Association Between Testosterone Reactivity and Maximal Physical Performance: Pilot Study

Tactical athletes (TA) are required to maintain a state of physical readiness to meet occupational performance demands. Physical performance prediction has previously been related to acute hormonal levels, in particular, testosterone (T)and cortisol (C), whose salivary levels are correlated with serums. However, it is unclear if baseline T and C levels or reactivity to stress (∆T and ∆C) are most associated with physical performance. PURPOSE: To determine the association of T and C reactivity to physical stress with physical performance measures. METHODS: We measured salivary T and C concentrations (passive drool) from 7 participants (5 M/2F, 32.29 yrs ± 9.52 SD) pre and post an hour-long fatiguing protocol simulating military training. Participants also completed physical performance measures pre- and post-fatigue (Queens step test, 1-minute cycling average power, and max hand release pushups and plank hold). Spearman correlations were computed between baseline T, C, ∆T, ∆C and pre-fatigue performance measures. Linear regression models were also computed for baseline T and ∆T as predictors of pre-fatigue max pushups and plank hold time. RESULTS: Significant correlations (p < 0.01) were found for ∆T with push-ups (r = 0.883) and plank hold (r = 0.929) while none were found for Baseline T. ∆C was correlated with max plank hold time (r = 0.786, p < 0.05). No correlations were found between any hormone measure and Queens test or 1-minutecycling power. Linear regression model (Figure 1) indicated that ∆T, but not baseline T, predict plank hold time (adjusted R2 = 0.915) and push-ups(adjusted R2 = 0.48). When C was added, the model improved (adjustedR2 = 0.713). CONCLUSION: Baseline T did not significantly predict upper body strength or core endurance in our sample while ∆T did. This suggests that hormonal response instead of baseline levels may be more informative in assessing and optimizing physical performance. Future studies should investigate individual variations.ChatGPT used for text refinement (less than 10%). It was not use in the analysis in any way.