Evidence map›Paper›PMID 34620159›Full record

ArticleBMC public health2021

Firearm laws and the network of firearm movement among US states.

Sae Takada, Kristen R Choi, Shaw Natsui, Altaf Saadi, Liza Buchbinder, Molly Easterlin, Frederick J Zimmerman

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

7 authors.

Sae TakadaDivision of General Internal Medicine & Health Services Research, Department of Medicine, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, 90024, USA. stakada@mednet.ucla.edu.ORCID 0000-0002-1319-353X
Kristen R ChoiDivision of General Internal Medicine & Health Services Research, Department of Medicine, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, 90024, USA.
Shaw NatsuiDivision of General Internal Medicine & Health Services Research, Department of Medicine, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, 90024, USA.
Altaf SaadiDivision of General Internal Medicine & Health Services Research, Department of Medicine, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, 90024, USA.
Liza BuchbinderDivision of General Internal Medicine & Health Services Research, Department of Medicine, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, 90024, USA.
Molly EasterlinDivision of General Internal Medicine & Health Services Research, Department of Medicine, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, 90024, USA.
Frederick J ZimmermanDepartment of Health Policy and Management, Fielding School of Public Health University of California, Los Angeles, 90024, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe movement of firearm across state lines may decrease the effectiveness of state-level firearm laws. Yet, how state-level firearm policies affect cross-state movement have not yet been widely explored. This study aims to characterize the interstate movement of firearms and its relationship with state-level firearm policies.

methodsWe analyzed the network of interstate firearm movement using Bureau of Alcohol, Tobacco, Firearms, and Explosives firearm trace data (2010-2017). We constructed the network of firearm movement between 50 states. We used zero-inflated negative binomial regression to estimate the relationship between the number of a state's firearm laws and number of states for which it was the source of 100 or more firearms, adjusting for state characteristics. We used a similar model to examine the relationship between firearm laws and the number of states for which a given state was the destination of 100 or more firearms.

resultsOver the 8-year period, states had an average of 26 (Standard Deviation [SD] 25.2) firearm laws. On average, a state was the source of 100 or more crime-related firearms for 2.2 (SD 2.7) states and was the destination of 100 or more crime-related firearms for 2.2 (SD 3.4) states. Greater number of firearm laws was associated with states being the source of 100 or more firearms to fewer states (Incidence Rate Ratio [IRR] 0.58 per SD, p < 0.001) and being the destination of 100 or more firearms from more states (IRR1.73 per SD, p < 0.001).

conclusionsRestrictive state-level firearm policies are associated with less movement of firearms to other states, but with more movement of firearms from outside states. The effectiveness of state-level firearm-restricting laws is complicated by a network of interstate firearm movement.

Indexed as

FirearmsSuicideWounds, GunshotCross-Sectional StudiesHomicideHumansIncidencePolicyUnited StatesFirearm lawsFirearm trace dataState laws

Identifiers

PMID34620159
PMCPMC8499462

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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.