45 datasets found
  1. National Neighborhood Data Archive (NaNDA): Socioeconomic Status and...

    • icpsr.umich.edu
    • archive.icpsr.umich.edu
    ascii, delimited, r +3
    Updated Jan 22, 2025
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    Clarke, Philippa; Melendez, Robert; Noppert, Grace; Chenoweth, Megan; Gypin, Lindsay (2025). National Neighborhood Data Archive (NaNDA): Socioeconomic Status and Demographic Characteristics of Census Tracts and ZIP Code Tabulation Areas, United States, 1990-2022 [Dataset]. http://doi.org/10.3886/ICPSR38528.v5
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    stata, delimited, sas, spss, r, asciiAvailable download formats
    Dataset updated
    Jan 22, 2025
    Dataset provided by
    Inter-university Consortium for Political and Social Researchhttps://www.icpsr.umich.edu/web/pages/
    Authors
    Clarke, Philippa; Melendez, Robert; Noppert, Grace; Chenoweth, Megan; Gypin, Lindsay
    License

    https://www.icpsr.umich.edu/web/ICPSR/studies/38528/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/38528/terms

    Time period covered
    1990 - 2022
    Area covered
    United States
    Description

    These datasets contain measures of socioeconomic and demographic characteristics by U.S. census tract for the years 1990-2022 and ZIP code tabulation area (ZCTA) for the years 2008-2022. Example measures include population density; population distribution by race, ethnicity, age, and income; income inequality by race and ethnicity; and proportion of population living below the poverty level, receiving public assistance, and female-headed or single parent families with kids. The datasets also contain a set of theoretically derived measures capturing neighborhood socioeconomic disadvantage and affluence, as well as a neighborhood index of Hispanic, foreign born, and limited English.

  2. US Socioeconomic Indicators Data Package

    • johnsnowlabs.com
    csv
    Updated Jan 20, 2021
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    John Snow Labs (2021). US Socioeconomic Indicators Data Package [Dataset]. https://www.johnsnowlabs.com/marketplace/us-socioeconomic-indicators-data-package/
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    csvAvailable download formats
    Dataset updated
    Jan 20, 2021
    Dataset authored and provided by
    John Snow Labs
    Description

    This data package has the purpose to offer data for socio-economic indicators and to cover as much as possible the entire this indicator category with regard to the indicator type and to the geographic level. The major sources of the data are the U.S. Census Bureau and the U.S. Bureau for Labor Statistics. Another used sources of data are the U.S. Department of Housing and Urban Development and the U.S. Department of Housing and the U.S. Department Of Agriculture (Economic Research Service).

  3. U.S. household income distribution 2023

    • statista.com
    Updated Sep 16, 2024
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    Statista (2024). U.S. household income distribution 2023 [Dataset]. https://www.statista.com/statistics/203183/percentage-distribution-of-household-income-in-the-us/
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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, just over 50 percent of Americans had an annual household income that was less than 75,000 U.S. dollars. The median household income was 80,610 U.S. dollars in 2023. Income and wealth in the United States After the economic recession in 2009, income inequality in the U.S. is more prominent across many metropolitan areas. The Northeast region is regarded as one of the wealthiest in the country. Maryland, New Jersey, and Massachusetts were among the states with the highest median household income in 2020. In terms of income by race and ethnicity, the average income of Asian households was 94,903 U.S. dollars in 2020, while the median income for Black households was around half of that figure. What is the U.S. poverty threshold? The U.S. Census Bureau annually updates its list of poverty levels. Preliminary estimates show that the average poverty threshold for a family of four people was 26,500 U.S. dollars in 2021, which is around 100 U.S. dollars less than the previous year. There were an estimated 37.9 million people in poverty across the United States in 2021, which was around 11.6 percent of the population. Approximately 19.5 percent of those in poverty were Black, while 8.2 percent were white.

  4. l

    ACS 5YR Socioeconomic Estimate Data by State

    • data.lojic.org
    • opendata.atlantaregional.com
    • +2more
    Updated Aug 21, 2023
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    Department of Housing and Urban Development (2023). ACS 5YR Socioeconomic Estimate Data by State [Dataset]. https://data.lojic.org/datasets/HUD::acs-5yr-socioeconomic-estimate-data-by-state/geoservice?geometry=-179.684%2C-89.977%2C180.316%2C67.776
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    Dataset updated
    Aug 21, 2023
    Dataset authored and provided by
    Department of Housing and Urban Development
    Area covered
    Description

