Biomedical demography focuses on patterns of human health, frailty and longevity by linking various biological indicators—including biomarkers, neuroimaging and genomic information—to individual, family and other population data. CPHA Scholars are conducting biomarker and genomic data collection and research on human populations in the U.S. and around the world.
Illustrative biomedical demographic research includes:
- The Dunedin Multidisciplinary Health and Development Study carried out by Terrie Moffit and Avshalom Caspi is determining the impact of genomic factors (e.g. polygenic risk scores), genomic family history, family medical history, early life adversity, personality development, and other life course factors on the pace of aging.
- Dan Belsky demonstrates the heterogeneity in the “pace of aging” within a cohort using multiple clinical biomarkers and, most recently, genomic data through his project Advancing Translation of Molecular Signatures of Biological Aging.
- Using the Chinese Longitudinal Health Longevity Study (CLHLS), Yi Zeng identifies sex-related genomic sources of longevity.
- Seth Sanders and colleagues pursue the development of a new, unobtrusive method for measuring severe cognitive decline in their project Using Response Time Data from Social Science Surveys to Model Cognition and Early Alzheimer's Disease.
- Anatoliy Yashin is identifying the current time trends of Alzheimer’s disease (AD) and other dementias with a high level of accuracy. He is investigating the relationship between the time-trend in AD and the time-trend in cognitive impairment in U.S. older persons to reconcile their seemingly contradictory patterns and to uncover the role of potential risk factors contributing to variation of these time trends.
CPHA research scholars in the affiliated Biodemography of Aging Research Unit (BARU) also focus on genome-wide association studies of the biological bases of longevity, using data from many sources including the Framingham Study and the National Long-Term Care Survey, Medicare databases and patient’s electronic health records.