Expanding a Multi-Level, Longitudinal Database to Assess Ecological Risk Factors in Community Violence

在美国，每年有超过8.5万人遭受枪支伤害。故意攻击约占所有枪支伤害的40%，每年约有12,000人因此丧生。枪支暴力在人口中的分布并不均匀，大多数凶杀和枪击受害者是生活在结构上处于不利地位的城市社区的特定人口群体的年轻男子。对这种暴力的宏观结构原因有充分的了解是必要的，以便为该国受影响最严重的社区制定减少暴力的政策提供信息。这项研究将扩展先前的研究，考虑生态风险因素如何相互作用，并与枪支暴力率相互对应，从而产生持续的循环，随着时间的推移伤害社区。调查结果将极大地促进知识的进步，为制定有效的政策和方案提供信息，以防止社区枪支暴力。此外，它将生成一个全面的社区级数据集，可以公开提供给研究人员，以便继续研究当地社区枪支暴力的生态相关性。调查人员将建立一个全面的数据库，并在10年内对美国100个城市近16,000个社区的社区枪支暴力的多层次和相互的生态原因进行调查。该研究将包括一系列纵向、多变量分析以及巧合分析（CNA），这是一种用于因果推理的新型跨案例方法，旨在更好地了解驱动当地空间枪支暴力循环和相关社区差异的生态因素。研究人员将首先分析一系列社区、城市和州一级风险因素的多层次模型，以确定预测当地枪支杀人和非致命枪击率的关键相关性和多因素途径。在此之后，研究人员将评估社区条件和枪支暴力率之间的相互关系，特别关注社区差异的影响。研究结果有助于为联邦、州和地方负责预防和解决社区暴力的机构以及支持有文件证明的以群体为基础的暴力干预（GVI）的联邦项目优先提供资金和资源，以成功减少高风险社区的暴力犯罪。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Each year more than 85,000 people suffer from firearm injuries in the United States. Intentional assaults account for about 40% of all firearm injuries with approximately 12,000 killed each year as a result. Firearm violence is not evenly distributed across the population and the majority of homicide and shooting victims are young men of particular demographic groups living in structurally disadvantaged urban communities. A robust understanding of the macrostructural causes of this violence is necessary to inform violence reduction policies in the nation’s most affected communities. This study will extend prior research by considering how ecological risk factors operate in concert with one another and correspond reciprocally to rates of firearm violence to generate persistent cycles that harm communities over time. Findings will significantly contribute to the advancement of knowledge to inform the development of effective policies and programs to prevent firearm violence in communities. Moreover, it will generate a comprehensive neighborhood-level dataset that can be made publicly available to researchers for continued study on the ecological correlates of firearm violence in local communities. Investigators will construct a comprehensive database and examine the multilevel and reciprocal ecological causes of community firearm violence in almost 16,000 neighborhoods in 100 U.S. cities over ten years. The research will include an integrated series of longitudinal, multivariate analyses alongside coincidence analysis (CNA), a novel cross-case method for causal inference, to generate greater knowledge of the ecological factors that drive cycles of firearm violence in local spaces and related community disparities. The investigators will first analyze a series of multilevel models of neighborhood-, city-, and state-level risk factors to identify key correlates and multifactorial pathways that predict rates of local firearm homicides and non-fatal shootings over time. Following this, the researchers will assess the reciprocal relationship between community conditions and rates of firearm violence with particular attention to implications for community disparities. Findings can help prioritize funding and resource provision for federal, state, and local agencies tasked with preventing and addressing community violence as well as federal programs that support group-based violence interventions (GVI’s) documented to successfully help reduce violent crime in high-risk neighborhoods.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.