Chronic Diseases and Injuries in Canada Inside this issue

Chronic Diseases and Injuries in Canada Inside this issue
Chronic Diseases and
Injuries in Canada
Volume 32 · Number 3 · June 2012
Inside this issue
113 Application of a national administrative case definition for the
identification of pre-existing diabetes mellitus in pregnancy
121 Divergent associations between incident hypertension and
deprivation based on different sources of case identification
131 Trends in incidence of childhood cancer in Canada, 1992-2006
140 Cultural factors related to the maintenance of health behaviours
in Algonquin women with a history of gestational diabetes
149 Coaches’ knowledge and awareness of spit tobacco use among
youth athletes: results of a 2009 Ontario survey
156 Unhealthy behaviours among Canadian adolescents: prevalence,
trends and correlates
164 Longitudinal trends in mental health among ethnic groups in
Canada
Chronic Diseases and Injuries in Canada
a publication of the Public Health Agency
of Canada
Howard Morrison, PhD
Editor-in-Chief
(613) 941-1286
CDIC Editorial Board
Lesley Doering, MSW
Public Health Agency of Canada
Robert Geneau, PhD
Robert A. Spasoff, MD
Associate Scientific Editor
International Development Research Centre
Isra Levy, MB, FRCPC, FACPM
Claire Infante-Rivard, MD
Associate Scientific Editor
Ottawa Public Health
Elizabeth Kristjansson, PhD
Associate Scientific Editor
Centers for Disease Control and Prevention
Lesli Mitchell, MA
Scott Patten, MD, PhD, FRCPC
Michelle Tracy, MA
Managing Editor
University of Calgary
Barry Pless, CM, MD, FRCPC
Sylvain Desmarais, BA, BEd
Assistant Managing Editor
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
Public Health Agency of Canada
Don Wigle, MD, PhD
University of Ottawa
Russell Wilkins, MUrb
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.
Chronic Diseases and Injuries in Canada
Public Health Agency of Canada
785 Carling Avenue
Address Locator 6807B
Ottawa, Ontario K1A 0K9
Fax: (613) 941-2633
E-mail: [email protected]
Indexed in Index Medicus/MEDLINE,
SciSearch® and Journal Citation Reports/
Science Edition
Statistics Canada
To promote and protect the health of Canadians through leadership, partnership, innovation and action in public health.
— Public Health Agency of Canada
Published by authority of the Minister of Health.
© Her Majesty the Queen in Right of Canada, represented by the Minister of Health, 2012
ISSN 1925-6515
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
Application of a national administrative case definition for the
identification of pre-existing diabetes mellitus in pregnancy
V. M. Allen, MD (1,2); L. Dodds, PhD (1,2,3,4); A. Spencer, MSc (4); E. A. Cummings, MD (3); N. MacDonald, MD (3);
G. Kephart, PhD (2)
This article has been peer reviewed.
Abstract
Introduction: Accurate ascertainment of pregnant women with pre-existing diabetes
allows for the comprehensive surveillance of maternal and neonatal outcomes associated
with this chronic disease.
Method: To determine the accuracy of case definitions for pre-existing diabetes mellitus
when applied to a pregnant population, a cohort of women who were pregnant in
Nova Scotia, Canada, between 1991 and 2003 was obtained from a population-based
provincial perinatal database, the Nova Scotia Atlee Perinatal Database (NSAPD).
Person-level data from administrative databases using hospital discharge abstract data
and outpatient physician services data were linked to this cohort. Various algorithms for
defining diabetes mellitus from the administrative data, including the algorithm
suggested by the National Diabetes Surveillance System (NDSS), were compared to a
reference standard definition from the NSAPD.
Results: Validation of the NDSS case definition applied to this pregnant population
demonstrated a sensitivity of 87% and a positive predictive value (PPV) of 66.4%. Use of
ICD-9 and ICD-10 diagnostic codes among hospitalizations with diabetes mellitus in
pregnancy showed important increases in sensitivity and PPV, especially for those pregnancies
delivered in tertiary centres. In this population, pregnancy-related administrative data
from the hospitalization database alone appear to be a more accurate data source for
identifying pre-existing diabetes than applying the NDSS case definition, particularly
when pregnant women are delivered in a tertiary hospital.
Conclusion: Although the NDSS definition of diabetes performs reasonably well compared
to a reference standard definition of diabetes, using this definition for evaluating maternal
and perinatal outcomes associated with diabetes in pregnancy will result in a certain
degree of misclassification and, therefore, biased estimates of outcomes.
Keywords: diabetes mellitus, pregnancy, validation studies
Introduction
Monitoring the prevalence and incidence
of diabetes, estimating the burden of
illness, and evaluating the impact of care
on prevention and progression are
essential for planning and evaluating
treatment and prevention programs for
chronic disease.1,2 Increasing maternal age3
and changing maternal characteristics such
as pre-pregnancy weight4,5 may contribute
to increasing rates of pre-existing diabetes
in pregnant women,6 with associated
increased costs related to diabetes care.7
Obstetrical complications associated with
pre-existing diabetes also have important
maternal and neonatal consequences.6,8-11
Accurate ascertainment of pregnant women
with pre-existing diabetes allows for the
comprehensive surveillance of maternal and
neonatal outcomes associated with this
complication.
The identification of diabetes cases in
the population using administrative data
began in Canada in 1991, followed by the
development of a provincial diabetes
database in Manitoba in 1998.12 To be
labelled as having diabetes, a person must
have recorded two physician claims within
a two-year period or one hospitalization
with a diagnosis of diabetes. With further
refinement related to age threshold, and
clarification of the claim date, the National
Diabetes Surveillance System (NDSS)
established an algorithm for the collection of
national data related to diabetes.13 The NDSS
is a collaborative network of provincial and
territorial surveillance systems. Supported
by the Public Health Agency of Canada, it
was developed in 2001 to improve the
breadth of information about the burden of
diabetes in Canada so that policy makers,
public health and health care professionals
and the general public can make better
public and personal health decisions. At
the provincial level, the NDSS compiles
administrative health care data relating to
individual diabetes cases and sends aggregate anonymous data to the Public Health
Agency of Canada for national analyses.14
Author references:
1. Department of Obstetrics and Gynaecology, Dalhousie University, Halifax, Nova Scotia, Canada
2. Department of Community Health and Epidemiology, Dalhousie University, Halifax, Nova Scotia, Canada
3. Department of Pediatrics, Dalhousie University, Halifax, Nova Scotia, Canada
4. Perinatal Epidemiology Research Unit, Dalhousie University, Halifax, Nova Scotia, Canada
Correspondence: Victoria M. Allen, Department of Obstetrics and Gynaecology, IWK Health Centre, Room G2141, 5850/5980 University Avenue, Halifax, NS B3K 6R8; Tel.: (902) 470-6486;
Fax: (902) 425-1125; Email: [email protected]
113
Vol 32, No 3, June 2012 – Chronic Diseases and Injuries in Canada
Validation studies have evaluated the
NDSS case definition for the detection of
diabetes mellitus in the general population
as well as a more liberal definition that
requires only one physician visit or hospitalization. They have compared these
definitions to reference standards such as
provincial health surveys, diabetes registries,
medical charts and laboratory data.2,15 The
results of these validation studies have been
inconsistent as measured by ascertainment
rate12 or sensitivity,15-19 which may be related
to regional, temporal or reference standard
definitions.12,15-19 In addition, the utility of the
NDSS in sub-populations such as pregnancy
becomes challenging when diagnoses of
gestational diabetes are also considered. The
NDSS is limited in its ability to distinguish
between type 1, type 2 and gestational
diabetes, and although gestational diabetes
has its own ICD-9* and ICD-10† codes,
increases in the prevalence of pre-existing
diabetes among women of child-bearing
years (20–49 years) may be the result of
changing maternal characteristics, such as
increasing pre-pregnancy weight,4 or the
result of miscoding.14,20 To eliminate gestational diabetes cases that were miscoded
with a diabetes mellitus code, the NDSS
case definition excludes women first
meeting the case definition for diabetes
120 days preceding or 90 days after any
pregnancy-related visit.
Previous validation studies used to develop
a Nova Scotia diabetes repository demonstrated an unacceptably high number of
false positive diagnoses of diabetes mellitus
using the NDSS case definition in the
general population.21 The purpose of our
study was to evaluate the application of the
NDSS case definition for diabetes mellitus
using data derived from administrative data­
bases to a population of pregnant women,
and to compare this application to a clinical
definition for the diagnosis of pre-existing
diabetes in pregnancy using data derived
from a reference standard perinatal database.
Methods
The province of Nova Scotia has a
homogeneous, predominantly Caucasian
population of about one million, with
approximately 10 000 live births each year.22
The population of Nova Scotia has universal
health coverage with a single payer
health system within Canada. Although
nine hospitals offer intrapartum obstetrical
care, 50% of deliveries occur at one of the
tertiary maternity facilities.
Data sources and linkage
Information on all women who delivered
in Nova Scotia between 1988 and 2003
is available from the Nova Scotia Atlee
Perinatal Database (NSAPD), which is
managed by the Reproductive Care
Program (RCP) of Nova Scotia. The NSAPD
is a high quality, provincial populationbased database containing clinical
information on all births born at a
gestational age of at least 20 weeks or
having a birth weight of at least 500 grams.
It contains maternal and newborn
information, such as demographic variables,
procedures, interventions, maternal and
newborn diagnoses and morbidity, and
mortality information for every pregnancy
and birth in Nova Scotia since 1988.
Home births without hospital admission
are currently not entered into the database.
(However, there are few home births,
approximately 0.2% per year.) Information
in the database is abstracted by trained
health records personnel using standardized
forms and hospital medical records across
Nova Scotia. Detailed information on
several hundred variables is collected on
specific lifestyle and other subject characteristics, medical conditions, labour and
delivery events and neonatal outcomes.
All information is entered into the database soon after the time of collection. In
addition to the routine data checks and edits
that are made at the time of collection, an
ongoing data quality-assurance program,
which carries out periodic rigorous
abstraction studies, has shown that the
information in the database continues to
be reliable. In particular, the information
collected on pre-existing diabetes was
considered the reference standard for the
diagnosis of diabetes for this study
because cases were clinically confirmed and
accurately coded.21 The database has been
used previously for numerous studies,
* International Classification of Diseases, 9th Revision.
†
International Classification of Diseases, 10th Revision.
Vol 32, No 3, June 2012 – Chronic Diseases and Injuries in Canada
114
including diabetes-related studies,9,23,24
and has been used to validate other
sources of data.25
The data from the NSAPD were linked to
the two administrative health databases
relevant to this study, the Canadian
Institute for Health Information’s Discharge
Abstract Database (CIHI-DAD) and the
Medical Services Insurance (physician visits)
Database (MSID). The administrative
databases are housed at the Population
Health Research Unit (PHRU), Department
of Community Health and Epidemiology,
Dalhousie University, and include
population-level administrative health data
for the Province of Nova Scotia. These
administrative data are obtained from
provincial billing information (MSI) and
recorded from hospital medical records
abstracted by trained health records
personnel. Nine facilities provide regional or
tertiary level obstetrical services in Nova
Scotia; in 6 of these facilities, the data
abstractor who codes and abstracts information is the same coder for both CIHI-DAD
and NSAPD data, while in 3 facilities, the
data are collected for the CIHI system and
the NSAPD system by two different individuals. Each data abstractor is registered
with the Canadian Health Information
Management Association and is qualified for
and knowledgeable about data collection in
either system for data collection.
These health databases capture all
diagnosed cases of diabetes in both
outpatient and hospital settings. The
CIHI-DAD contains information on medical
diagnoses and procedures from hospital
discharge data. Discharges are coded using
ICD-9 codes for 1987 to 2001 and ICD-10
codes since 2001; surgical and other
procedures are coded using the Canadian
Classification of Procedures for 1987 to
2001 and the Canadian Classification of
Health Interventions for 2001 to the present
day. The MSID records outpatient visits
and diagnoses through physician billing,
including information on physician specialty.
In Nova Scotia, clinical fees for obstetrical
services are coded separately for prenatal
visits, admission to hospital, care for labour
and delivery, and postpartum care.
Table 1a
Diagnostic codes used to define pregnancies with pre-existing diabetes in the NSAPD
NSAPD (reference-standard) criteria
Since inception, the NSAPD has defined
pre-existing diabetes in pregnancy using
the White classification, then ICD-10-CA
(Canada) or CCI (Canadian Classification
of Health Interactions) code, and finally the
NSAPD code for diabetes mellitus during
a pregnancy-related admission (Table 1a).26
However, during this study, we used only
the White classification, which considers
duration of diabetes and the presence of
vascular, retinal and renal complications of
diabetes mellitus.27 Pre-existing diabetes in
pregnancy is coded in the NSAPD when
it is identified anywhere in the patient
record, regardless of whether the diagnosis
was of an outpatient or an inpatient. The
NSAPD case definition is able to distinguish
gestational diabetes mellitus (White
classification, Class A) from pre-existing
type 1 or type 2 diabetes mellitus (White
classification Class B-T).
Diagnostic codes
Year of use
White Classification
1988–2003
Class A: Gestational diabetes
Class B: Less than 10 years duration; no vascular disease; onset after age 20 years
Class C: Duration 10–19 years; minimal vascular disease; onset after age 10 years
Class D: Duration 20 years or more; benign retinopathy; onset before age 10 years
Class F: Patient with Class D and nephropathy
Class R: Patient with proliferative retinopathy
Class T: Diagnosis made by level of glucose challenge test equal
to or greater than 10.3 mmol/l
ICD-10-CA or CCI
NSAPD code
The NDSS case definition was applied to
this study population using all coding
fields in the hospital discharge data for
any hospital admission in pregnancy and
2006–present
Abbreviations: CCI, Canadian Classification of Health Interactions; ICD-10-CA, International Classification of Diseases,
10th Revision, Canadian version; NSAPD, Nova Scotia Atlee Perinatal Database.
Table 1B
Diagnostic codes used in the application of the National Diabetes Surveillance
System case definition for pre-existing diabetes to pregnancies in the NSAPD
NDSS criteria
The case definition used by the NDSS for
the diagnosis of diabetes mellitus requires
that an individual have either at least one
hospitalization or at least two medical
claims coded with a diagnosis of diabetes
mellitus (250 in ICD-9 or E10–E14 in ICD-10,
Table 1b) within two years (Algorithm A,
Table 2). To meet the two MSI physician
claims requirements, the claims could
not occur on the same day. These case
definitions are applied to all patient-level
claims, irrespective of age or gestational
status.20 To eliminate miscoding of gestational diabetes cases as diabetes mellitus,
and because birth date information is
not available to NDSS, the NDSS case
definition distinguishes pre-existing diabetes
mellitus from gestational diabetes by
removing any cases with a diagnostic
code for diabetes mellitus (Table 1b) that
occur 120 days before or 90 days after any
pregnancy-related visit (relevant obstetrical
claims codes summarized in Table 1b).
The NDSS case definition includes type 1
and type 2 diabetes mellitus but is unable
to distinguish between types.
2003–2006
Diabetes mellitus
codes
Obstetrical
codes
Diabetes mellitus in
pregnancy codes
250
640–669
648.0
E10–E14
O265, O290–O30, O318, O320–O369,
O40–O439, O60–O669, O680–O849, O890–O899,
O904, O908, O95–O97, Z354–Z356
O24.0, O24.1, O24.2,
O24.3, O24.9
ICD-9a
ICD-10
b
Abbreviations: ICD-9, International Classification of Diseases, 9th Revision; ICD-10, International Classification of Diseases,
10th Revision; NSAPD, Nova Scotia Atlee Perinatal Database.
a
In use 1987–2001.
b
In use 2001–present day.
Table 2
Algorithms based on the application of the NDSS case definition for diabetes
mellitus to pregnancies in the NSAPD, or existing diagnostic codes for diabetes
in pregnancy using CIHI-DAD and MSI
Algorithm
Definition
A (NDSS)
removes cases with at least one hospitalization or at least two MSI claims with a diagnostic
code for diabetes mellitus (ICD-9 250 or ICD-10 E10–14) that is followed within 120 days, or
90 days after, by an obstetrics claims code
B
removes cases with at least one hospitalization or at least two MSI claims with a diagnostic
code for diabetes mellitus (ICD-9 250 or ICD-10 E10–14) that is followed within 150 days, or
90 days after, by an obstetrics claims code
C
removes cases with at least one hospitalization or at least three MSI claims with a diagnostic
code for diabetes mellitus (ICD-9 250 or ICD-10 E10–14) that is followed within 120 days, or
90 days after, by an obstetrics claims code
D
includes cases with at least one hospitalization with a diagnostic code for diabetes mellitus
during pregnancy (ICD-9 648.0 or ICD-10 O24.0, O24.1, O24.2, O24.3, O24.9)
E
algorithm A or algorithm D
Abbreviations: CIHI-DAD, Canadian Institute for Health Information’s Discharge Abstract Database; ICD-9, International
Classification of Diseases, 9th Revision; ICD-10, International Classification of Diseases, 10th Revision; MSI, Medical Services
Insurance; NDSS, National Diabetes Surveillance System; NSAPD, Nova Scotia Atlee Perinatal Database.
115
Vol 32, No 3, June 2012 – Chronic Diseases and Injuries in Canada
physician claims data for the study period.
The NSAPD began coordinating data
collection in Nova Scotia in 1988; however,
since the databases at the PHRU only
included data beginning April 1, 1989,
and to allow for a two-year period before a
pregnancy (NDSS case definition includes
two medical claims codes within two years),
the study period included all pregnancies
between April 1, 1991, and December 2003.
In Nova Scotia, ICD-9 was replaced by
ICD-10 in the CIHI-DAD, beginning April 1,
1997; however, MSI coding with respect to
billing continued in ICD-9.
Statistical analysis
All pregnancies in the NSAPD (i.e.
≥ 20 weeks gestation and births ≥ 500g)
between April 1, 1991, and April 1, 2003,
that resulted in live-birth singletons were
considered for analysis. Because diabetes
status in pregnancy may change over time,
only the diabetes status for a nulliparous
pregnancy recorded in the NSAPD was
considered. A pregnant woman must also
have been eligible to receive MSI (i.e. did
not move out of province or die) during
a period at least two years before the
start of pregnancy to 90 days after the
delivery date to ensure sufficient time to
meet the NDSS case definition. Since
the administrative databases began in
April 1, 1989, the earliest delivery date
was April 1, 1991. The delivery date,
which was determined from the NSAPD, was
not used in the administrative definitions,
but was used only to place the cases in
the appropriate time intervals. Only patient
obstetrical and diabetes records were
retained.
Analyses compared the reference standard
to two modifications of the application of
the NDSS case definition to this pregnant
population (Algorithm B and C, Table 2)
and two alternate definitions using admini­
strative databases (Algorithm D and E,
Table 2). Algorithm B removed diabetes
mellitus claims followed within 150 days
by an obstetrical claim (instead of 120 days
used in the NDSS definition) to identify
a case of pre-existing diabetes mellitus.
Algorithm C required three (not two) MSI
physician claims (within two years) or
one hospital claim to identify a case of
pre-existing diabetes mellitus. Algorithm D
was defined by using only hospitalizations
with ICD-9 and ICD-10 diagnostic codes
specific for diabetes mellitus in pregnancy
(Table 1b) for the duration of the study
(1991–2003) from the CIHI-DAD, because
the fourth digit for the ICD-9 code 648,
which distinguishes pre-existing diabetes in
pregnancy (ICD-9 648.0) from gestational
diabetes (ICD-9 648.8), only became
available for MSI physician claims in Nova
Scotia on March 31, 1996. Algorithm E
required either the application of the original
NDSS case definition to this pregnant
population or at least one hospitalization
with ICD-9 and ICD-10 diagnostic codes
specific for diabetes mellitus in pregnancy
(based on the model with either algorithm
A or D). The analysis was also done for
each algorithm separating the cohort into
those who delivered in tertiary hospitals
from those that delivered in non-tertiary
(regional or community) hospitals, and
also into two time periods, before and
after April 1, 1997.
The development and maintenance of
study databases such as those used in
this study is consistent with the
Tri-Council’s guidelines pertaining to
database linkages under their Code of
Ethical Conduct for Research Involving
Humans. This research project received
approval from the IWK Health Centre
Research Ethics Board and from the
Joint Data Access Committee of the RCP
of Nova Scotia.
Results
Linkage of the NSAPD and the administrative
databases housed by the PHRU, which
included the CIHI-DAD and MSI, yielded
41 533 nulliparous pregnancies in the
NSAPD with corresponding hospitalization
and outpatient physician visit administrative
codes. There were 8.4% less women in
the PHRU eligibility file compared to the
data file derived from the NSAPD.
Table 3 summarizes the sensitivity,
specificity, positive predictive value (PPV)
and negative predictive value (NPV) for the
evaluation of each algorithm of the NDSS
case definition used in comparison with
the reference standard diagnosis. During the
study period, 200 women with pre-existing
diabetes mellitus were identified using
Vol 32, No 3, June 2012 – Chronic Diseases and Injuries in Canada
116
the NSAPD, while 262 women who met
inclusion criteria were identified as having
pre-existing diabetes mellitus by applying
the NDSS case definition (Algorithm A).
The estimated prevalence in the study
population was 0.48% (95% CI 0.42–0.55)
using data from the NSAPD and 0.63%
(95% CI 0.56–0.71) using administrative
data based on the NDSS case definition
(31% higher prevalence in the NDSS).
Based on the reference standard, the NDSS
case definition of diabetes had a sensitivity
of 87.0%, specificity of 99.8%, PPV of
66.4% and NPV of 99.9%. There were
88 pregnancies falsely identified as having
pre-existing diabetes when applying the
NDSS case definition compared to the
reference standard. Of these 88 pregnancies,
22 were diagnosed by the NSAPD as having
gestational diabetes. The NSAPD does not
collect information on glucose intolerance
in pregnancy.
The consequences of variations in
components of the NDSS case definition
are summarized in Table 3. Modification
of the NDSS case definition to remove
women diagnosed with diabetes 150 days
preceding any pregnancy-related visit
(Algorithm B) slightly reduced the number
of false positive cases of diabetes mellitus
to 84, but also decreased the sensitivity
to 84.5% compared to the NSAPD.
Modification of the NDSS case definition
removing women with diabetes codes
120 days preceding or 90 days after any
pregnancy-related visit using three MSI
codes (Algorithm C) reduced the number
of pregnancies falsely identified as having
diabetes mellitus to 50, with a concurrent
slight decrease in sensitivity to 82.5%
compared to the NSAPD.
When testing the algorithm that used
diagnostic codes specifically for diabetes
mellitus in pregnancy among hospita­l­
izations (Algorithm D), we found that
228 pregnancies had at least one hospita­l­
ization with a diagnostic code for diabetes
mellitus in pregnancy during the study
period, while 200 pregnancies were identified by the NSAPD as having pre-existing
diabetes mellitus. Compared to the reference
standard, 51 pregnancies were falsely
identified with diabetes mellitus, with a
sensitivity of 88.5%, specificity of 99.9%,
PPV of 77.6% and NPV of 99.9% (Table 3).
When testing Algorithm E (based on the
model with either algorithm A or D),
sensitivity was increased to 92.0% but
PPV was decreased to 60.1% (Table 3).
Categorization by type of delivery hospital
(tertiary versus non-tertiary) showed higher
sensitivity and PPV for deliveries within a
tertiary hospital (n = 26 165) for all of the
algorithms compared to all pregnancies
combined or to deliveries in non-tertiary
hospitals (n = 15 368; Table 3). The best
performance was for Algorithm D for
deliveries in a tertiary hospital, where
the sensitivity was 98.0% and PPV was
82.0%. Poorer performance was seen
when applied to deliveries in non-tertiary
hospitals. The prevalence was lower than
the entire study population when deliveries
occurred in non-tertiary hospitals (0.31%)
and higher when deliveries occurred in
tertiary hospitals (0.59%).
Categorization by period (before April 1,
1997, n = 20 993, or equal to or later than
April 1, 1997, n = 20 540) showed a very
slightly higher sensitivity in the later time
period, but poorer PPV (71.3% in the
earlier time period versus 63.4% in the
later time period), with application of
the NDSS case definition (algorithm A)
(Table 4). For all the other algorithms,
only small differences were observed in
the test characteristics between the two
time periods (Table 4). The prevalence was
lower than the entire study population
when deliveries occurred in the first
period (0.40%) and higher when deliveries
occurred in the second (0.57%).
Table 3
Test characteristics of the NDSS case definition compared to the NSAPD (reference standard)
for nulliparous pregnancies, by type of delivery hospital, Nova Scotia, 1991–2003
Algorithm
A (NDSS)
B
C
D
E
All pregnancies
Sensitivity
% (95% CI)
Specificity
% (95% CI)
PPV
% (95% CI)
NPV
% (95% CI)
87.0 (81.4–91.1)
99.8 (99.7–99.8)
66.4 (60.3–72.0)
99.9 (99.9–99.9)
Delivery in a non-tertiary hospital
72.3 (57.1–84.0)
99.8 (99.7–99.8)
46.6 (35.0–58.6)
99.9 (99.9–100)
Delivery in a tertiary hospital
91.5 (85.6–95.2)
99.8 (99.6–99.8)
74.1 (67.1–80.0)
99.9 (99.9–100)
84.5 (78.6–89.1)
99.8 (99.8–99.9)
66.8 (60.6–72.5)
99.9 (99.8–100)
Delivery in a non-tertiary hospital
70.2 (54.9–82.2)
99.8 (99.8–99.8)
46.5 (34.7–58.6)
99.9 (99.9–100)
Delivery in a tertiary hospital
88.9 (82.6–93.2)
99.8 (99.7–99.8)
74.7 (67.7–80.7)
99.9 (99.9–99.9)
82.5 (76.4–87.4)
99.9 (99.8–99.9)
76.7 (70.4–82.1)
99.9 (99.8–99.9)
Delivery in a non-tertiary hospital
68.1 (52.8–80.1)
99.9 (99.8–99.9)
68.1 (52.8–80.5)
99.9 (99.9–100)
Delivery in a tertiary hospital
86.9 (80.3–91.6)
99.9 (99.8–99.9)
82.6 (75.7–88.0)
99.9 (99.9–100)
88.5 (83.1–92.4)
99.9 (99.8–99.9)
77.6 (71.6–82.8)
99.9 (99.9–100)
Delivery in a non-tertiary hospital
57.4 (42.3–71.4)
99.9 (99.8–99.9)
60.0 (44.4–73.9)
Delivery in a tertiary hospital
98.0 (93.9–99.5)
99.9 (99.8–99.9)
82.0 (75.5–87.1)
100.0 (100–100)
100.0 (99.9–100)
All pregnancies
All pregnancies
All pregnancies
All pregnancies
99.9 (99.8–99.9)
92.0 (87.1–95.2)
99.7 (99.7–99.8)
60.1 (54.4–65.6)
Delivery in a non-tertiary hospital
72.3 (57.1–83.9)
99.6 (99.5–99.7)
38.2 (28.3–49.2)
99.9 (99.9–100)
Delivery in a tertiary hospital
98.0 (93.9–99.5)
99.7 (99.7–99.8)
69.1 (62.5–75.1)
100.0 (100–100)
Abbreviations: CI, confidence interval; NDSS, National Diabetes Surveillance System; NPV, negative predictive value; NSAPD, Nova Scotia Atlee Perinatal Database;
PPV, positive predictive value.
Table 4
Test characteristics of the NDSS case definition compared to the NSAPD (reference standard)
for nulliparous pregnancies, by period, Nova Scotia, 1991–2003
Algorithm
Sensitivity
% (95% CI)
Specificity
% (95% CI)
PPV
% (95% CI)
Delivery before April 1, 1997
85.7 (76.0–92.1)
99.9 (99.8–99.9)
71.3 (61.3–79.6)
99.9 (99.9–100)
Delivery April 1, 1997, or later
87.9 (80.3–93.0)
99.7 (99.7–99.8)
63.4 (55.4–70.7)
99.9 (99.9–100)
B
Delivery before April 1, 1997
81.0 (70.6–88.4)
99.9 (99.5–99.6)
71.6 (61.3–80.1)
99.9 (99.9–100)
Delivery April 1, 1997, or later
87.1 (79.3–92.3)
99.7 (99.6–99.8)
63.9 (55.9–71.3)
99.9 (99.9–100)
C
Delivery before April 1, 1997
79.8 (69.3–87.4)
99.9 (99.8–99.9)
79.8 (69.3–87.4)
99.9 (99.9–100)
Delivery April 1, 1997, or later
84.5 (76.3–90.3)
100.0 (99.9–100)
74.8 (66.3–81.8)
99.9 (99.9–100)
Delivery before April 1, 1997
82.1 (71.9–89.3)
99.9 (99.8–99.9)
72.6 (62.4–81.0)
99.9 (99.9–100)
Delivery April 1, 1997, or later
93.1 (86.4–96.8)
99.9 (99.8–99.9)
81.2 (73.3–87.3)
99.9 (99.9–100)
Delivery before April 1, 1997
89.3 (80.2–94.7)
99.8 (99.7–99.8)
61.5 (52.2–70.0)
100.0 (99.9–100)
Delivery April 1, 1997, or later
94.0 (87.5–97.3)
99.6 (99.5–99.7)
59.2 (51.8–66.3)
100.0 (99.9–100)
A (NDSS)
D
E
NPV
% (95% CI)
Abbreviations: CI, confidence interval; NDSS, National Diabetes Surveillance System; NPV, negative predictive value; NSAPD, Nova Scotia Atlee Perinatal Database;
PPV, positive predictive value.
117
Vol 32, No 3, June 2012 – Chronic Diseases and Injuries in Canada
Discussion
Accurate identification of a population with
diabetes quantifies the burden of disease,
but also contributes to the evaluation
of disease management and outcomes
associated with diabetes. Studies employing
the NDSS case definition for the diagnosis of
diabetes mellitus in the general population
have demonstrated high ascertainment rates
with the original case definition,12 but
have improved at estimating incidence
by adding clearance periods to minimize
the inclusion of prevalent cases,18 by
modifying the number of hospitalizations
or physician visits in the NDSS criteria,2,15
or by adding clinical data to the original
case definition.2,16,17,19 The application of the
NDSS case definition to a subpopulation
such as pregnancy is challenging. We
demonstrated that applying the NDSS
case definition to a pregnant population
underestimated true cases of pre-existing
diabetes mellitus (sensitivity 87%) and
a high number of false positive cases
(PPV 66%). The prevalence of pre-existing
diabetes mellitus among pregnant women
in Nova Scotia was 0.5% using the reference
standard, lower than the general female
population in Canada as identified by
the NDSS (0.7%–2.5% in 2006–2007 in
women of child-bearing age).14 Grouping
by type of delivery hospital increased
both the sensitivity and the PPV for
those delivering in a tertiary hospital,
but usually resulted in poorer results
for non-tertiary hospitals. The algorithm
employing only hospitalization diagnostic
codes for pre-existing diabetes in pregnancy
(Algorithm D) among women delivering
in tertiary centres performed the best,
with sensitivity 98%, specificity 99.9%,
PPV 82%, and NPV 100% compared to
the reference standard (NSAPD). However,
using an algorithm which excludes both
outpatients and non-tertiary hospitals
would limit the province-wide assessment
of diabetes in pregnancy needed for
programming and making policy decisions.
The false positive cases identified by
applying the NDSS case definition to the
studied pregnant population in Nova Scotia
may reflect coding errors or misdiagnosis,
such as coding glucose intolerance
as diabetes in administrative data. The
low PPV suggests a high potential for
misclassifying non-diabetic individuals as
having diabetes mellitus. Implications of
this misclassification become apparent
when potential uses of the administrative
data are considered. For an outcome study
on the effect of pre-existing diabetes on
birth outcomes, this degree of misclassification would be a major source of bias;
if an administrative definition of preexisting diabetes was used as part of a
risk adjustment in a study in pregnancy
examining an additional risk factor, then
the misclassification would result in residual
confounding. However, since the prevalence
of pre-existing diabetes mellitus is small
(0.5%–0.6%), the residual confounding
resulting from misclassification would
be small from the perspective of absolute
numbers of misclassified women. In
addition, if the administrative definition
was used descriptively to measure the
prevalence of pre-existing diabetes in
pregnancy, the degree to which the
misclassification biases the prevalence
estimates should be taken into account.
The influence of misclassification bias
in understanding results using large
administrative databases was recently
highlighted in a cohort evaluation of
the identification of diabetes mellitus in
Ontario.28 The authors emphasized the
need for verifying the accuracy following
the mass application of identification
criteria to minimize misclassification
bias, compared to regularly validated data
collection employed by electronic databases
such as the NSAPD.
Evaluation of the NDSS case definition
applied to a population of pregnant women
using the NSAPD demonstrated higher
sensitivity and PPV for women who
delivered at tertiary centres compared to
those delivered at non-tertiary hospitals.
Pregnancies complicated by severe diabetes
mellitus may be preferentially delivered at
a tertiary maternity facility, introducing
severity bias into the assessment of the
NDSS case definition. This difference in
level of hospital for delivery may also
represent variability in coding practice
among centres. Additionally, specialists
and subspecialists involved in the care of
pregnant women with diabetes may be
more likely to accurately code for
pre-existing diabetes mellitus than general
practitioners, as has been demonstrated
Vol 32, No 3, June 2012 – Chronic Diseases and Injuries in Canada
118
with other systemic diseases outside of
pregnancy and where medical care unrelated
to the disease is required.29,30
A switch from the ICD-9 to ICD-10 coding
system occurred in April 1997 in Nova
Scotia, but despite this factor, the study
interval did not affect the operating
characteristics. This observation may be a
result of improved coding as coders gained
experience with new coding systems,31
balanced with increasing reimbursement
for medical services using alternate funding
programs established by the government
of Nova Scotia. This change in the
environment of funding, with a variable
requirement for shadow billing to document
clinical care, may have resulted in
decreased accuracy in coding. In particular,
there was a growth in alternate funding
programs in the tertiary care centres in
Nova Scotia in later years of the study.
Alshammari and Hux demonstrated that
detection of chronic disease is more likely
with hospitalization, but that these diseases
are less likely to be detected in surveillance
programs dependent on administrative data
algorithms in non-fee-for-service settings.16
Chronic diseases such as diabetes mellitus
are treated largely on an outpatient basis,
and surveillance efforts are heavily
dependent on outpatient physician services
claims. In the NDSS, nearly 75% of cases
are detected by physician claims alone.16 For
this population of women who delivered
in Nova Scotia hospitals, the hospitalization
code for pregnancies complicated by
pre-existing diabetes is a more accurate
method for identifying diabetes mellitus
than the NDSS case definition. The addition
of this hospitalization code (for pregnancies
complicated by pre-existing diabetes) to the
NDSS definition for the general population
should increase sensitivity; however PPV
may decrease.
The validation of administrative databases
typically occurs with medical record
audits, and results of validation studies have
varied depending on the type of administrative data (inpatient versus outpatient and
diagnostic versus procedural), specific
disease area and codes used for case
identification, and disease severity.32 Some
provinces continue to use three-digit
coding, which may decrease the PPV.
