The prevalence of disabilities in the United States shows a clear correlation with age, with nearly half of Americans aged 75 and older experiencing some form of disability. This stark contrast to younger age groups highlights the increasing challenges faced by the elderly population in maintaining their independence and quality of life. Disability rates across age groups According to 2023 data, only 0.7 percent of children under 5 years old have a disability, compared to 6.3 percent of those aged 5 to 15. The percentage rises steadily with age, reaching 11.2 percent for adults between 21 and 64 years old. A significant jump occurs in the 65 to 74 age group, where 23.9 percent have a disability. The most dramatic increase is seen in those 75 and older, with 45.3 percent experiencing some form of disability. These figures underscore the importance of accessible services and support systems for older Americans. The Individuals with Disabilities Education Act (IDEA) The prevalence of disabilities among younger Americans has significant implications for the education system. The Individuals with Disabilities Education Act (IDEA) is a law in the United States that guarantees the right to a free appropriate education for children with disabilities. In the 2021/22 academic year, 7.26 million disabled individuals aged 3 to 21 were covered by the Individuals with Disabilities Education Act (IDEA). This number includes approximately 25,000 children with traumatic brain injuries and 434,000 with intellectual disabilities.

In 2023, the U.S. states with the highest share of the population that had a disability were West Virginia, Arkansas, and Kentucky. At that time, around 19.7 percent of the population of West Virginia had some form of disability. The states with the lowest rates of disability were New Jersey, Utah, and Minnesota. Disability in the United States A disability is any condition, either physical or mental, that impairs one’s ability to do certain activities. Some examples of disabilities are those that affect one’s vision, hearing, movement, or learning. It is estimated that around 14 percent of the population in the United States suffers from some form of disability. The prevalence of disability increases with age, with 46 percent of those aged 75 years and older with a disability, compared to just six percent of those aged 5 to 15 years. Vision impairment One common form of disability comes from vision impairment. In 2023, around 3.6 percent of the population of West Virginia had a vision disability, meaning they were blind or had serious difficulty seeing even when wearing glasses. The leading causes of visual disability are age-related and include diseases such as cataracts, glaucoma, and age-related macular degeneration. This is clear when viewing the prevalence of vision disability by age. It is estimated that 8.3 percent of those aged 75 years and older in the United States have a vision disability, compared to 4.3 percent of those aged 65 to 74 and only 0.9 percent of those aged 5 to 15 years.

Users can access data pertaining to individuals with disabilities. Topics include but are not limited to: people with disabilities’ access to employment, technology, healthcare, and community based services. Background The Disability Statistics Center is based at the Institute for Health and Aging at the University of California, San Francisco (UCSF). The Disability Statistics Center generates reports ranging from employment opportunities, Medicaid home and community-based services, mobility device use, computer and internet use, wheelchair use, vocational rehabilitation, education, medical expenditures, and functional limitations among people with disabilities. User functiona lity Data is presented in report or abstract form and can be downloaded in PDF or HTML formats by clicking on the publications link. All reports and abstracts use United States data. Additional data sources are listed under “Finding Disability Data” and include data from the United States as well as international data. Data Notes The data sources are clearly referenced for each article. The most recent publications are from 2003. There is no indication on the site when the data will be updated.

Graph and download economic data for Population - With a Disability, 16 Years and over (LNU00074597) from Jun 2008 to Aug 2025 about disability, civilian, 16 years +, population, and USA.

Graph and download economic data for Unemployment Rate - With a Disability, 16 Years and over (LNU04074597) from Jun 2008 to Aug 2025 about disability, 16 years +, household survey, unemployment, rate, and USA.

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...

Context

I've published a few different datasets targeting people with disabilities. I am interested in the topic because I seek to help other people with disabilities (I am a data scientist with a disability).

This particular dataset is most useful for viewing the number and % of people with disabilities by age and demographics within the United States. It also includes statistics by sex.

Content

This dataset is reformatted already. It is the 2018 American Community Survey from Census.gov. It's more useable for visualization and analysis this way.

I will work on cleaning up 2017 so that you can get a year over year comparison.

Acknowledgements

ACS, all topics covered: https://www.census.gov/programs-surveys/acs/guidance/subjects.html

Source Data: https://data.census.gov/cedsci/table?d=ACS%201-Year%20Estimates%20Detailed%20Tables&q=B18&table=B18101&tid=ACSDT1Y2018.B18101&lastDisplayedRow=27

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.

In 2023, it was estimated that around 14 percent of the population of the U.S. had some form of disability, such as a vision disability, hearing disability, or cognitive disability. This statistic presents the percentage of people in the U.S. who had a disability from 2008 to 2023.

