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

Classified as probably not a substantial claim.

Predictive equations must be selected for subjects with similar characteristics regarding gender, age group, pubertal stage, ethnicity, and nutritional status.

“However, it is essential that predictive equations are selected for subjects with similar characteristics regarding gender, age group, pubertal stage, ethnicity, and nutritional status (20, 21).”

• cites [20] Achamrah, 2018, Comparison of body composition assessment by DXA and BIA according to the body mass index: a retrospective study on 3655 measures., PLoS One. sourcePartly supported

  The Discussion (page unavailable) recommends population-specific BIA equations or equations that account for age, warning that equations developed in young subjects can be biased in older subjects. The Introduction (page unavailable) identifies age, ethnicity, and body weight as possible contributors to differing results, but the paper does not give the claimed selection rule covering gender and pubertal stage. (LLM, conf=0.85)

  Experimental — accuracy not yet measured
• cites [21] Sergi, 2017, Measurement of lean body mass using bioelectrical impedance analysis: a consideration of the pros and cons., Aging Clin Exp Res. sourceNot checked — no full text of the source

May combine two claims.

DXA measurements using the current equipment had CV of 0.74%, 0.28%, and 0.26% for FM, BMC, and LST, and TEM of 0.25, 0.02, and 0.25 kg, respectively.

“As described elsewhere, CV for FM, bone mineral content (BMC), and lean soft tissue (LST) using the current equipment were 0.74, 0.28, and 0.26%, respectively. TEM were 0.25, 0.02, and 0.25 kg to FM, BMC, and LST, respectively (32).”

• cites [32] Langer, 2016, Validity of bioelectrical impedance analysis to estimation fat-free mass in the army cadets., Nutrients. sourceSupported

Probably not a substantial claim: may not pass S3 (load-bearing).

BIA is the most used tool to assess body composition worldwide.

“These characteristics make BIA the most used tool to assess body composition worldwide (22).”

• cites [22] de-Mateo-Silleras, 2019, Bioelectrical impedance vector analysis in obese and overweight children., PLoS One. sourcePartly supported

  The Discussion describes bioimpedance analysis as “one of the most used in clinical practice,” and the Introduction lists BIA among methods commonly used in clinical settings. Neither passage establishes that it is the single most used body-composition tool worldwide. (LLM, conf=0.85)

  Experimental — accuracy not yet measured

Classified as probably not a substantial claim.

The use of DXA to derive BIA equations has been widely accepted.

“Although DXA cannot be considered the gold standard for the determination of FFM at the molecular level, and the four-compartment model (4C) is the most suitable reference method to assess FM and FFM at the molecular level (12), due to the complexity of the technique (13), the use of DXA to derive BIA equations has been widely accepted (14, 15).”

• cites [14] Beaudart, 2020, Equation models developed with bioelectric impedance analysis tools to assess muscle mass: a systematic review., Clin Nutr ESPEN. sourceSupported
• cites [15] Sun, 2003, Development of bioelectrical impedance analysis prediction equations for body composition with the use of a multicomponent model for use in epidemiologic surveys., Am J Clin Nutr. sourceNot checked — no full text of the source

Probably not a substantial claim: may not pass S3 (load-bearing).

The four-compartment model is the most suitable reference method to assess FM and FFM at the molecular level.

“Although DXA cannot be considered the gold standard for the determination of FFM at the molecular level, and the four-compartment model (4C) is the most suitable reference method to assess FM and FFM at the molecular level (12), due to the complexity of the technique (13), the use of DXA to derive BIA equations has been widely accepted (14, 15).”

• cites [12] Heymsfield, 2015, Multi-component molecular-level body composition reference methods: evolving concepts and future directions., Obes Rev. sourcePartly supported

  The Body Volume Approach section (page unavailable) says the four-component model improves the accuracy of body-fat estimates over two- and three-component models. But the Conclusions (page unavailable) say there is no agreed reference or gold-standard method. The paper therefore supports using the model as a reference for fat mass, not the stronger claim that it is the most suitable method for both FM and FFM. (LLM, conf=0.85)

  Experimental — accuracy not yet measured

Classified as probably not a substantial claim.

Resistance of a conductor is expressed by R = ρL2/V, so V = ρL2/R, where ρ is the conductor resistivity, L is the length, and V is volume.

“R of the conductor is expressed by R = ρL2/V, so V = ρL2/R, wherein ρ is the conductor resistivity, L is the length, and V is volume (48, 49).”

