Introduction

In a previous study (Nold et al., 2025), we investigated the effect of high-(HI) and low-intensity (LI) aerobic exercise on pain perception in a heterogeneous sample of both sexes and diverse fitness levels (N = 39, 21 females), where exploratory analyses revealed a three-way interaction of sex, fitness level, and drug treatment. Males showed greater hypoalgesia after HI compared to LI exercise with increasing fitness levels. This effect was reduced when the µ-opioid antagonist naloxone was administered. These effects were not evident in females. Taken together, these results point to the nuanced interplay of individual factors such as fitness level and sex underlying exercise-induced hypoalgesia.

Correspondingly, previous research in humans (Geva and Defrin, 2013; Schmitt et al., 2020; Sluka et al., 2018) suggests that fitness level plays a crucial role in exercise-induced pain modulation, where subjects with higher fitness levels showed increased hypoalgesia following exercise compared to subjects with lower fitness levels (Schmitt et al., 2020). Furthermore, higher self-reported fitness levels were shown to be associated with reduced pain ratings (Geva and Defrin, 2013), reduced temporal summation (Naugle and Riley, 2014), and greater opioid release in the orbitofrontal cortex and insula (Saanijoki et al., 2022). Crucially, most of these studies (Saanijoki et al., 2022; Schmitt et al., 2020) have been conducted in healthy all-male samples, limiting the translation to females, where the association of physical fitness and pain perception after exercise remains less clear (de Bruijn et al., 2011).

Despite the majority of chronic pain patients being female (Fillingim et al., 2009; Mogil, 2012; Rice et al., 2019), evidence on potential sex differences in exercise-induced pain modulation is surprisingly limited (Koltyn et al., 2014). Of those studies that have considered potential sex differences in exercise-induced pain modulation, some (Brellenthin et al., 2017; Koltyn et al., 2014; Niwa et al., 2022; Smith, 2004) could show that there are no sex differences, whereas others (Koltyn, 2000; Sternberg et al., 2001; Vaegter et al., 2014) suggest that hypoalgesia following exercise is more robust in females, but overall results remain inconclusive (Rice et al., 2019).

This current behavioural study aims to build on our previous findings (Nold et al., 2025) by investigating exercise-induced pain modulation in an independent all-female sample (N = 21) with a high fitness level using the same paradigm as in the previous study, without a pharmacological intervention. Importantly, fitness levels (quantified by the weight-corrected functional threshold power (FTP)) in the previous study (Nold et al., 2025) differed significantly (P = 0.003) between females (M = 1.58, SD = 0.44) and males (M = 2.03, SD = 0.40), thus, warranting further investigation into whether exercise-induced hypoalgesia after HI compared to LI aerobic exercise can also be observed in females with a higher fitness. Disentangling if and to what extent exercise-induced hypoalgesia depends on fitness level and sex is a crucial step to determine exercise-based interventions for (chronic) pain populations.

Results

The final sample included N = 21 healthy female participants with high fitness (weight-corrected FTP: M = 2.25 W/kg, SD = 0.41; Fig. 1A). The distribution of menstrual cycle phases (based on self-report and divided into three phases: follicular, ovulatory, and luteal as well as hormonal contraceptives) was equal across (χ2(3) = 1.66, P = 0.65) as well as within days (Day 1: χ2(3) = 2.26, P = 0.52; Day 2: χ2(3) = 0.40, P = 0.94; Supplemental Fig. S1A). Furthermore, the expectation of how acute exercise affects different pain domains was assessed (Lindheimer et al., 2020) and yielded no significant effects overall (joint pain: t(20) = −1.78, P = 0.09, muscle pain: t(20) = 0.15, P = 0.88). However, participants indicated that they expect acute aerobic exercise to reduce whole-body pain (t(20) = −2.83, P = 0.01; Supplemental Fig. S1B). Finally, mood ratings were assessed using the Profile of Mood States (POMS) questionnaire (Curran et al., 1995) before the experiment commenced (pre) and after it was completed (post). There were no significant differences in pre- and post-levels of fatigue (t(20) = −0.50, P = 0.62), discontent (t(20) = 1.84, P = 0.08), and drive (t(20) = 0.58, P = 0.57). However, participants rated significantly reduced dejection post compared to pre experimental testing (t(20) = 3.61, P = 0.002; Supplemental Fig. S1C).

Figure 1.

