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Harry P. Cintineo, MS, CSCS – PhD Student, Rutgers University

Alan J. Walker, PhD. – PhD., IFNH Center for Health and Human Performance, Rutgers University

Marissa L. Bello

David J. Sanders, MS, CSCS*D – Research Assistant, Rutgers University

Bridget A. McFadden, MBS, CSCS*D – PhD Candidate, Rutgers Center for Health and Human Performance

Shawn M. Arent


Preparing for a triathlon requires planned and deliberate programming to maximize adaptations while minimizing health decrements. Monitoring training, performance, and biomarkers can be useful for determining physiological responses throughout a competitive season. Purpose: To monitor training, performance, and biomarkers in an international high-level, 41-year-old male triathlete over a 40-week period, including three 113.1-km triathlons. Methods: Training was monitored throughout the season by a fitness tracker. Body composition, performance, and biomarkers were measured every 32.5±6.2 d (T1-T8). The final testing session (T9) occurred 45 d after the final race. At each time point, the subject arrived in a fasted, euhydrated state between 0700-0900 h following a rest day. First, body composition was measured via BodPod. Blood samples were then collected for analysis of free and total cortisol (FC; TC) and free and total testosterone (FT; TT). Lastly, velocity at lactate threshold (VLT) and VO2peak were measured using an intermittent treadmill protocol. Results: Weekly training volume (VOL) throughout the season was 12.4±3.3 h, and competitions occurred between T3/T4, T7/T8, and T8/T9. VOL peaked in preparation of all races, with the largest increase occurring prior to the final race (18.1 h/wk) followed by a 3-wk VOL taper (6.5±6.7 h/wk). This coincided with the best performance (4h:10m:51s), which was a 36.78- and 15.43-min improvement over the first and second races, respectively. Following the final competition, VOL was 6.8±3.4 h/wk. Weekly training intensity (INT), indicated by average heart rate, did not vary notably throughout the season (145.7±3.2 beats/min). Fat free mass (FFM) increased slightly from T1-T2 (Δ+1.84 kg) and steadily decreased until T8, constituting a 3.69% decrease from T1 (Δ-4.00 kg). FFM rebounded by T9 but remained 0.93% below T1 (Δ-0.54 kg). VLT and VO2peak did not change over the season (12.9±0.4 km/h; 55.70±1.54 mL/kg/min). At T3, FC was 26% higher than T1 (Δ+0.24 mcg/mL) but remained stable until increasing again from T7-T9, reaching a 41% increase above T1 (Δ+0.38 mcg/mL). TC remained stable throughout the season (23.34±1.21 mcg/dL). FT and TT remained stable from T1-T7 (46.72±4.06 pg/mL; 543.33±49.47 ng/dL) but both began to fall at T8 and reached 39.47% and 49.40% decreases from T1 at T9  (Δ-18.00 pg/mL; Δ-288.00 ng/dL). Conclusions: Overall, a periodized training program aims to improve performance while maintaining health. Although the subject’s training VOL was structured appropriately, INT was not similarly manipulated. Interestingly, VLT, VO2peak, and FFM maintained or decreased, but race times improved throughout the season. The modest increase in FC at T3 corresponds with the first preparation period. Counterintuitively, despite the reduction in VOL and regain of FFM following the final competition, FC increased robustly along with a decrease in FT and TT, which may be attributable to lifestyle changes after this race. Practical Applications: Here, laboratory performance measures do not appear to vary with competition outcomes, likely due to the lack of specificity compared to the demands of triathlons or because of other factors impacting race performance. Additionally, a structured training and diet plan implemented immediately following the final race of the season may allow for a faster and complete recovery of FFM, FC, and FT while setting up athletes for a successful offseason.


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