SPORTS DIETITIANS’ KNOWLEDGE AND PERCEPTION OF NUTRITIONAL GENOMICS AND THE ENHANCEMENT OF ATHLETIC PERFORMANCE

A thesis submitted to the Kent State University College of Education, Health, and Human Services In partial fulfillment of the requirements For the degree of Masters of Science

By

Christopher S. Cooper

August 2015

A thesis written by

Christopher Samiá Cooper

B.S., Howard University, 2004

M.S., Kent State University, 2015

Approved by

______, Director, Master’s Thesis Committee Amy Miracle

______, Member, Master’s Thesis Committee Karen Lowry Gordon

______, Member, Master’s Thesis Committee Natalie Caine-Bish

Accepted by

______, Director, School of Health Sciences Lynne E. Rowan

______, Interim Dean, College of Education, Health and Human Mark Kretovics Services

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COOPER, CHRISTOPHER S., M.S., August 2015 Nutrition

SPORTS DIETITIANS’ KNOWLEDGE AND PERCEPTION OF NUTRITIONAL GENOMICS AND THE ENHANCEMENT OF ATHLETIC PERFORMANCE (96 pp.)

Director of Thesis: Amy Miracle, Ph.D., R.D., C.S.S.D., L.D.

The purpose of this study was to investigate sports dietitians’ knowledge of nutritional genomics and their perceptions of nutritional genomics for enhancing athletic performance. The study was an online voluntary response sampling of Registered

Dietitians (n=6219) from the membership database of the Academy of Nutrition and

Dietetics (AND). Participants completed a questionnaire composed of 3 sections designed to investigate: (1) Demographics; (2) Knowledge of genetics and diet-gene interactions; (3) Perceptions of nutritional genomics for enhancing athletic performance.

For statistical analysis, participant demographic characteristics were used to differentiate between Sports Dietitians (SRDs) and Non-Sports Dietitians (NSRDs).

Results of the study indicate that Total Knowledge Scores (TKS) among SRDs were significantly greater than NSRDs; however, there were only six knowledge questions to which >50% of the participants answered correctly. Increases in TKS correlated with increases in Perception scores, and SRDs responses to the six Perception items were significantly greater than responses from NSRDs. Overall, there was a weak to moderate positive correlation for SRDs and NSRDs between TKS and the six Perception items.

The results indicate that more knowledge of genetics and diet-gene interactions is needed for all dietitians in order for them to feel comfortable and confident in the

advancing field of nutritional genomics. Both SRDs and NSRDs agree that there is a need for continuing research in nutritional genomics.

ACKNOWLEDGMENTS

It is with immense gratitude that I acknowledge everyone that has supported and guided me throughout this long process. It has been one heck of a roller coaster ride. I enjoyed it, and look forward to what the future has in store.

First, I must give a very special thank you to my thesis adviser, Dr. Amy Miracle. I am truly thankful for your guidance, patience, encouragement, the deadlines, and especially your leniency. You knew exactly when and how to push me and when to back off. You made this process enjoyable.

I am also truly thankful for Dr. Karen Lowry Gordon and Dr. Natalie Caine-Bish for helping to guide me throughout this process. I can’t just say my committee members because the two of you are so much more. Your knowledge and insight have been invaluable from day one. I thank the two of you for believing in me and allowing me the opportunity to make this a reality.

Also, thank you to Edward Bolden (Kent State University Research and Evaluation

Bureau), Ron Dear (KSU Qualtrics account representative) and Eryn Schmidt (Qualtrics

University Support). The guidance and support offered by you all was irreplaceable and probably saved me a few gray hairs.

I am so Blessed to have the support of awesome family members, loved ones, and friends. My parents have always supported me in everything that I do. They are there to cheer me on and lift my spirit with encouragement when needed. I cannot thank you all enough for everything that you do, but THANK YOU! Thank you to my Grandmother,

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for always encouraging and believing in me. Thank you to my brother and niece, Will and Chelsea, for always bringing a smile to face. Thank you to all of my family, friends and anyone else that I cannot name in this short space. And a very special THANK YOU to my very best friend, Julie Abraham, MD: you are my sunshine.

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TABLE OF CONTENTS

Page

ACKNOWLEDGMENTS...... iii

LIST OF FIGURES...... vii

LIST OF TABLES...... viii

CHAPTER I. INTRODUCTION...... 1 Statement of the Problem...... 3 Purpose…………...... 5 Research Hypotheses...... 5 Operational Definitions...... 6

II. LITERATURE REVIEW...... 8 Human Genome Project...... 8 International HapMap Project...... 10 Genetics and Genomics Research...... 11 Nutritional Genomics...... 11 Personalized Nutrition...... 14 Genomics and Athletic Performance...... 16 Education of Health Professionals...... 18 Nutrition Education of Physicians...... 18 Genetics and Genomics Education of Dietitians...... 19 National Coalition for Health Professional Education in Genetics...... 21 Role of Sports Dietitians...... 23 Link Between Sports Dietitians’ and Non-Sports Dietitians Knowledge and Perception of Nutritional Genomics for Enhancing Athletic Performance...... 25

III. METHODS...... 26 Study Design...... 26 Participants...... 26 Instruments...... 27 Procedure...... 28 Questionnaire Scoring...... 28 Data Analysis...... 29

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IV. JOURNAL ARTICLE...... 30 Introduction...... 30 Methods...... 31 Study Design...... 31 Participants...... 32 Instruments...... 32 Procedure...... 33 Questionnaire Scoring...... 34 Data Analysis...... 34 Results...... 35 Discussion...... 51 Knowledge of Nutritional Genomics between Dietitians...... 52 Perceptions of Nutritional Genomics between Dietitians...... 53 Linking Knowledge and Perceptions...... 54 Limitations...... 54 Applications...... 56 Recommendation for Future Research...... 57 Conclusion...... 58

APPENDICES...... 59 APPENDIX A. QUESTIONNAIRE...... 60 APPENDIX B. RECRUITMENT E-MAILS...... 69 APPENDIX C. STUDY CONSENT FORM...... 72 APPENDIX D. GLOSSARY OF TERMS...... 75 APPENDIX E. FREQUENCIES OF RESPONSES TO THE KNOWLEDGE QUESTIONS...... 78

REFERENCES...... 80

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LIST OF FIGURES

Figure Page

1. Primary Practice Setting for Survey Respondents Completing the “Dietitians’ Knowledge and Perceptions of Nutritional Genomics for Enhancing Athletic Performance” Questionnaire (n = 6219)...... 36

2. Pearson Correlation Scores between Total Knowledge Score and the Six Perception Responses for Sports Dietitians and Non-Sports Dietitians Completing the “Dietitians’ Knowledge and Perceptions of Nutritional Genomics for Enhancing Athletic Performance” Questionnaire...... 41

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LIST OF TABLES

Table Page

1. Demographic Characteristics of Survey Respondents Completing the “Dietitians’ Knowledge and Perceptions of Nutritional Genomics for Enhancing Athletic Performance” Questionnaire...... 37

2. Qualifying Demographic Characteristics for Sport Dietitians Completing the “Dietitians’ Knowledge and Perceptions of Nutritional Genomics for Enhancing Athletic Performance” Questionnaire...... 38

3. Summary of Total Knowledge Scores and Perception Responses Between Sport and Non-Sport Dietitian Groups Completing the “Dietitians’ Knowledge and Perceptions of Nutritional Genomics for Enhancing Athletic Performance” Questionnaire ( = mean, SD = standard deviation)...... 40

4. Pearson Correlation Coefficient Values assessing the relationship between Total Knowledge Score and the Six Perception Responses for Sports Dietitians and Non-Sports Dietitians Completing the “Dietitians’ Knowledge and Perceptions of Nutritional Genomics for Enhancing Athletic Performance” Questionnaire...... 42

5. Results of one-way (1x5) between groups ANOVA for Education Level ( = mean, SD = standard deviation)...... 44

6. Results of one-way (1x4) between groups ANOVA for Time spent working with athletes ( = mean, SD = standard deviation)...... 46

7. Results of one-way (1x5) between groups ANOVA for Athlete Level ( = mean, SD = standard deviation)...... 49

8. Frequency Distribution of Sports Dietitians and Non-Sports Dietitians Correct, Incorrect, and Do Not Know Responses to Knowledge Questions for the “Dietitians’ Knowledge and Perceptions of Nutritional Genomics for Enhancing Athletic Performance” Questionnaire (n = 6219)...... 79

viii CHAPTER I

INTRODUCTION

One of the key factors enabling the study of diet-gene interactions is the Human

Genome Project (Stover, 2006). Knowing the sequences of the human genome opened the door to examine the relationship among an individual’s genetic makeup, dietary intake, and health outcomes (Baumler, 2012). Upon completion of the Human Genome

Project in April 2003, nutritional genomics (the science of understanding the complex interaction between genes and diet) emerged as a promising field of nutrition research.

Nutritional genomics is an amalgamation of nutrigenomics (the way in which nutrients or dietary constituents influence gene expression) and nutrigenetics (the influence of genetic variation on the response to nutrients or dietary constituents) (McCarthy, Pufulete, &

Whelan, 2008). Nutrigenomics focuses on the interaction of food and nutrients with the human organism as a species, whereas nutrigenetics addresses how changes in the genetic composition of the human organism, particularly polymorphisms, modulate this interaction (Vergères, 2013). The aim of nutritional genomics is to identify the genetic variations that account for why some individuals react differently to dietary components

(Stover, 2006). This is in relation to the genetotrophic principle, introduced by Roger J.

Williams in the 1950s, and the concept of biochemical individuality. Williams, a nutritional biochemist, pioneered the idea of individuality in nutritional needs as he found evidence that individuals unique set of genes control their metabolism and nutritional needs (Williams, 2008). According to Williams (1963), the genetotrophic principle is a 1 2 very broad one encompassing the whole of biology, and it may be stated as: every individual organism that has a distinctive genetic background has distinctive nutritional needs which must be met for optimal well-being. It can be said that biochemical individuality is the foundation and nutritional genomics is the platform onto which the idea of personalized nutrition, the concept of adapting food to individual needs, has expanded.

Athletic performance is one area that nutritional genomics and personalized nutrition has the potential to impact. It is the joint position of the Academy of Nutrition and

Dietetics (formerly known as the American Dietetic Association), Dietitians of Canada

(DOC), and the American College of Sports Medicine (ACSM) that physical activity, athletic performance and recovery from exercise are enhanced by optimal nutrition

(Rodriguez, DiMarco, & Langley, 2009). Physical fitness is a complex phenotype influenced by a myriad of environmental and genetic factors (MacArthur & North, 2005), and athletes adopt various nutritional strategies in an effort to succeed at the highest level

(Maughan & Shirreffs, 2012). Additionally, the development of technology for rapid

DNA sequencing and genotyping has allowed the identification of some of the individual genetic variations that contribute to athletic performance (MacArthur & North, 2005).

Information derived from DNA profiling of relevant genes can indicate both advantages and genetic barriers that reflect on the athletic performance phenotype (Kambouris,

Ntalouka, Ziogas, & Maffulli, 2012). It’s the competitive nature of sports that keeps most athletes looking for an edge, and when all else is equal, as it usually is in elite sport,

3 an assortment of minor factors can determine the successor (Maughan & Shirreffs, 2012).

Understanding the genetic nutritional needs of an athlete provides an additional valuable tool in strategies to optimize sports performance (Boehl, 2007; Debusk, Fogarty,

Ordovas, & Kornman, 2005; Stover & Caudill, 2008).

Statement of the Problem

Nutritional genomics is an emerging field of genetics and nutrition research.

However, not many healthcare professionals, including Registered Dietitians (RDs) and

Registered Dietitian Nutritionists (RDNs), understand the role of nutritional genomics in the future of daily nutrition care. Past surveys and observations indicate that physicians, nurses and other health professionals are not adequately informed about the role of genetics in health care (Lapham, Kozma, Weiss, Benkendorf, & Wilson, 2000). Nor are they prepared to integrate genetics into clinical practice (Collins, 1997). As nutritional genomics expands, nutritional assessment is expected to evolve from simply measuring nutrient concentrations in blood, urine or tissue to measuring a genomic function of a nutrient within a cell (King, 2003). Additionally, nutritional genomics will provide early biomarkers for disease and dietitians will be able to use this information to make dietary counseling more accurate (King, 2003).

