Alaska saw the highest rape rate in the United States in 2023, with 118.4 rapes per 100,000 inhabitants. The lowest rate was found in New Jersey, with 17.9 rapes per 100,000 inhabitants. Sexual assault in Alaska Fighting sexual assault in Alaska is particularly difficult due to small, isolated, close-knit communities who can be wary of airing their dirty laundry to outsiders, as well as a low number of law enforcement employees in the state. In addition, Alaska’s low population is spread out over a large land area, meaning that in the event of an assault being reported to police, it can take law enforcement hours, or even days, to reach the most isolated communities. The victims of sexual assault There tends to be more reported female victims of sexual assault than male victims. However, since sexual assault is typically an underreported crime, especially among males, these figures could be, and probably are, much higher. In addition, many victims of sexual offenses tend to be young, although sexual assault can occur at any age.

In 2023, the rate of forcible rapes in the United States stood at 38 per 100,000 inhabitants. As the FBI revised the definition of rape in 2013, the 2023 rate is a slight decrease from 1990, when there were 41.2 forcible rapes per 100,000 inhabitants. What is forcible rape? According to the FBI, forcible rape is defined as “sexual penetration, no matter how slight, with a body part or object without the consent of the victim.” This definition changed in 2013 from the previous definition, which specified “carnal knowledge of a female victim forcibly and against her will.” Attempted rape was included in the previous definition, but statutory rape and other sexual offenses were excluded. The old definition was seen as problematic, as people of any gender can be raped. Since the revision of the definition of rape, reported rapes increased, although it is not clear if this is due to the revised definition or if the rate itself has increased. Rape in the United States While rape and sexual assault have been extensively talked about in the U.S. in recent years, especially since the start of the #metoo movement, there is still a large number of sexual offences committed each year. Sadly, the majority of sex offences in the U.S. are carried out against individuals age 20 and under. Astoundingly, the Anchorage, Alaska metropolitan area had the highest rape rate in the United States in 2023, followed by St Joseph in Missouri and Kansas. Since rape and sexual assault continue to be underreported in the United States, it is important to find a solution to this devastating problem.

In 2023, Texas had the highest number of forcible rape cases in the United States, with 15,097 reported rapes. Delaware had the lowest number of reported forcible rape cases at 194. Number vs. rate It is perhaps unsurprising that Texas and California reported the highest number of rapes, as these states have the highest population of states in the U.S. When looking at the rape rate, or the number of rapes per 100,000 of the population, a very different picture is painted: Alaska was the state with the highest rape rate in the country in 2023, with California ranking as 30th in the nation. The prevalence of rape Rape and sexual assault are notorious for being underreported crimes, which means that the prevalence of sex crimes is likely much higher than what is reported. Additionally, more than a third of women worry about being sexually assaulted, and most sexual assaults are perpetrated by someone the victim knew.

Despite the fact that most states enacted rape reform legislation by the mid-1980s, empirical research on the effect of these laws was conducted in only four states and for a limited time span following the reform. The purpose of this study was to provide both increased breadth and depth of information about the effect of the rape law changes and the legal issues that surround them. Statistical data on all rape cases between 1970 and 1985 in Atlanta, Chicago, Detroit, Houston, Philadelphia, and Washington, DC, were collected from court records. Monthly time-series analyses were used to assess the impact of the reforms on rape reporting, indictments, convictions, incarcerations, and sentences. The study also sought to determine if particular changes, or particular combinations of changes, affected the case processing and disposition of sexual assault cases and whether the effect of the reforms varied with the comprehensiveness of the changes. In each jurisdiction, data were collected on all forcible rape cases for which an indictment or information was filed. In addition to forcible rape, other felony sexual assaults that did not involve children were included. The names and definitions of these crimes varied from jurisdiction to jurisdiction. To compare the pattern of rape reports with general crime trends, reports of robbery and felony assaults during the same general time period were also obtained from the Uniform Crime Reports (UCR) from the Federal Bureau of Investigation when available. For the adjudicated case data (Parts 1, 3, 5, 7, 9, and 11), variables include month and year of offense, indictment, disposition, four most serious offenses charged, total number of charges indicted, four most serious conviction charges, total number of conviction charges, type of disposition, type of sentence, and maximum jail or prison sentence. The time series data (Parts 2, 4, 6, 8, 10, and 12) provide year and month of indictment, total indictments for rape only and for all sex offenses, total convictions and incarcerations for all rape cases in the month, for those on the original rape charge, for all sex offenses in the month, and for those on the original sex offense charge, percents for each indictment, conviction, and incarceration category, the average maximum sentence for each incarceration category, and total police reports of forcible rape in the month. Interviews were also conducted in each site with judges, prosecutors, and defense attorneys, and this information is presented in Part 13. These interviewees were asked to rate the importance of various types of evidence in sexual assault cases and to respond to a series of six hypothetical cases in which evidence of the victim's past sexual history was at issue. Respondents were also presented with a hypothetical case for which some factors were varied to create 12 different scenarios, and they were asked to make a set of judgments about each. Interview data also include respondent's title, sex, race, age, number of years in office, and whether the respondent was in office before and/or after the reform.

