Development and validation of BIA prediction equations of upper and lower limb lean soft tissue in athletes

Sardinha, Luís B.; Correia, Inês R.; Magalhães, João P.; Júdice, Pedro B.; Silva, Analiza M.; Hetherington‐Rauth, Megan

doi:10.1038/s41430-020-0666-8

Cited by 26 publications

(44 citation statements)

References 23 publications

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“…For this reason, a previous review called for action by the scientific community, since such regression equations were not available [ 23 ]. Most recently, some regression equations have been proposed for athletes, distinguishing the male and female population [ 24 , 25 , 26 ]. Similarly, new elements for a qualitative analysis in sport-specific populations have been developed [ 30 , 31 , 32 , 33 , 34 , 35 , 36 ].…”

Section: Aim Of Narrative Reviewmentioning

confidence: 99%

Section: Bioelectric Impedance Analysis (Bia) In Athletesmentioning

confidence: 99%

“…This may have led to inaccurate values, generating doubts about the accuracy and usefulness of BIA in athletes [23,27,28]. These perplexities have pushed researchers to develop specific equations [24][25][26] or use alternative evaluation approaches [31,45,56,78,109,110]. From 2000 to 2014, BIA was used in 15 studies [34,35,[37][38][39][40][41][42][43][44][45][46][47][48][49], with a peak of 11 articles published in 2015 [50][51][52][53][54][55][56][57][58][59][60], followed by a decline 2 years later [24,[61][62][63][64], before undergoing a progressive increase beginning in 2018 up until 2020 .…”

Section: Bioelectric Impedance Analysis (Bia) In Athletesmentioning

confidence: 99%

“…Current application of BIS and BIA aims to predict body composition parameters for inclusion in multicomponent models. However, only single-frequency BIA has been used to develop prediction equations to estimate different body composition parameters in athletes [ 24 , 25 , 26 ].…”

Section: Introductionmentioning

confidence: 99%

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Assessment of Body Composition in Athletes: A Narrative Review of Available Methods with Special Reference to Quantitative and Qualitative Bioimpedance Analysis

et al. 2021

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Body composition is acknowledged as a determinant of athletic health and performance. Its assessment is crucial in evaluating the efficiency of a diet or aspects related to the nutritional status of the athlete. Despite the methods traditionally used to assess body composition, bioelectric impedance analysis (BIA) and bioelectric impedance vector analysis (BIVA) have recently gained attention in sports, as well as in a research context. Only until recently have specific regression equations and reference tolerance ellipses for athletes become available, while specific recommendations for measurement procedures still remain scarce. Therefore, the present narrative review summarizes the current literature regarding body composition analysis, with a special focus on BIA and BIVA. The use of specific technologies and sampling frequencies is described, and recommendations for the assessment of body composition in athletes are provided. Additionally, the estimation of body composition parameters (i.e., quantitative analysis) and the interpretation of the raw bioelectrical data (i.e., qualitative analysis) are examined, highlighting the innovations now available in athletes. Lastly, it should be noted that, up until 2020, the use of BIA and BIVA in athletes failed to provide accurate results due to unspecific equations and references; however, new perspectives are now unfolding for researchers and practitioners. In light of this, BIA and especially BIVA can be utilized to monitor the nutritional status and the seasonal changes in body composition in athletes, as well as provide accurate within- and between-athlete comparisons.

