As of 2022, Black people were more likely than those of other races to be imprisoned in the United States. In that year, the rate of imprisonment for Black men stood at 1,826 per 100,000 of the population. For Black women, this rate stood at 64 per 100,000 of the population.

In 2022, the incarceration rate of African Americans in local jails in the United States was 558 incarcerations per 100,000 of the population -- the highest rate of any race or ethnicity. The second-highest incarceration rate was among American Indians/Alaska Natives, at 391 incarcerations per 100,000 of the population.

The National Prisoner Statistics (NPS) data collection began in 1926 in response to a congressional mandate to gather information on persons incarcerated in state and federal prisons. Originally under the auspices of the United States Census Bureau, the collection moved to the Bureau of Prisons in 1950, and then in 1971 to the National Criminal Justice Information and Statistics Service, the precursor to the Bureau of Justice Statistics (BJS) which was established in 1979. Since 1979, the Census Bureau has been the NPS data collection agent. The NPS is administered to 51 respondents. Before 2001, the District of Columbia was also a respondent, but responsibility for housing the District of Columbia's sentenced prisoners was transferred to the federal Bureau of Prisons, and by yearend 2001 the District of Columbia no longer operated a prison system. The NPS provides an enumeration of persons in state and federal prisons and collects data on key characteristics of the nation's prison population. NPS has been adapted over time to keep pace with the changing information needs of the public, researchers, and federal, state, and local governments.

In 2022, about 1,826 Black men per 100,000 residents were imprisoned in the United States. This rate was much lower for Black women, at 64 per 100,000 residents. The overall imprisonment rate in 2022 stood at 355 per 100,000 Americans.

As of February 2025, El Salvador had the highest prisoner rate worldwide, with over 1,600 prisoners per 100,000 of the national population. Cuba, Rwanda, Turkmenistan, and the United States, rounded out the top five countries with the highest rate of incarceration. Homicides in El Salvador Interestingly, El Salvador, which long had the highest global homicide rates, has dropped out of the top 20 after a high number of gang members have been incarcerated. A high number of the countries with the highest homicide rate are located in Latin America. Prisoners in the United StatesThe United States is home to the largest number of prisoners worldwide. More than 1.8 million people were incarcerated in the U.S. at the beginning of 2025. In China, the estimated prison population totaled 1.69 million people that year. Other nations had far fewer prisoners. The largest share of the U.S. prisoners in federal correctional facilities were of African-American origin. As of 2020, there were 345,500 black, non-Hispanic prisoners, compared to 327,300 white, non-Hispanic inmates. The U.S. states with the largest number of prisoners in 2022 were Texas, California, and Florida. Over 160,000 prisoners in state facilities were sentenced for rape or sexual assault, which was the most common cause of imprisonment. The second most common was murder, followed by aggravated or simple assault.

The data contain records of sentenced offenders committed to the custody of the Bureau of Prisons (BOP) during fiscal year 2009. The data include commitments of United States District Court, violators of conditions of release (e.g., parole, probation, or supervised release violators), offenders convicted in other courts (e.g., military or District of Columbia courts), and persons admitted to prison as material witnesses or for purposes of treatment, examination, or transfer to another authority. These data include variables that describe the offender, such as age, race, citizenship, as well as variables that describe the sentences and expected prison terms. The data file contains original variables from the Bureau of Prisons' SENTRY database, as well as "SAF" variables that denote subsets of the data. These SAF variables are related to statistics reported in the Compendium of Federal Justice Statistics, Tables 7.9-7.16. Variables containing identifying information (e.g., name, Social Security Number) were replaced with blanks, and the day portions of date fields were also sanitized in order to protect the identities of individuals. These data are part of a series designed by the Urban Institute (Washington, DC) and the Bureau of Justice Statistics. Data and documentation were prepared by the Urban Institute.

