Smoking frequency, prevalence and trends, and their socio-demographic associations in Alberta, Canada.
Li, Feng Xiao ; Robson, Paula J. ; Ashbury, Fredrick D. 等
Tobacco smoking is one of the most important yet preventable causes
of diseases and deaths in the world. (1-5) Despite substantial declines
over the past few decades in Canada, (6) one-fifth of Canadians still
smoked in 2006. (7) In 2007, the Canadian Federal Tobacco Control
Strategy set a new target to further reduce the smoking rate to 12% by
2011. (8) Although the strategy has been articulated at a federal level,
the provincial/territorial health authorities have an important role to
play in achieving this national goal.
In Alberta, regional health authorities (RHAs) have been
responsible for making and implementing local public health policies,
including those relevant to cigarette smoking. While there are data
describing the smoking trends in Alberta, (9) there is a paucity of
published information concerning the numbers of smokers, and smoking
prevalence and trends at the RHA level. Furthermore, the
socio-demographic factors that may be associated with smoking in Alberta
have not been examined.
The aims of this study were to determine the smoking frequency,
prevalence and trends at the RHA level, and to examine their
socio-demographic associations in Alberta. Such information will help
guide policy-makers in facilitating resource planning and in evaluating
the effectiveness of smoking control programs.
METHODS
Three Canadian Community Health Surveys (CCHS: Cycle 1.1, 2000/01;
Cycle 2.1, 2002/03; Cycle 3.1, 2004/05) were carried out by Statistics
Canada between 2000 and 2005. The surveys collected self-reported health
information from a representative sample of Canadians aged 12 years and
older, with the exclusion of the population on Indian reserves and
Canadian forces bases, in institutions and in some remote areas. The
three surveys were designed to provide reliable health estimates at the
RHA level across Canada. The sample sizes were, respectively, 130,880,
134,072 and 132,221 for Canada, and 14,456, 13,871 and 11,800 for
Alberta. The response rates ranged from 78.9% to 84.7% for Canada and
from 81.5% to 85.1% for Alberta. The survey methodology has been
published widely (6,10,11) and can also be found on the Statistics
Canada website. (12)
During CCHS 1.1, there were 17 RHAs in Alberta. The 17 RHAs were
collapsed into nine RHAs by Alberta Health and Wellness in 2003. To
facilitate comparisons over time, the 17 RHAs were regrouped into the
nine corresponding RHAs using a 2006 Postal Code Translation File
(prepared by Alberta Finance). This contains information on both postal
codes and RHA designations, and can be merged with the postal codes in
the CCHS 1.1 dataset to redefine the RHAs. To characterize the
urban/rural status of the nine RHAs, the 2006 Census urban/rural
population for Alberta census subdivisions13 was matched to the census
subdivisions of the nine RHAs in the Postal Code Translation File. An
urban area was defined by the Census as a minimum population of 1,000
and a population density of at least 400 persons/km2. On the basis of
this definition, the percent urban population (PUP) for the nine RHAs
ranged from 46% to 93%, with an average of 82%. A map outlining the 2008
RHA boundaries is presented in Figure 1.
In the CCHS surveys, a variable known as "type of smoker"
was derived. For the purposes of this analysis, respondents defined as
"current daily smokers" or "occasional smokers" were
combined into a single group (smokers), and all other respondents were
combined into a "non-smoker" group. The missing values (i.e.,
"don't know" or "refusal"), accounting for less
than 6% of the responses in each survey, were excluded from the
analysis. The respondents' sex, age, educational level, household
income and immigration status were also extracted to examine their
association with smoking.
The estimated numbers of smokers and smoking prevalence were first
determined by survey, sex and RHAs, and then by the sociodemographic and
urban/rural status of the population using the final and Bootstrap
weights. The final weight was used to adjust the sample into the
appropriate population distribution. The Bootstrap weight was used in
variance estimation to account for the complex sample design of the
surveys. The association between smoking and socio-demographic factors
was further examined using logistic regression. The likelihood ratio
test was used to retain the significant predictors of smoking by means
of backward elimination. For all significance tests performed, a p-value
of <0.05 was considered statistically significant. The analyses were
performed using SAS 9.1 (SAS Institute Inc., Cary, NC, US) and STATA 9.2
(Stata Corporation, College Station, TX, US).
[FIGURE 1 OMITTED]
RESULTS
Table 1 presents the smoking prevalence and numbers of smokers by
survey and sex for the nine RHAs and for the entire province of Alberta.
