Evidence map›Paper›PMID 35666501›Full record

ArticleJAMA network open2022

County-Level Variation in Changes in Firearm Mortality Rates Across the US, 1989 to 1993 vs 2015 to 2019.

Michelle Degli Esposti, Jason Gravel, Elinore J Kaufman, M Kit Delgado, Therese S Richmond, Douglas J Wiebe

Abstract read
In one paragraph

Article in JAMA network open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. State expansion of Supplemental Nutrition Assistance Program eligibility and rates of firearm-involved deaths in the United States.Injury prevention : journal of the International Society for Child and Adolescent Injury Prevention · 2024
    Article
  5. Article
  6. A Statistical Analysis of the Impact of Gun Ownership on Mass Shootings in the USA Between 2013 and 2022.Journal of urban health : bulletin of the New York Academy of Medicine · 2024
    Article
  7. Article
  8. Article
  9. Mechanisms of traumatic injury by demographic characteristics: an 8-year review of temporal trends from the National Trauma Data Bank.Injury prevention : journal of the International Society for Child and Adolescent Injury Prevention · 2023
    Article
  10. Article
  11. Article
  12. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Michelle Degli EspostiPenn Injury Science Center, University of Pennsylvania, Philadelphia.
Jason GravelDepartment of Criminal Justice, Temple University, Philadelphia, Pennsylvania.
Elinore J KaufmanPenn Injury Science Center, University of Pennsylvania, Philadelphia.
M Kit DelgadoPenn Injury Science Center, University of Pennsylvania, Philadelphia.
Therese S RichmondPenn Injury Science Center, University of Pennsylvania, Philadelphia.
Douglas J WiebePenn Injury Science Center, University of Pennsylvania, Philadelphia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Importance: Firearm violence remains a critical public health challenge, disproportionately impacting some US regions. County-level variation may hold key insights into how firearm mortality rates vary across the US. Objective: To model county-level changes in firearm mortality rates (total, homicide, and suicide) from 1989 to 1993 vs 2015 to 2019 and identify and characterize hot spots showing unexpected changes over time. Design, Setting, and Participants: This is a cross-sectional study with 2 time points using a novel small area estimation method to analyze restricted access mortality microdata by cause of death and US county. The analysis included 3111 US counties from 49 states and the District of Columbia from January 1, 1989, to December 31, 2019. Bayesian spatial models were fitted to map geographical variation in changes in age-standardized firearm mortality rates (per 100 000 person-years) from 1989 to 1993 vs 2015 to 2019. County outliers (or hot spots) were defined as having observed rates that fell outside the 95% credible intervals of their expected posterior predictive distribution. These counties were characterized using visualization and descriptive statistics of their characteristics. Data were analyzed from June to December 2021. Exposures: County of residence. Main Outcomes and Measures: Five-year age-standardized mortality rates by US county, age, and cause of death for 1989 to 1993 and 2015 to 2019. Results: Between 1989 and 2019, 1 036 518 firearm deaths were recorded in counties across the US. Suicide was the most common cause of firearm mortality (589 285 deaths) followed by homicide (412 231 deaths). Age-standardized rates (deaths per 100 000 individuals) for firearm deaths and suicides increased from 1989 to 1993 vs 2015 to 2019 (mean [SD] change, 0.16 [8.78] for firearm deaths and 1.21 [6.91] for suicides), while firearm homicides decreased (mean [SD] change, -0.39 [3.96]). However, these national trends were not homogeneous across counties and often varied by geographical region. The West and Midwest showed the most pronounced increases in firearm suicide rates, whereas the Southeast showed localized increases in firearm homicide rates, despite the national decreasing trend. Critical hot spots were identified in urban counties of Alabama, and firearm homicide rates (per 100 000) in Baltimore City, Maryland, almost doubled from 29.71 to 47.43, and by 2015 to 2019 it accounted for 66.7% of all firearm homicide in Maryland. By contrast, District of Columbia showed promising improvements over time, decreasing from 56.5 firearm homicides per 100 000 in 1989 to 1993 to 14.45 in 2015 to 2019. Conclusions and Relevance: There was substantial variation in rates and changes in firearm deaths among US counties. Geographical hot spots may be useful to inform targeted prevention efforts and local policy responses.

Indexed as

FirearmsSuicideBayes TheoremCross-Sectional StudiesHomicideHumans

Identifiers

PMID35666501
PMCPMC9171565

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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.