In 2023, there were ****** fatalities caused by injuries related to firearms in the United States, a slight decrease from the previous year. In 2021, there were ****** firearm deaths, the highest number of gun deaths ever recorded in the country. However, this figure has remained relatively high over the past 25 years, with ****** firearm deaths in 1990 and a slight dip in fatalities between 1999 and 2002. Firearms in the United States The right to own firearms in the United States is enshrined in the 2nd Amendment of the U.S. Constitution, and while this right may be seen as quintessentially American, the relationship between Americans and their firearms has become fraught in the last few years. The proliferation of mass shootings in the U.S. has brought the topic of gun control into the national spotlight, with support for banning assault-style weapons a particularly divisive issue among Americans. Gun control With a little less than **** of all Americans owning at least one firearm and the highest rate of civilian gun ownership in the world, it is easy to see how the idea of gun control is a political minefield in the U.S. However, public opinion has begun to shift over the past ten years, and a majority of Americans report that laws governing the sale of firearms should be stricter than they are now.

Number and percentage of homicide victims, by type of firearm used to commit the homicide (total firearms; handgun; rifle or shotgun; other firearm-like weapons; firearm, type of firearm is unknown), Canada, 1974 to 2024.

In recent years, gun violence in the United States has become an alarmingly common occurrence. From 2016, there has been over ****** homicides by firearm in the U.S. each year and firearms have been found to make up the majority of murder weapons in the country by far, demonstrating increasing rates of gun violence occurring throughout the nation. As of 2025, Mississippi was the state with the highest gun violence rate per 100,000 residents in the United States, at **** percent, followed by Louisiana, at **** percent. In comparison, Massachusetts had a gun violence rate of *** percent, the lowest out of all the states. The importance of gun laws Gun laws in the United States vary from state to state, which has been found to affect the differing rates of gun violence throughout the country. Fewer people die by gun violence in states where gun safety laws have been passed, while gun violence rates remain high in states where gun usage is easily permitted and even encouraged. In addition, some states suffer from high rates of gun violence despite having strong gun safety laws due to gun trafficking, as traffickers can distribute firearms illegally past state lines. The right to bear arms Despite evidence from other countries demonstrating that strict gun control measures reduce rates of gun violence, the United States has remained reluctant to enact gun control laws. This can largely be attributed to the Second Amendment of the Constitution, which states that citizens have the right to bear arms. Consequently, gun control has become a highly partisan issue in the U.S., with ** percent of Democrats believing that it was more important to limit gun ownership while ** percent of Republicans felt that it was more important to protect the right of Americans to own guns.

The dataset is sourced and edited from
data.world

Description is given as below:

Centers for Disease Control and Prevention, National Center for Health Statistics. Multiple Cause of Death with U.S. - Mexico Border Regions 1999-2019 on CDC WONDER Online Database, released in 2020. Data are from the Multiple Cause of Death Files, 1999-2019, as compiled from data provided by the 57 vital statistics jurisdictions through the Vital Statistics Cooperative Program. U.S. - Mexico border counties has been demarcated as the 44 counties that are located within 100 kilometers (62 miles) defined under the 1983 La Paz Agreement. Accessed at http://wonder.cdc.gov/ucd-border.html on Nov 6, 2021 12:22:30 AM

Query Parameters: Title: Gun Deaths by County MCD - ICD-10 Codes: W32 (Handgun discharge); W33 (Rifle, shotgun and larger firearm discharge); W34 (Discharge from other and unspecified firearms); X72 (Intentional self-harm by handgun discharge); X73 (Intentional self-harm by rifle, shotgun and larger firearm discharge); X74 (Intentional self-harm by other and unspecified firearm discharge); X93 (Assault by handgun discharge); X94 (Assault by rifle, shotgun and larger firearm discharge); X95 (Assault by other and unspecified firearm discharge); Y22 (Handgun discharge, undetermined intent); Y23 (Rifle, shotgun and larger firearm discharge, undetermined intent); Y24 (Other and unspecified firearm discharge, undetermined intent); Y35.0 (Legal intervention involving firearm discharge)

