Effect of Carbohydrate Content in a Pre-event Meal on Endurance Performance-Determining Factors: A Randomized Controlled Crossover-Trial

Abstract

The current study aimed to investigate the effect of the relative CHO content in a pre-event meal on time to exhaustion (TTE), peak oxygen uptake (V∙O2peak), the 2nd lactate threshold (LT2), onset of blood lactate accumulation (OBLA), and work economy (WE) and to compare responses between well-trained and recreationally trained individuals. Eleven well-trained and 10 recreationally trained men performed three trials in a randomized cross-over design, in which they performed exercise tests (1) after a high-CHO pre-event meal (3 g · kg−1), (2) a low-CHO pre-event meal (0.5 g · kg−1), or (3) in a fasted-state. The test protocol consisted of five submaximal 5-min constant-velocity bouts of increasing intensity and a graded exercise test (GXT) to measure TTE. A repeated measure ANOVA with a between-subjects factor (well-trained vs. recreational) was performed. A main effect of pre-event meal was found (p = 0.001), with TTE being 8.0% longer following the high-CHO meal compared to the fasted state (p = 0.009) and 7.2% longer compared to the low-CHO meal (p = 0.010). No significant effect of pre-event meal on V∙O2peak, LT2, OBLA, or WE (p ≥ 0.087) was found and no significant interaction effect between training status and pre-event CHO intake was found for TTE or any of the performance-determining variables (p ≥ 0.257). In conclusion, high-CHO content in the pre-event meal led to a longer TTE compared to a meal with a low-CHO content or exercising in a fasted state, both in well-trained and recreationally trained participants. However, the underlying physiological reason for the increased TTE is unclear, as no effect of pre-event meal on the main physiological performance-determining variables was found. Thus, pre-event CHO intake should be standardized when the goal is to assess endurance performance but seems to be of less importance when assessing the main performance-determining variables.