85 datasets found
  1. U.S. poverty rate in the United States 2023, by race and ethnicity

    • statista.com
    Updated Jun 25, 2025
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    Statista (2025). U.S. poverty rate in the United States 2023, by race and ethnicity [Dataset]. https://www.statista.com/statistics/200476/us-poverty-rate-by-ethnic-group/
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    Dataset updated
    Jun 25, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    United States
    Description

    In 2023, **** percent of Black people living in the United States were living below the poverty line, compared to *** percent of white people. That year, the total poverty rate in the U.S. across all races and ethnicities was **** percent. Poverty in the United States Single people in the United States making less than ****** U.S. dollars a year and families of four making less than ****** U.S. dollars a year are considered to be below the poverty line. Women and children are more likely to suffer from poverty, due to women staying home more often than men to take care of children, and women suffering from the gender wage gap. Not only are women and children more likely to be affected, racial minorities are as well due to the discrimination they face. Poverty data Despite being one of the wealthiest nations in the world, the United States had the third highest poverty rate out of all OECD countries in 2019. However, the United States' poverty rate has been fluctuating since 1990, but has been decreasing since 2014. The average median household income in the U.S. has remained somewhat consistent since 1990, but has recently increased since 2014 until a slight decrease in 2020, potentially due to the pandemic. The state that had the highest number of people living below the poverty line in 2020 was California.

  2. U.S. poverty rate of Black families 1990-2023

    • statista.com
    Updated Sep 17, 2024
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    Statista (2024). U.S. poverty rate of Black families 1990-2023 [Dataset]. https://www.statista.com/statistics/205059/percentage-of-poor-black-families-in-the-us/
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    Dataset updated
    Sep 17, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    In 2023, 15.4 percent of Black families were living below the poverty line in the United States. Poverty is the state of one who lacks a certain amount of material possessions or money. Absolute poverty or destitution is inability to afford basic human needs, which commonly includes clean and fresh water, nutrition, health care, education, clothing, and shelter.

  3. Share of the population living in poverty by race in the United States...

    • statista.com
    Updated Oct 28, 2024
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    Statista (2024). Share of the population living in poverty by race in the United States 1959-2023 [Dataset]. https://www.statista.com/statistics/1225017/poverty-share-by-race-race-us/
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    Dataset updated
    Oct 28, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    In the U.S., the share of the population living in poverty fluctuated significantly throughout the six decades between 1987 and 2023. In 2023, the poverty level across all races and ethnicities was 11.1 percent. Black Americans have been the ethnic group with the highest share of their population living in poverty almost every year since 1974. In 1979 alone, Black poverty was well over double the national average, and over four times the poverty rate in white communities; in 1982, almost 48 percent of the Black population lived in poverty. Although poverty rates have been trending downward across all ethnic groups, 17.8 percent of Black Americans and 18.9 percent of American Indian and Alaskan Natives still lived below the poverty line in 2022.

  4. c

    Poverty Status by County - Datasets - CTData.org

    • data.ctdata.org
    Updated Mar 16, 2016
    + more versions
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    (2016). Poverty Status by County - Datasets - CTData.org [Dataset]. http://data.ctdata.org/dataset/poverty-status-by-county
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    Dataset updated
    Mar 16, 2016
    License

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

    Description

    The Census Bureau determines that a person is living in poverty when his or her total household income compared with the size and composition of the household is below the poverty threshold. The Census Bureau uses the federal government's official definition of poverty to determine the poverty threshold. Beginning in 2000, individuals were presented with the option to select one or more races. In addition, the Census asked individuals to identify their race separately from identifying their Hispanic origin. The Census has published individual tables for the races and ethnicities provided as supplemental information to the main table that does not dissaggregate by race or ethnicity. Race categories include the following - White, Black or African American, American Indian or Alaska Native, Asian, Native Hawaiian or Other Pacific Islander, Some other race, and Two or more races. We are not including specific combinations of two or more races as the counts of these combinations are small. Ethnic categories include - Hispanic or Latino and White Non-Hispanic. This data comes from the American Community Survey (ACS) 5-Year estimates, table B17001. The ACS collects these data from a sample of households on a rolling monthly basis. ACS aggregates samples into one-, three-, or five-year periods. CTdata.org generally carries the five-year datasets, as they are considered to be the most accurate, especially for geographic areas that are the size of a county or smaller.Poverty status determined is the denominator for the poverty rate. It is the population for which poverty status was determined so when poverty is calculated they exclude institutionalized people, people in military group quarters, people in college dormitories, and unrelated individuals under 15 years of age.Below poverty level are households as determined by the thresholds based on the criteria of looking at household size, Below poverty level are households as determined by the thresholds based on the criteria of looking at household size, number of children, and age of householder.number of children, and age of householder.

