Canadian Community Health Survey - Nutrition (CCHS)

Detailed information for 2004 (Cycle 2.2)





Record number:


The main objective of this cycle of the Canadian Community Health Survey (CCHS) is to gather information at the provincial level on the overall nutritional status of the Canadian population.

Data release - July 6, 2005


PLEASE NOTE: The following description is a brief summary only. For a more detailed description please refer to the document entitled "Master File Userguide" in the Documentation section below.

The CCHS 2.2 -- Nutrition data are disseminated in three separate releases, July 6, 2005 (General Health Component); July 6, 2006 (General Health Component and 24-Hour Dietary Recall Component); April 4, 2008 (General Health Component, including vitamin and mineral supplements, and 24-Hour Dietary Recall Component). The first release involved the release of the data collected in the general health component while the second release involved data collected for the two components of the survey: the general health component and the 24-hour dietary recall component. The third release involved data collected for the two components of the survey: the general health component, including the vitamin and mineral supplement data, and the 24-hour dietary recall component. This release also included three new derived income variables, a new geography variable and updates to several previously released variables.

In recognition of a critical need for more extensive and recent information about the nutrition of Canadians, it was decided that Cycle 2.2 of CCHS would focus on nutrition. The primary goal of the Nutrition Survey is to provide reliable, timely information about dietary intake, nutritional well-being and their key determinants to inform and guide programs, policies and activities of federal and provincial governments and local health agencies.

The main objectives of the survey include:

- estimating the distribution of usual dietary intake in terms of foods, food groups, dietary supplements, nutrients and eating patterns among a representative sample of Canadians at national and provincial levels using a 24-hour dietary recall;
- gathering physical measurements for accurate body height and weight assessment;
- measuring the prevalence of household food insecurity;
- collecting data on selected health conditions and socio-economic and demographic characteristics of respondents.

In Canada, the primary use of the data is for health surveillance, such as in prevalence of disease and other forms of health research. The data are used extensively by the research community and other health professionals. Federal and provincial departments of health and human resources, social service agencies, and other types of government agencies use the information collected from the respondents to plan, implement and evaluate programs to improve health and the efficiency of health services. Non-profit health organizations and researchers in the academic fields use the information to make research to improve health. The media uses the results from the surveys to raise awareness about health, an issue of concern to all.

Collection period: Varies according to the question


  • Diseases and health conditions
  • Health
  • Lifestyle and social conditions

Data sources and methodology

Target population

The Nutrition Survey covers the population of all ages living in the ten provinces. Excluded from the survey's coverage are: persons living on reserves and other Aboriginal settlements; full-time members of the Canadian Forces and the institutionalized population. Altogether, these exclusions represent less than 3% of the target population.

Instrument design

The Nutrition questionnaire has been conceived with the collaboration of specialists from Statistics Canada, Health Canada and the United States Department of Agriculture (USDA), nutrition experts and members of an Expert Advisory Group. The questionnaire is composed of two components: 1) General Health and 2) 24-hour dietary recall. The general health component collected information about respondents such as height and weight, physical activities, chronic health conditions, smoking, food security, vitamin and mineral supplement consumption, and socio-demographic characteristics. The 24-hour dietary recall, a collection instrument developed by the USDA, collected information about all the foods and beverages respondents consumed during the 24 hours preceding the interview day, from midnight to midnight. Through consultations with Health Canada's nutrition experts, it was modified to fit the Canadian market in both official languages.

The 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. With CAI, the interview can be controlled based on answers provided by the respondent. On-screen prompts are shown when an invalid entry is recorded and thus immediate feedback is given to the respondent and/or the interviewer to correct inconsistencies.

Another enhancement is the automatic insertion of reference periods based on current dates. Pre-filling of text or data based on information gathered during the interview allows the interviewer to proceed without having to search back for previous answers. This type of pre-fill includes such things as using the correct name or sex within the questions themselves. Allowable ranges/answers based on data collected during the interview can also be programmed. In other words, the questionnaire can be customized to the respondent based on data collected at that time or during a previous interview.

The questionnaire was subjected to qualitative testing which consisted of one-on-one interviews and focus groups. A field test of all new survey content and methods was conducted during the month of June 2003. The main objectives of these tests 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 tests, the data collection computer application was extensively tested in-house in order to identify any errors in the questionnaire flow and text. The testing of the data collection computer application was an ongoing operation up until the start of the main survey.


