To assist communities in identifying racially/ethnically-concentrated areas of poverty (R/ECAPs), HUD has developed a census tract-based definition of R/ECAPs. The definition involves a racial/ethnic concentration threshold and a poverty test. The racial/ethnic concentration threshold is straightforward: R/ECAPs must have a non-white population of 50 percent or more. Regarding the poverty threshold, Wilson (1980) defines neighborhoods of extreme poverty as census tracts with 40 percent or more of individuals living at or below the poverty line. Because overall poverty levels are substantially lower in many parts of the country, HUD supplements this with an alternate criterion. Thus, a neighborhood can be a R/ECAP if it has a poverty rate that exceeds 40% or is three or more times the average tract poverty rate for the metropolitan/micropolitan area, whichever threshold is lower. Census tracts with this extreme poverty that satisfy the racial/ethnic concentration threshold are deemed R/ECAPs. This translates into the following equation: Where i represents census tracts, () is the metropolitan/micropolitan (CBSA) mean tract poverty rate, is the ith tract poverty rate, () is the non-Hispanic white population in tract i, and Pop is the population in tract i.While this definition of R/ECAP works well for tracts in CBSAs, place outside of these geographies are unlikely to have racial or ethnic concentrations as high as 50 percent. In these areas, the racial/ethnic concentration threshold is set at 20 percent. Data Source: Related AFFH-T Local Government, PHA Tables/Maps: Table 4, 7; Maps 1-17.Related AFFH-T State Tables/Maps: Table 4, 7; Maps 1-15, 18.References:Wilson, William J. (1980). The Declining Significance of Race: Blacks and Changing American Institutions. Chicago: University of Chicago Press.To learn more about R/ECAPs 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: 2017 - 2021 ACSDate Updated: 10/2023

A total of 350 unique census tracts were included in the analysis; there are 946 census tracts in the Atlanta MSA, which was the catchment area for the study. Because we calculated the mean of census tracts where the participants lived, the number of items of census tract data included in the average was equal to the number of participants for all calculations except for HIV diagnosis rate. Diagnosis rates are missing for 49 individuals who lived in census tracts not included in the data released from the state and for 40 individuals who lived in census tracts for which the numerator (number of persons living with an HIV infection diagnosis) was less than 5 and/or the denominator (number of people in the census tract in that population group) was

This layer contains a Vermont-only subset of block group level 2020 Decennial Census redistricting data as reported by the U.S. Census Bureau for all states plus DC and Puerto Rico. The attributes come from the 2020 Public Law 94-171 (P.L. 94-171) tables.Data download date: August 12, 2021Census tables: P1, P2, P3, P4, H1, P5, HeaderDownloaded from: Census FTP siteProcessing Notes:Data was downloaded from the U.S. Census Bureau FTP site, imported into SAS format and joined to the 2020 TIGER boundaries. Boundaries are sourced from the 2020 TIGER/Line Geodatabases. Boundaries have been projected into Web Mercator and each attribute has been given a clear descriptive alias name. No alterations have been made to the vertices of the data.Each attribute maintains it's specified name from Census, but also has a descriptive alias name and long description derived from the technical documentation provided by the Census. For a detailed list of the attributes contained in this layer, view the Data tab and select "Fields". The following alterations have been made to the tabular data:Joined all tables to create one wide attribute table:P1 - RaceP2 - Hispanic or Latino, and not Hispanic or Latino by RaceP3 - Race for the Population 18 Years and OverP4 - Hispanic or Latino, and not Hispanic or Latino by Race for the Population 18 Years and OverH1 - Occupancy Status (Housing)P5 - Group Quarters Population by Group Quarters Type (correctional institutions, juvenile facilities, nursing facilities/skilled nursing, college/university student housing, military quarters, etc.)HeaderAfter joining, dropped fields: FILEID, STUSAB, CHARITER, CIFSN, LOGRECNO, GEOVAR, GEOCOMP, LSADC, and BLOCK.GEOCOMP was renamed to GEOID and moved be the first column in the table, the original