Ageing, Sex Differences, and REDs Risk in Endurance Runners: An Integrated Cross-Sectional Study Protocol

1. Introduction

Endurance running performance is shaped by a complex interplay of physiological, biomechanical, and sociocultural factors, with biological sex and ageing representing two of the most influential determinants across the lifespan. Consistently across all levels of competition, male runners consistently outperform female runners in events ranging from middle-distance to ultramarathons. This performance disparity is primarily attributed to sex-specific physiological characteristics, including higher maximal oxygen uptake (VO₂max), greater cardiac stroke volume, elevated haemoglobin concentrations, and larger skeletal muscle mass in men, which collectively enhance oxygen transport and utilisation during prolonged exercise. These differences largely reflect divergent hormonal environments, with testosterone promoting muscle hypertrophy, erythropoiesis, and aerobic capacity. Thereby supporting higher aerobic power and endurance performance in male athletes [1,2,3].

However, sex-based differences in endurance performance extend beyond aerobic capacity alone. Female runners exhibit sex-specific biomechanical and metabolic characteristics, including a greater reliance on lipid oxidation during submaximal exercise, a higher proportional area of type I muscle fibres, and pacing strategies that may be more even in prolonged events, which may contribute to performance in ultra-endurance contexts [4,5]. Despite these adaptations, males typically outperform females in endurance events, with the magnitude of the sex-based performance gap varying by discipline, event demands, and competitive level (approximately 10–30% in many athletic contexts) [2,4,5]. Endogenous hormonal fluctuations across the menstrual cycle may influence selected physiological responses to exercise in female athletes; however, the current evidence linking menstrual-cycle phase to performance outcomes remains mixed and inconclusive. Findings are highly variable between individuals, and results differ across study designs and methodological approaches [1]. Ageing introduces an additional layer of complexity to endurance performance. Master athletes experience a progressive decline in physiological capacity, primarily driven by reductions in VO₂max, maximal heart rate, stroke volume, and skeletal muscle mass. After approximately 70 years of age, the rate of performance decline accelerates, exceeding 1.3% per year in both sexes. While older male runners generally retain higher absolute performance levels, they often exhibit steeper relative declines compared with female runners, suggesting that ageing may partially attenuate sex-based performance differences, particularly in long-duration endurance events [5,6,7].

Beyond performance-related determinants, endurance running is increasingly associated with the risk of Relative Energy Deficiency in Sport (REDs), a syndrome resulting from prolonged low energy availability and affecting multiple physiological systems, particularly endocrine, metabolic, musculoskeletal, and cardiovascular function. REDs has been documented in both male and female endurance runners across age groups, with sex-specific manifestations driven by hormonal and physiological variability. Female athletes tend to exhibit a greater number of affected physiological systems, with previous studies reporting an average of 2.9 affected systems in females (most frequently reproductive, endocrine, skeletal, and metabolic) compared with 1.6 in males (most frequently endocrine, skeletal and haematological) [8]. Furthermore, female runners more frequently report menstrual dysfunction, disordered eating behaviours, and compulsive training patterns, all of which are strongly linked to REDs development.

Importantly, emerging evidence suggests that the prevalence of REDs may be increasing among ageing master endurance runners, potentially due to cumulative training loads, age-related changes in energy requirements, and inadequate nutritional compensation [9]. Although long-term endurance training may attenuate certain aspects of physiological ageing, insufficient energy intake relative to expenditure may exacerbate hormonal disturbances, impaired bone health, and maladaptive musculoskeletal changes. Targeted training strategies combined with evidence-based nutritional interventions, therefore, represent a critical component in mitigating REDs risk across the lifespan, not only in master athletes but also as a preventive strategy in younger endurance runners.

Consequently, a multidisciplinary approach integrating sports medicine, nutrition, and training science is essential for the early identification and management of REDs Such an approach enables timely screening, individualised intervention, and improved long-term health and performance outcomes in endurance athletes of both sexes.

