Potential Associations Between Anthropometric Characteristics, Biomarkers, and Sports Performance in Regional Ultra-Marathon Swimmers: A Quasi-Experimental Study

Abstract

Background/Objectives: This study aimed to investigate the associations of anthropometric characteristics with performance and potential biomarker changes resulting from a continuous 10 h ultra-marathon swimming effort in regional-level swimmers. Methods: Nine adult male swimmers (age: 43 ± 6 years) participated in a 10 h swim in a 50 m outdoor pool, self-managing their nutrition and hydration breaks. Pre- and post-swim measurements included body weight (BW), body fat percentage (BF%), limb lengths (LL), circumferences (C), lean mass (LM), body mass index (BMI), skinfold thicknesses, heart rate (HR) and blood pressure (BP). Results: A significant reduction was observed in bicep skinfold thickness (Fb) (p = 0.022), while both HR and systolic BP increased post-effort (p = 0.030 and p = 0.045, respectively). Also, most anthropometric parameters, such as BMI, LM, and some C, remained unchanged (p ≥ 0.05). A statistically significant negative correlation was found between post-swim hip circumference (Ph) and total swimming distance (r = –0.682, p = 0.043). Conclusions: While most anthropometric traits remained stable and unrelated to performance, isolated changes in specific biomarkers indicate a physiological response to prolonged exertion. Although pacing and nutritional strategies were not directly examined, observational data—such as consistent swimming rhythm, time allocation for active recovery (AR), and structured carbohydrate intake—suggest these factors may have contributed to performance maintenance and probably the lack of body composition differences after the ultra-marathon effort. These insights are interpretive and align with the existing literature, highlighting the need for future studies with targeted experimental designs.

1. Introduction

Swimming is a popular and competitive sport requiring a combination of aerobic capacity and endurance [1]. There are a variety of swimming events, from 50 m in the pool to 25 km and more in open water variations. Open water swimming and ultra-marathon distances have an augmented participation, especially during the summer period [2]. Therefore, there is interest in the examination of several factors that affect performance, each to varying degrees. Among them, the most influential are gender, age, anthropometric characteristics, and body composition [3,4].

1.1. Gender and Age

Men generally outperform women in most sports, mainly due to their higher muscle mass percentage [5]. As such, the shorter the event’s duration, the more performance differences are observed in favor of men, owing to the efficiency of power-speed movements enabled by greater muscle mass [6], particularly in adult swimmers [7]. These differences appear to diminish in long-distance and ultra-endurance swimming [8,9], where sex-based discrepancies in race pace are smaller [7].

In contrast, in marathon running, the performance gap between genders tends to increase, especially among elite runners [6]. Furthermore, Senefeld et al. [10] noted that competition level amplifies this gap. Some studies have reported better performance by women in ultra-swimming events (e.g., a 32.5 km swim), with women outperforming men by an average of 16 ± 12% [11], while others found no performance difference at 20 °C water temperature [12]. Regarding age, the fastest ultra-endurance swimmers today are older, regardless of gender [8]. Research suggests that participants during the fourth decade of their life have conducive conditions for peak performance in ultra-swimming across both genders [3,13,14,15].

1.2. Identifying Ultra–Marathon Swimming

Ultra-marathon swimming presents a unique physiological challenge due to prolonged exposure to water, horizontal body positioning, and thermoregulatory demands. Compared to land-based endurance events, swimmers must manage buoyancy, cold water exposure, and often reduced gastrointestinal tolerance during feeding. Energy expenditure during ultra-swimming is estimated between 600 and 900 kcal/h, depending on intensity and water temperature. Research has shown that even minimal anthropometric differences, such as limb length or torso fat mass, can influence hydrodynamics and fatigue onset. Despite the growth of ultra-distance events globally, there is a lack of standardized data on how body composition impacts performance in ultra-swimmers, especially those performing self-paced efforts in controlled environments.

However, this varies across studies: Rust et al. [16] identified 29 years as the ideal age, while other work suggested performance declines with age. Still, this was primarily noted in triathlon studies, and when swimming was examined independently, it showed the least age-related performance decline [4]. Another considerable point is the anthropometrics and body composition, whose role is to evaluate and predict performance across various sports [17]. Early studies in ultra-swimming found no significant relationship between performance and body mass, BMI, or limb length [18]. Over time, theories regarding the role of anthropometric features in ultra-swimming performance have evolved, suggesting a more nuanced relationship.

