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

    • statista.com
    Updated Sep 16, 2024
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    Statista (2024). 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
    Sep 16, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    United States
    Description

    In 2023, 17.9 percent of Black people living in the United States were living below the poverty line, compared to 7.7 percent of white people. That year, the total poverty rate in the U.S. across all races and ethnicities was 11.1 percent. Poverty in the United States Single people in the United States making less than 12,880 U.S. dollars a year and families of four making less than 26,500 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. Poverty and low-income statistics by selected demographic characteristics

    • www150.statcan.gc.ca
    • open.canada.ca
    • +1more
    Updated Apr 26, 2024
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    Government of Canada, Statistics Canada (2024). Poverty and low-income statistics by selected demographic characteristics [Dataset]. http://doi.org/10.25318/1110009301-eng
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    Dataset updated
    Apr 26, 2024
    Dataset provided by
    Statistics Canadahttps://statcan.gc.ca/en
    Area covered
    Canada
    Description

    Poverty and low-income statistics by visible minority group, Indigenous group and immigration status, Canada and provinces.

  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. Fight Child Poverty with Demographic Analysis

    • hub.arcgis.com
    Updated Nov 28, 2018
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    Esri Tutorials (2018). Fight Child Poverty with Demographic Analysis [Dataset]. https://hub.arcgis.com/documents/56ed6ddf23374721b0f675a864e38822
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    Dataset updated
    Nov 28, 2018
    Dataset provided by
    Esrihttp://esri.com/
    Authors
    Esri Tutorials
    Description

    The poverty-fighting charity you work for wants to alleviate suffering among impoverished children in Detroit, a Michigan city which consistently ranks among America's poorest urban centers. In this lesson, you'll combine census-tract data with ArcGIS Living Atlas of the World demographic information to identify the most poverty-stricken neighborhoods. With that newly discovered knowledge, you'll configure an app which will help you articulate a report to top donors.

    In this lesson you will build skills in the these areas:

    • Mapping income
    • Styling layers and pop-ups
    • Creating an app

    Learn ArcGIS is a hands-on, problem-based learning website using real-world scenarios. Our mission is to encourage critical thinking, and to develop resources that support STEM education.

  5. F

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

    • fred.stlouisfed.org
    json
    Updated Dec 12, 2024
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    (2024). Percent of Population Below the Poverty Level (5-year estimate) in Miami-Dade County, FL [Dataset]. https://fred.stlouisfed.org/series/S1701ACS012086
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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
    Miami-Dade County, Florida
    Description

    Graph and download economic data for Percent of Population Below the Poverty Level (5-year estimate) in Miami-Dade County, FL (S1701ACS012086) from 2012 to 2023 about Miami-Dade County, FL; Miami; FL; percent; poverty; 5-year; population; and USA.

  6. c

    Poverty Rate

    • data.ccrpc.org
    csv
    Updated Oct 17, 2024
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    Champaign County Regional Planning Commission (2024). Poverty Rate [Dataset]. https://data.ccrpc.org/dataset/poverty-rate
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    csv(393)Available download formats
    Dataset updated
    Oct 17, 2024
    Dataset provided by
    Champaign County Regional Planning Commission
    Description

    This poverty rate data shows what percentage of the measured population* falls below the poverty line. Poverty is closely related to income: different “poverty thresholds” are in place for different sizes and types of household. A family or individual is considered to be below the poverty line if that family or individual’s income falls below their relevant poverty threshold. For more information on how poverty is measured by the U.S. Census Bureau (the source for this indicator’s data), visit the U.S. Census Bureau’s poverty webpage.

    The poverty rate is an important piece of information when evaluating an area’s economic health and well-being. The poverty rate can also be illustrative when considered in the contexts of other indicators and categories. As a piece of data, it is too important and too useful to omit from any indicator set.

    The poverty rate for all individuals in the measured population in Champaign County has hovered around roughly 20% since 2005. However, it reached its lowest rate in 2021 at 14.9%, and its second lowest rate in 2023 at 16.3%. Although the American Community Survey (ACS) data shows fluctuations between years, given their margins of error, none of the differences between consecutive years’ estimates are statistically significant, making it impossible to identify a trend.

