Preseason Body Composition Adaptations in Elite White and Polynesian Rugby Union Athletes

Nutritional knowledge, attitudes and behaviours in rugby league; influences of age, body composition and ancestry

INTRODUCTION

Rugby league is a physically demanding sport that necessitates considerable nutritional intake, focusing on quality and type, in order to optimize training and competition demands. However, rugby league athletes are reported to have inadequate nutrition intake to match these demands. Some factors that may determine an athlete's nutrition intake have been reported in other sports, including (but not limited to, knowledge, time, cooking skills, food costs, income, belief in the importance of nutrition, body composition goals, and family/cultural support). However, these potential factors are relatively unexplored in rugby league, where a range of personal (age, body composition) or social (ancestry) influences could affect nutritional intake. Further exploration of these factors is warranted to understand the knowledge, attitudes and behavior underlying rugby league athletes' nutritional intake that can provide practitioners with a more detailed understanding of how to approach nutrition behaviors and attitudes in rugby league athletes.

OBJECTIVES

The primary aim was to describe the nutrition behaviors and knowledge of rugby league athletes. A secondary aim was to compare nutrition knowledge and behavior based on age, body composition and self-identified ancestry.

METHODS

Fifty professional rugby league athletes anonymously completed a seventy-six-question online survey. The survey consisted of three sections : 1) sports nutrition knowledge, 2) attitudes toward nutrition on performance , and 3) nutrition behaviors. All participants completed the online survey without assistance using their own personal device, with data entered via REDCap during pre-season. Nutrition knowledge was compared based on age (years), body composition (body fat percentage (%)) and ancestral groups (Pasifika, Aboriginal and/or Torres Strait Islander (ATSI) and Anglo- European).Pearson correlation was used for the relationship between nutrition knowledge, age and body composition. An Analysis of Covariance (ANCOVA) was used to determine nutrition knowledge differences between ancestral groups with age and body composition as covariates. Attitudes and behaviors were compared based on age groups (<20, 20-24 and >25 y), ancestry and body composition. Attitudes and behaviors were analyzed by Pearson correlation for body composition, one-way ANOVA for age groups and ANCOVA for ancestry with covariates age and body composition.

RESULTS

Overall athletes' nutrition knowledge score was reported as 40 ± 12% (overall rating "poor"). Nutritional behaviors were significant for body composition, as those with lower body fat percentage had higher intakes of vegetables and dairy products (p = 0.046, p = 0.009), and ate more in the afternoon (lunch p = 0.048, afternoon snack p = 0.036). For ancestry, after adjustment for both age and body composition, Pasifika athletes were more inclined to miss breakfast and lunch compared to their Anglo-European (p = 0.037, p = 0.012) and ATSI (p = 0.022, p = 0.006) counterparts and ate more fruit than Anglo-Europeans (p = 0.006, p = 0.016). After adjustment for body composition, ATSI athletes also viewed the impact of nutrition on mental health and well-being significantly lower than Pasifika (p = 0.044).

CONCLUSION

These findings suggest differences exist within rugby league athletes based on ancestral backgrounds and body composition for nutrition attitudes, behaviors and knowledge. Such outcomes could be used when designing nutrition education interventions, with consideration given to these factors to optimize long-term positive behavior change.

Energy Balance and Dietary Intake in Young Rugby Players during a Pre-Season Micro-Cycle: A Cluster Analysis

Rugby players must develop excellent levels of conditioning during adolescence. However, this pivotal period of life is also characterized by a surge in biological growth, which further increases the energy and nutritional requirements of this population. This study examined within-individual differences in energy intake (EI) and energy balance (EB) of 46 young rugby players during a pre-season micro-cycle. Two clusters were identified with significantly different characteristics and EB states, suggesting that young rugby players adjust their EI to match their body composition goals. The first cluster is characterized by players with a low body fat% (12.87 ± 2.53). They had a positive EB (330 ± 517 kcal), suggesting a goal of increasing muscle mass. Conversely, the second cluster is characterized by a higher body fat% (23.1 ± 1.6, p < 0.005) and reported a negative, lower EB (-683 ± 425 kcal, p < 0.005), suggesting a goal focused on reducing fat mass. Although our study provides more optimistic results than previous ones regarding the high risk of inadequate EI in young rugby players, we emphasize the importance of rigorous nutritional support, especially for players aiming to lose weight, to avoid severe caloric restriction, as well as the downstream effects of such practices on their nutritional status, given the higher risk of macro- (e.g., CHO < 6 g/kg/d) and micronutrient (e.g., iron < 11 mg/d, calcium < 1300 mg/d, vitamin D < 5 mg/d) deficiencies.