Therefore, the main aim of this study protocol is to comprehensively examine how biological sex and ageing influence physiological performance, skeletal muscle characteristics, bone health, and REDs risk in young and master endurance runners. The secondary aim is to compare endurance runners with their age- and sex-matched inactive counterparts to determine the extent to which long-term endurance training preserves physiological function and mitigates age-related decline across the lifespan. To address these aims, the primary outcome of this study is cardiorespiratory fitness, assessed as VO₂max, while musculoskeletal, metabolic, endocrine, and REDs related parameters are treated as secondary outcomes, providing complementary physiological context

2. Materials and Methods

Study Design

The overall study design, illustrated in Figure 1, follows a cross-sectional approach. Publishing this protocol enhances methodological transparency, preregistration of outcomes, and reproducibility of complex multimodal assessments involving invasive procedures. The study protocol was developed in accordance with the SPIRIT guidelines and is comprehensively documented using the SPIRIT checklist (Appendix A1), ensuring that all essential items required for reporting study protocols are systematically addressed. All measurements will be conducted under standardised laboratory conditions using calibrated equipment and trained personnel to ensure data quality and reproducibility across all study groups.

Sample Size

Based on the planned between-group comparisons across eight study groups (sex × age category × training status), an a priori sample size calculation for an omnibus factorial ANOVA (fixed effects) was performed (α = 0.05, power = 0.90). Assuming a mean effect size of Cohen’s f ≈ 0.42, the required total sample size was n = 112, corresponding to 14 participants per group. The sample size estimation was performed using G*Power software (version 3.1.9.2).

Study Subjects

A total of 112 subjects will be enrolled in this cross-sectional study and stratified into eight groups according to sex, age, and athletic status: (1) Young Male Endurance Runners, (2) Master Male Endurance Runners, (3) Young Male Age-Matched Controls, (4) Elderly Male Age-Matched Controls, (5) Young Female Endurance Runners, (6) Master Female Endurance Runners, (7) Young Female Age-Matched Controls, and (8) Elderly Female Age-Matched Controls. The young adult groups will include subjects aged 20–35 years, while the master and elderly groups will include individuals aged 65–80 years. Endurance runner groups will include elite-level Slovak athletes actively competing in national and international long-distance events. Young endurance runners will be defined as those with ≥3 years of national-level competitive experience, whereas master runners will be characterised by >5 years of continuous competitive participation. Group inclusion will be further validated using performance benchmarks of ≤35 min (young) and ≤55 min (masters) in the 10-km run. Control groups will comprise non-athletic individuals matched by sex and age, reporting <150 min of moderate and < 75 of vigorous weekly activity during the past five years. This distinction reflects sustained physiological performance and adaptation in the context of ageing between both sexes [10].

The study will be conducted in accordance with the Declaration of Helsinki. All participants will receive detailed information about the study aims, procedures, and potential risks, and written informed consent will be obtained prior to enrolment. Ethical approval has been granted by the Ethical Committee of the University Hospital Bratislava – Hospital of Ladislav Dérer (No. 31/2020).

All data will be anonymised and stored securely following applicable data-protection regulations, with access restricted to authorised research staff. The protocol adheres to SPIRIT guidelines, and anonymised datasets will be made available upon reasonable request in line with institutional and ethical requirements.

Inclusion Criteria

Subjects will be considered eligible if they meet all the following criteria. Young adult groups will comprise individuals aged 20–35 years, whereas older adult groups will comprise individuals aged 65–80 years. Endurance-trained participants must perform ≥300 min·week⁻¹ of structured endurance running, consistently maintained for at least three years, and compete at the national or international level. Physically inactive participants must report ≤150 min·week⁻¹ of moderate-intensity activity and ≤75 min·week⁻¹ of vigorous-intensity activity over the same period. Eligible participants must have a BMI between 18.5 and 35.0 kg·m⁻² and sufficient Slovak language proficiency to understand study procedures and instructions (Appendix A2.1). All participants will provide written informed consent and will be required to comply with all study requirements.

Female-Specific Considerations (Menstrual Status and Hormonal Contraception)

Menstrual status and hormonal contraceptive (HC) use will be recorded at screening. HC users (if any) will be eligible only with a stable regimen for ≥3 months, and the type and formulation of HC (including dose/route where available) will be reported. If HC users are enrolled, analyses will consider naturally menstruating women and HC users separately (e.g., combined vs progestin-only) in sensitivity analyses where appropriate. In the present cohort, no endurance-trained female runners using HC enrolled; therefore, analyses in female runners reflect naturally menstruating participants only.

