Boulifard David A, Pescosolido Bernice A
Indiana University, Bloomington.
US Census Bur Cent Econ Stud Res Pap Ser. 2017;2017. Epub 2017 Mar 1.
This paper describes a novel database and an associated suicide event prediction model that surmount longstanding barriers in suicide risk factor research. The database comingles person-level records from the National Violent Death Reporting System (NVDRS) and the American Community Survey (ACS) to establish a case-control study sample that includes all identified suicide cases, while faithfully reflecting general population sociodemographics, in sixteen USA states during the years 2005-2011. It supports a statistical model of individual suicide risk that accommodates person-level factors and the moderation of these factors by their community rates. Named the , the database was developed outside the RDC laboratory using publicly available ACS microdata, and reconstructed inside the laboratory using restricted access ACS microdata. Analyses of the latter version yielded findings that largely amplified but also extended those obtained from analyses of the former. This experience shows that the analytic precision achievable using restricted access ACS data can play an important role in conducting social research, although it also indicates that publicly available ACS data have considerable value in conducting preliminary analyses and preparing to use an RDC laboratory. The database development strategy may interest scientists investigating sociodemographic risk factors for other types of low-frequency mortality.
本文介绍了一种新型数据库及相关自杀事件预测模型，该模型克服了自杀风险因素研究中长期存在的障碍。该数据库将来自国家暴力死亡报告系统（NVDRS）和美国社区调查（ACS）的个人层面记录合并，以建立一个病例对照研究样本，其中包括所有已确认的自杀案例，同时在2005年至2011年期间如实反映美国16个州的总体人口社会 demographics情况。它支持一个个体自杀风险的统计模型，该模型考虑了个人层面的因素以及这些因素受社区发生率的调节作用。该数据库名为，它是在RDC实验室之外利用公开可用的ACS微观数据开发的，并在实验室内部利用受限访问的ACS微观数据进行了重建。对后一版本的分析得出的结果在很大程度上放大了但也扩展了从前一版本分析中获得的结果。这一经验表明，使用受限访问的ACS数据可实现的分析精度在进行社会研究中可发挥重要作用，尽管这也表明公开可用的ACS数据在进行初步分析和准备使用RDC实验室方面具有相当大的价值。该数据库开发策略可能会引起研究其他类型低频死亡率的社会人口风险因素的科学家的兴趣。
