100+ datasets found
  1. 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
    Explore at:
    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).

  2. c

    Poverty Status by Town - Datasets - CTData.org

    • data.ctdata.org
    Updated Mar 16, 2016
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    (2016). Poverty Status by Town - Datasets - CTData.org [Dataset]. http://data.ctdata.org/dataset/poverty-status-by-town
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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.

  3. Vital Signs: Poverty - by tract

    • data.bayareametro.gov
    application/rdfxml +5
    Updated Dec 12, 2018
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    U.S. Census Bureau (2018). Vital Signs: Poverty - by tract [Dataset]. https://data.bayareametro.gov/dataset/Vital-Signs-Poverty-by-tract/974p-p6wz
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    xml, application/rssxml, tsv, json, csv, application/rdfxmlAvailable download formats
    Dataset updated
    Dec 12, 2018
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    U.S. Census Bureau
    Description

    VITAL SIGNS INDICATOR Poverty (EQ5)

    FULL MEASURE NAME The share of the population living in households that earn less than 200 percent of the federal poverty limit

    LAST UPDATED December 2018

    DESCRIPTION Poverty refers to the share of the population living in households that earn less than 200 percent of the federal poverty limit, which varies based on the number of individuals in a given household. It reflects the number of individuals who are economically struggling due to low household income levels.

    DATA SOURCE U.S Census Bureau: Decennial Census http://www.nhgis.org (1980-1990) http://factfinder2.census.gov (2000)

    U.S. Census Bureau: American Community Survey Form C17002 (2006-2017) http://api.census.gov

    METHODOLOGY NOTES (across all datasets for this indicator) The U.S. Census Bureau defines a national poverty level (or household income) that varies by household size, number of children in a household, and age of householder. The national poverty level does not vary geographically even though cost of living is different across the United States. For the Bay Area, where cost of living is high and incomes are correspondingly high, an appropriate poverty level is 200% of poverty or twice the national poverty level, consistent with what was used for past equity work at MTC and ABAG. For comparison, however, both the national and 200% poverty levels are presented.

    For Vital Signs, the poverty rate is defined as the number of people (including children) living below twice the poverty level divided by the number of people for whom poverty status is determined. Poverty rates do not include unrelated individuals below 15 years old or people who live in the following: institutionalized group quarters, college dormitories, military barracks, and situations without conventional housing. The household income definitions for poverty change each year to reflect inflation. The official poverty definition uses money income before taxes and does not include capital gains or noncash benefits (such as public housing, Medicaid, and food stamps). For the national poverty level definitions by year, see: https://www.census.gov/hhes/www/poverty/data/threshld/index.html For an explanation on how the Census Bureau measures poverty, see: https://www.census.gov/hhes/www/poverty/about/overview/measure.html

    For the American Community Survey datasets, 1-year data was used for region, county, and metro areas whereas 5-year rolling average data was used for city and census tract.

    To be consistent across metropolitan areas, the poverty definition for non-Bay Area metros is twice the national poverty level. Data were not adjusted for varying income and cost of living levels across the metropolitan areas.

  4. School Neighborhood Poverty Estimates, 2020-21

    • catalog.data.gov
    • s.cnmilf.com
    • +1more
    Updated Oct 21, 2024
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    National Center for Education Statistics (NCES) (2024). School Neighborhood Poverty Estimates, 2020-21 [Dataset]. https://catalog.data.gov/dataset/school-neighborhood-poverty-estimates-2020-21
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    Dataset updated
    Oct 21, 2024
    Dataset provided by
    National Center for Education Statisticshttps://nces.ed.gov/
    Description

    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 17 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.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.

