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

Abstract

Objectives: The main objective of the survey is to provide information about Canadian adults whose daily activities are limited because of a long-term condition or health-related problem. This information will be used to plan and evaluate services, programs and policies for adults with disabilities to help enable their full participation in Canadian society. Information from the CSD will be used by all levels of government, as well as associations for persons with disabilities and researchers working in the field of disability. Data may be used to plan and evaluate policies and programs for Canadian adults with disabilities to help enable their full participation in society. In particular, information on adults with disabilities is essential for the effective development and operation of the Employment Equity Program. Data on disability are also used to fulfil Canada's international agreement relating to the United Nations Convention on the Rights of Persons with Disabilities.

Reference Period: 2013-01-13

Periodicity of Data Collection: Quinquennial

Geographic coverage

Whole country

Analysis unit

Individuals

Universe

Population groups: 15 years and over

Total population covered: All

Economic activities: All economic activities

Sectors covered: All sectors

Labor force status: Employed persons, unemployed persons, persons outside labour force

Status in Employment: Employees, employers, own-account workers, contributing family workers, members of producers' cooperatives

Establishments: NR

Other limitations: Survey covers all age groups 15 years and over, the employment statistics cover only those aged 15 to 64

Classifications: Sex, age, level of education, other personal characteristics, type of living arrangements, status in employment, occupation (classification system: NOC), economic activity (classification system: NAICS), type of disability

Cross-classification: Na

Kind of data

Sample survey data [ssd]

Frequency of data collection

Periodicity of Data collection: Quinquennial

This dataset includes snapshot information for 33,615 individuals, including: * age * gender * living arrangement * income source(s) * communication * use of disability aids * health and medical conditions * behavioural traits * level of support need The 2010 survey was completed by agencies providing residential services. The 2013 survey was completed by agencies providing non-residential services. Responses from multiple agencies for the same client were consolidated to ensure that only one case existed for each client.

Differences in the number and proportion of persons with and without disabilities, by age group and gender, Canada, provinces and territories.

Income of individuals by disability status, age group, sex and income source, Canada, annual.

Data prior to April 1998 includes recipients of:

• general welfare assistance
• family benefits
• foster care
• handicapped children benefits

Data from April 1, 1998 onward includes recipients of:

• Ontario Works
• Ontario Disability Support Program
• Temporary Care Assistance
• Assistance for Children with Severe Disabilities

Poverty and low-income statistics by disability status, age group, sex and economic family type, Canada, annual.

This data includes the characteristics of Ontario Works and Ontario Disability Support Program cases, by census metropolitan area, and by the province including: * family type * family size * primary applicant's age and sex * consecutive months on social assistance A census metropolitan area (CMA) is formed by one or more adjacent municipalities centred on a population centre (known as the core). A CMA must have a total population of at least 100,000 of which 50,000 or more must live in the core. *[CMA]: census metropolitan area

Labour force status for adults with disabilities, by disability type and global severity, sex and age group, occasional.

This dataset contains the number of individuals actively participating in Ontario Works Employment Assistance activities, by type of activity. It contains the number of active participants in a month, on average, receiving Ontario Works income support or Ontario Disability Support Program (ODSP) income support for each of the fiscal years(1) from 2016-17 to 2022-23. The dataset shows average monthly counts grouped by Consolidated Municipal Service Manager (CMSM) or District Social Services Administration Board (DSSAB) and by Catchment Area.(1) Fiscal year refers to a twelve-month period from April to March of the following year.Contextual DocumentationDataset

This dataset contains the number of individuals actively participating in Ontario Works Employment Assistance activities, by type of activity. It contains the number of active participants in a month, on average, receiving Ontario Works income support or Ontario Disability Support Program (ODSP) income support for each of the fiscal years(1) from 2016-17 to 2022-23. The dataset shows average monthly counts grouped by Consolidated Municipal Service Manager (CMSM) or District Social Services Administration Board (DSSAB) and by Catchment Area.(1) Fiscal year refers to a twelve-month period from April to March of the following year.Contextual DocumentationDataset

This document was adapted from the Conference Board's Employers' Toolkit: Making Ontario Workplaces Accessible to People with Disabilities, 2nd Edition, is provided for informational purposes only, and should not be construed as legal advice or an opinion on any issue. You should not act or refrain from acting on the basis of any content included in these documents without seeking legal or other professional advice.

