scholarly journals Anthropometric prediction of DXA-measured body composition in female team handball players

PeerJ ◽  
2018 ◽  
Vol 6 ◽  
pp. e5913 ◽  
Author(s):  
Valentina Cavedon ◽  
Carlo Zancanaro ◽  
Chiara Milanese
Keyword(s):  
Body Composition ◽  
Body Fat ◽  
Female Athletes ◽  
Linear Regression Analysis ◽  
Fat Free Mass ◽  
Whole Body ◽  
Tissue Mass ◽  
Predictive Equations ◽  
Team Handball ◽  
Total Body

Background The relevance of body composition (BC) to performance in sport has long been appreciated with special concern on the total and regional proportion of fat and muscle. Dual-energy X-ray absorptiometry (DXA) is able to accurately measure BC, but it may not be easily available in practice; anthropometry has long been used as a simple and inexpensive field method to objectively assess BC. The aim of this study was twofold: first, to develop and validate a sport-specific anthropometric predictive equation for total body fat mass (FM) and lean mass components in female handball players to be used in the sport setting; second, to cross-validate in female team handball players several independently developed, predictive equations for BC in female athletes. Methods A total of 85 female team handball players (30 wings, 31 backs, 14 pivots, 10 goalkeepers) of different competitive levels underwent anthropometry and a whole-body DXA scan. Multiple linear regression analysis was used to develop predictive equations in a derivation sample (n = 60) of randomly selected players using demographic and anthropometric variables. The developed equations were used to predict DXA outcomes in an independent validation sample (n = 25). Results Statistically significant (P < 0.001) models were developed for total body FM (adjusted R2 = 0.943, standard error of the estimate, SEE = 1,379 g), percentage FM (adjusted R2 = 0.877, SEE = 2.00%), fat-free soft tissue mass (FFSTM) (adjusted R2 = 0.834, SEE = 2,412 g), fat-free mass (FFSTM + bone mineral content; adjusted R2 = 0.829, SEE = 2,579 g). All models were robust to collinearity. Each developed equation was successfully validated in the remaining 25 players using correlation analysis, mean signed difference, t-test, and Bland–Altman plot. The whole dataset of team handball players (n = 85) was used to cross-validate several predictive equations independently developed by others in female athletes. Equations significantly (P < 0.001 for all; t-test) over- or underestimated the corresponding DXA measurements. Discussion It is concluded that in team female handball players the anthropometric equations presented herein are able to estimate body fat and FFSTM with accuracy. Several BC predictive anthropometric equations developed in different female athletic populations revealed inaccurate when tested in team handball players. These results should be of use for coaches, physical trainers, and nutritionists when evaluating the physical status of female team handball players.

scholarly journals Stav antropometrických parametrov a telesného zloženia u detí mladšieho školského veku

2017 ◽  
Vol 11 (2) ◽  
pp. 15-27
Author(s):  
Tomáš Hadžega ◽  
Václav Bunc
Keyword(s):  
Body Composition ◽  
Body Weight ◽  
Body Fat ◽  
Body Height ◽  
The Body ◽  
Fat Free Mass ◽  
Whole Body ◽  
School Age ◽  
Total Body ◽  
Frequency Apparatus

The aim of our observation was to measure selected anthropometric characteristics and to analyze actual body composition in children of younger school age from elementary schools in Prague. The group consisted of a total of 222 probands, boys (n-117) and girls (n-105) aged 8–11 years (average boys age = 9.0 ± 1.0 years, body height = 139.9 ± 8.6 cm, body weight = 32 ± 7.5 kg, BMI = 16.3 ± 2.4 kg.m–2). Average age girls = 8.9 ± 0.9 years, body height = 137.3 ± 8.8 cm, body weight = 30.5 ± 7.3 kg, BMI = 15.9 ± 2.4 kg.m–2). The BIA 2000 M multi-frequency apparatus (whole-body bioimpedance analysis) was used to analyze the body composition. Children of younger school age showed higher TBW values – total body water (boys 65.5 ± 6.0%, girls 66.6 ± 6.5%), low body fat (boys 16.1 ± 2.4%, girls 16.5 ± 2.9%) and higher ECM/BCM coefficients (boys 1.0 ± 0.13, girls 1.02 ± 0.11). The authors draws, attention to the importance of monitoring other body composition parameters. The percentage of fat-free mass (FFM) and the share of segmental distribution of body fat and muscle mass on individual parts of the human body.

