Chronic Diseases and Injuries in Canada Inside this issue

Chronic Diseases and Injuries in Canada Inside this issue
Chronic Diseases and
Injuries in Canada
Volume 33 · Number 2 · March 2013
Inside this issue
55
Influence of viewing professional ice hockey on youth hockey
injuries
61
How active are children in Toronto? A comparison with
accelerometry data from the Canadian Health Measures Survey
69
Cancer incidence, mortality and survival trends in Canada,
1970–2007
81
Parenting disability, parenting stress and child behaviour in
early inflammatory arthritis
88
Population-based surveillance of asthma among workers in
British Columbia, Canada
95
Unintentional injury mortality and external causes in Canada
from 2001 to 2007
103 Report summary – Health-Adjusted Life Expectancy in
Canada: 2012 Report by the Public Health Agency of Canada
104 CSEB Student Conference 2012 abstract winners
Chronic Diseases and Injuries in Canada
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Associate Scientific Editor
University of Calgary
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Associate Scientific Editor
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Associate Scientific Editor
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Associate Scientific Editor
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Centers for Disease Control and Prevention
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Public Health Agency of Canada
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University of Ottawa
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V ancouver Island Health Authority
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McGill University
Andreas T. Wielgosz, MD, PhD, FRCPC
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Influence of viewing professional ice hockey on youth hockey
injuries
G. Keays, MSc (1); B. Pless, MD (2)
This article has been peer reviewed.
Abstract
Introduction: Most televised National Hockey League (NHL) games include violent
body checks, illegal hits and fights. We postulated that minor league players imitated
these behaviours and that not seeing these games would reduce the rate of injuries
among younger hockey players.
Methods: Using a quasi-experimental design, we compared 7 years of televised NHL
matches (2002–2009) with the year of the NHL lock-out (2004/2005). Data from the
Canadian Hospitals Injury Reporting and Prevention Program (CHIRPP) were used to
identify the injuries and to ascertain whether they were due to intentional contact and
illegal acts including fights.
Results: We found no significant differences in the proportions of all injuries and those
involving intentional contact, violations or illegal acts among male minor league hockey
players during the year when professional players were locked out and the years before
and after the lock-out.
Conclusion: We concluded that not seeing televised NHL violence may not reduce
injuries, although a possible effect may have been obscured because there was a striking
increase in attendance at equally violent minor league games during the lock-out.
Keywords: adolescent, males, television viewing, violence, sports injuries, hockey
Introduction
‘‘Sure you try what they do. You see them
do all sorts of things and get away with
it.’’ So said a 12-year-old hockey player
being interviewed on Canadian television
following the blind-side hit that concussed
National Hockey League (NHL) star,
Sidney Crosby, removing him from play
for nearly eleven months. Recent deaths of
NHL enforcers—players whose main role
is to fight—have fuelled the debate regarding ice hockey violence.
The influence of the media on the behaviour of viewers has been the subject
of controversy since the 1950s.1–3 In
particular, disagreement remains about
whether viewing violence on TV has a
negative effect on children. In 1975,
Rothenberg was convinced by 146 studies
‘‘that violence viewing produces increased
aggressive behaviour in the young.’’4
More recent reports, however, including
systematic reviews and meta-analyses,
have reached varying conclusions ranging
from no effect5 to clearly harmful.6–11
Nevertheless, the American Psychological
Association12 and the American Academy
of Pediatrics13 assert that the bulk of the
evidence points to negative effects.
Although most televised violence seen by
children is presented in cartoons or action
dramas, it is also evident in many sports
broadcasts. Ice hockey, in particular, has a
reputation for combining skilful play with
aggression. It has the highest rate of sport
injuries for boys14 and is second only to
football as a cause of catastrophic spinal
injuries.15 The amount of violence typically found on hockey broadcasts is
striking: about 40% of NHL games include
at least one fight16 and about 16% of all
severe injuries (e.g. those that force a
player to leave the game) are caused by
behaviours resulting in a penalty or
suspension.17 Minor professional hockey
leagues, viewed by many as the most
violent in hockey, generally have three to
four fights per game.18 Checking from
behind—an action usually associated with
severe injuries—only became illegal in
2000,19 and there is still controversy about
what to do about deliberate hits aimed at
the head (‘‘head shots’’).20 The macho
aspect of professional hockey delayed the
introduction of helmets until 197921 and
continues to delay compulsory visor use.22
In minor hockey, both have been obligatory for many years.
The behaviour of children and youth
playing in minor leagues seems to be
influenced by their watching televised
NHL games.23–27 A survey showed that
90% reported having learned a ‘‘behaviour, technique or skill’’ from watching
professional hockey players. In addition,
56% stated they had copied illegal tactics
of professional players at least once during
the current hockey season.28 Another
survey indicated that high school hockey
players who chose aggressive NHL players
as role models were more likely to assault
others during games.29 More recently, a
Author references:
1. McGill University Health Centre, Montreal Children’s Hospital, Montréal, Quebec, Canada
2. Department of Pediatrics, Epidemiology and Biostatistics, McGill University, Montréal, Quebec, Canada
Correspondence: Glenn Keays, McGill Health Centre, Montreal Children’s Hospital, 2300 Tupper, Room CB-27, Montréal, QC
Email: glenn@keays.ca
$
55
H3H 1P3; Tel.: 514-412-4400 ext 2316; Fax: 514-412-4477;
Vol 33, No 2, March 2013 – Chronic Diseases and Injuries in Canada
report commissioned by the ministry of
sports in British Columbia noted that 27%
of the 144 young hockey players surveyed
imitated illegal hits they had seen after
watching NHL players.30
Accordingly, we concluded there was a
reasonable basis for postulating that not
watching professional hockey on TV would
improve the behaviour of younger players
such that there would be fewer injuries. To
examine this hypothesis, we took advantage of a natural experiment: during the
winter of 2004/2005, owners locked out
NHL players during a contract dispute. As a
result, except for replays of old NHL games
in April 2005 and junior league championship games at the end of May, there was no
hockey on Canadian television. We investigated whether the absence of televised
professional hockey during this season was
associated with a lower rate of injuries
among minor league players.
Methods
Our study was restricted to boys playing
organized hockey in formal minor leagues
in Canada throughout seven successive
seasons beginning in 2002/2003. Minor
leagues are categorized as peewees, bantams, or midgets according to the age of
the players.31
We considered only those injuries that
occurred during the regular NHL season.
The Canadian Hospitals Injury Reporting
and Prevention Program (CHIRPP)32,33
provided details concerning the injuries.
CHIRPP is an injury surveillance system
situated in 14 emergency departments in
seven provinces. It gathers information
from parents of patients (or older patients)
regarding the circumstances of the injury
and includes medical details such as the
nature of the injury, the body part and the
treatment.
We used several definitions to describe the
cause or mechanism of the injury. Initially,
we compared all injuries to ‘‘contact-related
injuries,’’ which include all types of contact, intentional or not. Then, we analysed
two specific types of contacts. The first,
‘‘injuries due to illegal contact,’’ refers to
those cases caused by an illegal hit (or act),
as defined by Hockey Canada:31 elbowing
(extending elbow in a manner to cause
injury), cross-checking (using the shaft of
the stick to forcefully check an opponent),
checking from behind, boarding (checking
a defenceless opponent so as to cause him
to impact the boards violently), checking to
the head, kneeing (leading with the knee to
make contact with the opponent), slashing
(any forceful or powerful chops with the
stick on an opponent’s body), tripping
(placing the stick, knee, foot, arm, hand
or elbow in way that causes the opponent to
trip or fall), roughing, or any acts of
violence such as fights, altercations and
deliberate punches. The second category,
‘‘injuries due to fights,’’ includes all injuries
resulting from fights, altercations and deliberate punches.
To calculate rates, we obtained from
Hockey Canada, for each year of study,
the numbers of boys aged 11 to 17 years
registered in each of the minor hockey
leagues and expressed the proportion as
numbers of injuries per 1000 registered
male players in this age group in all the
cities with pediatric CHIRPP centres.
Confidence intervals for individual rates
and individual proportions were calculated using the Poisson test.
Results
From September to April in the years 2002
to 2009, CHIRPP reported 14 717 hockey
injuries for 11- to 17-year-old boys. Of the
injured, 24% were peewees (11- to 12year-olds), 39% were bantam (13- to 14year-olds) and 37% were midgets (15- to
17-year-olds). During most years, at each
level, about 70% of the injuries were
contact related. For all age levels combined, the rates per 1000 registered
players varied from 19.0 to 24.9 for any
injury and from 13.7 to 18.4 for those
judged to be contact related (Table 1). The
data do not reveal, however, any pattern
or trend over time nor any evidence that
the proportion of injuries changed markedly when the lock-out year is compared
with the preceding or following years. The
same is true when these data are examined for each league or age group.
Although not statistically significant,
Table 2 shows a consistent pattern indicating slightly more injuries arising from
Vol 33, No 2, March 2013 – Chronic Diseases and Injuries in Canada
$
56
acts that were judged to be dangerous,
that is, intentional or illegal, during the
lock-out year.
Figure 1 shows attendance records at
minor professional league games before,
during and after the lock-out. We reasoned that, deprived of NHL games on TV,
avid fans would compensate by attending
these games, some of which were televised. The figure clearly shows that there
was a peak in attendance at these games
during the lock-out; what the figure does
not reveal is that many contend that
spectators attend these games in part
because of their violence.34,35 Players
and coaches of these teams accept that
the ‘‘goon’’ (who play hockey with an
emphasis on intimidation and violence) is
part of the games’ appeal.36,37
Discussion
Professional hockey is violent because it
relies on aggressive play. In Violence and
Sport, Smith28 defines aggression as ‘‘any
behaviour designed to injure another
person, psychologically or physically.’’ It
is physical violence that typifies much of
professional hockey. Robidoux and
Trudel38 observe that ‘‘body-checking is
an example of the regulated use of
physical force to gain an advantage … it
clearly leads to an increase in injuries.’’
Several previous studies suggest that
observing the behaviour of professionals
during televised hockey matches influences young hockey players.25,28–30,39,40
Contrary to what we expected, however,
we found no consistent difference
between rates of injuries of all kinds when
youngsters were not watching NHL games
on TV versus seasons when they were.
Nonetheless, the belief that young players
imitate viewing violence on TV remains
plausible and prompted us to search for an
explanation.
One explanation is that the behaviours
related to youth hockey injuries are so
deeply ingrained that they are not likely to
change after only one year during which
they were not reinforced by viewing the
actions of professional players. A second
possible explanation is that, by way of
compensation, during the lock-out junior
players attended more minor professional
TABLE 1
Approximate ratesa of all hockey injuries and contact-related injuries by league (age group) and season per 1000 minor league players (11–17
years), all CHIRPP centres, Canada
Hockey season
Registered players,
n
All injuries
Contact-related injuries
n
Rates/1000 (95% CI)
n
Rates/1000 (95% CI)
PEEWEES
(11–12 years)
2002/2003
32561
596
18.3
(16.9–19.8)
440
13.5
(12.3–14.8)
2003/2004
34541
508
14.7
(13.5–16.0)
356
10.3
(9.3–11.4)
2004/2005
32339
492
15.2
(13.9–16.6)
362
11.2
(10.1–12.4)
2005/2006
35492
449
12.7
(11.5–13.9)
322
9.1
(8.1–10.1)
2006/2007
33526
482
14.4
(13.1–15.7)
356
10.6
(9.6–11.8)
2007/2008
32235
525
16.3
(14.9–17.7)
392
12.2
(11.0–13.4)
2008/2009
34354
523
15.2
(14.0–16.6)
378
11.0
(9.9–12.2)
2002/2003
30116
939
31.2
(29.2–33.2)
682
22.6
(21.0–24.4)
2003/2004
30448
861
28.3
(26.4–30.2)
624
20.5
(18.9–22.2)
2004/2005
30848
833
27.0
(25.2–28.9)
604
19.6
(18.1–21.2)
2005/2006
33332
761
22.8
(21.3–24.5)
558
16.7
(15.4–18.2)
2006/2007
31249
731
23.4
(21.7–25.1)
535
17.1
(15.7–18.6)
2007/2008
30049
754
25.1
(23.4–26.9)
558
18.6
(17.1–20.2)
2008/2009
32978
854
25.9
(24.2–27.7)
619
18.8
(17.3–20.3)
28023
721
25.7
(23.9–27.7)
544
19.4
(17.8–21.1)
BANTAMS
(13–14 years)
MIDGETS
(15–17 years)
2002/2003
2003/2004
28152
837
29.7
(27.8–31.8)
614
21.8
(20.1–23.6)
2004/2005
28597
738
25.8
(24.0–27.7)
562
19.7
(18.1–21.3)
2005/2006
32615
715
21.9
(20.4–23.6)
510
15.6
(14.3–17.0)
2006/2007
32070
813
25.4
(23.7–27.1)
577
18.0
(16.6–19.5)
2007/2008
29963
777
25.9
(24.2–27.8)
570
19.0
(17.5–20.6)
2008/2009
34970
808
23.1
(21.6–24.7)
601
17.2
(15.9–18.6)
2002/2003
90700
2256
24.9
(23.9–25.9)
1666
18.4
(17.5–19.3)
2003/2004
93141
2206
23.7
(22.7–24.7)
1594
17.1
(16.3–18.0)
2004/2005
91784
2063
22.5
(21.6–23.5)
1528
16.6
(15.9–17.5)
2005/2006
101438
1925
19.0
(18.2–19.9)
1390
13.7
(13.0–14.5)
2006/2007
96844
2026
20.9
(20.1–21.9)
1468
15.2
(14.4–16.0)
ALL PLAYERS
(11–17 years)
2007/2008
92248
2056
22.3
(21.4–23.3)
1520
16.5
(15.7–17.4)
2008/2009
102302
2185
21.4
(20.5–22.3)
1598
15.6
(14.9–16.4)
Sources: Canadian Hospitals Injury Reporting and Prevention Program32; Hockey Canada (http://www.hockeycanada.ca/index.php/ci_id/23952/la_id/1.htm).
Abbreviations: CHIRPP, Canadian Hospitals Injury Reporting and Prevention Program; NHL, National Hockey League.
Notes: 2004/2005 (bolded) was the year when owners locked out NHL players during a contract dispute. As a result, except for replays of old NHL games in April 2005 and junior league
championship games at the end of May, there was no hockey on Canadian television.
a
Injuries treated in children’s hospital emergency departments do not necessarily parallel the denominator data of registered players. Thus, the rates we used are not ‘‘true’’ rates in that the
numerators and denominators are from different populations.
league games. Paradoxically perhaps,
these are widely regarded as even more
violent than NHL games,34–37 and it is
noteworthy, as Figure 1 shows, that there
was a striking increase in attendance at
these games during the lock-out.41,42
$
57
Thus, exposure to violence may have
remained much the same for the entire
period of the study.
Vol 33, No 2, March 2013 – Chronic Diseases and Injuries in Canada
TABLE 2
Proportions of injuries due to illegal acts and fights during organized hockey, by minor hockey league and year, 2002/2003 to 2008/2009
Hockey season
a
All injuries,
Injuries due to illegal acts
n
%
(95% CI)
Injuries due to fights
%
b
(95% CI)
PEEWEES (11–12 years)
2002/2003
596
22.5
(18.1–26.9)
0.5
(0.0–1.3)
2003/2004
508
16.7
(12.5– 21.0)
0.2
(0.0–0.8)
2004/2005
492
27.4
(22.3–32.7)
1.2
(0.0–2.5)
2005/2006
449
25.4
(20.1–30.7)
0.4
(0.0–1.3)
2006/2007
482
21.8
(17.0–26.7)
0.2
(0.0–0.8)
2007/2008
525
26.5
(21.6–31.5)
0.6
(0.0–1.5)
2008/2009
523
22.9
(18.3–27.7)
0.2
(0.4–0.7)
2002/2003
939
17.1
(14.0–20.4)
0.2
(0.0–0.7)
2003/2004
861
13.8
(10.8–16.9)
0.6
(0.0–1.3)
2004/2005
833
18.7
(15.3–22.3)
1.0
(0.1–1.9)
2005/2006
761
18.3
(14.7–21.9)
0.4
(0.0–1.0)
2006/2007
731
18.5
(14.8–22.2)
0.8
(0.0–1.7)
2007/2008
754
16.4
(13.0–20.0)
0.9
(0.1–1.9)
2008/2009
854
17.6
(14.3–21.0)
0.5
(0.0–1.1)
721
17.2
(13.6–20.9)
1.9
(0.7–3.3)
BANTAMS (13–14 years)
MDGETS (15–17 years)
2002/2003
2003/2004
837
19.5
(16.0–23.1)
1.9
(0.7–3.2)
2004/2005
738
23.2
(19.2–27.2)
2.7
(1.2–4.3)
2005/2006
715
19.3
(15.5–23.2)
1.3
(0.2–2.4)
2006/2007
813
17.2
(13.9–20.7)
1.6
(0.5–2.8)
2007/2008
777
19.9
(16.3–23.7)
2.1
(0.8–3.4)
2008/2009
808
19.3
(15.8–22.9)
1.6
(0.5–2.8)
2256
18.6
(16.5–20.7)
0.8
(0.4–1.4)
ALL PLAYERS (11–17 years)
2002/2003
2003/2004
2206
16.6
(14.6–18.7)
1.0
(0.5–1.6)
2004/2005
2063
22.4
(20.1–24.8)
1.6
(1.0–2.4)
2005/2006
1925
20.3
(18.0–22.7)
0.7
(0.3–1.3)
2006/2007
2026
18.8
(16.6–21.0)
1.0
(0.5–1.6)
2007/2008
2056
20.3
(18.1–22.7)
1.3
(0.7–1.9)
2008/2009
2185
19.5
(17.4–21.7)
0.8
(0.4–1.4)
32
Source: Canadian Hospitals Injury Reporting and Prevention Program ; Hockey Canada (http://www.hockeycanada.ca/index.php/ci_id/23952/la_id/1.htm)
Abbreviation: NHL, National Hockey League.
