Characteristics of the Female Athlete Triad in Collegiate Cross- Country Runners

Written By: Sam Savage

Published Date: November 9, 2007 Last Edited: November 9, 2007

By Thompson, Sharon H

Abstract. The Female Athlete Triad is a life-threatening syndrome defined by disordered eating, amenorrhea, and osteoporosis. Objective and Participants: The author’s purpose in this study was to examine female cross-country runners’ (N = 300) calcium consumption, along with the prevalence of 2 components of the triad: disordered eating and menstrual dysfunction. Methods: The author used measures including the Orientation to Exercise Questionnaire, Calcium Rapid Assessment Method, and questions related to height, weight, exercise time, perceptions of eating disorders, and menstrual status. Previous or current eating disorders were reported by 19.4% of the women, 23.0% had irregular menstrual cycles, and 29.1% had inadequate calcium intake. Results: Those athletes perceiving a previous/current eating disorder scored higher on the Orientation to Exercise questionnaire than did those who did not perceive such. Conclusion: The author recommends educational efforts for the prevention of components of the Female Athlete Triad. Keywords: body image, eating disorders, female athletes, menstrual dysfunction

The American College of Sports Medicine first described the Female Athlete Triad a decade ago.1 It is a life-threatening syndrome that is defined by disordered eating, amenorrhea, and osteoporosis.2 Female athletes at the elite level, those involved in appearance or endurance sports,3 and those with a low body weight are particularly susceptible to developing the triad.1 Data on the prevalence of the triad is needed to improve prevention efforts.4 The researchers who composed a position stand for the American College of Sports Medicine advised further study to better understand the triad areas.5

Although physical exercise has many benefits, too much exercise can negatively affect the female athlete, causing amenorrhea (defined as the absence of 3 to 6 consecutive menstrual cycles), one of the components of the triad.6,7 When athletes restrict food and train hard, hormonal changes can affect the reproductive system and cause menstrual dysfunction. 8 Menstrual dysfunction is more prevalent among female athletes than it is among nonathletes6 and is especially common among women who participate in sports where a thin build may improve performance.1 Several forms of menstrual dysfunction have been found in female athletes, the most severe form being amenorrhea.8,9 Athletic amenorrhea is most common among long- distance runners and ballet dancers, with a prevalence of up to 66%.10 Amenorrhea is also a primary characteristic of anorexia, an eating disorder marked by low body weight and excessive dieting.11 Athletes who appear to be at the greatest risk of developing menstrual dysfunction usually begin training prior to menarche (first menstrual bleeding), have an extremely intense training regimen, consume few calories, and have a low body weight.12

A second component of the triad, disordered eating, is more common among women who participate in certain sports. Researchers1,13 have previously reported that 15% to 65% of those women in thin build sports have pathogenic eating patterns, a fact that may influence the history, development, and course of eating disorders. When studying risk factors for eating problems, Macleod13 found that the same personality characteristics that are required for success in sport, such as perfectionism, persistence, high self- expectation, and independence, are risk factors for eating disorders. Furthermore, athletes who perceive that they have no control over their environments often compensate for this lack of control by controlling food intake. They might also view excessive exercise as a method to control weight and improve performance9; however, these practices are ultimately self-defeating and actually weaken athletic performance.14

Although anorexia and bulimia nervosa are the most commonly researched clinical eating disorders, Eating Disorders Not Otherwise Specified (EDNOS), or subclinical eating disorders, account for 50% of all eating disorders.15 A diagnosis of EDNOS applies when symptoms for anorexia or bulimia are only partially met. People with EDNOS are preoccupied with eating, engage in excessive exercise, and may experience some depression and low-self esteem.16 Beals and Manore17 have reported increases in subclinical eating disorders among active women with rates that may exceed that of clinical eating disorders. Although active women with subclinical eating disorders might not suffer the life-threatening medical complications of those with clinical eating disorders, they have poor nutritional status and health.17

