Precision Error in Dual-Energy X-Ray Absorptiometry Body Composition Measurements in Elite Male Rugby League Players

Network-based modelling reveals cell-type enriched patterns of non-coding RNA regulation during human skeletal muscle remodelling

A majority of human genes produce non-protein-coding RNA (ncRNA), and some have roles in development and disease. Neither ncRNA nor human skeletal muscle is ideally studied using short-read sequencing, so we used a customised RNA pipeline and network modelling to study cell-type specific ncRNA responses during muscle growth at scale. We completed five human resistance-training studies (n=144 subjects), identifying 61% who successfully accrued muscle-mass. We produced 288 transcriptome-wide profiles and found 110 ncRNAs linked to muscle growth in vivo, while a transcriptome-driven network model demonstrated interactions via a number of discrete functional pathways and single-cell types. This analysis included established hypertrophy-related ncRNAs, including CYTOR - which was leukocyte-associated (FDR = 4.9 ×10-7). Novel hypertrophy-linked ncRNAs included PPP1CB-DT (myofibril assembly genes, FDR = 8.15 × 10-8), and EEF1A1P24 and TMSB4XP8 (vascular remodelling and angiogenesis genes, FDR = 2.77 × 10-5). We also discovered that hypertrophy lncRNA MYREM shows a specific myonuclear expression pattern in vivo. Our multi-layered analyses established that single-cell-associated ncRNA are identifiable from bulk muscle transcriptomic data and that hypertrophy-linked ncRNA genes mediate their association with muscle growth via multiple cell types and a set of interacting pathways.

Network-based modelling reveals cell-type enriched patterns of non-coding RNA regulation during human skeletal muscle remodelling

A majority of human genes produce non-protein-coding RNA (ncRNA), and some have roles in development and disease. Neither ncRNA nor human skeletal muscle is ideally studied using short-read sequencing, so we used a customized RNA pipeline and network modelling to study cell-type specific ncRNA responses during muscle growth at scale. We completed five human resistance-training studies (n = 144 subjects), identifying 61% who successfully accrued muscle-mass. We produced 288 transcriptome-wide profiles and found 110 ncRNAs linked to muscle growth in vivo, while a transcriptome-driven network model demonstrated interactions via a number of discrete functional pathways and single-cell types. This analysis included established hypertrophy-related ncRNAs, including CYTOR-which was leukocyte-associated (false discovery rate [FDR] = 4.9 × 10-7). Novel hypertrophy-linked ncRNAs included PPP1CB-DT (myofibril assembly genes, FDR = 8.15 × 10-8), and EEF1A1P24 and TMSB4XP8 (vascular remodelling and angiogenesis genes, FDR = 2.77 × 10-5). We also discovered that hypertrophy lncRNA MYREM shows a specific myonuclear expression pattern in vivo. Our multi-layered analyses established that single-cell-associated ncRNA are identifiable from bulk muscle transcriptomic data and that hypertrophy-linked ncRNA genes mediate their association with muscle growth via multiple cell types and a set of interacting pathways.

Precision of the GE Lunar Total Body-Less Head Scan for the Measurement of Three-Compartment Body Composition in Athletes

INTRODUCTION

Dual energy X-ray absorptiometry (DXA) is widely used for the assessment of lean mass (LM), fat mass (FM) and bone mineral content (BMC). When observing standardised protocols, DXA has a high level of precision for the assessment of total body composition, including the head region. However, including the head region may have limited relevance in athletes and can be problematic when positioning taller athletes who exceed scan boundaries. This study investigated the precision of a new total-body-less-head (TBLH) DXA scan for three-compartment body composition measurement in athletes, with outcomes compared to the standard total-body DXA scan.

METHODS

Precision errors were calculated from two consecutive scans with re-positioning (Lunar iDXA, GE Healthcare, Madison, WI), in male and female athletes from a range of sports. TBLH precision was determined from repeat scans in 95 athletes (male n = 55; female n = 40; age: 26.0 ± 8.5 y; body mass: 81.2 ± 20.5 kg; stature: 1.77 ± 0.11 m), and standard total-body scan precision was derived from a sub-sample of 58 athletes (male n = 19; female n = 39; age: 27.6 ± 9.9 y; body mass: 69.6 ± 14.8 kg; stature: 1.72 ± 0.94 m). Data from the sub-sample were also used to compare precision error and 3-compartment body composition outcomes between the standard total-body scan and the TBLH scan.