To ensure respondent confidentiality, estimates below a certain threshold are suppressed. For Canada, Quebec, Ontario, Alberta and British Columbia suppression is applied to all data below 1,500. The threshold level for Newfoundland and Labrador, Nova Scotia, New Brunswick, Manitoba and Saskatchewan is 500, while in Prince Edward Island, estimates under 200 are suppressed. For census metropolitan areas (CMAs) and economic regions (ERs), use their respective provincial suppression levels mentioned above. Estimates are based on smaller sample sizes the more detailed the table becomes, which could result in lower data quality. Fluctuations in economic time series are caused by seasonal, cyclical and irregular movements. A seasonally adjusted series is one from which seasonal movements have been eliminated. Seasonal movements are defined as those which are caused by regular annual events such as climate, holidays, vacation periods and cycles related to crops, production and retail sales associated with Christmas and Easter. It should be noted that the seasonally adjusted series contain irregular as well as longer-term cyclical fluctuations. The seasonal adjustment program is a complicated computer program which differentiates between these seasonal, cyclical and irregular movements in a series over a number of years and, on the basis of past movements, estimates appropriate seasonal factors for current data. On an annual basis, the historic series of seasonally adjusted data are revised in light of the most recent information on changes in seasonality. Number of civilian, non-institutionalized persons 15 years of age and over who, during the reference week, were employed or unemployed. Estimates in thousands, rounded to the nearest hundred. Number of persons who, during the reference week, worked for pay or profit, or performed unpaid family work or had a job but were not at work due to own illness or disability, personal or family responsibilities, labour dispute, vacation, or other reason. Those persons on layoff and persons without work but who had a job to start at a definite date in the future are not considered employed. Estimates in thousands, rounded to the nearest hundred. Number of persons who, during the reference week, were without work, had looked for work in the past four weeks, and were available for work. Those persons on layoff or who had a new job to start in four weeks or less are considered unemployed. Estimates in thousands, rounded to the nearest hundred. The unemployment rate is the number of unemployed persons expressed as a percentage of the labour force. The unemployment rate for a particular group (age, gender, marital status, etc.) is the number unemployed in that group expressed as a percentage of the labour force for that group. Estimates are percentages, rounded to the nearest tenth. Industry refers to the general nature of the business carried out by the employer for whom the respondent works (main job only). Industry estimates in this table are based on the 2022 North American Industry Classification System (NAICS). Formerly Management of companies and administrative and other support services"." This combines the North American Industry Classification System (NAICS) codes 11 to 91. This combines the North American Industry Classification System (NAICS) codes 11 to 33. This combines the North American Industry Classification System (NAICS) codes 41 to 91. Unemployed persons who have never worked before, and those unemployed persons who last worked more than 1 year ago. For more information on seasonal adjustment see Seasonally adjusted data - Frequently asked questions." Labour Force Survey (LFS) North American Industry Classification System (NAICS) code exception: add group 1100 - Farming - not elsewhere classified (nec). When the type of farm activity cannot be distinguished between crop and livestock, (for example: mixed farming). Labour Force Survey (LFS) North American Industry Classification System (NAICS) code exception: add group 2100 - Mining - not elsewhere classified (nec). Whenever the type of mining activity cannot be distinguished. Also referred to as Natural resources. The standard error (SE) of an estimate is an indicator of the variability associated with this estimate, as the estimate is based on a sample rather than the entire population. The SE can be used to construct confidence intervals and calculate coefficients of variation (CVs). The confidence interval can be built by adding the SE to an estimate in order to determine the upper limit of this interval, and by subtracting the same amount from the estimate to determine the lower limit. The CV can be calculated by dividing the SE by the estimate. See Section 7 of the Guide to the Labour Force Survey (opens new window) for more information. The standard errors presented in this table are the average of the standard errors for 12 previous months The standard error (SE) for the month-to-month change is an indicator of the variability associated with the estimate of the change between two consecutive months, because each monthly estimate is based on a sample rather than the entire population. To construct confidence intervals, the SE is added to an estimate in order to determine the upper limit of this interval, and then subtracted from the estimate to determine the lower limit. Using this method, the true value will fall within one SE of the estimate approximately 68% of the time, and within two standard errors approximately 95% of the time. For example, if the estimated employment level increases by 20,000 from one month to another and the associated SE is 29,000, the true value of the employment change has a 68% chance of falling between -9,000 and +49,000. Because such a confidence interval includes zero, the 20,000 change would not be considered statistically significant. However, if the increase is 30,000, the confidence interval would be +1,000 to +59,000, and the 30,000 increase would be considered statistically significant. (Note that 30,000 is above the SE of 29,000, and that the confidence interval does not include zero.) Similarly, if the estimated employment declines by 30,000, then the true value of the decline would fall between -59,000 and -1,000. See Section 7 of the Guide to the Labour Force Survey (opens new window) for more information. The standard errors presented in this table are the average of standard errors for 12 previous months. They are updated twice a year The standard error (SE) for the year-over-year change is an indicator of the variability associated with the estimate of the change between a given month in a given year and the same month of the previous year, because each month's estimate is based on a sample rather than the entire population. The SE can be used to construct confidence intervals: it can be added to an estimate in order to determine the upper limit of this interval, and then subtracted from the same estimate to determine the lower limit. Using this method, the true value will fall within one SE of the estimate, approximately 68% of the time, and within two standard errors, approximately 95% of the time. For example, if the estimated employment level increases by 160,000 over 12 months and the associated SE is 55,000, the true value of the change in employment has approximately a 68% chance of falling between +105,000 and +215,000. This change would be considered statistically significant at the 68% level as the confidence interval excludes zero. However, if the increase is 40,000, the interval would be -15,000 to +95,000, and this increase would not be considered statistically significant since the interval includes zero. See Section 7 of the Guide to the Labour Force Survey (opens new window) for more information. The standard errors presented in this table are the average of standard errors for 12 previous months and are updated twice a year Excluding the territories. Starting in 2006, enhancements to the Labour Force Survey data processing system may have introduced a level shift in some estimates, particularly for less common labour force characteristics. Use caution when comparing estimates before and after 2006. For more information, contact statcan.labour-travail.statcan@statcan.gc.ca

