Serious violent crimes consist of Part 1 offenses as defined by the U.S. Department of Justice’s Uniform Reporting Statistics. These include murders, nonnegligent homicides, rapes (legacy and revised), robberies, and aggravated assaults. LAPD data were used for City of Los Angeles, LASD data were used for unincorporated areas and cities that contract with LASD for law enforcement services, and CA Attorney General data were used for all other cities with local police departments. This indicator is based on location of residence. 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.Neighborhood violence and crime can have a harmful impact on all members of a community. Living in communities with high rates of violence and crime not only exposes residents to a greater personal risk of injury or death, but it can also render individuals more susceptible to many adverse health outcomes. People who are regularly exposed to violence and crime are more likely to suffer from chronic stress, depression, anxiety, and other mental health conditions. They are also less likely to be able to use their parks and neighborhoods for recreation and physical activity.For more information about the Community Health Profiles Data Initiative, please see the initiative homepage.

These data are part of NACJD's Fast Track Release and are distributed as they were received from the data depositor. The files have been zipped by NACJD for release, but not checked or processed except for the removal of direct identifiers. Users should refer to the accompanying readme file for a brief description of the files available with this collection and consult the investigator(s) if further information is needed. The study integrated neighborhood-level data on robbery and burglary gathered from local police agencies across the United States, foreclosure data from RealtyTrac (a real estate information company), and a wide variety of social, economic, and demographic control variables from multiple sources. Using census tracts to approximate neighborhoods, the study regressed 2009 neighborhood robbery and burglary rates on foreclosure rates measured for 2007-2008 (a period during which foreclosure spiked dramatically in the nation), while accounting for 2007 robbery and burglary rates and other control variables that captured differences in social, economic, and demographic context across American neighborhoods and cities for this period. The analysis was based on more than 7,200 census tracts in over 60 large cities spread across 29 states. Core research questions were addressed with a series of multivariate multilevel and single-level regression models that accounted for the skewed nature of neighborhood crime patterns and the well-documented spatial dependence of crime. The study contains one data file with 8,198 cases and 99 variables.

The Part 1 crime rate captures incidents of homicide, rape, aggravated assault, robbery, burglary, larceny, and auto theft that are reported to the Police Department. These incidents are per 1,000 residents in the neighborhood to allow for comparison across areas. Source: Baltimore Police Department Years Available: 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023

This dataset reflects reported incidents of crime (with the exception of murders where data exists for each victim) that occurred in the City of Chicago from 2001 to present, minus the most recent seven days. Data is extracted from the Chicago Police Department's CLEAR (Citizen Law Enforcement Analysis and Reporting) system. In order to protect the privacy of crime victims, addresses are shown at the block level only and specific locations are not identified. Should you have questions about this dataset, you may contact the Research & Development Division of the Chicago Police Department at 312.745.6071 or RandD@chicagopolice.org. Disclaimer: These crimes may be based upon preliminary information supplied to the Police Department by the reporting parties that have not been verified. The preliminary crime classifications may be changed at a later date based upon additional investigation and there is always the possibility of mechanical or human error. Therefore, the Chicago Police Department does not guarantee (either expressed or implied) the accuracy, completeness, timeliness, or correct sequencing of the information and the information should not be used for comparison purposes over time. The Chicago Police Department will not be responsible for any error or omission, or for the use of, or the results obtained from the use of this information. All data visualizations on maps should be considered approximate and attempts to derive specific addresses are strictly prohibited. The Chicago Police Department is not responsible for the content of any off-site pages that are referenced by or that reference this web page other than an official City of Chicago or Chicago Police Department web page. The user specifically acknowledges that the Chicago Police Department is not responsible for any defamatory, offensive, misleading, or illegal conduct of other users, links, or third parties and that the risk of injury from the foregoing rests entirely with the user. The unauthorized use of the words "Chicago Police Department," "Chicago Police," or any colorable imitation of these words or the unauthorized use of the Chicago Police Department logo is unlawful. This web page does not, in any way, authorize such use. Data is updated daily Tuesday through Sunday. The dataset contains more than 65,000 records/rows of data and cannot be viewed in full in Microsoft Excel. Therefore, when downloading the file, select CSV from the Export menu. Open the file in an ASCII text editor, such as Wordpad, to view and search. To access a list of Chicago Police Department - Illinois Uniform Crime Reporting (IUCR) codes, go to http://data.cityofchicago.org/Public-Safety/Chicago-Police-Department-Illinois-Uniform-Crime-R/c7ck-438e

