Development and cross-validation of predictive equations for fat-free mass and lean soft tissue mass by bioelectrical impedance in Brazilian women

The bioelectrical impedance analysis (BIA) international database: aims, scope, and call for data

BACKGROUND

Bioelectrical impedance analysis (BIA) is a technique widely used for estimating body composition and health-related parameters. The technology is relatively simple, quick, and non-invasive, and is currently used globally in diverse settings, including private clinicians' offices, sports and health clubs, and hospitals, and across a spectrum of age, body weight, and disease states. BIA parameters can be used to estimate body composition (fat, fat-free mass, total-body water and its compartments). Moreover, raw measurements including resistance, reactance, phase angle, and impedance vector length can also be used to track health-related markers, including hydration and malnutrition, and disease-prognostic, athletic and general health status. Body composition shows profound variability in association with age, sex, race and ethnicity, geographic ancestry, lifestyle, and health status. To advance understanding of this variability, we propose to develop a large and diverse multi-country dataset of BIA raw measures and derived body components. The aim of this paper is to describe the 'BIA International Database' project and encourage researchers to join the consortium.

METHODS

The Exercise and Health Laboratory of the Faculty of Human Kinetics, University of Lisbon has agreed to host the database using an online portal. At present, the database contains 277,922 measures from individuals ranging from 11 months to 102 years, along with additional data on these participants.

CONCLUSION

The BIA International Database represents a key resource for research on body composition.

The Body Adiposity Index is not applicable to the Brazilian adult population

Background

Obesity is a serious disease that burdens public health systems around the world. It is a risk factor for the development of several non-communicable chronic diseases that are related to the amount and distribution of body fat. Body composition assessment using simple and low-cost techniques can help in the early detection of excess fat, allowing for the prevention and treatment of both obesity and associated diseases. Thus, identifying and proposing valid anthropometric indices for this purpose can be a great ally of health programs.

Objective

To verify the validity of the Body Adiposity Index (BAI) in relation to Dual Energy X-Ray Absorptiometry (DXA) for estimating body fat percentage in Brazilian adults, as well as to propose a new mathematical model to estimate the fat-free mass of this population.

Methods

In a cross-sectional study, 424 subjects (of which 220 were women), aged between 20 and 59 years, were evaluated by BAI and DXA, then randomly divided into two groups stratified by sex: the development group (n = 283) and the cross-validation group (n = 141). Statistical analyses to test the validity of BAI as a predictor of fat mass, in addition to proposing a new mathematical model for estimating fat-free mass, using DXA as a reference method. The analysis included paired t-test, stepwise multiple regression, coefficient of concordance correlation, and Bland-Altman plots.

Results

The BAI validity analysis showed a low correlation coefficient of agreement [CCC = 0.626; ρ (precision) = 0.795; C_b(accuracy) = 0.787]; in addition, the mean difference in the Bland-Altman plot was different from zero in the cross-validation group (p < 0.01) and limits of agreement (LOA) ranged between−8.0 and 14.4 kg, indicating a poor agreement between the BAI and the reference method. The new mathematical model for estimating FFM showed a high correlation coefficient of agreement (CCC = 0.952; ρ = 0.953; C_b = 0.999), in addition to acceptable LOA in the Bland-Altman plot (-6.7 and 6.7).

Conclusion

In the studied sample, the BAI showed low validity for estimating body fat, while the new proposed model was found to be a good option to assess the body composition of Brazilian adults.

Fat-Free Mass Index, Visceral Fat Level, and Muscle Mass Percentage Better Explain Deviations From the Expected Value of Aortic Pressure and Structural and Functional Arterial Properties Than Body Fat Indexes

Bioelectrical impedance analysis (BIA)-derived indexes [e.g., fat (FMI) and fat-free mass indexes (FFMI), visceral fat level (VFL)] are used to characterize obesity as a cardiovascular risk factor (CRF). The BIA-derived index that better predicts arterial variability is still discussed.

Development and Cross-Validation of a Predictive Equation for Fat-Free Mass in Brazilian Adolescents by Bioelectrical Impedance

The bioelectrical impedance analysis (BIA) is one of the most commonly used techniques for assessing body composition in a clinical setting and in field approaches, as it has the advantages of easy application, fast, and non-invasive, in addition to its relatively low cost. However, the available predictive equations need to be valid for the evaluated subjects. The aim of this study was to verify the validity of several published BIA equations in estimating fat-free mass (FFM) among Brazilian adolescents, in addition to developing and cross-validating a BIA equation to estimate FFM appropriate for Brazilian adolescents. This is a cross-sectional study with 257 adolescents (128 girls) aged 10-19 years, randomly divided into two groups, namely, development (n = 172) and cross-validation (n = 85). The standard technique for assessing FFM was dual X-ray absorptiometry (DXA). The paired t-test, multiple regression, and the Bland-Altman plots were used to test the validity of the proposed models and to perform cross-validation of the model. The equation derived in this study was as follows: FFM = -17.189 + 0.498 (Height²/Resistance) + 0.226 Weight + 0.071 Reactance - 2.378 Sex + 0.097 Height + 0.222 Age; r ² = 0.92; standard error of the estimate = 2.49 kg; the new equation for FFM showed better agreement when compared with that of the equations developed in other countries. In conclusion, the newly developed equations provide a valid FFM estimation and are recommended for Brazilian adolescents with similar characteristics.

Prognostic prediction by hypermetabolism varies depending on the nutritional status in early amyotrophic lateral sclerosis

To examine whether hypermetabolism could predict the prognosis of early amyotrophic lateral sclerosis (ALS) patients with differing nutritional profiles. This single-center, retrospective study examined the prognosis of ALS patients with hypermetabolism in relation to their nutritional status at hospitalization. The metabolic state was estimated by the ratio of measured resting energy expenditure (mREE) to lean soft tissue mass (LSTM) (mREE/LSTM), wherein patients with ratios ≥ 38 were defined as hypermetabolic. Malnutrition was defined as %ideal body weight < 0.9. Forty-eight patients were enrolled in this study. The hypermetabolic group had shorter survival in the normal-weight group but more prolonged survival in the malnutrition group. Multiplication of nutritional and metabolic factors, such as [(body mass index (BMI) − 19.8) × (mREE/LSTM − 38)], designated as BMI-muscle metabolism index (BMM index), successfully predicted the prognosis in the group with a high BMM index (≥ 1), which showed shorter survival and a faster rate of weight loss and functional decline. Multivariate analysis using the Cox model showed high BMM index was an independent poor prognostic factor (hazard ratio: 4.05; p = 0.025). Prognostic prediction by hypermetabolism varies depending on the nutritional status in ALS, and the BMM index is a consistent prognostic factor.