Influence of Immune and Nutritional Biomarkers on Illness Risk During Interval Training.

Intensive training periods may negatively influence immune function, but the immunological consequences of specific high-intensity-training (HIT) prescriptions are not well defined. PURPOSE: To explore whether 3 different HIT prescriptions influence multiple health-related biomarkers and whether biomarker responses to HIT were associated with upper-respiratory-illness (URI) risk. METHODS: Twenty-five male cyclists and triathletes were randomized to 3 HIT groups and completed 12 HIT sessions over 4 wk. Peak oxygen consumption (V˙O2peak) was determined using an incremental cycling protocol, while resting serum biomarkers (cortisol, testosterone, 25[OH]D, and ferritin), salivary immunoglobulin-A (s-IgA), and energy availability (EA) were assessed before and after the training intervention. Participants self-reported upper-respiratory symptoms during the intervention, and episodes of URI were identified retrospectively. RESULTS: Fourteen athletes reported URIs, but there were no differences in incidence, duration, or severity between groups. Increased risk of URI was associated with higher s-IgA secretion rates (odds ratio = 0.90, 90% confidence interval 0.83-0.97). Lower preintervention cortisol and higher EA predicted a 4% increase in URI duration. Participants with higher V˙O2peak reported higher total symptom scores (incidence rate ratio = 1.07, 90% confidence interval 1.01-1.13). CONCLUSIONS: Although multiple biomarkers were weakly associated with risk of URI, the direction of associations between s-IgA, cortisol, EA, and URI risk were inverse to previous observations and physiological rationale. There was a cluster of URIs in the first week of the training intervention, but no samples were collected at this time point. Future studies should incorporate more-frequent sample time points, especially around the onset of new training regimens, and include athletes with suspected or known nutritional deficiencies.

Effects of Initial Performance, Gross Efficiency and O 2peak Characteristics on Subsequent Adaptations to Endurance Training in Competitive Cyclists.

The present study investigated the effects of initial levels of cycling performance, peak oxygen uptake (O2peak) and gross efficiency (GE) on the subsequent adaptations of these variables and their relationship following high-intensity training (HIT) designed to increase O2peak in competitive cyclists. Sixty cyclists (O2peak = 61 ± 6 mL kg-1 min-1) were assigned a 12-week training program consisting of twenty-four supervised high-intensity interval training sessions and ad libitum low intensity training. GE was calculated at 125, 175, and 225 W and performance was determined by mean power during a 40-min time-trial (Power40 min). In addition to correlation analyses between initial level and pre- to post-intervention changes of the different variables, we compared these changes between four groups where participants were categorized with either low and/or high initial levels of O2peak and GE. Average volume of high- and low-intensity training during the 12-week intervention was 1.5 ± 0.3 and 8.3 ± 2.7 h·week-1, respectively. Following the 12-week training period, there was a significant increase in absolute and body mass normalized O2peak and Power40 min (p < 0.05) and a significant decrease in GE (p < 0.05) for all athletes pooled. There was no change in body mass following the 12-week training period. We found a moderate negative correlation between initial level of O2peak and the change in O2peak following the training period (r = -0.32; p < 0.05). A small negative correlation was also found between initial Power40 min and its change following training both when expressed in absolute power and power normalized for body mass (r = -0.27 and -0.28; both p < 0.05). A moderate negative correlation was also found between initial levels for GE and its change following training (r = -0.44; p < 0.01). There were no differences between the four groups based on initial levels of O2peak and GE in the response to training on O2peak, GE, or Power40 min (all p > 0.12). In conclusion, the present findings suggest that there are statistically significant effects of initial levels of cycling performance and O2peak and on the subsequent adaptations following a 12-week HIT program, but the small and moderate effects indicate limited influence on training practice.

Within-Day Energy Deficiency and Metabolic Perturbation in Male Endurance Athletes.

