Developing an Impedance Based Equation for Fat-Free Mass of Black Preadolescent South African Children

Fat-free mass predictive equation using multifrequency bioelectrical impedance data in adolescent soccer athletes: development and cross-validation

OBJECTIVES

This study aimed to develop and cross-validate a fat-free mass (FFM) predictive equation using multifrequency bioelectrical impedance analysis (BIA) data in adolescent soccer athletes.

METHODS

Male adolescent soccer athletes (n = 149; 13-19 y old) were randomly sorted using Excel and independently selected for development group (n = 100) or cross-validation group (n = 49). The FFM reference values were determined using dual-energy X-ray absorptiometry. Single-frequency BIA was used to plot tolerance ellipses. Multifrequency-BIA raw data were used as independent variables in regression models. Student's independent t-test was used to compare development and cross-validation groups. Stepwise multiple regression was used to develop the FFM predictive equation. Bland-Altman plots, Lin's concordance correlation coefficient, according to McBride criteria, precision, accuracy, and standard error of estimate (SEE) were calculated to evaluate the concordance and reliability of estimates. Bioelectrical impedance vector analysis was plotted to assess hydration status.

RESULTS

No differences (P > 0.05) were observed between development and validation groups in chronological age, anthropometric data, bioelectrical impedance data, and FFM values obtained using dual-energy X-ray absorptiometry. Bioelectrical impedance vector analysis tolerance showed that all participants presented adequate hydration status compared to the reference population. The new FFM predictive equation developed and validated: FFM (kg) = -7.064 + 0.592 × chronological age (y) + 0.554 × weight (kg) + 0.365 × height²/resistance (cm²/Ω), presented R² = 0.95; SEE = 1.76 kg; concordance correlation coefficient = 0.95, accuracy = 0.98, and strength of concordance = 0.99.

CONCLUSIONS

The present study developed and cross-validated an FFM predictive equation based on multifrequency bioelectrical data providing substantial FFM accuracy for male adolescent soccer athletes.

High-standard predictive equations for estimating body composition using bioelectrical impedance analysis: a systematic review

The appropriate use of predictive equations in estimating body composition through bioelectrical impedance analysis (BIA) depends on the device used and the subject's age, geographical ancestry, healthy status, physical activity level and sex. However, the presence of many isolated predictive equations in the literature makes the correct choice challenging, since the user may not distinguish its appropriateness. Therefore, the present systematic review aimed to classify each predictive equation in accordance with the independent parameters used. Sixty-four studies published between 1988 and 2023 were identified through a systematic search of international electronic databases. We included studies providing predictive equations derived from criterion methods, such as multi-compartment models for fat, fat-free and lean soft mass, dilution techniques for total-body water and extracellular water, total-body potassium for body cell mass, and magnetic resonance imaging or computerized tomography for skeletal muscle mass. The studies were excluded if non-criterion methods were employed or if the developed predictive equations involved mixed populations without specific codes or variables in the regression model. A total of 106 predictive equations were retrieved; 86 predictive equations were based on foot-to-hand and 20 on segmental technology, with no equations used the hand-to-hand and leg-to-leg. Classifying the subject's characteristics, 19 were for underaged, 26 for adults, 19 for athletes, 26 for elderly and 16 for individuals with diseases, encompassing both sexes. Practitioners now have an updated list of predictive equations for assessing body composition using BIA. Researchers are encouraged to generate novel predictive equations for scenarios not covered by the current literature.Registration code in PROSPERO: CRD42023467894.

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.

Growth and Body Composition 5 y After Treatment for Severe Acute Malnutrition: A 5-y Prospective Matched Cohort Study in Ethiopian Children

BACKGROUND

Short-term anthropometric outcomes are well documented for children treated for severe acute malnutrition (SAM). However, anthropometric recovery may not indicate restoration of healthy body composition.

OBJECTIVES

This study aimed to evaluate long-term associations of SAM with growth and body composition of children 5 y after discharge from community-based management of acute malnutrition (CMAM).

METHODS

We conducted a 5-y prospective cohort study, enrolling children aged 6 to 59 mo discharged from CMAM (post-SAM) (n = 203) and nonmalnourished matched controls (n = 202) from Jimma Zone, Ethiopia in 2013. Anthropometry and body composition (bioelectrical impedance) were assessed. Multiple linear regression models tested differences in height-for-age (HAZ), weight-for-age (WAZ), and body mass index-for-age (BAZ) z-scores; height-adjusted fat-free mass index (FFMI); and FM index (FMI) between groups.