Increasingly, athletes and active individuals are seeking professional guidance in making optimal food and fluid choices, and the onus is on sports dietitians to apply sports nutrition science to fuel fitness and performance (Rodriguez, Di Marco, & Langley,

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2009). It’s the role of sports dietitians to provide individual and group/team nutrition counseling and education to enhance the performance of competitive and recreational athletes (American Dietetic Association, 2008 as cited in Sports, Cardiovascular, and

Wellness Nutrition, 2015). Yet, human athletic performance is a highly complex phenotype that can be considered both multi-factorial and polygenic (Kambouris et al.,

2012). It is now widely acknowledged that several genes influence athletic performance and a major integration between genetic and environmental factors might contribute towards unveiling the most important determinants of physiology and pathology in humans, allowing the construction of a rational personalized framework that would be applied in both clinical and sport settings (Lippi, 2008). As with all multi-factorial conditions, genetic makeup plays a major role in determining the complex phenotype of athletic performance, and knowledge of genetic advantages and barriers conferred by the presence of such genomic variations can be of utmost importance and benefit to athletes guidance (Brutsaert, 2006; Lippi, 2010; MacArthur, 2005). DNA sequence variations in genes controlling biological processes (such as muscle, cartilage and bone formation; blood and tissue oxygenation; etc) confer genetic advantages that can be exploited, or genetic ‘barriers’ that could be overcome to achieve optimal athletic performance

(Kambouris et al., 2012).

To build capacities in nutritional genomics, dietetics professionals will require expertise in human genetics combined with specialized knowledge in biochemistry, molecular nutrition, and food service (DeBusk, 2002). However, studies investigating

5 knowledge of genetics and nutritional genomics among dietitians show that dietitians generally have low involvement, confidence, and knowledge in genetics and diet-gene interactions (Whelan, McCarthy, & Pufulette, 2008). In theory, the application of nutritional genomics has the potential to impact athletic performance; yet, there is a lack of studies regarding sports dietitians’ knowledge of nutritional genomics or their perceptions regarding the implementation of nutritional genomics for enhancing athletic performance.

Purpose

The purpose of this study is to investigate sports dietitians’ knowledge of nutritional genomics and their perceptions regarding the potential implementation of nutritional genomics for enhancing athletic performance.

Research Hypotheses

H₁: There will be a difference between Sports Dietitians (SRDs) and Non-Sports

Dietitians (NSRDs) in knowledge of nutritional genomics and perceptions regarding potential implementation of nutritional genomics for enhancing athletic performance.

H₂: Dietitians with more knowledge of nutritional genomics will have stronger perceptions regarding potential implementation of nutritional genomics for enhancing athletic performance.

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Operational Definitions

Knowledge of nutritional genomics: Understanding of genetics and diet-gene interactions in relation to nutritional genomics; based on the number of correct answers in the

Knowledge section of the questionnaire (Appendix A).

Non-Sports Registered Dietitian (NSRD): Any Dietitian that is not a Certified Specialist in Sports Dietetics (CSSD) and does not work directly with athletes for nutrition counseling one or more hours per week.

Nutrigenetics: The influence of genetic variation on the response to nutrients or dietary constituents (McCarthy et al., 2008).

Nutrigenomics: The way in which nutrients or dietary constituents influence gene expression (McCarthy et al., 2008).

Nutritional genomics: The science of understanding the complex interaction between genes and diet; a combination of nutrigenomics and nutrigenetics.

Perception: Comfort level discussing diet-gene interactions, nutritional genomics and potential implementation of nutritional genomics into practice for enhancing athletic performance; assessed using a five-point Likert scale (ranging from 1, “Strongly

Disagree” to 5, “Strongly Agree”) and scored based on summed responses in the

Perception section of the questionnaire (Appendix A).

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Sports Registered Dietitian (SRD): Any Dietitian that is a Certified Specialist in Sports

Dietetics (CSSD) or is not a CSSD but works directly with athletes for nutrition counseling one or more hours per week.

CHAPTER II

LITERATURE REVIEW

Human Genome Project

The first serious discussion of the possibility of sequencing the human genome was convened in 1985 by Robert Sinsheimer, then chancellor of the University of California at Santa Cruz. At the time, many thought the idea was crazy or, at best, premature

(Collins, Morgan, & Patrinos, 2003). From the beginning, the project emphasized the development and pilot testing of new technologies (Collins et al., 2003). Today, recent breakthroughs in genomic association studies have paved the way for predictive, preventive, and personalized medicine (Kambouris et al., 2012). Nutritional genomics is an emerging field of genetics and nutrition research. However, not many healthcare professionals, including Registered Dietitians (RDs) and Registered Dietitian

Nutritionists (RDNs), understand the role of nutritional genomics in the future of daily nutrition care. Understanding the science of nutritional genomics is important to dietitians and other health professionals because major scientific advancements such as this usually have a significant impact on ethics, policy, and practice (Ryan-Harshman et al., 2008).

The human genome project has demonstrated that any two individuals share 99.9% of their DNA sequence (Human Genome, 2004). Yet, the 0.1% difference between any two individuals may explain why some individuals are more susceptible than others to 8 9 common diseases (Vakili & Caudill, 2007). Genetic advances have improved the ability to define molecular mechanisms underlying human health and disease, and to subdivide diseases and conditions into more distinct entities (Patterson et al., 1999). The human genome contains 3-10 million genetic variations, in forms such as single nucleotide polymorphisms (SNPs), insertion/deletion polymorphisms, and short tandem repeat polymorphisms (Ku, Loy, Salim, Pawitan, & Chia, 2010). The simplest and most prevalent forms of genetic variability in the human genome are the single nucleotide polymorphisms, changes in a single base pair that exist in more than 1% of the population

(Vakili & Caudill, 2007). Functional SNPs, those that alter gene expression, mRNA processing, and protein function are of the most interest to research scientists and health professionals (Vakili & Caudill, 2007). Scientists are studying how SNPs in the human genome correlate with disease, drug response, and other phenotypes (Collins, n. d.).

Many of the deleterious SNPs discovered are diet responsive and can be rendered harmless with the “right” diet (Vakili & Caudill, 2007).

The millions of people around the world who supported the quest to sequence the human genome did so with the expectation that it would benefit humankind (Collins et al., 2003). Upon conclusion of the Human Genome Project, those involved fully expected the new disciplines of genomics and genomics-based medicine, to carry on its tradition of pushing the envelope of biological thinking (Collins et al., 2003). Common diseases such as cardiovascular disease, cancer, obesity, diabetes, psychiatric illnesses and inflammatory diseases are caused by combinations of multiple genetic and

10 environmental factors (King, Rotter, & Motulsky, 1992). Discovering these genetic factors will provide fundamental new insights into the pathogenesis, diagnosis and treatment of human disease (International HapMap Consortium, 2003). A novel perspective on medical treatment that may be seen as pushing the envelope is the concept of personalized medicine. According to the National Academy of Sciences (NAS), personalized medicine has been defined as “the use of genomic, epigenomic, exposure and other data to define individual patterns of disease, potentially leading to better individual treatment,” (as cited in U.S. Food and Drug Administration [FDA], 2013).

Sadee and Dai (2005), describe it as providing “the right patient with the right drug at the right dose at the right time,” (as cited in FDA, 2013). To strengthen this effort, scientist and funding agencies from around the world have partnered to create the International

HapMap Project.

International HapMap Project

The International HapMap Project is a multi-country effort to identify and catalog genetic similarities and differences in human beings, and researchers will be able to use this information to find genes that affect health, disease, and individual responses to medications and environmental factors (International HapMap Consortium, 2003). It is their aim to determine the common patterns of DNA sequence variation in the human genome, by characterizing sequence variants, their frequencies, and correlations between them, in DNA samples from populations with ancestry from parts of Africa, Asia and

Europe (International HapMap Consortium, 2003). The project will thus provide tools

11 that will allow the indirect association approach to be applied readily to any functional candidate gene in the genome, to any region suggested by family-based linkage analysis, or ultimately to the whole genome for scans for disease risk factors (International

HapMap Consortium, 2003).

Genetics and Genomics Research

Nutritional Genomics

Substantial progress has been made in human genetics and genomics research since the publication of the draft sequence of the human genome (Naidoo, Pawitan, Soong,

Cooper, & Ku, 2011). Knowledge of the human genome is helping us better understand nutrition (Chavez & Munoz de Chavez, 2003), and nutritional genomics has emerged as a promising field of nutrition research. According to Ordovas and Mooser (2004), nutritional genomics has tremendous potential to change the future of dietary guidelines and personal recommendations. The nutrition–health relationship depends on the adaptive capacity of genes and their functioning with the diet consumed; thus, the greater the efficiency of the system, the lower the metabolic wear suffered (Chavez & Munoz de

Chavez, 2003). The basic principle of nutritional genomics is that less metabolic wear is suffered when the adaptive capacity and functioning of genes within a particular dietary pattern is most efficient (Chavez & Munoz de Chavez, 2003). Kaput and Rodriguez

(2004) describe the five tenets of genomic/nutritional research as:

1. Common dietary chemicals alter gene expression or structure.

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2. In some people and in some circumstances, diet can be a serious risk factor for

disease.

3. Some diet regulated genes are susceptibility genes, and are likely to play a role in

chronic diseases.

4. The influence of diet on the balance between healthy and disease states may

depend upon genetic makeup.

5. Dietary intervention based on “individualized nutrition” can be used to prevent, `

mitigate, or cure chronic disease.

Recent reviews indicate that nutritional genomic approaches can enhance understanding of molecular processes that maintain health and reduce disease risk (Rosen, Earthman,

Marquart, & Reicks, 2006). The ultimate aim of practitioners of nutrigenetics is to use the insight for making better nutrition choices at all levels of decision making, from personal nutrition to international policy (Kohlmeier, 2013). In practice, registered dietitians will be asked to translate scientific knowledge of how diet affects individuals in both clinical and public health settings (Patterson, Eaton, & Potter, 1999).

One of the key opportunities for nutritional genomics is the exploration of the link between specific gene polymorphisms and the individual response to nutrients, with a long-term goal of providing personalized dietary advice on the predicted response to nutrients derived from the genetic profile of an individual (Trayhurn, 2003).

Nutrigenetics is often associated with personalized nutrition and the debatable idea that each human genotype can be associated with a specific diet (Vergères, 2013). According

13 to Vergères, (2013), this idea that was once gaining momentum in the public is no longer

‘main stream’ among researchers due to the epigenetic effect and modifications on the human phenotype. Epigenetics adds an important layer of variability to the human genome that can best be observed along the time axis throughout the life cycle of the organism or even across generations (Weber, 2010). It clearly makes the story more complex, as the environment can modify our genome or its expression along the cellular chain of information (RNA, proteins, and metabolites) in a tissue and life-cycle dependent manner (Vergères, 2013). Yet, the age of personalized nutrition has arrived

(Williams, 2008) as nutrigenetics has been a reality in clinical practice for decades

(Kohlmeier, 2013). Nutrigenetics has been used for decades in certain rare monogenic diseases such as phenylketonuria (Ordovas & Mooser, 2004). Every year we screen millions of newborns for genetic diseases such as phenylketonuria (PKU, OMIM 261600) and biotinidase deficiency (OMIM 253260) because these conditions generally respond well to nutritional therapy (Kohlmeier, 2013). Nutritional genomics has quickly advanced our knowledge on blood lipid profiles and associated conditions such as obesity and Type 2 diabetes while dietary advice has become more specific to individuals with hyperlipoproteinemia (Ryan-Harshman et al., 2008). Additionally, the application of both genomic and nutritional genomic approaches has led to the discovery of the protein leptin and knowledge that mutations in the genes for leptin, adrenergic receptors, and insulin are associated with obesity in humans (Trayhurn, 2003). Other areas of nutritional genomic interest include the investigations of green tea or soy polyphenols

14 and their relationship to genetics, receptor function, and cancer risk (Guo and

Sonenshein, 2006); diet-gene interactions between vitamin D and immunity (Sadeghi et al., 2006); and future perspectives on personalized nutrition for the prevention of cardiovascular disease (Lovegrove and Gitau, 2008) to name a few.

