BACKGROUND
While much progress has been made in understanding the demographic determinants of mortality in the United States using individual survey data and aggregate tabulations, the lack of population-level register data is a barrier to further advances in mortality research. With the release of Social Security application (SS-5), claim, and death records, the National Archives and Records Administration (NARA) has created a new administrative data resource for researchers studying mortality. We introduce the Berkeley Unified Numident Mortality Database (BUNMD), a cleaned and harmonized version of these records. This publicly available dataset provides researchers access to over 49 million individual-level mortality records with demographic covariates and fine geographic detail, allowing for high-resolution mortality research.

OBJECTIVE
The purpose of this paper is to describe the BUNMD, discuss statistical methods for estimating mortality differentials based on this deaths-only dataset, and provide case studies illustrating the high-resolution mortality research possible with the BUNMD.

METHODS
We provide detailed information on our procedure for constructing the BUNMD dataset from the most informative parts of the publicly available Social Security Numident application, claim, and death records.



中文翻译：

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Berkeley Unified Numident Mortality Database：个人死亡率研究的公共行政记录（作者：Casey Breen、Joshua R. Goldstein）

背景
虽然使用个人调查数据和汇总表在了解美国死亡率的人口决定因素方面取得了很大进展，但缺乏人口水平的登记数据是死亡率研究进一步发展的障碍。随着社会保障申请 (SS-5)、索赔和死亡记录的发布，美国国家档案和记录管理局 (NARA) 为研究死亡率的研究人员创建了一个新的管理数据资源。我们介绍了伯克利统一数字死亡率数据库 (BUNMD)，这是这些记录的清洁和协调版本。这个公开可用的数据集为研究人员提供了访问超过 4900 万个具有人口统计协变量和精细地理细节的个体水平死亡率记录，从而可以进行高分辨率死亡率研究。

目的
本文的目的是描述 BUNMD，讨论基于此仅死亡数据集估计死亡率差异的统计方法，并提供案例研究来说明 BUNMD 可能进行的高分辨率死亡率研究。

方法
我们从公开的社会保障 Numident 申请、索赔和死亡记录中信息最丰富的部分提供了关于我们构建 BUNMD 数据集的程序的详细信息。