Employment outcomes for disabled people in the UK aged 16 to 64 years, with analysis by age, sex, impairment type, country, region, type of occupation and working patterns using Annual Population Survey (APS) data.

Key Table Information.Table Title.Disability Characteristics.Table ID.ACSST1Y2024.S1810.Survey/Program.American Community Survey.Year.2024.Dataset.ACS 1-Year Estimates Subject Tables.Source.U.S. Census Bureau, 2024 American Community Survey, 1-Year Estimates.Dataset Universe.The dataset universe of the American Community Survey (ACS) is the U.S. resident population and housing. For more information about ACS residence rules, see the ACS Design and Methodology Report. Note that each table describes the specific universe of interest for that set of estimates..Methodology.Unit(s) of Observation.American Community Survey (ACS) data are collected from individuals living in housing units and group quarters, and about housing units whether occupied or vacant. For more information about ACS sampling and data collection, see the ACS Design and Methodology Report..Geography Coverage.ACS data generally reflect the geographic boundaries of legal and statistical areas as of January 1 of the estimate year. For more information, see Geography Boundaries by Year.Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on 2020 Census data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Sampling.The ACS consists of two separate samples: housing unit addresses and group quarters facilities. Independent housing unit address samples are selected for each county or county-equivalent in the U.S. and Puerto Rico, with sampling rates depending on a measure of size for the area. For more information on sampling in the ACS, see the Accuracy of the Data document..Confidentiality.The Census Bureau has modified or suppressed some estimates in ACS data products to protect respondents' confidentiality. Title 13 United States Code, Section 9, prohibits the Census Bureau from publishing results in which an individual's data can be identified. For more information on confidentiality protection in the ACS, see the Accuracy of the Data document..Technical Documentation/Methodology.Information about the American Community Survey (ACS) can be found on the ACS website. Supporting documentation including code lists, subject definitions, data accuracy, and statistical testing, and a full list of ACS tables and table shells (without estimates) can be found on the Technical Documentation section of the ACS website.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section.Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables.Users must consider potential differences in geographic boundaries, questionnaire content or coding, or other methodological issues when comparing ACS data from different years. Statistically significant differences shown in ACS Comparison Profiles, or in data users' own analysis, may be the result of these differences and thus might not necessarily reflect changes to the social, economic, housing, or demographic characteristics being compared. For more information, see Comparing ACS Data..Weights.ACS estimates are obtained from a raking ratio estimation procedure that results in the assignment of two sets of weights: a weight to each sample person record and a weight to each sample housing unit record. Estimates of person characteristics are based on the person weight. Estimates of family, household, and housing unit characteristics are based on the housing unit weight. For any given geographic area, a characteristic total is estimated by summing the weights assigned to the persons, households, families or housing units possessing the characteristic in the geographic area. For more information on weighting and estimation in the ACS, see the Accuracy of the Data document.Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, the decennial census is the official source of population totals for April 1st of each decennial year. In between censuses, the Census Bureau's Population Estimates Program produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of hous...

This table shows working age population that has a disability and Employment, unemployment, economic activity and inactivity rates by disability (includes Equalities Act Core disabled, DDA & work-limiting disabled) The definition of ‘disability’ under the Equality Act 2010 shows a person has a disability if: they have a physical or mental impairment the impairment has a substantial and long-term adverse effect on their ability to perform normal day-to-day activities For the purposes of the Act, these words have the following meanings: 'substantial' means more than minor or trivial 'long-term' means that the effect of the impairment has lasted or is likely to last for at least twelve months (there are special rules covering recurring or fluctuating conditions) 'normal day-to-day activities' include everyday things like eating, washing, walking and going shopping There are additional provisions relating to people with progressive conditions. People with HIV, cancer or multiple sclerosis are protected by the Act from the point of diagnosis. People with some visual impairments are automatically deemed to be disabled. 18/03/2015 Data has been reweighted in line with the latest ONS estimates. 2013 data is not available for disability measures from this survey. Due to changes in the health questions on the Annual Population Survey there is quite a large discontinuity in the estimates from the Apr 2012 to Mar 2013 period onwards. These became available again from the Apr 2013 to March 2014 period as new variables. 95% confidence interval of percent figure (+/-).

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

Labour market status of disabled people, UK, published quarterly, non-seasonally adjusted. Labour Force Survey. These are official statistics in development.

2013-2023 Virginia Disability Characteristics by Census Tract. Contains estimates and margins of error.

Special data considerations: Large negative values do exist (more detail below) and should be addressed prior to graphing or aggregating the data. A null value in the estimate means there is no data available for the requested geography.

A value of -888,888,888 indicates that the estimate or margin of error is not applicable or not available.