GEOID was dropped.Placeholder fields for future legislative districts have been dropped: CD118, CD119, CD120, CD121, SLDU22, SLDU24, SLDU26, SLDU28, SLDL22, SLDL24 SLDL26, SLDL28.P0020001 was dropped, as it is duplicative of P0010001. Similarly, P0040001 was dropped, as it is duplicative of P0030001.In addition to calculated fields, County_Name and State_Name were added.The following calculated fields have been added (see long field descriptions in the Data tab for formulas used): PCT_P0030001: Percent of Population 18 Years and OverPCT_P0020002: Percent Hispanic or LatinoPCT_P0020005: Percent White alone, not Hispanic or LatinoPCT_P0020006: Percent Black or African American alone, not Hispanic or LatinoPCT_P0020007: Percent American Indian and Alaska Native alone, not Hispanic or LatinoPCT_P0020008: Percent Asian alone, Not Hispanic or LatinoPCT_P0020009: Percent Native Hawaiian and Other Pacific Islander alone, not Hispanic or LatinoPCT_P0020010: Percent Some Other Race alone, not Hispanic or LatinoPCT_P0020011: Percent Population of Two or More Races, not Hispanic or LatinoPCT_H0010002: Percent of Housing Units that are OccupiedPCT_H0010003: Percent of Housing Units that are VacantPlease note these percentages might look strange at the individual block group level, since this data has been protected using differential privacy.*VCGI exported a Vermont-only subset of the nation-wide layer to produce this layer--with fields limited to this popular subset: OBJECTID: OBJECTID GEOID: Geographic Record Identifier NAME: Area Name-Legal/Statistical Area Description (LSAD) Term-Part Indicator County_Name: County Name State_Name: State Name P0010001: Total Population P0010003: Population of one race: White alone P0010004: Population of one race: Black or African American alone P0010005: Population of one race: American Indian and Alaska Native alone P0010006: Population of one race: Asian alone P0010007: Population of one race: Native Hawaiian and Other Pacific Islander alone P0010008: Population of one race: Some Other Race alone P0020002: Hispanic or Latino Population P0020003: Non-Hispanic or Latino Population P0030001: Total population 18 years and over H0010001: Total housing units H0010002: Total occupied housing units H0010003: Total vacant housing units P0050001: Total group quarters population PCT_P0030001: Percent of Population 18 Years and Over PCT_P0020002: Percent Hispanic or Latino PCT_P0020005: Percent White alone, not Hispanic or Latino PCT_P0020006: Percent Black or African American alone, not Hispanic or Latino PCT_P0020007: Percent American Indian and Alaska Native alone, not Hispanic or Latino PCT_P0020008: Percent Asian alone, not Hispanic or Latino PCT_P0020009: Percent Native Hawaiian and Other Pacific Islander alone, not Hispanic or Latino PCT_P0020010: Percent Some Other Race alone, not Hispanic or Latino PCT_P0020011: Percent Population of two or more races, not Hispanic or Latino PCT_H0010002: Percent of Housing Units that are Occupied PCT_H0010003: Percent of Housing Units that are Vacant SUMLEV: Summary Level REGION: Region DIVISION: Division COUNTY: County (FIPS) COUNTYNS: County (NS) TRACT: Census Tract BLKGRP: Block Group AREALAND: Area (Land) AREAWATR: Area (Water) INTPTLAT: Internal Point (Latitude) INTPTLON: Internal Point (Longitude) BASENAME: Area Base Name POP100: Total Population Count HU100: Total Housing Count *To protect the privacy and confidentiality of respondents, data has been protected using differential privacy techniques by the U.S. Census Bureau. This means that some individual block groups will have values that are inconsistent or improbable. However, when aggregated up, these issues become minimized.Download Census redistricting data in this layer as a file geodatabase.Additional links:U.S. Census BureauU.S. Census Bureau Decennial CensusAbout the 2020 Census2020 Census2020 Census data qualityDecennial Census P.L. 94-171 Redistricting Data Program

This dataset contains Iowa median age by sex and Hispanic or Latino origin for State of Iowa, individual Iowa counties, Iowa places and census tracts within Iowa. Data is from the American Community Survey, Five Year Estimates, Tables B01002H and B01002I. Sex includes the following: Male, Female and Both Hispanic includes, yes or no. Yes = Hispanic or Latino; No = White Alone, Not Hispanic or Latino