Notes: 2004/2005 (bolded) was the year when owners locked out NHL players during a contract dispute. As a result, except for replays of old NHL games in April 2005 and junior league
championship games at the end of May, there was no hockey on Canadian television.
a
Illegal acts: hooking, tripping, holding, cross-checking, checking from the back, slashing, elbowing, boarding, checking to the head, kneeing, slashing, roughing.
b
Fights and altercations.
Limitations
We acknowledge several limitations. First,
CHIRPP data only include a portion of all
injuries across Canada, which cannot be
regarded as a genuine sample of these
injuries. The injuries treated in children’s
hospital emergency departments do not
necessarily parallel the denominator data
of registered players. Thus, we accept that
the rates we used are not true rates in that
the numerators and denominators are
from somewhat different populations.
However, it is the relative comparisons
Vol 33, No 2, March 2013 – Chronic Diseases and Injuries in Canada
$
58
that we were examining and there is no
reason to believe that the relationship
changed over the study period.
A second limitation is that there is often
insufficient detail in CHIRPP reports to be
certain whether an injury was caused by
FIGURE 1
Attendance records from two minor professional hockey leagues (North American Hockey
League and the American Hockey League) between the 2002/2003 and 2008/2009 hockey
seasons
(n)
hospitals and acknowledge the work of
Steven McFaull and Robin Skinner, Health
Canada, for making the CHIRPP dataset
available to us.
References
NHL lockout
8500
8000
1.
Maccoby EE. Television: its impact on school
children. Public Opin Quart. 1951;15(3):421–4.
2.
Bandura A, Walters RH. Social learning and
personality development. New York: Holt,
Rinchast and Winston; 1963.
3.
Berkowitz L. Aggression: a social psychological analysis. New York: McGraw-Hill;
1962.
4.
Rothenberg MB. Effect of television violence on children and youth. JAMA.
1975;234(10):1043–6.
5.
Ferguson CJ. Media violence: miscast causality. 2002. Am Psychol. 2002;57(6–7):446–7.
6.
Ybarra ML. Linkages between depressive
symptomatology and Internet harassment
among young regular Internet users.
Cyberpsychol Behav. 2004;7(2):247–57.
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Villani S. Impact of media on children and
adolescents: a 10-year review of the research.
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Bar-on ME. The effects of television on
child health: implications and recommendations. Arch Dis Child. 2000;83(4):289.
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Browne KD, Hamilton-Giachritsis C. The
influence of violent media on children and
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Lancet. 2005;365(9460):702–10.
7500
7000
6500
6000
2002-3
2003-4
2004-5
2005-6
2006-7
2007-8
2008-9
Sources: www.theahl.com, www. lnah.com.
Abbreviation: NHL, National Hockey League.
an aggressive or illegal act, and there are
missing data. However, all records are
coded centrally by trained coders and the
information regarding the nature of injury
and level of treatment is generally consistent over time. Again, unless there is
reason to assume a change in these
variables over time, our comparisons are
justified.
Third, we did not attempt to verify that all
our subjects actually watched televised
NHL games between 2002 and 2008.
However, the Canadian Broadcasting
Corporation (CBC) recently announced
Hockey Night in Canada as its highest
rated show, estimating that 78% of
Canadians aged 25 to 54 years watch
NHL games.43 If we apply the same
proportion to our target group of 11- to
17-year-old male adolescents living in
Canada and note that NHL hockey games
were not only broadcast by the CBC, we
can comfortably assume that there are at
least one million boys of that age watching
the NHL regularly. Moreover, given the
extent to which ice hockey is part of
Canadian culture, it would be surprising if
most games involving home teams were
not also watched. In addition, we believe
it reasonable to assume that, except for the
lock-out season where there was nothing
to watch, the proportion of young spectators remained the same over the study
years.
Finally, although we cannot be certain
that young hockey players were part of the
increase in attendance in minor professional leagues during the lock-out, it
seems reasonable to assume that they
were. Although attendance went up significantly, even if this included children
and adolescents it would not come close to
the number of children and adolescents
who watch televised hockey.
Although not statistically significant based
on Jonckheere trend test (p = .099), it is
worth noting that the data in Table 1
suggest a small decline in these injuries
over time. If true, this development may
represent the success of various preventive initiatives or a decreased propensity
to go to emergency departments when an
injury occurs.
Conclusion
In spite of a reasonable hypothesis, we
failed to demonstrate that not viewing the
violence that typifies so much of professional hockey has a beneficial effect on the
behaviour of young players. Specifically,
we found no significant differences in the
rates of injuries during one year when
professional players were locked out and
there were no televised hockey broadcasts. However, the effect may have been
partly obscured by compensatory viewing
of even more violent junior league games.
Acknowledgments
We thank the CHIRPP directors for providing permission to use data from their
$
59
10. Hopf WH, Huber GL, Weiss RH. Media
violence and youth violence: a 2-year
longitudinal study. J Media Psychol.
2008;20(3):79–96.
11. Huesmann LR, Taylor LD. The role of
media violence in violent behavior. Annu
Rev Publ Health. 2006;27:393–415.
12. McIntyre JJ; American Psychological
Association. On the impact of media violence
on children [Internet]. Testimony before the
United States Senate Committee on
Commerce, Science, and Transportation.
2007 [cited 2011 Sep 7]. Available from:
http://www.apa.org/about/gr/pi/advocacy
/2007/mcintyre-media.aspx
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13. Council on Communications and Media.
From the American Academy of Pediatrics:
policy statement--media violence. Pediatrics.
2009;124(5):1495–503.
14. Benson BW, Meeuwisse WH. Ice hockey
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15. Boden BP, Jarvis CG. Spinal injuries in
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25. Nash JE, Lerner E. Learning from the pros:
violence in youth hockey. Youth Soc.
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37. Conacher B. As the puck turns: a personal
journey through the world of hockey.
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26. Kerr JH. Book review: Aggression in the
sports world: a social psychological perspective. Int J Sport Manage Market.
2009;5(4):477–8.
38. Robidoux M, Trudel P. Hockey Canada and
the bodychecking debate in minor hockey.
In: David Whitson D, Gruneau R, editors.
Artificial ice: hockey, culture, and commerce. Toronto (ON): University of
Toronto Press; 2006:101–22.
27. Smith MD. Violence and injuries in ice
hockey. Clin J Sport Med. 1991;1(2):104–9.
16. Singer, DM. Hockey Fights [Internet]. [cited
2011 Sep 7]. Available from: http://www
.hockeyfights.com
28. Smith MD. Violence and sport. Toronto
(ON): Butterworths; 1983.
17. TSN. NHL injuries [Internet]. [cited 2011
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29. Smith MD. Significant others’ influence on
the assaultive behavior of young hockey
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18. NHL fights [Internet]. [cited 2011 Sep 7].
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/Fights/LeagueFights.aspx?League=1
30. Pascall B, White S. Eliminating violence in
hockey. Vancouver (BC): Ministry of Small
Business, Tourism and Culture; 2000 May.
19. IIHF. IIHFederation Rule Book, 2010–2014
[Internet]. Zurich (CH): The International
Ice Hockey Federation; 2010 [cited 2011
Sep 7]. Available from: http://www.iihf
.com/iihf-home/sport/iihf-rule-book.html
31. Hockey Canada. Articles, by-laws, regulations, history as adopted at Ottawa,
December 4, 1914 and amended to June
2009.
Effective
2009–2010
Season
[Internet]. Canada: Hockey Canada; 2009
[cited 2011 Sep 7]. Available from: http://
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/66601/la_id/1.htm
20. Associated Press. NHL GMs form committee
to study headshots [Internet]. Ottawa (ON):
The National Hockey League; 2009 Nov 11
[cited 2011 Sep 7]. Available from: http://
www.nhl.com/ice/news.htm?id=505769
21. Duhatsche E. Should visors be mandatory
in the NHL? [Internet]. Toronto (ON): The
Globe and Mail; 2011 Nov 22 [cited 2012
Jan 7]; Available from: http://m
.theglobeandmail.com/sports/hockey/globeon-hockey/should-visors-be-mandatory-inthe-nhl/article1951461/?service=mobile
22. Anderson D. Sports of the times; the great
visor debate in hockey [Internet]. New
York: The New York Times; 2000 Mar 22
[cited 2012 Jan 7]; Available from: http://
www.nytimes.com/2000/03/22/sports
/sports-of-the-times-the-great-visor-debatein-hockey.html
23. Cusimano MD. Canadian minor hockey
participants’ knowledge about concussion.
Can J Neurol Sci. 2009;36(3):315–20.
24. Gee CJ, Leith LM. Aggressive behavior in
professional ice hockey: a cross-cultural
comparison of North American and
European born NHL players. Psychol
Sport Exerc. 2007;8(4):567–83.
32. Canadian Hospitals Injury Reporting and
Prevention Program (CHIRPP) [Internet].
Ottawa (ON): Public Health Agency of
Canada; 2011 [cited 2011 Sep 7].
Available from: http://www.phac-aspc
.gc.ca/injury-bles/chirpp/index-eng.php
33. Mackenzie SG, Pless IB. CHIRPP: Canada’s
principal injury surveillance program. Inj
Prev. 1999;5(3):208–13.
34. Zhang JJ, Lam ET, Connaughton EP,
Bennett G, Pease DG, Pham UL, etc.
Variables affecting spectator enjoyment of
minor league hockey games. Int J Sport
Manage Market. 2004;5:1–26.
35. Andrew DP, Koo GY, Hardin R, Greenwell
TC. Analysing motives of minor league
hockey fans: the introduction of violence as
a spectator motive. Int J Sport Manag
Market. 2009;5:73–89.
36. Andrijiw AM. Life after hockey: an examination of athletic career transition and the
National Hockey League’s career transition
program. Saint Catherine (ON): Faculty of
Applied Health Sciences, Brock University;
2010.
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39. Reid SR, Losek JD. Factors associated with
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players.
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media. In: Gamon MA, editor. Violence in
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7]. Available from: http://theahl.com/ahlattendance-surpasses-7-million-p136423
43. Number 1 NHL broadcast in Canada. CBC
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from:
http://www.cbc.ca/revenuegroup
/images/HNIC%20-%20Fall%202011.pdf
How active are children in Toronto? A comparison with
accelerometry data from the Canadian Health Measures Survey
M. R. Stone, PhD (1); G. E. Faulkner, PhD (2); R. N. Buliung, PhD (3)
This article has been peer reviewed.
Abstract
Introduction: The Canadian Health Measures Survey (CHMS) is the most
comprehensive direct health measures survey ever conducted in Canada. Results
show that the majority of children and youth (93%) do not meet current physical activity
recommendations for health. CHMS data have not yet been considered alongside an
independent sample of Canadian youth; such a Canadian-context examination could
support CHMS results and contribute to discussions regarding accelerometry data
reduction protocols.
Methods: From 2010 to 2011, valid accelerometry data were collected on 856 children
living in the Greater Toronto Area (GTA). Where possible, data presentation and
analyses were aligned with the CHMS protocol such that physical activity outcomes
could be compared.
Results: Overall, trends were similar, with some deviations likely due to contextual and
sampling differences and differences in data collection/reduction protocols regarding
accelerometer model selection, wear time, activity intensity thresholds and epoch.
Conclusion: The similar trends support the notion that physical inactivity is an ongoing
problem in communities across Canada.
Keywords: ActiGraph, accelerometer, physical activity, sedentary behaviour, obesity,
public health, youth, CHMS
Introduction
Regular physical activity in childhood is
associated with many physical, physiological and mental health benefits.1
Canada’s physical activity guidelines suggest children and adolescents aged 5 to
17 years accumulate at least 60 minutes
of moderate-to-vigorous physical activity
(MVPA) each day.2 There is also evidence
that they should engage in vigorous
physical activity (VPA) at least 3 days a
week.2 While self-report and pedometer
data have provided some evidence of
national physical activity trends over
time,3 direct, objective assessments using
accelerometry (on a national scale) have
been absent until recently.
March 2011 saw the release of physical
activity and sedentary behaviour data
collected on a nationally representative
sample of Canadian children and youth
(n = 1608; boys = 809; girls = 799) as
part of the Canadian Health Measures
Survey (CHMS).4 Actical accelerometers
(Phillips – Respironics, Oregon, US) were
used to capture minute-by-minute data
over 7 consecutive days. Information was
extracted using quality control and data
reduction decisions5 on the amount of
time children and youth typically spend
sedentary and in light, moderate and
vigorous intensity physical activity; the
amount of time spent in MVPA; the
average number of steps taken per day;
and the percentage of children attaining
selected physical activity criteria. Results
indicated that very few (7%) achieve
recommended levels of physical activity
(with more boys achieving guidelines
than girls), and many spend a significant
portion of their day sedentary (average of
8.6 hours per day).4
The CHMS is the most comprehensive
direct health measures survey conducted
in Canada. In addition to national estimates of physical activity levels, the study
has also shed light on the declining levels
of fitness observed in Canadian youth over
the past few decades.6 These data have
received considerable public interest and
media attention. They have also fuelled
national campaigns (i.e. ParticipACTION;
www.participaction.com) to increase
population-wide levels of physical activity
in children and youth. Comparisons with
nationally representative data from the
United States7 revealed similar trends in
physical activity and sedentary behaviour,
despite some contextual, sampling and
methodological differences between the
two datasets. However, to our knowledge
CHMS data have yet to be compared with
an independent sample of Canadian children and youth. It would be relevant
to verify their accuracy, given the widespread dissemination of the CHMS findings and their impact on research, policy
and practice across Canada.
The aim of this study is to present
accelerometer data from another study,
Author references:
1. School of Health and Human Performance, Dalhousie University, Halifax, Nova Scotia, Canada
2. Faculty of Kinesiology and Physical Education, University of Toronto, Toronto, Ontario, Canada
3. Department of Geography, University of Toronto Mississauga, Mississauga, Ontario, Canada
Correspondence: Michelle R. Stone, School of Health and Human Performance, Dalhousie University, 6230 South Street, Halifax, NS B3H 4R2; Tel.: (902) 494-1167; Fax: (902) 494-1084;
Email: michelle.stone@dal.ca
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Vol 33, No 2, March 2013 – Chronic Diseases and Injuries in Canada
Project BEAT, in a similar fashion to the
way CHMS data have been reported,
and discuss similarities and discrepancies
between the two datasets.
Methods
Data source
Project BEAT (Built Environment and
Active Transport; www.beat.utoronto.ca)
is a large-scale, multidisciplinary and
mixed method study examining how the
built environment influences the way
elementary school children travel to
school in Toronto, Ontario. In January
2010 all elementary schools with Grade 5
and 6 students within the Toronto District
School Board (n = 469) received an
invitation to participate. Out of the pool
of interested schools (54 responded,
40 of which were interested; response
rate = 11.5%), 16 were selected because
they varied with respect to built form
(suburban looping street layout versus
urban grid-based street layout) and
socio-economic status (SES; low- and
high-income households based on median
household income reported in the 2006
Canada Census). Half of the surveyed
schools were low-SES schools, and
the other half were high-SES schools.
Consent was obtained from participating school boards, individual schools,
parents and students. Student participation was voluntary. Ethics approval from
the Toronto District School Board and
University of Toronto Ethics Committee
was received.
wear an accelerometer for a minimum of
10 hours for at least 3 weekdays and 1
weekend day. A string of 30 minutes of
consecutive zeros was classified as nonwear time/sleep time; these periods
(most of which occurred during sleep)
were removed from the analyses.
