This Alberta Official Statistic describes the percent change in Alberta’s population between 1986 and 2011 by 5-year census cycles. The population is divided into "Larger Urban Centres" and Rural and Small Town areas. Within rural Alberta, the population is divided into four categories with each category consecutively representing lesser integration with urban economies. The four categories are called Metropolitan Influenced Zones (MIZ) and capture urban integration based on the percent of the working population commuting to urban centers. The categories are: Strong MIZ (where 30% or more of the workforce commutes to an urban core) Moderate MIZ (where 5% to 29% commute to any urban core) Weak MIZ (where greater than 0% but less than 5% commute to any urban core) No MIZ (where there are no residents commuting to an urban core)

Estimated number of persons by quarter of a year and by year, Canada, provinces and territories.

This Alberta Official Statistic describes the percent change in Alberta’s population between 1986 and 2011 by 5-year census cycles. The population is divided into "Larger Urban Centres" and Rural and Small Town areas. Within rural Alberta, the population is divided into four categories with each category consecutively representing lesser integration with urban economies. The four categories are called Metropolitan Influenced Zones (MIZ) and capture urban integration based on the percent of the working population commuting to urban centers. The categories are: Strong MIZ (where 30% or more of the workforce commutes to an urban core) Moderate MIZ (where 5% to 29% commute to any urban core) Weak MIZ (where greater than 0% but less than 5% commute to any urban core) No MIZ (where there are no residents commuting to an urban core)

Estimated number of persons on July 1, by 5-year age groups and gender, and median age, for Canada, provinces and territories.

The National Population Health Survey (NPHS) collects information related to the health of the Canadian population and related socio-demographic information. The NPHS is composed of three components: the household survey,the Health Care Institution Survey and the Northern Territories survey. These Public Use Microdata Files (PUMF) contain data collected in the household component of NPHS Cycle 3, 1998-1999. The NPHS household component includes household residents in all provinces, with the exclusion of populations on Indian Reserves,Canadian Forces Bases and some remote areas in Qubec and Ontario. The first Cycle of data collection began in 1994 and data will be collected every second year, for approximately 20 years in total. Three cycles of collection are now completed for each component: NPHS Cycle 1 (1994-1995), NPHS Cycle 2 (1996-1997) and NPHS Cycle 3 (1998-1999). For the first cycle, a sample of approximately 20,000 households was drawn from the Labour Force Survey sampling frame. For Cycle 3, this frame was also used to select an additional sample of recent immigrants and young children, thus ensuring that the data represent the 1998-1999 Canadian population. NPHS collects general health information from all household members and, in each household, a person, randomly selected during cycle 1 answers a more in-depth interview on health questions.For Cycle 3, approximately 49,000 respondents answered the general portion of the questionnaire while approximately 17,000 answered the more detailed health portion. The questionnaire includes questions related to health status, use of health services, determinants of health, chronic conditions and activity restrictions. The use of health services was measured through questions on visits to health care providers, both traditional and non-traditional, hospital cares and on use of drugs and other medications. Health determinants that are explored include smoking, alcohol use and physical activity. New content for the third Cycle of NPHS includes family medical history, self-care and nutrition. The socio-demographic information collected includes age, sex, education, ethnicity, household income and labour forcestatus. NOTE: A master file for this data set exists at SWORDC - Statistics Canadas Regional Data Centre located at the University of Waterloo. See Documentation section for details. The NPHS questions were designed for computer-assisted interviewing (CAI). Collection was divided into four quarters (June, August and November 1998 and February 1999). An additional collection was held in June 1999 with further tracing attempts of non-respondents from previous quarters. Respondents in the sample and the top-up sample of households with young children were first contacted by telephone. 95% of the interviews were done by telephone. NPHS collects general information from all household members and, in each household, a person, randomly selected during cycle 1, answers a more in-depth interview on health questions. For cycle 3, approximately 49,000 respondents answered the general portion of the questionnaire while approximately 17,000 answered the more detailed health portion.

