Andrea Wirth

Differential correlations between anthropometry, training volume, and performance in male and female Ironman triathletes.

Knechtle, B, Wirth, A, Baumann, B, Knechtle, P, Rosemann, T, and Senn, O. Differential correlations between anthropometry, training volume, and performance in male and female Ironman triathletes. J Strength Cond Res 24(10): 2785-2793, 2010-We investigated in 27 male Ironman triathletes aged 30.3 (9.1) years, with 77.7- (9.8) kg body mass, 1.78- (0.06) m body height, 24.3- (2.2) kg·m−2 body mass index (BMI), and 14.4 (4.8) % body fat and in 16 female Ironman triathletes aged 36.6 (7.0) years, with 59.7- (6.1) kg body mass, 1.66- (0.06) m body height, 21.5 (1.0) kg·m−2 BMI, and 22.8 (4.8) % body fat to ascertain whether anthropometric or training variables were related to total race time. The male athletes were training 14.8 (3.2) h·wk−1 with a speed of 2.7 (0.6) km·h−1 in swimming, 27.3 (3.0) in cycling, and 10.6 (1.4) in running. The female athletes trained for 13.9 (3.4) h·wk−1 at 2.1 (0.8) km·h−1h in swimming, 23.7 (7.6) km·h−1 in cycling, and 9.0 (3.7) km·h−1 in running, respectively. For male athletes, percent body fat was highly significantly (r2 = 0.583; p < 0.001) associated with total race time. In female triathletes, training volume showed a relationship to total race time (r2 = 0.466; p < 0.01). Percent body fat was unrelated to training volume for both men (r2 = 0.001; p > 0.05) and women (r2 = 0.007; p > 0.05). We conclude that percent body fat showed a relationship to total race time in male triathletes, and training volume showed an association with total race time in female triathletes. Presumably, the relationship between percent body fat, training volume, and race performance is genetically determined.

Personal best marathon performance is associated with performance in a 24-h run and not anthropometry or training volume

Objective: In this study, the influence of anthropometric and training parameters on race performance in ultra-endurance runners in a 24-h run was investigated. Design: Descriptive field study. Setting: 24-h run in Basel 2007. Participants: 15 male Caucasian ultra-runners (mean (SD) 46.7 (5.8 years), 71.1 (6.8 kg), 1.76 (0.07 m), body mass index 23.1 (1.84 kg/m2)). Interventions: None. Main outcome measures: Age, body mass, body height, length of lower limbs, skin-fold thicknesses, circumference of extremities, skeletal muscle mass, body mass, percentage of body fat, and training volume in 15 successful finishers were determined to correlate anthropometric and training parameters with race performance. Results: No significant association (p>0.05) was found between the reached distance and the anthropometric properties. There was also no significant association between the reached distance with the weekly training hours, running years, the number of finished marathons and the number of finished 24-h runs. The reached distance was significantly (p<0.05) positively correlated with the personal best marathon performance (r2 = 0.40) and the personal best 24-h run distance (r2 = 0.58). Furthermore, the personal best marathon performance was significantly and positively correlated (p<0.01) with the best personal 24-h run distance (r2 = 0.76). Conclusions: Anthropometry and training volume does not seem to have a major effect on race performance in a 24-h run. Instead, a fast personal best marathon time seems to be the only positive association with race performance in a 24-h run.

Training volume and personal best time in marathon, not anthropometric parameters, are associated with performance in male 100-km ultrarunners.

Knechtle, B, Wirth, A, Knechtle, P, and Rosemann, T. Training volume and personal best time in marathon, not anthropometric parameters, are associated with performance in male 100-km ultrarunners. J Strength Cond Res 24(3): 604-609, 2010-We investigated the relation between selected anthropometric and training variables and the personal best time in a marathon with total race time in 66 Caucasian male nonprofessional ultrarunners in a 100-km run. In the multiple linear regression analysis, the average weekly training volume in kilometers (r2 = 0.224, p < 0.01) and the personal best time in a marathon (r2 = 0.334, p < 0.01) were significantly associated with total race time, whereas no anthropometric variable was related to race performance (p > 0.05). We conclude that high training volume and a fast time in a marathon were more important for a fast race time in male 100-km runners than any of the determined anthropometric variables.