Biologically implausible data were
assessed to determine whether to include
files in the final analyses. Of the 1001
children who wore an accelerometer,
95.8% had at least 1 valid day of data
and 85.5% had at least 3 weekdays and
1 weekend day of valid data (n = 856;
boys = 389, girls = 467; Table 1). This
article is therefore based on these 856
participants (mean age [standard deviation] 11.1 [0.6] years), who met these
inclusion parameters. This final response
rate (856/1704 = 50.2%) is consistent
with other active-consent studies with
Canadian elementary school students.8
Using age- and sex-specific BMI cut-points
provided by the International Obesity
Task Force,9 participants were classified
as normal weight, overweight or obese
(Table 2).
Children’s physical activity was measured
for seven days using an accelerometer
(ActiGraph GT1M; Pensacola, FL, United
States). The ActiGraph series are the most
commonly used devices in the field, and
they have moderate to good validation in
children.10 Prior to data collection, the
intra-unit and inter-unit variability of all
ActiGraph monitors (n = 120) was tested
using a standardized treadmill protocol.
The coefficients of variation were within
acceptable limits.11,12
We used a 5-second epoch to capture
rapid transitions in activity typical in
children and related to health outcomes.13
Children were asked to wear their
accelerometer consistently; they were
asked to only remove the device when
engaging in water-based activities. The
monitors were initialized to start collecting data at 12:00 A.M. on the day they
were handed out to participants. The first
day was excluded from data analyses to
TABLE 1
Distribution of Project BEAT and CHMS participants, by valid days of accelerometer wear
(10 or more wear hours), age group and sex
Number of valid days of accelerometer wear, %
0
1
2
3
4
5
6
7
§1
§ 4b
Total
4.2
1.8
1.6
6.9
2.1
7.9
21.9
53.6
95.8
85.5
Boys
4.1
2.6
1.7
7.6
1.7
8.4
20.5
53.3
95.9
84.0
Girls
4.3
1.1
1.5
6.3
2.4
7.4
23.0
53.9
95.7
86.8
4.6
2.9
3.6
4.1
8.2
12.7
24.0
39.8
95.4
84.7
Boys
2.7
2.4
3.2
1.5
6.4
11.5
24.7
47.7
97.3
90.2
Girls
4.2
2.4
2.1
1.8
6.6
13.4
22.1
47.4
95.8
89.5
Boys
4.4
2.0
1.7
5.1
6.4
11.9
30.5
38.0
95.6
86.8
Girls
3.2
2.8
3.6
2.1
7.8
12.1
23.1
45.2
96.8
88.3
Study, Age group
a
Project BEAT
10–12 years
Participants
Of the 1704 students enrolled in Grades 5
through 6 at the 16 participating schools,
1027 (60.3%; boys, n = 478; girls, n = 549)
completed the travel behaviour survey and
were given consent to participate in the
study by their parents/guardians; missing
responses resulted from parent or student
refusal. Prior to any data collection, children
completed an assent form (n = 1001; 26
students were absent for data collection).
Height and weight were measured to
calculate body mass index (BMI), and
accelerometer-measured physical activity
data were collected. For inclusion in
data analysis, each child was required to
Measurement of physical activity and
sedentary behaviour
CHMS
Totalc
6–10 years
11–14 years
Sources: Built Environment and Active Transport (BEAT) Project (2010–2011); 2007–2009 Canadian Health Measures Survey
(CHMS)4
Abbreviations: BEAT, Built Environment and Active Transport; CHMS, Canadian Health Measures Survey.
a
Agreed to wear accelerometer, but returned device with no valid data (invalid wear or device malfunctioned).
b
Three weekdays and one weekend day.
c
Total includes additional age group (aged 15–19 years) sampled in CHMS. Remainder of table reflects results for those aged
6–10 years and 11–14 years, in light of Project BEAT’s sample demographics (aged 10–12 years).
Vol 33, No 2, March 2013 – Chronic Diseases and Injuries in Canada
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TABLE 2
Descriptive characteristics of Project BEAT and CHMS participants, by age group and sex
Project BEAT
Canadian Health Measures Survey (CHMS)
10–12 years
6–10 years
Characteristics
Boys
Girls
Boys
Sample size, n
389
467
369
11–14 years
Girls
Boys
340
256
Girls
248
Mean age, years
11.0
11.1
8.2
8.1
12.5
12.3
Mean height, cm
147.2
Mean weight, kg
2
Mean BMI, kg/m
147.5
133.9
131.6
158.9
156.9
42.3a
40.9
32.5
29.9
52.1
50.6
a
19.3
18.6
17.8
17.0
20.3
20.4
67.4a
73.9
74.4
82.5
72.5
70.5
21.5
23.0E
BMI category, %b
Normal
Overweight
Obese
21.9
a
10.8
21.6
4.5
E
17.1
E
8.1
E
12.6
E
E
4.9
6.0
6.5E
Sources: Built Environment and Active Transport (BEAT) Project (2010–2011); 2007–2009 Canadian Health Measures Survey
(CHMS).4
Abbreviations: BEAT, Built Environment and Active Transport; BMI, body mass index; CHMS, Canadian Health Measures
Survey.
a
Significantly different from girls; p < .05.
b
International Obesity Task Force classification.9
E
Use with caution.
control for any participant reactivity and
because they were often handed out midday. Data collection took place during the
Spring/Summer (April to June) and Fall
(September to December) school period to
limit any seasonal effect.
was also calculated. The probability of
accumulating any VPA (at least 5, 10
and 20 minutes) on at least 1, 2, 3, 4,
5 or 6 days of the week was also
calculated. Minimal activity was assumed
on missing days.
Time spent at various levels of movement
intensity (sedentary, light, moderate,
vigorous, hard) was classified according
to published thresholds in children14 and
used to determine accumulated minutes
of sedentary behaviour; light, moderate,
vigorous and hard activity; and MVPA.
The percentage of time spent sedentary, in
light intensity activity and in MVPA were
calculated using wear time data (the
percentage of time spent in hard intensity
activity was <1%, and therefore not
reported). The proportion of children
attaining different physical activity targets
was examined in line with CHMS analyses. For example, Canadian and World
Health Organization (WHO) physical
activity guidelines recommend 60 minutes
of MVPA each day.2,15 Like the CHMS
analyses, adherence was defined as
the probability of accumulating at least
60 minutes of MVPA at least 6 days a
week. The probability of accumulating at
least 30, 60 and 90 minutes of MVPA on
at least 1, 2, 3, 4, 5 or 6 days of the week
Statistical analyses
All analyses were conducted using SPSS
version 19.0 for Windows (IBM, Armonk,
NY, US) and were based on data for
participants with at least 4 valid days.
Similar to CHMS output, comparisons of
physical activity intensity and duration
were made according to gender and
body weight classification (normal weight,
overweight and obese)9 using mixedmodel ANOVAs with pair-wise contrasts.
Differences between estimates were tested
for statistical significance (p < .05).
Results
Participants
Table 1 shows a comparison of accelerometer wear by age group and sex between
the studies. Table 2 shows the demographic characteristics (gender distribution, mean age, height, weight and BMI)
for Project BEAT and CHMS participants.
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63
Hours spent sedentary or in light intensity
activity
Project BEAT collected an average of
16.7 hours per day of valid accelerometer
data. Children spent an average of
13.3 hours (or 79.6% of that period) sedentary (790 minutes for boys, 802 minutes for
girls; Table 3), a percentage nearly 20%
higher than that identified by Colley et al.4
using 2007 to 2009 CHMS data (62%).
Similar to the CHMS, time spent sedentary
did not differ by gender or weight classification. While the CHMS dataset did
demonstrate differences between genders
according to weight classification (with
normal weight boys significantly less
sedentary than normal weight girls,
p < .05), there was no such relationship
in Project BEAT. Project BEAT participants
spent another 2.9 hours of their day (17.4%
of wear time), on average, in light intensity
activity (versus 4 hours per Colley et al.4);
only in Project BEAT did gender differences
in the accumulation of light intensity
activity appear, with boys accumulating
an average of 20 minutes more light intensity activity per day than girls (p < .05,
Table 3). In both datasets, children classified as either overweight or obese accumulated a similar amount of light intensity
activity per day compared to normal weight
children.
Moderate-to-vigorous and vigorous activity
Boys achieved just over half the recommended levels of MVPA per day (35 minutes) while girls attained just 24 minutes
per day, findings lower than those
reported by Colley et al.4 based on the
CHMS (average of 61 and 47 minutes,
respectively), yet similar with respect to
gender differences. As observed in the
CHMS, overweight and obese boys in
Project BEAT accumulated less MVPA
(32 and 26 minutes per day, respectively)
compared with boys who were normal
weight (38 minutes). Unlike the CHMS,
this gradient was also observed in girls;
girls classified as being overweight or
obese accumulated 4 to 5 minutes less
MVPA per day compared with normal
weight girls (Table 3).
Project BEAT and CHMS data both
revealed that the vast majority of all
Vol 33, No 2, March 2013 – Chronic Diseases and Injuries in Canada
TABLE 3
Average daily minutes of activity (at various levels of intensity) of Project BEAT and CHMS
participants, by gender, age and BMI category
Intensity of activity, average minutes/day
Study, Sex, Age,
BMI category
Sedentary
Light
Moderate
Vigorous
Hard
MVPA
790
185a
27a
7a
1
35a
Normal weightb
786
185a
29a
8a
1
38a
Overweight
796
184
25c
6c
<1
32c
Obese
800
186
21c
4c
<1
26c
802
165
18
5
<1
24
799
165
19
1
25
Project BEAT
Boys
Age 10–12 years
BEAT children (27.1%) accumulated at
least 10 minutes of VPA on at least 3 days
of the week (35.1% of boys and 20.4%
of girls; p < .05). Nearly two-thirds of
children (64.7%) accumulated at least
5 minutes of VPA on at least 3 days of
the week (72.8% of boys and 57.9% of
girls; p < .05), findings that are proportionately higher compared to CHMS observations (Figure 1).
BMI category
Girls
Age 10–12 years
BMI category
Normal weightb
Overweight
808
Obese
163
830
5
c
16
174
c
4
c
<1
c
21c
c
20c
16
3
<1
67a
2
–
69a
a
2
–
59a
2
CHMS
Boys
Age 6–10 yearsb
Age 11–14 years
445
298
c
c
524
252
58
500a
262
64a
c
d
BMI category
Normal weightb
–
65a
c
Overweight
524
260
50
1
–
51c
Obese
536
248
43c
<1c
–
44c
56
2
–
58
Girls
Age 6–10 yearsb
Age 11–14 years
446
306
c
c
c
E
527
250
46
2
–
47c
524
249
46
2
–
48
d
BMI category
Normal weightb
E
Overweight
515
262
43
1
–
44
Obese
544
263
47
<3
–
48
Sources: Built Environment and Active Transport (BEAT) Project (2010–2011); 2007–2009 Canadian Health Measures Survey
(CHMS).4
Abbreviations: BEAT, Built Environment and Active Transport; BMI, body mass index; CHMS, Canadian Health Measures
Survey; MVPA, moderate-to-vigorous physical activity.
a
Significantly different from estimate for girls (p < .05).
b
Reference category; International Obesity Task Force classification.9
c
Significantly different from estimate for reference category (p < .05).
d
Includes additional age group (aged 15–19 years) sampled in CHMS. Remainder of table reflects results for those aged 6–10
years and 11–14 years, in light of Project BEAT’s sample demographics (age 10–12 years).
E
Use with caution.
MVPA is accumulated at moderate intensity (80% and 97%, respectively). Around
4.3% of children in Project BEAT accumulated at least 20 minutes of VPA at
least 3 days a week, a result quite similar
to CHMS findings (4%) (Figure 1).*
*
Project BEAT data showed a significantly
greater proportion of boys than girls
meeting this target (7.1% and 1.9%,
respectively; p < .05); gender comparisons were not made in the CHMS cohort.
A little more than a quarter of Project
While the vast majority of children in
both datasets did not meet the current
physical activity recommendations of at
least 60 minutes of MVPA at least 6 days a
week, the proportion achieving recommendations was lower in Project BEAT
(< 1%; 0.5% of boys, no girls) in
comparison to the CHMS (6.7% of children; 9.0% of boys, 4.1% of girls)
(Table 4). Like the CHMS, the difference
in the proportion of Project BEAT children
who met guidelines on at least 3 days a
week compared to at least 6 days a week
was much greater for boys than girls
(13.3% and 2.1% increase, respectively;
Figure 2).
In both datasets, considerably higher
percentages of children accumulated
30 minutes of MVPA per day; in Project
BEAT, 22.6% of boys and 5.4% of girls do
so at least 6 days a week (CHMS: 29.0%
and 21.3%, respectively; Table 4). Like
the CHMS (82.6%), the majority of boys
in Project BEAT (71.8%) accumulated
30 minutes of MVPA at least 3 days a
week; yet unlike the CHMS (72.6%), this
was not the case for girls (36.9%). In fact,
just over half of Project BEAT girls
(52.6%) only managed to accumulate
30 minutes of MVPA on 2 or more days
of the week.
Not a single child in Project BEAT (and
fewer than 2% in the CHMS) accumulated
at least 90 minutes of MVPA at least 6 days
of the week and only 2% met these criteria
on at least 2 days of the week (3.3% of
boys, 0.9% of girls; p < .05, Table 4). The
proportion of children attaining these
standards rose to 16.8% for at least 1
day of the week, with approximately 10%
more boys than girls doing so (22.3% and
12.3%, respectively; p < .05), an increase
The CHMS results in Figure 1 are based on children and youth aged 6–19 years, whereas Project BEAT results are based on children aged 10–12 years.
Vol 33, No 2, March 2013 – Chronic Diseases and Injuries in Canada
$
64
FIGURE 1
Percentage of Project BEAT participants (10–12 years) and CHMS participants (6–19 years)
with at least 5, 10 and 20 minutes of vigorous physical activity a day, by number of days
a week
88
75
65
56
49
42
37
37
24
20
9
Project BEAT
At least 5
At least 10
At least 20
CHMS
27
16
12
Project BEAT
CHMS
At least 2
At least 1
11
4
6
4
Project BEAT
CHMS
At least 3
Days per week
Sources: Built Environment and Active Transport (BEAT) Project (2010–2011); 2007–2009 Canadian Health Measures Survey
(CHMS).4
FIGURE 2
Percentage of Project BEAT participants (10–12 years) and CHMS participants (6–10 years
and 11–14 years) with at least 60 minutes of moderate-to-vigorous physical activity, by days
per week and by sex
Sample and age group
Project BEAT - Age 10 to 12 years
90 86
85
CHMS - Age 6 to 10 years
72b
63
49a
14a
Girls
At least 1
CHMS - Age 11 to 14 years
51
33b
22
Boys
51b
14E
2
0.5
Girls
Boys
7
b,E
0
Boys
At least 3
7
E
5
E
Girls
At least 6
Days per week
Sources: Built Environment and Active Transport (BEAT) Project (2010–2011); 2007–2009 Canadian Health Measures Survey
(CHMS).4
a
Significantly different from estimate for girls (p < .05), Project BEAT.
b
Significantly different from estimate for 6- to 10-year olds of same sex (p < .05), CHMS.
E
Use with caution.
Discussion
similar trends appeared) with some deviations probably due to differences in data
collection and reduction protocols and in
sample demographics.
To our knowledge, this is the first attempt
to compare accelerometer-measured physical activity data from a large sample with
results from a nationally representative
dataset (the CHMS, n = 1608).4 Overall,
findings were broadly consistent (i.e.
Strengths of this study include the large
sample size (856 children) and use of an
objective measure of physical activity to
examine multiple aspects of physical
activity behaviour. Our collection of
high-frequency physical activity data was
much lower than that reported in the
CHMS dataset (60%; Table 4).
$
65
particularly appropriate for quantifying
children’s activity behaviour.13 In addition, a relatively low number of participants were excluded due to invalid
accelerometer wear (less than 15%). The
biggest limitation of the study is the
contextual, sampling and methodological
differences between the two datasets,
which posed challenges in making direct
comparisons. For example, the narrow
age range of children sampled and the
investigation of Toronto neighbourhoods
in Project BEAT was quite different to the
national data collection strategy of the
CHMS. These issues limit the generalizability of findings to other age groups
and geographic locations. While both
studies present objectively measured
data, the accelerometer measurement and
data reduction protocols differed. The lack
of standardized physical activity measurement and data reduction protocols in the
field are a limitation to any study that
attempts to compare results to an independent dataset. Despite these differences,
overall trends were similar between the
two studies, which supports the notion of
very few children (< 10%) accumulating
enough daily activity for health benefits
and too many spending a significant
amount of their day sedentary.
With methodological differences between
Project BEAT and the CHMS acknowledged, the similar trends in findings are
sobering. The Canadian physical activity
guidelines for children and youth (which
are in line with the World Health
Organization Global Physical Activity
Recommendations15) encourage children
and youth to accumulate at least
60 minutes of MVPA every day.2 CHMS
data illustrate that only 7% achieve these
recommendations, while Project BEAT
data show that even less do so (< 1%).
