Female football specific energy availability questionnaire and menstrual cycle hormone monitoring

Abstract

Abstract Objectives The purpose of this study was to assess the energy availability status of professional female football players with an online Female Football Energy Availability Questionnaire (FFEAQ), combined with the clinical tool to model menstrual cycle hormones using artificial intelligence (AI) techniques. Methods The Female Football Energy Availability (FFEAQ) was developed based on published questionnaires, with a weighted scoring system to assess risk of Relative Energy Deficiency in Sport (RED-S). For menstrual cycle hormones AI techniques modelled hormone variation over a cycle, using the results from capillary blood samples taken at two time points. Results 21 female footballers of professional club level participated in this study, with mean age 22 years [range 16 to 30]. 20 athletes recorded positive scores on the FFEAQ, suggesting a low risk of Relative Energy Deficiency in Sport (RED-S). No players had experienced primary amenorrhoea. 5 athletes reported previous history of secondary amenorrhoea. Amongst the 15 players not taking hormonal contraception, 2 reported current oligomenorrhoea. The application of AI techniques to model menstrual cycle hormones found that in 1 of the 3 players, subclinical hormone disruption was occurring with this player reporting variable flow of menstruation. Although the other 2 players showed expected menstrual hormone variation, 1 player reported variable flow according to training load, suggestive of subclinical anovulation. At the time of testing training load was low due to pandemic lock down. Conclusions The professional female football athletes in this study were found to be at low risk of RED-S from the FFEAQ. Modelling menstrual cycle hormones using AI techniques indicated that this has the potential to be an effective clinical tool in identifying subtle hormone dysfunction such as subclinical anovulatory cycles in female athletes.