Endurance athletes are at increased risk of relative energy deficiency associated with metabolic perturbation and impaired health. We aimed to estimate and compare within-day energy balance in male athletes with suppressed and normal resting metabolic rate (RMR) and explore whether within-day energy deficiency is associated with endocrine markers of energy deficiency. A total of 31 male cyclists, triathletes, and long-distance runners recruited from regional competitive sports clubs were included. The protocol comprised measurements of RMR by ventilated hood and energy intake and energy expenditure to predict RMRratio (measured RMR/predicted RMR), energy availability, 24-hr energy balance and within-day energy balance in 1-hr intervals, assessment of body composition by dual-energy X-ray absorptiometry, and blood plasma analysis. Subjects were categorized as having suppressed (RMRratio < 0.90, n = 20) or normal (RMRratio > 0.90, n = 11) RMR. Despite there being no observed differences in 24-hr energy balance or energy availability between the groups, subjects with suppressed RMR spent more time in an energy deficit exceeding 400 kcal (20.9 [18.8-21.8] hr vs. 10.8 [2.5-16.4], p = .023) and had larger single-hour energy deficits compared with subjects with normal RMR (3,265 ± 1,963 kcal vs. -1,340 ± 2,439, p = .023). Larger single-hour energy deficits were associated with higher cortisol levels (r = -.499, p = .004) and a lower testosterone:cortisol ratio (r = .431, p = .015), but no associations with triiodothyronine or fasting blood glucose were observed. In conclusion, within-day energy deficiency was associated with suppressed RMR and catabolic markers in male endurance athletes.

Effects of High-Intensity Training on Physiological and Hormonal Adaptions in Well-Trained Cyclists.

PURPOSE: Investigate development of specific performance adaptions and hormonal responses every fourth week during a 12-wk high-intensity training (HIT) period in groups with different interval-training prescriptions. METHODS: Sixty-three well-trained cyclists performing a 12-wk intervention consisting of two to three HIT sessions per week in addition to ad libitum low-intensity training. Groups were matched for total training load, but increasing HIT (INC) group (n = 23) performed interval-sessions as 4 × 16 min in weeks 1-4, 4 × 8 min in weeks 5-8, and 4 × 4 min in weeks 9-12. Decreasing HIT (DEC) group (n = 20) performed interval sessions in the opposite order as INC, and mixed HIT (MIX) group (n = 20) performed all interval-sessions in a mixed distribution during 12 wk. Cycling-tests and measures of resting blood hormones were conducted pre, weeks 4, 8, and 12. RESULTS: INC and MIX achieved >70% of total change in workload eliciting 4 mmol·L [la] (Power4mM) and V˙O2peak during weeks 1-4, versus only 34%-38% in DEC. INC induced larger improvement versus DEC during weeks 1-4 in Power4mM (effect size, 0.7) and V˙O2peak (effect size, 0.8). All groups increased similarly in peak power output during weeks 1-4 (64%-89% of total change). All groups' pooled, total and free testosterone and free testosterone/cortisol ratio decreased by 22% ± 15%, 13% ± 23%, and 14% ± 31% (all P < 0.05), and insulin-like growth factor-1 increased by 10% ± 14% (P < 0.05) during weeks 1-4. CONCLUSIONS: Most of progression in Power4mM, V˙O2peak and peak power output was achieved during weeks 1-4 in INC and MIX, and accompanied by changes in resting blood hormones consistent with increased but compensable stress load. In these well-trained subjects, accumulating 2-3 h·wk performing 4 × 16 min work bouts at best effort induces greater adaptions in Power4mM and V˙O2peak than accumulating ~1 h·wk performing best effort intervals as 4 × 4 min.

How Does Interval-Training Prescription Affect Physiological and Perceptual Responses?