RESULTS

TBLH precision errors [root mean squared-standard deviation, RMS-SD (coefficient of variation, %CV)] were bone mineral content (BMC): 15.6 g (0.5%), lean mass (LM): 254.3 g (0.4%) and fat mass (FM): 199.4 g (1.3%). These outcomes compared favourably to the precision errors derived from the standard total-body scan [BMC: 12.4 g (0.4%), LM: 202.2 g (0.4%), and FM: 160.8 g (1.1%)]. The TBLH scan resulted in lower BMC (-19.5%), LM (-6.6%), and FM (-4.5%) compared to the total-body scan (BMC: 2,308 vs. 2,865 g; LM: 46,954 vs. 50,276 g; FM: 15,183 vs. 15,888 g, all p<0.005). ConclusionThe TBLH scan demonstrates high in-vivo precision comparable to that of the standard total-body scan in a heterogeneous cohort of athletes. Given the impact of head exclusion on total body composition outcomes, TBLH scans should not be used interchangeably with the standard total-body scan.

Simple anthropometry-based calculations to monitor body composition in athletes: Scoping review and reference values

BACKGROUND

Kinanthropometry offers to exercise and health professionals a standardized procedure of acquiring surface anatomical measurements that might be used to track changes in body composition.

AIM

To describe simple anthropometric indices to monitor body composition changes in amateur and elite athletes, and to provide reference values during the competition phase.

METHODS

A search of articles indexed in PubMed/MEDLINE, ScienceDirect, Cochrane, and SciELO databases using the string body composition AND (anthropometric OR skinfolds OR circumferences OR girth OR estimation equation) AND "body fat". Inclusion criteria were: quantitative and/or qualitative research published between 2009 and 2020, written in English or Spanish, reporting simple anthropometric indices that included skinfolds, girths, or basic measures in amateur and elite athletes.

RESULTS

A total of 51 studies (Price's index = 66.4%) met all the inclusion criteria and were included in this scoping review. Contrary to the frequent practice, the use of a regression equation might not be accurate to evaluate body composition. To avoid this, anthropometrists should base their analysis on the absolute values of the sum of skinfolds (∑S) and related variables, such as skinfold-corrected girths and lean mass index. While not definitive, because further research is required, the practical recommendations and updated reference values in competition phase provided by this review would contribute to the accurate identification of body composition changes.

CONCLUSIONS

∑S and lean mass index have been shown to be valid for monitoring changes in fat mass and fat-free mass, respectively. More research is needed to derive the lean mass index-specific coefficient for each sports population.

Piloting a training program in computed tomography (CT) skeletal muscle assessment for Registered Dietitians

BACKGROUND

Consensus definitions for disease-associated malnutrition and sarcopenia include reduced skeletal muscle mass as a diagnostic criterion. There is a need to develop and validate techniques to assess skeletal muscle in clinical practice. Skeletal muscle mass can be precisely quantified from computed tomography (CT) images. This pilot study aimed to train Registered Dietitians (RD) to complete precise skeletal muscle measurements using CT.

METHODS

Purposive sampling identified RDs employed in clinical areas where CT scans are routinely performed. CT training included: 1) a 3-day training session focused on manual segmentation of skeletal muscle cross-sectional areas (cm² ) from abdominal CT images at the third lumber (L3) vertebra, using SliceOmatic® software, and 2) a precision assessment to quantify the intra- and inter-observer precision error of repeated skeletal muscle measurements (30 images in duplicate). Precision error is reported as the root mean standard deviation (cm² ) and % coefficient of variation (%CV), our primary performance indicator was defined as a precision error <2%.

RESULTS

Five RDs completed CT training. RDs were from three clinical areas (cancer care (N=1), surgery (N=2), and critical care (N=1). RDs precision error was low and below the minimal acceptable error of <2%; intra-observer error was ≤1.8 cm² (range 0.8 - 1.8 cm² ) or ≤1.5% (range 0.8 - 1.5%) and inter-observer error was 1.2 cm² or 1.1%.