In fact, not a single girl managed to
accumulate at least 60 minutes of MVPA
every day of the week, based on Project
BEAT data. Perhaps just as sobering is the
finding that only 13.2% of children in
Project BEAT managed to attain at least
30 minutes of MVPA on at least 6 days of
the week, lower than the CHMS results at
25.3%. BEAT and CHMS data both illustrate that children and youth spend the
majority of their day sedentary (anywhere
from 62% to 80%).
Vol 33, No 2, March 2013 – Chronic Diseases and Injuries in Canada
TABLE 4
Percentage of Project BEAT participants (10–12 years) and CHMS participants (6–19 years)
attaining selected physical activity criteria
Days active out of 7, %
Minutes of MVPA
0
§1
§2
§3
§4
§5
§6
Project BEAT
§ 30
Total
22.0
78.0
65.2
52.8
40.9
25.0
13.2
Boys
11.0*
89.0*
80.3*
71.8*
59.5*
39.2*
22.6*
Girls
31.1
68.9
52.6
36.9
25.3
13.1
5.4
Total
66.0
34.0
15.4
7.5
3.4
1.4
0.2
Boys
51.0*
49.0*
26.2*
13.8*
6.2*
2.8*
0.5
Girls
78.5
21.5
6.4
2.1
1.1
0.2
0.0
§ 60
§ 90
Total
83.2
16.8
2.0
0.4
0.1
0.0
0.0
Boys
77.7*
22.3*
3.3*
0.5
0.3
0.0
0.0
Girls
87.7
12.3
0.9
0.2
0.0
0.0
0.0
Total
5.1
94.9
87.6
77.7
64.5
47.1
25.3
Boys
3.3
96.7*
91.1*
82.6*
70.1*
52.6*
29.0*
Girls
6.9
93.1
83.9
72.6
58.4
41.2
21.3
CHMS
§ 30
§ 60
Total
20.2
79.8
61.3
44.4
29.3
16.6
6.7
Boys
14.8
85.2*
69.5*
52.9*
36.4*
21.5*
9.0*
Girls
26.1
73.9
52.6
35.4
21.7
11.3
4.1E
Total
40.9
59.8
35.1
20.1
10.7
5.0E
1.7E
Boys
33.7
66.3*
42.5*
26.0*
14.7*
7.1*E
2.5*E
§ 90
Girls
47.1
52.9
27.3
13.7
E
6.5
E
2.7
<2
Sources: Built Environment and Active Transport (BEAT) Project (2010–2011); 2007–2009 Canadian Health Measures Survey
(CHMS).4
Abbreviations: BEAT, Built Environment and Active Transport; CHMS, Canadian Health Measures Survey; MVPA, moderateto-vigorous physical activity.
*
Significantly different from estimate for girls (p < .05).
E
Use with caution.
Comparing CHMS and BEAT accelerometry
procedures
Proportions attaining physical activity
recommendations differed in both studies.
Three methodological differences highlight
the lack of standardization in accelerometrybased physical activity measurement protocols, which continues to make comparability
between studies difficult.
1. The accelerometer wear protocols differed
In Project BEAT, participants were asked
to wear their accelerometer while awake
and asleep to maximize compliance and
thus boost the probability of generating a
large sample of participants with valid
data for inclusion in data analyses. The
CHMS requested that participants wear
their accelerometer during waking hours
only. In Project BEAT, the decision was
made to exclude periods of 30 consecutive
minutes of zero counts (most of which
occurred during sleep time), whereas the
CHMS used a less conservative approach.
These decisions affect wear time and thus
explain the difference in average wear
times (Project BEAT: 16.7 hours; CHMS:
13.6 hours). These discrepancies also provide some rationale for differences seen in
Vol 33, No 2, March 2013 – Chronic Diseases and Injuries in Canada
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66
the proportion of the day spent sedentary
and in light intensity activity and MVPA
between the two datasets. For example,
Project BEAT data show that children
spend 79.6% of their day sedentary.
Another 17.4% is spent in light intensity
activity, with MVPA only contributing
to 3% of the daily profile. In the CHMS
dataset, children spent an average of 62%
of their waking hours sedentary, with
another 29.4% and 8.6% spent in light
intensity activity and MVPA, respectively.
2. The accelerometer devices and activity
intensity classification thresholds differed
Project BEAT used ActiGraph GT1M
accelerometers to monitor physical activity behaviour, while the CHMS used
Actical accelerometers. While the GT1M
model is one of the most validated and
widely used devices of their kind, a
possible limitation is that it measures
acceleration in the vertical plane only;
the Actical device is omni-directional,
allowing it to capture a wider range of
movement than a uni-axial device and
capture non-ambulatory activities. Despite
the theoretical advantage of the Actical
accelerometer, in reality both accelerometers provide similar information given
that the majority of movement is detected
in the vertical plane.16 Each accelerometer
model provides a unique dimensionless
activity count over a user-defined interval
(i.e. between 1 and 60 seconds). These
raw data are converted to useable information using calibration research that
generates model-specific activity intensity
thresholds. Consequently, time spent
sedentary and in light, moderate, vigorous
and hard intensity activity can be computed. The CHMS activity intensity
thresholds for the Actical were derived
from calibration work in children17,18
and adults,18 and the Project BEAT thresholds only from calibration trials with
children.14
Metabolic energy turnover (MET) values
are often used to express the intensity of
physical activity according to intensity
categories; a compendium of energy costs
for a variety of children’s activities is
available.19 In most studies like the CHMS,
moderate intensity is defined as 3 METs
or more. However, more recent evidence
suggests that a threshold of 4 METs or
more may be more appropriate for describing moderate or higher intensity activity in children20–23 and for determining
relationships between activity and health
outcomes.14 Indeed, the National Health
and Nutrition Examination Survey
(NHANES) in the U.S. uses a moderate
intensity threshold based on 4 METs
to classify MVPA in children24; in the
BEAT study, the threshold for moderate
intensity was also based on 4 METs. Our
use of a more stringent threshold to
classify MVPA (a decision made before
the release of the CHMS findings) likely
explains the lower levels of MVPA
observed (and fewer children meeting
guidelines) in Project BEAT data compared with CHMS data.
Reports in other countries, for example,
NHANES7 in the U.S. and the Avon
Longitudinal Study of Parents and
Children (ALSPAC)25 in England, support
these results. It is of particular interest to
compare Project BEAT data with the
ALSPAC data since both studies used the
same thresholds to classify moderate and
vigorous intensity activity: we see very
similar proportions of children achieving
the 60 minutes of MVPA per day guidelines (BEAT at < 1% and ALSPAC at
2.5%) and similar average levels of MVPA
(BEAT at 29 minutes per day and ALSPAC
at 20 minutes per day).
3. The user-specified data collection interval
differed
Project BEAT used a 5-second epoch to
capture the short and sporadic bursts of
activity that are typical in children,13
whereas the CHMS captured physical
activity data at 1-minute intervals. The
influence of epoch length on physical
activity data has been discussed at length:
shorter epochs capture more MVPA, and
longer epochs ‘‘dilute’’ the intensity of the
data26,27 and therefore affect the proportion of children attaining PA guidelines.28
Some have found significant epoch effects
for hard and very hard activity,26 and
others for all intensities.29 Using direct
observation, McClain at al.30 showed that
a 5-second epoch provided the least
discrepant estimates of MVPA in fifth
grade children compared with 10-, 15-,
20-, 30- and 60-second epochs. Indeed,
there is strong support for utilizing a
5-second epoch to truly capture children’s
spontaneous, discontinuous patterns of
activity.13,29,30
Project BEAT’s finding of a greater proportion of children accumulating at
least 5, 10 and 20 minutes of vigorous
intensity activity on one or more days
in comparison to the CHMS results
could be a reflection of utilizing a
shorter epoch to capture and express
accelerometer data. The discrepancies
were more apparent for lower levels of
VPA (at least 5 and 10 minutes); in fact,
when examining those accumulating at
least 20 minutes of VPA per day, the
proportions
were
nearly
identical
between datasets (around 4% for each).
The epoch effect may be diluted at the
upper extremes of daily VPA accumulation
and have a less significant impact on
levels of MVPA than accelerometer intensity thresholds, given levels were somewhat lower in Project BEAT compared
with the CHMS dataset.
terms of facilities and resources, supports
the notion that physical inactivity is
most likely an ongoing problem across
Canada.
Acknowledgements
This research was funded by the Built
Environment, Obesity and Health Strategic
Initiative of the Heart and Stroke
Foundation and the Canadian Institutes
of Health Research (CIHR).
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Katzmarkyk PT, Ardern CI. Physical activity levels of Canadian children and youth:
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Clarke J, Tremblay MS. Physical activity of
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Tremblay MS, Shields M, Laviolette M,
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Troiano RP, Berrigan D, Dodd K, Masse LC,
Tilert T, McDowell M. Physical activity in the
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Conclusion
Using data from Project BEAT, this
study demonstrates that the low levels
of physical activity and high levels of
sedentary behaviour amongst Canadian
youth, as reported in the CHMS, do occur
in an independent sample of Canadian
youth. Accelerometry data in both datasets show that the majority of children
and youth do not meet current physical
activity recommendations and spend a
significant proportion of their day sedentary. These similarities have been established despite contextual, sampling and
methodological differences between the
two datasets, limitations that have been
noted and discussed, and also presented
as three methodological considerations in
analyzing accelerometry data. That both
datasets reveal similar trends in physical
activity and inactivity behaviour among
Canadian children and youth is encouraging for purposes of validation, yet disheartening given the ramifications of
such inactivity on health. The consistency
of data from the CHMS and that on a
sample of children from the Greater
Toronto Area, where conditions might be
most conducive for physical activity in
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8.
Veugelers PJ, Fitzgerald AL. Prevalence of
and risk factors for childhood overweight
and obesity. CMAJ. 2005;173:607–13.
9.
Cole TJ, Bellizzi MC, Flegal KM, Dietz WH.
Establishing a standard definition for child
overweight and obesity worldwide: international survey. BMJ. 2000;320:1240.
10. De Vries SI, Van Hirtum HW, Bakker I,
Hopman-Rock M, Hirasing RA, Van
Mechelen W. Validity and reproducibility
of motion sensors in youth: a systematic
update. Med Sci Sports Exerc. 2009;41:
818–27.
11. Chen KY, Bassett DR, Jr. The technology of
accelerometry-based activity monitors: current and future. Med Sci Sports Exerc.
2005;37:S490–500.
12. Welk GJ. Principles of design and analyses
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13. Stone MR, Rowlands AV, Middlebrooke
AR, Jawis MN, Eston RG. The pattern of
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4:306–15.
14. Stone MR, Rowlands AV, Eston RG.
Relationships between accelerometerassessed physical activity and health in
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15. World Health Organization. Global recommendations on physical activity for health.
Geneva (CH): World Health Organization;
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16. Corder K, Brage S, Ekelund U.
Accelerometers and pedometers: methodology and clinical application. Curr Opin Clin
Nutr Metab Care. 2007;10:597–603.
17. Puyau MR, Adolph AL, Vohra FA, Zakeri I,
Butte NF. Prediction of activity energy
expenditure using accelerometers in
children. Med Sci Sports Exerc. 2004;36:
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Tremblay M. Actical accelerometer sedentary activity thresholds for adults. J Phys
Act Health. 2011;8:587–91.
19. Ridley K, Olds TS. Assigning energy costs to
activities in children: a review and synthesis. Med Sci Sports Exerc. 2008;40:
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Pennell ML, Pearce PF, Bangdiwala SI.
Energy costs of physical activities in children and adolescents. Med Sci Sports Exerc.
2005;37:329–36.
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Saunders J, Tilling K, et al. Calibration of
an accelerometer during free-living activities in children. Int J Pediatr Obes.
2007;2:218–26.
22. Reilly JJ, Penpraze V, Hislop J, Davies G,
Grant S, Paton JY. Objective measurement
of physical activity and sedentary behaviour: review with new data. Arch Dis
Child. 2008;93:614–9.
23. Treuth MS, Schmitz K, Catellier DJ,
McMurray RG, Murray DM, Almeida MJ,
et al. Defining accelerometer thresholds for
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Taylor WC, Dowda M, et al. Age and
gender differences in objectively measured
physical activity in youth. Med Sci Sports
Exerc. 2002;34:350–5.
25. Riddoch CJ, Mattocks C, Deere K, Saunders
J, Kirkby J, Tilling K, et al. Objective
measurement of levels and patterns of
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26. Nilsson A, Ekelund U, Yngve A, Sjoestroem
M. Assessing physical activity among children with accelerometers using different
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Pediatr Exerc Sci. 2002;14:87–96.
27. Trost SG, McIver KL, Pate RR. Conducting
accelerometer-based assessments in fieldbased research. Med Sci Sports Exerc.
2005;37:S531–43.
28. Ojiambo R, Cuthill R, Budd H, Konstabel K,
Casajus JA, Gonzalez-Aguero A, et al.
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29. Edwardson CL, Gorely T. Epoch length and
its effect on physical activity intensity. Med
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Cancer incidence, mortality and survival trends in Canada,
1970–2007
L. Kachuri, MPH (1); P. De, PhD (1, 2); L. F. Ellison, MSc (3); R. Semenciw, MSc (4); The Advisory Committee on
Canadian Cancer Statistics
This article has been peer reviewed.
Abstract
Introduction: Monitoring cancer trends can help evaluate progress in cancer control
while reinforcing prevention activities. This analysis examines long-term trends for
selected cancers in Canada using data from national databases.
Methods: Annual changes in trends for age-standardized incidence and mortality rates
between 1970 and 2007 were examined by sex for 1) all cancers combined, 2) the four
most common cancers (prostate, breast, lung, colorectal) and 3) cancers that
demonstrate the most recent notable changes in trend. Five-year relative survival for
1992–2007 was also calculated.
comprehensive examination of long-term
Canadian cancer trends. As such, it can be
used to compare with reported trends in
other countries. More importantly, trends
are discussed in the context of major
cancer risk factors and associated health
behaviours to provide perspective on the
possible determinants of disease.
Methods
Data sources
Results: Incidence rates for all primary cancer cases combined increased 0.9% per year
in males and 0.8% per year in females over the study period, with varying degrees of
increase for melanoma, thyroid, liver, prostate, kidney, colorectal, lung, breast, and
bladder cancers and decrease for larynx, oral, stomach and cervical cancers. Mortality
rates were characterized by significant declines for all cancers combined and for most
cancers examined except for melanoma and female lung cancer. The largest
improvements in cancer survival were for prostate, liver, colorectal and kidney
cancers. While the overall trends in mortality rates and survival point to notable
successes in cancer control, the increasing trend in incidence rates for some cancers
emphasize the need for continued efforts in prevention.
Keywords: cancer surveillance, incidence, mortality, survival, risk factors
Introduction
At the beginning of 2007, nearly 750 000
Canadians had a diagnosis of cancer in the
previous 10 years.1 Cancer is the leading
cause of death in Canada,2 with 82% of all
cancer deaths occurring in those aged 60
years and over.1 By 2036, about 10.9
million Canadians will be aged 65 years
or older,3 which will lead to more new
cancer cases and create significant
demands for cancer care.
An examination of historical cancer trends
can help us predict future patterns of this
disease and evaluate progress in cancer
control, thus allowing public health professionals to reinforce existing cancer
prevention and control activities.
This analysis examines long-term trends
for (1) all cancers combined, (2) the four
most common cancers in Canada (prostate, female breast, lung, colorectal), and
(3) those cancers shown to have the most
notable changes in their incidence or
mortality trends in the past decade (stomach, liver, thyroid, larynx, melanoma,
bladder, kidney, cervix). To our knowledge, this is the most up-to-date and
We took cancer incidence data from 1992
to 2007 from the July 2010 version of
the Canadian Cancer Registry, a personoriented, population-based database.4
Data for the earlier period, from 1970
to 1991, are from the National Cancer
Incidence and Reporting System, a
tumour-oriented database established
in 1969.5 Mortality data were from
the Canadian Vital Statistics Death
Database. Population estimates were
from Statistics Canada’s Demographic
Estimates Compendium 2010.6
We created a file containing records of
invasive cancer cases for all ages and in
situ bladder cancer cases (except from
the province of Ontario) using the
International Agency for Research on
Cancer multiple primary coding rules.7
Cancer cases were classified based on the
International Classification of Diseases
for Oncology, 3rd Edition.8 Cancer group
definitions are provided elsewhere.1 For
cancer deaths, the underlying causes
of death were selected according to the
International Classification of Diseases
and classified to version 10 (ICD-10).9
Author references:
1.
2.
3.
4.
Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
Cancer Control Policy, Canadian Cancer Society, Toronto, Ontario, Canada
Health Statistics Division, Statistics Canada, Ottawa, Ontario, Canada
Chronic Diseases Prevention and Control, Public Health Agency of Canada, Ottawa, Ontario, Canada
Correspondence: Prithwish De, Canadian Cancer Society, 55 St Clair Ave West, Suite 300, Toronto, ON M4V 2Y7; Tel.: 416-934-5335; Fax: 416-961-4189; Email: prithwish.de@cancer.ca
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Vol 33, No 2, March 2013 – Chronic Diseases and Injuries in Canada
Statistical analysis
Results
We calculated age-specific rates for each
year and then standardized them to the
1991 Canadian population to obtain the
age-standardized incidence rates (ASIR)
and mortality rates (ASMR). Trends over
the short and long terms were analyzed
by calculating the annual percent change
(APC) and average annual percent
change (AAPC) in rates, respectively,
using Joinpoint version 3.5.1 software.10
Joinpoint uses piecewise regression to
model the change in ASIR and ASMR on
the log scale. While other approaches,
such as a polynomial fit to the data, could
be used, Joinpoint characterizes trends
more succinctly by transforming the slope
of each segment into an average percent
change.11 A minimum of 5 years of data
before and after a point of change was
required to identify a new trend. Models
were tested using the Monte Carlo permutation method (p = .05 level of significance).
Any statistically significant changes in
trend are described here as ‘‘decreasing’’
or ‘‘declining’’ or, conversely, ‘‘increasing.’’
In 2007, 85 430 new cancer cases and
36 569 cancer deaths were reported in
males, and 78 099 new cases and 33 026
deaths occurred in females. Together, the
most frequently diagnosed cancers (prostate, female breast, colorectal and lung)
accounted for 55% and 52% of all new
cancer diagnoses in males and females,
respectively, as well as 50% and 51% of
cancer deaths in each sex.
Relative survival analyses were based on a
publicly available algorithm12 which we
adapted slightly. The focus of this analysis
was on all primary cancer cases aged 15 to
99 years at diagnosis. Mortality follow-up
through December 31, 2007, was determined by record linkage of the Canadian
Cancer Registry to the Canadian Vital
Statistics Death Database and from information reported by provincial/territorial
cancer registries. Data from Quebec were
excluded because the method of ascertaining the date of diagnosis of cancer cases in
this province differed from that of the
other provinces13,14 and because of issues
in correctly ascertaining the vital status of
cases diagnosed in Quebec within the
Canadian Cancer Registry. We derived
5-year relative survival ratio (RSR) estimates using the cohort method for 1992 to
1994, 1996 to 1998, and 2000 to 2002 and
the period method for 2005 to 2007.
Because more recent data were unavailable, expected survival data for 2005 to
2007 (used in the derivation of relative
survival) were assumed to be the same as
in 2000 to 2002. Further information on
the survival methodology used is provided
elsewhere.15
Trends in incidence and mortality
All cancers combined
Table 1 shows the APCs and AAPCs for
cancer incidence. The ASIRs for all cancers combined for 1970 and 2007 were
higher in males (1970: 330.4 per 100 000;
2007: 463.2 per 100 000) than in females
(1970: 272.0 per 100 000; 2007: 362.3 per
100 000). The rate increased at an average
of 0.9% per year in males and 0.8% per
year in females over the study period.
The APCs and AAPCs for cancer mortality
are shown in Table 2. As for incidence,
the ASMR for all cancers combined was
higher in males (1970: 228.4 per 100 000;
2007: 200.1 per 100 000) than in females
(1970: 152.1 per 100 000; 2007: 141.2 per
100 000) but decreased at a rate of 0.3%
per year in males and 0.2% per year in
females over the study period.
Selected cancers
Between 1970 and 2007, there was an
overall upward trend in male incidence
rates (Figure 1) for melanoma (AAPC:
3.7%) and for thyroid (3.6%), liver
(3.5%), prostate (2.2%), kidney (1.8%),
colorectal (0.6%) and bladder cancers
(0.4%) but a declining trend for larynx
(0.8%), oral (1.4%) and stomach (2.1%)
cancers. Incidence rates increased in
females for thyroid (AAPC: 4.4%), lung
(4.4%), melanoma (2.9%), kidney
(2.1%), liver (1.9%), breast (0.5%) and
bladder cancers (0.5%) while decreasing
AAPCs were observed for cervix (2.5%)
and stomach cancers (2.3%).
For most cancers, mortality rates between
1970 and 2007 were characterized by
statistically significant decreases (Figure 2)
with the exception of female lung cancer
Vol 33, No 2, March 2013 – Chronic Diseases and Injuries in Canada
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70
(AAPC: 4.0%) and melanoma (AAPC: 2.3%
for males, 0.8% for females), for which
increases were observed.
The trends for certain cancers are worth
highlighting. For example, the prostate
cancer incidence rate peaked twice, in
1993 and 2001 (Table 1 and Figure 1).
Following the first peak, the incidence rate
decreased (APC: 5.2%) until 1997, after
which the rate climbed at 3.9% per year
to a second peak in 2001, followed by
a period of non-significant decline. We
observed only one period of increase in
the mortality rate for this cancer, between
1977 and 1993, which preceded a continuous decline that has further accelerated since 2001 (Table 2).
The incidence rate of lung cancer
increased by 3.7% per year in males
between 1970 and 1983. This was followed by a period of non-significant
change until 1990 when the incidence rate
started declining (Table 1). In females, the
incidence rate has been increasing since
1970 but has slowed from 8.4% per year
(1970–1983) to 3.8% per year (1983–
1992) and finally to 1.4% per year
(1992–2007). Lung cancer mortality in
males followed a trajectory similar to
incidence: the rate increased (2.7% per
year) until 1983, remained stable (0.0%
per year) from 1983 to 1992, and then
began declining at an annual rate of 2.2%
(Table 2). In contrast, the lung cancer
mortality rate in females has continued to
increase since 1970, from 6.9% per year
(1970–1985) to 3.6% per year (1985–1994)
and finally 1.0% per year (1994–2007).
Larynx cancer incidence rates increased
from 1970 until 1980 in males (APC:
3.6%) and until 1989 in females (3.2%
per year). Male incidence rates declined
at 1.0% per year from 1980 to 1992, after
which the decrease accelerated to 3.4%
per year. Female incidence rate declined at
an annual rate of 3.1% since 1989. The
mortality rate increased from 1970 until
1988 for males (0.8% per year) and until
1991 for females (1.9% per year), followed
by significant declines in both sexes.
Bladder cancer incidence rates increased
from 1970 to 1981 (males: 3.3% per year;
females: 3.5% per year), but the trend
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Vol 33, No 2, March 2013 – Chronic Diseases and Injuries in Canada
24.5
1.5
6.9
2.0
3.4
20.6
Bladder
Thyroid
Larynx
Liver
Melanoma
Oral
98.4
3.7
Kidney
9.0
4.8
7.8
1.7
1.0
18.0
1970–1980
1970–1986
1970–1988
1970–1979
1970–1980
1970–2007
1970–1989
1970–1989
1970–1981
1970–1983
1970–1983
1970–1998
1970–1981
1970–1977
1970–1983
1970–1978
1970–1986
1970–2007
1970–1980
1970–1997
1970–1981
1970–1983
1970–1984
1970–1989
1970–1983
Year
1.4* (0.1, 2.7)
21.9* (22.3, 21.5)
23.3* (23.6, 23.0)
1.4 (0.0, 2.9)
7.4* (5.8, 9.1)
1.9* (1.6, 2.2)
3.2* (2.3, 4.1)
1.8* (1.4, 2.2)
3.5* (1.9, 5.1)
8.4* (7.9, 8.9)
1.0* (0.6, 1.4)
0.9* (0.8, 1.1)
1.6* (1.2, 1.9)
1.2 (20.3, 2.6)
21.3* (21.7, 20.9)
0.2 (20.8, 1.1)
6.2* (5.4, 7.1)
3.5* (3.3, 3.7)
3.6* (2.5, 4.6)
2.4* (1.9, 2.8)
3.3* (2.5, 4.0)
3.7* (3.4, 4.0)
2.2* (1.9, 2.5)
2.8* (2.6, 3.1)
2.6* (2.3, 2.9)
APC (95% CI)
Trend 1
1980–1987
1986–1991
1988–2007
1979–2007
1980–2007
1989–2007
1989–1994
1981–2007
1983–1992
1983–1996
1998–2007
1981–2007
1977–1989
1983–2007
1978–1992
1986–2007
1980–1992
1997–2007
1981–2007
1983–1990
1984–1996
1989–1993
1983–1989
Year
6.7* (4.4, 8.9)
24.2* (27.2, 21.1)
21.8* (22.1, 21.5)
20.4* (20.6, 20.2)
1.3* (1.0, 1.5)
23.1* (23.8, 22.3)
6.9* (3.5, 10.4)
20.4* (20.6, 20.2)
3.8* (3.2, 4.4)
21.5* (21.8, 21.1)
20.7* (21.2, 20.2)
0.4* (0.4, 0.5)
4.0* (3.4, 4.6)
22.6* (22.7, 22.4)
21.7* (22.1, 21.3)
1.9* (1.6, 2.2)
21.0* (21.8, 20.3)
6.9* (5.7, 8.1)
20.7* (20.9, 20.6)
20.4 (21.2, 0.4)
20.6* (21.0, 20.3)
9.7* (6.4,13.1)
0.0 (21.0,1.0)
APC (95% CI)
Trend 2
1987–1997
1991–2007
1994–1998
1992–2007
1996–2000
1989–1998
1992–1998
1992–2007
1990–2007
1996–2000
1993–1997
1989–1993
Year
20.1 (21.0, 0.8)
22.0* (22.4, 21.7)
1.9 (22.7, 6.7)
1.4* (1.2, 1.5)
1.3 (21.8, 4.4)
20.3 (21.0, 0.4)
23.5* (25.2, 21.8)
23.4* (23.9, 23.0)
21.9* (22.0, 21.7)
1.4 (20.9, 3.7)
25.2* (27.8, 22.6)
2.3* (0.3, 4.4)
APC (95% CI)
Trend 3
*
a
Two-sided p < .05.
Excluding Quebec.
Abbreviations: AAPC, average annual percent change; APC, annual percent change; ASIR, age-standardized incidence rates; CI, confidence interval.
11.2
Stomach
5.4
5.1
4.1
Melanoma
19.4
0.9
Liver
Oral
0.7
Larynx
Cervix
11.3
3.9
7.9
6.7
Thyroid
47.2
40.6
Bladder
Colorectal
9.3
77.1
44.5
Breast
362.3
15.1
10.4
12.9
13.7
6.2
4.8
5.2
26.9
67.8
60.4
124.7
463.2
2007
Lung
272.0
All cancers
Females
7.8
59.3
Lung
Kidney
47.8
Colorectal
23.4
53.8
Prostate
Stomach
330.4
1970
ASIR
All cancers
Males
Cancer
type
1997–2007
1998–2002
2000–2007
1998–2007
1998–2007
2000–2007
1997–2001
1993–1997
Year
1.8* (1.2, 2.5)
12.5* (8.2,17.0)
20.8* (21.6, 20.1)
1.4* (0.9, 2.0)
21.0* (21.7, 20.3)
20.7* (21.3, 20.2)
3.9* (1.2, 6.7)
22.2* (24.0, 20.3)
APC (95% CI)
Trend 4
2002–2007
Year
APC
(95% CI)
Trend 6
1.1 (20.7, 3.0) 2001–2007 20.6* (21.2, 0.0)
APC (95% CI)
6.9* (5.4, 8.3)
2001–2007 20.7 (21.5, 0.1)
1997–2001
Year
Trend 5
TABLE 1
Annual percent change and average annual percent change in age-standardized incidence rates per 100 000 for selected cancers, Canadaa, 1970–2007
2.1* (1.5, 2.7)
22.3* (22.7, 21.8)
22.5* (22.7, 22.3)
0.0 (20.3, 0.4)
2.9* (2.4, 3.3)
1.9* (1.6, 2.2)
0.1 (20.5, 0.6)
4.3* (3.5, 5.1)
0.5* (0.1, 0.9)
4.4* (4.2, 4.6)
20.2 (20.6, 0.2)
0.5* (0.4, 0.7)
0.8* (0.7, 0.9)
1.8* (1.4, 2.2)
22.1* (22.3, 22.0)
21.4* (21.8, 21.0)
3.7* (3.3, 4.1)
3.5* (3.3, 3.7)
20.8* (21.2, 20.4)
3.6* (3.1, 4.0)
0.4* (0.2, 0.7)
0.3* (0.1, 0.5)
0.6* (0.3, 0.9)
2.2* (1.6, 2.7)
0.9* (0.5, 1.3)
(1970–2007)
AAPC (95% CI)
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72
33.9
55.0
9.0
0.6
3.1
1.8
1.3
6.3
23.3
Colorectal
Lung
Bladder
Thyroid
Larynx
Liver
Melanoma
Oral
Stomach
0.4
0.7
1.1
1.9
Larynx
Liver
Melanoma
Oral
2.3
2.9
1.9
1.5
1.6
0.8
0.4
0.4
2.1
36.1
16.3
21.8
141.2
5.0
6.5
4.1
2.8
3.1
1.8
0.4
6.9
57.0
24.4
20.4
200.1
2007
–0.7* (–0.8, –0.6)
2.7* (2.4, 3.0)
0.0 (–0.2, 0.2)
–0.2 (–1.3, 0.8)
0.7* (0.6, 0.7)
APC (95% CI)
–1.2* (–1.5, –0.8)
6.9* (6.5, 7.4)
–1.2* (–1.5, –1.0)
–0.4* (–0.7, –0.1)
–0.6* (–1.1, –0.1)
0.8* (0.5, 1.1)
–3.3* (–3.4, –3.3)
–0.5* (–0.8, –0.1)
4.2* (3.0, 5.3)
0.1 (–1.7, 1.8)
0.8* (0.4, 1.3)
1970–1978
1970–1977
1970–1976
1970–2007
1970–1983
1970–1989
1970–1991
–1.1 (–2.8, 0.8)
–5.3* (–6.7, –3.9)
–7.7* (–9.8, –5.6)
–0.6* (–0.8, –0.3)
2.0* (0.7, 3.3)
1.2* (0.3, 2.0)
1.9* (0.8, 3.0)
Not applicable: small number of deaths
1970–1996
1970–1985
1970–1986
1970–1982
1970–1977
1970–1992
1970–2007
1970–1991
1970–1985
1970–1982
1970–1988
Not applicable: small number of deaths
1970–2007
1970–1983
1970–1988
1970–1977
1970–1988
Year
Trend 1
1978–1988
1977–2007
1976–2007
1983–2007
1989–1994
1991–2007
1996–2007
1985–1994
1986–2007
1982–1986
1977–1988
1992–2007
1991–2007
1985–2007
1982–1987
1988–2001
1983–1992
1988–2003
1977–1993
1988–2001
Year
2.1* (0.8, 3.4)
–3.1* (–3.3, –2.9)
–3.1* (–3.3, –2.8)
0.2 (–0.2, 0.6)
–6.3 (–13.2, 1.1)
–2.7* (–4.0, –1.4)
0.3 (–0.7, 1.3)
3.6* (2.9, 4.2)
–1.7* (–1.8, –1.5)
2.0 (–0.4, 4.4)
0.5* (0.2, 0.8)
–0.7* (–1.1, –0.2)
–2.5* (–3.0, –2.0)
1.1* (0.6, 1.5)
8.6* (0.3, 17.6)
–2.3* (–2.9, –1.7)
0.0 (–0.5, 0.5)
–1.1* (–1.4, –0.8)
1.4* (1.1, 1.7)
20.9* (–1.0, –0.8)
APC (95% CI)
Trend 2
1988–2007
1994–2007
1994–2007
1986–1994
1988–2002
1987–1991
2001–2007
1992–2007
2003–2007
1993–2001
2001–2007
Year
*
a
Two-sided p < .05.
Excluding Quebec.
Abbreviations: AAPC, average annual percent change; APC, annual percent change; ASMR, age-standardized mortality rates; CI, confidence interval.