For detailed information, visit the Tucson Equity Priority Index StoryMap.Download the layer's data dictionaryWhat is the Tucson Equity Priority Index (TEPI)?The Tucson Equity Priority Index (TEPI) is a tool that describes the distribution of socially vulnerable demographics. It categorizes the dataset into 5 classes that represent the differing prioritization needs based on the presence of social vulnerability: Low (0-20), Low-Moderate (20-40), Moderate (40-60), Moderate-High (60-80) High (80-100). Each class represents 20% of the dataset’s features in order of their values. The features within the Low (0-20) classification represent the areas that, when compared to all other locations in the study area, have the lowest need for prioritization, as they tend to have less socially vulnerable demographics. The features that fall into the High (80-100) classification represent the 20% of locations in the dataset that have the greatest need for prioritization, as they tend to have the highest proportions of socially vulnerable demographics. How is social vulnerability measured?The Tucson Equity Priority Index (TEPI) examines the proportion of vulnerability per feature using 11 demographic indicators:Income Below Poverty: Households with income at or below the federal poverty level (FPL), which in 2023 was $14,500 for an individual and $30,000 for a family of fourUnemployment: Measured as the percentage of unemployed persons in the civilian labor forceHousing Cost Burdened: Homeowners who spend more than 30% of their income on housing expenses, including mortgage, maintenance, and taxesRenter Cost Burdened: Renters who spend more than 30% of their income on rentNo Health Insurance: Those without private health insurance, Medicare, Medicaid, or any other plan or programNo Vehicle Access: Households without automobile, van, or truck accessHigh School Education or Less: Those highest level of educational attainment is a High School diploma, equivalency, or lessLimited English Ability: Those whose ability to speak English is "Less Than Well."People of Color: Those who identify as anything other than Non-Hispanic White Disability: Households with one or more physical or cognitive disabilities Age: Groups that tend to have higher levels of vulnerability, including children (those below 18), and seniors (those 65 and older)An overall percentile value is calculated for each feature based on the total proportion of the above indicators in each area. How are the variables combined?These indicators are divided into two main categories that we call Thematic Indices: Economic and Personal Characteristics. The two thematic indices are further divided into five sub-indices called Tier-2 Sub-Indices. Each Tier-2 Sub-Index contains 2-3 indicators. Indicators are the datasets used to measure vulnerability within each sub-index. The variables for each feature are re-scaled using the percentile normalization method, which converts them to the same scale using values between 0 to 100. The variables are then combined first into each of the five Tier-2 Sub-Indices, then the Thematic Indices, then the overall TEPI using the mean aggregation method and equal weighting. The resulting dataset is then divided into the five classes, where:High Vulnerability (80-100%): Representing the top classification, this category includes the highest 20% of regions that are the most socially vulnerable. These areas require the most focused attention. Moderate-High Vulnerability (60-80%): This upper-middle classification includes areas with higher levels of vulnerability compared to the median. While not the highest, these areas are more vulnerable than a majority of the dataset and should be considered for targeted interventions. Moderate Vulnerability (40-60%): Representing the middle or median quintile, this category includes areas of average vulnerability. These areas may show a balanced mix of high and low vulnerability. Detailed examination of specific indicators is recommended to understand the nuanced needs of these areas. Low-Moderate Vulnerability (20-40%): Falling into the lower-middle classification, this range includes areas that are less vulnerable than most but may still exhibit certain vulnerable characteristics. These areas typically have a mix of lower and higher indicators, with the lower values predominating. Low Vulnerability (0-20%): This category represents the bottom classification, encompassing the lowest 20% of data points. Areas in this range are the least vulnerable, making them the most resilient compared to all other features in the dataset.

