Female Athlete Triad Knowledge and the Risk of Low Energy Availability and Disordered Eating in Recreationally Active and Competitive Adult Females

Abstract

Objective:

To examine and compare the knowledge related to the female athlete triad and the signs and symptoms of low energy availability (LEA) and disordered eating (DE) in competitive (CO) and recreationally active (RA) females.

Methods:

Premenopausal females (n = 631, age 25 ± 7 years) completed an electronic survey that assessed female athlete triad knowledge and risk for LEA and DE. Participants self-selected as CO (n = 123) or RA (n = 508). Logistic regression examined the associations between membership in RA versus CO (reference group) and knowledge related to the female athlete triad. Linear regression assessed the association of group membership as predictor variables with LEA and DE risk scores.

Results:

Only 22% of participants were familiar with the female athlete triad term and almost half the total participants were at risk for LEA (45%) and/or DE (45%). The RA group was less likely to be familiar with the female athlete triad than CO (odds ratio = 0.34, confidence interval [CI]: 0.22, 0.53, p < 0.001), yet group membership did not predict risk for LEA (β = −0.57, CI: −1.42, 0.28, p = 0.19) or DE (β = 1.34, CI: −1.72, 4.39, p = 0.39).

Conclusion:

There is a lack of knowledge related to the female athlete triad, coupled with a relatively high prevalence of LEA and DE risk among physically active females, regardless of athletic status (CO vs. RA). Given the high prevalence of LEA and DE risk found in our study, expanding nutrition education and awareness of the health consequences of the female athlete triad to all physically active females is warranted.

Introduction

Energy availability is defined as the amount of energy available for metabolic functions after exercise energy expenditure (EEE) is subtracted from energy intake and is expressed relative to fat-free mass (FFM) (energy availability = energy intake [kcal] – EEE [kcal]/FFM [kg]).^1,2 Inadequate energy availability can result from increased exercise, reduced energy intake, or a combination of both, and is otherwise known as low energy availability (LEA).³ LEA, along with menstrual dysfunction and poor bone health, is the characteristic that defines the female athlete triad.^2,4 Menstrual cycle dysfunction occurs on a spectrum, ranging from the least severe perturbation (i.e., luteal phase defect) that occurs within the framework of an outwardly “normal” menstrual cycle, to the most severe dysfunction that results in cessation of the menstrual cycle (i.e., amenorrhea).⁵ Moreover, long-term effects of LEA may result in low bone mineral density, which increases the risk for bone stress injuries (e.g., stress fractures).^4,6,7 Female athletes are at high risk for LEA, with an estimated prevalence of LEA occurring in 23–80% of female athletes, depending on sport.⁸ However, less is known about the prevalence of LEA in a recreationally active (RA) population.

Although the female athlete triad is a well-established phenomenon that is associated with serious health consequences,³ only a few previous studies have assessed knowledge of the female athlete triad among active females. For example, only 8% of female ultramarathoners were familiar with the female athlete triad, yet 44% were at risk for LEA.⁹ When Australian female exercisers (i.e., ranging from local to international competitors) were asked to report a history of disordered eating (DE), menstrual dysfunction, and stress fractures, 39% had experienced at least one of these issues, but only 10% could recall the three components of the female athlete triad.¹⁰ Additional studies have also reported poor knowledge among individuals who work closely with athletes, such as coaches¹¹ and medical professionals.¹² To date, knowledge about the female athlete triad among RA females is less well characterized, but investigation is warranted since this subpopulation may be at risk for LEA.

The etiology of LEA can be either intentional or unintentional. Energy intake may be reduced intentionally to decrease body mass/fat percentage for optimal athletic performance or to improve appearance.¹³ LEA may also be caused unintentionally by suppression of appetite from prolonged exercise, which stimulates anorexigenic hormones,¹⁴ or by consuming a “healthy” diet that lacks sufficient amounts of energy for the individuals’ needs.¹⁵ Eating disorders (ED) (clinical) or DE (subclinical) are another potential cause of suboptimal energy intake, yet individuals with DE tendencies may only engage in these behaviors sporadically, such that LEA is highly variable and inconsistent or may only result in a reduced energy availability state, without the severe consequences of long-term LEA or any of its established symptoms. DE prevalence in female athletes ranges between 6% and 45% and varies based on sport.¹⁶ Torstveit et al.¹⁷ reported a smaller percentage of DE in elite athletes when compared to nonelite controls. Although physical activity was not an inclusion criterion for the controls, it highlights the need to assess DE in all populations.