The National Crime Victimization Survey (NCVS), previously called the National Crime Survey (NCS), has been collecting data on personal and household victimization through an ongoing survey of a nationally-representative sample of residential addresses since 1973. The NCVS was designed with four primary objectives: (1) to develop detailed information about the victims and consequences of crime, (2) to estimate the number and types of crimes not reported to the police, (3) to provide uniform measures of selected types of crimes, and (4) to permit comparisons over time and types of areas. Beginning in 1992, the survey categorizes crimes as "personal" or "property." Personal crimes include rape and sexual assault, robbery, aggravated and simple assault, and purse-snatching/pocket-picking, while property crimes include burglary, theft, motor vehicle theft, and vandalism. Each respondent is asked a series of screen questions designed to determine whether she or he was victimized during the six-month period preceding the first day of the month of the interview. A "household respondent" is also asked to report on crimes against the household as a whole (e.g., burglary, motor vehicle theft). The data include type of crime, month, time, and location of the crime, relationship between victim and offender, characteristics of the offender, self-protective actions taken by the victim during the incident and results of those actions, consequences of the victimization, type of property lost, whether the crime was reported to police and reasons for reporting or not reporting, and offender use of weapons, drugs, and alcohol. Basic demographic information such as age, race, gender, and income is also collected, to enable analysis of crime by various subpopulations. This dataset represents the concatenated version of the NCVS on a collection year basis for 1992-2023. A collection year contains records from interviews conducted in the 12 months of the given year. Under the collection year format, victimizations are counted in the year the interview is conducted, regardless of the year when the crime incident occurred.For additional information on the dataset, please see the documentation for the data from the most current year of the NCVS, ICPSR Study 38962.

The following datasets contain the crime rate for cities in the United States. The four datasets are separated based on population ranges.

FILE DESCRIPTION

File names: - 'crime_40 _60.csv': dataset for population ranging from 40,000 to 60,000. - 'crime_60 _100.csv': dataset for population ranging from 60,000 to 100,000. - 'crime_100 _250.csv': dataset for population ranging from 100,000 to 250,000. - 'crime_250 _plus.csv': dataset for population greater than 250,000.

COLUMN DESCRIPTION

For file: crime_40 _60.csv: - 'states': name of the state - 'cities': name of the city - 'population': population of the city - 'violent_crime': violent crime - 'murder': murder and nonnegligent manslaughter - 'rape': forcible rape - 'robbery': robbery - 'agrv_ The following datasets contain the crime rate for cities in the United States. The four datasets are separated based on population ranges.

FILE DESCRIPTION

File names: - 'crime_40 _60.csv': dataset for population ranging from 40,000 to 60,000. - 'crime_60 _100.csv': dataset for population ranging from 60,000 to 100,000. - 'crime_100 _250.csv': dataset for population ranging from 100,000 to 250,000. - 'crime_250 _plus.csv': dataset for population greater than 250,000.

COLUMN DESCRIPTION

For file: crime_40 _60.csv: - 'states': name of the state - 'cities': name of the city - 'population': population of the city - 'violent_crime': violent crime - 'murder': murder and nonnegligent manslaughter - 'rape': forcible rape - 'robbery': robbery - 'agrv_ assault': agrv_ assault - 'prop_crime': property crime - 'burglary': burglary - 'larceny': larceny theft - 'vehicle_theft': motor vehicle theft

