More than 40% of U.S. adults are affected by obesity, according to the Centers for Disease Control and Prevention (CDC). But in rural areas, the challenge is even greater, with obesity rates roughly six times higher than in urban communities. So why the disparity?
That’s the question Kennesaw State University Assistant Professor Liang Zhao at the College of Computing and Software Engineering is tackling. His research, backed by a $51,747 AIM-AHEAD grant from the National Institutes of Health (NIH), uses artificial intelligence (AI) and machine learning to explore the factors driving obesity rates in rural areas.
Health outcomes are shaped by more than just personal habits. Social determinants of health (SDOH)—factors like where you live, your income, education level, and job access—affect up to 70% of health outcomes. In rural areas, limited access to healthcare resources, fewer educational opportunities, and economic challenges create significant health barriers.
“These figures show the urgent need for targeted solutions in rural areas and highlight necessary changes,” Zhao said.
Zhao’s research examines how these factors contribute to obesity in underserved communities. Using AI and machine learning, he analyzes large datasets to identify patterns and help policymakers make data-driven decisions that could transform rural healthcare.
A key tool in Zhao’s research is the OCHIN database, a nonprofit healthcare innovation center that collects electronic health records and SDOH data from more than 6 million patients across 33 states. This extensive resource allows Zhao to uncover correlations between social factors and health outcomes, providing a clearer picture of how to combat rural obesity.
His goal? To develop a predictive model that identifies which factors most influence obesity in rural areas. The insights gained will guide policy recommendations to improve healthcare infrastructure, accessibility, and health education in these communities.
“We want to build a model that identifies contributing factors specific to these populations to drive widespread change,” he said.
Shaoen Wu, chair of KSU’s Department of Information Technology, praised Zhao’s efforts.
“We are proud to support Professor Zhao and his important research,” Wu said. “His work exemplifies our commitment to addressing real-world challenges and improving health outcomes in our communities.”
Addressing rural health disparities takes teamwork. Zhao has partnered with the AIM-AHEAD program, Morehouse School of Medicine, and Harvard Medical School to ensure his research benefits from a wide range of expertise and perspectives.
“Working with other brilliant minds allows us to create innovative solutions for the communities that need them most,” he said.
His findings will be tested against real-world data from rural hospitals, ensuring the results are both accurate and applicable. By combining AI with community insights, the research team can refine its model for maximum impact.
Zhao knows that change requires more than just data. Community engagement plays a critical role in his work. He plans to share his findings through workshops and meetings with rural residents and healthcare providers, sparking conversations about health challenges and potential solutions.
Looking ahead, Zhao envisions a comprehensive rural healthcare network shaped by community input while safeguarding patient privacy.
“If successful, this research could open new doors for funding and initiatives to address more health disparities,” Zhao said.
With innovation, collaboration, and a focus on real-world impact at the forefront, Kennesaw State is helping lead the way toward healthier futures for communities nationwide.
