Influence of early follicular and mid-luteal phases of the menstrual cycle on aerobic performance, perceived exertion, and cardiac autonomic responses in eumenorrheic women: a randomized crossover trial

Influence of early follicular and mid-luteal phases of the menstrual cycle on aerobic performance, perceived exertion, and cardiac autonomic responses in eumenorrheic women: a randomized crossover trial | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Influence of early follicular and mid-luteal phases of the menstrual cycle on aerobic performance, perceived exertion, and cardiac autonomic responses in eumenorrheic women: a randomized crossover trial Nicolle Souza Dias, Adriano Eduardo Lima-Silva, Priscila Chierotti, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7773829/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 07 Jan, 2026 Read the published version in Sport Sciences for Health → Version 1 posted 9 You are reading this latest preprint version Abstract Purpose The aim of the present study was to compare aerobic performance, anthropometry, heart rate variability (HRV) pre-exercise and during graded exercise testing (GXT) on HRV threshold (HRVT), heart rate (HR) and rate of perceived exertion (RPE) between the early follicular and mid-luteal phases of the menstrual cycle. Methods Sixteen eumenorrheic women (28.8 ± 6.7 years) randomly completed two GXT (starting at 50W and increasing 25W every two minutes until exhaustion), one in the early follicular phase and another in the mid-luteal phase. Cardiac autonomic responses were continually monitored via HRV indices, recorded pre-exercise and during GXT, throughout the HRVT, HR and RPE. Results There were no differences between early follicular and mid-luteal phases for body mass (67.2 ± 10.1 vs. 66.6 ± 10.1 kg, p = 0.08), time to exhaustion (753.0 ± 193.8 vs. 730.8 ± 179.5 s, p = 0.10), peak power (181.9 ± 40.4 vs. 177.3 ± 37.4 W, p = 0.10), maximal HR (176 ± 13 vs. 176 ± 13 bpm, p = 0.80), and maximal RPE (median: 19.0 vs. 18.5 units, p = 0.37), respectively. In addition, no significant differences were observed between early follicular and mid-luteal phases for pre-exercise HRV indices ( p > 0.05). There were also no significant differences between early follicular and mid-luteal phases for power output and HR at HRVT identified during the GXT ( p > 0.05). However, the RPE at the HRVT identified using vagal index (SD1) was ( p = 0.03) higher in the early follicular phase (median: 12.0, interquartile distance 10.8 to 13.8) than in the mid-luteal phase (median: 10.5, interquartile distance 9.0 to 12.0). Conclusion In eumenorrheic women, endurance performance and cardiac autonomic responses were similar in early follicular and mid-luteal phases, but RPE of the exercise intensity at which a shift in autonomic nervous system balance occurs is higher in the early follicular phase than in the mid-luteal phase. menstrual period autonomic nervous systems perceived exertion maximal progressive exercise testing Figures Figure 1 Figure 2 INTRODUCTION The menstrual cycle is a complex physiological process lasting approximately 28–32 days and can be divided into different phases, each with distinct hormonal profiles and body temperature[ 1 , 2 ]. The early follicular phase (days 1–5) is characterized by low concentrations of both estrogen and progesterone. During the mid-to-late follicular phase (days 6–13, approximately), estrogen progressively increases until the pre-ovulatory surge in luteinizing hormone (LH) and follicle-stimulating hormone (FSH), which trigger ovulation[ 3 , 4 ]. The luteal phase can be involved in early to mid- and late-luteal phase, which follows ovulation and is marked by a substantial rise in progesterone and a moderate elevation in estrogen in the early to mid-luteal phase, with both hormones declining in the late-luteal phase[ 3 , 5 ]. While these hormonal changes are essential to prepare the endometrium for embryo implantation, they also have the potential to influence autonomic nervous system regulation [ 6 , 7 ]. Some evidence suggests that these fluctuations in sex hormones have been associated with alterations in autonomic nervous system (ANS) regulation, and the estrogen levels may enhance parasympathetic activity, whereas elevated progesterone tends to promote sympathetic dominance[ 8 – 10 ]. However, such associations depend on the specific timing of assessment within each phase, and inconsistencies remain in the literature regarding the magnitude and direction of autonomic changes across the cycle[ 6 , 7 ]. The heart rate variability (HRV) provides a non-invasive tool to examine cardiac autonomic modulation [ 11 ]. In this way, the use of HRV to indirectly assess the ANS throughout the menstrual cycle has been studied, with rest or baseline conditions[ 5 , 7 , 9 , 12 ]. While phase-related differences in HRV have been described at rest, the responses during exercise remain less clear. Exercise induces vagal withdrawal and sympathetic activation, leading to characteristic reductions in HRV and increases in HR[ 13 ]. Subsequent studies identified the HRV threshold (HRVT), further elucidating this autonomic shift during exercise (i.e., a transition from parasympathetic to sympathetic nervous system dominance) during graded or incremental exercise testing[ 14 – 17 ]. The HRVT, defined as the point of transition from parasympathetic to sympathetic predominance, has been proposed as a surrogate of ventilatory and lactate thresholds, offering a non-invasive and cost-effective alternative[ 14 , 16 ]. However, the extent to which menstrual cycle phases influence the HRVT is largely unknown. Maximal graded exercise tests (GXT) are widely used to evaluate aerobic performance, providing important information about physiological responses to incremental exercise for exercise prescription. In this context, simple and non-invasive measures such as heart rate (HR) and ratings of perceived exertion (RPE) are commonly employed to complement metabolic and ventilatory markers [ 16 , 18 – 20 ]. While HR reflects the balance between sympathetic and parasympathetic activity, RPE captures the integrative perception of effort by incorporating cardiovascular, respiratory, neuromuscular and psychobiological demands[ 18 , 20 – 22 ]. These variables offer a practical and cost-effective approach to monitor exercise intensity and tolerance, particularly in settings where invasive or laboratory-based measures are less feasible. In this way, studies have investigated the influence of menstrual cycle phases on aerobic performance, but the results remain inconclusive [ 23 – 25 ]. Some studies suggest that higher estrogen levels in the follicular phase may favour aerobic performance by enhancing carbohydrate metabolism, promoting vasodilation, and improving oxygen delivery to muscles [ 26 , 27 ]. Otherwise, the luteal phase, when progesterone is predominant, has been linked to increased body temperature, greater fat utilisation, and possible impairments in thermoregulation, which may reduce exercise tolerance [ 26 , 28 , 29 ]. Nevertheless, meta-analyses show that these effects are usually small and highly variable among individuals, highlighting the importance of further research under controlled conditions[ 27 ]. Although there is no consensus in the literature, the hormonal profile of the early follicular phase, marked by low estrogen and low progesterone[ 28 ], we consider the hypothesis to favour aerobic performance, higher resting vagal HRV indices and a delayed HRV threshold, accompanied by lower HR and RPE values at the HRVT. In contrast, in the mid-luteal phase, the elevated estrogen, progesterone and body temperature are expected to impair aerobic performance compared to the early follicular phase, with higher global or sympathetic indices from HRV, HR and RPE values at HRVT. Thus, the aim of the present study was to examine the influence of the early follicular and mid-luteal phases of the menstrual cycle on aerobic performance, cardiac autonomic responses by HRV in pre-exercise and HRV threshold during GXT, as well as HR and RPE at HRVT. responses and subjective perception of effort. METHODS Participants Sixteen healthy women (28.8 ± 6,8 years, 166.4 ± 7.8 cm, and 28.0 ± 2.9 days of menstrual cycle; ≥ 150 min − 1 .week physical activity) were included in the experimental phase and were randomized, in a crossover design, to undergo evaluation in both the early follicular and mid-luteal phases of the menstrual cycle, performed during visits 2 and 3. But initially, 36 women volunteered to participate in the study. Of these, 14 did not meet the inclusion criteria and 3 declined to participate. Consequently, 19 women initiated the study protocol, which included risk assessment procedures, anthropometric measurements (body mass and stature), resting HRV assessment, a familiarisation session with GXT including HR and RPE measurements, and monitoring of three consecutive menstrual cycles. During this period, 3 participants discontinued participation due to pregnancy (n = 1), amenorrhea (n = 1), or withdrawal (n = 1). The sample size of a minimum of 15 women was estimated based on a previous study that found an effect size of 0.92 comparing endurance performance in GXT between the follicular and luteal phases[ 25 ] and adopting an alpha of 5% and a power of 95% (G*Power software, version 3.1.9.6). Participants were recruited voluntarily and through the researchers' social media (@ciclo.vfc), and flyers were posted at the University Campus. As inclusion criteria, participants were required to be aged between 18 and 40 years, not using hormonal contraceptives, and be engaged in exercise programs at least 2 times per week and ≥ 150 min − 1 .week. Participants were excluded from the study if they had one or more positive responses in the Physical Activity Readiness Questionnaire (PAR-Q+), indicating moderate or high risk according to the decision tree analysis for cardiorespiratory fitness assessments [ 30 ]. The use of medications that affect the cardiovascular system, eating disorders, polycystic ovary syndrome, or diagnosed endometriosis, were also used as exclusion criteria. Participants agreed to participate in the study by signing an informed consent form, and the local ethics committee (Human Research Ethics Committee of the University) approved the study (CAAE number: 69341323.7.0000.0108), which meets the Declaration of Helsinki for research involving humans. Experimental Design Participants attended the laboratory three times (see Fig. 1 ). On the first visit, researchers explained the experimental procedures and clarified potential questions about the study. After signing an informed consent form, participants were instructed to track three consecutive menstrual cycles (~ 12 weeks). In addition, their exercise-associated risk was assessed using the PAR-Q + and risk assessment for cardiorespiratory fitness [ 30 ]. Participants were also familiarized with the experimental procedures during this first visit to the graded exercise test (GXT) procedures. On the 2nd and 3rd visits, participants performed a GXT, in randomized crossover order, in the early follicular to mid-luteal or mid-luteal to early follicular phases, following one or two consecutive menstrual cycles. The cardiac autonomic responses were measured throughout R-R interval recordings on the pre-exercise condition and throughout GXT to further HRV analysis at rest and HRVT. The randomization was controlled by a blinded researcher who was not aware of the study aims. All tests were performed in a climate-controlled environment, with a temperature of 22 ± 1 ºC. The participants were instructed to maintain their usual dietary habits on the test days and to consume a meal at least 2 hours before testing. However, the participants were instructed to avoid caffeine, alcohol, and strenuous physical activity for 24 hours before each test. *** INSERT FIGURE *** Anthropometric Measurements Body mass (kg) and height (cm) were measured during both the early follicular and luteal phases prior to GXT testing. Body mass was assessed using a calibrated digital scale, with participants wearing light clothing and no shoes. Height was measured using a stadiometer, with