crime_60 _100.csv: - 'states': name of the state - 'cities': name of the city - 'population': population of the city - 'violent_crime': violent crime - 'murder': murder and nonnegligent manslaughter - 'rape': forcible rape - 'robbery': robbery - 'agrv_ assault': agrv_ assault - 'prop_crime': property crime - 'burglary': burglary - 'larceny': larceny theft - 'vehicle_theft': motor vehicle theft

crime_100 _250.csv: - 'states': name of the state - 'cities': name of the city - 'population': population of the city - 'violent_crime': violent crime - 'murder': murder and nonnegligent manslaughter - 'rape': forcible rape - 'robbery': robbery - 'agrv_ assault': agrv_ assault - 'prop_crime': property crime - 'burglary': burglary - 'larceny': larceny theft - 'vehicle_theft': motor vehicle theft

crime_250 _plus.csv: - 'states': name of the state - 'cities': name of the city - 'population': population of the city - 'total_crime': total crime - 'murder': murder and nonnegligent manslaughter - 'rape': forcible rape - 'robbery': robbery - 'agrv_ assault': agrv_ assault - 'total_violent _crime': total violent crime - 'prop_crime': property crime - 'burglary': burglary - 'larceny': larceny theft - 'vehicle_theft': motor vehicle theft - 'tot_prop _crime': total property crime - 'arson': arson

Photo by David von Diemar on Unsplash

In 2023, Anchorage, Alaska had the highest rape rate in the United States with 144.6 offenses of rape per 100,000 inhabitants. The St. Joseph metropolitan statistical area, in Missouri and Kansas, had the second-highest rape rate in the country, at 141.4 offenses per 100,000 of the population.

In response to a growing concern about hate crimes, the United States Congress enacted the Hate Crime Statistics Act of 1990. The Act requires the attorney general to establish guidelines and collect, as part of the Uniform Crime Reporting (UCR) Program, data "about crimes that manifest evidence of prejudice based on race, religion, sexual orientation, or ethnicity, including where appropriate the crimes of murder and non-negligent manslaughter, forcible rape, aggravated assault, simple assault, intimidation, arson, and destruction, damage or vandalism of property." Hate crime data collection was required by the Act to begin in calendar year 1990 and to continue for four successive years. In September 1994, the Violent Crime Control and Law Enforcement Act amended the Hate Crime Statistics Act to add disabilities, both physical and mental, as factors that could be considered a basis for hate crimes. Although the Act originally mandated data collection for five years, the Church Arson Prevention Act of 1996 amended the collection duration "for each calendar year," making hate crime statistics a permanent addition to the UCR program. As with the other UCR data, law enforcement agencies contribute reports either directly or through their state reporting programs. Information contained in the data includes number of victims and offenders involved in each hate crime incident, type of victims, bias motivation, offense type, and location type.

This study examined the results of new DNA testing of old physical evidence from 634 sexual assault and homicide cases resulting in 715 convictions that took place in Virginia between 1973 and 1988. The research team conducted a retrospective study using data collected from the Virginia Department of Forensic Science files, visits to three Virginia county courthouses, and the COUNTY STATISTICS FILE 1 (CO-STAT): UNITED STATES to estimate the rate at which defendants are wrongly convicted and to identify case attributes associated with such wrongful convictions.

In the United States, significantly more women than men are sexually assaulted. In 2023, about ******* women were raped or sexually assaulted in the U.S. - a decrease from the previous year. In comparison, ******* men were raped or sexually assaulted in 2023, which was an increase compared to the year before.

Context

The Uniform Crime Reporting (UCR) Program has been the starting place for law enforcement executives, students of criminal justice, researchers, members of the media, and the public at large seeking information on crime in the nation. The program was conceived in 1929 by the International Association of Chiefs of Police to meet the need for reliable uniform crime statistics for the nation. In 1930, the FBI was tasked with collecting, publishing, and archiving those statistics.

Today, four annual publications, Crime in the United States, National Incident-Based Reporting System, Law Enforcement Officers Killed and Assaulted, and Hate Crime Statistics are produced from data received from over 18,000 city, university/college, county, state, tribal, and federal law enforcement agencies voluntarily participating in the program. The crime data are submitted either through a state UCR Program or directly to the FBI’s UCR Program.

This dataset focuses on the crime rates and law enforcement employment data in the state of California.

Content

Crime and law enforcement employment rates are separated into individual files, focusing on offenses by enforcement agency, college/university campus, county, and city. Categories of crimes reported include violent crime, murder and nonnegligent manslaughter, rape, robbery, aggravated assault, property crime, burglary, larceny-theft, motor vehicle damage, and arson. In the case of rape, data is collected for both revised and legacy definitions. In some cases, a small number of enforcement agencies switched definition collection sometime within the same year.