    The American Community Survey (ACS) 5 Year 2016-2020 socioeconomic estimate data is a subset of information derived from the following census tables:B08013 - Aggregate Travel Time To Work Of Workers By Sex;B08303 - Travel Time To Work;B17019 - Poverty Status In The Past 12 Months Of Families By Household Type By Tenure;B17021 - Poverty Status Of Individuals In The Past 12 Months By Living Arrangement;B19001 - Household Income In The Past 12 Months;B19013 - Median Household Income In The Past 12 Months;B19025 - Aggregate Household Income In The Past 12 Months;B19113 - Median Family Income In The Past 12 Months;B19202 - Median Non-family Household Income In The Past 12 Months;B23001 - Sex By Age By Employment Status For The Population 16 Years And Over;B25014 - Tenure By Occupants Per Room;B25026 - Total Population in Occupied Housing Units by Tenure by year Householder Moved into Unit;B25106 - Tenure By Housing Costs As A Percentage Of Household Income In The Past 12 Months;C24010 - Sex By Occupation For The Civilian Employed Population 16 Years And Over;B20004 - Median Earnings In the Past 12 Months (In 2015 Inflation-Adjusted Dollars) by Sex by Educational Attainment for the Population 25 Years and Over;B23006 - Educational Attainment by Employment Status for the Population 25 to 64 Years, and;B24021 - Occupation By Median Earnings In The Past 12 Months (In 2015 Inflation-Adjusted Dollars) For The Full-Time, Year-Round Civilian Employed Population 16 Years And Over.

    To learn more about the American Community Survey (ACS), and associated datasets visit: https://www.census.gov/programs-surveys/acs, for questions about the spatial attribution of this dataset, please reach out to us at GISHelpdesk@hud.gov. Data Dictionary: DD_ACS 5-Year Socioeconomic Estimate Data by StateDate of Coverage: 2016-2020

  5. a

    2018 ACS Demographic & Socio-Economic Data Of USA At Census Tract Level

    • one-health-data-hub-osu-geog.hub.arcgis.com
    Updated May 22, 2024
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    snakka_OSU_GEOG (2024). 2018 ACS Demographic & Socio-Economic Data Of USA At Census Tract Level [Dataset]. https://one-health-data-hub-osu-geog.hub.arcgis.com/items/5b67f243e6584ef1986f815932020034
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    Dataset updated
    May 22, 2024
    Dataset authored and provided by
    snakka_OSU_GEOG
    Area covered
    Description

    Data SourcesAmerican Community Survey (ACS):Conducted by: U.S. Census BureauDescription: The ACS is an ongoing survey that provides detailed demographic and socio-economic data on the population and housing characteristics of the United States.Content: The survey collects information on various topics such as income, education, employment, health insurance coverage, and housing costs and conditions.Frequency: The ACS offers more frequent and up-to-date information compared to the decennial census, with annual estimates produced based on a rolling sample of households.Purpose: ACS data is essential for policymakers, researchers, and communities to make informed decisions and address the evolving needs of the population.CDC/ATSDR Social Vulnerability Index (SVI):Created by: ATSDR’s Geospatial Research, Analysis & Services Program (GRASP)Utilized by: CDCDescription: The SVI is designed to identify and map communities that are most likely to need support before, during, and after hazardous events.Content: SVI ranks U.S. Census tracts based on 15 social factors, including unemployment, minority status, and disability, and groups them into four related themes. Each tract receives rankings for each Census variable and for each theme, as well as an overall ranking, indicating its relative vulnerability.Purpose: SVI data provides insights into the social vulnerability of communities at the census tract level, helping public health officials and emergency response planners allocate resources effectively.Utilization and IntegrationBy integrating data from both the ACS and the SVI, this dataset enables an in-depth analysis and understanding of various socio-economic and demographic indicators at the census tract level. This integrated data is valuable for research, policymaking, and community planning purposes, allowing for a comprehensive understanding of social and economic dynamics across different geographical areas in the United States.ApplicationsLocalized Interventions: Facilitates the development of localized interventions to address the needs of vulnerable populations within specific census tracts.Resource Allocation: Assists emergency response planners in allocating resources more effectively based on community vulnerability at the census tract level.Research: Provides a detailed dataset for academic and applied research in socio-economic and demographic studies at a granular census tract level.Community Planning: Supports the planning and development of community programs and initiatives aimed at improving living conditions and reducing vulnerabilities within specific census tract areas.Note: Due to limitations in the data environment, variable names may be truncated. Refer to the provided table for a clear understanding of the variables.CSV Variable NameShapefile Variable NameDescriptionStateNameStateNameName of the stateStateFipsStateFipsState-level FIPS codeState nameStateNameName of the stateCountyNameCountyNameName of the countyCensusFipsCensusFipsCounty-level FIPS codeState abbreviationStateFipsState abbreviationCountyFipsCountyFipsCounty-level FIPS codeCensusFipsCensusFipsCounty-level FIPS codeCounty nameCountyNameName of the countyAREA_SQMIAREA_SQMITract area in square milesE_TOTPOPE_TOTPOPPopulation estimates, 2014-2018 ACSEP_POVEP_POVPercentage of persons below poverty estimateEP_UNEMPEP_UNEMPUnemployment Rate estimateEP_HBURDEP_HBURDHousing cost burdened occupied housing units with annual income less than $75,000EP_UNINSUREP_UNINSURUninsured in the total civilian noninstitutionalized population estimate, 2014-2018 ACSEP_PCIEP_PCIPer capita income estimate, 2014-2018 ACSEP_DISABLEP_DISABLPercentage of civilian noninstitutionalized population with a disability estimate, 2014-2018 ACSEP_SNGPNTEP_SNGPNTPercentage of single parent households with children under 18 estimate, 2014-2018 ACSEP_MINRTYEP_MINRTYPercentage minority (all persons except white, non-Hispanic) estimate, 2014-2018 ACSEP_LIMENGEP_LIMENGPercentage of persons (age 5+) who speak English "less than well" estimate, 2014-2018 ACSEP_MUNITEP_MUNITPercentage of housing in structures with 10 or more units estimateEP_MOBILEEP_MOBILEPercentage of mobile homes estimateEP_CROWDEP_CROWDPercentage of occupied housing units with more people than rooms estimateEP_NOVEHEP_NOVEHPercentage of households with no vehicle available estimateEP_GROUPQEP_GROUPQPercentage of persons in group quarters estimate, 2014-2018 ACSBelow_5_yrBelow_5_yrUnder 5 years: Percentage of Total populationBelow_18_yrBelow_18_yrUnder 18 years: Percentage of Total population18-39_yr18_39_yr18-39 years: Percentage of Total population40-64_yr40_64_yr40-64 years: Percentage of Total populationAbove_65_yrAbove_65_yrAbove 65 years: Percentage of Total populationPop_malePop_malePercentage of total population malePop_femalePop_femalePercentage of total population femaleWhitewhitePercentage population of white aloneBlackblackPercentage population of black or African American aloneAmerican_indianamerican_iPercentage population of American Indian and Alaska native aloneAsianasianPercentage population of Asian aloneHawaiian_pacific_islanderhawaiian_pPercentage population of Native Hawaiian and Other Pacific Islander aloneSome_othersome_otherPercentage population of some other race aloneMedian_tot_householdsmedian_totMedian household income in the past 12 months (in 2019 inflation-adjusted dollars) by household size – total householdsLess_than_high_schoolLess_than_Percentage of Educational attainment for the population less than 9th grades and 9th to 12th grade, no diploma estimateHigh_schoolHigh_schooPercentage of Educational attainment for the population of High school graduate (includes equivalency)Some_collegeSome_collePercentage of Educational attainment for the population of Some college, no degreeAssociates_degreeAssociatesPercentage of Educational attainment for the population of associate degreeBachelor’s_degreeBachelor_sPercentage of Educational attainment for the population of Bachelor’s degreeMaster’s_degreeMaster_s_dPercentage of Educational attainment for the population of Graduate or professional degreecomp_devicescomp_devicPercentage of Household having one or more types of computing devicesInternetInternetPercentage of Household with an Internet subscriptionBroadbandBroadbandPercentage of Household having Broadband of any typeSatelite_internetSatelite_iPercentage of Household having Satellite Internet serviceNo_internetNo_internePercentage of Household having No Internet accessNo_computerNo_computePercentage of Household having No computer