CONCLUSION

RDs can be trained to perform precise CT skeletal muscle measurements. Increasing capacity to assess skeletal muscle is a first step toward developing this technique for use in clinical practice.

CLINICAL RELEVANCE STATEMENT

There is significant interest from both researchers and clinicians to undertake the measurement of skeletal muscle. Reduced skeletal muscle mass places individuals at risk of experiencing adverse outcomes and is a diagnostic criterion for disease-associated malnutrition and sarcopenia. In this study we piloted a training program in computed tomography (CT)-skeletal muscle assessments for RDs, and demonstrated after completion of the program RDs were able to perform CT skeletal muscle measurements with high precision. The addition of new tools to the comprehensive nutrition assessment tool box may benefit clinical practice in multiple ways including improved identification of patients with reduced skeletal muscle mass, individualization of interventions, and monitoring effectiveness of interventions over time. Other clinicians may also benefit from knowing about their patients' skeletal muscle mass to help identify risk and make treatment decisions. This article is protected by copyright. All rights reserved.

Precision of Lunar Dual-energy X-ray Absorptiometry (iDXA) in measuring body composition among colorectal cancer patients and healthy subjects

BACKGROUND & AIMS

High quality and precise methods are needed when monitoring changes in body composition among colorectal cancer (CRC) patients and healthy subjects. The aim of this study was to estimate precision of the Dual-energy X-ray absorptiometry (Lunar iDXA, GE Healthcare software enCORE version 16) in measuring body composition in CRC patients and healthy subjects.

METHODS

Precision error of iDXA in measuring body composition was investigated in the current study. Thirty CRC patients and 30 healthy subjects, including both men and women underwent two consecutive whole-body DXA scan with repositioning. Precision estimates of visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) in the abdominal region, and total fat mass (FM), fat-free mass (FFM), lean mass (LM), bone mineral density (BMD) and bone mineral content (BMC) were calculated.

RESULTS

Precision error expressed as coefficient of variation (% CV) of VAT and SAT were estimated to be 3.56% and 3.28% among CRC patients, and 5.30% and 3.46% among healthy subjects. Estimated precision errors for body masses in the total region ranged between 0.49-1.01% and 0.40-0.88% in CRC patients and healthy subjects, respectively. Least significant change (LSC) in VAT mass, SAT mass, FM and LM were 140.9 g, 121.4 g, 637.0 g and 701.0 g, respectively, among CRC patients. Among healthy subjects the LSC in VAT, SAT, FM and LM were 80.93 g, 98.90 g, 484.0 g and 618.0 g, respectively. Only minor and non-significant differences between the two consecutive measurements for each body compartment were observed within both populations, and we found no systematic bias in the distribution of the differences.

CONCLUSION

The Lunar iDXA demonstrated high precision in body composition measurements among both CRC patients and healthy subjects. Hence, iDXA is a useful tool in clinical following-up and interventions targeted towards changes in body composition.

Precision and Effects of a Small Meal on DXA-Derived Visceral Adipose Tissue, Appendicular Lean Mass, and Other Body Composition Estimates In Nonobese Elderly Men

BACKGROUND

Information on precision errors and the least significant change (LSC) of dual energy X-ray absorptiometry (DXA)-derived body composition estimates is scarce, particularly for the appendicular lean mass (ALM) and appendicular lean mass index (ALMI). Overnight fasting is recommended for body composition measurements but has not been well tolerated by some elderly patients. This study aimed to establish precision errors and LSC values of body composition estimates in all regions-including visceral adipose tissue (VAT) and ALM-and the ALMI to assess the effect of a small meal on body composition and to estimate the changes it incurred.

METHODOLOGY

Our institutional review board approved the study protocol. Altogether, 36 non-obese men aged ≥60 years, having given written informed consent, underwent body composition assessment after fasting overnight except for water. They underwent DXA scans three times, each time with repositioning (to simulate the clinical setting), the last after consuming a standardized meal (210-250 g and 200 cc of water).

