Chronic Diseases and Injuries in Canada Inside this issue

Chronic Diseases and Injuries in Canada Inside this issue
Chronic Diseases and
Injuries in Canada
Volume 32 · Number 4 · September 2012
Inside this issue
177 Distribution of human papillomavirus types, cervical cancer
screening history, and risk factors for infection in Manitoba
186 Features of physician services databases in Canada
194 Using national surveys for mental health surveillance
of individuals with intellectual disabilities in Canada
200 Cardiovascular disease mortality among First Nations people
in Canada, 1991–2001
208 Income disparities in life expectancy in the City of Toronto
and Region of Peel, Ontario
216 Prevalence of meeting physical activity guidelines for cancer
prevention in Alberta
227 National Fall Prevention Workshop: stepping up pan-Canadian
coordination
229 Report summary: Injury in Review, 2012 Edition – Spotlight
on Road and Transport Safety
Chronic Diseases and Injuries in Canada
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University of Calgary
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Associate Scientific Editor
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Isra Levy, MB, FRCPC, FACPM
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Centers for Disease Control and Prevention
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Public Health Agency of Canada
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Assistant Managing Editor
University of Ottawa
Ania Syrowatka, MSc
McGill University
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Public Health Agency of Canada
Russell Wilkins, MUrb
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Distribution of human papillomavirus types, cervical
cancer screening history, and risk factors for infection
in Manitoba
A. A. Demers, PhD (1,2,3); B. Shearer, PhD (4); A. Severini, MD (5); R. Lotocki, MD, FRCSC (6,7);
E. V. Kliewer, PhD (2,3,8); S. Stopera, MSc (9); T. Wong, MD, FRCPC (1,10); G. Jayaraman, PhD (1,11)
This article has been peer reviewed.
Abstract
Introduction
Objectives: We conducted a study to investigate the prevalence of human papillomavirus
(HPV) infections in an opportunistic sample of women in Manitoba, Canada. We inquired
about risk factors associated with HPV infections and linked the HPV typing results
with the cervical cancer screening history of the participants.
The publicly funded human papillomavirus
(HPV) immunization programs implemented
across Canada between 2007 and 2009 have
the potential to prevent a large proportion of
anogenital warts, high-grade cervical lesions
and HPV-related invasive cancers.1-6 They
also have the potential to influence cervical
cancer screening as currently practiced
because of the changes in prevalence of
cervical abnormalities they can bring about.1,7
The extent of this impact, however, will
depend on the distribution of HPV types,
the type-specific infection rates among
females and the vaccine uptake.
Methods: The study population included 592 women attending Papanicolaou (Pap) test
clinics. After signing a consent form, participants were given a self-administered
questionnaire on risk factors and received a conventional Pap test. Residual cells from
the Pap tests were collected and sent for HPV typing.
Results: The mean age of the population was 43 years. A total of 115 participants
(19.4%) had an HPV infection, 89 of whom had a normal Pap test. Of those who were
HPV-positive, 61 (10.3%) had high-risk (Group 1) HPV. HPV-16 was the most prevalent
type (15/115: 13.0% of infections). The most consistent risk factors for HPV infection
were young age, Aboriginal ethnicity, higher lifetime number of sexual partners and
higher number of sexual partners in the previous year.
Conclusion: The prevalence of HPV types in Manitoba is consistent with the distributions
reported in other jurisdictions. These data provide baseline information on type-specific
HPV prevalence in an unvaccinated population and can be useful in evaluating the
effectiveness of the HPV immunization program. An added benefit is in the validation
of a proof of concept which links a population-based Pap registry to laboratory test
results and a risk behaviour survey to assess early and late outcomes of HPV infection.
This methodology could be applied to other jurisdictions across Canada where such
capacities exist.
Keywords: papillomavirus infections, prevalence, risk factors, uterine cervical dysplasia,
early detection of cancer
The objective of this study was to determine
the baseline type-specific prevalence of
and risk factor for HPV infection in an
opportunistic sample of women attending
walk-in, no-appointment Papanicolaou (Pap)
test clinics in Manitoba (Canada) during
an annual cervical cancer awareness week.
The survey information and HPV typing
results were linked to the Manitoba Cervical
Cancer Screening Program (MCCSP) database. Manitoba is well positioned to host and
conduct this kind of surveillance projects
because of the availability of linkable
population-based databases on cancer,
Author references:
1. Centre for Communicable Diseases and Infection Control, Public Health Agency of Canada, Ottawa, Ontario, Canada
2. Department of Epidemiology and Cancer Registry, CancerCare Manitoba, Winnipeg, Manitoba, Canada
3. Department of Community Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
4. International Centre for Infectious Diseases, Winnipeg, Manitoba, Canada
5. National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, Manitoba, Canada
6. Gynecological Oncology, CancerCare Manitoba, Winnipeg, Manitoba, Canada
7. Manitoba Cervical Cancer Screening Program, Manitoba, Canada
8. Cancer Control Research, British Columbia Cancer Agency, Vancouver, British Columbia, Canada
9. Communicable Disease Control Branch, Public Health and Primary Health Care, Manitoba Health, Winnipeg, Manitoba, Canada
10. Department of Infectious Diseases, University of Ottawa, Ottawa, Ontario, Canada
11. Department of Epidemiology and Community Medicine, University of Ottawa, Ottawa, Ontario, Canada
Correspondence: Alain Demers, Centre for Communicable Diseases and Infection Control, Public Health Agency of Canada, 100 Eglantine Driveway, Tunney’s Pasture, AL 0602C, Ottawa, ON
K1A 0K9; Tel.: (613) 948-8247; Fax: (613) 941-9813; Email: alain.demers@phac-aspc.gc.ca
177
Vol 32, No 4, September 2012 – Chronic Diseases and Injuries in Canada
cervical screening, medical procedures
provided by physicians and immunization.8
These resources provide a robust
environment to evaluate the impact of the
HPV immunization program impact, the
utilization of cervical screening among
vaccinated and non-vaccinated females,
and the resulting disease distribution and
outcomes.
Methods
Study environment
Since 2003 the MCCSP has conducted an
annual Pap Week in October. During this
week women are encouraged to attend
Pap test clinics without appointment. The
objective is to reach those who have
never attended or do not regularly attend
cervical screening. In 2008, 123 clinics
participated in Pap Week across Manitoba.
Of these, 52 consented to take part in this
study. In addition to performing conventional Pap tests, these clinics took the
residual cells from the Pap tests, put them
in a liquid-based cytology medium, and
sent the samples to Cadham Provincial
Laboratory in Winnipeg, Manitoba, for
HPV typing. The participating clinics also
supervised the administration of a consent
form and a self-administered survey on
risk factors for HPV infections.
Population
The study population was composed of
an opportunistic sample of women aged
18 years and older from different ethnic
backgrounds. Pregnant women were
excluded. Women interested in participating
in the study discussed the objectives with
clinic staff and, upon agreement, signed a
consent form and completed a risk factor
questionnaire. Women who decided not
to complete the questionnaire were still
eligible for HPV testing, and their HPV
results were included in the analysis.
The study was publicized on posters in the
clinics, and staff told potential participants
about it. Overall, 1182 women underwent
cervical screening in the 52 participating
clinics, and 642 (54%) consented to
participate in the study.
Follow-up of participants
Health care providers received the Pap test
results and the HPV typing results. Medical
management of participants diagnosed with
cervical abnormalities followed the MCCSP
cervical cancer screening management
guidelines in effect at the time of the
study. Women who tested positive for
high-risk HPV and negative for cytology
were recalled by the clinics for further
investigation according to the MCCSP
guidelines.
Risk factor survey
The survey included questions on socio­
demographic characteristics and relevant
risk factors for cervical neoplasia including
smoking, oral contraceptive use, recent
sexual activity, previous diagnosis with
sexually transmitted infections and HPV
immunization status. The questionnaire
was tested to a grade four reading level
before use.
Cervical specimen processing and HPV
detection and typing
The Luminex assay is a method developed
at the National Microbiology Laboratory
that detects 45 HPV types. These include
23 of the 25 high-risk (as defined by the
International Agency for Research on
Cancer) types found in groups 1, 2a and
2b: HPV types 16, 18, 26, 30, 31, 33, 35,
39, 45, 51, 52, 53, 56, 58, 59, 66, 67, 68,
69, 70, 73, 82 and 85.9 Also included
are 22 types considered of low risk or
unknown risk: HPV types 6, 11, 13, 32,
40, 42, 43, 44, 54, 61, 62, 71, 72, 74, 81,
83, 84, 86, 87, 89, 90 and 91. In brief,
samples in viral transport medium were
centrifuged and their DNA extracted from
the resulting pellet using a MagnaZorb
DNA extraction kit.10,11 The DNA was
amplified with a nested polymerase chain
reaction (PCR) method using the general
PGMY primer set for the first round12
and the GP5+/GP6+ primer set for
the second.13 This method amplifies a
fragment of the L1 region of the HPV
genome (about 150 base pairs in length).
The quality of the DNA sample for
PCR was checked by co-amplification
*http://www.luminexcorp.com/
Vol 32, No 4, September 2012 – Chronic Diseases and Injuries in Canada
178
of the human beta-globin gene. PCR
products were visually detected by gel
electrophoresis.13-16
HPV DNA was detected and typed
by hybridization to microspheres coupled
to specific probes for the 45 HPV
types according to the xMAP Luminex
technology*. Specificity and sensitivity of
this method for all the 45 types of HPV
was measured using cloned HPV DNAs.
Comparison against the LinearArray
(Roche)17 and other HPV genotyping
kits showed that this Luminex assay is
comparable to other commercial genotyping
methods.18
Data analysis
HPV typing results and survey results
were linked to the MCCSP database using
a unique identifier in order to get the
results of the Pap tests performed during
Pap Week 2008 and the cervical cancer
screening history of the consenting participants. Univariate and multivariate logistic
regression analyses was used to calculate
odds ratios (ORs) and 95% confidence
intervals (CIs) as estimates of the relative
risk of HPV detection associated with the
various predictor variables. Because of the
higher prevalence of HPV in women aged
less than 30 years, results were tabulated
for women aged less than 30 years and for
those aged 30 years plus. HPV types were
grouped according to Bouvard et al. and
de Villiers et al.9,19
The protocol was approved by the
research ethics boards of Health Canada/
Public Health Agency of Canada and the
University of Manitoba.
Results
Tissue samples collected from the
642 women who consented to participate
in the study were sent for HPV infection
testing. Of these, 33 women did not
complete the consent form and were
excluded from the analyses. A further
17 were excluded because of inadequate
samples. The final study population
included 592 participants, of which
527 completed the questionnaire. The
mean age of the study population was
43 years (median: 44). The mean age of
infected women was 35 years (median:
31 years), and the mean age of noninfected women was 45 years (median:
46 years). The majority of participants came
from rural areas (66.3%), and the remainder
came from Winnipeg and Brandon.
Survey results
reflect the higher prevalence of HPV infections in younger women. In older women,
HPV infection was associated with
Aboriginal ethnicity and a self-described
difficult financial situation. Compared with
non-smokers, participants who smoked
were at greater risk of being HPV-positive,
regardless of age. Not having a history of
Variables associated with the HPV infection using univariate analysis are reported
in Table 1. Results are presented for
women aged less than 30 years (referred
to as “younger”) and for women aged 30
years and older (referred to as “older”) to
Table 1
Survey results by age and HPV infection status
Variablesa
Categories
Age < 30 years
HPV−(n = 75)
n
Ethnic identity
19 (33.9)
Caucasian
38 (50.7)
24 (42.9)
Other
10 (13.3)
Difficult
32 (42.7)
25 (44.6)
2
Reference
(3.6)
0.3 (0.1, 1.4)
1.4 (0.5, 4.0)
9 (12.0)
10 (17.9)
High school or less
28 (37.3)
19 (33.9)
College
14 (18.7)
8 (14.3)
University
25 (33.3)
19 (33.9)
19
5
(8.5)
(0.7, 5.8)
2.5 (1.1, 5.6)
3.3 (1.2, 9.4)
(4.7)
6 (10.2)
18 (30.5)
201 (50.0)
19 (32.2)
(8.0)
Reference
2.0
10 (16.9)
110 (27.4)
32
3.3 (1.7, 6.4)
5
(8.5)
1.7
(0.9, 3.4)
Reference
1.7
(0.6, 4.7)
2.9 (1.3, 6.5)
40 (10.0)
11 (18.6)
139 (34.6)
18 (30.5)
0.8 (0.3, 2.4)
114 (28.4)
15 (25.4)
1.0
(0.5, 2.1)
1.1 (0.5, 2.6)
110 (27.4)
16 (27.1)
1.1
(0.5, 2.3)
(0.8, 4.6)
Reference
8 (10.7)
10 (17.9)
1.8 (0.6, 5.5)
(9.7)
10 (16.9)
2.0
21 (28.0)
23 (41.1)
2.5 (1.1, 5.7)
101 (25.1)
24 (40.7)
2.5 (1.3, 5.0)
(9.3)
6 (10.7)
2.0 (0.6, 6.7)
103 (25.6)
11 (18.6)
1.1
39 (52.0)
17 (30.4)
Reference
159 (39.6)
15 (25.4)
Reference
7
39
Reference
(0.5, 2.6)
8 (10.7)
10 (17.9)
2.9 (1.0, 8.5)
39
(9.7)
9 (15.3)
2.5 (1.0, 6.0)
Yes
24 (32.0)
15 (26.8)
0.7 (0.3, 1.6)
18
(4.5)
3
1.3
No
31 (41.3)
27 (48.2)
Don’t know
2
(2.7)
1
(1.8)
Not stated
18 (24.0)
13 (23.2)
Yes
47 (62.7)
41 (73.2)
No
20 (26.7)
(0.0)
17 (28.8)
46 (78.0)
1.4
(0.8, 2.7)
Reference
(1.7)
2
(3.4)
(0.0)
2
(3.4)
—
38
(9.5)
9 (15.3)
1.8
Reference
55 (13.7)
15 (25.4)
Reference
0.4 (0.2, 0.9)
286 (71.1)
29 (49.2)
0.4 (0.2, 0.7)
No
52 (69.3)
24 (42.9)
Don’t know
0
Not stated
8 (10.7)
10 (17.9)
None
44 (58.7)
29 (51.8)
1
10 (13.3)
(5.3)
91 (22.6)
357 (88.8)
—
7
18 (32.1)
4
(1.7)
0
15 (20.0)
10 (13.3)
1
—
Yes
≥3
Reference
(0.2)
0.3 (0.1, 0.8)
10 (17.9)
Not stated
0.8 (0.3, 2.0)
1
(0.4, 4.6)
Reference
(8.9)
8 (10.7)
(9.3)
—
38 (64.4)
(0.0)
Not stated
7
292 (72.6)
5
0
(0.0)
Reference
(5.1)
0
Don’t know
2
Number of sexual partners
over last year
42 (10.4)
Comfortable
Not stated
Number of children
1.8 (0.6, 5.0)
1.3 (0.3, 4.9)
Former smoker
Ever had an STI
10 (17.9)
0.9 (0.4, 2.1)
Yes
26 (44.1)
(6.5)
OR (95% CI)
%
276 (68.7)
26
5
n
18 (30.5)
0.5 (0.1, 1.9)
(8.9)
9 (12.0)
%
HPV+ (n = 59)
58 (14.4)
(5.4)
14 (25.0)
Never
Ever had a Pap test
(6.7)
Reference
20 (26.7)
Not stated
Currently use oral
contraceptive
5
HPV−(n = 402)
n
1.7 (0.7, 3.8)
Moderate
Not stated
Currently smoking
9 (12.0)
3
Age ≥ 30 years
OR (95% CI)
%
18 (24.0)
Very comfortable
Education
n
Aboriginal
Not stated
Financial situation
%
HPV+ (n = 56)
4
(7.1)
1.4 (0.5, 4.0)
—
1.0 (0.3, 3.3)
Reference
20
(5.0)
6 (10.2)
41 (10.2)
9 (15.3)
48 (11.9)
10 (16.9)
33
2.2 (0.4, 11.0)
(0.8, 4.0)
—
0.8
(0.3, 2.0)
Reference
9 (16.1)
1.4 (0.5, 3.8)
(8.2)
10 (16.9)
5
(8.9)
1.1 (0.3, 3.7)
113 (28.1)
9 (15.3)
2
(3.6)
0.8 (0.1, 4.4)
167 (41.5)
21 (35.6)
0.6
(0.3, 1.4)
11 (19.6)
1.7 (0.6, 4.4)
41 (10.2)
9 (15.3)
1.1
(0.4, 2.8)
11 (18.6)
1.4
0
7
(9.3)
2
(3.6)
> 0b
0
(0.0)
1
(1.8)
0.7 (0.1, 3.8)
74
(18.4)
—
7
(1.7)
1
1.5
(0.5, 3.9)
0.4 (0.2, 1.0)
(1.7)
(0.7, 2.9)
—
1
48 (64.0)
19 (33.9)
Reference
280
(69.7)
30 (50.8)
Reference
2 or more
15 (20.0)
26 (46.4)
4.4 (1.9, 10.0)
12
(3.0)
11 (18.6)
8.6 (3.5, 21.1)
8 (14.3)
4.0 (1.2, 13.9)
29
(7.2)
Not stated
5
(6.7)
6 (10.2)
1.9
(0.7, 5.0)
Continued on the following page
179
Vol 32, No 4, September 2012 – Chronic Diseases and Injuries in Canada
Table 1 (continued)
Survey results by age and HPV infection status
Variablesa
Categories
Age < 30 years
HPV−(n = 75)
n
Lifetime number
of sexual partners
Currently in a stable
relationship
Total number of Pap testsc
6
(8.0)
2
(3.6)
(6.7)
1
(1.8)
1–4
36 (48.0)
12 (21.4)
≥5
24 (32.0)
33 (58.9)
4
(5.3)
8 (14.3)
Yes
14 (18.7)
10 (17.9)
No
52 (69.3)
35 (62.5)
Don’t know
0
(0.0)
Not stated
9 (12.0)
1
10 (17.9)
Yes
54 (72.0)
23 (41.1)
11 (14.7)
19 (33.9)
1.0
(0.2, 5.6)
—
Reference
4.1
(1.8, 9.5)
%
HPV+ (n = 59)
n
OR (95% CI)
%
12
(3.0)
3
(5.1)
3.3 (0.9, 13.0)
23
(5.7)
4
(6.8)
—
227 (56.5)
17 (28.8)
Reference
111 (27.6)
28 (47.5)
3.4 (1.8, 6.4)
6.0 (1.5, 23.5)
29
(7.2)
7 (11.9)
3.2 (1.2, 8.4)
0.9
38
(9.5)
7 (11.9)
0.8 (0.3, 1.8)
307 (76.4)
43 (72.9)
Reference
(0.4, 2.4)
Reference
—
1.6
(0.5, 5.2)
Reference
4.1 (1.7, 9.9)
(7.1)
—
3
(0.7)
54 (13.4)
0
(0.0)
9 (15.3)
—
0.9 (0.3, 2.6)
289 (71.9)
35 (59.3)
Reference
64 (15.9)
12 (20.3)
1.5 (0.8, 3.1)
Not sure
1
Not stated
9 (12.0)
10 (17.9)
2.6
(0.9, 7.3)
45 (11.2)
9 (15.3)
1.7 (0.7, 3.7)
22 (29.3)
14 (25.0)
0.8
(0.3, 1.8)
43 (10.7)
11 (18.6)
2.1 (1.0, 4.5)
0
4
HPV−(n = 402)
n
(1.8)
No
(1.3)
OR (95% CI)
%
5
1–4
30 (40.0)
25 (44.6)
5+
23 (30.7)
17 (30.4)
64 (85.3)
49 (87.5)
11 (14.7)
7 (12.5)
0.8
(0.3, 2.3)
1.0
(0.5, 2.4)
1+
Worst histologyc
n
0
Total number of colposcopiesc 0
Worst cytologyc
HPV+ (n = 56)
> 0b
Not stated
Had unprotected anal sex
over last year
%
Age ≥ 30 years
No history
22 (29.3)
14 (25.0)
Normal
42 (56.0)
26 (46.4)
Other than normal
11 (14.7)
16 (28.6)
No history
64 (85.3)
49 (87.5)
Reference
0.9
(0.4, 2.0)
Reference
Reference
2.4
(0.9, 5.8)
Reference
4
(1.0)
3
(5.1)
—
270 (67.2)
33 (55.9)
Reference
89 (22.1)
15 (25.4)
1.4 (0.7, 2.7)
379 (94.3)
55 (93.2)
23
4
Reference
(6.8)
1.2 (0.4, 3.6)
43 (10.7)
11 (18.6)
2.0 (1.0, 4.3)
323 (80.3)
40 (67.8)
Reference
(9.0)
8 (13.6)
1.8 (0.8, 4.1)
379 (94.3)
55 (93.2)
36
(5.7)
Reference
Normal
3
(4.0)
2
(3.6)
0.9
(0.1, 5.4)
12
(3.0)
1
(1.7)
0.6 (0.1, 4.5)
Other than normal
8 (10.7)
5
(8.9)
0.8
(0.3, 2.7)
11
(2.7)
3
(5.1)
1.9 (0.5, 6.9)
Abbreviations: ASC-H, atypical squamous cells–cannot rule out high-grade lesion; ASC-US, atypical squamous cells of unknown significance; CI, confidence interval;
CIN, cervical intraepithelial neoplasia; HPV, human papillomavirus; HPV−, HPV-negative; HPV+, HPV-positive; HSIL, high-grade squamous intraepithelial lesions;
LSIL, low-grade squamous intraepithelial lesions; OR, odds ratio; Pap, Papanicolaou; STI, sexually transmitted infection.
Note: Bolded values are significant.
a
Variables are all self-reported.
b
c
Value obtained by combining information on the number of children and sexual activity questions.
Manitoba Cervical Cancer Screening Program data; other cytology: ASC-US, LSIL, ASC-H, HSIL; other histology: CIN I, CIN II, CIN III; all the other variables are self-reported by the participants.
sexually transmitted infections (STIs) was
protective for HPV infection for both age
groups. Women with a higher number of
lifetime sexual partners or a higher number
of sexual partners over the previous year
were more likely to be HPV-positive.
Younger women who were not in a
stable relationship were more likely to
be HPV-positive than those in a stable
relationship or older women.
(OR = 2.04; 95% CI: 1.20–3.47 compared to
one or no sexual partner) were significant
predictors for testing HPV-positive. The
variables that were not significant predictors
of HPV infection in the multivariate
model were currently smoking (yes/no),
Pap test history (yes/no), history of
cervical abnormality (yes/no) and having
had at least two consecutive screening
events within a year (yes/no).
In the multivariate logistic regression
analysis, being younger (OR = 0.97;
95% CI: 0.95–0.99; age was treated
as a continuous variable), Aboriginal
(OR = 4.83; 95% CI: 2.70–8.65; compared
to non-Aboriginal), and having two or
more sexual partners in the previous year
Reported and registry-based Pap test history
Older women who had had zero Pap
tests between 2001 (the year the MCCSP
database was started) and October 2008
were at higher risk of being HPV-positive
(Table 1; data from the MCCSP). A similar
Vol 32, No 4, September 2012 – Chronic Diseases and Injuries in Canada
180
trend was observed with Pap test history,
although the number of respondents who
had had no Pap test was small. Younger
women who self-reported not ever having
a Pap test were at lower risk of having an
HPV infection, although this was not
observed when the analyses were performed
with the MCCSP data.
HPV infections and cytological outcomes
A total of 115 participants (19%) were
found to be HPV-positive (Table 2).
Overall, 33% (38/115) of these infections
were among participants aged less than
25 years. The participants aged less
than 25 years were also more likely
to be infected with Group 1 HPV types
Table 2
Age distribution of women by infection status and HPV type (person-based)
Age,
years
HPV−
HPV+a
n
n
(%)
(%)
Group 1b
n
HPV
16 or 18c
(%)
n
Group 2d
(%)
n
HPV
6 or 11c
(%)
n
Low-riske
(%)
n
Multiple
infections
(%)
n
(%)
Total
n
(%)
< 25
40 (8.4)
38 (33.0)
27 (44.3)
8 (40.0)
4 (21.1)
3 (75.0)
13 (29.5)
15 (50.0)
78 (13.2)
25–29
35 (7.3)
18 (15.7)
9 (14.8)
4 (20.0)
3 (15.8)
1 (25.0)
7 (15.9)
4 (13.3)
53 (9.0)
30–34
46 (9.6)
5 (4.3)
5 (8.2)
2 (10.0)
0 (0.0)
0 (0.0)
0 (0.0)
1 (3.3)
51 (8.6)
35–39
41 (8.6)
9 (7.8)
2 (3.3)
0 (0.0)
3 (15.8)
0 (0.0)
4 (9.1)
1 (3.3)
50 (8.4)
40–44
66 (13.8)
11 (9.6)
6 (9.8)
1 (5.0)
1 (5.3)
0 (0.0)
5 (11.4)
2 (6.7)
77 (13.0)
45–49
56 (11.7)
14 (12.2)
4 (6.6)
1 (5.0)
3 (15.8)
0 (0.0)
7 (15.9)
3 (10.0)
70 (11.8)
50–54
62 (13.0)
10 (8.7)
5 (8.2)
2 (10.0)
2 (10.5)
0 (0.0)
4 (9.1)
3 (10.0)
72 (12.2)
55–59
51 (10.7)
5 (4.3)
2 (3.3)
2 (10.0)
1 (5.3)
0 (0.0)
2 (4.5)
0 (0.0)
56 (9.5)
60–64
36 (7.5)
4 (3.5)
1 (1.6)
0 (0.0)
2 (10.5)
0 (0.0)
1 (2.3)
1 (3.3)
40 (6.8)
0 (0.0)
0 (0.0)
65+
Total
44 (9.2)
477
1 (0.9)
115
0 (0.0)
61
0 (0.0)
20
19
1 (2.3)
4
0 (0.0)
44
30
45 (7.6)
592
Abbreviation: HPV, human papillomavirus.
a
Any HPV type included in Group 1, Group 2, and low-risk (see text); note that HPV 34 and 97, which belong to Group 2,9 are not included in the HPV types covered by the methodology
used in this study.
b
Group 1: HPV 16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58, 59.
c
Either one type or both present at the same time.
d
Group 2: HPV 26, 30, 53, 66, 67, 68, 69, 70, 73, 82, 85.
e
Low-risk: HPV 6, 11, 13, 32, 40, 42, 43, 44, 54, 61, 62, 71, 72, 74, 81, 83, 84, 86, 87, 89, 90, 91.