This Alberta Official Statistic describes the percentage of the population that reported having an Aboriginal identity in 2011. The population is divided into larger urban centres and rural and small town areas. Within the larger urban centres, the population is divided between Census Metropolitan Areas (CMA) and two different sizes of Census Agglomerations (CA). Within rural and small town Alberta, the population is divided into four categories with each category consecutively representing less integration with urban economies. The four categories are called Metropolitan Influence Zones (MIZ) and capture urban integration by measuring the percentage of the working population commuting to urban centers. The categories are: Strong MIZ (where 30% to 49% of the workforce commutes to an urban core) Moderate MIZ (where 5% to 29% commute to an urban core) Weak MIZ (where 1% to 4% commute to an urban core) No MIZ (where there are no residents commuting to an urban core)

This Alberta Official Statistic describes the percentage of the population that reported having an Aboriginal identity in 2011. The population is divided into larger urban centres and rural and small town areas. Within the larger urban centres, the population is divided between Census Metropolitan Areas (CMA) and two different sizes of Census Agglomerations (CA). Within rural and small town Alberta, the population is divided into four categories with each category consecutively representing less integration with urban economies. The four categories are called Metropolitan Influence Zones (MIZ) and capture urban integration by measuring the percentage of the working population commuting to urban centers. The categories are: Strong MIZ (where 30% to 49% of the workforce commutes to an urban core) Moderate MIZ (where 5% to 29% commute to an urban core) Weak MIZ (where 1% to 4% commute to an urban core) No MIZ (where there are no residents commuting to an urban core)

This Alberta Official Statistic describes the per capita health service providers in 2011. Per capita health service providers are the number of individuals working in medicine or health occupations per 1,000 people. The population is divided into larger urban centres and rural and small town areas. Within rural and small town Alberta, the population is divided into four categories according to integration with urban economies. The four categories are called Metropolitan Influence Zones (MIZ) and capture urban integration by measuring the percentage of the working population commuting to urban centers. The categories are: Strong MIZ (where 30% to 49% of the workforce commutes to an urban core) Moderate MIZ (where 5% to 29% commute to an urban core) Weak MIZ (where 1% to 4% commute to an urban core) No MIZ (where there are no residents commuting to an urban core)

In 2022, 9.9 percent of all Canadians were living in low income. Between 2000 and 2022, the percentage of population with low income experienced a decrease, reaching the lowest value in 2020. The highest share of Canadians with low income was recorded in 2015, with 14.5 percent of the total population.

Low Income Measures

The low income measures (LIMs) were developed by Statistics Canada in the 1990s. They, along with the low income cut-offs (LICOs) and the market basket measure (MBM), were created in order to measure and track the low income population of Canada. With low income measures, individuals are classified as being in low income if their income falls below fifty percent of the median adjusted household income. The median income is adjusted in order to reflect the differing financial needs of households based on the number of its members. The low income measures are a useful tool to compare low income populations between countries as they do not rely on an arbitrary standard of what constitutes the threshold for poverty. Statistics Canada insists that the low income measures are not meant to be representative of a poverty rate. The department has no measure which they define as a measurement of poverty in Canada. Latest data and trends In 2022, around 2.1 million people were living in low income families in Canada. This figure has been fluctuating over the years, both in absolute numbers and in proportion over the total population. More women than men were living in low income families in 2022, though the number of men in low income has risen at twice the rate as that of women. One of the more drastic changes has been the rise in the number of single individuals living in low income, increasing by more than 60 percent since 2000.

The 2001 Census Public Use Microdata File (PUMF) on Families contains data based on a 2.7% sample of the population enumerated in the census. It provides information on the demographic, social and economic characteristics of the census families and non-family persons. This microdata file allows users to group and manipulate the data to suit their own requirements. The documentation (metadata) provided in the PUMF on families is divided into four chapters: Chapter I contains the record layout, an essential tool for using the file; Chapter II describes the variables included in the file; Chapters III and IV deal with the sampling method and data quality. There are two other public use microdata files: one on individuals and another on households and housing. For the 2001 Census, several changes were made to the census family concept: Two persons living in a same-sex common-law relationship, along with any of their children residing in the household, will be considered a census family. Children in a census family can have been previously married (as long as they are not currently living with a spouse or common-law partner). Previously, they had to be "never-married". A grandchild living in a three-generation household where the parent (middle generation) is never-married will, contrary to previous censuses, now be considered as a child in the census family of his or her parent, provided the grandchild is not living with his or her own spouse, common-law partner, or child. Traditionally, the census family usually consisted of the two older generations. A grandchild of another household member, where a middle-generation parent is not present, will now be considered as a child in the census family of his or her grandparent, provided the grandchild is not living with his or her own spouse, common-law partner, or child. Traditionally, such a grandchild would not be considered as the member of a census family. For same-sex common-law couples, the records were handled as follows: regardless of the sex of each partner, the census family reference person was designated as the male common-law partner, and his or her partner was designated as the female common-law partner. The question on religion, which is asked every 10 years, was re-introduced in 2001. In 2001, two new questions were added: one on the birthplace of parents and the other on the language of work. A second part was also added to the question on home language. In view of the legal recognition of same-sex couples, the census definition of a common-law couple was changed to "two people of the opposite sex or of the same sex who live together as a couple but who are not legally married to each other". The question on fertility was not asked in the 2001 census.

