In the United States, Black people have higher rates of gun homicide than White people across all age groups. As of 2022, gun homicide rates were highest among Black people aged between 15 and 24 years, at ***** gun homicides per 100,000 of the population. In comparison, there were only **** gun homicides per 100,000 of the White population within this age range. However, the risk for gun homicide was greatest among all adolescents and adults between the ages of 15 to 44 in that year. The impact of guns on young Americans In the last few years, firearms have become the leading cause of death for American children and teenagers aged one to 19 years old, accounting for more deaths than car crashes and diseases. School shootings also remain on the rise recently, with the U.S. recording ** times as many school shootings than other high-income nations from 2009 to 2018. Black students in particular experience a disproportionately high number of school shootings relative to their population, and K-12 teachers at schools made up mostly of students of color are more likely to report feeling afraid that they or their students would be a victim of attack or harm. The right to bear arms Despite increasingly high rates of gun-related violence, gun ownership remains a significant part of American culture, largely due to the fact that the right to bear arms is written into the U.S. Constitution. Although firearms are the most common murder weapon used in the U.S., accounting for approximately ****** homicides in 2022, almost **** of American households have at least one firearm in their possession. Consequently, it is evident that firearms remain easily accessible nationwide, even though gun laws may vary from state to state. However, the topic of gun control still causes political controversy, as the majority of Republicans agree that it is more important to protect the right of Americans to own guns, while Democrats are more inclined to believe that it is more important to limit gun ownership.

As of 2021, Black men had the highest firearm homicide rate in the United States, with ***** homicides by firearm per 100,000 of the population. In comparison, Black women had a firearm homicide rate of **** per 100,000 of the population. In that year, the risk of gun homicide was lowest among Asian people across all genders.

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.

This dataset contains aggregate data on violent index victimizations at the quarter level of each year (i.e., January – March, April – June, July – September, October – December), from 2001 to the present (1991 to present for Homicides), with a focus on those related to gun violence. Index crimes are 10 crime types selected by the FBI (codes 1-4) for special focus due to their seriousness and frequency. This dataset includes only those index crimes that involve bodily harm or the threat of bodily harm and are reported to the Chicago Police Department (CPD). Each row is aggregated up to victimization type, age group, sex, race, and whether the victimization was domestic-related. Aggregating at the quarter level provides large enough blocks of incidents to protect anonymity while allowing the end user to observe inter-year and intra-year variation. Any row where there were fewer than three incidents during a given quarter has been deleted to help prevent re-identification of victims. For example, if there were three domestic criminal sexual assaults during January to March 2020, all victims associated with those incidents have been removed from this dataset. Human trafficking victimizations have been aggregated separately due to the extremely small number of victimizations.

This dataset includes a " GUNSHOT_INJURY_I " column to indicate whether the victimization involved a shooting, showing either Yes ("Y"), No ("N"), or Unknown ("UKNOWN.") For homicides, injury descriptions are available dating back to 1991, so the "shooting" column will read either "Y" or "N" to indicate whether the homicide was a fatal shooting or not. For non-fatal shootings, data is only available as of 2010. As a result, for any non-fatal shootings that occurred from 2010 to the present, the shooting column will read as “Y.” Non-fatal shooting victims will not be included in this dataset prior to 2010; they will be included in the authorized dataset, but with "UNKNOWN" in the shooting column.

The dataset is refreshed daily, but excludes the most recent complete day to allow CPD time to gather the best available information. Each time the dataset is refreshed, records can change as CPD learns more about each victimization, especially those victimizations that are most recent. The data on the Mayor's Office Violence Reduction Dashboard is updated daily with an approximately 48-hour lag. As cases are passed from the initial reporting officer to the investigating detectives, some recorded data about incidents and victimizations may change once additional information arises. Regularly updated datasets on the City's public portal may change to reflect new or corrected information.

How does this dataset classify victims?

The methodology by which this dataset classifies victims of violent crime differs by victimization type:

Homicide and non-fatal shooting victims: A victimization is considered a homicide victimization or non-fatal shooting victimization depending on its presence in CPD's homicide victims data table or its shooting victims data table. A victimization is considered a homicide only if it is present in CPD's homicide data table, while a victimization is considered a non-fatal shooting only if it is present in CPD's shooting data tables and absent from CPD's homicide data table.

To determine the IUCR code of homicide and non-fatal shooting victimizations, we defer to the incident IUCR code available in CPD's Crimes, 2001-present dataset (available on the City's open data portal). If the IUCR code in CPD's Crimes dataset is inconsistent with the homicide/non-fatal shooting categorization, we defer to CPD's Victims dataset.