Match-Play Demands and Anthropometric Characteristics of National and International Women's Fifteen-a-side Rugby Union: A Systematic Scoping Review

ABSTRACT

Curtis, C, Mitchell, S, and Russell, M. Match-play demands and anthropometric characteristics of national and international women's, fifteen-a-side rugby union: a systematic scoping review. J Strength Cond Res 37(10): e569-e580, 2023-An increased professionalization within women's 15-a-side rugby union (R15s) has prompted greater sports science support and a need to better understand demands of the sport. Online database (PubMed, MEDLINE, and SPORTDiscus) searches were performed according to the PRISMA Scoping Review protocol. Studies were eligible if match-play demands or anthropometric characteristics of women's R15s players were investigated. After calibration exercises, the lead and senior authors independently quality assessed each study. A total of 1,068 studies were identified; 15 of which met the study criteria. The mean total match-play distance covered was 5,378 ± 626 m (forwards: 5,188 ± 667 m and backs: 5,604 ± 609 m), with first half values exceeding second half (2,922 ± 87 m vs. 2,876 ± 115 m). The mean relative distance (RD) (72.0 m·min -1 ) was greater than their male counterparts (64.2 m·min -1 -68.2 m·min -1 ). Backs were exposed to more severe collisions compared with forwards (6 ± 1 vs. 5 ± 4). Work:rest ratios ranged between 1.0:0.7-1.0:0.9. Regarding anthropometric characteristics, the mean lean and fat mass was reported as 51.9 ± 5.2 kg and 18.6 ± 4.6 kg, respectively. The mean body fat percentage was 24.7 ± 5.4%. The mean bone mineral density and bone mineral content was 1.27 ± 0.04 g·cm -2 and 3.07 ± 0.2 kg, respectively. This scoping review summarizes the current evidence base and key findings relating to the match-play demands and anthropometric characteristics that can be used in practice to inform player welfare and sport science support to women's R15s players at a national and international standard. Numerous gaps in our understanding of how best to develop and optimize performance, physical demands, and anthropometric characteristics of women's R15s players remain.

In-Season Longitudinal Hydration/Body Cell Mass Ratio Changes in Elite Rugby Players

BACKGROUND

Hydration status has a direct role in sports performance. Bioelectrical Impedance Vector Analysis (BIVA) and Urine Specific Gravity (USG) are commonly used to assess hydration. The study aims to identify the sensitivity and relationship between BIVA and USG in a field sports setting.

METHODS

BIVA and USG measurements were conducted five times throughout one rugby season. 34 elite male rugby players (25.1 ± 4.4 years; 184.0 ± 7.8 cm; 99.9 ± 13.4 kg) were enrolled. Differences over time were tested using one-way repeated measures ANOVA, and Bonferroni's post-hoc test was applied in pairwise comparisons. Resistance-reactance graphs and Hotelling's T2 test were used to characterize the sample and to identify bioelectrical changes. A repeated measures correlation test was conducted for BIVA-USG associations.

RESULTS

Two clear trends were seen: (1) from July to September, there was a vector shortening and an increase of the phase angle (p < 0.001); and (2) from December to April, there was a vector lengthening and a decrease of the phase angle (p < 0.001). USG reported neither changes nor correlation with BIVA longitudinally (p > 0.05). Vector variations indicated a body fluid gain (especially in the intracellular compartment) and a body cell mass increase during the preseason, suggesting a physical condition and performance improvement. During the last months of the season, the kinetic was the opposite (fluid loss and decreased body cell mass).

CONCLUSIONS

Results suggested that BIVA is sensitive to physiological changes and a better option than USG for assessing hydration changes during a rugby sports season.

Effects of preseason training on body composition, running performance, biochemical markers and workload variation in professional rugby union players

Few studies have examined the impact of a preseason training intervention through systematic measures in Pro D2 rugby union (RU). Therefore, this study aimed to describe the effects of 12 weeks of preseason training (three blocks) on body composition, running performance, biochemical markers, and workload (WL) variation in professional RU players. Physiological (physical and biochemical) responses to preseason WL were analyzed by examining changes in anthropometric characteristics, Yo-Yo intermittent recovery level 1 (Yo-Yo IR1) test, blood samples (BS), Hooper index (1-7), the 10-Hz global positioning system (GPS), and session rating of perceived exertion (s-RPE) in nineteen elite male players. Changes throughout the preseason were analyzed using the one-way and mixed-model analysis of variance. Significant (p < 0.01) improvements occurred in anthropometry and Yo-Yo IR1 running performance in forwards and backs. Total distance (p < 0.01) and impact (p < 0.05) during the second block were meaningfully higher than the other two blocks, with backs showing higher values than forwards. As expected, WL decreased significantly (p < 0.01) during the last training block. The WL variations were correlated with changes in biochemical markers over the preseason period. The collected data can be used for i) profiling French Pro D2 rugby championships players, ii) establishing effective training strategies, and iii) setting preseason WL expectations.

