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

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          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.

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          A pooled analysis of magnetic fields and childhood leukaemia

          Previous studies have suggested an association between exposure to 50–60 Hz magnetic fields (EMF) and childhood leukaemia. We conducted a pooled analysis based on individual records from nine studies, including the most recent ones. Studies with 24/48-hour magnetic field measurements or calculated magnetic fields were included. We specified which data analyses we planned to do and how to do them before we commenced the work. The use of individual records allowed us to use the same exposure definitions, and the large numbers of subjects enabled more precise estimation of risks at high exposure levels. For the 3203 children with leukaemia and 10 338 control children with estimated residential magnetic field exposures levels < 0.4 μT, we observed risk estimates near the no effect level, while for the 44 children with leukaemia and 62 control children with estimated residential magnetic field exposures ≥ 0.4 μT the estimated summary relative risk was 2.00 (1.27–3.13), P value = 0.002). Adjustment for potential confounding variables did not appreciably change the results. For North American subjects whose residences were in the highest wire code category, the estimated summary relative risk was 1.24 (0.82–1.87). Thus, we found no evidence in the combined data for the existence of the so-called wire-code paradox. In summary, the 99.2% of children residing in homes with exposure levels < 0.4 μT had estimates compatible with no increased risk, while the 0.8% of children with exposures ≥ 0.4 μT had a relative risk estimate of approximately 2, which is unlikely to be due to random variability. The explanation for the elevated risk is unknown, but selection bias may have accounted for some of the increase. © 2000 Cancer Research Campaign
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            ELECTRICAL WIRING CONFIGURATIONS AND CHILDHOOD CANCER

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              Pooled analysis of recent studies on magnetic fields and childhood leukaemia

              Background: Previous pooled analyses have reported an association between magnetic fields and childhood leukaemia. We present a pooled analysis based on primary data from studies on residential magnetic fields and childhood leukaemia published after 2000. Methods: Seven studies with a total of 10 865 cases and 12 853 controls were included. The main analysis focused on 24-h magnetic field measurements or calculated fields in residences. Results: In the combined results, risk increased with increase in exposure, but the estimates were imprecise. The odds ratios for exposure categories of 0.1–0.2 μT, 0.2–0.3 μT and ⩾0.3 μT, compared with <0.1 μT, were 1.07 (95% CI 0.81–1.41), 1.16 (0.69–1.93) and 1.44 (0.88–2.36), respectively. Without the most influential study from Brazil, the odds ratios increased somewhat. An increasing trend was also suggested by a nonparametric analysis conducted using a generalised additive model. Conclusions: Our results are in line with previous pooled analyses showing an association between magnetic fields and childhood leukaemia. Overall, the association is weaker in the most recently conducted studies, but these studies are small and lack methodological improvements needed to resolve the apparent association. We conclude that recent studies on magnetic fields and childhood leukaemia do not alter the previous assessment that magnetic fields are possibly carcinogenic.
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                Author and article information

                Journal
                Int J Environ Res Public Health
                Int J Environ Res Public Health
                ijerph
                International Journal of Environmental Research and Public Health
                MDPI
                1661-7827
                1660-4601
                08 November 2019
                November 2019
                : 16
                : 22
                : 4363
                Affiliations
                [1 ]CNR IEIIT—Consiglio Nazionale delle Ricerche, Istituto di Elettronica e di Ingegneria dell’Informazione e delle Telecomunicazioni, 20133 Milan, Italy; emma.chiaramello@ 123456ieiit.cnr.it (E.C.); marta.bonato@ 123456ieiit.cnr.it (M.B.); serena.fiocchi@ 123456ieiit.cnr.it (S.F.); marta.parazzini@ 123456ieiit.cnr.it (M.P.); paolo.ravazzani@ 123456ieiit.cnr.it (P.R.)
                [2 ]EDF Electricité de France, 75017 Paris, France; isabelle.magne@ 123456edf.fr (I.M.); martine.souques@ 123456edf.fr (M.S.)
                [3 ]Dipartimento di Elettronica, Informazione e Bioingegneria DEIB, Politecnico di Milano, 20133 Milan, Italy
                Author notes
                Author information
                https://orcid.org/0000-0002-2433-449X
                https://orcid.org/0000-0003-2503-4779
                https://orcid.org/0000-0002-5941-297X
                https://orcid.org/0000-0002-5527-1049
                https://orcid.org/0000-0002-6568-8841
                https://orcid.org/0000-0001-9008-7530
                https://orcid.org/0000-0003-0282-3329
                Article
                ijerph-16-04363
                10.3390/ijerph16224363
                6888053
                31717366
                a044dfcc-0fd1-46c5-81f3-6d07145b2a0b
                © 2019 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 10 September 2019
                : 06 November 2019
                Categories
                Article

                Public health
                children,elf mf,magnetic field,residential exposure,cluster analysis,machine learning,electric heating,residence age,residence type,family size

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