Canadian Community Health Survey - Annual Component (CCHS)
Detailed information for 2016
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 - Scheduled for September 27, 2017
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 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.
In 2012, CCHS began work on a major redesign project that was completed and implemented for the 2015 cycle. The objectives of the redesign were to review the sampling methodology, adopt a new sample frame, modernize the content and review the target population. Consultations were held with federal, provincial and territorial share partners, health region authorities and academics.
As a result of the redesign, the 2015 CCHS has a new collection strategy, is drawing the sample from two different frames and has undergone major content revisions. With all these factors taken together, caution should be taken when comparing data from previous cycles to data released for the 2015 cycle 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 to December
- Diseases and health conditions
- Health care services
- Lifestyle and social conditions
- Mental health and well-being
Data sources and methodology
The CCHS covers the population 12 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, children aged 12-17 that are living in foster care, 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 12 and over.
In the north, the frame for the CCHS covers 92% of the targeted population in the Yukon, 96% in the Northwest Territories and 92% in Nunavut. In Nunavut, starting in 2013, the coverage was expanded to represent 92% of the targeted population. Before 2013, the coverage was 71% since the survey covered only the 10 largest communities.
Each component of the CCHS questionnaire is developed in collaboration with specialists from Statistics Canada, other federal and provincial departments and/or academic fields. The CCHS questions are designed for computer-assisted interviewing (CAI), meaning that, as the questions were developed, the associated logical flow into and out of the questions was programmed. This includes specifying the type of answer required, the minimum and maximum values, on-line edits associated with the question and what to do in case of item non-response.
CCHS content is comprised of four components. Core content is asked of all respondents and remains stable over time. Theme content is asked of all respondents for one or two years and alternates from year to year. Optional content is chosen by provincial and territorial stakeholders in coordination with health regions and is only asked in provinces and territories that selected the module. Rapid Response modules are cost-recovery projects asked of all respondents living in the ten provinces, usually for one collection period (3 months). The optional content fulfils the unique data needs of each province or territory and may vary from year to year. The Rapid Response component is offered to organizations interested in national estimates on an emerging or specific issue related to the population's health. Provincial estimates may also be yielded from a Rapid Response, however they may be of limited quality. A Rapid Response component may be added to the survey in each three-month collection period. The data will be released about six months after the collection period via an announcement in The Daily.
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 any errors in the program flow and text before the start of the main survey.
This is a sample survey with a cross-sectional design.
To provide reliable estimates at the health region (HR) level, a sample of 130,000 respondents is required on a two years basis: 120,000 respondents to cover the population aged 18 and over and 10,000 respondents to cover the population aged 12 to 17 years.
Since 2015, a multi-stage sample allocation strategy is used to give relatively fair sample distribution to the HRs and the provinces. For each age group (18 and over, 12 to 17), the sample is first allocated among the provinces using a power allocation of 0.75 according to the size of their respective population. Each province's sample is then allocated among its HRs using a power allocation of 0.35 according to the size of the population in each HR.
From 2015 onwards, the CCHS sample is selected using two different frames: an Area frame and the Canadian Child Tax Benefit (CCTB) frame. Using the Area frame, a sample of dwellings is selected to target the population aged 18 and over. 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. The CCTB frame is used to sample persons aged 12 to 17 years. One child is then pre-selected to complete the survey.
The area frame is mainly designed to serve the Labour Force Survey (LFS). Thus, the sampling plan of the LFS must be considered in selecting the CCHS dwelling sample. The LFS plan is a complex two stage stratified design in which each stratum is formed of clusters. The LFS first selects clusters using a sampling method with a probability proportional to size (PPS), and then the final sample is chosen using a systematic sampling of dwellings in the cluster. For CCHS, LFS clusters are grouped in each HR. Then, a sample of clusters and systematic dwellings are selected in each HR. The process maximises the overlap between the clusters selected by both surveys and ensures that the same dwelling is selected only once.
For the CCTB frame, a HR is assigned to each child in the target population based on the address. The CCTB frame is then stratified by HR. A simple random sample (SRS) of children aged 12 to 17 is selected within each HR.
The size of the sample is enlarged during the selection process to account for non responses and units outside the coverage (for example, vacant dwellings, institutions, children not eligible due to age or death, etc.).
Data collection for this reference period: 2016-01-04 to 2016-12-24
Responding to this survey is voluntary.
Data are collected directly from survey respondents.
Data were collected using computer assisted personal and telephone interview software. Cases from the area frame are collected using a combination of both modes, while CCTB cases are collected exclusively by telephone interview.
In both cases (area frame and CCTB), proxy reporting is allowed, although certain questions may be skipped.
Respondents are initially offered to complete the 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.
Health Statistics Division has linked the 2016 CCHS survey data to existing tax files to collect income information.
The first step for linkage is to determine if tax data are available for the CCHS 2016 sampled households. When this information is available, respondents will be given a linkage statement which includes a specific reference to linking to tax data. They will have the opportunity to refuse the linkage. For those respondents that refuse to link, a set of income questions will then be asked. For households where there is no tax data available, the income questions will be asked followed by the linkage statement.
After collection, the second step will be to link the 2016 CCHS data to the most recent available tax files (generally a two year lag from the collection year) to collect the income information for those respondents who did not refuse to link.
