Time series analysis in environmental epidemiology: challenges and considerations

• Authors: Sandra Gudziunaite , Zana Shabani , Lisbeth Weitensfelder , Hanns Moshammer

Abstracts

EN

In environmental epidemiology, time series analyses represent a widely used statistical tool. However, though being commonly used, there is soften confusion regarding the specific requirements, such as which link function might be most appropriate, when or how to control for seasonality or how to account for lags. The present overview draws from experiences in other disciplines and discusses the proper execution of time series analyses based on considerations that are relevant in environmental epidemiology. Time series analysis in environmental epidemiology focuses on acute events caused by short-term changes in exposure. These exposures should be fairly wide-spread affecting a large number of persons, usually all inhabitants of a political entity. Pollutants in air or drinking water as well as meteorological factors serve as typical examples. Despite the many time series analyses performed world-wide, some health effects that would lend themselves to that approach are still under-explored. This would include also some neurological and psychiatric endpoints.

Keywords

EN

statistical methods; regression models; environmental epidemiology; short-term effects; time series analyses; confounder control

• Publisher: Instytut Medycyny Pracy im. prof. dra Jerzego Nofera w Łodzi
• Journal: International Journal of Occupational Medicine and Environmental Health
• Year: 2023
• Volume: 36
• Issue: 6
• Pages: 704-716

Dates

published

2023

Contributors

author

Sandra Gudziunaite

• Medical University of Vienna, Vienna, Austria (Department of Environmental Health, Center for Public Health)

author

Zana Shabani

• University of Hasan Pristina, Pristina, Kosovo (Medical Faculty)

author

Lisbeth Weitensfelder

• Medical University of Vienna, Vienna, Austria (Department of Environmental Health, Center for Public Health)

author

Hanns Moshammer

• Medical University of Vienna, Vienna, Austria (Department of Environmental Health, Center for Public Health)

Identifiers

DOI

10.13075/ijomeh.1896.02237

Biblioteka Nauki

23364734