Objective measures of LEA are difficult to obtain and are not available to most researchers. Therefore, questionnaires often act as a surrogate marker to determine LEA risk via questions related to DE/ED (i.e., cognitive and behavioral characteristics) or symptoms of LEA (e.g., menstrual function). However, unintentional LEA may not be accurately identified when only DE is assessed,¹⁸ since there are multiple pathways to LEA, several of which do not include DE/ED. Thus, it is important to assess both symptoms and eating behaviors to determine risk for LEA.

To date, most research related to LEA has focused on elite athletes, especially endurance athletes or those participating in the “leanness” sports (e.g., ballet and gymnastics), and these athletes are thought to have the highest prevalence of LEA, menstrual dysfunction,¹⁹ and low bone health²⁰ compared to other athletes. However, much less is known about the knowledge related to the female athlete triad, its components (i.e., LEA), and DE risk in females who are not considered elite athletes but engage in exercise across a wide range of modalities, durations, and intensities on a regular basis. Since this population of physically active females appears to be largely overlooked in the female athlete triad research, the purpose of this study was to examine and compare (1) the knowledge related to the female athlete triad and (2) signs, symptoms, and risk of LEA and DE in a sample of competitive and RA females.

Materials and Methods

The sample for this cross-sectional descriptive study consisted of physically active, premenopausal females aged 18–45 years. Inclusion criteria consisted of the following: (1) performing at least 75 minutes of vigorous aerobic activity, 150 minutes of moderate aerobic activity, or two days of resistance training per week and (2) being at least 18 years of age. All surveys were administered via an online survey platform (Qualtrics; Provo, Utah, USA, 2019). The anonymous survey links were distributed via email to all University of North Carolina-Greensboro female students, faculty, and staff ages 18–45, as well as through social media, with postings focused on fitness groups. All participants provided consent prior to data collection. This study was reviewed and approved by the University of North Carolina-Greensboro Institutional Review Board (IRB 21-0412).

Demographic information

Participants self-identified themselves in terms of their current athletic status as competitive (CO) at any level (i.e., amateur, collegiate, professional) or RA (i.e., exercised but did not participate in competitive events). Participants also self-reported age, race, body mass, exercise duration, modes of exercise. Participants were asked to report diagnoses of medical conditions associated with the female athlete triad DE, oligomenorrhea (i.e., menstrual cycle length 36–90 days), amenorrhea (i.e., menstrual cycle length >90 days), and weight cycling history. To assess medical conditions, the question asked “Have you ever been diagnosed with the following?” and participants were allowed to select all conditions that applied. Weight cycling was assessed with “At your current height, has your weight fluctuated more than 10 pounds in the last three years?” If participants answered yes, a follow-up question asked how many times weight fluctuation had occurred in the last three years. All the information listed above was collected prior to any questions assessing the female athlete triad.

Knowledge related to the female athlete triad

Participants’ knowledge related to the female athlete triad was assessed using the following four items obtained from previous research.^9,10 (1) Are you familiar with the term “female athlete triad”? (2) There are three components to the female athlete triad. Name as many as you can. (3) Is it normal to cease menstruation with heavy training? (4) The female athlete triad’s three components are energy deficiency (low caloric intake), amenorrhea (cessation of the menstrual cycle), and low bone density. Do you feel you are at risk for the female athlete triad?

Questions were displayed one at a time so participants’ answers could not be influenced by the wording of the following questions. Question 1, “Are you familiar with the Female Athlete Triad?” was answered with a yes/no format, and only participants that answered yes were asked to answer the prompt (question 2) “name as many components as possible.” One investigator evaluated the components named. A broad approach was taken and answers associated with the three pillars of the female athlete triad (i.e., LEA with or without an eating disorder [ED], amenorrhea, and osteoporosis) were acknowledged as correct answers. Answers related to the following were accepted: (1) LEA, DE, ED, energy/caloric deficiency, low caloric intake; (2) amenorrhea, decreased or missed periods, no period or menstrual cycle, menstrual irregularities/disturbances; and (3) poor bone health, low bone density, osteoporosis, and stress fractures. All participants were asked questions 3 and 4 which were answered by yes, no, or maybe. The “yes” and “maybe” responses to questions 3 and 4 were combined for the final analyses.

