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Screening Athletes for Eating Disorders

How do you know if the athletes you work with have an eating disorder?

 

Dietitians are expected to screen the athletes they support to better assess who they’re working with. Often, those early screening questionnaires or first meetings between the athlete and dietitian would include questions surrounding body weight or composition goals, if the athlete takes supplements, and include a 24-hour recall of what the athlete eats. Those screens also include clinical concerns, including the risk for or presence of eating disorders (ED), disordered eating (DE), low energy availability (LEA), and relative energy deficiency in sport (REDs).

 

This article is going to cover the following:

  • Understanding the population a survey is validated in and why this matters.

  • Available screening tools for evaluating the risk and/or presence of ED, DE, LEA, or REDs.

  • How to apply screening in your workplace.

 

 

Understanding the Population(s) a Survey Has Been Validated In

 

The Female Athlete Triad originally linked eating disorders, osteoporosis, and amenorrhea (the absence of menstruation) in female athletes. Over time, it has evolved to include males and other health implications and is now referred to as Relative Energy Deficiency in Sport (REDs).

 

Eating disorders are more common in females, with lifetime estimates in the US being 8.6% of females and 4.07% of males (1). Ravi et al. (2021) polled more than 800 female athletes across multiple sports and found that “25% reported restrictive eating and 18% reported eating disorders.” (2) Using the Eating Attitudes Test to evaluate the risk of eating disorders, Borowiec et al. (2023) discovered that of the 241 highly trained female athletes ages 12-30 years who were evaluated, 14.6% of adolescents and 6.9% of adults were categorized as at risk for an eating disorder. (3)

 

However, diagnosing concerning behaviors relies on properly evaluating those at risk—and traditionally, males weren’t considered in this equation. For instance, Bratland-Sanda and Sundgot-Borgen (2013) wrote that “the prevalence of disordered eating and eating disorders vary from 0-19% in male athletes. (4) That’s quite the range and makes me wonder if the right questions were being asked of those males to be confident with the validity of the answers collected.

 

Regarding transgender and non-binary individuals, their risk is thought to be 3-4-fold when compared with cis-gender individuals. (5)

 

Many eating disorder screening tools were validated in women—not men. And even then, in women who are not athletes.

 

For instance, the EAT-26 survey was validated in adult women (not athletes). A few of the screening questions are as follows, asking the woman to state if/when they experience each item as always, usually, often, sometimes, rarely, or never:

  • “Am preoccupied with a desire to be thinner.”

  • “Other people think that I am too thin.”

  • “Eat diet foods.”

 

In my experience working with male athletes with eating disorders, often they don’t want to be “thin”. They want to be “lean”, “cut”, “buff”, “jacked”, or to experience body recomposition (i.e., fat loss with muscle mass gain). Often, males don’t identify with dieting or consuming “diet” foods, even though they arguably are.

 

If using the EAT-26 to screen for eating disorders in men, my guess is you’ll miss out on a diagnosis. This isn’t to call out the EAT-26, but to be mindful about who your chosen tool was developed for, validated in, and what it was meant to screen for. For example, are you trying to evaluate the presence of disordered eating, an eating disorder, or body image concerns? In males, male athletes, females, female athletes, adults, etc.?

A variety of screening tools for ED, DE, LEA, REDs.
A variety of screening tools are available.

Available Screening Tools

 

Table 2 in Torstveit et al. (2023) outlined 11 common screening tools that have been validated and tested in athletes for LEA, REDs, and DE behavior. (6) Four of these include the LEAM-Q, LEAF-Q, DESA-6, and the EDE-Q. I don’t highlight these for a specific reason, but to get you thinking about who is your target population and what the purpose of your chosen screening tool is.

 

 

The LEAM-Q and LEAF-Q: Low Energy Availability in Males/Females

 

Different versions exist for males (LEAM-Q) and females (LEAF-Q), both of which screen for LEA. They’re relatively short… with 33 questions in the male version and 25 questions in the female version.

 

I find it common for female athletes to expect questions about their period, but what would a dietitian ask a male that helps capture their suppressed hormones? The LEAM-Q asks males about their sex drive and frequency of morning erections.

 

 

The DESA-6: Disordered Eating Screen for Athletes

 

Validated in male and female high school athletes aged 13-19-year-old, the DESA-6 includes six questions designed to assess risk for DE. Once identified for DE, additional screening tools could be used to evaluate ED.

 

If working in college athletics, this tool could be used for freshman, sophomore, and possibly junior year. It also allows one survey to be used across the male and female population. However, if screening annually, what tool would you use once the athlete hits their twentieth birthday?

 

 

EDE-Q (6.0): Eating Disorder Examination Questionnaire

 

This is currently the gold standard for clinically diagnosing ED and is based on DSM-5 diagnostic criteria for anorexia nervosa, bulimia nervosa, binge eating disorder, and unspecified eating disorders (8). The EDE-Q was originally validated in non-Hispanic white women with and without EDs, but has been since validated in female and male national level athletes (9).

 

The EDE-Q also has versions designed for adolescents (EDE-E) and youth (YEDE-Q), plus a shortened version (EDE-QS) that contains 12 versus 28 questions.

 

 

 

Screening in Your Workplace: Factors to Consider

 

Do You Use the Same Tool for Men and Women?