2.2
1.0
Thyroid
Kidney
2.8
Bladder
7.3
8.3
Lung
11.3
28.6
Colorectal
Stomach
30.7
Breast
Cervix
152.1
All cancers
Females
4.7
25.4
Kidney
228.4
All cancers
1970
ASMR
Prostate
Males
Cancer type
–0.8* (–1.2, –0.5)
1.9* (0.7, 3.1)
1.0* (0.8, 1.3)
–1.0* (–1.6, –0.4)
–0.3* (–0.4, –0.1)
–5.2 (–15.0, 5.7)
–6.0* (–7.8, –4.2)
–2.2* (–2.3, –2.0)
–2.5* (–4.1, –0.9)
–2.3* (–3.0, –1.6)
–2.0* (–2.3, –1.7)
APC (95% CI)
Trend 3
1994–2007
2002–2007
1991–2007
2001–2007
Year
–2.4* (–2.7, –2.2)
–1.2* (–1.8, –0.6)
2.4* (1.7, 3.2)
–4.2* (–5.1, –3.4)
APC (95% CI)
Trend 4
–0.1 (–0.6, 0.4)
–3.5* (–3.8, –3.2)
–3.8* (–4.2, –3.5)
–0.6* (–0.8, –0.3)
0.8* (0.3, 1.3)
0.4 (–0.8, 1.5)
–0.1 (–0.9, –0.7)
–0.7* (–1.1, –0.4)
4.0* (3.8, 4.3)
–1.5* (–1.6, –1.3)
–1.0* (–1.3, –0.7)
–0.2* (–0.4, –0.1)
0.2 (–0.1, 0.4)
–3.3* (–3.4, –3.3)
–1.3* (–1.6, –1.0)
2.3* (1.8, 2.8)
1.6 (0.0, 3.3)
–1.4* (–1.4, –1.0)
–0.7* (–0.8, -0.6)
0.0 (–0.1, 0.2)
–0.7* (–0.9, –0.5)
–0.6* (–0.9, –0.3)
–0.3* (–0.4, –0.3)
(1970–2007)
AAPC (95% CI)
TABLE 2
Annual percent change and average annual percent change in age-standardized mortality rates per 100 000 for selected cancers in Canadaa, 1970–2007
FIGURE 1
Average annual percent change in age-standardized incidence rates for selected cancers in males and females, Canada, 1970–2007
Males
Females
160
120
2.2*%/yr
140
0.5*%/yr
100
Prostate
Lung
Colorectal
Bladder
Stomach
Larynx
100
0.3%/yr
80
Age-standardized incidence rate (per 100 000)
Age-standardized incidence rate (per 100 000)
120
0.6*%/yr
60
40
0.4*%/yr
Breast
Colorectal
Cervix
Stomach
Lung
Thyroid
80
60
_0.2%/yr
40
4.4*%/yr
20
20
0
0
1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006
25
4.4*%/yr
_2.3*%/yr
1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006
12
Liver
Thyroid
Kidney
Melanoma
Oral
_1.4*%/yr
0.5*%/yr
15
1.8*%/yr
10
2.9*%/yr
10
Age-standardized incidence rate (per 100 000)
20
Age-standardized incidence rate (per 100 000)
_2.5*%/yr
_2.1*%/yr
_0.8*%/yr
3.7*%/yr
5
3.5*%/yr
8
2.1*%/yr
6
_0.1%/yr
Bladder
Oral
Melanoma
Kidney
Liver
Larynx
4
2
0.1%/yr
1.9*%/yr
3.6*%/yr
0
0
1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006
1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006
Note: Joinpoint analyses with up to 5 joinpoints were based on age-adjusted rates (per 100 000 persons).
a
Excluding Quebec.
* Two-sided p < .05.
reversed in 1981 when incidence rates
began decreasing (males: 0.7% per year;
females: 0.4% per year). Mortality rates,
on the other hand, have decreased over
the entire study period for males (0.7%
per year) and from 1970 to 1996 for
females (1.2% per year).
The overall incidence rate of kidney
cancer in males increased over two
periods, 1977 to 1989 and 1998 to 2007.
We observed two similar periods of
increase in females, from 1980 to 1987
and from 1997 to 2007. In contrast, the
male mortality rate increased from 1970 to
1992 but has been decreasing since then,
while the female mortality rate increased
from 1978 to 1988 and has since declined.
The incidence rate of thyroid cancer has
been steadily increasing since 1970 in
both sexes. In males, the rate increased
at 2.4% per year between 1970 and 1997
and then accelerated to 6.9% per year
until 2007. More notably, in females
the incidence rate has varied from 1.8%
per year between 1970 and 1989, 6.9% per
year between 1989 and 1994, 12.5% per
year between 1998 and 2002, and more
recently (2002–2007), 6.9% per year.
Thyroid cancer mortality rates were too
low to permit a Joinpoint analysis.
$
73
Trends in survival
Between 1992 to 1994 and 2005 to 2007,
the 5-year age-standardized RSR for all
cancers combined rose by 6.8 percentage
points to 62% (Table 3). Larger gains in
survival were seen for males than females
(8.5 vs. 5.0 percentage points) over this
period, resulting in considerable narrowing in the previous gap.
The degree of improvement in the 5-year
RSR varied considerably for individual
cancers. The largest improvements of
approximately 8 to 10 percentage points
were for prostate, liver, colorectal and
kidney cancers. Small improvements of 2
Vol 33, No 2, March 2013 – Chronic Diseases and Injuries in Canada
FIGURE 2
Average annual percent change in age-standardized mortality rates for selected cancers in males and females, Canadaa, 1970–2007
Males
Females
90
Lung
Colorectal
Prostate
Stomach
Bladder
Kidney
80
70
35
60
50
40
_0.7*%/yr
30
_0.6*%/yr
20
10
0
_0.7*%/yr
25
_1.5*%/yr
20
15
10
_3.8*%/yr
_3.5*%/yr
5
0.2*%/yr
0
1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006
_0.7*%/yr
1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006
4.0
Oral
Larynx
Liver
Melanoma
Thyroid
_1.3*%/yr
6
5
4
_1.4*%/yr
3
2.3*%/yr
2
1.6*%/yr
1
Kidney
Oral
Melanoma
Thyroid
Liver
Larynx
3.5
Age-standardized mortality rate (per 100 000)
7
3.0
_0.1*%/yr
2.5
_0.6*%/yr
2.0
1.5
0.8*%/yr
1.0
0.4*%/yr
_0.1*%/yr
0.5
N/A
N/A
0
Breast
Colorectal
Stomach
Lung
Cervix
Bladder
30
_3.3*%/yr
8
Age-standardized mortality rate (per 100 000)
4.0*%/yr
_1.0*%/yr
Age-standardized mortality rate (per 100 000)
0.0*%/yr
Age-standardized mortality rate (per 100 000)
40
0.0
1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006
1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006
Abbreviation: N/A, not applicable.
Note: Joinpoint analyses with up to 5 joinpoints were based on age-adjusted rates (per 100 000 persons).
a
Excluding Quebec.
* Two-sided p < .05.
to 3 percentage points were observed for
lung, larynx, cervical and oral cancers.
There was no apparent improvement for
bladder cancer over the study period.
Disparities between the sexes in survival
gains favoured females (data not shown)
and included oral (3.7% females vs. 1.1%
males), larynx (4.1% vs. 1.5%), lung
(3.5% vs. 1.3%) and stomach cancers
(6.3% vs. 4.5%).
Discussion
Over the nearly 40-year period between
1970 and 2007, incidence rates for all
cancers combined increased significantly
in both Canadian males and females.
While rates have stabilized in males since
1993, in females the overall incidence
rate appears to have started plateauing
only recently. These overall trends were
driven largely by the three most common
cancers in males (i.e. lung, prostate and
colorectal) and in females (i.e. breast, lung
and colorectal).
Cancer mortality rates in both sexes
peaked in 1988 and have since declined
largely due to reductions in mortality rates
in the four leading causes of cancer death
(i.e. lung, colorectal, prostate and breast
cancers). The gains in 5-year RSR since the
Vol 33, No 2, March 2013 – Chronic Diseases and Injuries in Canada
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74
period 1992 to 1994 for all cancers
combined and for selected cancers
suggest improvements in treatment and
early detection of certain cancers as well
as advances in supportive and general
medical care.
Trends in leading cancers
Prostate cancer
Little is known about the risk factors for
prostate cancer aside from age. Although
androgens are critical for prostate cancer
growth, it is unclear whether high androgen levels can promote cancer initiation.16
A link with physical activity has been
TABLE 3
Five-year age-standardized relative survival ratios for selected cancersa by time period,
Canadab, 1992–2007
RSRc, % (95% CI)
Cancer type
Changed
1992–1994
1996–1998
2000–2002
2005–2007
1992–1994
to 2005–2007
All cancers
56 (55–56)
57 (57–57)
60 (60–61)
62 (62–63)
6.8
Male
54 (54–54)
55 (55–56)
60 (60–60)
62 (62–63)
8.5
Female
57 (56–57)
58 (58–59)
60 (60–60)
62 (62–63)
5.0
Prostate
87 (86–87)
90 (89–90)
94 (94–95)
96 (96–97)
9.8
Female breast
82 (82–83)
85 (85–86)
87 (86–87)
88 (87–88)
5.6
Colorectal
56 (55–56)
58 (57–59)
61 (60–61)
64 (64–65)
8.6
Lung
14 (13–14)
15 (14–15)
15 (15–15)
16 (16–17)
2.6
Bladder
73 (72–74)
71 (70–72)
71 (70–72)
72 (71–73)
20.3
Thyroid
93 (92–94)
94 (93–95)
96 (96–97)
98 (97–98)
4.9
Larynx
62 (60–64)
63 (61–65)
62 (59–64)
64 (61–66)
1.9
Liver
10 (8–11)
12 (11–14)
17 (15–18)
18 (17–20)
8.7
Melanoma
84 (83–86)
87 (86–87)
89 (88–90)
89 (89–90)
4.9
Oral
60 (59–61)
59 (58–61)
61 (59–62)
62 (61–64)
2.3
Cervix
70 (68–71)
70 (69–72)
73 (71–75)
72 (70–73)
2.2
Stomach
19 (18–21)
22 (20–23)
22 (21–23)
25 (23–26)
5.1
Kidney
60 (58–61)
62 (60–63)
64 (63–65)
67 (66–69)
7.7
Abbreviations: CI, confidence interval; RSR, relative survival ratio.
a
For persons aged 15 to 99 years at diagnosis.
b
Excluding Quebec.
c
Results derived using both the cohort (1992–1994, 1996–1998 and 2000–2002) and period (2005–2007) methods.
d
Absolute difference in percentage points.
suggested17 but the evidence remains
inconclusive.18,19 Obesity is only weakly
associated with the development of prostate cancer, but there is some suggestion
that it could increase the risk of death and
metastasis.20–22
Despite uncertainty about the benefits and
risks of prostate cancer testing using the
prostate-specific antigen (PSA) test, its use
is widespread.23 According to national
health surveys, the proportion of males
aged 35 plus who had ever had a PSA test
was 53.8% in 2008.24 Two recent randomized trials have not confirmed PSA as a
viable population-based screening tool for
reducing prostate cancer deaths,25,26 and it
is not currently recommended in Canada
as a population-based screening test.
Nonetheless, the prostate cancer incidence
rate in Canada rose sharply following the
introduction of the PSA test in 1988. The
incidence rate peaked in 1993 and then
again in 2001. This second date could be
explained by the publicity that year surrounding the then federal health minister’s
disclosure that he had been diagnosed
with prostate cancer.
The prostate cancer mortality rate in
Canada has declined since 1995, returning
to pre-1970 levels in 2007. Early detection
of prostate cancer through widespread
screening is believed to have contributed
to the decreasing mortality trend in the
United States,27 and there is some suggestion that a similar phenomenon is responsible for the mortality and survival trends
in Canada.28 The nearly 10 percentage
point gain in the 5-year RSR since 1992
to 1994 may also, to some degree, be
explained by the greater availability of
effective hormonal therapy for early and
advanced-stage disease in the mid-1980s29
followed by the introduction of watchful
waiting and advances in combined radiation and hormonal therapy for prostate
cancer which occurred in the 1990s.30
Breast cancer
The female breast cancer incidence rate in
Canada rose steadily at 0.9% per year
$
75
between 1970 and 1998, after which the
rate started to decline at 0.7% per year.
Trends in breast cancer incidence likely
reflect long-term changes in hormonal
factors (e.g. early age at menarche, late
age at menopause, breastfeeding, oral
contraceptive use, hormone replacement
therapy use) and the increasing uptake
of mammography screening, especially
throughout the 1980s.31 The first provincial organized breast cancer screening
program was implemented in Canada in
1988, and all 10 Canadian provinces had
established programs by 1998.32 While all
provincial programs offer mammography
screening to women aged 50 to 69 years,
some are also open to those in their 40s
and those older than 69 years.32
National health surveys show that the
proportion of postmenopausal females
aged between 50 and 69 years who selfreport having a mammogram within the
previous two years has increased from
40.5% in 1990 to 72.5% in 2008.32 The
brief decline in the breast cancer incidence
rate between 1998 and 2005 could be due
to the exhaustion of undiagnosed prevalent cases as a result of screening and/or
to a reduction in breast cancer risk as
a result of postmenopausal women avoiding hormone replacement therapy following reports from the Women’s Health
Initiative and earlier investigations that
highlighted the associated risks.33
Although postmenopausal obesity and
alcohol consumption can increase breast
cancer risk34,35 and physical activity can
reduce risk,36 the impact of these factors
in the Canadian context is not clear.
The breast cancer mortality rate started
declining in 1986 at 1.0% per year and
accelerated to 2.4% per year after 1994.
The lower mortality and improved survival likely resulted from the increasing
use of opportunistic mammography testing prior to the establishment of provincial
screening programs, the increasing use of
hormonal and adjuvant chemotherapy37,38
and the shift in clinical practice to breastconserving surgery and lumpectomy.39,40
Lung cancer
Smoking is a causal factor in the development of lung, oral cavity and larynx
Vol 33, No 2, March 2013 – Chronic Diseases and Injuries in Canada
cancers, among others.41 The effects of
smoking tobacco on lung cancer incidence
are observed only after a latency period of
approximately 25 years.42 The prevalence
of smoking in Canada has decreased
substantially between 1965 and 2007 from
61% to 20% in males and from 38% to
18% in females aged 15 plus years.43 After
reaching a peak in 1965, tobacco use
dropped in response to the widely publicized negative health effects of cigarette
smoking reported by the U.S. Surgeon
General.44 This resulted in a decline in the
male lung cancer incidence rate after this
peaked in 1983 and in male mortality rate
after this peaked in 1988. By 2007, the
male lung cancer incidence rate had fallen
to nearly the same level as in 1970.
The lung cancer mortality rate in females,
on the other hand, has continued to
increase, albeit at a slower pace since the
mid-2000s. Smoking rates in females
started to decrease about 15 years after
those in males, remaining between 37%
and 39% until 1979.43 Though there is
still an upward trend in lung cancer
incidence and mortality rates in
Canadian females, encouraging U.S. data
show that the female lung cancer death
rate in that country is decreasing following
a plateau.45
Colorectal cancer
Colorectal cancer is associated with
several modifiable risks including obesity,
physical inactivity, consumption of red
and processed meat and smoking.46 The
prevalence of obesity (i.e. body mass
index § 30 kg/m2) in Canadian adults
has increased from 13.8% to 23.9%
over the 30 years until 2007/2009.47,48
Prevalence was higher in females (15.9%)
than in males (11.5%) in 1978/1979,
but this pattern has now reversed such
that slightly more males (24.2%) than
females (23.6%) were considered obese in
2007/2009.47,48
The colorectal cancer incidence rate in
males has returned to a level seen in the
early 1980s, while in females the rate is
now lower than that in the 1970s. The
decline in the male death rate began in
1988, while in females the rate continued
a decline that began before 1970. These
differing trends suggest different risk
factors. It has been suggested that increasing use of hormone replacement therapy
in women prior to the early 2000s may
have contributed to the declining risk of
colon cancer in this sex.34,49
The decline in colorectal cancer death
rates in both sexes began before the
growing uptake of screening through the
organized programs largely implemented
across Canadian provinces in the past six
years. Testing of occult blood in the stools
of average-risk individuals aged 50 plus
years50 and colonoscopy for high-risk
individuals have been the predominant
approaches for the early detection and
removal of pre-cancerous polyps,51 aimed
at lowering colorectal cancer incidence
and mortality. Currently, the average
participation rate for those aged between
50 and 74 years in provincial organized
screening programs is 32.2%.52 Greater
uptake of screening will likely further
reduce colorectal cancer incidence and
mortality rates in Canada.
Emerging trends in other cancers
Thyroid cancer
Thyroid cancer has been one of the most
rapidly increasing cancers in Canada in
recent years.1,53 The steep upward trend
could be due to the increasing use
of diagnostic technologies such as fineneedle aspiration for the detection of
subclinical tumours, increased exposure
to diagnostic ionizing radiation that could
promote the initiation of new tumours,
or increased exposure to an as yet unidentified environmental risk factor.54,55
Ionizing radiation remains the most established risk factor for thyroid cancer, but
mounting evidence points to a possible
role of body weight and female reproductive factors, both of which probably
operate in carcinogenesis through hormonal pathways. Despite the growing incidence rate, thyroid cancer mortality rates
have remained low and the 5-year RSR in
both sexes (98%) is the highest of all the
major cancers.
