Paul Hough

Achieving adequate sleep is considered important for athletic performance and recovery from exercise, yet the sleep monitoring methods applied amongst practitioners within highperformance sport are not well documented. This study aimed to identify the athlete sleep monitoring practices currently being implemented by practitioners working with full-time, junior (competing at the highest level), and semi-professional athletes. An online survey was developed and disseminated via email and social media to practitioners working with high-performance athletes. A sample of 145 practitioners completed the survey. Most (88%) practitioners rated sleep as ‘extremely important’ for recovery and performance (79%) and 84% of practitioners had advised athletes on improving sleep. The practitioners who reported monitoring sleep used several methods, including a questionnaire (37%), diary (26%) and actigraphy (19%). The most cited barrier to monitoring sleep was lack of time/resources. Most (79%) practitioners had not determined athletes’ chronotypes. Over half (54%) of the practitioners suggested their athletes did not get enough sleep outside of competition periods; the highest ranked suggested reason for this was screen time (i.e., using electronic devices). Practitioners recognise the importance of sleep for athletes and sleep education/monitoring was common amongst the practitioners; however, chronotype analysis was not widely used. Most practitioners used questionnaires and diaries to monitor athletes’ sleep and suggested that their athletes often experience insufficient sleep outside of competition periods. 

Introduction. Restricted carbohydrate diets (RCDs) have become popular amongst endurance athletes as a means of increasing fat oxidation and improving health outcomes. However, it is unclear if these adaptations improve exercise performance. Aim of Study. This case study investigated the effect of a three-week RCD on exercise metabolism and performance, alongside evaluating the subjective experiences, of three recreational cyclists. Material and Methods. Participants were randomly assigned to the normal diet (ND) (~50% CHO, ~30% fat, ~20% protein) or RCD (10% carbohydrate, 70% fat and 20% protein) and switched diets after three weeks. The participant’s performed a weekly laboratory assessment consisting of an incremental, sub-maximal cycling step-test and a 20-minute time trial (TT). Body fat (skinfold) measures were repeated after each diet and the participants recorded their food/drink intake using a smartphone app throughout the study. Results. Whole-body peak fat oxidation, measured during sub-maximal cycling, markedly increased during the RCD (ND 0.61 ± 0.1 vs RCD 1.45 ± 0.3 g/min). There was no improvement in average power output during the TT for any participant following the RCD (243 ± 5 W) versus the ND (253 ± 5 W) condition. Two participants experienced a reduction (–8% and –10%) in (∑7) skinfolds following the RCD. The participants’ subjective reports indicated an improvement in general dietary habits, but there were reports of increased perceived exertion to exercise during the RCD. Conclusions. The RCD increased whole-body fat oxidation, promoted positive subjective dietary habits and decreased body fat amongst amateur cyclists. However, these outcomes did not translate into improved exercise performance.

Commercially available wrist-worn heart rate (HR) monitors have become increasingly popular. However, the accuracy of the devices across a range of exercise intensities is largely unknown. This study investigated the accuracy of four wrist-worn HR monitors (Apple Watch Series 1, Fitbit Charge, TomTom Touch, and Mio Fuse). Eighteen adults completed three trials on a cycle ergometer wearing a chest-worn HR monitor (Polar). Trial 1 established the HR-power output relationship, and resting and maximum HR. In trials 2 and 3, participants were fitted to an electrocardiogram (ECG) and completed a step test consisting of 5 x 3 minute stages at 40 - 80% of HR reserve (determined in trial 1) whilst wearing two wrist-worn HR monitors. Relative to ECG, there were no differences in HR between the devices during exercise (p = 0.239), and no device × exercise intensity interaction (p = 0.370). There were no instances where ECG and Polar data differed by ≥ 5 b·min-1. Conversely, there were two instances (2.2%) with the Apple, four (4.4%) with the Mio, 10 (11.1%) with the TomTom, and 19 (21.1%) with the Fitbit. A chest-worn HR monitor offers greater accuracy compared to wrist-worn devices.

Endurance athletes are recommended to maintain energy balance and ensure adequate energy availability (EA) so that endurance performance is not compromised. Purpose: Describe and evaluate the energy balance of an athlete competing in a self-sufficient, multistage ultramarathon (MSU). Methods: A male endurance athlete (age 35 years; height 183.0 cm; body mass 78.4 kg; VO2max 66 ml/kg/min) volunteered to take part in this observational case study prior to competing in the Marathon des Sables (MdS) 2016. The subject self-reported energy intake (EI) by reviewing his dietary plan following each stage. Basal metabolic rate (BMR) was estimated prior to the MdS based on fat-free mass. Distance and moving speed were recorded using a GPS device throughout the race. Exercise energy expenditure (EEE) was calculated using the GPS device algorithm. Total energy expenditure (TEE) was calculated by adding the athlete’s BMR to the recorded EEE. Energy balance was calculated by subtracting EI from TEE. Results: Mean daily EI was 2946 ± 358 kcal and daily EEE was 3006 ± 1030 kcal. This resulted in a total energy deficit of 9609 kcal with a daily energy deficit of 1922 ± 952 kcal/day. The athlete did not report any subjective feelings of hunger at any point during the event. Conclusions: The athlete did not consume enough calories to meet estimated energy requirements, resulting in a negative energy balance and low EA throughout the event. Relying on subjective perception of hunger to modulate energy intake is an ineffective strategy during a MSU.

Purpose: We hypothesized that the use of trekking poles would help maintain muscle function and reduce indices of muscle damage after a day's mountain trekking.

Methods: Thirty-seven physically active males (n = 26) and females (n = 11) volunteered to participate and were divided into either a trekking pole (TP) or no pole (NP) group. Participants carried a day sack (5.6 ± 1.5 kg) and made the ascent and descent of the highest peak in England and Wales (Mount Snowdon). HR and RPE were recorded during the ascent and descent. Indices of muscle damage, namely, maximal voluntary contraction, muscle soreness, creatine kinase (CK), and vertical jump performance, were measured before, immediately after (except CK), and 24, 48, and 72 h after trek.

Results: HR was not different between groups, although RPE was significantly lower in TP during the ascent. The TP group showed attenuation of reductions in maximal voluntary contraction immediately after and 24 and 48 h after the trek; muscle soreness was significantly lower at 24 and 48 h after the trek, and CK was also lower at 24 h after the trek in the TP group. No differences in vertical jump were found.

Conclusions: Trekking poles reduce RPE on mountain ascents, reduce indices of muscle damage, assist in maintaining muscle function in the days after a mountain trek, and reduce the potential for subsequent injury.

The results of previous research have demonstrated that static stretching (SS) can reduce muscular performance and that dynamic stretching (DS) can enhance muscular performance. The purpose of this study was to assess the effects of SS and DS on vertical jump (VJ) performance and electromyographic (EMG) activity of the m. vastus medialis. Eleven healthy men (age 21 +/- 2 years) took part in 3 conditions (no stretching [NS], SS, and DS), on separate occasions in a randomized, crossover design. During each condition, measurements of VJ height and EMG activity during the VJ were recorded. A repeated-measures analysis of variance and post hoc analysis indicated that VJ height was significantly less (4.19 +/- 4.47%) after SS than NS (p