HP33-2-35-1-eng .

HP33-2-35-1-eng .
Health Promotion and
Chronic Disease Prevention
in Canada
Research, Policy and Practice
Volume 35 · Number 1 · March 2015
Inside this issue
1
Editorial – Mobilizing Evidence for Impact: From CDIC to Health
Promotion and Chronic Disease Prevention
3
Chronic fatigue syndrome and fibromyalgia in Canada: prevalence and
associations with six health status indicators
12
A DASH dietary pattern and the risk of colorectal cancer in Canadian
adults
21
Report Summary – Congenital Anomalies in Canada 2013: A Perinatal
Health Surveillance Report by the Public Health Agency of Canada’s
Canadian Perinatal Surveillance System
23
Report Summary – Perinatal Health Indicators 2013: a Surveillance
Report by the Public Health Agency of Canada’s Perinatal Surveillance
System
25
Release notice: Data release for the Canadian Longitudinal Study on
Aging
26
With thanks to our 2014 peer reviewers
27
Other PHAC publications
Health Promotion and Chronic Disease
Prevention in Canada
a publication of the Public Health Agency of Canada
HPCDP Editorial Board
Margaret de Groh, PhD
Gerry Gallagher, MBA, MPA
Editor-in-Chief
Public Health Agency of Canada
Claire Infante-Rivard, MD, PhD, FRCPC
Associate Scientific Editor
Barry Pless, CM, MD, FRCPC
Associate Scientific Editor
Elizabeth Kristjansson, PhD
Associate Scientific Editor
Robert Geneau, PhD
International Development Research Centre
Brent Hagel, PhD
University of Calgary
Isra Levy, MB, FRCPC, FACPM
Ottawa Public Health
Gavin McCormack, PhD
Associate Scientific Editor
Lesli Mitchell, MA
US Centers for Disease Control and Prevention
Michelle Tracy, MA
Managing Editor
613-716-4523
Scott Patten, MD, PhD, FRCPC
Sylvain Desmarais, BA, BEd
Production Editor
Richard Stanwick, MD, FRCPC, FAAP
University of Calgary
Island Health
Joanna Odrowaz, BSc
Freelance Copyeditor
Ania Syrowatka, MSc
Anna Olivier, PhD
Freelance Copyeditor
Wendy Thompson, MSc
McGill University
Public Health Agency of Canada
Andreas T. Wielgosz, MD, PhD, FRCPC
Public Health Agency of Canada
Russell Wilkins, MUrb
Health Promotion and Chronic Disease Prevention in Canada: Research, Policy and Practice
(HPCDP) is a monthly online scientific journal
that showcases applied science and research on
disease prevention, health promotion and
health equity in the areas of chronic diseases,
injuries and life course health, with a key focus
on the Public Health Agency of Canada’s
research and collaborations. Since 1980 the
journal has published a unique blend of
peer-reviewed feature articles from such fields as
epidemiology, public/community health, biostatistics, the behavioural sciences, and health
services or economics. Authors retain responsibility for the content of their articles; the
opinions expressed are not necessarily those of
the HPCDP editorial committee nor of the
Public Health Agency of Canada.
Health Promotion and Chronic Disease
Prevention in Canada
Public Health Agency of Canada
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To promote and protect the health of Canadians through leadership, partnership, innovation and action in public health.
— Public Health Agency of Canada
Published by authority of the Minister of Health.
© Her Majesty the Queen in Right of Canada, represented by the Minister of Health, 2015
ISSN 2368-738X
Pub. 140397
This publication is also available online at www.publichealth.gc.ca/cdic
Également disponible en français sous le titre : Promotion de la santé et prévention des maladies chroniques au Canada
Editorial
Mobilizing Evidence for Impact: From CDIC to Health
Promotion and Chronic Disease Prevention
Kerry Robinson, PhD, Publisher, Health Promotion and Chronic Disease Prevention in Canada
Michelle Tracy, MA, Managing Editor, Health Promotion and Chronic Disease Prevention in Canada
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The journal Health Promotion and Chronic
Disease Prevention in Canada: Research,
Policy and Practice (HPCDP) (formerly
Chronic Diseases and Injuries in Canada
[CDIC]) had humble beginnings at Health
Canada in 1980 as a ‘‘New Bulletin’’
aimed at publishing ‘‘material based on
research, surveillance and control aspects
of non-communicable diseases or conditions such as cancer, heart disease and
accidents.’’1 The main audience for this
new national publication was the estimated 300 to 400 Canadian professionals
involved directly or indirectly in programs
related to chronic disease.
AECL (Atomic Energy of Canada Limited)
Nuclear Review. As a federal government
publication, HPCDP will feature articles
that showcase applied science and
research on disease prevention, health
promotion and health equity in the areas
of chronic diseases, injuries and life
course health, with a key focus on the
Public Health Agency of Canada’s
research and collaborations. It is important to note, however, that the new model
does not represent a change in topic scope
for the journal, as CDIC has been publishing in each of these areas for over a
decade.
Now, 35 years later, with an impact factor
of 1.22, the journal has become a credible
source of peer-reviewed scientific research
and an important platform for knowledge
exchange within Canada’s public health
community. As an open-access and bilingual journal, it also serves readers in the
United States, Europe and francophone
Africa. To date, the journal has published
hundreds of articles on a range of topics
from maternal health to injuries to cancer
trends. It has a robust online presence via
many scientific publication indexes and
aggregators, including MEDLINE, Thomson
Reuters, Elsevier, SCOPUS and EBSCO.
The journal will maintain its high scientific credibility by maintaining central
inclusion of external associate scientific
editors and peer reviewers, as well as an
editorial board primarily composed of
members external to the federal government. These external advisors will continue to contribute their expertise to
reviewing papers and ensuring that the
articles published in HPCDP remain of
high quality and expand upon the latest
pan-Canadian knowledge in this field.
Just as the journal’s subject matter has
expanded over time and we have moved
from a small printing press to an online,
fully accessible publication, the journal is
now evolving its governance and production model. The new governance model is
based on existing governance practices
for government-published journals, like
Statistics Canada’s Health Reports or the
HPCDP’s new model also represents a
move from passive knowledge dissemination to a more integrated model involving
interactive and collaborative knowledge
exchange. Within the realm of knowledge
translation, traditional (passive) dissemination approaches often result less successfully in uptake of public health
innovations.2 It was within this context,
and within the context of a transformation
of science governance as a whole within
the Public Health Agency of Canada (the
publisher of this journal), that a new
governance and publishing model for the
journal was proposed.
In the past, public health has emphasized
the creation and publication of applied
research; however, there is now a growing
need for this knowledge to be better
synthesized and translated for use by a
range of decision makers.3,4 The renewed
HPCDP will showcase the breadth and
quality of collaborative government
science, surveillance and intervention
evaluation/studies. The journal represents
an important dissemination platform for
the Agency’s peer-reviewed health promotion and chronic disease prevention
science. Our goal is to continue to grow
the journal as a much-needed vehicle to
share and support use of peer-reviewed
public health science/research, analysis
and related collaborative work with
applied research, policy and practice
audiences in Canada.
As part of its aim to increase policy
relevant and intervention-related evidence
that can help inform policy and practice
decisions, HPCDP has expanded its types
of articles to include evidence syntheses
and evidence briefs, qualitative and mixed
methods studies and intervention studies,
as well as a section called ‘‘At-a-Glance’’
that allows for quick statistics updates
from the latest surveillance analyses [see
http://www.phac-aspc.gc.ca/publicat/hpcdp
-pspmc/authinfo-eng.php].
HPCDP is also demonstrating its responsiveness to a need for increased mobilization for uptake and impact. While a 2012
Author reference:
Public Health Agency of Canada
Vol 35, No 1, March 2015
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Health Promotion and Chronic Disease Prevention in Canada
Research, Policy and Practice
Stakeholder Satisfaction Survey showed
that most respondents were satisfied with
the journal (90% overall satisfaction),
some remarked that using social media
to promote journal content would increase
awareness of and access to the journal.
With this and the demand for quicker
access to evidence in view, the journal has
now become a monthly, online-only publication, which allows us to accelerate the
frequency and timeliness of article release.
We will be promoting and sharing published findings through professional social
networking sites, webinars and social
media platforms and looking into mobile
options for the journal.
Going forward, the journal will place greater
emphasis on collaborative research and
analysis between government and external
researchers, a range of public health practitioners, health policy planners and related
professionals. As part of this new model, the
journal particularly welcomes articles
resulting from a substantive collaboration
with the Public Health Agency or Health
Canada, through co-authorship (including
with staff from the Canadian Institutes of
Health Research), funding or use of Public
Health Agency or Health Canada data.*
In the same collaborative vein, HPCDP is
being renewed to also increase access and
use of a broader range of public health and
community systems knowledge.4 The
Agency will be in a position to share
externally in a more timely fashion the
various evidence syntheses and high quality Canadian scans that we conduct in
collaboration with others; these are often
not published by other means on the web
or disseminated broadly.
the Agency’s latest surveillance reports on
two important areas, perinatal health indicators and congenital anomalies. Finally,
please do look at the section ‘‘Other PHAC
Publications,’’ which highlights and links
to peer-reviewed article collaborations published in other venues.
We hope that you enjoy some of the
features of our new journal model. On
behalf of our colleagues at the Public
Health Agency of Canada, we look forward to collaborating with you on the
creation, synthesis and mobilization of
applied research and analysis for positive
impact on health promotion and chronic
disease prevention in Canada.
References
1.
Clayton AJ. Guest editorial – Launching of
new bulletin. Chronic Dis Can. 1980;1(1):1.
2.
Robinson K, Elliott SJ, Driedger SM, et al.
Using linking systems to build capacity and
enhance dissemination in heart health
promotion: a Canadian multiple-case study.
Health Educ Res. 2005;20(5):499-513.
3.
Speller V, Wimbush E, Morgan A.
Evidence-based health promotion practice:
how to make it work? Promot Educ. 2005;
Suppl 1:15-20.
4.
McDonald PW, Viehbeck S. From Evidencebased practice making to practice-based
evidence making: creating communities of
(research) and practice. Health Promot
Pract. 2007;8(2):140-4.
We are pleased to welcome you to this
inaugural issue of the journal’s new model.
The original research articles ‘‘A DASH
dietary pattern and the risk of colorectal
cancer among Canadian adults,’’ by JonesMcLean et al., and ‘‘Chronic fatigue
syndrome and fibromyalgia in Canada:
Prevalence and associations with six health
status indicators,’’ by Rusu et al., contribute to the Canadian evidence base in these
fields. This issue also features summaries of
* PHAC/Health Canada data are defined as those datasets that are owned (solely or collaboratively) by PHAC or Health Canada, or of which PHAC or Health Canada are the custodians or
guardians.
Health Promotion and Chronic Disease Prevention in Canada
Research, Policy and Practice
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Vol 35, No 1, March 2015
Chronic fatigue syndrome and fibromyalgia in Canada:
prevalence and associations with six health status indicators
C. Rusu, MD (1); M. E. Gee, MSc (1); C. Lagacé, MSc (1); M. Parlor, LLB (2)
This article has been peer reviewed.
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Abstract
Introduction: Few studies have considered the factors independently associated with
chronic fatigue syndrome (CFS) and/or fibromyalgia (FM) or considered the impact of
these conditions on health status using population-based data.
Methods: We used data from the nationally representative 2010 Canadian Community
Health Survey (n= 59 101) to describe self-reported health professional-diagnosed CFS
and/or FM, and their associations with 6 health status indicators.
Results: In 2010, diagnosed CFS and FM are reported by 1.4% (95% confidence interval
[CI]: 1.3%–1.6%) and 1.5% (1.4%–1.7%), respectively, of the Canadian household
population aged 12 years and over, with comorbid CFS and FM affecting 0.3% (0.3%–
0.4%) of that population. Prevalent CFS and/or FM were more common among women,
adults aged 40 years and over, those with lowest income, and those with certain risk
factors for chronic disease (i.e. obesity, physical inactivity and smoking). After
controlling for differences between the groups, people with CFS and/or FM reported
poorer health status than those with neither condition on 5 indicators of health status,
but not on the measure of fair/poor mental health. Having both CFS and FM and having
multiple comorbid conditions was associated with poorer health status.
Conclusion: Co-occurrence of CFS and FM and having other chronic conditions were
strongly related to poorer health status and accounted for much of the differences in
health status. Understanding factors contributing to improved quality of life in people
with CFS and/or FM, particularly in those with both conditions and other comorbidities,
may be an important area for future research.
Keywords: myalgic encephalomyelitis, fibromyalgia, health status, health surveys,
cross-sectional studies
Introduction
In 2003, about 1.3% of the adult Canadian
population reported having chronic fatigue
syndrome (CFS) and 1.5% reported having
fibromyalgia (FM).1 CFS, or myalgic encephalomyelitis, is characterized by persistent and profound physical and cognitive
fatigue, whereas FM is characterized by
chronic and widespread musculoskeletal
pain.2 In addition, these 2 conditions often
co-occur.1-4 Co-occurrence of multiple
chronic conditions in the same individual
increases the costs and intensifies the use
of health care resources5,6 and, as demonstrated in the context of other chronic
conditions, can profoundly affect people’s
health-related quality of life.6-10
A few studies in Canada1,2 and elsewhere1113
have considered the impact of CFS and
FM on health status. Lavergne et al.2
showed that Canadian patients with CFS/
FM had poorer health status, measured
using the Short Form-36, compared to the
general Canadian population. In this tertiary care / referral clinic patient population, considered by the authors to be more
impaired than other people of the same sex
and age range with these disorders (e.g.
people with CFS and/or FM selected as part
of population-based surveys), lower functioning was associated with younger age at
onset, lower socio-economic status, and
CFS and FM coexisting.2 Nonetheless,
data from the national population-based
2003 Canadian Community Health Survey
(CCHS) indicate that Canadians with CFS
and FM report poorer general health and
mental health, greater dissatisfaction with
life, higher prevalence of mental illness,
needing more assistance in the activities of
daily living and using health care services
more often.1 These data also showed that
being female, older, of lower income, and of
lower educational attainment are associated with prevalent CFS1 and FM.1,14
However, analyses did not consider
whether these factors were independently
associated with these conditions.
Using more recent data, from the 2010
CCHS, we sought to determine (1) the
factors independently associated with having CFS and FM; (2) the impact of these
conditions on health status; and (3) the
factors associated with poorer health status
among Canadians with these conditions.
Methods
Data source
We analyzed data from the 2010 CCHS–
Annual Component Share File. The CCHS
is a cross-sectional survey conducted by
Author references:
1. Centre for Chronic Disease Prevention, Public Health Agency of Canada, Ottawa, Ontario, Canada
2. National ME/FM Action Network, Nepean, Ontario, Canada
Correspondence: Claudia Lagacé, Centre for Public Health Infrastructure, Public Health Agency of Canada, 120 Colonnade Road, A.L. 6701A, Ottawa, ON K1A 0K9; Tel: 418-842-2685;
Fax: 613-960-3966; Email: [email protected]
Vol 35, No 1, March 2015
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Health Promotion and Chronic Disease Prevention in Canada
Research, Policy and Practice
Statistics Canada that collects information
related to the health of Canadians (i.e.
health status, health behaviours, chronic
conditions, various demographic and
socio-economic health determinants,
etc.). The target population was aged 12
years and older and lived in private
dwellings in the 10 provinces and 3
territories of Canada. The survey did not
include institutional residents, full-time
members of the Canadian Forces, or
people living on Indian Reserves or
Crown lands or in certain remote regions,
which accounted for less than 2% of the
overall Canadian population aged 12 years
and older. Data were collected between
January and December 2010. Further
details on survey methodology, including
strategies to ensure representativeness
of the sample, have been published
elsewhere.15 The overall household-level
response rate to the survey was 80.7%
and person-level response rate was
88.6%, with a final sample size of 59 302
people aged 12 years or older who agreed
to share their data with certain governmental partners.
