The disability employment gap is defined as the difference between the employment rates of people with no and those with some or severe limitation in their daily activities, aged 20-64. The employment rate is calculated by dividing the number of persons aged 20 to 64 in employment by the total population of the same age group. Source: EU Statistics on Income and Living Conditions (EU-SILC).

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

The disability employment gap is defined as the difference between the employment rates of people with no and those with some or severe limitation in their daily activities, aged 20-64. The employment rate is calculated by dividing the number of persons aged 20 to 64 in employment by the total population of the same age group. Source: EU Statistics on Income and Living Conditions (EU-SILC).

In 2023, the employment rate of women with one or more disability in the United States stood at **** percent. This was significantly lower than the rate of men with one or more disability, which was **** the same year.

Disability employment gap by level of activity limitation and sex (source EU-SILC)

The European Statistics of Income and Living Condition (EU-SILC) survey contains a small module on health, composed of 3 variables on health status and 4 variables on unmet needs for health care.

The variables on health status represent the so called Minimum European Health Module (MEHM), and measures 3 different concepts of health:

• Self-perceived health
• Chronic morbidity (people having a long-standing illness or health problem)
• Activity limitation – disability (self-perceived long-standing limitations in usual activities due to health problems)

The variables on unmet needs for health care targets two broad types of services: medical care and dental care. The variables refer to the respondent's own assessment of whether he or she needed the respective type of examination or treatment, but did not have it and if so what was the main reason of not having it, Eurostat currently disseminates the following indicators for unmet needs:

• Self-reported unmet needs for medical examination for reasons of barriers of access
• Self-reported unmet needs for medical examination by reason
• Self-reported unmet needs for dental examination by reason

All indicators are expressed as percentages within (or share of) the population and breakdowns are given by: sex, age, labour status, educational attainment level, and income quintile group.

Data for individual countries are disseminated starting the fourth quarter of year N+1 (where N = year of data collection). EU aggregates and health indicators for all countries (provided that the data is available) for year N are usually published by the end of February N+2.

Difference in employment rate between gender, ethnic groups and disability status. The following employment gaps are covered: Male - Female gap Non-disabled - Disabled gap (also split by gender) White - All ethnic minority gap (also split by gender) White - Mixed ethnicity gap (also split by gender) White - Indian gap (also split by gender) White - Pakistani/Bangladeshi gap (also split by gender) White - Black/Black British gap (also split by gender) White - Other ethnicities gap (also split by gender) This dataset is one of the Greater London Authority's measures of Economic Fairness. Click here to find out more.

Difference in employment rate between gender, ethnic groups and disability status. The following employment gaps are covered: Male - Female gap Non-disabled - Disabled gap (also split by gender) White - All ethnic minority gap (also split by gender) White - Mixed ethnicity gap (also split by gender) White - Indian gap (also split by gender) White - Pakistani/Bangladeshi gap (also split by gender) White - Black/Black British gap (also split by gender) White - Other ethnicities gap (also split by gender) This dataset is one of the Greater London Authority's measures of Economic Fairness. Click here to find out more.

Disability employment gap by level of activity limitation and sex (source EU-SILC) Copyright notice and free re-use of data on: https://ec.europa.eu/eurostat/about-us/policies/copyright

This dataset contains disability pay gap estimates for all employees in London and the UK.

The disability pay gap is the difference in the average hourly wage of non-disabled employees and disabled employees across a workforce. If disabled employees do more of the less well paid jobs within an organisation than the non-disabled persons, the disablity pay gap is usually bigger.

This dataset is one of the Greater London Authority's measures of Economic Fairness. Click here to find out more.

Разрыв в занятости по инвалидности в зависимости от уровня ограничения активности и пола. Период сбора данных: 2010 - 2024 гг. Количество наблюдений: 3551. Код набора данных: TEPSR_SP200. Тип: НАБОР ДАННЫХ. Последнее обновление данных: 2024-07-12T23:00:00+0200. Последнее структурное изменение: 2024-07-12T23:00:00+0200. Disability employment gap by level of activity limitation and sex. Data period: 2010 - 2024. Number of observations: 3,551. Dataset code: TEPSR_SP200. Type: DATASET. Last data update: 2024-07-12T23:00:00+0200. Last structural change: 2024-07-12T23:00:00+0200.

Estimates for employment rates and disability gaps.

Estimates for employment rates and disability gaps.

