Evidence map›Paper›PMID 30777160›Full record

ArticleAmerican journal of preventive medicine2019

Nicotine Dependence and Pre-Enlistment Suicidal Behavior Among U.S. Army Soldiers.

Laura Campbell-Sills, Ronald C Kessler, Robert J Ursano, Xiaoying Sun, Steven G Heeringa, Matthew K Nock, Sonia Jain, Murray B Stein

Abstract read
In one paragraph

Article in American journal of preventive medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.3field-weighted citation impact, top 38% 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

4 citing papers in PubMed, 7 citations in OpenAlex.

  1. Tobacco Product Use and Type by Military Veteran Status: Findings from the National Health Interview Survey, 2021-2023.Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco · 2025
    Article
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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

8 authors at 4 institutions in 1 country.

Laura Campbell-SillsDepartment of Psychiatry, University of California, San Diego, La Jolla, California. Electronic address: campbell-sills@ucsd.edu.
Ronald C KesslerDepartment of Health Care Policy, Harvard Medical School, Boston, Massachusetts.
Robert J UrsanoCenter for the Study of Traumatic Stress, Department of Psychiatry, Uniformed Services University of the Health Sciences, Bethesda, Maryland.
Xiaoying SunDepartment of Family Medicine and Public Health, University of California, San Diego, La Jolla, California.
Steven G HeeringaInstitute for Social Research, University of Michigan, Ann Arbor, Michigan.
Matthew K NockDepartment of Psychology, Harvard University, Cambridge, Massachusetts.
Sonia JainDepartment of Family Medicine and Public Health, University of California, San Diego, La Jolla, California.
Murray B SteinDepartment of Psychiatry, University of California, San Diego, La Jolla, California; Department of Family Medicine and Public Health, University of California, San Diego, La Jolla, California; VA San Diego Healthcare System, San Diego, California.
University of California San Diego · USHarvard University · USUniformed Services University of the Health Sciences · USUniversity of Michigan · US

Funding

Modifiable Risk and Protective Factors for Suicidal Behaviors in the US ArmyU01MH087981 · NIMH · HENRY M. JACKSON FDN FOR THE ADV MIL/MED · PI STEIN, MURRAY B., URSANO, ROBERT J. · 2009 to 2013
$65.0M
NIMH NIH HHS U01 MH087981
6 · The paper itself

Abstract

introductionIdentification of modifiable risk factors for suicidal behaviors is a priority for the U.S. Army. This study investigated associations of nicotine dependence with suicidal behaviors among incoming soldiers.

methodsLifetime DSM-IV nicotine dependence, mental disorders, suicidal behaviors, and their ages of onset were retrospectively assessed in the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS) New Soldier Study. Discrete-time survival analysis of person-year data from 30,436 soldiers was performed to evaluate associations of nicotine dependence with subsequent suicidal ideation, plans, and attempts. Among respondents with lifetime ideation (n=4,060), models tested associations of nicotine dependence with progression from ideation to first onset of plan, from plan to first attempt, and, among ideators without plans, from ideation to first unplanned attempt. A hierarchy of models incorporated increasing controls for other risk factors. Data were collected in 2011-2012 and analyzed in 2017-2018.

resultsIn models controlling for sociodemographic characteristics, nicotine dependence was associated with onset of all suicidal behaviors (AORs, 2.07-4.08, p<0.001) and with each type of progression of suicidal behavior (AORs, 1.48-2.44, p<0.005). After adjusting for childhood adversities and mental disorders, nicotine dependence remained associated with onset of ideation (AOR=1.27, 95% CI=1.10, 1.46, p=0.001) and attempt (AOR=1.83, 95% CI=1.41, 2.37, p<0.001); and with progression from ideation to unplanned attempt (AOR=2.03, 95% CI=1.17, 1.74, p<0.001).

conclusionsNicotine dependence exhibited associations with onset of suicidal ideation and suicide attempt-and with progression from ideation to unplanned attempt-that were independent of other measured risk factors. Awareness of associations of nicotine dependence with suicidal behaviors may inform risk assessment, facilitate targeting of prevention efforts, and provide further impetus for reducing nicotine dependence.

Indexed as

Suicidal IdeationAdolescentAdultAdverse Childhood ExperiencesAge FactorsFemaleHumansMaleMental DisordersMilitary PersonnelRetrospective StudiesRisk FactorsSex FactorsSocioeconomic FactorsSuicide, AttemptedTobacco Use Disorder

Identifiers

PMID30777160
PMCPMC6383784
OpenAlexW2912477860

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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.