Chronic Diseases and Injuries in Canada Inside this issue

Chronic Diseases and Injuries in Canada Inside this issue
Chronic Diseases and
Injuries in Canada
Volume 31 · Number 3 · June 2011
Inside this issue
94
95
97
Preface – What’s in a name: Chronic Diseases
and Injuries in Canada
H. Morrison, M. Tracy
Editorial – Non-communicable diseases – finally
on the global agenda
A. T. Wielgosz
Patterns of fatal machine rollovers
in Canadian agriculture
J. M. DeGroot, C. Isaacs, W. Pickett, R. J. Brison
103 Estimating gestational age at birth:
a population-based derivation-validation study
M. L. Urquia, T. A. Stukel, K. Fung, R. H. Glazier, J. G. Ray
109 The influence of primary health care
organizational models on patients’ experience
of care in different chronic disease situations
R. Pineault, S. Provost, M. Hamel, A. Couture, J. F. Levesque
121 An assessment of the barriers to accessing food
among food-insecure people in Cobourg, Ontario
S. Tsang, A. M. Holt, E. Azevedo
129 Estimates of the treated prevalence of bipolar
disorders by mental health services in the
general population: comparison of results
from administrative and health survey data
A. G. Bulloch, S. Currie, L. Guyn, J. V. Williams,
D. H. Lavorato, S. B. Patten
CDIC: Information for authors
Chronic Diseases and Injuries in Canada
a publication of the Public Health Agency
of Canada
Howard Morrison, PhD
Editor-in-Chief
(613) 941-1286
Robert A. Spasoff, MD
Associate Scientific Editor
Claire Infante-Rivard, MD
Associate Scientific Editor
Elizabeth Kristjansson, PhD
Associate Scientific Editor
Lesley Doering, MSW
Public Health Agency of Canada
Robert Geneau, PhD
Public Health Agency of Canada
Isra Levy, MB, FRCPC, FACPM
Ottawa Public Health
Lesli Mitchell, MA
Centers for Disease Control and Prevention
Scott Patten, MD, PhD, FRCPC
University of Calgary
Michelle Tracy, MA
Managing Editor
Chronic Diseases and Injuries in Canada (CDIC) is a
CDIC Editorial Board
Barry Pless, CM, MD, FRCPC
Montreal Children’s Hospital
Kerry Robinson, PhD
Public Health Agency of Canada
Fabiola Tatone-Tokuda, MSc
University of Ottawa
Andreas T. Wielgosz, MD, PhD, FRCPC
University of Ottawa
References: In Vancouver style (consult a recent CDIC
issue for examples); num­bered in superscript in the
Chronic Diseases and Injuries in Canada (CDIC)
is a quarterly scientific journal focussing
on current evidence relevant to the control
and prevention of chronic (i.e. noncommunicable) diseases and injuries in
Canada. Since 1980 the journal has published
a unique blend of peer-reviewed feature
articles by authors from the public and
private sectors and which may include
research from such fields as epidemiology,
public/community health, biostatistics, the
behavioural sciences, and health services or
economics. Only feature articles are peer
reviewed. Authors retain responsibility for
the content of their articles; the opinions
expressed are not necessarily those of the
CDIC editorial committee nor of the Public
Health Agency of Canada.
and control of non‑communicable diseases and injuries
Submit manuscripts to the Managing Editor,
order cited in text, tables and figures; listing up to
in Canada. Its feature articles are peer reviewed.
Chronic Diseases and Injuries in Canada, Public
six authors (first six and et al. if more); without any
The content of articles may include research from
Health Agency of Canada, 785 Carling Avenue,
automatic reference numbering feature used in
such fields as epidemiology, public/community
Address Locator 6805B, Ottawa, Ontario K1A 0K9,
word processing; any unpublished observations/
health, biostatistics, the behavioural sciences, and
email: [email protected]
data or personal communications used (discouraged)
Chronic Diseases and Injuries in Canada
Public Health Agency of Canada
785 Carling Avenue
Address Locator 6805B
Ottawa, Ontario K1A 0K9
papers, and opinions expressed are not necessarily
Fax: (613) 941-9502
E-mail: [email protected]
Public Health Agency of Canada
Don Wigle, MD, PhD
Submitting Manuscripts
quarterly scientific journal focusing on the prevention
Indexed in Index Medicus/MEDLINE,
SciSearch® and Journal Citation Reports/
Science Edition
Russell Wilkins, MUrb
Statistics Canada
health services or economics. CDIC endeav­ours to
to be cited in the text in parentheses (authors
foster communication on chronic diseases and injuries
Since CDIC adheres in general (section on illustrations
responsible for obtaining written per­mis­sion); authors
among public health practitioners, epidemiolo­gists
not applicable) to the “Uniform Requirements for
are responsible for verifying accuracy of references.
and researchers, health policy plan­ners and health
Manuscripts Submitted to Biomedical Journals”
educators. Submissions are selected based on scientific
as approved by the International Committee of
Tables and Figures: Send vector graphics only.
quality, public health relevance, clarity, concise­ness
Medical Journal Editors, authors should refer to this
Each on a separate page and in electronic file(s)
and technical accuracy. Although CDIC is a publication
document for complete details before submitting a
separate from the text (not imported into the text
of the Public Health Agency of Canada, contributions
manuscript to CDIC (see <www.icmje.org>).
body); as self‑explanatory and succinct as possible;
are welcomed from both the public and pri­vate sectors.
Authors retain responsibility for the contents of their
those of the CDIC editorial committee nor of the
Public Health Agency of Canada.
Article Types
Checklist for Submitting
Manuscripts
in
footnotes,
identified
by
lower‑case
superscript letters in alpha­
betical order; figures
limited to graphs or flow charts/templates (no
photographs), with software used specified and
the authorship criteria including a full statement
titles/footnotes on a separate page.
regarding any prior or duplicate publi­
cation or
submission for publication.
Peer‑reviewed Feature Article: Maximum 4000
Number of copies: If submitting by mail, one
complete copy, including tables and figures; one
words for main text body (excluding abstract,
First title page: Concise title; full names of all
copy of any related supple­men­tary material, and a
tables, figures, references) in the form of original
authors and institutional affiliations; name, postal
copy of the manuscript on diskette. If submitting by
research, surveillance reports, meta‑analyses or
and email addresses, tele­phone and fax numbers
email to cdic‑[email protected]‑aspc.gc.ca, please fax or
methodological papers.
for corresponding author; separate word counts for
mail the covering letter to the address on the inside
abstract and text.
front cover.
studies or information systems bearing on Canadian
Second title page: Title only; start page numbering
public health (maximum 3000 words). Abstract
here as page 1.
Abstract: Unstructured (one paragraph, no headings),
Workshop/Conference Report: Summarize significant,
maximum 175 words (100 for short reports); include
recently held events relat­ing to national public health
3-8 keywords (preferably from the Medical Subject
(maximum 1200 words). Abstract not required.
Headings [MeSH] of Index Medicus).
Cross‑Canada Forum: For authors to present or
Text: Double‑spaced, 1 inch (25 mm) margins,
exchange information and opin­ions on regional or
12 point font size.
national surveillance findings, programs under
development or public health policy initiatives
Acknowledgements: Include disclosure of financial
(maximum 3000 words). Abstract not required.
and material support in acknowledgements; if anyone
is credited in acknowledgements with substantive
This publication is also available online at www.publichealth.gc.ca/cdic
Également disponible en français sous le titre : Maladies chroniques et blessures au Canada
tables
seen and approved the final manuscript and have met
not required.
Published by authority of the Minister of Health.
© Her Majesty the Queen in Right of Canada, represented by the Minister of Health, 2011
ISSN 1925-6523
are mentioned in the text; explanatory material for
Cover letter: Signed by all authors, stating that all have
Status Report: Describe ongoing national programs,
To promote and protect the health of Canadians through leadership, partnership, innovation and action in public health.
— Public Health Agency of Canada
not too numerous; numbered in the order that they
Letter to the Editor: Comments on articles recently
scientific contributions, authors should state in the
published in CDIC will be consid­ered for publication
cover letter that they have obtained written permission.
(maximum 500 words). Abstract not required.
Book/Software Review: Usually solicited by the
editors (500-1300 words), but requests to review
are welcomed. Abstract not required.
Preface
What’s in a name: Chronic Diseases and Injuries in Canada
As of this current issue, Chronic Diseases
in Canada (CDIC) has been renamed Chronic
Diseases and Injuries in Canada (CDIC).
Reporting on injuries (accidents, occupational
injuries and intentional injuries, including
suicide) has always been part of the journal’s
implicit mandate, if not its name. As the
guest editor, Dr. A. J. Clayton, wrote in the
inaugural issue, “We propose to include
material based on research, surveillance and
control aspects of non-communicable diseases or conditions such as cancer, heart
disease and accidents.” Since 1993, the
mission statement on the inside cover of the
journal has included mention of injuries as
part of the journal’s focus.
In fact, since its inception in June 1980, CDIC
has published over 50 articles on injuries, as
well as the proceedings of the International
Conference on Air Bags and Seat Belts
(October 18-20, 1992, Montreal, Quebec).
Two theme issues were devoted to the topic
of injuries (Volume 11, Number 6, 1990 and
Volume 15, Number 1, 1994). CDIC was
one of the first journals to publish a study
based on data obtained from the Canadian
Hospitals Injury Reporting and Prevention
Program (CHIRPP), which has a strong
focus on paediatric injury surveillance.
More recently, CDIC has published papers
on variations in injury among urban-rural
geographic status (Jiang, 2007;28(1-2):56-62),
seniors and falls (Leclerc, 2008;28(4):111-120),
the link between deprivation and unintentional
injury hospitalization (Gagné, 2009;29(2):5669) and how to make injury data useful to
policy makers (Mitton, 2009;29(2):70-9).
In the current issue, we are pleased to feature
a paper by DeGroot et al., “Patterns of fatal
machine rollovers in Canadian agriculture”
(p. 97). A paper by Campbell et al. entitled
“Can we use medical examiners’ records for
suicide surveillance and prevention research
in Nova Scotia?” will be published in our
September 2011 issue (Volume 31:4).
Changing the journal’s name to include the
word “Injuries” in the title is more than just
calling a spade a spade, however. It reflects
a shift in research priorities where experts
will be needed to perform risk assessment
as well as the usual surveillance. This shift
is reflected on a corporate level within the
Public Health Agency of Canada, which is
the organization that publishes CDIC. In
this vein, the editors would be interested
in seeing papers that support or challenge
current platforms for chronic disease risk
assessment and/or make novel use of
available data sources to report on injury
risk factors. We would also be interested in
receiving manuscripts of structured reviews of
population interventions meant to reduce
injury risk in the Canadian population.
Howard Morrison, PhD, Editor-in-Chief
Chronic Diseases and Injuries in Canada
Michelle Tracy, MA, Managing Editor
Chronic Diseases and Injuries in Canada
94
Vol 31, No 3, June 2011 – Chronic Diseases and Injuries in Canada
Editorial
Non-communicable diseases – finally on the global agenda
A.T. Wielgosz, MD, PhD, Professor of Medicine and Epidemiology & Community Medicine, University of Ottawa
After the UN Millennium Development
Goals were declared in September 2000
(see Table 1), one of the major short-comings recognized world-wide was the lack
of mention of non-communicable diseases
(NCDs). While AIDS and malaria were
included, none of the leading and universal non-communicable causes of death
made the list. There was no mention of
cardiovascular diseases, cancer or diabetes, even though these place a far greater
burden on global health and economic
development than the infectious diseases
and are predicted to continue to increase
in epidemic proportions.
After much public discussion and intense
lobbying, a significant—and uncommon—
achievement occurred: on May 13th, 2010,
the United Nations General Assembly
voted in favour of convening a summit on
non-communicable diseases, to take place
in September 2011.
The resolution calling for the UN Summit,
tabled by Trinidad and Tobago on behalf
of the Caribbean Community (CARICOM)
member states, was cosponsored by over
100 countries including the United States,
which traditionally resists UN summits.
However, in this case support even came
from the US First Lady and the Secretary of
State. This level of support acknowledges
the burden of NCDs—diabetes, cancer, and
cardiovascular and chronic respiratory illnesses are responsible for 60 percent of
deaths world-wide—and indicates that
NCDs have become a priority matter for
world leaders.
Although the lead-up to September’s Summit
has taken a decade, momentum has increased
such that there is a short timeline for preparation. The resolution calls on member states
and the international community to:
• convene a high-level meeting of the
General Assembly in September 2011,
with the participation of Heads of State
and Government, on the prevention
and control of NCDs;
• include discussions on the rising incidence and the socio-economic impact
of NCDs in developing countries during the 2010 Millennium Development
Goals Review Summit;
• request the UN Secretary-General
to prepare a global status report on
NCDs, with a particular focus on
the developmental challenges faced
by developing countries.
High expectations emerged early after the
resolution was declared. After reviewing data
about the impact of NCDs on individuals and
countries, the Summit should recognize that
a collaborative, international effort will be
most effective at controlling these diseases
and preventing their spread. More importantly, it is expected that such a high-level
event—with a potential effect similar to that
of a UN General Assembly Special Session
(UNGASS)—will result in concrete action
steps applicable on a global scale. These will
have to be monitored through periodic progress reports, so as to provide a measure
of accountability to any resolutions and
particularly the declared action steps.
Vol 31, No 3, June 2011 – Chronic Diseases and Injuries in Canada
95
Through comprehensive consultation,
specific indicators and outcomes need to
be identified to use for monitoring and
evaluating progress. There are issues of
resources and capacity to effectively carry
out the actions that will be agreed upon,
particularly in low- and middle-income
countries. Broad representation and buy-in
will be required from the start in order to
ensure societal uptake. The work will not
stop with the Summit, of course. At the
end of the discussions, there must be a
strong commitment, appropriately articulated, to continue the work with the full
participation of member states.
Preparing for the Summit will offer opportunities for widespread engagement, and
various non-governmental organizations
are working together through a global alliance. In late December 2010, a UN modalities resolution was adopted that declared
September 19-20, 2011 as the dates of
the Summit. It included a call for all UN
Member States to be represented by Heads
of State but most importantly, it called for
Member States to adopt a concise actionoriented outcome document at the end of
the Summit. Three roundtable sessions are
planned, which will focus on the rising
incidence of NCDs, strengthening national
capacities and fostering international
cooperation and coordination.
Given Canada’s experience and resources,
it must not only be a leader but must be
seen to be a leader in this global effort.
Canada made a significant contribution
to the Framework Convention on Tobacco
Control (FCTC), which was a success as the
first international treaty on a matter of health,
and which continues to reap benefits country
by country by reducing the effects on health
of tobacco use through international cooperation and action on tobacco control.
Canadian strengths are in policy development, intersectoral collaboration and community engagement.
The challenges in stemming the epidemic
of NCDs with all the lifestyle-related factors are enormous. As a wealthy nation
with considerable experience in addressing prevention and control of the leading
causes of death and disability, there will
be a high expectation of assistance from
Canada for countries with middle and low
economies, even as Canada is challenged
to stem this epidemic within its own borders. Success will be achieved through
trust, mutual respect and collaboration.
The Summit will be a historic event. More
importantly, it must succeed.
TABLE 1
United Nations Millennium
Development Goals
1. Eradicate extreme poverty and hunger.
2. Achieve universal primary education.
3. Promote gender equality and empower women.
4. Reduce child mortality.
5. Improve maternal health.
6. Combat HIV/AIDS, malaria and other diseases.
7. Ensure environmental sustainability.
8. Develop a global partnership for development.
96
Vol 31, No 3, June 2011 – Chronic Diseases and Injuries in Canada
Patterns of fatal machine rollovers in Canadian agriculture
J.M. DeGroot, MSc (1); C. Isaacs, MSc (1); W. Pickett, PhD (1,2); R.J. Brison, MPH (1,2,3)
Abstract
Introduction: Our objectives were to examine the activities and circumstances associated
with agricultural machine-related rollover fatalities.
Methods: We identified agricultural machine rollover fatalities recorded by the Canadian
Agricultural Injury Surveillance Program (CAISP) in 1990–2005. We determined sideways
and backwards rollovers by year, age and sex of the victims, agricultural season, machine
type, and the activity, circumstances and location of the injury event.
Results: The annual rate of rollover fatalities in Canada was 9.1 per 100 000 farm operations.
Rollover fatalities decreased to 30% of baseline over the 16-year study period (p = .004).
Fatal rollovers most often occurred among men aged 50–69 years and 60–79 years for sideways and backwards rollovers, respectively.
Discussion: Sideways rollovers occur when driving across an incline or at the edge
of a ditch bordering a roadway or field. Backwards rollovers occur when driving up an
incline, towing or extracting stuck machines, pulling stumps or trees, and towing implements
or logs. Primary prevention programs for rollover injuries should target these identified
patterns of injury.
Keywords:agricultural machine rollover, agricultural injuries, injury prevention,
mortality, rollover protection structures, injury surveillance
Introduction
Agriculture is one of the most dangerous
industries in Canada, with estimated annual
population fatality rates between 14.6 and
25.6 per 100 000.1 It is similarly hazardous
in other developed countries.2,3 In Canada,
agricultural-related machine rollovers—when
a vehicle or machine turns over either
onto its side or backwards—account for
approximately 40 hospitalizations (2.4%
of agriculture-related hospitalized injuries)
and 21 fatalities per year (20% of agriculture-related fatal injuries).1,4 Rollover events
develop rapidly leaving little or no time for
evasive action; tractors can tip backwards
to the point of no return in 0.75 seconds.5
There is ample evidence to support the
efficacy of rollover protection structures
(ROPS) as a secondary prevention strategy
in reducing injury in rollover events.6-8
(Secondary prevention is defined as any
strategy that limits the severity of an
injury during the occurrence of an injury
event such as a rollover.)9 There are less
data available to inform primary prevention
strategies that might decrease the occurrence
of rollover events. (Primary prevention is
defined as any strategy that might prevent
the occurrence of the injury event in the
first place.)9
A number of studies have examined rollovers
while exploring a spectrum of agricultural
workplace injuries.1-4 However, a recent
search of the biomedical literature did not
identify any studies that describe common
patterns of occurrence for rollover injuries.
Knowing the circumstances of injury
events and the people involved can inform
primary prevention methods for rollover
events and perhaps better target secondary
strategies such as ROPS installation.
Identifying the most hazardous situations
and those people at highest risk could
assist in targeting prevention messages.
The objectives of this study were to use
data from a national agricultural injury
surveillance program in Canada to examine
the activities and circumstances associated
with fatal agricultural-related rollover injuries
and to describe who sustained these injuries.
Methods
Study population and data collection
Ethics approval was provided by Queen’s
University Health Sciences Research Ethics
Board.
The study population included all people who
died as a result of a vehicle or machine rollover on a Canadian farm or ranch between
January 1, 1990, and December 31, 2005.
Cases were identified by the Canadian
Agricultural Injury Surveillance Program
(CAISP).1 Briefly, CAISP identified accidental
Author references
1. Clinical Research Centre, Kingston General Hospital, Kingston, Ontario, Canada
2. Department of Community Health and Epidemiology, Queen’s University, Kingston, Ontario, Canada
3. Department of Emergency Medicine, Queen’s University, Kingston, Ontario, Canada
Correspondence: Robert Brison, Kingston General Hospital, 76 Stuart Street, Kingston ON K7L 2V7. Tel.: (613) 548-2389; Fax: (613) 548-1381; Email: [email protected]
Vol 31, No 3, June 2011 – Chronic Diseases and Injuries in Canada
97
agriculture-related injury fatalities in databases maintained by offices of provincial
coroners or chief medical examiners in the
ten Canadian provinces. Each coroner’s file
is abstracted on-site by CAISP provincial
collaborators using a standardized template.1
Fatal rollover information was not available
from the province of Quebec for 2004 and
2005. CAISP also identifies hospitalized cases
of agricultural injury;4 however, as the focus
of our analysis was on patterns associated
with fatal injuries only, these data were
not considered here.
Injury definition
We reviewed documentation on fatal agriculture-related injuries and coded those caused
by rollovers. We defined a backwards rollover
as one where the vehicle or machine turns
over backwards with its front tires rotating
around its rear axle by 90° to 180° and a
sideways rollover as one where a vehicle or
machine turns onto its side. Incidents that did
not have sufficient documentation to determine whether the rollover was backwards
or sideways were deemed unspecified.
Data analysis
We counted the number of backwards and
sideways rollovers described in CAISP for
the time period 1990 to 2005. We profiled
sideways and backwards rollovers by age
and sex of the victims, type of machine,
agricultural season, location of the injury
event, type of activity prior to rollover, and
most probable cause of rollover. Overall
and age-specific annual rates of fatal injury
were calculated per 100 000 farms and then
per 100 000 people using population estimates
from the 1996 Canada Census of Agriculture
as the denominator.10 All analyses were
performed using SAS software (version 9.2,
SAS Institute Inc., Cary, NC, United States).
Results
Number of rollovers
Of the 1766 agriculture-related fatalities
identified between 1990 and 2005, 360
(20.4%) were due to rollovers. Of these, 221
(61.4%) were sideways rollovers, 107 (29.7%)
were backwards rollovers, and 32 (8.9%) were
unspecified (Table 1). The overall number
of rollovers decreased significantly from a
high of 31 in 1990 to a low of 9 in 2005
TABLE 1
Number of fatal agriculture-related rollovers by type of rollover, personal
characteristics of the victim and rollover circumstance
Number of rollovers,
n
Sideways
(n = 221)
Backwards
(n = 107)
4
3
Age of victim, years
0–9
10–19
29
5
20–29
13
10
30–39
21
7
40–49
28
15
50–59
35
15
60–69
46
25
70–79
28
22
80+
17
5
207
103
14
4
Sex of victim
Male
Female
Agricultural season
126
47
Planting, April–June
46
39
Winter, Nov–March
49
19
0
2
189
97
Harvest, July–Oct
Unknown
Machine type
Tractor
Off-road vehicle
11
8
Construction equipment
6
2
Motor vehicle
6
0
Other
9
0
Field
44
44
Public road
71
6
Farm road
39
10
Woodlot
14
32
Water source
Location of injury event
24
3
Farmyard
7
4
Driveway
10
0
Farm building
5
3
Other
4
3
Unknown
3
2
Notes: Bolding highlights the most prevalent patterns of risk.
(p = .004), with considerable variability
in the annual occurrence of both sideways
and backwards rollovers. (Note: The observed
decline should be interpreted cautiously
due to the lack of fatality records from
Quebec for 2004–2005). Though counts
98
of rollover events varied over the study
period, a descending trend in numbers
of sideways rollovers was statistically
significant (p = .01) while a descending
trend in numbers of backwards rollovers
was less clear (p = .08) (Figure 1).
Vol 31, No 3, June 2011 – Chronic Diseases and Injuries in Canada
FIGURE 1
Number of fatal agriculture-related sideways and backwards rollovers by year with trend lines
25
Sideways
Backwards
20
Number
15
10
5
4
20
0
20
02
0
20
0
98
19
96
19
94
19
92
19
19
90
0
Year
Slopes for regression lines: - 0.6 deaths per year (sideways rollovers)
- 0.3 deaths per year (backwards rollovers)
Injury circumstances
Rates of fatal rollover injuries
That older age groups experienced large
number of rollover injury events is consistent
with the known demographic distribution
of farmers in Canada.10 The highest number
of fatal sideways rollovers occurred in
people aged 50 to 69 years, and the highest
number of backwards rollovers in those
aged 60 to 79 years (Table 1). Fatal rollovers
occurred most often among men and boys,
with the majority occurring during the
harvest season, and on tractors, irrespective of the type of rollover. The next most
common machine type for both sideways
and backwards rollovers was the off-road
vehicle (n = 19); of these, 8 (42.1%) were
reported for children aged 16 years and
less. Available injury narratives suggest that
almost all of these children were engaged
in recreational rather than work-related
activities at the time of the accident. Sideways
rollovers were most likely to occur on fields
or public roads while backwards rollovers
were most likely to occur in a field or a
woodlot (woods, forest or orchard).