The smoking prevalence in the nine RHAs ranged from 18.5% to 36.1% among
men and from 15.5% to 32.5% among women during the 6-year period. Over
the three surveys, smoking was more prevalent among men than women in
Alberta as a whole. However, in each survey, the smoking prevalence
varied widely by RHA. In addition to the weighted prevalence, Table 1
also presents the estimated number of smokers in each RHA. While Calgary
ranked lowest or second lowest for smoking prevalence in each of the
three surveys for both men and women, the size of the smoking population
was much greater than in any of the other RHAs, with the exception of
Capital Health.
On the basis of the PUP, the nine RHAs were grouped into three
categories: major urban RHAs, including Calgary and Capital Health (PUP:
93%, 91%); minor urban RHAs, including Palliser, Northern Lights and
Chinook (PUP: 76%, 73%, 72%); and rural RHAs, including David Thompson,
Peace County, East Central and Aspen (PUP: 60%, 58%, 50%, 46%). The
weighted number of smokers and the prevalence were further
cross-tabulated against the socio-demographic variables and urban/rural
status of the three surveys (Table 2). As shown, both the smoking
prevalence and the number of smokers were higher among men than women,
in middle-aged groups (20-39 and 40-59 years) than in younger (12-19
years) and older (>60 years) groups, and among Canadian-born people
than immigrants to Canada. The smoking prevalence tended to 1) increase
with the increasing rurality of the RHAs, 2) decrease over the three
surveys, 3) be inversely proportional to educational level and 4) be
inversely proportional to household income. However, when examined in
terms of numbers of smokers in the three surveys, the smoking population
was the largest in the major urban RHAs and among those who reported the
highest educational achievement and highest household income.
The above associations were further examined using logistic
regression (Table 3). As shown, the odds of being a smoker were
significantly lower in women than men and about four times higher in
those aged 20-39 and 40-59 years than in those aged 12-19 years and 60
years or older. The odds of being a smoker in Canadian-born participants
were approximately twice as high as those observed in immigrants to
Canada. The odds of being a smoker increased with increasing rurality of
the RHAs and decreased with increasing educational level and household
income. The odds of being a smoker were significantly lower during the
second and third survey than during the first survey.
DISCUSSION
Tobacco smoking was essentially a male habit about half a century
ago (14) but became more common among women after World War II. (15) In
1965, the smoking prevalence among Canadian women aged 15 years and
older reached 38%, compared with 61% among men. (16) Over the past 30
years, tobacco use, especially among male Canadians, has decreased
significantly, so much so that in 2005 the smoking prevalence among
Canadian men and women aged 12 years and older was 24% and 20%,
respectively. (9) Smoking has been widely reported to be more prevalent
in the lower socio-economic classes, (17-19) and among Canadian-born
people than Canadian immigrants. (20) The socio-demographic
distributions of the smoking rates, as observed by this study, are
consistent with the previous findings.
Several Canadian studies have examined the urban/rural variation in
smoking rates. (21,22) According to Mitura and Bollman, (22) smoking
prevalence was significantly higher in small towns, rural areas and
northern regions of Canada. Our finding that smoking prevalence was
positively associated with the rurality of the RHAs is consistent with
these findings. It has been suggested that the differences may be
associated with the fewer smoking restrictions in rural areas. This may
be compounded by an over-representation of blue-collar jobs in rural
areas relative to urban areas. Previously, smoking rates among those
performing manual labour have been observed to be higher than those in
non-manual occupations. (23,24) Our finding of higher smoking rates in
the lower socio-economic groups does appear to support these findings.
(5,19)
It should be noted that we also observed a negative association
between the immigrant population and the rurality of the RHAs,
immigrants accounting for an average of 22%, 12% and 7% (data not shown)
of the population of the major urban, minor urban and rural RHAs,
respectively, during the six years. The proportionately greater
immigrant population in the urban RHAs may have contributed to the lower
smoking prevalence in those regions. However, this potential
contribution did not substantially change the urban/rural smoking
difference when immigration status was modelled as a covariate.
Studies from European countries have yielded different results with
respect to smoking prevalence in urban areas. (25,26) It has been
suggested that life in urban areas is more stressful than in rural
areas, (27,28) and this explains the higher smoking rate in urban areas.
According to a health behaviour model, people under stress are more
likely to engage in behaviours that are detrimental to their health.
(29) This model has been repeatedly supported by previous studies in the
context of low socio-economic class in relation to smoking. (30,31)
These results support our findings in the sense that the proportion of
Albertans with low socio-economic status was higher in rural areas than
in urban areas. For example, the per capita income and educational level
in rural Alberta was lower than in urban Alberta. (32,33) How much other
stressful events (e.g., stress at work or home) might contribute to the
urban/rural smoking difference in Alberta is not known and may be worth
further investigation.
Our finding that the smoking prevalence has been declining in
Alberta coincides with the smoking trends observed for all of Canada.
