Functional Foods and Natural Health Products Survey

Detailed information for 2011





Record number:


The objectives of the survey are to produce statistical information on the functional food and natural health product sector and a profile of firms engaged in functional food and/or natural health product related activities in Canada.

Data release - May 6, 2013


The objectives of the survey are to produce statistical information on the functional food and natural health product sector and a profile of firms engaged in functional food and/or natural health product related activities in Canada.

Information from this survey may be used by businesses for economic or market analysis, by trade associations to study industry performance, by government departments and agencies to assist policy formation, and by the academic community for research purposes.


  • Biotechnology
  • Food, beverage and tobacco
  • Manufacturing
  • Science and technology

Data sources and methodology

Target population

The target population includes all establishments identified as engaged in functional food and/or natural health product related activities (for the purpose of human consumption) in Canada. Establishment must have developed, produced or provided services related to functional foods or natural health products. Establishments which strictly retailed or wholesaled functional foods or natural health products were not surveyed. These activities are not aligned with a specific industry or industries as defined by the North American Industry Classification System (NAICS). Establishments of the following types are excluded: not-for-profit organizations, associations, alliances, unions, universities, as well as government agencies, departments and commissions.

Instrument design

The Functional Food and Natural Health Products Survey used one paper questionnaire to collect data from respondents. This questionnaire was designed by Statistics Canada in co-operation with Agriculture and Agri-Food Canada and in consultation with a group of functional food and natural health product experts. Following the initial design work, the questionnaire was field-tested with potential respondents. Their comments on the design and content were incorporated into the final version.


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

The statistical unit is the establishment. The survey population includes all establishments identified by Agriculture and Agri-Food Canada as engaged in functional food and/or natural health product-related activities in Canada.

The survey frame was developed in several stages. Agriculture and Agri-Food Canada compiled a list of business units they identified as engaged in functional food and/or natural health product-related activities in Canada. Additional units were added to this list from respondents to the 2007 iteration of the survey and from other related external data sources. Businesses in the list were then matched to units on the Statistics Canada Business Register and duplicates were removed. The final survey frame comprised 1,623 establishments engaged in functional food and natural health product-related activities.

Data sources

Data collection for this reference period: 2012-04-12 to 2012-08-10

Responding to this survey is mandatory.

Data are collected directly from survey respondents.

All establishments were "pre-contacted" by telephone to confirm they were in-scope for the survey, as well as to determine the name and mailing address for the senior plant manager or research and development manager who would be asked to complete the questionnaire.

Data were collected using a mail out/mail back questionnaire. Questionnaires were mailed to 1,233 establishments following pre-contact. Respondents were asked to return the completed questionnaire within 30 days of receipt. Follow-up for non-response was conducted by telephone and fax. Upon receipt, the collected questionnaires were imaged and data from the questionnaires was captured.

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

Error detection

Error detection is an integral part of both collection and data processing activities. Automated edits were applied to data records during collection to identify capture and reporting errors. During collection, respondents were contacted by telephone to validate collected data which failed edits.

Prior to imputation, subject matter specialists used a variety of tools to identify and resolve inconsistencies and outliers in the collected data. This review of the micro data focused on records which would have the most significant impact on the final survey estimates either because of the size of their contribution or because of their use in imputation. Problems were resolved using historical and administrative data, data from other surveys, and information from other external sources.

Following imputation, subject matter specialists compared patterns in the current estimates with those observed in data from previous iterations of the survey. The largest differences in the patterns were investigated by reviewing the source of the change in the micro data and resolving any remaining data issues.


Imputation is used to determine plausible values for all variables that are missing or inconsistent in the collected data and which could not be resolved through editing. A number of different approaches were used to impute missing or inconsistent data. The simplest technique involved using a group of deterministic and coherence rules that dictate acceptable relationships among variables and derive missing values residually. Missing variables were also imputed by applying the ratios between variables and historical trends observed in the respondent data, to data records with partial information. Direct replacement of missing variables with data from other sources was another imputation approach used. Lastly, donor imputation was also used. This involved identifying a respondent record (donor) that was similar to the record which required imputation (recipient) based on information which was available for both businesses. The data available for the respondent was then used to derive that for the record requiring imputation.

Imputation groups were based on a number of criteria including firm type, various measures of size, complexity and province or region. Data for selected survey questions (1a, 1b and 2a) were used to assign a firm type to each respondent. Seven firms types were defined as follows: functional foods only; natural health products only; services only; functional foods and natural health products; functional foods and services; natural health products and services; and functional foods, natural health products and services.

No imputation was done for records when their firm type could not be assigned.


A complete micro data file was created for all establishments in the survey population for which data were reported or could be imputed. In a census, each establishment in the population would ordinarily represent only itself in the estimates with a weight of 1. However, no imputation was done for records when their firm type could not be assigned. These records were treated as non-respondents. As a result, weights on all records were adjusted by a factor to account for survey non-response so that the final estimates would be representative of the entire survey population.

Weighted estimates were produced using the Generalised System of Estimation.

Quality evaluation

Survey estimates were compared with estimates for previous iterations of the survey where possible. In addition, subject matter experts from outside Statistics Canada were given an opportunity to review the estimates and provide feedback on quality prior to their release.

Disclosure control

Statistics Canada is prohibited by law from releasing any information it collects which 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 was done using the G-CONFID system. G-CONFID was used for primary confidentiality as well as for the secondary suppression (residual disclosure). Direct disclosure or primary confidentiality occurs when the value in a tabulation cell is composed or dominated by few enterprises. 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 type does not apply to this statistical program.

Data accuracy

The data accuracy indicators used for the Functional Foods and Natural Health Products Survey are the standard error and the coefficient of variation. The standard error is a commonly used statistical measure indicating the error of an estimate associated to sampling and to adjustments made because of complete non-response. For this survey there was no error associated to sampling. The coefficient of variation is the standard error expressed as a percentage of the estimate.

The response rate for this survey was 50.6%.

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