The purpose of this study was to compare physiological responses and perceived exertion among well-trained cyclists (n = 63) performing 3 different high-intensity interval-training (HIIT) prescriptions differing in work-bout duration and accumulated duration but all prescribed with maximal session effort. Subjects (male, mean ± SD 38 ± 8 y, VO2peak 62 ± 6 mL · kg-1 · min-1) completed up to 24 HIIT sessions over 12 wk as part of a training-intervention study. Sessions were prescribed as 4 × 16, 4 × 8, or 4 × 4 min with 2-min recovery periods (8 sessions of each prescription, balanced over time). Power output, HR, and RPE were collected during and after each work bout. Session RPE was reported after each session. Blood lactate samples were collected throughout the 12 wk. Physiological and perceptual responses during >1400 training sessions were analyzed. HIIT sessions were performed at 95% ± 5%, 106% ± 5%, and 117% ± 6% of 40-min time-trial power during 4 × 16-, 4 × 8-, and 4 × 4-min sessions, respectively, with peak HR in each work bout averaging 89% ± 2%, 91% ± 2%, and 94% ± 2% HRpeak. Blood lactate concentrations were 4.7 ± 1.6, 9.2 ± 2.4, and 12.7 ± 2.7 mmol/L. Despite the common prescription of maximal session effort, RPE and sRPE increased with decreasing accumulated work duration (AWD), tracking relative HR. Only 8% of 4 × 16-min sessions reached RPE 19-20, vs 61% of 4 × 4-min sessions. The authors conclude that within the HIIT duration range, performing at "maximal session effort" over a reduced AWD is associated with higher perceived exertion both acutely and postexercise. This may have important implications for HIIT prescription choices.

The Effect of Different High-Intensity Periodization Models on Endurance Adaptations.

PURPOSE: This study aimed to compare the effects of three different high-intensity training (HIT) models, balanced for total load but differing in training plan progression, on endurance adaptations. METHODS: Sixty-three cyclists (peak oxygen uptake (V˙O2peak) 61.3 ± 5.8 mL·kg·min) were randomized to three training groups and instructed to follow a 12-wk training program consisting of 24 interval sessions, a high volume of low-intensity training, and laboratory testing. The increasing HIT group (n = 23) performed interval training as 4 × 16 min in weeks 1-4, 4 × 8 min in weeks 5-8, and 4 × 4 min in weeks 9-12. The decreasing HIT group (n = 20) performed interval sessions in the opposite mesocycle order as the increasing HIT group, and the mixed HIT group (n = 20) performed the interval prescriptions in a mixed distribution in all mesocycles. Interval sessions were prescribed as maximal session efforts and executed at mean values 4.7, 9.2, and 12.7 mmol·L blood lactate in 4 × 16-, 4 × 8-, and 4 × 4-min sessions, respectively (P < 0.001). Pre- and postintervention, cyclists were tested for mean power during a 40-min all-out trial, peak power output during incremental testing to exhaustion, V˙O2peak, and power at 4 mmol·L lactate. RESULTS: All groups improved 5%-10% in mean power during a 40-min all-out trial, peak power output, and V˙O2peak postintervention (P < 0.05), but no adaptation differences emerged among the three training groups (P > 0.05). Further, an individual response analysis indicated similar likelihood of large, moderate, or nonresponses, respectively, in response to each training group (P > 0.05). CONCLUSIONS: This study suggests that organizing different interval sessions in a specific periodized mesocycle order or in a mixed distribution during a 12-wk training period has little or no effect on training adaptation when the overall training load is the same.

The road to gold: training and peaking characteristics in the year prior to a gold medal endurance performance.

