Radiation and Environmental Biophysics

, Volume 57, Issue 4, pp 321–347 | Cite as

Modelling the bimodal distribution of indoor gamma-ray dose-rates in Great Britain

  • G. M. KendallEmail author
  • P. Chernyavskiy
  • J. D. Appleton
  • J. C. H. Miles
  • R. Wakeford
  • M. Athanson
  • T. J. Vincent
  • N. P. McColl
  • M. P. Little
Original Article


Gamma radiation from naturally occurring sources (including directly ionizing cosmic-rays) is a major component of background radiation. An understanding of the magnitude and variation of doses from these sources is important, and the ability to predict them is required for epidemiological studies. In the present paper, indoor measurements of naturally occurring gamma-rays at representative locations in Great Britain are summarized. It is shown that, although the individual measurement data appear unimodal, the distribution of gamma-ray dose-rates when averaged over relatively small areas, which probably better represents the underlying distribution with inter-house variation reduced, appears bimodal. The dose-rate distributions predicted by three empirical and geostatistical models are also bimodal and compatible with the distributions of the areally averaged dose-rates. The distribution of indoor gamma-ray dose-rates in the UK is compared with those in other countries, which also tend to appear bimodal (or possibly multimodal). The variation of indoor gamma-ray dose-rates with geology, socio-economic status of the area, building type, and period of construction are explored. The factors affecting indoor dose-rates from background gamma radiation are complex and frequently intertwined, but geology, period of construction, and socio-economic status are influential; the first is potentially most influential, perhaps, because it can be used as a general proxy for local building materials. Various statistical models are tested for predicting indoor gamma-ray dose-rates at unmeasured locations. Significant improvements over previous modelling are reported. The dose-rate estimates generated by these models reflect the imputed underlying distribution of dose-rates and provide acceptable predictions at geographical locations without measurements.


Gamma radiation Natural background radiation Childhood cancer Leukaemia 



The authors are grateful to Kathryn Bunch, Graham Smith, Hans Vanmarcke, Kaare Ulbak, Juhani Lahtinen, Francesco Bochicchio, Marta Garcia-Talavera, Bernd Grosche, David Pawel, and the two referees for detailed and helpful comments and information on national data. Cristina Nuccetelli and Rosabianca Trevisi kindly provided data from their database of NORM in building materials. The authors are also very grateful to Jill Simpson of the University of York and to the other UKCCS investigators for making available the results of the indoor gamma-ray measurements made for the United Kingdom Childhood Cancer Study and for advice on the interpretation of the data. They are grateful to Phil Gilvin, Luke Hager, and Rick Tanner at Public Health England (PHE) for advice on the dosimetry of the National Survey and the UKCCS. The Digital Land Utilisation Survey 1933–1949 (AfA213) was used under licence from the Environment Agency (The Land Utilisation Survey of Britain, 1933–1949, copyright Audrey N. Clark). J. D. Appleton publishes with permission from the Executive Director of the BGS. This work was supported by Children with Cancer (UK) and by the Intramural Research Program of the National Institutes of Health, the National Cancer Institute, Division of Cancer Epidemiology and Genetics.

Supplementary material

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Supplementary material 1 (DOC 36 KB)
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Supplementary material 2 (DOC 67 KB)
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Supplementary material 3 (DOC 28 KB)
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Supplementary material 4 (DOCX 3333 KB)


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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Cancer Epidemiology Unit, NDPHUniversity of OxfordHeadingtonUK
  2. 2.Radiation Epidemiology Branch, Division of Cancer Epidemiology and GeneticsNational Cancer Institute, DHHS, NIHBethesdaUSA
  3. 3.Department of Mathematics and Statistics, Ross Hall 331University of WyomingLaramieUSA
  4. 4.British Geological SurveyKingsley Dunham CentreNottinghamUK
  5. 5.Nobles Close, Grove, OxfordshireUK
  6. 6.Centre for Occupational and Environmental Health, Institute of Population HealthThe University of ManchesterManchesterUK
  7. 7.Bodleian LibraryUniversity of OxfordOxfordUK
  8. 8.Childhood Cancer Research GroupUniversity of OxfordOxfordUK
  9. 9.Centre for Radiation, Chemical and Environmental HazardsPublic Health England, ChiltonDidcot OxonUK

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