CPH alumna Taniqua Ingol, MPH ’17, BSPH ’15, works as a research associate and data coordinator in Keim Lab at Nationwide Children's Hospital in Columbus, where she studies child health and growth outcomes.
Ingol was recently awarded a diversity supplement grant from the National Institutes of Health (NIH) and the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), to provide support to underrepresented individuals in health-related fields for research experiences. Ingol said the lack of representation of people of color in academia and health-related research has “increased her drive to work hard in the field of public health.”
“A lot of the health disparities that we see disproportionately affect communities of color. It is my God-given duty to advocate for them and to help future generations through my work,” Ingol said. “Growing up, I lived in poverty and struggled with my eating and physical activity behaviors. Thus, I can empathize with what they are going through when trying to make behavior changes.”
With this grant, Ingol plans to link birth certificate data to primary data collected during the Play and Grow Study conducted by Sarah Anderson, PhD, professor of epidemiology at the College of Public Health, and Sarah Keim, PhD, from Nationwide Children’s Hospital, to gain access to participating mothers’ weight status during and before the periconceptional period. She then hopes to examine the association between “maternal weight-change patterns across pregnancy ... and child overweight and obesity status at 18 months of age.”
“There is emerging epidemiological evidence that suggests that risk factors for childhood obesity emerge as early as the periconceptional period,” Ingol said. “If there is some truth to these findings, we need to be open and honest with women and let them know that their eating and physical activity behaviors before and during pregnancy could affect their child’s obesity risk in the future.”
She hopes to use data from the 300 mother-child participants in the Play and Grow Study to gain access to their vital statistics data. Once the data is obtained, Ingol will work alongside one of the co-mentors on the project, Joe Rausch, PhD, to learn an advanced method of statistical modeling called Latent Class Mixture Modeling. According to Ingol, this modeling technique is flexible and allows researchers to construct an accurate representation of growth trajectories. She emphasizes the importance of using data to drive cost-saving, efficient public health solutions.
“Data should drive everything,” Ingol said. “We need to use data to guide how we address issues like childhood obesity and other epidemics. It’s important to use data to drive science. Sadly, we don’t always see that.”