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
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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
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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,
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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;
18

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.
19
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 geneticallyassociated 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 subunit 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
Female
Missing data
269 (4%)
5906 (95%)
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 nonCSSD 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
Does not work with athletes
Missing data
61 (1%)
4917 (79.1%)
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
Perception
7.88
2.525
7.36
2.744
0.001
2.69
1.223
2.22
1.196
0.001
4.39
0.853
4.26
0.871
0.001
1.88
1.095
1.63
0.954
0.001
3.7
0.792
3.47
0.742
0.001
3.85
0.843
3.66
0.812
0.001
**
I am comfortable
discussing genetic
information with a client
as part of a family history
There is a need for
continuing research in
Nutritional Genomics
I am comfortable
discussing with a client
how the MTHFR 677C→T
defect may influence risk of
disease
Nutritional Genomics
research can be used to
improve athletic
performance
Understanding the genetic
nutritional needs of an
athlete provides a valuable
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
information with a client as part of a family
history.
0.247
0.253
2.
There is a need for continuing research in
Nutritional Genomics.
0.173
0.215
3.
I am comfortable discussing with a client
how the methylenetetrahydrofolate reductase
(MTHFR) 677C-->T defect may influence
risk of disease.
0.346
0.253
4.
Nutritional Genomics research can be used
to improve athletic performance.
0.161
0.155
5.
Understanding the genetic nutritional needs
of an athlete provides a valuable tool in
strategies to optimize sports performance.
0.109
0.087
6.
I am comfortable discussing with clients
how diet may interact with genes to
influence athletic performance.
0.225
0.192
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 (+/-)
High School Graduate
Bachelor’s
Masters
Doctoral
Professional
Total
Between Groups
6.50
6.95
7.60
9.47
6.58
7.44
I am comfortable discussing
genetic information with a
client as part of a family history
High School Graduate
Bachelor’s
Masters
Doctoral
Professional
Total
Between Groups
1.50
2.17
2.34
2.78
2.52
2.30
0.707
1.169
1.223
1.269
1.218
1.213
There is a need for continuing
Research in Nutritional Genomics
High School Graduate
Bachelor’s
Masters
Doctoral
Professional
Total
Between Groups
3.00
4.23
4.31
4.48
4.36
4.29
1.414
0.877
0.861
0.856
0.757
0.869
I am comfortable discussing with a
client how the methylenetetrahydrofolate
reductase (MTHFR) 677C→T
defect may influence risk of disease
High School Graduate
Bachelor’s
Masters
Doctoral
Professional
Total
Between Groups
1.50
1.55
1.70
2.29
1.70
1.67
0.707
0.886
0.988
1.260
0.992
0.983
Nutritional Genomics research
can be used to improve athletic
performance
High School Graduate
Bachelor’s
Masters
Doctoral
Professional
Total
Between Groups
3.00
3.48
3.54
3.50
3.44
3.51
1.414
0.739
0.758
0.821
0.747
0.755
Understanding the genetic nutritional
needs of an athlete provides a valuable
tool in strategies to optimize sports
performance
High School Graduate
Bachelor’s
Masters
Doctoral
Professional
Total
Between Groups
3.50
3.69
3.70
3.63
3.68
3.69
2.121
0.808
0.823
0.896
0.660
0.820
I am comfortable discussing with
clients how diet may interact with
genes to influence athletic
performance
High School Graduate
Bachelor’s
Masters
Doctoral
Professional
Total
Between Groups
3.00
1.88
2.02
2.36
2.17
1.99
1.414
0.999
1.050
1.126
1.046
1.042
Total Knowledge Score
F
P
80.637
0.001
3.536
2.627
2.655
2.689
2.899
2.716
Perception Items
23.700
0.001
9.302
0.001
48.809
0.001
2.501
0.040
0.682
0.605
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 posthoc 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, 610, 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 (+/-)
0 hours
1-5 hours
6-10 hours
10+ hours
Total
Between Groups
7.36
7.90
8.20
7.47
7.45
I am comfortable discussing
genetic information with a
client as part of a family history
