CPHA Scholars have contributed to this “long view” of the life course using many existing databases, including many public domain studies such as the Health and Retirement Study (HRS), the Panel Study of Income Dynamics (PSID), and National Longitudinal Surveys (NLS), and original Data Collections under Duke leadership. They also have developed new measurements and statistical methods for analyzing life-course data.
Illustrative CPHA research in this thematic area include:
- Scott Lynch studies the impact of educational and income inequality on trajectories of health and mortality in his project Understanding US Regional Health and Mortality Disparities: A Life Course Approach.
- Using the Chinese Longitudinal Healthy Longevity Survey (CLHLS), Yi Zeng explores which determinants from a large set of social, behavioral, biological and environmental risk factors are important for healthy longevity.
- Eric Stallard and colleagues have shown that the progression of Alzheimer’s disease is a multidimensional phenomenon with substantial heterogeneity at the point of patient intake and substantial variability in the rate of deterioration from various starting points.
- Tyson Brown investigates the intersectionality of race, ethnicity and gender and the heterogeneity in age trajectories of health across adulthood and investigates race, structural disadvantage, stress and health in later life using the HRS.
- Angela O’Rand and Scott Lynch document the increasing disparities in health and mortality associated with educational levels using the Integrated Health Interview Study (IHIS) over the last three decades.
- Jen’nan Read uses the American Community Survey (ACS) focusing on gender, age, health and ethnicity to investigate diversity in ethnic identity and its association with different patterns of disability and self-assessed health.
- Kaare Christensen focuses on understanding the pathways responsible for exceptional longevity in certain families that could lead to the discovery of targets for therapy or prevention in the wider population using data from the Long-Life Family Study (LLFS).