HealthLandscape Launches a New Mapping Tool
Using Census Tract-Level Data from the CDC 500 Cities
Small area estimates of health and health outcomes are difficult and prohibitively expensive to acquire. National data systems such as the National Health Interview Survey and the Behavioral Risk Factor Surveillance System do not collect samples large enough to produce detailed small area data. And while state and local efforts like the California Health Interview Survey and the Greater Cincinnati Community Health Status Survey are important efforts, most communities find these projects to be cost prohibitive.
The ambitious 500 Cities Project was launched by the Centers for Disease Control and Prevention (CDC), along with the Robert Wood Johnson Foundation, and the CDC Foundation. Its purpose is to allow cities and local health departments gain a better understanding of the health issues and geographic distribution of health measures in their municipal boundaries.
With the Project 500 Cities Mapping Tool, users can map synthetic small area estimates for chronic disease risk factors, health outcomes, and clinical preventive services at the Census Tract level for the largest 500 cities across the U.S. (To ensure inclusion of all states, 3 cities from Vermont, West Virginia, and Wyoming were included in the 500 list).
The Project 500 Cities Mapper allows users to select 27 metrics from three major categories (Unhealthy Behaviors, Health Outcomes, and Prevention) and use a slider bar to set thresholds. By default, thresholds are set at values that represent national benchmarks.
The tool will highlight those counties that are outside of the national benchmark, or will incrementally shade or remove counties depending on how the user modifies the thresholds for selected indicators. Darker gradations of color will indicate which counties are outside of the established thresholds for multiple indicators. Users can also view a histogram that shows the number of counties outside of thresholds by the number of indicators, allowing users to quickly filter by the number of indicators that are outside of the established thresholds.
In these two examples, we compare the combined distributions of Binge Drinking, Smoking, and lacking Leisure Time Physical Activity as markers of health risk for Chicago and Seattle.