Canadian Health Survey on Seniors (CHSS)
Detailed information for 2020
The Canadian Health Survey on Seniors (CHSS) is a supplement to the Canadian Community Health Survey (CCHS) - Annual component. It collects information related to health status, health care services, supports, as well as social and health determinants for the Canadian population aged 65 and over.
Data release - October 1, 2021 (Important information: Please note that due to the COVID-19 pandemic, our offices had to close mid-collection. Collection was resumed September 2020.); April 19, 2022
This survey collects health-related data on the Canadian population aged 65 and over.
The objectives of the Canadian Health Survey on Seniors are:
1. To better understand what contributes to healthy aging by collecting data on the health and well-being of seniors, including their use of health care services and supports, as well as social, demographic, geographic and economic determinants.
2. To produce estimates on the health of seniors aged 65 and over at the provincial level, and for seniors aged 85 and over at the national level.
3. To produce a cross-sectional dataset on the health of seniors that permits analysis on a range of research questions and surveillance activities.
4. To evaluate changes on certain aspects of health from the CCHS - Healthy Aging (HA), 2008/2009.
The data collected in the survey will be used by Statistics Canada, Health Canada, the Public Health Agency of Canada, provincial ministries of health, as well as federal and provincial health planners across the country.
The CHSS will help policy makers, researchers and planners to make informed decisions regarding health care, social services and support programs for the aging population and that will affect all Canadians.
Reference period: Varies according to the question (for example, "in the past 12 months", "in the past month", 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 CHSS covers the population 65 years of age and over living in the ten provinces. 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.
The Canadian Health Survey on Seniors questionnaire was developed in collaboration with stakeholders at Health Canada and the Public Health Agency of Canada and an expert advisory group.
The 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.
In collaboration with Statistics Canada's Questionnaire Design Resource Centre (QDRC), the questionnaire was subjected to qualitative testing in May 2018, which consisted of one-on-one interviews. The objective was to evaluate respondent reactions to and understanding of the survey, as well as their willingness to respond to the questions.
This is a sample survey with a cross-sectional design.
The CHSS is a combination of the CCHS - Annual component respondents from all provinces who are at least 65 years old, along with an oversample in all provinces except Ontario and Quebec (no oversample was required to achieve the sample targets in those two provinces). A description of the CCHS - Annual component sample design can be found on that survey's IMDB page. The oversample for CHSS is selected from a list frame of dwellings with a valid telephone number that have at least one occupant aged 65 years or older.
Both the CCHS - Annual component for respondents 18+ and the oversample for CHSS for respondents 65+, have the dwelling as the sampling unit. Once contact with the household has been established, a roster of household members is taken, from which one person is randomly selected to complete the survey.
The oversample of the CCHS for CHSS purposes is stratified by province. The stratification method for the CCHS - Annual component can be found on that survey's IMDB page.
Sampling and sub-sampling:
The oversample of the CCHS for CHSS purposes is 10,000 dwellings per year. When combined with the CCHS - Annual component sample (15,000), it is estimated that overall there will be approximately 25,000 respondents to the CHSS per year.
The oversample was allocated to all provinces except Ontario and Quebec. The aim of the allocation is that when the oversample is combined with the CCHS Annual sample, it will be possible to obtain at most a 16.5% coefficient of variation when estimating the same minimum proportion at the provincial level for all provinces.
Data collection for this reference period: 2020-01-02 to 2020-12-12
Responding to this survey is voluntary.
Data are collected directly from survey respondents.
Data are collected using computer assisted personal and telephone interview software. Proxy reporting is allowed, although some modules will 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 recruits interviewers with a wide range of language competencies.
The average time to complete the survey is 15 minutes.
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 2020 CHSS is imputed in cases where it was missing. 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 CHSS uses two sampling frames for its sample selection: an area frame for the Canadian population aged 18 and over, and a list frame of dwellings with a valid telephone number that have at least one occupant aged 65 years or older.
The CCHS and CHSS weighting steps are aligned for as long as possible; first, the weighting strategy treats both the area and the CHSS frames independently up to and including the adjustment for household nonresponse; then, it integrates both samples (adjusting the weights to account for the overlap in population), resulting in a person-level weight for the adult population. It is at that point that the CCHS and CHSS weighting strategies diverge and they undergo their respective final weight adjustments. For CHSS, only CCHS senior respondents are kept. Their weights undergo some more adjustments (including being matched to known senior population totals) and become the final CHSS 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.
More details on the weighting steps can be found in chapter 7 of the CHSS 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.
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.
After the CHSS 2020 data were compiled, the data were reviewed in terms of the accuracy, coherence and overall reasonableness. A variety of summary indicators were calculated from the 2020 data and were reviewed for reasonableness with respect to changes in the survey collection methodology, and demographic and health trends.
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.
Revisions and seasonal adjustment
This methodology type does not apply to this statistical program.
The quality of estimates produced with CHSS 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.