RESULTS

Precision errors and LSC values of DXA-derived body composition estimates in these elderly men tended to be higher than those in reports on younger subjects. Coefficients of variation (CVs (%)) of total bone mass (Tb.BMC) and total lean mass (Tb.LM) were <1%, whereas those of total fat mass (Tb.FM) and total %fat mass (Tb.%FM) were <2%, with LSCs of 45.8 g, 706.52 g, 731.4 g, and 1.15%, respectively. The CVs (LSC) of VAT, ALM, and ALMI were 8.9% (150.65 g), 0.93% (501 g), and 0.94% (0.19), respectively. After meal consumption, the mean changes in Tb.FM, Tb.BMC, and Tb.LM were -100, -8.2, and 440 g, respectively.

CONCLUSIONS

Effects of a small meal on most parameters were trivial, including those for VAT, ALM, and ALMI, where changes were not statistically significant. None exceeded the LSC of ALM and ALMI, suggesting that a small meal is allowable before these measurements.

Use of bioelectrical impedance analysis to monitor changes in fat-free mass during recovery from colorectal cancer- a validation study

BACKGROUND & AIMS

Although previous research show high correlation between fat-free mass (FFM) measured by bioelectrical impedance analysis (BIA) and dual-energy X-ray absorptiometry (DXA), the validity of BIA to track longitudinal changes in FFM is uncertain. Thus, the aim of this study was to validate the ability of BIA to assess changes in FFM during 6 months of recovery from non-metastatic colorectal cancer (CRC).

METHODS

A total of 136 women and men (50-80 years) with stage I-III CRC and a wide range of baseline FFM (35.7-73.5 kg) were included in the study. Body composition was measured at study baseline within 2-9 months of surgery and again 6 months later. Whole-body BIA FFM estimates (FFM_BIA) were calculated using three different equations (manufacturer's, Schols' and Gray's) before comparison to FFM estimates obtained by DXA (FFM_DXA).

RESULTS

Correlation between changes in FFM_BIA and FFM_DXA was intermediate regardless of equation (r ≈ 0.6). The difference in change of FFM_BIA was significant compared to FFM_DXA, using all three equations and BIA overestimated both loss and gain. However, BIA showed 100% sensitivity and about 90% specificity to identify individuals with ≥5% loss in FFM, using all three equations. Sensitivity of FFM_BIA to detect a smaller loss of FFM (60-76%) or a gain in FFM of ≥5% (33-62%) was poor.

CONCLUSION

In a well-nourished population of non-metastatic CRC patients, a single-frequency whole-body BIA device yielded imprecise data on changes in FFM, regardless of equation. BIA is thus not a valid option for quantifying changes in FFM in individuals. However, BIA could be used to identify patients with loss in FFM ≥5% in this population. The validity of BIA to monitor changes in FFM warrants further investigation before implementation in clinical praxis.

Short-Term Precision Error of Body Composition Assessment Methods in Resistance-Trained Male 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.

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 anthropometric characteristics in professional Rugby League players: Is there too much emphasis on the pre-season period?

Rugby League is a team sport requiring players to experience large impact collisions, thus requiring high amounts of muscle mass. Many players (academy and senior) strive to increase muscle mass during the pre-season, however, quantification of changes during this period have not been thoroughly investigated. We therefore assessed changes in body-composition using Dual X-Ray Absorptiometry (DXA) in eleven academy players over three successive pre-seasons and ninety-three senior players from four different European Super League clubs prior to, and at the end of, a pre-season training period. There was no meaningful change in lean mass of the academy players during any of the pre-season periods (year 1 = 72.3 ± 7.1-73.2 ± 7.2kg; ES 0.05, year 2 = 74.4 ± 6.9-75.5 ± 6.9kg; ES 0.07, year 3 = 75.9 ± 6.7-76.8 ± 6.6kg; ES 0.06) with small changes only occurring over the three-year study period (72.3-75.9kg; ES = 0.22). Senior players showed trivial changes in all characteristics during the pre-season period (total mass = 95.1-95.0kg; ES -0.01, lean mass = 74.6-75.1kg; ES 0.07, fat mass = 13.6-12.9kg; ES -0.17, body fat percentage = 14.8-14.1%; ES -0.19). These data suggest that academy players need time to develop towards profiles congruent with senior players. Moreover, once players reach senior level, body-composition changes are trivial during the pre-season and therefore teams may need to individualise training for players striving to gain muscle mass by reducing other training loads.