We estimated annual rates of fatal rollover
injury per 100 000 farm operations at 9.1
for total fatal rollovers, 5.6 for sideways
rollovers and 2.7 for backwards rollovers.
Annual rates of fatal rollover injury per
100 000 farm population were 2.4 for total
fatal rollovers, 1.6 for sideways rollovers
and 0.8 for backwards rollovers. Annual
age-specific rates of rollover injury generally
increased with age for both sideways roll­
overs (minimum 0.2 per 100 000 for ages
0–9; maximum 13.7 per 100 000 for ages
80+) and backwards rollovers (minimum
0.2 per 100 000 for ages 0–9; maximum 4.5
per 100 000 for ages 70–79).
Activities and contributing factors
The most common activities contributing
to sideways rollovers were transportation
(particularly on public roadways) and field
work. For backwards rollovers, the most
common activities were forestry, field work
and towing or extraction (Table 2). Factors
contributing to the occurrence of sideways
rollovers were (1) driving too close to the
edge of a ditch or an embankment and (2)
Vol 31, No 3, June 2011 – Chronic Diseases and Injuries in Canada
99
driving on an incline. Most backwards rollovers were associated with (1) attempting to
free stuck machines with a tractor or towing machines; (2) driving on an incline or
dragging logs or implements; and (3) pulling stumps or trees.
Discussion
Our study describes a number of clear
patterns of injury associated with fatal
rollover injuries on Canadian farms.
We found that men are much more
frequently involved in a fatal rollover.
Locker et al. reported an age-standardized
rate ratio for males to females of 11.8 to 1
for rollovers that resulted in hospitalization or death.11 Similar patterns are found
in other types of agriculture-related
injuries.2,11-12 Adults aged 50 to 79 years
account for the highest number of sideways
and backwards rollover fatalities. This is
consistent with US-based reports by Myers
et al. who found that the risk of rollover
fatality increases with age, with people
aged 75 years and older having approximately 6.5 times the rate of death compared
TABLE 2
Activity and factors contributing to fatal agriculture-related rollover events
Number of rollovers
Sideways
(n = 221)
Backwards
(n = 107)
Activity at time of event
123
8
Field work
38
23
Forestry
14
39
Transportation
7
23
Working in farm yard
12
9
Mowing
12
0
Recreation
5
2
Road Maintenance
4
1
Unknown
6
2
104
12
Towing (extraction)
Factors contributing to rollover event
Driving too close to edge of a ditch or embankment
62
19
Towing (extraction)
7
23
Dragging logs/implements
4
19
Pulling stumps/trees
0
14
Rough terrain
5
7
Fall from ramp
7
1
Collision with object
6
2
Cornering
6
1
Carrying heavy load in bucket
6
1
Pulling heavy machine/trailer
4
3
Tractor arms/bucket caught in ground
2
0
Unknown
8
5
Driving on an incline
Notes: Bolding highlights the patterns of risk that are most prevalent.
to people aged 25 to 34 years.13 The tendency
for farmers to work past the normal age
of retirement is recognized, and is associated with an increased risk for injury.14-17
Because tractors are built to last, many
older operators use tractors that were made
before manufacturers routinely installed
ROPS, thereby increasing their likelihood
of fatality during a rollover.18-21
The most common cause of sideways rollovers is as a result of driving too close to
the edge of a steep slope, usually a ditch
by a public roadway or a field, and this
usually occurs during transportation or field
work. Rissanen and Taattola found that
another common cause is driving across an
incline in such a way that the machine goes
beyond its stability baseline and overturns.12
Driving up an incline is also a common cause.
Backwards rollovers usually occur in circumstances that use the same mechanism:
towing or extraction of machines, dragging
logs or implements, and pulling stumps or
trees in a field or woodlot. Rissanen and
Taattola reported that backwards rollovers
generally occur when towing another tractor,12
while our data suggest that towing, dragging
or pulling any object is the more likely
cause. Improper hitching, where the hitch
is mounted above the level of the rear axle,
is a frequent cause of backwards rollovers;
approximately 60% of the 16 reported
backwards rollovers on tractors in New York
from 1991 to 1995 involved improper hitching.7
Reports on rollovers often discuss the
use of ROPS on tractors as a means of
reducing the severity of injury. Because of the
extremely low probability of death due to
100
rollover on ROPS-equipped tractors,6-8 it is
likely that very few of the tractors in our
study (88% of all fatal agriculture-related
rollover injuries in Canada occurred on
tractors) used ROPS as a secondary
prevention strategy. The use of ROPS and
a seat belt is estimated “to be 99% effective
in preventing death or serious injury in the
event of a tractor rollover.”22 US data shows
significant increases in the use of ROPS
between 1993 and 2004, from 38% to 51%.18,23
As Canadian agricultural machinery practices typically mirror those observed
in the US, the observed decrease in fatal
rollovers over our study period is almost
certainly attributable to increased use
of ROPS in Canadian agriculture settings.
The observed decrease in fatalities also
demonstrates the merits of engineered
passive injury prevention strategies that
require no change in behaviour on the
part of the operator. Passive strategies are
effective, and their utility is not specific
to any particular demographic group defined
by age, gender or geography. Our study
findings point out a clear need for programs
and policies that encourage the universal
application of passive safety innovations
in order to protect farm machinery operators
from harm. In addition to the universal use
of ROPS and seatbelts,22 these might include
design innovations that (1) signal the operator when a machine is being operated at a
dangerous angle or (2) make the practice
of high hitching inconvenient if not impossible. Organizations involved in the development and promotion of such innovations are
many; they include national safety associations (e.g. the Canadian Agricultural Safety
Association), federal and provincial/territorial government departments and ministries
(e.g. agriculture, labour, and the workers’
safety and insurance boards), agricultural
machinery manufacturers and institutions,
health and safety coalitions, and coroners
and medical examiners.
In conjunction with secondary injury
prevention strategies such as ROPS, primary
prevention programs (less efficacious than
secondary prevention strategies) should focus
on the most common causes of rollovers
and educate operators about known operational hazards: side slopes and roadway
ditches, especially during seasons where
Vol 31, No 3, June 2011 – Chronic Diseases and Injuries in Canada
these are soft; steep inclines; dragging logs
or implements; towing machines or extracting
stumps or logs or machines stuck in fields.
The number of fatal rollover injuries we
observed among children aged less than 10
years point to a need for different primary
prevention strategies. Foremost of these
is the need to limit young children’s access
to known occupational hazards on the farm,
as described in a large existing case series.24
Young children typically do not possess the
developmental abilities to recognize and
react to dangerous occupational situations
in an appropriate manner.25 It is also
challenging for adults engaged in agricultural
work to simultaneously supervise young
children in the attentive, proximal and
continuous manner that may be necessary
to protect them from harm.25 The only truly
effective solution for these rollover deaths
is to prohibit young children from the
agricultural worksite, including being on
or in the vicinity of agricultural machinery.
Strengths and limitations
Our study was unique in that it examined
the circumstances of rollovers in detail
by mechanism. We made use of a robust
dataset of national fatality data to describe
patterns that are representative of agricultural
rollover injuries in Canada. Our study also
had its limitations. First, our analyses were
restricted by the circumstance information
recorded by the provincial abstractors, who
in turn were limited by the information
recorded on coroners’ investigation reports,
police reports, and occupational safety and
health agency investigation reports. We were
particularly limited in the information about
the victim and the rollover circumstances
such as whether the victim was a full-time
or part-time worker, the type of farm production where the injury occurred, and
whether safety equipment (ROPS or seatbelts) was on the machine and/or in use.
Second, as fatality information was not
available from Quebec in 2004–05, counts of
fatalities for these later years of surveillance
represent slight underestimates of expected
national totals. The observed decline in the
occurrence of rollover fatalities from 1990
to 2005 should also be interpreted with
caution, although the patterns of injury are
most likely to be representative.
Summary
Machine rollovers are one of the most
common, yet preventable, causes of fatal
agricultural injury in Canada. Our study
identified the groups most at risk for sideways
and backwards rollovers, and we documented the most common circumstances
that led to these rollovers. By adhering to
recommendations on ROPS and through
understanding the circumstances in which
these events most often occur, a substantial
number of rollover fatalities could be avoided.
5.Hathaway LR, Riney LA, editors.
Fundamentals of machine operation:
agricultural safety. Moline (IL): Deere &
Company Service Training; 1987.
6.
Centers for Disease Control and Prevention.
Public health focus: effectiveness of rollover
protective structures for preventing injuries associated with agricultural tractors.
MMWR. 1993;42:57-9.
7.
Centers for Disease Control and Prevention.
Fatalities associated with improper hitching
to farm tractors—New York, 1991-1995.
MMWR. 1996; 45:307-11.
8.
Springfeldt B, Thorson J, Lee BC. Sweden’s
thirty-year experience with tractor rollovers.
J Agric Saf Health. 1998;4:173-80.
Acknowledgements
This work was funded by the Canadian
Agricultural Safety Association.
The Canadian Agricultural Injury Surveillance
Program (CAISP) was initiated in 1995.
Collaborators representing each of Canada’s
ten provinces have been integral to the data
collection activities that formed the basis
of the data presented here. As of 2010, CAISP
has a new name: the Canadian Agricultural
Injury Reporting program (CAIR). It is now
managed by the Alberta Centre for Injury
Control and Research. CAIR is funded and
supported by a grant from the Canadian
Agricultural Safety Association, and Agriculture
and Agri-Food Canada. These groups were
not involved in the study design, data
collection, analysis, interpretation of data,
or the writing of and decision to submit
the paper for publication.
References
1.
Pickett W, Hartling L, Brison RJ, Guernsey JR.
Fatal work-related farm injuries in Canada,
1991-1995. Canadian Agricultural Injury
Surveillance Program. CMAJ. 1999;160:1843-8.
2. Franklin RC, Mitchell RJ, Driscoll TR,
Fragar LJ. Agricultural work-related fatalities in Australia, 1989-1992. J Agric Saf
Health. 2001;7:213-27.
3.
Hard DL, Myers JR, Gerberich SG. Traumatic
injuries in agriculture. J Agric Saf Health.
2002;8:51-65.
4. Pickett W, Hartling L, Dimich-Ward H,
Guernsey JR, Hagel L, Voaklander DC, et al.
Surveillance of hospitalized farm injuries
in Canada. Inj Prev. 2001;7:123-28.
Vol 31, No 3, June 2011 – Chronic Diseases and Injuries in Canada
101
9. Conroy C, Fowler J. The Haddon matrix:
applying an epidemiologic research tool
as a framework for death investigation.
Am J Forensic Med Pathol. 2000;21:339-42.
10. Statistics Canada. 2006 Census of agriculture
[Internet]. Ottawa (ON): Statistics Canada;
[modified 2009 Oct 5; accessed 2010 Dec
30]. Available from: http://www.statcan
.gc.ca/ca-ra2006/index-eng.htm
11. Locker AR, Pickett W, Hartling L, Dorland JL.
Agricultural machinery injuries in Ontario,
1985-1996: a comparison of males and
females. J Agric Saf Health. 2002;8:215-23.
12. Rissanen P, Taattola K. Fatal injuries in
Finnish agriculture, 1988-2000. J Agric Saf
Health. 2003; 9:319-26.
13. Myers JR, Hendricks KJ. Agricultural tractor
overturn deaths: assessment of trends and
risk factors. Am J Ind Med. 2009;53:662-72.
14. Horsburgh S, Feyer A-M, Langley JD.
Fatal work related injuries in agricultural
production and services to agriculture
sectors of New Zealand, 1985-94. Occup
Environ Med. 2001; 58:489-95.
15. Myers JR, Hard DL. Work-related fatalities
in the agricultural production and services
sectors, 1980-1989. Am J Ind Med.
1995;27:51-63.
16. Soloman C. Accidental injuries in agriculture
in the UK. Occup Med. 2002; 52:461-6.
17. Voaklander DC, Hartling L, Pickett W,
Dimich-Ward H, Brison RJ. Work-related
mortality among older farmers in Canada.
Can Fam Physician. 1999; 45:2903-10.
18. Loringer KA, Myers JR. Tracking the
prevalence of rollover protective structures
on U.S. farm tractors: 1993, 2001, and
2004. J Safety Res. 2008;39:509-17.
19. May JJ, Sorensen JA, Burdick PA, EarleRichardson GB, Jenkins PL. Rollover
protection on New York tractors and
farmers’ readiness for change. J Agric Saf
Health. 2006;12:199-213.
20. Sanderson WT, Madsen MD, Rautiainen R,
Kelly KM, Zwerling C, Taylor CD, et al.
Tractor overturn concerns in Iowa: perspectives from the Keokuk county rural health
study. J Agric Saf Health. 2006;12:71-81.
21. Wilkins JR III, Engelhardt HL, Bean TL,
Byers MV, Crawford JM. Prevalence
of ROPS-equipped tractors and farm/
farmer characteristics. J Agric Saf Health.
2003;9:107-18.
22. Murphy DJ, Buckmaster DR. Rollover
protection for farm tractor operators
[Internet]. Pennsylvania State University (PA):
Agricultural and Biological Engineering;
2003 [cited 2010 Dec 14.] Available from:
http://www.abe.psu.edu/extension/
factsheets/e/E42.pdf
23. Myers JR, Snyder K. Roll-over protective
structure use and cost of retrofitting tractors
in the United States, 1993. J Agric Saf
Health. 1995;1:185-97.
24. Brison RJ, Pickett W, Berg R, Linneman J,
Zentner J, Marlenga B. Fatal agricultural
injuries in preschool children: risks, injury
patterns and strategies for prevention.
CMAJ. 2006;174:1723-6.
25.Morrongiello B, Pickett W, Berg R,
Linneman J, Brison RJ, Marlenga BL. Adult
supervision and pediatric injuries in the
agricultural worksite. Accid Anal Prev.
2008; 40:1149-56
102
Vol 31, No 3, June 2011 – Chronic Diseases and Injuries in Canada
Estimating gestational age at birth: a population-based
derivation-validation study
M. L. Urquia, PhD (1,2); T. A. Stukel, PhD (2,3); K. Fung, MSc (2); R. H. Glazier, MD (1,2,3,4,5); J. G. Ray, MD (2,3,6)
Abstract
Introduction: Information on newborn gestational age (GA) is essential in research
on perinatal and infant health, but it is not always available from administrative databases.
We developed and validated a GA prediction model for singleton births for use in
epidemiological studies.
Methods: Derivation of estimated GA was calculated based on 130 328 newborn infants
born in Ontario hospitals between 2007 and 2009, using linear regression analysis, with
several infant and maternal characteristics as the predictor (independent) variables.
The model was validated in a separate sample of 130 329 newborns.
Results: The discriminative ability of the linear model based on infant birth weight
and sex was reasonably approximate for infants born before the 37th week of gestation
(r2 = 0.67; 95% CI: 0.65–0.68), but not for term births (37–42 weeks; r2 = 0.12; 95%
CI: 0.12–0.13). Adding other infant and maternal characteristics did not improve the
model discrimination.
Conclusion: Newborn gestational age before 37 weeks can be reasonably approximated
using locally available data on birth weight and sex.
Keywords:gestational age, birth, neonate, infant health, derivation, validation,
prediction, administrative datasets, Ontario
Introduction
Gestation starts on the day of conception
and ends at birth, but it is typically measured
from the first day of the last menstrual
period. Gestational age (GA) is a major
predictor of perinatal mortality and morbidity;1 it is important for dating for prenatal
genetic screening2 and for the timing of fetal
exposure to teratogens.3,4 It is also needed
to correctly determine if an infant is small
or large for GA, both for clinical practice
and epidemiological research.2
In countries where antenatal maternal care
is scarce, the collection of basic newborn
statistics may be hampered by a lack
of information on GA. On the other hand,
in industrialized nations, GA is often not
recorded in administrative health databases.3-5 Since all permanent residents
of Canada receive universal health care,
including prenatal, peripartum and newborn
care, the Discharge Abstract Database of the
Canadian Institute of Health Information
(CIHI-DAD), an administrative database,
has been recognized as an excellent
source for population-based estimates for
perinatal research;6,7 however, prior to fiscal
year 2002/03, CIHI-DAD did not collect
data on GA at birth in Ontario,8 which
could pose problems for some perinatal
outcomes research.
The aim of this study is to develop and
validate a GA prediction model for singleton
births for use in epidemiological studies.
Methods
General design
We used a derivation-validation analytical
method to estimate GA based on commonly
available perinatal data. We completed
a large population-based study of all singleton
infants born in Ontario hospitals in 2007/08
and 2008/09, the period during which GA
at birth was fully recorded by CIHI-DAD.
The derivation cohort consisted of a randomly selected sample of 50% of all live
births in this same period. This cohort was
used to generate a predictive model based
on infant characteristics. The other 50%
of births formed the validation cohort, to
test the derivation model’s prediction of
GA at birth. Simulation studies have shown
that split-sample validation is a reasonable
approach when the overall sample size is
very large, as in our study (N = 260 657).9
We excluded all stillbirths and multiple
births from our sample. To minimize the
influence of potential data errors and outliers,
we also excluded infants born at or less
than 23 completed weeks gestation or at
or more than 43 completed weeks gestation;
those with clinically implausible combinations of birth weight and GA;10 those who
Author references
1. Centre for Research on Inner City Health, The Keenan Research Centre of the Li Ka Shing Knowledge Institute, St. Michael’s Hospital, Toronto, Ontario, Canada
2. Institute for Clinical Evaluative Sciences, Toronto, Ontario, Canada
3. Department of Health Policy Management and Evaluation, University of Toronto, Toronto, Ontario, Canada
4. Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
5. Department of Family and Community Medicine, University of Toronto, Toronto, Ontario, Canada.
6. Department of Obstetrics and Gynecology, University of Toronto, Toronto, Ontario, Canada
Correspondence: Marcelo Luis Urquia, Centre for Research on Inner City Health, The Keenan Research Centre of the Li Ka Shing Knowledge Institute, St. Michael’s Hospital,
30 Bond Street, Toronto ON M5B 1W8; Tel.: (416) 864 6060 x 77340; Fax: (416) 864 5558; Email: [email protected]
Vol 31, No 3, June 2011 – Chronic Diseases and Injuries in Canada
103
stayed in hospital for more than 90 days;
those whose GA, birth weight or sex was
not recorded; those born to mothers aged
less than 16 years or over 50 years at the
time of delivery; and extreme outliers of the
birth weight distribution identified as values
located outside the inter-quartile range
exceeding two times its distance.11
Variables
In Ontario, GA is largely estimated by early
ultrasound dating. Since 2002, hospital
medical records departments have recorded
GA based on the attending physician’s best
interpretation of all clinical data, usually
presented on the antenatal record.12,13 This,
along with the infant’s sex and precisely
measured birth weight, is recorded in the
CIHI-DAD.14 We determined congenital
anomalies and diseases of prematurity from
the ICD-10-CA* codes15 entered in the 25 diagnostic fields in the hospital records (Table 1).
Analysis
Derivation of the estimate of GA involved
two steps.16 Using the derivation cohort,
we performed a series of linear regression
analyses with completed GA (in weeks)
as the dependent variable and several
independent variables, chosen a priori, as
listed in Table 2.
We first modelled GA using a restricted
cubic spline function of birth weight with
four degrees of freedom.17 We added infant
sex, congenital and chromosomal anomalies
and the diseases of prematurity (respiratory
distress syndrome, neonatal cerebral leukomalacia or intraventricular hemorrhage,
retinopathy of prematurity, necrotizing
enterocolitis) to the basic model. The details
of these variables are listed in Table 2.
We generated prediction models by multiplying the coefficients with each independent
variable in the derivation models by the
specific values that make up the profile of
each individual in the validation cohort.
We tested each prediction model using the
validation cohort’s true GA as the dependent
variable and estimated GA as the independent variable, rounded to the nearest
completed week. As a measure of model
discrimination, we computed the coefficient
of determination (r2) and its 95% confidence
interval (CI). Models were validated for
the entire birth cohort, and stratified by
infant sex and by timing of birth (less than
37 weeks GA and equal or more than 37
weeks GA). The true versus estimated GA
was plotted according to their respective
frequency distributions (Figure 1).
We plotted the true positive rate of the
derived model (i.e. the proportion of infants
whose true GA is equal to the derived GA,
is within 1 week of derived GA, or is within
2 weeks of derived GA) on a y-axis against
the estimated GA on the x-axis (Figure 2).
All analyses were conducted using SAS version 9.1 (SAS Institute Inc., Cary, NC, US).
Results
There were 281 406 infant records in 2007/08
and 2008/09. After excluding stillbirths
and multiple births and obvious outliers
(7.4%), the final available dataset consisted
of 260 657 singletons. Infant characteristics
in both the derivation and validation cohorts
were similar (Table 2).
The optimal model included a restricted cubic
spline function of birth weight (in kilogram)
as well as infant sex. The coefficient of determination (r2) for this predictive model was
0.44 (95% CI: 0.43–0.45). Adding any congenital or chromosomal anomaly or diseases
of prematurity, or stratifying by infant sex
to the above model did not appreciably affect
the coefficient of determination (Table 3).
Stratifying by timing of birth, the discriminative ability of the model was poor for
infants delivered at term (37–42 weeks:
r2 = 0.12; 95% CI = 0.12–0.13), but much
better for preterm births (24–36 weeks:
r2 = 0.67; 95% CI = 0.65–0.68) (Table 3).
Adding admission to a neonatal intensive care
unit, infant hospital length of stay, maternal
preeclampsia or gestational hypertension and
mode of delivery to the pre-term model
did not further improve the coefficient of
determination (data not shown).
Up to about 36 weeks gestation, there
was high concordance in the distribution
curves for true versus derived GA, after
which there was marked discordance
(Figure 1). At term, predicted GA does not
estimate the true GA well, especially at 39
weeks, when most infants are born (Figure 1).
The GA model that included infant birth
weight and sex had a positive predictive value
of 34% at 28 ± 1 weeks, 67% at 28 ± 2
weeks, 47% at 32 ± 1 weeks, 74% at 32 ± 2
weeks, 60% at 37 ± 1 weeks and 85% at 37
± 2 weeks gestation (Figure 2).
We repeated the validation using the entire
dataset instead of the validation dataset and
the results did not change (data not shown).
Discussion
In a large population-based derivation-validation study, infant birth weight and sex
together provided a reasonable estimate of
GA among infants born before 37 weeks,
but not among term infants.
