Big data to be used to investigate dietary patterns

Associate Professor Hua Fang (Computer & Information Science) was recently awarded $2,735,127 as part of a prestigious National Institutes of Health (NIH) Research Project Grant (R01).

Fang’s award for her research project titled “iPAT: Intelligent Diet Quality Pattern Analysis for harmonized MA-National trials” is the first R01 grant in the history of UMass Dartmouth and Fang’s second such honor. The R01 grant program was created to support health-related research and is the oldest grant mechanism used by NIH.

Fang’s multi-year, multi-site project will combine several large longitudinal dietary datasets from highly comparative randomized controlled trials and observational studies for chronic diseases like diabetes, cardiovascular disease, or obesity generated from her ongoing NIH Vaccine Immunology Program (VIP) project. Leveraging these large data sets, the Intelligent Diet Quality Pattern Analysis (iPAT) research team will detect patterns that capture the long-term diet quality variations among people and examine pattern-associated chronic diseases for participants.

Most importantly, Fang will lead her research team to develop further intelligent diet quality pattern analysis that will help people visualize distinctions among complex diet patterns, shed light on how patterns evolve in relationship to health outcomes, and clarify how well a diet pattern works in various subgroups.

“It is a great honor to receive this large-scale research grant award from NIH, and it is a recognition of my many-year research in trajectory pattern recognition in longitudinal studies and its potential expansions, as well as the joint efforts, expertise, local and national recourses from our investigator team, related labs, centers, and institutions,” said Fang.

“Our work will help grow more valid evidence for formulating dietary guidelines and may enable better personalized, adaptive dietary strategies, leading towards the next phase of digital trials and nutrition precision health,” said Fang.

Fang is leading a national research team that includes UMass Dartmouth Professor Honggang Wang (Electrical & Computer Engineering) and faculty members from UMass Medical School, including Jeroan Allison, Arlene Ash, Catarina Kiefe, and Milagros Rosal. The team also consists of Lyn Steffen of the University of Minnesota, Lesley Tinker of the Fred Hutchinson Cancer Research Center, James Shikany of the University of Alabama at Birmingham, and Associate Professor Molin Wang of the Harvard T.H. Chan School of Public Health. UMass Dartmouth students from Fang’s Computational Statistics and Data Science Lab will participate as research assistants.

“I’d like to congratulate Dr. Fang on receiving such a prestigious grant award for the second time in her career and for being the first UMass Dartmouth researcher to receive an NIH R01 grant,” said Ramprasad Balasubramanian, PhD, Vice Chancellor for Research and Innovation.

Fang’s research project has twin goals.

First, Fang and her team aim to better understand human food intake behavior and related health risks, which is critical for important societal goals such as preventing or managing many chronic conditions, promoting well-being and safety, and improving lifelong health learning. The second goal is to evolve the use of the iPAT tool and system to uncover more valid evidence for dietary guidelines and more broadly contribute to creating a platform that supports harmonized data management, near-real-time intelligent pattern analyses, and adaptive interventions, leading towards the next phase of digital trials and nutrition precision health.

“Dr. Fang and her team’s research of how diets influence other processes within the body is remarkable. I have no doubt their results will further our understanding of this important issue.”

The NIH R01 award received by Fang is one of the most prestigious and highly competitive awards in America. It is the single largest highly competitive federal research grant award received in UMassD history. This grant, and Fang’s prior NIH grant are the first grants in the UMass System and the U.S. that particularly focus on longitudinal dietary data harmonization from local and national randomized controlled trials and observational studies. Fang’s emphasis on patient-derived visual analytics, pattern validation, statistical machine learning, and artificial intelligence-driven approach in nutrition precision health aligns with NIH and National Science Foundation strategic funding goals.