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.

Comprehensive crime statistics for Los Angeles County including homicides, property crime, robbery, assault, and neighborhood-by-neighborhood breakdowns with five-year trend analysis.

There has been little research on United States homicide rates from a long-term perspective, primarily because there has been no consistent data series on a particular place preceding the Uniform Crime Reports (UCR), which began its first full year in 1931. To fill this research gap, this project created a data series that spans two centuries on homicides per capita for the city of Los Angeles. The goal was to create a site-specific, individual-based data series that could be used to examine major social shifts related to homicide, such as mass immigration, urban growth, war, demographic changes, and changes in laws. The basic approach to the data collection was to obtain the best possible estimate of annual counts and the most complete information on individual homicides. Data were derived from multiple sources, including Los Angeles court records, as well as annual reports of the coroner and daily newspapers. Part 1 (Annual Homicides and Related Data) variables include Los Angeles County annual counts of homicides, counts of female victims, method of killing such as drowning, suffocating, or strangling, and the homicide rate. Part 2 (Individual Homicide Data) variables include the date and place of the murder, the age, sex, race, and place of birth of the offender and victim, type of weapon used, and source of data.

In a world of increasing crime, many organizations are interested in examining incident details to learn from and prevent future crime. Our client, based in Los Angeles County, was interested in this exact thing. They asked us to examine the data to answer several questions; among them, what was the rate of increase or decrease in crime from 2020 to 2023, and which ethnicity or group of people were targeted the most.

Our data was collected from Kaggle.com at the following link:

https://www.kaggle.com/datasets/nathaniellybrand/los-angeles-crime-dataset-2020-present

It was cleaned, examined for further errors, and the analysis performed using RStudio. The results of this analysis are in the attached PDF entitled: "crime_data_analysis_report." Please feel free to review the results as well as follow along with the dataset on your own machine.

This indicator is based on location of residence. Mortality rate has been age-adjusted to the 2000 U.S. standard population. ICD 10 codes used to identify homicides are X85-Y09, Y87.1, and U01-U02. 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. Almost three quarters of homicides involve firearms. 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. Comprehensive prevention strategies should work to address the 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.

Comprehensive crime statistics for Los Angeles County's safest neighborhoods including violent crime rates, property crime rates, and annual victimization chances by neighborhood for 2024-2025.

Comprehensive crime statistics for Los Angeles County's most dangerous neighborhoods including violent crime rates, property crime rates, gang activity, and annual victimization chances by neighborhood for 2024-2025.

The purpose of this data collection was to investigate the effects of crime rates, city characteristics, and police departments' financial resources on felony case attrition rates in 28 cities located in Los Angeles County, California. Demographic data for this collection were obtained from the 1983 COUNTY AND CITY DATA BOOK. Arrest data were collected directly from the 1980 and 1981 CALIFORNIA OFFENDER BASED TRANSACTION STATISTICS (OBTS) data files maintained by the California Bureau of Criminal Statistics. City demographic variables include total population, minority population, population aged 65 years or older, number of female-headed families, number of index crimes, number of families below the poverty level, city expenditures, and police expenditures. City arrest data include information on number of arrests disposed and number of males, females, blacks, and whites arrested. Also included are data on the number of cases released by police, denied by prosecutors, and acquitted, and data on the number of convicted cases given prison terms.

Los Angeles County is a premier government agency responsible for providing a range of services to its residents. From law enforcement and healthcare to public works and social services, the organization is committed to supporting the diverse needs of its population.

One of the primary goals of Los Angeles County is to maintain transparency and accessibility in its operations. This is reflected in the vast amounts of data it provides online, including metrics and statistics on topics such as crime rates, health outcomes, and infrastructure development. By making this information publicly available, the agency hopes to foster greater understanding and engagement between government and community.

This study was conducted in 1979 at the Social Science Research Institute, University of Southern California, and explores the relationship between neighborhood change and crime rates between the years 1950 and 1976. The data were aggregated by unique and consistently-defined spatial areas, referred to as dummy tracts or neighborhoods, within Los Angeles County. By combining United States Census data and administrative data from several state, county, and local agencies, the researchers were able to develop measures that tapped the changing structural and compositional aspects of each neighborhood and their interaction with the patterns of juvenile delinquency. Some of the variables included are annual income, home environment, number of crimes against persons, and number of property crimes.