    Poverty rate data was sourced from the U.S. Census Bureau’s American Community Survey 1-Year Estimates, which are released annually.

    As with any datasets that are estimates rather than exact counts, it is important to take into account the margins of error (listed in the column beside each figure) when drawing conclusions from the data.

    Due to the impact of the COVID-19 pandemic, instead of providing the standard 1-year data products, the Census Bureau released experimental estimates from the 1-year data in 2020. This includes a limited number of data tables for the nation, states, and the District of Columbia. The Census Bureau states that the 2020 ACS 1-year experimental tables use an experimental estimation methodology and should not be compared with other ACS data. For these reasons, and because data is not available for Champaign County, no data for 2020 is included in this Indicator.

    For interested data users, the 2020 ACS 1-Year Experimental data release includes a dataset on Poverty Status in the Past 12 Months by Age.

    *According to the U.S. Census Bureau document “How Poverty is Calculated in the ACS," poverty status is calculated for everyone but those in the following groups: “people living in institutional group quarters (such as prisons or nursing homes), people in military barracks, people in college dormitories, living situations without conventional housing, and unrelated individuals under 15 years old."

    Sources: U.S. Census Bureau; American Community Survey, 2023 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using data.census.gov; (17 October 2024).; U.S. Census Bureau; American Community Survey, 2022 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using data.census.gov; (25 September 2023).; U.S. Census Bureau; American Community Survey, 2021 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using data.census.gov; (16 September 2022).; U.S. Census Bureau; American Community Survey, 2019 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using data.census.gov; (8 June 2021).; U.S. Census Bureau; American Community Survey, 2018 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using data.census.gov; (8 June 2021).; U.S. Census Bureau; American Community Survey, 2017 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using American FactFinder; (13 September 2018).; U.S. Census Bureau; American Community Survey, 2016 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using American FactFinder; (14 September 2017).; U.S. Census Bureau; American Community Survey, 2015 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using American FactFinder; (19 September 2016).; U.S. Census Bureau; American Community Survey, 2014 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2013 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2012 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2011 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2010 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2009 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2008 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2007 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2006 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2005 American Community Survey 1-Year Estimates, Table S1701; generated by CCRPC staff; using American FactFinder; (16 March 2016).

  7. U.S. poverty rate 1990-2023

    • statista.com
    Updated Sep 16, 2024
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    Statista (2024). U.S. poverty rate 1990-2023 [Dataset]. https://www.statista.com/statistics/200463/us-poverty-rate-since-1990/
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    Dataset updated
    Sep 16, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    In 2023, the around 11.1 percent of the population was living below the national poverty line in the United States. Poverty in the United StatesAs shown in the statistic above, the poverty rate among all people living in the United States has shifted within the last 15 years. The United Nations Educational, Scientific and Cultural Organization (UNESCO) defines poverty as follows: “Absolute poverty measures poverty in relation to the amount of money necessary to meet basic needs such as food, clothing, and shelter. The concept of absolute poverty is not concerned with broader quality of life issues or with the overall level of inequality in society.” The poverty rate in the United States varies widely across different ethnic groups. American Indians and Alaska Natives are the ethnic group with the most people living in poverty in 2022, with about 25 percent of the population earning an income below the poverty line. In comparison to that, only 8.6 percent of the White (non-Hispanic) population and the Asian population were living below the poverty line in 2022. Children are one of the most poverty endangered population groups in the U.S. between 1990 and 2022. Child poverty peaked in 1993 with 22.7 percent of children living in poverty in that year in the United States. Between 2000 and 2010, the child poverty rate in the United States was increasing every year; however,this rate was down to 15 percent in 2022. The number of people living in poverty in the U.S. varies from state to state. Compared to California, where about 4.44 million people were living in poverty in 2022, the state of Minnesota had about 429,000 people living in poverty.