Assessment of low energy availability risk

The LEA in Females Questionnaire (LEAF-Q) is a validated screening tool composed of 25 questions that assesses risk for LEA by asking questions related to symptoms of LEA, such as injuries, gastrointestinal (GI) issues, and menstrual function. The LEAF-Q has a 78% sensitivity and 90% specificity. The internal consistency of the LEAF-Q is α = 0.71 for the total score and similar for the subscales injuries (α = 0.79), GI symptoms (α = 0.75), and menstrual dysfunction (α = 0.61).²¹ Participants with a total score of ≥8 were considered at risk for LEA. The question “Have your periods ever stopped for 3 consecutive months or longer (besides pregnancy)?” was altered to include “besides pregnancy or due to medications” since some medications (i.e., long-acting reversible contraceptive, GnRH agonists) are known to cause amenorrhea.

Assessment of disordered eating risk

The Female Athlete Screening Tool (FAST) identifies DE behaviors in athletes and is a reliable questionnaire with high internal consistency as shown in previous research (Cronbach’s α = 0.87).²² In previous studies, a score of 74–94 indicates a presence of subclinical DE, and a score of >94 has been used to classify individuals as being at an increased risk of a clinical ED.^9,23

Statistical analysis

Data from the completed questionnaires were analyzed using IBM Statistics SPSS 28 and R Statistical Software (v2022.12.0; R Core Team 2021). Variables were summarized as means ± SD and/or %(n) based on the nature of the data. Statistical significance was set at p < 0.05. Univariate logistic regression analyses were conducted to estimate the association of continuous participant characteristics as predictor variables with a membership in the RA versus CO group, with CO set as the reference group. Logistic regression determined the odds of being in the RA versus CO group for every one-unit increase in each variable. Additional logistic regression analyses further assessed the association group membership (RA vs. CO) as a predictor to dichotomous outcomes such as knowledge related to the female athlete triad, risk of LEA, risk of DE, and with additional factors of the female athlete triad, to include medical conditions, injuries, menstrual function, weight cycling, and eating behaviors. CO was set as the reference group. Results of the logistic regression were expressed as odds ratios (ORs) and 95% confidence intervals (CIs). Linear regression assessed (1) the association of group membership as predictor variables with LEA and DE raw risk scores, with CO set as the reference group and (2) the association of physical activity duration and LEA and DE raw risk scores. Internal consistency of the LEAF-Q and FAST was examined by Cronbach’s α.

Results

Participant characteristics

Participant characteristics are presented in Table 1. Only participants with complete surveys (n = 631; CO, n = 123; RA, n = 508) were included from 804 initial surveys. CO was composed of four professional athletes, 25 collegiate athletes, and 94 competitive amateurs. RA were younger, shorter, and less physically active than CO (Table 1). Participants self-identified as 74% Caucasian or White, 9% Hispanic or Latino, 11% Black or African American, 1% Native American or Alaskan Native, and 2% as either biracial or race/ethnicity not listed. Resistance training, running, and yoga were the top three modes of exercise, with over 70% of participants engaged in resistance training, 70% ran, and 43% performed yoga. Nearly half (49%) performed running and resistance training. Overall, most participants participated in multiple modes of exercise, with 28% participating in two activities, 27% in three, and 31% in four or more modalities.

Table 1.

Participant Characteristics

Characteristic	RA	CO	OR	95% CI
Age (year)	25 ± 6	29 ± 8	0.92 ^**	0.89, 0.94
Height (cm)	163.8 ± 8.6	166.2 ± 7.0	0.97 ^*	0.94, 0.99
Body mass (kg)	67.2 ± 16.3	67.2 ± 13.7	1.00	0.99, 1.01
BMI (kg·m²)	25.1 ± 5.8	24.3 ± 4.5	1.03	0.99, 1.07
Physical Activity/week (min)	254.4 ± 262.4	403.9 ± 302.4	0.99 ^*	0.99, 0.99

Values that were significant are bolded.