The third component of the triad, osteoporosis, has serious health effects. Amenorrhea and low body weight are 2 factors that are significant predictors of osteoporosis,18 a condition characterized by low bone mass and fragility fractures of the hip, wrist, and spine.19 Numerous researchers8,18,20 have confirmed the development of osteoporosis among eating-disordered women. Poor nutrition from disordered eating and menstrual dysfunction negatively affects the skeletal system.6,7 Adequate calcium and vitamin D intake, along with balanced nutrition, are recommended as part of the preventive guidelines against osteoporosis.20 On the basis of the Reference Dietary Intakes, the daily calcium recommendation for women aged 19-30 years with normal menstrual cycles is 1,000 mg,21 whereas those with oligomenorrhea or amenorrhea are advised to consume 1,500 mg.22

My purpose in this study was to examine the prevalence of characteristics of the Female Athlete Triad in a study of National Collegiate Athletic Association (NCAA) Division I, II, and III cross- country female athletes. Because women in this sport are considered to be at risk for developing components of the Female Athlete Triad,5 I examined their perceptions of a previous/current eating disorder, exercise time, subclinical eating disorder characteristics, current calcium consumption, current menstrual status, and body mass index (BMI).

METHODS

Procedure

I mailed packets containing 20 copies of self-report paper surveys for female collegiate cross-country runners to 85 randomly selected coaches of NCAA United States teams. Included with the surveys was a stamped, self-addressed envelope for survey return. In the coaches’ cover letter, I asked them to have someone other than themselves distribute the surveys to the runners and return them. As an incentive for participation, I offered coaches osteoporosis educational materials I developed for the athletes (brochures and prepared transparencies). I distributed these materials to the coaches when I received the completed surveys. Participation was voluntary, anonymous, and in accordance with university guidelines for human participants.

Participants

Twenty-nine collegiate teams (34.12% return rate) from 22 states completed the survey. From these teams, 300 female collegiate cross- country runners from 44 states and 1 foreign country returned their completed surveys. Mean age for the athletes was 19.64 years (SD = 1.56). A majority reported their race as white (90.3%).

Measurements

Demographic Information

Race, age, height, and weight were self-reported. I used height and weight measures to calculate BMI, a standard acceptable measure of body size. (BMI is measured in kg/m2.) BMI is a function of weight adjusted for height and is one of the most commonly used methods of weight categorization.23 Thomas et al24 found that BMI is related to problem eating and body dissatisfaction.

Perception of Previous/Current Eating Disorder

I assessed the athletes’ perceptions of previous/current eating disorders with the question, “Have you ever been told or perceived that you had an eating disorder?” Thompson et al25 obtained a 1- week test-retest reliability coefficient of 1.0 for this question with a sample of young women. Those who answered “yes” were also asked, “What age were you at the onset?”

Current Menstrual Status

Participants were asked their age at menarche, and they then indicated their current menstrual status by choosing between these responses: have not started menstruation, have not had a menstrual period for 6 months (amenorrhea), have a menstrual period every 6 weeks (oligomenorrhea), or have menstrual periods every 25-35 days.6

Exercise Time

I asked the women, “How many times a week do you engage in vigorous physical activity long enough to work up a sweat?” and also “How many minutes a day do you usually exercise?” I multiplied their reported minutes of exercise a day by the number of times they reported exercising each week to determine their total minutes of weekly exercise. I also asked the women their age when they first became involved in competitive athletics.

Orientation to Exercise

Yates et al26 derived this 27-item questionnaire, the Orientation to Exercise Questionnaire [OEQ], from statements made by athletes and eating disordered patients about sports and investment in exercise. They designed it to determine patterns of risk for progression toward subclinical and clinical eating disorders among athletes and nonathletes. The 6 subscales within the questionnaire and a sample of questions for each factor include: self-control (“I feel better after I exercise”), orientation to exercise (“I follow a controlled training regimen”), self-loathing (“I hate my body when it won’t do what I want”), weight reduction (“I would like a lower percent body fat”), identity (“I am a serious athlete”), and competition (“If I make one goal, I shoot for a harder one”). The alpha coefficients for these factors indicated reliability from .74 to .87, with .92 for the total score.26 Participants indicated agreement or disagreement with statements by checking responses on a 5-point Likert scale (1 = strongly disagree, 5 = strongly agree).26 Current Calcium Intake

Hertzler and Frary27 developed a Rapid Assessment Method (RAM) to estimate usual calcium intake on the basis of correlations with a 24- hour recall for adults and students. Similar to other RAMs, dietary calcium tends to be overreported; however, the relationship for this RAM and Dietary Records was in an acceptable range (r = .68) for a large proportion (85%) of the test population. The RAM portion of the survey included a listing of calcium-rich foods for participants to estimate their consumption on a typical day in the past week. The assessment then provided estimates of daily calcium intake (mg) from 6 categories of foods: milk, yogurt, and cheese; breads, cereals, rice, and pasta; fruits and vegetables; meat, fish, poultry, beans, and nuts; and fat, sugar, and alcohol.

