RISK FACTORS FOR PSYCHIATRIC DISORDERS

拟议的项目检查精神病因学，并选择 精神障碍的危险因素 以社区为基础的代表性样本。精神障碍 使用三种方法进行检查：(A)DIS/DSM-III诊断， (B)综合安全分遣队症状计数；及(C)由 隶属度(GOM)分析。GOM分析是 尤其重要的是，它们提供了有关 基于经验的症状描述在多大程度上符合 构成病因学框架的诊断类别 DIS-III.这种折衷的精神诊断方法也 允许对符合以下条件的精神健康问题进行检查 在社区人群中最普遍(例如，症状 症状以及正式诊断)。风险因素分析 重点放在三个领域：(A)工作特点在多大程度上 是精神障碍的危险因素吗？(B) 在生活事件中，社会支持，社会融合，以及 精神障碍，以及(C)环境影响的程度 居民区的特点是 精神障碍。多种统计建模方法 将在风险分析中使用技术，包括 环境影响评价的多层次分析方法 效果。将特别关注互动性，因为 以及风险因素的直接和间接影响 检查过了。建议的分析将有助于我们的 社区人群对精神障碍的认识 以及将个体置于以下位置的变量识别 增加精神疾病的风险。 建议项目中使用的数据来自 流行病学集水区规划。大多数分析将是 用于Duke ECA样本，但选定的分析将使用 从所有五个ECA站点汇集而来。建议的分析包括 横截面模型和纵向模型。在可能的地方， 暴露于利息风险因素的持续时间也将是 检查过了。拟议的项目充分利用了丰富的 非洲经委会项目的广度，并将审查长期- 对精神病学流行病学的持续兴趣在一个创造性和 在方法上很老练。

The proposed project examines psychiatric nosology and selected risk factors for psychiatric disorders in the context of a representative community-based sample. Psychiatric disorders are examined using three approaches: (a) DIS/DSM-III diagnoses, (b) DIS symptom counts, and (c) symptom profiles generated by grade of membership (GOM) analysis. The GOM analyses are particularly important in that they provide information about the extent to which empirically-based symptom profiles match the diagnostic categories that comprise the nosologic framework of DIS-III. This eclectic approach to psychiatric diagnosis also permits examination of the kinds of mental health problems that are most prevalent in community populations (e.g. symptom syndromes as well as formal diagnoses). Risk factor analyses focus on three areas: (a) the extent to which job characteristics are risk factors for psychiatric disorders, (b) the relationships among life events, social support, social integration, and psychiatric disorders, and (c) the extent to which environmental characteristics of the residential area are risk factors for psychiatric disorders. A variety of statistical modeling techniques will be employed in the risk analyses, including multilevel analysis for examining the impact of enviromental effects. Special attention will be devoted to the interactive, as well as the direct and indirect effects, of the risk factors examined. The proposed analyses will be contribute to our understanding of psychiatric disorders in community populations and the identification of variables that place individuals at increased risk of psychiatric disorders. The data to be used in the proposed project are from the Epidemiologic Catchment Area Program. Most analyses will be used on the Duke ECA sample, but selected analyses will use pooled from all five ECA sites. The proposed analyses included both cross-sectional and longitudinal models. Where possible, length of exposure to the risk factors of interest also will be examined. The proposed project capitalizes upon the richness and breadth of the ECA Project and will examine issues of long- standing interest in psychiatric epidemiology in a creative and methodologically sophisticated manner.