Dataset Information

Are ethnic and gender specific equations needed to derive fat free mass from bioelectrical impedance in children of South asian, black african-Caribbean and white European origin? Results of the assessment of body composition in children study.

ABSTRACT:

Background

Bioelectrical impedance analysis (BIA) is a potentially valuable method for assessing lean mass and body fat levels in children from different ethnic groups. We examined the need for ethnic- and gender-specific equations for estimating fat free mass (FFM) from BIA in children from different ethnic groups and examined their effects on the assessment of ethnic differences in body fat.

Methods

Cross-sectional study of children aged 8-10 years in London Primary schools including 325 South Asians, 250 black African-Caribbeans and 289 white Europeans with measurements of height, weight and arm-leg impedance (Z; Bodystat 1500). Total body water was estimated from deuterium dilution and converted to FFM. Multilevel models were used to derive three types of equation {A: FFM?=?linear combination(height+weight+Z); B: FFM?=?linear combination(height(2)/Z); C: FFM?=?linear combination(height(2)/Z+weight)}.

Results

Ethnicity and gender were important predictors of FFM and improved model fit in all equations. The models of best fit were ethnicity and gender specific versions of equation A, followed by equation C; these provided accurate assessments of ethnic differences in FFM and FM. In contrast, the use of generic equations led to underestimation of both the negative South Asian-white European FFM difference and the positive black African-Caribbean-white European FFM difference (by 0.53 kg and by 0.73 kg respectively for equation A). The use of generic equations underestimated the positive South Asian-white European difference in fat mass (FM) and overestimated the positive black African-Caribbean-white European difference in FM (by 4.7% and 10.1% respectively for equation A). Consistent results were observed when the equations were applied to a large external data set.

Conclusions

Ethnic- and gender-specific equations for predicting FFM from BIA provide better estimates of ethnic differences in FFM and FM in children, while generic equations can misrepresent these ethnic differences.

SUBMITTER: Nightingale CM

PROVIDER: S-EPMC3799736 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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Publications

Are ethnic and gender specific equations needed to derive fat free mass from bioelectrical impedance in children of South asian, black african-Caribbean and white European origin? Results of the assessment of body composition in children study.

Nightingale Claire M CM Nightingale Claire M CM Rudnicka Alicja R AR Owen Christopher G CG Donin Angela S AS Newton Sian L SL Furness Cheryl A CA Howard Emma L EL Gillings Rachel D RD Wells Jonathan C K JC Cook Derek G DG Whincup Peter H PH

PloS one 20131018 10

<h4>Background</h4>Bioelectrical impedance analysis (BIA) is a potentially valuable method for assessing lean mass and body fat levels in children from different ethnic groups. We examined the need for ethnic- and gender-specific equations for estimating fat free mass (FFM) from BIA in children from different ethnic groups and examined their effects on the assessment of ethnic differences in body fat.<h4>Methods</h4>Cross-sectional study of children aged 8-10 years in London Primary schools incl ...[more]

PMID: 24204625

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Project description:INTRODUCTION:BMI is the most commonly used indicator to evaluate overweight and obesity, but it cannot distinguish changes in body composition. Over recent years, it has been demonstrated that bioelectrical impedance analysis (BIA) is a more accurate method for analyzing body composition. Bioelectrical impedance vector analysis (BIVA) has revealed its effectiveness as an indicator of nutritional status and hydration. OBJECTIVE:To assess the usefulness of bioimpedance analysis on the study of body composition in a group of children with overweight and obesity. MATERIALS AND METHODS:Cross-sectional observational study. The anthropometric parameters of 167 (79 were older than 12 years) overweight and obese children were recorded. Their body composition was analyzed using BIA and BIVA, and was classified based on different criteria. Concordance was analyzed (intraclass correlation coefficient, Bland-Altman analysis and weighted Kappa coefficient). The BIVA of the subgroups was compared using the Mahalanobis distance and Hotelling's T2. Statistical significance was considered for p<0.05. RESULTS:The BMI revealed that the majority of the assessed subjects were obese, although 12% had a normal percentage of fat mass (%FM). The classification by Z-BMI and Z-%FM significantly discriminate between subjects with different levels of adiposity. In children over the age of 12, the classification of fat mass index also discriminates significantly between obesity and non-obesity. As anticipated, in the tolerance ellipses, most of the individual vectors were situated in the left lower quadrant. CONCLUSIONS:BIVA reflects differences in the bioelectric patterns of children who are classified as being overweight or obese (BMI) and who have different levels of %FM and FMI. BIVA permits a fast and easy monitoring of the evolution of the nutritional state and changes associated with body composition, and it identifies those children whose body compartments may be precisely estimated using traditional BIA methods.

