Detecting Mortality Trends in the Netherlands Across 625 Causes of Death
Cause of death (COD) data are essential to public health monitoring and policy. This study aims to determine the proportion of CODs, at ICD-10 three-position level, for which a long-term or short-term trend can be identified, and to examine how much the likelihood of identifying trends varies with C...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6862141/ https://www.ncbi.nlm.nih.gov/pubmed/31661859 http://dx.doi.org/10.3390/ijerph16214150 |
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author | Mitratza, Marianna Kunst, Anton E. Kardaun, Jan W. P. F. |
author_facet | Mitratza, Marianna Kunst, Anton E. Kardaun, Jan W. P. F. |
author_sort | Mitratza, Marianna |
collection | PubMed |
description | Cause of death (COD) data are essential to public health monitoring and policy. This study aims to determine the proportion of CODs, at ICD-10 three-position level, for which a long-term or short-term trend can be identified, and to examine how much the likelihood of identifying trends varies with COD size. We calculated annual age-standardized counts of deaths from Statistics Netherlands for the period 1996–2015 for 625 CODs. We applied linear regression models to estimate long-term trends, and outlier analysis to detect short-term changes. The association of the likelihood of a long-term trend with COD size was analyzed with multinomial logistic regression. No long-term trend could be demonstrated for 216 CODs (34.5%). For the remaining 409 causes, a trend could be detected, following a linear (211, 33.8%), quadratic (126, 20.2%) or cubic model (72, 11.5%). The probability of detecting a long-term trend increased from about 50% at six mean annual deaths, to 65% at 22 deaths and 75% at 60 deaths. An exceptionally high or low number of deaths in a single year was found for 16 CODs. When monitoring long-term mortality trends, one could consider a much broader range of causes of death, including ones with a relatively low number of annual deaths, than commonly used in condensed lists. |
format | Online Article Text |
id | pubmed-6862141 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-68621412019-12-05 Detecting Mortality Trends in the Netherlands Across 625 Causes of Death Mitratza, Marianna Kunst, Anton E. Kardaun, Jan W. P. F. Int J Environ Res Public Health Article Cause of death (COD) data are essential to public health monitoring and policy. This study aims to determine the proportion of CODs, at ICD-10 three-position level, for which a long-term or short-term trend can be identified, and to examine how much the likelihood of identifying trends varies with COD size. We calculated annual age-standardized counts of deaths from Statistics Netherlands for the period 1996–2015 for 625 CODs. We applied linear regression models to estimate long-term trends, and outlier analysis to detect short-term changes. The association of the likelihood of a long-term trend with COD size was analyzed with multinomial logistic regression. No long-term trend could be demonstrated for 216 CODs (34.5%). For the remaining 409 causes, a trend could be detected, following a linear (211, 33.8%), quadratic (126, 20.2%) or cubic model (72, 11.5%). The probability of detecting a long-term trend increased from about 50% at six mean annual deaths, to 65% at 22 deaths and 75% at 60 deaths. An exceptionally high or low number of deaths in a single year was found for 16 CODs. When monitoring long-term mortality trends, one could consider a much broader range of causes of death, including ones with a relatively low number of annual deaths, than commonly used in condensed lists. MDPI 2019-10-28 2019-11 /pmc/articles/PMC6862141/ /pubmed/31661859 http://dx.doi.org/10.3390/ijerph16214150 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Mitratza, Marianna Kunst, Anton E. Kardaun, Jan W. P. F. Detecting Mortality Trends in the Netherlands Across 625 Causes of Death |
title | Detecting Mortality Trends in the Netherlands Across 625 Causes of Death |
title_full | Detecting Mortality Trends in the Netherlands Across 625 Causes of Death |
title_fullStr | Detecting Mortality Trends in the Netherlands Across 625 Causes of Death |
title_full_unstemmed | Detecting Mortality Trends in the Netherlands Across 625 Causes of Death |
title_short | Detecting Mortality Trends in the Netherlands Across 625 Causes of Death |
title_sort | detecting mortality trends in the netherlands across 625 causes of death |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6862141/ https://www.ncbi.nlm.nih.gov/pubmed/31661859 http://dx.doi.org/10.3390/ijerph16214150 |
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