However, it should be noted that although the smoking prevalence among
men fell over time, the number of Alberta men defined as smokers did not
decrease substantially over time. Furthermore, in Capital Health,
although the smoking prevalence among men dropped from 30% to 28%, the
weighted number of smokers rose, because the number of smokers is a
function of both smoking prevalence and population size. These findings
illustrate that smoking prevalence should not be examined in isolation
from absolute numbers of smokers.
Alberta is currently establishing new tobacco legislation to
prevent initiation of tobacco use and to increase motivation to quit, by
increasing tobacco taxes, restricting smoking in public places and
prohibiting tobacco retail displays. (34) Although such strategies have
been shown to be effective in decreasing smoking prevalence in other
jurisdictions, (34,35) our findings suggest that additional strategies
may have to be employed if the numbers of smokers in the large urban
RHAs are to be reduced. Given that the smokers in these regions tend to
have higher income, it is conceivable that financial penalties
associated with the new tobacco legislation may have less impact in such
regions than in the regions of lower socioeconomic status. Smoking
control programs targeting these regions may lead to more effective
reduction of the smoking population and the overall smoking prevalence
in Alberta.
This study was conducted using data from three consecutive surveys
that had high response rates and consistent methodology, making the data
highly comparable across these surveys. Since the surveys depended on
respondents' self-report of their smoking status, a potential for
misclassification of information exists. Such misclassification, if it
exists, is likely to be consistent across the three surveys and should
have minimal impact on the smoking trends examined.
CONCLUSIONS
Although the new tobacco legislation being introduced in Alberta in
2009 may have a positive impact on smoking reduction, targeted
interventions tailored to the regions or groups with the largest numbers
of smokers may help further reduce the smoking population and the
overall smoking prevalence in Alberta.
Acknowledgements: We wish to express our gratitude to Statistics
Canada for granting our access to the Research Data Centre (RDC), where
this data analysis was conducted. We also thank Ms. Shirley Loh at the
RDC for her full support and assistance when the data analysis was
conducted.
The research and analysis are based on data from Statistics Canada,
and the opinions expressed do not represent the views of Statistics
Canada.
* See page 478 for a letter to the editor updating the information
in this article.
Received: March 9, 2009
Accepted: July 30, 2009
REFERENCES
(1.) Centers for Disease Control and Prevention. Annual
smoking-attributable mortality, years of potential life lost, and
economic costs: United States, 19951999. MMWR Morb Mortal Wkly Rep
2002;51(14):300-3.
(2.) Colditz GA, Samplin-Salgado M, Ryan CT, Dart H, Fisher L,
Tokuda A, et al; Harvard Center for Cancer Prevention. Harvard report on
cancer prevention, volume 5: Fulfilling the potential for cancer
prevention: policy approaches. Cancer Causes Control 2002;13(3):199-212.
(3.) World Health Organization. Tobacco or Health: A Global Status
Report. Geneva: WHO, 1997.
(4.) World Health Organization, International Agency for Research
on Cancer. Tobacco Smoke and Involuntary Smoking. Vol. 83. Oxford, UK:
WHO, 2002.
(5.) Health Canada. The National Strategy: Moving Forward--the 2005
Progress Report on Tobacco Control. 2005. Available at:
http://www.hc-sc.gc.ca/ hcps/pubs/tobac-tabac/foward-avant/index-eng.php
(Accessed June 5, 2009).
(6.) Stephens M, Siroonian J. Smoking prevalence, quit attempts and
successes. Health Rep 1998;9(4):31-37.
(7.) Health Canada. Canadian Tobacco Use Monitoring Survey (CTUMS).
2007. Available at: http://www.hc-sc.gc.ca/hc-ps/tobac-tabac/research-recherche/ stat/ctums-esutc_2007-eng.php (Accessed June 5, 2009).
(8.) Health Canada. Federal Tobacco Control Strategy. 2007.
Available at: http://www.hc-sc.gc.ca/hc-ps/tobac-tabac/about-apropos/role/federal/ strategeng.php (Accessed June 5, 2009).
(9.) Li FX, Robson PJ, Chen Y, Qiu Z, Lo Siou G, Bryant HE.
Prevalence, trend and sociodemographic association of five modifiable
lifestyle risk factors for cancer in Alberta and Canada. Cancer Causes
Control 2008;20(3):395-407.
(10.) Statistics Canada. Personal health practices: Smoking,
drinking, physical activity and weight. Health Rep 1999;11(3):83-90.
(11.) Shields M. The journey to quitting smoking. Health Rep
2005;16(3):19-36.
(12.) Statistics Canada. Population Health Surveys: National
Population Health Survey (NPHS); Canadian Community Health Survey
(CCHS). 2005. Available at: http://www.statcan.ca/english/
concepts/hs/index.htm (Accessed June 5, 2009).
