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, 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, 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.

In 2023, it was estimated that *** percent of those aged 21 to 64 years had a cognitive disability, such as Down syndrome, autism, or dementia. This statistic presents the percentage of people in the U.S. with a cognitive disability as of 2023, by age.

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

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

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.

Graph and download economic data for Labor Force Participation Rate - With a Disability, 16 Years and over (LNU01374597) from Jun 2008 to Jul 2025 about disability, participation, civilian, 16 years +, labor force, labor, household survey, rate, and USA.

As of 2023, almost ***** percent of those living in the state of West Virginia had a cognitive disability, such as Down syndrome, autism, or dementia. This statistic shows the percentage of people in the U.S. who had a cognitive disability as of 2023, by state.

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.

As of 2023, an estimated four percent of those living in the state of West Virginia had a self-care disability. This statistic shows the percentage of people in the U.S. who had a self-care disability as of 2023, by state.

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

This data layer depicts, by census tract, the number of people that have a disability for the San Francisco Bay Region. The source data, from the United States Census Bureau, has been reprocessed by the Metropolitan Transportation Commission.

To produce this feature set, the Metropolitan Transportation Commission downloaded American Community Survey (ACS) table B18101 and joined the table to a Census 2010 tract polygon feature set. The joined feature set was then exported to create a feature set representing the disability status of persons, by tract, for the region.

The resulting attribute table had all margin of error and non-disability fields deleted and the remaining field names were changed. In addition, a percent of population field was added for each disability field and percent fields for total disabled, total male disabled, and total female disabled fields were added.

The source table used to develop this feature service is from the United States Census Bureau, 2015-2019 American Community Survey 5-Year Estimates and can be downloaded from https://data.census.gov/cedsci/table?q=B18101&g=0400000US06%241400000&tid=ACSDT5Y2019.B18101

This statistic presents the percentage of people in the U.S. who had a disability from 2008 to 2016, by type. In 2016, it was estimated that *** percent of the population of the U.S. had an ambulatory disability and *** percent had a visual disability.

*Please note that # refer to the number of people within the age group with a disability and % refers to the percent of those with a disability within that age group. Source: U.S. Census Bureau; 2012-2016 American Community Survey 5-Year Estimates, Table S1810.

This layer was developed by the Research & Analytics Division of the Atlanta Regional Commission using data from the U.S. Census Bureau's American Community Survey in order to show the count of the civilian noninstitutionalized population who are disabled by census tract in the Atlanta region. Attributes:Civilian Noninstitutionalized Population Under 18 YearsCivilian Noninstitutionalized Under 18 Years with a Disability% Civilian Noninstitutionalized Under 18 Years with a DisabilityCivilian Noninstitutionalized Population 18 to 64 YearsCivilian Noninstitutionalized 18 to 64 Years with a Disability% Civilian Noninstitutionalized 18 to 64 Years with a DisabilityCivilian Noninstitutionalized Population 65 Years and OverCivilian Noninstitutionalized 65 Years and Over with a Disability% Civilian Noninstitutionalized 65 Years and Over with a DisabilityPopulation Change per Square Mile from 2000-2010GEOID10 = The FIPS code for this geographyNAME10 = Census tract codePLNG_REGIO = Planning RegionPercent_BA_or_Higher = Percentage of the population with a Bachelor's degree or higherMedian_household_income = Median household incomeCivilian_veterans = Civilian veteransPercent_Civilian_veterans = Percentage of the population who are civilian veteransShape.STArea() = Total area in square feetSource: U.S. Census Bureau, Atlanta Regional CommissionDate: 2008-2012For additional information, please visit the Atlanta Regional Commission at www.atlantaregional.com