Intra- and Inter-Judge Reliabilities in Measuring the Skin-Fold Thicknesses of Ultra Runners under Field Conditions

Inter- and intra-judge reliabilities of skinfold measures were investigated in a sample of 27 men and 11 women ultramarathon runners. Two physicians had agreement higher than 90% in field measurements before an ultramarathon race.

Predictors of race time in male Ironman triathletes: physical characteristics, training, or prerace experience?

The aim of the present study was to assess whether physical characteristics, training, or prerace experience were related to performance in recreational male Ironman triathletes using bi- and multivariate analysis. 83 male recreational triathletes who volunteered to participate in the study (M age 41.5 yr., SD = 8.9) had a mean body height of 1.80 m (SD = 0.06), mean body mass of 77.3 kg (SD = 8.9), and mean Body Mass Index of 23.7 kg/m2 (SD = 2.1) at the 2009 IRONMAN SWITZERLAND competition. Speed in running during training, personal best marathon time, and personal best time in an Olympic distance triathlon were related to the Ironman race time. These three variables explained 64% of the variance in Ironman race time. Personal best marathon time was significantly and positively related to the run split time in the Ironman race. Faster running while training and both a fast personal best time in a marathon and in an Olympic distance triathlon were associated with a fast Ironman race time.

Increase of Total Body Water With Decrease of Body Mass While Running 100 km Nonstop—Formation of Edema?

We investigated whether ultraendurance runners in a 100-km run suffer a decrease of body mass and whether this loss consists of fat mass, skeletal muscle mass, or total body water. Male ultrarunners were measured pre- and postrace to determine body mass, fat mass, and skeletal muscle mass by using the anthropometric method. In addition, bioelectrical impedance analysis was used to determine total body water, and urinary (urinary specific gravity) and hematological parameters (hematocrit and plasma sodium) were measured in order to determine hydration status. Body mass decreased by 1.6 kg (p < .01), fat mass by 0.4 kg (p < .01), and skeletal muscle mass by 0.7 kg (p < .01), whereas total body water increased by 0.8 L (p < .05). Hematocrit and plasma sodium decreased significantly (p < .01), whereas plasma urea and urinary specific gravity (USG) increased significantly (p < .01). The decrease of 2.2% body mass and a USG of 1.020 refer to a minimal dehydration. Our athletes seem to have been relatively overhydrated (increase in total body water and plasma sodium) and dehydrated (decrease in body mass and increase in USG) during the race, as evidenced by the increased total body water and the fact that plasma sodium and hematocrit were lower postrace than prerace. The change of body mass was associated with the change of total body water (p < .05), and we presume the development of

No fluid overload in male ultra-runners during a 100 km ultra-run.

We investigated the change in body composition and hydration status in 27 male ultra-runners during a 100 km ultra-run. The athletes drank fluids ad libitum during the run; intake of calories, fluids, and electrolytes during performance were determined. Body mass decreased by 1.9 kg, haematocrit decreased, plasma [Na+] remained unchanged, and urinary specific gravity and plasma volume increased. Fluid intake was 0.52 (0.18) L/h and was related to running speed (r = 0.50; p = 0.0081). Δ body mass was associated with total fluid intake during the race (r = 0.49, p = 0.0095). Sodium intake amounted to 425 (478) mg/h and potassium intake to 140 (179) mg/h. Sodium and potassium intake were not related to either postrace concentration or change in plasma concentration. Sodium intake, however, was related to Δ urinary sodium concentration (r = 0.45, p = 0.0227). The increase in plasma volume was significantly and negatively related to both postrace plasma [Na+] (r = − 0.42, p = 0.0278) and the postrace potassium-to-sodium ratio in urine (r = − 0.44, p = 0.0218). To conclude, we found no fluid overload in these ultra-runners, the increase in plasma volume was most probably due to a stimulation of the renin-angiotensin-aldosterone system (RAAS) since sodium intake was not related to both the change in plasma [Na+] or postrace plasma [Na+].