Data are presented as mean ± SD.

Significant <0.05.

Significant <0.001.

BMI, body mass index; CI, 95% confidence interval; CO, competitive; OR, odds ratio; 95%; RA, recreationally active; SD, standard deviation.

Knowledge related to the female athlete triad

When RA and CO were assessed together, 22% were familiar with the female athlete triad term (Table 2). Only 12% (n = 76) were able to list all three components of the female athlete triad, with amenorrhea being the most recalled component (19%; n = 117). Furthermore, 8% of participants were able to name one (2%; n = 13) or two (6%; n = 35) components. Less than half (40%) of participants recognized that cessation of menstruation even with heavy training was abnormal, with the majority being unsure (33%) or unaware of this being a problem (27%). The participants’ knowledge related to the female athlete triad differed by the type of self-reported athletic status (i.e., CO, RA) (Table 2). RA displayed less knowledge about the female athlete triad compared to CO, with RA having lower odds of being familiar with the female athlete triad (p < 0.001) and were less likely to name at least one of the three female athlete triad components (p < 0.001). RA had higher odds of believing that it was normal for the menstrual cycle to stop with exercise compared to CO (p = 0.02). There were similar risk levels (p = 0.34) between RA and CO when presented with the three components of the female athlete triad, with 10% of total participants feeling they were at risk for the triad and 15% thought they might be at risk.

Table 2.

Knowledge Related to the Female Athlete Triad

	RA	CO	OR	95% CI	Total
Not familiar with the triad	83% (419)	62% (76)	0.34 **	0.22, 0.53	78% (495)
Triad components named
Amenorrhea	14% (73)	36% (44)	0.30 **	0.19, 0.47	19% (117)
Low energy availability	13% (67)	29% (35)	0.40 **	0.25, 0.64	16% (101)
Low bone health	12% (61)	29% (25)	0.34 **	0.21, 0.55	15% (96)
Able to name at least one triad component	16% (79)	37% (45)	0.32 **	0.21, 0.50	20% (124)
Is it normal for menstruation to stop with training?^a (Yes/Maybe)	62% (314)	50% (62)	1.59 *	1.07, 2.37	60% (376)
Believed to be at risk of the female athlete triad^a (Yes/Maybe)	25% (127)	24% (29)	1.08	0.69, 1.74	25% (156)

Values that were significant are bolded.

Data are presented as % (n).

Yes and maybe were combined for analysis.

Significant at p < 0.05.

Significant at p < 0.001.

Low energy availability and disordered eating risk

Overall, 45% of all participants were determined to be at risk for LEA (LEAF-Q score ≥8) and 45% of the participants were at risk for DE (FAST score ≥74), with 10% considered to be at an increased risk for a clinical ED (FAST score >94) (Table 3). Group membership (CO, RA) did not influence risk for LEA (p = 0.19) or DE/ED (p = 0.39). Utilizing at-risk criteria for both surveys (i.e., ≥8 LEAF-Q, ≥74 FAST), 25% females were at risk for both LEA and DE (LEAF-Q 11.9 ± 2.2; FAST 88.6 ± 10.0), and this risk was similar among CO (22%) and RA (26%) (OR = 1.07, CI: 0.92, 1.27, p = 0.36). Group membership did not predict LEA or DE risk using the LEAF-Q (p = 0.39) and FAST (p = 0.19) scores, respectively (Table 4), and physical activity duration also did not predict LEA (p = 0.91) or DE risk (p = 0.12) scores. When the subscales of the LEAF-Q were examined, RA had a lower risk of injuries than CO (p < 0.001), yet no association between group membership and GI or menstrual function was found. The FAST demonstrated excellent internal consistently (α = 0.91), while the LEAF-Q displayed an overall internal consistency of α = 0.61, with subscales having a Cronbach α of 0.77, 0.52, and 0.58 for injury, GI function, and menstrual function, respectively.

Table 3.