Employing administrative databases for
the ascertainment of diagnoses is
challenging in light of varying coding
practices and the accuracy and comprehen­
siveness of data sources.33,34 The NSAPD is
a validated database25 and has been used to
validate perinatal data in the CIHI-DAD.35
It is considered a reference standard
component of the Nova Scotia Diabetes
Repository.21 The population-based nature
of the administrative databases and the
NSAPD in this study limits the selection
bias that may occur with single-centre
validation studies. In addition, health
surveillance increases in pregnancy, reducing
rates of undiagnosed diabetes.9,23 It would
be important to validate the NDSS case
definition using other perinatal database
sources to rule out a regional bias in
the comparison population,28 and to
assess coding quality and the coding
environments in different provinces and
regions.29
A limitation to this validation study
includes the introduction of new provincial
health card numbers after 1995. Before
this time, women had their father’s (if
under 18) or their husband’s (if married)
social insurance number plus a suffix, for
a health card number (HCN), while after
1995 they were assigned their own HCN.
Both the PHRU and the RCP have optimized
mapping of the old to the new HCN;
however, there may be occurrences where
mapping is incomplete. This would lead
to women appearing in the data as left
censored or lost to follow-up when the
old MSI number is changed, and would
underestimate the prevalence of pre-existing
diabetes.
The PPV of case definitions derived from
administrative data is highly dependent
on the prevalence of diabetes mellitus in
the population to which they are applied.
Accordingly, as prevalence decreases, more
stringent case definitions are required
in order to have an acceptable PPV.27 In
this study, the hospitalization code for
pregnancies complicated by pre-existing
diabetes performed the best. Other modifications could include the addition of
clinical or laboratory data to improve
detection.17
Conclusion
Validation of the NDSS case definition
using the NSAPD as the reference standard
diagnosis demonstrated adequate sensitivity
but low positive predictive values. In the
Nova Scotia pregnant population, admi­
nistrative data using the ICD-9 and ICD-10
codes for diabetes mellitus in pregnancy
from the CIHI-DAD (hospitalization database) alone appear to be a more accurate
data source for the identification of
pre-existing diabetes than the application
of the NDSS case definition, particularly
when pregnant women are delivered in
a tertiary hospital. Although the NDSS
definition of diabetes performs reasonably
well compared to a reference standard
definition of diabetes, using this definition
for evaluating maternal and perinatal
outcomes associated with diabetes in
pregnancy will result in a certain degree
of misclassification and, therefore, biased
estimates of outcomes.
Acknowledgements
This study was funded by the Canadian
Institutes of Health Research (CIHR). VMA
and LD were supported by a Clinical
Research Scholar Award from Dalhousie
University and the New Investigator
Award from CIHR. The authors thank the
Reproductive Care Program of Nova Scotia
and the Population Health Research Unit
of Dalhousie University for data access.
Although this research is based partially
on data obtained from the Population
Health Research Unit, the observations
and opinions expressed are those of the
authors and do not represent those of the
Population Health Research Unit. The
authors thank the Diabetes Care Program
of Nova Scotia (DCPNS) for assistance
with the methodology.
References
1. Saydah SH, Geiss LS, Tierney E,
Benjamin SM, Engelgau M, Brancati F.
Review of the performance of methods to
identify diabetes cases among vital statistics,
administrative, and survey data. Ann
Epidemiol. 2004;14:507-16.
119
2. Southern DA, Roberts B, Edwards A, Dean S,
Norton P, Svenson LW, et al. Validity of
administrative data claim-based methods
for identifying individuals with diabetes at
a population level. Can J Public Health.
2010;101:61-4.
3. Joseph KS, Allen AC, Dodds L, Turner LA,
Scott H, Liston R. The perinatal effects of
delayed childbearing. Obstet Gynecol.
2005;105:1410-8.
4. Joseph KS, Young DC, Dodds L,
O’Connell CM, Allen VM, Chandra S, et al.
Changes in maternal characteristics and
obstetric practice and recent increases in
primary cesarean delivery. Obstet Gynecol
2003;102:791-800.
5. Robinson HE, O’Connell CM, Joseph KS,
McLeod NL. Maternal outcomes in
pregnancies complicated by obesity.
Obstet Gynecol. 2005;106:1357-64.
6. Pridjian G. Pregestational diabetes. Obstet
Gynecol Clin North Am. 2010;37:143-58.
7. Johnson JA, Pohar SL, Majumdar SR.
Health care use and costs in the decade
after identification of type 1 and
type 2 diabetes: a population-based study.
Diabetes Care. 2006;29:2403-8.
8. Feig DS, Razzaq A, Sykora K, Hux JE,
Anderson GM. Trends in deliveries,
prenatal care, and obstetrical complications
in women with pregestational diabetes:
a population-based study in Ontario,
Canada,
1996-2001.
Diabetes
Care.
2006;29:232-5.
9. Yang J, Cummings EA, O’Connell C,
Jangaard K. Fetal and neonatal outcomes
of diabetic pregnancies. Obstet Gynecol.
2006;108:644-50.
10. Rosenberg TJ, Garbers S, Lipkind H,
Chiasson MA. Maternal obesity and diabetes
as risk factors for adverse pregnancy
outcomes: differences among 4 racial/
ethnic groups. Am J Public Health.
2005;95:1545-51.
11. Jensen DM, Damm P, Moelsted-Pedersen L,
Ovesen P, Westergaard JG, Moeller M,
Beck-Nielsen H. Outcomes in type 1
diabetic pregnancies: a nationwide,
population-based study. Diabetes Care.
2004;27:2819-23.
Vol 32, No 3, June 2012 – Chronic Diseases and Injuries in Canada
12. Blanchard JF, Ludwig S, Wajda A, Dean H,
Anderson K, Kendall O, et al. Incidence
and prevalence of diabetes in Manitoba,
1986-1991. Diabetes Care. 1996;19:807-11.
13. Clottey C, Mo F, LeBrun B, Mickelson P,
Niles J, Robbins G. The development of the
National Diabetes Surveillance System
(NDSS) in Canada. Chron Dis Can.
2001(2);22:67-9.
14. Report from the National Diabetes
Surveillance
System:
Diabetes
in
Canada, 2009 [Internet]. Ottawa (ON):
Public Health Agency of Canada; 2009.
Available from: http://www.phac-aspc.gc.ca
/publicat/2009/ndssdic-snsddac-09/pdf
/report-2009-eng.pdf
15. Hux JE, Ivis F, Flintoft V, Bica A. Diabetes
in Ontario: determination of prevalence and
incidence using a validated administrative
data algorithm. Diabetes Care. 2002;25:512-6.
16. Alshammari AM, Hux JE. The impact of
non-fee-for-service reimbursement on chronic
disease surveillance using administrative
data. Can J Public Health. 2009;100:472-4.
17. Chen G, Khan N, Walker R, Quan H.
Validating ICD coding algorithms for diabetes
mellitus from administrative data. Diabetes
Res Clin Pract. 2010;89:189-95.
18. Asghari S, Couteau J, Carpentier AC,
Vanasse A. Optimal strategy to identify
incidence of diagnostic of diabetes using
administrative data. BMC Med Res
Methodol. 2009;9:62.
19. Ho ML, Lawrence N, van Walraven C,
Manuel D, Keely E, Malcolm J, et al. The
accuracy of using integrated electronic
health care data to identify patients
with undiagnosed diabetes mellitus.
J Eval Clin Pract. 2011 Feb 17. doi:
10.1111/j.1365-2753.2011.01633.x.
20. National Diabetes Surveillance System.
Responding to the challenge of diabetes in
Canada: first report of the NDSS, 2003.
Ottawa (ON): Health Canada; 2003 [cited
2010 Nov 22]. Available from: http://www.
phac-aspc.gc.ca/ccdpc-cpcmc/ndss-snsd
/english/pubs_reports/pdf/WEB_NDSS
_English_Report-nocover.pdf
21. Diabetes Care Program of Nova Scotia.
Development of a Nova Scotia Diabetes
Repository: Provincial Report. Halifax (NS):
Diabetes Care Program of Nova Scotia;
Aug 2009.
22. Statistics Canada. 2006 Community
profiles [Internet]. Ottawa (ON): Statistics
Canada; 2006 [modified 2011 Jun 06; cited
2010 Nov 25]. Available at: http://www12
.statcan.ca/census-recensement/2006
/dp-pd/index-eng.cfm
23. McMahon MJ, Ananth CV, Liston RM.
Gestational diabetes mellitus. Risk factors,
obstetric complications and infant outcomes.
J Reprod Med. 1998;43:372-8.
24. Russell C, Dodds L, Armson BA, Kephart G,
Joseph KS. Diabetes mellitus following
gestational diabetes: role of subsequent
pregnancy. BJOG. 2008;115:253-60.
25. Fair M, Cyr M, Allen AC, Wen SW, Guyon G,
MacDonald RC. An assessment of the
validity of a computer system probabilistic
record linkage of birth and infant death
records in Canada. Chronic Dis Can.
2000(1);21:8-13.
26. Reproductive Care Program of Nova Scotia.
The Nova Scotia Atlee Perinatal Database
[Internet]. Halifax (NS): RCP; [cited 2011
Jul 17]. Available at: http://rcp.nshealth.ca
/atlee-database
27. Gabbe SG, Niebyl JR, Simpson JL, editors.
Obstetrics: normal and problem pregnancies.
5th ed. Philadelphia (PA): Churchill
Livingstone; 2007.
28. Manuel DG, Rosella LC, Stukel TA. The
importance of accurately identifying
disease in studies using electronic health
records. BMJ. 2010;341:c4226. doi: 10.1136/
bmj.c4226.
29. Myers RP, Shaheen AA, Fong A, Wan AF,
Swain MG, Hilsden RJ, et al. Validation of
coding algorithms for the identification of
patients with primary biliary cirrhosis
using
administrative
data.
Can
J
Gastroenterol. 2010;24:175-82.
30. Farrokhyar F, McHugh K, Irvine EJ.
Self-reported awareness and use of the
International Classification of Diseases
coding of inflammatory bowel disease
services by Ontario physicians. Can J
Gastroenterol. 2002;16:519-26.
Vol 32, No 3, June 2012 – Chronic Diseases and Injuries in Canada
120
31. Quan H, Li Bing, Saunders LD, Parsons GA,
Nilsson CI, Alibhai A, et al.; IMECCHI
Investigators. Assessing validity of ICD-9-CM
and ICD-10 administrative data in recording
clinical conditions in a unique dually coded
database. Health Serv Res. 2008;43:1424-41.
32. Myers RP, Leung Y, Shaheen AAM, Li B.
Validation of ICD-9-CM/ICD-10 coding
algorithms for the identification of
patients with acetaminophen overdose and
hepatotoxicity using adminstrative data.
BMC Health Serv Res. 2007;7:159.
33. Leslie WD, Lix LM, Yogendran MS.
Validation of a case definition for
osteoporosis
disease
surveillance.
Osteoporos Int. 2011;22:37-46. doi: 10.1007/
s00198-010-1225-2.
34. Juurlink D, Preyra C, Croxford R, Chong A,
Austin P, Tu J, et al. Canadian Institute for
Health Information Discharge Abstract
Database: a validation study [Internet].
Toronto (ON): Institute for Clinical
Evaluative Sciences; 2006 [cited 2011 Jul
17]. Available at: http://www.ices.on.ca
/file/CIHI_DAD_Reabstractors_study.pdf
35. Joseph KS, Fahey J. Validation of perinatal
data in the Discharge Abstract Database
of the Canadian Institute for Health
Information.
Chronic
Dis
Can.
2009(3);29:96-100.
Divergent associations between incident hypertension and
deprivation based on different sources of case identification
J. Aubé-Maurice, MD, MSc, FRCPC (1,2); L. Rochette, MSc (1); C. Blais, PhD (1,3)
This article has been peer reviewed.
Abstract
Introduction: Studies suggest that hypertension is more prevalent in the most deprived.
Our objective was to examine the association between incident hypertension and
deprivation in Quebec based on different modes of case identification, using two
administrative databases.
Methods: We identified new incident cases of hypertension in 2006/2007 in the population
aged 20 years plus. Socio-economic status was determined using a material and social
deprivation index. Negative binomial regression analyses were carried out to examine
the association between incident hypertension and deprivation, adjusting for several
covariates.
Results: We found a positive and statistically significant association between material
deprivation and incident hypertension in women, irrespective of the identifying database.
Using the hospitalization database, the incidence of hypertension increased for both
sexes as deprivation increased, except for social deprivation in women. However, whether
using the physician billing database or the validated definition of hypertension obtained
by combining data from the two databases, the incidence of hypertension decreased
overall as deprivation increased.
Conclusions: Associations between hypertension and deprivation differ based on the
database used: they are generally positively associated with the hospitalization database
and inversely with the standard definition and the physician billing database, which
suggests a consultation bias in favour of the most socio-economically advantaged.
Keywords: hypertension incidence, socio-economic status, administrative databases
Introduction
About 1 in 5 people have been diagnosed
with arterial hypertension in Quebec, a
proportion similar to that of the entire
population of Canada.1,2 Moreover, the
prevalence of hypertension increased by
29% in Quebec between 2000/2001 and
2006/2007 and by 57% in Canada
between 1998/1999 and 2007/2008.1,2 The
incidence remained comparatively stable at
the Canadian level, whereas it decreased
slowly in Quebec, from approximately
31 per 1000 population in 2000/2001 to
25 per 1000 population in 2006/2007.1 The
divergence between the change in prevalence
and incidence over time is most likely
due to a decline in mortality, probably as
a result of better treatment and control.1,3
Because it is strongly associated with
cardiovascular, renal and cerebrovascular
diseases, suboptimal blood pressure is the
risk factor associated with the greatest
mortality in developed countries.4 Although
an important cause of mortality and
morbidity,5 hypertension is also a condition
that can be modified.6-8 In fact, apart from
age, sex, family antecedents and ethnic
origin, most risk factors for hypertension—
overweight, physical inactivity, high salt and
alcohol consumption and smoking9-11—
are associated with lifestyle. It is also
well accepted that some of these risk
factors are unequally distributed, usually
at the expense of those with lower
socio-economic status (SES).9,12
Several studies suggest at least a partial
link between SES, particularly material
deprivation,13 and hypertension. This link
remains statistically significant even when
adjusting for lifestyle characteristics9-11,14
and is often more pronounced in women.10
However, Tu et al. found no association
between income alone and incident hypertension in Ontario.15 Research that examined
the social component of deprivation13 found
an association between social deprivation
and hypertension.16-19 Most of the studies
reviewed were cross-sectional and examined
more specifically the relationship between
prevalent hypertension and SES.
Our objective was to examine the association
between incident hypertension and material
and social deprivation in Quebec based
on different modes of case identification,
using two administrative databases. We
expected to find a tendency similar to
the one identified in the literature, namely,
an inverse association between SES and
incident hypertension that is more
Author references:
1. Institut national de santé publique du Québec, Québec, Quebec, Canada
2. Faculté de médecine, Université Laval, Québec, Quebec, Canada
3. Faculté de pharmacie, Université Laval, Québec, Quebec, Canada
Correspondence: Claudia Blais, Institut national de santé publique du Québec, 945, avenue Wolfe, Québec, QC G1V 5B3; Tel.: (418) 650-5115 ext. 5708; Fax: (418) 643-5099;
Email: [email protected]
121
Vol 32, No 3, June 2012 – Chronic Diseases and Injuries in Canada
pronounced in women. We hypothesized
that the most materially and socially
advantaged people would present a lower
incidence of hypertension, possibly as a
result of a healthier lifestyle.9,20 We also
supposed that this association would differ
based on the administrative database used
to identify the cases. In fact, we predicted
that the hypertensive cases identified only
on the hospitalization database present more
comorbidities and a lower SES.
Methods
Study population and data sources
Our study population was aged 20 years and
more, lived in Quebec between 2006-04-01
and 2007-03-31, and was identified as newly
hypertensive based on a validated definition
of hypertension21 that is used in Ontario15
and Quebec1 and by the Public Health
Agency of Canada.2,22 The data used to
identify hypertension cases were drawn
from two administrative files, the physician
billing and the hospitalization databases.
The physician billing database compiles
every medical procedure billed to the Régie
de l’assurance maladie du Québec whereas
the hospitalization database provides
information about the principal diagnosis
and up to 15 or 25 secondary diagnoses,
depending on the year of compilation.
ICD-10* codes have been used in the
hospitalization database since 2006-04-01,
whereas the ICD-9† codes are still used
in the physician billing database. The
socio-demographic information from both
databases is also found in the health
insurance registry database. The data used
are based on a longitudinal follow-up of
hypertension since 1996-01-01.1
Case definition
The case definition of hypertension selected
(“standard definition”) corresponds to the
following criteria: one hospitalization or
two or more physician claims within two
years, identified by one or more of the
hypertension-related diagnoses codes: 401,
402, 403, 404 or 405 in ICD-9 or I10, I11, I12,
I13 or I15 in ICD-10. This case definition has,
according to a validation study conducted
in Ontario, a sensitivity of 72%, a specificity
of 95%, and a positive and negative
predictive value of 87% and 88%,
respectively.21 According to this definition,
the codes associated with hypertension
identified within the 120 days preceding
or 180 days following an obstetrical event
(641–676 or V27 in ICD-9 or O1, O21–O95,
O98, O99 or Z37 in ICD-10) are excluded as
they could be related to pregnancy-induced
hypertension. In order to verify that the
associations differed based on the source
of case identification, the hypertensive
individuals identified with the physician
billing database were separated from
those identified with the hospitalization
database.
Deprivation index
As the administrative databases contain
neither psychosocial nor material characteristics, we used the material and social
deprivation index, a geographical proxy of
the SES containing six indicators that can
be linked to the administrative databases
by postal code.13,23 These six indicators
reflect the two types of deprivation, which
were assigned to the individuals living
within each census dissemination area.
The material deprivation is determined
by 1) the proportion of persons who have
no high-school diploma; 2) the ratio of
employment to population; and 3) average
personal income. The social deprivation is
determined by the proportion of 1) persons
who are separated, divorced or widowed;
2) people living alone; and 3) single-parent
families. With the exception of the last
category, these indicators are adjusted for the
age and sex.23 Each of the two components
of the index is divided into quintiles, the
most deprived people in the population
being in the fifth quintile (Q5).
Statistical analysis
An exploratory descriptive analysis
compared the profile of individuals in
the general population with one identified
as newly hypertensive. We used a negative
binomial regression to examine the
association between incident hypertension
and material and social deprivation. Two
* International Classification of Diseases, 10th Revision.
†
International Classification of Diseases, 9th Revision.
Vol 32, No 3, June 2012 – Chronic Diseases and Injuries in Canada
122
models were used: the first included patients
identified as newly hypertensive based on
the standard definition, and the second
distinguished the patients based on their
identification database (hospitalization
database versus physician billing database).
The analysis was adjusted for age and
geographical area of residence, and stratified
for sex. The 2001 census was used as a
reference for the adjustment of incidence
rates for age. Analysis of material deprivation
was adjusted for social deprivation, and vice
versa. The reference group was the most
advantaged (Q1). Interaction between age
and sex and between deprivation and sex
were verified. The statistical threshold for
the analyses was p ≤ .05. All the analyses
were conducted using the statistical package
SAS, version 9.1.3 (SAS Institute Inc.).
Results
The deprivation index could be assigned
to 92% of our newly hypertensive cohort.
Those who were unassigned did not have a
permanent address or lived in areas where
the index could not be attributed (as a result
of being very small census geographical
units, very sparsely populated or on Cree
or Inuit territories and including health or
social services institutions of more than
75 beds).13 Approximately 20% of the cases
were identified with the hospitalization
database and 80% with the physician billing
database. Table 1 shows that 45% of the
general population (≥ 20 years) was aged
between 20 and 44 years. In spite of being
the largest in size, this age group had the
smallest number of newly hypertensive
cases, irrespective of the definition used.
Table 2 shows approximately 20% of the
population in each deprivation quintile, as
expected. The subsequent exclusion from
each quintile of people aged less than
20 years and those for whom no deprivation
index could be assigned explains why each
does not represent exactly 20% of the
population. Using the standard definition,
and after excluding the most advantaged
quintile (Q1), the incidence of hypertension
decreased as the level of material deprivation
increased. The association was the same for
social deprivation, but the increase was
Table 1
Distribution of the study population according to method of case identification and age-specific incidence rate, 2006/2007, Quebec, Canada
Age, years
All adults aged ≥ 20 years
Method of case identification
Standard definition of
hypertension
n
%
Hospitalization database
ASIR
(per 1000)
na
n
Physician billing database
ASIR
(per 1000)
n
ASIR
(per 1000)
20–44
2 686 955
45.28
12 958
4.97
1 065
0.41
11 677
4.60
45–64
2 172 123
36.60
45 121
26.73
6 922
3.87
37 609
26.70
≥ 65
1 075 101
18.12
30 754
71.28
9 701
12.36
20 584
56.02
Abbreviation: ASIR, age-specific incidence rate.
Note: The study population consists of adults aged ≥ 20 years and newly identified as hypertensive.
a
The number of people identified with the standard definition is not the sum of the people identified with the hospitalization database and the physician billing database; around 4%
of the people are identified with both databases. These 4% are only included in the standard definition.
Table 2
Characteristics of study population according to the method of case identification
and age-adjusted incidence rate, 2006/2007, Quebec, Canada
Method of case identification
All adults aged ≥ 20 years
n
Standard definition of
hypertension
%
n
AAIR
(per 1000)
Hospitalization database
n
AAIR
(per 1000)
Physician billing database
n
AAIR
(per 1000)
Material deprivation
Q1 (most advantaged)
1 067 990
19.99
16 527
31.19
2 763
2.93
13 661
20.57
Q2
1 063 965
19.92
16 969
33.15
2 999
3.23
13 827
21.27
Q3
1 072 000
20.07
17 449
31.49
3 371
3.38
13 887
20.01
Q4
1 072 410
20.08
17 457
30.36
3 653
3.58
13 664
19.20
Q5 (most disadvantaged)
1 065 005
19.94
17 233
28.09
4 247
4.18
12 924
17.31
1 009 705
18.90
16 576
37.13
3 029
3.65
13 459
22.31
Social deprivation
Q1 (most advantaged)
Q2
1 033 605
19.35
16 813
32.59
3 218
3.52
13 470
20.36
Q3
1 060 605
19.86
17 564
30.93
3 454
3.46
13 994
19.83
Q4
1 097 045
20.54
17 885
29.59
3 541
3.29
14 215
19.40
Q5 (most disadvantaged)
1 140 410
21.35
16 797
26.69
3 791
3.51
12 825
16.98
Women
3 036 049
51.16
42 434
23.18
7 321
2.71
34 463
21.00
Men
2 898 130
48.84
46 399
25.76
10 367
4.72
35 407
20.61
2 518 670
47.15
43 061
37.63
7 967
3.57
34 718
23.39
1 028 885
19.26
16 188
37.94
2 926
3.19
13 192
22.42
644 670
12.07
10 446
32.51
2 314
3.76
8 094
19.33
1 149 145
21.51
18 410
26.41
4 481
3.97
13 866
16.38
Sex
Geographical area
Montreal
CMAs
a
Agglomerations
b
Ruralc
Abbreviations: AAIR, average age-adjusted incidence rate; CMA, census metropolitan area; Q, quintile.
Notes: Q1 = most advantaged; Q5 = most disadvantaged
The study population consists of adults aged ≥ 20 years and newly identified as hypertensive.
a
Other census metropolitan areas, populations > 100 000 inhabitants (Québec, Sherbrooke, Trois-Rivières, Saguenay and Gatineau).
b
Mid-size cities, population 10 000–100 000 inhabitants.
c
Small towns and rural settings, populations < 10 000.
123
Vol 32, No 3, June 2012 – Chronic Diseases and Injuries in Canada
Table 3 shows the results of the multivariate
analyses. We did not find any statistically
significant interactions between each
type of deprivation and method of case
identification, that is, physician billing
database or hospitalization database. As
the interaction between age and sex was
statistically significant (p = .0011), the
results are stratified by sex. The results
obtained with the standard definition
showed a positive association between age
and incident hypertension for both sexes,
with the oldest age group (≥ 65 years)
having a relative risk of hypertension
7 times that of the youngest age group
(20–44 years). Figure 1 shows the same
positive associations between age and
hypertension with the hospitalization and
physician databases. Women and men in
the oldest age group (≥ 65 years) have an
adjusted incidence rate of hypertension
24 and 29 times, respectively, that of those
in the youngest group (20–44 years) when
identified with the hospitalization database.
The positive association between age and
hypertension is less pronounced when
using the physician billing database (relative
risk [RR] ≈ 5 times).
deprivation, and is statistically significant
only for Q4 and Q5. There was no significant
association between material deprivation
and the incidence of hypertension in men,
but social deprivation influences the
incidence of hypertension for men in the
same way as for women (RRQ5 = 0.87),
the association also being statistically
significant only for Q4 and Q5.
For cases identified with the hospitali­zation
database (Table 3 and Figure 3), there is
a positive and statistically significant
association between material deprivation
and the incidence of hypertension in women
(RRQ5 = 1.60), though the association
between incident hypertension and social
deprivation is not statistically significant. In
men, the association between the incidence
of hypertension and material deprivation
is also positive, but it is statistically
significant only for Q3 to Q5 (RRQ5 = 1.29).
The association between incident hypertension and social deprivation in this
group is positive but statistically significant
only for the most deprived quintile
(RRQ5 = 1.14).
When incident cases are identified with
the physician billing database (Table 3 and
Figure 4), the associations are similar to
those found using the standard definition.
In women, the positive association between
material deprivation and hypertension is
weak and statistically significant only for
Q3 to Q5 (RRQ5 = 1.07). In contrast,
there is an inverse association between
hypertension and social deprivation that
is statistically significant only for Q4 and
Q5 (RRQ5 = 0.80). In men, the association
between material deprivation and the
incidence of hypertension is inversely
related but statistically significant only for the
most deprived quintile, Q5 (RRQ5 = 0.94),
while the level of social deprivation is,
as for women, inversely associated with
incident hypertension and statistically
significant only for Q3 to Q5 (RRQ5 = 0.81).
Discussion
Our results demonstrate divergent
associations between the incidence of
hypertension and deprivation in people
aged 20 years and more in Quebec during
Figure 1
Adjusted relative risk of men and women by the standard definition of hypertension
and methods of case identification, by age, 2006/2007, Quebec, Canada
*
30
25
Relative Risk
larger and steadier. The associations differ
when we take into account the database
used for case identification: using the hospitalization database, hypertension increases
as material deprivation increases, whereas
the association is less pronounced for social
deprivation; for cases identified with the
physician billing database, hypertension
decreases as the level of material and social
deprivation increases, the same as with the
standard definition. Men identified with the
hospitalization database show an incidence
of hypertension almost twice that of women
(4.72 per 1000 population versus 2.71
per 1000 population) (see Table 2). The
incidence rate of hypertension is higher in
urban areas with the standard definition
and with the physician billing database
than with the hospitalization database.
*
20
15
*
*
10
5
*
*
*
*
*
*
*
0
Standard
definition
Hospitalization
Physician
database
billing database
Standard
definition
45–64 years
As in Table 3, Figure 2 shows a positive and
statistically significant association between
material deprivation in women and
incidence of hypertension, as defined by
the standard definition (RRQ5 = 1.15). The
association between social deprivation and
incident hypertension in women is the
opposite (RRQ5 = 0.83) to that of material
*
Women
Men
5.32
4.78
7.86
10.29
Hospitalization
Physician
database
billing database
≥ 65 years
5.09
4.27
7.24
6.82
23.80
28.71
5.77
4.77
Mode of case identification of hypertension
Notes: The relative risks for the people aged between 20–44 years were chosen as the reference and are not shown in this
graph. The relative risks for the 45–64 and ≥65 years age groups were adjusted for the level of material and social deprivation
and the area of residence.
The study population consists of adults aged ≥ 20 years and newly identified as hypertensive.
* Statistically significant results, p < .0001.
Vol 32, No 3, June 2012 – Chronic Diseases and Injuries in Canada
124
Table 3
Relative risk of male and female study population according to the method of case identification, by age,
geographical area of residence, and material and social deprivation, 2006/2007, Quebec, Canada
Method of case identification
Standard definition of hypertension
Women
Age, years
20–44 (ref)
45–64
≥ 65
Geographical area
Montreal (ref)
CMAsa
Agglomerations b
Ruralc
Material deprivation
Q1 (most advantaged) (ref)
Q2
Q3
Q4
Q5 (most disadvantaged)
Social Deprivation
Q1 (most advantaged) (ref)
Q2
Q3
Q4
Q5 (most disadvantaged)
Men
Age, years
20–44 (ref)
45–64
≥ 65
Geographical area
Montreal (ref)
CMAsa
Agglomerationsb
Ruralc
Material deprivation
Q1 (most advantaged) (ref)
Q2
Q3
Q4
Q5 (most disadvantaged)
Social Deprivation
Q1 (most advantaged) (ref)
Q2
Q3
Q4
Q5 (most disadvantaged)
Hospitalization database
RR
95% CI
p
1.00
5.32*
7.24*
–
5.10–5.55
6.93–7.56
–
<.0001
<.0001
1.00
7.86*
23.80*
–
7.02–8.82
21.30–26.64
1.00
0.89*
0.89*
0.82*
–
0.85–0.93
0.85–0.93
0.78–0.85
–
<.0001
<.0001
<.0001
1.00
0.86*
1.05
1.04
1.00
1.06*
1.07*
1.10*
1.15*
–
1.00–1.12
1.02–1.13
1.04–1.16
1.09–1.21
–
.0321
.0091
.0004
<.0001
1.00
0.97
0.95
0.92*
0.83*
–
0.92–1.02
0.91–1.00
0.88–0.97
0.79–0.88
1.00
4.78*
6.82*
RR
Physician billing database
p
95% CI
p
RR
95% CI
–
<.0001
<.0001
1.00
5.09*
5.77*
–
4.87–5.33
5.51–6.04
–
<.0001
<.0001
–
0.79–0.94
0.95–1.16
0.95–1.14
–
.0011
.3127
.4389
1.00
0.90*
0.86*
0.78*
–
0.86–0.94
0.82–0.90
0.74–0.82
–
<.0001
<.0001
<.0001
1.00
1.13*
1.18*
1.32*
1.60*
–
1.01–1.26
1.05–1.32
1.18–1.48
1.43–1.79
–
.0375
.0040
<.0001
<.0001
1.00
1.05
1.06*
1.06*
1.07*
–
0.99–1.11
1.00–1.12
1.01–1.13
1.01–1.14
–
.0712
.0364
.0292
.0153
–
.2367
.0589
.0012
<.0001
1.00
1.01
0.99
0.95
1.04
–
0.90–1.12
0.89–1.10
0.85–1.06
0.93–1.16
–
.9182
.8381
.3653
.4553
1.00
0.97
0.95
0.92*
0.80*
–
0.91–1.02
0.90–1.00
0.87–0.97
0.76–0.85
–
.2152
.0671
.0023
<.0001
–
4.62–4.96
6.57–7.08
–
<.0001
<.0001
1.00
10.29*
28.71*
–
9.39–11.28
26.24–31.45
–
<.0001
<.0001
1.00
4.27*
4.77*
–
4.12–4.43
4.59–4.96
–
<.0001
<.0001
1.00
0.90*
0.89*
0.87*
–
0.87–0.93
0.86–0.93
0.84–0.90
–
<.0001
<.0001
<.0001
1.00
0.91*
1.05
1.06
–
0.85–0.98
0.98–1.13
0.99–1.14
–
.0089
.1859
.0737
1.00
0.90*
0.84*
0.81*
–
0.86–0.93
0.81–0.88
0.78–0.85
–
<.0001
<.0001
<.0001
1.00
1.01
1.01
1.00
1.00
–
0.96–1.05
0.96–1.06
0.96–1.05
0.96–1.05
–
.8265
.6954
.8563
.8354
1.00
1.08
1.15*
1.18*
1.29*
–
1.00–1.18
1.06–1.25
1.09–1.29
1.18–1.40
–
.0579
.0010
<.0001
<.0001
1.00
0.99
0.99
0.97
0.94*
–
0.95–1.04
0.94–1.03
0.93–1.02
0.90–0.99
–
.8244
.5721
.2441
.0213
1.00
0.98
0.97
0.93*
0.87*
–
0.94–1.02
0.93–1.01
0.89–0.97
0.83–0.91
–
.2931
.1351
.0011
<.0001
1.00
1.02
1.05
1.05
1.14*
–
0.94–1.10
0.97–1.14
0.97–1.13
1.05–1.24
–
.6976
.2184
.2579
.0015
1.00
0.97
0.95*
0.91*
0.81*
–
0.93–1.01
0.91–1.00
0.86–0.95
0.77–0.85
–
.1850
.0322
<.0001
<.0001
Abbreviations: CI, confidence interval; ref, reference; RR, relative risk; Q, quintile.
Note: Q1 = most advantaged; Q5 = most disadvantaged.
The study population consists of adults aged ≥ 20 years and newly identified as hypertensive.
a
Other census metropolitan areas, populations > 100 000 inhabitants (Québec, Sherbrooke, Trois-Rivières, Saguenay and Gatineau).
b
Mid-size cities, population 10 000–100 000 inhabitants.
c
Small towns and rural settings, populations < 10 000.
* Statistically significant results, p ≤ .05.
125
Vol 32, No 3, June 2012 – Chronic Diseases and Injuries in Canada
Figure 2
Adjusted relative risk of men and women by the standard definition
of hypertension and material and social deprivation, 2006/2007, Quebec, Canada
*
1.20
*
*
1.10
Relative Risk
*
*
*
1.00
*
0.90
*
0.80
2
3
4
5
2
Material deprivation
Women
Men
1.06
1.01
1.07
1.01
1.10
1.00
3
4
5
Social deprivation
1.15
1.00
0.97
0.98
0.95
0.97
0.92
0.93
0.83
0.87
Deprivation Quintile
Notes: The relative risks for the first quintile (Q1) of material and social deprivation (the most advantaged) were chosen as the reference and are not shown in this graph. These relative risks were
also adjusted for age and the geographical area of residence.
The study population consists of adults aged ≥ 20 years and newly identified as hypertensive.
* Statistically significant results, p ≤ .05.
the fiscal year 2006/2007. These associations
vary based on the source of case identi­
fication, the type of deprivation, and
sex. Associations between the incidence of
hypertension and deprivation are generally
positive when individuals were identified
with the hospitalization database as opposed
to the physician billing database or the
standard definition. Associations made with
the hospitalization database are also more
pronounced and more constant than those
made with the physician billing database.
