IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v16y2019i22p4363-d284992.html
   My bibliography  Save this article

Cluster Analysis of Residential Personal Exposure to ELF Magnetic Field in Children: Effect of Environmental Variables

Author

Listed:
  • Gabriella Tognola

    (CNR IEIIT—Consiglio Nazionale delle Ricerche, Istituto di Elettronica e di Ingegneria dell’Informazione e delle Telecomunicazioni, 20133 Milan, Italy)

  • Emma Chiaramello

    (CNR IEIIT—Consiglio Nazionale delle Ricerche, Istituto di Elettronica e di Ingegneria dell’Informazione e delle Telecomunicazioni, 20133 Milan, Italy)

  • Marta Bonato

    (CNR IEIIT—Consiglio Nazionale delle Ricerche, Istituto di Elettronica e di Ingegneria dell’Informazione e delle Telecomunicazioni, 20133 Milan, Italy
    Dipartimento di Elettronica, Informazione e Bioingegneria DEIB, Politecnico di Milano, 20133 Milan, Italy)

  • Isabelle Magne

    (EDF Electricité de France, 75017 Paris, France)

  • Martine Souques

    (EDF Electricité de France, 75017 Paris, France)

  • Serena Fiocchi

    (CNR IEIIT—Consiglio Nazionale delle Ricerche, Istituto di Elettronica e di Ingegneria dell’Informazione e delle Telecomunicazioni, 20133 Milan, Italy)

  • Marta Parazzini

    (CNR IEIIT—Consiglio Nazionale delle Ricerche, Istituto di Elettronica e di Ingegneria dell’Informazione e delle Telecomunicazioni, 20133 Milan, Italy)

  • Paolo Ravazzani

    (CNR IEIIT—Consiglio Nazionale delle Ricerche, Istituto di Elettronica e di Ingegneria dell’Informazione e delle Telecomunicazioni, 20133 Milan, Italy)

Abstract

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.

Suggested Citation

  • Gabriella Tognola & Emma Chiaramello & Marta Bonato & Isabelle Magne & Martine Souques & Serena Fiocchi & Marta Parazzini & Paolo Ravazzani, 2019. "Cluster Analysis of Residential Personal Exposure to ELF Magnetic Field in Children: Effect of Environmental Variables," IJERPH, MDPI, vol. 16(22), pages 1-14, November.
    • Handle: RePEc:gam:jijerp:v:16:y:2019:i:22:p:4363-:d:284992
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/16/22/4363/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/16/22/4363/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Peter Gajšek & Paolo Ravazzani & James Grellier & Theodoros Samaras & József Bakos & György Thuróczy, 2016. "Review of Studies Concerning Electromagnetic Field (EMF) Exposure Assessment in Europe: Low Frequency Fields (50 Hz–100 kHz)," IJERPH, MDPI, vol. 13(9), pages 1-14, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Malka N. Halgamuge, 2020. "Supervised Machine Learning Algorithms for Bioelectromagnetics: Prediction Models and Feature Selection Techniques Using Data from Weak Radiofrequency Radiation Effect on Human and Animals Cells," IJERPH, MDPI, vol. 17(12), pages 1-27, June.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Raquel Ramirez-Vazquez & Jesus Gonzalez-Rubio & Isabel Escobar & Carmen del Pilar Suarez Rodriguez & Enrique Arribas, 2021. "Personal Exposure Assessment to Wi-Fi Radiofrequency Electromagnetic Fields in Mexican Microenvironments," IJERPH, MDPI, vol. 18(4), pages 1-20, February.
    2. Sonja Michèle Schmidtpott & Saliba Danho & Vijay Kumar & Thorsten Seidel & Wolfgang Schöllhorn & Karl-Josef Dietz, 2022. "Scrutinizing the Impact of Alternating Electromagnetic Fields on Molecular Features of the Model Plant Arabidopsis thaliana," IJERPH, MDPI, vol. 19(9), pages 1-19, April.
    3. Paweł A. Mazurek & Aleksander Chudy & Piotr Hołyszko, 2024. "Assessment of Electromagnetic Fields in Trolleybuses and Electric Buses: A Study of Municipal Transport Company Lublin’s Fleet," Energies, MDPI, vol. 17(14), pages 1-21, July.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:16:y:2019:i:22:p:4363-:d:284992. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.