Liver cancer
The most common type of primary liver
cancer, hepatocellular carcinoma, is associated with low survival and high mortality. Between 1970 and 2007, incidence of
Vol 33, No 2, March 2013 – Chronic Diseases and Injuries in Canada
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76
liver cancer in Canada has increased faster
in males (3.5% per year) than in females
(1.9% per year). Gender differences in
incidence may be due to the different
distribution of liver cancer risk factors,
such as heavy drinking (i.e. above the
low-risk drinking guidelines56), smoking
and hepatitis infection. Population-based
estimates show that the heavy drinking
rate in Canada has increased between
1989 and 2007 from 18.9% to 25% for
males and 7.2% to 9.6% for females.57,58
In developed countries the greatest burden
of liver cancer is due to chronic hepatitis C
infection rather than hepatitis B virus
(HBV) infection, which is more prevalent
in other parts of the world.59 A link has
also been hypothesized between obesity
and liver cancer, which is believed to occur
through non-alcoholic fatty liver disease.60
Such an association places greater importance on the increasing obesity rate in
Canada, which has climbed from 14% in
the late 1970s to 24% in 2007/2009.47,48
Melanoma
Ultraviolet radiation can cause all forms of
skin cancer.61 Although the increasing
incidence of melanoma in Canada could
be in part due to better detection,62,63 it
more likely reflects greater recreational
UV exposure from sun and artificial
tanning. The prevalence of tanning is
about 49% in Canadian women and 28%
in Canadian men aged 16 to 24 years
according to the 2006 National Sun
Survey.64
Of all the major cancers, melanoma has
had the second greatest increase in mortality rate (after liver cancer in males and
lung cancer in females) since 1970.
Although the mortality rate in females
has remained essentially unchanged since
1983, in males the mortality rate rose by
1.1% per year over a similar time period
(1985–2007). The lower 5-year RSR65 and
the higher proportion of more advancedstage cases in males66 reflects the higher
melanoma mortality rate in men compared with women. However, the upward
rise in male mortality has been diminishing, possibly due to improved survival
through earlier detection and better treatments for melanoma including surgical
resection.67
Kidney
The reason behind the increasing kidney
cancer incidence rate, while not clear,
could reflect several changes including the
availability of newer diagnostic techniques68,69 as well as the increased prevalence of obesity and hypertension, both of
which are important risk factors.70 In fact,
55% of kidney cancers in Canadian males
and 27% in females may be attributable to
being overweight or obese.71
Trends in cancers with decreasing rates
Stomach, cervix, oral, larynx, bladder
Smoking is an important risk factor shared
by stomach, oral, larynx, bladder and
cervical cancers. The decreasing incidence
and mortality trends for these cancers can
be largely explained by trends in smoking,
which dropped dramatically after 1965
for males and after 1979 for females in
Canada.43 Changes in other risk factors
have also influenced observed trends.
For example, the decline in stomach
cancer rates since the 1970s resulted from
improvements in diet including higher
intakes of fruits and vegetables and
lower intake of salt-preserved foods,72
and more recently, an increased recognition and treatment of Helicobacter pylori
bacterium infection, a key stomach cancer
risk factor.73
Cervical cancer incidence and mortality
rates in Canada continued to decline
during the study period due to the widespread use of the Papanicolaou (Pap) test
screening introduced in 1949.74 As a
complement to Pap screening, immunization of females aged 9 to 26 years with
a human papillomavirus (HPV) vaccine
(approved in Canada in 200875) is
expected to further reduce the long-term
incidence and mortality rates. With the
growing recognition of HPV in the etiology
of certain oral cancers, such as those
arising in the tonsils and oropharynx,76,77
HPV immunization could also help shape
future oral cancer trends in Canada.
Limitations
Our analysis had several limitations.
First, we attempted to explain observed
cancer trends with regard to populationbased data on risk factors that are largely
cross-sectional and mostly self-reported.
Second, because of data availability, we
were able to consider only a subset of
modifiable lifestyle factors that influence
disease rates. Moreover, we considered
only modifiable risk factors that may be
etiologically relevant to adult-onset cancers but not those unique to pediatric
and adolescent cancers. Third, the data
sources, methods for cancer registration,
as well as completeness and accuracy of
data used for deriving incidence estimates
can vary across Canada.1 Such differences
can lead to minor under- and overestimates of disease rates, which are discussed more fully elsewhere.1 Finally,
relative survival estimates for the years
2005 to 2007 may be overestimated due to
the necessity of using expected survival
data from an earlier time period in their
derivation. The effect would likely be
greatest for cancers with older case distributions such as prostate cancer.
of data supplied by the provincial and
territorial cancer registries whose cooperation is gratefully acknowledged.
Conflict of interest: none.
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65. Joosse A, de Vries E, Eckel R, Nijsten T,
Eggermont AM, Holzel D, et al. Gender
differences in melanoma survival: female
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66. Howlader N, Noone AM, Krapcho M,
Neyman N, Aminou R, Waldron W, et al.,
editors. SEER Cancer Statistics Review,
1975–2008. Bethesda (MD): National
Cancer Institute; 2011 [cited 2011 Dec 13].
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67. Morton DL. Current management of malignant melanoma. Ann Surg. 1990;212(2):
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70. Chow WH, Gridley G, Fraumeni JF Jr,
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Cancer. 2010;116(11):2635–44.
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Parenting disability, parenting stress and child behaviour in
early inflammatory arthritis
P. Zelkowitz, EdD (1); K. J. Looper, MD (1); S. S. Mustafa, PhD (1); M. Purden, PhD (2); M. Baron, MD (3);
McGill Early Arthritis Research Group*
This article has been peer reviewed.
Abstract
Introduction: Our study examines the association between the disease characteristics of
inflammatory arthritis and patients’ self-perception of mental health, parenting
disability, parenting stress and child behaviour in early inflammatory arthritis (EIA).
Methods: Patients in the early phase (more than 6 weeks, less than 18 months) of
inflammatory arthritis were recruited from a larger EIA registry that recorded
sociodemographic data and measures of pain, physical functioning and disease
activity. Patient-perceived parenting disability, parenting stress, depression and
children’s behaviour problems were assessed using the Parenting Disability Index,
Parenting Stress Index, Center for Epidemiologic Studies - Depression Mood Scale and
Child Behavior Checklist, respectively.
Results: Pain, physical dysfunction, number of tender joints and physician global
assessment of disease activity were associated with parenting disability. Self-report
measures of parenting disability were associated with those of depression and parenting
stress. Parenting stress was associated with children internalizing and externalizing
behaviour problems while parenting disability was associated with children
externalizing behaviour problems.
Conclusion: This study suggests a possible reciprocal relationship among physical
aspects of disease activity, parenting disability and parent and child distress in EIA.
Keywords: parenting disability, parenting stress, child behaviour, arthritis, physical
functioning, pain
Introduction
Arthritis comprises more than a hundred
rheumatic conditions involving joints and
their surrounding tissues. Inflammatory
arthritis occurs when joints get inflamed
because of immune system disruptions. It
is a painful disabling condition associated
with impairment in psychological and
social functioning.1,2 Rheumatoid arthritis
*
(RA) is the most common form of inflammatory arthritis and is characterized by
chronic destructive synovitis. Undifferentiated arthritis is one that does not fulfill
disease classification criteria and can
ultimately either resolve or else evolve to
full-blown rheumatoid arthritis.
Physical illness in a parent can affect
children in many ways. The parent may be
unable to perform usual childcare tasks and
may, in fact, expect children to take on
additional household responsibilities.3
Moreover, the parent may be emotionally
unavailable due to pain, fatigue and preoccupation with the disease.4,5 Family stress
related to possible loss of income or marital
conflict around changing roles and division
of labour may also take its toll on the parentchild relationship.6 Children’s adjustment is
most likely to be affected if the ill parent
exhibits psychological distress4 and if parenting behaviour is affected.5
Research in families with a parent suffering from arthritis has been limited, but
what is available indicates significant
negative effects. For example, an exploratory study by Grant et al.7 showed that
parents and grandparents with RA experience difficulties with instrumental childcare tasks such as lifting a child. Katz
et al.8 found that women with RA
experience disability in parenting activities and hence perform fewer parenting
functions. Backman et al9 qualitatively
examined the experiences of mothers
living with arthritis and described the
impact of inflammatory arthritis on
motherhood as dramatic, with both positive and negative influences. They
described participation in the mothering
role as fluctuating and influenced by the
support available and the unpredictable
balance of fatigue and energy.9 This
resulted in the family being more cohesive
at certain times and feeling regret about
lost family activities at other times.9
M. Starr, MD; M. Gagné, MD; M. Stein, MD; H. Kang, MD; M. Kapusta, MD; F. Couture, MD; M. A. Fitzcharles, MD; B. Garfield, MD; H. A. Ménard, MD; L. Berkson, MD; C. Pineau, MD;
A. Gutkowski, MD; M. Zummer, MD; J. P. Mathieu, MD; S. Mercille, MD; S. Ligier, MD; J. Krasny, MD; C. Bertrand, MD; S. Y. Yuen, MD; J. Schulz, MD.
Author references:
1. Department of Psychiatry, McGill University, Montréal, Quebec, Canada
2. Department of Nursing, McGill University, Montréal, Quebec, Canada
3. Department of Rheumatology, McGill University, Montréal, Quebec, Canada
Correspondence: Karl Looper, Department of Psychiatry, McGill University, Jewish General Hospital, 3755 Chemin de la Côte-Ste-Catherine, Montréal, QC H3T 1E2; Tel.: 514-340-8222;
Fax: 514-230-8126; Email: karl.looper@mcgill.ca
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Vol 33, No 2, March 2013 – Chronic Diseases and Injuries in Canada
Arthritis patients often perceive themselves as functioning inadequately with
regard to their children and grandchildren.10 One study reported that children of
RA patients had more daily hassles,
smaller social support networks and
poorer social adjustment than did the
controls.11 Adolescent children of a parent
with RA reported lower self-esteem than
those of well parents.12
Much of the research in this area has
consisted of small, qualitative studies.
Moreover, it usually involved patients
who have been ill for many years.
However, parenting issues may be different in early versus longstanding inflammatory arthritis. Clearly needed is
research examining the relationship
between parenting and children, mental
health, and illness outcomes early in
the disease trajectory, with the aim
of developing treatment interventions
directed at specific factors in the early
stage of illness to improve subsequent
health and parenting outcomes.
To that end, we undertook this study to
explore the associations between disease
variables such as pain, physical dysfunction and disease activity, mental distress,
parenting factors such as parenting
ability and parenting stress, and child
behavioural measures during the first
18 months of the parents’ inflammatory
arthritis.
assessed by asking the patient ‘‘When
did you first start to have this episode of
joint pain?’’ and ‘‘Have you ever had
episodes of similar pain and swelling in
your joints before this episode?’’) Patients
were 18 years or older, spoke English or
French, and agreed to periodic physical
and laboratory examinations as well as
to completing questionnaires assessing
demographics, disability, pain and psychosocial factors related to their illness.
Exclusion criteria included clinical evidence of remote joint damage suggestive
of a previous episode of RA, any rheumatic diagnosis other than RA or undifferentiated inflammatory arthritis, severe
functional limitation from a disease other
than arthritis, and any disorder that
compromised the ability to give informed
consent.
Of the 257 patients enrolled in the McEAR,
80 had children younger than 18 years of
age living with them. All the 257 patients
enrolled in the McEAR were invited to
participate in psychosocial studies, which
involved a home visit by interviewers, and
104 (40.5%) agreed to do so. Of the 104
participants, 29 had children aged less
than 18 years living with them. All of
those 29 parent participants agreed to
participate and constituted the sample for
this study, a response rate of 36% (29/80 of
the McEAR participants who had children
under 18 years) when considering the
McEAR as a whole and 100% of those
who agreed to the psychosocial study.
Methods
Participants
Two hundred and fifty-seven patients
were enrolled in the McGill Early
Arthritis Registry (McEAR) between
March 2006 and May 2009. Referrals to
the McEAR come from 21 rheumatologists
working in Montréal, Quebec. The participating rheumatologists, each of whom
works in a private office or outpatient
hospital clinic, were asked to recruit all
new patients with early inflammatory
arthritis (EIA) who fit the inclusion criteria, that is, they had newly diagnosed
inflammatory arthritis, defined as one or
more joints with inflammation that lasted
a minimum of 6 weeks to a maximum
of 18 months. (Disease duration was
All patients in the registry were seen by
one of the two study nurses who met
them at the office of the referring rheumatologist with whom the clinical care
remained. (This made it easier for those
patients who lived on or near the island
of Montreal.) Each nurse was trained to
perform a complete tender and swollen
joint count. Nurses, physicians and patients
were not blind to one another’s evaluations.
A trained interviewer, blind to patients’
information recorded in the main registry
database, arranged to see the patient at
home within 10 days of the registry visit
for this study. The trained interviewer
obtained consent to proceed with the interview and assisted the patients in filling out
the study-specific questionnaires. Patients
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received $25 for each meeting with the
study interviewer. All patients in the
McEAR signed an informed consent and
the study was approved by the Institutional
Review Boards of McGill University and
the Jewish General Hospital.
Illness outcome measures
Physical functioning
We measured physical functioning using
the Medical Outcomes Study Short-Form
36 (SF-36)13 which, with its good psychometric properties, has been frequently
used to measure health-related quality
of life. It consists of eight domains:
physical functioning, social functioning,
role limitations (physical problems), role
limitations (emotional problems), mental
health, vitality, bodily pain and general
health perceptions. Scores range from 0
(worst) to 100 (best). Although the 8
scales are combined into 2 summary
measures, one of which, the Physical
Component Score (SF36-PCS), provides
an overall estimate of physical health,
we chose to measure physical function
using the physical functioning domain
score. We measured pain more specifically
using the McGill Pain Questionnaire
(MPQ). 14
Pain
Pain was assessed using the Short-Form
MPQ,15 which contains 11 items related
to the sensory dimension of pain and 4
related to the affective dimension. Each
descriptor is ranked on a four-point
intensity scale (0–3; none to severe), and
total scores range from 0 (no pain) to 45
(severe pain). The MPQ has been extensively used and has sound psychometric
properties. The total pain score was used
in this study.
Disease activity
We assessed disease activity using joint
counts, with the number of swollen and
tender joints determined according to the
American College of Rheumatology joint
count.16 We also measured blood level of
the acute-phase reactant, C-reactive protein (CRP). Number of swollen joints,
number of tender joints, patient global
assessment of disease activity and blood
CRP level together make up the Disease
Activity Score in 28 joints (DAS28).17–20
DAS28, based on 28 specific joints that are
a subset of the American College of
Rheumatology criteria, was developed17
and validated18 for patients with RA and is
considered to be a valid measure of
disease activity.18 The validation criteria
included correlations with a selected
group of other disease variables (correlational validity), with physical disability
and judgment of a group of rheumatologists in clinical practice (criterion validity I
and II, respectively) and with the radiographically determined damage of hands
and feet (construct validity).18 DAS28,
however, excludes joints of the ankles
and feet.21
In our study, we completed the patient
global assessment of disease activity using
an 11-point visual analogue scale that
ranged from 0 (best) to 10 (worst) with
reference to the past week. The rheumatologist rated the physician global assessment of disease activity using a single
11-point numerical rating scale where 0
meant ‘‘no arthritis activity’’ and 10 meant
‘‘worst arthritis.’’
Psychosocial measures and parenting and
child functioning measures
Center for Epidemiologic Studies Depression Mood Scale
The Center for Epidemiologic Studies –
Depression Mood Scale (CES-D) is a
20-item self-report scale designed to measure depression in the general population.22 Answers are based on how
frequently in the previous week each item
was experienced. Scores range from 0 to
60, with higher scores indicating greater
depression. A cut-off score of 16 is the
requirement for identifying depression,
but in chronic disease such as RA, cutoffs of 19 have been recommended.23,24
In our study, we used the total score
(continuous variable) to measure symptom severity.
Parenting Stress Index
The Parenting Stress Index (PSI) (Short
Form)25 is a 36-item self-report measure
assessing parental distress. It has 3 subscales, Parental Distress, Parent-Child
Dysfunctional Interaction and Difficult
Child. Each item is rated from 1 (‘‘strongly
disagree’’) to 5 (‘‘strongly agree’’). Higher
scores indicate greater stress. Cronbach’s
a ranges from .88 to .95, and the scale has
construct validity compared to measures
of children’s behaviour problems.25 We
used the total score in this study.
Parenting Disability Index
The Parenting Disability Index (PDI) was
developed as a measure of parenting
function and disability and validated in
women with RA.8 The 27 items on the
scale are scored from 0 to 3, with 0
meaning no disability and 3 meaning
inability to perform parenting tasks.
The PDI is the mean difficulty level
across the domains within the parent
cohort/child age group. Two summary
scores were developed; the summary
score used in this study is the modified
PDI (MPDI).8 This scale was validated in
an RA population.
Child Behavior Checklist
The Child Behavior Checklist (CBCL)26,27
was used to assess children’s behaviour
problems, using the relevant versions for
children aged 1.5 to 5 years and 6 to
18 years. Parents rate their children’s
behaviour over the previous 2 months.
Items are scored 0 for ‘‘not true’’ to 2 for
‘‘very or often true.’’ Both versions have
3 broadband (summary) scores representing internalizing problems, externalizing problems and total problems.
Internalizing problems include anxiety,
depression and somatic symptoms, while
externalizing problems include conduct
problems, hyperactivity and aggression.