  5. T

    Vital Signs: Poverty - by tract (2022)

    • data.bayareametro.gov
    application/rdfxml +5
    Updated Jan 3, 2023
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    (2023). Vital Signs: Poverty - by tract (2022) [Dataset]. https://data.bayareametro.gov/dataset/Vital-Signs-Poverty-by-tract-2022-/xciv-yzma
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    csv, application/rdfxml, tsv, xml, json, application/rssxmlAvailable download formats
    Dataset updated
    Jan 3, 2023
    Description

    VITAL SIGNS INDICATOR
    Poverty (EQ5)

    FULL MEASURE NAME
    The share of the population living in households that earn less than 200 percent of the federal poverty limit

    LAST UPDATED
    January 2023

    DESCRIPTION
    Poverty refers to the share of the population living in households that earn less than 200 percent of the federal poverty limit, which varies based on the number of individuals in a given household. It reflects the number of individuals who are economically struggling due to low household income levels.

    DATA SOURCE
    U.S Census Bureau: Decennial Census - http://www.nhgis.org
    1980-2000

    U.S. Census Bureau: American Community Survey - https://data.census.gov/
    2007-2021
    Form C17002

    CONTACT INFORMATION
    vitalsigns.info@mtc.ca.gov

    METHODOLOGY NOTES (across all datasets for this indicator)
    The U.S. Census Bureau defines a national poverty level (or household income) that varies by household size, number of children in a household, and age of householder. The national poverty level does not vary geographically even though cost of living is different across the United States. For the Bay Area, where cost of living is high and incomes are correspondingly high, an appropriate poverty level is 200% of poverty or twice the national poverty level, consistent with what was used for past equity work at MTC and ABAG. For comparison, however, both the national and 200% poverty levels are presented.

    For Vital Signs, the poverty rate is defined as the number of people (including children) living below twice the poverty level divided by the number of people for whom poverty status is determined. The household income definitions for poverty change each year to reflect inflation. The official poverty definition uses money income before taxes and does not include capital gains or non-cash benefits (such as public housing, Medicaid and food stamps).

    For the national poverty level definitions by year, see: US Census Bureau Poverty Thresholds - https://www.census.gov/data/tables/time-series/demo/income-poverty/historical-poverty-thresholds.html.

    For an explanation on how the Census Bureau measures poverty, see: How the Census Bureau Measures Poverty - https://www.census.gov/topics/income-poverty/poverty/guidance/poverty-measures.html.

    American Community Survey (ACS) 1-year data is used for larger geographies – Bay counties and most metropolitan area counties – while smaller geographies rely upon 5-year rolling average data due to their smaller sample sizes. Note that 2020 data uses the 5-year estimates because the ACS did not collect 1-year data for 2020.

    To be consistent across metropolitan areas, the poverty definition for non-Bay Area metros is twice the national poverty level. Data were not adjusted for varying income and cost of living levels across the metropolitan areas.

  6. l

    Low Poverty Index

    • data.lojic.org
    • hub.arcgis.com
    • +2more
    Updated Jul 5, 2023
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    Department of Housing and Urban Development (2023). Low Poverty Index [Dataset]. https://data.lojic.org/datasets/HUD::low-poverty-index
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    Dataset updated
    Jul 5, 2023
    Dataset authored and provided by
    Department of Housing and Urban Development
    Area covered
    Description

    LOW POVERTY INDEXSummary The low poverty index captures poverty in a given neighborhood. The index is based on the poverty rate (pv). The mean and standard error are estimated over the national distribution.The poverty rate is determined at the census tract level.InterpretationValues are inverted and percentile ranked nationally. The resulting values range from 0 to 100. The higher the score, the less exposure to poverty in a neighborhood.

    Data Source: American Community Survey, 2011-2015. Related AFFH-T Local Government, PHA and State Tables/Maps: Table 12; Map 12. School Proficiency Index.

