Gross efficiency and cycling performance: a review.

Efficiency, the ratio of work generated to the total metabolic energy cost, has been suggested to be a key determinant of endurance cycling performance. The purpose of this brief review is to evaluate the influence of gross efficiency on cycling power output and to consider whether or not gross efficiency can be modified. In a re-analysis of data from five separate studies, variation in gross efficiency explained ~30% of the variation in power output during cycling time-trials. Whilst other variables, notably VO2max and lactate threshold, have been shown to explain more of the variance in cycling power output, these results confirm the important influence of gross efficiency. Case study, cross-sectional, longitudinal, and intervention research designs have all been used to demonstrate that exercise training can enhance gross efficiency. Whilst improvements have been seen with a wide range of training types (endurance, strength, altitude), it would appear that high intensity training is the most potent stimulus for changes in gross efficiency. In addition to physiological adaptations, gross efficiency might also be improved through biomechanical adaptations. However, ‘intuitive’ technique and equipment adjustments may not always be effective. For example, whilst ‘pedalling in circles’ allows pedalling to become mechanically more effective, this technique does not result in short term improvements in gross efficiency

Gross efficiency and cycling performance: a review

Abstract Efficiency, the ratio of work generated to the total metabolic energy cost, has been suggested to be a key determinant of endurance cycling performance. The purpose of this brief review is to evaluate the influence of gross efficiency on cycling power output and to consider whether or not gross efficiency can be modified. In a re-analysis of data from five separate studies, variation in gross efficiency explained ~30% of the variation in power output during cycling time-trials. Whilst other variables, notably VO2max and lactate threshold, have been shown to explain more of the variance in cycling power output, these results confirm the important influence of gross efficiency. Case study, cross-sectional, longitudinal, and intervention research designs have all been used to demonstrate that exercise training can enhance gross efficiency. Whilst improvements have been seen with a wide range of training types (endurance, strength, altitude), it would appear that high intensity training is the most potent stimulus for changes in gross efficiency. In addition to physiological adaptations, gross efficiency might also be improved through biomechanical adaptations. However, 'intuitive' technique and equipment adjustments may not always be effective. For example, whilst 'pedalling in circles' allows pedalling to become mechanically more effective, this technique does not result in short term improvements in gross efficiency

Knowledge is Power: Issues of Measuring Training and Performance in Cycling.

Mobile power meters provide a valid means of measuring cyclists’ power output in the field. These field measurements can be performed with very good accuracy and reliability making the power meter a useful tool for monitoring and evaluating training and race demands. This study examines power meter data from a Grand Tour cyclist’s training and racing and explores the inherent complications created by its stochastic nature. Simple summary methods cannot reflect a session’s variable distribution of power output or indicate its likely metabolic stress. Binning power output data, into training zones for example, provides information on the detail but not the length of efforts within a session. An alternative approach is to track changes in cyclists’ modelled training and racing performances. Both Critical Power and Record Power Profiles have been used for monitoring training-induced changes in this manner. Ultimately, new methods for quantifying the effects of training loads and modelling their implications for future performance are required. Although first proposed 40 years ago, our ability to model the effects of training on performance remain limited and merits further research

Abstracts from the NIHR INVOLVE Conference 2017

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Psychosocial impact of undergoing prostate cancer screening for men with BRCA1 or BRCA2 mutations.

OBJECTIVES: To report the baseline results of a longitudinal psychosocial study that forms part of the IMPACT study, a multi-national investigation of targeted prostate cancer (PCa) screening among men with a known pathogenic germline mutation in the BRCA1 or BRCA2 genes. PARTICPANTS AND METHODS: Men enrolled in the IMPACT study were invited to complete a questionnaire at collaborating sites prior to each annual screening visit. The questionnaire included sociodemographic characteristics and the following measures: the Hospital Anxiety and Depression Scale (HADS), Impact of Event Scale (IES), 36-item short-form health survey (SF-36), Memorial Anxiety Scale for Prostate Cancer, Cancer Worry Scale-Revised, risk perception and knowledge. The results of the baseline questionnaire are presented. RESULTS: A total of 432 men completed questionnaires: 98 and 160 had mutations in BRCA1 and BRCA2 genes, respectively, and 174 were controls (familial mutation negative). Participants' perception of PCa risk was influenced by genetic status. Knowledge levels were high and unrelated to genetic status. Mean scores for the HADS and SF-36 were within reported general population norms and mean IES scores were within normal range. IES mean intrusion and avoidance scores were significantly higher in BRCA1/BRCA2 carriers than in controls and were higher in men with increased PCa risk perception. At the multivariate level, risk perception contributed more significantly to variance in IES scores than genetic status. CONCLUSION: This is the first study to report the psychosocial profile of men with BRCA1/BRCA2 mutations undergoing PCa screening. No clinically concerning levels of general or cancer-specific distress or poor quality of life were detected in the cohort as a whole. A small subset of participants reported higher levels of distress, suggesting the need for healthcare professionals offering PCa screening to identify these risk factors and offer additional information and support to men seeking PCa screening

