Health Reports Volume 2

Health Reports  Volume 2
Catalogue no. 82-003-X
Health
Reports
Volume 21, Number 4
Statistics
Canada
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HealthReports
Health
Reports
Catalogue no. 82-003-XPE • Volume 21 Number 4
A C a n a d i a n p e e r - r e v i e w e d j o u r n a l o f
population health and health services research
Published by authority of the Minister responsible for Statistics Canada
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Catalogue no. 82-003-XPE, Vol. 21, No. 4
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Catalogue no. 82-003-XIE, Vol. 21, No. 4
ISSN 1209-1367
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Health Reports, Vol. 21, no. 4, December 2010 • Statistics Canada, Catalogue no. 82-003-XPE
Editor-in-Chief
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Managing Editor
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Aussi disponible en français : Rapports sur la santé, no 82-003-X au catalogue
Nazeem Muhajarine
University of Saskatchewan
Georgia Roberts
Statistics Canada
Nancy Ross
McGill University and Statistics Canada
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Statistics Canada, Catalogue no. 82-003-XPE • Health Reports, Vol. 21, no. 4, December 2010
3
About Health Reports
H
ealth Reports publishes original research on diverse
topics related to the health of populations and the
delivery of health care. The journal archives, for the
research and policy communities and for the general public,
discoveries from analyses of national/provincial surveys and
administrative databases, as well as results of international
comparative health research. Health Reports is also a forum
for sharing methodological information by those using
health surveys or administrative databases. Health Reports
is produced by the Health Analysis Division at Statistics
Canada. Articles appear monthly in electronic format and
quarterly in print, and are indexed in Index Medicus and
MEDLINE.
For more information about Health Reports, contact
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Canada, 24th Floor, R.H. Coats Building, Ottawa,
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Editorial Board
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University of Toronto
Bill Avison
University of Western Ontario
Adam Baxter-Jones
University of Saskatchewan
Lise Dubois
University of Ottawa
James Dunn
University of Toronto and Centre for
Research on Inner City Health
Bob Evans
University of British Columbia
David Feeny
Kaiser Permanente
Rick Glazier
Institute for Clinical Evaluative Sciences and
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Judy Guernsey
Dalhousie University
Glenn Irwin
Health Canada
Howard Morrison
Public Health Agency of Canada
Cameron Mustard
Institute for Work and Health, University of
Toronto
Tom Noseworthy
University of Calgary
Patricia O’Campo
University of Toronto and Centre for
Research on Inner City Health
Jennifer O’Loughlin
University of Montreal
Indra Pulcins
Canadian Institute for Health Information
Nancy Ross
McGill University and Statistics Canada
Paul Veugelers
University of Alberta
Michael Wolfson
Statistics Canada
4
Health Reports, Vol. 21, no. 4, December 2010 • Statistics Canada, Catalogue no. 82-003-XPE
In this issue
Research articles
Neighbourhood variation in hospitalization for
unintentional injury among children and teenagers... 9
by Lisa N. Oliver and Dafna E. Kohen
Children and teenagers in the lowest neighbourhood income quintile
are generally more likely to be hospitalized for unintentional injury than
are those in the highest neighbourhood income quintile.
Socio-economic status and vitamin/mineral
supplement use in Canada ........................................ 19
by Hassanali Vatanparast, Jennifer L. Adolphe and
Susan J. Whiting
Age, being female, high household income and education, and being
food secure are positively associated with supplement use.
Trends in long-term care staffing by facility
ownership in British Columbia, 1996 to 2006 ........ 27
by Margaret J. McGregor, Robert B. Tate, Lisa A. Ronald,
Kimberlyn M. McGrail, Michelle B. Cox, Whitney Berta and
Anne-Marie Broemeling
From 1996 to 2006, total nursing hours per resident-day rose in all
facility ownership groups, but the rate of increase was greater in notfor-profit facilities operated by health authorities.
Asthma and school functioning ................................ 35
by Dafna E. Kohen
Compared with children who did not have a chronic condition, those
with asthma score lower on standardized math and reading tests and
have less favourable mother-reported school performance.
Statistics Canada, Catalogue no. 82-003-XPE • Health Reports, Vol. 21, no. 4, December 2010
Health matters
Recent trends in upper respiratory infections, ear
infections and asthma among young Canadian
children ....................................................................... 47
by Eleanor M. Thomas
Since 1994/1995, the prevalence of asthma declined among children
aged 2 to 7. Among children aged 2 to 3, the prevalence of upper
respiratory infections remained constant or fell in most regions, and ear
infections declined significantly in all regions.
Chronic pain at ages 12 to 44 .................................... 53
by Pamela L. Ramage-Morin and Heather Gilmour
In 2007/2008, about 1 in 10 Canadians aged 12 to 44—9% of men and
12% of women—experienced chronic pain.
H1N1 vaccination ....................................................... 63
by Heather Gilmour and Nancy Hofmann
As of April 2010, the majority of Canadians aged 12 or older—59%—
had not been vaccinated against the H1N1 virus.
5
6
Health Reports, Vol. 21, no. 4, December 2010 • Statistics Canada, Catalogue no. 82-003-XPE
In this issue
Methodological insights
Combining nutrient intake from food/beverages
and vitamin/mineral supplements ............................ 71
by Didier Garriguet
To calculate total intake of a nutrient and estimate inadequate intake for
a population, the amounts derived from from food/beverages and from
vitamin/mineral supplements must be combined.
Validation of cognitive functioning categories in
the Canadian Community Health Survey—Healthy
Aging ........................................................................... 85
by Leanne Findlay, Julie Bernier, Holly Tuokko, Susan Kirkland
and Heather Gilmour
Four measures of cognitive functioning for the household population
aged 45 or older were coded into five categories that can be used in
future work on cognition based on the Canadian Community Health
Survey—Healthy Aging.
Erratum .................................................................... 101
Statistics Canada, Catalogue no. 82-003-XPE • Health Reports, Vol. 21, no. 4, December 2010
7
Peer reviewers
The clinical, methodological and subject matter specialists
listed below have reviewed articles submitted for Volume 21
of Health Reports. The editors thank them for their valuable
contributions of time and expertise.
Stephanie A. Atkinson
Tory Atwood
Julie Bernier
Peter Bolli
Evelyne Bougie
Joe Braun
Danielle Brulé
Lyne Cloutier
Jennifer L. Copeland
Carolyn De Coster
Michael Cusimano
Kevin Dodd
Malcolm Doupe
John A. Fleishman
George Fodor
Eduardo Franco
Cy Frank
Rochelle Garner
Didier Garriguet
Richard H. Glazier
Katherine Gray-Donald
Tim Green
Pierre Guy
Pavel Hamet
Charlene Harrington
John Hay
Michael Hayes
Scott Hofer
Chanda Nicole Holsey
Michel Joffres
Tracy Johnson
Louise Johnson-Down
Shonna Kelly
Scott T. Leatherdale
Nora Lee
Brian McCrindle
Margaret A. McDowell
Alex McKay
Sheniz Moonie
Cameron Mustard
Lindsay Nettlefold
K. Bruce Newbold
Edward Ng
Arto Ohinmaa
Robert Pampalon
Beth Pietersen
Annie Robitaille
Michelle Rotermann
Don Schopflocher
Margot Shields
Lesbia Smith
Janet Smylie
Paula J. Stewart
Scott Thomas
Angus H. Thompson
Brian W. Timmons
Ellen L. Toth
Frank Trovato
Hope Weiler
Kathryn Wilkins
Doug Willms
E L E C T R O N I C P U B L I C AT I O N S
AVA I L A B L E AT
w w w. s t a t c a n . g c . c a
Statistics Canada, Catalogue no. 82-003-XPE • Health Reports, Vol. 21, no. 4, December 2010
Neighbourhood variation in hospitalization for unintentional injury among children and teenagers • Research article
9
Neighbourhood variation in
hospitalization for unintentional injury
among children and teenagers
by Lisa N. Oliver and Dafna E. Kohen
Abstract
Background
Research suggests that living in more affluent
neighbourhoods positively influences children’s
health. Relationships with injury are less
clear. This study examines variations in
rates of unintentional injury hospitalization by
neighbourhood income for the population aged 0
to 19 in urban Canada.
Data and methods
Acute-care inpatient hospitalization discharge
records from 2001/2002 through 2004/2005 for
0- to 19-year-olds were examined. Injuries were
classified using the International Classification
of Diseases. Census Dissemination Areas were
used as neighbourhood proxies; income quintiles
were calculated from the 2001 Census. Agestandardized rates of hospitalization per 10,000
person-years at risk were calculated for each type
of injury, by sex, age group and neighbourhood
income quintile.
Results
Children and teenagers in the lowest
neighbourhood income quintile generally had a
higher rate of unintentional injury hospitalization
than did those in the highest. The pattern was
particularly evident among children aged 0 to 9
in lower-income neighbourhoods for injuries due
to land transportation, poisoning, fire, drowning/
suffocation, being cut or pierced, and the natural
environment.
Interpretation
Canadian children in lower-income
neighbourhoods generally have higher rates
of hospitalization due to unintentional injuries,
compared with children in higher-income
neighbourhoods.
Keywords
Child development, hospital records, social class,
social conditions, socio-economic status, trauma,
wounds and injuries
Authors
Lisa N Oliver (1-613-951-4708; [email protected]
statcan.gc.ca) and Dafna E Kohen (1-613-9513346; [email protected]) are with the
Health Analysis Division at Statistics Canada,
Ottawa , Ontario, K1A 0T6
U
nintentional injury of children and teenagers
has been identified as a public health problem
in Canada.1 In 2004, unintentional injuries were
responsible for 30,345 hospitalizations of children
and youth aged 0 to 19.2 About one-fifth of all
acute-care inpatient hospitalization costs for children
in 2003/2004 were attributable to injuries and
poisonings.3 Severe injury and trauma in childhood
are associated with disability and poor health-related
quality of life in both the short- and long-term.4-7
Moreover, unintentional injury is the leading cause
of death among Canadian children and teenagers,
accounting for 664 deaths in 2004.8
The neighbourhood environment has
been identified as an important factor in
children’s health.9-13 But while research
suggests that living in more affluent
neighbourhoods positively influences
children’s health, relationships with
injury are less clear, and growing
evidence indicates that associations
depend on the type of injury.14-22
For several reasons, neighbourhood
income may be related to childhood injury.
The social and physical environments in
lower-income neighbourhoods may place
children at risk of injury.23-26 As well,
associations between neighbourhood
income and injury may reflect individual
and family factors. For instance, children
in low-income families are less likely
than those in more affluent families to
use bicycle helmets,27,28 and more likely
to be exposed to hazards in the home.29
Previous studies have examined
associations between neighbourhood
disadvantage and childhood injury using
self- or parent-reported survey data30-32 or
administrative data on hospitalizations
and mortality.22,33-35 Surveys, however,
typically collect information about only
one injury, and the reported prevalence
of severe injuries (that is, resulting in
hospitalization) is low. Studies based
on administrative data tend to focus on
a single hospital or city,22,35 or do not
10
Health Reports, Vol. 21, no. 4, December 2010 • Statistics Canada, Catalogue no. 82-003-XPE
Neighbourhood variation in hospitalization for unintentional injury among children and teenagers • Research article
investigate a full range of unintentional
injuries.33,34
To address some of these
shortcomings, this study uses national
hospital data to examine relationships
between urban neighbourhood income
and hospitalization for unintentional
injury among children and teenagers.
Methods
The Hospital Morbidity Database
(HMBD) contains discharge records
for each hospital stay. Health PersonOriented Information (HPOI), processed
from the HMBD, links these records
at the person level. HPOI includes the
patient’s age, sex, medical diagnoses,
admission/discharge dates, and place of
residence.
For this analysis, 87% of the hospital
morbidity records were linked at the
person level. Of the 13% that were
not linked, 10% were for newborns
(excluded), and 3% contained an invalid
identifier. This study is based on 852,234
hospitalization records for children and
youth aged 0 to 19 in urban Canada who
had been discharged from acute-care
hospitals during fiscal years (April to
March) 2001/2002 to 2004/2005.
Injury classification
The International Classification of
Diseases (ICD) was used to classify
unintentional injuries. Not all Canadian
provinces used the same version of the
ICD during the study period; ICD codes
were analysed by the version submitted
(Appendix Table A).
The data represent “injury episodes,”
not the number of hospital discharges or
unique individuals.
Hospital discharge records allow
multiple diagnoses to be listed; records
were included in this analysis if an
unintentional injury appeared as a
diagnosis at least once.
HPOI has a unique record for
each hospital discharge. To prevent
multiple counting of a single injury, an
“injury episode” was constructed for
people discharged and readmitted (for
example, transferred between hospitals)
on the same day. During the study
period, there were 76,227 unintentional
“injury episodes” for 0- to 19-yearolds, representing 73,244 individuals.
The vast majority of these individuals
(96.3%, n=70,537) were hospitalized
once; 3.7% (n=2,707) had more than
one unintentional injury hospitalization
during the four years.
In all provinces except Quebec,
multiple injury codes can be recorded
for a single injury. A total of 349
hospitalizations (0.45% of all cases) had
injury codes in multiple categories. A
sample of cases with multiple injuries
was examined, and because all appeared
plausible (for instance, hypothermia and
motor vehicle traffic injury), they were
included in the study.
Definitions
Unintentional injury refers to all
unintentional injuries excluding adverse
effects or complications of medical
and surgical care. Unintentional injuries
were grouped into nine categories based
on injury classifications from the Public
Health Agency of Canada36: falls, land
transportation, being struck, being cut/
pierced, poisoning, fire, drowning/
suffocation,
natural
environment,
and other. This classification system
was originated by the International
Collaborative Effort on Injury.
Injuries from falls result from falls
on ice/snow, furniture, playground
equipment, trees, or cliffs.
Falls
involving transport vehicles, in water
(for instance, drowning), and associated
with fire are categorized elsewhere.
Land transportation injuries pertain to
accidents on land involving pedestrians,
cyclists, motorcycles, cars, pick-up
trucks, vans, heavy transport vehicles,
buses, trains, streetcars, industrial
vehicles, and off-road vehicles.
Struck refers to injuries due to being
struck by or against a thrown object,
sports equipment, a person or crowd, or
walking into an object.
Cut/Pierce injuries (including those
due to machinery) result from contact
with objects such as glass, knives, hand
tools, lawnmowers, powered tools and
household machinery, and contact with
lifting devices, agricultural machinery or
unspecified machinery.
Fire injuries result from fires in private
dwelling, buildings, or other structures,
outside of buildings (for example, forest
fire), ignition of clothing, and from the
burning of objects.
Poisoning
includes
accidental
poisoning by exposure to medication,
narcotics, pesticides, chemicals, gases
and vapours.
Drowning/Suffocation
(separate
causes that were combined into
one category) refers to drowning or
submersion in a bathtub, swimming
pool or natural body of water, and
suffocation due to earth or other
substances, obstruction of respiratory
tract, confinement in a low-oxygen
environment, or in bed.
Natural environment includes being
bitten, stung or struck by an animal,
insect, plant; exposure to noise, vibration,
heat, cold, change in air pressure; and
lack of food and water.
Other encompasses injuries due to
firearms, overexertion, explosion of
an object, exposure to electric current,
sequelae or late effects of an event
classified elsewhere, and non-land
transportation accidents.
Dissemination
Areas
(DAs)—
small geographic census units with a
population of 400 to 700—were used as
proxies for neighbourhoods. During data
processing, the DAs in which patients
lived were determined from their postal
code by the Postal Code Conversion
File + .37 DA assignment was less
precise in the province of Quebec, where
hospital discharge records contain only
the first three digits of the six-digit postal
code. Sensitivity analyses that excluded
Quebec did not produce significantly
different results, so Quebec was
included in all analyses. DAs in Census
Metropolitan Areas (CMAs) or Census
Agglomerations (CAs) were considered
urban. CMAs are urban areas with a
population of at least 100,000; CAs have
an urban core of at least 10,000.38
Statistics Canada, Catalogue no. 82-003-XPE • Health Reports, Vol. 21, no. 4, December 2010
Neighbourhood variation in hospitalization for unintentional injury among children and teenagers • Research article
Neighbourhood income quintiles were
constructed from the 2001 Census using
the average income per single-person
equivalent in each DA, which adjusts for
differences in household size. Average
income per single-person equivalent
was calculated by dividing the total
household income of the DA by the total
number of single-person equivalents. To
account for variations in the cost of living
across Canada, income quintiles were
constructed within each CMA and CA.
Income was suppressed in DAs with
populations less than 250, and in such
cases, was imputed from surrounding
DAs with unsuppressed data.
A total of 1,086 unintentional injury
hospitalizations (1.4%) were excluded
from analyses because DA income data
were not available: in 1,049 of these
cases, this was because of a missing or
invalid postal code; in 37 cases, income
data could not be imputed because of
suppression in surrounding DAs.
significance. SAS (version 9.1, SAS
Institute, USA) software was used for all
statistical analyses.
Results
Rates higher among males/teens
During the four years from 2001/2002
through 2004/2005, hospitalizations
for unintentional injuries among 0- to
19-year-olds in urban areas totalled
76,227 (Table 1). Males accounted for
two-thirds of these hospitalizations,
so as might be expected, the crude
hospitalization rate per 10,000 personyears at risk was much higher for males
(40.8) than for females (21.6). Crude
rates tended to rise with age from about
30 hospitalizations per 10,000 personyears at risk for children younger than 10
to almost 35 per 10,000 person-years at
risk for 15- to 19-year-olds.
Falls were the leading cause of
unintentional injury hospitalizations
(43%), followed by injuries associated
with land transportation (21%) (Figure 1).
Another 11% of unintentional injury
hospitalizations resulted from being
struck. Relatively few were attributable
to poisoning (5%), cut/pierce (3%), fire
(2%), natural environment (2%), or
drowning/suffocation (1%).
Because of the uneven age distribution
of the population across neighbourhood
income
quintiles,
unintentional
injury hospitalization rates were agestandardized. The age-standardized rates
fell from about 33 hospitalizations per
10,000 person-years at risk in the lowestincome neighbourhoods to about 30 per
Table 1
Number of hospitalizations for unintentional injury, person-years at risk and
crude rate per 10,000 person-years at risk, urban population aged 0 to 19,
Canada, 2001/2002 to 2004/2005
Statistical methods
Hospitalization rates for unintentional
injuries were calculated based on
the 2001 Census. Rates were agestandardized to account for the unequal
distribution of the population by age
across neighbourhood income quintiles.
Person-years at risk were used as
the denominator for hospitalization
rates. This was interpolated from the
2001 and 2006 Census using the midpoint of the fiscal year (October). The
final denominator was the sum of the
interpolated populations across the
four fiscal years: 2001/2002 through
2004/2005. Rates per 10,000 personyears at risk were calculated by age group
(0 to 9 and 10 to 19) and by sex for income
quintiles; 95% confidence intervals were
based on a Poisson distribution.
The t-test was used to determine if
injury hospitalization rates in the highest
neighbourhood income quintile differed
significantly from the lower quintiles.
A Linear Trend Test (LTT) was used to
detect linear relationships between injury
hospitalization rates and neighbourhood
income quintiles.39 An alpha level
of p<0.05 was used to determine
11
Rate per 10,000
person-years at risk
Hospitalizations
Person-years
at risk
Crude
Agestandardized
Total
76,227
24,295,310
31.4
31.3
Sex
Male
Female
50,653
25,574
12,426,567
11,868,743
40.8
21.6
40.7
21.6
Age (years)
0 to 4
5 to 9
10 to 14
15 to 19
16,212
16,556
20,972
22,487
5,391,425
6,008,589
6,395,095
6,500,201
30.1
27.6
32.8
34.6
...
...
...
...
Neighbourhood income quintile
1 (lowest )
2
3
4
5 (highest)
14,806
14,346
15,401
16,139
15,535
4,514,570
4,500,780
4,852,265
5,266,500
5,161,195
32.8
31.9
31.7
30.6
30.1
32.7
31.9
31.7
30.6
29.9
Injury category†
Falls
Land transportation
Struck
Poisoning
Cut/Pierce
Natural environment
Fire
Drowning/Suffocation
Other
32,695
15,880
8,335
3,953
2,230
1,760
1,750
993
8,980
24,295,310
24,295,310
24,295,310
24,295,310
24,295,310
24,295,310
24,295,310
24,295,310
24,295,310
13.5
6.5
3.4
1.6
0.9
0.7
0.7
0.4
3.7
13.5
6.5
3.4
1.6
0.9
0.7
0.7
0.4
3.7
†
because multiple injuries were recorded, subcategories add to more than total
... not applicable
Source: 2001/2002 to 2004/2005 Hospital Morbidity Database.
12
Health Reports, Vol. 21, no. 4, December 2010 • Statistics Canada, Catalogue no. 82-003-XPE
Neighbourhood variation in hospitalization for unintentional injury among children and teenagers • Research article
Table 2
Age-standardized rate of unintentional injury hospitalizations per 10,000 person-years at risk, by injury category,
neighbourhood income quintile, sex and age group, urban population aged 0 to 19, Canada, 2001/2002 to 2004/2005
Sex
Injury category/
Neighbourhood
income quintile
Rate
Age group (years)
Total
Male
Female
0 to 9
10 to 19
95%
confidence
interval
95%
confidence
interval
95%
confidence
interval
95%
confidence
interval
95%
confidence
interval
from
to LTT†
Rate
from
to LTT†
Rate
from
to LTT†
21.6
22.8*
22.2*
21.7*
20.9
20.2
21.3
22.2
21.6
21.1
20.4
19.7
21.8 -0.03*
23.4
22.9
22.3
21.5
20.8
Rate
from
to LTT
Rate
from
28.7
32.2*
29.8*
28.7*
27.2*
25.8
28.4
31.5
29.0
28.0
26.5
25.2
29.0 -0.05*
33.0
30.5
29.4
27.8
26.5
33.7
33.2
33.8
34.4
33.6
33.4
33.4
32.5
33.0
33.7
33.0
32.8
34.0
34.0
34.5
35.1
34.3
34.1
12.3
11.6
12.0
12.0
12.3
12.4
12.7 0.01*
12.5
12.9
12.8
13.1
13.2
Total
Total
1 (lowest)
2
3
4
5 (highest)
31.3
32.7*
31.9*
31.7*
30.6*
29.9
31.1
32.2
31.4
31.2
30.1
29.4
31.6 -0.02*
33.3
32.4
32.2
31.1
30.3
40.7
42.4*
41.1*
41.2*
39.7
39.1
40.4
41.6
40.3
40.4
39.0
38.3
41.1 -0.02*
43.3
41.9
42.0
40.5
39.8
Falls
Total
1 (lowest)
2
3
4
5 (highest)
13.5
13.5
13.6
13.4
13.3
13.5
13.3
13.2
13.3
13.1
13.0
13.2
13.6
13.9
14.0
13.7
13.6
13.8
0.0
17.1
17.1
17.2
16.9
17.1
17.2
16.9
16.5
16.7
16.4
16.6
16.8
17.3
17.6
17.8
17.4
17.6
17.8
0.0
9.7
9.9
9.9
9.7
9.4
9.6
9.5
9.5
9.5
9.3
9.0
9.2
9.9
10.3
10.3
10.1
9.8
10.0
0.0
14.6
15.2*
14.9
14.5
14.1
14.3
14.4
14.7
14.4
14.0
13.6
13.8
14.8 -0.02*
15.7
15.5
15.0
14.6
14.8
12.5
12.1*
12.5
12.4
12.7
12.8
-0.1
8.8
9.2*
9.1*
9.5*
8.5*
7.7
8.6
8.8
8.8
9.1
8.2
7.4
8.9
9.6
9.5
9.8
8.8
8.0
0.0
4.2
4.5*
4.4*
4.6*
4.1*
3.6
4.1
4.2
4.1
4.3
3.8
3.3
4.3
4.8
4.7
4.9
4.3
3.8
-0.1
3.3
4.2*
3.5*
3.5*
3.1*
2.5
3.2
3.9
3.3
3.2
2.9
2.3
3.4 -0.12*
4.5
3.8
3.7
3.3
2.7
9.4
9.3*
9.8*
10.3*
9.2*
8.5
Land transportation
Total
1 (lowest)
2
3
4
5 (highest)
6.5
6.9*
6.8*
7.1*
6.3*
5.7
6.4
6.6
6.6
6.8
6.1
5.5
6.6
7.1
7.1
7.3
6.6
5.9
Struck
Total
1 (lowest)
2
3
4
5 (highest)
3.4
3.0*
3.2*
3.3*
3.6
3.9
3.4
2.8
3.0
3.2
3.5
3.7
3.5 0.07*
3.1
3.3
3.5
3.8
4.0
5.3
4.6*
4.9*
5.2*
5.6
5.8
5.1
4.3
4.7
4.9
5.3
5.5
5.4 0.06*
4.9
5.2
5.5
5.9
6.1
1.5
1.3*
1.3*
1.4*
1.6
1.8
1.4
1.2
1.2
1.2
1.5
1.7
1.6 0.08*
1.5
1.5
1.5
1.8
2.0
1.9
2.0
1.9
1.9
1.9
1.8
1.8
1.8
1.7
1.7
1.7
1.6
2.0
2.1
2.1
2.0
2.1
2.0
Poisoning
Total
1 (lowest)
2
3
4
5 (highest)
1.6
2.2*
1.7*
1.5*
1.4
1.3
1.6
2.0
1.6
1.4
1.3
1.2
1.7 -0.13*
2.3
1.8
1.7
1.5
1.4
1.7
2.4*
1.8*
1.7*
1.4
1.4
1.7
2.2
1.7
1.5
1.3
1.2
1.8 -0.14*
2.6
2.0
1.8
1.5
1.5
1.5
2.0*
1.6*
1.4*
1.4*
1.2
1.4
1.8
1.4
1.3
1.2
1.0
1.6 -0.12*
2.2
1.8
1.6
1.5
1.3
2.3
3.0*
2.4*
2.2*
1.9
1.7
2.2
2.8
2.2
2.0
1.8
1.6
Cut/Pierce
Total
1 (lowest)
2
3
4
5 (highest)
0.9
1.2*
1.0*
0.9*
0.8
0.7
0.9
1.1
0.9
0.8
0.7
0.6
1.0 -0.13*
1.3
1.1
1.0
0.9
0.8
1.3
1.7*
1.5*
1.3
1.2
1.1
1.3
1.6
1.3
1.1
1.1
1.0
1.4 -0.11*
1.9
1.6
1.4
1.3
1.2
0.5
0.6*
0.6*
0.5*
0.4*
0.3
0.5
0.5
0.5
0.4
0.4
0.2
0.5 -0.18*
0.7
0.7
0.6
0.5
0.4
0.7
0.9*
0.7
0.7
0.6
0.6
Natural environment
Total
1 (lowest)
2
3
4
5 (highest)
0.7
0.8*
0.7*
0.8*
0.7
0.6
0.7
0.7
0.6
0.8
0.6
0.5
0.8
0.9
0.8
0.9
0.8
0.7
0.8
0.9*
0.7
0.9*
0.8*
0.6
0.7
0.8
0.6
0.8
0.7
0.5
0.8
1.0
0.8
1.0
0.9
0.7
0.7
0.7
0.7
0.8
0.6
0.6
0.6
0.6
0.6
0.7
0.5
0.6
0.7
0.8
0.8
0.9
0.7
0.8
Fire
Total
1 (lowest)
2
3
4
5 (highest)
0.7
1.0*
0.8*
0.6*
0.6
0.5
0.7
1.0
0.7
0.6
0.5
0.5
0.8 -0.17*
1.1
0.9
0.7
0.6
0.6
0.9
1.2*
1.0*
0.9*
0.7
0.7
0.8
1.1
0.8
0.8
0.6
0.6
0.9 -0.15*
1.3
1.1
1.0
0.8
0.8
0.6
0.9*
0.7*
0.4
0.5
0.4
0.5
0.8
0.6
0.3
0.4
0.3
Drowning/Suffocation
Total
1 (lowest)
2
3
4
5 (highest)
0.4
0.5*
0.4
0.4
0.4
0.4
0.4
0.4
0.4
0.3
0.3
0.3
0.4 -0.07*
0.5
0.5
0.4
0.4
0.4
0.5
0.6
0.5
0.5
0.5
0.5
0.5
0.5
0.5
0.4
0.4
0.4
0.6
0.7
0.6
0.6
0.5
0.6
-0.1
0.3
0.3*
0.3*
0.3
0.3*
0.2
Other
Total
1 (lowest)
2
3
4
5 (highest)
3.7
3.9*
3.7*
3.8*
3.6
3.5
3.6
3.7
3.5
3.6
3.4
3.3
3.8 -0.02*
4.0
3.9
4.0
3.7
3.6
4.6
5.1*
4.5
4.8*
4.3
4.3
4.5
4.8
4.2
4.5
4.1
4.1
4.7
5.4
4.8
5.1
4.6
4.6
0.0
2.7
2.6
2.9*
2.7
2.8
2.6
-0.1
†
LTT=linear trend test coefficient
* significantly different from highest quintile (p<0.05)
Source: 2001/2002 to 2004/2005 Hospital Morbidity Database.
-0.1
9.2 9.6
8.9 9.7
9.4 10.2
9.9 10.7
8.9 9.6
8.2 8.9
0.0
0.0
4.8
3.9*
4.3*
4.6*
5.2*
5.7
4.7
3.6
4.1
4.4
4.9
5.5
4.9 0.10*
4.2
4.6
4.9
5.4
6.0
2.4 -0.13*
3.2
2.6
2.4
2.1
1.9
1.0
1.4*
1.2*
0.9
0.9
0.9
1.0
1.3
1.0
0.8
0.8
0.8
1.1 -0.13*
1.6
1.3
1.1
1.0
1.0
0.6
0.7
0.6
0.6
0.5
0.5
0.7 -0.10*
1.0
0.8
0.8
0.7
0.7
1.1
1.5*
1.3*
1.1*
1.0
0.9
1.1
1.3
1.2
1.0
0.9
0.8
1.2 -0.14*
1.6
1.5
1.2
1.1
1.0
1.1
1.1*
1.1
1.2*
1.1*
0.9
1.0
1.0
0.9
1.0
1.0
0.8
1.1
1.2
1.2
1.3
1.2
1.0
0.4
0.5*
0.4
0.5*
0.4
0.4
0.4
0.4
0.3
0.5
0.3
0.3
0.5
0.6
0.5
0.6
0.4
0.4
0.6 -0.21*
1.0
0.8
0.5
0.5
0.5
1.1
1.7*
1.3*
0.9
0.9
0.8
1.0
1.5
1.1
0.8
0.7
0.7
1.2 -0.19*
1.8
1.4
1.1
1.0
0.9
0.4
0.5*
0.4*
0.4
0.3
0.3
0.3
0.4
0.3
0.3
0.3
0.2
0.4 -0.12*
0.6
0.5
0.5
0.4
0.4
0.3
0.3
0.3
0.2
0.3
0.2
0.3
0.4
0.4
0.4
0.4
0.3
-0.1
0.7
0.8*
0.7
0.7
0.7
0.6
0.7
0.7
0.6
0.6
0.6
0.5
0.8 -0.06*
0.9
0.9
0.8
0.8
0.7
0.1
0.2*
0.2
0.1
0.2
0.1
0.1
0.2
0.1
0.1
0.1
0.1
0.2
0.3
0.2
0.2
0.2
0.2
-0.1
2.6
2.4
2.7
2.5
2.6
2.4
2.8
2.8
3.1
3.0
3.0
2.8
0.0
3.3
3.7*
3.5*
3.3*
3.1
2.9
3.2
3.5
3.2
3.1
2.9
2.7
3.4 -0.06*
4.0
3.7
3.5
3.3
3.1
4.0
4.0
3.9
4.2
4.0
4.0
3.9
3.7
3.7
4.0
3.8
3.8
4.2
4.3
4.2
4.5
4.3
4.2
0.0
0.0
0.0
to LTT†
0.0
-0.1
Statistics Canada, Catalogue no. 82-003-XPE • Health Reports, Vol. 21, no. 4, December 2010
Neighbourhood variation in hospitalization for unintentional injury among children and teenagers • Research article
10,000 person-years at risk in the highest
(Figure 2). This pattern applied to males
and females and to children aged 0 to 9.
However, among 10- to 19-year-olds,
associations between neighbourhood
income and injury hospitalizations were
not statistically significant.
Figure 1
Percentage distribution of unintentional injury hospitalizations, by category,
urban population aged 0 to 19, Canada, 2001/2002 to 2004/2005
High neighbourhood income/High
hospitalization rates
At ages 10 to 19, age-standardized rates
of hospitalization due to being struck
tended to rise with neighbourhood income
42.7
Falls
20.7
Land transportation
10.9
Struck
Low neighbourhood income/High
hospitalization rates
For several causes of unintentional
injury, children and teens in low-income
neighbourhoods were more likely to be
hospitalized than were their counterparts
in high-income neighbourhoods (Table 2,
Appendix Table B). Age-standardized
rates of hospitalization due to poisoning
and to being cut/pierced were
significantly higher in the three lowest
neighbourhood income quintiles than
among those in the highest. Confirming
this, the LTT was significant overall, by
sex, and by age group. Similarly, rates
of hospitalization due to fires tended to
rise as neighbourhood income decreased.
The LTT across the five income quintiles
was significant for all age and sex groups.
For a number of other causes,
hospitalization rates were higher in lowerincome neighbourhoods among children,
but not teens. For instance, while children
and teenagers in the lower-income
neighbourhoods had signficantly higher
rates of hospitalization for drowning/
suffocation, for land transportation, and
for other causes than did those in the
highest, the LTT was significant only
among children aged 0 to 9.
Children aged 0 to 9 in the lowestincome neighbourhoods had significantly
higher rates of hospitalization for falls
than did those in the highest income
quintile. By contrast, 10- to 19-year-olds
in such neighbourhoods actually had a
siginficantly lower rate of hospitalization
for falls than did those in the highestincome neigbourhoods.
13
Poisoning
5.2
2.9
Cut/Pierce
Natural environment
2.3
Fire
2.3
Drowning/Suffocation
1.3
11.7
Other
Source: 2001/2002 to 2004/2005 Hospital Morbidity Database.
Figure 2
Rate of unintentional injury hospitalizations per 10,000 person-years at risk,
by sex, age group and neighbourhood income quintile, urban population aged
0 to 19, Canada, 2001/2002 to 2004/2005
Per 10,000
person-years
at risk
45
*
*
Neighbourhood
income quintile
*
40
35
*
*
*
1 (lowest)
2
3
4
5 (highest)
*
30
25
*
*
*
*
*
*
*
20
15
Male
Total
Female
Sex
* significantly different from highest quintile (p< 0.05)
Source: 2001/2002 to 2004/2005 Hospital Morbidity Database.
0 to 9
10 to 19
Age group (years)
14
Health Reports, Vol. 21, no. 4, December 2010 • Statistics Canada, Catalogue no. 82-003-XPE
Neighbourhood variation in hospitalization for unintentional injury among children and teenagers • Research article
quintile. The LTT was significant for the
10-to-19 age group, but not for children
aged 0 to 9.
No gradient
For injuries due to the natural
environment,
no
gradient
by
neighbourhood income was evident
in hospitalization rates. For example,
young people from middle-income
neighbourhoods (quintile 3) had
higher natural environment injury
hospitalization rates than did those
from the lowest neighbourhood income
quintile.
Discussion
As has been found in other
studies,14,15,22,34,40 this analysis shows
that rates of unintentional injury
hospitalization among Canadian children
and teenagers generally increased with
neighbourhood disadvantage.
The
pattern was consistent for most types
of unintentional injuries suggesting that
they are related to the level of income in
the neighbourhood where children live.
Rates of hospitalization for poisoning,
being cut/pierced and fire were higher
among children and teens in lower-income
neighbourhoods. As well, for children
aged 0 to 9 (but not 10- to 19-year-olds),
associations between low neighbourhood
income and hospitalizations for injuries
related to falls and other unintentional
causes were signficant.
However,
hospitalization
rates
for all injury categories were not
invariably higher for children in lowerincome neighbourhoods.
In fact,
rates for injuries due to being struck
were significantly higher among 10to 19-year-olds in higher-income
neighbourhoods. A possible explanation
is that this category includes sports
injuries, which may be more common in
higher-income neighbourhoods. A study
in England, Scotland and Wales found
that rates of childhood sports-related
fractures increased with area affluence.41
A preliminary analysis of ICD codes
for the causes of hospitalization in this
study supported this theory: 29% of the
struck injuries in the highest-income
neighbourhoods were sports-related,
compared with 24% of the struck injuries
in the lowest income neighbourhoods.
Similar to findings reported in some,42-44
but not all, 18,22 studies, children aged 0 to
9 in the lowest-income neighbourhoods
had a higher rate of hospitalization for
falls than did those in the highest-income
neighbourhoods, but for 10- to 19-yearolds, the rate was lower in the lowestincome neighbourhoods. It is possible
that the circumstances surrounding falls
differ among younger and older children.
For instance, hazards such as a lack of
baby gates may expose young children to
fall-related hospitalizations.
Strengths and limitations
Canadian studies of associations
between neighbourhood income and
childhood injury have typically used
self-reported survey data, which do not
provide information on diagnoses,30-32 or
administrative data that pertain only to a
single city or hospital.22,35 By contrast,
the present analysis uses four years of
population-based hospitalization data
for children in urban Canada to produce
rates by age and sex. Moreover, the rates
in this article are likely conservative,
because injury hospitalizations occurring
outside the individual’s province of
residence were excluded, as were injuries
to children and teenagers who died before
hospital admission. And by design,
individuals presenting only to emergency
rooms, doctors offices or clinics were not
included.
This study has several limitations.
Because Quebec provides only the
first three digits of the postal code, the
assignment of neighbourhood income
quintile was less precise than that in other
provinces.
Research suggests that neighbourhood
has independent effects on childhood
injury even when controlling for
individual and family factors.45 Even
so, the lack of information about family
characteristics or children’s behaviours
that can influence injury risk32,46 meant
that the relative contributions of
individual, family and neighbourhood
What is already
known on this
subject?
■ In urban Canada, children and
teenagers in lower-income
neighbourhoods have higher rates of
mortality due to unintentional injury.
What does this study
add?
■ Children and teenagers in lowerincome urban neighbourhoods are
more likely than those in higherincome neighbourhood to be
hospitalized for unintentional injuries.
■ The association between living in a
lower-income neighbourhood and
injury hospitalization was strongest
among children aged 0 to 9.
■ Injury hospitalization rates due to
being struck were higher among
10- to 19-year-olds in higherincome neighbourhoods, compared
with those in lower-income
neighbourhoods.
factors could not be ascertained in this
analysis.
This is an ecological study—
associations
observed
at
the
neighbourhood level do not necessarily
apply at the individual level. As well, the
findings apply only to urban areas, and do
not necessarily hold for rural areas. Data
on the geographical location where the
injury happened were also not available.
Implications for research
Childhood injury has been identified as
a key policy area in Canada.1 Results
of the current study may be useful in
the development of strategies to reduce
childhood injury.
In addition, the
hospitalization rates presented here can
be used to examine changes over time. It
remains for future research to examine:
how social and physical dimensions of the
neighbourhood affect childhood injury;
the relative influence of individual and
Statistics Canada, Catalogue no. 82-003-XPE • Health Reports, Vol. 21, no. 4, December 2010
Neighbourhood variation in hospitalization for unintentional injury among children and teenagers • Research article
neighbourhood factors; and if patterns
are similar in rural neighbourhoods.
Conclusion
Unintentional
childhood
injury
hospitalization in urban Canada varies by
neighbourhood income. Hospitalizations
due to fire, poisoning, drowning/
suffocation, and being cut/pierced rose
with decreasing neighbourhood income.
Injury hospitalizations due to being
15
struck showed a reverse gradient—
increasing
neighbourhood
income
quintile was associated with a higher rate
of hospitalization. ■
Acknowledgements
We acknowledge the contributions of
Russell Wilkins, Michelle Rotermann
and Helen Johansen from the Health
Analysis Division, Statistics Canada.
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Davey TM, Aitken LM, Kassulke D, et al.
Long-term outcomes of seriously injured
children: a study using the Child Health
Questionnaire. Journal of Paediatrics and
Child Health 2005; 41(5-6): 278-83.
14. Reimers A, Laflamme L. Neighbourhood
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1488-94.
Hu X, Wesson DE, Logsetty S, Spence LJ.
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with severe trauma: a one-year follow-up.
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15. Poulos R, Hayen A, Finch C, Zwi A. Area
socioeconomic status and childhood injury
morbidity in New South Wales, Australia.
Injury Prevention 2007; 13(5): 322-7.
Winthrop AL, Brasel KJ, Stahovic L, et al.
Quality of life and functional outcome after
pediatric trauma. Journal of Trauma 2005;
58(3): 468-73.
16. Moustaki M, Petridou E, Trichopoulos
D. Person, time and place coordinates of
pedestrian injuries: a study in Athens. Acta
Paediatrica 2001; 90(5): 558-62.
Public Health Agency of Canada. Leading
causes of death, Canada, 2004, males and
females combined: counts (crude death rate
per 100,000), 2009.
17. Locke JA, Rossignol AM, Burke JF.
Socioeconomic factors and the incidence of
hospitalized burn injuries in New England
counties, USA. Burns 1990; 16(4): 273-7.
Leventhal T, Brooks-Gunn J. The
neighborhoods they live in: the effects
of neighborhood residence on child and
adolescent outcomes. Psychological Bulletin
2000; 126(2): 309-37.
18. Engstrom K, Diderichsen F, Laflamme L.
Socioeconomic differences in injury risks in
childhood and adolescence: a nation-wide
study of intentional and unintentional injuries
in Sweden. Injury Prevention 2002; 8(2):
137-42.
19. Laflamme L, Reimers A. Neighborhood social
characteristics and fall injuries in children. An
area-based study in Stockholm County. Soz
Praventivmed 2006; 51(6): 355-62.
20. Reimers A, Laflamme L. Neighborhood
social composition and injury risks among
pre-adolescent and adolescent boys and
girls. A study in Stockholm metropolitan.
International Journal of Adolescent Medicine
and Health 2004; 16(3): 215-27.
21. Hewson P. Deprived children or deprived
neighbourhoods? A public health approach to
the investigation of links between deprivation
and injury risk with specific reference to child
road safety in Devon County, UK. BMC
Public Health 004; 4:15.
22. Faelker T, Pickett W, Brison RJ.
Socioeconomic differences in childhood
injury: a population based epidemiologic
study in Ontario, Canada. Injury Prevention
2000; 6(3): 203-8.