  8. Time Series Current Population Survey: Poverty Status

    • catalog.data.gov
    • s.cnmilf.com
    Updated Sep 13, 2023
    + more versions
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    U.S. Census Bureau (2023). Time Series Current Population Survey: Poverty Status [Dataset]. https://catalog.data.gov/dataset/current-population-survey-time-series-current-population-survey-poverty-status
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    Dataset updated
    Sep 13, 2023
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Description

    The Current Population Survey (CPS), sponsored jointly by the U.S. Census Bureau and the U.S. Bureau of Labor Statistics (BLS), is the primary source of labor force statistics for the population of the United States. The CPS is the source of numerous high-profile economic statistics, including the national unemployment rate, and provides data on a wide range of issues relating to employment and earnings. The CPS also collects extensive demographic data that complement and enhance our understanding of labor market conditions in the nation overall, among many different population groups, in the states and in substate areas.

  9. T

    Economic Poverty Rate by County WA

    • open.piercecountywa.gov
    • internal.open.piercecountywa.gov
    Updated Mar 26, 2025
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    U.S. Census American Community Survey (2025). Economic Poverty Rate by County WA [Dataset]. https://open.piercecountywa.gov/Demographics/Economic-Poverty-Rate-by-County-WA/xyg9-chf5
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    xml, csv, application/rdfxml, application/rssxml, kmz, kml, tsv, application/geo+jsonAvailable download formats
    Dataset updated
    Mar 26, 2025
    Dataset authored and provided by
    U.S. Census American Community Survey
    Area covered
    Washington
    Description

    Count and rate of population with income in the last 12 months below poverty level in an area. ( B17001). County and State values are from ACS 1-year survey.

  10. d

    Iowa Population by Poverty Status (Past 12 Months), Sex and Age (ACS 5-Year...

    • catalog.data.gov
    • s.cnmilf.com
    • +3more
    Updated Jun 14, 2024
    + more versions
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    data.iowa.gov (2024). Iowa Population by Poverty Status (Past 12 Months), Sex and Age (ACS 5-Year Estimates) [Dataset]. https://catalog.data.gov/dataset/iowa-population-by-poverty-status-past-12-months-sex-and-age-acs-5-year-estimates
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    Dataset updated
    Jun 14, 2024
    Dataset provided by
    data.iowa.gov
    Area covered
    Iowa
    Description

    This dataset provides Iowa population estimates by poverty status in past 12 months, sex and age for State of Iowa, individual Iowa counties, Iowa places and census tracts within Iowa. Data is from the American Community Survey, Five Year Estimates, Table B17001. Poverty status categories include the following: Total, At or Above Poverty, and At or Below Poverty. Sex categories include the following: Male, Female, and Both. Age categories include the following: All Ages, 04 Years and Under, 05 Years, 06 to 11 Years, 12 to 14 Years, 15 Years, 16 to 17 Years, 18 to 24 Years, 25 to 34 Years, 35 to 44 Years, 45 to 54 Years, 55 to 64 Years, 65 to 74 Years, and 75 Years and Over.

  11. Share of world population living in poverty 1990-2022

    • statista.com
    Updated Jan 23, 2025
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    Statista (2025). Share of world population living in poverty 1990-2022 [Dataset]. https://www.statista.com/statistics/1341003/poverty-rate-world/
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    Dataset updated
    Jan 23, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    World
    Description

