Pereira MA, Pins JJ. Dietary fiber and cardiovascular disease: experimental and epidemiologic advances. Curr Atheroscler Rep. 2000 ;2:494 502. 43. Story JA, Kritchevsky D. Denis Parsons Burkitt (1911 1993). J Nutr. 1994 ;124:1551 4. 44. Amos AF, McCarty DJ, Zimmet P. The rising global burden of diabetes and its complications: estimates and projections to the year 2010. Diabet Med. 1997;14 Suppl 5:S1 85. 45. McKeown NM, Meigs JB, Liu S, Wilson PW, Jacques PF. Whole grain intake is favorabl y associated with metabolic risk factors for type 2 diabetes and cardiovascular disease in the Framingham Offspring Study. Am J Clin Nutr. 2002 ;76:390 8. 46. Kaline K, Bornstein SR, Bergmann A, Hauner H, Schwarz PE. The importance and effect of dietary fiber in diabetes prevention with particular consideration of whole grain products. Horm Metab Res. 2007 ;39:687 93. 47. Juntunen KS, Niskanen LK, Liukkonen KH, Poutanen KS, Holst JJ, Mykknen HM. Postprandial glucose, insulin, and incretin responses t o grain products in healthy subjects. Am J Clin Nutr. 2002 ;75:254 62. 48. Fung TT, Hu FB, Pereira MA, Liu S, Stampfer MJ, Colditz GA, Willett WC. Whole grain intake and the risk of type 2 diabetes: a prospective study in men. Am J Clin Nutr. 2002 ;7 6:535 40. 49. Erkkil AT, Lichtenstein AH. Fiber and cardiovascular disease risk: how strong is the evidence? J Cardiovasc Nurs. 2006 2006 ;21:3 8. 50. Pereira MA, O'Reilly E, Augustsson K, Fraser GE, Goldbourt U, Heitmann BL, Hallmans G, Knekt P, L iu S, et al. Dietary fiber and risk of coronary heart disease: a pooled analysis of cohort studies. Arch Intern Med. 2004 ;164:370 6. 51. Wolk A, Manson JE, Stampfer MJ, Colditz GA, Hu FB, Speizer FE, Hennekens CH, Willett WC. Long term intake of dietar y fiber and decreased risk of coronary heart disease among women. JAMA. 1999 ;281:1998 2004. 52. King DE. Dietary fiber, inflammation, and cardiovascular disease. Mol Nutr Food Res. 2005 ;49:594 600. 53. Knoops KT, de Groot LC, Kromhout D, Perrin AE, Moreiras Varela O, Menotti A, van Staveren WA. Mediterranean diet, lifestyle factors, and 10 year mortality in elderly European men and women: the HALE project. JAMA. 2004 ;292:1433 9. 54. Sol R, Gods G, Ribalta J, Vallv JC, Girona J, Anguera A, Ost os M, Recalde D, Salazar J, et al. Effects of soluble fiber (Plantago ovata husk) on plasma lipids, lipoproteins, and apolipoproteins in men with ischemic heart disease. Am J Clin Nutr. 2007 ;85:1157 63. 55. Burkitt DP. Dietary fiber and cancer. J Nutr. 1988 ;118:531 3. 56. Willett WC. Epidemiologic studies of diet and cancer. Med Oncol Tumor Pharmacother. 1990;7:93 7.

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103 57. Willett WC, Stampfer MJ, Colditz GA, Rosner BA, Speizer FE. Relation of meat, fat, and fiber intake to the risk of colon cancer in a prospective study among women. N Engl J Med. 1990 ;323:1664 72. 58. Fuchs CS, Giovannucci EL, Colditz GA, Hunter DJ, Stampfer MJ, Rosner B, Speizer FE, Willett WC. Dietary fiber and the risk of colorectal cancer and adenoma in women. N Engl J Med. 19 99 ;340:169 76. 59. Cassidy A, Bingham SA, Cummings JH. Starch intake and colorectal cancer risk: an international comparison. Br J Cancer. 1994 ;69:937 42. 60. Le Marchand L, Hankin JH, Wilkens LR, Kolonel LN, Englyst HN, Lyu LC. Dietary fiber and c olorectal cancer risk. Epidemiology. 1997 ;8:658 65. 61. Larsson SC, Giovannucci E, Bergkvist L, Wolk A. Whole grain consumption and risk of colorectal cancer: a population based cohort of 60,000 women. Br J Cancer. 2005 ;92:1803 7. 62. Schatzkin A, Mouw T, Park Y, Subar AF, Kipnis V, Hollenbeck A, Leitzmann MF, Thompson FE. Dietary fiber and whole grain consumption in relation to colorectal cancer in the NIH AARP Diet and Health Study. Am J Clin Nutr. 2007 ;85:1353 60. 63. Michels KB, Fuchs CS, Gi ovannucci E, Colditz GA, Hunter DJ, Stampfer MJ, Willett WC. Fiber intake and incidence of colorectal cancer among 76,947 women and 47,279 men. Cancer Epidemiol Biomarkers Prev. 2005 ;14:842 9. 64. Terry P, Terry JB, Wolk A. Fruit and vegetable consumpt ion in the prevention of cancer: an update. J Intern Med. 2001 ;250:280 90. 65. Howarth NC, Saltzman E, Roberts SB. Dietary fiber and weight regulation. Nutr Rev. 2001 ;59:129 39. 66. Gropper SS, Acosta PB. The therapeutic effect of fiber in treating obesity. J Am Coll Nutr. 1987 ;6:533 5. 67. Kimm SY, Glynn NW, Obarzanek E, Kriska AM, Daniels SR, Barton BA, Liu K. Relation between the changes in physical activity and body mass index during adolescence: a multicentre longitudinal study. Lancet. 200 5 2005 23 29;366:301 7. 68. Flint HJ, Duncan SH, Scott KP, Louis P. Interactions and competition within the microbial community of the human colon: links between diet and health. Environ Microbiol. 2007 ;9:1101 11. 69. Roberfroid MB. Inulin type fru ctans: functional food ingredients. J Nutr. 2007 ;137:2493S 502S. 70. Menne E, Guggenbuhl N, Roberfroid M. Fn type chicory inulin hydrolysate has a prebiotic effect in humans. J Nutr. 2000 ;130:1197 9. 71. Buddington RK, Williams CH, Chen SC, Witherl y SA. Dietary supplement of neosugar alters the fecal flora and decreases activities of some reductive enzymes in human subjects. Am J Clin Nutr. 1996 ;63:709 16. 72. Bouhnik Y, Raskine L, Simoneau G, Paineau D, Bornet F. The capacity of short chain fru cto oligosaccharides to stimulate faecal bifidobacteria: a dose response relationship study in healthy humans. Nutr J. 2006;5:8. 73. Kleessen B, Sykura B, Zunft HJ, Blaut M. Effects of inulin and lactose on fecal microflora, microbial activity, and bowel h abit in elderly constipated persons. Am J Clin Nutr. 1997 ;65:1397 402. 74. Delzenne NM. Oligosaccharides: state of the art. Proc Nutr Soc. 2003 ;62:177 82.