Comparison with the previous study sample

We compared the weight-corrected FTP values of the current sample with those of the previous sample (Nold et al., 2025) (N = 39, 21 females) for males and females separately using two-sample t-tests. The females employed in the current study (Fig.1A; dark blue) had a significantly higher FTP compared to the females of the previous study (light blue) (t(40) = −5.00, P = 1.23×10⁻⁵; Fig. 1A). There was no significant difference in the FTP between the females in this study (dark blue) and males in the previous study (red) (t(36) = 1.65, P = 0.11; Fig. 1A). The self-reported training volume was significantly higher in the females of the current study (dark blue) compared to the females (light blue) (t(22) = 3.45, P = 0.003, Fig. 1B) and males (red) (t(24) = 2.82, P = 0.009; Fig. 1B) of the previous study. Further, analyses comparing the females of the previous study and the females of the current study concerning height, weight, and BMI revealed no significant differences but a significant age difference (t(32.98) = 3.27, P = 0.003) (Supplemental Fig. S2). Overall, this suggests that this current study included females of overall higher fitness levels compared to the previous study.

Successful pain calibration and exercise intervention

We calibrated pain intensity levels corresponding to 30, 50, and 70 on a Visual Analog Scale (VAS), where VAS 0 marks the pain threshold (Supplemental Fig. S3A–B). On the experimental day, we introduced an online rating scale where the pain threshold corresponded to VAS 50 (Supplemental Fig. S3C–D) to more accurately track the temporal dynamics of pain perception through online ratings and incorporate non-painful sensation. Participants perceived the stimulus intensities as significantly different for pressure (β = 1.13, SE = 0.07, t(553.13) = 16.84, P < 2×10⁻¹⁶; Supplemental Table S6) and heat pain (β = 1.75, SE = 0.08, t(532.61) = 21.46, P < 2×10⁻¹⁶; Supplemental Table S8). The anticipated intensities of VAS 50 and VAS 70 were rated above the pain threshold on the online scale, indicating that they were perceived as painful (Supplemental Fig. S4), despite the ratings being lower than the anticipated intensities, potentially due to habituation effects between days (Ellerbrock et al., 2015; May et al., 2012). We achieved a significant difference between HI and LI exercise conditions in absolute power (t(20) = 19.34, P = 2.043e-14, d = 0.97; Fig. 2A), relative power (%FTP; t(20) = 42.35, P < 2.2e-16, d = 7.97; Fig. 2B), HR (t(13) = 20.98, P = 2.073e-11, d = 3.45; Fig. 2C), and (t(20) = 17.17, P = 1.942e-13, d = 4.61; Fig. 2D), confirming the successful implementation of the exercise intervention at the anticipated intensities (55% FTP at LI exercise and 100% at HI exercise).

Figure 2.

Greater pain relief after high-intensity exercise at higher stimulus intensities

In the current study, participants provided online ratings throughout the stimulus duration. We calculated the maximum pain ratings (in the following referred to as pain ratings) across the whole stimulus duration (0 –17 seconds), which closely correspond to the pain ratings provided in the previous study (Nold et al., 2025), where participants were asked to rate the most painful sensation after the stimulus concluded. To statistically test the effect of exercise intensity (HI and LI) on pain ratings, we calculated separate Linear Mixed Effect models (LMER) with the dependent variables overall pain ratings, pressure pain ratings, and heat pain ratings, respectively. All models included exercise intensity or the interaction of exercise intensity and stimulus intensity as a fixed effect, as well as subject, trial, and block as random effects.

There was no main effect of exercise intensity on overall pain ratings (β = −3.07, SE = 2.14, t(1119.79) = −1.43, P = 0.15) as well as no main effect of exercise intensity on pressure pain ratings (β = −2.96, SE = 2.15, t(556.23) = −1.37, P = 0.17; Fig. 3A) or heat pain ratings (β = −3.99, SE = 2.92, t(540.57) = −1.37, P = 0.17; Fig. 3A). However, an interaction of exercise intensity and stimulus intensity on overall pain ratings was evident (β = −0.22, SE = 0.10, t(1114.27) = −2.21, P = 0.03). This interaction was driven by the interaction of exercise intensity and stimulus intensity during heat pain (β = −0.35, SE = 0.11, t(531.93) = −3.183, P = 0.002; Fig. 3B–C). Post–hoc t-tests revealed that the effect was especially evident at the highest stimulus intensity (P = 0.004; Fig. 3B–C). For pressure pain, this interaction of exercise intensity and stimulus intensity was not significant (β = −0.10, SE = 0.09, t(548.88) = −1.05, P = 0.29; Fig. 3B–C) but a similar trend was evident when considering the post-hoc t-tests (Fig. 3B–C), where pain relief following HI compared to LI was greater at the highest stimulus intensity (P = 0.07). The full model outputs and post-hoc t-tests can be found in Supplemental Tables S1–S9.

