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 33 · Number 1 · December 2012
Inside this issue
1
Child care: implications for overweight / obesity in Canadian
children?
12
Self-management, health service use and information seeking
for diabetes care among recent immigrants in Toronto
19
Assessing the reach of nicotine replacement therapy as a
preventive public health measure
29
Utilization of the Canadian Incidence Study of Reported Child
Abuse and Neglect by child welfare agencies in Ontario
38
Emergency department surveillance of injuries associated with
bunk beds: the Canadian Hospitals Injury Reporting and
Prevention Program (CHIRPP), 1990–2009
47
Validation of ICD-9 diagnostic codes for bronchopulmonary
dysplasia in Quebec’s provincial health care databases
53
Report summary – Diabetes in Canada: facts and figures from
a public health perspective
Chronic Diseases and Injuries in Canada
a publication of the Public Health Agency
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Howard Morrison, PhD
Editor-in-Chief
Public Health Agency of Canada
Lesley Doering, MSW
Anne-Marie Ugnat, PhD
Robert Geneau, PhD
Deputy Editor-in-Chief
International Development Research Centre
Claire Infante-Rivard, MD, PhD, FRCPC
Associate Scientific Editor
University of Calgary
Barry Pless, CM, MD, FRCPC
Associate Scientific Editor
Elizabeth Kristjansson, PhD
Associate Scientific Editor
Gavin McCormack, PhD
Associate Scientific Editor
Michelle Tracy, MA
Managing Editor
(613) 946-6963
Sylvain Desmarais, BA, BEd
Assistant Managing Editor
Brent Hagel, PhD
Isra Levy, MB, FRCPC, FACPM
Ottawa Public Health
Lesli Mitchell, MA
Centers for Disease Control and Prevention
Scott Patten, MD, PhD, FRCPC
University of Calgary
Kerry Robinson, PhD
Public Health Agency of Canada
Robert A. Spasoff, MD
University of Ottawa
Richard Stanwick, MD, FRCPC, FAAP
V ancouver Island Health Authority
Ania Syrowatka, MSc
McGill University
Andreas T. Wielgosz, MD, PhD, FRCPC
Chronic Diseases and Injuries in Canada (CDIC)
is a quarterly scientific journal focussing on
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Chronic Diseases and Injuries in Canada
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ISSN 1925-6515
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Également disponible en français sous le titre : Maladies chroniques et blessures au Canada
Child care: implications for overweight / obesity in Canadian
children?
L. McLaren, PhD (1); M. Zarrabi, PhD (1); D. J. Dutton, MA (1); M. C. Auld, PhD (2); J. C. H. Emery, PhD (1, 3)
This article has been peer reviewed.
Abstract
Introduction: Over recent decades, two prominent trends have been observed in Canada
and elsewhere: increasing prevalence of childhood overweight and obesity, and
increasing participation of women (including mothers) in the paid labour force and
resulting demand for child care options. While an association between child care and
children’s body mass index (BMI) is plausible and would have policy relevance, its
existence and nature in Canada is not known.
Methods: Using data from the National Longitudinal Survey of Children and Youth, we
examined exposure to three types of care at age 2/3 years (care by non-relative, care by
relative, care in a daycare centre) in relation to change in BMI percentile (continuous
and categorical) between age 2/3 years and age 6/7 years, adjusting for health and sociodemographic correlates.
Results: Care by a non-relative was associated with an increase in BMI percentile
between age 2/3 years and age 6/7 years for boys, and for girls from households of low
income adequacy.
Conclusion: Considering the potential benefits of high-quality formal child care for an
array of health and social outcomes and the potentially adverse effects of certain
informal care options demonstrated in this study and others, our findings support calls
for ongoing research on the implications of diverse child care experiences for an array of
outcomes including those related to weight.
Keywords: body mass index, Canada, child care, obesity, overweight
Introduction
The prevalence of childhood overweight/
obesity has increased in North America,
Europe and elsewhere over recent decades.1,2 In Canada, the prevalence of
obesity has more than doubled from 3%
in 1978 to 8% in 2004 among children
aged 2 to 17 years,3 which has led to
increasing concern about short- and
long-term health implications such as
hypertension, type 2 diabetes and psychosocial problems.4
Over a similar period, a key societal trend
in North America has been the increasing
proportion of women in the paid labour
force.1,5,6 For example, the participation
of women in the labour force in Alberta
increased steadily from 20% in 1951 to
68% in 20086 and in Canada from
50% in 1976 to 80% in 2001.7 Although
historical statistics on the participation of
mothers in the Canadian labour force is
sparse, data on women’s labour force
participation by age7 and marital status6
suggest a similar growth in proportion
of working mothers of young children. In
2005, 76% of mothers with a youngest
child between 3 and 5 years old worked
outside the home.5 This may have
implications for overweight/obesity in
children:8 studies from the United
States,9 Canada10,11 and the United
Kingdom12 have shown a positive association between maternal work intensity (i.e.
hours of work per week) and her child’s
likelihood of being overweight/obese.
One way through which maternal employment may impact children’s weight status
is child care arrangements. The rise in
maternal employment has increased the
demand for both formal (e.g. regulated
care settings) and informal (e.g. care by
relatives) child care arrangements, particularly for preschool-age children. Availability and use of formal versus informal
care varies by country. Canada, relative to
other countries in the Organisation for
Economic Co-operation and Development,
has a fairly high proportion of mothers of
young children who work outside the
home, low spending on child and family
programs as a proportion of gross domestic product and high costs to parents for
formal child care programs.5,13 Thus, in
contrast to some other countries (e.g.
Sweden) that provide high quality, publically funded care,5,6 Canada (along with
other liberal-democratic regimes* such as
* Term used in classifications of welfare state regimes to describe those characterized by active and passive encouragement of market forces.14 These regimes have also been described as AngloSaxon models of capitalism.15
Author references:
1. Department of Community Health Sciences, University of Calgary, Calgary, Alberta, Canada
2. Department of Economics, University of Victoria, Victoria, British Columbia, Canada
3. Department of Economics, University of Calgary, Calgary, Alberta, Canada
Correspondence: Lindsay McLaren, Department of Community Health Sciences, University of Calgary, 3280 Hospital Dr. NW, Calgary, AB T2N 4Z6; Tel.: 403-210-9424; Fax: 403-270-7307;
Email: [email protected]
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Vol 33, No 1, December 2012 – Chronic Diseases and Injuries in Canada
the U.S.) relies much more on the market
for this service. This results in high use of
informal care,5 which can vary considerably in quality. Regulated care opportunities in Canada, with the possible
exception of Quebec, are in short supply
and are inaccessible to many because of
their cost or inflexibility to the labour
force needs of parents.5
Child care arrangements—formal or informal—may have implications for childhood
obesity. The care setting may promote
weight gain if, for example, care providers
are less likely than parents to provide
adequate nutrition and/or opportunities
for physical activity. A handful of studies
have examined child care arrangements
in relation to obesity in children. Lumeng
et al.16 examined overweight status
among a nationally representative sample
of 6- to 12-year-old U.S. children in
relation to child care attendance from
age 3 to 5 years (retrospective reporting
by parents); they observed a reduced risk
of overweight among children who had
experienced some (i.e. less than 15 hours
per week) centre-based care attendance
compared with those with no attendance.
Maher et al.17 examined obesity among a
nationally representative sample of U.S.
children entering kindergarten in relation
to various types of care prior to kindergarten (retrospective reporting by parents);
they observed that children in family/
friend/neighbour care (paid or unpaid, at
least 10 hours per week) were more
likely to be obese than children in no
or limited care. Benjamin et al.18 examined adiposity in a sample of U.S.
children in relation to child care from
birth to 6 months and found that care in
someone else’s home (such as a licensed
family child care home or family’s,
friend’s or neighbour’s home) was associated with increased adiposity at 1 and
3 years of age. For both Maher et al.17
and Benjamin et al.,18 centre-based care
was not associated with weight outcomes. Kim and Petersen19 found that
child care by a relative, but not centrebased or non-relative care, was associated with significantly more weight
gain in the first 9 months of life when
compared to no child care. Pearce
et al.20 examined the association
between child care (formal and informal)
and overweight/obesity among children
in the U.K. Millennium Cohort. They
found that informal child care (especially
care by grandparents) between 9 months
and 3 years of age was associated with
increased risk of overweight/obesity at
age 3 years, but only for children from
more advantaged backgrounds. There
was no association between overweight/
obesity and formal care (nursery, child
care centre, nanny, or au pair). Among
a representative German sample, Rapp
et al.21 found no association between
type of preschool care and body mass
index (BMI) at age 4 and 6 years.
Finally, Gubbels et al.22 observed that,
among a sample of Dutch offspring of
women participating in a prospective
cohort study, the use of formal child
care outside the home at 1 and 2 years
of age was positively associated with
BMI at age 2 years as well as change in
BMI from age 1 to 2 years.
Based on these studies, certain informal
types of care may present a risk for BMI
and weight gain.17–20 Findings for formal
centre-based care are less clear: one study
showed a protective effect,16 one showed
a risk effect,22 and several others showed
no effect.17–21 One limitation of the existing studies, which may complicate the
overall conclusions, is that boys and girls
were combined rather than examined
separately. The child-caregiver interaction
may differ by sex (for example, due to
gender norms held by the caregiver) such
that previous null and inconsistent findings may reflect non-stratified analysis.
Our objective was to examine three types
of child care arrangement at age 2/3 years
in relation to subsequent change in BMI
between age 2/3 years and age 6/7 years
in a nationally representative sample of
Canadian children. We stratified the analyses by sex to investigate whether the
possible effects of different care arrangements on BMI differ for boys and girls.
Data and methods
Data source
We analyzed data from the National
Longitudinal Survey of Children and
Youth (NLSCY), a long-term study of
Vol 33, No 1, December 2012 – Chronic Diseases and Injuries in Canada
$
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Canadian children that follows their development from birth to early adulthood.
The inaugural cohort, which was the only
subsample for whom BMI data were
available from age 2/3 years to age 6/7
years, included over 22 000 children aged
0 to 11 years at the time of enrollment in
1994. Since then, there has been some
sample attrition so that by cycle 5 (2002–
2003) approximately 67% of the original
cycle 1 cohort remained. Like other
Statistics Canada surveys, the NLSCY
excludes children living on First Nations
reserves or on Crown Land, residents of
institutions, families of full-time members
of the Canadian armed forces, and residents of some remote regions and the
territories. A probability sampling strategy
was used (with elements of both cluster
and stratified random sampling based on
geographic region and urban/rural status),
and sampling weights were developed to
enhance the sample’s representativeness
of its underlying original population. Data
were collected using computer-assisted
interviewing, in person or via telephone,
with the respondent or his/her parent/
guardian.
We focused on children from the original
cohort who were aged 2 or 3 years in
either of the first two survey cycles (cycle
1 [1994] or cycle 2 [1996]), for whom
we also had BMI data at age 6 or 7 years.
We selected age 2/3 years as the exposure
period because 2 is the youngest age for
which BMI and BMI-for-age percentile
is recommended.23 We selected age 6/7
years as the follow-up age because it
represents a significant period of time
over which to examine a possible enduring effect of child care, but it is not so long
that it would be impossible to account
for a myriad of intervening factors.
Variables
BMI was calculated for each child at age
2/3 years and age 6/7 years using height
and weight data reported by the parent/
guardian. A corresponding BMI-for-age
percentile was assigned to each child,
using the growth charts developed by
Centers for Disease Control and Prevention.24 Several Canadian professional
organizations25 have endorsed these
growth charts, which are based on a
reference population of U.S. children, to
track growth of individual children.25,26
We examined BMI percentile as an outcome variable in two ways: first, as a
continuous variable, indicating the difference in percentile between age 2/3 years
and age 6/7 years; and second, as a
categorical variable, as in whether the
child falls into the normal (BMI < 85th
percentile) or at-risk (BMI § 85th percentile) range at age 2/3 years and age 6/7
years.
Our main predictor variable was exposure
to child care (at least 10 hours per week)
at age 2/3 years, as reported by the
primary caregiver. We examined three
types of care: care by a non-relative, care
by a relative and care in a daycare
centre. We also included the following
covariates (from age 2/3 years), based
on the literature27,28: income adequacy
(standard Statistics Canada classification
based on household income and number
of persons in the household{; three categories); highest household educational
attainment (high school graduation or
less, some post-secondary education,
post-secondary graduation or higher);
number of siblings (0, 1, § 2); number
of parents in the household (1 versus 2);
birth weight (normal versus low/very low
[< 2500 g]); mother’s age at birth (13–19
years or 35–54 years [both higher risk]
versus 20–34 years [lower risk]); province
of residence; urban versus rural residence;
and survey cycle (i.e. whether the child
was age 2/3 in cycle 1 [1994] or cycle 2
[1996]).
Analysis
We used two analytic strategies, corresponding to the two (continuous and
categorical) versions of the outcome variable. First, we used ordinary least squares
(OLS) regression to regress BMI percentile
change (continuous) on child care (care
by non-relative, care by relative, daycare
centre), unadjusted and adjusted for
covariates, for boys and girls separately.
Also using OLS, we tested two-way (child
care type * income adequacy [low versus
{
not low]) interaction terms to explore
the possibility that the impact of child
care on BMI percentile differs by socioeconomic circumstances, as shown elsewhere.20 Second, using binary logistic
regression, we examined a) the odds of
moving into the at-risk BMI percentile
range (§ 85th percentile) by age 6/7 years
in children who were in the normal BMI
percentile range (< 85th percentile) at age
2/3 years, and b) the odds of moving into
the normal BMI percentile range by age
6/7 years among children who were in the
at-risk percentile range at age 2/3 years,
in relation to child care type, unadjusted
and adjusted for covariates, for boys and
girls separately. The logistic models were
used to explore whether response to child
care may vary by initial BMI status, thus
complementing the OLS regression model
that assumes uniform response regardless
of BMI.
We initially ran models using five types
of care (care in someone else’s home by a
non-relative; care in own home by a nonrelative; care in someone else’s home by a
relative; care in own home by a relative;
and care in a daycare centre). Because
respondents could report more than one
type of care, the five care types were
represented in the models using five nonmutually exclusive variables. To query
whether it was appropriate to assume no
interactions amongst care types, we conducted a likelihood ratio test comparing
two OLS models: the first containing the
five care types, and the second containing
all possible combinations of care types
(n = 28, excluding combinations with
zero cases). For both boys and girls, we
were unable to reject the null hypothesis
of no difference between models, thus
supporting use of the model with five care
types entered as independent variables.
However, none of the five care types
showed an association with BMI percentile, and thus we explored the possibility
of a more parsimonious model. Specifically, we tested the interaction between
caregiver (relative; non-relative) and care
venue (in own home; in other’s home).
Finding no interaction, we collapsed these
four care types into two (care by nonrelative, regardless of venue; and care by
relative, regardless of venue). Care in a
daycare centre constituted the third care
type. Because respondents could report
more than one type of care, the reference
category for each care type is absence of
that care type, regardless of other forms
of care reported.
We used Stata version 11.0 (StataCorp LP)
for all analyses. All models incorporate
appropriate longitudinal sampling weights
to account for the complex survey design
and to approximate the original population (i.e. the population at the time of
original cohort sample selection), and
bootstrap weights to estimate standard
errors and confidence intervals.
The study received ethics approval from
the Conjoint Health Research Ethics Board
at the University of Calgary, Ethics ID #
E-22399.
Results
Descriptive statistics for the sample are
shown in Table 1. Of the 5654 children
potentially available for our study (i.e. age
2/3 years in cycle 1 or cycle 2 and still in
the survey at age 6/7 years), 4955 had BMI
data at age 2/3 years and 3916 had BMI
data at both age 2/3 years and age 6/7
years. Thus, 1738 children (30.7% of the
original sample) were excluded due to
missing BMI data, mostly at age 6/7 years.
Compared to those with complete BMI
data at age 2/3 years and age 6/7 years,
those with missing BMI data at age 6/7
years were more likely to have low
household income adequacy (both boys
and girls); have low household education
(both boys and girls); live in a singleparent household (both boys and girls);
have a young (i.e. < 20 years) mother at
time of birth (both boys and girls); and
live in Quebec (both boys and girls) (at
p < .05). They were less likely to have
siblings (girls only); live in Prince Edward
Island (boys only); live in Ontario (girls
only); and live in a rural environment
(boys only). For girls, there were no
For example, the lowest income adequacy category in the 1994 cohort was assigned to households for which household income was < $10,000 and household size was 1 to 4 persons, and
those for which household income was < $15,000 and household size was 5 or more persons (NLSCY Data Dictionary, Cycle 1. Available at www.statcan.gc.ca). The original variable had 5
categories, which we collapsed to 3 so that each category had adequate size.
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Vol 33, No 1, December 2012 – Chronic Diseases and Injuries in Canada
TABLE 1
Weighted descriptive statistics for study sample, stratified by sex
Variable
Girls
(n = 1760)
Boys
(n = 1804)
Mean (SD) BMI percentile change, age 2/3 to 6/7 years
2.064 (.018)
2.060 (.016)
45.8
47.4
38.3
40.1
25.5
28.8
Care by relative (yes), %
13.7
13.4
Care in daycare centre (yes), %a
11.9
9.0
No care (other than parents), %b
57.0
56.0
Lower
13.8
14.3
Middle
30.1
31.7
Higher
56.1
54.1
High school graduation or less
19.9
17.1
Some post-secondary
24.8
25.7
Post-secondary graduation plus
55.3
57.2
0 (only child)
26.2
27.6
1
47.0
45.4
2+
26.7
27.0
9.1
12.4
90.9
87.6
BMI status
At risk (§ 85th percentile) at age 2/3 years, %
th
At risk (§ 85 percentile), age 6/7, %
Care by non-relative (yes), %a
a
Household income adequacy, %c
Household education, %
Number of siblings, %
Number of parents in household, %
1 (single parent)
2
Birth weight, %
Low / very low [< 2500g]
7.9
5.1
92.1
94.9
13–19 years or 35 years+ (high risk)
10.7
12.2
20–34 years
89.3
87.8
1.6
1.9
3.1
4.0
Normal
Mother’s age at child’s birth, %
Province of residence, %
Newfoundland
d
Nova Scotia and Prince Edward Island
New Brunswick
differences in reported child care between
those with missing and non-missing BMI
data. For boys, those with missing BMI
data were less likely to report care in
another’s home by a non-relative or care
in their own home by a relative than
those with complete BMI data. Of the 3916
children with complete BMI data, 3889
had complete child care data and 3745
had complete data on all covariates. Our
final sample size, after purposefully
excluding an additional 181 who reported
less than 10 hours of child care per week,
was 3564 (1760 girls and 1804 boys).
Results of OLS regression (BMI percentile
change regressed on the three care types)
are presented in Table 2a (for girls) and
2b (for boys). There were no associations
between child care and BMI percentile
change for girls (Table 2a), while for boys
(Table 2b), care by a non-relative was
associated with an increase in BMI percentile between age 2/3 years and 6/7
years, relative to no non-relative care.
According to results of our OLS models
testing a two-way (child care type * low
income adequacy) interaction (not shown),
there was one significant interaction
whereby care by a non-relative (relative
to no care of this type) was associated
with an increase in BMI percentile
between age 2/3 years and age 6/7 years
for girls in low-income adequacy households (coefficient for interaction term from
adjusted model: 0.32; 95% confidence
interval [CI] = 0.016 to 0.62, p = .039).
Results of binary logistic regression (to
examine the odds of moving into or out of
the at-risk BMI percentile range by age
2.7
2.7
Quebec
22.9
23.2
Ontario
42.7
41.6
4.0
3.8
Abbreviations: BMI, body mass index; SD, standard
deviation.
Manitoba
Saskatchewan
Alberta
British Columbia
3.6
3.8
a
§ 10 hours/week of child care.
10.0
9.7
b
9.5
9.3
Sum of percentages for care variables exceeds 100 because
more than one type of child care could be reported.
c
Household income adequacy is a standard Statistics
Canada classification based on household income and
household size.
d
Nova Scotia and Prince Edward Island combined due to
small sample size for these provinces.
e
Survey cycle refers to when child was enrolled in the study
(cycle 1, enrolled in 1994; cycle 2, enrolled in 1996).
Percentages within variables may not add up to 100 due to
rounding.
Urban / rural residence, %
Urban
83.7
82.6
Rural
16.3
17.4
Cycle 1
55.7
57.0
Cycle 2
44.3
43.0
Survey cycle, %e
Table continued, see right column
Vol 33, No 1, December 2012 – Chronic Diseases and Injuries in Canada
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TABLE 2A
Results of OLS regression analysis for girls (n = 1760), with BMI percentile change (continuous variable) regressed on child care type and
socio-demographic variables
Unadjusted estimatesa coefficient (95% CI)
Predictor variable
Child care
Adjusted modelb coefficient (95% CI)
c
By non-relative
2.042 (2.13 to .04)
2.040 (2.13 to .05)
By relative
2.014 (2.11 to .09)
2.006 (2.10 to .09)
Daycare centre
.060 (2.063 to .18)
.056 (2.07 to .18)
Household income adequacy (Reference: lower)
Middle
.014 (2.09 to .12)
2.003 (2.13 to .12)
Higher
2.022 (2.12 to .08)
2.050 (2.18 to .08)
Some post-secondary
2.017 (2.12 to .08)
2.001 (2.11 to .10)
Post-secondary graduation
2.001 (2.09 to .09)
.017 (2.09 to .12)
1
2.054 (2.15 to .04)
2.052 (2.14 to .04)
§2
2.065 (2.18 to .04)
2.073 (2.18 to .03)
2.025 (2.14 to .09)
2.047 (2.20 to .10)
.064 (2.08 to .21)
.050 (2.09 to .19)
.061 (2.054 to .18)
.068 (2.04 to .18)
Household education (Reference: ƒ high school graduation)
Number of siblings (Reference: 0)
Number of parents in household (Reference: 2)
1
Birth weight (Reference: normal)
Low / very low (< 2500 g)
Mother’s age at birth, years (Reference: 20–34)
13–19 or 35+ (combined)d
Province of residence (Reference: Ontario)
Newfoundland
2.040 (2.16 to .08)
2.049 (2.18 to .08)
2.063 (2.15 to .03)
2.066 (2.16 to .02)
.040 (2.08 to .16)
.031 (2.09 to .15)
Quebec
.050 (2.06 to .16)
.034 (2.07 to .14)
Manitoba
.009 (2.12 to .13)
.009 (2.12 to .13)
2.020 (2.13 to .09)
2.018 (2.13 to .09)
Nova Scotia & Prince Edward Island
e
New Brunswick
Saskatchewan
Alberta
British Columbia
.084 (2.03 to .20)
.078 (2.03 to .19)
2.055 (2.15 to .04)
2.050 (2.15 to .05)
.010 (2.06 to .08)
2.000035 (2.07 to .07)
Urban/rural residence (Reference: urban)
Rural
Survey cycle (Reference: cycle 2)f
Cycle 1
.073 (.003 to .14)**
.066 (2.003 to .14)*
Abbreviations: BMI, body mass index; CI, confidence interval; OLS, ordinary least squares.
a
Bi-variate associations between each predictor variable and BMI percentile change, with the exception of child care and province of residence, for which all categories are entered as a block.
b
Associations from single model containing all variables.
c
§ 10 hours/week of child care.
d
The two high-risk age groups were combined to ensure adequate cell size for vetting.
e
Nova Scotia and Prince Edward Island combined due to small sample size for these provinces.
f
Survey cycle refers to when child was enrolled in the study (cycle 1, enrolled in 1994; cycle 2, enrolled in 1996).
* p < .10
** p < .05
6/7 years, among those in the normal and
at-risk BMI percentile range at age 2/3
years, in relation to child care type) are
shown in Table 3. No associations
between child care and shift in BMI
percentile range were observed for girls
(Table 3a) or boys (Table 3b).