The addition of other newborn and maternal
characteristics did not improve the coefficient
of determination of our model among preterm
infants. Others have noted similar results
in the development of newborn birth
weight curves.18
A parsimonious model based on infant
birth weight and sex has some advantages
in that both variables are captured and
recorded in nearly all clinical encounters
within both poorer and wealthier nations
and also within large administrative datasets
in which GA is not available. It is noteworthy
that infant birth weight and sex are the
two main variables used for the construction of population-based references of birth
weight for GA.10,19,20 Therefore, in the absence
of recorded GA, we recommend using
information on infant birth weight and sex
to approximate GA, and figures from local
birth weight for GA charts, including the
observed sex-specific 50th percentile of birth
weight at each week of GA. Lower (5th, 10th)
and upper (90th, 95th) percentiles of birth
* International Statistical Classification of Diseases and Related Health Problems, 10th Revision, Canadian Enhancement
104
Vol 31, No 3, June 2011 – Chronic Diseases and Injuries in Canada
TABLE 1
ICD-10-CA codes used to determine congenital anomalies, diseases of prematurity,
multiple births and stillbirths among singleton live-born newborns, Ontario, 2007–09
Variable
CIHI-DAD
record source
ICD-10-CA
Any congenital or chromosomal anomaly
Infant
Q00-Q99
Diseases of prematurity
Infant
Necrotizing enterocolitis
P77
Respiratory distress syndrome
P22
Neonatal cerebral leukomalacia
P91.2, P52
or intraventricular hemorrhage
Retinopathy of prematurity
H35.1
Multiple gestation
Infant
Q89.4, Z38.3-Z38.8
Multiple gestation
Maternal
O30, O31,
Z37.2-Z37.7,
Z38.3-Z38.8, Z37.9.0
Intrauterine death
Infant
P95
Intrauterine death
Maternal
O36.4, Z37.1, Z37.4,
Z37.7
Abbreviations: CIHI-DAD, Discharge Abstract Database of the Canadian Institute of Health Information; ICD-10-CA,
International Statistical Classification of Diseases and Related Health Problems, 10th Revision, Canadian Enhancement.
TABLE 2
Characteristics of singleton live-born newborns in the derivation cohort (n = 130 328)
and validation cohort (n = 130 329), Ontario, 2007–09
Infant characteristics
Male
Derivation cohort,
n (%)
Validation cohort,
n (%)
66 551 (51.06)
66 898 (51.33)
122 723 (94.16)a
122 760 (94.19)b
7 605 (5.84)
7 569 (5.81)
Gestational age at birth
Term, 37–42 weeks
Preterm, 24–36 weeks
Very preterm, 24–27 weeks
187 (0.14)
206 (0.16)
3 392 ± 531
3 392 ± 532
< 2500 grams
5 715 (4.39)
5 797 (4.45)
≥ 2500 grams
Mean birth weight ± SD, grams
Birth weightc
124 613 (95.61)
124 532 (95.55)
Congenital or chromosomal anomaliesd
5 655 (4.34)
5 677 (4.36)
Diseases of prematurityd,e
7 587 (5.82)
7 771 (5.96)
7 474 (5.73)
7 681 (5.89)
206 (0.16)
207 (0.16)
111 (0.09)
112 (0.09)
62 (0.05)
62 (0.05)
Respiratory distress syndrome
Neonatal cerebral leukomalacia or
intraventricular hemorrhage
Retinopathy of prematurity
Necrotizing enterocolitis
Abbreviations: ICD-10-CA, International Statistical Classification of Diseases and Related Health Problems, 10th Revision,
Canadian Enhancement; n, sample size; SD, standard deviation.
The mean gestational age (± SD) at birth in this group was 39.2 (± 1.14) weeks.
a
The mean gestational age (± SD) at birth in this group was 39.2 (± 1.15) weeks.
b
The mean birth weight (± SD) was 3392 (± 531) grams for the derivation cohort and 3392 (± 532) grams for the validation cohort.
c
Congenital or chromosomal anomalies and diseases or prematurity determined from ICD-10-CA codes in hospital records.
d
Many newborns may have more than one disease of prematurity. Hence the percentages do not add up to 100.
e
Vol 31, No 3, June 2011 – Chronic Diseases and Injuries in Canada
105
weight could also be used to express biological
variability in GA at a given birth weight.
The finding that GA and birth weight are
poorly correlated after 36 weeks gestation is
noteworthy given that about 94% of singleton infants are born at term. The poor
prediction of GA at term is basically due to
the large variability in birth weight as GA
increases. For example, a recent Canadian
birth weight chart for male newborns
showed a minimum 1100-gram difference
between the 10th and the 90th percentiles of
birth weight at 37 to 41 weeks gestation.20
The latter reflects a large amount of variability in birth weight within the “normal”
range of birth weight. The better prediction
of GA at earlier gestational periods is reflective
of less biological variability. In addition,
the birth weight slope is more linear and
steeper at lower GAs than at term.20
Limitations
This study has a number of limitations.
First, we relied on ICD-10-CA codes within
an administrative database in which infant
measurements were not performed for the
purpose of this study. Second, we only
included singleton live-born infants, so our
approach may not apply to multiple pregnancies. Unfortunately, population-based
birth weight curves for multiple births are
scarce.21,22 Third, the database did not contain
information on other factors associated
with length of gestation and newborn
weight, such as parental ethnicity, maternal
anthropometry and health behaviours during
pregnancy, each of which may be used in
the construction of customised newborn
weight charts.23,24 Inclusion of these factors
might improve our prediction model.25,26
Fourth, we based our analyses on the clinical
estimate of GA (typically based on early
ultrasound dating), which is known to
differ from the estimate based on the date
of last menstrual period.12,13 The latter has
been found to overestimate preterm and
postterm birth rates and present bimodal
birth weight distributions between 28 and
34 weeks of gestation.20,25,27-29 Replication of
our validation approach using the menstrual
estimate of gestation as the “gold standard”
may likely lead to poorer prediction.
Finally, we caution others that our models
were not designed to specifically estimate
the GA of individual newborns.
FIGURE 1
Comparison of the predicted gestational age based on infant birth weight and sex (solid line) versus the true gestational
age at birth (dashed line), validation data (n = 130 329)
70
60
Percent
50
40
30
20
10
0
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
Gestational age (weeks)
FIGURE 2
Agreement between derived gestational age and true gestational age among singleton live births in Ontario, 2007/08 to 2008/09.
The curves represent the percentage of infants whose true gestational age is equal to the derived gestational age (lower),
or is within ±1 week (middle) and ± 2 weeks (upper)
100
90
80
+/- 2 weeks
Percent agreement
70
60
+/- 1 week
50
40
30
20
Same week
10
0
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
Derived gestational age (weeks)
106
Vol 31, No 3, June 2011 – Chronic Diseases and Injuries in Canada
TABLE 3
Discriminative ability of a model generated from the derivation cohort to predict
known gestational age at birth in the validation cohorta
Group
All (n = 130 329)
Coefficient of
determination, r2
(95% CI)b
Model variables
Birth weight and sex
0.44 (0.43–0.45)
Birth weight, sex, congenital or chromosomal
anomalies, and diseases of prematurityc
0.45 (0.44–0.46)
Birth weight
0.46 (0.44–0.47)
Birth weight, congenital or chromosomal
anomalies, and diseases of prematurityc
0.47 (0.45–0.48)
Birth weight
0.43 (0.41–0.44)
Birth weight, congenital or chromosomal
anomalies, and diseases of prematurityc
0.44 (0.42–0.45)
Birth weight and sex
0.12 (0.12–0.13)
Birth weight, sex, congenital or chromosomal
anomalies, and diseases of prematurityc
0.13 (0.12–0.13)
Birth weight and sex
0.67 (0.65–0.68)
Birth weight, sex, congenital or chromosomal
anomalies, and diseases of prematurityc
0.68 (0.67–0.70)
Sex
Males (n = 66 898)
Females (n = 63 431)
Timing at birth
Term, 37–42 weeks
(n = 122 760)
Preterm, 24–36 weeks
(n = 7569)
Abbreviations: ICD-10-CA, International Statistical Classification of Diseases and Related Health Problems, 10th Revision,
Canadian Enhancement; n, sample size.
a
Cohorts are singleton infants live born in Ontario in 2007/08–2008/09.
b
Birth weight is modeled as a restricted cubic spline with 4 degrees of freedom.
Respiratory distress syndrome, neonatal cerebral leukomalacia or periventricular hemorrhage, retinopathy of prematurity,
necrotizing enterocolitis based on ICD-10-CA codes.
4. Hardy JR, Leaderer BP, Holford TR,
Hall GC, Bracken MB. Safety of medications prescribed before and during early
pregnancy in a cohort of 81,975 mothers
from the UK General Practice Research
Database. Pharmacoepidemiol Drug Saf.
2006;15(8):555-64.
5. Toh S, Mitchell AA, Werler MM,
Hernandez-Diaz S. Sensitivity and specificity of computerized algorithms to classify gestational periods in the absence of
information on date of conception. Am J
Epidemiol. 2008;167(6):633-40.
6. Joseph KS, Fahey J; Canadian Perinatal
Surveillance System. Validation of perinatal
data in the Discharge Abstract Database of
the Canadian Institute for Health Information.
Chronic Dis Can. 2009;29(3):96-100.
7.
Wen SW, Liu S, Marcoux S, Fowler D. Uses
and limitations of routine hospital admission/
separation records for perinatal surveillance.
Chronic Dis Can. 1997;18(3):113-9.
8.
Canadian Institute for Health Information.
Data quality documentation: Discharge
Abstract Database 2002–2003. Ottawa
(ON): CIHI; 2005.
9.
Steyerberg EW, Harrell FE Jr, Borsboom GJ,
Eijkemans MJ, Vergouwe Y, Habbema JD.
Internal validation of predictive models:
efficiency of some procedures for logistic
regression analysis. J Clin Epidemiol.
2001;54(8):774-81.
c
In conclusion, in the absence of information
on actual GA, newborn GA can be reasonably
approximated at the population level as a
continuous variable up to 36 weeks gestation using birth weight and sex, although
substantial uncertainty seems unavoidable,
even after considering other predictors of GA.
Acknowledgements
This study was supported by the Institute
for Clinical Evaluative Sciences (ICES),
which is funded by an annual grant from
the Ontario Ministry of Health and LongTerm Care (MOHLTC). The positions, results
and conclusions reported in this paper are
those of the authors and are independent
from the funding sources. No endorsement by ICES or the Ontario MOHLTC
is intended and nor should it be inferred.
References
1. Cheng YW, Nicholson JM, Nakagawa S,
Bruckner TA, Washington AE, Caughey
AB. Perinatal outcomes in low-risk term
pregnancies: do they differ by week of
gestation? Am J Obstet Gynecol. 2008;
199(4):370-7.
2.
3.
Behrman RE, Butler AS, editors; Committee
on Understanding Premature Birth and
Assuring Healthy Outcomes. Preterm birth:
causes, consequences, and prevention. 1st
ed. Washington (DC): National Academies
Press; 2007.
Andrade SE, Raebel MA, Morse AN, Davis
RL, Chan KA, Finkelstein JA, et al. Use of
prescription medications with a potential
for fetal harm among pregnant women.
Pharmacoepidemiol Drug Saf. 2006;
15(8):546-54.
Vol 31, No 3, June 2011 – Chronic Diseases and Injuries in Canada
107
10. Alexander GR, Himes JH, Kaufman RB,
Mor J, Kogan M. A United States national
reference for fetal growth. Obstet Gynecol.
1996;87(2):163-8.
11.Tukey JW. Exploratory data analysis.
Reading (MA): Addison-Wesley; 1977.
12. Wingate MS, Alexander GR, Buekens P,
Vahratian A. Comparison of gestational
age classifications: date of last menstrual
period vs. clinical estimate. Ann Epidemiol.
2007;17(6):425-30.
13. Qin C, Hsia J, Berg CJ. Variation between
last-menstrual-period and clinical estimates
of gestational age in vital records. Am J
Epidemiol. 2008;167(6):646-52.
14. Canadian Institute for Health Information.
DAD abstracting manual (for use with
ICD-10-CA/CCI) 2006-2007. Ottawa (ON):
CIHI; 2006.
15. Canadian Institute for Health Information.
Final report: the Canadian enhancement
of
ICD-10
(International
Statistical
Classification of Diseases and Related
Health Problems, Tenth Revision). Ottawa
(ON): CIHI; 2001.
16. Sullivan LM, Massaro JM, D’Agostino RB Sr.
Presentation of multivariate data for clinical
use: The Framingham Study risk score
functions. Stat Med. 2004;23(10):1631-60.
17. Durrleman S, Simon R. Flexible regression
models with cubic splines. Stat Med.
1989;8(5):551-61.
18. Hutcheon JA, Zhang X, Cnattingius S,
Kramer MS, Platt RW. Customised birthweight percentiles: does adjusting for
maternal characteristics matter? BJOG.
2008;115(11):1397-404.
19. Bonellie S, Chalmers J, Gray R, Greer I,
Jarvis S, Williams C. Centile charts
for birthweight for gestational age for
Scottish singleton births. BMC Pregnancy
Childbirth. 2008;8:5.
24. Gardosi J, Chang A, Kalyan B, Sahota D,
Symonds EM. Customised antenatal growth
charts. Lancet. 1992;339(8788):283-7.
25. Kierans WJ, Joseph KS, Luo ZC, Platt R,
Wilkins R, Kramer MS. Does one size fit
all? The case for ethnic-specific standards
of fetal growth. BMC Pregnancy Childbirth.
2008;8:1.
26. Ray JG, Jiang D, Sgro M, Shah R, Singh G,
Mamdani MM. Thresholds for small for
gestational age among newborns of East
Asian and South Asian ancestry. J Obstet
Gynaecol Can. 2009;31(4):322-30.
27. Joseph KS, Huang L, Liu S, Ananth CV,
Allen AC, Sauve R, et al. Reconciling the
high rates of preterm and postterm birth
in the United States. Obstet Gynecol.
2007;109(4):813-22.
28.Platt RW, Abrahamowicz M, Kramer
MS, Joseph KS, Mery L, Blondel B, et al.
Detecting and eliminating erroneous gestational ages: a normal mixture model. Stat
Med. 2001;20(23):3491-503.
29. Tentoni S, Astolfi P, De PA, Zonta LA.
Birthweight by gestational age in preterm
babies according to a Gaussian mixture
model. BJOG. 2004;111(1):31-7.
20. Kramer MS, Platt RW, Wen SW, Joseph KS,
Allen A, Abrahamowicz M, et al. A new
and improved population-based Canadian
reference for birth weight for gestational
age. Pediatrics. 2001;108(2):E35.
21. Ananth CV, Vintzileos AM, Shen-Schwarz S,
Smulian JC, Lai YL. Standards of birth
weight in twin gestations stratified by
placental chorionicity. Obstet Gynecol.
1998;91(6):917-24.
22. Glinianaia SV, Skjaerven R, Magnus P.
Birthweight percentiles by gestational age
in multiple births. A population-based
study of Norwegian twins and triplets. Acta
Obstet Gynecol Scand. 2000; 79(6):450-8.
23. Gardosi J, Francis A. A customized standard
to assess fetal growth in a US population.
Am J Obstet Gynecol. 2009;201(1):25.e1-7.
108
Vol 31, No 3, June 2011 – Chronic Diseases and Injuries in Canada
The influence of primary health care organizational models on
patients’ experience of care in different chronic disease situations
R. Pineault, MD, PhD (1,2,3); S. Provost, MD, MSc (1,2); M. Hamel, MSc (1,2); A. Couture, MSc (1,2); J.F. Levesque, MD, PhD (1,2,3)
Abstract
Objectives: To examine the extent to which experience of care varies across chronic
diseases, and to analyze the relationship of primary health care (PHC) organizational models
with the experience of care reported by patients in different chronic disease situations.
Methods: We linked a population survey and a PHC organizational survey conducted
in two regions of Quebec. We identified five groups of chronic diseases and contrasted
these with a no–chronic-disease group.
Results: Accessibility of care is low for all chronic conditions and shows little variation
across diseases. The contact and the coordination-integrated models are the most accessible,
whereas the single-provider model is the least. Process and outcome indices of care
experience are much higher than accessibility for all conditions and vary across diseases,
with the highest being for cardiovascular-risk-factors and the lowest for respiratory
diseases (for people aged 44 and under). However, as we move from risk factors to
more severe chronic conditions, the coordination-integrated and community models are
more likely to generate better process of care, highlighting the greater potential of these
two models to meet the needs of more severely chronically ill individuals within the
Canadian health care system.
Keywords:chronic disease, organizational models, primary health care, continuity of
care, accessibility of care, process of care, outcome of care, Quebec
Introduction
As our population ages, management of
chronic diseases has become a prime
concern for policy makers and clinicians
alike.1,2 Health care systems need to shift
from a disease-focused approach to one
that is more holistic and comprehensive.2-5
One convincing argument for adopting
case- rather than disease-management
approaches is the high prevalence of
comorbidities associated with the presence of a chronic disease.1,5,6 Indeed, only
10% of chronically ill individuals present
a single morbidity, whereas 60% present
at least four.7 For these reasons, the optimal
setting for achieving case management
for the chronically ill could arguably be in
primary care.4,8
Several proposals have focused on
approaches linked with primary health
care (PHC) that advocate more accessible
and coordinated patient-centred care, thus
emphasizing health promotion and disease
prevention.9-11 Modalities of care such as
those proposed in the chronic care model
and its derivatives have shown great
potential for achieving such results.12-14
However, less attention has been paid to the
organizational contexts in which these
modalities of care are implemented.15
These integrated models of chronic care do
not specify in which type of organization
and under what organizational modalities
such improvements in chronic care are
most likely to occur. However, some studies
have explored the association between
structural features of PHC practices and
their performance, including experience
of care.14,16,17 A recent study in Ontario
found that chronic disease management
was superior in community health centres
compared with other types of practices.18
Another Ontario study compared two
models of primary care delivery where the
main difference was the way physicians were
paid, with one being enhanced fee-for-service and the other capitation.19 However,
few studies have examined PHC practices
as complex organizational entities.14,17,20,21
Further, to our knowledge no study has
looked at variations in experience of care
across different chronic conditions in relation
to various PHC organizational models.
The objectives of this article are to examine
the extent to which experience of care varies
across chronic diseases and to analyze the
relationship of PHC organizational models
with the experience of care reported by
patients in different chronic disease situations.
Methods
Research design
Our study consisted of two interrelated
surveys. The first, a population-based
telephone survey, involved 9206 randomly
Author references
1. Direction de santé publique de l’Agence de la santé et des services sociaux de Montréal, Montréal, Quebec, Canada
2. Institut national de santé publique du Québec, Québec, Quebec, Canada
3. Centre de recherche du Centre hospitalier de l’Université de Montréal, Montréal, Quebec, Canada
Correspondence: Raynald Pineault, Direction de santé publique, Agence de la santé et des services sociaux, 1301 rue Sherbrooke Est, Montréal QC H2L 1M3;
Tel.: (514) 528-2400 ext. 3480; Fax: (514) 528-2470; Email: [email protected]
Vol 31, No 3, June 2011 – Chronic Diseases and Injuries in Canada
109
TABLE 1
Results of factor analysis for 23 variables of care experience according to survey
respondents (N = 6222) having a regular source of primary care, Quebec, 2003–2005
Experience of care
First-contact accessibility
Number
of variables
Cronbach reliability
coefficient
4
0.579
14
0.848
5
0.849
If the doctor who is responsible for your care is not available, you can see another doctor at your regular clinic
If you need to see a doctor for a new health problem, you go to your regular clinic first
If you need to see a doctor on the same day for a health problem such as fever or a slight accident, you
go to your regular clinic first
When you consult a doctor at your regular clinic, you go directly there without making an appointment
Process of care
Affiliation continuity
You see the same doctor when you go to your regular clinic
At your regular clinic, your medical history is known
At your regular clinic, the doctors/staff are aware of all the prescription medications you take
At your regular clinic, you can receive routine ongoing care for a chronic problem, for example, for high
blood pressure (hypertension), diabetes or back pain, etc.
Comprehensiveness
At your regular clinic, the doctor takes the time to talk to you about prevention and asks you about your
lifestyle habits
At your regular clinic, the doctors/staff help you get all the health care services you need
At your regular clinic, your opinion and your preferences are taken into account in the care that you receive
At your regular clinic, you are helped to weigh the pros and cons when you have to make decisions about
your health
At your regular clinic, your questions are clearly answered by all the clinic staff
At your regular clinic, the doctors spend enough time with you
Responsiveness
You feel respected when you go to your regular clinic
You are greeted courteously at the reception of your regular clinic
Your physical privacy is respected at your regular clinic
The premises of your regular clinic are pleasant
Outcomes of care
The services you get at your regular clinic help you better understand your health problems
The services you get at your regular clinic help you prevent certain health problems before they appear
The services you get at your regular clinic help you control your health problems
The professionals you see at your regular clinic encourage you to follow the treatments prescribed
The professionals you see at your regular clinic help motivate you to adopt good lifestyle habits like quitting
smoking, eating more healthy foods, etc.
selected adults (aged 18 years or older)
in two regions of Quebec, in 2005. To ensure
that the 23 territories of the Health and
Social Service Centres were locally represented, the sample was non-proportionally
stratified. Accordingly, all analyses were
done on weighted data to account for
this characteristic of the sampling frame.
The survey assessed respondents’ current
affiliation with PHC organizations, their
health services utilization level, the attributes
of their experience of care, and their
perception of unmet care needs.22,23
The second survey was a mail survey with
response from 473 PHC organizations in the
same two regions of Quebec. This survey
assessed aspects related to vision, structure,
resources and practices of the PHC organizations. In each organization, a key informant,
generally a doctor designated by his or her
colleagues, responded to the questionnaire.
110
A nominal link between the two surveys
was established by asking population
survey respondents to identify their usual
source of PHC. Response rates were 64%
for the population survey and 75% for the
organizational survey; 89% of respondents
were linked to one of the 473 PHC organizations. For this study, we used responses
from the 6222 respondents who used services
in the two years prior to the study (2003–
2005) and who could be linked to one of
Vol 31, No 3, June 2011 – Chronic Diseases and Injuries in Canada
the 473 PHC organizations as their usual
source of care. Further information about
the surveys is available elsewhere.22-24
Variables
Two complex constructs were operationalized in this study: experience of care and
organizational model. Using a factor analysis
of 23 items from the population survey,
we constructed three indices of experience
of care: first-contact accessibility, process
of care and perceived outcomes of care.
In this study, first-contact accessibility corresponds to the ease with which individuals
can access and use health services, and
process of care corresponds to affiliation
and follow-up continuity, namely, comprehensiveness and responsiveness. Affiliation
and follow-up continuity refer to conditions
associated with having a regular source of
care and its capacity to manage chronic
diseases; comprehensiveness measures the
organization’s ability to respond to a wide
spectrum of needs expressed by the patient;
responsiveness focuses on the respect and
attention given to the dignity of the person
and to the non-technical aspect of care.
Table 1 shows the Cronbach reliability coefficients for the three indices of experience
of care and the items making up these indices.
We operationalized the indices based on an
approach that measures performance by
recategorizing each multiple category item
into dichotomous low/high variables.25,26
Responses in the low category received
a score of zero and those in the high category
a score of one. For each index, we averaged
the dichotomized scores and placed each
on a scale of 0 to 10. For the purpose of the
analyses, we created three dichotomous
variables with each index using a cut-off
point of 7.5, based on its distribution and
the judgment of a panel of three experts
that a score of 7.5 or higher represented
better performance, whereas a score below
7.5 represented lower, but not necessarily
poor, performance. As such, we analyzed
three dichotomous variables of first-contact
accessibility (high vs. low), process of care
(high vs. low), and perceived outcomes of
care (high vs. low).