    To learn more about the Low Poverty Index visit: https://www.hud.gov/program_offices/fair_housing_equal_opp/affh ; https://www.hud.gov/sites/dfiles/FHEO/documents/AFFH-T-Data-Documentation-AFFHT0006-July-2020.pdf, for questions about the spatial attribution of this dataset, please reach out to us at GISHelpdesk@hud.gov. Date of Coverage: 07/2020

  7. Poverty- San Mateo County- American Community Survey

    • data.wu.ac.at
    • performance.smcgov.org
    csv, json, xml
    Updated Aug 8, 2016
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    American Community Survey, Census Bureau-- S1701: POVERTY STATUS IN THE PAST 12 MONTHS (2016). Poverty- San Mateo County- American Community Survey [Dataset]. https://data.wu.ac.at/schema/performance_smcgov_org/M2U2dS1mc3Zn
    Explore at:
    json, csv, xmlAvailable download formats
    Dataset updated
    Aug 8, 2016
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Description

    Poverty threshold available at https://www.census.gov/hhes/www/poverty/data/threshld/index.html

    Additional information about how the Census Bureau measures poverty is available at https://www.census.gov/hhes/www/poverty/about/overview/measure.html

    How Poverty is Calculated in the ACS

    Poverty statistics presented in ACS reports and tables adhere to the standards specified by the Office of Management and Budget in Statistical Policy Directive 14. The Census Bureau uses a set of dollar value thresholds that vary by family size and composition to determine who is in poverty. Further, poverty thresholds for people living alone or with nonrelatives (unrelated individuals) and two-person families vary by age (under 65 years or 65 years and older).

    If a family’s total income is less than the dollar value of the appropriate threshold, then that family and every individual in it are considered to be in poverty. Similarly, if an unrelated individual’s total income is less than the appropriate threshold, then that individual is considered to be in poverty. The poverty thresholds do not vary geographically. They are updated annually to allow for changes in the cost of living (inflation factor) using the Consumer Price Index (CPI).

    Poverty status was determined for all people except institutionalized people, people in military group quarters, people in college dormitories, and unrelated individuals under 15 years old. These groups were excluded from the numerator and denominator when calculating poverty rates.

    Since the ACS is a continuous survey, people respond throughout the year. Because the income items specify a period covering the last 12 months, the appropriate poverty thresholds are determined by multiplying the base-year poverty thresholds (1982) by the monthly inflation factor based on the 12 monthly CPIs and the base-year CPI. (Source: https://www.census.gov/hhes/www/poverty/poverty-cal-in-acs.pdf)

  8. A

    ‘School Neighborhood Poverty Estimates, 2017-18’ analyzed by Analyst-2

    • analyst-2.ai
    Updated Dec 18, 2018
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    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com) (2018). ‘School Neighborhood Poverty Estimates, 2017-18’ analyzed by Analyst-2 [Dataset]. https://analyst-2.ai/analysis/data-gov-school-neighborhood-poverty-estimates-2017-18-fdf8/latest
    Explore at:
    Dataset updated
    Dec 18, 2018
    Dataset authored and provided by
    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com)
    License

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

    Description

    Analysis of ‘School Neighborhood Poverty Estimates, 2017-18’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/117a7cb7-0c50-46a1-888e-4a95b323fdb9 on 12 February 2022.

    --- Dataset description provided by original source is as follows ---

    The 2017-2018 School Neighborhood Poverty Estimates are based on school locations from the 2017-2018 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 2014-2018 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.

    --- Original source retains full ownership of the source dataset ---

  9. a

    Poverty Rate by HRA

    • equity-indicators-kingcounty.hub.arcgis.com
    Updated May 16, 2023
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    King County (2023). Poverty Rate by HRA [Dataset]. https://equity-indicators-kingcounty.hub.arcgis.com/datasets/poverty-rate-by-hra
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    Dataset updated
    May 16, 2023
    Dataset authored and provided by
    King County
    Area covered
    Description

    This dataset contains details about income below 200 percent of the Federal Poverty Level (FPL) in King County by Health Reporting Area (HRA) for 2021. It has been developed for the Determinant of Equity - Jobs and Jobs Training presentation. It includes information about Poverty Rate equity indicator. Fields describe the total population for whom poverty status is determined (Denominator), population below 200% of FPL (Numerator), the type of equity indicator being measured (Indicator), and the value that describes this measurement (Indicator Value).