Cardiovascular Health of Retired Field-Based Athletes: A Systematic Review and Meta-analysis

BACKGROUND

Retirement from elite sport participation is associated with decreased physical activity, depression, obesity, and ischemic heart disease. Although engagement in physical activity through sport is recognized as cardioprotective, an estimated one-quarter of deaths in American football players are associated with cardiovascular disease (CVD), predominately in players classified as obese.

PURPOSE

To systematically investigate the cardiovascular health profile of retired field-based athletes.

STUDY DESIGN

Systematic review; Level of evidence, 4.

METHODS

This review was conducted and reported in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines and preregistered with PROSPERO. Four databases (PubMed, CINAHL, Embase, and Web of Science) were systematically searched from inception to October 2018 using MeSH terms and keywords. Inclusion criteria were retired field-based athletes, age >18 years, and at least 1 CVD risk factor according to the European Society of Cardiology and the American Heart Association. Review articles were not included. Control groups were not required for inclusion, but when available, an analysis was included. Eligible articles were extracted using Covidence. Methodological quality was assessed independently by 2 reviewers using the AXIS tool. The accuracy of individual study estimates was analyzed using a random-effects meta-analysis.

RESULTS

This review yielded 13 studies. A total of 4350 male retired field-based athletes from 2 sports (football and soccer; age range, 42.2-66 years) were included. Eight studies compared retired athletes with control groups. Retired athletes had elevated systolic blood pressure in 4 of 6 studies; approximately 50% of studies found greater high-density lipoprotein, approximately 80% found lower triglyceride levels, and all studies found greater low-density lipoprotein for retired athletes compared with controls. The prevalence and severity of coronary artery calcium and carotid artery plaque were similar to controls. Retired linemen had double the prevalence of cardiometabolic syndrome compared with nonlinemen.

CONCLUSION

The overall findings were mixed. Inconsistencies in the reporting of CVD risk factors and methodological biases reduced the study quality. Retired athletes had a comparable CVD risk profile with the general population. Retired athletes with an elevated body mass index had an increased prevalence and severity of risk factors. Significant gaps remain in understanding the long-term cardiovascular effects of elite athleticism.

The LunHab project: Muscle and bone alterations in male participants following a 10 day lunar habitat simulation

NEW FINDINGS

What is the central question of this study? It is well established that muscle and bone atrophy in conditions of inactivity or unloading, but there is little information regarding the effect of a hypoxic environment on the time course of these deconditioning physiological systems. What is the main finding and its importance? The main finding is that a horizontal 10 day bed rest in normoxia results in typical muscle atrophy, which is not aggravated by hypoxia. Changes in bone mineral content or in metabolism were not detected after either normoxic or hypoxic bed rest.

ABSTRACT

Musculoskeletal atrophy constitutes a typical adaptation to inactivity and unloading of weightbearing bones. The reduced-gravity environment in future Moon and Mars habitats is likely to be hypobaric hypoxic, and there is an urgent need to understand the effect of hypoxia on the process of inactivity-induced musculoskeletal atrophy. This was the principal aim of the present study. Eleven males participated in three 10 day interventions: (i) hypoxic ambulatory confinement; (ii) hypoxic bed rest; and (iii) normoxic bed rest. Before and after the interventions, the muscle strength (isometric maximal voluntary contraction), mass (lean mass, by dual-energy X-ray absorptiometry), cross-sectional area and total bone mineral content (determined with peripheral quantitative computed tomography) of the participants were measured. Blood and urine samples were collected before and on the 1st, 4th and 10th day of the intervention and analysed for biomarkers of bone resorption and formation. There was a significant reduction in thigh and lower leg muscle mass and volume after both normoxic and hypoxic bed rests. Muscle strength loss was proportionately greater than the loss in muscle mass for both thigh and lower leg. There was no indication of bone loss. Furthermore, the biomarkers of resorption and formation were not affected by any of the interventions. There was no significant effect of hypoxia on the musculoskeletal variables. Short-term normoxic (10 day) bed rest resulted in muscular deconditioning, but not in the loss of bone mineral content or changes in bone metabolism. Hypoxia did not modify these results.

