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Assessing seasonality and the role of its potential drivers in environmental epidemiology: a tutorial
Several methods have been used to assess the seasonality of health outcomes in epidemiological studies. However, little information is available on the methods to study the changes in seasonality before and after adjusting for environmental or other known seasonally varying factors. Such investigati...
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/PMC9557844/ https://www.ncbi.nlm.nih.gov/pubmed/35639562 http://dx.doi.org/10.1093/ije/dyac115 |
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author | Madaniyazi, Lina Tobias, Aurelio Kim, Yoonhee Chung, Yeonseung Armstrong, Ben Hashizume, Masahiro |
author_facet | Madaniyazi, Lina Tobias, Aurelio Kim, Yoonhee Chung, Yeonseung Armstrong, Ben Hashizume, Masahiro |
author_sort | Madaniyazi, Lina |
collection | PubMed |
description | Several methods have been used to assess the seasonality of health outcomes in epidemiological studies. However, little information is available on the methods to study the changes in seasonality before and after adjusting for environmental or other known seasonally varying factors. Such investigations will help us understand the role of these factors in seasonal variation in health outcomes and further identify currently unknown or unmeasured risk factors. This tutorial illustrates a statistical procedure for examining the seasonality of health outcomes and their changes, after adjusting for potential environmental drivers by assessing and comparing shape, timings and size. We recommend a three-step procedure, each carried out and compared before and after adjustment: (i) inspecting the fitted seasonal curve to determine the broad shape of seasonality; (ii) identifying the peak and trough of seasonality to determine the timings of seasonality; and (iii) estimating the peak-to-trough ratio and attributable fraction to measure the size of seasonality. Reporting changes in these features on adjusting for potential drivers allows readers to understand their role in seasonality and the nature of any residual seasonal pattern. Furthermore, the proposed approach can be extended to other health outcomes and environmental drivers. |
format | Online Article Text |
id | pubmed-9557844 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-95578442022-10-14 Assessing seasonality and the role of its potential drivers in environmental epidemiology: a tutorial Madaniyazi, Lina Tobias, Aurelio Kim, Yoonhee Chung, Yeonseung Armstrong, Ben Hashizume, Masahiro Int J Epidemiol Education Corner Several methods have been used to assess the seasonality of health outcomes in epidemiological studies. However, little information is available on the methods to study the changes in seasonality before and after adjusting for environmental or other known seasonally varying factors. Such investigations will help us understand the role of these factors in seasonal variation in health outcomes and further identify currently unknown or unmeasured risk factors. This tutorial illustrates a statistical procedure for examining the seasonality of health outcomes and their changes, after adjusting for potential environmental drivers by assessing and comparing shape, timings and size. We recommend a three-step procedure, each carried out and compared before and after adjustment: (i) inspecting the fitted seasonal curve to determine the broad shape of seasonality; (ii) identifying the peak and trough of seasonality to determine the timings of seasonality; and (iii) estimating the peak-to-trough ratio and attributable fraction to measure the size of seasonality. Reporting changes in these features on adjusting for potential drivers allows readers to understand their role in seasonality and the nature of any residual seasonal pattern. Furthermore, the proposed approach can be extended to other health outcomes and environmental drivers. Oxford University Press 2022-05-26 /pmc/articles/PMC9557844/ /pubmed/35639562 http://dx.doi.org/10.1093/ije/dyac115 Text en © The Author(s) 2022. Published by Oxford University Press on behalf of the International Epidemiological Association. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs licence (https://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial reproduction and distribution of the work, in any medium, provided the original work is not altered or transformed in any way, and that the work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Education Corner Madaniyazi, Lina Tobias, Aurelio Kim, Yoonhee Chung, Yeonseung Armstrong, Ben Hashizume, Masahiro Assessing seasonality and the role of its potential drivers in environmental epidemiology: a tutorial |
title | Assessing seasonality and the role of its potential drivers in environmental epidemiology: a tutorial |
title_full | Assessing seasonality and the role of its potential drivers in environmental epidemiology: a tutorial |
title_fullStr | Assessing seasonality and the role of its potential drivers in environmental epidemiology: a tutorial |
title_full_unstemmed | Assessing seasonality and the role of its potential drivers in environmental epidemiology: a tutorial |
title_short | Assessing seasonality and the role of its potential drivers in environmental epidemiology: a tutorial |
title_sort | assessing seasonality and the role of its potential drivers in environmental epidemiology: a tutorial |
topic | Education Corner |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9557844/ https://www.ncbi.nlm.nih.gov/pubmed/35639562 http://dx.doi.org/10.1093/ije/dyac115 |
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