U.S. Census Bureau; American Community Survey, American Community Survey 5-Year Estimates, Table S1810 Data accessed from: Census Bureau's API for American Community Survey (https://www.census.gov/data/developers/data-sets.html)

The United States Census Bureau's American Community Survey (ACS): -What is the American Community Survey? (https://www.census.gov/programs-surveys/acs/about.html) -Geography & ACS (https://www.census.gov/programs-surveys/acs/geography-acs.html) -Technical Documentation (https://www.census.gov/programs-surveys/acs/technical-documentation.html)

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. (https://www.census.gov/programs-surveys/acs/technical-documentation/code-lists.html)

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. (https://www.census.gov/acs/www/methodology/sample_size_and_data_quality/)

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.

Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation https://www.census.gov/programs-surveys/acs/technical-documentation.html). The effect of nonsampling error is not represented in these tables.

2005/6 KIHBS Table 5.13: Percentage Distribution of Population by type of Disability County Estimates

Notice: The U.S. Census Bureau is delaying the release of the 2016-2020 ACS 5-year data until March 2022. For more information, please read the Census Bureau statement regarding this matter. -----------------------------------------This layer shows six different types of disability. Data is from US Census American Community Survey (ACS) 5-year estimates and joined with Tempe census tracts. 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). Layer includes percent of population with a disability categorized as: · an independent living difficulty · a hearing difficulty · an ambulatory difficulty · a vision difficulty · a cognitive difficulty · a selfcare difficulty Data is from US Census American Community Survey (ACS) 5-year estimates. Vintage: 2015-2019 ACS 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 Date of Census update: December 10, 2020 National Figures: data.census.gov

Employment rates broken down by gender, age or disability. The data are taken from the Annual Population Survey (APS), produced by the Office for National Statistics. Employment Rate by Gender, for working age, and Age groups: 16-24, 25-34, 35-49, 50-64, and disability groups: All disabled, Both DDA & also work-limiting, DDA only disabled, Work-limiting only disabled, Not disabled, recently replaced with: Equality Act core or work-limiting disabled, EA core disabled, Work-limiting disabled, Not EA core or work-limiting disabled. 18/03/2015 Data has been reweighted in line with the latest ONS estimates.

Percentage of people who use services who have control over their daily life - Disabled People (ASC User Survey)

Context

There are more than 26.8 million people or 2.2% of the population currently who have disabilities in India (Census 2011) which itself is said to be a very conservative estimate. There is a lot of stigma associated with the disabled community and a very high inequality in terms of social as well as monetary status between the disabled community and the entire population.

Content

The data in the csv file gives us the statewise values of the following:

1.State 2.number_disabled : It gives the total number of people in the region that are disabled. 3.total_population: It gives the total number of people in the region. 4.percent_disabled: It gives the total percentage of the people disabled in the given region. 5.literacy_rate_disabled : It represents the literacy rate of the disabled community in the region. 6.literacy_rate_general : It shows the total literacy rate of the population in the state. 7.workforce_rate_disabled : It tells us the total percent of all the disabled people that are part of the workforce in the given region.(inclusive all ages). 8.workforce_rate_general : It shows the total percent of all the people that are part of the workforce in the given region(inclusive of all ages).

The aim of this publication is to provide information about the key differences in healthcare between people with a learning disability and those without. It contains aggregated data on key health issues for people who are recorded by their GP as having a learning disability, and comparative data about a control group who are not recorded by their GP as having a learning disability. Six new indicators were introduced in the 2022-23 reporting year for patients with and without a recorded learning disability. These relate to: • Patients with an eating disorder • Patients with both an eating disorder and autism diagnosis • Patients with a diagnosis of autism who are currently treated with antidepressants More information on these changes can be found in the Data Quality section of this publication. Data has been collected from participating practices using EMIS and Cegedim Healthcare Systems GP systems.

Series Name: [ILO] Proportion of population with severe disabilities receiving disability cash benefit by sex (percent)Series Code: SI_COV_DISABRelease Version: 2021.Q2.G.03 This dataset is part of the Global SDG Indicator Database compiled through the UN System in preparation for the Secretary-General's annual report on Progress towards the Sustainable Development Goals.Indicator 1.3.1: Proportion of population covered by social protection floors/systems, by sex, distinguishing children, unemployed persons, older persons, persons with disabilities, pregnant women, newborns, work-injury victims and the poor and the vulnerableTarget 1.3: Implement nationally appropriate social protection systems and measures for all, including floors, and by 2030 achieve substantial coverage of the poor and the vulnerableGoal 1: End poverty in all its forms everywhereFor more information on the compilation methodology of this dataset, see https://unstats.un.org/sdgs/metadata/

People who assessed their day-to-day activities as limited by long-term physical or mental health conditions or illnesses are considered disabled. This definition of a disabled person meets the harmonised standard for measuring disability and is in line with the Equality Act (2010).CoverageThis dataset is focused on the data for Birmingham at Ward level. Also available at LSOA, MSOA and Constituency levels.About the 2021 CensusThe Census takes place every 10 years and gives us a picture of all the people and households in England and Wales.Protecting personal dataThe ONS sometimes need to make changes to data if it is possible to identify individuals. This is known as statistical disclosure control. In Census 2021, they:

