25 datasets found
  1. Infant mortality rate in the U.S. in 2022 and 2023, by maternal race and...

    • statista.com
    Updated Jun 23, 2025
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    Statista (2025). Infant mortality rate in the U.S. in 2022 and 2023, by maternal race and ethnicity [Dataset]. https://www.statista.com/statistics/260521/infant-mortality-rate-in-the-us-by-race-ethnicity-of-mother/
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    Dataset updated
    Jun 23, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    Infant mortality rates in the United States reveal significant disparities among racial and ethnic groups. In 2023, Black mothers faced the highest rate at nearly 11 deaths per 1,000 live births, more than double the rate for white mothers. This stark contrast persists despite overall improvements in healthcare and highlights the need for targeted interventions to address these inequalities. Birth rates and fertility trends While infant mortality rates vary, birth rates also differ across ethnicities. Native Hawaiian and Pacific Islander women had the highest fertility rate in 2022, with about 2,237.5 births per 1,000 women, far exceeding the national average of 1,656.5. In 2023, this group maintained the highest birth rate at 79 births per 1,000 women. Asian women, by contrast, had a much lower birth rate of around 50 per thousand women. These differences in fertility rates can impact overall population growth and demographic shifts within the United States. Hispanic birth trends and fertility decline The Hispanic population in the United States has experienced significant changes in birth trends over recent decades. In 2021, 885,916 babies were born to Hispanic mothers, with a birth rate of 14.1 per 1,000 of the Hispanic population. This represents a slight increase from the previous year. However, the fertility rate among Hispanic women has declined dramatically since 1990, dropping from 108 children per 1,000 women aged 15-44 to 63.4 in 2021. This decline aligns with broader trends of decreasing fertility rates in more industrialized nations.

  2. Number, percentage and rate of homicide victims, by racialized identity...

    • www150.statcan.gc.ca
    Updated Jul 22, 2025
    + more versions
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    Government of Canada, Statistics Canada (2025). Number, percentage and rate of homicide victims, by racialized identity group, gender and region [Dataset]. http://doi.org/10.25318/3510020601-eng
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    Dataset updated
    Jul 22, 2025
    Dataset provided by
    Statistics Canadahttps://statcan.gc.ca/en
    Area covered
    Canada
    Description

    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.

  3. Number of people killed by police by ethnicity U.S. 2013-2024

    • statista.com
    Updated Dec 2, 2024
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    Statista (2024). Number of people killed by police by ethnicity U.S. 2013-2024 [Dataset]. https://www.statista.com/statistics/1124036/number-people-killed-police-ethnicity-us/
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    Dataset updated
    Dec 2, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    As of November 17, 277 Black people were killed by the police in the United States in 2024. This compares to 201 Hispanic people and 445 white people. The rate of police shootings of Black Americans is much higher than any other ethnicity, at 6.2 per million people. This rate stands at 2.8 per million for Hispanic people and 2.4 per million for white people.

  4. d

    Divergent trends in life expectancy across the rural-urban gradient and...

    • datasets.ai
    • catalog.data.gov
    Updated Nov 12, 2020
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    U.S. Environmental Protection Agency (2020). Divergent trends in life expectancy across the rural-urban gradient and association with specific racial proportions in the contiguous United States 2000-2005 [Dataset]. https://datasets.ai/datasets/divergent-trends-in-life-expectancy-across-the-rural-urban-gradient-and-association-w-2000
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    Dataset updated
    Nov 12, 2020
    Dataset authored and provided by
    U.S. Environmental Protection Agency
    Area covered
    Contiguous United States, United States
    Description

    We used individual-level death data to estimate county-level life expectancy at 25 (e25) for Whites, Black, AIAN and Asian in the contiguous US for 2000-2005. Race-sex-stratified models were used to examine the associations among e25, rurality and specific race proportion, adjusted for socioeconomic variables. Individual death data from the National Center for Health Statistics were aggregated as death counts into five-year age groups by county and race-sex groups for the contiguous US for years 2000-2005 (National Center for Health Statistics 2000-2005). We used bridged-race population estimates to calculate five-year mortality rates. The bridged population data mapped 31 race categories, as specified in the 1997 Office of Management and Budget standards for the collection of data on race and ethnicity, to the four race categories specified under the 1977 standards (the same as race categories in mortality registration) (Ingram et al. 2003). The urban-rural gradient was represented by the 2003 Rural Urban Continuum Codes (RUCC), which distinguished metropolitan counties by population size, and nonmetropolitan counties by degree of urbanization and adjacency to a metro area (United States Department of Agriculture 2016). We obtained county-level sociodemographic data for 2000-2005 from the US Census Bureau. These included median household income, percent of population attaining greater than high school education (high school%), and percent of county occupied rental units (rent%). We obtained county violent crime from Uniform Crime Reports and used it to calculate mean number of violent crimes per capita (Federal Bureau of Investigation 2010). This dataset is not publicly accessible because: EPA cannot release personally identifiable information regarding living individuals, according to the Privacy Act and the Freedom of Information Act (FOIA). This dataset contains information about human research subjects. Because there is potential to identify individual participants and disclose personal information, either alone or in combination with other datasets, individual level data are not appropriate to post for public access. Restricted access may be granted to authorized persons by contacting the party listed. It can be accessed through the following means: Request to author. Format: Data are stored as csv files.

    This dataset is associated with the following publication: Jian, Y., L. Neas, L. Messer, C. Gray, J. Jagai, K. Rappazzo, and D. Lobdell. Divergent trends in life expectancy across the rural-urban gradient among races in the contiguous United States. International Journal of Public Health. Springer Basel AG, Basel, SWITZERLAND, 64(9): 1367-1374, (2019).

  5. w

    Race and the criminal justice system 2010

    • gov.uk
    Updated Jul 26, 2012
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    Ministry of Justice (2012). Race and the criminal justice system 2010 [Dataset]. https://www.gov.uk/government/statistics/race-and-the-criminal-justice-system--3
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    Dataset updated
    Jul 26, 2012
    Dataset provided by
    GOV.UK
    Authors
    Ministry of Justice
    Description

    Statistics on race and the criminal justice system 2010

    Biennial statistics on the representation of Black, Asian and Minority Ethnic groups as victims, suspects, offenders and employees in the Criminal Justice System.

