Canadian Community Health Survey - Annual Component (CCHS)

Detailed information for 2024

The central objective of the Canadian Community Health Survey (CCHS) is to gather health-related data at the sub-provincial levels of geography (health region or combined health regions).

Data release - To be determined

• Questionnaire(s) and reporting guide(s)
• Description
• Data sources and methodology
• Data accuracy

Description

In 1991, the National Task Force on Health Information cited a number of issues and problems with the health information system. To respond to these issues, the Canadian Institute for Health Information (CIHI), Statistics Canada and Health Canada joined forces to create a Health Information Roadmap. From this mandate, the Canadian Community Health Survey (CCHS) was conceived.

The CCHS is a cross-sectional survey that collects information related to health status, health care utilization and health determinants for the Canadian population. The survey is offered in both official languages. It relies upon a large sample of respondents and is designed to provide reliable estimates at the health region level every 2 years.

The CCHS has the following objectives:
- Support health surveillance programs by providing health data at the national, provincial and intra-provincial levels;
- Provide a single data source for health research on small populations and rare characteristics;
- Timely release of information easily accessible to a diverse community of users;
- Create a flexible survey instrument that includes a rapid response option to address emerging issues related to the health of the population.

The CCHS produces an annual microdata file and a file combining two years of data. The CCHS collection years with both consistent design and consistent population representation can also be combined by users to examine populations or rare characteristics.

The primary use of the CCHS data is for health surveillance and population health research. Federal and provincial departments of health and human resources, social service agencies, and other types of government agencies use the information collected from respondents to monitor, plan, implement and evaluate programs to improve the health of Canadians. Researchers from various fields use the information to conduct research to improve health. Non-profit health organizations and the media use the CCHS results to raise awareness about health, an issue of concern to all Canadians.

The survey began collecting data in 2001 and was repeated every two years until 2005. Starting in 2007, data for the Canadian Community Health Survey (CCHS) were collected annually instead of every two years. While a sample of approximately 130,000 respondents were interviewed during the reference periods of 2001, 2003 and 2005, the sample size was changed to 65,000 respondents each year starting in 2007.

The CCHS has undergone two major redesigns. The first in 2015 reviewed the sampling methodology, adopted a new sample frame, modernized and updated its health content, and reviewed the target population. The second in 2022, further reviewed and updated the content of the survey as well as transitioned it to an online electronic questionnaire (EQ) that was available for direct self reporting by selected respondents. Consultations were held with federal, provincial and territorial share partners, health region authorities and academics for both redesigns.

As a result of these redesigns and major changes to collection and sampling approaches as well as content updates, caution should be taken when comparing data from previous cycles to data released for the 2015 and 2021 and for data released 2022 and onwards.

Reference period: Varies according to the question (for example: "over the last 12 months", "over the last 6 months", "during the last week", etc.)

Collection period: January 2, 2024 to December 31, 2024

Subjects

• Diseases and health conditions
• Health
• Health care services
• Lifestyle and social conditions
• Mental health and well-being

Data sources and methodology

Target population

The 2024 CCHS covers the population 18 years of age and over living in the ten provinces and the three territories. Excluded from the survey's coverage are: persons living on reserves and other Aboriginal settlements in the provinces; full-time members of the Canadian Forces; the institutionalized population, and persons living in the Quebec health regions of Région du Nunavik and Région des Terres-Cries-de-la-Baie-James. Altogether, these exclusions represent less than 3% of the Canadian population aged 18 and over.

Instrument design

Each content component of the CCHS questionnaire is developed in collaboration with specialists from Statistics Canada, other federal and provincial departments and/or academic fields. Questions are designed to be answered directly by the respondent via an online electronic questionnaire (EQ). Statistics Canada interviewers will also interview respondents by phone or in person using the same questionnaire for follow up on non-responses. In designing the electronic questionnaire (EQ), questions flow logically according to conditions such as previous responses, non-responses and specific demographic variables such as sex at birth and age. Additional specifications provide guidance on the type of answer required, the minimum and maximum values, and edits associated with the question. Help text is made available by clicking on an on-screen bubble or by being included with the question text.

CCHS content is comprised of groups of questions (referred to as modules), which focus on a particular theme of health. These modules may be included in multiple cycles of CCHS or may be asked only periodically. Examples of modules asked in most cycles are: general health, chronic conditions, smoking, and alcohol use. For the 2024 cycle, thematic content related to the Health Utility Index, physical activity, colorectal cancer testing and telework, among many others, has been included. In addition to the health component of the survey are questions about respondent characteristics such as labour market activities, income, and sociodemographics.