23. Romero AJ, Robinson TN, Kraemer HC et al.
Are perceived neighborhood hazards a barrier
to physical activity in children? Archives of
Pediatrics and Adolescent Medicine 2001;
155(10): 1143-8.
24. Coen S, Ross N. Exploring the material basis
for health inequalities: Characteristics of parks
in Montreal with contrasting health outcomes.
Health and Place 2006; 12(4): 361-71.
25. Collins DC, Kearns RA. Geographies of
inequality: child pedestrian injury and walking
school buses in Auckland, New Zealand.
Social Science and Medicine 2005; 60(1):
61-9.
26. Istre GR, McCoy MA, Osborn L, et al. Deaths
and injuries from house fires. New England
Journal of Medicine 2001; 344(25): 1911-6.
16
Health Reports, Vol. 21, no. 4, December 2010 • Statistics Canada, Catalogue no. 82-003-XPE
Neighbourhood variation in hospitalization for unintentional injury among children and teenagers • Research article
27. Macpherson AK, Macarthur C, To TM, et
al. Economic disparity in bicycle helmet use
by children six years after the introduction
of legislation. Injury Prevention 2006; 12(4):
231-5.
34. Brownell MD, Friesen D, Mayer T. Childhood
injury rates in Manitoba: Socioeconomic
influences. Canadian Journal of Public Health
2002; 93(suppl. 2): S50-6.
41. LyonsRA, Delahunty MA, Heaven M, et al.
Incidence of childhood fractures in affluent
and deprived areas: population based study.
British Medical Journal 2000; 320: 149.
28. Millar WJ, Pless IB. Factors associated with
bicycle helmet use. Health Reports (Statistics
Canada, Catalogue 82-003) 1997; 9(2): 31-9.
35. Dougherty G, Pless IB, Wilkins R. Social
class and the occurrence of traffic injuries and
deaths in urban children. Canadian Journal
of Public Health 1990; 81(3): 204-9.
42. Reimers A, Laflamme L. Neighbourhood
social and socio-economic composition and
injury risks. Acta Paediatrica 2005; 94(10):
1488-94.
29. Turner JV, Spallek M, Najman JM et al.
Socio-economic distribution of environmental
risk factors for childhood injury. Australian
and New Zealand Journal of Public Health
2006; 30(6): 514-8.
36. Public Health Agency of Canada. Injury
Surveillance
On-Line:
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Transition Matrix. Report. 2008. Available at:
http://dsol-smed.phac-aspc.gc.ca/dsol-smed/is-ib/
chirpp/ICD10-ICD9Transition-MatrixISOL.pdf
43. Birken CS, Macarthur C. Socioeconomic
status and injury risk in children. Journal of
Paediatrics and Child Health 2004; 9(5):
323-5.
30. Simpson K, Janssen I, Craig WM, Pickett
W. Multilevel analysis of associations
between socioeconomic status and injury
among Canadian adolescents. Journal of
Epidemiology and Community Health 2005;
59(12): 1072-7.
37. Wilkins R. PCCF + Version 4G User’s Guide:
Automated Geographic Coding Based on the
Statistics Canada Postal Code Conversion
Files Including Postal Codes to October 2005
(Catalogue 82F0086-XDB) Ottawa: Statistics
Canada; 2006.
31. Potter BK, Speechley KN, Koval JJ, et al.
Socioeconomic status and non-fatal injuries
among Canadian adolescents: variations
across SES and injury measures. BMC Public
Health 2005; 5: 132.
38. Statistics Canada. Census Metropolitan Area
(CMA) and Census Agglomeration (CA).
2001 Census Dictionary: Internet Version
(Catalogue 92-378-XIE) Ottawa: Statistics
Canada, 2002.
32. Soubhi H, Raina P, Kohen DE. Neighborhood,
family, and child predictors of childhood
injury in Canada. American Journal of Health
Behavior 2004; 28(5): 397-409.
39. Rosner B. Fundamentals of Biostatistics. 5th
Edition. Duxbury: Pacific Grove, 2000.
33. Birken CS, Parkin PC, To T, Macarthur C.
Trends in rates of death from unintentional
injury among Canadian children in urban
areas: influence of socioeconomic status.
Canadian Medical Association Journal 2006;
175(8): 867.
40. Hippisley-Cox J, Groom L, Kendrick D, et
al. Cross sectional survey of socioeconomic
variations in severity and mechanism of
childhood injuries in Trent 1992-7. British
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Appendix
Table A
International Classification of Disease versions used, by province and fiscal year
Province
Fiscal 2001
Fiscal 2002
Fiscal 2003
Fiscal 2004
Newfoundland and Labrador
ICD-10-CA
Prince Edward Island
ICD-10-CA
Nova Scotia
ICD-10-CA
New Brunswick
ICD-9-CM
Quebec
ICD-9
Ontario
ICD-9; ICD-9-CM
Manitoba
ICD-9-CM
Saskatchewan
ICD-9; ICD-9-CM; ICD-10-CA
Alberta
ICD-9-CM
British Columbia
ICD-10-CA
ICD-10-CA
ICD-10-CA
ICD-10-CA
ICD-9-CM
ICD-9
ICD-10-CA
ICD-9-CM
ICD-10-CA
ICD-10-CA
ICD-10-CA
ICD-10-CA
ICD-10-CA
ICD-10-CA
ICD-10-CA
ICD-9
ICD-10-CA
ICD-9-CM
ICD-10-CA
ICD-10-CA
ICD-10-CA
ICD-10-CA
ICD-10-CA
ICD-10-CA
ICD-10-CA
ICD-9
ICD-10-CA
ICD-10-CA
ICD-10-CA
ICD-10-CA
ICD-10-CA
ICD-10-CA= International Statistical Classification of Diseases and Related Health Problems, Tenth Revision, Canadian Adaptation
ICD-9-CM= International Statistical Classification of Diseases, Injuries and Causes of Death, Ninth Revision, Clinical Modification
ICD-9= International Statistical Classification of Diseases, Injuries and Causes of Death, Ninth Revision
44. Khambalia A, Joshi P, Brussoni M, et al. Risk
factors for unintentional injuries due to falls in
children aged 0-6 years: a systematic review.
Injury Prevention 2006; 12(6): 378-81.
45. Haynes R, Reading R, Gale S. Household and
neighbourhood risks for injury to 5-14 year
old children. Social Science and Medicine
2003; 57(4): 625-36.
46. Reading R, Langford IH, Haynes R, Lovett A.
Accidents to preschool children: comparing
family and neighbourhood risk factors. Social
Science and Medicine 1999; 48(3): 321-30.
Statistics Canada, Catalogue no. 82-003-XPE • Health Reports, Vol. 21, no. 4, December 2010
Neighbourhood variation in hospitalization for unintentional injury among children and teenagers • Research article
Table B
Number of unintentional injury hospitalizations,
by injury category, neighbourhood income quintile,
sex and age group, urban population aged 0 to 19,
Canada, 2001/2002 to 2004/2005
Injury category/
Neighbourhood
income quintile
Total
Male
Female
0 to 9
10 to 19
Total
Total
1 (lowest)
2
3
4
5 (highest)
76,227
14,806
14,346
15,401
16,139
15,535
50,653
9,679
9,448
10,282
10,772
10,472
25,574
5,127
4,898
5,119
5,367
5,063
32,768
7,396
6,435
6,491
6,595
5,851
43,459
7,410
7,911
8,910
9,544
9,684
Falls
Total
1 (lowest)
2
3
4
5 (highest)
32,695
6,119
6,126
6,484
7,011
6,955
21,240
3,895
3,957
4,196
4,616
4,576
11,455
2,224
2,169
2,288
2,395
2,379
16,601
3,441
3,214
3,277
3,419
3,250
16,094
2,678
2,912
3,207
3,592
3,705
Land transportation
Total
1 (lowest)
2
3
4
5 (highest)
15,880
2,995
3,033
3,447
3,365
3,040
10,896
2,022
2,081
2,365
2,316
2,112
4,984
973
952
1,082
1,049
928
3,753
914
743
781
748
567
12,127
2,081
2,290
2,666
2,617
2,473
Struck
Total
1 (lowest)
2
3
4
5 (highest)
8,335
1,310
1,411
1,620
1,930
2,064
6,553
1,015
1,125
1,295
1,519
1,599
1,782
295
286
325
411
465
2,125
443
397
419
463
403
6,210
867
1,014
1,201
1,467
1,661
Poisoning
Total
1 (lowest)
2
3
4
5 (highest)
3,953
1,053
796
752
722
630
2,161
590
438
417
369
347
1,792
463
358
335
353
283
2,622
732
526
510
471
383
1,331
321
270
242
251
247
Cut/Pierce
Total
1 (lowest)
2
3
4
5 (highest)
2,230
527
464
438
429
372
1,656
388
333
319
321
295
574
139
131
119
108
77
764
194
149
151
144
126
1,466
333
315
287
285
246
Natural environment
Total
1 (lowest)
2
3
4
5 (highest)
1,760
366
324
405
362
303
949
206
165
226
205
147
811
160
159
179
157
156
1,208
252
231
264
263
198
552
114
93
141
99
105
Fire
Total
1 (lowest)
2
3
4
5 (highest)
1,750
508
380
309
297
256
1,084
294
225
217
183
165
666
214
155
92
114
91
1,268
398
283
211
207
169
482
110
97
98
90
87
993
233
201
187
200
172
635
151
128
115
119
122
358
82
73
72
81
50
810
189
165
160
158
138
183
44
36
27
42
34
8,980
1,765
1,679
1,844
1,889
1,803
5,726
1,170
1,037
1,194
1,171
1,154
3,254
595
642
650
718
649
3,769
870
760
746
748
645
5,211
895
919
1,098
1,141
1,158
Drowning/Suffocation
Total
1 (lowest)
2
3
4
5 (highest)
Other
Total
1 (lowest)
2
3
4
5 (highest)
Sex
Age group (years)
Source: 2001/2002 to 2004/2005 Hospital Morbidity Database.
17
E L E C T R O N I C P U B L I C AT I O N S
AVA I L A B L E AT
w w w. s t a t c a n . g c . c a
Statistics Canada, Catalogue no. 82-003-XPE • Health Reports, Vol. 21, no. 4, December 2010
Socio-economic status and vitamin/mineral supplement use in Canada • Research article
19
Socio-economic status and vitamin/
mineral supplement use in Canada
by Hassanali Vatanparast, Jennifer L. Adolphe and Susan J. Whiting
Abstract
Background
The link between diet quality and socio-economic
status (SES) may extend to the use of vitamin/
mineral supplements. This article examines factors
related to Canadians’ use of such supplements, with
emphasis on associations with household income and
education.
Data and methods
The data are from the 2004 Canadian Community
Health Survey―Nutrition (n= 35,107). The
prevalence of vitamin/mineral supplement
consumption during the previous month was
recorded. Supplement use at the national level
was estimated by age/sex groups, SES and chronic
conditions. Logistic regression was used to determine
significant associations between socio-economic
factors and vitamin/mineral supplement use.
Estimates of usual calcium intake from food and
from food plus supplements were obtained using
SIDE-IML.
Results
The prevalence of supplement use was significantly
higher in females than in males in all age groups 14
or older. Age, being female, high household income
and education, and being food-secure were positively
associated with supplement use. Supplement
use substantially increased the percentage of the
population, particularly older adults, meeting the
Adequate Intake level for calcium.
Interpretation
The reported use of vitamin/mineral supplements
varies by age, sex and SES. The relatively low
prevalence of use among Canadians of low SES is
similar to findings from American studies. These
individuals, already at risk for inadequate intake from
food, do not make up the difference with vitamin/
mineral supplements.
Keywords
calcium, diet, food security, nutrition, nutrition surveys,
nutritional requirements
Authors
Hassanali Vatanparast (1-306-966-6341;
[email protected]), Jennifer L. Adolphe and
Susan J. Whiting are with the College of Pharmacy
and Nutrition at the University of Saskatchewan,
Saskatoon, Saskatchewan, S7N 5C9.
T
he use of supplements can increase daily intake
of vitamins and minerals (micronutrients)
beyond what is obtained from food alone,1,2 and thus,
may confer health benefits, including chronic disease
prevention.3
Some population groups have been
identified as being at risk for low nutrient
intakes.4,5 Specifically, diet quality has
been linked to socio-economic status
(SES), with higher-quality diets being
associated with greater affluence.
People of lower SES tend to consume
more high-calorie, nutrient-poor foods,
whereas those of higher SES consume
more whole grains, lean meats, fish, lowfat dairy products, and fresh vegetables
and fruit.6
Vitamin/Mineral supplements offer
the potential to improve the micronutrient
intake of people with a nutrient-poor
diet, in that the cost of regular retail
supplements is less than that of foods
such as fruits, vegetables, and dairy
products.
However, according to the inverse
supplement hypothesis,7 people at risk
for nutrient inadequacy, or in need of
more nutrients because of disease risk,
are not the ones who take supplements.
In fact, a number of American studies
have shown that the use of vitamin/
mineral supplements is also related to
SES. Seven of ten studies that examined
the association between income and
supplement use among adults and
children found a positive association.7-13
A higher level of education was also
a strong predictor of supplement
use.1,7,8,10,11,14-17
With data collected by the 2004
Canadian Community Health Survey
(CCHS) (cycle 2.2), it is possible to
determine if the inverse relationship
between vitamin/mineral supplement
consumption and SES prevails in
Canada.1,2,18 The objective of the 2004
CCHS was to provide estimates of
dietary intake in terms of nutrients,
foods, food groups, dietary supplements,
and eating patterns, at the national and
provincial levels for a representative
sample of Canadians. Because the
CCHS collects demographic, socioeconomic, health status and food security
data, associations between these factors
and vitamin/mineral supplement use can
be examined.
For this analysis, it was hypothesized
that people of high SES are more
likely than those of lower SES to take
supplements, but that other factors (age,
sex) are also significantly associated
with supplement use. Calcium, one of
the most common mineral supplements,
is used to demonstrate the impact of
supplements on total intake.
20
Health Reports, Vol. 21, no. 4, December 2010 • Statistics Canada, Catalogue no. 82-003-XPE
Socio-economic status and vitamin/mineral supplement use in Canada • Research article
Data and methods
Data source
From January through December 2004,
the CCHS (cycle 2.2) interviewed 35,107
respondents.
The survey excludes
residents of institutions, the territories,
Indian reserves, crown lands and some
remote areas; members of the regular
Canadian Forces; and military and
civilian residents of Canadian Forces
bases.
Cycle 2.2 had two components: 1)
a general health component containing
demographic and health information
including the use of vitamin and mineral
supplements, and 2) a dietary intake
component based on (a) 24-hour recall(s).
The details of survey methodology and
data collection have been described
elsewhere.19 This study pertains to all
cycle 2.2 respondents aged 1 or older
(n=34,818).
Definitions
Respondents were asked to provide the
bottle or package of each supplement
that they took, and if possible, the
drug identification number, which the
interviewer could immediately check
against the Drug Product Database. For
each supplement, respondents reported
the amount taken per day, week or month
during the last month. Average daily
consumption of each supplement was
derived from these data. The April 2008
release of CCHS 2.2 contains three files
including vitamin/mineral supplement
use information. For this analysis, data
from two files—vitamin and mineral
supplement details and vitamin and
mineral summary—were used. The
variables of interest were overall
supplement use and calcium intake from
supplements.
Total annual household income was
classified into four categories based on
the number of people in the household:
lowest (less than $15,000 if 1 or 2 people;
less than $20,000 if 3 or 4 people; and
less than $30,000 if 5 or more people);
lower-middle ($15,000 to $29,999 if 1
or 2 people; $20,000 to $39,999 if 3 or
4 people; and $30,000 to $50,000 if 5 or
more people); upper-middle ($30,000
to $59,999 if 1 or 2 people; $40,000
to $79,000 if 3 or 4 people; $60,000 to
$79,999 if 5 or more people); and highest
($60,000 or more if 1 or 2 people;
$80,000 if 3 or more people).
Respondents’ education was classified
into four categories according to the
highest level they had attained: less
than secondary graduation; secondary
graduation; some postsecondary; and
postsecondary graduation.
Because
preliminary analyses showed secondary
graduation to be an important cutoff in
terms of supplement use, a new variable
was created, categorizing education
into two levels: less than secondary
graduation and secondary graduation or
more.
Food security status was based on 18
CCHS questions designed to determine
if households had been able to afford
the food they needed in the previous 12
months. The Statistics Canada derived
variable defines four categories: food
secure, food insecure without hunger,
food insecure with moderate hunger, and
food insecure with severe hunger.
Respondents aged 19 or older
reported if they had been diagnosed by
a medical professional with (a) chronic
health condition(s) that had lasted or
were expected to last six months or
more. These included long-term mental
conditions.
Information about dietary intake
was collected from each respondent
during a face-to-face interview. To
help respondents recall what and how
much they ate and drank in the past 24
hours, interviewers used the five-step
Automated Multiple Pass Method.20,21
The calorie and nutrient content of
the foods reported was derived from
Health Canada’s Canadian Nutrient File
2001b supplement, a recipe database,
and a survey foods database containing
foods not in the other databases.19 A
second recall was conducted 3 to 10
days later from a subset of about 30% of
participants (n=10,786). Response rates
to the first and second recalls were 76.5%
and 72.8%, respectively.
Analytical techniques
Because a large majority—83%—
of supplement users reported taking
supplements every day the previous
month (only 3.5% had taken supplements
fewer than 15 days), for these analyses,
it was assumed that all supplement users
took them regularly.
Descriptive statistics were used to
estimate the percentage of the population
who took vitamin/mineral supplements,
and the distribution of supplement users
in various Dietary Reference Intake
age/sex groups at the national level.
Supplement use by adults (19 or older)
was determined by household income,
education, and food security status.
Some analyses examined just two adult
age groups: 19 to 50 and 51 or older.
The dietary intake data from the two
24-hour recalls were adjusted for withinsubject variability to obtain betweensubject distributions of estimated intakes;
this process converts recall data that are
not representative of habitual intake into
estimates of usual intake.19 This was
done with the modified version of SIDEIML (Software for Intakes Distribution
Estimation).19
Calcium was chosen to illustrate the
impact of taking a specific supplement.22
Usual intake of calcium (mg/d) and the
percentage of the population meeting
the recommended value from food alone
were calculated by age group and sex
for the population aged 1 or older. The
calculation was repeated after adding
supplement intake values to food intake
values, based on the first and second
24-hour recalls. Differences in calcium
intake between supplement users and
non-users were also examined.
Logistic regression was used to
determine
significant
associations
between supplement use and age, sex,
household income, education, food
security, chronic conditions, and urban/
rural residence. Sampling weights were
used to obtain unbiased estimates of
population sizes. The bootstrap method,
which takes the complex survey design
into account, was used to estimate
standard errors, coefficients of variation
and confidence intervals. The absence
Statistics Canada, Catalogue no. 82-003-XPE • Health Reports, Vol. 21, no. 4, December 2010
Socio-economic status and vitamin/mineral supplement use in Canada • Research article
of overlapping 95% confidence intervals
denoted statistical significance.19 SPSS
version 15 was used to merge CCHS 2.2
files, create new variables, and generate
the final data set; SAS version 9, to
obtain the usual intake of nutrients of
interest using SIDE-IML; and STATA
SE 10 for the other analyses, weighting
and bootstrapping. Alpha was set at 0.05.
Results
Vitamin/Mineral supplements
Age was closely related to vitamin/
mineral supplement use. Around 40%
of children aged 1 to 8 took supplements
(Table 1). The percentage declined
through adolescence to less than 30%
at ages 14 to 18 and then rose steadily
with advancing age to about 60% among
women and 40% among men aged 51 or
older.
Overall, the prevalence of vitamin/
mineral supplement use was significantly
higher among females than males: 47%
versus 34%. This difference prevailed
among all age groups 14 or older and
widened at older ages, with the greatest
gap at ages 51 to 70. The highest
prevalence of supplement use was among
women aged 51 or older (60%), and the
lowest, among boys aged 14 to 18 (23%).
Supplement use was generally more
common among people in higher- than
lower-income households (Figure 1).
The exceptions were women aged 71 or
older, among whom supplement use was
high regardless of household income,
and unexpectedly, men aged 19 to 30
and 71 or older in the lowest income
households.
Supplement use also tended to rise
with level of education (Figure 2).
Among men, the difference between
those who had not graduated from
secondary school and those who had at
least some postsecondary education was
particularly pronounced.
Among women, as food insecurity
became more severe, supplement use
tended to decline (Table 2). Among men,
the association between supplement use
and food security followed a U-shaped
pattern, with relatively high percentages
21
Table 1
Prevalence of vitamin/mineral supplement use, by age group and sex,
household population aged 1 or older, Canada excluding territories, 2004
Male
Female
95%
confidence
interval
Age group
Total
1 to 3
4 to 8
9 to 13
14 to 18
19 to 30
31 to 50
51 to 70
71 or older
95%
confidence
interval
%
from
to
33.5
38.2
44.3
33.9
23.4
27.9
29.2
40.2
44.9
32.0
33.9
40.5
30.4
20.5
24.5
26.1
37.3
40.5
34.9
42.5
48.1
37.3
26.4
31.3
32.3
43.2
49.3
%
from
to
46.9*
38.9
45.0
32.0
29.5*
37.4*
46.8*
60.3*
60.1*
45.5
34.5
40.9
28.5
26.5
34.0
43.6
57.4
56.8
48.3
43.3
49.1
35.5
32.5
40.8
50.1
63.2
63.4
* significantly higher than males (p<0.05)
Source: 2004 Canadian Community Health Survey—Nutrition.
Figure 1
Prevalence of vitamin/mineral supplement use, by household income group,
age group and sex, household population aged 19 or older, Canada excluding
territories, 2004
%
Household income group
Lowest
Lower-middle
Upper-middle
Highest
80
70
60
*
*
50
*
30
20
*
*
40
*
*
*
*
*
*
*
*
10
0
Men
Women
19 to 30
Men
Women
31 to 50
Men
Women
51 to 70
Men
Women
71 or older
Sex and age group
* significantly lower than highest income group (p<0.05)
Source: 2004 Canadian Community Health Survey—Nutrition.
of supplement users among those
reporting the most severe level of food
insecurity.
Many of the factors associated with
taking supplements are, themselves,
interrelated. For instance, household
income and education are associated
with each other, and food security
tends to be associated with both. When
logistic regression was used to control
for these potentially confounding effects,
age, sex, household income, education,
food security and chronic conditions
were found to be independently and
significantly associated with supplement
use.
For example, compared with children
aged 1 to 8, the only group significantly
more likely to use supplements was
women aged 51 or older; for all other
age/sex groups, the odds of supplement
use were significantly lower (Table 3).
Household income and education were
each independently related to supplement
22
Health Reports, Vol. 21, no. 4, December 2010 • Statistics Canada, Catalogue no. 82-003-XPE
Socio-economic status and vitamin/mineral supplement use in Canada • Research article
Table 2
Prevalence of vitamin/mineral supplement use, by food security status, age
group and sex, household population aged 19 or older, Canada excluding
territories, 2004
Food insecure
Age group/Sex
Food secure
Low
Moderate
Severe
%
%
%
%
29 ± 1
44 ± 1
27 ± 6
39 ± 5
16 ± 5*
35 ± 6
31 ± 13
23 ± 9*
42 ± 1
60 ± 1
19 ± 9*
61± 8
13 ± 10*
48 ± 13
31 ± 19
50 ± 17
19 to 50
Men
Women
51 or older
Men
Women
* significantly different from food secure (p<0.05)
Source: 2004 Canadian Community Health Survey—Nutrition.
Figure 2
Prevalence of vitamin/mineral supplement use, by education, age group and
sex, household population aged 19 or older, Canada excluding territories, 2004
%
Education
80
Less than secondary graduation
70
Secondary graduation
60
Some postsecondary
Postsecondary graduation
*
50
*
†
40
30
*
*
Discussion
*
20
10
0
Women
Men
Women
Men
51 or older
19 to 50
Sex and age group
* significantly lower than some postsecondary and postsecondary graduation (p<0.05)
†
significantly lower than postsecondary graduation (p<0.05)
Source: 2004 Canadian Community Health Survey—Nutrition.
use: even when the effects of the other
variables were taken into account, the
odds that people in the highest income
households would take supplements were
1.6 times those of people in the lowest
income households, and people with at
least secondary graduation had 1.4 times
the odds of taking supplements, compared
with those who had not graduated
from secondary school. The odds of
taking supplements were significantly
low among people with moderate food
to ensure nutritional adequacy, is 1,000
milligrams of calcium a day at ages 19 to
50, and rises to 1,200 milligrams a day at
age 51 or older.23
Regardless of whether they took
supplements, people in all age groups
derived about the same amount of
calcium from food (data not shown), and
the majority were not meeting daily AI.
The percentage meeting AI from food
alone was highest (slightly more than
50%) among men aged 19 to 30, and
lowest (less than 10%) among women
older than 50 (Figure 3). In all age
groups, higher percentages of men than
women met AI based on diet alone.
The use of calcium supplements
boosted the percentage of men and
women of all ages meeting AI, but the
effect was particularly pronounced
among older women. For women aged 51
to 70, calcium intake from supplements
increased the percentage at or above AI
from 8% to 35%, and for those older than
70, from 5% to 29%. In fact, at these
ages, higher percentages of women than
men met calcium AI, a difference solely
attributable to supplement use.
insecurity, compared with those who
were food secure.
People without
chronic conditions were significantly less
likely than those with chronic conditions
to take supplements. No significant
difference in supplement use emerged
between rural and urban residents.
Calcium
The impact of taking supplements can
be illustrated with calcium. Adequate
intake (AI), the level that is considered
The inverse supplement hypothesis,9
which states that people at risk of
nutritional inadequacy or in need of
more nutrients because of disease risk
are not the ones who take vitamin/
mineral supplements, is supported by
the CCHS data analysed in this study.
In addition to sex and age, household
income, education, food security status
and having (a) chronic condition(s) were
significantly related to supplement use.
The supplement use patterns reported
here for Canadians resemble those of
Americans, based on data from the 19992000 National Health and Nutrition
Examination Survey (NHANES).24 In
both countries, a higher percentage of
women than men used supplements;
supplement use increased with age; and a
higher level of education was positively
associated with supplement use.7,8,14,17
Associations with household income
and education in this and in an earlier
Statistics Canada, Catalogue no. 82-003-XPE • Health Reports, Vol. 21, no. 4, December 2010
Socio-economic status and vitamin/mineral supplement use in Canada • Research article
Table 3
Adjusted odds ratios showing factors associated with supplement use, by
selected characteristics, household population aged 1 or older, Canada
excluding territories, 2004
Characteristics
Age group/Sex
1 to 8 (both sexes)†
9 to 18
Male
Female
19 to 50
Men
Women
51 or older
Men
Women
Household income
Lowest†
Lower-middle
Upper-middle
Highest
Education
Less than secondary graduation†
Secondary graduation or more
Food security
Food secure†
Food insecure
Low
Moderate
Severe
Chronic condition(s)
Yes†
No
Residence
Rural†
Urban
What is already
known on this
subject?
95%
confidence
interval
Adjusted
odds
ratio
from
to
p value
1.00
...
...
...
0.59*
0.62*
0.51
0.53
0.68
0.73
<0.0001
<0.0001
0.41*
0.81*
0.33
0.67
0.50
0.98
<0.0001
0.032
0.75*
1.70*
0.62
1.50
0.91
2.10
0.004
<0.0001
■ Evidence points to a link between the
use of supplements and income and
education.
1.00
1.00
1.20
1.60*
...
0.83
1.00
1.30
...
1.20
1.40
1.90
...
0.91
0.02
<0.0001
What does this study
add?
1.00
1.40*
...
1.20
...
1.70
...
<0.0001
...
...
...
■ This is the first study based on
nationally representative data to
examine determinants of supplement
use in Canada.
0.93
0.71*
0.78
0.72
0.53
0.43
1.20
0.95
1.40
0.6
0.02
0.41
1.00
0.87*
...
0.77
...
0.99
...
0.014
1.00
1.00
...
0.90
...
1.10
...
0.8
1.00
†
reference category
* significantly different from reference category (p<0.05)
... not applicable
Source: 2004 Canadian Community Health Survey—Nutrition.
study,24 and the additional relationship
with food insecurity in this study, indicate
relatively low supplement use among
people of lower SES. As well, interviews
and focus groups have revealed income,
education, preferences, health issues
and accessibility to be barriers to using
supplements.24
A 2009 study22 showed that Canadian
adults’ mean calcium intake from
food alone was below recommended
levels for most age/sex groups except
young adult men, and that men had
consistently higher intakes than women.
In the present study, supplements had a
relatively small impact on the percentage
23
■ Diet quality is linked to socioeconomic status―higher-quality diets
tend to be associated with greater
affluence.
■ Vitamin/Mineral supplements
offer the possibility of improving
micronutrient intake and achieving
recommended levels among people
who consume a nutrient-poor diet.
■ In all age groups older than 14, a
higher percentage of females than
males took supplements.
■ The prevalence of supplement use
was highest among women aged
50 or older, at least 60% of whom
reported taking vitamin/mineral
supplements in the past month.
■ Socio-economic gradients in
supplement use were evident for
most adult age/sex groups.
of men with adequate calcium intake, but
the increase among women, particularly
older women, was substantial, raising
the percentage with adequate intake at
least fourfold. In fact, because of the
considerable amount of calcium older
women derive from supplements, their
total intake exceeded that of their male
contemporaries.
Limitations
A limitation of this analysis is that the data
on vitamin/mineral supplement use were
self-reported and pertained to the month
before the CCHS interview. By contrast,
24-hour recalls were used to collect data
■ These findings support the literature
on supplement use from the United
States and indicate a potential
health disparity in access to vitamin/
mineral supplementation.
about food and beverage consumption.
The second recall, in which about 30% of
respondents participated, made it possible
to reduce within-person variation to some
extent and better estimate usual food and
beverage consumption. With 83% of
the CCHS respondents reporting daily
use of supplements over the past month,
it was assumed that this represented
24
Health Reports, Vol. 21, no. 4, December 2010 • Statistics Canada, Catalogue no. 82-003-XPE
Socio-economic status and vitamin/mineral supplement use in Canada • Research article
Figure 3
Percentage meeting Adequate Intake for calcium from food and from food plus
supplements, by age group and sex, household population aged 19 or older,
Canada excluding territories, 2004
%
60
Supplements
Food
50
the high percentage of supplement
users among men aged 19 to 30 in
the lowest household income group)
might be explained by high betweenindividual variability in supplement use,
and possibly, by an irregular pattern of
supplement use for clinical reasons in
some subsets of respondents.
Conclusion
40
30
20
10
0
19 to 30
31 to 50
51 to 70
71 or older
19 to 30
31 to 50
51 to 70
71 or older
Women
Men
Age group and sex
Source: 2004 Canadian Community Health Survey—Nutrition.
their usual practice. Nonetheless, the
different data collection methods for
food/beverage versus supplement intake,
the different reference periods (previous
day versus past month), and the lack of
a within-person variability measure for
supplement use could affect the estimate
of total combined intake from food and
from supplements. Unexpected results
for some age/sex groups (for example,
Data from the 2004 Canadian Community
Health Survey provide evidence that SES
indicators such as household income,
education and food security are associated
with vitamin/mineral supplement use,
and that adults of lower SES are less
likely to take supplements. This finding,
consistent with research from the United
States, reveals a potential health disparity
with unequal uptake of vitamin/mineral
supplementation. ■
Statistics Canada, Catalogue no. 82-003-XPE • Health Reports, Vol. 21, no. 4, December 2010
Socio-economic status and vitamin/mineral supplement use in Canada • Research article
25
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Archer SL, Stamler J, Moag-Stahlberg A,
et al. Association of dietary supplement use
with specific micronutrient intakes among
middle-aged American men and women: The
INTERMAP Study. Journal of the American
Dietetic Association 2005; 105: 1106-14.
Barr SI. British Columbia Nutrition Survey:
Report on Supplements. University of British
Columbia; 2004. Available at: http://www.
health.gov.bc.ca/prevent/nutrition/. Accessed
March 6, 2009.
National
Institutes
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Health
State-of-the-Science Panel. National Institutes
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257S-64S.
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Lemstra M, Neudorf C, Opondo J. Health
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Kirkpatrick SI, Tarasuk V. Food insecurity is
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Canadian adults and adolescents. Journal of
Nutrition 2008; 138(3): 604-12.
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Darmon N, Drewnowski A. Does social class
predict diet quality? The American Journal
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Balluz LS, Kieszak SM, Philen RM, Mulinare
J. Vitamin and mineral supplement use in the
United States. Archives of Family Medicine
2000; 9: 258-62.
10. Pelletier D, Kendall A. Supplement use may
not be associated with better food intake in
all population groups. Family Economics and
Nutrition Review 1997; 10: 32-45.
11. Ma J, Johns RA, Stafford RS. Americans are
not meeting current calcium recommendations.
The American Journal of Clinical Nutrition
2007; 85: 1361-6.
12. Picciano MF, Dwyer JT, Radimer KL, et
al. Dietary supplement use among infants,
children, and adolescents in the United
States, 1999-2002. Archives of Pediatrics &
Adolescent Medicine 2007; 161: 978-85.
13. Yu SM, Kogan MD, Gergen P. Vitamin-mineral
supplement use among preschool children in
the United States. Pediatrics 1997;100: E4.
14. Balluz LS, Okoro CA, Bowman BA, et al.
Vitamin or supplement use among adults,
behavioral risk factor surveillance system,
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120: 117-23.
15. Lyle BJ, Mares-Perlman JA, Klein BE, et
al. Supplement users differ from nonusers
in demographic, lifestyle, dietary and health
characteristics. Journal of Nutrition 1998; 128:
2355-62.
16. Nayga R, Reed D. Factors associated with
dietary supplements. Family Economics and
Nutrition Review 1999; 12: 43-9.
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Fennell D. Determinants of supplement usage.
Preventive Medicine 2004; 39: 932-9.
17. Radimer K, Bindewald B, Hughes J, et al.
Dietary supplement use by US adults: data
from the National Health and Nutrition
Examination Survey, 1999-2000. American
Journal of Epidemiology 2004; 160: 339-49.
9.
Lino M, Dinkins J, Bente L. Household
expenditure on vitamins and minerals by
income level. Family Economics and Nutrition
Review 1999; 12: 39-44.
18. Troppmann L, Johns T, Gray-Donald K.
Natural health product use in Canada.
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Health Survey, Cycle 2.2, Nutrition (2004). A
Guide to Accessing and Interpreting the Data
(Catalogue H164-20/2006E-PDF). Available
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nutrition/commun/cchs_guide_escc_e.html.
Accessed February 9, 2009.
20. Moshfegh AJ, Borrud L,Perloff B, et al.
Improved method for the 24-hour dietary
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Whiting S. Canadians are not meeting
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and Metabolism 2009; 34: 191-6.
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E L E C T R O N I C P U B L I C AT I O N S
AVA I L A B L E AT
w w w. s t a t c a n . g c . c a
Statistics Canada, Catalogue no. 82-003-XPE • Health Reports, Vol. 21, no. 4, December 2010
Trends in long-term care staffing by facility ownership in British Columbia, 1996 to 2006 • Research article
27
Trends in long-term care staffing by
facility ownership in British Columbia,
1996 to 2006
by Margaret J. McGregor, Robert B. Tate, Lisa A. Ronald, Kimberlyn M. McGrail, Michelle B. Cox,
Whitney Berta and Anne-Marie Broemeling
Abstract
Background
Long-term care facilities (nursing homes) in
British Columbia consist of a mix of for-profit,
not-for-profit non-government, and not-for-profit
health-region-owned establishments. This study
assesses the extent to which staffing levels have
changed by facility ownership category.
Data and methods
With data from Statistics Canada’s Residential
Care Facilities Survey, various types of care
hours per resident-day were examined from 1996
through 2006 for the province of British Columbia.
Random effects linear regression modeling
was used to investigate the effect of year and
ownership on total nursing hours per resident-day,
adjusting for resident demographics, case mix,
and facility size.
Results
From 1996 to 2006, crude mean total nursing
hours per resident-day rose from 1.95 to 2.13
hours in for-profit facilities (p=0.06); from 1.99
to 2.48 hours in not-for-profit non-government
facilities (p<0.001); and from 2.25 to 3.30 hours
in not-for-profit health-region-owned facilities
(p<0.001). The adjusted rate of increase in total
nursing hours per resident-day was significantly
greater in not-for-profit health-region-owned
facilities.
Interpretation
While total nursing hours per resident-day have
increased in all facility groups, the rate of increase
was greater in not-for-profit facilities operated by
health authorities.
Keywords
aged, frail elderly, geriatrics, geriatric nursing,
homes for the aged, nursing care, nursing homes,
nursing staff
Authors
Margaret J. McGregor (1-604-827-4129;
[email protected]) and Michelle B. Cox
are with the Department of Family Practice
Research Office at the University of British
Columbia, Vancouver, British Columbia
V5Z 1L8. Robert B. Tate is with the Department
of Community Health Sciences at the University
of Manitoba. Lisa A. Ronald is with the Centre
for Clinical Epidemiology and Evaluation at the
Vancouver Coastal Health Research Institute.
Kimberlyn M. McGrail and Anne-Marie Broemeling
are with the UBC Centre for Health Services
and Policy Research. Whitney Berta is with the
Department of Health Policy, Management and
Evaluation at the University of Toronto.
L
ong-term care facilities (nursing homes) provide
housing, support and direct care to frail seniors
who are unable to function independently. Nursing
care in these facilities is provided by a combination
of registered nurses (RNs), licensed practical nurses
(LPNs), and resident care aides. Higher total
nursing1,2 and RN3,4 hours per resident day have
been associated with better care. Thus, nursing hours
per resident-day is considered to be one reasonable
measure of nursing home quality.5
Long-term residential care in Canada
is delivered by a mix of for-profit
(proprietary) and not-for-profit (nonproprietary)
non-government
and
government-owned facilities.
This
diversity of delivery models offers an
opportunity to compare services by
facility ownership—information that
is useful to provincial governments
faced with rising health care costs and
challenged to provide the best “value for
money.”
Research, mainly in the United States,
has found that not-for-profit ownership
is associated with higher staffing
levels,6,7 lower staff turnover,8 and
better outcomes on a range of measures,
compared with for-profit-ownership.5-7,9
While the results of American analyses
are intriguing, differences in the market
mix may limit the generalizability of
such findings to Canada.
Only three Canadian studies have
quantitatively examined associations
between staffing levels and facility
ownership.10-12 Analyses in Ontario and
British Columbia found that for-profit
facilities employed fewer nursing staff
than did not-for-profit facilities.10,12 By
contrast, a Manitoba study reported no
apparent differences in nursing staff
levels between for-profit and not-forprofit facilities.11
The seniors in long-term care facilities
today tend to be older, more disabled
and closer to the end of life than were
residents a decade ago.13-15 This shift
in the resident profile has placed new,
more complex demands on staff. Yet
despite these changes in the case mix
of residents, data on nursing home staff
have not been examined over time.
This analysis uses data from Statistics
Canada’s annual Residential Care
28
Health Reports, Vol. 21, no. 4, December 2010 • Statistics Canada, Catalogue no. 82-003-XPE
Trends in long-term care staffing by facility ownership in British Columbia, 1996 to 2006 • Research article
(n=10); and facilities reporting extreme
outliers for total direct care hours per
resident-day in a given year (three
times greater or three times less than the
standard deviation from the mean of the
study population) (n=132). If a facility’s
total direct care hours per resident-day
more than doubled or were reduced
to less than half over two consecutive
years with no corresponding change in
ownership, this was considered to be a
reporting error, and the response for the
survey year in question was excluded
(n=66).
Facility size was defined as the
mean number of licensed and staffed
beds. Facilities were divided into two
ownership categories: for-profit and notfor-profit. The for-profit group consisted
of institutions that self-identified as
proprietary, and included smaller private
organizations and chain corporations.
Not-for-profit facilities were subdivided
into non-government (owned and
operated by religious or lay not-forprofit societies) and health-region-owned
(owned and/or operated by a regional
governance structure responsible for
the continuum of health services for
the defined geographic regions). Notfor-profit facilities were categorized
this way because research has revealed
significantly lower hospitalization rates
for care-sensitive outcomes in facilities
that are health-region-owned.17 At the
beginning of the study period (1996),
very few facilities were health-regionowned, but after the regionalization of
health services in the late 1990s, the
number increased substantially.
Facilities Survey to examine changes in
staffing levels over the past decade in
nursing homes in the province of British
Columbia, by facility ownership.
Data and methods
Data source
Each year since 1974, Statistics
Canada has conducted the Residential
Care Facilities Survey (RCFS).16
The questionnaire has not changed
appreciably since the inception of the
survey and covers facility type and
size, resident demographics, case mix
and staffing. Copies are available on
Statistics Canada’s website (www.
statcan.gc.ca).
Each March, the questionnaire is
mailed to the director of care in every
long-term care facility with at least four
beds, which is licensed by the provincial/
territorial department of health and/
or social services, and whose financial
statements are not embedded in those
of an acute-care hospital. During the
subsequent four months, reminders
are mailed to non-respondents, and if
possible, the survey is administered by
telephone.
In this analysis, the study “population”
consists of British Columbia facilities
that self-identified as providing
residential care mainly to the “aged,” and
that responded to the RCFS at least once
between April 1, 1996 and March 31,
2007 (Table 1). The analysis excluded:
facilities with fewer than 10 beds or
housing mostly residents who required
minimal assistance (n=13); facilities
reporting 0 residents in a given year
During the 1996-to-2006 period, the
response rates to the RCFS were 56%
for for-profit facilities, 77% for notfor-profit non-government facilities,
and 66% for not-for-profit healthregion-owned facilities. After the data
exclusions, a total of 1,640 responses
were analysed, representing 48% (577),
72% (781) and 51% (282) of the total
potential responses for for-profit, notfor-profit non-government, and not-forprofit health-region-owned facilities,
respectively (Table 1). The number
of times facilities reported during the
eleven-year period varied from 1 to 11,
with 38% of facilities reporting 8 or more
times.
Ethics approval for this study was
obtained from the relevant academic and
institutional ethics boards.
Measures
Staffing
Each facility’s average number of paid
hours per resident-day for every staff
category (RN, LPN, care aide) was
calculated by dividing the total reported
number of paid hours in that staff category
on March 31 of the survey year by the
number of beds reported as being staffed
and in operation, all divided by 365.25
days. For every year, mean RN hours
per resident-day, total nursing (RN, LPN
and care aide) hours per resident-day,
RN hours as a proportion of total nursing
hours, total therapist (occupational,
physical and recreation therapy) hours
per resident-day and activity aide hours
per resident-day were calculated.
