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Is the Pair-wise Contrast of Fatfolds Significant in Determining Body Composition

Dados Bibliográficos

ID6136042
AutoresKomei Hattori (Ibaraki University, autor correspondente)
Ano1994
Volume102
Fascículo1
Páginas75-84
Data de publicação1994-01-01
Peer ReviewedSim
Open AccessSim
TipoARTICLE
PeriódicoAnthropological Science (JOURNAL)
Identificadores do periódicoISSN: 0918-7960 • E-ISSN: 1348-8570
EditoraAnthropological Society of Nippon (PUBLISHER • JP)
DOI10.1537/ase.102.75
OpenAlexW2086805372
IdiomaEN
Referências citadas5

Regional variability of skinfold thickness differs from individual to individual. This may be affected by differences in total body composition. If so, individual's fat distribution patterns may contribute to the prediction of body composition. On this premise, the regression relationships between body composition and fat distribution patterns which is represented by the pair-wise contrast of fatfolds, were analyzed by the quantification method of the first type. This method is a multivariate analysis method for categorical data. First, skinfold thickness was measured at 9 sites. From these 9 sites, independent pair-wise combinations of measures were established, for example subscapular>abdomen. Within each pair-wise contrast if A>B then the statement is true and a value of 1 was attached. If the statement is false a 0 was recorded. Thus the pair-wise relationships of skinfold measures were expressed as categorical data. These data subsequently served as predictor variables for multivariate regression analyses with the dependent variable being fat mass. The results suggested that regardless of gender, the series of pair-wise contrasts of fatfolds significantly correlated with fat mass. However, the reliability of the equations is not sufficient for the prediction of body composition

Body mass index · Categorical variable · Classification of obesity · Composition (language · Contrast (vision · Fat mass · Multivariate analysis · Multivariate statistics · Regression · Regression analysis · Statistics · Body Composition Measurement Techniques · Computer Science · Effects of Environmental Stressors on Livestock · Mathematics · Medicine · Artificial Intelligence · Internal Medicine

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