This indicator provides number and percentage of persons with a disability (one or more) within each age group. Disability status is determined for the civilian non-institutionalized population who responded to questions regarding six types of difficulty and may vary by age. For children under 5 years old, hearing and vision difficulty are used to determine disability status. For children between the ages of 5 and 14, disability status is determined from hearing, vision, cognitive, ambulatory, and self-care difficulties. For people aged 15 years and older, they are considered to have a disability if they have difficulty with any one of the six difficulty types. *Refers to the percent of those with a disability within the specific age group.

Source: U.S. Census Bureau; 2013-2017 American Community Survey 5-Year Estimates, Table S1810.

This layer was developed by the Research & Analytics Group of the Atlanta Regional Commission, using data from the U.S. Census Bureau’s American Community Survey 5-year estimates for 2013-2017, to show counts and percentages of the civilian noninstitutionalized population with disabilities by age group by Strong, Prosperous, And Resilient Communities Challenge in the Atlanta region.

The user should note that American Community Survey data represent estimates derived from a surveyed sample of the population, which creates some level of uncertainty, as opposed to an exact measure of the entire population (the full census count is only conducted once every 10 years and does not cover as many detailed characteristics of the population). Therefore, any measure reported by ACS should not be taken as an exact number – this is why a corresponding margin of error (MOE) is also given for ACS measures. The size of the MOE relative to its corresponding estimate value provides an indication of confidence in the accuracy of each estimate. Each MOE is expressed in the same units as its corresponding measure; for example, if the estimate value is expressed as a number, then its MOE will also be a number; if the estimate value is expressed as a percent, then its MOE will also be a percent.

The user should also note that for relatively small geographic areas, such as census tracts shown here, ACS only releases combined 5-year estimates, meaning these estimates represent rolling averages of survey results that were collected over a 5-year span (in this case 2013-2017). Therefore, these data do not represent any one specific point in time or even one specific year. For geographic areas with larger populations, 3-year and 1-year estimates are also available.

For further explanation of ACS estimates and margin of error, visit Census ACS website.

Naming conventions:

Prefixes:

None

Count

p

Percent

r

Rate

m

Median

a

Mean (average)

t

Aggregate (total)

ch

Change in absolute terms (value in t2 - value in t1)

pch

Percent change ((value in t2 - value in t1) / value in t1)

chp

Change in percent (percent in t2 - percent in t1)

Suffixes:

None

Change over two periods

_e

Estimate from most recent ACS

_m

Margin of Error from most recent ACS

_00

Decennial 2000

Attributes:

SumLevel

Summary level of geographic unit (e.g., County, Tract, NSA, NPU, DSNI, SuperDistrict, etc)

GEOID

Census tract Federal Information Processing Series (FIPS) code

NAME

Name of geographic unit

Planning_Region

Planning region designation for ARC purposes

Acres

Total area within the tract (in acres)

SqMi

Total area within the tract (in square miles)

County

County identifier (combination of Federal Information Processing Series (FIPS) codes for state and county)

CountyName

County Name

CivNonInstPopTotal_e

# Civilian non-institutionalized population, 2017

CivNonInstPopTotal_m

# Civilian non-institutionalized population, 2017 (MOE)

WithDisabilityTotal_e

# Civilian non-institutionalized population with a disability, 2017

WithDisabilityTotal_m

# Civilian non-institutionalized population with a disability, 2017 (MOE)

pWithDisabilityTotal_e

% Civilian non-institutionalized population with a disability, 2017

pWithDisabilityTotal_m

% Civilian non-institutionalized population with a disability, 2017 (MOE)

CivNonInstPopU18_e

# Civilian non-institutionalized population under age 18, 2017

CivNonInstPopU18_m

# Civilian non-institutionalized population under age 18, 2017 (MOE)

WithDisabilityU18_e

# Civilian non-institutionalized population under age 18 with a disability, 2017

WithDisabilityU18_m

# Civilian non-institutionalized population under age 18 with a disability, 2017 (MOE)

pWithDisabilityU18_e

% Civilian non-institutionalized population under age 18 with a disability, 2017

pWithDisabilityU18_m

% Civilian non-institutionalized population under age 18 with a disability, 2017 (MOE)

