In the PCA, the first three components had eigenvalues greater
than 1, indicating that they should be interpreted (Kaiser Criterion)
(Bayarri et al., 2011; Symoneaux et al., 2012). The first principal
component (PC1) explained 56.18% of the variability contained in
the original variables, whereas the second (PC2) and third (PC3)
principal components explained 21.59 and 10.75%, respectively,
explaining 88.52% of the total variability.