Evaluation the Impact of Hormonal Fluctuations During the Menstrual Cycle on the Performance of Female Athletes—Systematic Review

atic review aims to evaluate the impact of hormonal fluctuations during the menstrual cycle on the performance of female athletes. Methods: Following PRISMA guidelines, a comprehensive search was conducted in Scopus, Web of Science, and PubMed databases using the keywords: (“Menstrual cycle”) AND (“performance” OR “female athlete” OR “sport” AND NOT “male”); AND NOT (“contraceptive”). In- clusion criteria focused on original studies published between 2013 and 2023, in English or Spanish, involving eumenorrheic female athletes without menstrual disorders or oral contraceptive use. The studies were critically assessed using the McMaster scientific review method. Results: Thirteen eligible articles were reviewed, comprising a total sample of 152 athletes. Significant findings include increased flexibility during the ovulatory phase and enhanced aerobic and anaerobic capacities in the luteal phase. Additionally, the menstrual and premenstrual phases notably influenced aerobic and anaerobic capaci- ties, performance perception, symptomatology, and exercise-induced muscle damage. Conclusion: Hormonal fluctuations can impact female athletes’ performance. However, further research is warranted due to inconsistent results stemming from variations in cycle phases studied, lack of standardized methodologies, small sample sizes, and short observation periods. Keywords:menstrual cycle; estrogen; progesterone;

phase. Additionally, the menstrual and premenstrual phases notably influenced aerobic and anaerobic capaci- ties, performance perception, symptomatology, and exercise-induced muscle damage. Conclusion: Hormonal fluctuations can impact female athletes’ performance. However, further research is warranted due to inconsistent results stemming from variations in cycle phases studied, lack of standardized methodologies, small sample sizes, and short observation periods. Keywords:menstrual cycle; estrogen; progesterone; female athletes; eumenorrheic; performance 1. Introduction Sports represent a global social phenomenon that transcends cultural boundaries, creating shared experiences and fostering enthusiasm worldwide [1]. However, societal challenges, such as gender inequality, have historically been mirrored in sports, with women being excluded from participation for many years. In recent times, the growth and professionalization of women’s sports have led to an increase in research focusing on female physiology, particularly the effects of sex hormones on athletic performance [2]. Although findings vary, there is broad agreement that biological differences between men and women—particularly the influence of steroid hormones such as progesterone (P4) and estradiol (E2)—significantly impact female athletes’ physiological responses to exercise [3]. Muscles2025,4, 15 https://doi.org/10.3390/muscles4020015

Muscles2025,4, 15 2 of 17 The menstrual cycle, which typically lasts 28 days in eumenorrheic women, is reg- ulated by interactions among hypothalamic, pituitary, and ovarian hormones [4]. The secretion of P4, follicle-stimulating hormone (FSH), luteinizing hormone (LH), and E2 occurs in distinct phases, resulting in hormonal fluctuations that influence physical perfor- mance and metabolic requirements [5]. These fluctuations can affect performance metrics and mood throughout the cycle, with E2 and P4 playing pivotal roles in these variations [6]. For instance, some studies [7] indicate that premenstrual symptoms during the late luteal phase—such as abdominal discomfort and mood changes—negatively impact perfor- mance perception. Additionally, Solli et al., (2020) [8] found that 20% of athletes modify their training routines or use analgesics during the early follicular phase to manage symp- toms. Performance parameters such as strength fluctuate, with increases observed during the luteal and ovulatory phases, while declines in strength and heightened fatigue are noted during the late luteal and early follicular phases [9–11]. Research on endurance has produced inconsistent results, with minor reductions in anaerobic capacity during the late follicular phase and lower aerobic capacity during the late luteal phase [12]. Furthermore, athletes with menstrual dysfunctions or delayed menstruation face an elevated risk of injury. In sports such as soccer, 88% of muscular and tendinous injuries occur during ovulation, likely due to elevated levels of estrogen and relaxin, which increase the risk of anterior cruciate ligament (ACL) injuries [13,14]. While there is evidence suggesting that hormonal fluctuations influence performance, the results remain inconsistent, underscoring the necessity of further research to achieve a more precise understanding [15]. Consequently, this study seeks to analyze the existing literature on the impact of hormonal fluctuations during the menstrual cycle on female athletes’ physical performance parameters over the past decade (2013–2023). 2. Methods The present systematic review follows the guidelines established by PRISMA (Pre- ferred Reporting Items for Systematic Reviews and Meta-Analyses), recommended for conducting systematic reviews and meta-analyses [16], and is registered on the platform https://www.crd.york.ac.uk/PROSPERO/ The systematic review follows a strategy for searching original articles. To identify eligible articles for the study, a

