Multivariate statistical approach to a data set of dioxin and furan contaminations in human milk

The levels of chlorinated dibenzodioxins, PCDDs, and dibenzofurans, PCDFs, in human milk have been of great concern after the discovery of the toxic 2,3,7,8-substituted isomers in milk of European origin. As knowledge of environmental contamination of human breast milk increases, questions will continue to be asked about possible risks from breast feeding. Before any recommendations can be made, there must be knowledge of contaminant levels in mothers' breast milk. Researchers have measured PCB and 17 different dioxins and furans in human breast milk samples. To date the data has only been analyzed by univariate and bivariate statistical methods. However to extract as much information as possible from this data set, multivariate statistical methods must be used. Here the authors present a multivariate analysis where the relationships between the polychlorinated compounds and the personalia of the mothers have been studied. For the data analysis partial least squares (PLS) modelling has been used.