(44%; 27/61) than Group 2 types (21%;
4/19). While HPV types 6 and 11 were not
detected in women aged 30 years plus, HPV
types 16 and 18 (but mostly 16) were
detected over a wider age range. One-quarter
of the infected women (26%; 30/115) had
multiple HPV infections, that is, more than
one HPV of any type.
Of the study population with a normal
Pap test, 17% (89/517) tested positive for
an HPV infection and 9% (46/517) were
infected with Group 1 HPV (Table 3).
Overall, 7% (41/592) of all participants
had an abnormal Pap test result. An HPV
infection (any type) was found in 11% of
unsatisfactory Pap tests (2/18), 32% of
atypical squamous cells of unknown
significance (ASC-US; 6/19), 63% of
low-grade squamous intraepithelial lesions
(LSIL; 10/16) and 75% of high-grade
squamous intraepithelial lesions (HSIL;
3/4). Group 1 HPV type was found in 6%
of unsatisfactory Pap tests (1/18), 11% of
ASC-US (2/19), 38% of LSIL (6/16) and
75% of HSIL (3/4). Group 1 HPV types
(overall: 10.3% [61/592]; among HPVinfected participants: 53.0% [61/115])
were detected more frequently than
Group 2 (overall: 3.2% [19/592]; among
HPV-infected participants: 16.5% [19/115])
It is not clear why some Pap tests
were not sent to the lab for evaluation.
We suspect that the clinicians that
performed these tests understood that
taking a tissue sample for HPV typing
and low-risk HPV types (overall: 7.4%
[44/592]; among HPV-infected participants:
38.2% [44/115]). Pap test results were not
available for 3% (16/592) of the HPV
samples tested.
Table 3
Person-based HPV prevalence by cytological outcome
HPV
types
Negative
Anya
6 or 11b
16
16 or 18b
Group 1c
Group 2d
Low-riske
Multiplef
Total
Missing
Normal
n
n
Unsatisfactory
n
11
5
0
2
2
3
1
1
1
16
428
89
3
10
14
46
13
36
22
517
16
2
1
0
0
1
0
1
0
18
ASC-US
LSIL
ASC-H
HSIL
Total
n
n
n
n
n
%
13
6
0
1
1
2
2
3
2
19
6
10
0
2
2
6
2
3
4
16
2
0
0
0
0
0
0
0
0
2
1
3
0
0
1
3
1
0
1
4
477
115
4
15
20
61
19
44
30
592
80.6
19.4
0.7
2.5
3.4
10.3
3.2
7.4
5.1
Abbreviations: ASC-H, atypical squamous cells–cannot rule out high-grade lesion;
ASC-US, atypical squamous cells of unknown significance; HPV, human papillomavirus;
HSIL, high-grade squamous intraepithelial lesions; LSIL, low-grade squamous intraepithelial lesions.
a
Any HPV type included in Group 1, Group 2, and low-risk (see following text); note that HPV 34 and 97, which belong
to Group 2,9 are not included in the HPV types covered by the methodology that was used in this study.
b
One type or the other or both can be present at the same time.
c
Group 1: HPV 16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58, 59.
d
Group 2: HPV 26, 30, 53, 66, 67, 68, 69, 70, 73, 82, 85.
e
Low-risk: HPV 6, 11, 13, 32, 40, 42, 43, 44, 54, 61, 62, 71, 72, 74, 81, 83, 84, 86, 87, 89, 90, 91.
f
Multiple HPV infections.
181
Vol 32, No 4, September 2012 – Chronic Diseases and Injuries in Canada
Table 4
Infection-based prevalence of the HPV genital species of the alpha genus
was their only task for this study and
did not request a regular cytological
testing.
Among Group 1 types, HPV-16 (10%) was
the most frequently detected followed by
HPV-39 (5%), 58 (5%), 18 (4%), 35 (4%),
51 (4%), 52 (4%), 59 (4%) and 33 (3%)
(Table 4). Within the genus alpha, species
9 (29%; 45/157), 3 (19%; 29/157) and 7
(17%; 26/157) were the most frequently
detected. Species 9 includes viruses related
to HPV-16, while species 7 includes those
related to HPV-18, and species 3 includes
low-risk HPV types.
Discussion
Comparing the prevalence of HPV infections
across studies is difficult because typing
technologies, sampled populations and
sampling strategies are often different.
In addition, prevalence rates are rarely
age-standardized. With this in mind, a
meta-analysis reported HPV infection
rates as varying from 7% to 8% in Europe
and Asia, 14% in North America, and
23% in Africa in women with normal
cytology.20 In the United States, rates have
been estimated as 27% in females aged
14 to 59 years.21 Our study found an HPV
prevalence of 19% (17% among those
with a normal Pap test). HPV-16 was the
most prevalent cervical type detected, while
other common high-risk types included
types 18, 33, 35, 39, 51, 52, 58 and 59.
These results are consistent with other
findings where HPV types 16, 18, 31, 39,
51, 52, 56 and 58 were found to be among
the most frequent types worldwide in
women with normal cytological findings;22
HPV types 16, 18, 31, 33, 45, 51, 52, 56
and 58 in women diagnosed with low-grade
cervical lesions;23 and HPV types 16, 18, 31,
33, 35, 45, 52 and 58 in women diagnosed
with high-grade abnormalities.24 HPV
type-specific prevalence rankings, however,
varied regionally and by country.22-24 For
example, a Belgium population-based study
reported that the most common high-risk
type was HPV-16 (3.7%), followed by
types 31, 51 and 53, which were identified
in at least 2% of the population (HPV-18
was found in 1.5% of the population).25 A
Swedish population-based study reported
infection prevalence for HPV-16 of 2.5%,
followed by HPV-31 (1.4%), HPV-45 (0.9%)
HPV
types
A1
A3
A5
A6
A7
A8
A9
A10
A11
A13
Other
Total
32
42
Total
62
72
81
83
84
86
89
Total
51
69
82
Total
30
53
56
66
Total
18
39
45
59
70
85
Total
7
40
91
Total
16
31
33
35
52
58
67
Total
6
11
44
74
Total
73
54
8
38
Total
Missing
n
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
1
0
0
0
0
2
0
0
0
0
1
1
4
0
0
1
0
1
0
0
0
0
0
6
Negative Unsatisfactory
n
n
4
0
6
0
10
0
5
0
2
0
5
0
3
0
2
0
2
0
6
0
25
0
4
0
1
0
1
0
6
0
2
0
0
0
3
0
4
0
9
0
5
0
4
0
1
0
5
0
4
0
1
0
20
0
1
0
1
0
0
0
2
0
10
0
2
0
5
0
4
0
6
0
4
1
1
0
32
1
2
0
1
1
0
3
5
0
11
1
0
0
4
0
1
0
0
0
1
0
120
2
ASC-US
LSIL
HSIL
n
0
0
0
1
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1
0
2
1
3
1
1
0
0
0
0
0
2
0
0
1
0
1
1
0
0
0
0
9
n
0
0
0
0
0
1
1
0
0
1
3
1
0
0
1
1
1
0
0
2
0
1
0
1
0
0
2
0
0
0
0
2
0
0
1
0
1
1
5
0
0
0
0
0
0
1
0
1
1
15
n
0
0
0
0
0
0
0
0
0
0
0
1
0
0
1
0
1
0
0
1
1
1
0
0
0
0
2
0
0
0
0
0
0
0
1
0
0
0
1
0
0
0
0
0
0
0
0
0
0
5
Abbreviations: ASC-H, atypical squamous cells–cannot rule out high-grade lesion;
ASC-US, atypical squamous cells of unknown significance; HPV, human papillomavirus;
HSIL, high-grade squamous intraepithelial lesions; LSIL, low-grade squamous intraepithelial lesions.
Vol 32, No 4, September 2012 – Chronic Diseases and Injuries in Canada
182
Total
n
4
6
10
6
2
6
4
2
2
7
29
6
1
1
8
3
2
3
4
12
6
7
1
6
5
1
26
1
3
1
5
15
3
5
6
6
7
3
45
2
2
5
5
14
1
5
1
1
2
%
2.5
3.8
6.4
3.8
1.3
3.8
2.5
1.3
1.3
4.5
18.5
3.8
0.6
0.6
5.1
1.9
1.3
1.9
2.5
7.6
3.8
4.5
0.6
3.8
3.2
0.6
16.6
0.6
1.9
0.6
3.2
9.6
1.9
3.2
3.8
3.8
4.5
1.9
28.7
1.3
1.3
3.2
3.2
8.9
0.6
3.2
0.6
0.6
1.3
157
and HPV-18 (0.7%); 13.0% of women had
multiple infections.26 Many studies have
reported an increase in HPV infections in
women 60 years of age and older.27 There
were insufficient cases to confirm that
trend in Manitoba.
A few studies have investigated the
prevalence of HPV in Canada. A British
Columbia study found an overall HPV
prevalence rate of 16.8% (high-risk HPV:
13.9%; HPV-16: 10.7%);28 an Ontario study
found an overall infection rate of 13.3%
(high-risk HPV: 9.6%, HPV-16: 7.3%);29 A
New Brunswick study found a prevalence
of 28% (high-risk HPV: 21%).30 A study
conducted between 1992 and 1995 recruited
a large proportion of Aboriginal women
(42%) from a clinic located in a low-income
inner-city area of Winnipeg, Manitoba,
and found that HPV infections rates in
Aboriginal and non-Aboriginal women
were comparable (33.6% and 31.8%,
respectively).31 However, because of the
different populations included in our present
study and this earlier one, comparison of
results is difficult.
The prevalence of high-risk HPV has been
consistently reported to increase with
the severity of lesions. For example, a
meta-analysis reported high-risk HPV in
71.9% (95% CI: 62.8%–80.9%) of LSIL
cases23 and 88.3% (95% CI: 85.8%–
90.8%) of HSIL cases.24 Moore et al.28
reported that 52.3% of LSIL and 79.4%
of HSIL contained high-risk HPV. They
also found that HPV positivity increased
from normal (12.3%) to benign (19.6%) to
low-grade (69.3%) to high-grade (81.0%).28
We found 37.5% of LSIL were high-risk
(Group 1) HPV-positive, as were 75%
of HSIL.
A number of cofactors are associated
with risk of having an HPV infection and
different grades of cervical abnormalities,
many of which are related to sexual
behaviours. The factors that have been
the most consistently associated with
higher rates of HPV infections include
younger age and having a greater number
of lifetime and recent sex partners.32,33
Other cofactors for HPV infection, including
age at sexual debut, smoking, oral
contraceptive use, ethnicity, alcohol
consumption, history of STI, income, and
condom use have also been reported,
but not consistently.33-41 The multivariate
analysis showed that age, ethnicity, and
the number of sexual partners in the
last year were independent predictors.
Our present study also suggests that some
of these risk factors are common for all
age groups while other factors are found
only in either younger or older women.
Women with no history of cervical
cancer screening and those who were
under-screened have been reported to
have higher incidence rates of cervical
cancer than women who regularly received
screening.42-45 In the present study, women
30 years of age and older with no Pap test
history were found to be HPV-positive
more often.
Limitations of the study
The present study has several limitations.
As with almost all seroprevalence
studies, our study relied on opportunistic
samples and was not population-based.
Consequently, the results do not necessarily
represent the rate of HPV infections in the
general female population. The publicity
made around Pap Week in Manitoba and
the clinics dedicated to one-day screening
could also create a selection bias by
encouraging symptomatic women who
have delayed screening to finally get a Pap
test. It is difficult to predict the outcome
of such bias on the current risk factor
analysis, but if it is differential, it may
explain why the risk of infection was
higher in some groups of people. The
cervical screening participation rate in
Manitoba between 2007 and 2009 in
women aged 20 to 69 years was 65.9%.
The breakdown of their cytological results
was normal cytology, 95.5%; ASC-US
3.1%; LSIL 2.1%; atypical glandular cells
(AGC) 0.1%; ASC-H 0.3%; and HSIL 0.9%.
Among study participants, the cervical
screening participation rate since 2001 was
84.8% (502/592), with a breakdown of
cytology results of normal cytology 87%
(517/592); ASC-US 3% (19/592); LSIL 3%
(16/592); ASC-H 0.3% (2/592); and
HSIL 1% (4/592).
This comparison suggests that most of
the study participants attend cervical
screening regularly and that their cytological
183
outcomes were comparable to the women
who attended cervical screening in
Manitoba between 2007 and 2009. The
cross-sectional nature of the study design
does not allow for establishing a causal
relationship between HPV infection and
the cofactors investigated. In addition,
self-administered questionnaires can be
subject to biases. Nevertheless, findings
are consistent with current knowledge on
risk factors for HPV infections. Due to
the high sensitivity of the HPV detection
method, the clinical significance of the
present study is limited. The PCR amplification can detect as little as one copy of
the targeted genes (L1 DNA), and this
sensitivity does not necessarily translate
into infection of clinical significance.
Depuydt et al. showed that below a
critical viral load, detection of visually
detectable lesions is very rare.46 A highly
sensitive test has the potential to limit the
triaging of people with HPV infections.
Conclusion
The results from our study suggest that
the distribution of oncogenic HPV types in
Manitoba is in accordance with what has
been reported in Canada and in other
countries. These data provide a baseline
of HPV prevalence in an unvaccinated
population in Manitoba. In addition, the use
of data linkage provides a proof of concept
for the applicability of population-based
registry linkage to evaluate HPV immunization programs in those jurisdictions where
the capacity to conduct such linkages exist.
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Vol 32, No 4, September 2012 – Chronic Diseases and Injuries in Canada
Features of physician services databases in Canada
L. M. Lix, PhD (1); R. Walker, MSc (2); H. Quan, PhD (2); R. Nesdole, MEd (1); J. Yang, BSc (3); G. Chen, PhD (2);
for the CHEP-ORTF Hypertension Outcomes and Surveillance Team
This article has been peer reviewed.
Abstract
Introduction: Physician services databases (PSDs) are a valuable resource for
research and surveillance in Canada. However, because the provinces and territories
collect and maintain separate databases, data elements are not standardized. This
study compared major features of PSDs.
Methods: The primary source was a survey of key informants that collected information about years of data, patient/provider characteristics, database inclusions/exclusions, coding of diagnoses, procedures and service locations. Data from the Canadian
Institute for Health Information’s (CIHI) National Physician Database were used to
examine physician remuneration methods, which may affect PSD completeness.
Survey data were obtained for nine provinces and two territories.
Results: Most databases contained post-1990 records. Diagnoses were frequently
recorded using ICD-9 codes. Other coding systems differed across jurisdictions and
time, although all PSDs identified in-hospital services and distinguished family
medicine from other specialties. Capture of non-fee-for-service records varied
and CIHI data revealed an increasing proportion of non-fee-for-service physicians
over time.
Conclusion: Further research is needed to investigate the potential effects of PSD
differences on comparability of findings from pan-Canadian studies.
Keywords: administrative health databases, physician services, medical insurance
programs, International Classification of Diseases
Introduction
Administrative health data, which are
collected to monitor and manage health
systems, are a rich resource for research
and surveillance in Canada. The data
are obtained from multiple sectors
including health insurance registration
systems, inpatient facilities, emergency
departments, medical services plans, vital
statistics files and prescription drug
systems. Increasingly, administrative data
are being used to conduct pan-Canadian
studies on population health and the
use of health services. For example,
the Public Health Agency of Canada’s
Canadian Chronic Disease Surveillance
System uses diagnoses recorded in hospital
and physician records to estimate prevalence and incidence for such conditions as
diabetes and hypertension for all Canadian
provinces and territories.1-3 Multi-province
chronic disease studies using administrative
data have also been undertaken for
rheumatic diseases, inflammatory bowel
disease and mental disorders,4-6 and are
underway for other conditions, including
hypertension.7
Administrative
health
data are appealing for research and
surveillance because they provide an
economical alternative to primary data
collection, encompass entire populations
and span multiple years.
Despite the many advantages of administrative health data, their use is not
without challenges. Canada has a
system of universal health care, but
the delivery of services is a provincial and
territorial responsibility. The collection
and management of most administrative
data are undertaken using information
systems developed for each province and
territory, which may contribute to a lack
of standardization and harmonization in
how the data are collected and recorded.
Exceptions are the national hospital databases developed by the Canadian Institute
for Health Information (CIHI), including
the Discharge Abstract Database and the
Hospital Morbidity Database, which use a
common abstraction form and quality
evaluation methodology.
Data quality is a relevant research topic
in today’s environment, where large
databases are frequently used for decision
making
and
policy
development.8
Researchers, epidemiologists and decision
makers interested in undertaking panCanadian studies could benefit from
results of comparisons of administrative
health data from different jurisdictions.
Information about features of these data
can facilitate developing quality evaluation
methodologies and research protocols
to investigate the potential impact of
differences on study findings. Physician
services databases (PSDs), which contain
billing records or claims for physician
Author references:
1. School of Public Health, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
2. Department of Community Health Sciences, University of Calgary, Calgary, Alberta, Canada
3. Western College of Veterinary Medicine, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
Correspondence: Lisa Lix, School of Public Health, University of Saskatchewan, 107 Wiggins Road, Saskatoon, SK S7N 5E5; Tel.: (306) 966-1617; Fax: (306) 966-7920; Email: lisa.lix@usask.ca
Vol 32, No 4, September 2012 – Chronic Diseases and Injuries in Canada
186
contacts with patients, are particularly
important for chronic disease research
and surveillance. They are a source of
diagnosis and procedure information for
outpatient visits, and contain information
about contacts with both primary care
and specialist physicians. Given this
background, the purpose of this study
was to compare major features of PSDs
in Canada’s provinces and territories.
A paper on this topic is critical to establishing a baseline level of scientific
knowledge. Further, this article will likely
remain relevant for some time because
many database features, including first
year of data accessible to researchers,
International Classification of Diseases
(ICD) version, number of diagnosis
fields, specificity of diagnosis fields and
availability of information about outof-province services, are unlikely to change
quickly; in fact, they have been static
in several provinces and territories over
recent years.
Methods
The primary source of data for this study
was a survey, emailed to key informants
from all provinces and territories, to
collect information about selected features
of PSDs. Published CIHI reports were a
secondary source of data, and were used
to collect information about the ways
physicians are remunerated, a factor that
can affect completeness of PSDs.8
Key informants were primarily identified
from the membership of the Hypertension
Outcomes and Surveillance Team (HOST),9
a subgroup of the Canadian Hypertension
Education Program Outcomes Research
Task Force (CHEP-ORTF). HOST includes
approximately 20 researchers, analysts and
government representatives from British
Columbia, Alberta, Saskatchewan, Manitoba,
Ontario and Quebec as well as from the
Public Health Agency of Canada and
Statistics Canada. Members of HOST have
expertise in health services or population
health research or surveillance using
administrative data. In those provinces or
territories that have no HOST member, we
contacted HOST collaborators, individuals
employed by ministries of health who
facilitate access to administrative data and
documentation for research purposes. Up
to two individuals from each province and
territory were contacted to participate in
the study.
Study investigators developed the survey
based on earlier research on features of
administrative health data.10 The survey
included questions about the years of
data available for researcher access and the
availability and contents of fields for patient
and provider information, patient diagnosis
and procedure codes, out-of-province
services and services of providers paid by
non-fee-for-service methods. Physician fee
schedules were also consulted as a source of
information about remuneration methods.11
Open-ended response categories were used
for all survey questions.
Key informants were initially contacted in
June 2010. Follow-up questions and online
documentation about PSDs was used to
clarify responses and to develop additional
questions. A second round of questionnaires
was sent to the key informants in
November 2010 to obtain more detailed
information about PSD features.
Secondary data published by CIHI were
used to compile additional information about
non-fee-for-service (i.e. alternate clinical)
providers and payments.12-14 The data were
from reports based on the National Physician
Database, which contains aggregate
physician payment data from provincial
and territories medical services plans.
Information about the National Physician
Databases and the data collection
methodology was previously published.12,15
Ethics approval for the HOST project,
which includes the extraction and analysis
of administrative health data from the
provinces and territories and the collection
and reporting of documentation associated
with the administrative health data, was
obtained from the University of Calgary
Research Ethics Board (Ethics Review
#E188889). The analysis of publicly
available data from CIHI did not require
ethics approval.
Results
Key informants from all provinces and
territories except New Brunswick
responded to the survey, though only
187
partial information was available from
the Northwest Territories. As a result,
New Brunswick and Northwest Territories
were excluded from the analysis of the
survey data.
PSD availability
The survey results indicate that PSDs in
Canada contain records from as early as
1970 (see Table 1); the range for the first
accessible year of data was 24 years. The
Manitoba and Saskatchewan databases
contain the oldest records, from the early
1970s. Databases for four provinces hold
records from the 1980s. However, Quebec
and Alberta reported that some of the
earliest records were not easily accessed
because they were archived and/or in a
format different to more recent records.
The other provinces and territories reported
that their databases contained records
from the 1990s.
Patient and provider information
The survey results also revealed that all
PSDs contain unique patient and provider
identifiers (Table 1). With appropriate
permissions, these identifiers can be used
to link the databases to other sources. For
example, linkage to a population registry
file can be used to obtain dates of coverage by provincial health insurance plans,
residence information (e.g. postal code
or geographic area), birthdates or age,
and sex.
All databases also record provider specialty.
The number of specialist categories
reported by respondents ranged from
about 25 to more than 80. However, broad
groupings of family medicine, medical
specialties, and surgical specialties were
identified in the categories provided by
all provinces and territories. At the same
time, there was a heterogeneous mix
of provider specialties in the “other”
category. Depending on the jurisdiction,
this category could include nurse
practitioners, midwives, pharmacists or
other allied health professionals. Most
respondents indicated that provider
specialty was assigned by each jurisdiction’s medical services plan at the time
the service record was submitted for
payment.
Vol 32, No 4, September 2012 – Chronic Diseases and Injuries in Canada
Table 1
Major features of physician services databases by province or territory: data availability, patient, provider
Province/
Territory
First year of data
accessible to researchers
Patient
identifier
Patient
demographicsa
Provider
identifier
British
Columbia
1990
✓
✓
✓
50+ categories from family medicine, medical, surgical, other.
Multiple specialty fields defined.
1982; data prior to 1994
are in a different format
✓
✓
✓
60+ categories from family medicine, medical, surgical, other.
Specialty defined by the payment plan.
Saskatchewan
1971
✓
✓
✓
70+ categories from family medicine, medical, surgical, other.
Specialty defined by physician certification.
Manitoba
1970
✓
✓
✓
80+ categories from family medicine, medical, surgical, other.
Multiple specialty fields defined.
Ontario
1991
✓
✓
✓
35+ categories from family medicine, medical, surgical, other.
Multiple specialty fields defined.
Quebec
1983; data prior to 1996
are in a different format
✓
✓
✓
One field distinguishes family physicians from specialists.
A second field identifies the type of specialty. 60+ categories
are identified from family medicine, medical, surgical, other.
Specialty defined by physician training.
Prince Edward
Island
1983; Data prior to 1996
are archived
✓
✓
✓
45+ specialty code descriptions within family medicine, medical,
surgical, other. Specialty defined by the services provided.
Nova Scotia
1989
✓
✓
✓
50+ categories from family medicine, medical, surgical, other.
Billing specialty and main specialty defined.
Newfoundland
and Labrador
1995
✓
✓
✓
80+ categories from family medicine, medical, surgical, other.
Specialty defined by physician training.
Yukon
1995
✓
✓
✓
25+ categories from family medicine, medical, surgical. Specialty
defined by physician certification.
Nunavut
1999
✓
✓
✓
Approximately 70% of records are coded as generalist or specialist
physician. The remaining records are missing information about
physician specialty.
Alberta
Provider categories and specialties
Note: Incomplete or no survey data was available for New Brunswick and Northwest Territories. As a result, these were excluded from the analysis.
a
Includes date of birth or age, sex, location of residence (e.g. postal code, health region or county)
Diagnosis and procedure information
Table 2 shows information about diagnosis
and procedure codes, as identified by
the survey respondents. ICD codes were
used to record the majority of diagnoses
in all jurisdictions. In Saskatchewan and
Manitoba, ICD-8* diagnosis codes were
primarily used in the 1970s. Three jurisdictions, Manitoba, Alberta and Nunavut, use
ICD-9-CM codes†. In Yukon, diagnoses
are recorded using ICD-9‡ codes as well
as a free-form text format. In Ontario, data
contain both ICD-8 and ICD-9 codes,
although neither system is used in its
entirety. In Saskatchewan, not all ICD-9
codes are used to assign diagnosis.
Respondents from all but three provinces
reported that a single diagnosis is
recorded for each claim in their PSDs.
For British Columbia, up to three diagnosis
fields may be present on some of the
claim records. Nova Scotia’s database
contains three diagnosis codes for
selected years. Alberta’s database also
contains three diagnosis fields, although
respondents noted that the second
and third fields were not consistently
coded in all records. The Yukon and
Nunavut databases contain multiple
diagnosis fields.
Location of services
Diagnosis codes were recorded with
different degrees of specificity, with
three-digit codes being most common.
While procedural information was
most commonly identified from service
fee codes, other procedure coding
systems were adopted, including the
Canadian Classification of Procedures
in both Nova Scotia and Alberta.
PSD inclusions and exclusions
* International Classification of Diseases, Eighth Revision.
†
International Classification of Diseases, Ninth Revision, Clinical Modification.
‡
International Classification of Diseases, Ninth Revision.
Vol 32, No 4, September 2012 – Chronic Diseases and Injuries in Canada
188
Survey respondents reported that not all
PSDs contain a field or fields to identify
location of service (see Table 3); service
fee codes and billing location are
sometimes required to ascertain service
location. However, in all provinces and
territories, it is possible to distinguish
in-hospital services from those provided
in other locations.
Table 3 also contains survey information
about records from out-of-province
providers.