Analytical strategy
We developed our analytical strategy in 3
interrelated stages: (1) Covariates were
identified a priori based on previous
studies of CFS and FM, either using
CCHS data1,14 or conducted in clinical
settings.2,3 We did not consider some
potential covariates, namely disease severity, duration of illness, and stressful life
events,2 because the CCHS did not measure them. (2) We examined bivariate
relationships between potential covariates
and CFS/FM. (3) We retained covariates
in multivariate models if they were associated with CFS and FM at the bivariate
level. Our analytical strategy was constrained by the available sample size. In
order to produce reliable estimates for
most health indicator variables and covariates, some response categories had to
be combined with others and some variables were dichotomized. The sections
below describe in details how each variable was analyzed.
CFS and FM
As part of the interview, respondents were
asked ‘‘Do you have chronic fatigue
syndrome?’’ and ‘‘Do you have fibromyalgia?’’ The following introduction was read
to respondents at the beginning of the
chronic conditions module: ‘‘Now I’d like
to ask about certain long-term health
conditions which you may have. We are
interested in ‘long-term conditions’ which
are expected to last or have already lasted
6 months or more and that have been
diagnosed by a health professional.’’
Answering ‘‘yes’’ to either question qualified a respondent as a case. No verification was done to confirm the diagnosis or
to determine what case definition was
used by the health professional who made
the diagnosis.
People who either refused or did not state
an answer to the questions about CFS or
FM were excluded (n = 201), leaving
59 101 respondents available for analysis.
Covariates
Prevalence of CFS and FM were described
by sex, age (12–39, 40–59 and 60+ years),
ethnicity (white, Aboriginal, other), highest level of household education (postsecondary graduate, some post-secondary,
secondary graduate, less than secondary
education), marital status (single vs.
widowed/separated/divorced vs. married/common-law) and adjusted income
adequacy quintile. For the latter, respondents were divided into income quintiles
based on the ratio of their total household
income to the low income cut-off corresponding to their household and community size, as derived by Statistics Canada;
this measure provides, for each respondent, a relative measure of their household income to the household incomes of
all other respondents.15
For the education variable, we included a
‘‘not stated’’ category because 8% of
participants did not provide a response
to the question.
For respondents with missing income
information, Statistics Canada uses nearest neighbour donor imputation that
models income based on family structure,
sociodemographics, some health variables and income based on aggregate tax
information; income was imputed for
33% of respondents (18% based on fully
reported income; 4% based on partially
Health Promotion and Chronic Disease Prevention in Canada
Research, Policy and Practice
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4
reported income; and 12% without
income information).15 We also included
a ‘‘not stated’’ category for the remaining
2.4% who had missing values for the
income variable; this proportion represents the residents of the 3 territories,
for whom Statistics Canada does not
calculate an adjusted income adequacy
quintile.
Prevalence of CFS and FM were also
described by body mass index (BMI),
based on self-reported height and weight
(underweight/normal weight < 25 kg/m2,
overweight 25–29 kg/m2; and obese §
30 kg/m2), alcohol consumption (weekly
alcohol consumption, less than weekly and
did not consume any alcohol in the past 12
months), smoking status (never, former,
current), fruit and vegetable consumption
(< 5 vs. § 5 servings/day) and physical
activity (active, moderately active, inactive). The physical activity index is based
on total estimated daily energy expenditure
calculated from self-reported frequency
and duration of leisure-time and transportation-related physical activities for the 3
months prior to the interview.15
We also examined the presence of other
chronic conditions. We defined comorbidity as the total number of other chronic
conditions reported and categorized these
in 2 groups: less than 3 versus 3 or more.
This cut-off was determined based on the
results of our bivariate analysis that
showed that a feature of CFS and FM is
that almost all of respondents with the
conditions had at least 1 or 2 other chronic
conditions. The chronic conditions
included in the 2010 CCHS were asthma,
arthritis, back problems, chronic obstructive pulmonary disease (COPD), bowel
disorders, multiple chemical sensitivities,
migraine, high blood pressure, heart disease, diabetes, cancer, stomach ulcer,
urinary incontinence, mood disorder,
anxiety disorder, Alzheimer or other
dementia, amyotrophic lateral sclerosis,
cerebral palsy, dystonia, epilepsy, hydrocephalus, Huntington disease, muscular
dystrophy, multiple sclerosis, Parkinson
disease, spina bifida, stroke, Tourette
syndrome and neurological conditions
caused by brain and/or spinal cord injury
and/or tumour.
Vol 35, No 1, March 2015
N
Health status indicators
Six self-reported health status indicators
were estimated among Canadians with
both CFS and FM, CFS only, FM only and
neither CFS nor FM: fair/poor general
health, fair/poor mental health, activity
limitations, help needed for tasks, severe
level of impairment and presence of pain.
N Fair/poor general and mental health.
We based general health and mental
health status on the self-report items
‘‘In general, would you say your health
is: excellent, very good, good, fair,
poor?’’ and ‘‘In general, would you
say your mental health is: excellent,
very good, good, fair, poor?’’ We
dichotomized the responses as fair/
poor versus excellent/very good/good
for each respective question.
Activity limitations. We derived a
measure of the limitations in a respondent’s daily activities based on the
responses—often,
sometimes
or
never—to a series of 5 questions:
(1)‘‘Do you have any difficulty hearing,
seeing,
communicating,
walking,
climbing stairs, bending, learning or
doing any similar activities?’’ and
‘‘Does a long-term physical condition
or mental condition or health problem
reduce the amount or the kind of
activity you can do... (2) at home?...
(3) at school?... (4) at work?... (5) in
other activities, for example, transportation or leisure?’’ We categorized
respondents as having activity limitations if they answered often or sometimes to any of the 5 questions.
N
N
Help needed for tasks. We classified
respondents as needing help for tasks if
they reported requiring the help of
another person to perform any 1 of 6
activities of daily living: preparing
meals, getting to appointments/running errands, doing housework, personal care, moving about inside the
house and looking after personal
finances.
Severe level of impairment. We measured health-related quality of life
using the Health Utilities Index (HUI).
The HUI health states are defined by 8
attributes (vision, hearing, speech,
ambulation, dexterity, emotion, cognition, and pain and discomfort), with 5
or 6 levels of functioning for each
attribute. A utility function is used to
FIGURE 1
Prevalence of chronic fatigue syndrome, fibromyalgia and both conditions by age and sex, Canadians 12 years and older, 2010 Canadian Community
Health Survey
3.0
2.8
2.7
2.5
2.3
Percentage (%)
2.0
1.6
1.5
1.5
1.2E
1.1
1.0E
1.0
1.0E
0.8
0.7E
0.7E
0.5
0.5
0.2E
0.2E
0.0
CFS only
FM only
FM only
CFS only
CFS and FM
Female
CFS and FM
Male
12–44 years
45–64 years
65+ years
Abbreviations: CFS, chronic fatigue syndrome; FM, fibromyalgia.
Note: Prevalence estimates for males with FM only aged 12–44 and for males with comorbid FM and CFS aged 12–44 and 65+ are not shown due to high sampling variability.
E
Interpret with caution – coefficient of variation between 16.6% and 33.3%.
Vol 35, No 1, March 2015
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Health Promotion and Chronic Disease Prevention in Canada
Research, Policy and Practice
TABLE 1
Prevalence of chronic fatigue syndrome and fibromyalgia by sociodemographic and health
characteristics, § 12 years, 2010 Canadian Community Health Survey
Characteristics
Chronic Fatigue Syndrome
Fibromyalgia
N
%
Multivariate
PR (95% CI)
N
%
Multivariate
PR (95% CI)
Male
313
1.0
Referent
157
0.7E
Referent
Female
693
1.8
1.7 (1.2–2.2)
956
2.4
3.5 (2.3–5.4)
12–39
160
0.8
Referent
103
0.4E
Referent
40–59
378
1.8
2.1 (1.3–3.4)
472
2.3
4.3 (2.7–6.9)
§ 60
468
2.2
2.0 (1.3–3.2)
538
2.6
3.5 (2.2–5.8)
Sex
Age, years
Ethnicity
White
861
1.5
Referent
996
1.6
Referent
Aboriginal off-reserve
66
2.3E
1.5 (0.9–2.4)
54
1.7E
1.2 (0.7–1.9)
Other
60
1.2E
0.9 (0.5–1.5)
47
1.2E
0.6 (0.3–1.5)
440
1.3
Referent
562
1.5
Referent
Education
Post-secondary graduate
Some post-secondary
E
E
76
1.2
1.4 (0.9–2.2)
73
1.5
1.0 (0.6–1.6)
Secondary school graduate
180
1.7
0.9 (0.6–1.3)
177
1.6
0.8 (0.5–1.1)
Less than secondary school
287
1.8
1.1 (0.8–1.5)
281
1.6
0.8 (0.6–1.1)
57
1.5E
1.4 (0.8–2.5)
48
1.5E
1.2 (0.5–3.2)
94
0.8E
Referent
139
1.0
Referent
Quintile 4
126
0.9
1.1 (0.7–1.8)
172
1.7
1.7 (1.1–2.6)
Quintile 3
148
1.3
1.5 (0.8–2.5)
190
1.4
1.2 (0.7–1.9)
Quintile 2
245
1.6
1.6 (1.0–2.7)
252
1.4
1.1 (0.8–1.7)
Quintile 1 (lowest)
379
2.5
2.3 (1.4–3.9)
347
2.1
1.6 (1.0–2.4)
—
F
—
F
Single
191
1.0
Referent
137
0.6
Referent
Married/common-law
462
1.4
1.1 (0.7–1.8)
402
3.8
1.6 (0.9–2.8)
Widowed/separated/divorced
348
2.7
1.0 (0.6–1.4)
571
1.5
1.2 (0.7–1.8)
Not stated
Income adequacy
Quintile 5 (highest)
Not stated
Marital status
2
Body mass index, kg/m
< 25
375
1.1
Referent
371
1.2
Referent
25–29
281
1.4
1.2 (0.9–1.6)
356
1.6
1.3 (0.9–1.7)
§ 30
254
1.8
1.2 (0.9–1.6)
319
2.3
1.5 (1.1–2.1)
Active
151
0.8
Referent
170
1.0
Referent
Moderately active
170
1.1
1.2 (0.8–1.9)
234
1.1
0.8 (0.6–1.3)
Inactive
624
1.8
1.6 (1.2–2.2)
688
2.0
1.4 (1.0–1.8)
At least weekly
237
0.9
Referent
296
1.2
Referent
Less than weekly
419
1.7
1.5 (1.2–2.0)
435
1.6
1.3 (1.0–1.8)
Not in past 12 months
336
2.0
1.8 (1.3–2.6)
369
2.1
1.8 (1.3–2.5)
Never smoker
272
1.0
Referent
333
1.3
Referent
Former smoker
392
1.4
1.7 (1.2–2.4)
499
1.8
1.2 (0.8–1.8)
Physical activity
Drinks alcohol
Smoking status
Continued on the following page
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$
6
N
obtain an overall score for health states
that range from 20.36 to 1.0 (20.36 =
health status worse than death, 0.0 =
health status equal to death and 1.0 =
perfect health). We grouped HUI scores
into 2 categories reflecting level of
impairment: none to moderate (0.70–
1.00) and severe (< 0.70).
Presence of pain was assessed with the
following question: ‘‘Are you usually
free of pain or discomfort?’’ [Yes vs.
no].
Statistical analysis
We analyzed data using SAS Enterprise
Guide version 5.1 (SAS Institute Inc., Cary,
NC, US). Significance was specified as a p
value of less than 0.05 in all analyses. To
account for sample allocation and survey
design, all estimates were weighted using
survey weights generated by Statistics
Canada, and 95% confidence intervals (CI)
were estimated using bootstrap resampling
method. Associations were quantified using
prevalence ratios (PRs) estimated using
multivariate binomial regression, using an
intercept of 24 to improve convergence.16
Results
Prevalence of CFS and FM
In 2010, about 411 000 (1.4%; 95% CI:
1.3%–1.6%) and 444 000 (1.5%; 95% CI:
1.4%–1.7%) of Canadians aged 12 years
and older reported having been diagnosed
with CFS and FM, respectively. About
0.3% (95% CI: 0.3%–0.4%) of the total
household population reported having
both conditions. Approximately 1 in 4
people with CFS (23.0%) also reported
having FM, and 1 in 5 people with FM
(21.2%) also reported having CFS. Overall,
the prevalence of CFS and/or FM was
higher in women across all age groups
(Figure 1).
Factors associated with prevalent CFS
and FM
After adjusting for covariates, women,
adults aged 40 years and over and those
with the lowest income were more likely
to report having been diagnosed with CFS
or FM (Table 1). In addition, prevalent
Vol 35, No 1, March 2015
chronic conditions had 1.6 to 2.9 times the
likelihood of reporting these indicators of
poor health. Finally, people classified as
physically inactive were 1.2 to 1.8 times
more likely to report fair to poor general
health, severe level of impairment, activity
limitations and needing help with tasks.
Furthermore, some sociodemographic and
lifestyle factors were associated with 1 or 2
indicators of poor health status (Table 4).
TABLE 1 (continued)
Prevalence of chronic fatigue syndrome and fibromyalgia by sociodemographic and health
characteristics, § 12 years, 2010 Canadian Community Health Survey
Characteristics
Current smoker
Chronic Fatigue Syndrome
Fibromyalgia
N
%
Multivariate
PR (95% CI)
N
%
Multivariate
PR (95% CI)
336
2.3
2.7 (1.9–3.8)
276
1.6
1.3 (0.8–1.9)
Fruit and vegetable consumption
< 5 servings/day
549
1.3
Referent
572
1.6
Referent
§ 5 servings/day
336
1.3
1.2 (0.9–1.6)
467
1.4
0.9 (0.7–1.1)
Discussion
Abbreviations: CI, confidence interval; PR, prevalence ratio.
Note: Statistically significant associations (p < 0.05) are bolded.
E
Interpret with caution (coefficient of variation is between 16.6% and 33.3%).
F
Too unreliable to be reported (coefficient of variation >33.3%).
CFS was associated, in multivariate analysis, with physical inactivity, former or
current smoking and less frequent consumption of alcohol. FM was associated
with obesity and less than weekly or no
consumption of alcohol. Comorbidities
were largely present in people with CFS
and/or FM, as 65.2% (95% CI: 59.9–70.6)
reported 3 or more comorbidities.
Impact of CFS and/or FM on health status
Canadians with CFS and/or FM reported
having indicators of poor health status
more commonly than did Canadians with
neither of these conditions (Table 2). After
controlling for differences in the number
of other chronic conditions, sociodemographics and health risk factors, people
with CFS and/or FM were 1.2 to 1.9 times
more likely to report poor health status (5
indicators) compared to those without
these conditions (Table 3). No significant
difference was found for the sixth indicator, self-reported fair/poor mental health.
Factors associated with poor health status
in people with CFS and/or FM
The factors most consistently associated
with indicators of poor health status
among people with CFS or FM were (1)
being diagnosed with both CFS and FM;
(2) being diagnosed with 3 or more other
chronic conditions; and (3) being physically inactive (Table 4), independent of
sociodemographic and health characteristics. Compared to those with either CFS or
FM, people with both conditions were 1.3
to 1.6 times more likely to report fair to
poor general health, a severe level of
impairment (based on health utility index
score), pain, having activity limitations
and requiring assistance in the activities of
daily living. In addition, people with CFS
and/or FM and with 3 or more other
We used data from a nationally representative population-based survey of Canadians
to estimate the prevalence and correlates of
CFS and FM. In 2010, approximately 1.4%
and 1.5% of the Canadian household
population reported having been diagnosed
with CFS and FM, respectively, representing 411 000 and 444 000 Canadians aged
12 years and older.
Consistent with other Canadian and recent
worldwide data,1,14,17 we found that female
sex, being 40 years of age and older and
low income were associated with prevalent
CFS and FM. Whether lower socio-economic status is a determinant or a consequence of CFS/FM remains unclear, given
the cross-sectional nature of the survey.