• cites [48] Houtkooper, 1996, Why bioelectrical impedance analysis should be used for estimating adiposity., Am J Clin Nutr. sourceNot checked — no full text of the source
• cites [49] Khalil, 2014, The theory and fundamentals of bioimpedance analysis in clinical status monitoring and diagnosis of diseases., Sensors (Basel). sourceSupported

Probably not a substantial claim: may not pass S3 (load-bearing).

Adolescence is a phase of profound morphological changes, which include body composition.

“Considering that adolescence is a phase of profound morphological changes, which include body composition (4, 50, 51)”

• cites [4] Kyle, 2015, Body composition during growth in children: limitations and perspectives of bioelectrical impedance analysis., Eur J Clin Nutr. sourceNot checked — no full text of the source
• cites [50] Koury, 2019, Fat-free mass in adolescent athletes: accuracy of bioimpedance equations and identification of new predictive equations., Nutrition. sourceNot checked — no full text of the source
• cites [51] Takahashi, 2019, Influence of sexual maturation status on the relationship between body adiposity indicators and age: a cross-sectional study., BMC Res Notes. sourceSupported

May combine two claims.

DXA is one of the standard reference methods and non-invasive measurements for FFM and FM in children and adolescents.

“Several techniques have been used to assess the body composition of children and adolescents, and dual X-ray absorptiometry (DXA) is one of the standard reference methods and non-invasive measurements for FFM and FM (8–10).”

• cites [8] Helba, 2009, Pediatric body composition analysis with dual-energy X-ray absorptiometry., Pediatr Radiol. sourceNot checked — no full text of the source
• cites [9] Kuriyan, 2018, Body composition techniques., Indian J Med Res. sourcePartly supported

  The Models of body composition section describes DEXA as a rapid, non-invasive method for whole-body composition measurement, and the Body composition in infants and children section lists it among techniques used to measure body fat in children. The Laboratory methods section says DEXA estimates body fat and lean tissue mass, but calls it a gold standard only for bone mineral density—not a standard reference method for FM and FFM in children and adolescents. Page numbers were not provided in the supplied passages. (LLM, conf=0.83)

  Experimental — accuracy not yet measured
• cites [10] de Macêdo Cesário, 2021, Body adiposity index to analyze the percentage of fat in young men aged between 7 and 17 years., Am J Hum Biol. sourcePartly supported

  The Body composition section (page unavailable) calls DXA a gold-standard parameter for body-composition analysis and describes its use with pediatric participants. The paper uses DXA to assess body-fat percentage, but the passages do not specifically address fat-free mass (FFM) or describe DXA as non-invasive. (LLM, conf=0.85)

  Experimental — accuracy not yet measured

Probably not a substantial claim: may not pass S3 (load-bearing).

BIA is one of the most convenient techniques for assessing body composition in a clinical setting and in epidemiological approaches, mainly because it is easy to apply, fast, and non-invasive, in addition to having a relatively low cost.

“The BIA is one of the most convenient techniques for assessing body composition in a clinical setting and in epidemiological approaches, mainly, because it is easy to apply, fast, and non-invasive, in addition to having a relatively low cost (5, 45, 46).”

• cites [5] Marra, 2019, Assessment of body composition in health and disease using bioelectrical impedance analysis (BIA) and dual energy X-ray absorptiometry (DXA): a critical overview., Contrast Media Mol Imaging. sourcePartly supported

  The Introduction (page unavailable) describes BIA as widely used for epidemiological and clinical purposes, noninvasive, and low cost. It does not state that BIA is easy to apply or fast; the reference to monitoring over the short and long term in Section 2 concerns follow-up, not the speed of a measurement. (LLM, conf=0.83)

  Experimental — accuracy not yet measured
• cites [45] Grilo, 2020, Validity of bioelectrical impedance to estimate fat-free mass in boys with Duchenne muscular dystrophy., PLoS One. sourcePartly supported

  The Introduction describes BIA as simple, practical, and low-cost for evaluating body composition in clinical practice; the Discussion calls it easy to apply and inexpensive compared with DXA. Our copy does not establish its use in epidemiological approaches or explicitly describe it as fast or non-invasive. (LLM, conf=0.84)

  Experimental — accuracy not yet measured
• cites [46] Teigen, 2017, The use of technology for estimating body composition: strengths and weaknesses of common modalities in a clinical setting., Nutr Clin Pract. sourceNot checked — no full text of the source

May combine two claims.

