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Author: Wilde, Hilary Grace Title: Assessment of risk factors for the female athlete triad in female collegiate

gymnasts The accompanying research report is submitted to the University of Wisconsin-Stout, Graduate School in partial

completion of the requirements for the

Graduate Degree/ Major: MS Food and Nutritional Sciences

Research Advisor: Laura Knudsen, MS, RD

Submission Term/Year: Spring, 2013

Number of Pages: 51

Style Manual Used: American Psychological Association, 6th edition

I understand that this research report must be officially approved by the Graduate School and that an electronic copy of the approved version will be made available through the University Library website

I attest that the research report is my original work (that any copyrightable materials have been used with the permission of the original authors), and as such, it is automatically protected by the laws, rules, and regulations of the U.S. Copyright Office.

My research advisor has approved the content and quality of this paper. STUDENT:

NAME Hilary Wilde DATE: 5-14-2013

ADVISOR:

NAME Laura Knudsen DATE: 5-14-2013

--------------------------------------------------------------------------------------------------------------------------------- This section to be completed by the Graduate School This final research report has been approved by the Graduate School.

Director, Office of Graduate Studies: DATE:

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Wilde, Hilary G. Assessment of risk factors for the female athlete triad in female collegiate

gymnasts.

Abstract

A Division III collegiate female gymnastics team (n=15) was assessed for the presence of

the following risk factors of the female athlete triad: menstrual dysfunction, disordered eating,

low energy availability, stress fractures, and low bone mineral density. The mean age of

menarche was 14.33 years. Eight gymnasts met the criteria for primary amenorrhea, and three

presented current menstrual dysfunction. Two of the gymnasts tested positive for disordered

eating, two were in a state of low energy availability (≤30 kcal/kg fat free mass), and 11 did not

meet their calcium RDA. Ten gymnasts had one risk factor, while three had two risk factors.

Menstrual dysfunction was the most prevalent risk factor, with low energy availability and

disordered eating the second most prevalent risk factors. Two gymnasts had diagnosed stress

fractures, but none of the gymnasts had low bone mineral density despite mean dietary calcium

intakes below the RDA and menstrual dysfunction, indicating that the forces imposed by

gymnastics counteract the risk factors for low bone mineral density.

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Table of Contents

.................................................................................................................................................... Page

Abstract ............................................................................................................................................2

Chapter I: Introduction ....................................................................................................................5

Statement of the Problem .....................................................................................................7

Purpose of the Study ............................................................................................................7

Definition of Terms..............................................................................................................8

Limitations of the Study.......................................................................................................9

Methodology ........................................................................................................................9

Chapter II: Literature Review ........................................................................................................11

The Female Athlete Triad ..................................................................................................11

Figure 1. The female athlete triad ......................................................................................12

Energy Availability ............................................................................................................13

Menstrual Dysfunction.......................................................................................................18

Bone Mineral Density ........................................................................................................20

Chapter III: Methodology ..............................................................................................................24

Subject Selection and Description .....................................................................................24

Instrumentation ..................................................................................................................24

Data Collection Procedures ................................................................................................25

Data Analysis .....................................................................................................................27

Limitations .........................................................................................................................27

Chapter IV: Results ........................................................................................................................28

Table 1: Summary of Subject Characteristics ...................................................................28

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Gymnast Characteristics ....................................................................................................28

Energy Availability ............................................................................................................29

Disordered Eating ..............................................................................................................29

Menstrual Dysfunction.......................................................................................................30

Bone Mineral Density ........................................................................................................30

Cumulative female athlete triad risk factors ......................................................................31

Figure 2. Number of athletes with risk factors ..................................................................31

Chapter V: Discussion ...................................................................................................................32

Limitations ........................................................................................................................32

Conclusions ........................................................................................................................33

Recommendations ..............................................................................................................36

References ......................................................................................................................................37

Appendix A: ACSM Permission to re-print Figure 1 ...................................................................42

Appendix B: Consent Form ...........................................................................................................46 Appendix C: Female Athlete Nutritional Assessment Form ..........................................................49

Appendix D: 1-Day Food Record ..................................................................................................51

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Chapter I: Introduction

Females of all ages enjoy numerous benefits from participating in sports at the

recreational level to the elite level. Athletics allow women to form friendships, a positive self-

image, and most of all, reduce their risk for lifestyle diseases such as heart disease and diabetes.

Since the passage of Title IX in 1972, the number of female collegiate student-athletes has

increased significantly from 74,239 athletes in 1981, to 191,131 athletes today (Title IX, 2010).

Sports participation and general physical activity are also linked to healthy strong bones, with

female athletes having higher bone mineral density than non-active or recreationally active

women. Higher bone mass reduces the risk of fragility fractures later in life (Nichols, Sanborn,

& Essery, 2007).

As women’s sports have become more competitive and training more rigorous, specific

health risks relating to high levels of training have become more apparent with in the last 30

years, and are now recognized as the female athlete triad. Researchers Drinkwater et. al (1984)

were some of the first researchers to study the link between bone density and amenorrhea among

runners and crew members. In 1993, researchers Yeager et al. first coined the term “female

athlete triad” as a condition of disordered eating, amenorrhea, and osteoporosis occurring

concurrently. In 1997 the first position stand on the female athlete triad was released by the

American College of Sports Medicine classifying terms and recommendations for screening,

diagnosis, prevention, and treatment of the triad (Otis, Drinkwater, Johnson, Loucks, &

Wilmore, 1997).

The most recent position stand released in 2007 includes updated definitions highlighting

new information gathered from research on the topic. Importantly, it revised its first position

stand diagram of the female athlete triad which diagramed the disorder as a triangle connecting

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disordered eating, amenorrhea, and osteoporosis. The revised diagram recognizes that the

disorder occurs on a spectrum which varies in each athlete in each diagnostic area from optimal

energy availability to low energy availability with or without an eating disorder, optimal bone

health to osteoporosis, and eumenorrhea to functional hypothalamic amenorrhea (Nattiv, Loucks,

Manore, Sanborn, Sundgot-Borgen, & Warren, 2007). This new view of the risk factors of the

female athlete triad aims to recognize those athletes at risk early in their athletic career before

clinical disorders occur (Nattiv et al., 2007).

Though any female athlete is at risk for the female athlete triad, sports that emphasize

leanness or require long intense training regimens are more likely to increase the occurrence of

risk factors. While the exact occurrence of risk factors for the triad is unknown, risk factors are

being identified early among high school athletes, with 19.7% of athletes reporting menstrual

irregularity and 63.1% reporting musculoskeletal injury of which aesthetic sports reporting the

most injuries (Thein-Nissenbaum, Rauh, Carr, Loud, & McGuine, 2012). Gymnastics is a sport

that emphasizes leanness and is known to have a higher prevalence of athletes with disordered

eating patterns. A study conducted by Kudlac et. al. (2004) found that the impact loading forces

of the sport result in the athletes having significantly higher bone densities than non-athletes.

Identifying risk factors early among gymnasts is key to preventing long term health

consequences and ensuring healthy eating and exercise habits for the young women. Since

effects on bone density due to amenorrhea and low energy availability may not be detectable for

a year (Nattiv et al., 2007), a comprehensive female athlete triad assessment is necessary to

determine current risk factors as well as measure bone density for current and future comparison

of osteoporosis risk.