CivNonInstPop1864_e

# Civilian non-institutionalized population ages 18-64, 2017

CivNonInstPop1864_m

# Civilian non-institutionalized population ages 18-64, 2017 (MOE)

WithDisability1864_e

# Civilian non-institutionalized population ages 18-64 with a disability, 2017

WithDisability1864_m

# Civilian non-institutionalized population ages 18-64 with a disability, 2017 (MOE)

pWithDisability1864_e

% Civilian non-institutionalized population ages 18-64 with a disability, 2017

pWithDisability1864_m

% Civilian non-institutionalized population ages 18-64 with a disability, 2017 (MOE)

CivNonInstPop65P_e

# Civilian non-institutionalized population ages 65 and over, 2017

CivNonInstPop65P_m

# Civilian non-institutionalized population ages 65 and over, 2017 (MOE)

WithDisability65P_e

# Civilian non-institutionalized population ages 65 and over with a disability, 2017

WithDisability65P_m

# Civilian non-institutionalized population ages 65 and over with a disability, 2017 (MOE)

pWithDisability65P_e

% Civilian non-institutionalized population ages 65 and over with a disability, 2017

pWithDisability65P_m

% Civilian non-institutionalized population ages 65 and over with a disability, 2017 (MOE)

last_edited_date

Last date the feature was edited by ARC

Source: U.S. Census Bureau, Atlanta Regional Commission

Date: 2013-2017

For additional information, please visit the Census ACS website.

According to various measures of access to care, Americans experienced different levels of access to care depending on their disability status. From 2017 to 2019, disabled individuals experienced better access to care than individuals with no disabilities for roughly ** percent of measures. However, disabled individuals faced worse access to care for the same share of measures.

In 2022, the crude death rate among people with disabilities in South Korea stood at ****** deaths per 100,000 population. This has increased significantly over the past years.

This layer shows six different types of disability. Data is from US Census American Community Survey (ACS) 5-year estimates.This layer is symbolized to show the percent of population with a disability. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right (in ArcGIS Online). To view only the census tracts that are predominantly in Tempe, add the expression City is Tempe in the map filter settings.Layer includes percent of population with a disability categorized as:an independent living difficultya hearing difficultyan ambulatory difficultya vision difficultya cognitive difficultya selfcare difficultyA ‘Null’ entry in the estimate indicates that data for this geographic area cannot be displayed because the number of sample cases is too small (per the U.S. Census).Vintage: 2017-2021ACS Table(s): S1810 (Not all lines of this ACS table are available in this feature layer.)Data downloaded from: Census Bureau's API for American Community Survey Data Preparation: Data table downloaded and joined with Census Tract boundaries that are within or adjacent to the City of Tempe boundaryDate of Census update: December 8, 2022National Figures: data.census.gov

Estimated percent of the civilian noninstitutionalized population with one or more types of disabilities, between 2017-2021. Percentage calculations are suppressed in cases where the denominator of the calculation was less than 10 of the unit that is being described (e.g., households, people, householders, etc.).

In 2022, the crude death rate among women with disabilities in South Korea stood at ******* deaths per 100,000 population. This rate was generally higher among women than men, though the difference was larger in 2022 compared to previous years.

This layer shows Disability Status of the Civilian Noninstitutionalized Population. This is shown by state and county boundaries. This service contains the 2017-2021 release of data from the American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. This layer is symbolized to show Total Civilian Noninstitutionalized Population - with a disability 65 and over. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Current Vintage: 2017-2021ACS Table(s): DP02, S2201, S1810Data downloaded from: Census Bureau's API for American Community Survey Date of API call: February 16, 2023National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:Boundaries come from the Cartographic Boundaries via US Census TIGER geodatabases. Boundaries are updated at the same time as the data updates, and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines clipped for cartographic purposes. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). The States layer contains 52 records - all US states, Washington D.C., and Puerto Rico. The Counties (and equivalent) layer contains 3221 records - all counties and equivalent, Washington D.C., and Puerto Rico municipios. See Areas Published. Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells.Margin of error (MOE) values of -555555555 in the API (or "*****" (five asterisks) on data.census.gov) are displayed as 0 in this dataset. The estimates associated with these MOEs have been controlled to independent counts in the ACS weighting and have zero sampling error. So, the MOEs are effectively zeroes, and are treated as zeroes in MOE calculations. Other negative values on the API, such as -222222222, -666666666, -888888888, and -999999999, all represent estimates or MOEs that can't be calculated or can't be published, usually due to small sample sizes. All of these are rendered in this dataset as null (blank) values.

Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the .Technical Documentation.. section......Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the .Methodology.. section..Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau's Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties..Explanation of Symbols:..An "**" entry in the margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate..An "-" entry in the estimate column indicates that either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution..An "-" following a median estimate means the median falls in the lowest interval of an open-ended distribution..An "+" following a median estimate means the median falls in the upper interval of an open-ended distribution..An "***" entry in the margin of error column indicates that the median falls in the lowest interval or upper interval of an open-ended distribution. A statistical test is not appropriate..An "*****" entry in the margin of error column indicates that the estimate is controlled. A statistical test for sampling variability is not appropriate. .An "N" entry in the estimate and margin of error columns indicates that data for this geographic area cannot be displayed because the number of sample cases is too small..An "(X)" means that the estimate is not applicable or not available...Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..While the 2013-2017 American Community Survey (ACS) data generally reflect the February 2013 Office of Management and Budget (OMB) definitions of metropolitan and micropolitan statistical areas; in certain instances the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB definitions due to differences in the effective dates of the geographic entities..The Census Bureau introduced a new set of disability questions in the 2008 ACS questionnaire. Accordingly, comparisons of disability data from 2008 or later with data from prior years are not recommended. For more information on these questions and their evaluation in the 2006 ACS Content Test, see the .Evaluation Report Covering Disability....Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see .Accuracy of the Data..). The effect of nonsampling error is not represented in these tables..Source: U.S. Census Bureau, 2013-2017 American Community Survey 5-Year Estimates

In 2019, according to a recent publication released by INSEE (National Institute of Statistics and Economic Studies), **** million of the French population between the ages of 15 and 64 years old had a disability. This number has experienced some fluctuations since 2016, but has increased overall. Indeed, it rose by about **** million between 2016 and 2017, and, despite a slight decrease the following year, by 2019 the number of people with disabilities had almost returned to its 2017 value.

Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section...Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau''s Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties..Explanation of Symbols:An ''**'' entry in the margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate..An ''-'' entry in the estimate column indicates that either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution..An ''-'' following a median estimate means the median falls in the lowest interval of an open-ended distribution..An ''+'' following a median estimate means the median falls in the upper interval of an open-ended distribution..An ''***'' entry in the margin of error column indicates that the median falls in the lowest interval or upper interval of an open-ended distribution. A statistical test is not appropriate..An ''*****'' entry in the margin of error column indicates that the estimate is controlled. A statistical test for sampling variability is not appropriate. .An ''N'' entry in the estimate and margin of error columns indicates that data for this geographic area cannot be displayed because the number of sample cases is too small..An ''(X)'' means that the estimate is not applicable or not available..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..While the 2017 American Community Survey (ACS) data generally reflect the July 2015 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas, in certain instances the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineations due to differences in the effective dates of the geographic entities..Occupation codes are 4-digit codes and are based on Standard Occupational Classification 2010..Industry codes are 4-digit codes and are based on the North American Industry Classification System 2012. The Industry categories adhere to the guidelines issued in Clarification Memorandum No. 2, "NAICS Alternate Aggregation Structure for Use By U.S. Statistical Agencies," issued by the Office of Management and Budget..The Census Bureau introduced a new set of disability questions in the 2008 ACS questionnaire. Accordingly, comparisons of disability data from 2008 or later with data from prior years are not recommended. For more information on these questions and their evaluation in the 2006 ACS Content Test, see the Evaluation Report Covering Disability..Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables..Source: U.S. Census Bureau, 2017 American Community Survey 1-Year Estimates

Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Data and Documentation section...Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau''s Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities and towns and estimates of housing units for states and counties..Explanation of Symbols:An ''**'' entry in the margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate..An ''-'' entry in the estimate column indicates that either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution..An ''-'' following a median estimate means the median falls in the lowest interval of an open-ended distribution..An ''+'' following a median estimate means the median falls in the upper interval of an open-ended distribution..An ''***'' entry in the margin of error column indicates that the median falls in the lowest interval or upper interval of an open-ended distribution. A statistical test is not appropriate..An ''*****'' entry in the margin of error column indicates that the estimate is controlled. A statistical test for sampling variability is not appropriate. .An ''N'' entry in the estimate and margin of error columns indicates that data for this geographic area cannot be displayed because the number of sample cases is too small..An ''(X)'' means that the estimate is not applicable or not available..Estimates of urban and rural population, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..While the 2017 American Community Survey (ACS) data generally reflect the February 2013 Office of Management and Budget (OMB) definitions of metropolitan and micropolitan statistical areas; in certain instances the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB definitions due to differences in the effective dates of the geographic entities..The Census Bureau introduced a new set of disability questions in the 2008 ACS questionnaire. Accordingly, comparisons of disability data from 2008 or later with data from prior years are not recommended. For more information on these questions and their evaluation in the 2006 ACS Content Test, see the Evaluation Report Covering Disability..Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables..Source: U.S. Census Bureau, 2017 American Community Survey 1-Year Estimates

Labour market statistics (disability) provides comparisons between labour market measures for disabled and non-disabled people in New Zealand. Information includes labour market participation and employment rates as well as differences in wages and salaries received.

This layer shows Disability Status of the Civilian Noninstitutionalized Population. This is shown by state and county boundaries. This service contains the 2017-2021 release of data from the American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. This layer is symbolized to show Total Civilian Noninstitutionalized Population - with a disability 65 and over. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Current Vintage: 2017-2021ACS Table(s): DP02, S2201, S1810Data downloaded from: Census Bureau's API for American Community Survey Date of API call: February 16, 2023National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:Boundaries come from the Cartographic Boundaries via US Census TIGER geodatabases. Boundaries are updated at the same time as the data updates, and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines clipped for cartographic purposes. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). The States layer contains 52 records - all US states, Washington D.C., and Puerto Rico. The Counties (and equivalent) layer contains 3221 records - all counties and equivalent, Washington D.C., and Puerto Rico municipios. See Areas Published. Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells.Margin of error (MOE) values of -555555555 in the API (or "*****" (five asterisks) on data.census.gov) are displayed as 0 in this dataset. The estimates associated with these MOEs have been controlled to independent counts in the ACS weighting and have zero sampling error. So, the MOEs are effectively zeroes, and are treated as zeroes in MOE calculations. Other negative values on the API, such as -222222222, -666666666, -888888888, and -999999999, all represent estimates or MOEs that can't be calculated or can't be published, usually due to small sample sizes. All of these are rendered in this dataset as null (blank) values.

Labour market statistics (disability) provides comparisons between labour market measures for disabled and non-disabled people in New Zealand. Information includes labour market participation and employment rates as well as differences in wages and salaries received.