Acknowledgements

This dataset originates from the FBI UCR project, and the complete dataset for all 2015 crime reports can be found here.

Inspiration

• What are the most common types of crimes in California? Are there certain crimes that are more common in a particular place category, such as a college/university campus, compared to the rest of the state?
• How does the number of law enforcement officers compare to the crime rates of a particular area? Is the ratio similar throughout the state, or do certain campuses, counties, or cities have a differing rate?
• How does the legacy vs. refined definition of rape differ, and how do the rape counts compare? If you pulled the same data from FBI datasets for previous years, can you see a difference in rape rates over time?

In 2023, there were 127,216 reported rape cases in the United States. This figure also includes attempts and assaults to commit rape, but unforced statutory rape and other sex offenses are excluded. Sexual assault in the U.S. What is particularly common when it comes to sexual assault, is that many victims know their assailant. A rapist being a stranger lurking in the shadows is less likely than people may like to think. Additionally, most cases of rape or sexual assault in the United States often report the fact that the assailant did not have a weapon on them. These are frightening thoughts for anyone, which has led the U.S. to take a deeper look at what exactly is happening.

metoo

Sexual assault, in any form, has been a long simmering problem in the U.S.; one which has only recently begun to be addressed in the public spotlight. The #metoo movement began to go viral in October 2017 in response to sexual assault allegations against movie producer Harvey Weinstein. The movement aims to show just how widespread sexual assault is, and over half of Americans support the movement.

Context

Violent Crime Rates by US State

Content

This data set contains statistics, in arrests per 100,000 residents for assault, murder, and rape in each of the 50 US states in 1973. Also given is the percent of the population living in urban areas.

A data frame with 50 observations on 4 variables.

Murder is numeric and Murder arrests (per 100,000) Assault is numeric and Assault arrests (per 100,000) UrbanPop is numeric and UrbanPop arrests (per 100,000) Rape is numeric and Rape arrests (per 100,000)

Source

World Almanac and Book of facts 1975. (Crime rates).

Statistical Abstracts of the United States 1975. (Urban rates).

References

McNeil, D. R. (1977) Interactive Data Analysis. New York: Wiley.

This project sought to investigate a possible relationship between sentencing guidelines and family structure in the United States. The research team developed three research modules that employed a variety of data sources and approaches to understand family destabilization and community distress, which cannot be observed directly. These three research modules were used to discover causal relationships between male withdrawal from productive spheres of the economy and resulting changes in the community and families. The research modules approached the issue of sentencing guidelines and family structure by studying: (1) the flow of inmates into prison (Module A), (2) the role of and issues related to sentencing reform (Module B), and family disruption in a single state (Module C). Module A utilized the Uniform Crime Reporting (UCR) Program data for 1984 and 1993 (Parts 1 and 2), the 1984 and 1993 National Correctional Reporting Program (NCRP) data (Parts 3-6), the Urban Institute's 1980 and 1990 Underclass Database (UDB) (Part 7), the 1985 and 1994 National Longitudinal Survey on Youth (NLSY) (Parts 8 and 9), and county population, social, and economic data from the Current Population Survey, County Business Patterns, and United States Vital Statistics (Parts 10-12). The focus of this module was the relationship between family instability, as measured by female-headed families, and three societal characteristics, namely underclass measures in county of residence, individual characteristics, and flows of inmates. Module B examined the effects of statewide incarceration and sentencing changes on marriage markets and family structure. Module B utilized data from the Current Population Survey for 1985 and 1994 (Part 12) and the United States Statistical Abstracts (Part 13), as well as state-level data (Parts 14 and 15) to measure the Darity-Myers sex ratio and expected welfare income. The relationship between these two factors and family structure, sentencing guidelines, and minimum sentences for drug-related crimes was then measured. Module C used data collected from inmates entering the Minnesota prison system in 1997 and 1998 (Part 16), information from the 1990 Census (Part 17), and the Minnesota Crime Survey (Part 18) to assess any connections between incarceration and family structure. Module C focused on a single state with sentencing guidelines with the goal of understanding how sentencing reforms and the impacts of the local community factors affect inmate family structure. The researchers wanted to know if the aspects of locations that lose marriageable males to prison were more important than individual inmate characteristics with respect to the probability that someone will be imprisoned and leave behind dependent children. Variables in Parts 1 and 2 document arrests by race for arson, assault, auto theft, burglary, drugs, homicide, larceny, manslaughter, rape, robbery, sexual assault, and weapons. Variables in Parts 3 and 4 document prison admissions, while variables in Parts 5 and 6 document prison releases. Variables in Part 7 include the number of households on public assistance, education and income levels of residents by race, labor force participation by race, unemployment by race, percentage of population of different races, poverty rate by race, men in the military by race, and marriage pool by race. Variables in Parts 8 and 9 include age, county, education, employment status, family income, marital status, race, residence type, sex, and state. Part 10 provides county population data. Part 11 contains two different state identifiers. Variables in Part 12 describe mortality data and welfare data. Part 13 contains data from the United States Statistical Abstracts, including welfare and poverty variables. Variables in Parts 14 and 15 include number of children, age, education, family type, gender, head of household, marital status, race, religion, and state. Variables in Part 16 cover admission date, admission type, age, county, education, language, length of sentence, marital status, military status, sentence, sex, state, and ZIP code. Part 17 contains demographic data by Minnesota ZIP code, such as age categories, race, divorces, number of children, home ownership, and unemployment. Part 18 includes Minnesota crime data as well as some demographic variables, such as race, education, and poverty ratio.

