Training and Competition Readiness in Triathlon

Triathlon is characterized by the multidisciplinary nature of the sport where swimming, cycling, and running are completed sequentially in different events, such as the sprint, Olympic, long-distance, and Ironman formats. The large number of training sessions and overall volume undertaken by triathletes to improve fitness and performance can also increase the risk of injury, illness, or excessive fatigue. Short- and medium-term individualized training plans, periodization strategies, and work/rest balance are necessary to minimize interruptions to training due to injury, illness, or maladaptation. Even in the absence of health and wellbeing concerns, it is unclear whether cellular signals triggered by multiple training stimuli that drive training adaptations each day interfere with each other. Distribution of training intensity within and between different sessions is an important aspect of training. Both internal (perceived stress) and external loads (objective metrics) should be considered when monitoring training load. Incorporating strength training to complement the large body of endurance work in triathlon can help avoid overuse injuries. We explore emerging trends and strategies from the latest literature and evidence-based knowledge for improving training readiness and performance during competition in triathlon

Power profiling and the power-duration relationship in cycling: a narrative review

[EN] Emerging trends in technological innovations, data analysis and practical applications have facilitated the measurement of cycling power output in the field, leading to improvements in training prescription, performance testing and race analysis. This review aimed to critically reflect on power profiling strategies in association with the power-duration relationship in cycling, to provide an updated view for applied researchers and practitioners. The authors elaborate on measuring power output followed by an outline of the methodological approaches to power profiling. Moreover, the deriving a power-duration relationship section presents existing concepts of power-duration models alongside exercise intensity domains. Combining laboratory and field testing discusses how traditional laboratory and field testing can be combined to inform and individualize the power profiling approach. Deriving the parameters of power-duration modelling suggests how these measures can be obtained from laboratory and field testing, including criteria for ensuring a high ecological validity (e.g. rider specialization, race demands). It is recommended that field testing should always be conducted in accordance with pre-established guidelines from the existing literature (e.g. set number of prediction trials, inter-trial recovery, road gradient and data analysis). It is also recommended to avoid single effort prediction trials, such as functional threshold power. Power-duration parameter estimates can be derived from the 2 parameter linear or non-linear critical power model: P(t) = W '/t + CP (W '-work capacity above CP; t-time). Structured field testing should be included to obtain an accurate fingerprint of a cyclist's power profile.Open access funding provided by University of Innsbruck and Medical University of Innsbruck. No funding was received for the preparation of this manuscript

Training cessation and subsequent retraining of a world-class female Olympic sailor after Tokyo 2020: A case study

Olympic sailing is a complex sport where sailors are required to predict and interpret weather conditions while facing high physical and physiological demands. While it is essential for sailors to develop physical and physiological capabilities toward major competition, monitoring training status following the competition is equally important to minimize the magnitude of detraining and facilitate retraining. Despite its long history in the modern Olympics, reports on world-class sailors' training status and performance characteristics across different periodization phases are currently lacking. This case study aimed to determine the influence of training cessation and subsequent retraining on performance parameters in a world-class female sailor. A 31-year old female sailor, seventh in the Women's Sailing 470 medal race in Tokyo 2020, completely stopped training for 4 weeks following the Olympics, and resumed low-intensity training for 3 weeks. Over these 7 weeks, 12.7 and 5.3% reductions were observed in 6 s peak cycling power output and jump height, respectively, with a 4.7% decrease in maximal aerobic power output. Seven weeks of training cessation-retraining period induced clear reductions in explosive power production capacities but less prominent decreases in aerobic capacity. The current findings are likely attributed to the sailor's training characteristics during the retraining period.This study was part of Functional Development Project for Resilient Athlete Support commissioned by Japan Sports Agency

Physical Activity, Sedentary Behavior, and Sleep Quality in Adults with Primary Hypertension and Obesity before and after an Aerobic Exercise Program: EXERDIET-HTA Study

Background: The purposes of the study were to: analyze, by objective (accelerometry) and subjective (International Physical Activity Questionnaire, IPAQ) methodologies, the physical activity (PA) and sedentary behavior (SB) in healthy adults (HEALTHY, n = 30) and individuals with primary hypertension (HTN) and overweight/obesity (n = 218); assess the effects of an aerobic exercise intervention on physical activity (PA), sedentary behavior (SB), and sleep quality in the HTN group; and evaluate the relationship between objectively measured and subjectively reported PA and SB. Methods: The measurements were performed before a 16-week exercise intervention period in both HEALTHY and HTN groups and after the intervention period only in the HTN group, randomized to attention control or exercise training (ExT) subgroups. Results: The HEALTHY group showed more moderate-to-vigorous PA (p < 0.05) and better sleep quality (p < 0.05) than the HTN group, but no difference in SB. After the intervention, HTN participants’ PA and SB, objectively measured by accelerometry, were unchanged, but increased PA and decreased SB (p < 0.05) were observed through IPAQ in ExT. The intervention was effective in improving sleep quality in HTN participants. Conclusions: The differences in moderate-to-vigorous PA and SB may be useful in defining the health profile of a population. The supervised aerobic exercise program was effective in increasing PA, reducing SB, and improving sleep quality in overweight/obese adults with HTN. Accelerometer-measured and self-reported data were not comparable, but complementary.A.M.A.-B., P.C. and I.G.-A. were supported by the Basque Government with predoctoral grants. This study was supported by the University of the Basque Country (EHU14/08, PPGA18/15)

Actigraphy-based sleep analysis in sedentary and overweight/obese adults with primary hypertension: data from the EXERDIET-HTA study

Purpose: The aim of this study was to analyze actigraphy-based sleep quantity and quality in sedentary and overweight/obese adults with primary hypertension (HTN) divided by sex and cardiorespiratory fitness (CRF) and to assess the association of sleep parameters with body composition, blood pressure (BP), and CRF. Methods: This is a cross-sectional design utilizing data from the EXERDIET-HTA study conducted in 154 non-physically, obese adults with HTN (53.3 ± 7.8 years). Sleep parameters (total bedtime; total sleep time, TST; and sleep efficiency = (TST/total bedtime) × 100)) were calculated from raw accelerometer data (ActiGraph GT3X+). Peak oxygen uptake (V̇O2peak) determined the CRF. Blood pressure was assessed with the 24-h ambulatory BP monitoring. The distributions of V̇O2peak were divided into tertiles (low, medium, and high CRF) in each sex. Series of linear regression analyses were conducted between sleep, fitness, and health-related variables. Results: Short sleep duration (6.2 h) both on weekdays and weekends, poor sleep quality (< 85% of efficiency), and no significant differences in sleep variables between women and men, nor among CRF groups, were observed. The short sleeping pattern was negatively associated (P < 0.05) with mean and night systolic BP (mmHg, β = - 0.2), and sleep efficiency with waist circumference (cm, β = - 0.08, P = 0.05). Conclusions: Actigraphy-based sleep analysis reinforces that sleep disorders, such as short sleep duration and poor sleep quality, are associated with high BP and abdominal obesity in sedentary adults with overweight/obesity and HTN. Sleep pattern did not appear to be related with CRF level in this population.The University of the Basque Country (EHU14/08, PPGA18/15) supported this study and The Basque Government to AMAB, PC and IGAwith predoctoral grants