SOCIOECONOMIC STATUS, PSYCHOLOGICAL RESOURCES, & HEALTH

这是一个竞争性更新应用程序，用于支持一个项目的 03 和 04 年，重点关注社会经济地位与健康的关系，通过考虑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来详细阐述。我们寻求对两个主要纵向数据集的二次分析的支持，这些数据集衡量生命周期不同阶段的社会经济经历、认知功能、个性、社会参与和健康的个体差异。拟议研究的主要目标是解决四个具体目标：（1）调查中年成年人当前社会经济状况（例如教育、职业、收入和资产、就业状况）的各种衡量标准与多个健康和功能领域（例如身体、心理、认知、社会）的关系，排除其他健康风险和人口因素； (2) 研究当前社会经济地位与健康之间联系的潜在机制（例如，儿童社会经济地位的作用、成年前的认知功能、社会融合、人格特征、健康行为）； (3) 研究这些相同机制阐述和调节社会经济地位与健康之间联系的方式； (4) 测试这些关系和机制中发现的模式是否因性别、种族/民族或在可能的情况下跨特定健康领域而有所不同。为了完成这些任务，我们寻求支持来分析两个现有的纵向数据集：（1）威斯康星州纵向研究（WLS），以威斯康星州 1957 名高中毕业生为样本（n = 8,493），跟踪范围从 1992-93 年的青年期到大约 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国家小组研究，于 1992 年进行了评估（n=9,824），并于 1994 年和 1996 年进行了重新访谈。我们建议在分析这些数据时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。

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.