The National Crime Victimization Survey (NCVS), previously called the National Crime Survey (NCS), has been collecting data on personal and household victimization through an ongoing survey of a nationally-representative sample of residential addresses since 1973. The NCVS was designed with four primary objectives: (1) to develop detailed information about the victims and consequences of crime, (2) to estimate the number and types of crimes not reported to the police, (3) to provide uniform measures of selected types of crimes, and (4) to permit comparisons over time and types of areas. Beginning in 1992, the survey categorizes crimes as "personal" or "property." Personal crimes include rape and sexual assault, robbery, aggravated and simple assault, and purse-snatching/pocket-picking, while property crimes include burglary, theft, motor vehicle theft, and vandalism. Each respondent is asked a series of screen questions designed to determine whether she or he was victimized during the six-month period preceding the first day of the month of the interview. A "household respondent" is also asked to report on crimes against the household as a whole (e.g., burglary, motor vehicle theft). The data include type of crime, month, time, and location of the crime, relationship between victim and offender, characteristics of the offender, self-protective actions taken by the victim during the incident and results of those actions, consequences of the victimization, type of property lost, whether the crime was reported to police and reasons for reporting or not reporting, and offender use of weapons, drugs, and alcohol. Basic demographic information such as age, race, gender, and income is also collected, to enable analysis of crime by various subpopulations. This dataset represents the concatenated version of the NCVS on a collection year basis for 1992-2018. A collection year contains records from interviews conducted in the 12 months of the given year. Under the collection year format, victimizations are counted in the year the interview is conducted, regardless of the year when the crime incident occurred. For additional information on the dataset, please see the documentation for the data from the most current year of the NCVS, ICPSR Study 37297.

These data provide information on the number of arrests reported to the Federal Bureau of Investigation's Uniform Crime Reporting (UCR) Program each year by police agencies in the United States. These arrest reports provide data on 43 offenses including violent crime, drug use, gambling, and larceny. The data received by ICPSR were structured as a hierarchical file containing (per reporting police agency) an agency header record, 1 to 12 monthly header records, 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.

Source:

Creator: Michael Redmond (redmond '@' lasalle.edu); Computer Science; La Salle University; Philadelphia, PA, 19141, USA -- culled from 1990 US Census, 1995 US FBI Uniform Crime Report, 1990 US Law Enforcement Management and Administrative Statistics Survey, available from ICPSR at U of Michigan. -- Donor: Michael Redmond (redmond '@' lasalle.edu); Computer Science; La Salle University; Philadelphia, PA, 19141, USA -- Date: July 2009

Data Set Information:

Many variables are included so that algorithms that select or learn weights for attributes could be tested. However, clearly unrelated attributes were not included; attributes were picked if there was any plausible connection to crime (N=122), plus the attribute to be predicted (Per Capita Violent Crimes). The variables included in the dataset involve the community, such as the percent of the population considered urban, and the median family income, and involving law enforcement, such as per capita number of police officers, and percent of officers assigned to drug units.