participants standing upright, heels together, and head in the Frankfurt plane. Body mass index (BMI) was calculated as weight in kilograms divided by the square of height in meters (kg/m²). Menstrual Cycle Tracking Three consecutive menstrual cycles were monitored using an online questionnaire [ 31 ]. The regularity and phases of the menstrual cycle were determined using the day-counting method [ 3 , 32 ]. The early follicular phase was considered to occur between days 2 and 3 of the cycle. The mid-luteal phase was defined as the last 10 days before the onset of the next menstruation, with the test performed between days 5 and 8 before the expected bleeding, corresponding to the anticipated peak in progesterone levels [ 2 , 33 , 34 ]. To access menstrual cycle data, a questionnaire was sent weekly using a calendar app installed on the participant’s smartphone. Graded exercise test (GXT) The GXT tests were scheduled according to the participant’s availability, ensuring that they were performed at the same time of day (± 1 hour), to minimize any potential influence of circadian rhythm. On all test days, HRV measures were taken in pre-exercise rest conditions that included 5 minutes of free breathing in a supine position. The maximal GXT was performed on a cycle ergometer (WATTBIKE®, Pro-Trainer model). Saddle and handlebar height and horizontal adjustments were performed on the first visit and were repeated during the experimental tests during visits 2 and 3. The GXT started with a warm-up, cycling at 50 W for five minutes. Subsequently, the work rate was increased by 25 W every two minutes, with participants maintaining cycling cadence from 60 to 80 rpm, until the attainment of voluntary exhaustion or failure to maintain the minimum cadence (i.e., 60 rpm) for longer than 10 s despite verbal encouragement. The maximal HR (HRmax) and HR at each stage were determined as the average of the final 10 s of the recordings. Time to exhaustion (TTE) was the total duration the individual was able to sustain progressive increases in workloads during a graded exercise test until volitional fatigue. The peak power output was the highest mechanical power achieved during the GXT before termination due to exhaustion. When the last stage was incomplete, the peak power output was calculated as the fractional time completed in the last stage multiplied by the increment rate [ 35 ]. HRV was analysed to consider all visits in the conditions at rest (5 minutes in a supine position with minimal light and noise exposure) with a self-selected breathing pattern and throughout the GXT test. The GXT consisted of an incremental test until exhaustion, with the R-R interval recordings being saved for the HR and HRV analysis. And the RPE was recorded during the last 30 seconds of each stage using the Borg 15-point scale (6–20) [ 18 ]. The maximum RPE (RPEmax) on the GXT represents the highest subjective perception of effort reported by the participant. Heart rate variability and Heart rate variability threshold The R-R intervals were recorded using the EliteHRV® application to assess cardiac autonomic responses, considering HR (bpm) and HRV parameters, using a chest strap sensor Polar H10 (Polar Electro Oy, Kempele, Finland) [ 36 ]. The H10 sensor was positioned at the xiphoid process level and the strip was moistened to improve conductivity. The R-R interval data were exported and analysed using Kubios HRV Standard® software (version 3.4.0) [ 37 ]. A filtering process was applied to eliminate potential noise from ectopic beats or device reading errors, with a correction threshold not exceeding 2% of the R-R intervals combined with visual inspection. The HRV analysis included time, nonlinear, and frequency domains. The time-domain analyses included: 1) SDNN: standard deviation of all normal R-R intervals recorded as a global autonomic index; and 2) rMSSD: root mean square of the successive differences between adjacent normal R-R intervals. The nonlinear-domain analyses included Poincaré plot analysis, where SD1 and SD2 represent the standard deviation of short- and long-term beat-to-beat variability, respectively. The rMSSD and SD1 were considered as parasympathetic nervous system indices, while SDNN and SD2 were considered as global autonomic HRV indices [ 11 ]. Finally, the frequency-domain analyses included low- and high-frequency analyses. For this, normal-to-normal R-R intervals were corrected and interpolated using a cubic method at a sampling frequency of 2 Hz. Spectral power density was estimated using the Fast Fourier Transform with Welch’s windowing method. The low-frequency component (LF: 0.04–0.15 Hz) was considered indicative of both sympathetic and parasympathetic modulation, while the high-frequency component (HF: 0.15–0.40 Hz) is primarily associated with parasympathetic activity and influenced by respiratory frequency. The LF and HF values were expressed in absolute units (ms²) and log-transformed values (log-ms²). The sympathovagal balance was represented by the LF/HF ratio [ 11 ] The HRV threshold was determined using visual inspection by two independent researchers who were unaware which menstrual cycle phase they were analysing. A third evaluator would be consulted in case of disagreement [ 14 , 38 , 39 ]. However, as two researchers agreed in all analysis, a third evaluator was not necessary. Given the distinct physiological significance of the HRV indices, HRV threshold was analysed in two different ways, one using vagal indices (HRVT SD1 ) and another using global indices (HRVT SDNN ), analysing HRV data every 40 seconds. Briefly, the workload at which HRV stabilization occurred, characterized by the absence of large declines in the SDNN panel and SD1 indices panel, separately, was considered the HRV threshold [ 14 ], as show in the Fig. 2 . *** INSERT FIGURE *** Statistical analysis Normality in data distribution was checked using the Shapiro-Wilk test. Normally-distributed variables, such as power output measures, HR at the HRV threshold, time to exhaustion, and peak power, were compared between early follicular and luteal phases using the paired t-test. Non-normally-distributed variables, such as HRV measures [HF (log) and LF/HF ratio pre-exercise; and LF (ms 2 ), HF (ms 2 ), and, or ordinal qualitative variables, such as RPE at HRVT measures, were compared using the Wilcoxon signed-rank test. As one data point was missing in the follicular phase for one participant, an intention-to-treat analysis was applied, with missing data imputed using the expected maximization procedure. The significance level was set at p < 0.05. For parametric comparisons, the effect sizes (ES) using the Cohen's d effect size ( d -Cohen) was used to quantify the standardized differences between means, with values of 0.2, 0.5, and 0.8 indicating small, medium, and large effects, respectively [ 40 ]. For non-parametric comparisons, the effect size was calculated using ( r = z ÷ √N) , derived from the Z statistic. This approach standardizes the ES for the r values to a range between − 1 and 1, with values of 0.1, 0.3, and 0.5 representing small, medium, and large effects, respectively [ 41 ]. To facilitate the interpretation of the results, the negative signs of the ES results were removed. All statistical analyses were performed using SPSS software (version 30.0). RESULTS Body mass and parameters obtained in the GXT during follicular and luteal phases are described in Table 1 . There were no significant differences and small effect sizes for body mass, time to exhaustion, peak power, HRmax, and RPEmax between follicular and luteal phases. Table 1 Data on body mass and parameters obtained in the graded exercise test in early follicular and mid-luteal phases of the menstrual cycle. Early Follicular phase Mid-Luteal phase p ES Body mass (kg) 67.2 ± 10.1 66.6 ± 10.1 0.08 0.48 Time to exhaustion (s) 753.0 ± 193.8 730.8 ± 179.5 0.10 0.43 Peak power (W) 181.9 ± 40.4 177.3 ± 37.4 0.10 0.43 HRmax (bpm) 175.6 ± 13,0 176.0 ± 13.1 0.80 0.26 RPEmax (units) 19.0 (17.3–19.0) 18.5 (17.3–19.0) 0.37 0.22 # Note: Data are means ± standard deviation (± SD) for body mass (kg), time to exhaustion (s), peak power (W), and HRmax (bpm). Median and quartiles 1 and 3 (q1-q3) for RPEmax (Borg 6–20). p : p-value; Cohen’s d or r # [from Z (-0.89, p = 0.37) statistic] effect sizes ( ES ) for dependent samples. ***INSERT Table 1 *** The power output, heart rate, and RPE at the HRV thresholds are presented in Table 2 . There were no differences for power output and HR at HRVT SDNN or HRVT SD1 between follicular and luteal phases ( p > 0.05). The RPE at the HRVT SD1 ( p 0.05), was significantly higher in the follicular than in the luteal phase. Table 2 Power output (W), heart rate (bpm), and RPE (units) at the heart rate variability threshold identified by global autonomic parameters (SDNN) and the vagally mediated index (SD1) during a graded exercise test performed in the early follicular and luteal phases of the menstrual cycle. Earl Follicular phase Mid-Luteal phase p ES Power output HRVT SDNN (W) 144.7 ± 34.2 134.8 ± 30.9 0.22 0.32 HRVT SD1 (W) 123.7 ± 29.7 114.0 ± 24.5 0.11 0.42 Heart rate HR-HRVT SDNN (bpm) 150 ± 16 148 ± 12 0.74 0.08 HR-HRVT SD1 (bpm) 140 ± 11 137 ± 9 0.38 0.22 RPE RPE-HRVT SDNN (units) 13.5 (12.3–15.0) 13.0 (10.5–14.0) 0.18 0.33 # RPE-HRVT SD1 (units) 12.0 (10.8–13.8) 10.5 (9.0–12.0) 0.03* 0.55 # Note : Data are means and standard deviation (± SD) for power output (W) and heart rate (bpm) and median (quartiles 1 and 3) for RPE. p : p-value; Cohen’s d or r # [from Z (RPE-HRVT sdnn : -1.34; RPE-HRVT sd1/rmssd : -2.22) statistic] effect sizes ( ES ) for dependent samples. *Significant difference between follicular and luteal phases ( p 0.05) for any cardiac autonomic responses analysed by HRV. Table 3 Pre-exercise HRV response to graded exercise test performed in the early follicular and luteal phases of the menstrual cycle. Early Follicular phase Mid-Luteal phase p ES Pre-exercise HR (bpm) 67 ± 13 67 ± 10 0.84 0.05 iRR (ms) 913.1 ± 191.1 913.2 ± 127.3 0.99 0.001 SDNN (ms) 24.7 ± 6.2 25.6 ± 4.7 0.46 0.19 RMSSD (ms) 24.6 ± 7.4 27.3 ± 6.4 0.14 0.39 LF (ms 2 ) 360.0 ± 269.4 284.1 ± 167.2 0.29 0.27 LF (log) 5.6 ± 0.7 5.4 ± 0.7 0.33 0.25 HF (ms 2 ) 273.9 ± 129.3 298.7 ± 117.2 0.55 0.15 HF (log) 5.8 (5.1–6.0) 5.8 (5.4–6.0) 0.72 0.09 LF/HF ratio 1.1 (0.8–2.9) 0.9 (0.4–1.4) 0.30 0.26 SD1 (ms) 17.6 ± 5.9 19.3 ± 4.6 0.13 0.40 SD2 (ms) 29.4 ± 8.4 30.3 ± 6.0 0.59 0.14 Note : Data are means and standard deviation (± SD) when using the paired t-test. Median and quartiles 1 and 3 (q1 – q3) when using the Wilcoxon signed-rank test. Effect sizes (ES) from Cohen’s d or r effect size for dependent samples. ***INSERT Table 3 *** DISCUSSION The present study investigated the effects of early follicular and mid-luteal phases of the menstrual cycle on pre- and during GTX on cardiac autonomic responses and aerobic performance. The main findings of the present study were: 1) chronotropic responses, HRV pre-exercise and HRVT were similar between early follicular and mid-luteal phases; 2) parameters of endurance performance (time to exhaustion and peak power output) were similar in both phases analysed; 3) perceived exertion at HRVT SD1 was higher in the early follicular phase than mid-luteal phase. During physical exercise, the HR increase is mainly regulated by the sympathetic and parasympathetic nervous systems. Exercise intensity is directly proportional to vagal withdrawal and sympathetic activity [ 13 , 42 ]. As women experience fluctuations in oestrogen and progesterone throughout the menstrual cycle, the fluctuations in these hormones couple [ 29 , 43 ]. In this way, it was expected that hormonal changes might explain the autonomic differences observed between menstrual phases. Pre-exercise HRV responses did not differ significantly between the early follicular and mid-luteal phases. All time-domain, nonlinear, and frequency-domain HRV indices remained statistically unchanged across the phases studied, similar to what was found by Leicht et al. (2003)[ 9 ] at rest. However, these findings contrast with studies indicating increased parasympathetic modulation during the follicular phase due to elevated oestrogen levels[ 6 ]. For instance, Brar et