RESULTS

Post-SAM children had higher stunting prevalence than controls at discharge (82.2% compared with 36.0%; P < 0.001), 1 y (80.2% compared with 53.7%; P < 0.001), and 5 y postdischarge (74.2% compared with 40.8%; P < 0.001). Post-SAM children remained 5 cm shorter throughout follow-up, indicating no HAZ catch-up. No catch-up in WAZ or BAZ was observed. Post-SAM children had lower hip (-2.05 cm; 95% CI: -2.73, -1.36), waist (-0.92 cm; CI: -1.59, -0.23) and mid-upper arm (-0.64 cm; CI: -0.90, -0.42) circumferences and lower-limb length (-1.57 cm; 95% CI: -2.21, -0.94) at 5 y postdischarge. They had larger waist-hip (0.02 cm; 95% CI: 0.008, 0.033) and waist-height (0.013 cm; 95% CI: 0.004, 0.021) ratios, and persistent deficits in FFMI at discharge and 6 mo and 5 y postdischarge (P < 0.001 for all). No difference was detected in head circumference, sitting height, or FMI.

CONCLUSIONS

Five y after SAM treatment, children maintained deficits in HAZ, WAZ, BAZ, and FFMI, with preservation of FMI, sitting height, and head circumference at the expense of lower-limb length, indicating a "thrifty growth" pattern. Research is urgently needed to identify effective clinical and public health interventions to mitigate these consequences of malnutrition.

Development of bioelectrical impedance-based equations for the prediction of body composition of Malawian adolescents aged 10-18 years: a cross-sectional study

OBJECTIVES

The accuracy of bioelectrical impedance analysis (BIA) depends on population-specific prediction equations and there is no population-specific equation for predicting fat-free mass (FFM) in Malawian adolescents. This study aimed at determining the agreement between FFM measured by deuterium oxide dilution technique (the reference) and FFM by BIA; and propose BIA-based prediction equations to estimate FFM for Malawian adolescents.

DESIGN

This was a cross-sectional study.

SETTING

The study was conducted in Blantyre, Malawi PARTICIPANTS: 186 Malawian adolescents aged between 10 and 18 years were included in this study. Body composition was estimated by both the BodyStat BIA analyser and the deuterium oxide dilution method.

RESULTS

BIA inbuilt equation underestimated FFM compared with deuterium oxide dilution (p=0.039). The new prediction equation for FFM (kg)=-4.316+ 0.425* height²(cm)/resistance (Ω)+1.287* sex (male=1, female=0)+0.307*age(years)+0.344* weight(kg)+0.019*reactance(Ω) yielded an R2 of 0.926. The equation for total body water (TBW) (kg)=-2.152 + 0.328*height²(cm)/resistance (Ω) 0.910*sex (male=1, female=0)+0.307 *age (years)+0.249*weight(kg)+0.015*reactance(Ω) yielded an R2 of 0.922. The Bland-Altman plot illustrated a good level of concordance between the FFM and TBW predicted by the new equations and the values derived using deuterium dilution method.

CONCLUSIONS

The new BIA prediction equations for estimating FFM and TBW could be used to assess with very good accuracy and precision the body composition of Malawian and adolescents with similar characteristics.

Associations of Growth Impairment and Body Composition among South African School-Aged Children Enrolled in the KaziAfya Project

(1) Background: Early childhood malnutrition may result in increased fat mass (FM) among school-aged children in low- and middle-income countries (LMICs). We explored whether South African children with shorter stature have greater overall and abdominal FM compared to normal stature children. (2) Methods: Baseline assessments of body composition and weight were determined among school-aged children enrolled in a randomized controlled trial in Port Elizabeth, South Africa, using bioelectrical impedance analysis. Multiple linear regression models tested associations of children’s height and degree of stunting with FM, fat free mass (FFM), truncal fat mass (TrFM), and truncal fat free mass (TrFFM) overall and by sex. (3) Results: A total of 1287 children (619 girls, 668 boys) were assessed at baseline. Reduced child height was associated with higher FM and lower FFM and TrFFM, but these associations were reversed with increases in height. Girls classified as mildly or moderately/severely stunted had higher FM and TrFM but lower FFM and TrFFM, while no association was found for boys. (4) Conclusions: Our study suggests that efforts to reduce the non-communicable disease burden in LMICs should target growth-impaired children who may have greater overall FM and greater abdominal FM.