Kin Networks and Old-Age Survival During the Demographic Transition

点击翻译按钮获取中文摘要

Kin networks and old-age survival during the demographic transition Project Summary/Abstract This is a K01-award for Dr. Julia Jennings, a biological anthropologist and demographer at the University at Albany, State University of New York. Dr. Jennings is an early-career investigator in kin support and aging. This award will provide Dr. Jennings with the support to accomplish the following career development objectives: (1) to become an expert in social support, gerontology, and social network analysis; (2) to conduct original research on kin networks and adult mortality; (3) develop an independent research career and become competitive for R-level funding. To meet these objectives, Dr. Jennings has assembled a mentoring team that includes primary mentor Dr. Merril Silverstein, Marjorie Cantor Endowed Professor in Aging at Syracuse University and an expert in intergenerational support and aging in international contexts, and three co-mentors: Dr. Benjamin Shaw, an expert in the social determinants of healthy aging, Dr. Karl Rethemeyer, a social network analyst, and Dr. Ken Smith, a specialist on the familial aspects of health, aging, and longevity. Kinship and social ties are associated with longer lives among older adults. This project will focus on the associations among multiple measures of kin networks, the spatial location of kin, and old-age mortality; the possible role of economic status in explaining these relationships; and network change over time. In Aim 1, Dr. Jennings will use a unique historical dataset with 60 years of observation to study whole kin networks for an entire population. She will address possible independent and joint effects of the structure and spatial distribution of kin networks and change over time and the life course. In Aim 2, Dr. Jennings will investigate the effects of co-resident kin and survival using a modern linked census sample from the same country. Aim 3 will focus on the relationship between social network measures and health status in a longitudinal study of aging from the same country while drawing comparisons across the datasets and findings from Aims 1-2. Each aim will use advanced quantitative techniques, including social network analysis, spatial analysis, and event history analysis. This research will be the foundation of a R01 application on the effects on kin networks on mortality in contemporary and comparative contexts to be submitted in the last year of the K-award.