Education is a social determinant of health — and Philly’s data shows just how fast policy can move it.

As we kick-off the 2026-2026 school year, Generocity is relaunching our (e)mpact series with a focus on Education. Educational data is an often overlooked social determinant of health (SDOH). According to a study published in the Lancet Public Health, educational attainment plays a strong role in health by shaping opportunities, employment and income. By studying educational data, stakeholders can not only make important decisions regarding policy and resource allocation, but can help those making decisions better understand how to help the people in their community. As mentioned in the Lancet study, education is the most modifiable determinant of health; cities can have more direct influence over this determinant in comparison to others like poverty or mortality rates. Using our Philadelphia SDOH Climate Map on Tableau Public, we analyzed different educational data, and compared results with other SDOH indicators in different years from 2018 – 2023. The educational data referenced, specifically advanced/proficiency ratings for PSSAs, is used to better understand recent policy shifts in the city, and connects the data to other SDOH indicators from the same time period to highlight the relationship between each indicator and educational data.  

Policy Effect Insights

When examining the advanced/proficient scores per district across a 5-year period, there are a few telling insights across districts that are a direct response to a specific policy change within the Department of Education. Effective August 1st, 2024, the School District of Philadelphia reconfigured existing learning network boundaries to geographically align with major roadways, rivers, and train lines, considering current catchment areas as well. In doing so, certain schools that existed in one learning network were changed to completely different districts; this change directly affected learning district’s standardized testing results in the 2024-2025 school year, with some districts growing or decreasing in score dramatically. One district that suffered from major changes in their testing results was University Southwest. In both Math and ELA, University Southwest consistently performed well. However, in the 2024-2025 school year, when the learning networks were restructured, University Southwest’s advanced/proficiency scores dropped significantly. 

Another district that had a similar dramatic shift, however in the opposite direction, was Central. From 2018-2024, Central’s reading and math advanced/proficiency scores did not surpass 25%. However, following the network restructuring, Central’s reading advanced/proficiency rates increased to 51%, and math scores increased to 47%. Central is encompassed within Learning Network 4, which holds elementary and middle schools like Greenfield School, a consistently high-achieving K-8 school that was in Learning Network 5 prior to the 2024 restructuring. This showcases how something that can seem as simple as a policy change on paper, can have significant impacts to the people within the districts; as stated above, many policy adaptations and creations are rooted in the data yielded in each district. Therefore, the shift in schools from one district to another creates major shifts in district budgets based on where different schools like Title I or high-performing schools land.  

Social, Health, and Education Indicator Insights

When re-analyzing the SDOH indicators, North and Lower North are districts that had consistently high poverty rates, percentage of adults without a Bachelor’s degree, and percentage of adults without health insurance. Learning district 8 initially housed much of the North planning district schools from 2018-2024; however, when learning networks were redrawn to place schools in networks based on geography, North district schools got split between Learning Networks 8 and 9, with some Lower North schools entering into the network as others left. The geographical breakdown of learning networks shows a more accurate depiction of how district schools and students are performing and helps provide a clearer picture on the relationship between academic outcomes and social and health indicator data; specifically, the relationship between state testing advanced/proficiency scores and socioeconomic and health indicators like poverty status. 

The scores of the students within learning network 8, or Lower North and North district schools, pre- and post-restructuring highlight just how low this specific area is performing academically and how the lack of a strong academic foundation can, and is likely currently perpetuating a cycle of poverty and health concerns in different areas throughout the city. This does, however, connect to Title I funding; school districts have an overall Title I fund that is allocated amongst the schools that qualify for the funding through a formula. Therefore, if a school is added to the network/district, that would heavily impact the budget as the formula would be taking more schools into account than before, shifting priorities and therefore funds. While the restructuring of districts helps paint a more accurate picture, the potential real-time consequences of these shifts and specifically budgets can create a ripple of unintended negative consequences for the districts who need it the least. 

Why This Matters

In a study where 8 different cohorts were studied across time in 6 different geographical regions, the overall findings suggested that the relationship between low education and wealth might have largely impacted health conditions in early life stages, which led to persistent differences throughout older ages. The list of studies suggesting the importance of receiving a quality education goes on, but the fact remains that quality education helps prepare young people for a quality life, can help break the cycle of poverty, and can lead to more job and life opportunities. By impacting someone’s life early on, it helps set the stage for a balanced, sturdy life, and the easiest and fastest way districts, cities, states, and any other entity involved in policymaking can make an impact is through education.

There are a number of influences that affect the state of education and our schools, such as overall school climate, the number and types of programs the school provides, teacher attendance and satisfaction, and much more. Education data, when utilized properly and intersectionally, can help districts, cities, and  those directly involved in education policy create and revise policy and determine funding allocation that is rooted in real-time data.  

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Interested in digging into the data, check out the data we compiled and let us know what you would like to see in our Philadelphia SDOH Climate Dashboard.