CFS and FM may affect a person’s ability to
work and, as a result, affect total household
income. In a study of people with CFS
living in the United Kingdom, Collin et al.18
found that 50% discontinued their employment due to symptoms related to CFS. The
authors estimated that CFS cost the UK
economy £75 to £129 million in lost
TABLE 2
Health status outcomes in Canadians 12 years and older with self-reported health-professional-diagnosed chronic fatigue syndrome and/or
fibromyalgia, 2010 Canadian Community Health Survey
Health status outcome
CFS and FM
(n = 270)
CFS only
(n = 736)
FM only
(n = 843)
Neither CFS nor FM
(n = 57 252)
% (95% CI)
% (95% CI)
% (95% CI)
% (95% CI)
Fair/poor general health
77.0 (69.4–84.6)
60.3 (54.0–66.6)
38.7 (32.4–44.9)
10.4 (10.0–10.8)
Fair/poor mental health
40.9 (30.4–51.4)
32.4 (25.5–39.2)
16.5 (10.5–22.5)E
4.7 (4.4–5.0)
Severe level of impairment
81.0 (74.0–87.9)
53.3 (46.6–60.1)
45.2 (38.0–52.5)
11.5 (11.0–11.9)
Presence of pain
94.8 (92.0–97.6)
56.7 (50.1–63.3)
73.6 (67.3–79.9)
16.0 (15.4–16.5)
Activity limitation
92.8 (88.1–97.4)
79.0 (73.1–84.9)
71.0 (63.9–78.2)
27.3 (26.7–28.0)
Help needed for tasks
65.5 (57.2–73.8)
41.7 (35.3–48.1)
31.6 (25.3–37.9)
8.2 (7.9–8.6)
Abbreviations: CFS, chronic fatigue syndrome; CI, confidence interval; FM, fibromyalgia.
E
Interpret with caution (coefficient of variation is between 16.6% and 33.3%).
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Health Promotion and Chronic Disease Prevention in Canada
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TABLE 3
Associations between chronic fatigue syndrome and fibromyalgia and indicators of health status in Canadians 12 years and older, 2010
Canadian Community Health Survey
CFS and/or FM
Fair/poor
general health
Fair/poor
mental health
Severe level
of impairment
Presence
of pain
Activity
limitations
Help needed
for tasks
PR (95% CI)
PR (95% CI)
PR (95% CI)
PR (95% CI)
PR (95% CI)
PR (95% CI)
1.0
1.0
1.0
1.0
1.0
1.0
CFS and FM
7.4 (6.7–8.2)
8.8 (6.7–11.6)
7.0 (6.4–7.8)
5.9 (5.7–6.2)
3.4 (3.2–3.6)
7.9 (6.9–9.2)
CFS only
5.8 (5.2–6.5)
6.9 (5.6–8.6)
4.6 (4.1–5.3)
3.5 (3.1–4.0)
2.9 (2.7–3.1)
5.0 (4.3–5.9)
FM only
3.7 (3.2–4.4)
3.5 (2.5–5.1)
3.9 (3.1–5.3)
4.6 (4.2–5.1)
2.6 (2.3–2.9)
3.8 (3.3–5.9)
Crude
Ref: neither CFS nor FM
a
Partially adjusted
Ref: neither CFS nor FM
1.0
1.0
1.0
1.0
1.0
1.0
1.3 (0.7–2.3)
1.7 (1.0–2.8)
1.0 (0.5–2.1)
1.4 (0.8–2.3)
1.2 (1.0–1.4)
1.2 (0.9–1.6)
1.3 (0.9–1.9)
1.8 (1.5–2.1)
1.2 (1.0–1.5)
1.2 (0.9–1.7)
CFS and FM
1.2 (0.9–1.7)
1.0 (0.3–3.0)
CFS only
1.4 (1.2–1.7)
2.7 (1.9–3.8)
1.3 (0.9–2.0)
FM only
1.2 (1.0–1.4)
1.2 (0.6–2.4)
1.3 (1.0–1.7)
b
Fully adjusted
Ref: neither CFS nor FM
CFS and FM
1.0
1.0
1.4 (1.1–1.7)
1.4 (0.9–2.2)
1.0
1.0
1.0
1.0
1.5 (1.2–1.9)
1.9 (1.2–2.9)
1.1 (0.8–1.4)
1.4 (1.1–1.7)
CFS only
1.4 (1.2–1.6)
1.4 (0.9–2.1)
1.3 (1.1–1.5)
1.2 (1.0–1.3)
1.2 (1.0–1.3)
1.2 (1.0–1.4)
FM only
1.3 (1.1–1.5)
0.8 (0.5–1.4)
1.4 (1.2–1.6)
1.8 (1.6–2.1)
1.2 (1.1–1.4)
1.2 (1.0–1.3)
Abbreviations: CFS, chronic fatigue syndrome; CI, confidence interval; FM, fibromyalgia; PR, prevalence ratio; Ref, referent.
Note: Statistically significant associations (p <.05) are shown in bold.
a
Adjusted for number of comorbid chronic conditions (continuous).
b
Adjusted for sex, age, ethnicity, household education level, income, marital status, body mass index, physical activity, alcohol use, smoking status, fruit and vegetable consumption, and
number of comorbid chronic conditions (continuous).
productivity.18 Similarly, Reynolds et al.19
estimated a 37% decline in household
productivity and a 54% reduction in labour
force productivity as a result of CFS. The
annual total value of lost productivity in
the United States was about $9.1 billion
or $20 000 per person with CFS. Knight
et al.20 estimated that FM costs the US
economy $7333 per patient in lost productivity due to disability and $1228 per
patient in lost productivity due to absenteeism. Thus, inability to work or reduced
work time due to CFS or FM may affect
income, as opposed to lower income being
a determinant of these conditions.
We also showed, consistent with findings
from the 2000–2001 CCHS,14 that lifestyle
risk factors for chronic disease (i.e. obesity, physical inactivity and smoking)
were associated with CFS and/or FM, but
again the direction of the relationship is
unclear given the cross-sectional nature of
the data. In the current analysis, people
who were obese were 1.5 times more
likely to report having FM. Ursini et al.21
hypothesized a number of mechanisms
linking FM and obesity including reduced
physical activity, sleep disturbances,
depression, thyroid dysfunction, and hormonal disturbances involving the deregulation of insulin-like growth factor.
In our analysis, self-reported physical
inactivity was related to reporting a diagnosis of CFS. Using data from the prospective 1958 National Child Development
Study birth cohort in England, Wales, and
Scotland, Goodwin et al.22 showed that
weekly physical activity at age 23 and 33
years was unrelated to the development of
CFS by the age of 42 years. This lack of
correlation is in contrast to the finding from
the 1946 birth cohort in these same
countries that showed more frequent exercise in childhood and early adulthood
predicted CFS by the age of 53 years.23
Although only 2 prospective studies, to our
knowledge, have examined this relationship, these findings suggest that physical
inactivity is more likely a consequence of
CFS than a cause. Physical inactivity may
arise from greater physical impairment,
fatigue and pain in CFS and FM, and was
Health Promotion and Chronic Disease Prevention in Canada
Research, Policy and Practice
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associated with these factors in our
analysis.
Our study found that former and current
smoking was also related to CFS; to our
knowledge no study has prospectively
considered whether smoking is a risk
factor for CFS.
Comorbidity, whether having both CFS
and FM or having other chronic conditions
in addition to CFS or FM, is a central issue
in the population examined in this study.
Other studies have shown that patients
diagnosed with both FM and CFS reported
a worse disease course, worse overall
health, greater dissatisfaction with health
and greater disease impact than those with
CFS or FM alone.2,24 Our results also show
that a person’s level of comorbidity may
substantially affect their health status
outcomes. In addition, 2 out of 3 people
with CFS and/or FM reported at least 3
other chronic conditions. Our analysis
showed that the number of concurrent
health conditions among those with CFS
and/or FM largely accounted for much of
Vol 35, No 1, March 2015
TABLE 4
Multivariate-adjusted associations between characteristics and health status indicators in Canadians 12 years and older with chronic fatigue
syndrome or fibromyalgia (n = 1849), 2010 Canadian Community Health Survey
Characteristics
Fair/poor
general health
Fair/poor
mental health
Severe level
of impairment
Presence
of pain
Activity
limitations
Help needed
for tasks
PR (95% CI)
PR (95% CI)
PR (95% CI)
PR (95% CI)
PR (95% CI)
PR (95% CI)
1.0
1.0
1.0
1.0
1.0
1.0
1.3 (1.1–1.5)
1.4 (0.9–2.0)
1.3 (1.0–1.6)
1.6 (1.1–2.4)
1.3 (1.0–1.7)
1.4 (1.1–1.7)
1.0
1.0
1.0
1.0
1.0
1.0
2.0 (1.4–2.7)
2.7 (1.6–4.5)
2.0 (1.3–3.1)
1.6 (1.1–2.4)
1.6 (1.1–2.2)
2.9 (2.0–4.2)
1.0
1.0
1.0
1.0
1.0
1.0
1.1 (0.9–1.3)
1.3 (0.9–1.8)
1.2 (0.9–1.4)
1.0 (0.8–1.2)
0.9 (0.8–1.1)
0.9 (0.7–1.1)
CFS or FM comorbidity
Ref: either CFS or FM
Both CFS and FM
Number of other chronic conditions
Ref: 0–2
§3
Gender
Ref: female
Male
Age, years
Ref: 12–39
1.0
1.0
1.0
1.0
1.0
1.0
40–59
0.9 (0.6–1.4)
0.8 (0.3–2.1)
1.7 (0.9–3.2)
2.3 (1.2–4.4)
1.3 (0.9–1.8)
1.4 (0.6–3.5)
60+
0.8 (0.5–1.3)
0.5 (0.2–1.3)
1.5 (0.8–2.8)
1.8 (1.0–3.3)
1.2 (0.9–1.8)
1.7 (0.7–4.2)
1.0
1.0
1.0
1.0
1.0
1.0
Aboriginal off-reserve
1.2 (0.9–1.6)
1.6 (0.9–2.6)
1.1 (0.8–1.4)
1.1 (0.8–1.4)
0.8 (0.6–1.1)
1.2 (0.8–1.8)
Other
0.9 (0.6–1.4)
1.4 (0.8–2.5)
0.8 (0.5–1.2)
0.9 (0.6–1.3)
0.7 (0.5–1.1)
1.2 (0.7–1.9)
Ethnicity
Ref: White
Education
Ref: Post-secondary graduate
1.0
1.0
1.0
1.0
1.0
1.0
Some post-secondary
1.2 (1.0–1.6)
1.5 (0.9–2.6)
1.2 (0.9–1.5)
1.0 (0.8–1.2)
1.0 (0.8–1.2)
1.2 (0.9–1.7)
High school graduate
1.2 (1.0–1.6)
0.7 (0.4–1.1)
1.1 (0.9–1.4)
1.0 (0.8–1.2)
1.2 (1.0–1.5)
1.1 (0.8–1.5)
Less than high school
1.3 (1.1–1.6)
1.2 (0.8–1.8)
1.1 (0.9–1.3)
0.9 (0.7–1.0)
1.0 (0.8–1.2)
0.9 (0.7–1.2)
Not stated
1.3 (0.8–2.0)
1.8 (0.6–5.5)
0.8 (0.5–1.5)
0.7 (0.4–1.3)
1.0 (0.6–1.6)
1.1 (0.6–1.5)
Income adequacy
Ref: Quintile 5 (highest)
1.0
1.0
1.0
1.0
1.0
1.0
Quintile 4
1.3 (0.9–1.9)
1.4 (0.7–2.6)
1.1 (0.8–1.7)
1.2 (0.9–1.6)
1.1 (0.8–1.5)
1.0 (0.6–1.5)
Quintile 3
1.4 (1.0–2.1)
1.7 (0.8–3.5)
0.9 (0.6–1.3)
1.1 (0.9–1.5)
1.4 (1.0–1.9)
1.2 (0.7–1.9)
Quintile 2
1.4 (1.0–1.9)
1.9 (1.0–3.6)
1.2 (0.9–1.7)
1.3 (1.0–1.6)
1.4 (1.0–1.6)
1.3 (0.8–2.0)
Quintile 1 (lowest)
1.5 (1.0–2.1)
1.8 (1.0–3.3)
1.3 (0.9–1.8)
1.3 (1.0–1.8)
1.5 (1.1–2.1)
1.5 (1.0–2.3)
Not stated
0.6 (1.0–2.3)
0.5 (0.0–6.6)
0.8 (0.4–1.5)
1.0 (0.5–1.8)
0.9 (0.4–1.8)
0.7 (0.2–1.9)
Marital status
Ref: Single
1.0
1.0
1.0
1.0
1.0
1.0
Married/common-law
1.1 (0.9–1.4)
0.7 (0.5–1.2)
0.8 (0.7–1.0)
1.1 (0.9–1.4)
0.8 (0.7–1.1)
0.7 (0.5–1.0)
Widowed/separated/divorced
1.1 (0.9–1.4)
0.6 (0.4–0.9)
0.9 (0.7–1.0)
1.1 (0.9–1.4)
0.9 (0.7–1.1)
0.9 (0.7–1.2)
1.0
1.0
1.0
1.0
1.0
1.0
2
Body mass index, kg/m
Ref: < 25
25–29
0.9 (0.8–1.1)
1.2 (0.8–1.8)
1.0 (0.8–1.2)
1.0 (0.9–1.3)
1.3 (1.0–1.6)
0.9 (0.7–1.2)
§ 30
1.0 (0.8–1.1)
1.4 (1.0–1.9)
1.2 (1.0–1.4)
1.1 (0.9–1.3)
1.4 (1.1–1.8)
1.1 (0.9–1.4)
Physical activity
Ref: Active
1.0
1.0
1.0
1.0
1.0
1.0
Moderately active
1.2 (0.9–1.7)
0.7 (0.4–1.3)
1.3 (0.8–1.9)
1.2 (0.9–1.6)
1.1 (0.8–1.4)
1.0 (0.6–1.6)
Inactive
1.7 (1.3–2.3)
1.1 (0.7–1.8)
1.4 (1.1–2.0)
1.3 (1.0–1.8)
1.2 (1.0–1.4)
1.5 (1.0–2.2)
Continued on the following page
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Health Promotion and Chronic Disease Prevention in Canada
Research, Policy and Practice
TABLE 4 (continued)
Multivariate-adjusted associations between characteristics and health status indicators in Canadians 12 years and older with chronic fatigue
syndrome or fibromyalgia (n = 1849), 2010 Canadian Community Health Survey
Characteristics
Fair/poor
general health
Fair/poor
mental health
Severe level
of impairment
Presence
of pain
Activity
limitations
Help needed
for tasks
PR (95% CI)
PR (95% CI)
PR (95% CI)
PR (95% CI)
PR (95% CI)
PR (95% CI)
1.0
1.0
1.0
1.0
1.0
1.0
Drinks alcohol
Ref: At least weekly
Less than weekly
1.5 (1.1–1.9)
1.7 (1.1–2.5)
1.1 (0.9–1.3)
1.1 (0.9–1.3)
1.2 (1.0–1.4)
1.2 (0.9–1.6)
Not in past 12 months
1.4 (1.1–1.8)
1.7 (1.2–2.6)
1.1 (0.9–1.4)
1.2 (1.0–1.4)
1.0 (0.9–1.2)
1.4 (1.0–1.9)
Smoking
Ref: Never smoker
1.0
1.0
1.0
1.0
1.0
1.0
Former smoker
1.3 (1.0–1.6)
1.4 (0.9–2.0)
0.9 (0.7–1.1)
0.8 (0.7–1.0)
0.9 (0.8–1.1)
1.2 (0.9–1.6)
Current smoker
1.4 (1.1–1.8)
1.6 (1.1–2.5)
1.1 (0.9–1.4)
0.9 (0.7–1.1)
1.2 (1.0–1.6)
1.4 (1.1–1.9)
1.0
1.0
1.0
1.0
1.0
1.0
1.1 (0.9–1.2)
0.8 (0.5–1.2)
1.0 (0.8–1.1)
1.1 (1.0–1.3)
1.0 (0.9–1.2)
1.4 (1.1–1.7)
Fruit and vegetable consumption, servings per day
Ref: <5 servings
§5
Abbreviations: CFS, chronic fatigue syndrome; FM, fibromyalgia; Ref, referent; PR, prevalence ratio.