BackgroundEquity-deserving groups (EDGs) have increased emergency department (ED) use, and often report negative ED care. Past studies have largely been qualitative and suffer from methodological bias and lack of comparison groups, thereby limiting their identification of interventions to ensure equitable care among equity-deserving populations. This study sought to better understand ED care experiences among EDGs in our local setting.Materials and methodsWe conducted a community-engaged, mixed-methods cross-sectional study using sensemaking methodology at the Kingston Health Sciences Centre's ED and Urgent Care Centre (Ontario, Canada), as well as at community partner organizations. From June-August 2021, eligible participants were invited to complete a survey about an ED care experience within the previous 24 months. Multiple-choice questions collected demographic/ED visit information including self-identification with up to three EDGs (Indigenous; having a disability; experiencing mental health concerns; persons who use substances (PWUS); 2SLGBTQ+; people who experience homelessness (PWEH); a visible minority; or having experienced violence). We evaluated differences in overall ED care experiences by EDG self-identification using chi-squared tests. Quantitative analysis of survey questions disaggregated by EDG status, and a thematic analysis of participant experiences are presented.ResultsOverall, 1,973 unique participants completed the survey (949 controls and 994 EDGs) sharing 2,114 ED care experiences in total. Participants who identified as PWUS, having mental health concerns, 2SLGBTQ+, PWEH, or having a disability, reported more negative overall experiences (p < 0.001). Compared with controls, each of the eight EDGs were statistically more likely to report feelings of judgement/disrespect, that there was too little attention paid to their needs (p < 0.001), and that it was more important to be treated with kindness/respect than to receive the best possible care (p < 0.001). Thematic analysis supported quantitative findings and identified four themes: stigma/judgement, poor staff communication, lack of compassionate care, and patients feeling unsupported.DiscussionNegative ED care experiences were pervasive among EDGs including feelings of judgement/stigma and a perception that a better understanding of personal situation/identity/culture was needed to improve care. Qualitative findings identified the following future interventions: universal trauma-informed care, improved care for addiction/substance use, and improved access to mental health care resources.

