| Julie Plano |
Extreme weather events are becoming frequent and more severe. The effects of climate change on environmental factors can decrease air quality in many areas of the US, including the Northeast.
Air quality has important implications for public health. Exposure to pollutants, including fine particulate matter (PM2.5) have been linked to respiratory disease.
PM2.5 data was acquired from the Environmental Protection Agency (EPA) Air Quality System (AQS), a repository of ambient air quality data. These datasets are publicly accessible through AirNow. Using the maximum PM2.5 monitor measurement for each monitoring site by calendar day, we calculated a previous 5-day moving average PM2.5 value using PROC EXPAND in SAS, version 9.4. This average was then linked to patient health and location data to assess the incidence of PM2.5 and COVID-19-associated hospitalizations.
The EXPAND procedure is simple yet very efficient. Used here to create a moving average variable with a specified window size. In addition, PROC EXPAND can produce lead and lag variables or fill in missing data. This session is intended for intermediate users and will review the use of PROC EXPAND in current air quality analyses. |