Two, three and four compartment (2C, 3C and 4C) models of body composition are popular methods to measure fat mass (FM) and fat-free mass (FFM) in athletes. However, the impact of food and fluid ...intake on measurement error has not been established. The purpose of this study was to evaluate standardised (overnight fasted, rested and hydrated) v. non-standardised (afternoon and non-fasted) presentation on technical and biological error on surface anthropometry (SA), 2C, 3C and 4C models. In thirty-two athletic males, measures of SA, dual-energy X-ray absorptiometry (DXA), bioelectrical impedance spectroscopy (BIS) and air displacement plethysmography (BOD POD) were taken to establish 2C, 3C and 4C models. Tests were conducted after an overnight fast (duplicate), about 7 h later after ad libitum food and fluid intake, and repeated 24 h later before and after ingestion of a specified meal. Magnitudes of changes in the mean and typical errors of measurement were determined. Mean change scores for non-standardised presentation and post meal tests for FM were substantially large in BIS, SA, 3C and 4C models. For FFM, mean change scores for non-standardised conditions produced large changes for BIS, 3C and 4C models, small for DXA, trivial for BOD POD and SA. Models that included a total body water (TBW) value from BIS (3C and 4C) were more sensitive to TBW changes in non-standardised conditions than 2C models. Biological error is minimised in all models with standardised presentation but DXA and BOD POD are acceptable if acute food and fluid intake remains below 500 g.
Dual energy X-ray absorptiometry (DXA) is rapidly becoming more accessible and popular as a technique to monitor body composition, especially in athletic populations. Although studies in sedentary ...populations have investigated the validity of DXA assessment of body composition, few studies have examined the issues of reliability in athletic populations and most studies which involve DXA measurements of body composition provide little information on their scanning protocols. This review presents a summary of the sources of error and variability in the measurement of body composition by DXA, and develops a theoretical model of best practice to standardize the conduct and analysis of a DXA scan. Components of this protocol include standardization of subject presentation (subjects rested, overnight-fasted and in minimal clothing) and positioning on the scanning bed (centrally aligned in a standard position using custom-made positioning aids) as well as manipulation of the automatic segmentation of regional areas of the scan results. Body composition assessment implemented with such protocol ensures a high level of precision, while still being practical in an athletic setting. This ensures that any small changes in body composition are confidently detected and correctly interpreted. The reporting requirements for studies involving DXA scans of body composition include details of the DXA machine and software, subject presentation and positioning protocols, and analysis protocols.
Nutrition education (NE) is one of several strategies aimed at enhancing the dietary intake of athletes. This study investigated NE preferences of New Zealand and Australian athletes competing ...nationally and internationally. Athletes (
= 124, 22 (18, 27) years, female 54.8%) from 22 sports completed an online survey, with responses analysed using descriptive statistics. Teaching techniques considered 'extremely effective' were life examples (47.6% of athletes), hands-on activities (30.6%), and discussions with a facilitator (30.6%). Setting personal nutrition goals was important to most athletes (83.9%), along with two-way feedback with a facilitator (75.0%). General nutrition topics considered 'essential' were energy requirements (52.9%), hydration (52.9%), and nutrient deficiencies (43.3%). Performance topics considered 'essential' were recovery (58.1%), pre-exercise nutrition (51.6%), nutrition during exercise (50.0%), and energy requirements for training (49.2%). Athletes preferred a 'combination of in-person group and one-on-one sessions' (25% of athletes), 'one-on one sessions' (19.2%) and 'in-person group sessions' (18.3%), with only 13.3% interested in 'exclusively online delivery'. Sessions of 31-60 min (61.3% of athletes) held monthly (37.5%) and undertaken with athletes of the same sporting calibre (61.3%) were favoured by the participants. The preferred facilitator was a performance dietitian or nutritionist (82.1% of athletes), who had knowledge of the sport (85.5%), experience in sports nutrition (76.6%), and credibility (73.4%). This research provides novel insights into the factors that need to be considered when designing and implementing nutrition education for athletes.
Athletic populations require high-precision body composition assessments to identify true change. Least significant change determines technical error via same-day consecutive tests but does not ...integrate biological variation, which is more relevant for longitudinal monitoring. The aim of this study was to assess biological variation using least significant change measures from body composition methods used on athletes, including surface anthropometry (SA), air displacement plethysmography (BOD POD), dual-energy X-ray absorptiometry (DXA), and bioelectrical impedance spectroscopy (BIS). Thirty-two athletic males (age = 31 ± 7 years; stature = 183 ± 7 cm; mass = 92 ± 10 kg) underwent three testing sessions over 2 days using four methods. Least significant change values were calculated from differences in Day 1 Test 1 versus Day 1 Test 2 (same-day precision), as well as Day 1 Test 1 versus Day 2 (consecutive-day precision). There was high agreement between same-day and consecutive-day fat mass and fat-free mass measurements for all methods. Consecutive-day precision error in comparison with the same-day precision error was 50% higher for fat mass estimates from BIS (3,607 vs. 2,331 g), 25% higher from BOD POD (1,943 vs. 1,448 g) and DXA (1,615 vs. 1,204 g), but negligible from SA (442 vs. 586 g). Consecutive-day precision error for fat-free mass was 50% higher from BIS (3,966 vs. 2,276 g) and SA (1,159 vs. 568 g) and 25% higher from BOD POD (1,894 vs. 1,450 g) and DXA (1,967 vs. 1,461 g) than the same-day precision error. Precision error in consecutive-day analysis considers both technical error and biological variation, enhancing the identification of small, yet significant changes in body composition of resistance-trained male athletes. Given that change in physique is likely to be small in this population, the use of DXA, BOD POD, or SA is recommended.