Note: Statistically significant associations (p < 0.05) are bolded.
the differences in health status when
compared to those with neither condition.
Thus, our findings point to the importance
of considering the cumulative effects of
coexisting chronic conditions and CFS/FM
when examining health outcomes in people with either or both conditions.
Strengths and limitations
Our study is strengthened by our use of a
large, population-based survey of the
Canadian population living in the community, with a good response rate. The CCHS
provides comprehensive data on descriptive
variables, enabling in-depth analysis of the
health status of people living with CFS and
FM as well as allowing comparisons with
different subgroups. The CCHS relies on
self-reporting of chronic conditions and
health events. While it is the most practical
method of assessing disease status in large
population studies, self-reporting of diagnosis is susceptible to misclassification, resulting in potential under- or over-estimation of
disease prevalence and societal burden. In
our study, CCHS respondents self-reported
their disease history (including the diagnosis of CFS and/or FM), and there was no
third-party corroboration or verification of
these self-reports. Research has found
acceptable to good agreement between
self-reported physical health conditions
and diagnoses made by medical professionals,25 but validation of self-reported CFS
and FM in particular has not, to our knowledge, been specifically undertaken. Studies
of diagnostic practices, focussing on the
case definition used by health professionals
in diagnosing CFS/FM, are scarce and have
yet to be done in Canada.
As previously acknowledged, the crosssectional design of the survey does not
allow the examination of possible causal
pathways or mechanisms, so it is unclear
whether the associations we found with
lifestyle risk behaviours could be viewed as
(a) risk factors for developing the conditions or (b) a result of the condition.
Etiological studies (such as case-control or
cohort studies) are required to determine
whether, in the context of CFS and FM,
these represent potential preventable risk
factors or not. Finally, while we have
included in our analytical strategy the
important covariates identified in the CFS
and FM literature, our analysis was
restricted to the set of variables collected
by the CCHS. This may have precluded the
inclusion of other important covariates that
may have been confounders of the associations we examined in this study, such as
disease severity or duration of illness.
Conclusion
We found that, in 2010, CFS and FM were
reported by approximately 1.4% and 1.5%,
respectively, of the Canadian household
Health Promotion and Chronic Disease Prevention in Canada
Research, Policy and Practice
$
10
population 12 years of age and older. We
observed that prevalent CFS and FM were
related to female sex, adults 40 years and
older and lifestyle risk factors for chronic
diseases, although the reasons behind
these associations are unclear. These findings may warrant further research to
examine whether these lifestyle risk factors
are part of the causal pathway or are the
effects of the conditions. Co-occurrence of
CFS and FM and having other diagnosed
chronic conditions were strongly related to
poorer health status and accounted for
much of the differences in health status.
Comorbidity as a driving force behind
poorer health status cannot be ignored.
Given the relative paucity of data on CFS and
FM, these results from a community-based
survey are relevant to the field of public
health. They reinforce prior findings that
these conditions frequently co-occur with a
range of other diseases. Because CFS or
FM without comorbidities is actually rare,
researchers and clinicians can anticipate
substantial complexity in their studies and
clinical care. In particular, research that does
not exclude patients with comorbidities
would be most relevant to health professionals and public health practitioners.
Finally, understanding the factors that contribute to improved quality of life in people
with CFS and/or FM, particularly in those
with both conditions and other comorbidities,
may be an important area for future research.
Vol 35, No 1, March 2015
Acknowledgements
The Canadian Community Health Survey
was conducted by Statistics Canada in
partnership with Health Canada and the
Public Health Agency of Canada with
funding from the Canadian federal government.
References
1.
2.
3.
4.
Park J, Knudson S. Medically unexplained
physical symptoms. Health Rep. 2007;18:437.
Lavergne MR, Cole DC, Kerr K, Marshall LM.
Functional impairment in chronic fatigue
syndrome, fibromyalgia, and multiple chemical sensitivity. Can Fam Physician.
2010;56:e57-65.
Jason LA, Taylor RR, Kennedy CL. Chronic
fatigue syndrome, fibromyalgia, and multiple chemical sensitivities in a communitybased sample of persons with chronic fatigue
syndrome-like symptoms. Psychosom Med.
2000; 62:655-63.
Goldenberg DL, Simms RW, Geiger A,
Komaroff AL. High frequency of fibromyalgia in patients with chronic fatigue seen in
a primary care practice. Arthritis Rheum
1990;33:381-7.
5.
Westert GP, Satariano WA, Schellevis FG,
van der Bos GA. Patterns of comorbidity and
the use of health services in the Dutch
population. Eur J Public Health 2001;11:36572.
6.
Struijs JN, Baan CA, Schellevis FG, Westert
GP, van der Bos GA. Comorbidity in
patients with diabetes mellitus: impact on
medical health care utilization. BMC Health
Serv Res. 2006;6:84.
7.
8.
Picavet HS, Hoeymans N. Health related
quality of life in multiple musculoskeletal
diseases: SF-36 and EQ-5D in the DMC3
study. Ann Rheum Dis. 2004;63:723-9.
Bollegala D, Perruccio AV, Badley EM.
Combined impact of concomitant arthritis
and back problems on health status: results
from a nationally representative health
survey. Arthritis Care Res (Hoboken).
2011;63:1584-91.
Vol 35, No 1, March 2015
9.
El-Gabalawy R, Mackenzie CS, Shooshtari
S, et al. Comorbid physical health conditions and anxiety disorders: a populationbased exploration of prevalence and health
outcomes among older adults. Gen Hosp
Psychiatry. 2011;33:556-4.
10. Moussavi S, Chatterji S, Verdes E, Tandon
A, Patel V, Ustun B. Depression, chronic
diseases, and decrements in health: results
from the World Health Surveys. Lancet.
2007;370:851-8.
11. Creed FH, Tomenson B, Chew-Graham C,
et al. Multiple somatic symptoms predict
impaired health status in functional somatic
syndromes. Int J Behav Med. 2013;20:194205.
12. Bombardier CH, Buchwald D. Chronic fatigue, chronic fatigue syndrome, and fibromyalgia. Disability and health-care use. Med
Care. 1996;34:924-30.
13. Scheeres K, Wensing M, Severens H, Adang
E, Bleijenberg G. Determinants of health care
use in chronic fatigue syndrome patients: a
cross-sectional study. J Psychosom Res.
2008;65:39-46.
14. McNally JD, Matheson DA, Bakowsky VS.
The epidemiology of self-reported fibromyalgia in Canada. Chronic Dis Can 2006;
27:9-16.
15. Statistics Canada. Canadian Community
Heatlh Survey (CCHS) Annual Component.
2010 and 2009-2010 Microdata File User
Guide. 2011 [cited 2013 Jan 31]. Available
from: http://www23.statcan.gc.ca/imdb
-bmdi/pub/document/3226_D7_T9_V8-eng
.htm
19. Reynolds KJ, Vernon SD, Bouchery E,
Reeves WC. The economic impact of
chronic fatigue syndrome. Cost Eff Resour
Alloc. 2004;21:4.
20. Knight T, Schaefer C, Chandran A, Zlateva
G, Winkelmann A, Perrot S. Healthresource use and costs associated with
fibromyalgia in France, Germany, and the
United States. Clinicoecon Outcomes Res.
2013;5:171-80.
21. Ursini F, Naty S, Grembiale RD. Fibromyalgia
and obesity: the hidden link. Rheumatol Int.
2011;31:1403-8.
22. Goodwin L, White PD, Hotopf M, Standsfield
CA, Clark C. Psychopathology and physical
activity as predictors of chronic fatigue
syndrome in the 1958 British birth cohort: a
replication study of the 1946 and 1970 birth
cohorts. Ann Epidemiol. 2011;21:343-50.
23. Harvey SB, Wadsworth M, Wessely S,
Hotopf M. Etiology of chronic fatigue syndrome: testing popular hypotheses using a
national birth cohort study. Psychosom
Med. 2008;70:488-95.
24. Dobkin PL, De Civita M, Bernatsky S, Kang
H, Baron M. Does psychological vulnerability
determine health-care utilization in fibromyalgia? Rheumatology (Oxford). 2003;42:
1324-31.
25. Kriegsman DM, Penninx BW, van Eijk JT,
Boeke AJ, Deeg DJ. Self-reports and general
practitioner information on the presence of
chronic diseases in community dwelling
elderly. A study on the accuracy of patients’
self-reports and on determinants of inaccuracy. J Clin Epidemiol. 1996;49:1407-17.
16. Deddens JA, Petersen MR, Lei X. Estimation
of prevalence ratios when PROC GENMOD
does not converge. SAS User Group
International (SUGI) Proceedings, Seattle,
Washington, March 30-April 2, 2003. Paper
#270-28.
17. Queiroz LP. Worldwide epidemiology of
fibromyalgia. Curr Pain Headache Rep.
2013;17:356.
18. Collin SM, Crawley E, May MT, et al. The
impact of CFS/ME on employment and
productivity in the UK: a cross-sectional
study based on the CFS/ME national outcomes database. BMC Health Serv Res.
2011;11:217.
$
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Health Promotion and Chronic Disease Prevention in Canada
Research, Policy and Practice
A DASH dietary pattern and the risk of colorectal cancer in
Canadian adults
E. Jones-McLean, MSc (1); J. Hu, MD (1); L. S. Greene-Finestone, PhD (1, 2); M. de Groh, PhD (1)
This article has been peer reviewed.
Tweet this article
Abstract
Introduction: Colorectal cancer (CRC) is a high incidence cancer affecting many
Canadian adults each year. Diet is important in the etiology of CRC with many dietary
components identified as potential risk factors. The Dietary Approaches to Stop
Hypertension (DASH) diet is a well-established pattern to characterize overall eating.
The purpose of this study was to characterize a DASH pattern within the Canadian
context and to assess its relationship to the risk of CRC in Canadian adults.
Methods: Unconditional multiple logistic regression with control for confounding
variables was performed using data from the National Enhanced Cancer Surveillance
Study. Dietary intake was captured for this case-control study through a food frequency
questionnaire (FFQ) and categorized into a DASH score ranging from 0 to 10 representing
a poor to a strong DASH pattern respectively.
Results: Consuming a strong DASH pattern of eating (score § 8) was not common in the
3161 cases and 3097 controls. Overall, only 10.8 % of men and 13.6 % of women had a
strong DASH pattern. Multivariate analysis demonstrated a trend for decreasing risk of
CRC in men with increasing DASH scores (p value for trend = .007). Men with a strong
DASH score had a 33% reduction in risk of CRC compared to those with a low DASH
score. There were no significant trends for women for CRC or for colon or rectal cancers
separately.
Conclusion: Our findings are similar to other researchers suggesting a benefit with a
strong DASH pattern associated with a decreased risk of CRC, especially in men.
Research should further investigate our gender-based differences.
Keywords: diet, colorectal neoplasms, primary prevention
Introduction
Colorectal cancer (CRC) is the second
leading cause of cancer deaths in Canada,
with 5000 males and 4200 females forecast
to die from the disease in 2013.1 Risk
factors for CRC include family history,
certain genetic syndromes (e.g. familial
adenomatous polyposis), medical conditions (e.g. inflammatory diseases), medications, as well as lifestyle behaviours
associated with excess body weight (e.g.
low physical activity level) and diet.2
Modifiable dietary factors are believed to
be crucial in the etiology of CRC.3
The relationships between diet and complex chronic diseases such as CRC can be
examined by investigating dietary patterns. Chronic diseases are likely mediated
by the culmination of multiple dietary
components interacting synergistically or
antagonistically over time. Examining dietary patterns by capturing combinations of
specific foods or dietary components and
expressing these as a summary exposure
measure may accurately and comprehensively describe dietary exposure. Common
dietary patterns include the Western, the
Prudent and the Mediterranean dietary
patterns, but the list continues to grow.4
One established dietary pattern is the Dietary
Approaches to Stop Hypertension (DASH)
diet, which is rich in fruit, vegetables, whole
grains, low-fat dairy products and legumes/
seeds but low in saturated fat, sodium and
added sugars.5 Initially designed and evaluated for reducing blood pressure,6 the
DASH diet has now been studied in relation
to outcomes such as cardiovascular disease,
kidney function, metabolic syndrome and
gestational diabetes.7-9
Few studies have looked at the DASH diet
in relation to risk of CRC despite that many
of the foods or nutrients the DASH diet
recommends are associated with a lessened
risk of CRC.10 Studies by Dixon et al.11 and
Fung et al.,12 as well as one on eating
frequency using the DASH diet13 used
different methodologies to characterize a
DASH pattern. Recognizing possible differences across countries with respect to food
choices, we set out to establish a DASH
pattern within the Canadian context and to
determine if adherence to this pattern is
associated with a decreased risk of CRC.
We hypothesized that with increasing
DASH pattern scores, the risk of CRC in
Canadian adults would decrease.
Despite the availability of other dietary
patterns or indices, we chose to focus on
the DASH pattern because many Canadians
may already be following this diet to prevent
Author references:
1. Social Determinants and Science Integration Directorate, Health Promotion and Chronic Disease Prevention Branch, Public Health Agency of Canada, Ottawa, Ontario, Canada
2. Division of Physical Medicine and Rehabilitation, Faculty of Medicine, University of Ottawa, Ottawa, Ontario, Canada
Correspondence: Elaine Jones-McLean, Social Determinants and Science Integration Directorate, HPCDPB, Public Health Agency of Canada, 785 Carling Avenue, AL 6809A, # 926A2, Ottawa,
ON K1A 0K9; Tel: 613-960-6974; Fax: 613-960-0921; Email: [email protected]
Health Promotion and Chronic Disease Prevention in Canada
Research, Policy and Practice
$
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Vol 35, No 1, March 2015
or treat hypertension. In Canada, the
prevalence of hypertension is high; in
2010, 17.1% of all Canadians aged 12 years
or older were diagnosed with high blood
pressure, with those aged 65 years or older
having a significantly higher prevalence (i.e.
40%).14
Methods
Between 1994 and 1997, the National
Enhanced Cancer Surveillance Study
(NECSS) collected data from a populationbased sample that included people with 19
types of cancer. Cases as well as controls
lived in the Canadian provinces of British
Columbia, Alberta, Saskatchewan, Manitoba, Prince Edward Island, Nova Scotia
and Newfoundland and Labrador. Ontario
provided controls but no cases and, as a
result, was excluded from our current
analyses.
Details of the NECSS and diet-based analyses are available elsewhere.15-17
Cases
Participating provincial cancer registries
ascertained 5112 (2227 women and
2885 men) histologically confirmed incident cases of CRC aged 20 to 76 years. Of
these, 325 people (6.4 %; 111 women and
214 men) had died by the time of physician
contact, and 341 (6.7%; 177 women and
164 men) were not contacted because the
attending physician refused consent (generally because the patient was too ill). Of
4446 questionnaires sent by provincial
cancer registries, 3174 were completed, a
response rate of 62.1% of cases ascertained
or 71.4% of patients contacted. Cases were
confirmed using definitions from the current International Classification of Diseases
for Oncology (ICD-O-2)18 and resulted in 1
male and 2 female cases being excluded
due to missing ICD-O codes. Our study
analysed the resulting sample of 1816 male
and 1355 female cases.
Controls
We selected people without cancer from a
random sample within each participating
province, with an age/sex distribution
similar to that of all cancer cases in the
NECSS. The selection of controls made sure
Vol 35, No 1, March 2015
that at least one sex-specific control was
chosen for each case within a 5-year age
group and for each type of cancer. The
sampling strategy for population-based controls was determined for each province
based on research experience with specific
databases, access to data and data quality as
well as database confidentiality conditions.
As such, the sampling strategy for selecting
controls varied by province. Data from
provincial health insurance plans were
used in British Columbia, Saskatchewan,
Manitoba, Prince Edward Island and Nova
Scotia. The Ontario Ministry of Finance
Property Assessment Database provided
Ontario’s controls. Random digit dialling
provided controls for Alberta and Newfoundland and Labrador. Controls were also
collected over the whole calendar year to
ensure an even distribution of responses
that may be influenced by seasonality (e.g.
on questions of diet and physical activity). A
nominal financial incentive was tried in
Ontario to improve response rates.