    Over the past 30 years, there has been an almost constant reduction in the poverty rate worldwide. Whereas nearly 38 percent of the world's population lived on less than 2.15 U.S. dollars in terms of 2017 Purchasing Power Parity (PPP) in 1990, this had fallen to 8.7 percent in 2022. This is despite the fact that the world's population was growing over the same period. However, there was a small increase in the poverty rate during the COVID-19 pandemic in 2020 and 2021, when thousands of people became unemployed overnight. Moreover, rising cost of living in the aftermath of the pandemic and spurred by the Russian invasion of Ukraine in 2022 meant that many people were struggling to make ends meet. Poverty is a regional problem Poverty can be measured in relative and absolute terms. Absolute poverty concerns basic human needs such as food, clothing, shelter, and clean drinking water, whereas relative poverty looks at whether people in different countries can afford a certain living standard. Most countries that have a high percentage of their population living in absolute poverty, meaning that they are poor compared to international standards, are regionally concentrated. African countries are most represented among the countries in which poverty prevails the most. In terms of numbers, Sub-Saharan Africa and South Asia have the most people living in poverty worldwide. Inequality on the rise How wealth, or the lack thereof, is distributed within the global population and even within countries is very unequal. In 2022, the richest one percent of the world owned almost half of the global wealth, while the poorest 50 percent owned less than two percent in the same year. Within regions, Latin America had the most unequal distribution of wealth but this phenomenon is present in all world regions.

  12. F

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

    • fred.stlouisfed.org
    json
    Updated Dec 12, 2024
    + more versions
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    (2024). Percent of Population Below the Poverty Level (5-year estimate) in District of Columbia [Dataset]. https://fred.stlouisfed.org/series/S1701ACS011001
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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
    Washington
    Description

    Graph and download economic data for Percent of Population Below the Poverty Level (5-year estimate) in District of Columbia (S1701ACS011001) from 2012 to 2023 about DC, Washington, percent, poverty, 5-year, population, and USA.

  13. 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.

  14. a

    2020 Population and Poverty at Split Tract

    • demography-lacounty.hub.arcgis.com
    • egis-lacounty.hub.arcgis.com
    Updated May 7, 2024
    + more versions
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    County of Los Angeles (2024). 2020 Population and Poverty at Split Tract [Dataset]. https://demography-lacounty.hub.arcgis.com/maps/lacounty::2020-population-and-poverty-at-split-tract/explore
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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 2020 census tracts split by 2020 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 tractFIP21: 2020 City FIP CodeCITY: City name for incorporated cities and “Unincorporated” for unincorporated areas (as of July 1, 2020) CSA: Countywide Statistical Area (CSA) - Unincorporated area community names and LA City neighborhood names.CT20FIP21CSA: 2020 census tract with 2020 city FIPs for incorporated cities, 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.POP20_AGE_0_4: 2020 population 0 to 4 years oldPOP20_AGE_5_9: 2020 population 5 to 9 years old POP20_AGE_10_14: 2020 population 10 to 14 years old POP20_AGE_15_17: 2020 population 15 to 17 years old POP20_AGE_18_19: 2020 population 18 to 19 years old POP20_AGE_20_44: 2020 population 20 to 24 years old POP20_AGE_25_29: 2020 population 25 to 29 years old POP20_AGE_30_34: 2020 population 30 to 34 years old POP20_AGE_35_44: 2020 population 35 to 44 years old POP20_AGE_45_54: 2020 population 45 to 54 years old POP20_AGE_55_64: 2020 population 55 to 64 years old POP20_AGE_65_74: 2020 population 65 to 74 years old POP20_AGE_75_84: 2020 population 75 to 84 years old POP20_AGE_85_100: 2020 population 85 years and older POP20_WHITE: 2020 Non-Hispanic White POP20_BLACK: 2020 Non-Hispanic African AmericanPOP20_AIAN: 2020 Non-Hispanic American Indian or Alaska NativePOP20_ASIAN: 2020 Non-Hispanic Asian POP20_HNPI: 2020 Non-Hispanic Hawaiian Native or Pacific IslanderPOP20_HISPANIC: 2020 HispanicPOP20_MALE: 2020 Male POP20_FEMALE: 2020 Female POV20_WHITE: 2020 Non-Hispanic White below 100% Federal Poverty Level POV20_BLACK: 2020 Non-Hispanic African American below 100% Federal Poverty Level POV20_AIAN: 2020 Non-Hispanic American Indian or Alaska Native below 100% Federal Poverty Level POV20_ASIAN: 2020 Non-Hispanic Asian below 100% Federal Poverty Level POV20_HNPI: 2020 Non-Hispanic Hawaiian Native or Pacific Islander below 100% Federal Poverty Level POV20_HISPANIC: 2020 Hispanic below 100% Federal Poverty Level POV20_TOTAL: 2020 Total population below 100% Federal Poverty Level POP20_TOTAL: 2020 Total PopulationAREA_SQMIL: Area in square milePOP20_DENSITY: Population per square mile.POV20_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, 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.