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Statement of the Problem

Gymnastics is a sport known to emphasize body weight, placing the athletes at risk for

low energy availability, menstrual dysfunction, and low bone mineral density. These risk factors

for the female athlete triad have short term and long term consequences if not caught early

enough to prevent further damage. Since early detection of risk factors for the female athlete

triad is imperative, a female athlete nutrition assessment was conducted on the gymnasts at a

National Collegiate Athletic Association (NCAA) division III university. The athletes’ height,

weight, fat free mass, and bone mineral density were measured, a one day food record was

analyzed, the Eating Attitudes Test-2 taken, and several interview questions were used to gather

other health information.

Purpose of the Study

The purpose of this study was to investigate the occurrence of risk factors for the female

athlete triad among a NCAA Division III women’s gymnastics team. Specifically, the following

research questions were addressed.

1. What is the presence of risk factors for the female athlete triad among collegiate

gymnasts?

2. What is the presence of menstrual dysfunction and its correlation to bone mineral

density?

3. What is the presence of low energy availability from the athletes’ caloric intake?

4. Are the gymnasts meeting their dietary needs for calcium intake and how does their

intake correlate to their bone density?

5. What is the presence of gymnasts with disordered eating?

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6. What is the presence of stress fractures among the gymnasts and how does their prior

history relate to their bone density?

Definition of Terms

Amenorrhea. For the purposes of this study, athletes were classified with primary

amenorrhea if they reported an absence of menarche by age 15, and secondary amenorrhea if

they reported an absence of menstrual cycles for more than 90 days.

Disordered eating. Any restrictive eating behavior the athlete takes on to increase

performance and achieve a desired body image or weight. A score greater than 20 on the EAT-

26 will be defined as disordered eating.

Eumenorrhea. Normal menstruation, with cycles 21-35 days apart.

Impact loading. Describes sports such as volleyball, gymnastics, and rugby. They

involve frequent jumping movements that places force on the bones and body, which causes an

increase in bone mass.

Low energy availability. Classified as a caloric intake below that of 30 kcals per

kilogram of fat free mass.

Menstrual dysfunction. Describes any menstrual dysfunction including primary and

secondary amenorrhea, oligomenorrhea, or other non-characterizeable dysfunction.

Non-impact loading. Describes sports such as swimming, rowing, and cycling. The

sports movements do not place extra force on the body and bones.

Oligomenorrhea. Irregular menstruation with cycles longer than 35 days apart.

Osteoporosis. A disease resulting in skeletal fragility in which fractures occur with

trauma that is no greater than daily activities. It is clinically diagnosed by a z-score of less than

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or equal to -2.0 among physically active women in addition to secondary risk factors for

fractures such as undernutrition, hypoestrogenism, or prior fractures.

Osteopenia. Abnormally low bone density, and is a risk factor for developing

osteoporosis or incurring stress fractures. The clinical definition is a z-score between -1.0 to -

2.5.

Limitations of the Study

When examining the findings of this study, it is important to consider the assumptions

and limitations involved. First, it was assumed that the 1-day food record completed by the

gymnasts was accurate, and that they not only understood how to correctly complete the form

and measure portion sizes, but also were not influenced by perceptions of what they felt they

should be eating. Second, it was assumed that the gymnasts answered all questions during the

assessment interview and EAT-26 questionnaire honestly. Limitations to this study include the

accuracy of Food Processor SQL to evaluate the gymnasts’ 1-day food record, in that the food

analyzed was similar to what the athlete actually ate. Day to day variations also exist within

peoples diets, so analysis of a single day is not entirely reflective of the athletes’ diet over the

long term. Findings of this study may not apply to other female collegiate gymnasts. Finally,

there may be additional variables not accounted for in the methods which may affect the results

and conclusions of this study.

Methodology

The participants included all members of the 2012-2013 gymnastics team at a midwest

NCAA division three university. Athletes completed an assessment which included height,

weight, EAT-26 questionnaire, DXA scan, menstrual history and stress fracture interview, and

submitted a 1-day food record. The data was analyzed for the presence of the female athlete

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triad risk factors of low energy availability, disordered eating, low bone mineral density, and

menstrual dysfunction.

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Chapter II: Literature Review

This chapter investigates the health risks and components of the female athlete triad,

focusing specifically on gymnasts, diet and eating history, menstrual history, bone density, and

the factors affecting each component. This population was chosen since risk factors are

prevalent among these particular athletes due to intense training and focus on achieving a lean

body type. Conducting a risk factor assessment on gymnasts is not only beneficial to the health

of the specific athletes, but also to the coaches and trainers to know which risk factors are most

prevalent among their athletes. As each of the components of the female athlete triad are closely

inter-related, the risk factors and health consequences will be addressed within each component.

Sports participation and general physical activity are linked to healthy strong bones, as

well as decreased risk of lifestyle diseases. Studies reviewed over the past 30 years have

revealed that athletes tend to have higher bone mineral density than non-active or recreationally

active women, and thus a reduced risk of fragility fractures later in life (Nichols, Sanborn, &

Essery, 2007). As women’s sports have become more competitive and training more rigorous

since the passage of title IX in 1972, specific health risks relating to high levels of training have

become more apparent with in the last 30 years. Increased levels of training among female

athletes have given rise to three main health concerns which are now known as the “female

athlete triad”.

The Female Athlete Triad

One of the largest health concerns to athletic females is the “female athlete triad”. The

female athlete triad, as addressed by the American College of Sports Medicine (ACSM), is

defined as the “relationships among energy availability, menstrual function, and bone mineral

density that may have clinical manifestations including eating disorders, functional hypothalamic

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amenorrhea, and osteoporosis” (Nattiv et al., 2007, p. 1867). The clinical manifestations of the

triad have serious health consequences, and by the time all three of the components for diagnosis

are met, long-term possibly irreversible damage has already occurred. The ACSM classifies the

triad as a spectrum of disorders that can occur on a continuum from eumenorrheic to

amenorrheic, optimal energy availability to low energy availability with or without the presence

of an eating disorder, and optimal bone health to osteoporosis (Nattiv et al., 2007). Figure 1

shows the current depiction of the female athlete triad and is re-printed with permission by the

ACSM (see appendix A).

Figure 1. The female athlete triad.

The key to protecting the current and long-term health of a female athlete is early

recognition and treatment of the triad’s risk factors of subclinical menstrual disorders, reduced

energy availability with or without disordered eating, and low bone mineral density. The ACSM

is the leading national and international organization which compiles research on the female

athlete triad, and has released three position stands on the disorder. As such, the most recent in

2007 defines each risk factor based on extensive research. For the purposes of this study, this

position statement will be used for defining the disorders of the female athlete triad and

referenced for related information (Nattiv et al., 2007).

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It is extremely difficult to determine the exact prevalence of the female athlete triad due

to differences in diagnostic criteria prior to the most recent ACSM position statement and limited

numbers of schools and colleges reporting data. Much of the research has found that many

athletes will meet components for one or two of the risk factors, and only a very small number

meet the threshold for all three components. Beals and Hill studied the prevalence of disordered

eating, menstrual dysfunction, and low bone mineral density among collegiate athletes (n=112)

from seven different sports, and found ten athletes with two of the components and one athlete

with all three of the disorders (2006). A significant number of athletes from the study were

found to meet the criteria for one of the disorders, indicating that the individual disorders are

more prevalent (Beals & Hill, 2006). While the presence of factors varies for each sport, similar

rates were reported in elite Brazilian swimmers. Almost half of the swimmers met the criteria

for one of the components of the female athlete triad, while 15.4% met the criteria for two

components, and 1.3% of the athletes met the criteria for all three components (Schtscherbyna,

Soares, de Oliveira, & Ribeiro, 2009). A study conducted on elite endurance runners (n=44)

reported all of the triad components in 15.9% of the athletes (Pollock et al., 2010). Specifically,

women who participate in sports that emphasize a lean physique as a competitive advantage are

more likely to be at risk for developing at least one of the components of the female athlete triad

(Torsiveit & Sundgot-Borgen, 2005) . As the separate components of the female athlete triad are

heavily inter-related, it is important to discuss the factors affecting each of the components.