Investigator(s): Bureau of Justice Statistics This series of studies contains a descriptive analysis of federal and state-operated adult confinement and correctional facilities nationwide. The census included prisons, penitentiaries, and correctional facilities; boot camps; community corrections; prison farms; reception, diagnostic, and classification centers; road camps; forestry and conservation camps; youthful offender facilities (except in California); vocational training facilities; prison hospitals; and correctional drug and alcohol treatment facilities. Variables include physical security, age of facilities, functions of facilities, programs, inmate work assignments, staff employment, facilities under court order/consent decree for conditions of confinement, capital and operating expenditures, custody level of residents/inmates, one-day and average daily population counts, race/ethnicity of inmates, inmate deaths, special inmate counts, and assaults and incidents by inmates. The institution is the unit of analysis. The Census of State and Federal Adult Correctional Facilities is produced every 5 years.

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.

This collection provides annual data on jail populations across the nation and examines the "spillover" effect on local jails resulting from the dramatic growth in federal and state prison populations. These data permit an assessment of the demands placed on correctional resources and provide a comprehensive picture of the adult correctional system and changes that occur within the system. Information is available on the number of inmates by sex, race, adult or juvenile status, reason being held, and cause of death. Facility characteristics were collected regarding capacity, court orders, conditions of confinement, and alternative programs.

The data contain records of sentenced offenders released from the custody of the Bureau of Prisons (BOP) during fiscal year 2003. The data include commitments of United States District Court, violators of conditions of release (e.g., parole, probation, or supervised release violators), offenders convicted in other courts (e.g., military or District of Columbia courts), and persons admitted to prison as material witnesses or for purposes of treatment, examination, or transfer to another authority. Records of offenders who exit federal prison temporarily, such as for transit to another location, to serve a weekend sentence, or for health care, are not included in the exiting cohort. These data include variables that describe the offender, such as age, race, citizenship, as well as variables that describe the sentences and expected prison terms. The data file contains original variables from the Bureau of Prisons' SENTRY database, as well as "SAF" variables that denote subsets of the data. These SAF variables are related to statistics reported in the Compendium of Federal Justice Statistics, Tables 7.9-7.16. Variables containing identifying information (e.g., name, Social Security Number) were replaced with blanks, and the day portions of date fields were also sanitized in order to protect the identities of individuals. These data are part of a series designed by the Urban Institute (Washington, DC) and the Bureau of Justice Statistics. Data and documentation were prepared by the Urban Institute.

In 2021, around 221,200 Black/African American people were confined to local jails in the United States. In that year, Black and African American people were confined to local jails at a higher rate than any other ethnicity.

The data contain records of sentenced offenders released from the custody of the Bureau of Prisons (BOP) during fiscal year 2012. The data include commitments of United States District Court, violators of conditions of release (e.g., parole, probation, or supervised release violators), offenders convicted in other courts (e.g., military or District of Columbia courts), and persons admitted to prison as material witnesses or for purposes of treatment, examination, or transfer to another authority. Records of offenders who exit federal prison temporarily, such as for transit to another location, to serve a weekend sentence, or for health care, are not included in the exiting cohort. These data include variables that describe the offender, such as age, race, citizenship, as well as variables that describe the sentences and expected prison terms. The data file contains original variables from the Bureau of Prisons' SENTRY database, as well as "SAF" variables that denote subsets of the data. These SAF variables are related to statistics reported in the Compendium of Federal Justice Statistics, Tables 7.9-7.16. Variables containing identifying information (e.g., name, Social Security Number) were replaced with blanks, and the day portions of date fields were also sanitized in order to protect the identities of individuals. These data are part of a series designed by the Urban Institute (Washington, DC) and the Bureau of Justice Statistics. Data and documentation were prepared by the Urban Institute.

This collection provides nationally representative data on persons held prior to trial and on convicted offenders serving sentences in local jails or awaiting transfer to state prisons. Data cover demographic characteristics of jail inmates (sex, race, ethnicity, Hispanic origin, employment), current offenses and sentences, detention status, trial, bail, characteristics of victims, criminal histories, incident characteristics, socioeconomic circumstances, jail conditions and activities, and prior drug and alcohol use and treatment. Part 1, Numeric Data, contains numeric data for all questions in the survey, while Part 2, Alphanumeric Data, consists of nonnumeric answers to the "Other, Specify" selection available for some of the questions.

