scholarly journals Proposal of new body composition prediction equations from bioelectrical impedance for Indonesian men

2016 ◽  
Vol 70 (11) ◽  
pp. 1271-1277 ◽  
Author(s):  
J Hastuti ◽  
M Kagawa ◽  
N M Byrne ◽  
A P Hills
1985 ◽  
Vol 58 (5) ◽  
pp. 1565-1571 ◽  
Author(s):  
K. R. Segal ◽  
B. Gutin ◽  
E. Presta ◽  
J. Wang ◽  
T. B. Van Itallie

This study 1) further validated the relationship between total body electrical conductivity (TOBEC) and densitometrically determined lean body mass (LBMd) and 2) compared with existing body composition techniques (densitometry, total body water, total body potassium, and anthropometry) two new electrical methods for the estimation of LBM: TOBEC, a uniform current induction method, and bioelectrical impedance analysis (BIA), a localized current injection method. In a sample of 75 male and female subjects ranging from 4.9 to 54.9% body fat the correlation between LBMd and LBM predicted from TOBEC by use of a previously developed regression equation was extremely strong (r = 0.962), thus confirming the validity of the TOBEC method. LBM predicted from BIA by use of prediction equations provided with the instrument also correlated with LBMd (r = 0.912) but overestimated LBM compared with LBMd in obese subjects. However, no such systematic error was apparent when new prediction equations derived from this heterogeneous sample of subjects were applied. Thus the TOBEC and BIA methods, which are based on the differing electrical properties of lean tissue and fat and which are convenient, rapid, and safe, correlate well with more cumbersome human body composition techniques.


Nutrients ◽  
2019 ◽  
Vol 11 (9) ◽  
pp. 2021
Author(s):  
Amanda van Zyl ◽  
Zelda White ◽  
Johan Ferreira ◽  
Friedeburg A. M. Wenhold

Bioelectrical impedance analysis (BIA) is a practical alternative to dual-energy X-ray absorptiometry (DXA) for determining body composition in children. Currently, there are no population specific equations available for predicting fat-free mass (FFM) in South African populations. We determined agreement between fat-free mass measured by DXA (FFMDXA) and FFM calculated from published multi-frequency bioelectrical impedance prediction equations (FFMBIA); and developed a new equation for predicting FFM for preadolescent black South African children. Cross-sectional data on a convenience sample of 84 children (mean age 8.5 ± 1.4 years; 44 {52%} girls) included body composition assessed using Dual X-ray Absorptiometry (FFMDXA) and impedance values obtained from the Seca mBCA 514 Medical Body Composition analyzer used to calculate FFM using 17 published prediction equations (FFMBIA). Only two equations yielded FFM estimates that were similar to the DXA readings (p > 0.05). According to the Bland–Altman analysis, the mean differences in FFM (kg) were 0.15 (LOA: −2.68; 2.37) and 0.01 (LOA: −2.68; 2.66). Our new prediction equation, F F M = 105.20 + 0.807 × S e x + 0.174 × W e i g h t + 0.01 × R e a c t a n c e + 15.71 × log ( R I ) , yielded an adjusted R2 = 0.9544. No statistical shrinkage was observed during cross-validation. A new equation enables the BIA-based prediction of FFM in the assessment of preadolescent black South African children.


1996 ◽  
Vol 6 (2) ◽  
pp. 146-164 ◽  
Author(s):  
Linda B. Houtkooper

Body composition assessment techniques provide estimates of percent body fat (%BF), fat mass (FM), and fat-free mass (FFM) based on indirect assessment models and methods. Prediction equations for %BF developed using a two-component model based on adult body composition constants will overestimate %BF in youths, especially prepubescent youths. Body composition prediction equations that have been validated and cross-validated using multiple-component criterion models which include measurements of body density and the water and mineral components of FFM provide the most accurate means for assessment of body composition in youths. Use of appropriate prediction equations and proper measurement techniques, for either bioelectrical impedance or skinfolds, results in body composition estimates with standard errors of estimate (prediction errors) of 3 to 4% BF and 2.0 to 2.5 kg of FFM. Poor measurement technique and inappropriate prediction equations will result in much larger prediction errors.