Energy Availability

Athletes are at an increased energy requirement to sustain their body systems

functionality in addition to a higher than average energy output. This is defined by the ACSM as

“the amount of dietary energy remaining for other body functions after exercise training” (Nattiv

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et al., 2007). If an athlete’s diet does not adequately compensate for calories burned during

exercise, the body will compensate as a means to survive, and in female athletes this can lead to

menstrual dysfunction (Nattiv et al., 2007). The concept of whether the stress of exercise or low

energy availability was the cause of amenorrhea was first studied in the 1990s.

Research regarding energy availability centers around the luteinizing hormone, which is

secreted by the pituitary gland to trigger ovulation (VanPutte, 2013). The release of lutenizing

hormone itself is regulated by gonadotropin releasing hormone in the hypothalamus of the brain,

and its secretion requires sufficient energy (Loucks, 2003). Loucks, Verdun, and Heath studied

the effect of luteinizing hormone pulsatility in exercising women by altering their energy

availability (1998). Women were placed into balanced and energy restricted groups, with the

restricted energy availability group consuming 30 kcal/kg of lean body mass per day, which

resulted in an average negative 1,400 kcal/day energy balance. Those women experienced a

24% reduction in deriving energy from carbohydrate oxidation, which led to a significant weight

loss of 1.7 kg over the four day treatment period (Loucks, Verdun, & Heath, 1998).

Consequently, the low energy availability resulted in a luteinizing hormone pulse frequency

decrease of 10%. This finding specifically notes that menstrual cycle function is linked to

energy availability, and not strictly restrictive eating behaviors (Loucks et al., 1998).

Further research was conducted to quantify the absolute caloric limit at which lutenizing

hormone pulsatility is disrupted. Two clinically controlled trials were conducted in which

participants consumed 45 kcals/kg lean body mass per day for 5 days of the early follicular

phase. Subjects were then randomized into three separate calorie restricted diets of 10, 20, or 30

kcal/kg lean body mass per day and repeated the trial two months later. Lutenizing hormone

pulsatility was not affected at 30 kcal/kg lean body mass per day, but it was disrupted

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significantly at lower levels of caloric restriction, indicating that the threshold for minimum

energy availability to retain normal reproductive function occurs between 20 and 30 kcal/kg lean

body mass per day (Loucks & Thuma, 2003). A female athlete triad investigation conducted in

young female distance runners reported no difference in total caloric intake between

eumenorrheic and oligo/amenorrheic athletes, but a significantly decreased daily fat intake

(-3.4% of total calories). Though, oligomenorrheic and amenorrheic runners ran significantly

more miles per week indicating the menstrual dysfunction could be explained by an energy

imbalance (Cobb et al., 2003).

Energy availability is also decreased if the athlete has disordered eating or a clinical

eating disorder. The ACSM defines disordered eating as “various abnormal eating behaviors,

including restrictive eating, fasting, frequently skipped meals, diet pills, laxatives, diuretics,

enemas, overeating, binge-eating, and then purging” (Nattiv et al., 2007). Knowing the

relationship of disordered eating in athletes on energy availability is difficult due to the limited

data availability. Beals and Hills first studied the nutritional status of female athletes with sub-

clinical eating disorders participating in endurance and aesthetic sports (1998). Athletes with

sub-clinical eating disorders reported an average caloric intake significantly lower (1,989

kcal/day) than healthy controls (2,300 kcal/day), with no difference in mean energy expenditure,

and thus were in a state of negative energy balance (Beals & Manore, 1998). Looking

specifically at the macronutrient intake levels, the athletes with sub-clinical eating disorders

consumed significantly less protein and fat than the healthy controls, with some not even

meeting the needs for high activity (Beals & Manore, 1998). While mean micronutrient status

for both groups was with in normal ranges; fortified foods and dietary supplements were

consumed at similar rates, indicating that maintenance of micronutrient levels is dependent upon

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their intake (Beals & Manore, 1998). The athletes’ height, weight, and BMI were measured to

assess the relationship between disordered eating, low energy availability, and menstrual

dysfunction. A one-day food record was chosen for this study as an efficient tool to determine

total caloric intake and dietary calcium. This method was chosen over the more accurate three

day record to increase participation and efficiency. Low energy availability was determined as a

caloric intake lower than that of 30 kcals/kg of fat free mass as defined by the ACSM (Nattiv et

al., 2007). It is expected though, that the gymnasts will under report their caloric intake given

the results of a previous study finding that 61% of elite gymnastic participants underreported

their energy intake, which significantly impacted their micronutrients status (Jonnalagadda,

Benardot, & Dill, 2000).

Higher rates of disordered eating among athletes in sports that focus on a lean physique

have been widely reported, but all female athletes remain at risk. Almost one third (32%) of the

Norwegian junior and senior level female football, handball, and endurance athletes met the

DSM-IV criteria for clinical eating disorders, with higher rates reported among the handball and

endurance athletes (Sundgot-Borgen & Torstveit, 2007). Recently, a study conducted on NCAA

Division I female collegiate gymnasts and swimmers reported that over 30% of the athletes had

some degree of disordered eating. Specifically, levels of sub-clinical and eating disordered were

28.9% and 6.1% among gymnasts respectively (Anderson & Petrie, 2012). Among the runners

studied by Cobb et. al., those runners with oligomenorrhea or amenorrhea scored much higher on

the Eating Disorder Inventory screening tool for sub-clinical eating disorders (2003). Using a

different disordered eating screening tool, Beals and Hill (2006), reported that 20% of collegiate

athletes from seven different sports had disordered eating behaviors.

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Looking specifically at sports that emphasize leanness or ascetics, a study on Brazilian

elite adolescent swimmers ages 11-19 used three different screening tools to test for the presence

of disordered eating: the Eating Attitudes Test, Bulimic Investigatory Test Edinburgh, and Body

Shape Questionnaire. Of the 78 athletes tested, 44.9% tested positive for at least one of the tests

(Schtscherbyna et al., 2009). A dietary analysis was not conducted though, so it is unknown if

the swimmers that reported a presence of disordered eating were also in a state of low energy

availability. Other researchers have reported the presence of disordered eating in conjunction

with other components of the female athlete triad. Beals and Manore conducted a large female

athlete triad study across seven different universities looking at the relationship between

disordered eating, menstrual dysfunction, and musculoskeletal injuries (2002). Significantly

more athletes in aesthetic sports (cheerleading, diving, gymnastics) scored above the cut-off

criteria for disordered eating on the EAT-26 assessment. Additionally, all athletes who reported

at risk for disordered eating were significantly correlated with menstrual dysfunction and bone

injuries (Beals & Manore, 2002).

