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

摘要/摘要 CENSOC项目-之所以这样命名，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联系起来 记录-将构建和共享用于推进的新的、大规模的公共微数据集 了解美国的死亡率差异。该项目使用记录链接技术来匹配 从1975年到2009年，65岁及以上的死亡人数回溯到个人、家庭和邻里 人口普查中的特点。在初步研究的基础上，我们估计使用现代数据链接 这些技术将使我们能够构建一个大约1500万人死亡的数据集，是 现有最大规模的抽样调查。CENSOC数据前所未有的规模和细节将使研究人员能够 在以下领域取得新发现：(A)按教育、国籍和种族划分的死亡率差距；(B) 早期生活条件和晚年死亡率；和(C)地理变异和社区决定因素 死亡率。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点的人口级行政死亡率数据是 这是促进美国严格和可复制的死亡率科学研究目标的核心。 遵循人类死亡数据库(HMD)和综合公共用途微数据系列的模式 (IPUMS)，CENSOC的数据将在分发网站上提供分析。对于那些想要工作的人 有了可识别的记录和完整的计数普查，将可以使用现有的网络进行访问 作为许可协议的一部分，已经存在的50多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额外的数据集 其中各个标识符链接到CENSOC数据。 为了方便使用这一丰富的数据集，该项目将包括开发新的估计方法 死亡率尤其适用于关联数据。我们还将开展一系列高分辨率的研究 死亡率差异和长寿决定因素，将有助于促进知识和论证 CENSOC数据集的潜在用途。 通过利用现有的行政记录，CENSOC项目有可能提供广泛的、 为研究老年死亡率差距和老年死亡率差距的研究人员提供详细的公共“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.