Season-Long Changes in the Body Composition Profiles of Competitive Female Rugby Union Players Assessed via Dual Energy X-Ray Absorptiometry

Background: Reference data for the body composition values of female athletes are limited to very few sports, with female Rugby Union players having mostly been omitted from such analyses.Methods: Using dual energy X-ray absorptiometry (DXA) scans, this study assessed the body composition profiles (body mass, bone mineral content; BMC, fat mass; FM, lean mass; LM, bone mineral density; BMD) of 15 competitive female Rugby Union players before and after the 2018/19 competitive season. Total competitive match-play minutes were also recorded for each player.Results: Body mass (73.7 ± 9.6 kg vs 74.9 ± 10.2 kg, p ≤ 0.05, d = 0.13) and BMC (3.2 ± 0.4 kg vs 3.3 ± 0.4 kg, p ≤ 0.05, d = 0.15) increased pre- to post-season for all players. Conversely, FM (21.0 ± 8.8 kg), LM (50.7 ± 3.9 kg), and BMD (1.31 ± 0.06 g·cm^-2) were similar between time-points (all p > .05). Accounting for position, body mass (r_partial(12) = 0.196), FM (r_partial(12) = -0.013), LM (r_partial(12) = 0.351), BMD (r_partial(12) = 0.168) and BMC (r_partial(12) = -0.204) showed no correlation (all p > .05) against match-play minutes.Conclusion: The demands of the competitive season influenced specific body composition indices (i.e., body mass, BMC) in female Rugby Union players; a finding which was unrelated to the number of minutes played in matches. While the causes of such differences remain unclear, practitioners should be cognizant of the body composition changes occurring throughout a female Rugby Union competitive season and, where necessary, consider modifying variables associated with adaptation and recovery accordingly.

Differences in Adiposity Profile and Body Fat Distribution between Forwards and Backs in Sub-Elite Spanish Female Rugby Union Players

The purpose of this study was to analyze the adiposity profile and the body fat distribution in 56 sub-elite female rugby union players involved in the Spanish National Women's Rugby Union Championships. The participants included in this study, which was the first to analyze sub-elite players, show thinner skinfolds, lower fat mass, and lesser fat percentage than previously reported for elite female rugby union players. Forwards were heavier and had higher body mass index (BMI) and fat mass, thicker skinfolds, and higher fat percentage than back players. Forwards also possessed significantly greater total fat-free mass than backs. All these differences were applicable only to players under 25 years of age. A negative correlation between age and both abdominal and lower extremity fat was found in forward players but not in the backs. Both Yuhasz and Faulkner equations tended to underestimate fat percentage in comparison to Reilly equation. Although Yuhasz equation provided higher systematic error, random error was lower in comparison to Faulkner equation. This study shows the relevance of analyzing and monitoring adiposity in female rugby union players to optimize adaptation to the sports requirements of different playing positions and age.

The Physical Characteristics of Elite Female Rugby Union Players

This study explored the anthropometric and body composition characteristics of elite female rugby union players, comparing between and within different playing positions. Thirty elite female rugby union players (25.6 ± 4.3 y, 171.3 ± 7.7 cm, 83.5 ± 13.9 kg) from New Zealand participated in this study. Physical characteristics were assessed using anthropometric (height, body mass, skinfolds) and body composition (dual-energy X-ray absorptiometry) measures. Forwards were significantly taller (p < 0.01; d = 1.34), heavier (p < 0.01; d = 2.19), and possessed greater skinfolds (p < 0.01; d = 1.02) than backs. Forwards also possessed significantly greater total (p < 0.01; d = 1.83–2.25) and regional (p < 0.01; d = 1.50–2.50) body composition measures compared to backs. Healthy bone mineral density values were observed in both forwards and backs, with significantly greater values observed at the arm (p < 0.01; d = 0.92) and femoral neck (p = 0.04; d = 0.77) sites for forwards. Tight-five players were significantly heavier (p = 0.02; d = 1.41) and possessed significantly greater skinfolds (p < 0.01; d = 0.97) than loose-forwards. Tight-five also possessed significantly greater total body composition measures (p < 0.05; d = 0.97–1.77) and significantly greater trunk lean mass (p = 0.04; d = 1.14), trunk fat mass (p < 0.01; d = 1.84), and arm fat mass (p = 0.02; d = 1.35) compared to loose-forwards. Specific programming and monitoring for forwards and backs, particularly within forward positional groups, appear important due to such physical characteristic differences.