Respondents
from
four
provinces (Newfoundland and Labrador,
Nova Scotia, Manitoba, and British
Columbia) reported that these records
were contained in a separate database. For
Table 2
Major features of physician services databases in Canada: diagnoses and procedures
Province/
Territory
ICD version
Number of
diagnosis fields
Specificity of diagnosis codes
(number of digits)
Source of procedure
information
Other information about diagnosis/
procedure fields
British
Columbia
ICD-9
Most claims
contain 1 code, but
some primary care
physicians record
up to 3
Up to 5, but 3 digits
are the most common
Fee codes
ICD-9-CM codes are also found in some
claims. Some diagnosis codes are specific
to the provincial medical services plan.
ICD-9-CM
3 (1 before 1994)
Up to 5, but the 5th digit is not
well recorded; 3-digit codes were
used before 1994
Canadian
Classification of
Procedures
Saskatchewan
ICD-8 until 1978,
then ICD-9
1
3
Fee codes
Manitoba
ICD-8 until 1979,
then ICD-9-CM
1
3
ICD-9-CM and fee
codes
Ontario
Hybrid of ICD-8
and ICD-9
1
3; a 1-digit suffix is
added for physiotherapy and
chiropractic codes
Fee codes
Quebec
ICD-9
1
4
Province-specific
codes
Prince Edward
Island
ICD-9
1
3, except for E-codes and
V-codes, which are 5 digits
ICD-9 and fee codes
Nova Scotia
ICD-9
3 (1 before 1997)
Up to 5; 3-digit codes are
the most common and were
used before 1997
Modified version
of CCP. A single code
is recorded
Newfoundland
and Labrador
ICD-9
1
3
Fee codes
ICD-9 + text
2 before 2006,
unlimited since then
Up to 5 but most records
use only 4
Fee codes
ICD-9-CM
11
5
None
Alberta
Yukon
Nunavut
Some diagnostic codes assigned by the
province are also used and some ICD-9
codes (including all E-codes and selected
other codes) are not used.
Not all ICD-8 and -9 diagnosis codes
are found in the database.
Some E-codes are captured in an
“injury diagnosis” field, but the capture
rate or completeness is not known.
The databases support the collection
of procedure codes, but this information
is not currently captured.
Abbreviations: E-codes, external cause of injury codes; ICD-8, International Classification of Diseases, Eighth Revision; ICD-9, International Classification of Diseases, Ninth Revision;
ICD-9-CM, International Classification of Diseases, Ninth Revision, Clinical Modification; V-codes, supplemental codes.
Note: Incomplete or no survey data was available for New Brunswick and Northwest Territories. As a result, these were excluded from the analysis.
the remaining provinces and territories,
respondents noted that a specific code or
field within the PSD could be used to
identify out-of-province records.
submitted by non-fee-for-service physicians.
In three provinces, information from a
provider registry is needed to distinguish
these two types of records.
The collection of records from fee-for-service
and non-fee-for-service physicians was the
final topic of inquiry. With the exception of
Newfoundland and Labrador and of Quebec,
respondents indicated that PSDs in all
jurisdictions contain records of services
provided by non-fee-for-service physicians.
However, respondents also indicated that
the completeness of capture of records from
non-fee-for-service physicians was not
consistently known. This might be due to
changes in medical service plans over time
and/or a lack of documentation about
alternate payment plans. Respondents from
six jurisdictions reported that PSDs contain
a field to distinguish records submitted by
fee-for-service physicians from those
CIHI data on physician remuneration
methods
The secondary data from CIHI were used to
investigate physician remuneration methods
across jurisdictions, which may affect the
completeness of PSDs. Data from the
territories were not consistently available
and are therefore not reported. In Figure 1,
the percentage of full-time equivalent
physicians remunerated by non-fee-forservice (i.e. alternate clinical) payment
methods are reported for fiscal years
1999/2000 and 2005/2006; the last year is
the most recent available from CIHI. This
percentage increased in all provinces,
except for British Columbia and for
189
Newfoundland and Labrador. The largest
absolute increase occurred in New Brunswick
(17.3%) and Prince Edward Island (15.0%).
When the data from the four Atlantic
provinces were combined, the percentage of
full-time equivalent physicians remunerated
by alternate clinical payments rose from
20.3% to 25.6%. Saskatchewan also saw
a large absolute increase (6.5%). Figure 2
provides data about alternative clinical
payments to physicians in fiscal years
1999/2000 and 2008/2009. Overall, payments
in the four Atlantic provinces increased
from 23.8% to 39.8%. Large increases
between the two study years were also
observed in Ontario and Saskatchewan.
Discussion
We identified only one other published
paper that systematically documented the
features of PSDs in Canada; it focused on
Vol 32, No 4, September 2012 – Chronic Diseases and Injuries in Canada
Table 3
Major features of physician services databases in Canada: service location and completeness
Province/
Territory
Location of service categories
Out-of-province
services
Shadow-billed records
Shadow-billing indicator
British
Columbia
Province and out-of-country locations are identified.
Service locations including hospitals and clinics are available
from 1990.
Recorded in a
separate database
Yes, but completeness
is unknown
Yes. As of 1999
shadow-billed claims can
be identified using a flag.
Alberta
Service locations are identified from address information.
Identified in one
field in the database
Yes, but completeness
is unknown
Yes
Saskatchewan
Office, hospital inpatient, hospital outpatient, home, other,
location not indicated, emergency room physician. Fee
codes are also used to identify services provided in hospital.
Location of services became a required field in the 1980s,
but the exact date is not known. This field is not validated.
Identified by a field
in the database
Yes, but completeness
is unknown
Yes
Manitoba
Hospital location categories are identified in one field.
Services to other locations, including personal care
homes and patient home are identified from fee codes.
Clinic locations are identified from the billing location.
Collected in a
separate database.
Available since
1993/1994
Yes, but completeness
is unknown
No. Shadow-billed claims
can be identified using
information contained in
the provider registry.
Ontario
In the current data, there is no field for location of service.
Locations are identified from fee codes and/or institution
numbers. A hospital master number is recorded for services
provided in hospital.
Identified by a
numeric code in
the database or
by the fee code or
physician number
Yes, but completeness
is unknown
Yes
Quebec
Two primary locations: private cabinet (e.g. office/clinic)
and establishment (e.g. hospital). For establishments,
there are 40+ location categories including private firms,
hospitals, laboratory diagnostic radiology, office of
physiotherapy, home centres for children and youth,
federal agencies, universities, private clinics, private
labs orthotics-prosthetics, detention centres.
Identified by a
numeric code
in the database
No
No
Prince Edward
Island
25 codes are currently used: office, home visit, inpatient,
outpatient, other office, day surgery, specialty clinic,
community care facility, other site, UPEI clinic, detox
centres, First Patient, inpatient radiology, night clinic,
outpatient radiology, visiting specialist in Prince County
Hospital, visiting specialist in Queen Elizabeth hospital,
Saturday/Sunday office, radiology, provider in any facility
type, radiology emergency, walk-in clinic, public dental
facility, private dental facility, public health hygienist.
Identified by a
numeric code
in the database
Yes, but completeness is
unknown. Effective July 1,
2008, the Clinical Work
Incentive (an incentive to
shadow bill) was introduced,
at which time shadow-billing
has become more complete
No. Shadow-billed claims
can be identified from
the physician billing or
specialty number.
Nova Scotia
Office, correctional centre, home hospital care, patient’s
home, hospital, nursing home. Hospital locations include
detox, emergency, intensive care, inpatient, neonatal unit,
outpatient.
Collected in a
separate database
Yes, but completeness
is unknown
Yes, from 1997 onward.
Newfoundland
and Labrador
Home, office, inpatient, outpatient, emergency department.
Collected in a
separate database
No
No
Yukon
Office/practitioner office, patient’s home, hospital inpatient, Identified in one
hospital outpatient, lab, surgery specialty clinic, community
field in the database
care facility, other, out of town clinic, nursing home, injection,
anesthesia, assist surgery, admit, maternity, jail.
Yes, but completeness
is unknown
Yes
Nunavut
No field for location of service.
No
No
Identified by a
numeric code
in the database
Abbreviation: UPEI, University of Prince Edward Island.
Note: Incomplete or no survey data was available for New Brunswick and Northwest Territories. As a result, these were excluded from the analysis.
the Saskatchewan database.16 However,
previous research that compared prescription
drug administrative databases in several
Canadian provinces found differences in
patient, provider and drug features.10
These findings are consistent with the
findings of the current study, which
revealed heterogeneity in many features of
PSDs in Canada, including the years of
available data, classification of provider
specialty, database inclusions and exclusions,
and coding of diagnoses, procedures and
service locations.
PSDs have a tremendous potential to
benefit population health and health
services
research
and
surveillance
initiatives in Canada. The Canadian
Chronic Disease Surveillance System uses
administrative health databases to provide
Vol 32, No 4, September 2012 – Chronic Diseases and Injuries in Canada
190
comparable, longitudinal data on chronic
disease prevalence and incidence. This is
used to support provincial and territorial
surveillance efforts. Statistic Canada’s
Longitudinal Health and Administrative
Data Initiative links administrative health
databases with population health survey
data, including data from the National
Population Health Survey and Canadian
Community Health Survey, to facilitate
some limitations. The study relied on a
purposive sample; the key informants
may not have had complete information
about features of PSDs over time or across
the geographic regions of a province or
territory. A second limitation is that the
quality of the data associated with different
features was not investigated.25 For example,
this study did not examine accuracy or
completeness of fields containing location
of service codes.
Figure 1
Full-time equivalent physicians receiving non-fee-for-service
(alternate clinical) payments, by province, 1999/2000 and 2005/2006
Newfoundland & Labrador
Prince Edward Island
Nova Scotia
New Brunswick
Quebec
Ontario
Manitoba
Saskatchewan
1999/2000
Alberta
2005/2006
British Columbia
0
5
10
15
20
25
30
Percent of Full-time Equivalent Physicians
Source: Canadian Institute for Health Information.13,14
pan-Canadian research about determinants
of health, health outcomes and their
relationships.17
However, differences in PSDs across
Canada are an important consideration
for comparability of the findings from
research and surveillance studies. Changes
in disease prevalence estimates over time
may be due, in part, to measurement
artifact arising from changes in ICD
coding systems rather than true change in
the population distribution of disease.18
The incomplete capture of services by
non-fee-for-service physicians may result in
biased estimates of trends over time and
differences across health regions.19 The
number of years of available data might
influence the results of studies about
duration of disease exposure and time to
disease onset.20 Text diagnosis fields, such
as those found in the Yukon PSD, may
require the use of data mining techniques
to assign diagnosis codes,21 a different
methodology than would be used in other
jurisdictions to ascertain disease cases.
Some studies may not be feasible for all
Canadian provinces and territories because
of the differences in data coding systems.
For example, some forms of arthritis cannot
be identified using the first three digits of
ICD-9.22 Ontario and Saskatchewan PSDs do
not contain all codes from either the ICD-8 or
ICD-9 systems; incomplete codes may result
in missing observations. Heterogeneity in
coding systems may affect the consistent
identification of some types of procedures,
such as casting or immobilization procedures, which are used to ascertain fracture
cases23,24 or endoscopy or colonoscopy
procedures, which have been the focus
of previous pan-Canadian research.11
Strengths and limitations of the study
While our study is the first to document
and report the features of PSDs from many
provinces and territories, it does have
Our study suggests a rich set of opportunities
to examine further the use and compa­
rability of PSDs in pan-Canadian research
and surveillance initiatives. Previous
research about the potential bias caused by
the length of the observation period and
incompleteness of data on prevalence and
incidence estimation has often focused on
cancer registries and on data from a single
jurisdiction.26,27 Computer simulation and
statistical modeling techniques that have
been proposed to estimate or adjust for
these effects28,29 could be extended to
multiple jurisdictions. Methodological
investigations about the utility of other
administrative databases, such as prescription drug databases, to estimate the
completeness of PSDs for chronic disease
surveillance8 could also be used for
comparisons across many jurisdictions. A
recent study about methods to ascertain
chronic disease cases in administrative
health databases emphasized the need to
assess the validity of diagnosis codes
Figure 2
Non-fee-for-service (alternate clinical) payments to physicians,
by province, 1999/2000 and 2008/2009
Newfoundland & Labrador
Prince Edward Island
Nova Scotia
New Brunswick
Quebec
Ontario
Manitoba
Saskatchewan
1999/2000
Alberta
2008/2009
British Columbia
0
10
20
30
40
50
Percent of Total Clinical Payments
Source: Canadian Institute for Health Information.
12
191
Vol 32, No 4, September 2012 – Chronic Diseases and Injuries in Canada
across populations and over time to ensure
the generalizability of case-detection
algorithms.30 There are other features of
PSDs that require investigation, including
data access procedures, service fee codes,
and processes for data linkage. For example,
substantial differences have been observed
in service fees for colonoscopy and endoscopy using provincial and territorial fee
schedules.11 There may also be differences
in the types of procedures and services for
which fee codes have been developed. While
there are an increasing number of studies
that link PSDs to other administrative,
clinical and population-based survey data
sources,31-33 we did not consider how the
capability to conduct these linkages might
vary across provinces and territories.
The authors also acknowledge the investigators of the Hypertension Outcomes and
Surveillance Team, including Dr. Karen Tu,
Dr. Brenda Hemmelgarn, Dr. Norman
Campbell, Dr. Finlay McAlister, Dr. Michael
Hill, Dr. Nadia Khan, Dr. Andreas Wielgosz,
Dr. Gary Teare, Mark Smith, Larry Svenson,
Dr. Oliver Baclic, Dr. Gillian Bartlett,
Dr. Sulan Dai, Jay Onysko, and Dr. Helen
Johansen.
7.Campbell N, Onysko J; Canadian
Hypertension Education Program; Outcomes
Research Task Force. The Outcomes Research
Task Force and the Canadian Hypertension
Education Program. Can J Cardiol.
2006;22:556-8.
This study is based, in part, on information
provided by the Saskatchewan Ministry of
Health. The interpretation and conclusions
contained herein do not necessarily
represent those of the Government of
Saskatchewan or the Saskatchewan Ministry
of Health.
9. Campbell N, Chen G. Canadian efforts to
prevent and control hypertension. Can J
Cardiol. 2010;26(Suppl C):14C-17C.
In summary, this study has demonstrated
differences across provinces and territories
in a number of PSDs features. This may
affect the comparability of pan-Canadian
research and surveillance. Studies that
investigate the potential impact of these
differences will benefit Canadian researchers,
epidemiologists and health care decision
makers.
References
11. Roth LS, Adams PC. Variation in physician
reimbursement for endoscopy across
Canada. Can J Gastroenterol. 2009;23:503-5.
Acknowledgements
This study was supported by funding from
the Canadian Institutes of Health Research
to LML and HQ and the University of
Saskatchewan Centennial Research Chair
Program to LML. The authors are indebted
to the many individuals who participated
in this study, including Michael A. Ruta
(Government of Nunavut); Dr. Gillian Bartlett
(McGill University); Deanna Rothwell (The
Ottawa Hospital, The Ottawa Hospital
Research Institute, and the Institute of
Clinical Evaluative Sciences); Nedeene R. L.
Hudema (Saskatchewan Health Quality
Council), Nadine MacLean (Health PEI);
Dr. Carol McClure (PEI Department of
Health and Wellness); Dr. Khokan C. Sikdar
(Newfoundland and Labrador Centre for
Health Information); Robert Fisk, Kim
Reimer and Jenny Sutherland (Population
Health Surveillance and Epidemiology
Population and Public Health, BC Ministry
of Health); Mike Tribes (consultant,
Yukon) and Charles Burchill (Manitoba
Centre for Health Policy, University of
Manitoba).
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2. Khan L, Mincemoyer S, Gabbay RA.
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where are we headed? Diabetes Technol
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3. Dai S, Robitaille C, Bancej C, Loukine L,
Waters C, Baclic O. Executive summary–
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Surveillance System: hypertension in Canada,
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4. Bernatsky S, Joseph L, Pineau CA, Bélisle P,
Boivin JF, Banerjee D, et al. Estimating the
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8. Alshammari AM, Hux JE. The impact of
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National physician database, 2008-2009.
Ottawa (ON): Canadian Institute for Health
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Ottawa (ON): Canadian Institute for Health
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Rajan R, Moore A, et al. Bayesian modelling
of imperfect ascertainment methods in
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30.Manuel DG, Rosella LC, Stukel TA.
Importance of accurately identifying disease
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C, Metge C, Bond R. Population-based data
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TK, Gelskey DE. Comparison of survey
and physician claims data for detecting
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33.Roos LL, Brownell M, Lix L, Roos NP,
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24.Jean S, Candas B, Belzile E, Morin S,
Bessette L, Dodin S, et al. Algorithms can
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2004;5:141-52.
193
Vol 32, No 4, September 2012 – Chronic Diseases and Injuries in Canada
Using national surveys for mental health surveillance
of individuals with intellectual disabilities in Canada
I. A. Bielska, MSc (1); H. Ouellette-Kuntz, MSc (1,2); D. Hunter, PhD (1)
This article has been peer reviewed.
Abstract
Introduction: Individuals with intellectual disabilities have a higher prevalence of health
problems, including psychiatric and behavioural conditions, than the general population.
However, there is little population-based information in Canada about individuals with
a dual diagnosis of psychiatric disorder and intellectual impairment. The aim of this
study was to determine whether the 2005 Canadian Community Health Survey (CCHS)
and the 2006 Participation and Activity Limitation Survey (PALS) could be used to estimate
the prevalence of dual diagnosis in Canada.
intellectual disability. Research suggests
that the proportion of people with
intellectual
disabilities
who
have
co-morbid psychiatric or behavioural
conditions ranges from 14% to 64%
depending on the population studied
and the diagnostic criteria used.9-14
Conclusion: The estimates should be interpreted with caution due to concerns regarding
the representativeness of the sample with intellectual disabilities in the national surveys.
Although up to 3% of Canadians may
have an intellectual disability, no studies
have examined the feasibility of using
national health surveys to research this
population. In response to this, we
examined two national health surveys,
Canadian Community Health Survey
(CCHS) and Participation and Activity
Limitation Survey (PALS), to determine
if they could be used for mental
health surveillance among Canadians
with an intellectual disability to
potentially aid service and policy
planners in learning more about this
population.
Keywords: mental retardation, mental disorders, health surveys, health services research
Methods
Methods: We undertook a secondary analysis of two population-based surveys to determine
if these could be used to estimate the prevalence of psychiatric or behavioural conditions
among adults with intellectual disabilities in Canada.
Results: The surveys reflect prevalence estimates of intellectual disabilities (CCHS: 0.2%
and PALS: 0.5%) that are considerably lower than those published in the literature.
While it was possible to calculate the proportion of individuals with a dual diagnosis
(CCHS: 30.6% and PALS: 44.3%), the surveys were of limited use for detailed analyses.
The estimates of prevalence derived from the surveys, especially from the CCHS, were
of unacceptable quality due to high sampling variability and selection bias.
Introduction
Intellectual disabilities can be defined
as life-long conditions that present before
the age of 18 years that are characterized
by limitations in intellectual functioning
and adaptive behaviour.1 Intellectual
disabilities affect up to 3% of the
population.2 Most studies have shown
that intellectual disabilities affect more
males than females.3,4 The prevalence
of diagnosed intellectual disabilities
increases with age among children
and adolescents.2 However, studies of
prevalence among adults consistently
report rates below 1%.5 Compared to
the general population, individuals with
intellectual disabilities have a higher
prevalence of health problems,6,7 including
a psychiatric or behavioural condition.8 In
Canada, the term “dual diagnosis,” as
defined by the Canadian Mental Health
Association*, usually refers to an individual
with both a mental illness and an
We conducted a secondary analysis of
two population-based surveys, CCHS and
PALS. The CCHS, Cycle 3.1 (2005), is a
cross-sectional survey of 130 000 Canadians
aged 12 years and over, representing
residents of all provinces and territories.15
A multistage stratified cluster sampling
design is used in the survey. The PALS
(2006) is a cross-sectional survey of
47 500 individuals16 that has a two-phase
stratified sample design. The sampling
frame for the second phase comprised all
people who reported activity limitations
*http://www.ontario.cmha.ca/about_mental_health.asp?cID=7598
Author references:
1. Department of Community Health & Epidemiology, Queen’s University, Kingston, Ontario, Canada
2. Department of Psychiatry, Queen’s University, Kingston, Ontario, Canada
Correspondence: Hélène Ouellette-Kuntz, Carruthers Hall, 2nd floor, 62 Fifth Field Company Lane, Kingston, ON K7L 3N6; Tel.: (613) 533-2901; Fax: (613) 533-6686;
Email: helene.kuntz@queensu.ca
Vol 32, No 4, September 2012 – Chronic Diseases and Injuries in Canada
194
on the 2006 Canadian census. A separate
dataset containing demographic information
about individuals who completed the census
but did not indicate activity limitations
was combined with the PALS dataset. For
the PALS, proxy respondents were allowed
when the selected respondent was not
present during the duration of the survey,
did not speak English or French, or could
not participate in the survey due to a
physical or mental condition.16 In the
CCHS, proxy respondents were not
allowed for certain questions. In both the
CCHS and PALS, individuals living on
Indian Reserves, Canadian Forces Bases,
and institutions were excluded from the
sampling frame.15,16
Permission was obtained from Statistics
Canada to use the survey master files at
the Queen’s University Research Data
Centre. Ethical approval was obtained
from the Queen’s University Research
Ethics Board.
Measurement of dual diagnosis
To estimate the proportion of adults
with intellectual disabilities, the CCHS
asked: “Do you have autism or any other
developmental disorder such as Down’s
syndrome, Asperger’s syndrome or Rett
syndrome?”17 The PALS, in turn, asked the
question: “Has a doctor, psychologist or
other health professional ever said that
you had a developmental disability or
disorder?”18 Conditions such as Down
syndrome, autism, Asperger syndrome
and mental impairment due to a lack of
oxygen at birth were included as examples
for the PALS respondents.
To classify an individual as having a
dual diagnosis, the question assessing
intellectual disability was cross-tabulated
with questions in the survey that assessed
self-reported mental illness. In the CCHS,
mental illness was defined as having
one or more of the following conditions:
schizophrenia; mood disorders—depression,
bipolar disorder, mania or dysthymia;
anxiety disorders—phobia, obsessivecompulsive disorder or panic disorder;
and eating disorders—anorexia or bulimia.17
In the PALS, mental illness was assessed
by asking respondents about emotional,
psychological or psychiatric conditions
that had lasted or were expected to
last for 6 months or more.18 These
conditions included phobias, depression,
schizophrenia, and drinking/drug problems.
coefficient of variation scores greater
than 33.3% are not recommended for
release by Statistics Canada.15,16
Data analysis
Measurement of demographic variables
The analysis included data regarding
respondents’ sex, age and province of
residence. Only individuals aged 18 years
or older were included. Data regarding
province of residence were grouped to create
five geographical areas: British Columbia
and Alberta, Saskatchewan and Manitoba,
Ontario, Quebec, and the Atlantic Provinces
(New Brunswick, Nova Scotia, Prince
Edward Island, Newfoundland and
Labrador). Yukon, Northwest Territories
and Nunavut were excluded due to low
cell counts.
We calculated the proportion of individuals
with an intellectual disability in the
whole population. Age- and sex-specific
proportions of intellectual disability by
geographic region were determined.
Proportions were also calculated for each
overall geographical region. The percentage
of individuals with an intellectual disability
who have a co-morbid psychiatric or
behavioural condition was also determined,
along with 95% CIs.
Results
Prevalence of intellectual disabilities
in Canada
Data management
For both surveys, responses where the
answer was “refusal,” “don’t know” or
“not stated” were not included in the
analysis. SPSS software version 6.0 for
Sun Ray Microsystems was used to analyze
the national surveys. Data with cell counts
less than 5 or 10 for the CCHS or PALS,
respectively, were suppressed and the estimates not released due to confidentiality.
Appropriate population weights were
applied to the data. In order to calculate
the 95% confidence intervals (CIs) for
the prevalence estimates in the CCHS,
bootstrap weights and Statistics Canada’s
BOOTVAR macros were used for SPSS
software version 14.0 (SPSS, Chicago, IL).
For the PALS, bootstrap weights were
used for STATA version 10.0 software
(StataCorp LP, College Station, Texas).
When assessing data quality, the coefficient
of variation was calculated for each estimate
by dividing the standard error of the
estimate by the estimate itself, in accordance with Statistics Canada data release
procedures. The quality of the estimate
was quantified by Statistics Canada based
on the size of the coefficient of variation
as a small value corresponds to smaller
variability in the sample population.15
Estimates with coefficient of variation scores
between 16.5% and 33.3% should be
considered with caution due to the
high sampling variability. Estimates with
195
Using the CCHS, Cycle 3.1 (2005), 51 655 or
0.2% (0.17%–0.26%) of the Canadian
adult population is estimated to have an
intellectual disability (Table 1). The estimate
is higher when using the PALS (2006):
0.5% (0.43%–0.56%) representing 112 919
individuals. In the CCHS, the prevalence
of intellectual disability was 0.2% for both
men (0.18%–0.30%) and women (0.12%–
0.25%, high sampling variability). These
proportions are higher in the PALS, where
0.6% (0.47%–0.68%) of the men and
0.4% (0.34%–0.50%) of the women have
an intellectual disability. When analyzed
by age, the proportion of individuals with
an intellectual disability is higher in the
PALS as compared to the CCHS for most
age groups. In the PALS, 35% of those
with an intellectual disability are under
35 years of age. A significantly lower
proportion of individuals in the oldest age
group (65+ years old) have an intellectual
disability when compared to the other age
groups in the PALS.
The geographical distribution of individuals
with an intellectual disability across Canada
shows a similar pattern in both surveys,
but the CCHS estimates tended to be of poor
quality. In the PALS, the estimates in British
Columbia and Alberta, Saskatchewan and
Manitoba, Ontario, and the Maritime
Provinces ranged from 0.5%–0.6%.