1992 ◽  
Vol 4 (6) ◽  
pp. 739-745 ◽  
Author(s):  
Kiyoji Tanaka ◽  
Fumio Nakadomo ◽  
Kanji Watanabe ◽  
Atsushi Inagaki ◽  
Hun Kyung Kim ◽  
...  

2020 ◽  
Vol 124 (12) ◽  
pp. 1345-1352 ◽  
Author(s):  
Phuong Hong Nguyen ◽  
Melissa F. Young ◽  
Long Quynh Khuong ◽  
Usha Ramakrishnan ◽  
Reynaldo Martorell ◽  
...  

AbstractThere is a need for accurate, inexpensive and field-friendly methods to assess body composition in children. Bioelectrical impedance analysis (BIA) is a promising approach; however, there have been limited validation and use among young children in resource-poor settings. We aim to develop and validate population-specific prediction equations for estimating total fat mass (FM), fat free-mass (FFM) and percentage body fat (PBF) in Vietnamese children (4–7 years) using reactance and resistance from BIA, anthropometric variables and demographic information. We conducted a cross-sectional survey of 120 children. Body composition was measured using dual-energy X-ray absorptiometry (DXA), BIA and anthropometry. To develop prediction equations, we split all data into development (70 %) and validation datasets (30 %). The model performance was evaluated using predicted residual error sum of squares, root mean squared error (RMSE), mean absolute error (MAE) and R2. We identified a top performing model with the least number of parameters (age, sex, weight and resistance index or resistance and height), low RMSE (FM 0·70, FFM 0·74, PBF 3·10), low MAE (FM 0·55, FFM 0·62, PBF 2·49), high R2 (FM 0·95, FFM 0·92, PBF 0·82) and the least difference between predicted values and actual values from DXA (FM 0·03 kg or 0·01 sd, FFM 0·06 kg or 0·02 sd, PBF 0·27 % or 0·04 sd). In conclusion, we developed the first valid and highly predictive equations to estimate FM, FFM and PBF in Vietnamese children using BIA. These findings have important implications for future research on the double burden of disease and risks associated with overweight and obesity in young children.


2020 ◽  
Vol 28 (4) ◽  
pp. 598-604
Author(s):  
Nathan F. Meier ◽  
Yang Bai ◽  
Chong Wang ◽  
Duck-chul Lee

Changes in body composition are related to mobility, fall risk, and mortality, especially in older adults. Various devices and methods exist to measure body composition, but bioelectrical impedance analysis (BIA) has several advantages. The purpose of this study was to validate a common BIA device with a dual-energy X-ray absorptiometer (DXA) in older adults and develop prediction equations to improve the accuracy of the BIA measurements. The participants were 277 older adults (162 women and 115 men; age 73.9 ± 5.8 years) without a history of cancer and without a history of severe medical or mental conditions. Individuals fasted 12 hr before BIA and DXA measurement. The correlations between the two methods for appendicular lean mass (ALM), fat-free mass (FFM), and percentage body fat (%BF) were .86, .93, and .92, respectively, adjusting for age and sex. The mean percentage error (DXA—InBody) and mean absolute percentage error were −12% and 13% for ALM, −13% and 13% for FFM, and 16% and 17% for %BF. The prediction equations estimated ALM, FFM, and %BF; sex was coded as 1 for male and 0 for female: Although highly correlated, BIA overestimated FFM, and ALM and underestimated %BF compared with DXA. An application of prediction equations eliminated the mean error and reduced the range of individual error across the sample. Prediction equations may improve BIA accuracy sufficiently to substitute for DXA in some cases.


1998 ◽  
Vol 8 (3) ◽  
pp. 285-307 ◽  
Author(s):  
Vivian H. Heyward

This paper provides an overview of practical methods for assessing body composition of children, adults, and older adults. Three methods commonly used in field and clinical settings are skinfolds, bioelectrical impedance analysis, and anthropometry. For each method, standardized testing procedures, sources of measurement error, recommendations for technicians, and selected prediction equations for each age category are presented. The skinfold method is appropriate for estimating body fat of children (6–17 years) and body density of adults (18–60 years) from diverse ethnic groups. Likewise, bioimpedance is well suited tor estimating the fat-free mass of children (10-19 years) as well as American Indian, black, Hispanic, and white adults. Anthropometric prediction equations that use a combination of circumferences and bony diameters are recommended for older adults (up to 79 years of age), as well as obese men and women.


