Assumptions in quantitative analyses of health risks of overhead power lines

One of the major issues hampering the formulation of uncontested policy decisions on contemporary risks is the presence of uncertainties in various stages of the policy cycle. In literature, different lines are suggested to address the problem of provisional and uncertain evidence. Reflective approaches such as pedigree analysis can be used to explore the quality of evidence when quantification of uncertainties is at stake. One of the issues where the quality of evidence impedes policy making, is the case of electromagnetic fields. In this case, a (statistical) association was suggested with an increased risk on childhood leukaemia in the vicinity of overhead power lines. A biophysical mechanism that could support this association was not found till date however. The Dutch government bases its policy concerning overhead power lines on the precautionary principle. For The Netherlands, previous studies have assessed the potential number of extra cases of childhood leukaemia due to the presence over overhead power lines. However, such a quantification of the health risk of EMF entails a (large) number of assumptions, both prior to and in the calculation chain. In this study, these assumptions were prioritized and critically appraised in an expert elicitation workshop, using a pedigree matrix for characterization of assumptions in assessments. It appeared that assumptions that were regarded to be important in quantifying the health risks show a high value-ladenness. The results show that, given the present state of knowledge, quantification of the health risks of EMF is premature. We consider the current implementation of the precautionary principle by the Dutch government to be adequate.

► We characterized assumptions in risk assessments regarding electromagnetic fields.
► Important assumptions appear to show a high value-ladenness.
► Quantification of the health risks of EMF appears to be premature.
► The precautionary principle is advised as guiding principle in policy decisions.