    For more information about King County's equity efforts, please see:

    Equity, Racial & Social Justice Vision Ordinance 16948 describing the determinates of equity Determinants of Equity and Data Tool

  10. School Neighborhood Poverty Estimates, 2017-18

    • catalog.data.gov
    • datasets.ai
    • +2more
    Updated Oct 21, 2024
    + more versions
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    National Center for Education Statistics (NCES) (2024). School Neighborhood Poverty Estimates, 2017-18 [Dataset]. https://catalog.data.gov/dataset/school-neighborhood-poverty-estimates-2017-18-72403
    Explore at:
    Dataset updated
    Oct 21, 2024
    Dataset provided by
    National Center for Education Statisticshttps://nces.ed.gov/
    Description

    The 2017-2018 School Neighborhood Poverty Estimates are based on school locations from the 2017-2018 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 2014-2018 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.

  11. d

    Low Food Access Areas

    • catalog.data.gov
    • datasets.ai
    • +2more
    Updated Feb 4, 2025
    + more versions
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    City of Washington, DC (2025). Low Food Access Areas [Dataset]. https://catalog.data.gov/dataset/low-food-access-areas
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    Dataset updated
    Feb 4, 2025
    Dataset provided by
    City of Washington, DC
    Description

    Polygons in this layer represent low food access areas: areas of the District of Columbia which are estimated to be more than a 10-minute walk from the nearest full-service grocery store. These have been merged with Census poverty data to estimate how much of the population within these areas is food insecure (below 185% of the federal poverty line in addition to living in a low food access area).Office of Planning GIS followed several steps to create this layer, including: transit analysis, to eliminate areas of the District within a 10-minute walk of a grocery store; non-residential analysis, to eliminate areas of the District which do not contain residents and cannot classify as low food access areas (such as parks and the National Mall); and Census tract division, to estimate population and poverty rates within the newly created polygon boundaries.Fields contained in this layer include:Intermediary calculation fields for the aforementioned analysis, and:PartPop2: The total population estimated to live within the low food access area polygon (derived from Census tract population, assuming even distribution across the polygon after removing non-residential areas, followed by the removal of population living within a grocery store radius.)PrtOver185: The portion of PartPop2 which is estimated to have household income above 185% of the federal poverty line (the food secure population)PrtUnd185: The portion of PartPop2 which is estimated to have household income below 185% of the federal poverty line (the food insecure population)PercentUnd185: A calculated field showing PrtUnd185 as a percent of PartPop2. This is the percent of the population in the polygon which is food insecure (both living in a low food access area and below 185% of the federal poverty line).Note that the polygon representing Joint Base Anacostia-Bolling was removed from this analysis. While technically classifying as a low food access area based on the OP Grocery Stores layer (since the JBAB Commissary, which only serves military members, is not included in that layer), it is recognized that those who do live on the base have access to the commissary for grocery needs.Last updated November 2017.

  12. T

    Vital Signs: Poverty - Bay Area (2022)

    • data.bayareametro.gov
    application/rdfxml +5
    Updated Jan 3, 2023
    + more versions
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    (2023). Vital Signs: Poverty - Bay Area (2022) [Dataset]. https://data.bayareametro.gov/dataset/Vital-Signs-Poverty-Bay-Area-2022-/g2wq-gn4h
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    xml, csv, json, application/rssxml, application/rdfxml, tsvAvailable download formats
    Dataset updated
    Jan 3, 2023
    Area covered
    San Francisco Bay Area
    Description

    VITAL SIGNS INDICATOR
    Poverty (EQ5)

    FULL MEASURE NAME
    The share of the population living in households that earn less than 200 percent of the federal poverty limit

    LAST UPDATED
    January 2023

    DESCRIPTION
    Poverty refers to the share of the population living in households that earn less than 200 percent of the federal poverty limit, which varies based on the number of individuals in a given household. It reflects the number of individuals who are economically struggling due to low household income levels.