Individuals residing in Quebec had the
Vol 32, No 4, September 2012 – Chronic Diseases and Injuries in Canada
Table 1
Proportion of Canadian population with an intellectual disability by sex, age and geographical area: CCHS (2005) and PALS (2006)
CCHS
Sex
Male
Female
Age, years
18–19
20–24
25–34
35–44
45–54
55–64
65+
Geographical area
Newfoundland, Prince Edward Island,
Nova Scotia and New Brunswick
Quebec
Ontario
Saskatchewan and Manitoba
British Columbia and Alberta
Total
PALS
Number
% (95% CI)
Number
% (95% CI)
28 484
23 171
0.2 (0.18, 0.30)
0.2a (0.12, 0.25)
63 582
49 337
0.6 (0.47, 0.68)
0.4 (0.34, 0.50)
—
(0.32, 0.79)
(0.20, 0.50)
(0.10, 0.23)
(0.09, 0.28)
(0.01, 0.07)
(0.03, 0.13)
6 288
13 871
19 798
21 603
25 623
18 858
6 879
0.8
0.7
0.5
0.5
0.5
0.6a
0.2a
0.3a (0.15, 0.39)
11 027
0.6 (0.56, 0.74)
(0.09, 0.24)
(0.13, 0.28)
(0.13, 0.41)
(0.15, 0.33)
(0.17, 0.26)
21 962
45 913
9 054
24 963
112 919
—
12 351
14 606
8 404
8 751
1 436
3 145
4 931
9 623
19 377
4 118
13 607
51 655
0.6a
0.4a
0.2a
0.2a
< 0.1a
< 0.1a
0.2a
0.2a
0.3a
0.2a
0.2
0.4
0.5
0.6
0.5
0.5
(0.55, 1.00)
(0.59, 0.82)
(0.39, 0.65)
(0.37, 0.57)
(0.37, 0.72)
(0.27, 0.85)
(0.09, 0.28)
(0.28, 0.49)
(0.38, 0.67)
(0.51, 0.76)
(0.38, 0.56)
(0.43, 0.56)
Abbreviations: CCHS, Canadian Community Health Survey; CI, confidence interval; PALS, Participation and Activity Limitation Survey.
Note: Estimates are adjusted using bootstrap weights.
a
The estimate is considered to be of poor quality due to high sampling variability.
lowest prevalence estimate (0.4%), which
was
statistically
significant
when
compared to the estimates from other
geographical areas.
proportion of individuals with a dual
diagnosis ranged from 37% to 49% by
geographical area and the estimates were
not statistically significantly different from
each other.
Dual diagnosis in Canada
Quality of survey estimates
The CCHS estimates the proportion of
adults with an intellectual disability
who have a dual diagnosis to be 30.6%
(95% CI: 21.1%–40.0%) representing
15 783 Canadians (Table 2). This proportion
was slightly higher in the PALS at 44.3%
(95% CI: 37.5%–51.1%) representing
50 053 Canadians. The remaining CCHS
estimates were of poor quality with high
coefficient of variation scores limiting their
publication. In the PALS, the prevalence
estimates of dual diagnosis were 46.9%
(95% CI: 37.1%–56.7%) for men and 41.0%
(95% CI: 31.5%–50.5%) for women.
However, the confidence intervals were
very wide, indicating poor precision. The
proportion of individuals with a dual
diagnosis was lower in the youngest age
group (aged 18–19 years), although this
was not statistically significant. In addition,
the estimate was of marginal or poor
quality. The remaining estimates did not
differ significantly from each other. The
A substantial number of the estimates
derived from the national surveys were of
poor or unacceptable quality due to high
sampling variability, and therefore
conclusions could not be drawn from
them. This was especially true for the
CCHS data where only 3 of the estimates
were of reportable quality, 19 were of
marginal or poor quality and 6 were of
unacceptable quality and could not be
released. In comparison, 27 estimates from
the PALS were of reportable quality with
only 5 being of marginal or poor quality.
Discussion
Identifying the population with
intellectual disabilities
Both the CCHS and PALS reported a
prevalence of intellectual disabilities
considerably lower than the reported
Vol 32, No 4, September 2012 – Chronic Diseases and Injuries in Canada
196
population prevalence, especially when
compared to the estimates when children
are included. A recent meta-analysis
of 52 studies (cohort, case control, crosssectional studies) found the prevalence
of intellectual disability to be 1.04%,
with lower rates among adults (0.49%).5
According to the CCHS, 0.2% of Canadians
reported an intellectual disability, while in
the PALS this prevalence estimate was 0.5%.
The prevalence estimates were dissimilar
due to differences in the sample populations
participating in the surveys and the
manner in which information was collected
for the surveys. The PALS included individuals who reported activity limitations
on the Canadian census, while the CCHS
was based on the selected households that
replied to the survey.
Additionally, the PALS could have
increased the likelihood of a person with
an intellectual disability being included
in the survey as it allowed proxy respondents to complete the entire survey on
behalf of the selected individuals. In
comparison, the CCHS restricted the type
of questions that could be answered by
proxy respondents. The proxy respondents
needed to be familiar with the challenges
Table 2
Proportion of adults with intellectual disabilities with a dual diagnosis by sex, age and geographical area: CCHS (2005) and PALS (2006)
CCHS
Sex
Male
Female
Age, years
18–19
20–24
25–34
35–44
45–54
55+
Geographical area
Newfoundland, Prince Edward Island,
Nova Scotia, New Brunswick
Quebec
Ontario
Saskatchewan, Manitoba
British Columbia, Alberta
Total
PALS
Number
% (95% CI)
Number
% (95% CI)
8 594
7 189
30.2a (19.8, 40.5)
31.0a (15.1, 46.9)
29 826
20 227
46.9 (37.1, 56.7)
41.0 (31.5, 50.5)
—
—
—
2 626
3 936
—
—
—
—
31.3a (14.8, 47.7)
45.0a (18.1, 71.9)
—
1 886
5 599
9 063
10 916
12 418
10 171
30.0a
40.4
45.8
50.5
48.5a
39.5a
1 970
40.0a (17.8, 62.1)
4 021
—
4 266
—
22.0a (8.2, 35.9)
5 914
43.5a (24.4, 62.5)
15 783
30.6 (21.1, 40.0)
10 066
19 758
3 884
12 323
50 053
(17.2, 42.8)
(32.5, 48.3)
(33.0, 58.6)
(40.0, 61.1)
(31.2, 65.7)
(20.5, 58.6)
36.5 (29.5, 43.5)
45.8
43.0
42.9
49.4
44.3
(31.1, 60.6)
(29.3, 56.8)
(32.2, 53.7)
(39.8, 58.9)
(37.5, 51.1)
Abbreviations: CCHS, Canadian Community Health Survey; CI, confidence interval; PALS, Participation and Activity Limitation Survey.
Note: Estimates are adjusted using bootstrap weights.
a
The estimate is considered of poor quality due to high sampling variability.
However, both of the national surveys
found that the estimates of the proportion
of adults with a dual diagnosis are similar
to those reported in the literature. In studies
that surveyed service recipients, 28% to
31% of individuals with intellectual
disabilities had a concurrent mental
health problem.21-23
and difficulties the person faced due to
the disability.16 Overall, 12.1% of the
sample over the age of 15 years completed
the PALS using a proxy respondent. Close
to 60% of the subjects who completed
the survey by a proxy respondent cited
an inability to participate due to a
physical or mental condition.16 In contrast,
less than 2% of the sample in the CCHS
completed the survey using a proxy
respondent.19
Use of national surveys for mental
health surveillance
The prevalence estimates presented by
CCHS and PALS data are likely lower
than expected due to the population
frame used. Both national surveys
excluded individuals living in institutions
and long-term care facilities. In 2003,
an estimated 20 000 individuals with
intellectual disabilities resided in healthrelated institutions across Canada and
an additional 12 000 lived in institutional
facilities specifically for people with
intellectual disabilities.20 Therefore, it
is likely that a large portion of the
population with intellectual disabilities
was ineligible to participate in the national
surveys, thereby lowering the estimate of
the prevalence of intellectual disabilities
in Canada from such surveys.
Although it was possible to determine
the overall prevalence of intellectual
disabilities among adults in the CCHS
(0.2%) and in the PALS (0.5%), it is
possible that the samples were biased
because of the low prevalence of intellectual disability detected and the method
of respondent selection, raising concerns
about the generalizability of the estimates.
The prevalence rates of intellectual disability
by sex, age and geography were of poor
quality from the CCHS due to high sampling
variability and could not be reported. Some
prevalence rates (sex and geography) could
be determined from the PALS, although age
comparisons, particularly in the older age
groups, were also of poor quality. Both
surveys were able to determine the overall
197
prevalence of dual diagnosis but were of
limited use for more detailed analyses. Of
the two surveys, the best approach for
estimating the prevalence of intellectual
disabilities and the proportion of these
individuals with a dual diagnosis was
through the PALS. These estimates are
of higher quality because they had lower
coefficients of variation, and the survey
included proxy respondents, which potentially allowed the inclusion of people with
severe intellectual disabilities in the survey.
The data from the CCHS were mostly of poor
quality, which limits the use of this survey.
Limitations of the surveys
Individuals with intellectual disabilities
may be under-represented by the national
surveys as the sampling frames exclude
those who lived in institutions, such as
long-term care facilities and hospitals.15,16
The sampling frame used in the PALS may
cause selection bias, as individuals with
activity limitations who live in the
community are chosen to participate.
Moreover, individuals who do not indicate
having activity limitations on the census
are not included in the PALS sampling
frame. Therefore, individuals with a mild
Vol 32, No 4, September 2012 – Chronic Diseases and Injuries in Canada
intellectual disability and those who are
not aware of their limitations may be
missed. As a result, individuals with a
very mild intellectual disability or a severe
or profound intellectual disability may
be missed, while those with mild or
moderate intellectual disability may be
over-represented.
Additionally, questions used to assess
intellectual disability and mental health
varied across the surveys. As a result,
differing populations could have been
classified as having an intellectual disability
and co-morbid psychiatric or behavioural
conditions, hence limiting comparability
across the surveys. The level of intellectual
disability, which is related to the prevalence
of psychopathology,12,22,24 was not assessed
in any of the surveys.
Another limitation of using the national
survey data is the inability to investigate
numerous factors associated with intellectual disabilities and mental health due
to low cell counts and data suppression.
However, the major limitation of using
national survey data is the quality of the
estimates that are produced as measured
by the coefficient of variation. Some of the
reported estimates from the national surveys
were of marginal, poor or unacceptable
quality due to high sampling variability,
which would limit the generalizability of
the results. This limited the conclusions
that could have been made about the
data, particularly those in the CCHS.
Strengths of the study
To the best of our knowledge, this is
the first study to examine data from two
national surveys—CCHS (2005) and PALS
(2006)—to assess the prevalence of intellectual disabilities and dual diagnosis in
Canada. The results highlight the gaps
in knowledge regarding the prevalence of
intellectual disabilities in Canada and the
proportion of these individuals with a dual
diagnosis. However, selection bias and data
quality must be taken into account when
applying the results to the population
with intellectual disabilities. Secondly, the
variables used in the survey are available
and accessible for analysis and differences
across future surveys can be examined.
As a result, this study can be easily
reproduced.
Conclusion
Psychiatric and behavioural conditions are
present in about one-third of the population
with intellectual disabilities, as shown by
the two surveys examined. Among the
surveys, the PALS presented the highest
quality of data regarding the population
with a dual diagnosis. It has recently been
reported that the PALS will not be funded
by Human Resources and Skills Development
Canada in 2011, and a new strategy for
monitoring people with disabilities is to
replace the survey.25,26 The collection of data
on individuals with intellectual disabilities
is of importance as Canada ratified the
United Nations Convention on the Rights
of Persons with Disabilities in 2010.27 The
new strategy should ensure that subgroups
of the population with disabilities, such as
individuals with intellectual disabilities,
are properly identified and that their health
status is validly and reliably ascertained.
Proxy responses from family members or
caregivers should be allowed. In addition, the
new strategy should consider identifying
individuals residing in institutions. Oversampling of adults whose disabilities onset
in childhood will be required to ensure
adequate representation in the surveys.
Tools that have been validated to assess
psychopathology among adults with
intellectual disabilities may be considered,
especially among those individuals with
moderate or severe intellectual disability.
Acknowledgements
Iwona Bielska was supported by the
R.S. McLaughlin and the Empire Life
Fellowships, as well as the South Eastern
Ontario Community-University Research
Alliance in Intellectual Disabilities (SEO
CURA in ID). Funding for SEO CURA in ID
was provided through a grant from the
Social Sciences and Humanities Research
Council of Canada (SSHRC #833-200031008). The views expressed in this article are
not necessarily the views of all SEO CURA
Vol 32, No 4, September 2012 – Chronic Diseases and Injuries in Canada
198
in ID partners, researchers, collaborators
or of SSHRC. While the research and
analysis are based on data from Statistics
Canada, the opinions expressed are those
of the authors and do not necessarily
represent the views of Statistics Canada.
The authors declare no conflict of interest.
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199
Vol 32, No 4, September 2012 – Chronic Diseases and Injuries in Canada
Cardiovascular disease mortality among First Nations people
in Canada, 1991–2001
M. Tjepkema, MPH (1); R. Wilkins, MUrb (1,2); N. Goedhuis, BSc (3); J. Pennock, MSc (3)
This article has been peer reviewed.
Abstract
Objective: To compare cardiovascular disease mortality patterns between First Nations
people and non-Aboriginal adults by sex and by income adequacy quintile and level of
educational attainment.
Methods: A 15% sample of 1991 Canadian census respondents aged 25 years or older
was previously linked to 11 years of mortality data. In this study, First Nations people
were defined by North American Indian ethnic origin (ancestry), registration under the
Indian Act, and/or membership in an Indian band or First Nation. The cohort included
62 400 First Nations people and 2 624 300 non-Aboriginal people.
Results: Compared to non-Aboriginal cohort members, the age-standardized cardiovascular
disease mortality rate was 30% higher for First Nations men and 76% higher for
First Nations women. This represented an excess of 58 deaths and 71 deaths per
100 000 person-years at risk, for First Nations men and women, respectively. Within
each income adequacy quintile (adjusted for family size and region of residence) and
level of educational attainment, the risk of dying from cardiovascular disease was higher
for First Nations people compared to their non-Aboriginal counterparts.
Conclusion: First Nations people had higher rates of death from cardiovascular disease
than non-Aboriginal Canadians within each income quintile and level of education.
Income and education accounted for 67% and 25% of the excess mortality of First
Nations men and women respectively.
Keywords: indigenous, Registered Indian, non-status Indian, Aboriginal, income, education
Introduction
Indigenous peoples worldwide experience a
disproportionate burden of disease and
illness.1,2 Historically, infectious diseases were
largely responsible for the poorer health of
Aboriginal people.3 However, since the 1960s
the Aboriginal population has undergone
an epidemiological transition during which
the prevalence of non-communicable
diseases such as diabetes and cardiovascular disease has increased while that of
infectious diseases has decreased.4,5
Cardiovascular disease is a major cause of
premature death, admissions to hospitals
and disability,6 and it imposes a large burden
on the health care system.7 Survey data
have demonstrated that the prevalence of
self-reported heart disease is higher among
First Nations people residing on-reserve,8
and similar for Aboriginal (including First
Nations, Métis and Inuit) people residing
off-reserve, compared to the non-Aboriginal
population.9 However, results based on
self-reporting may not reflect the true extent
of the disparities between First Nations
people and other Canadians.10 A more
fundamental indicator of disease burden
and one which is more reliable for tracking
trends over time could be based on mortality
rates. In Canada, death registrations usually
contain no First Nations identifiers, so either
a record linkage or an area-based approach
is required. Studies that have linked
lists of Registered Indians (First Nations
individuals who are registered under the
Indian Act of Canada) to vital statistics death
registrations have shown that Registered
Indians had higher rates of cardiovascular
disease mortality than other Canadians.5,11,12
However, those studies excluded people who
self-identify as First Nations but are not
registered under the Indian Act (“non-Status
Indians”) and provided no information on
whether differences in socio-economic
status played a role in explaining the
disparities.
An estimated 80% of premature cardiovascular disease can be prevented,7 so it
should be possible to considerably reduce
the burden of cardiovascular disease. A
target for 2020 described as “ambitious
but achievable” in the Canadian Heart
Healthy Strategy and Action Plan7 is to
decrease the burden of cardiovascular
diseases among Aboriginal people to the
same level as that for other Canadians. To
monitor progress towards that goal, it
will be necessary to track cardiovascular
disease mortality among all Aboriginal
peoples, including First Nations, Inuit and
Métis. The objective of this study is to
assess the burden of cardiovascular disease
mortality for First Nations people, including
both Status and non-Status Indians,
and to compare the rates to those of
Author references:
1. Health Analysis Division, Statistics Canada, Ottawa, Ontario, Canada
2. Department of Epidemiology and Community Medicine, University of Ottawa, Ottawa, Ontario, Canada
3. First Nations and Inuit Health Branch, Health Canada, Ottawa, Ontario, Canada
Correspondence: Michael Tjepkema, Health Analysis Division, Statistics Canada, RHC-24Q, 100 Tunney’s Pasture Driveway, Ottawa, ON K1A 0T6; Tel.: (613) 951-3896; Fax: (613) 951-3959;
Email: michael.tjepkema@statcan.gc.ca
Vol 32, No 4, September 2012 – Chronic Diseases and Injuries in Canada
200
non-Aboriginal adults by sex and by
income adequacy quintile and level of
educational attainment.
Methods
Data source
This study is a secondary analysis of data
from the 1991–2001 Canadian census
mortality follow-up study.13 Individuals were
eligible to be in the original study cohort
if they were aged 25 years or more and
enumerated by the 1991 census long-form
questionnaire, which excluded institutionalized residents. To be followed for
mortality, in-scope census respondents first
had to be linked to an encrypted name file
abstracted from non-financial tax-filer data.
About 80% of in-scope census records
(n = 2 860 244) were linked to the name
file. A random sample of respondents
(n = 125 093) were then removed so that
the final cohort (n = 2 735 152) would be
a 15% sample of the Canadian population,
as stipulated in the record linkage protocol.
This cohort was then matched to the
Canadian mortality database (4 June 1991
to 31 December 2001) using probabilistic
record linkage methods primarily based on
names and dates of birth.14,15 Ascertainment
of death was estimated to be slightly lower
(95% to 96%) among First Nations cohort
members, compared with the cohort as a
whole (97%). Additional details of the
construction and contents of the previously
linked file are reported elsewhere.13 In our
study we compared cardiovascular disease
mortality patterns between First Nations
people and non-Aboriginal adults by sex and
by income adequacy quintile and level of
educational attainment.
The Canadian census mortality follow-up
study was approved by the Statistics Canada
Policy Committee after consultations with
the Statistics Canada Confidentiality and
Legislation Committee, the Data Access and
Control Services Division, and the Federal
Privacy Commissioner.
Definitions
For the purposes of this study, we defined
First Nations people as census respondents
who either reported one ancestry, North
American
Indian,
or
indicated
being registered under the Indian Act, or
indicated being a member of an Indian
Band or First Nation. About three-quarters
of the First Nations cohort members met all
three criteria. About 9% of First Nations
cohort members did not indicate being a
Registered Indian.
Non-Aboriginal cohort members included
anyone except those whose census responses
indicated North American Indian, Métis or
Inuit ancestry, Registered Indian status or
membership in a North American Indian
band or First Nation. Cohort members
not defined as either First Nations or
non-Aboriginal were excluded from this
analysis.
A First Nations community (or Indian
reserve) refers to land set aside by the
Federal Government for the use and
occupancy of an Indian group or band.
Level of education was grouped into
two categories: less than high school
diploma and high school diploma (or
trades certificate) or higher.
Quintiles of population by income
adequacy were constructed as follows.
First, for each economic family or
unattached individual, total pre-tax,
post-transfer income from all sources
was pooled across all family members,
and the ratio of total income to the
Statistics Canada low-income cut-off for
the applicable family size and community
size group was calculated.16 Thus, all
members of a given family were assigned
the same ratio, which was calculated
for all non-institutionalized people (the
in-scope population), including people
living on Indian reserves. The population
was then ranked according to that
ratio, and quintiles of population were
constructed within each census metropolitan area, census agglomeration or
total rural and small-town area within a
given province or territory. The purpose
of constructing the quintiles within
each area was to take account of regional
differences in housing costs, which were
not reflected in the low income cut-offs.
For this analysis, quintiles 4 and 5 were
grouped due to the small number
of First Nations respondents in those
categories.
201
Analytical techniques
For each member of the cohort, we
calculated person-days of follow-up from the
beginning of the study (4 June 1991) to
the date of death, the date of emigration
(which was only known for 1991), or to
the end of study (31 December 2001). For
each category of cardiovascular disease,
we first calculated age- and sex-specific
mortality rates by 5-year age groups (at
baseline), and then, using the total Aboriginal
cohort population structure (person-years
at risk) as the standard population (an
internal weighting scheme), we calculated
age-standardized mortality rates (ASMRs)
for each disease group, by sex and for
subgroups of the population. Rate ratios
(RRs) and rate differences (RDs) were
calculated comparing the ASMRs for First
Nations to those of non-Aboriginal cohort
members. The rate difference was our
measure of excess mortality. We calculated
95% confidence intervals (CIs) for the
ASMRs, RRs and RDs based on a Poisson
distribution.
Cox proportional hazard ratios for death by
cardiovascular disease were calculated for
First Nations compared to non-Aboriginal
cohort members, by sex, first controlling for
age (in years), then controlling for age and
education (less than high school diploma
versus high school diploma or higher), then
controlling for age and income adequacy
(quintiles 1, 2 and 3 compared to quintiles 4
and 5 combined). The final, fully adjusted
model controlled for age, education and
income adequacy (simultaneously). We
interpreted differences in the hazard ratios
between the age-adjusted model and the
fully adjusted model as estimates of the
effect of education and income on the extent
of disparities between First Nations and
non-Aboriginal adults. The proportion of
excess mortality explained by differences
in education and income was calculated as
the difference between the age-adjusted and
the fully adjusted hazard ratios, divided
by the age-adjusted hazard ratio minus 1.
The cause of death of those who died
in the years 1991 to 1999 had been
previously coded using the World Health
Organization’s International Classification
of Diseases, Ninth Revision (ICD-9) codes,
and that of those who died in 2000 or 2001
Vol 32, No 4, September 2012 – Chronic Diseases and Injuries in Canada
Table 1
Selected characteristics of First Nations and non-Aboriginal men and women,
non-institutional cohort members aged 25 years or older at baseline, Canada, 1991
had been previously coded using the Tenth
Revision (ICD-10) codes. We grouped the
ICD codes as follows: all cardiovascular
diseases (ICD-9 390–459; ICD-10 I00–I99),
ischemic heart disease (ICD-9 410–414;
ICD-10 I20–I25), acute myocardial infarction
(ICD-9 410; ICD-10 I21–I22), cerebrovascular
disease (ICD-9 430–438; ICD-10 I60–I69),
stroke (ICD-9 430, 431, 434, 436; ICD-10
I60, I61, I63, I64), congestive heart failure
(ICD-9 428.0; ICD-10 I50.0), inflammatory
heart disease (ICD-9 420–422, 425; ICD-10
I30–I33, I38, I40, I42), rheumatic heart
disease (ICD-9 390–398; ICD-10 I01–I09),
and hypertensive heart disease (ICD-9
401–405; ICD-10 I10–I13).
First Nations
Number
Women
Men
Women
27 300
35 100
1 307 800
1 316 500
100
100
100
100
41
44
27
28
Percentage
Age group (years), %
25–34
35–44
28
28
26
26
45–54
16
15
18
17
55–64
9
8
14
12
65–74
5
4
10
10
75–84
2
2
4
5
<1
<1
1
1
85+
Results
Province, region or territory of residence, %
Atlantic Canadaa
The cohort follow-up tracked mortality
for 27 300 First Nations men, 1 307 800
non-Aboriginal men, 35 100 First Nations
women and 1 
316 
500 non-Aboriginal
women. Compared to non-Aboriginal cohort
members, First Nations cohort members
tended to be younger, with a lower level
of formal education, less income and
more often lived in western Canada and
the north (Table 1).
Cardiovascular disease deaths accounted for
29% and 27% of all deaths among First
Nations men and women, respectively.
Ischemic heart disease was the most
common type of cardiovascular disease
mortality (62% of all cardiovascular
disease deaths for First Nations men;
45% for First Nations women), followed
by cerebrovascular disease (14% for
First Nations men; 25% for First Nations
women). Compared to non-Aboriginal
cohort members, the risk of dying from
cardiovascular disease was 30% higher
among First Nations men and 76% higher
among First Nations women. This
translates into an additional 58 deaths
per 100 000 person-years at risk for First
Nations men and an additional 71 deaths
per 100 000 person-years at risk for First
Nations women (Table 2).
Compared to non-Aboriginal cohort
members, the relative risk of dying was
particularly elevated among First Nations
men and women for rheumatic heart
disease (RR = 3.8 and 2.9, respectively),
congestive heart failure (RR = 2.2 and 3.2,
Non-Aboriginal
Men
Quebec
5
5
8
8
12
13
26
26
Ontario
18
17
37
37
Manitoba
18
16
4
4
Saskatchewan
12
13
4
3
9
11
9
9
20
19
12
12
6
5
1
0
Yes
67
63
0
0
No
33
37
100
100
Less than high school graduation
59
55
34
34
Alberta
British Columbia
Territoriesb
Residing in a First Nations community, %
Educational attainment, %
High school graduation
33
29
38
35
Post-secondary diploma
7
13
13
19
University degree
2
3
15
12
Income adequacy quintile, %
Quintile 1 – lowest
38
42
14
19
Quintile 2
26
25
19
19
20
Quintile 3
18
17
21
Quintile 4
12
11
23
20
6
6
23
21
Quintile 5 – highest
Source: 1991–2001 Canadian census mortality follow-up study.
Note: Counts have been rounded to the nearest 100.
a
New Brunswick, Prince Edward Island, Nova Scotia and Newfoundland and Labrador.
b
Yukon, Northwest Territories and Nunavut.
respectively), inflammatory heart disease
(RR = 1.7 and 2.3, respectively), stroke
(RR = 1.3 and 2.0, respectively) and
hypertensive heart disease (RR = 2.1 for
First Nations women) (Table 2).
RDs, a measure of absolute burden, indicate
that ischemic heart disease accounted for
Vol 32, No 4, September 2012 – Chronic Diseases and Injuries in Canada
202
the majority of excess mortality due to
cardiovascular disease (61% of the RD)
for First Nations men whereas both
ischemic heart disease (36% of the RD)
and cerebrovascular disease (29% of
the RD) were the largest contributors to
such excess mortality for First Nations
women (Table 2).
