PLACES: Local Data for Better Health

Abstract

Local-level data on the health of populations are important to inform and drive effective and efficient actions to improve health, but such data are often expensive to collect and thus rare. Population Level Analysis and Community EStimates (PLACES) (www.cdc.gov/places/), a collaboration between the Centers for Disease Control and Prevention (CDC), the Robert Wood Johnson Foundation, and the CDC Foundation, provides model-based estimates for 29 measures among all counties and most incorporated and census-designated places, census tracts, and ZIP Code tabulation areas across the US. PLACES allows local health departments and others to better understand the burden and geographic distribution of chronic disease-related outcomes in their areas regardless of population size and urban-rural status and assists them in planning public health interventions. Online resources allow users to visually explore health estimates geographically, compare estimates, and download data for further use and exploration. By understanding the PLACES overall approach and using the easy-to-use PLACES applications, practitioners, policy makers, and others can enhance their efforts to improve public health, including informing prevention activities, programs, and policies; identifying priority health risk behaviors for action; prioritizing investments to areas with the biggest gaps or inequities; and establishing key health objectives to achieve community health and health equity.

Figure 1

Screen shot of a PLACES Compare Counties Report comparing data for 3 Georgia counties and the US overall. Users can choose and compare data between the US and up to 3 counties.

Figure 2

PLACES interactive map application (www.cdc.gov/PLACES). Users can examine and visualize health data estimates across different geographic levels by using the PLACES interactive mapping application. By clicking a specific location, the selected measure (eg, estimated prevalence and crude prevalence) will appear for the selected chronic disease at that location. By zooming in and clicking on a particular geographic area, users can view the estimate for smaller geographic units. In Figure 2A, the county-level prevalence of COPD in Dekalb County, Georgia, is shown. Figure 2B displays COPD prevalence estimates at the ZIP Code tabulation area (ZTCA), which can be discerned by looking at the layer tool. Abbreviations: COPD, chronic obstructive pulmonary disease; PLACES, Population Level Analysis and Community EStimates.