Evidence map›Paper›PMID 40950470›Full record

ArticlemedRxiv : the preprint server for health sciences2025

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

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

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Kushagra TiwariDepartment of Industrial Engineering, University of Pittsburgh.ORCID 0009-0000-5786-4166
M Amin RahimianDepartment of Industrial Engineering, University of Pittsburgh.ORCID 0000-0001-9384-1041
Marie-Laure CharpignonKaiser Permanente Northern California, Division of Research, Pleasanton, CA; Computational Health Informatics Program, Boston Children's Hospital & Harvard Medical School.
Philippe J GiabbanelliVirginia Modeling, Analysis, and Simulation Center (VMASC), Old Dominion University.ORCID 0000-0001-6816-355X
Praveen KumarDepartment of Health Policy and Management, School of Public Health, University of Pittsburgh; Public Health Dynamics Laboratory, School of Public Health, University of Pittsburgh.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Identifiers

PMID40950470
PMCPMC12424903

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.