Effect of Chemotherapy on Dual-Energy X-ray Absorptiometry (DXA) Body Composition Precision Error in Head and Neck Cancer Patients

BACKGROUND

Precision error in dual-energy X-ray absorptiometry (DXA) is defined as difference in results due to instrumental and technical factors given no biologic change. The aim of this study is to compare precision error in DXA body composition scans in head and neck cancer patients before and 2 months after chemotherapy.

METHODOLOGY

A total of 34 male head and neck cancer patients with normal body mass index (BMI) were prospectively enrolled and all patients received 2 consecutive DXA scans both before and after 2 months of chemotherapy for a total of 4 scans. The precision error of 3 DXA body composition values (lean mass, fat mass, and bone mineral content) was calculated for total body and 5 body regions (arms, legs, trunk, android, and gynoid). Precision errors before and after treatment were compared using generalized estimating equation model.

RESULTS

There was no significant change in precision error for the DXA total body composition values following chemotherapy; lean mass (0.33%-0.40%, p = 0.179), total fat mass (1.39%-1.70%, p = 0.259) and total bone mineral content (0.42%-0.56%, p = 0.243). However, there were significant changes in regional precision error; trunk lean mass (1.19%-1.77%, p = 0.014) and android fat mass (2.17%-3.72%, p = 0.046).

CONCLUSIONS

For head and neck cancer patients, precision error of DXA total body composition values did not change significantly following chemotherapy; however, there were significant changes in fat mass in the android and lean mass in the trunk. Caution should be exercised when interpreting longitudinal DXA body composition data in those body parts.

Longitudinal Changes in Body Composition Assessed Using DXA and Surface Anthropometry Show Good Agreement in Elite Rugby Union Athletes

Rugby union athletes have divergent body composition based on the demands of their on-field playing position and ethnicity. With an established association between physique traits and positional requirements, body composition assessment is routinely undertaken. Surface anthropometry and dual-energy X-ray absorptiometry (DXA) are the most common assessment techniques used, often undertaken synchronously. This study aims to investigate the association between DXA and surface anthropometry when assessing longitudinal changes in fat-free mass (FFM) and fat mass (FM) in rugby union athletes. Thirty-nine elite male rugby union athletes (age: 25.7 ± 3.1 years, stature: 187.6 ± 7.7 cm, and mass: 104.1 ± 12.2 kg) underwent assessment via DXA and surface anthropometry multiple times over three consecutive international seasons. Changes in the lean mass index, an empirical measure to assess proportional variation in FFM, showed large agreement with changes in DXA FFM (r = .54, standard error of the estimate = 1.5%, p < .001); the strength of association was stronger among forwards (r = .63) compared with backs (r = .38). Changes in the sum of seven skinfolds showed very large agreement with changes in DXA FM (r = .73, standard error of the estimate = 5.8%, p < .001), with meaningful differences observed regardless of ethnicity (Whites: r = .75 and Polynesians: r = .62). The lean mass index and sum of seven skinfolds were able to predict the direction of change in FFM and FM 86% and 91% of the time, respectively, when DXA change was >1 kg. Surface anthropometry measures provide a robust indication of the direction of change in FFM and FM, although caution may need to be applied when interpreting magnitude of change, particularly with FM.

Same-Day Vs Consecutive-Day Precision Error of Dual-Energy X-Ray Absorptiometry for Interpreting Body Composition Change in Resistance-Trained Athletes

The application of dual-energy X-ray absorptiometry (DXA) in sport science settings is gaining popularity due to its ability to assess body composition. The International Society for Clinical Densitometry (ISCD) recommends application of the least significant change (LSC) to interpret meaningful and true change. This is calculated from same-day consecutive scans, thus accounting for technical error. However, this approach does not capture biological variation, which is pertinent when interpreting longitudinal measurements, and could be captured from consecutive-day scans. The aims of this study were to investigate the impact short-term biological variation has on LSC measures, and establish if there is a difference in precision based on gender in a resistance-trained population. Twenty-one resistance-trained athletes (age: 30.6 ± 8.2 yr; stature: 174.2 ± 7.2 cm; mass: 74.3 ± 11.6 kg) with at least 12 mo consistent resistance training experience, underwent 2 consecutive DXA scans on 1 d of testing, and a third scan the day before or after. ISCD-recommended techniques were used to calculate same-day and consecutive-day precision error and LSC values. There was high association between whole body (R² = 0.98-1.00) and regional measures (R² = 0.95-0.99) for same-day (R² = 0.98-1.00), and consecutive-day (R² = 0.95-0.98) measurements. The consecutive-day precision error, in comparison to same-day precision error, was significantly different (p < 0.05), and almost twice as large for fat mass (1261 g vs 660 g), and over 3 times as large for lean mass (2083 g vs 617 g), yet still remained within the ISCD minimum acceptable limits for DXA precision error. No whole body differences in precision error were observed based on gender. When tracking changes in body composition, the use of precision error and LSC values calculated from consecutive-day analysis is advocated, given this takes into account both technical error and biological variation, thus providing a more accurate indication of true and meaningful change.

