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

• 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
• 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; 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

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 人口普查项目 - 之所以命名，是因为它将1940年的人口普查数据与社会保障管理部门联系起来 记录 - 将构建并共享一个新的大规模公共微型数据集，用于前进 了解美国的死亡率分布。该项目使用记录链接技术来匹配 从1975年到2009年的65岁及65岁的死亡回到个人，家庭和社区 人口普查中的特征。在初步研究的基础上，我们估计使用现代数据链接 技术将使我们能够构建约1500万人死亡的数据集，超过30倍 现有最大的样本调查。人口普查数据的前所未有的规模和细节将使研究人员能够 在（a）教育，国籍和种族的死亡率分布等领域中进行新发现； （b） 早期生活状况和后期死亡率； （c）地理差异和邻里的决定者 死亡。这些主题在理解预期寿命的分布增加方面的重要性越来越重要 在美国。 具有个人特征的人口级行政死亡率数据的创建和分布是 促进美国死亡率严格和可复制科学研究的目标的核心。 遵循人类死亡率数据库（HMD）的模型和集成的公共用途Microdata系列 （IPUMS），人口普查数据将在分销网站上进行分析。对于那些希望工作的人 使用可识别的记录和完整的计数人口普查，使用现有网络可以访问 作为许可协议的一部分，已有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。此安全访问将允许其他数据集 将单个标识符链接到人口普查数据。 为了促进该丰富数据集的使用，该项目将包括开发用于估算的新方法 死亡率特别适合链接数据。我们还将对 死亡率差异和寿命确定词，将有助于提高知识并证明 人口普查数据集的潜在用途。 通过利用现有的行政记录，人口普查项目有可能提供广泛的， 精心详细的公共“大数据”资源，用于研究老年死亡率分布的研究人员 长寿的决定因素。