Neighborhoods shape the health of their residents, but those impacts have been difficult to measure over time or across populations.
New research from the University of Chicago seeks to bridge that gap, examining different dimensions of neighborhood vulnerability by using census data that covers nearly all of the United States.
By using innovative machine-learning techniques, researchers looked beyond the three most commonly tracked social determinants of health—education, minority status and poverty—to understand how different outcomes can be traced to a confluence of factors such as disability, rent burden and the lack of vehicle ownership.
“We know that these factors are individually important to health outcomes for a number of different reasons,” said Lect. Marynia Kolak, lead author of the new study and a health geographer trained in both public health and spatial statistics. “We wanted to understand why they seem to matter more in some places than others.”
Collaborating with the Center for Health Innovation at the American Hospital Association, Kolak and her fellow researchers looked at 71,901 census tracts in the U.S.—with approximately 312 million people—to identify neighborhood-level characteristics that impact health outcomes.
They then measured associations between these “social determinants of health” and premature mortality in Chicago. The variables range from English language proficiency, to whether most residents have access to a vehicle or face a high rent burden.
One key finding: Even after accounting for violent crime and regional differences, the team found that more than 65% of premature mortality in Chicago was associated with social determinants of health, such as lead exposure.
The cross-sectional study was published Jan. 29 in the Journal of the American Medical Association (JAMA) Open.
After gathering data, Kolak and her team created multiple indices reflecting different dimensions of vulnerability that reflect neighborhood advantage, mobility, opportunity and cohesion.