Group By: Year; County Show Totals: True Show Zero Values: False Show Suppressed: False Standard Population: 2000 U.S. Std. Population Calculate Rates Per: 100,000 Rate Options: Default intercensal populations for years 2001-2009 (except Infant Age Groups)

picture sourced from peterplit

Mortality rate from firearms includes homicides, suicides, accidental deaths, deaths by law enforcement, and deaths for which intent was undetermined. Mortality rate is based on the location of residence and has been age-adjusted to the 2000 U.S. standard population. ICD 10 codes used to identify firearm deaths are W32-W34, X72-X74, X93-X95, Y22-Y24, Y35.0, and U01.4. Single-year data are only available for Los Angeles County overall, Service Planning Areas, Supervisorial Districts, City of Los Angeles overall, and City of Los Angeles Council Districts.Violence is a public health crisis in the US, with gun violence being a major driver. In the US, the age-adjusted homicide rate from firearms is more than 20 times higher than in the European Union or in Australia. Significant disparities by age, sex, and race and ethnicity exist, with young adults (ages 15-34 years), males, and Black individuals most disproportionately impacted. Firearm-related suicides disproportionately impact older, White men. Comprehensive prevention strategies should work to address underlying physical, social, economic, and structural conditions known to increase risk.For more information about the Community Health Profiles Data Initiative, please see the initiative homepage.

Updated dataset for the "Gun Deaths in America" project https://fivethirtyeight.com/features/gun-deaths/, documenting firearm usage fatalities.

The R code for processing the raw data is taken from https://github.com/fivethirtyeight/guns-data

I will be progressively adding the years before 2006, but the data format changed several times, so it is not as fast as I would like :-/ User guide for processing: https://www.cdc.gov/nchs/nvss/mortality_public_use_data.htm

The dataset that I have created through web scraping using BeautifulSoup library in Python provides a comprehensive overview of the legality of firearms across various countries. It contains detailed information on the laws and regulations governing firearms possession, use, and ownership. The dataset also includes data on the number of deaths resulting from firearm incidents, including suicides, accidents, and police shootings. In addition, the dataset provides insights into the number of firearms owned by citizens, whether they are registered or unregistered. The information is compiled from reliable sources such as Wikipedia, Wisevoter, GunPolicy, and WorldPopulationReview, ensuring that the dataset is both comprehensive and accurate. This dataset is an invaluable resource for researchers, policymakers, and others who are interested in studying the prevalence and impact of firearms on society. With its comprehensive coverage of firearm laws and incidents across various countries, this dataset offers valuable insights into the complex issue of gun control and can be used to inform policy decisions aimed at reducing the negative impact of firearms on individuals and communities.

The dataset I have created can be used for various technical applications such as machine learning and data analytics. For example, researchers and developers can use this dataset to train machine learning algorithms to identify patterns and correlations between firearm laws and incidents. This can help in developing predictive models to forecast firearm-related incidents and aid in policymaking. Data analytics techniques can also be applied to the dataset to identify trends and patterns in the data, helping researchers to gain a better understanding of the complex issues surrounding firearms. Overall, the dataset I have created offers a wealth of information on firearms laws and incidents, and its potential applications extend beyond research to include policy and decision-making in various fields.

*******Links used:******* - Wikipedia - WiseVoter - GunPolicy - WorldPopulationReview

The death rate from firearm-related injuries in the United States reached 19.4 per 100,000 population among males in 2016. Females have a much smaller rate of firearm-related deaths than males, with the rate among males over five times that of females. The overall death rate from firearm-related injuries has risen in recent years after seeing a drop in the late 1990s.

Homicides from firearms

Homicides account for a large portion of firearm-related deaths. In 2017, there were almost 11,000 homicides by firearm in the United States. In fact, as of that time, homicides by firearm accounted for around 72.6 percent of all homicides in the U.S. Handguns are the most commonly used firearm for homicide.

Gun ownership

Firearms regulation, or gun control, remains a relevant and divisive issue in the U.S. However, the ownership of legal firearms is widespread. As of 2018, around 43 percent of households had at least one firearm, an increase from recent years. Unsurprisingly, just as men have a higher death rate from firearms, they also have a much higher firearm ownership rate.

1) Data Introduction • The Gun Violence Dataset in US is a tabularized data set for gun violence analysis that includes the date, location, victim and suspect information, and geographic coordinates of major 2024 shootings across the U.S.

2) Data Utilization (1) Gun Violence Dataset in US has characteristics that: • Each row contains key information about the shooting, including incident-specific ID, date of occurrence, state and city/county, number of deaths and injuries, suspects (death, injury, arrest), latitude, and longitude. • Data is designed to analyze the distribution of gun incidents and the extent of damage by month and region, and spatial analysis through geographic coordinates is also possible. (2) Gun Violence Dataset in US can be used to: • Analysis of shooting trends by region: Use data by location, magnitude of damage, and time to visualize and analyze the regional and temporal distribution and risk areas of gun violence. • Establishing public safety policies and prevention strategies: Based on victim and suspect information and incident characteristics, it can be used to establish effective gun control, prevention policies, resource allocation strategies, and more.