We observed few associations between
socio-demographic covariates and BMI
$
5
percentile. In girls with normal BMI
percentile at age 2/3 years, those living
in middle income status households
were marginally less likely to move into
the at-risk BMI percentile range by age
Vol 33, No 1, December 2012 – Chronic Diseases and Injuries in Canada
TABLE 2B
Results of OLS regression analysis for boys (n = 1804), with BMI percentile change (continuous variable) regressed on child care type and
socio-demographic variables
Unadjusted estimatesa
coefficient (95% CI)
Predictor variable
Adjusted modelb
coefficient (95% CI)
Child carec
By non-relative
.061 (2.02 to .14)
.10 (.02 to .18)**
2.037 (2.14 to .06)
2.021 (2.12 to .07)
.031 (2.05 to .12)
.043 (2.05 to .13)
Middle
2.010 (2.14 to .11)
2.061 (2.19 to .07)
Higher
2.077 (2.19 to .04)
By relative
Daycare centre
Household income adequacy (Reference: lower)
2.18 (2.31 to 2.05)***
Household education (Reference: ƒ high school graduation)
Some post-secondary
2.019 (2.13 to .10)
2.026 (2.15 to .10)
Post-secondary graduation
2.017 (2.10 to .07)
2.010 (2.11 to .09)
1
.019 (2.06 to .10)
.012 (2.07 to .09)
§2
.014 (2.08 to .10)
2.020 (2.11 to .07)
Number of siblings (Reference: 0)
Number of parents in household (Reference: 2)
1
2.066 (2.21 to .08)
2.16 (2.33 to .002)*
Birth weight (Reference: normal)
Low / very low (< 2500 g)
.074 (2.13 to .28)
.071 (2.12 to .27)
2.051 (2.17 to .07)
2.052 (2.17 to .06)
Mother’s age at birth, years (Reference: 20–34)
13–19 or 35+ (combined)d
Province of residence (Reference: Ontario)
Newfoundland
2.074 (2.19 to .04)
Nova Scotia & Prince Edward Islande
.037 (2.06 to .13)
2.11 (2.23 to .01)*
2.00057 (2.10 to .10)
New Brunswick
.064 (2.08 to .21)
.027 (2.11 to .17)
Quebec
.034 (2.05 to .12)
.0038 (2.08 to .09)
Manitoba
.029 (2.09 to .15)
.011 (2.11 to .13)
.10 (2.02 to .22)
.070 (2.05 to .19)
Saskatchewan
Alberta
2.095 (2.21 to .02)*
British Columbia
2.079 (2.21 to .05)
2.11 (2.23 to 2.0005)**
2.079 (2.20 to .04)
Urban/rural residence (Reference: urban)
Rural
.034 (2.03 to .10)
.014 (2.05 to 0.08)
.012 (2.05 to .07)
.020 (2.04 to .08)
f
Survey cycle (Reference: cycle 2)
Cycle 1
Abbreviations: BMI, body mass index; CI, confidence interval; OLS, ordinary least squares.
a
Bi-variate associations between each predictor variable and BMI percentile change, with the exception of child care and province of residence, for which all categories are entered as a block.
b
Associations from single model containing all variables.
c
§ 10 hours/week of child care.
d
The two high-risk age groups were combined to ensure adequate cell size for vetting.
e
Nova Scotia and Prince Edward Island combined due to small sample size for these provinces.
f
Survey cycle refers to when child was enrolled in the study (cycle 1, enrolled in 1994; cycle 2, enrolled in 1996).
* p < .10
** p < .05
*** p < .01
6/7 years than girls in a lower household
income status (Table 3a). For boys, the
following attributes were associated with
a decrease in BMI percentile between age
2/3 years and age 6/7 years: higher
household income adequacy, single parent
Vol 33, No 1, December 2012 – Chronic Diseases and Injuries in Canada
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household, residence in Newfoundland
and residence in Alberta (Table 2b).
Among boys who were in the normal
TABLE 3A
Results of binary logistic regression analysis for girls (n = 1760), with BMI percentile change regressed on child care type, unadjusted and
adjusted for socio-demographic variables
Girls with normal BMIa at age 2/3 years (n = 912)
Predictor variable
Girls with at-risk BMIb at age 2/3 years (n = 848)
OR (95% CI) for moving into the at-risk BMI range by age OR (95% CI) for moving into the normal BMI range by age
6/7 years
6/7 years
Child care
Unadjustedc
Adjustedd
Unadjustedc
Adjustedd
0.86 (0.51 to 1.40)
0.86 (0.49 to 1.50)
1.10 (0.67 to 1.80)
0.88 (0.50 to 1.50)
e
By non-relative
By relative
1.06 (0.50 to 2.30)
0.95 (0.45 to 2.00)
0.77 (0.42 to 1.40)
0.66 (0.35 to 1.20)
Daycare centre
1.82 (0.82 to 4.00)
1.66 (0.70 to 3.90)
0.64 (0.34 to 1.20)
0.55 (0.26 to 1.20)
Household income adequacy (Reference: lower)
Middle
0.55 (0.28 to 1.10)*
0.43 (0.18 to 1.05)*
0.59 (0.30 to 1.10)
0.60 (0.28 to 1.30)
Higher
0.62 (0.31 to 1.20)
0.48 (0.18 to 1.30)
1.17 (0.64 to 2.10)
1.30 (0.61 to 2.90)
Household education (Reference: ƒ high school graduation)
Some post-secondary
1.12 (0.54 to 2.30)
1.21 (0.51 to 2.80)
1.40 (0.71 to 2.80)
1.27 (0.63 to 2.60)
Post-secondary graduation
0.71 (0.38 to 1.30)
0.77 (0.36 to 1.70)
1.50 (0.81 to 2.80)
1.36 (0.69 to 2.70)
1
0.72 (0.40 to 1.30)
0.73 (0.39 to 1.40)
0.67 (0.35 to 1.30)
0.60 (0.31 to 1.20)
2 or more
0.62 (0.32 to 1.20)
0.53 (0.25 to 1.20)
0.66 (0.31 to 1.40)
0.61 (0.28 to 1.30)
0.96 (0.45 to 2.10)
0.55 (0.19 to 1.60)
1.08 (0.56 to 2.10)
1.12 (0.46 to 2.70)
0.91 (0.37 to 2.20)
0.87 (0.34 to 2.30)
0.84 (0.29 to 2.40)
1.10 (0.38 to 3.20)
0.71 (0.33 to 1.50)
0.75 (0.33 to 1.70)
0.82 (0.35 to 1.90)
0.71 (0.29 to 1.70)
Newfoundland
1.76 (0.74 to 4.20)
1.41 (0.52 to 3.80)
0.72 (0.31 to 1.70)
0.69 (0.29 to 1.70)
Nova Scotia & Prince Edward Islandg
1.01 (0.48 to 2.10)
0.96 (0.44 to 2.10)
1.27 (0.66 to 2.40)
1.41 (0.67 to 3.00)
New Brunswick
1.76 (0.76 to 4.10)
1.64 (0.67 to 4.00)
0.84 (0.43 to 1.60)
0.91 (0.44 to 1.90)
Quebec
1.48 (0.78 to 2.80)
1.41 (0.73 to 2.80)
0.60 (0.31 to 1.20)
0.65 (0.32 to 1.30)
Manitoba
1.02 (0.31 to 3.30)
0.97 (0.29 to 3.20)
0.81 (0.41 to 1.60)
0.83 (0.39 to 1.70)
Saskatchewan
1.56 (0.76 to 3.20)
1.76 (0.82 to 3.80)
1.80 (0.88 to 3.60)
1.85 (0.81 to 4.20)
Alberta
0.92 (0.40 to 2.10)
1.03 (0.44 to 2.40)
0.81 (0.38 to 1.80)
0.87 (0.38 to 2.00)
British Columbia
0.78 (0.32 to 1.90)
0.84 (0.32 to 2.20)
1.35 (0.61 to 3.00)
1.39 (0.58 to 3.30)
1.20 (0.77 to 1.90)
1.06 (0.62 to 1.80)
0.95 (0.63 to 1.40)
1.04 (0.64 to 1.70)
1.06 (0.67 to 1.70)
1.01 (0.61 to 1.70)
0.94 (0.60 to 1.50)
1.05 (0.64 to 1.70)
Number of siblings (Reference: 0)
Number of parents in household (Reference: 2)
1
Birth weight (Reference: normal)
Low / very low (< 2500 g)
Mother’s age at birth, years (Reference: 20–34)
13–19 or 35+ (combined)f
Province of residence (Reference: Ontario)
Urban/rural residence (Reference: urban)
Rural
h
Survey cycle (Reference: cycle 2)
Cycle 1
Abbreviations: BMI, body mass index; CI, confidence interval; OR, odds ratio.
a
BMI < 85th percentile.
b
BMI § 85th percentile.
c
Bi-variate associations between each predictor variable and BMI percentile change, with the exception of child care and province of residence, for which all categories are entered as a block.
d
Associations from single model containing all variables.
e
§ 10 hours/week of child care.
f
The two high-risk age groups were combined to ensure adequate cell size for vetting.
g
Nova Scotia and Prince Edward Island combined due to small sample size for these provinces.
h
Survey cycle refers to when child was enrolled in the study (cycle 1, enrolled in 1994; cycle 2, enrolled in 1996).
* p < .10
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Vol 33, No 1, December 2012 – Chronic Diseases and Injuries in Canada
TABLE 3B
Results of binary logistic regression analysis for boys (n = 1804), with BMI percentile change regressed on child care type, unadjusted and
adjusted for socio-demographic variables
Predictor variable
Boys with normal BMIa at age 2/3 years (n = 918)
Boys with at-risk BMIb at age 2/3 years (n = 886)
OR (95% CI) for moving into the at-risk BMI range by
age 6/7 years
OR (95% CI) for moving into the normal BMI range
by age 6/7 years
Unadjustedc
Child care
Adjustedd
Unadjustedc
Adjustedd
0.73 (0.45 to 1.20)
0.75 (0.45 to 1.20)
e
By non-relative
1.01 (0.60 to 1.70)
1.47 (0.87 to 2.5)
By relative
0.60 (0.33 to 1.10)
0.68 (0.35 to 1.30)
0.84 (0.42 to 1.70)
0.78 (0.38 to 1.60)
Daycare centre
1.35 (0.60 to 3.00)
1.56 (0.63 to 3.90)
1.04 (0.46 to 2.40)
0.90 (0.38 to 2.10)
0.89 (0.40 to 2.00)
0.88 (0.35 to 2.20)
0.94 (0.49 to 1.80)
0.83 (0.38 to 1.80)
0.45 (0.22 to 0.96)**
0.51 (0.18 to 1.40)
0.87 (0.47 to 1.60)
0.73 (0.33 to 1.60)
Household income adequacy (Reference: lower)
Middle
Higher
Household education (Reference: ƒ high school graduation)
Some post-secondary
0.75 (0.37 to 1.50)
0.84 (0.39 to 1.80)
1.96 (0.97 to 4.00)*
1.89 (0.87 to 4.10)
0.52 (0.28 to 0.95)**
0.64 (0.31 to 1.30)
1.34 (0.70 to 2.60)
1.33 (0.67 to 2.60)
1
1.06 (0.56 to 2.00)
1.12 (0.59 to 2.10)
0.80 (0.50 to 1.30)
0.81 (0.47 to 1.40)
§2
1.67 (0.78 to 3.60)
1.60 (0.72 to 3.60)
0.71 (0.39 to 1.30)
0.67 (0.35 to 1.30)
1.60 (0.58 to 4.50)
1.32 (0.29 to 6.10)
0.86 (0.41 to 1.80)
0.77 (0.32 to 1.90)
0.23 (0.06 to 0.80)**
0.15 (0.03 to 0.69)**
1.51 (0.50 to 4.50)
1.18 (0.35 to 4.00)
1.14 (0.49 to 2.60)
1.15 (0.44 to 3.00)
0.90 (0.44 to 1.80)
0.97 (0.44 to 2.20)
Newfoundland
1.49 (0.61 to 3.70)
1.28 (0.47 to 3.50)
1.40 (0.64 to 3.10)
1.26 (0.56 to 2.80)
Nova Scotia and Prince Edward Islandg
1.10 (0.47 to 2.60)
0.78 (0.29 to 2.10)
0.94 (0.46 to 1.90)
0.98 (0.46 to 2.10)
New Brunswick
1.83 (0.77 to 4.4)
1.80 (0.63 to 5.10)
1.15 (0.54 to 2.40)
1.11 (0.48 to 2.60)
Quebec
1.68 (0.85 to 3.30)
1.52 (0.77 to 3.00)
1.28 (0.69 to 2.40)
1.11 (0.60 to 2.10)
Manitoba
0.89 (0.37 to 2.10)
0.79 (0.30 to 2.00)
1.16 (0.50 to 2.70)
1.04 (0.41 to 2.70)
Saskatchewan
1.20 (0.60 to 2.40)
0.98 (0.46 to 2.10)
1.54 (0.75 to 3.10)
1.62 (0.73 to 3.60)
Alberta
0.92 (0.37 to 2.30)
0.87 (0.33 to 2.30)
1.61 (0.85 to 3.00)
1.48 (0.75 to 2.90)
British Columbia
1.47 (0.67 to 3.20)
1.67 (0.74 to 3.70)
1.93 (0.92 to 4.00)*
1.73 (0.78 to 3.80)
1.20 (0.73 to 2.00)
0.97 (0.56 to 1.70)
0.85 (0.55 to 1.30)
0.75 (0.47 to 1.20)
1.15 (0.73 to 1.80)
0.88 (0.55 to 1.40)
0.94 (0.61 to 1.50)
1.00 (0.65 to 1.60)
Post-secondary graduation
Number of siblings (Reference: 0)
Number of parents in household (Reference: 2)
1
Birth weight (Reference: normal)
Low / very low [<2500g]
Mother’s age at birth (Reference: 20–34 yrs)
13–19 or 35+ (combined)f
Province of residence (Reference: Ontario)
Urban/rural residence (Reference: urban)
Rural
Survey cycle (Reference: cycle 2)
Cycle 1
Abbreviations: BMI, body mass index; CI, confidence interval; OR, odds ratio.
a
BMI < 85th percentile.
b
BMI § 85th percentile.
c
Column contains bi-variate associations between each predictor variable and BMI percentile change, with the exception of child care and province of residence, for which all categories are
entered as a block.
d
Column contains associations from single model containing all variables.
e
§ 10 hours/week of child care.
f
The two high-risk age groups were combined to ensure adequate cell size for vetting.
g
Nova Scotia and Prince Edward Island combined due to small sample size for these provinces.
h
Survey cycle refers to when child was enrolled in the study (cycle 1, enrolled in 1994; cycle 2, enrolled in 1996).
* p < .10
** p < .05
Vol 33, No 1, December 2012 – Chronic Diseases and Injuries in Canada
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8
BMI percentile range at age 2/3 years, a
low/very low birth weight was associated
with reduced odds of moving into the
at-risk BMI percentile range by age 6/7
years, relative to a normal birth weight
(Table 3b).
Discussion
We examined the association between
child care (three types) at age 2/3 years
and change in BMI between age 2/3 years
and age 6/7 years, using both OLS models
(to capture change in BMI percentile
regardless of starting point) and logistic
regression models (to capture change that
crosses a recognized threshold, the 85th
BMI percentile). Although an association
between child care and later BMI is
plausible and would have policy relevance, its existence and nature in Canada
is not known. To examine this association,
we used a data source (NLSCY) that is
well-suited to our question: the NLSCY is
a longitudinal, nationally representative
survey that contains information on
several types of child care, height and
weight data from multiple time points,
and sufficient sample size to stratify by
sex. While other studies included sex as a
covariate,16–19,21–22 ours is unique in that
we examined the child care–BMI relationship in boys and girls separately.
For boys, care by a non-relative, for
example, by a nanny, a baby-sitter, an
informal day-home, a friend, or a neighbour, was associated with an increase in
BMI percentile between age 2/3 and age
6/7 years. Although the reason for the
association is not known, the appearance
of this main effect in boys but not girls
brings to mind a plausible role of nonrelative caregiver behaviour such as providing sugary treats as a way of placating
energetic boys or distracting them with
television, thereby increasing sedentary
behaviour. Although a statistically significant effect of this care type was not
observed in logistic regression models,
we note that the direction of the effect in
the logistic regression model in boys is
consistent with the OLS finding (Table 3b,
adjusted models, odds ratio (OR) for boys
with normal BMI percentile at age 2/3
moving into the at-risk BMI percentile by
age 6/7 was 1.47, whereas OR for boys
with at-risk BMI percentile at age 2/3
years moving into the normal BMI percentile by age 6/7 was 0.75). For girls, no
main effects of child care on BMI percentile were apparent; however, the model
containing interaction terms revealed that
care by a non-relative was associated with
an increase in BMI percentile between age
2/3 years and age 6/7 years among girls
from low-income adequacy households.
One possible explanation for this finding
is that families with lower income, who
have a financial imperative to work outside the home, may have a limited array of
child care options from which to choose,
and in some cases may have to resort to
care options that are sub-optimal in terms
of nutrition and opportunities for physical
activity / active play. It is not known why
the interaction effect was not observed
in boys. The child care effects observed
(main effect of care by non-relative in
boys, interaction between care by nonrelative and low income adequacy status
in girls) differed only negligibly between
the adjusted and the unadjusted models,
suggesting that the socio-demographic
correlates included were neither confounders nor mediators.
Although existing studies on child care
and BMI vary in terms of population, age
group, duration, and country, we can
nonetheless comment on how our findings
fit with and build on the existing literature. Several studies found an association
between various types of ‘‘informal’’ care
and weight gain / increase in BMI.17,18,20 :
Our findings are consistent with these
effects, and build on them. We identified
non-relatives as a pertinent dimension of
informal care with relevance to BMI in
the Canadian context. The effect of informal care on increased risk of overweight
observed by Pearce et al.20 was specific
to children from more advantaged backgrounds, while we observed that care by a
non-relative was associated with increasing BMI percentile among girls from
a lower income adequacy household.
Collectively, findings from our study and
others indicate that future research on
the topic should take a nuanced view of
informal child care – including whether
the caregiver is a relative or not, the socioeconomic circumstances of the child’s
family and the child’s gender.
$
9
Our findings are consistent with those of
Maher et al.,17 Benjamin et al.18 and Kim
et al.19 (all based on samples of U.S.
children) in terms of finding no association between formal centre-based care
and BMI outcomes. Although on the one
hand it is good news that formal daycare
does not appear to have a clear adverse
effect on BMI, the absence of effect (particularly in the logistic regression models)
also suggests a potentially under-exploited
opportunity for health promotion. As
noted, the number of young children in
Canada with mothers in the paid labour
force far exceeds the number of spots
available in formal high-quality, affordable and accessible child care settings.5
Many families accordingly rely on other
care options, including care by a nonrelative, which we observed to have an
adverse effect on later BMI. Were it
more widely available and accessible, it
is plausible that at least some of the
families currently using informal care
options would opt for the formal highquality daycare. To the extent that this
care is indeed higher in quality, it could
provide a more favourable environment
for BMI and other outcomes. A strong case
for investment in formal centre-based care
requires ongoing high-quality research
that examines the implications of formal
centre-based care (including variants and
attributes thereof) for diverse outcomes
(health, social, economic) at different
levels (child, family, community) over
the short and particularly the longer
term.29–31
Limitations
Our study suffers from some methodological limitations. One issue is the relatively
large amount of missing data on the BMI
variable. Our comparison of respondents
with missing and non-missing BMI data
indicated clear socio-demographic differences between the groups, though it is
reassuring that the groups did not differ
dramatically in terms of child care use
(and not at all in the case of girls). Second,
because all of our baseline data were
reported at age 2/3 years, it is impossible
to ascertain that BMI at age 2/3 had not
already been affected by child care at age
2/3; however, we would argue that the
nature of these associations is such that
Vol 33, No 1, December 2012 – Chronic Diseases and Injuries in Canada
immediate influence is unlikely. A third
and particularly important limitation of
the data is the parent-reported nature of
children’s heights and weights. The errors
that parents commit in reporting height
and weight of their children tend to result
in overestimation of BMI, and these
errors are larger for younger children and
decline with increasing age.32,33 One way
to explore the potential implications of
reporting inaccuracy for our findings is to
examine correlates of reporting inaccuracy; in particular, socio-demographic
attributes that are likely to be associated
with child care use. Shields et al.33
examined the association between parental education and reporting inaccuracy
among children aged 6 to 11 years in
the Canadian Health Measures Survey
(CHMS): the CHMS is the only population-based dataset of Statistics Canada
that contains both measured and parentreported height and weight data for the
same children. They found no association
between parent education and reporting
inaccuracy. Although the age group in
the CHMS is older than our age group
of interest (unfortunately, no Canadian
national population-based data are available that contain both measured and
parent-reported height and weight data
for children of pre-school age), the findings of Shields et al.33 support the view
that parents’ reports of their child’s
height and weight are not irredeemably
biased by parents’ education (one aspect
of socio-economic circumstances), which
heightens our confidence in our findings
to some extent.
outcomes specifically, measured height
and weight data are essential.
Emery JC, Ferrer AM. Marriage market
imbalances and labor force participation
of Canadian women. Rev Econ Household.
2009;7:43–57.
8.
Mindlin M, Jenkins R, Law C. Maternal
employment and indicators of child health:
a systematic review in pre-school children
in OECD countries. J Epidemiol Community
Health. 2009;63:340–50.
9.
Anderson PM, Butcher KF, Levine PB.
Maternal employment and overweight
children. J Health Econ. 2003;22:477–504.
Acknowledgements
This project was funded by grant #8202008-1019 from the Social Sciences and
Humanities Research Council of Canada
(SSHRC) awarded to McLaren, Auld and
Emery and an Establishment Grant from
Alberta Innovates – Health Solutions
awarded to McLaren.
L. McLaren is supported by a Population
Health Investigator Award from Alberta
Innovates – Health Solutions. D. Dutton is
supported by a Doctoral Traineeship from
the Canadian Population Health Intervention Research Network (PHIRNET). M.C.
Auld is supported by a Health Scholar
Award from the Alberta Innovates –
Health Solutions. J.C. Herbert Emery
holds the Svare Professor in Health
Economics at the University of Calgary.
Conflict of interest: none.
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In summary, among children in the
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formal child care for child social and
health outcomes,5,29–30 and the potentially
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significant policy relevance, for which
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obesity in the early years? Findings from
the UK Millennium Cohort Study. Int J
Obes. 2010;34:1160–8.
21. Rapp K, Schick KH, Bode H, Weiland SK.
Type of kindergarten and other potential
determinants of overweight in pre-school
children. Public Health Nutr. 2005;8:642–9.
22. Gubbels JS, Kremers SP, Stafleu A,
Dagnelie PC, de Vries NK, van Buuren S,
et al. Child-care use and the association
with body mass index and overweight in
children from 7 months to 2 years of age.
Int J Obes. 2010;34:1480–6.
29. Baker M. Innis Lecture: universal early
childhood interventions: what is the evidence base? Can J Econ. 2011;44:1069–105.
30. Barnett WS. Effectiveness of early educational intervention. Science. 2011;333:
975–8.
31. D’Onise K, Lynch JW, Sawyer MG,
McDermott RA. Can preschool improve
child health outcomes? A systematic
review. Soc Sci Med. 2010;70:1423–40.
32. Phipps SA, Burton P, Lethbridge L, Osberg
L. Measuring obesity in young children.
Can Public Policy. 2004;30:349–64.
33. Shields M, Connor Gorber S, Janssen I,
Tremblay MS. Obesity estimates for
children based on parent-reported versus
direct measures. Health Rep. 2011;22:47–
58. Statistics Canada, Catalogue no. 82-003XPE.
23. Healthy Weight – it’s not a diet, it’s a
lifestyle! [Internet]. Atlanta (GA): Centers
for Disease Control and Prevention [cited
2011 Jun]. Available at: http://www.cdc.
gov/healthyweight/assessing/bmi/childrens
_bmi/about_childrens_bmi.html
24. Growth Charts [Internet]. Atlanta (GA):
Centers for Disease Control and Prevention; 2002 May [cited 2011 Jun]. Available
at: http://www.cdc.gov/GrowthCharts
25. Dieticians of Canada; Canadian Paediatric
Society; College of Family Physicians of
Canada; Community Health Nurses Association of Canada. The use of growth charts
for assessing and monitoring growth in
Canadian infants and children. Can J Diet
Pract Res. 2004;65:22–32.
26. Ball GD, Willows ND. Definitions of pediatric obesity. CMAJ. 2005;172:309–10.
27. Dubois L, Girard M. Early determinants of
overweight at 4.5 years in a populationbased longitudinal study. Int J Obes.
2006;30:610–7.
28. Power C, Parsons T. Overweight and
obesity from a life course perspective.
In: Kuh D, Hardy R, eds. A life course
approach to women’s health. Oxford (UK):
Oxford University Press; 2002. p. 304–28.