Data Analysis

I manually coded the surveys, entered, and crossvalidated into EPI: INFO, Version 6: A Word-processing, Database, and Statistics Program (Centers for Disease Control and Prevention, Geneva, Switzerland). The data set was then exported to the Statistical Analysis System v. 6.12 (SAS Inc, Cary, NC) and prepared for analysis. I required a probability value of p

Independent variables included perception of a previous/current eating disorder (yes or no) and BMI. Dependent variables were age at menarche, exercise time (minutes per week), current calcium consumption (RAM) items, and Orientation to Exercise items. To assess interactions between these independent variables and test for equal BMI slopes, I used the General Linear Model (GLM) Analysis of Variance procedure. I initially ran the model with interaction terms for the independent variables, and if I could not find these to be significant, I removed them and reanalyzed the model. I calculated least square means to adjust each dependent variable for independent variables.

RESULTS

Table 1 shows participants’ demographic information. Most respondents (83.3%) were of an average weight based on their BMI, which I calculated from their self-reported height and weight (average weight BMI = 18.5-

Perception of Previous/Current Eating Disorder

When asked, “Have you ever perceived or been told that you have an eating disorder?” 19.3% (n = 58) answered “yes.” Those who answered yes reported that their eating disorder began at a mean age of 15.76 years (SD = 1.86, range 11-20 years). Of those individuals, 15 (26.3%) said they had received treatment for eating disorders (see Table 2).

Current Menstrual Status

Participants reported menarche to be at the age of 13.46 (SD = 1.65). When examining rates of menstrual dysfunction, 77% reported normal cycles, 5.3% reported amenorrhea, and 17.7% reported oligomenorrhea. When using the GLM to examine differences in age at menarche by perception of a previous/current eating disorder (yes or no) and BMI, I found no significant differences.

Exercise Time

The women reported a total exercise time each week of 544.72 minutes (SD = 343.45). They became involved in competitive athletics at the age of 11 (M = 11.37, SD = 3.22) and had been competitive athletes for an average of 8 years (M = 8.26, SD = 3.54). Using the GLM, I did not find minutes of exercise time per week to be significantly different on the basis of perception of a past/ current eating disorder (yes or no) or by BMI.

Current Calcium Intake

To determine the effects of BMI and the athletes’ reports of previous/current eating disorders on calcium consumption, I used the GLM. Reported calcium intake (mg) from milk products with intake decreased by 39% for each unit increase in BMI (p = .0221, slope = – .3880; see Table 3). Calcium intake from bread products was also significant by BMI. For each unit increase in BMI, calcium from bread products decreased by 62% (p = .0258, slope = -.6261). In addition, calcium intake from the fats and sweets group was significant by BMI. For each unit increase in BMI, scores decreased (less calcium from fats and sweets) by 49.9% (p = .0152, slope = – .4986. I found no differences in calcium intake for the independent variables in the fruit and vegetable or meat group. Overall scores for the calcium screener were significantly different by BMI. For each unit increase in BMI, scores on the calcium screener decreased by 58.64% (ie, less calcium intake reported) (p = .0081, slope = – .5864).

I next examined the percentage of women who consumed less than recommended amounts of calcium on the basis of the calcium RAM results.27 Young women with menstrual dysfunction should consume 1,500 mg/d calcium.22 I found 50.72% (n = 35) of those athletes reporting amenorrhea and oligomenorrhea had scores lower than this amount on the calcium screener. I found 22.51% (n = 52) of the women who reported normal menstrual status consumed less than this recommended amount.

Orientation to Exercise

To determine the effects of BMI and the athletes’ reports of previous/current eating disorders on subscales within and on the entire OEQ (a measure of patterns of risk for subclinical and clinical eating disorders), I used the GLM (see Table 4).