    These reports are released by the Ministry of Justice and produced in accordance with arrangements approved by the UK Statistics Authority.

    Introduction

    This report provides information about how members of Black, Asian and Minority Ethnic (BME) Groups in England and Wales were represented in the Criminal Justice System (CJS) in the most recent year for which data were available, and, wherever possible, across the last five years. Section 95 of the Criminal Justice Act 1991 requires the Government to publish statistical data to assess whether any discrimination exists in how the CJS treats people based on their race.

    These statistics are used by policy makers, the agencies who comprise the CJS and others to monitor differences between ethnic groups and where practitioners and others may wish to undertake more in-depth analysis. The identification of differences should not be equated with discrimination as there are many reasons why apparent disparities may exist.

    Specific findings

    Victims

    The most recent data on victims showed differences in the risks of crime between ethnic groups and, for homicides, in the relationship between victims and offenders. Overall, the number of racist incidents and racially or religiously aggravated offences recorded by the police had decreased over the last five years. Key Points:

    • The 2010/11 British Crime Survey (BCS) showed that the risk of being a victim of personal crime was higher for adults from a Mixed background than for other ethnic groups. It was also higher for members of all BME groups than for the White group.
    • Over the five-year period 2006/07 to 2010/11, there was a statistically significant fall in the risk of being a victim of personal crime for members of the White group of 0.8%. The apparent decrease for those from BME groups was not statistically significant.
    • Of the 2,007 homicides recorded for the latest three-year period (2007/08 to 2009/10), 75% of victims were White, 12% Black and 8% Asian.
    • In the majority of homicide cases, victims were suspected of being killed by someone from the same ethnic group, which is consistent with previous trends (88% of White victims, 78% of Black victims and 60% of Asian victims).

    Suspects

    Per 1,000 population, higher rates of s1 Stop and Searches were recorded for all BME groups (except for Chinese or Other) than for the White group. While there were decreases across the last five years in the overall number of arrests and in arrests of White people, arrests of those in the Black and Asian group increased.

    • Per 1,000 of the population, Black persons were Stopped and Searched 7.0 times more than White people in 2009/10 compared to 6.0 times more in 2006/07.
    • When referring to the rate per 1,000 population for England and Wales, it is important to bear in mind that the higher rate than that obtained for the rest of England and Wales(excluding the Metropolitan Police Service) is the product of the aggregation of 42 police force areas (PFAs), each with different distributions of both ethnic population and use of Stop and Search powers. While the area served by the Metropolitan Police Service accounts for 14% of the England and Wales population, 43% of s1 Stop and Searches are carried out by the Metropolitan Police Service.
    • Across England and Wales, there was a decrease (just over 3%) in the total number of arrests in 2009/10 (1,386,030) compared to 2005/06 (1,429,785). While the number of arrests for the White group also decreased during this period, arrests of Black persons rose by 5% and arrests of Asian people by 13%.
    • Overall, there were more arrests per 1,000 population of each BME group (except for Chinese or Other) than for people of White ethnicity in 2009/10. Black persons were arrested 3.3 times more than White people, and those from the Mixed ethnic group 2.3 times more.
    • In 2009/10, just over 9% of s1 Stop and Searches compared with 12%, 4% and 1% respectively in 2006/07.

    Defendants

    Data on out of court disposals and court proceedings show some differences in the sanctions issued to people of differing ethnicity and also in sentence lengths. These differences are likely to relate to a range of factors including variations in the types of offences committed and the plea entered, and should therefore be treated with caution. Key points:

    • Conviction ratios for indictable offences were higher for Wh

  6. Data from: Lost on the frontline, and lost in the data: COVID-19 deaths...

    • figshare.com
    zip
    Updated Jul 22, 2022
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    Loraine Escobedo (2022). Lost on the frontline, and lost in the data: COVID-19 deaths among Filipinx healthcare workers in the United States [Dataset]. http://doi.org/10.6084/m9.figshare.20353368.v1
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    zipAvailable download formats
    Dataset updated
    Jul 22, 2022
    Dataset provided by
    Figsharehttp://figshare.com/
    Authors
    Loraine Escobedo
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    United States
    Description