  6. AmeriCorps Participant Demographics Data

    • catalog-dev.data.gov
    • data.americorps.gov
    • +1more
    Updated Mar 20, 2025
    + more versions
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    AmeriCorps (2025). AmeriCorps Participant Demographics Data [Dataset]. https://catalog-dev.data.gov/dataset/americorps-participant-demographics-data-a1985
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    Dataset updated
    Mar 20, 2025
    Dataset provided by
    AmeriCorpshttp://www.americorps.gov/
    Description

    This dataset provides comparisons of demographic group prevalence in AmeriCorps Member/Volunteers populations to that of the greater U.S. population. The odds ratio analysis was completed by the Office of the Chief Data Officer. Population estimates were obtained from U.S. Census Bureau data reported in American Community Survey 5-Year tables DP05 (total U.S. populations) and S1701 (U.S. populations below poverty line), and socioeconomic status-related microdata maintained by IPUMS USA. See Attached Document 'AmeriCorps Demographic Analysis Procedure.pdf' for a full technical documentation of the analysis.

  7. o

    National Neighborhood Data Archive (NaNDA): Socioeconomic Status and...

    • openicpsr.org
    Updated Jul 15, 2024
    + more versions
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    Philippa Clarke; Robert Melendez; Lindsay Gypin (2024). National Neighborhood Data Archive (NaNDA): Socioeconomic Status and Demographic Characteristics of Census Tracts, 1990-2010 [Dataset]. http://doi.org/10.3886/E207962V1
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    Dataset updated
    Jul 15, 2024
    Dataset provided by
    University of Michigan. Institute for Social Research
    Authors
    Philippa Clarke; Robert Melendez; Lindsay Gypin
    License

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

    Time period covered
    1990 - 2010
    Area covered
    United States
    Description

    This dataset contains measures of socioeconomic and demographic characteristics by US census tract 1990-2010. Example measures include population density; population distribution by race, ethnicity, age, and income; and proportion of population living below the poverty level, receiving public assistance, and female-headed families. The dataset also contains a set of index variables to represent neighborhood disadvantage and affluence.

  8. U.S. poverty rate in the United States 2023, by race and ethnicity

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

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

  9. Birth rate by poverty status in the U.S. 2005-2023

    • statista.com
    Updated Oct 25, 2024
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    Statista (2024). Birth rate by poverty status in the U.S. 2005-2023 [Dataset]. https://www.statista.com/statistics/562541/birth-rate-by-poverty-status-in-the-us/
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    Dataset updated
    Oct 25, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    In 2023, women in households with an income below the poverty threshold had the highest birth rate in the United States, at 72 births per 1,000 women.