Personalized Nutrition

Nutritional Genomics has the potential to provide a basis for personalized dietary recommendations based on the individual's genetic makeup in order to prevent common multi-factorial disorders decades before their clinical manifestation (Ordovas & Mooser,

2004). Multi-factorial conditions such as obesity, atherosclerosis, diabetes, and hypertension result from poor regulation of human metabolism, and are due to complex interactions between several genes and environmental conditions (German & Watzke,

2004; Kaput & Rodriguez, 2004). As a result, it is expected by 2020 that 57% of all disease worldwide will be chronic disease (World Health Organization, 2002), and because diet is closely linked to metabolism, food choices will play a key role in providing solutions to these problems (German & Watzke, 2004). Proposed solutions to such chronic conditions include modifications in macronutrient consumption and increased intakes of certain micronutrients (Darnton-Hill, Margetts, & Deckelbaum

2004). Individuals, however, vary in their response to dietary modifications. As demonstrated in the Dietary Approaches to Stop Hypertension (DASH) study, subjects with one genotype were able to lower their blood pressure through diet, while subjects with differing genotypes did not respond to diet (Svetkey, et al., 2001). Hence, the

15 argument by Simopoulos (2002) that degree of genetic variation and heterogeneity among humans is such that general dietary recommendations are not necessarily valid.

On the other hand, Ryan-Harshman et al. (2008) counters that identification of genetic polymorphisms need not change dietary guidelines and recommendations, but indicate the need for more intensive individual dietary counseling.

Although nutrition professionals have been involved in the management of patients with single-gene disorders such as inherited metabolic diseases and cystic fibrosis for some time (Burton, Sanderson, Dixon, Hallam, & White, 2007), a variety of disorders commonly managed by nutrition professionals (e.g., obesity, diabetes, and cancer) are known to involve multiple environmental and genetic interactions (DeBusk, Fogarty,

Ordovas, & Kornman, 2005). At this time, the best "genetic test" for most disorders and traits is the family history, and dietitians need to be able to gather and interpret family history to incorporate into the nutrition care process (NCHPEG, 2007). Applying nutritional genomics in clinical practice through the use of genetic testing requires that

RDNs understand, interpret, and communicate complex test results in which the actual risk of developing a disease may not be known (Camp & Trujillo, 2014). McCarthy et al.

(2008) argues that knowledge of genetics and nutritional genomics will become increasingly important in the prevention and management of disease and for the tailoring of personalized dietary advice. Apostolatos (n.d.), offers this review:

While the field is still growing, and nutritional genomics has the potential to create preventative measures against disease, current knowledge is still limited and cannot

16 guarantee significant benefits. It is important to note that lifestyle changes and nutrition are only a part of the equation. DNA is the blueprint that determines growth and development, but what we eat will not necessarily modify our code. External factors, like diet, can only improve or diminish health, but do not, as far as we know, offer a cure-all.

Consequently, the question of magnitude remains: how much of a role does food play in health? Over the next few years, further research on the role of nutrients in epigenetic mechanisms may provide a definite answer.

Genomics and Athletic Performance

According to Lippi, Solero, and Guidi (2004) and Maughan (2007), it is now widely acknowledged that several genes influence athletic performance and it is being increasingly highlighted that a major integration between genetic and environmental factors might contribute towards unveiling the most important determinants of physiology and pathology in humans, allowing the construction of a rational personalized framework that would be applied in both clinical and sport settings (as cited in Lippi,

2008). Although most of the knowledge in sports genetics have been almost exclusively applied to cohorts with small sample sizes, over 200 SNPs associated with physical performance traits and over 20 SNPs associated with elite athletic status have been reported in the literature and summarized in ‘The Human Gene Map for Performance and

Health Related Fitness Phenotypes’ (Bray et al., 2009).

Many recent studies provide details about the kinds of diet, nutrients and other compounds that are the “best for Man”, and biotechnology is becoming an instrument

17 that enables food to be offered in the best of conditions (Chavez & Munoz de Chavez,

2003). As discussed in Kambouris et al. (2012), individualized nutritional guidance can significantly enhance anti-oxidation and detoxification abilities, promoting optimal health and consequently optimal sports performance; as such, sports dietitians often regard increased iron intake and supplementation as a necessity in athletes involved in endurance sports. However genetic profiles of individual athletes may be indicative of increased risk for hemochromatosis, when specific variants in gene HFE are present

(Chicharro, 2004; Coppinn, 2003). While gene therapy is acquiring considerable importance in the prospective treatment of many genetic or acquired diseases (Sheridan,

2011), the same methods could be used by athletes aiming to enhance the endogenous production of some particular proteins artificially (Oliveira, Collares, Smith, Collares, &

Seixas, 2011). Fischetto and Bermon (2013) warn that misused gene therapies would be likely to show the same effectiveness as the actual doping methods based on the administration of exogenous recombinant molecules. Pitsiladis et al. (2013) discusses three ways that genomics of elite sporting performance might impact clinical practice:

 Genetic markers of sports injuries (e.g., tendinopathy) are being

discovered and may be used in the future in conjunction with other health

indices to provide personalized care for an athlete;

 Genetic variants influencing elite performance are also expected to impact

on cardiac, skeletal muscle, and energy metabolism;

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 Genomic data may eventually help to prevent, diagnose, and treat diseases

such as myocardial dysfunction and muscular skeletal diseases, and to

determine whether or not to tailor prevention and treatments to specific

populations.

At this point, however, the number of large genetic cohorts of world-class athletes is limited and current genetic testing has zero predictive power on talent identification; therefore, it is not recommended for athletes, coaches, or parents (Pitsiladis et al., 2013).

Education of Health Professionals

Nutrition Education of Physicians

A key factor in the implementation of nutritional genomics is knowledge and education among health care professionals. The adequacy of nutrition instruction in medical education remains an issue of concern, as more than one-half of graduating medical students rate their nutrition preparation as inadequate (Adams, Lindell,

Kohlmeier, & Zeisel, 2006). Nutrition education has either been ignored as an integral part of standard healthcare or the responsibility has been transferred to RDs (DeBusk,

Fogarty, Ordovas, & Kornman, 2005; Truswell, 1999). There is greater responsibility on the shoulders of dietitians; thus, highlighting an urgent need for training in emerging fields of nutrition such as nutritional genomics (Prasad, Imrhan, & Rew, 2011). While physicians can specialize in medical problems that have a genetic basis, there is currently no such sub-specialty in dietetics.

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Genetics and Genomics Education of Dietitians

For the potential of advances in diet-gene interactions to be realized, dietitians must become a genetics-literate profession; however, there is a gap in knowledge and skills that must be filled if the goal is to be achieved (Whelan et al., 2008). Although the evidence from nutritional genomics to support individual tailored nutritional advice is still in the infancy stages (Arab, 2004), it is necessary that those involved in interpreting and translating this evidence, including RDNs, are prepared for the possible opportunities that it may offer (Whelan et al., 2008). It will take a coordinated effort among genetics professionals, professional associations, and academic institutions to assure that primary and continuing education efforts lead to the enactment of genetic competencies and the fulfillment of the identified priority education topics by all health care professionals

(Lapham et al, 2000).

Our readiness to deliver nutritional genomic based education has been slow due to the complexity of gene-nutrient interaction and interplays between many disciplines such as genetics, nutrition, biostatistics, sociology, law, and philosophy (Prasad et al., 2011).

One of the largest surveys of health professionals’ involvement and confidence in genetics was completed in the Human Genome Education Model Project II (HuGEM) study, and it revealed a critical need for genetics education of allied and counseling health professionals (Lapham et al., 2000). Lampham et al. (2000) and McCarthy et al.

(2008) both reported similarly low levels of genetics content of university education, where approximately 40% had “no training in genetics” and almost half reported “some

20 training in genetics”. While attitudes about the benefits of the application of nutritional genomics are positive, barriers involving the lack of background knowledge and experts to convey professional expertise may limit the ability of RDNs to apply nutritional genomics in a clinical setting (Rosen, Earthman, Marquart, & Reicks, 2006).

Dietitians study a variety of subjects, ranging from food and nutrition sciences, foodservice systems management, business, economics, computer science, culinary arts, sociology and communication to science courses such as biochemistry, physiology, microbiology, anatomy and chemistry (Academy of Nutrition and Dietetics [AND],

2015). As Wright (2014) discusses, this content is designed to provide students with threshold concepts of nutrition science as a basis for more advanced courses and the translation of science understanding into individualized medical nutrition therapy.

However, medical nutrition therapy of the future will harness advances in nutrition research and new technology to optimize health, target chronic disease prevention approaches in population subgroups, and alleviate the progression of genetically- associated conditions (Wright, 2014). To make a public impact, RDNs and other allied health professionals must be prepared with the knowledge necessary to provide nutritional genomic education (Prasad et al., 2011). Thus, nutrition science components of nutrition and dietetic university curricula and professional development programs need to be augmented with nutritional genomics material so that current and future nutrition and dietetics practitioners are familiar with this innovative field (Wright, 2014).

21

National Coalition for Health Professional Education in Genetics

The National Coalition for Health Professional Education in Genetics (NCHPEG) is a

United States non-profit organization whose mission is to promote the education of health professionals and to provide access to information about advances in human genetics to improve the health care of the nation (NCHPEG, 2007). According to NCHPEG (2007), the emerging discipline of nutritional genomics provides challenges and opportunities for expanding future nutrition education and training. The Academy of Nutrition and

Dietetics (AND), formerly known as the American Dietetic Association (ADA), has also recognized the importance of genetics in nutrition and has addressed nutritional genomics in it strategic plan (NCHPEG, 2007). The long-term goal is for the development of a set of core competencies in genetics to encourage clinicians and other professionals to integrate genetics knowledge, skills, and attitudes into routine health care, thereby providing effective and comprehensive services to individuals and families (NCHPEG,

2007). NCHPEG (2007) reports that basic education in genetics for dietitians should include:

 genetics-related terminology and nomenclature;

 a basic understanding of genetic principles, including:

o inheritance patterns

o basic genetic concepts underlying common, complex disease, and

o identification of individuals at risk;

 gathering and interpretation of family history data;

22

 nutritional needs of "traditional" genetic conditions including chromosome

abnormalities and inborn errors of metabolism;

 nutritional needs indicated by common genetic variation, as such data become

clinically relevant; and

 the validity and utility of genetic tests and the implications of nutritionally-related

genetic test results.

One approach to increase the profile of genetics and nutritional genomics among dietitians has been the use of genetics tutorials and lectures, which have been shown to result in increased genetics knowledge among student dietitians (Cragun, Couch, Prows,

Warren, & Christianson, 2005). Continuing education needs to focus on background foundational knowledge and the ability to translate information about gene-diet interactions, mechanisms, and recommendations into practical advice for clients and the lay public (Rosen et al., 2006). According to NCHPEG (2007), having a foundation of genetic knowledge will help dietitians:

 interact with other health care professionals around issues of nutritional genomics;

 appreciate the genetic and environmental aspects of health promotion and disease

prevention including the effects of foods and specific nutrients on gene

expression;

 locate, access, and evaluate information about nutritional genomics and be

involved in teams evaluating when new findings are ready for clinical use;

23

 appraise genetic information in family histories and incorporate data into the

nutrition care process; and

 communicate effectively about diet and genetic susceptibility and to educate

clients on how genetics affects their nutritional health.

Role of Sports Dietitians

It has been established that nutrition status plays a critical role in athletic performance.

In the joint position statement of the Academy of Nutrition and Dietetics (AND),

Dietitians of Canada (DOC), and the American College of Sports Medicine these organizations recommend appropriate selection of foods and fluids, timing of intake, and supplement choices for optimal health and exercise performance (Rodriguez et al., 2009).