parameters over the past decade (2013–2023). 2. Methods The present systematic review follows the guidelines established by PRISMA (Pre- ferred Reporting Items for Systematic Reviews and Meta-Analyses), recommended for conducting systematic reviews and meta-analyses [16], and is registered on the platform https://www.crd.york.ac.uk/PROSPERO/ The systematic review follows a strategy for searching original articles. To identify eligible articles for the study, a search was conducted in the main databases: Scopus, Web of Science, and PubMed, using a search strategy that includes Boolean operators with the established search terms: (“menstrual cycle”) AND (“performance” OR “female athlete” OR “sport” AND NOT “male”); AND NOT (“contraceptive”) (Figure). No restrictions were applied in the advanced search, and all studies published in the main database categories were included, incorporating all those indexed in the Core Collection of Web of Science. 2.1. Study Selection The selection of studies for this systematic review follows the PICO criteria. Studies involving eumenorrheic female athletes participating in any sport [P] that assessed physio- logical and performance variables [I] in relation to the different phases of the menstrual cycle [C] were included to determine the significant effects of the menstrual cycle phases on athletic performance [O]. All articles that met the inclusion and exclusion criteria outlined in Table

Muscles2025,4, 15 3 of 17 Figure 1.PRISMA 2020 Flow Diagram for New Systematic Reviews. Table 1.Inclusion and exclusion criteria. Inclusion Criteria Exclusion Criteria - menstrual cycle on the performance of female athletes - - variables throughout the menstrual cycle phases - - - - - exertion by Borg scale, interviews) - - Studies with women suffering from menstrual cycle disorders - - - - 2.2. Inclusion and Exclusion Criteria Data extraction from eligible articles is classified in a table that includes the following: (1) authors and year; (2) study design; (3) observation period; (4) sport; (5) category; (6) sample size; (7) mean age; (8) menstrual cycle measurement; (9) phases analyzed; (10) performance parameters and tests; (11) subjective variables; (12) main conclusions. Data from the included studies were recorded in a spreadsheet designed for this review.

Muscles2025,4, 15 4 of 17 The studies included in this systematic review were assessed using the McMaster form, which aims to evaluate the methodological quality and risk of bias of the research [17]. Sixteen items were evaluated to determine whether the studies met specific criteria, with scoring conducted using two indicators: “YES = 1 point” or “NO = 0 points”, except for items 6 and 13, for which the response “Not applicable” could also be selected. Finally, the total score of the studies classifies the articles into five categories: poor methodological quality (P with≤8 points); acceptable methodological quality (A with 10–11 points); good methodological quality (G with 12–13 points); very good methodological quality (VG with 14–15 points); and excellent methodological quality (E with≥16 points). 3. Results The systematic review includes a total of 13 scientific articles (Table), with significant heterogeneity in both the characteristics of the athletes and the performance tests conducted, as multiple sports disciplines were included.

Muscles2025,4, 15 5 of 17 Table 2.Data extraction from included articles. Variables Analyzed Author, Year and Design of the Study Study Design Observation Time Sport Category Sample No. Average Age CM Measurement Phases Analyzed Parameters and Performance Tests Subjective Variables Main Conclusions Shaktina et al., (2016) [18] Observational2 months Athletics (800 and 1500 m) 13 17-24 Basal body temperature FF (FM), FOVU and FL (FPM) PWC Test FM, FOVU and FPM reduce endurance performance4×400 m Stefanovský et al., (2016) [19] Randomized 3 months Judo 8 18.44 Notification from the first day of bleeding and calculation of the phases FFF and FLM Wingate No significant differences were found in the tests performed SJFT Ross et al., (2017) [20] Observational3 months Soccer 2nd German Division 9 18.6 App registrations and blood samples FFT and FLM CMJ Negative impact of FLM on aerobic capacity3×30 RPE Tounsi et al., (2018) [21] Observational1 month Soccer High level 11 21.18 Blood tests FFT, FFF and FL 5JT Strength and endurance tests showed no interference from CM in sportswomenRSA Romero- Moraleda et al., (2019) [22] Randomized 1 month Triathlon 13 31.1 App registration and urine tests FFT, FFF and FLM 1RM half-squat No differences in strength were found during the CM phases Nabo et al., (2021) [23] Observational1 month Indoor soccer 1st National League 14 24.1 Registration by app FF and FL Balke maximal test Greater maximum aerobic capacity during the luteal phase Ross et al., (2021) [24] Observational4 months Soccer 1st and 2nd German 15 Divisions 15 23 Records, blood tests and urine tests FF and FL Distance and intensity by zones measured by GPS in matches Greater distances traveled at high intensity in FF Campa et al., (2021) [25] Observational50 days Soccer Italian 1st Division 20 23.8 Calendar records FFT and FOVU CMJ A notable influence of CM on flexibility, with greater capacity during ovulation 20 m Sit and reach Graja et al., (2022) [26] Randomized 30 days Handball National League Tunisian 10 22.5 Blood tests, urine tests and records FF, FL and FPM MVC Hooper Index FPM reduces sprinting ability and strength, with increased

