Emily O’Brien, PhD, assistant professor of medicine (Clinical Pharmacology and the Duke Clinical Research Institute), uses the tools of epidemiology to try to improve clinical care of patients with chronic health conditions such as cardiovascular and pulmonary disease.
“My research is mostly at the intersection between clinical research and epidemiological research,” she says. “I love focusing on large-scale problems and using data from many people to come up with actionable strategies for improving health.”
O’Brien particularly wants to shine a light on healthcare disparities. “Disparities work is really at the heart of public health,” she says. “I believe we have an imperative as researchers to improve access to care and health outcomes in high-risk populations so that everyone has the chance to live a healthy life. The first step is documenting where these disparities exist.”
How can epidemiology help address healthcare disparities?
Many factors contribute to healthcare disparities. Non-modifiable factors, like genetics, are important for identifying who is at highest risk so that appropriate screening and therapeutic strategies can be used. Modifiable factors are important because they provide a starting point for public health interventions, such as smoking cessation and physical activity programs, to reduce the incidence and impact of chronic disease. Epidemiologic research helps to elucidate the strength and direction of these risk factor associations so we can prioritize which strategies are most likely to reduce risk and improve health at the population level.
You recently published a paper in Circulation: Quality and Outcomes. What were your findings?
We had three major findings. First, depressive symptoms were common in the African American cohort, affecting nearly one quarter of study participants. Second, people with major depressive symptoms had greater risk of incident stroke and coronary heart disease than those with no depressive symptoms. Finally, this increased risk persisted even after accounting for other clinical and behavioral risk factors commonly associated with depression.
What is the significance of those findings?
These findings are significant for two reasons. First, depression in this population is more common than previously thought. Coupled with the fact that African Americans are less likely to receive treatment for depression, this underscores the importance of depression screening and identifying optimal therapeutic strategies in this high-risk population. Second, depressive symptoms were a strong and independent risk factor for stroke and heart disease. Effective therapies are available, so this increased risk can be managed. But first, the condition has to be identified.
What was your motivation for doing this study?
Other studies have shown a relationship between depression and cardiovascular disease, but many of these studies focused on white populations. In this study, we wanted to find out if there was a similar relationship in an African American population. African Americans are more likely to have cardiovascular disease and are at higher risk for complications, so it’s important to identify treatable risk factors. We used data from the Jackson Heart Study (JHS), which is a longitudinal, community-based cohort study of nearly 6,000 African Americans aged 21-94 years living in Jackson, Mississippi. The study has been following participants since 2000 to evaluate socioeconomic characteristics, health behaviors, and cardiovascular disease risk factors. Many studies to date have focused on only white populations. The Jackson Heart Study helps us understand the generalizability of those research findings to other racial and ethnic groups.
Final thoughts?
Health disparities research is an important part of improving public health, but we need data to conduct this research effectively. Minority populations are underrepresented in clinical trials, which reduces the generalizability of research findings. Improving engagement of minority and/or disenfranchised populations in research is critical to generating robust evidence to guide clinical care, particularly in high-risk subgroups.