A Statistical Analysis of the Impact of Gun Ownership on Mass Shootings in the USA Between 2013 and 2022

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Abstract

Mass shootings (incidents with four or more people shot in a single event, not including the shooter) are becoming more frequent in the United States, posing a significant threat to public health and safety in the country. In the current study, we intended to analyze the impact of state-level prevalence of gun ownership on mass shootings—both the frequency and severity of these events. We applied the negative binomial generalized linear mixed model to investigate the association between gun ownership rate, as measured by a proxy (i.e., the proportion of suicides committed with firearms to total suicides), and population-adjusted rates of mass shooting incidents and fatalities at the state level from 2013 to 2022. Gun ownership was found to be significantly associated with the rate of mass shooting fatalities. Specifically, our model indicated that for every 1-SD increase—that is, for every 12.5% increase—in gun ownership, the rate of mass shooting fatalities increased by 34% ( p value < 0.001). However, no significant association was found between gun ownership and rate of mass shooting incidents. These findings suggest that restricting gun ownership (and therefore reducing availability to guns) may not decrease the number of mass shooting events, but it may save lives when these events occur.

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Over 30,000 people die annually in the United States from injuries caused by firearms. Although most firearm laws are enacted by states, whether the laws are associated with rates of firearm deaths is uncertain. To evaluate whether more firearm laws in a state are associated with fewer firearm fatalities. Using an ecological and cross-sectional method, we retrospectively analyzed all firearm-related deaths reported to the Centers for Disease Control and Prevention Web-based Injury Statistics Query and Reporting System from 2007 through 2010. We used state-level firearm legislation across 5 categories of laws to create a "legislative strength score," and measured the association of the score with state mortality rates using a clustered Poisson regression. States were divided into quartiles based on their score. Fifty US states. Populations of all US states. The outcome measures were state-level firearm-related fatalities per 100,000 individuals per year overall, for suicide, and for homicide. In various models, we controlled for age, sex, race/ethnicity, poverty, unemployment, college education, population density, nonfirearm violence-related deaths, and household firearm ownership. Over the 4-year study period, there were 121,084 firearm fatalities. The average state-based firearm fatality rates varied from a high of 17.9 (Louisiana) to a low of 2.9 (Hawaii) per 100,000 individuals per year. Annual firearm legislative strength scores ranged from 0 (Utah) to 24 (Massachusetts) of 28 possible points. States in the highest quartile of legislative strength (scores of ≥9) had a lower overall firearm fatality rate than those in the lowest quartile (scores of ≤2) (absolute rate difference, 6.64 deaths/100,000/y; age-adjusted incident rate ratio [IRR], 0.58; 95% CI, 0.37-0.92). Compared with the quartile of states with the fewest laws, the quartile with the most laws had a lower firearm suicide rate (absolute rate difference, 6.25 deaths/100,000/y; IRR, 0.63; 95% CI, 0.48-0.83) and a lower firearm homicide rate (absolute rate difference, 0.40 deaths/100,000/y; IRR, 0.60; 95% CI, 0.38-0.95). A higher number of firearm laws in a state are associated with a lower rate of firearm fatalities in the state, overall and for suicides and homicides individually. As our study could not determine cause-and-effect relationships, further studies are necessary to define the nature of this association.

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Author and article information

Contributors

Lucy Kerns:

ORCID: http://orcid.org/0000-0002-6108-9737

xlu@ysu.edu

Journal

Journal ID (nlm-ta): J Urban Health

Journal ID (iso-abbrev): J Urban Health

Title: Journal of Urban Health : Bulletin of the New York Academy of Medicine

Publisher: Springer US (New York )

ISSN (Print): 1099-3460

ISSN (Electronic): 1468-2869

Publication date (Electronic): 3 June 2024

Publication date PMC-release: 3 June 2024

Publication date (Print): June 2024

Volume: 101

Issue: 3

Pages: 571-583

Affiliations

[1 ]GRID grid.422649.f, ISNI 0000 0004 0438 7388, Department of Mathematics, , Westminster College, ; New Wilmington, PA USA

[2 ]Department of Statistics, The University of Virginia, ( https://ror.org/0153tk833) Charlottesville, VA USA

[3 ]Department of Mathematics, Wellesley College, ( https://ror.org/01srpnj69) Wellesley, MA USA

[4 ]Department of Mathematics & Statistics, Youngstown State University, One University Plaza, ( https://ror.org/038zf2n28) Youngstown, OH 44555 USA

Author information

Lucy Kerns http://orcid.org/0000-0002-6108-9737

Article

Publisher ID: 881

DOI: 10.1007/s11524-024-00881-9

PMC ID: 11189892

PubMed ID: 38831155

SO-VID: 14aba712-6954-48e5-b304-00a1902cb6ab

License:

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

History

Date accepted : 29 April 2024

Custom metadata

ScienceOpen disciplines: Public health

Keywords: mass shootings,gun ownership,negative binomial generalized linear mixed model,mass shooting incidents,mass shooting fatalities

Data availability:

ScienceOpen disciplines: Public health

Keywords: mass shootings, gun ownership, negative binomial generalized linear mixed model, mass shooting incidents, mass shooting fatalities

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