al. (2015)[ 8 ] examined resting cardiac autonomic function in eumenorrheic women across three menstrual cycle phases and found significant differences in mean R-R intervals and HR between the follicular phase (2nd day of menstrual phase) and mid-luteal phase (21st day, secretory phase), which were observed differently in the present study, but close to early follicular and mid-luteal phase. These differences, which contrast with the findings of the present study but are physiologically close to the early follicular and mid-luteal phases, were attributed to increased vagal activity during the follicular phase, likely mediated by higher oestrogen levels, and to elevated progesterone during the luteal phase, which may attenuate vagal tone[ 8 ]. In contrast, Leicht et al. (2003)[ 9 ] reported higher HR values during ovulation but found no significant differences in HR between the menstrual and luteal phases, nor in HRV measures at rest across the menstrual cycle. In addition, Leicht et al. (2003)[ 9 ] observed a positive correlation between HRV (vagal and global indices) and 17b-oestradiol concentrations at rest during the ovulatory phase, but this result was not observed in menses (equivalent to early follicular phase) or luteal phases, probably due to inhibitory influences of progesterone, FSH and LH and on oestrogen. These suggest that the interplay between oestrogen may influence as a protective effect of hormonal fluctuations on HRV and autonomic regulation. In the present study, the ovulatory phase was not assessed, given the methodological difficulty arising from a lack of a precise method to track days in the menstrual cycle and the HRV at rest, as similar in both phases. During exercise, the HRVT identified by global (SDNN) and vagal (SD1) indices occurred at similar workloads and HR in both phases. These findings suggest that the autonomic transition point from parasympathetic to sympathetic dominance during incremental exercise is not phase-dependent, considering the early follicular and mid-luteal phases, unlike previously hypothesised. There are many HRVT methodologies which, in general, are often correlated with lactate and ventilatory thresholds [ 16 , 17 , 44 ]. In the current study, no differences were observed between the early follicular phase and luteal phase for HR at HRVT SD1 and HRVT SDNN , HRmax, or time to exhaustion. These findings can be compared, in part, and considered consistent with studies analysing cardiorespiratory measures and ventilatory thresholds [ 1 , 27 , 45 – 48 ]. RPE showed a significant difference at the HRVT SD1 , with higher values during the early follicular phase compared to the mid-luteal phase. This aligns with Delp et al. (2024), 19, who found (using a similar analysis to the present study) that RPE was higher during the early follicular phase compared to ovulation and the luteal phase in both trained and untrained women. Similarly, Hooper et al. (2011) [ 49 ] reported higher RPE in the follicular phase in sedentary women during moderate intensity cycling. This finding highlights the sensitivity of RPE as a measure of effort perception across menstrual phases, beyond simple stage-by-stage comparisons. Curiously, the higher values of the RPE responses significantly with a moderate effect size at the HRVT SD1 during the early follicular phase, compared to the mid-luteal phase, may be due to the influence of psychobiological factors, reflected in submaximal intensities[ 22 ], such as mood disturbances, decreased motivation, and heightened perception of physical discomfort, which are frequently reported by women during the early follicular phase and can modulate the central processing of effort perception, even in the absence of significant physiological alterations[ 50 ]. The findings of the current study indicate that the menstrual cycle phase does not significantly influence aerobic performance during maximal progressive exercise observed in GXT, as evidenced by similar values for time to exhaustion [ 1 , 25 ] HR, and power output from workload at the HRVT SD1 and HRVT SDNN . These results align with Taipale-Mikkonen et al., (2021)[ 51 ], who found no significant differences in HR, %HRmax, blood lactate, or oxygen consumption (VO 2 ) between menstrual phases in eumenorrheic women and oral contraceptive users. Other studies have also reported no significant differences in physiological and performance parameters across the menstrual cycle [ 47 , 52 – 54 ]. Variations in performance during the menstrual cycle may stem from changes in exercise metabolism driven by fluctuations in ovarian hormones [ 33 , 55 ]. For example, Rael et al. (2021)[ 56 ] compared cardiorespiratory responses to exercise in eumenorrheic women, oral contraceptive users, and postmenopausal women. Tests were conducted during periods of low hormonal activity (e.g., during menstruation for eumenorrheic women). The authors found that postmenopausal women exhibited cardiovascular responses similar to eumenorrheic women and oral contraceptive users, suggesting that hormonal fluctuations may not always translate into significant performance differences [ 56 ]. Findlay et al. (2020)[ 50 ] explored the impact of the menstrual cycle on athletic performance in rugby players, finding that 93% of athletes reported negative physical or psychological symptoms associated with their cycle. These symptoms, including decreased energy, cramps, and mood disturbances, often affect training and competition. The authors emphasized the importance of individualized approaches and cycle monitoring to mitigate negative effects and optimize performance [ 50 ]. Although performance at maximum effort did not differ, considering the early follicular and mid-luteal phases of the menstrual cycle, some perceptual submaximal indicators (i.e. RPE) proved to be more sensitive to possible known changes arising during the different phases of the menstrual cycle in women. The current study presents some limitations. First, menstrual cycle tracking was performed using the day-counting method, which may not be as precise as basal temperature tracking or hormonal assays. Second, the study was conducted with eumenorrheic women who are physically active, which does not allow the application of the findings to oral contraceptive users or postmenopausal women. Third, individual variability in hormone levels and responses to exercise was not measured, which may have influenced physiological and performance outcomes. CONCLUSION Our findings indicate no differences in pre-exercise and during GXT on cardiac autonomic responses between early follicular and mid-luteal phases of the menstrual cycle in physically active eumenorrheic women. However, the perceived effort of the exercise intensity at which a shift in vagal-mediated autonomic balance occurs was higher in the early follicular phase than in the mid-luteal phase. From a practical perspective, these results suggest that while objective physiological markers of cardiac autonomic responses at rest and during GXT remain stable across menstrual phases, RPE in submaximal conditions may vary. Therefore, coaches, clinicians, and exercise professionals should consider that women may experience differences in effort perception depending on the menstrual cycle phase, even when physiological responses remain unchanged. This insight highlights the importance of integrating both physiological and perceptual measures when prescribing and monitoring exercise in physically active female populations. Abbreviations bpm beats per minute d -Cohen Cohen’s effect size value ES effect size value FSH follicle-stimulating hormone GXT graded exercise testing HF high frequency HR heart rate HRmax maximal heart rate HRV heart rate variability HRVT heart rate variability threshold HRVT SD1 vagal index to determine heart rate variability threshold HRVT SDNN global index to determine heart rate variability threshold Hz Hertz LH luteinizing hormone LF low frequency LF/HF sympathovagal balance PAR-Q+ version plus of the Physical Activity Readiness Questionnaire RPE rate of perceived exertion RPEmax maximal value of rate of perceived exertion in exercise testing R-R intervals of R-waves from electrocardiogram signals rMSSD root mean square of the successive differences between adjacent normal R-R intervals SDNN standard deviation of all normal R-R intervals SD1 standard deviation of short-term beat-to-beat variability from Poincaré plotting SD2 standard deviation of long-term beat-to-beat variability from Poincaré plotting VO 2 volume of oxygen consumed per unit of time W power expressed in watts Declarations Conflict of interest None of the authors has any conflicts of interest related to this manuscript. Author Contribution Authors contributions:All the authors participated critically in the important intellectual content and in revising the manuscript “Influence of early follicular and mid-luteal phases of the menstrual cycle on aerobic performance, perceived exertion, and cardiac autonomic responses in eumenorrheic women: a randomized crossover trial.”. The authors, NSD, PC, and LFSC, were specifically involved in data collection and statistical analysis. All authors approved the final manuscript and take full responsibility for its content and integrity. Acknowledgement We would like to thank all the volunteers who participated in the study. We also thank CAPES, which provided the scholarship to the author Nicolle Souza Dias. Data Availability The datasets generated and analyzed during the current study are not publicly available due to ethical restrictions, as they contain information that could compromise the privacy of research participants. In accordance with the approval granted by the Institutional Research Ethics Committee (Protocol number: CAAE number: 69341323.7.0000.0108), access to the data is restricted. However, anonymized datasets are available from the corresponding author upon reasonable request and subject to compliance with ethical and legal requirements. References Lebrun CM, McKenzie DC, Prior JC, Taunton JE. Effects of menstrual cycle phase on athletic performance. Med Sci Sports Exerc. 1995;27. Sims ST, Heather AK. Myths and Methodologies: Reducing scientific design ambiguity in studies comparing sexes and/or menstrual cycle phases. Exp Physiol. 2018;103:1309–17. https://doi.org/10.1113/EP086797. Janse de Jonge X, Thompson B, Han A. Methodological Recommendations for Menstrual Cycle Research in Sports and Exercise. Med Sci Sports Exerc. 2019;51:2610–7. https://doi.org/10.1249/MSS.0000000000002073. Elliott-Sale KJ, Minahan CL, de Jonge XAKJ, Ackerman KE, Sipilä S, Constantini NW, et al. 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Cardiorespiratory response to exercise in endurance-trained premenopausal and postmenopausal females. Eur J Appl Physiol. 2021;121:903–13. https://doi.org/10.1007/S00421-020-04574-4/METRICS. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 07 Jan, 2026 Read the published version in Sport Sciences for Health → Version 1 posted Editorial decision: Revision requested 11 Nov, 2025 Reviews received at journal 07 Nov, 2025 Reviews received at journal 29 Oct, 2025 Reviewers agreed at journal 27 Oct, 2025 Reviewers agreed at journal 20 Oct, 2025 Reviewers invited by journal 14 Oct, 2025 Editor assigned by journal 04 Oct, 2025 Submission checks completed at journal 04 Oct, 2025 First submitted to journal 03 Oct, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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1","display":"","copyAsset":false,"role":"figure","size":208353,"visible":true,"origin":"","legend":"\u003cp\u003eExperimental study design.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7773829/v1/8926766808161410d441998f.png"},{"id":94587298,"identity":"03ad334a-ef17-4a77-924d-b57c111b791a","added_by":"auto","created_at":"2025-10-28 18:18:03","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":78064,"visible":true,"origin":"","legend":"\u003cp\u003eHeart rate variability threshold panels to GXT.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7773829/v1/2face942434acbec7c13c8d4.png"},{"id":100069083,"identity":"a93e193e-0734-4425-8758-4de36ff62160","added_by":"auto","created_at":"2026-01-12 16:08:31","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1110216,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7773829/v1/ec2328a4-c68f-436f-a9de-8a8284c31dfb.