This Alberta Official Statistic describes the highest level of educational attainment among the population (25 to 64 years of age) in 2011. The population is divided into larger urban centres and rural and small town areas. Within rural and small town Alberta, the population is divided into four categories according to integration with urban economies. The four categories are called Metropolitan Influence Zones (MIZ) and capture urban integration by measuring the percentage of the working population commuting to urban centers.

Ontario was the province with the most immigrants in 2024, with 197,657 immigrants. Nunavut, Canada’s northernmost territory, had 56 immigrants arrive in the same period. Immigration to Canada Over the past 20 years, the number of immigrants to Canada has held steady and is just about evenly split between men and women. Asian countries dominate the list of leading countries of birth for foreign-born residents of Canada, although the United Kingdom, the United States, and Italy all make the list as well. Unemployment among immigrants In 2023, the unemployment rate for immigrants in Canada was highest among those who had been in the country for five years or less. The unemployment rate decreased the longer someone had been in Canada, and unemployment was lowest among those who had been in the country for more than ten years, coming more into line with the average unemployment rate for the whole of Canada.

This Alberta Official Statistic describes the per capita health service providers in 2011. Per capita health service providers are the number of individuals working in medicine or health occupations per 1,000 people. The population is divided into larger urban centres and rural and small town areas. Within rural and small town Alberta, the population is divided into four categories according to integration with urban economies. The four categories are called Metropolitan Influence Zones (MIZ) and capture urban integration by measuring the percentage of the working population commuting to urban centers. The categories are: Strong MIZ (where 30% to 49% of the workforce commutes to an urban core) Moderate MIZ (where 5% to 29% commute to an urban core) Weak MIZ (where 1% to 4% commute to an urban core) No MIZ (where there are no residents commuting to an urban core)

This Alberta Official Statistic describes the highest level of educational attainment among the population (25 to 64 years of age) in 2011. The population is divided into larger urban centres and rural and small town areas. Within rural and small town Alberta, the population is divided into four categories according to integration with urban economies. The four categories are called Metropolitan Influence Zones (MIZ) and capture urban integration by measuring the percentage of the working population commuting to urban centers.