Swapped records (targeted record swapping), for example, if a household was likely to be identified in datasets because it has unusual characteristics, they swapped the record with a similar one from a nearby small area. Very unusual households could be swapped with one in a nearby local authority. Added small changes to some counts (cell key perturbation), for example, we might change a count of four to a three or a five. This might make small differences between tables depending on how the data are broken down when they applied perturbation.For more geographies, aggregations or topics see the link in the Reference below. Or, to create a custom dataset with multiple variables use the ONS Create a custom dataset tool.Population valueThe value column represents All usual residents.The percentage shown is the value as a percentage of All usual residents within the given geography.

This dataset provides Census 2021 estimates that classify usual residents in England and Wales by long-term health problems or disabilities, sex, age and level of deprivation. The estimates are as at Census Day, 21 March 2021. Age-standardisation allows for comparisons between populations that may contain proportions of different ages.

Census questions relating to disability enable different levels of detail in relation to the presence of conditions and extent of activity limitation people experience. For simplicity, we have referred to these as ‘categories’ as shown in the table below. We consider the Census 2021, 2011 and 2001 questions to be broadly comparable. However, the 2021 Census disability question changed compared with 2011 to align more closely with the Equality Act (2010). The potential influence of question changes should be considered when drawing comparisons between years, particularly for older age groups.

Age specific percentage

Age-specific percentages are estimates of disability prevalence in each age group, and are used to allow comparisons between specified age groups.

Age-standardised percentage

Age-standardised percentages are estimates of disability prevalence in the population, across all age groups. They allow for comparison between populations over time and across geographies, as they account for differences in the population size and age structure.

Details can be found here

Category

The measures of disability in each Census (2021, 2011 and 2001) enable different categorisations of responses to the question. These provide different levels of detail from the responses provided. Further information on the categories available is given in the "Questions_asked" sheet.

Count

The count is the number of usual residents in each category (disabled, non-disabled, disabled; limited a lot, disabled; limited a little, Non-disabled; with non-limiting condition, Non-disabled; no condition), sex, age group and geographic breakdown. To ensure that individuals cannot be identified in the data, counts and populations have been rounded to the nearest 5, and counts under 10 have not been included.

Disability

The definition of disability used in the 2021 Census is aligned with the definition of disability under the Equality Act (2010) . A person is considered disabled if they self-report having a physical or mental health condition or illness that has lasted or is expected to last 12 months or more, and that this reduces their ability to carry out day-to-day activities. Please see the questions asked tab to see how disability was defined in 2021.

Index of Multiple Deprivation and Welsh Index of Multiple Deprivation

National deciles and quintiles of area deprivation are created through ranking small geographical populations known as Lower layer Super Output Areas (LSOAs), based on their deprivation score from most to least deprived. They are then grouped into 10 (deciles) or 5 (quintiles) divisions based on the subsequent ranking. We have used the 2019 IMD and WIMD because this is the most up-to-date version at the time of publishing.

Population

The population is the number of usual residents of each sex, age group and geographic breakdown. To ensure that individuals cannot be identified in the data, counts and populations have been rounded to the nearest 5, and counts under 10 have not been included.

Usual resident

For Census 2021, a usual resident of the UK is anyone who, on census day, was in the UK and had stayed or intended to stay in the UK for a period of 12 months or more or had a permanent UK address and was outside the UK and intended to be outside the UK for less than 12 months.

This layer shows disability status by sex and age group. This is shown by tract, county, and state boundaries. This service is updated annually to contain the most currently released 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 the percentage of elderly (65+) 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. Current Vintage: 2019-2023ACS Table(s): B18101Data downloaded from: Census Bureau's API for American Community Survey Date of API call: December 12, 2024National 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. For more information about ACS layers, visit the FAQ. 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:This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb_(year)_a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2023 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. 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 RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).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 file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations: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.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.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.

Percentage of people who use services who have control over their daily life - Disabled People (ASC User Survey)

The dataset includes fiscal year data for initial claims for SSA disability benefits that were referred to a state agency for a disability determination. Specific data elements for each year and state include receipts, determinations, eligible population, and favorable determination rates.

• 'normal day-to-day activities' include everyday things like eating, washing, walking and going shopping There are additional provisions relating to people with progressive conditions. People with HIV, cancer or multiple sclerosis are protected by the Act from the point of diagnosis. People with some visual impairments are automatically deemed to be disabled. 18/03/2015 Data has been reweighted in line with the latest ONS estimates. 2013 data is not available for disability measures from this survey. Due to changes in the health questions on the Annual Population Survey there is quite a large discontinuity in the estimates from the Apr 2012 to Mar 2013 period onwards. These became available again from the Apr 2013 to March 2014 period as new variables. 95% confidence interval of percent figure (+/-).