New modules and revisions to existing CCHS content are tested using different methods. Qualitative tests using individual cognitive interviews or, more rarely, focus groups are used to ensure that questions and concepts are appropriately worded.

The computer application for data collection is extensively tested in-house each time changes are made. The objective of these tests is to identify and correct any errors in the program flow and text before the start of the main survey.

Sampling

This is a sample survey with a stratified sample and cross-sectional design.

Frame
The CCHS uses two frames.

The regular CCHS sample is selected from the area frame of the Labour Force Survey.
An additional sample is also selected from the 2021 Census.

Sampling unit

Area frame:
A stratified multi-stage design is used. A small contiguous geographical area, called a cluster, is the sampling unit at the first stage. The sampling unit at the second stage is the dwelling and at the third stage, the sampling unit is the person.

Census 2021:
A two-stage design is used. Dwellings are selected at the first stage while persons are selected at the second stage.

Stratification method
The area frame is stratified by health region (HR), except in two provinces. In Ontario, strata are intersections of HRs and Home and Community Care Support Services organizations. In Alberta, strata are subdivisions of HRs named subzones.
The frame built using Census 2021 is stratified by province and employment equity group.

Sampling and sub-sampling

Area frame:
The sample has a multi-stage design. First, a sample of clusters was selected independently within each stratum. At the second stage, a systematic sample of dwellings was selected within each of the sampled clusters. During collection, all members of the dwelling are listed, and a person aged 18 years or over is automatically selected using various selection probabilities based on age and household composition.

Sufficient sample was allocated to each of the provinces and HRs so that the survey could produce estimates of good quality at the provincial level each year and at the HR level for a two-year cycle. For each of the three territories, the data from a two-year cycle is needed to produce estimates of good quality. In 2024, the size of the sample selected from the area frame is approximately 100,000 dwellings.

Census 2021:
In 2021, Statistics Canada created a new initiative called the 'Disaggregated Data Action Plan (DDAP)'. The DDAP aims to support more representative data collection methods, enhance statistics on diverse populations to allow for intersectional analyses, and support government and societal efforts to address known inequalities by bringing considerations of fairness and inclusion into decision-making. Disaggregated data based on the four employment equity groups should be provided for: Indigenous peoples (First Nations, Inuit, Métis), Gender (women, men, gender diverse people), Persons from racialized populations (various subcategories), Persons with disabilities (various subcategories). More information about the DDAP can be found here: www.statcan.gc.ca/en/trust/modernization/disaggregated-data

In response to the DDAP initiative, the sample size for CCHS was increased by 51,000 units in 2021 and 56,500 for 2022. The goal of these sample increases was to increase the number of DDAP group respondents by increasing the number of overall respondents. For CCHS 2023 and 2024, the DDAP initiative was enhanced by the availability of data from Census 2021. For these two years, the extra sample was selected from the respondents to the Census 2021 long-form (33,500 in 2023 and 50,000 in 2024).

Census 2021 was again chosen as an additional frame for the CCHS 2024 as it is the best option to allow stratification by population characteristics. Census 2021 data was used to target households with members who identified on the Census 2021 as belonging to groups that are part of the DDAP initiative. An extra sample of 50,000 households was selected from Census 2021 long form data. These households were allocated equally across the four collection periods of 2024. This extra sample was selected at the province and equity group level.

Data sources

Data collection for this reference period: 2024-01-02 to 2024-12-31

Responding to this survey is voluntary.

Data is collected from survey respondents either through an electronic questionnaire (EQ) directly online or assisted by a Statistics Canada interviewer through CATI (computer assisted telephone interviewing) or CAPI (computer assisted personal interviewing). A letter is mailed to the selected dwelling, which contains a code that gives access to the online questionnaire. It also informs the householder about the survey and asks that a household member access the questionnaire online with the given access code to answer some preliminary questions including a listing of all people that reside in that dwelling. From this information, a household member aged 18 or older is then randomly selected to participate in the survey. An email containing a second access code is sent to the selected respondent so that they may answer their portion online.

A Statistics Canada interviewer may follow up by calling, emailing, texting, or visiting the respondent if a completed online questionnaire is not received within a certain period of time.

Proxy reporting (when a selected respondent is unable to answer for themselves) is allowed on CCHS, although certain questions may be skipped.

The questionnaire is available in both official languages and can be completed by interview in either English or French. To remove language as a barrier to conducting interviews, each of the Statistics Canada regional offices recruited interviewers with a wide range of language competencies. When necessary, cases were transferred to an interviewer with the language competency needed to complete an interview. The average time to complete the survey is 40 minutes.

