Canadian Health Measures Survey (CHMS)

Detailed information for Spring 2007 to Spring 2009 (Cycle 1)




Every 2 years

Record number:


The Canadian Health Measures Survey (CHMS) aims to collect important health information through an household interview and direct physical measures at a mobile clinic.

Data release - November 19, 2008 (first in a series of releases. Please refer to the left sidebar, under the heading "The Daily"); November 20, 2023 (Diabetes among Canadian Adults)


The Canadian Health Measures Survey (CHMS), launched in 2007, is collecting key information relevant to the health of Canadians by means of direct physical measurements such as blood pressure, height, weight and physical fitness. As part of the CHMS, a clinical oral health examination helps to evaluate the association of oral health with major health concerns such as diabetes and respiratory and cardiovascular diseases. In addition, the survey is collecting blood and urine samples to test for chronic and infectious diseases, nutrition and environment markers.

Through household interviews, the CHMS is gathering information related to nutrition, smoking habits, alcohol use, medical history, current health status, sexual behaviour, lifestyle and physical activity, the environment and housing characteristics, as well as demographic and socioeconomic variables.

All of this valuable information will create national baseline data on the extent of such major health concerns as obesity, hypertension, cardiovascular disease, exposure to infectious diseases, and exposure to environmental contaminants. In addition, the survey will provide clues about illness and the extent to which many diseases may be undiagnosed among Canadians. The CHMS will enable us to determine relationships between disease risk factors and health status, and to explore emerging public health issues.

Canada is currently relying on self-reported information, isolated clinical studies and U.S. data to make estimates on the health status of Canadians. The Canadian Health Measures Survey (CHMS) is collecting health information about Canadians that cannot be otherwise captured or that may be inaccurately reported through self-report questionnaires or health care records. Hospital and medical records do provide data, but only on those who have received or are undergoing treatment, or on those who seek medical advice regularly.

The following are some of the measures that the CHMS includes:

Physical measures
. Anthropometry (standing height, sitting height, weight, waist circumference, hip circumference, skinfolds)
. Cardiovascular fitness (blood pressure, modified Canadian Aerobic Fitness Test)
. Musculoskeletal fitness (hand grip strength, sit and reach test, partial curl-ups)
. Physical activity (accelerometry)
. Lung function (spirometry)
. Oral health (clinical oral examination)

Blood measures
. Nutritional status (e.g., folate, calcium)
. Metabolic syndrome (e.g., indicators of pre-diabetes)
. Cardiovascular disease (e.g., lipid profile)
. Environmental exposure (e.g., lead, mercury)
. Infectious disease markers (e.g., hepatitis)

Urine measures
. Indicators of kidney disease (e.g., microalbumin, creatinine)
. Environmental exposure (e.g., cotinine, pesticides)
. Nutritional markers (e.g., iodine)

The CHMS stores biological samples for further analyses of measures at a later date. The CHMS team works closely with the Health Canada Research Ethics Board and the Office of the Privacy Commissioner of Canada in order to address privacy issues and to implement proper laboratory procedures.

Reference period: Varies according to the question (for example: "over the last 12 months," "over the last 6 months," "during the last week")


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

Data sources and methodology

Target population

The target population for the CHMS covers those individuals between 6 and 79 years of age living in privately occupied dwellings in the ten provinces and the three territories. Persons living on Indian Reserves or Crown lands, residents of institutions, full-time members of the Canadian Forces and residents of certain remote regions are excluded from this survey. Approximately 97% of Canadians will be represented.

Instrument design

Household Questionnaire Design

The CHMS household questionnaire was conceived in collaboration with specialists from Statistics Canada, Health Canada, the Public Health Agency of Canada and specialists in medical and academic fields. The CHMS questions were designed for computer-assisted personal interviewing (CAPI), 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.

Each question had to relate to a physical measure. Experts thoroughly reviewed the questionnaire many times during development. They provided valuable feedback on the questions and on the related physical measures.

The CHMS questionnaire and collection application were qualitatively tested to ensure respondent understanding of the questions and to identify any errors.