Dual-energy x-ray absorptiometry (DXA) is becoming a popular tool to measure body composition in athletes, owing to its ease of operation and comprehensive analysis of body composition. This study ...represents the first systematic investigation of the reliability of DXA measurements of body composition in trained individuals and includes measurements of daily variability as well as the specific effect of the intake of a meal.
Physically active young adults (15 females, 16 males) underwent five whole-body DXA scans during a 2-d period: in the morning after an overnight fast, ~5 min later after repositioning on the scanning bed, ~8 h later after usual daily activities, and the next morning before and ~30 min after consumption of a simple breakfast. Magnitudes of typical (standard) errors of measurement and changes in the mean of DXA measures were assessed by standardization.
Repositioning produced trivial typical errors for whole-body composition, whereas regional body composition showed substantial errors. Daily activities and consumption of breakfast generally produced a substantial increase in the typical error and mean of DXA estimates of total and regional lean mass and associated body mass.
Having a standardized scanning protocol and fasted subjects is the most practical way to minimize measurement errors. Future studies involving DXA in measuring body composition should report their scanning and analysis protocol with their associated typical errors of measurement so that the level of reliability can be assessed.
This study describes the body composition traits of modern-day elite rugby union athletes according to playing position and ethnicity. Thirty-seven international Australian rugby athletes of ...Caucasian and Polynesian descent undertook body composition assessment using dual-energy X-ray absorptiometry and surface anthropometry. Forwards were significantly taller, heavier and had a greater total fat mass and lean mass than backs. Backs displayed a higher percentage lean mass and lower sum of seven skinfolds and percentage fat mass. While no whole body composition differences were seen between ethnicities, significant regional differences were observed. In the periphery (arm and leg) regions, Polynesians had a greater proportion of fat mass (53.1% vs. 51.3%, P = 0.052, d = 0.5) and lean mass (49.7% vs. 48.6%, P = 0.040, d = 0.9), while in the trunk region a lower proportion of fat mass (37.2% vs. 39.5%, P = 0.019, d = 0.7) and lean mass (45.6% vs. 46.8%, P = 0.020, d = 1.1). Significant differences were also seen between Caucasian and Polynesian forwards in leg lean mass (31.4 kg vs. 35.9 kg, P = 0.014, d = 2.4) and periphery lean mass (43.8 kg vs. 49.6 kg, P = 0.022, d = 2.4). Elite Polynesian rugby athletes have different distribution patterns of fat mass and lean mass compared to Caucasians, which may influence their suitability for particular positions.
A questionnaire-based screening tool for male athletes at risk of low energy availability (LEA) could facilitate both research and clinical practice. The present options rely on proxies for LEA such ...screening tools for disordered eating, exercise dependence, or those validated in female athlete populations. in which the female-specific sections are excluded. To overcome these limitations and support progress in understanding LEA in males, centres in Australia, Norway, Denmark, and Sweden collaborated to develop a screening tool (LEAM-Q) based on clinical investigations of elite and sub-elite male athletes from multiple countries and ethnicities, and a variety of endurance and weight-sensitive sports. A bank of questions was developed from previously validated questionnaires and expert opinion on various clinical markers of LEA in athletic or eating disorder populations, dizziness, thermoregulation, gastrointestinal symptoms, injury, illness, wellbeing, recovery, sleep and sex drive. The validation process covered reliability, content validity, a multivariate analysis of associations between variable responses and clinical markers, and Receiver Operating Characteristics (ROC) curve analysis of variables, with the inclusion threshold being set at 60% sensitivity. Comparison of the scores of the retained questionnaire variables between subjects classified as cases or controls based on clinical markers of LEA revealed an internal consistency and reliability of 0.71. Scores for sleep and thermoregulation were not associated with any clinical marker and were excluded from any further analysis. Of the remaining variables, dizziness, illness, fatigue, and sex drive had sufficient sensitivity to be retained in the questionnaire, but only low sex drive was able to distinguish between LEA cases and controls and was associated with perturbations in key clinical markers and questionnaire responses. In summary, in this large and international cohort, low sex drive was the most effective self-reported symptom in identifying male athletes requiring further clinical assessment for LEA.
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