Canadian Tobacco and Nicotine Survey (CTNS)
Detailed information for 2020 and 2021
The main objective of the Canadian Tobacco and Nicotine Survey is to gather information about the prevalence of cigarette smoking, vaping, and cannabis use.
Data release - March 17, 2021
The information collected in this survey will be used to fill important data gaps related to vaping, cannabis, and tobacco usage. The data will inform policy and provide a current snapshot of use across Canada.
Until 2017, Statistics Canada conducted the Canadian Tobacco, Alcohol and Drugs Survey (CTADS), which collected data on tobacco as well as alcohol and drug use in Canada. In 2019, the Canadian Alcohol and Drugs Survey (CADS) was conducted to collect data on alcohol and drug use independently from the Canadian Tobacco and Nicotine Survey (CTNS) which was conducted to primarily collect data on tobacco and nicotine.
- Lifestyle and social conditions
Data sources and methodology
The target population for the survey is non-institutionalized persons 15 years of age or older, living in Canada's ten provinces, who are not members of collectives or living on reserves.
The content for the Canadian Tobacco and Nicotine Survey electronic questionnaire was drafted in consultation with Health Canada.
The questionnaire underwent cognitive testing in the form of in-depth interviews in both of Canada's official languages, conducted by Statistics Canada's Questionnaire Design Resource Centre. The goal of the qualitative study was to test the survey content.
This is a sample survey.
This is a sample survey with a stratified sample and cross-sectional design.
For the 15 to 24 years old, the CTNS sample has a one-stage design, and the person is the sampling unit.
For the 25 years old and older, the CTNS sample has a two-stage design: the sampling unit for the first stage is the dwelling, and the sampling unit for the second stage is the person.
For the 15-24 years old: the frame was stratified by age group and province, and a systematic sample was selected independently within each age group and province.
For the 25 years old and older: the frame was stratified by province, and a simple random sample of dwellings was selected independently within each province.
Sampling and sub-sampling
Sufficient sample was allocated to each of the provinces and age groups so that the survey could produce provincial level estimates, as well as estimates for the three age groups of interest (15-19, 20-24, 25+). An initial sample of 20,000 dwellings or individuals was selected and sent to collection.
Data collection for this reference period: 2020-12-08 to 2021-01-16
Responding to this survey is voluntary.
Data are collected directly from survey respondents.
Data are collected directly from survey respondents either through an electronic questionnaire (EQ) or through CATI (computer assisted telephone interviewing).
View the Questionnaire(s) and reporting guide(s) .
Electronic files containing the daily transmissions of completed respondent survey records were combined to create the "raw" survey file. Before further processing, verification was performed to identify and eliminate potential duplicate records and to drop non-response and out-of-scope records.
In addition, some out-of-scope respondent records were found during the data clean-up stage. All respondent records that were determined to be out-of-scope and those records that contained no data were removed from the data file.
After the verification stage, editing was performed to identify errors and modify affected data at the individual variable level. The first editing step was to identify errors and determine which items from the survey output needed to be kept on the survey master file. Subsequent to this, invalid characters were deleted and the remaining data items were formatted appropriately.
This methodology type does not apply to this statistical program.
The estimation of population characteristics from a sample survey is based on the premise that each person in the sample represents a certain number of other persons in addition to themselves. This number is referred to as the survey weight. The process of computing survey weights for each survey respondent involves several steps.
1) Each selected dwelling (in the household sample) is given an initial weight equal to the inverse of its selection probability from the sampling frame (DUF). Dwellings identified as out-of-scope during collection are dropped from the sample.
2) The weights for responding households are adjusted to represent the households that did not respond. Adjustment factors are calculated separately by province, and using a nonresponse model based on frame information.
3) The household weights are calibrated so that the sum of the weights match province level household size demographic counts.
4) Person weights are computed by multiplying the household level weights by the inverse of the probability of selecting the person within the household.
5) Each selected person in the targeted respondent sample is given an initial weight to the inverse of the selection probability from the person frame. Persons identified as out of scope are dropped from the sample.
6) The weights of respondents are adjusted to represent the persons which did not respond to the survey. Adjustment factors are computed separately by province, based on a nonresponse model using frame information.
7) The person weights coming from the household sample and the targeted respondent sample are pooled together.
8) The person weights are calibrated so that the sum of the weights match demographic population counts at the region by age group by gender level. The weights are also calibrated to demographic counts for large Census Metropolitan Areas (CMAs).
Variance estimation is based on a resampling method called the bootstrap.
The Generalized Estimation System (G-Est) was used to generate the survey weights and bootstrap weights.
While quality assurance mechanisms are applied at all stages of the statistical process, the validation and detailed review of data by statisticians is the final verification of quality prior to release. Many validation measures were implemented, they include:
a. Verification of estimates through cross-tabulations
b. Consultation with stakeholders internal to Statistics Canada
c. Consultation with external stakeholders
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.
Survey errors come from a variety of different sources. One dimension of survey error is sampling error. Sampling error is defined as the error that arises because an estimate is based on a sample rather than the entire population. Sampling error can be expressed through a confidence interval (CI) or coefficient of variation (CV).
The following are approximate sampling error estimates for Canada level estimates. These are based on average results; these are not results for a specific variable.
- Approximate length of 95% confidence intervals for a proportion of 50% (Canada level): 4.0%
- Approximate length of 95% confidence intervals for a proportion of 10% (Canada level): 2.5%
- Approximate coefficients of variation (CVs) for a proportion of 10% (Canada level): 6%
The response rate for the Canadian Tobacco and Nicotine Survey was 41%.
Non-sampling errors can be defined as errors arising during the course of virtually all survey activities, apart from sampling. These include coverage errors, non-response errors, response errors, interviewer errors, coding errors, and other types of processing errors.
The survey estimates are adjusted to account for non-response through the survey weights. To the extent that the non-responding households and persons differ from the rest of the sample, the results may be biased.
Coverage errors arise when there are differences between the target population and the observed population. The observed population is persons living in dwellings with mailable addresses on the frame. Approximately 95% of the dwellings on the frame had mailable addresses. To the extent that the excluded population differs from the rest of the target population, the results may be biased.