A major cause of poor performance during competition is improper nutrition (Zoorob,

Parrish, O'Hara, & Kalliny, 2013); however, understanding the genetic nutritional needs of an athlete provides an additional valuable tool in strategies to optimize sports performance (Boehl, 2007; Debusk, Fogarty, Ordovas, & Kornman, 2005; Stover &

Caudill, 2008). As established by the AND, formerly known as the American Dietetic

Association (2008), it is the role of sports dietitians to provide individual and group/team nutrition counseling and education to enhance the performance of competitive and recreational athletes (as cited in Sports, Cardiovascular, and Wellness Nutrition [SCAN],

2015). Rodriguez et al (2009) reports the following:

24

In 2005, the Commission on Dietetic Registration (CDR) - the credentialing

agency of the American Dietetic Association - created a specialty credential for

food and nutrition professionals who specialize in sports dietetic practice. The

Board Certification Specialist in Sports Dietetics (CSSD) credential is designed as

the premier professional sports nutrition credential in the United States.

Specialists in Sports Dietetics provide safe, effective, evidence-based nutrition

assessment, guidance, and counseling for health and performance for athletes,

sport organizations, and physically active individuals and groups. The credential

requires current Registered Dietitian (RD) status, maintenance of RD status for a

minimum of 2 yr, and documentation of 1500 sports specialty practice hours as an

RD within the past 5 yr.

The Sports, Cardiovascular, and Wellness Nutrition (SCAN) dietetic practice group is the largest dietetic practice group of the Academy of Nutrition and Dietetics (SCAN, 2015).

With over 7,200 members, SCAN brings together Registered Dietitians, Registered

Dietetic Technicians and others with nutrition expertise in the areas of sports, physical activity, cardiovascular health, wellness, and the prevention and treatment of disordered eating and eating disorders (SCAN, 2015). Additionally, Sports Dietetics-USA, is a sub- unit of SCAN that focuses on sports nutrition issues, educating sports dietetics professionals, and advancing sports dietetics as a career specialty (SCAN, 2015). Sports

Dietetics-USA is dedicated to promoting nutrition practices that enhance lifelong health,

25 fitness, and sports performance; and advancing the vocation of sports dietetics (Sports,

Cardiovascular, and Wellness Nutrition, 2015).

Link Between Sports Dietitians’ and Non-Sports Dietitians Knowledge and

Perception of Nutritional Genomics for Enhancing Athletic Performance

Because the field of nutritional genomics is still a new area of research, there are many challenges and much uncertainty about the impact that promising scientific investigations will have on the public’s health. Genetics research has moved to the genomics era, and having identified the genes involved in athletic performance, there are intriguing possibilities of using this information within the scope of practice for sports dietitians

(Trent & Yu, 2009). However, there does not appear to be data related to Sports

Dietitians’ knowledge of nutritional genomics, nor any literature reviewing the possible implementation of nutritional genomics for the enhancement of athletic performance.

CHAPTER III

METHODS

Study Design

This was a quantitative, cross-sectional study designed to investigate sports dietitians’ knowledge of nutritional genomics and their perceptions of nutritional genomics for enhancing athletic performance. It was hypothesized that there would be a difference between Sports Dietitians (SRDs) and Non-Sports Dietitians (NSRDs) knowledge of nutritional genomics and their perceptions of nutritional genomics for enhancing athletic performance. Accordingly, dietitians with more knowledge of nutritional genomics would have stronger perceptions of nutritional genomics for enhancing athletic performance.

Participants

The study was a voluntary response sampling of Registered Dietitians from the membership database of the Commission on Dietetic Registration (CDR). The sampling represented 100% of the total membership database. While the focus of the study was on currently practicing sports dietitians, all CDR members were invited to complete the survey. Registered Dietitians who are Board Certified Specialists in Sports Dietetics

(CSSD) currently in practice and Registered Dietitians without CSSD certification who work directly with athletes for nutrition counseling one or more hours per week were included as Sports Dietitians (SRDs). Registered Dietitians who were not a Certified

26 27

Specialist in Sports Dietetics (CSSD) and did not work directly with athletes for nutrition counseling one or more hours per week were included as Non-Sports Dietitians (NSRDs).

Instruments

The study utilized a voluntary response questionnaire (Appendix A) composed of 3 sections to investigate: (1) Demographics (twelve questions); (2) Knowledge of genetics and diet-gene interactions (fourteen questions); (3) Perceptions of nutritional genomics for enhancing athletic performance (six questions). The demographic questions were used to assess identification criteria in the classification of dietitians as either SRDs or

NSRDs and factors that might affect knowledge of nutritional genomics and/or perceptions of nutritional genomics for enhancing athletic performance. To assess knowledge of genetics and diet-gene interactions, the knowledge section of the questionnaires used in Collins et al (2013), McCarthy et al (2008), and Whelan et al

(2008) were adapted, with permission. To assess perception of nutritional genomics for enhancing athletic performance: participants were presented with a general definition of nutritional genomics (Rosen et al., 2008) and a snippet from the Academy of Nutrition and Dietetics position paper on nutritional genomics (Camp & Trujillo, 2014), followed by items that asked about confidence in the ability to apply nutritional genomics based on the definition using a Likert scale. The questionnaire was created and distributed using

Qualtrics -v. 1.817s.

28

Procedure

A voluntary response survey was conducted to investigate knowledge of nutritional genomics and perceptions of nutritional genomics for enhancing athletic performance amongst sports dietitians. Permission to conduct the survey was obtained from the Kent

State University Office of Research Compliance Institutional Review Board for Human

Subjects research. An initial invitation to complete the survey questionnaire was distributed via email (March, 2015) to the membership database of the Commission on

Dietetic Registration (CDR). The CDR provides a complimentary e-mail list of its membership database to students conducting approved research studies. After a two week period from the original distribution date, an email reminder of the survey with revised invitation to complete the questionnaire was distributed to all subjects who had yet to complete the questionnaire. The survey remained open for a total of four weeks.

Questionnaire Scoring

The knowledge section of the questionnaire was scored according to the number of correct answers. Questions answered correctly were given a score of 1, while a score of 0 was given for questions answered incorrectly or as “Do Not Know”. The perception section was assessed using a five-point Likert scale (ranging from 1, “Strongly Disagree” to 5, “Strongly Agree”), and scored based on summed responses.

29

Data Analysis

Statistical Package for the Social Sciences (SPSS) version 21.0 was utilized for quantitative data analysis. Means and frequencies were calculated for demographic information. Parametric tests [independent t-test, Pearson correlation, and analysis of variance (ANOVA)] and Least Significant Difference post-hoc tests were used to detect and compare differences in knowledge and perception scores. Frequency and percent were determined for each knowledge question based on answers scored as correct, incorrect, “Do Not Know”, and for the total. An independent t-test was conducted to compare means for total knowledge score (TKS) and means for each perception item between SRDs and NSRDs. A Pearson product-moment correlation coefficient was computed to assess the relationship between TKS and the six perception items for both

SRDs and NSRDs. Finally, three one-way between subjects ANOVA were conducted to compare the effects of education level, athlete level, and the amount of time spent counseling athletes per week on TKS and each perception item. The Least Significant

Difference post-hoc test was used to identify where the differences occurred. A p value with a significance of < 0.05 was used for comparison.

Chapter IV

JOURNAL ARTICLE

Introduction

One of the key factors enabling the study of diet-gene interactions is the Human

Genome Project (Stover, 2006). Knowing the sequences of the human genome opened the door to examine the relationship among an individual’s genetic makeup, dietary intake, and health outcomes (Baumler, 2012). Upon completion of the Human Genome

Project in April 2003, nutritional genomics (the science of understanding the complex interaction between genes and diet) emerged as a promising field of nutrition research.

Nutritional genomics is an amalgamation of nutrigenomics (the way in which nutrients or dietary constituents influence gene expression) and nutrigenetics (the influence of genetic variation on the response to nutrients or dietary constituents) (McCarthy, Pufulete, &

Whelan, 2008). The aim of nutritional genomics is to identify the genetic variations that account for why some individuals react differently to dietary components (Stover, 2006).

Athletic performance is one area that nutritional genomics and personalized nutrition can potentially enhance, as physical fitness is a complex phenotype influenced by a myriad of environmental and genetic factors (MacArthur & North, 2005). Athletes adopt various nutritional strategies in an effort to succeed at the highest level (Maughan &

Shirreffs, 2012), and the development of technology for rapid DNA sequencing and genotyping has allowed the identification of some of the individual genetic variations that 30 31 contribute to athletic performance (MacArthur & North, 2005). It’s the competitive nature of sports that keeps most athletes looking for an edge, and when all else is equal as it usually is in elite sport, an assortment of minor factors can determine the successor

(Maughan & Shirreffs, 2012). Information derived from DNA profiling of relevant genes can indicate both advantages and genetic barriers that reflect on the athletic performance phenotype (Kambouris, Ntalouka, Ziogas, & Maffulli, 2012); thus, understanding the genetic nutritional needs of an athlete provides an additional valuable tool in strategies to optimize sports performance (Boehl, 2007; Debusk, Fogarty, Ordovas, & Kornman,

2005; Stover & Caudill, 2008).

Currently, there is a lack of studies regarding knowledge of nutritional genomics amongst sports dietitians and whether knowledge differences exist between sports dietitians and non-sports dietitians. The purpose of this study was to investigate sports dietitians’ knowledge of nutritional genomics and their perceptions of nutritional genomics for enhancing athletic performance.

Methods

Study Design

This was a quantitative, cross-sectional study designed to investigate sports dietitians’ knowledge of nutritional genomics and their perceptions regarding the potential implementation of nutritional genomics for enhancing athletic performance. It was hypothesized that there would be a difference between Sports Dietitians’ (SRDs) and

32

Non-Sports Dietitians’ (NSRDs) knowledge of nutritional genomics and their perceptions of nutritional genomics for enhancing athletic performance. Accordingly, dietitians with more knowledge of nutritional genomics would have stronger perceptions of nutritional genomics for enhancing athletic performance.

Participants

The study was a voluntary response sampling of Registered Dietitians from the membership database of the Commission on Dietetic Registration (CDR). The sampling represented 100% of the total membership. While the focus of the study was on currently practicing sports dietitians, all CDR members were invited to complete the survey.

Registered Dietitians who are Board Certified Specialists in Sports Dietetics (CSSD) currently in practice and Registered Dietitians without CSSD certification who work directly with athletes for nutrition counseling one or more hours per week were included as SRDs. Registered Dietitians who were not a Certified Specialist in Sports Dietetics

(CSSD) and did not work directly with athletes for nutrition counseling one or more hours per week were included as NSRDs.

Instruments

The study utilized a voluntary response questionnaire (Appendix A) composed of 3 sections to investigate: (1) Demographics (twelve questions); (2) Knowledge of genetics and diet-gene interactions (fourteen questions); (3) Perceptions regarding the potential implementation of nutritional genomics for enhancing athletic performance (six

33 questions). The demographic questions were used to assess identification criteria in the classification of dietitians as either SRDs or NSRDs and factors that might affect knowledge of nutritional genomics and/or perceptions of nutritional genomics for enhancing athletic performance. To assess knowledge of genetics and diet-gene interactions, the knowledge section of the questionnaires used in Collins et al (2013),

McCarthy et al (2008), and Whelan et al (2008) were adapted, with permission. To assess perception of nutritional genomics for enhancing athletic performance: participants were presented with a general definition of nutritional genomics as done in Rosen et al

(2008) and a snippet from the Academy of Nutrition and Dietetics position paper on nutritional genomics (Camp & Trujillo, 2014), followed by items that asked about confidence in their ability to apply nutritional genomics based on the definition using a

Likert scale. The questionnaire was created and distributed using the online survey, software, Qualtrics -v. 1.817s.

Procedure

A voluntary response survey was conducted to investigate sports dietitians’ knowledge of nutritional genomics and their perceptions of nutritional genomics for enhancing athletic performance. Permission to conduct the survey was obtained from the Kent State

University Office of Research Compliance Institutional Review Board for Human

Subjects research. An initial invitation to complete the survey questionnaire was distributed via email (March, 2015) to the membership database of the Commission on

Dietetic Registration (CDR). The CDR provides a complimentary e-mail list of its

34 membership database to students conducting approved research studies. After a two week period from the original distribution date, an email reminder of the survey with revised invitation to complete the questionnaire was distributed to all subjects that had not completed the questionnaire. The survey remained open for a total of four weeks.

