| Title |
Prediction of sprint triathlon performance from laboratory tests
|
|---|---|
| Published in |
European Journal of Applied Physiology, September 2003
|
| DOI | 10.1007/s00421-003-0911-6 |
| Pubmed ID | |
| Authors |
R. Van Schuylenbergh, B. Vanden Eynde, P. Hespel |
| Abstract |
This study investigated whether sprint triathlon performance can be adequately predicted from laboratory tests. Ten triathletes [mean (SEM), age 21.8 (0.3) years, height 179 (2) cm, body mass 67.5 (2.5) kg] performed two graded maximal exercise test in random order, either on their own bicycle which was mounted on an ergometer or on a treadmill, to determine their peak oxygen consumption ( VO(2)peak). Furthermore, they participated in two to three 30-min constant-load tests in both swimming, cycling and running to establish their maximal lactate steady state (MLSS) in each exercise mode. Swim tests were performed in a 25-m swimming pool (water temperature 27 degrees C). During each test heart rate (HR), power output (PO) or running/swimming speed and blood lactate concentration (BLC) were recorded at regular intervals. Oxygen uptake ( VO(2)) was continuously measured during the graded tests. Two weeks after the laboratory tests all subjects competed in a triathlon race (500 m swim, 20-km bike, 5-km run) [1 h 4 min 45 s (1 min 38 s)]. Peak HR was 7 beats.min(-1) lower in the graded cycle test than in the treadmill test ( p<0.05) at similar peak BLC (approximately 10 mmol.l(-1)) and VO(2)peak (approximately 5 L.min(-1)). High correlations were found between VO(2)peak during cycling ( r=-0.71, p<0.05) or running ( r=-0.69, p<0.05) and triathlon performance. Stepwise multiple regression analysis showed that running speed and swimming speed at MLSS, together with BLC in running at MLSS, yielded the best prediction of performance [1 h 5 min 18 s (1 min 49 s)]. Thus, our data indicate that exercise tests aimed to determine MLSS in running and swimming allow for a precise estimation of sprint triathlon performance. |
X Demographics
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Netherlands | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 182 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Brazil | 2 | 1% |
| United Kingdom | 2 | 1% |
| Chile | 1 | <1% |
| Italy | 1 | <1% |
| South Africa | 1 | <1% |
| Germany | 1 | <1% |
| Spain | 1 | <1% |
| United States | 1 | <1% |
| Unknown | 172 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 35 | 19% |
| Student > Bachelor | 29 | 16% |
| Student > Ph. D. Student | 24 | 13% |
| Other | 13 | 7% |
| Researcher | 13 | 7% |
| Other | 43 | 24% |
| Unknown | 25 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Sports and Recreations | 93 | 51% |
| Medicine and Dentistry | 22 | 12% |
| Nursing and Health Professions | 10 | 5% |
| Agricultural and Biological Sciences | 10 | 5% |
| Biochemistry, Genetics and Molecular Biology | 4 | 2% |
| Other | 13 | 7% |
| Unknown | 30 | 16% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 26 January 2016.
All research outputs
#20,653,708
of 25,368,786 outputs
Outputs from European Journal of Applied Physiology
#3,712
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#51,251
of 54,002 outputs
Outputs of similar age from European Journal of Applied Physiology
#20
of 24 outputs
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