    To estimate county of residence of Filipinx healthcare workers who died of COVID-19, we retrieved data from the Kanlungan website during the month of December 2020.22 In deciding who to include on the website, the AF3IRM team that established the Kanlungan website set two standards in data collection. First, the team found at least one source explicitly stating that the fallen healthcare worker was of Philippine ancestry; this was mostly media articles or obituaries sharing the life stories of the deceased. In a few cases, the confirmation came directly from the deceased healthcare worker's family member who submitted a tribute. Second, the team required a minimum of two sources to identify and announce fallen healthcare workers. We retrieved 86 US tributes from Kanlungan, but only 81 of them had information on county of residence. In total, 45 US counties with at least one reported tribute to a Filipinx healthcare worker who died of COVID-19 were identified for analysis and will hereafter be referred to as “Kanlungan counties.” Mortality data by county, race, and ethnicity came from the National Center for Health Statistics (NCHS).24 Updated weekly, this dataset is based on vital statistics data for use in conducting public health surveillance in near real time to provide provisional mortality estimates based on data received and processed by a specified cutoff date, before data are finalized and publicly released.25 We used the data released on December 30, 2020, which included provisional COVID-19 death counts from February 1, 2020 to December 26, 2020—during the height of the pandemic and prior to COVID-19 vaccines being available—for counties with at least 100 total COVID-19 deaths. During this time period, 501 counties (15.9% of the total 3,142 counties in all 50 states and Washington DC)26 met this criterion. Data on COVID-19 deaths were available for six major racial/ethnic groups: Non-Hispanic White, Non-Hispanic Black, Non-Hispanic Native Hawaiian or Other Pacific Islander, Non-Hispanic American Indian or Alaska Native, Non-Hispanic Asian (hereafter referred to as Asian American), and Hispanic. People with more than one race, and those with unknown race were included in the “Other” category. NCHS suppressed county-level data by race and ethnicity if death counts are less than 10. In total, 133 US counties reported COVID-19 mortality data for Asian Americans. These data were used to calculate the percentage of all COVID-19 decedents in the county who were Asian American. We used data from the 2018 American Community Survey (ACS) five-year estimates, downloaded from the Integrated Public Use Microdata Series (IPUMS) to create county-level population demographic variables.27 IPUMS is publicly available, and the database integrates samples using ACS data from 2000 to the present using a high degree of precision.27 We applied survey weights to calculate the following variables at the county-level: median age among Asian Americans, average income to poverty ratio among Asian Americans, the percentage of the county population that is Filipinx, and the percentage of healthcare workers in the county who are Filipinx. Healthcare workers encompassed all healthcare practitioners, technical occupations, and healthcare service occupations, including nurse practitioners, physicians, surgeons, dentists, physical therapists, home health aides, personal care aides, and other medical technicians and healthcare support workers. County-level data were available for 107 out of the 133 counties (80.5%) that had NCHS data on the distribution of COVID-19 deaths among Asian Americans, and 96 counties (72.2%) with Asian American healthcare workforce data. The ACS 2018 five-year estimates were also the source of county-level percentage of the Asian American population (alone or in combination) who are Filipinx.8 In addition, the ACS provided county-level population counts26 to calculate population density (people per 1,000 people per square mile), estimated by dividing the total population by the county area, then dividing by 1,000 people. The county area was calculated in ArcGIS 10.7.1 using the county boundary shapefile and projected to Albers equal area conic (for counties in the US contiguous states), Hawai’i Albers Equal Area Conic (for Hawai’i counties), and Alaska Albers Equal Area Conic (for Alaska counties).20

  7. Race and the criminal justice system statistics 2018

    • gov.uk
    Updated Nov 28, 2019
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    Ministry of Justice (2019). Race and the criminal justice system statistics 2018 [Dataset]. https://www.gov.uk/government/statistics/race-and-the-criminal-justice-system-statistics-2018
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    Dataset updated
    Nov 28, 2019
    Dataset provided by
    GOV.UKhttp://gov.uk/
    Authors
    Ministry of Justice
    Description

    The areas of focus include: Victimisation, Police Activity, Defendants and Court Outcomes, Offender Management, Offender Characteristics, Offence Analysis, and Practitioners.

    This is the latest biennial compendium of Statistics on Race and the Criminal Justice System and follows on from its sister publication Statistics on Women and the Criminal Justice System, 2017.

    Introduction

    This publication compiles statistics from data sources across the Criminal Justice System (CJS), to provide a combined perspective on the typical experiences of different ethnic groups. No causative links can be drawn from these summary statistics. For the majority of the report no controls have been applied for other characteristics of ethnic groups (such as average income, geography, offence mix or offender history), so it is not possible to determine what proportion of differences identified in this report are directly attributable to ethnicity. Differences observed may indicate areas worth further investigation, but should not be taken as evidence of bias or as direct effects of ethnicity.

    In general, minority ethnic groups appear to be over-represented at many stages throughout the CJS compared with the White ethnic group. The greatest disparity appears at the point of stop and search, arrests, custodial sentencing and prison population. Among minority ethnic groups, Black individuals were often the most over-represented. Outcomes for minority ethnic children are often more pronounced at various points of the CJS. Differences in outcomes between ethnic groups over time present a mixed picture, with disparity decreasing in some areas are and widening in others.

    Key findings

    Victims

    • The Asian ethnic group had the lowest proportion of both adults (2%) and children (5%) who had experienced personal crime in the last year. In 2018/19, both adults and children from the Asian ethnic group were half as likely to report victimisation when compared to the White ethnic group.
    • A higher proportion of Black homicides were against children, 17% of Black victims were 17 or younger, compared to an average of 11% across all ethnicities. Between 2015/16 and 2017/18, Black children made up 20% of all child victims, while Black victims made up 13% of victims across all age groups.

    Police Activity

    • The proportion of stop and searches conducted on White suspects decreased from 75% in 2014/15 to 59% in 2018/19 and increased for all minority ethnic groups. The largest increases were from 13% to 22% for Black suspects and from 8% to 13% for Asian suspects.
    • In the last five years, the proportion of stop and searches involving Black suspects in London increased from 30% to 37%, now equal to the number of White suspects searched. In 2018/19, 48% of all stop and searches (where ethnicity is known) were conducted in London, and increasingly involving a higher proportion of suspects from minority ethnic groups when compared to the rest of England and Wales.
    • Black suspects had the highest proportion of arrests that resulted from stop and searches in the latest year, at 20% which has increased from 15% since 2014/15. This is driven by a higher number of stop and searches in London, where resultant arrests accounted for 22% of all arrests, compared to 5% for the rest of England and Wales. For other groups, between 6% and 13% of arrests resulted from stop and searches.
    • In 2018/19, two thirds (67%) of children arrested in London were from minority ethnic groups, compared to 21% of children arrested in the rest of England and Wales. Just over half (52%) of adults arrested in London were from minority ethnic groups, compared to 22% of adults arrested in the rest of England and Wales.

    Defendants

    • In the latest year, the largest fall in the volume of prosecutions and convictions for indictable offences was seen in the Asian group, down by 22% and 20% respectively. Prosecutions and convictions fell by 18% and 16% for Black defendants, by 13% each for White defendants, by 8% and 10% for defendants from Mixed ethnic groups and by 7% and 14% for defendants from Chinese or Other ethnic groups.
    • White defendants consistently had the highest conviction ratio for indictable offences over the last 5 years (with the exception of 2015) and was 85% in 2018. The conviction ratios for White, Asian (83%) and Black (81%) defendants have converged with each other over the last 5 years, remained constant for defendants from Mixed ethnic groups (77%) and fallen for Chinese or Other ethnic groups (75%).
    • Compared to White defendants (38%), larger proportions of Asian (40%), Mixed ethnicity (45%), Black (46%) and Chinese or Other (46%) defendants were remanded in custody for indictable

  8. f

    Data_Sheet_1_Differential Impact of COVID-19 Risk Factors on Ethnicities in...