  10. o

    National Neighborhood Data Archive (NaNDA): Neighborhood Socioeconomic and...

    • doi.org
    • openicpsr.org
    • +1more
    Updated Aug 5, 2019
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    Philippa Clarke; Robert Melendez (2019). National Neighborhood Data Archive (NaNDA): Neighborhood Socioeconomic and Demographic Characteristics of Census Tracts, United States, 2000-2010 [Dataset]. http://doi.org/10.3886/E111107V1
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    Dataset updated
    Aug 5, 2019
    Dataset provided by
    University of Michigan. Institute for Social Research
    Authors
    Philippa Clarke; Robert Melendez
    License

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

    Time period covered
    2000 - 2010
    Area covered
    United States
    Description

    This dataset contains measures of socioeconomic and demographic characteristics by US census tract for the years 2000-2010. Example measures include population density; population distribution by race, ethnicity, age, and income; and proportion of population living below the poverty level, receiving public assistance, and female-headed families. The dataset also contains a set of index variables to represent neighborhood disadvantage and affluence.A curated version of this data is available through ICPSR at http://dx.doi.org/10.3886/ICPSR38528.v1.

  11. d

    US Social Vulnerability by Census Block Groups

    • dataone.org
    Updated Nov 8, 2023
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    Bryan, Michael (2023). US Social Vulnerability by Census Block Groups [Dataset]. http://doi.org/10.7910/DVN/ARBHPK
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    Dataset updated
    Nov 8, 2023
    Dataset provided by
    Harvard Dataverse
    Authors
    Bryan, Michael
    Area covered
    United States
    Description

    blockgroupvulnerability OPPORTUNITY The US Centers for Disease Control (CDC) publishes a set of percentiles that compare US geographies by vulnerability across household, socioeconomic, racial/ethnic and housing themes. These Social Vulnerability Indexes (SVI) were originally intended to to help public health officials and emergency response planners identify communities that will need support around an event. They are generally valuable for any public interest that wants to relate themselves to needy communities by geography. The SVI publication and its basis variables are provided at the Census tract level of geographic detail. The Census' American Community Survey is available down the to the block group level, however. Recasting the SVI methods at this lower level of geography allows it to be tied to thousands of other demographic variables available. Because the SVI relies on ACS variables only available at the tract level, a projection model needs to applied to approximate its results using blockgroup level ACS variables. The blockgroupvulnerability dataset casts a prediction for the CDCs logic for a new contribution to the Open Environments blockgroup series available on Harvard's dataverse platform. DATA The CDC's annual SVI publication starts with 23 simple derivations using 50 ACS Census variables. Next the SVI process ranks census geographies to calculate a rank for each, where Percentile Rank = (Rank-1) / (N-1). The SVI themes are then calculated at the tract level as a percentile rank of a sum of the percentile ranks of the first level ACS derived variables. Finally, the overall ranking is taken as the sum of the theme percentile rankings. The SVI data publication is keyed by geography (7 cols) where ultimately the Census Tract FIPS code is 2 State + 3 County + 4 Tract + 2 Tract Decimals eg, 56043000301 is 56 Wyoming, 043 Washakie County, Tract 3.01 republishes Census demographics called 'adjunct variables' including area, population, households and housing units from the ACS daytime population taken from LandScan 2020 estimates derives 23 SVI variables from 50 ACS 5 Year variables with each having an estimate (E_), estimate precentage (EP_), margin of error (M_), margin percentage (MP_) and flag variable (F_) for those greater than 90% or less than 10% provides the final 4 themes and a composite SVI percentile annually vars = ['ST', 'STATE', 'ST_ABBR', 'STCNTY', 'COUNTY', 'FIPS', 'LOCATION'] +\ ['SNGPNT','LIMENG','DISABL','AGE65','AGE17','NOVEH','MUNIT','MOBILE','GROUPQ','CROWD','UNINSUR','UNEMP','POV150','NOHSDP','HBURD','TWOMORE','OTHERRACE','NHPI','MINRTY','HISP','ASIAN','AIAN','AFAM','NOINT'] +\ ['TOTAL','THEME1','THEME2','THEME3','THEME4'] + \ ['AREA_SQMI', 'TOTPOP', 'DAYPOP', 'HU', 'HH'] knowns = vars + \ # Estimates, the result of calc against ACS vars [('E_'+v) for v in vars] + \ # Flag 0,1 whether this geog is in 90 percentile rank (its vulnerable) [('F_'+v) for v in vars] +\ # Margine of error for ACS calcs [('M_'+v) for v in vars] + \ # Margine of error for ACS calcs, as percentage [('MP_'+v) for v in vars] +\ # Estimates of ACS calcs, as percentage [('EP_'+v) for v in vars] + \ # Estimated percentile ranks [('EPL_'+v) for v in vars] + \ # Sum across var percentile ranks [('SPL_'+v) for v in vars]+ \ # Percentile rank of the sum of percentile ranks [('RPL_'+v) for v in vars] [c for c in svitract.columns if c not in knowns] The SVI themes range over [0,1] but the CDC uses -999 as an NA value; this is set for ~800 or 1% of tracts which have no total poulation. The themes are numbered: Socioeconomic Status – RPL_THEME1 Household Characteristics – RPL_THEME2 Racial & Ethnic Minority Status – RPL_THEME3 Housing Type & Transportation – RPL_THEME4 The themes with their variables and ACS sources are as follows: Unlike Census data, the CDC ranks Puerto Rico and Tribal tracts separately from the US otherwise. Theme SVI Variable ACS Table ACS Variables Socioeconomic E_UNINSUR S2701 S2701_C04_001E Socioeconomic E_UNEMP DP03 DP03_0005E Socioeconomic E_POV150 S1701 S1701_C01_040E Socioeconomic E_NOHSDP B06009 B06009_002E Socioeconomic E_HBURD S2503 S2503_C01_028E + S2503_C01_032E + S2503_C01_036E + S2503_C01_040E Household E_SNGPNT B11012 B11012_010E + B11012_015E Household E_LIMENG B16005 B16005_007E + B16005_008E + B16005_012E + B16005_013E + B16005_017E + B16005_018E + B16005_022E + B16005_023E + B16005_029E + B16005_030E + B16005_034E + B16005_035E + B16005_039E + B16005_040E + B16005_044E + B16005_045E Household E_DISABL DP02 DP02_0072E Household E_AGE65 S0101 S0101_C01_030E Household E_AGE17 B09001 B09001_001E Racial & Ethnic E_TWOMORE DP05 DP05_0083E Racial & Ethnic E_OTHERRACE DP05 DP05_0082E Racial & Ethnic E_NHPI DP05 DP05_0081E Racial & Ethnic E_MINRTY DP05 DP05_0071E + DP05_0078E + DP05_0079E + DP05_0080E + DP05_0081E + DP05_0082E + ... Visit https://dataone.org/datasets/sha256%3A3edd5defce2f25c7501953ca3e77c4f15a8c71251352373a328794f961755c1c for complete metadata about this dataset.