In 2023, the Balearic Islands region had the highest crime rate in Spain. Catalonia followed with a rate of 64.1 crimes per 1,000 inhabitants. Extremadura was the autonomous community with the lowest crime rate at 33.5.

This study explores the relationship between crime and neighborhood deterioration in eight neighborhoods in Chicago. The neighborhoods were selected on the basis of slowly or rapidly appreciating real estate values, stable or changing racial composition, and high or low crime rates. These data provide the results of a telephone survey administered to approximately 400 heads of households in each study neighborhood, a total of 3,310 completed interviews. The survey was designed to measure victimization experience, fear and perceptions of crime, protective measures taken, attitudes toward neighborhood quality and resources, attitudes toward the neighborhood as an investment, and density of community involvement. Each record includes appearance ratings for the block of the respondent's residence and aggregate figures on personal and property victimization for that city block. The aggregate appearance ratings were compiled from windshield surveys taken by trained personnel of the National Opinion Research Center. The criminal victimization figures came from Chicago City Police files.

Recorded crime figures for CSP areas. Number of offences for the last two years, percentage change, and rates per 1,000 population for the latest year.

The property crime rate measures the number of Part 1 crimes identified as being property-based (burglary and auto theft) that are reported to the Police Department. These incidents are per 1,000 residents in the neighborhood to allow for comparison across areas. Source: Baltimore Police DepartmentYears Available: 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023

The rate of people who considered their neighborhood unsafe in Guerrero increased by 1.3 thousand people per 100,000 inhabitants (+4.27 percent) in 2024. In total, the rate amounted to 31.74 thousand people per 100,000 inhabitants in 2024. For more insights about the rate of people who considered their neighborhood unsafe consider different countries: In 2024, in comparison to Guerrero, the rate in Querétaro as well as in Sonora was forecast to be higher.

Data is no longer provided by the Calgary Police Service. To access latest data click here. This data is considered cumulative as late-reported incidents are often received well after an offence has occurred. Therefore, crime counts are subject to change as they are updated. Crime count is based on the most serious violation (MSV) per incident. Violence: These figures include all violent crime offences as defined by the Centre for Canadian Justice Statistics Universal Crime Reporting (UCR) rules. Domestic violence is excluded. Break and Enter: Residential B&E includes both House and ‘Other’ structure break and enters due to the predominantly residential nature of this type of break in (e.g. detached garages, sheds). B&Es incidents include attempts.

The property crime rate measures the number of Part 1 crimes identified as being property-based (burglary and auto theft) that are reported to the Police Department. These incidents are per 1,000 residents in the neighborhood to allow for comparison across areas. Source: Baltimore Police Department Years Availabile: 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023

The rate of adults perceiving their neighborhood as unsafe per 100,000 inhabitants in Puebla was approximately ****** in 2024. Between 2011 and 2024, the rate rose by around *****, though the increase followed an uneven trajectory rather than a consistent upward trend.

The rate of adults perceiving their neighborhood as unsafe per 100,000 inhabitants in Yucatán was approximately ****** in 2024. Between 2011 and 2024, the rate rose by around *****, though the increase followed an uneven trajectory rather than a consistent upward trend.