Research has shed light on the employment barriers faced by individuals with disabilities, and by racialized people. The challenges faced by people belonging to both marginalized groups are less well-understood. The purpose of this scoping review was to examine existing research on labour market and workplace experiences of racialized people with disabilities, and to identify how ableism and racism intersect to shape employment experiences and outcomes. Seven international databases were searched, covering the period from 2000 to April 2022. Four reviewers independently conducted the screening, and data extraction and analysis were performed on 44 articles that met our inclusion criteria. The findings highlighted rates of workplace ableism and racism (including discrimination allegations and perceived discrimination); types and forms of experiences arising from the intersection of ableism and racism (including unique individual stereotyping and systemic and institutional discrimination); and the role of other demographic variables. The intersection of ableism and racism impacted labour market outcomes, well-being in the workplace, and career/professional advancement. Our review highlights the need for greater in-depth research focusing explicitly on the intersection of ableism and racism (and of other forms of discrimination), to better understand and address the barriers that racialized people with disabilities face in employment.IMPLICATIONS FOR REHABILITATIONThe experiences of racialized people with disabilities have been under explored, and clinicians and rehabilitation specialists should consider incorporating intersectionality into their practices to better understand and serve these populations.Ableism and racism do not operate in isolation, and clinicians and other professionals need to be aware that racialized people with disabilities may face unique challenges and barriers as a result.Service providers should aim to address gaps and inequities in services faced by racialized people with disabilities which may prevent them from finding and/or maintaining meaningful employment. The experiences of racialized people with disabilities have been under explored, and clinicians and rehabilitation specialists should consider incorporating intersectionality into their practices to better understand and serve these populations. Ableism and racism do not operate in isolation, and clinicians and other professionals need to be aware that racialized people with disabilities may face unique challenges and barriers as a result. Service providers should aim to address gaps and inequities in services faced by racialized people with disabilities which may prevent them from finding and/or maintaining meaningful employment.

Introduction: Persons with mental illness experience social life restriction and stigma that may have implications for their work ability. The aims of this study are (i) to report experienced and anticipated discrimination and social functioning in persons with mental disabilities in Kenya and (ii) to investigate the association between experienced and anticipated discrimination, social functioning, and employment in this population.Materials and Methods: Cross-sectional study design where we randomly recruited 72 persons with mental illness through two networks of persons with psychosocial disabilities in Kenya. Experienced and anticipated discrimination were measured using the Discrimination and Stigma Scale version 12 (DISC 12) while social functioning was measured using the Social Functioning questionnaire (SFQ).Results: Experienced discrimination was reported by 81.9% in making or keeping friends, 69.7 and 56.3% in finding or keeping job, respectively, and 63.3% in dating or having an intimate relationship. Anticipated discrimination stopped 59.2% from applying for work, 40.8% from applying for education or training courses, and 63.4% from having a close personal relationship. Females reported an overall higher experienced discrimination than males. Unemployed participants had slightly increased rates of experienced and anticipated discrimination (9.5 vs. 9.1 and 2.5 vs. 2.3, respectively) (p > 0.05), while there was a significant association between impaired social functioning and unemployment [14.0 vs. 11.2 (p = 0.037)].Conclusion: The rates of experienced and anticipated discrimination faced by persons with mental disabilities in Kenya is high and with significant gender disparity. Although no strong associations were observed between experienced and anticipated discrimination and employment, impaired social functioning of persons with mental disabilities seems to have implications for employment. Further research is essential to understand the predictors of the discrimination and measures to reduce them in persons with psychosocial disabilities.

The RAND Center for Population Health and Health Disparities (CPHHD) Data Core Series is composed of a wide selection of analytical measures, encompassing a variety of domains, all derived from a number of disparate data sources. The CPHHD Data Core's central focus is on geographic measures for census tracts, counties, and Metropolitan Statistical Areas (MSAs) from two distinct geo-reference points, 1990 and 2000. The current study, Disability, contains cross-sectional data from the year 2000. Based on the Decennial Census Special Table Series published by the Administration on Aging, this study contains a large number of disability measures categorized by age (55+), type of disability (sensory, learning, employment, and self-care), and poverty status.

ObjectivesTo examine disability-related disparities in participation in national health screenings in South Korea and to determine how these gaps vary by disability severity, type, and socio-economic factors.MethodsA trend analysis of screening participation from 2012 to 2020 and multivariable logistic regression for 2019–2020 were conducted using the National Health Insurance Service database, linking eligibility, health screening, and disability registration data. The cohort comprised 10,413,089 adults aged ≥40 years (20% population sample). Annual screening uptake was the outcome; predictors included disability status, severity, type, employment, sex, income, insurance, and region.ResultsScreening uptake rose overall between 2012 and 2020 yet remained lower for people with disabilities, particularly those with severe physical, visual, communication, mental, developmental, epilepsy, and internal disabilities. Age-sex standardization and socio-economic adjustment attenuated but did not remove gaps. Employment narrowed disparities, whereas women with disabilities faced wider gaps than men.ConclusionDespite nationwide gains, disability-related inequities in preventive screening persist, amplified by severe impairment, unemployment, and female gender. Policies should prioritize accessible facilities, targeted outreach, and socio-economic support to ensure equitable screening for people with disabilities.

This dataset provides workforce representation by Employment Equity Occupational Groups within the federally regulated private sectors for designated Employment Equity groups. It is now available on the Open Government portal to assist employers under the Legislated Employment Equity Program (LEEP) in supporting their employment equity gap analysis in meeting employment equity obligations.