0 hours
1-5 hours
6-10 hours
10+ hours
Total
Between Groups
2.22
2.68
2.83
2.63
2.30
1.195
1.225
1.189
1.227
1.212
There is a need for continuing
Research in Nutritional Genomics
0 hours
1-5 hours
6-10 hours
10+ hours
Total
Between Groups
4.26
4.37
4.48
4.46
4.28
0.873
0.878
0.666
0.667
0.870
I am comfortable discussing with a client
how the Methylenetetrahydrofolate
Reductase (MTHFR) 677C→T
defect may influence risk of
disease
0 hours
1-5 hours
6-10 hours
10+ hours
Total
Between Groups
1.63
1.87
1.97
1.81
1.67
0.954
1.084
1.168
1.070
0.981
Nutritional Genomics research
can be used to improve athletic
performance
0 hours
1-5 hours
6-10 hours
10+ hours
Total
Between Groups
3.47
3.71
3.78
3.53
3.51
0.742
0.785
0.806
0.813
0.755
Understanding the genetic nutritional needs
of an athlete provides a valuable tool in
strategies to optimize sports performance
0 hours
1-5 hours
6-10 hours
10+ hours
Total
Between Groups
3.65
3.86
3.98
3.79
3.69
0.813
0.827
0.807
0.938
0.820
I am comfortable discussing with
clients how diet may interact with
genes to influence athletic
performance
0 hours
1-5 hours
6-10 hours
10+ hours
Total
Between Groups
1.91
2.36
2.50
2.29
1.98
1.008
1.119
1.127
0.991
1.039
Total Knowledge Score
F
P
11.212
0.001
43.144
0.001
6.431
0.001
17.092
0.001
28.619
0.040
18.490
0.605
56.640
0.001
2.751
2.466
2.558
2.789
2.718
Perception Items
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 posthoc 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
49
Table 7
Results of one-way (1x5) between groups ANOVA for Athlete Level ( = mean, SD = standard deviation)
Level of Athlete
worked with
SD (+/-)
Beginner
Recreational
Well-trained
Elite
None
Total
Between Groups
7.43
7.83
8.39
7.62
7.35
7.44
I am comfortable discussing
genetic information with a
client as part of a family history
Beginner
Recreational
Well-trained
Elite
None
Total
Between Groups
2.44
2.67
3.01
2.64
2.21
2.30
1.205
1.229
1.214
1.096
1.192
1.214
There is a need for continuing
Research in Nutritional Genomics
Beginner
Recreational
Well-trained
Elite
None
Total
Between Groups
4.27
4.41
4.38
4.49
4.27
4.29
0.880
0.806
0.954
0.766
0.864
0.864
I am comfortable discussing with a client
how the methylenetetrahydrofolate
reductase (MTHFR) 677C→T defect may
influence risk of
disease
Beginner
Recreational
Well-trained
Elite
None
Total
Between Groups
1.62
1.83
2.17
1.77
1.63
1.67
0.864
1.066
1.246
0.902
0.954
0.982
Nutritional Genomics research
can be used to improve athletic
performance
Beginner
Recreational
Well-trained
Elite
None
Total
Between Groups
3.60
3.68
3.73
3.74
3.47
3.51
0.783
0.759
0.827
0.964
0.738
0.753
Understanding the genetic nutritional
needs of an athlete provides a valuable
tool in strategies to optimize sports
performance
Beginner
Recreational
Well-trained
Elite
None
Total
Between Groups
3.71
3.82
3.95
3.97
3.66
3.69
0.865
0.794
0.853
1.032
0.807
0.816
I am comfortable discussing with
clients how diet may interact with
genes to influence athletic
performance
Beginner
Recreational
Well-trained
Elite
None
Total
Between Groups
2.20
2.23
2.70
2.66
1.90
1.98
1.057
1.082
1.128
1.250
1.004
1.041
Total Knowledge Score
F
P
12.359
0.001
2.316
2.484
2.469
2.990
2.758
2.718
Perception Items
46.420
0.001
5.299
0.001
23.392
0.001
18.584
0.001
14.198
0.001
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.
51
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.
52
Knowledge of Nutritional Genomics between Dietitians
The hypothesis that there would be a difference between Sports Dietitians and NonSports 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 dietgene interactions relevant to majority, or individual specialties, of dietitians.
53
Perception of Nutritional Genomics between Dietitians
The hypothesis that there would be a difference between Sports Dietitians’ and NonSports 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 dietgene 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
61
62
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
63
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
64
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
65
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
66
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
67
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.
68
Please choose your answer based on your level of agreement or disagreement with the
statement.
