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The future excess fraction model for calculating burden of disease

BACKGROUND: Estimates of the burden of disease caused by a particular agent are used to assist in making policy and prioritizing actions. Most estimations have employed the attributable fraction approach, which estimates the proportion of disease cases or deaths in a specific year which are attribut...

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Autores principales: Fritschi, Lin, Chan, Jayzii, Hutchings, Sally J., Driscoll, Tim R., Wong, Adrian Y. W., Carey, Renee N.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4865002/
https://www.ncbi.nlm.nih.gov/pubmed/27169472
http://dx.doi.org/10.1186/s12889-016-3066-1
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author Fritschi, Lin
Chan, Jayzii
Hutchings, Sally J.
Driscoll, Tim R.
Wong, Adrian Y. W.
Carey, Renee N.
author_facet Fritschi, Lin
Chan, Jayzii
Hutchings, Sally J.
Driscoll, Tim R.
Wong, Adrian Y. W.
Carey, Renee N.
author_sort Fritschi, Lin
collection PubMed
description BACKGROUND: Estimates of the burden of disease caused by a particular agent are used to assist in making policy and prioritizing actions. Most estimations have employed the attributable fraction approach, which estimates the proportion of disease cases or deaths in a specific year which are attributable to past exposure to a particular agent. While this approach has proven extremely useful in quantifying health effects, it requires historical data on exposures which are not always available. METHODS: We present an alternative method, the future excess fraction method, which is based on the lifetime risk approach, and which requires current rather than historical exposure data. This method estimates the future number of exposure-related disease cases or deaths occurring in the subgroup of the population who were exposed to the particular agent in a specific year. We explain this method and use publically-available data on current asbestos exposure and mesothelioma incidence to demonstrate the use of the method. CONCLUSIONS: Our approach to modelling burden of disease is useful when there are no historical measures of exposure and where future disease rates can be projected on person years at risk.
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spelling pubmed-48650022016-05-13 The future excess fraction model for calculating burden of disease Fritschi, Lin Chan, Jayzii Hutchings, Sally J. Driscoll, Tim R. Wong, Adrian Y. W. Carey, Renee N. BMC Public Health Technical Advance BACKGROUND: Estimates of the burden of disease caused by a particular agent are used to assist in making policy and prioritizing actions. Most estimations have employed the attributable fraction approach, which estimates the proportion of disease cases or deaths in a specific year which are attributable to past exposure to a particular agent. While this approach has proven extremely useful in quantifying health effects, it requires historical data on exposures which are not always available. METHODS: We present an alternative method, the future excess fraction method, which is based on the lifetime risk approach, and which requires current rather than historical exposure data. This method estimates the future number of exposure-related disease cases or deaths occurring in the subgroup of the population who were exposed to the particular agent in a specific year. We explain this method and use publically-available data on current asbestos exposure and mesothelioma incidence to demonstrate the use of the method. CONCLUSIONS: Our approach to modelling burden of disease is useful when there are no historical measures of exposure and where future disease rates can be projected on person years at risk. BioMed Central 2016-05-11 /pmc/articles/PMC4865002/ /pubmed/27169472 http://dx.doi.org/10.1186/s12889-016-3066-1 Text en © Fritschi et al. 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Technical Advance
Fritschi, Lin
Chan, Jayzii
Hutchings, Sally J.
Driscoll, Tim R.
Wong, Adrian Y. W.
Carey, Renee N.
The future excess fraction model for calculating burden of disease
title The future excess fraction model for calculating burden of disease
title_full The future excess fraction model for calculating burden of disease
title_fullStr The future excess fraction model for calculating burden of disease
title_full_unstemmed The future excess fraction model for calculating burden of disease
title_short The future excess fraction model for calculating burden of disease
title_sort future excess fraction model for calculating burden of disease
topic Technical Advance
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4865002/
https://www.ncbi.nlm.nih.gov/pubmed/27169472
http://dx.doi.org/10.1186/s12889-016-3066-1
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