Field Definition:GEOID - "Census tract identifier; a concatenation of 2020 Census state FIPS code, county FIPS code, and census tract code"NAMELSAD - Census translated legal/statistical area description and the census tract nameALAND - Census Area LandAWATER - Census Area waterINTPTLAT - Census Internal Point (Latitude)INTPTLON - Census Internal Point (Longitude)NAME20 - "2020 Census tract name, this is the census tract code converted to an integer or integer plus two-digit decimal if the last two characters of the code are not both zeros"POPULATION - Total PopulationP18PLUS - Population 18 years and olderHHPOP - Household PopulationGQ - Group Quarters PopulationHOUSING - Total Housing unitsOCCUNITS - Occupied Housing Units (Households)VACUNITS - Vacant Housing UnitsVACRATE -Vacancy RateHISPANIC - Hispanic or Latino NH_WHT - Not Hispanic or Latino, White alone NH_BLK - Not Hispanic or Latino, Black or African American alone NH_IND - Not Hispanic or Latino, American Indian and Alaska Native aloneNH_ASN - Not Hispanic or Latino, Asian aloneNH_HWN - Not Hispanic or Latino, Native Hawaiian and Other Pacific Islander alone NH_OTH - Not Hispanic or Latino, Some Other Race alone NH_TWO - Not Hispanic or Latino, Population of two or more races

Feature class representing retail alcohol outlet density at the census tract level developed directly from address information from liquor licensee lists that were obtained from the Colorado Department of Revenue-Liquor Enforcement Division (DOR-LED). This file was developed for use in activities and exercises within the Colorado Department of Public Health and Environment (CDPHE), including the Alcohol Outlet Density StoryMap. CDPHE nor DOR-LED are responsible for data products made using this publicly available data. It should be stated that neither agency is acting as an active data steward of this map service/geospatial data layer at this point in time. This dataset is representative of Colorado licensing data gathered in January 2024. The data file contains the following attributes:FIPSTract Name Tract FIPS StateCountyLand Area Square Miles (Area of Land in Square Miles)Water Area SquareMiles (Area of Water in Square Miles)Population Total (Total Population as estimated in ACS 2018-2022)Percent Race White (Percent of population identifying as White as estimated in ACS 2018-2022) Percent Race African American Percent (Percent of population identifying as African American as estimated in ACS 2018-2022)Race American Indian Alaskan Native (Percent of population identifying as American Indian or Alaskan Native as estimated in ACS 2018-2022)Percent Race Asian (Percent of population identifying as Asian as estimated in ACS 2018-2022)Percent Race NHawaiian OPI (Percent of population identifying as Native Hawaiian or Pacific Islander as estimated in 2018-2022)Percent Race Other (Percent of population identifying as another race as estimated in 2018-2022)Percent Ethnicity Hispanic Latino (Percent of population identifying as Hispanic or Latino as estimated in 2018-2022)Percent Ethnicity Not Hispanic or Latino (Percent of population identifying as not Hispanic or Latino as estimated in 2018-2022)Percent Race Minority Race or Hispanic Latino (Percent of population made up of a Race and/or Ethnicity other than White, Non-Hispanic)Percent Population over 24 Years No HS Diploma (Percent of population over 24 years old without a High School Diploma as estimated in 2018-2022)Frequency All Retail Outlets 2024 (All retail alcohol outlets from January 2024)Average Distance Between Outlets in Meters (Average distance in Meters between an alcohol outlet and its nearest neighboring outlet)Frequency Off Premises Outlets 2024 (All Off-premises retail alcohol outlets from January 2024)Frequency On Premises Outlets 2024 (All On-premises retail alcohol outlets from January 2024)Rate Total Outlets per Square Mile (Rate of all retail alcohol outlets per square mile)Rate Total Outlets per 1,000 Residents (Rate of all retail alcohol outlets per 1,000 residents)Rate On Premises Outlets per Square Mile (Rate of On-premises retail alcohol outlets per square mile)Rate Off Premises Outlets per Square Mile (Rate of On-premises retail alcohol outlets per square mile)Rate On Premises Outlets per 1,000 Residents (Rate of on-premises retail alcohol outlets per 1,000 residents)Rate Off Premises Outlets per 1,000 Residents (Rate of off-premises retail alcohol outlets per 1,000 residents)Average Distance Between Outlets in Miles (Average distance in Miles between an alcohol outlet and its nearest neighboring outlet)