We conceptualized organizations as having
four dimensions: vision, resources, structure
and practices.27 Vision refers to the representation, values and orientation shared
by members of the organization. Resources
are expressed in terms of the number
of professionals and the quantity and type
of technical platforms and communications
technologies available. Structure consists of
rules, regulations and governance that give
coherence to the functioning of organizations and to relationships with their environment. Finally, practices represent clinical
and organizational mechanisms supporting
delivery of services.27 In total, we allocated
43 variables (described in detail elsewhere23)
to these dimensions. Based on these 43
variables, we performed a cluster analysis
of the 473 PHC organizations, and derived
a taxonomy of five different models: one
community model and four professional
models, namely, single-provider, contact,
coordination and coordination-integrated
models. (These models are described in
greater detail elsewhere.23)
Table 2 presents distinctive characteristics of
the models’ four dimensions. As we move
from left to right in Table 2, the models
clearly become increasingly complex in
terms of their characteristics, the most complex ones being the professional coordination-integrated model and the community
models. Figure 1 shows the correspondence
between currently existing types of PHC
organizations in the two regions and the
five models of the taxonomy.
Selection of diseases
As mentioned earlier, we used the responses
from those respondents who had used
services in the two years prior to the study
(2003–2005) and who could be linked to
one of the 473 PHC organizations as their
usual source of care (N = 6222). We asked
them about their experience of care and
whether a doctor had ever told them they
had one or more of the chronic diseases
listed in the questionnaire.* Respondents
were then classified according to whether or
not they had a chronic disease. Individuals
with only one morbidity were classified
in the corresponding morbidity category.
Those with more than one morbidity were
assigned to the first category of morbidity
listed in decreasing order, as shown in the
flow diagram (Figure 2). To ensure that the
no–chronic-disease group (37.6%) did not
include any chronic disease patients, people
with chronic diseases other than those
being studied (15.2%) were excluded from
the analyses. Cardiovascular risk factors
include diabetes, hypertension and hypercholesterolemia; for other chronic diseases,
it was generally not possible to make finer
distinctions within categories.
To assess the association of different organizational models with the care experience
of chronic illness patients, we performed
stratified logistic regressions of the three
dichotomous variables of interest (access,
process, outcomes) for each chronic illness
group. All analyses included age, sex,
income and educational level as covariates.
Results
Individual characteristics and affiliation
of respondents
Table 3 shows the characteristics of respondents, including their affiliation with a community or professional model of care. Each
disease group, including the group with
no chronic disease, is compared to the
reference group “all users.” Compared with
those in the “all users” reference group, individuals in the no–chronic-disease group
tend to be younger, in better health, male
and better educated. On the other hand, the
cardiovascular-risk-factors group is older,
includes more men and has a lower level
of education than the reference group.
The arthritic, respiratory (≥ 45 years)
and cardiac-disease groups share similar
characteristics: individuals are older, in
poorer health, and have lower education
and income levels than the “all users”
reference group. The arthritic and the
respiratory-disease groups also include a
higher percentage of women. Individuals
in the respiratory disease group (≤ 44
years) are younger and tend to have higher
levels of education and income.
* Cardiac (heart disease or heart failure), respiratory (chronic obstructive pulmonary disease [COPD], asthma), arthritic (arthritis, osteoarthritis, rheumatism),
cardiovascular risk factor (hypertension, diabetes, hypercholesterolemia) or other (peripheral vascular disease, cancer).
Vol 31, No 3, June 2011 – Chronic Diseases and Injuries in Canada
111
TABLE 2
Primary health care (PHC) organizations (N = 473) surveyed, Quebec, 2003–2005
Professional models of care
Characteristics
Single provider
Contact
Coordination
Coordinationintegrated
Community model
Population **
Population ***
Vision (values)
Responsibility
Clientele**
Individuals who present *** Clientele ***
Continuity - accessibility
NS
Accessibility > continuity *** Continuity > accessibility* NS
Team work
Not important ***
NS
Important ***
Important ***
Important ***
MDs supply
Low ***
Average *
Low ***
High ***
High ***
Professionals supply
Low ***
High ***
High ***
High ***
Average ***
Technical platform
Very low ***
NS
Average **
High ***
Average ***
Information and communication technologies
Very low ***
NS
NS
High ***
High ***
Governance
Prof. private ***
Prof. private ***
Prof. private ***
Prof. private ***
Public ***
MD payment
FFS ***
FFS ***
FFS ***
FFS ***
Time based ***
Internal collaboration
None ***
Informal **
Informal ***
Formal ***
Formal***
Link with primary care
NS
No **
No *
Yes***
NS
Link with specialized
services
NS
No *
No**
Yes***
NS
Appointment/walk-in
Mostly scheduled
appointment***
Mostly walk-in ***
NS
NS
NS
Scope of services
Narrow ***
Narrow **
Broad ***
Very broad ***
Very broad ***
Quality assessment
None ***
More or less ***
More or less ***
More ***
More ***
Continuity > accessibility **
Resources
Structure
Practices
Abbreviations: FFS, fee-for-service; N, overall sample size; NS, not significant; p, statistical significance; prof., professional
Difference between levels of the characteristics within each model
* p ≤ .05
** p ≤ .01
*** p ≤ .001
FIGURE 1
Correspondance between currently existing types of PHC organizations and models of the taxonomya
100%
80%
100
CLSC (12)b
100
100
35
FMG (6)c
65
20
60%
44
100
29
100
Group (50)
40%
Community (12)
Coordination-integrated (15)
Coordination (22)
Contact (14)
7
11
20%
0
Solo (32)
100
89
Currently existing types of PHC
Single provider (37)
Models of PHC org.
a
Percentages read as follows: all (100%) of CLSC (left bar) fall into the community category (right bar) and constitute 100% of this category
b
CLSC: Centres locaux de services communautaires (Local community health centers)
c
FMG: Family medicine groups
112
Vol 31, No 3, June 2011 – Chronic Diseases and Injuries in Canada
FIGURE 2
Flow diagram for assignment of survey respondents to chronic disease group
Respondents (n = 6222)
Heart disease / heart failure
No
Cardiac (7.8%)
No
Respiratory (≥ 45 years) (6.3%)
Chronic obstructive pulmonary
disease (COPD)
No
Respiratory (≤ 44 years) (6.3%)
Asthma
No
Arthritic (15.7%)
Arthritis / osteoarthritis /
rheumatism
No
Cardiovascular risk factors (11.1%)
Hypertension / diabetes /
hypercholesterolemia
No
Other chronic diseases (15.2%)
Peripheral vascular disease /
cancer / etc.
No chronic disease (37.6%)
There is little variation across disease
groups with respect to affiliation to the
various PHC organizational models (Table 3).
An exception, however, is the no–chronicdisease group of respondents, who tend
to concentrate more in the contact model
and less in the single-provider model, compared with all service users. The singleprovider model also attracts more than its
share of individuals with cardiac diseases
and less than its share of respiratory-disease patients (≤ 44 years). Aside from these
differences, the percentage of individuals
affiliated with organizational models in the
different chronic-disease groups is similar
to the figures for all users. However, the
percentage of users of services that identify
each model as their regular source of care
varies considerably, from 10.4% for the
community model to 29.0% for the coordination-integrated model.
As we move from the no–chronic-disease
to the cardiac-disease group (Table 3),
perceived health status tends to deteriorate,
presumably reflecting an increasing gradient
of disease severity.
Further analysis of the comorbidities
associated with these chronic diseases
confirms this increasing degree of severity,
as the number of comorbidities associated
with the main morbidity increases steadily
from the no–chronic-disease to the cardiacdisease group (Table 4).
Experience of care by disease
Experience of care varies across disease
conditions (Table 5). First-contact accessibility presents the lowest percentage of
individuals with scores of 7.5 and more,
and the least variation across diseases.
First-contact accessibility is slightly lower
for people in the no–chronic-disease group,
although there is no statistically significant
difference between each chronic disease
category and the all-users one.
Process of care reveals a higher percentage
of individuals with scores of 7.5 and more,
and with greater variation across diseases
than first-contact accessibility. The respiratory
group aged 44 years and less has the lowest percentage of individuals with scores
of 7.5 and more, even lower than the
Vol 31, No 3, June 2011 – Chronic Diseases and Injuries in Canada
113
no–chronic-disease group, whereas the
cardiovascular-risk-factors group has the
highest percentage. Outcomes of care follow
the same pattern as process of care: the
percentage of those with scores of 7.5 and
more varies and is much lower for people
aged 44 years and less with respiratory
diseases, and higher for those with cardiovascular risk factors.
Experience of care related to organizational
models in different disease situations
Table 6 shows odds ratios (ORs) with 95%
confidence intervals (CIs) for relationships
between the organizational models and
experience of care in the different chronic
disease groups, with the professional contact
model as reference. Data are adjusted for
respondents’ characteristics except for
perceived health status, which was highly
correlated with the chronic diseases
included in the analyses.
First-contact accessibility is better in the
contact and coordination-integrated models
(OR > 1 with lower limit of CI ≥ 1) and
much worse in the single-provider model
TABLE 3
Characteristics of population survey respondents (N = 6222) by chronic disease group, Quebec, 2003–2005
Chronic disease group, %
Respondent characteristic
All users
No chronic
disease
Cardiovascular
risk factors
Arthritic
Respiratory
(≤ 44 years)a
Respiratory
(≥ 45 years)b
Cardiac
Age
18–39
35.3
53.8*
8.7*
8.3*
81.5
-
10.1*
40–54
31.0
34.8*
29.4
27.6
18.5
41.8
16.5*
55–69
21.5
9.4*
41.8*
37.8*
-
36.5
34.8*
70 plus
12.2
2.0*
20.2*
26.3*
-
21.7
38.5*
Male
44.3
48.7*
56.9*
31.6*
37.7*
37.8*
46.8
Female
55.7
51.3*
43.1*
68.4*
62.3*
62.2*
53.2
Bad/average
17.5
5.3*
19.2
25.9*
17.5
35.5*
39.5*
Good
29.4
22.5*
37.0*
34.1*
37.7*
33.1
33.3
Excellent
53.1
72.2*
43.8*
40.0*
44.7*
31.4*
27.2*
Primary (less than high school)
15.6
6.6*
20.5*
26.3*
7.7*
24.9*
34.4*
Secondary diploma
32.7
32.4
35.1
33.1
32.7
32.7
31.9
Post-secondary diploma
24.1
27.5*
19.3*
19.6*
32.0*
25.1
17.1*
University degree
27.5
33.5*
25.1
21.0*
27.6
17.3*
16.5*
Less than 15,000
11.9
9.3*
10.3
15.0*
13.2
17.0*
18.8*
15,000–34,999
31.2
26.3*
33.9
36.8*
24.0*
35.8
42.1*
35,000–74,999
34.5
37.0
34.4
30.9
38.2
31.1
28.3*
75,000 plus
22.5
27.3*
21.4
17.3*
24.5
16.1*
10.7*
Sex
Perceived health status
Level of education completed
Income, CAD
Model of organization as regular source of care
Contact
22.7
25.8*
19.2
20.6
26.0
21.9
20.8
Coordination
25.3
22.9
27.3
29.1
25.5
25.5
23.7
Coordination-integrated
29.0
29.5
27.9
26.6
27.6
28.5
28.9
Community
10.4
11.7
10.7
8.9
10.8
9.2
8.7
Single provider
12.5
10.1*
14.8
14.7
10.1
14.8
17.9*
Abbreviations: CAD, Canadian dollars; N, overall sample size; p, statistical significance.
a
The main morbidity in this age group (≤ 44 years) is likely asthma.
b
The main morbidity in this age group (≥ 45 years) is likely chronic obstructive pulmonary disease (COPD).
* p ≤ .05; reference is all users
(OR < 1 with upper limit of CI < 1), for all
the chronic disease and no–chronic-disease
groups. The community model is also among
the more accessible models for arthritic as well
as respiratory diseases for both age groups.
The odds ratios for process of care also vary
by organizational model across diseases.
The contact model tends to offer a less
favourable process of care than the other
models in all disease groups, as well as the
no–chronic-disease group, except in the cardiovascular-risk-factors and respiratory-diseases
(≤ 44 years) groups. For both these groups,
all organizational models other than single
provider show a less favourable experience
of care.
Results for outcomes of care follow the
same pattern as for process of care. Those
for the no–chronic-disease group follow
the pattern observed for process of care
more closely. The other results are similar
to those for process of care, but for the most
part they fail to reach statistical significance.
114
Discussion
Our study sheds light on the range of care
experience across chronic disease conditions.
It also explores the extent to which the
relationship between organizational PHC
models and care experience varies across
different types of chronic diseases.
Two major findings emerge from our study.
First, accessibility of care is relatively low
for all chronic conditions, as well as for
those with no chronic disease, and shows
little variation across diseases. Process
Vol 31, No 3, June 2011 – Chronic Diseases and Injuries in Canada
of care and outcomes of care indices are
much higher for all conditions and these vary
across diseases, with the highest being for
the cardiovascular-risk-factors group and
the lowest for respiratory-diseases (≤ 44
years) group.
Second, first-contact accessibility for all
chronic disease conditions is more likely to
be attained in the contact and the coordination-integrated models than in the other
models. Conversely, first-contact accessibility is likely to be lower for patients
whose regular source of care is either the
single-provider or the coordination model
of PHC organization.
In contrast, for process of care and, to a lesser
extent, outcomes of care, the single-provider
model is associated with better results than
the contact model for all chronic diseases
and no chronic diseases. Patients with cardiovascular risk factors and respiratory diseases (≤ 44 years) report a worse process
of care for all models other than the singleprovider model, while for the no–chronicdisease, arthritic, respiratory (≥ 45 years)
and cardiac-disease groups, all models surpass the contact model for process of care.
The community model is superior for older
patients (≥ 45 years) with respiratory diseases, as is the coordination model for those
with cardiac diseases (Table 6).
These findings on accessibility deserve a
lengthier explanation. First, in our study
the percentage of individuals with high
score (≥ 7.5 out of 10) of first-contact
accessibility of PHC is rather low (range:
28.4%–32.1%), regardless of their condition, and the percentage is much lower
than for other aspects of care experience (Table 5). Other studies have also
alerted us to major problems of accessibility in the delivery of PHC services.28-30
Although the variation between models is
small, logistic regression analysis reveals
two interesting contrasting results: the
single-provider model is the least accessible at first contact, whereas the contact model is the most accessible in all
conditions. Since a higher proportion of
patients affiliated with the single-provider
model than with the contact model have
regular doctors (94% vs. 64%), this suggests that having a regular doctor is not
among the most important factors fostering
accessibility (Figure 3).29,31-33 At least for
this dimension of care experience, having
a regular doctor does not seem to be the
sole important factor explaining the relationship between first-contact accessibility
and PHC organizational models; some
intrinsic attributes of these various models,
such as group practice, also seem to be
important. This is due to the fact that
access to health care is conceptualized in
this study as having access to a specific
general practitioner as well as to other
doctors in the absence of one’s family doctor.
Obviously, solo providers fail to address
this broader view of first-contact access.
Conversely, the contact model possesses
intrinsic features that foster first-contact
accessibility (Table 2).
In comparison with first-contact accessibility, process of care and, to a lesser extent,
outcomes of care show much higher percentages of individuals having high scores
for all diseases. There is also greater variation
across diseases, with the respiratory-diseases
(≤ 44 years) group having the lowest
percentage and cardiovascular-risk-factors
group the highest (Table 5). These differences
may reflect the fact that patients in the
respiratory-diseases (≤ 44 years) group are
less likely to have a regular doctor (63%)
than patients in the cardiovascular-risk-factors group (93%) (Figure 4). Patients in the
respiratory-diseases (≤ 44 years) group are
also younger than those in the cardiovascular-risk-factor groups (Table 3). Studies
reveal that older patients and those who
have a regular doctor are more likely to
report a favourable experience of care.29,31,32
In comparison to accessibility, process
of care is much higher for patients in
all the disease groups who are with the
single-provider model of PHC (Table 6).
The two coordination models and the
community model also generate better
processes and outcomes of care than the
contact model for no-chronic disease or
arthritic and respiratory (≥ 45 years) diseases
(Table 6). This indicates that, at least for
these three conditions, organizational models
influence these aspects of experience of
care, although part of this influence can be
mediated through age of patients and their
having a regular doctor. This explanation
Vol 31, No 3, June 2011 – Chronic Diseases and Injuries in Canada
115
does not hold, however, for the younger
no-chronic-disease group, in which a lower
percentage of individuals have a regular
doctor. Finally, these two factors—age and
having a regular doctor—probably explain
the lack of relationship, in the younger
group of patients with respiratory diseases,
between models and care experience,
except for the single-provider model.
These findings suggest a possible interaction
between age and having a regular doctor
that we did not explore further. The divergent
pattern observed for the cardiovascularrisk-factors group is difficult to explain.
Indeed, one would expect age and having
a regular doctor to contribute to a better
experience of care as compared to the contact
model. The lack of difference among models
probably reflects the fact that patients with
cardiovascular risk factors are less sensitive
to differential characteristics of PHC models
and find their needs evenly met by the
various organizational models. It is also
plausible that these patients have fewer
symptomatic conditions and thus require less
diligent medical attention. This hypothesis
remains to be tested in further analyses.
Overall, the professional coordination-integrated and the community models emerge as
the ones more likely to cover the whole spectrum of care experience, in terms of accessibility, process of care and outcomes of care
for most conditions. Notably, these two models
yield more favourable processes of care for
more severe conditions, such as cardiac,
respiratory (≥ 45 years) and arthritic diseases.
As noted earlier, these more severe diseases
also include a greater number of comorbidities
and thus require a more comprehensive and
integrated approach to fulfill the diversity
of needs. Hence, the coordination-integrated
and the community models are particularly
well suited to face the growing challenge
of chronic disease management.
Although the results for process of care and
outcomes of care follow similar patterns,
most results for outcomes of care fail to
reach statistical significance. This could be
due to a lack of statistical power but also
to the lack of specificity of our outcomes
indicators, which are largely related to prevention. The tenuous relationship between
process and outcomes of care is a common
TABLE 4
Population survey respondents (N = 6222) with comorbidities associated with their chronic disease group
Comorbidities, %
Chronic disease groups
Cardiac
problems
Cardiac
Respiratory
problems
Arthritic
problems
Cardiovascular
risk factors
Other health
problems
100.0
24.3
45.9
65.4
74.9
a
Respiratory (≥ 45 years)
-
100.0
50.0
38.9
67.2
Respiratory (≤ 44 years)b
-
100.0
9.9
3.6
38.2
Arthritic
-
-
100.0
39.1
51.1
Cardiovascular risk factors
-
-
-
100.0
39.9
Other health problems
-
-
-
-
100.0
No chronic disease
-
-
-
-
-
Abbreviations: N, overall sample size.
a
The main morbidity in this age group (≥ 45 years) is likely chronic obstructive pulmonary disease (COPD).
b
The main morbidity in this age group (≤ 44 years) is likely asthma.
TABLE 5
Population survey respondents (N = 6222) who experienced better carea by chronic disease group
Chronic disease group, %
Experience of care
All users
No chronic
disease
Cardiovascular
risk factors
Arthritic
Respiratory
(≤ 44 years)b
Respiratory
(≥ 45 years)c
Cardiac
First-contact accessibility
29.7
28.4
31.7
32.1
29.1
30.7
30.3
Process of care
61.4
54.7*
79.1*
69.0*
48.8*
71.5*
69.5*
Outcomes of care
56.8
52.4*
73.4*
62.5*
42.5*
63.9*
62.9*
Abbreviations: N, sample size; p, statistical significance.
a
Having a score of 7.5 out of 10 on a scale of 0 to 10 of dichotomized scores.
b
The main morbidity in this age group (≤ 44 years) is likely asthma.
c
The main morbidity in this age group (≥ 45 years) is likely chronic obstructive pulmonary disease (COPD).
*p ≤ .05; reference is all users
finding of studies reporting on experience
of care and continuity.34
Finally, our findings must also be interpreted
in light of the relative importance of the five
PHC organizational models presented. As
shown in Table 3, the three professional
models—contact, coordination and coordination-integrated—share more than 75%
of the utilization coverage, whereas the community and single-provider models represent
just over 10% each. Further, the single-provider model is fading out as a model of PHC
organization and the community model has
not demonstrated the capacity to develop
beyond its current level. Hence, major
improvements to our health care system
will likely come from the three most widely
used professional models, either by their
moving towards the best performing model,
identified in our study as the coordinationintegrated model, or by establishing networks
in which each model accomplishes specific
and complementary functions in a coordinated and integrated way.
Strengths and limitations
Our study has some limitations. Firstly, the
cross-sectional design makes it difficult
to infer causal relationships between models
of care and care experience reported in the
last two years. In addition, a recall bias may
limit the accuracy and reliability of information gathered on the experience of care.
Another limitation is self-reporting of chronic
conditions. Although the wording of the question referred to validation of the diagnosis
by a doctor (i.e. “Has a doctor ever told
you that you have diabetes?”), the response
is always limited by respondents’ subjective
interpretation and their capacity to report
medical information accurately. Likewise, it
was not possible to obtain greater diagnostic
116
specificity. For example, we broke down
the category of respiratory diseases into two
age categories, assuming that people aged
44 years and younger were mainly reporting
asthma, while for those aged 45 years plus
the main morbidity was COPD, but we were
unable to validate these assumptions.
Assigning morbidities to mutually exclusive
categories adds more comorbidities to the
first ones appearing in the scale. At the same
time, this procedure increases the heterogeneity of these categories. But given the
correlation between perceived health status
and categories of chronic diseases, we
considered the inclusive order of categories
of morbidities as accurately representing
decreasing degrees of severity. However,
since it remains a measure of prevalence of
a diagnosis and not a true measure of health
status, our analyses cannot claim to have
fully controlled for severity of disease and
Vol 31, No 3, June 2011 – Chronic Diseases and Injuries in Canada
Vol 31, No 3, June 2011 – Chronic Diseases and Injuries in Canada
117
1.292
0.753
0.185
Community
Single provider
1.845
1.292
4.254
Coordination-integrated
Community
Single provider
2.370
Single provider
(0.604 –1.009)
(CI 95%)
1.281
1.441
(1.731 – 3.245)
1.122
1.062
2.558
0.902
0.684
0.853
0.135
0.250
0.723
0.451
ORb
Adjusted for age, sex, income and level of education but not for perceived health status
Reference is the professional contact model
a
b
(0.788 – 2.637)
(0.664 – 2.471)
(0.678 – 1.858)
(0.640 – 1.764)
(1.136 – 5.758)
(0.438 – 1.858)
(0.396 – 1.181)
(0.483 – 1.507)
(0.067 – 0.271)
(0.127 – 0.491)
(0.462 – 1.131)
(0.282 – 0.720)
(CI 95%)
Cardiovascular
risk factors
(0.983 – 1.742)
(1.182 – 1.834)
(1.402 – 2.246)
(3.016 – 5.999)
(0.969 – 1.722)
(1.478 – 2.304)
(1.475 – 2.368)
(0.113 – 0.303)
(0.548 – 1.036)
(1.027 – 1.624)
Abbreviations: CI, confidence interval; OR, odds ratio
1.308
1.472
Coordination-integrated
Community
1.774
Coordination
Outcomes of care
1.869
Coordination
Process of care
0.781
Coordination-integrated
ORb
Coordination
First-contact accessibility
Experience of care
No chronic disease
1.637
1.510
1.235
1.416
5.067
2.345
1.937
2.243
0.216
0.678
0.926
0.689
ORb
(1.042 – 2.573)
(0.891 – 2.558)
(0.848 – 1.798)
(0.977 – 2.052)
(2.947 – 8.711)
(1.349 – 4.078)
(1.314 – 2.855)
(1.528 – 3.294)
(0.124 – 0.376)
(0.399 – 1.155)
(0.636 – 1.348)
(0.473 – 1.002)
(CI 95%)
Arthritic
2.480
1.556
1.665
1.249
4.208
1.466
1.684
1.152
0.130
0.897
0.756
0.443
ORb
(1.165 – 5.277)
(0.747 – 3.242)
(0.944 – 2.935)
(0.702 – 2.222)
(1.862 – 9.510)
(0.711 – 3.024)
(0.963 – 2.944)
(0.656 – 2.025)
(0.039 – 0.431)
(0.425 – 1.894)
(0.425 – 1.344)
(0.238 – 0.822)
(CI 95%)
Respiratory
(≤ 44 years)
Chronic disease group, %
TABLE 6
Experience of care by organizational model and by chronic disease groups
1.760
1.588
1.046
1.285
2.869
4.959
1.710
2.919
0.249
1.085
1.476
0.709
ORb
ORb
0.227
0.605
0.458
0.173
4.024
1.670
1.241
2.577
1.677
1.219
0.625
1.115
(CI 95%)
(0.375 – 1.338)
(0.814 – 2.677)
(0.459 – 2.566)
(0.096 – 0.646)
(1.538 – 5.540)
(0.950 – 3.077)
(1.724 – 14.266)
(1.340 – 6.140)
(0.705 – 2.341)
(0.583 – 1.877)
(0.656 – 3.846)
(0.850 – 3.645)
Respiratory
(≥ 45 years)
(0.609 – 2.042)
(0.299 – 1.307)
(0.717 – 2.072)
(0.944 – 2.980)
(1.353 – 4.907)
(0.591 – 2.606)
(0.980 – 2.845)
(2.139 – 7.572)
(0.083 – 0.358)
(0.210 – 0.997)
(0.358 – 1.024)
(0.122 – 0.420)
(CI 95%)
Cardiac
its potential impact on the experience of
care. Finally, self-selection of patients into
different primary care organizational models
cannot be totally discarded.
