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

CenSoc：用于研究死亡率不平等的新的、公共的、个人层面的数据集

基本信息

批准号：
10602507
负责人：
JOSHUA R. GOLDSTEIN
金额：
$ 55.81万
依托单位：
UNIVERSITY OF CALIFORNIA BERKELEY
依托单位国家：
美国
项目类别：
财政年份：
2019
资助国家：
美国
起止时间：
2019-08-01 至 2025-03-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10602507
关键词：
Adult Age Age Distribution Aging Agreement Area Back Big Data Case Study Censuses Cessation of life Characteristics Communities Data Data Linkages Data Set Databases Death Records Development Dimensions Disparity Education Elderly Estimation Techniques Ethnic Population Family Female First Name Genetic Transcription Geography Goals Health Policy Height Heterogeneity Household Housing Immigrant Income Individual Inequality Institution Intelligence Tests Investigation Knowledge Last Name Lead levels Licensing Life Life Expectancy Link Longevity Maintenance Measurement Measures Methods Military Personnel Minnesota Minority Minority Groups Modeling Modernization Mortality Determinants Names National origin Nature Neighborhoods Occupations Population Population Distributions Population Registers Production Public Health Race Records Reproducibility Research Research Personnel Resolution Sample Size Sampling Scandinavia Schedule Secure Series Social Security Street Address Structure Surveys System Techniques United States United States Social Security Administration Universities War Water Weight Work access restrictions aged cohort data resource ethnic identity flexibility frontier geographic difference human mortality human old age (65+)improved innovation male mortality mortality disparity open data prospective racial population repository residence response tool trend web site

项目摘要

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.

摘要/摘要 CENSOC 项目——如此命名是因为它将 1940 年人口普查数据与社会保障管理局的死亡联系起来记录——将构建和共享一个新的、大规模的、公共的微观数据数据集，用于推进了解美国的死亡率差异该项目使用记录关联技术来匹配。 1975 年至 2009 年间观察到的 65 岁及以上死亡人数，涉及个人、家庭和社区根据初步研究，我们估计现代数据链接的使用。技术将使我们能够构建包含约 1500 万死亡数据的数据集，是数据集规模的 30 多倍。 CENSOC 数据前所未有的规模和详细程度将使研究人员能够在以下领域取得新发现：(a) 受教育程度、国籍和种族的死亡率差异；(b) 早期生活条件和晚年死亡率；以及(c) 地理差异和邻里决定因素这些主题对于理解预期寿命差异的扩大越来越重要。在美国。具有个体特征的人口层面行政死亡率数据的创建和分发对于在美国促进严格且可复制的死亡率科学研究的目标至关重要。遵循人类死亡率数据库（HMD）和综合公共使用微数据系列的模型 (IPUMS)，CENSOC 数据将可在分发网站上供那些希望工作的人进行分析。有了可识别的记录和完整的人口普查，就可以使用现有的网络进行访问超过 50 个 Complete Count Census 存储库已作为许可协议的一部分存在美国学术机构和明尼苏达大学将允许额外的数据集。具有链接到 CENSOC 数据的个人标识符。为了方便使用这个丰富的数据集，该项目将包括开发新的估计方法我们还将针对关联数据开展一系列“高分辨率”研究。死亡率差异和长寿决定因素将有助于增进知识并展示 CENSOC 数据集的潜在用途。通过利用现有的行政记录，CENSOC 项目有潜力提供大量的、为研究老年人死亡率差异和人口老龄化问题的研究人员提供详细的公共“大数据”资源长寿的决定因素。