In the systematic review, most equations were developed using DXA as a reference method, but a limited number of studies provided cross-validation results.

“Similar to this study, most of the equations were developed using DXA as a reference method, but a limited number of studies provided cross-validation results.”

• cites [7] Silva, 2013, A PRISMA-driven systematic review of predictive equations for assessing fat and fat-free mass in healthy children and adolescents using multicomponent molecular models as the reference method., J Obes. sourceSupported

May combine two claims.

In the systematic review, of 33 equations analyzed, only seven were cross-validated, two studies examined the PE in the FFM estimate, none examined the CCC, and agreement between methods was included in only three studies.

“The authors of the systematic review identified that, of the 33 equations analyzed, only seven were cross-validated, two studies examined the PE in the FFM estimate, and none of the studies examined the CCC, while the agreement between the methods was included only in three studies.”

• cites [7] Silva, 2013, A PRISMA-driven systematic review of predictive equations for assessing fat and fat-free mass in healthy children and adolescents using multicomponent molecular models as the reference method., J Obes. sourceSupported

Probably not a substantial claim: may not pass S3 (load-bearing).

The age at which each stage of puberty occurs can vary considerably.

“and that the age at which each stage of puberty occurs can vary considerably (52)”

• cites [52] Cintra Ide, 2013, Body fat percentiles of Brazilian adolescents according to age and sexual maturation: a cross-sectional study., BMC Pediatr. sourceSupported

Probably not a substantial claim: may not pass S3 (load-bearing).

The 4C model is the most appropriate reference method for assessing FM and FFM at the molecular level.

“The 4C model is the most appropriate reference method for assessing FM and FFM at the molecular level (12).”

• cites [12] Heymsfield, 2015, Multi-component molecular-level body composition reference methods: evolving concepts and future directions., Obes Rev. sourcePartly supported

  The Body Volume Approach section says the four-component model improves the accuracy of body-fat estimates over two- and three-component models. But the Conclusions state that there is no agreed reference or gold-standard method, so the paper does not establish the 4C model as the most appropriate method for assessing FM and FFM. (LLM, conf=0.88)

  Experimental — accuracy not yet measured

Classified as probably not a substantial claim. May combine two claims.

Due to the complexity of the 4C technique, the use of DXA to derive BIA equations has been widely accepted.

“However, due to the complexity of the technique (13), the use of DXA to derive BIA equations has been widely accepted (14, 15).”

• cites [13] Silva, 2006, Body fat measurement in adolescent athletes: multicompartment molecular model comparison., Eur J Clin Nutr. sourceNot checked — no full text of the source
• cites [14] Beaudart, 2020, Equation models developed with bioelectric impedance analysis tools to assess muscle mass: a systematic review., Clin Nutr ESPEN. sourceSupported
• cites [15] Sun, 2003, Development of bioelectrical impedance analysis prediction equations for body composition with the use of a multicomponent model for use in epidemiologic surveys., Am J Clin Nutr. sourceNot checked — no full text of the source

The quote only partly states this claim.

For only three of the eight published BIA equations (Deurenberg et al., Horlick et al., Wang et al.), no association was found between the mean and the difference of the BIA and DXA methods (p > 0.05).

“The analysis of the validity of the eight equations (Table 3), developed in other countries, showed that, only for three equations (23, 41, 44), no association was found between the mean and the difference of the BIA and DXA methods (p > 0.05).”

The quote only partly states this claim.

The mean difference in the Bland-Altman plot was not different from zero in only two of the eight published equations (Sun et al., Schaefer et al.; p > 0.05).

“The mean difference in the Bland-Altman plot was not different from zero in just two equations (15, 42; p > 0.05).”

May combine two claims.

The limits of agreement for FFM between DXA and the BIA equation derived in this study ranged between −4.0 and 3.7 kg in the cross-validation group, indicating good agreement.

“The LOA ranged between −4.0 and 3.7 kg to the cross-validation group, indicating a good agreement between the developed equation and the reference method.”

May combine two claims.

No significant interaction with sex was found for any of the main independent predictors, so girls and boys were combined for the development of the prediction models.

“In preliminary analyses, we found no significant interaction with sex for any of the main independent predictor, and, thus, girls and boys were combined for the development of the prediction models.”

The quote only partly states this claim.