Our study also has distinctive strengths.
By approaching a large sample of the entire
population of the two most populous regions
of Quebec, and sending the organizational
questionnaire to all the PHC organizations
in these two regions, we were able to link
89% of the respondents to one of the 473
PHC organizations surveyed.
Conclusion
Study findings reveal that different organizational models of PHC behave differently
in different chronic disease situations.
Accessibility of care is lowest for all chronic
conditions and shows little variation across
diseases. The contact and the coordinationintegrated models are the most accessible,
whereas the single-provider model is the
least. Indices for process of care and outcomes
of care are much higher than for accessibility
for all conditions and vary across diseases,
the highest being for patients with cardiovascular risk factors and the lowest for
younger patients (≤ 44 years) with respiratory diseases. The contact model seems to
be at the forefront in terms of accessibility
whereas the single-provider model is best
when the focus is on process of care.
However, these two models have severe
limitations as far as other aspects of care
experience are concerned. For chronic diseases
of increased severity, the coordinationintegrated and the community models are
more likely to generate a better process of
care and, consequently, to meet essential
conditions for successful implementation
of the chronic-care model. The coordination-integrated model in particular emerges
as the most complete model that can
concomitantly achieve a higher level of
accessibility and of process of care for nearly
all chronic conditions and attain a higher
level of utilization coverage. In this sense,
it is probably the model with the greatest
potential for bringing about important
changes to our health care system.
FIGURE 3
Percentage of survey respondents (N = 6222) who have a regular doctor by organizational model of that doctor’s practice
% 100
94.1*
90
79.9*
80
76.3
75.8
70
67.6*
64.3*
60
Contact
Coordination
Community
Coordinationintegrated
Single provider
All users
*p ≤ .05 Reference: All users
FIGURE 4
Percentage of survey respondents (N = 6222) who have a regular doctor by chronic disease group
% 100
92.5*
90
88.9*
88.6*
87.3*
80
75.8
70
63.7*
63.2*
60
Cardiac
Respiratory
(≥ 45 years)
Respiratory
(≤ 44 years)
Arthritic
No chronic
disease
Cardiovascular
risk factors
All users
*p ≤ .05 Reference: All users
Acknowledgements
The data presented in this article originated
from a research project funded by the
Canadian Institutes of Health Research
(CIHR), Canadian Health Services Research
Foundation (CHSRF) and Fonds de la
recherche en santé du Québec (FRSQ).
Financial support was also provided by the
Agence de la santé et des services sociaux
de Montréal and Agence de la santé et des
services sociaux de la Montérégie, Institut
national de santé publique du Québec
(INSPQ), Groupe de recherche sur l’équité
d’accès et l’organisation des services de
santé de 1re ligne (GRÉAS 1), and Groupe
interuniversitaire de recherche sur les
urgences (GIRU).
The authors declare that there are no conflicts
of interest.
References
1. Broemeling AM, Watson DE, Prebtani F.
Population patterns of chronic health conditions, co-morbidity and healthcare use in
Canada: implications for policy and practice.
Healthc Q. 2008;11(3):70-6.
2.
The authors wish to thank Alexandre
Prud’homme, Odette Lemoine and Brigitte
Simard for their contribution to the data
analysis; Sylvie Gauthier and Isabelle Rioux
revised the text and provided editorial
assistance in preparing the manuscript.
118
Wagner EH. Meeting the needs of chronically
ill people. BMJ. 2001;323(7319):945-6.
3. Epping-Jordan JE, Pruitt SD, Bengoa R,
Wagner EH. Improving the quality of
health care for chronic conditions. Qual Saf
Health Care. 2004;13(4):299-305.
Vol 31, No 3, June 2011 – Chronic Diseases and Injuries in Canada
4. Starfield B, Lemke KW, Bernhardt T,
Foldes SS, Forrest CB, Weiner JP.
Comorbidity: implications for the importance
of primary care in ‘case’ management. Ann
Fam Med. 2003;1(1):8-14.
5. Starfield B, Lemke KW, Herbert R,
Pavlovich WD, Anderson G. Comorbidity
and the use of primary care and specialist
care in the elderly. Ann Fam Med.
2005;3(2):215-22.
6.
7.
8.
Grumbach K. Chronic illness, comorbidities,
and the need for medical generalism. Ann
Fam Med. 2003;1(1):4-7.
Broemeling AM, Watson DE, Black C. Chronic
conditions and co-morbidity among residents
of British Columbia. Vancouver (BC): Centre
for Health Services and Policy Research,
University of British Columbia; 2005.
Rothman AA, Wagner EH. Chronic illness
management: what is the role of primary
care? Ann Intern Med. 2003;138(3):256-61.
9. Davis K, Schoenbaum SC, Audet AM. A
2020 vision of patient-centered primary
care. J Gen Intern Med. 2005;20(10):953-7.
10. Starfield B, Shi L. The medical home, access
to care, and insurance: a review of evidence.
Pediatrics. 2004;113(5 Suppl):1493-8.
11. O’Connor PJ, Sperl-Hillen JM, Pronk NP,
Murray T. Primary care clinic-based chronic
disease care: Features of successful programs.
Dis Manag Health Out. 2001;9(12):691-8.
12. Bodenheimer T, Wagner EH, Grumbach K.
Improving primary care for patients with
chronic illness: the chronic care model,
Part 2. JAMA. 2002;288(15):1909-14.
13.Barr VJ, Robinson S, Marin-Link B,
Underhill L, Dotts A, Ravensdale D, et
al. The expanded Chronic Care Model:
an integration of concepts and strategies
from population health promotion and the
Chronic Care Model. Hosp Q. 2003;7(1):73-82.
14. Rundall TG, Shortell SM, Wang MC, Casalino
L, Bodenheimer T, Gillies RR, et al. As
good as it gets? Chronic care management
in nine leading US physician organizations.
BMJ. 2002;325(7370):958-61.
15.Levesque JF, Feldman D, Dufresne C,
Bergeron P, Pinard B, Gagné V. Barrières
et éléments facilitant l’implantation de
modèles intégrés de prévention et de gestion
des maladies chroniques. Prat Organ Soins.
2009;40(4):251-65. French.
16.Friedberg MW, Coltin KL, Safran DG,
Dresser M, Zaslavsky AM, Schneider EC.
Associations between structural capabilities
of primary care practices and performance
on selected quality measures. Ann Intern
Med. 2009;151(7):456-63.
17. Shortell SM, Marsteller JA, Lin M, Pearson ML,
Wu SY, Mendel P, et al. The role of perceived
team effectiveness in improving chronic illness care. Med Care. 2004;42(11):1040-8.
18. Russell GM, Dahrouge S, Hogg W, Geneau R,
Muldoon L, Tuna M. Managing chronic
disease in Ontario primary care: the impact
of organizational factors. Ann Fam Med.
2009;7(4):309-18.
19. Glazier RH, Klein-Geltink J, Kopp A,
Sibley LM. Capitation and enhanced fee-forservice models for primary care reform:
a population-based evaluation. CMAJ.
2009;180(11):E72-E81.
20.Tsai AC, Morton SC, Mangione CM,
Keeler EB. A meta-analysis of interventions
to improve care for chronic illnesses. Am J
Manag Care. 2005;11(8):478-88.
21. Cretin S, Shortell SM, Keeler EB. An evaluation of collaborative interventions to improve
chronic illness care: Framework and study
design. Eval Rev. 2004;28(1):28-51.
22.Levesque JF, Pineault R, Simard B,
Roberge D, Hamel M, Kapetanakis C, et
al. L’expérience de soins de la population:
portrait des variations intra-régionales
à Montréal et en Montérégie [Internet].
Montréal (QU): Institut national de santé
publique du Québec; 2007 [cited 2010
Nov 8]. Available from: http://www
.inspq.qc.ca/pdf/publications/627-ExperienceDeSoinsDeLaPopulation.pdf French.
Jointly published by Direction de santé
publique de l’Agence de la santé et des services
sociaux de Montréal.
Vol 31, No 3, June 2011 – Chronic Diseases and Injuries in Canada
119
23.Pineault R, Levesque JF, Roberge D,
Hamel M, Lamarche P, Haggerty J.
Accessibility and continuity of care: a study
of primary healthcare in Québec. Research
report presented to the Canadian Institutes
of Health Research and the Canadian
Health Services Research Foundation
[Internet]. Montréal (QU): Direction de
santé publique de l’Agence de la santé
et des services sociaux de Montréal;
2009 [cited 2010 Nov 8]. Available from:
http://www.inspq.qc.ca/pdf/publications
/911_ServicesPremLigneANGLAIS.pdf Jointly
published by Institut national de santé publique du Québec and Centre de recherche
de l’Hôpital Charles LeMoyne.
24. Hamel M, Pineault R, Levesque JF, Roberge D,
Lozier-Sergerie A, Prud’homme A, Simard B.
L’organisation des services de santé de
première ligne: portrait des services médicaux de première ligne à Montréal et en
Montérégie. Montréal (QU): Institut national
de santé publique du Québec; 2007 [cited
2010 Nov 8]. http://www.inspq.qc.ca/pdf/
publications/726-OrganisationServices.pdf
French. Jointly published by Direction de santé
publique de l’Agence de la santé et des services
sociaux de Montréal.
25. Nietert PJ, Wessell AM, Jenkins RG, Feifer C,
Nemeth LS, Ornstein SM. Using a summary
measure for multiple quality indicators in
primary care: the Summary QUality InDex
(SQUID). Implement Sci. 2007;2:11.
26. Feifer C, Nemeth L, Nietert PJ, Wessell AM,
Jenkins RG, Roylance L, et al. Different
paths to high-quality care: three archetypes
of top-performing practice sites. Ann Fam
Med. 2007;5(3):233-41.
27. Lamarche PA, Beaulieu MD, Pineault R,
Contandriopoulos AP, Denis JL, Haggerty
J. Choices for change: the path for restructuring primary healthcare services in
Canada. Ottawa (ON): Canadian Health
Services Research Foundation; 2003.
28. Schoen C, Osborn R, Doty MM, Bishop M,
Peugh J, Murukutla N. Toward higher-performance health systems: adults’ health care
experiences in seven countries, 2007. Health
Aff (Millwood). 2007;26(6):w717-34.
29. Canadian Institute for Health Information.
Experiences with primary health care in
Canada. Ottawa (ON): Canadian Institute
for Health Information; 2009 [cited 2010
May 4]. Available from: http://secure.cihi
.ca/cihiweb/products/cse_phc_aib_en.pdf
30. Sanmartin C, Ross N. Experiencing difficulties
accessing first-contact health services in
Canada: Canadians without regular doctors
and recent immigrants have difficulties
accessing first-contact healthcare services.
Reports on difficulties in accessing care
vary by age, sex and region. Healthc Policy.
2006;1(2):103-19.
31. Nutting PA, Goodwin MA, Flocke SA,
Zyzanski SJ, Stange KC. Continuity of
primary care: to whom does it matter and
when? Ann Fam Med. 2003;1(3):149-55.
32. Haggerty JL, Pineault R, Beaulieu MD,
Brunelle Y, Gauthier J, Goulet F, et al. Room for
improvement: patients’ experiences of primary care in Quebec before major reforms.
Can Fam Physician. 2007;53(6):1056-7.
33. Starfield B. Primary Care: Balancing health
needs, services and technology. New York:
Oxford University Press; 1998.
34. Christakis DA. Continuity of care: process or
outcome? Ann Fam Med. 2003;1(3):131-3.
120
Vol 31, No 3, June 2011 – Chronic Diseases and Injuries in Canada
An assessment of the barriers to accessing food among
food-insecure people in Cobourg, Ontario
S. Tsang, MHSc, RD (1); A.M. Holt, MHSc (2); E. Azevedo, MSc, RD (1)
Abstract
Introduction: Low-income people are most vulnerable to food insecurity; many turn
to community and/or charitable food programs to receive free or low-cost food. This needs
assessment aims to collect information on the barriers to accessing food programs, the
opportunities for improving food access, the barriers to eating fresh vegetables and fruit,
and the opportunities to increasing their consumption among food-insecure people
in Cobourg, Ontario.
Methods: We interviewed food program clients using structured individual interviews
consisting of mostly opened-ended questions.
Results: Food program clients identified barriers to using food programs as lack of transportation and the food programs having insufficient quantities of food or inconvenient
operating hours. They also stated a lack of available vegetables and fruit at home, and
income as barriers to eating more vegetables and fruit, but suggested a local fresh fruit
and vegetable bulk-buying program called “Good Food Box” and community gardens
as opportunities to help increase their vegetable and fruit intake.
Discussion: Many of the barriers and opportunities identified can be addressed by working
with community partners to help low-income individuals become more food secure.
Keywords: nutrition, low-income population, poverty, healthy food, accessibility, fruit,
vegetables, food insecurity, Ontario
Introduction
The link between low-income and health
is well documented: people at the lowest
socio-economic level are at risk of developing
chronic diseases, including heart disease,
diabetes, chronic respiratory diseases
and cancer, and of dying prematurely.1-13
Previous studies report that income greatly
impacts food accessibility, which in turn
influences food consumption, especially of
nutritious food required to keep healthy.14-19
Individuals who have limited physical and
economic access to safe, nutritious, and
personally acceptable food are defined as
food insecure.20-21 People in low-income
groups are most vulnerable to food insecurity; they include single-parent families,
those receiving social assistance, those
who reside in rented dwellings, the homeless, the working poor, the unemployed,
unskilled and semi-skilled workers, people
with literacy needs, people with mental
illness and addictions, teenage parents,
and those with disabilities.22
In Ontario, 47.2% of households earning
less than $10,000 before tax are food insecure,
compared to only 1.8%, 5.2% and 14.4%
for households in the highest, upper middle,
and middle-income categories, respectively.23
Food-insecure individuals turn to community
food programs, such as community gardens
and kitchens, or charitable food programs,
such as food banks, or both, to receive free
or low-cost food to help alleviate some
of their financial constraints.
The purpose of this needs assessment
is to collect information on the barriers
to accessing food programs, whether community- or charity-based; the opportunities for improving food access; the barriers
to eating vegetables and fruit; and the
opportunities to increasing the consumption
of vegetables and fruit among food-insecure
people in Cobourg, Ontario.
Background
Cobourg is located in the province of Ontario,
approximately 110 kilometres east of
Toronto. It is the largest urban-like centre in
Northumberland County, which is made
up of mostly rural communities. The population in 2006 was 18 210, with the majority
aged over 25 years.24 At that time it was
home to 5235 families, with 18% of these
being single-parent families.24 The unemployment rate was 6.7%, compared to 6.4%
for Ontario.24 About 7% of Cobourg’s population was low-income before tax.24
Cobourg has a public transportation system
of two fixed bus routes. There are four
major grocery chain stores, two of which
Author references
1. Chronic Disease & Injury Prevention Department; Haliburton, Kawartha, Pine Ridge District Health Unit, Port Hope, Ontario, Canada
2. Epidemiology & Evaluation Services; Haliburton, Kawartha, Pine Ridge District Health Unit, Port Hope, Ontario, Canada
Correspondence: Sarah Tsang, Public Health Dietitian, Chronic Disease and Injury Prevention Department, Haliburton, Kawartha, Pine Ridge District Health Unit, 200 Rose Glen Road;
Port Hope ON L1A 3V6; Tel.: (905) 885-9100 ext 497; Fax: (905) 885-9551; Email: [email protected]
Vol 31, No 3, June 2011 – Chronic Diseases and Injuries in Canada
121
are discount food stores. There is one
food bank, one free lunch program, one
community garden, and a handful of
charitable community organizations that
manage pantries of donated foods that
are available for free to any food-insecure
person. The food bank is open every
Wednesday and Friday for three hours in
the morning, and clients are able to access
it two times per month. The free lunch
program is available every day of the week
for one hour to anyone in need. Charitable
community organizations that manage
food pantries are opened during their normal
business hours.
Methods
We used a convenience sample to gather
information from adults who had used
services such as food banks and counselling
programs at least once.
Potential respondents were recruited at two
local non-governmental organizations that
manage charitable food programs but
whose primary mandate is not the provision
of food. We chose these particular charitable
food programs because they are located in
safe and friendly neighbourhoods, which
facilitated the recruitment and the interview
process. Also, these two organizations
reach people who use any of the available
charitable food programs, as well as a
broader spectrum of food-insecure people.
Four members of a local food security
committee volunteered to be trained to
conduct interviews. The needs assessment
was advertised on flyers posted at the
designated locations. Interview respondents
were recruited using two different sampling
strategies: at one location, two trained
interviewers approached food program
clients with a standard script; at the other,
an individual who had a relationship with
many of the food program clients facilitated
recruitment of potential respondents. Both
recruitment methods requested voluntary
participation. Potential respondents were
told of the purpose of the needs assessment and assured confidentiality; consent
was verbal. They were shown to a quiet
corner or a separate room to be interviewed
by the two trained interviewers using
the interview guide. In total, 35 people
completed the interview, after which every
respondent received an information letter
describing the needs assessment and
detailing the consent process.
The interview guide consisted of structured,
open-ended questions and several closedended questions. Prior to starting this
needs assessment, the interview guide was
reviewed by a member of the local food
security committee and health unit staff, and
piloted-tested with a sample of food bank
recipients from another municipality. The
questions were about barriers to using and
opportunities for improving access to food
programs; barriers to and opportunities for
eating vegetables and fruit; and the respondents’ own definitions of what it means to have
enough food. The interviewers took notes
of the respondents’ keywords and phrases,
or explanations of their answers, and recorded
descriptions of their body language to provide additional context to the answer. The
interviewers checked the trustworthiness
of the data they had recorded by periodically
repeating the response to verify their understanding and interpretation of what the
respondents had said.
At the end of each day, all the interviewers
were debriefed so as to analyze the written
responses and the interviewers’ thoughts,
feelings and insights about each interview.
The needs assessment protocol was reviewed
for ethical consideration in accordance
with established standards of the Haliburton,
Kawartha, Pine Ridge District Health Unit.
Data analysis
Using framework analysis, we qualitatively
analyzed all the responses to open-ended
questions and all field notes recorded for
both open- and closed-ended questions.25
Framework analysis is a qualitative method
ideally suited to studies with specific questions, a limited time frame, a convenience
sample and a priori objectives, such as the
barriers and opportunities assessed in our
study.26 Tallies and percentages to each
closed-ended question and the demographics were calculated separately. The data
were analyzed throughout and after the
data collection process, enabling the lead
researcher to identify the point when data
saturation was reached.
122
Using La Pelle’s methods, answers and field
notes to all interview questions were entered
into a table formatted in Microsoft Word.27
Data were coded using a thematic framework
developed a priori from the needs assessment objectives.25 Expressions indicating
barriers or opportunities were marked with
colours and different fonts. A separate document was created to group all expressions
of barriers and opportunities together.28
The grouped expressions were then separated
into (1) barriers and opportunities according
to their question number and reference to
food programs in general; (2) reasons for
accessing food programs more than once
a month; and (3) vegetables and fruit
consumption. These distinct clusters were
then analyzed for common subthemes.
One question from the standard script
interview, “What does ‘having enough
food’ mean to you?” did not fit into the
a priori framework. Rather, the question
gave context and meaning to food insecurity
as experienced locally by individuals and
households. For this question, themes were
generated as they surfaced from the data
without the use of an a priori framework.
All of the raw data were analyzed independently by two investigators using the same
framework, and their analysis was reviewed
by a third. The three investigators discussed
any discrepancies to reach a consensus
on the categories.
Results
Table 1 shows the characteristics and the
household make-up of the respondents.
Of the 35 respondents who completed an
interview, 43% said that if there were no
restrictions, they wished they could access
food programs once a week (data not
shown). All of the respondents said they
enjoy eating vegetables, while 97% said
they enjoy eating fruit. Only 23% said they
are able to get as much vegetables and
fruit as they want.
Barriers to using food programs
The most common barrier mentioned by the
respondents was transportation, as 14
respondents (40%) either lacked the means
Vol 31, No 3, June 2011 – Chronic Diseases and Injuries in Canada
TABLE 1
Characteristics of respondents (N = 35) who completed a needs assessment interview about barriers
to accessing food programs and to eating vegetables and fruit.
Number of respondents,
n
Percentage of respondents,
%
31
89
4
11
18–29 years
5
14
30–39 years
12
34
40–49 years
12
34
50–59 years
5
14
60–69 years
1
3
70+ years
0
0
30
86
5
14
9
26
26
74
None
12
34
Children 12 years and under
18
51
Children 13–18 years
10
29
0
13
37
1
15
43
2
5
14
3
2
6
Ontario Works
10
29
Ontario Disability Support Program
11
31
Ontario Child Care Supplement for Working Families
5
14
Canada Pension Plan Disability (CPPD)
0
0
Canada Pension Plan (CPP)
3
9
Old Age Security Program
2
6
Ontario Student Assistance Program
0
0
Regular employment
22
63
Employment Insurance (EI)
22
63
Workplace Safety and Insurance Board (WSIB) Benefits
0
0
Other
2
6
None
0
0
Group
Sex
Female
Male
Age
Place of residence
Cobourg
Outside Cobourg
Interview request approach
Interviewers approached potential respondents directly
Interviewers introduced to potential respondents by an individual who had
a relationship with the respondents
Children in the householda
People working in the household
Source of household incomeb
a
Some households include children in both age groups (less than 12 years, 13–18 years), hence the percentages add up to more than 100.
b
Some households have more than one source of income, hence the percentages add up to more than 100.