Table 1
Survey frame for Residential Care Facilities Survey, by ownership, British Columbia, 1996-to-2006 period
Not-for-profit
Total
Long-term care facilities
Surveyed
Responded at least once
Included in study
For-profit
Non-government
Health-region-owned
Facilities
Responses
Facilities
Responses
Facilities
Responses
Facilities
Responses
321
281
270
2,827
1,861
1,640
140
111
103
1,197
667
577
135
127
127
1,078
828
781
97
86
81
552
366
282
Notes: Because some facilities changed ownership during the 11-year period, the number by ownership type may not add to the total in each category. Hospital-based facilities were not included in the
survey frame (N=66 in 1999, estimated from previous research18). Facilities excluded: fewer than 10 beds (N=13); reported 0 residents in a given year (N=10); total direct care hours per resident
day +/- 3 standard deviations from mean for study population (N=132); total direct care hours per resident day more than doubled or were reduced to less than half over two consecutive years with
no change in ownership (N=66).
Source: 1996 to 2006 Residential Care Facilities Survey.
Statistics Canada, Catalogue no. 82-003-XPE • Health Reports, Vol. 21, no. 4, December 2010
Trends in long-term care staffing by facility ownership in British Columbia, 1996 to 2006 • Research article
Resident characteristics
The sex of facility residents was
measured as the percentage male. Age of
residents was measured as the percentage
85 or older. A facility’s case mix was
calculated as the percentage of residents
whose care level was at least Type III
(defined as needing 24-hour availability
of professional nursing care and
supervision; medical management and/or
therapeutic care required), grouped into
four categories: 0%; 1% to 49%; 50%
to 99%; and 100%. A facility’s annual
mortality rate was total deaths divided by
the total number of residents in care the
same year.
Analyses
Descriptive data for facility response rates
were calculated by ownership and by
demographic and case mix characteristics
for each year. Descriptive data for all
staffing measures were produced by
year and stratified by ownership. Each
staffing measure was tested for the effect
of year to assess linear trends over time.
A random effects linear regression
model (PROC GENMOD, SAS v9.1)
was used to examine the adjusted effect of
year and ownership on total nursing hours
per resident-day. The regression models
adjusted for resident demographics
(percentage male; percentage aged 85 or
older), case mix (percentage of residents
Type III or higher; annual mortality
rate), and facility size (number of staffed
and operating beds). Three separate
regression models were produced: the
first included survey year; the second
included survey year and ownership;
and the third included survey year,
ownership, and the interaction of year
and ownership.
To analyze the separate effect of the
two types of not-for-profit ownership, the
data for the adjusted models pertained to
1999 onward because there were very
few health region-owned facilities before
1999. To be included in this analysis,
facilities had to have responded to the
RCFS at least twice in the 1999-to-2006
period.
Several tests were conducted to assess
the robustness of results. Models were
run with and without implementing
the descriptive data exclusion rules.
To assess the potential impact of
frequency of response, the model was
run to progressively exclude facilities
responding less than three, four and five
times during the period. In all cases, the
direction and significance of the results
were consistent with those reported in
this study.
29
Results
Case mix
Between 1996 and 2006, the population
of residents in British Columbia’s
nursing homes became older and frailer
(Table 2). The percentage of residents
aged 85 or older rose from 50% to 55%.
The percentage of facilities with 100%
of residents requiring Type III care or
higher increased from 4% to 38%. The
mean annual mortality rate of residents
went from 11% to 17%.
Staffing levels
Trends in nursing home staffing levels
differed by ownership (Table 3). In
for-profit facilities, crude mean total
nursing (RN, LPN and care aide) hours
per resident-day increased from 1.95
(SD 0.62) in 1996 to 2.13 (SD 0.84) in
2006 (p=0.06). In not-for-profit nongovernment facilities, the increase was
from 1.99 (SD 0.35) to 2.48 (SD 0.94)
hours per resident-day (p<0.001), and
in not-for-profit health-region-owned
facilities, from 2.25 (SD 0.60) to 3.30
(SD 1.51) hours per resident-day
(p<0.001). However, in each type of
facility, RN hours as a proportion of total
nursing hours did not change appreciably
over the period, so the increases in total
Table 2
Case mix in long-term care facilities, British Columbia, 1996 to 2006
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
Facilities
Number
% of total surveyed
165
70.8
158
68.1
146
62.4
153
68.0
131
58.2
163
70.9
159
70.7
151
64.0
147
59.3
133
52.6
134
59.0
Residents aged 85 or older
Mean proportion
Standard deviation
0.50
0.16
0.52
0.14
0.51
0.14
0.54
0.15
0.54
0.15
0.54
0.14
0.54
0.15
0.55
0.16
0.52
0.17
0.54
0.15
0.55
0.15
Male residents
Mean proportion
Standard deviation
0.30
0.15
0.29
0.15
0.28
0.14
0.27
0.14
0.28
0.15
0.28
0.14
0.27
0.13
0.28
0.14
0.29
0.13
0.28
0.14
0.29
0.13
Mortality
Mean annual rate*
Standard deviation
0.11
0.07
0.12
0.06
0.12
0.06
0.13
0.06
0.13
0.07
0.14
0.07
0.14
0.07
0.16
0.08
0.17
0.07
0.17
0.08
0.17
0.09
7
4.2
12
7.6
15
10.3
12
7.8
21
16.0
16
9.8
21
13.2
34
22.5
47
32.0
49
36.8
51
38.3
Facilities with all residents Type III†
or higher‡
Number
%
* total deaths divided by total residents in care in same year
†
client needs 24-hour availability of professional nursing care and supervision; medical management and/or therapeutic care required
‡
client needs 24-hour monitoring by professional nursing staff, but not resources of acute-care hospital
Source: 1996 to 2006 Residential Care Facilities Survey.
30
Health Reports, Vol. 21, no. 4, December 2010 • Statistics Canada, Catalogue no. 82-003-XPE
Trends in long-term care staffing by facility ownership in British Columbia, 1996 to 2006 • Research article
Table 3
Selected measures of nursing hours in long-term care facilities, by ownership, British Columbia, 1996 to 2006
Total nursing hours
per resident-day
For-profit
Mean number
Standard deviation
Not-for-profit non-government
Mean number
Standard deviation
Not-for-profit health-region-owned
Mean number
Standard deviation
Registered nurse (RN) hours
per resident-day
For-profit
Mean number
Standard deviation
Not-for-profit non-government
Mean number
Standard deviation
Not-for-profit health-region-owned
Mean number
Standard deviation
Registered nurse (RN) hours/
Total nursing† hours
For-profit
Mean proportion
Standard deviation
Not-for-profit non-government
Mean proportion
Standard deviation
Not-for-profit health-region-owned
Mean proportion
Standard deviation
Total therapist‡ and activity aide
hours per resident-day
For-profit
Mean number
Standard deviation
Not-for-profit non-government
Mean number
Standard deviation
Not-for-profit health-region-owned
Mean number
Standard deviation
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
Linear
regression
coefficient
for year
of survey
1.95
0.62
2.04
0.49
2.11
0.61
2.13
0.54
2.10
0.52
2.17
0.71
2.17
0.63
2.26
0.73
2.18
0.76
2.33
0.76
2.13
0.84
0.023
...
-0.001
...
0.047
...
1.99
0.35
2.05
0.33
2.18
0.54
2.27
0.64
2.34
0.63
2.36
0.61
2.36
0.57
2.37
0.78
2.37
0.66
2.58
0.78
2.48
0.94
0.051***
...
0.031
...
0.071
...
2.25
0.60
2.25
0.89
2.22
0.53
2.23
0.72
2.12
0.54
2.23
0.49
2.17
0.50
2.72
0.80
3.05
0.86
2.98
0.63
3.30
1.51
0.142***
...
0.092
...
0.191
...
0.51
0.23
0.58
0.20
0.58
0.24
0.63
0.35
0.57
0.20
0.59
0.42
0.50
0.18
0.52
0.20
0.46
0.20
0.45
0.18
0.43
0.25
-0.014***
...
-0.022 -0.007
...
...
0.51
0.13
0.54
0.12
0.61
0.32
0.59
0.18
0.62
0.17
0.59
0.17
0.57
0.17
0.59
0.32
0.55
0.20
0.56
0.25
0.52
0.21
-0.0004
...
-0.007
...
0.006
...
0.47
0.09
0.47
0.13
0.53
0.20
0.52
0.17
0.56
0.21
0.51
0.37
0.49
0.33
0.49
0.26
0.54
0.27
0.54
0.31
0.56
0.36
0.005
...
-0.008
...
0.019
...
0.27
0.10
0.28
0.07
0.28
0.12
0.30
0.15
0.27
0.07
0.29
0.18
0.24
0.07
0.23
0.08
0.26
0.22
0.24
0.19
0.27
0.28
-0.004
...
-0.010
...
0.002
...
0.26
0.09
0.27
0.05
0.29
0.14
0.27
0.07
0.28
0.07
0.26
0.07
0.26
0.11
0.25
0.12
0.25
0.15
0.24
0.16
0.28
0.26
-0.002
...
-0.007
...
0.003
...
0.22
0.07
0.22
0.08
0.28
0.23
0.25
0.11
0.28
0.14
0.23
0.18
0.23
0.16
0.20
0.12
0.21
0.16
0.19
0.11
0.28
0.31
-0.004
...
-0.012
...
0.005
...
0.15
0.13
0.14
0.05
0.14
0.07
0.14
0.06
0.14
0.05
0.12
0.06
0.11
0.05
0.12
0.06
0.10
0.06
0.11
0.07
0.12
0.07
-0.004**
...
-0.007 -0.001
...
...
0.19
0.15
0.17
0.08
0.19
0.19
0.18
0.08
0.19
0.08
0.18
0.08
0.17
0.09
0.17
0.08
0.20
0.25
0.18
0.09
0.18
0.10
-0.001
...
-0.005
...
0.004
...
0.20
0.14
0.10
0.08
0.15
0.09
0.27
0.38
0.31
0.43
0.22
0.08
0.21
0.11
0.23
0.09
0.22
0.14
0.20
0.14
0.22
0.13
-0.001
...
-0.014
...
0.012
...
95%
confidence
interval
from
to
†
** p<0.01, ***p<0.001
†
registered nurses. licensed practical nurses, care aides
‡
occupational, physical and recreation therapy
... not applicable
Source: 1996 to 2006 Residential Care Facilities Survey.
nursing hours per resident-day were
almost entirely the result of increases in
non-RN hours.
Total therapist/activity aide hours
per resident-day decreased in for-profit
facilities, but remained stable in both
types of not-for-profit facilities.
Adjusted effect of year and
ownership
When
adjusting
for
resident
demographics, case mix, mortality rate
and facility size, there was a significant
positive effect of year on mean total
nursing hours per resident-day across the
period (Table 4, Model 1). Compared
with for-profit facilities, total nursing
hours per resident-day were significantly
higher in both types of not-for-profit
facilities in the adjusted model (Table 4,
Model 2). Finally, the rate of increase
across time in total nursing hours per
Statistics Canada, Catalogue no. 82-003-XPE • Health Reports, Vol. 21, no. 4, December 2010
Trends in long-term care staffing by facility ownership in British Columbia, 1996 to 2006 • Research article
31
Table 4
Linear regression models for adjusted effect of year, facility ownership, and year x ownership on mean total nursing
hours per resident-day in long-term care facilities,† British Columbia, 1999 to 2006
Model 1‡
Regression
coefficient§
0.039**
Year
Model 2‡
95%
confidence
interval
from
to
0.012
0.066
Model 3‡
95%
confidence
interval
Regression
coefficient§
95%
confidence
interval
from
to
Regression
coefficient§
from
to
0.037**
0.010
0.064
0.004
-0.034
0.042
0.064
0.279
0.434
0.666
0.184
-0.677*
-0.168 0.536
-1.232 -0.123
...
...
...
...
0.008
0.153***
-0.039
0.076
Ownership (reference=for-profit)
Not-for-profit non-government
Not-for-profit health-region-owned
...
...
...
...
...
...
0.249**
0.472***
Interaction (year x ownership)
Year x not-for-profit non-government
Year x not-for-profit health-region-owned
...
...
...
...
...
...
...
...
0.054
0.230
* p<0.05, **p<0.01, ***p<0.001
†
N=233 facilities (1,073 survey responses)
‡
adjusted for population mean values of % male residents, % residents aged 85 or older, % residents Type III or higher, annual mortality rate, and facility size
§
excludes 30 facilities responding only once in 1999-to-2006 period
... not applicable
Source: 1996 to 2006 Residential Care Facilities Survey.
resident-day was significantly greater
for not-for-profit health-region-owned
facilities, compared with for-profit
facilities (Table 4, Model 3).
By 2006, not-for-profit health-regionowned facilities had an adjusted estimate
of 61 more minutes per resident-day and
not-for-profit non-government-owned
facilities, 16 more minutes per residentday, compared with for-profit facilities
(Table 5).
Discussion
With data from Statistics Canada’s
Residential Care Facilities Survey, this
study traced trends in staffing levels
in British Columbia’s nursing homes
from 1996 to 2006. The estimates of
total nursing hours per resident-day are
similar to levels reported for Ontario,10
but substantially below those in a crosssectional British Columbia study.12 This
may reflect the data sources: the Ontario
estimates were based on the same
source as the current study (the RCFS),
whereas the British Columbia study
used data submitted to the province’s
Labour Relations Board by union and
management before a contract dispute.
This analysis shows that since 1996,
total nursing hours per resident-day rose
for all three facility ownership groups,
but increases in RN (the most highly
trained staff) hours were negligible. That
RN hours in British Columbia did not
rise during a period of increasing resident
clinical complexity is of particular note,
given evidence of a link between RN
staffing levels and quality of care.3,4,17
Consistent with earlier research,6,7,9,10,12
total adjusted nursing hours per
Table 5
Estimated difference in mean total nursing minutes per resident-day in longterm care facilities,† by facility ownership and year, British Columbia, 1999 to
2006
Ownership
1999
2000
2001
2002
2003
2004
2005
2006
15.0
42.0
15.6
51.0
16.2
60.6
(minutes per resident-day)
Non-profit non-government
Non-profit health-region-owned
12.6
- 3.6
13.2
5.4
13.8
14.4
14.4
24.0
15.0
33.0
†
N=233 facilities (1,073 survey responses)
Notes: Random effects linear regression models adjusted for population mean values of % male residents, % residents aged 85
or older, % residents Type III or higher, mortality rate, and facility size. Reference category is for-profit. Models exclude 30
facilities that responded only once in the 1999-to-2006 period.
Source: 1996 to 2006 Residential Care Facilities Survey.
resident-day in British Columbia were
significantly lower in for-profit facilities,
compared with the two not-for-profit
groups. One explanation may be the
institutional mandate. Staff constitute
one of the largest expenditure categories,
so lowering costs by reducing staff time
is a means of increasing profits.19,20
Moreover, British Columbia has no
formal regulation of minimum staffing
levels, so facilities have some leeway
in deciding what is appropriate, thereby
enabling such a difference to persist.
Previous research in British Columbia18
found lower hospital admission rates for
a number of care-sensitive diagnoses in
health-region-owned facilities, compared
with both for-profit facilities and not-forprofit non-government facilities. The
dramatically higher total nursing hours
per resident-day in health region-owned
facilities in the current study suggests
that staffing levels may be one element
driving these improved outcomes.
The high total nursing hours per
resident-day in not-for-profit healthregion-owned facilities is consistent with
findings from Ontario,10 but not Manitoba
where staffing levels were found to be
uniform for all ownership groups.11
While the difference in nursing hours
per resident-day in for-profit and notfor-profit non-government facilities is
statistically significant, the magnitude
of the difference is small and may be
32
Health Reports, Vol. 21, no. 4, December 2010 • Statistics Canada, Catalogue no. 82-003-XPE
Trends in long-term care staffing by facility ownership in British Columbia, 1996 to 2006 • Research article
What is already
known on this
subject?
■ American studies have found that
not-for-profit ownership of nursing
homes is associated with higher
staffing levels, lower staff turnover,
and better outcomes on a range of
measures, compared with for-profitownership.
■ Differences in the market mix may
limit the generalizability of American
findings to Canada.
■ Only three Canadian studies have
quantitatively examined associations
between long-term care facility
staffing levels and facility ownership,
and the results have not been
consistent.
■ Seniors living in long-term care
facilities today are older, more
disabled and closer to the end of life
than were residents a decade ago,
but data on nursing home staff have
not been examined over time.
What does this study
add?
■ Total nursing hours per resident day
have increased over the past decade
for all facility ownership groups in
British Columbia.
■ The rate of increase in not-for-profit
facilities owned by a health region
was significantly greater compared
with for-profit facilities.
■ Total nursing hours per resident
day were also significantly lower in
for-profit facilities, compared with
not-for-profit facilities.
of questionable clinical significance.
Nonetheless, given previous research
demonstrating that one toileting episode
takes approximately eight minutes,21
even fairly small increases in nursing
staff time may add meaningful quality to
residents’ lives.
Regardless of facility ownership, total
nursing hours per resident-day in this
study (2.13 to 3.30 hours) were below
current recommendations.2,22 The U.S.
Centers for Medicare and Medicaid
determined that 4.1 hours per residentday (combined 2.8 hours for non-licensed
and 1.3 hours for licensed) was the
threshold below which poorer outcomes
such as weight loss and pressure ulcers
were more likely to occur.2
Limitations
This study has a number of limitations.
Although the initial survey response
rate was relatively good, outliers and
inconsistent responses across time
were concerns. Consequently, these
data were excluded from the analysis.
The regression models were run with
and without these exclusions, and the
significance and direction of the effect
estimates were unchanged, but it is still
possible that some bias was introduced
by the decision rules.
A second limitation is the potential
inclusion in the dataset of a small number
of privately financed user-pay for-profit
facilities.
However, this subgroup
represents fewer than 5% of facilities in
British Columbia and is unlikely to have
influenced the overall results.
A third limitation is that case mix
adjustment was done at the facility
level, not the resident level. Therefore,
it was not possible to determine if the
differences in staffing were due to
differences in the underlying case mix
of residents not captured by the facilitylevel data.
Another limitation is that while the
outcome was staffing hours per residentday, staffing hours per bed-day were
measured, based on the assumption
that facilities were operating at 100%
capacity and that residents were always
on site (versus in hospital, for example).
The former assumption is reasonable
given the long waitlists for admission to
residential care facilities in most health
regions. However, if occupancy rates
differed across facilities by ownership,
staffing hours per resident-day may have
spuriously appeared lower or higher than
they actually were.
Finally, staffing levels are only one
measure of quality. Other staff-related
measures such as the turnover rate,23 and
management practices24 have been found
to be highly correlated with the quality
of care.
Conclusion
While total nursing hours per residentday in all long-term residential care
facility groups in British Columbia have
increased over time, the percentage of
RN hours did not rise substantially. As
well, the rate of increase in nursing hours
per resident-day varied considerably
by ownership. Increases in staffing
since 1996 were much greater in
not-for-profit facilities operated by
regional health authorities than in forprofit facilities and not-for-profit nongovernment facilities. ■
Acknowledgements
This project was supported by a
Canadian Institute for Health Research
Institute for Aging pilot grant FY06/07.
Margaret J. McGregor holds a
Vancouver Foundation, Communitybased Clinician Investigator award and
is further supported by the University
of British Columbia, Centre for Health
Services and Policy Research and the
Department of Family Practice, Division
of Geriatrics.
We gratefully acknowledge the
following individuals:
Dr Batoul
Shariati, who helped in the early stages
of data analysis; Richard Trudeau, Lee
Grenon and Cheryl Fu from Statistics
Canada, who assisted in working with the
Statistics Canada data; Shannon Berg,
Director, Community Care Network
Integration Vancouver Coastal Health
and Ron Van Halen, Director, Financial
Planning,
Vancouver
Community,
Vancouver Coastal Health, who assisted
in interpreting some of the “outlier” data;
Christine Lusk, Director of Care, Royal
Arch Masonic Lodge, who also assisted
in interpreting some of the “outlier” data
and provided feedback on an earlier
draft of the manuscript; Marcy Cohen,
Research Director with the Hospital
Employees Union, who assisted with data
interpretation and provided feedback on
an earlier draft of the manuscript; and Dr.
Janice Murphy, who assisted in accessing
some of the relevant literature.
Statistics Canada, Catalogue no. 82-003-XPE • Health Reports, Vol. 21, no. 4, December 2010
Trends in long-term care staffing by facility ownership in British Columbia, 1996 to 2006 • Research article
33
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E L E C T R O N I C P U B L I C AT I O N S
AVA I L A B L E AT
w w w. s t a t c a n . g c . c a
Statistics Canada, Catalogue no. 82-003-XPE • Health Reports, Vol. 21, no. 4, December 2010
Asthma and school functioning • Research article
35
Asthma and school functioning
by Dafna E. Kohen
Abstract
Background
The impact of asthma on school performance,
particularly compared with that of other chronic
conditions, is relatively unexplored, and the
results of analyses that have been conducted are
inconclusive. This article examines associations
between asthma and school functioning.
Data and methods
The data are from the 1998/1999 National
Longitudinal Survey of Children and Youth. The
study pertains to a sample of 8,914 children aged
7 to 15. Descriptive and regression analyses were
used to examine associations between asthma
severity and scores on standardized math and
reading tests, and maternal ratings of school
performance. School absence and the use of
educational services were considered as potential
mediators. Comparisons were made with children
who had other chronic conditions or no chronic
conditions.
Results
Compared with children who did not have a
chronic condition, children with asthma scored
lower on standardized math and reading tests
and had less favourable mother-reported school
performance. Those with the most severe asthma
had the poorest outcomes. These associations
persisted when adjusting for child and family
factors. The poorer scholastic outcomes were not
mediated by school absence. However, the use
of educational services appeared to mediate low
math scores for children with severe asthma.
Interpretation
The relationship between asthma and children’s
school functioning may be of interest to physicians
and educators. Educational support and remedial
services may be beneficial.
Keywords
achievement, asthma severity, chronic illness,
math performance, reading performance
Author
Dafna E. Kohen (613-951-3346; [email protected]
statcan.gc.ca) is with the Health Analysis Division
at Statistics Canada.
T
he prevalence of asthma has been increasing
among Canadian children and youth.1
Compared with other children, those with asthma are
in poorer health, are limited in daily activities, and
experience more visits to health care professionals
and hospitalizations.2,3 They also miss more school
than children who do not have the condition.3-10 In
fact, asthma has been reported to be the leading cause
of school absence.11,12
The increased absenteeism of children
with asthma has been well documented,5-10
but associations between asthma severity
and absence are less clear. Some studies
have found asthma severity to be related
to school absences,5,13 while others have
not.14-16
Although frequent absences may
mean that children with asthma do less
well academically than those who do
not have the condition,9,10 the impact
of asthma on school performance is
relatively unexplored, and the results
of the studies that have been conducted
are inconclusive.10 In a populationbased sample of American children in
Grades 1 to 12, Fowler et al.17 noted a
greater likelihood of grade failure among
children with asthma compared with
healthy children. Other research suggests
associations between asthma and reading
problems,18 grade repetition,19 learning
disabilities,17 and behaviour problems.20-22
On the other hand, a population-based
cohort study by Silverstein et al.8 reported
no difference in school functioning
between children who did and did not
have asthma. Several other studies4,14,23
have had similar findings.
These discrepant results may be
attributable to differences in the
definitions of asthma and of school
performance; whether the analysis
accounted for asthma severity; the
inclusion of a control group; and the use
of standardized versus caregiver-reported
measures of school performance.
The current study is based on a crosssectional sample of school-aged children
from the third cycle (1998/1999) of
Statistics Canada’s National Longitudinal
Survey of Children and Youth (NLSCY).
Associations between asthma severity
and standardized and parent-reported
measures of school functioning are
examined.
36
Health Reports, Vol. 21, no. 4, December 2010 • Statistics Canada, Catalogue no. 82-003-XPE
Asthma and school functioning • Research article
Methods
Data source and sample
Since 1994/1995, the NLSCY has
collected information about Canadian
children’s development and factors
related to their well-being.24 This study
presents cross-sectional estimates from
the third NLSCY cycle, which obtained
data for a sample of 38,035 children
aged 0 to 15 years in the fall of 1998
and the spring of 1999. Cycle 3 was
selected because it contains standardized
and parent-reported school performance
outcomes that were dropped in later
cycles of the NLSCY.
The sample for this study consisted of
8,914 children aged 7 to 15 (Grade 2 and
higher) who had complete data on the
measures of interest. All analyses were
weighted using a normalized population
weight. To adjust the standard error
estimates for the complex design of the
survey, bootstrap techniques were used
in the regression analyses.25
Measures
Although clinical information was not
available, and questions about asthma
severity were not specifically asked, the
NLSCY collected data that can serve as
proxies for severity:26 past-year wheezing
or whistling in the chest and regular use
of inhalers. Three levels of severity were
identified: low, moderate and severe
(Appendix Table A).
Questions about socio-demographic
characteristics, child health, school
absences, and use of educational services
were answered by the person most
knowledgeable about the child (the
biological mother in 92% of cases) in
computer-assisted personal interviews.
Math and reading scores were based
on standardized tests administered in the
classroom with parental consent; these
scores were available for only a subset of
children.24
Analyses
Descriptive analyses were conducted
by asthma severity for three measures
of school performance: scores on
standardized math tests and reading
tests and maternal raatings of the child’s
scholastic functioning. Comparisons
were made with children with no chronic
conditions and children who had chronic
conditions other than asthma.
Logistic regression was used
to
“validate”
the
survey-based
categorization of asthma severity.
Associations between asthma severity
and maternal reports of child health
(excellent/very good versus good/fair/
poor) and activity limitations (yes/no)
were compared with results for children
without chronic conditions.
These
analyses revealed associations between
asthma severity and other ratings of
child health, thereby providing some
validation for the categorization of
asthma severity. Associations between
asthma severity and school absence and
the use of educational services were also
examined.
Logistic regressions were then used
to assess associations between asthma
severity and scores on standardized math
and reading tests and maternal ratings
of school performance, controlling for
child age and sex, maternal age, female
family headship, maternal education,
and household income.2,27,28
In final
regression models, school absences and
the use of educational services were
examined as mediating factors in the
relationship between asthma severity and
scholastic outcomes.
The sample sizes for the logistic
regression
models
examining
associations between asthma severity
and math scores were: 4,742 (sociodemographic variables only); 4,616
(school absence included); and 4,739
(use of educational services included).
The corresponding sample sizes for the
reading scores model were 4,744, 4,418
and 4,615, and for the mother-rated
school performance model, 8,723, 8,380
and 8,377.
Results
The sample
The characteristics of children varied
depending on whether they had
been diagnosed with asthma or other
chronic conditions. Significantly high
percentages of children with asthma
or other chronic conditions were male,
lived in mother-headed households, had
poor health, had missed at least 7 days
of school, and had received educational
services (Table 1). Children who did not
have a chronic condition were slightly
younger than those with a condition
other than asthma, but not significantly
different in age from children with
asthma. Children with severe asthma
tended to have younger mothers than did
other children.
Health status and activity
limitations
As might be expected, the odds of
less favourable health ratings were
significantly high among children with
asthma, even when other factors that
could potentially be associated with
health status were taken into account
(Table 2).
As well, a gradient was
evident, with the odds of poor health
increasing with asthma severity. For
instance, children with the least severe
asthma had twice the odds of poor health,
compared with children without chronic
conditions; for children with the most
severe asthma, the odds of poor health
were almost ten times higher. Children
with a chronic condition other than
asthma also had significantly high odds
of poor health.
Similarly, children with asthma were
more likely to have activity limitations,
and the odds of activity limitations rose
with asthma severity. Children with the
least severe asthma had about three and a
half times the odds of activity limitations,
compared with those who had no chronic
conditions; for children with the most
severe asthma, the odds were more than
twenty-two times higher. Children with
a chronic condition other than asthma
were also more likely to have activity
limitations.
These associations between asthma
severity and poor health and activity
limitations are not surprising, but the
gradients do support the categorization
of asthma severity in this analysis.
Statistics Canada, Catalogue no. 82-003-XPE • Health Reports, Vol. 21, no. 4, December 2010
37
Asthma and school functioning • Research article
Table 1
Characteristics of sample, household population aged 7 to 15 with complete data on measures of school functioning,
1998/1999 National Longitudinal Survey of Children and Youth
Asthma
No asthma, but
other chronic
Severe
condition
Characteristic
Total
No chronic
condition
Total number
8,914
5,626
513
438
482
1,855
10.8 (2.6)
49.6
10.7 (2.7)‡
52.4
11.0 (2.6)
43.1
10.8 (2.6)
41.8
10.8 (2.5)
42.3
11.1 (2.6)§
47.1
F = 7.80*
2= 176.18*
38.5 (5.53)
15.3
38.5 (5.5)‡
14.6
38.3 (5.3)‡
16.8
38.6 (5.3)
17.0
38.0 (5.4)§
17.4
38.9 (5.7)‡
16.2
F = 5.74*
2= 38.84*
13.1
19.9
28.4
38.6
6.6
18.7
3.66 (0.96)
13.4
21.1
27.7
37.8
6.6
18.8
3.66 (0.96)
13.1
17.4
29.8
39.8
7.5
20.1
3.65 (0.96)
11.4
17.1
29.5
42.0
8.1
17.9
3.68 (0.94)
11.8
17.4
32.0
32.8
4.6
19.9
3.59 (0.98)
13.0
18.3
28.8
39.9
6.4
18.0
3.67 (0.94)
2=100.68*
Child health
Health status
Excellent (%)
Very good (%)
Good/Fair/Poor (%)
Chronic condition (%)
53.4
33.0
13.6
29.7
62.5
29.8
7.8
0.0
44.3
41.9
13.8
39.6
32.0
46.0
22.2
58.2
13.7
42.1
44.2
69.7
43.8
35.0
21.1
100.0
2=1543.27*
School functioning
Days absent (%)
0
1 to 3
4 to 6
7 or more
Use of educational services (%)
39.0
46.0
9.6
5.5
6.6
41.8
44.9
9.0
4.3
2.6
37.6
47.6
9.2
5.7
6.3
30.6
53.9
10.3
5.3
9.1
28.0
50.6
12.2
9.1
11.2
35.4
45.7
10.8
8.1
17.0
2=268.94*
Child
Mean age† (standard deviation)
Female (%)
Family
Mean maternal age† (standard deviation)
Female-headed (%)
Maternal education
Less than secondary graduation (%)
Secondary graduation (%)
Some postsecondary (%)
Postsecondary graduation (%)
Mother not currently employed (%)
Mother not employed prior year (%)
Income adequacy
Low
Moderate
Statistical
comparison
2=5.25
2=7.57
F=0.58
2=1164.24*
* p < 0.05; significantly different categories for continuous variables have different superscripted symbols
†
continuous variable
Source: 1998/1999 National Longitudinal Survey of Children and Youth.
Math and reading scores/
Maternal ratings
Scores on standardized math and reading
tests and maternal ratings of children’s
school performance were related to
family structure, maternal education
and employment, and household income
(Tables 3 to 5, column 1). But even when
the influence of these factors was taken
into account, differences in standardized
scores and maternal ratings emerged by
asthma severity.
The odds of low math scores were
significantly high for children with
moderate or severe asthma, compared
with children who had no chronic
conditions. The odds of low reading
scores were significantly high only for
children with moderate asthma. And the
odds that mothers would rate their child’s
school performance as poor were high for
children whose asthma symptoms were
low or severe, but did not reach statistical
significance for the moderate group.
Children with other chronic conditions
were also more likely to have low math
and reading scores and poor maternal
ratings of their school performance,
compared with children who did not have
chronic conditions.
School absence and use of
educational services
Children with asthma were significantly
more likely than those with no chronic
conditions to have been absent from
school and to have used educational
services (Table 2). This was also the
case for children with chronic conditions
other than asthma.
Additional models examined the
effects of these potential mediators—
school absence and use of educational
services—on the associations between
the three measures of school functioning
and asthma and other chronic conditions.
Being away from school was
linearly associated with low scores on
standardized math tests. That is, the
children who missed the most days (a
week or more) had about two and a half
times the odds of low scores, compared
with children who missed no days (Table
3, column 2). However, controlling
for school absence did not appreciably
diminish the odds of low math scores
38
Health Reports, Vol. 21, no. 4, December 2010 • Statistics Canada, Catalogue no. 82-003-XPE
Asthma and school functioning • Research article
Table 2
Odds ratios relating selected characteristics to poor health status, activity limitations, school absence and educational
services , household population aged 7 to 15, Canada, 1998/1999
Poor health status
(n=8,723)
Characteristic
Odds
ratio
95%
confidence
interval
from
to
Activity limitations
(n=8,722)
Odds
ratio
School absence
more than one week§
(n=8,380)
95%
confidence
interval
from
to
Odds
ratio
95%
confidence
interval
from
to
Use of educational
services
(n=8,377)
Odds
ratio
95%
confidence
interval
from
to
Child
Age (continuous)
Female†
1.02
1.32*
1.00 1.04
1.20 1.45
1.05*
1.32*
1.02 1.08
1.15 1.52
1.15*
1.26*
1.12 1.19
1.09 1.46
1.00
0.72*
1.00 1.02
0.63 0.82
Family
Older maternal age†
Female-headed†
Higher maternal education†
Mother not currently employed†
Mother not employed prior year†
Higher income adequacy†
1.03*
0.88
0.84*
1.08
1.22*
0.73*
1.02
0.77
0.80
0.88
1.08
0.69
1.03
1.00
0.88
1.34
1.37
0.78
1.00
0.95
0.87*
1.11
1.02
0.95
0.99
0.78
0.81
0.82
0.84
0.87
1.01
1.16
0.97
1.52
1.23
1.03
0.99
1.40*
0.81*
1.06
1.31*
0.88*
0.98
1.15
0.76
0.76
1.08
0.80
1.01
1.71
0.88
1.49
1.59
0.96
0.98*
1.77*
0.85*
0.96
1.28*
0.92
0.97
1.50
0.79
0.72
1.08
0.85
1.00
2.09
0.90
1.29
1.51
1.00
…
…
…
…
…
…
…
…
1.55
1.14
2.74
1.72
2.67
2.21
4.55
2.43
Chronic condition
None‡
Asthma
Low
Moderate
Severe
Other
1.00
1.98*
3.42*
9.46*
2.92*
1.64 2.39
2.85 4.11
8.06 11.10
2.61 3.26
1.00
3.49* 2.56 4.75
6.61* 4.97 8.78
21.55* 17.22 26.97
8.81* 7.32 10.60
1.00
2.03*
1.59*
3.53*
2.05*
1.00
2.64*
4.08*
5.38*
8.85*
2.00 3.49
3.13 5.32
4.21 6.88
7.58 10.34
* significantly different from estimate for reference category (p < 0.05)
†
reference category is absence of characteristic
‡
reference category
§
interview date included as a control
... not applicable
Notes: All models control for province of residence. Because of rounding, an odds ratio with 1.00 as upper confidence limit is significant.
Source: 1998/1999 National Longitudinal Survey of Children and Youth.
among children with asthma or with
other chronic conditions.
Children who used educational
services were much more likely than
those who had not to obtain low math
scores (Table 3, column 3). Controlling
for the use of educational services
reduced the strength of the association
between moderate asthma and low math
scores, and for children with severe
asthma, the association was no longer
significant.
Unlike the results for math, school
absence was not related to low scores
on the standardized reading tests (Table
4, column 2). Moreover, including
school absence in the model actually
strengthened the association between
moderate and severe asthma and low
reading scores, suggesting the presence
of a suppressor effect or a correlation
between school absence and a variable
that was not examined in this analysis.
The use of educational services,
however, was associated with low
reading scores (Table 4, column 3).
Controlling for the use of educational
services reduced the odds that children
with moderate asthma would have low
reading scores, and for those with severe
asthma, the association was no longer
significant.
School absence was related to
poor maternal ratings of academic
performance only for children who
missed the fewest days (no more than 3)
(Table 5, column 2). As well, controlling
for days absent had almost no effect on
the relationship between asthma and poor
mother-reported school performance.
On the other hand, the use of
educational services was associated with
poor maternal ratings (Table 5, column
3). And when the use of educational
services was taken into account, the
strength of the association between
asthma and poor maternal ratings was
reduced.
Discussion
The estimates of asthma and asthma
severity in this study differ from those
derived from other contemporary
sources. According to the 1998/1999
NLSCY, 16% of school-aged children
had been diagnosed with asthma, well
above the estimated 12%, based on the
1996/1997 National Population Health
Survey (NPHS).29 However, the NPHS
figure includes children younger than age
4, and the low prevalence of asthma (8%)
at these ages would reduce the overall
prevalence rate.
In this study, about one-third of the
children who had asthma were classified
in the most severe category, whereas
in Bussing et al.,20 the figure was just
over 18%. But Bussing et al. looked at
Statistics Canada, Catalogue no. 82-003-XPE • Health Reports, Vol. 21, no. 4, December 2010
39
Asthma and school functioning • Research article
Table 3
Adjusted odds ratios relating selected characteristics to low scores on standardized math tests, household population
aged 7 to 15, Canada, 1998/1999
Adjusted for sociodemographics and chronic
conditions
(n=4,742)
Characteristic
Odds
ratio
95%
confidence
interval
Adjusted for sociodemographics, school
absences and chronic
conditions
(n=4,616)
from
to
Odds
ratio
Adjusted for sociodemographics, use of
educational services
and chronic conditions
(n=4,739)
95%
confidence
interval
from
to
Odds
ratio
95%
confidence
interval
from
to
Child
Age (continuous)
Female†
1.01
1.06
0.98
0.90
1.05
1.26
1.01
1.02
0.97
0.86
1.05
1.21
1.01
1.02
0.99
0.99
1.02
1.06
Family
Older maternal age†
Female-headed†
Higher maternal education†
Mother not currently employed†
Mother not employed prior year†
Higher Income adequacy†
0.98*
1.91*
0.81*
0.74
1.53*
0.86*
0.97
1.53
0.75
0.49
1.24
0.80
1.00
2.37
0.88
1.12
1.88
0.96
0.98*
1.91*
0.81*
0.72
1.59*
0.88*
0.96
1.52
0.79
0.47
1.28
0.79
1.00
2.40
0.98
1.11
1.97
0.98
0.98
1.84*
0.82*
0.71
1.63*
0.92
0.97
1.46
0.75
0.46
1.31
0.82
1.00
2.32
0.90
1.09
2.04
1.02
…
1.28
1.52
1.71
…
1.93
2.75
3.41
…
…
…
…
…
…
…
…
…
…
…
…
3.72
6.17
…
…
0.89
1.13
1.00
1.10
1.74
2.30
1.98
1.70
Days absent
0‡
1 to 3
4 to 6
7 or more
…
…
…
…
…
…
…
…
…
…
…
…
1.00
1.57*
2.05*
2.41*
Use of educational services†
…
…
…
…
…
…
4.79*
1.00
…
…
1.00
…
…
1.00
1.00
1.34
1.17
1.43
1.92
2.68
2.25
2.14
0.98
1.30
1.14
1.40
1.90
2.62
2.22
2.11
Chronic condition
None‡
Asthma
Low
Moderate
Severe
Other
1.39
1.90*
1.62*
1.75*
1.36
1.84*
1.59*
1.72*
1.24
1.61*
1.41
1.37*
* significantly different from estimate for reference category (p < 0.05)
†
reference category is absence of characteristic
‡
reference category
§
interview date included as a control
... not applicable
Notes: All models control for province of residence. Because of rounding, some odds ratios with 1.00 as upper confidence limit are significant.
Source: 1998/1999 National Longitudinal Survey of Children and Youth.
severity among children who had only
asthma, whereas children with asthma
in the present study may also have had
other chronic conditions.
The association between asthma
severity and school absence observed in
this study has been found in other research,
based on school administrative records5-10
and on maternal reports.3,4 However, in
the literature, the relationship between
school absence and school performance
is less clear. The NLSCY results suggest
that the associations between asthma and
poor school performance are not due to
absences.
On the other hand, the use of
educational services seemed to mediate
some of these associations, particularly
for children with severe asthma.
Unfortunately, with NLSCY data, it was
not possible to determine what kind or
how many services were used or where
they were offered.
The variations in research findings
may be related to the specific outcomes
examined and to whether asthma severity
was taken into account. Fowler et al.17
found that children with asthma had more
mother-reported learning difficulties than
did healthy children, but according to
school records, no more grade failure or
suspension/expulsion. Similarly, other
studies have not reported differences
between children with asthma and their
healthy peers on standardized tests of
math, reading and overall performance,6
though based on maternal reports,
outcomes for children with asthma have
been less favourable.
Thus, the NLSCY results are
consistent with the literature for poor
mother-reported school performance,
but not for scores on standardized math
and reading tests. However, the present
study, unlike many others,8,23,30 includes
40
Health Reports, Vol. 21, no. 4, December 2010 • Statistics Canada, Catalogue no. 82-003-XPE
Asthma and school functioning • Research article
Table 4
Adjusted odds ratios relating selected characteristics to low scores on standardized reading tests, household population
aged 7 to 15, Canada, 1998/1999
Adjusted for sociodemographics and chronic
conditions
(n=4,744)
Characteristic
Odds
ratio
95%
confidence
interval
from
to
Adjusted for sociodemographics, school
absences and chronic
conditions
(n=4,618)
Odds
ratio
Adjusted for sociodemographics, use of
educational services
and chronic conditions
(n=4,615)
95%
confidence
interval
from
to
Odds
ratio
95%
confidence
interval
from
to
Child
Age (continuous)
Female†
1.07*
0.90
1.04
0.78
1.11
1.04
1.07*
0.91
1.04
0.78
1.11
1.06
1.08*
0.95
1.04
0.81
1.11
1.10
Family
Older maternal age†
Female-headed†
Higher maternal education†
Mother not currently employed†
Mother not employed prior year†
Higher Income adequacy†
0.99
1.27*
0.78*
0.76
1.04
0.71*
0.97
1.05
0.72
0.54
0.86
0.65
1.00
1.55
0.84
1.08
1.26
0.77
0.99
1.34*
0.76*
0.78
1.09
0.71*
0.97
1.09
0.71
0.55
0.89
0.64
1.00
1.64
0.82
1.10
1.32
0.77
0.99
1.26*
0.77*
0.75
1.05
0.71*
0.97
1.03
0.71
0.53
0.86
0.65
1.00
1.55
0.83
1.06
1.27
0.78
...