The per capita violent crimes variable was calculated using population and the sum of crime variables considered violent crimes in the United States: murder, rape, robbery, and assault. There was apparently some controversy in some states concerning the counting of rapes. These resulted in missing values for rape, which resulted in incorrect values for per capita violent crime. These cities are not included in the dataset. Many of these omitted communities were from the midwestern USA.

Data is described below based on original values. All numeric data was normalized into the decimal range 0.00-1.00 using an Unsupervised, equal-interval binning method. Attributes retain their distribution and skew (hence for example the population attribute has a mean value of 0.06 because most communities are small). E.g. An attribute described as 'mean people per household' is actually the normalized (0-1) version of that value.

The normalization preserves rough ratios of values WITHIN an attribute (e.g. double the value for double the population within the available precision - except for extreme values (all values more than 3 SD above the mean are normalized to 1.00; all values more than 3 SD below the mean are normalized to 0.00)).

However, the normalization does not preserve relationships between values BETWEEN attributes (e.g. it would not be meaningful to compare the value for whitePerCap with the value for blackPerCap for a community)

A limitation was that the LEMAS survey was of the police departments with at least 100 officers, plus a random sample of smaller departments. For our purposes, communities not found in both census and crime datasets were omitted. Many communities are missing LEMAS data.

Attribute Information:

'(125 predictive, 4 non-predictive, 18 potential goal) ', ' communityname: Community name - not predictive - for information only (string) ', ' state: US state (by 2 letter postal abbreviation)(nominal) ', ' countyCode: numeric code for county - not predictive, and many missing values (numeric) ', ' communityCode: numeric code for community - not predictive and many missing values (numeric) ', ' fold: fold number for non-random 10 fold cross validation, potentially useful for debugging, paired tests - not predictive (numeric - integer) ', ' population: population for community: (numeric - expected to be integer) ', ' householdsize: mean people per household (numeric - decimal) ', ' racepctblack: percentage of population that is african american (numeric - decimal) ', ' racePctWhite: percentage of population that is caucasian (numeric - decimal) ', ' racePctAsian: percentage of population that is of asian heritage (numeric - decimal) ', ' racePctHisp: percentage of population that is of hispanic heritage (numeric - decimal) ', ' agePct12t21: percentage of population that is 12-21 in age (numeric - decimal) ', ' agePct12t29: percentage of population that is 12-29 in age (numeric - decimal) ', ' agePct16t24: percentage of population that is 16-24 in age (numeric - decimal) ', ' agePct65up: percentage of population that is 65 and over in age (numeric - decimal) ', ' numbUrban: number of people living in areas classified as urban (numeric - expected to be integer) ', ' pctUrban: percentage of people living in areas classified as urban (numeric - decimal) ', ' medIncome: median household income (numeric - may be integer) ', ' pctWWage: percentage of households with wage or salary income in 1989 (numeric - decimal) ', ' pctWFarmSelf: percentage of households with farm or self employment income in 1989 (numeric - decimal) ', ' pctWInvInc: percentage of households with investment / rent income in 1989 (numeric - decimal) ', ' pctWSocSec: percentage of households with social security income in 1989 (numeric - decimal) ', ' pctWPubAsst: pe...

In 2022, the rate of violent crime victimization was **** per 1,000 persons in the United States. Among the types of violent crime, this figure was highest for simple assault, at **** cases per 1,000 persons. For rape and sexual assault, this rate stood at *** cases per 1,000 persons in that year.

In 2022, there were slightly more female victims of violent crime than male victims in the United States, with about ********* male victims and ********* female victims. These figures are a significant increase from the previous year, when there were ********* male victims and ********* female victims. What counts as violent crime? Violent crime in the United States includes murder, rape, sexual assault, robbery, and assault. While violent crime across all areas has been steadily falling over the past few decades, the rate of aggravated assault is still relatively high, at ***** cases per 100,000 of the population. In 2021, there were more property crimes committed in the U.S. than there were violent crimes. Keep your enemies closer It is usually said that most victims know their attacker, and the data backs this up. In 2021, very few murders were committed by strangers. The same goes for rape and sexual assault victims; the majority were perpetrated by acquaintances, intimate partners, or relatives.

In 2023, a total of ****** victims of rape or sexual assault in the United States stated that there was a firearm present during the crime. For ******* victims, there was no weapon present during the crime.