A recent study by Northwestern University has shed light on the substantial impact of residential segregation on the life expectancies of Black residents residing in highly segregated neighborhoods. The study reveals that individuals living in such areas face an average reduction of four years in their life expectancies when compared to their counterparts in less segregated predominantly white neighborhoods.
Life disparities
Through the systematic examination of disparities in life expectancy across different neighborhoods, the study effectively quantifies the contribution of residential segregation to racial health inequities based on geographical location.
In addition to the significant decrease in life expectancies, the research also uncovers a range of socio-economic challenges faced by residents in more segregated areas, including a higher likelihood of lacking college education, residing below the federal poverty line, and experiencing unemployment.
These socioeconomic characteristics are recognized as influential social determinants that impact overall health outcomes. The findings underline the critical role that residential segregation plays in perpetuating racial health disparities.
Empirical evidence
By providing empirical evidence of the link between neighborhood segregation and adverse health outcomes, the research highlights the urgent need for targeted interventions and policies that address the underlying causes of residential segregation. Only through addressing these systemic issues can we hope to achieve equitable health outcomes for all individuals, regardless of their place of residence.
“A common phrase is ‘your zip code is more important than your genetic code,’” the researchers explain. “At a broader level, we’ve learned much about the health consequences of adverse social determinants of health, but we were trying to better understand on a local level what the implications of racial segregation are on life expectancy.”
While prior studies have explored the life expectancy of racially segregated populations on a state and county level, this represents an effort to examine life expectancy at the neighborhood level.
Granular level
“By looking at this on the state or county level, you often don’t get at the impact of segregation at the neighborhood level; this emphasizes the importance of the local environment in which one resides,” the researchers explain. “Cook County is a great example of this with significant variation in life expectancy from among the highest in a neighborhood like Streeterville compared with the lowest in the South Side of Chicago.”
The study analyzed 63,694 census tracts in the United States to examine life expectancy. The national average life expectancy was 78 years. In predominantly Black neighborhoods with high racial segregation, the average life expectancy was 75 years, lower than the average life expectancy of 79 years in neighborhoods with low racial segregation.
The study also found differences in socioeconomic indicators between highly segregated and less segregated neighborhoods. A higher percentage of residents in highly segregated areas lacked a college education (81% compared to 69% in less segregated areas), lived below the federal poverty line (24% compared to 11% in less segregated areas), and were unemployed (16% compared to 8% in less segregated areas).
The researchers did not consider other factors such as access to healthcare, housing stability, and environmental pollution, which are related to structural racism and could potentially influence the relationship between segregation and life expectancy.
“While the mechanisms by which neighborhood segregation may contribute to differences in life expectancy are many, we sought to focus on key socioeconomic factors that are likely attributable to redlining and downstream differences by neighborhood in economic investment and resources in communities, which all have downstream consequences on health,” they conclude. “These factors explained more than half of the differences in life expectancy across neighborhoods in our analysis.”