For a criminal homicide, the only sensible IUCR codes are 0110 (first-degree murder) or 0130 (second-degree murder). For a non-fatal shooting, a sensible IUCR code must signify a criminal sexual assault, a robbery, or, most commonly, an aggravated battery. In rare instances, the IUCR code in CPD's Crimes and Victims dataset do not align with the homicide/non-fatal shooting categorization:

1. In instances where a homicide victimization does not correspond to an IUCR code 0110 or 0130, we set the IUCR code to "01XX" to indicate that the victimization was a homicide but we do not know whether it was a first-degree murder (IUCR code = 0110) or a second-degree murder (IUCR code = 0130).
2. When a non-fatal shooting victimization does not correspond to an IUCR code that signifies a criminal sexual assault, robbery, or aggravated battery, we enter “UNK” in the IUCR column, “YES” in the GUNSHOT_I column, and “NON-FATAL” in the PRIMARY column to indicate that the victim was non-fatally shot, but the precise IUCR code is unknown.

Other violent crime victims: For other violent crime types, we refer to the IUCR classification that exists in CPD's victim table, with only one exception:

1. When there is an incident that is associated with no victim with a matching IUCR code, we assume that this is an error. Every crime should have at least 1 victim with a matching IUCR code. In these cases, we change the IUCR code to reflect the incident IUCR code because CPD's incident table is considered to be more reliable than the victim table.

Note: All businesses identified as victims in CPD data have been removed from this dataset.

Note: The definition of “homicide” (shooting or otherwise) does not include justifiable homicide or involuntary manslaughter. This dataset also excludes any cases that CPD considers to be “unfounded” or “noncriminal.”

Note: In some instances, the police department's raw incident-level data and victim-level data that were inputs into this dataset do not align on the type of crime that occurred. In those instances, this dataset attempts to correct mismatches between incident and victim specific crime types. When it is not possible to determine which victims are associated with the most recent crime determination, the dataset will show empty cells in the respective demographic fields (age, sex, race, etc.).

Note: The initial reporting officer usually asks victims to report demographic data. If victims are unable to recall, the reporting officer will use their best judgment. “Unknown” can be reported if it is truly unknown.

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.

Number, percentage and rate (per 100,000 population) of homicide victims, by racialized identity group (total, by racialized identity group; racialized identity group; South Asian; Chinese; Black; Filipino; Arab; Latin American; Southeast Asian; West Asian; Korean; Japanese; other racialized identity group; multiple racialized identity; racialized identity, but racialized identity group is unknown; rest of the population; unknown racialized identity group), gender (all genders; male; female; gender unknown) and region (Canada; Atlantic region; Quebec; Ontario; Prairies region; British Columbia; territories), 2019 to 2024.

This dataset includes the number and rate of firearm-related deaths among Virginia residents by patient health district and race/ethnicity over 5 combined years. Virginia Department of Health (VDH) health districts are assigned based on the residence of the patient at the time of death, not where the death occurred. Data include Virginia residents only, whether or not they died in Virginia. Data set includes deaths from 2018 through 2022.

The VDH Office of Vital Records tracks causes of death among Virginia residents using death certificates. Codes on the death certificate indicate underlying and contributing causes of death. Deaths are classified as firearm-related using the definition from the Centers for Disease Control and Prevention State Injury Indicators Report.

In 2023, the FBI reported that there were 9,284 Black murder victims in the United States and 7,289 white murder victims. In comparison, there were 554 murder victims of unknown race and 586 victims of another race. Victims of inequality? In recent years, the role of racial inequality in violent crimes such as robberies, assaults, and homicides has gained public attention. In particular, the issue of police brutality has led to increasing attention following the murder of George Floyd, an African American who was killed by a Minneapolis police officer. Studies show that the rate of fatal police shootings for Black Americans was more than double the rate reported of other races. Crime reporting National crime data in the United States is based off the Federal Bureau of Investigation’s new crime reporting system, which requires law enforcement agencies to self-report their data in detail. Due to the recent implementation of this system, less crime data has been reported, with some states such as Delaware and Pennsylvania declining to report any data to the FBI at all in the last few years, suggesting that the Bureau's data may not fully reflect accurate information on crime in the United States.

These data provide information on the number of arrests reported to the Federal Bureau of Investigation's (FBI) Uniform Crime Reporting (UCR) Program each month by police agencies in the United States. Although not as well known as the "Crimes Known to the Police" data drawn from the Uniform Crime Report's Return A form, the arrest reports by age, sex, and race provide valuable data on 44 offenses including violent, drug, gambling, and larceny crimes. The data received by ICPSR were structured as a hierarchical file containing (per reporting police agency) an agency header record, and 1 to 12 monthly header reports, and 1 to 43 detail offense records containing the counts of arrests by age, sex, and race for a particular offense. ICPSR restructured the original data to a rectangular format.