Data tables relating to offences involving weapons as recorded by police and hospital episode statistics.

The Office of Gun Violence Prevention (OGVP) shares real-time gun violence data to increase government transparency, improve the public's awareness, and support community-based gun violence prevention and reduction partners. All District crime data is available through Crime Cards. The dashboards below focus on gun violence only. The data in these dashboards is updated daily at 7:40AM with the incidents from the day before. View data covering 7-Day Look-back of Gun Violence and Year-to-date Gun Violence.All statistics presented here are based on preliminary DC criminal code offense definitions. The data do not represent official statistics submitted to the FBI under the Uniform Crime Reporting program (UCR) or National Incident Based Reporting System (NIBRS). All preliminary offenses are coded based on DC criminal code and not the FBI offense classifications. Please understand that any comparisons between MPD preliminary data as published on this website and the official crime statistics published by the FBI under the Uniform Crime Reporting Program (UCR) are inaccurate and misleading. The MPD does not guarantee (either expressed or implied) the accuracy, completeness, timeliness, or correct sequencing of the information. The MPD will not be responsible for any error or omission, or for the use of, or the results obtained from the use of this information. Read complete data notes at buildingblocks.dc.gov/data.

This dataset consists of gun violence within Jefferson county that may fall within LMPDs radar, including non-fatal shootings, homicides, as well as shot-spotter data. The mapping data points where there are victims have been obfuscated to maintain privacy, while still being accurate enough to be placed in its correct boundaries, particularly around, neighborhoods, ZIP Codes, Council districts, and police divisions. The data also excludes any victim information that could be used to identify any individual. this data is used to make the public aware of what is going on in their communities. The data consists of only criminal incidents, excluding any cases that are deemed non-criminal.Field NameField DescriptionCase numberPolice report number. For ShotSpotter detections, it is the ShotSpotter ID.DateTimeDate and time in which the original incident occurred. Time is rounded down.AddressAddress rounded down to the one hundred block of where the initial incident occured. Unless it is an intersection.NeighborhoodNeighborhood in which the original incident occurred.Council DistrictCouncil district in which the original incident occurred.LatitudeLatitude coordinate used to map the incidentLongitudeLongitude coordinate used to map the incidentZIP CodeZIP Code in which the original incident occurred.Crime Typea distinction between incidents, whether it is a non-fatal shooting, homicide, or a ShotSpotter detection.CauseUsed to differentiate on the cause of death for homicide victims.SexGender of the victim of the initial incident.RaceRace/Ethnicity of the victim in a given incident.Age GroupCategorized age groups used to anonymize victim information.Division NamePolice division or department where the initial incident occurred.Crime report data is provided for Louisville Metro Police Divisions only; crime data does not include smaller class cities, unless LMPD becomes involved in smaller agency incident.The data provided in this dataset is preliminary in nature and may have not been investigated by a detective at the time of download. The data is therefore subject to change after a complete investigation. This data represents only calls for police service where a police incident report was taken. Due to the variations in local laws and ordinances involving crimes across the nation, whether another agency utilizes Uniform Crime Report (UCR) or National Incident Based Reporting System (NIBRS) guidelines, and the results learned after an official investigation, comparisons should not be made between the statistics generated with this dataset to any other official police reports. Totals in the database may vary considerably from official totals following the investigation and final categorization of a crime. Therefore, the data should not be used for comparisons with Uniform Crime Report or other summary statistics.Contact:Ivan Benitez, Ph.D.Gun Violence Data FellowOffice for Safe and Healthy Neighborhoodsivan.benitez@louisvilleky.gov

THIS DATASET WAS LAST UPDATED AT 7:11 AM EASTERN ON DEC. 1

OVERVIEW

2019 had the most mass killings since at least the 1970s, according to the Associated Press/USA TODAY/Northeastern University Mass Killings Database.

In all, there were 45 mass killings, defined as when four or more people are killed excluding the perpetrator. Of those, 33 were mass shootings . This summer was especially violent, with three high-profile public mass shootings occurring in the span of just four weeks, leaving 38 killed and 66 injured.

A total of 229 people died in mass killings in 2019.

The AP's analysis found that more than 50% of the incidents were family annihilations, which is similar to prior years. Although they are far less common, the 9 public mass shootings during the year were the most deadly type of mass murder, resulting in 73 people's deaths, not including the assailants.

