How have firearm laws changed in states with unexpected decreases or increases in firearm homicide, 1990-2019?
Firearm homicide
Firearm policy
Inductive research
State outliers
Journal
SSM - population health
ISSN: 2352-8273
Titre abrégé: SSM Popul Health
Pays: England
ID NLM: 101678841
Informations de publication
Date de publication:
Jun 2023
Jun 2023
Historique:
received:
25
12
2022
revised:
11
02
2023
accepted:
13
02
2023
entrez:
21
3
2023
pubmed:
22
3
2023
medline:
22
3
2023
Statut:
epublish
Résumé
Firearm violence is one of the leading preventable causes of death and injury in the United States and is on the rise. While policies regulating access to firearms offer opportunities to prevent firearm-related deaths, an understanding of the holistic impact of changing state firearm policies on firearm homicide rates over the last 30 years is limited. To identify US states that showed unexpected decreases and increases in firearm homicide rates and summarise their firearm policy changes in the last three decades. We analysed changes in firearm homicide rates by US state and county from 1990 to 2019. We triangulated across three estimation approaches to derive state rankings and identify the top and bottom three states which consistently showed unexpected decreases (low outliers) and increases (high outliers) in firearm homicide rates. We summarised firearm policy changes in state outliers using the RAND State Firearm Law Database. We identified New York, District of Columbia, and Hawaii as low state outliers and Delaware, New Jersey, and Missouri as high state outliers. Low state outliers made more restrictive firearm policy changes than high state outliers, which covered a wider range of policy types. Restrictive changes in high state outliers primarily targeted high-risk populations (e.g., prohibited possessors, safe storage). Specific legislative details, such as the age threshold (18 vs 21 years old) for firearm minimum age requirements, also emerged as important for differentiating low from high state outliers. While no firearm law change emerged as necessary or sufficient, an accumulation of diverse restrictive firearm policies may be key to alleviating the death toll from firearm homicide.
Sections du résumé
Background
UNASSIGNED
Firearm violence is one of the leading preventable causes of death and injury in the United States and is on the rise. While policies regulating access to firearms offer opportunities to prevent firearm-related deaths, an understanding of the holistic impact of changing state firearm policies on firearm homicide rates over the last 30 years is limited.
Objectives
UNASSIGNED
To identify US states that showed unexpected decreases and increases in firearm homicide rates and summarise their firearm policy changes in the last three decades.
Methods
UNASSIGNED
We analysed changes in firearm homicide rates by US state and county from 1990 to 2019. We triangulated across three estimation approaches to derive state rankings and identify the top and bottom three states which consistently showed unexpected decreases (low outliers) and increases (high outliers) in firearm homicide rates. We summarised firearm policy changes in state outliers using the RAND State Firearm Law Database.
Results
UNASSIGNED
We identified New York, District of Columbia, and Hawaii as low state outliers and Delaware, New Jersey, and Missouri as high state outliers. Low state outliers made more restrictive firearm policy changes than high state outliers, which covered a wider range of policy types. Restrictive changes in high state outliers primarily targeted high-risk populations (e.g., prohibited possessors, safe storage). Specific legislative details, such as the age threshold (18 vs 21 years old) for firearm minimum age requirements, also emerged as important for differentiating low from high state outliers.
Conclusions
UNASSIGNED
While no firearm law change emerged as necessary or sufficient, an accumulation of diverse restrictive firearm policies may be key to alleviating the death toll from firearm homicide.
Identifiants
pubmed: 36941896
doi: 10.1016/j.ssmph.2023.101364
pii: S2352-8273(23)00029-0
pmc: PMC10024039
doi:
Types de publication
Journal Article
Langues
eng
Pagination
101364Informations de copyright
© 2023 The Authors.
Déclaration de conflit d'intérêts
None.
Références
Curr Epidemiol Rep. 2022;9(3):109-125
pubmed: 35874623
Am J Public Health. 2020 Oct;110(10):e1-e9
pubmed: 32816550
JAMA Intern Med. 2017 Jan 1;177(1):106-119
pubmed: 27842178
J Behav Med. 2019 Aug;42(4):741-762
pubmed: 31367938
Epidemiol Rev. 2016;38(1):140-57
pubmed: 26905895
JAMA Netw Open. 2022 Feb 1;5(2):e220077
pubmed: 35188553
N Engl J Med. 2022 Jul 14;387(2):189-191
pubmed: 35830647
JAMA. 2000 Aug 2;284(5):585-91
pubmed: 10918704
JAMA Intern Med. 2013 May 13;173(9):732-40
pubmed: 23467753
Int J Epidemiol. 2001 Jun;30(3):427-32; discussion 433-4
pubmed: 11416056
Am J Public Health. 2014 Aug;104(8):1384-6
pubmed: 24922158
Proc Natl Acad Sci U S A. 2020 Jun 30;117(26):14906-14910
pubmed: 32541042
JAMA Intern Med. 2018 May 1;178(5):692-700
pubmed: 29507953
Am J Public Health. 2017 Jul;107(7):1122-1129
pubmed: 28520491
JAMA. 2022 Sep 27;328(12):1189-1190
pubmed: 36166016
BMJ. 2020 Jul 22;370:m2436
pubmed: 32699008
JAMA Netw Open. 2022 Jun 1;5(6):e2215557
pubmed: 35666501