The effect of XC-running race Lidingöloppet on determinants of performance

Aim: This study aimed to investigate the determinants of running performance in a cross-country running race and examine whether running economy and biomechanics are affected. Moreover, we analyzed whether the magnitude of change in running economy (RE) is related to changes in biomechanics, performance, and fitness measures. Method: Thirteen runners (12 male and 1 female), with an average 10 km personal best time of 36:46 ± 3:17 (min:s), participated in the 30 km cross-country race, Lidingöloppet. Assessments of submaximal and maximal running physiology, biomechanics, and anthropometry were conducted before and immediately after the race. A multiple linear regression model was applied to explain performance variance. Pearson's correlation analyses examined the relationships between performance and pre-test variables, and between changes in running economy and both pre-test fitness measures and changes in biomechanics. Paired Student's t-tests were used to compare pre- and post-race values. Results: Performance was best explained using a model including oxygen uptake at lactate threshold (LT), fat utilization, and allometrically scaled running economy (R 2 = 0.918, adjusted R 2 = 0.887, F = 29.7, p < 0.01). Race performance also correlated with maximal oxygen uptake (VO2max, r = -0.776, p = 0.003), fat mass (r = 0.646, p = 0.032), and velocity at VO2max (vVO2max, r = -0.853, p < 0.01). The oxygen cost of running increased (201.8 ± 14 vs. 208.4 ± 9.3 mL kg-1·km-1; p = 0.041), whereas respiratory exchange ratio (0.91 ± 0.04 vs. 0.85 ± 0.05; p < 0.01) and body mass (69.2 ± 7.5 vs. 67.6 ± 7.7 kg; p < 0.01) decreased post-race. Energetic cost of running (0.997 ± 0.076 vs. 1.015 ± 0.052 kcal kg-1·km-1; p = 0.192) and all biomechanical measurements, including cadence, contact time, overstride, vertical displacement, and vertical force, were unaffected by the race. The magnitude of change in running economy was related only to pre-test running economy (r = -0.749; p = 0.003) but not to performance (r = -0.440; p = 0.132), other pre-test fitness measures, or any changes in biomechanics. Conclusion: The best performance prediction model included oxygen uptake at estimated lactate threshold, fat utilization during submaximal running, and allometrically scaled running economy. Oxygen cost of running increased post-race, likely due to increased fat oxidation, despite decreased body mass. No changes in biomechanics were observed, and changes in running economy could not be explained by changes in biomechanics. Aerobic fitness, anthropometry, and performance were not associated with changes in running economy. Given the small and relatively homogeneous sample, findings should be considered exploratory, although they suggest that practitioners may benefit from targeting fat oxidation, oxygen uptake at the estimated lactate threshold, and running economy in training.