ContextDespite the high prevalence of work disability due to common mental disorders (CMD), no information exists on the rates and predictors of recurrence in a United States population.ObjectiveTo estimate recurrent work disability statistics and evaluate factors associated with recurrence due to CMDs including adjustment, anxiety, bipolar, and depressive disorders.MethodsRecurrent work disability statistics were calculated using a nationwide database of disability claims. For the CMDs, univariate and multiple variable analyses were used to examine demographic factors and comorbidities associated with the time to recurrence.ResultsOf the CMDs, cases with bipolar (n = 3,017) and depressive disorders (n = 20,058) had the highest recurrence densities, 98.7 and 70.9 per 1000 person-years, respectively. These rates were more than three times higher than recurrence rates for other chronic disorders (e.g., diabetes, asthma; n = 105,558) and non-chronic disorders (e.g., injury, acute illnesses; n = 153,786). Individuals with CMD were also more likely to have a subsequent disability distinct from their mental health condition. Risk factors for recurrent CMD disability included being younger, being an hourly employee, living in a geographic area with more college graduates, having more previous psychiatric visits, having a previous work leave, and the type of work industry.ConclusionsResults indicate that CMD patients may benefit from additional care and disability management both during and after their work absence to help prevent subsequent CMD and non-CMD related leaves.

Graph and download economic data for Civilian Labor Force - With a Disability, 16 Years and over (LNU01074597) from Jun 2008 to Jul 2025 about disability, civilian, 16 years +, labor force, labor, household survey, and USA.

Contains the total size of the Social Security Administration’s backlog of unprocessed initial applications for its disability benefit programs (SSDI and SSI) for 2019 and 2022 in each state. Calculations for percent change in backlog size between the two years by state and the average difference in backlog size per state on a monthly basis are also included.

Purpose: We aim to determine the prevalence and characteristics of developmental disabilities among the clinical population of children who receive hearing health care in the United States.Method: Using electronic health records of 131,709 children (0–18 years), we identified those with a diagnosis of attention deficit/hyperactivity disorder, autism spectrum disorder, vision differences, cerebral palsy, chromosomal abnormalities, delayed milestones, Down syndrome, or intellectual disability. We determined prevalence, age of first audiology encounter, age of diagnosis for the developmental disability, and hearing status based on the specific disability and the number of diagnoses. Binomial and multinomial logistic regressions were performed.Results: One in four children had a diagnosed developmental disability. The most common disabilities were delayed milestones (11.3%), vision differences (7.4%), attention-deficit/hyperactivity disorder (6.6%), and autism spectrum disorder (6.2%). Half of the children with developmental disabilities had at least one diagnosis before their first audiology encounter. Children with developmental disabilities were more likely to have a reduced hearing or an unknown hearing status than children without developmental diagnoses. For children with reduced hearing, those with developmental disabilities had higher rates of bilateral configurations and poorer hearing severity levels.Conclusions: Developmental disabilities are common among children who seek hearing health care. Moreover, developmental disabilities often co-occur with reduced hearing. Further research and advocacy efforts are critical for creating clinical practices that are inclusive of, and equitable for, children with complex and diverse developmental profiles.Supplemental Material S1. ICD-9/10 umbrella mappings for the specific developmental disabilities used in the study.Supplemental Material S2. Binomial logistic regression results for if a diagnosis of attention deficit/hyperactivity disorder (ADHD) was known at the time of the first audiology encounter.Supplemental Material S3. Binomial logistic regression results for if a diagnosis of autism spectrum disorder was known at the time of the first audiology encounter.Supplemental Material S4. Binomial logistic regression results for if a diagnosis of cerebral palsy was known at the time of the first audiology encounter.Supplemental Material S5. Binomial logistic regression results for if a diagnosis of a chromosomal abnormality was known at the time of the first audiology encounter.Supplemental Material S6. Binomial logistic regression results for if a diagnosis of delayed milestones was known at the time of the first audiology encounter.Supplemental Material S7. Binomial logistic regression results for if a diagnosis of Down syndrome was known at the time of the first audiology encounter.Supplemental Material S8. Binomial logistic regression results for if a diagnosis of an intellectual disability was known at the time of the first audiology encounter.Supplemental Material S9. Binomial logistic regression results for if a diagnosis of a vision difference was known at the time of the first audiology encounter.Bonino, A. Y., Goodwich, S. F., & Mood, D. (2025). Prevalence and characteristics of developmental disabilities among children who receive hearing health care. American Journal of Audiology, 34(1), 60–71. https://doi.org/10.1044/2024_AJA-24-00118