Evidence map›Paper›PMID 30132159›Full record

ArticleRadiation and environmental biophysics2018

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

G M Kendall, P Chernyavskiy, J D Appleton, J C H Miles, R Wakeford, M Athanson, T J Vincent, N P McColl, M P Little

Abstract read
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In one paragraph

Article in Radiation and environmental biophysics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Review
  5. A review of studies of childhood cancer and natural background radiation.International journal of radiation biology · 2021
    Review
  6. Article
  7. Epidemiological studies of natural sources of radiation and childhood cancer: current challenges and future perspectives.Journal of radiological protection : official journal of the Society for Radiological Protection · 2020
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

G M KendallCancer Epidemiology Unit, NDPH, University of Oxford, Richard Doll Building, Old Road Campus, Headington, Oxford, OX3 7LF, UK. Gerald.Kendall@ndph.ox.ac.uk.ORCID 0000-0002-9195-754X
P ChernyavskiyRadiation Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, DHHS, NIH, Bethesda, MD, 20892-9778, USA.
J D AppletonBritish Geological Survey, Kingsley Dunham Centre, Nicker Hill, Keyworth, Nottingham, NG12 5GG, UK.
J C H Miles, Nobles Close, Grove, Oxfordshire, OX12 0NR, UK.
R WakefordCentre for Occupational and Environmental Health, Institute of Population Health, The University of Manchester, Ellen Wilkinson Building, Oxford Road, Manchester, M13 9PL, UK.
M AthansonBodleian Library, University of Oxford, Broad Street, Oxford, OX1 3BG, UK.
T J VincentChildhood Cancer Research Group, University of Oxford, New Richards Building, Old Road, Oxford, UK.
N P McCollCentre for Radiation, Chemical and Environmental Hazards, Public Health England, Chilton, Didcot Oxon, OX11 0RQ, UK.
M P LittleRadiation Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, DHHS, NIH, Bethesda, MD, 20892-9778, USA.

Funding

Studies of Populations Exposed to Environmental Sources of RadiationZIACP010132 · NCI · DIVISION OF CANCER EPIDEMIOLOGY AND GENETICS · PI CAHOON, ELIZABETH · 2009 to 2025
$35.2M
Cancer Research UK 16491
6 · The paper itself

Abstract

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.

Indexed as

Gamma RaysModels, StatisticalRadiation DosageUnited KingdomChildhood cancerGamma radiationLeukaemiaNatural background radiation

Identifiers

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.