Of 5119 questionnaires sent to potential
controls, 81 were returned because they
were incorrectly addressed; of the remainder, 3097 (1635 men and 1462 women)
were completed, yielding a response rate
of 61.5% of controls contacted.19-20
Data collection
The provincial cancer registries identified
most cases within 1 to 3 months of diagnosis
through pathology reports. After obtaining
physician consent, the registries mailed
questionnaires to potential participants
(cases and controls). If a completed questionnaire was not returned, a reminder
postcard was sent out after 14 days, and a
second copy of the questionnaire at 4
weeks. After 6 weeks, recipients who had
not yet completed the questionnaire were
reminded to do so by telephone. Information was collected from controls using the
same protocol as for cases.
Information was collected on socio-economic status, self-reported height and
weight, smoking history, alcohol consumption, physical activity, menstrual and
reproductive history and diet.
For self-reported weight, participants were
asked to recall their weight 2 years before
$
13
the study to calculate body mass index
(BMI, in kg/m2).21
We defined ‘‘ever smokers’’ as those who
had smoked at least 100 cigarettes in their
entire life and ‘‘current smokers’’ as those
who were still smoking during the year
before the interview.
Information on recreational physical activity was obtained by asking about the time
spent doing both moderate and strenuous
activities 2 years prior to the study.
We derived dietary information from a
semi-quantitative food frequency questionnaire (FFQ) based on 2 validated instruments: the short Block questionnaire22 and
the Willett questionnaire.23 The FFQ was
used to determine usual dietary intake 2
years before participants’ enrollment in the
study. The FFQ included 69 specific foods/
beverages that were categorized into 8 food
groups: (a) breads and cereals; (b) meat,
poultry, fish, eggs and cheese; (c) vegetables; (d) fruit; (e) sweets; (f) miscellaneous
foods such as peanut butter and nuts; (g)
beverages made with water such as coffee,
tea and juices/drinks; (h) other beverages
such as soft drinks, milk and alcohol. For
each food item, participants were asked to
describe how often (per day, per week, per
month) they consumed, on average, the
specified serving size. We used a nutrient
database based on the Canadian Nutrient
File to estimate nutrient and total energy
intake according to the nutrient profile of
foods at that time.24
We derived a 10-point score to describe
participants’ DASH pattern intake (see
Table 1), rather than use a 9-point scoring
system as reported in some studies.11,25 We
based our scoring system on the foods or
food groups in the DASH Eating Plan from
the Dietary Guidelines for Americans26 and
from a related publication11 to capture
intake of whole grains, vegetables, fruit,
low-fat dairy, red and processed meats,
sweets, alcohol, saturated fat, and nuts,
legumes and seeds. We modified our scale
by including a tenth item, sodium intake,
as other researchers have done.12
We controlled for total energy intake by
establishing quartiles based on the energy
distribution in controls. For each of the
Health Promotion and Chronic Disease Prevention in Canada
Research, Policy and Practice
TABLE 1
DASH-Pattern scoring scheme
Dietary component
Examples of FFQ items (or nutrient calculation)
POSITIVE
Excluding
1 point for intakes § median; 0 points for intakes < median
Whole grains
Bran, granola cereals, shredded wheat, cooked cereals, dark and whole
grain bread
White bread, rice, macaroni
Vegetables
Tomatoes, carrots, broccoli, cabbage, cauliflower, Brussels
sprouts, spinach or other greens, winter squash, sweet potatoes,
any other vegetable including green beans, corn, peas
French fries, soups with vegetables or tomato, vegetable juice
Fruit
Apples, pears, oranges, bananas, cantaloupe, other fruit, fresh or
canned, orange or grapefruit juice
Items with added sugar such as drinks from frozen
concentrate, crystals
Low-fat dairy products
2% milk, 1% milk, skim milk
Whole milk, regular cheese, ice cream
Nuts/seeds/legumes
Nuts, tofu, soybeans, baked beans or lentils
High fat peanut butter
NEGATIVE
1 point for intakes ƒ median; 0 points for intakes > median
Meat (red, processed)
Beef, pork, lamb as a main or mixed dish, hamburger, sausage,
hotdog, smoked or corned beef, luncheon meats, liver
SFAs
Total dietary SFA intake from all foods in the FFQ, as defined by:
% = Saturated Fat (g) x 9 (kcal) / Total energy of the diet (kcal)
Sodium
Total dietary sodium intake from all foods of FFQ
Alcohol
Beer, wine, liquor
Sweets
Cake, cookies, doughnuts, pastry, pies, ice cream, chocolate,
soft drinks, drinks from powdered drink crystals, etc.
Fish, poultry, eggs
Abbreviations: DASH, Dietary Approaches to Stop Hypertension; FFQ, Food Frequency Questionnaire; SFA, saturated fat.
quartiles, we calculated specific median
intakes for all 10 dietary components
using the intake of controls, stratified by
sex. Our energy quartiles were 1458 kcal/
day or less, 1459 to 1843 kcal/day, 1844 to
2284 kcal/day and 2285 kcal/day or
more. Study participants received a point
for intakes at or above the energy sexspecific median for the following ‘‘positive’’ dietary components: whole grains,
vegetables, fruit, low-fat dairy and
legumes/nuts/seeds. Intakes below the
median for these components were scored
a zero. Alternatively, a point was given to
each intake at or below the median for
‘‘negative’’ dietary components: red and
processed meat; saturated fat; alcohol; and
sweets. For these, a zero was assigned to
intakes above the median.
We assigned foods from the FFQ into the
appropriate food groups and calculated
the number of servings of each food based
on existing DASH pattern methodology.5,11,26 When information was lacking,
we supplemented this approach by examining common nutrients across foods
within a food group to ensure nutrient
equivalency. This was especially important for groups that contained heterogeneous food items such as the sweets
group. Because the Canadian Nutrient
File24 is limited in reporting the sugar
content of foods, we assessed foods in the
sweets group according to calories. As
such, one cookie was equivalent to 1
serving (54 kcal) and one glass of soft
drink to 2 servings (98 kcal). For saturated
fat and sodium intakes, we did not rely on
consumption of specific FFQ items as with
the other food groups; rather, we scored
people based on their total intakes of these
nutrients across all foods captured in
relation to the median total intakes across
the energy quartiles.
The DASH score could range from 0 to 10.
In this study, DASH scores represent a
DASH-like pattern as they are based on
estimates over or under the sex- and
energy-specific medians. As such, a DASH
score of 8 or higher is a strong DASH
pattern of eating while a score of 2 or less is
a poor DASH pattern.
Statistical analysis
We used unconditional logistic regression,
stratified by sex, to estimate odds ratios
(OR) and the corresponding 95% confidence intervals (CI), including terms for age
groups (20–49, 50–59, 60–69, § 70 years),
Health Promotion and Chronic Disease Prevention in Canada
Research, Policy and Practice
$
14
province, education (ƒ 8, 9–13, § 14
years), BMI (< 25.0, 25.0–29.9, § 30.0 kg/
m2), pack-years of smoking, income, moderate and strenuous leisure-time physical
activity, calcium supplementation and age
at first pregnancy. Confounding variables,
except for age group, province, BMI and
sex, were treated as continuous variables in
the models. Tests for trend were assessed
for each study variable by substituting the
variable in the model in continuous form.
All analyses were carried out using statistical package SAS version 9.01 (SAS
Institute Inc., Cary, NC, US).27
Results
Study participants included 3171 cases
and 3097 controls, with 23% more men
(n = 3451) than women (n = 2817). The
majority of participants had a high school
education or higher, had middle- to highlevel family incomes and were ever and
current smokers. Cases tended to be older
and have a higher BMI, and women with
CRC tended have been over the age of 20
years when they had a child. Of those
reporting family income, there was no
statistical difference between cases and
controls (Table 2).
Vol 35, No 1, March 2015
TABLE 2
Distribution of colorectal cancer cases (n = 3171) and population-based controls (n = 3097)
based on selected covariates, NECSS, Canada, 1994–1997
Cases
Controls
p value for Chi-Square
n
%
n
%
Men
1816
57.2
1635
52.8
Women
1355
42.8
1462
47.2
378
11.9
838
27.1
50–59
645
20.4
605
19.5
60–69
1342
42.3
1043
33.7
§ 70
806
25.4
611
19.7
Sex
Age, years
20–49
Education, years
ƒ8
577
18.2
471
15.2
9–13
1818
57.3
1689
54.5
§ 14
711
22.4
900
29.1
65
2.1
37
1.2
Family incomea
Low
584
18.4
584
18.9
Lower-middle
570
18.0
585
18.9
Upper-middle
758
23.9
779
25.2
Missing values
High
474
14.9
440
14.2
Missing values
785
24.8
709
22.9
Pack-year smoking
Never smokers
995
31.4
1123
36.5
ƒ 10
626
19.7
705
23.0
11–20
525
16.6
470
15.3
21–30
377
11.9
302
9.8
> 30
592
18.7
447
14.5
56
1.8
50
1.6
Missing values
BMI, kg/m2
< 25.0
1175
37.1
1461
47.2
25.0–29.9
1345
42.4
1176
38.0
637
20.1
447
14.4
14
0.2
13
0.4
Moderate physical activity, hour/month
ƒ 4.22
598
18.9
638
20.6
4.23–11.57
645
20.3
702
22.7
11.58–24.44
720
22.7
725
23.4
§ 24.45
730
23.0
636
20.5
Missing values
478
15.1
396
§ 30.0
Missing values
< .0001
Our analyses showed a significant trend
towards decreased risk of CRC with
increasing DASH scores (p value for
trend = .007) in men. After adjusting for
confounders, men who scored § 8 on the
DASH scale had a 33% reduced risk of CRC
compared to men with lower DASH scores.
Men showed a decreasing trend for risk of
rectal cancer (p = .003), but not colon
cancer (p = .09), with increasing DASH
scores, although a similar pattern was
evident. For women, trends with increasing
DASH scores for either colon or rectal
cancers or both cancers combined were
not significant.
< .0001
0.32
< .0001
We stratified analyses according to BMI
(Table 5) and found no interaction between
DASH scores and risk of CRC. The trend for
rectal cancer (p = .01) was significant and
the trend for CRC (p = .05) was borderline
significant in men who were not overweight/obese (BMI < 25.0 kg/m2). Men
had a 50% and 36% risk reduction for
rectal cancer and CRC respectively with a
strong DASH pattern. In men who were
overweight/obese (BMI § 25.0 kg/m2),
CRC was reduced by 35% in those with a
strong DASH pattern though this was
borderline significant (p = .05). Although
not statistically significant (p = .07), there
seemed to be a decreasing risk of rectal
cancer in overweight/obese men with
increasing DASH scores.
< .0001
< .0019
12.8
Continued on the following page
Median intakes of foods or nutrients tended
to increase with increasing energy intake.
The exception was alcohol, which appeared
relatively stable for women across the
Vol 35, No 1, March 2015
energy quartiles (Table 3). Saturated fat
intake was similar for men and women at
between 1.5% and 1.7% of total energy
intake, across all energy quartiles.
$
15
Consuming foods largely to a DASH pattern
(i.e. a score of § 8) was not common in
study participants (Table 4). Overall, only
10.8 % of all men (374/3451) and 13.6 %
of all women (382/2817) scored 8 or higher
(Table 4). Similarly, only a small percentage of participants had a low DASH score
(ƒ 2) representing a poor DASH pattern of
eating; 10.1% of men (349/3451) and
10.2% of women (286/2817) scored 2 or
less. Approximately 50% of study participants had DASH scores in the mid-range of
4 to 6.
Trends for increasing DASH scores and
risk of any cancers for women in either
weight status group were not statistically
significant.
We also assessed parity in women, for
potential confounding, but found no sta-
Health Promotion and Chronic Disease Prevention in Canada
Research, Policy and Practice
tistical difference between cases and controls (data not shown).
TABLE 2 (continued)
Distribution of colorectal cancer cases (n = 3171) and population-based controls (n = 3097)
based on selected covariates, NECSS, Canada, 1994–1997
Cases
Controls
n
%
n
Strenuous physical activity, hour/month
Never
1324
41.8
1146
Discussion
p value for Chi-Square
%
37.0
ƒ 0.19
174
5.5
162
5.2
0.20–3.68
565
17.8
644
20.8
§ 3.69
597
18.8
647
20.9
Missing values
511
16.1
498
16.1
Calcium supplementation
Never
1944
61.3
1849
59.7
Not regularly
603
19.0
649
20.9
Regularly
369
11.6
430
13.9
Missing values
255
8.0
169
5.5
Age at first pregnancy, years
ƒ 20
270
19.9
358
24.5
21–23
343
25.3
343
23.5
24–26
238
17.6
239
16.4
> 26
302
22.3
283
19.4
Missing values
202
14.9
239
16.4
This is the first published Canadian study
to investigate the DASH pattern in relation
to risk of CRC.
< .0006
Our results parallel other studies that
showed an inverse relationship between
a strong DASH pattern and risk of CRC
with some variability across sex.11-13,28
Fung et al.12 reported a protective association for proximal colon cancer in women,
but not men, who followed a DASH or
Mediterranean type of diet. In our study,
adherence to a DASH dietary pattern was
protective for men but not for women. Our
findings agree with those of Dixon et al.11
who demonstrated a significant trend for
increased DASH scores with lower risk of
distal CRC adenomas in men regardless of
other factors such as body weight or
smoking status. Other studies have also
shown inverse relationships between
strong DASH patterns or other healthy
diet indices in men, but not women,13,29
with some researchers explaining these
differences as being due to the differences
in the etiology of CRC between men and
women.29
< .0001
< .01
Abbreviations: BMI, body mass index; NECSS, National Enhanced Cancer Surveillance Study.
a
Family income was indicated as a categorical variable with the following values: low:< $20 000 with ƒ 3 people or $30 000
with § 4 people; lower-middle: $20 000–$30 000 with ƒ 3 people or $30 000–$50 000 with § 4 people; upper-middle:
< $50 000 with ƒ 3 people or $50 000–$100 000 with § 4 people; high: § 50 000 for ƒ 3 people or § 100 000 for § 4
people.
Some researchers strongly suggest that men
and women respond differently to dietary
TABLE 3
Median intakes of foods or nutrients by sex and energy levels, NECSS, Canada, 1994–1997
Food Componentsa
(servings/day)
Energy Level (Kcal/day)
ƒ 1458
Men
1459–1843
Women
Men
1844–2284
Women
Men
§ 2285
Women
Men
Women
Whole grains
0.71
0.79
1.29
1.64
1.99
2.14
2.13
2.43
Vegetables
0.86
1.20
1.28
1.71
1.42
1.85
1.78
2.21
Fruit
0.23
1.23
1.42
1.88
1.67
2.12
2.15
2.76
Low-fat dairy products
0.14
0.17
0.79
0.79
1.00
1.00
1.00
1.00
Nuts/seeds/legumes
0.07
0.07
0.10
0.07
0.10
0.10
0.11
0.14
Meat
0.79
0.70
1.11
1.05
1.43
1.24
1.93
1.71
Sweets
1.35
1.10
2.26
2.18
3.14
2.66
4.57
4.60
1408.54
1451.54
2043.39
2025.40
2458.56
2491.16
3388.26
3198.28
Sodium (mg/day)
Saturated fats (% of total
energy)
0.016
0.015
0.016
0.015
0.017
0.016
0.016
0.016
Alcohol
0.13
0.00
0.35
0.07
0.50
0.07
0.56
0.07
Abbreviations: CI, confidence interval; DASH, Dietary Approaches to Stop Hypertension; OR, odds ratio; NECSS, National Enhanced Cancer Surveillance Study.
a
The food components are the same as in Table 1.