A comparison of fat mass and skeletal muscle mass estimation in male ultra-endurance athletes using bioelectrical impedance analysis and different anthropometric methods.

Two hundred and fifty seven male Caucasian ultra-endurance athletes were recruited, pre-race, before different swimming, cycling, running and triathlon races. Fat mass and skeletal muscle mass were estimated using bioelectrical impedance analysis (BIA) and anthropometric methods in order to investigate whether the use of BIA or anthropometry would be useful under field conditions. Total body fat estimated using BIA was significantly high (P < 0.001) compared with anthropometry. When the results between BIA and anthropometry were compared, moderate to low levels of agreement were found. These results were in accordance with the differences found in the Bland-Altman analysis, indicating that the anthropometric equation of Ball et al. had the highest level of agreement (Bias = -3.0 ± 5.8 kg) with BIA, using Stewart et al. (Bias = -6.4 ± 6.3 kg), Faulkner (Bias = -4.7 ± 5.8 kg) and Wilmore-Siri (Bias = -4.8 ± 6.2 kg). The estimation of skeletal muscle mass using BIA was significantly (P < 0.001) above compared with anthropometry. The results of the ICC and Bland-Altman method showed that the anthropometric equation from Lee et al. (Bias = -5.4 ± 5.3 kg) produced the highest level of agreement. The combined method of Janssen et al. between anthropometry and BIA showed a lower level of agreement (Bias = -12.5 ± 5.7 kg). There was a statistically significant difference between the results derived from the equation of Lee et al. and Janssen et al. (P < 0.001). To summarise, the determination of body composition in ultra-endurance athletes using BIA reported significantly high values of fat and skeletal muscle mass when compared with anthropometric equations.

An Ironman Triathlon Does Not Lead to a Change in Body Mass in Female Triathletes

In 16 female nonprofessional Ironman triathletes, body mass, percent body fat, and skeletal muscle mass were determined before and after an Ironman race in order to detect changes. Selected hematological and urinary variables as well as percent total body water were measured in order to quantify a change in hydration status. Body mass, skeletal muscle mass, percent body fat, and percent body water did not change (p > 0.05). Plasma volume increased significantly by 8.1 (13.7) % (p < 0.05). The significant increase in plasma volume, plasma urea concentration, and urinary specific gravity after the race was associated with a significant fall in hematocrit and plasma sodium concentration (p < 0.05). In contrast to studies of male Ironman triathletes, we could not detect a decrease in body mass in female Ironman triathletes. The statistically insignificant loss of 0.6 kg in body mass was smaller than reported in studies of male athletes.

A faster running speed is associated with a greater body weight loss in 100-km ultra-marathoners.

Abstract In 219 recreational male runners, we investigated changes in body mass, total body water, haematocrit, plasma sodium concentration ([Na+]), and urine specific gravity as well as fluid intake during a 100-km ultra-marathon. The athletes lost 1.9 kg (s = 1.4) of body mass, equal to 2.5% (s = 1.8) of body mass (P < 0.001), 0.7 kg (s = 1.0) of predicted skeletal muscle mass (P < 0.001), 0.2 kg (s = 1.3) of predicted fat mass (P < 0.05), and 0.9 L (s = 1.6) of predicted total body water (P < 0.001). Haematocrit decreased (P < 0.001), urine specific gravity (P < 0.001), plasma volume (P < 0.05), and plasma [Na+] (P < 0.05) all increased. Change in body mass was related to running speed (r = −0.16, P < 0.05), change in plasma volume was associated with change in plasma [Na+] (r = −0.28, P < 0.0001), and change in body mass was related to both change in plasma [Na+] (r = −0.36) and change in plasma volume (r = 0.31) (P < 0.0001). The athletes consumed 0.65 L (s = 0.27) fluid per hour. Fluid intake was related to both running speed (r = 0.42, P < 0.0001) and change in body mass (r = 0.23, P = 0.0006), but not post-race plasma [Na+] or change in plasma [Na+] (P > 0.05). In conclusion, faster runners lost more body mass, runners lost more body mass when they drank less fluid, and faster runners drank more fluid than slower runners.