20 23.8 Calendar records FFT and FOVU CMJ A notable influence of CM on flexibility, with greater capacity during ovulation 20 m Sit and reach Graja et al., (2022) [26] Randomized 30 days Handball National League Tunisian 10 22.5 Blood tests, urine tests and records FF, FL and FPM MVC Hooper Index FPM reduces sprinting ability and strength, with increased muscle damage after the tests 20×5 by bike

Muscles2025,4, 15 6 of 17 Table 2.Cont. Variables Analyzed Author, Year and Design of the Study Study Design Observation Time Sport Category Sample No. Average Age CM Measurement Phases Analyzed Parameters and Performance Tests Subjective Variables Main Conclusions Igoinin et al., (2022) [23] Observational, longitudi- nal 3 years Soccer French 2nd Division 8 25.7 Registration by app FFT, FFF and FLM Match statistics (Total distance and speeds reached) Longer total distance traveled, and moderate and high speed in FL Sánchez et al., (2022) [27] Observational3 months Soccer Regional 12 16.18 Records by app FFT, FFF and FL 40 m Hooper Index Reduction in subjective well-being during FM and FL V-cut, Hop test (unipodal and bipodal) and SJ Gasperi et al., (2023) [28] Descriptive, retrospec- tive 14 weeks Basketball 1st Lithuanian Division 11 20.5 Notification from the first day of bleeding and calculation of the phases FF and FL Match stats (PIR, REB, eFG%, TO, PL min) * and factors, game contexts RPE and TQRpre Better rebounds and shooting effectiveness during FF, with correlation of Subjective variables with shooting in matches Morenas- Aguilar et al., (2023) [29] Observational4 months Handball Regional 8 19.8 Urine analysis and calendar FFT, FFF and FLM CMJ and pitching velocity SAM scale CM does not affect the performance variables of athletesVAS scale Abbreviations: CM (menstrual cycle); FF (follicular phase); FM (menstrual phase); FOVU (ovulatory phase); FL (luteal phase); FPM (pre-menstrual phase); FFF (final follicular phase); FLM (mid-luteal phase); FFT (early follicular phase); Test PWC (physical working capacity), SJFT (special judo fitness test), CMJ (countermovement jump), RPE (rate of perceived exertion); TQRpre (total quality recovery); 5JT (5-jump test), RSA (repeated sprint ability), MVC (maximum voluntary contraction), SJ (squat jump); PIR (performance index rating), REB (rebounds), eFG% (effective field goal percentage), TO (turnovers), PL min (player load per minute), SAM (self-assessment manikin), VAS (visual analogue scale).

Muscles2025,4, 15 7 of 17 The table summarizes studies on how the menstrual cycle affects female athletic perfor- mance. Different cycle phases were analyzed in sports like soccer, basketball, and athletics using physical tests and biological analyses. Some studies found reduced performance or well-being in certain phases, while others found no significant differences. The sample of the included studies comprises a total of 152 athletes, all of whom have eumenorrheic menstrual cycles, without the need for contraceptive use of any kind among the total participants. Ten articles focus on team sports, involving 118 athletes, including 75 soccer players [20,21,24,25,27,30], 18 handball players [26,29], 14 futsal players [23], and 11 basketball players [28]. Three articles focus on individual sports, with a total of 34 women: 13 track and field athletes specializing in 800 m and 1500 m distances [31], 13 triathletes [22], and 8 judokas [32]. The duration of the studies ranges from the analysis of an entire menstrual cycle, with one month of research [21,22,26], to durations of two months [31], threemonths [20,27,32] , and even three years [30]. The main phases analyzed focus on the follicular and luteal phases, determined using tools such as blood tests, urine tests, and records in apps or calendars. The main variables examined include the phases of the menstrual cycle and sport- specific performance parameters, with performance tests specific to each sport, competition measurements, and even subjective variables, as detailed in Tables. Table 3.Analysis of the results of studies in collective sports. Authors Sports Principal Results of Performance Test Principal Results of Psychological Variables Ross et al., (2017) [20] Soccer ↔CMJ ↔3×30 sprint ↓Total distance covered in Yo-Yo IET on LF * ↑FC pre Yo-Yo test in LF * ↑3-5 ′ lactate post Yo-Yo test in FF * ↔RPE in MC Tounsi et al., (2018) [21] Soccer ↔5JT y RSA between phases ↑In the tests (5JT and RSA) when carried out in the afternoon * ↑YYIRT1 Nabo et al., (2021) [23] Futsal ↑VO2Max in FL compared to FF in Balke Maximal Test * ↑Duration in Balke Test in LF * Ross et al., (2021)