...
...
...
...
...
...
...
...
...
...
...
2.16
3.52
…
…
0.56
1.17
0.85
1.12
1.09
2.15
1.60
1.62
Days absent
0‡
1 to 3
4 to 6
7 or more
...
...
...
...
...
...
...
...
...
...
...
...
...
0.97
1.14
0.90
...
0.82
0.88
0.63
...
1.14
1.49
1.28
Use of educational services†
...
...
...
...
...
...
2.76*
1.00
…
…
1.00
…
…
1.00
0.59
1.28
0.91
1.27
1.15
2.32
1.67
1.81
0.62
1.36
1.00
1.31
1.20
2.46
1.86
1.88
Chronic condition
None‡
Asthma
Low
Moderate
Severe
Other
0.82
1.73*
1.23
1.52*
0.86
1.83*
1.36*
1.57*
0.78
1.59*
1.17
1.35*
* significantly different from estimate for reference category (p < 0.05)
†
reference category is absence of characteristic
‡
reference category
§
interview date included as a control
... not applicable
Note: All models control for province of residence.
Source: 1998/1999 National Longitudinal Survey of Children and Youth.
a control group of children with and
without chronic conditions and uses a
large population-based sample.
According to the NLSCY, most
children, even those with severe asthma,
had not been absent from school for
many days: 96% of healthy children
and 91% of children with severe asthma
were reported to have missed fewer
than 7 days. By contrast, Fowler et al,17
found that just 58% of children with
asthma missed no more than 5 days of
school, substantially below the figure
even for children with severe asthma in
the present study. Although the models
for the NLSCY analysis controlled for
the number of days since school started,
many interviews were completed early
in the school year, which could be one
reason why reported school absence was
so low.
Consistent with other findings,23 school
absence was independently associated
with low scores on standardized math
tests. However, school absence did not
mediate the association between asthma
severity and math and reading scores
and mother-rated performance. Even
though children with asthma were more
likely to miss school, it is possible that
they and/or their parents compensated for
the absences, perhaps through additional
services within and outside the school.
Future studies could examine these
possibilities, as well as factors such as
parenting practices and the provision of
learning experiences in the home.
The worsening of health outcomes
with asthma severity suggests that the
conceptualization of asthma severity in
this study captured a construct related to
the child’s health. Associations between
asthma severity and school performance
were less straightforward. Potential
confounders such as maternal education,
family structure and household income
were taken into account, but other factors
related to school performance could not
Statistics Canada, Catalogue no. 82-003-XPE • Health Reports, Vol. 21, no. 4, December 2010
41
Asthma and school functioning • Research article
Table 5
Adjusted odds ratios relating selected characteristics to poor mother-rated school performance, household population
aged 7 to 15, Canada, 1998/1999
Adjusted for sociodemographics and chronic
conditions
(n=4,742)
Characteristics
Odds
ratio
95%
confidence
interval
from
to
Adjusted for sociodemographics, school
absences and chronic
conditions
(n=4,616)
Odds
ratio
Adjusted for sociodemographics, use of
educational services
and chronic conditions
(n=4,739)
95%
confidence
interval
from
to
Odds
ratio
95%
confidence
interval
from
to
Child
Age (continuous)
Female†
0.60*
0.71*
0.59
0.66
0.62
0.77
0.60*
0.71*
0.59
0.65
0.61
0.77
0.60*
0.73*
0.58
0.67
0.61
0.80
Family
Older maternal age†
Female-headed†
Higher maternal education†
Mother not currently employed†
Mother not employed prior year†
Higher Income adequacy†
0.99
1.28*
0.82*
0.98
1.01
0.92*
0.99 1.00
1.13 1.44
0.78 0.85
0.82 1.62
0.91 1.13
0.88 0.97*
0.99*
1.31*
0.82*
0.99
1.05
0.93*
0.98
1.16
0.78
0.83
0.94
0.88
1.00
1.48
0.85
1.18
1.18
0.98
0.99*
1.24*
0.82*
0.98
1.03
0.94*
0.98
1.09
0.79
0.82
0.92
0.89
1.00
1.40
0.86
1.18
1.15
0.99
...
1.05
0.95
0.90
...
1.26
1.29
1.38
...
...
...
...
...
...
...
...
...
...
...
...
2.72
3.70
…
…
1.34
0.90
1.17
1.13
1.88
1.32
1.69
1.41
Days absent
0‡
1 to 3
4 to 6
7 or more
...
...
...
...
...
...
...
...
...
...
...
...
...
1.15*
1.11
1.12
Use of educational services†
...
...
...
...
...
...
3.12*
1.00
…
…
1.00
…
…
1.00
1.35
0.96
1.32
1.40
1.88
1.40
1.88
1.72
1.38
0.95
1.29
1.40
1.93
1.39
1.89
1.73
Chronic condition
None‡
Asthma
Low
Moderate
Severe
Other
1.60*
1.16
1.57*
1.55*
1.63*
1.15
1.55*
1.56*
1.59*
1.09
1.41*
1.27*
* significantly different from estimate for reference category (p < 0.05)
†
reference category is absence of characteristic
‡
reference category
§
interview date included as a control
... not applicable
Notes: All models control for province of residence. Because of rounding, some odds ratios with 1.00 as upper confidence limit are significant.
Source: 1998/1999 National Longitudinal Survey of Children and Youth.
be considered: the child’s prior levels of
performance, motivation, intelligence,
and behavioural problems; parenting
practices; resources and learning
environments; and parental participation
in school activities.31-34
Strengths and limitations
Although
the
analysis
pertains
to 1998/1999, the data source is
undoubtedly a strength of the current
study. Cycle 3 of the NLSCY collected
data for a large, representative sample of
children with various health conditions,
thereby making it possible to compare
those with asthma with healthy children
and with children who had other chronic
conditions. Standardized test results
and mother-reported measures of school
performance were available.
Even so, the NLSCY is limited in a
number of ways. It was not designed
to specifically address chronic illnesses
and their association with children’s
school performance. The identification
of children with asthma was based
on maternal reports, not medical
records.
Although parental reports
of children’s chronic conditions have
been demonstrated to be valid,35 the
reported prevalence of asthma may be
underestimated as a result of undiagnosed
cases.
The ability to generate classes of
individuals with similar conditions
(asthma of varying levels of severity with
and without other chronic conditions) is
limited. Guidelines for more rigorous
methods of severity classification exist,36
but they were not part of the NLSCY.
The three levels of asthma severity
specified in this study are not
homogeneous, and likely represent
differences in asthma other than just
severity. For example, to be in the
42
Health Reports, Vol. 21, no. 4, December 2010 • Statistics Canada, Catalogue no. 82-003-XPE
Asthma and school functioning • Research article
What is already
known on this
subject?
■ The prevalence of asthma among
Canadian children and youth has
been increasing.
■ Children with asthma miss more
school than do children without the
condition.
■ Frequent school absences can
interfere with learning, but the impact
of asthma on school performance is
relatively unexplored, and the results
of the analyses that have been
conducted are inconclusive.
What does this study
add?
■ Children with asthma scored lower
on standardized math and reading
tests and had less favourable
mother-reported school performance
than did children who did not have
chronic conditions.
■ Children with the most severe
asthma had the poorest outcomes.
■ These associations persisted even
when adjusting for child and family
factors.
■ The poorer scholastic outcomes
were not mediated by school
absences, but the use of educational
services appeared to mediate low
math scores for children with severe
asthma.
“severe” category, children had to be
taking asthma medication, but still
coughing or wheezing. This may not
indicate the most severe asthma, but
rather, that the children are not responding
to the medication, are not receiving the
appropriate dosage, or are not complying
with the administration of the medication.
Nevertheless, the consistency of the
associations with ratings of health and
with activity limitations suggests that the
conceptualization of asthma severity in
this study represents an aspect of poor
health.
A high percentage of children with
asthma, especially severe asthma (70%),
had another chronic condition. The
NLSCY sample for this group was
not large enough to permit an in-depth
investigation of the other conditions
affecting the children with asthma nor of
asthmatic children by severity.
Another factor to be considered is the
reported use of asthma medication. The
NLSCY question asks about inhalers.
However, asthma treatment includes
relievers (inhalers and puffers) and
controllers (oral medication when a
child becomes symptomatic).3 Detailed
information about the use of these
medications was not available in the
NLSCY.
A further complication is the uncertain
effect of the medications on school
performance. Taking medication may
reduce and control symptoms and improve
school performance. On the other hand,
side-effects such as drowsiness and
decreased attention, could interfere
with academic attainment.9,37 Further
research is required to disentangle these
associations.
A final limitation is the high nonresponse to the standardized math and
reading tests.24 Complete data on these
measures were more likely to be available
for children with asthma than for those
who did not have the condition. Attrition
analyses were performed to compare the
group that had math and reading scores
with the group that did not (Appendix
Table B).
Conclusion
With data from Statistics Canada’s
National Longitudinal Survey of
Children and Youth, this study examined
associations between asthma severity and
three measures of school performance.
Compared with children who did not
have chronic conditions, those with
asthma tended to perform less well, and
those with the most severe asthma had
the poorest outcomes. Children with the
most severe asthma had the greatest odds
of missing more than a week of school,
but their low scores on standardized
math and reading tests and poor motherrated academic performance were not
mediated by school absences. The use of
educational services, however, appeared
to mediate the associations.
The increased risk of poor scholastic
outcomes for children with asthma
(and other chronic conditions) has
implications for clinicians, teachers,
and parents. The results suggest the
importance of additional assistance such
as educational services to improve the
school performance of children with
asthma. ■
Statistics Canada, Catalogue no. 82-003-XPE • Health Reports, Vol. 21, no. 4, December 2010
Asthma and school functioning • Research article
43
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44
Health Reports, Vol. 21, no. 4, December 2010 • Statistics Canada, Catalogue no. 82-003-XPE
Asthma and school functioning • Research article
Appendix
Table A
Measures used in analyses
Variable
Description
Province of residence
Ontario as comparison group
Child characteristics
Age
Gender
Years
Female
Maternal characteristics
Age
Education
Currently employed
Employed prior year
Income adequacy
Years
Highest level: less than secondary graduation; secondary graduation; some postsecondary; postsecondary graduation
Yes/No
Yes/No
Based on household income and household size; range 1 to 5
Child health
Asthma
Asthma severity
Low
Moderate
Severe
Chronic condition
No chronic condition
Health status
Activity limitations
School functioning
School absence
Use of educational services
Standardized math and reading tests
Maternal rating of school performance
†
‡
§
Maternal report of ever having been diagnosed with asthma†
Based on two items: child had wheezing or whistling in chest any time in previous 12 months; prescribed and regular use of
Ventolin, inhalants or puffers for asthma
Diagnosed asthma, but no wheezing or whistling and no use of medication
Diagnosed asthma with reported wheezing or whistling OR use of medication
Diagnosed asthma with reported wheezing or whistling AND use of medication
Presence of any of following: allergies, bronchitis, heart condition, epilepsy, cerebral palsy, kidney, mental handicap, learning
disability, emotional problems
No diagnosis of asthma or other chronic condition
Maternal rating of child's health as excellent/very good or good/fair/poor
Long-term conditions or health problems that prevent or limit participation in school, play or sports (yes/no)
Maternal report of number of school days absent for any reason: 0, 1 to 3, 4 to 6, 7 or more‡
Maternal report of receipt of special help because of physical, emotional, behavioural or other problem limiting kind or amount
of school work child can do (yes/no)
Shortened version of Mathematics Computation Test and Reading Comprehension Test of Canadian Achievement Tests
(CAT/2): good/low§
Maternal rating of child's performance in math, reading, writing and overall; range 4 to 20; dichotomized into good/poor
phrasing of this item, consistent with other large studies, limits variability because of seasonality of child age
number of days missed since start of school; analyses controlled for month and day of survey administration
because of ceiling effects on these tests, scores were dichotomized; scores above mean categorized as good, and scores below mean categorized as low
Statistics Canada, Catalogue no. 82-003-XPE • Health Reports, Vol. 21, no. 4, December 2010
Asthma and school functioning • Research article
Table B
Odd ratios comparing characteristics of respondents with
math and reading scores with characteristics of those
who did not, household population aged 7 to 15, Canada,
1998/1999
Characteristic
Odds
ratio
95%
confidence
interval
from
to
Province
Ontario†
Newfoundland
Prince Edward Island
Nova Scotia
New Brunswick
Quebec
Manitoba
Saskatchewan
Alberta
British Columbia
1.00
0.68*
0.47*
0.42*
0.48*
1.17*
0.75*
0.77*
0.79*
0.82*
…
0.53
0.28
0.34
0.38
1.07
0.63
0.64
0.70
0.73
…
0.88
0.78
0.53
0.61
1.29
0.91
0.92
0.90
0.92
Child
Age (continuous)
Female‡
1.03*
0.85*
1.01
0.79
1.05
0.91
Family
Older maternal age‡
Female-headed‡
Higher maternal education‡
Mother not currently employed‡
Mother not employed prior year‡
Higher Income adequacy‡
1.00
1.18*
0.98
0.82*
0.95
0.95
0.99
1.06
0.94
0.70
0.86
0.90
1.00
1.13
1.01
0.96
1.04
0.99
…
…
0.71
0.71
0.62
0.91
0.95
0.83
Chronic condition
None†
Asthma
Low
Moderate
Severe
1.00
0.80*
0.82*
0.72*
* significantly different from estimate for reference category (p < 0.05)
†
reference category
‡
reference category is absence of characteristic
§
interview date included as a control
... not applicable
Source: 1998/1999 National Longitudinal Survey of Children and Youth.
45
E L E C T R O N I C P U B L I C AT I O N S
AVA I L A B L E AT
w w w. s t a t c a n . g c . c a
Statistics Canada, Catalogue no. 82-003-XPE • Health Reports, Vol. 21, no. 4, December 2010
Recent trends in upper respiratory infections, ear infections and asthma among young Canadian children • Health matters
47
Recent trends in upper respiratory
infections, ear infections and asthma
among young Canadian children
by Eleanor M. Thomas
Abstract
Upper respiratory (nose and throat) infections, ear
infections and asthma are common among young
children. This article uses data from the National
Longitudinal Survey of Children and Youth
(NLSCY) to trace trends in the prevalence of
these conditions among young children in Canada
from 1994/1995 to 2008/2009. Gender, age and
regional differences in the occurrence of these
conditions are examined, and possible links with
exposure to cigarette smoke are considered. The
prevalence of upper respiratory infections among
children aged 2 to 3 remained constant or declined
in most regions of Canada between 1994/1995
and 2008/2009, but rose significantly in Quebec.
Ear infections declined significantly in all regions.
The prevalence of asthma among children aged
2 to 7 rose steadily until 2000/2001 and then
declined. A wide range of environmental factors,
including reduced exposure to cigarette smoke,
may have contributed to these trends.
Keywords
common cold, ear diseases, otitis media, passive
smoking, respiratory diseases, respiratory sounds
Author
Eleanor M. Thomas (1-613-951-3002;
[email protected]) is with the
Special Surveys Division at Statistics Canada,
Ottawa, Ontario, K1A 0T6.
U
pper respiratory (nose and throat) infections,
otitis media (ear infection and inflammation)
and asthma affect large numbers of young children.1-5
This article uses data from the National Longitudinal
Survey of Children and Youth (NLSCY) to
report trends from 1994/1995 to 2008/2009 in the
prevalence of these conditions among children in
Canada. Data on upper respiratory infections and
ear infections are available for 2- to 3-year-olds,
and data on asthma are available for children aged
2 to 7. Gender, age and regional differences in
the occurrence of these conditions are examined.
Possible links with exposure to cigarette smoke are
considered.
Upper respiratory infections
Upper respiratory infections, including
the common cold, are frequent among
children, with 3 to 8 infections a year
being typical.6 In 1994/1995, 26% of
Canadian children aged 2 to 3 years were
reported by their parents as having upper
respiratory infections “almost all the
time,” “often,” or “from time to time”
(Table 1). This percentage remained
almost stable over the next 14 years: the
2008/2009 figure was 23%.
In 1994/1995, boys were more
likely than girls to have frequent upper
respiratory infections: 29% versus 23%.
Thereafter, no male-female differences
were apparent, because among boys (but
not girls), the prevalence of frequent
infections decreased.
Throughout
the
1994/1995-to2008/2009 period, the prevalence of
frequent upper respiratory infections
among 2- to 3-year-olds was lowest in
the Atlantic provinces (Newfoundland
and Labrador, Prince Edward Island,
Nova Scotia, and New Brunswick), and
highest in Quebec.
48
Health Reports, Vol. 21, no. 4, December 2010 • Statistics Canada, Catalogue no. 82-003-XPE
Recent trends in upper respiratory infections, ear infections and asthma among young Canadian children • Health matters
Table 1
Prevalence of “frequent” (almost all the time/often/from time to time) upper
respiratory infections, by sex and region, household population aged 2 to 3,
Canada excluding territories and Nunavut, 1994/1995 to 2008/2009
1994/1995
Total
Sex
Male
Female†
Region
Atlantic provinces
Quebec†
Ontario
Prairie provinces
British Columbia
2000/2001
%
2006/2007
2008/2009
Comparison
between 1994/1995
and 2008/2009
(p-value)
24.4
23.5
0.141
25.8
25.9
28.7*
22.7
26.7
25.0
24.2
24.6
23.1
24.0
0.010
0.571
20.3
28.0
26.4
24.3
25.1
18.8*
36.8‡
22.1*
22.4*
27.8*
17.6*
41.1
19.7*
17.0*‡
25.6*
16.8*
38.9
19.5*
19.3*
18.4*‡
0.153
0.003
0.013
0.052
0.081
(p<0.001). Similarly, the percentage of
boys who had had frequent ear infections
dropped from 30% to 14%; among girls,
the decline was from 23% to 11%.
The Atlantic provinces and Quebec
tended to have high ear infection rates,
while in British Columbia, the rates
tended to be low (Table 2). In all
regions except Quebec, the prevalence
of ear infections fell since 1994/1995.
These variations may be linked to
regional differences in upper respiratory
infections, which increase the risk of ear
infections.3,4
In fact, significant links were found
between upper respiratory infections
and ear infections in each of the four
survey cycles (Figure 1). For example,
in 1994/1995, 44% of children aged
2 to 3 with frequent upper respiratory
infections were also reported to have
had frequent ear infections since birth;
this compared with 20% of children who
rarely or never had upper respiratory
infections (p<0.001). In 2008/2009, the
prevalence of frequent ear infections
was lower among both groups, but the
difference between those who did and did
not experience frequent upper respiratory
infections remained significant, at 24%
versus 9% (p<0.001).
†
reference category
* significantly different from estimate for reference category (p<0.05)
‡
significantly different from estimate for previous survey cycle (p<0.05)
Source: 1994/1995 to 2008/2009 National Longitudinal Survey of Children and Youth.
In all provinces except Quebec, the
prevalence of frequent upper respiratory
infections declined over the 14 years. In
Ontario, the percentage fell from 26%
to 20%, and in the Prairie provinces
(Manitoba, Saskatchewan and Alberta),
from 24% to 19%. Declines in the
Atlantic provinces and British Columbia
did not reach statistical significance. By
contrast, in Quebec, the percentage rose
from 28% to 39%.
The significant increase in frequent
upper respiratory infections in Quebec
could partly reflect changes in child care
funding in that province in 1997, which
resulted in a substantial increase in the
percentage of Quebec children in daycare
centres.7 Children in these settings have
an increased risk of contracting colds and
other infectious conditions, compared
with children who are not in such
centres.6,8,9
Otitis media
Otitis media (middle-ear infection
or inflammation) is also common in
childhood.1,10 In 1994/1995, 67% of
Canadian children aged 2 to 3 years had
had at least one ear infection since birth
(Table 2). The percentage with frequent
(four or more) ear infections was 26%.
However, by 2008/2009, the percentage
who had had at least one ear infection
had dropped to 50%, and the percentage
who had had four or more had fallen to
13%.
Boys were more likely than girls to have
had at least one (data not shown) or four
or more ear infections (Table 2). From
1994/1995 to 2008/2009, the prevalence
of at least one ear infection among boys
declined from 70% to 53% (p<0.001),
and among girls, from 64% to 47%
Table 2
Prevalence of ear infections, by sex and region, household population aged 2 to
3, Canada excluding territories and Nunavut, 1994/1995 to 2008/2009
1994/1995
2000/2001
2008/2009
Comparison
between 1994/1995
and 2008/2009
(p-value)
51.5‡
50.2
<0.001
14.2‡
12.6
<0.001
2006/2007
%
At least one ear infection
66.9
62.6‡
Frequent ear infections
26.3
19.8
29.9*
22.5
21.2‡
18.2‡
16.2*‡
12.1‡
14.2*
10.9
<0.001
<0.001
35.2*
24.4
25.3
27.4
25.8
22.6*‡
25.8*
19.7*‡
18.3*‡
9.6‡
17.3*‡
22.0*
12.3‡
11.5‡
9.2E
16.0*
18.4*§
11.5*
10.5
7.3E
<0.001
0.080
<0.001
<0.001
<0.001
Sex
Male
Female†
Region
Atlantic provinces
Quebec
Ontario
Prairie provinces
British Columbia†
‡
†
reference category
* significantly different from estimate for reference category (p<0.05)
‡
significantly different from estimate for previous survey cycle (p<0.05)
§
significantly different from estimate for 2000/2001 (p<0.05)
E
use with caution
Source: 1994/1995 to 2008/2009 National Longitudinal Survey of Children and Youth.
Statistics Canada, Catalogue no. 82-003-XPE • Health Reports, Vol. 21, no. 4, December 2010
Recent trends in upper respiratory infections, ear infections and asthma among young Canadian children • Health matters
Figure 1
Prevalence of frequent ear infections and of asthma among children aged 2
to 3, by frequency of upper respiratory infections (URIs), Canada excluding
territories and Nunavut, 1994/1995 to 2008/2009
Upper respiratory infections
Frequent
44
Not frequent
31
27
24
20
16
10
1994/1995
2000/2001
2006/2007
15
13
9
7
2008/2009
11
8
1994/1995
6
2000/2001
Frequent ear infections
2006/2007
11
6
2008/2009
Asthma
Note: “Frequent” upper respiratory infections occurred “almost all the time,” “often” or “from time to time.”
Source: 1994/1995 to 2008/2009 National Longitudinal Survey of Children and Youth.
Asthma
In Canada and many other western
countries, the prevalence of asthma
among children increased steadily for
several decades, and then levelled off
or even declined.11-14 Echoing trends in
an earlier report on Canadian children
aged 0 to 11,14 the present study found
that the percentage of children aged 2 to
7 who had been diagnosed with asthma
rose from 11% in 1994/1995 to 13% in
2000/2001, but by 2008/2009, had fallen
to 10% (Table 3).
Because the lifetime prevalence of
health conditions increases with age, it is
not surprising that at each NLSCY cycle,
a higher percentage of 6- to 7-year-olds
than 2- to 3-year-olds were reported to
have been diagnosed with asthma. For
example, in 2006/2007, 15% of children
Table 3
Prevalence of asthma, by sex, age and region, household population aged 2 to
7, Canada excluding territories and Nunavut, 1994/1995 to 2008/2009
1994/1995
Total
Sex
Male
Female†
Age
2 to 3
4 to 5
6 to 7†
Region
Atlantic provinces
Quebec
Ontario
Prairie provinces
British Columbia†
2000/2001
11.5
13.2‡
14.2*
8.7
2006/2007
%
2008/2009
Comparison
between 1994/1995
and 2008/2009
(p-value)
11.5‡
9.8‡§
0.008
16.2*‡
10.0
13.5*‡
9.4
11.4*‡§
7.9§
0.006
0.364
8.8*
11.6*
14.2
10.1*
13.5
15.7
7.6*‡
12.7
14.9
7.4*§
10.1‡§
12.4§
0.135
0.185
0.178
14.2*
11.2
12.1
10.3
10.2
15.2*
15.5*‡
13.7*
10.9
9.2
12.5‡
13.2
10.9‡
11.7
10.1
10.8*§
10.6§
9.8§
9.6‡
7.9
0.004
0.686
0.052
0.489
0.174
†
reference category
* significantly different from estimate for reference category (p<0.05)
‡
significantly different from estimate for previous survey cycle (p<0.05)
§
significantly different from estimate for 2000/2001 (p<0.05)
Source: 1994/1995 to 2008/2009 National Longitudinal Survey of Children and Youth.
49
The data
The data are from the National Longitudinal
Survey of Children and Youth (NLSCY), which
has been conducted every two years since
1994/1995. This report examines trends from
1994/1995 to 2008/2009 in the prevalence of
upper respiratory infections and otitis media
among children aged 2 to 3 years, and in the
prevalence of asthma among children aged 2
to 7 years.
The information used in this analysis was
provided to the NLSCY by the person most
knowledgeable about the child, usually the
mother. The prevalence of health conditions
was based on the parent’s response to the
following questions:
● Upper respiratory infections: How often
does this child have nose or throat
infections (almost all the time, often,
from time to time, rarely, or never)?
● Otitis media: Since birth, has this child
had an ear infection (otitis)? If yes, how
many times?
● Asthma and asthma symptoms: Has
this child ever had asthma that was
diagnosed by a health professional?
Has this child had an asthma attack
in the past 12 months? Has this child
had wheezing or whistling in the chest
any time in the last 12 months? Does
this child take any of the following
prescribed medications on a regular
basis: Ventolin, inhalers, puffers for
asthma?
Income status was measured as the
ratio of household income to the low-income
cut-off for the size and location of the child’s
household.
Cross-sectional survey weights were used
for the analyses. For statistical tests, the
variances and standard errors of all estimates
were calculated using the bootstrap weights
developed by Statistics Canada for each of
the cross-sectional samples.
aged 6 to 7 had been diagnosed with
asthma, compared with 8% of those aged
2 to 3. The increase in prevalence rates
to 2000/2001 and the subsequent drop
occurred in all age groups.
A significantly higher percentage of
boys than girls had been diagnosed with
asthma at each NLSCY cycle (Table 3).
Among both sexes, asthma prevalence
followed the general trend, rising from
50
Health Reports, Vol. 21, no. 4, December 2010 • Statistics Canada, Catalogue no. 82-003-XPE
Recent trends in upper respiratory infections, ear infections and asthma among young Canadian children • Health matters
1994/1995 to 2000/2001, and then
declining.
Previous studies have reported regional
variations in the prevalence of childhood
asthma,14,15 with British Columbia and
the Prairie provinces having lower
rates than other regions. However, this
pattern has changed markedly. Since
2000/2001, the prevalence of asthma
among 2- to 7-year-olds declined in the
Atlantic provinces, Quebec and Ontario,
but remained relatively stable in British
Columbia and the Prairies (Table 3). As
a result, in 2006/2007 and 2008/2009, no
significant regional differences in asthma
prevalence emerged.
During the 1994/1995-to-2008/2009
period, the percentage of children with
asthma who had had an asthma attack
in the past 12 months fell steadily from
53% to 36% (data not shown).
As expected, rates of wheezing and
whistling in the chest were much higher
for children who had been diagnosed with
asthma than for children overall (data not
shown). However, while the prevalence
of such symptoms among the general
population of children aged 2 to 7 did not
change over time (ranging between 17%
and 20%), it dropped significantly among
those with asthma (from 70% to 61%).
In 1994/1995, about 50% of children
with asthma used asthma medication
regularly, a rate that did not change
significantly over the 14 years (data not
shown).
Although boys were more likely than
girls to have asthma, the severity of the
condition did not appear to differ by sex:
no differences emerged in the percentage
who had had an asthma attack or
experienced wheezing or whistling in the
chest in the past year, or in the percentage
who used asthma medication regularly
(data not shown).
frequent upper respiratory infections had
been diagnosed with asthma; by contrast,
7% of children who rarely or never had
these infections had asthma (p<0.003).
In 2008/2009, the figures were 11% and
6% (p<0.002).
Environmental factors
A number of environmental factors
may be related to the recent declines in
childhood ear infections and asthma:
changes in the population structure;
changes in diagnostic practices; decreases
in the prevalence of respiratory allergies12;
improvements in air quality16,17; changes
in hygiene practices (particularly, in
child care settings); and reductions in
children’s exposure to cigarette smoke
at home.18 An investigation of most of
these factors is beyond the scope of this
paper, but the possible role of exposure
to cigarette smoke can be considered.
The
Canadian
Tobacco
Use
Monitoring Survey (CTUMS) reported
a steady decline in daily smoking among
people aged 15 or older from 19% in 2000
to 13% in 2008,19 and a simultaneous
decrease in the percentage of children
aged 0 to 11 who were regularly exposed
to tobacco smoke at home from 24% to
6%.20 NLSCY data also show a decline
in the percentage of children aged 2 to
3 living in households where at least
one parent smoked daily, from 39% in
1994/1995 to 20% in 2008/2009. These
trends suggest that reduced exposure to
tobacco smoke may be contributing to
the decreased prevalence of ear infections
and asthma among young children.
Exposure to cigarette smoke has been
causally linked to ear infections.18,21
According to NLSCY results, children
in households where at least one parent
was a daily smoker were more likely than
children in non-smoking households to
have had at least one ear infection since
birth (Figure 2). However, since the early
1990s, regardless of whether they lived in
a smoking- or non-smoking household,
the percentage of children who had had
ear infections dropped steadily, and
the gap in prevalence between the two
groups narrowed. In 1994/1995, 71%
of children in households with a parent
who smoked had had at least one ear
infection, compared with 64% of those
in non-smoking households (p=0.012);
by 2008/2009, the corresponding figures
were 53% and 50%, a difference that
was not statistically significant. These
trends are consistent with the hypothesis
that reduced exposure to cigarette smoke
contributed to declines in ear infections.
But given the drop in the prevalence of
ear infections among children in both
smoking and non-smoking households,
changes in other factors may have
also played a role. The current lack of
Figure 2
Prevalence of at least one ear infection and of asthma among children aged
2 to 3, by household smoking, Canada excluding territories and Nunavut,
1994/1995 to 2008/2009
71
64
67
Smoking household
61
57
50
50
53
Non-smoking household
Asthma and upper respiratory
infections
Upper respiratory infections are major
asthma inducers.2,5,12 In the present study,
significant links were found between
upper respiratory infections and asthma
(Figure 1). For example, in 1994/1995,
13% of children aged 2 to 3 who had
8
1994/1995
2000/2001
2006/2007
2008/2009
11
1994/1995
Ear infection
Source: 1994/1995 to 2008/2009 National Longitudinal Survey of Children and Youth.
9
14
2000/2001
7 8
7 9
2006/2007
2008/2009
Asthma
Statistics Canada, Catalogue no. 82-003-XPE • Health Reports, Vol. 21, no. 4, December 2010
Recent trends in upper respiratory infections, ear infections and asthma among young Canadian children • Health matters
a difference in the prevalence of ear
infections between children in smoking
and non-smoking households may
indicate that adult smoking rates have
become low enough that exposure to
tobacco smoke is no longer a prominent
cause of ear infections among young
children.
The medical literature has also
causally linked exposure to cigarette
smoke with asthma.18,21 For instance,
legislation banning smoking in public
places in Scotland was followed by
decreases in the incidence of severe
episodes of asthma among preschool and
school-age children.22
In the early years covered by the present
study (1994/1995 and 2000/2001),
children in households where at least
one parent was a daily smoker were
more likely than those in non-smoking
households to have been diagnosed
with asthma (Figure 2). However,
in 2006/2007 and in 2008/2009, no
statistically significant differences were
found in asthma prevalence between
children in smoking and non-smoking
households. Again, this suggests that
reduced exposure to cigarette smoke
contributed to declines in asthma over
time, and that adult smoking rates
51
have become low enough that parental
smoking has ceased to be major cause of
asthma in young children.
And even in households where a parent
smokes, children’s exposure may now
be lower because of growing awareness
of the dangers of second-hand smoke.
According to the CTUMS results, in
2009, 47% of households where smoking
was allowed inside the home imposed
some restrictions.19 Parents who smoke
may, for example, do so outdoors or in
restricted areas.
infection and asthma prevalence reported
above for children in smoking and nonsmoking households were found for
both the low- and higher-income groups.
The decline over time in ear infections
and asthma also occurred among
children in smoking and non-smoking
households in both income groups (data
not shown). These findings suggest that
the links between parental smoking and
ear infections and asthma did not arise
from unidentified factors associated with
income.
Smoking and household income
Summary
Rates of cigarette smoking tend to be
relatively high among low-income
groups.23,24 For example, in 2008/2009,
the prevalence of daily smoking by at
least one parent in households below
the low-income cut-off was 27%; in
households at or above the low-income
cut-off, the figure was 18%.
To determine if the associations
between parental smoking and the
prevalence of ear infections and asthma
among children was related to factors
other than smoking, low-income
and higher-income households were
examined separately. The patterns of ear
From 1994/1995 to 2008/2009,
the prevalence of upper respiratory
infections among children aged 2 to 3
remained constant or declined in most
regions of Canada, but rose significantly
in Quebec. Ear infections declined in
all regions. The prevalence of asthma
among children aged 2 to 7 rose steadily
until 2000/2001 and then fell. A wide
range of environmental factors, including
reduced exposure to cigarette smoke,
may have contributed to these trends.
An examination of possible mechanisms
falls outside the scope of this paper, but
is a topic for future research. ■
52
Health Reports, Vol. 21, no. 4, December 2010 • Statistics Canada, Catalogue no. 82-003-XPE
Recent trends in upper respiratory infections, ear infections and asthma among young Canadian children • Health matters
References
1.
Bluestone CD, Klein JO. Otitis Media
in Infants and Children, Fourth Edition.
Hamilton, Ontario: B.C. Decker Inc., 2007.
2.
Canadian Lung Association. Asthma
Treatment. Available at: http://lung.
ca/diseases-maladies/asthma-asthme/
treatment-traitement/index_e.php. Accessed
June 11, 2010.
3.
Daly KA, Brown JE, Lingren BR, et al.
Epidemiology of otitis media onset by six
months of age. Pediatrics 1999; 103: 1158-66.
4.
Peristein D. Otitis media (Middle ear infection
or inflammation). MedicineNet.com. Available
at: http://www.medicinenet.com/otitis_media/
article.htm. Accessed June 7, 2010.
5.
6.
7.
8.
9.
Urquhart DS, Anderson AK, McKenzie SA.
Fewer colds, less asthma? A hypothesis to
explain the fall in childhood asthma in the
UK. Journal of Epidemiology and Community
Health, 2008; 62: 921-5.
Meneghetti A. Upper respiratory tract infection.
eMedicine.com. Available at: http://emedicine.
medscape.com/article/302460-overview.
Accessed June 10, 2010.
Bushnik, T. Child care in Canada. Children
and Youth Research Paper Series. (Statistics
Canada, Catalogue 89-599-MIE2006pub003)
Ottawa: Statistic Canada, 2006. Available at:
http://www.statcan.gc.ca/pub/89-599-m/89599-m2006003-eng.pdf. Accessed June 23,
2010.
American Academy of Otolaryngology. Fact
Sheet: Day Care and Ear, Nose and Throat
Problems. Available at: http://www.entnet.
org/HealthInformation/dayCareENT.cfm.
Accessed June 11, 2010.
Nabili S. Upper respiratory tract infection.
eMedicine.com. Available at: http://
medicinenet.com/upper_respiratory_infection/
article.htm. Accessed June 7, 2010.
10. Teele DW, Klein JO, Rosner B. Epidemiology
of otitis media during the first seven years of
life in children in Boston: a prospective cohort
study. Journal of Infectious Diseases 1989;
160: 83-94.
11. Anderson HR, Gupta R, Strachan DP,
Limb ES. 50 years of asthma: UK trends
from 1955 to 2004. Thorax 2007; 62: 85-90.
12. Bollag U, Grize L, Braun-Fahrländer C. Is the
ebb of asthma due to the decline of allergic
asthma? A prospective study by the Swiss
Sentinel Surveillance Network, 1999-2005.
Family Practice 2009; 26: 96-101.
13. Dell SD, Foty RG, Gilbert NL, et al. Asthma
and allergic disease prevalence in a diverse
sample of Toronto school children: Results
from the Toronto Child Health Evaluation
Questionnaire (T-CHEQ) Study. Canadian
Respiratory Journal 2010; 17: 1-6.
14. Garner R, Kohen D. Changes in the prevalence
of asthma among Canadian children. Health
Reports (Catalogue 82-003) 2008; 19(2): 1-6.
15. Dales RE, Raizenne M, El-Saadany S,
et al. Prevalence of childhood asthma
across Canada. International Journal of
Epidemiology 1994; 23: 775-81.
16. Battacharyya N, Shapiro NL. Air quality
improvement and the prevalence of frequent
ear infections in children. Otolaryngology –
Head and Neck Surgery 2010; 142: 242-6.
17. Brauer MB, Gehring U, Brunekreef B, et al.
Traffic-related air pollution and otitis media.
Environmental Health Perspectives 2006; 114:
1414-8.
18. World Health Organization. International
Consultation on Environmental Tobacco
(ETS) and Child Health: Consultation
Report. Geneva: World Health Organization,
1999. Available at: http://www.smoke-free.
ca/second-hand-smoke/health_kids.htm.
Accessed June 8, 2010.
19. Health Canada . Canadian Tobacco Use
Monitoring Survey (CTUMS): Overview
of historical data, Wave 1, 1999-2009.
Available at: http://www.hc-sc.gc.ca/
hc-ps/tobac-tabac/research-recherche/stat/_
ctums-esutc_2009/w-p-1_histo-eng.php.
Accessed June 8, 2010.
20. Health Canada (2008). Canadian Tobacco Use
Monitoring Survey (CTUMS): Supplementary
Tables, CTUMS Annual 2008. Available at:
http://www.hc-sc.gc.ca/hc-ps/tobac-tabac/
research-recherche/stat/_ctums-esutc_2008/
ann-table9-eng.php. Accessed June 8, 2010.
21. Physicians for a Smoke-free Canada.
Cigarette Smoke and Kids’ Health (Fact
Sheet). Available at: http://www.smoke-free.
ca/second-hand-smoke/health_kids.htm.
Accessed June 8, 2010.
22. Mackay D, Haw S, Ayres JG, et al.
Smoke-free legislation and hospitalizations
for childhood asthma. The New England
Journal of Medicine 2010; 363(12): 1139-45.
23. National Household Survey on Drug Abuse.
Tobacco Use, Income, and Educational Level.
Washington, DC: Department of Health and
Human Services, 2002. Available at: http://
www.oas.samhsa.gov/2k2/Tob/tob.htm.
Accessed July 19, 2010.
24. Smith P, Begley L, O’Loughlin JL, Snider J.
Smoking Behaviour: 2002 Youth Smoking
Survey – Technical Report. Ottawa: Health
Canada, 2002. Available at: http://www.hc-sc.
gc.ca/hc-ps/pubs/tobac-tabac/yss-etj-2002/
chap3-eng.php.
Statistics Canada, Catalogue no. 82-003-XPE • Health Reports, Vol. 21, no. 4, December 2010
Chronic pain at ages 12 to 44 • Health matters
53
Chronic pain at ages 12 to 44
by Pamela L. Ramage-Morin and Heather Gilmour
Abstract
According to results from the 2007/2008
Canadian Community Health Survey, about 1 in
10 Canadians aged 12 to 44—9% of males and
12% of females, an estimated 1.5 million people—
experienced chronic pain. The prevalence
of chronic pain increased with age and was
significantly higher among people in households
where the level of educational attainment was
low and among the Aboriginal population. The
most common pain-related chronic conditions at
ages 12 to 44 were back problems and migraine
headaches. Chronic pain prevented at least a
few activities in the majority of sufferers. It was
associated with activity limitations and needing
help with everyday tasks, and had work-related
implications. Individuals with chronic pain were
frequent users of health care services, and were
less likely than people without chronic pain to
respond positively on measures of well-being,
including mood and anxiety disorders.
Key words
ADL, anxiety disorders, cross-sectional studies,
health status, health surveys, IADL, mood
disorders, prevalence, quality of life
Authors
Pamela L. Ramage-Morin ([email protected]; 613-951-1760) and
Heather Gilmour ([email protected]
gc.ca; 613-951-2114) are with the Health Analysis
Division at Statistics Canada, Ottawa, Ontario,
K1A 0T6.
P
ain lasting for several months,1 or persisting after
an injury has healed,2 is considered chronic.
Chronic pain affects not only individuals, but also
their families, the health care system, and society as
a whole.3 It may lead to other health concerns such
as eating problems, sleep disturbances and fatigue.4-6
Absences from school, work and social activities
have been linked to chronic pain.3,7,8 People may lose
or change jobs, and in more extreme cases, cannot
work at all.3,5,9,10 Mental health may be compromised;
chronic pain has been associated with anxiety,
depression, loneliness, and suicide ideation and
attempts.11
Although chronic pain is usually
associated with aging, it is relatively
common at younger ages. However,
few large, population-based studies
have examined chronic pain among nonelderly people.4,12-14 Instead, research
on pain at younger ages has focused
on specific chronic conditions and pain
sites,15-17 small sectors of the population
such as occupational or ethnic groups,18-20
or convenience samples such as children
attending certain schools or living in
certain areas.4,21 Results from such
studies provide only a partial picture of
chronic pain in younger people.
This population-based analysis uses
data from the 2007/2008 Canadian
Community Health Survey (CCHS). It
provides estimates of the prevalence
of chronic pain by socio-demographic
characteristics for a sample of 57,660
respondents aged 12 to 44, representing
the 14.6 million Canadians in that age
range (Appendix Table A). Chronic
pain is examined in relation to chronic
conditions, impact on functioning, work
characteristics, health care use, and
general well-being and mental health.
54
Health Reports, Vol. 21, no. 4, December 2010 • Statistics Canada, Catalogue no. 82-003-XPE
Chronic pain at ages 12 to 44 • Health matters
The data
The cross-sectional Canadian Community Health Survey (CCHS) collects information about health status, health care use and health determinants for about
98% of the population aged 12 or older. It covers household residents in the provinces and territories; members of the Canadian Forces and residents of
institutions, Indian reserves and other Aboriginal settlements, and some remote areas are excluded.
Data collection for cycle 4.1 began in January 2007 and continued over 24 months. The sample size was 131,959; the response rate was 76.4%. To
account for survey design effects, in this analysis, standard errors and coefficients of variation were estimated using the bootstrap technique.22,23 A significance
level of p < 0.05 was used.