Strongly
Disagree
Disagree
Neither Agree Agree Strongly
nor Disagree
Agree
I am comfortable discussing
genetic information with a
client as part of a family
history.
o
o
o
o
o
There is a need for
continuing research in
Nutritional Genomics.
o
o
o
o
o
I am comfortable discussing
with a client how the
Methylenetetrahydrofolate
Reductase (MTHFR)
677C®T defect may
influence risk of disease.
o
o
o
o
o
Nutritional Genomics
research can be used to
improve athletic
performance.
o
o
o
o
o
Understanding the genetic
nutritional needs of an
athlete provides a valuable
tool in strategies to optimize
sports performance.
o
o
o
o
o
I am comfortable discussing
with clients how diet may
interact with genes to
influence athletic
performance.
o
o
o
o
o
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}
70
71
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.
73
74
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.
76
77
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
Knowledge Questions
*
Incorrect
Do not know
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%
2244
36.1%
1273
20.5%
2702
43.4%
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%
"Single nucleotide
polymorphisms
(SNPs)" are:**
A "mutation" is:
"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
REFERENCES
REFERENCES
Adams, K. M., Lindell, K. C., Kohlmeier, M., & Zeisel, S. H. (2006). Status of nutrition
education in medical schools,. The American Journal of Clinical Nutrition, 83(4),
941S–944S.
Afman, L., & Müller, M. (2006). Nutrigenomics: From molecular nutrition to prevention
of disease. Journal of the American Dietetic Association, 106(4), 569-576. doi:
http://dx.doi.org/10.1016/j.jada.2006.01.001
American Dietetic Association. (2008). Job Descriptions: Models for the Dietetics
Profession (2nd ed.). ISBN: 978-0-88091-420-8.
Arab, L. (2004). Individualized nutritional recommendations: Do we have the
measurements needed to assess risk and make dietary recommendations? The
Proceedings of the Nutrition Society, 63(1), 167-172. doi:10.1079/PNS2003325
Baars, M. J., Henneman, L., & Ten Kate, L. P. (2005). Deficiency of knowledge of
genetics and genetic tests among general practitioners, gynecologists, and
pediatricians: A global problem. Genetics in Medicine : Official Journal of the
American College of Medical Genetics, 7(9), 605-610. doi:00125817-20051100000002
Banni, S. (2009). Tailor-made fatty acids for a personalized nutrition. European Journal
of Lipid Science and Technology, 111(7), 625-626. doi:10.1002/ejlt.200900145
81
82
Baumler, M., (2012). Nutrigenetics — Building a Platform for Dietitians to Offer
Personalized Nutrition. Today’s Dietitian, Vol. 14 (9). Retrieved from
http://www.todaysdietitian.com/newarchives/090112p48.shtml
Bendik, I., Friedel, A., Roos, F. F., Weber, P., Eggersdorfer, M., Dixon, K. M., &
Maestro, M. A. (2014). Vitamin D: A critical and essential micronutrient for human
health. Frontiers in Physiology, 5, 1-14. doi:10.3389/fphys.2014.00248
Bersch, C. (2006). Nutritional genomics: Part of the evolution of personalized
medicine. MLO: Medical Laboratory Observer, 38(7), 52-52.
Boehl, T.Emerging science raises questions: What to tell your clients about nutritional
genomics. Journal of the American Dietetic Association, 107(7), 1094-1096.
doi:10.1016/j.jada.2007.05.029
Boland, M. (2008). Innovation in the food industry: Personalised nutrition and mass
customisation. Innovation: Management, Policy & Practice, 10(1), 53-60.
Bouchard, C., & Ordovas, J. M. (2012). Fundamentals of nutrigenetics and
nutrigenomics doi:10.1016/B978-0-12-398397-8.00001-0
Bouwman, L., Te Molder, H., & Hiddink, G. (2008). Patients, evidence and genes: An
exploration of GPs' perspectives on gene-based personalized nutrition advice. Family
Practice, 25 Suppl 1, i116-i122. doi:10.1093/fampra/cmn067
83
Bray, M. S., Hagberg, J. M., Perusse, L., Rankinen, T., Roth, S. M., Wolfarth, B., &
Bouchard, C. (2009). The human gene map for performance and health-related
fitness phenotypes: The 2006-2007 update. Medicine and Science in Sports and
Exercise, 41(1), 35-73.
Burke, S., Stone, A., Bedward, J., Thomas, H., & Farndon, P. (2006). A neglected part of
the curriculum or of limited use? views on genetics training by nongenetics medical
trainees and implications for delivery. Genetics in Medicine : Official Journal of the
American College of Medical Genetics, 8(2), 109-115.