This dataset was developed by the Research & Analytics Group at the Atlanta Regional Commission using data from the U.S. Census Bureau across all standard and custom geographies at statewide summary level where applicable. For a deep dive into the data model including every specific metric, see the ACS 2017-2021 Data Manifest. The manifest details ARC-defined naming conventions, field names/descriptions and topics, summary levels; source tables; notes and so forth for all metrics. Find naming convention prefixes/suffixes, geography definitions and user notes below.Prefixes:NoneCountpPercentrRatemMedianaMean (average)tAggregate (total)chChange in absolute terms (value in t2 - value in t1)pchPercent change ((value in t2 - value in t1) / value in t1)chpChange in percent (percent in t2 - percent in t1)sSignificance flag for change: 1 = statistically significant with a 90% CI, 0 = not statistically significant, blank = cannot be computedSuffixes:_e21Estimate from 2017-21 ACS_m21Margin of Error from 2017-21 ACS_e102006-10 ACS, re-estimated to 2020 geography_m10Margin of Error from 2006-10 ACS, re-estimated to 2020 geography_e10_21Change, 2010-21 (holding constant at 2020 geography)GeographiesAAA = Area Agency on Aging (12 geographic units formed from counties providing statewide coverage)ARC21 = Atlanta Regional Commission modeling area (21 counties merged to a single geographic unit)ARWDB7 = Atlanta Regional Workforce Development Board (7 counties merged to a single geographic unit)BeltLine (buffer)BeltLine Study (subareas)Census Tract (statewide)CFGA23 = Community Foundation for Greater Atlanta (23 counties merged to a single geographic unit)City (statewide)City of Atlanta Council Districts (City of Atlanta)City of Atlanta Neighborhood Planning Unit (City of Atlanta)City of Atlanta Neighborhood Planning Unit STV (3 NPUs merged to a single geographic unit within City of Atlanta)City of Atlanta Neighborhood Statistical Areas (City of Atlanta)City of Atlanta Neighborhood Statistical Areas E02E06 (2 NSAs merged to single geographic unit within City of Atlanta)County (statewide)Georgia House (statewide)Georgia Senate (statewide)MetroWater15 = Atlanta Metropolitan Water District (15 counties merged to a single geographic unit)Regional Commissions (statewide)SPARCC = Strong, Prosperous And Resilient Communities ChallengeState of Georgia (single geographic unit)Superdistrict (ARC region)US Congress (statewide)UWGA13 = United Way of Greater Atlanta (13 counties merged to a single geographic unit)WFF = Westside Future Fund (subarea of City of Atlanta)ZIP Code Tabulation Areas (statewide)The user should note that American Community Survey data represent estimates derived from a surveyed sample of the population, which creates some level of uncertainty, as opposed to an exact measure of the entire population (the full census count is only conducted once every 10 years and does not cover as many detailed characteristics of the population). Therefore, any measure reported by ACS should not be taken as an exact number – this is why a corresponding margin of error (MOE) is also given for ACS measures. The size of the MOE relative to its corresponding estimate value provides an indication of confidence in the accuracy of each estimate. Each MOE is expressed in the same units as its corresponding measure; for example, if the estimate value is expressed as a number, then its MOE will also be a number; if the estimate value is expressed as a percent, then its MOE will also be a percent. The user should also note that for relatively small geographic areas, such as census tracts shown here, ACS only releases combined 5-year estimates, meaning these estimates represent rolling averages of survey results that were collected over a 5-year span (in this case 2017-2021). Therefore, these data do not represent any one specific point in time or even one specific year. For geographic areas with larger populations, 3-year and 1-year estimates are also available. For further explanation of ACS estimates and margin of error, visit Census ACS website.Source: U.S. Census Bureau, Atlanta Regional CommissionDate: 2017-2021Data License: Creative Commons Attribution 4.0 International (CC by 4.0)Link to the data manifest: https://garc.maps.arcgis.com/sharing/rest/content/items/34b9adfdcc294788ba9c70bf433bd4c1/data

Comparison of sample prevalence of reported disability and SINTEF disability national survey 2017.

Differences in the number and proportion of persons with and without disabilities, aged 15 years and over, by census metropolitan areas.

Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section...Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau''s Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties..Explanation of Symbols:An ''**'' entry in the margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate..An ''-'' entry in the estimate column indicates that either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution..An ''-'' following a median estimate means the median falls in the lowest interval of an open-ended distribution..An ''+'' following a median estimate means the median falls in the upper interval of an open-ended distribution..An ''***'' entry in the margin of error column indicates that the median falls in the lowest interval or upper interval of an open-ended distribution. A statistical test is not appropriate..An ''*****'' entry in the margin of error column indicates that the estimate is controlled. A statistical test for sampling variability is not appropriate. .An ''N'' entry in the estimate and margin of error columns indicates that data for this geographic area cannot be displayed because the number of sample cases is too small..An ''(X)'' means that the estimate is not applicable or not available..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..While the 2017 American Community Survey (ACS) data generally reflect the July 2015 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas, in certain instances the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineations due to differences in the effective dates of the geographic entities..The Census Bureau introduced a new set of disability questions in the 2008 ACS questionnaire. Accordingly, comparisons of disability data from 2008 or later with data from prior years are not recommended. For more information on these questions and their evaluation in the 2006 ACS Content Test, see the Evaluation Report Covering Disability..Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables..Source: U.S. Census Bureau, 2017 American Community Survey 1-Year Estimates