In their study, Knechtle et al. [19] examined 18 male and 7 female athletes participating in two ultra-distance open-water swims (26.4 and 88 km). They found a slight but statistically significant correlation between upper limb length and swimming performance, indicating that swimmers with longer arms tended to achieve faster times, potentially due to improved stroke length and propulsion efficiency. Additionally, body fat percentage (BF%) was positively associated with performance, particularly in the longer 88 km swim, suggesting a thermoregulatory or buoyancy advantage in cold-water conditions.

The authors concluded that although anthropometric characteristics were not the sole predictors of success, they may contribute meaningfully in conjunction with pacing, endurance capacity, and environmental adaptation strategies. Other findings revealed that body fat may decrease after ultra-endurance events [20,21]. In a study by Knechtle et al. [17], two experienced ultra-endurance swimmers participated in a 12 h continuous swim, during which no significant changes were observed in body mass, fat mass, or skeletal muscle mass. These results suggest that prolonged swimming, even at ultra-endurance durations, may not elicit substantial alterations in body composition when hydration and nutritional intake are adequately maintained.

The authors hypothesized that the thermoregulatory effects of water, combined with the horizontal body position and low-impact muscular activity, may contribute to maintaining homeostasis in body tissues. Furthermore, the swimmers consumed fluids and carbohydrates at regular intervals, minimizing the risk of energy deficit and dehydration. Ultra-marathon swimming has seen an increased participation among adults and middle-aged athletes worldwide. However, misconceptions still exist regarding how anthropometric and body composition variables affect performance across different ages and genders. Therefore, this study aims to address the demands of a 10 h ultra–marathon swimming effort on body composition and physiological indices, investigating simultaneously how these variables behave before and after swim effort and their association with performance in regional-level male swimmers, orienting coaches, and ultra-marathon swimmers on the strategies that must be implemented before and during that kind of effort.

2. Materials and Methods

2.1. Participants

Participants were recruited through a regional swimming club. All the swimmers who were accepted to participate were healthy, trained male swimmers specializing in freestyle, competing at a regional level with a minimum of five years of experience in long-distance swimming. Inclusion criteria included (a) good general health, (b) daily participation in swimming training, (c) participation in swimming meetings, and (d) placement within the top sixteen of their age group in at least one national championship event.

Nine male healthy swimmers participated in the study. Their mean age was 43 ± 6 years, with a training history of 11 ± 9 years in long-distance swimming. The average height was 174.3 ± 8.5 cm, weight 82.3 ± 12.4 kg, arm span (Aoh) 175.6 ± 10.2 cm, and BMI 27 ± 3 kg/m². Training frequency ranged from 4 to 5 times per week, with a daily training volume of 4 to 5 km. Before data collection, all swimmers were thoroughly informed about the study’s procedures and safety protocols. Informed consent was obtained from all subjects involved in the study. The study was conducted in accordance with the Declaration of Helsinki. Also, it is hereby certified that the Research Ethics and Deontology Committee of the Aristotle University of Thessaloniki was established in accordance with Article 21 of Law 4521/2018, which was published on March 2, 2018. Prior to this date, there was no obligation to submit a research proposal for approval, as such a requirement was not provided for by law. The study measurements were performed in three phases: before, during, and after the ultra-swimming session.

2.2. Measurements

2.2.1. Before Ultra Swimming

Before the ultra-marathon effort, the swimmers were measured for anthropometrics and body composition. Anthropometric assessments included body type classification (endomorph, mesomorph, ectomorph), height, weight, and BMI. Height and body weight (BW) were measured using a stadiometer and digital scale, respectively (Seca GmbH & Co. KG., Hamburg, Germany). Limb lengths (LL), seated height (As), Aoh, and foot length (Apl) were measured too.

Circumferences (C) were recorded for the arm (Pa), thigh (Pl), waist (Pm), hip (Ph), and chest (Pc), taking at the midpoint of each limb and standard anatomical landmarks according to International Society for the Advancement of Kinanthropometry (ISAK) protocol, using a flexible non-elastic tape measure (Seca 201, Seca GmbH & Co. KG., Hamburg, Germany).