  15. l

    2019 Population and Poverty at Split Tract

    • data.lacounty.gov
    • egis-lacounty.hub.arcgis.com
    • +2more
    Updated May 7, 2024
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    County of Los Angeles (2024). 2019 Population and Poverty at Split Tract [Dataset]. https://data.lacounty.gov/maps/lacounty::2019-population-and-poverty-at-split-tract
    Explore at:
    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. F

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

    • fred.stlouisfed.org
    json
    Updated Dec 12, 2024
    + more versions
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    (2024). Percent of Population Below the Poverty Level (5-year estimate) in Douglas County, NE [Dataset]. https://fred.stlouisfed.org/series/S1701ACS031055
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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
    Douglas County, Nebraska
    Description

    Graph and download economic data for Percent of Population Below the Poverty Level (5-year estimate) in Douglas County, NE (S1701ACS031055) from 2012 to 2023 about Douglas County, NE; Omaha; NE; percent; poverty; 5-year; population; and USA.

  17. f

    Poverty 2016

    • gisdata.fultoncountyga.gov
    Updated Jan 2, 2018
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    Georgia Association of Regional Commissions (2018). Poverty 2016 [Dataset]. https://gisdata.fultoncountyga.gov/datasets/GARC::poverty-2016/about
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    Dataset updated
    Jan 2, 2018
    Dataset provided by
    The Georgia Association of Regional Commissions
    Authors
    Georgia Association of Regional Commissions
    License

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

    Area covered
    Description

    This layer was developed by the Research & Analytics Group of the Atlanta Regional Commission, using data from the U.S. Census Bureau’s American Community Survey 5-year estimates for 2012-2016, to show counts and percentages of population in poverty, by census tract in the Atlanta region. The user should note that American Community Survey data represent estimates derived from a surveyed sample of the population, which creates some level of uncertainty, as opposed to an exact measure of the entire population (the full census count is only conducted once every 10 years and does not cover as many detailed characteristics of the population). Therefore, any measure reported by ACS should not be taken as an exact number – this is why a corresponding margin of error (MOE) is also given for ACS measures. The size of the MOE relative to its corresponding estimate value provides an indication of confidence in the accuracy of each estimate. Each MOE is expressed in the same units as its corresponding measure; for example, if the estimate value is expressed as a number, then its MOE will also be a number; if the estimate value is expressed as a percent, then its MOE will also be a percent. The user should also note that for relatively small geographic areas, such as census tracts shown here, ACS only releases combined 5-year estimates, meaning these estimates represent rolling averages of survey results that were collected over a 5-year span (in this case 2012-2016). Therefore, these data do not represent any one specific point in time or even one specific year. For geographic areas with larger populations, 3-year and 1-year estimates are also available.