Exclusion Criteria

Subjects will be excluded if they have musculoskeletal conditions that limit mobility or prevent participation in study assessments; acute or chronic infection; or diagnosed cardiovascular, neurological, metabolic, oncological, autoimmune, or other systemic diseases that contraindicate study involvement. Individuals with nutritional disorders (including malnutrition) or BMI < 18.5 kg·m⁻² will also be excluded. The use of medications or substances within the past six months that may interfere with biological analyses (e.g., systemic corticosteroids, immunosuppressants, chemotherapeutic agents, hormonal treatments, or other immunomodulatory drugs) will constitute an exclusion criterion. In addition, the use of non-steroidal anti-inflammatory drugs (NSAIDs) within 24 h prior to any study visit will not be permitted and will result in rescheduling or exclusion, depending on frequency and clinical necessity. Any current or prior use of doping or performance-enhancing substances, major surgery or hospitalisation within the previous six months, and pregnancy or lactation will also result in exclusion (Appendix A2.2).Female-specific exclusions (menstrual status and hormonal contraception)

Young adult female subjects will be excluded if they have initiated, discontinued, or changed the type, dose, or delivery method of hormonal contraception within the past 3 months, or if the contraceptive formulation and delivery method cannot be reliably documented (where applicable).

Familiarisation and Pre-Participation Medical Screening

Prior to enrolment, all prospective participants will complete a familiarisation session at the testing facility to ensure full understanding of study procedures, equipment, and the laboratory environment. This step is implemented to reduce procedural anxiety, improve compliance, and minimise learning effects during subsequent assessments.

Following familiarisation, a licensed sports medicine physician will conduct a comprehensive pre-participation medical evaluation, including medical history, resting heart rate and blood pressure measurements, physical examination, and resting and graded-exercise electrocardiography and assessment of maximal oxygen uptake (VO₂max) to screen for latent cardiovascular abnormalities. Additional assessments, such as spirometry, will be performed when clinically indicated.

Only participants who are medically cleared and present no contraindications to maximal or submaximal exertion will proceed to the study. This two-stage pre-inclusion process—familiarisation followed by medical clearance—ensures participant safety, strengthens the reliability of physiological measurements, and adheres to established ethical standards for human research [11,12].

Primary Outcomes

Cardiorespiratory fitness expressed as estimated (VO₂max) is defined as the primary outcome of interest, with secondary outcomes encompassing body composition, musculoskeletal function, biochemical and hormonal markers, and REDs–related screening variables. While VO₂max (mL·kg⁻¹·min⁻¹) will serve as the primary clinical outcome, estimated VO₂max normalised to fat-free mass (FFM) will be analysed as a secondary, mechanistically informative indicator of aerobic capacity relative to metabolically active tissue.

Cardiorespiratory Fitness Assessment

Maximal oxygen uptake (VO₂max) will be estimated indirectly from the maximal power output (Wmax) achieved during a continuous incremental cycling test using the American College of Sports Medicine (ACSM) metabolic equation for leg cycling:

Where Wmax represents the maximal achieved power output in watts and BM denotes body mass in kilograms. This equation is derived from the standard ACSM relationship between work rate and oxygen uptake during cycle ergometry and will be applied to estimate VO₂max at peak exercise intensity. VO₂max will serve as the primary physiological outcome, representing a validated indicator of aerobic capacity and cardiorespiratory health [13,14]. All testing will be conducted at the SPORTMED Sports Medicine Centre under medical supervision and in accordance with ACSM Guidelines for Exercise Testing and Prescription [12]. The test will begin with a 1-minute rest and a warm-up at 20 W, followed by a continuous ramp protocol with workload increments of 20 W/min until volitional exhaustion or clinical termination. Increment size may be adjusted slightly (e.g., 25–30 W/min) based on sex, age, and predicted capacity to achieve an optimal test duration of 8–12 minutes, consistent with validated ramp protocols [15].

Heart rate and blood pressure will be monitored continuously via 12-lead ECG (Quark T12, Cosmed, Rome, Italy), and brachial blood pressure will be assessed before, during, and after exercise (Metronik BL-6, STOLL Medizintechnik, Germany). Maximum workload (in W and W·kg⁻¹) will also be recorded. Tests will be terminated upon volitional fatigue, abnormal ECG responses, or safety-related criteria, following ACSM termination guidelines [12].

Secondly, to account for differences in body composition between sexes and age groups, VO₂max will be normalised to fat-free mass obtained by dual-energy X-ray absorptiometry (DXA) by using the following equation:

$$VO₂max\_FFM \left(mL·kg�¹ FFM·min�¹\right)={\displaystyle \frac{VO₂max\_abs }{2aFFM}}$$

All assessments will be administered by a licensed sports physician and a trained exercise physiologist to ensure participant safety, standardisation, and data quality.

