Maximum performance of master cross-country skiers in loppets
Relationship with age
DOI:
https://doi.org/10.51224/SRXIV.277Keywords:
age-performance relationship, age-graded performance, cross-country ski, cross-sectional data, loppet, skiing techniqueAbstract
BACKGROUND. Most participants in long-distance cross-country ski races (loppets) are masters (age ≥ 30 yrs). They represent an effective study population to quantify the age-performance relationship. AIM. 1) to determine the relationship between age, gender, skiing style and performance of master skiers; 2) to test the force development theory that suggests that the decreased performance with age should be larger for the more strenuous free style technique than for the classic style, for both men and women. MEASURES. Cross-sectional data were gathered from nine loppets from the Worldloppet Circuit that comprised 89 events in total between 1995 and 2005. A total of 190,304 master men and 24,917 master women took part to these events. Participant age was classified mainly in 5-year categories, while average speed was calculated from the loppet distance divided by individual
race times. MODELING APPROACH. The boundary line approach was used to select the maximum performance by age class in each event. ANALYSES. A general modified power model was fitted to the relative average maximum speed achieved in each age category for each event. Loppets were considered as random factor and each event within loppets as subjects in a repeated-measure regression analysis. OUTCOMES. Age, gender and skiing style influenced maximum performance. The general model fit was considered good (r2 = 0.70; p < 0.001). Maximum performance of skiers decreased with age, with more moderate declines for men than for women, and also for the classic style compared with the free style. Age correction factors were calculated direct from the general model, giving preliminary age-graded factors making comparable performances at different ages in various loppet events. CONCLUSIONS. The results supported the force development theory. However, the study of longitudinal data is needed to confirm or refine age-graded factors, particularly for elderly skiers (≥ 60 yrs).
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References
Anton MA, Spirduso WW and Tanaka H (2004). Age-related declines in anaerobic muscular performance: weightlifting and powerlifting. Med. Sci. Sports Exerc. 36, 143-147.
Baker AB, Tang YQ and Turner MJ (2003). Percentage decline in masters superathletes track and field performance with aging. Exp. Aging Res. 29, 47-65.
Bilodeau B, Rundell KW, Roy B and Boulay MR (1996). Kinematics of cross-country ski racing. Med. Sci. Sports Exerc. 28, 128-138.
Böttiger LE (1971). Physical working capacity with age. Acta Medica Scandinavica 190, 359-362.
Farahmand B, Hallmarker U, Brobert GP and Ahlbom A (2007). Acute mortality during long-distance ski races (Vasaloppet). Scand. J. Med. Sci. Sports (in press).
Farahmand BY, Ahlbom A, Ekblom O, Ekblom B, Llmarker UH, Aronson D and Brobert GP (2003). Mortality amongst participants in Vasaloppet: a classical longdistance ski race in Sweden. J. Int. Med. 253, 276-283.
Grogan TJ, Wilson BRA and Camm JD (1991). The relationship between age and optimal performance of elite athletes in endurance running events. Res. Quart. Exerc. Sport 62, 333-339.
Hoffman MD (1992). Physiological comparisons of cross-country skiing techniques. Med. Sci. Sports Exerc. 24, 1023-1032.
Korhonen MT, Mero A and Suominen H (2003). Age-related differences in 100-m sprint performance in male and female master runners. Med. Sci. Sports Exerc. 35, 1419-1428.
SAS Institute Inc. (2003) SAS OnlineDoc 9.1. , Cary, NC. Smith GA (1989). Kinetic analysis of the V1 skate in cross country skiing. In
Proceedings of the First IOC World Congress on Sport Sciences, Colorado Springs, USA, 1989. pp 281-282.
Tanaka H and Seals DR (2003). Dynamic exercise performance in masters athletes: insight into the effects of primary human aging on physiological functional capacity. J. Appl. Physiol. 95, 2152-2162.
Webb RA (1972). Use of the boundary line in the analysis of biological data. J. Hort. Sci. 47, 309-319.
Weir PL, Kerr T, Hodges NJ, McKay SM and Starkes JL (2002). Master swimmers: how are they different from younger elite swimmers? An examination of practice and performance patterns. J. Aging Phys. Activ. 10, 41-63.
Wiebe CG, Gledhill N, Jamnik VK and Ferguson S (1999). Exercise cardiac function in young through elderly endurance trained women. Med. Sci. Sports Exerc. 31, 684-691.
Young BW and Starkes JL (2005). Career-span analyses of track performance: longitudinal data present a more optimistic view of age-related performance decline. Exp. Aging Res. 31, 69-90.
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