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Record W2887790776 · doi:10.3390/nu10081086

Comparison of Bioelectrical Impedance Analysis, Slaughter Skinfold-Thickness Equations, and Dual-Energy X-ray Absorptiometry for Estimating Body Fat Percentage in Colombian Children and Adolescents with Excess of Adiposity

2018· article· en· W2887790776 on OpenAlexfundno aff
Katherine González‐Ruíz, María Medrano, Jorge Enrique Correa‐Bautista, Antônio García‐Hermoso, Daniel Humberto Prieto‐Benavides, Alejandra Tordecilla‐Sanders, César Agostinis‐Sobrinho, María Correa‐Rodríguez, Jacqueline Schmidt‐RioValle, Emilio González‐Jiménez, Robinson Ramírez‐Vélez

Bibliographic record

VenueNutrients · 2018
Typearticle
Languageen
FieldMedicine
TopicBody Composition Measurement Techniques
Canadian institutionsnot available
FundersEgg Farmers of Canada
KeywordsBioelectrical impedance analysisDual-energy X-ray absorptiometryMedicineOverweightPopulationBody fat percentageLimits of agreementBland–Altman plotDual energySkinfold thicknessMathematicsAnimal scienceAnthropometryNuclear medicineObesityInternal medicineBody mass indexOsteoporosisBone mineralBiology

Abstract

fetched live from OpenAlex

Dual-energy X-ray absorptiometry (DXA) has been considered a reference method for measuring body fat percentage (BF%) in children and adolescents with an excess of adiposity. However, given that the DXA technique is impractical for routine field use, there is a need to investigate other methods that can accurately determine BF%. We studied the accuracy of bioelectrical impedance analysis (BIA) technology, including foot-to-foot and hand-to-foot impedance, and Slaughter skinfold-thickness equations in the measurement of BF%, compared with DXA, in a population of Latin American children and adolescents with an excess of adiposity. A total of 127 children and adolescents (11–17 years of age; 70% girls) from the HEPAFIT (Exercise Training and Hepatic Metabolism in Overweight/Obese Adolescent) study were included in the present work. BF% was measured on the same day using two BIA analysers (Seca® 206, Allers Hamburg, Germany and Model Tanita® BC-418®, TANITA Corporation, Sportlife Tokyo, Japan), skinfold measurements (Slaughter equation), and DXA (Hologic Horizon DXA System®, Quirugil, Bogotá, Columbia). Agreement between measurements was analysed using t-tests, Bland–Altman plots, and Lin’s concordance correlation coefficient (ρc). There was a significant correlation between DXA and the other BF% measurement methods (r > 0.430). According to paired t-tests, in both sexes, BF% assessed by BIA analysers or Slaughter equations differ from BF% assessed by DXA (p < 0.001). The lower and upper limits of the differences compared with DXA were 6.3–22.9, 2.2–2.8, and −3.2–21.3 (95% CI) in boys and 2.3–14.8, 2.4–20.1, and 3.9–18.3 (95% CI) in girls for Seca® mBCA, Tanita® BC 420MA, and Slaughter equations, respectively. Concordance was poor between DXA and the other methods of measuring BF% (ρc < 0.5). BIA analysers and Slaughter equations underestimated BF% measurements compared to DXA, so they are not interchangeable methods for assessing BF% in Latin American children and adolescents with excess of adiposity.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.036
Threshold uncertainty score0.072

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.017
GPT teacher head0.321
Teacher spread0.304 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations60
Published2018
Admission routes1
Has abstractyes

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