2020 ◽  
Vol 4 (Supplement_2) ◽  
pp. 875-875
Author(s):  
Phuong Nguyen ◽  
Melissa Young ◽  
Long Khuong ◽  
Reynaldo Martorell ◽  
Usha Ramakrishnan ◽  
...  

Abstract Objectives Bioelectrical impedance analysis (BIA) is an accurate, inexpensive and field-friendly methods to assess body composition, but there is limited information on its use and validity for children in low-middle income countries. Our aim was to develop and validate population-specific prediction equations for estimating total fat mass (FM) and fat free-mass (FFM) in Vietnamese children using reactance and resistance from BIA and anthropometric variables. Methods We conducted a cross-sectional survey of 120 children in Thai Nguyen, Vietnam. Body composition was measured using dual energy x-ray absorptiometry (DXA), BIA and anthropometry (height, weight, triceps and subscapular skinfolds, and waist, hip, and mid upper arm circumferences). To develop prediction equations, we split the sample into development (70%) and validation datasets (30%). The model performance was evaluated using PRESS (Predicted residual error sum of squares), RMSE (Root mean squared error), MEA (Mean absolute error) and R,2. Results %MCEPASTEBIN% The development of prediction equations for total FM resulted in seven models. We identified a top performing model with the least number of parameters (age, sex, weight and resistance index), low RMSE (178 and 164 for FM and FFM, respectively), low MAE (136 and 141 for FM and FFM, respectively), high R2 (>.90), and the least difference between predicted and actual values (FM 25 0.03 g and FFM 8 0.01 g). Conclusions We developed valid and highly predictive equations to estimate FM and FFM in Vietnamese children using BIA. These findings have important implications for future research examining the risks associated with overweight and obesity in young children in resource-poor settings. Funding Sources Rollins School of Public Health (RSPH) Dean's Pilot and Innovation Grant, the New Jersey Institute for Food, Nutrition, and Health, and the Nestle Foundation.


2020 ◽  
Author(s):  
Richard Powell ◽  
Emanuella De Lucia Rolfe ◽  
Felix R. Day ◽  
John R.B. Perry ◽  
Simon J. Griffin ◽  
...  

AbstractAimsSingle-frequency segmental Bioelectrical Impedance Analysis (BIA) is commonly used to estimate body composition. To enhance the value of information derived from BIA, especially for use in large-scale epidemiological studies, we developed and validated equations to predict total and regional (arms, legs, trunk, android, gynoid, visceral) body composition parameters (lean mass and fat mass) from anthropometry and single-frequency (50 kHz) segmental BIA variables, using Dual Energy X-ray Absorptiometry (DEXA) as the criterion method.MethodsThe 11,559 adults (age 30 to 65) from the UK population-based Fenland Study with data on DEXA, BIA and anthropometry were randomly assigned to a Derivation sample (4,827 men; 5,732 women) or a Validation sample (500 men; 500 women). Prediction equations based on anthropometry and BIA variables were derived using forward stepwise multiple linear regression in the Fenland Derivation sample. These were validated in the Fenland Validation sample and also in the UK Biobank Imaging Study (2,392 men; 2,606 women) using Pearson correlations and Bland–Altman models.Results and ConclusionsBland Altman analyses revealed no significant mean bias for any predicted DEXA parameter (all P>0.05) for the fenland population. Bias expressed as % of the mean was between -0.6% and 0.5% for all parameters in both men and women, except for visceral FM and subcutaneous abdominal FM (range -3.6 to 1.1%). However, in UK Biobank most predicted parameters showed significant bias: % mean bias was <2% in both sexes only for total fat mass and total lean mass, and was >10% for leg and visceral fat mass in both sexes. In conclusion, new equations based on anthropometry and BIA variables predicted DEXA parameters with sufficient accuracy to assess relative differences between individuals, and were sufficiently accurate to predict absolute values for total body but not regional fat and lean mass.


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