Table 2
All cardiovascular disease deaths by sub-type, age-standardized mortality rate per 100 000 person-years at risk,
rate ratios and rate differences per 100 000 persons-years at risk for First Nations men and women compared to non-Aboriginal
men and women, by age groups, non-institutional cohort members aged 25 years or older at baseline, Canada, 1991–2001
First Nations
Deaths % of all
CVD
deaths
Men
All causes
All cardiovascular disease
Ischemic heart disease
Acute myocardial
infarction
Cerebrovascular disease
Stroke
Other cardiovascular
diseases
Congestive heart failure
Inflammatory heart
diseases
Rheumatic heart disease
Hypertensive heart
disease
Women
All causes
All cardiovascular disease
Ischemic heart disease
Acute myocardial
infarction
Cerebrovascular disease
Stroke
Other cardiovascular
diseases
Congestive heart failure
Inflammatory heart
diseases
Rheumatic heart disease
Hypertensive heart
disease
ASMR
Non-Aboriginal
95% CI
852.4,
233.0,
143.2,
72.6,
Deaths
% CVD
deaths
ASMR
920.3 149 335
268.6 55 514
171.5 34 383
93.1 18 270
—
100.0
61.9
32.9
566.7
192.5
121.4
65.9
First Nations compared to non-Aboriginal
95% CI
2 633
763
476
250
—
100.0
62.4
32.8
885.7
250.2
156.7
82.2
109
95
178
14.3
12.5
23.3
35.3
30.7
58.1
29.3, 42.7
25.1, 37.6
50.2, 67.4
8 638
7 209
12 493
15.6
13.0
22.5
28.2
23.7
43.0
34
23
4.5
3.0
10.8
7.6
7.7, 15.1
5.0, 11.4
1 670
1 033
3.0
1.9
5.0
4.5
4.7,
4.2,
9
8
1.2
1.0
3.1
2.5
1.6,
1.3,
216
731
0.4
1.3
0.8
2.5
2 317
628
280
147
—
100.0
44.6
23.4
622.3
164.9
73.5
38.8
597.4,
152.5,
65.3,
33.0,
648.2 103 890
178.4 39 066
82.6 20 098
45.6 10 009
—
100.0
51.4
25.6
318.9
94.0
48.1
25.1
157
139
81
25.0
22.1
12.9
41.7
37.0
49.8
35.6, 48.7
31.3, 43.7
43.2, 57.4
8 835
7 611
10 133
22.6
19.5
25.9
21.4
18.7
24.5
41
13
6.5
2.1
10.3
3.5
7.6, 14.0
2.1, 6.1
1 714
439
4.4
1.1
3.2
1.6
3.0,
1.4,
12
15
1.9
2.4
3.2
4.0
389
862
1.0
2.2
1.1
1.9
1.0,
1.8,
1.8,
2.4,
5.9
5.1
5.7
6.7
563.4,
190.8,
120.0,
64.9,
RR
95% CI
RD
95% CI
284.9, 353.1
39.8, 75.6
21.2, 49.5
6.0, 26.6
569.9
194.3
122.8
67.0
1.56
1.30
1.29
1.25
1.50,
1.21,
1.18,
1.10,
1.62
1.40
1.41
1.41
319.0
57.7
35.3
16.3
27.5, 28.8
23.1, 24.3
42.1, 43.8
1.25
1.30
1.35
1.04, 1.52
1.06, 1.59
1.17, 1.57
7.2
7.1
15.2
0.5,
0.8,
6.6,
13.9
13.3
23.8
5.2
4.8
2.18
1.68
1.55, 3.06
1.11, 2.55
5.8
3.1
2.2,
0.0,
9.5
6.2
0.7,
2.3,
0.9
2.7
3.83
1.04
1.96, 7.49
0.52, 2.08
2.3
0.1
0.3,
−1.7,
4.3
1.9
316.5,
92.9,
47.3,
24.6,
321.2
95.1
48.8
25.7
1.95
1.76
1.53
1.54
1,87,
1.62,
1.36,
1.31,
2.03
1.90
1.72
1.82
303.4
71.0
25.4
13.6
20.9, 21.9
18.2, 19.2
23.9, 25.1
1.95
1.98
2.03
1.66, 2.28
1.67, 2.34
1.76, 2.35
20.3
18.3
25.3
13.7,
12.1,
18.2,
26.8
24.4
32.4
3.4
1.7
3.23
2.27
2.36, 4.40
1.30, 3.96
7.1
2.0
3.9,
0.0,
10.3
3.9
1.3
2.1
2.88
2.07
1.62, 5.14
1.24, 3.46
2.1
2.1
0.3,
0.0,
4.0
4.1
277.9, 328.9
58.0, 84.0
16.7, 34.1
7.3, 19.9
Source: 1991 to 2001 Canadian census mortality follow-up study.
Abbreviations: ASMR, age-standardized mortality rate; CI, confidence interval; CVD, cardiovascular disease; RD, rate difference; RR, rate ratio.
Note: Reference population (person-years at risk) for age standardization was taken from the Aboriginal age distribution (5 -year age groups).
ASMRs for cardiovascular disease mortality
were highest for First Nations people
residing in the Atlantic region (New
Brunswick, Prince Edward Island, Nova
Scotia, Newfoundland and Labrador) and
Manitoba, and lowest for those residing in
Quebec and the territories (Yukon,
Northwest Territories, Nunavut) (Table 3).
The ASMRs for cardiovascular disease were
similar among First Nations people regardless of residence on- or off-reserve (Table 3).
The relative risk of dying from cardiovascular
disease (compared to non-Aboriginal cohort
members) was highest in the younger age
groups and diminished with age (Figure 1).
For First Nations people aged 25 to 34 years
at baseline, the risk of dying from cardiovascular disease was 62% higher for men and
217% higher for women compared to their
non-Aboriginal counterparts. By contrast the
relative risk of dying from cardiovascular
disease was slightly lower for First Nations
men aged 75 years or older and similar for
First Nations women aged 85 years or older.
For both First Nations and non-Aboriginal
cohort members, ASMRs for cardiovascular
disease were higher for those with less
than a high school diploma compared to
203
those with a high school diploma or higher
(Table 4). Higher relative risks (First Nations
compared to non-Aboriginal) were evident
within both levels of education for both
sexes. For First Nations compared to nonAboriginal men, relatively higher RRs and
RDs were observed for those with a high
school diploma or higher. For First Nations
compared to non-Aboriginal women, RRs
and RDs were similarly elevated regardless
of level of educational attainment (Table 4).
By income adequacy quintile, cardiovascular disease mortality rates showed a
stair-stepped gradient (with the lowest
Vol 32, No 4, September 2012 – Chronic Diseases and Injuries in Canada
Table 3
All cardiovascular disease deaths, age-standardized mortality rates per 100 000 person-years at risk, rate ratios and rate
differences per 100 000 person-years at risk comparing First Nations men and women to non-Aboriginal men and women,
by selected geographic areas, non-institutional cohort members age 25 years or older at baseline, Canada, 1991–2001
Residence in June 1991
Deaths
Men
Canada
763
39
Atlantic Canadaa
Quebec
57
Ontario
146
Manitoba
195
Saskatchewan
87
Alberta
67
British Columbia
152
20
Territoriesb
Residing in a First Nations community
Yes
550
No
213
Women
Canada
628
Atlantic Canada
36
Quebec
57
Ontario
121
Manitoba
132
Saskatchewan
71
Alberta
57
British Columbia
138
16
Territoriesb
Residing in a First Nations community
Yes
424
No
204
First Nations
ASMR
95% CI
Deaths
Non-Aboriginal
ASMR
95% CI
RR
First Nations compared to non-Aboriginal
95% CI
RD
95% CI
250.2
396.4
164.4
264.8
337.1
252.1
277.9
233.2
98.8
233.0,
270.0,
126.5,
224.9,
292.5,
204.1,
217.2,
198.7,
63.3,
268.6
581.8
213.5
311.8
388.4
311.5
355.7
273.6
154.2
55 514
4 956
13 527
20 854
2 681
2 437
4 090
6 877
92
192.5
214.1
200.0
192.5
201.6
188.2
181.7
169.4
167.8
190.8,
207.7,
196.4,
189.6,
193.1,
179.6,
175.9,
165.0,
133.0,
194.3
220.7
203.6
195.4
210.6
197.3
187.7
173.9
211.7
1.30
1.85
0.82
1.38
1.67
1.34
1.53
1.38
0.59
1.21,
1.26,
0.63,
1.17,
1.44,
1.08,
1.19,
1.17,
0.36,
1.40
2.72
1.07
1.62
1.94
1.66
1.96
1.62
0.97
57.7
182.3
−35.6
72.3
135.4
63.9
96.2
63.8
−69.0
257.6
232.9
236.9, 280.2
203.4, 266.6
—
55 393
—
192.5
—
—
190.7, 194.2
1.34
1.21
1.23, 1.46
1.06, 1.39
65.2
40.4
43.4,
8.9,
86.9
71.9
164.9
244.5
117.4
182.6
212.7
143.6
141.3
183.7
73.7
152.5,
174.0,
90.4,
152.7,
178.9,
113.7,
108.9,
155.0,
43.6,
178.4
343.6
152.4
218.5
252.8
181.4
183.4
217.8
124.8
39 066
3 521
9 064
15 100
2 073
1 619
2 762
4 905
22
94.0
108.8
83.7
98.6
102.4
94.0
94.7
90.4
147.2
92.9,
104.6,
81.7,
96.8,
96.9,
88.3,
90.9,
87.5,
48.1,
95.1
113.2
85.8
100.4
108.3
100.1
98.7
93.4
450.6
1.76
2.25
1.40
1.85
2.08
1.53
1.49
2.03
0.50
1.62,
1.60,
1.08,
1.55,
1.73,
1.20,
1.15,
1.71,
0.15,
1.90
3.16
1.82
2.22
2.49
1.95
1.94
2.42
1.72
71.0
135.7
33.6
84.1
110.2
49.6
46.6
93.3
−73.5
58.0,
52.4,
2.9,
51.3,
73.1,
15.5,
9.6,
61.9,
−242.6,
84.0
219.0
64.4
116.8
147.4
83.7
83.7
124.7
95.7
167.3
162.9
152.0, 184.2
142.0, 186.9
—
39 013
—
93.9
—
—
92.8, 95.0
1.78
1.73
1.62, 1.96
1.51, 1.99
73.4
69.0
57.3,
46.5,
89.5
91.4
39.8, 75.6
30.0, 334.5
−78.8,
7.6
29.0, 115.7
86.8, 184.0
9.9, 117.9
27.4, 165.1
26.2, 101.3
−127.9, −10.2
Source: 1991 to 2001 Canadian census mortality follow-up study.
Abbreviations: ASMR, age-standardized mortality rate; CI, confidence interval; CVD, cardiovascular disease; RD, rate difference; RR, rate ratio.
Note: Reference population (person-years at risk) for age standardization was taken from the Aboriginal age distribution (5 -year age groups).
a
New Brunswick, Prince Edward Island, Nova Scotia and Newfoundland.and and Labrador.
b
Yukon, Northwest Territories and Nunavut.
Figure 1
Cardiovascular disease mortality rate ratios comparing
First Nations to non-Aboriginal cohort members
85+
First Nations men
Age group at baseline
75–84
First Nations women
65–74
55–64
45–54
35–44
25–34
0.50
1.50
2.50
Rate ratio
Vol 32, No 4, September 2012 – Chronic Diseases and Injuries in Canada
3.50
4.50
204
income quintile having the highest
mortality) for both First Nations and
non-Aboriginal cohort members (Table 4).
The mortality gradient was steeper for
non-Aboriginal cohort members than
for First Nations cohort members. Higher
relative risks (First Nations compared to
non-Aboriginal) were evident within each
income strata, with the highest ratios in
the highest income quintile (RR = 1.29 for
First Nations men; RR = 1.91 for First
Nations women).
After adjusting for educational attainment
and income adequacy, the risk of dying
from cardiovascular disease was 8%
higher for First Nations men and 50%
higher for First Nations women (compared
to non-Aboriginal cohort members)
Discussion
dying
from
cardiovascular
disease
compared to non-Aboriginal adults, both
overall and within subgroups classified
by education and income. This study
included First Nations people who
were not registered under the Indian
Act (non-Status Indians), and included
data from all provinces and territories
of Canada.
This study was the first to estimate cardiovascular disease mortality rates for First
Nations people by level of educational
attainment and income adequacy in
Canada. Our results show that First
Nations adults were at higher risk of
The burden of cardiovascular disease
has increased among Aboriginal peoples in
Canada over the past several decades.5,7,17
However, results from British Columbia
indicate that ASMRs for cardiovascular
disease among Status Indians decreased
(Table 5). Compared to the age-adjusted
hazard ratios, the relative risk of dying
from cardiovascular disease (after adjusting
for education and income) was reduced
by 67% (from 1.24 to 1.08) for First
Nations men and by 25% for First Nations
women (from 1.67 to 1.50).
between 1993 and 2006, but the rate
remained 25% higher compared to that of
other residents of British Columbia.12
Research has demonstrated that the
prevalence of traditional cardiovascular
disease risk factors is more common among
First Nations than among non-Aboriginal
people. These include higher rates of
smoking,8,9,18,19 high blood pressure,8,9
obesity,8,20 diabetes,21,22 and poor diet.22-24
In addition to those well-known cardiovascular disease risk factors, it has been
argued that social factors such as education
and income are fundamental determinants
Table 4
All cardiovascular disease deaths, age-standardized mortality rates per 100 000 person-years at risk, rate ratios and rate
differences per 100 000 person-years at risk comparing First Nations men and women to non-Aboriginal men and women, by
selected socio-economic indicators, non-institutional cohort members aged 25 years or older at baseline, Canada, 1991–2001
Characteristic
measured in 1991
Educational attainment
Men
Less than high school diploma
High school diploma or higher
Women
Less than high school diploma
High school diploma or higher
Income adequacy quintile
Men
Quintile 1 – lowest
Quintile 2
Quintile 3
Quintiles 4,5 – highest
Women
Quintile 1 – lowest
Quintile 2
Quintile 3
Quintiles 4,5 – highest
First Nations
Deaths ASMR
95% CI
Non-Aboriginal
Deaths ASMR
95% CI
First Nations compared to non-Aboriginal
RR
95% CI
RD
95% CI
606
157
256.7
231.4
236.3, 278.8
190.6, 281.0
33 776
21 738
227.8
166.4
224.5, 231.1
164.2, 168.7
1.13
1.39
1.04, 1.23
1.14, 1.69
28.9
65.0
7.4, 50.4
20.0, 110.0
530
98
176.3
141.8
161.3, 192.6
108.5, 185.4
25 307
13 759
110.6
79.7
108.6, 112.7
78.3, 81.1
1.59
1.78
1.46, 1.74
1.36, 2.33
65.7
62.1
49.9, 81.4
24.1, 100.2
309
239
116
99
298.4
257.3
222.4
208.0
266.4,
225.0,
185.2,
169.0,
334.3
294.4
267.2
256.0
13 053
15 476
10 088
16 897
273.1
213.4
185.0
161.1
267.3,
209.1,
181.2,
158.6,
279.1
217.8
189.0
163.6
1.09
1.21
1.20
1.29
0.97,
1.05,
1.00,
1.05,
1.23
1.38
1.45
1.59
25.3
44.0
37.4
46.9
−9.1,
9.1,
−3.5,
3.7,
59.7
78.9
78.3
90.2
275
211
81
61
185.5
172.6
142.2
146.7
164.7,
149.8,
113.6,
112.1,
209.0
198.8
178.1
192.0
15 918
9 346
5 559
8 243
127.7
98.6
88.9
76.7
124.5,
96.0,
86.4,
75.1,
131.0
101.3
91.5
78.5
1.45
1.75
1.60
1.91
1.29,
1.51,
1.28,
1.46,
1.64
2.02
2.01
2.50
57.8
74.0
53.3
70.0
35.5,
49.4,
21.2,
30.5,
80.2
98.6
85.4
109.4
Source: 1991 to 2001 Canadian census mortality follow-up study.
Abbreviations: ASMR, age-standardized mortality rate; CI, confidence interval; CVD, cardiovascular disease; RD, rate difference; RR, rate ratio.
Note: Note: Reference population (person-years at risk) for age standardization was taken from the Aboriginal age distribution (5-year age groups).
Table 5
Hazard ratios for dying from cardiovascular disease for First Nations compared to non-Aboriginal cohort members, controlling
for selected socio-economic indicators, non-institutionalized persons aged 25 years or older at baseline, Canada, 1991–2001
Adjusted for:
Age
Age + education
Age + income adequacy
Age + education + income adequacy
Men
Hazard ratio
1.24
1.15
1.13
1.08
95% CI
1.16, 1.34
1.07, 1.24
1.05, 1.21
1.00, 1.16
Hazard ratio
1.67
1.55
1.58
1.50
Women
95% CI
1.54, 1.80
1.44, 1.68
1.46, 1.71
1.39, 1.63
Source: 1991 to 2001 Canadian census mortality follow-up study.
Abbreviation: CI, confidence interval.
Note: Models controlled for age in years (continuous), education (high school diploma or higher versus less than high school diploma) and income adequacy quintiles (1, 2, or 3 versus 4 + 5 combined).
205
Vol 32, No 4, September 2012 – Chronic Diseases and Injuries in Canada
of illness and disease.25 First Nations
people have lower levels of educational
attainment and income compared to other
Canadians.8,26 We examined the relationship
of education and income adequacy to
inequalities in cardiovascular disease
mortality comparing First Nations and
non-Aboriginal cohort members. Differences
remained when mortality rates were
calculated within each level of educational
attainment and income adequacy, indicating
that these factors alone do not explain the
disparity. In Cox models that controlled
for income and education simultaneously,
hazard ratios were attenuated by 67% for
men and 25% for women, suggesting that
these factors are important in explaining
some but not all of the disparity. Research
that examined the impact of socio-economic
status on inequalities in self-rated health
and chronic conditions—comparing First
Nations people living off-reserve and other
Canadians—demonstrated that factors such
as income and education minimize but do
not eliminate those health disparities.27
This research also showed that factors
often associated with health in the general
population do not always act in the same
way for First Nations people.27 For example,
among non-Aboriginal adults, men were
less likely than women to report being
in excellent or very good health whereas
among First Nations adults, men and
women were equally likely to report being
in excellent or very good health. Although
our results showed that cardiovascular
disease mortality was higher among men
than women for both First Nations and
non-Aboriginal cohort members, the rate
difference between men and women was
smaller for First Nations than for nonAboriginal cohort members. Thus, in terms
of sex differences in cardiovascular disease
mortality, First Nations women appeared
to have less of an advantage compared to
non-Aboriginal women. Determining why
that is true would require additional study.
Limitations
Our data excluded people who were not
enumerated by the 1991 census long-form
questionnaire, that is, people residing in
long-term care facilities, seniors’ residences
or prisons, as well as people not enumerated
by the census (about 3.4% of Canadian
residents of all ages). The missed individuals
were more likely to be young, mobile,
living in low income, of Aboriginal
ancestry,28 homeless and residents of Indian
reserves.29 In addition, since it was
necessary to obtain encrypted names
from tax filer data, only tax filers could
be followed for mortality. Linkage rates
to the name file abstracted from tax filer
data were lower for First Nations (54%)
compared with non-Aboriginal census
respondents (77%). However, the socioeconomic profile of First Nations cohort
members was similar to that of all First
Nations long-form census respondents,
suggesting that there was little bias in the
first linkage (data not shown).
This study defined First Nations people
by ancestry, Registration under the Indian
Act, or membership in an Indian band
or First Nation, because questions on
self-perceived Aboriginal identity were not
included in the 1991 census. Our definition
of First Nations excluded many people of
mixed Aboriginal and non-Aboriginal origin
whose census characteristics (data not
shown) were closer to those of nonAboriginal people than to First Nations
people as defined for this study.
and educational attainment were important
factors that help to explain the differences
in cardiovascular disease mortality
rates between First Nations people and
non-Aboriginal Canadians.
Acknowledgements
Funding for this study was provided by the
First Nations and Inuit Health Branch of
Health Canada. Funding for the creation
of the cohort was provided by the
Canadian Population Health Initiative,
part of the Canadian Institute of Health
Information. We would also like to thank
Eric Guimond from Indian and Northern
Affairs Canada on his earlier work
developing operational definitions for
First Nations using the 1991 census.
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207
Vol 32, No 4, September 2012 – Chronic Diseases and Injuries in Canada
Income disparities in life expectancy in the City of Toronto
and Region of Peel, Ontario
J. Stratton, MHSc (1); D. L. Mowat, FRCPC (1,2,3,4); R. Wilkins, MUrb (5,6); M. Tjepkema, MPH (5)
This article has been peer reviewed.
Abstract
Introduction: To understand the lack of a gradient in mortality by neighbourhood
income in a previous study, we used individual-level data from the 1991–2001 Canadian
census mortality follow-up study to examine income-related disparities in life expectancy
and probability of survival to age 75 years in the City of Toronto and Region of Peel.
Methods: We calculated period life tables for each sex and income adequacy quintile,
overall and separately for immigrants and non-immigrants.
Results: For all cohort members of both sexes, including both immigrants and
non-immigrants, there was a clear gradient across the income quintiles, with higher life
expectancy in each successively richer quintile. However, the disparities by income were
much greater when the analysis was restricted to non-immigrants. The lesser gradient
for immigrants appeared to reflect the higher proportion of recent immigrants in the
lower income quintiles.
Conclusion: These findings highlight the importance of using individual-level
ascertainment of income whenever possible, and of including immigrant status and
period of immigration in assessments of health outcomes, especially for areas with a
high proportion of immigrants.
Keywords: cohort study, mortality, probability of survival, healthy immigrant effect, Canada
Introduction
The “income gradient in health,” where
health improves with each incremental
increase in income, has been repeatedly
demonstrated in both Canada and the
United States, in studies of a variety of
health outcomes including mortality,1,2
life expectancy,2 health-related quality of
life3 and disability.3,4 Those in a lower
socio-economic position experience poorer
health outcomes than their more affluent
counterparts across a whole spectrum of
measures. The socio-economic gradient
is not static; it varies over time,
by age and sex, as well as by the
health measure and population subgroup
studied.
In a recent small-area analysis that
examined the relationship between life
expectancy and neighbourhood income in
the Region of Peel (immediately west of
the City of Toronto), we used mortality
data from the Ontario vital statistics
mortality database for the year 2005, and
2006 census data on the census tract
proportion of population with low income
(Appendix Table A). Our results showed
that for both men and women, life
expectancy was similar across all neighbourhood income quintiles—the expected
gradient was clearly not present. We
therefore undertook an analysis of previously
linked census-mortality cohort data5 to help
us understand how and why this was
happening. We speculated that the high
proportion of immigrants (49%) who live
in the region may have masked an income
gradient in mortality due to the “healthy
immigrant” effect. Moreover, because of the
mixing of rich and poor in many neighbourhoods, neighbourhood averages misclassify
many individuals, thus attenuating effect
estimates. Studies in Canada and the
United States have shown that the income
gradient in mortality is more pronounced
when data are analyzed by family income
rather than by various measures of neighbourhood income.3-6 Previous studies of
mortality among immigrants in Canada
have either not dealt with differences
across income groups7-11 or only adjusted
for income or neighbourhood income
(rather than explicitly showing results
by income level).12-15
Our objectives were to report differences in
all-cause mortality across income quintiles,
using individual and family income derived
from census microdata, and to examine how
those differences varied among immigrants
compared to non-immigrants. Using data
from the 1991–2001 Canadian census
mortality follow-up study, we calculated
period life tables by sex for the combined
area of the City of Toronto and Region of
Author references:
1. Peel Public Health, Brampton, Ontario, Canada
2. Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
3. Department of Community Health and Epidemiology, Queen’s University, Kingston, Ontario, Canada
4. Faculty of Nursing, McMaster University, Hamilton, Ontario, Canada
5. Health Analysis Division, Statistics Canada, Ottawa, Ontario, Canada
6. Department of Epidemiology and Community Medicine, University of Ottawa, Ottawa, Ontario, Canada
Correspondence: Russell Wilkins, Health Analysis Division, Statistics Canada, RHC-24A, 100 Tunney’s Pasture Driveway, Ottawa, ON K1A 0T6; Tel.: (613) 951-5305; Fax: (613) 951-4936;
Email: russell.wilkins@statcan.gc.ca
Vol 32, No 4, September 2012 – Chronic Diseases and Injuries in Canada
208
Peel, by income adequacy quintile, for all
cohort members as well as for immigrants
and non-immigrants separately. Canadian
data on all-cause mortality by individual
or family income comparing results for
immigrants and non-immigrants have not
previously been published, and we hoped
that the results would help us to better
understand the findings of our previous
study in this area.
Methods
Data source
The 1991–2001 Canadian census mortality
follow-up study, conducted by Statistics
Canada, is a probabilistically linked
cohort database where a 15% sample
(n = 2 735 152) of the non-institutional
population aged 25 years or older who
were enumerated by the 1991 census
long-form questionnaire (the cohort) was
linked to nearly 11 years of death records
(from 4 June 1991 to 31 December 2001)
from the Canadian mortality database.
This linked file contains information on
various demographic characteristics, socioeconomic position, activity limitations, and
cause and date of any death. Additional
details on the construction and contents
of the linked file have previously been
reported.5
For this study, data were extracted for
the 1991 census divisions corresponding
to the current Region of Peel (Mississauga,
Brampton and Caledon) and the amalgamated City of Toronto (including the
former cities of Toronto, North York, York,
Etobicoke and Scarborough, and the former
borough of East York). We combined
the two areas to obtain sufficient sample
size to construct life tables for the
20 sub-populations, each requiring death
data by 5-year age group. Both areas have
about the same percentage of immigrants,
and both are in the same labour market
area (the census metropolitan area of
Toronto).
Definitions
Income adequacy quintiles. To construct
income adequacy quintiles (fifths of the
population), a previous study5 determined
the total pre-tax, post-transfer income from
all sources for each economic family
or unattached individual in the entire
non-institutional census population. Then,
for each family size and community size
group, it calculated the ratio of total
income to the 1991 low income cut-off.
Within each census metropolitan area,
census agglomeration and rural areas of
each province, the population of all
ages, both sexes together, was then
ranked according to this ratio and
divided into fifths.