(13.) Statistics Canada. Population Counts, for Canada, Provinces
and Territories, Census Divisions and Census Subdivisions
(Municipalities), by Urban and Rural, 2006 Census--100% Data. 2008.
Available at: http://www12.statcan.ca/
english/census06/data/popdwell/Table.cfm?
T=306&PR=48&S=0&O=A&RPP=25 (Accessed June 5, 2009).
(14.) Hammond EC, Garfinkel L. Smoking habits of men and women. J
Natl Cancer Inst 1961;27:419-42.
(15.) Harris JE. Cigarette smoking among successive birth cohorts
of men and women in the United States during 1900-80. J Natl Cancer Inst
1983;71:473 79.
(16.) Physicians for a Smoke-Free Canada. Smoking Prevalence
1965-2007. 2007. Available at:
http://www.smoke-free.ca/factsheets/pdf/prevalence.pdf (Accessed June 5,
2009).
(17.) Giskes K, Kunst AE, Benach J, Borrell C, Costa G, Dahl E, et
al. Trends in smoking behaviour between 1985 and 2000 in nine European
countries by education. J Epidemiol Community Health 2005;59(5):395-401.
(18.) Laaksonen M, Rahkonen O, Karvonen S, Lahelma E. Socioeconomic
status and smoking: Analysing inequalities with multiple indicators. Eur
J Public Health 2005;15(3):262-69.
(19.) Public Health Agency of Canada. The Chief Public Health
Officers' Report on the State of Public Health in Canada
2008--Social and Economic Factors that Influence Our Health and
Contribute to Health Inequalities. 2008. Available at:
http://www.phac-aspc.gc.ca/publicat/ 2008/cphorsphc-respcacsp/
cphorsphc-respcacsp07h-eng.php (Accessed June 5, 2009).
(20.) Dunn JR, Dyck I. Social determinants of health in
Canada's immigrant population: Results from the National Population
Health Survey. Soc Sci Med 2000;51:1573-93.
(21.) Canadian Institute for Health Information. Differences in
Health for Rural and Urban Canadians. 2006. Available at:
http://secure.cihi.ca/ cihiweb/dispPage.jsp?cw_page=media_19sep2006_e
(Accessed June 5, 2009).
(22.) Mitura V, Bollman RD. The health of rural Canadians: A
rural-urban comparison of health indicators. Rural and Small Town Canada
Analysis Bulletin 2003;4(6):1-23.
(23.) Krahn H, van Roosmalen E. Smoking policies and public
reaction in Alberta: An analysis of the 1990 Alberta survey. Ottawa, ON:
Health and Welfare Canada, 1991.
(24.) Health Canada. Restrictions on Workplace Smoking--Variations
in Workplace Smoking Restrictions. 2007. Available at:
http://www.hc-sc.gc.ca/ hcps/pubs/tobac-tabac/1996-work-travail/
part2_variations-eng.php (Accessed June 5, 2009).
(25.) Volzke H, Neuhauser H, Moebus S, Baumert J, Berger K, Stang
A, et al. Urban-rural disparities in smoking behaviour in Germany. BMC
Public Health 2006;6:146.
(26.) Idris BI, Giskes K, Borrell C, Benach J, Costa G, Federico B,
et al. Higher smoking prevalence in urban compared to non-urban areas:
Time trends in six European countries. Health Place 2007;13(3):702-12.
(27.) Shohaimi S, Luben R, Wareham N, Day N, Bingham S, Welch A, et
al. Residential area deprivation predicts smoking habit independently of
individual educational level and occupational social class. A cross
sectional study in the Norfolk cohort of the European Investigation into
Cancer (EPIC-Norfolk). J Epidemiol Community Health 2003;57(4):270-76.
(28.) Colby JP, Jr., Linsky AS, Straus MA. Social stress and
state-to-state differences in smoking and smoking related mortality in
the United States. Soc Sci Med 1994;38:373-81.
(29.) Redding CA, Rossi JS, Rossi SR, Velicer WF, Prochaska JO.
Health behavior models. Int Electron J Health Educ 2000;3(Special
Issue):180-93.
(30.) Fisher E, Musick J, Scott C, Miller JP, Gram R, Richardson V,
et al. Improving clinic- and neighborhood-based smoking cessation
services within federally qualified health centers serving low-income,
minority neighborhoods. Nicotine Tob Res 2005;7(Suppl 1):S45-S56.
(31.) Ritchie D, Parry O, Gnich W, Platt S. Issues of
participation, ownership and empowerment in a community development
programme: Tackling smoking in a low-income area in Scotland. Health
Promot Int 2004;19:51-59.
(32.) Alasia A. Rural and urban educational attainment: An
investigation of patterns and trends, 1981-1996. Rural and Small Town
Canada Analysis Bulletin 2003;4:1-24.