The information collected during the 2024 CCHS will be linked to the personal tax records (T1, T1FF or T4) of respondents, and tax records of all household members. Household information (address, postal code, and telephone number), respondent's information (social insurance number, surname, name, date of birth/age, sex) and information on other members of the household (surname, name, age, sex and relationship to respondent) are key variables for the linkage.

Respondents are notified of the planned linkage before and during the survey. Any respondents who object to the linkage of their data have their objections recorded, and no linkage to their tax data takes place. Income information obtained from income tax records will also be provided to federal, provincial and territorial share partners only with respondent consent.

View the Questionnaire(s) and reporting guide(s).

Error detection

Most editing of the data is performed at the time of completing the electronic questionnaire or the interview by the computer-assisted interviewing application. It is not possible for respondents and interviewers to enter out-of-range values and flow errors are controlled through programmed skip patterns. For example, the application ensures that questions that did not apply to the respondent are not asked.

In response to some types of inconsistent or unusual reporting, warning messages are invoked but no corrective action is taken at the time of completing the questionnaire. Where appropriate, edits are instead developed to be performed after data collection at Head Office. Inconsistencies are usually corrected by setting one or both of the variables in question to "not stated".

Imputation

Household income data in the 2024 CCHS is imputed. Missing values are replaced using different techniques, among them a nearest neighbour imputation method based on a modeled household income.

Estimation

In order for estimates produced from survey data to be representative of the covered population, and not just the sample itself, users must incorporate the survey weights in their calculations. A survey weight is given to each respondent included in the final sample. This weight corresponds to the number of persons in the entire population that are represented by the respondent.

As described above, the CCHS uses an area frame to select a sample of the Canadian population aged 18 and over.

The adjustments applied to the initial weights are based on modeling probabilities of response (at the household level and person level). Variables derived from the collection paradata as well as characteristics of the units are used to create the models. Then, these probabilities are used to create groups of respondents and nonrespondents in which the weights of the nonrespondents to the respondents are transferred. The person-level weights undergo two more adjustments (Winsorization and Calibration to known population totals such as by geography and age and sex) and become the final person-level weights.

An extra sample was selected for the DDAP initiative. Adjustments applied to those initial weights are very similar to those applied to the sample coming from the areaframe. Before starting the adjustments to the person-level weights, an integration of the two samples is done at the household level where there is an overlap between them.

Bootstrap weights are created through resampling the original sample by applying similar adjustments to the bootstrap weights as to the sample weights. Bootstrap weights are used to evaluate the quality of survey estimates. The steps for weighting are described in chapter 8 of the CCHS User Guide.

The sample design used for this survey is not self-weighting. That is to say, the sampling weights are not identical for all individuals in the sample. When producing simple estimates, including the production of ordinary statistical tables, users must apply the proper sampling weight.

Estimates of the number of people with a certain characteristic are obtained from the data file by summing the final weights of all records possessing the characteristic of interest.

Proportions and ratios are obtained by summing the final weights of records having the characteristic of the numerator and the denominator, and then dividing the first estimate by the second.

Quality evaluation

Throughout the collection process, control and monitoring measures were put in place and corrective action was taken to minimize non-sampling errors. These measures included response rate evaluation, reported and non-reported data evaluation, on site observation of interviews, improved collection tools for interviewers and others.

Once processing steps are completed, two data validation steps are undertaken. First, a validation program is run in order to compare estimates for the health indicators taken from the common content with the previous year. This validation is performed at various geographical levels, as well as by age and sex. Significant differences are examined further to find any anomalies in data. Also, the work of analysts who use the CCHS data to publish analytical articles on specific themes, allows for an in-depth look at many variables of the survey and represents a very effective way to find error.

Disclosure control

Statistics Canada is prohibited by law from releasing any information it collects that could identify any person, business, or organization, unless consent has been given by the respondent or as permitted by the Statistics Act. Various confidentiality rules are applied to all data that are released or published to prevent the publication or disclosure of any information deemed confidential. If necessary, data are suppressed to prevent direct or residual disclosure of identifiable data.

In order to prevent any data disclosure, confidentiality analysis is done using the Statistics Canada Generalized Disclosure Control System (G-Confid). G-Confid is used for primary suppression (direct disclosure) as well as for secondary suppression (residual disclosure). Direct disclosure occurs when the value in a tabulation cell is composed of or dominated by few enterprises while residual disclosure occurs when confidential information can be derived indirectly by piecing together information from different sources or data series.

Revisions and seasonal adjustment

This methodology does not apply to this survey.

Data accuracy

The quality of estimates produced with CCHS data is measured using the confidence interval or the coefficient of variation (CV), both produced using bootstrap weights.