  12. Share of the population by income level in Latin America 2022

    • statista.com
    • ai-chatbox.pro
    Updated Jan 7, 2025
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    Statista (2025). Share of the population by income level in Latin America 2022 [Dataset]. https://www.statista.com/statistics/1334387/distribution-population-by-income-level-latin-america/
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    Dataset updated
    Jan 7, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2022
    Area covered
    Latin America, LAC
    Description

    In 2022, less than eight percent of the population in Latin America had either a high or upper-middle income level. Slightly over a fifth of the population fell in the non-poor with low incomes' stratum.

  13. n

    National Longitudinal Mortality Study

    • neuinfo.org
    • rrid.site
    • +2more
    Updated Jul 2, 2011
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    (2011). National Longitudinal Mortality Study [Dataset]. http://identifiers.org/RRID:SCR_008946
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    Dataset updated
    Jul 2, 2011
    Description

    A database based on a random sample of the noninstitutionalized population of the United States, developed for the purpose of studying the effects of demographic and socio-economic characteristics on differentials in mortality rates. It consists of data from 26 U.S. Current Population Surveys (CPS) cohorts, annual Social and Economic Supplements, and the 1980 Census cohort, combined with death certificate information to identify mortality status and cause of death covering the time interval, 1979 to 1998. The Current Population Surveys are March Supplements selected from the time period from March 1973 to March 1998. The NLMS routinely links geographical and demographic information from Census Bureau surveys and censuses to the NLMS database, and other available sources upon request. The Census Bureau and CMS have approved the linkage protocol and data acquisition is currently underway. The plan for the NLMS is to link information on mortality to the NLMS every two years from 1998 through 2006 with research on the resulting database to continue, at least, through 2009. The NLMS will continue to incorporate data from the yearly Annual Social and Economic Supplement into the study as the data become available. Based on the expected size of the Annual Social and Economic Supplements to be conducted, the expected number of deaths to be added to the NLMS through the updating process will increase the mortality content of the study to nearly 500,000 cases out of a total number of approximately 3.3 million records. This effort would also include expanding the NLMS population base by incorporating new March Supplement Current Population Survey data into the study as they become available. Linkages to the SEER and CMS datasets are also available. Data Availability: Due to the confidential nature of the data used in the NLMS, the public use dataset consists of a reduced number of CPS cohorts with a fixed follow-up period of five years. NIA does not make the data available directly. Research access to the entire NLMS database can be obtained through the NIA program contact listed. Interested investigators should email the NIA contact and send in a one page prospectus of the proposed project. NIA will approve projects based on their relevance to NIA/BSR''s areas of emphasis. Approved projects are then assigned to NLMS statisticians at the Census Bureau who work directly with the researcher to interface with the database. A modified version of the public use data files is available also through the Census restricted Data Centers. However, since the database is quite complex, many investigators have found that the most efficient way to access it is through the Census programmers. * Dates of Study: 1973-2009 * Study Features: Longitudinal * Sample Size: ~3.3 Million Link: *ICPSR: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/00134