One-third of the offenders died at the scene of the killing or soon after, half from suicides.

About this Dataset

The Associated Press/USA TODAY/Northeastern University Mass Killings database tracks all U.S. homicides since 2006 involving four or more people killed (not including the offender) over a short period of time (24 hours) regardless of weapon, location, victim-offender relationship or motive. The database includes information on these and other characteristics concerning the incidents, offenders, and victims.

The AP/USA TODAY/Northeastern database represents the most complete tracking of mass murders by the above definition currently available. Other efforts, such as the Gun Violence Archive or Everytown for Gun Safety may include events that do not meet our criteria, but a review of these sites and others indicates that this database contains every event that matches the definition, including some not tracked by other organizations.

This data will be updated periodically and can be used as an ongoing resource to help cover these events.

Using this Dataset

To get basic counts of incidents of mass killings and mass shootings by year nationwide, use these queries:

Mass killings by year

Mass shootings by year

To get these counts just for your state:

Filter killings by state

Definition of "mass murder"

Mass murder is defined as the intentional killing of four or more victims by any means within a 24-hour period, excluding the deaths of unborn children and the offender(s). The standard of four or more dead was initially set by the FBI.

This definition does not exclude cases based on method (e.g., shootings only), type or motivation (e.g., public only), victim-offender relationship (e.g., strangers only), or number of locations (e.g., one). The time frame of 24 hours was chosen to eliminate conflation with spree killers, who kill multiple victims in quick succession in different locations or incidents, and to satisfy the traditional requirement of occurring in a “single incident.”

Offenders who commit mass murder during a spree (before or after committing additional homicides) are included in the database, and all victims within seven days of the mass murder are included in the victim count. Negligent homicides related to driving under the influence or accidental fires are excluded due to the lack of offender intent. Only incidents occurring within the 50 states and Washington D.C. are considered.

Methodology

Project researchers first identified potential incidents using the Federal Bureau of Investigation’s Supplementary Homicide Reports (SHR). Homicide incidents in the SHR were flagged as potential mass murder cases if four or more victims were reported on the same record, and the type of death was murder or non-negligent manslaughter.

Cases were subsequently verified utilizing media accounts, court documents, academic journal articles, books, and local law enforcement records obtained through Freedom of Information Act (FOIA) requests. Each data point was corroborated by multiple sources, which were compiled into a single document to assess the quality of information.

In case(s) of contradiction among sources, official law enforcement or court records were used, when available, followed by the most recent media or academic source.

Case information was subsequently compared with every other known mass murder database to ensure reliability and validity. Incidents listed in the SHR that could not be independently verified were excluded from the database.

Project researchers also conducted extensive searches for incidents not reported in the SHR during the time period, utilizing internet search engines, Lexis-Nexis, and Newspapers.com. Search terms include: [number] dead, [number] killed, [number] slain, [number] murdered, [number] homicide, mass murder, mass shooting, massacre, rampage, family killing, familicide, and arson murder. Offender, victim, and location names were also directly searched when available.

This project started at USA TODAY in 2012.

Contacts

Contact AP Data Editor Justin Myers with questions, suggestions or comments about this dataset at jmyers@ap.org. The Northeastern University researcher working with AP and USA TODAY is Professor James Alan Fox, who can be reached at j.fox@northeastern.edu or 617-416-4400.

The Gun Violence Archive (GVA) is an online archive of gun violence incidents collected from over 7,500 law enforcement, media, government and commercial sources daily in an effort to provide near-real time data about the results of gun violence. GVA was established in 2013 an independent data collection and research group to provide comprehensive data for the national conversation regarding gun violence.

GVA catalogs both incidents of gun-related deaths and incidents where a victim was injured by shooting or by a victim who was the subject of an armed robber or home invader. Incidents of defensive gun use, homeowners who stop a home invasion, store clerks who stop a robbery, individuals who stop an assault or rape with a gun are also collected. The two exceptions to the near real-time collection are suicides by gun, which are collected quarterly and annually due to differing distribution methods by government agencies, and for armed robberies with no injuries or DGU characteristics, which are collected in aggregate with law enforcement quarterly and annual reports. GVA also records incidents of Bureau of Alcohol, Tobacco, Firearms, and Explosives (ATF) and local law enforcement involvement in recovering illegal or stolen weapons; incidents where guns were reported stolen from homes, vehicles, and businesses; incidents where Airsoft or BB guns are used as weapons (but not where they are used in general vandalism or delinquency); and TSA data of guns illegally taken through airport security points. Incident data are categorized by number of deaths, number of injuries, number of children, number of teens, mass shootings, officers shot, suspect shot by officer, home invasion, defensive use, and unintentional shooting.