Health Promotion and Chronic Disease Prevention in Canada
Research, Policy and Practice
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16
Vol 35, No 1, March 2015
TABLE 4
Odds ratiosa and 95% confidence intervals of colorectal cancer according to median score by sex, NECSS, Canada, 1994–1997
Cancer site
DASH score
ƒ2
3
4
5
6
7
§8
p value
for trend
Colon
Men
Cases
93
124
169
174
177
130
89
Controls
181
226
272
279
242
217
216
OR (95% CI)
Ref.
0.98 (0.68–1.41)
1.07 (0.76–1.51)
1.06 (0.75–1.50)
1.20 (0.85–1.70)
0.92 (0.63–1.33)
0.65 (0.44–0.97)
.09
Women
Cases
71
89
135
149
111
99
108
Controls
152
173
259
251
225
202
196
OR (95% CI)
Ref.
1.04 (0.69–1.57)
1.12 (0.76–1.64)
1.06 (0.72–1.55)
1.01 (0.67–1.51)
1.00 (0.66–1.51)
1.15 (0.76–1.74)
.81
Rectum
Men
Cases
75
128
173
158
143
110
69
Controls
181
226
272
279
242
217
216
OR (95% CI)
Ref.
1.32 (0.91–1.93)
1.57 (1.10–2.25)
1.27 (0.88–1.83)
1.26 (0.87–1.83)
1.01 (0.68–1.50)
0.64 (0.42–0.98)
.003
Women
Cases
63
67
79
112
108
82
78
Controls
152
173
259
251
225
202
196
OR (95% CI)
Ref.
1.02 (0.66–1.57)
0.79 (0.52–1.19)
0.98 (0.65–1.47)
1.23 (0.81–1.97)
0.92 (0.59–1.42)
1.03 (0.66–1.60)
.58
Colorectum
Men
Cases
168
252
342
332
320
240
158
Controls
181
226
272
279
242
217
216
OR (95% CI)
Ref.
1.13 (0.84–1.53)
1.31 (0.98–1.75)
1.17 (0.88–1.57)
1.25 (0.93–1.68)
0.97 (0.71–1.32)
0.66 (0.47–0.92)
0.007
Women
Cases
134
156
214
261
219
181
186
Controls
152
173
259
251
225
202
196
OR (95% CI)
Ref.
1.05 (0.74–1.48)
0.96 (0.70–1.33)
1.04 (0.75–1.42)
1.10 (0.79–1.53)
0.96 (0.68–1.35)
1.09 (0.77–1.54)
.70
Abbreviations: CI, confidence interval; DASH, Dietary Approaches to Stop Hypertension; OR, odds ratio; NECSS, National Enhanced Cancer Surveillance Study; Ref., reference.
Note: Totals may vary due to missing values.
a
Adjusted for 10-year age group (20–49, 50–59, 60–69, 70–76 years), province, education, body mass index (< 25.0, 25.0–29.9, § 30.0), pack-year smoking, moderate and strenuous activity,
calcium supplementation and age at first pregnancy for women.
interventions.30,31 In one Canadian study,
men were found to have better two-hour
post-load insulin concentrations than women
after both stayed on a Mediterranean diet.30
In addition, only the male participants
experienced a statistically significant reduction in BMI with the Mediterranean diet.
Both findings were attributed to improved
insulin sensitivity and homeostasis in
males.30
In another group of adults, adherence to a
Mediterranean diet was associated with
greater insulin sensitivity in young men
but not in pre-menopausal women.31
Although these sex-specific findings were
not assessed with regard to CRC or any
Vol 35, No 1, March 2015
other cancer, insulin response has important implications for colorectal cancer risk.
Insulin and insulin-like growth factor 1
together can promote CRC by activating
several signalling pathways associated
with an elevated risk of oncogenesis.32
That insulin may play a role in the
development of CRC is supported by the
association between type 2 diabetes and
an elevated risk of cancer including
CRC.33,34 Since the Mediterranean and
DASH diets are very similar (e.g. emphasis
on whole grains, nuts and legumes,
limited sweets) and highly correlated,12 it
is possible that our findings in men may
only be related to metabolic processes
involving insulin sensitivity.
$
17
We stratified study participants according
to BMI since dietary patterns may influence the risk of CRC only in those at high
risk of insulin resistance (i.e. with a high
BMI).35 However, we did not observe the
influence of a protective DASH pattern in
only the overweight or the obese. We
observed a protective effect of a strong
DASH pattern for rectal cancer in normal
weight men and a protective effect that
was borderline significant for CRC in
normal, overweight and obese males. We
found no statistical trends for rectal, colon
or combined cancers for women.
To further help understand this protective
association with men but not women, we
Health Promotion and Chronic Disease Prevention in Canada
Research, Policy and Practice
TABLE 5
Odds ratiosa and 95% confidence intervals of colorectal cancer according to median DASH score stratified by body mass index and sex, NECSS,
Canada, 1994–1997
Cancer site
DASH Score
3
ƒ2
4
5
6
7
§8
p value
for trend
BMI < 25.0 kg/m2
Colon (n = 629)
Men (n = 274)
Ref.
1.30 (0.68–2.51)
0.84 (0.45–1.60)
0.86 (0.45–1.63)
1.39 (0.74–2.62)
0.94 (0.48–1.85)
0.69 (0.34–1.40)
.40
Women (n = 355)
Ref.
1.53 (0.79–2.96)
1.49 (0.81–2.73)
1.53 (0.82–2.84)
2.09 (1.13–3.89)
1.60 (0.84–3.05)
1.65 (0.86–3.17)
.16
Men (n = 268)
Ref.
1.55 (0.80–3.01)
1.34 (0.72–2.51)
0.89 (0.46–1.72)
1.25 (0.64–2.43)
0.91 (0.45–1.83)
0.50 (0.24–1.07)
.01
Women (n = 278)
Ref.
0.97 (0.51–1.84)
0.77 (1.43–1.39)
0.88 (0.48–1.60)
0.91 (0.49–1.69)
0.74 (0.39–1.40)
1.04 (0.56–1.95)
.96
Men (n = 542)
Ref.
1.48 (0.87–2.52)
1.18 (0.71–1.95)
0.92 (0.55–1.55)
1.40 (0.83–2.36)
0.98 (0.57–1.70)
0.64 (0.36–1.14)
.05
Women (n = 633)
Ref.
1.32 (0.79–2.20)
1.10 (0.69–1.76)
1.17 (0.72–1.89)
1.43 (0.88–2.32)
1.13 (0.68–1.87)
1.32 (0.80–2.19)
.41
Rectum (n = 546)
Colorectum (n = 1175)
BMI § 25.0 kg/m2
Colon (n = 1084)
Men (n = 681)
Ref.
0.85 (0.55–1.32)
1.13 (0.75–1.72)
1.14 (0.75–1.72)
1.13 (0.74–1.72)
0.88 (0.56–1.38)
0.61 (0.38–0.99)
.15
Women (n = 403)
Ref.
0.74 (0.44–1.24)
1.03 (0.63–1.69)
0.74 (0.45–1.21)
0.73 (0.42–1.25)
0.75 (0.44–1.30)
0.78 (0.42–1.45)
.30
Rectum (n = 891)
Men (n = 586)
Ref.
1.21 (0.77–1.91)
1.64 (1.05–2.56)
1.45 (0.93–2.26)
1.24 (0.79–1.96)
1.06 (0.66–1.71)
0.70 (0.41–1.17)
.07
Women (n = 305)
Ref.
1.02 (0.56–1.86)
0.75 (0.41–1.38)
1.10 (0.63–1.92)
1.58 (0.90–2.80)
1.06 (0.58–1.93)
0.65 (0.50–1.82)
.47
Men (n = 1267)
Ref.
0.99 (0.68–1.43)
1.35 (0.95–1.94)
1.29 (0.91–1.84)
1.18 (0.82–1.70)
0.95 (0.65–1.39)
0.65 (0.43–0.98)
.05
Women (n = 707)
Ref.
0.85 (0.53–1.36)
0.88 (0.56–1.38)
0.96 (0.62–1.48)
0.85 (0.54–1.35)
0.83 (0.52–1.33)
0.93 (0.57–1.52)
.78
Colorectum (n = 1974)
Abbreviations: BMI, body mass index; DASH, Dietary Approaches to Stop Hypertension; CI, confidence interval; OR, odds ratio; NECSS, National Enhanced Cancer Surveillance Study.
Note: Totals may vary due to missing values.
a
Adjusted for 10-year age group (20–49, 50–59, 60–69, 70–76 years), province, education, smoking, strenuous and moderate activity, calcium supplementation and age at first pregnancy for women.
considered reproductive health factors.
We were able to assess parity, a factor
that may be associated with decreasing
risk of CRC,36-38 but the difference
between female cases and controls was
not statistically significant. We did not
collect data on the use of hormone
replacement therapy (HRT) and of oral
contraceptives (OC), although these variables are related to CRC risk. HRT is
inversely associated with risk of CRC in
most studies including the Women’s
Health Initiative, which showed a 36%
decreased risk of CRC with use of HRT.39-41
The predominant age group for HRT use is
50 to 69 years. In our study, 63% of the
cases and 53% of the controls were in that
age range. During this study period, usage
of HRT was peaking at almost 40% in
Canadian women aged 50 to 59 years and
approaching 20% for those aged 60 to 69
years.42 Thus HRT could have been a
protective factor for a high percentage
of the female participants. Nonetheless,
another study that controlled for HRT in
the logistic modelling did not report significant findings with a DASH diet in
women, even though findings in men were
significant.11 In younger women, the use
of OC may have attenuated the effect
of a low DASH-type of diet as some
studies43,44 have shown an inverse relationship between OC use and risk of CRC in
past or current OC users. Yet we suspect
the potential influence of OC use on risk of
CRC to be negligible.
fibre-containing foods (e.g. legumes), vegetables, fruit, meat, milk and vitamin D/
calcium-rich foods, sugar, alcohol, saturated fat and selenium-rich foods such as
nuts, seeds and whole grains. This global
assessment of diet and reference to specific
foods offers a scientific basis from which to
explore the DASH pattern to study the risk
of CRC and offers biological plausibility to
support our finding of an inverse association between a high score and a lower risk
of CRC in men.
Our finding that adhering to a strong DASH
pattern was associated with a reduced risk
of CRC in men is consistent with evidence
for the link of certain dietary factors with
CRC. A global assessment of diet and
prevention of cancer10 identified all of our
score’s food components or their dominant
nutrients—with the exception of sodium—
as potentially contributing to risk for CRC,
with varying strengths of association.
Specifically, these components include
Differences between cases and controls in
intakes of some DASH components varied
by sex. Some components may have been
more influential than others. For males,
higher consumption of saturated fat, alcohol
and sweets (negative nutrients) was
reported in the cases. This pattern of greater
negative nutrients was not evident in
females. For females, greater consumption
of fruit and whole grains (positive nutrients)
were reported in cases, suggesting the
Health Promotion and Chronic Disease Prevention in Canada
Research, Policy and Practice
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18
Vol 35, No 1, March 2015
presence of other factors that negate the
positive effects of these dietary components.
These findings align with reports from other
researchers that high alcohol intakes (along
with high intakes of meat and refined
grains) increased the risk of CRC—a risk
that was attenuated with increased intakes
of fruit, vegetables and whole grains.4
Conclusion
9.
Our findings suggest that a DASH pattern
of eating may be associated with a lower
risk of CRC, especially in men. Further
research could investigate the gender
differences we observed and assess the
potential importance of a DASH pattern
beyond prevention of CRC.
10. World Cancer Research Fund/American
Institute for Cancer Research. Food, nutrition, physical activity, and the prevention
of cancer: a global perspective. Washington
(DC): AICR; 2007.
Limitations
References
The case-control design of this study
inherently imparts weaknesses associated
with recall bias. This may be particularly
relevant to having to recall diet from 2
years before.
Applying dietary patterns involves some
degree of subjectivity.4,11,45 This is true
also for how authors define and determine
adherence to a DASH diet.28,46-48 In our
study, we relied on available information
to define food groups and to add relevant
foods to each group, including assigning
equivalent serving sizes. In this regard, we
may have misclassified some foods,
thereby possibly misclassifying participants into an adjacent DASH score and
possibly over-populating mid-range DASH
scores. Mid-range scores are difficult to
interpret as they may represent a lack of
positive attributes, a presence of many
negative attributes or a combination of
both. Our finding that few study participants achieved a high DASH score is an
observation reported in another similar
study.11 Further, the FFQ used in this
study was a shortened version of the Block
and Willett questionnaires and included
only 69 items. Compared with other
FFQs,11,12 ours may have been too limiting
to capture all foods contributing to the
DASH pattern.
All 10 food groups were given equal weight
for a final DASH score. However, the effect
on CRC of some dietary components
probably differ.29 For example, red and
processed meats are convincingly associated with increased risk of CRC while
saturated fats are less convincingly
linked.10 The sex differences we observed
may further point to the importance of
weighting some foods differently, especially between sexes. For example, alcohol
is convincingly associated with CRC in men
but only of probable risk for women.10
Vol 35, No 1, March 2015
1.
2.
3.
4.
Canadian cancer statistics publication
[Internet]. Ottawa (ON): Canadian Cancer
Society; 2013 [cited 2013 Jul 20]. Available
from:
http://www.cancer.ca/en/cancer
-information/cancer-101/canadian-cancer
-statistics-publication/?region=on
Colorectal cancer: risk factors [Internet].
Ottawa (ON): Public Health Agency of
Canada; 2013 [cited 2013 Dec 16]. Available
from: http://www.phac-aspc.gc.ca/cd-mc/
cancer/colorectal_cancer-cancer_colorectal
-eng.php
Huxley RR, Ansary-Moghaddam A, Clifton P,
Czernichow S, Parr CL, Woodward M. The
impact of dietary and lifestyle risk factors on
risk of colorectal cancer: a quantitative
overview of the epidemiological evidence.
Int J Cancer. 2009;125(1):171-80.
Randi G, Edefonti V, Ferraroni M, La
Vecchia C, Decarli A. Dietary patterns and
the risk of colorectal cancer and adenomas.
Nutr Rev. 2010;68:389-408.
5.
Harnden KE, Frayn KN, Hodson L. Dietary
Approaches to Stop Hypertension (DASH)
diet: applicability and acceptability to a UK
population. J Hum Nutr Diet. 2010;23:3-10.
6.
Appel LJ, Moore TJ, Obarzanek E, et al. A
clinical trial of the effects of dietary patterns
on blood pressure. N Engl J Med. 1997;336:
1117-24.
7.
Taylor EN, Stampfer MJ, Mount DB, Curhan
GC. DASH-style diet and 24-hour urine
composition. Clin J Am Soc Nephrol. 2010;
5(12):2315-22. DOI: 10.2215/CJN.04420510.
8.
Azadbakht L, Mirmiran P, Esmaillzadeh A,
Azizi T, Azizi F. Beneficial effects of a
Dietary Approaches to Stop Hypertension
eating plan on features of the metabolic
syndrome. Diabetes Care. 2005;28:2823-31.
$
19
Tobias DK, Zhang C, Chavarro J, et al.
Prepregnancy adherence to dietary patterns
and lower risk of gestational diabetes
mellitus. Am J Clin Nutr. 2012;96:289-95.
11. Dixon LB, Subar AF, Peters U, et al.
Adherence to the USDA food guide, DASH
eating plan, and Mediterranean dietary
pattern reduces risk of colorectal adenoma.
J Nutr. 2007;137:2443-50.
12. Fung TT, Hu FB, Chiuve SE, Fuchs CS,
Giovannucci E. The Mediterranean and
Dietary Approaches to Stop Hypertension
(DASH) diets and colorectal cancer. Am J
Clin Nutr. 2010;92:1429-35.
13. Mekary RA, Hu FB, Willett WC, et al. The
joint association of eating frequency and
diet quality with colorectal cancer risk in
the Health Professionals Follow-up Study.
Am J Epidemiol. 2012;175:664-72.