(33.) Singh V. The rural-urban income gap within provinces: An
update to 2000. Rural and Small Town Canada Analysis Bulletin
2004;5:1-20.
(34.) Alberta Cancer Board/Alberta Cancer Foundation. Briefing Note
Re: Evidence supporting tobacco control policies. 2007. Available at:
http://www.cancerboard.ab.ca/
NR/rdonlyres/7461AA2C-31EE-4D79-B362-4C6DACBB6066/0/Tobacco
BriefingNotesFinalFeb15.pdf (Accessed June 5, 2009).
(35.) Division of Population Health & Information, Alberta
Cancer Board. Snapshot of Tobacco Facts: A Resource to Guide Tobacco
Control Planning in Alberta. 2007. Available at:
http://www.cancerboard.ab.ca/NR/rdonlyres/
9AE60707AC51-4C61-8BA1-AAAA54778E2D/0/ACBSnapshot_Tobacco_electronic_Low
Res.pdf (Accessed June 5, 2009).
Feng Xiao Li, PhD, [1] Paula J. Robson, PhD, [2] Fredrick D.
Ashbury, PhD, [3,4] Juanita Hatcher, PhD, [1] Heather E. Bryant, MD, PhD
[5]
Author Affiliations
[1.] Surveillance, Health Promotion, Disease and Injury
Prevention--Cancer Bureau, Population and Public Health, Alberta Health
Services, Edmonton, AB
[2.] Population Health Research, Alberta Health Services--Cancer
Care, Edmonton, AB
[3.] PICEPS Consultants, Inc., Ajax, ON
[4.] Division of Preventive Oncology, Department of Oncology,
University of Calgary, AB
[5.] Canadian Partnership against Cancer, Toronto, ON
Correspondence: Feng Xiao Li, Surveillance, Health Promotion,
Disease and Injury Prevention--Cancer Bureau, Population and Public
Health, Alberta Health Services, 14th Floor, Sun Life Building, 10123 99
St, Edmonton, AB T5J 3H1, Tel: 780-643-4357, Fax: 780-643-4380, E-mail:
fengxiao.li@albertahealthservices.ca
Table 1. Numbers of Smokers and Smoking Prevalence by Survey,
Sex and Regional Health Authority, sorted by PUP *
2000/01
Men n n Prev (95% CI)
([dagger]) ([double ([section])
dagger])
Calgary 391 123,353 27.7 (24.7-30.7)
Capital 385 117,377 30.0 (26.4-33.5)
Palliser 115 11,376 29.3 (23.9-34.8)
Northern Lights 161 7627 34.0 (28.0-40.1)
Chinook 112 17,275 28.9 (22.8-35.0)
David Thompson 287 35,252 30.8 (26.7-35.0)
Peace County 250 16,915 32.5 (28.5-36.5)
East Central 136 16,920 36.1 (29.9-42.4)
Aspen 295 23,824 34.1 (29.5-38.7)
Alberta 2132 369,919 29.8 (28.1-31.5)
Women
Calgary 359 101,778 23.0 (20.5-25.5)
Capital 367 102,955 26.2 (22.7-29.6)
Palliser 109 10,731 26.9 (21.2-32.6)
Northern Lights 138 5913 29.3 (24.1-34.5)
Chinook 104 13,090 21.9 (17.6-26.2)
David Thompson 282 30,743 27.6 (24.5-30.6)
Peace County 234 14,701 30.7 (26.5-34.9)
East Central 132 15,190 32.5 (27.0-38.0)
Aspen 264 18,899 28.3 (24.6-32.1)
Alberta 1989 313,999 25.5 (24.0-27.0)
2002/03
Men n n Prev (95% CI)
([dagger]) ([double ([section])
dagger])
Calgary 304 107,013 22.6 (19.5-25.7)
Capital 329 98,374 24.1 (20.8-27.3)
Palliser 96 12,416 29.8 (22.2-37.3)
Northern Lights 130 8979 32.9 (27.0-38.7)
Chinook 92 15,261 24.9 (19.5-30.4)
David Thompson 249 34,144 28.1 (24.2-32.0)
Peace County 163 15,570 29.3 (23.6-34.9)
East Central 84 10,438 22.9 (17.0-28.9)
Aspen 223 20,475 30.0 (25.3-34.8)
Alberta 1670 322,670 24.8 (23.1-26.5)
Women
Calgary 298 84,198 18.1 (15.6-20.6)
Capital 326 91,239 22.3 (18.8-25.8)
Palliser 100 10,724 26.5 (21.1-31.9)
Northern Lights 106 6736 27.8 (22.6-33.1)