The Ontario health survey is designed to provide baseline statistical data on the health of the Ontario population, with meaningful information at the health unit/district level. The objectives of the survey were: measure the health status of the population collect data on the determinants (risk factors) of the major causes of illness and death in Ontario collect data related to the social, economic, demographic and geographic variations in health measure awareness of the risk behaviours related to smoking, alcohol, nutrition and exercise collect measures of the use of health services provide planning data for each of the 42 public health units and 28 district health councils across the province collect data comparable to measure in the Canadian and Quebec health surveys Part one of the survey, completed by the person most knowledgeable, focused on recent or current health problems of members of the household, disability days, accidents and injuries, health status, chronic health problems, the use of health services, and demographic information such as income and education. Part two of the survey, completed by each member of the household, covered self-rated health, the use of medicines and drugs, smoking, alcohol use, family relationships, social support, psychological/emotional well-being, suicide, dental health, driving and road safety, women's reproductive health, sexual health, occupational health, physical activities, and nutrition. The variables in this file can be used to link the OHS with the Mental Health Supplement. The first variable on each record is a 4-digit idetification number (SID) which uniquely idetifies each record of the Supplement sample. The same identification number is on the Supplement microdata file and allows the OHS microdata file for the Supplement file sample to be linked to the Supplement file.

The Ontario health survey is designed to provide baseline statistical data on the health of the Ontario population, with meaningful information at the health unit/district level. The objectives of the survey were: measure the health status of the population collect data on the determinants (risk factors) of the major causes of illness and death in Ontario collect data related to the social, economic, demographic and geographic variations in health measure awareness of the risk behaviours related to smoking, alcohol, nutrition and exercise collect measures of the use of health services provide planning data for each of the 42 public health units and 28 district health councils across the province collect data comparable to measure in the Canadian and Quebec health surveys Part one of the survey, completed by the person most knowledgeable, focused on recent or current health problems of members of the household, disability days, accidents and injuries, health status, chronic health problems, the use of health services, and demographic information such as income and education. Part two of the survey, completed by each member of the household, covered self-rated health, the use of medicines and drugs, smoking, alcohol use, family relationships, social support, psychological/emotional well-being, suicide, dental health, driving and road safety, women's reproductive health, sexual health, occupational health, physical activities, and nutrition.

Characteristics of individuals with a TBI-related healthcare visit in the emergency department or hospital in Ontario, Canada, April 1, 2002 to November 20, 2020 (N = 94,514)a.

Number of days lost per full-time employee in a year, by public and private sector and gender, annual.

Mechanisms of traumatic brain injury by social determinants of health variables in Ontario, Canada, April 1, 2002 to November 20, 2020 (N = 94,442)a,b.

Rank, number of deaths, percentage of deaths, and age-specific mortality rates for the leading causes of death, by age group and sex, 2000 to most recent year.