Skinfold thickness was assessed using a Harpenden skinfold caliper (Baty International, Burgess Hill, UK) with a constant pressure of 10 g/mm² and a precision of 0.2 mm. Also, LLwere recorded using a metal anthropometric tape with ± 0.1 cm accuracy. Measurements were taken at four anatomical sites on the right side of the body: triceps (Ft), biceps (Fb), subscapular (Fs), and suprailiac (Fh), following the standardized procedures recommended by the ISAK. Each site was measured three times by the same trained anthropometrist, and the median value was used for analysis to reduce intra-rater variability. The sum of the four skinfolds was then applied to the Durnin and Rahaman equation [22] to estimate BF%. The specific formula used was:

BF% = (4.95/BD − 4.5) × 100, where BD = 1.161 − 0.0632 × log (SF).

HR and BP were measured using an automatic sphygmomanometer (Omron M6 Comfort, Omron Healthcare Co., Kyoto, Japan). Measurements were taken in a resting supine position, 10–15 min before and approximately 4–6 min after the swim to assess pre- and post-effort values. All measurements were conducted by the same certified anthropometrist (ISAK Level 1), ensuring high inter-rater reliability.

Thereafter, the initial measurements, the participants followed the same warm-up, which included a five-minute full-body dry land routine of dynamic and explosive exercises. The participants did not follow an additional in-water warm-up because it was considered unnecessary for that kind of effort. At the end of the dry-land warm-up procedure, the swimmers had ten minutes of rest and continued with the swimming effort.

The ultra-endurance swimming trial was conducted in an outdoor 50 m Olympic-size pool and lasted for 10 h. All environmental conditions, including pool water temperature (26 °C) and ambient temperature (22–25 °C), were monitored and recorded using a calibrated thermometer (Extech 445580, Extech Instruments, Nashua, NH, USA).

2.2.2. During the Swim

The number of pool laps completed, stroke frequency, stroke–breath coordination, and leg kicking were observed through direct visual assessment, following protocols previously described in swimming performance analysis literature [23]. Break duration and type (active/passive), food and supplement intake, and perceived exertion were recorded hourly. The food and supplement intake included the most preferred and often consumed carbohydrate meals for each swimmer (

Table 1. Food and supplement intake.

Liquids	Food	Supplements	Drugs
Refreshment drinks Coffee Isotonics Water Electrolytes	Banana Chocolate Tahini Sandwich Chicken Biscuits Croissant Pasta Bread	Powerbar Carbons Fruit gels	Anti-inflammatory pills Caffeine Caffeine gel Salt stick

). The Borg Rating of Perceived Exertion (RPE) (6–20 scale) was used to assess exercise intensity [24]. Swimmers could take breaks at will for hydration, food intake, or urination. Also, after each feeding period, a doctor was checking about the swimmers’ condition, ensuring the safety of their participation.

2.2.3. Post-Swim Measurements

Post-swim assessments included measurements of fat percentage, body C, HR, and BP (4–6 min post-swim). Participants also reported any pain, injuries, hypothermia symptoms, water temperature satisfaction, and food/liquid intake. No re-measurements were made for height, limb lengths, or Apl.

2.3. Statistical Analysis

A priori sample size (n) calculation was completed with G*Power 3.1.9.7 (Düsseldorf, Germany, Universität Düsseldorf) on Windows [25]. Determining a high effect size at 0.9 for one group and two measurements (before, and after the ultra–marathon effort), we ascertained that a sample size of 9 participants, giving a 66% chance to reject the null hypothesis, will be needed to detect significant differences. Descriptive statistics were used for all variables. The Shapiro–Wilk test assessed normality. Due to the small sample size, the sample was analyzed as a single group. Paired sample t-tests compared pre- and post-swim values. Pearson’s correlation analysis identified relationships between variables and performance. SPSS (IBM Corp. Released 2017. IBM SPSS Statistics for Windows, Version 25.0. Armonk, NY, USA: IBM Corp.) was used for all analyses, with significance set at α = 0.05.

3. Results

According to the Shapiro–Wilk test, the data were normally distributed (p > 0.05). Thus, parametric analyses were followed for all examined variables. Each participant’s BF% and the total distance covered during the 10 h swim were also recorded individually as shown in

Table A1. Individual body fat percentage and total distance swum per participant.

Participant	Fat (%)	Distance (m)
1	20.2	33.000
2	21.4	19.000
3	31.6	24.600
4	19.6	26.200
5	19.6	33.600
6	25.9	26.100
7	20.4	18.900
8	34.3	27.000
9	35.0	25.000

(Appendix A). Fat percentages ranged from 19.6 to 35.0%, and distances covered ranged between 18,900 m and 33,600 m. However, no apparent association was observed between individual fat percentage and total distance swum.

