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In International journal of environmental research and public health ; h5-index 73.0

Personal exposure to Extremely Low Frequency Magnetic Fields (ELF MF) in children is a very timely topic. We applied cluster analysis to 24 h indoor personal exposures of 884 children in France to identify possible common patterns of exposures. We investigated how electric networks near child home and other variables potentially affecting residential exposure, such as indoor sources of ELF MF, the age and type of the residence and family size, characterized the magnetic field exposure patterns. We identified three indoor personal exposure patterns: children living near overhead lines of high (63-150 kV), extra-high (225 kV) and ultra-high voltage (400 kV) were characterized by the highest exposures; children living near underground networks of low (400 V) and mid voltage (20 kV) and substations (20 kV/400 V) were characterized by mid exposures; children living far from electric networks had the lowest level of exposure. The harmonic component was not relevant in discriminating the exposure patterns, unlike the 50 Hz or broadband (40-800 Hz) component. Children using electric heating appliances, or living in big buildings or in larger families had generally a higher level of personal indoor exposure. Instead, the age of the residence was not relevant in differentiating the exposure patterns.

Tognola Gabriella, Chiaramello Emma, Bonato Marta, Magne Isabelle, Souques Martine, Fiocchi Serena, Parazzini Marta, Ravazzani Paolo

2019-Nov-08

ELF MF, children, cluster analysis, electric heating, family size, machine learning, magnetic field, residence age, residence type, residential exposure