Several of the associations observed in
our study differ from those found in the
literature.10,11,16,17 To explain the unexpected
results for cases identified with the physician
billing database or with the standard
definition, it is important to emphasize
that the definition of hyper­tension we
chose involves medical consultations,
whereas most other studies reviewed
relied mainly on surveys. Our results
suggest that the most advantaged people
visit a doctor in a medical practice more
frequently, increasing the likelihood of
identifying hypertension, which results in
a consultation bias with more frequent
identification of hypertension. However,
the research varies on this issue.20,24 Our
results show that material deprivation is
associated with a decrease in the incidence
of hypertension in men identified with the
physician billing database. Pineault et al.
found that individuals identified with
cardiovascular risk factors, including
hypertension, were more likely to be
older, male and less educated.24 However,
even if the risk factor group had difficulty
accessing primary care services, access
was not statistically different compared
to other users.24
On the other hand, some studies showed
that individuals with a lower SES
use ambulatory medical services more
frequently.25,26 However, these ambulatory
visits reflect both emergency room and
Vol 32, No 3, June 2012 – Chronic Diseases and Injuries in Canada
126
medical office visits, two very different
types of physician consultations. Although
both are included in the physician billing
database, the people who rely on the
emergency room visits are probably less
likely to benefit from the long-term care
required for certain medical conditions
including hypertension and thus more
likely to experience subsequent hospita­l­
izations due to the deterioration of the
medical condition; follow-up medical visits
are indeed known to reduce hospita­l­
ization.27 Moreover, an asymptomatic
health condition such as hypertension is
less likely to be identified as a diagnosis in
the physician billing database by emergency
doctors compared to family physicians
who see a patient as part of a medical
follow-up. It is also possible, especially
in the emergency room, that the diagnosis
of more urgent medical conditions
supersedes the hypertension diagnoses for
more deprived people who often present
with several conditions,28 which would lead
to the frequency of hypertension being
underestimated in this group. Interestingly,
some studies have suggested that the
most socioeconomically deprived individuals
are more likely to seek medical care in an
emergency context,29,30 and some authors
have shown that these ambulatory consultations were less likely to prevent
hospitalization in the most deprived people
of the society.31 Two Canadian studies
showed that lower income is positively
associated with emergency department
visits32 and inversely associated with
continuity of care,33 which is defined as a
“long-term relationship between a patient
and a physician or a patient and a physician
group, regardless of the presence of
any specific disease.”33 However, another
Canadian study demonstrated the opposite.34
In contrast, the association between
material deprivation and hypertension
in women shows the same tendency as
described in the literature, regardless of
the source of case identification. The data
suggests that the use of medical services
by women is less influenced by material
deprivation. In fact, Birch et al. found that
women were more likely to have consulted a
family physician in the previous year compared with men.35 Broyles et al. suggested
that this was a result of women, especially
those of childbearing age, being more heavily
involved in maternity and family planning.36
Medical consultations for cervical cancer
screening, renewal of oral contraceptives
and, at around age fifty years, breast cancer
screening could also be contributing to this
phenomenon. Several studies also showed
that women were more concerned about
and aware of hypertension than men.37-41
In addition, Birch et al. found a positive
association between the frequency of contacts
with friends or relatives and the number
of visits to a doctor.35 Thus, compared to the
most socially deprived, the most socially
advantaged would be more likely to be
diagnosed with a condition such as
hypertension. This goes towards explaining
the reverse association between social
deprivation and hypertension identified
with both the physician billing database
and the standard definition for both sexes.
According to Billings et al., compared to
those living in more advantaged areas,
people living in deprived areas tend to
delay consulting a physician for the
treatment of manageable conditions, which
leads to more frequent avoidable hospitali­
zation.42 This delay may be associated with
decreased access to health care services
for disadvantaged people, even in a country
like Canada with a public health care
system. Other studies showed that the
most deprived individuals use hospital
services more often.43-45 Since hypertension
is a frequent asymptomatic comorbidity,1,15
it is likely to be omitted from the list of
secondary diagnoses collected in the
hospital record of patients with several
comorbidities. Thus, since the most
materially deprived people have more
comorbidities,46
our
results
may
Figure 3
Adjusted relative risk of men and women as identified by the hospitalization database,
by material and social deprivation, 2006/2007, Quebec, Canada
1.80
*
1.60
Relative Risk
*
1.40
*
*
1.20
1.00
*
*
*
*
.80
2
3
4
5
2
Material deprivation
Women
Men
1.13
1.08
1.18
1.15
1.32
1.18
3
4
5
Social deprivation
1.60
1.29
1.01
1.02
0.99
1.05
0.95
1.05
1.04
1.14
Deprivation Quintile
Notes: The relative risks for the first quintile (Q1) of material and social deprivation (the most advantaged) were chosen as the reference and are not shown in this graph. These relative risks were
also adjusted for the geographical area of residence and age.
The study population consists of adults aged ≥ 20 years and newly identified as hypertensive.
* Statistically significant results, p ≤ .05.
127
Vol 32, No 3, June 2012 – Chronic Diseases and Injuries in Canada
Figure 4
Adjusted relative risk of men and women as identified by the physician billing database,
by material and social deprivation, 2006/2007, Quebec, Canada
1.20
*
*
*
1.10
*
*
Relative Risk
1.00
*
*
*
0.90
*
0.80
0.70
0.60
2
3
4
5
2
Material deprivation
Women
Men
1.05
0.99
1.06
0.99
1.06
0.97
3
4
5
Social deprivation
1.07
0.94
0.97
0.97
0.95
0.95
0.92
0.91
0.80
0.81
Deprivation Quintile
Notes: The relative risks for the first quintile (Q1) of material and social deprivation (the most advantaged) were chosen as the reference and are not shown in this graph. These relative risks were
also adjusted for the geographical area of residence and age.
The study population consists of adults aged ≥ 20 years and newly identified as hypertensive.
* Statistically significant results, p ≤ .05.
under­estimate the positive association found
between deprivation and hypertension
identified with the hospitalization database.
Limitations
Some limitations are associated with the use
of administrative databases, not least that
these exclude people with hypertension
who have not consulted any health care
professionals. The asymptomatic presentation of hypertension probably increases
the risk of such a bias, with the detection
of hypertension probably varying with SES.
Moreover, in their validation study, Tu et al.
concluded that the standard definition
fails to identify up to 28% of hypertensive
patients compared to the consultation of
primary care physician charts.21 However,
there is no reason to believe that individuals
identified as hypertensive with the primary
care physician charts alone are different from
those identified with our case definition.
The physician billing administrative database
is used primarily to compile acts rather than
diagnosis, and may therefore miss certain
diagnoses such as hypertension; this may
partly explain this proportion of unidentified
hypertensive patients. However, in our study
population, these omissions represent less
than 10% of the physician billing acts. It
is also important to underline that the
deprivation index is not an individual
measure of socio-economic conditions, but
rather a measure of the conditions at the
neighbourhood level. Finally, our data
sources relied on two different editions of
ICD codes. However, since there was no
new ICD code for hypertension between
the ninth and the tenth revisions, this
difference is not likely to affect our results.
Conclusion
Acknowledgements
This study reaffirms the importance of
considering social and material health
inequalities when planning interventions
targeted at preventing hypertension. It
suggests different health service utilisation
based on SES, and thus inequalities in
Vol 32, No 3, June 2012 – Chronic Diseases and Injuries in Canada
medical detection, treatment and control
of hypertension at the expense of the most
deprived. In the light of our results, it would
be interesting to refine our understanding
of primary health care access based on
deprivation, to better understand how it
varies in different health care settings such
as family physicians’ practices, walk-in
clinics, and emergency care, of which the
first is in a much better position to follow
up on chronic health conditions. It would
also be of value to policy makers to improve
our understanding of the potential barriers
to health care services and the strategies
that can be used to address these, given that
universal health care has been in operation
in Canada for decades.
128
The authors gratefully acknowledge
the following from the Institut national
de santé publique du Québec: Denis
Hamel for the study design, Robert
Pampalon for interpreting the results,
Najwa Ouhoummane for suggesting new
analyses and interpreting the results,
Philippe Gamache for his statistical
contributions, Jean-Frédéric Lévesque for
the transmission of new results and
Danielle Saint-Laurent for her advice. We
also thank the Public Health Agency of
Canada for their help in funding this
project and Chris Waters from the Public
Health Agency of Canada for the SAS code.
References
1. Blais C, Rochette L. Surveillance de
l’hypertension au Québec: incidence,
prévalence et mortalité. Québec (QC):
Institut national de santé publique du
Québec; 2011. Available at: http://
w w w. i n s p q . q c. c a / p d f / p u b l i c a t i o n s
/1059_HypertensionArterielle.pdf
2. Robitaille C, Dai S, Waters C, Loukine L,
Bancej C, Quach S, et al. Diagnosed
hypertension in Canada: incidence,
prevalence and associated mortality.
CMAJ. 2012;184(1):E49-56 [online version
consulted 2011 Nov 21].
3. Tu K, Chen Z, Lipscombe LL; Canadian
Hypertension Education Program Outcomes
Research Taskforce. Mortality among
patients with hypertension from 1995 to
2005: a population-based study. CMAJ.
2008;178(11):1436-40.
4. Ezzati M, Lopez AD, Rodgers A,
Vander Hoorn S, Murray CJ. Comparative
Risk Assessment Collaborating Group.
Selected major risk factors and global
and regional burden of disease. Lancet.
2002;360(9343):1347-60.
5. Organisation mondiale de la santé. Rapport
sur la santé dans le monde 2002: Réduire
les risques et promouvoir une vie saine.
Geneva (CH): WHO; 2002.
6. Goldstein LB, Adams R, Alberts MJ,
Appel LJ, Brass LM, Bushnell CD, et al.
Primary prevention of ischemic stroke:
a guideline from the American Heart
Association/American Stroke Association
Stroke Council: cosponsored by the
Atherosclerotic
Peripheral
Vascular
Disease Interdisciplinary Working Group;
Cardiovascular Nursing Council; Clinical
Cardiology Council; Nutrition, Physical
Activity, and Metabolism Council; and the
Quality of Care and Outcomes Research
Interdisciplinary Working Group: the
American Academy of Neurology affirms
the value of this guideline. Stroke.
2006;37(6):1583-633.
7. Lee DE, Cooper RS. Recommendations
for
global
hypertension
monitoring
and prevention. Curr Hypertens Rep.
2009;11(6):444-9.
8. Santé Canada, Coalition canadienne
pour la prévention et le traitement
de l’hypertension. Stratégie nationale
de prévention et de traitement de
l’hypertension: rapport sommaire du
Groupe d’experts. Ottawa (ON): Health
Canada; 2000. p. 1-27.
9. Bell AC, Adair LS, Popkin BM.
Understanding the role of mediating risk
factors and proxy effects in the association
between socio-economic status and
untreated hypertension. Soc Sci Med.
2004;59(2):275-83.
10. Colhoun HM, Hemingway H, Poulter NR.
Socio-economic status and blood pressure:
an overview analysis. J Hum Hypertens.
1998;12(2):91-110.
11. Levenstein S, Smith MW, Kaplan GA.
Psychosocial predictors of hypertension
in men and women. Arch Intern Med.
2001;161(10):1341-6.
12. Public Health Agency of Canada, Canadian
Institute for Health Information, Canadian
Stroke Network, Heart and Stroke
Foundation of Canada, Statistics Canada,
editors. Suivi des maladies du cœur et des
accidents vasculaires cérébraux au Canada.
Ottawa (ON): Public Health Agency of
Canada; 2009. p. 1-118. [Catalogue No.:
HP32-3/2009F].
13. Pampalon R, Raymond G. A deprivation
index for health and welfare planning
in
Quebec.
Chronic
Dis
Can.
2000;21(3):104-13.
14. Matheson FI, White HL, Moineddin R,
Dunn JR, Glazier RH. Neighbourhood
chronic stress and gender inequalities
in hypertension among Canadian adults:
a multilevel analysis. J Epidemiol
Community Health. 2010;64(8):705-13.
129
15. Tu K, Chen Z, Lipscombe LL. Canadian
Hypertension Education Program Outcomes
Research Taskforce. Prevalence and
incidence of hypertension from 1995
to 2005: a population-based study. CMAJ.
2008;178(11):1429-35.
16. Uchino BN, Cacioppo JT, Kiecolt-Glaser JK.
The relationship between social support
and physiological processes: a review with
emphasis on underlying mechanisms and
implications for health. Psychol Bull.
1996;119(3):488-531.
17. Tomaka J, Thompson S, Palacios R. The
relation of social isolation, loneliness,
and social support to disease outcomes
among the elderly. J Aging Health.
2006;18(3):359-84.
18. Hawkley LC, Masi CM, Berry JD, Cacioppo JT.
Loneliness is a unique predictor of
age-related differences in systolic blood
pressure. Psychol Aging. 2006;21(1):152-64.
19. Thorpe RJ Jr, Brandon DT, LaVeist TA.
Social context as an explanation for
race disparities in hypertension: findings
from the Exploring Health Disparities in
Integrated Communities (EHDIC) Study.
Soc Sci Med. 2008;67(10):1604-11.
20. Daveluy C, Pica L, Audet N, Courtemanche R,
Lapointe F. Enquête sociale et de santé
1998, 2nd ed. Montreal (QC): Institut de la
statistique du Québec: 2000.
21. Tu K, Campbell NRC, Chen ZL,
Cauch-Dudek KJ, McAlister FA. Accuracy
of administrative databases in identifying
patients with hypertension. Open Medicine.
2007;1(1):E18-E26.
22. Rapport
du
Système
national
de
surveillance des maladies chroniques:
L’hypertension au Canada. Ottawa (ON):
Public Health Agency of Canada; 2010.
1-28. [Cat.: HP32-4/2010].
23. Pampalon R, Raymond G. Indice de
défavorisation matérielle et sociale: son
application au secteur de la santé et du
bien-être. Santé, société et solidarité.
2003;1:191-208.
24. Pineault R, Provost S, Hamel M, Couture A,
Levesque JF. The influence of primary
health care organizational models on
patients’ experience of care in different
chronic disease situations. Chronic Dis Inj
Can. 2011;31(3):109-20.
Vol 32, No 3, June 2012 – Chronic Diseases and Injuries in Canada
25. Carr-Hill RA, Rice N, Roland M.
Socioeconomic determinants of rates of
consultation in general practice based on
fourth national morbidity survey of general
practices. BMJ. 1996; 312(7037):1008-12.
35. Birch S, Eyles J, Newbold KB. Equitable
access to health care: methodological
extensions to the analysis of physician
utilization in Canada. Health Econ.
1993;2(2):87-101.
26. Evans RG, Barer ML, Marmor TR, editors.
Être ou ne pas être en bonne santé:
biologie et déterminants sociaux de la
maladie. Montreal (QC): Les presses de
l’Université de Montréal; 1996.
36. Broyles RW, Manga P, Binder DA, Angus DE,
Charette A. The use of physician services
under a national health insurance scheme.
An examination of the Canada Health
Survey. Med Care. 1983;21(11):1037-54.
27. Mainous AG 3rd, Gill JM. The importance
of continuity of care in the likelihood of
future hospitalization: is site of care
equivalent to a primary clinician?
Am J Public Health. 1998;88(10):1539-41.
37. Falaschetti E, Chaudhury M, Mindell J,
Poulter N. Continued improvement in
hypertension management in England:
results from the Health Survey for England
2006. Hypertension. 2009;53(3):480-6.
28. Mercer SW, Watt GC. The inverse care
law: clinical primary care encounters in
deprived and affluent areas of Scotland.
Ann Fam Med. 2007;5(6):503-10.
38. Danon-Hersch N, Marques-Vidal P, Bovet P,
Chiolero A, Paccaud F, Pécoud A, et al.
Prevalence, awareness, treatment and
control of high blood pressure in a
Swiss city general population: the CoLaus
study. Eur J Cardiovasc Prev Rehabil.
2009;16(1):66-72.
29. Béland F, Philibert L, Thouez JP, Maheux B.
Socio-spatial perspectives on the utilization
of emergency hospital services in two
urban territories in Quebec. Soc Sci Med.
1990;30(1):53-66.
30. Lemoine O, Simard B, Juneau O, Provost S,
Roy Y, Tousignant P. L’utilisation des
services de santé par les Montréalais
souffrant d’hypertension artérielle, Années
2000-2001 à 2005-2006. Québec (QC):
Direction de santé publique de l’Agence de
la santé et des services sociaux de Montréal
et Institut national de santé publique du
Québec; 2010.
31. Roos LL, Walld R, Uhanova J, Bond R.
Physician visits, hospitalizations, and
socioeconomic status: ambulatory care
sensitive conditions in a Canadian setting.
Health Serv Res. 2005;40(4):1167-85.
32. Menec VH, Sirski M, Attawar D. Does
continuity of care matter in a universally
insured population? Health Serv Res.
2005;40(2):389-400.
33. Menec VH, Roos NP, Black C, Bogdanovic B.
Characteristics of patients with a regular
source of care. Can J Public Health.
2001;92(4):299-303.
34. McCusker J, Roberge D, Lévesque JF,
Ciampi A, Vadeboncoeur A, Larouche D.
Emergency department visits and primary
care among adults with chronic conditions.
Med Care. 2010; 48(11):972-80.
39. Kastarinen M, Antikainen R, Peltonen M,
Laatikainen T, Barengo NC, Jula A, et al.
Prevalence, awareness and treatment of
hypertension in Finland during 1982-2007.
J Hypertens. 2009;27(8):1552-9.
40. Marques-Vidal P, Arveiler D, Amouyel P,
Bingham A, Ferrieres J. Sex differences in
awareness and control of hypertension in
France. J Hypertens. 1997;15(11):1205-10.
41. Brindel P, Hanon O, Dartigues JF, Ritchie K,
Lacombe JM, Ducimetière P, et al.
3C Study Investigators. Prevalence,
awareness, treatment, and control of
hypertension in the elderly: the Three
City study. J Hypertens. 2006;24(1):51-58.
42. Billings J, Anderson GM, Newman LS.
Recent
findings
on
preventable
hospitalizations. Health Aff (Millwood).
1996;15(3):239-49.
43. Manga P, Broyles RW, Angus DE. The
determinants of hospital utilization under
a universal public insurance program in
Canada. Med Care. 1987;25(7):658-70.
44. Trahan L, Bégin P, Piché J. Recours à
l’hospitalisation, à la chirurgie d’un jour et
aux services posthospitaliers. In: Enquête
sociale et de santé 1988, 2nd ed.
Québec (QC): Institut de la statistique du
Québec; 2000.
Vol 32, No 3, June 2012 – Chronic Diseases and Injuries in Canada
130
45. Roos N, Burchill C, Carriere K. Who are the
high hospital users? A Canadian case study.
J Health Serv Res Policy. 2003;8(1):5-10.
46. Levasseur M, Goulet L. Problèmes de
santé. In: Enquête sociale et de santé 1988,
2nd ed. Québec (QC): Institut de la statistique du Québec; 2000.
Trends in incidence of childhood cancer in Canada, 1992–2006
D. Mitra, MSc; A. K. Shaw, MSc; K. Hutchings, MSc
This article has been peer reviewed.
Abstract
Introduction: Cancer is the leading cause of disease-related death in children aged 1 to
14 years in Canada. Despite the importance to public health of childhood cancer, there
have been few reports on Canadian trends published in the peer-reviewed literature.
This study examines childhood cancer trends by age, sex, and province of residence using
the most current cancer registration data.
Methods: Data from the population-based Canadian Cancer Registry were used to
compute incidence trends in primary cancers diagnosed between 1992 and 2006 in
children (0-14 years) for the 12 major diagnostic groups of the International Classification
of Childhood Cancer, 3rd Edition.
Results: Between 1992 and 2006, incidence rates for all cancers remained stable, although
trends varied by cancer type. We observed a significant decrease in retinoblastoma in boys
for the entire period (−6.5% per year) and an increase in leukemia from 1992 to 1999
(+3.5% per year). In girls, there was a significant decrease in renal tumours from 1998 to
2006 (−5.7% per year) and an increase in hepatic tumours from 1997 to 2006 (+8.1%
per year). Differences by age and province were also apparent. Some caution should be
exercised when interpreting trends involving a small number of cases per year and those
with wide 95% confidence intervals.
Conclusions: Our findings suggest an ongoing need for population-based surveillance
and etiologic research.
Keywords: cancer incidence, pediatric, childhood, trends, Canadian Cancer Registry
Introduction
Several large scale epidemiological
studies have reported an increase in the
incidence of childhood cancers, parti­
cularly leukemia and brain tumours.1-6
An increase in the incidence of all
childhood cancers combined has also
been observed in Europe and the United
States, although recent evidence suggests
a plateau in rates.7,8 It is not clear
whether these trends are a real phenomenon or an artefact reflecting changes
in diagnostics, case ascertainment,
registration practices or differential
access to health care.
Although accounting for less than 1% of
all cancers diagnosed in Canada, childhood
cancers nevertheless pose a significant
burden on child health.9 On average,
850 children aged under 15 years are
diagnosed with cancer each year in Canada
and 135 die of the disease.9 Cancer remains
the leading cause of disease-related deaths
in children aged 1 to 14 years, corresponding
to 19% of deaths between 1992 and 2005.9
The Canadian Late Effects Study shows
that in addition to personal loss, childhood
cancer can negatively impact the finances
of affected families due to loss of income,
unpaid care-giving and out-of-pocket
expenses associated with treatment.10,11
Aside from one 1997 study of neuro­
blastoma, there have been no peerreviewed publications on national
childhood cancer incidence trends in
Canada.12 A complete picture of trends
in childhood cancer would allow for
monitoring change over time, estimating
burden and prompting etiological
research, which in turn would provide
information on health care needs. In this
report, we aim to provide a detailed
analysis of the trends in childhood
cancer incidence in Canada in relation
to sex, age, and regional differences.
Methods
We used data on cancer incidence from
the July 2009 version of the Canadian
Cancer Registry (CCR).13 This dynamic
registry contains information on cases
diagnosed from 1992 onward, compiled
from reports from all provincial and
territorial cancer registries in Canada.
The reporting of the CCR is assumed
to be complete since each Canadian
province and territory has a legislated
responsibility to collect and control
cancer data. Information is available at
the patient level and includes date of
birth, sex, province and postal code
of residence at diagnosis, date and
cause of death as well as cancer
characteristics such as date of diagnosis,
histology (morphology), site of origin
(topography) and behaviour classifi­
cation.13 Our analysis includes CCR
data on all malignant tumours diagnosed
in children aged less than 15 years
between 1992 and 2006.14 We based
population estimates on quinquennial
national censuses conducted from 1986
through 2006; intercensal estimates
provided by Statistics Canada were
Author references:
Centre for Chronic Disease Prevention and Control, Public Health Agency of Canada, Ottawa, Ontario, Canada
Correspondence: Debjani Mitra, Centre for Chronic Disease Prevention and Control, Public Health Agency of Canada, Room 726A4, 785 Carling Avenue, Ottawa, ON K1A 0K9;
Tel.: (613) 948-7506; Fax: (613) 960-0944; Email: [email protected]
131
Vol 32, No 3, June 2012 – Chronic Diseases and Injuries in Canada
used for non-census years. All population
estimates have been corrected for
census net undercoverage and components of international and interprovincial
migration.15 All rates were age-standardized
using the direct method to the 1991
Canadian population.
We classified childhood cancers according
to diagnostic categories of the International
Classification of Childhood Cancer,
3rd Edition (ICCC-3), a classification
system based on the morphology and
topography codes used in International
Classification of Diseases for Oncology,
3rd edition (ICD-O-3),16,17 and used the
same ICCC-3 abbreviated names for
cancer categories. The analysis included
all cancers in the ICCC-3 classification
system except non-malignant intracranial
and intraspinal neoplasms, which are not
captured by the Canadian Cancer Registry.
All age-standardized incidence rates (ASIRs)
were extracted and computed using the
statistical package SAS EG version 9.1 (SAS
Institute Inc.); trends were characterized
by calculating annual percent change (APC)
and 95% confidence intervals (CI) using
Joinpoint Regression Program, developed
by the Surveillance, Epidemiology, and End
Results (SEER) Program.18 Standard linear
regression assumptions used the logarithm
for the rate assigned as the dependant
variable and the midpoint of the calendar
year as the independent variable.
Permutation-based joinpoint models were
used to assess the magnitude and direction
of trends, and a maximum of two joinpoints
(allowing a minimum of 5 years between
joinpoints) was allowed. Significance was
determined by calculating two-sided
p-values to test the slope of the trend
line, using α = 0.05 as the cut-off for
significance.19 Age-standardized rates and
trends were calculated by diagnosis, sex,
age group (< 1 year, 1–4 years, 5–9 years,
10–14 years) and province/territory of
residence. Neither rates involving fewer
than six cases nor trends for cancers with
annual rates equal to zero are presented.
Results
Between 1992 and 2006, 13 211 children
aged less than 15 years were diagnosed
with cancer in Canada, equivalent to an
ASIR of 152 cases per million children per
year. The most common diagnoses during
the 15-year study period were leukemias
(32.5% of all cancers diagnosed in children),
central nervous system (CNS) tumours
(19.9%), lymphomas (11.2%), neuroblastomas (7.3%), soft tissue sarcomas (6.2%),
renal tumours (5.7%), and malignant bone
tumours (4.5%) (Table 1). The remaining
histological categories represented approxi­
mately 13% of the total cancer burden
in children. The male to female ratio for
overall childhood cancer incidence was 1.12
to 1, and there were marked differences in
incidence between age groups. The incidence
rate was highest in infants (245 cases per
million per year), followed by children
between the ages of 1 and 4 (213 cases per
million per year), 10 and 14 (120 cases
per million per year), and 5 and 9
(116 cases per million per year) (Table 1).
The incidence for all childhood cancers
combined remained relatively stable for the
duration of the study period (see Table 2);
however, trends varied by diagnostic category and sex. Incidence of retinoblastoma
decreased significantly for the entire period
(APC = −2.6% per year, 95% CI = −4.7
to −0.4) and of leukemia increased
significantly from 1992 to 1999 (APC =
2.4% per year, 95% CI = 0.0 to 4.9).
Incidence of retinoblastoma in boys
decreased significantly for the entire period
(APC = −6.5% per year, 95% CI =
−10.4 to −2.6) and of leukemia increased
significantly (APC = 3.5% per year, 95%
CI = 1.3 to 5.8). Corresponding trends
were not evident in girls; trends for
retinoblastoma showed a modest but nonsignificant decrease and were stable for
leukemia. However, incidence of renal
tumours in girls decreased significantly
between 1998 and 2006 (APC = −5.7% per
year, 95% CI = −10.7 to −0.5) while that
of hepatic tumours increased significantly
between 1997 and 2006 (APC = 8.1% per
year, 95% CI = 1.8 to 14.7).
Incidence trends by age (Table 3) revealed
a significant increase in renal tumours in
children aged less that 1 year between 1992
and 1998 (APC = 18.2% per year, 95%
CI = 5.3 to 32.7), followed by a period of
non-significant trends. Leukemia rates in
children aged 1 to 4 years rose modestly
but significantly between 1992 and 1999
(APC = 3.2% per year, 95% CI = 0.3
Vol 32, No 3, June 2012 – Chronic Diseases and Injuries in Canada
132
to 6.1), decreased (albeit insignificantly)
between 1999 and 2002, and then increased
significantly again between 2002 and 2006
(APC = 4.0% per year, 95% CI = 2.7
to 11.1). In children aged 5 to 9 years,
there was a rapid increase in carcinomas
(APC = 8.9% per year, 95% CI = 2.2
to 16.1) and germ cell tumours (APC =
10.9% per year, 95% CI = 2.2 to 20.3). In
those aged 10 to 14 years, CNS cancers
decreased significantly between 1994 and
2004 (APC = −2.3% per year, 95%
CI = −4.4 to −0.2). This trend was driven
primarily by the decreasing incidence
in astrocytomas, which account for
over half of the brain tumours in this
age group.
We calculated trends for every Canadian
province, but not for the sparsely populated
territories of Yukon, Northwest Territories
and Nunavut. The only province with a
significant trend for all cancers combined
for the total study period was Alberta
(APC =1.3% per year, 95% CI = 0.2 to
2.4), primarily due to increased incidence
of leukemia (APC = 3.1% per year, 95%
CI = 0.2 to 6.1) and lymphoma (APC =
6.5% per year, 95% CI = 1.4 to 12.0).
Rates for neuroblastoma also increased
but not significantly. Leukemia incidence
trends increased significantly in Quebec
(APC = 1.6% per year, 95% CI = 0.1
to 3.1), while carcinomas, including
unspecified malignant epithelial tumours,
increased significantly in Ontario (APC =
4.0% per year, 95% CI = 0.0 to 8.2).
Intermediate study period analyses found
increases in incidence of leukemia in
Manitoba between 1996 and 2006 (APC =
3.6% per year, 95% CI = 0.1 to 7.3) and
of hepatic tumours in British Columbia
between 1992 and 1998 (APC = 12.4%
per year, 95% CI = 0.2 to 25.9). Incidence
of brain tumours increased in New
Brunswick from 1992 to 1998 (APC =
11.9% per year, 95% CI = 3.3 to 21.1) but
decreased in Ontario between 1992 and
2004 (APC = −1.5% per year, 95% CI =
−2.8 to −0.1). (Additional data available
upon request.)
Discussion
While publications reporting trend data from
the mid- to late-1970s found that childhood
cancer rates have been increasing at a rate
Table 1
Number of childhood cancer cases (0–14 years) and average age-standardized
incidence rate per million by sex and age group, Canada, 1992–2006
Diagnostic group
Sex
Age group, years
Boys
Girls
<1
1–4
5–9
10–14
All children
Total number of cases, n
7131
6070
1308
4768
3441
3694
13211
ASIR, per million
160.7
143.4
245.1
213.1
116.2
120.3
152.3
Total number of cases, n
2345
1940
264
2060
1175
788
4287
ASIR, per million
53.1
46.1
49.5
92.1
39.7
25.7
49.7
Total number of cases, n
981
499
46
222
426
786
1480
ASIR, per million
21.4
11.4
8.6
9.9
14.4
25.6
16.5
Total number of cases, n
1408
1217
142
820
915
754
2631
ASIR, per million
31.5
28.5
26.6
36.6
30.9
24.6
30.0
All cancers combined
I
II
III
IV
V
VI
VII
VIII
IX
X
XI
XII
Leukemias
Lymphomas
CNS
Neuroblastomas
Total number of cases, n
498
463
334
475
119
32
960
ASIR, per million
11.8
11.5
62.6
21.2
4.0
1.0
11.7
Total number of cases, n
167
156
108
200
11
3
322
ASIR, per million
4.0
3.9
20.2
8.9
0.3
< 0.1
3.9
Total number of cases, n
343
414
99
436
178
44
757
ASIR, per million
7.9
10.0
18.6
19.5
6.0
1.4
9.0
Total number of cases, n
120
79
49
109
20
22
200
ASIR, per million
2.8
2.0
9.2
4.9
0.7
0.7
2.4
Total number of cases, n
304
294
5
50
175
368
598
ASIR, per million
6.5
6.6
0.9
2.2
5.9
12.0
6.6
Total number of cases, n
451
366
84
210
230
292
816
ASIR, per million
10.0
8.6
15.7
9.4
7.8
9.5
9.3
Total number of cases, n
201
237
75
91
57
216
439
ASIR, per million
4.6
5.5
14.1
4.1
1.9
7.0
5.0
Total number of cases, n
213
295
40
34
96
338
508
ASIR, per million
4.6
6.7
7.5
1.5
3.2
11.0
5.6
Total number of cases, n
100
110
62
61
39
50
212
ASIR, per million
2.4
2.7
11.6
2.7
1.3
1.6
2.5
Retinoblastomas
Renal tumours
Hepatic tumours
Malignant bone tumours
Soft tissue sarcomas
Germ cell tumours
Carcinomas and malignant epithelial neoplasms
Other/unspecified malignant neoplasms
Abbreviations: ASIR, age-standardized incidence rate; CNS, central nervous system.
Note: Diagnostic groups were classified according to the International Classification of Childhood Cancer, 3rd edition (ICCC-3). Rates were directly standardized to the Canadian 1991 population.
133
Vol 32, No 3, June 2012 – Chronic Diseases and Injuries in Canada
Table 2
Trends in childhood cancer (0–14 years) by sex, Canada, 1992–2006
Diagnostic group
Trend 1
Trend 2
Years
APC (95% CI)
All cancers combined
1992–2006
0.0 (−0.5 to 0.4)
Leukemias
1992–1999
2.4 (0.0 to 4.9)
Years
APC (95% CI)
Trend 3
Years
APC (95% CI)
All children
I
1999–2002 −4.4 (−20.1 to 14.2) 2002–2006
II
Lymphomas
1992–2006
0.0 (−1.4 to 1.4)
III
CNS
1992–2006
−0.4 (−1.3 to 0.5)
IV
Neuroblastomas
1992–2006
−0.2 (−1.8 to 1.5)
V
Retinoblastomas
1992–2006 −2.6 (−4.7 to −0.4)
VI
Renal tumours
1992–2006
−1.3 (−3.2 to 0.7)
VII
Hepatic tumours
1992–2006
1.6 (−0.8 to 4.0)a
VIII Malignant bone tumours
1992–2006
−1.2 (−2.8 to 0.5)
IX
Soft tissue sarcomas
1992–2006
−1.4 (−3.6 to 0.8)
1992–2006
−0.4 (−2.2 to 1.4)
X
Germ cell tumours
XI
Carcinomas and malignant epithelial neoplasms 1992–2006
XII
Other/unspecified malignant neoplasms
1992–2006
4.6 (0.1 to 9.4)a
All cancers combined
1992–1999
1.1 (−0.2 to 2.3)
1999–2006 −1.5 (−2.7 to −0.3)
1999–2002 −6.7 (−20.6 to 9.7) 2002–2006
3.0 (−2.6 to 9.0)
2.5 (−0.5 to 5.6)
Boys
I
Leukemias
1992–1999
3.5 (1.3 to 5.8)
II
Lymphomas
1992–2006
0.2 (−1.6 to 2.0)
III
CNS
1992–2006
−0.6 (−2.3 to 1.1)
IV
Neuroblastomas
1992–2006
0.0 (−1.9 to 1.9)
V
Retinoblastomas
1992–2006 −6.5 (−10.4 to −2.6)a
VI
Renal tumours
1992–2006
VII
Hepatic tumours
1992–2006 −1.1 (−4.0 to 1.8)a
2.2 (−2.9 to 7.5)
−1.5 (−4.6 to 1.8)
VIII Malignant bone tumours
1992–2006
−0.3 (−2.9 to 2.4)
IX
Soft tissue sarcomas
1992–2006
−1.8 (−4.8 to 1.3)
X
Germ cell tumours
1992–2006
−1.1 (−3.8 to 1.6)
XI
Carcinomas and malignant epithelial neoplasms 1992–2006
3.4 (−1.2 to 8.2)a
XII
Other/unspecified malignant neoplasms
1992–2006
8.4 (−1.8 to 19.7)a
Girls
All cancers combined
1992–2006
−0.5 (−1.1 to 0.2)
I
Leukemias
1992–2006
0.0 (−1.0 to 1.0)
II
Lymphomas
1992–2006
−0.4 (−2.3 to 1.5)
III
CNS
1992–2006
−0.6 (−2.2 to 0.9)
IV
Neuroblastomas
1992–2006
−1.5 (−3.7 to 0.8)
V
Retinoblastomas
1992–2006
−0.6 (−4.0 to 2.9)
VI
Renal tumours
1992–1998
3.1 (−5.2 to 12.1)a
VII
Hepatic tumours
1992–1994 55.6 (−19.1 to 199.1) 1994–1997 −16.6 (−56.6 to 60.2)a 1997–2006
1998–2006 −5.7 (−10.7 to −0.5)a
a
VIII Malignant bone tumours
1992–2006
−1.7 (−4.5 to 1.2)
IX
Soft tissue sarcomas
1992–2006
−1.3 (−2.9 to 0.3)
X
Germ cell tumours
1992–2006
0.0 (−3.6 to 3.7)
XI
Carcinomas and malignant epithelial neoplasms 1992–2006
1.9 (−1.0 to 4.9)
XII
Other/unspecified malignant neoplasms
2.2 (−2.2 to 6.8)a
1992–2006
Abbreviations: APC, annual percent change; CI, confidence interval; CNS, central nervous system.
