Why compare Disparities across Urban, Suburban & Rural Locations?
We often talk about the importance of eliminating health disparities across race, ethnicity, gender, income and zip code. This activity focuses on geographic disparities, the differences within which other disparities (e.g. across race/ethnicity) are embedded. The discussion kit is designed to facilitate conversations about the extent of health disparities, their social determinants, root causes, and other determinants of health such as self-care and medical care.
Why is physical activity lower in some zip codes than others? What are the determinants for disparities in obesity and diabetes? Is there a connection? What about variances in the amount of investment in children’s education? The availability and accessibility of green space? What about the proximity of healthcare places and professionals?
For the purposes of this Discussion Kit we have researched data from three specific areas.
Anacostia in SE Washington DC is an historically Black community across the river from central DC. Historians have documented how centuries-old segregationist policies, including redlining have led to disinvestment and disparities on the doorstop of our Capitol. There are few healthcare resources, and the food dessert category applies. And yet billions of dollars have been spent there – on a major commuter freeway that separates communities from the waterfront, and very nearby you will find the place where all of Washington D.C. processes its wastewater.
Contrast that with Bethesda in Maryland on the NW border of Washington DC, close to the National Institutes of Health, the National Children’s Hospital, Sibley Memorial Hospital and Georgetown University. You can choose from three Whole Foods locations nearby, the sidewalks and parks are safe to walk and run, and the lack of a freeway deters suburbanite commuters.
Head south-west from DC and eventually you will arrive in Hazard, Kentucky, in the landlocked states that form central Appalachia. The railroad that opened in 1912 brought access to the coal in the mountains and Hazard became a boom town. The population grew. But the era of prosperity has since turned to decline, and the mining of coal took its toll on health, a pattern repeated throughout the coal fields of Appalachia. Disparaging stereotypes have been applied to these communities.
The extent of disparities is often surprising and disturbing. Data is abstract, but differences in life expectancy are real. Which disparities do we need to prioritize, and how do we move the needle? Research and discussion are essential to identifying community health needs.
For a more detailed discussion about using the discussion kit, see the video instruction video on this page.
How to use this discussion map activity: With the Discussion Guide.
Version 1: Using the provided reference data in the Discussion Guide
- Select a facilitator to lead the discussion and access the reference answers.
- Open the Discussion Map (or project the map onto a whiteboard using the downloadable slide set).
- Take a card from the deck (or select from the Discussion Guide). Ask the group to predict the value (e.g., “Life Expectancy”) for each geographic area (urban, suburban & rural).
- Write in predicted values in RED, using the provided erasable pens.
- Add actual results from the reference table in BLACK.
- Discuss the variances. Are they more or less than expected?
- Discuss the possible determinants of the disparities. How could the disparities be addressed?
Version 2: Choosing locations and finding data via Google
- Follow process as above, but choose your own urban, suburban, and rural zip codes (or counties, census tracts).
- Write the names of the locations on the map.
- Take a card from the deck. Ask the group to predict the value (e.g. “Life Expectancy”) for each geographic area (urban, suburban & rural).
- Use Google to research the actual data using keyword searches. Experiment with different keyword and location combinations.
Other parameters and determinants to consider and research:
- Primary care providers per 1000 population.
- Availability of fresh vegetables.
- Median Real Estate Tax
- Spending per pupil by school district
- Environmental Pollution (air, water, noise)