Updated April 15, 2019
The Area Deprivation Index replaces the Vulnerable Population Footprint tool.
On April 5, 2019 we released our first iteration of the Area Deprivation Index (ADI). The ADI can show you where areas of deprivation exist in your location. The ADI is calculated by combining 17 indicators of income, education, employment, and housing quality.
There are 3 ways the ADI can help communities and changemakers:
1. Help to Target Valuable Resources
2. Benchmark Your Community to Others
3. Identify Disparities within Your Community
Other resources you might find useful:
- Here’s What You Can Do on Community Commons Now
- The Community Commons Map Room is where – with just a few clicks – you’re on your way to looking at visual data of your community.
- Our Member Gallery is a great place to see what other communities are doing with the data, stories, and collections available on the Commons.
Researchers have identified that educational attainment and poverty are two factors that can have significant influence when it comes to health. When organizations focus their work on improving these two disparities, health outcomes can improve for everyone.
Our Vulnerable Populations Footprint (VPF) tool helps identify areas of a community with specific levels of educational attainment and poverty. Community Commons team member Eloi Espanol breaks it down for us.
How is it Mapped?
After specifying a location, the following information is mapped.
Orange represents a scale displaying precent of population in poverty for a specific area
Purple represents a scale displaying percent of population with less than a high school education for a specific area.
Brown represents those areas in which specific degrees of poverty and educational attainment converge.
In this case, for instance, brown areas are those in which at least 30 percent of the population is in poverty and at least 25 percent of the population has less than a high school education.
The threshold values can be adjusted by the user in order to display a customized definition of area.
In the example below, there are now more brown areas that in the previous map because the thresholds have been reduced and now more areas fit the definition created.
The brown areas now represent at least 20 percent of the population is in poverty and at least 14 percent of the population has a less than high school education.
How is it Interpreted?
The resulting brown areas do not necessarily represent individuals with both characteristics at the same time, but areas which have both defined characteristics independently. As a result, we cannot tell how many people in the area are poor and have less than a high school education.
Imagine a case in which our orange area had at least 30 percent of the population in poverty. Our purple area had at least 20 percent of the population with a less than high school education. The brown areas are defined as having both. If 10 people lived in this area, two realities would be possible.
In both cases, 30 percent of the population is in poverty and 20 percent of the population has less than a high school education, but the distribution of these characteristics is different in each case. This happens because the available data doesn’t allow us to know if an individual has both characteristics at the same time.
Fortunately, there are many data sources that do break down into individual numbers, such as male population or 18-64 years population, and that data for your VPF can be seen when you generate a report.