Figure 3.

Discussion

In this study, we investigated exercise-induced pain modulation between high-intensity (HI) and low-intensity (LI) exercise in a sample of fit females (N = 21). In a previous study by our group (Nold et al., 2025), exploratory analyses suggested a three-way interaction of fitness levels, sex, and drug treatment, where males showed hypoalgesia after HI compared to LI exercise with increasing fitness levels, which was diminished when naloxone was administered. These effects were not evident in females. In this current study, we could show that, for heat pain, fit females showed a similar pain relief after HI compared to LI exercise, especially for highly painful stimuli. A similar trend was observed for pressure pain. These results suggest that fit females show a hypoalgesic response to HI compared to LI exercise. Together with our previous findings (Nold et al., 2025), this underscores that the hypoalgesic response to exercise depends on fitness level but not on sex.

Comparison with the previous study (Nold et al., 2025)

We confirmed that the females of the current sample showed significantly higher fitness level (as measured in weight-corrected FTP) than the females of the previous study (Nold et al., 2025). Furthermore, the absolute training volume was significantly higher compared to the males and females of the previous study, suggesting overall higher fitness levels of the females of the current study. Interestingly, although the training volume of the females of the current study was significantly higher compared to the males of the previous study, the FTP did not significantly differ. Furthermore, as pain is a dynamic experience, we utilised real-time pain ratings in the current study as opposed to static post-stimulus pain ratings (Nold et al., 2025) to better capture the temporal dynamics of pain. Previous research (Koyama et al., 2004) has shown that, in heat pain, real-time ratings account for R² = 0.89 of the variability of post-stimulus rating, where much of the variability for the post-stimulus intensity pain rating is accounted for by the peak response during the online ratings (adj. R² = 0.3 – 0.4), suggesting good comparability of both pain measures.

Effect of exercise and stimulus intensity on pain

Corresponding to our previous study (Nold et al., 2025), there was no overall effect of exercise intensity on heat or pressure pain. However, we identified an interaction of stimulus intensity and exercise intensity that was driven by heat pain, with greater pain relief after HI compared to LI exercise at high stimulus intensity (VAS 70). A similar trend was evident in pressure pain, but it did not reach significance. These findings align with the results of our previous study (Nold et al., 2025), where exercise-induced pain modulation after HI compared to LI exercise was more prominent in heat than pressure pain.

A multitude of findings on exercise-induced hypoalgesia have been derived from earlier studies with male-dominated samples with higher fitness levels (Geisler et al., 2019; Haier et al., 1981; Janal et al., 1984; Scheef et al., 2012), and results on sex dependent effects in exercise-induced hypoalgesia are still equivocal (Rice et al., 2019). Of those studies that have included both sexes in their samples (Naugle et al., 2014; Niwa et al., 2022), a dose-response relationship of aerobic exercise intensity and the analgesic response could be shown in the overall sample, where high-intensity (70% heart rate reserve (HRR)) aerobic exercise produced larger hypoalgesic effects compared to moderate-intensity (50% HRR) exercise (Naugle et al., 2014; Niwa et al., 2022) and low-intensity (30% HRR) exercise (Niwa et al., 2022). Importantly, despite including both sexes, these studies did not include sex as a factor in their analyses, potentially confounding the observed effects (Tesarz et al., 2012). Of those studies that have explicitly accounted for sex as a moderating variable in exercise-induced hypoalgesia, some studies could show a hypoalgesic response from exercise in both sexes (Koltyn et al., 2014, 2001), whereas others (Gajsar et al., 2017; Lemley et al., 2016) found a stronger hypoalgesic response in females. When administering an aerobic exercise protocol, one study found the hypoalgesic response following exercise to be more pronounced in females compared to males (Vaegter et al., 2014).