Title VI of the Civil Rights Act and the Executive Order on Environmental Justice (#12898) do not provide specific guidance to evaluate EJ issues within a region's transportation planning process. Therefore, MPOs must devise their own methods for ensuring that EJ issues are investigated and evaluated in transportation decision-making. In 2001, DVRPC developed an EJ technical assessment to identify direct and disparate impacts of its plans, programs, and planning process on defined population groups in the Delaware Valley region. This assessment, called the Indicators of Potential Disadvantage Methodology, is utilized in a variety of DVRPC plans and programs. DVRPC currently assesses the following population groups, defined by the U.S. Census Bureau:

Youth

Older Adults

Female

Racial Minority

Ethnic Minority

Foreign-Born

Disabled

Limited English Proficiency

Low-Income Census tables used to gather data from the 2017-2021 American Community Survey 5-Year Estimates Using U.S. Census American Community Survey data, the population groups listed above are identified and located at the census tract level. Data is gathered at the regional level, combining populations from each of the nine counties, for either individuals or households, depending on the indicator. From there, the total number of persons in each demographic group is divided by the appropriate universe (either population or households) for the nine-county region, providing a regional average for that population group. Any census tract that meets or exceeds the regional average level, or threshold, is considered an EJ-sensitive tract for that group. Census tables used to gather data from the 2017-2021 American Community Survey 5-Year Estimates. For more information and for methodology, visit DVRPC's website: https://www.dvrpc.org/GetInvolved/TitleVI/ For technical documentation visit DVRPC's GitHub IPD repo: https://github.com/dvrpc/ipd Source of tract boundaries: US Census Bureau. The TIGER/Line Files Note: Tracts with null values should be symbolized as "Insufficient or No Data". Data Dictionary for Attributes: (Source = DVRPC indicates a calculated field) Field Alias Description Source geoid20 GEOID20 Census tract identifier (text) Census statefp20 State FIPS FIPS Code for State Census countyfp20 County FIPS FIPS Code for County Census name20 Tract Number Tract Number Census d_class Disabled Classification Classification of tract's disabled percentage as: well below average, below average, average, above average, or well above average DVRPC d_cntest Disabled Count Estimate Estimated count of disabled population Census d_cntmoe Disabled Count MOE Margin of error for estimated count of disabled population Census d_pctest Disabled Percentage Estimate Estimated percentage of disabled population DVRPC d_pctile Disabled Percentile Tract's regional percentile for percentage disabled DVRPC d_pctmoe Disabled Percentage MOE Margin of error for percentage of disabled population DVRPC d_score Disabled Score Corresponding numeric score for tract's disabled classification: 0, 1, 2, 3, 4 DVRPC em_class Ethnic Minority Classification Classification of tract's Hispanic/Latino percentage as: well below average, below average, average, above average, or well above average DVRPC em_cntest Ethnic Minority Count Estimate Estimated count of Hispanic/Latino population Census em_cntmoe Ethnic Minority Count MOE Margin of error for estimated count of Hispanic/Latino population Census em_pctest Ethnic Minority Percentage Estimate Estimated percentage of Hispanic/Latino population DVRPC em_pctile Ethnic Minority Percentile Tract's regional percentile for percentage Hispanic/Latino DVRPC em_pctmoe Ethnic Minority Percentage MOE Margin of error for percentage of Hispanic/Latino population DVRPC em_score Ethnic Minority Score Corresponding numeric score for tract's Hispanic/Latino classification: 0, 1, 2, 3, 4 DVRPC f_class Female Classification Classification of tract's female percentage as: well below average, below average, average, above average, or well above average DVRPC f_cntest Female Count Estimate Estimated count of female population Census f_cntmoe Female Count MOE Margin of error for estimated count of female population Census f_pctest Female Percentage Estimate Estimated percentage of female population DVRPC f_pctile Female Percentile Tract's regional percentile for percentage female DVRPC f_pctmoe Female Percentage MOE Margin of error for percentage of female population DVRPC f_score Female Score Corresponding numeric score for tract's female classification: 0, 1, 2, 3, 4 DVRPC fb_class Foreign Born Classification Classification of tract's foreign born percentage as: well below average, below average, average, above average, or well above average DVRPC fb_cntest Foreign Born Count Estimate Estimated count of foreign born population Census fb_cntmoe Foreign Born Count MOE Margin of error for estimated count of foreign born population Census