  5. T

    Racially/Ethnically Concentrated Areas of Poverty

    • data.bayareametro.gov
    csv, xlsx, xml
    Updated Jan 31, 2022
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    Metropolitan Transportation Commission (2022). Racially/Ethnically Concentrated Areas of Poverty [Dataset]. https://data.bayareametro.gov/dataset/Racially-Ethnically-Concentrated-Areas-of-Poverty/tsz4-2bqi
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    xml, csv, xlsxAvailable download formats
    Dataset updated
    Jan 31, 2022
    Dataset authored and provided by
    Metropolitan Transportation Commission
    Description

    This dataset contains R/ECAP data for the nine-county San Francisco Bay Region at the census tract level.

    To assist communities in identifying racially/ethnically-concentrated areas of poverty (R/ECAPs), HUD has developed a census tract-based definition of R/ECAPs.

    To assist communities in identifying racially/ethnically-concentrated areas of poverty (R/ECAPs), HUD has developed a census tract-based definition of R/ECAPs. The definition involves a racial/ethnic concentration threshold and a poverty test. The racial/ethnic concentration threshold is straightforward: R/ECAPs must have a non-white population of 50 percent or more. Regarding the poverty threshold, Wilson (1980) defines neighborhoods of extreme poverty as census tracts with 40 percent or more of individuals living at or below the poverty line. Because overall poverty levels are substantially lower in many parts of the country, HUD supplements this with an alternate criterion. Thus, a neighborhood can be a R/ECAP if it has a poverty rate that exceeds 40% or is three or more times the average tract poverty rate for the metropolitan/micropolitan area, whichever threshold is lower. Census tracts with this extreme poverty that satisfy the racial/ethnic concentration threshold are deemed R/ECAPs.

    Data Source: Decennial census (2010); American Community Survey (ACS), 2006-2010; Brown Longitudinal Tract Database (LTDB) based on decennial census data, 2000 & 1990 References: Wilson, William J. (1980). The Declining Significance of Race: Blacks and Changing American Institutions. Chicago: University of Chicago Press.

    Data Source: American Community Survey (ACS), 2009-2013; Decennial Census (2010); Brown Longitudinal Tract Database (LTDB) based on decennial census data, 1990, 2000 & 2010.

    Related AFFH-T Local Government, PHA Tables/Maps: Table 4, 7; Maps 1-17.

    Related AFFH-T State Tables/Maps: Table 4, 7; Maps 1-15, 18.

    References: Wilson, William J. (1980). The Declining Significance of Race: Blacks and Changing American Institutions. Chicago: University of Chicago Press.

  6. U.S. poverty rate of Black married-couple families 1990-2023

    • statista.com
    Updated Sep 17, 2024
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    Statista (2024). U.S. poverty rate of Black married-couple families 1990-2023 [Dataset]. https://www.statista.com/statistics/205097/percentage-of-poor-black-married-couple-families-in-the-us/
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    Dataset updated
    Sep 17, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    In 2023, 6.5 percent of Black married-couple families were living below the poverty line in the United States. Poverty is the state of one who lacks a certain amount of material possessions or money. Absolute poverty or destitution is inability to afford basic human needs, which commonly includes clean and fresh water, nutrition, health care, education, clothing and shelter.

  7. F

    Percent of Population Below the Poverty Level (5-year estimate) in Black...

    • fred.stlouisfed.org
    json
    Updated Dec 12, 2024
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    (2024). Percent of Population Below the Poverty Level (5-year estimate) in Black Hawk County, IA [Dataset]. https://fred.stlouisfed.org/series/S1701ACS019013
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    jsonAvailable download formats
    Dataset updated
    Dec 12, 2024
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Area covered
    Iowa, Black Hawk County
    Description

    Graph and download economic data for Percent of Population Below the Poverty Level (5-year estimate) in Black Hawk County, IA (S1701ACS019013) from 2012 to 2023 about Black Hawk County, IA; Waterloo; IA; poverty; percent; 5-year; population; and USA.