Vol 31, No 3, June 2011 – Chronic Diseases and Injuries in Canada
123
to get to the program location (no vehicle,
no access to rides) or had difficulty walking
home with large boxes of food. Certain
foodstuffs in the food banks, such as milk,
pasta, and peanut butter, were quickly
depleted, and 6 respondents (17%) mentioned that they receive insufficient quantities of food for themselves and their
household. One single, middle-aged woman
exclaimed about the food banks’ food supply in general, “It’s the food—running out
of food all the time.” Another respondent,
a mother of two younger children and two
teenagers, explained, “The food bank don’t
[sic] give enough food.” Ten respondents
(29%) complained that the food programs
are not open for long enough during the
day or throughout the month, and that the
times of operation conflict with their personal schedules. One woman explained the
current operation of the food bank: “[the
food bank] now opens 10 [a.m.] to 1 [p.m.],
but [I] would like [it to be open] from
9 [a.m.] to 4 [p.m.].” Other barriers were
not knowing where food programs are
located throughout the community; the
quality of food, which is described as
being mostly “junk food;” the need to show
personal identification; not being able to
choose preferred food; and that the food
bank service area was too small and could
not be accessed by people in wheelchairs
or with children in strollers. Regarding food
quality, a mother of two recounted, “I got
home once to find 50 percent or more [of
the food from the food bank] are [sic] fruit
cakes, doughnuts, cookies, and I cried…
I thought, how can I feed my child?”
Opportunities for improving food
program access
Three respondents suggested opening food
programs on more days of the week and
during morning, afternoon and evening
hours. One mother of three said, “Most
programs [are] open Monday, Wednesday,
Friday…[It would be] nice if something
[was] available other than those days.”
Several others expressed the theme of social
support networks, where people help
each other by growing food and sharing
together or making sure there is enough
food remaining for the next individual.
A part-time working mother of two children
explained her ideal barrier-free food bank
system, “Have to be fair to other people—don’t
be greedy or selfish—don’t be taking too
much, just enough to get by.” Finally, thirteen
respondents (37%) reported very few or no
barriers to using food programs.
Barriers to eating vegetables and fruit
Twelve respondents (34%) mentioned that
not having enough vegetables and fruit was
a barrier to eating them. A part-time working
mother of one stated that she does not need
encouragement to eat more vegetables and/or
fruit. Rather, she said, “[I] don’t eat them
because I don’t have them [in my home].”
Another single mother of three explained why
she does not eat more vegetables or fruit in
the context of food insecurity, “If I knew I
had enough for my boys, I myself would eat
more.” Not having enough money to afford
vegetables or fruit, and vegetables and
fruit being expensive were other common
themes. When asked “What would encourage
you to eat more vegetables and/or fruit”,
an unemployed, single, middle-aged man
replied, “[I] don’t make enough money.
If I had more money, I’[d] make sure to buy
some fruit.” A working mother of two who
is the sole breadwinner of the household
described what might help her get more
fruits and vegetables, “more money…they
say [vegetables and fruit] are cheaper, but
[they’re] not.”
Opportunities for increasing consumption
of vegetables and fruit
Eleven respondents (31%) suggested that the
food program use or offer a local fresh fruit
and vegetable bulk-buying program, the
“Good Food Box,”* as a way to help increase
their vegetable and fruit consumption.
Sixteen respondents (46%) stated that the
affordability of vegetables and fruit and their
availability at food programs are factors
in how much they consume them. Ten
respondents (29%) mentioned having or
joining a gardening program, or having
a garden or more room to grow their own
vegetables and fruits. Ten respondents (29%)
also mentioned that they would eat more
vegetables and fruit if they knew more
about the benefits of eating these, if they
had recipes and/or took cooking classes,
and if they knew how to keep vegetables
and fruit longer without spoilage.
Reasons for accessing food programs more
than once a month
Seven respondents (20%) explained that
they need to return to different food banks
in the greater region several times each
month because they do not receive enough
food at any one particular location. A part-time
working mother of two described her experience with a food bank, “We get one can
of tomato soup for two weeks and a bag of
pasta for a family of six…It’s not enough!”
Two respondents commented on the lack of
variety of food at food banks; one full-time
working mother of two explained why she
visits several food outlets during the month,
including food banks: “I don’t get balanced
nutrition…I can’t hit all four food groups
going to food banks.” Two respondents
explained that visiting only one food bank
limited their choice; one non-working
mother of two teenagers stated, “[a certain
food bank]—they decided for me…I don’t
need mushrooms, beans and tomatoes.”
Fourteen respondents (40%) said that they
wish they could access several food programs
each week.
Having enough food means…
For fourteen respondents (40%), having
enough food meant being able to feed
their children healthy, nutritious diets
that included a variety of foods. A single,
part-time employed mother of two had
this to say about having enough food:
“[It] doesn’t even mean choice…have one
thing from each food group to give to [the]
children and myself at every meal—make
do with what you have.” Having peace
of mind that “everyone in the family has
all they need” and not worrying about
budgeting or the children going hungry
also represented having enough food.
One part-time employed mother defined
having enough food as “knowing there’s
enough food in the fridge or cupboard
until the next time I’m getting a cheque.”
*http://www.foodshare.net/goodfoodbox01.htm
124
Vol 31, No 3, June 2011 – Chronic Diseases and Injuries in Canada
Five respondents (14%) equated having
an adequate amount of food to being able
to eat several times in the day or allowing
the children to eat as much food as they
could. Seven respondents (20%) also reported
wanting to be able to eat healthy meals
on a regular basis and “feed their entire
family every day.”
Discussion
In this needs assessment, we found that
(1) transportation, food quantity and food
program hours limit food access; (2) that
availability and income hinder vegetable
and fruit consumption for food-insecure
individuals; (3) that food quantity and
quality caused respondents to visit food
programs more than once a month; and
that (4) being able to feed the children
in the household adequate quantities of
nutritious food was a common definition
of having enough food.
Several studies assessing charitable food
programs found that recipients commonly
receive insufficient quantities of food and
that what there is is of poor quality.29-31
Teron and Tarasuk assessed 85 food hampers
received by Toronto Daily Food Bank clients
and found that over half of the households
with three or more persons received less than
a three-day supply of food.29 In addition,
over 78% of the food hampers contained
at least one damaged or out-dated food
item.29 Hamelin et al. suggested that for
low-income food-insecure households meeting basic physical needs by having enough
food to eat is just as important as having
a diverse, balanced diet.32,33 Respondents
in our needs assessment also expressed
the importance of fulfilling their basic
physical need through quantity and quality
of food; not having this need met may be
one of the reasons why almost half of the
respondents wished they could access food
programs and services more often, i.e.
once a week.
Most of the respondents in our needs
assessment were mothers. Other Canadian
studies also found that it was vitally important to mothers that their children received
optimal nutrition.33-36 They equated having
enough food with providing for their children. These mothers go to great lengths
to satisfy their children’s hunger, opting
to visit food programs several times each
month, despite the stigma associated with
using food banks and the feeling of loss of
dignity33,37.
Because food banks and other similar types
of programs are so dependent on charity
or donated products, there is no guarantee
of the stock levels or type of foods distributed at any one location at a particular
time. This makes them unreliable as a food
outlet source for food-insecure individuals
who depend on the programs simply to feed
their families from day to day.22,29,32,33
Many respondents said that transportation
is a barrier to their using food programs.
This finding is not exclusive to low-income
individuals, as a recent study conducted
with all Northumberland County residents
reported transportation as one of the top
three concerns in the county.38 For low-income
individuals who barely get by paying for
basic living necessities, public transportation is a luxury,39 and for the few who are
able to afford a vehicle, these are typically
unreliable or non-functioning.40 Our needs
assessment indicated that walking is the
primary or preferred mode of transportation
because of its low cost; of course, carrying
food supplies makes the return trip problematic. Exploring the experiences of lowincome mothers caring for children, Bostock
pointed out that 82% of the mothers did
not own a car and relied on walking to get to
places;41 since they found walking stressful
and physically tiring, they were confined
to accessing only those resources that were
within walking distance. In short, lack of
transportation restricts an individual’s way
of life and their access to resources, such as
the quantity of food one can carry back home.
In our needs assessment, many interviewees
commented that they would eat more vegetables and fruit if such fresh produce was
available in their homes. Further discussion
revealed that the underlying reason for the
lack of vegetables and fruit in the home is
that fresh produce is unaffordable and not
readily available through food programs.
Previous studies show that individuals at the
lowest socio-economic status tend to eat
fewer vegetables and fruit than people of
higher socio-economic status.42-48 Health
Vol 31, No 3, June 2011 – Chronic Diseases and Injuries in Canada
125
Canada recommends that adults aged 19 to
50 years eat a minimum of seven servings
of vegetables and fruit daily.49 However, for
those living on a low income, the price of
vegetables and fruit often precludes eating
the recommended number of servings.
Along with other social determinants such
as employment, housing, education, and
access to services, income has a profound
effect on individual health and the health
of a community;50-52 some argue that it is
the most important determinant of health.53,54
Although our findings are consistent with
the literature on the barriers to food access,
our study also has a number of limitations.
First, to reduce intimidation and thus
increase participation, interviews were not
tape-recorded. The interviewers played a dual
role as both interviewer and recorder. In such
instances, interviewers may either elicit
important information but forget to record
it verbatim, or they may record diligently
but forget to probe for clarification when
necessary. There may also be interviewer
bias as interviewers must quickly filter
responses to note keywords, phrases, or
sentences spoken by each respondent.
This subjects the data to a preliminary level
of sorting and analysis, which may vary
slightly from interviewer to interviewer, and it
is difficult to ascertain the extent to which
interviewers have filtered the information.
Second, more interviews took place at one
location than the other. Consequently, the
sample population may not be representative
of all food-insecure individuals.
Despite the limitations, this needs assessment
has highlighted the need to address:
1) Food availability: working to ensure that
certain types of food will be available at
food programs and that sufficient quantities
of food is given relative to household size;
2) Transportation: working to ensure that
affordable public transportation is available
to get to and from food program locations;
3) Supportive networks: working to enhance
social networking opportunities so that
people can support each other’s needs;
4) Local fresh fruit and vegetable bulk-buying program: working to ensure that the
program is affordable especially for lowincome families and individuals.
5) Community gardening: working to generate
interest and skills around community gardens
to help increase vegetable and fruit intake.
Addressing these food access issues would
present a new set of challenges that would
need to be considered. It is crucial, then, that
everyone, community partners and local
communities alike, work together in a concerted effort to overcome the obstacles.
Programs such as food banks and soup
kitchens were never meant to be long-term
services. They were originally intended to
temporarily relieve people facing economic
trouble so that they could direct their
finances towards bill payments and other
basic living necessities. However, such programs have become permanent and will
not be eliminated unless other socioeconomic
factors, such as transportation, employment, education, childcare and affordable
housing, are addressed in tandem. While
there is still a long way to go in eliminating
such social challenges, individuals in the
interim can help break down barriers and
reduce the risk factors of chronic diseases
by addressing food access first. This research
will help inform local decision-making and
strengthen programming in the area of
food security.
Algoma University, Dr. Lynn Scruby, assistant professor of the Faculty of Nursing
at University of Manitoba, and Dr. Valerie
Tarasuk, professor of the Dalla Lana School
of Public Health at University of Toronto
for their comments on the preliminary
research methodology.
References
1. Gordon D, Shaw M, Dorling D, Davey
Smith G, editors. Inequalities in health:
the evidence presented to the independent
inquiry into inequalities in health. Bristol
(UK): Policy Press; 1999. (Studies in poverty,
inequality and social exclusion.)
2.
Sram I, Ashton J. Millennium report to Sir
Edwin Chadwick. Br Med J. 1998;317:592-6.
3.
Pantazis C, Gordon D. Tackling inequalities:
Where are we now and what can be done?
Bristol (UK): Policy Press; 2000. (Studies in
poverty, inequality and social exclusion.)
4. World Health Organization. Preventing
chronic diseases: a vital investment [Internet].
Geneva (CH): World Health Organization;
2005 [cited 2010 Jan 27]. Available from:
http://www.who.int/chp/chronic_disease
_report/contents/en/index.html
5.
Acknowledgements
We would like to thank the Canadian Cancer
Society, GTA Cancer Prevention and Screening
Network for their financial support of this
research. We would like to acknowledge
the two non-governmental organizations
where we recruited the respondents for
their assistance with data collection and
recruitment. We thank the participants who
shared their experiences and stories with
us. We would also like to acknowledge
Ms. Lesley Hamilton, executive director
of Literacy Ontario Central South, and
Ms. Sasha Korper, early literacy consultant,
for their assistance with the readability and
literacy level of our information letter to
participants. Finally, we would like to thank
Dr. Gayle Broad, assistant professor at
Lynch J, Smith GD, Hillemeier M, Shaw M,
Raghunathan T, Kaplan G. Income inequality,
the psychosocial environment, and health:
comparisons of wealthy nations. Lancet.
2001;358(9277):194-200.
6. Wilkins R, Berthelot JM, Ng E. Trends in
mortality by neighbourhood income in
urban Canada from 1971 to 1996. Health
Rep. 2002;13 Suppl: 45-71.
7. Gwatkin DR. Health inequalities and the
health of the poor: what do we know?
What can we do? Bull World Health Organ.
2000;78(1):3-18.
8. Williamson DL. The role of the health
sector in addressing poverty. Can J Public
Health. 2001;92(3):178-83.
9.
Gyorfi-Dyke E. Poverty and chronic disease:
recommendations for action [Internet].
Ottawa (ON): Chronic Disease Prevention
Alliance of Canada; 2008 [cited 2010 Jan 27].
126
Available from: http://www.healthyenvironmentforkids.ca/sites/healthyenvironmentforkids.ca/files/cpche-resources/CDandPoverty_CDPAC.pdf
10. Archeson D. Independent inquiry into
inequalities in health [Internet]. United
Kingdom: Her Majesty Stationary Office;
1998 [cited 2009 Dec 9]. Available from:
http://www.archive.official-documents.co.uk
/document/doh/ih/ih.htm
11. Lightman E, Mitchell A, Wilson B. Poverty
is making us sick: a comprehensive survey
of income and health in Canada. Toronto
(ON): Wellesley Institute; 2008.
12. Wilson B. Sick and tired: the compromised
health of social assistance recipients and
the working poor in Ontario. Toronto (ON):
The Community Social Planning Council of
Toronto (CSPC-T); 2009.
13. Lightman E, Herd D, Mitchell A. Precarious
lives: work, health and hunger among welfare recipients in Toronto. J Policy Prac.
2008;7(4):242-59.
14. Vozoris N, Davis B, Tarasuk V. The affordability of a nutritious diet for households
on welfare in Toronto. Can J Public Health.
2002;93(1):36-41.
15. Riches G. Food banks and the welfare crisis.
Ottawa (ON): Lorimer; 1986.
16.Kirkpatrick SI, Tarasuk V. Adequacy
of food spending is related to housing expenditures among lower-income
Canadian households. Public Health Nutr.
2007;10(12);1464-73.
17. Williams PL, Johnson CP, Kratzmann ML,
Johnson CS, Anderson BJ, Chenhall C.
Can households earning minimum wage in
Nova Scotia afford a nutritious diet? Can J
Public Health. 2006;97(6):430-4.
18. Tarasuk V, McIntyre L, Li J. Low-income
women’s dietary intakes are sensitive to the
depletion of household resources in one
month. J Nutr. 2007;137:1980-7.
19. Kirkpatrick SI, Tarasuk V. Food insecurity
is associated with nutrient inadequacies
Vol 31, No 3, June 2011 – Chronic Diseases and Injuries in Canada
among Canadian adults and adolescents.
J Nutr. 2008;138:604-12.
20. Agriculture and Agri-Food Canada. Canada’s
action plan for food security: in response
to the World Food Summit Plan for Action
[Internet]. Ottawa (ON): Agriculture and
Agri-Food Canada; 1998 [cited 2009 Oct
29]. Available from: http://www.agr.gc.ca
/misb/fsec-seca/pdf/action_e.pdf
21. Dietitians of Canada. Community food
security: position of Dietitians of Canada
[Internet]. Toronto: Dietitians of Canada;
2007 [cited 2009 Apr 9]. Available from:
http://www.dietitians.ca/Dietitians-View
/Community-Food-Security.aspx
22. Dietitians of Canada. Individual and household food insecurity in Canada: position of
Dietitians of Canada [Internet]. Toronto:
Dietitians of Canada; 2005 [cited 2009
Apr 9]. Available from: http://www.dietitians.ca/Dietitians-View/Individual-and
-Household-Food-Insecurity.aspx
23. Vogt J, Tarasuk V. Analysis of Ontario
sample in cycle 2.2 of the Canadian
Community Health Survey, 2004 [Internet].
Ontario: Public Health Research, Education
and Development; 2007 [cited 2009 Jan 8].
Available from: http://www.phred-redsp
.on.ca/CCHSReport.htm
24. Statistics Canada. 2006 Community profiles
census division [Internet]. Ottawa (ON):
Statistics Canada; 2009 [cited 2009 Dec 3].
Available from: http://www12.statcan.ca/
census-recensement/2006/dp-pd/prof/92
-591/index.cfm
25. Lacey A, Luff D. Qualitative data analysis
[Internet]. Nottingham (UK): The NIHR
Research Design Service for the East
Midlands; 2007 [updated 2009; cited 2009
Oct 29]. Available from: http://www.rds
-eastmidlands.org.uk/resources/cat_view
/13-resource-packs.html?start=5
26. Srivastava A, Thomson SB. Framework analysis: a qualitative methodology for applied
policy research. JOAAG. 2009;4(2):72-9.
27. La Pelle N. Simplifying qualitative data
analysis using general purpose software
tools. Field Method. 2004;16(1):85-108.
28. Ryan GW. Using a word processor to tag
and retrieve blocks of text. Field Method.
2004;16(1):109-30.
29. Teron AC, Tarasuk V. Charitable food assistance: what are food bank users receiving?
Can J Public Health. 1999;90(6):382-4.
30. Irwin JD, Ng VK, Rush TJ, Nguyen C, He M.
Can food banks sustain nutrient requirements?
A case study in Southwestern Ontario. Can
J Public Health. 2007;98(1):17-20.
31. Tse C, Tarasuk V. Nutritional assessment of
charitable meal programmes serving homeless people in Toronto. Public Health Nutr.
2008;11(12):1296-305.
32.Hamelin AM, Mercier C, Bedard A.
Discrepancies in households and other
stakeholders viewpoints on the food security
experience: a gap to address. Health Educ
Res. 2010;25(3):401-2.
33. Hamelin AM, Beaudry M, Habicht JP.
Characterization of household food insecurity
in Québec: food and feelings. Soc Sci Med.
2002;54:119-32.
34. McIntyre L, Glanville NT, Raine KD, Dayle JB,
Anderson B, Battaglia N. Do low-income
lone mothers compromise their nutrition to
feed their children? CMAJ 2003;168:686-91.
35.McIntyre L, Glanville NT, Officer S,
Anderson B, Raine KD, Dayle JB. Food
insecurity of low-income lone mothers and
their children in Atlantic Canada. Can J
Public Health. 2002; 93(6):411-5.
36. Tarasuk V, Maclean H. The food problems of
low income single mothers: an ethnographic
study. Can Home Econ J. 1990;40:76-82.
37. Riches G. Food banks and food security:
welfare reform, human rights and social
policy. Lessons from Canada? Soc Policy
Admin. 2002;36(6):648-63.
38. Northumberland United Way. Community
matters: community consultation final
report [Internet]. Cobourg (ON); 2006
[cited 2010 Aug 25]. Available from:
http://www.cobourg.unitedway.ca/Local
_images/cobourg/CommunityMatters.pdf
Vol 31, No 3, June 2011 – Chronic Diseases and Injuries in Canada
127
39.
Northumberland
Poverty
Reduction
Action Committee. Report from the
Northumberland Poverty Reduction Action
Committee community action day. Cobourg
(ON): Northumberland Poverty Reduction
Action Committee; 2008.
40.Garasky S, Fletcher CN, Jensen HH.
Transiting to work: the role of private
transportation for low-income households.
J Consum Aff. 2006;40(1):64-89.
41.Bostock L. Pathways of disadvantage?
Walking as a mode of transportation
among low-income mothers. Health Soc
Care Community. 2000;9(1):11-8.
42. Perez CE. Fruit and vegetable consumption.
Health Rep. 2002;13(3):23-31.
43. Subar AF, Heimendinger J, Patterson BH.
Fruit and vegetable intake in the United
States: the baseline survey of the Five-A-Day
for Better Health Program. Am J Health
Promot. 1995;9(5):352-60.
44. Xie B, Gilliland FD, Li YF, Rockett HRH.
Effects of ethnicity, family income, and
education on dietary intake among adolescents. Prev Med. 2003;36:30-40.
45. Giskes K, Turrell G, Patterson C, Newman B.
Socioeconomic differences among Australian
adults in consumption of fruit and vegetables and intakes of vitamins A, C and
folate. J Hum Nutr Diet. 2002;15:375-85.
46. Mishra G, Ball K, Arbuckle J, Crawford D.
Dietary patterns of Australian adults and
their association with socioeconomic status:
results from the 1995 National Nutrition
Survey. Eur J Clin Nutr. 2002;56:687-93.
47. Reicks M, Randall RL, Haynes BJ. Factors
affecting consumption of fruits and vegetables
by low-income families. J Am Diet Assoc.
1994;94(11):1309-11.
48. Kirkpatrick S, Tarasuk V. The relationship
between low income and household food
expenditure patterns in Canada. Public
Health Nutr. 2003;6(6):589-97.
49. Health Canada. Eating well with Canada’s
Food Guide [Internet]. Ottawa (ON): Health
Canada; 2009 [cited 2009 Jan 7]. Available
from: http://www.hc-sc.gc.ca/fn-an/food
-guide-aliment/index-eng.php
50. Wilkinson R, Marmot M, editors. Social
determinants of health: the solid facts. 2nd
ed [Internet]. Copenhagen (DK): World
Health Organization; 2003 [cited on 2009
Dec 3]. Available from: http://www.euro
.who.int/DOCUMENT/E81384.PDF
51. Raphael D. Health effects of economic inequality. Can Rev Soc Policy. 1999;44:25-40.
52. Raphael D. Health inequalities in Canada:
current discourses and implications for
public health action. Crit Public Health.
2000;10:193-216.
53. Raphael D. Poverty, income inequality,
and health in Canada [Internet]. Toronto
(ON): The CSJ Foundation for Research
and Education; 2002 [cited 2009 Dec 3].
Available from: http://www.socialjustice
.org/uploads/pubs/PovertyIncomeInequalityandHealthinCanada.pdf
54. Commission on Social Determinants of
Health. Closing the gap in a generation:
health equity through action on the social
determinants of health. Final report of
the Commission on Social Determinants
of Health. Geneva (CH): World Health
Organization; 2008. Available from: http://
www.who.int/social_determinants/thecommission/finalreport/en/index.html
128
Vol 31, No 3, June 2011 – Chronic Diseases and Injuries in Canada
Estimates of the treated prevalence of bipolar disorders by
mental health services in the general population: comparison
of results from administrative and health survey data
A.G. Bulloch, PhD (1); S. Currie, PhD (2); L. Guyn, BSc, BA (2); J.V. Williams, MSc (1); D.H. Lavorato, MSc (1);
S.B. Patten, MD, PhD (1)
Abstract
Introduction: Informed provision of population mental health services requires accurate
estimates of disease burden.
Methods: We estimated the treated prevalence of bipolar disorders by mental health services
in the Calgary Zone, a catchment area in Alberta with a population of over one million.
Administrative data in a central repository provides information of mental health care
contacts for about 95% of publically funded mental health services. We compared this
treated prevalence against self-reported data in the 2002 Canadian Community Health
Survey: Mental Health and Well-Being (CCHS 1.2).