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eInfluence of early follicular and mid-luteal phases of the menstrual cycle on aerobic performance, perceived exertion, and cardiac autonomic responses in eumenorrheic women: a randomized crossover trial\u003c/p\u003e","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eThe menstrual cycle is a complex physiological process lasting approximately 28\u0026ndash;32 days and can be divided into different phases, each with distinct hormonal profiles and body temperature[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. The early follicular phase (days 1\u0026ndash;5) is characterized by low concentrations of both estrogen and progesterone. During the mid-to-late follicular phase (days 6\u0026ndash;13, approximately), estrogen progressively increases until the pre-ovulatory surge in luteinizing hormone (LH) and follicle-stimulating hormone (FSH), which trigger ovulation[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. The luteal phase can be involved in early to mid- and late-luteal phase, which follows ovulation and is marked by a substantial rise in progesterone and a moderate elevation in estrogen in the early to mid-luteal phase, with both hormones declining in the late-luteal phase[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eWhile these hormonal changes are essential to prepare the endometrium for embryo implantation, they also have the potential to influence autonomic nervous system regulation [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Some evidence suggests that these fluctuations in sex hormones have been associated with alterations in autonomic nervous system (ANS) regulation, and the estrogen levels may enhance parasympathetic activity, whereas elevated progesterone tends to promote sympathetic dominance[\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. However, such associations depend on the specific timing of assessment within each phase, and inconsistencies remain in the literature regarding the magnitude and direction of autonomic changes across the cycle[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe heart rate variability (HRV) provides a non-invasive tool to examine cardiac autonomic modulation [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. In this way, the use of HRV to indirectly assess the ANS throughout the menstrual cycle has been studied, with rest or baseline conditions[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. While phase-related differences in HRV have been described at rest, the responses during exercise remain less clear. Exercise induces vagal withdrawal and sympathetic activation, leading to characteristic reductions in HRV and increases in HR[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Subsequent studies identified the HRV threshold (HRVT), further elucidating this autonomic shift during exercise (i.e., a transition from parasympathetic to sympathetic nervous system dominance) during graded or incremental exercise testing[\u003cspan additionalcitationids=\"CR15 CR16\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. The HRVT, defined as the point of transition from parasympathetic to sympathetic predominance, has been proposed as a surrogate of ventilatory and lactate thresholds, offering a non-invasive and cost-effective alternative[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. However, the extent to which menstrual cycle phases influence the HRVT is largely unknown.\u003c/p\u003e\u003cp\u003eMaximal graded exercise tests (GXT) are widely used to evaluate aerobic performance, providing important information about physiological responses to incremental exercise for exercise prescription. In this context, simple and non-invasive measures such as heart rate (HR) and ratings of perceived exertion (RPE) are commonly employed to complement metabolic and ventilatory markers [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan additionalcitationids=\"CR19\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. While HR reflects the balance between sympathetic and parasympathetic activity, RPE captures the integrative perception of effort by incorporating cardiovascular, respiratory, neuromuscular and psychobiological demands[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan additionalcitationids=\"CR21\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. These variables offer a practical and cost-effective approach to monitor exercise intensity and tolerance, particularly in settings where invasive or laboratory-based measures are less feasible.\u003c/p\u003e\u003cp\u003eIn this way, studies have investigated the influence of menstrual cycle phases on aerobic performance, but the results remain inconclusive [\u003cspan additionalcitationids=\"CR24\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Some studies suggest that higher estrogen levels in the follicular phase may favour aerobic performance by enhancing carbohydrate metabolism, promoting vasodilation, and improving oxygen delivery to muscles [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Otherwise, the luteal phase, when progesterone is predominant, has been linked to increased body temperature, greater fat utilisation, and possible impairments in thermoregulation, which may reduce exercise tolerance [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Nevertheless, meta-analyses show that these effects are usually small and highly variable among individuals, highlighting the importance of further research under controlled conditions[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eAlthough there is no consensus in the literature, the hormonal profile of the early follicular phase, marked by low estrogen and low progesterone[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e], we consider the hypothesis to favour aerobic performance, higher resting vagal HRV indices and a delayed HRV threshold, accompanied by lower HR and RPE values at the HRVT. In contrast, in the mid-luteal phase, the elevated estrogen, progesterone and body temperature are expected to impair aerobic performance compared to the early follicular phase, with higher global or sympathetic indices from HRV, HR and RPE values at HRVT.\u003c/p\u003e\u003cp\u003eThus, the aim of the present study was to examine the influence of the early follicular and mid-luteal phases of the menstrual cycle on aerobic performance, cardiac autonomic responses by HRV in pre-exercise and HRV threshold during GXT, as well as HR and RPE at HRVT. responses and subjective perception of effort.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eParticipants\u003c/h2\u003e\u003cp\u003eSixteen healthy women (28.8\u0026thinsp;\u0026plusmn;\u0026thinsp;6,8 years, 166.4\u0026thinsp;\u0026plusmn;\u0026thinsp;7.8 cm, and 28.0\u0026thinsp;\u0026plusmn;\u0026thinsp;2.9 days of menstrual cycle; \u0026ge; 150 min\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e.week physical activity) were included in the experimental phase and were randomized, in a crossover design, to undergo evaluation in both the early follicular and mid-luteal phases of the menstrual cycle, performed during visits 2 and 3. But initially, 36 women volunteered to participate in the study. Of these, 14 did not meet the inclusion criteria and 3 declined to participate. Consequently, 19 women initiated the study protocol, which included risk assessment procedures, anthropometric measurements (body mass and stature), resting HRV assessment, a familiarisation session with GXT including HR and RPE measurements, and monitoring of three consecutive menstrual cycles. During this period, 3 participants discontinued participation due to pregnancy (n\u0026thinsp;=\u0026thinsp;1), amenorrhea (n\u0026thinsp;=\u0026thinsp;1), or withdrawal (n\u0026thinsp;=\u0026thinsp;1). The sample size of a minimum of 15 women was estimated based on a previous study that found an effect size of 0.92 comparing endurance performance in GXT between the follicular and luteal phases[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] and adopting an alpha of 5% and a power of 95% (G*Power software, version 3.1.9.6). Participants were recruited voluntarily and through the researchers' social media (@ciclo.vfc), and flyers were posted at the University Campus. As inclusion criteria, participants were required to be aged between 18 and 40 years, not using hormonal contraceptives, and be engaged in exercise programs at least 2 times per week and \u0026ge;\u0026thinsp;150 min\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e.week. Participants were excluded from the study if they had one or more positive responses in the Physical Activity Readiness Questionnaire (PAR-Q+), indicating moderate or high risk according to the decision tree analysis for cardiorespiratory fitness assessments [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. The use of medications that affect the cardiovascular system, eating disorders, polycystic ovary syndrome, or diagnosed endometriosis, were also used as exclusion criteria. Participants agreed to participate in the study by signing an informed consent form, and the local ethics committee (Human Research Ethics Committee of the University) approved the study (CAAE number: 69341323.7.0000.0108), which meets the Declaration of Helsinki for research involving humans.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eExperimental Design\u003c/h3\u003e\n\u003cp\u003eParticipants attended the laboratory three times (see Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). On the first visit, researchers explained the experimental procedures and clarified potential questions about the study. After signing an informed consent form, participants were instructed to track three consecutive menstrual cycles (~\u0026thinsp;12 weeks). In addition, their exercise-associated risk was assessed using the PAR-Q\u0026thinsp;+\u0026thinsp;and risk assessment for cardiorespiratory fitness [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Participants were also familiarized with the experimental procedures during this first visit to the graded exercise test (GXT) procedures. On the 2nd and 3rd visits, participants performed a GXT, in randomized crossover order, in the early follicular to mid-luteal or mid-luteal to early follicular phases, following one or two consecutive menstrual cycles. The cardiac autonomic responses were measured throughout R-R interval recordings on the pre-exercise condition and throughout GXT to further HRV analysis at rest and HRVT. The randomization was controlled by a blinded researcher who was not aware of the study aims. All tests were performed in a climate-controlled environment, with a temperature of 22\u0026thinsp;\u0026plusmn;\u0026thinsp;1 \u0026ordm;C. The participants were instructed to maintain their usual dietary habits on the test days and to consume a meal at least 2 hours before testing. However, the participants were instructed to avoid caffeine, alcohol, and strenuous physical activity for 24 hours before each test.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\n\u003ch3\u003e*** INSERT FIGURE *** \u003c/h3\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003eAnthropometric Measurements\u003c/h2\u003e\u003cp\u003eBody mass (kg) and height (cm) were measured during both the early follicular and luteal phases prior to GXT testing. Body mass was assessed using a calibrated digital scale, with participants wearing light clothing and no shoes. Height was measured using a stadiometer, with participants standing upright, heels together, and head in the Frankfurt plane. Body mass index (BMI) was calculated as weight in kilograms divided by the square of height in meters (kg/m\u0026sup2;).