Bioelectrical impedance estimation of fat-free body mass in children and youth: a cross-validation study

The purposes of this study were to develop and cross-validate the “best” prediction equations for estimating fat-free body mass (FFB) from bioelectrical impedance in children and youth. Predictor variables included height2/resistance (RI) and RI with anthropometric data. FFB was determined from body density (underwater weighing) and body water (deuterium dilution) (FFB-DW) and from age-corrected density equations, which account for variations in FFB water and bone content. Prediction equations were developed using multiple regression analyses in the validation sample (n = 94) and cross-validated in three other samples (n = 131). R2 and standard error of the estimate (SEE) values ranged from 0.80 to 0.95 and 1.3 to 3.7 kg, respectively. The four samples were then combined to develop a recommended equation for estimating FFB from three regression models. R2 and SEE values and coefficients of variation from these regression equations ranged from 0.91 to 0.95, 2.1 to 2.9 kg, and 5.1 to 7.0%, respectively. As a result of all cross-validation analyses, we recommend the equation FFB-DW = 0.61 RI + 0.25 body weight + 1.31, with a SEE of 2.1 kg and adjusted R2 of 0.95. This study demonstrated that RI with body weight can predict FFB with good accuracy in Whites 10–19 yr old.

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PSVI-8 Meta-regression Analysis to Determine the Relationship Between Growing Pig Body Weight and Variation

Journal of Animal Science ◽

10.1093/jas/skab054.357 ◽

2021 ◽

Vol 99 (Supplement_1) ◽

pp. 218-219

Author(s):

Andres Fernando T Russi ◽

Mike D Tokach ◽

Jason C Woodworth ◽

Joel M DeRouchey ◽

Robert D Goodband ◽

...

Keyword(s):

Body Weight ◽

Regression Analysis ◽

Sample Size ◽

Polynomial Regression ◽

Data Sets ◽

Regression Equations ◽

Prediction Equations ◽

Data Set ◽

Rate Of Increase ◽

The Relationship

Abstract The swine industry has been constantly evolving to select animals with improved performance traits and to minimize variation in body weight (BW) in order to meet packer specifications. Therefore, understanding variation presents an opportunity for producers to find strategies that could help reduce, manage, or deal with variation of pigs in a barn. A systematic review and meta-analysis was conducted by collecting data from multiple studies and available data sets in order to develop prediction equations for coefficient of variation (CV) and standard deviation (SD) as a function of BW. Information regarding BW variation from 16 papers was recorded to provide approximately 204 data points. Together, these data included 117,268 individually weighed pigs with a sample size that ranged from 104 to 4,108 pigs. A random-effects model with study used as a random effect was developed. Observations were weighted using sample size as an estimate for precision on the analysis, where larger data sets accounted for increased accuracy in the model. Regression equations were developed using the nlme package of R to determine the relationship between BW and its variation. Polynomial regression analysis was conducted separately for each variation measurement. When CV was reported in the data set, SD was calculated and vice versa. The resulting prediction equations were: CV (%) = 20.04 – 0.135 × (BW) + 0.00043 × (BW)2, R2=0.79; SD = 0.41 + 0.150 × (BW) - 0.00041 × (BW)2, R2 = 0.95. These equations suggest that there is evidence for a decreasing quadratic relationship between mean CV of a population and BW of pigs whereby the rate of decrease is smaller as mean pig BW increases from birth to market. Conversely, the rate of increase of SD of a population of pigs is smaller as mean pig BW increases from birth to market.

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Spine’s Sagittal Plane Curves’ Coherence with Anthropometric Parameters in Schoolchildren

Baltic Journal of Sport and Health Sciences ◽

10.33607/bjshs.v3i57.635 ◽

2018 ◽

Vol 3 (57) ◽

Author(s):

Vilma Mauricienė ◽

Kristina Bačiulienė

Keyword(s):

Body Weight ◽

Body Mass ◽

Fat Mass ◽

Lumbar Lordosis ◽

Thoracic Kyphosis ◽

Anthropometric Measurements ◽

Sagittal Profile ◽

Anthropometric Parameters ◽

Significant Difference ◽

Free Body

The aim of this study — to identify how anthropometric measurements are connected with spine sagittal curves inschoolchildren.Anthropometric and sagittal body posture measurements were performed for 405 schoolchildren, age range 10—13years. Such anthropometric measurements as body height, weight, fat mass and fat free mass were assessed. Degreesof thoracic kyphosis and lumbar lordosis as sagittal profile features were evaluated.According to the data analysis could be concluded, that coherence between anthropometric parameters and spine’ssagittal profile differs according to gender. The number of statistically significant connections between these twoparameters’ groups was greater in boys. Anthropometric measurements had greater coherence with thoracic kyphosisin comparison with lumbar lordosis. Body weight and fat mass were statistically significantly different according tokyphosis and lordosis values in boys, although fat-free body mass had no significant difference with sagittal curves’expression. Body weight, fat mass and fat-free body mass among girls were associated only with thoracic kyphosis.Keywords: thoracic kyphosis, lumbar lordosis, height, weight, fat mass.