These data were collected to examine the relationships among crime rates, residents' attitudes, physical deterioration, and neighborhood structure in selected urban Baltimore neighborhoods. The data collection provides both block- and individual-level neighborhood data for two time periods, 1981-1982 and 1994. The block-level files (Parts 1-6) include information about physical conditions, land use, people counts, and crime rates. Parts 1-3, the block assessment files, contain researchers' observations of street layout, traffic, housing type, and general upkeep of the neighborhoods. Part 1, Block Assessments, 1981 and 1994, contains the researchers' observations of sampled blocks in 1981, plus selected variables from Part 3 that correspond to items observed in 1981. Nonsampled blocks (in Part 2) are areas where block assessments were done, but no interviews were conducted. The "people counts" file (Part 4) is an actual count of people seen by the researchers on the sampled blocks in 1994. Variables for this file include the number, gender, and approximate age of the people seen and the types of activities they were engaged in during the assessment. Part 5, Land Use Inventory for Sampled Blocks, 1994, is composed of variables describing the types of buildings in the neighborhood and their physical condition. Part 6, Crime Rates and Census Data for All Baltimore Neighborhoods, 1970-1992, includes crime rates from the Baltimore Police Department for aggravated assault, burglary, homicide, larceny, auto theft, rape, and robbery for 1970-1992, and census information from the 1970, 1980, and 1990 United States Censuses on the composition of the housing units and the age, gender, race, education, employment, and income of residents. The individual-level files (Parts 7-9) contain data from interviews with neighborhood leaders, as well as telephone surveys of residents. Part 7, Interviews with Neighborhood Leaders, 1994, includes assessments of the level of involvement in the community by the organization to which the leader belongs and the types of activities sponsored by the organization. The 1982 and 1994 surveys of residents (Parts 8 and 9) asked respondents about different aspects of their neighborhoods, such as physical appearance, problems, and crime and safety issues, as well as the respondents' level of satisfaction with and involvement in their neighborhoods. Demographic information on respondents, such as household size, length of residence, marital status, income, gender, and race, is also provided in this file.

Crime rates for various neighborhoods in Atlanta, Georgia, highlighting areas with higher crime rates compared to the city average.

The Part 1 crime rate captures incidents of homicide, rape, aggravated assault, robbery, burglary, larceny, and auto theft that are reported to the Police Department. These incidents are per 1,000 residents in the neighborhood to allow for comparison across areas. Source: Baltimore City Police Department Years Available: 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022

In 2024, the rate of adults perceiving their neighborhood as unsafe per 100,000 inhabitants in Sinaloa was approximately ******. Between 2011 and 2024, the figure dropped by around ******, though the decline followed an uneven course rather than a steady trajectory.

This compilation includes five historical datasets that are part of the University of Pittsburgh Library collection. The datasets were transcribed from The Pittsburgh Neighborhood Atlas, published in 1977. The atlas was prepared by the Pittsburgh Neighborhood Alliance. The information provides an insight into the neighborhoods conditions and the direction in which they were moving at the time of preparation. Much of the material describing neighborhood characteristics came from figures compiled for smaller areas: voting districts or census blocks. The five datasets in this collection provide data about overall neighborhood satisfaction and satisfaction with public services, based on a city-wide citizen survey. Also included are statistics about public assistance, the crime rate and the changes in real estate and mortgage loans transactions.

The rate of people who considered their neighborhood unsafe in Mexico State increased by 2.6 thousand people per 100,000 inhabitants (+4.62 percent) compared to the previous year. In total, the rate amounted to 58.86 thousand people per 100,000 inhabitants in 2024. Over the observed period, the rate has been subject to fluctuation.For more insights about the rate of people who considered their neighborhood unsafe consider different countries: In 2024, in comparison to Mexico State, the rate in Yucatán was forecast to be lower and in Baja California Sur it was forecast to be considerably lower.

The rate of adults perceiving their neighborhood as unsafe per 100,000 inhabitants in Baja California stood at approximately ****** in 2024. Between 2011 and 2024, the rate rose by around ***, though the increase followed an uneven trajectory rather than a consistent upward trend.