\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eMenstrual Cycle Tracking\u003c/h3\u003e\n\u003cp\u003eThree consecutive menstrual cycles were monitored using an online questionnaire [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. The regularity and phases of the menstrual cycle were determined using the day-counting method [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. The early follicular phase was considered to occur between days 2 and 3 of the cycle. The mid-luteal phase was defined as the last 10 days before the onset of the next menstruation, with the test performed between days 5 and 8 before the expected bleeding, corresponding to the anticipated peak in progesterone levels [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. To access menstrual cycle data, a questionnaire was sent weekly using a calendar app installed on the participant\u0026rsquo;s smartphone.\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eGraded exercise test (GXT)\u003c/h2\u003e\u003cp\u003eThe GXT tests were scheduled according to the participant\u0026rsquo;s availability, ensuring that they were performed at the same time of day (\u0026plusmn;\u0026thinsp;1 hour), to minimize any potential influence of circadian rhythm. On all test days, HRV measures were taken in pre-exercise rest conditions that included 5 minutes of free breathing in a supine position. The maximal GXT was performed on a cycle ergometer (WATTBIKE\u0026reg;, Pro-Trainer model). Saddle and handlebar height and horizontal adjustments were performed on the first visit and were repeated during the experimental tests during visits 2 and 3. The GXT started with a warm-up, cycling at 50 W for five minutes. Subsequently, the work rate was increased by 25 W every two minutes, with participants maintaining cycling cadence from 60 to 80 rpm, until the attainment of voluntary exhaustion or failure to maintain the minimum cadence (i.e., 60 rpm) for longer than 10 s despite verbal encouragement.\u003c/p\u003e\u003cp\u003eThe maximal HR (HRmax) and HR at each stage were determined as the average of the final 10 s of the recordings. Time to exhaustion (TTE) was the total duration the individual was able to sustain progressive increases in workloads during a graded exercise test until volitional fatigue. The peak power output was the highest mechanical power achieved during the GXT before termination due to exhaustion. When the last stage was incomplete, the peak power output was calculated as the fractional time completed in the last stage multiplied by the increment rate [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. HRV was analysed to consider all visits in the conditions at rest (5 minutes in a supine position with minimal light and noise exposure) with a self-selected breathing pattern and throughout the GXT test.\u003c/p\u003e\u003cp\u003eThe GXT consisted of an incremental test until exhaustion, with the R-R interval recordings being saved for the HR and HRV analysis. And the RPE was recorded during the last 30 seconds of each stage using the Borg 15-point scale (6\u0026ndash;20) [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. The maximum RPE (RPEmax) on the GXT represents the highest subjective perception of effort reported by the participant.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eHeart rate variability and Heart rate variability threshold\u003c/h3\u003e\n\u003cp\u003eThe R-R intervals were recorded using the EliteHRV\u0026reg; application to assess cardiac autonomic responses, considering HR (bpm) and HRV parameters, using a chest strap sensor Polar H10 (Polar Electro Oy, Kempele, Finland) [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. The H10 sensor was positioned at the xiphoid process level and the strip was moistened to improve conductivity.\u003c/p\u003e\u003cp\u003eThe R-R interval data were exported and analysed using Kubios HRV Standard\u0026reg; software (version 3.4.0) [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. A filtering process was applied to eliminate potential noise from ectopic beats or device reading errors, with a correction threshold not exceeding 2% of the R-R intervals combined with visual inspection.\u003c/p\u003e\u003cp\u003eThe HRV analysis included time, nonlinear, and frequency domains. The time-domain analyses included: 1) SDNN: standard deviation of all normal R-R intervals recorded as a global autonomic index; and 2) rMSSD: root mean square of the successive differences between adjacent normal R-R intervals. The nonlinear-domain analyses included Poincar\u0026eacute; plot analysis, where SD1 and SD2 represent the standard deviation of short- and long-term beat-to-beat variability, respectively. The rMSSD and SD1 were considered as parasympathetic nervous system indices, while SDNN and SD2 were considered as global autonomic HRV indices [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Finally, the frequency-domain analyses included low- and high-frequency analyses. For this, normal-to-normal R-R intervals were corrected and interpolated using a cubic method at a sampling frequency of 2 Hz. Spectral power density was estimated using the Fast Fourier Transform with Welch\u0026rsquo;s windowing method. The low-frequency component (LF: 0.04\u0026ndash;0.15 Hz) was considered indicative of both sympathetic and parasympathetic modulation, while the high-frequency component (HF: 0.15\u0026ndash;0.40 Hz) is primarily associated with parasympathetic activity and influenced by respiratory frequency. The LF and HF values were expressed in absolute units (ms\u0026sup2;) and log-transformed values (log-ms\u0026sup2;). The sympathovagal balance was represented by the LF/HF ratio [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/p\u003e\u003cp\u003eThe HRV threshold was determined using visual inspection by two independent researchers who were unaware which menstrual cycle phase they were analysing. A third evaluator would be consulted in case of disagreement [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. However, as two researchers agreed in all analysis, a third evaluator was not necessary. Given the distinct physiological significance of the HRV indices, HRV threshold was analysed in two different ways, one using vagal indices (HRVT\u003csub\u003eSD1\u003c/sub\u003e) and another using global indices (HRVT\u003csub\u003eSDNN\u003c/sub\u003e), analysing HRV data every 40 seconds. Briefly, the workload at which HRV stabilization occurred, characterized by the absence of large declines in the SDNN panel and SD1 indices panel, separately, was considered the HRV threshold [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], as show in the Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\n\u003ch3\u003e*** INSERT FIGURE ***\u003c/h3\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eNormality in data distribution was checked using the Shapiro-Wilk test. Normally-distributed variables, such as power output measures, HR at the HRV threshold, time to exhaustion, and peak power, were compared between early follicular and luteal phases using the paired t-test. Non-normally-distributed variables, such as HRV measures [HF (log) and LF/HF ratio pre-exercise; and LF (ms\u003csup\u003e2\u003c/sup\u003e), HF (ms\u003csup\u003e2\u003c/sup\u003e), and, or ordinal qualitative variables, such as RPE at HRVT measures, were compared using the Wilcoxon signed-rank test. As one data point was missing in the follicular phase for one participant, an intention-to-treat analysis was applied, with missing data imputed using the expected maximization procedure. The significance level was set at \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05. For parametric comparisons, the effect sizes (ES) using the Cohen's d effect size (\u003cem\u003ed\u003c/em\u003e-Cohen) was used to quantify the standardized differences between means, with values of 0.2, 0.5, and 0.8 indicating small, medium, and large effects, respectively [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. For non-parametric comparisons, the effect size was calculated using (\u003cem\u003er\u0026thinsp;=\u0026thinsp;z \u0026divide; \u0026radic;N)\u003c/em\u003e, derived from the Z statistic. This approach standardizes the ES for the \u003cem\u003er\u003c/em\u003e values to a range between \u0026minus;\u0026thinsp;1 and 1, with values of 0.1, 0.3, and 0.5 representing small, medium, and large effects, respectively [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. To facilitate the interpretation of the results, the negative signs of the ES results were removed. All statistical analyses were performed using SPSS software (version 30.0).\u003c/p\u003e\u003c/div\u003e"},{"header":"RESULTS","content":"\u003cp\u003eBody mass and parameters obtained in the GXT during follicular and luteal phases are described in Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. There were no significant differences and small effect sizes for body mass, time to exhaustion, peak power, HRmax, and RPEmax between follicular and luteal phases.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eData on body mass and parameters obtained in the graded exercise test in early follicular and mid-luteal phases of the menstrual cycle.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eEarly Follicular phase\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003eMid-Luteal phase\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cem\u003eES\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBody mass (kg)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e67.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026plusmn;\u0026thinsp;10.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e66.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026plusmn;\u0026thinsp;10.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.48\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTime to exhaustion (s)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e753.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026plusmn;\u0026thinsp;193.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e730.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026plusmn;\u0026thinsp;179.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.43\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePeak power (W)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e181.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026plusmn;\u0026thinsp;40.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e177.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026plusmn;\u0026thinsp;37.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.43\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHRmax (bpm)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e175.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026plusmn;\u0026thinsp;13,0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e176.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026plusmn;\u0026thinsp;13.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.26\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRPEmax (units)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e19.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(17.3\u0026ndash;19.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e18.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(17.3\u0026ndash;19.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.22\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e\u003cp\u003eNote: Data are means\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (\u0026plusmn;\u0026thinsp;SD) for body mass (kg), time to exhaustion (s), peak power (W), and HRmax (bpm). Median and quartiles 1 and 3 (q1-q3) for RPEmax (Borg 6\u0026ndash;20). \u003cem\u003ep\u003c/em\u003e: p-value; Cohen\u0026rsquo;s d or r\u003csup\u003e#\u003c/sup\u003e [from Z (-0.89, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.37) statistic] effect sizes (\u003cem\u003eES\u003c/em\u003e) for dependent samples.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003e***INSERT Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e ***\u003c/h2\u003e\u003cp\u003eThe power output, heart rate, and RPE at the HRV thresholds are presented in Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. There were no differences for power output and HR at HRVT\u003csub\u003eSDNN\u003c/sub\u003e or HRVT\u003csub\u003eSD1\u003c/sub\u003e between follicular and luteal phases (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). The RPE at the HRVT\u003csub\u003eSD1\u003c/sub\u003e (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), but not at the HRVT\u003csub\u003eSDNN\u003c/sub\u003e threshold (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05), was significantly higher in the follicular than in the luteal phase.