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美国自杀死亡率的社会空间模式。

Socio-Spatial Patterns of Suicide Mortality in the United States.

作者信息

Tiwari Kushagra, Rahimian M Amin, Charpignon Marie-Laure, Giabbanelli Philippe J, Kumar Praveen

机构信息

Department of Industrial Engineering, University of Pittsburgh.

Kaiser Permanente Northern California, Division of Research, Pleasanton, CA; Computational Health Informatics Program, Boston Children's Hospital & Harvard Medical School.

出版信息

medRxiv. 2025 Sep 2:2025.08.29.25334693. doi: 10.1101/2025.08.29.25334693.

Abstract

Suicide mortality in the United States exhibits substantial geographical and sociodemographic heterogeneity. Yet the role of large-scale social networks in shaping this variation remains underexplored. We integrate data on county-level suicide mortality (2010-2022) and Facebook's Social Connectedness Index (SCI) to assess how both the risk of suicide mortality and the effect of firearm restriction policies propagate through inter-county social ties. First, using two-way fixed effects regression models with sociodemographic, economic, and spatial controls, we find that a one-standard-deviation increase in (SCI-weighted) suicide mortality in socially connected counties is associated with an increase of 2.78 suicide deaths per 100,000 people in the focal county (95% CI: 1.06- 4.50). Second, we examine Extreme Risk Protection Orders (ERPOs) - state-level firearm policies that allow temporary restriction of firearm access for individuals at risk of self-harm - and show that counties with stronger (Facebook) social ties to ERPO-adopting states experience reductions in suicide mortality, even without local policy implementation. Our findings suggest that a one-standard-deviation increase in ERPO social exposure is associated with a decrease of 0.301 suicide deaths per 100,000 people in the focal county (95% CI: 0.480-0.121). This protective association persists after adjusting for geographical proximity and including state-by-year fixed effects that capture time-varying state-level factors. In sum, our findings suggest that social networks can facilitate the diffusion of both harmful exposures and protective interventions. This socio-spatial structuring of suicide mortality underscores the need for network-driven prevention strategies that incorporate social network topology (e.g., SCI-derived influence metrics), alongside more traditional approaches based on geographical targeting.

摘要

美国的自杀死亡率存在显著的地理和社会人口统计学异质性。然而,大规模社会网络在塑造这种差异方面的作用仍未得到充分探索。我们整合了县级自杀死亡率数据(2010 - 2022年)和脸书的社交连通性指数(SCI),以评估自杀死亡率风险和枪支限制政策的影响如何通过县际社会关系传播。首先,使用具有社会人口统计学、经济和空间控制的双向固定效应回归模型,我们发现,在社交连通的县中,(SCI加权)自杀死亡率每增加一个标准差,中心县每10万人的自杀死亡人数就会增加2.78例(95%置信区间:1.06 - 4.50)。其次,我们研究了极端风险保护令(ERPOs)——州级枪支政策,该政策允许暂时限制有自我伤害风险的个人获取枪支——并表明,与采用ERPOs的州有更强(脸书)社会联系的县,即使没有当地政策实施,自杀死亡率也会降低。我们的研究结果表明,ERPO社会暴露每增加一个标准差,中心县每10万人的自杀死亡人数就会减少0.301例(95%置信区间:0.480 - 0.121)。在调整地理距离并纳入捕捉随时间变化的州级因素的逐年固定效应后,这种保护关联仍然存在。总之,我们的研究结果表明,社会网络可以促进有害暴露和保护性干预措施的传播。自杀死亡率的这种社会空间结构凸显了需要网络驱动的预防策略,这些策略应纳入社会网络拓扑结构(例如,基于SCI得出的影响指标),以及更传统的基于地理定位的方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4e2e/12424903/e7f599f0a4f5/nihpp-2025.08.29.25334693v1-f0001.jpg

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