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The LEAF questionnaire is a good screening tool for the identification of the Female Athlete Triad/Relative Energy Deficiency in Sport among young football players

Łuszczki, Edyta, Jagielski, Pawel, Bartosiewicz, Anna, Kuchciak, Maciej, Dereń, Katarzyna, Stolarczyk, Artur, Pakosz, Paweł, Oleksy, Lukasz·2021·PeerJ

Abstract

Background: It has been noticed that Female Athlete Triad (Fat) and Relative Energy Deficiency (Red-S) in Sport are characterized by the symptoms of impaired endocrine-metabolic function and bone health in female athletes. In addition, it may be evaluated with a qualitative tool, such as Low Energy Availability in Females questionnaire (LEAF-Q) and quantitative measurements: bone mineral density (BMD), resting energy expenditure (REE), body composition, 24-hour dietary recall. Methods: The aim of this study was to assess the prevalence of Triad and Red-S using the LEAF-Q in youth female football players. Additionally, the difference in the BMD, body composition, REE and energy intake (EI) were assessed between the Triad/Red-S risk and not at-risk groups. Results: Almost two thirds (64.7%) of participants are classified as being at-risk for the triad according to their LEAF-Q scores. There were no statistically significant differences (p > 0.05) between most of the values among children from the analyzed groups. There was a statistically significant difference (p < 0.001) between the EI values among girls from the two analyzed groups: at-risk (1,773.18 kcal ± 232.57) and not at-risk (2,054.00 kcal ± 191.39). Girls who did not meet the energy intake recommendations were 10.00 as likely to be in the Triad/Red-S risk group. Conclusion: Early identification of Fat/Red-S symptoms by screening tools such as the LEAF questionnaire is important in protecting young athletes from long-term damage due to the progression of the risk factors associated with the Fat/Red-S.

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Research works printed but not linked: 23

  1. Bachrach, 2007, Consensus and controversy regarding osteoporosis in the pediatric population, Endocrine Practice, 13, 513, 10.4158/EP.13.5.513 · DOI
  2. Bartosiewicz, 2021, Risk factors of metabolic syndrome among polish nurses, Metabolites, 11, 267, 10.3390/metabo11050267 · DOI
  3. Black, 1991, Critical evaluation of energy intake data using fundamental principles of energy physiology: 2. Evaluating the results of published surveys, European Journal of Clinical Nutrition, 45, 583
  4. Burke, 2006, Energy and carbohydrate for training and recovery, Journal of Sports Sciences, 24, 675, 10.1080/02640410500482602 · DOI · Paper page
  5. Cole, 2000, Establishing a standard definition for child overweight and obesity worldwide: international survey, The BMJ, 320, 1240, 10.1136/bmj.320.7244.1240 · DOI · Paper page
  6. De Souza, 2014, Female Athlete Triad Coalition Consensus Statement on treatment and return to play of the female athlete triad: 1st International Conference held in San Francisco, California, 2012 and 2nd International Conference held in Indianapolis, Indiana, 2013, British Journal of Sports Medicine, 48, 289, 10.1136/bjsports-2013-093218 · DOI · Paper page
  7. Dusek, 2001, Influence of high intensity training on menstrual cycle disorders in athletes, Croatian Medical Journal, 42, 79
  8. Folscher, 2015, Ultra-marathon athletes at risk for the female athlete triad, Sports Medicine - Open, 1, 29, 10.1186/s40798-015-0027-7 · DOI
  9. Foster, 2018, Methodological considerations and future insights for 24-hour dietary recall assessment in children, Nutrition Research, 51, 1, 10.1016/j.nutres.2017.11.001 · DOI
  10. Gibbs, 2013, Prevalence of individual and combined components of the female athlete triad, Medicine & Science in Sports & Exercise, 45, 985, 10.1249/MSS.0b013e31827e1bdc · DOI
  11. Goldberg, 1991, Critical evaluation of energy intake data using fundamental principles of energy physiology: 1. Derivation of cut-off limits to identify under-recording, European Journal of Clinical Nutrition, 45, 569
  12. Kiens, 2011, Energy availability in athletes, Journal of Sports Sciences, 29, S7, 10.1080/02640414.2011.588958 · DOI · Paper page
  13. Kraus, 2019, Bone stress injuries in male distance runners: higher modified Female Athlete Triad Cumulative Risk Assessment scores predict increased rates of injury, British Journal of Sports Medicine, 53, 237, 10.1136/bjsports-2018-099861 · DOI
  14. Kwiatkowska-Pamuła, 2017, Assessment of nutrition in female judokas during the precompetitive body mass reduction period, Trends in Sport Sciences, 4, 183
  15. Logue, 2018, Low energy availability in athletes: a review of prevalence, dietary patterns, physiological health, and sports performance, Sports Medicine, 48, 73, 10.1007/s40279-017-0790-3 · DOI · Paper page
  16. Łuszczki, 2020, Resting energy expenditure of physically active boys in southeastern Poland—the accuracy and validity of predictive equations, Metabolites, 10, 493, 10.3390/metabo10120493 · DOI
  17. Marcason, 2016, Female athlete triad or relative energy deficiency in sports (RED-S): is there a difference?, Journal of the Academy of Nutrition and Dietetics, 116, 744, 10.1016/j.jand.2016.01.021 · DOI
  18. Melin, 2014, The LEAF questionnaire: a screening tool for the identification of female athletes at risk for the female athlete triad, British Journal of Sports Medicine, 48, 540, 10.1136/bjsports-2013-093240 · DOI · Paper page
  19. Mielgo-Ayuso, 2015, Evaluation of nutritional status and energy expenditure in athletes, Nutricion Hospitalaria, 31, 227
  20. Mountjoy, 2015, Authors’ 2015 additions to the IOC consensus statement: Relative Energy Deficiency in Sport (RED-S), British Journal of Sports Medicine, 49, 417, 10.1136/bjsports-2014-094371 · DOI
  21. Nazem, 2012, The female athlete triad, Sports Health, 4, 302, 10.1177/1941738112439685 · DOI
  22. Rauh, 2010, Relationships among injury and disordered eating, menstrual dysfunction, and low bone mineral density in high school athletes: a prospective study, Journal of Athletic Training, 45, 243, 10.4085/1062-6050-45.3.243 · DOI
  23. Thomas, 2021, The relationship between weight cutting and the female athlete triad in combat sport athletes, International Journal of Kinesiology and Sports Science, 9, 9, 10.7575/aiac.ijkss.v.9n.1p.9 · DOI

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Metadata

Authors
Łuszczki, E., Jagielski, P., Bartosiewicz, A., Kuchciak, M., Dereń, K., Stolarczyk, A., Pakosz, P., & Oleksy, L.
Affiliations
  • Institute of Health Sciences, Medical College of Rzeszów University, Rzeszów, Poland
  • Department of Nutrition and Drug Research, Institute of Public Health, Faculty of Health Sciences, Jagiellonian University Medical College, Kraków, Poland
  • Institute of Physical Culture Sciences, Medical College of Rzeszów University, Rzeszów, Poland
  • Orthopaedic and Rehabilitation Department, Medical University of Warsaw, Warszawa, Poland
  • Faculty of Physical Education and Physiotherapy, Opole University of Technology, Opole, Poland
Venue
PeerJ
Publisher
PeerJ
Published
2021-09-03
Volume
9
Pages
e12118
ISSN
2167-8359
Cited by
32
References
7
Language
en

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