  8. d

    Poverty Rate

    • data.ore.dc.gov
    • racial-equity-dashboard-dcgis.hub.arcgis.com
    Updated Aug 28, 2024
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    City of Washington, DC (2024). Poverty Rate [Dataset]. https://data.ore.dc.gov/datasets/poverty-rate
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    Dataset updated
    Aug 28, 2024
    Dataset authored and provided by
    City of Washington, DC
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    ACS 1-year estimates are based on data collected over one calendar year, offering more current information but with a higher margin of error. ACS 5-year estimates combine five years of data, providing more reliable information but less current. Both are based on probability samples. Some racial and ethnic categories are suppressed to avoid misleading estimates when the relative standard error exceeds 30%.

    Data Source: American Community Survey (ACS) 1- & 5-Year Estimates

    Why This Matters

    Poverty threatens the overall well-being of individuals and families, limiting access to stable housing, healthy foods, health care, and educational and employment opportunities, among other basic needs.Poverty is associated with a higher risk of adverse health outcomes, including chronic physical and mental illness, lower life expectancy, developmental delays, and others.

    Racist policies and practices have contributed to racial economic inequities. Nationally, Black, Indigenous, and people of color experience poverty at higher rates than white Americans, on average.

    The District's Response

    Boosting assistance programs that provide temporary cash and health benefits to help low-income residents meet their basic needs, including Medicaid, TANF For District Families, SNAP, etc.

    Housing assistance and employment and career training programs to support resident’s housing and employment security. These include the Emergency Rental Assistance Program, Permanent Supportive Housing vouchers, Career MAP, the DC Infrastructure Academy, among other programs and services.

    Creation of the DC Commission on Poverty to study poverty issues, evaluate poverty reduction initiatives, and make recommendations to the Mayor and the Council.

  9. l

    2022 Population and Poverty at Split Tract

    • data.lacounty.gov
    • egis-lacounty.hub.arcgis.com
    • +2more
    Updated May 8, 2024
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    County of Los Angeles (2024). 2022 Population and Poverty at Split Tract [Dataset]. https://data.lacounty.gov/datasets/2022-population-and-poverty-at-split-tract
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    Dataset updated
    May 8, 2024
    Dataset authored and provided by
    County of Los Angeles
    Area covered
    Description