    • frontiersin.figshare.com
    pdf
    Updated May 30, 2023
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    Prashant Athavale; Vijay Kumar; Jeremy Clark; Sumona Mondal; Shantanu Sur (2023). Data_Sheet_1_Differential Impact of COVID-19 Risk Factors on Ethnicities in the United States.PDF [Dataset]. http://doi.org/10.3389/fpubh.2021.743003.s001
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    pdfAvailable download formats
    Dataset updated
    May 30, 2023
    Dataset provided by
    Frontiers
    Authors
    Prashant Athavale; Vijay Kumar; Jeremy Clark; Sumona Mondal; Shantanu Sur
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    United States
    Description

    The coronavirus disease (COVID-19) has revealed existing health inequalities in racial and ethnic minority groups in the US. This work investigates and quantifies the non-uniform effects of geographical location and other known risk factors on various ethnic groups during the COVID-19 pandemic at a national level. To quantify the geographical impact on various ethnic groups, we grouped all the states of the US. into four different regions (Northeast, Midwest, South, and West) and considered Non-Hispanic White (NHW), Non-Hispanic Black (NHB), Hispanic, Non-Hispanic Asian (NHA) as ethnic groups of our interest. Our analysis showed that infection and mortality among NHB and Hispanics are considerably higher than NHW. In particular, the COVID-19 infection rate in the Hispanic community was significantly higher than their population share, a phenomenon we observed across all regions in the US but is most prominent in the West. To gauge the differential impact of comorbidities on different ethnicities, we performed cross-sectional regression analyses of statewide data for COVID-19 infection and mortality for each ethnic group using advanced age, poverty, obesity, hypertension, cardiovascular disease, and diabetes as risk factors. After removing the risk factors causing multicollinearity, poverty emerged as one of the independent risk factors in explaining mortality rates in NHW, NHB, and Hispanic communities. Moreover, for NHW and NHB groups, we found that obesity encapsulated the effect of several other comorbidities such as advanced age, hypertension, and cardiovascular disease. At the same time, advanced age was the most robust predictor of mortality in the Hispanic group. Our study quantifies the unique impact of various risk factors on different ethnic groups, explaining the ethnicity-specific differences observed in the COVID-19 pandemic. The findings could provide insight into focused public health strategies and interventions.

  9. Rate of fatal police shootings U.S. 2015-2024, by ethnicity

    • statista.com
    Updated Feb 6, 2025
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    Statista (2025). Rate of fatal police shootings U.S. 2015-2024, by ethnicity [Dataset]. https://www.statista.com/statistics/1123070/police-shootings-rate-ethnicity-us/
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    Dataset updated
    Feb 6, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    The rate of fatal police shootings in the United States shows large differences based on ethnicity. Among Black Americans, the rate of fatal police shootings between 2015 and December 2024 stood at 6.1 per million of the population per year, while for white Americans, the rate stood at 2.4 fatal police shootings per million of the population per year. Police brutality in the United States Police brutality is a major issue in the United States, but recently saw a spike in online awareness and protests following the murder of George Floyd, an African American who was killed by a Minneapolis police officer. Just a few months before, Breonna Taylor was fatally shot in her apartment when Louisville police officers forced entry into her apartment. Despite the repeated fatal police shootings across the country, police accountability has not been adequate according to many Americans. A majority of Black Americans thought that police officers were not held accountable for their misconduct, while less than half of White Americans thought the same. Political opinions Not only are there differences in opinion between ethnicities on police brutality, but there are also major differences between political parties. A majority of Democrats in the United States thought that police officers were not held accountable for their misconduct, while a majority of Republicans that they were held accountable. Despite opposing views on police accountability, both Democrats and Republicans agree that police should be required to be trained in nonviolent alternatives to deadly force.

  10. Child abuse rate U.S. 2023, by race/ethnicity of the victim

    • statista.com
    Updated Jul 21, 2025
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    Statista (2025). Child abuse rate U.S. 2023, by race/ethnicity of the victim [Dataset]. https://www.statista.com/statistics/254857/child-abuse-rate-in-the-us-by-race-ethnicity/
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    Dataset updated
    Jul 21, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    United States
    Description

    In 2023, the child abuse rate for children of Hispanic origin was at 6.7, indicating 6.7 out of every 1,000 Hispanic children in the United States suffered from some sort of abuse. This rate was highest among American Indian or Alaska Native children, with 13.8 children out of every 1,000 experiencing some form of abuse. Child abuse in the U.S. The child abuse rate in the United States is highest among American Indian or Alaska Native victims, followed by African-American victims. It is most common among children between two to five years of age. While child abuse cases are fairly evenly distributed between girls and boys, more boys than girls are victims of abuse resulting in death. The most common type of maltreatment is neglect, followed by physical abuse. Risk factors Child abuse is often reported by teachers, law enforcement officers, or social service providers. In the large majority of cases, the perpetrators of abuse were a parent of the victim. Risk factors, such as teen pregnancy, violent crime, and poverty that are associated with abuse and neglect have been found to be quite high in the United States in comparison to other countries.

  11. f

    Supplementary Material for: Multiple Sclerosis Mortality by Race/Ethnicity,...