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Section: Aim Of Narrative Reviewmentioning

confidence: 99%

Section: Bioelectric Impedance Analysis (Bia) In Athletesmentioning

confidence: 99%

Section: Bioelectric Impedance Analysis (Bia) In Athletesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Assessment of Body Composition in Athletes: A Narrative Review of Available Methods with Special Reference to Quantitative and Qualitative Bioimpedance Analysis

et al. 2021

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“…An estimated regression equation (ERE) is then used to predict FM and FFM (kg) (Kyle et al, 2004a). Recently, BIA has been used for the quantitation of BC through a specific mathematical model without empirically derived variables for athletic players (Sardinha et al, 2020) (Campa & Toselli, 2018;Toselli et al, 2020), children (Colica et al, 2018), older adults (Silveira et al, 2020), and young patients with cystic fibrosis (Charatsi et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

Development and validation of bioimpedance prediction equations for fat-free mass in unilateral male amputees

Choi¹,

Ko²,

Chang³

et al. 2021

PeerJ

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Background Metabolic disease due to increased fat mass is observed in amputees (APTs), thereby restricting their activity. Systemic health management with periodic body composition (BC) testing is essential for healthy living. Bioelectrical impedance analysis (BIA) is a non-invasive and low-cost method to test BC; however, the APTs are classified as being exempted in the BIA. Objective To develop segmental estimated regression equations (sEREs) for determining the fat-free mass (FFM, kg) suitable for APTs and improve the accuracy and validity of the sERE. Methods Seventy-five male APTs participated in this cross-sectional study. Multiple regression analysis was performed to develop highly accurate sEREs of BIA based on independent variables derived from anthropometric measurements, dual-energy X-ray absorptiometry (DXA), and BIA parameters. The difference in validity between the predicted DXA and sum of the segmentally-predicted FFM values by sEREs (Sum_sEREs) values was evaluated using bivariate linear regression analysis and the Bland–Altman plot. Results The coefficient of determination (R2) and total error (TE) between DXA and Sum_sEREs were 71% and 5.4 (kg) in the cross-validation analysis. Conclusions We confirmed the possibility of evaluating the FFM of APTs through the sEREs developed in this study. We also identified several independent variables that should be considered while developing such sEREs. Further studies are required to determine the validity of our sEREs and the most appropriate BIA frequencies for measuring FFM in APTs.

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Bioelectrical impedance analysis versus reference methods in the assessment of body composition in athletes

et al. 2022

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The present systematic review aimed to compare the accuracy of Bioelectrical Impedance Analysis (BIA) and 33 Bioelectrical Impedance Vector Analysis (BIVA) vs. reference methods for the assessment of body composition in 34 athletes. Studies were identified based on a systematic search of internationally electronic databases (PubMed and Scopus) 35and hand searching of the reference lists of the included studies. In total, 42 studies published between 1988 and 2021 36 were included. The methodological quality was assessed using the Quality Assessment Tool for Observational Cohort 37 and Cross-sectional Studies as recommended by the National Institute of Health. Twenty-three studies had an overall 38 good rating in terms of quality, while 13 were rated as fair and six as poor, resulting in a low to moderate risk of bias. Fat 39 mass was inconsistently determined using BIA vs. the reference methods, regardless of the BIA-technology. When using 40 the foot to hand technology with predictive equations for athletes, a good agreement between BIA and the reference 41 methods was observed for fat-free mass, total body, intra and extra cellular water. However, an underestimation in fat-42 free mass and body fluids was found when using generalized predictive equations. Classic and Specific BIVA represented 43 a valid approach for assessing body fluids (Classic BIVA) and percentage of fat mass (Specific BIVA). The present 44 systematic review suggests that BIA and BIVA can be used for assessing body composition in athletes, provided that 45 foot-to-hand technology, predictive equations, and BIVA references for athletes are used.

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Development and validation of BIA prediction equations of upper and lower limb lean soft tissue in athletes

Cited by 26 publications

References 23 publications

Assessment of Body Composition in Athletes: A Narrative Review of Available Methods with Special Reference to Quantitative and Qualitative Bioimpedance Analysis

Assessment of Body Composition in Athletes: A Narrative Review of Available Methods with Special Reference to Quantitative and Qualitative Bioimpedance Analysis

Development and validation of bioimpedance prediction equations for fat-free mass in unilateral male amputees

Bioelectrical impedance analysis versus reference methods in the assessment of body composition in athletes

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