Assessing seasonality and the role of its potential drivers in environmental epidemiology: a tutorial

Author:

Madaniyazi Lina12ORCID,Tobias Aurelio13,Kim Yoonhee4,Chung Yeonseung5ORCID,Armstrong Ben6,Hashizume Masahiro27

Affiliation:

1. School of Tropical Medicine and Global Health, Nagasaki University , Nagasaki, Japan

2. Department of Pediatric Infectious Diseases, Institute of Tropical Medicine, Nagasaki University , Nagasaki, Japan

3. Institute of Environmental Assessment and Water Research (IDAEA), Spanish Council for Scientific Research (CSIC) , Barcelona, Spain

4. Department of Global Environmental Health, Graduate School of Medicine, The University of Tokyo , Tokyo, Japan

5. Department of Mathematical Sciences, Korea Advanced Institute of Science and Technology , Daejeon, South Korea

6. Centre for Statistical Methodology, London School of Hygiene & Tropical Medicine , London, UK

7. Department of Global Health Policy, Graduate School of Medicine, The University of Tokyo , Tokyo, Japan

Abstract

Abstract 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.

Funder

Japan Society for the Promotion of Science (JSPS) KAKENHI

Japanese Society for the Promotion of Science (JSPS) Invitational Fellowships for Research in Japan

Senior Research

National Research Foundation of Korea

Ministry of Science, ICT

Japan Science and Technology Agency (JST) as part of SICORP

Publisher

Oxford University Press (OUP)

Subject

General Medicine,Epidemiology

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