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Quantifying cause-related mortality in Australia, incorporating multiple causes: observed patterns, trends and practical considerations
BACKGROUND: Mortality statistics using a single underlying cause of death (UC) are key health indicators. Rising multimorbidity and chronic disease mean that deaths increasingly involve multiple conditions. However, additional causes reported on death certificates are rarely integrated into mortalit...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9908048/ https://www.ncbi.nlm.nih.gov/pubmed/35984318 http://dx.doi.org/10.1093/ije/dyac167 |
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author | Bishop, Karen Moreno-Betancur, Margarita Balogun, Saliu Eynstone-Hinkins, James Moran, Lauren Rao, Chalapati Banks, Emily Korda, Rosemary J Gourley, Michelle Joshy, Grace |
author_facet | Bishop, Karen Moreno-Betancur, Margarita Balogun, Saliu Eynstone-Hinkins, James Moran, Lauren Rao, Chalapati Banks, Emily Korda, Rosemary J Gourley, Michelle Joshy, Grace |
author_sort | Bishop, Karen |
collection | PubMed |
description | BACKGROUND: Mortality statistics using a single underlying cause of death (UC) are key health indicators. Rising multimorbidity and chronic disease mean that deaths increasingly involve multiple conditions. However, additional causes reported on death certificates are rarely integrated into mortality indicators, partly due to complexities in data and methods. This study aimed to assess trends and patterns in cause-related mortality in Australia, integrating multiple causes (MC) of death. METHODS: Deaths (n = 1 773 399) in Australia (2006–17) were mapped to 136 ICD-10-based groups and MC indicators applied. Age-standardized cause-related rates (deaths/100 000) based on the UC (ASR(UC)) were compared with rates based on any mention of the cause (ASR(AM)) using rate ratios (RR = ASR(AM)/ASR(UC)) and to rates based on weighting multiple contributing causes (ASR(W)). RESULTS: Deaths involved on average 3.4 causes in 2017; the percentage with >4 causes increased from 20.9 (2006) to 24.4 (2017). Ischaemic heart disease (ASR(UC) = 73.3, ASR(AM) = 135.8, ASR(W) = 63.5), dementia (ASR(UC) = 51.1, ASR(AM) = 98.1, ASR(W) = 52.1) and cerebrovascular diseases (ASR(UC) = 39.9, ASR(AM) = 76.7, ASR(W) = 33.5) ranked as leading causes by all methods. Causes with high RR included hypertension (ASR(UC) = 2.2, RR = 35.5), atrial fibrillation (ASR(UC) = 8.0, RR = 6.5) and diabetes (ASR(UC) = 18.5, RR = 3.5); the corresponding ASR(W) were 12.5, 12.6 and 24.0, respectively. Renal failure, atrial fibrillation and hypertension ranked among the 10 leading causes by ASR(AM) and ASR(W) but not by ASR(UC). Practical considerations in working with MC data are discussed. CONCLUSIONS: Despite the similarities in leading causes under the three methods, with integration of MC several preventable diseases emerged as leading causes. MC analyses offer a richer additional perspective for population health monitoring and policy development. |
format | Online Article Text |
id | pubmed-9908048 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-99080482023-02-09 Quantifying cause-related mortality in Australia, incorporating multiple causes: observed patterns, trends and practical considerations Bishop, Karen Moreno-Betancur, Margarita Balogun, Saliu Eynstone-Hinkins, James Moran, Lauren Rao, Chalapati Banks, Emily Korda, Rosemary J Gourley, Michelle Joshy, Grace Int J Epidemiol Miscellaneous BACKGROUND: Mortality statistics using a single underlying cause of death (UC) are key health indicators. Rising multimorbidity and chronic disease mean that deaths increasingly involve multiple conditions. However, additional causes reported on death certificates are rarely integrated into mortality indicators, partly due to complexities in data and methods. This study aimed to assess trends and patterns in cause-related mortality in Australia, integrating multiple causes (MC) of death. METHODS: Deaths (n = 1 773 399) in Australia (2006–17) were mapped to 136 ICD-10-based groups and MC indicators applied. Age-standardized cause-related rates (deaths/100 000) based on the UC (ASR(UC)) were compared with rates based on any mention of the cause (ASR(AM)) using rate ratios (RR = ASR(AM)/ASR(UC)) and to rates based on weighting multiple contributing causes (ASR(W)). RESULTS: Deaths involved on average 3.4 causes in 2017; the percentage with >4 causes increased from 20.9 (2006) to 24.4 (2017). Ischaemic heart disease (ASR(UC) = 73.3, ASR(AM) = 135.8, ASR(W) = 63.5), dementia (ASR(UC) = 51.1, ASR(AM) = 98.1, ASR(W) = 52.1) and cerebrovascular diseases (ASR(UC) = 39.9, ASR(AM) = 76.7, ASR(W) = 33.5) ranked as leading causes by all methods. Causes with high RR included hypertension (ASR(UC) = 2.2, RR = 35.5), atrial fibrillation (ASR(UC) = 8.0, RR = 6.5) and diabetes (ASR(UC) = 18.5, RR = 3.5); the corresponding ASR(W) were 12.5, 12.6 and 24.0, respectively. Renal failure, atrial fibrillation and hypertension ranked among the 10 leading causes by ASR(AM) and ASR(W) but not by ASR(UC). Practical considerations in working with MC data are discussed. CONCLUSIONS: Despite the similarities in leading causes under the three methods, with integration of MC several preventable diseases emerged as leading causes. MC analyses offer a richer additional perspective for population health monitoring and policy development. Oxford University Press 2022-08-19 /pmc/articles/PMC9908048/ /pubmed/35984318 http://dx.doi.org/10.1093/ije/dyac167 Text en © The Author(s) 2022. Published by Oxford University Press on behalf of the International Epidemiological Association. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Miscellaneous Bishop, Karen Moreno-Betancur, Margarita Balogun, Saliu Eynstone-Hinkins, James Moran, Lauren Rao, Chalapati Banks, Emily Korda, Rosemary J Gourley, Michelle Joshy, Grace Quantifying cause-related mortality in Australia, incorporating multiple causes: observed patterns, trends and practical considerations |
title | Quantifying cause-related mortality in Australia, incorporating multiple causes: observed patterns, trends and practical considerations |
title_full | Quantifying cause-related mortality in Australia, incorporating multiple causes: observed patterns, trends and practical considerations |
title_fullStr | Quantifying cause-related mortality in Australia, incorporating multiple causes: observed patterns, trends and practical considerations |
title_full_unstemmed | Quantifying cause-related mortality in Australia, incorporating multiple causes: observed patterns, trends and practical considerations |
title_short | Quantifying cause-related mortality in Australia, incorporating multiple causes: observed patterns, trends and practical considerations |
title_sort | quantifying cause-related mortality in australia, incorporating multiple causes: observed patterns, trends and practical considerations |
topic | Miscellaneous |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9908048/ https://www.ncbi.nlm.nih.gov/pubmed/35984318 http://dx.doi.org/10.1093/ije/dyac167 |
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