Burton, H., Sanderson, S., Dixon, M., Hallam, P., & White, F. (2007). Review of
specialist dietitian services in patients with inherited metabolic disease in the United
Kingdom. Journal of Human Nutrition and Dietetics : The Official Journal of the
British Dietetic Association, 20(2), 84-92; quiz 92-4. doi:JHN752
Burton, H., & Zimmern, R. (2005). Education in the genetics era: Genetics education for
health professionals--an essential component of genetics policy. Medical
Education, 39(3), 243-244. doi:MED2084
Byham-Gray, L. D., Gilbride, J. A., Dixon, L. B., & Stage, F. K. (2005). Evidence-based
practice: What are dietitians' perceptions, attitudes, and knowledge? Journal of the
American Dietetic Association,105(10), 1574-1581. doi:S0002-8223(05)01215-0
84
Chavez, A., & Munoz, d. C. (2003). Nutrigenomics in public health nutrition: Short-term
perspectives. European Journal of Clinical Nutrition, 57, S97-S100.
Collins, F. S. (n. d.). In Talking Glossary of Genetic Terms. National Institutes of
Health: National Human Genome Research Institute. Retrieved from
http://www.genome.gov/Glossary/index.cfm?id=90
Collins, F. S. (1997). Preparing health professionals for the genetic
revolution. Jama, 278(15), 1285-1286.
Collins, F. S., Morgan, M., & Patrinos, A. (2003). The human genome project: Lessons
from large-scale biology. Science (New York, N.Y.), 300(5617), 286-290.
Collins, J., Bertrand, B., Hayes, V., Li, S., Thomas, J., Truby, H., & Whelan, K. (2013).
The application of genetics and nutritional genomics in practice: An international
survey of knowledge, involvement and confidence among dietitians in the US,
australia and the UK. Genes & Nutrition, 8(6), 523-533. doi:10.1007/s12263-0130351-9
Costa, V., Casamassimi, A., & Ciccodicola, A. (2010). Nutritional genomics era:
Opportunities toward a genome-tailored nutritional regimen. The Journal of
Nutritional Biochemistry, 21(6), 457-467. doi:10.1016/j.jnutbio.2009.10.012
85
Cragun, D. L., Couch, S. C., Prows, C. A., Warren, N. S., & Christianson, C. A. (2005).
A success of a genetics educational intervention for nursing and dietetic students: A
model for incorporating genetics into nursing and allied health curricula. Journal of
Allied Health, 34(2), 90-96.
Darnton-Hill, I., Margetts, B., & Deckelbaum, R. (2004). Public health nutrition and
genetics: Implications for nutrition policy and promotion. The Proceedings of the
Nutrition Society, 63(1), 173-185. doi:10.1079/PNS2003330
Debusk, R. M. (2002). Genetics: the nutrition connection. Chicago, IL: American
Dietetic Association.
DeBusk, R. M., Fogarty, C. P., Ordovas, J. M., & Kornman, K. S. (2005). Nutritional
genomics in practice: Where do we begin? Journal of the American Dietetic
Association, 105(4), 589-598. doi:S0002822305000039
Ehlert, T., Simon, P., & Moser, D. A. (2013). Epigenetics in sports. Sports Medicine
(Auckland, N.Z.), 43(2), 93-110. doi:10.1007/s40279-012-0012-y
Fischetto, G., & Bermon, S. (2013). From gene engineering to gene modulation and
manipulation: Can we prevent or detect gene doping in sports? Sports Medicine
(Auckland, N.Z.), 43(10), 965-977. doi:10.1007/s40279-013-0075-4
86
Gaboon, N. E. A. (2011). Nutritional genomics and personalized diet. Egyptian Journal
of Medical Human Genetics, 12(1), 1-7. doi:10.1016/j.ejmhg.2011.02.001
Goldman, E. (2014). Genetics, nutrition & the battle over health freedom. Nutraceuticals
World, 17(2), 32-35.
Guo, S., & Sonenshein, G. (2006). Green tea polyphenols and cancer prevention. In: J.
Kaput & R. L. Rodriguez (Eds.), Nutritional genomics: discovering the path to
personal nutrition (pp. 177-194). Hoboken, NJ: John Wiley & Sons Inc.
