Jaemin Jeon
Research Mentor(s): Peter Larson
Mentor Department: Injury Prevention Center/School of Public Health/SEAS
Authors: Jaemin Jeon, Douglas Wiebe, Nichole Whitehead, Jason Goldstick, Peter S. Larson
Session: Session 1 (9:00am – 9:50am)
Presentation Type: Poster 63
Abstract
Background: Injury-related outcomes, including drowning, violence including firearm-related incidents, and self-harm/suicide, are thought to have associations with environmental factors such as precipitation, extreme temperature and air pollution. Despite growing evidence of these associations, there are limited resources that explore the relationship between injury-related outcomes and environmental factors through an interactive interface. Objective: This study will develop and test an interactive Environment and Injury Outcome Tracker (EIOT) to allow users to explore possible links between environmental factors and injury. This interactive tool will help to inform research and policy initiatives on environmental health and injury. EIOT will help to expand knowledge of how the ambient environment influences risk for important injury outcomes. Methods: EIOT will be developed using R Shiny, a web based tool for creating interactive data visualizations. This tool will visualize mortality from select injury related categories using data from the US Centers for Disease Control and other sources. For environmental data, we will use temperature and precipitation data from the PRISM climate group along with pollution data from the Environmental Protection Agency. This dashboard will aggregate and visualize state- and county-level injury data across multiple demographics, including gender, age, and race, over different time periods and provide an interactive U.S. map where users can explore injury trends at various geographic levels, allowing for comparative analysis between states and counties. Dashboard functionality will include summary statistics, normalization by population for all variables but will also include regression based tests for association between county level environmental exposures and mortality counts. The tool will visualize prominent clusters of hot and cold spots of injury measures and locations where injury outcomes are significantly higher or lower than those predicted by environmental variables.