Risk for Low Energy Availability and Disordered Eating

At risk for	RA	CO	OR	95% CI	Total
Low energy availability	44% (223)	47% (58)	0.96	0.84, 1.50	45% (281)
Disordered eating	46% (235)	42% (51)	1.06	0.93, 1.22	45% (286)
Subclinical	36% (181)	32% (39)	1.07	0.93, 1.22	35% (220)
Clinical	11% (54)	10% (12)	1.06	0.85, 1.34	10% (66)

Data are presented as % (n). Subclinical disordered eating (DE) risk, scores between 74 and 94; clinical eating disorder (ED) risk, scores >94.

FAST, female athlete screening tool²²; LEAF-Q, Low Energy Availability in Females Questionnaire, scores ≥8 at risk.²¹

Table 4.

Association of Athletic Group with LEAF-Q and FAST Scores

	RA	CO	β	95% CI	Total
LEAF-Q
Total score	7.4 ± 4.2	7.9 ± 4.6	−0.57	−1.42, 0.28	7.5 ± 4.3
Injuries	1.2 ± 1.9	2.0 ± 2.2	−0.84 ^*	−0.22, −0.46	1.4 ± 2.0
GI function	2.9 ± 2.2	2.5 ± 2.3	0.35	−0.09, 0.78	2.8 ± 2.2
Menstrual function	3.3 ± 2.5	3.3 ± 2.9	−0.07	−0.59, 0.44	3.3 ± 2.6
FAST
Total score	72.8 ± 15.7	71.4 ± 14.8	1.34	−1.72, 4.39	72.5 ± 15.5

Values that were significant are bolded.

Data are presented as mean ± SD and % (n). Subclinical disordered eating (DE) risk, scores between 74 and 94; clinical eating disorder (ED) risk, scores >94.

Significant at p < 0.001.

GI, gastrointestinal.

Menstrual cycle changes

Group membership was not a predictor of any menstrual dysfunction that is typically linked with LEA that was identified in the LEAF-Q. Only 8% (RA, 8%; CO, 9%; OR = 0.93, CI: 0.75, 1.20, p = 0.59) reported menarche occurring at 15 years or older. Almost a third of participants (RA, 29%; CO, 26%; OR = 1.07, CI: 0.92, 1.24, p = 0.36) reported having their menstrual cycle stop for at least three consecutive months or longer that was not due to pregnancy or medication, while 3% indicated that was the current situation. Over 40% (RA, 42%; CO, 41%; OR = 1.02, CI: 0.89, 1.16, p = 0.80) indicated a change in menstruation with increased exercise intensity, frequency, or duration. Bleeding less and/or fewer days was the most common menstrual cycle change reported to occur with increased exercise, with over a third of participants (RA, 31%; CO, 31%; OR = 1.00, CI: 0.87, 1.15, p = 0.97) reporting this change, while 8% (RA, 8%; CO, 11%; OR = 0.88, CI: 0.71, 1.11, p = 0.26) reported menstruation stops in response to increased exercise.

Self-reported medical conditions associated with the female athlete triad

DE (13%) and stress fractures (12%) were the most prevalent self-reported medical conditions, while oligomenorrhea/amenorrhea (6%) and low bone mineral density (2%) were less common. RA had lower odds of reporting a diagnosis of a stress fracture (OR = 0.69, CI: 0.58, 0.82, p < 0.001), oligomenorrhea and/or amenorrhea (OR = 0.75, CI: 0.59, 0.96, p = 0.02), or low bone health (OR = 0.66, CI: 0.43, 0.99, p = 0.04) than the CO group, while RA and CO had similar odds of reporting DE (OR = 1.01, CI: 0.83, 1.2, p = 0.96).

Weight cycling

Almost 69% of participants (RA, 71%; CO, 61%) self-reported weight cycling (≥10 lbs) in the last three years at their current height, excluding pregnancy. This weight fluctuation occurred three or more times in 25% (RA, 26%; CO, 22%) of females. RA had 1.2 higher odds for weight cycling than CO (OR = 1.16, CI: 1.01, 1.33, p = 0.03). In the FAST, 46% of all participants reported dissatisfaction with their current weight and only 36% believed their methods or techniques used to control body weight were healthy. While group membership did not predict participant satisfaction with their current body weight (OR = 1.13, CI: 0.99, 1.39, p = 0.06), RA had higher odds of engaging in unhealthy methods for weight control (OR = 1.37, CI: 1.19, 1.59, p < 0.001).