    DATA SOURCE
    U.S Census Bureau: Decennial Census - http://www.nhgis.org
    1980-2000

    U.S. Census Bureau: American Community Survey - https://data.census.gov/
    2007-2021
    Form C17002

    CONTACT INFORMATION
    vitalsigns.info@mtc.ca.gov

    METHODOLOGY NOTES (across all datasets for this indicator)
    The U.S. Census Bureau defines a national poverty level (or household income) that varies by household size, number of children in a household, and age of householder. The national poverty level does not vary geographically even though cost of living is different across the United States. For the Bay Area, where cost of living is high and incomes are correspondingly high, an appropriate poverty level is 200% of poverty or twice the national poverty level, consistent with what was used for past equity work at MTC and ABAG. For comparison, however, both the national and 200% poverty levels are presented.

    For Vital Signs, the poverty rate is defined as the number of people (including children) living below twice the poverty level divided by the number of people for whom poverty status is determined. The household income definitions for poverty change each year to reflect inflation. The official poverty definition uses money income before taxes and does not include capital gains or non-cash benefits (such as public housing, Medicaid and food stamps).

    For the national poverty level definitions by year, see: US Census Bureau Poverty Thresholds - https://www.census.gov/data/tables/time-series/demo/income-poverty/historical-poverty-thresholds.html.

    For an explanation on how the Census Bureau measures poverty, see: How the Census Bureau Measures Poverty - https://www.census.gov/topics/income-poverty/poverty/guidance/poverty-measures.html.

    American Community Survey (ACS) 1-year data is used for larger geographies – Bay counties and most metropolitan area counties – while smaller geographies rely upon 5-year rolling average data due to their smaller sample sizes. Note that 2020 data uses the 5-year estimates because the ACS did not collect 1-year data for 2020.

    To be consistent across metropolitan areas, the poverty definition for non-Bay Area metros is twice the national poverty level. Data were not adjusted for varying income and cost of living levels across the metropolitan areas.

  13. School Neighborhood Poverty Estimates, 2016-17

    • catalog.data.gov
    • datasets.ai
    • +2more
    Updated Oct 21, 2024
    + more versions
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    National Center for Education Statistics (NCES) (2024). School Neighborhood Poverty Estimates, 2016-17 [Dataset]. https://catalog.data.gov/dataset/school-neighborhood-poverty-estimates-2016-2017-dbe26
    Explore at:
    Dataset updated
    Oct 21, 2024
    Dataset provided by
    National Center for Education Statisticshttps://nces.ed.gov/
    Description

    The 2016-2017 School Neighborhood Poverty Estimates are based on school locations from the 2016-2017 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 2013-2017 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.

  14. A

    ‘School Neighborhood Poverty Estimates, 2016-2017’ analyzed by Analyst-2

    • analyst-2.ai
    Updated Feb 12, 2022
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    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com) (2022). ‘School Neighborhood Poverty Estimates, 2016-2017’ analyzed by Analyst-2 [Dataset]. https://analyst-2.ai/analysis/data-gov-school-neighborhood-poverty-estimates-2016-2017-0b25/ab8aa368/?iid=000-202&v=presentation
    Explore at:
    Dataset updated
    Feb 12, 2022
    Dataset authored and provided by
    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com)
    License

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

    Description

    Analysis of ‘School Neighborhood Poverty Estimates, 2016-2017’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/b6e31e97-5692-4850-8360-b32bc28117ba on 12 February 2022.

    --- Dataset description provided by original source is as follows ---

    The 2016-2017 School Neighborhood Poverty Estimates are based on school locations from the 2016-2017 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 2013-2017 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.

    --- Original source retains full ownership of the source dataset ---

  15. PovertyEstimates

    • kaggle.com
    Updated Mar 4, 2023
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    DongYK (2023). PovertyEstimates [Dataset]. https://www.kaggle.com/datasets/dongyk/povertyestimates
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Mar 4, 2023
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    DongYK
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    This dataset is the estimation of Poverty by county at 2020.