  14. Current Population Survey: Annual Social and Economic (ASEC) Supplement...

    • icpsr.umich.edu
    ascii, delimited, r +3
    Updated May 31, 2018
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    Inter-university Consortium for Political and Social Research [distributor] (2018). Current Population Survey: Annual Social and Economic (ASEC) Supplement Survey, United States, 2017 [Dataset]. http://doi.org/10.3886/ICPSR37075.v1
    Explore at:
    ascii, delimited, stata, spss, sas, rAvailable download formats
    Dataset updated
    May 31, 2018
    Dataset provided by
    Inter-university Consortium for Political and Social Researchhttps://www.icpsr.umich.edu/web/pages/
    License

    https://www.icpsr.umich.edu/web/ICPSR/studies/37075/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/37075/terms

    Time period covered
    2016 - 2017
    Area covered
    United States
    Description

    The Annual Social and Economic (ASEC) 2017 Supplement is part of the Current Population Survey (CPS) Series. The CPS is a source of the official Government statistics on employment and unemployment. The Census Bureau conducts the ASEC (known as the Annual Demographic File prior to 2003) over a three-month period, in February, March, and April, with most of the data collected in the month of March. The ASEC uses two sets of survey questions, the basic CPS and a set of supplemental questions. The CPS, administered monthly, is a labor force survey providing current estimates of the economic status and activities of the population of the United States. Specifically, the CPS provides estimates of total employment (both farm and nonfarm), nonfarm self-employed persons, domestics, and unpaid helpers in nonfarm family enterprises, wage, and salaried employees, and estimates of total unemployment. In addition to the basic CPS questions, respondents were asked questions from the ASEC, which provides supplemental data on poverty, geographic mobility/migration, and work experience. Comprehensive work experience information was given on the employment status, occupation, and industry of persons aged 15 and over. Additional data for persons aged 15 and older were available concerning weeks worked and hours per week worked, reason not working full-time, total income and supplemental income components. Demographic variables include age, sex, race, Hispanic origin, marital status, veteran status, educational attainment, occupation, and income. Data on employment and income refer to the previous calendar year, although demographic data refer to the time of the survey. The occupation and industry information variables in this data collection can help the data users identify individuals who worked in arts and culture related fields. The occupations are listed in a category entitled "Arts, Design, Entertainment, Sports, and Media Occupations," which includes professions such as artists, designers, actors, musicians, and writers (see Appendix B of the User Guide for further category details). Industries related to the arts and culture are in the "Arts, Entertainment, and Recreation" category (see Appendix C of the User Guide for further category details). For example, using the occupation and industry information variables from the ASEC help data users to obtain statistics about people in artists occupations that receive supplemental income, live public housing, or are full-time students. The ASEC data provided by the Census Bureau are distributed in a hierarchical file structure, with three record types present: Household, Family, and Person. The ASEC is designed to be a multistage stratified sample of housing units, where the hierarchical file structure can be thought of as a person within a family within a household unit. Here the main unit of analysis is the household unit.

  15. Yost Index with 90% confidence intervals (with all contributing source files...

    • figshare.com
    zip
    Updated May 31, 2023
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    Francis P. Boscoe; Bian Liu; Furrina F. Lee; Li Niu; jordana lafantasie (2023). Yost Index with 90% confidence intervals (with all contributing source files - LARGE) [Dataset]. http://doi.org/10.6084/m9.figshare.16649773.v3
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    zipAvailable download formats
    Dataset updated
    May 31, 2023
    Dataset provided by
    figshare
    Figsharehttp://figshare.com/
    Authors
    Francis P. Boscoe; Bian Liu; Furrina F. Lee; Li Niu; jordana lafantasie
    License

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

    Description

    We extend our previous work with the Yost Index by adding 90% confidence intervals to the index values. These were calculated using the variance replicate estimates published in association with the American Community Survey of the United States Census Bureau.

    In the file yost-tract-2015-2019.csv, the data fields consists of 11-digit geographic ID built from FIPS codes (2 digit state, 3 digit county, 6 digit census tract); Yost index, 90% lower confidence interval; 90% upper confidence interval. Data is provided for 72,793 census tracts for which sufficient data were available. The Yost Index ranges from 1 (lowest socioeconomic position) to 100 (highest socioeconomic position).

    For those only interested in using the index as we have calculated it, the file yost-tract-2015-2019 is the only file you need. The other 368 files here are provided for anyone who wishes to replicate our results using the R program yost-conf-intervals.R. The program presumes the user is running Windows machine and that all files reside in a folder called C:/yostindex. The R program requires a number of packages, all of which are specified in lines 10-22 of the program.

    Details of this project were published in Boscoe FP, Liu B, LaFantasie J, Niu L, Lee FF. Estimating uncertainty in a socioeconomic index derived from the American Community Survey. SSM-Population Health 2022; 18: 101078. Full text

    Additional years of data following this format are planned to be added to this repository in time.

