Oluwasegun A. Akinyemi • Temitope Ogundare • Terhas Wedeslase • Brandon Hartmann • Eunice Odusanya • Mallory Williams • Kakra Hughes • Edward Cornwell III
Introduction
Firearm injuries and deaths are a significant public health problem in the United States, accounting for about 48,830 deaths in 2021 [1]. Compared to other high-income countries, the United States has higher rates of firearm-related deaths, estimated to be about 25 times higher [2]. Globally, in 2016, the United States accounted for 91.7% of women and 98.1% of children killed by firearms [2]. Black and other minority groups are disproportionately affected by firearm-related deaths; Black men are 10-20 times more likely to be killed by firearms, and American Indian and Alaskan Native men are about 3-4 times more likely to die from firearm-related suicides [3]. Over the past decade, there has been a steady but fluctuating increase in firearm-related deaths in the United States, with firearm-related homicides and suicides contributing to the total number. In 2021, firearm-related suicides accounted for 54% of all firearm-related deaths in the United States, while 43% were firearm-related homicides [1]. Firearm-related deaths have an impact on individuals, families, and communities, with an estimated economic burden of $280 billion annually [4]. Firearm-related deaths are also associated with anxiety disorders, substance use disorders, and increased firearm purchasing [3].
Effective prevention strategies depend on the identification of risk factors. The Centers for Disease Control and Prevention proposed a socioecological model as a framework for determining the various levels of risk factors associated with firearm-related violence [4]. Individual-level risk factors related to firearm-related deaths include low socioeconomic status, mental health disorders, substance use disorders, adverse childhood events, and access to firearms [5]. Risk factors at the interpersonal and community levels include the absence of social support, family mental illness, substance use disorder, community-level poverty/unemployment, aspects of the built environment (such as green spaces, concentration of liquor stores, and vacant lots), social factors (such as access to healthcare, including mental health and substance use treatments), and crime levels [5,6]. At the structural/policy levels, structural racism, funding for firearm prevention research, firearm policies, and policies related to health, economics, and education all serve as risk factors for firearm-related deaths [5,6]. These risk factors interact with each other and are dynamic [5].
The passage of the Omnibus Act in 1996 stalled research into firearms and firearm death prevention for more than two decades by significantly limiting funding, leading to a decline in publications related to firearm injuries and deaths [7,8]. In 2013, the National Academy of Medicine and National Research Council outlined five key areas in developing research in firearm-related injuries and deaths, including characteristics of firearm violence, risk and protective factors, intervention and strategies, firearm safety technology, and influence of video games and other media [7]. There is a need for a comprehensive body of evidence to inform policies and design public health interventions to reduce harm from firearms and improve community safety and health [7].
In this study, we provide comprehensive data on trends in firearm-related deaths in the United States over the past 55 years to provide valuable insights into the changing landscape of firearm mortalities. In addition, we aim to determine the risk and protective factors associated with firearm-related suicides and homicides to provide evidence for the design and implementation of public health interventions. We also aim to provide data that can inform effective policies. Most often, firearm research and violence prevention have been highly politicized. However, it is important that, given the significant burden of firearm-related injuries and deaths, we have data to support arguments for proposed interventions. Data-driven policies and interventions are the most effective and cost-effective [9,10].
Materials & Methods
This study utilized data from the Centers for Disease Control and Prevention’s Web-based Injury Statistics Query and Reporting System (WISQARS). It is a national database containing detailed information on fatal injuries. It covers homicides, suicides, deaths of undetermined intent possibly related to violence, law enforcement fatalities (excluding executions), and unintentional firearm-related deaths. This database offers more comprehensive insights compared to other violent death databases. Violent death is defined as those involving intentional physical force against oneself, another person, or a group/community. The database provides extensive data on circumstances leading to deaths, including events preceding the incident and toxicology details, as well as specifics on weapons, injuries, and other incident characteristics. Circumstances reported vary by manner of death, with suicides and undetermined deaths related to mental health history, disclosure of suicidal intent, and precipitating factors like crises or financial issues. Homicide circumstances focus on criminal activity and interpersonal conflicts, while unintentional firearm-related death circumstances relate to the incident context and firearm usage. Data for WISQARS is sourced from law enforcement reports, medical examiner/coroner reports, and death certificates. The database was launched in 2003 with six states but now includes data from all 50 states, the District of Columbia, and Puerto Rico and is updated annually. Population estimates used in WISQARS are generated by the US Census Bureau in collaboration with the CDC’s National Center for Health Statistics (NCHS) [11]. Violent death statistics in the database rely on International Classification of Disease-10th Revision (ICD-10) codes and manner of death information from source documents. Each record includes data on victims and alleged perpetrators associated with the incident, defined as related fatal injuries occurring within a 24-hour period. WISQARS is a comprehensive, publicly accessible database that provides information on injury-related morbidities and mortalities in the United States. The WISQARS violent module was used in the study. It is a restricted-access database that is available upon request. The data extracted for this study were from 1968 to 2022. The study population comprised all recorded cases in the WISQARS database within the specified timeframe.
Outcome variables
The primary outcome variables were categorized into four distinct types of firearm-related deaths: suicides, homicides, unintentional, and undetermined. These categories were based on the manner of death recorded in the database.
Covariates
Covariates included demographic data, such as age (categorized into different groups), gender, race/ethnicity, and education level; mental health disorders, such as depression, dementia, bipolar disorder, and anxiety; and physical health conditions, such as hypertension and obesity. Temporal factors such as the season of the death occurrence were also included in our analysis.
Statistical analysis
The statistical analysis was conducted using STATA 16 (StataCorp LLC, College Station, TX, United States) statistical software. Descriptive statistics are presented using tables and figures. Age was categorized into four groups: 10-19 years, 20-44 years, 45-64 years, and 65 years and older. Education level was categorized into high school education, tertiary (represents those who have a college education), and advanced (represents those with advanced degrees).
A multivariate logistic regression model was employed to identify independent predictors of firearm-related suicides, homicides, and unintentional deaths. Covariates included in the regression model were age, gender, race/ethnicity, education level, mental health disorders, and seasonal factors, based on their known associations with firearm-related mortalities, as indicated by previous research and theoretical frameworks. The model also included interaction terms between race/ethnicity and education level to explore the intersectionality of these factors. A simultaneous entry method was used to fit the variables in the regression model. This method was selected because it allows for the assessment of the effect of each variable while controlling for the other variables and assessing the overall explanatory power of a set of variables without prioritizing any particular one. The analysis excluded missing data, ensuring that only complete cases were used in the final models. This approach was taken to maintain the robustness of the statistical analyses and avoid biases that could arise from imputation methods. All tests were two-sided, with a significance level set at p < 0.05. The goodness-of-fit of the logistic regression models was assessed using the Hosmer-Lemeshow test, and the variance inflation factor was calculated to check for multicollinearity.
Ethical approval
The study was conducted in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. Institutional Review Board approval was waived because the study was carried out on a national database that contained de-identified data and did not require informed consent or direct patient participation.
Results
From 1968 to 2022, the total number of firearm-related deaths in the United States displayed a generally increasing trend, rising from 23,875 in 1968 to 48,205 in 2022. Over the past 55 years, firearm-related suicides consistently accounted for a significant proportion of firearm-related deaths, rising from 10,911 in 1968 to 27,034 in 2022. In contrast, firearm-related homicides, after a decline in the early 2000s, saw a resurgence, climbing from 11,208 in 2013 to 19,645 in 2022.
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