Secondary Outcomes

Anthropometric and Body Composition Assessment

Basic anthropometric variables, including standing height and body weight, will be collected as input parameters for subsequent body composition analyses. Standing height will be measured to the nearest 0.1 cm using a digital stadiometer (BSM 170, InBody Co., Ltd., Cerritos, CA, USA), with participants barefoot and positioned upright. Body weight will be assessed to the nearest 0.1 kg using a calibrated bioelectrical impedance analyser (InBody 230, InBody Co., Ltd., Cerritos, CA, USA) with subjects wearing minimal clothing.

The bioimpedance system (InBody 230, InBody Co., Ltd., Cerritos, CA, USA) will be used to obtain standardised body weight and descriptive estimates of body fat percentage and skeletal muscle mass for the calculation of strength normalised to body mass and/or skeletal muscle mass, whereas DXA will serve as the reference method for detailed regional body composition, fat-free mass (FFM), and all bone-related outcomes [16,17].Therefore to obtain a comprehensive and accurate assessment of body composition, all participants will undergo a whole-body Dual-Energy X-ray Absorptiometry (DXA). Scans will be performed using standardised positioning procedures in the supine position, with careful alignment of the head, trunk, and limbs to minimise movement artefacts. All assessments will be conducted in the radiology department under the supervision of a certified radiologist and according to manufacturer guidelines to ensure measurement reliability and between-subject consistency.

DXA will provide a full set of bone-related parameters, including bone mineral content (BMC; g), bone mineral density (BMD; g·cm⁻²), and T-scores for whole body, proximal femur, and lumbar spine, enabling evaluation of bone health status. Additionally, body composition outcomes will be obtained, including total and regional lean soft tissue mass, fat mass, body fat percentage, appendicular lean mass (ALM), and indices relevant for functional and clinical assessment such as the appendicular lean mass index (ALMI; kg·m⁻²) and fat-free mass index (FFMI). Regional compartmental analysis (arms, legs, trunk) will also be performed. Furthermore, in accordance with the recent viewpoint advocating for sport-specific bone mineral density reference values for athletes rather than general population thresholds, we will compare our runners’ bone health classifications using both conventional clinical criteria and the updated athlete-oriented cut-offs [18].

Assessment of Lower Body Strength

Lower-body strength will be assessed using an isometric knee dynamometer (ARS dynamometry, S2P Ltd., Ljubljana, Slovenia) to determine maximal voluntary contraction (MVC) of the knee extensors and flexors, following validated procedures [19,20]. Testing will be performed in a custom-designed isometric chair adjusted individually to ensure optimal joint alignment and reproducibility, in accordance with established dynamometry guidelines [21,22].

Prior to MVC assessment, subjects will complete two submaximal warm-up contractions at approximately 50% and 80% of perceived maximal effort, separated by 30 seconds of rest, to minimise variability and enhance measurement accuracy [22]. Subjects will then perform three maximal isometric trials for both knee extension and flexion. Each contraction will involve a rapid force production sustained for five seconds, with strong verbal encouragement provided. A 90-second rest will be given between trials and a 3-minute rest between muscle groups to limit fatigue and potentiation effects [23,24].

Peak torque and the rate of torque development (RTD) will be recorded at 0–50 ms, 0–100 ms, 0–150 ms, and 0–200 ms to capture early-phase neuromuscular performance relevant for athletic capacity and age-related functional decline [25,26]. The highest-performing trial will be retained for analysis. To normalise relative MVC, the following formulas will be used to enable better interindividual comparisons among groups:

(1)

peak torque (PT; Nm) to body mass (m; kg):

$$RelativePT\left(Nm·k{g}^{-1}\right)={\displaystyle \frac{PT\left(Nm\right)}{m \left(kg\right)}}$$

(2)

peak torque (PT; Nm) to total lean body mass (LBM; kg):

$$RelativePT\left(Nm·kg LB{M}^{-1}\right)={\displaystyle \frac{PT\left(Nm\right)}{LBM \left(kg\right)}}$$

(3)

peak torque (PT; Nm) to thigh lean mass from DXA segment analysis (thigh LBM; kg):

$$RelativePT\left(Nm·kg thigh LB{M}^{-1}\right)={\displaystyle \frac{PT\left(Nm\right)}{thigh LBM \left(kg\right)}}$$

3. Discussion

This study aims to examine how sex and ageing jointly influence physical fitness, physiological adaptations, endurance performance, and REDs risk in young and master endurance runners. A secondary aim is to determine whether long-term endurance running can preserve physiological function and mitigate age-related decline.