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

A sample of 29,000 responding units was desired. A two-step strategy was used to allocate the sample to the provinces. First and in order to estimate intake distributions, 80 sample units were allocated to each domain of interest (14 age/sex groups) in each province (note that intake distributions for the <1 age group are required at the national level only). Thus, 1,120 units were assigned to each province in the first step for a total of 11,200. The remaining 17,800 units were allocated to the provinces using a power-allocation scheme using a power q=0.7 (except Prince Edward Island). The total sample size of any given province is found by adding the sizes obtained in the two steps.

Province Total sample

Newfoundland and Labrador 1,662
Prince Edward Island 1,120
Nova Scotia 1,957
New Brunswick 1,833
Quebec 4,864
Ontario 6,740
Manitoba 2,170
Saskatchewan 1,976
Alberta 3,116
British Columbia 3,562
CANADA 29,000

Moreover, Health Canada, Ontario, PEI and Manitoba bought extra sample which brought the final sample size to more than 35,000 respondents. The sample of 35,000 individuals was selected from four different frames: the Labour Force Survey (LFS) area frame, a list of CCHS 2.1 dwellings, the PEI and Manitoba Healthcare registries. The use of more than one frame was necessary to ensure the minimum number of 80 individuals required in each domain of interest.

The area frame, as designed for the LFS, covers almost the entire population. A sample of dwellings was selected under a multistage stratified cluster design. For those areas selected in the first stage of the design, a list of dwellings is prepared and maintained in the field. A sample of dwellings is then selected at the second stage from each list. The households in the selected dwellings become part of the sample.

The list frame of CCHS 2.1 dwellings was created using the household information of respondents from the regional component of the CCHS Cycle 2.1 for which the data was collected in 2003. Households in which there were at least one individual aged 18 or less (or, in Ontario only, at least one individual aged 71 or more) at the time of CCHS 2.1 data collection were identified and a list of dwelling addresses was created. This list was stratified by province and urban/rural zone and a sample of municipalities and/or cities was selected at the first stage. A sample of dwelling addresses was selected at the second stage.

The PEI and Manitoba Healthcare registries were used in these two provinces instead of the list frame of CCHS 2.1 dwellings. Using the information of health insurance cardholders, the provincial Ministries of Health of these two provinces provided STC with a list of dwelling addresses along with the household composition of these dwellings. The lists were stratified by urban/rural, a sample of municipalities and/or cities was selected at the first stage, and a sample of dwelling addresses was then selected at the second stage.

For this survey, it was decided to select one person per household using varying probabilities of selection that vary by age and by sampling frame. As well, in order to estimate the day to day variability in a person's diet, approximately 30% of respondents were asked to participate in a second 24-hour dietary recall interview.

Data sources

Data collection for this reference period: Varies according to the question

Responding to this survey is voluntary.

Data are collected directly from survey respondents.

Data collection, which began in January 2004, spanned the entire 2004 calendar year in order to eliminate possible seasonal effects and to spread out the interviewer workload in the field. The average length of interview was 60 minutes including the 24-hour dietary recall module (30 minutes). The majority of interviews were done face-to-face and conducted using the computer-assisted interviewing method. The height and weight measures of all respondents aged 2 and older were collected at the end of the interview. In addition to the exact measures, self-perceived height and weight were also collected from 10% of respondents aged 18 and older. In order to ensure a good representation of every day of the week in the final sample, field work was monitored on a regular basis.

Interviewers received 3.5 days of training before going out into the field. One of the advantages of using the 24-hour dietary recall application as developed by the USDA is that a trained nutritionist was not required to conduct the interview. It should be noted that this is one of the most complex computer assisted applications ever implemented in the field by Statistics Canada. To deal with this, much of the interviewer training focused around using the application and practising many scenarios which may arise in the field. Cycle 2.2 of the CCHS also presented a couple of other challenges to interviewers. Specifically collecting physical measurements of height and weight and food recall details from children.