Discussion

This study investigated and compared the knowledge related to the female athlete triad and the risk of LEA and DE in RA and CO females. Our primary findings were that most females in our sample displayed poor knowledge about the female athlete triad, with RA likely to have less knowledge of the female athlete triad compared to CO. Surprisingly, nearly half (45%) of the total study population were at risk for LEA or reported being at risk for DE (45%), with similar risk between groups. Furthermore, 25% of our study sample was at risk for both LEA and DE, regardless of their group membership (self-identified competitive vs. recreational athlete).

Previous studies using ultra-endurance and elite athletes indicated only 8–10% of participants were able to identify all three components of the female athlete triad.^9,10 This same lack of knowledge about the female athlete triad was evident in our study, with only 22% of the participants being familiar with the concept of the female athlete triad and only 12% capable of identifying all three components. Since the prevalence of the female athlete triad tends to be higher and thus overall knowledge would be expected to be greater among elite athletes, it is perhaps not surprising that our CO group had slightly higher odds of being familiar with the female athlete triad than the RA females. This outcome may be related to females in the CO group possibly having better access to information via professionals such as registered dietitians, trainers, or coaches because of their athletic status. However, both groups had remarkably low knowledge levels considering that this construct, medical diagnosis, and treatment guidelines have been around since 1992.^24,25 Additionally, the diagnostic criteria were updated in 2007²⁶ to the “triad umbrella”—a spectrum or continuum for all three components—and eliminated the requirement for all three components to be present simultaneously, significantly broadening the criteria for females that would be tagged as “at risk.” Despite these changes in criterion for diagnosis, the lack of information and misconceptions related to the female athlete triad are still highly prevalent. Not only among athletes but also coaches and even health professionals.^11,12,24 These findings highlight the eminent need for broader education about the female athlete triad across all populations from medical professionals down to athletes.

Age may play a potential role in increased female athlete triad knowledge, on average, CO was four years older than RA. As females start trying to conceive, awareness on reproductive health may increase, and the mean age of CO (29 years) aligns closely with the mean age (27 years) of new mothers.²⁷ Although this study did not investigate pregnancy, commonality among age groups suggests the potential importance of menstrual health knowledge as females focus on childbearing. Furthermore, this outcome suggests younger, physically active females may not be receiving proper exposure and education concerning the female athlete triad or related risks. Nevertheless, the overall low level of knowledge about the female athlete triad among all our participants emphasizes the need for educating active females regardless of the athletic status and/or age.

The menstrual cycle is considered a marker of overall health in premenopausal females,^28,29 yet many participants surveyed did not understand that cessation of the menstrual cycle is abnormal. This point is further corroborated by the fact that only 6% of females surveyed reported a medical diagnosis of either oligomenorrhea or amenorrhea, yet 30% of all participants reported experiencing amenorrhea at some point, regardless of group. Approximately half of CO recognized the cessation of the menstrual cycle as abnormal and had a higher likelihood to determine amenorrhea as abnormal compared to RA. Outcomes for CO were similar to ultramarathoners, reporting 50% of surveyed able to identify amenorrhea as a result of increased exercise as abnormal.⁹ Since CO may be more aware of the abnormal signs and symptoms of the female athlete triad than RA, they may be more likely to seek medical treatment. However, without direct assessment, we are unable to determine if the rates of oligomenorrhea and amenorrhea were lower in RA due to lack of knowledge and thus decreased likelihood to seek medical help.

The fact that almost half of the females in our sample were at risk for LEA and/or DE, regardless of athletic status, is troubling. Reported LEAF-Q results are similar to other reports assessing LEA risk, which found increased risk in ∼40% of physically active females of varying athletic abilities in Ireland,³⁰ 45% of RA females in New Zealand,³¹ and 44% of ultramarathoners.⁹ Only the ultramarathoners were given the FAST along with the LEAF-Q, but the risk from both surveys was not established. While LEA risk was similar based on the LEAF-Q, the ultramarathoners were at less risk for DE (27%) and ED (5%)⁹ compared to our females. This may be attributed to variation in sports, as ultra-endurance sports require large caloric intakes to counterbalance increased energy expenditures. Similarities exist among reports in military females assessed for DE/ED risk via the FAST, 35% of these females were at risk for DE and 13% at an increased risk for ED,²³ which is comparable to the currently study population levels of 35% and 10%, respectively. These data further substantiate the need to expand current female athlete triad research and screening to include all physically active females, not just elite athletes.

