Development and validation of two equations based on anthropometry, estimating body fat for the Greek adult population

Kanellakis, Spyridon; Skoufas, Efstathios; Khudokonenko, Vladlena; Apostolidou, Eftychia; Gerakiti, Loukia; Andrioti, Maria-Chrysi; Bountouvi, Evangelia; Μanios, Yannis

doi:10.1002/oby.21736

Cited by 19 publications

(17 citation statements)

References 26 publications

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“…The best results were obtained using the methods of Kanellakis et al 14 and Tran and Weltman. 17 Both mathematical models developed in this study showed better statistical results than other equations, and those were the only models which did not differ from BF% in paired t-test.…”

Section: Resultsmentioning

confidence: 99%

Estimation of Female Body Fat Percentage Based on Body Circumferences

Salamunes

Stadnik

Neves

2018

Rev Bras Med Esporte

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Introduction: The increase in the prevalence of obesity entails the need for accurate low-cost methods to estimate body fat percentage (BF%). Objective: The aim of this study was to develop mathematical models to estimate the BF% of young women from southern Brazil using inexpensive equipment, based on body circumferences (BC), considering the shortage of specific studies of this population. Methods: Subjects were women (n=130) aged 18 to 35 years (26.06±4.41 years), from the city of Curitiba. Body mass and stature were measured and used to estimate body mass index (BMI), while BC measurements of the arm, forearm, waist (narrowest point and umbilicus), abdomen, hip, thigh and leg were taken for use in the mathematical models. Dual-Energy X-Ray Absorptiometry (DXA) equipment recorded the BF%. Pearson's correlation was used for anthropometric variables and age in association with BF%. The indicators with best correlations were used to estimate linear regression mathematical models for prediction of BF%. The results of the two models and of nine anthropometric equations were compared to those obtained with the DXA using Pearson's correlation coefficient and paired t-test. Results: Age was not significantly correlated with BF% (r=0.113 and p=0.200). The BCs with the highest correlations with BF% were abdomen, hip and waist -umbilicus (r=0.697, 0.682, 0.660, respectively, and p<0.001). Eight equations showed positive correlation with BF%, but only the results obtained with the models estimated in this study did not differ from those of DXA, with paired t-test. Mathematical models were developed with three (r=0.744, r²=0.554; t=0.16 and p=0.869) and six (r=0.768, r²=0.591; t=-0.04 and p=0.967) anthropometric variables. Conclusion: The use of mathematical models developed for estimating BF% based on body circumference and body mass is considered feasible. Level of Evidence II; Diagnostic studies -Investigating a diagnostic test.Keywords: Body composition; X-ray absorptiometry; Anthropometry; Women. (26,06 ± 4,41 anos) (r = 0,697, 0,682, 0,660, respectivamente, com p < 0,001 (r = 0,697, 0,682, 0,660, respectivamente, con p < 0,001 RESUMO Introdução: O aumento da prevalência de obesidade implica a necessidade de métodos precisos e de baixo custo para estimar o percentual de gordura corporal (GC%). Objetivo: O objetivo deste estudo foi desenvolver modelos matemáticos para calcular o GC% de mulheres jovens do sul do Brasil, usando equipamentos de baixo custo, com base em circunferências corporais (CC), considerando a escassez de estudos específicos dessa população. Métodos: Foram avaliadas mulheres (n = 130) com idade de 18 a 35 anos

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Section: Resultsmentioning

confidence: 99%

Estimation of Female Body Fat Percentage Based on Body Circumferences

Salamunes

Stadnik

Neves

2018

Rev Bras Med Esporte

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“…Anthropometric equations are widely used to estimate body composition and recently new equations have been developed for specific populations 5 - 9 . The equations are developed following three general steps 10 .…”

Section: Introductionmentioning

confidence: 99%

“…Las ecuaciones antropométricas son ampliamente usadas para estimar la composición corporal y, recientemente, nuevas ecuaciones han sido desarrolladas para poblaciones específicas 5 - 9 . Las ecuaciones son desarrolladas generalmente en tres pasos 10 .…”

Section: Introductionunclassified

Development and validation of anthropometric equations to estimate body composition in adult women

