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Data Notes - Rapid Risk Factor Surveillance System (RRFSS)

The Halton Region Health Department uses data from the Rapid Risk Factor System to monitor the health of our community. Learn more about our methodology.

These data notes provide you with information on the Rapid Risk Factor Surveillance System (RRFSS), as well as methods and limitations associated with RRFSS health indicator reports produced by the Halton Region Health Department (HRHD). Health indicator reports can be found on the Halton Health Statistics website.


RRFSS is an ongoing telephone survey used to collect information on attitudes, behaviours, knowledge and awareness of issues related to health in Halton. RRFSS is conducted by the Institute of Social Research at York University.

Since 2001, every month a random sample of approximately 100 adults aged 18 and over are surveyed in Halton Region. The information collected in these surveys is used by the HRHD to produce health indicator reports which support program planning and evaluation, policy development and help to improve awareness of health issues in the community.

Making Comparisons

When multiple years of data are available, comparisons in health indicator reports are made over time. Comparisons are also made by sex, age, municipality, income and education for questions related to individuals, and by municipality and income for questions related to households.


Household weights are used for questions related to individuals. The household weights adjust for the fact that an adult from a household with a large number of adults is less likely to be selected than an adult from a household with a smaller number of adults.

Calculating Income Groups

Income groups are determined by first calculating a respondent’s adjusted household income (household income divided by the square root of their household size). Adjusted household income reflects the fact that a household’s needs increase as the number of members increase. The adjusted household income for all Halton respondents are then organized into 10 equal deciles and placed into low (decile 1-3), middle (decile 4-7) and high (decile 8-10) income groups. Respondents who do not know or refuse to provide their household income (about 25% of respondents) are excluded from the income analysis.

Statistical Significance and Variation

Overlapping 95% confidence intervals (CIs) are used to determine statistical significance in health indicator reports. A 95% confidence interval refers to a range of values that have a 95% chance of including the true estimate. When CIs do not overlap between 2 or more groups (e.g. when comparing males and females) it means that the differences between the groups are statistically significant and unlikely to be due to chance alone. Since overlapping confidence intervals are used to determine statistical significance, p-values are not calculated. This is a conservative approach which is more appropriate when multiple comparisons are being made, such as in health indicator reports. CIs are used to determine statistical significance, however CIs are not always presented in health indicator reports.

When six or more years of data are available, trends over time are tested for statistical significance using linear regression and adjusting for auto-correlation.

Coefficient of variation (CV) refers to the precision of an estimate. When the CV is between 16.6 and 33.3, the estimate should be interpreted with caution because of high variability, and has been marked with an asterisk (*). Estimates with a CV of greater than 33.3 are not reportable and have been marked with double asterisks (**) in the figures and tables.


RRFSS results are self-reported and may not be recalled accurately. Individuals not living in households (such as those in prison, hospitals, or the homeless) are excluded. Individuals who live in a household without a landline telephone are also not reached through RRFSS (over 21% of all Canadian households, and 61% of Canadian households under 35 years old). As a result, the percentages may not represent the true estimates for the general population.

Rounded estimates are used for the presentation of data, therefore estimates may not total 100 percent.

Don’t know and refused responses are typically excluded from the analysis. When “don’t know” is considered a valid response, or when over 5% of respondents answer “don't know”, the response is included in the analysis.