    • karger.figshare.com
    jpeg
    Updated May 30, 2023
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    Amezcua L.; Rivas E.; Joseph S.; Zhang J.; Liu L. (2023). Supplementary Material for: Multiple Sclerosis Mortality by Race/Ethnicity, Age, Sex, and Time Period in the United States, 1999–2015 [Dataset]. http://doi.org/10.6084/m9.figshare.5788974.v1
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    jpegAvailable download formats
    Dataset updated
    May 30, 2023
    Dataset provided by
    Karger Publishers
    Authors
    Amezcua L.; Rivas E.; Joseph S.; Zhang J.; Liu L.
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    United States
    Description

    Background: Multiple sclerosis (MS) carries high morbidity and shortens life span. While there is recent recognition of other US minority populations such as blacks and Hispanics being affected with MS, examination of MS-specific mortality trends by race/ethnicity has been lacking. Objective: To investigate MS mortality rates and trends in the United States by sex, age, and race/ethnicity. Methods: We used the Compressed Mortality data file for 1999–2015 in the Wide-ranging online Data for Epidemiological Research system developed by the Center for Disease Control and Prevention to calculate the age-adjusted (US 2000 standard population) and age-specific MS mortality rate (per 100,000) by race/ethnicity and sex over time. Five mutually exclusive racial/ethnic groups were included in the analysis: non-Hispanic (NH) white, NH black, NH Asian or Pacific Islander (API), NH American Indian or Alaska Native, and Hispanic. Results: The average annual age-adjusted MS mortality rate was highest among NH whites (0.90 for males and 1.50 for females) immediately followed by NH blacks (0.75 for males and 1.42 for females), and lowest among APIs (0.05 for males and 0.12 for females). Statistically significant, increasing trend in age-adjusted MS mortality was observed during 1999–2015 among NH whites and NH blacks regardless of sex, more substantially in the latter. Age-specific MS mortality patterns showed NH blacks had the highest rate under age 55 and NH whites had the highest rate after that age point. For these 2 groups, MS mortality increased with age in both sexes and peaked at ages 55–64 for NH blacks and 65–74 for NH whites before declining substantially, while for Hispanic and API groups the risk plateaued after age 55. Conclusion: MS-specific mortality trends demonstrate distinctive differences by race/ethnicity and age. The observations that whites and females are more likely to die from MS is in line with the overall understanding that these groups are affected more by MS. However, the findings of blacks dying at an earlier age and having more substantially increasing mortality trends than whites suggest that MS burden weighs unequally by race. Further investigation into these trends may provide additional evidence into risk or protective factors within each group.

  12. Mass shootings in the U.S. by shooter’s by race/ethnicity as of September...

    • statista.com
    • ai-chatbox.pro
    Updated Jul 14, 2025
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    Statista (2025). Mass shootings in the U.S. by shooter’s by race/ethnicity as of September 2024 [Dataset]. https://www.statista.com/statistics/476456/mass-shootings-in-the-us-by-shooter-s-race/
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    Dataset updated
    Jul 14, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    Between 1982 and September 2024, 82 out of the 151 mass shootings in the United States were carried out by White shooters. By comparison, the perpetrator was African American 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.

  13. a

    In the Red the US Failure to Deliver on a Promise of Racial Equality (with...

    • sdg-transformation-center-sdsn.hub.arcgis.com
    Updated Mar 22, 2023
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    Sustainable Development Solutions Network (2023). In the Red the US Failure to Deliver on a Promise of Racial Equality (with indicators) [Dataset]. https://sdg-transformation-center-sdsn.hub.arcgis.com/items/5695593e93b94d53bfd608c1ec09c299
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    Dataset updated
    Mar 22, 2023
    Dataset authored and provided by
    Sustainable Development Solutions Network
    Area covered
    Description