Note: Significant APC values are bolded. p < .05.
a
Trends involving fewer than 10 cases per year based on rates standardized to the 1991 Canadian population. These should be interpreted with caution.
Vol 32, No 3, June 2012 – Chronic Diseases and Injuries in Canada
134
8.1 (1.8 to 14.7)a
Table 3
Trends in childhood cancer (0–14 years) by age group, Canada, 1992–2006
Diagnostic group
Trend 1
Trend 2
Years
APC (95% CI)
Years
APC (95% CI)
Trend 3
Years
APC (95% CI)
< 1 year
All cancers combined
1992–2006
−0.9 (−2.4 to 0.5)
I
Leukemias
1992–2006
−0.2 (−2.6 to 2.3)
II
Lymphomas
1992–2006 −4.1 (−10.0 to 2.1)a
III
CNS
1992–2006
0.7 (−3.8 to 5.3)a
IV
Neuroblastomas
1992–2006
−1.5 (−4.6 to 1.7)
V
Retinoblastomas
1992–2006 −4.8 (−9.7 to 0.4)a
VI
Renal tumours
1992–1998
VII
Hepatic tumours
1992–2006 −0.7 (−8.6 to 7.9)
18.2 (5.3 to 32.7)a
VIII Malignant bone tumours
1992–2006
—
IX
Soft tissue sarcomas
1992–2006
0.5 (−5.6 to 7.0)a
X
Germ cell tumours
1992–2006
0.2 (−5.5 to 6.2)a
XI
Carcinomas and malignant epithelial neoplasms 1992–2006
—
XII
Other/unspecified malignant neoplasms
1992–2006
—
All cancers combined
1992–2006
0.4 (0.0 to 0.9)
1998–2001 −21.5 (−60.4 to 55.4)* 2001–2006
6.5 (−8.6 to 24.1)*
1999–2002 −5.2 (−23.2 to 6.9) 2002–2006
4.0 (2.7 to 11.1)
a
1–4 years
I
Leukemias
1992–1999
3.2 (0.3 to 6.1)
II
Lymphomas
1992–2006
0.6 (−1.7 to 3.0)a
III
CNS
1992–2006
1.2 (−1.1 to 3.6)
IV
Neuroblastomas
1992–2006
−1.5 (−4.7 to 1.8)
V
Retinoblastomas
1992–2006 −2.1 (−4.8 to 0.6)a
VI
Renal tumours
1992–2006
VII
Hepatic tumours
1992–2006 −2.2 (−5.3 to 0.9)a
3.4 (−0.9 to 7.8)
VIII Malignant bone tumours
1992–2006 −1.8 (−5.6 to 2.1)a
IX
Soft tissue sarcomas
1992–2006
2.1 (−6.1 to 10.9)
X
Germ cell tumours
1992–2006
0.7 (−2.5 to 4.1)a
XI
Carcinomas and malignant epithelial neoplasms 1992–2006
0.6 (−1.7 to 3.0)
XII
Other/unspecified malignant neoplasms
1992–2006
—
5–9 years
All cancers combined
1992–2006
0.1 (−0.5 to 0.7)
I
Leukemias
1992–2006
1.3 (−0.3 to 2.8)
II
Lymphomas
1992–2006
0 (−2.7 to 2.7)
III
CNS
1992–2006
−0.9 (−2.4 to 0.6)
IV
Neuroblastomas
1992–2006 −1.6 (−6.5 to 3.7)a
V
Retinoblastomas
1992–2006
VI
Renal tumours
1992–2006 −0.6 (−4.4 to 3.4)a
VII
Hepatic tumours
VIII Malignant bone tumours
1992–2006
—
—
1992–2006 −1.4 (−6.1 to 3.6)a
IX
Soft tissue sarcomas
1992–2006
−2.0 (−4.7 to 0.9)
X
Germ cell tumours
1994–2004
10.9 (2.2 to 20.3)a
XI
Carcinomas and malignant epithelial neoplasms 1992–2006
8.9 (2.2 to 16.1)a
XII
Other/unspecified malignant neoplasms
1992–2006
—
Continued on the following page
135
Vol 32, No 3, June 2012 – Chronic Diseases and Injuries in Canada
Table 3 (continued)
Trends in childhood cancer (0–14 years) by age group, Canada, 1992–2006
Diagnostic group
Trend 1
Years
Trend 2
APC (95% CI)
Years
APC (95% CI)
Trend 3
Years
APC (95% CI)
10–14 years
All cancers combined
1992–2006
0.5 (−1.5 to 0.4)
I
Leukemias
1992–2006
1.2 (−2.6 to 0.3)
II
Lymphomas
1992–2006
0 (−1.9 to −2.1)
III
CNS
1992–2004 −2.3 (−4.4 to −0.2)
IV
Neuroblastomas
1992–2006
—
V
Retinoblastomas
1992–2006
—
VI
Renal tumours
1992–2006 −0.5 (−6.9 to 8.5)a
VII
Hepatic tumours
1992–2006 −0.9 (−2.7 to 1.0)a
−1.2 (−5.3 to 3.0)
VIII Malignant bone tumours
1992-2006
IX
Soft tissue sarcomas
1992–2006 −0.9 (−5.7 to 4.1)a
X
Germ cell tumours
1992–2006
—
XI
Carcinomas and malignant epithelial neoplasms
1992–2006
1.9 (−2.2 to 6.3)
XII
Other/ unspecified malignant neoplasms
1992–2006
—
Abbreviations: APC, annual percent change; CI, confidence interval; CNS, central nervous system.
Note: Significant APC values are bolded. p < .05
a
Trends involving fewer than 10 cases per year based on rates standardized to the 1991 Canadian population. These should be interpreted with caution.
of 0.6% per year in the United States
(1975–2005)20 and 1.1% per year in
Europe (1978–1997),21 our findings are
consistent with those of reports analyzing
more recent data from the United States
(1992–2004)7 and Australia (1983–2007)8
showing that incidence rates have been
levelling off since the early 1990s.
Our analyses show two significant
full-period trends: a decrease in retinoblastoma in boys and an increase in
carcinomas in children aged 5 to 9 years.
Decreasing retinoblastoma trends in infants,
the group most affected by this genetically
predisposed cancer, were not significant.
In comparison, the most recent research
on childhood cancer trends in the United
States (1992–2004)7,22 and Europe (1998–
2007)22 shows modest but non-significant
increases in incidence of retinoblastoma.
The inconsistency with trends observed
elsewhere might be due to small numbers
of cases. For an extremely rare disease
such as retinoblastoma, where the average
ASIR over the 15-year study period is
4 cases per million children per year
(Table 1), the possibility that the trend
may be a chance occurrence due to random
fluctuations in annual rates should not be
dismissed.
Recent reports from Australia (1983–2006)8
and Europe (1978–1997)21 confirm our
findings of a rapid rise in carcinomas
in 5- to 9-year-olds. Improvement in
registration alone does not adequately
explain this phenomenon since this is
likely to yield consistent increases in
incidence across all diagnoses unless there
is reason to believe that registry-specific
practices would lead to under-reporting or
over-reporting of a particular diagnosis.
Change in tumour classification also does
not explain this trend since an exchange
in cases between diagnostic groups is not
apparent. Descriptive analysis of CCR data
shows that carcinoma incidence increases
with age and that carcinomas are very
rare in Canadian children aged less than
10 years.9 It is possible that improvement in
diagnostic technologies such as seroassays
of tumour markers is inflating the incidence
of tumours—previously undetected—in
children aged 5 to 9 years, a pattern evident
for some subtypes of CNS cancers.23,24 The
rise in pediatric germ cell cancer incidence
in 5- to 9-year-olds that we observed is
also supported by data from Australia and
Europe.8,21 This trend likely reflects a true
phenomenon since there have been no
changes to diagnostics, coding, registration
or screening practices corresponding to
Vol 32, No 3, June 2012 – Chronic Diseases and Injuries in Canada
136
the study period. To better understand the
factors that underlie this trend, research
should examine changes in underlying
risk factors associated with germ cell
tumours, such as exposure to exogenous
estrogen, prenatal exposure to x-rays and
parental exposure to chemicals, solvents,
or resins.25,26
Our results point to several interesting
sub-period trends. These include a signi­
ficant positive trend in leukemia for boys
(1992–1999: APC = 3.5%, 95% CI = 1.3
to 5.8) and an insignificant positive trend
in hepatic tumours for girls (1997–2006)
as well as an insignificant negative trend
in renal tumours for girls (1998–2006). A
significant decrease in CNS cancers was
also evident in older children aged 10 to
14 years (1994–2004: APC = −2.3%,
95% CI = −4.4 to −0.2). The modest
but significant increase in leukemia
between 1992 and 1999 (APC = 2.4,
95% CI = 0.0 to 4.9) is compatible with
research from Europe22,27 and the United
States.28 As with other changes described
earlier, registration artefacts such as changes
in coding practices and legislation are likely
not associated with this trend; there is
little evidence for the former and the latter
is refuted by the lack of uniform trends
across diagnostic categories and sex.
Diagnostic interdependence is also an
unlikely possibility for this period, and
there is no indication that leukemias that
would be otherwise captured as lymphomas
at a later stage are being captured earlier.
Further research should investigate if the
positive trends in leukemia specific to
boys continue over time and whether they
correlate with shifting demographic changes
such as the increase in frequency of
high birth weight infants in Canada, a
phenomenon shown to be positively
associated with leukemia and certain types
of brain cancers.29-33 It is also important to
note that the increased trends in leukemia
in boys versus girls that we observed has
been reported in many regions around the
world,34 although factors underlying this
phenomenon remain largely unsubstan­
tiated.35 The rapid increase in unspecified
leukemias noted between 1992 and 1999
(in both sexes) implies that a greater
number of cases are being grouped in the
unspecified category, with the possible
result that other leukemia subtypes are
being underestimated.
Our study did not have the power to analyse
trends in pediatric hepatic cancers by
subtype; future research should investigate
this given the emerging evidence from some
countries that links the rise of hepatoblastoma with increased survival of very low
birth weight babies.36,37 We found a modest
but non-significant increase in hepatic
cancers, a trend likely driven by annual
increases in rates in girls from 1997
onwards (APC = 8.1% per year, 95%
CI = 1.8 to 14.7); however, it is not clear
why positive trends were detected in girls
but not boys even though this cancer
tends to occur at a slightly higher rate in the
latter.20,35 We could not confirm significant
increases in brain cancer incidence recently
reported from the United States.7 Our data
showed stable incidence rates for children
aged under 10 years, and significant
decreases in 10- to 14-year-olds, a finding
that is likely attributed to astrocytomas, a
subtype of brain cancer that is known to
increase with age.23 It is worth noting that
our analysis was conducted after the
wide-scale availability and adoption of
magnetic resonance imaging in clinical
practice in North America, a tool partially
attributed with the increased diagnosis of
low-grade gliomas in the early- to mid1980s in the United States. (The incidence
of high-grade gliomas or medulloblastomas,
which are more easily detected by
computerized tomography scans, did not
increase during this period in the United
States.1,38).
Alberta was the only province with a
significant increase in the annual incidence
rates for all childhood cancers combined
(APC = 1.3%, 95% CI = 0.2 to 2.4).
Moreover, histology-specific analyses
revealed significant positive trends for
leukemia in Quebec (APC = 1.6%, 95%
CI = 0.1 to 3.1) and Alberta (APC = 3.1%,
95% CI = 0.2 to 6.1), lymphomas in
Alberta (APC = 6.5%, 95% CI = 1.4
to 12.0) and carcinomas in Ontario (APC =
4.0%, 95% CI = 0.0 to 8.2), findings that
require investigation in the context of
historical changes to registration practices.
Although considerable effort has been made
to achieve uniformity in defining and
classifying new cancer cases in the CCR,
reporting procedures and completeness
may still vary across the country. The
registry in Quebec, for example, relies more
heavily on hospitalization data for cancer
registration than do other jurisdictions.9
Childhood cancer is rare; as a result, trend
patterns that appear to be important may
in fact be due to random fluctuations.
Trends that involve just a few cases per
year and those with wide 95% confidence
intervals need to be interpreted cautiously.
Statistically significant findings may be
due to chance and not real changes in
incidence rates. Alternatively, true trends
may have also been undetected due
random fluctuation in incidence rates.
Further, it is difficult to understand how
underlying risk factors may be influencing
trends since the causes of childhood cancer
remain poorly understood.39 About 5%
to 15% of childhood cancers may be
attributable to familial and genetic factors
and less than 5% to 10% to known
environmental exposures.40,41 While we
acknowledge that the observed incidence
trends may reflect changes in unknown
risk factors or random variation, it is
encouraging that the overall rates of
childhood cancers have remained relatively
stable in Canada over the last two
decades. Some sex-specific trends, such as
137
increases in leukemia in boys and hepatic
cancers in girls, merit further investigation,
as do cancers that are increasing in certain
age groups, such as germ cell cancers and
carcinomas in 5- to 9-year-olds and CNS
cancers in 10- to 14-year-olds.
Acknowledgements
This research was funded by the Public
Health Agency of Canada. The authors
gratefully acknowledge the cooperation
of the provincial and territorial cancer
registries, the national Canadian Cancer
Registry maintained by Statistics Canada,
and the review of the draft manuscript by
Dr. Mark Bernstein, oncologist, from the
Isaac Walton Killam Health Centre. The
authors disclose that they have no financial
or personal incentives with individuals or
organizations that could inappropriately
influence or bias this research.
References
1. Linet MS, Ries LA, Smith MA, Tarone RE,
Devesa SS. Cancer surveillance series:
recent trends in childhood cancer incidence
and mortality in the United States. J Natl
Cancer Inst. 1999;91:1051-8.
2. Dalmasso P, Pastore G, Zuccolo L, Maule
MM, Pearce N, Merletti F, et al.
Temporal trends in incidence of childhood
leukemia, lymphomas and solid tumors in
north-west Italy, 1967-2001. A report of the
Childhood Cancer Registry of Piedmont.
Haematologica. 2005;90:1197-204.
3. Sharp L, Cotton S, Little J. Descriptive
Epidemiology. In: Little J, editor.
Epidemiology of Childhood Cancer. No.
149. Lyon (FR): International Agency for
Research on Cancer; 1999, p. 10-66.
4. Kenney LB, Miller BA, Ries LA, Nicholson HS,
Byrne
J,
Reaman
GH.
Increased
incidence of cancer in infants in the U.S.:
1980-1990. Cancer. 1998;82:1396-400.
5. Gurney JG, Davis S, Severson RK, Fang JY,
Ross JA, Robison LL. Trends in cancer
incidence among children in the U.S.
Cancer. 1996;78:532-41.
6. Shah A, Coleman MP. Increasing incidence
of childhood leukemia: a controversy
re-examined. Br J Cancer. 2007;97:1009-12.
Vol 32, No 3, June 2012 – Chronic Diseases and Injuries in Canada
7. Linabery AM, Ross JA. Trends in childhood
cancer incidence in the US (1992-2004).
Cancer. 2008;112:416-32.
8. Baade PD, Youlden DR, Valery PC, Hassall T,
Ward L, Green AC, et al. Trends in
incidence of childhood cancer in Australia,
1983-2006. Br J Cancer. 2010;102:620-6.
9. Canadian Cancer Statistics 2008. Toronto
(ON): Canadian Cancer Society/National
Cancer Institute of Canada; 2010.
10. Shaw AK, Morrison HI, Speechley KN,
Maunsell E, Barrera M, Schanzer D, et al.
The late effects study: design and subject
representativeness
of
a
Canadian,
multi-centre study of late effects of
childhood cancer. Chronic Dis Can.
2004;25(3-4):119-26.
11. Limburg H, Shaw AK, McBride ML. Impact
of childhood cancer on parental employment
and sources of income: a Canadian pilot
study. Pediatr Blood Cancer. 2008;51(1):93-8.
12. Gao RN, Levy IG, Woods WG, Coombs BA,
Gaudette LA, Hill GB. Incidence and
mortality of neuroblastoma in Canada
compared with other childhood cancers.
Cancer Causes Control. 1997;8:745-54.
13. Canadian Cancer Registry [Internet].
Ottawa (ON): Statistics Canada; [modified
2011 Jul 26; cited 2011 Apr 05]. Available at:
http://www.statcan.gc.ca/cgi-bin/imdb
/p2SV.pl?Function=getSurvey&SDDS
=3207&lang=en&db=imdb&adm
=8&dis=2
14. History – Canadian Cancer Registry.
Ottawa (ON): Statistics Canada; 2007
[cited 2011 Apr 03]. Available at:
http://www.statcan.gc.ca/imdb-bmdi
/document/3207_D4_T9_V1-eng.pdf
15. Statistics Canada. Demographic Estimates
Compendium 2009. Ottawa (ON): Minister
of Industry; 2009.
16. Fritz A, Percy C, Jack A, Sobin LH, Parkin
MD, editors. International classification of
diseases for oncology. 3rd ed. Geneva
(CH): World Health Organization; 2000.
17. Steliarova-Foucher E, Stiller C, Lacour B,
Kaatsch P. International classification
on childhood cancer, 3rd ed. Cancer.
2005;103:1457-1467.
18. Joinpoint Regression Program [computer
program]. Version 3.4.2. Bethesda (MD):
SEER Program, National Cancer Institute,
Statistical Research and Applications Branch;
2010. Available at: http://srab.cancer.gov
/joinpoint
19. Kim HJ, Fay MP, Feuer EJ, Midthune DN.
Permutation tests for joinpoint regression
with application to cancer rates. Stat Med.
2000;19:335-51.
20. Ries LA, Smith MA, Gurney JG, Linet M,
Tamra T, Young JL, et al., editors. Cancer
incidence and survival among children and
adolescents: United States SEER Program
1975-2005. 1st ed. Bethesda (MD): National
Cancer Institute; 1999.
21. Kaatsch P, Steliarova-Foucher E, Crocetti E,
Magnani C, Spix C, Zambon P. Time trends
of cancer incidence in European children
(1978-1997): report from the Automated
Childhood Cancer Information System
project. Eur J Cancer. 2006;42:1961-71.
22. Kaatsch P. Epidemiology of childhood
cancer. Cancer Treat Rev. 2010;36:277-85.
23. Smith MA, Freidlin B, Ries LA, Simon R.
Trends in reported incidence of primary
malignant brain tumors in children in
the United States. J Natl Cancer Inst.
1998;90:1269-77.
24. Diamandis EP, Fritche HA, Lilja H, Chan DW,
Schwartz MK, editors. Tumor markers:
physiology, pathobiology, technology and
clinical applications. 1st ed. Washington
(DC): AACC Press; 2002.
25. Johnston HE, Mann JR, Williams J,
Waterhouse JA, Birch JM, Cartwright RA,
et al. The Inter-Regional, Epidemiological
Study of Childhood Cancer (IRESCC):
case-control study in children with germ
cell tumours. Carcinogenesis. 1986;7:717-22.
26. Shu XO, Nesbit ME, Buckley JD, Krailo MD,
Robinson LL. An exploratory analysis of
risk factors for childhood malignant germ-cell
tumors: report from the Childrens Cancer
Group (Canada, United States). Cancer
Causes Control. 1995;6:187-98.
27. Kroll ME, Draper GJ, Stiller CA, Murphy
FA. Childhood leukemia incidence in
Britain, 1974-2000: time trends and possible
relation to influenza epidemics. J Natl
Cancer Inst. 2006;98:417-20.
Vol 32, No 3, June 2012 – Chronic Diseases and Injuries in Canada
138
28. Ries LA, Eisner MP, Kosary CL, Hankey BF,
Miller BA, Clegg L, et al., editors. SEER
cancer
statistics
review,
1975-2002
[Internet]. Bethesda (MD): National Cancer
Institute; 2005 [cited 2011 Feb 22].
Available from: http://seer.cancer.gov
/csr/1975_2002/
29. Ananth CV, Wen SW. Trends in fetal growth
among singleton gestations in the United
States and Canada, 1985 through 1998.
Semin Perinatol. 2002;26:260-7.
30. Hjalgrim LL, Westergaard T, Rostgaard K,
Schmiegelow K, Melbye M, Hjalgrim H, et al.
Birth weight as a risk factor for childhood
leukemia: a meta-analysis of 18 epidemiologic
studies. Am J Epidemiol. 2003;158:724-35.
31. Ross JA, Perentesis JP, Robison LL, Davies SM.
Big babies and infant leukemia: a role for
insulin-like growth factor-1? Cancer Causes
Control. 1996;7:553-9.
32. Emerson JC, Malone KE, Daling JR, Starzyk P.
Childhood brain tumor risk in relation to
birth characteristics. J Clin Epidemiol.
1991;44(11):1159-66.
33. Von Behren J, Reynolds P. Birth characteristics
and brain cancers in young children. Int J
Epidemiol. 2003;32(2):248-56.
34. Linet MS, Devesa SS. Descriptive
epidemiology of childhood leukaemia.
Br J Cancer. 1991;63(3):424-9.
35. Cartwright RA, Gurney KA, Moorman AV.
Sex ratios and the risks of haematological
malignancies.
Br
J
Haematol.
2002;118(4):1071-7.
36. McLaughlin CC, Baptiste MS, Schymura MJ,
Nasca PC, Zdeb MS. Maternal and infant
birth characteristics and hepatoblastoma.
Am J Epidemiology. 2006;162(9):818-28.
37. Tanimura M, Matusui I, Abe J, Ikeda H,
Kobayashi N, Ohira M. Increased risk of
hepatoblastoma among immature children
with a lower birth weight. Cancer Res.
1998;58(14):3032-5.
38. King MA, Newton MR, Jackson GD,
Fitt GJ, Mitchell LA, Silvapulle MJ,
et al. Epileptology of the first-seizure
presentation: a clinical, electroencephalographic,
and
magnetic
resonance
imaging study of 300 consecutive
patients. Lancet. 1998;352(9113):1007-11.
39. Ward EM, Thun MJ, Hannan LM, Jemal A.
Interpreting cancer trends. Ann N Y Acad
Sci. 2006;1076:29-53.
40. Bunin GR. Nongenetic causes of childhood
cancers: evidence from international variation,
time trends, and risk factor studies. Toxicol
Appl Pharmacol. 2004;199:91-103.
41. Lichtenstein P, Holm N, Verkasalo P,
Iliadou A, Kaprio J, Koskenvuo M, et al.
Environmental and heritable factors in the
causation of cancer: analyses of cohorts of
twins from Sweden, Denmark, and Finland.
N Engl J Med. 2000;343:78-84.
139
Vol 32, No 3, June 2012 – Chronic Diseases and Injuries in Canada
Cultural factors related to the maintenance of health behaviours
in Algonquin women with a history of gestational diabetes
S. Gaudreau, MSc (1); C. Michaud, PhD (2)
This article has been peer reviewed.
Abstract
Introduction: Though the cultural factors that may contribute to the diabetes epidemic
in First Nations are frequently discussed, little is known about the factors that may help
prevent it. In this ethnonursing study, we explore the cultural factors that help maintain
health behaviours in Algonquin women who had received a diagnosis of gestational
diabetes 2 to 10 years before this study.
Methods: The data were collected in two Algonquin communities through semi-structured
interviews with key informants (n = 7) and general informants (n = 8) and through
cultural immersion, with detailed observations being recorded into logbooks.
Results: The cultural factors that are likely to affect the prevention of diabetes are the
importance of family and social ties, the possibility of preserving cultural values, the
opportunity to learn behaviours through educational resources adapted to needs and
culture, the chance of saving money through better diet and access to blood sugar data
as a means of control.
Conclusion: In the long term, these cultural factors could influence health behaviours
and thus help prevent type 2 diabetes.
Keywords: cultural factors, gestational diabetes, Algonquin women, health behaviours,
health, type 2 diabetes
Introduction
Gestational diabetes (GD) is an intolerance
to glucose that occurs during pregnancy1
and usually disappears after delivery.2 It
is associated with complications such as
macrosomia, toxemia of pregnancy and
preeclampsia, which make delivery risky
for both mother and baby.3-4 Further, half of
those diagnosed with GD will eventually
develop type 2 diabetes.2,5,6 Interventions
support the adoption of health behaviours
that keep blood sugar at normal levels, thus
reducing the risks of complications for
mother and child.1,4,5,7 However, interventions
should take place in a cultural context and
be delivered with a knowledge of their
cultural significance,8-10 where culture is
defined as “the learned, shared, and
transmitted values, beliefs, norms, and
lifeways of a particular culture that
guides thinking, decisions, and actions in
patterned ways”9.
A number of researchers have studied
diabetes (mainly type 2) and cultural
dimensions within First Nations and
American Indian communities.10-15 According
to these studies, First Nation peoples and
American Indians perceive diabetes as
a “white disease”11-13 that is inseparable
from the profound socio-economic and
political transformations that have
characterized the relationship between
Aboriginal and non-Aboriginal societies.12
In fact, the transformation of traditional
ways of life has created socio-economic
inequalities that have a direct impact on
the health of First Nations (e.g. as a result
of fewer available natural resources, less
consumption of traditional foods and less
access to healthy, nutritious foods in some
communities).15 Further, First Nations may
have different concepts of health, including
a fatalistic view of diabetes.14 Food is a sign
of hospitality, and slimness may be viewed
negatively13 as is physical exercise such as
walking.11,12 Finally, cultural differences
are not reflected in treatments designed
to modify lifestyles.13 All these cultural
factors are impediments to health
behaviours.
In this qualitative study, we undertook
to understand the cultural factors that
contribute to the maintenance of those
health behaviours encouraged during
pregnancy in Algonquin women diagnosed
with GD. Such an understanding may
influence the development of culturally
competent care aimed at preserving those
behaviours in these women as well as in
their children and those around them.
Methods
The ethnographic approach is designed to
deepen understanding of a cultural system
from the standpoint of those who share
this culture.16 The ethnonursing approach
used in this study reveals an individual’s
lifeways and cultural vision while taking
into account context. Ethnonursing aims
Author references:
1. Centre de santé et de services sociaux Les Eskers de l’Abitibi, Amos, Quebec, Canada
2. École des sciences infirmières, Faculté de médecine et des sciences de la santé, Université de Sherbrooke, Longueuil, Quebec, Canada
Correspondence: Cécile Michaud, École des sciences infirmières, Faculté de médecine et des sciences de la santé, Université de Sherbrooke, Longueuil Campus, 150, place Charles-Le Moyne,
suite 200, Longueuil, QC J4K 0A8; Tel.: (450) 463-1835, local 61793; Fax: (450) 463-1837; Email: [email protected]
Vol 32, No 3, June 2012 – Chronic Diseases and Injuries in Canada
140
to describe, understand and interpret the
meaning of practices, beliefs and values of
other cultures.8,10,17
Population
The two Algonquin communities (Pikogan
and Lac Simon*) in this study were
chosen because of their geographical
proximity and because the directors of
the two community health centres were
interested in the study. Pikogan is in
an urban setting, while Lac Simon is
mainly rural. They are primarily Frenchspeaking, although the Algonquin
language is also used. Pikogan is a
village located about 3 km from the
municipality of Amos. In 2008, out of
551 registered inhabitants, 278 were
women.18 Approximately 52% of the
population was aged less than 25 years.19
Lac Simon is located about 32 km
from the municipality of Val-d’Or. Of the
1362 registered inha­bitants in 2008,
659 were women,18 and approximately
61% of the population was aged less
than 25 years.19 The two commu­nities
have similar health, educational and
community services: both have a health
centre, visiting doctors, an elementary
school, a daycare, a police station, a church,
a community room, a convenience store, a
community radio station, a youth centre
and buildings belonging to each Band
Council. Lac Simon also has a high school,
a post office and a restaurant, while Pikogan
has a sports arena.
Informant selection and recruitment
An ethnonursing study involves two kinds of
participants: key informants and general
informants.8,9 The key informants in this
study (n = 7) were directly concerned
with the issue: they had been diagnosed with
GD and had received care in their community
health centre (Table 1). Inclusion criteria
were the following: Algonquin; aged 18 years
plus; diagnosed with GD 2 to 10 years before
the start of this study; received health care
in the Algonquin community when given
the diagnosis of GD; neither breastfeeding
nor pregnant during the study. The key
informants were recruited by three of the
general informants.
For reasons of anonymity, age and
education are not given, though mean
age was 34 years (range: 29–40 years) and
half had not completed high school. We
assigned each key informant a fictitious
given name similar to those used in the
two communities in the order of the
interviews. Thus, the first person interviewed at Lac Simon was assigned
the letter A and given a name starting
with a (e.g. Amy), and so on until d. To
differentiate from them, the women of
Pikogan were given fictitious names that
began with i and continued until k (see
Table 1).
General informants have a more general
view of the issue. They were introduced
to us by the resource people who, in turn,
were our first point of contact in the
communities. General informants were
willing to speak freely of their experience
with the community and to give feedback
on the participant observation notes. A
total of 8 people were consulted as general
informants: 4 nurses, a nutritionist, a social
worker, a nursing assistant and a dental
hygienist; 2 were First Nations and 6 worked
in Lac Simon. They had between several
months and eight years of experience in
the community ( x– = 3.5 years).
Data collection
The data were collected through participantobservers and semi-structured interviews.
Our cultural immersion in the Pikogan and
Lac Simon communities took place over
2 months in March and April 2006, during
which time we observed the activities of
health workers; participated in collective
kitchen activities, community meals, home
visits, etc.; and made observations on the
environment, for example, the food in the
convenience store and the school canteen
(“Club des petits déjeuners”). We used a
logbook to record our observations in a
condensed, consistent format to encourage
reflection, as recommended by the
Observation-Participation-Reflection
Enabler.8 We interviewed key informants
in French, usually at the community health
centre, using semi-structured interviews
based on Leininger’s cultural factors8,9 and
the Taylor et al. study.14 (see Appendix A).
The interviews, which lasted on average
Table 1
Summary of the sociodemographic and health profiles of the key informants (n = 7)
Fictitious
namea
Community
Language spoken
Algonquin
French
English
Time of GD
diagnosis
Diagnosed
with T2D
BMI, kg/m2
Number of
children
Amy
Lac Simon
Yes
Yes
No
1999
Yes
36.0
6
Brenda
Lac Simon
No
Yes
No
2003
Yes
28.3
6
Céline
Lac Simon
No
Yes
No
2004
No
36.0
5
Diane
Lac Simon
Yes
Yes
No
2003
No
34.4
4
Isabelle
Pikogan
No
Yes
Yes
2003
No
33.9
4
Julie
Pikogan
No
Yes
Yes
2003
No
36.6
5
Kimberly
Pikogan
No
Yes
No
2003
No
28.9
5
Abbreviations: BMI, body mass index; GD, gestational diabetes; T2D, Type 2 diabetes.
a
A fictitious given name (similar to those found in the two communities) was assigned to the key informants according to the order of the interviews. Thus, the first person interviewed at
Lac Simon was assigned the letter A and a given name starting with the letter a and so on until D. To differentiate the women of Pikogan, the fictitious names began with the letter I and
continued until the letter K.
* The directors of both community health centres agreed to the communities being named in this article.
141
Vol 32, No 3, June 2012 – Chronic Diseases and Injuries in Canada
for 47 minutes, were recorded to allow
subsequent verbatim transcription and
analysis.
The focus of the interviews was on
maintaining health behaviours and not
on obstacles to maintaining them. This
study was not intended to influence or
judge existing health behaviours.
Data analysis
We analyzed our observations in four
phases10 and followed Miles and Huberman’s
process of data analysis.20 The first phase
was based on our observations during the
cultural immersion and the interviews with
the Algonquin women. The log book entries
helped to place the verbatim interviews in
context. In the second phase, we conducted
a vertical analysis of the verbatim interviews,
classifying each sentence according to
Leininger’s cultural factors,8,9 in order to
reveal the cultural factors within each
transcript. The third phase, the horizontal
analysis of patterns and context of the
cultural factors, resulted in a collection of
those cultural factors that contributed to
the maintenance of the health behaviours
encouraged during the pregnancies of all
the interviewees. During the fourth phase,
we confirmed the themes and subthemes
with the key and general informants. Only
one theme was reconstructed after this
confirmation: it concerned the importance
of friends in the maintenance of health
behaviours.
Appendix B lists the strategies used to
ensure rigorous data analysis.
Ethical considerations
The ethics board of the clinical research
centre of the Centre hospitalier universitaire
de Sherbrooke and the directors of the
Pikogan and Lac Simon health centres
approved this study. It followed the
guidelines set by the Tri-Council Policy
Statement21 for research projects conducted
on lands under the jurisdiction of a
First Nations authority, including obtaining
written approval from the responsible
community bodies and masking the
identities of participants.
Results and discussion
Table 2 summarizes the main cultural
factors that contributed to the maintenance
of health behaviours, arranged according
to five themes and several subthemes. The
results are presented and discussed in the
same section.
Family and social ties as motivation and
support for maintaining health behaviours
Family and social ties were the primary motivation for maintaining health behaviours. As
found by Taylor et al.,14 the Algonquin
women participating in this study did not
want their children to develop diabetes:
“Yes, I kept eating the same way. I did it
mainly for myself and my daughter. I don’t
want her to have adolescent diabetes either.
She’s overweight, and I don’t want that for
her. So I kept my way of eating... but more
for myself... and her too” (Julie†, line 528).
The experiences of key informants’ parents
was a constant reminder of the possible
complications: “I can’t allow myself to have
complications like that in just five years... My
father was on dialysis, and my grandmother
had to have an amputation” (Amy, line 45).
The encouragement of family and the community was important: “Everyone tells me
they can see I am losing weight. It helps
when someone tells you that” (Julie, line
840). Also important was offering support:
“... We tried to come up with a kind of diet
that we could go on, her and me, to help
our diabetes” (Julie, line 359). Another way
of encouraging was by giving advice: “[My
sister] told me: ‘That has too much sugar
in it... That’s what’s in there. How many
calories are in a meal if you go to a restaurant?’ Because my sister is diabetic. That
really helped me too” (Kimberly, line 378).