Description:

This comprehensive dataset offers an in-depth look at gun-related deaths in the United States from 2012 to 2014, as reported by the Centers for Disease Control and Prevention (CDC). It provides a rich source of information for public health research, policy development, and sociological studies, offering a nuanced understanding of the dynamics and demographics of gun-related fatalities.

Features:

• Year: The year when the death occurred, providing a temporal context.
• Month: The month of the incident, adding more granularity to the timeline.
• Intent: Categorizes the death by intent, such as suicide or homicide, essential for understanding the circumstances.
• Police: Indicates whether a police officer was involved in the death.
• Sex: The gender of the deceased, crucial for demographic analysis.
• Age: The age of the deceased, providing insights into age-related trends.
• Race: The race of the deceased, essential for understanding racial disparities.
• Place: The location of the incident, such as home or street, which can influence the context of the death.
• Education: Educational background of the deceased, offering a socio-economic dimension.

Use Case:

This dataset is highly valuable for tasks such as public health research, policy formulation in gun control, and sociological studies. It can be employed to analyze trends and patterns in gun-related deaths, assist in crafting informed laws and public safety measures, and provide a foundation for educational and awareness initiatives about gun violence and its impact on different demographic groups.

Note: - Entries are organized chronologically, capturing each recorded incident in detail. - The dataset is especially significant for examining year-on-year trends and demographic variances in gun-related fatalities, serving as a critical resource for comprehensive analysis and research.

This statistic shows the number of gun deaths in the United States annually as an average from the years 2012 to 2014, by race per 100,000 population. On average, there were 20 deaths per 100,000 people annually among to the black population of the United States. The corresponding rate among the white population was nearly half at 11.2 gun deaths per 100,000 people annually.

Context

This dataset includes information about gun-death in the US in the years 2012-2014.

Content

The data includes data regarding the victim's age, sex, race, education, intent, time (month and year) and place of death, and whether or not police was at the place of death.

Acknowledgements

I came across this thanks to FiveThirtyEight's Gun Deaths in America project. The data originated from the CDC, and can be found here.

BackgroundGun violence has shortened the average life expectancy of Americans, and better knowledge about the root causes of gun violence is crucial to its prevention. While some empirical evidence exists regarding the impacts of social and economic factors on violence and firearm homicide rates, to the author’s knowledge, there has yet to be a comprehensive and comparative lagged, multilevel investigation of major social determinants of health in relation to firearm homicides and mass shootings.Methods and findingsThis study used negative binomial regression models and geolocated gun homicide incident data from January 1, 2015, to December 31, 2015, to explore and compare the independent associations of key state-, county-, and neighborhood-level social determinants of health—social mobility, social capital, income inequality, racial and economic segregation, and social spending—with neighborhood firearm-related homicides and mass shootings in the United States, accounting for relevant state firearm laws and a variety of state, county, and neighborhood (census tract [CT]) characteristics. Latitude and longitude coordinates on firearm-related deaths were previously collected by the Gun Violence Archive, and then linked by the British newspaper The Guardian to CTs according to 2010 Census geographies. The study population consisted of all 74,134 CTs as defined for the 2010 Census in the 48 states of the contiguous US. The final sample spanned 70,579 CTs, containing an estimated 314,247,908 individuals, or 98% of the total US population in 2015. The analyses were based on 13,060 firearm-related deaths in 2015, with 11,244 non-mass shootings taking place in 8,673 CTs and 141 mass shootings occurring in 138 CTs. For area-level social determinants, lag periods of 3 to 17 years were examined based on existing theory, empirical evidence, and data availability. County-level institutional social capital (levels of trust in institutions), social mobility, income inequality, and public welfare spending exhibited robust relationships with CT-level gun homicide rates and the total numbers of combined non-mass and mass shooting homicide incidents and non-mass shooting homicide incidents alone. A 1–standard deviation (SD) increase in institutional social capital was linked to a 19% reduction in the homicide rate (incidence rate ratio [IRR] = 0.81, 95% CI 0.73–0.91, p < 0.001) and a 17% decrease in the number of firearm homicide incidents (IRR = 0.83, 95% CI 0.73–0.95, p = 0.01). Upward social mobility was related to a 25% reduction in the gun homicide rate (IRR = 0.75, 95% CI 0.66–0.86, p < 0.001) and a 24% decrease in the number of homicide incidents (IRR = 0.76, 95% CI 0.67–0.87, p < 0.001). Meanwhile, 1-SD increases in the neighborhood percentages of residents in poverty and males living alone were associated with 26%–27% and 12% higher homicide rates, respectively. Study limitations include possible residual confounding by factors at the individual/household level, and lack of disaggregation of gun homicide data by gender and race/ethnicity.ConclusionsThis study finds that the rich–poor gap, level of citizens’ trust in institutions, economic opportunity, and public welfare spending are all related to firearm homicide rates in the US. Further establishing the causal nature of these associations and modifying these social determinants may help to address the growing gun violence epidemic and reverse recent life expectancy declines among Americans.