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePower output (W), heart rate (bpm), and RPE (units) at the heart rate variability threshold identified by global autonomic parameters (SDNN) and the vagally mediated index (SD1) during a graded exercise test performed in the early follicular and luteal phases of the menstrual cycle.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"8\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eEarl Follicular phase\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003eMid-Luteal phase\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cem\u003eES\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"1\" nameend=\"c8\" namest=\"c8\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003ePower output\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"1\" nameend=\"c8\" namest=\"c8\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHRVT\u003csub\u003eSDNN\u003c/sub\u003e (W)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e144.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026plusmn;\u0026thinsp;34.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e134.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026plusmn;\u0026thinsp;30.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c8\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHRVT\u003csub\u003eSD1\u003c/sub\u003e (W)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e123.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026plusmn;\u0026thinsp;29.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e114.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026plusmn;\u0026thinsp;24.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c8\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHeart rate\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c8\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHR-HRVT\u003csub\u003eSDNN\u003c/sub\u003e (bpm)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e150\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026plusmn;\u0026thinsp;16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e148\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026plusmn;\u0026thinsp;12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.74\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c8\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHR-HRVT\u003csub\u003eSD1\u003c/sub\u003e (bpm)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e140\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026plusmn;\u0026thinsp;11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e137\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026plusmn;\u0026thinsp;9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c8\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eRPE\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c8\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRPE-HRVT\u003csub\u003eSDNN\u003c/sub\u003e (units)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e13.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(12.3\u0026ndash;15.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e13.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(10.5\u0026ndash;14.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.33\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c8\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRPE-HRVT\u003csub\u003eSD1\u003c/sub\u003e (units)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e12.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(10.8\u0026ndash;13.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(9.0\u0026ndash;12.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.03*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.55\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c8\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e\u003cp\u003e\u003cem\u003eNote\u003c/em\u003e: Data are means and standard deviation (\u0026plusmn;\u0026thinsp;SD) for power output (W) and heart rate (bpm) and median (quartiles 1 and 3) for RPE. \u003cem\u003ep\u003c/em\u003e: p-value; Cohen\u0026rsquo;s \u003cem\u003ed\u003c/em\u003e or \u003cem\u003er\u003c/em\u003e\u003csup\u003e#\u003c/sup\u003e [from Z (RPE-HRVT\u003csub\u003esdnn\u003c/sub\u003e: -1.34; RPE-HRVT\u003csub\u003esd1/rmssd\u003c/sub\u003e: -2.22) statistic] effect sizes (\u003cem\u003eES\u003c/em\u003e) for dependent samples. *Significant difference between follicular and luteal phases (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0,05).\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003e***INSERT Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e ***\u003c/h2\u003e\u003cp\u003ePre-exercise HRV indices are shown in Table \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. There were no differences between follicular and luteal phases (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05) for any cardiac autonomic responses analysed by HRV.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePre-exercise HRV response to graded exercise test performed in the early follicular and luteal phases of the menstrual cycle.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eEarly Follicular phase\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003eMid-Luteal phase\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cem\u003eES\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003ePre-exercise\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHR (bpm)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026plusmn;\u0026thinsp;13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026plusmn;\u0026thinsp;10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.84\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.05\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eiRR (ms)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e913.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026plusmn;\u0026thinsp;191.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e913.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026plusmn;\u0026thinsp;127.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSDNN (ms)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e24.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026plusmn;\u0026thinsp;6.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e25.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026plusmn;\u0026thinsp;4.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.19\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRMSSD (ms)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e24.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026plusmn;\u0026thinsp;7.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e27.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026plusmn;\u0026thinsp;6.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.39\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLF (ms\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e360.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026plusmn;\u0026thinsp;269.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e284.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026plusmn;\u0026thinsp;167.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.27\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLF (log)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026plusmn;\u0026thinsp;0.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026plusmn;\u0026thinsp;0.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.25\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHF (ms\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e273.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026plusmn;\u0026thinsp;129.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e298.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026plusmn;\u0026thinsp;117.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.15\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHF (log)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(5.1\u0026ndash;6.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(5.4\u0026ndash;6.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.72\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.09\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLF/HF ratio\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(0.8\u0026ndash;2.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(0.4\u0026ndash;1.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.26\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSD1 (ms)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e17.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026plusmn;\u0026thinsp;5.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e19.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026plusmn;\u0026thinsp;4.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.40\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSD2 (ms)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e29.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026plusmn;\u0026thinsp;8.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e30.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026plusmn;\u0026thinsp;6.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.59\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.14\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e\u003cp\u003e\u003cem\u003eNote\u003c/em\u003e: Data are means and standard deviation (\u0026plusmn;\u0026thinsp;SD) when using the paired t-test. Median and quartiles 1 and 3 (q1 \u0026ndash; q3) when using the Wilcoxon signed-rank test. Effect sizes (ES) from Cohen\u0026rsquo;s \u003cem\u003ed\u003c/em\u003e or r effect size for dependent samples.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003e***INSERT Table \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e ***\u003c/h2\u003e\u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThe present study investigated the effects of early follicular and mid-luteal phases of the menstrual cycle on pre- and during GTX on cardiac autonomic responses and aerobic performance. The main findings of the present study were: 1) chronotropic responses, HRV pre-exercise and HRVT were similar between early follicular and mid-luteal phases; 2) parameters of endurance performance (time to exhaustion and peak power output) were similar in both phases analysed; 3) perceived exertion at HRVT\u003csub\u003eSD1\u003c/sub\u003e was higher in the early follicular phase than mid-luteal phase.\u003c/p\u003e\u003cp\u003eDuring physical exercise, the HR increase is mainly regulated by the sympathetic and parasympathetic nervous systems. Exercise intensity is directly proportional to vagal withdrawal and sympathetic activity [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. As women experience fluctuations in oestrogen and progesterone throughout the menstrual cycle, the fluctuations in these hormones couple [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. In this way, it was expected that hormonal changes might explain the autonomic differences observed between menstrual phases.