(StatCan Product) Employed by industries and sectors (NAICS 2007 – 1, 2, 3 and 4 digits) for Canada, selected provinces (QC, ON, AB and BC), Edmonton (CMA) and Calgary (CMA) (annual averages). Customization details: This information product has been customized to present information on the employed by industries: - TABLE 1: Employed by industries (NAICS 2007 – 1, 2, 3 and 4 digits) for Canada, selected provinces (Quebec, Ontario, Alberta and British Columbia) and the Alberta Census Metropolitan Areas (CMA) of Edmonton and Calgary – Annual Averages from 2001 to 2011 (in thousands). Labour Force Survey The Canadian Labour Force Survey was developed following the Second World War to satisfy a need for reliable and timely data on the labour market. Information was urgently required on the massive labour market changes involved in the transition from a war to a peace-time economy. The main objective of the LFS is to divide the working-age population into three mutually exclusive classifications - employed, unemployed, and not in the labour force - and to provide descriptive and explanatory data on each of these. Target population The LFS covers the civilian, non-institutionalized population 15 years of age and over. It is conducted nationwide, in both the provinces and the territories. Excluded from the survey's coverage are: persons living on reserves and other Aboriginal settlements in the provinces; full-time members of the Canadian Armed Forces and the institutionalized population. These groups together represent an exclusion of less than 2% of the Canadian population aged 15 and over. National Labour Force Survey estimates are derived using the results of the LFS in the provinces. Territorial LFS results are not included in the national estimates, but are published separately. Instrument design The current LFS questionnaire was introduced in 1997. At that time, significant changes were made to the questionnaire in order to address existing data gaps, improve data quality and make more use of the power of Computer Assisted Interviewing (CAI). The changes incorporated included the addition of many new questions. For example, questions were added to collect information about wage rates, union status, job permanency and workplace size for the main job of currently employed employees. Other additions included new questions to collect information about hirings and separations, and expanded response category lists that split existing codes into more detailed categories. Sampling This is a sample survey with a cross-sectional design. Data sources Responding to this survey is mandatory. Data are collected directly from survey respondents. Data collection for the LFS is carried out each month during the week following the LFS reference week. The reference week is normally the week containing the 15th day of the month. LFS interviews are conducted by telephone by interviewers working out of a regional office CATI (Computer Assisted Telephone Interviews) site or by personal visit from a field interviewer. Since 2004, dwellings new to the sample in urban areas are contacted by telephone if the telephone number is available from administrative files, otherwise the dwelling is contacted by a field interviewer. The interviewer first obtains socio-demographic information for each household member and then obtains labour force information for all members aged 15 and over who are not members of the regular armed forces. The majority of subsequent interviews are conducted by telephone. In subsequent monthly interviews the interviewer confirms the socio-demographic information collected in the first month and collects the labour force information for the current month. Persons aged 70 and over are not asked the labour force questions in subsequent interviews, but rather their labour force information is carried over from their first interview. In each dwelling, information about all household members is usually obtained from one knowledgeable household member. Such 'proxy' reporting, which accounts for approximately 65% of the information collected, is used to avoid the high cost and extended time requirements that would be involved in repeat visits or calls necessary to obtain information directly from each respondent. Error detection The LFS CAI questionnaire incorporates many features that serve to maximize the quality of the data collected. There are many edits built into the CAI questionnaire to compare the entered data against unusual values, as well as to check for logical inconsistencies. Whenever an edit fails, the interviewer is prompted to correct the information (with the help of the respondent when necessary). For most edit failures the interviewer has the ability to override the edit failure if they cannot resolve the apparent discrepancy. As well, for most questions the interviewer has the ability to enter a response of Don't Know or Refused if the respondent does not answer the question. Once the data is received back at head office an extensive series of processing steps is undertaken to thoroughly verify each record received. This includes the coding of industry and occupation information and the review of interviewer entered notes. The editing and imputation phases of processing involve the identification of logically inconsistent or missing information items, and the correction of such conditions. Since the true value of each entry on the questionnaire is not known, the identification of errors can be done only through recognition of obvious inconsistencies (for example, a 15 year-old respondent who is recorded as having last worked in 1940). Estimation The final step in the processing of LFS data is the assignment of a weight to each individual record. This process involves several steps. Each record has an initial weight that corresponds to the inverse of the probability of selection. Adjustments are made to this weight to account for non-response that cannot be handled through imputation. In the final weighting step all of the record weights are adjusted so that the aggregate totals will match with independently derived population estimates for various age-sex groups by province and major sub-provincial areas. One feature of the LFS weighting process is that all individuals within a dwelling are assigned the same weight. In January 2000, the LFS introduced a new estimation method called Regression Composite Estimation. This new method was used to re-base all historical LFS data. It is described in the research paper ""Improvements to the Labour Force Survey (LFS)"", Catalogue no. 71F0031X. Additional improvements are introduced over time; they are described in different issues of the same publication. Data accuracy Since the LFS is a sample survey, all LFS estimates are subject to both sampling error and non-sampling errors. Non-sampling errors can arise at any stage of the collection and processing of the survey data. These include coverage errors, non-response errors, response errors, interviewer errors, coding errors and other types of processing errors. Non-response to the LFS tends to average about 10% of eligible households. Interviews are instructed to make all reasonable attempts to obtain LFS interviews with members of eligible households. Each month, after all attempts to obtain interviews have been made, a small number of non-responding households remain. For households non-responding to the LFS, a weight adjustment is applied to account for non-responding households. Sampling errors associated with survey estimates are measured using coefficients of variation for LFS estimates as a function of the size of the estimate and the geographic area.