    For further explanation of ACS estimates and margin of error, click here.Attributes: GEOID10 = 2010 Census tract identifier (combination of Federal Information Processing Series (FIPS) codes for state, county, and census tract) County = County identifier (combination of Federal Information Processing Series (FIPS) codes for state and county) Area_Name = 2010 Census tract name- - - - - -Total_Population = # Total Population, 2016 Total_Population_MOE_2016 = # Total population (Margin of Error), 2016- - - - - -Pop_PovertyStatus_Determine = # Population for whom poverty status is determined, 2016 Pop_PovertyStatus_Determine_MOE = # Population for whom poverty status is determined (Margin of Error), 2016 Pop_below_poverty = # Population below poverty, 2016 Pop_below_poverty_MOE = # Population below poverty (Margin of Error), 2016 Pct_below_poverty = % Population below poverty, 2016 Pct_below_poverty_MOE = % Population below poverty (Margin of Error), 2016 Pop_below_poverty_2000 = # Population below poverty, 2000 Pct_below_poverty_2000 = % Population below poverty, 2000 Chg_Pct_in_poverty_2000_16 = Change, % Population below poverty, 2000-2016 Pop_u18_PovStatus_Determine = # Population under 18 years for whom poverty status is determined, 2016 Pop_u18_PovStatus_Determine_MOE = # Population under 18 years for whom poverty status is determined (Margin of Error), 2016 Pop_under18_inPoverty = # Population under 18 years below poverty, 2016 Pop_under18_inPoverty_MOE = # Population under 18 years below poverty (Margin of Error), 2016 Pct_Pop_u18_in_Poverty = % Population under 18 years below poverty, 2016 Pct_Pop_u18_in_Poverty_MOE = % Population under 18 years below poverty (Margin of Error), 2016 Pop_18_64_PovStatus_Determ = # Population 18 to 64 years for whom poverty status is determined, 2016 Pop_18_64_PovStatus_Determ_MOE = # Population 18 to 64 years for whom poverty status is determined (Margin of Error), 2016 Pop_18_64_Years_in_Poverty = # Population 18 to 64 years below poverty, 2016 Pop_18_64_Years_in_Poverty_MOE = # Population 18 to 64 years below poverty (Margin of Error), 2016 Pct_Pop_18_64_in_Poverty = % Population 18 to 64 years below poverty, 2016 Pct_Pop_18_64_in_Poverty_MOE = % Population 18 to 64 years below poverty (Margin of Error), 2016 Pop_65up_PovStatusDetermine = # Population 65 years and over for whom poverty status is determined, 2016 Pop_65up_PovStatusDetermine_MOE = # Population 65 years and over for whom poverty status is determined (Margin of Error), 2016 Pop_65up_in_Poverty = # Population 65 years and over below poverty, 2016 Pop_65up_in_Poverty_MOE = # Population 65 years and over below poverty (Margin of Error), 2016 Pct_Pop_65up_inPoverty = % Population 65 years and over below poverty, 2016 Pct_Pop_65up_inPoverty_MOE = % Population 65 years and over below poverty (Margin of Error), 2016- - - - - -Planning_Region = Planning region designation for ARC purposes AcresLand = Land area within the tract (in acres) AcresWater = Water area within the tract (in acres) AcresTotal = Total area within the tract (in acres) SqMi_Land = Land area within the tract (in square miles) SqMi_Water = Water area within the tract (in square miles) SqMi_Total = Total area within the tract (in square miles) TRACTCE10 = Census tract Federal Information Processing Series (FIPS) code. Census tracts are identified by an up to four-digit integer number and may have an optional two-digit suffix; for example 1457.02 or 23. The census tract codes consist of six digits with an implied decimal between the fourth and fifth digit corresponding to the basic census tract number but with leading zeroes and trailing zeroes for census tracts without a suffix. The tract number examples above would have codes of 145702 and 002300, respectively. CountyName = County Name last_edited_date = Last date the feature was edited by ARC Source: U.S. Census Bureau, Atlanta Regional CommissionDate: 2012-2016

    For additional information, please visit the Atlanta Regional Commission at www.atlantaregional.com.

