Time series regression to identifying the relationship between air pollution and health in Vietnam

Abstract

Time series has been widely used in environmental epidemiology; especially in identifying the short-term associations between ambient air pollution and health outcomes. For both exposure and outcome, data are available at regular time intervals (daily hospital admissions and pollution levels) to explore short-term associations between them. In this article, we described main steps to conduct time series regression and highlighted some key ideas when applying this technique. A sample data was used to investigate short-term association between PM₁₀ and daily hospital admission among children in Hanoi between 2008 and 2016. This analysis was conducted with R software.