Are professional young rugby league players eating enough? Energy intake,expenditure and balance during a pre-season

Abstract

Due to the unique energetic demands of professional young collision sport athletes, accurate assessment of energy balance is required. Consequently, this is the first study to simultaneously investigate the energy intake, expenditure and balance of professional young rugby league players across a pre-season period. The total energy expenditure of six professional young male rugby league players was measured via doubly labelled water over a fourteen-day assessment period. Resting metabolic rate was measured and physical activity level calculated. Dietary intake was reported via Snap-N-Send over a non-consecutive ten-day assessment period, alongside changes in fasted body mass and hydration status. Accordingly, energy balance was inferred. The mean (standard deviation) difference between total energy intake (16.73 (1.32) MJ^.day^?1) and total energy expenditure (18.36 (3.05) MJ^.day^?1) measured over the non-consecutive ten-day period was unclear (?1.63 (1.73) MJ^.day^?1; ES?=?0.91?±?1.28; p?=?0.221). This corresponded in a most likely trivial decrease in body mass (?0.65 (0.78) kg; ES?=?0.04?±?0.03; p?=?0.097). Resting metabolic rate and physical activity level across the fourteen-day pre-season period was 11.20 (2.16) MJ^.day^?1 and 1.7 (0.2), respectively. For the first time, this study utilises gold standard assessment techniques to elucidate the distinctly large energy expenditures of professional young rugby league players across a pre-season period, emphasising a requirement for equally large energy intakes to achieve targeted body mass and composition adaptations. Accordingly, it is imperative that practitioners regularly assess the energy balance of professional young collision-sport athletes to ensure their unique energetic requirements are achieved.     

Energy expenditure in professional flat jockeys using doubly labelled water during the racing season: Implications for body weight management

To formulate individualized dietary strategies for jockeys, it is vital that energy requirements are quantified. We measured total energy expenditure (TEE) over two separate weeks in spring and summer using doubly labelled water in a group of male flat jockeys (n?=?8, 36.9?±?5.7 years, 164?±?8?cm, 54.6?±?2.5?kg). Total energy intake (TEI) was self-recorded, as were all riding and structured exercise activity. Mean daily TEE was 10.83 (±2.3) and 10.66 (±1.76) MJ, (p?=?.61) respectively. Self-reported TEI were 6.03 (±1.7) and 5.37 (±1.1) MJ (p?=?.40), respectively, and were significantly lower than TEE (p?=?.01). Mean race rides were 17 (±6) and 13 (±3; p?=?0.37) and horses ridden at morning exercise were 8 (±6) and 7 (±4; p?=?.77) respectively. Additional structured exercise was 76.25 (±95.1) and 52.5 (±80.9) min per week (p?=?.35), respectively. At the individual level, TEE was related to body mass and the level of non-racing physical activity, but not riding. Physical activity levels for TEE were 1.76 (±0.37) and 1.69 (±0.27; p?=?.59) and appear modest when compared with other athletes, and similar to age-matched non-athletes, suggesting that conventional sport-specific nutritional recommendations do not appear applicable. The large discrepancy between TEE and TEI suggests significant under reporting of dietary intake. These data now provide an appropriate framework from which to formulate jockey nutritional guidelines to promote the ability to achieve the daily weight target and improve athlete welfare.     

Cross-sectional comparison of body composition and resting metabolic rate in Premier League academy soccer players: Implications for growth and maturation

ABSTRACT

For the first time we aimed to: (1) assess fat-free mass (FFM) and RMR in youth soccer players, (2) compare measured RMR to estimated RMR using previously published prediction equations, and (3) develop a novel population-specific prediction equation. In a cross-sectional design, 99 males from a Premier League academy underwent assessments of body composition (DXA) and RMR (indirect-calorimetry). Measured RMR was compared to estimated values from five prediction equations. A novel RMR prediction equation was developed using stepwise multiple regression. FFM increased (P<0.05) between U12 (31.6±4.2 kg) and U16 (56.3±5.3 kg) after which no further increases occurred (P>0.05). RMR in the U12s (1655±195 kcal.day^?1), U13s (1720±205 kcal.day^?1) and U14s (1846±218kcal.day^?1) was significantly lower than the U15s (1957±128 kcal.day^?1), U16s (2042±155 kcal.day^?1), U18s (1875±180 kcal.day^?1) and U23s (1941±197 kcal.day^?1) squads (P>0.05). FFM was the single best predictor of RMR (r²=0.43; P<0.01) and was subsequently included in the novel prediction equation: RMR (kcal.day^?1) = 1315 + (11.1 x FFM in kg). Both FFM and RMR increase from 12-16 years old, thus highlighting the requirement to adjust daily energy intake to support growth and maturation. The novel prediction RMR equation developed may help to inform daily energy requirements.     

Comparison of total energy expenditure assessed by two devices in controlled and free-living conditions

Abstract

The objective of this study was to evaluate the validity of total energy expenditure (TEE) provided by Actiheart^® and Armband^®. Normal-weight adult volunteers wore both devices either for 17 hours in a calorimetric chamber (CC, n = 49) or for 10 days in free-living conditions (FLC) outside the laboratory (n = 41). The two devices and indirect calorimetry or doubly labelled water, respectively, were used to estimate TEE in the CC group and FLC group. In the CC, the relative value of TEE error was not significant (p > 0.05) for Actiheart^® but significantly different from zero for Armband^®, showing TEE underestimation (?4.9%, p < 0.0001). However, the mean absolute values of errors were significantly different between Actiheart^® and Armband^®: 8.6% and 6.7%, respectively (p = 0.05). Armband^® was more accurate for estimating TEE during sleeping, rest, recovery periods and sitting–standing. Actiheart^® provided better estimation during step and walking. In FLC, no significant error in relative value was detected. Nevertheless, Armband^® produced smaller errors in absolute value than Actiheart^® (8.6% vs. 12.8%). The distributions of differences were more scattered around the means, suggesting a higher inter-individual variability in TEE estimated by Actiheart^® than by Armband^®. Our results show that both monitors are appropriate for estimating TEE. Armband^® is more effective than Actiheart^® at the individual level for daily light-intensity activities.     

Quantification of training load during one-, two- and three-game week schedules in professional soccer players from the English Premier League: implications for carbohydrate periodisation

Muscle glycogen is the predominant energy source for soccer match play, though its importance for soccer training (where lower loads are observed) is not well known. In an attempt to better inform carbohydrate (CHO) guidelines, we quantified training load in English Premier League soccer players (n = 12) during a one-, two- and three-game week schedule (weekly training frequency was four, four and two, respectively). In a one-game week, training load was progressively reduced (P < 0.05) in 3 days prior to match day (total distance = 5223 ± 406, 3097 ± 149 and 2912 ± 192 m for day 1, 2 and 3, respectively). Whilst daily training load and periodisation was similar in the one- and two-game weeks, total accumulative distance (inclusive of both match and training load) was higher in a two-game week (32.5 ± 4.1 km) versus one-game week (25.9 ± 2 km). In contrast, daily training total distance was lower in the three-game week (2422 ± 251 m) versus the one- and two-game weeks, though accumulative weekly distance was highest in this week (35.5 ± 2.4 km) and more time (P < 0.05) was spent in speed zones >14.4 km · h^?1 (14%, 18% and 23% in the one-, two- and three-game weeks, respectively). Considering that high CHO availability improves physical match performance but high CHO availability attenuates molecular pathways regulating training adaptation (especially considering the low daily customary loads reported here, e.g., 3–5 km per day), we suggest daily CHO intake should be periodised according to weekly training and match schedules.