Those who perceived they had previous/current eating disorders had significantly higher scores on self-loathing (M = 12.60, SD = 3.57, p

The athletes who reported a previous/current eating disorder also had significantly higher scores for using exercise as a method of weight reduction (M = 11.98, SD = 2.26, p = .0028) than did those with no reported eating disorder (M = 10.94, SD = 2.94). For BMI, scores for exercise as a means of reducing weight increased by 41.75% for each unit increase in BMI (p

For identity to exercise, only BMI was significant. Scores decreased by 19.43% for each unit increase in BMI, meaning the athletes reported less of an identity to exercise as their weight increased (p = .0005, slope = -.1944).

I found no significant differences by BMI or for perceptions of previous/current eating disorders for the OEQ subscales of competition, self-control, or orientation to exercise.

When examining overall scores for the OEQ, I found significant differences for those who perceived having a previous/current eating disorder because they obtained higher scores (ie, greater risk of having subclinical or clinical eating disorders) (yes: M = 88.59, SD = 8.95; no: M = 83.39, SD = 9.45, p = .0002) than did those who did not report eating disorders. I also found BMI to be significant. For each unit increase in BMI, scores on this questionnaire increased by 71.39% (p = .0087, slope = .7139).

Female Athlete Triad Components

In 1998, Otis2 cited disordered eating, osteoporosis, and menstrual dysfunction as components of the Female Athlete Triad. I examined the components of disordered eating and menstrual dysfunction on the basis of the athletes’ reports of previous/ current eating disorders and reports of their menstrual status. Although inadequate calcium intake is not a direct measure of osteoporosis, it is one of the risk factors for osteoporosis20; therefore, I used the final calcium RAM scores as one measure of risk for osteoporosis. (I defined low calcium consumption as less than 1,500 mg/d for those with menstrual dysfunction22 and 1,000 mg/ d for those with normal menstrual periods.21) To summarize the results provided previously, 19.4% of the women reported previous/ current eating disorders, 23.0% had irregular menstrual cycles, and 29.1% had inadequate calcium intake.

COMMENT

Although sports participation should be promoted among girls and women for health benefits and enjoyment, education and counseling should be provided for collegeage women regarding components of the Female Athlete Triad.29 Noted in the results are several important findings for college health professionals.

Approximately one-fifth (19.3%) of the female athletes said they perceived or had been told that they had an eating disorder. Although the self-reported responses to this question cannot be equated to clinical diagnoses of eating disorders, the rates were higher than the lifetime prevalence of anorexia and bulimia among women in general, which is estimated to be 3.7% and 4.2%, respectively.30 However, the rates of eating disorders were lower than previous estimates of 36% to 55% for women involved in running and endurance team sports.6,31 Similar to previous findings on age of eating disorder initiation,32 the collegiate runners in this study reported their eating disorders began at age 15 years.

Most athletes’ (83.3%) BMI was in the average-weight category, which I found encouraging because a BMI > 17.5 is a diagnostic criteria for anorexia nervosa.15 Also, a low body weight is a risk factor for the Female Athlete Triad1 and is believed to be a stronger influence on menstrual function than is body fat.8

Menstrual dysfunction is common among female athletes who are involved in intensive athletic activity or are consuming inadequate calories (ie, energy); however, determining the prevalence of menstrual dysfunction is difficult because of the variations in the definition of amenorrhea and the limitations in assessing history of menstrual dysfunction.32 Among these cross-country runners, 23% of the women reported current menstrual dysfunction, a percentage which is higher than the rate of 2% to 5% for women in general,9 yet lower than the rates of 25% to 66% previously reported for female runners.1,6,33 My findings reiterate the importance of screening collegiate cross-country runners for menstrual irregularities because women who suffer from prolonged amenorrhea may never achieve ageappropriate bone mineral densities.33 A weakness of this study was my not identifying those athletes who were using hormone replacement therapy to regulate menstrual cycles or for other medical reasons. There is currently controversy regarding whether hormone therapy will prevent or reverse bone mineral deficits.20 Investigators should conduct further research to determine the role this medication plays in athletes’ health. Because the athletes in this study were physically active but calcium intake was not known, I used calcium intake scores on the RAM to determine one of the risk factors for osteoporosis: low calcium consumption. Approximately 29% of all athletes did not consume adequate calcium, and more than 50% of the women reporting irregular menstrual cycles did not consume the recommended 1,500 mg/d of calcium. Because there is a positive relationship between calcium intake and premenopausal bone density, interventions are needed to encourage female athletes to increase calcium to retard bone loss.34,35 Nutrition education is needed for these athletes to provide information on food choices from the milk, cheese, and yogurt group, which will keep calcium consumption at an adequate level and not promote the weight gain they feel could hinder athletic performance.

