Canadian Tobacco and Nicotine Survey (CTNS)

Detailed information for 2022

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 - September 11, 2023

• Questionnaire(s) and reporting guide(s)
• Description
• Data sources and methodology
• Data accuracy

Description

Health Canada and other organizations will use the data to monitor changes in vaping, cannabis use and tobacco use.

This information is vital to the effective development and implementation of national and provincial strategies, policies and programs aimed at reducing the harms associated with the use of these substances.

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 primarily to collect data on tobacco and nicotine use.

Subjects

• Health
• Lifestyle and social conditions

Data sources and methodology

Target population

The target population for the survey is non-institutionalized persons aged 15 years or older living in Canada's ten provinces, who are not members of collectives or living on reserves.

Instrument design

The content for the CTNS electronic questionnaire was drafted in consultation with Health Canada.

The questionnaire underwent cognitive testing through 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.

Sampling

This is a sample survey with a stratified sample and cross-sectional design.

Sampling unit
Individuals aged 15 to 24: The CTNS sample has a one-stage design, and the individual is the sampling unit.

Individuals aged 25 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 individual.

Stratification method
Individuals aged 15 to 24: The frame was stratified by age group (15 to 19, 20 to 24) and province, and a systematic sample was selected independently within each age group and province.

Individuals aged 25 and older: The frame was stratified by province and a simple random sample of dwellings was selected independently within each province.

Sampling and subsampling
Individuals aged 15 to 24: The sample was allocated to the provinces so that the survey could produce province-level estimates for this age group. The sample was also allocated so that the survey could produce region-level estimates for age groups 15 to 19 and 20 to 24. An initial sample of 12,000 individuals aged 15 to 24 was selected.

Individuals aged 25 and older: The sample was allocated to the provinces so that the survey could produce province-level estimates for this age group. An initial sample of 15,000 dwellings was selected to cover individuals aged 25 and older.

An initial sample of 27,000 dwellings or individuals was sent to collection.

Data sources

Data collection for this reference period: 2022-11-30 to 2023-01-31

Responding to this survey is voluntary.

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) .

Error detection

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. Lastly, invalid characters were deleted and the remaining data items were formatted appropriately.

Imputation

This methodology type does not apply to this statistical program.

Estimation

The estimation of population characteristics from a sample survey is based on the premise that each individual in the sample represents a certain number of other individuals 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 dwelling selected from the dwelling frame is given an initial weight equal to the inverse of its selection probability from the sampling frame. 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, using a non-response 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 individual within the household.
5) Each individual selected from the person frame is given an initial weight equal to the inverse of the selection probability from the sampling frame. Individuals identified as out of scope are dropped from the sample.
6) The respondent weights are adjusted to represent the individuals who did not respond to the survey. Adjustment factors are computed separately by province based on a non-response model using frame information.
7) The person weights coming from the household sample and the person sample are pooled together.
8) The person weights are calibrated so that the sum of the weights match demographic population counts at the region level by age group and by gender. The weights are also calibrated to demographic counts for large Census Metropolitan Areas.

Variance estimation is based on a resampling method called the bootstrap.

Quality evaluation

While quality assurance mechanisms are applied at all stages of the statistical process, validation and detailed data review by statisticians are the final quality verifications prior to release. Many validation measures are implemented, including

a. verification of estimates through cross-tabulation
b. consultation with stakeholders internal to Statistics Canada
c. consultation with external stakeholders.

Disclosure control

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 survey.

Data accuracy

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.

Non-sampling error
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.

Non-response bias
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. The response rate for the survey was 46%.