Questionnaire Scoring

The knowledge section was scored according to the number of correct answers.

Questions answered correctly were given a score of 1. A score of 0 was given for questions answered incorrectly or as “Do Not Know”. The perception section was assessed using a five-point Likert scale (ranging from 1, “Strongly Disagree” to 5,

“Strongly Agree”), and scored based on summed responses.

Data Analysis

Statistical Package for the Social Sciences (SPSS) version 21.0 was utilized for quantitative data analysis. Means and frequencies were calculated for demographic information. Parametric tests [independent t-test, Pearson correlation, and analysis of variance (ANOVA)] and Least Significant Difference post-hoc tests were used to detect and compare differences in knowledge and perception scores. Frequency and percent were determined for each knowledge question based on answers scored as correct, incorrect, “Do Not Know”, and for the total. An independent t-test was conducted to compare means for total knowledge score (TKS) and means for each perception item between SRDs and NSRDs. A Pearson product-moment correlation coefficient was

35 computed to assess the relationship between TKS and the six perception items for both

SRDs and NSRDs. Finally, three one-way between subjects ANOVA were conducted to compare the effects of education level, athlete level, and the amount of time spent counseling athletes per week on TKS and each perception item. The Least Significant

Difference post-hoc test was used to identify where the differences occurred between groupings. A p value with a significance of < 0.05 was used for comparison.

Results

The membership database of the Commission on Dietetic Registration (CDR), as provided electronically, included ninety-two thousand four hundred thirty (92,430) potential participants. One thousand forty-six (1,046) members were missing an e-mail address, so the survey was distributed to ninety-one thousand three hundred eighty-four

(91,384) potential participants. There were seven thousand two hundred eighty-nine

(7,289) responses to the survey for an overall response rate of 7.98%. Of the 7, 289 total responses, six thousand two hundred nineteen (6,219) questionnaires were used in the study for a completion rate of 85.3%. The remaining one thousand seventy (1,070) participants did not complete the questionnaire before the close of the survey and were excluded from the study.

The target group, Sports Dietitians (n = 1027), comprised 16.5% of the participants while Non-Sports Dietitians (n = 5192) comprised 83.5% of the participants.

Demographic characteristics of survey respondents who completed the questionnaire are

36 displayed in Figure 1 (primary practice setting) and Table 1 (gender, age, race/ethnicity, and education level).

Figure 1 Primary Practice Setting for Survey Respondents Completing the “Dietitians’ Knowledge and Perceptions of Nutritional Genomics for Enhancing Athletic Performance” Questionnaire (n = 6219)

37

Table 1 Demographic Characteristics of Survey Respondents Completing the “Dietitians’ Knowledge and Perceptions of Nutritional Genomics for Enhancing Athletic Performance” Questionnaire

Survey Respondents Characteristic n = 6219 (%) Gender Male 269 (4%) Female 5906 (95%) Missing data 44 (0.7%) Age, years 18-29 1493 (24%) 30-49 2628 (42.3%) 50-64 1807 (29.1%) 65+ 252 (4.1%) Missing data 39 (0.6%) Race/Ethnicity Caucasian 5396 (86.8%) Other 660 (10.7%) Prefer not to answer 105 (1.7%) Missing data 58 (0.9%) Education Level High School Degree 2 (<1%) Bachelor's Degree 2465 (39.6%) Master's Degree 3285 (52.8%) Doctoral 374 (6%) Professional 66 (1.1%) Missing data 27 (0.4%)

Participant demographic characteristics were used to differentiate between Sports

Dietitians (SRDs) and Non-Sports Dietitians (NSRDs). SRDs are defined as any

Registered Dietitian that is a Certified Specialist in Sports Dietetics (CSSD) or a non-

CSSD Registered Dietitian who works directly with athletes for nutrition counseling one

38 or more hours per week. NSRDs are defined as any Registered Dietitian that is not a

Certified Specialist in Sports Dietetics (CSSD) and does not work directly with athletes for nutrition counseling one or more hours per week. The qualifying demographic characteristics used to identify the target group are displayed in Table 2.

Table 2 Qualifying Demographic Characteristics for Sport Dietitians Completing the “Dietitians’ Knowledge and Perceptions of Nutritional Genomics for Enhancing Athletic Performance” Questionnaire Survey Respondents n = 6219 (%) Registered Dietitian Yes 6153 (98.9%) No 8 (0.1%) Missing data 58 (0.9%) Board Certified Specialist in Sports Dietetics Yes 85 (1.4%) No 6017 (96.8%) Missing data 117 (1.9%) Duration of Board Certification in Sports Dietetics 0-4 years 46 (0.7%) 5-9 years 31 (0.5%) 10+ years 6 (0.1%) Missing data 6136 (98.7%) Level of athlete worked with: Beginner 237 (3.8%) Recreational 590 (9.5%) Well-trained 256 (4.1%) Elite 61 (1%) Does not work with athletes 4917 (79.1%) Missing data 158 (2.5%) Hours per week working with athletes 0 5145 (82.7%) 1-5 856 (13.8%) 6-10 64 (1%) 10+ 94 (1.5%) Missing data 60 (1%)

39

For knowledge section of the questionnaire, there were only six knowledge questions to which >50% of the participants answered correctly. There were three knowledge questions where the frequency of those answering “Do Not Know” exceeded the frequencies of both those who answered correctly or incorrectly. Additionally, there was one knowledge question where the frequency of those answering incorrectly exceeded the frequencies of those who answered correctly or “Do Not Know”. Frequencies of correct, incorrect, and do not know responses to the 14 knowledge questions for the entire sample are presented in Appendix E.

Overall, both groups of participants (SRDs and NSRDs) achieved a mean Total

Knowledge Score (TKS) of <60%. An independent-samples t-test was conducted to compare TKS and responses to the six Perception items between the SRDs and NSRDs.

Using p < 0.05 for comparison of means, the differences between the groups are significant on all items. TKS was calculated based on 14 genetics and diet-gene interaction questions answered correctly while Perception scores ranged from 1,

“Strongly Disagree” to 5, “Strongly Agree”. Mean scores and standard deviations representing TKS and Perception Responses between SRDs and NSRDs are presented in

Table 3.

A Pearson product-moment correlation coefficient was computed to assess the relationship between the TKS and responses to the six perception items for SRDs and

NSRDs. Pearson correlation scores showing the relationship between TKS and the six

40

Table 3 Summary of Total Knowledge Scores and Perception Responses Between Sport and Non-Sport Dietitian Groups Completing the “Dietitians’ Knowledge and Perceptions of Nutritional Genomics for Enhancing Athletic Performance” Questionnaire ( = mean, SD = standard deviation) Sports Dietitians Non-Sports Dietitians n = 1027 n = 5192 SD SD P

Knowledge* Total Score 7.88 2.525 7.36 2.744 0.001 Perception** I am comfortable discussing genetic 2.69 1.223 2.22 1.196 0.001 information with a client as part of a family history

There is a need for 4.39 0.853 4.26 0.871 0.001 continuing research in Nutritional Genomics

I am comfortable discussing with a client 1.88 1.095 1.63 0.954 0.001 how the MTHFR 677C→T defect may influence risk of disease

Nutritional Genomics research can be used to 3.7 0.792 3.47 0.742 0.001 improve athletic performance

Understanding the genetic nutritional needs of an athlete provides a valuable 3.85 0.843 3.66 0.812 0.001 tool in strategies to optimize sports performance

I am comfortable discussing with clients how 2.37 1.107 1.91 1.01 0.001 diet may interact with genes to influence athletic performance * The knowledge section was scored according to the number of correct answers. Do not know answers were counted as incorrect. ** The six perception items were assessed using a five-point Likert scale (ranging from 1, “Strongly Disagree” to 5, “Strongly Agree”), and scored based on summed responses.

41 perception items for SRDs and NSRDs completing the questionnaire are presented in

Figure 2 and Table 4. Pearson’s correlation is significant at the 0.01 level (2-tailed), and increases in TKS correlated with increases in Perception scores.

Figure 2 Pearson Correlation Scores between Total Knowledge Score and the Six Perception Responses for Sports Dietitians and Non-Sports Dietitians Completing the “Dietitians’ Knowledge and Perceptions of Nutritional Genomics for Enhancing Athletic Performance” Questionnaire

42

Table 4 Pearson Correlation Coefficient Values assessing the relationship between Total Knowledge Score and the Six Perception Responses for Sports Dietitians and Non-Sports Dietitians Completing the “Dietitians’ Knowledge and Perceptions of Nutritional Genomics for Enhancing Athletic Performance” Questionnaire

Pearson Correlation Coefficient (r)

Perception Questions Sports RDs Non-Sports RDs

1. I am comfortable discussing genetic 0.247 0.253 information with a client as part of a family history.

2. There is a need for continuing research in 0.173 0.215 Nutritional Genomics.

3. I am comfortable discussing with a client 0.346 0.253 how the methylenetetrahydrofolate reductase (MTHFR) 677C-->T defect may influence risk of disease.

4. Nutritional Genomics research can be used 0.161 0.155 to improve athletic performance.

5. Understanding the genetic nutritional needs 0.109 0.087 of an athlete provides a valuable tool in strategies to optimize sports performance.

6. I am comfortable discussing with clients 0.225 0.192 how diet may interact with genes to influence athletic performance. Note. All Pearson Correlation Coefficients were significant at the 0.01 level (2-tailed). Increases in Total Knowledge Score correlated with increases in Perception scores.

One-way (1x5) between subjects analysis of variance (ANOVA) was conducted to compare the effects of education level (High School graduate, Bachelor’s, Master’s,

Doctoral, or Professional degree) on TKS and each Perception item. The ANOVA

43 revealed significant differences in TKS and five of the six perception items at the p <

0.05 level. The means and standard deviation results are presented in Table 5. Post-hoc comparisons using the Fisher LSD test indicate that TKS increases reliably as education level increases to the Doctoral level. Unexpectedly, the mean TKS of dietitians with

Professional degrees were significantly lower than Master’s and Doctoral level dietitians.

For Perception item one (P₁), “I am comfortable discussing genetic information with a client as part of a family history,” post-hoc comparisons using the Fisher LSD test indicate that dietitians are uncomfortable discussing genetic information with clients.