Total Body Potassium and Body Fat Estimation in Relationship to Height, Sex, Age, Malnutrition and Obesity

1975 ◽  
Vol 48 (5) ◽  
pp. 431-440 ◽  
Author(s):  
C. J. Edmonds ◽  
B. M. Jasani ◽  
T. Smith
Keyword(s):  
Body Weight ◽  
Food Intake ◽  
Body Fat ◽  
Fat Free Mass ◽  
Whole Body ◽  
Regression Equations ◽  
Total Body Potassium ◽  
Normal Individuals ◽  
Males And Females ◽  
Total Body

1. Total body potassium was estimated by 40K measurement with a high-sensitivity whole-body counter in normal individuals over a wide age range and in patients who were obese or were grossly wasted as a result of various conditions which restricted food intake. 2. Potassium concentration (mmol/kg body weight) fell with increasing age over 30 years in both normal males and females, but when individuals of different age groups were matched for height, a significant fall in total body potassium with increasing age was observed only in males. Total body potassium of females was about 75% that of males of similar height when young, the sex difference decreasing with ageing. In the normal population, total body potassium was significantly correlated with height and with weight; regression equations for various relationships are given. 3. Fat-free mass was estimated from total body potassium, values of 65 and 56 mmol of potassium/kg fat-free mass being used for males and females respectively. Body fat estimated by this method correlated well with skinfold measurements over a wide range of body weight but in malnourished individuals having inadequate food intake there was considerable discrepancy and present formulae for estimating fat-free mass from total body potassium appear unsatisfactory in malnutrition. Considerable differences between expected and observed values of total body potassium were found in muscular individuals and in normal individuals who were thin but whose body weight was relatively constant. 4. The patients with malnutrition were low both in body fat as estimated by skinfold thickness and in total body potassium estimated on the basis of height. Plasma potassium was, however, normal and potassium supplements did not increase the total body potassium. 5. Total body potassium of obese individuals was not significantly different from that of normal weight individuals on the basis of height. Total body potassium fell on weight reduction with a very low energy diet of 1260 kJ (300 kcal.) daily but changed little with a 3300 kJ (800 kcal.) diet over several months' observation. 6. For overweight, obese individuals, total body potassium was best predicted from the individual's height. For those whose body weight was less than expected, the use of weight gave the best prediction but the error was considerable when the weight deviation was large.

The effects of lipid location on non-invasive estimates of body composition using EM-SCAN technology

2002 ◽  
Vol 205 (19) ◽  
pp. 3101-3105
Author(s):  
Edward T. Unangst ◽  
Lance A. Merkley
Keyword(s):  
Body Composition ◽  
Body Fat ◽  
Fat Free Mass ◽  
Estimation Accuracy ◽  
Non Invasive ◽  
Electromagnetic Scanning ◽  
Lipid Mass ◽  
Total Body ◽  
Lipid Control ◽  
Scanning Em

SUMMARY We evaluated the effect of lipid location on body-composition estimation accuracy using electromagnetic scanning (EM-SCAN), a non-invasive [total body electrical conductivity (TOBEC)] method. Molds were constructed that simulated a `general' small mammal, either 93% lean/7% lipid (control) or 82% lean/18%lipid (lipid-location groups). In the 18% lipid molds, we varied the location of the fat; simulating all the fat in the head, tail or midsection or simulating homogenous distribution. Comparisons were made between the EM-SCAN output of each lipid-location group, and multiple-regression techniques were performed to derive body-composition estimation equations for both lipid mass(ML) and fat-free mass (MFF). Device output varied significantly for all lipid-location groups even though all groups contained 18% body fat, showing a lipid-location effect on device output. Calibration equations derived for each lipid-location condition estimated both ML and MFF accurately,but an independent equation was required for each lipid-location condition. In situations where species significantly vary body fat content and location, for example during hibernation or reproductive periods, we suggest deriving a calibration equation that is more representative of the actual body composition to improve ML and MFFestimation accuracy using non-invasive EM-SCAN methods.