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Vol 33, No 1, December 2012 – Chronic Diseases and Injuries in Canada
Self-management, health service use and information seeking
for diabetes care among recent immigrants in Toronto
I. Hyman, PhD (1, 2); D. Patychuk, MA (3); Q. Zaidi, MSc, MSW (4); D. Kljujic, MA (5); Y. B. Shakya, PhD (1, 6);
J. A. Rummens, PhD (7, 8, 9); M. Creatore, MSc (10); B. Vissandjee, PhD (11)
This article has been peer reviewed.
Abstract
Introduction: Our objective was to explore self-management practices, health services
use and information-seeking for type 2 diabetes care among adult men and women from
four recent immigrant communities in Toronto.
Methods: A structured questionnaire was adapted for the Canadian context and translated
into 4 languages. A total of 184 participants with type 2 diabetes—130 recent immigrants
and 54 Canadian-born—were recruited in both community and hospital settings.
Results: Recent immigrants were significantly less likely than the Canadian-born group
to perform regular blood glucose and foot checks and significantly more likely than the
Canadian-born group to be non-smokers, participate in regular physical activity and
reduce dietary fat. Recent immigrants were significantly less likely than the Canadianborn group to use a specialist, alternative provider and dietician and less likely to
report using dieticians, nurses and diabetes organizations as sources of diabetes-related
information. Important differences were observed by sex and country of origin.
Conclusion: Findings suggest that diabetes prevention and management strategies for
recent immigrants must address linguistic, financial, informational and systemic barriers
to information and care.
Keywords: type 2 diabetes, self management, utilization of health services, informationseeking, immigrants, racialized groups
Introduction
About 5% of the Canadian population is
living with type 2 diabetes,1 and this
proportion is expected to increase to
11% by 2020.2 The prevalence of diabetes
is also rapidly increasing among Canadian
immigrants,3 with pronounced variation
across ethnicity and country of origin.4,5
Recent immigrants and refugees from
South Asia, Latin America, the Caribbean
and sub-Saharan Africa have a two- to
three-times greater risk of developing
diabetes than their counterparts from
western Europe or North America.6
Moreover, this elevated risk begins earlier
in life (i.e. from 20 to 40 years of age),
compared with immigrants from Europe
and North America and Canadian-born
populations.6
Evidence suggests that recent immigrants do
not always benefit from diabetes management programs7,8 due to informational,
financial, linguistic, cultural and systemic
barriers to health and diabetes care.9,10
Adherence to self-management activities
and the use of health services for diabetesrelated information and care varies across
ethno-racial populations and among those
who integrate to a host society.4,11–14
Our study reports findings related to selfmanagement practices, health services
use and help-seeking patterns among
immigrants with diabetes in Canada.* As
this was an exploratory study, no hypotheses were specified; however, the literature suggests that seeking information
about diabetes and diabetes care may be
compromised among recent immigrants.
In particular, our key research question
was how the migration process and
being new to Canada affects diabetes
* In 2008, the Public Health Agency of Canada (PHAC) commissioned a survey in two large Canadian urban centres (Toronto and Montreal) to explore the experiences of recent immigrants
(less than 10 years in Canada) with type 2 diabetes. This research was part of an international collaborative study on migration and diabetes co-ordinated by the International Centre for
Migration and Health in Geneva, Switzerland.
Author references:
1. Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
2. Cities Centre, University of Toronto, Toronto, Ontario, Canada
3. Steps to Equity, Toronto, Ontario, Canada
4. Health Policy and Management, York University, Toronto, Ontario, Canada
5. Community Health Systems Research Group, The Hospital for Sick Children, Toronto, Ontario, Canada
6. Access Alliance Multicultural Health and Community Services, Toronto, Ontario, Canada
7. Child Health Evaluative Sciences, The Hospital for Sick Children, Toronto, Ontario, Canada
8. Institute of Medical Sciences, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
9. CERIS - The Ontario Metropolis Centre, Toronto, Ontario, Canada
10. St. Michael’s Hospital, Toronto, Ontario, Canada
11. Faculté des sciences infirmières - School of Nursing, Université de Montréal, Montréal, Quebec, Canada
Correspondence: Ilene Hyman, Cities Centre, University of Toronto, 455 Spadina Ave., Suite 400, Toronto, ON M5S 2G8; Tel.: 416-978-0708; Fax: 416-978-7162; Email: [email protected]
Vol 33, No 1, December 2012 – Chronic Diseases and Injuries in Canada
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self-management and care. Our findings
have implications for the development of
health- and community-based interventions to enhance informational outreach,
support self-management activities and
facilitate access to diabetes care for newcomer populations in Canada.
Methods
The research team adapted a survey
instrument developed by the International
Centre for Migration and Health (ICMH)
to collect information on the experiences
of immigrants with type 2 diabetes. This
involved extensive consultation with
representatives of immigrant-serving
organizations, diabetes education centres
and community health centres. The final
questionnaire was pre-tested and translated into four languages: Mandarin,
Tamil, Bengali and Urdu. Ethics approval
was obtained from University of Toronto,
Mount Sinai Hospital and St. Michael’s
Hospital, in Toronto, Ontario.
Sample sizes and eligibility criteria for age
and length of stay were pre-established by
the Public Health Agency of Canada in
order to ensure consistency with those
used by other countries participating in
the ICMH migration and diabetes study.
The study population consisted of recent
immigrant (less than 10 years in Canada)
and Canadian-born adults (aged 35 to 64
years) with self-reported type 2 diabetes.
This temporal definition of recent immigrants has been used in other provincial
and national studies of Canadian immigrants.15–17 Four newcomer communities
were targeted based on the following
criteria: risk of developing diabetes postmigration; current immigration trends;
the presence of social, economic and
linguistic barriers to care; and pre-existing
relationships with the research team that
would facilitate recruitment and optimize
participation.
We used several techniques to recruit
participants. Census data from 2006 were
used to identify census tracts in the
{
Greater Toronto Area where more than
half of the population spoke one of the
four study languages. These neighbourhoods were targeted for information
campaigns about the study, and participants were recruited via posters in
buildings, stores and community centres.
A convenience sample of recent immigrant participants was also recruited
via information sharing at community
health centres, diabetes education centres
and immigrant-serving organizations. To
recruit Canadian-born study participants
from across the city, we relied on existing
partnerships with community health
centres, diabetes education centres and
hospital-based diabetes clinics located
across the city as well as the Canadian
Diabetes Association. Interested participants called the research co-ordinator
first and were screened to determine their
eligibility for the study. Others were
approached in the clinics by the research
co-ordinator or peer researchers.
All potential participants were then contacted by the project co-ordinator or a peer
researcher fluent in their language who
explained the aims of the study as well
as the risks and benefits of participation.
If the potential participant agreed to
participate, an interview was arranged at
a mutually convenient time and place.
Consent forms were translated into each
of the study languages. The interviews
were conducted in the participant’s language of choice using computer-assisted
personal interviewing. This methodology
for data collection was chosen because of
its great potential to eliminate or minimize
human errors, contribute to standardization of survey administration, enhance the
efficiency of data collection and improve
general data quality and validity. It also
allows for more complex questionnaire
structures and flexibility in design by
incorporating skip patterns and automatic
fill-in options. Since respondents cannot
record implausible or ‘‘out-of-range’’
responses, all inconsistencies can be
identified and resolved during the interview.18,19 SPSS Data Entry Builder 4.0
software (SPSS Inc., Chicago, IL, US;
2003) was used to create the computerassisted personal interviewing. Two
members of the research team (AR, DK)
developed this methodology for the Wave
II data collection of the New Canadian
Children and Youth Study (NCCYS) and
have since used it—and shared it—across
multiple projects.
Measures
Apart from age, which was treated as
continuous, many of the sociodemographic variables in the survey were
dichotomized due to small sample sizes:
sex (male, female), current marital status
(married/living with partner, not married), level of education (no university
degree, university degree or higher),
employment (employed, not employed),
type of employment (permanent, temporary) and job reflecting education and
credentials (yes, no). Income was calculated from the estimate of household
income from all sources and number
of people dependent on household
income,20 and later dichotomized as low
income (yes, no). Racialized status{ was
determined by asking participants with
which ethnic or racial group they best
identified, with responses dichotomized
(racialized, non-racialized) according to
their self-response.
Variables regarding self-management
practices were based on behaviours
defined in the research literature as
important to self-management.22 The
survey participants were asked questions
about the frequency with which their
blood glucose is checked (‘‘How often do
you usually have your blood checked for
glucose or sugar either by yourself or by a
family member or friend? Yes daily/
weekly glucose check, no’’); the frequency
that their feet are checked for sores or
irritations (‘‘How often do you usually
have your feet checked for any sores or
irritations by yourself or a family member
or friends? Yes daily/weekly foot check,
no’’); their smoking status (‘‘At the
The research team adopted the term racialized status (as opposed to visible minority status) in this project to acknowledge the fact that racialization is a social process whereby certain groups
come to be designated as different and consequently subjected to differential and unequal treatment.21 Unlike the term visible minorities, which Canada’s Employment Equity Act defines as
‘‘non-Caucasian in race or non-white in colour,’’ racialized groups makes clear that race is not an objective biological fact, but rather a social and cultural construct that potentially exposes
individuals to prejudicial attitudes and discriminatory treatment.
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Vol 33, No 1, December 2012 – Chronic Diseases and Injuries in Canada
present time, do you smoke cigarettes?
Yes, no’’); their physical activity (‘‘Do you
usually do some physical activity for at
least 30 minutes per day? Yes, no’’); and
their diet (‘‘During the past 12 months, to
what extent have you tried to reduce
carbohydrates (pasta, bread)? A great deal
or moderately, only a little or not at all’’).
Items regarding use of health services
included eye examinations (‘‘Have you
ever had an eye exam for diabetes where
the pupils of your eyes were dilated?
Yes, no’’); checking for sores or irritations (‘‘In the past 12 months, has a health
care professional checked your feet for
any sores or irritations? Yes, no’’); and
blood indicators (‘‘In the past 12 months,
has a health care professional tested
you for hemoglobin A1C? How many
times?’’ Every 3 months, not every three
months).{
Questions about information-seeking practices included, ‘‘Who provides you with
information about managing your diabetes
(physician, dietician, nurse, family or
friends, diabetes association, Internet)?
Participants were able to indicate more
than one source. The survey instrument
also included a series of questions on
barriers to accessing health care including
finding a doctor who was accepting new
patients, long waits to see a family doctor
or specialist, not knowing where to go for
health care, linguistic barriers, finding
child care, transportation problems, time
off work, gender issues and costs not
covered by health insurance.
Statistical analyses
Bivariate analyses (Student’s t tests, Chisquare tests) were used to compare the
recent immigrant and Canadian-born
study groups, and to explore possible
variations within the recent immigrant
group itself by country of origin and sex.
Statistical significance was set at p < .05.
Results
Survey data was collected from 184
participants with type 2 diabetes using
{
convenience sampling. Of these, 130
were recent immigrants from Sri Lanka
(n = 30), Bangladesh (n = 35), Pakistan
(n = 35) and China (n = 30), and 54 were
Canadian-born respondents. In the recent
immigrant group, 58 (45%) were men and
72 (55%) were women, compared with 28
men (52%) and 26 women (48%) in the
Canadian-born group. All participants in
the recent immigrant group were racialized. About 76% of the Canadian-born
group was non-racialized, an identical
proportion to that reported among the
Canadian-born population in Toronto.23
Demographic information describing the
study participants is shown in Table 1.
Recent immigrants were three times more
likely to be married than the Canadianborn respondents, but less likely to have
a permanent job or a job that reflected
their educational credentials and experiences. There were no significant differences between groups in terms of
mean age, education or employment
status. The incidence of low income was
notably high among recent immigrants
(36%) as well as those who were
Canadian-born (42%), but the difference
between the two groups was statistically
nonsignificant. Some significant differences were, however, noted within the
recent immigrant group by sex and
country of origin. For example, recent
immigrant women had completed lower
levels of education, were less likely
to be employed and were less likely to
be permanently employed than recent
immigrant men.
Figure 1 shows data on the five diabetes
self-management variables by migration
status. The recent immigrant group was
less likely than the Canadian-born group
to perform regular glucose checks (76.2%
vs. 90.8%, p < 0.001) and foot checks
(57.0% vs. 75.9%, p < .001). Recent
immigrants were more likely than the
Canadian-born to be non-smokers
(10.0% vs. 35.2%, p < .001), participate
in regular physical activity (81.5% vs.
66.7%, p < .05) and reduce carbohydrates moderately or a lot (76.2% vs.
51.9%, p < .001). Statistically significant
differences by sex and country of origin
were also observed. Recent immigrant
women were significantly less likely than
recent immigrant men to be smokers,
TABLE 1
Demographics: recent immigrant and Canadian-born study groups
Recent immigrants
(N = 130)
Canadian-born
adults (N = 54)
p value
51.2
52.3
NS
89.2
24.1
< .001
52.3
35.2
NS
Yes
33.8
29.6
NS
Yes
60.0
94.4
< .01
Yes
41.3
0
< .01
36.3
41.9
NS
Mean age, years
Significant differences
By sex
(p < .05)
By country of
origin (p < .05)
Yes
Marital status
Married, %
Education
University or higher, %
Yes
Employment
Unemployed, %
Type of employment
Permanent, %
Job reflects credentials
No, %
Income
Low income, %
Race
Racialized, %
100
24.1
Abbreviation: NS, non-significant.
The time frames indicated are the minimum periods recommended for diabetes care. For example, if a problem such as a retinopathy is found, more regular eye exams would be indicated.
Vol 33, No 1, December 2012 – Chronic Diseases and Injuries in Canada
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whereas recent immigrants from Pakistan
were more likely to check their glucose
and feet and engage in regular physical
activity than recent immigrants from other
countries (data not shown).
FIGURE 1
Diabetes self-management practices by recent immigrant and Canadian-born study groups
100
90
80
70
Figure 2 shows data on the utilization of
health care professional services for diabetes care. Similar proportions of the
recent immigrant group and the Canadianborn group ever had an eye exam (66.2%
vs. 75.9%) and had their hemoglobin
A1C level checked every three months
(17.1% vs. 24%). However, recent immigrants were more likely to have never
had a foot exam compared with the
Canadian-born participants in our study
sample (60.0% vs. 33.3%, p < .001).
Table 2 presents data on the reported
usual sources of diabetes care and information. While both groups reported using
general practitioners or family physicians
as their usual source of health care, recent
immigrants were significantly less likely
to consult a specialist (24.6% vs. 40.7%,
p < .05), alternative health care provider
(0.8% vs. 7%, p < .05) or dietician
(19.2% vs. 38.9%, p < .01). Some significant differences were observed by sex
and country of origin. Recent female
immigrants were, for example, more likely
to use a dietician than recent male
immigrants (data not shown).
60
50
40
Recent immigrant
30
Canadian-born
20
10
0
% daily/weekly
glucose
check**b
% daily/weekly
foot
check**a,b
a
Significant differences by sex.
b
Significant differences by country of origin.
% regular
physical
activity*
% reducing
carbohydrates
moderately or a
lot**
*p < .05.
**p < .001.
to see doctors or specialists, a lack of
information on where to go, linguistic
barriers, child care issues, difficulties
finding a doctor of the same sex, and
dealing with costs not covered by insurance (data not shown). Several of these
barriers were more significant for recent
immigrant women compared with recent
immigrant men.
Discussion
This survey was the first in Canada to
collect information on the experiences of
FIGURE 2
Use of health services for diabetes care by recent immigrant and Canadian-born study groups
80
Although both groups reported that
physicians were their primary source of
information on diabetes, compared with
the Canadian-born respondents, recent
immigrants were significantly less likely
to report using dieticians (24.6% vs.
40.7%, p < .05), nurses (11.5% vs.
24.1%, p < .05) and diabetes associations
(2.3% vs. 24.1%, p < .001) as sources of
information. They were also significantly
more likely to use family (46.9% vs.
27.8%, p < .05) and friends (39.2% vs.
13.0%, p < .001). There was no statistically significant difference between groups
regarding Internet use for this purpose
(28.5% vs. 29.6%).
70
60
50
40
Recent immigrant
30
Canadian-born
20
10
0
% eye exam (ever)a,b
When asked about the types of barriers
experienced in accessing health care,
recent immigrants reported significantly
more problems than did their Canadianborn counterparts, indicating long waits
% smoking**b
% foot exam (never)*b
% AIC (every 3 months)
Abbreviation: AIC, hemoglobin A1C.
a
Significant difference by sex.
b
Significant differences by country of origin.
* p <.001.
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Vol 33, No 1, December 2012 – Chronic Diseases and Injuries in Canada
TABLE 2
Sources of diabetes health care and information for recent immigrant and Canadian-born
study groups
Recent immigrants
(N = 130)
Canadian-born
(N = 54)
p value
Significant differences
By sex
By country
of origin
Usual source of care, %
GP or FP
95.4
85.3
< .1
Specialist
24.6
40.7
< .05
Social worker
2.3
1.9
NS
Alternative health care provider
0.8
7.4
< .05
Dietician
19.2
38.9
< .01
Nurse educator
12.3
22.2
NS
Yes
Yes
Yes
Main source of information, %
MD
89.2
96.3
NS
Dietician
24.6
40.7
< .05
Nurse
11.5
24.1
< .05
Social worker
5.4
0
NS
Family
46.9
27.8
< .05
Friends
39.2
13.0
< .001
2.3
24.1
< .001
28.5
29.6
NS
Diabetes associations
Internet
Yes
Yes
Yes
Among the differences that were observed
between recent immigrant and Canadianborn adults with diabetes were differences
in type of employment and underemployment. This is consistent with the literature
documenting differences in these employment patterns between recent immigrant
and Canadian-born individuals.24 Furthermore, racialized Canadians (immigrant
and Canadian-born) are more likely to be
unemployed and less likely to have
This study identified informational and
systemic barriers to health care faced by
recent immigrants with diabetes, particularly for those from non-European
backgrounds. Several other studies indicated that racialized Canadians, as most
recent immigrants are, are less likely to
use preventive, chronic and specialist
health services than the Canadian-born
population.9,33–34
permanent employment than non-racialized Canadians.21,25 Precarious status can
have a negative impact on health care
access particularly since it prevents access
to insured services.26,27 The fact that the
unemployment rate among the Canadianborn group in our study (29.6%) was
higher than that of the Canadian population as a whole is likely because the study
population was composed of people with
diabetes, a condition that has been shown
to have a significant negative impact on
employment probabilities.28 In addition,
diabetes is more prevalent in low-income
populations.
It is possible that differences in the
severity of diabetes between the recent
immigrant and Canadian-born study
groups might account for differences in
self-management and health services use.
However, both groups reported similar
rates of under-control diabetes and of
gestational diabetes. Rates of obesity (as
determined by BMI and waist circumference) were significantly higher in the
Canadian-born group compared with the
recent immigrant group, and yet the latter
reported more problems associated with
their diabetes than did the Canadian-born
group. Multivariate analyses are called
for to examine in greater detail demographic and other risk factors associated
with self-management practices, access to
diabetes care and information seeking,
and possible variations by sex and country
of origin.
In terms of self-management practices, the
differences between recent immigrants
and the Canadian-born groups were less
clear cut. Recent immigrants were less
likely to perform regular glucose or foot
checks than the Canadian-born population. This suggests that recent immigrants
may be experiencing informational barriers regarding optimal diabetes care.
In our study group, recent immigrants
with diabetes were less likely than
their Canadian-born counterparts to use
tobacco and more likely to engage in
It is also possible that our findings reflect
differences in racialized status rather than
newcomer status since all of the recent
immigrants in our study were racialized.
Newcomer status, racialized status, country of origin, sex and other social determinants are all important and intersecting
predictors of self-management and access
to diabetes information and care that need
to be considered by health care providers
and decision makers in developing culturally and contextually sensitive models of
diabetes care.
Yes
Abbreviations: FP, family physician; GP, general practitioner; MD, medical doctor; NS, non-significant.
recent immigrants with diabetes in their
own language. We purposefully sampled
high-risk newcomer populations and, with
our recruitment strategies, we most likely
ended up oversampling individuals from
low-income backgrounds. This was not
intentional but simply reflects the economic realities of recent immigrants. As
the proportion of low income was similarly high (over one-third) among both
recent immigrant and Canadian-born
study groups, our analyses were able to
identify some differences, over and above
absolute income, regarding demographics,
self-management practices, the use of
health services information and information seeking.
physical activity and healthy eating, positive practices that need to be encouraged
and supported as an integral part of
diabetes care. However, other research
suggests that, whereas new immigrants
are significantly less likely to smoke than
the Canadian-born population, they are
also less likely to engage in physical
activity.29–32
Vol 33, No 1, December 2012 – Chronic Diseases and Injuries in Canada
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These issues will be further addressed in
the second phase of our research in which
we examine diabetes outcomes among
recent, non-recent and Canadian-born
members of the Black Caribbean community with type 2 diabetes.
Conclusion
While our results are not generalizable to
the entire newcomer immigrant population due to small sample size and nonrandom sampling, these findings have
important implications for the organization and delivery of diabetes prevention
and management strategies in newcomer
communities, particularly those that are
economically marginalized and at high
risk of developing diabetes. Diabetes
prevention strategies must continue to
address the social determinants of health,
especially precarious employment, which
may contribute to inequities in health and
access to care. Health service delivery
policies and strategies need to recognize
the unique needs and barriers facing
newcomer communities as a priority
population that require financial, linguistic and gender-sensitive supports. The
strong reliance of recent immigrants on
family and friends for diabetes-related
information suggests that raising community awareness and capacity with respect
to diabetes is critical. Community information sharing networks and communitybased informal and formal support
systems should be considered as the
foundation for diabetes prevention and
health promotion strategies.
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Research in Canada. Vancouver (BC): UBC
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11. Shah BR. Utilization of physician services
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12. Gary TL, McGuire M, McCauley J, Brancati
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glycemic control for African American and
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13. Mah CA, Soumerai SB, Adams AS, RossDegnan D. Racial differences in impact of
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14. Robbins JM, Vaccarino V, Zhang H, Kasl
SV. Excess type 2 diabetes in AfricanAmerican women and men aged 40–74
and socioeconomic status: evidence from
the Third National Health and Nutrition
Examination Survey. J Epidemiol Community Health. 2000;54(11):839–45.
15. Chen J, Ng E, Wilkins R. The health of
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16. Vissandjee B, DesMeules M, Cao Z, Abdool
S, Kazanjian A. Integrating ethnicity and
immigration as determinants of Canadian
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.com/1472-6874/4/s1/s32
17. Hyman I, Jackson, B. The healthy immigrant effect: a temporary phenomenon?
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18. Randolph JJ, Virnes M, Jormanainen I,
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Assessing the reach of nicotine replacement therapy as a
preventive public health measure
S. J. Bondy, PhD (1, 2); L. M. Diemert, MSc (2); J. C. Victor, MSc (2, 3); P. W. McDonald, PhD (2, 4);
J. E. Cohen, PhD (1, 5)
This article has been peer reviewed.
Abstract
Introduction: Access to Nicotine Replacement Therapy (NRT) is a key public health
intervention to reduce smoking. We assessed prevalence and correlates of use of NRT in
Ontario, where NRT is available without prescription.
Methods: Participants were a representative sample of 2262 adult smokers in the
Ontario Tobacco Survey cohort. Prospectively measured use of NRT over a 6-month
period was reported in relation to smoking behaviour and history, attempts to quit,
receipt of other supports for cessation supports and attitudes toward NRT.
Results: Overall, 11% of smokers used NRT over the six-month follow-up period.
Prevalence was 25% among the 27% of smokers matching clinical guidelines that
recommend NRT as a therapeutic option, and low among smokers not trying to quit.
Conclusion: With increasing accessibility of NRT, further surveillance and research are
warranted to determine the impact of the reach and benefits of NRT, considering both
the general and targeted smoking populations.
Keywords: smoking cessation, nicotine, evidence-based medicine, population surveillance
Introduction
In trials, nicotine replacement therapy
(NRT) nearly doubles the likelihood of
smoking cessation,1–3 and so has the
potential to reduce the disease burden
from tobacco.4 Ensuring access to NRT is
a required public health intervention for
all nations, including Canada, that have
signed the World Health Organization
Framework Convention on Tobacco Control.5,6 Several jurisdictions (e.g. Canada,
United States, United Kingdom, Australia
and much of Europe) have made NRT
available over the counter (OTC) without
prescription, while others propose to do
the same.
