A Novel Metric “Exercise Cardiac Load” Proposed to Track and Predict the Deterioration of the Autonomic Nervous System in Division I Football Athletes

Abstract

Current metrics like baseline heart rate (HR) and HR recovery fail in predicting overtraining (OT), a syndrome manifesting from a deteriorating autonomic nervous system (ANS). Preventing OT requires tracking the influence of internal physiological loads induced by exercise training programs on the ANS. Therefore, this study evaluated the predictability of a novel, exercise cardiac load metric on the deterioration of the ANS. Twenty male American football players, with an average age of 21.3 years and body mass indices ranging from 23.7 to 39.2 kg/m2 were included in this study. Subjects participated in 40 strength- and power-focused exercise sessions over 8 weeks and wore armband monitors (Warfighter Monitor, Tiger Tech Solutions) equipped with electrocardiography capabilities. Exercise cardiac load was the product of average training HR and duration. Baseline HR, HR variability (HRV), average HR, and peak HR were also measured. HR recovery was measured on the following day. HRV indices assessed included the standard deviation of NN intervals (SDNN) and root mean square of successive RR interval differences (rMSSD) Linear regression models assessed the relationships between each cardiac metric and HR recovery, with statistical significance set at α < 0.05. Subjects were predominantly non-Hispanic black (70%) and aged 21.3 (±1.4) years. Adjusted models showed that exercise cardiac load elicited the strongest negative association with HR recovery for previous day (β = −0.18 ± 0.03; p < 0.0000), one-week (β = −0.20 ± 0.03; p < 0.0000) and two-week (β = −0.26 ± 0.03; p < 0.0000) training periods compared to average HR (βetas: −0.09 to −0.02; p < 0.0000) and peak HR (βetas: −0.13 to −0.23; p < 0.0000). Statistically significant relationships were also found for baseline HR (p < 0.0000), SDNN (p < 0.0000) and rMSSD (p < 0.0000). Exercise cardiac load appears to best predict ANS deterioration across one- to two-week training periods, showing a capability for tracking an athlete’s physiological tolerance and ANS response. Importantly, this information may increase the effectiveness of exercise training programs, enhance performance, and prevent OT.