Canadian Community Health Survey: Combined data, 2019/2020

The Canadian Community Health Survey (CCHS) for the 2019/2020 reference period contains information on the average population aged 12 and older over the two-year period. The CCHS is a cross-sectional survey that collects information related to health status, health care utilization and health determinants for the Canadian population. Data were collected from approximately 110,000 respondents over the two years.

The CCHS produces an annual microdata file and a second microdata file combining two years of data, every second year. The combined data are the same as the two individual annual data files, but also contain data for Yukon, the Northwest Territories, and Nunavut. The annual data for 2020 were released in The Daily on September 8, 2021 and the 2019 data were released on August 6, 2020. The two-year data can be used to disaggregate estimates to represent smaller populations and rare characteristics. This data has been tabulated in the table 13-10-0113-01 with estimates of key health indicators by health region, age group, and sex and the table 13-10-0805-01 with the same health indicators tabulated by census metropolitan area, age group, and sex.

Although data for 2019 and 2020 are from the CCHS, the 2020 cycle of the survey had some notable differences compared with 2019. In March 2020, the CCHS collection was paused and did not resume until September 2020 due to the COVID-19 pandemic, when the collection periods were reduced from three-month periods to five-week periods. In-person interviews were halted and collection was only completed via telephone interviews, which affected the number of cases collected. In the territories, the coverage was exceptionally limited to the capitals (Whitehorse, Yellowknife and Iqaluit) during the last three collection periods of 2020 given that in-person interviews were not possible during the pandemic.

As was done for previous CCHS cycles, for the 2019/2020 data, survey weights were adjusted to minimise any potential bias that could arise from survey non-response; non-response adjustments and calibration using available auxiliary information were applied and are reflected in the survey weights provided with the data file. Extensive validations of survey estimates were also performed and examined from a bias analysis perspective. Despite these rigorous adjustments and validations, the higher non-response in 2020 increases the risk of a remaining bias as well as increasing the magnitude with which such a bias could impact estimates produced using the survey data.

The data are now available in the Research Data Centres.