Several authors have stated that measures to make NRT more available have
increased its use,7,8 while others argue it
is still underutilized.9–11 However, few
reports have described uptake of NRT at
population levels where these have been
made available OTC.12–14 The cost of
NRT in Canada has been described both
as a serious barrier15 and a contribution to
inequality in access to effective cessation
services.16 New publicly funded programs
are being considered and enacted to
increase access and use of this treat-
ment.17 The effectiveness of making NRT
readily accessible should be evaluated
with quantitative surveillance data on the
size of the ideal target population as well
as the proportion of the population
reached by the intervention.18 These data
have not been available in Canada.
This report addresses a gap in knowledge
about the size of the population of
smokers representing unmet need for
increased use of NRT in Ontario. There is
some controversy about whether all, or
only specific, smokers should be encouraged to use NRT, and if medication is
over-promoted to smokers who do not
need it to quit.19 Therefore, we report on
prevalence of NRT use in all smokers and
those matching de jure guidelines applied
in programs providing publicly funded
NRT in Ontario20 and elsewhere1,21 to
quantify reach of this preventive measure
in smokers representing targeted and not
targeted users. Targeting criteria used are
drawn from evidence-based reviews,22
including Cochrane reports 1,2 and metaanalyses.23,24 These have concluded that
there is strong evidence of the benefit of
NRT for smokers who are both nicotine
dependent (largely defined as consuming
more than 10 to 15 cigarettes per day) and
motivated to quit smoking.1,2 It is also
recommended as a best practice that NRT
users receive behavioural counselling, to
achieve the additive effects of both interventions.1,2,22 Authors who advocate that
NRT is suited to all smokers without
restrictions8,11,25 argue that NRT may be
effective without clinical help and that
Author references:
1.
2.
3.
4.
5.
Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
Ontario Tobacco Research Unit, University of Toronto, Toronto, Ontario, Canada
Institute for Clinical Evaluative Sciences, Toronto, Ontario, Canada
School of Public Health and Health Systems, University of Waterloo, Waterloo, Ontario, Canada
Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States
Correspondence: Susan Bondy, Dalla Lana School of Public Health, 6th Floor, 155 College Street, Toronto, ON M5T 3M7; Tel.: 416-978-0141; Fax: 416-978-8299;
Email: [email protected]
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Vol 33, No 1, December 2012 – Chronic Diseases and Injuries in Canada
the number of cigarettes smoked per day
may not correlate with the presence or
severity of withdrawal symptoms targeted
by the medication or the perceived need
for the medication.11,24–33 Others have
suggested there may be increased use of
NRT for reasons other than quitting (e.g.
to postpone quitting or to cut down but
continue smoking), and they have indicated a need to monitor such potential
trends.34–38
Evidence for the effectiveness of NRT
obtained OTC also remains weaker than
for clinical settings. This will depend on
who uses it and how it is used, which
makes patterns of NRT use important to
monitor.39
Methods
Study population and design
We conducted our research in Ontario,
Canada, a province with a comprehensive
Tobacco Control Strategy. Throughout the
study period, NRT patch and gum forms
were readily available OTC at pharmacies,
grocery stores and convenience stores. No
other forms of NRT (e.g. inhaler, lozenge)
were licensed for use, and NRT products
were licensed for use in immediate cessation (i.e. not to be used while still smoking
or quitting gradually). Most OTC products
were paid for privately40 and not covered
in universal drug benefits.
Data were from the Ontario Tobacco
Survey, a population-representative telephone survey and panel study of adult
smokers41,42 recruited from July 2005
through June 2007 (for whom NRT attitude questions were included in the interview). Of 2681 smokers at baseline (daily
or occasional smokers who had smoked
within 30 days and 100 or more cigarettes
in their lifetime), 2262 had complete baseline and first six-month follow-up data
(84.4% retention). Approximately 12% of
the sample were studied during a time
when they could have been eligible for a
free, government-funded NRT distribution
program.20
The University of Toronto and the
University of Waterloo provided ethical
approval to conduct and use the data from
the Ontario Tobacco Survey.
Study variables
Respondents were asked at baseline if they
had ever or never previously used NRT. At
the six-month interview, respondents
were asked if they had used either the
nicotine patch, gum or inhaler in the
preceding six months ‘‘to quit or reduce
smoking.’’ We defined six-month period
prevalence of NRT use as any use of NRT
during follow-up, regardless of history.
A number of smokers’ characteristics
were considered as predictors of NRT
use. These included factors known to be
associated with quit attempts and measures derived to reflect practice guidelines
around NRT (intention to quit; indications
of nicotine dependence assessed through
consumption level, typically 10 or more
cigarettes; and receipt of behavioural
supports for cessation). Six-month intention to quit smoking was obtained at
baseline by asking, ‘‘Are you planning to
quit smoking within the next month,
within the next six months, sometime in
the future, beyond six months, or are you
not planning to quit?’’ 43,44 A second
derived covariate classified smokers as
intending to quit if they intended to do so
at baseline or reported having made a
serious attempt to quit during the sixmonth follow-up. We calculated baseline
consumption, time to first cigarette after
waking45 and Heaviness of Smoking
Index.46 Respondents were also asked
if they considered themselves ‘‘very,’’
‘‘somewhat’’ or ‘‘not at all’’ addicted to
cigarettes.47 Derived variables were also
created for combinations of indications
for NRT (defined as above).
Respondents’ confidence in their ability to
quit was measured in four levels from
‘‘not at all’’ through ‘‘very confident’’ that
they would succeed if they decided to
quit completely in the next six months.
Reports of having made a serious attempt
to quit smoking, having received physician advice to quit smoking and using
specific behavioural supports for cessation
were obtained at baseline and follow-up.
Attitudes toward pharmaceutical smoking
cessation aids were determined at baseline
Vol 33, No 1, December 2012 – Chronic Diseases and Injuries in Canada
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20
from agreement with the following statements: ‘‘stop-smoking medications make
it easier to quit than trying to quit on your
own’’; ‘‘the cost of stop-smoking medications makes it difficult to use them’’;
‘‘stop-smoking medications are hard to
get’’; and ‘‘the risk of side effects from
stop-smoking medications concerns you.’’
The demographic characteristics considered were age, sex, education and rural
residence.48 Rural residence was considered as a potential indicator of relatively
poorer access to NRT (due to any of the
following: limited access to primary care
providers who might recommend pharmacotherapy; larger distances to pharmacies
that carry the product; or greater cost of
the product in more remote locations).
Analyses
Use of NRT was reported in bivariate
analyses and multivariable models relating NRT use to smoker demographics,
baseline attitudes and smoking characteristics and to behaviours related to smoking cessation.
We obtained prevalence ratios for NRT
use in relation to covariates using logbinomial regression models including all
smokers. We restricted this to smokers
who reported making a quit attempt
during the six-month follow-up period.
Regression diagnostics included assessment
for non-linearity and multi-colinearity.
All descriptive and multivariable analyses
used sampling weights for the Ontario
Tobacco Survey smoker cohort, which
were calculated to produce estimates
representative of the underlying population of Ontario adult recent smokers at
baseline.41 Variance estimates took the
sampling design into account and were
obtained using the Taylor series expansion
methods in Stata version 11 (StataCorp LP,
College Station, TX, United States).49
Results
Table 1 presents the characteristics of
2262 respondents with complete sixmonth follow-up data, along with sixmonth prevalence of NRT use by smoker
characteristics, predictors of cessation and
attitudes toward NRT. Similarity of the
sample to the underlying population is
TABLE 1
Sample characteristics and prevalence of NRT use in six months by smoker characteristics, in
a population-representative cohort of adult smokers, Ontario, Canada
Characteristic of smoker, history of smoking Unweighted
and cessation attempts, and attitudes
sample size, n
Percent of
sample, weighted
%
All smokers with complete 6 month data
2262
Prevalence of NRT use
in 6 months, by group
%
95% CI
100
11.4
9.7–13.1
Demographics
Age, years
2261
18–34
592
33.4
11.0
7.8–14.2
35–54
1120
49.1
12.2
9.8–14.6
549
17.4
10.1
7.0–13.1
993
52.5
11.2
8.8–13.6
Female
1269
47.5
11.7
9.4–13.9
Education
2256
55+
Sex
Male
2262
Some post-secondary education
1178
54.5
13.0
10.6–15.3
High school or less
1078
45.5
9.6
7.3–11.9
Heaviness of smoking at baseline
Number of cigarettes smoked/daya
2239
0–9
695
36.4
9.3
6.3–12.2
10–15
568
25.1
15.1
11.1–19.0
976
38.5
11.4
9.1–13.7
16+
Time from waking to first cigarette, minutes
1300
51.5
12.4
10.2–14.6
> 30
956
48.5
10.2
7.7–12.8
Quit attempts and intentions
2260
0
321
16.7
6.4
2.1–10.6
1
514
23.2
8.2
5.3–11.0
2
506
23.1
10.6
7.1–14.1
§3
919
37.0
16.3
13.3–19.3
Intended to quit at baselinea
Between baseline and the first six-month
follow-up, 11% reported using NRT (see
Table 1). Overall, 26% reported making
a serious quit attempt and just 2% of all
smokers in the sample were first-time
users of NRT in this six-month period.
There was no detectable difference in NRT
use among the 12% of respondents whose
time on study coincided with a free NRT
give-away program in Ontario (data not
shown).
2256
ƒ 30
Lifetime number of quit attempts at baselinea
reported elsewhere.41,42 In this cohort
64% smoked 10 or more cigarettes per
day at baseline, and 52% reported smoking within 30 minutes of waking. Most
respondents (83%) had previously tried to
quit, and 47% had previously used NRT.
In our sample, 40% reported an intention
to quit smoking at baseline, which is
somewhat lower than estimates from
other sources for the same population
(55%–59%,50,51 although with different
measures of intention52).
2230
Yes
914
40.2
17.5
14.4–20.5
No
1316
59.8
7.6
5.6–9.5
Made a serious attempt to quit smoking during 6-month follow-up period (reported at follow-up)a
2098
Yes
467
25.5
29.6
24.2–35.0
No
1631
74.5
3.9
2.9–4.9
Table 1 also shows the prevalence of NRT
use by smoker characteristics. Use was
significantly higher among respondents
who intended to quit altogether (using
various measures), who made serious
attempts to quit, and who had received
behavioural or professional supports for
cessation. NRT use was also positively
associated with baseline cigarette consumption, lifetime number of quit attempts,
prior use of NRT, perceived addiction,
confidence in ability to quit and attitudes
toward stop-smoking medications. Age,
sex or education were not associated with
NRT use; nor was rural/urban residence
in our analyses (data not shown).
Supports for cessation
Lifetime history of NRT usea
2262
Yes
1177
46.8
19.4
16.5–22.3
No
1085
53.2
4.4
2.6–6.2
Lifetime history of any behavioural supports (including physician advice)a
2262
Yes
415
16.0
23.7
18.3–29.2
No
1847
84.0
9.1
7.4–10.8
Physician advice or use of behavioural supports during follow-upa
2235
Either
959
43.6
17.2
14.1–20.4
Neither
1276
56.4
7.3
5.6–9.0
Continued on the following page
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21
Among smokers who intended to quit
altogether (either a prior intention to quit
at baseline or a reported serious attempt
during the follow-up period) and a baseline consumption of 10 or more cigarettes
per day (the 27% of smokers meeting
explicit practice guidelines), 25% used
NRT. The highest prevalence of NRT use
observed by subgroup, at 31%, was
among smokers who exactly met the
most conservative eligibility criteria and
also reported past or recent receipt of
behavioural support (Table 1).
Vol 33, No 1, December 2012 – Chronic Diseases and Injuries in Canada
TABLE 1 (continued)
Sample characteristics and prevalence of NRT use in six months by smoker characteristics, in
a population-representative cohort of adult smokers, Ontario, Canada
Characteristic of smoker, history of smoking Unweighted
and cessation attempts, and attitudes
sample size, n
Percent of
sample, weighted
%
Prevalence of NRT use
in 6 months, by group
%
95% CI
Attitudes and beliefs
Perceived addictiona
2253
Not at all
151
8.8
2.1
0.0–6.0
Somewhat
603
30.7
8.1
5.2–10.9
1499
60.5
14.5
12.2–16.8
5.4–14.4
Very
Confident of quitting altogether in the next 6 monthsa
2248
Not at all confident
310
12.0
9.9
Not very confident
654
27.3
12.3
9.1–15.4
Fairly confident
753
33.8
14.4
11.0–17.7
Very confident
531
26.8
7.9
5.2–10.5
Stop-smoking medications make it easier to quit than trying to quit on your owna
2261
Agree
1656
70.5
13.6
11.4–15.8
Disagree
494
24.8
6.8
4.2–9.4
Don’t know
111
4.8
3.3
0.8–5.7
1334
55.5
12.0
9.8–14.2
Disagree
771
37.0
12.4
9.4–15.4
Don’t know
156
7.5
2.4
0.4–4.5
344
14.2
7.6
4.2–11.1
1776
79.5
12.6
10.6–14.6
142
6.3
5.3
1.2–9.5
a
The cost of stop-smoking medications makes it difficult to use them
2261
Agree
Stop-smoking medications are hard to geta
2262
Agree
Disagree
Don’t know
The risk of side effects from stop-smoking medications concerns youa
2262
Agree
1309
56.1
10.5
8.4–12.6
Disagree
840
38.5
14.2
11.1–17.3
Don’t know
113
5.5
1.5
0.1–3.0
Combination of indications for NRT use
Intention or attempts to quit plus 10+ cigarettes/daya
2206
Yes
658
26.6
25.3
21.0–29.6
No
1548
73.4
6.5
4.8–8.1
a
Intention or attempts to quit plus 10+ cigarettes/day plus any support
2223
Yes
349
13.9
30.8
24.4–37.3
No
1874
86.1
8.3
6.7–10.0
a
Intention or attempts to quit plus any supports 2212
Yes
526
23.6
26.8
21.7–32.0
No
1686
76.4
6.8
5.3–8.2
Source: Ontario Tobacco Survey, Ontario Tobacco Research Unit, July 2005 to December 2007 (Cohorts 1 to 4 with 6-month
follow-up data).
Abbreviations: CI, confidence interval; NRT, nicotine replacement therapy.
a
Statistically significant bivariate association as indicated using global chi-square test for association.
Vol 33, No 1, December 2012 – Chronic Diseases and Injuries in Canada
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Table 2 shows the characteristics and
responses of the 301 individuals who used
NRT in the six-month follow-up window.
The large majority of NRT users had a
history of quit attempts at the baseline
interview (91%), expressed an intention
to quit (as baseline intention to quit [61%]
or attempt in follow-up [72%]), had used
NRT at or before the baseline interview
(80%) and reported themselves to be
‘‘very addicted’’ (77%). NRT users tended
to believe stop-smoking medications made
it easier to quit (84%) and that they were
readily available (88%), but also that the
cost made it difficult to use them (58%).
Table 3 shows the results of simultaneously adjusted log-binomial regression
models predicting use of NRT during sixmonth follow-up among all smokers and
among only those who reported attempting to quit during the same follow-up
window. Demographic characteristics
including age and education were not
associated with NRT use after adjustment
for smoking behaviour and history.
Among all smokers, history of quit
attempts at baseline was unrelated to
NRT use. However, respondents were
over 6 times more likely to use NRT if
they reported a serious attempt to quit
smoking over the same six-month followup period; they were also more likely to
use NRT if they had previously used it.
Both a lifetime history of physician advice
or behavioural supports for cessation
and reported receipt of advice or support during the same follow-up window
were statistically significant predictors
of NRT use in the fully adjusted model.
Consumption-based smoking behaviour
measures at baseline (number of cigarettes
per day and time to first cigarette) and
confidence in ability to quit were not
statistically significant after adjustment
for history of quitting behaviour.
When the analysis of predictors of NRT
use was restricted to smokers who made a
serious attempt to quit in the six-month
time frame, history of support for cessation was positively associated with NRT
use. However, after adjustment for this,
behavioural support reported during the
same reference period was not related to
TABLE 2
Characteristics of a population-representative cohort of adult smokers who reported using
NRT products ‘‘to quit or cut down’’ in a six-month follow-up period, Ontario, Canada
Characteristics of smokers (n = 301)
Weighted,
%
95% confidence
interval
18–34
32.2
24.6–39.9
35–54
52.4
44.7–60.1
55+
15.4
10.7–20.0
Demographics
Age, years
Sex
Education
Male
51.5
43.8–59.1
Female
48.5
40.9–56.2
Some post-secondary
High school or less
61.8
54.2–69.3
38.2
30.7–45.8
0–9
29.1
21.5–36.8
10–15
32.8
25.4–40.2
16+
38.1
31.1–45.2
ƒ 30
56.4
48.5–64.2
> 30
43.6
35.8–51.5
Heaviness of smoking at baseline
Number of cigarettes smoked/day
Time from waking to first cigarette, minutes
Quit attempts and intentions
Lifetime number of quit attempts at baseline 0
9.3
3.3–15.4
1
16.6
11.1–22.0
2
21.3
14.8–27.8
§3
52.8
45.1–60.5
Yes
60.8
53.0–68.5
No
39.2
31.5–47.0
Intended to quit at baseline
Made a serious attempt to quit smoking during the 6-month follow-up period (reported at follow-up)
Yes
72.3
65.5–79.0
No
27.7
21.0–34.5
Yes
79.6
72.4–86.8
No
20.4
13.2–27.6
Yes
33.3
26.2–40.3
No
66.7
59.7–73.8
Either
64.6
57.5–71.7
Neither
35.4
28.3–42.5
Not at all
Suppresseda
Suppresseda
Somewhat
21.6
14.8–28.4
Very
76.7
69.6–83.8
Supports for cessation
Lifetime history of NRT use
Lifetime history of any behavioural supports (including physician advice)
Physician advice or use of behavioural supports during 6-month follow-up
Attitudes and beliefs
Perceived addiction
Confidence of quitting altogether in the next 6 months
Not at all confident
10.3
5.7–15.0
Not very confident
29.1
22.4–35.8
Fairly confident
42.2
34.5–49.9
Very confident
18.3
12.6–24.0
Continued on the following page
$
23
NRT use. (Additional models, not shown,
indicate substitution effect where either
past or same-time period history of
behavioural supports were positively
associated with NRT use, and the two
were correlated.) Unlike the associations
found among all smokers, among those
who made a quit attempt higher number
of cigarettes per day at baseline was
positively associated with reported use of
NRT in the next six months, but not
previous quit attempts. A ‘‘don’t know’’
response to the attitude item about price
of NRT was negatively correlated with
use. Conversely a ‘‘don’t know’’ response
to the question on ease of access was
positively associated with use (p = .048
for the contrast).
Discussion
In Ontario, 30% of those making a quit
attempt used NRT. This is lower than that
found in a study by Reid and Hammond53
that showed that a fairly stable 50% of
smokers making quit attempts over two
years used medication. Our study is the
first to consider which smokers should
be using NRT, based on evidence-based
guidelines for NRT effectiveness. Of the
27% of smokers who met guidelines for
use in our analysis, just under 25% used
NRT. This leaves roughly 20% of all
Ontario smokers as, arguably, an ‘‘ideal’’
but unreached target population.
Despite the importance of quantitative
data on the reach of public health interventions,18 few reports have estimated
population prevalence of NRT in specific
time periods. Population health surveys
often lack the precision to quantify NRT
conditional on smoking and quit attempts.
In 1990, in a sample of Minnesotans with
access to NRT through insurance plans
with co-payment,54 roughly half of those
trying to quit used aids, primarily pharmacotherapy; in California between 1999
and 2002, 17% of all smokers used pharmacotherapy in the past year.55 In the U.S.
in 2003, 32% reported a quit attempt in
the past year using medication,56 whereas
in 2010, 30% of all smokers used medication in the past year.57 In the United
Vol 33, No 1, December 2012 – Chronic Diseases and Injuries in Canada
TABLE 2 (continued)
Characteristics of a population-representative cohort of adult smokers who reported using
NRT products ‘‘to quit or cut down’’ in a six-month follow-up period, Ontario, Canada
Characteristics of smokers (n = 301)
Weighted,
%
95% confidence
interval
Stop-smoking medications make it easier to quit than trying to quit on your own
Agree
83.9
78.5–89.3
Disagree
14.8
9.5–20.1
1.4
0.4–2.4
Agree
58.2
50.5–65.9
Disagree
Don’t know
The cost of stop-smoking medications makes it difficult to use them
Stop-smoking medications are hard to get
40.2
32.5–47.9
Don’t know
1.6
0.3–3.0
Agree
9.5
5.3–13.7
87.6
82.9–92.2
3.0
0.7–5.3
Agree
51.5
43.8–59.2
Disagree
47.8
40.1–55.5
0.7
0.0–1.4
Yes
58.6
50.7–66.4
No
41.4
33.6–49.3
Yes
37.3
29.8–44.7
No
62.7
55.3–70.2
Yes
55.0
47.3–62.7
No
45.0
37.3–52.7
Disagree
Don’t know
The risk of side effects from stop-smoking medications concerns you
Don’t know
Combination of indications for NRT use
Intention or attempts to quit plus 10+ cigarettes/day
Intention or attempts to quit plus 10+ cigarettes/day plus any support
Intention or attempts to quit plus any support
Source: Ontario Tobacco Survey, Ontario Tobacco Research Unit, July 2005 to December 2007 (Cohorts 1 to 4 with six-month
follow-up data).
Abbreviation: NRT, nicotine replacement therapy.
a
Cell size less than 5: estimates have been suppressed to maintain confidentiality.
Kingdom, where NRT is publically funded
through the National Health Service,
roughly half of smokers used it in recent
quit attempts.12
Not all smokers feel medications are
necessary,13,14,58 and many quit on their
own.56,59 However, Ontario utilization
rates may not reflect lack of interest; in
2006, a provincial NRT giveaway attracted
16 000 people in six weeks.60 We found
no difference in use by education, as
anticipated and seen in American data;57
however, we did not have access to
more direct measures of insurance or
ability to pay.40
Earlier studies showed that ever users of
NRT tend to be more dependent or smoke
more cigarettes.7,45,54,61–63 In our study,
number of cigarettes smoked did not
predict NRT use, which contrasts with
several retrospective studies;7,54 however,
cigarette consumption was associated
with NRT use among smokers trying to
quit, as elsewhere.12 Among all smokers,
lower consumption may follow from
efforts to cut down.64 American guidelines
on NRT cite a minimum number of
cigarettes primarily because of a lack
of clinical trials data for people who smoke
less.1–3 Australian practice guidelines, in
contrast, state that NRT should be offered
with evidence of dependence.65 We found
that over 90% of respondents who smoked
fewer than 10 cigarettes at baseline and
who used NRT perceived themselves to be
very or somewhat addicted.
Vol 33, No 1, December 2012 – Chronic Diseases and Injuries in Canada
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24
Intending or actually trying to quit were
significantly associated with NRT use,
which was consistent with findings from
California.63 Just 3% of Ontarians who
neither intended nor tried to quit used
NRT. This does not suggest widespread
use of NRT with no intention to quit, as
has been suggested as a negative consequence of NRT availability.34–38,66,67
However, we asked about NRT use ‘‘to
quit or reduce smoking’’ (to exclude use
of services for a different health reason)
and may not have captured all NRT use,
for example, by people who planned only
to reduce, but not discontinue, smoking.
Intention to quit may also change or be
unreliably measured.68 We addressed this
by considering intention with and without
subsequent attempts to quit.
In our study, smokers who received nonpharmaceutical support were more likely
to use NRT, whereas previous studies
report mixed findings. NRT users rarely
used behavioural supports in Minnesota,54
whereas in California7 and Australia62
NRT users were more likely to use
behavioural supports. Ontario data may
reflect consistency of advice from professionals and packaging to use behavioural
supports. However, as in most studies,69
we have no information on the intensity
or quality of the supports received. Our
study, like others,45,61 found that past use
of NRT was associated with prospective
use, but some use may have started before
the baseline interview and continued into
follow-up. Not surprisingly, smokers with
positive attitudes towards NRT were more
likely to use these medications.62,70–72
Our analysis used data to 2008, after which
time NRT manufacturers were permitted to
advertise NRT for use while cutting down
to quit. Future studies should ask about
NRT for use only to cut down or only
when one cannot smoke.63,66,67,73 Our
study will provide baseline data to evaluate the impact of these changes and recent
initiatives to publicly fund NRT.