In order to ensure accuracy and consistency for the measured height and weight several procedures were put in place. First high quality scales were used which did not require calibration, were easy to use and incredibly accurate (to within 50 grams). The accuracy of the scales was assessed at the beginning and end of the survey to ensure that their functioning did not degrade over time. Weight estimates were also monitored throughout collection to ensure that further interviewer training was not required.

Measuring height is a slightly more complicated procedure. Due to the constraint that interviewer staff are not trained health professionals the procedure must be non technical and non invasive. The procedure was developed with experts in the field to meet this objective. A training video was developed to ensure consistency among interviewers across the country. Further to measure inter-interviewer variability a test requiring interviewers to measure the same test subject was conducted before and after collection. Data was also monitored throughout collection to assess the need for further training during collection.

Regarding the procedure for interviewing children the following methods were implemented. All respondents aged 12 and older provided their own information. For children aged 6 to 11 the interview was conducted with assistance from the parent. This will ensure to the extent possible that details regarding foods eaten not in the parent's presence are collected. For children under the age of 6 only the parents provided the information. It is felt that for these age groups parents have much more control over what their children eat. In the instances where parents cannot provide the details, such as meals eaten at a daycare, parents were asked to contact the persons responsible to fill in the details as much as possible.

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

Error detection

Most editing of the data was performed at the time of the interview by the computer-assisted interviewing (CAI) application. In general, it was not possible for interviewers to enter out-of-range values and flow errors were controlled through programmed skip patterns. For example, in the General Health component CAI ensured that questions which applied only to children were not asked of adult respondents. Also, the 24-hour dietary recall included an extensive compilation of food-specific questions and answer options. In response to some types of inconsistent or unusual reporting, warning messages were invoked but in general, 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".


This methodology does not apply.


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% (1/50) 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 appears on the microdata file, and must be used to derive meaningful estimates from the survey. For example, if the number of individuals who consumed fruits and vegetables is to be estimated, it is done by selecting the records referring to those individuals in the sample having that characteristic and summing the weights entered on those records. 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. A survey weight is given to each person included in the final sample, that is, the sample of persons having answered the survey. This weight corresponds to the number of persons represented by the respondent for the entire population.

In order to determine the quality of the estimate and to calculate the coefficient of variation (CV), the standard deviation must be calculated. Confidence intervals also require the standard deviation of the estimate. The CCHS uses a multi-stage survey design, which means that there is no simple formula that can be used to calculate variance estimates. Therefore, an approximation method is needed. The bootstrap method is used because the sample design information needs to be taken into account when calculating variance estimates. The bootstrap method does this, and with the use of a proper computer program, remains a method that is fairly easy for users to use. The bootstrap re-sampling method used in the CCHS involves the selection of random samples known as replicates, and the calculation of the variation in the estimates from replicate to replicate. In each stratum, a simple random sample of (n-1) of the n clusters is selected with replacement to form a replicate. Note that since the selection is with replacement, a cluster may be chosen more than once. In each replicate, the survey weight for each record in the (n-1) selected clusters is recalculated. These weights are then post-stratified according to demographic information in the same way as the sampling design weights in order to obtain the final bootstrap weights. The entire process (selecting random samples, recalculating and post-stratifying weights for each stratum) is repeated B times, where B is large. The CCHS typically uses B=500, to produce 500 bootstrap weights. To obtain the bootstrap variance estimator, the point estimate for each of the B samples must be calculated. The standard deviation of these estimates is the bootstrap variance estimator. Statistics Canada has developed a program that can perform all of these calculations for the user: the Bootvar program.

Quality evaluation

Survey design has a profound effect on the objectives of the survey which are listed under "Survey Description". To meet these objectives the survey was designed under the guidance of an Expert Advisory Committee consisting of members from the nutrition field. The members represented regional, provincial and federal levels of government as well as academic institutions. Further a working group composed of members from Statistics Canada and Health Canada met regularly throughout the project cycle. This working group discussed and developed solutions to problems encountered throughout the survey cycle including: application development, training of interviewers, collection issues, data processing and verification as well as dissemination related activities. The partnership with Health Canada has been instrumental in ensuring the quality of the final data product. During the 1990s, Health Canada conducted a series of provincial nutrition surveys. The project has benefited greatly from the expertise that Health Canada developed during these initiatives.