 

Sure, it may be easy to use the same tool, but if you want accurate data, use validated tools. The earlier the medical team can capture LEA, DE, or an ED, the better outcomes there are for the human/athlete (7). Otherwise, ineffective screening may delay an athlete’s medical care and possibly affect their career trajectory, as they suffer for longer.

 

 

Do You Use a Different Tool Depending on Your Goal or Population?

 

You could also consider the purpose of your screening tool:

  • Is it more useful to run a department-wide screen to capture athletes at risk of LEA and DE, essentially to capture more cases?

  • And then once an athlete has been flagged by the medical team, would it then be helpful to have the athlete complete an additional ED-specific questionnaire to provide baseline and possibly future objective data to evaluate progress, decline, or no change in their condition?

 

 

How Often Will You Screen?

 

Think back to when you began and ended high school or university. Likely, you weren’t the same person, possibly having different views on your body and fueling. Keep this in mind when working in athletics: A one-time nutrition screening questionnaire at the beginning of freshmen year likely isn’t enough. Consider an annual re-assessment, whether online or in-person, to capture the athlete’s changing relationship with their bodies over time.

 

 

Will Survey Length Affect the Athlete’s Likelihood of Completing It?

 

Will a busy athlete complete the Athletic Milieu Direct Questionnaire (AMDQ) that includes 119 questions, despite being designed for and validated in NCAA Division 1 female student-athletes? Or would this female population be more suited for the Physiologic Screening Test (PST) of 18 questions, also validated in college female athletes (NCAA sports, club sports, and dance team athletes)?

 

 

If Screening, Plan for the Next Step: The Management of Flagged Athletes

 

You need an actionable plan ready on the other side of that questionnaire. Otherwise, you’re placing yourself at risk for not acting in the face of concerning medical data. The solution isn't to avoid screening (don’t default to ignorance), but to begin those conversations with your medical team.

 

For instance:

  • Who will review the athlete's survey?

  • Once flagged, what medical team members will need to be made aware?

  • Will they be referred to an in-house or external physician for further evaluation or care?

  • For ED management, do you have a psychologist, physician, and dietitian on staff to round out the athlete's care?

  • Does the sports dietitian in-house have both the skills and capacity to manage this athlete?

  • If in-house, where does the sport dietitian’s ED caseload capacity end? Athletes with EDs could easily require weekly meetings with the dietitian. Is their supervisor wanting to use the sport RD to manage EDs? If so, great. If not, have a plan to refer out, with a referral list of local providers at the ready.

  • If in-house, what is the sports dietitian’s continuing education and supervision plan from an ED-certified dietitian? Is the employer able to pay for those supervision hours?




References


(1) Report: Economic Costs of Eating Disorders. (n.d.). Harvard T.H. Chan School of Public Health. Retrieved May 24, 2024, from https://www.hsph.harvard.edu/striped/report-economic-costs-of-eating-disorders/


(2) Ravi, S., Ihalainen, J.K., Taipale-Mikkonen, R.S., Kujala, U.M., Waller, B., ... & Valtonen, M. (2021). Self-reported restrictive eating, eating disorders, menstrual dysfunction, and injuries in athletes competing at different levels and sports. Nutrients,13(9):3275. https://pubmed.ncbi.nlm.nih.gov/34579154/


(3) Borowiec, J., Banio-Krajnik, A., Malchrowicz-Mosko, E., & Kantanista, A. (2023). Eating disorder risk in adolescent and adult female athletes: the role of body satisfaction, sport type, BMI, level of competition, and training background. BMC Sports Sci Med Rehabil,15(1):91. https://pubmed.ncbi.nlm.nih.gov/37491299/


(4) Bratland-Sanda, S., & Sundgot-Borgen, J. (2013). Eating disorders in athletes: overview of prevalence, risk factors and recommendations for prevention and treatment. Eur J Sport Sci,13(5):499-508. https://pubmed.ncbi.nlm.nih.gov/24050467/


(5) Simone, M., Hazzard, V.M., Askew, A.J., Tebbe, E.A., Lipson, S.K., & Pisetsky, E.M. (2022). Variability in eating disorder risk and diagnosis in transgender and gender diverse college students. Ann Epidemiol,70(June 2022):53-60. https://pubmed.ncbi.nlm.nih.gov/35472489/


(6) Torstveit, M.K., Ackerman, K.E., Constantini, N., Holtzman, B., Koehler, K., ... & Melin, A. (2023). Primary, secondary and tertiary prevention of relative energy deficiency in sport (REDs): a narrative review by a subgroup of the IOC consensus on REDs. Br J Sports Med,57(17):1119-1126. https://pubmed.ncbi.nlm.nih.gov/37752004/


(7) Allen, K.L., Mountford, V.A., Elwyn, R., Flynn, M., Fursland, A., ... & Wade, T. (2023). A framework for conceptualising early intervention for eating disorders. Eur Eat Disord Rev,31(2): 320-334. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10100476/


(8) Kennedy, S.F., Kovan, J., Werner, E., Mancine, R., Gusfa, D., & Kleiman, H. (2021). Initial validation of a screening tool for disordered eating in adolescent athletes. J Eat Disord,9(1):21. https://pubmed.ncbi.nlm.nih.gov/33588900/


(9) Lichtenstein, M.B., Johansen, K.K., Runge, E., Hansen, M.B., Holmberg, T.T., & Tarp, K. (2022). Behind the athletic body: a clinical interview study of identification of eating disorder symptoms and diagnoses in elite athletes. BMJ Open Sport Exerc Med,8(2):e001265. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9214368/

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