Background: In 1992 the American College of Sports Medicine first described the Female Athlete Triad. The Triad is a metabolic injury involving three distinct clinical traits: low energy availability, with possible eating disorder, low bone mineral density and menstrual dysfunction (MD). Although the estimated prevalence of the Triad is low (1.2 %), single factors are common in female athletes, at all competitive levels and ages. Even though the Triad was described over two decades ago, the interrelation of the three diagnostics components is still debated: additional evidence is required to improve the multidisciplinary treatment approach for this complex condition. MD is one of the first signs of energy impairment. The present study aims at investigating MD determinants and predictors in female athletes, to allow an early diagnosis of the Triad and to implement adequate preventive strategies. Materials and methods: An original structured questionnaire was composed to detect the presence of MD risk factors. Included participants were active female athletes within reproductive age range (15-40 years old). Anthropometric parameters and training-related factors, possibly affecting the regularity of the menstrual cycle, were investigated. Results: Respondents were 288 female athletes. Among them, 73.3 % were under 25 years of age; 6.6 % resulted underweight; 30.6 % reported to follow a meal plan/diet and 13.9 % declared to be a smoker. Lean sports were practiced by 30.6 % of responders. Body-weight congruence was detected in in 79.9 % of participants, whereas overestimation of body image was found in 16.3 % of athletes. Irregular menstrual cycle, a possible MD predictor, was present in 33.0 % of athletes, with 41.1 % practicing some lean sport (p = 0.007). Also, overestimation of body image suggested an increased risk of menstrual irregularity (p = 0.001). BMI <18.5 or BMI >30 could also act as risk factor, although significance was not fully obtained (p = 0.053). Overall, practice of lean sports and overestimation of body image appeared good determinants of increased menstrual irregularity (AOR 2.02 and 3.83, respectively). Conclusions: Menstrual irregularity in female athletes can be considered an early predictor of MD: risk is further increased in athletes of lean sports and reporting an overestimation of self-perceived body image. Screenings and awareness programs should specifically address female athletes, because of their vulnerable-group profile. In order to define a standardized at-risk profile for Triad onset and sequelae likelihood, evaluation of menstrual regularity should especially be considered, in conjunction with the assessment of other indicators of energy availability (e.g. TEE, lean and fat mass, BMC). Testing for sport-derived stress and disordered eating attitudes is also recommended. Preventive strategy should involve the proactive engagement of sport clubs and periodic competitive sport medical assessment.
Determinants of menstrual dysfunction in the female athlete triad: A cross-sectional study in Italian athletes
Amoruso, Irene;Fonzo, Marco;Bertoncello, Chiara;Baldovin, Tatjana
2024
Abstract
Background: In 1992 the American College of Sports Medicine first described the Female Athlete Triad. The Triad is a metabolic injury involving three distinct clinical traits: low energy availability, with possible eating disorder, low bone mineral density and menstrual dysfunction (MD). Although the estimated prevalence of the Triad is low (1.2 %), single factors are common in female athletes, at all competitive levels and ages. Even though the Triad was described over two decades ago, the interrelation of the three diagnostics components is still debated: additional evidence is required to improve the multidisciplinary treatment approach for this complex condition. MD is one of the first signs of energy impairment. The present study aims at investigating MD determinants and predictors in female athletes, to allow an early diagnosis of the Triad and to implement adequate preventive strategies. Materials and methods: An original structured questionnaire was composed to detect the presence of MD risk factors. Included participants were active female athletes within reproductive age range (15-40 years old). Anthropometric parameters and training-related factors, possibly affecting the regularity of the menstrual cycle, were investigated. Results: Respondents were 288 female athletes. Among them, 73.3 % were under 25 years of age; 6.6 % resulted underweight; 30.6 % reported to follow a meal plan/diet and 13.9 % declared to be a smoker. Lean sports were practiced by 30.6 % of responders. Body-weight congruence was detected in in 79.9 % of participants, whereas overestimation of body image was found in 16.3 % of athletes. Irregular menstrual cycle, a possible MD predictor, was present in 33.0 % of athletes, with 41.1 % practicing some lean sport (p = 0.007). Also, overestimation of body image suggested an increased risk of menstrual irregularity (p = 0.001). BMI <18.5 or BMI >30 could also act as risk factor, although significance was not fully obtained (p = 0.053). Overall, practice of lean sports and overestimation of body image appeared good determinants of increased menstrual irregularity (AOR 2.02 and 3.83, respectively). Conclusions: Menstrual irregularity in female athletes can be considered an early predictor of MD: risk is further increased in athletes of lean sports and reporting an overestimation of self-perceived body image. Screenings and awareness programs should specifically address female athletes, because of their vulnerable-group profile. In order to define a standardized at-risk profile for Triad onset and sequelae likelihood, evaluation of menstrual regularity should especially be considered, in conjunction with the assessment of other indicators of energy availability (e.g. TEE, lean and fat mass, BMC). Testing for sport-derived stress and disordered eating attitudes is also recommended. Preventive strategy should involve the proactive engagement of sport clubs and periodic competitive sport medical assessment.File | Dimensione | Formato | |
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