The frames chosen to provide the sample, the Labour Force Survey frame and households selected in Cycle 2.1 of the CCHS have been combined with sampling design methodologies which have been tested, used repeatedly, and have been proven to produce accurate results. Each province large samples guarantee exact and significative results.

High response rates are essential for quality data. Actions have been taken to reduce non-sampling errors to a minimum. To reduce the number of non-response cases, the interviewers are all extensively trained by Statistics Canada, provided with detailed Interviewer Manuals, and are under the direction of interviewer supervisors. The extent of non-response varies from partial non-response (failure to answer just one or some questions) to total non-response. Partial non-response was basically non-existent. Total non-response occurred because the interviewer was either unable to trace the respondent, no member of the household was able to provide the information or the respondent refused to participate in the survey. In most cases, partial non-response to the survey occurred when the respondent did not understand or misinterpreted a question, refused to answer a question, could not recall the requested information or could not provide personal or proxy information. Total non-response was handled by adjusting the weight of households that responded to the survey to compensate for those who did not respond.

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.

Public Use Microdata Files (PUMFs) are produced in addition to the Master files. The PUMFs differ in a number of important aspects from the survey Master files held by Statistics Canada. These differences are the result of actions taken to protect the anonymity of individual survey respondents. First, only cross-sectional data are available on such files, because longitudinal information can lead to the identification of respondents. Also, some sensitive variables are regrouped, capped or completely deleted from the files. Users requiring access to information excluded from the microdata files may purchase custom tabulations, or access the Master files through the Research Data Centres program or the Remote Access program. Outputs are vetted for confidentiality before being given to users.

Before releasing and/or publishing any estimate from these files, users should first determine the number of sampled respondents who contribute to the calculation of the estimate. If this number is less than 30, the weighted estimate should not be released regardless of the value of the coefficient of variation for this estimate. For weighted estimates based on sample sizes of 30 or more, users should determine the coefficient of variation of the rounded estimate and follow the guidelines below.

Estimates in the main body of a statistical table are rounded to the nearest hundred units using the normal rounding technique. If the first or only digit dropped is zero to four, the last digit retained is not changed. If the first or only digit dropped is five to nine, the last digit retained is raised by one. Marginal sub-totals and totals in statistical tables are derived from their corresponding unrounded components and are then rounded themselves to the nearest 100 units using normal rounding methods. Averages, proportions, rates and percentages are computed from unrounded components (for example, numerators and/or denominators) and then are rounded themselves to one decimal using normal rounding. In normal rounding to a single digit, if the final or only digit dropped is zero to four, the last digit retained is not changed. If the first or only digit dropped is five to nine, the last digit retained is increased by one. Sums and differences of aggregates (or ratios) are derived from their corresponding unrounded components and then are rounded themselves to the nearest 100 units (or the nearest one decimal) using normal rounding. Under no circumstances are unrounded estimates published or otherwise, released. Unrounded estimates imply greater precision than actually exists.

Revisions and seasonal adjustment

This methodology does not apply to this survey.

Data accuracy

The survey targeted respondents from all age groups living in private occupied dwellings in the ten provinces. Excluded from the sampling frames were residents of the three territories, persons living on Indian reserves or Crown lands, persons living in institutions, full-time members of the Canadian Forces and residents of some remote regions. It is estimated that the sampling strategy employed for the survey covered 98% of the population living in the provinces.

The survey had a targeted response rate of 80%. Upon completion of collection activities, the survey had achieved an overall response rate of 76.5%. Response rates ranged from a low of 72.7% in Ontario to a high of 83.3% in Newfoundland and Labrador. For the second 24-hour dietary recall interview 72.8% of all respondents of the first recall that were selected to do a second recall agreed to participate.

All respondents aged 2 and older were asked for their permission to have their height and weight measured by the interviewer. In total 63% of respondents had both their height and weight measured by interviewers. The main reasons for non-response include refusal (11%), respondent not available (6%), respondent too tall for the interviewer to measure (5%), equipment problems (5%) and interview conducted over the phone (4%). In order to minimize the potential for non-response bias a special weight was created to be used with the measured height and weight information and the subsequent calculation of measured Body Mass Index.

For information on response rates, please refer to the document Response rates.pdf, under the Documentation section.


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