The newly developed equation showed better agreement with DXA than the eight published equations developed in other countries for Brazilian adolescents.

“the new equation for FFM showed better agreement when compared with that of the equations developed in other countries.”

May combine two claims.

The developed equation had a coefficient of determination (r2) of 0.95 and a standard error of the estimate (SEE) of 2.5 kg in the development model.

“The performance of the developed model can be observed by high coefficients of determination (r2 = 0.95) and low SEE (SEE = 2.5 kg).”

May combine two claims.

All eight published equations showed high limits of agreement, indicating poor agreement with the reference method.

“All equations showed high LOA, indicating poor agreement with the reference method (Figure 2).”

May combine two claims.

The equation developed in this study showed a high coefficient of determination and good limits of agreement in relation to the reference method.

“The equation developed in our study showed a high coefficient of determination and good limits of agreement in relation to the reference method”

• AssumptionRests on an assumption: Participants were euhydrated during body composition measurements.

Probably not a substantial claim: may not pass S3 (load-bearing).

The sample size calculation required 171 participants for the development of the predictive equation.

“For the sample size calculation, using FFM as a primary outcome, we considered a medium to small effect size (0.12) with five predictors (independent variables), with a type I error of 5% and a power of 95%. Using these parameters, a total of 171 participants were required.”

Probably not a substantial claim: may not pass S3 (load-bearing).

Multicollinearity was assessed using VIF and tolerance, with VIF < 10 or tolerance > 0.1 considered appropriate.

“If more than one variable remained in the model, and to assess multicollinearity, a variance inflation factor (VIF) and the tolerance (reciprocal of VIF) were calculated for each independent variable, and a VIF < 10 or tolerance higher than 0.1 was considered appropriate (36, 37).”

• cites [36] Guo, 1996, Statistical methods for the development and testing of predictive equations., Hum Body Composit.Not checked yet

  Not checked in the free run.

• cites [37] Ndagire, 2018, Prediction equations for body composition of children and adolescents aged 8-19 years in Uganda using deuterium dilution as the reference technique., Clin Nutr ESPEN. sourceNot checked — no full text of the source

Classified as probably not a substantial claim.

The sample was randomly divided into development (n = 172) and cross-validation (n = 85) groups.

“After their inclusion in the study, the sample was randomly divided into two groups, namely, the development of a predictive equation for FFM (n = 172) and cross-validation (n = 85).”

Probably not a substantial claim: may not pass S3 (load-bearing).

DXA measurements were performed following the recommendations proposed by Nanna et al.

“Measurements were performed following the recommendations proposed by Nanna et al. (31).”

• cites [31] Nana, 2015, Methodology review: using dual-energy X-ray absorptiometry (DXA) for the assessment of body composition in athletes and active people., Int J Sport Nutr Exerc Metab. sourceNot checked — no full text of the source

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

The BIA equipment was periodically calibrated with an electrical resistor and capacitor, with normal calibration values defined as R ≤ 500 ± 5 Ω and Xc ≤ 52 ± 0.5 Ω.

“The BIA equipment validity measurement was periodically measured with an electrical resistor and capacitor. Calibration values were considered normal if the R was not higher than 500 ± 5 ohm (Ω) and Xc was not higher than 52 ± 0.5 Ω, according to the manufacturer’s instructions.”

May combine two claims.

Reproducibility of BIA measurements was calculated in a previous study with 46 women, yielding CV of 0.17% and 0.72% for R and Xc, and TEM of 0.76 Ω (0.22%) and 0.35 Ω (0.92%) for R and Xc.

“To verify the quality of the measurements obtained by the equipment, reproducibility was calculated in a previous study with 46 women from the northeast region of Brazil. The results obtained were a coefficient of variation (CV) of 0.17 and 0.72% for R and Xc, respectively, and a technical error of measurement (TEM) of 0.76 Ω (0.22%) and 0.35 Ω (0.92%) for R and Xc, respectively (17).”

• cites [17] Costa, 2022, Development and cross-validation of predictive equations for fat-free mass and lean soft tissue mass by bioelectrical impedance in Brazilian women., Eur J Clin Nutr. sourceNot checked — no full text of the source

Probably not a substantial claim: may not pass S3 (load-bearing).

Anthropometric measurements were performed by one physical education professional who was properly trained in accordance with international recommendations.

“Anthropometric measurements were performed by one physical education professional, who was properly trained in accordance with international recommendations (29).”