\u003c/p\u003e\u003cp\u003ePre-exercise HRV responses did not differ significantly between the early follicular and mid-luteal phases. All time-domain, nonlinear, and frequency-domain HRV indices remained statistically unchanged across the phases studied, similar to what was found by Leicht et al. (2003)[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] at rest. However, these findings contrast with studies indicating increased parasympathetic modulation during the follicular phase due to elevated oestrogen levels[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. For instance, Brar et al. (2015)[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] examined resting cardiac autonomic function in eumenorrheic women across three menstrual cycle phases and found significant differences in mean R-R intervals and HR between the follicular phase (2nd day of menstrual phase) and mid-luteal phase (21st day, secretory phase), which were observed differently in the present study, but close to early follicular and mid-luteal phase. These differences, which contrast with the findings of the present study but are physiologically close to the early follicular and mid-luteal phases, were attributed to increased vagal activity during the follicular phase, likely mediated by higher oestrogen levels, and to elevated progesterone during the luteal phase, which may attenuate vagal tone[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. In contrast, Leicht et al. (2003)[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] reported higher HR values during ovulation but found no significant differences in HR between the menstrual and luteal phases, nor in HRV measures at rest across the menstrual cycle. In addition, Leicht et al. (2003)[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] observed a positive correlation between HRV (vagal and global indices) and 17b-oestradiol concentrations at rest during the ovulatory phase, but this result was not observed in menses (equivalent to early follicular phase) or luteal phases, probably due to inhibitory influences of progesterone, FSH and LH and on oestrogen. These suggest that the interplay between oestrogen may influence as a protective effect of hormonal fluctuations on HRV and autonomic regulation. In the present study, the ovulatory phase was not assessed, given the methodological difficulty arising from a lack of a precise method to track days in the menstrual cycle and the HRV at rest, as similar in both phases.\u003c/p\u003e\u003cp\u003eDuring exercise, the HRVT identified by global (SDNN) and vagal (SD1) indices occurred at similar workloads and HR in both phases. These findings suggest that the autonomic transition point from parasympathetic to sympathetic dominance during incremental exercise is not phase-dependent, considering the early follicular and mid-luteal phases, unlike previously hypothesised. There are many HRVT methodologies which, in general, are often correlated with lactate and ventilatory thresholds [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. In the current study, no differences were observed between the early follicular phase and luteal phase for HR at HRVT\u003csub\u003eSD1\u003c/sub\u003e and HRVT\u003csub\u003eSDNN\u003c/sub\u003e, HRmax, or time to exhaustion. These findings can be compared, in part, and considered consistent with studies analysing cardiorespiratory measures and ventilatory thresholds [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan additionalcitationids=\"CR46 CR47\" citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eRPE showed a significant difference at the HRVT\u003csub\u003eSD1\u003c/sub\u003e, with higher values during the early follicular phase compared to the mid-luteal phase. This aligns with Delp et al. (2024), 19, who found (using a similar analysis to the present study) that RPE was higher during the early follicular phase compared to ovulation and the luteal phase in both trained and untrained women. Similarly, Hooper et al. (2011) [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e] reported higher RPE in the follicular phase in sedentary women during moderate intensity cycling. This finding highlights the sensitivity of RPE as a measure of effort perception across menstrual phases, beyond simple stage-by-stage comparisons. Curiously, the higher values of the RPE responses significantly with a moderate effect size at the HRVT\u003csub\u003eSD1\u003c/sub\u003e during the early follicular phase, compared to the mid-luteal phase, may be due to the influence of psychobiological factors, reflected in submaximal intensities[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], such as mood disturbances, decreased motivation, and heightened perception of physical discomfort, which are frequently reported by women during the early follicular phase and can modulate the central processing of effort perception, even in the absence of significant physiological alterations[\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe findings of the current study indicate that the menstrual cycle phase does not significantly influence aerobic performance during maximal progressive exercise observed in GXT, as evidenced by similar values for time to exhaustion [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] HR, and power output from workload at the HRVT\u003csub\u003eSD1\u003c/sub\u003e and HRVT\u003csub\u003eSDNN\u003c/sub\u003e. These results align with Taipale-Mikkonen et al., (2021)[\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e], who found no significant differences in HR, %HRmax, blood lactate, or oxygen consumption (VO\u003csub\u003e2\u003c/sub\u003e) between menstrual phases in eumenorrheic women and oral contraceptive users. Other studies have also reported no significant differences in physiological and performance parameters across the menstrual cycle [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan additionalcitationids=\"CR53\" citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. Variations in performance during the menstrual cycle may stem from changes in exercise metabolism driven by fluctuations in ovarian hormones [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. For example, Rael et al. (2021)[\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e] compared cardiorespiratory responses to exercise in eumenorrheic women, oral contraceptive users, and postmenopausal women. Tests were conducted during periods of low hormonal activity (e.g., during menstruation for eumenorrheic women). The authors found that postmenopausal women exhibited cardiovascular responses similar to eumenorrheic women and oral contraceptive users, suggesting that hormonal fluctuations may not always translate into significant performance differences [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. Findlay et al. (2020)[\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e] explored the impact of the menstrual cycle on athletic performance in rugby players, finding that 93% of athletes reported negative physical or psychological symptoms associated with their cycle. These symptoms, including decreased energy, cramps, and mood disturbances, often affect training and competition. The authors emphasized the importance of individualized approaches and cycle monitoring to mitigate negative effects and optimize performance [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. Although performance at maximum effort did not differ, considering the early follicular and mid-luteal phases of the menstrual cycle, some perceptual submaximal indicators (i.e. RPE) proved to be more sensitive to possible known changes arising during the different phases of the menstrual cycle in women.\u003c/p\u003e\u003cp\u003eThe current study presents some limitations. First, menstrual cycle tracking was performed using the day-counting method, which may not be as precise as basal temperature tracking or hormonal assays. Second, the study was conducted with eumenorrheic women who are physically active, which does not allow the application of the findings to oral contraceptive users or postmenopausal women. Third, individual variability in hormone levels and responses to exercise was not measured, which may have influenced physiological and performance outcomes.\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eOur findings indicate no differences in pre-exercise and during GXT on cardiac autonomic responses between early follicular and mid-luteal phases of the menstrual cycle in physically active eumenorrheic women. However, the perceived effort of the exercise intensity at which a shift in vagal-mediated autonomic balance occurs was higher in the early follicular phase than in the mid-luteal phase. From a practical perspective, these results suggest that while objective physiological markers of cardiac autonomic responses at rest and during GXT remain stable across menstrual phases, RPE in submaximal conditions may vary. Therefore, coaches, clinicians, and exercise professionals should consider that women may experience differences in effort perception depending on the menstrual cycle phase, even when physiological responses remain unchanged. This insight highlights the importance of integrating both physiological and perceptual measures when prescribing and monitoring exercise in physically active female populations.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003ebpm\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ebeats per minute\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cem\u003ed\u003c/em\u003e-Cohen\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eCohen\u0026rsquo;s effect size value\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eES\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eeffect size value\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eFSH\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003efollicle-stimulating hormone\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eGXT\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003egraded exercise testing\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eHF\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ehigh frequency\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eHR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eheart rate\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eHRmax\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003emaximal heart rate\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eHRV\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eheart rate variability\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eHRVT\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eheart rate variability threshold\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eHRVT\u003csub\u003eSD1\u003c/sub\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003evagal index to determine heart rate variability threshold\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eHRVT\u003csub\u003eSDNN\u003c/sub\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eglobal index to determine heart rate variability threshold\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eHz\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eHertz\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eLH\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eluteinizing hormone\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eLF\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003elow frequency\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eLF/HF\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003esympathovagal balance\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003ePAR-Q+\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eversion plus of the Physical Activity Readiness Questionnaire\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eRPE\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003erate of perceived exertion\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eRPEmax\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003emaximal value of rate of perceived exertion in exercise testing\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eR-R\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eintervals of R-waves from electrocardiogram signals\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003erMSSD\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eroot mean square of the successive differences between adjacent normal R-R intervals\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eSDNN\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003estandard deviation of all normal R-R intervals\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eSD1\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003estandard deviation of short-term beat-to-beat variability from \u003cem\u003ePoincar\u0026eacute;\u003c/em\u003e plotting\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eSD2\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003estandard deviation of long-term beat-to-beat variability from \u003cem\u003ePoincar\u0026eacute;\u003c/em\u003e plotting\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eVO\u003csub\u003e2\u003c/sub\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003evolume of oxygen consumed per unit of time\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eW\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003epower expressed in watts\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003ch2\u003eConflict of interest\u003c/h2\u003e\u003cp\u003eNone of the authors has any conflicts of interest related to this manuscript.