Cross Calibration of the GE Prodigy and iDXA for the Measurement of Total and Regional Body Composition in Adults

Dual-energy X-ray absorptiometry (DXA) body composition measurements are widely performed in both clinical and research settings, and enable the rapid and noninvasive estimation of total and regional fat and lean mass tissues. DXA upgrading can occur during longitudinal monitoring or study; therefore, cross calibration of old and new absorptiometers is required. We compared soft tissue estimations from the GE Prodigy (GE Healthcare, Madison, WI) with the more recent iDXA (GE Healthcare) and developed translational equations to enable Prodigy values to be converted to iDXA values. Eighty-three males and females aged 20.1-63.3 yr and with a body mass index range of 17.0-34.4 kg/m² were recruited for the study. Fifty-nine participants (41 females and 18 males) comprised the cross-calibration group and 24 (14 females and 10 males) comprised the validation group. Total body Prodigy and iDXA scans were performed on each subject within 24 h. Predictive equations for total and regional soft tissue parameters were derived from linear regression of the data. Measures of lean and fat tissues were highly correlated (R² = 0.95-0.99), but significant differences and variability between machines were identified. Bland-Altman analysis revealed significant biases for most measures, particularly for arm, android, and gynoid fat mass (12.3%-22.7%). The derived translational equations reduced biases and differences for most parameters, although limits of agreement exceeded iDXA least significant change. In conclusion, variability in soft tissue estimates between the Prodigy and iDXA were detected, supporting the need for translational equations in longitudinal monitoring. The derived equations are suitable for group analysis but not individual analysis.

Interpretation of Dual-Energy X-Ray Absorptiometry-Derived Body Composition Change in Athletes: A Review and Recommendations for Best Practice

Dual-energy X-ray absorptiometry (DXA) is a medical imaging device which has become the method of choice for the measurement of body composition in athletes. The objectives of this review were to evaluate published longitudinal DXA body composition studies in athletic populations for interpretation of "meaningful" change, and to propose a best practice measurement protocol. An online search of PubMed and CINAHL via EBSCO Host and Web of Science enabled the identification of studies published until November 2016. Those that met the inclusion criteria were reviewed independently by 2 authors according to their methodological quality and interpretation of body composition change. Twenty-five studies published between 1996 and November 2016 were reviewed (male athletes: 13, female athletes: 3, mixed: 9) and sample sizes ranged from n = 1 to 212. The same number of eligible studies was published between 2013 and 2016, as over the 16 yr prior (between 1996 and 2012). Seven did not include precision error, and fewer than half provided athlete-specific precision error. There were shortfalls in the sample sizes on which precision estimates were based and inconsistencies in the level of pre-scan standardization, with some reporting full standardization protocols and others reporting only single (e.g., overnight fast) or no control measures. There is a need for standardized practice and reporting in athletic populations for the longitudinal measurement of body composition using DXA. Based on this review and those of others, plus the official position of the International Society for Clinical Densitometry, our recommendations and protocol are proposed as a guide to support best practice.