In 2021, 53.3 percent of the total population in Canada were Christian, 4.9 percent were Muslim, but almost more than a third are not religious at all – with the rest stating they adhere to Hinduism, Sikhism, Buddhism, the Jewish faith, and other Christian denominations. Canada’s religious pluralismCanada is not a very religious country in general. Canadians adhere to a wide variety of beliefs and faiths, with the majority following Christianity, followed by those who do not believe in any deity or religion at all. As with many Western countries, the younger generations are less inclined to identify with faith, and Christianity in particular is not as popular as it is among the older generations. Alternative worship for the younger generations?Canadian teenagers are no less enthusiastic about religion than their parents, and they are just as grounded in their faith as the older generations. They are, however, also just as indecisive when it comes to whether they would call themselves religious or not. Interestingly, they seem much more interested in traditional aboriginal spirituality than in the Judeo-Christian model. They also seem quite interested in another alternative to Christianity: Buddhism is quite popular among the younger generations. Whether this signifies a general trend away from Christianity and towards religious alternatives remains to be seen.

Health characteristics, two-year period estimates, census metropolitan areas and population centres (1, 2, 3, 4, 5, 6, 7, 8, 9)Frequency: OccasionalTable: 13-10-0805-01 (formerly CANSIM 105-0593)Release date: 2022-04-19Geography: Canada, Province or territory, , Census metropolitan area, Census metropolitan area partFootnotes:1 Source: Statistics Canada, Canadian Community Health Survey (CCHS).2 All estimates in this table are calculated excluding non-response categories (refusal"3 Data for the Canadian Community Health Survey (CCHS) are collected yearly from a sample of approximately 65,000 respondents. The table 13-10-0805-01 presents estimates from two-year combined data and features breakdown by all census metropolitan areas (CMA), population centre (POPCTR) and rural areas.4 A census metropolitan area (CMA) is an area consisting of one or more adjacent municipalities situated around a major urban core. A CMA must have a total population of at least 100,000 of which 50,000 or more must live in the core. Beginning in 2013/2014, the CMAs are defined by the 2011 Census.5 A population centre (POPCTR) has a population of at least 1,000 and a population density of 400 persons or more per square kilometre, based on population counts from the 2011 Census of Population. Population centres are classified into three groups, depending on the size of their population: small population centres, with a population between 1,000 and 29,999; medium population centres, with a population between 30,000 and 99,999; large urban population centres, with a population of 100,000 or more. The rural area of Canada is the area that remains after the delineation of population centres using 2011 census population data. Included in rural areas are: small towns, villages and other populated places with less than 1,000 population; rural areas of census metropolitan areas and census agglomerations that may contain estate lots, as well as agricultural, undevelopped an non-developable lands; agricultural lands; remote and wilderness areas.6 In the north, the frame for the Canadian Community Health Survey (CCHS) covers 92% of the targeted population in the Yukon, 96% in the Northwest Territories and 92% in Nunavut. In Nunavut, starting in 2013, the coverage was expanded to represent 92% of the targeted population. Before 2013, the coverage was 71% since the survey covered only the 10 largest communities.7 Due to changes in content and methodology, this table now replaces table 13-10-0464-01, which will now only be made available for historical revisions. As a result of the changes, users should use caution when comparing data in this table with the data in 13-10-0464-01.8 As a result of the 2015 redesign, Canadian Community Health Survey (CCHS) has a new collection strategy, a new sample design, and has undergone major content revisions. With all these factors taken together, caution should be taken when comparing data from previous cycles to data released for the 2015 cycle onwards.9 The COVID-19 pandemic had major impacts on the data collection operations for Canadian Community Health Survey (CCHS) 2020. The collection was stopped mid-March, towards the end of the first collection period, and did not resume until September. The second, third and fourth quarterly samples were collected during very short collection periods, each of about five weeks, from September to December. The impossibility of conducting in-person interviews, the shorter collection periods and collection capacity issues resulted in a significant decrease in the response rates. As for previous CCHS cycles, survey weights were adjusted to minimise any potential bias that could arise from survey non-response; non-response adjustments and calibration using available auxiliary information were applied and are reflected in the survey weights provided with the data file. Extensive validations of survey estimates were also performed and examined from a bias analysis perspective. Despite these rigorous adjustments and validations, the high non-response increases the risk of a remaining bias and the magnitude with which such a bias could impact estimates produced using the survey data. Therefore, users are advised to use the CCHS 2020 data with caution, especially when creating estimates for small