This analysis pertains to 57,660 CCHS respondents aged 12 to 44, representing an estimated 14.6 million Canadians (Appendix Table A). Proxy respondents
(1,062) were excluded from the study sample. (The prevalence of pain did not differ significantly between proxy and non-proxy respondents). An estimated
63% of the study population were aged 25 to 44, and 69% were married or living in common-law relationships. The majority lived in households where at least
one member was a postsecondary graduate (81%) and resided in urban areas (84%). An estimated 4% were Aboriginal; 76% defined their cultural or racial
background as “White.” An estimated 11% reported chronic pain, and more than half of these people characterized their pain as at least “moderate.”
Respondents were asked, “Are you usually free of pain or discomfort?” Those who answered “No” were considered to have chronic pain and were asked
to assess the usual intensity as “mild,” “moderate” or “severe.” They were also asked how many activities their pain prevents. Those who responded “a few,”
“some” or “most” (versus “none”) were considered to have pain that prevents activities.
Respondents were categorized into four age groups: 12 to 17; 18 to 24; 25 to 34; and 35 to 44.
Among respondents aged 25 to 44, marital status was categorized as single (never married); married/common-law; or separated/divorced/widowed.
Based on the highest level of education in the household, respondents were grouped into four categories: less than secondary graduation, secondary
graduation, some postsecondary, and postsecondary graduation.
Racial/Cultural group was defined as White, Aboriginal, or other (includes multiple racial/cultural origins).
Residence identified whether a respondent lived in an urban or rural area based on 2006 Census geography.
The presence of chronic conditions was established by asking respondents if a health professional had diagnosed them as having a condition that had
lasted, or was expected to last, at least six months. The interviewer read a list of conditions. Individual conditions reported in this study included back problems
(excluding fibroymyalgia and arthritis), arthritis, migraine, mood disorder, anxiety disorder, stomach/intestinal ulcers, bowel disorder/Crohn’s disease or colitis,
and diabetes.
A more comprehensive list of chronic conditions was used to estimate the total number of chronic conditions each respondent had. In addition to those listed
above, cancer, asthma, high blood pressure, heart disease, effects of stroke, urinary incontinence, Alzheimer’s disease or other dementia, emphysema, and
chronic obstructive pulmonary disease were included. The count of chronic conditions was categorized into four groups: none, 1, 2, and 3 or more.
Activity restriction was based on a response of “often” or “sometimes” (versus “never”) to the questions: “Does a long-term physical condition or mental
condition or health problem, reduce the amount or the kind of activity you can do . . .
● . . . at home?”
● . . . at school?”
● . . . at work?”(respondents aged 25 to 44)
● . . . in other activities, for example, transportation or leisure?”
Perceived health was based on the question, “In general would you say your health is:…” The five response categories were combined into two groups:
good/very good/excellent and fair/poor. A similar question was asked for perceived mental health.
Among respondents aged 25 to 44, perceived work stress at the main job or business in the past 12 months was measured by asking: “Would you say that
most days at work were: not at all stressful? a bit stressful? quite a bit stressful? extremely stressful?” Respondents who answered “quite a bit” or “extremely
stressful” were classified as having high perceived work stress.
Based on respondents’ working status in the week before the interview, they were classified as worked at a job last week; absent from work last week; did
not have a job last week; or permanently unable to work. These variables were restricted to respondents aged 25 to 44.
This study has a number of limitations. Respondents were not asked about the duration, frequency or site of their pain, and no distinction is made between
cancer and non-cancer pain. Information on medications, especially those that may have an impact on pain, was not collected. The data are cross-sectional,
so no conclusions can be made about temporal order, that is, whether pain led to activity limitations or vice versa. Finally, chronic conditions were self-reported
and not verified by another source.
One in ten
In 2007/2008, more than 1.5 million
Canadians aged 12 to 44—9% of males
and 12% of females—reported chronic
pain (Table 1). The prevalence of chronic
pain rose with advancing age: among
12- to 17-year-olds, 2% of males and 6%
of females reported chronic pain; at ages
35 to 44, the corresponding figures were
14% and 17%.
Consistent
with
previous
research,9,10,20,24,25
data
from
the
2007/2008 CCHS show that females
aged 12 to 44 had higher odds of
chronic pain than did males in that age
range. However, the relationship was
no longer significant when the presence
of chronic conditions was considered,
suggesting that they largely account for
the association between gender and pain
(data not shown).
Household educational attainment
was associated with pain. People in
households where no one had graduated
from secondary school were almost
twice as likely to report chronic pain as
Statistics Canada, Catalogue no. 82-003-XPE • Health Reports, Vol. 21, no. 4, December 2010
Chronic pain at ages 12 to 44 • Health matters
Table 1
Prevalence of chronic pain, by sex and selected characteristics, household
population aged 12 to 44, Canada, 2007/2008
Males
%
Total with chronic pain
669
Pain intensity
Mild
Moderate
Severe
chronic conditions people had, the more
likely they were to report chronic pain.
Activity limitations
Females
95%
confidence
interval
Estimated
number
’000
95%
confidence
interval
to
Estimated
number
’000
%
9.1
8.6 9.6
257
323
88
3.5
4.4
1.2
3.2 3.8
4.0 4.8
1.0 1.4
Age group
12 to 17†
18 to 24
25 to 34
35 to 44
30
99
212
327
2.4
6.5*
9.7*‡
13.7*‡
2.0
5.5
8.7
12.7
2.9
7.6
10.7
14.8
71
131
261
404
5.9§
5.0 6.7
9.2*§
8.0 10.3
11.8*ठ10.9 12.7
16.7*ठ15.7 17.8
Marital status (ages 25 to 44)
Single (never married)†
Married/Common-law
Separated/Divorced/Widowed
143
356
40
11.3
11.5
20.1*
10.0 12.6
10.6 12.4
16.1 24.1
147
437
80
14.5§
13.6§
20.1*
12.9 16.1
12.8 14.5
17.4 22.9
Highest level of education in household
Less than secondary graduation
Secondary graduation
Some postsecondary
Postsecondary graduation†
Missing
39
60
45
450
74
17.0*
9.4
11.7*
8.7
8.1
14.0
7.8
9.4
8.1
6.7
20.1
11.1
13.9
9.3
9.5
39
88
57
610
73
19.0*
14.5*§
13.8*
11.4§
10.5§
15.6
12.3
11.6
10.8
8.7
22.5
16.7
16.0
12.0
12.3
Racial/Cultural group
White†
Aboriginal (off reserve)
Other (includes multiple racial/cultural origins)
Missing
503
46
101
19
9.3
15.4*
7.1*
9.7
8.7
12.5
5.7
6.7
9.8
18.2
8.4
12.7
619
53
171
23
11.6§
16.5*
11.9§
13.3
11.1
13.9
10.4
9.4
12.2
19.1
13.4
17.1
Residence
Urban†
Rural
536
133
8.7
11.0*
8.2 9.3
9.8 12.2
721
146
11.8§
12.6
11.2 12.4
11.5 13.6
Characteristic
from
from
to
867
11.9
§
11.4 12.5
303
451
105
4.2§
6.2§
1.5
3.8 4.5
5.8 6.6
1.3 1.6
†
reference category
* significantly different from estimate for reference category (p<0.05)
‡
significantly different from preceding age group (p<0.05)
§
significantly different from estimate for males (p<0.05)
Source: 2007/2008 Canadian Community Health Survey, 24-month file.
were those in households with at least
one postsecondary graduate.
Compared with people whose
racial/cultural background was White,
Aboriginal people were more likely
to report pain. This may, in part, be
explained by the higher prevalence of
pain-related chronic conditions (back
problems, migraine, arthritis, stomach/
intestinal ulcers, anxiety disorders and
mood disorders) among the Aboriginal
population (data not shown).
And for males, chronic pain was more
common among those in rural than urban
areas.
55
Chronic conditions
Back problems were reported by more
than 2 million people aged 12 to 44 (14%
of males and 17% of females), about a
third of whom also reported chronic pain
(Table 2). Migraine headaches, too, were
common at these ages, especially among
females (17%), and almost a quarter of
these females reported chronic pain.
Arthritis, relatively uncommon at ages
12 to 44 (fewer than 5%), was highly
associated with pain; about half of males
and females with arthritis also reported
chronic pain. Not surprisingly, the more
More than 60% of 12- to 44-year-olds
with chronic pain reported experiencing
activity limitations “sometimes” or
“often,” compared with 15% of those
who did not have chronic pain (Table 3).
These limitations touched all domains of
life—home, school, work, transportation
and leisure—and persisted in multivariate
analysis that accounted for age, sociodemographic characteristics and chronic
conditions (data not shown).
The majority of males (64%) and
females (74%) with chronic pain reported
that it not only limited but prevented at
least a few activities. The prevalence
of activity-preventing pain rose with
age and was consistently higher among
females than males. The difference
between the sexes was particularly
pronounced at ages 12 to 17: 66% of
females with chronic pain reported that it
prevented activities, compared with 42%
of males.
Needing help
Activities of daily living (ADL) (activities
vital to retaining independence)
include personal care such as bathing,
dressing, eating and taking medication,
as well as moving about inside the
house. Instrumental activities of daily
living (IADL) further assess functional
independence and include preparing
meals, doing everyday housework,
getting to appointments, running errands
such as grocery shopping, and banking
and paying bills. People who needed
help with ADL or IADL tasks because of
health problems were identified. Because
most 12- to 17-year-olds, regardless
of their health status, require help with
many IADL, this variable was examined
only for people aged 18 to 44.
Very few pain-free 18- to 44-year-olds
needed help with ADL, but among those
with chronic pain, 3% of men and 5%
of women required assistance (Table 3).
Similarly, while 2% of people without
chronic pain needed help with IADL,
the figures were 13% for men and 23%
56
Health Reports, Vol. 21, no. 4, December 2010 • Statistics Canada, Catalogue no. 82-003-XPE
Chronic pain at ages 12 to 44 • Health matters
Table 2
Percentage reporting chronic conditions and chronic pain, by sex, household
population aged 12 to 44, Canada, 2007/2008
Prevalence of chronic pain
among those with
chronic condition
Chronic condition
Males
Chronic condition
Back problems
Migraine
Mood disorder
Anxiety disorder
Arthritis
Stomach/Intestinal ulcers
Bowel disorder/Crohn's Disease or colitis
Diabetes
Number of chronic conditions
None†
One
Two
Three or more
Females
Chronic condition
Back problems
Migraine
Mood disorder
Anxiety disorder
Arthritis
Stomach/Intestinal ulcers
Bowel disorder/Crohn's Disease or colitis
Diabetes
Number of chronic conditions
None†
One
Two
Three or more
possibly as a consequence of trying to
cope with pain-related work limitations,
those with chronic pain were more likely
to report work stress.
95%
confidence
interval
Estimated
number
’000
%
from
to
1,058
542
277
255
249
165
152
106
14.4
7.4
3.8
3.5
3.4
2.3
2.1
1.4
13.8
6.9
3.5
3.2
3.1
2.0
1.8
1.2
15.1
7.8
4.1
3.8
3.7
2.5
2.3
1.7
4,728
1,698
551
255
65.4
23.5
7.6
3.5
64.5
22.8
7.1
3.2
1,215
1,220
561
540
327
151
312
99
16.7§
16.8§
7.7§
7.4§
4.5§
2.1
4.3§
1.4
3,993
1,830
810
555
55.6§
25.5§
11.3§
7.7§
Estimated
number
’000
95%
confidence
interval
%
from
to
313
106
81
56
122
44
37
21E
29.6
19.7
29.2
21.8
49.0
26.6
24.1
19.7E
27.5
17.3
25.1
18.5
44.3
21.1
18.9
13.4
31.7
22.0
33.4
25.1
53.8
32.1
29.3
26.1
66.2
24.2
8.1
3.8
184
208
147
107
3.9
12.3*
26.8*‡
42.1*‡
3.5
11.0
23.9
37.6
4.3
13.6
29.6
46.7
16.1
16.2
7.3
7.0
4.2
1.8
4.0
1.2
17.4
17.5
8.2
7.9
4.8
2.3
4.6
1.6
408
296
177
156
160
51
98
28
33.6§
24.3§
31.7
28.9§
48.9
33.9§
31.5§
28.3
31.6
22.6
28.9
26.0
45.2
29.1
28.1
21.3
35.6
26.0
34.5
31.8
52.6
38.6
34.9
35.3
54.7
24.7
10.7
7.3
56.4
26.2
11.8
8.2
169
240
190
248
4.2
13.1*
23.5*‡
44.7*‡
3.7
12.0
21.5
41.8
4.7
14.2
25.5
47.6
†
reference category
* significantly different from estimate for reference category (p<0.05)
‡
significantly different from preceding category (p<0.05)
§
significantly different from estimate for males (p<0.05)
E
interpret with caution (coefficient of variation 16.6% to 33.3%)
Source: 2007/2008 Canadian Community Health Survey, 24-month file.
for women with chronic pain. Among
people with chronic pain, women were
more likely than men to need help moving
about inside the house, doing housework,
running errands, and preparing meals.
The percentages of men and women
with chronic pain who needed help with
personal care or managing finances did
not differ significantly (data not shown).
Employment
In the week before they were interviewed,
the majority of 25- to 44-year-olds had
worked at a job. However, while 87%
of men and 72% of women who were
pain-free had done so, the figures were
78% for men and 65% for women who
reported chronic pain (Table 3). As
these differences suggest, people with
chronic pain were more likely than the
no-pain group to be without a job in
the week before their interview or to be
permanently unable to work.
Workers with chronic pain were no
more likely than those without chronic
pain to be absent from their jobs. But
Health care
Not surprisingly, people aged 12 to 44
with chronic pain were more likely than
those without chronic pain to use a variety
of health care services, including many
not covered by public health insurance
(Table 4). For example, 19% of males
and 18% of females with chronic pain
had consulted a physiotherapist in the
previous 12 months, compared with 7%
of males and females who were generally
pain-free.
Well-being
As might be expected, people with
chronic pain were less likely than those
who were generally pain-free to assess
their well-being positively (Table 5).
While almost all (more than 95%) of 12to 44-year-olds who were free of chronic
pain described their health as good, very
good or excellent, the percentages were
considerably lower for those with chronic
pain: 80% of males and 76% of females.
As well, 23% of people with chronic pain
reported that their health was worse than
it had been a year earlier; this was the
case for 7% of those who were pain-free.
People with chronic pain were less
likely than those without it to be satisfied
with their lives or to have a positive sense
of community belonging. They were
more likely to perceive life as stressful
and were less likely to report good, very
good or excellent mental health.
Mood disorders such as depression
and dysthymia, and anxiety disorders
such as a phobia and panic disorder are
relatively common at ages 12 to 44,
especially among females (Table 2). The
prevalence of mood and anxiety orders
was particularly high among people with
chronic pain (Table 5). For example,
21% of females with chronic pain had a
mood disorder and 18% had an anxiety
disorder; among women who were painfree, 6% reported a mood disorder, and
6%, an anxiety disorder.
Statistics Canada, Catalogue no. 82-003-XPE • Health Reports, Vol. 21, no. 4, December 2010
57
Chronic pain at ages 12 to 44 • Health matters
Table 3
Measures of functioning and work characteristics, by sex and chronic pain status, household population aged 12 to 44,
Canada, 2007/2008
Males
Population reporting chronic pain that
prevents a few/some/most activities
Age group
12 to 17†
18 to 24
25 to 34
35 to 44
Number of activities prevented
None
A few
Some
Most
Pain intensity
Mild†
Moderate
Severe
†
reference category
* significantly different from estimate for reference category (p<0.05)
‡
significantly different from estimate for males (p<0.05)
E
interpret with caution (coefficient of variation 16.6% to 33.3%)
Source: 2007/2008 Canadian Community Health Survey, 24-month file.
95%
confidence
interval
%
from
to
Estimated
number
’000
417
970
62.4*
14.6
59.6
13.9
65.2
15.3
269
369
40.2*
5.5
37.4
5.1
31
139
21.3*
5.0
198
271
Estimated
number
’000
Activity limitation (sometimes/often)
Chronic pain
No chronic pain†
Activity limitation at home (sometimes/often)
Chronic pain
No chronic pain†
Activity limitation at school (sometimes/often)
Chronic pain
No chronic pain†
Activity limitation at work (sometimes/often) (ages 25 to 44)
Chronic pain
No chronic pain†
Activity limitation - other (sometimes or often)
Chronic pain
No chronic pain†
Help needed for ADL
Chronic pain
No chronic pain†
Help needed for IADL (ages 18 to 44)
Chronic pain
No chronic pain†
Worked at a job last week (ages 25 to 44)
Chronic pain
No chronic pain†
Absent from work last week (ages 25 to 44)
Chronic pain
No chronic pain†
Did not have a job last week (ages 25 to 44)
Chronic pain
No chronic pain†
Permanently unable to work (ages 25 to 44)
Chronic pain
No chronic pain†
Work stress (ages 25 to 44)
Chronic pain
No chronic pain†
Females
95%
confidence
interval
%
from
to
547
980
63.3*
15.3
61.1
14.7
65.5
16.0
43.0
6.0
426
459
49.2*‡
7.2‡
46.8
6.7
51.6
7.7
16.9
4.4
25.8
5.5
77
191
31.8*‡
6.8‡
27.5
6.1
36.2
7.5
42.1*
7.0
38.5
6.4
45.7
7.7
227
254
44.5*
7.5
41.7
6.9
47.4
8.2
300
432
44.9*
6.5
42.0
6.0
47.8
7.0
411
475
47.5*
7.4‡
45.2
7.0
49.7
7.9
23
28
3.4*
0.4
2.4
0.3
4.4
0.6
47
31
5.4*‡
0.5
4.3
0.4
6.6
0.6
85
89
13.3*
1.6
11.2
1.4
15.3
1.9
180
122
22.6*‡
2.3‡
20.4
2.0
24.8
2.6
409
3,420
77.5*
87.3
74.8
86.5
80.2
88.1
425
2,770
65.3*‡
71.7‡
62.6
70.6
68.0
72.8
31
183
5.8
4.7
4.3
4.2
7.3
5.2
48
339
7.3
8.8‡
6.0
8.1
8.7
9.5
57
297
10.8*
7.6
8.9
6.9
12.7
8.2
145
743
22.3*‡
19.2‡
19.9
18.3
24.7
20.2
5.9*
0.4E
4.6
0.3
7.3
0.6
5.0*
0.3E
3.9
0.2
6.2
0.4
40.3*
29.2
36.9
28.2
43.6
30.3
202
1,059
39.2*
31.5‡
36.1
30.3
42.3
32.8
424
63.5
60.9
66.1
634
73.6‡
71.4
75.9
13
58
139
215
42.0
58.0*
65.7*
65.8*
32.5
50.1
61.0
62.1
51.4
65.9
70.3
69.5
46
93
199
297
65.6‡
71.9‡
76.7*‡
73.6‡
57.6
65.6
72.8
70.2
73.6
78.2
80.6
77.1
244
210
126
88
36.5
31.4
18.9
13.1
33.9
28.9
16.5
11.4
39.1
34.0
21.3
14.9
227
316
203
115
26.4‡
36.7‡
23.6‡
13.3
24.1
34.3
21.7
11.8
28.7
39.0
25.5
14.9
118
231
75
45.9
71.5*
85.6*
41.4
67.9
80.4
50.4
75.2
90.9
165
371
94
55.1‡
82.3*‡
89.5*
50.6
79.7
85.5
59.6
85.0
93.5
31
17E
193
1,132
33
12E
58
Health Reports, Vol. 21, no. 4, December 2010 • Statistics Canada, Catalogue no. 82-003-XPE
Chronic pain at ages 12 to 44 • Health matters
Table 4
Health care use in past 12 months, by sex and chronic pain status, household population aged 12 to 44, Canada, 2007/2008
Males
Estimated
number
’000
Characteristic
Females
95%
confidence
interval
%
from
to
Estimated
number
’000
95%
confidence
interval
%
from
to
Consulted health care professional
Chronic pain
No chronic pain†
622
5,919
93.0*
89.0
91.8
88.4
94.3
89.6
846
6,125
97.7*‡
96.0‡
97.0
95.6
98.5
96.3
Has regular medical doctor
Chronic pain
No chronic pain†
511
4,862
76.5*
73.1
74.1
72.4
78.9
73.9
762
5,398
88.0*‡
84.6‡
86.4
83.9
89.6
85.3
Consulted family doctor/general practitioner
Chronic pain
No chronic pain†
507
4,045
75.8*
60.8
73.5
59.8
78.1
61.7
756
4,919
87.4*‡
77.0‡
85.7
76.2
89.0
77.8
Consulted other medical doctor
Chronic pain
No chronic pain†
214
985
32.1*
14.8
29.4
14.1
34.8
15.4
420
1,843
48.4*‡
28.8‡
46.0
28.0
50.9
29.7
Consulted nurse
Chronic pain
No chronic pain†
92
541
13.8*
8.1
12.0
7.7
15.6
8.6
193
903
22.3*‡
14.1‡
20.3
13.5
24.3
14.8
Consulted chiropractor
Chronic pain
No chronic pain†
139
644
20.7*
9.7
18.4
9.2
23.1
10.1
177
705
20.5*
11.0‡
18.5
10.5
22.4
11.6
Consulted physiotherapist
Chronic pain
No chronic pain†
127
441
19.0*
6.6
16.7
6.2
21.4
7.1
176
427
20.3*
6.7
18.4
6.3
22.3
7.1
Consulted social worker/counsellor
Chronic pain
No chronic pain†
47
279
7.1*
4.2
5.8
3.8
8.4
4.5
117
427
13.5*‡
6.7‡
11.9
6.3
15.1
7.1
Consulted psychologist
Chronic pain
No chronic pain†
38
172
5.7*
2.6
4.6
2.3
6.9
2.8
89
294
10.3*‡
4.6‡
8.9
4.2
11.7
5.0
†
reference category
* significantly different from estimate for reference category (p<0.05)
‡
significantly different from estimate for males (p<0.05)
Source: 2007/2008 Canadian Community Health Survey, 24-month file.
The relationships between chronic
pain and measures of well-being
persisted when potentially confounding
socio-demographic characteristics and
painful chronic conditions were taken
into account (Table 5). In most cases,
the associations between pain and well-
being were present regardless of pain
intensity (data not shown).
Summary
Chronic pain is common in younger
Canadians. It affects daily activities,
employment, health care use, and general
and psycho-social well-being.
The
association between chronic pain and
mood and anxiety disorders revealed in
this study highlights the importance of
monitoring younger people with chronic
pain for these mental disorders. ■
Statistics Canada, Catalogue no. 82-003-XPE • Health Reports, Vol. 21, no. 4, December 2010
Chronic pain at ages 12 to 44 • Health matters
59
Table 5
Prevalence of and adjusted odds ratios for well-being and mental health disorders, by sex and chronic pain status, household
population aged 12 to 44, Canada, 2007/2008
Males
Estimated
number
’000
Positive self-perceived health
Chronic pain
No chronic pain†
Self-perceived health worse
than a year ago
Chronic pain
No chronic pain†
95%
confidence
interval
%
from
to
Females
Adjusted‡
odds
ratio
95%
confidence
interval
from
to
Estimated
number
’000
95%
confidence
interval
%
from
to
95%
Adjusted‡ confidence
interval
odds
ratio from to
537
6,381
80.4*
95.7
78.3 82.6
95.3 96.1
0.3*
1.0
0.2 0.3
… …
661
6,164
76.4*
96.4
74.4 78.5
96.1 96.7
0.2*
1.0
0.1 0.2
… …
151
444
22.5*
6.7
20.1 25.0
6.2 7.2
3.4*
1.0
2.8 4.2
… …
198
474
22.9*
7.4
20.8 24.9
6.9 7.9
2.7*
1.0
2.3 3.3
… …
Satisfied with life in general
Chronic pain
No chronic pain†
549
6,235
82.2*
93.6
80.0 84.5
93.2 94.1
0.4*
1.0
0.3 0.5
… …
711
6,001
82.4*
94.0
80.5 84.3
93.6 94.4
0.4*
1.0
0.4 0.5
… …
Positive sense of community belonging
Chronic pain
No chronic pain†
368
4,138
55.3*
62.8
52.5 58.1
61.8 63.7
0.8*
1.0
0.7 1.0
… …
486
4,072
56.6*
64.4
54.3 59.0
63.4 65.3
0.8*
1.0
0.7 1.0
… …
Perceived life stress
Chronic pain
No chronic pain†
242
1,233
37.1*
20.4
34.2 40.0
19.6 21.2
1.8*
1.0
1.5 2.1
… …
343
1,375
40.6*
23.7
38.1 43.0
22.8 24.5
1.6*
1.0
1.5 1.9
… …
Positive self-perceived mental health
Chronic pain
No chronic pain†
584
6,439
87.6*
96.6
85.7 89.5
96.3 97.0
0.3*
1.0
0.2 0.4
… …
748
6,170
86.3*
96.5
84.6 88.1
96.2 96.9
0.3*
1.0
0.3 0.4
… …
Anxiety disorder
Chronic pain
No chronic pain†
56
199
8.3*
3.0
9.6
3.3
1.8*
1.0
1.4 2.4
… …
156
384
18.0*
6.0
16.1 19.9
5.6 6.5
2.2*
1.0
1.8 2.6
… …
Mood disorder
Chronic pain
No chronic pain†
81
196
12.1*
2.9
10.2 14.0
2.6 3.2
2.9*
1.0
2.2 3.9
… …
177
383
20.5*
6.0
18.5 22.4
5.6 6.4
2.3*
1.0
1.9 2.8
… …
7.0
2.7
†
reference category
* significantly different from estimate for reference category (p<0.05)
‡
adjusted for age, marital status, household, education, race/culture, urban/rural residence; arthritis, back problems, migraine headaches
... not applicable
Note: Because of rounding, odds ratios for which upper confidence intervals were 1.0 were statistically significant.
Source: 2007/2008 Canadian Community Health Survey, 24-month file.
60
Health Reports, Vol. 21, no. 4, December 2010 • Statistics Canada, Catalogue no. 82-003-XPE
Chronic pain at ages 12 to 44 • Health matters
References
1.
Turk DC, Melzack R, eds. Handbook of Pain
Assessment. Second Edition. New York: The
Guilford Press, 2001.
10. Neville A, Peleg R, Singer Y, et al. Chronic
pain: a population-based study. Israel Medical
Association Journal 2008; 10: 676-80.
2.
Melzak R, Wall PD. The Challenge of Pain.
Markham: Penguin Books, 1988.
3.
Breivik H. Collett B, Ventafridda V, et al.
Survey of chronic pain in Europe: Prevalence,
impact on daily life, and treatment. European
Journal of Pain 2006; 10(4): 287-333. doi:
10.1016/j.ejpain.2005.06.009.
11. Ratcliffe GE, Enns MW, Belik SL, Sareen, J.
Chronic pain conditions and suicidal ideation
and suicide attempts: An epidemiologic
perspective. Clinical Journal of Pain 2008;
24(3): 204-10.
12. Millar WJ. Chronic pain. Health Reports
(Statistics Canada, Catalogue 82-003)1996;
7(4): 47-53.
4.
Roth-Isigkeit A, Thyen U, Stöven H, et al. Pain
among children and adolescents: Restrictions
in daily living and triggering factors. Pediatrics
2005;115(2):e152-e162. Available at www.
pediatrics.org. Accessed October 14, 2009.
doi: 10.1542/peds.2004-0682.
5.
Cosby AG, Hitt HC, Thornton-Neaves T, et al.
Profiles of pain in Mississippi: Results from
the Southern Pain Prevalence Study. Journal
of Mississippi State Medical Association 2005;
46(10): 301-9.
14. Rustøen T, Klopstad Wahl A, Hanestad BR,
et al. Age and the experience of chronic pain.
Differences in health and quality of life among
younger, middle-aged and older adults.
Clinical Journal of Pain 2005; 21(6): 513-23.
6.
Karoly P, Ruehlman LS. Psychosocial aspects
of pain-related life task interference: An
exploratory analysis in a general population
sample. Pain Medicine 2007; 8(7): 563-72.
doi: 10.1111/j.1526-4637.2006.00230.x.
15. Briggs AM, Smith AJ, Straker LM, Bragge P.
Thoracic spine pain in the general population:
Prevalence, incidence and associated factors in
children, adolescents and adults. A systematic
review. BMC Musculoskeletal Disorders
2009; 10: 77. doi: 10.1186/1471.2474-10-77.
7.
8.
9.
Côté P, Kristman V, Vidmar M, et al. The
prevalence and incidence of work absenteeism
involving neck pain. Spine 2008; 33(4suppl.):
S192-8.
Stewart WF, Ricci JA, Chee E, et al. Lost
productive time and cost due to common pain
conditions in the US workforce. Journal of the
American Medical Association 2003; 290(18):
2443-54. doi: 10.1001/jama.290.18.2443.
Mailis-Gagnon A, Yegneswaran B, Lakha SF,
et al. Pain characteristics and demographics of
patients attending a university-affiliated pain
clinic in Toronto, Ontario. Pain Research and
Management 2007; 12(2): 93-9.
13. Mäntyselkä PT, Turunen JHO, Ahonen
RS, et al. Chronic pain and poor self-rated
health. Journal of the American Medical
Association 2003; 290(18): 2435-42. doi:
10.001/jama.290.18.2435.
16. Tripp DA, Nickel JC, Ross S, et al. Prevalence,
symptom impact and predictors of chronic
prostatitis-like symptoms in Canadian males
aged 16 to 19 years. British Journal of Urology
International 2008;103(8): 1080-4. doi:
10.1111/j.1464-410x.2008.08157.x.
17. Hill CL, Gill TK, Menz HB, Taylor AW.
Prevalence and correlates of foot pain
in a population-based study: the North
West Adelaide health study. Journal of
Foot and Ankle Research 2008; 1: 2. doi:
10.1186/1757-1146-1-2.
18. Green CR, Baker TA, Sato Y, et al. Race and
chronic pain: A comparative study of young
black and white Americans presenting for
management. Journal of Pain 2003; 4(4):
176-83. doi: 10.1016/51526-5900(02)65013-8.
19. Hastie BA, Riley JL, Fillingim RB. Ethnic
differences and responses to pain in healthy
young adults. Pain Medicine 2005; 6(1):
61-71.
20. Kopec JA, Sayre EC. Work-related
psychosocial factors and chronic pain: a
prospective cohort study in Canadian workers.
Journal of Occupational and Environmental
Medicine 2004; 46(12): 1263-71. doi:
10.1097/01.jom.0000147230.29859.69.
21. van Dijk A, Mcgrath PA, Pickett W,
VandenKerkhof EG. Pain prevalence in
nine- to 13-year-old school children. Pain
Research and Management 2006; 11(4):
234-40.
22. Rao JNK, Wu CFJ, Yue K. Some recent work
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23. Rust KF, Rao JNK. Variance estimation for
complex surveys using replication techniques.
Statistical Methods in Medical Research 1996;
5: 281-310.
24. Elliott AM, Smith BH, Penny KI, et al.
The epidemiology of chronic pain in the
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25. Eriksen J, Jensen MK, Sjøgren P, et al.
Epidemiology of chronic non-malignant
pain in Denmark. Pain 2003; 106: 221-8.
doi: 10.1016/S0304-3959(03)00225-2.
Statistics Canada, Catalogue no. 82-003-XPE • Health Reports, Vol. 21, no. 4, December 2010
Chronic pain at ages 12 to 44 • Health matters
Appendix
Table A
Selected characteristics of study sample, household population aged 12 to 44,
Canada, 2007/2008
Sample size
Estimated
number
’000
%
Total
57,660
14,607
100.0
Chronic pain
No
Yes
Missing
51,147
6,472
41
13,062
1,536
...
89.5
10.5
...
Pain intensity
No chronic pain
Mild
Moderate
Severe
Missing
51,147
2,314
3,285
834
80
13,062
560
774
193
...
89.5
3.8
5.3
1.3
...
Sex
Male
Female
27,325
30,335
7,340
7,267
50.3
49.7
Age group
12 to 17
18 to 24
25 to 34
35 to 44
10,660
9,983
17,610
19,407
2,459
2,952
4,396
4,801
16.8
20.2
30.1
32.9
Marital status (ages 25 to 44)
Single (never married)
Married/Common-law
Separated/Divorced/Widowed
Missing
10,145
23,822
3,004
46
2,276
6,312
599
...
24.8
68.7
6.5
...
Highest level of education in household
Less than secondary graduation
Secondary graduation
Some postsecondary
Postsecondary graduation
Missing
2,384
5,487
3,223
40,423
6,143
431
1,243
805
10,508
...
3.3
9.6
6.2
80.9
...
Racial/Cultural group
White
Aboriginal (off reserve)
Other (includes multiple racial/cultural origins)
Missing
45,556
4,280
6,504
1,320
10,743
621
2,870
...
75.5
4.4
20.2
...
Residence
Urban
Rural
43,814
13,846
12,232
2,375
83.7
16.3
... not applicable
Notes: Excludes 1,062 proxy respondents. Because of rounding, detail may not add to totals.
Source: 2007/2008 Canadian Community Health Survey, 24-month file.
61
E L E C T R O N I C P U B L I C AT I O N S
AVA I L A B L E AT
w w w. s t a t c a n . g c . c a
Statistics Canada, Catalogue no. 82-003-XPE • Health Reports, Vol. 21, no. 4, December 2010
H1N1 vaccination • Health matters
63
H1N1 vaccination
by Heather Gilmour and Nancy Hofmann
Abstract
Early results (January to April) from the 2010
Canadian Community Health Survey show that
an estimated 41% of Canadians (excluding
those in the territories) aged 12 or older had
been vaccinated for H1N1 by April 2010. The
percentages were higher in the Atlantic provinces,
Quebec and Saskatchewan than in Canada
overall. Relatively high percentages of females
and people aged 45 or older were vaccinated;
the percentage of immigrants who had done
so was relatively low. Being in a priority group
(health-care worker, having children younger than
5 in the household, or having a chronic condition
that could increase the risk for complications from
H1N1) increased the likelihood of vaccination. A
history of seasonal flu vaccination and having a
regular doctor were also associated with H1N1
vaccination. Nearly three-quarters of those who
had not been vaccinated reported that they did not
think it was necessary.
Keywords
Immunization, influenza, pandemic, public health
Authors
Heather Gilmour (1-613-951-2114; Heather.
[email protected]) is with the Health
Analysis Division and Nancy Hofmann (1-613951-0789; [email protected]) is with
the Health Statistics Division at Statistics Canada,
Ottawa, Ontario, K1A 0T6.
T
he H1N1 flu virus, a new influenza strain to
which most people have no natural immunity,
emerged in April 2009.1 In June of that year, the
World Health Organization (WHO) announced “the
start of the 2009 influenza pandemic”2 and raised its
influenza pandemic alert to phase 6, the highest level.
Phase 6 indicates that the same identified virus has
caused sustained outbreaks in two or more countries
in one WHO region and in at least one other country
in another WHO region. A year later, 214 countries
had reported H1N1 cases, with more than 18,000
deaths world-wide.3 In Canada, 428 people died from
H1N1, and thousands more were infected.4 In August
2010, the WHO announced that the world was “now
in the post-pandemic period.”5
An integral part of the public health
response to pandemic influenza is
prevention through vaccination.6 The
Public Health Agency of Canada advised
Canadians that the H1N1 vaccine was the
best way to protect themselves and others
from infection.7 The federal government
oversaw the purchase and distribution
of the vaccine to the provinces, but each
province was ultimately responsible for
determining how it would be administered
in its jurisdiction.8 Beginning in the fall
of 2009, vaccination clinics across the
country offered the vaccine to Canadians.
Based on data from the 2010 Canadian
Community Health Survey (CCHS), this
study examines uptake of the H1N1
vaccine. Socio-demographic, priority
group and health service characteristics
of those who were vaccinated, along with
reasons for not doing so, are analyzed.
Four in ten
By April 2010, an estimated 41%
of Canadians aged 12 or older (11.6
million) living in the 10 provinces had
had an H1N1 flu shot (Table 1). Data to
64
Health Reports, Vol. 21, no. 4, December 2010 • Statistics Canada, Catalogue no. 82-003-XPE
H1N1 vaccination • Health matters
The data
Estimates are based on data collected from the 2010 Canadian Community Health Survey (CCHS) between January and April 2010. The CCHS covers the
household population aged 12 or older in all provinces. It excludes members of the Canadian Forces; residents of Indian reserves, institutions, and some remote
areas; and military and civilian residents of Canadian Forces bases. Data were collected by telephone (63.6%) and personal (36.4%) interview from a sample
of 20,855 individuals. The response rate was 73.1%.
Respondents were asked, “Have you had the H1N1 shot?” Those who did not receive the shot were asked, “What are the reasons that you have not had
the H1N1 flu shot?” The interviewer read a list of reasons that included: “have not gotten around to it,” “you did not think it was necessary,” “your doctor did not
think it was necessary,” “waiting time was too long,” “bad reaction to previous shot.” Response categories of “not available at time required,” “not available at all
in the area,” and “did not know where to go/uninformed” were grouped as access problems. “Personal or family responsibilities,” “transportation problems,” and
being “unable to leave the house because of a health problem” were grouped as personal barriers. The numbers indicating that they did not receive the H1N1
vaccination because of a “language problem” or “cost” were too low to be released and were included in the other category. Respondents could indicate as
many reasons as applied. The H1N1 questions were asked only of respondents who were answering on their own behalf; proxy responses were not accepted.
To account for the complex design of the CCHS, the bootstrap method9,10 was used to estimate standard errors, coefficients of variation and confidence
intervals. The statistical significance level was set at <0.05.
Respondents were categorized into five age groups: 12 to 19; 20 to 44; 45 to 64; 65 to 84; and 85 or older.
Province pertains to the province of residence at the time of the interview. (Information about H1N1 vaccination in the three territories will be available when
data for the entire year have been processed.)
Among respondents aged 25 or older, marital status was categorized as: married/common-law; separated/ divorced/ widowed; and single.
Highest level of household education refers to the highest level of educational attainment of at least one household member: less than secondary graduation,
secondary graduation, some postsecondary, and postsecondary graduation.
Immigrant status is based on Canadian citizenship by birth and immigration to Canada. Respondents who were not born Canadian citizens and identified a
year of immigration to Canada were classified as immigrants.
Health-care workers were identified based on the North American Industry Classification System (NAICS) 2002: Ambulatory Health Care Services (code
621), Hospitals (622), and Nursing and Residential Care Facilities (623).11 The classification was applied to respondents aged 15 to 75 who indicated that they
had a job in the week before their CCHS interview.
Children aged 5 or younger in household indicates if a child(ren) in this age group was (were) living in the household of respondents aged 15 to 55.
Pregnant women were identified by asking women aged 15 to 49 in non-proxy interviews if they were pregnant. It is not known if pregnant women
responding to the CCHS received the adjuvanted or unadjuvanted version of the vaccine that was recommended by WHO.12 (Adjuvants are compounds added
to vaccines that stimulate the immune response.)
Priority groups not examined in this study included those living in remote and isolated settings or communities and household contacts and care providers
of persons at high risk.8
Respondents who indicated that they had been diagnosed with diabetes, heart disease, asthma, chronic obstructive pulmonary disease, cancer, Alzheimer’s
disease or dementia, or were classified as obese (children aged 12 to 17) or class III obese (adults) were considered to have conditions that put them at high
risk for complications should they contract the H1N1 virus.13 The presence of chronic conditions was established by asking respondents if a health professional
had diagnosed them with a condition that had lasted, or was expected to last, at least six months. Interviewers read a list of conditions.
Body mass index (BMI) was calculated by dividing self-reported weight in kilograms by the square of self-reported height in metres. Adults aged 18 or older
with a BMI of 40 or more were classified as obese class III; children aged 12 to 17 were identified as obese according to the age- and sex-specific BMI cut-points
defined by Cole et al.14
The CCHS does not determine the presence of kidney disease, blood disorders, liver disease or AIDS, each of which was considered to increase the risk
of complications from H1N1.13 People with neurological disorders were also at greater risk, but the only disease in this category on the CCHS was Alzheimer’s
disease or dementia. People with weakened immune systems, for example, those taking cancer drugs, were also at greater risk; the CCHS could identify people
who reported that they had cancer, but not if they were taking cancer drugs.
Respondents who indicated that they had ever received a seasonal flu shot were asked when they had last done so: less than 1 year ago; 1 to 2 years ago;
2 years ago or more; and never.
Having a regular family doctor was determined with the question, “Do you have a regular family doctor?”
the end of January 2010 indicate lower
rates for Americans: 37% of 6-month
to 17-year-olds and 20% of adults.15
The percentage of Canadians vaccinated
for H1N1 exceeded the percentage
who typically get the seasonal flu shot
(32% in 2007 and 2008).16 By contrast,
American adults were more likely to have
been vaccinated against seasonal (39%)
than H1N1 influenza (20%) during the
2009/2010 flu season.17
The percentage vaccinated for H1N1
surpassed the national figure (41%) in six
provinces: Newfoundland and Labrador
(69%), Prince Edward Island (62%),
Nova Scotia (58%), New Brunswick
(62%), Quebec (56%) and Saskatchewan
(46%) (Figure 1, Table 1). In British
Columbia (36%), Alberta (37%),
Manitoba (37%) and Ontario (32%),
percentages were below the national
level.
Socio-demographic
characteristics
In Canada, females were more likely
than males to report having had an H1N1
flu shot—45% versus 37% (Table 1).