PURPOSE: To describe training variations across the annual cycle in Olympic and World Champion endurance athletes, and determine whether these athletes used tapering strategies in line with recommendations in the literature. METHODS: Eleven elite XC skiers and biathletes (4 male; 28±1 yr, 85±5 mL x min(-1) x kg(-1) VO2max, 7 female, 25±4 yr, 73±3 mL x min(-1) x kg(-1) VO2max) reported one year of day-to-day training leading up to the most successful competition of their career. Training data were divided into periodization and peaking phases and distributed into training forms, intensity zones and endurance activity forms. RESULTS: Athletes trained ∼800 h/500 sessions x year(-1), including ∼500 h x year(-1) of sport-specific training. Ninety-four percent of all training was executed as aerobic endurance training. Of this, ∼90% was low intensity training (LIT, below the first lactate threshold) and 10% high intensity training (HIT, above the first lactate threshold) by time. Categorically, 23% of training sessions were characterized as HIT with primary portions executed at or above the first lactate turn point. Training volume and specificity distribution conformed to a traditional periodization model, but absolute volume of HIT remained stable across phases. However, HIT training patterns tended to become more polarized in the competition phase. Training volume, frequency and intensity remained unchanged from pre-peaking to peaking period, but there was a 32±15% (P<.01) volume reduction from the preparation period to peaking phase. CONCLUSIONS: The annual training data for these Olympic and World champion XC skiers and biathletes conforms to previously reported training patterns of elite endurance athletes. During the competition phase, training became more sport-specific, with 92% performed as XC skiing. However, they did not follow suggested tapering practice derived from short-term experimental studies. Only three out of 11 athletes took a rest day during the final 5 days prior to their most successful competition.

From heart-rate data to training quantification: a comparison of 3 methods of training-intensity analysis.

PURPOSE: The authors directly compared 3 frequently used methods of heart-rate-based training-intensity-distribution (TID) quantification in a large sample of training sessions performed by elite endurance athletes. METHODS: Twenty-nine elite cross-country skiers (16 male, 13 female; 25 ± 4 y; 70 ± 11 kg; 76 ± 7 mL · min-1 · kg-1 VO2max) conducted 570 training sessions during a ~14-d altitude-training camp. Three analysis methods were used: time in zone (TIZ), session goal (SG), and a hybrid session-goal/time-in-zone (SG/TIZ) approach. The proportion of training in zone 1, zone 2, and zone 3 was quantified using total training time or frequency of sessions, and simple conversion factors across different methods were calculated. RESULTS: Comparing the TIZ and SG/TIZ methods, 96.1% and 95.5%, respectively, of total training time was spent in zone 1 (P < .001), with 2.9%/3.6% and 1.1%/0.8% in zones 2/3 (P < .001). Using SG, this corresponded to 86.6% zone 1 and 11.1%/2.4% zone 2/3 sessions. Estimated conversion factors from TIZ or SG/TIZ to SG and vice versa were 0.9/1.1, respectively, in the low-intensity training range (zone 1) and 3.0/0.33 in the high-intensity training range (zones 2 and 3). CONCLUSIONS: This study provides a direct comparison and practical conversion factors across studies employing different methods of TID quantification associated with the most common heart-rate-based analysis methods.

Do elite endurance athletes report their training accurately?

PURPOSE: The purpose of this study was to validate the accuracy of self-reported (SR) training duration and intensity distribution in elite endurance athletes. METHODS: Twenty-four elite cross-country skiers (25 ± 4 y, 67.9 ± 9.88 kg, 75.9 ± 6.50 mL · min-1 · kg-1) SR all training sessions during an ~14-d altitude-training camp. Heart rate (HR) and some blood lactate measurements were collected during 466 training sessions. SR training was compared with recorded training duration from HR monitors, and SR intensity distribution was compared with expert analysis (EA) of all session data. RESULTS: SR training was nearly perfectly correlated with recorded training duration (r = .99), but SR training was 1.7% lower than recorded training duration (P < .001). SR training duration was also nearly perfectly correlated (r = .95) with recorded training duration >55% HRmax, but SR training was 11.4% higher than recorded training duration >55% HRmax (P < .001) due to SR inclusion of time <55% HRmax. No significant differences were observed in intensity distribution in zones 1-2 between SR and EA comparisons, but small discrepancies were found in zones 3-4 (P < .001). CONCLUSIONS: This study provides evidence that elite endurance athletes report their training data accurately, although some small differences were observed due to lack of a SR "gold standard." Daily SR training is a valid method of quantifying training duration and intensity distribution in elite endurance athletes. However, additional common reporting guidelines would further enhance accuracy.