Value of Education-Paths to Well Being over Life Course

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DESCRIPTION (provided by applicant): The overall aim of the proposed research is to examine possible etiologic pathways explaining the associations between education and health among an African American population. The population consists of a total cohort (N=1242) of African American adults first studied in 1966 when they were in first grade in Woodlawn, an inner city neighborhood of Chicago. They were assessed in first grade (1966), in third grade (1968), during adolescence (1976), in 1993-94 when they were young adults; they are currently being interviewed again at age 42. In particular, this study will investigate how educational performance and achievement relate to health risk behaviors and physical and psychological health outcomes. The Woodlawn data includes information about educational performance and achievement throughout the life course as well as information about health risk behaviors, such as cigarette, alcohol and drug use, and physical and mental health conditions of the cohort over the life course. Mortality data also have been collected. We focus on a life course developmental framework for understanding how family background of education, one's own educational performance, and school engagement may enhance one's physical and mental health within an African American population. We consider several possible etiologic pathways that might explain the association between education and health. The first specific aim focuses on the relationship between educational achievement and adult health problems, taking into account socioeconomic resources during childhood, adolescence, and adulthood. The second aim examines the dynamic relationship across development between school performance and psychological well-being. The third aim examines the relationship between childhood school performance and attachment and later social integration and health. Finally, the fourth aim examines the bi-directionality of the relationship between education and health across generations and throughout the life course. We will employ multiple regression, survival analyses, and structural equation modeling for the analyses of these research questions.