Human Genome, S. C. (2004). Finishing the euchromatic sequence of the human
genome. Nature, 431(7011), 931-945.
International HapMap Consortium. (2003). The international HapMap
project. Nature, 426(6968), 789-796. doi:10.1038/nature02168
Isaak, C. K., & Siow, Y. L. (2013). The evolution of nutrition research. Canadian
Journal of Physiology & Pharmacology, 91(4), 257-267.
Kambouris, M., Del Buono, A., & Maffulli, N. (2014). Genomics DNA profiling in elite
professional soccer players: A pilot study. Translational Medicine @ Unisa, 9, 1822.
87
Kambouris, M., Ntalouka, F., Ziogas, G., & Maffulli, N. (2012). Predictive genomics
DNA profiling for athletic performance. Recent Patents on DNA & Gene
Sequences, 6(3), 229-239. doi:DNAG-EPUB-20120724-2
Kaput, J. (2008). Nutrigenomics research for personalized nutrition and
medicine. Current Opinion in Biotechnology, 19(2), 110-120.
doi:http://dx.doi.org/10.1016/j.copbio.2008.02.005
Kaput, J., & Rodriguez, R. L. (2004). Nutritional genomics: The next frontier in the
postgenomic era. Physiological Genomics, 16(2), 166-177.
doi:10.1152/physiolgenomics.00107.2003
King, J. (2003). Nutritional genomics. Interview by Deborah Shattuck. Journal of the
American Dietetic Association, 103(1), 16, 18.
King, R. A., Rotter, J. I. & Motulsky, A. G. (1992). The Genetic Basis of Common
Diseases (Vol. 20). Motulsky, A. G., Harper, P. S., Scriver, C. & Bobrow, M. (Eds.).
Oxford: Oxford Univ. Press.
Kohlmeier, M. (2013). Nutrigenetics : Applying the science of personal nutrition. Saint
Louis, MO, USA: Academic Press.
88
Krishnaswamy, K. (2012). Personalized nutrition: Translating nutrigenetic/nutrigenomic
research into dietary guidelines. Indian Journal of Medical Research, 135(6), 924925. 2p.
Ku, C. S., Loy, E. Y., Salim, A., Pawitan, Y., & Chia, K. S. (2010). The discovery of
human genetic variations and their use as disease markers: Past, present and
future. Journal of Human Genetics, 55(7), 403-415. doi:10.1038/jhg.2010.55
Lapham, E. V., Kozma, C., Weiss, J. O., Benkendorf, J. L., & Wilson, M. A. (2000). The
gap between practice and genetics education of health professionals: HuGEM survey
results. Genetics in Medicine : Official Journal of the American College of Medical
Genetics, 2(4), 226-231. doi:10.109700125817-200007000-00005
Leamy, L. J., Kelly, S. A., Hua, K., & Pomp, D. (2012). Exercise and diet affect
quantitative trait loci for body weight and composition traits in an advanced
intercross population of mice. Physiological Genomics, 44(23), 1141-1153.
doi:10.1152/physiolgenomics.00115.2012
Lippi, G. (2008). Genomics and sports: Building a bridge towards a rational and
personalized training framework. International Journal of Sports Medicine, 29(3),
264-265. doi:10.1055/s-2008-1038323
89
Lippi, G., Solero, G. P., & Guidi, G. (2004). Athletes genotyping: Ethical and legal
issues. International Journal of Sports Medicine, 25(2), 159; author reply 160-1.
doi:10.1055/s-2004-819956
Lovegrove, J. A., & Gitau, R. (2008). Personalized nutrition for the prevention of
cardiovascular disease: A future perspective. Journal of Human Nutrition &
Dietetics, 21(4), 306-316.
Macarthur, D. G., & North, K. N. (2005). Genes and human elite athletic
performance. Human Genetics, 116(5), 331-339.
Maughan, R. (2007). Physiology of sport. British Journal of Hospital Medicine, 68, 376379.
Maughan, R. J., & Shirreffs, S. M. (2012). Nutrition for sports performance: Issues and
opportunities. The Proceedings of the Nutrition Society, 71(1), 112-119.
doi:10.1017/S0029665111003211
McCarthy, S., Pufulete, M., & Whelan, K. (2008). Factors associated with knowledge of
genetics and nutritional genomics among dietitians. Journal of Human Nutrition &
Dietetics, 21(6), 547-554.