Results
Immigrant. In this analysis, the term
“immigrant” refers to people who were
not Canadian citizens by birth. It
includes all persons who were or had
ever been landed immigrants in Canada
or who had the status of non-permanent
residents as reported in the 1991 census.
Some immigrants had resided in Canada
for a number of years, while others had
only arrived recently; virtually all were
born outside of Canada.
For all cohort members, as well as for
immigrants and non-immigrants of each
sex, Table 1 shows the number of cohort
members in each income quintile, together
with the corresponding person-years at risk
and number of deaths. Mainly because
cohort members had to be linked to tax
filer data in order to be followed for
mortality, and people of higher income
were more likely to be tax filers, fewer
than 20% of the cohort were in the lowest
income quintile, and more than 20% were
in the highest.
Non-immigrant. In this analysis, “nonimmigrant” refers to people who were
Canadian citizens by birth. Almost all
non-immigrants were born in Canada.
Analytical techniques
Mortality analyses. For each member
of the cohort, person-days of follow-up
were calculated from the beginning of
the study (4 June 1991) to the date
of death, emigration (known for 1991
only) or end of the study (31 December
2001). Person-days of follow-up were
then divided by 365.25 to get person-years
at risk.
Abridged period life tables for each sex
and quintile, plus corresponding standard
errors and 95% confidence intervals (CIs)
were calculated according to Chiang’s
method.16 These calculations were done
after age was transformed from age at
baseline to age at the beginning of
each year of follow-up, and deaths
and person-years at risk were calculated
separately for each year (or partial year)
of follow-up. Deaths and person-years at
risk were then pooled by 5-year age
groups at the beginning of each year of
follow-up, before the calculation of the
life tables.5
209
Cohort members and deaths during the
follow-up period
At cohort inception a total of 287 500 cohort
members lived in either the City of Toronto
(220 400) or Region of Peel (67 100), of
whom 53% were immigrants. Of those
eligible cohort members, 25 648 died during
the follow-up period (12 134 immigrants,
13 514 non-immigrants).
Socio-economic characteristics of each
income quintile
For all cohort members, immigrants and
non-immigrants of both sexes combined,
Table 2 shows various socio-economic
characteristics for each income adequacy
quintile at baseline, expressed as a
percentage of the total number of cohort
members in each quintile. Since all the
characteristics shown were clearly graded
by income, we only note the highest and
lowest values in each series.
Compared to cohort members in the
highest income quintile, those in the
lowest income quintile were much more
likely to have not graduated from high
school (46% versus 16%) and to have
government transfers as their major
source of income (41% versus 2%);
further, they were less likely to
have received a university degree (10%
versus 39%).
Nearly 100% of immigrants, but fewer than
1% of non-immigrants, were foreign-born.
The proportion of foreign-born ranged from
38% in the highest income quintile to
66% in the lowest income quintile. The
Vol 32, No 4, September 2012 – Chronic Diseases and Injuries in Canada
Table 1
Cohort members, person-years at risk, and deaths during the study period, by income adequacy quintile and sex, by immigrant
status, City of Toronto and Region of Peel, 1991–2001 (non-institutionalized people aged 25 and over at baseline)
Immigrant status
Income quintile
Immigrantsa and non-immigrants
Total, all income quintiles
Quintile 1 (lowest)
Quintile 2
Quintile 3
Quintile 4
Quintile 5 (highest)
Immigrantsa
Total, all income quintiles
Quintile 1 (lowest)
Quintile 2
Quintile 3
Quintile 4
Quintile 5 (highest)
Non-immigrants
Total, all income quintiles
Quintile 1 (lowest)
Quintile 2
Quintile 3
Quintile 4
Quintile 5 (highest)
Cohort members
Men
Person-years
at risk
Deaths
Cohort members
Women
Person-years
at risk
Deaths
139 700
24 000
28 700
29 100
29 300
28 600
1 402 110
232 550
285 830
294 830
298 240
290 690
14 451
3 873
3 286
2 623
2 371
2 298
147 800
31 000
31 300
29 800
28 700
27 000
1 508 140
307 590
319 980
306 080
295 790
278 760
11 197
4 125
2 314
1 779
1 503
1 476
75 100
16 400
17 900
16 000
13 800
11 000
756 830
162 030
180 080
162 780
140 430
111 540
7 212
2 140
1 766
1 319
1 108
879
76 100
19 600
18 300
15 400
13 000
9 900
780 790
197 530
188 510
158 530
134 110
102 120
4 922
1 885
1 066
788
656
527
64 600
7 600
10 800
13 100
15 600
17 600
645 270
70 510
105 760
132 020
157 840
179 150
7 239
1 733
1 520
1 304
1 263
1 419
71 700
11 400
13 000
14 400
15 700
17 100
727 360
110 040
131 450
147 560
161 680
176 600
6 275
2 240
1 248
991
847
949
Source: Special tabulations from the 1991–2001 Canadian census mortality follow-up study.5
Note: The number of cohort members and person-years at risk were rounded independently (to the nearest 100, or the nearest 10, respectively).
a
Foreign-born, including non-permanent residents.
Table 2
Characteristics of cohort members (immigrants and non-immigrants combined) within each
income adequacy quintile, City of Toronto and Region of Peel, at cohort inception, 1991
Percentage of quintile total, %
Income quintile
Total
Foreign-borna
Recent
immigrantsb
Visible
minoritiesc
Total, all quintiles
Quintile 1 (lowest)
Quintile 2
Quintile 3
Quintile 4
Quintile 5 (highest)
100.0
100.0
100.0
100.0
100.0
100.0
52.8
65.7
60.5
53.5
46.4
37.9
10.7
23.0
14.1
8.7
5.1
2.8
24.0
35.2
29.5
24.0
18.4
12.8
Less than high
school
graduation
31.2
46.4
37.5
31.1
25.1
16.0
University
degree
Government
transfersd
Aboriginale
19.8
10.4
12.2
16.1
22.1
38.8
14.5
41.0
15.9
8.7
5.3
2.4
0.8
1.0
0.8
0.8
0.7
0.6
Source: Special tabulations from the 1991–2001 Canadian census mortality follow-up study.5
a
Almost 100% of immigrants, but less than 1% of non-immigrants, were foreign born.
b
Immigrants in the period 1986–1991.
c
In Canada, the term “visible minorities” does not include Aboriginal peoples; 43% of immigrants and 3% of non-immigrants were visible minorities.
d
Percentage of cohort members whose major source of income was from government transfer payments.
e
Aboriginal ancestry or Registered Indian; almost all (96%) were non-immigrants.
proportion of recent immigrants (1986–1991)
ranged from 3% in the highest income
quintile to 23% in the lowest.
In Canada, the term “visible minorities”
does not include Aboriginal peoples.5
In our Toronto-Peel cohort, the proportion
of visible minorities ranged from 13%
in the highest income quintile to
35% in the lowest. Almost all
Aboriginal cohort members (96%) were
non-immigrants, but the proportion
of Aboriginal people was low (≤ 1%)
in all quintiles.
Vol 32, No 4, September 2012 – Chronic Diseases and Injuries in Canada
210
Table 3 shows the overall percentages
of each characteristic for immigrants
and non-immigrants separately, plus
the percentages for immigrant and nonimmigrants within each income quintile.
Overall, one-fifth (20%) of immigrants were
recent immigrants (1986–1991), but that
Table 3
Characteristics of cohort members, showing immigrants and non-immigrants separately within each income adequacy quintile,
City of Toronto and Region of Peel, at cohort inception, 1991 (percentage of row total for immigrants and non-immigrants)
Recent immigrantsa
Visible minoritiesb
Less than high school University degree
Government
Aboriginald
graduation
transfersc
Income quintile
Immigrant
NonImmigrant
NonImmigrant
NonImmigrant
NonImmigrant
NonImmigrant
Nonimmigrant
immigrant
immigrant
immigrant
immigrant
immigrant
Total, all quintiles
20.3
0.0
43.1
2.8
36.4
25.5
16.3
23.7
16.1
12.6
0.1
1.6
Quintile 1 (lowest)
35.2
0.0
52.1
3.3
45.7
47.7
10.8
9.8
36.6
49.2
0.0
2.7
Quintile 2
23.3
0.0
47.1
2.8
40.5
32.9
11.8
13.0
15.5
16.4
0.0
1.9
Quintile 3
16.4
0.0
42.7
2.6
35.7
25.8
14.5
17.9
9.7
7.6
0.1
1.6
Quintile 4
11.0
0.0
36.5
2.8
30.7
20.2
19.2
24.6
6.8
3.9
0.1
1.3
Quintile 5 (highest)
7.6
0.0
29.7
2.6
21.6
12.6
33.0
42.4
3.5
1.7
0.1
0.9
Source: Special tabulations from the 1991–2001 Canadian census mortality follow-up study.5
a
Immigrants in the period 1986−1991.
b
In Canada, the term “visible minorities” does not include Aboriginal people; 43% of immigrants and 3% of non-immigrants were visible minorities.
c
Percentage of cohort members whose major source of income was from government transfer payments.
d
Aboriginal ancestry or Registered Indian; almost all (96%) were non-immigrants.
varied from over one-third (35%) of the
lowest income quintile, to less than one-tenth
(8%) of the highest income quintile. Not
unexpectedly immigrants were far more
likely than non-immigrants to be visible
minorities (43% versus 3%), though within
immigrants, the proportion of visible
minorities varied from over half in the
lowest income quintile (52%), to less
than one-third (30%) in the highest. Over
one-third of immigrants had less than
high school graduation (36%), compared to
about one-quarter of non-immigrants (26%).
Compared to non-immigrants, immigrants
were less likely to have a university degree
(16% versus 24%), and somewhat more
likely to have government transfers as their
major source of income (16% versus 13%).
Among non-immigrants, the percentage
of Aboriginal people was 3% in the lowest
income quintile, compared to less than 1%
in the highest.
For
non-immigrants,
the
income
gradient in remaining life expectancy
was steeper, with a very clear stepwise
progression across the income quintiles
Table 4
Remaining life expectancy at age 25 years (conditional on surviving
to age 25 years), by income adequacy quintile and sex, by immigrant
status, City of Toronto and Region of Peel, 1991–2001
Immigrant status
Income quintile
Men
Years (95% CI)
Immigrantsa and non-immigrants
Total, all quintiles
Quintile 1 (lowest)
Quintile 2
Quintile 3
Quintile 4
Quintile 5 (highest)
Difference Q5−Q1
Immigrantsa
Total, all quintiles
Quintile 1 (lowest)
Quintile 2
Quintile 3
Quintile 4
Quintile 5 (highest)
Difference Q5−Q1
Non-immigrants
Total, all quintiles
Quintile 1 (lowest)
Quintile 2
Quintile 3
Quintile 4
Quintile 5 (highest)
Difference Q5−Q1
Disparities in remaining years of life at age
25 years
Remaining years of life expectancy at age
25 years (conditional on surviving to
age 25 years) are shown in Table 4. For all
cohort members of each sex in the study
area (including both immigrants and nonimmigrants), there was a clear gradient
across the income quintiles, with higher
life expectancy in each successively richer
quintile. The difference in remaining life
expectancy between the lowest and
highest income quintiles was 5.3 years for
men and 3.3 years for women.
for both men and women. The gap
between the lowest and the highest
income quintiles was 9.8 years for men
and 7.4 years for women.
Women
Years (95% CI)
53.7
50.6
53.0
54.0
55.0
56.0
5.3
(53.5, 53.9)
(50.2, 51.0)
(52.6, 53.4)
(53.6, 54.4)
(54.6, 55.4)
(55.5, 56.4)
(4.7, 5.9)
59.3
57.1
59.2
59.7
60.6
60.4
3.3
(59.1, 59.5)
(56.7, 57.5)
(58.8, 59.6)
(59.2, 60.1)
(60.2, 61.1)
(60.0, 60.9)
(2.7, 3.9)
55.4
53.8
55.0
55.6
56.4
57.6
3.8
(55.1, 55.6)
(53.3, 54.3)
(54.5, 55.5)
(55.0, 56.1)
(55.7, 57.0)
(56.9, 58.3)
(3.0, 4.7)
60.9
60.3
60.7
60.9
61.2
61.1
0.8
(60.6, 61.1)
(59.8, 60.8)
(60.1, 61.2)
(60.3, 61.5)
(60.5, 61.9)
(60.3, 61.8)
(−0.1, 1.7)
51.7
45.1
49.7
51.7
53.6
55.0
9.8
(51.4, 52.0)
(44.4, 45.9)
(49.0, 50.4)
(51.1, 52.3)
(53.0, 54.1)
(54.5, 55.5)
(8.9, 10.7)
57.6
52.5
57.3
58.4
60.1
60.0
7.4
(57.4, 57.9)
(51.8, 53.2)
(56.7, 58.0)
(57.7, 59.0)
(59.4, 60.7)
(59.4, 60.5)
(6.5, 8.3)
Source: Special tabulations from the 1991–2001 Canadian census mortality follow-up study.5
Abbreviations: CI, confidence interval; Q, quintile.
a
Foreign-born, including non-permanent residents.
211
Vol 32, No 4, September 2012 – Chronic Diseases and Injuries in Canada
For immigrants, the income gradient in
remaining life expectancy was markedly less
steep. The gap between the highest and
lowest quintiles was 3.8 years for immigrant
men and 0.8 years for immigrant women.
Table 5
Probability of survival to age 75 years (conditional on surviving to age 25 years), by income
adequacy quintile and sex, by immigrant status, City of Toronto and Region of Peel, 1991–2001
Immigrant status
Income quintile
Immigrants and non-immigrants
Total, all quintiles
Quintile 1 (lowest)
Quintile 2
Quintile 3
Quintile 4
Quintile 5 (highest)
Difference Q5−Q1
Immigrantsa
Total, all quintiles
Quintile 1 (lowest)
Quintile 2
Quintile 3
Quintile 4
Quintile 5 (highest)
Difference Q5−Q1
Non-immigrants
Total, all quintiles
Quintile 1 (lowest)
Quintile 2
Quintile 3
Quintile 4
Quintile 5 (highest)
Difference Q5−Q1
Note that within each income quintile and
for both sexes, the remaining life expectancy
of immigrants always exceeded that of
non-immigrants. However, the differences
between immigrants and non-immigrants
were smallest in the highest income quintile
(2.6 years for men, 1.1 years for women)
and largest in the lowest (8.7 years for men,
7.8 years for women).
Disparities in the probability of survival to
age 75 years
The probability of surviving to age 75 years
(conditional on surviving to age 25 years) is
shown in Table 5. As with life expectancy
at age 25 years, the proportion of men and
women expected to survive to age 75 years
increased in each successively higher
income quintile, for all cohort members
as well as for both immigrants and nonimmigrants. However, the disparities were
much more striking for non-immigrants.
For all cohort members of each sex there
was a clear gradient across the income
quintiles, with higher probability of survival
to age 75 years in each successively richer
quintile. Among men, the probability of
survival to age 75 years was 57% in the
lowest income quintile and 74% in the
highest (a difference of 17 percentage
points). Among women, the probability of
survival to age 75 years ranged from 73%
in the lowest income quintile to 84% in
the highest (a difference of 10 percentage
points).
For non-immigrant men, the probability of
survival to age 75 years was 40% in the
lowest income quintile and 73% in the
highest (a difference of 33 percentage
points). For immigrant men, the probability
of survival to age 75 years was 67% for
those in the lowest income quintile and
76% for those in the highest (a difference
of 9 percentage points).
For non-immigrant women, the probability
of survival to age 75 years ranged from
61% in the lowest income quintile to 82% in
% Probability (95% CI)
Men
Women
66.9
57.0
64.1
67.3
69.5
74.1
17.2
(66.3, 67.5)
(55.5, 58.5)
(62.7, 65.5)
(66.0, 68.7)
(68.2, 70.8)
(72.9, 75.4)
(15.2, 19.1)
80.1
73.3
79.5
81.8
82.9
83.6
10.3
(79.5, 80.6)
(72.0, 74.5)
(78.4, 80.7)
(80.6, 82.9)
(81.7, 84.1)
(82.4, 84.7)
(8.6, 12.0)
71.5
67.2
69.3
72.3
73.1
75.8
8.6
(70.7, 72.3)
(65.4, 69.1)
(67.6, 71.0)
(70.6, 74.0)
(71.3, 74.9)
(74.0, 77.7)
(6.0, 11.2)
83.6
81.0
82.4
85.1
85.3
85.4
4.4
(82.9, 84.3)
(79.5, 82.4)
(80.9, 83.8)
(83.7, 86.6)
(83.7, 86.9)
(83.6, 87.2)
(2.1, 6.7)
61.0
39.7
54.5
59.7
65.1
72.9
33.1
(60.0, 62.0)
(37.3, 42.2)
(52.0, 56.9)
(57.5, 61.9)
(63.1, 67.2)
(71.2, 74.6)
(30.2, 36.1)
76.0
60.9
75.1
77.6
80.2
82.3
21.5
(75.2, 76.9)
(58.6, 63.1)
(73.2, 77.1)
(75.8, 79.5)
(78.5, 82.0)
(80.8, 83.9)
(18.7, 24.2)
Source: Special tabulations from the 1991–2001 Canadian census mortality follow-up study.5
Abbreviations: CI, confidence interval; Q, quintile.
a
Foreign-born, including non-permanent residents.
the highest (a difference of 21 percentage
points). For immigrant women, the probability of survival to age 75 years ranged
from 81% in the lowest income quintile
to 85% in the highest (a difference of
4 percentage points).
Note that in each income quintile and for
both sexes, the probability of survival to age
75 years for immigrants always exceeded
that for non-immigrants. However, the
difference between immigrants and nonimmigrants was largest in the lowest income
quintile (28 percentage points for men,
20 percentage points for women), and
smallest in the highest (3 percentage
points for both men and women).
Discussion
Results from this study clearly show that
for both men and women in the City of
Toronto and Region of Peel, remaining life
expectancy at age 25 years and probability of
Vol 32, No 4, September 2012 – Chronic Diseases and Injuries in Canada
212
survival to age 75 years differed substantially
across income quintiles. That was not
surprising, though data with individual
and family-level income were required to
demonstrate it. We also found that the
disparities in mortality by income were
much greater when the analysis was
restricted to non-immigrants. Moreover,
within each income quintile, immigrants
had more favourable results compared
to non-immigrants, but the immigrant
advantage was particularly marked within
the lowest income quintiles. Neither the
greater disparities in mortality by income
among non-immigrants, nor the greater
survival advantage for immigrants in lower
income groups has previously been reported
for Canada.
The failure of our previous small-area
based study to detect differences in life
expectancy across neighbourhood income
quintiles was likely because of considerable
confounding due to the presence of a
much higher than average proportion of
low-mortality immigrants (and especially
of recent immigrants, with particularly
low mortality) within otherwise highmortality low-income neighbourhoods, as
well as non-differential misclassification
due to the use of census tract
averages rather than individual and family
income.
In terms of both remaining life expectancy
and probability of survival to age 75 years,
these results not only confirm previous
work by showing substantial disparities by
income overall, but they also reveal that the
income gradient in mortality was much
steeper among non-immigrants compared
to immigrants.
The healthy immigrant effect presumably
reflects a high degree of self-selection.
First, people are less likely to try to
immigrate if they are unhealthy. Second,
the immigration process requires that
immigrants undergo medical screening to
enter Canada, and immigrants are selected
based on their wealth, employability,9
education, and language abilities.17 Third,
unhealthy behaviours such as smoking,
heavy drinking and poor diet tend to be
less common among immigrants compared
to non-immigrants.9,18
Research has shown that immigrants in
general tend to enjoy better health than do
non-immigrants. This has been observed
for a variety of chronic diseases as well as
disability, dependency, life expectancy
and disability-free life expectancy.17-24
Although immigrants are usually in
excellent health upon arrival in Canada,
over time their health status tends to
converge toward that of the Canadianborn population.7,25 In particular, research
has shown that recent immigrants have
lower mortality rates compared to longerterm immigrants.5 The larger gap between
immigrants and non-immigrants that we
observed in the lower income quintiles
compared to the higher income quintiles
appears to be related, at least in part, to
the higher proportion of recent immigrants
in the lower income quintiles. Future
studies with adequate power should
attempt to control for such confounding.
Limitations
The 1991–2001 Canadian census mortality
follow-up study excluded people who were
missed by the 1991 census (about 3.4% of
the total population). The missed individuals
were more likely to be young, mobile,
low income, of Aboriginal ancestry26 or
homeless. In addition, people residing in
long-term care facilities, seniors’ residences
or prisons (who were not enumerated by a
long-form questionnaire), and non-tax filers
in both the 1990 and 1991 tax years (as this
information was needed for the linkage)
were excluded from the cohort. As a result,
the entire cohort across Canada had one
year longer remaining life expectancy for
men, and two years longer remaining life
expectancy for women when compared
to life tables for the entire population of
Canada.5
Information on family income and place of
residence was only available at baseline.
Since these characteristics are expected
to change over time, it would have been
preferable to have income and place of
residence for each year of follow-up.
Because this analysis was restricted to
the City of Toronto and Region of Peel,
our cohort had insufficient numbers to
allow us to further distinguish between
recent and long-term immigrants, except
in terms of population characteristics.
Future analyses using the entire cohort
should both do so and examine other
factors such as country or region of origin
and visible minority status to better
understand the trends by income that we
see in these data.27
Conclusion
Our results highlight the importance of
using individual and family level data when
analysing income disparities in health
outcomes in a population as diverse as that
of Canada’s largest metropolitan area. It also
shows the importance of taking account
of both immigrant status and recency
of immigration in understanding the
relationship between income and two basic
health outcomes—remaining life expectancy
at age 25 years and the probability of
213
survival to age 75 years. This is especially
important for areas such as the City of
Toronto and Region of Peel, which have a
very high proportion of immigrants,
including many recent immigrants.
While vital statistics death and birth
registrations collect information on the
birthplace of the decedent, or of the mother,
that information is often overlooked when
data are compiled and analysed. In other
administrative datasets, such as cancer
registries and hospital morbidity data, no
information is collected on place of birth.
This study demonstrates the importance
of collecting and analysing this type of
data, not just for understanding the
relationships between immigration and
health (though that is important), but also
for clarifying the extent and nature of
socio-economic disparities in health more
generally.
Future work could investigate ways of
including the morbidity and mortality
experience of institutional residents—the
most disabled segment of the population—
as well as that of people aged less than
25 years, to get a more comprehensive
picture of morbidity and mortality in
relation to socio-economic position.3
Analyses examining causes of death within
each of the quintiles would further
enhance knowledge with regard to potential
prevention efforts intended to reduce health
disparities related to socio-economic
circumstances.
Acknowledgements
Major funding for the creation of the
1991–2001 Canadian census mortality
follow-up study, upon which this work
was based, was provided by the Canadian
Population Health Initiative, part of the
Canadian Institute for Health Information.
We are grateful to Canada’s provincial and
territorial registrars of vital statistics, who
provided the death data used in this study;
to Statistics Canada, which conducted the
1991 census; and to the people of Canada,
whose answers to the long-form census
questionnaire provided the basis for these
analyses.
Vol 32, No 4, September 2012 – Chronic Diseases and Injuries in Canada
Appendix
Table A
Remaining life expectancy at age 25, by neighbourhood income quintile, Peel Region, 2005
Neighbourhood
income quintile
Years remaining
Men
Women
Quintile 1 (lowest)
56.6
61.1
Quintile 2
57.3
60.6
Quintile 3
56.8
61.0
Quintile 4
57.3
59.9
Quintile 5 (highest)
57.0
59.4
+0.4
−1.7
Difference: Q5−Q1
Source: Stratton J et al. 2010 . Special tabulations based on Ontario Mortality Database 2005, HELPS (Health Planning
System), Ministry of Health Promotion; and 2006 census tract profiles, Statistics Canada.
28
Note: Neighbourhood income quintiles based on census tract proportion of people whose economic family or individual
income was less than the Statistics Canada low income cut-off for the applicable family size and community size group.
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215
Vol 32, No 4, September 2012 – Chronic Diseases and Injuries in Canada
Prevalence of meeting physical activity guidelines for cancer
prevention in Alberta
F. E. Aparicio-Ting, PhD (1,2); C. M. Friedenreich, PhD (1,3,4); K. A. Kopciuk, PhD (1,3,5); R. C. Plotnikoff, PhD (6);
H. E. Bryant, PhD (4,7)
This article has been peer reviewed.
Abstract
Introduction: Guidelines for recommended physical activity (PA) levels have been
developed by the Canadian Society for Exercise Physiology (CSEP) and the U.S.
Department of Health and Human Services (USDHHS) for health benefits and by the
American Cancer Society (ACS) and the World Cancer Research Fund/American
Institute for Cancer Research (WCRF/AICR) for cancer prevention benefits.
Methods: We examined if these guidelines were met using a sample of 14 294 Albertan
participants of the Tomorrow Project, aged 35 to 64 years, enrolled from 2001 to 2005. We
used logistic regression to examine correlates of leisure PA behaviour.
Results: An estimated 55%, 42%, 26% and 23% of participants met CSEP, ACS,
USDHHS, and WCRF/AICR guidelines, respectively. Women were less likely than
men to meet ACS (Odds Ratio [OR] = 0.72, 95% confidence interval [CI]: 0.55–0.93),
USDHHS (OR = 0.67, 95% CI: 0.50–0.89) and WCRF/AICR (OR = 0.63, 95%
CI: 0.47–0.85) guidelines, and being obese was correlated with not meeting USDHHS
(OR = 0.45, 95% CI: 0.32–0.65) and WCRF/AICR guidelines (OR = 0.79, 95% CI:
0.63–0.98).
Conclusion: Albertans, particularly women and obese individuals, are not sufficiently
active for cancer prevention benefits.
Keywords: physical activity, cancer prevention, population health, lifestyle, health
behaviour, guidelines
Introduction
Cancer remains the second leading cause
of mortality and morbidity in Canada with
an estimated 177 800 incident cases and
75 000 deaths in 2011.1 The total economic
cost of cancer has been estimated to
represent roughly 9% of the total cost of
illness in Canada.2 Whilst treatment and
early detection have improved over the
past decades, cancer prevention by
modifying environmental and lifestyle
risk factors remains the most viable
long-term strategy for substantially
reducing the burden of cancer in Canada.3
Several modifiable lifestyle risk factors
have been extensively investigated
including tobacco use, alcohol use,
dietary intake, sun exposure and, more
recently, physical activity (PA).4,5
Evidence that PA is a key modifiable
lifestyle risk factor that may reduce the risk
of several cancers is now accumulating.