Chinook 77 9527 15.5 (11.1-20.0)
David Thompson 267 32,248 26.9 (23.2-30.5)
Peace County 152 10,295 20.7 (16.4-25.1)
East Central 91 10,315 22.6 (16.7-28.6)
Aspen 219 17,121 26.1 (21.9-30.2)
Alberta 1636 272,403 21.2 (19.7-22.8)
2004/05
Men n n Prev (95% CI) PUP *
([dagger]) ([double ([section])
dagger])
Calgary 312 110,582 22.2 (19.4-25.0) 93%
Capital 317 118,935 28.1 (24.4-31.8) 91%
Palliser 130 14,353 33.8 (28.3-39.2) 76%
Northern Lights 111 9513 32.6 (26.5-38.6) 73%
Chinook 103 11,389 18.5 (13.7-23.3) 72%
David Thompson 171 30,853 25.7 (21.7-29.6) 60%
Peace County 132 16,911 31.3 (25.5-37.0) 58%
East Central 109 13,136 27.6 (22.1-33.0) 50%
Aspen 127 18,858 27.2 (22.0-32.3) 46%
Alberta 1512 344,530 25.6 (23.9-27.3) 82%
Women
Calgary 262 86,876 17.6 (15.0-20.2) 93%
Capital 281 81,124 18.9 (16.1-21.7) 91%
Palliser 98 10,220 24.3 (18.4-30.1) 76%
Northern Lights 85 7132 28.1 (22.0-34.2) 73%
Chinook 132 13,220 21.6 (17.2-26.1) 72%
David Thompson 166 29,731 25.3 (20.8-29.8) 60%
Peace County 136 12,471 24.8 (18.5-31.1) 58%
East Central 98 10,195 22.0 (17.5-26.5) 50%
Aspen 120 15,497 23.5 (18.9-28.2) 46%
Alberta 1378 266,466 20.0 (18.6-21.4) 82%
* Percent urban population
([dagger]) Unweighted number of respondents who were
current daily or occasional smokers
([double dagger]) Weighted number of respondents who
were current daily or occasional smokers
[section]) Weighted prevalence in percent
(95% confidence interval)
Table 2. Numbers of Smokers and Smoking Prevalence by
Socio-demographic Factors, Survey and Urban/Rural Status
of the Regional Health Authorities
2000/01
Variable Category Major Urban
Sex Male 776 *
240,730
([dagger])
28.7 (26.3-31.1)
([double dagger])
Female 726
204,733
24.5 (22.3-26.6)
Age group 12-19 147
(years) 40,108
17.9 (14.7-21.0)
20-39 644
203,649
32.2 (29.4-34.9)
40-59 546
164,617
29.4 (26.5-32.3)
[greater than 165
or equal to] 60 37,089
14.4 (11.9-17.0)
Education <Secondary 381
level graduation 110,571
26.7 (24.0-29.4)
Secondary 338
graduation 104,538
33.8 (30.5-37.1)
Some post- 172
secondary 51,790
30.2 (25.2-35.2)
Post-secondary 593
graduation 174,192
22.8 (20.5-25.0)
Household <$30,000 346
income 79,991
31.9 (28.3-35.5)
$30,000- 288
$49,999 86,300
31.0 (27.4-34.5)
$50,000- 322
$79,999 104,383
27.3 (24.3-30.4)
[greater than 546
or equal to] 174,789
$80,000 22.9 (20.5-25.3)
Immigrant Yes 187
status 66,597
17.5 (14.7-20.3)
No 1296
371,750
29.3 (27.3-31.2)
2000/01
Variable Category Minor Urban Rural
Sex Male 388 968
36,278 92,911
30.0 (26.2-33.7) 32.8 (30.4-35.2)
Female 351 912
29,733 79,533
24.8 (21.8-27.8) 29.1 (27.3-31.0)
Age group 12-19 58 167
(years) 6887 15,491
18.9 (13.4-24.4) 18.3 (15.4-21.2)
20-39 341 812
30,106 81,689
34.3 (30.1-38.4) 40.9 (37.7-44.2)
40-59 285 684
24,308 59,403
32.6 (27.8-37.3) 33.4 (30.9-35.9)
[greater than 55 217
or equal to] 60 4710 15,861
11.3 (7.2-15.3) 16.9 (13.9-19.9)
Education <Secondary 216 648
level graduation 18,595 56,116
23.6 (19.9-27.4) 29.8 (27.2-32.5)
Secondary 150 397
graduation 14,519 38,225
31.0 (26.0-35.9) 36.1 (32.4-39.7)
Some post- 60 145
secondary 5865 15,558
29.1 (21.6-36.7) 36.1 (30.5-41.7)
Post-secondary 295 625
graduation 25,573 56,790
28.3 (25.1-31.5) 27.6 (25.3-29.8)
