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Voigt, K. ; Brüggemann, R.* ; Scherb, H.* ; Cok, I.* ; Mazmanci, B.* ; Mazmanci, M. A.* ; Turgut, C.* ; Schramm, K.-W.

Features of PyHasse software used for the evaluation of chemicals in human breast milk samples.

In: Proceedings (Simulation in Umwelt- und Geowissenschaften). Aachen: Shaker Verl., 2012. 169-180 (ASIM-Mitteilung AM 141)

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Environmental chemicals like Organochlorine Pesticides (OCPs) have been reported in human breast milk samples for several decades. These OCPs are widespread used chemicals in agriculture and industry for different purposes all over the world. Epidemiological evidence and theoretical considerations imply that these compounds are potentially hazardous to human and wildlife reproductive health. In a recently performed project 44 breast milk samples were measured in 5 different regions in the Taurus Mountains in Turkey. 18 OCPs were looked upon. The data analysis method applied in this paper is the Hasse diagram technique, an ordinal mathematical multi-criteria data analysis method based on Discrete Mathematics. The software package used is the PyHasse software. This software is written in the free available interpreter language Python by the second author and it is under constant development. It comprises several modules which are of great support also in the data evaluation of environmental health data. In this presentation we will apply the main Hasse Diagram Technique Module (mainHD20), the Similarity Analysis (similarity8) for the comparison of two data matrices and the Sensitivity Module (Sensi18) for detecting the most important attribute. The PyHasse software can be obtained from the second author on request. Within the breast milk study in the Taurus Mountains in Turkey several co-variables were examined among them the fish eating habit of the mothers. It is known that many OCPs are accumulating in fish. From the 44 mothers only 8 never ate fish. All the other 36 women did so. In a first approach it might be interesting to compare the fish eaters with the non-fish eaters with respect to their chemicals’ profiles and corresponding Hasse diagrams. A clear difference can be detected between the contamination profiles of breast milk samples from mother with no fish eating habits from those who are eating fish regularly.

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