My findings were difficult to compare with previous findings because there is limited research on the prevalence of the components of the Female Athlete Triad.9 Researchers have noted that when examining self-reported exercise, eating problems, and body dissatisfaction, investigators should be concerned with social desirability effects.36,37 Because many individuals with disordered eating carefully guard this secret, actual prevalence rates of those with at least 1 component of the triad could be higher.

Future Directions

One aspect that deserves further examination is that of EDNOS. Because it is believed that approximately 50% of those with eating disorders fall into this category,15 further research is warranted to determine specific identifying features. In this study, those women perceiving a previous/current eating disorder had significantly higher scores than did the others on the 2 OEQ subscales related to eating problems: self-loathing and use of exercise for weight reduction, and also on their total OEQ score. The higher scores of those with perceptions of eating disorders could indicate warning signs for body dissatisfaction, obligatory exercise, and possible eating problems. The OEQ seems to be a useful tool to assist in screening athletes for subclinical or clinical eating disorders.

Another item of interest was the effect of BMI on the OEQ scores. Similar to the results discussed previously for those women with a history of eating disorders, as BMI increased there were significant increases in self-loathing and using exercise as a method of weight control. Shame and starvation initiate self-loathing and other destructive behaviors38; therefore, those with higher BMIs in this sport could be at an increased risk for subclinical eating disorders. However, unlike those women who perceived they had eating disorders, there was an inverse relationship between identity to exercise as BMI increased. This means that as BMI increased, the women were less likely to identify themselves as athletes. I speculate that these women feel the need to exercise to lose weight to achieve the usual thin ideal body size for competitive collegiate runners, yet, at the same time, could psychologically try to disassociate themselves from the sport. Also, although I used the wording “higher BMI,” this is probably a misnomer because only 3.7% of the women fell into the overweight or obese categories. This finding is one that experts should note for future study; cross- country runners on the higher end of the average-weight BMI category may be at an increased risk for eating problems.

Limitations

Important deficits exist in knowledge about the triad among active women; therefore, investigators involved in future research in this area should address the following limitations of this study. First, although the surveys were anonymous and I instructed coaches to have someone else collect the surveys and return them via mail, the women could have thought that their coaches or teammates would examine their self-reported information. Those who perceived their BMI to be high could have been overly sensitive about being involved in a sport where a thin body size is considered ideal, and this sensitivity could have influenced their responses. Second, responses about weight, dieting, and body dissatisfaction could have been inaccurate because of social desirability bias or the secretive nature of eating problems. Last, the method of survey distribution and low return rate of the surveys are causes for concern.

Additional studies, particularly those of a longitudinal nature, are needed to better determine how training intensity, hormone replacement therapy, body fat, and body weight influence menstrual irregularities and health of competitive female runners. Thrash and Anderson4 indicated that nutrition education of female athletes should receive greater attention, and the results of this study confirm this recommendation. Coaches should place greater emphasis on prevention of components of the Female Athlete Triad by not promoting disordered eating behaviors and the pursuit of low body weight when working with these athletes. Increased awareness and educational efforts among college health professionals, collegiate coaches, athletes, trainers, athletic department directors, health educators, parents, and physicians are needed to insure optimal physical and mental health among these athletes.

ACKNOWLEDGMENT

The author thanks Presley Smith, Melissa Gabriel, and Lindsey Grainger for assistance in gathering the data.

This study was funded by a grant from the South Carolina Osteoporosis Coalition and the South Carolina Department of Health and Environmental Control, Columbia, SC.

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Sharon H. Thompson, EdD, CHES

Dr Thompson is with Coastal Carolina University’s Health, Physical Education, and Recreation Department.

NOTE

For comments and further information, please address correspondence to Dr Sharon H. Thompson, Health, Physical Education, and Recreation Department, College of Education, Coastal Carolina University, PO Box 261954, Conway, SC 29528 (email: [email protected].).

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