Physical and Fitness Characteristics of Elite Professional Rugby Union Players

This study explored the physical and fitness characteristics of elite professional rugby union players and examined the relationships between these characteristics within forwards and backs. Thirty-nine elite professional rugby union players from the New Zealand Super Rugby Championship participated in this study. Body composition was measured using dual-energy X-ray absorptiometry alongside anthropometrics. Fitness characteristics included various strength, power, speed, and aerobic fitness measures. Forwards were significantly (p ≤ 0.01) taller and heavier than backs, and possessed greater lean mass, fat mass, fat percentage, bone mass, and skinfolds. Forwards demonstrated greater strength and absolute power measures than backs (p = 0.02), but were slower and possessed less aerobic fitness (p ≤ 0.01). Skinfolds demonstrated very large correlations with relative power (r = −0.84) and speed (r = 0.75) measures within forwards, while backs demonstrated large correlations between skinfolds and aerobic fitness (r = −0.54). Fat mass and fat percentage demonstrated very large correlations with speed (r = 0.71) and aerobic fitness (r = −0.70) measures within forwards. Skinfolds, fat mass, and fat percentage relate strongly to key fitness characteristics required for elite professional rugby union performance. Individual and positional monitoring is important due to the clear differences between positions.

Development of an Anthropometric Prediction Model for Fat-Free Mass and Muscle Mass in Elite Athletes

The monitoring of body composition is common in sports given the association with performance. Surface anthropometry is often preferred when monitoring changes for its convenience, practicality, and portability. However, anthropometry does not provide valid estimates of absolute lean tissue in elite athletes. The aim of this investigation was to develop anthropometric models for estimating fat-free mass (FFM) and skeletal muscle mass (SMM) using an accepted reference physique assessment technique. Sixty-four athletes across 18 sports underwent surface anthropometry and dual-energy X-ray absorptiometry (DXA) assessment. Anthropometric models for estimating FFM and SMM were developed using forward selection multiple linear regression analysis and contrasted against previously developed equations. Most anthropometric models under review performed poorly compared with DXA. However, models derived from athletic populations such as the Withers equation demonstrated a stronger correlation with DXA estimates of FFM (r = .98). Equations that incorporated skinfolds with limb girths were more effective at explaining the variance in DXA estimates of lean tissue (Sesbreno FFM [R2 = .94] and Lee SMM [R2 = .94] models). The Sesbreno equation could be useful for estimating absolute indices of lean tissue across a range of physiques if an accepted option like DXA is inaccessible. Future work should explore the validity of the Sesbreno model across a broader range of physiques common to athletic populations.

Is an Energy Surplus Required to Maximize Skeletal Muscle Hypertrophy Associated With Resistance Training

Resistance training is commonly prescribed to enhance strength/power qualities and is achieved via improved neuromuscular recruitment, fiber type transition, and/ or skeletal muscle hypertrophy. The rate and amount of muscle hypertrophy associated with resistance training is influenced by a wide array of variables including the training program, plus training experience, gender, genetic predisposition, and nutritional status of the individual. Various dietary interventions have been proposed to influence muscle hypertrophy, including manipulation of protein intake, specific supplement prescription, and creation of an energy surplus. While recent research has provided significant insight into optimization of dietary protein intake and application of evidence based supplements, the specific energy surplus required to facilitate muscle hypertrophy is unknown. However, there is clear evidence of an anabolic stimulus possible from an energy surplus, even independent of resistance training. Common textbook recommendations are often based solely on the assumed energy stored within the tissue being assimilated. Unfortunately, such guidance likely fails to account for other energetically expensive processes associated with muscle hypertrophy, the acute metabolic adjustments that occur in response to an energy surplus, or individual nuances like training experience and energy status of the individual. Given the ambiguous nature of these calculations, it is not surprising to see broad ranging guidance on energy needs. These estimates have never been validated in a resistance training population to confirm the "sweet spot" for an energy surplus that facilitates optimal rates of muscle gain relative to fat mass. This review not only addresses the influence of an energy surplus on resistance training outcomes, but also explores other pertinent issues, including "how much should energy intake be increased," "where should this extra energy come from," and "when should this extra energy be consumed." Several gaps in the literature are identified, with the hope this will stimulate further research interest in this area. Having a broader appreciation of these issues will assist practitioners in the establishment of dietary strategies that facilitate resistance training adaptations while also addressing other important nutrition related issues such as optimization of fuelling and recovery goals. Practical issues like the management of satiety when attempting to increase energy intake are also addressed.