Food Availability (per person)
Detailed information for 2015
The food statistics tables are designed to provide annual measures of the availability of food for consumption on a per person basis along with supply and disposition data for selected food products.
Data release - May 30, 2016
The food statistics tables are designed to provide annual measures of food availability per person along with supply and disposition of selected food products. A wide range of food products consumed by Canadians is covered by this program. These include dairy products, beverages, eggs, pulses and nuts, sugars and syrups, cereal products, meats and poultry, citrus fruits, fresh fruits, processed fruits, fresh vegetables, processed vegetables, juices, oils and fats, and fish.
The data are of interest to agricultural producers and their organizations, governments, financial institutions, the agri-food industry and the Canadian consumers. The data are used by agricultural industry analysts and producers as they make production and marketing decisions and by government analysts to monitor the agriculture industry or to develop agricultural policies in Canada.
Reference period: Calendar year
Collection period: January to December
- Crops and horticulture
- Food and nutrition
- Food, beverage and tobacco
- Livestock and aquaculture
Data sources and methodology
Conceptually, the universe consists of all Canadians although practically speaking, the food availability (disappearance) is derived residually.
Data are extracted from administrative files and derived from other Statistics Canada surveys and/or other sources.
Data presented in this program are compiled from a wide variety of sources, both survey and administrative, from within Statistics Canada, as well as other provincial and federal government departments, growers' associations and marketing boards.
A full description on collection and methodology is provided in the document "Food supply and disposition", available in the Documentation section below.
All efforts are taken to minimize non-sampling errors through quality controls in the data collection process and through careful review and analysis of all data for consistency. The data that is supplied by other programs of Statistics Canada are considered to have been rigorously analyzed. In case of any doubt about the data, the analyst proceeds to double-check the numbers with the person responsible for the source data. The analyst in charge of data collection and data analysis verifies each data series taking into account historical trends and revisions in order to detect any potential error. To eliminate data capture errors, a double-check of data capture is done by different persons.
This methodology type does not apply to this survey.
The supply-disposition approach is used to produce per capita food availability. All components of supply are added together and all uses (total disposition) other than domestic disappearance are deducted. This residual, which represents the amount of food available for human consumption, is referred to as "food available" (previously known as disappearance). To calculate total supply, imports, beginning stocks and Canadian production are added together. Domestic disappearance information is obtained by deducting ending stocks, exports, manufacturing uses, livestock feed, and waste where applicable from the total supply. This is then divided by the Canadian population to derive the per capita availability of the numerous food types.
The quality of the survey data is maintained through the expertise of analysts assigned to it. They develop a thorough knowledge of the domain, which is supplemented by outside personal contacts for particular food commodities. Much time and effort is devoted to detecting and following up unusual fluctuations over time of the supply disposition components such as the stocks, the international trade and the production at the Canadian level. Prior to dissemination, the data are analyzed and historic trends reviewed.
The survey results are regularly discussed with survey managers and analysts for the purposes of validation and to ensure data quality.
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.
Revisions and seasonal adjustment
For each period of study, the previous periods' data are revised if necessary. The revisions can be necessary when there are revisions done in the programs or surveys that feed the Food Statistics program. These revisions usually apply to the Canadian population, international trade data, intercensal revisions, loss factors or any other revisions. The Food Statistics program does not benchmark. Some commodities such as cereal products necessitate a calendarization adjustment.
The methodology of this program has been designed to control errors and to reduce the potential effects of these. The food statistics program is collecting data from administrative sources that originate from existing survey's data sets and from other various sources. The sampling errors from each survey have been controlled and minimized by the team responsible for the survey. To know more on sampling errors of a particular survey, the user must refer to the methodology of the particular survey. The food statistics program is not revising the sampling errors from the surveys. In case of a situation where the data from a survey are questionable, the analyst of the food statistic program will inform the section responsible for the survey of the finding. If data need to be revised, it will be done by the section responsible of the survey. Then after, the corrections will be incorporated to the food statistics program. The other possible source of errors is non-sampling errors. Examples of non-sampling error are data response error, non-response error and processing error. A discussion of these types of errors and the steps taken to address them follows.
- Food supply and disposition
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