PhD Student Brittney Marian Receives F31 Award from the National Institutes of Health

Brittney Marian is the recipient of the prestigious Individual Pre-Doctoral (F31) Award from the National Institutes of Health. Marian is a fifth-year student in the Doctor of Philosophy in Biostatistics program in the Department of Population and Public Health Sciences at the Keck School of Medicine of USC. The F31 grant is awarded to promising pre-doctoral candidates to obtain mentored research training while conducting their dissertation. Marian’s research focuses on time series clustering to identify and translate time-varying multipollutant exposures for health effects studies.

“Brittney is the first USC Biostatistics PhD student to receive an F31 award, and this major accomplishment is reflective of her talent and resourcefulness,” shares mentor Sandy Eckel, PhD, associate professor, and director of PhD programs in biostatistics. Erika Garcia, PhD, MPH, assistant professor of population and public health sciences also serves as Marian’s co-mentor.

Growing up in Riverside, CA smog alerts were a part of Marian’s childhood: “we couldn’t go out at recess or attend after school activities,” she reveals. “When I first came to USC, I worked on the Children’s Health Study and my hometown was listed as one of the cities with the worst air pollution.” Marian’s lived experience and this concerning data sparked her interest in air pollution exposures and time series methodologies.

Air pollution continues to be a concerning environmental health risk linked to a wide range of adverse health outcomes. “Ambient air pollution is a complex environmental exposure that arises from numerous sources and varies over time,” explains Marian. Historically, many air pollution health effects studies fail to consider more than a single pollutant at a time and rely on an exposure that has been averaged over time. Recently, there have been an increased number of studies on the impacts of multipollutant mixtures on human health, due to advancement in statistical methodologies. “However, these methodologies often result in hard-to-interpret effect estimates and do not always extend to repeated measures of exposure,” she indicates.

In order to address this, Marian intends to develop more interpretable and meaningful models for time series data. Time series data are a sequence of data points recorded over time; similar to meteorologists tracking the weather or analysts monitoring the performance of the economy. In Marian’s research, she intends to improve the methodologies used to study multiple pollutants in the air to help understand the health effects of collective exposures.

Marian’s dissertation aims to improve current mixtures methods and provide new tools for the study of time-varying exposures. She will achieve this through three projects. The first two projects focus on supplementing current literature by extending methodologies to the understandable and interpretable analysis of time series data, providing a strong foundation for later application to identify and translate multipollutant diurnal exposure profiles in the third project. The third project is an application in environmental epidemiological where she will identify the daily profiles of typical air pollutants found across Southern California and evaluate their associations with exhaled nitric oxide levels recorded in the Southern California Children’s Health Study. Exhaled nitric oxide is a marker of airway inflammation and increased levels have been associated with higher risk of asthma incidence. Through hourly monitoring, Marian will identify ambient air pollution exposures and relate them to pediatric health.

After graduation, Marian will continue conducting research to improve the scientific community by applying her skillset towards public health research. “I have a curiosity for learning and improving upon ideas and applying my expertise to work that genuinely benefits people,” she affirms. She also hopes to continue mentoring students who are interested in biostatistics. This past summer she was involved in LA’s Best at USC, which offers undergraduate students from across the country an opportunity to receive training in biostatistics and data science. “I am really proud of my accomplishment in receiving this award, especially as I had never envisioned attending graduate school. I loved the opportunity to share my experience with the LA’s Best mentees and encourage them—and share that if I can do it, they can do it too!”