This biodemographic investigation has two primary goals. First, we elaborate the relationship between life challenge and health, exploring how the social environment affects that relationship. Specifically we: 1) Identify challenges that are most strongly associated with, and discriminate best between, the preservation and deterioration of health; 2) Examine both the costs and benefits to health of social connection, support networks, instrumental assistance and emotional support, and social activity. We identify the components that are most important for the maintenance of mental and physical functioning and for mediating the effects of challenge on health outcomes; and 3) Explore the effects of cumulative advantage and cumulative adversity on health taking into account both timing and severity of life events. Second, we explore how our understanding of the relationships among life challenge, the social environment, and health can be enhanced by incorporating biological markers of health and stress. We: 1) Investigate the extent to which biological markers of stress and chronic illness are related to reports of life events; 2) Examine the associations between the biological markers and data from physicians' examinations and self-reported health status, and explore their links to survival based on data from death certificates and the household registry; and 3) Explore the extent to which the biological markers can explicate the relations among the social environment, challenge, and health.

We use unusually rich, population-based data from a longitudinal study of the elderly. These data have been collected periodically since 1989 and comprise detailed retrospective and current status information on health and on social, economic, and demographic characteristics. We collect biological markers of health and of life challenge from a subset of 1000 of the participants based on physical exams, and assays of blood and urine specimens. Our analytical strategy uses two multivariate procedures: 1) generalized linear models (especially those for limited dependent variables); and 2) grade of membership models. Our use of both techniques will exploit their complementary strengths for answering our research questions.

A public use data set and full documentation for the biomarker study are available from the ICPSR.

For publications from the biomarker study, please click on this link: Publications.