Confidence intervals are 95%.

^a Population aged 12 and over who reported being a current smoker. Daily smoker refers to those who reported smoking cigarettes every day. Does not take into account the number of cigarettes smoked. Occasional smoker refers to those who reported smoking cigarettes occasionally. This includes former daily smokers who now smoke occasionally.

^b Non-smoking population aged 12 and over who reported being exposed to second-hand smoke in private vehicles and/or public places on every day or almost every day in the past month.

^c Starting in 2009, the denominator includes all respondents aged 12 and over. This change applies to rates from all years in this table. In data released before 2009, the denominator included only those respondents who reported having had at least one drink in the past 12 months. Increasing the population in the denominator reduces the estimate rates. This change was implemented to produce more comparable rates over time and is more consistent with methods used in calculating other indicators in this table. Not available for 2013-2014.

^d A definition change was implemented in 2013 to conform with the World Health Organization (WHO) and Health Canada guidelines for Heavy drinking. Heavy drinking refers to males who reported having 5 or more drinks, or women who reported having 4 or more drinks, on one occasion, at least once a month in the past year. While this indicator remains comparable for males to the 5 or more drinks indicator published in previous years, it is no longer comparable for females. Not available for 2007-2012.

^e BMI is only calculated for those aged 18 and over, excluding women who are pregnant and persons less than 3 feet tall or greater than 6 feet 11 inches.

^f Body Mass Index (BMI) for youth is different from that of adults as they are still considered to be maturing. This definition change was implemented in 2004 to conform with Health Canada guidelines for body weight classification.

E denotes a high sampling variability associated with the estimate. The coefficient of variation for these estimates is equal to or falls between 16.6% and 33.3%. Please use with caution.

Proxy Interview

In cases where the selected respondent was, for reasons of physical or mental health, incapable of completing an interview, another knowledgeable member of the household provided information about the selected respondent.

Canadian Community Health Survey (CCHS)

The Canadian Community Health Survey is a cross-sectional survey that collects information related to health status, health care utilization and health determinants for the Canadian population. It is designed to answer two crucial questions:

1. How healthy are Canadians?

2. How healthy is the Canadian health care system?

The CCHS targets persons age 12 years and older living in private dwellings. Excluded from the sample are individuals living on Indian Reserves or Crown Lands, institutional residents, full time members of the Canadian Armed Forces and residents in certain remote areas.

Confidence Interval

A confidence interval gives an estimated range of values which is likely to include an unknown population parameter, the estimated range being calculated from a given set of sample data.

If independent samples are taken repeatedly from the same population, and a confidence interval calculated for each sample, then a certain percentage (confidence level) of the intervals will include the unknown population parameter. A confidence level of 95% implies that 95% of all samples would give an interval that includes the population parameter.

The width of the confidence interval gives us some idea about how uncertain we are about the unknown parameter. A very wide interval may indicate that more data should be collected before anything very definite can be said about the parameter.

Confidence Level

The confidence level is the probability value (1-alpha) associated with a confidence interval.

It is often expressed as a percentage. For example, say alpha = 0.05 = 5%, then the confidence level is equal to (1-0.05) = 0.95, i.e. a 95% confidence level.

If independent samples are taken repeatedly from the same population, and a confidence interval calculated for each sample, then a certain percentage (confidence level) of the intervals will include the unknown population parameter. A confidence level of 95% implies that 95% of all samples would give an interval that includes the population parameter.

Example:
Suppose an opinion poll predicted that, if the election were held today, the Conservative party would win 60% of the vote. The pollster might attach a 95% confidence level to the interval 60% plus or minus 3%. That is, he thinks it very likely that the Conservative party would get between 57% and 63% of the total vote.

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