Despite some studies showing comparable or greater hypoalgesic effects in females, these studies rarely account for fitness levels or athletic status (Tesarz et al., 2012). Generally, it has been shown that athletes exhibit increased pain tolerance and decreased pain intensity compared to non-athletic controls (Geva and Defrin, 2013; Tesarz et al., 2012). Among the few studies that have explicitly considered both fitness levels and sex in the hypoalgesic response to exercise, one study (Sternberg et al., 2001) found that treadmill running induced hypoalgesia in the cold pressor test in females, regardless of athletic status, but not in males. Notably, both male and female athletes showed a significant decrease in forearm withdrawal latency from a radiant heat device after treadmill exercise (Sternberg et al., 2001). Further corroborating this, female athletes experienced more pronounced hypoalgesia following aerobic exercise, especially during cold pressor and thermal pain tests (Smith, 2004). For isometric exercise, one study (Black et al., 2017) found that females demonstrated analgesic responses regardless of their physical activity levels, which is in contrast to our previous findings (Nold et al., 2025), where females did not show an analgesic response after aerobic exercise. Thus, the extent of sex differences might also vary depending on the type of exercise, the pain stimulus administered, and the measurement method employed (Tesarz et al., 2012), emphasising the complexity of sex-specific pain modulation mechanisms. Overall, female athletes tend to report pain similarly to their male counterparts (Tesarz et al., 2012), suggesting that athletic training may mitigate typical sex differences in the hypoalgesic response after exercise and potentially reduce disparities observed in the general population. Our results advance this by showing that fitter females show a hypoalgesic response, and even after cycling for 10 minutes at HI compared to LI in response to heat pain.

Limitations

On the experimental day, heat stimuli with a target rating of VAS 30 were rated below the pain threshold. The anticipated intensities of VAS 50 and VAS 70 were rated above the pain threshold, suggesting that they were perceived as painful. However, the lower pain ratings on the experimental day as opposed to the calibration day are likely due to habituation effects between days (Ellerbrock et al., 2015; May et al., 2012). Moreover, as we compared HI and LI exercise but no sedentary rest condition, we cannot draw conclusions on the overall effect of exercise as opposed to no exercise on pain. Thus, it could be possible that even LI exercise suffices to evoke a hypoalgesic response (Niwa et al., 2022) or that individuals with higher fitness levels can show a distinction in the analgesic response based on the exercise intensity. However, previous research has suggested that HI exercise produces greater hypoalgesia compared to LI exercise (Jones et al., 2019; Naugle et al., 2014; Niwa et al., 2022; Smith, 2004; Vaegter et al., 2014, p. 201). Therefore, we chose the LI exercise as the control condition instead of rest to contribute to the understanding of the dose-response relationship between exercise intensities and hypoalgesic effects. Future research should investigate whether LI exercise suffices to induce an analgesic response.

Conclusion

In this study, we could show that fit females experience pain relief following high-intensity compared to low-intensity exercise, especially at high pain intensities. Together with our previous findings, this indicates that fitness level, rather than sex, plays a central role in modulating exercise-induced hypoalgesia.

Methods

Participants

Overall, N = 22 female participants were recruited for this study from local cycling clubs and by (online) advertisements. Participants were required to be aged between 18 – 50 years and have a body mass index (BMI) ranging from 18 – 30, and to be physically active. One participant was excluded due to a technical failure on the experimental day, resulting in incomplete data. For one participant, heat pain calibration failed, resulting in N = 20 participants for heat pain data and N = 21 participants for pressure pain data (for participant characteristics, see Table 1). It is crucial to note that the N = 21 females included in the current study did not participate in the previous study (Nold et al., 2025).

Table 1.

Experimental Paradigm

The experimental paradigm was similar to that of the original study (Nold et al., 2025), using the same study setup and equipment (CPAR and TSA 2 and Wahoo KICKR bike). Furthermore, the same calibration procedures were used to calibrate heat and pressure pain as well as the functional threshold power using the FTP₂₀ test (Allen and Coggan, 2012, 2006) as implemented and validated in previous studies (Borszcz et al., 2018; McGrath et al., 2019; Nold et al., 2025). However, participants in the current study did not receive a pharmacological intervention and did not undergo fMRI scans; therefore, they received the painful stimuli outside the MR scanner whilst lying in a supine position. To monitor the painful stimuli more closely, participants provided online ratings whilst the pain stimulus was ongoing on a VAS scale ranging from “no sensation” (0) to “almost unbearably painful” (150), with VAS 50 marking “minimally painful” (pain threshold). Furthermore, we administered the same questionnaires as described in the previous study. For a detailed description of the study procedures and experimental paradigm, please refer to Nold et al. (2025). Overall, the current study consisted of one calibration day (Day 1) and one experimental day (Day 2).