These findings are similar to a study conducted among high school athletes in seven

different sports using the Eating Disorder Examination questionnaire to assess the athletes’

global score in addition to dietary restraint, weight, shape, and eating concern subscales (Rauh,

Nichols, & Barrack, 2010). Athletes with an elevated shape concern score were at a 4.2 fold

increase in musculoskeletal injury risk, while those with an elevated dietary restraint or global

score were at a 7 fold risk (Rauh et al., 2010). Among the female collegiate population, the

presence of disordered eating was studied in athlete and non-athlete controls. While non-athletes

reported a non-significant higher rate of risk for an eating disorder than the collegiate athletes,

25% of female lean-sport athletes (distance running, swimming, gymnastics, dance, and diving)

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were reported at greater risk for an eating disorder (Reinking & Alexander, 2005). Eating

disorder symptoms were studied in former collegiate gymnasts to determine the effects of

retirement on body composition. Retired gymnasts reported significantly lower eating disorder

symptoms, lower body-dissatisfactions scores, and were less pre-occupied by their weight than

during college gymnastics (O'Connor & Lewis, 1996). This finding specifically links disordered

eating behaviors with the sport of gymnastics.

Menstrual Dysfunction

The female menstrual cycle is generally described using three terms: eumenorrhea,

oligomenorrhea, and amenorrhea. While the definitions of each of these terms are varied, the

ACSM defined the terms in their 2007 position statement. Eumenorrhea describes a healthy

cycle occurring every 28 ±7 days. Oligomenorrhea describes a cycle occurring every 36 days or

greater. Amenorrhea is broken into two categories, primary and secondary. Primary amenorrhea

is a delay in the age of menarche, which was reduced from age 16 to age 15 in 2004 (Nattiv et

al., 2007). Secondary amenorrhea describes any time period following menarche in which there

is an absence of a menstrual cycle in a 90 day period (Nattiv et al., 2007).

The female menstrual cycle is directly linked with bone mineral density. The link

between amenorrhea and decreased bone mineral density was first reported in 1984. Drinkwater

et. al. compared the bone mineral status of 14 athletic amenorrheic women to eumenorrhic

controls, and reported that the amenorrheic group had a significantly lower (-0.18 g/cm2) lumbar

bone mineral density (1984). More recently, a cross-sectional analysis of collegiate white

women ages 19-26 reported that for each year menarche was delayed past age 12.6 years, bone

density was lower by -0.023 g/cm2 in the spine and -0.0129 g/cm2 in the femoral neck (Galuska

& Sowers, 1999). Additionally, higher bone density in the lumbar spine was significantly related

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to a higher number of lifetime menstrual cycles (Galuska & Sowers, 1999). These findings

indicate that bone mineral density is linked to cumulated estrogen exposure during adolescents.

Though among Danish gymnasts, bone mineral density was not related to menstrual status, and

instead it was proposed that the forces placed on the athletes bones during gymnastic exercises

induces osteogenesis (Helge & Kanstrup, 2002). Thus, it appears that menstrual dysfunction in

different sports impacts the female body differently, increasing the need for sport specific

research among all components of the female athlete triad.

As previously discussed, the female menstrual cycle is directly related to energy

availability (Loucks et al., 1998), but it was not recognized as early as the bone mineral density

link. The dietary intake and percent body fat of the athletes studied initially by Drinkwater et al.

were not significantly different from the eumenorrhic controls, but the amenorrhic athletes ran

16.9 more miles each week (1984). Though the finding was not initially reported as low energy

availability or negative caloric imbalance, research findings since confirm the link between

energy availability and menstrual dysfunction. Menstrual dysfunction was recently linked to an

increase in musculoskeletal injuries among high school athletes. A prevalence of menstrual

irregularity of 19.7% was reported from a cross-sectional sample (n=249) of female athletes from

three different high schools and 33 different sports (Thein-Nissenbaum et al., 2012). Though the

relationship between musculoskeletal injury and menstrual irregularity was not statistically

significant, athletes reporting menstrual irregularity were three times more likely to incur a

musculoskeletal injury resulting in seven or more missed days from the sport (Thein-Nissenbaum

et al., 2012). Considering the health and wellness of the female athlete, it would be prudent to

detect and correct menstrual dysfunction before an injury occurs.

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Bone Mineral Density Low bone mineral density places the female at risk for developing osteoporosis, which is

the third component of the female athlete triad. While osteoporosis is commonly diagnosed in

post-menopausal women due to an accelerated bone loss, it can occur prior to menopause due to

not accumulating enough bone mineral density during adolescents and young adult-hood (Nattiv

et al., 2007). Understanding and monitoring the risk factors that lead to low bone mineral

density is key to preventing stress fractures or osteoporosis later in life.

Weight bearing exercise and dietary calcium intake contribute to building bone density,

while a multitude of other factors lead to low bone mineral density. The term “low bone mineral

density” is defined by the ACSM as “a history of nutritional deficiencies, hypoestrogenism,

stress fractures, and/or secondary clinical risk factors for fracture together with a bone mineral

density z-score between -1.0 and -2.0” (Nattiv et al., 2007). The relationship between bone

mineral density and the menstrual cycle of athletes was initially studied in 1984 by Drinkwater

et. al. The study compared anthropometric data, training hours, and bone density between

amenorrheic and eumenorrheic runners and crew members. A significantly lower lumbar

vertebrae bone mineral density was reported among amenorrheic athletes (Drinkwater, Nilson, &

Chesnut, 1984).

Athletes participating in different sports are subject to different bone loading modalities,

in that gravitational forces contribute to bone mass differently. Regarding bone density, it is

important to understand how the type of sport affects bone density. The sport of swimming

subjects the athlete to the buoyancy force, and thus decreases the bone loading forces. A study

conducted on adolescent swimmers reported a mean of 1.070±0.81 g/cm2 total body bone

density, with 17.8% reporting low bone mineral density according to age (Schtscherbyna et al.,

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2009). A large study of collegiate athletes reported that lean build sports (diving, cross-country,

swimming, and track sprinters) had significantly lower spinal bone mineral density when

compared to non-lean build sports (field hockey, softball, tennis, and track and field events)

(Beals & Hill, 2006).

As previously discussed there is a direct relationship between the female athletes’

menstrual cycle and bone density. A comparative study of runners with normal eating behaviors

reported that runners with menstrual dysfunction had significantly lower (-5%) bone mineral

density than eumenorrheic runners (Tomten, Falch, Birkeland, Hemmersbach, & Hostmark,

1998). However, a longitudinal cross-sectional observational study conducted on elite endurance

runners reported no significant relationship between eumenorrheic status and normal bone

mineral density, but instead a negative correlation between increased weekly training hours and

decreased lumbar bone density (Pollock et al., 2010). This finding eludes to the relationship

between bone density and low energy availability.

The bone density of gymnasts has been well studied comparing the high impact bone

loading potential of gymnastics training with the sports stigma for low body weight. An initial

bone mineral density study comparing different body regions and different sports, revealed that

gymnasts lumbar spine, femoral neck, ward’s triangle, right arm, and pelvis was similar to that of

volleyball players site density, and both were significantly greater than swimmers and controls.

Gymnasts total body, left arm, right and left legs were significantly greater than swimmers and

controls (Fehling, Alekel, Clasey, Rector, & Stillman, 1995). Though this study did not include

other measures of risk factors of the female athlete triad, the findings indicate the high level of

active bone loading related to gymnastics. Another study comparing eumenorrheic athletes of

weight bearing sports versus swimming similarly reported that gymnasts had a significantly

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higher total normalized body bone mineral density than swimmers (Taaffe et al., 1995). When

controlling for amenorrhea and oligomenorrhea in a study comparing bone density of gymnasts

and runners, the osteogenic effects of gymnastics appeared to counteract bone resorption from

oligomenorrhea and amenorrheic status (Robinson et al., 1995). Gymnasts total body bone

mineral density was significantly higher than runners, and their femoral neck bone mineral

density was significantly higher than runners and controls (Robinson et al., 1995). These

findings are similar to those of (Kirchner, Lewis, O’Connor 1995) who also found that despite

gymnasts not meeting their RDA for calcium and total calories, and reporting an increased

prevalence of menstrual irregularities, their whole body bone density was greater than

controls(Kirchner, Lewis, & O'Connor, 1995).