Project description:BackgroundIschemic heart disease (IHD) rates are lower in UK black Africans and black Caribbeans and higher in South Asians when compared with white Europeans. Ethnic differences in lipid concentrations may play a part in these differences.ObjectiveThe objective was to investigate blood lipid and dietary patterns in UK children from different ethnic groups.DesignThis was a cross-sectional study in 2026 UK children (including 285 black Africans, 188 black Caribbeans, 534 South Asians, and 512 white Europeans) attending primary schools in London, Birmingham, and Leicester. We measured fasting blood lipid concentrations and collected 24-h dietary recalls.ResultsIn comparison with white Europeans, black African children had lower total cholesterol (-0.14 mmol/L; 95% CI: -0.25, -0.04 mmol/L), LDL-cholesterol (-0.10 mmol/L; 95% CI: -0.20, -0.01 mmol/L), and triglyceride concentrations (proportional difference: -0.11 mmol/L; 95% CI: -0.16, -0.06 mmol/L); HDL-cholesterol concentrations were similar. Lower saturated fat intakes (-1.4%; 95% CI: -1.9%, -0.9%) explained the differences between total and LDL cholesterol. Black Caribbean children had total, LDL-cholesterol, HDL-cholesterol, and triglyceride concentrations similar to those for white Europeans, with slightly lower saturated fat intakes. South Asian children had total and LDL-cholesterol concentrations similar to those for white Europeans, lower HDL-cholesterol concentrations (-0.7 mmol/L; 95% CI: -0.11, -0.03 mmol/L), and elevated triglyceride concentrations (proportional difference: 0.14 mmol/L; 95% CI: 0.09, 0.20 mmol/L); higher polyunsaturated and monounsaturated fat intakes did not explain these lipid differences.ConclusionsOnly black African children had a blood lipid profile and associated dietary pattern likely to protect against future IHD. The loss of historically lower LDL-cholesterol concentrations among UK black Caribbeans and South Asians may have important adverse consequences for future IHD risk in these groups.

Project description:Background: Patients with chronic kidney disease (CKD) are vulnerable to loss of muscle mass due to several metabolic alterations derived from the uremic syndrome. Reference methods for body composition evaluation are usually unfeasible in clinical settings. Aims: To evaluate the accuracy of predictive equations based on bioelectrical impedance analyses (BIA) and anthropometry parameters for estimating fat free mass (FFM) and appendicular FFM (AFFM), compared to dual energy X-ray absorptiometry (DXA), in CKD patients. Methods: We performed a longitudinal study with patients in non-dialysis-dependent, hemodialysis, peritoneal dialysis and kidney transplant treatment. FFM and AFFM were evaluated by DXA, BIA (Sergi, Kyle, Janssen and MacDonald equations) and anthropometry (Hume, Lee, Tian, and Noori equations). Low muscle mass was diagnosed by DXA analysis. Intra-class correlation coefficient (ICC), Bland-Altman graphic and multiple regression analysis were used to evaluate equation accuracy, linear regression analysis to evaluate bias, and ROC curve analysis and kappa for reproducibility. Results: In total sample and in each CKD group, the predictive equation with the best accuracy was AFFMSergi (men, n = 137: ICC = 0.91, 95% CI = 0.79-0.96, bias = 1.11 kg; women, n = 129: ICC = 0.94, 95% CI = 0.92-0.96, bias = -0.28 kg). AFFMSergi also presented the best performance for low muscle mass diagnosis (men, kappa = 0.68, AUC = 0.83; women, kappa = 0.65, AUC = 0.85). Bias between AFFMSergi and AFFMDXA was mainly affected by total body water and fat mass. None of the predictive equations was able to accurately predict changes in AFFM and FFM, with all ICC lower than 0.5. Conclusion: The predictive equation with the best performance to asses muscle mass in CKD patients was AFFMSergi, including evaluation of low muscle mass diagnosis. However, assessment of changes in body composition was biased, mainly due to variations in fluid status together with adiposity, limiting its applicability for longitudinal evaluations.

Project description:Dual-energy X-ray absorptiometry (DXA) has been considered a reference method for measuring body fat percentage (BF%) in children and adolescents with an excess of adiposity. However, given that the DXA technique is impractical for routine field use, there is a need to investigate other methods that can accurately determine BF%. We studied the accuracy of bioelectrical impedance analysis (BIA) technology, including foot-to-foot and hand-to-foot impedance, and Slaughter skinfold-thickness equations in the measurement of BF%, compared with DXA, in a population of Latin American children and adolescents with an excess of adiposity. A total of 127 children and adolescents (11?17 years of age; 70% girls) from the HEPAFIT (Exercise Training and Hepatic Metabolism in Overweight/Obese Adolescent) study were included in the present work. BF% was measured on the same day using two BIA analysers (Seca® 206, Allers Hamburg, Germany and Model Tanita® BC-418®, TANITA Corporation, Sportlife Tokyo, Japan), skinfold measurements (Slaughter equation), and DXA (Hologic Horizon DXA System®, Quirugil, Bogotá, Columbia). Agreement between measurements was analysed using t-tests, Bland?Altman plots, and Lin's concordance correlation coefficient (?c). There was a significant correlation between DXA and the other BF% measurement methods (r > 0.430). According to paired t-tests, in both sexes, BF% assessed by BIA analysers or Slaughter equations differ from BF% assessed by DXA (p < 0.001). The lower and upper limits of the differences compared with DXA were 6.3?22.9, 2.2?2.8, and -3.2?21.3 (95% CI) in boys and 2.3?14.8, 2.4?20.1, and 3.9?18.3 (95% CI) in girls for Seca® mBCA, Tanita® BC 420MA, and Slaughter equations, respectively. Concordance was poor between DXA and the other methods of measuring BF% (?c < 0.5). BIA analysers and Slaughter equations underestimated BF% measurements compared to DXA, so they are not interchangeable methods for assessing BF% in Latin American children and adolescents with excess of adiposity.

Dataset Information

Are ethnic and gender specific equations needed to derive fat free mass from bioelectrical impedance in children of South asian, black african-Caribbean and white European origin? Results of the assessment of body composition in children study.

Background

Methods

Results

Conclusions

Publications

Are ethnic and gender specific equations needed to derive fat free mass from bioelectrical impedance in children of South asian, black african-Caribbean and white European origin? Results of the assessment of body composition in children study.

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