British Columbia Smoking Survey (BCSS)

Detailed information for 2006




One Time

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The central objective of the British Columbia Smoking Survey (BCSS) was to gather information related to the smoking history, mobility history and risk propensity of British Columbia residents.

Data release - December 8, 2008


The central objective of the British Columbia Smoking Survey (BCSS) was to gather information related to the smoking history, mobility history and risk propensity of British Columbia residents. The survey was sponsored by the B.C. Ministry of Health. The BCSS was a cross-sectional survey that was a follow-up to the Canadian Community Health Survey (CCHS), Cycle 3.1 conducted in 2005.

Reference period: Varied according to the question (for example: "in your lifetime", "at the present time", "in the past 12 months" etc.)

Collection period: February 2006 to June 2006


  • Health
  • Lifestyle and social conditions

Data sources and methodology

Target population

The target population consisted of B.C. residents aged 18 and over, living in private occupied dwellings at the time of the CCHS cycle 3.1 interview. Only non-proxy respondents who agreed to link their CCHS 3.1 data were included. Individuals living on Indian Reserves and on Crown Lands, institutional residents, full-time members of the Canadian Armed Forces and residents of certain remote regions were excluded.

Instrument design

Each component of the BCSS questionnaire was developed by Statistics Canada, in consultation with the survey sponsor, the B.C. Ministry of Health. The BCSS questions were 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 included 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.

Two qualitative tests were conducted to assess the content and flow of the BCSS questionnaire. Approximately 25 respondents, covering a cross-section of current and former smokers, including daily and occasional, were represented in face-to-face interviews. In both tests the frame used to select participants for qualitative testing was the CCHS Cycle 2.1 (2003). The first qualitative test was conducted in November 2004 in Ottawa, Ontario. After this test, some changes were made to improve the questionnaire including introducing a timeline to improve recall during collection of the respondents' history of smoking. A second and final qualitative test was conducted in February 2005 in Vancouver B.C.. The key finding was that the timeline approach proved to be a success and most respondents found it very useful in helping them to gather their thoughts about when and how much they had smoked over various periods of time in their lives.

One field test was conducted for BCSS in November 2005. The test involved Statistics Canada's Edmonton Regional Office. Experienced Statistics Canada interviewers carried out interviews. The main objectives of the test were to observe respondent reaction to the survey, to obtain estimates of time for the various sections, to study the response rates and to test feedback questions. Field operations and procedures, interviewer training and the data collection computer application were also tested. In addition to the field test, the data collection computer application was extensively tested in-house in order to identify any errors in the program flow and text. The testing of the data collection computer application was ongoing up until the start of the main survey.


This was a sample survey with a cross-sectional design.

The survey frame for the BCSS sample was created by using the respondents from the Canadian Community Health Survey (CCHS) Cycle 3.1 (2005). Since the CCHS data would be linked to the BCSS data, only those individuals who agreed to link their CCHS Cycle 3.1 data were included on the BCSS frame. Also, only those CCHS respondents aged 18 years or older and living in BC at the time of the Cycle 3.1 interview were contacted for the BCSS. All proxy CCHS Cycle 3.1 respondents were not included on the BCSS frame because of the personal nature and recall demands of the BCSS questionnaire. For CCHS, proxy interviews were allowed in cases where the respondent did not have the capacity to complete the interview because of physical or mental limitations. Finally, any partially completed CCHS Cycle 3.1 interviews were excluded from the BCSS frame. The reason for this exclusion was two-fold. First, the question concerning agreement to link the CCHS Cycle 3.1 data was asked in the last module of the questionnaire and most partially complete interviews did not reach this point. Second, since the CCHS data would be linked with the BCSS data, it was not desirable to have large portions of missing data. All units that make up the BCSS frame were included in the BCSS sample.

Since this was a targeted respondent survey, only the particular member of a household who had completed a CCHS Cycle 3.1 interview was eligible to be followed up for the BCSS.

The CCHS Cycle 3.1 sample in B.C. came from 16 health regions (HR) covering the entire province and was allocated proportionally to the square root of the population size of the HR. There were between 500 and 1,600 respondents in each HR. The distribution of the CCHS sample by gender and age was very similar to the actual distribution in the province, with the exception of a slight over-representation of individuals aged 65 and over.

For the BCSS, the collection period for the survey was from February to June 2006. During this time, there were two samples sent for collection. A sample of approximately 5,900 respondents was assigned at the end of January 2006, representing eligible respondents who had a CCHS Cycle 3.1 interview from January 2005 to June 2005. A second sample of approximately 5,700 respondents was delivered at the end of March 2006, comprising all other eligible CCHS Cycle 3.1 respondents. A total of 11,587 records were delivered for possible BCSS interviews.

Data sources

Responding to this survey is voluntary.

Data are collected directly from survey respondents.

The BCSS questionnaire was administered using computer-assisted interviewing (CAI). Sample units were selected from the frame and interviewed using the Computer-Assisted Telephone Interviewing (CATI) method.

CAI offers a number of data quality advantages over other collection methods. First, question text, including reference periods and pronouns, is customised automatically based on factors such as the age and sex of the respondent, the date of the interview and answers to previous questions. Second, edits to check for inconsistent answers or out-of-range responses are applied automatically and on-screen prompts are shown when an invalid entry is recorded. Immediate feedback is given to the respondent and the interviewer is able to correct any inconsistencies. Third, questions that are not applicable to the respondent are skipped automatically.

CATI interviewers work in a centralised office and are supervised by a senior interviewer located in the same office. Transmission of cases from the office to head office is the responsibility of the regional office project supervisor, senior interviewer and the technical support team.

An automated call scheduler, for example a central system to optimise the timing of call-backs and the scheduling of appointments, is used to support CATI collection.

View the Questionnaire(s) and reporting guide(s) .

Error detection

Some 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 a 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 at Head Office after data collection. Inconsistencies were usually corrected by setting one or both of the variables in question to "not stated".

Several edits were performed at Head Office during the data processing step. A critical error edit was done that rejected respondent entries (for instance, excluded populations). Flow errors were also adjusted during processing and a data inconsistency detection and correction program was applied.


This methodology type does not apply to this statistical program.


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. The computation of exact coefficients of variation is not a straightforward task since there is no simple mathematical formula that would account for all BCSS sampling frame and weighting aspects. Therefore, other methods such as resampling methods must be used in order to estimate measures of precision. Among these methods, the bootstrap method is the one recommended for analysis of BCSS data.

The computation of coefficients of variation (or any other measure of precision) with the use of the bootstrap method requires access to information that is considered confidential and not available on the data file. This computation must be done using the Master file.

For the computation of coefficients of variation, the bootstrap method is advised. A macro program, called "Bootvar", was developed in order to give users easy access to the bootstrap method. The Bootvar program is available in SAS and SPSS formats, and is made up of macros that calculate the variances of totals, ratios, differences between ratios, and linear and logistic regressions.

Although some standard statistical packages allow sampling weights to be incorporated in the analyses, the variances that are produced often do not take into account the stratified and clustered nature of the design properly, whereas the exact variance program would do so.

Quality evaluation

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.

Disclosure control

Statistics Canada is prohibited by law from releasing any data which would divulge information obtained under the Statistics Act that relates to any identifiable person, business or organization without the prior knowledge or the consent in writing of that person, business or organization. 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.

Users requiring access to information from the master files may purchase custom tabulations. Outputs are vetted for confidentiality before being given to users.

Revisions and seasonal adjustment

This methodology type does not apply to this statistical program.

Data accuracy

For further details on data accuracy measures, please refer to the User Guide.


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