Update August 3, 2023: Ten Census Block Groups for field "May 2023 DI Type" were corrected to display "Area under Tribal Jurisdiction". Previously, they were labeled as "Within a Justice 40 Census Tract". While those areas are within Justice 40 Census Tracts, the most correct label based on HB23-1233 DI Definition is "Area under Tribal Jurisdiction". CO EnviroScreen does not provide or display environmental health data for areas under tribal jurisdiction (see FAQ page 4).Impacted Census Block Groups include: 080679404002, 080679403003, 080679403002, 080679403001, 080839411002, 080839411001, 080079404002, 080079404001, 080679404003, 080679404001Colorado EnviroScreen is an environmental justice mapping tool that uses population and environmental factors to calculate an EnviroScreen Score. A higher EnviroScreen Score means the area is more likely to be affected by environmental inequities. This dataset also includes variables for CBGs that qualify as a “Disproportionately Impacted Community” under Colorado law. House Bill 23-1233 adopted a definition that applies to all state agencies, including CDPHE in May 2023. The definition includes census block groups where more than 40% of the population are low-income (meaning that median household income is at or below 200% of the federal poverty line), 50% of the households are housing cost-burdened (meaning that a household spends more than 30% of its income on housing costs like rent or a mortgage), 40% of the population are people of color (including all people who do not identify as non-Hispanic white), or 20% of households are linguistically isolated (meaning that all members of a household that are 14 years old or older have difficulty with speaking English. Also included in this definition are mobile home communities, the Ute Mountain Ute and Southern Ute Indian Reservations, and all areas that qualify as disadvantaged in the federal Climate and Economic Justice Screening Tool. The definition also includes census block groups that experience higher rates of cumulative impacts, which is represented by an EnviroScreen Score (Percentile) above 80. This definition is not part of the EnviroScreen components or score, and does not influence the results presented in the map, charts or table.Prior to May 2023, “Disproportionately Impacted Community” was defined under the Colorado Environmental Justice Act (HB21-1266). The prior “DI Community” variable is also included in this dataset.Click here to access the data download field key. The tool includes scores for each county, census tract, and census block group in Colorado. CDPHE will improve and update the tool in response to feedback and as new data becomes available. Please note that EnviroScreen data for areas under Ute Mountain Ute and Southern Ute tribal jurisdictions are not currently provided though those areas are included in the May 2023 DI Community definition update. Although EnviroScreen provides a robust measure of cumulative environmental burden, it is not a perfect tool. The tool uses limited environmental, health, and sociodemographic data to calculate the EnviroScreen Score. Colorado EnviroScreen does: Show which areas in Colorado are more likely to have higher environmental health injustices. Identify areas in Colorado where government agencies can prioritize resources and work to reduce pollution and other sources of environmental injustice.Provide information to empower communities to advocate to improve public health and the environment. Identify areas that meet the updated definition of “Disproportionately Impacted Community” under House Bill 23-1233 adopted a definition that applies to all state agencies, including CDPHE.Identify areas where the Air Quality Control Commission (AQCC) Regulation (Reg.) Number 3, which governs permitting in disproportionately impacted communities, applies. Identify areas that meet the prior definition of “Disproportionately Impacted Community” under the Colorado Environmental Justice Act (HB21-1266).Colorado EnviroScreen does not: Define a healthy or unhealthy environment. Establish causal associations between environmental risks and health. Define all areas that may be affected by environmental injustice or specific environmental risks. Provide information about an individual person’s health status or environment. Take all environmental exposures into account. Tell us about smaller areas within a census block group that may be more vulnerable to environmental exposures than other areas. Provide information about non-human health or ecosystem risks.