By contrast, in Australia,18 Greece19 and
France,20 women were less likely than
men to report that they intended to get
the H1N1vaccination, while studies in
the Netherlands21 and Malaysia22 found
Statistics Canada, Catalogue no. 82-003-XPE • Health Reports, Vol. 21, no. 4, December 2010
H1N1 vaccination • Health matters
65
Table 1
Percentage vaccinated for H1N1, by selected characteristics, Canada excluding territories, 2010
Both sexes
Characteristic
Total
Males
95%
confidence
interval
Females
95%
confidence
interval
Number
’000
%
from
to
Number
’000
%
from
to
Number
’000
95%
confidence
interval
%
from
to
11,609
41.3
40.2
42.4
5,141
37.1
35.6
38.7
6,468
45.4*
43.9
46.8
Age group
12 to 19
20 to 44
45 to 64
65 to 84
85 or older
1,200
3,673
4,193
2,326
217
37.0‡
32.2‡
45.2‡
60.9‡
62.1‡
34.1
30.6
43.0
58.7
56.3
39.8
33.8
47.4
63.1
68.0
586
1,542
1,891
1,053
70
35.6
26.9‡
41.0‡
60.7‡
61.8‡
31.7
24.6
37.8
57.5
51.6
39.5
29.1
44.2
64.0
72.0
614
2,131
2,302
1,273
148
38.3‡
37.6*‡
49.4*‡
61.0‡
62.3‡
34.2
35.2
46.5
58.2
54.9
42.5
40.0
52.2
63.8
69.8
Marital status (age 25 or older)
Married/Common-law†
Widowed/Separated/Divorced
Single
7,232
1,609
1,086
45.5
48.3
32.7‡
43.9
45.5
29.8
47.2
51.1
35.7
3,454
456
467
42.3
43.5
26.1‡
40.1
39.1
22.1
44.6
47.9
30.1
3,778
1,153
619
48.9*
50.6*
40.4*‡
46.7
47.0
36.2
51.1
54.1
44.6
Highest level of household education
Less than secondary graduation†
Secondary graduation
Some postsecondary
Postsecondary graduation
865
1,007
479
8,477
49.9
36.7‡
32.7‡
42.3‡
46.7
33.7
28.5
40.9
53.1
39.7
36.9
43.6
345
412
174
3,850
46.6
31.0‡
26.5‡
38.7‡
41.9
26.9
21.3
36.8
51.3
35.1
31.7
40.6
520
595
305
4,627
52.4
42.1*‡
37.7*‡
45.8*‡
48.1
37.9
31.0
43.9
56.7
46.3
44.5
47.6
Immigrant status
Immigrant
Non-immigrant†
2,410
8,928
37.6‡
42.4
35.0
41.3
40.3
43.6
1,084
3,924
34.6
37.8
30.9
36.2
38.2
39.5
1,326
5,004
40.6*‡
46.9*
37.0
45.3
44.1
48.5
Health care worker (ages 15 to 75)
Yes
No†
1,101
5,200
65.9‡
34.8
60.8
33.3
70.9
36.3
196
2,780
62.8‡
32.9
49.2
30.9
76.4
34.9
905
2,420
66.6‡
37.3*
61.2
35.0
71.9
39.5
Children 5 or younger in household (ages 15 to 55)
Yes
No†
1,405
5,064
44.0‡
32.9
40.7
31.4
47.3
34.4
605
2,217
39.3‡
28.4
34.3
26.4
44.3
30.4
800
2,846
48.4*‡
37.6*
43.9
35.4
52.8
39.8
…
…
…
…
…
…
…
…
…
…
…
…
…
…
…
…
129
2,907
47.2
37.8
37.4
35.6
39.9
57.0
High risk for complications§
Yes
No†
3,142
8,110
54.8‡
37.8
52.6
36.6
57.1
39.0
1,455
3,616
51.2‡
33.4
47.7
31.7
54.6
35.2
1,687
4,494
58.5*‡
42.2*
55.6
40.5
61.5
43.8
Seasonal flu shot
Less than 1 year ago
1 to less than 2 years ago
2 or more years ago
Never
5,105
1,341
810
4,258
76.2‡
50.3‡
23.1‡
28.3‡
74.3
46.7
20.2
26.9
78.1
53.8
25.9
29.8
2,222
585
349
1,942
75.6‡
48.0‡
19.9‡
24.8‡
72.6
42.7
15.9
22.9
78.7
53.3
24.0
26.7
2,883
756
462
2,316
76.6‡
52.2‡
26.1*‡
32.2*‡
74.4
47.5
22.2
30.0
78.8
56.8
30.1
34.4
10,503
1,101
43.9‡
26.4
42.7
24.1
45.1
28.7
4,530
610
40.4‡
23.3
38.6
20.2
42.2
26.4
5,973
491
47.1*‡
31.7*
45.5
27.5
48.6
35.8
301
75
455
384
3,678
3,531
356
377
1,103
1,347
69.2‡
62.3‡
57.9‡
61.8‡
55.5‡
32.2‡
37.2‡
46.4‡
37.1‡
35.6‡
63.8
56.3
53.8
57.5
53.2
30.3
33.2
42.5
33.9
32.8
74.6
68.3
62.1
66.1
57.8
34.0
41.2
50.4
40.2
38.4
131
32
198
168
1,640
1,540
171
168
470
622
63.5‡
55.9‡
52.2‡
55.5‡
50.3‡
28.7‡
36.6
41.6
30.7‡
33.3‡
55.4
46.5
46.4
48.9
46.7
26.1
30.7
37.1
26.7
29.4
71.5
65.2
58.0
62.2
54.0
31.3
42.6
46.2
34.7
37.2
170
43
258
216
2,038
1,991
185
209
633
725
74.4*‡
68.2*‡
63.3*‡
67.8*‡
60.6*‡
35.5*‡
37.7‡
51.2*
43.8*
37.9‡
68.5
60.5
57.2
62.5
57.5
32.9
31.4
44.8
39.0
34.0
80.2
76.0
69.3
73.0
63.6
38.0
44.0
57.6
48.6
41.8
Pregnant woman (ages 15 to 49)
Yes
No†
Regular family doctor
Yes
No†
Province
Newfoundland and Labrador
Prince Edward Island
Nova Scotia
New Brunswick
Quebec
Ontario
Manitoba
Saskatchewan
Alberta
British Columbia
†
reference category
* significantly different from estimate for males (p<0.05)
‡
significantly different from estimate for reference category (p<0.05); where reference category not indicated, estimate compared with Total
§
respondents with chronic conditions that could put them at high risk for complications from H1N1 virus: heart disease, diabetes, asthma, chronic obstructive pulmonary disease, Alzheimer’s or dementia,
cancer, any obesity for ages 12 to 17 and obesity class III for adults 18 or older
... not applicable
Source: 2010 Canadian Community Health Survey, partial content file January to April 2010.
66
Health Reports, Vol. 21, no. 4, December 2010 • Statistics Canada, Catalogue no. 82-003-XPE
H1N1 vaccination • Health matters
Figure 1
Percentage vaccinated for H1N1, by province, household population aged 12 or
older, Canada excluding territories, 2010
Canada
41
Newfoundland and Labrador
69*
Prince Edward Island
62*
Nova Scotia
58*
New Brunswick
62*
Quebec
Ontario
Manitoba
56*
32*
37*
Saskatchewan
Alberta
British Columbia
46*
37*
36*
* significantly different from estimate for Canada (p<0.05)
Source: 2010 Canadian Community Health Survey, partial content file January to April 2010.
no significant differences between the
sexes in intentions to be vaccinated.
However, intentions may not reflect
ultimate behaviour and could change
during a pandemic or be influenced
by cultural issues, media coverage, or
vaccine promotion campaigns.19,22
Compared with seasonal influenza,2,23,24
the H1N1 virus affected a much younger
age group. Possible reasons include preexisting immunity in older people due
to prior exposure to H1N1 strains, or
less contact with younger age groups.2,25
Nonetheless, the age pattern of H1N1
vaccination paralleled that of the seasonal
flu shot,16,26-28 with
the percentage
immunized generally rising with age: an
estimated 45% at ages 45 to 64 and just
over 60% at age 65 or older. To some
extent, this may be because older people
were more likely than younger age
groups to have chronic conditions that
could put them at risk for complications
from H1N1 (data not shown).
Single people were less likely to have
been vaccinated than were people with
a partner, an association that persisted
even when the generally younger age
distribution of single people was taken
into account (data not shown).
Residents of households where no
member had graduated from secondary
school were more likely to have been
vaccinated (50%) than were those in
households where the level of educational
attainment was higher. However, the
apparent association between education
and H1N1 vaccination did not persist
in multivariate analysis controlling for
socio-demographic, priority group and
health service variables (data not shown).
Immigrants were less likely than nonimmigrants to have been vaccinated:
38% versus 42%.
Priority groups
While the Government of Canada
obtained enough H1N1 vaccine for all
Canadians, certain populations were
given priority for early immunization.7,13
The priority groups that could be
assessed with CCHS data were healthcare workers, children aged 6 months
to 5 years, pregnant women, and people
with certain chronic conditions.
Vaccination of health-care workers
helps reduce transmission of the virus
to patients at risk of complications from
influenza.29,30 Health-care workers were
nearly twice as likely as other Canadians
to have had an H1N1 shot: 66% versus
35% (Table 1). In the United States,
the percentage of health-care workers
vaccinated was much lower, at 37%.31
Although children aged 6 months
through 5 years were not covered by
the CCHS, it was possible to identify
respondents who lived in a household
with children in this age range. Such
respondents were more likely to have
received the H1N1 vaccine than were
those who did not live with young
children (44% versus 33%) (Table 1).
Similarly, a French study20 found that
the presence of a child in the household
was associated with greater acceptability
of the H1N1 vaccine, compared with
households with no child. The French
study also found that only a small
percentage (4%) of parents who stated
that they would accept the H1N1
vaccination for themselves would refuse
it for their children. If this relationship
prevails in Canada, the majority of
people with children younger than 5
years in the household who received the
H1N1 vaccine themselves would have
also ensured their young children were
vaccinated.
While the percentage of pregnant
women vaccinated against the H1N1
virus exceeded the percentage for women
who were not pregnant (47% versus
38%), the difference was not statistically
significant.
The presence of chronic conditions
(see The data) increases the risk of
complications from H1N1 influenza.14
People with such conditions were more
likely to have been vaccinated than were
those without them (55% versus 38%).
Health care use
People who get annual flu shots or
who have a regular doctor may have
health-care attitudes and practices
that predispose them to be vaccinated
Statistics Canada, Catalogue no. 82-003-XPE • Health Reports, Vol. 21, no. 4, December 2010
H1N1 vaccination • Health matters
against the H1N1 virus. In fact, 76% of
Canadians who had had the seasonal flu
shot within the last year, and half (50%)
of those who had done so one or two
years earlier, had the H1N1 vaccine; this
compared with 23% of those whose last
flu shot had been more than two years
earlier, and 28% of those who had never
had a flu shot.
About four in ten (44%) Canadians
with a regular family doctor were
vaccinated, compared with 26% of
those without a regular doctor. It is not
known if respondents sought the advice
of their doctors about the H1N1 vaccine.
However, a survey of Canadian family
physicians and paediatricians estimated
that 75% of them intended to recommend
the vaccine to their patients.32
Why not?
The majority of Canadians aged 12 or
older―59% or 16.5 million―did not get
vaccinated against the H1N1 virus. The
most frequent reason was “did not think it
was necessary,” cited by 74% of those not
vaccinated (Table 2). This is consistent
with results of a small survey conducted
by the Strategic Counsel,33 which found
that 67% of Canadians were not worried
that they would catch the H1N1 virus,
and that 78% believed that the media
had exaggerated the threat. An EKOS
survey found that 53% of Canadians
believed that the level of concern about
H1N1 was exaggerated, given the level
of risk.34 Studies of attitudes in other
countries also found that the belief that
the illness did not pose a serious threat35
or that vaccination was not necessary18,36
were leading reasons for not intending to
be vaccinated.
Males were more likely than females
to give “did not think it was necessary”
as a reason for not getting the H1N1
vaccine (76% versus 73%). At ages
85 or older, this reason was cited by a
smaller percentage of people: 60% (data
not shown). The percentages of the nonvaccinated who said that they did not
think that vaccination was necessary
ranged from about two-thirds in Nova
Scotia, New Brunswick and Manitoba to
80% in Quebec (data not shown).
“Have not gotten around to it yet”
was the second most common reason for
not being vaccinated, reported by 13%
of Canadians who did not get the H1N1
shot.
Males were more likely than
females to give this reason: 14% versus
11%.
Fear was cited as a reason for not being
vaccinated by 7% of those who did not
receive the H1N1 vaccination. Women
were more likely than men to report fear
(9% versus 5%). Although the nature of
67
the fear was not specified, studies from
other countries found concerns about
safety and side-effects.17-20,35,37-39
Relatively few people who were not
vaccinated (3% or less) cited access
problems (for example, not available
at time required, not available in area,
respondent did not know where to go),
their doctor advising them they did
not need it, long wait times, a previous
bad reaction, personal barriers (family
responsibilities, being unable to leave
the house because of a health problem, or
transportation problems) (Table 2).
Concluding remarks
The information in this article about
who did and did not get vaccinated
against H1N1 will aid in the evaluation
of the program, support public health
planning and help target messages about
vaccination in the event of another
pandemic. Province of residence,
socio-demographic
characteristics,
belonging to a priority group, and
health service factors were associated
with the likelihood of receiving the
H1N1 vaccination. As in other studies,
the belief that the vaccination was not
necessary was the most common reason
for non-vaccination. ■
Table 2
Reasons for not getting H1N1 vaccination, household population aged 12 or older who were not vaccinated, Canada
excluding territories, 2010
Both sexes
Reason
Did not think it was necessary
Have not gotten around to it
Fear
Access problems
Doctor did not think it was necessary
Waiting time too long
Bad reaction to previous flu shot
Personal barriers
Other
Males
95%
confidence
interval
Number
’000
%
from
to
12,137
2,088
1,067
555
385
347
342
186
501
74.2
12.8
6.5
3.4
2.4
2.1
2.1
1.1
3.1
72.8
11.7
5.8
2.9
1.9
1.7
1.7
0.9
2.5
75.6
13.8
7.3
3.9
2.8
2.6
2.5
1.4
3.6
* significantly different from estimate for males (p<0.05)
E
use with caution (coefficient of variation 16.6% to 33.3%)
Note: Respondents could give more than one reason.
Source: 2010 Canadian Community Health Survey, partial content file January to April 2010.
Number
’000
6,525
1,208
413
290
154
228
119E
81E
247
Females
95%
confidence
interval
%
from
to
Number
’000
75.7
14.0
4.8
3.4
1.8
2.7
1.4E
0.9E
2.9
73.8
12.5
3.8
2.6
1.2
1.9
0.9
0.6
2.0
77.7
15.6
5.7
4.1
2.4
3.4
1.9
1.3
3.7
5,612
879
654
265
231
119
223
105
255
95%
confidence
interval
%
from
to
72.5*
11.4*
8.5*
3.4
3.0*
1.5*
2.9*
1.4
3.3
70.6
10.0
7.4
2.7
2.3
1.1
2.1
0.9
2.6
74.4
12.7
9.6
4.2
3.6
2.0
3.7
1.8
4.0
68
Health Reports, Vol. 21, no. 4, December 2010 • Statistics Canada, Catalogue no. 82-003-XPE
H1N1 vaccination • Health matters
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E L E C T R O N I C P U B L I C AT I O N S
AVA I L A B L E AT
w w w. s t a t c a n . g c . c a
Statistics Canada, Catalogue no. 82-003-XPE • Health Reports, Vol. 21, no. 4, December 2010
Combining nutrient intake from food/beverages and vitamin/mineral supplements • Methodological insights
71
Combining nutrient intake from
food/beverages and vitamin/mineral
supplements
by Didier Garriguet
Abstract
Background
To calculate total intake of a nutrient and estimate
inadequate intake for a population, the amounts
derived from food/beverages and from vitamin/
mineral supplements must be combined. The two
methods Statistics Canada has suggested present
problems of interpretation.
Data and methods
Data collected from 34,386 respondents
to the 2004 Canadian Community Health
Survey―Nutrition were used to compare four
methods of combining nutrient intake from food/
beverages and vitamin/mineral supplements:
adding average intake from supplements to the
24-hour food/beverage recall and estimating
the usual distribution in the population (Method
1); estimating usual individual intake from food/
beverages and adding intake from supplements
(Method 2); and dividing the population into
supplement users and non-users and applying
Method 1 or Method 2 and combining the
estimates based on the percentages of users and
non-users (Methods 3 and 4).
Results
Interpretation problems arise with Methods 1 and
2; for example, the percentage of the population
with inadequate intake of vitamin C and folate
equivalents falls outside the expected minimummaximum range. These interpretation problems
are not observed with Methods 3 and 4.
Interpretation
Interpretation problems that may arise in
combining food and supplement intake of a given
nutrient are overcome if the population is divided
into supplement users and non-users before
Method 1 or Method 2 is applied.
Keywords
nutrition surveys, 24-hour dietary recall, vitamin
and mineral supplements, usual intake
Author
Didier Garriguet (1-613-951-7187; Didier.
[email protected]) is with the Health
Analysis Division at Statistics Canada, Ottawa,
Ontario, K1A 0T6.
T
he 2004 Canadian Community Health Survey
(CCHS)―Nutrition was the first in more than
30 years to study Canadians’ eating habits. One
of the goals was to determine total usual intake of
selected nutrients. To that end, the CCHS collected
information about food and beverage consumption,
based on a 24-hour recall.
To calculate the usual distribution of
intake of a nutrient in a population or to
estimate the percentage of people above
or below certain thresholds, withinperson variations must be taken into
account.1 This is because what people
eat and drink varies from day to day. If
two or more dietary recalls are available
for at least a subsample of the population,
the daily distribution of a nutrient in
the entire population can be adjusted
with a computer application such as
the Software for Intake Distribution
Estimation (SIDE)2,3 to derive usual
intake. With the data collected in the
CCHS, Statistics Canada and Health
Canada produced usual intake from
food/beverages for an extensive array of
nutrients.4-6
However, as well as from food/
beverages, many nutrients, notably
vitamins and minerals, are derived
from supplements. Thus, estimates of
total consumption of any nutrient must
include supplement intake.
Consumption of vitamin/mineral
supplements was not part of the CCHS
24-hour dietary recall. This information
was obtained from questions about
consumption frequency during the
past month, the aim of which was to
directly estimate usual intake. However,
calculations of usual intake of any
nutrient from food/beverages must be
derived from daily, not monthly, intake.
Statistics Canada has suggested
two ways to combine nutrient intake
from food/beverages with that from
supplements.7
The first transforms
vitamin/mineral supplement intake
into daily consumption using the
daily average and assumes no withinindividual variation, adds this to daily
intake from food/beverages, and derives
total usual intake of the nutrient. For the
second method, usual intake distribution
from food/beverages (derived from daily
consumption) is added to usual intake
of supplements (derived from monthly
consumption).
72
Health Reports, Vol. 21, no. 4, December 2010 • Statistics Canada, Catalogue no. 82-003-XPE
Combining nutrient intake from food/beverages and vitamin/mineral supplements • Methodological insights
The analysis in this study demonstrates
that these two methods of combining
nutrient intake from food/beverages
and from supplements can create
interpretation problems, for example, in
estimating the prevalence of inadequacy.
Two alternatives are proposed, based on
partitioning the data between supplement
users and non-users. Finally, the four
methods are compared.
Data source
The 2004 CCHS was designed to gather
data about the household population’s
food/beverage consumption and nutrient
intake. The survey excluded members
of the regular Canadian Forces; residents
of the three territories, Indian reserves,
institutions and some remote areas;
and all residents (military and civilian)
of Canadian Forces bases. A detailed
description of the survey design, sample
and interview procedures is available in a
published report.8
The 2004 CCHS estimated food/
beverage consumption with 24-hour
dietary recalls, using the five-step
automated multiple-pass method9,10 to
help respondents remember what and
how much they ate and drank the previous
day. A total of 35,107 people responded
to an initial recall, and a subsample of
10,786 took part in a second recall three
to ten days later. The response rates were
76.5% and 72.8%, respectively.
This study pertains to people aged
1 or older. Children younger than 1
(288), pregnant women (175), nursing
women (92), breastfeeding children
(104), and respondents with no dietary
intake (16) or invalid dietary intake (45)
were excluded from the analysis. A total
of 34,386 people were included in the
study, 10,591 of whom responded to the
second 24-hour dietary recall.
Use of vitamin/mineral supplements
was not part of the dietary recall.
Instead, respondents were asked: “In the
past month, did you take any vitamins
or minerals?” If so, they were asked
to get the supplement containers from
which the drug identification number
or product name and concentration of
main ingredients could be obtained. The
interviewer then asked: “In the past
month, how often did you usually take
this supplement?”, and if not daily, the
interviewer asked: “On the days that you
took it, how many times did you usually
take this supplement?”
“How many
pills or tablets, capsules or teaspoons did
you usually take each time?” was asked
to obtain an estimate of the quantities
consumed. Based on answers to these
questions, variables were derived
indicating the number of days per month
that supplements were taken and the
average quantity consumed per day.
More information about these derived
variables is available in the survey
documentation11
The nutrient content of food and
beverages reported in the recalls was
derived from Health Canada’s Canadian
Nutrient File (Supplement 2001b).12 The
composition of supplements was taken
from the September 2003 Drug Product
Database (DPD)13 in the case of drug
identification numbers listed at the time
of collection, and from the spring 2005
DPD in the case of drug identification
numbers that were missing or incorrect at
the time of collection.
Methods proposed by Statistics
Canada
After an examination of various means
that have been used to combine nutrient
intake from food and supplements and to
estimate the percentage of the population
below a given threshold,1,14,15 Statistics
Canada suggested two methods:
Method 1 (add, shrink)
● Add the average intake of the
selected nutrient from vitamin and
mineral supplements to the first 24hour dietary recall, and if available,
to the second recall.
● Adjust the first dietary recall with
the second using SIDE.2,3
● Calculate the percentage of the
population whose total intake of
the selected nutrient is below a
given threshold using the estimated
average requirement (EAR) cut-off
method.
Method 2 (shrink, add)
● Calculate usual individual dietary
intake of the selected nutrient based
on the two dietary recalls using
SIDE.2,3
● Add the average intake of the
selected nutrient from supplements.
● Calculate the percentage of the
population with total intake of the
selected nutrient below a given
threshold, such as the EAR.
SIDE produces a usual intake
distribution based on back-transformed
Blom scores that represent a
perfect theoretical normal distribution
(Method 1), and the empirical distribution
based on individual shrunken means
(Method 2). Even if applied only to
food sources, these estimates will differ.
Method 2 may be more robust to the
assumption of perfect normality of the
usual intake distribution, but at the cost
of being more variable than Method 1,
especially in the tails of the distribution.
Estimates
of
vitamin/mineral
supplement consumption represent
the long-run average, or usual average
intake. It is used as is in Method 2. For
Method 1, within-individual variation
is assumed to be null, and therefore,
Table 1
Percentage distribution of frequency
of use of vitamin/mineral supplements
in past month, household population
aged 1 or older who used supplement,
Canada excluding territories, 2004
Days consumed
in past month
Supplement
Vitamin C
Vitamin D
Calcium
Thiamin
Riboflavin
Vitamin B6
Vitamin B12
Folic acid
Magnesium
Zinc
Phosphore
Potassium
30 or 31 20 to 29 10 to 19 1 to 9
80.7
83.9
84.8
82.2
82.4
82.2
82.0
82.5
85.9
85.7
82.5
85.8
%
2.3
2.2
2.2
2.5
2.5
2.5
2.4
2.5
2.0
2.1
2.5
2.3
7.7
7.0
6.7
7.8
7.7
7.7
7.7
7.7
6.4
6.4
7.5
6.3
Source: Canadian Community Health Survey - Nutrition,
detailed vitamins and minerals file, 2004.
9.3
6.9
6.3
7.5
7.5
7.5
7.8
7.3
5.7
5.8
7.5
5.6
Statistics Canada, Catalogue no. 82-003-XPE • Health Reports, Vol. 21, no. 4, December 2010
Combining nutrient intake from food/beverages and vitamin/mineral supplements • Methodological insights
for respondents who reported taking
supplements in the past month, each
recall is assumed to have the same
average supplement consumption on
both days. Because more than 80% of
people who took common supplements
did so daily (Table 1), that assumption is
reasonable. In fact, a simulation of daily
intake based on the actual frequency
of supplement consumption reveals
only minor differences from results for
Method 1 (data not shown).
The data were weighted to represent
the Canadian population. The bootstrap
method16-18 was used to calculate
standard errors and confidence intervals.
The statistical significance level was set
at 0.05.
Interpretation problems with
Methods 1 and 2
Each method of combining intake of a
selected nutrient from food/beverages
and from supplements has expected
minimum and maximum values for the
estimate of the prevalence of inadequate
intake.
Maximum value
The expected maximum value is based
on the fact that adding supplements to the
diet cannot change the percentage of the
population with inadequate intake of the
selected nutrient from food alone.
The maximum can be estimated with
Method 1 or Method 2, although it is
reasonable to use the same method to
calculate the maximum and total usual
intake. In addition, a single distribution
for supplement users and non-users or
separate distributions can be assumed.
Methods 1 and 2, however, are based on
a single distribution.
Minimum value
The expected minimum value of the
prevalence of inadequate intake of a
selected nutrient is based on the fact that
adding supplements to total intake cannot
change the percentage of supplement
non-users whose intake of that nutrient is
inadequate.
The minimum value of inadequate
intake can be estimated with Methods 1 or
2, but it relies only on the the distribution
of supplement non-users. The estimate of
the minimum value of inadequate intake
is based on the assumption that no one
who takes the supplement has inadequate
intake of that nutrient (that is, everyone
who takes it has adequate intake).
Vitamin C
Vitamin C is the supplement most
commonly taken by Canadians,
either alone or as an ingredient of
other supplements (data not shown).
Depending on their age and sex, the
percentage of Canadians who take
vitamin C supplements ranges from
about 20% to more than 40% (Table 2).
However, substantial shares of the
population have relatively low total
intake of vitamin C. For example, based
on Method 1, an estimated 13.2% of men
aged 19 to 30 had intake below the the
estimated average requirement (EAR)
(single distribution, data not shown).
Logically, adding supplements to total
intake should not increase the percentage
of this group below the EAR. Assuming
separate distributions for supplement
users and non-users yields a maximum of
13.1% with inadequate vitamin C intake
(Table 3). Among supplement non-users
(74.9% of the men in this age group),
13.3% had inadequate vitamin C intake.
The minimum value of the estimate of
the percentage with inadequate intake is
then set at 9.9%.
Table 2
Prevalence of use of supplements
containing vitamin C, by age group
and sex, household population
aged 1 or older, Canada excluding
territories, 2004
Age group
Both
sexes
1 to 3
4 to 8
9 to 13
14 to 18
19 to 30
31 to 50
51 to 70
71 or older
36.2
43.7
...
...
...
...
...
...
Male Female
%
...
...
...
...
31.9
30.4
20.9
24.2
25.1
29.2
24.7
34.7
31.9
37.4
31.6
38.1
... not applicable
Source: Canadian Community Health Survey - Nutrition, 2004.
73
If Method 2 is used to set the limits
for the prevalence of inadequate vitamin
C intake, the maximum values are
14.2% assuming a single distribution
(data not shown) and 13.8% assuming
separate distributions; the minimum
value is 10.8% (Table 3). Although
there are few differences between the
minimum and maximum values using
a single or separate distributions, an
advantage of separate distributions is that
the maximum will always exceed the
minimum.
For analytical purposes, it is useful to
determine if the 95% confidence interval
for the estimate of the percentage of the
population with inadequate intake falls
outside the range defined by the expected
minimum and maximum values. But
even point estimates falling outside
this range can create interpretation
difficulties. Since the expected minimum
and maximum values are also estimates,
they have standard errors and confidence
intervals. For the purpose of comparison,
they will be treated as point estimates.
When Method 1 is used to combine
intake from food/beverages and
supplements, the 95% confidence
intervals of the estimates of the
prevalence of inadequate vitamin C
intake among teenagers (14 to 18) and
young adult women (19 to 30) are outside
the expected minimum-maximum value
range, clearly presenting an interpretation
problem (Table 3). Three other point
estimates fall outside the range, although
their confidence intervals overlap it.
While these last estimates may not be
statistically different, questions about
their interpretation still arise.
When Method 2 is used to combine
vitamin C from food/beverages and
supplements, none of the 95% confidence
intervals for the prevalence of inadequacy
is outside the expected minimummaximum value range, but seven of the
10 publishable point estimates fall below
this range, again raising questions of
interpretation.
The distribution of usual intake
in the total population is based on
average intake and between-individual
variation.
Total variance for daily
74
Health Reports, Vol. 21, no. 4, December 2010 • Statistics Canada, Catalogue no. 82-003-XPE
Combining nutrient intake from food/beverages and vitamin/mineral supplements • Methodological insights
Table 3
Prevalence of vitamin C intake below estimated average requirement (EAR)
using Method 1 and Method 2 for combining intake from food/beverages and
supplements, by age group and sex, household population aged 1 or older,
Canada excluding territories, 2004
Below EAR
Expected values
for estimate of
% of population
Method 1 (add, shrink)
1 to 3 (both sexes)
4 to 8 (both sexes)
9 to 13
Males
Females
14 to 18
Males
Females
19 to 30
Men
Women
31 to 50
Men
Women
51 to 70
Men
Women
71 or older
Men
Women
Method 2 (shrink, add)
1 to 3 (both sexes)
4 to 8 (both sexes)
9 to 13
Males
Females
14 to 18
Males
Females
19 to 30
Men
Women
31 to 50
Men
Women
51 to 70
Men
Women
71 or older
Men
Women
95%
confidence
interval
Minimum
Maximum
%
from
to
F
F
F
F
F
F
…
…
…
…
F
F
F
F
2.5E
3.3E
1.5
1.9
3.6
4.7
6.0E
4.8E
7.1E
5.6E
11.2†
9.5†
8.6
7.2
13.8
11.7
9.9E
10.4E
13.1E
10.7E
14.7‡
16.3†
11.0
13.0
18.4
19.6
18.5
12.8
23.5
19.7
22.6
16.0
19.3
13.4
25.9
18.5
18.5
11.4
24.8
14.5
20.5
16.0‡
17.8
13.6
23.2
18.3
25.8
15.2
32.7
20.4
24.6‡
18.3
20.7
15.8
28.5
20.7
F
F
F
F
F
F
…
…
…
…
F
F
F
F
F
0.9E*
…
0.0
…
1.8
6.9E†*
4.5E†*
4.2
2.0
9.6
7.0
8.5E
4.6E
10.0E
5.4E
10.8E
10.5E
13.8E
10.6E
11.4E
8.5†*
6.0
4.2
16.7
12.8
18.8
13.4
23.8
20.3
19.1
14.7
14.1
11.3
24.1
18.1
18.5
11.6
25.4
14.5
17.9†
10.1†*
14.5
7.5
21.2
12.7
25.1
15.1
33.1
20.2
23.8†
13.2†*
19.3
10.2
28.4
16.2
confidence interval outside minimum-maximum value interval
point estimate outside minimum-maximum value interval
* significantly different from estimate for Method 1
E
use with caution (coefficient of variation 16.6% to 33.3%)
F too unreliable to be published
... not applicable
Notes: Minimum and maximum values estimated with Method 1 using separate distributions and are combined with (1-α)*percent
below EAR from non-users plus α*percent below EAR from users, where α is percentage of supplement users. Based on
assumption that all supplement users meet EAR. For those not taking supplements, maximum value represents highest
possible percentage below EAR. Minimum and maximum values estimated with Method 2 using separate empirical
distributions that were combined.
Source: Canadian Community Health Survey - Nutrition 2004.
†
‡
intake includes between- and withinindividual variation. SIDE removes
within-individual variation by shrinking
the daily intake distribution by the ratio
of within-individual variation over the
total variation ratio. When supplements
are added to intake using Method 1, the
skew of average intake shifts to the right;
that is, the percentage of the population
with relatively high levels of intake
increases. Within-individual variation
does not change, since the same intake
from supplements is added to each recall
for supplement users. However, the total
variance changes because the average
intake of some individuals changes.
Consequently, the ratio will change
(Table 4). With a smaller shrinkage
factor, using the EAR cut-point method,
the area beneath the curve can increase
even if average intake increases. This
explains the estimates above the
maximum produced by Method 1. Even
small changes in within-individual
variation combined with different
daily intake averages and normality
transformations can lead to interpretation
problems, as seen with Method 2.
Dividing the data
In light of the potential for interpretation
problems, it is necessary to combine
nutrient intake from food/beverages
and from supplements in such a way
that estimates of the prevalence of
inadequacy fall within the expected
minimum-maximum range. Methods
1 and 2 could be extended by using
separate distributions.
Method 3 (divide, add, shrink):
● Divide the population according
to whether they obtain the selected
nutrient from supplements.
● Using SIDE and the EAR cut-point
method, estimate the percentage
of supplement non-users whose
intake of the selected nutrient from
food/beverages is below a given
threshold.
● Using Method 1, estimate the
percentage of supplement users
whose intake of the nutrient
from both food/beverages and
Statistics Canada, Catalogue no. 82-003-XPE • Health Reports, Vol. 21, no. 4, December 2010
75
Combining nutrient intake from food/beverages and vitamin/mineral supplements • Methodological insights
Table 4
Ratio of within-individual variance over total variance for vitamin C intake, by age group, sex and use of supplements,
household population aged 1 or older, Canada excluding territories, 2004
Vitamin C intake from food/beverages
and supplements
Vitamin C intake from food/beverages only
Supplement
non-users
One distribution
Age group/
Sex
1 to 3 (both sexes)
4 to 8 (both sexes)
9 to 13
Males
Females
14 to 18
Males
Females
19 to 30
Men
Women
31 to 50
Men
Women
51 to 70
Men
Women
71 or older
Men
Women
Ratio
Standard
error
0.53
0.69
0.03
0.05
0.68
0.72
Supplement
users
Total population
(Method 1)
Supplement
users
Standard
error
Ratio
Standard
error
Ratio
Standard
error
Ratio
Standard
error
0.53
0.81*
0.04
0.05
0.52
0.57
0.06
0.07
0.42†
0.54†
0.03
0.03
0.34†
0.41†
0.05
0.05
0.03
0.03
0.69
0.71
0.04
0.04
0.66
0.72
0.06
0.06
0.48†
0.49†
0.03
0.03
0.27†
0.30†
0.04
0.05
0.66
0.67
0.03
0.03
0.67
0.69
0.03
0.04
0.64
0.67
0.07
0.07
0.45†
0.44†
0.02
0.03
0.20†
0.19†
0.03
0.03
0.72
0.72*
0.04
0.04
0.75
0.65*
0.04
0.04
0.65
0.88
0.09
0.07
0.49†
0.37†
0.03
0.02
0.17†
0.27†
0.04
0.03
0.61
0.53
0.04
0.03
0.64
0.56
0.05
0.04
0.55
0.49
0.08
0.05
0.36†
0.29†
0.03
0.02
0.15†
0.14†
0.04
0.03
0.58
0.61
0.03
0.03
0.60
0.59
0.03
0.03
0.55
0.67
0.07
0.05
0.31†
0.25†
0.02
0.02
0.11†
0.15†
0.03
0.02
0.51
0.53
0.03
0.02
0.54
0.52
0.04
0.03
0.49
0.54
0.07
0.04
0.27†
0.19†
0.02
0.01
0.09†
0.12†
0.03
0.02
Ratio
* significantly different from estimate for supplement users
†
significantly different from estimate for food/beverages only population in same age/sex group
Source: Canadian Community Health Survey - Nutrition 2004.
supplements is below a given
threshold.
● Calculate the combined overall
estimate of inadequate intake of the
nutrient (based on the percentages
for supplement users and non-users)
with the following formula:
P[X T < EAR] = (1 − α ) P[X SNU < EAR] + αP[X SU < EAR]
where XT represents total nutrient intake;
XSNU, supplement non-users’ nutrient
intake from food/beverages; XSU,
supplement users’ total nutrient intake;
and α, the percentage of supplement
users.
Method 4 (divide, shrink, add):
● Divide the population according
to whether they obtain the selected
nutrient from supplements.
● Using SIDE, calculate supplement
non-users’ usual individual intake
of the nutrient from food/beverages.
● Calculate supplement users’ usual
intake of the nutrient from food/
beverages; add their average intake
from supplements.
● Add the results for the two
populations and calculate the
percentage of the total population
whose total intake of the nutrient is
below a given threshold, such as the
EAR.
With Method 3, the 95% confidence
intervals for the prevalence of inadequate
vitamin C intake are not outside the
expected minimum-maximum range
for any of the 10 age/sex groups with
publishable results (Table 5). And only
for women aged 19 to 30 was the point
estimate of the prevalence of inadequate
vitamin C intake outside that range
(0.08% above the maximum). Even
with a much smaller shrinkage factor
for supplement users (Table 5), average
consumption of vitamin C including
supplements results in fewer than 3% of
the population below the EAR. Coupled
with the probability of being a consumer,
most of the combined estimates of
inadequate vitamin C intake depend on
the percentage of supplement non-users
whose intake from food/beverages is
inadequate.
With Method 4 (Table 5), by design,
every estimate of the prevalence of
inadequate vitamin C intake is equal to
or within the minimum-maximum value
range.
Comparing methods
Method 1 differs significantly from
the other three, among which there is
no statistically significant difference.
However, compared with Method 3,
Method 4 yields a more variable
prevalence of inadequate vitamin C
intake with wider 95% confidence
intervals.
Published estimates of usual intake
of vitamin C from food/beverages, as
76
Health Reports, Vol. 21, no. 4, December 2010 • Statistics Canada, Catalogue no. 82-003-XPE
Combining nutrient intake from food/beverages and vitamin/mineral supplements • Methodological insights
Table 5
Prevalence of vitamin C intake below estimated average requirement (EAR)
using Method 3 and Method 4 for combining intake from food/beverages and
supplements, by age group and sex, household population aged 1 or older,
Canada excluding territories, 2004
Below EAR
Expected values
for estimate of
% of population
Method 3 (divide, add, shrink)
1 to 3 (both sexes)
4 to 8 (both sexes)
9 to 13
Males
Females
14 to 18
Males
Females
19 to 30
Men
Women
31 to 50
Men
Women
51 to 70
Men
Women
71 or older
Men
Women
Method 4 (divide, shrink, add)
1 to 3 (both sexes)
4 to 8 (both sexes)
9 to 13
Males
Females
14 to 18
Males
Females
19 to 30
Men
Women
31 to 50
Men
Women
51 to 70
Men
Women
71 or older
Men
Women
95%
confidence
interval
Minimum
Maximum
%
from
to
F
F
F
F
F
F
…
…
…
…
F
F
F
F
F
F
…
…
…
…
6.0E
4.8E
7.1E
5.6E
6.2 E*
5.2 E*
3.4
2.7
9.1
7.7
9.9E
10.4E
13.1E
10.7E
10.5 E
10.8 E†
5.0
6.2
16.0
15.4
18.5
12.8
23.5
19.7
19.0
13.3
14.1
9.7
23.9
16.8
18.5
11.4
24.8
14.5
18.8
11.7*
15.1
8.5
22.6
14.8
25.8
15.2
32.7
20.4
26.7
15.4
22.1
12.0
31.3
18.7
F
F
F
F
F
F
…
…
…
…
F
F
F
F
F
F
…
…
…
…
8.5E
4.6E
10.0E
5.4E
8.5 E
4.6 E*
3.6
2.0
13.4
7.3
10.8E
10.5E
13.8E
10.6E
11.1 E
10.5 E*
4.7
5.9
17.4
15.0
18.8
13.4
23.8
20.3
19.2
13.6
13.1
9.8
25.3
17.4
18.5
11.6
25.4
14.5
18.7
11.7 *
15.1
8.7
22.2
14.7
25.1
15.1
33.1
20.2
25.9
15.1
21.3
11.3
30.6
19.0
†
point estimate outside minimum-maximum value interval
* significantly different from estimate for Method 1
E
use with caution (coefficient of variation 16.6% to 33.3%)
F too unreliable to be published
... not applicable
Notes: Minimum and maximum values for Method 3 estimated with Method 1 using separate distributions and are combined with
(1-α)*percent below EAR from non-users plus α*percent below EAR from users, where α is percentage of supplement users.
Based on assumption that all supplement users meet EAR. For those not taking supplements, maximum value represents
highest possible percentage below EAR. Minimum and maximum values for Method 4 estimated with Method 2 using
separate empirical distributions that were combined.
Source: Canadian Community Health Survey - Nutrition 2004.
in the Compendium of Tables,4-6 use
the EAR cut-point method to calculate
the percentage of the population
with inadequate intake based a single
distribution, thereby assuming the same
average intake and variance components
for supplement users and non-users.
Therefore, this estimate might be used
for the maximum value. In such a case,
without the differences being significant,
one estimate using Method 3 and two
estimates using Method 4 will be outside
the expected minimum-maximum value
range (data not shown).
Other nutrients
Interpretation problems are not limited
to vitamin C (Appendix Table A).
Appendix Tables B to G show estimates
for vitamin D, calcium and dietary
folate equivalents (including folic acid)
based on the four methods of combining
intake from food/beverages and from
supplements. The vitamin D (Tables
B and C) and calcium (Tables D and
E) data present the percentages of each
age/sex group below the adequate intake
(AI) level. AI is used as a cut-off, but
it does not represent the percentage of
the population with inadequate intake.
By contrast, the EAR is used for dietary
folate equivalents (Tables F and G), so
it is possible to discuss inadequate folate
intake. (A 2009 study19 demonstrated
that folate concentrations in some food
groups actually exceed what is in the
database; the calculations presented
here use an adjustment factor to estimate
dietary folate equivalents intake.)
For calcium, no interpretation
problems arise. The results obtained with
the four methods are not significantly
different, and all point estimates fall
within the expected minimum-maximum
range (Tables B and C).
For vitamin D, there are no statistically
significant differences between the four
Methods (Tables D and E). None of the
confidence intervals falls completely
outside the expected minimummaximum value range, but some are
below the minimum for Methods 1 and 2.
These interpretation problems are solved
with Methods 3 or 4.
Statistics Canada, Catalogue no. 82-003-XPE • Health Reports, Vol. 21, no. 4, December 2010
Combining nutrient intake from food/beverages and vitamin/mineral supplements • Methodological insights
For dietary folate equivalents,
Method 1 results differ from the other
three (Tables F and G). With Method
1, some confidence intervals for the
estimate of the prevalence of inadequacy
are completely outside the expected
minimum-maximum value range. With
Method 2, some point estimates fall
outside that interval, but, the confidence
intervals overlap the minimummaximum value range. Methods 3 and 4
do not have interpretation problems.
Recommendations, limitations
and conclusion
Combining nutrient intake from food/
beverages with that from supplements is
challenging. Problems can arise as early
as the survey interview stage if some
questions about supplement use were not
understood by respondents. Although
a review was carried out, it is possible
that some answers resulted in high but
plausible values for supplement use.
Those high values may account for part
of the large increase in between-person
variation.
A second challenge lies in the
attempt to combine daily intake from
food/beverages with usual intake
from supplements. However, because
more than 80% of people who took
supplements did so daily, the effect is
likely minimal. For daily supplement
intake, it would be preferable to estimate
within-individual variation. But the
interpretation problems resulting from
a large decrease in the ratio of withinindividual variation over total variation
will persist. Addressing these collectionrelated limitations will not solve the
interpretation problems.