Results: Of the 63 016 individuals aged 18 years plus treated in the Calgary Zone in
2002–2008, 3659 (5.81%) and 1065 (1.70%) were diagnosed with bipolar I and bipolar
II disorder, respectively. The estimated treated population prevalence of these disorders
was 0.41% and 0.12%, respectively. We estimated that 0.44% to 1.17% of the Canadian
population was being treated by psychiatrists for bipolar I disorder from CCHS 1.2.
Discussion: For bipolar I disorder the estimate based on local administrative data is close to the
lower end of the health survey range. The degree of agreement in our estimates reinforces
the utility of administrative data repositories in the surveillance of chronic mental disorders.
Keywords: bipolar disorder, administrative data, health surveys, prevalence
Introduction
Accurate estimates of the disease burden
of mental disorders in the population are
necessary to provide adequate mental health
services. Traditionally, estimates of the prevalence of mental disorders in the general
population have used data from health
surveys carried out either in person and/
or by telephone. However, such health
surveys suffer from a number of shortcomings. For example, the 2002 Canadian
Community Health Survey: Mental Health
and Well-Being (CCHS 1.2),1 which estimated
the prevalence of mental disorders and the
use of health services, relies on self-report
data rather than on professional diagnosis.
Though this data is obtained by trained
personnel through face-to-face interviews,
it is subject to recall bias; hence the possible
value of estimates based on other sources
of data.
In Canada, the public health care sector
provides the majority of health services,
including treatment for addictions and
mental disorders. Detailed information on the
recipients of health services are captured
in various administrative datasets. This
information is easily accessible, and its use
for research purposes is cost effective.2 Such
databases provide a “real-world” perspective on treatment of mental disorders that
generalize to the actual practice of providing
mental health services. Further, administrative
datasets can provide precise estimates of
treated prevalence and avoid the recall bias
of health surveys.3 As such, they can contribute significantly towards increasing the
capacity for national health surveillance.4
Administrative data on mental health has
been used to research the effects of system
changes on service use and quality of care,5
variations in treatment practices across settings,6 performance measurement including
adherence to best practices,7 predictors of
service utilization,8 determining the proportion of the general population with mental
disorders who receive treatment,9,10 the
cost effectiveness of mental health services,11
place-based population health research2
and long-term evaluation of changes in the
use of psychiatric emergency services.12
The Calgary Zone is one of five defined
catchment areas for the province of Alberta.
All public health services in Alberta are
under a single governing body called Alberta
Health Services (AHS). The Calgary Zone
covers a geographic area of 39 000 square
kilometres and has a population of over 1.3
million inhabitants. It includes one large
Author references
1. Department of Community Health Sciences and Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
2. Mental Health Information Management, Evaluation & Research, Alberta Health Services, Addiction & Mental Health, Calgary Zone, Calgary, Alberta, Canada
Correspondence: Andrew Bulloch, Mental Health Centre for Research and Education, Hotchkiss Brain Institute, TRW Building, University of Calgary, 3280 Hospital Dr NW,
Calgary AB T2N 4Z6; Tel.: (403) 220-4586; Fax: (403) 210-8840; Email: [email protected]
Vol 31, No 3, June 2011 – Chronic Diseases and Injuries in Canada
129
urban city (Calgary) and several smaller
cities and towns including Banff, Airdrie,
Okotoks and Canmore. The Calgary Zone
provides a wide range of adult addiction
and mental health services including
specialized inpatient treatment in three
large urban hospitals, day hospital services,
outpatient programs including one clinic
that specializes in bipolar disorder, and
community outreach programs. People with
bipolar disorder can access any of these
services at no personal cost.
The use of a central data repository created
by linking administrative data from separate
information systems is an innovative way
of deriving period prevalence estimates for
treated mental health conditions. It is a
different approach to that taken by most
record linkage studies in Canada, for which
family doctor visits or hospitalizations are
the primary patient encounters. The data
repository maintained in the Calgary Zone
links data from the entire spectrum of psychiatric services, including inpatient, day
hospital, outpatient, and community outreach
programs. As such, this data repository
is unique, although it does resemble the
now defunct Kingston Psychiatric Record
Linkage System.13 The majority of research
using administrative data is conducted on
acute care service users. However, many
people with mental disorders never require
hospitalization or emergency psychiatric
care. Physician billing records are also limited
for estimating the prevalence of specific
mental disorders; in Alberta, physicians
are required to submit only the first three
digits of the ICD-9* code that identifies
the patient as having either a depressive
or bipolar mood disorder, for example.
In addition, alternative relationship plans
may preclude access to physician billing data
since these plans replace fee-for-service
billings. For example, in a multidisciplinary
setting physicians may be paid through
sessional arrangements that do not require
submission of a diagnostic code as part of
a fee-for-service submission or they may
not be required to submit a fee-for-service
billing at all.
Bipolar disorders can be devastating; they
usually begin in early life and are associated with a high risk of suicide.14 Bipolar
I disorder is characterized by one or more
manic or mixed episodes that may or
may not be accompanied by one or more
episodes of major depression.15 Symptoms
of mania include flight of ideas or racing
thoughts, inflated self-esteem, decreased
need for sleep, talkativeness and irritability. Bipolar II disorder is characterized by
hypomanic episodes that, in contrast to
manic episodes, are not severe enough
to cause marked impairment in social or
occupational functioning, or result in hospitalization. In order to meet DSM-IV-TR†
diagnostic criteria for bipolar II disorder,
there must also be one or more episodes of
major depression.
Whereas it is often proposed that bipolar
disorders are underdiagnosed, some authors
postulate the opposite.16 One controversial
proposal is to lower the threshold for
diagnosis of bipolar disorder, which would
substantially increase estimates of its prevalence.17 Either way, it is apparent that there
is a need to evaluate the actual prevalence
in real world treatment.
The purpose of our study is to compare
estimates of the treated prevalence of
bipolar disorders from CCHS 1.2 and the
mental health service data repository
of the Calgary Zone.
Methods
This study is based on data from two sources.
National estimates of the treated prevalence
of bipolar disorder I in the general population
came from CCHS 1.2. We compared these
estimates to the calculated treated prevalence
for both bipolar I and II disorders from
administrative data in the Calgary Zone. In
terms of physician type, the administrative
data covers various mental health services
(see below), but not general physicians (GPs).
To be able to compare the 2 datasets,
we restricted our analysis of CCHS 1.2 to
psychiatrists alone.
National mental health survey
CCHS 1.2 has been described in detail
elsewhere.18 Briefly, conducted in 2002,
CCHS 1.2 was a population-based, crosssectional survey designed to monitor the
mental health of Canadians and their
need and use of mental health services.
Statistics Canada obtained a nationally
representative sample of individuals aged
15 years or older in 2002 that did not include
individuals from the three territories, armed
forces, Aboriginal populations, or living in
institutions or in some remote areas; the
response rate was 77% (n = 36 984). In the
majority of cases, trained personnel conducted
face-to-face interviews, with telephone
interviews being conducted when this was
not possible.
We received approval to access the CCHS
1.2 Master File from the Social Sciences
and Humanities Research Council, and
accessed these data at the Statistics
Canada Prairie Regional Research Data
Centre at the University of Calgary. Ethical
approval for access was acquired from
the University of Calgary Conjoint Health
Research Ethics Board.
Assessment of bipolar I disorder in CCHS 1.2
is based upon the diagnosis of manic or
mixed episodes in accordance with DSMIV-TR diagnostic criteria.13 The specific
questions on mania were based on a World
Mental Health version of the Composite
International Diagnostic Interview (WMHCIDI)19 modified for CCHS 1.2 and were
delivered by trained interviewers. Respondents
were not asked if they have bipolar disorder.
Instead, they were asked series of questions. Algorithms were then used to assess
this disorder depending on the answers
received. Two algorithms were used to
determine if manic episodes occurred in
either the last year (12-month prevalence)
or during the respondents’ lifetime (lifetime
prevalence). Separate questions asked
whether a GP or psychiatrist was treating
their disorder.
To calculate the treated prevalence of bipolar I disorder in the Canadian population,
*International Statistical Classification of Diseases and Related Health Problems, 9th Revision
Diagnostic and Statistical Manual of Mental Disorders Fourth Edition, Text Revision.
†
130
Vol 31, No 3, June 2011 – Chronic Diseases and Injuries in Canada
we cross-tabulated the raw CCHS 1.2
data and calculated population estimates
with 95% confidence intervals (CIs). (Note
that CCHS 1.2 did not survey bipolar II
disorder.) These estimates and CIs were
both weighted and bootstrapped, using
sampling weights and replicate bootstrap
weights provided by Statistics Canada, to
compensate for complex sampling procedures. For example, small provinces were
oversampled so the impact of these results
on the national estimate has to be reduced
accordingly, i.e. given less weight. Since
the sample size of bipolar cases in CCHS
1.2 was insufficient to create a separate,
reliable estimate for the province of the
Alberta, we used the national prevalence
estimates as a surrogate. While there is no
reason to believe that prevalence estimates
vary substantially across Canada, research
has shown regional differences in mental
health service use,20 and these would influence
estimates of treatment prevalence.
Administrative data
The administrative records of mental health
service users in the Calgary Zone are
maintained in a central data repository.
All these users had been seen by a mental
health professional (psychiatrist, psychiatric nurse, psychologist or social worker)
licensed in Alberta to conduct diagnostic
evaluations. For each service user there is
a minimum dataset consisting of a unique
lifetime identifier (ULI), referral source,
admission and discharge dates, length of
stay, program enrolment, age, gender,
postal code, mental health diagnoses based
on DSM-IV-TR nosology, and disposition
at discharge. Records are extracted from
over 95% of the mental health information systems used to provide services to
adult, child and adolescent, geriatric and
Aboriginal clients, and then linked into
the central database; the remaining 5% of
users engage in services in which complete
data may not obtained from the client
because of the nature of the service (e.g. in
some crisis or outreach services the clients
are not formally enrolled and ULI is not
obtained). Based on the postal codes, the
majority of mental health service users live
within the Calgary Zone.
We defined cases of bipolar illness from
the administrative dataset based on the
following criteria: (1) the patient was formally
registered in a mental health service in the
Calgary Zone; these services included
inpatient services, day hospitals, psychiatric
emergency services, outpatient clinics, and
community outreach programs; and (2)
the most responsible diagnosis (MRD)
recorded for the registration was bipolar I
or II disorder; the MRD represents the main
reason the patient was admitted to the
program in question. This case definition
excluded patients treated by other health
care workers for medical care unrelated
to their bipolar condition (e.g. dietary
consultation) and one-time visits to other
professionals for non-specific social issues
(e.g. housing). Most patients registered in
mental health have multiple diagnoses.
The presence of other diagnostic codes in
the health record did not exclude patients
as long as bipolar I or II disorder was
listed as the MRD. We were concerned
about including secondary (i.e. not MRD)
diagnoses as these may often have been
recorded as a “rule out” diagnosis on certain
visits. In all mental health services, diagnosis is made based on comprehensive
clinical assessment, although the specific
interview tools and other assessment
instruments vary across programs.
The Calgary Zone does not have a long-term
psychiatric institution although it does
have long-term care facilities for geriatric
patients. Data from these facilities are not
linked to the central data repository for
mental health services; as a result, elderly
people with bipolar illness who live in
nursing homes are not represented in our
estimate of treated prevalence unless they
had accessed one of the services covered.
We obtained aggregate estimates of the
treated prevalence of bipolar disorders from
the Information and Evaluation Unit in the
Calgary Zone. These analyses were performed “in house” as part of the functioning
of these units and did not require ethical
approval. Results from the administrative
database are expressed as a mean with
95% CI, and are not weighted since they
are not samples.
All the data we present here are for individuals 18 years and older.
Vol 31, No 3, June 2011 – Chronic Diseases and Injuries in Canada
131
Results
The basic demographics of the study populations are shown in Table 1. In CCHS 1.2,
364 and 890 respondents scored positive in
the 12-month and lifetime bipolar I algorithms, respectively. The higher proportion
of women compared to men reflects the
higher percentage of female respondents in
CCHS 1.2; the prevalence of bipolar I disorder has been estimated to be equal in men
and women in this survey.21 Data from the
Calgary Zone are very similar to that for
CCHS 1.2 as assessed by lifetime criteria.
In the case of the Calgary Zone, however,
treated prevalence was sex dependent:
significantly more men than women were
being treated for bipolar I disorder, while
the opposite was true for bipolar II disorder,
with almost two-thirds of treated patients
women. These discrepancies suggest differential help-seeking between the two
disorders by gender.
Stratification by age group (Table 1) shows
that the four study populations were similar
in terms of age distribution. The only clear
exception is the somewhat younger population that screened positive for 12-month
bipolar I disorder in CCHS 1.2 when compared
to the other 3 groups.
We used administrative data from the
Calgary Zone to estimate the treated prevalence for both bipolar disorders as 0.41%
and 0.12% for bipolar I and II disorders,
respectively (Table 2).
Data from CCHS 1.2 enabled us to estimate
the proportion of Canadians with bipolar I
disorder who sought help for their condition. (Bipolar II disorder was not included
in the survey.) We made both 12-month and
lifetime estimates since these might be
expected to bracket our 7-year administrative data estimate. These 12-month and
lifetime estimates were 0.44% and 1.17%
respectively (Table 3).
Discussion
To the best of our knowledge, we are
the first to investigate the consistency of
self-reported treatment rates with actual
administrative records for a specific mental
health disorder.
TABLE 1
Characteristics of bipolar patients in the general population of Canada, 2002, and the Calgary Zone, 2002–2008
Canadaa
(2002)
Calgary Zoneb
(2002–2008)
Bipolar I
(12-month estimate)c
(n = 364)
Bipolar I
(lifetime estimate)d
(n = 890)
Bipolar I
(n = 3659)
Bipolar II
(n = 1065)
Men
42.2%
(35.2–49.3)
46.1%
(41.6–50.5)
53.7%
(52.1–55.3)
38.5%
(35.6–41.4)
Women
57.7%
(50.7–64.8)
53.9%
(49.5–58.4)
46.3%
(44.6–47.9)
61.5%
(58.6–64.4)
34.8
(33.0–36.5)
38.7
(37.6–39.9)
40.0
(39.5–40.5)
39.5
(38.7–40.3)
18–24
26.5%
(19.9–33.1)
17.2%
(13.5–20.9)
17.0%
(15.8–18.2)
14.4%
(12.3–16.5)
25–44
49.9%
(42.7–57.0)
48.0%
(43.4–52.6)
48.4%
(46.8–50.0)
52.0%
(49.0–55.0)
45–64
23.7%
(17.7–29.6)
33.1%
(28.8–37.4)
27.8%
(26.3–29.2)
29.8%
(27.0–32.5)
—f
1.7%
(0.8–2.6)
6.8%
(6.0–7.6)
3.8%
(2.7–5.0)
Mean percentagee (95% CI)
Mean age, years
Age distribution in yearse (95% CI)
65+
Abbreviations: CCHS 1.2: 2002 Canadian Community Health Survey: Mental Health and Well-Being; CI, confidence interval; n, sample size.
a
Derived from CCHS 1.2.
b
Derived from 2002–2008 Calgary Zone administrative data repository.
c
One or more episodes in the preceding 12 months.
d
One or more lifetime episodes.
e
Percentages may not add up to 100% due to rounding.
f
Sample size is too small for release; Statistics Canada forbids the release of small cell sizes due to confidentiality concerns.
TABLE 2
Treatment by psychiatrists of bipolar I and II disorders in the population with mental health disorders, Calgary Zone, 2002–2008
Number of adults with bipolar
disorder,
n
Percentage of mental health patients
with
bipolar disordera,
%
(95% CI)
Treated prevalence of
bipolar disorder in the Calgary Zoneb,
%
(95% CI)
Bipolar I
3659
5.81
(5.63–5.99)
0.41%
(0.40–0.42)
Bipolar II
1065
1.70
(1.59–1.79)
0.12%
(0.11–0.13)
Abbreviations: CI, confidence interval; n, sample size.
a
Denominator is 63 016, i.e. the number of adults diagnosed with a mental disorder, 2002–2008.
b
Denominator is 894 905, i.e., the estimated population of the Calgary Health Region aged 18 years and older at the mid-point between 2002 and 2008.
A key element of this study is the use of
data repository rather than physician billing
data. Our results indicate that the population
survey estimate of the proportion of people
with bipolar disorder who self-report receiving
treatment from a psychiatrist approximates
the treated prevalence estimate derived from
actual administrative records of mental health
service users. The congruence of these
estimates is an important finding and has
implications for future prevalence studies:
using administrative data could be a costeffective and accessible way of accurately
estimating prevalence of a disorder in
general population.
132
Since we were unable to account for patients
who were receiving treatment by GPs and
not psychiatrists, the question arises as to
what proportion of patients in the Calgary
Zone are being treated only by GPs. Using
data from CCHS 1.2 on respondents that
screen positive for bipolar I disorder, we
estimated the prevalence of lifetime bipolar
Vol 31, No 3, June 2011 – Chronic Diseases and Injuries in Canada
TABLE 3
Treatment of bipolar Ia disorder by psychiatrists based on CCHS 1.2, 2002, Canada
Prevalence estimates
12 months
Lifetime
34 946b
34 921b
Who screened positive for bipolar I
c
357
880c
Who were being treated for bipolar I
171
430
Percentage of those who screened positive for bipolar I who receive psychiatric treatment
48.7%d
(41.8–55.6)
49.8%d
(45.1–54.4)
Percentage of CCHS respondents who receive psychiatric treatment
0.44%d
(0.36–0.52)
1.17%d
(1.02–1.33)
Number of survey respondents, n:
Overall
Abbreviations: CCHS 1.2: 2002 Canadian Community Health Survey: Mental Health and Well-Being; CI, confidence interval; n, sample size.
a
Bipolar II disorder was not included in CCHS 1.2.
b
Numbers less than the full number of CCHS 1.2 respondents (36 984) due to missing data.
c
Numbers lower than those shown in Table 1 due to missing data.
d
Weighted estimate.
I disorder in respondents aged 18 years and
over to be 2.39% (95% CI: 2.19–2.60%)‡
and the proportion treated by GPs alone to
be 0.46% (95% CI: 0.35–0.57%). In actuality,
a higher proportion of respondents (1.17%;
Table 3) receive psychiatric care, and hence
the proportion of patients receiving psychiatric care is 72%, i.e. [1.17/(1.17 + 0.46)]
x 100. This suggests that the data repository
has captured the majority (about 70%) of
patients under medical care for bipolar I
disorder in the Calgary Health Region.
What proportion of patients with bipolar
disorders is not being treated by either a
GP or a psychiatrist? From CCHS 1.2, we
estimate that 0.73% (95% CI: 0.62–0.84%)
of respondents with bipolar I disorder are
not under medical care. Individuals with
mild variants of bipolar disorder may not
require treatment; others may have clinically
significant disorders that could benefit
from treatment, but issues such as fear
of stigma or limited access to specialized
care stop them from accessing treatment.
These alternatives obviously have important implications; it is likely that the availability of a variety of sources of information
will help to distinguish between these
possibilities. Survey data can estimate
the proportion of a population that has a
diagnosable disorder, whereas a treated
prevalence is restricted to the proportion
actually receiving treatment. These results
indicate that administrative data may provide a valuable perspective on the treated
prevalence of bipolar disorder.
A limitation of health surveys is that they
rely upon self-report. On the other hand,
administrative data provide an objective
assessment of actual treatment received.
For mental disorders that are relatively
infrequent in the population, administrative
data can provide substantially more cases
for analysis than survey samples.3 This
was evident in the present study in which
the sample of bipolar I cases obtained
from administrative data sources was
substantially larger than the sample from
a national mental health survey (Table 1).
Researchers have questioned the quality of
administrative data, particularly regarding the
coding of diagnoses.22,23 Local re-abstraction
studies for inpatient encounters24,25 suggest
that the Calgary Zone’s coding practices
are reliable. Although sensitivity rates vary
considerably by medical condition, specificity rates in Calgary have been found
to be 99% or better across all conditions
examined (i.e. in nearly every case, the
most responsible diagnosis on record for the
inpatient encounter was verified by an
independent medical expert). We acknowledge that there is limited research on the
‡
validity of mental health diagnoses in
administrative data.
It should be noted that we may have overestimated actual treated prevalence since
some individuals may contact a physician
but not receive treatment. For this reason the
term “contact prevalence” may be preferable
when estimating the prevalence of an
illness from administrative data sources.26
Limitations
A limitation of our study is that we were
unable to assess the proportion of bipolar
patients being treated by those private psychiatrists (about 30%) who do not have
an affiliation with the psychiatric services
in the Calgary Zone. Taken together these
considerations suggest that the actual
treated prevalence of bipolar disorders by
psychiatrists in the Calgary Zone (Table 2)
is even closer to the national-survey–based
estimates (Table 3).
Second, CCHS 1.2 did not include Aboriginal
peoples or those living in institutions.
These individuals cannot be removed
from the data repository so this limits the
comparison of administrative data to that
from CCHS 1.2.
Another limitation of CCHS 1.2 is that the
criteria for bipolar I disorder do not fully
This differs slightly from the prevalence of 2.2% reported by Shaffer et al.21 because their result was for all respondents aged 15 years and over.
Vol 31, No 3, June 2011 – Chronic Diseases and Injuries in Canada
133
conform with DSM-IV criteria. The latter
requires manic symptoms to be present for
7 days unless hospitalization is required.15
Meanwhile, CCHS 1.2 requires manic
symptoms to be present for 4 days, reducing
the specificity compared with that obtainable
by strict DSM-IV criteria. This consideration may in part explain the higher estimate of treatment of bipolar I disorder
from CCHS 1.2 data relative to our local
administrative data.
In summary, we found a significant degree
of agreement between estimates of treated
bipolar I disorder in local administrative data
and national survey data. This observation
reinforces the potential utility of administrative data repositories in the surveillance
of chronic mental disorders.
Acknowledgements
This project was funded by a grant from
the Hotchkiss Brain Institute, Faculty of
Medicine, University of Calgary. We thank Jim
Si (Population Surveillance Group, Calgary
Zone) for providing the estimated population
of the Calgary Zone in 2005. CCHS 1.2
data were collected by Statistics Canada.
However, the analyses and interpretations
presented here are those of the authors
and not Statistics Canada.
References
1.
2.
2002 Canadian Community Health Survey:
Mental Health and Well-being [Internet].
Ottawa (ON): Health Canada; 2003 [cited
2010 Apr 6]. Available from: http://www
.statcan.gc.ca/pub/82-617-x/index-eng.htm
Frohlich KL, Dunn JR, McLaren L, Shiell A,
Potvin L, Hawe P, et al. Understanding
place and health: a heuristic for using
administrative
data.
Health
Place.
2007;13:299-309.
chronic disease risk factors and determinants. Ottawa (ON): Public Health
Agency of Canada; 2005. Catalogue No.:
HP5-11/2005.
5.
6.
Greenberg GA, Rosenheck RA. Does system
reform reduce geographic variation in mental
health system performance. Psychiatric Q.
2005;76:231-42.
Speer DC, Newman FL. Mental health services
outcome evaluation. Clin Psychol Sci Pr.
1996;3:105-29.
7. Addington D, McKenzie E, Addington J,
Patten S, Smith H, Adair C. Performance
measures for early psychosis treatment service. Psychiatric Serv. 2005;56:1570-82.
8.
Karlin BE, Norris MP. Public mental health
care utilization by older adults. Adm Policy
Ment Health. 2006;33:730-6.
9. Andrews G, Issakidis C, Sanderson K,
Corry J, Lapsley H. Utilising survey data
to inform public policy: comparison of
the cost-effectiveness of treatment of
ten mental disorders. Br J Psychiatry.
2004;184:526-33.
