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1.  Changes in Skinfold Thicknesses and Body Fat in Ultra-endurance Cyclists 
Purpose
The present study investigated the changes in single skinfold thicknesses and body fat during an ultra-endurance cycling race.
Methods
One hundred and nineteen ultra-endurance cyclists in the ‘Swiss Cycling Marathon’ covering a distance of 600 km were included. Changes in skinfold thickness, fat mass, skeletal muscle mass and total body water were estimated using anthropometric methods.
Results
The subjects were riding at a mean speed of 23.5±4.0 km/h and finished the race within 1,580±296 min. During the race, body mass decreased by 1.5±1.2 kg (P<0.001), and fat mass decreased by 1.5±1.1 kg (P<0.001). Skeletal muscle mass and total body water remained unchanged (P>0.05). The decrease in body mass correlated to the decrease in fat mass (r = 0.20, P=0.03). The skinfold thicknesses at pectoral (-14.7%), abdominal (-14.9%), and thigh (-10.2%) site showed the largest decrease. The decrease in abdominal skinfold was significantly and negatively related to cycling speed during the race (r = -0.31, P<0.001).
Conclusion
Cycling 600 km at ∼23 km/h led to a decrease in fat mass and in all skinfold thicknesses. The largest decrease in skinfold thickness was recorded for pectoral, abdominal, and thigh site. The decrease in abdominal skinfold thickness was negatively related to cycling speed. The body seems to reduce adipose subcutaneous fat during an ultra-endurance performance at the site of the thickest skinfold.
PMCID: PMC3685155  PMID: 23785571
Endurance; Fat Mass; Muscle Mass; Anthropometry; Body Fat; Training
2.  Does Muscle Mass Affect Running Times in Male Long-distance Master Runners? 
Asian Journal of Sports Medicine  2012;3(4):247-256.
Purpose
The aim of the present study was to investigate associations between skeletal muscle mass, body fat and training characteristics with running times in master athletes (age > 35 years) in half-marathon, marathon and ultra-marathon.
Methods
We compared skeletal muscle mass, body fat and training characteristics in master half-marathoners (n=103), master marathoners (n=91) and master ultra-marathoners (n=155) and investigated associations between body composition and training characteristics with race times using bi- and multi-variate analyses.
Results
After multi-variate analysis, body fat was related to half-marathon (β=0.9, P=0.0003), marathon (β=2.2, P<0.0001), and ultra-marathon (β=10.5, P<0.0001) race times. In master half-marathoners (β=-4.3, P<0.0001) and master marathoners (β=-11.9, P<0.0001), speed during training was related to race times. In master ultra-marathoners, however, weekly running kilometers (β=-1.6, P<0.0001) were related to running times.
Conclusions
To summarize, body fat and training characteristics, not skeletal muscle mass, were associated with running times in master half-marathoners, master marathoners, and master ultra-marathoners. Master half-marathoners and master marathoners rather rely on a high running speed during training whereas master ultra-marathoners rely on a high running volume during training. The common opinion that skeletal muscle mass affects running performance in master runners needs to be questioned.
PMCID: PMC3525821  PMID: 23342223
Body Fat; Skinfold Thickness; Anthropometry; Running; Sports
3.  Participation and Performance Trends in Triple Iron Ultra-triathlon – a Cross-sectional and Longitudinal Data Analysis 
Asian Journal of Sports Medicine  2012;3(3):145-152.
Purpose
The aims of the present study were to investigate (i) the changes in participation and performance and (ii) the gender difference in Triple Iron ultra-triathlon (11.4 km swimming, 540 km cycling and 126.6 km running) across years from 1988 to 2011.
Methods
For the cross-sectional data analysis, the association between with overall race times and split times was investigated using simple linear regression analyses and analysis of variance. For the longitudinal data analysis, the changes in race times for the five men and women with the highest number of participations were analysed using simple linear regression analyses.
Results
During the studied period, the number of finishers were 824 (71.4%) for men and 80 (78.4%) for women. Participation increased for men (r 2=0.27, P<0.01) while it remained stable for women (8%). Total race times were 2,146 ± 127.3 min for men and 2,615 ± 327.2 min for women (P<0.001). Total race time decreased for men (r 2=0.17; P=0.043), while it increased for women (r 2=0.49; P=0.001) across years. The gender difference in overall race time for winners increased from 10% in 1992 to 42% in 2011 (r 2=0.63; P<0.001). The longitudinal analysis of the five women and five men with the highest number of participations showed that performance decreased in one female (r 2=0.45; P=0.01). The four other women as well as all five men showed no change in overall race times across years.