The communities supported some physical
activities, mainly walking, by painting
these in a positive light: “I think people
Table 2
Factors promoting the maintenance of health behaviours in the key informants (n = 7)
Factors
Family and social
Theme
Family and social factors as motivation and support
for the maintenance of health behaviours
Subthemes
Concern for children’s health
Family and community support
Family members’ experiences
Desire to be together
Lifestyle and
cultural
Adopting new health behaviours while preserving
cultural values
Adaptation of traditional foods
Diet modification
Walking
Synergy between diet and walking
Educational
†
Learning through educational resources adapted to
needs and culture
Economic
Saving money through better diet
Technological
Access to blood sugar data through technological
advances with glucometers
Capacity for self-learning
Cultural adaptation of teaching and support
Glucometers as a means of immediately checking whether blood sugar is normal
Downloading eliminates the need to write the information down
When doing so did not affect the phenomena under study, we deleted or changed certain facts to preserve the anonymity of the key informants.
Vol 32, No 3, June 2012 – Chronic Diseases and Injuries in Canada
142
are starting to see the value of it ...”
(Kimberly, line 939). Walking lets people
socialize as they engage in a physical
activity: “I go walking with a friend. We talk
and chat while we walk... sometimes I go
with my boyfriend” (Kimberly, line 947).
Family or social support was very important
to the participants, and lack of it makes
it more difficult for some First Nations
women with diabetes to effectively
adopt new health behaviours.12 From a
psychosocial standpoint, individuals who
receive peer support run less of a risk of
developing physical or mental problems.22
Adopting new health behaviours while
preserving cultural values
The second theme consists of adopting
new health behaviours, especially those
related to diet and physical activity, while
preserving cultural values.
According to the Algonquin women, their
traditional diet can be adapted to help
maintain health behaviours. The methods
of cooking certain traditional foods and
using less fat in food preparation can
contribute to good health and prevent
diabetes. The key informants said they
could choose game meats that have less
fat than others (e.g. moose versus beaver).
The key informants changed their diets
following a GD diagnosis and followed
a balanced diet that reflected the goals
of Canada’s Food Guide.23 The changes
consisted of additions to traditional foods,
not their removal. Due to their symbolic
aspect, the use of traditional foods and
methods of preparation are important
to First Nations peoples, and they feel
accepted and respected when health
care professionals take these traditional
practices into account.24
The key informants said that they would
like a cookbook that included traditional
foods to help them manage their diabetes;
this would also uphold respect for traditional values. Both health centres held
community meals that included traditional
foods adapted for a special diet, for example,
banik (traditional bread) prepared with
whole-wheat flour, and also distributed
the recipes.
The participants also considered exercise
key to maintaining a healthy weight and
preventing type 2 diabetes: “Exercise is the
important thing for me because when you
train a lot, diet follows. I know that when
I was walking a lot, I was less likely to eat
chips and drink soft drinks” (Kimberly,
line 881). Walking was the physical activity
that was mentioned most often during
the interviews because of its numerous
advantages, not least that it both energizes
and relaxes: “Walking? Yes, it helps me a
lot with stress because I work and I have
five children at home under the age of 10”
(Julie, line 746). Walking can also be
compatible with family values (e.g. walking
with the children) and the participants’
lifestyles (e.g. not having a car, working
outside the home).
The significance of weight loss as
described by the participants is supported
by research that shows that overweight
and lack of physical activity are risk factors
for type 2 diabetes,2 and that a 5% to 10%
weight loss through changes in diet and
physical activity can prevent or delay the
emergence of type 2 diabetes in certain
persons with glucose intolerance.25 Critical
to this was the participants’ perception of
thinness and overweight. Although each had
a high body mass index (BMI x– = 33.4),
they did not associate slenderness with
disease, unlike people in other studies.13
Rather, they had a negative perception
of overweight, as did the women of the
Oklahoma First Nations.14
Learning new behaviours through educational
resources adapted to needs and culture
According to the key informants, certain
ways of acquiring new knowledge provide
more choices and freedom: the third theme
addresses the opportunity of learning with
educational resources adapted to needs and
culture. For example, self-learning through
reading helps prevent frequent visits to the
health centre and provides a certain form
of autonomy where there is an overall lack
of other resources: “... usually it meant
I didn’t have to go anywhere... because...
since there are no training sessions on
that here, and often there was a long wait
to see the nurse” (Céline, line 1168). The
capacity for self-learning and keeping
informed increases the chances of staying
143
healthy: “Are there things you do to be able
to say ‘that’s important for me for staying
healthy’?” (Sylvie, line 1183, interviewing
Isabelle). “Yes, keeping informed, that’s
all!” (Isabelle, line 1187). Daniel and
Messer26 also found that First Nations
place considerable value on autonomy
and may even be wary of health education
initiatives they perceive as an occidental
intrusion into their way of life. This
preference for autonomy is supported by
the shared decision-making framework,27
which could be more acceptable to them
than regular diabetes classes.
The Algonquin women who participated
in this study mentioned the importance
of learning with educational resources
and supports adapted to their needs
and culture, especially to their way of life.
For example, they wanted to learn how
to choose ingredients to preserve or improve
nutritional values in their traditional foods.
“I made banik at home using vegetable
oil. I wanted to change oils, but I didn’t
know which one to choose...the one with
the lowest fat (the least unhealthy one)”
(Julie, line 618). They also wanted to learn
ways that uphold the traditional
Algonquin way of life, which involves
frequently being in the woods: “What
we eat, the Anicinabek [Algonquins]...
[laughter]... we often go out in the
woods as well... They should think about
that...we go out in the woods” (Brenda,
line 855).
This cultural adaptation of learning can also
take place through other adapted activities.
Several key informants mentioned the idea
of a forest “diabetes camp” co-facilitated by
the nurse and the nutritionist who would
incorporate instruction into traditional
activities (e.g. walking in the woods,
snowshoeing). Macaulay et al.28 also
understood the importance of adapting
instruction
to Mohawk culture to
positively affect diabetes prevention.
According to the key informants, the
continual illness prevention and health
promotion activities of health care
professionals were key to maintaining
health behaviours. The health care
professionals would frequently encourage
those making progress with respect to
their health, especially people living with
Vol 32, No 3, June 2012 – Chronic Diseases and Injuries in Canada
diabetes of any type. They took advantage
of community events to hold their
health promotion activities. They adapted
appointments to the Algonquin way of
life: instead of making appointments for
a fixed time and date, they intervened
immediately, adapting to a culture-specific
concept of time described by the general
informants as “now or never.”
Some general informants maintained that,
compared to previous generations, the
younger generation of Algonquin women
are more likely to make individual life
choices. Further, if they feel good in their
everyday lives, they tend to “shop well”
and buy healthy, nutritionally balanced
foods. Some key informants said they felt
more comfortable with the First Nations
nurse who questioned them regularly
about drug and alcohol use, the support
given by their family, etc. This holistic
approach was in line with the values of
the women in both communities.
Even though previous studies found that
educational activities are not always adapted
to First Nations culture, according to the
key informants the health care professionals
facilitated the adoption of health behaviours
and organized a number of activities that
were culturally adapted to Algonquin
women, as recommended by Daniel and
Messer.26
Saving money through better diet
After learning how to manage their diabetes,
a number of participants found themselves
saving money by eating a better diet. Some
said they went to restaurants less often or
ate differently when they did go out to
eat: “I didn’t eat out as often. It became
less expensive to eat out because I cut down
on my portions” (Isabelle, line 1062). They
maintained the health behaviours after
pregnancy because of the money-saving
aspect of the better diet.
During their pregnancy, some of the
participants took part in community
kitchens funded by the Canada Prenatal
Nutrition Program.29 They learned about
the costs of different foods as well as how
to read flyers and make shopping lists:
“I often looked at the flyers... I went to the
places where there were better specials”
(Céline, line 1110). They said that as a
result they could make more informed
choices about the quality and quantity of
foods, and that this affected their budget.
Access to information on blood sugar using
glucometers
The final theme concerns access to blood
sugar monitoring through technology.
Several participants in both communities
used a glucometer to measure their blood
sugar levels: “It shows whether...your
blood is normal and all that!... You see
right away whether your blood is normal”
(Céline, line 182). Some of the participants who did not currently have diabetes
continued to use their glucometers
regularly to monitor their blood sugar as
a preventive means.
Technology available to the Algonquin
women in both community health centres
allows them to monitor and compare their
blood sugar levels more easily by downloading the glucometer data in a graphic
so that they do not have to record their
blood sugar levels. Self-monitoring can
reduce the use of clinical and professional
care, and users feel more self-confident
and independent, both important elements
in self-management.30
Limitations of the study
This study sheds light on cultural factors
that contribute to the maintenance of health
behaviours in a First Nation population.
This perspective is primarily that of the
Algonquin women who received educational services and support for GD during
their pregnancy and post-partum. General
informants of both Algonquin and nonAlgonquin origin supported the themes that
emerged from the data. As a result of
basing this study in the two communities
of Lac Simon and Pikogan, we have taken
into account about one-quarter of the
Algonquin population in Quebec,31 though
not necessarily those living in urban
communities.
Conclusions
While this study is exploratory in nature,
it suggests that cultural practices can
influence the maintenance of health
Vol 32, No 3, June 2012 – Chronic Diseases and Injuries in Canada
144
behaviours among Algonquin women
who have had GD.
Our study found that an approach centred
on friends and family rather than on the
individual could help Algonquin women
who have had GD maintain healthy
behaviours. Cultural adaptations of health
education were a priority in the maintenance
of health behaviours for the study
participants. Health care professionals
could continue to develop activities for
Algonquin women that are culturally
adapted, such as those in the woods or
in environments conducive to physical
activity. Working closely with their
clients, health care professionals can help
them make full use of their own abilities
to become autonomous and improve
their well-being.32 In addition, Health
Canada has published a new Canada’s
Food Guide, including one specifically
for First Nations, Inuit and Métis.23 The
adapted version could be used to explain
the nutritional, social and spiritual value
of traditional foods and to explain the
harmful effects of processed foods as part of
a strategy to reduce obesity and obesityrelated chronic disease such as diabetes.33
The Algonquin women in the study also
found that they were able to save money
through a more nutritious diet.
Our study found that using a glucometer
to measure blood sugar levels seemed to
empower participants, indicating that it
could be used as a tool in preventive
self-management practices. This is at
variance with the 2009 recommendations
on glucometer use made by the Canadian
Agency for Drugs and Technologies in
Health (CADTH).34 In its review the
CADTH did not notice significant clinical
improvement of the A1C concentrations
in non-insulin-dependent patients.34
The themes emerging from this study present
a unique cultural perspective that could help
health care professionals and First Nation
communities develop services and strategies
specifically for Algonquin women who have
had a GD diagnosis. These services and
strategies could contribute to the health and
well-being of pregnant women and their
children and in the prevention of type 2
diabetes in the Algonquin population.
Acknowledgements
The authors wish to thank those who
helped recruit participants for this study:
Suzanne Paré, Nurse (Pikogan Health
Centre); Karen Morency, Nutritionist (Lac
Simon Health Centre); and Rose Dumont,
Nurse (Lac Simon Health Centre). We also
acknowledge the collective contribution of
the communities to this research as well
as that of the individual contributions
described in this study.
We thank the following for their financial
contribution in the form of scholar­ships:
Health Canada, Tembec, National Aboriginal
Achievement Foundation, and the Ordre
régional des infirmières et infirmiers de la
Montérégie. We thank Health Canada as
one of our authors was an employee at the
time this paper was being written. Finally,
we thank the Abitibiwinni Band Council
for a school allowance to help young
Algonquins continue their education.
Appendices
Appendix A
Interview guide (based on Taylor et al.14, p.9)
World view
• Describe your current health.
• Describe how you feel about your health.
• What do you do to stay healthy?
• Do you have any health concerns?
• What are the major health concerns of Aboriginal women?
• What comes to mind when I say “gestational diabetes”?
• What do you think happens to a woman once she develops gestational diabetes?
• And after her pregnancy?
• What do you think happens to the baby of a woman who develops gestational diabetes?
• And after his or her birth?
• What does a woman in your community do if she is diagnosed with gestational diabetes?
• In your community, how do people explain gestational diabetes?
• Do you think that gestational diabetes is more or less frequent in your community?
• How does your community care for a woman who is diagnosed with gestational diabetes?
Language
• What are the words used to speak about diabetes?
• What are the words health care professionals use to speak about diabetes?
Technological factors
• How did you monitor the sugar in your blood when you were pregnant?
• Are there technological tools that help manage gestational diabetes?
Religious and philosophical factors
• Did you consult with a wise man or a shaman when you had gestational diabetes? Explain.
• What treatments do you trust to treat gestational diabetes?
Social and family factors
• What is the role of members of your family regarding gestational diabetes?
• How would you make decisions regarding gestational diabetes in your family? In your community?
Cultural values and way of life
• What do you think causes gestational diabetes?
• Why do you think these things (mentioned above) cause gestational diabetes?
• How did you react when you received the diagnosis of gestational diabetes?
• Which changes did you make during your pregnancy after you learned of the diagnosis of gestational diabetes?
• Which changes didn’t you make among those that were recommended?
• What did you maintain in the changes you made while pregnant?
• What is your main concern about having gestational diabetes?
• In your view what is good nutrition or a balanced diet?
• In your community what do you consider to be traditional foods? Are they part of the regular diet of your community?
• Do you think eating a more traditional diet would help prevent diabetes or gestational diabetes?
• Which foods should a woman with gestational diabetes eat?
• In your community can a woman with gestational diabetes exercise?
Continued on the following page
145
Vol 32, No 3, June 2012 – Chronic Diseases and Injuries in Canada
Appendix A (continued)
Interview guide (based on Taylor et al.14, p.9)
Political and legal factors
• How does the community show its concern for women who have gestational diabetes?
• What do you think the Band Council or the government could do to help women that have gestational diabetes?
Economic factors
• What are the main expenses caused by having gestational diabetes?
• Did those expenses have a repercussion on your budget?
Educational factors
• How did you learn what you know about gestational diabetes?
• Where do you find your information about diabetes?
• To what extent are you satisfied with the information you received on gestational diabetes? How was this information adapted to your culture?
Care practices
• What are the most important behaviours to maintain your health?
• How did you come to associate health with these behaviours?
• In your opinion, are those behaviours also important for your children?
• What are the health behaviours that you would like to pass on to your children?
• How do you try to pass on those health behaviours to your children?
• Do you think these behaviours have an impact on diabetes or gestational diabetes?
• If yes, what kind of impact?
• If not, which health behaviours could have an impact?
• What could a woman who has/had gestational diabetes do to try to prevent or to delay onset of diabetes?
Appendix B
Strategies used to ensure rigour in analysis of data
Criteria
Credibility
Definition17
Strategies
Accuracy, truthfulness and authenticity of results
Verbatim transcript
Sentence by sentence analysis
Inter-rater agreement
Confirmability
Approval of results by informants
Results submitted to informants and modification of a theme
Meaning in context
Meaning given to results reveals one of people from
a specific context
Rich and dense description of the context, supported by notes in the logbook
Recurrent patterning
Detailed examination of data to discover the repetitions
of themes, patterns, behaviour reflecting a trend
Horizontal analysis
Saturation
Results answer the goal of the research and additional data
won’t help in the understanding of the phenomenon
Confirmation by informants that the phenomenon was adequately covered
Transferability
Application of results to other contexts, situations
or cultures
Conference given to the Rapid Lake
Inter-rater agreement
Presentation to First Nations and Inuit Health, Quebec Region
Rich and dense description of the context
Publication of an article in a scientific journal
Vol 32, No 3, June 2012 – Chronic Diseases and Injuries in Canada
146
References
1. Canadian Diabetes Association Clinical
Practice Guidelines Expert Committee.
Canadian Diabetes Association 2008 clinical
practice guidelines for the prevention and
management of diabetes in Canada. Can J
Diabetes. 2008;32(suppl 1):S1-S201.
2. Diabetes in Canada [Internet]. 2nd ed.
Ottawa (ON): Health Canada; 2002 [cited
2010 Nov 2]. Available at: http://
www.phac-aspc.gc.ca/publicat/dic-dac2
/english/01cover-eng.php
3. Lowdermilk DL, Perry S, Bobak IM. Soins
infirmiers: périnatalité. Laval : Groupe
Beauchemin Éditeur Inc.; 2003.
4. Masseboeuf N, Corset E. Diabète gestationnel,
nécessité d’une éducation diététique.
Soins. 2002;667:17-9.
5. Boivin S, Derdour-Gury H, Perpetue J,
Jeandidier N, Pinget M. Diabète et
grossesse.
Ann
Endocrinol
(Paris).
2002;63(5):480-7.
6. Rodrigues S, Robinson E, Gray-Donald K.
Prevalence of gestational diabetes mellitus
among James Bay Cree women in Northern
Quebec. CMAJ. 1999;160(9):1293-7.
7. Setji TL, Brown AJ, Feinglos MN.
Gestational diabetes mellitus. Clinical
Diabetes. 2005;23(1):17-24.
8. Leininger M, McFarland MR. Transcultural
nursing: concept, theories, research and
practice. 3rd ed. Toronto (ON): McGraw-Hill
Medical Publishing Division; 2002.
9. Leininger M, McFarland MR. Culture care
diversity and universality: a worldwide
theory of nursing. 2nd ed. Boston (MA):
Jones and Bartlett; 2006.
10. McFarland MR. The ethnonursing research
method and the culture care theory:
implication for clinical nursing practice.
In: Parker M, editor. Nursing theories
and nursing practice. Philadelphia (PA):
F.A. Davis Company; 2001. p. 377-90.
11. Roy B. Le diabète chez les autochtones: regard
sur la situation à Betsiamites, Natashquan
et La Romaine. Recherches amérindiennes
au Québec. 1999;XXIX(3):3-18.
12. Roy B. Sang sucré, pouvoirs codés et
médecine amère. Diabète et processus de
construction identitaire: Les dimensions
socio-politiques du diabète chez les Innus
de Pessamit [PhD thesis], [Sainte-Foy
(QC)]: Université Laval; 2002.
22. Devault A, Fréchette L. Le soutien social:
ses composantes, ses effets et son insertion
dans les pratiques sociosanitaires. In:
Carroll G, editor. Pratiques en santé
communautaire. Montréal (QC): Chenelière
Éducation; 2006.p. 141-52.
13. Smith-Morris CM. Reducing diabetes in
Indian Country: lessons from the three
domains influencing Pima diabetes. Hum
Org [Internet]. 2004;63(1):34-46.
23. Health Canada. Eating well with Canada’s
food guide – First Nations, Inuit and Métis.
Ottawa: Government of Canada, 2007 [cited
2008 Nov 24]. Available at: http://
www.hc-sc.gc.ca/fn-an/food-guide-aliment
/fnim-pnim/index-eng.php
14. Taylor C, Keim KS, Sparrer A, Van Delinder
J, Parker S. Social and cultural barriers to
diabetes prevention in Oklahoma American
Indian women. Prev Chronic Dis.
2004;1(2);1-10.
15. Travers KD. Using qualitative research to
understand the sociocultural origins of
diabetes among Cape Breton Mi’kmaq.
Chronic Dis Can. 1995;16(4).
24. Tom-Orme L. Transcultural nursing and
health care among Native American
peoples. In: Leininger M, McFarland MR,
editors. Transcultural nursing: concept,
theories, research and practice. 3rd ed.
Toronto (ON): McGraw-Hill Medical
Publishing Division; 2002. p. 429-40.
16. Fortin M-F. Le processus de la recherche:
de la conception à la réalisation. VilleMont-Royal (QC): Décarie Éditeur Inc; 1996.
25. American Diabetes Association. Diagnosis
and classification of diabetes mellitus.
Diabetes Care. 2008;31(suppl. 1):S55-S60.
doi:10.2337/dc08-S055.
17. Leininger MM. Theory of culture care
diversity and university. In: Parker M, editor.
Nursing theories and nursing practice.
Philadelphia (PA): F.A. Davis Company;
2001. p. 361-76.
26. Daniel M, Messer LC. Perceptions of
disease severity and barriers to self-care
predict glycemic control in Aboriginal
persons with type 2 diabetes mellitus.
Chronic Dis Can. 2002;23(4):130-8.
18. Welcome to First Nation Profiles [Internet].
Gatineau (QC): Aboriginal Affairs and
Northern Development Canada; 2008 [updated
2008 Nov 14; cited 2008 Nov 19]. Available
at: http://pse5-esd5.ainc-inac.gc.ca/fnp/
27. Quill T E, Brody H. Physician recommendations and patient autonomy: finding a
balance between physician power and
patient
choice.
Ann
Intern
Med.
1996;125(9):763-9.
19. 2006 Community Profiles [Internet].
Ottawa (ON): Statistics Canada; 2009
[cited 2008 Apr 20]. Available at: http://
www12.statcan.ca/census-recensement
/2006/dp-pd/prof/92-591/index.cfm?Lang=E
28. Macaulay A C, Cargo M, Bisset S, Delormier T,
Lévesque L, Potvin L, et al. Community
empowerment for the primary prevention of
type 2 diabetes: Kanien’keha:ka (Mohawk)
ways for the Kahnawake Schools Diabetes
Prevention Project. In: Ferreira MK, Lang GC,
editors. Indigenous peoples and diabetes:
community empowerment and wellness.
Durham (NC): Carolina Academic Press;
2006. p. 407-33.
20. Miles MB, Huberman, MA. Analyse des
données qualitatives. Paris (FR): De Boeck
Université; 2003.
21. Canadian Institutes of Health Research;
Natural Sciences and Engineering Research
Council of Canada; Social Sciences and
Humanities Research Council of Canada.
Tri-Council Policy Statement: ethical conduct
for research involving humans [Internet].
Ottawa (ON): Government of Canada; 2010
[cited 2010 Mar 2]. Available at: http://
www.pre.ethics.gc.ca/pdf/eng/tcps2
/TCPS_2_FINAL_Web.pdf
147
29. Public Health Agency of Canada. The
Canada Prenatal Nutrition Program: A decade
of promoting the health of mothers, babies
and communities. Ottawa (ON): Government
of Canada; 2007 [cited 2008 Dec 29]
[Catalogue No.: HP10-11/2007]. Available at:
http://www.phac-aspc.gc.ca/hp-ps/dca-dea
/publications/pdf/mb_e.pdf
Vol 32, No 3, June 2012 – Chronic Diseases and Injuries in Canada
30. Health Promotion and Programs Branch,
Health Canada. Supporting self-care: the
contribution of nurses and physicians – an
exploratory study. Ottawa (ON): Health
Canada; 1997.
31. Secrétariat aux affaires autochtones.
Aboriginal population in Québec [Internet].
Québec: Government of Québec; [cited
2005 Sep 26]. Available at: http://
www.autochtones.gouv.qc.ca/nations
/population_en.htm
32. Hagan L, Proulx S. L’éducation pour la
santé: le temps d’agir. Linfirm Que.
1996:3(3);44-52.
33. Federal, provincial and territorial governments
of Canada; National Aboriginal Organizations.
Blueprint on Aboriginal Health: A 10-Year
Transformative Plan. November 24-25, 2005
[Internet]. [Cited 2008 Nov 24]. Available at:
http://www.hc-sc.gc.ca/hcs-sss/alt_formats
/hpb-dgps/pdf/pubs/2005-blueprint
-plan-abor-auto/plan-eng.pdf
34. COMPUS. Summary report: optimal
prescribing and use of blood glucose test
strips for self-monitoring of blood glucose
[Internet]. Ottawa (ON): Canadian Agency
for Drugs and Technologies in Health; 2009
[cited 2011 Oct 8]. Available at: http://
www.cadth.ca/media/pdf/C1109_bgts
_summary_report_e.pdf
Vol 32, No 3, June 2012 – Chronic Diseases and Injuries in Canada
148
Coaches’ knowledge and awareness of spit tobacco use among
youth athletes: results of a 2009 Ontario survey
J. H. C. Skinner, MSc (1); S. J. Bobbili, MPH (2)
This article has been peer reviewed.
Abstract
Background
Introduction: Public health professionals have become concerned that spit tobacco
(ST) use among athletes is increasing. However, little is known about the issue in
Canada, particularly among youth.
Spit tobacco: use and risks
Methods: The Not to Kids Coalition and the Coaches Association of Ontario
surveyed coaches regarding ST knowledge and awareness and their perceived roles
as coaches in influencing ST use among their athletes. Surveys were distributed
electronically to individuals who coached male and female youth aged 9 to 18 years
in baseball, basketball, football, soccer, and track and field, in Ontario.
Results: Almost all of the surveyed coaches responded correctly to questions about
the health effects of ST use, and about 80% of respondents answered correctly to the
question about legislation associated with ST and youth.
Conclusion: Most coaches are interested in receiving information about ST, particularly
the health effects of ST use and how to prevent ST use among athletes. Multiple
formats should be used to provide information to coaches, including both electronic
and hard copy materials.
Keywords: tobacco, smokeless chewing tobacco, youth, sport, mentor, coach
Introduction
Anecdotal observations and local survey
results shared at Not to Kids Coalition
(NTK) meetings between 2006 and 2007
have indicated that the use of oral
(spit) tobacco is increasing among
sports participants.1 The purpose of our
research is to assess the knowledge
level of Ontario coaches about spit
tobacco (ST) products and to assess
their perceptions of ST use among the
athletes they coach. This study is
not intended to measure prevalence;
it was undertaken to direct health
promotion initiatives that prevent
initiation and promote cessation of
the use of ST products among youth.
The study was completed through an
online survey of amateur coaches
who work with children and youth in
Ontario.
This project directly addresses legislation
mandated by the Ontario government:
to work with priority populations to
adopt tobacco-free living and reduce
the burden of preventable chronic
diseases.
It
also
addresses
the
requirement of Boards of Health
to
monitor
emerging
trends
in
tobacco use.2
Smokeless tobacco is defined as tobacco
products that are administered without
being burned.3 Smokeless tobacco is mainly
found in two forms: oral (moist) snuff,
which is powdered, and chewing tobacco,
which is coarsely cut.4 Those who use
smokeless tobacco either place a “pinch”
of snuff between their gum and their lip
or cheek or chew a “wad” of chewing
tobacco. The released nicotine is absorbed
through membranes in the mouth.4 The
term spit tobacco (ST) is used here to
refer to both these forms of tobacco.
Like all tobacco products, ST is associated
with many adverse health outcomes.
Tobacco-specific nitrosamines (cancercausing chemicals) have been linked to
oral cancers in humans.5 Specifically, ST
use has been shown to cause leukoplakia,
white patches and lesions on the cheeks,
gums or tongue that may lead to oral
cancer.5 ST use can also lead to gum
disease and tooth decay and is associated
with increased mortality from cardiovascular
disease and stroke.6,7 Of particular concern
is that ST may be more addictive than
cigarettes; compared to cigarette smokers,
ST users are exposed to large amounts of
nicotine over longer periods.5
Use of spit tobacco among youth
The NTK is a network of 31 public health
units from across Ontario whose aim is to
reduce youth access to and use of tobacco
Author references:
1. Haliburton, Kawartha, Pine Ridge District Health Unit, Port Hope, Ontario, Canada
2. Centre for Addiction and Mental Health, Toronto, Ontario, Canada
Correspondence: Jennifer Hope Campin Skinner, Haliburton, Kawartha, Pine Ridge District Health Unit, 200 Rose Glen Road, Port Hope, ON L1A 3V6; Tel.: (905) 885-9100;
Fax: (905) 885-9551; Email: [email protected]
149
Vol 32, No 3, June 2012 – Chronic Diseases and Injuries in Canada
products. NTK recently conducted surveys
and focus groups among Ontario youth
aged 14 to 19 years. These indicated that
youth perceive ST as a safer alternative to
cigarette smoking because it produces no
smoke.1 Moreover, youth respondents failed
to identify many of the health-related
consequences of using ST.1
In North America and Europe, ST use is not
as prevalent as cigarette smoking, but it
may be increasing due to the introduction of
smoking bans in public spaces.7 According to
the 2008 Canadian Tobacco Use Monitoring
Survey, 1% of youth aged 15 to 19 years
(n = 30 000) and 1% of young adults
aged 20 to 24 years (n = 27 000) reported
using ST in the preceding 30 days.8
However, in the 2008/2009 Youth Smoking
Survey, 5% of Canadian youth in grades
6 through 12 (n = 2 600) and 4% of
Ontario students in grades 6 through 12
(n = 360) reported having “ever tried” ST.9
In the United States, the National Survey
on Drug Use and Health reported that
ST use among persons aged 12 or older
remained stable at between 3.0% and 3.3%
from 2002 to 2007.10 However, ST use
increased among certain subpopulations,
specifically adolescent males, from 3.4%
in 2002 to 4.4% in 2007, and was higher
among those residing in rural areas.10
Age, gender, geography, ethnicity and
education are all factors related to the
prevalence of ST use. The 2009 National
Youth Risk Behavior Survey estimated the
prevalence of ST use among American
high school students at 8.9%.11 This
prevalence varied across states, ranging
from 4.9% in Hawaii to 16.2% in
Wyoming, and was higher among male
compared to female high school students
and among White compared to Black
and Hispanic students.11 The prevalence
among White male students was very
high, at 20.1%.11
Use of spit tobacco in sport
To determine how ST use varies across
sports, a 2001 National Collegiate Athletic
Association (NCAA) study asked male
athletes (17–20 years) to report their ST use
in the preceding 30 days. ST use was reported
as follows: baseball, 41%; wrestling, 39%;
ice hockey, 35%; lacrosse, 32%; football,
29%; golf, 27%; water polo, 25%; soccer,
20%; track and field, 17%; tennis, 13%;
and basketball, 12%.13
Research indicates that adolescents who
participate in organized sports, while less
likely to smoke cigarettes, are more likely
to use ST.14,15 Castrucci et al. reported that
adolescents in grades 9 through 12 who
participate in organized sports have 33%
increased odds of ever using ST and 76%
increased odds of currently using ST.14
Rigotti et al. reported similar findings in
their study of 14 138 students aged 18 to
24 years at 119 colleges in the United
States.16 The researchers found that
intercollegiate athletes were more likely to
use ST than cigarettes and suggested that
athletes may be using ST instead of
cigarettes as a substitute form of nicotine.16
The NCAA conducted a study of 1985
teams through 1032 member institutions
that produced 19 676 responses; they found
the prevalence of ST use to be 16.3%.17
Among athletes who use ST, more than
50% began in high school; however,
approximately 10% began using ST in
junior high school or earlier.17
College student-athletes reported using
recreational drugs, such as ST, primarily for
recreational or social reasons (46.8%) or “to
feel good” (28.1%).18 Other reasons given
included to help deal with the stress of
college life and college athletics (21.2%),
to improve athletic performance (2.0%)
and to fit in with the team (1.8%).17
The role of coaches
Goebel et al. identified several correlates
to ST use among fifth, eighth and eleventh
graders in the United States, including
having a family member not living at
home who uses ST, having a friend who
uses ST, playing football, trying cigarettes
in the past, and having parents that
permit ST use at home.12
Coaches play the role of teacher, mentor,
role model, friend and leader in the
community.19 They have a strong influence
over team values and norms and, as
role models, can have a marked effect
on shaping the habits of children and
young adults.20
Vol 32, No 3, June 2012 – Chronic Diseases and Injuries in Canada
150
Walsh et al. confirmed coaches’ influence on
athletes, specifically in regard to ST use.21
Their findings indicate that male high
school baseball players were three to four
times more likely to use ST if they saw
their high school coach or father using ST.21
Coaches have the ability to encourage
uptake as well as to discourage ST use. They
are key players in the effort to decrease ST
use among athletes because of their access
to players at different stages of ST use
(e.g. initiation, experimentation, regular
use).22 Of the coaches surveyed by Horn et
al., 80% agree that they play vital roles in
preventing ST use among athletes, while
86% believe they could assist youth with
ST cessation.22 Coaches report using several
strategies to address ST use among their
athletes, including advising athletes to quit,
informing athletes about the health hazards
of ST use, and informing athletes’ parents
or school principals.22
Methods
NTK partnered with the Coaches
Association of Ontario (CAO), a non-profit
coach-led organization that provides
development opportunities and educational
resources for coaches, to develop and
electronically distribute a survey to amateur
coaches in June 2009. The purpose of the
survey was (1) to assess coaches’ general
knowledge and awareness of ST use
and (2) to better understand coaches’
perceptions of their roles in influencing
and preventing ST use among their athletes.
All of the coaches surveyed were members
of amateur sport organizations. As such, it is
assumed that they were unpaid volunteers
at all levels of all sports and coached their
athletes on their own time.
Members of CAO and NTK and an epidemiologist decided on the criteria for
participating in the survey and developed
the survey through an iterative process of
identifying content and refining questions.
Eligibility criteria, including the rationale
for inclusion and exclusion of coaches,
were as follows:
• Participants were at least 18 years of
age. Anyone younger than 18 would
have required more extensive consent
procedures.
• Participants coached at least one of the
following: hockey, baseball, soccer,
basketball, football, or track and field.
CAO, the primary vehicle for initial
data collection, only included coaches
of these sports in their membership.
• Participants coached youth aged
between 9 and 18 years. A broad age
group was chosen as little research has
been conducted regarding ST among
youth athletes, and none to date has
included youth aged less than 12 years.
The surveys were distributed electronically
using SurveyMonkey, an Internet-based
survey development tool. Responses
were encrypted and housed on the
SurveyMonkey web server.
CAO members who met the eligibility
criteria were the initial target population.
The sample size estimate of 321 was
determined based on the CAO membership
size and given a margin of error of 5%
and a confidence interval of 95% (Table 1).
CAO informed their members about the
project and supplied the survey link in
their monthly e-newsletter on June 11, 2009.
Respondents were offered the opportunity
to win one of four $50 gift certificates or
various anti-tobacco promotional items as
an incentive to participate, the winners
being selected by a random draw following
the survey end date.
Two weeks after the initial e-newsletter
distribution by CAO, there were 79 completed
surveys. A reminder about the survey was
included in the July e-newsletter to CAO
members. Following this communication,
the survey completion rate remained
poor. As a result, the survey link was also
distributed to the provincial governing
bodies of the targeted sports: Ontario
Baseball Association, Ontario Basketball
Association, Ontario Football Alliance,
Ontario Hockey Federation, Ontario Soccer
Association and Athletics Ontario. CAO
formally requested that these organizations
distribute the link to their members in
their own e-newsletters. One month after
the initial communication, there were
270 completed surveys. The survey link
was then made available to NTK members
to distribute among their local sport
organizations to increase the number of
Table 1
CAO members participating in a survey of spit tobacco use among youth athletes
Sport
Coaches, n
Population in CAO
Sample size required for
subgroup analysisa
Baseball
124
94
Basketball
969
276
Football
119
92
Hockey
244
150
Soccer
353
185
Track and field
113
88
Total
1922
321
Abbreviation: CAO, Coaches Association of Ontario.
a
Sample size estimate based on a margin of error of 5% and a confidence interval of 95%.
responses. In broadening the population,
statistical significance could no longer be
computed. However, statistical significance
would not have been attained based on the
survey completion rate by CAO members
alone due to the small sample size. It was
also recognized that in changing the data
collection strategy the population might
carry an inherent geographical bias (e.g.
different health regions may advocate more
strongly than others); however, this also
was offset by the need to increase the
number of survey respondents.
coach reported only coaching athletes aged
8 years or less, n = 9, or 19 years or older,
n = 4). The remaining 261 survey responses
were analysed using descriptive statistics.