Household <$30,000 131 365
income 10,432 26,400
32.0 (26.8-37.1) 31.8 (27.9-35.7)
$30,000- 121 335
$49,999 11,386 30,325
27.2 (22.2-32.2) 33.5 (29.8-37.3)
$50,000- 156 425
$79,999 14,489 40,011
28.0 (22.8-33.1) 31.5 (28.3-34.7)
[greater than 331 755
or equal to] 29,704 75,707
$80,000 25.9 (22.4-29.5) 29.6 (27.1-32.1)
Immigrant Yes 54 83
status 4447 5984
15.3 (10.6-20.1) 15.9 (11.3-20.6)
No 680 1787
61,087 165,841
29.1 (26.1-32.0) 32.3 (30.5-34.1)
2002/03
Variable Category Major Urban Minor Urban
Sex Male 633 318
205,387 36,656
23.3 (21.0-25.6) 28.1 (24.2-32.1)
Female 624 283
175,437 26,987
20.0 (17.9-22.1) 21.4 (18.3-24.5)
Age group 12-19 109 67
(years) 27,960 6552
12.2 (8.8-15.6) 17.0 (12.4-21.7)
20-39 552 253
184,615 26,211
27.8 (24.9-30.7) 28.3 (23.9-32.6)
40-59 439 217
133,600 25,655
22.5 (19.6-25.5) 31.0 (26.2-35.9)
[greater than 157 64
or equal to] 60 34,562 5225
12.8 (10.1-15.4) 12.3 (9.2-15.4)
Education <Secondary 262 166
level graduation 71,188 16,773
20.0 (16.6-23.3) 21.8 (18.1-25.6)
Secondary 303 154
graduation 92,284 17,067
28.9 (25.0-32.8) 34.9 (29.0-40.8)
Some post- 137 67
secondary 47,088 7025
28.9 (22.9-34.8) 26.5 (18.4-34.7)
Post-secondary 521 198
graduation 156,790 20,704
17.9 (15.8-20.0) 20.9 (17.4-24.5)
Household <$30,000 224 97
income 44,101 8084
26.5 (22.0-31.1) 29.0 (22.2-35.5)
$30,000- 238 71
$49,999 57,237 7216
26.6 (22.5-30.7) 24.3 (17.9-30.7)
$50,000- 279 95
$79,999 82,740 10,419
23.0 (19.8-26.1) 23.0 (16.5-29.5)
[greater than 516 338
or equal to] 196,746 37,924
$80,000 19.4 (17.3-21.5) 24.7 (21.7-27.8)
Immigrant Yes 159 50
status 57,283 7229
15.0 (11.8-18.3) 21.9 (14.3-29.5)
No 1088 530
321,007 54,599
23.7 (22.0-25.4) 25.4 (22.6-28.2)
2002/03 2004/05
Variable Category Rural Major Urban
Sex Male 719 629
80,627 229,517
27.9 (25.6-30.3) 24.9 (22.6-27.2)
Female 729 543
69,979 168,001
24.9 (22.7-27.1) 18.2 (16.4-20.1)
Age group 12-19 168 73
(years) 15,026 25,328
17.1 (13.8-20.5) 10.7 (7.7-13.6)
20-39 540 511
66,793 180,336
34.7 (31.6-37.8) 27.0 (24.5-29.5)
40-59 536 426
54,475 154,408
28.9 (25.9-32.0) 23.9 (20.9-26.8)
[greater than 204 162
or equal to] 60 14,399 37,446
14.2 (11.9-16.5) 12.8 (10.4-15.3)
Education <Secondary 490 250
level graduation 47,461 83,999
26.0 (23.4-28.5) 22.9 (19.7-26.2)
Secondary 144 242
graduation 35,907 80,731
31.9 (28.2-35.6) 28.4 (24.5-32.4)
Some post- 101 121
secondary 13,783 40,891
31.7 (24.8-38.5) 26.0 (21.2-30.8)
Post-secondary 471 539
graduation 47,924 184,525
22.3 (19.9-24.7) 18.5 (16.5-20.5)
Household <$30,000 252 250
income 20,970 50,896
30.3 (26.2-34.4) 30.4 (25.9-35.0)
$30,000- 207 204
$49,999 19,052 50,953
27.6 (23.4-31.9) 24.5 (20.4-28.6)
$50,000- 276 209
$79,999 31,684 76,534
29.3 (25.2-33.5) 23.5 (19.8-27.2)
>$80,000 713 509
78,900 219,135
24.4 (22.3-26.5) 19.2 (17.3-21.1)
Immigrant Yes 63 161
status 7401 55,296
19.9 (13.8-26.1) 14.4 (11.7-17.1)
No 1353 996
140,086 336,351
26.8 (25.1-28.5) 23.5 (21.7-25.3)
2004/05
Variable Category Minor Urban Rural
Sex Male 344 539
35,255 79,758
26.5 (23.3-29.6) 27.4 (24.7-30.0)
Female 315 520
30,572 67,894
23.8 (20.7-26.9) 24.2 (21.8-26.7)
Age group 12-19 59 66
(years) 5693 8179
15.6 (11.4-19.8) 9.6 (7.1-12.2)
20-39 276 433