A study of just elite gymnasts reported that bone mineral density was correlated to

maximal muscle strength and serum progesterone indicating that sex hormone concentrations

influence osteogenesis in gymnasts with menstrual disturbances (Helge & Kanstrup, 2002).

This important finding notes that menstrual status alone in gymnasts is an inadequate

measurement of sex hormone concentrations and that the exact estrogen and progesterone

concentrations are needed to determine a hormone-bone interaction (Helge & Kanstrup, 2002).

With gymnasts reporting significantly higher bone densities than that of runners and controls, it

is important to note how their bone density changes with retirement of the sport. A study

conducted on collegiate varsity gymnasts compared their bone mineral densities during their

final competitive season, one year after retirement, and an average of four years later to the bone

density of controls. At the initial one year follow up, gymnasts had significantly higher femoral

neck, ward’s triangle, greater trochanter, and total body bone mineral density (Kudlac, Nichols,

Sanborn, & DiMarco, 2004). Bone densities for gymnasts at four years of retirement remained

23

significantly greater than controls, but their bone density did decline at a slower rate indicating

that their high bone densities may help prevent osteoporosis later in life (Kudlac et al., 2004).

Dietary calcium intake and oral contraceptive use are other factors contributing to bone

mineral density. A cross-sectional, population based study using data from the Canadian

Multicentre Osteoporosis Study aimed to determine the relationship between oral contraceptives

and bone mineral density. Average bone mineral densities for oral contraceptive users were

0.02-0.04 g/cm2 lower than non-users, and significantly lower at the lower spine and trochanter.

These findings are clinically significant in that over time the differences could lead to an

increased fracture risk of 20-30% among oral contraceptive users (Prior et al., 2001). Another

similar study conducted with a younger age group (18-25) also reported that oral contraceptive

users had significantly lower bone mineral density, with a mean difference of 1.8% between the

two groups (Almstedt Shoepe & Snow, 2005). These findings suggest that adolescent to young

adult use of oral contraceptives may alter bone metabolism and result in a lower peak bone mass.

A one year intervention study was conducted in young adults using oral contraceptives with a

dietary calcium intake less than 800mg/day. Participants were divided into control, medium

calcium intake (1000-1100mg/day), and high calcium intake (12000-1300 mg/day). The

increased dietary calcium intake through dairy product consumption levels of at least 1000

mg/day prevented bone loss in the total hip and spine bone density, indicating its necessity

among oral contraceptive using young women (Teegarden et al., 2005). Additionally, since

athletes require more energy to balance energy expended during exercise, their needs for calcium

and other nutrients may be higher (Nattiv et al., 2007). The current calcium requirements for

females ages 14-18 are 1300 mg/day and ages 19-30 years require 1000 mg/day (Food and

Nutrition Board, 2010).

24

Chapter III: Methodology

The purpose of this study was to investigate a Division III women’s gymnastics team for

risk factors of the female athlete triad. Included in this section are descriptions of the subject

selection process, the sample, and instruments used. The data collection procedures, data

analysis, and the limitations of the study are also addressed.

Subject Selection and Description

Subjects were selected from a Midwest National Collegiate Athletic Association (NCAA)

Division III university women’s gymnastics team. Athletes were recruited during a team

meeting held in the spring of 2013 to explain the study, benefits of participation, and ask for their

consent to participate. All athletes on the official gymnastics roster were asked to participate,

and those not present at the team meeting were provided an explanation of the study and asked to

participate the next time they were available. Exclusionary criteria for this study included

pregnancy or possible pregnancy. Participation in this study was entirely voluntary and subjects

who chose to participate signed a consent form (see Appendix B). A total of 15 gymnasts ages

18-23 participated in the study.

Instrumentation

A nutrition assessment form (see Appendix C) was developed by the researcher that

included all of the areas of interest addressed by this study. The complete nutrition assessment

was directed at identifying risk factors for the female athlete triad among collegiate gymnasts.

The assessment form included areas to record demographic information (name, age, gender, and

age), height, weight, body mass index (BMI), menstrual cycle information, medications

(including supplements and oral contraceptive use), stress fracture history, bone density

classification including z-score, and risk category for an eating disorder.

25

A one-day food record form (see Appendix D) was used to assess the subject’s diet for

average caloric intake and calcium intake. The one-day food record included lines for the

subject’s name, date, and day of the week the food record was completed. Directions were

included at the top of the sheet instructing the subjects how to record the type and amount of

foods and fluids consumed.

The Eating Attitudes Test (EAT-26) was used to identify risk factors of an eating disorder

among the athletes. The instrument included 26 questions, requiring the athletes to respond on a

6 point scale from “always to never.” Responses were scored on a scale of 0-3 points per

question. A score of 3 points was assigned for the most symptomatic response, 2 points for the

adjacent response, 1 point for the next response, and 0 point for the farthest three responses in

the asymptomatic direction. Those scoring a 20 or higher were referred to the campus

counseling center for further evaluation, as well as provided contact information for the

university’s sports dietitian.

Height, weight, and BMI were measured using a Tanita body composition analyzer

(model-TBF-215). Height was measured to the nearest 0.5 inch and weight to the nearest 0.1

pound. BMI was then calculated by the Tanita body composition analyzer. Bone mineral

density (g/cm2) and z-scores were measured by dual-energy x-ray absorptiometry (DXA) (Lunar

DPXIQ, Lunar-GE Corp., Madison, WI). A quality assurance test was performed each testing

day prior to assessment according to manufacturer specification.

Data Collection Procedures

A female athlete nutrition assessment aimed at identifying risk factors for the female

athlete triad was conducted on each subject during the spring of 2013. Upon consenting to

26

participate, the athlete received her 1-day food record to be completed on one day during the

training week that most reflected her average eating habits.

Individual athlete assessment sessions were scheduled following the completion of the

gymnastics season. Upon arrival to the Nutrition Assessment Lab, a personal interview was

conducted and responses were recorded on the nutrition assessment form. First, the subject was

asked her name and age. Next, the subject was asked her age of menarche, number of cycles in

the past year, average length of cycle, how her cycle was impacted during the gymnastics season,

and any other descriptive information. The subject was then asked if she was taking any

medications, including dietary supplements and contraceptives, and if so, what were they and

how often were they taken. The subject was next asked about her stress fracture history,

including number in the past year, previous season, and locations. The subject then completed

the EAT-26 questionnaire.

Upon completion of the data collection interview, the physical assessment began. The

athlete’s height and weight were measured using the Tanita body composition analyzer (model

TBF-215). One pound of clothing was entered to account for the minimal clothing worn by the

subject.

The final measurement was total bone mass density, using a Lunar DPXIQ dual-energy

x-ray absorptiometry (DXA) scan. Each morning at least forty minutes before the scan occurred,

the machine was turned on to warm up, and a quality assurance test was completed to ensure the

machine was calibrated within normal limits. The subjects were then instructed to lie on the

scanning table mat, and their spine and pelvis were aligned with the lines on the mat. Their

placement was checked that their body did not fall outside of the measurement zone. The

subjects were instructed to lie still as the scanning arm passed over their body. All data collected

27

during the female athlete nutrition assessment was kept in a locked area, accessible only by the

researcher and the researcher’s advisor.

Data Analysis

Statistical analyses were conducted using the computer software program, Microsoft

Office Excel 2010, to gather descriptive statistics including mean, median, mode, and standard

deviation for interval data. Food Processor SQL version 9.9.0 computer software program was

used to analyze total caloric and calcium intake for the one day food records.