The risk of colon, breast and endometrial
cancers is reduced by 25% to 30% in
physically active individuals, and evidence
for a beneficial effect of PA in reducing
prostate, ovarian, lung and other gastrointestinal cancers is emerging.6-9 The evidence
for a role of PA in cancer etiology is now
considered to be fairly strong, consistent and
biologically plausible. Several biological
mechanisms have been hypothesized to
explain how PA reduces cancer risk,
including an impact on endogenous sex and
metabolic hormone levels, growth factors,
inflammation and insulin resistance, all of
which impact carcinogenesis.10-12 In addition,
PA may act to decrease cancer risk by
decreasing obesity and central adiposity,
both established risk factors for colon,
postmenopausal breast, endometrial, kidney
and oesophageal cancers.12-14 Overweight
and obesity result in a shift in the sex and
metabolic hormone balance in the body
and influence the availability of a number
of growth factors involved in the insulin
resistance and inflammation pathways
that initiate and promote carcinogenesis.14
As a result, PA can also be used for weight
management to reduce cancer risk.12-14
This overwhelming evidence that PA plays
an important role in preventing cancer
and other chronic diseases has driven the
development of PA recommendations or
guidelines by a number of organizations.
Author references:
1. Department of Population Health Research, Alberta Health Services-Cancer Care, Calgary, Alberta, Canada
2. Community Health Sciences, Faculty of Medicine, University of Calgary, Calgary, Alberta, Canada
3. Department of Oncology, Faculty of Medicine, University of Calgary, Calgary, Alberta, Canada
4. Department of Community Health Sciences, Faculty of Medicine, University of Calgary, Calgary, Alberta, Canada
5. Department of Mathematics and Statistics, Faculty of Science, University of Calgary, Calgary, Alberta, Canada
6. School of Education, University of Newcastle, New South Wales, Australia
7. Canadian Partnership Against Cancer, Toronto, Ontario, Canada
Correspondence: Fabiola Aparicio-Ting, Community Health Sciences, Faculty of Medicine, University of Calgary, 3rd Floor, TRW Building, 3280 Hospital Drive N.W., Calgary, AB T2N 4Z6;
Tel.: (403) 220-8124; Fax: (403) 270-7307; Email: feaparic@ucalgary.ca
Vol 32, No 4, September 2012 – Chronic Diseases and Injuries in Canada
216
The purpose of these guidelines is to
encourage inactive populations to engage in
PA and to provide a target to set personal
PA goals and measure progress.15 In Canada,
the Canadian Society for Exercise Physiology
(CSEP) has developed guidelines for adults,
older adults and children.16 The 2003 CSEP
guidelines recommend that adults engage in
at least 150 minutes of moderate to vigorous
aerobic PA per week. The guidelines also
indicate that more PA provides greater
health benefits.16 Moderate-intensity activity
is defined as aerobic activity that is not
exhausting and leads to light perspiration
(e.g. brisk walking), while vigorous activity
results in rapid heart rates, sweating and
heavy breathing (e.g. jogging, aerobics).17-18
CSEP also recommends that adults incorporate strength training activities at least two
days per week; however, our study focuses
only on levels of aerobic activity.
The American Cancer Society (ACS),19 the
United States Department of Health and
Human Services (USDHHS) with the United
States Department of Agriculture,20 and the
World Cancer Research Fund with the
American Institute for Cancer Research
(WCRF/AICR)21 also recommend a minimum
of 150 minutes of moderate to vigorous PA
per week for general health. Further, they
have extended their recommendations to
include higher levels of activity to prevent
other chronic diseases. Based on reviews of
current research, ACS recommended at least
45 minutes of moderate and preferably
vigorous PA at least 5 days per week to
reduce cancer risk. USDHHS recommended
that adults engage in at least 30 minutes of
moderate-intensity PA on most days of the
week as a means of reducing the risk
of chronic diseases. However, USDHHS
also recommended that adults engage in
60 minutes of moderate to vigorous activity
on most days of the week to help manage
body weight and prevent weight gain, and
60 to 90 minutes of daily moderate to
vigorous activity for sustained weight loss
to reduce the risk of chronic disease,
including cancer, associated with overweight
and obesity.20 Most recently, WCRF/AICR
conducted a comprehensive review of
current evidence and recommended that
adults aim to participate in at least
60 minutes of moderate activity or
30 minutes or more of vigorous activity
daily as a means of reducing cancer risk.21
Using data from the Alberta cohort study
known as the Tomorrow Project,22 our aim
was to estimate the percentage of Albertans
meeting the PA guidelines for cancer
prevention. Since there has been little
research on the levels of PA necessary for
cancer prevention, this study also explored
potential associations between personal and
demographic characteristics and meeting
PA guidelines for cancer prevention.
Methods
Study sample
The Population Research Laboratory at the
University of Alberta recruited Tomorrow
Project participants from all geographic
regions of Alberta using the Random Digit
Dialing (RDD) method.23 This method was
selected for random population sampling
because 97% of Alberta households had
at least one telephone line in 2000.24
Participants were sampled from over
400 cities, towns and villages and from all
rural areas throughout the province to build
a geographically representative sample.22
A total of 29 270 Albertans aged 35 to
65 years were recruited to the Tomorrow
Project from 2001 to 2005, or 49% of the
59 735 eligible individuals who responded
positively to telephone calls; the number
of eligible individuals who did not respond
to telephone calls is unknown, so the
response rate cannot be calculated. Of
the 29 270 people recruited, 16 040 had
complete data for lifestyle risk factors. A
total of 1746 participants were excluded from
this study sample based on the established
exclusion criteria: transgendered (n = 2),
over 65 years old (n = 1328), pregnant
(n = 55), prior cancer diagnosis (n = 188),
not resident in Alberta (n = 75), and
being underweight (n = 98). Data for
the remaining 14 294 Tomorrow Project
participants were used for this analysis.
We can conclude that the response rate
cannot be greater than 25% (14 294/[59
735−1746]).
This study received approval by the
ethics review boards of the University of
Calgary and the former Alberta Cancer
Board, now part of Alberta Health
Services–Alberta Cancer Research Ethics
Committee.
217
Data collection
Albertans who consented to participate in
the Tomorrow Project completed the selfadministered, mailed questionnaires about
lifestyle risk factors and exposures. Data
collected using the Past Year Total Physical
Activity Questionnaire (PYTPAQ) and the
Health and Lifestyle Questionnaire (HLQ)
were analyzed in this study. The PYTPAQ
is a valid and reliable self-administered
questionnaire used to collect the frequency,
duration and intensity of occupational,
household, active transport and leisure
activities of the previous twelve months.25
The PYTPAQ was correlated with 7-day
activity logs (Spearman rank correlation
[ρ] = 0.41) and 7-day accelerometer
measurements (ρ = 0.26). The HLQ was
developed from pre-existing questionnaires,
including those used in the Canadian
Community Health Survey (CCHS)
cycle 1.1,26 the Prostate, Lung, Colorectal
and Ovarian Cancer Screening Trial,27 and
the European Prospective Investigation into
Cancer and Nutrition28 to assess health
history, family history, cancer screening
practices, smoking, stress, social support
and demographic characteristics.
Participating in sufficient leisure activity to
meet the PA guidelines recommended by
CSEP, ACS, USDHHS and WCRF/AICR was
the outcome of interest for this study. While
occupational, household and transportation
activities can also contribute to overall
health, leisure activity is the most modifiable
type of activity and has been the main
target of public health promotion of PA.15,19,21
Four outcome variables were derived from
data collected using the PYTPAQ. Metabolic
Equivalents (MET) values, the ratio of energy
expenditure of an activity to the energy
cost of the metabolic rate at rest,18 were
assigned to each reported leisure, household, occupational and active transport
activity using the Compendium of Physical
Activities.29 Reported values for frequency
and duration for each separate activity with
intensity of 3 or more METs (considered a
moderate intensity) were multiplied for a
single estimate of the hours per week at
moderate and vigorous intensity. Outcome
variables were derived as follows:
• To meet the CSEP guidelines of at least
2.5 hours/week of moderate to vigorous
activity;
Vol 32, No 4, September 2012 – Chronic Diseases and Injuries in Canada
• To meet the ACS guidelines of at
least 3.75 hours/week of moderate to
vigorous activity;
• To meet the WCRF/AICR guidelines of
at least 7 hours/week of moderateintensity activity or 3.5 hours/week of
vigorous activity;
• To meet the USDHHS guidelines of
at least 5 hours/week of moderate
to vigorous activity to prevent
weight gain.
Pertinent explanatory variables obtained
from the HLQ included age, sex,
annual household income, educational
attainment, marital status, employment
status, pre-existing chronic conditions
(including hypertension, hypercholesterolemia
and
diabetes),
self-rated
health status, smoking behaviour,
social support (using the Medical
Outcomes
Study
Social
Support
Survey)30 and urban or rural residence
(from postal codes).
Statistical analysis
Univariate analysis provided an overall
description of the study sample and an
estimate of the percentage of the study
sample that met each of the PA guidelines.
We used the Cochran–Armitage test to
assess trends across proportions that met
each guideline.
Characteristics of the study sample and
of the Alberta population, using 2001
Canadian census data,31 were compared to
assess the representativeness of the sample.
Prevalence of smoking and weight status
were obtained from the CCHS 2.1. The
CCHS 2.1 had a response rate of about
83% in Alberta in 2003 and reflects
population-based estimates of health.32 A
postal code conversion file from Statistics
Canada was used to code participants
into health regions. Sample weights
were estimated using the distribution
weights of age group and sex by health
region of residence as well as by
educational attainment and annual
household income according to Canadian
2001 census data. The proportion of
the sample that met each guideline was
then weighted to obtain estimates of the
percentage of Albertans that met each of
the guidelines.
Logistic regression was used to explore
the potential correlates of meeting each
guideline. Prior to modelling, the data were
assessed for multicollinearity.33 Variable
selection was done through hierarchical
backward elimination,34 beginning with
all available explanatory variables and
all models adjusted for age, sex and
BMI. A 10-fold cross-validation procedure
was used to avoid overfitting.35 For each
guideline, data were divided into 10
randomly selected subsets and variable
selection was conducted using each
of 9 training sets. The resulting model was
fit to a test subset, repeating this procedure
10-fold until each subset was used as a test
subset.35 Variables selected in at least 3 of
10 folds at a significance level of p = .05,
were included in the final models. Estimated
coefficients and their standard errors were
averaged across the folds and used to yield
odds ratio (OR) estimates and 95% confidence intervals (CIs). Final models were fit
to the entire sample and tested for goodnessof-fit using the Hosmer–Lemeshow test,
for predictive value using receiver operating
characteristic (ROC) curves, and for appro­
priateness of the logit link.36 All statistical
procedures were performed using STATA
version 10 (StataCorp LP).37
Results
Meeting physical activity guidelines
Those who met CSEP and ACS guidelines
(63% and 48%, respectively) mainly
participated in leisure activities rather
than in household, occupational or active
transport activities (Table 3). On the
other hand, participants were most likely
to meet USDHHS and WCRF/AICR
guidelines through occupational activity.
Regardless of the type of activity considered,
participants were most likely to meet CSEP
guidelines (93%) and least likely to meet
USDHHS and WCRF/AICR guidelines (78%
and 72%, respectively) (Table 3).
Prevalence of meeting physical activity
guidelines in Alberta
After weighting by age, sex, and health
region of residence and then by educational attainment and household income,
55% of the overall Alberta population
was estimated to be sufficiently active to
meet CSEP guidelines for general good
health. However, the proportions of
Albertans estimated to meet the more
rigorous guidelines set by ACS, USDHHS
and WCRF/AICR were comparatively
low: 42%, 26% and 23%, respectively
(Figure 1).
Study sample characteristics
Correlates of meeting physical activity
guidelines through leisure activity
The study sample was largely female
(60%) and averaged 49 years of age
(Table 1). Most participants were of high
socio-economic status, with one-third
having some university education or
higher (33%) and an annual household
income of $80,000 or higher (37%). Most
were married or living with a common-law
partner (77%), employed (77.5%) and
urban residents (80%). Most of the sample
self-rated their health as very good or better
(61%), yet the majority were overweight
(39%) and obese (25%) (Table 1). In
comparison to the Alberta population, the
study participants were more likely to be
female, older, more educated and wealthier
(Table 2). Study participants were also
more likely to be overweight and obese
and less likely to smoke than the Alberta
population (Table 2). Overall, the sample
represented all nine former health regions
in Alberta.
Overall, marital status, employment status,
annual household income and self-rated
health status were correlated with meeting
all PA guidelines through leisure activity
(Table 4). Divorced, separated or widowed
participants were more likely to meet CSEP
(OR = 1.54; 95% CI: 1.06–2.26), ACS
(OR = 1.63; 95% CI: 1.12–2.35), USDHHS
(OR = 1.62; 95% CI: 1.08–2.43), and
WCRF/AICR (OR = 1.51; 95% CI: 1.09–2.10)
guidelines than those who were married or
single. Retired participants were also more
likely to meet all guidelines than those
who were employed or unemployed.
However, this strength of association
increased with increasingly demanding
guidelines: retirees were almost 3 times
more likely to meet WCRF/AICR
guidelines (OR = 2.76; 95% CI: 1.57–4.87)
compared to over 2 times more likely to
meet CSEP guidelines (OR = 2.30; 95%
CI: 1.32–4.01). In contrast, the strength of
Vol 32, No 4, September 2012 – Chronic Diseases and Injuries in Canada
218
Table 1
Study sample characteristics, Alberta, 2005
Variable
Whole sample
n = 14 294
%
Men
n = 5729
%
Women
n = 8565
%
48.7 (7.9)
48.6 (7.9)
48.7 (8.0)
18.5–24.9 kg/m2
35.4
24.6
42.7
25.0–29.9 kg/m2
39.4
49.3
32.7
30.0–39.9 kg/m2
22.5
24.7
21.0
2.7
1.5
3.5
Married/Common law
76.9
81.9
75.4
Divorced, separated or widowed
15.2
10.7
18.5
6.5
7.3
6.1
Mean age (SD), years (n = 13 970)
BMI, % (n =13 970)
≥ 40 kg/m2
Marital status, % (n = 14 216)
Single
Educational attainment, % (n = 14 005)
Some high school
High school diploma
8.6
8.9
8.4
18.6
15.0
21.0
Technical school/College training
39.9
40.7
39.3
Some university/University degree
22.9
22.7
22.9
Postgraduate university
10.1
12.6
8.4
Employment status, % (n = 14 051)
Employed full-time
60.7
80.6
47.4
Employed part-time
16.8
5.6
24.2
Unemployed
13.5
5.0
19.1
Retired
8.0
7.2
8.5
Self-employed
1.0
1.4
0.8
6.0
3.6
7.5
19.6
Annual household income, % (n = 14 022)
< $20,000
$20,000–$39,999
16.6
12.1
$40,000–$59, 999
20.0
19.3
20.4
$60,000–$79, 999
20.1
21.6
19.1
$80,000–$99, 999
14.5
16.0
13.4
≥ $100,000
22.9
27.3
19.9
Rural
19.6
19.9
20.0
Urban
80.4
80.1
80.0
Excellent
17.3
15.8
18.3
Very Good
43.4
43.2
43.6
Good
Place of residence, % (n = 14 294)
Self-rated health status, % (n = 14 036)
33.4
35.3
32.1
Fair
5.3
5.2
5.3
Poor
0.6
0.4
0.7
Non-smoker
80.5
79.8
80.9
Occasional
3.5
3.8
3.2
16.0
16.4
15.8
19.5
21.7
18.0
24.8
29.8
21.4
3.8
4.5
3.3
Current smoking status, % (n = 14 151)
Daily
Hypertension, % (n = 14 031)
Yes
Hypercholesterolemia, % (n = 14 022)
Yes
Diabetes, % (n = 14 237)
Yes
Abbreviations: BMI, body mass index; SD, standard deviation.
219
association between an annual household
income of $100,000 or higher and meeting
CSEP guidelines (OR = 2.51; 95% CI:
1.36–4.63) was higher than for meeting
WCRF/AICR guidelines (OR = 1.56;
95% CI: 1.06–3.27). Participants who rated
their health as good or worse were significantly less likely to meet CSEP guidelines
(OR = 0.54, 95% CI: 0.37–0.80), whereas
participants with self-rated health status
lower than excellent were significantly
less likely to meet ACS (OR = 0.72;
95% CI: 0.52–0.99), USDHHS (OR =
0.72; 95% CI: 0.53–0.97) and WCRF/AICR
(OR = 0.67; 95% CI: 0.47–0.95) guidelines
(Table 4).
Sex and BMI were the only characteristics
found to be significantly associated with
sufficient activity to meet guidelines
relevant for cancer prevention (Table 4).
Women were less likely than men to
meet guidelines recommended by ACS
(OR = 0.72; 95% CI: 0.55–0.93),
USDHHS (OR = 0.67; 95% CI: 0.50–0.89)
or WCRF/AICR (OR = 0.63; 95% CI:
0.47–0.85), though there were no sex
differences in meeting CSEP guidelines
for general health. Being overweight
was associated only with meeting
USDHHS guidelines (OR = 0.52; 95%
CI: 0.39–0.70), whereas being obese was
associated with meeting both USDHHS
(OR = 0.45; 95% CI: 0.32–0.65) and
WCRF/IARC guidelines (OR = 0.79; 95%
CI: 0.63–0.98).
Discussion
Our findings suggest that few Albertans are
participating in sufficient leisure activity
to reduce cancer risk, probably because of
the higher levels of activity required to meet
ACS or WCRF/AICR guidelines compared to
CSEP guidelines for general health. Since
the WCRF/AICR guidelines take almost
3 times as long as do the CSEP guidelines,
participants need to commit more time to
physical activity to benefit from cancer risk
reduction. Thus, retired people, with more
available leisure time, were more likely to be
active at levels recommended for cancer
prevention.
These findings are consistent with the
Health Belief Model, which proposes
that as perceived barriers for a behaviour
Vol 32, No 4, September 2012 – Chronic Diseases and Injuries in Canada
Table 2
Comparison of sociodemographic characteristics between the study sample (2005)
and the Alberta population (2001 Canadian Census data)
Sociodemographic characteristics
Study sample (%)
Alberta (%)a
35–39
16.6
21.4
40–44
20.6
22.5
45–49
20.3
19.7
50–54
17.7
16.0
55–59
14.3
11.5
60–64
10.4
9.0
Men
40.1
50.3
Women
59.9
49.7
18.5–24.9 kg/m2
35.4
43.5
25.0–29.9 kg/m2
39.4
38.1
≥ 30 kg/m2
25.2
18.4
16.0
24.5
increase, the likelihood of performing the
health behaviour decreases.38 Sufficient
leisure activity to reduce cancer risk is
likely associated with greater barriers related
to time, competing commitments, and
motivation than participating in the lower
levels required for general health benefits.
In addition, CSEP guidelines have been
consistently communicated to Canadians
since 1998.15 Canadians who aim to be active
may be striving to meet CSEP guidelines
for general health benefits without being
aware that higher levels of activity are
needed to reduce cancer risk. Perceived
benefits, another component of the
Health Belief Model, are also important to
encourage behaviour;38 increasing public
awareness of the PA guidelines relevant to
preventing cancer may encourage individuals
to use these guidelines as a benchmark for
being physically active.
Age range, years
Sex
BMIb
Current smoking statusb
Daily smoker
Educational attainment
Some high school
8.6
22.3
High school diploma
18.6
16.0
Technical school/College training
39.9
29.1
Some university/University degree
22.9
27.4
Postgraduate university
10.1
5.1
5.8
32.6
$20,000–$39,999
16.2
29.3
$40,000–$59, 999
19.5
19.3
$60,000–$74, 999
19.7
8.2
≥ $75,000
36.6
10.5
In our study, women were less likely
than men to participate in the levels of
leisure activity recommended for cancer
risk reduction, a finding consistent with
other reports,39-41 even after controlling for
other sociodemographic factors. A number
of cultural and social contextual factors,
such as gender roles, result in differences in
PA behaviour between men and women.40-44
Motivating factors are also different;
women more commonly report body
image, appearance and health concerns
as being equally important reasons for
being physically active.45-48 These results
Annual household income
< $20,000
a
Data from 2001 Canada Census.31
b
Data from Canadian Community Health Survey Cycle 2.1 (2003)32
Table 3
Percentage of study population that met physical activity guidelines by organization and type of physical activity, Alberta, 2001–2005
Guidelines
CSEPa
ACSb
USDHHSc
WCRF/AICRd
n
%
n
%
n
%
n
%
8773
62.6
6734
48.1
4115
29.5
3377
24.1
Trend p-valuee
Type of activityf
Leisure
< .0001
Household
7711
55.1
6034
43.1
4156
29.8
3689
26.3
< .0001
Occupation
5680
40.6
5387
38.5
4930
35.3
4841
34.6
< .0001
Active transport
Total physical activityf
470
3.4
162
1.2
50
0.4
72
0.5
< .0001
12 965
92.6
12 322
88.0
10 912
78.1
10 132
72.4
< .0001
Abbreviations: ACS, American Cancer Society; AICR, American Institute for Cancer Research; CSEP, Canadian Society for Exercise Physiology; PA, physical activity;
USDHHS, United States Department of Health and Human Services; WCRF, World Cancer Research Fund.
a
Minimum 2.5 hours/week of moderate to vigorous PA.
b
Minimum 3.75 hours/week of moderate to vigorous PA.
c
Minimum 5 hours/week of moderate to vigorous PA to prevent weight gain.
d
Minimum 7 hours/week of moderate-intensity PA or 3.5 hours/week of vigorous PA.
e
Cochran–Armitage test for trend.
f
Moderate- and vigorous-intensity activity.
Vol 32, No 4, September 2012 – Chronic Diseases and Injuries in Canada
220
Figure 1
Estimateda Alberta population percentage that met physical
activity guidelines through leisure activity, 2001–2005
100%
90%
80%
70%
60%
50%
54.9%
40%
41.9%
30%
26.3%
20%
22.9%
10%
0%
CSEP
ACS
USDHHS
WCRF/AICR
Physical Activity Guidelines
Abbreviations: ACS, American Cancer Society; AICR, American Institute for Cancer Research;
CSEP, Canadian Society for Exercise Physiology; USDHHS, United States Department of Health and Human Services;
WCRF, World Cancer Research Fund.
a
Weighted by health region of residence, age and sex, and further weighted by household income and educational
attainment using 2001 Census data.
suggest that gender differences need to be
considered when prompting PA for cancer
prevention in the population.
Despite gender differences, both men and
women who were either overweight or
obese were significantly less likely than
normal weight individuals to meet USDHHS
and WCRF/AICR guidelines. Given that these
guidelines require 30 to 60 minutes of daily
leisure PA, it is possible that overweight
and obese individuals may be physically
unable to take part in sufficient amounts of
activity or make the lifestyle changes
required to achieve these levels of activity.
In fact, overweight and obese individuals
are less likely than normal weight adults to
adhere to PA programs, even those that
involve only walking.49-50 PA may be especially challenging for those overweight and
obese individuals with pain or discomfort
exacerbated by their weight status.51
Alternatively, these results may reflect the
fact that sufficient activity to meet
USDHHS and WCRF/AICR guidelines aids
in weight loss and protects from unhealthy
weight.52-55 Either way, our results are
consistent with other findings that
overweight and obesity are independently
associated with low levels of PA.51,56-57
Individuals in the highest income category
were the most likely to participate in
sufficient activity to meet all guidelines,
also consistent with previous findings.42,58-59
Low socio-economic status is often
associated with caregiver responsibilities,
time devoted to childcare, physical
labour as an occupation, lack of
transportation, unsafe neighbourhoods,
inflexible work schedules and transient
homes,41 all of which may hamper
participation
in
leisure
activity.
Interestingly, the association between
annual household income and meeting
PA guidelines decreased in strength
as the amount of activity needed to meet
guidelines increased. This relation was
weakest for meeting USDHHS and
WCRF/AICR guidelines, suggesting that
participation in high levels of leisure PA
may be moderated by more complex
intrapersonal factors. The weakening
association between activity and income
may also reflect that retirees were more
frequently middle-class income earners,
yet more likely to meet guidelines for
cancer risk reduction. Despite this
weaker relation, income was still strongly
correlated with meeting guidelines for
cancer prevention.
221
This study is among the first to investigate
the prevalence of PA at levels sufficient for
cancer prevention. So far, estimates of PA
among Canadians have used the CSEP
guidelines as the benchmark for sufficient
activity for health benefits. Using this
approach, the CCHS (cycle 2.1) estimated
that during the time period of this study,
48% of Canadians60 and 52% of Albertans,61
35 to 65 years old, were physically active.61
In comparison, our current study estimated
that 63% of Albertans were sufficiently
active to meet CSEP guidelines (Table 3).
This difference in estimates persisted even
when the estimate was adjusted for age,
sex, income and educational attainment,
suggesting that the study sample differs
from the Alberta population in other
factors that need to be adjusted for when
estimating population prevalence for PA,
which is a complex behaviour. The higher
estimate derived from our study could also
be attributed to a “healthy enrolee” effect.
About 60% of the study sample rated their
health as very good or excellent, and
the study sample had a lower prevalence
of diabetes (3.8% compared to 4.9% for
Albertans61) and smoking than the Alberta
population (16% of the study sample were
daily smokers versus 25% of Albertans).