Conclusions
Participation increased and performance improved for male Triple Iron ultra-triathletes while participation remained unchanged and performance decreased for females between 1988 and 2011. The reasons for the increase of the gap between female and male Triple Iron ultra-triathletes need further investigations.
PMCID: PMC3445641  PMID: 23012633
Swimming; Bicycling; Running; Ultra-endurance; Athletic Performance
4.  Predictor Variables for Marathon Race Time in Recreational Female Runners 
Purpose
We intended to determine predictor variables of anthropometry and training for marathon race time in recreational female runners in order to predict marathon race time for future novice female runners.
Methods
Anthropometric characteristics such as body mass, body height, body mass index, circumferences of limbs, thicknesses of skin-folds and body fat as well as training variables such as volume and speed in running training were related to marathon race time using bi- and multi-variate analysis in 29 female runners.
Results
The marathoners completed the marathon distance within 251 (26) min, running at a speed of 10.2 (1.1) km/h. Body mass (r=0.37), body mass index (r=0.46), the circumferences of thigh (r=0.51) and calf (r=0.41), the skin-fold thicknesses of front thigh (r=0.38) and of medial calf (r=0.40), the sum of eight skin-folds (r=0.44) and body fat percentage (r=0.41) were related to marathon race time. For the variables of training, maximal distance ran per week (r=− 0.38), number of running training sessions per week (r=− 0.46) and the speed of the training sessions (r= − 0.60) were related to marathon race time. In the multi-variate analysis, the circumference of calf (P=0.02) and the speed of the training sessions (P=0.0014) were related to marathon race time. Marathon race time might be partially (r 2=0.50) predicted by the following equation: Race time (min)=184.4 + 5.0 x (circumference calf, cm) –11.9 x (speed in running during training, km/h) for recreational female marathoners.
Conclusions
Variables of both anthropometry and training were related to marathon race time in recreational female marathoners and cannot be reduced to one single predictor variable. For practical applications, a low circumference of calf and a high running speed in training are associated with a fast marathon race time in recreational female runners.
PMCID: PMC3426727  PMID: 22942994
Body Fat; Skin-fold; Training; Limb Circumference; Gender; Marathon
5.  The Relationship between Anthropometry and Split Performance in Recreational Male Ironman Triathletes 
Purpose
The aim of this study was to investigate the relation between anthropometric variables and total race time including split times in 184 recreational male Ironman triathletes.
Methods
Body mass, body height, body mass index, lengths and circumferences of imbs, thicknesses of skin-folds, sum of skin-fold thicknesses, and percent body fat were related to total race time including split times using correlation analysis and effect size.
Results
A large effect size (r>0.37) was found for the association between body mass index and time in the run split and between both the sum of skin-folds and percent body fat with total race time. A medium effect size (r=0.24–0.36) was observed in the association between body mass and both the split time in running and total race time, between body mass index and total race time, between both the circumferences of upper arm and thigh with split time in the run and between both the sum of skin-folds and percent body fat with split times in swimming, cycling and running.
Conclusions
The results of this study showed that lower body mass, lower body mass index and lower body fat were associated with both a faster Ironman race and a faster run split; lower circumferences of upper arm and thigh were also related with a faster run split.
PMCID: PMC3289191  PMID: 22375214
Body Fat; Skin-Fold Thickness; Swimming; Running; Cycling
6.  Is Body Fat a Predictor of Race Time in Female Long-Distance Inline Skaters? 
Asian Journal of Sports Medicine  2010;1(3):131-136.
Purpose
The aim of this study was to evaluate predictor variables of race time in female ultra-endurance inliners in the longest inline race in Europe.
Methods
We investigated the association between anthropometric and training characteristics and race time for 16 female ultra-endurance inline skaters, at the longest inline marathon in Europe, the ‘Inline One-eleven’ over 111 km in Switzerland, using bi- and multivariate analysis.
Results
The mean (SD) race time was 289.7 (54.6) min. The bivariate analysis showed that body height (r=0.61), length of leg (r=0.61), number of weekly inline skating training sessions (r=-0.51) and duration of each training unit (r=0.61) were significantly correlated with race time. Stepwise multiple regressions revealed that body height, duration of each training unit, and age were the best variables to predict race time.
Conclusion
Race time in ultra-endurance inline races such as the ‘Inline One-eleven’ over 111 km might be predicted by the following equation (r2=0.65): Race time (min)=-691.62+521.71 (body height, m)+0.58 (duration of each training unit, min)+1.78 (age, yrs) for female ultra-endurance inline skaters.
PMCID: PMC3289175  PMID: 22375200
Skinfold thickness; Physical Endurance; Body Fat; Skating; Training volume

Results 1-6 (6)