In 2024, **** percent of Black people living in the United States were living below the poverty line, compared to *** percent of white people. That year, the overall poverty rate in the U.S. across all races and ethnicities was **** percent. Poverty in the United States The poverty threshold for a single person in the United States was measured at an annual income of ****** U.S. dollars in 2023. Among families of four, the poverty line increases to ****** U.S. dollars a year. Women and children are more likely to suffer from poverty. This is due to the fact that women are more likely than men to stay at home, to care for children. Furthermore, the gender-based wage gap impacts women's earning potential. Poverty data Despite being one of the wealthiest nations in the world, the United States has some of the highest poverty rates among OECD countries. While, the United States poverty rate has fluctuated since 1990, it has trended downwards since 2014. Similarly, the average median household income in the U.S. has mostly increased over the past decade, except for the covid-19 pandemic period. Among U.S. states, Louisiana had the highest poverty rate, which stood at some ** percent in 2024.

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.

In 2023, there were about 336,000 Black married-couple families living below the poverty level 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.

In 2023, there were about 1.6 million Black families living below the poverty level 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.

In 2023, 17.8 percent of Black families with a single father 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.

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.

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.

Mortality rates in the United States vary based on race, individual economic status and neighborhood. Correlations among these variables in most urban areas have limited what conclusions can be drawn from existing research. Our study employs a unique factorial design of race, sex, age and individual poverty status, measuring time to death as an objective measure of health, and including both neighborhood economic status and income inequality for a sample of middle-aged urban-dwelling adults (N = 3675). At enrollment, African American and White participants lived in 46 unique census tracts in Baltimore, Maryland, which varied in neighborhood economic status and degree of income inequality. A Cox regression model for 9-year mortality identified a three-way interaction among sex, race and individual poverty status (p = 0.03), with African American men living below poverty having the highest mortality. Neighborhood economic status, whether measured by a composite index or simply median household income, was negatively associated with overall mortality (p

This product has been archived in accordance with Federal Grant Compliance and is no longer actively updated. The site remains accessible for historical reference purposes.Disclaimer: This application is a DRAFT and is still under development. A look at the Equity Atlas Poverty indicator in Dallas using the methodology described below. Poverty (S1701)

Each scored category represents 20% of the total population of the City of Dallas.

A score of 5 represents that the percentage of people in poverty is between 23.4% - 80.4%..

A score of 4 represents the percentage of people in poverty is between 16.4% - 23.4%.

A score of 3 represents that the percentage of people in poverty is between 9.9% - 16.3%.

A score of 2 represents that the percentage of people in poverty is between 5.1% - 9.8%.

A score of 1 represents the percentage of people in poverty is between 0.4% - 5%.

Parameter

Data Field

Data Source

American Community Survey 5-Year Estimate 2018-2022

POVERTY STATUS IN THE PAST 12 MONTHS

U.S. Census Bureau, Table: S1701

All people that are living in poverty

Estimated percent of all people that are living in poverty as of 2018-2022

U.S. Census Bureau, Table: S1701

White people who lived in poverty

Estimated percent of all White people who lived in poverty between 2018-2022

U.S. Census Bureau, Table: S1701

Black or African American people who lived in poverty

Estimated percent of all Black or African American people who lived in poverty between 2018-2022

U.S. Census Bureau, Table: S1701

Asian people who lived in poverty

Estimated percentage of all Asian people who lived in poverty between 2018-2022

U.S. Census Bureau, Table: S1701

American Indian and Alaskan Native people who lived in poverty

Estimated percent of all American Indian and Alaskan Native people who lived in poverty between 2018-2022

U.S. Census Bureau, Table: S1701

Native Hawaiian and Other Pacific Islander people who were living in poverty

Estimated percent of all Native Hawaiian and Other Pacific Islander people who were living in poverty between 2018-2022

U.S. Census Bureau, Table: S1701

people of Some Other Race living in poverty

Estimated percent of all people of "Some Other Race" living in poverty between 2018-2022

U.S. Census Bureau, Table: S1701

people of two or more races living below the poverty level

Estimated percent of all people of "two or more races" living below the poverty level between 2018-2022

U.S. Census Bureau, Table: S1701

Hispanic or Latino people who were living in poverty

Estimated percentage of all Hispanic or Latino people who were living in poverty between 2018-2022