Limitations

A major limitation of this study was the large amount of self-reported data. The subjects

were asked to report their one day food intakes of which they may have over or underestimated

the amount of food and added or left off food. The software, Food Processor SQL, does not

include all foods, and it is possible that the food item used for analysis did not match the food the

athlete ate. Conducting the athlete interview required honest responses to health questions, and

the athlete may not have been entirely truthful with their responses. The athletes may have also

responded to the EAT-26 questionnaire in a way to mask their true feelings, if they were trying

to hide an eating disorder. This limitation, however, is consistent with other eating disorder

questionnaires. A second limitation to this study was the small sample size (n=15) and that only

one gymnastics team was assessed. As such, the results of this study are only applicable to

Division III gymnasts in the midwest, and are not generalizable across other sports. It was

assumed that the Tanita body composition analyzed (model TBF-215) was properly calibrated,

and accurately measured height and weight. Finally, this study assumed that the components of

the nutrition assessment were valid and reliable for assessing risk factors for the female athlete

triad.

28

Chapter IV: Results

The purpose of this study was to investigate a Division III women’s gymnastics team for

risk factors of the female athlete triad. This chapter discusses the outcomes of the female athlete

assessments conducted looking specifically at the prevalence of risk factors for the female athlete

triad. The risk factors assessed include height, weight, BMI, age, years participated in the sport,

caloric intake, bone density, percent body fat, menstrual cycle, calcium intake, oral contraceptive

and supplement use, eating disorder risk, and history of stress fractures. Table 1 summarizes the

descriptive statistics.

Table 1

Summary of Subject Characteristics

Characteristic (n=15) Mean Median Standard deviation

Age (years) 20 20.00 1.60

Height (inches) 63.27 64.00 2.50

Weight (pounds) 131.02 132.4 13.97

Body mass index (BMI) 22.59 24 3.07

Fat Free Mass (kg) 44.91 44.65 2.83

Percent Body Fat 24.62 25.3 6.15

Number of years as a gymnast 16 17 3.09

Gymnast Characteristics

Of the 19 athletes on the official Division III women’s gymnastics roster at the university

who were asked to participate, 15 consented and completed the assessment. The participants’

ages ranged from 18 to 23 years (M=20.00 years, SD= 1.60), and had been gymnasts for an

29

average of 16 years (SD=3.09). The athletes average height was 63.27 inches (SD=2.50) and

their average weight was 131.02 pounds (SD=13.97). The average BMI was 22.59 (SD=3.07)

which was with in the healthy range of 18.9-25.9. The gymnasts’ average fat free mass was

44.91 kilograms (SD=2.83), which was used to determine the gymnasts’ minimum caloric need.

Energy Availability

The average caloric intake was 1831 kcals (SD=615). Using the gymnasts measured fat

free mass from the DXA scan, minimum caloric need was calculated using 30 kcals/kg fat free

mass, which is the minimum threshold recommended by the ACSM (Nattiv et al., 2007). The

average minimum caloric need was 1337 kcals (SD=89). Two gymnasts were found to be in

negative caloric imbalance, with four gymnasts consuming less than 300 kcals above their

minimum required intake. The gymnasts daily dietary calcium intake ranged 521 mg to 1470

mg, with an average of 780 milligrams (SD=316). Only one of the gymnasts reported taking a

calcium supplement regularly, but the calcium from the supplement was not included in the

dietary analysis. The recommended daily dietary intake of calcium for those aged 14-18 is 1300

mg, and 1000 mg for those aged 19-30 (Food and Nutrition Board, Institute of Medicine, 2010).

Only four athletes met the daily calcium RDA.

Disordered Eating

The Eating Attitudes Test-26 was used in many previous research studies regarding the

female athlete triad, and is the most widely used assessment tool to measure symptoms of

disordered eating. While it is not a diagnostic tool, previous studies have shown it to be an

efficient screening tool, with those scoring a 20 or higher referred to a physician for a formal

diagnostic interview (Beals, 2004). For this reason, the Eating Attitudes Test-26 is an

appropriate choice to identify disordered eating among study participants. Two gymnasts

30

reached the cut off score for the Eating Attitudes Test-26, indicating they displayed risk factors

for an eating disorder. One of the gymnasts testing positive for the test stated she had previously

been diagnosed with an eating disorder.

Menstrual Dysfunction

The gymnasts age of menarche ranged from age 11 to age 17, with the mean age of 14.33

years (SD=1.83). Eight, 53.33 percent, of the subjects began menstruating at age 15 or later, the

age criteria for primary amenorrhea. Gymnasts were asked if they were on an oral contraceptive

to note if their cycle was medically regulated. Seven of the gymnasts were on hormonal

contraceptives, leaving their natural cycles unable to be classified. Of the eight gymnasts whose

cycles were not hormonally regulated, five had menstrual dysfunction. Three of the gymnasts

met the oligomenorrhea classification, and one was classified as amenorrheic according to the

American College of Sports Medicine definitions (Nattiv et al., 2007). The fifth gymnast’s cycle

was unable to be classified as oligomenorrheic or amenorrheic, because she stated that her period

has occasionally lasted for over two months straight. Of the gymnasts with menstrual

dysfunction, one stated she occasionally misses cycles during the off-season, despite a decrease

in training intensity, while another reported she just started using hormonal regulation since she

had only had one cycle in the past year.

Bone Mineral Density

The gymnasts total body bone densities ranged from 1.148 to 1.72 g/cm2, with a mean

density of 1.27 g/cm2 (SD=0.13). Bone densities were analyzed using z-scores, which

compared the measured bone mineral density to age, race, and sex-matched controls. Z-scores

were chosen over t-scores because the ACSM quantifies low BMD in the female athlete triad

using z-scores (Nattiv et al., 2007). Their z-scores ranged from 0.35 to 2.64, with an average of

31

1.60 (SD=0.63). None of the gymnasts’ z-scores were below -1.0, the definition of low bone

mineral density. Gymnasts were asked if they had a history of stress fractures to assess the

relationship between bone density, menstrual dysfunction, and stress fractures. Two of the

gymnasts reported a history of previously diagnosed stress fractures. One gymnast reported hers

occurred in the foot during her final year of high school. The other gymnast reported she had

one stress fracture in the previous year, and two stress fractures two years ago.

Figure 2. Number of gymnasts with risk factors.

Cumulative Female Athlete Triad Risk Factors

The percentages of gymnasts with risk factors for the female athlete triad are shown in

Figure 1. Ten of the fifteen participants, 66.67 percent, had at least one risk factor, while three

gymnasts had two risk factors. The most prevalent risk factor was menstrual dysfunction,

followed by low energy availability or disordered eating. None of the gymnasts were at risk for

low bone mineral density based on their z-scores greater than -1.0.

0123456789

101112131415

Disorderedeating

Low energyavailability

Menstrualdysfunction

PrimaryAmenorrhea

Stress fractures Low bonemineral density

# of

ath

lete

s

Risk Factors

32

Chapter V: Discussion

This study aimed to evaluate a Division III university women’s gymnastics team for risk

factors of the female athlete triad. A female athlete nutrition assessment was conducted

including height, weight, total body bone density, disordered eating risk questionnaire, and an

analysis of a 1-day food record. Gymnasts were additionally asked questions to classify their

menstrual cycle, stress fracture history, and oral contraceptive use. This chapter states the

limitations, analyzes the results based on findings of previous research, draws conclusions, and

makes recommendations for future studies.