Extensive scientific evidence suggests that long-term endurance running in advanced age is effective in attenuating age-related physiological decline [53,54,55]. However, its effects differ between male and female runners due to various underlying, yet unclear biological and physiological mechanisms. Therefore, a deeper understanding of the physiological changes associated with ageing and sex differences in endurance runners is crucial not only for their training optimisation and performance [56,57,58].

Current research highlights several critical gaps in knowledge, particularly regarding female endurance runners and the ageing process. The scientific evidence remains limited or inconsistent concerning long-term cardiovascular and musculoskeletal remodulations and adaptations in master female runners, endocrine system fluctuations associated with prolonged excessive endurance training, and the complex interactions between excessive endurance exercise, chronic low energy availability, and physiological maladaptation across the lifespan. These mechanisms warrant further investigation from physiological, health, and performance perspectives. Importantly, such research should not be limited only to female athletes, as growing evidence indicates REDs also affects male endurance runners, underscoring the need for sex-inclusive research approaches.

Clinical and Practical Implications

The outcomes of this study protocol will have direct implications for clinical and applied practice in endurance sports. By integrating cardiorespiratory fitness, musculoskeletal health, endocrine status, and REDs screening, the study framework may support sports physicians and sports nutrition professionals in distinguishing healthy long-term endurance adaptations from early maladaptive responses, particularly in ageing athletes. This approach may facilitate earlier identification of REDs risk and more individualised preventive strategies across sex and age categories.

Expected Outcomes of the Study

It is expected that endurance-trained master athletes will demonstrate more favourable cardiorespiratory fitness and body composition profiles compared with age-matched sedentary controls. Differences between training status, age category, and sex are anticipated to emerge across selected physiological and cardiometabolic outcomes, reflecting long-term adaptations to endurance exercise and the ageing process. Given the growing recognition of low energy availability as a key factor underlying REDs, this study may also provide indirect insight into how chronic endurance training, in combination with age- and sex-specific energy demands, relates to physiological health markers in older athletes. Although causal relationships cannot be established due to the cross-sectional design, the findings are expected to contribute to a better understanding of the interaction between endurance training, energy availability, and healthy ageing, thereby informing future longitudinal studies and preventive strategies in master athletes.

Strengths of the Study

The main strength of this cross-sectional study is its comprehensive and multimodal assessment strategy. The comprehensive methodology enables a holistic linkage between physical performance, nutritional status, and overall health status across age and sex. The study further benefits from a robust design that includes young and master endurance runners alongside with their age- and sex-matched inactive counterparts, allowing precise evaluation of the effects of ageing, long-term endurance training, and sex differences. Moreover, the use of standardised screening tools for LEA strengthens the ability to detect REDs risk in a clinically relevant age and sex-specific manner in endurance runners.

Limitations of the Study

On the other hand, this study also has several important limitations. An important limitation of this study is that its cross-sectional design limits the ability to capture long-term physiological and health changes in the subgroups of the endurance runners. This short observational time frame is only focused on a single one-week period, where all assessments of subjects’ habitual week are conducted. Therefore, this study design does not allow for longitudinal monitoring of training load, dietary patterns, hormonal fluctuations, or menstrual cycle–related variability in female participants, which may influence energy availability, hormonal responses, and REDs manifestation over longer time scales. Additionally, the REDs screening tools used (LEAF-Q, LEAM-Q, IOC REDs CAT2) rely only on self-reported symptoms. Thus, these tools may be vulnerable to recall bias; however, their use in combination with objective physiological and biochemical measures strengthens overall interpretability. Moreover, the REDs risk categories, which derive from questionnaires, must be interpreted with caution, complemented by other objective physiological and biochemical markers collected in this study and afterwards interpreted by a responsible medical specialist.

4. Conclusions

This study protocol presents a comprehensive cross-sectional framework to investigate the combined effects of ageing, biological sex, and long-term endurance running on physiological performance, musculoskeletal and bone health, nutritional status, and the risk of REDs development. The protocol is designed to generate a multidimensional dataset across young adult and master endurance runners and their age-matched inactive counterparts. Importantly, this protocol has clear clinical and practical relevance, providing a structured framework for translational application in endurance athletes across the lifespan.