sub-populations or when comparing to other CCHS years.10 The content on material experiences was collected in New Brunswick, British Columbia and Nunavut for 2019/2020. This indicator is not available for the provinces or territories or Canada level for the 2019/2020 period.11 The confidence interval illustrates the degree of variability associated with a rate. Wide confidence intervals indicate high variability, thus, these rates should be interpreted with due caution. When comparing estimates, it is important to use confidence intervals to determine if differences between values are statistically significant.12 Bootstrapping techniques were used to produce the 95% confidence intervals (CIs).13 Data with a coefficient of variation (CV) from 15.1% to 35.0% are identified as follows: (E) use with caution.14 Data with a coefficient of variation (CV) greater than 35.0% or that did not meet the minimum sample size requirement were suppressed and are identified as follows: (F) too unreliable to be published.15 The following standard symbols are used in this Statistics Canada table: (..) for figures not available for a specific reference period and (...) for figures not applicable.16 Percentages are rounded to the nearest tenth. Numbers are rounded to the nearest hundred.17 Census population counts have been used to produce the population projection counts. These counts are used to ensure that the Canadian Community Health Survey (CCHS) weights and resulting estimates included in this table are consistent with known population totals.18 Population aged 12 and over who reported perceiving their own health status as being either excellent or very good or fair or poor, depending on the indicator. Perceived health refers to the perception of a person's health in general, either by the person himself or herself, or, in the case of proxy response, by the person responding. Health means not only the absence of disease or injury but also physical, mental and social well-being.19 Population aged 12 and over who reported perceiving their own mental health status as being excellent or very good or fair or poor, depending on the indicator. Perceived mental health refers to the perception of a person's mental health in general. Perceived mental health provides a general indication of the population suffering from some form of mental disorder, mental or emotional problems, or distress, not necessarily reflected in perceived health.20 Population aged 12 and over who reported perceiving that most days in their life were quite a bit or extremely stressful. Perceived life stress refers to the amount of stress in the person's life, on most days, as perceived by the person or, in the case of proxy response, by the person responding.21 Body mass index (BMI) is a method of classifying body weight according to health risk. According to the World Health Organization (WHO) and Health Canada guidelines, health risk levels are associated with each of the following BMI categories: normal weight = least health risk; underweight and overweight = increased health risk; obese, class I = high health risk; obese, class II = very high health risk; obese, class III = extremely high health risk.22 Body mass index (BMI) is calculated by dividing the respondent's body weight (in kilograms) by their height (in metres) squared.23 Body mass index (BMI) is calculated for the population aged 12 and over, excluding pregnant females and persons less than 3 feet (0.914 metres) tall or greater than 6 feet 11 inches (2.108 metres).24 According to the World Health Organization (WHO) and Health Canada guidelines, the index for body weight classification for the population aged 18 and older is: less than 18.50 (underweight); 18.50 to 24.99 (normal weight); 25.00 to 29.99 (overweight); 30.00 to 34.99 (obese, class I); 35.00 to 39.99 (obese, class II); 40.00 or greater (obese, class III). The population aged 12 to 17 is classified as severely obese"25 A systematic review of the literature concluded that the use of self-reported data among adults underestimates weight and overestimates height, resulting in lower estimates of obesity than those obtained from measured data. Using data from the 2005 Canadian Community Health Survey (CCHS) subsample, where both measured and self-reported height and weight were collected, BMI correction equations have been developed. This table presents obesity estimates adjusted using these equations.26 The Canadian Community Health Survey (CCHS) - Annual, the Canadian Health Measures Survey (CHMS) and the 2015 CCHS - Nutrition, all collect height and weight data and derive obesity rates based on Body Mass Index (BMI). Users should take note of the data collection method, the target population and the classification system used by each survey in order to select the appropriate data set.27 Population aged 15 and over who reported that they have been diagnosed by a health professional as having arthritis. Arthritis includes osteoarthritis and rheumatoid arthritis, but excludes fibromyalgia.28 Population aged 12 and over who reported that they have been diagnosed by a health professional as having Type 1 or Type 2 diabetes, including females 15 and over who reported that they have been diagnosed with gestational diabetes.29 Population aged 12 and over who reported that they have been diagnosed by a health professional as having asthma.30 Population aged 35 and over who reported being diagnosed by a health professional with chronic bronchitis, emphysema or chronic obstructive pulmonary disease (COPD).31 The Canadian Health Measures Survey (CHMS) and the Canadian Community Health Survey (CCHS) - Annual both collect data