U.S. Census Bureau, Table: S1701

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, for 2020, the 2020 Census provides the official counts of the population and housing units for the nation, states, counties, cities, and towns. For 2016 to 2019, the Population Estimates Program provides estimates of the population for the nation, states, counties, cities, and towns and intercensal housing unit estimates for the nation, states, and counties..Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2016-2020 American Community Survey 5-Year Estimates.Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..The categories for relationship to householder were revised in 2019. For more information see Revisions to the Relationship to Household item..The Hispanic origin and race codes were updated in 2020. For more information on the Hispanic origin and race code changes, please visit the American Community Survey Technical Documentation website..The 2016-2020 American Community Survey (ACS) data generally reflect the September 2018 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas. In certain instances, the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineation lists due to differences in the effective dates of the geographic entities..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.

This product has been archived in accordance with Federal Grant Compliance and is no longer actively updated. The site remains accessible for historical reference purposes.Data Source: U.S. Census Bureau, "ACS Demographic and Housing Estimates," American Community Survey, ACS 5-Year Estimates Data Profiles, Table DP05, 2022., U.S. Census Bureau, "Educational Attainment," American Community Survey, ACS 5-Year Estimates Subject Tables, Table S1501, 2022., U.S. Census Bureau, "Poverty Status in the Past 12 Months," American Community Survey, ACS 5-Year Estimates Subject Tables, Table S1701, 2022., U.S. Census Bureau, "Median Income in the Past 12 Months (in 2022 Inflation-Adjusted Dollars)," American Community Survey, ACS 5-Year Estimates Subject Tables, Table S1903, 2022., U.S. Census Bureau, "Selected Characteristics of Health Insurance Coverage in the United States," American Community Survey, ACS 5-Year Estimates Subject Tables, Table S2701, 2022.,Variables:DP05_0073PE: Percent Hispanic or Latino (of any race) %DP05_0079PE: White %DP05_0080PE: Black or African American %DP05_0081PE: American Indian and Alaskan Native %DP05_0082PE: Asian %DP05_0083PE: Native Hawaiian and Other Pacific Islander %DP05_0084PE: Some other race %DP05_0085PE: Two or more races %Race_Rank: Race and Ethnicity RankS1501_C02_014E: Estimate Percent Population 25 years and over High school graduate or higher (%)S1501_C02_032E: Estimate Percent White, not Hispanic or Latino High school graduate or higher (%)S1501_C02_035E: Estimate Percent Black High school graduate or higher (%)S1501_C02_038E: Estimate Percent American Indian or Alaska Native High school graduate or higher (%)S1501_C02_041E: Estimate Percent Asian High school graduate or higher (%)S1501_C02_044E: Estimate Percent Native Hawaiian and Other Pacific Islander High school graduate or higher (%)S1501_C02_047E: Estimate Percent Some other race High school graduate or higher (%)S1501_C02_050E: Estimate Percent Two or more races High school graduate or higher (%)S1501_C02_053E: Estimate Percent Hispanic or Latino Origin High school graduate or higher (%)Education_Rank: Education RankS1701_C01_001E: Estimate Total Population for whom poverty status is determinedS1701_C03_001E: Estimate Percent below poverty level Population for whom poverty status is determinedS1701_C03_021E: Estimate Percent below poverty level: White alone, not Hispanic or LatinoS1701_C03_014E: Estimate Percent below poverty level: Black or African American aloneS1701_C03_015E: Estimate Percent below poverty level: American Indian and Alaska Native aloneS1701_C03_016E: Estimate Percent below poverty level: Asian aloneS1701_C03_017E: Estimate Percent below poverty level: Native Hawaiian and Other Pacific Islander aloneS1701_C03_018E: Estimate Percent below poverty level: Some other race aloneS1701_C03_019E: Estimate Percent below poverty level: Two or more racesS1701_C03_020E: Estimate Percent below poverty level: Hispanic or Latino origin (of any race)S1701_C03_010E: Estimate Percent below poverty level: AGE 65 years and overPoverty_Rank: Poverty RankS1903_C03_001E: Estimate Median income (dollars) (general)S1903_C03_003E: Estimate Median income (dollars) Black or African AmericanS1903_C03_004E: Estimate Median income (dollars) American Indian and Alaska NativeS1903_C03_005E: Estimate Median income (dollars) AsianS1903_C03_006E: Estimate Median income (dollars) Native Hawaiian and Other Pacific IslanderS1903_C03_007E: Estimate Median income (dollars) Some other raceS1903_C03_008E: Estimate Median income (dollars) Two or more racesS1903_C03_009E: Estimate Median income (dollars) Hispanic or Latino origin (of any race)S1903_C03_010E: Estimate Median income (dollars) WhiteIncome_Rank: Income RankS2701_C05_001E: Estimate Percent Uninsured Civilian noninstitutionalized populationS2701_C03_017E: Estimate Percent Insured Black or African American aloneS2701_C03_018E: Estimate Percent Insured American Indian and Alaska Native aloneS2701_C03_019E: Estimate Percent Insured Asian aloneS2701_C03_020E: Estimate Percent Insured Native Hawaiian and Other Pacific Islander aloneS2701_C03_021E: Estimate Percent Insured Some other race aloneS2701_C03_022E: Estimate Percent Insured Two or more racesS2701_C03_023E: Estimate Percent Insured Hispanic or Latino (of any race)S2701_C03_024E: Estimate Percent Insured White alone, not Hispanic or LatinoInsurance_Rank: Insurance RankYear: 2022Provider: U.S. Census Bureau