Yet, the comfort level increases significantly as education level increases to the Doctoral level. Dietitians with Professional degrees were only reliably more comfortable than dietitians whose highest level of education was a Bachelor’s degree. Post-hoc comparisons using the Fisher LSD test for Perception item two (P2), “There is a need for continuing research in nutritional genomics,” indicate that dietitians agree more with this statement as education level increases to the Doctoral level. Dietitians at all education levels appear to have a low level of comfort discussing with a client how the

Methylenetetrahydrofolate Reductase (MTHFR) 677C→T defect may influence risk of disease. However, the results of post-hoc comparisons using the Fisher LSD test for

Perception item three (P3), “I am comfortable discussing with a client how the

Methylenetetrahydrofolate Reductase (MTHFR) 677C→T defect may influence risk of

44

Table 5 Results of one-way (1x5) between groups ANOVA for Education Level ( = mean, SD = standard deviation) Education Level SD (+/-) F P

Total Knowledge Score High School Graduate 6.50 3.536 Bachelor’s 6.95 2.627 Masters 7.60 2.655 Doctoral 9.47 2.689 Professional 6.58 2.899 Total 7.44 2.716 Between Groups 80.637 0.001

Perception Items

I am comfortable discussing High School Graduate 1.50 0.707 genetic information with a Bachelor’s 2.17 1.169 client as part of a family history Masters 2.34 1.223 Doctoral 2.78 1.269 Professional 2.52 1.218 Total 2.30 1.213 Between Groups 23.700 0.001 There is a need for continuing High School Graduate 3.00 1.414 Research in Nutritional Genomics Bachelor’s 4.23 0.877 Masters 4.31 0.861 Doctoral 4.48 0.856 Professional 4.36 0.757 Total 4.29 0.869 Between Groups 9.302 0.001 I am comfortable discussing with a High School Graduate 1.50 0.707 client how the methylenetetrahydrofolate Bachelor’s 1.55 0.886 reductase (MTHFR) 677C→T Masters 1.70 0.988 defect may influence risk of disease Doctoral 2.29 1.260 Professional 1.70 0.992 Total 1.67 0.983 Between Groups 48.809 0.001 Nutritional Genomics research High School Graduate 3.00 1.414 can be used to improve athletic Bachelor’s 3.48 0.739 performance Masters 3.54 0.758 Doctoral 3.50 0.821 Professional 3.44 0.747 Total 3.51 0.755 Between Groups 2.501 0.040 Understanding the genetic nutritional High School Graduate 3.50 2.121 needs of an athlete provides a valuable Bachelor’s 3.69 0.808 tool in strategies to optimize sports Masters 3.70 0.823 performance Doctoral 3.63 0.896 Professional 3.68 0.660 Total 3.69 0.820 Between Groups 0.682 0.605 I am comfortable discussing with High School Graduate 3.00 1.414 clients how diet may interact with Bachelor’s 1.88 0.999 genes to influence athletic Masters 2.02 1.050 performance Doctoral 2.36 1.126 Professional 2.17 1.046 Total 1.99 1.042 Between Groups 20.981 0.001

45 disease,” indicate that comfort level increases reliably as education level increases from the Bachelor’s degree level to the Professional degree level. Dietitians at all education levels tended to remain neutral on Perception item four (P4), “nutritional genomic research can be used to improve athletic performance.” The results of Fisher LSD post- hoc comparisons indicate that education level only significantly affected the Bachelor’s to Master’s level. Education level did not significantly affect dietitians level of agreement or disagreement with Perception item five (P5), “Understanding the genetic nutritional needs of an athlete provides a valuable tool in strategies to optimize sports performance.” Finally, dietitians at all education levels have a low level of comfort discussing how diet may interact with genes to influence athletic performance. The results of Fisher LSD post-hoc comparisons for Perception item six (P6), “I am comfortable discussing with clients how diet may interact with genes to influence athletic performance,” indicate that comfort level increases reliably as education level increases to the Doctoral level.

A separate one-way (1x4) ANOVA was conducted to compare the effects of time per week spent working directly with athletes for nutrition counseling (0 hours, 1-5 hours, 6-

10, hours, or 10+ hours) on TKS and each Perception item. The ANOVA revealed significant differences in TKS and each of the six Perception items at the p < 0.05 level.

The means and standard deviation results are presented in Table 6. Post-hoc comparisons using the Fisher LSD test indicate that TKS increases significantly as time spent with athletes per week increases up to 10 hours. Working directly with athletes for

46

Table 6 Results of one-way (1x4) between groups ANOVA for Time spent working with athletes ( = mean, SD = standard deviation)

Education Level SD (+/-) F P

Total Knowledge Score 0 hours 7.36 2.751 1-5 hours 7.90 2.466 6-10 hours 8.20 2.558 10+ hours 7.47 2.789 Total 7.45 2.718 Between Groups 11.212 0.001

Perception Items

I am comfortable discussing 0 hours 2.22 1.195 genetic information with a 1-5 hours 2.68 1.225 client as part of a family history 6-10 hours 2.83 1.189 10+ hours 2.63 1.227 Total 2.30 1.212 Between Groups 43.144 0.001 There is a need for continuing 0 hours 4.26 0.873 Research in Nutritional Genomics 1-5 hours 4.37 0.878 6-10 hours 4.48 0.666 10+ hours 4.46 0.667 Total 4.28 0.870 Between Groups 6.431 0.001 I am comfortable discussing with a client 0 hours 1.63 0.954 how the Methylenetetrahydrofolate 1-5 hours 1.87 1.084 Reductase (MTHFR) 677C→T 6-10 hours 1.97 1.168 defect may influence risk of 10+ hours 1.81 1.070 disease Total 1.67 0.981 Between Groups 17.092 0.001 Nutritional Genomics research 0 hours 3.47 0.742 can be used to improve athletic 1-5 hours 3.71 0.785 performance 6-10 hours 3.78 0.806 10+ hours 3.53 0.813 Total 3.51 0.755 Between Groups 28.619 0.040 Understanding the genetic nutritional needs 0 hours 3.65 0.813 of an athlete provides a valuable tool in 1-5 hours 3.86 0.827 strategies to optimize sports performance 6-10 hours 3.98 0.807 10+ hours 3.79 0.938 Total 3.69 0.820 Between Groups 18.490 0.605 I am comfortable discussing with 0 hours 1.91 1.008 clients how diet may interact with 1-5 hours 2.36 1.119 genes to influence athletic 6-10 hours 2.50 1.127 performance 10+ hours 2.29 0.991 Total 1.98 1.039 Between Groups 56.640 0.001

nutrition counseling greater than 10 hours per week did not significantly affect TKS. For

Perception item one (P₁), results of Fisher LSD post-hoc comparisons indicate that the

47 comfort level discussing genetic information with clients increases significantly as the amount of time spent with athletes per week increases up to 10 hours. Working directly with athletes for nutrition counseling greater than 10 hours per week did not significantly affect comfort level among SRDs. For Perception item two (P2), the results of Fisher

LSD post-hoc comparisons indicate that dietitians reliably agree more with the statement that there is a need for continuing research in nutritional genomics as time spent working directly with athletes for nutrition counseling increases up to 10 hours. However, working directly with athletes for nutrition counseling greater than 10 hours per week did not significantly affect level of agreement among SRDs. Both NSRDs and SRDs have low levels of comfort discussing with clients how the Methylenetetrahydrofolate

Reductase (MTHFR) 677C→T defect may influence risk of disease. Fisher LSD post- hoc comparisons of Perception item three (P3) and time spent with athletes indicate that comfort level increases as time spent working directly with athletes for nutrition counseling increases up to 10 hours. For Perception item four (P4), NSRDs and SRDs, alike, tended to remain neutral on this item. Fisher LSD post-hoc comparisons indicate that level of agreement increases as time spent working directly with athletes for nutrition counseling increases up to 10 hours. However, working directly with athletes for nutrition counseling greater than 10 hours per week had a significantly negative effect on level of agreement. Similar to P4, NSRDs and SRDs tended to remain neutral on

Perception item five (P5). The results of a post-hoc Fisher LSD test indicate that level of agreement increases as time spent working directly with athletes for nutrition counseling

48 increases up to 10 hours. Working directly with athletes for nutrition counseling greater than 10 hours per week does not significantly affect comfort level among SRDs. Finally, for Perception item six (P6), the results of a post-hoc Fisher LSD test indicate that comfort level discussing with clients how diet may interact with genes to influence athletic performance increases significantly as the amount of time spent with athletes per week increases up to 10 hours. Working directly with athletes for nutrition counseling greater than 10 hours per week did not significantly affect comfort level among SRDs.

Finally, a third one-way (1x5) between groups ANOVA was conducted to compare the effects of athlete level (beginner, recreational, well-trained, elite, and ‘I do not work with athletes’) on TKS and each Perception item. NSRDs are among those labeled, “I do not work with athletes.” The ANOVA revealed significant differences in TKS and each of the six Perception items at the p < 0.05 level. The means and standard deviation results are presented in Table 7. Post-hoc comparisons using the Fisher LSD test indicate that

TKS increases significantly as athlete level increases up to the well-trained level.

Working with elite level athletes did not have a significant effect on TKS. NSRDs and

SRDs working with beginner, recreational, and elite athletes are indicate low levels of comfort discussing genetic information with clients as part of a family history.

Comparing athlete level and Perception item one (P₁), the results of a post-hoc Fisher

LSD test indicate that comfort level increases significantly as athlete level increases up to

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Table 7 Results of one-way (1x5) between groups ANOVA for Athlete Level ( = mean, SD = standard deviation) Level of Athlete SD (+/-) F P

worked with Total Knowledge Score Beginner 7.43 2.316 Recreational 7.83 2.484 Well-trained 8.39 2.469 Elite 7.62 2.990 None 7.35 2.758 Total 7.44 2.718 Between Groups 12.359 0.001

Perception Items

I am comfortable discussing Beginner 2.44 1.205 genetic information with a Recreational 2.67 1.229 client as part of a family history Well-trained 3.01 1.214 Elite 2.64 1.096 None 2.21 1.192 Total 2.30 1.214 Between Groups 46.420 0.001 There is a need for continuing Beginner 4.27 0.880 Research in Nutritional Genomics Recreational 4.41 0.806 Well-trained 4.38 0.954 Elite 4.49 0.766 None 4.27 0.864 Total 4.29 0.864 Between Groups 5.299 0.001 I am comfortable discussing with a client Beginner 1.62 0.864 how the methylenetetrahydrofolate Recreational 1.83 1.066 reductase (MTHFR) 677C→T defect may Well-trained 2.17 1.246 influence risk of Elite 1.77 0.902 disease None 1.63 0.954 Total 1.67 0.982 Between Groups 23.392 0.001 Nutritional Genomics research Beginner 3.60 0.783 can be used to improve athletic Recreational 3.68 0.759 performance Well-trained 3.73 0.827 Elite 3.74 0.964 None 3.47 0.738 Total 3.51 0.753 Between Groups 18.584 0.001 Understanding the genetic nutritional Beginner 3.71 0.865 needs of an athlete provides a valuable Recreational 3.82 0.794 tool in strategies to optimize sports Well-trained 3.95 0.853 performance Elite 3.97 1.032 None 3.66 0.807 Total 3.69 0.816 Between Groups 14.198 0.001 I am comfortable discussing with Beginner 2.20 1.057 clients how diet may interact with Recreational 2.23 1.082 genes to influence athletic Well-trained 2.70 1.128 performance Elite 2.66 1.250 None 1.90 1.004 Total 1.98 1.041 Between Groups 56.791 0.001

50 the well-trained level. Dietitians working with elite level athletes are reliably less comfortable than those working with well-trained athletes. NSRDs and SRDs agree with

P2, “There is a need for continuing research in nutritional genomics.” Post-hoc comparisons using the Fisher LSD test indicate that SRDs reliably agree more. For

Perception item three (P3), the results of Fisher LSD post-hoc tests indicate that comfort level increases as the athlete level increases to the well-trained level. Working with elite level athletes does not have a significantly positive effect on comfort level. Both NSRDs and SRDs tended to remain neutral on P4, but Fisher LSD post-hoc comparisons indicate that SRDs have reliably stronger perceptions regarding potential implementation of nutritional genomics for enhancing athletic performance. Similarly, NSRDs and SRDs tended to remain neutral on P5, but the results of post-hoc Fisher LSD tests indicate that

SRDs have reliably stronger perceptions regarding this statement. This suggests that more evidence is needed for dietitians to take a definitive stance on how understanding the genetic nutritional needs of an athlete may provide a valuable tool in strategies to optimize sports performance. Finally, for Perception item six (P6), NSRDs and SRDs have low levels of comfort discussing with clients how diet may interact with genes to influence athletic performance. The results of a post-hoc Fisher LSD test indicate that comfort level increases significantly as athlete level increases up to the well-trained level.

Working with elite level athletes does not have a significantly positive effect on comfort level.

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Discussion

This study was a voluntary response sampling of Registered Dietitians from the membership database of the Commission on Dietetic Registration (CDR). An online questionnaire survey was conducted to investigate sports dietitians’ knowledge of nutritional genomics and their perceptions of nutritional genomics for enhancing athletic performance. It was hypothesized that there would be a difference between Sports

Dietitians (SRDs) and Non-Sports Dietitians (NSRDs) in both knowledge of nutritional genomics and the perception of nutritional genomics for enhancing athletic performance.

Additionally, dietitians with more knowledge of nutritional genomics would have stronger perceptions regarding implementation of nutritional genomics for enhancing athletic performance.

The distribution of responses to the knowledge questions are presented in Appendix E.