  16. Census Data - Selected socioeconomic indicators in Chicago, 2008 – 2012

    • data.cityofchicago.org
    • healthdata.gov
    • +2more
    application/rdfxml +5
    Updated Sep 12, 2014
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    U.S. Census Bureau (2014). Census Data - Selected socioeconomic indicators in Chicago, 2008 – 2012 [Dataset]. https://data.cityofchicago.org/Health-Human-Services/Census-Data-Selected-socioeconomic-indicators-in-C/kn9c-c2s2
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    csv, json, application/rssxml, tsv, xml, application/rdfxmlAvailable download formats
    Dataset updated
    Sep 12, 2014
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    U.S. Census Bureau
    Area covered
    Chicago
    Description

    This dataset contains a selection of six socioeconomic indicators of public health significance and a “hardship index,” by Chicago community area, for the years 2008 – 2012. The indicators are the percent of occupied housing units with more than one person per room (i.e., crowded housing); the percent of households living below the federal poverty level; the percent of persons in the labor force over the age of 16 years that are unemployed; the percent of persons over the age of 25 years without a high school diploma; the percent of the population under 18 or over 64 years of age (i.e., dependency); and per capita income. Indicators for Chicago as a whole are provided in the final row of the table. See the full dataset description for more information at: https://data.cityofchicago.org/api/views/fwb8-6aw5/files/A5KBlegGR2nWI1jgP6pjJl32CTPwPbkl9KU3FxlZk-A?download=true&filename=P:\EPI\OEPHI\MATERIALS\REFERENCES\ECONOMIC_INDICATORS\Dataset_Description_socioeconomic_indicators_2012_FOR_PORTAL_ONLY.pdf

  17. a

    ACS 5YR Socioeconomic Estimate Data by Tract

    • hub.arcgis.com
    • data.lojic.org
    • +1more
    Updated Aug 21, 2023
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    Department of Housing and Urban Development (2023). ACS 5YR Socioeconomic Estimate Data by Tract [Dataset]. https://hub.arcgis.com/datasets/HUD::acs-5yr-socioeconomic-estimate-data-by-tract/geoservice
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    Dataset updated
    Aug 21, 2023
    Dataset authored and provided by
    Department of Housing and Urban Development
    Area covered
    Description

    The American Community Survey (ACS) 5 Year 2016-2020 socioeconomic estimate data is a subset of information derived from the following census tables: B08013 - Aggregate Travel Time To Work Of Workers By Sex;B08303 - Travel Time To Work;B17019 - Poverty Status In The Past 12 Months Of Families By Household Type By Tenure;B17021 - Poverty Status Of Individuals In The Past 12 Months By Living Arrangement;B19001 - Household Income In The Past 12 Months;B19013 - Median Household Income In The Past 12 Months;B19025 - Aggregate Household Income In The Past 12 Months;B19113 - Median Family Income In The Past 12 Months;B19202 - Median Non-family Household Income In The Past 12 Months;B23001 - Sex By Age By Employment Status For The Population 16 Years And Over;B25014 - Tenure By Occupants Per Room;B25026 - Total Population in Occupied Housing Units by Tenure by year Householder Moved into Unit;B25106 - Tenure By Housing Costs As A Percentage Of Household Income In The Past 12 Months;C24010 - Sex By Occupation For The Civilian Employed Population 16 Years And Over;B20004 - Median Earnings In the Past 12 Months (In 2015 Inflation-Adjusted Dollars) by Sex by Educational Attainment for the Population 25 Years and Over;B23006 - Educational Attainment by Employment Status for the Population 25 to 64 Years, and;B24021 - Occupation By Median Earnings In The Past 12 Months (In 2015 Inflation-Adjusted Dollars) For The Full-Time, Year-Round Civilian Employed Population 16 Years And Over.To learn more about the American Community Survey (ACS), and associated datasets visit: https://www.census.gov/programs-surveys/acs, for questions about the spatial attribution of this dataset, please reach out to us at GISHelpdesk@hud.gov. Data Dictionary: DD_ACS 5-Year Socioeconomic Estimate Data by Tract Data Updated: BienniallyDate of Coverage: 2016-2020

  18. Birth rate by family income in the U.S. 2021

    • statista.com
    Updated Oct 25, 2024
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    Statista (2024). Birth rate by family income in the U.S. 2021 [Dataset]. https://www.statista.com/statistics/241530/birth-rate-by-family-income-in-the-us/
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    Dataset updated
    Oct 25, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2021
    Area covered
    United States
    Description

    In 2021, the birth rate in the United States was highest in families that had under 10,000 U.S. dollars in income per year, at 62.75 births per 1,000 women. As the income scale increases, the birth rate decreases, with families making 200,000 U.S. dollars or more per year having the second-lowest birth rate, at 47.57 births per 1,000 women. Income and the birth rate Income and high birth rates are strongly linked, not just in the United States, but around the world. Women in lower income brackets tend to have higher birth rates across the board. There are many factors at play in birth rates, such as the education level of the mother, ethnicity of the mother, and even where someone lives. The fertility rate in the United States The fertility rate in the United States has declined in recent years, and it seems that more and more women are waiting longer to begin having children. Studies have shown that the average age of the mother at the birth of their first child in the United States was 27.4 years old, although this figure varies for different ethnic origins.