This B.C. Corrections has ten adult custody centres. This extract provides the number of clients in custody in provincial custody centres on the first day of each month by centre, gender, ethnicity, marital status, age group, and month for the fiscal years 2008-09 to 2023-24. This data cannot be aggregated on a month by month bases; rather, it is a point in time snapshot giving a count of the provincial adult corrections population on the first of each month.

In 1980, the National Institute of Justice awarded a grant to the Cornell University College of Human Ecology for the establishment of the Center for the Study of Race, Crime, and Social Policy in Oakland, California. This center mounted a long-term research project that sought to explain the wide variation in crime statistics by race and ethnicity. Using information from eight ethnic communities in Oakland, California, representing working- and middle-class Black, White, Chinese, and Hispanic groups, as well as additional data from Oakland's justice systems and local organizations, the center conducted empirical research to describe the criminalization process and to explore the relationship between race and crime. The differences in observed patterns and levels of crime were analyzed in terms of: (1) the abilities of local ethnic communities to contribute to, resist, neutralize, or otherwise affect the criminalization of its members, (2) the impacts of criminal justice policies on ethnic communities and their members, and (3) the cumulative impacts of criminal justice agency decisions on the processing of individuals in the system. Administrative records data were gathered from two sources, the Alameda County Criminal Oriented Records Production System (CORPUS) (Part 1) and the Oakland District Attorney Legal Information System (DALITE) (Part 2). In addition to collecting administrative data, the researchers also surveyed residents (Part 3), police officers (Part 4), and public defenders and district attorneys (Part 5). The eight study areas included a middle- and low-income pair of census tracts for each of the four racial/ethnic groups: white, Black, Hispanic, and Asian. Part 1, Criminal Oriented Records Production System (CORPUS) Data, contains information on offenders' most serious felony and misdemeanor arrests, dispositions, offense codes, bail arrangements, fines, jail terms, and pleas for both current and prior arrests in Alameda County. Demographic variables include age, sex, race, and marital status. Variables in Part 2, District Attorney Legal Information System (DALITE) Data, include current and prior charges, days from offense to charge, disposition, and arrest, plea agreement conditions, final results from both municipal court and superior court, sentence outcomes, date and outcome of arraignment, disposition, and sentence, number and type of enhancements, numbers of convictions, mistrials, acquittals, insanity pleas, and dismissals, and factors that determined the prison term. For Part 3, Oakland Community Crime Survey Data, researchers interviewed 1,930 Oakland residents from eight communities. Information was gathered from community residents on the quality of schools, shopping, and transportation in their neighborhoods, the neighborhood's racial composition, neighborhood problems, such as noise, abandoned buildings, and drugs, level of crime in the neighborhood, chances of being victimized, how respondents would describe certain types of criminals in terms of age, race, education, and work history, community involvement, crime prevention measures, the performance of the police, judges, and attorneys, victimization experiences, and fear of certain types of crimes. Demographic variables include age, sex, race, and family status. For Part 4, Oakland Police Department Survey Data, Oakland County police officers were asked about why they joined the police force, how they perceived their role, aspects of a good and a bad police officer, why they believed crime was down, and how they would describe certain beats in terms of drug availability, crime rates, socioeconomic status, number of juveniles, potential for violence, residential versus commercial, and degree of danger. Officers were also asked about problems particular neighborhoods were experiencing, strategies for reducing crime, difficulties in doing police work well, and work conditions. Demographic variables include age, sex, race, marital status, level of education, and years on the force. In Part 5, Public Defender/District Attorney Survey Data, public defenders and district attorneys were queried regarding which offenses were increasing most rapidly in Oakland, and they were asked to rank certain offenses in terms of seriousness. Respondents were also asked about the public's influence on criminal justice agencies and on the performance of certain criminal justice agencies. Respondents were presented with a list of crimes and asked how typical these offenses were and what factors influenced their decisions about such cases (e.g., intent, motive, evidence, behavior, prior history, injury or loss, substance abuse, emotional trauma). Other variables measured how often and under what circumstances the public defender and client and the public defender and the district attorney agreed on the case, defendant characteristics in terms of who should not be put on the stand, the effects of Proposition 8, public defender and district attorney plea guidelines, attorney discretion, and advantageous and disadvantageous characteristics of a defendant. Demographic variables include age, sex, race, marital status, religion, years of experience, and area of responsibility.