The SoDHI Collaborative
Vertical Divider
|
We collaborate with a number of outstanding research scholars and across several NIH-funded datasets:
|
Research Scholars We Collaborate With:
Elizabeth Brondolo, St. John's
Karen A. Matthews, UPSOM
Tené T. Lewis, Emory
Shari R. Waldstein, UMBC
Rick Sadler, MSU
Elizabeth Pantesco, Villanova
Gilbert C. Gee, UCLA
Laura Zahodne, UMICH
Karen A. Matthews, UPSOM
Tené T. Lewis, Emory
Shari R. Waldstein, UMBC
Rick Sadler, MSU
Elizabeth Pantesco, Villanova
Gilbert C. Gee, UCLA
Laura Zahodne, UMICH
NIH-Funded Datasets We Work With:
Healthy Aging in Neighborhoods of Diversity across the Life Span (HANDLS)
HANDLS seeks to disentangle the relationship between race, socioeconomic status, and health outcomes by asking questions pertaining to the different influences on age-related diseases. This study uses mobile medical research vehicles that serve as a community-based platform for clinical research. It includes approximately 3,720 African American and White community-dwelling adults living in urban Baltimore city. HANDLS is a 20-year, longitudinal study funded by the National Institute on Aging. At baseline, participants were 30-64 years old. HANDLS allows us to assess early life adversity, discrimination, SES, and a host of CVD and cerebrovascular endpoints. Read More |
The Health Retirement Survey (HRS)
The HRS, supported by the National Institute on Aging, provides multidisciplinary data that researchers can use to investigate endpoints and opportunities of aging. This panel study has surveyed over 20,000 U.S. individuals over age 50 every two years since 1992. HRS data comes in many forms, including core survey content on health insurance, employment and retirement, psychosocial functioning, and venous blood for biomarkers. Read More |
Study of Women's Health Across the Nation (SWAN)
SWAN is a multi-site longitudinal study of mid-life aging women. Over 3,000 racially/ethnically diverse women were initially enrolled in 1996 and have been followed annually since then. SWAN allows us to assess various psychosocial factors and their relation to CVD endpoints. Read More |
Vertical Divider