A descriptive analysis including frequencies
and cross-tabulations was completed using
SurveyMonkey and Microsoft Excel 2000.
Geography
Results
There were 344 completed surveys on
the SurveyMonkey web server. Of these,
83 were excluded because the respondents
did not meet the eligibility criteria (coached
a sport other than sports of interest, n = 70;
Coaches
Of those surveyed, the majority of coaches
(72%) were aged between 35 and 54 years,
approximately 10% were aged 55 years
plus and the remaining 20% were aged
between 18 and 24 years. In addition,
most were male (76%).
Table 2 shows the geographic distribution
of coaches. Geographic regions are
based on Tobacco Control Area Networks
(TCANs), created by the Ministry of
Health Promotion and Sport under the
Smoke-Free Ontario Strategy in order to
coordinate regional initiatives, facilitate
use of limited resources and tailor
activities to suit specific contexts.23
Table 2
Geographic distribution of surveyed coaches, Ontario, Canada
TCAN region
Proportion, %
Central East
29
Central West
34
Eastern
9
North East
5
North West
1
South West
13
Toronto
9
Unknown
2
Abbreviation: TCAN, Tobacco Control Area Networks.
151
Vol 32, No 3, June 2012 – Chronic Diseases and Injuries in Canada
Sport
The distribution of coaches by sport
was uneven. Over a quarter (29%) of
respondents indicated they primarily
coach baseball, and about the same
proportion (28%) reported that they
mainly coach soccer. Basketball coaches
(17%) and hockey coaches (13%) were
also well represented. Football and track
and field coaches each represented less
than 10% of the sample respectively.
given ST products by friends, family and/
or acquaintances. Some coaches (15%)
believe athletes obtain ST through the
“grey market” (e.g. Internet, street
sales), 6% believe ST is taken from
home without permission, 3% selected
“Other,” and 18% believe that athletes
are not obtaining ST products.
Perceived prevalence of spit tobacco use
among athletes
Frequency and duration of coaching
The majority of coaches (78%) reported
that none of the players on their teams
used ST. Approximately 9% reported that
they have either witnessed their players
using ST or they suspect that one or more
players use ST, while 5% reported that
they have witnessed players on other teams
using ST. Ten per cent of respondents
reported they do not know if any of their
players use ST.
Coaches at all levels of competition
reported coaching two or more months
out of the year. One-third (32%) reported
coaching their team for three to five years;
however, 18% had been coaching for as
little as less than one year, and 26% for
as long as six or more years.
Only those coaching athletes aged 13 years
plus reported ST use on their teams.
However, a few coaches of athletes aged
between 9 and 12 years indicated that
they suspect ST use or they had witnessed
ST use among athletes in the same age
range on other teams.
Athletes
All coaches who reported seeing one or
more of their players using ST coached
all-male teams. Only coaches of baseball,
football and hockey reported witnessing
athletes on their teams using ST.
Level of competition
Most coaches reported coaching athletes
at more than one level of competition,
with the majority coaching at the
competitive (provincial) level (59%) and/
or recreational level (43%).
Most coaches reported coaching athletes
in many age categories. Overall, the
largest proportion were aged 13 to
14 years. Just over half of the coaches
(51%) reported coaching all-male teams,
though the sample also represented
coaches of all-female teams (31%) and
of mixed teams (26%).
Self-perceived knowledge about ST
Most coaches (68%) reported knowing at
least something about ST. More of the
coaches aged 45 years plus had at least
some knowledge of ST compared to
coaches aged less than 45 years, 74%
versus 58%.
Method of obtaining ST products
Many coaches (29%) believe athletes
purchase ST products directly from vendors,
for example, convenience stores, while
the same proportion believe athletes are
Knowledge about ST products and use
The “True or False” section of the survey
questioned coaches on their knowledge
of ST products and use. The majority
of coaches (98%) indicated correctly
that ST does not enhance athletic
performance; that ST is not a safe
alternative to smoking (98%); and that
ST may cause mouth sores, gum
recession and/or tooth loss (98%). Of
the respondents, 96% indicated correctly
that ST use might contribute to high
blood pressure, heart attacks and
strokes, 52% agreed that “spit tobacco
is a growing problem among youth
practicing sports in Ontario these days,”
and 78% indicated correctly that it
is illegal to give ST to youth younger
than 19 years.
Vol 32, No 3, June 2012 – Chronic Diseases and Injuries in Canada
152
Perceived role in addressing ST use
Coaches were asked what they thought
their role was with respect to addressing ST
issues on their team. Over half indicated
they would meet with and counsel their
athletes (56%) and/or inform the athlete’s
parents (54%). Providing athletes with
written information on ST was also a
popular choice (38%). Some also reported
referring athletes to support services
(e.g. health care providers, public
health professionals, sport officials) and/
or informing the league organizer or other
community agencies (e.g. leagues, schools)
of any ST use (36% and 25%, respectively).
Strategies used to address ST use
Almost half of respondents (45%)
reported they have not done anything
to influence their athletes regarding ST
use and that they have not addressed
ST use on their teams because they do
not consider it to be an issue. Several,
parti­cularly coaches of female athletes,
said they did not see a need to address ST
use as their athletes were too young.
Approximately one-quarter (23%) indicated
that they promote and/or enforce a
tobacco-free sports policy.
Useful ST information for coaches
Coaches were asked to select the types of
information that would be most helpful
in advising youth about ST use. Almost
half (47%) indicated that information
about the health effects of ST would be
the most helpful (Table 3).
Preferred means of receiving information
on ST
Many coaches indicated they would prefer
to receive information about ST via the
CAO website (40%), in their coaching
manuals, or in newsletters and pamphlets
(Table 4). Since many of the survey
respondents were CAO members and had
likely accessed the survey through the
CAO website, the preference for this
format as a way to receive further
information may not be true for the
larger coaching population. A small
proportion of respondents indicated they
would prefer to attend workshops to
Table 3
Types of information on spit tobacco that would be useful to coaches, by TCAN region, Ontario, Canada
Type of information
deemed useful
Coaches by TCAN region, %
Central East
Central West
Eastern
North East
Different forms of ST
29
22
25
13
0
North West
South West
Toronto
All regions
29
34
26
Health effects of ST
46
46
50
40
67
50
59
47
How to encourage athletes
to stay ST-free
36
35
25
47
0
38
48
36
How the tobacco industry
targets youth
28
21
43
20
0
31
31
27
I do not require information
at this time
24
31
21
27
33
26
7
25
Abbreviations: TCAN, Tobacco Control Area Networks; ST, spit tobacco.
Table 4
Coaches’ preferred sources of information on spit tobacco, by TCAN region, Ontario, Canada
Preferred source of information
Coaches by TCAN region, %
Central East
Central West
Eastern
North East
South West
Toronto
All regions
CAO website
45
35
54
47
0
29
55
40
Health Unit website
34
21
18
13
33
24
21
24
5
3
7
7
0
2
3
4
Workshops
North West
Newsletters and pamphlets
31
37
46
7
0
38
34
34
Coaches’ manual
45
32
29
27
67
43
31
36
Abbreviations: CAO, Coaches Association of Ontario; TCAN, Tobacco Control Area Networks.
learn about the topic. In the “Other”
category, most responses indicated email
(from their sport club or the CAO) as their
preferred format to receive information.
Discussion
Our aim was to find out about coaches’
knowledge of ST use among their athletes
and their knowledge gaps with respect to
ST use.
The majority of respondents reported they
have not witnessed any ST use among
athletes. Since this study was intended
to direct health promotion activities
rather than provide a prevalence estimate,
the results of this investigation are not
comparable with previous studies of
self-reported ST use among athletes.13,17
Additional
factors
associated
with
differences in the study populations
(e.g. age, geography and culture) may
further distort comparisons with previous
ST prevalence studies. However, our
finding that only coaches of all-male
teams observed ST use among their
athletes is consistent with findings from
other studies.
Many coaches report they have not done
anything to address the issue of ST on their
teams. However, rather than this being as a
result of a lack of interest in their athletes,
most coaches do not see the need to address
ST use because they do not regard it as an
issue on their teams. It is possible that this
study demonstrates that coaches are not
well aware of ST use among their athletes.
Coaches aged 45 years plus are more
confident about their knowledge of ST
products and use compared to younger
coaches. In addition to their age, certain
characteristics of coaches and athletes are
important to consider since they relate
to findings about coaches’ knowledge and
awareness of ST. For instance, results
from this study are mostly applicable to
all-male baseball, basketball, soccer and
hockey teams.
While many coaches report that ST use
is not a problem on their teams, almost
three-quarters of the coaches said they
would like more information on the topic.
The results of the study provide insight
into techniques that coaches currently use
to address ST use among their players.
153
Strengths and limitations
The survey link was initially distributed
only to coaches who were active members
of CAO. As data collection progressed
and it became apparent that sample size
targets would not be met, the sampling
strategy was amended. The survey link
was distributed to a much broader
population and distribution was not
uniform across the province. As a result,
there may be clustering among survey
respondents, causing some responses to
be more similar than would be expected if
it were a random sample. Given the broad
distribution and not knowing who
received the survey, the results may not
be generalizable to the larger population
of coaches.
Out of 36 public health units in Ontario,
31 are members of NTK. As a result,
and because of different strategies for
promoting the survey to coaches by
member health units, all areas in Ontario
were not equally represented. Thus, the
results of this survey may not be genera­
li­zable, particularly for underrepresented
geographical areas.
Vol 32, No 3, June 2012 – Chronic Diseases and Injuries in Canada
Since the sampling strategy changed
during data collection, it is not possible
to estimate a response rate. However,
considering the response rate among CAO
members was extremely low at the outset,
electronic distribution of surveys might
not be the most effective data collection
strategy for this population. Another
limitation associated with online surveys
is the potential for bias among respondents.
For example, a large proportion of respondents selected the CAO website as their
preferred format to receive information;
however, respondents who complete online
surveys are likely to be more familiar
with the virtual environment relative to
the larger population of coaches.
Web-based survey programs have the
inherent limitation of some degree of
data insecurity. No identifying or personal
information was collected in this study
and all data was encrypted.
Despite the limitations of electronic
survey distribution, this data collection
method is efficient and inexpensive,
making it well suited for a study involving
a large sample of geographically dispersed
respondents such as this one. Another
advantage of online surveys is that there
are clear start and end dates and results
may be analyzed as soon as the data
collection period ends.
website, etc.) and hard copy (included in
coaching manuals, newsletters, pamphlets,
etc.) formats were indicated as preferred
methods to receive information about ST.
Our findings may be used to increase
coaches’ knowledge of ST use and ST
effects in order to increase their ability to
influence the tobacco use habits of their
players. Coaches should learn more about
ST products and their use, particularly as
ST use is a growing issue in sport.
By better understanding coaches’ percep­
tions of ST use and their information needs,
public health professionals can develop
initiatives that encourage coaches to take
a more active role in ST prevention. These
initiatives could include information and
tools tailored to coaches’ needs.
Since TCANs develop regional tobacco
control plans and coordinate activities
among member public health units,24 the
results from this study may be used to
direct TCAN health promotion and tobacco
prevention activities as well as those of
provincial groups, such as NTK.
Despite its limitations, this study is one of
the first in Canada to shed light on an
important and emerging issue.
Public health professionals in Ontario are
currently focusing on tobacco-free sport
and recreation (TFSR) policy as the next
step in population-based tobacco control.
Results from this study support the TFSR
movement by adding new knowledge about
coaches’ awareness of the health effects of
ST and their perception of ST use among
Ontario athletes.
Conclusion
Acknowledgements
Based on the survey results, coaches are
fairly knowledgeable about the effects of
ST products and ST use: almost 100% of
coaches responded correctly to questions
about the health effects of ST use, and about
80% of respondents correctly answered the
question about legislation associated with
ST and youth.
The authors would like to acknowledge
the Not to Kids Coalition for supporting
and funding this project. They would
also like to acknowledge the individuals
and organizations that contributed to the
project:
• The Coaches Association of Ontario
(CAO), specifically Susan Kitchen and
Jessica Taggio, for their work in
developing the survey and providing
their expertise to the challenge of
generating interest among coaches;
• The Haliburton, Kawartha, Pine Ridge
District Health Unit for their support in
conducting the analysis and writing
this report;
Most coaches are interested in receiving
information about ST, particularly the health
effects of ST use and how to prevent ST
use among athletes. Multiple formats
should be used to disseminate information
to coaches. Both electronic (CAO website,
emails from sport organizations, Health Unit
Vol 32, No 3, June 2012 – Chronic Diseases and Injuries in Canada
154
• Theresa Chambers from the Simcoe
Muskoka District Health Unit for her
contribution to survey development;
• Coach respondents for volunteering
their time and sharing their experience
through the survey.
References
1. Youthography. Findings from qualitative
studies into tobacco products and
anti-tobacco creative development. Not
to Kids Coalition; 2007. 116 p.
2. Ministry of Health and Long-Term Care.
Ontario public health standards 2008
[Internet].
Toronto
(ON):
Ministry
of Health and Long-Term Care; 2008
[cited 2010 Jul 28]. Available from: http://
www.health.gov.on.ca/english/providers
/program/pubhealth/oph_standards/ophs
/progstds/pdfs/ophs_2008.pdf
3. Sapundzhiev N, Werner JA. Nasal snuff:
historical review and health related aspects.
J Laryngol Otol. 2003;117:686-91.
4. Cooper J, Ellison JA, Walsh MM. Spit
(smokeless)-tobacco use by baseball
players entering the professional ranks.
J Athl Train. 2003;38(2):126-32.
5. U.S. Department of Health & Human
Services (HHS). The health consequences
of using smokeless tobacco: a report of the
Advisory Committee to the Surgeon General
[Internet]. Bethesda (MD): United States
Public Health Service; 1986 Apr [cited 2011
Jan 28]. NIH Publication No. 86-2874.
Available from: http://profiles.nlm.nih.gov
/ps/access/NNBBFD.pdf
6. Tomar SL, Winn DM. Chewing tobacco
use and dental caries among U.S. men.
J Am Dent Assoc. 1999;130:1601-10.
7. Colilla SA. An epidemiologic review of
smokeless tobacco health effects and
harm reduction potential. Regul Toxicol
Pharmacol. 2010;56:197-211.
8. Canadian Tobacco Use Monitoring Survey
(CTUMS) 2008. Summary of annual results
for 2008. Ottawa (ON): Health Canada;
2008 [modified 2010 Jan 22; cited 2011
Jan 28]. Available from: http://hc-sc.gc.ca
/hc-ps/tobac-tabac/research-recherche
/stat/_ctums-esutc_2008/ann_summary
-sommaire-eng.php
9. Propel Centre for Population Health
Impact. Youth Smoking Survey 2008/2009:
Smoking Profile for Ontario Youth
[Internet]. Waterloo (ON): Propel Centre
for Population Health Impact; 2009
[cited 2011 Aug 17]. Available from:
http://www.yss.uwaterloo.ca/results
/yss08_provincial_report_ON.pdf
10. Office of Applied Studies. The NSDUH
report: smokeless tobacco use, initiation,
and relationship to cigarette smoking:
2002 to 2007 [Internet]. Rockville (MD):
Substance Abuse and Mental Health
Services Administration; 2009 Feb 19
[cited 2009 Mar 5]. Available from:
h t t p : / / w w w. o a s . s a m h s a . g o v / 2 k 9
/smokelessTobacco/smokelessTobacco.htm
11. Eaton DK, Kann L, Kinchen S, Sahnklin S,
Ross J, Hawkins J, et al. Centers for Disease
Control and Prevention. Morbidity and
Mortality Weekly Report: Youth Risk
Behavior Surveillance—United States, 2009
[Internet]. MMWR 2010 [cited 2011 Jan
28];59(SS-5):1-131. Available from: http://
www.cdc.gov/mmwr/pdf/ss/ss5905.pdf
12. Goebel LJ, Crespo RD, Abraham RT,
Masho SW, Glover ED. Correlates of youth
smokeless tobacco use. Nicotine Tob Res.
2000;2:319-25.
13. Gansky SA, Ellison JA, Rudy D,
Bergert N, Letendre MA, Nelson L, et al.
Cluster-randomized controlled trial of an
athletic trainer-directed spit (smokeless)
tobacco intervention for collegiate baseball
athletes: results after 1 year. J Athl Train.
2005;40(2):76-87.
14. Castrucci BC, Gerlach KK, Kaurman NJ,
Orleans CT. Tobacco use and cessation
behavior among adolescents participating
in organized sports. Am J Health Behav.
2004;28:63-71.
17. DeHass DM. Substance use: NCAA study
of substance use of college student athletes
[Internet]. Indianapolis (IN): National
Collegiate Athletic Association; 2006
[cited 2011 Jan 28]. Available from:
http://www.ncaa.org/wps/wcm/connect
/007d81004e0dabfe9f3aff1ad6fc8b25
/2006_substance_use_report.pdf?MOD
=AJPERES&CACHEID=007d81004e0dabfe
9f3aff1ad6fc8b25
18. Green GA, Uryasz FD, Petr TA, Bray CD.
NCAA study of substance use and abuse
habits of college student-athletes. Clin J
Sport Med. 2001;11:51-6.
19. Bloom GA, Durand-Bush N, Schinke RJ,
Salmela JH. The importance of mentoring
in the development of coaches and athletes.
Int J Sport Psychol. 1998;29:267-81.
20. Parrott R, Duggan A. Using coaches as role
models of sun protection for youth:
Georgia’s “Got Youth Covered” Project. J
Appl Commun Res. 1999;27:107-19.
21. Walsh MM, Ellison J, Hilton JF, Chesney M,
Ernster VL. Spit (smokeless) tobacco use
by high school baseball athletes in
California. Tob Control. 2000;9(2);ii32-ii39.
22. Horn KA, Maniar SD, Dino GA, Gao X,
Mechstroth RL. Coaches’ attitudes toward
smokeless tobacco and intentions to
intervene with athletes. J Sch Health.
2000;70(3):89-94.
23. Ministry
of
Health
Promotion.
Comprehensive tobacco control: guidance
document [Internet]. Toronto (ON):
Ministry of Health Promotion (ON); 2010
[cited 2011 Aug 19]. Available from http://
www.mhp.gov.on.ca/en/healthy-communities
/public-health/guidance-docs
/ComprehensiveTobaccoControl.PDF
15. Melnick MJ, Miller E, Sabo DF, Farrell MP,
Barnes GM. Tobacco use among high
school athletes and nonathletes: results of
the 1997 Youth Risk Behavior Survey.
Adolescence. 2001;36:727-47.
16. Rigotti NA, Lee JE, Wechsler H. US college
students’ use of tobacco products:
results of a national survey. JAMA.
2000;284(6):699-705.
155
Vol 32, No 3, June 2012 – Chronic Diseases and Injuries in Canada
Unhealthy behaviours among Canadian adolescents: prevalence,
trends and correlates
T. M. Gadalla, PhD
This article has been peer reviewed.
Abstract
Introduction: This study examines (1) time trends in the prevalence of selected unhealthy
behaviours among adolescents aged 12 to 17 years, (2) the most commonly adopted
combinations of unhealthy behaviours, and (3) socio-economic and sociodemographic
correlates of unhealthy behaviours among adolescents.
Methods: A secondary analysis used data collected from 13 198 Canadian Community
Health Survey (CCHS) respondents in 2000/2001 and 11 050 CCHS respondents in 2007/2008.
Results: Although the proportion of adolescents consuming a healthy diet increased over
the study period, about 50% are still consuming insufficient amounts of fruit and vegetables.
In both cycles over one-third of adolescents aged 15 to 17 years reported drinking
alcohol regularly. Income level, education level, sex, and language spoken at home
were significantly associated with the odds of engaging in unhealthy behaviours among
those aged 12 to 14 years, while income level was no longer associated with the odds
of engaging in unhealthy behaviours among those aged 15 to 17 years. For both age
groups, a language other than French or English spoken in the home was associated
with a low risk of unhealthy behaviours.
Conclusion: There was a general decrease in unhealthy behaviours among younger
adolescents aged 12 to 14 years.
Keywords: adolescents’ health, alcohol, smoking, healthy eating, body weight, physical
activity
Introduction
Unhealthy behaviours in adolescence,
such as smoking, physical inactivity,
unhealthy eating (for example, consuming
less fruit and vegetables than recommended)
and alcohol drinking, contribute to chronic
diseases in adulthood.1,2,3 Young adults who
reported having their first alcoholic drink
at the age of 11 to 14 years experienced
an increased risk of alcohol-related
diseases,1 such as certain cancers and
heart and vascular disease,4 as well as an
increased risk of adverse impact on
brain development.4,5 Chronic health
conditions, in turn, have significant
adverse effects on quality of life and
productivity.3,6
Physical inactivity and unhealthy eating
lead to overweight and obesity, risk
factors for a large number of chronic
health complications such as cardiovascular
disease, hypertension, type 2 diabetes,
stroke, sleep apnea and certain types
of cancer as well as complications in
pregnancy and during surgery.7 Obesity
has also been implicated as a risk factor
for functional limitations and poor
health-related quality of life.8,9
In studies using national samples of high
school students in the United States, almost
one-quarter were overweight10,11 and 13.6%
obese.11 More than three-quarters (78.4%)
of a U.S. national sample of young adults
aged 18 to 24 years consumed less than
five fruits and vegetables per day, and
43.2% reported insufficient or no physical
activity.12 Similar rates have been observed
in Canadian youth: based on national data
of Canadian children aged 7 to 13 years,
Tremblay and Willms reported an increase
of 0.1 kg/m2 per year in body mass index
(BMI) between 1981 and 1996.13 These
authors also reported a 28.8% and 23.6%
prevalence of overweight in boys and girls,
respectively.13
Seo et al. reported that the prevalence of
smoking among high school students
increased from 21.9% in 2003 to 23.0% in
2005.11 Pisetsky et al. found similar rates
of current smoking among adolescents.14
About one-third (34.3%) of students in
grades 7 to 12 living in the Atlantic
provinces in Canada reported smoking
cigarettes.15
Seo et al. also reported a detrimental
correlation between smoking and unhealthy
eating.11 Smoking among U.S. high school
students was associated with being
overweight, and this association became
stronger between 1999 and 2005.11
Pisetsky et al. found that 22.0% of female
and 27.7% of male high school students
binge drink, that is, consume 5 or more
alcoholic drinks in one sitting at least once
a month.14 In a sample of young adults
aged 18 to 24 years living in the U.S.,
28.9% reported being current smokers
Author references:
Factor-Inwentash Faculty of Social Work, University of Toronto, Toronto, Ontario, Canada
Correspondence: Tahany M. Gadalla, Factor-Inwentash Faculty of Social Work, University of Toronto, 246 Bloor Street West, Toronto, ON M5S 1V4; Tel.: (416) 946-0623; Fax: (416) 978-7072;
Email: [email protected]
Vol 32, No 3, June 2012 – Chronic Diseases and Injuries in Canada
156
and 30.1% reported binge drinking.12 A
national survey of 4296 Canadian adolescents found that 29% of those aged 14 to
15 years reported drinking to intoxication.16
Over half (53.6%) of students in grades
7 to 12 living in the Atlantic provinces of
Canada reported using alcohol.15
Differences exist in the prevalence of
health-risk behaviours by socio-economic
status, sex and ethnicity. Wardle et al.
found that adolescents from more deprived
neighbourhoods were more likely to have
tried smoking, to eat a high fat diet and to
be overweight; these differences persisted
after controlling for ethnicity.2 On the other
hand, Tremblay and Willms found that
levels of physical activity and sedentary
behaviour partially accounted for the
association between socio-economic status
and overweight/obesity in Canadian children
aged 7 to 11 years.17 In a recent study of
Californian adolescents aged 12 to 17 years,
the prevalence of obesity increased significantly between 2001 and 2007 among
lower-income adolescents but not among
higher-income adolescents.18
A number of studies have shown that,
compared to adolescent boys, adolescent
girls are generally more fixated on their
body weight and more engaged in weight
control methods, some of which are
unhealthy, for example, cigarette smoking
and using diet pills or laxatives.10,19-21 Garry
et al. also reported a strong association
between the use of diet pills and vomiting/
laxative-use with alcohol use and cigarette
smoking in middle school students.20
Allison et al. found that daily smoking
decreased as education level increased, but
that this decrease was not associated with
income level.22 More recently, Kestila et al.
examined the relationship between childhood social circumstances and overweight
in young adults aged 18 to 29 years.23 The
researchers found that being overweight
was associated with low parental education
and irregular parental employment in
women, but not in men. Women who lived
in rural municipalities in childhood were
more likely to be obese than those from
semi-urban or urban municipalities.23
Knowing the types and frequency of
adolescents’ unhealthy behaviours as well
as the rate of their engagement is essential
for planning prevention, intervention and
outreach programs aimed at increasing the
health of Canadians. Policy makers would
also benefit from an examination of the time
trends (years) of the unhealthy behaviours
as well as the identification of groups of
youth at high risk of engaging in such
behaviours, information that is currently
lacking. This study is an attempt to fill
these gaps in knowledge. Specifically, the
aim of this research is to (1) examine
trends in the prevalence of obesity or
overweight and unhealthy behaviours such
as low physical activity, unhealthy eating
(e.g. the consumption of less fruit and
vegetables than recommended for this age
group) and alcohol drinking in a nationally
representative sample of Canadian adoles­
cents aged 12 to 17 years between 2000/2001
and 2007/2008; (2) investigate the most
common combinations of unhealthy
behaviours adopted by adolescents by
sex; and (3) identify the socio­demographic
and economic attributes associated with
engaging in unhealthy behaviours in
younger as well as older adolescents.
Methods
Interviewers obtained verbal permission
from parents/guardians to interview youth
aged between 12 to 15 years and explained
the purpose of collecting the data, the
subjects to be covered and the need to
respect a child’s right to privacy and
confidentiality. If a youth could not be
privately interviewed either in person or
over the phone, the interview was
coded as a refusal. More details about the
survey design are published elsewhere.24,25
There were 13 198 respondents aged 12 to
17 years in the 2000/2001 survey and 11 050
in the 2007/2008 survey.
Measures
Alcohol drinking was measured using two
variables: frequency of drinking and binge
drinking. Frequency of drinking was based
on the respondent’s drinking habits in
the 12 months before the survey (regular,
occasional, did not drink). A regular drinker
drank alcohol once a month or more often
during the year before the survey, and
an occasional drinker drank alcohol less
frequently. Binge drinking was defined as
consuming five or more alcohol drinks in
one sitting at least once a month.
Sample
This research used data collected in two
cycles of the Canadian Community Health
Survey (CCHS) under the authority of
the Canadian Federal Statistics Act.24 This
cross-sectional survey, conducted every two
years, uses a multistage stratified cluster
probability sampling in which a dwelling is
the final sampling unit. The survey sample
was stratified by province/territory and
urban versus rural regions within each
province/territory. Sampling was designed to
represent 98% of the Canadian population
aged 12 years or more who lived in private
dwellings in the ten provinces and the three
territories. In both cycles, approximately half
of the respondents were randomly selected
to be interviewed face-to-face using
the computer-assisted personal interviewing
method, and half were interviewed
by telephone using the computer-assisted
telephone
interviewing
method.24,25
Introductory letters mailed to selected
respondents assured them of the confiden­
tiality laws governing the release and/or
publication of collected data and of
the voluntary nature of participation.
157
Cigarette smoking was measured using one
variable, frequency of smoking. Respondents
were asked: “At the present time, do you
smoke cigarettes daily, occasionally or
not at all?” Responses were categorized as
“daily smoker,” “occasional smoker” and
“non-smoker.”
BMI classification was based on the age- and
sex-specific BMI cut-off points as defined by
Cole et al. for 12 to 18 year olds.26 These, in
turn, were based on pooled international
data from Brazil, Great Britain, Hong Kong,
Netherlands, Singapore and the U.S.26 The
authors used heights and weights of over
192 000 individuals to develop age- and
sex-specific cut-off points for BMI categories
for 12- to 18-year-olds. Cut-off points were
specific for each sex and year of age, and
ranged between 21.22 kg/m2 and 30.0 kg/m2
for boys and from 21.68 kg/m2 and
30.0 kg/m2 for girls. This variable classifies
adolescents (except girls aged 15 to 17 years
who were either pregnant or did not answer
whether they were pregnant or not) as
“obese,” “overweight” or “neither obese
nor overweight.”
Vol 32, No 3, June 2012 – Chronic Diseases and Injuries in Canada
Other variables of health used in the
analysis included daily consumption of fruit
and vegetables (less than five servings versus
five or more servings) as a marker for
an unhealthy diet, and perceived general
health (excellent/very good, good and
fair/poor). Data on self-perceived stress were
collected only from respondents 15 years or
more in response to the following question:
“Thinking about the amount of stress in
your life, would you say that most days
are not at all stressful / not very stressful /
a bit stressful / quite a bit stressful /
extremely stressful?”
Physical activity was measured using two
variables, level of physical activity and
time spent in sedentary activities. Level of
physical activity categorizes respondents
as being “active,” for a total energy
expenditure (EE) in their transportation and
leisure activities of 3.0 kcal/kg/day or
greater, “moderately active” for an EE of
1.5 kcal/kg/day or greater, but less than
3.0 kcal/kg/day, or “inactive” for an EE of
less than 1.5 kcal/kg/day. Respondents’
energy expenditure was calculated using
the frequency and time per session of
each physical activity and its metabolic
energy cost (MET). For example, an activity
of 4 METs requires 4 times the amount of
energy as compared to when the body is
at rest. The amount of metabolic energy
used in a 15-minute session of each leisure
activity (MET) was calculated and multiplied
by the number of sessions to get the total
energy expenditure (EE) corresponding to
each activity. Survey respondents were not
asked to specify the intensity level of
their activities; therefore, the MET values
calculated here correspond to the low
intensity value of each activity. This approach
was adopted because people tend to
overestimate the intensity, frequency and
duration of their activities.24
The total number of hours spent in
sedentary activities in a typical week in
the three months before the survey was
also estimated. Sedentary activities
included using a computer (including
playing computer games and surfing the
Internet), playing video games, watching
television or videos and reading. The time
spent at school or work was not included.
Respondents’ sedentary activities were
then classified into four categories: less
than 15 hours/week, 15 to 29 hours/week,
30 to 44 hours/week and 45 or more
hours/week.
Sociodemographic characteristics used in
this research included sex, age group
(12–14 years and 15–17 years), language
spoken at home (English/French versus
other), place of birth (Canada versus
other), highest level of education in the
household (less than secondary school
degree, secondary school graduate, some
post-secondary education, post-secondary
graduate), and income level. However,
data on income level were reported dif­
fe­rently in the two cycles of CCHS. In the
2000/2001 cycle, income adequacy was
grouped into four levels, while in the
2007/2008 cycle it was grouped into
three.24 Consequently, a direct comparison
of this variable could not be carried out.
Data analyses
Age-specific rates of engagement in health
risk behaviours for the years 2000/2001 and
2007/2008 were calculated and compared,
and used chi-square (χ2) tests to compare
the prevalence of unhealthy behaviours in
the two cycles. χ2 tests were also used to
assess the bivariate relationships between
unhealthy behaviours and various socio­
de­mographic and economic attributes.
Sampling weights were rescaled and used
in all analyses. Rescaling the weights to
have an average of one has two advantages.
First, it takes into account the unequal
probabilities of selection of survey
respondents and adjusts the sample
results to the demographic composition
of the Canadian population so that the
results represent the population of Canada
and not just the sample itself. Second, it
keeps the total sample size unchanged to
guard against inflating the sample size for
hypothesis testing.24,25
Results
Table 1 shows the descriptive statistics of
all the variables used in the analysis. The
most notable change over the study period
was a 9 percentile point increase in
the proportion of adolescents consuming
five or more fruits/vegetables per day
(12–14 years: χ2 = 729.33, p < .001;
15–17 years: χ2 = 65.90, p < .001). There
was also a marked reduction in the
prevalence of cigarette smoking for both age
groups (12–14 years: χ2 = 96.79, p < .001;
15–17 years: χ2 = 120.53, p < .001).
Unhealthy behaviours with more than two
levels were recoded as yes/no variables. For
example, “physically inactive” was coded as
yes while “active” and “moderately active”
were coded as no, “daily” and “occasional”
cigarette smoking were coded as yes while
“not at all” was coded as no, “regular” and
“occasional” alcohol drinking were coded
as yes and “non-drinker” as no. Data were
then aggregated to show the most common
combinations of unhealthy behaviours
adopted by male and female adolescents
separately.
Although the data showed slight impro­
vement in the proportion of physically
active adolescents, the number of hours
spent in sedentary activities showed a bigger
increase; the proportion of adolescents who
spent more than 45 hours/week in sedentary
activities increased from 6.1% to 8.3%
among younger adolescents (12–14 years:
χ2 = 42.69, p < .001) and from 3.8% to
9.0% among older adolescents (15–17 years:
χ2 = 170.00, p < .001). There was also a
significant improvement in BMI distribution
for the younger adolescents (12–14 years:
χ2 = 23.43, p < .001), but not for the older
ones. Similarly, the prevalence of binge
drinking improved significantly for the
younger group (12–14 years: χ2 = 13.30,
p < .001), but not for the older one.
Logistic regression models were used to
examine the effects of sociodemographic
and economic attributes associated with
engaging in unhealthy behaviours in
younger as well as older adolescents. Only
those variables that were significantly
associated with engagement in unhealthy
behaviours in the bivariate tests were
included in the multivariate analysis.
Table 2 shows the number of unhealthy
behaviours adopted by adolescents and
their distribution based on age and sex.