Between 1982 and August 2025, 84 out of the 155 mass shootings in the United States were carried out by white shooters. By comparison, the perpetrator was Black in 26 mass shootings and Latino in 12. When calculated as percentages, this amounts to 54 percent, 17 percent, and eight percent, respectively. Race of mass shooters reflects the U.S. population Broadly speaking, the racial distribution of mass shootings mirrors the racial distribution of the U.S. population as a whole. While a superficial comparison of the statistics seems to suggest African American shooters are over-represented and Latino shooters underrepresented, the fact that the shooter’s race is unclear in around nine percent of cases, along with the different time frames over which these statistics are calculated, means no such conclusions should be drawn. Conversely, looking at the mass shootings in the United States by gender clearly demonstrates that the majority of mass shootings are carried out by men. Mass shootings and mental health With no clear patterns between the socio-economic or cultural background of mass shooters, increasing attention has been placed on mental health. Analysis of the factors Americans considered to be to blame for mass shootings showed 80 percent of people felt the inability of the mental health system to recognize those who pose a danger to others was a significant factor. This concern is not without merit – in over half of the mass shootings since 1982, the shooter showed prior signs of mental health issues, suggesting improved mental health services may help deal with this horrific problem. Mass shootings and guns In the wake of multiple mass shootings, critics have sought to look beyond the issues of shooter identification and their influences by focusing on their access to guns. The majority of mass shootings in the U.S. involve firearms which were obtained legally, reflecting the easy ability of Americans to purchase and carry deadly weapons in public. Gun control takes on a particular significance when the uniquely American phenomenon of school shootings is considered. The annual number of incidents involving firearms at K-12 schools in the U.S. was over 100 in each year since 2018. Conversely, similar incidents in other developed countries exceptionally rare, with only five school shootings in G7 countries other than the U.S. between 2009 and 2018.

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.

Age-adjusted rate of deaths from firearms by sex, race/ethnicity, age; trends if available. Source: Santa Clara County Public Health Department, VRBIS, 2007-2016. Data as of 05/26/2017; U.S. Census Bureau; 2010 Census, Tables PCT12, PCT12H, PCT12I, PCT12J, PCT12K, PCT12L, PCT12M; generated by Baath M.; using American FactFinder; Accessed June 20, 2017. METADATA:Notes (String): Lists table title, notes and sourcesYear (String): Year of data; presented as single year or pooled years (2012-2016)Category (String): Lists the category representing the data: Santa Clara County is for total population, sex: Male and Female, race/ethnicity: African American, Asian/Pacific Islander, Latino and White (non-Hispanic White only); age categories as follows: <18, 18 to 44, 45 to 64, 65+; United States and Healthy People 2020 targetRate per 100,000 people (Numeric): Rate of deaths from firearms. Rates for age groups are reported as age-specific rates per 100,000 people. All other rates are age-adjusted rates per 100,000 people.

This statistic shows the number of gun deaths in the United States annually as an average from the years 2012 to 2014, by race. On average, there were ****** white victims of gun deaths compared to ***** black victims.

In 2023, 8,842 murderers in the United States were white, while 6,405 were Black. A further 461 murderers were of another race, including American Indian or Alaska Native, Asian, and Native Hawaiian or Other Pacific Islander. However, not all law enforcement agencies submitted homicide data to the FBI in 2023, meaning there may be more murder offenders of each race than depicted. While the majority of circumstances behind murders in the U.S. are unknown, narcotics, robberies, and gang killings are most commonly identified.

There was a large spike in gun purchases and gun violence during the first year of the COVID-19 pandemic in the United States. We used an online U.S. national survey (N = 1036) to examine the characteristics of people who purchased a gun between March 2020 and October 2021 (n = 103) and compared them to non-gun owners (n = 763) and people who own a gun but did not purchase a gun during the COVID-19 pandemic (n = 170). Compared to non-gun owners, pandemic gun buyers were younger and more likely to be male, White race, and to affiliate with the Republican party. Compared to non-gun owners and pre-pandemic gun owners, pandemic gun buyers exhibited extreme elevations on a constellation of political (QAnon beliefs, pro-gun attitudes, Christian Nationalism, approval of former President Donald Trump, anti-vax beliefs, COVID-19 skepticism; mean Cohen’s d = 1.15), behavioral (intimate partner violence, antisocial behavior; mean d = 1.38), mental health (suicidality, depression, anxiety, substance use; mean d = 1.21), and personality (desire for power, belief in a dangerous world, low agreeableness, low conscientiousness; mean d = 0.95) characteristics. In contrast, pre-pandemic gun owners only endorsed more pro-gun attitudes (d = 0.67), lower approval of President Joe Biden (d = -0.41) and were more likely to be male and affiliate with the Republican party relative to non-gun owners. Pandemic gun buyers represent an extreme group in terms of political and psychological characteristics including several risk-factors for violence and self-harm.