fb_pctest Foreign Born Percentage Estimate Estimated percentage of foreign born population DVRPC fb_pctile Foreign Born Percentile Tract's regional percentile for percentage foreign born DVRPC fb_pctmoe Foreign Born Percentage MOE Margin of error for percentage of foreign born population DVRPC fb_score Foreign Born Score Corresponding numeric score for tract's foreign born classification: 0, 1, 2, 3, 4 DVRPC lep_class Limited English Proficiency Count Estimate Estimated count of limited english proficiency population Census lep_cntest Limited English Proficiency Count MOE Margin of error for estimated count of limited english proficiency population Census lep_cntmoe Limited English Proficiency Percentage Estimate Estimated percentage of limited english proficiency population DVRPC lep_pctest Limited English Proficiency Percentage MOE Margin of error for percentage of limited english proficiency population DVRPC lep_pctile Limited English Proficiency Percentile Tract's regional percentile for percentage limited english proficiency DVRPC lep_pctmoe Limited English Proficiency Classification Classification of tract's limited english proficiency percentage as: well below average, below average, average, above average, or well above average DVRPC lep_score Limited English Proficiency Score Corresponding numeric score for tract's limited english proficiency classification: 0, 1, 2, 3, 4 DVRPC li_class Low Income Classification Classification of tract's low income percentage as: well below average, below average, average, above average, or well above average DVRPC li_cntest Low Income Count Estimate Estimated count of low income (below 200% of poverty level) population Census li_cntmoe Low Income Count MOE Margin of error for estimated count of low income population Census li_pctest Low Income Percentage Estimate Estimated percentage of low income (below 200% of poverty level) population DVRPC li_pctile Low Income Percentile Tract's regional percentile for percentage low income DVRPC li_pctmoe Low Income Percentage MOE Margin of error for percentage of low income population DVRPC li_score Low Income Score Corresponding numeric score for tract's low income classification: 0, 1, 2, 3, 4 DVRPC oa_class Older Adult Classification Classification of tract's older adult percentage as: well below average, below average, average, above average, or well above average DVRPC oa_cntest Older Adult Count Estimate Estimated count of older adult population (65 years or older) Census oa_cntmoe Older Adult Count MOE Margin of error for estimated count of older adult population Census oa_pctest Older Adult Percentage Estimate Estimated percentage of older adult population (65 years or older) DVRPC oa_pctile Older Adult Percentile Tract's regional percentile for percentage older adult DVRPC oa_pctmoe Older Adult Percentage MOE Margin of error for percentage of older adult population DVRPC oa_score Older Adult Score Corresponding numeric score for tract's older adult classification: 0, 1, 2, 3, 4 DVRPC rm_class Racial Minority Classification Classification of tract's non-white percentage as: well below average, below average, average, above average, or well above average DVRPC rm_cntest Racial Minority Count Estimate Estimated count of non-white population DVRPC rm_cntmoe Racial Minority Count MOE Margin of error for estimated count of non-white population DVRPC rm_pctest Racial Minority Percentage Estimate Estimated percentage of non-white population DVRPC rm_pctile Racial Minority Percentile Tract's regional percentile for percentage non-white DVRPC rm_pctmoe Racial Minority Percentage MOE Margin of error for percentage of non-white population DVRPC rm_score Racial Minority Score Corresponding numeric score for tract's non-white classification: 0, 1, 2, 3, 4 DVRPC y_class Youth Classification Classification of tract's youth percentage as: well below average, below average, average, above average, or well above average DVRPC y_cntest Youth Count Estimate Estimated count of youth population (under 18 years) Census y_cntmoe Youth Count MOE Margin of error for estimated count of youth population Census y_pctest Youth Percentage Estimate Estimated percentage of youth population (under 18 years) DVRPC y_pctile Youth Percentile Tract's regional percentile for percentage youth DVRPC y_pctmoe Youth Percentage MOE Margin of error for percentage of youth population DVRPC y_score Youth Score Corresponding numeric score for tract's youth classification: 0, 1, 2, 3, 4 DVRPC ipd_score Composite Score Overall score adding the classification scores across all nine variables DVRPC u_tpopest Total Population Estimate Estimated total population of tract (universe [or denominator] for youth, older adult, female, racial minoriry, ethnic minority, & foreign born) Census u_tpopmoe Total Population MOE Margin of error for estimated total population of tract Census u_pop6est Population 6+ Estimated population over five years of age (universe [or