What makes a BIA equation unique? Validity of eight-electrode multifrequency BIA to estimate body composition in a healthy adult population.

BACKGROUND/OBJECTIVES: The validity of bioelectrical impedance analysis (BIA) for body composition analysis is limited by assumptions relating to body shape. Improvement in BIA technology could overcome these limitations and reduce the population specificity of the BIA algorithm. SUBJECTS/METHODS: BIA equations for the prediction of fat-free mass (FFM), total body water (TBW) and extracellular water (ECW) were generated from data obtained on 124 Caucasians (body mass index 18.5-35 kg/m(2)) using a four-compartment model and dilution techniques as references. The algorithms were validated in an independent multiethnic population (n=130). The validity of BIA results was compared (i) between ethnic groups and (ii) with results from the four-compartment model and two-compartment methods (air-displacement plethysmography, dual-energy X-ray absorptiometry and deuterium dilution). RESULTS: Indices were developed from segmental R and Xc values to represent the relative contribution of trunk and limbs to total body conductivity. The coefficient of determination for all prediction equations was high (R(2): 0.94 for ECW, 0.98 for FFM and 0.98 for TBW) and root mean square error was low (1.9 kg for FFM, 0.8 l for ECW and 1.3 kg for TBW). The bias between BIA results and different reference methods was not statistically different between Afro-American, Hispanic, Asian or Caucasian populations and showed a similar difference (-0.2-0.2 kg FFM) when compared with the bias between different two-compartment reference methods (-0.2-0.3 kg FFM). CONCLUSIONS: An eight-electrode, segmental multifrequency BIA is a valid tool to estimate body composition in healthy euvolemic adults compared with the validity and precision of other two-compartment reference methods. Population specificity is of minor importance when compared with discrepancies between different reference methods.

Total and regional relationship between lean and fat mass with increasing adiposity--impact for the diagnosis of sarcopenic obesity.

BACKGROUND/OBJECTIVE: Besides the effect of age used to define sarcopenia, there is need to understand the impact of adiposity on the relationship between lean (fat-free mass, FFM) and fat mass (FM) in order to diagnose sarcopenic obese phenotypes. More importantly, the regional distribution of skeletal muscle (SM) to adipose tissue (AT) or the composition of FFM (that is, SM proportion of lean mass) may also depend on adiposity. SUBJECTS/METHODS: In a large database (n=1737) of healthy males and females (age 11-84 years, BMI 13.5-52.5 kg/m(2)) we investigated changes in the relationship between FFM and FM (normalized by height as fat-free mass index and fat mass index: FFMI and FMI, kg/m(2) assessed by densitometry) with increasing adiposity and age. In a subgroup (n=263) we analyzed the relationship between regional SM and (i) AT (by magnetic resonance imaging) or (ii) lean soft tissue (by dual X-ray absorptiometry) with increasing adiposity. RESULTS: The relationship between lean and FM was influenced by adiposity, age and gender. With increasing adiposity, SM/AT declined faster at the trunk in men and at the extremities in women. The contribution of appendicular SM to lean soft tissue of arms and legs tended to decrease at a higher adiposity in both genders (FMI >6.97 kg/m(2) in women; FMI>7.77 kg/m(2) in men). CONCLUSION: Besides age and gender, adiposity and body region should be considered when evaluating the normal relationship between lean and FM, SM/FFM and SM/AT.

Associations between breast adipose tissue, body fat distribution and cardiometabolic risk in women: cross-sectional data and weight-loss intervention.

BACKGROUND/OBJECTIVES: Recent studies have shown that a high breast volume predicts visceral adipose tissue (VAT) and risk for type 2 diabetes independently of body mass index (BMI) and waist circumference (WC). To investigate the relationships between breast adipose tissue (BrAT), body fat distribution and cardiometabolic risk factors. SUBJECTS/METHODS: In all, 97 healthy females (age 19-46 years, BMI 16.8-46.8 kg/m2) were examined cross-sectionally. A subgroup of 57 overweight and obese women (BMI 34.7±4.5 kg/m2) was investigated before and after diet-induced weight loss (-8.3±4 kg). Fat mass (FM) was measured by air-displacement plethysmography. Volumes of BrAT, VAT and subcutaneous adipose tissue (SAT) of the trunk and extremeties were assessed by whole-body magnetic resonance imaging (MRI). Cardiometabolic risk was assessed by lipid profile, fasting glucose, insulin, adiponectin and leptin levels. RESULTS: A high proportion of BrAT was associated with higher truncal and lower leg SAT. Weight loss-induced decline in BrAT as a percentage of total adipose tissue was correlated with decreases in SAT(trunk) and inversely with SAT(legs) and VAT. No relationships were found between BrAT and cardiometabolic risk factors. By contrast, SAT(trunk) and VAT showed positive and SAT(legs) inverse associations with cardiometabolic risk factors in cross-sectional as well as longitudinal analysis. The association between BrAT and VAT was lost after adjusting for %FM and truncal SAT. CONCLUSIONS: Our results indicate that high BrAT reflects a phenotype with increased SAT(trunk) and low SAT(legs). BrAT showed no independent relationships with VAT and cardiometabolic risk factors.

Is the 1975 Reference Man still a suitable reference?

BACKGROUND/OBJECTIVE: In 1975, a Reference Man for the estimation of radiation doses without adverse health effects was created. However, during the past few decades, considerable changes in body weight and body composition were observed, as a result of which, new in vivo technologies of body composition analysis are now available. Thus, the Reference Man might be outdated as adequate standard to assess medication and radiation doses. The objective of this study was to compare body composition of an adult population with 1975 Reference Man data, thereby questioning its value as a suitable reference. METHODS: Body composition was assessed in 208 healthy, Caucasian subjects (105 males, 103 females) aged 18-78 years with a body mass index range of 16.8-35.0 kg/m(2). Fat mass (FM) and muscle mass (MM) were assessed by dual-energy X-ray absorptiometry, organ masses (OMs) were measured by magnetic resonance imaging. RESULTS: There was a considerable variance in body weight and body composition. When compared with Reference Man, great differences in body composition were found. Men and women of the study population were heavier, taller and had more FM, MM and higher masses of brain, heart and spleen. These differences did not depend on age. Relationships between body weight and body composition were investigated by general linear regression models, whereby deviations in FM, MM and heart mass disappeared, whereas differences in brain and spleen mass persisted. CONCLUSIONS: Our data indicate the need of a modern Reference Man and thus a recalculation of medical radiation doses and medication.

Functional body composition: insights into the regulation of energy metabolism and some clinical applications.

The application of advanced methods and techniques and their continuous development enable detailed body composition analyses (BCAs) and modeling of body composition at different levels (e.g., at atomic, molecular, organ-tissue and whole body level). Functional body composition integrates body components into regulatory systems (e.g., on energy balance). Regulation of body weight is closely linked to the mass and function of individual body components. Fat mass is part of the energy intake regulatory feedback system. In addition, fat-free mass (FFM) and fat mass are both determinants of resting energy expenditure (REE). Up to 80% of the variance in energy intake and energy expenditure is explained by body composition. A deviation from normal associations between body components and function suggests a metabolic disequilibrium (e.g., in the REE-FFM relationship or in the plasma leptin-fat mass association) that may occur in response to weight changes and diseases. The concept of functional body composition adds to a more sophisticated view on nutritional status and diseases, as well as to a characterization of biomedical traits that will provide functional evidence relating genetic variants.