Investigate factors that account for differences in health among populations
Objective 3: Investigate factors that account for differences in health among populations
Variations exist between populations—grouped by such factors as age, sex, race, and ancestry—in susceptibility and resilience to heart, lung, blood, and sleep (HLBS) diseases and in disease course and outcomes. While some of these variations are caused by genetic and other biological factors, a wide range of behavioral factors and socioeconomic inequities also contribute to health disparities. Research is needed to better understand the causes of population health differences and to identify strategies to effectively address these differences. Investigations in this area may range from basic laboratory studies to population science to community-centered implementation research.
Envision a future in which we are able to...
Leverage a deeper understanding of biologic differences related to sex or ancestral groups (e.g., variation in ancestry leading to differences in asthma phenotypes among ethnic subgroups) to devise more precise, targeted intervention strategies and further improve clinical outcomes.
Reduce health disparities and inequities in an era of information technology by leveraging epidemiology and the power of data science to understand and solve complex health problems.
What community-based effectiveness and implementation research strategies can help address HLBS health inequities? (3.CQ.01)
How can we improve the representation of women, minority, and disadvantaged populations in clinical research studies and ensure that findings are applicable to these populations? (3.CQ.02)
What are the environmental, genetic, and epigenetic factors and molecular, cellular, and systemic mechanisms that determine sex-related differences in HLBS health and disease? (3.CQ.03)
Do the factors that render individuals or populations subjected to the same exposures (e.g., diet, smoking, other environmental and social exposures) resilient or susceptible to disease differ across the lifespan and by sex/gender? (3.CQ.04)
How can cardiometabolic risk be managed to improve health trajectories in specific populations (e.g., according to race, ethnicity, sex/gender, socioeconomic status)? (3.CQ.05)