The study indicates that dietitians, overall, have general knowledge of the basic concepts of genetics (e.g., defining what a gene is). However, as indicated in previous studies, dietitians are lacking advanced knowledge of genetics and diet-gene interactions. To understand and apply the concepts of nutritional genomics, dietitians need more advanced education in genetics and diet-gene interactions. Currently, the science of nutritional genomics is not ready to be implemented for enhancing athletic performance, nor are dietitians prepared to implement it. Dietitians must be prepared with more than just the basic knowledge of genetics to provide nutritional genomics education to the public and in practice.

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Knowledge of Nutritional Genomics between Dietitians

The hypothesis that there would be a difference between Sports Dietitians and Non-

Sports Dietitians in knowledge of nutritional genomics was accepted. There are no previous studies investigating sports dietitians’ knowledge of nutritional genomics, or comparing knowledge of genetics and diet-gene interactions between Sports Dietitians and Non-Sports Dietitians. Results of this study indicate that Total Knowledge Scores

(TKS) among Sports Dietitians (SRDs) were significantly greater than Non-Sports

Dietitians (NSRDs), as presented in Table 4. TKS among SRDs increased significantly as time spent with athletes per week increased up to 10 hours and as athlete level increased up to the well-trained level. Working directly with athletes for nutrition counseling greater than 10 hours per week did not significantly affect Total Knowledge

Score, nor did working with elite level athletes have a significantly positive effect on

Total Knowledge Score. For both SRDs and NSRDs, Total Knowledge Scores increased as education level increased to the Doctoral level, which is similar to the findings of

McCarthy et al (2008). However, it was surprising to observe that professional degree level dietitians scored significantly lower than Master’s and Doctoral level dietitians.

This could be due to this group being furthest removed from the genetics content of university education and more specialized professionally. As Whelan et al (2008) discusses, while a Total Knowledge Score enables an overall estimate of knowledge, it is limited in that it cannot represent the totality of knowledge relating to genetics and diet- gene interactions relevant to majority, or individual specialties, of dietitians.

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Perception of Nutritional Genomics between Dietitians

The hypothesis that there would be a difference between Sports Dietitians’ and Non-

Sports Dietitians’ perception of nutritional genomics for enhancing athletic performance was also accepted. There are no previous studies investigating dietitians’ perception of nutritional genomics for enhancing athletic performance, nor comparing perception of nutritional genomics for enhancing athletic performance between Sports Dietitians and

Non-Sports Dietitians. The study indicates that SRDs responses to the six Perception items were significantly different than responses from NSRDs. SRDs responded more favorably to the statements that nutritional genomic research can be used to improve athletic performance and that understanding the genetic nutritional needs of an athlete provides a valuable tool in strategies to optimize sports performance, although both groups tended to remain neutral. The level of agreement with these statements increased significantly as athlete level increased, as well as with increased time spent working directly with athletes for nutrition counseling up to 10 hours. Working directly with athletes for nutrition counseling greater than 10 hours per week had a significantly negative effect on level of agreement. This indicates that the benefits of nutritional genomics for enhancing athletic performance are perceived to occur in higher level athletes. However, the perceived benefits may be limited amongst dietitians who spend that most time with athletes. Both groups agree that there is a need for continuing research in nutritional genomics, which indicates a need for more studies and evidence of

54 benefits of nutritional genomics for enhanced athletic performance to strengthen perceptions.

Linking Knowledge and Perceptions

The hypothesis that dietitians with more knowledge of nutritional genomics would have stronger perceptions regarding potential implementation of nutritional genomics in enhancing athletic performance was accepted. The study indicates that

Sports Dietitians’ Total Knowledge Scores and responses to the six Perception items were significantly greater than Non-Sports Dietitians, as presented in Table 4. There was a weak to moderate positive correlation for SRDs and NSRDs between TKS and the six

Perception items, as presented in Figure 2 and Table 5. SRDs and NSRDs both tended to disagree with the following perception items: I am comfortable discussing genetic information with a client as part of a family, I am comfortable discussing with a client how the methylenetetrahydrofolate reductase (MTHFR) 677C→T defect may influence risk of, and I am comfortable discussing with clients how diet may interact with genes to influence athletic performance. This suggests that dietitians still lack involvement and confidence in providing genetic services and diet-gene interactions, as were indicated in previous studies by Lapham et al (2000) and Whelan et al (2008).

Limitations

There were several limitations to this study. First, there were a disproportionate number of Non-Sports Dietitians (NSRDs) participating in the study in comparison to the

55 sample size of Sports Dietitians (SRDs). Access to members of an organization that represents a large number of dietitians in the United States who work full-time with athletes was denied due to concerns of double contacting members that may have already received an invitation to complete the survey through the Commission on Dietetic

Registration membership database. Alternatively, even if permission was granted to access members of that organization, the sample size of NSRDs to SRDs would still have been disproportionate. Additionally, some demographic questions were skipped by the participants, which lead to missing data. The demographic questions were used to determine the size of target group. It should also be noted that the ratio of SRDs to

NSRDs in the study is representative of the general breakdown of Registered Dietitians in the Commission on Dietetic Registration membership database.

Next, not defining what constituted a Professional degree may have caused confusion in the education level selection process. This designated education level may include dietitians from other education levels, which his may have particularly affected the mean

Total Knowledge Score. Surprisingly, the mean Total Knowledge Score for the professional level was significantly lower than the doctorate level, and more comparable to participants who reported a high school education level.

Lastly, the totality of the Perception items may not have fully anticipated perspective when designed. It has been noted that “there were statements about comfort in talking to people about application of nutritional genomics and statements about whether nutritional genomics can be used to enhance performance,” yet, someone can strongly agree with

56 being comfortable in talking to a client about nutritional genomics and the impact of gene-diet interactions while also concluding that the level of science is not there yet for meaningful impact. Thus, having strong disagreement that nutritional genomics can enhance performance and strong agreement with being comfortable in talking to athletes about the impact of nutritional genomics on their performance may provide seemingly disparate answers.

Applications

It was evident in this study that more knowledge of genetics and diet-gene interactions is needed for all dietitians in order for them to feel comfortable and confident in this advancing field. As noted by Lovgrove and Gitau (2008), while there is increasing evidence for interactions between nutrients, genes, and environmental factors, the study of nutritional genomics and its application are limited by inconsistencies in the evidence.

Experience with nutritional genomics is still limited, and many dietitians are not confident in their ability to apply nutrigenomics (Rosen et al, 2006). This was evidenced by the current study and as expressed by a participant, “my discussion with [athletes] would be along the lines of the limitations of the science at this point and that it's premature.”

In the future, it is believed that nutritional genomics will fill a critical gap in developing evidenced based nutritional interventions (Debusk et al, 2005). The map of the diet-genome interface is far from complete, yet broad ideas and interactions are

57 materializing. Athletes and active individuals are seeking professional guidance in making optimal food and fluid choices (Rodriguez, Di Marco, & Langley, 2009), and sports dietitians can potentially utilize nutritional genomics to enhance athletic performance. As individuals continue to explore their genetic information and it becomes available, this data is likely to redefine preventive medicine and dietetics professionals will have the potential to harness this information to influence health promotion and disease prevention (Debusk et al, 2005). As discussed in Whelan et al

(2008), there are knowledge and skills gaps that must be filled for the potential of advances in nutritional genomics to be realized. To understand and apply the concepts of nutritional genomics, dietitians need more advanced education in genetics and diet-gene interactions.

Recommendations for Future Research

This is one of the first studies to investigate sports dietitians’ knowledge of nutritional genomics and perception of nutritional genomics for enhancing athletic performance.

Additionally, this study is one of the first to compare knowledge of genetics and diet- gene interactions or perception of nutritional genomics for enhancing athletic performance between Sports Dietitians and Non-Sports Dietitians. Future studies can compare knowledge, involvement, and comfort level of sports dietitians to other professions (such as exercise physiologists, athletic trainers, physical therapists, or others involved in sports medicine) that work full-time with athletes. Future studies can also explore athletes’ knowledge of nutritional genomics and/or their perceptions of whether

58 or not the application of nutritional genomics for enhancing athletic performance is something that they would be interested in exploring. Finally, future studies involving perception should also anticipate perspective.

Conclusion

This investigation of sports dietitians’ knowledge of nutritional genomics and their perception regarding the potential implementation of nutritional genomics in enhancing athletic performance revealed significant differences in both knowledge of nutritional genomics and perception for enhancing athletic performance between Sports Dietitians and Non-Sports Dietitians. Results indicate that there is still a need for dietitians to become more versed in genetics and diet-gene interactions in order to feel more confident and comfortable implementing nutritional genomics into practice. It is hoped that there might be a future role for nutritional genomics in the enhancement of athletic performance, but most dietitians agree that the science is not there. The science of nutritional genomics, in its current state, is not ready to be implemented for enhancing athletic performance, nor are dietitians prepared to implement it. Dietitians must be prepared with more than just the basic knowledge of genetics to provide nutritional genomics education to the public and in practice.

APPENDICES

APPENDIX A

QUESTIONNAIRE

APPENDIX A

QUESTIONNAIRE

Section 1 - Demographics In order to ensure anonymity, please note that you will not be able to save your responses and return to the survey at a later stage. Please review your responses before clicking ‘submit’ to send your completed survey. You will not be able to return to your responses after submitting the survey. What is your age? o 18-29 years old o 30-49 years old o 50-64 years old o 65 years and over What is your gender? o Male o Female What is your race/ethnicity? o Asian or Asian Indian o Black or African American o Hispanic, Latino, or Spanish o Native American or Alaskan Native o Native Hawaiian or Other Pacific Islander o White/Caucasian o Other o Prefer not to answer

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What is the highest degree or level of school you have completed? If currently enrolled, mark the highest degree received. o High School graduate o Bachelor’s degree o Master’s degree o Doctoral degree o Professional degree Are you a Registered Dietitian? o Yes o No →Display this question: If “Are you a Registered Dietitian?” Yes is selected Are you a Board Certified Specialist in Sports Dietetics (CSSD)? o Yes o No →Display this question: If “Are you a Board Certified Specialist in Sports Dietetics (CSSD)?” Yes is selected How long have you been a Board Certified Specialist in Sports Dietetics (CSSD)? o 0-4 years o 5-9 years o 10 or more years How would you best describe your primary employment/practice setting? o Hospital/Clinical setting o University setting o Private practice o Consultant

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o Health Club/Fitness Center o Self-employed o Student o Retired o Other →Display this question: If “How would you best describe your primary employment/practice setting?” Other is selected You are at this question because you chose "Other" to describe your employment/practice setting. Please describe your employment/practice setting below. How many hours per week do you work directly with athletes for nutrition counseling? o 0 hours o 1-5 hours o 6-10 hours o 10 or more hours What type of athletes do you work with primarily? o Beginner o Recreational o Well-trained o Elite o I do not work with athletes

Section 2 – Knowledge about genetics and nutritional genomics Please attempt this questionnaire by yourself. We would like you to be honest in your answers and not refer to other sources during the completion of this questionnaire. This is so we can collect accurate data. Thank you for your cooperation.