HAZUS is an abbreviation for Hazards United States, and was developed by FEMA. The HAZUS dataset was designed to estimate the potential physical, economic and social losses during hazardous events such as flooding or earthquakes. To measure the social impact of these events, HAZUS includes detailed demographic data for the United States. This dataset pulls out the racial data from the demographic files, at the census block level for the Washington portion of the Portland Metropolitan Statistic Area (MSA). Attributes include Whites, Blacks, Asians, Hispanics, Hawaiian and Pacific Islanders, Native Americans, and populations stating other race. Demographics data was recent as of May 2006.

This data explores the race/ethnicity of public agency children adopted for the fiscal year 2006 (from October 1,2005 to September 30, 2006) by state.

The Mortality Detail File: External Cause Extract is a special subset of data prepared from the MORTALITY DETAIL FILES, 1968-1991 (ICPSR 7632). Due to changes in Cause of Death definitions incorporated in the INTERNATIONAL CLASSIFICATION OF DISEASES, NINTH REVISION (ICD-9), the 1968-1978 data files differ slightly from the 1979-1980 data files. The 1968-1978 data reflect cause of death codes of the INTERNATIONAL CLASSIFICATION OF DISEASES ADAPTED FOR USE IN THE UNITED STATES, EIGHTH REVISION (ICDA-8). The period immediately following (1979-80) utilizes ICD-9 cause of death codes. In addition to the differences in the Cause of Death codes and recodes, the 1979-1980 data include three variables not available in the 1968-1978 datasets. These are: mortality by marital status, state or country of birth, and place of death and status of decedent when death occurred in a hospital or medical center. With these exceptions, the data are similar in structure and content to the 1968-1978 data and provide detailed personal and geographic information such as month and day of death, decedent's race and gender, age of deceased at time of death, place of decedent's residence (specific to the city level), place of death (specific to the county level), and whether an autopsy was performed. The 1979-1980 files also contain new variables pertinent to criminal justice research: handgun versus other gun accidents, handgun versus other firearm suicides, handgun versus other firearm homicides, and drug poison versus other poison homicides.

This dataset was retrieved from the U.S. Department of Justice Federal Bureau of Investigation Criminal Justice Information Services Division website on February 29, 2008. "This table provides the estimated number of offenses and the actual number of offenses reported in the Metropolitan Statistical Areas (MSA), cities outside metropolitan areas, and nonmetropolitan counties, and the rate (per 100,000 inhabitants) for each grouping, and the estimated population for each state" however to simplify the dataset, I only included the state total and the rate for each state. Data for Puerto Rico was not included. "The FBI collects these data through the Uniform Crime Reporting (UCR) Program". Please see the Data Declaration for further information on the data set. Values of -1 represent no value.

The study was a comprehensive analysis of felonious killings of officers. The purposes of the study were (1) to analyze the nature and circumstances of incidents of felonious police killings and (2) to analyze trends in the numbers and rates of killings across different types of agencies and to explain these differences. For Part 1, Incident-Level Data, an incident-level database was created to capture all incidents involving the death of a police officer from 1983 through 1992. Data on officers and incidents were collected from the Law Enforcement Officers Killed and Assaulted (LEOKA) data collection as coded by the Uniform Crime Reporting (UCR) program. In addition to the UCR data, the Police Foundation also coded information from the LEOKA narratives that are not part of the computerized LEOKA database from the FBI. For Part 2, Agency-Level Data, the researchers created an agency-level database to research systematic differences among rates at which law enforcement officers had been feloniously killed from 1977 through 1992. The investigators focused on the 56 largest law enforcement agencies because of the availability of data for explanatory variables. Variables in Part 1 include year of killing, involvement of other officers, if the officer was killed with his/her own weapon, circumstances of the killing, location of fatal wounds, distance between officer and offender, if the victim was wearing body armor, if different officers were killed in the same incident, if the officer was in uniform, actions of the killer and of the officer at entry and final stage, if the killer was visible at first, if the officer thought the killer was a felon suspect, if the officer was shot at entry, and circumstances at anticipation, entry, and final stages. Demographic variables for Part 1 include victim's sex, age, race, type of assignment, rank, years of experience, agency, population group, and if the officer was working a security job. Part 2 contains variables describing the general municipal environment, such as whether the agency is located in the South, level of poverty according to a poverty index, population density, percent of population that was Hispanic or Black, and population aged 15-34 years old. Variables capturing the crime environment include the violent crime rate, property crime rate, and a gun-related crime index. Lastly, variables on the environment of the police agencies include violent and property crime arrests per 1,000 sworn officers, percentage of officers injured in assaults, and number of sworn officers.