    Link to this report's codebookUnfulfilled Promise of Racial EqualityUS states unequally distribute resources, services, and opportunities by raceThe US is failing to deliver on its promise of racial equality. While the US founding documents assert that ‘all men are created equal,’ this value is not demonstrated in outcomes across areas as diverse and varied as education, justice, health, gender, and pollution. On average, white communities receive resources and services at a rate approximately three times higher, than the least-served racial community (data on Asian, Black, Indigenous, Hawaiian and Pacific Islander, Hispanic, Multiracial and ‘Other’ racial communities, were used as available). Evidence shows that unequal treatment impacts each of these communities, however, it is most often Black and Indigenous communities that are left the furthest behind. When states are scored on how well they deliver the United Nations Sustainable Development Goals (SDGs) to the racial group least served, no state is even halfway to achieving the SDGs by 2030 (see Figure 1). To learn more about the Sustainable Development Goals, see the section “SDGs & Accountability.”One example of this inequality is in life expectancy. In Figure 2, the scatter plot on the left demonstrates a pattern in which Black and Indigenous communities, represented by orange and green dots closest to the bottom of the graph, are consistently the communities with least access to years of life. In the graph on the right, each box represents a racial population in a specific state, the boxes are organized from left to right, lowest to highest, according to the life expectancy for that group and state. The graph shows how large the gap is in life expectancy across racial communities and states, with green and orange boxes, representing Indigenous and Black communities respectively, clustered to the left of the graph.Patterns like this one, demonstrating both deep and wide racial inequalities, occur across the 51 indicators this analysis includes, covering 12 of 17 SDGs. In a similar example (Figure 3), a pattern emerges where white students are least likely to attend a school where 75 percent or more of its students receive free or reduced cost lunch when compared to all other racial groups. In the most unequal state, North Dakota, Indigenous students attend high poverty schools at a rate 42 times higher than white students. As Figure 3 shows, although the percentage of students from the least served racial group attending high poverty schools ranges from 2 percent in Vermont to 73 percent in Mississippi, the group least served, represented by the dots closest to the top of the graph, are most often Hispanic and Indigenous communities.Lack of Racial DataMore, and better, racially and ethnically disaggregated data are needed to assess delivery of racial equalityA significant barrier to evaluating progress is the unavailability of racial data across all areas of measurement. For too many important topic areas, such as food insecurity, maternal mortality and lead in drinking water, there is no racial data available at the state level. Even in the areas where there is some racial data, it is often not available for all groups (see Figure 4). Particularly missing, were measures of environmental justice; in Goals focusing on Water, Clean Energy, and Life on Land (Goals 6, 7, and 15), racial data was not found for any indicators, despite the fact that there is research indicating that clean water, for example, is unequally distributed across racial groups. The reasons for these gaps vary. For some indicators, data is not tracked through a nationally organized database, for other indicators, the data is old and out of date, and in many cases, surveys are not large enough to disaggregate by race. As was made clear with the disparate impacts of COVID-19 (for example, see CDC 2020), understanding to whom resources are being distributed has real life implications and is an important part of holding democratic institutions accountable to promises of equality.People are often left behind due to a combination of intersecting identities and factors; they remain hidden in averages. Evaluating the Leave No One Behind Agenda through the lens of gender, ability, class and other identities are undoubtedly important and urgent. Disaggregating data along two axes such as race and location—is revealing. But an even more refined analysis using multilevel disaggregation, such as looking at women and race in urban settings, would likely reveal even starker inequalities. Those are not included here and are important areas for future work. Other areas for further exploration include the use of longitudinal data to understand how these inequalities are changing over time.Though the full extent of this unequal treatment is unknown, this analysis sheds some light on the clouded story told by state averages. Whole group averages leave out important information, particularly about inequality. Racially disaggregated data is essential for holding governments accountable to the promise of racial equity. Without it, it is too easy to hide who is being excluded and left behind.SDGs and AccountabilitySDGs and AccountabilityThe SDGs can be an accountability tool to address racial inequality. This would not be the first time UN frameworks have been used to call attention to racial inequality in the US. In 1951, the Civil Rights Congress (CRC) led by William L. Patterson and Paul Robeson put a petition to the UN, named: “We Charge Genocide,” which charged that the United States government was in violation of the Charter of the United Nations and the Convention on the Prevention and Punishment of the Crime of Genocide (Figure 5). While this attempt did not succeed in charging the US government with genocide, it is a central example of how international instruments can be used to apply localized pressure to advance civil rights.All 193 member countries of the UN, including the United States, signed on to the Sustainable Development Goals in 2015, to be achieved by 2030. The Goals cover 17 wide-ranging topics, with 169 specific targets for action (Figure 6). The first agenda of the SDGs, the Leave No One Behind Agenda (LNOB), requires that those left furthest behind by governments must have the SDGs delivered to them first. The results of this project demonstrate that in a US-context, those left furthest behind would undoubtedly include Asian, Black, Indigenous, Hawaiian and Pacific Islander, Hispanic, Multiracial and ‘Other’ racial communities. The SDGs can offer a template for US states attempting to deliver on their promise of racial equality. The broad topic areas covered by the SDGs, in combination with the Leave No One Behind agenda, can be a tool to hold states accountable for addressing racial inequalities when and through developing solutions for clean water, quality education, ending hunger, delivering justice and more. This highlights an important implication of the Leave No One Behind Agenda, it is not meant to pit communities against each other, but rather to remind us how much everyone has to gain by building and advocating for sustainable communities that serve us all.Explore ResultsExplore the data from the In the Red: the US failure to deliver on a promise of racial equality in our interactive dashboards.These maps display how US states are delivering sustainability across different racial and ethnic groups. As part of the Leave No One Behind Agenda, which maintains that those who have been least served by development progress must be those first addressed through the SDGs, progress toward the goals in each state is displayed based on the racial group with the least access to resources, programs, and services in that state. In other words, the “Overall scores’’ map shows the score for the racial group least served in each state. Click on a state to toggle through the state’s performance by different SDGs, and click on an indicator to view how a state performs on a given indicator. At the indicator level, horizontal bar charts show the racial disparity in the selected indicator and state, when data is available.AboutIn the Red: the US Failure to Deliver on a Promise of Racial EqualityIn the Red: the US Failure to Deliver on a Promise of Racial Equality project highlights measurable gaps in how states deliver sustainability to different racial groups. The full report can be read here. It extends an earlier report, Never More Urgent, looking at policies and practices that have led to the inequalities described in this project. It was prepared by a group of independent experts at SDSN and Howard University.UN Sustainable Development Solutions Network (SDSN)The UN Sustainable Development Solutions Network (SDSN) mobilizes scientific and technical expertise from academia, civil society, and the private sector to support practical problem solving for sustainable development at local, national, and global scales. The SDSN has been operating since 2012 under the auspices of the UN Secretary-General Antonio Guterres. The SDSN is building national and regional networks of knowledge institutions, solution-focused thematic networks, and the SDG Academy, an online university for sustainable development.SDSN USASDSN USA is a network of 150+ research institutions across the United States and unincorporated territories. The network builds pathways toward achievement of the UN Sustainable Development Goals (SDGs) in the United States by mobilizing research, outreach, collective action, and global cooperation. SDSN USA is one of more than 40 national and regional SDSN networks globally. It is hosted by the UN Sustainable Development Solutions Network (SDSN) in New York City, and is chaired by Professors Jeffrey Sachs (Columbia University), Helen Bond (Howard University), Dan Esty (Yale University), and Gordon McCord (UC San Diego).

  14. s

    People living in deprived neighbourhoods

    • ethnicity-facts-figures.service.gov.uk
    csv
    Updated Sep 30, 2020
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    Race Disparity Unit (2020). People living in deprived neighbourhoods [Dataset]. https://www.ethnicity-facts-figures.service.gov.uk/uk-population-by-ethnicity/demographics/people-living-in-deprived-neighbourhoods/latest
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    csv(308 KB)Available download formats
    Dataset updated
    Sep 30, 2020
    Dataset authored and provided by
    Race Disparity Unit
    License

    Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
    License information was derived automatically

    Area covered
    England
    Description

    In 2019, people from most ethnic minority groups were more likely than White British people to live in the most deprived neighbourhoods.

  15. f

    Table_1_Trends of Racial/Ethnic Differences in Emergency Department Care...

