title: Prediction of half-marathon race time in recreational female and male runners.
abstract: Half-marathon running is of high popularity. Recent studies tried to find predictor variables for half-marathon race time for recreational female and male runners and to present equations to predict race time. The actual equations included running speed during training for both women and men as training variable but midaxillary skinfold for women and body mass index for men as anthropometric variable. An actual study found that percent body fat and running speed during training sessions were the best predictor variables for half-marathon race times in both women and men. The aim of the present study was to improve the existing equations to predict half-marathon race time in a larger sample of male and female half-marathoners by using percent body fat and running speed during training sessions as predictor variables. In a sample of 147 men and 83 women, multiple linear regression analysis including percent body fat and running speed during training units as independent variables and race time as dependent variable were performed and an equation was evolved to predict half-marathon race time. For men, half-marathon race time might be predicted by the equation (r(2) = 0.42, adjusted r(2) = 0.41, SE = 13.3) half-marathon race time (min) = 142.7 + 1.158 × percent body fat (%) - 5.223 × running speed during training (km/h). The predicted race time correlated highly significantly (r = 0.71, p < 0.0001) to the achieved race time. For women, half-marathon race time might be predicted by the equation (r(2) = 0.68, adjusted r(2) = 0.68, SE = 9.8) race time (min) = 168.7 + 1.077 × percent body fat (%) - 7.556 × running speed during training (km/h). The predicted race time correlated highly significantly (r = 0.89, p < 0.0001) to the achieved race time. The coefficients of determination of the models were slightly higher than for the existing equations. Future studies might include physiological variables to increase the coefficients of determination of the models.
authors.affiliation: Institute of General Practice and for Health Services Research, University of Zurich, Zurich, Switzerland ; Gesundheitszentrum St. Gallen, Vadianstrasse 26, 9001 St. Gallen, Switzerland.
authors.forename: Beat
authors.initials: B
authors.lastname: Knechtle
authors.affiliation: Institute of General Practice and for Health Services Research, University of Zurich, Zurich, Switzerland.
authors.forename: Ursula
authors.initials: U
authors.lastname: Barandun
authors.affiliation: Gesundheitszentrum St. Gallen, Vadianstrasse 26, 9001 St. Gallen, Switzerland.
authors.forename: Patrizia
authors.initials: P
authors.lastname: Knechtle
authors.affiliation: Institute of General Practice and for Health Services Research, University of Zurich, Zurich, Switzerland.
authors.forename: Matthias A
authors.initials: MA
authors.lastname: Zingg
authors.affiliation: Institute of General Practice and for Health Services Research, University of Zurich, Zurich, Switzerland.
authors.forename: Thomas
authors.initials: T
authors.lastname: Rosemann
authors.affiliation: Institute of General Practice and for Health Services Research, University of Zurich, Zurich, Switzerland.
authors.forename: Christoph A
authors.initials: CA
authors.lastname: Rüst
keywords: Body fat; Performance; Running; Training