    'POVAL_2020': Estimate of people of all ages in poverty 2020 'PCTPOVALL_2020': Estimated percent of people of all ages in poverty 2020 'MEDHHINC_2020': Estimate of median household income 2020

    https://www.ers.usda.gov/data-products/county-level-data-sets/county-level-data-sets-download-data/

  16. d

    DOHMH COVID-19 Antibody-by-Neighborhood Poverty

    • catalog.data.gov
    • data.cityofnewyork.us
    Updated Jul 7, 2024
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    data.cityofnewyork.us (2024). DOHMH COVID-19 Antibody-by-Neighborhood Poverty [Dataset]. https://catalog.data.gov/dataset/dohmh-covid-19-antibody-by-neighborhood-poverty
    Explore at:
    Dataset updated
    Jul 7, 2024
    Dataset provided by
    data.cityofnewyork.us
    Description

    This dataset contains information on antibody testing for COVID-19: the number of people who received a test, the number of people with positive results, the percentage of people tested who tested positive, and the rate of testing per 100,000 people, stratified by ZIP Code Tabulation Area (ZCTA) neighborhood poverty group. These data can also be accessed here: https://github.com/nychealth/coronavirus-data/blob/master/totals/antibody-by-poverty.csv Exposure to COVID-19 can be detected by measuring antibodies to the disease in a person’s blood, which can indicate that a person may have had an immune response to the virus. Antibodies are proteins produced by the body’s immune system that can be found in the blood. People can test positive for antibodies after they have been exposed, sometimes when they no longer test positive for the virus itself. It is important to note that the science around COVID-19 antibody tests is evolving rapidly and there is still much uncertainty about what individual antibody test results mean for a single person and what population-level antibody test results mean for understanding the epidemiology of COVID-19 at a population level. These data only provide information on people tested. People receiving an antibody test do not reflect all people in New York City; therefore, these data may not reflect antibody prevalence among all New Yorkers. Increasing instances of screening programs further impact the generalizability of these data, as screening programs influence who and how many people are tested over time. Examples of screening programs in NYC include: employers screening their workers (e.g., hospitals), and long-term care facilities screening their residents. In addition, there may be potential biases toward people receiving an antibody test who have a positive result because people who were previously ill are preferentially seeking testing, in addition to the testing of persons with higher exposure (e.g., health care workers, first responders.) Neighborhood-level poverty groups were classified in a manner consistent with Health Department practices to describe and monitor disparities in health in NYC. Neighborhood poverty measures are defined as the percentage of people earning below the Federal Poverty Threshold (FPT) within a ZCTA. The standard cut-points for defining categories of neighborhood-level poverty in NYC are: • Low: <10% of residents in ZCTA living below the FPT • Medium: 10% to <20% • High: 20% to <30% • Very high: ≥30% residents living below the FPT The ZCTAs used for classification reflect the first non-missing address within NYC for each person reported with an antibody test result. Rates were calculated using interpolated intercensal population estimates updated in 2019. These rates differ from previously reported rates based on the 2000 Census or previous versions of population estimates. The Health Department produced these population estimates based on estimates from the U.S. Census Bureau and NYC Department of City Planning. Rates for poverty were calculated using direct standardization for age at diagnosis and weighting by the US 2000 standard population. Antibody tests are categorized based on the date of specimen collection and are aggregated by full weeks starting each Sunday and ending on Saturday. For example, a person whose blood was collected for antibody testing on Wednesday, May 6 would be categorized as tested during the week ending May 9. A person tested twice in one week would only be counted once in that week. This dataset includes testing data beginning April 5, 2020. Data are updated daily, and the dataset preserves historical records and source data changes, so each extract date reflects the current copy of the data as of that date. For example, an extract date of 11/04/2020 and extract date of 11/03/2020 will both contain all records as they were as of that extract date. Without filtering or grouping by extract date, an analysis will almost certain

  17. Poverty-Level Wages in the USA Dataset (1973-2022)

    • kaggle.com
    Updated Nov 7, 2023
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    asaniczka (2023). Poverty-Level Wages in the USA Dataset (1973-2022) [Dataset]. http://doi.org/10.34740/kaggle/ds/3836090
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Nov 7, 2023
    Dataset provided by
    Kaggle
    Authors
    asaniczka
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Area covered
    United States
    Description

    This dataset provides information on poverty-level wages in the United States from 1973 to 2022.

    It includes data on both annual and hourly poverty-level wages, as well as wage shares for different income brackets.