County-level race and ethnicity estimates for populations for whom poverty status has been determined, cross-tabulated with income estimates for populations with income below poverty level. Race and ethnicity estimates include the following categories: White alone, Black or African American alone, American Indian or Alaska Native alone, Native Hawaiian or Other Pacific Islander alone, Some Other Race alone, Two or More Races, White alone and Not Hispanic or Latino, Hispanic or Latino, and people of color. Estimates are accompanied by margins of error, coefficients of variation, and percentages. Geometry source: 2020 Census. Attribute source: 2019-2023 American Community Survey 5-year estimates, tables B17001, B17001A, B17001B, B17001C, B17001D, B17001E, B17001F, B17001G, B17001H, and B17001I. Date of last data update: 2024-01-11 This is official RLIS data. Contact Person: Joe Gordon joe.gordon@oregonmetro.gov 503-797-1587 RLIS Metadata Viewer: https://gis.oregonmetro.gov/rlis-metadata/#/details/3845 RLIS Terms of Use: https://rlisdiscovery.oregonmetro.gov/pages/terms-of-use

This layer is part of source data for the State of Poverty 2018-2024 Los Angeles County Dashboard.Layers include estimates of total population and population in poverty by demographics at each geography level in LA County.Source: Annual Population and Poverty Estimation, Los Angeles County ISD-Demography.Datasets for all years available in the State of Poverty dashboard:PAI Poverty Map Data 2024PAI Poverty Map Data 2023PAI Poverty Map Data 2022PAI Poverty Map Data 2021PAI Poverty Map Data 2020PAI Poverty Map Data 2019PAI Poverty Map Data 2018 Included Geography LevelsSplit Census TractsCensus TractsCountywide Statistical Areas (CSA)Public Use Microdata Areas (PUMA)Service Planning Area (SPA)Supervisor District (SD)Los Angeles County Split Census Tract and CSA boundaries correspond to the year of the population and poverty estimates. Census Tract, PUMA, SPA, SD, and county boundaries are current as of 2020 US Census. Field NamesPlease see Field Aliases for detailed field names.Field name logic:1st character Race/Ethnicityt = Totala = Asianb = Black or African Americanh = Hispanic or Latinoi = American Indian and Alaska Native (AIAN)p = Pacific Islanderw = White2nd character Gendert = Totalf = Femalem = Male3-4th characters Year2-digit year (2018-22)Possible 5th character Poverty Level (%FPL)a = Below 100% FPLd = Below 200% FPLg = Below 266% FPLRemaining characters after underscoret = Total (all ages)

Poverty Status by Town reports the number and percentage of people and children living in poverty, by race/ethnicity and age range.

The Black food insecurity rate in the United States was in 2020. Explore a map of black hunger statistics in the United States at the state and local level.

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, the decennial census is the official source of population totals for April 1st of each decennial year. In between censuses, the Census Bureau's Population Estimates Program produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units and the group quarters population for states and counties..Information about the American Community Survey (ACS) can be found on the ACS website. Supporting documentation including code lists, subject definitions, data accuracy, and statistical testing, and a full list of ACS tables and table shells (without estimates) can be found on the Technical Documentation section of the ACS website.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2019-2023 American Community Survey 5-Year Estimates.ACS data generally reflect the geographic boundaries of legal and statistical areas as of January 1 of the estimate year. For more information, see Geography Boundaries by Year..Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..Users must consider potential differences in geographic boundaries, questionnaire content or coding, or other methodological issues when comparing ACS data from different years. Statistically significant differences shown in ACS Comparison Profiles, or in data users' own analysis, may be the result of these differences and thus might not necessarily reflect changes to the social, economic, housing, or demographic characteristics being compared. For more information, see Comparing ACS Data..The Hispanic origin and race codes were updated in 2020. For more information on the Hispanic origin and race code changes, please visit the American Community Survey Technical Documentation website..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on 2020 Census data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.