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Association between Hydration Status and Body Composition in Healthy Adolescents from Spain

Nutrients ◽

10.3390/nu11112692 ◽

2019 ◽

Vol 11 (11) ◽

pp. 2692 ◽

Cited By ~ 1

Author(s):

Ana Laja García ◽

Carmen Moráis-Moreno ◽

Mª Samaniego-Vaesken ◽

Ana Puga ◽

Gregorio Varela-Moreiras ◽

...

Keyword(s):

Body Composition ◽

Body Weight ◽

Body Mass ◽

Water Intake ◽

Fat Body ◽

Bioelectrical Impedance ◽

Impedance Analysis ◽

Normal Weight ◽

International Standards ◽

Hydration Status

At present, obesity and overweight are major public health concerns. Their classical determinants do not sufficiently explain the current situation and it is urgent to investigate other possible causes. In recent years, it has been suggested that water intake could have important implications for weight management. Thus, the aim of this study was to examine the effect of hydration status on body weight and composition in healthy adolescents from Spain. The study involved 372 subjects, aged 12–18 years. Water intake was assessed through the validated “hydration status questionnaire adolescent young”. Anthropometric measurements were performed according to the recommendations of the International Standards for Anthropometric Assessment (ISAK) and body composition was estimated by bioelectrical impedance analysis. Water intake normalized by body weight was positively correlated with body water content (boys (B): r = 0.316, p = 0.000; girls (G): r = 0.245, p = 0.000) and inversely with body mass index (BMI) (B: r = −0.515, p = 0.000; G: r = −0.385, p =0.000) and fat body mass (B: r = −0.306, p = 0.000; G: r = −0.250, p = 0.001). Moreover, according to BMI, overweight/obese individuals consumed less water than normal weight ones. In conclusion, higher water balance and intake seems to be related with a healthier body composition.

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Association between Ethnicity, Body Mass Index, and Bioelectrical Impedance: Implications for the Population Specificity of Prediction Equations

Annals of the New York Academy of Sciences ◽

10.1111/j.1749-6632.2000.tb06449.x ◽

2006 ◽

Vol 904 (1) ◽

pp. 199-202 ◽

Cited By ~ 31

Author(s):

L. C. WARD ◽

B. L. HEITMANN ◽

P. CRAIG ◽

D. STROUD ◽

E. C. AZINGE ◽

...

Keyword(s):

Body Mass Index ◽

Body Mass ◽

Bioelectrical Impedance ◽

Prediction Equations

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Prediction of body composition in premenopausal females from dual-energy X-ray absorptiometry

Journal of Applied Physiology ◽

10.1152/jappl.1993.75.4.1637 ◽

1993 ◽

Vol 75 (4) ◽

pp. 1637-1641 ◽

Cited By ~ 22

Author(s):

N. J. Hansen ◽

T. G. Lohman ◽

S. B. Going ◽

M. C. Hall ◽

R. W. Pamenter ◽

...

Keyword(s):

Body Mass Index ◽

Body Composition ◽

Body Mass ◽

Bioelectrical Impedance ◽

Dual Energy ◽

Body Density ◽

X Ray ◽

Density Values ◽

Free Body ◽

Individual Body

Four methods for predicting body composition were compared in premenopausal females (n = 100), 28#x2013;39 yr old, by using underwater weighing (UWW) as the criterion method. The four methods were dual energy X-ray absorptiometry (DEXA), skinfolds, bioelectrical impedance, and body mass index. The sample had a mean percent fat (%fat) of 29.7 +/- 6.8% (SD) by DEXA and 29.9 +/- 5.8% measured by UWW. DEXA yielded a standard error of estimate (SE) of 2.4% (r = 0.91) for the prediction of %fat from UWW. When %fat was estimated from other methods, larger SEs were obtained: 3.0% for skin-folds, 3.3% for body mass index, and 2.9% for bioelectrical impedance (height2/resistance) plus weight. Individual body density values derived from UWW were corrected for bone mineral variation. DEXA predicted the corrected body density with a lower SE (0.0040 vs. 0.0053 g/ml) than the original density values. We conclude that DEXA was a precise method and correlated highly with fat-free body weight and %fat from UWW in this homogeneous female sample.

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Undernutrition in grazing sheep. III.* Body composition and its estimation in vivo

Australian Journal of Agricultural Research ◽

10.1071/ar9720511 ◽

1972 ◽

Vol 23 (3) ◽

pp. 511 ◽

Cited By ~ 11

Author(s):

DJ Farrell ◽

TF Reardon

Keyword(s):

Body Weight ◽

Water Content ◽

Tritiated Water ◽

Body Part ◽

High Water ◽

The Body ◽

High Water Content ◽

Regression Equations ◽

Free Body

Twenty-four sheep, 12 fitted with rumen cannulae, were divided into three similar groups and kept at pasture. The grazing intake of group A was not restricted, but groups B and C were undernourished for a period of about 4 months and were then maintained in thin condition for a further 9 months, when all sheep were killed. The mean fat content was then 27, 9, and 5% of mean body weight in groups A, B, and C respectively. Undernourished sheep had a significantly higher (P < 0.01) water content in the fat-free empty body than well-nourished sheep. Multiple regression equations relating the fat, protein, and estimated energy contents of the body to tritiated water space and body weight differed between well-nourished and undernourished sheep. This was due to the larger amount of water in the rumell-reticulum of thin sheep and to the high water content of their fat-free body. __________________ *Part II, Aust. J. Agric. Res., 23: 499 (1972)

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