14. High blood pressure, 2011 [Internet].
Ottawa (ON): Statistics Canada; 2013 [cited
2013 Dec 16]. Available from: http://www
.statcan.gc.ca/pub/82-625-x/2012001/article
/11663-eng.htm
15. Villeneuve PJ, Johnson KC, Kreiger N, Mao
Y. Risk factors for prostate cancer: results
from the Canadian National Enhanced
Cancer Surveillance System. The Canadian
Cancer Registries Epidemiology Research
Group. Cancer Causes Control. 1999;10:35567.
16. Frise S, Kreiger N, Gallinger S, Tomlinson G,
Cotterchio M. Menstrual and reproductive
risk factors and risk for gastric adenocarcinoma in women: findings from the Canadian
National Enhanced Cancer Surveillance
System. Ann Epidemiol. 2006;16:908-16.
17. Hu J, La Vecchia C, Negri E, Mery L.
Nutrients and risk of colon cancer. Cancers.
2010;2:51-76.
18. Percy C, Holten VV, Muir C, editors.
International classification of diseases for
oncology, 2nd ed. Geneva (CH): World
Health Organization; 1990.
Health Promotion and Chronic Disease Prevention in Canada
Research, Policy and Practice
19. Johnson KC, Mao Y, Argo J, Dubois S,
Semenciw R, Lava Jl. The National
Enhanced Cancer Surveillance System: a
case-control approach to environmentrelated cancer surveillance in Canada.
Environmetrics. 1998;9:495-504.
20. Pan SY, Desmeules M, Morrison H, Wen
SW, and the Canadian Cancer Registries
Epidemiology Research Group. Obesity,
high energy intake, lack of physical activity, and the risk of kidney cancer. Cancer
Epidemiol Biomarkers Prev. 2006;15:245360.
21. World Health Organization. Obesity: preventing and managing the global epidemic.
Report of a WHO consultation. WHO
Technical Report Series 894. Geneva (CH):
World Health Organization; 2000.
29. Reedy J, Mitrou PN, Krebs-Smith SM, et al.
Index-based dietary patterns risk of colorectal cancer. The NIH-AARP Diet and
Study. Am J Epidemiol. 2008;168:38-48.
30. Bedard A, Riverin M, Dodin S, Corneau L
Lemieux S. Sex difference in the impact of
the Mediterranean diet on cardiovascular
risk profile. Br J Nutr. 2012;108:1428-34.
31. Carter SJ, Roberts MB, Salter J, Eaton CB.
Relationship between Mediterranean diet
score and atherothrombotic risk: findings
from the third National Health and Nutrition
Examination Survey (NHANES III), 19881994. Atherosclerosis. 2010;210:630-6.
32. Gribovskaja-Rupp I, Kosinski L, Ludwig
KA. Obesity and colorectal cancer. Clin
Colon Rectal Surg. 2011;24:229-43.
22. Block G, Hartman AM, Naughton D. A
reduced dietary questionnaire: development
and validation. Epidemiology. 1990;1:58-64.
33. Buysschaert M, Sadikot S. Diabetes and
cancer: a 2013 synopsis. Diabetes Metab
Syndr. 2013;7:247-50.
23. Willett WC. Nutritional epidemiology, 2nd
ed. New York (NY): Oxford University
Press; 1998.
34. Larsson SC, Orsini N, Wolk A. Diabetes
mellitus and risk of colorectal cancer: a
meta-analysis. J Natl Cancer Inst. 2005;97:
1679-87.
24. Health Canada. Canadian nutrient file:
compilation of Canadian food composition
data. Users’ guide. Ottawa (ON): Nutrition
Research Division and Office of Information
Management Technology Health Products
and Food Branch (Health Canada); 2005.
25. Mitrou PN, Kipnis V, Thiebaut AC, et al.
Mediterranean dietary pattern and prediction of all-cause mortality in a US population. Arch Intern Med. 2007;167:2461-8.
26. Dietary guidelines for Americans, 2005.
Appendix A. Eating patterns. Appendix A1: The DASH eating plan at 1,600-, 2,000-,
2,600-, and 3,100-calorie levels [Internet].
Rockville (MD): U.S. Department of Health
& Human Services; 2012 [cited 2012 Feb
13]. Available from: http://www.health
.gov/dietaryguidelines/dga2005/document
/html/appendixa.htm
27. SAS Institute Inc. The SAS system for
Windows release 9.01. Carey (NC): SAS
Institute Inc.; 2002.
28. Fung TT, Chiuve SE, McCullough ML,
Rexrode KM, Logroscino G, Hu FB.
Adherence to a DASH-style diet and risk
of coronary heart disease and stroke in
women. Arch Intern Med. 2008;168:713-20.
35. Fung TT, Hu FB, Schulze M, et al. A dietary
pattern that is associated with C-peptide
and risk of colorectal cancer in women.
Cancer Causes Control. 2012;23:959-65.
36. Wernli KJ, Wang Y, Zheng Y, Potter JD,
Newcomb PA. The relationship between
gravidity and parity and colorectal cancer
risk. J Womens Health. 2009;18:995-1001.
37. Zervoudakis A, Strickler HD, Park Y, et al.
Reproductive history and risk of colorectal
cancer risk in postmenopausal women. J
Natl Cancer Inst. 2011;103:826-34.
38. Nichols HB, Trentham-Dietz A, Hampton JM,
Newcomb PA. Oral contraceptive use, reproductive factors, and colorectal cancer risk:
findings from Wisconsin. Cancer Epidemiol
Biomarkers Prev. 2005;14:1212-8.
41. Lin PH, Allen JD, Li YJ, Yu M, Lien LF,
Svetkey LP. Blood pressure-lowering
mechanisms of the DASH dietary pattern. J
Nutr Metab. 2012;2012:472396. doi: 10.1155
/2012/472396.
42. De P, Neutel CI, Olivotto I, Morrison H.
Breast cancer incidence and hormone
replacement therapy in Canada. J Natl
Cancer Inst. 2010;102:1489-95.
43. Lin J, Zhang SM, Cook NR, Manson JE,
Buring JE, Lee IM. Oral contraceptives,
reproductive factors, and risk of colorectal
cancer among women in a prospective cohort
study. Am J Epidemiol. 2007;165:794-801.
44. Martinez ME, Grodstein F, Giovannucci E, et
al. A prospective study of reproductive factors,
oral contraceptive use, and risk of colorectal
cancer. Cancer Epidemiol Biomarkers Prev.
1997;6:1-5.
45. Jones-McLean EM, Shatenstein B, Whiting
SJ. Dietary pattern research and its application to nutrition policy for the prevention of
chronic disease among diverse North
American populations. Appl Physiol Nutr
Metab. 2010;35:195-8.
46. Hajna S, Liu J, LeBlanc P, Faught BE, et al.
Association between body composition and
conformity to the recommendations of
Canada’s Food Guide and the Dietary
Approaches to Stop Hypertension (DASH)
diet in peri-adolescence. Public Health
Nutr. 2012;15:1890-6.
47. Liese AD, Nichols M, Sun X, D’Agostino
RB, Haffner SM. Adherence to the DASH
diet is inversely associated with incidence
of type 2 diabetes: the Insulin Resistance
Atherosclerosis Study. Diabetes Care. 2009;
32:1434-6.
48. Whitt-Glover MC, Hunter JC, Foy CG, et al.
Translating the Dietary Approaches to Stop
Hypertension (DASH) diet for use in underresourced, urban African American communities, 2010. Prev Chronic Dis. 2013;10:120088.
doi: 10.5888/pcd10.120088.
39. Rossouw JE, Anderson GL, Prentice RL, et al.
Risks and benefits of estrogen plus progestin
in healthy postmenopausal women; principal results from the Women’s Health
Initiative. JAMA. 2002;288:321-33.
40. Kampman E, Bijl AJ, Kok C, van’t Veer P.
Reproductive and hormonal factors in male
and female colon cancer. Eur J Cancer Prev.
1994;3:329-36.
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Vol 35, No 1, March 2015
Report Summary
Congenital Anomalies in Canada 2013: A Perinatal Health
Surveillance Report by the Public Health Agency of Canada’s
Canadian Perinatal Surveillance System
B. Irvine, MA; W. Luo, MSc; J. A. León, MD
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Congenital anomalies (birth defects or
congenital malformations) are abnormalities that are present at birth, even if not
diagnosed until months or years later. They
may be present from conception, as is the
case with a chromosome defect (e.g. Down
syndrome) or gene mutation (e.g. achondroplasia), and they also include those
structural defects that occur in the embryonic period up to the end of the seventh
week of gestation (e.g. spina bifida) or in
the early fetal period between 8 and 16
weeks gestation, (e.g. orofacial clefts).
Congenital anomalies are an important
health issue because of their impact on the
health and wellbeing of Canadian infants
and children and their families and
because of the health resources they
require for management and treatment.
Approximately 1 in 25 Canadian babies is
diagnosed with 1 or more congenital
anomalies every year. Between 1998 and
2009, the national congenital anomalies
prevalence rate decreased from 451 to 385
per 10 000 total births, probably due to 3
factors: (1) increased prenatal diagnosis
and subsequent pregnancy termination;
(2) mandatory folic acid fortification of
food; and (3) changes in health behaviours and practices such as a reduction in
tobacco smoking in pregnancy. Despite
the decrease in the overall prevalence rate,
congenital anomalies are second only to
immaturity as the leading cause of infant
death.
Congenital Anomalies in Canada 2013: A
Perinatal Health Surveillance Report is the
second national surveillance report from
the Public Health Agency of Canada
dedicated to congenital anomalies.* It
provides comprehensive data on congenital anomalies in Canada, focussing on 6
categories of congenital anomalies: Down
syndrome, neural tube defects, congenital
heart defects, orofacial clefts, limb deficiency defects and gastroschisis. The
report presents national-level birth prevalence data and temporal trends, provincial
and territorial estimates, and international
comparisons. Known risk factors, prevalence-related impacts of prenatal diagnosis
and preventative measures are also discussed.
The report points to maternal obesity as
an important emerging risk factor for
some congenital anomalies. It also notes
that alcohol use and smoking during
pregnancy remain key risks that require
ongoing public health measures for prevention and prevalence reduction.
The report also highlights the difference
between primary and secondary prevention
of congenital anomalies. Primary prevention involves avoiding disease through
deliberate strategies that mitigate the risks
associated with low socio-economic status,
obesity and poor nutrition, environmental
contaminants, chronic diseases such as
hypertension and diabetes, and the influence of older maternal age. Secondary
prevention involves the early identification
of congenital anomalies through prenatal
testing, and subsequent treatment or pregnancy termination for the purpose of
reducing or preventing morbidity.
Prevalence rates
of 6 categories of congenital anomalies in Canada
Time framea
Rate per 10 000 total birthsb
Down syndrome
1998–2007
14.1
Neural tube defects
2004–2007
4.0
2009
85.1
1998–2007
16.3
Anomaly
Congenital heart defects
Orofacial clefts
c
Limb deficiency defects
Gastroschisis
2007
3.5
2002–2009
3.7
a
Time frames vary depending on the data source used for ascertainment of information.
b
Total births include live births and stillbirths.
c
For limb deficiency defects, total births include pregnancy terminations over 20 weeks occurring in hospitals.
* The first report, published in 2002 by Health Canada was entitled Congenital Anomalies in Canada – A Perinatal Health Report, 2002.
Author reference:
Health Surveillance and Epidemiology Division, Centre for Chronic Disease Prevention, Public Health Agency of Canada, Ottawa, Ontario, Canada
Correspondence: Canadian Congenital Anomalies Surveillance System, Surveillance and Epidemiology Division, Centre for Chronic Disease Prevention, Public Health Agency of Canada, 785
Carling Avenue, Ottawa, ON K1A 0K9; Email: [email protected]
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The surveillance information presented in
the report is meant to describe trends and
patterns of congenital anomalies in
Canada and to enhance our knowledge of
these conditions, thus contributing to the
evidence base that public health and
health care programs, policies and practices need for effective prevention and
management.
To download an electronic version of
the report, go to http://publications.gc.ca
/collections/collection_2014/aspc-phac/HP35
-40-2013-eng.pdf.
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Vol 35, No 1, March 2015
Report Summary
Perinatal Health Indicators 2013: a Surveillance Report by the
Public Health Agency of Canada’s Perinatal Surveillance System
B. Irvine, MA; S. Dzakpasu, PhD; J. A. León, MD
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Glossary of Definitions:
Introduction
N
The Canadian Perinatal Surveillance
System (CPSS) is a national health surveillance program of the Public Health
Agency of Canada. The CPSS mandate is
to monitor and report on key indicators of
maternal, fetal and infant health. These
indicators include both determinants and
outcomes of perinatal health.
N
N
N
N
N
N
N
N
The maternal mortality rate is the
number of maternal deaths (occurring
during pregnancy, childbirth, or within
42 days of delivery or termination of
pregnancy) divided by the number of
deliveries.
The fetal mortality rate is the number
of late fetal deaths per 1000 total births
(live births and stillbirths).
The infant mortality rate is the number
of deaths of live-born babies in the first
year after birth per 1000 live births.
Neonatal death is the death of a newborn aged 0–27 days.
Post-neonatal death is the death of an
infant aged 28–364 days.
The preterm birth rate is the number of
live births with a gestational age at
birth of less than 37 completed weeks
as a proportion of all live births.
The postterm birth rate is the number
of live births with a gestational age at
birth of 42 or more completed weeks of
pregnancy as a proportion of all live
births.
The small-for-gestational-age birth rate
is the number of singleton live births
whose birth weight is below the 10th
percentile of the sex-specific birth
weight for gestational age reference as
a proportion of all singleton live births.
The large-for-gestational-age birth rate
is the number of singleton live births
whose birth weight is above the 90th
percentile of the sex-specific birth
weight for gestational age reference as
a proportion of all singleton live births.
exclusive breastfeeding for six months
increased from 20.3% to 25.9%.
Perinatal Health Indicators 2013 reports
on 13 priority indicators using the most
recent data from vital statistics, hospitalizations, the Canadian Community Health
Survey and the National Longitudinal
Survey of Children and Youth.
The report includes the following main
findings:
Between 2001 and 2010, the rate of live
births to teenage mothers (15–19 years
old) decreased while the rate of live births
to older mothers (35–49 years old)
increased. Among mothers aged 15 to 17
and 18 to 19 years, the rate decreased from
9.1 to 7.7 and 31.1 to 25.8 per 1000
females respectively. Among mothers
aged 35 to 39, 40 to 44 and 45 to 49 years,
the rate increased from 32.0 to 49.3, 5.2 to
9.2 and 0.2 to 0.4 per 1000 females,
respectively. As a result of these trends,
the proportion of all live births to teenage
mothers declined from 5.6% to 4.2%,
while the proportion to older mothers
increased from 14.7% to 17.0%.
Maternal outcomes
Behaviours and practices
Between 1993–1996 and 2005–2008,
overall maternal smoking during pregnancy decreased from 21.9% to 12.3%.
Smoking prevalence decreased with age;
the smoking rate was seven times higher
in mothers aged less than 20 years
(38.8%) than in those aged 35 to 39
years (5.6%).
The rate of maternal alcohol consumption
also decreased over the same time, from
15.5% to 10.7%.
Between 2005 and 2009–2010, the rate of
breastfeeding initiation remained stable at
approximately 88%, while the rate of
Between 2003–2004 and 2010–2011, the
rate of severe maternal morbidity fluctuated between 13.2 and 15.4 per 1000
deliveries. The most common severe
maternal morbidities were blood transfusion, postpartum hemorrhage with blood
transfusion and hysterectomy. Between
2001–2002 and 2010–2011, the rate of
Caesarean delivery increased from 23.4%
to 28.0%.
Between 2003–2004 and 2010–2011, the
rate of maternal mortality fluctuated
between 8.2 and 6.1 per 100 000 hospital
deliveries. The most common diagnoses
associated with maternal deaths were
diseases of the circulatory system, post-
Author reference:
Health Surveillance and Epidemiology Division, Centre for Chronic Disease Prevention, Public Health Agency of Canada, Ottawa, Ontario, Canada
Correspondence: Canadian Perinatal Surveillance System, Surveillance and Epidemiology Division, Centre for Chronic Disease Prevention, Public Health Agency of Canada, 785 Carling,
Ottawa, ON K1A 0K9; Email: [email protected]
Vol 35, No 1, March 2015
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Health Promotion and Chronic Disease Prevention in Canada
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partum hemorrhage and hypertension
complicating pregnancy, childbirth and
the puerperium.