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

The sample was allocated over 10 age-gender groups, and 500 units per group will be required to produce national estimates, for a total of 5,000 reporting units.

Since reporting units have to get to a clinic located near their home for the physical measurements, site areas were limited to a radius of about 50 km (or up to 100 km for rural areas). To achieve this, collection sites were created using the Labour Force Survey's (LFS) area frame. The LFS geographic units used to define the sites were also grouped with respect to provincial and census metropolitan-area boundaries and population density criteria.

Using this frame, 257 sites were created, including 2 sites in the Territories. These sites were stratified based on the five regions of Canada: Atlantic, Quebec, Ontario, Prairies (including Yellowknife) and British Columbia (including Whitehorse). It was decided that a sample of 15 collection sites was required. These sites have been allocated by region in proportion to their populations: Atlantic (1), Quebec (4), Ontario (6), Prairies (2) and British Columbia (2).

Within each region, sites were sorted according to the size of their population and whether or not they belong to a census metropolitan area. Sites were randomly selected using a systematic sampling method with probability proportional to the size of each site's population.

Approximately 350 reporting units per site will participate in all parts of the survey.

Within each of the 15 selected sites, the list of the Census 2006 dwellings will be used as a frame.

Using the date of birth of household members present at Census time, dwellings will be stratified according to 5 age groups. The sample will be allocated in each stratum in such a manner as to obtain an equal number of respondents by age group.

Selected dwellings will be asked for the household member list at the time of the survey and one or two persons per household will be selected to participate in the survey. The selection of persons will be done randomly and will use a vector with variable selection probabilities by age group.

Data sources

Data collection for this reference period: 2007-03-01 to 2009-03-31

Responding to this survey is voluntary.

Data are collected directly from survey respondents.

Collection includes a combination of a personal interview using a computer-assisted interviewing method and, for the physical measures, a visit to a mobile clinic specifically designed for the survey.

The CHMS is collecting data in 15 sites across the country. The collection sites are located in five provinces: New Brunswick, Quebec, Ontario, Alberta and British Columbia. Collection is scheduled so that each region will be distributed within the two-year collection period, distributed between seasons and in a way that tries to minimize the movement of staff and equipment between sites. The CHMS mobile clinic stays in each site for six to eight weeks collecting direct measures from approximately 350 respondents per site.

First step: personal interview at the household

The first contact with respondents is a letter sent through the mail. The letter informs people living at the sampled address that an interviewer will visit their home to collect some information about the household.

When visiting the home, the interviewer randomly selects one or two respondents and conducts a separate health interview with each of them. The interview takes 45 to 60 minutes per respondent. The interviewer then assists the respondent in setting an appointment for the physical measures at the CHMS mobile clinic.

For children under 14 years of age, a parent or legal guardian must be present with the child at the clinic and must provide written consent for the child to participate in the tests.

Second step: visit to the CHMS mobile clinic

Statistics Canada uses mobile clinics to conduct the physical measures portion of the survey. Similar clinics have been used successfully for years by the NHANES in the United States.

The clinic consists of two trailers linked by an enclosed pedestrian walkway. One trailer serves as a reception and administration area, while the other contains clinic rooms and a laboratory.

For each respondent, the complete visit to the clinic lasts about two hours. This is an approximate time, given that each respondent will be assessed for their suitability for each measure and tested accordingly.

At the end of the visit to the mobile clinic, respondents are provided with a waterproof activity monitor. This small device is worn for a week at all times except when sleeping--even when swimming or bathing. It records information about normal physical activity patterns without the respondents having to do anything special. When the seven-day period is over, respondents return the monitor in a provided prepaid envelope.

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

Error detection

Edits were developed as part of the data capture application. These edits, including range checks and cross-references, are applied at the time of collection to ensure data quality. Anomalies in the information reported are confirmed with the respondent right away and corrected if necessary.

For the computer-assisted personal interviewing (CAPI) application, it is not possible for interviewers to enter out-of-range values, and flow errors are controlled through programmed skip patterns. For example, CAPI ensures that questions that do not apply to the respondent are not asked. In response to certain types of inconsistent or unusual reporting, warning messages are invoked. In some instances, no corrective action is taken at the time of the interview and edits are instead performed at Head Office after data collection.


