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about rapid risk factor surveillance system (RRFSS) data

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Need help understanding the data contained on this site?

  • For each data source, information about data collection and analytical methods, limitations, the citation and additional resources can be found on the Data Sources and Methods page.

The Rapid Risk Factor Surveillance System (RRFSS) is an on-going telephone survey administered in various public health units across Ontario. The survey collects information about health-related behaviours among adults aged 18 years and older. The purpose of RRFSS is to provide timely, useful information to help plan local public health programs and services.


Original Source: Region of Peel – Public Health

Cite as: Rapid Risk Factor Surveillance System, 2000-2011, 2016-2018, Region of Peel – Public Health.


Data Collection Methods

  • Monthly, a random sample of 100 Peel residents, aged 18 years and older, are interviewed by telephone regarding risk behaviours, knowledge, attitudes and awareness about health-related topics of importance to the public health unit.
  • The survey takes approximately 20 minutes to complete.
  • The survey content varies from year to year.
  • The Institute for Social Research (ISR) at York University conducts the survey on behalf of all RRFSS-participating health units.
  • In 2018, a 'dual frame' sample methodology was implemented. Dual frame refers to combining a single landline sample frame, as used in previous years, with a single cell sample frame. Due to this change in methodology, data from 2018 should not be compared to previous years.

  • NOTE: Peel Public Health did not participate in this survey from 2012 to 2015. Data are available for Peel Region from 2001 to 2011 and 2016 to 2018.

Release Guidelines

  • Coefficients of Variation (CV) are generated and are applied using the Statistics Canada release guidelines as follows:
    • CV between 0 and 16.5: Releasable
    • CV between 16.6 and 33.3: Use with caution. In this scenario, the letter ‘a’ is presented within the data table, with a footnote stating ‘Use estimate with caution’
    • CV greater than 33.3: Not releasable. In this scenario, the acronym ‘NR’ is presented in the data table, with a footnote stating ‘Not releasable due to small numbers’
  • Denominators with a cell size less than 30 and numerators with a cell size of less than ten (10) are not releasable and are reflected with the acronym ‘NR’ in the data table and a footnote stating ‘Not releasable due to small numbers’.

Data Analysis Methods

  • By applying population weights, measures such as percentages and numbers (referred to as population estimates in the tables on this website) are therefore estimates of the total population.
  • Household weights are provided by ISR to account for the probability of an adult being selected within their household. Module questions related to a household (e.g., household emergency plans) are not weighted. Individual-level responses (e.g., support for smoking bans) are weighted using the appropriate household weight variable.
  • 95% confidence intervals are also presented in the data tables. The confidence interval presents a lower and upper range of values, which contains the true value of the percentage for the whole population 95% of the time, or 19 times out of 20.
  • When the 95% confidence interval of one percentage does not overlap with that of another percentage, the difference between the percentages is considered statistically significant (i.e., very unlikely to be due to chance). Throughout the key messages, the terms “significantly higher” or “significantly lower” are used to describe data that are significantly higher or lower based on the 95% confidence intervals that do not overlap with one another.
  • For data up to 2011, when ‘Don’t Know’ and/or ‘Refused’ responses are greater than 5%, they are included in the denominator calculation and presented in the data tables; when ‘Don’t know’ and/or ‘Refused’ responses are less than 5%, they are excluded in the denominator for calculations.
  • Starting with data in 2016, ‘Don’t Know’ and ‘Refused’ responses were excluded from calculations, unless ‘Don’t know’ is a valid response option. If above 5%, a note below the table will indicate the proportion of ‘don’t know’ and ‘refused’ responses. This may be presented as a range to cover multiple years of data.


Responses to the questions are grouped by the following demographic variables:

Question: Could you please tell me how much income you and other members of your household received in the year ending Dec 31st, ???? (insert previous year), before taxes. Please include income from all sources such as savings, pensions, rent, as well as wages. Was the total household income from all sources:

  • Less than $20,000
  • $20-30,000 ($29,999)
  • $30-40,000 ($39,999)
  • $40-50,000 ($49,999)
  • $50-60,000 ($59,999)
  • $60-70,000 ($69,999)
  • $70-80,000 ($79,999)
  • $80-90,000 ($89,000)
  • $90-100,000 ($99,999)
  • $100-120,000 ($119,999)
  • $120-150,000
  • $150,000+
  • Don’t know
  • Refused
Question: What is your best estimate of the total income received by all household members, from all sources, before taxes and deductions, in the year ending December 31st, ???? (insert previous year).

Income categories:

  • < $30,000
  • $30,000 to $69,999
  • $70,000 to $99,999
  • $100,000+

Question: What is the highest level of education you have obtained?

  • did not graduate from high school
  • graduated from high school
  • some post high school education
  • college/university diploma/degree

Education categories:

  • Less than high school
  • High school, some college or university
  • Post-secondary graduate


  • Depending upon the question, self-reported data may be subject to a number of survey biases, including social desirability bias, response bias or recall bias.
  • Individuals and/or households without a landline telephone are excluded from the sampling frame.
  • In Peel, the survey is administered in English only.
  • Some analyses are limited by sample size.


  1. RRFSS Website

Last updated: June 6, 2019

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