• cites [29] Lohman, 1988, Anthropometric Standardization Reference Manual.Not checked yet

  Not checked in the free run.

Probably not a substantial claim: may not pass S3 (load-bearing).

DXA was performed by a laboratory technician experienced in radiological evaluation.

“Dual X-ray absorptiometry was performed with Lunar Prodigy equipment, NRL 41990 model (GE Lunar, Madison, WI, United States), by a laboratory technician experienced in radiological evaluation.”

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

Normality of residuals and homogeneity of variance were tested during model development.

“During model development, normality of residuals and homogeneity of variance were tested.”

Probably not a substantial claim: may not pass S3 (load-bearing).

The study protocol was approved by the Research Ethics Committee of the University Hospital Onofre Lopes-HUOL/UFRN.

“The overarching protocol was approved by the Research Ethics Committee of the University Hospital Onofre Lopes—HUOL/UFRN (#34804414.7.0000.5292).”

Probably not a substantial claim: may not pass S3 (load-bearing).

The World Health Organization defines adolescents as young people aged 10-19 years.

“The World Health Organization (WHO) defines adolescents as young people aged 10–19 years (6).”

• cites [6] 2003, Adolescent Friendly Health Services: An Agenda for Change.Not checked yet

  Not checked in the free run.

May combine two claims.

Although the sample was not representative of adolescents across Brazil, the relative body size of these adolescents seems to resemble that of other adolescents of the country living in larger cities.

“Thus, although the sample was not representative of adolescents across Brazil, the relative body size of these adolescents seems to resemble that of other adolescents of the country living in larger cities.”

May combine two claims.

Koury et al. developed gender-specific equations including skeletal maturity for boys and menarche status for girls, demonstrating good performance, but there was no cross-validation of the new equations.

“The authors developed gender-specific equations for the study sample, including skeletal maturity for boys and menarche status for girls as dependent variables, demonstrating good performance; however, there was no cross-validation of the new equations.”

• cites [50] Koury, 2019, Fat-free mass in adolescent athletes: accuracy of bioimpedance equations and identification of new predictive equations., Nutrition. sourceNot checked — no full text of the source

May combine two claims.

DXA use requires high-cost equipment and specialized technical personnel, making it unfeasible in clinical and field situations.

“However, its use requires high-cost equipment and specialized technical personnel, which makes it unfeasible in clinical and field situations (11).”

• cites [11] Hastuti, 2016, Proposal of new body composition prediction equations from bioelectrical impedance for Indonesian men., Eur J Clin Nutr. sourceNot checked — no full text of the source

Classified as probably not a substantial claim.

The use of predictive equations in subjects with different characteristics from those of the group of origin of the equations is questionable.

“Although the use of predictive equations in subjects with different characteristics from those presented by the group of origin of the equations is questionable (15)”

• cites [15] Sun, 2003, Development of bioelectrical impedance analysis prediction equations for body composition with the use of a multicomponent model for use in epidemiologic surveys., Am J Clin Nutr. sourceNot checked — no full text of the source

May combine two claims.

A study by Koury et al. in Brazil with 368 adolescent athletes aged 11-16 years tested the validity of three equations and concluded that none was adequate for the evaluated sample.

“A study carried out by Koury et al. (50) in Brazil, with a sample of 368 adolescent athletes aged 11–16 years, tested the validity of three equations (23, 41, 56), concluding that none of them was adequate for the evaluated sample.”

• cites [50] Koury, 2019, Fat-free mass in adolescent athletes: accuracy of bioimpedance equations and identification of new predictive equations., Nutrition. sourceNot checked — no full text of the source

May combine two claims.

Lean body mass contains a large amount of water and presents low resistance to the flow of electric current, while fat mass has greater resistance to the passage of current.

“Thus, as the lean body mass contains a large amount of water, it presents low R to the flow of electric current, while the FM has greater R to the passage of current.”

May combine two claims.

This study included a sample of adolescents from only one region of the country, and ethnicity was not assessed.

“This study included a sample of adolescents from only one region of the country, and ethnicity was not assessed.”

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

Hydration status was not determined to ensure a euhydration state prior to body composition measures, although self-reported water intake was within the normal range, and pale morning urine was reported.

“Hydration status was not determined to ensure a euhydration state prior to body composition measures, although self-reported water intake was within the normal range, and pale morning urine was reported.”