Thu Thi Nguyen Sc.D.

Dr. Nguyen uses a variety of different data sources (including Big Data) and approaches (including quantitative and qualitative research methods) to advance our understanding of social determinants of health. Dr. Nguyen also leads the interdisciplinary research collaborative, Big Data for Health Equity (BD4HE). BD4HE comprises faculty, trainees, and students from universities across the U.S committed to advancing theories, methods, and findings related to the use of Big Data for health equity research. The group investigates the impact of the social, cultural, and built environment on health disparities and identifies levers for change. An overarching objective of the group is to provide a formal space for training, mentorship, and collaboration.

She is the principal investigator of an R01, K99/R00, and American Heart Association postdoctoral fellowship examining the impact of discrimination and racial bias on health disparities. In her American Heart Association funded postdoctoral fellowship, Dr. Nguyen examined U.S. trends in encounters of health care discrimination overall and stratified by race/ethnicity and investigated the relationship between health care discrimination and biomarkers of cardiometabolic risk. Through her NIMHD K99/R00 funded research, she developed a place-level measure of racial climate from Twitter data and examined its association with birth and cardiovascular outcomes. This research project 1) compares the Twitter derived measure with existing national measures of racial attitudes and discrimination, 2) examines temporal trends in the relationship between place-level racial sentiment and adverse birth outcomes, and 3) investigates allostatic load, a measure of cumulative burden of chronic stress, as a mediator in the pathway between place-level racial sentiment and birth outcomes. Her recently awarded R01 builds upon the K99/R00 project to use online and social media data to track and detect changes in area-level racial bias and identify local and national race-related events. It will also determine the influence of changes in area-level racial bias on changes in adverse birth outcomes and identify protective factors to buffer the impact of racism on adverse birth outcomes.