The proportion of younger adolescents
(12–14 years) who had not adopted
any unhealthy behaviours increased
considerably (males: 25.2% to 36.4%;
females: 26.7% to 38.5%) between
2000/2001 and 2007/2008. Among older
Vol 32, No 3, June 2012 – Chronic Diseases and Injuries in Canada
158
Table 1
Characteristics and descriptive statistics of adolescent respondents (aged 12–17 years)
in the 2000/2001 and 2007/2008 Canadian Community Health Survey samples
CCHS respondents, n (%)
12–14 years
15–17 years
2000/2001
(n = 6251)
2007/2008
(n = 5574)
2000/2001
(n = 6947)
2007/2008
(n = 5476)
2993 (47.9)
2664 (48.7)
3459 (49.8)
2705 (49.4)
Highest 30%
–
1684 (37.0)
–
1267 (32.1)
Middle 40%
–
1839 (40.4)
–
1741 (44.1)
Lowest 30%
–
1034 (22.6)
–
943 (23.0)
English/French
–
5057 (90.7)
–
2914 (89.7)
Other
–
517 (9.3)
–
561 (10.3)
5551 (88.8)
4913 (88.9)
6058 (87.2)
4744 (87.9)
701 (11.2)
611 (11.1)
890 (12.8)
655 (12.1)
Less than secondary school
508 (8.3)
188 (4.3)
533 (7.9)
186 (4.2)
Secondary school graduate
898 (14.7)
478 (10.9)
986 (14.6)
576 (12.9)
Some post-secondary
449 (7.3)
248 (5.6)
621 (9.2)
305 (6.8)
4264 (69.7)
3487 (79.2)
4627 (68.4)
3410 (76.2)
Excellent/very good
4546 (72.7)
3902 (70.1)
4877 (70.2)
3749 (68.5)
Good
1461 (23.4)
1478 (26.5)
1690 (24.3)
1438 (26.3)
242 (3.9)
191 (3.4)
378 (5.4)
289 (5.3)
None
–
–
–
2261 (41.4)
A bit
–
–
–
2404 (44.0)
A lot
–
–
–
802 (14.6)
193 (4.2)
295 (4.3)
229 (4.6)
Female
Incomea
Language spoken at home
Country of birth
Canada
Other
Education within the household
Post-secondary graduate
Self-perceived health
Fair/poor
Self-perceived stress
b
BMI, kg/m
2
310 (5.2)**
Obesec
Overweight
1011 (17.0)
643 (14.1)
981 (14.4)
758 (15.1)
Neither
4636 (77.8)
3724 (81.7)
5528 (81.2)
4028 (80.3)
<5
3591 (58.5)**
2486 (50.1)
4050 (59.1)**
2665 (51.6)
≥5
2547 (41.5)
4608 (49.9)
2808 (40.9)
2497 (49.4)
Active
2595 (49.4)*
2724 (51.7)
2699 (44.0)**
2583 (48.5)
Moderately active
1347 (25.6)
1202 (22.8)
1461 (23.8)
1150 (21.6)
Inactive
1310 (24.9)
1346 (25.5)
1976 (32.2)
1597 (30.0)
1345 (26.0)
1404 (35.7)**
1414 (26.7)
d
Daily consumption of fruit/vegetables, servings
Physical activity
Sedentary activities, hours/week
< 15
973 (30.1)**
15–29
1481 (45.8)
2256 (43.6)
1761 (44.8)
2358 (44.6)
30–44
583 (18.0)
1145 (22.1)
615 (15.6)
1045 (19.8)
≥ 45
198 (6.1)
427 (8.3)
149 (3.8)
474 (9.0)
Continued on the following page
159
Vol 32, No 3, June 2012 – Chronic Diseases and Injuries in Canada
Table 1 (continued)
Characteristics and descriptive statistics of adolescent respondents (aged 12–17 years) in the 2000/2001
and 2007/2008 Canadian Community Health Survey samples
CCHS respondents, n (%)
12–14 years
15–17 years
2000/2001
(n = 6251)
2007/2008
(n = 5574)
185 (3.0)**
51 (0.9)
2000/2001
(n = 6947)
2007/2008
(n = 5476)
Cigarette smoking
Daily
1005 (14.5)**
450 (8.2)
Occasional
190 (3.0)
82 (1.5)
435 (6.3)
307 (5.6)
Non-smoker
5877 (94.0)
5430 (97.6)
5508 (79.3)
4703 (86.1)
335 (5.4)**
219 (3.9)
2288 (33.2)*
1859 (34.3)
Alcohol drinking
Regular
Occasional
1069 (17.2)
747 (13.5)
1987 (28.9)
1410 (26.0)
Non-drinker
3809 (77.4)
4581 (82.6)
2609 (37.9)
2155 (39.7)
Binge drinking
Yes
68 (1.1)**
27 (0.05)
920 (13.2)
683 (12.6)
No
6184 (98.9)
5521 (99.5)
6028 (86.8)
4723 (86.4)
Abbreviations: BMI, body mass index; CCHS, Canadian Community Health Survey.
a
Income level was grouped differently in the 2000/2001 CCHS survey compared to the 2007/2008 survey.
b
Only asked of respondents ≥ 15 years in 2007/2008.
c
BMI 26.02 kg/m2 for males aged 12–14 years, > 30.0 kg/m2 for males aged 15–17 years, 26.67 kg/m2 for females aged 12–14 years and > 30.00 kg/m2 for females aged 15–17 years.
d
BMI 21.22 kg/m2 for males aged 12–14 years, 30.0 kg/m2 for males aged 15–17 years, 21.68 kg/m2 for females aged 12–14 years and 30.0 kg/m2 for females aged 15–17 years.
*
p < .01 for the difference in prevalence over the study period (χ2 tests).
**
p < .01 for the difference in prevalence over the study period (χ2 tests).
Table 2
Canadian Community Health Survey adolescent respondents (aged 12–17 years)
engaging in unhealthy behaviours by age group and sex, 2000/2001 and 2007/2008
Age group,
years
12–14
CCHS survey
respondents, n (%)
Number of unhealthy behaviours
0
1
2
3
≥4
Total
2000/2001*
Male
820 (25.2)
1522 (46.7)
738 (22.6)
163 (5.0)
15 (0.5)
3258
Female
800 (26.7)
1323 (44.2)
710 (23.7)
129 (4.3)
32 (1.1)
2993
Male
1041 (36.4)
1136 (39.7)
592 (20.7)
85 (3.0)
7 (0.2)
2862
Female
1045 (38.5)
1076 (39.7)
508 (18.7)
70 (2.6)
14 (0.5)
2714
2007/2008
15–17
2000/2001*
Male
546 (15.7)
1139 (32.7)
999 (28.6)
498 (14.3)
307 (8.8)
3488
Female
631 (18.3)
1152 (33.3)
972 (28.1)
416 (12.0)
288 (8.4)
3459
Male
577 (20.8)
899 (32.5)
755 (27.3)
367 (13.3)
170 (6.1)
2768
Female
548 (20.3)
910 (33.6)
829 (30.6)
275 (10.2)
145 (5.3)
2707
2007/2008**
Abbreviation: CCHS, Canadian Community Health Survey.
Note: All data are weighted by the rescaled weights. The average of the rescaled weights being 1, many of the data would be fractions; therefore, the totals in different analyses may not be exactly
equal due to approximation.
* p < .01 for the difference between male and female adolescents (χ2 tests).
**p = .001 for the difference between male and female adolescents (χ2 tests).
Vol 32, No 3, June 2012 – Chronic Diseases and Injuries in Canada
160
adolescents (15–17 years), this increase
was more modest (males: 15.7% to 20.8%;
females: 18.3% to 20.3%).
of fruit/vegetables and regular alcohol
drinking (13.7%). Eight percent of male
adolescents and 5.7% of female adolescents
with two unhealthy behaviours combined
regular alcohol drinking with binge drinking.
Only 1.8% of males and 1.4% of females
combined regular alcohol dinking with
daily cigarette smoking (Table 3).
Consuming less than five servings of fruit
and vegetables was the most common
unhealthy behaviour among both male
and female adolescents who had
adopted one such behaviour (males: 57.3%;
females: 47.9%). Table 3 shows other
unhealthy behaviours by frequency and sex.
For male adolescents, the second most
common unhealthy attributes were being
overweight or obese (15.6%) and physically inactive (15.0%) followed by regular
alcohol drinking (10.5%) and daily smoking
(1.3%). Of female adolescents, 30.0% were
inactive, 11.6% drank alcohol regularly,
9.0% were overweight or obese and 1.6%
smoked daily.
Results of the bivariate χ2 tests show
that sex, income level, education level and
language spoken at home were associated
with engaging in unhealthy behaviours for
younger adolescents (12–14 years) while
place of birth was not. For the older group
(15–17 years), only sex, education level and
language spoken at home were significantly
associated with engaging in unhealthy
behaviours while self-perceived stress level,
place of birth and income were not.
The most common combination of
unhealthy behaviours among adolescents
with two such behaviours was insufficient
consumption of fruit/vegetables and
physical inactivity (35.3% in males and
51.1% in females) (Table 3). The second
most common combination among male
adolescents was insufficient consumption
of fruit/vegetables and overweight/
obesity (27.8%), while among female
adolescents it was insufficient consumption
Results of the logistic regression analysis
indicate that education level, sex and
language spoken at home were significantly
associated with the probability of engaging
in at least one unhealthy behaviour among
adolescents (Table 4). These probabilities
were slightly higher for boys aged 12 to
14 years compared with their female
counterparts (odds ratio [OR] = 1.18, 95%
confidence interval [CI] = 1.03–1.34),
but lower for boys aged 15 to 17 years
compared to females in that age range
(OR = 0.83, 95% CI = 0.70–0.97).
Respondents speaking languages other than
English/French at home had a lower risk
of engaging in unhealthy behaviours
(12–14 years: OR = 0.66, 95% CI =
0.51–0.85; 15–17 years: OR = 0.60,
95% CI = 0.46–0.80). Adolescents in
households where the highest level of
education was a high school certificate
had almost twice the risk of engaging in
unhealthy behaviours compared with those
in households with a post-secondary
degree (12–14 years: OR = 1.93, 95%
CI = 1.51–2.46; 15–17 years: OR = 1.46,
95% CI = 1.11–1.92).
Discussion
In this study, I examined prevalence
of smoking, obesity and overweight,
physical inactivity, unhealthy eating and
alcohol drinking in a nationally representative sample of Canadian adolescents
in 2000/2001 and 2007/2008. This study also
investigated trends of engaging in these
behaviours for younger (12–14 years) and
older (15–17 years) adolescents and for
male and female adolescents separately, as
well as the types of unhealthy behaviours
adopted by adolescents and the most
common combinations of such behaviours.
Table 3
Types of unhealthy behaviours adopted by Canadian Community Health Survey adolescent respondents by sex, 2007/2008
Number and type/combination of unhealthy behaviours
One
Females
(n = 1986)
1171 (57.3)
951 (47.9)
Overweight/obese
318 (15.6)
178 (9.0)
Physically inactive
305 (15.0)
595 (30.0)
Regular alcohol drinking
214 (10.5)
231 (11.6)
26 (1.3)
31 (1.6)
Males
(n = 1347)
Females
(n = 1337)
Eats less than 5 servings of fruit/vegetables + physically inactive
467 (34.7)
683 (51.1)
Eats less than 5 servings of fruit/vegetables + overweight/obese
374 (27.8)
156 (11.7)
Eats less than 5 servings of fruit/vegetables + regular alcohol drinking
176 (13.1)
183 (13.7)
Regular alcohol drinking + binge drinking
Eats less than 5 servings of fruit/vegetables per day
Daily smoking
Two
CCHS respondents, n (%)
Males
(n = 2035)
111 (8.2)
76 (5.7)
Regular alcohol drinking + overweight/obese
73 (5.4)
37 (2.8)
Regular alcohol drinking + physically inactive
34 (2.5)
76 (5.7)
Regular alcohol drinking + daily smoking
24 (1.8)
18 (1.4)
Eats less than 5 servings of fruit/vegetables + daily smoking
10 (0.7)
26 (1.9)
Abbreviation: CCHS, Canadian Community Health Survey.
161
Vol 32, No 3, June 2012 – Chronic Diseases and Injuries in Canada
Table 4
Results of logistic regression analysis of sociodemographic and economic correlates of
adopting unhealthy behaviours by adolescents aged 12–17 years, Canada, 2007/2008
OR
(95% CI)
p
Lowest 30%
1.20 (1.00–1.44)
.053
Middle 40%
1.23 (1.03–1.45)
.017
Highest 30%
1.00 (ref)
–
Age group,
years
12–14
Variable
Income distribution
Level of education in household
Less than secondary school
1.47 (1.04–2.08)
.027
Secondary school graduate
1.93 (1.51–2.46)
< .001
Some post-secondary
1.27 (0.96–1.70)
.100
1.00 (ref)
–
1.00 (ref)
–
Post-secondary graduate
Language spoken at home
English/French
Other
0.66 (0.51–0.85)
< .001
Male
1.18 (1.03–1.34)
.017
1.00 (ref)
–
Less than secondary school
1.53 (0.94–2.49)
.087
Secondary school graduate
1.46 (1.11–1.92)
.006
Some post-secondary
1.62 (1.10–2.40)
.015
1.00 (ref)
–
1.00 (ref)
–
Sex
Female
15–17
Over the study period, around one-third of
the 15- to 17-year-olds reported drinking
alcohol regularly during the previous
year, a proportion similar to that reported
elsewhere.12
Level of education within the household
Post-secondary graduate
Language spoken at home
English/French
Other
0.60 (0.46–0.80)
Male
0.83 (0.70–97)
< .001
Sex
Female
.022
1.00 (ref)
–
Abbreviations: CI, confidence interval; OR, odds ratio; ref, reference.
Sociodemographic and economic correlates
of engaging in unhealthy behaviours
were also examined.
A limitation of this study arises from the
fact that all the measures used were based
on self-reported data, which is subject
to bias.
While younger male adolescents had a
slightly higher probability of engaging in
unhealthy behaviours, older ones had a
slightly lower probability compared with
their female counterparts—a somewhat
puzzling result that suggests the need
for further research. This result under­
scores the importance of examining
adolescents’ behaviours separately for sex
and for age.
In spite of the increase in the proportion
of adolescents consuming sufficient
amounts of fruit and vegetables daily, in
2007/2008 approximately half were still
consuming less than the recommended
amount. This proportion, however, is much
lower than the 78% of U.S. youth reported
consuming less than the recommended
amount of fruit and vegetables.12 While
the proportion of obese or overweight
adolescents aged 12 to 14 years decreased
from 22.2% to 18.3% over the study period,
the corresponding proportion of those
aged 15 to 17 years remained almost the
same at 19.7%. Although these rates are
lower than those observed in the 1990s,13
they are still far from ideal and hence
require the attention of health advocates
and policy makers.
Vol 32, No 3, June 2012 – Chronic Diseases and Injuries in Canada
162
The logistic regression results indicated that
language spoken at home and parents’
education level are the most important
demographic correlates of unhealthy
behaviours among adolescents. Adolescents
who speak languages other than English/
French at home had a much lower
probability of engaging in unhealthy
behaviours. Lower levels of parental
education were associated with a higher
probability of unhealthy behaviours among
younger as well as older adolescents,
evidence supported by other research
findings.23 Low income was associated
with higher odds of unhealthy behaviours
among younger adolescents, but not among
older ones.
Conclusion
This study was based on secondary
data analysis of nationally representative
samples of adolescents aged 12 to 17 years
that were collected in the 2000/2001 and
2007/2008 cycles of the CCHS. The study
indicated a general decrease in unhealthy
behaviours among younger adolescents
aged 12 to 14 years. More outreach and
health educational programs should target
older adolescents with a special focus
on combating the detrimental effects of
unhealthy eating, physical inactivity and
alcohol drinking.
References
1. DeWit DJ, Adlaf EM, Offord DR, Ogborne AC.
Age at first alcohol use: a risk factor for
the development of alcohol disorders. Am J
Psychiatry. 2000;157:745-50.
2. Wardle J, Jarvis MJ, Steggles N, Sutton S,
Williamson S, Farrimond H, et al.
Socioeconomic disparities in cancer-risk
behaviors in adolescence: Baseline results
from the Health and Behaviour in
Teenagers Study (HABITS). Prev Med.
2003;36(6):721-30.
3. Sturm R. The effects of obesity, smoking,
and drinking on medical problems and
costs. Health Aff. 2002;21(2):245-53.
4. Windle M, Windle RC. Alcohol and other
substance use and abuse. In: Adams GR,
Berzonsky MD, editors. Blackwell handbook
of adolescence. Malden (MA): Blackwell;
2003. p. 450-69.
15. Poulin C, Van Til L, Wilbur B, Clarke B,
MacDonald CA, Barcelo A, et al. Alcohol and
other drug use among adolescent students
in the Atlantic provinces. Can J Public
Health. 1999;90:27-9.
5. Lemstra M, Bennett NR, Neudorf C,
Kunst A, Nannapaneni U, Warren LM, et
al. A meta-analysis of marijuana and
alcohol use by socio-economic status in
adolescents aged 10-15 years. Can J Public
Health. 2008;99(3):172-7.
16. Hotton T, Haans D. Alcohol and drug
use in early adolescence. Health Rep.
2004;15(3):9-19.
6. Gadalla TM. Disability associated with
comorbid anxiety disorders in women with
chronic physical illness in Ontario, Canada.
Women Health. 2008;48(1):1-20.
7. Li Z, Bowerman S, Heber D. Health
ramifications of the obesity epidemic.
Surg Clin North Am. 2005;85:681-701.
8. Gadalla TM. Association of obesity with
mood and anxiety disorders in the adult
general population. Chronic Dis Can.
2009;30(1):29-36.
9. Larsson U, Karlsson J, Sullivan M. Impact
of overweight and obesity on health-related
quality of life – a Swedish population
study. Int J Obesity Relat Metab Disord.
2002;26:417-24.
10. Lowry R, Galuska DA, Fulton JE, Wechsler H,
Kann L. Weight management goals and
practices among U.S. high school
students: associations with physical
activity, diet, and smoking. J Adolesc
Health. 2002;31(2):133-44.
11. Seo DC, Jiang N, Kolbe LJ. Association of
smoking with body weight in US high
school students, 1999-2005. Am J Health
Behav. 2009;33(2):202-12.
12. McCracken M, Jiles R, Blanck HM.
Health behaviors of the young adult U.S.
population:
behavioral
risk
factor
surveillance system, 2003. Prev Chronic
Dis. 2007;4(2):A25.
13. Tremblay MS, Willms JD. Secular trends in
the body mass index of Canadian children.
CMAJ. 2000;163(11):1429-33.
14. Pisetsky EM, Chao YM, Dierker LC, May
AM, Striegel-Moore RH. Disordered eating
and substance use in high school students:
Results from the Youth Risk Behavior
Surveillance System. Int J Eat Disord.
2008;41(5):464-70.
26. Cole TJ, Bellizzi MC, Flegal KM, Dietz WH.
Establishing a standard definition for
child overweight and obesity worldwide:
international survey. BMJ. 2000;320:1240-3.
17. Tremblay MS, Willms JD. Is the Canadian
childhood obesity epidemic related to
physical inactivity? Int J Obesity Relat
Metab Disord. 2003;27:1100-5.
18. Babey SH, Hastert TA, Wolstein J, Diamant
AL. Income disparities in obesity trends
among California adolescents. Am J Public
Health. 2010;100(11):2149-55.
19. Chao YM, Pisetsky EM, Dierker LC, Dohm F,
Rosselli F, May AM, et al. Ethnic differences
in weight control practices among U.S.
adolescents from 1995 to 2005. Int J Eat
Disord. 2008;41(2):124-33.
20. Garry JP, Morrissey SL, Whetstone LM.
Substance use and weight loss tactics
among middle school youth. Int J Eat
Disord. 2003;33(1):55-63.
21. Ho CH, Kingree JB, Thompson MP.
Associations between juvenile delinquency
and weight-related variables: analyses from
a national sample of high school students.
Int J Eat Disord. 2006:39(6):477-83.
22. Allison KR, Adlaf EM, Ialomiteanu A, Rehm
J. Predictors of health risk behaviours
among young adults: analysis of the
National Population Health Survey. Can J
Public Health. 1999;90(2):85-89.
23. Kestila L, Rahkonen O, Martelin T,
Lahti-Koski M, Koskinen S. Do childhood
social circumstances affect overweight and
obesity in early adulthood? Scand J Public
Health. 2009;37:206-19.
24. 2008 Canadian Community Health Survey,
cycle 4.1, 2007. Public Use Microdata
Documentation. Ottawa (ON): Statistics
Canada; 2008.
25. 2002 Canadian Community Health Survey,
cycle 1.1, 2000/2001 [Internet]. Public Use
Microdata Documentation. Ottawa (ON):
Statistics Canada, 2003 [cited 2003 Jan 28].
163
Vol 32, No 3, June 2012 – Chronic Diseases and Injuries in Canada
Longitudinal trends in mental health among ethnic groups
in Canada
P. Pahwa, PhD (1,2); C. P. Karunanayake, PhD (2); J. McCrosky, MSc (1); L. Thorpe, MD, PhD (1)
This article has been peer reviewed.
Abstract
Introduction: Immigration continues to transform the ethnic composition of the Canadian
population. We investigated whether longitudinal trends in mental distress vary between
seven cultural and ethnic groups and whether mental distress within the same ethnic group
varies by demographic (immigrant status, sex, age, marital status, place and length of
residence), socio-economic (education, income), social support and lifestyle factors.
Method: The study population consisted of 14 713 respondents 15 years and older from
the first six cycles of the National Population Health Survey (NPHS); 20% reported
themselves to be immigrant at Cycle 1, in 1994/1995. The logistic regression model was
fitted by modifying a multivariate quasi-likelihood approach, and robust variance estimates
were obtained by using balanced repeated replication techniques.
Results: Based on the multivariable model and self-reported data, we observed that female
respondents were more likely to report moderate/high mental distress than male
respondents; younger respondents more than older respondents; single respondents
more than those in a relationship; urban-dwellers more than rural-dwellers; less educated
respondents more than more educated respondents; current and former smokers more
than non-smokers; and those living in a smoking household more than those living in
non-smoking households. The relationship between ethnicity and mental distress was
modified by immigrant status, sex, social involvement score and education. Confirming
other research, we found an inverted U-shaped relationship between length of stay and
mental distress: those who had lived in Canada for less than 2 years were less likely to
report moderate/high mental distress, while those who had lived in Canada for 2 to
20 years were significantly more likely to report moderate/high mental distress than
those who had lived in Canada for more than 20 years.
Conclusion: There is a need to develop ethnicity-specific mental health programs targeting
those with low education attainment and low social involvement. Policies and programs
should also target women, the younger age group (15–24 years) and low-income adequacy
groups.
Keywords: mental distress, ethnicity, National Population Health Survey, generalized
estimating equations, balanced repeated replication, missing data, pattern mixture models
Introduction
According to the World Health Organization,
more than 25% of people worldwide
will experience mental illness at some
time during their lives.1 In Canada,
approximately 30% of disability claims
are based on mental illnesses, costing
between $15 billion and $33 billion
dollars annually.2 As with physical health,
mental health is an interplay between
demographic,
lifestyle,
social
and
environmental factors, among others.
Some examples of these are age, sex,
marital status, personal smoking habits,
exposure to second-hand smoke, socioeconomic status and social involvement.3-8
Immigrants may be at particular risk of
developing mental illnesses such as
depression, and the risk may vary with
the length of time since their arrival
in Canada.7 Variation between ethnic
groups is also likely; therefore it is
important to explore associations
between the ethnicity of immigrants and
mental health.
Despite its importance and relevance for
policy making, the literature on the issue
of ethnicity and mental health is very
limited.3 Including ethnicity in health
research would improve targeting of
resources to more vulnerable groups.
Canadian immigrants are heterogeneous
with respect to many factors such as
country of origin, age group, education,
income and ethnicity.9 These factors need
to be accounted for when analyzing
health data because they are likely to
affect the physical and mental health of
individuals.
The objectives of this report were to
investigate (1) how longitudinal trends in
mental distress, used as a measure of
mental health, vary between ethnic groups
in Canada; (2) whether these trends vary
between immigrant and Canadian-born
members of different ethnic groups; and
(3) how other variables influence the
relationship between mental health and
Author references:
1. Department of Community Health and Epidemiology, College of Medicine, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
2. Canadian Centre for Health and Safety in Agriculture, College of Medicine, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
Correspondence: Punam Pahwa, Canadian Centre for Health and Safety in Agriculture, University of Saskatchewan, Royal University Hospital, 103 Hospital Drive, Saskatoon, SK S7N 0W8;
Tel.: (306) 966-8300; Fax: (306) 966-8799; Email: [email protected]
Vol 32, No 3, June 2012 – Chronic Diseases and Injuries in Canada
164
ethnicity, in particular, socio-economic,
social support and lifestyle status, and
demographic factors.
Methods
Study design and study population
Statistics Canada has used complex,
multi-stage sampling designs to collect data
over time from cohorts of individuals.10
One such survey, the Canadian National
Population Health Survey (NPHS), includes
a set of questions designed to investigate
the mental health of respondents.10 Details
of the NPHS and multi-stage sampling
design can be found elsewhere.10-12
Our study population consisted of the
14 713 respondents aged 15 years and
older who were surveyed over the first
six cycles of the NPHS, from 1994/1995
to 2004/2005.
Variables
Dependent variable. Mental distress,
used as a measure of mental health, was
computed using a six-item “distress
scale” that assessed feelings of sadness,
nervousness, restlessness, hopelessness and
worthlessness within the preceding month.
Also assessed was the frequency with which
an individual felt that everything was
an effort. The distress scale was based on
the work of Kessler et al.13 and was
derived from the Composite International
Diagnostic Interview*. Scores on the
distress scale ranged from zero (no
distress) to 24 (highly distressed). The
derived distress scale was highly skewed
and was therefore categorized into a
dichotomous mental distress variable
(i.e. no/low [0–5 on the distress scale]
and moderate/high [6–24 on the distress
scale]), as suggested by a geriatric
psychiatrist (Personal communication,
27 October, 2010) and based on the
available literature.14,15
Independent variables. The main risk
factor of interest was ethnicity, which we
determined from self-reported ethnicity in
response to the NPHS question, “To which
ethnic or cultural group(s) did your/
his/her ancestors belong?” The possible
responses were coded10 and categorized
into seven groups according to ethnic or
cultural ancestry: British, Eastern European,
Western European, Chinese, South Asian,
Black and Other.
Other independent variables of interest
were demographic (immigrant status, sex,
age, marital status, place of residence and
length of residence), location of residence
(rural vs. urban†)16, geographical area
of residence (one of the 10 provinces),
socio-economic status (education, income),
social support status and lifestyle status.
Income adequacy was derived from
various combinations of total household
income and the number of people living
in the household, and was categorized
into three groups, low, middle and high.17
The social support variable consisted of a
social involvement score (SIS)16 based on
questions on the respondents’ frequency
of participation in associational activities
and of attending religious services. Lifestyle
variables consisted of a respondent’s
personal smoking history and household
smoking status. The general health variable
consisted of a self-perceived general health
status. Five dummy variables for ‘Cycle’
were used to study the effect of time on
mental distress.
Statistical methods
We used SAS (SAS Institute Inc., version 9.2,
2007) procedure PROC GENMOD to fit
the multivariable logistic regression model
and to obtain the predictive model for
mental distress.18 The longitudinal weight
variable computed by Statistics Canada
methodologists was used in the WEIGHT
statement of SAS syntax to account for
unequal probability of selection. Based
on the goodness-of-fit techniques, we
determined within-subject correlation
structure.19 We obtained the estimates of
regression coefficients for the logistic
regression model by modifying the
multivariate quasi-likelihood approach for
complex survey designs using the weight
variable.20
The robust variance estimation in GENMOD
based on generalized estimation equations
(GEE) approach accounts only for the
within-subject dependencies due to the
repeated measurements over time,20,21
and does not account for design effects
(stratification, clustering and unequal
probability of selection). In order to allow
for robust variance estimation without
compromising respondents’ privacy, Statistics
Canada provides pre-calculated bootstrap
weights with the survey. A resampling
technique known as balanced repeated
replication (BRR) is used for robust
variance estimation. We used the BRR
features of STATA (StataCorp LP, version 11,
2009), which for our purposes with precal­culated bootstrap weights is equivalent
to the bootstrapping method.22 A classical
multivariable logistic regression model
based on the GEE approach was extended
by including a categorical dropout variable
to incorporate the missing observations.
The categorical dropout variable included
four categories numbered consecutively
from one to four: one missing value for
the response variable; two or more missing
values for the response variable; deceased
during study duration; and no missing value
or completers (subjects who participated
in all the six cycles). Models such as these
that incorporate a missing pattern are called
pattern-mixture models.23 If a value was
missing for any covariate for any particular
cycle, then the entire observation was
deleted from the multivariable analysis.
Multivariable statistical analyses were
conducted in two steps. In the first, we
used the GEE approach to conduct the
analysis. In the second, the final model
obtained in the first step was extended by
including a categorical dropout variable.
The dropout variable was statistically
significant as a main effect and also as
an effect modifier of the relationship
between ethnicity and mental distress.
Hence, the pattern-mixture model was
used for prediction purposes. Standard
errors were computed using the BRR
resampling technique, which accounts for
the complexities of stratified multi-stage
design.
* http://www.hcp.med.harvard.edu/wmhcidi/index.php
†
Urban area is defined as area that has a minimum population concentration of 1000 or more and a population density of at least 400 per square kilometre based on previous census
counts.16 Rural areas are residual of urban areas.16
165
Vol 32, No 3, June 2012 – Chronic Diseases and Injuries in Canada
The main risk factor of interest was
ethnicity, which was adjusted for demographic, socio-economic, social support and
lifestyle factors as main effects. Various
interaction terms were tested in the multivariable model for statistical significance.
The final predictive model was used
to determine the predicted probabilities
for the moderate/high mental distress
category.
Results
The study population consisted of
14 713 respondents 15 years and older.
The 20% of respondents who self-reported
as immigrants at baseline described
themselves as belonging to the following
ethnic groups: British, 37.6%; Eastern
European, 4.6%; Western European, 36.4%;
Chinese, 2.4%; South Asian, 1.6%; Black,
1.0%; and Other, 16.4%. At baseline,
78.2% respondents reported having no/low
mental distress and 21.8% moderate/
high distress. Table 1 shows the baseline
characteristics of the study population
stratified by mental distress status (no/low
vs. moderate/high) in terms of weighted
percentages. Based on standard modelbuilding techniques,24 these variables were
selected for the multivariable modeling.
Results based on the final multivariable
model are shown in Table 2 (main effects)
and Table 3 (interaction terms).
Table 2 shows the relationship between
mental distress and the variables of interest.
Female respondents were more likely to
self-report mental distress than were
male respondents (adjusted odds ratio
[ORadj] = 1.69, 95% confidence interval
[CI]: 1.48–1.94). Younger respondents were
more likely to self-report mental distress
(15–24 years: ORadj = 2.67, 95% CI: 2.21–
3.22; 25–54 years: ORadj = 2.23, 95%
CI: 1.95–2.56; 55–69 years: ORadj = 1.23,
95% CI: 1.08–1.41; reference category
≥ 70 years). Respondents who were either
married, in common-law relationships or
in partnerships (ORadj = 0.69, 95% CI:
0.62–0.76) had significantly lower risk of
moderate/high mental distress compared
to single respondents. Rural residents had
a significantly lower risk of reporting
moderate/high mental distress than their
urban counterparts (ORadj = 0.87, 95%
CI: 0.79–0.97), while the geographical
area of residence was also a significant
predictor: Quebec residents were at a
significantly higher risk of reporting
moderate/high distress compared to Ontario
residents (ORadj = 1.46, 95% CI: 1.31–1.64).
The relationship between length of stay in
Canada and mental distress was in the
shape of an inverted u: those who had
lived in Canada for less than 2 years
were less likely to report moderate/
high mental distress, while those who
had lived in Canada for 2 to 20 years were
significantly more likely to report
moderate/high mental distress than those
who had lived in Canada for more than
20 years.
We also observed an inverse dose-response
relationship for income adequacy levels: the
respondents in the low-income adequacy
category were more likely to report
moderate/high mental distress than the
high-income adequacy group (ORadj = 1.35,
95% CI: 1.19–1.53).
Current smokers (ORadj = 1.36, 95% CI:
1.21–1.52) and ex-smokers (ORadj = 1.14,
95% CI: 1.04–1.24) were at a higher risk of
reporting moderate/high mental distress
compared to non-smokers, while those
exposed to household smoke (ORadj = 1.14,
95% CI: 1.05–1.25) were also at a significantly higher risk compared to those who
were not exposed to household smoke.
The self-perceived general health status
variable measures the overall self-reported
health, physical and mental, of an individual.
A dose-response relation was observed
between general health status and proba­
bility of moderate/high mental distress,
with those in poor health most likely to
report mental distress (ORadj= 13.40, 95%
CI: 11.11–16.15 against the reference category,
excellent general health status).
Canadian-born
people
of
Eastern
European ethnicity had the highest
predicted probability of moderate/high
mental distress at Cycle 1, declining sharply
over time, in contrast to immigrants of
Eastern European ethnicity, who were
much less likely to report moderate/high
mental distress (Figure 1). The predicted
probability for moderate/high mental
distress of immigrants of British ethnicity
Vol 32, No 3, June 2012 – Chronic Diseases and Injuries in Canada
166
was higher than for Canadian-born
people of British ethnicity; however,
these probabilities were the lowest of all
Canadian-born and immigrant respondents.
The predicted probability for moderate/
high mental distress for Canadian-born
respondents of Black ethnicity was average
(Figure 1) and did not change substantially
over the six cycles; however, among
immigrants of Black ethnicity there was
a steep decrease in this probability from
Cycle 1 to Cycle 2, followed by a sharp
increase and substantially higher probability
for moderate/high mental distress compared
to other ethnicities.
Among the female respondents, South Asian
females had the lowest probability of
reporting moderate/high mental distress.
Females of British ethnicity were less likely
to self-report moderate/high levels of mental
distress compared to those of other
ethnicities (Figure 2). In contrast to South
Asian females, South Asian males had the
highest probability of reporting moderate/
high mental distress among males. In
contrast, males of British ethnicity were
the least likely to report moderate/high
mental distress compared to the other
ethnicities (Figure 2).
Respondents of Chinese ethnicity with less
education (≤ grade 12) had the highest
predicted probability of reporting moderate/
high mental distress, in contrast to
those with an education beyond grade 12
(Figure 3, Table 3). This pattern was
opposite for respondents of South Asian
ethnicity; the predicted probability of
reporting moderate/high mental distress
was higher (with no particular pattern
over time) for those who are educated
beyond grade 12, with a slight decline
from Cycle 1 to Cycle 2 that then levelled
off. Similar trends were observed for
respondents of Eastern and Western
European ethnicities. For respondents of
British ethnicity, the predicted probability
of reporting moderate/high mental distress
was slightly lower for those who were
educated beyond grade 12.
Predicted probability of self-reporting
moderate/high mental distress was highest
for those who had a moderate SIS and
lowest for those with high SIS for all groups
except for those of Black ethnicity (Figure 4).