Conclusion
Widely available NRT is a recommended
population-based measure to reduce
tobacco-related health burden. In this
population, where NRT was available over
TABLE 3
Results of multiple log-binomial regression models predicting NRT use, in six-month follow-up, for all smokers and for those who attempted
to quit over the same six-month period
Characteristic
Age (continuous, per 10 years of age)
Predicting 6-month prevalent use of NRT in all
smokers (N = 2031)
Predicting NRT use among those who made a quit
attempt in 6-month follow-up (N = 439)
PR (95% CI)
p value
PR (95% CI)
p value
0.94 (0.84–1.05)
.250
1.01 (0.90–1.14)
.853
Sex
Female (reference)
Male
1.00
1.00
0.86 (0.65–1.15)
.319
0.73 (0.53–1.02)
.065
1.09 (0.80 –1.47)
.582
1.27 (0.89–1.81)
.183
1.01 (0.99–1.03)
.226
1.02 (1.00–1.04)
.025
0.90 (0.65–1.24)
.516
0.69 (0.47–1.00)
.053
Education
High school or less (reference)
More than high school
Consumption (continuous, cigarettes/day)
1.00
1.00
Time from waking to first cigarette, minutes
ƒ 30
> 30 (reference)
1.00
1.00
Previous number of quit attempts at baseline
§1
0 (reference)
0.69 (0.40–1.22)
.201
1.00
0.49 (0.27–0.88)
.017
1.00
History of NRT use at baseline
Yes, § 1 times
3.04 (2.04–4.54)
No (reference)
1.00
< .001
2.68 (1.69–4.26)
< .001
1.00
History of behavioural support at baselinea
Yes, § 1 times
1.35 (1.02–1.79)
No (reference)
1.00
.038
1.40 (1.06–1.87)
Baseline intention to quit in 6 months
Yes
.020
1.00
.042
–
–
No (reference)
0.68 (0.47–0.99)
1.00
Made a serious attempt to quit smoking during 6-month follow up period
Yes
No (reference)
6.76 (4.72–9.69)
< .001
1.00
–
–
1.15 (0.82–1.63)
.418
Use of any behavioural supports during follow-up
Yes
No (reference)
1.53 (1.11–2.11)
.009
1.00
1.00
Confidence in ability to quit
Very confident
0.78 (0.44–1.39)
.403
0.90 (0.48–1.70)
.751
Fairly confident
1.14 (0.68–1.93)
.611
1.30 (0.75–2.24)
.345
Not very confident
1.16 (0.68–1.98)
.584
1.36 (0.78–2.39)
.278
Not at all confident (reference)
1.00
1.00
a
Stop-smoking medications make it easier to quit than trying to quit on your own
Disagree
0.71 (0.44–1.13)
.150
0.76 (0.43–1.33)
.334
Don’t know
0.62 (0.26–1.47)
.276
0.57 (0.23–1.41)
.221
Agree (reference)
1.00
1.00
The cost of stop-smoking medications makes it difficult to use them
Disagree
1.04 (0.79–1.39)
.768
1.09 (0.80–1.50)
.579
Don’t know
0.27 (0.08–0.97)
.045
0.09 (0.02–0.58)
.011
Agree (reference)
1.00
1.00
Continued on the following page
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25
Vol 33, No 1, December 2012 – Chronic Diseases and Injuries in Canada
TABLE 3 (continued)
Results of multiple log-binomial regression models predicting NRT use, in six-month follow-up, for all smokers and for those who attempted
to quit over the same six-month period
Characteristic
Predicting 6-month prevalent use of NRT in all
smokers (N = 2031)
Predicting NRT use among those who made a quit
attempt in 6-month follow-up (N = 439)
PR (95% CI)
p value
PR (95% CI)
p value
Disagree
1.32 (0.78–2.25)
.296
1.18 (0.66–2.13)
.574
Don’t know
1.98 (0.86–4.59)
.110
2.72 (1.01–7.34)
.048
Stop-smoking medications are hard to get
Agree (reference)
1.00
1.00
The risk of side effects from stop-smoking medications concerns you
Disagree
1.13 (0.85–1.50)
.413
1.25 (0.90–1.73)
Don’t know
0.26 (0.06–1.14)
.073
[excluded]b
Agree (reference)
1.00
.181
1.00
Abbreviations: CI, confidence interval; NRT, nicotine replacement therapy; PR, prevalence ratio.
a
Behavioural support considered as either advice from a physician or other forms.
b
Excludes fewer than 5 observations who said ‘‘Don’t know.’’
the counter and use of supplemental
behavioural supports advocated, most
smokers trying to quit were not using
NRT. Approximately 20% of Ontario
smokers were an ‘‘ideal’’ but unreached
target population for NRT use. Ontario
has recently implemented new initiatives
to increase the accessibility of NRT. As
such, further surveillance and research
are warranted to determine the impact
of the reach and benefits of NRT, considering both the general and targeted
smoking populations.
Acknowledgements
Support for this research was provided by
the Ontario Tobacco Research Unit, which
receives funding from the Ontario Ministry
of Health Promotion and Sport, and the
University of Toronto Dalla Lana School of
Public Health.
The authors have no conflicts of interest.
None of the authors work or have worked
in any capacity with, or received remuneration from, the manufacturers or sellers of tobacco products or nicotine
replacement therapy products. The lead
author was an investigator on The Stop
Smoking for Ontario Patients study funded
by the Ontario Ministry of Health and
Long-Term Care and which received support in kind from manufacturers of nicotine replacement therapy products without
intellectual restriction.
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/files/documents/ASH_445.pdf
Utilization of the Canadian Incidence Study of Reported Child
Abuse and Neglect by child welfare agencies in Ontario
L. Tonmyr, MSW, PhD (1); S. M. Jack, RN, PhD (2); S. Brooks, BA (3); G. Williams, MSc (1); A. Campeau, MA (1);
P. Dudding, MM, MSW, RSW (4)
This article has been peer reviewed.
Abstract
Introduction: The purpose of this study was to analyze how child maltreatment
surveillance data from the Canadian Incidence Study of Reported Child Abuse and
Neglect (CIS) is used by senior child welfare decision makers.
Methods: This triangulation mixed-methods study included quantitative and qualitative
methods to facilitate an in-depth exploration from multiple perspectives. We interviewed
Ontario child welfare decision makers to measure utilization of the CIS in policy
development.
Results: The majority of respondents were aware of the CIS data. Decision makers
reported using these data to determine resource allocation, understand reported
maltreatment trends and validate findings at their own agencies. Urban agencies used
the data more than did rural agencies.
Conclusion: This study is the first to triangulate data to understand and improve
utilization of child maltreatment surveillance data. The study participants indicated
considerable appreciation of the data and also provided ideas for improvements across
the surveillance cycle.
Keywords: child maltreatment, surveillance, Canadian Incidence Study of Reported Child
Abuse and Neglect, data utilization, policy development
Introduction
The Canadian Incidence Study of Reported
Child Abuse and Neglect (CIS) is one of
the Public Health Agency of Canada’s
(PHAC) national health surveillance programs. Since 1998, data have been collected from child welfare agencies every
five years. The CIS captures data on child
maltreatment (exposure to intimate partner violence, neglect, emotional maltreatment, physical and sexual abuse), the
extent of its harm, the source of the
allegation, short-term investigation outcomes, child and family characteristics
and functioning issues.1 The CIS captures
information at the national level, but some
provinces and territories collect additional
data to obtain estimates specific to their
jurisdiction. For example, provincial data
in Ontario have been collected through the
Ontario Incidence Study of Reported Child
Abuse and Neglect (OIS), the antecedent
of the CIS, since 1993.
Surveillance data are collected to support
decision makers in setting priorities and
allocating resources in policy development. The data should be able to identify
at-risk populations, monitor trends, detect
emerging issues and notice changes in
professional practice.2 The components of
the surveillance cycle are the collection,
analyses, interpretation and dissemination
of data. Feedback is then solicited from
the field to improve subsequent cycles.
CIS data have been analyzed to produce
surveillance reports, articles, book chapters and fact sheets. These publications
illustrate how CIS surveillance data inform
child welfare practice and policy, for
example, by providing educational material about child welfare to students in high
schools, universities and continuing education programs;3 supporting the implementation of differential response in some
jurisdictions;3 contributing to the United
Nations’ understanding of child neglect;4
requesting augmented funding5 and
enhancing maltreatment prevention by
First Nations agencies. However, no CIS
surveillance evaluation on aspects such as
flexibility, system accessibility and stability has been published to date.
Provincial and local child welfare decision
makers are a target audience for the CIS
findings. They can influence and adapt
programs, policies and practices by
responding to emerging trends and issues
highlighted by surveillance data. While
there is an emerging field of science within
child welfare focused on evidenceinformed decision-making6 and the importance of integrating research evidence into
practice and policy,7 no attention has been
paid to exploring how decision makers
perceive and use surveillance data, a very
specific form of research evidence. We
identified only one study from First
Author references:
1.
2.
3.
4.
Injury and Child Maltreatment Section, Health Surveillance and Epidemiology Division, Public Health Agency of Canada, Ottawa, Ontario, Canada
School of Nursing, Faculty of Health Sciences, McMaster University, Hamilton, Ontario, Canada
Research Support Services, School of Nursing, Faculty of Health Sciences, McMaster University, Hamilton, Ontario, Canada
Child Welfare League of Canada/ La Ligue pour le bien-être de l’enfance du Canada (CWLC/LBEC), Ottawa, Ontario, Canada
Correspondence: Lil Tonmyr, Injury and Child Maltreatment Section, Health Surveillance and Epidemiology Division, Centre for Chronic Disease Prevention and Control, Public Health Agency
of Canada, 200 Eglantine Driveway, Tunney’s Pasture, A.L. 1910C Ottawa, ON K1A 0K9; Tel.: 613-954-3339; Email: [email protected]
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Vol 33, No 1, December 2012 – Chronic Diseases and Injuries in Canada
Nations agencies regarding the utility of
surveillance data.8 However, no clear
conclusions could be drawn due to the
small sample size. The authors speculated
that the remoteness of the locations
impeded opportunities for decision
makers to foster networks with researchers and/or participate in conferences and
meetings. Challenges in accessing evidence are an identified barrier to utilizing
child-welfare research in Australia,
Ireland and Ontario.9–11 A Quebec study
showed that relative position within an
organization mattered in terms of research
utilization.12
This analysis is a component of a larger
mixed-methods study.11 Our study focuses
on Ontario child welfare decision makers’
perceptions and use of the results from the
CIS/OIS. We define utilization of research,
and specifically surveillance data, as the
transfer and uptake of research-based
knowledge into policy and practice. The
objectives of this paper are to:
N
N
N
N
examine Ontario child-welfare agency
decision makers’ awareness and perceptions of the CIS;
describe the CIS dissemination methods that decision makers prefer;
explore how the CIS is utilized for child
welfare policy and practice in Ontario;
and
identify strategies for improving
aspects of the surveillance cycle (data
collection, data analysis, dissemination
and feedback from the field).
Methods
This mixed methods study included both
quantitative and qualitative methods to
facilitate in-depth research from a number
of perspectives.13 We administered a
quantitative survey to senior Ontario
child-welfare decision makers to measure
research utilization in policy development. This component covered the first
and third objectives of our study (awareness/perceptions of the CIS; preferred CIS
dissemination methods). The qualitative
component of this analysis used casestudy methodology14 to explore how
child-welfare decision makers used the
CIS/OIS public health surveillance data
and to identify what influence and impact
surveillance findings have had on childwelfare policy. The qualitative study
covered all four objectives.
Only the three most senior decision makers
in each agency (executive directors, services directors and supervisors/managers/
other positions) were eligible to participate
in both the quantitative and qualitative
components.
The Hamilton Health Sciences/McMaster
Faculty of Health Sciences Research
Ethics Board and the Ontario Association
of Children’s Aid Societies (OACAS)
reviewed and approved the project.
Qualitative case study
We used an embedded, multiple-case
approach14 to guide this case study of
child-welfare agencies delivering services
to populations in urban centres, mixed
rural/small urban centres, or remote
communities. It was determined that we
would reach theme saturation by selecting
13 agencies that provided services to
geographically or culturally unique populations. Nine consented to participate and
four declined due to time constraints.
From each of these nine participating
agencies, the three most senior decision
makers were invited to participate in two
semi-structured, in-depth qualitative interviews. We conducted 21 interviews inperson and six by telephone (due to
schedule conflicts or remote location of
agencies) between March and September
2007. The focus of the first interview,
lasting 60 to 90 minutes, was to explore
the individual, organizational and systemlevel influences on the interviewees’
ability to utilize research evidence in
decision-making. We also asked about
their awareness and utilization of CIS/
OIS data (questionnaire available upon
request). Six to nine months after this
initial interview, we conducted telephone
interviews (n = 19) lasting on average
45 minutes. This interview allowed us to
verify our interpretation of the data and
confirmed the validity of concepts that
arose throughout all the interviews. The
remaining 8 participants did not complete
a second interview either because they
had left the agency or because they
Vol 33, No 1, December 2012 – Chronic Diseases and Injuries in Canada
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could not be contacted despite numerous
attempts.
All participants completed a demographic
questionnaire. We kept field notes on
topics, observations and researchers’
responses to events.15
Qualitative data analysis
We conducted the data analysis and
collection concurrently to identify themes
requiring further exploration. Content
analysis principles guided the examination
of each transcript. Two investigators
independently reviewed and coded each
transcript. This double-coding and peer
examination promoted consistency of
emerging qualitative findings. Once the
core themes from each interview were
identified, we used a constant comparative process15 to contrast findings across
contexts and identify research utilization
concepts and factors influencing the
research uptake process.
Quantitative data
In the second phase of the study, aiming
for a census we contacted all 53 childwelfare agencies in Ontario to participate
in the study. Of these, 41 agreed to
participate (77% participation rate). Of
the 123 eligible senior decision makers
from the participating agencies, we interviewed 98 (80% participation rate) using a
questionnaire developed for decision
makers in public health.16,17 We added
questions about the CIS/OIS to this tool,
totalling 53 questions and lasting 30 to
45 minutes. One researcher conducted
telephone interviews (between December
2007 and September 2008) and completed
each questionnaire using a customized
module in Microsoft Access 2007
(Redmond, WA, United States).
Quantitative data analysis
We performed the statistical analyses in
two stages. First, we analyzed univariate
and bivariate relationships. We conducted
a significance test (Fisher exact test) for
each variable by the respondent’s position
and gender and the agency’s location.
Next, we ran a linear regression to model
participants’ satisfaction with the CIS/OIS.
Correlates were selected from the variables described in Table 1 using a backward selection approach (a=.10). Due to
the similarities between CIS and OIS
findings, we only report information about
the CIS. We used PROC FREQ and PROC
GLM in SAS/STATH software, version 9.1
for Windows (SAS Institute Inc., Cary,
NC) for the analyses.
women and 43 were men; 36 were
executive directors; 32 were service
directors; and 30 worked as supervisors/
managers or in other positions.
About half (55%) of the agencies in the
sample had a formal university affiliation.
Almost 85% of the respondents held a
graduate degree and had extensive experience in child welfare.
Sample characteristics
Results
Table 2 describes the demographics for
both parts of the study. For the quantitative phase, 84 of the respondents worked
in an urban/mixed agency and 14 in a
rural agency. Of the respondents, 55 were
The following qualitative results correspond to all four study objectives and the
quantitative results to the first and third
objectives.
Qualitative results
Awareness and perception of the CIS
The majority of respondents (84%) were
aware of the CIS, having learned about
it through, for example, the distribution
of reports, participation in meetings or
conferences, postings of CIS findings
(e.g. by the OACAS or the Child
Welfare League of Canada), and presentations and involvement in the data
collection by the agency. Most respondents acknowledged that the report was
circulated among senior decision makers
within the agency but did not always
reach the front-line workers.
TABLE 1
Description of the CIS/OIS questions/variables used in the quantitative survey
Variable
Measure
Organizational characteristics of agency
Type
Children’s Aid Society or First Nations Agency
Location
Urban/mixeda or rural
Individual characteristics
Sex
Male or female
Current position
Executive director, director (services or
quality assurance) or supervisor/manager/other
Education (highest degree achieved)
Secondary, post-secondary or other
Participant’s perception of research evidence
Direct supervisor expects the participant to use research evidence for planning
Likert scale: 1 (low) to 7 (high)
Research evidence is consistently included in program planning
Likert scale:1 (low) to 7 (high)
Relevance of research literature to the participant’s work
Likert scale:1 (low) to 7 (high)
Participant’s perception of the CIS/OIS
Has ever seen the CIS
Yes/no
Has ever seen the OIS
Yes/no
Has used the CIS within past year to make policy/program decisions
Yes/no
Has used the OIS within past year to make policy/program decisions
Yes/no
Organization has made policy/program decisions related to child abuse and neglect in the past year
Yes/no
CIS relevance to the participant’s field
Likert scale: 1 (low) to 7 (high)
CIS ease of use
Likert scale: 1 (low) to 7 (high)
OIS relevance to the participant’s field
Likert scale: 1 (low) to 7 (high)
OIS ease of use
Likert scale: 1 (low) to 7 (high)
Extent to which CIS data was considered in the decision-making process in the past year
Likert scale: 1 (low) to 7 (high)
Extent to which CIS data influenced that decision
Likert scale: 1 (low) to 7 (high)
Extent to which incorporating CIS data in the decision-making process leads to concrete changes in
policies/programs
Likert scale: 1 (low) to 7 (high)
Extent to which incorporating CIS data in the decision-making process confirmed current policies/programs
related to the decision
Likert scale: 1 (low) to 7 (high)
The participant’s general satisfaction with CIS
Likert scale: 1 (low) to 7 (high)
Abbreviations: CIS, Canadian Incidence Study of Reported Child Abuse and Neglect; OIS, Ontario Incidence Study of Reported Child Abuse and Neglect.
a
Urban and mixed locations were collapsed due to the small number of respondents and empirical similarities.
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Vol 33, No 1, December 2012 – Chronic Diseases and Injuries in Canada
TABLE 2
Characteristics of the respondents in the qualitative (initial interview) and quantitative
surveys
Variable
Location
Position
Qualitative (initial
interview)
(n = 27)
n
%
n
%
18
67
84
86
Rural
9
33
14
14
Executive Director
9
33
36
37
Services Director
9
33
32
33
Urban/mixed
Supervisor/manager/other positions
Experience
Education
9
33
30
31
Average years in child welfare
19
70
21
21
Average years in current agencya
14
52
—
—
Average years in current position
7
26
7
7
Bachelor’s degree
4
15
6
6
20
74
85
87
3
11
7
7
18
67
55
56
9
33
43
44
Master’s degree or higher
College/diploma/other
Sex
Female
Male
Total
a
Quantitative
(n = 98)
27
98
Not asked in quantitative survey.
Decision makers from urban/mixed sites
were knowledgeable about the content of
the CIS and could identify examples of
data collected. Those from rural agencies,
with the exception of respondents who
had participated in CIS data collection,
were not familiar with the CIS. One rural
respondent identified how their agency’s
participation in the CIS fostered an investment in the findings:
[…] we were one of the first rural
participators... So we’ve paid attention
to the outcome of that research because
we see it personally, we’re engaged in
it, so it was important for us to review
and think about the outcomes of that.
Description of preferred CIS dissemination
methods
Respondents emphasized the importance of
the CIS using many different ways to
disseminate information and the value of
frequent communication. They confirmed
that surveillance reports should be available
in hard and electronic formats. In addition,
they considered essential the inclusion of
interpretations of findings in report summaries because they were too busy to read
lengthy reports. The majority disclosed that
they primarily read the executive summary
and/or fact sheets and used the full report
only to obtain further information on
specific topics. Respondents also stressed
the value of face-to-face presentations to
agency staff by someone knowledgeable
about CIS findings, especially in rural
agencies. One respondent said:
The information was right there, it was
visual, and they were talking to people
who live this everyday. And so there
was time left in the presentation for a
discussion—why do you think that
would be, does that resonate with you
guys or not, does it seem like it’s right
off the wall? And there was lots of time
for conversation and for exchange of
ideas and really kind of connecting
with the information.
Respondents reflected positively on discussions with and presentations by CIS
researchers and agency staff who were
knowledgeable about CIS and could interpret the data. They saw it as an opportunity to increase learning and engagement
with the data.
An additional theme emerged around the
frequency with which CIS reports were
Vol 33, No 1, December 2012 – Chronic Diseases and Injuries in Canada
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disseminated. The respondents preferred
receiving data more frequently than the
present rate of every five years, current
data being most relevant to policy development. Decision makers are regularly
required to prioritize where to invest their
limited resources; thus up-to-date information on current and emerging trends
(such as the decline in substantiated
sexual abuse) is perceived as helpful.
Some respondents mentioned advantages
to regularly receiving ‘‘short CIS summaries’’ via portals frequently accessed by
staff. One respondent suggested:
I think people don’t have time to read
anymore. Here’s a great idea, do like a
one liner like every week… Send me a
highlight from this posted on OACAS,
wherever… So in the weekly news I
can say ok this is the finding I saw this
week. So it’s that constant messaging,
changing it up every time so you are
not saying the same thing…
Other suggestions included having fact
sheets and summaries with embedded
links to background documents or related
research. Yet another idea was to link
CIS results to practical interventions in
order to demonstrate a concrete utility of
findings.
Utilization of the CIS
Many of the decision makers acknowledged that the CIS data, presented at a
national level, provided the ‘‘big picture’’
and was very relevant for provincial
policy development. At the agency level,
decision makers found the CIS data most
useful in (1) identifying emerging child
maltreatment trends so that agency policies or programs could be adjusted; (2)
providing a benchmark for their local
statistics and insights into issues; and
(3) confirming local observations and
hypotheses about child maltreatment
trends. For example, in 2005 the CIS
confirmed an increase in reports of children exposed to intimate partner violence,
a decline in reported sexual abuse and that
neglect is common.1 These data influenced
some organizations to re-examine their
resource allocation to families exposed
to intimate partner violence or to restructure their sexual abuse prevention and
treatment programs. As one decision maker
explained:
I think [the CIS is] a very good effort to
iron out those wrinkles and to give the
people who are making policy and who
are doing the work related to this
phenomenon information about trends
and incidence so the amount of different
kinds of abuse and the nature of that
abuse and how it’s changing over time,
and some of the implications of that. One
of the strongest ones I think you know—
there’s upswings in physical abuse and
downswings in sexual abuse over the
years and we’re always challenged to
figure out why exactly those things are
happening, whether it’s because we’re
being more effective, less effective,
whatever.
Some respondents mentioned that the CIS
informed their policies indirectly by creating knowledge that could influence day-today decision-making. Others were less
optimistic about their ability to influence
policy and claimed that policy changes
only happen through the provincial
Ministry of Children and Youth Services.
Rural participants were the least convinced that the findings did—or would—
impact their agencies’ policy making.
Improving various aspects of the surveillance
cycle
Participants from the qualitative phase
provided insights into areas where the
CIS could be improved. The majority of
the respondents felt that the surveillance
report was comprehensive and required
no changes. Some others suggested that
further data could be collected and analyzed to be predictive of future trends,
rather than just reporting incidence. Yet
others suggested that the results needed to
be interpreted and contextualized in terms
of Ministry mandates. Some rural respondents sought agency staff involvement in
developing the CIS questionnaire to
ensure that the information was relevant.
Others suggested using longitudinal data
collection and linkages to existing data
sources such as Looking after Children.*
Respondents also asked if the CIS could
find a way to track the outcomes of
investigations and to determine the effectiveness of child welfare interventions.
Others proposed providing provincial
comparators or demographic characteristics, such as immigration/citizenship status, race and gender. Comparisons of the
findings to the community child population were also requested as well as the
collection and analysis of Aboriginal data.
One of the barriers to using CIS findings
was that it differs from data collection for
planning mandated by the Ministry of
Children and Youth Services. Definitions
and content used in the CIS differ from
Ministry systems, which impedes comparison. For instance, while agencies count
the final decision for short- and long-term
placements regardless of maltreatment
type, the CIS captures short-term placements and reason for the investigation.
Respondents provided suggestions for
specific analyses of the data, such as
detailed information about types of maltreatment in general, and neglect and
exposure to intimate partner violence
specifically, considering their high prevalence in the CIS and their co-occurrence
with other maltreatment. They also
requested data about the effectiveness of
placement, in particular, kinship. Other
areas for exploration included the relationship between poverty and the need for
child welfare intervention, and parents’
and children’s mental health and/or
addictions.