    • figshare.com
    docx
    Updated Jun 3, 2023
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    Xingyu Zhang; Maria Carabello; Tyler Hill; Sue Anne Bell; Rob Stephenson; Prashant Mahajan (2023). Table_1_Trends of Racial/Ethnic Differences in Emergency Department Care Outcomes Among Adults in the United States From 2005 to 2016.docx [Dataset]. http://doi.org/10.3389/fmed.2020.00300.s001
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    docxAvailable download formats
    Dataset updated
    Jun 3, 2023
    Dataset provided by
    Frontiers
    Authors
    Xingyu Zhang; Maria Carabello; Tyler Hill; Sue Anne Bell; Rob Stephenson; Prashant Mahajan
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    United States
    Description

    Importance: While the literature documenting health disparities has advanced in recent decades, less is known about the pattern of racial/ethnic disparities in emergency care in the United States.Objective: To describe the trends and differences of health outcomes and resource utilization among racial/ethnic groups in US emergency care for adult patients over a 12-year period.Design, Setting, and Participants: This cross-sectional study of emergency department (ED) data from the nationally representative National Hospital Ambulatory Medical Survey (NHAMCS) examined multiple dimensions of ED care and treatment from 2005 to 2016 among adults in the US.Main Outcomes and Measures: The main outcomes include ED care outcomes (hospital admission, ICU admission, and death in the ED/hospital), resource utilization outcomes (medical imaging use, blood test, and procedure use), and patients' waiting time in the ED. The main exposure variable is race/ethnicity including white patients (non-Hispanic), black patients (non-Hispanic), Hispanic patients, Asian patients, and Other.Results: During the 12-year study period, NHAMCS collected data on 247,989 adult (> 18 years old) ED encounters, providing a weighted sample of 1,065,936,835 ED visits for analysis. Asian patients were 1.21 times more likely than white patients to be admitted to the hospital following an ED visit (aOR 1.21, 95% CI 1.12–1.31). Hispanic patients presented no significant difference in hospital admission following an ED visit (aOR 1.01, 95% CI 0.97–1.06) with white patients. Black patients were 7% less likely to receive an urgent ESI score than white patients less likely to receive immediate or emergent scores, as opposed to semi- or non-urgent scores. Black patients were also 10% less likely than white patients to be admitted to the hospital and were 1.26 times more likely than white patients to die in the ED or hospital.Conclusions and Relevance: Race is associated with significant differences in ED treatment and admission rates, which may represent disparities in emergency care. Hispanic and Asian Americans were equal or more likely to be admitted to the hospital compared to white patients. Black patients received lower triage scores and higher mortality rates. Further research is needed to understand the underlying causes and long-term health consequences of these disparities.

  16. Adult obesity rates in the U.S. by race/ethnicity 2023

    • statista.com
    • ai-chatbox.pro
    Updated Jun 23, 2025
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    Statista (2025). Adult obesity rates in the U.S. by race/ethnicity 2023 [Dataset]. https://www.statista.com/statistics/207436/overweight-and-obesity-rates-for-adults-by-ethnicity/
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    Dataset updated
    Jun 23, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    United States
    Description

    In 2023, Black adults had the highest obesity rates of any race or ethnicity in the United States, followed by American Indians/Alaska Natives and Hispanics. As of that time, around ** percent of all Black adults were obese. Asians/Pacific Islanders had by far the lowest obesity rates. Obesity in the United States Obesity is a present and growing problem in the United States. An astonishing ** percent of the adult population in the U.S. is now considered obese. Obesity rates can vary substantially by state, with around ** percent of the adult population in West Virginia reportedly obese, compared to ** percent of adults in Colorado. The states with the highest rates of obesity include West Virginia, Mississippi, and Arkansas. Diabetes Being overweight and obese can lead to a number of health problems, including heart disease, cancer, and diabetes. Being overweight or obese is one of the most common causes of type 2 diabetes, a condition in which the body does not use insulin properly, causing blood sugar levels to rise. It is estimated that just over ***** percent of adults in the U.S. have been diagnosed with diabetes. Diabetes is now the seventh leading cause of death in the United States, accounting for ***** percent of all deaths.

  17. Reasons for study exclusion.

    • plos.figshare.com
    csv
    Updated Jan 17, 2025
    + more versions
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    Umar Ahmed Riaz Chaudhry; Rebecca Fortescue; Liza Bowen; Stephen J. Woolford; Felicity Knights; Derek G. Cook; Tess Harris; Julia Critchley (2025). Reasons for study exclusion. [Dataset]. http://doi.org/10.1371/journal.pone.0314318.s003
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    csvAvailable download formats
    Dataset updated
    Jan 17, 2025
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Umar Ahmed Riaz Chaudhry; Rebecca Fortescue; Liza Bowen; Stephen J. Woolford; Felicity Knights; Derek G. Cook; Tess Harris; Julia Critchley
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    AimsType 2 diabetes (T2D) is more common in certain ethnic groups. This systematic review compares mortality risk between people with T2D from different ethnic groups and includes recent larger studies.MethodsWe searched nine databases using PRISMA guidelines (PROSPERO CRD42022372542). We included community-based prospective studies among adults with T2D from at least two different ethnicities. Two independent reviewers undertook screening, data extraction and quality assessment using the Newcastle-Ottawa Scale. The primary outcome compared all-cause mortality rates between ethnic groups (hazard ratio (HR) with 95% confidence intervals).ResultsFrom 30,825 searched records, we included 13 studies (7 meta-analysed), incorporating 573,173 T2D participants; 12 were good quality. Mortality risk was lower amongst people with T2D from South Asian [HR 0.68 (0.65–0.72)], Black [HR 0.82 (0.77–0.87)] and Chinese [HR 0.57 (0.46–0.70)] ethnicity compared to people of White ethnicity. Narrative synthesis corroborated these findings but demonstrated that people of indigenous Māori ethnicity had greater mortality risk compared to European ethnicity.ConclusionsPeople with T2D of South Asian, Black and Chinese ethnicity have lower all-cause mortality risk than White ethnicity, with Māori ethnicity having higher mortality risk. Factors explaining mortality differences require further study, including understanding complication risk by ethnicity, to improve diabetes outcomes.