Aristizábal

Estrada-Restrepo²,

García³

2018

Colomb Med

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Objective: To develop anthropometric equations to predict body fat percentage (BF%). Methods: In 151 women (aged 18-59) body weight, height, eight- skinfold thickness (STs), six- circumferences (CIs), and BF% by hydrodensitometry were measured. Subjects data were randomly divided in two groups, equation-building group (n= 106) and validation group (n= 45). The equation-building group was used to run linear regression models using anthropometric measurements as predictors to find the best prediction equations of the BF%. The validation group was used to compare the performance of the new equations with those of Durnin-Womersley, Jackson-Pollock and Ramirez-Torun. Results: There were two preferred equations: Equation 1= 11.76 + (0.324 x tricipital ST) + (0.133 x calf ST) + (0.347 x abdomen CI) + (0.068 x age) - (0.135 x height) and Equation 2= 11.37 + (0.404 x tricipital ST) + (0.153 x axilar ST) + (0.264 x abdomen CI) + (0.069 x age) - (0.099 x height). There were no significant differences in BF% obtained by hydrodensitometry (31.5 ±5.3) and Equation 1 (31.0 ±4.0) and Equation 2 (31.2 ±4.0). The BF% estimated by Durning-Womersley (35.8 ±4.0), Jackson-Pollock (26.5 ±5.4) and Ramirez-Torun (32.6 ±4.8) differed from hydrodensitometry (p <0.05). The interclass correlation coefficient (ICC) was high between hydrodensitometry and Equation 1 (ICC= 0.77), Equation 2 (ICC= 0.76), and Ramirez-Torun equation (ICC= 0.75). The ICC was low between hydrodensitometry and Durnin-Womersley (ICC= 0.51) and Jackson-Pollock (ICC= 0.53) equations. Conclusion: The new Equations-1 and 2, performed better than the commonly used anthropometric equations to predict BF% in adult women.

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“…The use of PBF prediction equations that utilize easy to obtain inputs (predictor variables) is another option for both the exercise science researcher and fitness practitioner. Several PBF prediction equations, utilizing body mass index (BMI) as the main input, have already been validated in general populations [3,4]. However, little is known about the psychometric properties of such PBF prediction equations in generally healthy younger adults such as college students.…”

Section: Introductionmentioning

confidence: 99%

Equivalence Reliability and Convergent Validity of Percent Body Fat Prediction Equations

Hart¹

2019

AJSSM

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Background: The fitness professional may often benefit from the use of a simple equation in determining a health outcome for an individual in lieu of a more complicated or expensive procedure. Therefore, the purpose of this study was to examine the reliability and validity of several standard prediction equations for percent body fat (PBF). Methods: Data used for this study came from a body composition assessment of N = 131 college students. Five different PBF prediction equations were used, with body mass index (BMI), age, and sex as inputs for each (PBFEQ1 thru PBFEQ5). Additionally, PBF using a bioelectric impedance (BIA) handheld device (PBFHH) was measured for each participant. Equivalence reliability was examined across the five PBF prediction equations using different analysis of variance (ANOVA) models of the intraclass correlation coefficient (ICC). Convergent validity between the prediction equations and PBFHH was determined by examining Pearson correlation coefficients and Bland and Altman limits of agreement (LOA). Reliability and validity was also examined for obesity classification using the Kappa statistic. Results: Reliability across the five PBF prediction equations was excellent for all ICC models in both female (ICCs > .985) and male (ICCs > .976) analyses. PBFHH scores adequately converged with scores from each prediction equation in both female (rs > .913) and male (rs > .817) analyses. LOA between PBFHH and PBFEQ5 indicate small to moderate bias of 4.0 ± 5.1% and 4.7 ± 7.9% in female and male analyses, respectively. Finally, reliability and validity of the prediction equations to classify participants into obese and non-obese categories ranged from moderate to almost perfect. Conclusion: This study provides psychometric evidence supporting the use of PBF prediction equations in a college student population.

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Development and validation of two equations based on anthropometry, estimating body fat for the Greek adult population

Cited by 19 publications

References 26 publications

Estimation of Female Body Fat Percentage Based on Body Circumferences

Estimation of Female Body Fat Percentage Based on Body Circumferences

Development and validation of anthropometric equations to estimate body composition in adult women

Equivalence Reliability and Convergent Validity of Percent Body Fat Prediction Equations

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