90
Miggiano, G. A., & De Sanctis, R. (2006). Nutritional genomics: Toward a personalized
diet. [Nutrigenomica: verso una dieta personalizzata] La Clinica
Terapeutica, 157(4), 355-361.
Minich, D. M., & Bland, J. S. (2013). Personalized lifestyle medicine: Relevance for
nutrition and lifestyle recommendations. Thescientificworldjournal, 2013, 129841129841. doi:10.1155/2013/129841
Naidoo, N., Pawitan, Y., Soong, R., Cooper, D. N., & Ku, C. (2011). Human genetics and
genomics a decade after the release of the draft sequence of the human
genome. Human Genomics, 5(6), 577-622.
National Coalition for Health Professional Education in Genetics. (2007). Core
competencies in genetics for health professionals. Retrieved from
http://www.nchpeg.org/index.php?view=article&catid=50%3Acore-competenciesfor-all-health-care-professionals-2007&id=107%3Aabout-the-core-competencies-ingenetics
Oliveira, R. S., Collares, T. F., Smith, K. R., Collares, T. V., & Seixas, F. K. (2011). The
use of genes for performance enhancement: Doping or therapy? Brazilian Journal of
Medical and Biological Research = Revista Brasileira De Pesquisas Medicas e
Biologicas / Sociedade Brasileira De Biofisica ...[Et Al.], 44(12), 1194-1201.
doi:S0100-879X2011007500145
91
Ordovas, J., & Mooser, V. (2004). Nutrigenomics and nutrigenetics. Current Opinion in
Lipidology,15(2), 101-8.
Ordovás Muñoz, J. M. (2013). Predictors of obesity: The "power" of the omics. Nutricion
Hospitalaria, 28, 63-72. doi:10.3305/nh.2013.28.sup5.6869
Patterson, R. E., Eaton, D. L., & Potter, J. D. (1999). The genetic revolution: Change and
challenge for the dietetics profession. Journal of the American Dietetic
Association, 99(11), 1412-1420. doi:S0002-8223(99)00341-7
Pitsiladis, Y., Wang, G., Wolfarth, B., Scott, R., Fuku, N., Mikami, E., . . . Lucia, A.
(2013). Genomics of elite sporting performance: What little we know and necessary
advances. British Journal of Sports Medicine, 47(9), 550-555. doi:10.1136/bjsports2013-092400
Prasad, C., Imrhan, V., & Rew, M. (2011). Introducing nutritional genomics teaching in
undergraduate dietetic curricula. Journal of Nutrigenetics and Nutrigenomics, 4(3),
165-172. doi:10.1159/000330237
Rodriguez, N. R., Di Marco, N.,M., & Langley, S. (2009). American college of sports
medicine position stand. Nutrition and athletic performance. Medicine and Science
in Sports and Exercise, 41(3), 709-731. doi:10.1249/MSS.0b013e31890eb86
92
Rosen, R., Earthman, C., Marquart, L., & Reicks, M. (2006). Continuing education needs
of registered dietitians regarding nutrigenomics. Journal of the American Dietetic
Association, 106(8), 1242-1245.
Ryan-Harshman, M., Vogel, E., Jones-Taggart, H., Green-Johnson, J., Castle, D., Austin,
Z., & Anderson, K. (2008). Nutritional genomics and dietetic professional
practice. Canadian Journal of Dietetic Practice & Research, 69(4), 177-182.
Sadee, W., & Dai, Z. (2005). Pharmacogenetics/genomics and personalized medicine.
Human Molecular Genetics, 14(2), R207-R214.
Sadeghi, K., Wessner, B., Laggner, U., Ploder, M., Tamandl, D., Friedl, J., . . . Spittler,
A. (2006). Vitamin D3 down-regulates monocyte TLR expression and triggers
hyporesponsiveness to pathogen-associated molecular patterns. European Journal of
Immunology, 36(2), 361-370. doi:10.1002/eji.200425995
Shankar, S., Kumar, D., & Srivastava, R. K. (2013). Epigenetic modifications by dietary
phytochemicals: Implications for personalized nutrition. Pharmacology &
Therapeutics, 138(1), 1-17. doi:10.1016/j.pharmthera.2012.11.002
Sheridan, C. (2011). Gene therapy finds its niche. Nature Biotechnology, 29(2), 121-128.
doi:10.1038/nbt.1769
93
Simopoulos, A. P. (2002). Genetic variation and dietary response:
Nutrigenetics/nutrigenomics. Asia Pacific Journal of Clinical Nutrition, 11, S117S128. doi:10.1046/j.1440-6047.11.s6.3.x
Sports, Cardiovascular, and Wellness Nutrition - a dietetic practice group of the Academy
of Nutrition and Dietetics. (2015). Sports dietitian job description. Retrieved from
http://www.scandpg.org/sports-dietitian-job-description/
Stedman’s Medical Dictionary for the Health Professions and Nursing: Illustrated (5th
ed.). (2005). Baltimore, MD: Lippincott Williams & Wilkins.