    The dataset is based on the Economic Policy Institute’s State of Working America Data Library, which offers comprehensive economic data for analyzing trends and patterns in the labor market.

    Intresting Task Ideas:

    1. Analyze the trend of annual poverty-level wages over the years.
    2. Compare the hourly poverty-level wages between men and women.
    3. Investigate the share of workers earning below poverty-level wages based on race.
    4. Explore the distribution of wages across different poverty wage ranges.
    5. Examine the income disparities across different income brackets (0-75%, 75-100%, etc.) for men and women.
    6. Determine the proportion of workers earning above the poverty level (300%+) over time.
    7. Calculate the percentage change in poverty-level wages from one year to another.

    If you find this dataset valuable, don't forget to hit the upvote button! 😊💝

    Checkout my other datasets

    USA Wage Comparison for College vs. High School

    Productivity and Hourly Compensation

    150K TMDb TV Shows

    USA Unemployment Rates by Demographics & Race

    Gender Wage Gap in the USA

    Photo by Jon Tyson on Unsplash

  18. A

    ‘At-risk-of-poverty rate before social transfers by age group - EU-SILC...

    • analyst-2.ai
    Updated Sep 30, 2021
    + more versions
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    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com) (2021). ‘At-risk-of-poverty rate before social transfers by age group - EU-SILC survey’ analyzed by Analyst-2 [Dataset]. https://analyst-2.ai/analysis/data-europa-eu-at-risk-of-poverty-rate-before-social-transfers-by-age-group-eu-silc-survey-114d/27a6df86/?iid=006-388&v=presentation
    Explore at:
    Dataset updated
    Sep 30, 2021
    Dataset authored and provided by
    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com)
    License

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

    Description

    Analysis of ‘At-risk-of-poverty rate before social transfers by age group - EU-SILC survey’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://data.europa.eu/data/datasets/da7herajjfvbaazvwaue2w on 30 September 2021.

    --- Dataset description provided by original source is as follows ---

    The share of persons with an equivalised disposable income, before social transfers, below the at-risk-of-poverty threshold. Retirement and survivor's pensions are counted as income before transfers and not as social transfers.

    --- Original source retains full ownership of the source dataset ---

  19. g

    Poverty risk rates by gender and migratory status of persons | gimi9.com

    • gimi9.com
    Updated Dec 5, 2024
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    (2024). Poverty risk rates by gender and migratory status of persons | gimi9.com [Dataset]. https://gimi9.com/dataset/eu_1213478d-84ff-50de-a015-d594b27e56b4/
    Explore at:
    Dataset updated
    Dec 5, 2024
    Description

    The dataset describes the poverty risk rates in NRW by gender and migration status of the persons. For comparison, the Federal Median is also listed. The poverty risk rate is an indicator of relative income poverty. It indicates the proportion of people with an income below the poverty risk threshold of the population. The poverty risk rate is defined as the number of persons with an equivalised income (calculated on the basis of the new OECD scale) of less than 60% of the median equivalised income of the total population per 100 persons of the population. The risk-of-poverty threshold is the income value below which income poverty is to be referred to. Equivalised income is a demand-weighted per capita income per household member calculated on the basis of net household income.

  20. School Neighborhood Poverty Estimates, 2015-16

    • catalog.data.gov
    • s.cnmilf.com
    Updated Oct 21, 2024
    + more versions
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    National Center for Education Statistics (NCES) (2024). School Neighborhood Poverty Estimates, 2015-16 [Dataset]. https://catalog.data.gov/dataset/school-neighborhood-poverty-estimates-2015-2016-01098
    Explore at:
    Dataset updated
    Oct 21, 2024
    Dataset provided by
    National Center for Education Statisticshttps://nces.ed.gov/
    Description

    The 2015-2016 School Neighborhood Poverty Estimates are based on school locations from the 2015-2016 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 2012-2016 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.

Share
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Champaign County Regional Planning Commission (2024). Poverty Rate [Dataset]. https://data.ccrpc.org/dataset/poverty-rate

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).

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