In 2023, it was estimated that around ** percent of people in the United States living with a disability were in poverty. In comparison, the poverty rate among people in the U.S. without a disability was **** percent. A disability is any physical or mental condition that significantly impacts a person's ability to carry out daily tasks or life activities. How many people in the United States are disabled? In 2023, around ** percent of people in the United States were thought to be living with a disability. Types of disabilities include those that affect hearing, cognition, self-care, mobility, and vision. The most common type of disability in the United States is ambulatory disabilities, which impairs a person’s ability to walk. In 2023, almost ** percent of those aged 75 years and older in the U.S. had an ambulatory disability. However, disabilities are far less common among younger people, with less than **** percent of those aged 21 to 64 suffering from an ambulatory disability. Employment among the disabled The most obvious reason why the poverty rate among those with a disability is higher than those without a disability is because disabilities affect a person’s ability to work and be employed. In 2023, the employment rate for those with a disability was **** percent, compared to an employment rate of **** percent among those without a disability. Those with hearing disabilities are the most likely to be employed, with a rate of around ** percent, compared to an employment rate of ** percent among those with an ambulatory disability. Still, those with disabilities who do work have lower annual median earnings than those without disabilities. In 2023, the annual median earnings for U.S. adults without a disability were ****** U.S. dollars, compared to ****** U.S. dollars for those with a disability.

Graph and download economic data for Employed - With a Disability, 65 Years and over (LNU02075600) from Jun 2008 to Aug 2025 about 65 years +, disability, household survey, employment, and USA.

Graph and download economic data for Employment-Population Ratio - With a Disability, 16 Years and over (LNU02374597) from Jun 2008 to Aug 2025 about disability, employment-population ratio, 16 years +, household survey, population, employment, and USA.

Graph and download economic data for Labor Force Participation Rate - With No Disability, 16 to 64 Years, Men (LNU01376940) from Jun 2008 to Aug 2025 about 16 to 64 years, disability, males, participation, civilian, labor force, labor, household survey, rate, and USA.

Graph and download economic data for Not in Labor Force - With a Disability, 16 to 64 Years, Men (LNU05076955) from Jun 2008 to Aug 2025 about 16 to 64 years, disability, males, labor force, labor, household survey, and USA.

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..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..Source: U.S. Census Bureau, 2021 American Community Survey 1-Year Estimates.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..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..For cognitive difficulty, ambulatory difficulty, and self-care difficulty, the 'Population under 18 years' includes persons aged 5 to 17. Children under 5 are not included in these measures..The 2021 American Community Survey (ACS) data generally reflect the March 2020 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..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..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.

The Survey of Disability and Work was designed to examine the economic, medical, and social consequences of limitation in work activity for the disabled person and the person's family, including eligibility for public income-maintenance programs. This study includes information on disability program provisions and the public's knowledge of these government programs, as well as the source for this information and advice as to whether or not to apply for any of the various kinds of benefits. Other objectives of this survey were to examine work incentives and income adequacy as they affect a disabled person's inclination to apply for benefits or to return to the labor force once on the rolls. Measures of medical severity (in terms of symptoms and diagnoses) were established, as well as, the number and characteristics of the disabled, the proportion of different forms of health problems, national disability rates for different races and age groups, and the proportion of the disabled whose total family income falls below the poverty level. Included in this data collection are variables on the labor force, work experience and limitations, job satisfaction, attitudinal data, family income and background, government programs, and disability benefits.

In 2023, the unemployment rate of persons with a disability was at 7.2 percent in the United States. This was a decrease from the previous year, when the unemployment rate was at 7.6 percent. The high unemployment among persons with disabilities may be due to the COVID-19 pandemic that has impacted everyone's employment, as can be seen in the unemployment rate of adults in the United States. The persons with a disability section of the Current Population Survey (CPS) is a set of six questions to identify persons who have physical, mental, or emotional conditions that cause serious difficulty with their daily activities. Disability in the labor force The U.S. Bureau of Labor Statistics (BLS) shows the unemployment rate of persons with a disability that have the ability to participate in the civilian labor force. In 2020 around 20.5 percent of persons with disabilities in the United States participated in the civilian labor force. Among those capable of participating in the civilian labor force, persons with a disability tend to have a higher chance of employment the higher their level of education. Persons with a disability that had a bachelor's degree or higher had the highest employment rate in 2020 at 25.7 percent. Social Security benefits Due to the inability to work, or the lack of access to suitable employment, many persons with a disability rely on government sources for financial aid. A portion of civilian paychecks are taxed to fund programs like the Old-Age, Survivors, and Disability Insurance (OASDI) and Supplemental Security Income (SSI) which provide this aid. In 2018, around 12.46 million disabled persons received OASDI or SSI benefits in the United States.

Users can download reports and data on disabilities in the United States. Background The National Health Interview Survey on Disability (NHIS-D) was a supplement to the National Health Interview Survey (NHIS), both conducted by the Centers for Disease Control and Prevention (CDC). The purpose of the survey was to gather information to better understand disability, to develop policies, and to gather statistics on a number of health conditions. There were 3 additional sections used exclusively to gather information about children with disabilities: spec ial health needs, special education, and early childhood development. User Functionality Users can download the following: Report on Disability, all the surveys (including the ones for children), the data analysis reports, and the data sets. Data can usually be viewed by age group. Links to resources are also provided on the site. Data NotesThe NHIS- D was conducted in 1994 and 1995.

Measures data in specific areas related to the employment of persons with disabilities. Gives labor force participation rates, work history, barriers to employment, and types of workplace accommodations for persons with disabilities.

This layer shows Disability Status of the Civilian Noninstitutionalized Population and Households with 1+ Person with a Disability. This is shown by state and county boundaries. This service contains the 2018-2022 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: 2018-2022ACS Table(s): DP02, S2201, S1810 Data downloaded from: Census Bureau's API for American Community Survey Date of API call: January 18, 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. 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.