test in FF * ↔RPE in MC Tounsi et al., (2018) [21] Soccer ↔5JT y RSA between phases ↑In the tests (5JT and RSA) when carried out in the afternoon * ↑YYIRT1 Nabo et al., (2021) [23] Futsal ↑VO2Max in FL compared to FF in Balke Maximal Test * ↑Duration in Balke Test in LF * Ross et al., (2021) [24] Soccer ↑ Maintenance in zone 3 and high-intensity races in LF compared to FF * ↑ Campa et al., (2021) [25] Soccer ↔CMJ ↔20 m ↑Flexibility in the FO compared to the FF in the Sit and Reach test * Graja et al., (2022) [26] Handball ↔% dec sprint in FF and FL in RSA * ↓%dec in sprint in FF tan in FPM in RSA * ↓PP in FPM tan in FF and FL in RSA * ↓ PP in two finalsprintsin RSA in FL than in FF * ↑MVC in FF post RSA than in FPM and FF * ↓NME in vastus lateralis and rectus femoris in FPM post RSE than in FF and FL * ↓MDF in vastus lateralis and rectus femoris in FPM post RSE than in FF and FL * ↔During the three phases of CM in the Hooper Index (stress, sleep, pain, and fatigue)

Muscles2025,4, 15 8 of 17 Table 3.Cont. Authors Sports Principal Results of Performance Test Principal Results of Psychological Variables Igonin et al., (2022) [30] Handball ↓Total distance in FF than in FL * ↓Moderate speed in FF tan in FL * ↓High speed in FF than in FL * ↑Numbersprintsin FL * Sánchez et al., (2022) [27] Soccer ↔Hop test, SJ ↔40 m ↔V-cut ↓Subjective well-being in FM and FL compared to FF in the Hooper Index * ↑Fatigue in FM and LF compared to FF Gasperi et al., (2023) [28] Basketball ↑EFG% in FF than in LF * ↑REB in FF than in LF * ↑ RPE and TQRpre are related to higher EFG% with better shooting in FF and LF * Morenas-Aguilar et al., (2023) [29] Handball ↔CMJ ↔Launch speed ↔Mood and perceived pain throughout the phases evaluated by the SAM and VAS scales Abbreviations: MC (menstrual cycle); CMJ (countermovement jump); LP (luteal phase); 5JT (5-jump test); RSA (repeated sprint ability); VO2Max (maximum oxygen consumption); FP (follicular phase); DEC (deceleration); PM (premenstrual phase); PP (peak power); MVC (maximum voluntary contraction); NME (neuromuscular efficiency); MDF (median frequency); SJ (squat jump); eFG% (effective field goal percentage); REB (rebounds); RPE (rate of perceived exertion); TQRpre (total quality recovery); SAM (self-assessment manikin); VAS (visual analogue scale). Symbols: “↑” significant increase in capacity compared to other phases of the menstrual cycle, “↓” significant decrease in capacity compared to other phases of the menstrual cycle, “↔” no significant differences in capacity between phases, “*” statistically significant results (p< 0.05). Table 4.Analysis of results from studies on individual sports. Authors Sports Principal Results Of Performance Test Principal Results of Psychological Variables Shakhlina et al., (2016) [31] Athletics ↓Performance in series of 4×400 m in FM and FPM * ↑PWC170 in FL compared to FF and FOVU * ↑Blood lactate post 4×400 m in FM, FPM, and FOVU * ↑FM, FPM, and FOVU in the average HR post 4×400 * Not include the analysis of subjective variablesŠtefanovskýet al., (2016) [32] Judo ↔Test wingate ↔SJFT ↑In the first 15 seconds of SJFT in FLM * Romero-Moraleda et

The review analyzes how hormonal changes affect female athletic performance.