(65) THE INFLUENCE OF BREAKS AND TRANSITION STRATEGY ON HEART RATE VARIABILITY AND LACTATE IN HIGH-INTENSITY FUNCTIONAL TRAINING WORKOUTS

Purpose: Break and transition strategy is key to managing fatigue and maintaining a faster pace during high-intensity functional training (HIFT) workouts. Fatigue may be inferred by lactate responses, whereas heart rate variability (HRV) may be indicative of recovery and readiness to perform. Although lactate and HRV responses to HIFT have been reported, their relationships to pace, breaking, and transition strategy have not. This study examined the time course for relationships between break and transition strategy on post-exercise HRV and lactate responses to HIFT. Methods: Nineteen experienced (≥ 6 months) adults completed five rounds of power cleans (PC), toes-to-bar (TTB), and wall balls (WB) prescribed at standard loads but for either low (LV; 5-10-15 repetitions) or high repetition volume (HV; 10-15-20 repetitions) randomized across two visits. Prior to exercise (PRE), participants were fitted with a heart rate sensor and sat quietly for 10 minutes to find the root mean of square of successive differences (RMSSD) and standard deviation of normal-to-normal (SDNN) intervals over the last five minutes. A blood sample was then collected to quantify lactate concentrations. Participants sat quietly for 20 minutes post-exercise and blood samples were collected immediately (IP), and after 5 (5P) and 20 minutes (20P). Lactate responses were represented by the area-under-the-curve for PRE-IP, -5P, and -20P, whereas HRV was assessed by the slope from PRE to IP (0-5 minutes), 5P (5-10 minutes), and 20P (15-20 minutes). Workout video recordings were analyzed to quantify repetition completion rate, breaks, and transition times. Results: Spearman’s rho correlations revealed relationships (p < 0.05) between lactate (IP) and PC completion rate (ρ = -0.50) and TTB and round breaks (ρ = 0.51 to 0.62) of HV, and to WB completion rate (ρ = -0.48) and WB, TTB, and round breaks (ρ = 0.48 to 0.55) of LV. Aside from LV lactate (5P) and average TTB break time (ρ = 0.46, p = 0.045), no other relationships to lactate were seen. RMSSD (IP) was related (p < 0.05) to average TTB and round breaks (ρ = 0.51 to 0.52) of HV, and to TTB and round transitions (ρ = 0.51 to 0.74) of LV. RMSSD (5P) was related (p < 0.05) to the average round breaks (ρ = 0.49 to 0.50) for both workouts, transitions to PC (ρ = 0.47) of HV, and TTB and round transitions to TTB (ρ = 0.56 to 0.70) of LV. RMSSD (20P) was related (p < 0.05) to PC and round transitions (ρ=0.48 to 0.58) for both workouts and average round break and TTB transitions (ρ = 0.52 to 0.63) of LV. SDNN was related (p < 0.05) to TTB transitions (all time points; ρ = 0.60 to 0.65) and round transitions at 20P (ρ = 0.47) for LV. SDNN (20P) was related (p < 0.05) to PC transitions (ρ=0.48 to 0.50) of both workouts. Conclusions: Regardless of volume, a slower completion rate and more breaks led to higher lactate concentrations primarily at IP. Longer breaks and transitions led to greater RMSSD across all time points. Transitions and SDNN were positively linked, with most relationships being seen at 20P. Practical Applications: Monitoring lactate immediately post-exercise may provide insight into the success of the athlete’s pacing strategy but may be less valuable afterwards. Conversely, using a longer period (20 minutes) to track HRV metrics appears to be more useful in determining the influence of the athlete’s transition strategy on their post-exercise recovery. Acknowledgements: N/A