Canadian Community Health Survey - Annual Component (CCHS)
Detailed information for 2015
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 - December 12, 2016 (Rapid response on Risk Factors for Heart Disease); Scheduled for March 22, 2017 (2015 data)
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
- Prevention and detection of disease
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 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 ensure 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: 2015-01-06 to 2015-12-31
Responding to this survey is voluntary.
Data are collected directly from survey respondents.
The CCHS interview takes roughly 45 minutes to complete.
A small proportion of the data is collected from proxy respondents because of physical or mental incapacity from the selected respondent.
The CCHS questionnaire is administered using computer-assisted interviewing (CAI). All sample selected from the CCTB frame (respondent aged 12-17) and the sample selected from the Area frame (18+) with at least one telephone number (including cellular phone numbers) will be interviewed using the Computer Assisted Telephone Interviewing (CATI) method. The sample selected from the area frame without a telephone number will be interviewed using the Computer Assisted Personal Interviewing (CAPI) method. Some cases from the area frame may be transferred to CAPI if the selected dwelling is not reached using the phone number from the Area frame. Many social surveys, including the CCHS, use the SSPE. The SSPE consists of a set of generalized processes to be used in the processing activities of a survey. The purpose of these processes is to allow subject matter and survey support staff to specify and run the processing of a survey in a timely fashion with high quality outputs.
View the Questionnaire(s) and reporting guide(s).
Some editing of the data is performed at the time of the interview by the computer-assisted interviewing (CAI) application. It is not possible for interviewers to enter out-of-range values and flow errors are controlled through programmed skip patterns. For example, CAI ensures that questions that do not apply to a 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 the interview.
Several edits are performed at Head Office during the data processing step. A critical error edit is done that rejects respondent entries (for instance, excluded populations). Flow errors are also adjusted during processing and a data inconsistency detection and correction program is applied. Where appropriate, edits are instead developed to be performed at Head Office after data collection. Inconsistencies are usually corrected by setting one or both of the variables in question to "not stated". Response frequency obtained during the current period and previous reference periods is also compared to identify errors prior to release.
Finally, health indicators originating from the CCHS common content are going through a validation process after final microdata files are produced. Estimates for all geography levels by sex and by age groups are compared to estimates from previous years. This process allows to confirm that estimates of key indicators are acceptable.
Beginning with the 2011 reference year, the household income variable is imputed. Missing values due to either respondent refusal or respondent's lack of knowledge of household income will be completed using statistical techniques. The main variable of interest is THI_Q01: 'Total household income - best estimate' but all variables that are derived based on income will also be affected. The income variables along with an imputation flag (INCFIMP in 2011 and INCFIMP4 in subsequent years) indicating which values were imputed will be provided on the data file. For more information on the imputation process, please request the document 'Income Imputation for the Canadian Community Health Survey' from client services (613-951-1746; fax: 613-951-0792; email@example.com).
A respondent's postal code is employed, using the Postal Code Conversion File, to derive the rest of the geographical variables that are available on the CCHS data file. It is therefore important that all respondents have a valid postal code. If a respondent's postal code is missing or invalid, it is usually imputed through a donor imputation process, although other imputation methods are sometimes used. The donor is chosen from the same geographical area, with as much precision as possible, as the unit with the missing or invalid postal code.
The principle behind estimation in a probability sample is that each person in the sample "represents", besides himself or herself, several other persons not in the sample. For example, in a simple random 2% sample of the population, each person in the sample represents 50 persons in the population. In the terminology used here, it can be said that each person has a weight of 50. The weighting phase is a step that calculates, for each person, his or her associated sampling weight. This weight must be used to derive meaningful estimates from the survey. For example, if the number of individuals who had a major depressive episode is to be estimated, the weights of survey respondents having that characteristic should be summed. In order for estimates produced from survey data to be representative of the covered population and not just the sample itself, a user must incorporate the survey weights into their calculations.
In order to determine the quality of an estimate, the variance must be calculated. Because the CCHS uses a multi-stage survey design, there is no simple formula that can be used to calculate variance estimates. Therefore, an approximative method is needed. Coefficient of variation, standard deviation and confidence intervals can then be calculated from the variance. The bootstrap re-sampling method used in the CCHS involves the selection of simple random samples known as replicates, and the calculation of the variation between the estimates from replicate to replicate. In each stratum, a simple random sample of (n-1) of the n clusters is selected with replacement to form a replicate. Note that since the selection is with replacement, a cluster may be chosen more than once. In each replicate, the survey weight for each record in the (n-1) selected clusters is recalculated. These weights are then post-stratified according to demographic information in the same way as the sampling design weights in order to obtain the final bootstrap weights. The entire process (selecting simple random samples, recalculating and post-stratifying weights for each stratum) is repeated B times, where B is large. Starting in 2015, the CCHS uses B=1000, to produce 1000 bootstrap weights. To obtain the bootstrap variance estimator, the point estimate for each of the B samples must be calculated. The standard deviation of these estimates is the bootstrap variance estimator.
Estimates in the main body of a statistical table are rounded to the nearest hundred units using the normal rounding technique. If the first or only digit dropped is zero to four, the last digit retained is not changed. If the first or only digit dropped is five to nine, the last digit retained is raised by one. Marginal sub-totals and totals in statistical tables are derived from their corresponding unrounded components and then are rounded themselves to the nearest 100 units using normal rounding methods. Averages, proportions, rates and percentages are computed from unrounded components (for example, numerators and/or denominators) and then are rounded themselves to one decimal using normal rounding. In normal rounding to a single digit, if the final or only digit dropped is zero to four, the last digit retained is not changed. If the first or only digit dropped is five to nine, the last digit retained is increased by one. Sums and differences of aggregates (or ratios) are derived from their corresponding unrounded components and then are rounded themselves to the nearest 100 units (or the nearest one decimal) using normal rounding. Under no circumstances are unrounded estimates, published or otherwise, released. Unrounded estimates imply greater precision than actually exists.
Before interpreting and using a CCHS estimate, it is recommended to make sure that the estimates meets the following rules:
¿ Coefficient of Variation 35.0% or less
¿ a minimum of 10 respondents in the domain with the characteristic and
¿ total domain of interest includes at least 20 respondents.
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 survey.
For details on data accuracy measures and response rates, please refer to the Mode Study and User Guide documents. To obtain a copy of this documentation, contact Client Services (613-951-1746; fax: 613-951-0792; firstname.lastname@example.org).
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