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The risk linked to ionizing radiation: an alternative epidemiologic approach.

Radioprotection norms have been based on risk models that have evolved over time. These models show relationships between exposure and observed effects. There is a high level of uncertainty regarding lower doses. Recommendations have been based on the conservative hypothesis of a linear relationship...

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Detalles Bibliográficos
Autores principales: de Brouwer, C, Lagasse, R
Formato: Texto
Lenguaje:English
Publicado: 2001
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1240436/
https://www.ncbi.nlm.nih.gov/pubmed/11673115
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author de Brouwer, C
Lagasse, R
author_facet de Brouwer, C
Lagasse, R
author_sort de Brouwer, C
collection PubMed
description Radioprotection norms have been based on risk models that have evolved over time. These models show relationships between exposure and observed effects. There is a high level of uncertainty regarding lower doses. Recommendations have been based on the conservative hypothesis of a linear relationship without threshold value. This relationship is still debated, and the diverse observations do not allow any definitive conclusion. Available data are contradictory, and various interpretations can be made. Here we review an alternative approach for defining causation and reconciling apparently contradictory conclusions. This alternative epidemiologic approach is based on causal groups: Each component of a causal group is necessary but not sufficient for causality. Many groups may be involved in causality. Thus, ionizing radiation may be a component of one or several causal groups. This formalization reconciles heterogeneous observations but implies searching for the interactions between components, mostly between critical components of a causal profile, and, for instance, the reasons why specific human groups would not show any effect despite exposure, when an effect would be expected.
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spelling pubmed-12404362005-11-08 The risk linked to ionizing radiation: an alternative epidemiologic approach. de Brouwer, C Lagasse, R Environ Health Perspect Research Article Radioprotection norms have been based on risk models that have evolved over time. These models show relationships between exposure and observed effects. There is a high level of uncertainty regarding lower doses. Recommendations have been based on the conservative hypothesis of a linear relationship without threshold value. This relationship is still debated, and the diverse observations do not allow any definitive conclusion. Available data are contradictory, and various interpretations can be made. Here we review an alternative approach for defining causation and reconciling apparently contradictory conclusions. This alternative epidemiologic approach is based on causal groups: Each component of a causal group is necessary but not sufficient for causality. Many groups may be involved in causality. Thus, ionizing radiation may be a component of one or several causal groups. This formalization reconciles heterogeneous observations but implies searching for the interactions between components, mostly between critical components of a causal profile, and, for instance, the reasons why specific human groups would not show any effect despite exposure, when an effect would be expected. 2001-09 /pmc/articles/PMC1240436/ /pubmed/11673115 Text en
spellingShingle Research Article
de Brouwer, C
Lagasse, R
The risk linked to ionizing radiation: an alternative epidemiologic approach.
title The risk linked to ionizing radiation: an alternative epidemiologic approach.
title_full The risk linked to ionizing radiation: an alternative epidemiologic approach.
title_fullStr The risk linked to ionizing radiation: an alternative epidemiologic approach.
title_full_unstemmed The risk linked to ionizing radiation: an alternative epidemiologic approach.
title_short The risk linked to ionizing radiation: an alternative epidemiologic approach.
title_sort risk linked to ionizing radiation: an alternative epidemiologic approach.
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1240436/
https://www.ncbi.nlm.nih.gov/pubmed/11673115
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