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104 75. Druce MR, Small CJ, Bloom SR. Minireview: Gut peptides regulating satiety. Endocrinology. 2004 ;145:2660 5. 76. Verhoef SP, Meyer D, Westerterp KR. Effects of oligofructose on appetite profile, glucagon like peptide 1 and peptide YY3 36 concentrations and energy intake. Br J Nutr. 2011 ;106:1757 62. 77. Cani PD, Neyrinck AM, Maton N, Del zenne NM. Oligofructose promotes satiety in rats fed a high fat diet: involvement of glucagon like Peptide 1. Obes Res. 2005 ;13:1000 7. 78. Johnson RK. Dietary intake -how do we measure what people are really eating? Obes Res. 2002 ;10 Suppl 1:63S 8 S. 79. Thompson FE, Subar AF. Dietary Assessment methodology. Nutrition in the prevention and treatment of disease. 2 ed; 2001. 80. Subar AF, Thompson FE, Kipnis V, Midthune D, Hurwitz P, McNutt S, McIntosh A, Rosenfeld S. Comparative validation of the Bl ock, Willett, and National Cancer Institute food frequency questionnaires : the Eating at America's Table Study. Am J Epidemiol. 2001 ;154:1089 99. 81. Rockett HR, Berkey CS, Colditz GA. Evaluation of dietary assessment instruments in adolescents. Curr Opin Clin Nutr Metab Care. 2003 ;6:557 62. 82. Zimmerman TP, Hull SG, McNutt S, Mittl B, Islam N, Guenther PM, Thompson FE, Potischman NA, Subar AF. Challenges in converting an interviewer administered food probe database to self administration in the N ational Cancer Institute Automated Self administered 24 Hour Recall (ASA24). J Food Compost Anal. 2009 ;22:S48 S51. 83. Blanton CA, Moshfegh AJ Baer DJ, Kretsch MJ. The USDA Automated Multiple Pass Method accurately estimates group total energy and nutrient intake. J Nutr. 2006 ;136:2594 9. 84. Cani PD, Joly E, Horsmans Y, Delzenne NM. Oligofructose promotes satiety in healthy human: a pilot study. Eur J Clin Nutr. 2006 ;60:567 72. 85. Woods SC, Schwartz MW, Baskin DG, Seeley RJ. Food intake and the regulation of body weight. Annu Rev Psychol. 2000;51:255 77. 86. Haines PS, Hama MY, Guilkey DK, Popkin BM. Weekend eating in the United States is linked with greater energy, fat, and alcohol intake. Obes Res. 2003 ;11:945 9. 87. Holloway L, Moynihan S, Abrams SA, Kent K, Hsu AR, Friedlander AL. Effects of oligofructose enriched inulin on intestinal absorption of calcium and magnesium and bone turnover markers in postmenopausal women. Br J Nutr. 2007 ;97:365 72. 88. van den Heuvel EG, Schoterman MH, Muijs T. Transgalactooligosaccharides stimulate calcium absorption in postmenopausal women. J Nutr. 2000 ;130:2938 42. 89. Freitas KD, Amanci o OM, de Morais MB. High performance inulin and oligofructose prebiotics increase the intestinal absorption of iron in rats with iron deficiency anaemia during the growth phase. Br J Nutr. 2011 :1 9. 90. Marteau P, Jacobs H, Cazaubiel M, Signoret C, Pre vel JM, Housez B. Effects of chicory inulin in constipated elderly people: a double blind controlled trial. Int J Food Sci Nutr. 2011 ;62:164 70.

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10 5 BIOGRAPHICAL SKETCH ArNelle Renee Wright was born in Winter Haven, Florida, where her family currently r esides. She received her Bachelor of Science degree in f ood s cience and h uman n utrition with an emphasis in nutritional sciences from the University of Florida in 2010. This thesis is part of the completion of her Master of Science degree, also in f ood s ci ence and h uman n utrition again with an emphasis in n utritional s ciences from the University of Florida.