Principal components analysis is one of the modern mathematical-statistic methods and it enables the reduction and organization of the results in order to indicate important implicit features. In such an analysis the components, correlated with each other, are shown on the basis of the matrix correlation of many variables. The examined materials were femur heads of hip joints which had various degenerative-deforming changes and came from people who lived on the industrial area. The examined population of 103 femur heads came from 64 women and 39 men. The determination of the content of 12 metals in samples of femur heads was made using atomic absorption spectrophotometry (AAS) by the means of the Pye Unicam SP-9 in the flame acetylene-air. The principal components analysis in most examined groups showed that the first factor describes the change of the Cr, Ni, Cu, Zn, Na and Ca contents. Other main components emphasized variously the meaning of a given parameter. The results of PCA analysis are in accordance with the results of correlative analysis.