Constructing, Validating, and Testing the Predictive Power of Life-Course Health Histories

项目摘要 在项目“构建、验证和测试生命过程健康的预测能力”中 我们将创建一个全面的指南来帮助研究人员辨别是否以及何时 他们可以使用来自全国代表性调查的回溯性健康数据来创建生命周期 健康史。我们的项目利用了科学界的巨大投资 旨在通过横断面和纵向调查来衡量人口和个人健康。 我们将使用来自四个主要调查的数据为每个调查受访者创建生活历史 11种急性或慢性健康状况。然后我们将验证构建的健康记录， 比较过去一年特定出生队列的疾病患病率与 同时测量相同疾病、人口统计群体和 在同一个历年。我们将开发我们的指南和数据，关注三个主要方面 导致研究人员对使用追溯性问题创造生命犹豫不决的因素 健康史.回忆偏差、抽样规则和样本的异同 特征和选择性死亡。我们的总体目标是进行“概念验证” 探索是否以及在什么情况下可以使用回溯性问题 生成生命健康史，并为研究人员提供使用指南。我们的工作产品 将扩大研究人员可以利用已有的追溯健康数据解决的问题集 根据现有调查收集的数据。我们的结果将使研究人员能够描述和研究 目前很难研究的一系列健康状况的病因学 样本大小限制。

Project Summary In the project, "Constructing, Validating, and Testing the Predictive Power of Life-Course Health Histories," we will create a comprehensive guide to help researchers discern whether and when they can use retrospective health data from nationally representative surveys to create lifetime health histories. Our project leverages enormous investments the scientific community has made to measure population and individual health on cross-sectional and longitudinal surveys. We will use data from four major surveys to create life histories for each survey respondent for 11 acute or chronic health conditions. We will then validate the constructed health histories, comparing the prevalence of the condition for a given birth cohort in a past year against contemporaneously measured prevalence rates for the same condition, demographic group and in the same calendar year. We will develop our guide and data with attention to three major factors that cause researchers to hesitate about using retrospective questions to generate life health-histories – recall bias, similarities and differences in sampling rules and sample characteristics, and selective mortality. Our overall aims are to conduct a “proof-of-concept” exercise to explore whether and for what conditions one can use retrospective questions to generate life health histories and to provide a guide for researchers to use. Our work products will expand the set of questions researchers can address with retrospective health data already collected on existing surveys. Our results will enable researchers to describe and study the etiology of a wide range of health conditions that are currently difficult to study because of sample size limitations.