    Tabular data of population by age groups, race and gender, and the poverty by race is attached to the split tract geography to create this split tract with population and poverty data. Split tract data is the product of 2020 census tracts split by 2022 incorporated city boundaries and unincorporated community/countywide statistical areas (CSA) boundaries. The census tract boundaries have been altered and aligned where necessary with legal city boundaries and unincorporated areas, including shoreline/coastal areas. Census Tract:Every 10 years the Census Bureau counts the population of the United States as mandated by Constitution. The Census Bureau (https://www.census.gov/) released 2020 geographic boundaries data including census tracts for the analysis and mapping of demographic information across the United States. City Boundary:City Boundary data is the base map information for the County of Los Angeles. These City Boundaries are based on the Los Angeles County Seamless Cadastral Landbase. The Landbase is jointly maintained by the Los Angeles County Assessor and the Los Angeles County Department of Public Works (DPW). This layer represents current city boundaries within Los Angeles County. The DPW provides the most current shapefiles representing city boundaries and city annexations. True, legal boundaries are only determined on the ground by surveyors licensed in the State of California.Countywide Statistical Areas (CSA): The countywide Statistical Area (CSA) was defined to provide a common geographic boundary for reporting departmental statistics for unincorporated areas and incorporated Los Angeles city to the Board of Supervisors. The CSA boundary and CSA names are established by the CIO and the LA County Enterprise GIS group worked with the Los Angeles County Board of Supervisors Unincorporated Area and Field Deputies that reflect as best as possible the general name preferences of residents and historical names of areas. This data is primarily focused on broad statistics and reporting, not mapping of communities. This data is not designed to perfectly represent communities, nor jurisdictional boundaries such as Angeles National Forest. CSA represent board approved geographies comprised of Census block groups split by cities.Data Field:CT20: 2020 Census tractFIP22: 2022 City FIP CodeCITY: City name for incorporated cities and “Unincorporated” for unincorporated areas (as of July 1, 2022) CSA: Countywide Statistical Area (CSA) - Unincorporated area community names and LA City neighborhood names.CT20FIP22CSA: 2020 census tract with 2022 city FIPs for incorporated cities and unincorporated areas and LA neighborhoods. SPA22: 2022 Service Planning Area (SPA) number.SPA_NAME: Service Planning Area name.HD22: 2022 Health District (HD) number: HD_NAME: Health District name.POP22_AGE_0_4: 2022 population 0 to 4 years oldPOP22_AGE_5_9: 2022 population 5 to 9 years old POP22_AGE_10_14: 2022 population 10 to 14 years old POP22_AGE_15_17: 2022 population 15 to 17 years old POP22_AGE_18_19: 2022 population 18 to 19 years old POP22_AGE_20_44: 2022 population 20 to 24 years old POP22_AGE_25_29: 2022 population 25 to 29 years old POP22_AGE_30_34: 2022 population 30 to 34 years old POP22_AGE_35_44: 2022 population 35 to 44 years old POP22_AGE_45_54: 2022 population 45 to 54 years old POP22_AGE_55_64: 2022 population 55 to 64 years old POP22_AGE_65_74: 2022 population 65 to 74 years old POP22_AGE_75_84: 2022 population 75 to 84 years old POP22_AGE_85_100: 2022 population 85 years and older POP22_WHITE: 2022 Non-Hispanic White POP22_BLACK: 2022 Non-Hispanic African AmericanPOP22_AIAN: 2022 Non-Hispanic American Indian or Alaska NativePOP22_ASIAN: 2022 Non-Hispanic Asian POP22_HNPI: 2022 Non-Hispanic Hawaiian Native or Pacific IslanderPOP22_HISPANIC: 2022 HispanicPOP22_MALE: 2022 Male POP22_FEMALE: 2022 Female POV22_WHITE: 2022 Non-Hispanic White below 100% Federal Poverty Level POV22_BLACK: 2022 Non-Hispanic African American below 100% Federal Poverty Level POV22_AIAN: 2022 Non-Hispanic American Indian or Alaska Native below 100% Federal Poverty Level POV22_ASIAN: 2022 Non-Hispanic Asian below 100% Federal Poverty Level POV22_HNPI: 2022 Non-Hispanic Hawaiian Native or Pacific Islander below 100% Federal Poverty Level POV22_HISPANIC: 2022 Hispanic below 100% Federal Poverty Level POV22_TOTAL: 2022 Total population below 100% Federal Poverty Level POP22_TOTAL: 2022 Total PopulationAREA_SQMil: Area in square mile.POP22_DENSITY: Population per square mile.POV22_PERCENT: Poverty rate/percentage.How this data created?The tabular data of population by age groups, by ethnic groups and by gender, and the poverty by ethnic groups is attributed to the split tract geography to create this data. Split tract polygon data is created by intersecting 2020 census tract polygons, LA Country City Boundary polygons and Countywide Statistical Areas (CSA) polygon data. The resulting polygon boundary aligned and matched with the legal city boundary whenever possible. Note:1. Population and poverty data estimated as of July 1, 2022. 2. 2010 Census tract and 2020 census tracts are not the same. Similarly, city and community boundary are not the same because boundary is reviewed and updated annually.

  10. U.S. poverty rate of Black families with a single mother 1990-2023

    • statista.com
    Updated Sep 17, 2024
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    Statista (2024). U.S. poverty rate of Black families with a single mother 1990-2023 [Dataset]. https://www.statista.com/statistics/205114/percentage-of-poor-black-families-with-a-female-householder-in-the-us/
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    Dataset updated
    Sep 17, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    In 1990, 48.1 percent of all Black families with a single mother in the United States lived below the poverty level. In 2023, that figure had decreased to 25.9 percent. This is significantly higher than white households with a single mother. Poverty is the state of one who lacks a certain amount of material possessions or money. Absolute poverty or destitution is inability to afford basic human needs, which commonly includes clean and fresh water, nutrition, health care, education, clothing and shelter.

  11. C

    Central African Republic Poverty Headcount Ratio at Societal Poverty Lines:...

    • ceicdata.com
    Updated Mar 1, 2025
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    CEICdata.com (2025). Central African Republic Poverty Headcount Ratio at Societal Poverty Lines: % of Population [Dataset]. https://www.ceicdata.com/en/central-african-republic/social-poverty-and-inequality/poverty-headcount-ratio-at-societal-poverty-lines--of-population
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    Dataset updated
    Mar 1, 2025
    Dataset provided by
    CEICdata.com
    License

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

    Time period covered
    Dec 1, 1992 - Dec 1, 2021
    Area covered
    Central African Republic
    Description

