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A new data driven method for summarising multiple cause of death data
BACKGROUND: National mortality statistics are based on a single underlying cause of death. This practice does not adequately represent the impact of the range of conditions experienced in an ageing population in which multimorbidity is common. METHODS: We propose a new method for weighting the perce...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10074369/ https://www.ncbi.nlm.nih.gov/pubmed/37020203 http://dx.doi.org/10.1186/s12874-023-01901-z |
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author | Dobson, Annette McElwee, Paul Baneshi, Mohammad Reza Eynstone-Hinkins, James Moran, Lauren Waller, Michael |
author_facet | Dobson, Annette McElwee, Paul Baneshi, Mohammad Reza Eynstone-Hinkins, James Moran, Lauren Waller, Michael |
author_sort | Dobson, Annette |
collection | PubMed |
description | BACKGROUND: National mortality statistics are based on a single underlying cause of death. This practice does not adequately represent the impact of the range of conditions experienced in an ageing population in which multimorbidity is common. METHODS: We propose a new method for weighting the percentages of deaths attributed to different causes that takes account of the patterns of associations among underlying and contributing causes of death. It is driven by the data and unlike previously proposed methods does not rely on arbitrary choices of weights which can over-emphasise the contribution of some causes of death. The method is illustrated using Australian mortality data for people aged 60 years or more. RESULTS: Compared to the usual method based only on the underlying cause of death the new method attributes higher percentages of deaths to conditions like diabetes and dementia that are frequently mentioned as contributing causes of death, rather than underlying causes, and lower percentages to conditions to which they are closely related such as ischaemic heart disease and cerebrovascular disease. For some causes, notably cancers, which are usually recorded as underlying causes with few if any contributing causes the new method produces similar percentages to the usual method. These different patterns among groups of related conditions are not apparent if arbitrary weights are used. CONCLUSION: The new method could be used by national statistical agencies to produce additional mortality tables to complement the current tables based only on underlying causes of death. |
format | Online Article Text |
id | pubmed-10074369 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-100743692023-04-05 A new data driven method for summarising multiple cause of death data Dobson, Annette McElwee, Paul Baneshi, Mohammad Reza Eynstone-Hinkins, James Moran, Lauren Waller, Michael BMC Med Res Methodol Research Article BACKGROUND: National mortality statistics are based on a single underlying cause of death. This practice does not adequately represent the impact of the range of conditions experienced in an ageing population in which multimorbidity is common. METHODS: We propose a new method for weighting the percentages of deaths attributed to different causes that takes account of the patterns of associations among underlying and contributing causes of death. It is driven by the data and unlike previously proposed methods does not rely on arbitrary choices of weights which can over-emphasise the contribution of some causes of death. The method is illustrated using Australian mortality data for people aged 60 years or more. RESULTS: Compared to the usual method based only on the underlying cause of death the new method attributes higher percentages of deaths to conditions like diabetes and dementia that are frequently mentioned as contributing causes of death, rather than underlying causes, and lower percentages to conditions to which they are closely related such as ischaemic heart disease and cerebrovascular disease. For some causes, notably cancers, which are usually recorded as underlying causes with few if any contributing causes the new method produces similar percentages to the usual method. These different patterns among groups of related conditions are not apparent if arbitrary weights are used. CONCLUSION: The new method could be used by national statistical agencies to produce additional mortality tables to complement the current tables based only on underlying causes of death. BioMed Central 2023-04-05 /pmc/articles/PMC10074369/ /pubmed/37020203 http://dx.doi.org/10.1186/s12874-023-01901-z Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Article Dobson, Annette McElwee, Paul Baneshi, Mohammad Reza Eynstone-Hinkins, James Moran, Lauren Waller, Michael A new data driven method for summarising multiple cause of death data |
title | A new data driven method for summarising multiple cause of death data |
title_full | A new data driven method for summarising multiple cause of death data |
title_fullStr | A new data driven method for summarising multiple cause of death data |
title_full_unstemmed | A new data driven method for summarising multiple cause of death data |
title_short | A new data driven method for summarising multiple cause of death data |
title_sort | new data driven method for summarising multiple cause of death data |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10074369/ https://www.ncbi.nlm.nih.gov/pubmed/37020203 http://dx.doi.org/10.1186/s12874-023-01901-z |
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