Infant outcomes
Between 2001 and 2010, the fetal mortality
rate increased from 5.9 to 6.7 per 1000
total births. In 2010, the mortality rates for
fetuses weighing 500 g and over and
1000 g and over were 5.1 and 3.7 per
1000 total births, respectively. Between
2000 and 2009, the infant mortality rate
varied between 4.9 and 5.4 per 1000 live
births.
Neonatal death constituted 74% of infant
deaths in 2009. Immaturity and congenital
anomalies were the leading causes of
neonatal death. Congenital anomalies
and Sudden Infant Death Syndrome were
the leading causes of post-neonatal death.
After decreasing between 2001 and 2007
from 460 to 377 per 10 000 total births, the
overall prevalence of congenital anomalies
increased to 397 per 10 000 total births in
2010.
Between 2001 and 2010, the rate of
preterm birth fluctuated between 7.5%
and 8.2% of live births and was 7.7% in
2010. During this 10-year period, the rate
of post-term birth declined from 1.1% to
0.6%. The rate of small-for-gestational-age
birth among singleton infants fluctuated
between 7.8% and 8.3% while the rate of
large-for-gestational age birth among singleton infants decreased from 11.8% to
10.4%. The rate of multiple births
increased from 2.8% to 3.2% of total
births.
Conclusion
The picture of national perinatal health
provided by Perinatal Health Indicators
2013 is meant to enhance current knowledge in the field and to provide evidence
that using public health/health system
programs, policies and practices improves
the health of mothers and babies in
Canada.
To obtain an electronic copy of the report,
please contact the Canadian Perinatal
Surveillance System at [email protected]
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Vol 35, No 1, March 2015
Release notice
Data release for the Canadian Longitudinal Study on Aging
The first major data release from the Canadian Longitudinal Study on Aging (CLSA) is underway. The June 2014 release includes data
collected from 21 242 participants who each completed a 60-minute telephone interview. Additional data from these interviews will
become available early in 2015.
The process for accessing biospecimens and physical assessment data from an additional 30 000 participants who were interviewed in
person and have visited one of 11 data collection sites across the country, is currently being developed in anticipation of the first
release of these data in 2016.
Canadian and international public sector researchers interested in accessing the CLSA platform are invited to visit the DataPreview
Portal on the CLSA website for detailed information about the available data and the application process.
Data will be available to researchers following review of applications by the CLSA Data and Sample Access Committee. For more
information, visit www.clsa-elcv.ca.
Vol 35, No 1, March 2015
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Health Promotion and Chronic Disease Prevention in Canada
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With thanks to our 2014 peer reviewers
We are grateful to the following people for their significant contribution to Chronic Diseases and Injuries in Canada as peer reviewers
in 2014. Their expertise ensures the quality of our journal and promotes the sharing of new knowledge among peers in Canada and
internationally.
Calypse B. Agborsangaya
Milton Hasnat
Anthony Perruccio
Eric I. Benchimol
Ralph Hingson
Cynthia Robitaille
Pangala Bhat
Kathleen Kerr
A. Sentil Senthilselvan
Claudia Blais
Claudia Lagacé
Kelly Skinner
Michelle Cotterchio
Lisa M. Lix
Robert A. Spasoff
Eric Crighton
Dawn C. Mackey
Janice Sumpton
Patrick Daigneault
Alison Macpherson
Ania Syrowatka
Paula Fletcher
Steven R. McFaull
Jim Thrasher
Rochelle Garner
Delphine Mitanchez
Hayfaa Abdelmageed Ahmed Wahabi
Lawrence W. Green
Annie Montreuil
Peizhong Peter Wang
How-Ran Guo
Lynne Moore
Brent Hagel
Carmina Ng
Health Promotion and Chronic Disease Prevention in Canada
Research, Policy and Practice
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Vol 35, No 1, March 2015
Other PHAC publications
Researchers from the Public Health Agency of Canada also contribute to work published in other journals. Look for the
following articles published in 2014:
Auger N, Gilbert NL, Naimi AI, Kaufman JS. Fetuses-at-risk, to avoid paradoxical associations at early gestational ages: extension to
preterm infant mortality. Int J Epidemiol. 2014;43(4):1154-62.
De P, Otterstatter MC, Semenciw R, Ellison LF, Marrett LD, Dryer D. Trends in incidence, mortality, and survival for kidney cancer in
Canada, 1986-2007. Cancer Causes Control. 2014;25(10):1271-81.
Evans J, Skomro R, Driver H, Graham B, Mayers I, McRae L, Reisman J, Rusu C, To T, Fleetham J. Sleep laboratory test referrals in
Canada: Sleep Apnea Rapid Response survey. Can Respir J. 2014;21(1):e4-e10.
Gee ME, Campbell N, Sarrafzadegan N, Jafar T, Khalsa TK, Mangat B, et al. Standards for the uniform reporting of hypertension in
adults using population survey data: recommendations from the World Hypertension League Expert Committee. J Clin Hypertens.
2014;16(11):773-81.
Lemke LD, Lamerato LE, Xu X, Booza JC, Reiners Jr. JJ, Raymond III DM, Villeneuve PJ, Lavigne E, Larkin D, Krouse HJ. Geospatial
relationships of air pollution and acute asthma events across the Detroit-Windsor international border: study design and preliminary
results. J Expo Sci Environ Epidemiol. 2014;24(4):346-57.
Lo E, Hamel D, Jen Y, Lamontagne P, Martel S, Steensma C, et al. Projection scenarios of body mass index (2013-2030) for Public
Health Planning in Quebec. BMC Public Health. 2014;14:996.
Mehrabadi A, Liu S, Bartholomew S, Hutcheon JA, Magee LA, Kramer MS, et al. Hypertensive disorders of pregnancy and the recent
increase in obstetric acute renal failure in Canada: population based retrospective cohort study. BMJ. 2014;349:g4731.
Pickett W, Kukaswadia A, Thompson W, Frechette M, McFaull S, Dowdall H, et al. Use of diagnostic imaging in the emergency
department for cervical spine injuries in Kingston, Ontario. CJEM. 2014;16(1):25-33.
Shi Y, de Groh M, MacFarlane AJ. Socio-demographic and lifestyle factors associated with folate status among non-supplementconsuming Canadian women of childbearing age. Can J Public Health. 2014;105(3):e166-71.
Thompson B, Cooney P, Lawrence H, Ravaghi V, Quiñonez C. The potential oral health impact of cost barriers to dental care: findings
from a Canadian population-based study. BMC Oral Health. 2014;14:78.
Vol 35, No 1, March 2015
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Health Promotion and Chronic Disease Prevention in Canada
Research, Policy and Practice
HPCDP: Information for authors
Below are Health Promotion and Chronic Disease Prevention
in Canada’s article types and submission guidelines.
Information about the journal and its mandate can be
found at http://www.phac-aspc.gc.ca/publicat/hpcdppspmc/publica-eng.php and http://www.phac-aspc.gc.ca/
publicat/hpcdp-pspmc/authinfo-eng.php.
Article Types
Peer-reviewed Articles
Original Research Articles
Article Reporting on Quantitative Research: Maximum
3500 words in English (or 4400 words in French) for main
text body (excluding abstract, tables, figures, references)
in the form of original research, surveillance reports, or
methodological papers. Please include a structured abstract
(maximum 250 words in English, or 345 words in French)
with the following headings: Introduction, Methods, Results, Discussion, Conclusion. No more than 30 references.
Article Reporting on Qualitative Research or Mixed
Methods: Maximum 5000 words in English (or 6500 in
French) for main text body (excluding abstract, tables,
figures, references). Methodological papers welcomed.
Process evaluations that accompany qualitative analyses
are welcomed. Please include a structured abstract (maximum 250 words in English, or 345 words in French) with
the following headings: Introduction, Methods, Results,
Discussion, Conclusion. No more than 30 references. The
HPCDP Journal follows the guidelines for qualitative articles as set by Social Science and Medicine : http://www.
elsevier.com/wps/find/journaldescription.cws_home/315/
authorinstructions
Article Reporting on Public Health Intervention:
“Population health interventions are policies, programs and
resource distribution approaches that impact a number of
people by changing the underlying conditions of risk and
reducing health inequities.” [CIHR, Population Health Research Initiative for Canada] Quantitative, qualitative or
mixed methods studies and evaluations of interventions
are welcomed. Maximum 3500-5000 words in English
(4400-6500 words in French) for main text body (excluding abstract, tables, figures, references). Please include a
structured abstract (maximum 250 words in English, or 345
words in French) with the following headings: Objectives,
Participants, Setting and Context, Intervention, Evaluation
Methods, Results, Conclusion. No more than 30 references.
Evidence Synthesis
systems bearing on pan-Canadian public health (maximum
2000 words in English, or 2600 words in French). May
be peer reviewed and an abstract may be required at the
request of the Editor-in-Chief. No more than 40 references.
At-a-Glance
Infographic, chart or diagram depicting trends or providing
at-a-glance information on a specific public health issue
with pan-Canadian relevance. May be accompanied by
explanatory text of 500 words maximum (630 words in
French) supporting or explaining the depicted information.
No more than 6 references.
Release Notice/Report Summary
Maximum 1000 words in English, or 1300 words in French.
The “Report Summary” allows authors of grey literature
to have a summary of key findings appear in PubMed as
“News”. Abstract not required.
Book/Media Review
Usually solicited by the editors (maximum 800 words in
English, or 1000 words in French), but requests to review
are welcomed. Abstract not required.
Letter to the Editor
Commentary on recently published journal articles or
issues will be considered for publication (maximum 500
words in English, or 630 words in French). Comments
must be received within one month of publication date
to be considered. Abstract not required. No more than 6
references.
Submitting Manuscripts to the
HPCDP Journal
Kindly submit manuscripts to the Editor-in-Chief of the
journal at [email protected]
Since the HPCDP Journal generally adheres to the
“Recommendations for the Conduct, Reporting, Editing
and Publication of Scholarly Work in Medical Journals”
as approved by the International Committee of Medical
Journal Editors, authors should refer to this document
(section on illustrations not applicable) for complete details
before submitting a manuscript to the journal (see www.
icmje.org).
To obtain a more detailed style sheet, please contact the
Managing Editor at [email protected]
Provides a systematic assessment of literature and relevant
data sources (systematic review, meta-analysis), a scoping
review, realist review or an environmental scan. Authors
should report the type of review they undertook and
describe their methods for performing the review, including
the ways information was searched for, selected, analyzed
and summarized. Process evaluations that accompany
systematic reviews are welcomed. Please follow accepted
standards for the reporting of meta-analyses or systematic
reviews (e.g. AMSTAR, PRISMA, QUORUM, MOOSE).
Purely qualitative syntheses are accepted (e.g. realist
reviews). Please follow accepted standards in qualitative
reviewing (e.g. RAMSES for realist reviews/meta-narrative
reviews). Maximum 4000 words in English (5000 words
in French) for main text body (excluding abstract, tables,
figures, references). Please include a structured abstract
(maximum 250 words in English, or 345 words in French)
with the following headings: Introduction, Methods,
Results, Discussion, Conclusion. References: no limit.
Checklist for Submitting
Manuscripts
Evidence Brief
Concise title; full names, institutional affiliations and
highest academic degree of all authors; name, postal
and email addresses, and telephone and fax numbers
for corresponding author only; separate word counts for
abstract and text; indicate number of tables and figures.
Describes results of interest to a broad audience of public
health and related professionals. There should be no more
than 6 figures or tables (total). Maximum 1500 words
in English, or 1950 words in French. Please include an
unstructured abstract (maximum 100 words in English,
or 130 words in French). The unstructured abstract has
no more than 5 sentences, each one corresponding to
the subheadings in the body of the paper: Introduction,
Methods, Findings, Discussion, Conclusion. No more than
20 references.
Cover letter/Conditions of authorship
Signed by corresponding or first author, stating that all
authors have seen and approved the final manuscript. Must
confirm that the material has not been published in whole
or in part elsewhere and that the paper is not currently
being considered for publication elsewhere. Must state that
all authors meet the following conditions of authorship:
authors were involved in design or conceptualization of the
study, and/or analysis or interpretation of the data, and/
or drafting of the paper. Should declare if an author has a
conflict of interest, if applicable.
Please fax or email a scanned copy of the signed letter to
613-941-2057 or [email protected]
First title page
Second title page
Title only; start page numbering here as page 1.
Abstract
Non-Peer-reviewed Articles
Structured (Introduction, Methods, Results, Conclusion)
where applicable; include 3 to 8 key words (preferably from
the Medical Subject Headings [MeSH] of Index Medicus).
Status Report
Key Findings Box
Describes ongoing national health promotion or chronic
disease/injury prevention programs, studies or information
Maximum 100 words (130 in French) to describe the key
findings of the paper in plain language.
Text
In Microsoft Word. Double-spaced, 1 inch (25 mm)
margins, 12-point font size. For Original Research articles,
please structure the paper with the following subheadings:
Introduction, Methods, Results, Discussion, Conclusion.
The Discussion section should contain a “Strengths and
Limitations” subsection. The Conclusion should avoid
statements that are not supported by the results of the
investigation. For Public Health Intervention articles,
please structure the paper with the following subheadings:
Objectives, Participants, Setting and Context, Intervention,
Evaluation Methods, Results, Conclusion. The Conclusion
should avoid statements that are not supported by the
results of the investigation.
Acknowledgments
Include disclosure of financial and material support
in acknowledgements; if anyone is credited in
acknowledgements authors should state in their cover letter
that they have obtained written permission.
References
In Vancouver style (for examples see: http://www.ncbi.nlm.
nih.gov/books/NBK7256/); listing up to six authors (first
three and “et al.” if more than six). Numbered in superscript
in the order cited in text, tables and figures. Please do not
use an automatic reference numbering feature found in
word processing software. Any unpublished observations/
data or personal communications used (discouraged) to be
cited in the text in parentheses (authors are responsible for
obtaining written permission). Authors are responsible for
verifying accuracy of references and hyperlinks.
Tables and Figures
If created in Word, please place at the end of the main
manuscript. If created in Excel, please place in one separate
file. They must be as self-explanatory and succinct as
possible; numbered in the order that they are mentioned
in the text; explanatory material for tables in footnotes,
identified by lower-case superscript letters in alphabetical
order; figures limited to graphs, flow charts or diagrams, or
maps (no photographs). If figures are submitted in Word,
raw data will be requested if the manuscript is accepted
for publication.
Ethics in Publishing
Since the journal generally adheres to the “Recommendations
for the Conduct, Reporting, Editing and Publication of
Scholarly Work in Medical Journals” as approved by the
International Committee of Medical Journal Editors, authors
should refer to this document for information regarding
ethical considerations.
Revision Process
For peer-reviewed articles: Submitted articles first undergo an initial assessment by the Editor-in-Chief and an
external Associate Scientific Editor as to the suitability
of the manuscript for publication with our journal. If the
manuscript fits within our mandate, it will need to pass
through a streamlined institutional review process prior to
peer-review. Then the article will undergo a double-blind
peer-review process. Once the reviews have been received,
the Associate Scientific Editor assigned to the article will
adjudicate the reviews and make one of the following
recommendations: “accept,” “reconsider after minor revisions,” “reconsider after major revisions” or “reject.”
For non-peer-reviewed articles: Submitted articles first
undergo an initial assessment by the Editor-in-Chief and, if
deemed necessary, by an external Associate Scientific Editor as to the suitability of the manuscript for publication
with our journal. If the manuscript fits within our mandate,
it will then need to pass through a streamlined institutional
review process. Revisions may be requested.
Copyright
The Public Health Agency of Canada requests that authors
formally assign in writing their copyright for each article
published in the journal. Once the article is accepted for
publication, a copyright waiver will be distributed to the
authors of the article for signature. For more information,
please contact the Managing Editor at [email protected]
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