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eAuthors contributions:All the authors participated critically in the important intellectual content and in revising the manuscript \u0026ldquo;Influence of early follicular and mid-luteal phases of the menstrual cycle on aerobic performance, perceived exertion, and cardiac autonomic responses in eumenorrheic women: a randomized crossover trial.\u0026rdquo;. The authors, NSD, PC, and LFSC, were specifically involved in data collection and statistical analysis. All authors approved the final manuscript and take full responsibility for its content and integrity.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eWe would like to thank all the volunteers who participated in the study. We also thank CAPES, which provided the scholarship to the author Nicolle Souza Dias.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets generated and analyzed during the current study are not publicly available due to ethical restrictions, as they contain information that could compromise the privacy of research participants. In accordance with the approval granted by the Institutional Research Ethics Committee (Protocol number: CAAE number: 69341323.7.0000.0108), access to the data is restricted. However, anonymized datasets are available from the corresponding author upon reasonable request and subject to compliance with ethical and legal requirements.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eLebrun CM, McKenzie DC, Prior JC, Taunton JE. Effects of menstrual cycle phase on athletic performance. Med Sci Sports Exerc. 1995;27.\u003c/li\u003e\n\u003cli\u003eSims ST, Heather AK. Myths and Methodologies: Reducing scientific design ambiguity in studies comparing sexes and/or menstrual cycle phases. Exp Physiol. 2018;103:1309\u0026ndash;17. https://doi.org/10.1113/EP086797.\u003c/li\u003e\n\u003cli\u003eJanse de Jonge X, Thompson B, Han A. Methodological Recommendations for Menstrual Cycle Research in Sports and Exercise. Med Sci Sports Exerc. 2019;51:2610\u0026ndash;7. https://doi.org/10.1249/MSS.0000000000002073.\u003c/li\u003e\n\u003cli\u003eElliott-Sale KJ, Minahan CL, de Jonge XAKJ, Ackerman KE, Sipil\u0026auml; S, Constantini NW, et al. 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Hillsdale, NJ Lawrence Erlbaum Associates, Publishers. - References - Scientific Research Publishing. 1988. https://www.scirp.org/reference/ReferencesPapers?ReferenceID=2041144. Accessed 13 Feb 2025.\u003c/li\u003e\n\u003cli\u003eFritz CO, Morris PE, Richler JJ. Effect size estimates: Current use, calculations, and interpretation. J Exp Psychol Gen. 2012;141:2\u0026ndash;18. https://doi.org/10.1037/a0024338.\u003c/li\u003e\n\u003cli\u003eCottin F, M\u0026eacute;digue C, Lepr\u0026ecirc;tre PM, Papelier Y, Koralsztein JP, Billat V. Heart Rate Variability during Exercise Performed below and above Ventilatory Threshold. Med Sci Sports Exerc. 2004;36:594\u0026ndash;600. https://doi.org/10.1249/01.MSS.0000121982.14718.2A.\u003c/li\u003e\n\u003cli\u003eColenso-Semple LM, D\u0026rsquo;Souza AC, Elliott-Sale KJ, Phillips SM. Current evidence shows no influence of women\u0026rsquo;s menstrual cycle phase on acute strength performance or adaptations to resistance exercise training. Front Sports Act Living. 2023;5:1054542. https://doi.org/10.3389/FSPOR.2023.1054542.\u003c/li\u003e\n\u003cli\u003eSoares-Caldeira LF, Silva CC da, Chierotti P, Dias N de S, Nakamura FY. Influence of aerobic fitness on the correspondence between heart rate variability and ventilatory threshold. Revista Brasileira de Educa\u0026ccedil;\u0026atilde;o F\u0026iacute;sica e Esporte. 2020;34:555\u0026ndash;66. https://doi.org/10.11606/1807-5509202000040555.\u003c/li\u003e\n\u003cli\u003eLebrun CM. The effect of the phase of the menstrual cycle and the birth control pill on athletic performance. Clin Sports Med. 1994;13:419\u0026ndash;41. https://doi.org/10.1016/s0278-5919(20)30339-2.\u003c/li\u003e\n\u003cli\u003eRedman LM, Weatherby RP. Measuring Performance during the Menstrual Cycle: A Model Using Oral Contraceptives. 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J Womens Health (Larchmt). 2011;20:439\u0026ndash;46. https://doi.org/10.1089/JWH.2010.2042.\u003c/li\u003e\n\u003cli\u003eFindlay RJ, MacRae EHR, Whyte IY, Easton C, Forrest LJ. How the menstrual cycle and menstruation affect sporting performance: experiences and perceptions of elite female rugby players. Br J Sports Med. 2020;54:1108\u0026ndash;13. https://doi.org/10.1136/BJSPORTS-2019-101486.\u003c/li\u003e\n\u003cli\u003eTaipale-Mikkonen RS, Raitanen A, Hackney AC, Solli GS, Valtonen M, Peltonen H, et al. Influence of Menstrual Cycle or Hormonal Contraceptive Phase on Physiological Variables Monitored During Treadmill Testing. Front Physiol. 2021;12:761760. https://doi.org/10.3389/FPHYS.2021.761760.\u003c/li\u003e\n\u003cli\u003eFreemas J, Baranauskas M, Constantini K, Constantini N, Mickleborough T, Raglin J, et al. Aerobic Exercise Performance is Reduced in the Mid-luteal Compared to the Mid-follicular Phase of the Menstrual Cycle in Eumenorrheic Women. The FASEB Journal. 2020;34:1\u0026ndash;1. https://doi.org/10.1096/FASEBJ.2020.34.S1.03068.\u003c/li\u003e\n\u003cli\u003eQuinn TJ, Vroman NB. Postexercise oxygen consumption in trained females effect of exercise duration. Med Sci Sports Exerc. 1994;7:908\u0026ndash;13.\u003c/li\u003e\n\u003cli\u003eMattu AT, Iannetta D, MacInnis MJ, Doyle-Baker PK, Murias JM. Menstrual and oral contraceptive cycle phases do not affect submaximal and maximal exercise responses. Scand J Med Sci Sports. 2020;30:472\u0026ndash;84. https://doi.org/10.1111/SMS.13590.\u003c/li\u003e\n\u003cli\u003eKoenig J, Thayer JF. Sex differences in healthy human heart rate variability: A meta-analysis. Neurosci Biobehav Rev. 2016;64:288\u0026ndash;310. https://doi.org/10.1016/J.NEUBIOREV.2016.03.007.\u003c/li\u003e\n\u003cli\u003eRael B, Barba-Moreno L, Romero-Parra N, Alfaro-Magallanes VM, Castro EA, Cupeiro R, et al. Cardiorespiratory response to exercise in endurance-trained premenopausal and postmenopausal females. Eur J Appl Physiol. 2021;121:903\u0026ndash;13. https://doi.org/10.1007/S00421-020-04574-4/METRICS.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"sport-sciences-for-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ssfh","sideBox":"Learn more about [Sport Sciences for Health](http://link.springer.com/journal/11332)","snPcode":"11332","submissionUrl":"https://submission.nature.com/new-submission/11332/3","title":"Sport Sciences for Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"menstrual period, autonomic nervous systems, perceived exertion, maximal progressive exercise testing","lastPublishedDoi":"10.21203/rs.3.rs-7773829/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7773829/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose\u003c/h2\u003e\u003cp\u003eThe aim of the present study was to compare aerobic performance, anthropometry, heart rate variability (HRV) pre-exercise and during graded exercise testing (GXT) on HRV threshold (HRVT), heart rate (HR) and rate of perceived exertion (RPE) between the early follicular and mid-luteal phases of the menstrual cycle.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eSixteen eumenorrheic women (28.8\u0026thinsp;\u0026plusmn;\u0026thinsp;6.7 years) randomly completed two GXT (starting at 50W and increasing 25W every two minutes until exhaustion), one in the early follicular phase and another in the mid-luteal phase. Cardiac autonomic responses were continually monitored via HRV indices, recorded pre-exercise and during GXT, throughout the HRVT, HR and RPE.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eThere were no differences between early follicular and mid-luteal phases for body mass (67.2\u0026thinsp;\u0026plusmn;\u0026thinsp;10.1 vs. 66.6\u0026thinsp;\u0026plusmn;\u0026thinsp;10.1 kg, p\u0026thinsp;=\u0026thinsp;0.08), time to exhaustion (753.0\u0026thinsp;\u0026plusmn;\u0026thinsp;193.8 vs. 730.8\u0026thinsp;\u0026plusmn;\u0026thinsp;179.5 s, p\u0026thinsp;=\u0026thinsp;0.10), peak power (181.9\u0026thinsp;\u0026plusmn;\u0026thinsp;40.4 vs. 177.3\u0026thinsp;\u0026plusmn;\u0026thinsp;37.4 W, p\u0026thinsp;=\u0026thinsp;0.10), maximal HR (176\u0026thinsp;\u0026plusmn;\u0026thinsp;13 vs. 176\u0026thinsp;\u0026plusmn;\u0026thinsp;13 bpm, p\u0026thinsp;=\u0026thinsp;0.80), and maximal RPE (median: 19.0 vs. 18.5 units, p\u0026thinsp;=\u0026thinsp;0.37), respectively. In addition, no significant differences were observed between early follicular and mid-luteal phases for pre-exercise HRV indices (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). There were also no significant differences between early follicular and mid-luteal phases for power output and HR at HRVT identified during the GXT (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). However, the RPE at the HRVT identified using vagal index (SD1) was (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.03) higher in the early follicular phase (median: 12.0, interquartile distance 10.8 to 13.8) than in the mid-luteal phase (median: 10.5, interquartile distance 9.0 to 12.0).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eIn eumenorrheic women, endurance performance and cardiac autonomic responses were similar in early follicular and mid-luteal phases, but RPE of the exercise intensity at which a shift in autonomic nervous system balance occurs is higher in the early follicular phase than in the mid-luteal phase.\u003c/p\u003e","manuscriptTitle":"Influence of early follicular and mid-luteal phases of the menstrual cycle on aerobic performance, perceived exertion, and cardiac autonomic responses in eumenorrheic women: a randomized crossover trial","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-28 16:36:42","doi":"10.21203/rs.3.rs-7773829/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-11-11T14:49:23+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-07T16:41:10+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-29T19:52:50+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"294184173162772255741694100797049535988","date":"2025-10-27T19:24:07+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"58048133201968820832202477663533303265","date":"2025-10-20T14:15:19+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-10-14T17:33:05+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-10-04T08:55:21+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-10-04T08:54:03+00:00","index":"","fulltext":""},{"type":"submitted","content":"Sport Sciences for Health","date":"2025-10-03T13:13:59+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"sport-sciences-for-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ssfh","sideBox":"Learn more about [Sport Sciences for Health](http://link.springer.com/journal/11332)","snPcode":"11332","submissionUrl":"https://submission.nature.com/new-submission/11332/3","title":"Sport Sciences for Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"4edef449-d1f5-431a-aea8-43689e4c6644","owner":[],"postedDate":"October 28th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-01-12T16:00:43+00:00","versionOfRecord":{"articleIdentity":"rs-7773829","link":"https://doi.org/10.1007/s11332-025-01623-3","journal":{"identity":"sport-sciences-for-health","isVorOnly":false,"title":"Sport Sciences for Health"},"publishedOn":"2026-01-07 15:57:20","publishedOnDateReadable":"January 7th, 2026"},"versionCreatedAt":"2025-10-28 16:36:42","video":"","vorDoi":"10.1007/s11332-025-01623-3","vorDoiUrl":"https://doi.org/10.1007/s11332-025-01623-3","workflowStages":[]},"version":"v1","identity":"rs-7773829","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7773829","identity":"rs-7773829","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}