This analysis demonstrates that
estimates of inadequate intake of
nutrients have minimum and maximum
values, outside of which values logically
should not fall. Confidence intervals for
estimates of inadequate total intake that
fall outside these expected minimummaximum ranges are hard to interpret,
and although there may be no statistical
difference, even point estimates that
fall outside these limits can create
interpretation issues.
Conclusion
The use of Method 1 to combine nutrient
intake from food/beverages with that
from supplements is not recommended,
because several confidence intervals
for the estimates of the prevalence of
inadequacy fall outside the expected
minimum-maximum
value
range.
While the 95% confidence intervals for
77
Methods 2, 3 and 4 overlap the minimummaximum values, Method 2 estimates
can fall outside the interval. Methods
3 and 4, which are based on the original
Methods 1 and 2, are easier to interpret.
This study focused on estimating
the percentage of the population whose
nutrient intake was below a certain
threshold. These methods can also
be used to calculate the percentiles of
the distribution by combining the two
distributions on a prorated basis (Method
3) or by appending the datasets and using
empirical percentiles (Method 4). ■
78
Health Reports, Vol. 21, no. 4, December 2010 • Statistics Canada, Catalogue no. 82-003-XPE
Combining nutrient intake from food/beverages and vitamin/mineral supplements • Methodological insights
References
1.
Institute of Medicine. Dietary Reference
Intakes: Applications in Dietary Assessment.
Washington DC: National Academy Press,
2000.
2.
Nusser SM, Carriquiry AL, Dodd KW, et al.
A semiparametric transformation approach
to estimating usual daily intake distributions.
Journal of the American Statistical Association
1996; 91(436): 1440-9.
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4.
Novenario MJ. User’s Guide to SIDE,
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www.card.iastate.edu/publications/DBS/
PDFFiles/96tr32.pdf. Accessed September
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National Summary Data Tables, Volume 1.
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Health Canada. Canadian Community Health
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National Summary Data Tables, Volume 2.
Ottawa: Health Canada, 2008.
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Health Canada. Canadian Community Health
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Intakes from food: Provincial, Regional and
National Summary Data Tables, Volume 3.
Ottawa: Health Canada, 2008.
7.
Statistics Canada. Canadian Community
Health Survey (CCHS): Cycle 2.2, Nutrition:
General Health Component Including Vitamin
and Mineral Supplements, and 24-hour
Dietary Recall Component, User Guide,
2008. Available at: http://www.statcan.
gc.ca/imdb-bmdi/document/5049_D24_T9_
V1-eng.pdf. Accessed February 10, 2009.
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9.
Béland Y, Dale V, Dufour J, Hamel M. The
Canadian Community Health Survey: Building
on the success from the past. Proceedings
of the American Statistical Association
Joint Statistical Meeting, Section on Survey
Research Methods, August 2005. Minneapolis:
American Statistical Association, 2005.
Moshfegh AJ, Borrud L,Perloff B, et al.
Improved method for the 24-hour dietary
recall for use in national surveys . The
FASEB Journal: Official Publication of
The Federation of American Societies for
Experimental Biology 1999; 13: A603
(Abstract).
10. Moshfegh AJ, Raper N, Ingwersen L, et al.
An improved approach to 24-hour dietary
recall methodology. Annals of Nutrition and
Metabolism 2001; 45(suppl): 156 (abstract).
11. Statistics Canada. Canadian Community
Health Survey (CCHS), Cycle 2.2, Nutrition:
General Health File (including vitamin and
mineral supplements) and 24-Hour Dietary
Recall, Derived Variables Documentation,
2008.
12. Health Canada. 2005. Canadian Nutrient File,
2005 Version. Available at: http://www.hc-sc.
gc.ca/fnan/nutrition/fiche-nutri-data/index_e.
html.
13. Health Canada. Drug Product Database.
Available at: http://www.hc-sc.gc.ca/
dhp-mps/prodpharma/databasdon/index-eng.
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disponible à l’adresse: http://www.hc-sc.gc.ca/
dhp-mps/prodpharma/databasdon/index-fra.
php, site consulté le 26 janvier 2009.
14. British Columbia Ministry of Health Services.
British Columbia Nutrition Survey: Report
on Energy and Nutrient Intakes. Victoria,
British Columbia: British Columbia Ministry
of Health Services, 2004.
15. Carriquiry AL. Estimation of usual intake
distributions of nutrients and foods. The
Journal of Nutrition 2003; 133: 601S-608S.
16. Rao JNK, Wu CFJ, Yue K. Some recent work
on resampling methods for complex surveys.
Survey Methodology (Statistics Canada,
Catalogue 12-001) 1992; 18(2): 209-17.
17. Rust KF, Rao JNK. Variance estimation for
complex surveys using replication techniques.
Statistical Methods in Medical Research 1996;
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18. Yeo D, Mantel H, Liu TP. Bootstrap variance
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Statistics Canada, Catalogue no. 82-003-XPE • Health Reports, Vol. 21, no. 4, December 2010
Combining nutrient intake from food/beverages and vitamin/mineral supplements • Methodological insights
79
Annexe
Table A
Prevalence of use of calcium, vitamin
D and dietary folate equivalents
supplements in past month, by age
group and sex, household population
aged 1 or older, Canada excluding
territories, 2004
Age group/
Sex
1 to 3 (both sexes)
4 to 8 (both sexes)
9 to 13
Males
Females
14 to 18
Males
Females
19 to 30
Men
Women
31 to 50
Men
Women
51 to 70
Men
Women
71 or older
Men
Women
Calcium
Vitamin
D
Dietary
folate
equivalents
20.7
27.7
%
34.9
40.9
30.7
38.7
16.4
15.0
24.9
23.1
24.0
22.2
13.5
14.7
14.6
16.6
13.8
15.0
18.3
23.5
19.1
22.2
17.6
22.9
19.6
33.4
18.7
30.6
19.3
29.2
28.9
49.4
27.5
45.0
26.0
31.2
27.2
46.0
28.6
43.0
25.2
28.5
Source: Canadian Community Health Survey - Nutrition 2004.
Table B
Prevalence of calcium intake below adequate intake (AI) using Method 1 and
Method 2 for combining intake from food/beverages and supplements, by
age group and sex, household population aged 1 or older, Canada excluding
territories, 2004
Below AI
Expected values
for estimate of
% of population
Minimum
Method 1 (add, shrink)
1 to 3 (both sexes)
4 to 8 (both sexes)
9 to 13
Males
Females
14 to 18
Males
Females
19 to 30
Men
Women
31 to 50
Men
Women
51 to 70
Men
Women
71 or older
Men
Women
Method 2 (shrink, add)
1 to 3 (both sexes)
4 to 8 (both sexes)
9 to 13
Males
Females
14 to 18
Males
Females
19 to 30
Men
Women
31 to 50
Men
Women
51 to 70
Men
Women
71 or older
Men
Women
95%
confidence
interval
Maximum
%
from
to
2.5 E
15.3
2.9 E
22.9
2.7 E
19.1
1.5
15.6
3.8
22.7
53.8
72.5
63.2
83.6
60.5
81.3
55.1
76.5
65.9
86.1
45.1
71.1
51.7
83.8
49.5
81.1
43.8
77.1
55.2
85.1
41.2
55.9
47.3
69.8
44.6
60.8
37.8
54.8
51.4
66.9
51.5
48.9
61.5
72.6
57.8
58.6
53.0
54.2
62.6
63.0
61.5
47.7
86.2
91.8
78.1
66.8
74.7
63.8
81.5
69.8
66.1
51.6
89.9
94.7
79.9
73.3
74.3
69.4
85.5
77.2
F
15.9
2.7 E
23.8
2.1 E
20.0
0.9
16.0
3.3
24.0
53.9
72.9
63.1
83.8
61.6
82.4
56.7
77.9
66.5
86.9
46.5
71.6
53.2
84.7
51.2
82.5
46.3
78.9
56.1
86.0
40.6
57.4
46.7
71.1
44.2
63.6
37.0
58.1
51.4
69.1
52.3
50.1
63.2
74.0
58.9
62.1
54.1
57.8
63.6
66.4
61.8
47.8
86.6
91.4
79.7
67.7
76.6
64.5
82.9
71.0
66.2
51.7
90.1
94.7
81.9
75.3
77.6
71.9
86.2
78.7
E
use with caution (coefficient of variation 16.6% to 33.3%)
F too unreliable to be published
Notes: Minimum and maximum values estimated with Method 1 using separate distributions and are combined with (1-α)*percent
below AI from supplement non-users plus α*percent below AI from users, where α is percentage of supplement users. Based
on assumption that all supplement users have intake at or above AI. Minimum and maximum values estimated with Method 2
using separate empirical distributions that were combined.
Source: Canadian Community Health Survey - Nutrition 2004.
80
Health Reports, Vol. 21, no. 4, December 2010 • Statistics Canada, Catalogue no. 82-003-XPE
Combining nutrient intake from food/beverages and vitamin/mineral supplements • Methodological insights
Table C
Prevalence of calcium intake below adequate intake (AI) using Method 3 and
Method 4 for combining intake from food/beverages and supplements, by
age group and sex, household population aged 1 or older, Canada excluding
territories, 2004
Below AI
Expected values
for estimate of
% of population
Minimum
Method 3 (divide, add, shrink)
1 to 3 (both sexes)
4 to 8 (both sexes)
9 to 13
Males
Females
14 to 18
Males
Females
19 to 30
Men
Women
31 to 50
Men
Women
51 to 70
Men
Women
71 or older
Men
Women
Method 4 (divide, shrink, add)
1 to 3 (both sexes)
4 to 8 (both sexes)
9 to 13
Males
Females
14 to 18
Males
Females
19 to 30
Men
Women
31 to 50
Men
Women
51 to 70
Men
Women
71 or older
Men
Women
95%
confidence
interval
Maximum
%
from
to
2.5 E
15.3
2.9 E
22.9
2.6 E
18.7
1.5
15.2
3.8
22.2
53.8
72.5
63.2
83.6
60.9
81.9
55.5
77.1
66.4
86.8
45.1
71.1
51.7
83.8
49.9
81.8
44.0
77.7
55.8
85.8
41.2
55.9
47.3
69.8
45.0
61.7
37.7
55.7
52.2
67.6
51.5
48.9
61.5
72.6
57.5
60.0
52.6
55.5
62.4
64.4
61.5
47.7
86.2
91.8
79.6
68.1
76.2
65.1
83.0
71.1
66.1
51.6
89.9
94.7
81.0
74.6
75.9
71.3
86.0
77.9
F
15.9
2.7 E
23.8
2.1 E
19.5
0.7
15.2
3.5
23.9
53.9
72.9
63.1
83.8
61.5
82.9
56.6
78.4
66.5
87.4
46.5
71.6
53.2
84.7
51.6
82.8
46.4
79.2
56.7
86.4
40.6
57.4
46.7
71.1
43.8
63.9
36.0
58.5
51.6
69.4
52.3
50.1
63.2
74.0
58.9
61.9
53.7
57.8
64.1
66.1
61.8
47.8
86.6
91.4
80.0
68.3
76.6
65.2
83.3
71.4
66.2
51.7
90.1
94.7
81.6
74.7
77.1
70.7
86.2
78.7
E
use with caution (coefficient of variation 16.6% to 33.3%)
F too unreliable to be published
Notes: Minimum and maximum values for Method 3 estimated with Method 1 using separate distributions and are combined with
(1-α)*percent below AI from supplement non-users plus α*percent below AI from users, where α is percentage of supplement
users. Based on assumption that all supplement users have intake at or above AI. Minimum and maximum values for Method
4 estimated with Method 2 using separate empirical distributions that were combined.
Source: Canadian Community Health Survey - Nutrition 2004.
Statistics Canada, Catalogue no. 82-003-XPE • Health Reports, Vol. 21, no. 4, December 2010
Combining nutrient intake from food/beverages and vitamin/mineral supplements • Methodological insights
Table D
Prevalence of vitamin D intake below adequate intake (AI) using Method 1
and Method 2 for combining intake from food/beverages and supplements, by
age group and sex, household population aged 1 or older, Canada excluding
territories, 2004
Below AI
Expected values
for estimate of
% of population
Method 1 (add, shrink)
1 to 3 (both sexes)
4 to 8 (both sexes)
9 to 13
Males
Females
14 to 18
Males
Females
19 to 30
Men
Women
31 to 50
Men
Women
51 to 70
Men
Women
71 or older
Men
Women
Method 2 (shrink, add)
1 to 3 (both sexes)
4 to 8 (both sexes)
9 to 13
Males
Females
14 to 18
Males
Females
19 to 30
Men
Women
31 to 50
Men
Women
51 to 70
Men
Women
71 or older
Men
Women
95%
confidence
interval
Minimum
Maximum
%
from
to
22.8
20.0
31.9
39.0
21.4 †
20.8
18.5
18.3
24.3
23.3
20.2
38.7
26.5
47.4
20.7
35.3 †
17.1
30.8
24.4
39.7
21.6
48.5
24.1
57.9
21.7
45.8 †
18.1
41.6
25.4
50.1
40.1
51.7
47.4
64.8
36.4 †
47.0 †
30.3
41.8
42.5
52.2
39.8
41.2
47.9
58.8
38.5 †
38.3 †
33.7
33.8
43.3
42.7
60.8
50.1
80.0
91.3
63.7
59.9
59.2
56.1
68.3
63.6
69.0
54.4
96.3
97.1
80.1
73.6
75.1
67.6
85.2
79.5
22.5
20.8
32.2
40.6
22.2 †
23.2
18.8
20.4
25.6
26.1
21.4
38.3
28.0
47.6
21.8
38.1 †
17.3
33.1
26.3
43.1
22.9
48.8
25.5
58.1
22.8 †
50.8
18.2
45.9
27.4
55.7
38.7
52.2
45.9
65.6
39.0
52.7
32.9
47.4
45.1
57.9
41.2
42.5
49.4
60.3
41.3
43.0
35.4
36.7
47.1
49.3
60.6
50.3
79.9
91.4
62.4
58.5
56.9
54.4
67.9
62.7
69.6
55.3
96.9
98.2
80.6
74.6
76.8
68.9
84.5
80.3
point estimate outside minimum and maximum value interval
Notes: Minimum and maximum values estimated with Method 1 using separate distributions and are combined with (1-α)*percent
below AI from supplement non-users plus α*percent below AI from users, where α is percentage of supplement users. Based
on assumption that all supplement users have intake at or above AI. Minimum and maximum values estimated with Method 2
using separate empirical distributions that were combined.
Source: Canadian Community Health Survey - Nutrition 2004.
†
81
82
Health Reports, Vol. 21, no. 4, December 2010 • Statistics Canada, Catalogue no. 82-003-XPE
Combining nutrient intake from food/beverages and vitamin/mineral supplements • Methodological insights
Table E
Prevalence of vitamin D intake below adequate intake (AI) using Method 3
and Method 4 for combining intake from food/beverages and supplements, by
age group and sex, household population aged 1 or older, Canada excluding
territories, 2004
Below AI
Expected values
for estimate of
% of population
Method 3 (divide, add, shrink)
1 to 3 (both sexes)
4 to 8 (both sexes)
9 to 13
Males
Females
14 to 18
Males
Females
19 to 30
Men
Women
31 to 50
Men
Women
51 to 70
Men
Women
71 or older
Men
Women
Method 4 (divide, shrink, add)
1 to 3 (both sexes)
4 to 8 (both sexes)
9 to 13
Males
Females
14 to 18
Males
Females
19 to 30
Men
Women
31 to 50
Men
Women
51 to 70
Men
Women
71 or older
Men
Women
95%
confidence
interval
Minimum
Maximum
%
from
to
22.8
20.0
31.9
39.0
23.1
20.4
19.5
16.9
26.6
23.9
20.2
38.7
26.5
47.4
20.3
39.1
15.5
33.3
25.1
45.0
21.6
48.5
24.1
57.9
21.9
49.6
17.4
44.5
26.3
54.7
40.1
51.7
47.4
64.8
40.4
52.6
33.7
46.6
47.0
58.5
39.8
41.2
47.9
58.8
40.2
42.3
33.8
34.8
46.5
49.8
60.8
50.1
80.0
91.3
64.9
57.6
60.1
53.1
69.7
62.2
69.0
54.4
96.3
97.1
80.1
75.9
75.7
72.1
84.4
79.8
22.5
20.8
32.2
40.6
22.9
21.7
19.4
18.3
26.4
25.2
21.4
38.3
28.0
47.6
21.8
38.9
16.5
33.5
27.1
44.2
22.9
48.8
25.5
58.1
23.2
50.1
18.3
45.3
28.1
54.9
38.7
52.2
45.9
65.6
39.4
53.0
33.4
47.6
45.3
58.4
41.2
42.5
49.4
60.3
42.1
44.0
35.6
35.8
48.5
52.2
60.6
50.3
79.9
91.4
64.0
58.1
58.8
53.5
69.3
62.7
69.6
55.3
96.9
98.2
80.4
77.0
76.5
73.3
84.2
80.7
Notes: Minimum and maximum values for Method 3 estimated with Method 1 using separate distributions and are combined with
(1-α)*percent below AI from supplement non-users plus α*percent below AI from users, where α is percentage of supplement
users. Based on assumption that all supplement users have intake at or above AI. Minimum and maximum values for Method
4 estimated with Method 2 using separate empirical distributions that were combined.
Source: Canadian Community Health Survey - Nutrition 2004.
Statistics Canada, Catalogue no. 82-003-XPE • Health Reports, Vol. 21, no. 4, December 2010
Combining nutrient intake from food/beverages and vitamin/mineral supplements • Methodological insights
Table F
Prevalence of dietary folate equivalents intake below estimated average
requirement (EAR) using Method 1 and Method 2 for combining intake from
food/beverages and supplements, by age group and sex, household population
aged 1 or older, Canada excluding territories, 2004
Below EAR
Expected values
for estimate of
% of population
Minimum
Method 1 (add, shrink)
1 to 3 (both sexes)
4 to 8 (both sexes)
9 to 13
Males
Females
14 to 18
Males
Females
19 to 30
Men
Women
31 to 50
Men
Women
51 to 70
Men
Women
71 or older
Men
Women
Method 2 (shrink, add)
1 to 3 (both sexes)
4 to 8 (both sexes)
9 to 13
Males
Females
14 to 18
Males
Females
19 to 30
Men
Women
31 to 50
Men
Women
51 to 70
Men
Women
71 or older
Men
Women
95%
confidence
interval
Maximum
%
from
to
2.7E
<3
2.7E
<3
3.1E†
<3
1.7
...
4.6
...
<3
<3
<3
<3
<3
2.9E†
...
1.5
...
4.3
<3
11.4
<3
13.1
4.1E*
14.4†
2.6
11.6
5.7
17.2
<3
8.7E
<3
9.5E
3.6E*
15.2*
2.1
12.1
5.1
18.3
F
8.3E
F
15.1E
7.9*
14.6
6.0
12.0
9.9
17.3
5.9E
10.9E
7.2E
17.8
11.1*
18.4†
8.7
15.9
13.4
20.8
13.1E
24.4
14.5E
31.5
15.9†
23.8†
11.9
20.9
19.9
26.8
F
<3
F
<3
2.0E†
<3
0.8
...
3.1
...
<3
F
<3
F
<3
<3
...
...
...
...
<3
11.7
F
13.6
F
11.3†
...
7.9
...
14.7
<3
8.3E
<3
9.0E
<3
8.0†‡
3.5
12.4
F
8.4E
F
15.4E
F
10.0E
...
5.9
...
14.0
6.3E
10.8E
7.5E
17.9
6.5E‡
13.5‡
3.5
9.9
9.6
17.2
13.8E
24.4
15.3E
31.5
11.2E†
24.6
6.0
20.0
16.5
29.1
* confidence interval outside minimum and maximum value interval
†
point estimate outside minimum and maximum value interval
‡
significantly different from estimate for Method 1
E
use with caution (coefficient of variation 16.6 to 33.3%)
<3 coefficient of variation more than 33.3%, but limits of confidence interval included within interval (0.0, 3.0)
F too unreliable to be published
... not applicable
Notes: Minimum and maximum values estimated with Method 1 using separate distributions and combined with (1-α)*percent
below EAR from supplement non-users plus α*percent below EAR from users, where α is percentage of supplement users.
Based on assumption that all supplement users meet EAR. Minimum and maximum values estimated with Method 2 using
separate empirical distributions that were combined.
Source: Canadian Community Health Survey - Nutrition 2004.
83
84
Health Reports, Vol. 21, no. 4, December 2010 • Statistics Canada, Catalogue no. 82-003-XPE
Combining nutrient intake from food/beverages and vitamin/mineral supplements • Methodological insights
Table G
Prevalence of dietary folate equivalents intake below estimated average
requirement (EAR) using Method 3 and Method 4 for combining intake from
food/beverages and supplements, by age group and sex, household population
aged 1 or older, Canada excluding territories, 2004
Below EAR
Expected values
for estimate of
% of population
Minimum
Method 3 (divide, add, shrink)
1 to 3 (both sexes)
4 to 8 (both sexes)
9 to 13
Males
Females
14 to 18
Males
Females
19 to 30
Men
Women
31 to 50
Men
Women
51 to 70
Men
Women
71 or older
Men
Women
Method 4 (divide, shrink, add)
1 to 3 (both sexes)
4 to 8 (both sexes)
9 to 13
Males
Females
14 to 18
Males
Females
19 to 30
Men
Women
31 to 50
Men
Women
51 to 70
Men
Women
71 or older
Men
Women
95%
confidence
interval
Maximum
%
from
to
2.7E
<3
2.7E
<3
2.7E
<3
1.1
...
4.3
...
<3
<3
<3
<3
<3
<3
...
...
...
...
<3
11.4
<3
13.1
<3
11.5
...
7.9
...
15.1
<3
8.7E
<3
9.5E
<3
8.8E†
...
4.2
...
13.4
F
8.3E
F
15.1E
F
8.4E†
...
4.2
...
12.7
5.9E
10.9E
7.2E
17.8
5.9E†
11.2E†
2.8
6.8
9.1
15.7
13.1E
24.4
14.5E
31.5
13.3E
24.5
7.0
18.5
19.6
30.5
F
<3
F
<3
F
<3
...
...
...
...
<3
F
<3
F
<3
F
...
...
...
...
<3
11.7
F
13.6
<3
11.7
...
8.2
...
15.2
<3
8.3E
<3
9.0E
<3
8.3E†
...
3.5
...
13.1
F
8.4E
F
15.4E
F
8.4E†
...
4.4
...
12.5
6.3E
10.8E
7.5E
17.9
6.3E†
11.1E†
2.9
6.4
9.7
15.8
13.8E
24.4
15.3E
31.5
13.9E
24.5
6.7
19.2
21.2
29.9
significantly different from estimate for Method 1
use with caution (coefficient of variation 16.6 to 33.3%)
<3 coefficient of variation more than 33.3%, but limits of confidence interval included within interval (0.0, 3.0)
F too unreliable to be published
... not applicable
Notes: Minimum and maximum values for Method 3 estimated with Method 1 using separate distributions and combined with
(1-α)*percent below EAR from supplement non-users plus α*percent below EAR from users, where α is percentage of
supplement users. Based on assumption that all supplement users meet EAR. Minimum and maximum values for Method 4
estimated with Method 2 using separate empirical distributions that were combined.
Source: Canadian Community Health Survey - Nutrition 2004.
†
E
Statistics Canada, Catalogue no. 82-003-XPE • Health Reports, Vol. 21, no. 4, December 2010
Validation of cognitive functioning categories in the Canadian Community Health Survey • Methodological insights
85
Validation of cognitive functioning
categories in the Canadian Community
Health Survey—Healthy Aging
by Leanne Findlay, Julie Bernier, Holly Tuokko, Susan Kirkland and Heather Gilmour
Abstract
Background
The objective of this study was to validate
categories of cognitive functioning using data from
the 2009 Canadian Community Health Survey
(CCHS)—Healthy Aging Cognition Module.
Data and methods
Four measures of cognitive functioning—
immediate and delayed recall (memory), and
animal-naming and the Mental Alternation Test
(executive functioning)—were coded into five
categories for the Canadian household population
aged 45 or older. The scores for each measure
were standardized to t-scores that controlled
for age, sex and education. Respondents were
classified into five cognitive functioning categories.
Cross-tabulations, stratum-specific likelihood
ratios and multinomial logit regression were
used to assess associations between levels of
cognitive functioning and various health outcomes:
self-reported general and mental health status,
memory and problem-solving ability, activities of
daily living, life satisfaction, loneliness, depression,
and chronic conditions.
Results
Results supported the use of five levels of
cognitive functioning for all four outcomes on the
CCHS—Healthy Aging sample overall and by age
group (45 to 64, 65 or older) and language group
(English, French).
Interpretation
These categories can be used in future work
on cognitive functioning based on the CCHS—
Healthy Aging.
Keywords
activities of daily living, cognitive disorders, data
collection, memory disorders, mental recall, survey
methods
Authors
Leanne Findlay (1-613-951-4648;
[email protected]), Julie Bernier
(1-613-951-4556; Julie.Bernier @statcan.
gc.ca) and Heather Gilmour (1-613-951-2114;
[email protected]) are with the
Health Analysis Division at Statistics Canada,
Ottawa, Ontario K1A 0T6. Holly Tuokko is with
the University of Victoria. Susan Kirkland is with
Dalhousie University.
W
hile cognitive decline is not an inevitable
consequence of aging, it is more prevalent
at older ages.1 In 2006, one in seven Canadians
(13.7% of the total population) was aged 65 or
older.2 Among these seniors, the percentage aged
80 or older continues to grow, as does the number
of centenarians. These trends suggest that a rise
in the prevalence of cognitive impairment can be
anticipated.
Mild cognitive decline heightens the risk
of further deterioration,3-5 but seniors
with relatively low levels of impairment
may not be identified in cognition
studies, which typically focus on people
diagnosed with dementia.6 Nonetheless,
a substantial share of the senior
population is affected. According to
the 1991 Canadian Study of Health and
Aging (CSHA), about 17% of Canadians
aged 65 or older had mild impairment,
often labelled “cognitive impairment—
no dementia or CIND.”7 Similarly, data
from the Health and Retirement Survey
indicate that 22% of Americans aged
71 or older had CIND.6 Consequently,
examination of the prevalence of
various levels of cognitive well-being is
warranted.
The last national survey to include
measures of cognitive functioning among
seniors was the CSHA.7 The present
analysis uses data from the Cognition
Module of the 2009 Canadian Community
Health Survey (CCHS)—Healthy Aging
to validate a categorization of levels of
cognitive functioning in the Canadian
household population aged 45 or older.
Five categories of four measures of
cognitive functioning are examined for
the entire sample, and by age group and
language.
Methods
Data source
The 2009 Canadian Community Health
Survey (CCHS)—Healthy Aging is
a population-based, cross-sectional
survey. The sampling frame consisted
of people aged 45 or older living in
private dwellings in the ten provinces.
The survey excluded residents of the
three territories, some remote regions,
institutions, Indian reserves or Crown
lands, and military bases (military and
civilian), and full-time members of the
Canadian Forces. Data collection took
86
Health Reports, Vol. 21, no. 4, December 2010 • Statistics Canada, Catalogue no. 82-003-XPE
Validation of cognitive functioning categories in the Canadian Community Health Survey • Methodological insights
place from December 1, 2008 through
November 30, 2009 using ComputerAssisted Personal Interviewing.
The purpose of the Cognition Module
of the survey was to examine cognitive
functioning (as opposed to cognitive
impairment) across the lifespan. The
Module was administered in English
and French to non-proxy respondents
who consented to participate. This
differed from the main component of the
survey, for which proxy responses were
accepted if the mental or physical health
of selected participants prevented them
from completing the interview (2.2%
of the sample). Preliminary analyses
suggested that respondents interviewed
by proxy were more likely than those
who answered on their own behalf to
have dementia or to have suffered a
stroke. Exclusion of these respondents
from the Cognition Module means
that the data may slightly overestimate
cognitive functioning in the household
population.
The overall response rate to the
Cognition Module was 62.3% (N =
25,864), compared with 74.4% (N =
30,865) for the entire CCHS—Healthy
Aging.
Cognition Module variables
Previous studies have used clinical and
non-clinical means to assess cognitive
functioning. The Mini-Mental State
Examination (MMSE)8 and the Modified
Mini-Mental State Examination (3MS)9
are the instruments most commonly
employed in clinical settings.10-12
However, when clinical assessment is not
possible (in large, survey-based studies),
other measures must be used.
Cognition may be defined in terms
of domains, including memory and
executive functioning (for example,
planning,
problem-solving,
and
anticipation of outcomes).13 The 2009
CCHS—Healthy Aging Cognition
Module includes four cognitive tasks:
two relating to memory (immediate
and delayed recall) and two relating to
executive functioning (animal-naming
and the Mental Alternation Test). These
tasks are similar to those used in other
population-based surveys,14 as well as in
community-based studies.15-18
Recall tasks
A modified version of the Rey Auditory
Verbal Learning Test (RAVLT) was
administered
to
CCHS—Healthy
Aging respondents. The test involves
memorizing 15 common unrelated
words (for example, drum, curtain, bell)
and performing two recall trials: one
immediate and one delayed. The delayed
recall trial took place five minutes after
the immediate recall trial (the other
cognitive tasks were performed between
the recalls). Survey-administered tests
of immediate and delayed recall have
been shown to be related to each other
in a consistent way, to have similar
consistency across racial groups,19 and to
have good construct validity.20
Animal-naming
To test semantic fluency, respondents
were given one minute in which to
name as many items as possible from a
category, in this case, animals. Different
types of the same species were counted
(for example, robin and parrot counted
for two points), but different varieties of
the same type (for example, American
robin and European robin) received only
one point. The animal-naming test has
been widely administered, demonstrated
to be appropriate for evaluating different
populations, and sensitive to different
types of brain abnormalities, and it
correlates with other tests of verbal
fluency. 21
Mental Alternation Test
The Mental Alternation Test (MAT)
assesses
processing
speed.17,22
Respondents are asked recite the
alphabet, and then to count from 1 to 26.
They then have 30 seconds in which to
alternate between numbers and letters
in the sequence 1-A, 2-B, 3-C, etc. The
maximum possible score is 51.
Of those who completed any part of
the CCHS—Healthy Aging Cognition
Module, 85.9% responded to the
immediate recall, 75.5% to the delayed
recall, 92.6% to animal-naming, and
90.9% to the Mental Alternation Test.
Existing French versions of the recall
and animal-naming instruments were
used for interviews conducted in French;
the English version of the MAT was
translated into French.
The various measures reflect
independent markers of cognitive
functioning, and may have different
associations with health outcomes. For
example, memory impairment may
be important for the early detection of
dementia,23 and declines in executive
functioning, as well as memory, may
influence activities of daily living.24 It
is also possible that subgroups respond
differently to the various measures of
cognitive functioning. For instance,
people aged 45 to 64 may not demonstrate
the same patterns of cognitive functioning
as seniors, and patterns may vary by
language group.
Socio-demographic
characteristics
Cognitive functioning is typically
evaluated in terms of age, sex and
education, factors known to be related
to cognitive performance.6,7,10-12,25-28
For instance, results from the English
Longitudinal Study of Aging revealed
better cognitive performance among
younger people, women and individuals
with higher education.14
Respondents to the CCHS—Healthy
Aging reported their sex, age in years
and highest level of education. Ten
education levels were specified. The
language of the interview (English or
French) was recorded by the interviewer;
respondents who did not complete the
CCHS—Healthy Aging in either English
or French were excluded from the
Cognition Module.
Analysis variables
Numerous physical and psychological
correlates of impaired cognitive
functioning have been identified
(Table 1). Cognitive difficulties have
been associated with lower self-rated
health,29,30 depression,31-33 loneliness,34,35
decreased life satisfaction,36,37 and
reduced ability to perform instrumental
activities of daily living.24,38-40 People with
Statistics Canada, Catalogue no. 82-003-XPE • Health Reports, Vol. 21, no. 4, December 2010
Validation of cognitive functioning categories in the Canadian Community Health Survey • Methodological insights
Table 1
Selected characteristics of 2009 Canadian Community Health Survey—
Healthy Aging Cognition Module respondents, household population aged 45
or older, Canada excluding territories
Characteristic
%
Mean
Standard error
51.9
48.1
...
...
...
60.5
...
...
0.04
73.5
26.5
...
...
...
...
76.7
23.3
...
...
...
...
9.2
8.0
3.9
19.1
5.4
13.7
17.1
3.2
12.2
8.3
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
1.7
0.4
3.1
2.4
24.6
38.3
3.4
2.9
9.3
13.8
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
5.5
4.0
17.9
22.6
0.10
0.12
0.03
0.03
84.8
15.2
...
...
...
...
94.2
5.8
...
...
...
...
84.4
15.6
...
...
...
...
94.3
5.7
...
...
...
...
87.8
12.2
...
...
...
...
90.2
9.8
...
...
...
...
75.9
24.1
...
...
...
...
91.9
8.1
...
...
...
...
2.7
44.1
10.5
...
...
...
...
...
...
Socio-demographic
Sex
Women
Men
Age
Marital status
Married
Single
Language
English
French
Education
Grade 8 or lower (Quebec Secondary II or lower)
Grades 9 or 10
Grades 11 to 13
Secondary graduation
Some postsecondary
Trades certificate/diploma
College/CEGEP certificate/diploma
University certificate below bachelor's degree
Bachelor's degree
University certificate above bachelor's degree
Province
Newfoundland and Labrador
Prince Edward Island
Nova Scotia
New Brunswick
Quebec
Ontario
Manitoba
Saskachewan
Alberta
British Columbia
Cognitive outcomes
Immediate recall
Delayed recall
Animal naming
Mental Alternation Test
Health outcomes
Self-perceived health
Excellent/Very good/Good
Fair/Poor
Self-perceived mental health
Excellent/Very good/Good
Fair/Poor
Life satisfaction
Not low
Low
Likelihood of depression
Less than 0.9 probability
0.9 probability or higher
Loneliness
Not high
High
Activities of daily living
No problems
Mild/Moderate/Severe/Total problems
Memory
Able to remember most things
Somewhat forgetful/Very forgetful/Unable to remember anything
Ability to think clearly and solve problems
Able to think clearly/solve problems
Having a little/some/great deal of difficulty
Chronic conditions
Neurological disorder
Vascular disorder
Psychiatric disorder
... not applicable
Source: 2009 Canadian Community Health Survey—Healthy Aging Cognition Module.
87
cerebrovascular disease,29 diabetes,33,41-44
hypertension,45 or stroke12,46 are more
likely to be cognitively impaired
than are individuals without these
conditions. Psychiatric disorders have
also been associated with poor cognitive
functioning.47,48
Self-perceived health
CCHS―Healthy Aging respondents
were asked about their general and
mental health: “In general, would you
say your [mental] health is. . . .” The
response options―“excellent,” “very
good,” “good,” “fair,” and “poor”―were
dichotomized to reflect good (excellent/
very good/good) versus poor (fair/poor)
health.
Activities of daily living
Questions about respondents’ ability to
perform activities of daily living (ADL)
were based on the OARS Multidimential
Assessment Questionnaire.49 An overall
summary measure of ratings on the
ADL capacity-instrumental and physical
dimensions was derived. A score of
0 indicates no functional impairment;
1 = mild impairment; 2 = moderate
impairment; 3 = severe impairment; and
4 = total impairment. Responses were
dichotomized to identify respondents
with no impairment versus mild/
moderate/severe/total impairment.
Life satisfaction
On a scale from 0 to 10, with 0
representing very dissatisfied and 10, very
satisfied, respondents were asked: “How
do you feel about your life as a whole
right now?” Scores were dichotomized
to identify those whose life satisfaction
was low (at least 1 standard deviation
below the mean) versus not low.
Depression
The CCHS—Healthy Aging measure of
depression is a shortened version of the
World Health Organization Composite
International
Diagnostic
Interview
(CIDI) Scale, which is based on the
DSM-III-R and the Diagnostic Criteria
for the Research of the ICD-10. The
depression subscale pertains to people
who felt depressed or lost interest in
88
Health Reports, Vol. 21, no. 4, December 2010 • Statistics Canada, Catalogue no. 82-003-XPE
Validation of cognitive functioning categories in the Canadian Community Health Survey • Methodological insights
things for two or more weeks in the past
year. For the CCHS—Healthy Aging,
a derived variable was created based
on the depression score, indicating the
probability that respondents would have
been diagnosed as having experienced
a major depressive episode in the past
12 months if they had completed the
Long-Form CIDI. A probability of 0
was assigned to respondents who replied
negatively to the stem question (did not
have depression for two or more weeks
in the past year); a cut-off value of 0.9
was used to distinguish those with a high
probability of depression (above 0.9)
from those with a lower probability.
Loneliness
The 3-Item Loneliness Scale50 measures
an individual’s reported loneliness. On
a 3-point Likert scale (“hardly ever,”
“some of the time,” and “often”),
CCHS―Healthy Aging respondents
answered the questions: “How often do
you feel:
• that you lack of companionship?”
• left out?”
• isolated from others?”
Higher scores indicate greater loneliness.
Scores were dichotomized to identify
those with high loneliness (at least 1
standard deviation above the mean)
versus not high loneliness.
Self-reported cognition
(Health Utilities Index)
The Health Utilities Index (HUI) Mark
III assesses functional health status
in eight domains:
vision, hearing,
speech, ambulation, dexterity, emotion,
cognition, and pain.51,52 The HUI has
been shown to have strong reliability and
validity in general,53 as well as for patients
with lower cognitive functioning.54
Only the cognition subscale of the
HUI was pertinent to the current study.
The items of interest were: “How would
you describe your usual ability to:
• remember things (able to remember
most things; somewhat forgetful;
very forgetful; unable to remember
anything at all).”
• think and solve day-to-day problems
(able to think clearly and solve
problems; having a little difficulty;
having some difficulty; having a
great deal of difficulty; unable to
think or solve problems).”
Items were dichotomized as “able to
remember most things” versus at least
“somewhat forgetful,” and “able to
think clearly and solve problems” versus
having “at least some difficulty.”
Chronic conditions
Respondents were asked if they had
been diagnosed with specific long-term
health conditions. Conditions relevant
to the current analysis were grouped
into neurological (Alzheimer’s Disease
or other dementia, Parkinson’s Disease,
effects of stroke), vascular (high blood
pressure, diabetes, heart attack, heart
disease), and psychiatric (mood disorder
or anxiety) disorders.
Analytical techniques
T-score creation
Selecting
cut-points
to
identify
impairment implies that definitive
lines
demarcate
“normal”
from
“dysfunctional” scores. It is more likely
that cognitive functioning operates on a
continuum and that several categories
are more appropriate as indicators of
impairment.4
Consequently, for this
analysis, multiple categories of cognitive
functioning were identified.55 T-scores
that control for age, sex and education
can be calculated for each cognitive
measure. Using the sample data for the
current study, five categories of cognitive
functioning were created, representing
t-scores of 0 to 34, 35 to 44, 45 to 54, 55
to 64, and 65 or more.
To generate t-scores from the
results of each of the four cognitive
tasks, raw scores were converted to
scaled scores (mean = 10, standard
deviation = 3); higher scaled scores
indicate better performance.55 Scaled
scores were regressed separately for each
task on age, sex and education. In this
manner, equations were created for each
dependent variable (cognitive outcome)
in the form:
DV = intercept + b(age) + b(education) +
b(gender)
Each respondent’s predicted scaled
score was generated from this equation
(that is, independent of age, sex and
education). The respondent’s predicted
score was subtracted from the actual
scaled score to determine the residual,
indicating how well the individual
performed, compared with what would
be expected based on his/her age, sex and
education. Finally, residual scores were
converted to t-scores with the following
equation:
T = {[(residual/standard deviation of the
residual) x 10] + 50}
Thus, the t-scores are independent
of age, sex and education; are normally
distributed; have a mean of 50 and
a standard deviation of 10; and are
independent of a unit of measurement.55
Validation
Once t-scores were created and
individuals were assigned to one of
the five cognitive function categories,
the first step in empirically validating
the categories was to examine crosstabulations of the categories by health
outcome.
Stratum-specific likelihood ratios
(SSLRs) were calculated to determine
the accuracy of assigning individuals
to levels of cognitive functioning based
on the health outcomes.56-58 SSLRs are
generalizable and independent of actual
probabilities in the population.59 The
likelihood that people in each cognitive
functioning category (stratum) will
experience a certain outcome (for
example, fair/poor self-rated health)
is given relative to their likelihood of
experiencing a positive outcome (in this
example, excellent/very good/good selfrated health), according to the formula:
SSLR = (x1g/n1)/(x0g/n0)
where x1g is the number of people with
the health outcome (fair/poor health) in
the gth stratum; n1 is the total number
of people with the health outcome; x0g
is the number of people without the
health outcome (in good health) in the
Statistics Canada, Catalogue no. 82-003-XPE • Health Reports, Vol. 21, no. 4, December 2010
Validation of cognitive functioning categories in the Canadian Community Health Survey • Methodological insights
gth stratum; and n0 is the total number of
people without the health outcome.
An SSLR of 10 or more indicates
that the health outcome is highly likely;
an SSLR below 0.1 indicates that it is
highly unlikely.56,57 It is anticipated that
SSLRs would be high when a poor health
outcome is more likely, and low when a
poor health outcome is unlikely.
The final step was to examine all
relevant health variables as predictors
of cognitive functioning, comparing
lower levels of functioning to the highest
category (t-scores of 65 or more) for
each cognitive outcome.
Because
the dependent variable (cognitive
functioning category) comprised five
levels, a multinomial logit regression
analysis was used. The odds of reporting
a health problem (for example, fair/poor
health) should be greatest for those in
the lowest (versus the highest) cognitive
functioning category, with odds
decreasing for those in progressively
higher categories of functioning.
Results are presented only for the
immediate recall outcome; results were
similar for delayed recall, animal-naming,
and the MAT (Appendix Tables A to I).
Correlations between the four outcome
variables were moderate (immediate
recall with delayed recall, r = .69;
immediate recall with animal-naming, r
= .36, immediate recall with MAT, r =
.34; delayed recall with animal-naming,
r = .33, delayed recall with MAT, r =
.30; animal-naming with MAT, r = .45;
all p’s ≤ .001). Survey sampling weights
were applied to all point-estimates to
account for the complex survey design of
the CCHS—Healthy Aging.