Quantitative findings
Awareness/perception and utilization of the
CIS
Overall, 96% of respondents were aware
of the CIS. We found significant differences between urban/mixed and rural
agencies on awareness of the CIS, relevance of the research literature to the
participant’s work, as well as ease of
use of CIS data and general satisfaction
(Table 3). However, differences by position and gender were not significant in our
analysis and therefore are not shown.
Figure 1 shows the distribution of overall
satisfaction with the CIS data and the
difference between urban/mixed and rural
agencies. On a scale of 1 to 7, the most
common score was 6 in all types of
agencies. However, rural agencies had
more response variability.
Table 4 shows the regression results for
individual and agency characteristics that
are associated with satisfaction with and
relevance of the CIS. Respondents who
gave a higher score to the relevance of
research literature to their work also gave
a higher score to the relevance of the CIS.
The CIS relevance score was lower for
rural agencies. Overall CIS satisfaction
was associated with CIS ease of use and
urban/mixed location. Rural agencies
scored CIS satisfaction lower than did
urban/mixed agencies.
Discussion
The results of our study show that the
majority of respondents were aware of the
CIS. Study findings reached them through
websites, conferences and researchers’
visits to the agencies. Not surprisingly,
those agencies that participated in data
collection and/or attended researchers’
presentations had a better grasp of CIS
content. CIS data were considered useful
although respondents had suggestions for
improvements. Our data suggested that
respondents from urban/mixed locations
are more knowledgeable about the CIS
than those from rural areas. Cost is a
prohibitive factor in data collection from
rural agencies as is the ability to present
them with research findings individually.
Among the interviewed decision makers,
the CIS met its surveillance objectives in
that respondents confirmed its utility in
identifying at-risk populations, monitoring
trends, detecting emerging issues and
directing changes in practice. The respondents mentioned that it was especially
useful to monitor maltreatment trends and
confirm their local observations. It seems
counterintuitive that while respondents
were generally satisfied with the CIS and
considered it highly relevant, only a
minority used CIS data in decision-making. One possible explanation is that our
data collection tools did not successfully
* http://www.cwlc.ca/projects/canlac
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Vol 33, No 1, December 2012 – Chronic Diseases and Injuries in Canada
TABLE 3
Descriptive statistics from the quantitative survey
Total Respondents
(N = 98)
Urban/mixed (n = 84)
Respondeda, %
Median
Rural (n = 14)
Respondeda, %
p valueb
Median
Dichotomous response
Has ever seen the CIS
Yes
98
—
86
—
No
2
—
14
—
Missing/not applicable
0
—
0
—
95
—
86
—
< .05
Has ever seen the OIS
Yes
No
2
—
0
—
Missing/not applicable
2
—
14
—
Has used the CIS within last year to make policy/program decisions
Yes
33
—
14
—
No
62
—
71
—
5
—
14
—
21
—
Missing/not applicable
Has used the OIS within last year to make policy/program decisions
Yes
40
No
55
—
64
—
5
—
14
—
Missing/not applicable
—
Organization has made policy/program decisions related to child abuse and neglect in the past year
Yes
98
—
86
—
No
1
—
14
—
Missing
1
—
0
—
Likert scalec
Direct supervisor expects the participant to use research evidence for planning
95
5.00
93
4.00
100
4.00
< .001
Research evidence is consistently included in program planning
99
4.00
Relevance of research literature to the participant’s work
99
6.00
100
5.00
< .05
93
6.00
64
5.00
< .05
87
6.00
57
4.50
< .05
CIS relevance to the participant’s field
CIS ease of use
OIS relevance to the participant’s field
OIS ease of use
capture direct use at the agency level. It is
also possible that the CIS may be more
useful at the Ministerial level.
90
7.00
64
6.00
85
6.00
57
4.50
< .01
It is notable that many of the critiques and
suggested changes are outside the scope of
CIS surveillance. This indicates that some
respondents do not recognise the goal and
limitations of surveillance data. For
instance, the CIS is designed to inform
development of interventions through risk
factor identification, but this is not intervention data per se. It is important that the
scope of surveillance data be clarified for
users. The additional data requested by
respondents (i.e. demographics) already
exist in the CIS program (except immigration status), which suggests these respondents were unfamiliar with the CIS. Many
suggestions to expand the CIS scope
were likely derived from the paucity of
Canadian child maltreatment data. The
CIS has provided an important platform
to promote further data collection efforts.
However, there is a need to expand
research within child welfare.
Many of the gaps identified by respondents
are being addressed by PHAC and its
partners. For example, respondents in
various agencies mentioned the need for
more data on Aboriginal people. Aboriginal
agency participation has increased with
each cycle,18 and several analyses have
focused on Aboriginal children and their
families.19–22 Also, the CIS has started to be
used in conjunction with other data sets to
obtain a more complete depiction of child
maltreatment. For instance, one researcher
investigated the reported decline in substantiated sexual abuse comparing CIS and
Quebec data.23
Extent to which CIS data was considered in the decision-making process in the past year
85
2.00
79
1.00
2.00
79
1.00
Extent to which CIS data influenced that decision
83
Extent to which the incorporation of CIS data in the decision-making process lead to concrete changes in
policies/programs
81
1.00
93
1.00
Extent to which the incorporation of CIS data in the decision-making process confirmed current policies/
programs related to the decision
81
1.00
93
1.00
6.00
57
5.00
The participant’s general satisfaction with CIS
87
Also promising is that analyses have been
conducted on several of the issues suggested by the respondents, for example,
youth substance abuse,24 anxiety/depression in adolescents,25 neglect26 and exposure to domestic violence.27 In a recent
Abbreviations: CIS, Canadian Incidence Study of Reported
Child Abuse and Neglect; OIS, Ontario Incidence Study of
Reported Child Abuse and Neglect.
a
< .05
Table continued, see right column
Vol 33, No 1, December 2012 – Chronic Diseases and Injuries in Canada
$
34
May not add to 100% due to rounding.
b
Fisher exact test.
c
The Likert scale ranges from 1 (low) to 7 (high).
FIGURE 1
Distribution of the overall satisfaction with the Canadian Incidence Study of Reported Child
Abuse and Neglect (CIS) by location of respondents of the quantitative survey
Comparison of overall CIS satisfaction
60%
50%
Summary Statistics
Median
6.0
IQR
1.0
Interview respondents identified conferences as dissemination channels for CIS
findings; however, earlier research has
questioned the effectiveness of these for
health care professionals.29 Possibly conferences are viewed more positively by
those working in child welfare than in
health care. Other dissemination methods
such as websites and presentations at the
agencies were also mentioned. Rural
agencies valued in-person presentations
more than did urban/mixed agencies. The
respondents felt that on-site presentations
created an opportunity to clarify findings
and allowed all staff members, not just
management, to be present. We cannot
say which means of dissemination were
the most effective as participants were not
asked to rank information sources.
Urban/mixed
40%
30%
20%
10%
LOCATION
0%
60%
50%
Summary Statistics
Median
5.0
IQR
3.0
Rural
40%
30%
20%
10%
0%
1
2
3
4
5
6
7
Score
Abbreviation: IQR, Interquartile range.
TABLE 4
Results of multivariate analyses on the Canadian Incidence Study of Reported Child Abuse
and Neglect (CIS) perception and satisfaction
Model
Covariates
ß
se (ß)
t
p
Dependent variable
CIS relevancea
Intercept
Location (rural)
Relevance of research literature
to participant’s workb
4.14
0.70
5.95
< .01
20.86
0.44
21.95
.05
0.31
0.12
2.69
< .01
Overall satisfaction with the CISc
Intercept
3.17
0.57
5.54
< .01
20.70
0.34
22.06
.04
Child welfare experience (years)
0.02
0.01
1.94
.05
CIS ease of useb
0.36
0.09
4.01
< .01
Location (rural)
Abbreviations: CIS, Canadian Incidence Study of Reported Child Abuse and Neglect; CV, coefficient of variation.
a
review of the CIS, the authors identified 37
manuscripts based on original analyses
published in peer-reviewed journals.28
However, several issues remain unanalyzed, and a process needs to be developed to inform decision makers about
existing CIS analyses.
Model diagnostics: R2 = 0.14; CV = 21.02; p < .01.
b
The score for this variable ranges from 1 (low) to 7 (high).
c
Model diagnostics: R2 = 0.33; CV = 15.42; p < .01
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35
Dissemination plans have been developed
for each CIS cycle.30 These plans have
stressed the importance of developing
multiple strategies for different audiences
and targeting products specifically for these
audiences. The next dissemination plan
should incorporate key findings from this
study. The respondents valued fact sheets,
but they also found that the surveillance
reports were an important resource. The
utility would increase for them if the CIS
were indexed. They also concluded that
both hard and electronic copies of CISrelated materials were useful.
Collaboration is important in improving
research use in decision making.31 This
idea has been emphasized since the CIS
inception. For this, PHAC has established
committees with representatives from the
various Canadian Ministries. PHAC has
also hosted several fora for the exchange
of ideas about improvements to the
CIS.32,33 The findings from our regression
models are not surprising. Estabrooks
et al.34 showed that predicting research
utilization based on education had mixed
results. Among professionals, those in
managerial/leadership roles in health care
Vol 33, No 1, December 2012 – Chronic Diseases and Injuries in Canada
fields similar to the child welfare field
consistently demonstrated more research
utilization.12,34 Our findings of the underutilization of research are consistent with
the child welfare literature; lack of access
to the research has been suggested as
an explanation.8–11 Gender and age are
included as control variables in many
studies; however, they were not significant in this study, and thus were not
included in our models. Additionally,
since these variables are not modifiable,
the focus has been on other individual
characteristics.
We do not know if these findings are
generalizable outside Ontario. Moreover,
the small sample size may have precluded
the detection of differences in responses.
We can only speculate how the results
were influenced by attrition between the
first and the second qualitative interview.
The 19 who participated in the second
interview agreed that the research team
had accurately interpreted the experiences
they had described in the first interview;
however, it is impossible to predict if the
eight who did not participate would have
concurred.
Implications
Conclusion
Although some suggestions for improvements have been addressed, there are
others to consider. Several respondents
felt that the CIS needed to be conducted
more frequently to increase utility. A costbenefit analysis needs to be conducted;
service data have a shorter shelf-life than
population-based data, since changes in
practice influence what constitutes maltreatment. For instance, expansion of
reporting laws to include exposure to
intimate partner violence in Minnesota
created an influx of new cases.35 Other
respondents asked for longitudinal data, to
better understand children’s situation
when placed outside the home.
Intervention data were also requested.
Surveillance systems should be flexible
to meet the needs of the users so the
feasibility of including other requested
information in the CIS needs to be
explored. Most importantly, disseminating
efforts should target rural areas.
The CIS, as part of Canada’s child health
surveillance program, provides valuable
and important data on a highly vulnerable
population who face risk factors with
potential lifelong consequences. There is
a growing recognition of the significance
of these data in influencing practice,
policy and program development at all
levels. This triangulation study was the
first to analyze the utilization of maltreatment surveillance data among decision
makers. It identified a high appreciation of
the CIS and provided ideas for improvements in all aspects of the surveillance
cycle.
Strengths and limitations
This study has many strong points: we
used both qualitative and quantitative
methods for data collection and analysis
to promote overall data credibility; we
used
an
embedded,
multiple-case
approach to guide the case study (three
case studies were conducted at the same
agency providing different perspectives);
and we interviewed professionals at both
urban/mixed and rural agencies across
Ontario.
However, the findings should be interpreted within the limitations of the study.
Acknowledgements
We would like to thank the research
project participants from Ontario child
welfare agencies who shared their time,
knowledge and expertise with the members of the study team. We appreciate the
warm welcome that we received at each
participating agency.
This study was funded through the Ontario
Centre of Excellence for Child and Youth
Mental Health at the Children’s Hospital of
Eastern Ontario. We also want to extend
our thanks to Jasminka Draca, Pascal
Roberge, Dr. Anne-Marie Ugnat and Dr.
Catherine McCourt at the Public Health
Agency of Canada and Karen Levine for
their support.
Dr. Susan Jack is supported through the
Institute of Human Development, Child
and Youth Health, Reproduction and Child
Health New Investigator Personnel Award
Vol 33, No 1, December 2012 – Chronic Diseases and Injuries in Canada
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36
from the Canadian Institutes of Health
Research.
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Vol 33, No 1, December 2012 – Chronic Diseases and Injuries in Canada
Emergency department surveillance of injuries associated with
bunk beds: the Canadian Hospitals Injury Reporting and
Prevention Program (CHIRPP), 1990–2009
S. R. McFaull, MSc; M. Frechette, MSc; R. Skinner, MSP
This article has been peer reviewed.
Abstract
Introduction: Due to space constraints, bunk beds are a common sleeping arrangement
in many homes. The height and design of the structure can present a fall and
strangulation hazard, especially for young children. The primary purpose of this study
was to describe bunk bed-related injuries reported to the Canadian Hospitals Injury
Reporting and Prevention Program (CHIRPP), 1990–2009.
Methods: CHIRPP is an injury and poisoning surveillance system operating in 11
pediatric and 4 general emergency departments across Canada. Records were extracted
using CHIRPP product codes and narratives.
Results: Over the 20-year surveillance period, 6002 individuals presented to Canadian
emergency departments for an injury associated with a bunk bed. Overall, the frequency
of bunk bed-related injuries in CHIRPP has remained relatively stable with an average
annual percent change of 21.2% (21.8% to 20.5%). Over 90% of upper bunk-related
injuries were due to falls and children 3–5 years of age were most frequently injured
(471.2/100 000 CHIRPP cases).
Conclusion: Children with bunk bed-related injuries continue to present to Canadian
emergency departments, many with significant injuries. Injury prevention efforts should
focus on children under 6 years of age.
Keywords: injury prevention, injury surveillance, bunk bed Injuries, CHIRPP, furniturerelated injuries, product safety
Introduction
Unintentional injuries are the leading
cause of death among Canadian children
and youth,1 and many of these are related
to consumer products. Bunk beds have
been identified as an injury hazard for
over 30 years,2,3 especially for young
children. They are associated with more
severe injuries than those associated with
conventional beds,4 the most obvious
reason being their height. Other ‘‘hidden’’
hazards include guardrail openings
of specific dimensions that, given the
anthropometry of some young children,
could cause entrapment or strangulation.
Some decorative components (e.g. the
bedpost) can cause certain types of
clothing to snag, and coupled with the
height, present another potential form
of strangulation. Improper assembly, due
to unclear instructions, missing parts
or faulty components, may also be
hazardous.5,6
Since 1987, the United States has seen 34
product recalls involving 84 manufacturers and over 1.5 million bunk beds.7
Recent U.S. estimates for those aged 0 to
21 years indicate an annual average of
35 790 cases of non-fatal bunk bed-related
injuries treated in emergency departments
(42 per 100 000 population) and, during
1990–1999, 10 fatalities per year.8
Since 2007, there have been 4 product
recalls involving 4 manufacturers and
over 23 000 bunk beds9 in Canada, the
most recent of which were 2 joint
recalls with the Consumer Product Safety
Commission in the United States (May
and September, 2011) involving 21 707
units.10 Between 1983 and 2011, there
were 7 deaths related to the use of bunk
beds reported to Health Canada’s Consumer Product Safety Directorate. Three of
the deaths involved children under 3 years
of age, the most recent in 2008.11,12 There
are currently no specific regulations for
bunk beds. Health Canada recommends
that bunk beds sold, advertised, imported
or manufactured in Canada meet the
safety requirements of the latest version
of the ASTM F1427 Standard Consumer
Safety Specification for Bunk Beds.6,13
While a number of reports from other
countries discuss non-fatal bunk bedrelated injuries, including hospitalization
rate estimates,8,14–18 there is no comprehensive study of bunk bed-associated injuries
in Canada. Further, ICD-10* coding in
Canada does not allow identification of
deaths or hospitalizations by type of bed,
so specific rates are not readily available.
* International Classification of Diseases, 10th Revision.
Author reference:
Injury and Child Maltreatment Section, Health Surveillance and Epidemiology Division, Centre for Chronic Disease Prevention, Public Health Agency of Canada, Ottawa, Ontario, Canada
Correspondence: Steven McFaull, Public Health Agency of Canada, 200 Eglantine Driveway, Tunney’s Pasture, A.L. 1910D, Ottawa, ON K1A 0K9; Tel.: 613-946-0487; Fax: 613-941-9927;
Email: [email protected]
Vol 33, No 1, December 2012 – Chronic Diseases and Injuries in Canada
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38
While the leading cause of bunk bedrelated deaths is entrapment/strangulation
and all recalls are related to entrapment
or collapse,5,6 most non-fatal injuries
involving bunk beds are due to falls.8
The primary objective of our study was to
describe the Canadian experience of the
mechanisms and temporal trends associated with emergency department presentations for bunk bed-related injuries.
A secondary purpose was to provide
Canadian population-based estimates of
the rate of hospitalizations for falls from
bunk beds by using the Canadian Hospitals
Injury Reporting and Prevention Program
(CHIRPP) to develop a scaling factor
(based on the ratio of bunk bed injuries
to all bed injuries) that can be applied to
ICD-coded national hospitalization data.
Methods
Data source
CHIRPP is an injury and poisoning surveillance system presently operating in
11 pediatric and 4 general hospitals across
Canada since 1990.19,20 The CHIRPP system
runs on an Oracle platform and currently
contains over 2.2 million records. The
information collected includes activity at
the time of injury; activity leading to the
injury; the direct cause of the injury;
contributing factors; time and place of the
injury event; the patients’ age and sex; up to
3 injuries (body part and nature of injury);
and the treatment received in the emergency department. Narrative fields provide
information to further refine the coding and
to identify rare events. Numerous validation programs have been developed to track
data quality. Although only selected hospitals report to CHIRPP, previous research
has shown that the data collected through
the program represent general injury patterns among Canadian youth.21 Previous
investigations have reported on other
methodological aspects of CHIRPP.22–26
Data extraction, cleaning and analysis
We identified cases by searching the entire
CHIRPP database (1990–2009, all ages;
extraction date: May 5, 2011) for injuries
{
associated with bunk beds (CHIRPP
product code 213). To ensure complete
capture, we also searched narratives using
variations of the following bilingual text
strings: ‘‘BUNK BED,’’ ‘‘LIT SUPER,’’ ‘‘LIT
A 2 ETAGES’’ and ‘‘LOFT BED.’’ The
CHIRPP narratives were used to code a
mechanism variable that provided
detailed information on the injury event
beyond the basic numerical variables.
This process is time-consuming for large
datasets as the cases have to be reviewed
individually. As a result, we used a subset
of cases that had been previously coded as
part of a student project. On comparing
this subset (2002–2006) to the overall
dataset, we found that it displayed a
similar distribution on a number of key
variables (age, sex, nature of injury and
temporal variables). The full dataset
(1990–2009) was therefore used only for
the time-trend analysis.
Since CHIRPP is not population-based,
data are usually presented in terms of
proportions rather than strict counts. Age,
sex and year data were normalized to
the total numbers in the database using
the following expression (presented as the
number per 100 000 CHIRPP cases in the
given year, age group or sex):
NBB
~
100,000
NCHIRPP
proportion
Normalized
where NBB is the number of bunk bed
cases for the given age group, sex or year
and NCHIRPP is the total number of cases
of all types in CHIRPP for the same age
group, sex or year.
Year-to-year variations, likely due to small
sample sizes, were smoothed by applying
a three-point central moving average to
the normalized proportions.27 We examined trends in the normalized annual
proportions in two ways. We estimated
the average annual percentage change
(AAPC) in the normalized proportion
(with 95% confidence intervals [CIs]) by
performing a regression of the natural
logarithm of the normalized proportion on
year. The slope of this regression line, b,
was input into the following formula:28,29
AAPC~ eb {1 100
The data were also separated into 5-year
time blocks and analyzed for period-toperiod trends (X2 test, p < .05). Other
results are presented in conventional
descriptive format.
Bunk bed hospitalization rate estimates
To meet the secondary objective of the
study, CHIRPP was used as a data source
to develop a scaling factor to be applied
to national morbidity data. The scaling
factor is a ratio that quantifies the proportion of bunk bed cases to all bed-related
cases in CHIRPP. Hospitalization data30
for the fiscal years 2003/2004 to 2008/
2009, where the external cause of injury
was ‘‘fall involving a bed’’ (ICD-10 code
W06), were obtained from the Hospital
Morbidity Database (HMDB) for 2003/
2004 to 2005/2006 and the Discharge
Abstract Database (DAD) for 2006/2007
to 2008/2009 (excluding Quebec). The
hospital separation databases (HMDB
and DAD) are managed by the Canadian
Institute for Health Information (CIHI).
The decision to start the analysis at 2003/
2004 was due to the complex staggered
transition from ICD-9{ to ICD-10 prior to
that. CHIRPP data were arranged into the
same fiscal year ranges and stratified by
age group (0–4, 5–9, 10–14, 0–14 years)
and type of bed. For ages 0 to 4 years,
cribs, conventional beds and bunk bed
counts were identified and for ages 5 and
older, conventional beds and bunk beds
were identified. A CHIRPP scaling factor
(FCHIRPP) was developed for each age
group based on the ratio of bunk beds to
all beds (including cribs for 0–4 year olds).
The estimate for the rate of hospitalizab BB )
tions due to falls from bunk beds (R
was calculated (for each age group) using
the following equation:
!
bBB ~ FCHIRPP nW 06 100 000,
R
b age
N
where
nBB
,
FCHIRPP ~
NB
nw06 is the number of cases of hospitalization (HMDB/DAD) due to a fall involving
a bed, nBB is the number of cases admitted
to the hospital for falls from bunk beds
International Classification of Diseases, 9th Revision.
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39
Vol 33, No 1, December 2012 – Chronic Diseases and Injuries in Canada
(CHIRPP), NB is the number of cases
admitted to the hospital for falls from all
b age is the
bed types (CHIRPP), and N
population estimate for the given age
group.31
FIGURE 1
Annual trend of emergency department surveillance of injuries associated with bunk beds,
CHIRPP, all ages, 1990–2009, Canada (N = 6002)
400
N = 6002
AAPC (95% CI): −1.2% (−1.8, −0.5)
350
number per 100,000 CHIRPP cases
The rates were calculated over the 6-year
period 2003/2004 to 2008/2009. The
variability was characterized by calculating a 95% CI on FCHIRPP. All analyses were
performed using SAS version 9.2 (SAS
Institute Inc., Cary, NC, United States) and
Microsoft Excel 2007 (Redmond, WA,
United States).
Results
Time Period normalized proportion
Normalized proportion
3-point CMA
300
250
200
p = .046
150
p = .761
OR = 0.85 (0.80, 0.91)
p < .005
100
Annual trend
50
Over the 20-year surveillance period, 6002
individuals presented to Canadian emergency departments for injuries associated
with a bunk bed. While there were some
period-to-period fluctuations in the proportions of cases, the frequency of bunk
bed-related injuries in CHIRPP has overall
remained relatively stable with an AAPC
of 21.2% (21.8, 20.5; Figure 1).
0
2
3
0
1
5
6
3
8
9
9
0
5
6
7
8
1
7
2
4
4
199 199 199 199 199 199 199 199 199 199 200 200 200 200 200 200 200 200 200 200
Year
Abbreviations: AAPC, average annual percent change; CHIRPP, Canadian Hospitals Injury Reporting and Prevention
Program; CI, confidence interval; CMA, central moving average; OR, odds ratio.
Note: Counts are expressed as a proportion of all cases in the given year (normalized counts). A 3-point CMA is applied to the
normalized counts to smooth year-to-year fluctuations. The vertical bars are overall normalized counts ending on each 5-year
period (1990–1994, 1995–1999, 2000–2004 and 2005–2009).
Overview
Table 1 summarizes the 5-year subset
of analyzed cases. Figure 2 shows the
normalized age- and sex-distribution by
single year. Overall, 60.5% (n = 934) of
FIGURE 2
Emergency department surveillance of injuries associated with bunk beds according to age
and sex, CHIRPP, all ages, 2002–2006, Canada (N = 1545)a
TABLE 1
Summary of emergency department surveillance of injuries associated with bunk beds,
CHIRPP, all ages, 2002–2006, Canada
Number of cases,
n (%)
Falls,a %
Upper
934
(60.5)
93.0
Ladder
263
(17.0)
96.6
Lower
53
(3.4)
67.9
28
(1.8)
35.7
267
(17.3)
88.3
1,545
(100.0)
90.9
Other
b
Unknown
Total
N = 1545
800
Number per 100 000 CHIRPP cases
Bunk bed level
900
b
500
400
300
100
Percentage of all cases for the given bunk bed level that
were falls, including jumps.