Statistically significant differences were observed in the Fb and BP after the 10 h swimming effort (Figure 1 and Figure 2).

Analysis of the swimmers’ pacing strategy revealed a consistent pattern: a steady leg-kick rhythm and a 2:1 arm-stroke to breath ratio, occasionally shifting to 3:1. Stroke frequency remained consistent at approximately 30 strokes per minute, reflecting a low-intensity and controlled swimming pace. Also, each swimmer followed their personal nutritional preferences; however, across all participants, high-glycemic-index foods rich in carbohydrates, with moderate protein and low-fat content, were preferred. None of the athletes took excessively long breaks, and all maintained a steady routine of swimming and rest.

Regarding the RPE (Ratings of Perceived Exertion), participants reported their effort levels in a consistent pattern. Specifically, during the first and second hours, RPE scores ranged between 7 and 9. Between the fourth and seventh hour, values increased by two to three points and then stabilized. In the final hours, RPE approached 20 (Figure 3). The actual swimming time out of the total 10 h was 509.1 min. An additional 59.1 min were spent in active recovery (AR) and 31.8 min in passive recovery(PR) (Figure 4).

Additionally, no significant correlation was observed between fat percentage and total swim distance (r = −0.215, p = 0.57), nor between BMI and distance covered (r = −0.095, p = 0.78). The strongest association with performance was found in post-swim Ph (r = −0.682, p = 0.043), accounting for approximately 47% of the variance in swim distance (R² = 0.465). This is visually represented in Figure 5. All statistical results are presented with two decimal precision and were verified for normality using the Shapiro–Wilk test. The full dataset is available in Appendix A.

No statistically significant changes were observed in F, LBM, BMI, and HR (p > 0.05) (

Table 2. Mean and standard deviation of BF%, LM (lean mass), BMI, and HR before and after the 10 h swim.

Parameters	Meters (m)	BF% (%)	LBM (kg)	BMI (kg/m2)	HR (bpm)	p-Value
Before	----------------	24.2 ± 6.8	61.8 ± 11.8	27 ± 3	71 ± 9
After	25,993 ± 4832	25 ± 5.9	62 ± 12.4	27 ± 3	117 ± 18	0.06

BF%: Body fat percentage; LBM: Lean body mass; BMI: Body mass index; HR: Heart rate.

).

BW remained relatively stable pre- and post-swim (82.3 ± 12.4 vs. 82.0 ± 12.6 kg, p > 0.05), suggesting that any minor fluctuations were likely due to transient fluid shifts rather than actual fat mass reduction. Similarly, no statistically significant changes were found in the C of the arm, thigh, waist, hip, and chest (p > 0.05) (

Table 3. Mean and standard deviation of body C before and after the 10 h swim.

Parameters	Arm (cm)	Thigh (cm)	Waist (cm)	Hip (cm)	Chest (cm)	p-Value
Before	31.9 ± 2	54.3 ± 4.2	89.0 ± 7.8	103.0 ± 7.3	104.7 ± 7.5
After	32.4 ± 2	54.3 ± 4.7	89.0 ± 7.9	101.7 ± 7.5	104.7 ± 7.3	0.06

).

A statistically significant negative correlation was found between post-swim Ph and total distance covered by the swimmers (r = −0.682, R² = 0.465, p = 0.043) (Figure 5).

Additionally, time distribution across swimming, AR, and PR revealed that swimmers dedicated approximately 10% of total time to breaks, with a preference for active over PR (59.1 vs. 31.8 min). Despite variation in nutritional choices, all athletes consumed high-glycemic carbohydrate sources consistently across the effort. Although no direct statistical analysis was conducted on dietary intake, the stable pacing and RPE increase suggest that nutrition and hydration strategies may have contributed to energy maintenance and delayed onset of exhaustion.

4. Discussion

This study investigated the relationship between anthropometric characteristics and performance in ultra-marathon swimming over a continuous 10 h trial. The main findings indicated that most anthropometric variables, including BW, BMI, and C, remained unchanged following the swim. A significant reduction was observed in the biceps’ skinfold thickness, while HR and BP increased post-effort. Notably, a significant negative correlation was found between post-swim hip C and distance swum. These results suggest that morphological traits may not be strongly associated with performance in ultra-endurance swimming, highlighting instead the potential importance of pacing, nutrition, and physiological adaptability.

