A specific bioelectrical impedance equation to predict body composition in Turner's syndrome

Guedes, Alexis Dourado; Bianco, Bianca; Lipay, Mônica Vannucci Nunes; Callou, Emmanuela Quental; Castro, Maria da Graça Tanori de; Verreschi, Ieda Therezinha do Nascimento

doi:10.1590/s0004-27302010000100005

“…Several BIA studies conducted outside of Korea have included patients with hemiparalysis (Kafri, Potter & Myint, 2014;Nalepa et al, 2019;Yoo et al, 2016), pediatric scoliosis (Matusik, Durmala & Matusik, 2016), or Turner's syndrome (i.e., abnormally small body) (Guedes et al, 2010). However, no such studies have been conducted on the APTs.…”

Section: Discussionmentioning

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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“…In addition, some individuals may not fit appropriately on the scanning table and additional procedures will need to be performed to accommodate those individuals [33][34]. Some studies have attempted to create group specific (e.g., children, professional athletes, obese women) prediction equations for Skinfold or BIA measurements using DXA as the criterion [3,27,[36][37][38]. However, it is not clear if body fat percentage measured with skinfold and BIA is similar to those measured with DXA in college students.…”

Section: Introductionmentioning

confidence: 99%

Body fat prediction equations for skinfold and bioelectrical impedance analysis using dual-energy x-ray absorptiometry data as the criterion.

Grove¹,

Hung²

2017

physical-therapy

1

0

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Background and purposeBody composition evaluation during health screenings and physical examination is important for health professionals (including physical therapists) to categorize health risk and prescribe appropriate exercise interventions. In addition to measuring bone mineral density, dual energy x-ray absorptiometry (DXA) can provide precise measurement of body fat percentage with minimal radiation exposure. However, having access to DXA is very costly and other common body fat measurements are no very accurate. The purpose of this study was to develop body fat prediction equations for bioelectrical impedance analysis (BIA) and skinfold measurement, using DXA data as the criterion. MethodsThis was a within-group study with repeated measures. Sixty three college age students participated in the study. Subject's body fat percentage was examined with DXA, BIA, and the 3-site skinfold measurements. ResultsBody fat percentage measured with DXA (26.27%) is significantly higher than those measured with skinfold (17.64%) and BIA (20.70%). The DXA criterion regression equations were created for skinfold and BIA: DXA%BF=4.65+0.43 * S3SF (sum of 3 site skinfold in mm); DXA%BF=3.79+1.09 * BIA%BF. The new regression equations were further validated using 75%-25%subject cross-validation. DiscussionBody fat percentage varies greatly among different measurements. Adjustments are necessary to accurately predict body fat percentage when using skinfold or BIA techniques at a clinical setting. The limitation of the study is that it is unclear if the results can be generalized to subjects of a different age group and ethnicities. Implication for physiotherapy practiceObtaining an accurate body fat percentage measurement is important for health promotion and cardiovascular risk screening. Although skin-fold and BIA equipment are more readily available, their results underestimate the body fat percentage and may mislead clinicians on the wellbeing of the patient.

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“…Some studies have attempted to create group specific (e.g., children, professional athletes, obese women) prediction equations for Skinfold or BIA measurements using DXA as the criterion [3,27,[36][37][38] [10], were excluded from the study. Subjects with obesity may not fit on the DXA testing platform, which can hamper the DXA testing results.…”

Section: Introductionmentioning

confidence: 99%

Body fat prediction equations for skinfold and bioelectrical impedance analysis using dual-energy x-ray absorptiometry data as the criterion.

Grove¹,

Hung²

2017

J Phys Ther Sports Med

0

View full text Add to dashboard Cite

Background and purposeBody composition evaluation during health screenings and physical examination is important for health professionals (including physical therapists) to categorize health risk and prescribe appropriate exercise interventions. In addition to measuring bone mineral density, dual energy x-ray absorptiometry (DXA) can provide precise measurement of body fat percentage with minimal radiation exposure. However, having access to DXA is very costly and other common body fat measurements are no very accurate. The purpose of this study was to develop body fat prediction equations for bioelectrical impedance analysis (BIA) and skinfold measurement, using DXA data as the criterion. MethodsThis was a within-group study with repeated measures. Sixty three college age students participated in the study. Subject's body fat percentage was examined with DXA, BIA, and the 3-site skinfold measurements. ResultsBody fat percentage measured with DXA (26.27%) is significantly higher than those measured with skinfold (17.64%) and BIA (20.70%). The DXA criterion regression equations were created for skinfold and BIA: DXA%BF=4.65+0.43 * S3SF (sum of 3 site skinfold in mm); DXA%BF=3.79+1.09 * BIA%BF. The new regression equations were further validated using 75%-25%subject cross-validation. DiscussionBody fat percentage varies greatly among different measurements. Adjustments are necessary to accurately predict body fat percentage when using skinfold or BIA techniques at a clinical setting. The limitation of the study is that it is unclear if the results can be generalized to subjects of a different age group and ethnicities. Implication for physiotherapy practiceObtaining an accurate body fat percentage measurement is important for health promotion and cardiovascular risk screening. Although skin-fold and BIA equipment are more readily available, their results underestimate the body fat percentage and may mislead clinicians on the wellbeing of the patient.

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A specific bioelectrical impedance equation to predict body composition in Turner's syndrome

Cited by 4 publications

References 24 publications

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

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

Body fat prediction equations for skinfold and bioelectrical impedance analysis using dual-energy x-ray absorptiometry data as the criterion.

Body fat prediction equations for skinfold and bioelectrical impedance analysis using dual-energy x-ray absorptiometry data as the criterion.

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