SOCIOECONOMIC STATUS, PSYCHOLOGICAL RESOURCES, & HEALTH

这是一个竞争性的续期申请，以支持一个关注社会经济地位与健康关系的项目的第03年和第04年，该项目考虑了一系列个人心理资源（即认知功能、人格特征和社会参与/社会资本）和家庭社会经济背景因素，对其进行了详细阐述。我们寻求对两个主要纵向数据集的二次分析的支持，这些数据集测量了生命周期中不同阶段的社会经济经历、认知功能、个性、社会参与和健康方面的个体差异。本研究的主要目标是解决以下四个具体目标：(1)调查中年人当前社会经济状况（如教育、职业、收入和资产、就业状况）与多个健康和功能领域（如身体、心理、认知、社会）、其他健康风险和人口因素之间的关系；(2)研究当前社会经济地位与健康之间联系的机制（如童年社会经济地位、成年前认知功能、社会整合、人格特征、健康行为的作用）；(3)研究这些机制如何阐明和调节社会经济地位与健康之间的联系；(4)在可能的情况下，检验在这些关系和机制中发现的模式是否因性别、种族/民族或特定健康领域而异。为了完成这些任务，我们寻求对两个现有纵向数据集的分析支持：(1)威斯康星纵向研究（WLS），样本是来自威斯康星州的1957名高中毕业生（n=8,493），从1992-93年的青年到大约52岁；(2)健康与退休研究（HRS），这是一项针对51-61岁退休前男性和女性的全国性小组研究，于1992年进行评估（n=9,824），并于1994年和1996年再次进行访谈。我们建议采用一系列统计程序，包括结构方程模型、潜在增长曲线分析和逻辑回归技术来分析这些数据。

This is a competing renewal application to support years 03 and 04 of a project focusing on the relationship of socioeconomic status and health, elaborated on by the consideration of a range of personal psychological resources (viz. cognitive functioning, personality characteristics, and social participation/social capital) and family socioeconomic background factors. We seek support for the secondary analysis of two major longitudinal data sets that measure socioeconomic experiences, individual differences in cognitive functioning, personality, social participation, and health at various points in the life-span. The main objectives of the proposed research are to address four specific aims: (1) to investigate the relationships of various measures of current socioeconomic status (e.g. education, occupation, income and assets, employment status) on multiple health and function domains (e.g., physical, psychological, cognitive, social), net of other health risk and demographic factors, in middle-aged adults; (2) to examine the mechanisms underlying the links between current socioeconomic status and health (e.g., the role of childhood socioeconomic status, pre-adult cognitive functioning, social integration, personality characteristics, health behaviors); (3) to examine the ways in which these same mechanisms elaborate and moderate the linkages between SES and health; (4) to test whether the patterns found in these relationships and mechanisms differ by gender, race/ethnicity, or across specific health domains, where possible. To accomplish these tasks, we seek support to analyze two existing longitudinal datasets: (1) the Wisconsin Longitudinal Study (WLS), a sample of 1957 high school graduates from the state of Wisconsin (n=8,493), followed from youth to approximately age 52 in 1992-93; and (2) the Health and Retirement Study (HRS), a national panel study of preretirement men and women aged 51-61 assessed in 1992 (n=9,824), and reinterviewed in 1994 and 1996. We propose to employ a range of statistical procedures, including structural equation modeling, latent growth curve analysis, and logistic regression techniques in the analysis of these data.