CenSoc: A New, Public, Individual-level Dataset for Studying Mortality Inequality

摘要/摘要 CENSOC项目-如此命名是因为它将1940年的人口普查数据与社会保障管理局的死亡数据联系起来 记录-将构建和共享一个新的，大规模的，公共微数据数据集，用于推进 了解美国的死亡率差异。该项目使用记录链接技术来匹配 1975年至2009年观察到的65岁及以上死亡人数，返回到个人，家庭和社区 普查中的特征。在初步研究的基础上，我们估计，使用现代数据连接 技术将使我们能够构建一个大约1500万死亡的数据集，超过30倍的规模。 现有最大的抽样调查。CENSOC数据前所未有的规模和细节将使研究人员能够 在以下领域有新发现：（a）教育、民族血统和种族造成的死亡率差异;（B） 早期生活条件和晚年死亡率;（c）地理变化和邻里决定因素 mortality.这些主题对于理解预期寿命差距的增加越来越重要 在美国 创建和分发具有个人特征的人口一级行政死亡率数据， 这是在美国促进严格和可复制的死亡率科学研究的核心目标。 采用人类死亡率数据库和综合公共使用微数据系列的模式 （IPUMS），CENSOC数据将在分发网站上提供分析。对于那些希望工作的人来说， 通过可识别的记录和完整的人口普查，可以使用现有的 作为许可协议的一部分，已经存在超过50个完整的人口普查存储库， 美国学术机构和明尼苏达大学。这种安全访问将允许更多的数据集 与CENSOC数据链接的个人标识符。 为了方便使用这个丰富的数据集，该项目将包括开发新的方法， 死亡率尤其适用于关联数据。我们亦会进行一系列"高分辨率"研究， 死亡率差异和寿命决定因素，这将有助于推进知识，并表明 CENSOC数据集的潜在用途。 通过利用现有的行政记录，CENSOC项目有可能提供一个巨大的， 为研究老年死亡率差异和人口老龄化的研究人员提供了丰富详细的公共"大数据"资源。 长寿的决定因素

Summary/Abstract The CENSOC project – so named because it links 1940 Census data with Social Security Administration death records – will construct and share a new, large-scale, public microdata data set to be used for advancing understanding of mortality disparities in the United States. The project uses record linkage techniques to match deaths aged 65-and-over observed from 1975 to 2009 back to individual, family, and neighborhood characteristics in the census. Building on preliminary studies, we estimate that the use of modern data-linkage techniques will allow us to construct a data set of about 15 million deaths, more than 30 times the size of the largest existing sample surveys. The unprecedented scale and detail of CENSOC data will allow researchers to make new discoveries in areas such as (a) mortality disparities by education, national origin, and race; (b) early life conditions and later-life mortality; and (c) geographic variation and the neighborhood determinants of mortality. These topics are of increasing importance in understanding increases in disparities in life expectancy in the United States. The creation and distribution of population-level administrative mortality data with individual characteristics is central to the goal of promoting rigorous and replicable scientific research in mortality in the United States. Following the model of the Human Mortality Database (HMD) and the Integrated Public Use Microdata Series (IPUMS), the CENSOC data will be available for analysis on a distribution website. For those wishing to work with identifiable records and the complete count census, access will be possible using the existing network of more than 50 Complete Count Census repositories that already exist as part of licensing agreement between U.S. academic institutions and the University of Minnesota. This secure access will allow additional data sets with individual identifiers to be linked to the CENSOC data. To facilitate usage of this rich dataset, the project will include development of new methods for estimating mortality rates especially appropriate for linked data. We will also carry out a set of `high resolution' studies on mortality disparities and longevity determinants that will serve to advance knowledge as well as demonstrate the potential uses of the CENSOC data set. By taking advantage of existing administrative records, the CENSOC project has the potential to provide a vast, richly detailed, public “big data” resource for researchers studying old-age mortality disparities and the determinants of longevity.