Influence of muscular development, obesity, and age on the fat-free mass of adults

1976 ◽  
Vol 41 (2) ◽  
pp. 223-229 ◽  
Author(s):  
J. Womersley ◽  
J. V. Durnin ◽  
K. Boddy ◽  
M. Mahaffy
Keyword(s):  
Body Fat ◽  
The Body ◽  
Fat Free Mass ◽  
Potassium Content ◽  
Whole Body ◽  
Obese Women ◽  
Men And Women ◽  
Muscular Development ◽  
Total Body ◽  
Water Measurement

Body fat and the fat-free mass (FFM) were estimated in 36 men and 43 women deliberately chosen to represent a variety of physical types; these were 1) young sedentary, 2) “muscular,” 3) younger obese, 4) older obese, and 5) older nonobese individuals of both sexes. The body fat and the FFM were estimated from measurements of body density (by total immersion in water, measurement being made of the residual volume of air present in the lungs at immersion) and from measurements of total body potassium (using a whole-body monitor to assess the natural 40K isotope present in the body). The muscular men and women and the younger obese men and women had a considerably greater FFM and thus had greater quantities of potassium than the corresponding sedentary groups. There were significantly different estimates of the FFM calculated from density and from total body K in three groups, the sedentary young men, the muscular, and the younger obese women. The density and the potassium content of the FFM appear to decline with obesity and aging. Muscular development is associated with a decrease in the density but an increase in the potassium content of the FFM.

scholarly journals Between-laboratory comparison of densitometry and bio-electrical impedance measurements

1994 ◽  
Vol 71 (3) ◽  
pp. 309-316 ◽  
Author(s):  
Paul Deurenberg ◽  
Klaas R. Westerterp ◽  
Erica J. M. Velthuis-Te Wierik
Keyword(s):  
Body Composition ◽  
Body Fat ◽  
Total Body Water ◽  
Electrical Impedance ◽  
Normal Weight ◽  
Body Water ◽  
Fat Free Mass ◽  
Lower Amount ◽  
Total Body ◽  
The Relationship

Body composition was measured in nine healthy, normal-weight, weight-stable subjects in three different research centres. In each centre the usual procedures for the measurements were followed. It revealed that the measurement procedures in the three centres were comparable. Body composition was measured in each centre between 09.00 and 13.00 hours after a light breakfast by densitometry (underwater weighing) and bio-electrical impedance. A single, total-body-water determination by D2O dilution was used as a reference value. Body fat determined by densitometry was significantly lower in one centre, which, however, could be completely explained by a lower body weight, probably due to water loss (the subjects refrained for a longer time from food and drinks before the measurements in that centre) and, thus, by violation of the assumptions of Siri's (1961) formula. Also, body impedance was slightly higher in that centre, indicating a lower amount of body water. Mean body fat from densitometry was also slightly lower in that centre compared with body fat determined by D2O dilution. Individual differences between body fat from densitometry and from total body water were relatively large, up to 7% body fat. The relationship between fat-free mass from densitometry and bio-electrical impedance was not different between the centres. It is concluded that differences in the relationship between body composition and bio-electrical impedance, as reported in the literature, may be due to differences in standardization procedures and/or differences in reference population.

scholarly journals Changes in Body Composition and Its Relationship to Performance in Elite Female Track and Field Athletes Transitioning to the Senior Division

Sports ◽  
2020 ◽  
Vol 8 (9) ◽  
pp. 115
Author(s):  
Yuka Tsukahara ◽  
Suguru Torii ◽  
Fumihiro Yamasawa ◽  
Jun Iwamoto ◽  
Takanobu Otsuka ◽  
...  
Keyword(s):  
Body Composition ◽  
Female Athletes ◽  
International Association ◽  
Upper Extremities ◽  
Track And Field ◽  
Whole Body ◽  
Improve Performance ◽  
X Ray ◽  
University Level ◽  
Total Body

Many elite female athletes struggle to maintain performance while transitioning from high school to university-level (senior) sports. This study explores factors of body composition that influenced performance in elite junior female track and field athletes transitioning to the senior division. Forty-two elite female track and field athletes, ranked among the top 100 in Japan, were enrolled in this study. Whole-body mode dual-energy X-ray absorptiometry scans were performed during the post-season of 2016 and 2017. Athletes’ performances were assessed using the International Association of Athletics Federation scoring system. Relationships between changes in performance and those in body composition were investigated. There were significant negative correlations between changes in performance and fat mass (FM), and percentage FM (FM%). This was seen in total body and lower extremities, and not in the trunk and upper extremities. In addition, there was a positive correlation between changes in performance and percentage lean mass (LM%). However, there were no correlations between changes in performance and LM and total mass. Elite female track and field athletes transitioning to senior division should decrease their FM and FM% and increase LM%, to sustain or improve performance. It is also more important to monitor changes in body composition than body mass.