Table 1
Respondent characteristics at baseline (Cycle 1) of the National Population Health Survey
Variable
Self-reported mental distress
No/Low
%
Moderate/
Higha
%
OR (95% CI)b
39.6
32.9
1.00
a
Ethnicity
Ethnic groups
British
Eastern European
4.8
4.6
1.03 (1.00–1.05)
Western European
35.3
39.3
1.04 (1.03–1.05)
Chinese
2.1
3.0
1.02 (0.98–1.06)
South Asian
1.6
1.5
1.01 (0.97–1.06)
Black
1.0
1.2
1.01 (0.95–1.08)
Other
15.7
17.6
1.04 (1.02–1.06)
Canadian-born
81.5
79.7
1.00
Immigrant
18.5
20.3
1.01 (0.99–1.03)
Male
49.4
39.3
1.00
Female
50.6
60.7
1.07 (1.06–1.08)
14.2
25.1
1.10 (1.08–1.12)
Demographic variable
Immigrant status
Sex
Age group, years
15–24
25–54
59.2
56.0
1.03 (1.01–1.04)
55–69
16.8
11.7
0.99 (0.97–1.00)
9.9
7.2
1.00
65.4
49.5
0.92 (0.91–0.93)
≥70
Marital status
Married, common law, partnership
Widowed, separated, divorced
12.6
15.8
0.98 (0.97–1.00)
Single
22.0
34.7
1.00
17.6
13.9
0.98 (0.97–0.99)
82.4
86.1
1.00
Residence
Ruralc
Urban
d
Length of stay in Canada, years
≤2
1.4
0.9
1.05 (0.99–1.11)
2–20
14.4
24.5
1.07 (1.06–1.09)
> 20
84.3
74.6
1.00
8.5
7.6
0.99 (0.98–1.00)
British Columbia
13.1
11.6
1.00 (0.98–1.01)
Prairiesf
16.6
14.2
1.00 (0.98–1.01)
Quebec
23.9
31.7
1.06 (1.04–1.08)
Ontario
37.8
34.9
1.00
Geographical area
Atlantice
Socio-economic status
Income adequacyg
Low
16.1
25.4
1.13 (1.11–1.14)
Medium
67.0
62.7
1.03 (1.02–1.04)
High
16.9
11.9
1.00
Continued on the following page
167
Vol 32, No 3, June 2012 – Chronic Diseases and Injuries in Canada
Table 1 (continued)
Respondent characteristics at baseline (Cycle 1) of the National Population Health Survey
Variable
Self-reported mental distress
No/Low
%
Moderate/
Higha
%
OR (95% CI)b
≤ Grade 12
73.1
64.7
1.06 (1.05–1.07)
> Grade12
26.9
35.3
1.00
a
Education
Social involvement scoreh
Low
40.7
46.2
1.06 (1.04–1.07)
Moderate
37.4
38.4
1.04 (1.03–1.06)
High
21.9
15.4
1.00
Lifestyle
Smoking status
Current
27.8
40.9
1.08 (1.07–1.10)
Former
32.1
25.6
1.01 (1.00–1.02)
Never
40.1
33.6
1.00
Household smoking
Yes
34.1
46.4
1.07 (1.06–1.08)
No
65.9
53.6
1.00
1.0
6.4
1.51 (1.46–1.56)
General health status
Poor
Fair
Good
6.4
15.4
1.25 (1.23–1.28)
25.1
34.2
1.12 (1.11–1.13)
Very Good
39.1
30.6
1.04 (1.03–1.05)
Excellent
28.3
13.4
1.00
Abbreviations: CI, confidence interval; GEE, generalized estimating equations; OR, odds ratio; SIS, social involvement score.
Note: Bolded values are ones that are statistically significant.
a
Weighted percentages.
b
p < .20 based on the relationship between each of the risk factors and the outcome variable using GEE approach.
c
Urban: An area that has a minimum population concentration of 1000 or more and a population density of at least 400 per square kilometre based on previous census counts.16
d
Rural: Area residual of urban areas (see above).16
e
Nova Scotia, Newfoundland and Labrador, New Brunswick, Prince Edward Island.
f
Manitoba, Saskatchewan, Alberta.
g
Based on total household income and household size.16
h
The social involvement dimension is measured by two items that reflect the frequency of participation in associations or voluntary organizations and the frequency of attendance at religious
services in the last year. SIS is used as a time-independent variable (computed for Cycle I).16
Vol 32, No 3, June 2012 – Chronic Diseases and Injuries in Canada
168
Table 2
Relationship between self-reported mental distress and independent variables of interest (main effects)
based on dichotomous logistic regression of the prevalence of self-reported mental distress
Variable
Adjusted odds ratio
(ORadj) of self-reported
mental distress
(95% CI)
Ethnicity
Ethnic groups (Ref: British)
1.0
Eastern European
1.72 (0.75–3.90)
Western European
1.28 (0.88–1.85)
Chinese
0.45 (0.09–2.33)
South Asian
2.93 (0.36–23.82)
Black
1.80 (0.13–25.36)
Other
1.52 (0.91–2.52)
Demographic status
Immigrant status (Ref: Canadian-born)
1.0
Immigrant
0.89 (0.67–1.18)
Sex (Ref: Male)
1.0
Female
1.69 (1.48–1.94)
Age group, years (Ref: ≥ 70)
1.0
2.67 (2.21–3.22)
15–24
25–54
2.23 (1.95–2.56)
55–69
1.23 (1.08–1.41)
Marital status (Ref: Single)
1.0
Married/common law/partnership
0.69 (0.62–0.76)
Widowed/separated
0.98 (0.87–1.10)
1.0
Residence (Ref: Urban)a
0.87 (0.79–0.97)
Ruralb
Length of residence, years (Ref: > 20)
1.0
≤2
0.78 (0.46–1.33)
2–20
1.27 (1.09–1.49)
Geographical area (Ref: Ontario)
1.0
c
0.97 (0.86–1.09)
British Columbia
1.01 (0.89–1.15)
Atlantic
Prairies
0.94 (0.84–1.04)
d
1.46 (1.31–1.64)
Quebec
Socio-economic status
1.0
Income adequacy (Ref: High)e
Low
1.35 (1.19–1.53)
Medium
1.04 (0.86–1.25)
Education (Ref: > Grade 12)
1.0
1.21 (1.06–1.39)
≤ Grade 12
Social support statusf
SIS (Ref: High)
1.0
Low
1.14 (0.95–1.37)
Moderate
1.04 (0.86–1.25)
Continued on the following page
169
Vol 32, No 3, June 2012 – Chronic Diseases and Injuries in Canada
Table 2 (continued)
Relationship between self-reported mental distress and independent variables of interest (main effects)
based on dichotomous logistic regression of the prevalence of self-reported mental distress
Variable
Adjusted odds ratio
(ORadj) of self-reported
mental distress
(95% CI)
Lifestyle status
Smoking status (Ref: Never smoked)
1.0
Current smoker
1.36 (1.21–1.52)
Former smoker
1.14 (1.04–1.24)
Household smoking (Ref: No)
1.0
1.14 (1.05–1.25)
Yes
General health status
(Ref: Excellent)
1.0
13.40 (11.11–16.15)
Poor
Fair
5.77 (5.07–6.57)
Good
2.85 (2.58–3.15)
Very Good
1.54 (1.41–1.69)
Time point
(Ref: Cycle 1)
1.0
Cycle 6
0.75 (0.66–0.84)
Cycle 5
0.65 (0.58–0.72)
Cycle 4
0.58 (0.52–0.63)
Cycle 3
0.73 (0.66–0.81)
Cycle 2
0.68 (0.63–0.74)
Drop (Ref: Completers)
1.0
Missing value = 1
1.13 (0.95–1.35)
Missing values ≥ 2
1.28 (1.09–1.50)
Died during the cycles
1.26 (1.08–1.47)
Abbreviations: CI, confidence interval; ORadj, adjusted odds ratio; Ref, reference; SIS, social involvement score.
Note: Bolded values are statistically significant.
a
Urban: An area that has a minimum population concentration of 1000 or more and a population density of at least 400 per square kilometre based on previous census counts.16
b
Rural: Area residual of urban areas (see above).16
c
Nova Scotia, Newfoundland and Labrador, New Brunswick, Prince Edward Island.
d
Manitoba, Saskatchewan, Alberta.
e
Based on total household income and household size.16
f
The social involvement dimension is measured by two items that reflect the frequency of participation in associations or voluntary organizations and the frequency of attendance at
religious services in the last year. SIS used as a time-independent variable (computed for Cycle I).16
Respondents of Black ethnicity with one
missing observation had an extremely
high probability of reporting moderate/
high mental distress, while those of
Chinese ethni­city with two or more
missing obser­vations or who deceased
during the study period had an extremely
low probability of reporting moderate/
high mental distress (Figure 5).
Discussion
Our results show that the relationship
between ethnicity and mental distress was
modified by immigrant status, sex, SIS,
and education and by the missing data
pattern variable (dropout). The predicted
probability of moderate/high mental
distress was slightly higher for immigrant
versus Canadian-born respondents of all
except Black ethnicity (Table 3) and the
overall pattern of the longitudinal trend
was similar for all immigrants of different
ethnic groups except immigrants of Black
ethnicity (Figure 1). We observed an
inverted U-shaped relationship between
length of stay in Canada and mental distress.
These results support previous findings
Vol 32, No 3, June 2012 – Chronic Diseases and Injuries in Canada
170
that the physical and mental health of
immigrants deteriorates during the first
couple of years after immigration, and then
starts to improve slightly or to level off.25-27
Adjustment to a new country, for any
individual, is a complex process. Some
studies have shown that most new
immigrants to any country experience
some kind of mental or psychological
distress during the first few years,27,28
especially adolescents,29-31 and that length of
stay in the new country plays an important
role in the development of well being.27-29
Table 3
Relationship between self-reported mental distress and ethnicity as modified by several factors based
on dichotomous logistic regression of the prevalence of self-reported mental distress
Combinations of variables
Education (years) and ethnicity
≤ 12 (vs. > 12)
≤ 12 (vs. > 12)
≤ 12 (vs. > 12)
≤ 12 (vs. > 12)
≤ 12 (vs. > 12)
≤ 12 (vs. > 12)
SIS and ethnicity
Low (vs. high)
Low (vs. high)
Low (vs. high)
Low (vs. high)
Low (vs. high)
Low (vs. high)
Moderate (vs. high)
Moderate (vs. high)
Moderate (vs. high)
Moderate (vs. high)
Moderate (vs. high)
Moderate (vs. high)
Immigration status and ethnicity
Immigrant (vs. Canadian-born)
Immigrant (vs. Canadian-born)
Immigrant (vs. Canadian-born)
Immigrant (vs. Canadian-born)
Immigrant (vs. Canadian-born)
Immigrant (vs. Canadian-born)
Sex and ethnicityy
Female (vs. male)
Female (vs. male)
Female (vs. male)
Female (vs. male)
Female (vs. male)
Female (vs. male)
Drop and ethnicity
Missing value, number
1
1
1
1
1
1
≥2
≥2
≥2
≥2
≥2
≥2
Adjusted odds ratio
(ORadj) of self-reported
mental distress
(95% CI)
Eastern European
0.81 (0.48–1.34)
Western European
Chinese
South Asian
Black
Other
0.88 (0.73–1.06)a
2.16 (0.92–5.07)
0.83 (0.29–2.42)
0.40 (0.12–1.37)
1.03 (0.80–1.32)
Eastern European
Western European
Chinese
South Asian
Black
Other
Eastern European
Western European
Chinese
South Asian
Black
Other
1.11 (0.64–1.93)
1.03 (0.80–1.33)
2.90 (0.71–11.88)
2.46 (0.62–9.80)
0.80 (0.25–2.51)
0.98 (0.71–1.35)
1.51 (0.85–2.66)
1.18 (0.89–1.55)
5.67 (1.38–23.32)
2.30 (0.64–8.27)
0.45 (0.10–2.07)
1.13 (0.81–1.57)
Eastern European
Western European
Chinese
South Asian
Black
Other
1.80 (1.10–2.97)
1.38 (0.97–1.96)a
1.18 (0.55–2.53)
1.26 (0.35–4.57)
0.68 (0.15–3.08)
1.24 (0.88–1.74)
Eastern European
Western European
Chinese
South Asian
Black
Other
0.70 (0.47–1.04)a
0.98 (0.82–1.17)
0.73 (0.39–1.38)
0.40 (0.15–1.07)a
0.84 (0.22–3.16)
0.88 (0.70–1.13)
Eastern European
Western European
Chinese
South Asian
Black
Other
Eastern European
Western European
Chinese
South Asian
Black
Other
1.10 (0.65–1.87)
1.10 (0.85–1.43)
0.89 (0.39–2.05)
0.80 (0.21–3.06)
5.25 (1.20–22.85)
0.90 (0.64–1.27)
1.26 (0.77–2.05)
0.79 (0.63–1.00)
0.85 (0.42–1.71)
0.30 (0.09–1.04)a
0.95 (0.19–4.66)
0.77 (0.58–1.01)a
Abbreviations: CI, confidence interval; ORadj, adjusted odds ratio; SIS, social involvement score; vs., versus.
Note: Bolded values are statistically significant.
a
Borderline significant.
171
Vol 32, No 3, June 2012 – Chronic Diseases and Injuries in Canada
Figure 1
Predicted probability of developing moderate/high mental distress
over time among NPHS respondents aged 15 years plus stratified by ethnicity
and immigration status, cycle 1 (1994/1995) to cycle 6 (2004/2005)
Canadian Born
Immigrant
0.50
Predicted probability of distress
Predicted probability of distress
0.50
0.40
0.30
0.20
0.10
0.00
Canadian-born population, which our
results did not show.29 In this regard,
because of the aging of the Canadian
population, mental illness among elderly
people is likely to be a major health
problem, with a need for valid instruments
to both assess the mental health of elderly
people of different ethnicities and help in
their treatment.29
1
2
3
4
5
0.40
0.30
0.20
0.10
0.00
6
1
2
3
Cycle
4
5
6
Cycle
British
East European
West European
Chinese
South Asian
Black
Other
Abbreviation: NPHS, National Population Health Survey.
Figure 2
Predicted probability of developing moderate/high mental distress
over time among NPHS respondents aged 15 years plus stratified by ethnicity,
cycle 1 (1994/1995) to cycle 6 (2004/2005)
Males
Females
0.50
Predicted probability of distress
Predicted probability of distress
0.50
0.40
0.30
0.20
0.10
0.00
1
2
3
4
5
6
The inverse dose-response relationship
between income adequacy and mental
distress in our report (Table 2) supports
the results from various Canadian, North
American and British studies.32,33 Orpann
et al. reported that among both men and
women low household income was a
significant predictor for mental distress.33
0.40
0.30
0.20
0.10
0.00
1
Cycle
2
3
4
5
6
Cycle
British
East European
West European
Chinese
South Asian
Black
Other
Abbreviation: NPHS, National Population Health Survey.
However, other studies have shown that
this psychological stress does not improve
over time.14,31
Our data did not show the significant
interaction between age and ethnicity
observed by Rait et al.;29 rather, we
observed a decline in moderate/high
mental distress with increasing age
(Table 1), a finding consistent with those
of many other researchers.4,14,30 Rait et al.
also found poorer mental health among
the older (65+ years) immigrants of
Chinese ethnicity compared to the
Vol 32, No 3, June 2012 – Chronic Diseases and Injuries in Canada
Wu et al.,31 who investigated the differences
in mental distress of 12 ethnic groups
using 1996/97 NPHS data, reported that
Canadians of East and Southeast Asian,
South Asian, Chinese and Black ethnic
groups have a lower risk of depression
compared to British Canadians.31 These
differences among ethnic groups persisted
after adjusting for socio-economic status and
social support.31 We also observed that
respondents of Chinese ethnicity with
high SIS had the lowest moderate/high
mental distress compared to other ethnicities
and respondents of South Asian ethnicity
had the second lowest moderate/highest
mental distress (Table 3). Respondents of
Chinese ethnicity with high SIS had
remarkably low probability of moderate/
high mental distress compared to those
who had moderate SIS.
172
Personal smoking habits and exposure to
second-hand smoke have been linked to
mental health in several studies.34-39 We
found that both former and current smokers
were significantly more likely to report
moderate/high mental distress than nonsmoking respondents, and that exposure
to household smoking was significantly
associated with increased risk of moderate/
high mental distress (see Table 1).
Evidence suggests that smoking may
predate and may have a causal role in
the development of mental disorders
because of the complex effect of nicotine
on neuroregulators.40 Individuals with
mental illnesses may “self-medicate”
with tobacco.41-43 Further research could
Figure 3
Predicted probability of developing moderate/high mental distress
over time among NPHS respondents aged 15 years plus stratified by ethnicity
and education level, cycle 1 (1994/1995) to cycle 6 (2004/2005)
Education < grade 12
Education ≥ grade 12
0.50
Predicted probability of distress
Predicted probability of distress
0.50
0.40
0.30
0.20
0.10
0.00
1
2
3
4
5
0.40
0.30
0.20
0.10
0.00
6
1
2
3
Cycle
4
5
6
Cycle
British
East European
West European
Chinese
South Asian
Black
Other
investigate whether smoking causes mental
distress or whether smoking is the result
of mental health problems by comparing
smoking patterns before and after incidences
of mental distress.
Our findings echo those of Canadian
and Australian studies reporting that the
prevalence of depression or other mental
disorders was significantly lower in
rural populations.44,45 We also observed
that geographical area was a significant
risk factor for mental distress. Caron and
Liu reported that people living in Quebec
demonstrated significantly higher psychological distress compared to those living in
Atlantic Canada, Ontario, British Columbia
and the Prairie provinces.26 In contrast,
Stephens et al. found no relationship
between mental health and the province
of residence.14
Abbreviation: NPHS, National Population Health Survey.
It is not clear why respondents of Black
ethnicity with one missing observation
had an extremely high probability of
reporting moderate/high mental distress
(Figure 5; Table 3). Similarly, the opposite
finding for Chinese respondents for two or
more missing observations and for those
who had deceased during the study period
is hard to explain.
Figure 4
Predicted probability of developing moderate/high mental distress
over time among NPHS respondents stratified by ethnicity and
social involvement score, cycle 1 (1994/1995) to cycle 6 (2004/2005)
Low SIS
Moderate SIS
0.50
Predicted probability of distress
Predicted probability of distress
0.50
0.40
0.30
0.20
0.10
0.00
1
2
3
4
5
6
0.40
Strengths and limitations
0.30
0.20
0.10
0.00
1
2
Cycle
3
4
5
6
Cycle
High SIS
Predicted probability of distress
0.50
0.40
British
East European
West European
Chinese
0.30
0.20
South Asian
Black
Other
0.10
0.00
1
2
3
4
5
6
The strengths of our study were the
availability of information on a large
number of people over a 12-year period, the
small attrition rate of respondents, and
the large number of health determinants
available for analysis. There were also some
limitations. The NPHS survey includes
respondents from all 10 Canadian provinces,
but excludes people living in the territories,
long-term residents of health institutions,
individuals living on Indian Reserves and
Crown Lands, and full-time members of the
Canadian Forces. Since the prevalence of the
mental distress may be higher in the excluded
populations than the general population,
the analysis could have underestimated the
risk of moderate/high mental distress. In
addition, data in this analysis relied on selfreport, which always tends to be biased.
Cycle
Abbreviations: NPHS, National Population Health Survey; SIS, Social Involvement Score.
Note: For the low social involvement category, lines for British and Eastern European ethnicities overlap. For the moderate
social involvement category, lines for Western European and Other ethnicities overlap.
173
Increased prevalence of mental health
problems in immigrant populations has
been reported worldwide;46,47 however,
Vol 32, No 3, June 2012 – Chronic Diseases and Injuries in Canada
rates are not consistently elevated in
Canada.48 Based on results from the
Canadian Community Health Survey, recent
first-generation immigrants to Canada had
lower rates of depression compared to
Canadian-born residents; however, these
rates increased with length of stay in Canada
and among the second generation.9 The
reason for the lower rates in the first
generation could be because all applicants
are screened for a wide range of health
problems during the immigration process.
It is also possible that recent immigrants do
not seek help for mental health problems
due to ethnic and cultural barriers. As their
length of stay, comfort in Canadian society
and awareness increases, they may seek
the necessary help. Nevertheless, with
immigrant population growth varying
from 14% to 30% in different Canadian
provinces, this remains a challenge
for developing targeted mental health
strategies.48
Conclusion
The results of our study show that the
relationship between ethnicity and mental
distress is modified by factors such as
immigrant status (foreign born versus
Canadian born), sex, education and SIS.
The risk of reporting moderate/high mental
distress was highest among those aged 15 to
24 years and in the low-income adequacy
group. Marital status, sex, place and
geographical area of residence as well as
Figure 5
Predicted probability of developing mental distress over time among
NPHS respondents who participated in all the cycles from cycle 1 (1994/1995)
to cycle 6 (2004/2005) stratified by ethnicity and dropout pattern
Completes
Predicted probability of distress
Predicted probability of distress
0.50
0.40
0.30
0.20
0.10
0.00
1
2
3
4
5
0.20
0.10
1
2
3
4
5
Two or more missing observations
Died during the study period
6
0.50
0.40
0.30
0.20
0.10
1
2
3
4
5
6
0.30
0.10
1
Cycle
2
3
4
Cycle
South Asian
Black
Other
Abbreviation: NPHS, National Population Health Survey.
Vol 32, No 3, June 2012 – Chronic Diseases and Injuries in Canada
5. Hudson CG. Socioeconomic status and
mental illness: tests of the social
causation and selection hypotheses.
Am J Orthopsychiatry. 2005;75(1):3-18.
7. Ali J. Mental health of Canada’s
immigrants. Supplement to Health
Reports. 2002;13:1-11. [Statistics Canada,
Catalogue No.: 82-003;2002].
0.20
British
East European
West European
Chinese
2. Stephens T, Joubert N. The economic burden
of mental health problems in Canada.
Chronic Dis Can. 2001;22(1):18-23.
6. Murali V, Oyebode F. Poverty, social
inequality and mental health. Advances in
Psychiatric Treatment. 2004;10:216-24.
0.40
0.00
1. Murthy RS, Bertolote JB, Epping-Jordan J,
Funk M, Prentice T, Saraceno B, et al. The
world health report 2001—Mental health:
new understanding, new hope. Geneva
(CH): World Health Organization, 2001.
4. Hyman I. Setting the stage: reviewing current
knowledge on the health of Canadian
immigrants: what is the evidence and
where are the gaps? Can J Public Health.
2004; 95(3):14-8.
Cycle
Predicted probability of distress
Predicted probability of distress
0.30
Cycle
0.50
0.00
0.40
0.00
6
References
3. Clarke DE, Colantonio A, Rhodes AE,
Escobar M. Ethnicity and mental
health: conceptualization, definition and
operationalization of ethnicity from a
Canadian context. Chronic Dis Can.
2008;28(4):128-47.
One missing observation
0.50
personal smoking and household smoking
status were other significant predictors.
Our results suggest that there is a need
to develop ethnicity-specific mental-health
programs targeting those with low education
attainment and low social involvement. In
addition, policies and programs should also
be targeted towards women, the younger
age group (15–24 years) and low-income
adequacy groups.
174
5
6
8. Baron-Epel O, Kaplan G. Can subjective
and objective socioeconomic status explain
minority health disparities in Israel? Soc Sci
Med. 2009;69:1460-6.
9. Statistics Canada. Canadian Demographics
at a Glance [Internet]. Ottawa (ON): Statistics
Canada; 2008 [cited 2011 Apr 20]. [Statistics
Canada,
Catalogue No.: 91-003-XIE].
Available from: http://www.statcan.gc.ca
/pub/91-003-x/91-003-x2007001-eng.pdf
10. Statistics Canada. National population
health survey household component,
cycle 1 to 7 (1994/1995 to 2006/2007),
longitudinal documentation [Internet].
Ottawa (ON): Statistics Canada; Jul 2008
[cited 2008 Dec 20]. Available from: http://
w w w. s t a t c a n . g c . c a / i m d b - b m d i
/document/3225_D5_T1_V4-eng.pdf
11. Kish L. Multipurpose Sample Design.
Survey Methodology. 1988;14:19-32.
12. Tambay J-L, Catlin G. Sample design of
the National Population Health Survey.
Health Reports [Internet]. 1995 [cited 2011
Apr 20];7:29-38. Available from: http://
www.statcan.gc.ca/pub/82-003-x/1995001
/article/1661-eng.pdf
13. Kessler RC, Andrews G, Colpe LJ, Hiripi E,
Mroczek DK, and Zaslavsky A. Short
screening scales to monitor population
prevalences and trends in non-specific
psychological distress. Psychol Med.
2002;32(6):959-76.
14. Stephens T, Dulberg C, Joubert N.
Mental health of the Canadian population:
a comprehensive analysis. Chronic Dis
Can. 1999;20(3):118-26.
15. Baggaley RF, Ganaba R, Filippi V, Kere M,
Marshall T, Sombie I, et al. Detecting
depression after pregnancy: the validity of
the K10 and K6 in Burkina Faso. Trop Med
Int Health. 2007;12(10):1225-9.
16. Statistics Canada. National Population
Health Survey Household Component:
Documentation for the Derived Variables
and the Constant Longitudinal Variables
[Internet]. Ottawa (ON): Statistics Canada;
2009 Sep [cited 2011 Apr 20]. Available
from: http://www.statcan.gc.ca/imdb-bmdi
/document/3225_D10_T9_V3-eng.pdf
17. Wang J, EI-Guebaly N. Sociodemographic
factors associated with comorbid major
depressive episodes and alcohol dependence
in the general population. Can J Psychiatry.
2004;49(1):37-44.
18. SAS Institute. The SAS System for Windows,
release 9.03 [computer program]. SAS
Institute: Cary (NC); 2007.
19. Pahwa P, Karunanayake CP. Modeling
of longitudinal polytomous outcome from
complex survey data – application to
investigate an association between mental
distress and non-malignant respiratory
diseases. BMC Med Res Methodol.2009;9:84.
20. Liang KY, Zeger SL. Longitudinal data
analysis using generalized linear models.
Biometrika. 1986;73:13-22.
21. Zeger SL, Liang KY. Longitudinal data
analysis for discrete and continuous
outcomes. Biometrics. 1986;42:121-30.
22. StataCorp. Stata Statistical Software,
release 11 [computer program]. College
Station (TX): StataCorp LP; 2009.
23. Hedeker D, Gibbons RD. Application of
random-effects pattern-mixture models for
missing data in longitudinal studies.
Psychol Methods. 1997;2(1):64-78.
24. Hosmer DW, Lemshow S. Applied logistic
regression. Mississauga (ON): John Wiley
and Sons, Inc.; 1989. p. 82-134.
25. Mirsky J, Slonim-Nevo V, Rubinstein L.
Psychological wellness and distress among
recent immigrants: a four-year longitudinal
study in Israel and Germany. Int Migr.
2007;45(1):151-75.
26. Caron J, Liu A. A descriptive study of
the prevalence of psychological distress
and mental disorders in the Canadian
population: comparison between low-income
and non-low-income populations. Chronic
Dis Can. 2010;30(3):84-94.
27. Beiser M. Strangers at the gate: the “Boat
People’s” first ten years in Canada. Toronto
(ON): University of Toronto Press; 1999.
28. Hener T, Weller A, Shor R. Stages of
acculturation as reflected by depression
reduction in immigrant nursing students.
Int J Soc Psychiatry. 1997;43(4):247-56.
29. Rait G, Burns A, Chew C. Age, ethnicity,
and mental illness: a triple whammy. We
need validated assessment instruments for
specific communities. A letter to the editor.
BMJ. 1996;313:1347-8.
175
30. Wade TJ, Cairney J. Age and depression in
a nationally representative sample of
Canadians: a preliminary look at the
National Population Health Survey. Can J
Public Health. 1997;88(5):297-302.
31. Wu Z, Noh S, Kaspar V, Schimmele CM.
Race, ethnicity, and depression in
Canadian Society. J Health Soc Behav.
2003;44:426-41.
32. Marmot M, Ryff CD, Bumpass LL, Shipley M,
Marks NF. Social inequalities in health:
next questions and converging evidence.
Soc Sci Med. 1997;44(6):901-10.
33. Orpana HM, Lemyre L, Gravel R. Income
and psychological distress: the role
of the social environment. Health Rep.
2009;20(1):21-8.
34. Lawrence D, Mitrou F, Zubrick SR.
Smoking and mental illness: results from
population surveys in Australia and the
United States. BMC Public Health.
2009;9:285.
35. Hamer M, Stamatakis E, Batty GD.
Objectively assessed secondhand smoke
exposure and mental health in adults:
cross-sectional and prospective evidence
from the Scottish Health Survey. Arch Gen
Psychiatry. 2010;67(8):850-5.
36. Ratschen E, Britton J, Doody G, McNeill A.
Smoking attitudes, behaviour and nicotine
dependence among mental health acute
inpatients: an exploratory study. Int J Soc
Psychiatry. 2010;56(2):107-18.
37. Storr CL, Cheng H, Alonso J, Angermeyer
M, Bruffaerts R, de Girolamo G, et al.
Smoking estimates from around the world:
data from the first 17 participating countries
in the World Mental Health Survey
Consortium. Tob Control. 2010;19:65-74.
38. Glassman AH, Helzer JE, Covey LS,
Cottler LB, Stetner F, Tipp JE, et al.
Smoking, smoking cessation, and major
depression. JAMA. 1990;264:1546-9.
39. Lasser K, Boyd JW, Woolhandler S,
Himmelstein
DU,
McCormick
D,
Bor DH. Smoking and mental illness: a
population-based prevalence study. JAMA.
2000;284:2606-10.
Vol 32, No 3, June 2012 – Chronic Diseases and Injuries in Canada
40. Picciotto MR, Brunzell DH, Caldarone BJ.
Effect of nicotine and nicotinic receptors
on anxiety and depression. Neuroreport.
2002;13:1097-106.
41. Pomerleau OF. Nicotine as a psychoactive
drug; anxiety and pain reduction.
Psychopharmacol Bull. 1986;22:865-9.
42. Khantzian
EJ.
The
self-medication
hypothesis of substance use disorders: a
reconsideration and recent applications.
Harv Rev Psychiatry. 1997;4:231-44.
43. Saffer H, Dave D. Mental illness and the
demand for alcohol, cocaine, and cigarettes.
Econ Inq. 2005;43(2):229-46.
44. Wang JL. Rural-urban differences in the
prevalence of major depression and
associated impairment. Soc Psychiatry
Psychiatr Epidemiol. 2004;39(1):19-25.
45. Taylor AW, Wilson DH, Dal Grande E,
Ben Tovim D, Elzinga RH, Goldney RD,
et al. Mental health status of the South
Australian population. Aust N Z J Public
Health. 2000;24(1):29-34.
46. Levecque K, Lodewyckx I, Vranken J.
Depression and generalised anxiety in the
general population in Belgium: a comparison
between native and immigrant groups.
J Affect Disord. 2007; 97:229-39.
47. Sharpley M, Hutchinson G, McKenzie K,
Murray RM. Understanding the excess of
psychosis among the African-Caribbean
population in England. Review of current
hypotheses. Br J Psychiatry Suppl.
2001;40:s60-8.
48. Hansson E, Tuck A, Lurie S, McKenzie K,
for the Task Group of the Services
Systems Advisory Committee, Mental Health
Commission of Canada. (2010). Improving
mental health services for immigrant,
refugee, ethno-cultural and racialized
groups: issues and options for service
improvement [Internet]. Calgary (AB):
Mental Health Commission of Canada; 2010
[cited 2011 Apr 20]. Available online:
http://www.mentalhealthcommission.ca
/SiteCollectionDocuments/News/en/IO.pdf
Vol 32, No 3, June 2012 – Chronic Diseases and Injuries in Canada
176
CDIC: Information for authors
Chronic Diseases and Injuries in Canada (CDIC) is a
Submitting Manuscripts
References: In Vancouver style (consult a recent
quarterly scientific journal focusing on the prevention
CDIC issue for examples); numbered in superscript
and control of non‑communicable diseases and
Submit manuscripts to the Managing Editor,
injuries in Canada. Its feature articles are peer
Chronic Diseases and Injuries in Canada, Public
up to six authors (first six and et al. if more);
reviewed. The content of articles may include
Health Agency of Canada, 785 Carling Avenue,
without
research
Address Locator 6807B, Ottawa, Ontario K1A 0K9,
feature used in word processing; any unpublished
email: [email protected]
observations/data or personal communications
from
such
public/community
fields
health,
as
epidemiology,
biostatistics,
the
behavioural sciences, and health services or
in the order cited in text, tables and figures; listing
any
automatic
reference
numbering
used (discouraged) to be cited in the text in
economics. CDIC endeavours to foster communi‑
Since CDIC adheres in general (section on
parentheses (authors responsible for obtaining
cation on chronic diseases and injuries among
illustrations not applicable) to the “Uniform
written permission); authors are responsible for
public health practitioners, epidemiologists and
Requirements
verifying accuracy of references.
researchers, health policy planners and health
to Biomedical Journals” as approved by the
educators. Submissions are selected based on
International
Journal
Tables and Figures: Send vector graphics only.
scientific quality, public health relevance, clarity,
Editors, authors should refer to this document for
Each on a separate page and in electronic file(s)
conciseness and technical accuracy. Although
complete details before submitting a manuscript
separate from the text (not imported into the text
CDIC is a publication of the Public Health Agency
to CDIC (see <www.icmje.org>).
body); as self‑explanatory and succinct as possible;
of Canada, contributions are welcomed from both
the public and private sectors. Authors retain
responsibility for the contents of their papers, and
for
Manuscripts
Committee
of
Submitted
Medical
Checklist for Submitting
Manuscripts
opinions expressed are not necessarily those of the
not too numerous; numbered in the order that they
are mentioned in the text; explanatory material
for tables in footnotes, identified by lower‑case
superscript letters in alphabetical order; figures
CDIC editorial committee nor of the Public Health
Cover letter: Signed by all authors, stating that
limited to graphs or flow charts/templates (no
Agency of Canada.
all have seen and approved the final manuscript
photographs), with software used specified and
and have met the authorship criteria including a
titles/footnotes on a separate page.
Article Types
full statement regarding any prior or duplicate
publication 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
research, surveillance reports, meta‑analyses or
and email addresses, telephone and fax numbers
by email to cdic‑[email protected]‑aspc.gc.ca, please
methodological papers.
for corresponding author; separate word counts for
fax or mail the covering letter to the address on the
abstract and text.
inside front cover.
Status Report: Describe ongoing national programs,
studies or information systems bearing on Canadian
Second title page: Title only; start page numbering
public health (maximum 3000 words). Abstract not
here as page 1.
required.
Abstract: Unstructured (one paragraph, no
Summarize
headings), maximum 175 words (100 for short
relating
to
reports); include 3-8 keywords (preferably from
national public health (maximum 1200 words).
the Medical Subject Headings [MeSH] of Index
Abstract not required.
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.
Workshop/Conference
significant,
recently
Report:
held
events
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
Letter to the Editor: Comments on articles
substantive scientific contributions, authors should
recently published in CDIC will be considered for
state in the cover letter that they have obtained
publication (maximum 500 words). Abstract not
written permission.
required.
Book/Software Review: Usually solicited by the
editors (500-1300 words), but requests to review
are welcomed. Abstract not required.
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