A higher effort-based paradigm in physical activity and exercise for public health: making the case for a greater emphasis on resistance training

It is well known that physical activity and exercise is associated with a lower risk of a range of morbidities and all-cause mortality. Further, it appears that risk reductions are greater when physical activity and/or exercise is performed at a higher intensity of effort. Why this may be the case is perhaps explained by the accumulating evidence linking physical fitness and performance outcomes (e.g. cardiorespiratory fitness, strength, and muscle mass) also to morbidity and mortality risk. Current guidelines about the performance of moderate/vigorous physical activity using aerobic exercise modes focuses upon the accumulation of a minimum volume of physical activity and/or exercise, and have thus far produced disappointing outcomes. As such there has been increased interest in the use of higher effort physical activity and exercise as being potentially more efficacious. Though there is currently debate as to the effectiveness of public health prescription based around higher effort physical activity and exercise, most discussion around this has focused upon modes considered to be traditionally ‘aerobic’ (e.g. running, cycling, rowing, swimming etc.). A mode customarily performed to a relatively high intensity of effort that we believe has been overlooked is resistance training. Current guidelines do include recommendations to engage in ‘muscle strengthening activities’ though there has been very little emphasis upon these modes in either research or public health effort. As such the purpose of this debate article is to discuss the emerging higher effort paradigm in physical activity and exercise for public health and to make a case for why there should be a greater emphasis placed upon resistance training as a mode in this paradigm shift

A Novel Field Test to Determine Critical Speed

The aim of this study was to assess the reliability of a novel field test of critical running speed (CS). Ten trained male distance runners completed a familiarisation trial plus three separate experimental trials on a standard 400 m athletics track. Each trial consisted of three distances (1200, 2400 and 3600 metres) that were selected to produce finishing times in the region of 3, 7 and 12 minutes respectively. Participants were instructed to cover the set distance in the fastest time possible. Participants rested for 30 minutes between efforts. Data were modelled using the linear distance-time model, described by the equation: d = (CS x t) + ARC, where: d = distance run (m), t = running time (s), and ARC = anaerobic running capacity (m). Results demonstrated a coefficient of variation (CV) of 2.0% (95% confidence limit (95% CL): 1.4–3.8%) for trials 2–1 and 1.3% (95% CL: 0.9–2.4%) for trials 3–2. There was no significant difference in CS (m·s-1) across trials (P<0.05). The limits of agreement were ±0.27m·s-1 of the measure for trials 2–1 and ±0.18 m·s-1 for trials 3–2. ARC proved to be less reliable with a group CV of 18.4% (95% CL: 13.5– 39.9%) for trials 2–1 and 9.8% (95% CL: 7.0–19.6%) for trials 3–2. Although the assessment of ARC is less reliable, CV data are similar to those reported previously during laboratory-based testing

Validity and Reliability of the Wattbike cycle ergometer

The purpose of this study was to assess the validity and reliability of the Wattbike cycle ergometer against the SRM Powermeter using a dynamic calibration rig (CALRIG) and trained and untrained human participants. Using the CALRIG power outputs of 50–1 250 W were assessed at cadences of 70 and 90rev.min?1. Validity and reliability data were also obtained from 3 repeated trials in both trained and untrained populations. 4 work rates were used during each trial ranging from 50–300 W. CALRIG data demonstrated significant differences (P < 0.05) between SRM and Wattbike across the work rates at both cadences. Significant differences existed in recorded power outputs from the SRM and Wattbike during steady state trials (power outputs 50–300W) in both human populations (156 ± 72 W vs. 153 ± 64 W for SRM and Wattbike respectively; P < 0.05). The reliability (CV) of the Wattbike in the untrained population was 6.7 % (95 %CI 4.8–13.2 %) compared to 2.2 % with the SRM (95 %CI 1.5–4.1 %). In the trained population the Wattbike CV was 2.6 % (95 %CI 1.8–5.1 %) compared to 1.1 % with the SRM (95 %CI 0.7–2.0 %). These results suggest that when compared to the SRM, the Wattbike has acceptable accuracy. Reliability data suggest coaches and cyclists may need to use some caution when using the Wattbike at low power outputs in a test-retest setting