Given the CCHS sample is drawn from two frames (Canadian Child Tax Benefit file for respondents aged 12-17 and the Labour Force Survey (LFS) area frame for those 18+), there will be slightly different approaches to the two step linking strategy. For those aged 18 years or older, the sample records will all contain an ARUID (Address Registry Unique Identifier). Prior to collection of the CCHS Annual 2016, the ARUIDS for the selected sample will be linked to the 2014 IDENT_ARUID file using ARUID and then linked to the most recent tax data available at the time of collection to identify cases that do not have 2014 tax data. So for the 2016 CCHS master data file, this will be 2014 T1 Personal Master File(T1). Cases that do not have 2014 tax data will be asked income questions as a back-up measure to provide income data. All respondents will also be given the tax linkage statements. For all those agreeing to the tax linkage statement (regardless of whether they were also asked income questions) we will attempt data linkage in the following manner:
1.Link the ARUID to the 2015 IDENT_ARUID then use this to link to the 2015 T1, T1FF or T4 to obtain tax data.
2.If a link is not found for 2015 then link to the 2014 IDENT_ARUID and use that link to find the 2014 T1, T1FF, T4 tax data.
Personal information such as name, date of birth and gender, or contact information such as telephone number or postal code may be used to verify the links (through ARUID), or improve linkage rates.
For the 12-17 year old selected respondents, records can be linked through the SIN number of the parents to identify those without 2014 T1, T1FF or T4 data. Those without the 2014 T1 data will be asked the income questions as a back-up measure. All respondents will also be asked the tax data linkage statement. For those agreeing to it (regardless of whether they are asked the income questions) we will attempt linkage as follows:
1.If the child still lives with the recipient (parent/guardian) then link the SIN of the parent to the 2015 T1,T1FF or T4 to obtain the most recent tax data.
2.If a link is not found for the 2015 T1 or T1FF and the child still lives with the recipient (parent/guardian) then use the SIN to link to the 2014 T1,T1FF or T4 to obtain tax data.
3. Due to restrictions that prohibit the sharing of tax data to share partners, additional modeling is required if a linkage is successful and a respondent agrees to share their data. For share files Statistics Canada replaces these respondents household income with a modeled income using aggregate tax data and CCHS variables.
If the child no longer lives with the recipient (parent/guardian) then linking through contact information such as name, address or phone number may be attempted.
View the Questionnaire(s) and reporting guide(s).
Most editing of the data was performed at the time of the interview by the computer-assisted interviewing (CAI) application. It was not possible for interviewers to enter out-of-range values and flow errors were controlled through programmed skip patterns. For example, CAI ensured that questions that did not apply to the respondent were not asked.
In response to some types of inconsistent or unusual reporting, warning messages were invoked but no corrective action was taken at the time of the interview. Where appropriate, edits were instead developed to be performed after data collection at Head Office. Inconsistencies were usually corrected by setting one or both of the variables in question to "not stated".
Household income data in the 2016 CCHS is imputed. Missing values due to either respondent refusal or respondent's lack of knowledge of household income are replaced using a nearest neighbour imputation method based on a modeled household income.
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 two sampling frames for its sample selection: an area frame for the Canadian population aged 18 and over, and a frame of telephone numbers from Canada Child Tax Benefit (CCTB) records for the 12-17 population.
The weighting strategy treats both the area and CCTB frames independently to come up with separate person-level weights for each of the frames used. 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 to transfer the weights of the nonrespondents to the respondents. The person-level weights from the two frames are then combined into a single set of weights, jointly 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.
Bootstrap weights are created through resampling the original sample and applying similar adjustments to the bootstrap weights as to the sample weights.
The steps for weighting are described in chapter 8 of the CCHS User Guide.
The sample design used for this survey was 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.
Aggregate statistics produced using the CCHS data and published on CANSIM are validated against past cycles of the survey. For each domain produced (indicator, sex, age, and geography), the estimate is compared to the same domain from the previous cycle. Where statistically significant changes with the previous reference period were identified (for releasable estimates), estimates were then compared to all other reference periods.
Each indicator is first compared against the previous to assess differences that may be caused due to questionnaire changes.
Changes were then assessed by the level of statistical significance in the difference, the overlap of or distance between confidence intervals, and variability in sub-domains.
In the case of the 2015 cycle of the CCHS, comparisons with 2014 were made with caution. Aspects of the survey frame, sampling, collection, and weighting have changed significantly and may influence the difference seen between 2015 estimates and those of 2014. Because of the significant changes to the survey methodology, Statistics Canada does not recommend making comparisons of the redesigned 2015 cycle of the CCHS with past cycles.
Statistics Canada is prohibited by law from releasing any information it collects which 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.
Revisions and seasonal adjustment
This methodology type does not apply to this statistical program.
The quality of estimates produced with CCHS data is measured with the coefficient of variation (CV), produced using bootstrap weights. The CV magnitude will depend on the domain of interest and the prevalence of the characteristic.
In 2016, the high prevalence characteristic 'Very good or excellent self-perceived health' had a CV below 1% at the Canada level and no higher than 3% at the provincial level.
The low prevalence indicator 'Breastfed last baby exclusively for at least 6 months' had a CV of 5% at the Canada level and up to 33% in some provinces.
Disaggregating estimates further by age group or sex will increase the coefficient of variation.
In 2016, around 15% of respondents were imputed for total household income and 11% of respondents were imputed for personal income.
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