Comparison of Methods for the Measurement of Body Composition in Overweight and Obese Brazilian Children and Adolescents before and after a Lifestyle Modification Program

2014 ◽  
Vol 66 (1) ◽  
pp. 26-30 ◽  
Author(s):  
Arthur Lyra ◽  
Alexandre José Bonfitto ◽  
Vera Lucia P. Barbosa ◽  
Ana Cristina Bezerra ◽  
Carlos Alberto Longui ◽  
...  
Keyword(s):  
Physical Activity ◽  
Body Composition ◽  
Children And Adolescents ◽  
Body Fat ◽  
Fat Free Mass ◽  
Positive Correlation ◽  
Short Period ◽  
Total Body Fat ◽  
Before And After ◽  
Total Body

Aim: To compare the body composition of overweight children and adolescents by bioelectrical impedance analysis (BIA) and dual-energy X-ray absorptiometry (DXA) before and after physical activity program. Methods: One hundred and eleven patients with mean age (SD) of 12 (1.9) participated in the study. We assessed the weight, height, waist circumference (WC), and body composition by DXA and BIA. Patients underwent a program of diet and physical activity (1 h 30 min/day, 3 times a week for 3 months) and were evaluated before and after this period. Results: Mean initial zBMI were 2.3 (0.5) and waist SDS 5.9 (1.8). Significant differences were observed when we compared the measurements taken by DXA and BIA, respectively: total body fat percentage (40 and 31.5) and fat-free mass (43.1 and 50.6 kg). Regarding the trunk fat by DXA, there was a positive correlation with the WC/height ratio (r = 0.65; p < 0.01). After the intervention period, we observed a reduction in the zBMI, waist SDS, and total body fat and increase of fat-free mass by DXA. BIA only detected reduction in fat. Conclusion: BIA underestimates the percentage of fat and overestimates fat-free mass in relation to DXA. There is positive correlation between trunk fat and the ratio WC/height. In addition, DXA detected changes in body composition induced by a short period of physical training, unlike BIA. © 2014 S. Karger AG, Basel

scholarly journals Stav antropometrických parametrů a tělesného složení u studentů Vojenského oboru UK FTVS v Praze

2015 ◽  
Vol 9 (2) ◽  
pp. 57-67 ◽  
Author(s):  
Ivana Kinkorová ◽  
Matěj Vrba
Keyword(s):  
Body Composition ◽  
Body Fat ◽  
The Body ◽  
Whole Body ◽  
Composition Analysis ◽  
Extracellular Water ◽  
Body Composition Analysis ◽  
Segmental Analysis ◽  
Total Body ◽  
General Physical

The aim of our study was the measurement of selected anthropometric variables, respectively determining somatotype, body composition analysis of students Military Department (MD) at UK FTVS in Prague and compared to similar studies. The group consisted of 22 probands, men ranging in age from 19–27 years (mean age = 22,9 ± 2,6 years, height = 179,9 ± 6,0 cm, weight = 76,8 ± 7,0 kg, BMI = 23,8 ± 1,5 kg.m–2). In terms of measured average somatotype (1,7 – 7,3 – 2,5), the students MD have very good preconditions for general physical fitness. We used BIA-Tanita MC 980 for the body composition analysis (whole body and segmental analysis). The students MD showed a high proportion of lean body mass (70,5 ± 6,1 kg) and low proportion of fat mass (8,3 ± 3,0 %). The authors emphasize the importance of monitoring and other parameters of body composition, e.g. total body water (TBW), extracellular water (ECW), intracellular water (ICW), segmental analysis of muscle mass and body fat.

scholarly journals Fat and fat-free mass index references in children and young adults: assessments along racial and ethnic lines

