A closer look at how neighborhoods shape public health

Innovative UChicago study examines U.S. census data for nearly 312 million people

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.

The researchers also characterized and mapped tracts in the U.S. and identified 10% of all tracts as falling into “extreme poverty.” Those “extreme poverty” tracts included areas afflicted by known public health crises, such as Flint, Michigan and the Navajo Nation.

Using a multidimensional approach, they were able to underscore the complexity of underlying social determinants of health, and how combinations of variables can amplify impact.

For example, the vulnerability of areas with high poverty and low educational attainment (i.e., neighborhood disadvantage) can be magnified if they are also composed of mostly elderly and disabled residents, who may have unique mobility and access needs. Distinguishing these phenomena can help researchers better measure and understand their interactions.

While factors such as income, poverty and health insurance status play a significant role in health outcomes, the new analysis revealed some deeper nuances.

“We hope this research will help to enrich public policy for people with limited access to health care or other disadvantages,” said co-author Yoon Hong Park, MPP’19, an alum of the Harris School of Public Policy who now works as a Cook County data fellow.

The researchers published in an open-source journal to make their work more accessible to health professionals, other scholars and the general public. Other co-authors on the study were Jay Bhatt, Norma Padrón and Ayrin Molefe of the AHA Center for Health Innovation.

Some members of the team are now exploring the use of place-based insights to influence policy decisions, while others are exploring how to develop place-based interventions to ensure the right support is provided to the right patient groups at the right time.

The assistant director for health informatics at UChicago’s Center for Spatial Data Science, Kolak believes that if health care professionals can pinpoint the combination of social factors that positively or negatively affect health care outcomes, they will be able to better tailor policies and programs to meet the needs of vulnerable populations.

“Geographic data science approaches to public health are in demand and rapidly emerging as health professionals acknowledge the impact that community, poverty, mobility and other place-based factors have on health,” she said.

Citation: “Quantification of Neighborhood-Level Social Determinants of Health in the Continental United States,” Kolak et al., JAMA Network Open, Jan. 29, 2020. DOI: 10.1001/jamanetworkopen.2019.19928

—A version of this story was originally published by the Division of the Social Sciences.