    Central African Republic Poverty Headcount Ratio at Societal Poverty Lines: % of Population data was reported at 65.700 % in 2021. This records an increase from the previous number of 61.900 % for 2008. Central African Republic Poverty Headcount Ratio at Societal Poverty Lines: % of Population data is updated yearly, averaging 65.700 % from Dec 1992 (Median) to 2021, with 3 observations. The data reached an all-time high of 82.200 % in 1992 and a record low of 61.900 % in 2008. Central African Republic Poverty Headcount Ratio at Societal Poverty Lines: % of Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Central African Republic – Table CF.World Bank.WDI: Social: Poverty and Inequality. The poverty headcount ratio at societal poverty line is the percentage of a population living in poverty according to the World Bank's Societal Poverty Line. The Societal Poverty Line is expressed in purchasing power adjusted 2017 U.S. dollars and defined as max($2.15, $1.15 + 0.5*Median). This means that when the national median is sufficiently low, the Societal Poverty line is equivalent to the extreme poverty line, $2.15. For countries with a sufficiently high national median, the Societal Poverty Line grows as countries’ median income grows.;World Bank, Poverty and Inequality Platform. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are mostly from the Luxembourg Income Study database. For more information and methodology, please see http://pip.worldbank.org.;;The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than 2000 household surveys across 169 countries. See the Poverty and Inequality Platform (PIP) for details (www.pip.worldbank.org).

  12. T

    Percent of Population Below the Poverty Level (5-year estimate) in Black...

    • tradingeconomics.com
    csv, excel, json, xml
    Updated May 26, 2020
    + more versions
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    TRADING ECONOMICS (2020). Percent of Population Below the Poverty Level (5-year estimate) in Black Hawk County, IA [Dataset]. https://tradingeconomics.com/united-states/percent-of-population-below-the-poverty-level-in-black-hawk-county-ia-fed-data.html
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    csv, xml, json, excelAvailable download formats
    Dataset updated
    May 26, 2020
    Dataset authored and provided by
    TRADING ECONOMICS
    License

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

    Time period covered
    Jan 1, 1976 - Dec 31, 2025
    Area covered
    Iowa, Black Hawk County
    Description

    Percent of Population Below the Poverty Level (5-year estimate) in Black Hawk County, IA was 14.70% in January of 2023, according to the United States Federal Reserve. Historically, Percent of Population Below the Poverty Level (5-year estimate) in Black Hawk County, IA reached a record high of 17.00 in January of 2013 and a record low of 14.70 in January of 2023. Trading Economics provides the current actual value, an historical data chart and related indicators for Percent of Population Below the Poverty Level (5-year estimate) in Black Hawk County, IA - last updated from the United States Federal Reserve on September of 2025.

  13. s

    Persistent low income

    • ethnicity-facts-figures.service.gov.uk
    csv
    Updated Jan 23, 2025
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    Race Disparity Unit (2025). Persistent low income [Dataset]. https://www.ethnicity-facts-figures.service.gov.uk/work-pay-and-benefits/pay-and-income/low-income/latest
    Explore at:
    csv(81 KB), csv(304 KB)Available download formats
    Dataset updated
    Jan 23, 2025
    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
    United Kingdom
    Description

    Between 2018 and 2022, people in households in the ‘other’, Asian and black ethnic groups were the most likely to be in persistent low income, both before and after housing costs, out of all ethnic groups.

  14. f

    Negative binomial regression models estimating associations between area...

    • plos.figshare.com
    xls
    Updated May 30, 2023
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    David H. Chae; Sean Clouston; Mark L. Hatzenbuehler; Michael R. Kramer; Hannah L. F. Cooper; Sacoby M. Wilson; Seth I. Stephens-Davidowitz; Robert S. Gold; Bruce G. Link (2023). Negative binomial regression models estimating associations between area racism and Black cause-specific mortality rates. [Dataset]. http://doi.org/10.1371/journal.pone.0122963.t003
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    xlsAvailable download formats
    Dataset updated
    May 30, 2023
    Dataset provided by
    PLOS ONE
    Authors
    David H. Chae; Sean Clouston; Mark L. Hatzenbuehler; Michael R. Kramer; Hannah L. F. Cooper; Sacoby M. Wilson; Seth I. Stephens-Davidowitz; Robert S. Gold; Bruce G. Link
    License

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

    Description

    Note: MRR = Mortality Rate Ratio; CI = confidence interval.Among ≥ 25 years of age. Race-specific age and sex-adjusted mortality rates weighted using the US 2000 standard population per 100,000 person-years from death certificates and mid-year population counts collated by the National Center for Health Statistics (NCHS), 2004–2009. All models adjusted for individual age, sex, year of death, and Census region; area characteristics at the designated market area (DMA) level (urbanicity, % Black, % high school education among Blacks, Black poverty rate) from the American Community Survey, 2004–2009; and corresponding DMA-level White cause-specific mortality rates per 100,000 person-years from NCHS.Negative binomial regression models estimating associations between area racism and Black cause-specific mortality rates.