Handguns are by far the most common murder weapon used in the United States, accounting for 7,159 homicides in 2023. This is followed by firearms of an unstated type, with 5,295 cases in that year. Why do murders happen in the U.S.? While most of the time the circumstances of murders in the U.S. remain unknown, homicides due to narcotics come in as the second most common circumstance – making them more common than, for example, gang killings. Despite these gruesome facts, the violent crime rate has fallen significantly since 1990, and the United States is much safer than it was in the 1980s and 1990s. Knife crime vs disease: Leading causes of death The death rate in the U.S. had hovered around the same level since 1990 until there was a large increase due to the COVID-19 pandemic in recent years. Heart disease, cancer, and accidents were the three leading causes of death in the country in 2022. The rate of death from heart disease is significantly higher than the homicide rate in the United States, at 167.2 deaths per 100,000 population compared to a 5.7 homicides per 100,000. Given just 1,562 murders were caused by knife crime, it is fair to say that heart disease is a far bigger killer in the U.S.

This study was undertaken to obtain information on the characteristics of gun ownership, gun-carrying practices, and weapons-related incidents in the United States -- specifically, gun use and other weapons used in self-defense against humans and animals. Data were gathered using a national random-digit-dial telephone survey. The respondents were comprised of 1,905 randomly-selected adults aged 18 and older living in the 50 United States. All interviews were completed between May 28 and July 2, 1996. The sample was designed to be a representative sample of households, not of individuals, so researchers did not interview more than one adult from each household. To start the interview, six qualifying questions were asked, dealing with (1) gun ownership, (2) gun-carrying practices, (3) gun display against the respondent, (4) gun use in self-defense against animals, (5) gun use in self-defense against people, and (6) other weapons used in self-defense. A "yes" response to a qualifying question led to a series of additional questions on the same topic as the qualifying question. Part 1, Survey Data, contains the coded data obtained during the interviews, and Part 2, Open-Ended-Verbatim Responses, consists of the answers to open-ended questions provided by the respondents. Information collected for Part 1 covers how many firearms were owned by household members, types of firearms owned (handguns, revolvers, pistols, fully automatic weapons, and assault weapons), whether the respondent personally owned a gun, reasons for owning a gun, type of gun carried, whether the gun was ever kept loaded, kept concealed, used for personal protection, or used for work, and whether the respondent had a permit to carry the gun. Additional questions focused on incidents in which a gun was displayed in a hostile manner against the respondent, including the number of times such an incident took place, the location of the event in which the gun was displayed against the respondent, whether the police were contacted, whether the individual displaying the gun was known to the respondent, whether the incident was a burglary, robbery, or other planned assault, and the number of shots fired during the incident. Variables concerning gun use by the respondent in self-defense against an animal include the number of times the respondent used a gun in this manner and whether the respondent was hunting at the time of the incident. Other variables in Part 1 deal with gun use in self-defense against people, such as the location of the event, if the other individual knew the respondent had a gun, the type of gun used, any injuries to the respondent or to the individual that required medical attention or hospitalization, whether the incident was reported to the police, whether there were any arrests, whether other weapons were used in self-defense, the type of other weapon used, location of the incident in which the other weapon was used, and whether the respondent was working as a police officer or security guard or was in the military at the time of the event. Demographic variables in Part 1 include the gender, race, age, household income, and type of community (city, suburb, or rural) in which the respondent lived. Open-ended questions asked during the interview comprise the variables in Part 2. Responses include descriptions of where the respondent was when he or she displayed a gun (in self-defense or otherwise), specific reasons why the respondent displayed a gun, how the other individual reacted when the respondent displayed the gun, how the individual knew the respondent had a gun, whether the police were contacted for specific self-defense events, and if not, why not.