Stover, P. J. (2006). Influence of human genetic variation on nutritional
requirements. The American Journal of Clinical Nutrition, 83(2), 436S-442S.
doi:83/2/436S
Stover, P. J., & Caudill, M. A. (2008). Genetic and epigenetic contributions to human
nutrition and health: Managing genome-diet interactions. Journal of the American
Dietetic Association, 108(9), 1480-1487. doi:10.1016/j.jada.2008.06.430
Svetkey, L. P., Moore, T. J., Simons-Morton, D. G., Appel, L. J., Bray, G. A., Sacks, F.
M., . . . DASH collaborative research group. (2001). Angiotensinogen genotype and
blood pressure response in the dietary approaches to stop hypertension (DASH)
study. Journal of Hypertension, 19(11), 1949-1956.
94
Trayhurn, P. (2003). Nutritional genomics - "nutrigenomics". The British Journal of
Nutrition, 89(1), 1-2. doi:10.1079/BJN2002780
Truswell, A. S. (1999). What nutrition knowledge and skills do primary care physicians
need to have, and how should this be communicated? European Journal of Clinical
Nutrition, 53 Suppl 2, S67-71.
Ulloa, P., Iturra, P., Neira, R., & Araneda, C. (2011). Zebrafish as a model organism for
nutrition and growth: Towards comparative studies of nutritional genomics applied
to aquacultured fishes.Reviews in Fish Biology & Fisheries, 21(4), 649-666.
doi:10.1007/s11160-011-9203-0
U.S. Food and Drug Administration. (2013). Paving the way for personalized medicine:
FDA’s role in a new era of medical product development. Retrieved from
http://www.fda.gov/downloads/ScienceResearch/SpecialTopics/PersonalizedMedici
ne/UCM372421.pdf
Vakili, S., & Caudill, M. A. (2007). Personalized nutrition: Nutritional genomics as a
potential tool for targeted medical nutrition therapy. Nutrition Reviews, 65(7), 301315.
Vergères, G. (2013). Nutrigenomics – linking food to human metabolism. Trends in Food
Science & Technology, 31(1), 6-12. doi:10.1016/j.tifs.2013.02.002
95
Weber, W. W. (2010). The promise of epigenetics in personalized medicine. Molecular
Interventions, 10(6), 363-370. doi:10.1124/mi.10.6.5
Whelan, K., Copeland, E., Oladitan, L., Murrells, T., & Gandy, J. (2013). Development
and validation of a questionnaire to measure research involvement among registered
dietitians. Journal of the Academy of Nutrition and Dietetics, 113(4), 563-568.
doi:10.1016/j.jand.2012.08.027
Whelan, K., McCarthy, S., & Pufulete, M. (2008). Genetics and diet--gene interactions:
Involvement, confidence and knowledge of dietitians. The British Journal of
Nutrition, 99(1), 23-28. doi:S0007114507793935
Williams, R. J. (1963). Biochemical individuality; the basis for the genetotrophic
concept New York : Science Editions, 1963 (c1956).
Williams, S. F. (2008). Nutrigenomics: A new approach to personalized
nutrition. Nutritional Perspectives: Journal of the Council on Nutrition, 31(3), 9.
World Health Organization. (2002). The world health report 2002: reducing risks,
promoting healthy life. Geneva, Switzerland: World Health Organization
Wright, O. R. L. (2014). Systematic review of knowledge, confidence and education in
nutritional genomics for students and professionals in nutrition and dietetics. Journal
96
of Human Nutrition and Dietetics: The Official Journal of the British Dietetic
Association, 27(3), 298-307. doi:10.1111/jhn.12132
Zoorob, R., Parrish, M. E., O'Hara, H., & Kalliny, M. (2013). Sports nutrition needs:
Before, during, and after exercise. Primary Care, 40(2), 475-486.
doi:10.1016/j.pop.2013.02.013