Only 13% of our females reported a history of DE, while 45% of females surveyed were reported to be at risk for DE. These results focus attention on a potentially large percentage of females with undetected DE. Similar to research that assessed DE in a diverse sample that composed of over 900 females, 12% of females were reported at risk for DE while only 4% of those at risk reported having been identified as having DE or ED.³² Although this study displayed a lower prevalence of reported DE compared to other current studies, it highlights the low rate of DE history compared to those with an increased level of risk for DE.

Assessment of LEA risk by the LEAF-Q is linked to identification of LEA symptoms (i.e., injury, GI, and menstrual function). Since only a quarter of all participants surveyed were at risk for both LEA and DE, it is hard to discern if reported symptoms in the LEAF-Q were caused by LEA or other issues. LEA is associated with a higher injury risk, yet it is difficult to determine whether injuries reported were caused by LEA or another mechanism (i.e., poor biomechanics, excessive exercise). Furthermore, the LEAF-Q is unable to discern if the menstrual dysfunction is a result of LEA or other causes such as polycystic ovary syndrome, which is a common cause of menstrual dysfunction that is underdiagnosed.³³ Additionally, subclinical menstrual dysfunction (e.g., anovulation), which can occur with a seemingly normal menstrual cycle, is not detectable with a survey and requires hormone testing. Moreover, the overall internal consistency was slightly lower in our sample than the internal consistency from the LEAF-Q validation, with the largest discrepancy occurring with the GI subscale. Previous research investigated the LEAF-Q overall and subscale scores with a surrogate measure of LEA (i.e., resting metabolic rate ratio) in a mixed-sport cohort and found that while the overall, injury and menstrual function scores displayed high sensitivity with low specificity, the GI subscale had poor sensitivity and specificity in detecting LEA.³⁴ Regardless, the LEAF-Q is the most well-established, highly utilized survey to assess LEA symptoms and can be used to identify females who require further medical screening.

This study represented a population of females participating in a variety of exercise types at the recreational and CO level and highlights the need to include all physically active females in LEA research and education efforts. However, the present study is not without limitations. This study aimed to look at CO and RA females but had a lower response rate from CO athletes, comprised of professional, collegiate, and CO amateur females. Therefore, these findings should be interpreted with caution. Additionally, our data were self-reported, and survey findings are often limited by the influence of participant perceptions and self-bias. Last, the LEAF-Q only assessed LEA risk-based off injuries, GI issues, and menstrual function, but does not assess additional symptoms that are associated with LEA. Future research should include direct measurements of LEA (i.e., energy intake and physical activity monitoring) to specifically assess LEA and the female athlete triad components across a wide range of physically active females.

Conclusions

In summary, there is a lack of knowledge related to the female athlete triad, coupled with a relatively high prevalence of LEA and DE risk among physically active females, regardless of whether they self-identify as recreational or CO athletes. With almost half of the females in the current study being at risk for LEA and/or DE, our findings highlight the urgent need for a variety of educational programs to ensure all physically active females understand the signs, symptoms, and risks of the female athlete triad to prevent and/or minimize negative health outcomes in this population.

Footnotes

Authors’ Contributions

S.J.G. conceived the study, collected data, performed data analyses, and drafted the article. All coauthors discussed the study design, performed analysis, contributed substantially to interpreting the results, provided important revisions, and approved the article. All authors understand that they are accountable for all aspects of the work and ensure the accuracy or integrity of this article.

Declarations

The opinions or assertions contained herein are the private views of the author(s) and are not to be construed as official or as reflecting the views of the Army, the Department of Defense, or the U.S. Government.

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Author Disclosure Statement

No potential conflict of interest was reported by the authors.

Funding Information

This study has no funding.

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