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.

For the past several censuses, the Census Bureau has invited people to self-respond before following up in-person using census takers. The 2010 Census invited people to self-respond predominately by returning paper questionnaires in the mail. The 2020 Census allows people to self-respond in three ways: online, by phone, or by mail.The 2020 Census self-response rates are self-response rates for current census geographies. These rates are the daily and cumulative self-response rates for all housing units that received invitations to self-respond to the 2020 Census. The 2020 Census self-response rates are available for states, counties, census tracts, congressional districts, towns and townships, consolidated cities, incorporated places, tribal areas, and tribal census tracts.The Self-Response Rate of Los Angeles County is 65.1% for 2020 Census, which is slightly lower than 69.6% of California State rate.More information about these data is available in the Self-Response Rates Map Data and Technical Documentation document associated with the 2020 Self-Response Rates Map or review FAQs.Animated Self-Response Rate 2010 vs 2020 is available at ESRI site SRR Animated Maps and can explore Census 2020 SRR data at ESRI Demographic site Census 2020 SSR Data.Following Demographic Characteristics are included in this data and web maps to visualize their relationships with Census Self-Response Rate (SRR).1. Population Density: 2020 Population per square mile,2. Poverty Rate: Percentage of population under 100% FPL,3. Median Household income: Based on countywide median HH income of $71,538.4. Highschool Education Attainment: Percentage of 18 years and older population without high school graduation.5. English Speaking Ability: Percentage of 18 years and older population with less or none English speaking ability. 6. Household without Internet Access: Percentage of HH without internet access.7. Non-Hispanic White Population: Percentage of Non-Hispanic White population.8. Non-Hispanic African-American Population: Percentage of Non-Hispanic African-American population.9. Non-Hispanic Asian Population: Percentage of Non-Hispanic Asian population.10. Hispanic Population: Percentage of Hispanic population.

IntroductionUnequal healthcare access is linked to disparities in health outcomes. Public transit plays a critical role in promoting equitable healthcare access, particularly for disadvantaged populations. This study aims to assess disparities in hospital access via public transit in Austin, Texas, while considering socioeconomic and demographic factors.MethodsWe analyzed 30 hospitals using data from Definitive Healthcare, alongside demographic and socioeconomic factors for 283 census tracts in and around Austin, Texas, obtained from the U. S. Census Bureau. Variables included the percentage of the population who are Black or African American, Hispanic or Latino, uninsured, or have incomes below the poverty level. Using the TravelTime Isochrone API, we delineated one-hour public transit catchment areas for each hospital and overlaid them with demographic and socioeconomic data to examine spatial disparities in healthcare access and identify underserved communities.ResultsOverall, people in the western and eastern parts of the city lack hospital service coverage accessible by public transit within 1 hour. Of the 283 census tracts, 160 are either partially covered (125 tracts) or not covered at all (35 tracts), with 72 of the partially covered tracts having less than 50 percent area coverage. The eastern area has higher proportions of Black or African American, Hispanic or Latino, and uninsured populations, reflecting greater disparities.DiscussionThe results revealed notable disparities in healthcare access via public transit, where limited hospital coverage overlaps with high social and economic vulnerability. Targeted transit and healthcare planning for underserved areas and populations is needed to reduce these inequities.

The 2020-2021 School Neighborhood Poverty Estimates are based on school locations from the 2020-2021 Common Core of Data (CCD) school file and income data from families with children ages 5 to 18 in the U.S. Census Bureau’s 2017-2021 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.

Collections are available for the following years:

• School Neighborhood Poverty Estimates, 2020-2021
  
• School Neighborhood Poverty Estimates, 2019-2020
• School Neighborhood Poverty Estimates, 2018-2019
• School Neighborhood Poverty Estimates, 2017-2018
• School Neighborhood Poverty Estimates, 2016-2017
• School Neighborhood Poverty Estimates, 2015-2016

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.