  15. l

    2019 Population and Poverty at Split Tract

    • geohub.lacity.org
    • data.lacounty.gov
    • +1more
    Updated May 7, 2024
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    County of Los Angeles (2024). 2019 Population and Poverty at Split Tract [Dataset]. https://geohub.lacity.org/datasets/24aeac46b7764a188a9e20a0ba425c1b
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    Dataset updated
    May 7, 2024
    Dataset authored and provided by
    County of Los Angeles
    Area covered
    Description

    Tabular data of population by age groups, race and gender, and the poverty by race is attached to the split tract geography to create this split tract with population and poverty data. Split tract data is the product of 2010 census tracts split by 2019 incorporated city boundaries and unincorporated community/countywide statistical areas (CSA) boundaries. The census tract boundaries have been altered and aligned where necessary with legal city boundaries and unincorporated areas, including shoreline/coastal areas. Census Tract:Every 10 years the Census Bureau counts the population of the United States as mandated by Constitution. The Census Bureau (https://www.census.gov/) released 2010 geographic boundaries data including census tracts for the analysis and mapping of demographic information across the United States. City Boundary:City Boundary data is the base map information for the County of Los Angeles. These City Boundaries are based on the Los Angeles County Seamless Cadastral Landbase. The Landbase is jointly maintained by the Los Angeles County Assessor and the Los Angeles County Department of Public Works (DPW). This layer represents current city boundaries within Los Angeles County. The DPW provides the most current shapefiles representing city boundaries and city annexations. True, legal boundaries are only determined on the ground by surveyors licensed in the State of California.Countywide Statistical Areas (CSA): The countywide Statistical Area (CSA) was defined to provide a common geographic boundary for reporting departmental statistics for unincorporated areas and incorporated Los Angeles city to the Board of Supervisors. The CSA boundary and CSA names are established by the CIO and the LA County Enterprise GIS group worked with the Los Angeles County Board of Supervisors Unincorporated Area and Field Deputies that reflect as best as possible the general name preferences of residents and historical names of areas. This data is primarily focused on broad statistics and reporting, not mapping of communities. This data is not designed to perfectly represent communities, nor jurisdictional boundaries such as Angeles National Forest. CSA represent board approved geographies comprised of Census block groups split by cities.Data Field:CT10: 2010 Census tractFIP19: 2019 City FIP CodeCITY: City name for incorporated cities and “Unincorporated” for unincorporated areas (as of July 1, 2019) CSA: Countywide Statistical Area (CSA) - Unincorporated area community names and LA City neighborhood names.CT10FIP19CSA: 2010 census tract with 2019 city FIPs for incorporated cities, unincorporated areas and LA neighborhoods. SPA12: 2012 Service Planning Area (SPA) number.SPA_NAME: Service Planning Area name.HD12: 2012 Health District (HD) number: HD_NAME: Health District name.POP19_AGE_0_4: 2019 population 0 to 4 years oldPOP19_AGE_5_9: 2019 population 5 to 9 years old POP19_AGE_10_14: 2019 population 10 to 14 years old POP19_AGE_15_17: 2019 population 15 to 17 years old POP19_AGE_18_19: 2019 population 18 to 19 years old POP19_AGE_20_44: 2019 population 20 to 24 years old POP19_AGE_25_29: 2019 population 25 to 29 years old POP19_AGE_30_34: 2019 population 30 to 34 years old POP19_AGE_35_44: 2019 population 35 to 44 years old POP19_AGE_45_54: 2019 population 45 to 54 years old POP19_AGE_55_64: 2019 population 55 to 64 years old POP19_AGE_65_74: 2019 population 65 to 74 years old POP19_AGE_75_84: 2019 population 75 to 84 years old POP19_AGE_85_100: 2019 population 85 years and older POP19_WHITE: 2019 Non-Hispanic White POP19_BLACK: 2019 Non-Hispanic African AmericanPOP19_AIAN: 2019 Non-Hispanic American Indian or Alaska NativePOP19_ASIAN: 2019 Non-Hispanic Asian POP19_HNPI: 2019 Non-Hispanic Hawaiian Native or Pacific IslanderPOP19_HISPANIC: 2019 HispanicPOP19_MALE: 2019 Male POP19_FEMALE: 2019 Female POV19_WHITE: 2019 Non-Hispanic White below 100% Federal Poverty Level POV19_BLACK: 2019 Non-Hispanic African American below 100% Federal Poverty Level POV19_AIAN: 2019 Non-Hispanic American Indian or Alaska Native below 100% Federal Poverty Level POV19_ASIAN: 2019 Non-Hispanic Asian below 100% Federal Poverty Level POV19_HNPI: 2019 Non-Hispanic Hawaiian Native or Pacific Islander below 100% Federal Poverty Level POV19_HISPANIC: 2019 Hispanic below 100% Federal Poverty Level POV19_TOTAL: 2019 Total population below 100% Federal Poverty Level POP19_TOTAL: 2019 Total PopulationAREA_SQMIL: Area in square milePOP19_DENSITY: Population per square mile.POV19_PERCENT: Poverty percentage.How this data created?The tabular data of population by age groups, by ethnic groups and by gender, and the poverty by ethnic groups is attributed to the split tract geography to create this data. Split tract polygon data is created by intersecting 2010 census tract polygons, LA Country City Boundary polygons and Countywide Statistical Areas (CSA) polygon data. The resulting polygon boundary aligned and matched with the legal city boundary whenever possible. Note:1. Population and poverty data estimated as of July 1, 2019. 2. 2010 Census tract and 2020 census tracts are not the same. Similarly, city and community boundary are not the same because boundary is reviewed and updated annually.