  18. Preterm and Very Preterm Live Births

    • healthdata.gov
    • data.chhs.ca.gov
    • +2more
    application/rdfxml +5
    Updated Apr 8, 2025
    + more versions
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    chhs.data.ca.gov (2025). Preterm and Very Preterm Live Births [Dataset]. https://healthdata.gov/State/Preterm-and-Very-Preterm-Live-Births/i3u9-feiw
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    xml, json, csv, application/rssxml, tsv, application/rdfxmlAvailable download formats
    Dataset updated
    Apr 8, 2025
    Dataset provided by
    chhs.data.ca.gov
    Description

    This dataset contains percent preterm and very preterm live births by race/ethnic group of mother. Preterm births are all live births less than 37 weeks of gestation. Very preterm births are all live births less than 32 weeks of gestation. Important growth and development occur throughout pregnancy, especially in the final months and weeks. There is a higher risk of serious disability or death the earlier a baby is born. Gestational age is based on obstetric estimate at delivery (OE). Data includes births with gestational age of 17-47 weeks. Note: The race and ethnic groups in this table utilize eight mutually exclusive race and ethnicity categories. These categories are Hispanic and the following Non-Hispanic categories of Multi-Race, African-American, American Indian (includes Eskimo and Aleut), Asian, Pacific Islander (includes Hawaiian), White (includes Other race) and Unknown (includes refused to state and missing).

    Data should not be compared to other data where gestational age is based on the date of last normal menses (LMP) and not OE. The National Center for Health Statistics recently transitioned to using an OE-based gestational age measure due to increasing evidence of its greater validity compared with the LMP-based measure. (http://www.cdc.gov/nchs/data/nvsr/nvsr64/nvsr64_05.pdf)

  19. U.S. distribution of race and ethnicity among the military 2019

    • statista.com
    Updated Jan 24, 2025
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    Statista (2025). U.S. distribution of race and ethnicity among the military 2019 [Dataset]. https://www.statista.com/statistics/214869/share-of-active-duty-enlisted-women-and-men-in-the-us-military/
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    Dataset updated
    Jan 24, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    In the fiscal year of 2019, 21.39 percent of active-duty enlisted women were of Hispanic origin. The total number of active duty military personnel in 2019 amounted to 1.3 million people.

    Ethnicities in the United States The United States is known around the world for the diversity of its population. The Census recognizes six different racial and ethnic categories: White American, Native American and Alaska Native, Asian American, Black or African American, Native Hawaiian and Other Pacific Islander. People of Hispanic or Latino origin are classified as a racially diverse ethnicity.

    The largest part of the population, about 61.3 percent, is composed of White Americans. The largest minority in the country are Hispanics with a share of 17.8 percent of the population, followed by Black or African Americans with 13.3 percent. Life in the U.S. and ethnicity However, life in the United States seems to be rather different depending on the race or ethnicity that you belong to. For instance: In 2019, native Hawaiians and other Pacific Islanders had the highest birth rate of 58 per 1,000 women, while the birth rae of white alone, non Hispanic women was 49 children per 1,000 women.

    The Black population living in the United States has the highest poverty rate with of all Census races and ethnicities in the United States. About 19.5 percent of the Black population was living with an income lower than the 2020 poverty threshold. The Asian population has the smallest poverty rate in the United States, with about 8.1 percent living in poverty.

    The median annual family income in the United States in 2020 earned by Black families was about 57,476 U.S. dollars, while the average family income earned by the Asian population was about 109,448 U.S. dollars. This is more than 25,000 U.S. dollars higher than the U.S. average family income, which was 84,008 U.S. dollars.

  20. Share of mass public shooters U.S. 1999-2024, by race and location of...

    • statista.com
    Updated Jun 23, 2025
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    Statista (2025). Share of mass public shooters U.S. 1999-2024, by race and location of shooting [Dataset]. https://www.statista.com/statistics/1462777/mass-public-shooters-by-race-location-us/
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    Dataset updated
    Jun 23, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    From 1966 to January 2024, ** percent of mass public shooters who carried out the shooting at K-12 schools in the United States identified as White, followed by ** percent who were Native American and * percent who were Latinx. For mass public shootings occurring at colleges and universities, the shooter was most likely to identify as Asian, at ** percent, followed by ** percent who were White. In addition, Black and Middle Eastern shooters each made up ** percent. The source defines a mass public shooting as a multiple homicide incident in which 4 or more victims are murdered with firearms—not including the offender(s)—within one event, and at least some of the murders occurred in a public location or locations in close geographical proximity (e.g., a workplace, school, restaurant, or other public settings), and the murders are not attributable to any other underlying criminal activity or commonplace circumstance (armed robbery, criminal competition, insurance fraud, argument, or romantic triangle). Mass shootings attributable to gangs, as well as most domestic homicides, are therefore excluded from this definition.

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Statista (2025). Infant mortality rate in the U.S. in 2022 and 2023, by maternal race and ethnicity [Dataset]. https://www.statista.com/statistics/260521/infant-mortality-rate-in-the-us-by-race-ethnicity-of-mother/
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Infant mortality rate in the U.S. in 2022 and 2023, by maternal race and ethnicity

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Dataset updated
Jun 23, 2025
Dataset authored and provided by
Statistahttp://statista.com/
Area covered
United States
Description

Infant mortality rates in the United States reveal significant disparities among racial and ethnic groups. In 2023, Black mothers faced the highest rate at nearly 11 deaths per 1,000 live births, more than double the rate for white mothers. This stark contrast persists despite overall improvements in healthcare and highlights the need for targeted interventions to address these inequalities. Birth rates and fertility trends While infant mortality rates vary, birth rates also differ across ethnicities. Native Hawaiian and Pacific Islander women had the highest fertility rate in 2022, with about 2,237.5 births per 1,000 women, far exceeding the national average of 1,656.5. In 2023, this group maintained the highest birth rate at 79 births per 1,000 women. Asian women, by contrast, had a much lower birth rate of around 50 per thousand women. These differences in fertility rates can impact overall population growth and demographic shifts within the United States. Hispanic birth trends and fertility decline The Hispanic population in the United States has experienced significant changes in birth trends over recent decades. In 2021, 885,916 babies were born to Hispanic mothers, with a birth rate of 14.1 per 1,000 of the Hispanic population. This represents a slight increase from the previous year. However, the fertility rate among Hispanic women has declined dramatically since 1990, dropping from 108 children per 1,000 women aged 15-44 to 63.4 in 2021. This decline aligns with broader trends of decreasing fertility rates in more industrialized nations.

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