Despite being more likely to be overweight
and obese, study participants appeared to be
healthier than Albertans as a whole and
may have been more likely to participate
in leisure PA. Differences in leisure PA
measurement between the CCHS and the
PYTPAQ used in our study may also
account for the difference in prevalence
estimates. The CCHS utilized a multi-part
item to report frequency and duration of
participation in a given list of leisure
activities over the past three months.62 In
contrast, the PYTPAQ assessed leisure
activity over the past year using a more
detailed approach that permitted participants to report duration, frequency and
intensity of all recreational and sports
activities. The PYTPAQ was more likely to
reflect usual activity patterns, while the short
time frame of the CCHS questionnaire
may be more influenced by seasonal
variation and acute illness.63
During the study period, 45.9% of U.S.
adults64 and 29% of European Union
adults from 15 countries65 were estimated
to participate in 150 minutes of moderate
Vol 32, No 4, September 2012 – Chronic Diseases and Injuries in Canada
Table 4
Estimated odds ratiosa for meeting physical activity guidelines through leisure activity, Alberta, 2001–2005
Guidelines
Variable
Age, years
35–39
40–44
45–49
50–54
55–59
60–65
Sex
Male
Female
BMI, kg/m2
18.5–24.9
25.0–29.9
≥ 30.0
Marital Status
Married/Common law
Divorced, separated or widowed
Single
Educational attainment
Some high school
High school diploma
Technical school/College
Some university/University degree
Postgraduate university
Employment status
Employed full-time
Employed part-time
Unemployed
Retired
Self-employed
Annual household income
< $20,000
$20,000–$39,999
$40,000–$59,999
$60,000–$79,999
$80,000–$99,999
≥ $100,000
Self-rated health status
Excellent
Very Good
Good
Fair or Poor
Current smoking status
Non-smoker
Occasional
Daily
Social Supportf
ACSc
OR (95% CI)
CSEPb
OR (95% CI)
1.00
1.02
0.98
0.81
0.80
0.75
1.00
0.99
0.98
0.86
0.80
0.72
(0.69, 1.51)
(0.66, 1.44)
(0.54, 1.22)
(0.52, 1.25)
(0.44, 1.28)
(0.68, 1.44)
(0.68, 1.43)
(0.58, 1.27)
(0.52, 1.24)
(0.42, 1.22)
USDHHSd
OR (95% CI)
1.00
0.94
0.91
0.86
0.74
0.72
(0.63, 1.41)
(0.61, 1.37)
(0.56, 1.32)
(0.46, 1.21)
(0.40, 1.29)
WCRF/AICRe
OR (95% CI)
1.00
0.91
0.87
0.82
0.75
0.67
(0.60, 1.39)
(0.57, 1.34)
(0.53, 1.29)
(0.45, 1.24)
(0.36, 1.24)
1.00
0.85 (0.65, 1.11)
1.00
0.72 (0.55, 0.93)
1.00
0.67 (0.50, 0.89)
1.00
0.63 (0.47, 0.85)
1.00
0.96 (0.72, 1.28)
0.82 (0.60, 1.14)
1.00
0.94 (0.71, 1.23)
0.83 (0.60, 1.13)
1.00
0.52 (0.39, 0.70)
0.45 (0.32, 0.65)
1.00
0.96 (0.71, 1.31)
0.79 (0.63, 0.98)
1.00
1.54 (1.06, 2.26)
1.41 (0.84, 2.36)
1.00
1.63 (1.12, 2.35)
1.50 (0.90, 2.49)
1.00
1.62 (1.08, 2.43)
1.52 (0.87, 2.66)
1.00
1.51 (1.09, 2.10)
1.52 (0.85, 2.71)
1.00
1.20
1.28
1.40
1.40
(0.73, 1.95)
(0.81, 2.02)
(0.85, 2.30)
(0.78, 2.53)
1.00
1.06
1.10
1.22
1.08
(0.64, 1.74)
(0.69, 1.75)
(0.74, 2.01)
(0.61, 1.92)
1.00
0.91
0.90
1.03
0.91
(0.52, 1.61)
(0.53, 1.53)
(0.59, 1.81)
(0.48, 1.71)
1.00
1.00
0.93
1.12
0.97
(0.55, 1.81)
(0.54, 1.61)
(0.62, 2.01)
(0.50, 1.87)
1.00
1.19
1.19
2.30
0.74
(0.84, 1.69)
(0.81, 1.75)
(1.32, 4.01)
(0.21, 2.62)
1.00
1.27
1.27
2.65
0.76
(0.90, 1.78)
(0.87, 1.86)
(1.56, 4.48)
(0.21, 2.77)
1.00
1.19
1.40
3.04
0.97
(0.81, 1.73)
(0.92, 2.13)
(1.74, 5.31)
(0.22, 4.19)
1.00
1.11
1.41
2.76
1.20
(0.74, 1.67)
(0.91, 2.18)
(1.57, 4.87)
(0.29, 4.99)
1.00
1.16
1.26
1.62
1.80
2.51
(0.66, 2.04)
(0.71, 2.22)
(0.90, 2.90)
(0.97, 3.34)
(1.36, 4.63)
1.00
1.14
1.27
1.52
1.79
2.43
(0.64, 2.04)
(0.71, 2.26)
(0.84, 2.75)
(1.17, 2.75)
(1.32, 4.48)
1.00
1.06
1.16
1.39
1.58
2.05
(0.55, 2.06)
(0.60, 2.25)
(0.71, 2.74)
(0.78, 3.20)
(1.03, 4.08)
1.00
0.99
1.03
1.20
1.30
1.56
(0.49, 1.98)
(0.51, 2.06)
(0.59, 2.43)
(0.62, 2.73)
(1.06, 3.27)
1.00
0.75 (0.52, 1.08)
0.54 (0.37, 0.80)
0.38 (0.21, 0.71)
1.00
0.72 (0.52, 0.99)
0.52 (0.36, 0.74)
0.36 (0.19, 0.67)
1.00
0.72 (0.53, 0.97)
0.50 (0.34, 0.73)
0.37 (0.17, 0.78)
1.00
0.67 (0.47, 0.95)
0.47 (0.32, 0.71)
0.40 (0.19, 0.85)
1.00
1.14 (0.58, 2.23)
0.65 (0.47, 0.90)
1.12 (0.96, 1.31)
1.00
1.17 (0.62, 2.22)
0.70 (0.50, 0.97)
1.09 (0.94, 1.28)
1.00
1.16 (0.58, 2.31)
0.77 (0.53, 1.13)
1.08 (0.91, 1.28)
1.00
1.13 (0.56, 2.32)
0.82 (0.55, 1.22)
1.04 (0.87, 1.25)
Abbreviations: ACS, American Cancer Society; AICR, American Institute for Cancer Research; CI, confidence interval; CSEP, Canadian Society for Exercise Physiology; OR, odds ratio;
USDHHS, United States Department of Health and Human Services; PA, physical activity; WCRF, World Cancer Research Fund.
Note: Bolded values are significant.
a
Estimated from logistic regression using 10-fold cross-validation.
b
Minimum 2.5 hours/week of moderate to vigorous PA.
c
Minimum 3.75 hours/ week of moderate to vigorous PA.
d
Minimum 5 hours/week of moderate to vigorous PA to prevent weight gain.
e
Minimum 7 hours/week of moderate-intensity PA or 3.5 hours/week of vigorous PA.
f
Using the Medical Outcomes Study Social Support Survey.30
Vol 32, No 4, September 2012 – Chronic Diseases and Injuries in Canada
222
to vigorous activity per week through
large population-based surveys. Similarly,
a recent study estimated that 15% of
Canadian adults are active at these levels.66
However, because these estimates included
participation in occupational, transportation
and household activities in addition to
leisure PA, it is difficult to compare them
with our estimates, which considered
only leisure PA. Total PA has been used to
estimate PA prevalence estimates in the
different jurisdictions,64,67-69 but a focus on
leisure PA is valuable since this type of
activity is most likely to be modifiable,
unlike occupational and household activities. Established evidence suggests that
risk for breast, colorectal, prostate and
endometrial cancers is significantly reduced
when higher intensity PA is undertaken.6,8,70
This is likely the result of a shift in inflammation biomarkers, insulin resistance, and
sex and metabolic hormone levels that
favour cancer risk reduction in response
to moderate and vigorous leisure activities
but not to light intensity household
activities.12,71 Therefore, leisure PA is a logical
target for population health interventions
aimed at cancer prevention.
Limitations of the study
Our study had some limitations, including
in interpreting the findings. Although fairly
typical of random digit dialing (RDD)
studies, the response rate was low, at
less than 25%, and the unweighted
sample was not representative of the
Alberta population. Despite trying to weight
prevalence estimates to reflect more closely
those of the Alberta population, the generalizability of our results may be limited.
The data regarding PA were self-reported,
which may result in over-reporting of
activity levels due to social desirability
bias. Measurement error and inaccurate
estimates may have also come about
because it can be difficult to recall PA;18
participants in our study were asked to
remember exercise patterns from over a
year-long period. However, the PYTPAQ
has been shown to be valid and reliable
in a large random sample of men and
women.25 Our use of previously validated
and reliability-tested instruments to measure
PA and all other variables helped to
minimize potential measurement error.25
In addition, the cross-sectional design of
this study limits the interpretation of
results to correlations and not as causal
associations. Nonetheless, these results
have identified factors that warrant further
investigation as important intervention
targets for increasing PA for cancer
prevention in the population.
Recommendations
Given that 42% of Albertans are insufficiently active for general health benefits,
future interventions should focus on
encouraging sedentary individuals to
exercise. These efforts should include the
promotion of higher levels of PA to confer
additional benefits for cancer prevention
among this segment of the population
as well as those who are already active.
In 2005, Canadians spent approximately
6 hours each day on leisure activities,
from watching television and surfing
the internet, to participating in numerous
hobbies, both sedentary and active.72
The availability of so many options for
leisure time activities poses a challenge
for physical activity promotion. It also
highlights the need for effective interventions that strengthen those factors that
facilitate physical activity and reduce any
barriers to them.
Current national guidelines may not be
sufficient for cancer prevention, nor for
weight management.21 Given the ample
evidence that obesity contributes to cancer
risk, promoting sufficient levels of PA to
support weight loss and management
may be an important target for cancer
prevention strategies in the population.
Moreover, the specific dose of necessary
PA is not clear, hence the variations in the
guidelines. Guideline development depends
on the evolving research linking PA to
cancer,19-21 which has consisted mainly of
observational studies of varying designs.73
Randomized trials are needed to make
definitive dose recommendations, and until
these exist, it may be prudent to provide a
graded set of guidelines that highlight the
health benefits associated with various
levels and intensities of PA, including those
levels that will lead to a greater cancer
223
risk reduction.74 Lastly, further research is
needed to develop effective interventions to
promote PA that include individual-level
motivational factors as well as social and
environmental facilitators of PA.
Acknowledgments
This project was funded by the Alberta
Cancer Foundation. Fabiola Aparicio-Ting
was supported by a Doctoral Studentship
from the Canadian Cancer Society. Christine
Friedenreich was supported by a Health
Senior Scholar Award from the Alberta
Heritage Foundation for Medical Research.
Ronald Plotnikoff was supported by an
Applied Public Health Chair from the
Canadian Institutes of Health Research.
The authors gratefully acknowledge Paula
Robson, Principal Investigator for the
Tomorrow Project, for sharing baseline
data from this cohort. Thanks also to
Heather Whelan and Will Rosner for their
assistance in accessing and using the
Tomorrow Project dataset.
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226
National Fall Prevention Workshop: stepping up pan-Canadian
coordination
Centre for Health Promotion, Public Health Agency of Canada; British Columbia Injury Research and Prevention
Unit (BCIRPU)
Background
About one in three Canadian seniors will
experience a fall at least once each year.1-4
Such falls are the leading cause of
injury-related hospitalizations among older
people.5 Apart from causing injury, falls
can result in chronic pain, reduced
quality of life and, in severe cases, death.
Psychological effects of a fall may cause a
post-fall syndrome that includes dependence
on others for daily activities, loss of
autonomy, confusion, immobilization and
depression.1
Falls and the resulting injuries often occur
due to a combination of factors, including
health conditions associated with aging such
as vision problems, osteoporosis, dementia
and symptoms of a chronic disease.
They can be due to the side effects of
medications, environmental hazards and
risk-taking behaviours.
Fall prevention initiatives and strategies
are taking place in all provinces and
territories and at the national level. To
enhance the collaborative understanding
of these initiatives, a National Fall
Prevention Workshop was held at the
Canadian Injury Prevention and Safety
Promotion Conference in Vancouver,
British Columbia, on 17 November 2011.
The Workshop was co-hosted by the
British Columbia Injury Research and
Prevention Unit (BCIRPU) and the Public
Health Agency of Canada (PHAC). Fall
prevention leads from each province and
territory were invited to present their most
recent activities and their plans. This
event proved to be highly successful with
over 60 attendees representing all the
provinces and Yukon (see Table 1).
Table 1
Workshop attendees and presenters
Jurisdiction
Agency represented
Canada
Division of Aging and Seniors, Public Health Agency of Canada
British Columbia
BC Ministry of Health
BC Injury Research and Prevention Unit
Health Professions Strategy & Practice, Alberta Health Services
Alberta
Alberta Centre for Injury Control & Research
Fall Risk Management Program, Alberta Heath Services - Calgary Zone
Saskatchewan
Acquired Brain Injury Partnership Project, Ministry of Health
Manitoba
Department of Manitoba Healthy Living, Youth and Seniors, Healthy
Living and Populations Branch
Ontario
Ontario Injury Prevention Resource Centre
SMARTRISK
Quebec
Institut national de santé publique du Québec
New Brunswick
Office of the Chief Medical Officer of Health, New Brunswick
Department of Health
Prince Edward Island
Spectrum Solutions
Nova Scotia
Nova Scotia Department of Health and Wellness
Newfoundland and
Labrador
Chronic Disease Control Division, Department of Health and
Community Services
Yukon
Arctic Institute of Community-Based Research
Workshop objectives
The objectives of the 2011 National Fall
Prevention Workshop were to
1)
bring together federal, provincial
and territorial leads interested in
collaborating on evidence-based,
clinically
relevant
programming,
policy and practice to reduce the
risk
of
falls
and
related
injuries among older adults in
Canada;
2) present model strategic fall prevention
plan components from each province/
territory;
3)discuss current best practices and
their application in each province and
territory, including data standardization
for fall-related morbidity, fall risk
assessment tools and protocols,
implementation of best practices
and evaluation of progress and
outcomes.
Summary of workshop discussions
Education and training
Education of health care providers was
identified as a priority, with the Canadian
Fall Prevention Curriculum (CFPC) cited by
most participants as the training program
of choice. Standardizing and integrating
fall prevention training into postsecondary
education was considered an important
next step.
Correspondence: Director General’s Office, Centre for Health Promotion, Public Health Agency of Canada, Jeanne Mance Building, 1909A, Ottawa, ON K1A 0K9; Tel.: (613) 954-1691;
Fax: (613) 941-0443; Email: carolyn.landry@phac-aspc.gc.ca
227
Vol 32, No 4, September 2012 – Chronic Diseases and Injuries in Canada
Accreditation
Next steps
References
Accreditation
Canada’s
Required
Organizational Practices for fall prevention
was frequently cited as the impetus for
developing fall prevention strategies in
health care settings.6
The 2011 National Fall Prevention
Workshop introduced the idea of a National
Fall Prevention Collaborative composed of
the provincial and territorial leads who
presented at the workshop, with the
potential for other interested stakeholders
to participate. The presenters all agreed to
build on the momentum from the workshop
to formally establish a practice network
and virtual library of best/promising
practices. In the interests of further
collaboration—and building on the success
of the workshop—participants recommended
a larger-scale national conference on fall
preventions, which could take place in 2014,
to bring together provincial/territorial and
federal health care providers and policy
makers as well as other interested
stakeholders to share knowledge and
create networks that further advance fall
prevention initiatives.
1. World Health Organization. WHO global
report on falls prevention in older age. Geneva
(CH): World Health Organization; 2007.
Leadership and strategic planning
Many attendees identified that while work
on fall prevention is ongoing in parts of
their jurisdictions, there is no consistency
across their province or territory. Some
participants recommended developing a
sustainable, evidence-based fall prevention
strategy with feasible solutions to facilitate
a coordinated approach; however, it was
noted that fiscal considerations were a
limiting factor to implementing such
initiatives.
Team communication
Networks and coalitions were frequently
referred to as an important medium
for professionals to communicate about
implementing fall prevention programming.
Data and surveillance
Jurisdictions that reported having access to
data were able to demonstrate a positive
relationship between their fall prevention
programs and a reduction in falls and
fall-related injuries. Several jurisdictions
reported that lack of data and surveillance
at the setting and at provincial/territorial
level made it difficult to evaluate programs
rigorously.
Acknowledgements
The workshop organizers wish to thank the
workshop attendees for their involvement
and collaboration. Special thanks are also
extended to Joanne Veninga, Lori Wagar
and Sarah Elliot for their assistance in
organizing the workshop.
Vol 32, No 4, September 2012 – Chronic Diseases and Injuries in Canada
228
2. Scott VJ, Peck SH, Kendall PR. Prevention
of falls and injuries among the elderly: a
special report from the Office of the
Provincial Health Officer, January 2004.
Victoria (BC): Provincial Health Officer,
British Columbia Ministry of Health
Planning; 2004.
3. Tinetti ME, Speechley M. Prevention of
falls among the elderly. N Engl J Med.
1989;320(16):1055-9.
4. O’Loughlin JL, Robitaille Y, Boivin JF,
Suissa S. Incidence of and risk factors
for falls and injurious falls among the
community-dwelling elderly. Am J Epidemiol.
1993;137:342-54.
5. Public Health Agency of Canada. Report on
seniors’ falls in Canada. Ottawa (ON):
Division of Aging and Seniors, Public Health
Agency of Canada; 2005.
6. ROPS: Required Organizational Practices –
September 2011. Ottawa (ON): Accreditation
Canada; 2011 Jul [cited 2012 Feb 2].
Available from: http://www.accreditation.ca
/uploadedFiles/ROP%20Handbook.pdf
Report summary
Injury in Review, 2012 Edition: Spotlight on Road
and Transport Safety
M. Cardinal, MSc; J. Crain, MA; M. T. Do, PhD; M. Fréchette, MSc; S. McFaull, MSc; R. Skinner, MSP;
W. Thompson, MSc
Abstract
Injury in Review, 2012 Edition: Spotlight
on Road and Transport Safety, the
first national public health report of its
kind, synthesizes road- and transportrelated injury statistics from a variety of
sources. It profiles injury patterns among
Canadians aged up to 24 years, explains
risks and protective factors, and makes
recommendations for action. The findings
inform the development of targeted injury
prevention efforts.
The current report presents national
surveillance statistics on injury and
mortality in Canada from the leading
causes, including road- and transportrelated causes, among children, youth
and young adults aged up to 24 years.†
It also contains important information
and tips for young people, parents,
caregivers and others interested in helping
to prevent road- and transport-related
injuries.
have declined sharply since the early
1970s; most notably, the mortality rate for
those aged 15 to 24 years declined from
46.4 per 100 000 population in the early
1970s to 15.0 per 100 000 population
in 2007. It is important to note that this
dramatic decline started within two years
of the introduction of mandatory seat
belts in all new cars in 1971.
Select Results
In 2007, 20- to 24-year-old men were 3 times
more likely to die in MVT collisions than
were women in the same age group.
Introduction
Mortality
Hospitalization
Injuries* are the leading cause of death
among Canadians aged 1 to 44 years
and the fourth leading cause of death
among Canadians of all ages. Many
non-fatal injuries result in impairments
and disabilities such as blindness, spinal
cord injury and intellectual deficit due
to brain injury. Between 1979 and 2007
(the year of the most recent available
data for all provinces and territories at
time of publication), the number of
road fatalities in Canada decreased by
73%; however, motor vehicle traffic
collisions remain the leading cause of
injury death among Canadians aged 1 to
24 years.
Injury was the leading cause of death
among Canadians aged 1 to 44 years
and the fourth leading cause of death
among all Canadians of all ages in 2007.
Suffocation was the leading cause of
injury-related mortality among infants
(< 1 year), while motor vehicle traffic
(MVT) collisions led among those aged
1 to 24 years, suicide among those
aged 25 to 69 years, and falls among
those aged 70 years or older.
In 2008/2009,‡ injury was the leading
cause of hospitalization among Canadians
aged 10 to 24 years and the third
leading cause of hospitalization among
Canadians of all ages. Falls were the leading
cause of injury-related hospitalization
overall; however, among 15- to 19-year-old
youth, intentional self-harm was the
leading cause of hospitalization. Of every
100 000 Canadians aged under 25 years,
418 were hospitalized due to injuries in
general and 46 due to unintentional MVT
collisions. In the same period, 20- to
24-year-old men were almost twice as likely
to be hospitalized for injury compared
with women (odds ratio [OR] = 1.8).
In 2007, of every 100 000 Canadians
aged under 25 years, 19 were fatally
injured, 7 as a result of unintentional
MVT-related collisions. MVT-related deaths
* All causes of injury (intentional and unintentional) excluding adverse effects due to medical or surgical care.
†
Alcohol-related mortality statistics also refer to older age groups.
‡
Hospitalization data are traditionally reported according to a fiscal year beginning April 1 and ending on March 31 the following year. Canadian Hospitals Injury Reporting
and Prevention Program (CHIRPP) statistics are also presented by fiscal year to allow for timely reporting on the most recent data available and for comparability with hospitalization
statistics.
Author reference:
Injury Section, Health Surveillance and Epidemiology Division, Centre for Chronic Disease Prevention and Control, Ottawa, Ontario, Canada
Correspondence: Jennifer Crain, Injury Section, Health Surveillance and Epidemiology Division, Centre for Chronic Disease Prevention and Control, 200 Eglantine Driveway,
Tunney’s Pasture, AL D1910, Ottawa, ON K1A 0K9; Tel.: (613) 941-8635; Fax: (613) 941-9927; Email: Jennifer.Crain@phac-aspc.gc.ca
229
Vol 32, No 4, September 2012 – Chronic Diseases and Injuries in Canada
Off-highway vehicle-related injuries
Data for 2008/2009 from the Canadian
Hospitals Injury Reporting and Prevention
Program (CHIRPP)§ show that the pro­por­tion
of young Canadians (0-24 years of age)
admitted to hospital for off-highway vehicle
(OHV)-related injuries was almost twice
that of those admitted for MVT-related
injuries, at 24.8% versus 13.8%, respectively.
The number of injuries reported by CHIRPP
increased almost 3-fold for all-terrain
vehicles (ATVs) from 1990/91 to 2008/09.
Of the OHV-related cases involving children
aged 11 to 15 years, the proportion of these
underage drivers injured while in the
driver’s seat was 60% for ATV-related
injuries, 48% for snowmobiles, and 92%
for dirt bikes, proportions similar to those
observed for 0- to 24-year-olds. For young
adults aged 20 to 24 years, the number of
ATV-related injuries was more than twice
that of dirt bike-related injuries; almost half
of all injuries associated with OHV-related
collisions among those under 25 years old
were fractures.
Vulnerable road users
Vulnerable road users (VRUs) are defined as
roadway users who are unprotected by any
vehicle structure, for example, cyclists. In
the event of a crash, VRUs are susceptible
to injury or death due to mass differential.
VRUs can be classified as powered or
non-powered. Injury in Review, 2012 Edition
presents annual proportions of non-powered
and powered VRU cases reported to CHIRPP,
including, for example, pedestrians, pedal
cyclists, motorcyclists, and moped and
scooter riders.
Restraint use for motor-vehicle occupants
Based on data from Transport Canada’s
National Collision Database, between 1998
and 2008, unrestrained occupants of
§
light-duty vehicles (passenger cars, light
trucks, vans and sport-utility vehicles
[SUVs]) involved in collisions were 3 times
more likely to be injured (OR = 3.4) and
16 times more likely to die as a result
of injuries (OR = 15.7) sustained in
collisions compared with the occupants
who used restraints.
Alcohol-related mortality
Based on data from the Traffic Injury
Research Foundation’s Fatality Database,**
38% of motor vehicle-related fatalities in
Canada in 2009 involved alcohol use, with
males approximately twice as likely to die
in alcohol-related collisions compared
with females (OR = 2.3). From 1998
to 2009, there was no significant decrease
in the annual proportion of motor
vehicle-related fatalities involving alcohol
use,†† demonstrating the need for further
prevention efforts.
Canada, the Traffic Injury Research
Foundation and other partners to research
and advance knowledge and road safety
policies and programs. Together we are
contributing to making Canada a safer
place for road users.
Ordering instructions for Injury in Review,
2012 Edition: Spotlight on Road and
Transport Safety are available at http://
w w w. p h a c - a s p c. g c. c a / i n j u r y - b l e s /
chirpp/injrep-rapbles/index-eng.php.
Acknowledgements
Injury in Review, 2012 Edition: Spotlight
on Road and Transport Safety was produced
by the Public Health Agency of Canada
in collaboration with Safe Kids Canada
and the Traffic Injury Research Foundation.
PHAC would like to express its appreciation
to all collaborators for their valuable role
in this project.
Economic burden
References
Injury impacts the families of those
who are injured and society as a whole.
From a health-oriented perspective, the
economic burden of unintentional and
intentional injuries in Canada, for all
causes and ages combined, was estimated
to be $19.8 billion in 2004 (including
both direct and indirect costs), 19% of
which related to transport incidents alone.1
1.SMARTRISK. The Economic Burden
of Injury in Canada. Toronto (ON):
SMARTRISK; 2009.
Next steps
Surveillance statistics show an important
decline in the rates of motor vehicle
traffic-related injuries over the past
three decades. Nevertheless, injuries, and
in particular transport-related incidents,
are a major public health challenge in
Canada, and further injury prevention
efforts are necessary. The Public Health
Agency of Canada (PHAC) continues to
collaborate with Health Canada, Safe Kids
The Canadian Hospitals Injury Reporting and Prevention Program (CHIRPP) is an injury surveillance system that collects and analyzes data on injuries, mainly to children, seen
at the emergency rooms of the 11 paediatric hospitals and 4 general hospitals in Canada. CHIRPP is a unique, richly detailed database of injury information.
**The Fatality Database is developed and managed by the Traffic Injury Research Foundation. The following agencies have provided funding for the Fatality Database: Health Canada
(1973-1982); Transport Canada and the Canadian Council of Motor Transport Administrators (1984-2010; their funding for the Database has been in support of the Strategy to Reduce
Impaired Driving for several years).
Fatalities are considered to be alcohol-involved if the fatally injured person was a driver or pedestrian who had been drinking or if at least one driver involved in the collision had
been drinking; passenger fatalities are also considered to be alcohol-involved if one of the drivers involved had been drinking. The percentage of alcohol-involved fatalities is calculated
from the number of deceased persons categorized as an alcohol-involved fatality, divided by the total number of cases where alcohol involvement in the collision was known.
††
Vol 32, No 4, September 2012 – Chronic Diseases and Injuries in Canada
230
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