Patient was not on the bunk bed at the time of injury:
contact with bunk bed, other person fell or jumped from
the bunk bed and struck the patient who was sleeping on
the floor, ladder fell on patient.
Males
Females
600
200
Abbreviation: CHIRPP, Canadian Hospitals Injury
Reporting and Prevention Program.
a
700
0
<1
1
2
3
4
5
6
7
8
9
10 11 12 13
Age (years)
14
15
16
17
Abbreviation: CHIRPP, Canadian Hospitals Injury Reporting and Prevention Program.
a
Counts normalized to the total number of cases in CHIRPP for the specific age-sex combination.
Vol 33, No 1, December 2012 – Chronic Diseases and Injuries in Canada
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18
19
20
21 >21
cases were related to the upper bunk, and
of those, 93% were falls. When normalized for their total numbers in the database, girls were slightly more frequent for
certain age groups.
TABLE 2
Emergency department surveillance of injuries associated with upper bunk-related incidents,
CHIRPP, all ages, 2002–2006, Canada
Characteristic
Number of cases (n = 934)
n
%
<3
131
14.0
3–5
358
38.3
6–9
297
31.8
10–13
103
11.1
14–17
30
3.2
18 +
15
1.6
527
56.4
12:00 a.m. to 7:59 a.m.
127
13.6
8:00 a.m. to 11:59 a.m.
48
5.1
Age group, years
The remainder of the analysis relates
mostly to the 934 upper bunk-related cases.
Other cases will be described briefly.
Upper bunk
Table 2 summarizes select characteristics
of the upper bunk-related events. Incidents
peaked in the 3- to 5-year age group
(38.3%; 471.2/100 000) and 10.8% were
admitted to hospital. Where reported,
42.7% (186/436) of the incidents occurred while the child was sleeping. Table 3
summarizes the specific mechanisms
involved. Of the falls where the mechanism was known (n = 664), at least
45.9% (305/664) involved an activity
which would be considered as appropriate use (sleeping/resting, getting in/
out, sitting). Table 4 shows the distribution of all injuries suffered by the
patients. Up to 3 injuries can be recorded
on the CHIRPP form; Table 4 shows all
injuries sustained, that is, that 934
children suffered 1044 injuries. Head,
face and neck injuries accounted for
39.2% (409/1044) of all injuries, and
brain injuries represented about 20%.
Fractures made up about 40% of the
total and about 1% were skull fractures.
Sex
Males
Time of day
12:00 p.m. to 3:59 p.m.
69
7.4
4:00 p.m. to 7:59 p.m.
108
11.6
8:00 p.m. to 11:59 p.m.
127
13.6
Unknown
455
48.7
Disposition
Left without being seen, advice only
202
21.6
Treated, medical follow-up if necessary
226
24.2
Treated, medical follow-up required
368
39.4
Prolonged observation in ED
Admitted to hospital
Floor
Ladder and lower bunk
Almost one-fifth of all incidents involved
the bunk-bed ladder. As a proportion of
all same-age cases, 3- to 5-year-old children were most frequent at 147.4/100 000
CHIRPP cases. About one-third of the
injuries were fractures and 5.3% were
admitted to hospital. A smaller percentage
occurred on the lower bunk. Children
aged 10 to 13 years were most frequent
at 15.9/100 000, and 3.8% were admitted
to hospital.
Table 5 shows the results of the methodology used to estimate bunk bed-related
hospitalizations due to falls. Using the
example of 5- to 9-year-olds in Table 5,
the scaling factor (FCHIRPP) is interpreted
4.0
10.8
Direct Cause
660
70.7
Bed (including ladder)
73
7.8
Other furniture
40
4.3
7
0.7
Toy
Estimates of bunk bed-related
hospitalizations due to falls
37
101
a
Ceiling fan
5
0.5
24
2.6
125
13.4
Non-carpetedc
343
39.5
Carpeted
109
12.5
Unknown
417
48.0
Other
Unknown
b
Type of surface impacted (falls)
Usage
Playing
250
26.8
Sleeping
186
19.9
Other/unknown
498
53.3
Abbreviations: CHIRPP, Canadian Hospitals Injury Reporting and Prevention Program; ED, emergency department.
a
One other case related to a ceiling fan that resulted in a fall (direct cause was the floor).
b
Based on falls from the upper bunk (n = 869).
c
Includes hardwood, ceramic, cement and linoleum/vinyl floors.
as follows: In CHIRPP, among those
admitted to hospital for an injury
involving a fall from any type of bed,
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41.2% involved bunk beds. Overall, the
estimated rates were relatively low, peaking among children aged 5 to 9 years.
Vol 33, No 1, December 2012 – Chronic Diseases and Injuries in Canada
TABLE 3
Emergency department surveillance of mechanism of upper bunk-related incidents, CHIRPP,
all ages, 2002–2006, all ages, Canada
Mechanism
Number of cases (n = 934)
n
%
Falls
869
93.0
Unintentional fall
803
85.9
While playing
247
26.4
While sleeping or resting
186
19.9
While getting in or out
99
10.6
While reaching for an object or leaning over
21
2.2
While jumping/standing on bunk bed
21
2.2
While sitting on bunk bed
20
2.1
Due to guardrail collapse
3
0.3
Struck by ceiling fan
1
< 0.3
205
21.9
Jumped off
66
7.1
Non-falls
65
7.0
Playing (not further specified)
18
1.9
Pushed or interfered with
17
1.8
Struck ceiling or top bunk while jumping on bunk bed
6
0.6
Struck by ceiling fan
5
0.5
Hanging/strangulationa
3
0.3
Not specified
Body part entrapment
Otherb
Total
2
< 0.3
14
1.5
934
100.0
Abbreviation: CHIRPP, Canadian Hospitals Injury Reporting and Prevention Program.
a
The circumstances surrounding these cases are not clear – possibly attempted suicides, unintentional snagging or patient
playing the ‘‘choking game’’ or some form of autoerotic asphyxia.
b
Includes where patient jumped into bunk bed, struck against bunk bed, was jumped on by another person and incidents
that do not clearly indicate the circumstance of injury.
Discussion
Our study provides the first comprehensive analysis of children presenting to
Canadian emergency departments with
bunk bed-related injuries. The narrative
of the CHIRPP database was exploited
to profile bunk bed-related injuries. The
CHIRPP was also used as a tool to develop
a scaling factor, or multiplier, that could
be used to approximate the crude rates of
injury hospitalizations due to falls from
bunk beds and gain more insight into
national hospitalization data related to
these.
Annual trend
Although the CHIRPP data show a significant decline over 2000 to 2004, the
trend stabilized over 2004 to 2009.
Generally, one must be cautious when
interpreting time trends; admissions
policies, enhanced capture, changes in
exposure and other factors may obscure
subtle changes. However, sharp increases,
decreases or persistence (slope < 0) can
be detected. Although there was an AAPC
of 21.2%, this change is small and of little
practical significance to injury prevention
programs; it is equivalent to a reduction of
approximately 4 cases per year.
Age guidelines
Health Canada’s Consumer Product
Safety Directorate and the U.S. Consumer
Product Safety commission recommend
that children aged less than 6 years not
be allowed on the upper bunk.5,13 Our
results show that 52.3% of all injured
patients were aged less than 6 years and
Vol 33, No 1, December 2012 – Chronic Diseases and Injuries in Canada
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that the peak age of falls and injuries is 3
to 5 years.
International literature
There have been a number of reports from
other countries about bunk bed injuries.4,8,14–18,32–33 Belechri et al.4 compared
the fall injury risk of bunk versus conventional beds in children under 15 years old
who presented to the emergency departments of four hospitals in Greece over a
three-year period (1996–98). Overall,
10.5% of falls were from bunk beds,
with a peak age of 0 to 4 years (47.7%).
Compared with conventional beds, bunk
bed-related injuries were more serious,
with a higher proportion of fractures,
brain injuries and hospital admissions.
Almost one-fifth (18.8%) of the falls
occurred while the child was sleeping.
D’Souza et al.8 updated an earlier study by
Mack et al.15 who, using the National
Electronic Injury Surveillance System
(NEISS), examined bunk bed-related injuries among those aged under 21 years
treated in U.S. emergency departments
over a 16-year period (1990–2005).
During this 16-year period, about 35 790
(42/100 000) cases of bunk bed-related
injuries were treated annually, with the
peak age at 3 to 5 years (33.2%) and no
significant trend. Selbst et al.14 prospectively studied injuries associated with
bunk beds presenting to an emergency
department for a one-year period (1987–
1988). Of the 68 children who presented,
69% were aged under 6 years and almost
one-third (29%) of the injuries occurred
while the child was asleep. Mayr et al.16
retrospectively described 218 bunk bed
injuries from a pediatric trauma unit in
Graz, Austria, for 1990–1999. The injuries
were quite severe, including concussions
(20.2%), fractures (27.5%) and 2 lacerated spleens (0.9%). Almost one-quarter
(23.8%) of children were aged under 3
years. Macgregor17 reported on 28 children who had fallen from an upper bunk;
most (78%) were aged under 6 years, and
85% of falls occurred while the child was
sleeping. Watson et al.18 reported on bunk
bed injuries in Australia, where about
2100 bunk bed-related injuries were
treated annually in hospital emergency
departments (50/100 000). The majority
(86%) of these injuries occurred in
TABLE 4
Emergency department surveillance of injury profile (body part and nature of injury) of upper
bunk-related incidents (n = 934), CHIRPP, all ages, 2002–2006, Canada
Injurya
Upper extremity
Fracture
Number of cases,
n
%
411
39.4
340
Soft Tissue
36
Sprain/strain
16
Other minor upper extremity injuries
Head, face, neck
19
409
39.2
Closed head injuries (brain)
206
19.7
Minor closed head injury
163
Concussion
41
Intracranial
2
Scalp and facial lacerations
86
8.2
Fractures
19
1.8
Skull
10
Facial
7
Cervical
2
Neck sprain/strain
8
0.8
90
8.6
148
14.2
Other minor scalp, face and neck injuries
Lower extremity
Fracture
58
Soft tissue
43
Superficial
19
Sprain/strain
19
Other minor lower extremity injuries
Trunk
9
54
Bruise, abrasion
25
Soft tissue
19
Spinal fracture (thoracic)
2
Injury to internal organ (abdomen)
1
Other minor trunk injuries
7
Asphyxia
Other/unknown
Total
5.4
2
0.2
20
1.9
1044
100
Up to three injuries can be reported per case, all injuries are indicated in this table (i.e. the 934 patients suffered 1044
injuries)
children aged under 10 years, peaking
in the 5- to 9-year age group. Falls from
the upper bunk resulting in a fracture
accounted for 33% of injuries and concussions, 10%. Johnson33 described a
pediatric Lisfranc injury, commonly called
a ‘‘bunk bed’’ fracture. The injury is
considered major as there is ligamentous
involvement and deformity. While only
14.2% of all injuries in our study were to
the lower extremity, of those 53% of lower
Admissions to hospital are often used as a
proxy for injury severity. The admission
rates recorded in the above-referenced
international studies 4,8,14–18 ranged from
2.9% to over 30% of all bunk bed-related
injuries. It is difficult to compare admission rates between countries—or even
within a country—due to different administrative policies and other factors. The
most reliable comparison is between
different injury mechanisms within the
same surveillance system. In our study,
cases involving the upper bunk had an
admission rate of 10.8%, whereas those
involving the ladder and the lower bunk
had admission rates of 5.3% and 3.8%,
respectively. Injuries associated with conventional beds, which are about 8 times
as frequent as bunk-bed injuries in
CHIRPP, have an admission rate of 3%.
A comparison of injuries of lower bunk
users and those of conventional beds
users would be of interest; even though
height would not be a factor, there may
be a higher severity of injury for the
lower bunk user due to the presence of the
upper structure.
Short-distance free-falls
Abbreviation: CHIRPP, Canadian Hospitals Injury Reporting and Prevention Program.
a
In addition, a significant proportion of
incidents occurred while the child was
sleeping (19.9%; 186/934), which has
implications for regulations and standards. Although insufficient information
was available in the narratives, for a fall to
have occurred from the upper bunk while
the child was sleeping, the guardrails
were either not attached or broke off
during the fall or the child fell through
the guardrail opening or through the
portion of the bed frame that has no
guardrail (the entrance).
extremity fractures were to the foot.
However, there was insufficient anatomical detail to classify the foot fractures as a
Lisfranc injury.
The results of our investigation align
with that of many international studies: 4,8,14–18,32–33 a high proportion of
fractures and head injuries, more admissions compared to falls from conventional
beds and peak age of injury under 6 years.
$
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There is ample literature on free falls from
a height.34–47 Based on this literature,
short falls are defined as less than 1.2 m
to 1.5 m (4–5 feet) whereas significant fall
height for the purposes of triage and injury
severity is greater than 3.0 m to 4.6 m
(10 to 15 feet). Bunk beds, at 1.7 m to
2.0 m (5.5–6.5 feet), are generally slightly
higher than the cut-off for short distance
falls. Nevertheless, there is a 50% difference in kinetic energy between a 1.2 m
(4 feet) and a 2.0 m (6 feet) fall. The
results of this study and others show that
Vol 33, No 1, December 2012 – Chronic Diseases and Injuries in Canada
TABLE 5
Estimates of the crude rate of hospitalizations (per 100 000 population) associated with falls from bunk beds, 0–14 years,
fiscal years 2003/2004 to 2008/2009, Canada
Age group, years
Hospitalizations (all bed types)b
FCHIRPPa, mean (SD)
Count
ICD-10 W06
Bunk bed Falls
Crude rate
b BB )
Estimated rate (R
95% CIc
0–4
0.117 (0.038)
1286
16.72
1.95
1.44–2.45
5–9
0.412 (0.088)
461
5.41
2.23
1.85–2.61
10–14
0.656 (0.216)
114
1.18
0.78
0.57–0.98
0–14
0.242 (0.048)
1861
7.20
1.74
1.47–2.02
Abbreviations: CHIRPP, Canadian Hospitals Injury Reporting and Prevention Program; CI, confidence interval; CIHI, Canadian Institute for Health Information; ICD-10 W06, International
Classification of Diseases, 10th Revision code W06; SD, standard deviation.
a
Scaling factor developed from case ratios (bunk bed injuries to all bed injuries, admitted for falls from a bed) in CHIRPP, fiscal years 2003/2004 to 2008/2009, ages 0–14 years.
b
Source: Health Surveillance and Epidemiology Division (Centre for Chronic Disease Prevention) analysis of PHAC holdings of CIHI morbidity data. Bed types include cribs, toddler beds,
conventional beds and bunk beds.
c
Variability is calculated with respect to the scaling factor rather than the rate per se.
serious injuries are indeed possible from
bunk-bed falls.
Other events
Although most of the non-fatal injuries
are caused by falls, there are a number
of rare and/or serious non-fall injury
mechanisms associated with bunk beds,
principally to do with intentional or
unintentional strangulation. Our investigation found 3 (0.3%) cases of hanging/
strangulation. However, it was not clear
whether these were attempted suicides,
unintentional snagging of clothing or
possibly a result of playing a ‘‘choking
game,’’ the cause of death in one fatal case
of a 12-year-old girl found hanging from
her bunk bed.48
Another mechanism involves head injury
from ceiling fan blades. We found 6 cases,
one of which lead to a fall. Mack et al.15
found that 8% of cases involved ceiling
fans. Alias et al. 49 found jumping on a
bunk bed to be a mechanism of such
injuries.
Rate estimation and exposure
In this study, we used the CHIRPP
database in a different way to help overcome the limitations of ICD coding and to
form estimates of the rates of hospitalization due to falls from bunk beds. We
found these to be fairly low: 1.74/100 000
(ages 0–14 years) with a peak at age 5 to
9 years (2.23/100 000). D’Souza et al.8
reported a rate of 42/100 000 for all
emergency department presentations
(0–21 years) and Watson et al.18 found
this rate to be 50/100 000 for Australia and
22/100 000 for the Netherlands (0–
14 years). Since hospital admission rates
vary between countries, it is not possible
to compare estimates. As a comparison,
Canadian hospitalization data for falls
from playground equipment30 over the
same time period demonstrate rates
ranging from about 16/100 000 for those
aged under 4 years to 55/100 000 for 5–9
year-olds.
Although these rates for bunk bed-related
falls are population-based, they are not
the true population rates since we do not
know the number of children sleeping in
bunk beds who do not get injured. A first
step in calculating a true population rate
would be to have a reliable measure of
the number of Canadian households with
bunk beds. We were unable to find any
Canadian data, but there were a small
number of surveys from other countries.
Based on two Australian surveys, Watson
et al.18 found the prevalence of bunk beds
to be 11% to 15%, while Senturia et al.50
indicating that, based on a cross-sectional
survey of 679 Chicago families, 24% used
bunk beds.
Young children continue to present
to Canadian emergency departments
suffering from bunk bed-related injuries,
including serious ones. Injury prevention
programs would best be served by a twopronged approach. First, the high proportion of children falling out of the upper
bunk while they are sleeping indicates that
further attention is needed in the areas of
manufacturing and standards and regulation. The second arm of the mitigation
approach relates to education with respect
to appropriate/inappropriate use of the
bunk (age, playing). CHIRPP surveillance
will continue to help inform prevention/
mitigation programs.
Acknowledgements
We thank the Consumer Product Safety
Directorate, Health Canada, for suggestions related to regulation and standards
as well as for providing the Canadian
bunk bed fatality data.
Also, thank you to Sabrina Ramji, MHSc,
University of Toronto, for her preliminary
extraction and analysis of CHIRPP data
(student project).
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native people, people living in rural
areas and those fatally injured are all
under-represented.
Vol 33, No 1, December 2012 – Chronic Diseases and Injuries in Canada
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$
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40. Thompson AK, Bertocci G, Rice W, Pierce
MC. Pediatric short-distance household
falls: biomechanics and associated injury
severity. Acc Anal Prev. 2011;43:143–50.
41. Ehsani JP, Ibrahim JE, Bugeja L, Cordner S.
The role of epidemiology in determining if a
simple short fall can cause fatal head injury
in an infant. Am J Forensic Med Pathol.
2010;31(3):287–98.
42. Thompson AK, Bertocci G, Pierce MC.
Assessment of head injury risk associated
with feet-first falls in 12-month-old children
using an anthropomorphic test device. J
Trauma. 2009;66:1019–29.
43. Chadwick DL, Chin S, Salerno C, Landsverk
J, Kitchen L. Deaths from falls in children:
how far is fatal? J Trauma. 1991;31(10):
1353–5.
44. Lyons TJ, Oates RK. Falling out of bed: a
relatively benign occurrence. Pediatrics.
1993;92(1):125–7.
45. Khambalia A, Joshi P, Brussoni M, Raina P,
Morrongiello B, Macarthur C. Risk factors
for unintentional injuries due to falls in
children aged 0–6 years: a systematic
review. Inj Prev. 2006;12:378–81.
46. Leventhal JM, Thomas SA, Rosenfield NS,
Markowitz RI. Fractures in young children:
distinguishing child abuse from unintentional injuries. Am J Dis Child. 1993;147:
87–92.
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Validation of ICD-9 diagnostic codes for bronchopulmonary
dysplasia in Quebec’s provincial health care databases
J. S. Landry, MD (1, 2); D. Croitoru, MSc (1); D. Menzies, MD (1, 2)
This article has been peer reviewed.
Abstract
Introduction: Bronchopulmonary dysplasia (BPD) is a chronic respiratory disease
caused by neonatal lung injury. The aim of this study was to validate the use of ICD-9
diagnostic codes for BPD in administrative databases to allow for their use in health care
utilization analyses.
Methods: The validation process used a retrospective cohort composed of preterm
infants, with or without respiratory complications, admitted to the Montréal Children’s
Hospital, Montréal, Quebec, between 1983 and 1992. BPD subjects were identified using
ICD-9 diagnostic codes in the provincial administrative databases (medical services and
MED-ECHO) and then matched with subjects with confirmed BPD from the validation
cohort. We examined concordance and estimated sensitivity and specificity associated
with the use of these diagnostic codes for BPD.
Results: True positive and false negative BPD subjects did not differ significantly
according to gestational age, birth weight and Apgar scores. False positive BPD subjects
were found to have significantly lower gestational age than true negative subjects. The
use of the ICD-9 diagnostic codes for BPD was associated with a specificity between
97.6% and 98.0%. The sensitivity was lower at 45.0% and 52.4% for the medical
services and MED-ECHO databases, respectively. Milder cases of BPD tended to be
missed more frequently than more severe cases.
Conclusion: The specificity of the use of ICD-9 diagnostic codes for BPD in the Quebec
provincial health care databases is adequate to allow its routine use. Its lower sensitivity
for milder cases will likely result in an underestimation of the impacts of BPD on the
long-term health care utilization of preterm infants.
Keywords: bronchopulmonary dysplasia, administrative databases, international
classification of diseases
Introduction
Bronchopulmonary dysplasia (BPD) is a
chronic respiratory disease that develops
as a result of neonatal lung injury. It is one
of the most important sequelae of preterm
birth,1 and is most common in preterm
infants who need mechanical ventilation
and oxygen therapy for respiratory distress syndrome (RDS) of the newborn.2
BPD was first described four decades ago
in children born slightly preterm with
severe RDS who were then exposed to
aggressive mechanical ventilation and
high concentrations of inspired oxygen.3
It has since been largely replaced by a new
form of the condition occurring in more
extreme preterm infants, often with less
severe RDS as a result of administering
pulmonary surfactant.4
Despite notable advances in prenatal and
neonatal care, BPD remains a major
complication, frequently resulting in mortality as well as short-term and long-term
morbidities. With the high rate of preterm
births worldwide5 and the improved survival associated with preterm birth,
numerous young adults who were born
prematurely and suffered respiratory
complications at birth manifest chronic
obstructive pulmonary disease in late
adolescence and/or early adulthood.6
Health administrative databases
In the Canadian province of Quebec, the
costs of medical services and hospital care
for all residents are covered by a universal
health insurance program administered
by the Régie de l’Assurance-Maladie du
Québec (RAMQ). RAMQ holds a vast
quantity of information useful for facilitating clinical and epidemiological research
work and for assisting health professionals
in decision making.
Since 1983, RAMQ has recorded the date
of each delivered medical service claim
and the relevant ICD-9 (International
Classification of Diseases, 9th revision)7
codes for clinical diagnoses. The medical
service claims database includes all physician reimbursement claims for hospital
and ambulatory medical services provided
to Quebec residents.
Despite the potential advantages of administrative databases, the validity of the
data, particularly the clinical diagnoses,
may be uncertain. Studies have shown
that clinical diagnoses were not reliable
for common diseases such as asthma
Author references:
1. Respiratory Epidemiology and Clinical Research Unit, McGill University, Montréal, Quebec, Canada
2. Respiratory Division, Department of Medicine, McGill University Health Centre, Montréal, Quebec, Canada
Correspondence: Jennifer S. Landry, Respiratory Epidemiology and Clinical Research Unit, McGill University, 3650 avenue Saint-Urbain, room K1.18, Montréal, QC H2X 2P4;
Tel.: 514-934-1934 ext. 32152; Fax: 514-843-2083; Email: [email protected]
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Vol 33, No 1, December 2012 – Chronic Diseases and Injuries in Canada
and chronic obstructive pulmonary
disease.8,9 As a result, despite that records
such as these could prove extremely
valuable in examining the history, prognosis and treatment of a condition, the
ability of these databases to accurately
identify patients with such conditions
must be determined. The aim of this study
was to validate the use of the Quebec
provincial health administrative databases
to identify patients who developed BPD as
a complication of preterm birth and to
observe potential differences in their
health care utilization based on the presence or absence of BPD.
Methods
Study design and selection of subjects
Validation cohort
The retrospective validation cohort
included all preterm infants, that is,
gestational age of less than 37 weeks
(259 days),10 with or without respiratory
complications, who were admitted to the
Montréal Children’s Hospital (Montréal,
Que.) between 1 January 1983 and 31
December 1992. The Montréal Children’s
Hospital is a tertiary pediatric hospital
with specialized neonatal care that serves
as a referral centre for the province of
Quebec. It does not have a maternity unit,
and all study subjects were transferred
or admitted to the hospital following a
premature birth. Data were abstracted
from hospital records using a standardized
data collection sheet. The subjects were
identified using the ICD-9 codes listed on
their medical discharge summary (prematurity: 765.*; BPD: 770.7; RDS: 769.*).