Behavioural Data Acquisition

During cycling, heart rate (HR), maintained power (in watts), and cadence (in revolutions per minute (RPM)) were acquired continuously. In N = 7 participants, HR data were not recorded due to a technical failure, but were monitored throughout the cycling. The rating of perceived exertion (RPE) on the BORG scale, ranging from “no exertion” (6) to “maximal exertion” (20), was provided after each cycling block. Furthermore, the elapsed time between each cycling and pain within each block was five minutes to correspond with the mean time required in the previous study. Following the cycling, participants received a total of 18 pain stimuli, with 9 heat and 9 pressure stimuli applied in an alternating fashion and with their respective intensities (30, 50, 70 VAS) applied in a randomised order. Whilst the pain was ongoing, participants were asked to rate their currently perceived pain/non-painful sensation using the left and right buttons of a button box (Logitech). When their perception did not change, the cursor should remain at the same position. The online rating time exceeded the stimulus length by 2 seconds to capture changes in perception when the stimulus ramped down. The online ratings were sampled at 70 – 75 samples per second and interpolated at 0.9 seconds.

Statistical Analyses

The behavioural statistical analyses were performed in MATLAB and RStudio (Version 2021.09.1). We used the lmer and emmeans functions from the lme4 package (Version 1.1-35.1) to conduct linear mixed effect (LMER) (Bates et al., 2014; Hox et al., 2010) and post-hoc t-tests in R, respectively. Furthermore, the rstatix package (Kassambara, 2019) was used to conduct one and two-sample t-tests.

To investigate whether the distribution of menstrual cycle phases as well as hormonal contraceptives differed within and between days, χ2-tests were calculated. Furthermore, we evaluated whether there was a significant effect of expectation about acute aerobic exercise on different pain dimensions and calculated one-sample t-tests (two-tailed). Furthermore, we conducted paired samples t-tests comparing pre- and post-mood ratings on the dimensions of dejection, fatigue, discontent, and drive. To compare the FTP, self-reported fitness levels, training volume, age, weight, height, and BMI between the previous sample (males and females) and the current sample, we calculated two-sample t-tests. To evaluate the exercise parameters within the current study, watts and HR were averaged across time and blocks for each participant and for both exercise intensities. The RPE was also averaged across blocks for participants and exercise intensity. We calculated one-sample t-tests comparing the respective measures between HI and LI exercise.

For visualisation purposes, we displayed the online ratings (averaged across subjects, blocks, trials, and stimulus intensities) and the SEM following HI and LI exercise for heat and pressure pain separately (Supplemental Fig. S4). For a more comprehensive understanding, the averaged online ratings at each stimulus intensity were visualised in the Supplemental Fig. S5. To statistically evaluate the online pain ratings and improve consistency with the post-stimulus pain ratings reported in the previous study (Nold et al., 2025), we calculated the maximum rating by averaging the online rating across the whole stimulus duration (0 – 17 seconds) and extracting the peak rating. The peak pain ratings across the whole stimulus duration would most closely correspond to the post-stimulus pain ratings provided in the previous study, where participants were asked to rate the most painful sensation throughout the stimulus duration. We calculated separate LMER models with the dependent variables overall pain ratings, heat pain ratings, and pressure pain ratings, respectively. All LMER models included subject, trial, and block as random effects. In a first LMER model, we included exercise intensity as a fixed effect; in a second LMER model, the stimulus intensity and exercise intensity, as well as their interaction, served as fixed effects. Finally, we conducted post-hoc t-tests and applied a Tukey adjustment to correct for multiple comparisons.

Data availability

The dataset for the raw behavioural data generated in the current study is available from the corresponding author on reasonable request and after publication. All necessary data to evaluate the results of the study are included in the manuscript and supplementary materials.

Acknowledgements

We thank the participants for taking part in the study. Further, we thank Alexandra Tinnermann for her helpful comments.

Additional information

Funding

C.B. and J.N. are supported by ERC-AdG-883892-PainPersist. C.B. is supported by DFG SFB 289 Project A02 (Project-ID 422744262–TRR 289).

Author Contributions

Conceptualisation, C.B. and J.N.; Methodology, C.B. and J.N.; Investigation, C.B., J.N., T.F., and Z.G.; Visualisation, J.N.; Writing – Original Draft, C.B., J.N., and Z.G.; Funding Acquisition, C.B.; Resources, C.B.; Supervision, C.B.

Ethics

Human subjects: All participants gave informed written consent. The study was approved by the Ethics Board of the Hamburg Medical Association (PV7456/2020-10144-BO-ff). We support inclusive, diverse, and equitable conduct of research.

Code availability

This study was programmed using MATLAB 2021b and Psychophysics Toolbox (Version 3.0.19). For data visualisation, we used RStudio (Version 2021.09.1). The custom behavioural pipelines are available on the public repository https://github.com/jannenold/hotspin_analyses_behavioural_after_publication.

Additional files

Supplementary file 1. Supplemental Figures S1–S5 and Supplemental Tables S1-S9.