4.1. Anthropometrics

Most anthropometric characteristics were not significantly associated with performance. No significant changes were observed in BW, BMI, lean mass, or foot size—unsurprising given the anatomical stability of skeletal structures and the low intensity of the swim. Similarly, body C—including arm, thigh, waist, hip, and chest—showed no significant changes, confirming the stability of body composition and fat distribution. A negative correlation between Ph and total swim distance was identified. These observations are consistent with prior work by Knechtle et al. [17], who found no meaningful correlation between anthropometric traits and ultra-swim performance during a 12 h swim, reinforcing the limited predictive power of these variables in such conditions. Probably, the smaller hip girth may reduce frontal drag and perceived exertion, potentially allowing swimmers to cover greater distances—a hypothesis aligned with previous findings; however, the justification of this hypothesis demands the implementation of kinematic and biomechanical analysis [26,27].

4.2. Body Composition

Nearly all measured parameters remained stable after the 10 h swim, except for the biceps skinfold, which showed a significant decrease. The reduction in biceps skinfold might be attributed to localized fat oxidation, although the literature does not consistently support this theory [28]. Brobakken et al. [29] reported similar findings of local fat reduction following targeted exercise in the abdominal region. Similarly, Speedy et al. [30] and Weitkunat et al. [31] reported a reduced fat mass after prolonged endurance efforts. In contrast, Knechtle et al. [17] found no change in body composition variables after a 12 h ultra-swim. These inconsistencies may be due to differences in hydration and nutritional intake, which affect body composition measurements during prolonged exertion.

Moreover, changes in BW would require an energy deficit of approximately 7700 kcal per kilogram of fat. With fat oxidation averaging around 300 kcal/hour and concurrent caloric intake during the swim, meaningful fat mass loss was unlikely. Thus, any slight weight variations were most likely due to fluid balance shifts [32]. These null results should be interpreted with caution. Negative findings in body composition metrics may also reflect methodological limitations, such as the sensitivity of field-based assessments and intra-individual variability in hydration levels. Future studies should consider applying dual-energy X-ray absorptiometry (DEXA) or bioelectrical impedance techniques to confirm these findings.

4.3. Cardiopulmonary Biomarkers

Cardiovascular responses were as expected, with increased HR and a transient drop in BP post-effort. These responses reflect the elevated cardiac workload during long-duration exercise. The observed increase in HR and changes in BP were measured within 4 to 6 min after cessation, aligning with typical hemodynamic recovery behavior [33].

Nutrition and hydration are critical for performance optimization in endurance swimming. Future research should aim to identify optimal meal composition and timing strategies specific to the aquatic environment, where buoyancy and horizontal body positioning introduce unique challenges, including potential gastroesophageal reflux.

4.4. Nutrition and Recovery

While not directly analyzed through inferential statistics, the documented nutritional strategies—centered on high-glycemic-index carbohydrate foods with moderate protein—appeared to align with optimal endurance protocols. AR was favored over passive breaks, suggesting an intentional pacing approach. While the present study could not quantitatively assess the individual effect of pacing or nutrition strategies, the observational data indicate that consistent carbohydrate intake and AR may contribute to performance maintenance. Future studies should isolate these factors under controlled conditions to offer data-driven recommendations for endurance swimmers. The RPE curve, which progressively increased but remained within manageable limits for most of the session, may reflect the successful application of these nutritional and pacing strategies in delaying fatigue.

The current findings must be interpreted within the context of certain limitations: the small sample size (n = 9), inclusion of only male participants (because they were the unique who accepted to participate in the study), absence of a control group, the lack of continuous physiological monitoring (e.g., core temperature, lactate, or real-time HR tracking) during the swim and the appropriate statistical analysis (i.e., regression analysis). Additionally, in future studies must be analyzed in detail the hydration/nutrition strategies. Concluding, these factors restrict the generalizability of our results and underline the necessity for larger, multi-centered trials to validate and expand upon our observations.

5. Conclusions

This study focused on ultra-marathon swimming, specifically examining the relationship between anthropometric characteristics and performance during a 10 h continuous swim. While a minor correlation was found between waist circumference and swimming distance, most anthropometric variables appeared to have minimal association with performance. Significant post-effort changes were limited to a reduction in Fb and an increase in HR and BP. BW and other key morphological measures remained unaffected. Although no direct statistical comparison was performed between strategic and morphological variables, the descriptive trends observed suggest that race management and nutritional strategies may play a pivotal role in sustaining performance under ultra-endurance conditions. This study highlights the need for further research on ultra-endurance swimming and the anthropometric evaluation of athletes engaging in prolonged aquatic efforts.