Limitations

A major limitation of this study was the small sample size (N=15), which did not include

four members of the complete roster. Thus the proportion of female athlete triad risk factors

found may not accurately be used to predict their prevalence among the whole team. Another

limitation of this study was that only the women’s gymnastics team was asked to participate, thus

the results are not generalizable across other sports or populations. A second limitation was the

self-reported 1-day food record, leaving room for the participant to overestimate or

underestimate the foods eaten. The 1-day food record limits the nutrition assessment, in that it

does not reflect the athletes general average diet over the course of her season. During the

computerized nutrition assessment, it was possible that the foods selected did not represent the

actual food eaten. It was also assumed that the gymnasts honestly completed the EAT-26

questionnaire, and provided honest responses to interview questions. Finally, it was assumed

that the assessments used were both valid and reliable methods of assessing risk factors for the

female athlete triad.

33

Conclusions

This study looked at a combination of risk factors for the female athlete triad. The first

risk factors assessed were energy availability and disordered eating. The team’s average caloric

intake was 1831 kcals with a positive energy balance of 493 kcals above the minimum caloric

intake threshold of 30 kcals/kg lean body mass per day. The average caloric intake is greater

than that reported among Division I gymnasts of 1381 (SD=109) (Kirchner et al., 1995). Two of

the gymnasts were found to be in a state of low energy availability, while four others were within

300 kcals of consuming their minimum require caloric intake, indicating low energy availability

is a prevalent risk factor for the teams’ gymnasts. Though, it has been reported that gymnasts

with higher percent body fat and BMI tend to underreport caloric intake impacting the accuracy

of a micro and macronutrient diet analysis (Jonnalagadda et al., 2000).

The Eating Attitudes Test-26 questionnaire categorized two gymnasts, 13%, at risk for

eating disorders, which is similar to the 15.2% reported from a survey of 425 collegiate athletes

from 7 different universities also using the EAT-26 questionnaire (Beals & Manore, 2002). A

survey of Division I gymnasts utilizing the Questionnaire for Eating Disorder Diagnosis reported

28.9% of gymnasts had subclinical eating disorder symptoms, which is almost double the finding

of this study (Anderson & Petrie, 2012). Given though that not all gymnasts on the roster

participated in this study, the disordered eating risk rate could potentially be much higher.

Based on the age of menarche, half of the team experienced primary amenorrhea, which

was expected, given that previous studies reported higher ages of menarche among gymnasts.

Fehling et. al (1995) reported that gymnasts age of menarche was 15.7 (SD=1.4) years, Taffe et.

al reported 15.5 (SD=1.5) years among gymnasts (1995), and Robinson et al. reported 16.2

(SD=1.7) years (1995) as the average age of menarche. Given that primary amenorrhea is

34

prevalent among the sport, athletes should be educated about the necessity of the female

menstrual cycle and their predisposition to menstrual dysfunction.

The presence of menstrual dysfunction was assessed by excluding those gymnasts taking

oral contraceptives. Five participants out of the eight athletes that were not on oral

contraceptives, 62.5%, were experiencing menstrual dysfunction. The prevalence of amenorrhea

was 12%, which was lower than previously reported of gymnasts at 28%, but the prevalence of

oligomenorrhea, 37.5%, was higher than that reported at 19% by Robinson et. al.(1995). As

previously reported, athletes at risk for eating disorders who reported menstrual irregularity

experienced significantly more bone injuries (Beals & Manore, 2002). One of the five gymnasts

with menstrual dysfunction experienced a stress fracture within the past year, but was not at risk

for an eating disorder. It is worth noting that this athlete was currently amenorrheic, while the

other athletes with menstrual dysfunction were oligomenorrheic, showing the relationship

between amenorrhea and stress fractures.

The teams’ mean calcium intake was 780 mg, which is lower than recommended by the

Food and Nutrition Board (2011). The mean calcium intake level found in this study is lower

than the 1041 mg for gymnasts studied by Robinson et. al. (1995), but higher than Division I

gymnasts studied by Krichner, Lewis, and O’Connor (1995) who currently consumed 683 mg of

calcium. Only four of the gymnasts met their RDA for calcium from their dietary intake, with

one reporting taking a regular calcium supplement. Knowing menstrual dysfunction is prevalent

on the team, and that their average calcium intake is 280-520 mg below their daily need, it is

important to note that none of the gymnasts had bone mineral density z-scores below -1.0, the

threshold for low bone mineral density. The gymnasts mean bone density, 1.27 g/cm2, was

greater than previous studies on gymnasts, by Robinson et. al (1995) and Krichner, Lewis, and

35

O’Connor (1995) who reported 1.10 g/cm2 and 1.151 g/cm2 respectively. This finding indicates

that the forces imposed on the bones during gymnastic exercise are great enough to counteract

low dietary calcium intake levels and menstrual dysfunction, a similar conclusion drawn by

Robinson et al. (1995).

While none of the gymnasts displayed all three risk factors for the female athlete triad,

individual risk factors were prevalent, with 10 of 15 gymnasts meeting the requirements for at

least one risk factor. Disordered eating and/or low energy availability was reported in two of the

15 gymnasts, and low bone mineral density was reported in none of the gymnasts. The

prevalence of individual risk factors for the female athlete triad was expected, as Beals and Hill

(2006) reported that individual risk factors among collegiate athletes were more common than

combined factors. Lean build sports were found to be significantly more at risk for menstrual

dysfunction, which was very prevalent in the population studied (Beals & Hill, 2006). Also, the

finding of higher prevalence of disordered eating/low energy availability and menstrual

dysfunction with a low prevalence of low bone mineral density as individual risk factors was

similar to that of Beals and Hill (2006).

Based on the results of the female athlete nutrition assessment conducted on a Division

III women’s gymnastics team, risk factors for the female athlete triad are common, with over

65% of the team presenting at least one risk factor. Menstrual dysfunction was the most

common risk factor, with low energy availability and disordered eating the second most common

risk factors. None of thegymnasts had low bone mineral density despite mean dietary calcium

intakes below the RDA and menstrual dysfunction, indicating that the forces imposed by

gymnastics counteract the risk factors for low bone mineral density.

36

In conclusion, based on the prevalence of multiple female athlete triad risk factors,

athlete education and monitoring of the risk factors by athletic staff is paramount to the long term

health and well-being of the gymnasts. Athlete education should focus on what a normal

menstrual cycle is, the causes of dysfunction, and long term consequences of dysfunction. The

gymnasts should be educated on sources of dietary calcium and healthy eating practices to

achieve appropriate levels of caloric intake. Close monitoring of the gymnasts for risk factors of

disordered eating should occur on a continuing basis, given the sports predisposition to eating

disorders.

Recommendations

-Include all athletes on the roster by building a more trusting relationship with the team.

-Include other gymnasts from other Division III universities for an increased sample size.

-Assess dietary intake over a longer time period for a more accurate caloric intake

estimation

-Assess dietary vitamin D, phosphorus, magnesium, caffeine, and other nutrients that

affect bone mineral density

-Determine the athletes’ knowledge and attitudes toward the risk factors for the female

athlete triad

37

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status of eumenorrheic athletes. Journal of Bone and Mineral Research: The Official

Journal of the American Society for Bone and Mineral Research, 10(4), 586-593.

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(2005). Dietary calcium intake protects women consuming oral contraceptives from spine

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Athletic Training, 47(1), 74-82.

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Tomten, S. E., Falch, J. A., Birkeland, K. I., Hemmersbach, P., & Hostmark, A. T. (1998). Bone

mineral density and menstrual irregularities. A comparative study on cortical and trabecular

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42

Appendix A: ACSM Permission to re-print Figure 1.

