Green Space Data Challenge: Community Health Winners

Closing out our series of Q&As with the winners of the Green Space Data Challenge is the top-placing team of the Community Health category.

Community Health Challenge Category Winner: Uncovering Inequities in Green Space

Jia Xu, Yingtong Zhong, Tianyu Shi, and Yimin Sheng — all students at the University of Pennsylvania — believe in the power of data to advance environmental and social justice and improve community health. Jia, Yingtong, and Tianyu are all in the same Master’s degree program for social policy and data analysis. Jia also works as a research assistant for the School of Medicine and the Department of Political Science. Yimin, meanwhile, is earning her Master’s degree in computer and information technology.

When MDI began its Green Space Data Challenge, they were eager to participate. Their project on uncovering inequities in green space across the United States took first place in the Community Health category.

Q: Why did you take on this data challenge?

A: We believe that green space plays an important role in promoting community health and well-being and improving quality of life overall. We are also committed to leveraging data science in ways that drive positive social change, especially in local communities. For these reasons, we were all very excited to join this challenge.

Q: Tell us about your project. What was the problem you wanted to solve and what did you do with the data?

A: We wanted to examine the effects of green space on community fitness and wellness. At the time, there was no green space measure that captured environmental, health, and social impacts. So, we designed the Environmental-Social Green Space (ESGS) indicator, an actionable community indicator derived from fitness, greenery, and wellness data. It can be used to evaluate green space and environmental justice across the United States at the county level.

To create the ESGS indicator, we drew on data from four sources: The PAD-US-AR database, which contains information on protected areas in the U.S.; County Health Rankings, which provides data on health and social factors that affect health; the FEMA National Risk Index for Natural Hazards, which estimates annual losses due to natural hazards, social vulnerability, and community resilience; and EnviroAtlas, which provides geospatial data on the relationship between people and nature.

We then used a differential evolution algorithm to construct the ESGS index, integrating fitness, greenery, and wellness sub-level indices. Next, we conducted an ESGS equity analysis for eight demographic groups to assess whether green space impacts on community health are equitable. Finally, we performed a rigorous regression analysis and sensitivity analysis to validate our index.

We found that metropolitan cities across the U.S. enjoy higher ESGS scores — that is, they have more green space and higher levels of fitness and well-being. They have higher proportions of public park and forest cover, as well as lower rates of smoking, obesity, and excessive alcohol consumption than the population overall.

We also found several demographic inequities in ESGS scores. In the inner counties of the Western United States, we saw large ESGS inequities among older adults. In addition, we identified ESGS equity challenges in Southern counties with large Black populations. We also saw that cities in the South have low ESGS scores and high rates of crime and poverty.

These findings are not all that surprising. They show that places that are less privileged in terms of access to parks and other green space also tend to be less healthy.

Still, we believe that addressing geographic and demographic ESGS disparities is critical to promoting environmental and social justice and green space equity. Based on our findings, we have four recommendations.

First, counties in the West with significant aging populations should make their parks and recreational facilities more accessible and age friendly. Second, Southern counties with large Black populations should take a hard look at policies and institutions that may be perpetuating systemic racism and environmental and social injustice. Disadvantaged urban counties in the South should consider policies that encourage community-led green space projects that increase access to parks and recreational facilities. Finally, counties in the South with high rates of violent crime should improve green space safety and security.

Q: How did you decide on which dataset to use?

A: We wanted to use both county-level and city-level data and we wanted to capture the complex relationships between green spaces and their surrounding communities, so we needed a lot of variables. The four datasets we chose allowed us to do all this, and then we integrated the elements we chose from those data sets into our own data platform.

Q: What motivated you to focus on this topic area?

A: We all have a strong interest in social and environmental justice, and we have worked with green space data before. We wanted to do a project that would help advance the social good in some way and have a meaningful impact on communities. For us, this is really about the relationship between humans and their environment.

Q: How do you envision communities using what you created?

A: Communities can use the index to establish thresholds, or standards, for green space, and then they can see which parts of their communities are doing well and which are not. This kind of information can help inform new policies for increasing green space and improving community health. Community organizations and advocacy groups can all use the index to raise awareness of green space inequities and push for change. And local governments can use the index as a tool for prioritizing investment or interventions to improve green space quality and accessibility, especially in communities that are less privileged.

Q: What would you like to see happen with your idea/project next?

A: We want to continue refining the ESGS index and incorporating additional datasets and indicators as they become available. Ultimately, we would like to expand the geographic scope of the index so that it includes rural and less populated areas. Our hope is to contribute to a broader understanding of the importance of green space in promoting community health.