30,158 63,024
32.9 (28.9-36.9) 33.8 (30.3-37.3)
40-59 245 396
24,778 61,207
28.1 (24.1-32.2) 30.7 (26.9-34.5)
[greater than 79 164
or equal to] 60 5197 15,243
11.4 (8.6-14.3) 15.1 (12.5-17.8)
Education <Secondary 162 274
level graduation 15,980 34,348
24.5 (20.5-28.6) 21.8 (18.8-24.8)
Secondary 144 225
graduation 15,386 35,913
33.5 (27.8-39.1) 35.9 (30.5-41.3)
Some post- 57 80
secondary 5876 10,917
23.6 (16.7-30.4) 22.8 (16.6-28.9)
Post-secondary 280 454
graduation 26,996 62,409
22.4 (19.3-25.4) 24.5 (21.9-27.1)
Household <$30,000 116 195
income 7907 19,867
27.2 (21.9-32.5) 32.9 (27.9-38.0)
$30,000- 76 156
$49,999 7347 19,736
26.9 (20.7-33.2) 30.1 (25.1-35.0)
$50,000- 116 192
$79,999 12,116 28,635
23.8 (18.6-29.0) 29.0 (24.5-33.5)
[greater than 351 516
or equal to] 38,457 79,413
$80,000 24.9 (21.9-27.9) 22.9 (20.6-25.2)
Immigrant Yes 48 47
status 4776 6385
16.1 (10.5-21.7) 18.0 (11.3-24.8)
No 599 993
59,833 138,057
26.2 (23.9-28.6) 26.2 (24.3-28.1)
* Unweighted number of respondents who were current
daily or occasional smokers
([dagger]) Weighted number of respondents who were
current daily or occasional smokers
([double dagger]) Weighted prevalence in percent
(95% confidence interval)
Table 3. Socio-demographic Predictors of Smoking in
Alberta--Final Weighted Logistic Regression Model
Variable Category n * n ([dagger])
Sex Male 5128 1,037,119
Female 4842 852,869
Age group 12-19 898 151,224
(years) 20-39 4219 866,581
40-59 3643 702,451
[greater than 1210 169,732
or equal to]
60
Urban/rural Major urban RHAs 3831 1,223,805
RHAs Minor urban RHAs 1922 195,481
([section]) Rural RHAs 4217 470,702
Education <Secondary 2816 455,031
level school
graduation
Secondary 2276 434,570
school
graduation
Some 932 198,793
post-secondary
school
Post-secondary 3946 755,903
school
graduation
Household <$30,000 1945 268,648
income $30,000-$49,999 1679 289,552
$50,000-$79,999 2045 401,011
[greater than 4301 930,775
or equal to]
80,000
Immigration Immigrant 836 215,398
status Canadian-born 9134 1,648,611
Year of 2001/02 3986 683,918
survey 2003/04 3158 595,073
2005/06 2826 610,997
Variable Category OR (95 CI) p Value
([double dagger])
Sex Male Ref
Female 0.84 (0.80-0.88) <0.001
Age group 12-19 Ref
(years) 20-39 4.09 (3.73-4.49) <0.001
40-59 3.62 (3.30-3.97) <0.001
[greater than 1.08 (0.98-1.19) 0.14
or equal to]
60
Urban/rural Major urban RHAs Ref
RHAs Minor urban RHAs 1.03 (0.97-1.10) 0.319
([section]) Rural RHAs 1.06 (1.00-1.11) 0.038
Education <Secondary Ref
level school
graduation
Secondary 0.90 (0.84-0.97) 0.006
school
graduation
Some 0.69 (0.62-0.75) <0.001
post-secondary
school
Post-secondary 0.50 (0.47-0.54) <0.001
school
graduation
Household <$30,000 Ref
income $30,000-$49,999 0.82 (0.75-0.89) <0.001
$50,000-$79,999 0.65 (0.60-0.70) <0.001
[greater than 0.60 (0.57-0.65) <0.001
or equal to]
80,000
Immigration Immigrant Ref
status Canadian-born 2.08 (1.92-2.25) <0.001
Year of 2001/02 Ref
survey 2003/04 0.82 (0.77-0.86) <0.001
2005/06 0.88 (0.83-0.93) <0.001
* Unweighted number of smokers of the three surveys
([dagger]) Weighted number of smokers of the three surveys
([double dagger]) Odds ratio (95% confidence interval)
([section]) Regional health authorities