WOLTERS KLUWER HEALTH LICENSE

TERMS AND CONDITIONS

May 12, 2013

This is a License Agreement between Hilary G Wilde ("You") and Wolters Kluwer Health ("Wolters Kluwer Health") provided by Copyright Clearance Center ("CCC"). The license consists of your order details, the terms and conditions provided by Wolters Kluwer Health, and the payment terms and conditions.

All payments must be made in full to CCC. For payment instructions, please see information listed at the bottom of this form.

License Number

3140230933844

License date

May 01, 2013

Licensed content publisher

Wolters Kluwer Health

Licensed content publication

Medicine & Science in Sports & Exercise

Licensed content title

The Female Athlete Triad

Licensed content author

Licensed content date

Jan 1, 2007

Volume Number

39

Issue Number

43

10

Type of Use

Dissertation/Thesis

Requestor type

Individual

Author of this Wolters Kluwer article

No

Title of your thesis / dissertation

Assessment of risk factors for the female athlete triad in female collegiate gymnasts

Expected completion date

May 2013

Estimated size(pages)

54

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Invoice

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3508 Tara Lane

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Terms and Conditions

44

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46

Appendix B: Consent Form

Consent to Participate In UW-Stout Approved Research

Title: Assessment of overall nutritional health status of gymnasts.

Research Sponsor: Laura Knudsen 216 Sports and Fitness Center 715-232-2491 knudsenl@uwstout.edu

Investigator: Hilary Wilde wildeh7348@my.uwstout.edu 651-357-3818

Description: The goal of this study is to investigate a National Collegiate Athletic Association Division III women’s gymnastics team’s health risks through a nutrition assessment. The assessment will consist of a 1-day food record, disordered eating questionnaire, dual energy x-ray absorptiometry scan, and measurements of height and weight. You will also be asked several questions related to your nutritional status including age, ethnicity, menstrual cycle, and medications. All assessment procedures will be conducted by the investigator, trained by the Nutrition Assessment Laboratory graduate assistant as required by the University of Wisconsin-Stout. Benefits: Participating in this study will benefit you by making yourself more aware of your current nutritional status which may assist you in making positive dietary and lifestyle changes to improve your sports performance and overall health. Additionally, your participation includes the possibility of identifying nutritional risks in the female gymnast at a Division III university. Risks: Participation in this study carries some risk. For example, you will be asked to provide sensitive information regarding the nature of your menstrual cycle, medication use including contraceptives, alcohol intake, and dietary intake. In order to participate in this study you must currently not be pregnant. If you suspect you suspect you are pregnant, please notify the researcher. Pregnancy will cause you to be withdrawn from the study. A Dual Energy X-ray Absorptiometer (DXA) scan will be conducted to assess your body composition. This procedure involves lying on a table for 20-30 minutes as a moving arm on a machine is passed over your body. You cannot be wearing any clothing containing metal (metal zipper, snaps etc.). Although you will need to lay very still and quiet, you will feel no discomfort. The DXA is a test to measure body composition and is estimated to provide ~0.001 mSv of radiation for the average adult. This amount of radiation is comparable to approximately 3 hours of exposure to radiation received from natural sources (the annual natural background radiation is ~3 mSv). If you have participated in any other research study involving ionizing radiation exposure in the past 12 months, discuss this with the investigator to determine if you are eligible to participate in this study.

47

Time Commitment: For this study, you will be asked to record everything that you eat during one day of the week. Once you have completed the 1-day food record you will be asked to set up and individual appointment with the researcher to complete the rest of the nutritional assessment. The nutritional assessment will be done on campus in Room 421 in Heritage Hall. The assessment will take approximately 1 hour. Your results will be discussed with you following the assessment. Thank you for your time. Confidentiality: To ensure your data is kept confidential, individual appointments for the nutrition assessment will be arranged in which only you and the researcher will be in the lab. All data collected during the nutrition assessment will be kept in a locked area in which only the researcher and researcher’s advisor will have access. Data will be assigned a code number, rather than using your name. At the completion of this research all data that identifies individual participants will be shredded. Right to Withdraw: You participation in this study is entirely voluntary. You may choose not to participate without any adverse consequences incurred. Should you choose to participate today and later wish to withdraw from the study, you may discontinue your participation at any time without incurring adverse consequences. IRB Approval: This study has been reviewed and approved by The University of Wisconsin-Stout's Institutional Review Board (IRB). The IRB has determined that this study meets the ethical obligations required by federal law and University policies. If you have questions or concerns regarding this study please contact the Investigator or Advisor. If you have any questions, concerns, or reports regarding your rights as a research subject, please contact the IRB Administrator. Investigator: Hilary Wilde 651-357-3818 wildeh7348@my.uwstout.edu

IRB Administrator Sue Foxwell, Director, Research Services 152 Vocational Rehabilitation Bldg. UW-Stout Menomonie, WI 54751 715.232.2477 foxwells@uwstout.edu

Advisor: Laura Knudsen 715-232-3491 knudsenl@uwstout.edu

48

Statement of Consent: By signing this consent form you agree to participate in the nutrition assessment of risk factors in female collegiate gymnasts. Signature Date

49

Appendix C: Female Athlete Nutritional Assessment Form Female Athlete Nutritional Assessment

Name:

Date: Gender: M F

Ethnicity: Age: Total Years participated in sport:

Height ( to nearest 0.25 inch):

BMI: Classification: □Underweight <18.5 □Normal weight: 18.5-25.9 □Overweight: 25.0-29.9

Weight (to nearest .1 lb):

Menstrual Cycle: Age of Menarche _______________ Number of cycles in past year ____________ Length of average cycle_______________________________________________ Other descriptive factors: Medications: Supplements (Nutritional/Herbal) _______________________________________ ___________________________________________________________________ Oral Contraceptive: Y N Name of medications: Additional Information about use: 1-Day Food Record Completed: Y N Participants Name on record: Y N Replaced by code #: Y N Clarification questions asked: Y N Comments

50

Dual-energy X-Ray Absorptiometry (DEXA) Scan: Bone density g/cm2____________ T-Score:_____________________ Classification □Normal: >-1.0 SD □Osteopenia: -1.0 to -2.5 SD □Osteoporosis: <-2.5 SD Stress Fracture History Number in past year:_________________________________________________ Number in previous season:___________________________________________ Locations:__________________________________________________________ Other comments: Eating Attitudes Test Questionnaire: Completed: Y N Score:______________ Classification: □At risk for an eating disorder □Not at risk for an eating disorder Female Athletic Triad Risk Factor Score: □Amenorrhea □Osteoporosis □Disordered Eating If one of the above factors is checked you are at risk for long term health consequences. Other Comments:

51

Appendix D: 1-Day Food Record Form

1-Day Food Record

Research Participant’s Name:______________________________________________________ Date:_____________________Day of the Week:______________________________________ For this 1-day food record, please record everything you eat and drink for one day. Please choose a day that most reflects your average eating habits. Eat as you normally do as this will produce a more accurate assessment of your diet. Please record the time of day that you eat each food item, the type and amount of that item you eat, and any descriptive notes i.e. whole wheat, 100% juice, diet. Record any condiments, sauces, or salad dressing you eat with your food. Also record all beverages consumed including alcohol. Please be as specific as possible noting how the food was prepared and what brand it was. Use the back of this page if you run out of room. Time of day Food/Fluid Amount Notes (ex) 8:00am Cereal ¾ cup Wheaties