2020 ◽  
Vol 112 (3) ◽  
pp. 566-575 ◽  
Author(s):  
Roman J Shypailo ◽  
William W Wong
Keyword(s):  
Body Composition ◽  
Fat Mass ◽  
Fat Free Mass ◽  
Nutrition Status ◽  
Whole Body ◽  
Healthy Children ◽  
Health And Nutrition ◽  
Race Ethnicity ◽  
Total Body ◽  
Racial Ethnic

ABSTRACT Background Fat-free mass index (FFMI) and fat mass index (FMI) are superior to BMI and fat percentage in evaluating nutritional status. However, existing references fail to account for racial/ethnic differences in body composition among children. Objectives Our goal was to produce age-based normative references for FFMI and FMI in children for specific racial/ethnic groups. Methods Body composition, weight, and height were measured in 1122 normal healthy children aged 2–21 y. Bone mineral content measured by DXA, total body water by deuterium dilution, and total body potassium by whole-body γ counting were combined to calculate fat-free mass (FFM) and fat mass (FM) using equations based on the Reference Child and Adolescent models. FFMI and FMI were calculated by dividing FFM and FM by height squared, respectively. After outlier removal, the LMS (Lambda-Mu-Sigma) function within R's GAMLSS package was used to produce age-based FFMI and FMI growth curves for black (B), white (W), and Hispanic (H) children for each sex. Combined models were produced in cases where outcomes did not differ by race/ethnicity. Resulting models were compared with previously published FFMI and FMI models. Results FFMI and FMI models based on 1079 children, aged 2–21 y, were created for both sexes. FFMI models for B children showed higher values throughout. W and H children were combined to produce FFMI models for each sex. H boys were modeled individually for FMI, whereas W and B boys were combined. FMI models for girls were created for each race/ethnicity. Models agreed well with those based on children from the United Kingdom of comparable race/ethnicity. Conclusions Race/ethnicity-specific references for FFMI and FMI will increase the accuracy of health and nutrition status assessment in children over race/ethnicity-generic references. The models allow the calculation of SD scores to assess health and nutrition status in children.

scholarly journals Body Composition of Elite Female Players in Five Different Sports Games

2015 ◽  
Vol 45 (1) ◽  
pp. 207-215 ◽  
Author(s):  
Lucia Mala ◽  
Tomas Maly ◽  
František Zahalka ◽  
Vaclav Bunc ◽  
Ales Kaplan ◽  
...  
Keyword(s):  
Body Composition ◽  
Discriminant Function ◽  
Fat Mass ◽  
Female Athletes ◽  
Cell Mass ◽  
Fat Free Mass ◽  
Normative Values ◽  
Basketball Players ◽  
Target Values ◽  
Total Body

Abstract The goal of this study was to identify and compare body composition (BC) variables in elite female athletes (age ± years): volleyball (27.4 ± 4.1), softball (23.6 ± 4.9), basketball (25.9 ± 4.2), soccer (23.2 ± 4.2) and handball (24.0 ± 3.5) players. Fat-free mass (FFM), fat mass, percentage of fat mass (FMP), body cell mass (BCM), extracellular mass (ECM), their ratio, the percentage of BCM in FFM, the phase angle (α), and total body water, with a distinction between extracellular (ECW) and intracellular water, were measured using bioimpedance analysis. MANOVA showed significant differences in BC variables for athletes in different sports (F60.256 = 2.93, p < 0.01, η2 = 0.407). The results did not indicate any significant differences in FMP or α among the tested groups (p > 0.05). Significant changes in other BC variables were found in analyses when sport was used as an independent variable. Soccer players exhibited the most distinct BC, differing from players of other sports in 8 out of 10 variables. In contrast, the athletes with the most similar BC were volleyball and basketball players, who did not differ in any of the compared variables. Discriminant analysis revealed two significant functions (p < 0.01). The first discriminant function primarily represented differences based on the FFM proportion (volleyball, basketball vs. softball, soccer). The second discriminant function represented differences based on the ECW proportion (softball vs. soccer). Although all of the members of the studied groups competed at elite professional levels, significant differences in the selected BC variables were found. The results of the present study may serve as normative values for comparison or target values for training purposes.

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