  16. Population living in extreme poverty in Brazil 2022-2023, by ethnicity

    • statista.com
    Updated Oct 22, 2024
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    Statista (2024). Population living in extreme poverty in Brazil 2022-2023, by ethnicity [Dataset]. https://www.statista.com/statistics/1499248/share-population-living-extreme-poverty-by-ethnicity-brazil/
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    Dataset updated
    Oct 22, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Brazil
    Description

    In 2023, the prevalence of extreme poverty among black men and women in Brazil was higher than that observed in other demographic groups. In particular, the rate of extreme poverty among black men reached two percent, which was the highest among all demographic groups.

  17. C

    Central African Republic Multidimensional Poverty Headcount Ratio: UNDP: %...

    • ceicdata.com
    Updated Mar 1, 2025
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    CEICdata.com (2025). Central African Republic Multidimensional Poverty Headcount Ratio: UNDP: % of total population [Dataset]. https://www.ceicdata.com/en/central-african-republic/social-poverty-and-inequality/multidimensional-poverty-headcount-ratio-undp--of-total-population
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    Dataset updated
    Mar 1, 2025
    Dataset provided by
    CEICdata.com
    License

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

    Time period covered
    Dec 1, 2018
    Area covered
    Central African Republic
    Description

    Central African Republic Multidimensional Poverty Headcount Ratio: UNDP: % of total population data was reported at 80.400 % in 2018. Central African Republic Multidimensional Poverty Headcount Ratio: UNDP: % of total population data is updated yearly, averaging 80.400 % from Dec 2018 (Median) to 2018, with 1 observations. The data reached an all-time high of 80.400 % in 2018 and a record low of 80.400 % in 2018. Central African Republic Multidimensional Poverty Headcount Ratio: UNDP: % of total population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Central African Republic – Table CF.World Bank.WDI: Social: Poverty and Inequality. The multidimensional poverty headcount ratio (UNDP) is the percentage of a population living in poverty according to UNDPs multidimensional poverty index. The index includes three dimensions -- health, education, and living standards.;Alkire, S., Kanagaratnam, U., and Suppa, N. (2023). ‘The global Multidimensional Poverty Index (MPI) 2023 country results and methodological note’, OPHI MPI Methodological Note 55, Oxford Poverty and Human Development Initiative (OPHI), University of Oxford. (https://ophi.org.uk/mpi-methodological-note-55-2/);;

  18. h

    population-below-international-poverty-line-for-african-countries

    • huggingface.co
    + more versions
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    Electric Sheep, population-below-international-poverty-line-for-african-countries [Dataset]. https://huggingface.co/datasets/electricsheepafrica/population-below-international-poverty-line-for-african-countries
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    Dataset authored and provided by
    Electric Sheep
    Area covered
    Africa
    Description

    license: apache-2.0 tags: - africa - sustainable-development-goals - world-health-organization - development

      Population below international poverty line (%)
    
    
    
    
    
      Dataset Description
    

    This dataset provides country-level data for the indicator "1.1.1 Population below international poverty line (%)" across African nations, sourced from the World Health Organization's (WHO) data portal on Sustainable Development Goals (SDGs). The data is presented in a wide format… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/population-below-international-poverty-line-for-african-countries.