The following section consists of a series of multiple choice questions. Please choose the answer you think is correct by clicking on the relevant box. THERE IS ONLY ONE

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CORRECT ANSWER FOR EACH QUESTION. If you don’t know the answer, please choose ‘do not know’ rather than guessing. Remember that we want to know what YOU think. Please do not ask others for the answer or look it up in a book or on the internet. A "gene" is: o An alteration in DNA that results in disease o The protein produced from DNA o A short sequence of RNA  A DNA sequence that codes for a protein o Do not know A "chromosome" is:  A self-replicating genetic structure within cells o An abnormality occurring in DNA o A gene o A gene that causes a disease o Do not know An "allele" is: o A single stranded piece of DNA  One of a set of alternative forms of a gene o A gene o Part of the nucleus where DNA is stored o Do not know “Genotype” refers to:  The genetic information in an organism o The effect of the genetic code on proteins o The type of DNA in genes

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o Any genetic disorder o Do not know “Phenotype” is: o The genetic alteration responsible for PKU  A trait resulting from the genetic code o A type of gene that is expressed o A trait resulting from genes that do not code o Do not know “Single nucleotide polymorphisms (SNPs)” are: o The range of genes in one human o The changes in DNA during a cell cycle o A mutating gene  The most common form of genetic variability in the human genome o Do not know A “mutation” is: o Apoptosis o A change in DNA sequence o A change in DNA between generations o A change in DNA that results in disease o Do not know “PCR” stands for: o Promotion of cell replication o Polymorphism control region  Polymerase chain reaction o Penetrance of cancer risk

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o Do not know “NUTRIGENOMICS” is:  The effect of diet on how genes work o How genes affect what we eat o The effect of genes on the response to diet o Passing nutritional diseases to the offspring o Do not know “NUTRIGENETICS” is: o The effect of diet on how genes work o How genes affect what we eat  The effect of genes on the response to diet o Passing nutritional diseases to the offspring o Do not know Which of the following is NOT part of NUTRITIONAL GENOMICS?  Genetically modifying bacteria to change their susceptibility to antibiotics o The interaction between genes and diet to influence metabolic processes and disease risk o Genetically modifying plants to change the qualities of food crops o Using genetic tests to predict health susceptibilities and food intolerances o Do not know In which condition is a genetic test regularly used? o Hepatitis B o Irritable bowel syndrome (IBS)  Hemochromatosis o Anorexia Nervosa

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o Do not know Which of the following defects interact with dietary fat intake to influence the risk of cardiovascular disease? o CBS 844ins68 o Angiotensinogen M235T  ApoE2/E2 o MS 2756A→G o Do not know What condition is NOT associated with the Methylenetetrahydrofolate Reductase (MTHFR) 677C→T defect? o Cardiovascular disease o Colorectal cancer  Type 1 Diabetes Mellitus o Neural Tube Defects o Do not know Section 3 – Perceptions of nutritional genomics and potential implementation in the enhancement of athletic performance Nutritional Genomics is a term used to describe the relationship between the human genome, nutrition, and health. It is the position of the Academy of Nutrition and Dietetics that nutritional genomics provides insight into how diet and genotype interactions affect phenotype.

The following series of questions will assess your perception of Nutritional Genomics and confidence in the ability to apply nutritional genomics in the enhancement of athletic performance. Please choose your answer based on your level of agreement or disagreement with the statement. Remember that we want to know what YOU think. Please do not ask others for the answer or look it up in a book or on the internet.

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Please choose your answer based on your level of agreement or disagreement with the statement.

Strongly Disagree Neither Agree Agree Strongly Disagree nor Disagree Agree

I am comfortable discussing o o o o o genetic information with a client as part of a family history.

There is a need for o o o o o continuing research in Nutritional Genomics.

I am comfortable discussing o o o o o with a client how the Methylenetetrahydrofolate Reductase (MTHFR) 677C®T defect may influence risk of disease.

Nutritional Genomics o o o o o research can be used to improve athletic performance.

Understanding the genetic o o o o o nutritional needs of an athlete provides a valuable tool in strategies to optimize sports performance.

I am comfortable discussing o o o o o with clients how diet may interact with genes to influence athletic performance.

APPENDIX B

RECRUITMENT E-MAILS

Appendix B

Recruitment E-Mails

Subject: Survey investigating nutritional genomics and athletic performance Dear Colleagues, My name is Christopher S. Cooper and I am a graduate student in Nutrition at Kent State University. I received your e-mail address from the Commission on Dietetic Registration (CDR), as the CDR provides a complimentary e-mail list of its membership database to students conducting approved research studies.

I am writing to ask you to complete a short (10-15 minutes), anonymous survey to help me collect data to complete my Master’s Thesis. The study is investigating dietitians’ knowledge of nutritional genomics and perceptions regarding the potential implementation of nutritional genomics in enhancing athletic performance. The survey asks a series of questions regarding demographics, knowledge of genetics and diet-gene interactions, and perceptions of nutritional genomics. While the focus of the study is on currently practicing sports dietitians, I invite all dietitians to complete the survey.

If you would like to be removed from this e-mail list and not receive any future requests to take this survey, please click on the link at the bottom of the page to opt out of future e-mails. I apologize for any inconvenience. If you have any questions, please e-mail me ([email protected]) or my advisor Dr. Amy Miracle ([email protected]). Thank you in advance for your participation. Your time and efforts are greatly appreciated! Christopher S. Cooper Follow this link to the Survey: ${l://SurveyLink?d=Take the Survey} Or copy and paste the URL below into your internet browser: ${l://SurveyURL} Follow the link to opt out of future emails: ${l://OptOutLink?d=Click here to unsubscribe}

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Subject: REMINDER: Survey investigating nutritional genomics and athletic performance Dear Colleagues,

My name is Christopher S. Cooper and I am a graduate student in Nutrition at Kent State University. You may have already received an e-mail inviting you to participate in this survey. If you have already completed the questionnaire, please accept our thanks and delete this e-mail as no further involvement is required. If you have not completed the questionnaire please take the time to consider participating in this study.

I received your e-mail address from the Commission on Dietetic Registration (CDR). The CDR provides a complimentary e-mail list of its membership database to students conducting approved research studies.

This is an invitation to complete a short (10-15 minutes), anonymous survey to help me collect data to complete my Master’s Thesis. The study is investigating dietitians’ knowledge of nutritional genomics and perceptions regarding the potential implementation of nutritional genomics in enhancing athletic performance. The survey asks a series of questions regarding demographics, knowledge of genetics and diet-gene interactions, and perceptions of nutritional genomics. While the focus of the study is on currently practicing sports dietitians, I invite all dietitians to complete the survey.

If you have any questions, please e-mail me ([email protected]) or my advisor Dr. Amy Miracle ([email protected]).

Thank you in advance for your participation. Your time and efforts are greatly appreciated!

Christopher S. Cooper

Follow this link to the Survey: ${l://SurveyLink?d=Take the Survey} Or copy and paste the URL below into your internet browser: ${l://SurveyURL} Follow the link to opt out of future emails: ${l://OptOutLink?d=Click here to unsubscribe}

APPENDIX C

STUDY CONSENT FORM

Appendix C

Study Consent Form

Dietitians’ Knowledge and Perceptions of Nutritional Genomics for Enhancing Athletic Performance Welcome to "Dietitians’ Knowledge and Perceptions of Nutritional Genomics for Enhancing Athletic Performance," a thesis study investigating nutritional genomics from a sports dietitians’ perspective. Before taking part in this study, please read the consent form below and click on the "I Agree" button at the bottom of the page if you understand the statements and freely consent to participate in the study.

Consent Form

This study involves an online voluntary response questionnaire designed to investigate knowledge and perceptions of nutritional genomics for enhancing athletic performance. The study is being conducted by Dr. Amy Miracle of Kent State University, and it has been approved by the Kent State University Institutional Review Board. No deception is involved, and the study involves no more than minimal risk to participants (i.e., the level of risk encountered in daily life).

Participation in the study typically takes 10-15 minutes and is strictly anonymous. Participants begin by answering a series of demographic questions used to assess inclusion/exclusion criteria and factors that might affect knowledge of nutritional genomics and/or perceptions regarding its implementation in enhancing athletic performance. In the next section, participants will answer a series of questions to assess knowledge of genetics and diet-gene interactions. Finally, to assess perception about implementation of nutritional genomics in enhancing athletic performance, we will provide a simple general description of nutritional genomics followed by items that ask about level of agreement with the definition and confidence in the ability to apply nutritional genomics.

All responses are treated as confidential, and in no case will responses from individual participants be identified. Rather, all data will be pooled and published in aggregate form only.

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All visitors to this web site are welcome to complete the questionnaire, although there will be no credit or monetary compensation related to this study. Participation is voluntary, refusal to take part in the study involves no penalty or loss of benefits to which participants are otherwise entitled, and participants may withdraw from the study at any time without penalty or loss of benefits to which they are otherwise entitled.

If participants have further questions about this study or their rights, or if they wish to lodge a complaint or concern, they may contact the principal investigator, Dr. Amy Miracle, at (330) 672-2649; or the Kent State University Institutional Review Board, at (330) 672-2704.

If you are 18 years of age or older, understand the statements above, and freely consent to participate in the study, click on the "I Agree" button to begin the experiment.

I Agree I Do Not Agree

APPENDIX D

GLOSSARY OF TERMS

Appendix D

Glossary of Terms

Allele: One of a set of alternative forms of a gene (Whelan et al., 2008) that may occur at a given locus on a specific chromosome (Stedman’s, 2005).

Base pair: The complex of two heterocyclic nucleic acid bases, a purine (adenine or guanine) and a pyrimidine (cytosine, thymine, or uracil). DNA consists of two complementary chains of nucleotides – usually adenine (A) is paired with thymine (T) and guanine (G) with cytosine (C) (Stedman’s, 2005).

Chromosome: A self-replicating genetic structure within cells (Whelan et al., 2008).

Chromosomes, composed of double stranded DNA, are the bearers of genes (Stedman’s,

2005).

DNA: Deoxyribonucleic acid - a nucleic acid that contains genetic information

(Stedman’s, 2005).

Gene: A sequence of DNA that encodes a protein. Genes are a functional unit of heredity

(Stedman’s, 2005).

Gene expression: The detectable effect of a gene (Stedman’s, 2005). A gene is expressed when DNA is transcribed into messenger ribonucleic acid, called mRNA, which is usually then translated into a protein.

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Genome: The entire set of genetic instructions found in a cell. In humans, the genome consists of 23 pairs of chromosomes, found in the nucleus, as well as a small chromosome found in the cells' mitochondria. Each set of 23 chromosomes contains approximately 3.1 billion bases of DNA sequence. This is the complete genetic content of an organism (Collins, n. d.).

Genotype: The genetic information in an organism (Whelan et al., 2008).

Mutation: A change in DNA sequence (Whelan et al., 2008).

Nutrigenetics: The influence of genetic variation on the response to nutrients or dietary constituents (McCarthy et al., 2008).

Nutrigenomics: The way in which nutrients or dietary constituents influence gene expression (McCarthy et al., 2008).

Polymorphism: Variation in DNA sequence between individuals (Whelan et al., 2008).

A single nucleotide polymorphism (SNP) involves variation at a single base pair, and is the most common type of polymorphism (Collins, n. d.). Polymorphisms can also be much larger in size and involve long stretches of DNA; however, scientists are studying how SNPs in the human genome correlate with disease, drug response, and other phenotypes (Collins, n. d.).

APPENDIX E

FREQUENCIES OF RESPONSES TO THE KNOWLEDGE QUESTION

Table 8 Frequency Distribution of Sports Dietitians and Non-Sports Dietitians Correct, Incorrect, and Do Not Know Responses to Knowledge Questions for the “Dietitians’ Knowledge and Perceptions of Nutritional Genomics for Enhancing Athletic Performance” Questionnaire (n = 6219)

Correct Incorrect Do not know Knowledge Questions* n % n % n %

A "gene" is: 5157 82.9% 844 13.6% 218 3.5% A "chromosome" is: 5450 87.6% 609 9.8% 160 2.6% An "allele" is: 2588 41.6% 2294 36.9% 1337 21.5% "Genotype" refers to: 4349 69.9% 1420 22.8% 450 7.2% "Phenotype" is: 3277 52.7% 1622 26.1% 1320 21.2% "Single nucleotide polymorphisms 2244 36.1% 1273 20.5% 2702 43.4% (SNPs)" are:** A "mutation" is: 4810 77.3% 1271 20.4% 138 2.2% "PCR" stands for: 2961 47.6% 632 10.2% 2626 42.2% "NUTRIGENOMICS" is: 3013 48.4% 2110 33.9% 1096 17.6% "NUTRIGENETICS" 2218 35.7% 2539 40.8% 1462 23.5% is:** Which of the following is NOT part of 2621 42.1% 1727 27.8% 1871 30.1% NUTRITIONAL GENOMICS? In which condition is a genetic test regularly 4933 79.3% 533 8.6% 753 12.1% used? Which of the following defects interact with dietary fat intake to 1707 27.4% 566 9.1% 3946 63.5% influence the risk of cardiovascular disease?** What condition is NOT associated with the 967 15.5% 1050 16.9% 4202 67.6% MTHFR 677C→T defect?** * The knowledge section was scored according to the number of correct answers. Do not know answers were counted as incorrect. ** For these questions, the incorrect or do not know responses were greater than correct responses.

79

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