  18. a

    2018 Population and Poverty at Split Tract

    • egis-lacounty.hub.arcgis.com
    • geohub.lacity.org
    • +2more
    Updated May 7, 2024
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    County of Los Angeles (2024). 2018 Population and Poverty at Split Tract [Dataset]. https://egis-lacounty.hub.arcgis.com/datasets/2018-population-and-poverty-at-split-tract
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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 2018 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 tractFIP18: 2018 City FIP CodeCITY: City name for incorporated cities and “Unincorporated” for unincorporated areas (as of July 1, 2018) CSA: Countywide Statistical Area (CSA) - Unincorporated area community names and LA City neighborhood names.CT10FIP18CSA: 2010 census tract with 2018 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.POP18_AGE_0_4: 2018 population 0 to 4 years oldPOP18_AGE_5_9: 2018 population 5 to 9 years old POP18_AGE_10_14: 2018 population 10 to 14 years old POP18_AGE_15_17: 2018 population 15 to 17 years old POP18_AGE_18_19: 2018 population 18 to 19 years old POP18_AGE_20_44: 2018 population 20 to 24 years old POP18_AGE_25_29: 2018 population 25 to 29 years old POP18_AGE_30_34: 2018 population 30 to 34 years old POP18_AGE_35_44: 2018 population 35 to 44 years old POP18_AGE_45_54: 2018 population 45 to 54 years old POP18_AGE_55_64: 2018 population 55 to 64 years old POP18_AGE_65_74: 2018 population 65 to 74 years old POP18_AGE_75_84: 2018 population 75 to 84 years old POP18_AGE_85_100: 2018 population 85 years and older POP18_WHITE: 2018 Non-Hispanic White POP18_BLACK: 2018 Non-Hispanic African AmericanPOP18_AIAN: 2018 Non-Hispanic American Indian or Alaska NativePOP18_ASIAN: 2018 Non-Hispanic Asian POP18_HNPI: 2018 Non-Hispanic Hawaiian Native or Pacific IslanderPOP18_HISPANIC: 2018 HispanicPOP18_MALE: 2018 Male POP18_FEMALE: 2018 Female POV18_WHITE: 2018 Non-Hispanic White below 100% Federal Poverty Level POV18_BLACK: 2018 Non-Hispanic African American below 100% Federal Poverty Level POV18_AIAN: 2018 Non-Hispanic American Indian or Alaska Native below 100% Federal Poverty Level POV18_ASIAN: 2018 Non-Hispanic Asian below 100% Federal Poverty Level POV18_HNPI: 2018 Non-Hispanic Hawaiian Native or Pacific Islander below 100% Federal Poverty Level POV18_HISPANIC: 2018 Hispanic below 100% Federal Poverty Level POV18_TOTAL: 2018 Total population below 100% Federal Poverty Level POP18_TOTAL: 2018 Total PopulationAREA_SQMIL: Area in square milePOP18_DENSITY: Population per square mile.POV18_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.

  19. School Neighborhood Poverty Estimates, 2018-19

    • data-nces.opendata.arcgis.com
    • catalog.data.gov
    Updated Mar 29, 2021
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    National Center for Education Statistics (2021). School Neighborhood Poverty Estimates, 2018-19 [Dataset]. https://data-nces.opendata.arcgis.com/datasets/nces::school-neighborhood-poverty-estimates-2018-19
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    Dataset updated
    Mar 29, 2021
    Dataset authored and provided by
    National Center for Education Statisticshttps://nces.ed.gov/
    License

    https://resources.data.gov/open-licenses/https://resources.data.gov/open-licenses/

    Area covered
    Description

    The 2018-2019 School Neighborhood Poverty Estimates are based on school locations from the 2018-2019 Common Core of Data (CCD) school file and income data from families with children ages 5 to 17 in the U.S. Census Bureau’s 2015-2019 American Community Survey (ACS) 5-year collection. The ACS is a continuous household survey that collects social, demographic, economic, and housing information from the population in the United States each month. The Census Bureau calculates the income-to-poverty ratio (IPR) based on money income reported for families relative to the poverty thresholds, which are determined based on the family size and structure. Noncash benefits (such as food stamps and housing subsidies) are excluded, as are capital gains and losses. The IPR is the percentage of family income that is above or below the federal poverty level. The IPR indicator ranges from 0 to a top-coded value of 999. A family with income at the poverty threshold has an IPR value of 100. The estimates in this file reflect the IPR for the neighborhoods around schools which may be different from the neighborhood conditions of students enrolled in schools.All information contained in this file is in the public domain. Data users are advised to review NCES program documentation and feature class metadata to understand the limitations and appropriate use of these data.

