Evidence map›Paper›PMID 33465011›Full record

ArticlePublic health reports (Washington, D.C. : 1974)

State- and County-Level Social Capital as Predictors of County-Level Suicide Rates in the United States: A Lagged Multilevel Study.

Saloni Dev, Daniel Kim

Open access · bronzeAbstract read
In one paragraph

Article in Public health reports (Washington, D.C. : 1974). The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.0field-weighted citation impact, top 21% of its field
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

5 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
  2. Article
  3. The social determinants of mental health and disorder: evidence, prevention and recommendations.World psychiatry : official journal of the World Psychiatric Association (WPA) · 2024
    Article
  4. Setting a Course to Protect Indigenous Cultures and Communities in our National Suicide Prevention Agenda.Clinical psychology : a publication of the Division of Clinical Psychology of the American Psychological Association · 2022
    Article
  5. Article
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

2 authors at 1 institution in 1 country.

Saloni Dev1848 Department of Health Sciences, Bouvé College of Health Sciences, Northeastern University, Boston, MA, USA.ORCID 0000-0003-3385-7249
Daniel Kim1848 Department of Health Sciences, Bouvé College of Health Sciences, Northeastern University, Boston, MA, USA.
Northeastern University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

From 1999 through 2017, age-adjusted suicide rates in the United States rose by 33% (from 10.5 to 14.0 per 100 000 population). Social capital, a key social determinant of health, could protect against suicide, but empirical evidence on this association is limited. Using multilevel data from the Centers for Disease Control and Prevention, we explored state- and county-level social capital as predictors of age-adjusted suicide rates pooled from 2010 through 2017 across 2112 US counties. In addition, we tested for causal mediation of these associations by state-level prevalence of depression. A 1-standard deviation increase in state-level social capital predicted lower county-level suicide mortality rates almost 2 decades later (0.87 fewer suicides per 100 000 population;

Indexed as

Social CapitalAge DistributionBlack or African AmericanCenters for Disease Control and Prevention, U.S.DepressionFemaleFirearmsHumansMaleResidence CharacteristicsSex DistributionSocioeconomic FactorsSuicideUnited StatesWhite Peoplemultilevelsocial capitalsuicideUnited States

Identifiers

PMID33465011
PMCPMC8361567
OpenAlexW3121842736

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.