Because the response rate for the
Cognition Module was lower than that
for the full CCHS—Healthy Aging,
separate sampling weights were created
for use with the cognitive outcome
variables sample. All analyses were
performed with SAS 9.1 and SAScallable SUDAAN. Standard errors
in modelling were computed using a
bootstrapping technique.60
Results
Descriptive statistics
As expected,55 the distribution of
immediate recall scores across cognitive
functioning categories was normal, with
the most common category (39% of
respondents) being t-scores in the 45to-54 range (Table 2). Approximately
6% of respondents scored in the lowest
category, and 8%, in the highest.
89
People who reported fair/poor general
health were more likely to have relatively
low immediate recall scores. About
9% of them had scores in the lowest
category, compared with 6% overall.
Conversely, 5% of those with fair/poor
health had immediate recall scores in
the in the highest category, compared
with 8% overall. This pattern was
even more pronounced for self-reported
mental health. Similarly, relatively high
Table 2
Percentage distribution of respondents to 2009 Canadian Community Health
Survey—Healthy Aging Cognition Module, by immediate recall score and
selected health characteristics, household population aged 45 or older, Canada
excluding territories
Immediate recall t-score
Health characteristic
Low
0 to 34
35 to 44
45 to 54
High
55 to 64 65 or more
%
Total
5.6
24.5
39.2
23.0
7.6
Self-perceived health
Fair/Poor
Excellent/Very good/Good
8.5
5.1
28.6
23.8
39.8
39.1
18.1
23.8
5.1
8.1
14.9E
5.1
32.2
24.1
32.3
39.6
16.6
23.4
3.9E
7.9
Activities of daily living
No problems
Mild/Moderate/Severe/Total problems
5.3
8.6
24.1
28.4
39.2
39.3
23.5
18.4
7.9
5.3E
Life satisfaction
Low
Not low
7.8
5.2
30.7
23.4
38.2
39.4
18.0
23.9
5.3
8.0
Depression
0.9 probability or higher
Less than 0.9 probability
5.8E
5.5
25.7
24.4
39.3
39.3
18.3
23.4
10.8E
7.4
Loneliness
High
Not high
9.1
5.1
28.4
24.0
36.8
39.6
19.5
23.5
6.3
7.8
5.0
7.6
24.0
26.4
39.5
38.2
23.6
21.0
7.9
6.8
5.2
10.5
23.8
33.9
39.4
36.6
23.7
14.8
7.9
4.3E
Self-perceived mental health
Fair/Poor
Excellent/Very good/Good
Memory
Able to remember most things
Somewhat forgetful/Very forgetful/Unable to
remember anything
Ability to think clearly and solve problems
Able to think clearly/solve problems
Having a little/some/great deal of difficulty/unable
Neurological disorder
Yes
No
9.0E
5.6
30.3
24.4
41.1
39.1
16.0
23.2
F
7.7
Vascular disorder
Yes
No
5.0
6.1
24.0
25.0
41.0
37.9
23.0
22.9
7.0
8.1
Psychiatric disorder
Yes
No
9.6E
5.2
26.3
24.3
37.6
39.4
19.3
23.4
7.2E
7.7
E
interpret with caution (coefficient of variation 16.6% to 33.3%)
F too unreliable to be reported (coefficient of variation greater than 33.3%)
Source: 2009 Canadian Community Health Survey—Healthy Aging Cognition Module.
90
Health Reports, Vol. 21, no. 4, December 2010 • Statistics Canada, Catalogue no. 82-003-XPE
Validation of cognitive functioning categories in the Canadian Community Health Survey • Methodological insights
percentages of people who reported
difficulties with activities of daily living,
lower life satisfaction and loneliness had
low immediate recall scores. By contrast,
no pattern emerged for depression.
The HUI cognitive functioning
variables were associated with immediate
recall scores. Respondents who reported
that they were at least somewhat forgetful
and who had at least some difficulties
thinking clearly and solving problems
were more likely than others to have
immediate recall scores in the lowest
category and less likely to have scores in
the highest category.
The presence of a neurological or
psychiatric disorder was related to
cognitive functioning. Relatively high
percentages of people who reported such
conditions had low immediate recall
scores. However, this was not the case
for people with vascular disorders.
Stratum-specific likelihood ratios
In general, the stratum-specific likelihood
ratios (SSLR) supported the cognitive
functioning categories: the higher their
immediate recall score, the less likely
were respondents to have negative health
characteristics. (Although the SSLR
patterns were generally as anticipated,
some differences emerged for delayed
recall, animal-naming and MAT–
Appendix Tables D to F).
SSLRs for fair/poor self-rated
general and mental health, difficulties
with activities of daily living, low life
satisfaction and loneliness decreased
as immediate recall scores rose (Table
3). In general, depression also followed
the expected pattern, with the highest
SSLR for the lowest immediate recall
score category. The two HUI cognition
variables also demonstrated the
anticipated pattern.
Similarly, the SSLRs for neurological
and psychiatric disorders followed the
expected pattern in that the likelihood of
the conditions was associated with low
immediate recall scores; no association
was shown for vascular disorders.
Multinomial logistic regression
The final step was to examine the odds
of being in a low immediate recall score
category given the presence of a negative
health characteristic. The highest t-score
category was set as the reference group
(Table 4). As expected, scoring in the
lowest immediate recall category was
associated with the highest odds of poor
health. For instance, compared with
people whose immediate recall scores
were in the highest category, those with
scores in the lowest category had more
than twice the odds of being in fair/
poor general health, almost six times
the odds of being in fair/poor mental
health, and more than twice the odds
of having difficulties with activities of
daily living. Results were similar for
low life satisfaction and loneliness. Not
surprisingly, people with the lowest
immediate recall scores had almost twice
the odds of reporting that they were at
least somewhat forgetful, and almost
four times the odds of reporting that they
had some difficulty thinking clearly and
solving problems, compared with people
with the highest immediate recall scores.
However, no association was shown
between depression and immediate recall
scores.
People with immediate recall scores in
the lowest category had more than three
times the odds of reporting a neurological
condition and twice the odds of reporting
a psychiatric disorder. (Odds ratios were
generally similar for the other three
measures of cognitive functioning, with
the exception of psychiatric disorders
and the MAT—Appendix Tables G, H
and I).
Table 3
Stratum-specific likelihood ratios (SSLR) for selected health characteristics of respondents to 2009 Canadian
Community Health Survey—Healthy Aging Cognition Module, by immediate recall score, household population aged 45
or older, Canada excluding territories
Immediate recall t-score
0 to 34
Health characteristic
Low self-rated health
Low self-rated mental health
Difficulties with activities of daily living
Low life satisfaction
High probability of depression
High loneliness
Unable to remember things
Unable to think/solve problems
Neurological disorder
Vascular disorder
Psychiatric disorder
SSLR
1.66
2.93
1.62
1.49
1.07
1.79
1.51
2.00
1.61
0.82
1.86
35 to 44
95%
confidence
interval
from
to
1.65
2.92
1.61
1.49
1.06
1.78
1.50
1.99
1.59
0.82
1.85
1.67
2.95
1.63
1.50
1.08
1.80
1.52
2.01
1.63
0.82
1.87
Source: 2009 Canadian Community Health Survey—Healthy Aging Cognition Module.
SSLR
1.20
1.34
1.18
1.31
1.05
1.18
1.10
1.43
1.24
0.96
1.08
45 to 54
95%
confidence
interval
from
to
1.19
1.34
1.17
1.31
1.05
1.18
1.10
1.42
1.24
0.96
1.08
1.20
1.34
1.18
1.31
1.06
1.19
1.10
1.43
1.25
0.96
1.09
SSLR
1.02
0.82
1.00
0.97
1.00
0.93
0.97
0.93
1.05
1.08
0.95
55 to 64
95%
confidence
interval
from
to
1.01
0.81
1.00
0.97
1.00
0.93
0.97
0.93
1.05
1.08
0.95
1.02
0.82
1.00
0.97
1.00
0.93
0.97
0.93
1.05
1.08
0.96
SSLR
0.76
0.71
0.79
0.75
0.78
0.83
0.89
0.62
0.69
1.00
0.82
65 or more
95%
confidence
interval
from
to
0.76
0.71
0.78
0.75
0.78
0.82
0.89
0.62
0.68
1.00
0.82
0.76
0.72
0.79
0.75
0.79
0.83
0.89
0.63
0.69
1.01
0.83
SSLR
0.63
0.50
0.67
0.66
1.46
0.80
0.86
0.54
0.47
0.86
0.94
95%
confidence
interval
from
to
0.62
0.49
0.66
0.66
1.45
0.80
0.86
0.53
0.47
0.86
0.93
0.63
0.51
0.67
0.66
1.47
0.81
0.87
0.54
0.48
0.86
0.94
Statistics Canada, Catalogue no. 82-003-XPE • Health Reports, Vol. 21, no. 4, December 2010
Validation of cognitive functioning categories in the Canadian Community Health Survey • Methodological insights
91
Table 4
Odds ratios relating selected health status characteristics of respondents to 2009 Canadian Community Health Survey—
Healthy Aging Cognition Module, by immediate recall score, household population aged 45 or older, Canada excluding
territories
Immediate recall t-score
0 to 34
Health characteristic
Low self-rated health
Low self-rated mental health
Difficulties with activities of daily living
Low life satisfaction
High probability of depression
High loneliness
Unable to remember things
Unable to think/solve problems
Neurological disorder
Vascular disorder
Psychiatric disorder
Adjusted
degrees
of Adjusted
freedom chi-square
3.59
3.17
3.63
3.62
3.71
3.93
3.84
3.71
3.87
3.83
3.73
32.89
45.51
25.65
35.90
6.19
27.73
16.23
45.13
17.69
8.94
16.52
Odds
ratio
2.64
5.86
2.42
2.27
0.73
2.23
1.76
3.71
3.40
0.95
1.99
35 to 44
95%
confidence
interval
from
to
1.64
3.10
1.51
1.45
0.39
1.47
1.20
1.94
1.47
0.72
1.17
4.26
11.08
3.90
3.53
1.39
3.39
2.58
7.08
7.86
1.26
3.36
Odds
ratio
1.90
2.68
1.76
1.99
0.72
1.48
1.28
2.64
2.62
1.12
1.16
45 to 54
95%
confidence
interval
from
to
1.35
1.72
1.19
1.45
0.43
1.05
0.97
1.45
1.20
0.92
0.78
2.68
4.17
2.59
2.72
1.23
2.06
1.69
4.83
5.74
1.36
1.73
Odds
ratio
1.62
1.63
1.50
1.47
0.69
1.16
1.12
1.72
2.22
1.26
1.02
55 to 64
95%
confidence
interval
from
to
1.15
1.04
1.03
1.10
0.41
0.83
0.86
0.95
1.01
1.05
0.69
2.26
2.56
2.18
1.97
1.15
1.61
1.47
3.13
4.84
1.51
1.50
Odds
ratio
1.21
1.42
1.17
1.14
0.54
1.03
1.03
1.16
1.45
1.17
0.88
95%
confidence
interval
from
to
0.85
0.86
0.79
0.84
0.31
0.74
0.77
0.62
0.66
0.95
0.58
1.71
2.35
1.74
1.54
0.92
1.44
1.38
2.15
3.21
1.43
1.33
Note: Comparison group is 65 or more t-score category.
Source: 2009 Canadian Community Health Survey—Healthy Aging Cognition Module.
Subgroup analyses
Validation conducted for people aged
45 to 64 and for those aged 65 or older,
as well as for English and French
respondents, yielded results similar to
those obtained for the entire sample
(results available upon request). Whether
they were in the younger or older age
group, English or French, respondents
demonstrated similar patterns between
health outcomes and the five categories
of cognitive functioning (in both crosstabulations and SSLR comparisons).
Regardless of their age group, people
with low immediate recall scores were
more likely to have fair/poor self-rated
general and mental health, difficulties
with activities of daily living, low life
satisfaction, loneliness, less ability
to think and solve problems, and
neurological disorders, compared with
people whose scores placed them in
higher immediate recall categories. The
only differences between the younger
and older cohort were in memory and
psychiatric disorders—lower immediate
recall scores were not strongly associated
with ability to remember things and
psychiatric disorders among 45- to
64-year-olds, but they were for seniors.
For English and French respondents,
lower immediate recall scores were
associated with fair/poor self-rated
general and mental health, difficulties
with activities of daily living, low life
satisfaction, loneliness, lower self-rated
cognition, neurological disorders, and
psychiatric disorders. Depression and
vascular disorders were not associated
with immediate recall scores for either
language group
Discussion
The results of the current study
confirm that categories of cognitive
functioning can be described from the
CCHS—Healthy Aging Cognition
Module.
Four tests of cognitive
functioning—immediate recall, delayed
recall, animal-naming and the Mental
Alternation Test—were validated based
on literature-supported correlates of
cognitive functioning. Lower cognitive
functioning (notably, t-scores less than
34) was associated with poorer self-rated
general and mental health, difficulties
with activities of daily living, lower life
satisfaction, and loneliness. As might
be expected, self-reported cognitive
difficulties (forgetfulness and difficulty
thinking clearly and solving problems)
were associated with low immediate
recall scores. The fact that the strongest
correlates of the cognitive functioning
categories were self-rated mental health
and difficulties thinking clearly and
solving problems lends the greatest
support to the use of the categories
presented in this analysis.
Cognitive functioning was not
associated with the probability of
depression. However, the literature on
this subject is inconsistent. Some studies
have found no association between
depression and cognition,61 while
others have shown a relationship, even
accounting for socio-economic factors.33
Beirman et al.31 suggested a non-linear
relationship between depression and
cognitive decline, with elevated levels
of depression (and anxiety) in the early
stages of decline, but diminished levels
as deterioration progresses. Further
research on the association between
depression and cognitive functioning is
obviously necessary.
While neurological and psychiatric
disorders were associated with lower
cognitive functioning, no patterns
emerged for vascular disorders. Previous
work, too, has suggested that heart
92
Health Reports, Vol. 21, no. 4, December 2010 • Statistics Canada, Catalogue no. 82-003-XPE
Validation of cognitive functioning categories in the Canadian Community Health Survey • Methodological insights
disease, hypertension and diabetes are
not necessarily associated with cognitive
decline, especially over and above other
risk factors such as low educational
attainment.33,62,63
Limitations and future directions
A major strength of the current study
is the large, nationally representative
sample. However, several limitations
should be acknowledged.
Proxy responses were not accepted for
the Cognition Module. Other research
has shown that individuals for whom
proxy responses are provided tended to
perform poorly on cognitive measures
and were more likely to have dementia.20
Thus, the CCHS―Healthy Aging data
may underestimate the prevalence
of lower cognitive functioning in the
Canadian household population.
The
CCHS―Healthy
Aging
Cognition Module used non-clinical
measures of cognitive functioning. A
clinical assessment would have allowed
a test of sensitivity and specificity of the
measures in identifying cognitive decline
or dementia. This may explain why
relationships were not found between
vascular disorders (and/or depression)
and the cognition categories. Muller et
al.64 found a significant relation between
cardiovascular disease and MMSE
scores, but not administered tests.
The longitudinal assessment of
cognitive functioning among the
population is warranted. Such studies
would allow researchers to focus on
associations between specific risk factors
(or correlates) and cognitive functioning
over time. For instance, Wilson et al.36
found that loneliness was associated with
a more rapid cognitive decline in elderly
people.
Conclusions
Based on the results of tests of
immediate and delayed recall, animalnaming, and the MAT in the CCHS—
Healthy Aging Cognition Module,
five categories describing low to high
cognitive functioning were created.
These categories were validated for the
household population aged 45 or older
overall, and by age group and language.
The aging of Canada’s population
will likely be accompanied by a growing
number of people experiencing cognitive
decline. CCHS―Healthy Aging data
can contribute an understanding of
the prevalence of this condition in the
household population. This validation
study enhances the analytic value of the
information in the Cognition Module. ■
Acknowledgements
Statistics Canada thanks all participants
for their input and advice during the
development of the Canadian Community
Health Survey―Healthy Aging. The
survey content was developed by the
Health Statistics Division at Statistics
Canada in consultation with Health
Canada, the Public Health Agency of
Canada, and experts conducting the
Canadian Longitudinal Study on Aging
(CLSA), a major strategic initiative of the
Canadian Institute of Health Research.
Consultations included stakeholders
from Human Resources and Social
Development Canada and provincial and
territorial health ministries. The addition
of 5,000 respondents aged 45 to 54 was
funded by the CLSA.
Statistics Canada, Catalogue no. 82-003-XPE • Health Reports, Vol. 21, no. 4, December 2010
Validation of cognitive functioning categories in the Canadian Community Health Survey • Methodological insights
93
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47. Colenda CC, Legault C, Rapp SR, et
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women: Results from the women’s health
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of Geriatric Psychiatry 2010; 18: 177-86.
48. Rosenberg PB, Mielke MM, Xue Q, et
al. Depressive symptoms predict incident
cognitive impairment in cognitive healthy
older women. American Journal of Geriatric
Psychiatry 2010; 18: 204-11.
54. Kavirajan H, Hays CD, Vassar S, et al.
Responsiveness and construct validity of the
health utilities index in patients with dementia.
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and validation of a demographic correction
system for neuropsychological measures
used in the Canadian Study of Health and
Aging. Journal of Clinical and Experimental
Neuropsychology 1996; 18(4): 479-616.
56. Pierce JC, Cornell RG. Integrating
stratum-specific likelihood ratios with the
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57. Furukawa TA, Goldberg DP, Rabe-Hesketh S,
et al. Stratum-specific likelihood ratios of two
versions of the General Health Questionnaire.
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58. Wada K, Tamaka K, Theriault G, et al.
Application of the stratum-specific likelihood
ratio (SSLR) analysis to results of a depressive
symptoms screening survey among Japanese
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59. Schmitz N, Kruse J, Ress W. Application of
stratum-specific likelihood ratios in mental
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Statistics Canada, Catalogue no. 82-003-XPE • Health Reports, Vol. 21, no. 4, December 2010
Validation of cognitive functioning categories in the Canadian Community Health Survey • Methodological insights
Appendix
Table A
Percentage distribution of respondents to 2009 Canadian Community Health
Survey—Healthy Aging Cognition Module, by delayed recall score and
selected health characteristics, household population aged 45 or older, Canada
excluding territories
Delayed recall t-score
Low
0 to 34
35 to 44
45 to 54
Total
5.6
23.7
39.2
23.4
8.1
Self-perceived health
Fair/Poor
Excellent/Very good/Good
5.8
5.6
29.1
22.8
40.6
39.0
19.2
24.1
5.2
8.5
Self-perceived mental health
Fair/Poor
Excellent/Very good/Good
6.2E
5.6
36.2
23.0
40.6
39.1
12.9
24.0
4.2E
8.3
Activities of daily living
No problems
Mild/Moderate/Severe/Total problems
6.6
5.5
31.4
23.0
38.1
39.3
18.0
23.9
5.9E
8.3
Life satisfaction
Low
Not low
8.1
5.2
27.8
22.9
40.3
39.0
18.4
24.4
5.4
8.6
Depression
0.9 probability or higher
Less than 0.9 probability
6.9E
5.5
25.9
23.5
38.4
39.3
20.0
23.7
8.7E
8.1
Loneliness
High
Not high
7.9
5.3
26.0
23.3
38.5
39.4
21.0
23.7
6.6
8.3
5.4
6.3
22.9
26.3
39.3
38.8
23.8
22.3
8.6
6.4
Ability to think clearly and solve problems
Able to think clearly/solve problems
Having a little/some/great deal of difficulty/unable
5.3
9.9
23.4
27.1
39.2
39.2
23.8
19.1
8.3
4.6E
Neurological disorder
Yes
No
9.8E
5.5
32.1
23.5
39.0
39.2
16.6
23.6
F
8.2
Vascular disorder
Yes
No
4.6
6.4
25.0
22.7
39.8
38.8
23.0
23.7
7.6
8.4
Psychiatric disorder
Yes
No
7.3
5.4
26.9
23.3
39.4
39.2
20.1
23.8
6.3
8.3
Health characteristic
55 to 64
High
65 or more
%
Memory
Able to remember most things
Somewhat forgetful/Very forgetful/Unable to
remember anything
E
interpret with caution (coefficient of variation 16.6% to 33.3%)
F too unreliable to be reported (coefficient of variation greater than 33.3%)
Source: 2009 Canadian Community Health Survey—Healthy Aging Cognition Module.
95
96
Health Reports, Vol. 21, no. 4, December 2010 • Statistics Canada, Catalogue no. 82-003-XPE
Validation of cognitive functioning categories in the Canadian Community Health Survey • Methodological insights
Table B
Percentage distribution of respondents to 2009 Canadian Community Health
Survey—Healthy Aging Cognition Module, by animal-naming score and
selected health characteristics, household population aged 45 or older, Canada
excluding territories
Animal-naming t-score
Low
0 to 34
35 to 44
45 to 54
Total
7.4
24.9
36.6
23.2
7.8
Self-perceived health
Fair/Poor
Excellent/Very good/Good
9.0
7.1
30.0
24.0
37.3
36.5
18.4
24.0
5.3
8.3
12.7
7.1
31.5
24.5
34.1
36.8
16.4
23.6
5.4E
8.0
7.4
7.6
24.3
31.2
36.5
37.5
23.8
18.0
8.0
5.7
12.4
6.6
30.3
23.9
32.8
37.3
18.1
24.2
6.3
8.1
Health characteristic
High
55 to 64 65 or more
%
Self-perceived mental health
Fair/Poor
Excellent/Very good/Good
Activities of daily living
No problems
Mild/Moderate/Severe/Total problems
Life satisfaction
Low
Not low
Depression
0.9 probability or higher
Less than 0.9 probability
9.2E
7.3
22.5
25.0
34.6
36.7
26.2
23.1
7.5
7.8
Loneliness
High
Not high
9.6
7.1
28.7
24.4
34.0
37.0
20.6
23.6
7.0
7.9
6.7
9.7
24.4
26.6
37.1
35.2
23.5
22.4
8.3
6.2
Ability to think clearly and solve problems
Able to think clearly/solve problems
Having a little/some/great deal of difficulty/unable
6.9
13.4
24.5
30.3
36.7
35.2
23.8
16.5
8.1
4.6E
Neurological disorder
Yes
No
12.2
7.3
26.9
24.9
39.2
36.5
16.7
23.4
5.1E
7.9
Vascular disorder
Yes
No
7.0
7.8
24.7
25.2
38.7
34.9
22.9
23.5
6.8
8.6
Psychiatric disorder
Yes
No
8.3
7.3
27.3
24.7
37.3
36.5
21.9
23.4
5.2
8.1
Memory
Able to remember most things
Somewhat forgetful/Very forgetful/Unable to
remember anything
E
interpret with caution (coefficient of variation 16.6% to 33.3%)
Source: 2009 Canadian Community Health Survey—Healthy Aging Cognition Module.
Statistics Canada, Catalogue no. 82-003-XPE • Health Reports, Vol. 21, no. 4, December 2010
Validation of cognitive functioning categories in the Canadian Community Health Survey • Methodological insights
Table C
Percentage distribution of respondents to 2009 Canadian Community Health
Survey—Healthy Aging Cognition Module, by Mental Alternation Test score
and selected health characteristics, household population aged 45 or older,
Canada excluding territories
Mental Alternation Test t-score
Low
0 to 34
35 to 44
45 to 54
6.5
23.2
%
36.4
26.0
7.9
8.4
6.1
32.4
21.7
36.7
36.3
17.7
27.4
4.9
8.4
10.0
6.2
32.8
22.7
32.1
36.6
20.3
26.4
4.8E
8.1
Activities of daily living
No problems
Mild/Moderate/Severe/Total problems
6.4
7.3
22.4
30.6
36.2
37.6
26.8
19.2
8.2
5.3
Life satisfaction
Low
Not low
9.0
6.0
28.9
22.2
34.6
36.8
21.8
26.8
5.6
8.3
Depression
0.9 probability or higher
Less than 0.9 probability
6.9E
6.4
25.1
23.0
34.7
36.6
28.1
25.9
5.2E
8.1
Loneliness
High
Not high
8.6
6.2
26.6
22.7
36.1
36.5
22.7
26.4
6.0
8.2
6.2
7.3
22.3
26.1
36.6
35.6
26.5
24.5
8.4
6.4
Ability to think clearly and solve problems
Able to think clearly/solve problems
Having a little/some/great deal of difficulty/unable
6.0
11.4
22.6
30.8
36.3
36.8
26.8
17.5
8.3
3.6
Neurological disorder
Yes
No
11.9E
6.3
29.5
23.1
34.2
36.4
18.6
26.3
5.8E
8.0
Vascular disorder
Yes
No
6.4
6.5
24.7
22.0
37.2
35.8
23.6
28.0
8.2
7.7
Psychiatric disorder
Yes
No
7.1
6.4
25.6
23.0
33.4
36.7
27.4
25.9
6.6E
8.1
Health characteristic
Total
Self-perceived health
Fair/Poor
Excellent/Very good/Good
Self-perceived mental health
Fair/Poor
Excellent/Very good/Good
Memory
Able to remember most things
Somewhat forgetful/Very forgetful/Unable to
remember anything
E
interpret with caution (coefficient of variation 16.6% to 33.3%)
Source: 2009 Canadian Community Health Survey—Healthy Aging Cognition Module.
High
55 to 64 65 or more
97
98
Health Reports, Vol. 21, no. 4, December 2010 • Statistics Canada, Catalogue no. 82-003-XPE
Validation of cognitive functioning categories in the Canadian Community Health Survey • Methodological insights
Table D
Stratum-specific likelihood ratios (SSLR) for selected health characteristics of respondents to 2009 Canadian
Community Health Survey—Healthy Aging Cognition Module, by delayed recall score category, household population
aged 45 or older, Canada excluding territories
Delayed recall t-score
0 to 34
Health characteristic
Low self-rated health
Low self-rated mental health
Difficulties with activities of daily living
Low life satisfaction
High probability of depression
High loneliness
Unable to remember things
Unable to think/solve problems
Neurological disorder
Vascular disorder
Psychiatric disorder
SSLR
1.03
1.10
1.19
1.57
1.09
1.49
1.16
1.87
1.77
0.71
1.34
35 to 44
95%
confidence
interval
from
to
1.02
1.09
1.18
1.56
1.08
1.48
1.15
1.85
1.75
0.71
1.33
1.04
1.11
1.20
1.58
1.10
1.50
1.16
1.88
1.79
0.72
1.35
SSLR
1.28
1.57
1.37
1.21
1.11
1.12
1.15
1.16
1.37
1.10
1.16
45 to 54
95%
confidence
interval
from
to
1.27
1.57
1.36
1.21
1.10
1.11
1.14
1.15
1.36
1.10
1.15
1.28
1.58
1.37
1.22
1.11
1.12
1.15
1.16
1.38
1.10
1.16
SSLR
1.04
1.04
0.97
1.03
0.96
0.98
0.99
1.00
0.99
1.03
1.00
55 to 64
95%
confidence
interval
from
to
1.04
1.03
0.97
1.03
0.96
0.98
0.98
1.00
0.99
1.03
1.00
1.04
1.04
0.97
1.04
0.97
0.98
0.99
1.00
1.00
1.03
1.01
SSLR
0.80
0.54
0.75
0.76
0.87
0.88
0.94
0.81
0.70
0.97
0.84
65 or more
95%
confidence
interval
from
to
0.80
0.53
0.75
0.75
0.86
0.88
0.94
0.80
0.70
0.97
0.84
0.80
0.54
0.75
0.76
0.87
0.89
0.94
0.81
0.71
0.97
0.85
SSLR
0.62
0.51
0.71
0.63
1.20
0.79
0.74
0.56
0.31
0.91
0.77
95%
confidence
interval
from
to
0.61
0.50
0.71
0.62
1.19
0.79
0.74
0.55
0.31
0.90
0.76
0.62
0.52
0.72
0.63
1.21
0.80
0.75
0.56
0.32
0.91
0.77
Source: 2009 Canadian Community Health Survey—Healthy Aging Cognition Module.
Table E
Stratum-specific likelihood ratios (SSLR) for selected health characteristics of respondents to 2009 Canadian
Community Health Survey—Healthy Aging Cognition Module, by animal-naming score category, household population
aged 45 or older, Canada excluding territories
Animal-naming t-score
0 to 34
Health characteristic
Low self-rated health
Low self-rated mental health
Difficulties with activities of daily living
Low life satisfaction
High probability of depression
High loneliness
Unable to remember things
Unable to think/solve problems
Neurological disorder
Vascular disorder
Psychiatric disorder
SSLR
1.27
1.78
1.02
1.89
1.20
1.36
1.43
1.94
1.67
0.90
1.13
35 to 44
95%
confidence
interval
from
to
1.26
1.77
1.01
1.89
1.19
1.35
1.43
1.93
1.66
0.89
1.12
1.27
1.79
1.03
1.90
1.20
1.37
1.44
1.95
1.69
0.90
1.13
Source: 2009 Canadian Community Health Survey—Healthy Aging Cognition Module.
SSLR
1.25
1.29
1.28
1.27
0.87
1.18
1.09
1.24
1.08
0.98
1.11
45 to 54
95%
confidence
interval
from
to
1.24
1.28
1.28
1.27
0.87
1.17
1.09
1.23
1.07
0.98
1.10
1.25
1.29
1.29
1.27
0.87
1.18
1.09
1.24
1.09
0.98
1.11
SSLR
1.02
0.93
1.03
0.88
0.98
0.92
0.95
0.96
1.07
1.11
1.02
55 to 64
95%
confidence
interval
from
to
1.02
0.92
1.03
0.88
0.98
0.92
0.95
0.96
1.07
1.11
1.02
1.02
0.93
1.03
0.88
0.98
0.92
0.95
0.96
1.08
1.11
1.02
SSLR
0.77
0.69
0.76
0.75
1.16
0.87
0.95
0.69
0.71
0.97
0.94
65 or more
95%
confidence
interval
from
to
0.76
0.69
0.75
0.75
1.16
0.87
0.95
0.69
0.71
0.97
0.93
0.77
0.70
0.76
0.75
1.17
0.88
0.96
0.70
0.72
0.98
0.94
SSLR
0.64
0.67
0.71
0.78
0.86
0.89
0.75
0.57
0.64
0.78
0.64
95%
confidence
interval
from
to
0.64
0.67
0.71
0.78
0.85
0.88
0.74
0.57
0.63
0.78
0.64
0.65
0.68
0.72
0.79
0.86
0.89
0.75
0.58
0.65
0.79
0.65
Statistics Canada, Catalogue no. 82-003-XPE • Health Reports, Vol. 21, no. 4, December 2010
Validation of cognitive functioning categories in the Canadian Community Health Survey • Methodological insights
99
Table F
Stratum-specific likelihood ratios (SSLR) for selected health characteristics of respondents to 2009 Canadian
Community Health Survey—Healthy Aging Cognition Module, by Mental Alternation Test score category, household
population aged 45 or older, Canada excluding territories
Mental Alternation Test t-score
0 to 34
Health characteristic
SSLR
Low self-rated health
Low self-rated mental health
Difficulties with activities of daily living
Low life satisfaction
High probability of depression
High loneliness
Unable to remember things
Unable to think/solve problems
Neurological disorder
Vascular disorder
Psychiatric disorder
1.36
1.61
1.15
1.51
1.11
1.40
1.18
1.88
1.88
0.98
1.11
35 to 44
95%
confidence
interval
from
to
1.35
1.59
1.15
1.50
1.10
1.39
1.17
1.87
1.86
0.97
1.10
SSLR
1.37
1.62
1.16
1.52
1.12
1.41
1.18
1.89
1.90
0.98
1.12
45 to 54
95%
confidence
interval
from
to
1.49
1.45
1.36
1.31
1.04
1.17
1.17
1.36
1.28
1.12
1.12
1.49
1.44
1.36
1.30
1.04
1.17
1.17
1.36
1.27
1.12
1.11
1.50
1.45
1.37
1.31
1.05
1.17
1.17
1.37
1.29
1.12
1.12
SSLR
1.01
0.88
1.04
0.94
0.97
0.99
0.97
1.01
0.94
1.04
0.91
55 to 64
95%
confidence
interval
from
to
1.01
0.87
1.03
0.94
0.97
0.99
0.97
1.01
0.94
1.04
0.91
1.01
0.88
1.04
0.94
0.98
0.99
0.98
1.01
0.94
1.04
0.91
65 or more
95%
confidence
interval
from
to
SSLR
0.64
0.77
0.72
0.81
1.08
0.86
0.93
0.65
0.71
0.84
1.06
0.64
0.76
0.71
0.81
1.08
0.86
0.92
0.65
0.70
0.84
1.05
0.65
0.77
0.72
0.82
1.09
0.86
0.93
0.66
0.71
0.84
1.06
SSLR
0.58
0.59
0.65
0.68
0.65
0.73
0.77
0.43
0.73
1.06
0.81
95%
confidence
interval
from
to
0.58
0.59
0.64
0.68
0.64
0.72
0.76
0.43
0.72
1.05
0.81
0.59
0.60
0.65
0.68
0.66
0.73
0.77
0.44
0.74
1.06
0.82
Source: 2009 Canadian Community Health Survey—Healthy Aging Cognition Module.
Table G
Odds ratios relating selected health status characteristics of respondents to 2009 Canadian Community Health Survey—
Healthy Aging Cognition Module, by delayed recall score, household population aged 45 or older, Canada excluding
territories
Delayed recall t-score
0 to 34
Health characteristic
Low self-rated health
Low self-rated mental health
Difficulties with activities of daily living
Low life satisfaction
High probability of depression
High loneliness
Unable to remember things
Unable to think/solve problems
Neurological disorder
Vascular disorder
Psychiatric disorder
Adjusted
degrees
of Adjusted
freedom chi-square
3.89
3.43
3.30
3.71
3.86
3.97
3.93
3.77
3.77
3.93
3.88
28.86
38.94
23.94
29.47
3.07
12.05
10.67
18.96
20.40
12.07
9.67
Odds
ratio
1.67
2.16
1.67
2.51
1.17
1.88
1.56
3.36
5.65
0.79
1.75
Note: Comparison group is 65 or more t-score category.
Source: 2009 Canadian Community Health Survey—Healthy Aging Cognition Module.
35 to 44
95%
confidence
interval
from
to
1.10
1.24
0.97
1.64
0.60
1.22
1.07
1.72
2.34
0.58
1.07
2.53
3.74
2.90
3.82
2.27
2.89
2.27
6.58
13.66
1.07
2.84
Odds
ratio
2.07
3.08
1.92
1.93
1.02
1.41
1.55
2.09
4.38
1.21
1.51
45 to 54
95%
confidence
interval
from
to
1.44
1.91
1.18
1.40
0.63
1.00
1.17
1.15
1.97
0.96
1.04
2.98
4.98
3.14
2.67
1.67
1.98
2.04
3.80
9.72
1.53
2.19
Odds
ratio
1.69
2.03
1.36
1.65
0.90
1.23
1.33
1.80
3.17
1.13
1.31
55 to 64
95%
confidence
interval
from
to
1.21
1.29
0.84
1.24
0.56
0.88
1.01
0.98
1.43
0.92
0.91
2.35
3.21
2.21
2.20
1.47
1.73
1.74
3.30
7.06
1.40
1.88
Odds
ratio
1.30
1.05
1.05
1.21
0.78
1.11
1.26
1.45
2.25
1.07
1.10
95%
confidence
interval
from
to
0.91
0.65
0.64
0.89
0.46
0.79
0.94
0.76
0.98
0.86
0.75
1.83
1.69
1.73
1.65
1.34
1.57
1.70
2.75
5.14
1.32
1.61
100
Health Reports, Vol. 21, no. 4, December 2010 • Statistics Canada, Catalogue no. 82-003-XPE
Validation of cognitive functioning categories in the Canadian Community Health Survey • Methodological insights
Table H
Odds ratios relating selected health status characteristics of respondents to 2009 Canadian Community Health Survey—
Healthy Aging Cognition Module, by animal-naming score, household population aged 45 or older, Canada excluding
territories
Animal-naming t-score
0 to 34
Health characteristic
Low self-rated health
Low self-rated mental health
Difficulties with activities of daily living
Low life satisfaction
High probability of depression
High loneliness
Unable to remember things
Unable to think/solve problems
Neurological disorder
Vascular disorder
Psychiatric disorder
Adjusted
degrees
of Adjusted
freedom chi-square
3.82
3.62
3.92
3.70
3.55
3.86
3.68
3.67
3.78
3.90
3.68
39.18
27.76
34.77
57.94
3.60
14.20
19.96
36.37
13.17
13.50
7.87
Odds
ratio
1.97
2.64
1.43
2.42
1.31
1.53
1.92
3.38
2.61
1.14
1.75
35 to 44
95%
confidence
interval
from
to
1.42
1.59
0.98
1.70
0.76
1.02
1.43
2.09
1.20
0.87
1.16
2.75
4.38
2.09
3.43
2.25
2.30
2.58
5.47
5.66
1.50
2.65
Odds
ratio
1.95
1.91
1.80
1.62
0.94
1.33
1.46
2.16
1.68
1.25
1.72
45 to 54
95%
confidence
interval
from
to
1.50
1.19
1.30
1.23
0.66
0.97
1.17
1.44
0.84
1.03
1.25
2.53
3.06
2.48
2.14
1.33
1.82
1.81
3.24
3.37
1.52
2.36
Odds
ratio
1.59
1.38
1.44
1.12
0.98
1.04
1.27
1.67
1.67
1.41
1.59
55 to 64
95%
confidence
interval
from
to
1.24
0.88
1.05
0.85
0.70
0.77
1.03
1.12
0.85
1.17
1.18
2.04
2.14
1.97
1.48
1.39
1.40
1.56
2.50
3.30
1.71
2.13
Odds
ratio
1.19
1.03
1.06
0.96
1.18
0.98
1.28
1.21
1.11
1.24
1.46
95%
confidence
interval
from
to
0.91
0.69
0.77
0.71
0.82
0.72
1.01
0.77
0.51
1.02
1.06
1.57
1.55
1.47
1.28
1.72
1.34
1.61
1.90
2.41
1.52
2.00
Note: Comparison group is 65 or more t-score category.
Source: 2009 Canadian Community Health Survey—Healthy Aging Cognition Module.
Table I
Odds ratios relating selected health status characteristics of respondents to 2009 Canadian Community Health Survey—
Healthy Aging Cognition Module, by Mental Alternation Test score, household population aged 45 or older, Canada
excluding territories
Mental Alternation Test t-score
0 to 34
Health characteristic
Low self-rated health
Low self-rated mental health
Difficulties with activities of daily living
Low life satisfaction
High probability of depression
High loneliness
Unable to remember things
Unable to think/solve problems
Neurological disorder
Vascular disorder
Psychiatric disorder
Adjusted
degrees
of
freedom
Adjusted
chisquare
Odds
ratio
3.83
3.78
3.92
3.89
3.90
3.78
3.89
3.59
3.87
3.95
3.93
99.35
26.20
57.02
42.25
4.80
16.45
15.72
47.03
21.92
17.98
4.96
2.34
2.71
1.78
2.23
1.69
1.92
1.53
4.35
2.58
0.92
1.37
Note: Comparison group is 65 or more t-score category.
Source: 2009 Canadian Community Health Survey—Healthy Aging Cognition Module.
35 to 44
95%
confidence
interval
from
to
1.67
1.55
1.25
1.54
0.93
1.26
1.11
2.67
1.28
0.71
0.83
3.28
4.74
2.51
3.23
3.07
2.92
2.11
7.09
5.22
1.20
2.25
Odds
ratio
2.56
2.44
2.10
1.92
1.70
1.60
1.52
3.15
1.76
1.06
1.37
45 to 54
95%
confidence
interval
from
to
1.95
1.38
1.58
1.44
1.07
1.18
1.19
2.15
0.98
0.87
0.90
3.37
4.32
2.79
2.57
2.71
2.19
1.94
4.60
3.16
1.30
2.09
Odds
ratio
1.74
1.48
1.60
1.39
1.48
1.36
1.27
2.34
1.29
0.98
1.12
55 to 64
95%
confidence
interval
from
to
1.31
0.86
1.20
1.06
0.94
1.00
1.01
1.61
0.70
0.81
0.75
2.30
2.55
2.12
1.81
2.32
1.85
1.58
3.39
2.36
1.18
1.68
Odds
ratio
1.11
1.30
1.10
1.20
1.68
1.18
1.20
1.51
0.97
0.80
1.30
95%
confidence
interval
from
to
0.84
0.74
0.83
0.90
1.06
0.86
0.94
1.00
0.51
0.65
0.86
1.46
2.27
1.47
1.59
2.67
1.62
1.54
2.29
1.83
0.97
1.96
Statistics Canada, Catalogue no. 82-003-XPE • Health Reports, Vol. 21, no. 4, December 2010
Erratum
101
Erratum
Errors were discovered in the article, “Income disparities in health-adjusted life expectancy for Canadian
adults, 1991 to 2001,” by Cameron McIntosh, Philippe Finès, Russell Wilkins and Michael C. Wolfson in
Health Reports, Volume 20, Number 4. Corrections were made in August, 2010.
Data errors were found in:
Table 4 (Remaining health-adjusted life expectancy (years) at age 25, by income decile and sex, Canada, 1991-2001);
Figure 1 (Remaining life expectancy and health-adjusted life expectancy at age 25, by income decile, men, Canada, 1991-2001); Figure 2 (Remaining life
expectancy and health-adjusted life expectancy at age 25, by income decile, women, Canada, 1991-2001); and Appendix Table C (Remaining health-adjusted
life expectancy (years) at age 25, by educational attainment and sex, Canada, 1991-2001).
The data in these tables and charts for both the HTML and PDF versions were corrected and replaced.
The text was revised to reflect these corrections:
Results
Disparities in health-adjusted life expectancy
Third sentence (page 59):
Disparities in health-adjusted life expectancy between the highest and lowest deciles were 14.1 years for men and 9.5 years for women, whereas the
corresponding disparities in conventional life expectancy were only 7.4 and 4.5 years, respectively.
Discussion
First paragraph, third sentence (page 60):
For both men and women at age 25, the difference in remaining health-adjusted life expectancy between the highest and lowest income groups was much
larger than the corresponding difference in overall life expectancy: 6.8 years more for men, and 5.0 years more for women.
Second paragraph, third sentence (page 60):
By contrast, in this analysis, which examines health-adjusted life expectancy at age 25, the difference between the highest income decile and the overall
average was estimated at 5.8 years for men and 3.1 years for women. For men, this was around twice the impact of all cancers combined, while for women, it
was about the same as the impact for all cancers combined.
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