Assessing seasonality and the role of its potential drivers in environmental epidemiology: a tutorial
| Autor: | Lina Madaniyazi, Aurelio Tobias, Yoonhee Kim, Yeonseung Chung, Ben Armstrong, Masahiro Hashizume |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2022 |
| Předmět: | |
| Zdroj: | Digital.CSIC. Repositorio Institucional del CSIC instname |
| ISSN: | 0300-5771 |
| Popis: | 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. This work was primarily supported by the Japan Society for the Promotion of Science (JSPS) KAKENHI (grant number 19K19461). A.T. was supported by the Japanese Society for the Promotion of Science (JSPS) Invitational Fellowships for Research in Japan (S18149). Y.C. was supported by a Senior Research grant (2019R1A2C1086194) from the National Research Foundation of Korea (NRF), funded by the Ministry of Science, ICT (Information and Communication Technologies). M.H. was supported by the Japan Science and Technology Agency (JST) as part of SICORP, grant number JPMJSC20E4. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|