Effect of Hand Positioning on DXA Total and Regional Bone and Body Composition Parameters, Precision Error, and Least Significant Change

Dual-energy X-ray absorptiometry (DXA) body composition measurements are performed in both clinical and research settings for estimations of total and regional fat mass, lean tissue mass, and bone mineral content. Subject positioning influences precision and positioning instructions vary between manufacturers. The aim of the study was to determine the effect of hand position and scan mode on regional and total body bone and body composition parameters and determine protocol-specific body composition precision errors. Thirty-eight healthy subjects (men; mean age: 27.1 ± 12.1 yr) received 4 consecutive total body GE-Lunar iDXA (enCORE v 15.0) scans with re-positioning, and scan mode was dependent on body size. Twenty-three subjects received scans in standard mode and 15 received scans in thick scan modes. Two scans per subject were conducted with subject hands prone and 2 with hands mid-prone. The precision error (root mean squared standard deviation; percentage coefficient of variation) and least significant change for each protocol were determined using the International Society for Clinical Densitometry calculator. Hands placed in the mid-prone position increased arm bone mineral density (BMD) (standard mode: 0.185 g*cm^-2, thick mode: 0.265 g*cm^-2; p < 0.05), total body BMD (standard mode: 0.051 g*cm^-2, thick mode: 0.069 g*cm^-2; p < 0.001), and total body BMD Z-score (standard mode: 0.5. thick mode: 0.7; p < 0.001). This was due to reductions in bone area and bone mineral content. In standard mode, hands mid-prone reduced fat mass (0.05 kg, p < 0.05) and increased lean mass (0.11 kg, p < 0.05). There were no differences in body composition for thick mode scans. Hands mid-prone reduced lean mass precision error at the arms, trunk, and total body (p < 0.01). DXA clinical and research centers are advised to maintain consistency in their hand positioning and scan mode protocols, and consideration should be given to the hand positioning used for reference data. As a best practice recommendation, published DXA-based studies and reports for clinic-based total body assessments should ensure that subject positioning is fully described.

Six-year body composition change in male elite senior rugby league players

This study investigated the change in body composition and bone mineral content (BMC) of senior rugby league (RL) players between 2008 and 2014. Twelve male professional RL players (age, 24.6 ± 4.0 years; stature, 183.4 ± 8.4 cm) received a dual-energy X-ray absorptiometry scan during preseason in 2008 and 2014. Between 2008 and 2014, very likely increases in leg lean mass (LM), total trunk and leg BMC, and a likely increase in arm BMC and possible increases in body mass (BM), total and trunk fat mass (FM), and total, trunk and arm LM were observed. Unlikely decreases and unclear changes in leg and arm FM were also found. Large negative correlations were observed between age and BM (r = -0.72), LM (r = -0.70), FM (r = -0.61) and BMC (r = -0.84) change. Three participants (19.1 ± 1.6 years) increased LM by 7.0-9.3 kg. Younger players had the largest increases in LM during this period, although an older player (30-year old) still increased LM. Differences in body composition change were also observed for participants of the same age, thus contextual factors should be considered. This study demonstrates the individuality of body composition changes in senior professional rugby players, while considering the potential change in young athletes.

Three-Compartment Body Composition Changes in Professional Rugby Union Players Over One Competitive Season: A Team and Individualized Approach

The purpose of this study was to investigate the longitudinal body composition of professional rugby union players over one competitive season. Given the potential for variability in changes, and as the first to do so, we conducted individual analysis in addition to analysis of group means. Thirty-five professional rugby union players from one English Premiership team (forwards: n = 20, age: 25.5 ± 4.7 yr; backs: n = 15, age: 26.1 ± 4.5 yr) received one total-body dual-energy X-ray absorptiometry scan at preseason (August), midseason (January), and endseason (May), enabling quantification of body mass, total and regional fat mass, lean mass, percentage tissue fat mass (%TFM), and bone mineral content (BMC). Individual analysis was conducted by applying least significant change (LSC), derived from our previously published precision data and in accordance with International Society for Clinical Densitometry guidelines. Mean body mass remained stable throughout the season (p > 0.05), but total fat mass and %TFM increased from pre- to endseason, and from mid- to endseason (p <0.05). There were also statistically significant increases in total-body BMC across the season (p <0.05). In both groups, there was a loss of lean mass between mid- and endseason (p <0.018). Individual evaluation using LSC and Bland-Altman analysis revealed a meaningful loss of lean mass in 17 players and a gain of fat mass in 21 players from pre- to endseason. Twelve players had no change and there were no differences by playing position. There were individual gains or no net changes in BMC across the season for 10 and 24 players, respectively. This study highlights the advantages of an individualized approach to dual-energy X-ray absorptiometry body composition monitoring and this can be achieved through application of derived LSC.