Principal components analysis of morphological measures in the Québec family study: Familial correlations

Abstract

Principal components analysis was carried out on 13 morphological dimensions collected in the first phase of the Québec Family Study (weight, height, fat mass (FM), fat‐free mass (FFM), body surface area, six skinfolds, arm and calf girths). The first four principal components (PCs) account for 85.9% of the total phenotypic variance in the anthropometric dimensions. The first PC has almost equal loadings on the 13 variables, indicating its role as an overall body size and adiposity measure. This interpretation is supported by its high intraindividual correlations with other composite indices such as the BMI and sum of six skinfolds (SF6). An interesting finding compared to other studies dealing with PCs of only skinfolds is that the second component appears to contrast measures of body fat with those that are fat free or that represent overall body size, thus indexing a different dimension to the fat patterning. It explains 17% of the total phenotypic variance. The commonly observed component for the trunk‐extremity contrast is represented as the fourth principal component. The third component primarily indexes height, although an extremity‐trunk contrast is also weakly represented. Together, the 3rd and 4th components explain ∼10% of the total variance. The intraindividual correlation of PC3 with the trunk‐extremity skinfold ratio (TER) is moderately negative (−0.307), whereas that of PC4 is highly positive (0.764). Analysis of familial correlations (parent‐offspring and sibling) shows that the familial effect (transmissibility) ranges 0.43–0.75 for the first four PCs. The lack of significant spouse correlation for most of the PCs suggests that these familial effects may be primarily genetic. Am. J. Hum. Biol. 9:725–733, 1997. © 1997 Wiley‐Liss, Inc.

A statistical investigation into the sharing of common genetic factors between blood pressure and obesity phenotypes in nuclear families from the Greater Bilbao (Spain)

“…circumferences and skinfolds). Factor analysis is a useful multivariate methodology that offers the possibility to reduce a large set of correlated measures into a smaller number of uncorrelated domains or factors that capture much of the underlying covariance structure among the multiple dimensions [17]. The first analysis included five body circumferences (upper arm relaxed and contracted, waist, hip and medial calf) and the second analysis was carried out for the six skinfolds (biceps, triceps, subescapular, suprailiac, abdominal and medial calf).…”

“…Factors extracted from a factor analysis could represent features that contain a higher degree of genetic variance than the original variables separately [15]. This methodology is widely used in the study of correlated measures as circumferences or skinfold thickness [16][17][18]. Finally, Heath-Carter [19] somatotype provides a more generalized approach to body types and summarizes body shape in three basic components: endomorphy, mesomorphy and ectomorphy (fatness and leanness, musculoskeletal development for the individual's height and linearity-related component, respectively).…”