  19. Replication data for: The Wrong Side(s) of the Tracks: The Causal Effects of...

    • openicpsr.org
    Updated Apr 1, 2011
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    Elizabeth Oltmans Ananat (2011). Replication data for: The Wrong Side(s) of the Tracks: The Causal Effects of Racial Segregation on Urban Poverty and Inequality [Dataset]. http://doi.org/10.3886/E113786V1
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    Dataset updated
    Apr 1, 2011
    Dataset provided by
    American Economic Associationhttp://www.aeaweb.org/
    Authors
    Elizabeth Oltmans Ananat
    Description

    A striking negative correlation exists between an area's residential racial segregation and its population characteristics, but it is recognized that this relationship may not be causal. I present a novel test of causality from segregation to population characteristics by exploiting the arrangements of railroad tracks in the nineteenth century to isolate plausibly exogenous variation in areas' susceptibility to segregation. I show that this variation satisfies the requirements for a valid instrument. Instrumental variables estimates demonstrate that segregation increases metropolitan rates of black poverty and overall black-white income disparities, while decreasing rates of white poverty and inequality within the white population. (JEL I32, J15, N31, N32, N91, N92, R23)

  20. U.S. poverty rate 2023, by age and gender

    • statista.com
    Updated Mar 19, 2025
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    Statista (2025). U.S. poverty rate 2023, by age and gender [Dataset]. https://www.statista.com/statistics/233154/us-poverty-rate-by-gender/
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    Dataset updated
    Mar 19, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    United States
    Description

    In 2023 the poverty rate in the United States was highest among people between 18 and 24, with a rate of 16 percent for male Americans and a rate of 21 percent for female Americans. The lowest poverty rate for both men and women was for those aged between 45 and 54. What is the poverty line? The poverty line is a metric used by the U.S. Census Bureau to define poverty in the United States. It is a specific income level that is considered to be the bare minimum a person or family needs to meet their basic needs. If a family’s annual pre-tax income is below this income level, then they are considered impoverished. The poverty guideline for a family of four in 2021 was 26,500 U.S. dollars. Living below the poverty line According to the most recent data, almost one-fifth of African Americans in the United States live below the poverty line; the most out of any ethnic group. Additionally, over 7.42 million families in the U.S. live in poverty – a figure that has held mostly steady since 1990, outside the 2008 financial crisis which threw 9.52 million families into poverty by 2012. The poverty gender gap Wage inequality has been an ongoing discussion in U.S. discourse for many years now. The poverty gap for women is most pronounced during their child-bearing years, shrinks, and then grows again in old age. While progress has been made on the gender pay gap over the last 30 years, there are still significant disparities, even in occupations that predominantly employ men. Additionally, women are often having to spend more time attending to child and household duties than men.

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Statista (2025). U.S. poverty rate in the United States 2023, by race and ethnicity [Dataset]. https://www.statista.com/statistics/200476/us-poverty-rate-by-ethnic-group/
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U.S. poverty rate in the United States 2023, by race and ethnicity

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32 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Jun 25, 2025
Dataset authored and provided by
Statistahttp://statista.com/
Time period covered
2023
Area covered
United States
Description

In 2023, **** percent of Black people living in the United States were living below the poverty line, compared to *** percent of white people. That year, the total poverty rate in the U.S. across all races and ethnicities was **** percent. Poverty in the United States Single people in the United States making less than ****** U.S. dollars a year and families of four making less than ****** U.S. dollars a year are considered to be below the poverty line. Women and children are more likely to suffer from poverty, due to women staying home more often than men to take care of children, and women suffering from the gender wage gap. Not only are women and children more likely to be affected, racial minorities are as well due to the discrimination they face. Poverty data Despite being one of the wealthiest nations in the world, the United States had the third highest poverty rate out of all OECD countries in 2019. However, the United States' poverty rate has been fluctuating since 1990, but has been decreasing since 2014. The average median household income in the U.S. has remained somewhat consistent since 1990, but has recently increased since 2014 until a slight decrease in 2020, potentially due to the pandemic. The state that had the highest number of people living below the poverty line in 2020 was California.

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