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% 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. 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 CHMS uses a multi-stage survey design, which means that there is no simple formula that can be used to calculate variance estimates. Therefore, a rough method is needed to take into account the sample design information when calculating the variance estimates. The bootstrap method does this, and with the Bootvar program, remains a method that is fairly easy to use. CHMS will most likely use this method to calculate variance estimates. The bootstrap re-sampling method involves the selection of simple 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 first stage sampling units is selected with replacement to form a replicate. Note that since the selection is with replacement, a first stage sampling unit may be chosen more than once. In each replicate, the survey weight for each record in the (n-1) selected first stage sampling units 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 simple random samples, recalculating and post-stratifying weights for each stratum) is repeated B times, where B is large. To obtain the bootstrap variance estimator, the point estimate must be calculated for each of the B samples. 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, an internal Steering Committee and an external committee with Health Canada and the Public Health Agency of Canada were convened to determine the concepts and focus of the survey. An Expert Advisory Committee, a Physician Advisory Committee and a Laboratory Advisory Committee were convened, to advise on the measures to obtain the results envisioned by the Steering Committees and to recommend proven collection vehicles and indices. The resulting data is recognized as valid measures of contemporary concepts such as: physical activity, cardiovascular health, oral health, overweight and obesity, and chronic disease.

Household data quality evaluation

High response rates are essential to data quality. 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 the interviewer manager. 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 is basically non-existent. Total non-response occurs because the interviewer is unable to trace the respondent, no member of the household is able to provide the information or the respondent refuses to participate in the survey. Total non-response is handled by adjusting the weight of households that responded to the survey to compensate for those who do not respond. In most cases, partial non-response to the survey occurs when the respondent does not understand or misinterprets a question, refuses to answer a question, cannot recall the requested information or cannot provide personal or proxy information. Refusals are followed up by the interviewer manager to encourage respondents to participate in the survey.

Clinic and lab data quality evaluation

At the end of the home interview, the interviewer provides the respondent with guidelines specific to the appointment time slot for which they have been randomly selected (AM or PM/evening). The guidelines serve to ensure standardization by minimizing the potential factors that will affect the results of certain tests, thus enhancing the quality of the data collected. At the beginning of the MEC visit adherence to these guidelines is verified and documented within the data capture application.

Staff were selected based on the level of education, experience and certification(s) required for each field staff position. In addition to their specialized education, experience and training in their field of expertise, a significant amount of survey-specific training was provided to all field staff. Staff training emphasized the need for standardization of all survey procedures and focused on procedures relating to quality control guidelines.

Observations of all clinic staff and on all components are performed at regular intervals to provide a direct evaluation of protocol adherence, interaction with respondent and overall data collection quality and functioning of the clinic.

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.

In order to prevent any data disclosure, confidentiality analysis is done using the Statistics Canada Generalized Disclosure Control System (G-Confid). G-Confid is used for primary suppression (direct disclosure) as well as for secondary suppression (residual disclosure). Direct disclosure occurs when the value in a tabulation cell is composed of or dominated by few enterprises while residual disclosure occurs when confidential information can be derived indirectly by piecing together information from different sources or data series.

Revisions and seasonal adjustment

This methodology does not apply to this survey.

Data accuracy

As stated in the Quality Evaluation section, considerable efforts have been taken to ensure high standards throughout all stages of collection and processing. However, the resulting estimates are inevitably subject to a certain degree of non-sampling error. Non-sampling error is not related to sampling and may occur for various reasons. For example, non-response is an important source of non-sampling error. Population coverage, differences in the interpretations of questions and mistakes in recording, coding and processing data are other examples of non-sampling errors.

Total non-response is handled by adjusting the weight of persons in households that responded to the survey to compensate for those who do not respond.

Sampling error can be measured by the standard error (or standard deviation) of the estimate. The coefficient of variation (CV) is the estimated standard error percentage of the survey estimate. Estimates with smaller CVs are more reliable than estimates with larger CVs.


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