The objective of this study was to examine the observable offending patterns of recent and past drug offenders to assess the crime control potential associated with recent increases in the incarceration of drug offenders. The periods examined were 1986 (representing the second half of the 1980s, when dramatic shifts toward increasing incarceration of drug offenders first became evident), and 1990 (after escalating sentences were well under way). Convicted offenders were the focus, since these cases are most directly affected by changes in imprisonment policies, particularly provisions for mandatory prison terms. Offending patterns of convicted and imprisoned drug offenders were contrasted to patterns of convicted robbers and burglars, both in and out of prison. The researchers used data from the National Judicial Reporting Program (NJRP), sponsored by the U.S. Department of Justice, Bureau of Justice Statistics (BJS), for information on the court processing of individual felony convictions. The National Association of Criminal Justice Planners (NACJP), which maintains data for the approximately 50 counties included in the NJRP, was contracted to determine the counties to be sampled (Los Angeles County and Maricopa County in Arizona were chosen) and to provide individual criminal histories. Variables include number of arrests for robbery, violent crimes, property crimes, and other felonies, number of drug arrests, number of misdemeanor arrests, rate of violent, property, robbery, weapons, other felony, drug, and misdemeanor arrests, offense type (drug trafficking, drug possession, robbery, and burglary), total number of incarcerations, total number of convictions, whether sentenced to prison, jail, or probation, incarceration sentence in months, sex, race, and age at sampled conviction, and age at first arrest (starting at age 17).

The Justice Equity Need Index (JENI), by Advancement Project California, offers a means to map out the disparate burden that criminalization and a detention-first justice model place on specific communities. The index includes the following indicators:System Involvement: The system-involved population by ZIP Code results in direct needs for justice equity, as measured by adult and youth probation. Indicators: Adult Probation (per 1,000 people); Youth Probation (per 1,000 people) Inequity Drivers: Root inequities across communities that contribute to racial and economic disparities as seen in incarceration and policing. Indicators: Black, Latinx, AIAN, and NHPI Percentages of Population (average percentile); Unemployment Rate (%); Population aged 25+ without a High School Diploma (%); Population below 200% of the Federal Poverty Level (%); Violent Crime Rate (per 1,000 people) Criminalization Risk: Conditions where the criminal justice system has historically taken a detention-first, prevention-last approach. Indicators: Mental Health Hospitalizations (per 1,000 people); Substance Use-Related Hospitalizations (per 1,000 people); Homelessness Rate (per 1,000 people) Learn more at https://www.catalystcalifornia.org/campaign-tools/maps-and-data/justice-equity-need-index.Supervisorial Districts, SPAs, and CSAs determined by ZIP Code centroid.

The poly shapefile is based on HRSA of DHHS data from 2008. It shows the lower 48 state counties which have parts/areas that are medically underserved. The original data is by such parts/areas within each county. However,since there is no geographic boundary file for such areas, the such areas were combined and the data was aggreageted/averaged to create a county level boundary file. The counties with the most number of medically uderserved areas are: 1. Los Angeles, CA (705 medically underseved areas) 2. Cook County, IL (435 medically underserved ares) 3. Kings County, NY (319 medically underserved areas) 4. Wayne County, MI (292 medically underserved areas) 5. Harris County, TX (244 medically underserved areas)

The poly shapefile is based on Census data that compares Census 2000 population levels to estimates in July, 2006 for all the counties that are designated by NOAA (see the URL below) as "Coastal Region Counties". There are 645 jurisdictions, whose combined population in was over 146.6 million (Year 2000) and estimated to be 154.3 million in 2006. In both years, the largest and the smallest counties were Los Angeles, CA and Kenedy, TX. Flagler, FL registered the largest percent change (66.7%) and St. Bernard, LA registered the highest percent decrease (-76.9%). The later is direct result of the 2005 Katrina disaster. http://www.census.gov/geo/landview/lv6help/coastal_cty.pdf

The Children’s Bureau in the Administration for Children and Families contracted with the Urban Institute and its partners—the Chapin Hall Center for Children at the University of Chicago and the National Opinion Research Center—to conduct an evaluation of selected programs funded through John Chafee Foster Care Independence Program (CFCIP). This evaluation, using a rigorous, random assignment design, was called for in the Foster Care Independence Act of 1999. The goal of the evaluation is to determine the effects of Independent Living Programs funded under CFCIP in achieving key outcomes for participating youth including increased educational attainment, higher employment rates and stability, greater interpersonal and relationship skills, reduced non-marital pregnancy and births, and reduced delinquency and crime rates. An initial evaluability assessment was conducted to identify programs that could be rigorously evaluated and to develop an evaluation design that would meet the requirements of the authorizing legislation. Programs participating in the evaluation include an employment services program in Kern County, California; a one-on-one intensive, individualized life skills program in Massachusetts; and, a tutoring/mentoring program and a classroom-based life skills training program, both in Los Angeles County, California. Investigators: Mark E. Courtney, Ph.D. University of Wisconsin Madison, WI Matthew W. Stagner, Ph.D. U.S. Department of Health and Human Services Washington, DC Michael Pergamit, Ph.D. Urban Institute Washington, DC

ReSOLV is a longitudinal mixed methods study examining the school and community contexts that contribute to the root causes and prevention of violence in urban (Hanford), large county (Los Angeles), and rural (Mendota) study sites in California. Three data files are contained for this project, one for each study site. Each file contains aggregate data at the school and community level. The data include variables about school climate; community, school, and individual readiness to adopt comprehensive school safety approaches at the school level; student and school performance measures of chronic absenteeism, test score proficiency, graduation, suspension, and expulsion; crime data from the Uniform Crime Reports; and data from the US Census to create an index of concentrated disadvantage.