10. Slomp M, Bland R, Patterson S, Whittaker L.
Three-year physician treated prevalence
rate of mental disorders in Alberta. Can J
Psychiatry. 2009;54:199-203.
11. Andrews G. It would be cost-effective to
treat more people with mental disorders.
Aust N Z J Psychiatry. 2006;40:613-5.
12. Paradis M, Woogh C, Marcotte D, Chaput
Y. Is psychiatric emergency service (PES)
use increasing over time? Int J Ment Health
Syst. 2009;3:3.
16. Zimmerman M, Ruggero CJ, Chelminski
I, Young D. Is bipolar disorder overdiagnosed? J Clin Psychiatry. 2008;69:935-40.
17.Patten SB, Paris J. The bipolar spectrum—a bridge too far? Can J Psychiatry.
2008;53:762-8.
18.Gravel R, Beland Y. The Canadian
Community Health Survey: mental health
and well-being. Can J Psychiatry.
2005;10:573-9.
19. Kessler RC, Ustun TB. The World Mental
Health (WMH) Survey Initiative version
of the World Health Organization (WHO)
Composite
International
Diagnostic
Interview (CIDI). Int J Methods Psychiatr
Res. 2004;13:93-121.
20. Diaz-Granados N, Georgiades K, Boyle MH.
Regional and individual influences on use
of mental health services in Canada. Can J
Psychiatry. 2010;55:9-20.
21.Schaffer A, Cairney J, Cheung A,
Veldhuizen S, Levitt A. Community survey of bipolar disorder in Canada: lifetime
prevalence and illness characteristics. Can
J Psychiatry. 2006;51:9-16.
22. Roos LL, Soodeen R, Gupta S, Jebamani L.
Canadian administrative data: evaluating
the quality. Winnipeg (MB): University of
Manitoba; 2002.
23. Roos LL, Gupta S, Soodeen R, Jebamani L.
Data quality in an information-rich environment: Canada as an example. Can J
Ageing. 2005;24, Suppl 1:153-70.
13. Woogh CM. An experience in psychiatric
record linkage. Can J Psychiatry. 1988;33:134-9.
24. Quan H, Parsons GA, Ghali WA. Validity
of procedure codes in International
Classification of Diseases, 9th revision,
clinical modification of administrative
data. Med Care. 2004;42:801-9.
3. Mortensen PB. The untapped potential of
case registers and record-linkage studies in
psychiatric epidemiology. Epidemiologic
Rev. 1995;17:205-9.
14. Oswald P, Souery D, Kasper, Lecrubier Y,
Montgomery S, Wyckaert S, et al. Current
issues in bipolar disorder: a critical review.
Eur Neuropsychopharmacol. 2007;17:687-95.
25. Quan H, Parsons GA, Ghali WA. Assessing
accuracy of diagnosis-type indicators for
flagging complications in administrative
data. J Clin Epidemiol. 2004;57:366-74.
4.
15. American Psychiatric Association. Diagnostic
and statistical manual of mental disorders,
4th ed. rev. Washington (DC): American
Psychiatric Association; 2000.
26. Goldner EM, Jones W, Waraich P. Using
administrative data to analyze the prevalence and distribution of schizophrenic
disorders. Psychiatr Serv. 2003;54:1017-21.
Advisory Committee on Population Health
and Health Security Surveillance Systems
for Chronic Disease Risk Factors Task Group.
Enhancing capacity for surveillance of
134
Vol 31, No 3, June 2011 – Chronic Diseases and Injuries in Canada
Report summary
Life with arthritis in Canada: a personal and public health challenge
S. O’Donnell, MSc (1); C. Lagacé, MSc (1); L. McRae, BSc (1); C. Bancej, PhD (1)
Introduction
“Arthritis” describes more than 100 conditions
that affect the joints, the tissues that surround
joints and other connective tissue. These
conditions range from relatively mild
forms of tendonitis and bursitis to systemic
illnesses, such as rheumatoid arthritis.
Life with arthritis in Canada: a personal and
public health challenge presents the latest
knowledge about arthritis in the Canadian
population and its wide-ranging impact.
It provides an overview of the impact of
arthritis, and is designed to increase public
awareness of the importance of prevention
and timely management. Although progress
has been made on interventions, arthritis
remains common, disabling and costly.
Increasing participation in physical activity
and maintaining a healthy body weight
may help to mitigate the effects of arthritis.
Highlights
How common is arthritis?
In 2007–2008, arthritis was the second
and third most common chronic condition
among Canadian women and men, respectively, affecting over 4.2 million people
(16% of the population) 15 years and
older. As our population ages, this number
is expected to increase to approximately 7
million (20%) by 2031. However, despite
common myths about arthritis, it is not
confined to the elderly—nearly three in
five Canadians with arthritis were between
the ages of 15 and 64 years.
While prevalence estimates of arthritis
among First Nations (on and off-reserve)
and Métis adult populations were 1.3 to
1.6 times higher than those among the
Canadian adult population, those in the
Inuit adult population were similar.
The impact of arthritis
Many individuals with arthritis perceived
their general and mental health as fair or
poor, and needed help with daily activities
and in their work, community, social and
civic life. Of the 15% of Canadians living
with a disability in 2001, one-quarter
reported arthritis as the main cause; of
these, over one-quarter between 25 and 44
years of age were not in the labour force
because of their arthritis.
Economic burden of arthritis
In 2000, musculoskeletal diseases were the
most costly group of diseases; arthritis was
estimated to cost $6.4 billion (29% of the
total cost). Of the total arthritis-related
costs, the greatest impact was due to the
indirect costs ($4.3 billion) as a result of lost
productivity attributable to long-term disability and premature death.
Arthritis-related medications
In 2007, Canadians were prescribed over 4
million non-steroidal anti-inflammatory drugs
(NSAIDs), over 1 million disease-modifying
anti-rheumatic drugs (DMARDs), close to 1
million corticosteroids, and approximately
150 000 biological response modifiers (BRMs).
Health services utilization
In 2005–2006, approximately 14% of
Canadians over 15 years made at least one
visit to a physician (usually a primary care
physician) for any type of arthritis—an estimated total of 8.5 million visits in Canada
(excluding the territories). Arthritis was
associated with 6% of the total hospitalizations, of which surgical hospitalizations
(71%) were more common than medical
ones (29%). Nearly two-thirds of the
arthritis-related surgical hospitalizations
were joint replacements (63%). Between
2001 and 2006, the total number of joint
replacements increased by 54%.
Mortality burden
While deaths from arthritis are uncommon,
777 women and 296 men died from an
arthritis condition in 2005; rheumatoid
arthritis, systemic lupus erythematosus and
other connective tissue diseases accounted
for approximately 60% of all the arthritisrelated deaths.
Reducing the risks of developing osteoarthritis
and gout
The risk of developing osteoarthritis
and gout can be reduced. Maintaining a
healthy body weight and healthy joints
and muscles through physical activity
while protecting joints from injuries or
overuse can help prevent osteoarthritis.
Likewise, maintaining a healthy body
weight, keeping physically active, and
reducing consumption of purine-rich foods
Author references
1. Chronic Disease Surveillance and Monitoring Division, Centre for Chronic Disease Prevention and Control, Public Health Agency of Canada, Ottawa, Ontario, Canada
Correspondence: Siobhan O’Donnell, Centre for Chronic Disease Prevention and Control, Public Health Agency of Canada, 785 Carling Avenue, A/L 6806A, Ottawa ON K1A 0K9;
Tel.: (613) 954-6557; Fax: (613) 941-2057; Email: [email protected]
Vol 31, No 3, June 2011 – Chronic Diseases and Injuries in Canada
135
and drinks, such as red meat, certain types
of seafood and alcohol, reduces the risk of
developing gout.
Living with arthritis
Although there is no known cure for arthritis,
people with all types of arthritis can prevent
disability and improve their quality of life
by maintaining a healthy weight, being
physically active, avoiding joint injuries,
participating in self-management programs,
and—particularly for inflammatory types
of arthritis—getting an early diagnosis and
treatment. Nevertheless, high proportions
of Canadians with arthritis are physically
inactive (59%) and overweight/obese (63%).
Life with arthritis in Canada: a personal
and public health challenge is available at:
http://www.phac-aspc.gc.ca/cd-mc/arthritis-arthrite/lwaic-vaaac-10/index-eng.php
136
Vol 31, No 3, June 2011 – Chronic Diseases and Injuries in Canada
Book review
Internet, Mail and Mixed-Mode Surveys: The Tailored Design Method
K.K.Y. Poon, M.Sc. (Candidate), Queen’s University, Kingston, Ontario, Canada
Authors: Don A. Dillman, Jolene D. Smyth, Leah Melani Christian
Publisher: John Wiley & Sons, Inc.
Publication date: 2009
Number of pages: 499
Format: Hardcover
Price: $96.00
ISBN: 978-0-471-69868-5
Written in collaboration with Jolene D.
Smyth and Leah Melani Christian, Internet,
Mail and Mixed-Mode Surveys: The Tailored
Design Method (2009) is the third edition of
Don A. Dillman’s seminal work on survey
development and administration. The first
edition of this text, published in 1978, targeted the opportunities and challenges of
mail and telephone surveys, and raised
the credibility of these survey methods at
a time when face-to-face interviews were
considered the gold standard. Since then, his
work has been a go-to reference for countless researchers and survey developers. In
2000, Dillman published a second edition
to respond to changes in the technological
and social climate of surveying. This was
followed by an update in 2007.
Compared to the updated second edition,
there are three main features that make this
third edition a worthwhile read. First, while
the second edition had a brief section devoted
to Internet survey methods, this edition
incorporates Web-relevant considerations
into each chapter. Second, in addition to a
chapter dedicated to mixed-mode surveys,
the utility of hybrid survey methods is
emphasized throughout the text. Finally,
the importance of visual design is highlighted
and considered in detail. In a time when
respondents are being approached with
increased frequency, this text provides
insight on how researchers can obtain highquality responses using non-traditional
survey modes and current technology.
The authors’ goal was to create a complete
guide to planning and conducting surveys
using the Internet, mail, telephone and/or
a mixture of modes. Clear introductions,
distinct subsections and summarized guidelines help readers access detailed information
in each chapter.
between Internet, mail and telephone modes
within the context of coverage and sampling.
Chapter 1 starts off with a vivid description
of the evolution of survey development
and administration. From a time when
mail surveys were considered inferior to
telephone and in-person interviews, to the
prominence of electronic mail surveys
today, the authors describe the social and
technological variables that have contributed
to these changes.
Chapter 5 provides guidelines for constructing open and close-ended questions.
The authors explore numerical, item-list
and description responses to open-ended
questions, and nominal scale and ordinal
scale responses for close-ended questions.
Extensive guidelines are provided for each
response type.
Chapter 2 presents the psychology behind
survey responses and describes the different
types of survey errors, building the foundation for first-time survey developers. Using
a perspective of positive social exchange,
the authors describe how one can increase
the benefits of participation while decreasing
the costs. The language used is simple and
the explanations are easy to grasp, making
this an excellent introductory chapter.
However, for a more thorough understanding of these concepts, supplementary texts
would be needed.
Chapter 3 describes the fundamental concepts
of survey coverage and sampling. Using
straightforward definitions and descriptive
examples, the authors highlight differences
Vol 31, No 3, June 2011 – Chronic Diseases and Injuries in Canada
137
Chapter 4 presents the basics of crafting
high-quality survey questions. The authors
underscore the importance of visual presentation with helpful examples and figures.
Chapter 6 outlines how researchers can
transition from a list of questions to a
respondent-friendly questionnaire while
maximizing response and minimizing
measurement error. In describing this
process, the authors elaborate on question
order, technological considerations and the
importance of visual design.
Chapter 7 discusses strategies for implementing population-based surveys on the
Internet and through mail. In presenting
guidelines for these two modes, the
authors use a consistent format to highlight
fundamental principles, such as the importance of simple language.
Chapter 8 describes the utility of mixed
modal surveys with guidelines to help readers select the most effective combination
of survey modes. The authors provide a
useful chart to describe the motivations
and limitations of four identified types of
mixed modal surveys.
Chapter 9 discusses longitudinal and Internet
panel surveys. These surveys involve the
use of multiple questionnaires, which present
unique challenges common to both survey
types. The authors explore important
methodological concerns such as loss to
follow-up and respondent conditioning.
Chapter 10 focuses on developing surveys
to collect customer feedback. The authors
discuss sampling methods and measurement
issues. In particular, interactive voice response
technology, diaries and group administration
are presented as unique delivery methods
to improve the accuracy of customer responses.
Chapter 11 explores the legal considerations
of data collection. The authors point out
that interpretations of privacy laws can
often conflict with best practices for survey
administration. They also discuss the effects
of sponsorship with an emphasis on
research ethics.
Chapter 12 elaborates on the opportunities
and challenges of surveying businesses
and establishments. The authors provide
a useful list of questions for researchers
to consider and present to establishments
in order to optimize a survey’s success.
Chapter 13 postulates on the future of Internet,
mail and telephone surveying. Particularly,
the potential for increased use of Internet
surveys is discussed along with the continued
relevance of mail and paper surveys.
Overall, the authors succeeded in creating
a comprehensive guide to survey development
and administration. From fundamental survey principles to the unique challenges of
multiple questionnaires, this text covers an
excellent range of survey considerations.
In particular, it serves as a useful reference
for students and researchers looking to
expand their survey methodology to obtain
high quality responses in today’s technologically centered society.
138
Vol 31, No 3, June 2011 – Chronic Diseases and Injuries in Canada
With thanks to our 2010 peer reviewers
We are grateful to the following people for
their significant contribution to Chronic
Diseases in Canada as peer reviewers in
2010. Their expertise ensures the quality
of our journal and promotes the sharing
of new knowledge among peers in Canada
and internationally.
Devendra Amre
Kelly Anderson
Chris Andrews
Sten Ardal
Megan Aston
George Beaton
Nicholas Birkett
Carole Blanchet
Larry Chambers
Yves Chaput
Yue Chen
Margaret Cheney
Mary Chipman
Wong Ho Chow
Lynda Corby
Simone Dahrouge
Carl D’Arcy
Joseph DiFranza
Roland Dyck
Grace Egeland
Garry Egger
Daniel Fuller
Tracey Galloway
Didier Garriguet
Leslie Gaudette
William Gnam
Katherine Gray-Donald
Judy Guernsey
Leona Hakkaart-Van Roijen
Anne-Marie Hamelin
Trevor Hancock
Lisa Hartling
Ken Hoffman
Janie Houle
Jennifer Hutcheon
Brian Hutchison
K. S. Joseph
Anita Koushik
Yvonne Lamers
Jérôme Lavoué
Nancy Lightfoot
Shiliang Liu
Lisa Lix
Francine Lortie-Monette
Pat Martens
Jane McCusker
Rena Mendelson
Les Mery
Christiana Miewald
Anthony Miller
Judy Morona
John Myers
Bruce Newbold
Jill Newstead-Angel
Edward Ng
Michael Otterstatter
Gordon Phaneuf
Will Pickett
Robert Platt
Kevin Pottie
Sampsa Puttonen
Georgia Roberts
Elizabeth Robinson
Edmond Ryan
Diana Schendel
Cindy Scythes
Monique Séguin
David Streiner
Paul Taenzer
Mary Thompson
Ross Tsuyuki
Ana Velly
Harth Volker
Kitty Wilkins
Kristy Wittmeier
Margareth Zanchetta
Vol 31, No 3, June 2011 – Chronic Diseases and Injuries in Canada
139
CDIC: Information for authors
Chronic Diseases and Injuries in Canada
a publication of the Public Health Agency
of Canada
Howard Morrison, PhD
Editor-in-Chief
(613) 941-1286
Robert A. Spasoff, MD
Associate Scientific Editor
Claire Infante-Rivard, MD
Associate Scientific Editor
Elizabeth Kristjansson, PhD
Associate Scientific Editor
Lesley Doering, MSW
Public Health Agency of Canada
Robert Geneau, PhD
Public Health Agency of Canada
Isra Levy, MB, FRCPC, FACPM
Ottawa Public Health
Lesli Mitchell, MA
Centers for Disease Control and Prevention
Scott Patten, MD, PhD, FRCPC
University of Calgary
Michelle Tracy, MA
Managing Editor
Chronic Diseases and Injuries in Canada (CDIC) is a
CDIC Editorial Board
Barry Pless, CM, MD, FRCPC
Montreal Children’s Hospital
Kerry Robinson, PhD
Public Health Agency of Canada
Fabiola Tatone-Tokuda, MSc
University of Ottawa
Andreas T. Wielgosz, MD, PhD, FRCPC
University of Ottawa
References: In Vancouver style (consult a recent CDIC
issue for examples); num­bered in superscript in the
Chronic Diseases and Injuries in Canada (CDIC)
is a quarterly scientific journal focussing
on current evidence relevant to the control
and prevention of chronic (i.e. noncommunicable) diseases and injuries in
Canada. Since 1980 the journal has published
a unique blend of peer-reviewed feature
articles by authors from the public and
private sectors and which may include
research from such fields as epidemiology,
public/community health, biostatistics, the
behavioural sciences, and health services or
economics. Only feature articles are peer
reviewed. Authors retain responsibility for
the content of their articles; the opinions
expressed are not necessarily those of the
CDIC editorial committee nor of the Public
Health Agency of Canada.
and control of non‑communicable diseases and injuries
Submit manuscripts to the Managing Editor,
order cited in text, tables and figures; listing up to
in Canada. Its feature articles are peer reviewed.
Chronic Diseases and Injuries in Canada, Public
six authors (first six and et al. if more); without any
The content of articles may include research from
Health Agency of Canada, 785 Carling Avenue,
automatic reference numbering feature used in
such fields as epidemiology, public/community
Address Locator 6805B, Ottawa, Ontario K1A 0K9,
word processing; any unpublished observations/
health, biostatistics, the behavioural sciences, and
email: [email protected]
data or personal communications used (discouraged)
Chronic Diseases and Injuries in Canada
Public Health Agency of Canada
785 Carling Avenue
Address Locator 6805B
Ottawa, Ontario K1A 0K9
papers, and opinions expressed are not necessarily
Fax: (613) 941-9502
E-mail: [email protected]
Public Health Agency of Canada
Don Wigle, MD, PhD
Submitting Manuscripts
quarterly scientific journal focusing on the prevention
Indexed in Index Medicus/MEDLINE,
SciSearch® and Journal Citation Reports/
Science Edition
Russell Wilkins, MUrb
Statistics Canada
health services or economics. CDIC endeav­ours to
to be cited in the text in parentheses (authors
foster communication on chronic diseases and injuries
Since CDIC adheres in general (section on illustrations
responsible for obtaining written per­mis­sion); authors
among public health practitioners, epidemiolo­gists
not applicable) to the “Uniform Requirements for
are responsible for verifying accuracy of references.
and researchers, health policy plan­ners and health
Manuscripts Submitted to Biomedical Journals”
educators. Submissions are selected based on scientific
as approved by the International Committee of
Tables and Figures: Send vector graphics only.
quality, public health relevance, clarity, concise­ness
Medical Journal Editors, authors should refer to this
Each on a separate page and in electronic file(s)
and technical accuracy. Although CDIC is a publication
document for complete details before submitting a
separate from the text (not imported into the text
of the Public Health Agency of Canada, contributions
manuscript to CDIC (see <www.icmje.org>).
body); as self‑explanatory and succinct as possible;
are welcomed from both the public and pri­vate sectors.
Authors retain responsibility for the contents of their
those of the CDIC editorial committee nor of the
Public Health Agency of Canada.
Article Types
Checklist for Submitting
Manuscripts
in
footnotes,
identified
by
lower‑case
superscript letters in alpha­
betical order; figures
limited to graphs or flow charts/templates (no
photographs), with software used specified and
the authorship criteria including a full statement
titles/footnotes on a separate page.
regarding any prior or duplicate publi­
cation or
submission for publication.
Peer‑reviewed Feature Article: Maximum 4000
Number of copies: If submitting by mail, one
complete copy, including tables and figures; one
words for main text body (excluding abstract,
First title page: Concise title; full names of all
copy of any related supple­men­tary material, and a
tables, figures, references) in the form of original
authors and institutional affiliations; name, postal
copy of the manuscript on diskette. If submitting by
research, surveillance reports, meta‑analyses or
and email addresses, tele­phone and fax numbers
email to cdic‑[email protected]‑aspc.gc.ca, please fax or
methodological papers.
for corresponding author; separate word counts for
mail the covering letter to the address on the inside
abstract and text.
front cover.
studies or information systems bearing on Canadian
Second title page: Title only; start page numbering
public health (maximum 3000 words). Abstract
here as page 1.
Abstract: Unstructured (one paragraph, no headings),
Workshop/Conference Report: Summarize significant,
maximum 175 words (100 for short reports); include
recently held events relat­ing to national public health
3-8 keywords (preferably from the Medical Subject
(maximum 1200 words). Abstract not required.
Headings [MeSH] of Index Medicus).
Cross‑Canada Forum: For authors to present or
Text: Double‑spaced, 1 inch (25 mm) margins,
exchange information and opin­ions on regional or
12 point font size.
national surveillance findings, programs under
development or public health policy initiatives
Acknowledgements: Include disclosure of financial
(maximum 3000 words). Abstract not required.
and material support in acknowledgements; if anyone
is credited in acknowledgements with substantive
This publication is also available online at www.publichealth.gc.ca/cdic
Également disponible en français sous le titre : Maladies chroniques et blessures au Canada
tables
seen and approved the final manuscript and have met
not required.
Published by authority of the Minister of Health.
© Her Majesty the Queen in Right of Canada, represented by the Minister of Health, 2011
ISSN 1925-6515
are mentioned in the text; explanatory material for
Cover letter: Signed by all authors, stating that all have
Status Report: Describe ongoing national programs,
To promote and protect the health of Canadians through leadership, partnership, innovation and action in public health.
— Public Health Agency of Canada
not too numerous; numbered in the order that they
Letter to the Editor: Comments on articles recently
scientific contributions, authors should state in the
published in CDIC will be consid­ered for publication
cover letter that they have obtained written permission.
(maximum 500 words). Abstract not required.
Book/Software Review: Usually solicited by the
editors (500-1300 words), but requests to review
are welcomed. Abstract not required.
Chronic Diseases and
Injuries in Canada
Volume 31 · Number 3 · June 2011
Inside this issue
94
95
97
Preface – What’s in a name: Chronic Diseases
and Injuries in Canada
H. Morrison, M. Tracy
Editorial – Non-communicable diseases – finally
on the global agenda
A. T. Wielgosz
Patterns of fatal machine rollovers
in Canadian agriculture
J. M. DeGroot, C. Isaacs, W. Pickett, R. J. Brison
103 Estimating gestational age at birth:
a population-based derivation-validation study
M. L. Urquia, T. A. Stukel, K. Fung, R. H. Glazier, J. G. Ray
109 The influence of primary health care
organizational models on patients’ experience
of care in different chronic disease situations
R. Pineault, S. Provost, M. Hamel, A. Couture, J. F. Levesque
121 An assessment of the barriers to accessing food
among food-insecure people in Cobourg, Ontario
S. Tsang, A. M. Holt, E. Azevedo
129 Estimates of the treated prevalence of bipolar
disorders by mental health services in the
general population: comparison of results
from administrative and health survey data
A. G. Bulloch, S. Currie, L. Guyn, J. V. Williams,
D. H. Lavorato, S. B. Patten
Was this manual useful for you? yes no
Thank you for your participation!

* Your assessment is very important for improving the work of artificial intelligence, which forms the content of this project

Download PDF

advertisement