  20. l

    2023 Population and Poverty by Split Tract

    • data.lacounty.gov
    • geohub.lacity.org
    • +1more
    Updated May 31, 2024
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    County of Los Angeles (2024). 2023 Population and Poverty by Split Tract [Dataset]. https://data.lacounty.gov/datasets/2023-population-and-poverty-by-split-tract/about
    Explore at:
    Dataset updated
    May 31, 2024
    Dataset authored and provided by
    County of Los Angeles
    Area covered
    Description

    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 2023 incorporated city boundaries and unincorporated community/countywide statistical areas (CSA) boundaries as of July 1, 2023. 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 Fields:CT20: 2020 Census tractFIP22: 2023 City FIP CodeCITY: City name for incorporated cities and “Unincorporated” for unincorporated areas (as of July 1, 2023) CSA: Countywide Statistical Area (CSA) - Unincorporated area community names and LA City neighborhood names.CT20FIP23CSA: 2020 census tract with 2023 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.POP23_AGE_0_4: 2023 population 0 to 4 years oldPOP23_AGE_5_9: 2023 population 5 to 9 years old POP23_AGE_10_14: 2023 population 10 to 14 years old POP23_AGE_15_17: 2022 population 15 to 17 years old POP23_AGE_18_19: 2023 population 18 to 19 years old POP23_AGE_20_44: 2023 population 20 to 24 years old POP23_AGE_25_29: 2023 population 25 to 29 years old POP23_AGE_30_34: 2023 population 30 to 34 years old POP23_AGE_35_44: 2023 population 35 to 44 years old POP23_AGE_45_54: 2023 population 45 to 54 years old POP23_AGE_55_64: 2023 population 55 to 64 years old POP23_AGE_65_74: 2023 population 65 to 74 years old POP23_AGE_75_84: 2023 population 75 to 84 years old POP23_AGE_85_100: 2023 population 85 years and older POP23_WHITE: 2023 Non-Hispanic White POP23_BLACK: 2023 Non-Hispanic African AmericanPOP23_AIAN: 2023 Non-Hispanic American Indian or Alaska NativePOP23_ASIAN: 2023 Non-Hispanic Asian POP23_HNPI: 2023 Non-Hispanic Hawaiian Native or Pacific IslanderPOP23_HISPANIC: 2023 HispanicPOP23_MALE: 2023 Male POP23_FEMALE: 2023 Female POV23_WHITE: 2023 Non-Hispanic White below 100% Federal Poverty Level POV23_BLACK: 2023 Non-Hispanic African American below 100% Federal Poverty Level POV23_AIAN: 2023 Non-Hispanic American Indian or Alaska Native below 100% Federal Poverty Level POV23_ASIAN: 2023 Non-Hispanic Asian below 100% Federal Poverty Level POV23_HNPI: 2023 Non-Hispanic Hawaiian Native or Pacific Islander below 100% Federal Poverty Level POV23_HISPANIC: 2023 Hispanic below 100% Federal Poverty Level POV23_TOTAL: 2023 Total population below 100% Federal Poverty Level POP23_TOTAL: 2023 Total PopulationAREA_SQMil: Area in square mile.POP23_DENSITY: 2023 Population per square mile.POV23_PERCENT: 2023 Poverty rate/percentage.How this data created?Population by age groups, ethnic groups and 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. Notes:1. Population and poverty data estimated as of July 1, 2023. 2. 2010 Census tract and 2020 census tracts are not the same. Similarly, city and community boundaries are as of July 1, 2023.

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Statista (2024). 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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26 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Sep 16, 2024
Dataset authored and provided by
Statistahttp://statista.com/
Time period covered
2023
Area covered
United States
Description

In 2023, 17.9 percent of Black people living in the United States were living below the poverty line, compared to 7.7 percent of white people. That year, the total poverty rate in the U.S. across all races and ethnicities was 11.1 percent. Poverty in the United States Single people in the United States making less than 12,880 U.S. dollars a year and families of four making less than 26,500 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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