  19. a

    2020 ACS Demographic & Socio-Economic Data Of Oklahoma At Zip Code Level

    • one-health-data-hub-osu-geog.hub.arcgis.com
    Updated May 22, 2024
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    snakka_OSU_GEOG (2024). 2020 ACS Demographic & Socio-Economic Data Of Oklahoma At Zip Code Level [Dataset]. https://one-health-data-hub-osu-geog.hub.arcgis.com/items/5175de388f27415caf6087afafa1cc52
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    Dataset updated
    May 22, 2024
    Dataset authored and provided by
    snakka_OSU_GEOG
    Area covered
    Description

    we utilized data from two main sources: the United States Census Bureau's American Community Survey (ACS) and the Centers for Disease Control and Prevention/Agency for Toxic Substances and Disease Registry (CDC/ATSDR) Social Vulnerability Index (SVI).American Community Survey (ACS):Conducted by the U.S. Census Bureau, the ACS is an ongoing survey that provides detailed demographic and socio-economic data on the population and housing characteristics of the United States.The survey collects information on various topics such as income, education, employment, health insurance coverage, and housing costs and conditions.It offers more frequent and up-to-date information compared to the decennial census, with annual estimates produced based on a rolling sample of households.The ACS data is essential for policymakers, researchers, and communities to make informed decisions and address the evolving needs of the population.CDC/ATSDR Social Vulnerability Index (SVI):Created by ATSDR’s Geospatial Research, Analysis & Services Program (GRASP) and utilized by the CDC, the SVI is designed to identify and map communities that are most likely to need support before, during, and after hazardous events.

  20. a

    ACS 5YR Socioeconomic Estimate Data by County

    • hudgis-hud.opendata.arcgis.com
    • data.lojic.org
    • +2more
    Updated Aug 21, 2023
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    Department of Housing and Urban Development (2023). ACS 5YR Socioeconomic Estimate Data by County [Dataset]. https://hudgis-hud.opendata.arcgis.com/datasets/acs-5yr-socioeconomic-estimate-data-by-county
    Explore at:
    Dataset updated
    Aug 21, 2023
    Dataset authored and provided by
    Department of Housing and Urban Development
    Area covered
    Description

    The American Community Survey (ACS) 5 Year 2016-2020 socioeconomic estimate data is a subset of information derived from the following census tables:B08013 - Aggregate Travel Time To Work Of Workers By Sex;B08303 - Travel Time To Work;B17019 - Poverty Status In The Past 12 Months Of Families By Household Type By Tenure;B17021 - Poverty Status Of Individuals In The Past 12 Months By Living Arrangement;B19001 - Household Income In The Past 12 Months;B19013 - Median Household Income In The Past 12 Months;B19025 - Aggregate Household Income In The Past 12 Months;B19113 - Median Family Income In The Past 12 Months;B19202 - Median Non-family Household Income In The Past 12 Months;B23001 - Sex By Age By Employment Status For The Population 16 Years And Over;B25014 - Tenure By Occupants Per Room;B25026 - Total Population in Occupied Housing Units by Tenure by year Householder Moved into Unit;B25106 - Tenure By Housing Costs As A Percentage Of Household Income In The Past 12 Months;C24010 - Sex By Occupation For The Civilian Employed Population 16 Years And Over;B20004 - Median Earnings In the Past 12 Months (In 2015 Inflation-Adjusted Dollars) by Sex by Educational Attainment for the Population 25 Years and Over;B23006 - Educational Attainment by Employment Status for the Population 25 to 64 Years, and;B24021 - Occupation By Median Earnings In The Past 12 Months (In 2015 Inflation-Adjusted Dollars) For The Full-Time, Year-Round Civilian Employed Population 16 Years And Over.

    To learn more about the American Community Survey (ACS), and associated datasets visit: https://www.census.gov/programs-surveys/acs, for questions about the spatial attribution of this dataset, please reach out to us at GISHelpdesk@hud.gov. Data Dictionary: DD_ACS 5-Year Socioeconomic Estimate Data by CountyDate of Coverage: 2016-2020

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Clarke, Philippa; Melendez, Robert; Noppert, Grace; Chenoweth, Megan; Gypin, Lindsay (2025). National Neighborhood Data Archive (NaNDA): Socioeconomic Status and Demographic Characteristics of Census Tracts and ZIP Code Tabulation Areas, United States, 1990-2022 [Dataset]. http://doi.org/10.3886/ICPSR38528.v5
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National Neighborhood Data Archive (NaNDA): Socioeconomic Status and Demographic Characteristics of Census Tracts and ZIP Code Tabulation Areas, United States, 1990-2022

Explore at:
stata, delimited, sas, spss, r, asciiAvailable download formats
Dataset updated
Jan 22, 2025
Dataset provided by
Inter-university Consortium for Political and Social Researchhttps://www.icpsr.umich.edu/web/pages/
Authors
Clarke, Philippa; Melendez, Robert; Noppert, Grace; Chenoweth, Megan; Gypin, Lindsay
License

https://www.icpsr.umich.edu/web/ICPSR/studies/38528/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/38528/terms

Time period covered
1990 - 2022
Area covered
United States
Description

These datasets contain measures of socioeconomic and demographic characteristics by U.S. census tract for the years 1990-2022 and ZIP code tabulation area (ZCTA) for the years 2008-2022. Example measures include population density; population distribution by race, ethnicity, age, and income; income inequality by race and ethnicity; and proportion of population living below the poverty level, receiving public assistance, and female-headed or single parent families with kids. The datasets also contain a set of theoretically derived measures capturing neighborhood socioeconomic disadvantage and affluence, as well as a neighborhood index of Hispanic, foreign born, and limited English.

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