Information collected included demographic characteristics as well as maternal, prenatal, delivery and main neonatal
outcomes. Subjects’ charts were carefully
reviewed for evidence of BPD, as defined
by the need for supplemental oxygen for
at least 28 days11 (see Table 1). Disease
severity was assessed at 36 weeks postmenstrual age (or 56 days of life if born
after 32 weeks) as mild BPD if breathing
room air (fraction of inspired oxygen
[FiO2] = 0.21); moderate BPD (FiO2 <
0.30); and severe BPD (FiO2 § 0.30 or else
positive pressure ventilation). Infants with
BPD who died of respiratory causes before
the assessment date were considered to
have severe disease.11 The validation
cohort included only those subjects for
whom gestational age and neonatal exposure to supplemental oxygen (timing,
duration, FiO2) were known.
Provincial databases cohort
We constructed a retrospective cohort of
all subjects born in Quebec between 1983
and 1992 with respiratory complications
of preterm birth using data from two
RAMQ-administered provincial databases,
the MED-ECHO database and the Medical
services database. The MED-ECHO database7 contains information on acute care
hospitalizations and day surgeries performed in Quebec. Each record contains
identifying demographic information
along with the primary diagnosis on
admission and 15 possible secondary
diagnoses. This database was initiated 1
April 1987 and is complete for all subjects
born thereafter.12 The Medical services
database includes data on diagnosis,
medical billing (type of service performed,
specialty of claimant, setting of the service
(outpatient clinic, private clinic, emergency department, in-patient clinic) as
well as the number of claims, the date
on which the service was performed and
the cost paid by RAMQ to the billing
physician. This database is complete from
1 January 1983.
These two databases were used to identify
all subjects with a preterm birth, defined
as a gestational age of less than 37 weeks
(using ICD-9 code 765.*and ICD-10 code
P07.*) and diagnosed with associated
respiratory complications, either BPD
(ICD-9 code 770.7, ICD-10 code P27.1)
or RDS (ICD-9 code 769.*, ICD-10 code
P22.*).7 Data were extracted from 1
January 1983 (or 1 April 1987 in the case
of the MED-ECHO database) until 31
March 2008. ICD-9 codes were used in
these databases from 1 April 1981 until 31
March 2006, and ICD-10 codes from 1
April 2006.7
Matching process
The validation cohort was matched with
each of the provincial administrative
databases using the subjects’ unique
TABLE 1
Definition of bronchopulmonary dysplasia: diagnostic and severity criteria
Diagnosis of BPD
Gestational age, weeks
< 32
§ 32
Time of assessment
36 weeks PMA or discharge home, whichever comes first
> 28 days but < 56 days postnatal age or discharge home,
whichever comes first
Mild BPD
Breathing room air (FiO2 = 0.21) at 36 weeks PMA or discharge,
whichever comes first
Breathing room air by 56 days postnatal age or discharge,
whichever comes first
Moderate BPD
Need for FiO2 < 0.30 at 36 weeks PMA or discharge,
whichever comes first
Need for FiO2 < 0.30 at 56 days postnatal age or discharge,
whichever comes first
Severe BPD
Need for FiO2 § 0.30 and/or positive pressure (PPV or NCPAP)
at 36 weeks PMA or discharge, whichever comes first
Need for FiO2 § 0.30 and/or positive pressure (PPV or
NCPAP) at 56 days postnatal age or discharge or discharge,
whichever comes first
Treatment with oxygen
Source: Jobe & Bancalari, 200111
Abbreviations: BPD, bronchopulmonary dysplasia; NCPAP, nasal continuous positive airway pressure; PMA, postmenstrual age; PPV, positive pressure ventilation; FiO2, fraction of inspired
oxygen.
Vol 33, No 1, December 2012 – Chronic Diseases and Injuries in Canada
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RAMQ identification number. No nominal
data were used. Access to the RAMQ
database
was
approved
by
the
Commission d’accès à l’information du
Québec. This study was approved by the
research ethics board of the McGill
University Health Centre.
Statistical analyses
Subjects were divided into four categories:
(1) true positive BPD subjects who had
been diagnosed with BPD during their
initial admission following preterm birth
and were labelled as having BPD in the
administrative databases; (2) false positive BPD subjects who did not have BPD
during their initial admission or subsequent re-admissions but had been labelled
as such in the administrative databases;
(3) false negative BPD subjects who were
in the reverse situation, having been
diagnosed with BPD but not labelled as
such in the databases; and (4) true
negative subjects who had neither respiratory complications nor RDS following a
preterm birth and were not labelled as
Results
having BPD in the administrative databases. We examined the overall characteristics
associated
with
correctly
classified and misclassified cases of BPD
and used a subject-years approach to
analyze health care utilization. Analysis
of variance (ANOVA) or t-tests were
used to compare means of continuous
variables, and Mantel–Haenszel chisquare tests to compare ordinal variables.
Concordances were examined, resulting in
overall and yearly estimates of sensitivity
and specificity associated with the use
of diagnostic codes for BPD in each of
the administrative databases. For multivariable analysis, variables that were
significantly associated with the outcome
in univariate analyses were initially
included, and a multivariate Poisson
regression model12 was used to determine
the association of clinical factors with the
number of admissions and outpatient and
emergency department visits. Significance
was set at p ƒ .05. Statistical analyses
were conducted using statistical package
SAS version 9.2 (SAS Institute Inc., Cary,
NC, United States).
Subjects’ characteristics
The validation cohort consisted of 894
preterm subjects admitted to the Montréal
Children’s Hospital between 1983 and
1992. From the RAMQ records, 3442
preterm subjects were identified (773 with
BPD and 2669 with RDS). Of these, 876
were successfully matched with the validation cohort.
Table 2 shows the characteristics of the
matched subjects. Gestational age differed
significantly between the true negative
and false positive groups, with false
positive BPD subjects being on average more premature than the subjects
correctly classified as not suffering from
BPD (31 and 34 weeks of gestation,
respectively).
The use of the diagnostic codes for BPD
was associated with a specificity of 97.6%
for the medical services database and
98.0% for the MED-ECHO database.
TABLE 2
Characteristics of the correctly classified and misclassified preterm bronchopulmonary dysplasia subjects in the RAMQ databases, 1983–1992,
Quebec, Canada
RAMQ classification category
True positivea
Preterm subjects, n
Male, n (%)
104
59 (56.7)
False negativeb
True negativec
p
137
84 (61.3)
—
623
.47
384 (61.6)
False positived
12
8 (66.7)
p
—
.72
Birth weight, mean (SD) kg
1.15 (0.6)
1.05 (0.3)
.12
2.17 (0.7)
1.79 (0.7)
.12
Gestational age, mean (SD) weeks
28.0 (3.3)
27.7 (3.1)
.45
34.0 (2.9)
31.2 (3.8)
.004
1-minute Apgar score, mean (SD)
3.7 (2.4)
4.2 (2.4)
.13
6.5 (2.4)
6.1 (2.1)
.81
5-minute Apgar score, mean (SD)
6.2 (2.2)
6.4 (2.1)
.40
8.2 (1.9)
7.8 (1.3)
.78
—
623 (100)
12 (100)
—
BPD severity, (n, %)
None
0
0
Mild
16 (15.4)
36 (26.5)
—
0
0
—
Moderate
52 (50.0)
52 (38.2)
—
0
0
—
Severe
36 (34.6)
48 (35.3)
—
0
0
—
Mortality
Number, n (%)
Age, mean (SD) years
5 (4.8)
0
—
0
1 (8.3)
—
0.9 (0.64)
—
—
—
17.9 (—)
—
Abbreviations: BPD, bronchopulmonary dysplasia; RAMQ, Régie de l’Assurance-Maladie du Québec.
a
True positive subjects were diagnosed with BPD following a preterm birth and labelled as diagnosed with BPD in the administrative databases.
b
False negative subjects were not diagnosed with BPD but were labelled as such in the administrative databases.
c
True negative subjects were neither diagnosed with BPD nor labelled as such in the administrative databases.
d
False positive subjects were not diagnosed with BPD during their initial admission or subsequent re-admissions but were labelled as having BPD in the administrative databases.
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Vol 33, No 1, December 2012 – Chronic Diseases and Injuries in Canada
Sensitivity was somewhat lower, a value
of 45.0% and 52.4% respectively. Milder
cases of BPD tended to be missed more
frequently when comparing the proportion of false negative and true positive
cases (Table 2). The misclassification of
BPD subjects also varied over the years,
with the sensitivity improving after the
introduction of MED-ECHO in 1987 (see
Figure 1).
9.3 (95% confidence interval [CI]: 6.9–
12.5) for hospital readmissions, 8.1
(95% CI: 7.6–8.6) for outpatient visits
and 4.4 (95% CI: 3.6–5.3) for emergency
department visits when adjusted for
gestational age, birth weight, 1-minute
Apgar score, maternal age and the
initial severity of BPD according to the
National Institutes of Health (NIH)consensus definition.11
Implications on health care utilization
analyses
Discussion
Table 3 shows the hospital readmissions
rate per person-year across the four
categories for the entire duration of the
follow-up (mean follow-up duration:
19 years) as well as outpatient and
emergency department visits. A diagnosis
of BPD in the validation cohort was
associated with adjusted rate ratios of
The specificity for using ICD-9 diagnostic
codes for BPD in the Quebec provincial
health care databases was excellent, the
sensitivity less so, especially before the
introduction of the MED-ECHO database
in 1987. The tendency was to miss milder
cases of BPD. Since 2006, ICD-10 diagnostic codes have replaced ICD-9 codes in
Quebec’s administrative databases, but
the relevance of documenting the predictive values associated with the ICD-9
code for BPD remains, particularly
when looking at long-term health care
utilization of preterm subjects older than
6 years of age.
Subjects classified as true negative had
the fewest hospital readmissions and a
shorter length of stay, whereas true
positive BPD cases were associated with
more outpatient and emergency department visits for the duration of the 19-year
follow-up. False positive BPD subjects,
who had been more premature at birth
than those of their counterparts not
diagnosed with BPD, had more hospital
readmissions and a longer length of stay in
hospital. The presence of BPD as a complication of a preterm birth was found to
have a great impact on health care utilization, an effect that remained significant
FIGURE 1
Specificity and sensitivity of the medical services and MED-ECHO databases for the diagnostic codes of bronchopulmonary dysplasia,
1983–1992, Quebec, Canada
1.0
0.9
0.8
0.7
0.6
specificity (Med. Services)
0.5
specificity (MED-ECHO)
sensitivity (Med. Services)
0.4
sensitivity (MED-ECHO)
0.3
0.2
0.1
0.0
1983
1984
1985
1986
1987
1988
1989
Abbreviation: Med, Medical.
Vol 33, No 1, December 2012 – Chronic Diseases and Injuries in Canada
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1990
1991
1992
TABLE 3
Health care utilization across correctly classified and misclassified preterm bronchopulmonary dysplasia subjectsa
RAMQ classification category
True positiveb
f
Hospital admissions /person-year, n
Length of stay, mean (SD) days
1.6
False negativec
1.3
11.6 (26.4)
18.3 (32.6)
True negatived
p
False positivee
p
.023
1.1
1.7
.004
.22
4.2 (7.8)
6.4 (15.8)
.01
Outpatient visits/person-year, n
6.7
3.2
<.0001
3.7
5.4
.45
ED visits/person-year, n
3.0
1.7
.0001
2.8
2.7
.33
Abbreviations: BPD, bronchopulmonary dysplasia; ED, emergency department; RAMQ, Régie de l’Assurance-Maladie du Québec.
a
Mean follow-up duration of BPD subjects was 19 years.
b
True positive subjects were diagnosed with BPD following a preterm birth and labelled as having BPD in the administrative databases.
c
False negative subjects were not diagnosed with BPD but were labelled as such in the administrative databases.
d
True negative subjects were neither diagnosed with BPD nor labelled as such in the administrative databases.
e
False positive subjects were not diagnosed with BPD during their initial admission or subsequent re-admissions but were labelled as having BPD in the administrative databases.
f
Hospital re-admission following initial hospital discharge after birth.
when corrected for birth weight, gestational age, Apgar score and maternal age.
Limitations
The main limitation of this study is the
evolving definition of BPD in clinical
practice over the duration of the study
period. Until the consensus definition for
BPD was reached in 2000,11 there was a
striking lack of uniformity in the diagnostic criteria for BPD among clinicians and in
the medical literature.13 The criteria proposed to define BPD (suggested in an NIHsponsored workshop in 1979) included
continued oxygen dependency during the
first 28 days in addition to compatible
clinical and radiological changes.3 These
criteria were considered appropriate for
the classic presentation of BPD, but less so
for identifying ‘‘new’’ BPD cases identified
after the early 1990s. Accordingly, the
following definition was proposed: the
need for supplemental oxygen at 36 weeks
post-menstrual age (PMA).14 This stricter
definition was considered better for identifying infants with more severe lung
disease and therefore at predicting longterm outcome.15 This definition was
further refined at an NIH workshop in
2000 to include the need for 28 days or
more of supplemental oxygen as well as a
severity assessment date at 36 weeks
PMA.11 A repeat validation study using
subjects born after 2000 will address this
limitation.
A minor limitation was the incomplete
matching process (2%) between the validation cohort and the provincial databases
cohort. Missing unique RAMQ identification numbers at the time of admission, a
frequent occurrence in infants since they
are admitted at birth under their maternal
RAMQ identification number, accounted
for the discrepancy of the matching
process between the two cohorts.
A third limitation was the incompleteness
of the MED-ECHO database over the first
4 years of the study period, likely resulting
in an incomplete capture of the BPD cases
during this time and an underestimation of
the health care utilization with regard to
the number of hospitalizations.
References
1.
Wohl ME. Bronchopulmonary dysplasia
in adulthood. N Engl J Med. 1990 Dec
27;323(26):1834–6.
2.
Bancalari E, Claure N, Sosenko IR.
Bronchopulmonary dysplasia: changes in
pathogenesis, epidemiology and definition.
Semin Neonatol. 2003 Feb;8(1):63–71.
3.
Bancalari E, Abdenour GE, Feller R,
Gannon J. Bronchopulmonary dysplasia:
clinical presentation. J Pediatr. 1979
Nov;95(5 Pt 2):819–23.
4.
Russell RB, Green NS, Steiner CA, Meikle S,
Howse JL, Poschman K, et al. Cost of
hospitalization for preterm and low birth
weight infants in the United States.
Pediatrics. 2007 Jul;120(1):e1–9.
5.
Howson CP, Merialdi M, Lawn JE, Requejo
JH, Say L, , editors. March of Dimes white
paper on preterm birth, the global and
regional toll. White plains (NY): March of
Dimes Foundation; 2009.
6.
Landry JS, Chan T, Lands L, Menzies D.
Long-term impact of bronchopulmonary
dysplasia on pulmonary function. Can
Respir J. 2011 Sep;18(5):265–70.
7.
Classification of Diseases, Functioning, and
Disability. International Classification of
Diseases, 9th rev [Internet]. Atlanta (GA):
Centers for Disease Control and Prevention;
2010 [cited 2010 February 25]. Available from:
http://www.cdc.gov/nchs/icd/icd9.htm
Conclusion
The specificity of the use of ICD-9 diagnostic codes for BPD in the Quebec
provincial health care databases is adequate to allow its routine use. Its lower
sensitivity for milder cases will likely
result in an underestimation of the
impacts of BPD on the long-term health
care utilization of those born preterm.
Acknowledgements
This study was supported by a grant from
the Réseau en Santé Respiratoire - Fonds
de la recherche en santé du Québec.
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8.
Lacasse Y, Montori VM, Lanthier C, Maltis
F. The validity of diagnosing chronic
obstructive pulmonary disease from a large
administrative database. Can Respir J.
2005;12(5):251–6.
9.
Monfared AA, Lelorier J. Accuracy and
validity of using medical claims data to
identify episodes of hospitalizations in
patients with COPD. Pharmacoepidemiol
Drug Saf. 2006 Jan;15(1):19–29.
10. Landry JS, Menzies D. Occurrence and
severity of bronchopulmonary dysplasia
and respiratory distress syndrome after a
preterm birth. Paediatr Child Health. 2011
Aug/Sept 2011;16(7):399–403.
11. Jobe AH, Bancalari E. Bronchopulmonary
dysplasia. Am J Respir Crit Care Med. 2001
Jun;163(7):1723–9.
12. SAS annotated output: multinomial logistic
regression [Internet]. Los Angeles (CA):
UCLA, Academic Technology Services;
[cited 2009 May 1]. Available from:
http://www.ats.ucla.edu/stat/SAS/output
/SAS_mlogit.htm
13. Roussy JP, Aubin MJ, Brunette I, Lachaine
J. Cost of corneal transplantation for
the Quebec health care system. Can J
Ophthalmol. 2009 Feb;44(1):36–41.
14. Shennan AT, Dunn MS, Ohlsson A, Lennox
K, Hoskins EM. Abnormal pulmonary outcomes in premature infants: prediction
from oxygen requirement in the neonatal
period. Pediatrics. 1988 Oct;82(4):527–32.
15. Silber JH, Lorch SA, Rosenbaum PR,
Medoff-Cooper B, Bakewell-Sachs S,
Millman A, et al. Time to send the
preemie home? Additional maturity at
discharge and subsequent health care
costs and outcomes. Health Serv Res.
2009 Apr;44(2 Pt 1):444–63.
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Report summary
Diabetes in Canada: facts and figures from a public health
perspective
C. Pelletier, MSc; S. Dai, MD, PhD; K. C. Roberts, MSc; A. Bienek, MHA; J. Onysko, MA; L. Pelletier, MD, MPH
Introduction
Diabetes in Canada: facts and figures
from a public health perspective is the
first comprehensive diabetes surveillance
report published by the Public Health
Agency of Canada. The report aims to
support public health professionals and
organizations in developing effective,
evidence-based public health policies and
programs to prevent and manage diabetes
and its complications.
The report, developed in collaboration with
provincial and territorial governments, the
Canadian Diabetes Association, Juvenile
Diabetes Research Foundation, CNIB,
Health Canada and the academic community, uses data from national health surveys
and vital statistics, as well as populationbased administrative data from the
Canadian Chronic Disease Surveillance
System (CCDSS). For the first time, the
CCDSS contains data from all 13 Canadian
jurisdictions.
Using CCDSS data representing cases of
diagnosed diabetes among Canadians
aged one year and older, Diabetes in
Canada presents prevalence and incidence
national rates from the fiscal year 2008/
2009 and national trends from 1998/1999
onwards.* The report also outlines
sub-populations at higher risk, ways of
reducing the risks of developing the
disease and its complications, and
estimates of related economic costs. In
addition, it contains sections on specific
populations, including children and
youth and First Nations, Inuit and Métis
populations.
Highlights
Prevalence and incidence
Nearly 2.4 million Canadians (6.8%) were
living with diagnosed diabetes in 2008/
2009. According to data obtained from
blood samples, it is estimated that an
additional 450 000 had undiagnosed diabetes at that time.
The overall age-standardized prevalence
of diagnosed diabetes increased by 70%
since 1998/1999. Prevalence has been
consistently higher among males than
females, and has increased in every age
group, particularly in the 35- to 39-year
and 40- to 44-year age groups, where
proportions doubled. According to projections, an estimated 3.7 million Canadians
will have diabetes by 2018/2019.
Over 200 000 Canadians (6.3 incident
cases per 1000 population) were newly
diagnosed with diabetes in 2008/2009
alone (6.8 incident cases per 1000 males,
5.7 incident cases per 1000 females), and
nearly half were aged between 45 and
64 years. Age-standardized diabetes incidence rates among Canadians remained
relatively stable between 1998/1999 and
2008/2009.
Diabetes in children and youth
In 2008/2009, more than 3000 incident
cases of both types of diabetes were
reported among Canadians aged 1 to 19
years. Type 1 diabetes remains the most
prevalent form of diabetes in children and
youth, but type 2 diabetes has been on the
rise among youth worldwide for the last
two decades.
Diabetes in First Nations, Inuit and Métis
populations
The age-standardized prevalence of diabetes was 17.2% among First Nations
people living on-reserve, 10.3% among
those living off-reserve and 7.3% among
Métis, while the prevalence among Inuit
was comparable to that of the general
Canadian population. Compared to nonAboriginal individuals, Aboriginal people
are generally diagnosed with diabetes at a
younger age and experience higher rates
of complications, and females experience
higher rates of gestational diabetes.
Comorbidities, complications, health care
utilization and economic burden
In 2009–2010, 36.5% of Canadian adults
with diabetes reported having two or
more serious chronic conditions (hypertension, heart disease, chronic obstructive
pulmonary disease, mood disorder and/or
arthritis). Compared to individuals without diabetes, those with the disease were
* Specific conventions are used to distinguish between different periods of reference used by the various data sources. The following section of the report presents more information on these
conventions, periods of reference, and data sources: http://www.phac-aspc.gc.ca/cd-mc/publications/diabetes-diabete/facts-figures-faits-chiffres-2011/introduction-eng.php#bx3
Author reference:
Chronic Disease Surveillance and Monitoring Division, Centre for Chronic Disease Prevention, Public Health Agency of Canada, Ottawa, Ontario, Canada
Correspondence: Catherine Pelletier, Centre for Chronic Disease Prevention, Public Health Agency of Canada, 785 Carling Avenue, A.L. 6806A, Ottawa, ON K1A 0K9; Tel.: 613-946-6954;
Fax: 613-941-2057; Email: [email protected]
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53
Vol 33, No 1, December 2012 – Chronic Diseases and Injuries in Canada
over 3 times as likely to be hospitalized
with cardiovascular disease, 12 times as
likely with end-stage renal disease and
almost 20 times as likely with nontraumatic lower limb amputation.
In 2008/2009, working age adults (20–
49 years old) with diabetes saw a family
physician twice as often as those without
diabetes, and specialists two to three times
as often. Annual per capita health care
costs have been estimated to be three to
four times greater in a population with
diabetes than that without.
Mortality
Diabetes itself does not typically cause
death, but complications from diabetes
can and do. This is reflected in decreased
life expectancy and health-adjusted life
expectancy. More than a quarter (29.9%)
of those who died in 2008/2009 had
diabetes. In every age group, individuals
with diabetes have mortality rates at
least double that of those without the
disease.
Prevention
Summary
Although overall incidence of diabetes has
been stable over the last decade, prevalence has been increasing steadily, resulting in a substantial number of Canadians
living with diabetes. Our population is
aging; together with increasing rates of
obesity, the risk of developing diabetes is
expected to increase. However, Canadians
can reduce their individual risk by being
physically active and by maintaining
normal weight or losing excess body
weight.
For those with diabetes, self-management
through lifestyle modifications and/or use
of blood sugar-lowering medication is key.
Moreover, blood sugar, blood cholesterol,
blood pressure, kidney function and the
eyes should be regularly monitored to
prevent or mitigate the development of
complications.
The full version of this report is
available on the Public Health Agency of
Canada website at: http://www.phac-aspc
.gc.ca/cd-mc/publications/diabetes-diabete
/facts-figures-faits-chiffres-2011/index-eng
.php
Social, economic, environmental, lifestyle
and genetic factors all have significant
effects on the distribution of type 2
diabetes in the Canadian population.
Advancing age, obesity, physical inactivity
and ethnic background as well as a family
history of diabetes (or gestational diabetes) are all important risk factors.
Obese adults are two to four times as
likely to have type 2 diabetes. In 2007–
2009, 23.9% of adults aged 18 years and
older were obese according to measured
body mass index. In 2009–2010, almost
half (47.4%) of Canadians aged 12 years
and older reported that they were physically inactive (leisure and transportation
index); in the same period, more than half
(55.9%) reported eating vegetables and
fruit less than five times a day, which is
used as a proxy measure of unhealthy diet.
The risk factors for type 1 diabetes are still
not well understood. Studies suggest that
genetic predisposition and environmental
factors that trigger the auto-immune
response are implicated.
Vol 33, No 1, December 2012 – Chronic Diseases and Injuries in Canada
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54
CDIC: Information for authors
Chronic Diseases and Injuries in Canada (CDIC) is a
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injuries in Canada. Its feature articles are peer
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