Test-retest reliabilities range from .88 to
.91 for the broadband scales, and the
interrater reliability for the CBCL is .72 for
internalizing problems and .85 for externalizing problems.26 We used internalizing and externalizing scores for both age
groups. To obtain comparable data, if
there were 2 or more children residing at
home, parents were asked to rate the
behaviour of the child closest in age to
10 years.
Statistical analysis
Because of the small sample size (n = 29),
data analyses in this study must be
considered exploratory. Data were analyzed using SPSS version 17 for Windows
(IBM, Chicago, IL, US). Descriptive statis-
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tics were used to summarize baseline
characteristics of the EIA patients.
Pearson correlations were used to calculate the associations between the continuous study variables. Missing data
was not imputed, and we did not include
cases for which data were missing in our
calculations.
Results
The mean age of our study participants
was almost 42 years; 20 (69%) were
female and 23 (79%) were married/cohabiting. A total of 21 (72%) participants
were employed; 14 were working full
time, 3 were on sick leave, 2 were working
part time and 2 were self-employed. The
total yearly household income of more
than half of the participants was over
$60,000. The sample was highly educated
with 20 (69%) college, university or postgraduate educated. Out of our 29 participants, 15 (52%) had 1 child, 10 (35%) had
2 children and 4 (14%) had 3 children
aged under 18 years living at home. Our
participants had an average disease duration (standard deviation) of 8.24 (3.65)
months. Four participants (14%) had a
CES-D score above the cut-off of 19.
(See Table 1.)
The average age of the target child was
10.6 years. The proportion of boys and
girls was almost equally distributed along
the sample, and 48% of the target children
(those closest in age to 10 years) were
girls. Three children scored above the
clinical cut-off of 60 on CBCL internalizing
and externalizing problems.
Parenting stress (PSI) was significantly
correlated only to CES-D total depressive
mood score. On the other hand, patientperceived parenting disability (MPDI) was
correlated to all the disease measures:
physician global assessment of disease
activity, number of tender joints, physical
dysfunction (SF-36) and pain (MPQ) in
addition to depressive mood (CES-D).
Patient-perceived children’s externalizing
and internalizing behaviour problems
(CBCL, all ages) showed significant correlation to physician global assessment of
disease activity. Parental depressive symptoms were not associated with children’s
behaviour problems. Table 2 shows the
Vol 33, No 2, March 2013 – Chronic Diseases and Injuries in Canada
Discussion
TABLE 1
Characteristics of study participants (N = 29)
Study variable
Frequency,
n (%)
Mean
(SD)
95% Confidence
interval
41.97 (7.95)
26–57
Demographics
Age, years
Female
20 (69)
Married/co-habiting
23 (79)
Employed
21 (72)
Yearly household income
< $60,000
11 (38)
§ $60,000
17 (59)
Education level
High school or less
College or more
9 (31)
20 (69)
Number of children
1
15 (52)
2
10 (35)
3
4 (14)
a
Age of target child
Gender of target childa: girl
10.60 (5.10)
1.00–18.00
13 (48)
Disease characteristics
Duration, months
8.24 (3.65)
4.00–18.00
60.04 (28.90)
5.00–100.00
8.60 (11.17)
0.00–45.00
Number of swollen joints
9.19 (9.56)
0.00–39.00
Number of tender joints
16.00 (12.76)
0.00–43.00
CRP, mg/L
22.87 (22.49)
0.30–69.00
SF-36 physical functioning
MPQ total pain
DAS28
5.30 (1.80)
2.61–8.08
Physician global assessment of disease activity
3.96 (2.71)
0.00–10.00
CES-D total depressive mood
10.03 (10.58)
0.00–41.00
PSI
63.89 (19.43)
36.00–100.00
Psychosocial variables
MPDI for all ages
0.65 (0.61)
0.00–1.95
CBCL, externalizing problems, all ages
47.96 (8.18)
34.00–65.00
CBCL, internalizing problems, all ages
50.55 (11.39)
33.00–78.00
Abbreviations: CBCL, Child Behavior Checklist; CES-D, Center for Epidemiologic Studies - Depression Mood Scale; CRP,
C-reactive protein; DAS28, Disease Activity Score in 28 joints; MPDI, Modified Parenting Disability Index; MPQ, McGill Pain
Questionnaire; PSI, Parenting Stress Index; SF-36, Medical Outcomes Study Short Form 36; SD, standard deviation.
a
To obtain comparable data, if there were 2 or more children residing at home, parents were asked to rate the behaviour of
the child closest in age to 10 years.
relationships between parents’ physical
and mental health and parenting and child
behaviour problems.
Parenting stress (PSI) was significantly correlated to parenting disability (MPDI) and
children’s internalizing and externalizing
(CBCL) problems. Patient-perceived parenting disability (MPDI) showed significant
correlation to children’s externalizing
(CBCL) problems in addition to parenting
stress. Table 3 shows the interrelationships
between parenting and child behaviour
variables.
Other disease-related variables including
the number of swollen joints, CRP and the
DAS28 did not show significant correlations with any of the parenting or child
behaviour measures.
Vol 33, No 2, March 2013 – Chronic Diseases and Injuries in Canada
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Parenting is both physically and emotionally extremely demanding.28 Given the
scarcity of literature on how chronically
ill arthritis patients who have young
children manage both their illness and
parenting, we sought to examine the
relationship between arthritis in its early
stages (between 6 weeks and 18 months)
and patients’ self-rated distress, ability to
perform parenting tasks and perception of
their child’s behaviour.
The main findings of this study indicate
that arthritis, even in its early stages,
does interfere with parenting. Our patients
suffered increased parenting disability
with the increase in multiple measures of
disease activity including pain, physical
dysfunction, number of tender joints and
physicians’ assessment of disease activity.
Patients reported having difficulties with,
among others, bending, outdoor activities
or having other children in their home.
This perceived inability to parent adequately may have resulted in feelings of
distress. This is suggested by the fact that
parenting disability was highly correlated
with parenting stress and both of these
factors were related to CES-D depressive
mood score.
These findings are consistent with previous research in more advanced RA
patients.7,8 These studies found that many
patients had problems with parenting,
particularly with tasks related to physical
care activities such as lifting a child from
the floor and keeping up with children.
These problems are often attributed to
physical as well as psychological issues
such as anxiety, depression and guilt.
White et al.29 also found that for mothers
with RA, more fatigue was a significant
predictor of greater frequency and intensity of daily parenting problems and
greater difficulty monitoring their children’s whereabouts.29 Mothers with RA
had more problems monitoring their
child if they were more depressed and
experiencing an exacerbation.29 Our
results also agree with those of a very
recent study30 that investigated the
impact of systemic lupus erythematosus
on mothering abilities. The authors
reported that greater fatigue and func-
TABLE 2
Pearson product moment correlations (r) among study variablesa
Statistics
Parental health disease measure
CES-D total
depressive
mood
Physician global
assessment of
disease activity
Number
of tender
joints
SF-36
physical
functioning
MPQ
total
pain
Parenting variables
Parenting Stress
Index (PSI)
Parenting
Disability Index
(MPDI)
r
.565**
.360
.039
2.149
.045
p
.002
.077
.874
.488
.834
n
27
r
.716**
25
19
24
.648**
.541*
2.608**
.455*
24
p
<.001
.001
.025
.003
.038
n
24
22
17
21
21
Child behaviour problems (CBCL)
Internalizing
Externalizing
r
.348
.503*
.017
2.148
2.020
p
.113
.020
.951
.546
.934
n
22
21
15
19
19
r
.363
.441*
.016
2.274
2.092
p
.074
.035
.950
.218
.684
n
25
23
18
22
22
Abbreviations: CBCL, Child Behavior Checklist; CES-D, Center for Epidemiologic Studies - Depression Mood Scale; MPDI,
Modified Parenting Disability Index; MPQ, McGill Pain Questionnaire; PSI, Parenting Stress Index; SF-36, Medical Outcomes
Study Short Form 36.
a
Data on depression, pain, physical functioning, parenting stress, parenting disability, and children’s behaviour problems
based on patients’ perceptions.
* Correlation is significant at the 0.05 level (2-tailed).
** Correlation is significant at the 0.01 level (2-tailed).
tional disability resulted in higher PDI
scores in mothers with children aged
less than 18 years living with them.
The mean disease duration of those
mothers was 7 years. In our study we
were able to detect the association
between
patient-perceived
parenting
disability and disease variables within
8 months, on average, from the onset of
illness.
The patients’ reduced parenting efficacy
and concomitant psychological distress
also affected their children. Children
TABLE 3
Pearson product moment correlations (r) between parenting and child behaviour variables
Statistics
Parenting Stress
Index (PSI)
Parenting
Disability Index
(MPDI)
Child behaviour
problems
(CBCL)
Internalizing
Parenting variables
Child behaviour variables
PSI
MPDI
CBCL – internalizing
CBCL – externalizing
r
—
.441*
.537**
.572**
p
—
.031
.010
.003
n
—
24
22
25
r
—
—
.232
.486*
p
—
—
.325
.022
n
—
—
20
22
r
—
—
—
.759**
p
—
—
—
.000
n
—
—
—
22
Abbreviations: CBCL, Child Behavior Checklist; MPDI, Modified Parenting Disability Index; PSI, Parenting Stress Index.
* Correlation is significant at the 0.05 level (2-tailed).
** Correlation is significant at the 0.01 level (2-tailed).
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whose parents had more physician-rated
disease activity were rated by those
parents as exhibiting more externalizing
and internalizing behavioural problems.
Parenting stress was associated with both
internalizing and externalizing problems
while parenting disability was correlated
only with externalizing problems. It is
possible that children whose parents
are less well able to supervise and care
for them will be prone to more noncompliant, aggressive behaviour. In a
study by Welch et al.31 parents recently
diagnosed with cancer did not detect
emotional or behavioural problems on
the CBCL scale in their children; however,
their children, especially adolescent girls,
reported symptoms of anxiety/depression
and aggressive behaviour.31 These findings indicate that future studies should
include children’s self-reports along with
their parents’ in order to achieve a
more complete picture of child distress in
response to parental chronic illness.
That physician global assessment of disease activity—and not measures of function, pain or joint counts—relates to the
patients’ perceptions of their children’s
externalizing and internalizing behaviour
could indicate that patients’ reports of
distress about parenting have some influence on physicians’ global assessment.
Rheumatologists could be invited to refer
patients to allied health care professionals
for further assessment on an individualized basis.
Limitations
Our study was limited by a small sample
size (n = 29). Only 30% of the participants in the McEAR registry had children
under 18 living at home. Since our study
was concerned with parenting, we were
unavoidably limited to those patients with
children living at home with them. We
thus lacked power to detect significant
associations among the study variables.
For example, it was not possible to explore
differences in employment status as well
as other non-work responsibilities that
may have affected parenting stress and
mood. Nevertheless, we were able to
demonstrate significant relationships
between parental mood and parenting,
Vol 33, No 2, March 2013 – Chronic Diseases and Injuries in Canada
as well as between disease activity and
parenting behaviour.
This study was cross-sectional and therefore did not allow for estimation of the
causal direction of the observed associations. Longitudinal studies are required to
assess how disease progression may affect
the parent-child relationship as well as
child outcomes. However, based on previous research reporting that disability in
valued life activities is a strong predictor
of the subsequent development of depressive symptoms and that depressive symptoms lead to lower parental functioning,32
we speculate that disability in parenting
activities would be associated with psychological distress with consequent negative effects on the children.
A third limitation of our study is the use of
parental reporting of their own psychological
and physical symptoms as well as child
outcomes, which may result in shared
method variance. Future research should
follow the families longitudinally to see
how disease progression or improvement
following a course of treatment affects
the parent-child relationship and child
outcomes. Moreover, it would be useful
to obtain information from the children
themselves and also to have independent
ratings by teachers or other knowledgeable
informants.
Finally, recent research suggested that the
DAS28 may underestimate disease activity
in some RA patients with disease onset
mainly in the feet and particularly during
the first 2 years of the disease.21
Conclusion
Our study pointed towards the potential
inability of parents to provide their children
with quality care due to their arthritisinduced pain, physical dysfunction and
disease activity. This patient-perceived
physical impairment was associated with
psychological distress in the parents and
patient-perceived behaviour problems in
the children, which highlights the interrelatedness and complexity of the relationships between parents’ physical health,
psychological health and parent-child interactions. A multifaceted approach to the care
for parents with arthritis is called for. It is
important to manage not only the physical
symptoms of arthritis, but also the emotional distress attendant upon the pain and
functional impairment associated with the
disease. Backman et al. 9 suggested some
strategies that might help parents with
arthritis fulfill their parenting role. These
include adjusting expectations, adaptive
or alternative approaches to performing
parenting tasks, public health interventions
and credible advice grounded in the experiences of parents living with arthritis.9
Reframing and explaining illness behaviour
to children33 and encouraging mature child
behaviour34 could also be beneficial.
Acknowledgements
This study was supported by grant 8455
from the Fonds de la recherché en santé
du Québec.
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14. Melzack R. The McGill Pain Questionnaire:
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16. Felson DT, Anderson JJ, Boers M,
Bombardier C, Chernoff M, Fried B, et al.
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measures for rheumatoid arthritis clinical
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20. Wijnands MJ, van’t Hof MA, van Leeuwen
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21. Bakker MF, Jacobs JW, Kruize AA, van der
Veen MJ, van Booma-Frankfort C,
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23. Martens MP, Parker JC, Smarr KL, Hewett
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32. Pakenham KI, Cox S. Test of a model of the
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33. Allaire S. How a chronically ill mother
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24. McQuillan J, Fifield J, Sheehan TJ, Reisine
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analysis. Arthritis Rheum. 2003;49(3):
368–76.
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Vol 33, No 2, March 2013 – Chronic Diseases and Injuries in Canada
Population-based surveillance of asthma among workers in
British Columbia, Canada
M. Koehoorn, PhD (1); L. Tamburic, BSc (2); C. B. McLeod, PhD (2); P. A. Demers, PhD (3); L. Lynd, PhD (4);
S. M. Kennedy, PhD (1)
This article has been peer reviewed.
Abstract
Introduction: Population-based health databases were used for the surveillance of
asthma among workers in British Columbia for the period 1999 to 2003. The purpose
was to identify high-risk groups of workers with asthma for further investigation,
education and prevention.
Methods: Workers were identified using an employer-paid health premium field in the
provincial health registry, and were linked to their physician visit, hospitalization,
workers’ compensation and pharmaceutical records; asthma cases were defined by the
presence of an asthma diagnosis (International Classification of Diseases [ICD]-9-493) in
these health records. Workers were assigned to an ‘‘at-risk’’ exposure group based on
their industry of employment.
Results: For males, significantly higher asthma rates were observed for workers in the
Utilities, Transport/Warehousing, Wood and Paper Manufacturing (Sawmills), Health
Care/Social Assistance and Education industries. For females, significantly higher rates
were found for those working in the Waste Management/Remediation and Health Care/
Social Assistance industries.
Conclusion: The data confirm a high prevalence of active asthma in the working
population of British Columbia, and in particular, higher rates among females compared
to males and in industries with known respiratory sensitizers such as dust and chemical
exposures.
Keywords: population surveillance, occupational diseases, asthma, British Columbia
Introduction
Exposure to occupational hazards accounts
for a significant proportion of the national
and global burden of disease, which could
be substantially reduced through recognition, measurement and controls. Workrelated asthma is considered to be the most
common work-related respiratory disease
in industrialized countries.1 Occupational
exposures, including organic and inorganic
dusts, and biological agents, such as
flour/grains, plants, fur, feathers, fungi
and various types of woods, are important
risk factors for both the initiation and
aggravation of adult asthma.2,3 The
American Thoracic Society,4 in their review
of the literature based largely on studies
in industrialized countries, estimated that
approximately 15% of asthma was due to
occupational exposures, although other
estimates of the attributable risk proportions are as high as 29% and 36.5%.5,6
Workers’ compensation statistics often do
not reflect this level of risk in the population.7 There are limitations in the use
of accepted workers’ compensation claim
data for surveillance, in particular the
ability of the data systems to ascertain
cases of disease due to underreporting,8 a
lack of recognition of the relationship
between some exposures and health outcomes, or emerging relationships that are
not yet recognized without systematic data
collection.
The National Institute for Occupational
Safety and Health (NIOSH) in the United
States highlighted the need for improved
surveillance research methods.9–11 NIOSH
specifically mentions the use of linked
data sources, such as administrative and
health care data, to identify populations
that may not be well captured in existing
surveillance systems. We investigated
multiple administrative health databases
for population-based surveillance of
asthma rates by industry of employment
among workers in the Canadian province
of British Columbia. We also investigated
the face validity of this surveillance
approach by investigating asthma rates
among high-risk groups using an exposure
matrix.2 We hypothesized that the rate
would be higher among workers in industries with suspected or known allergens
such as wood dust (i.e. wood and paper
manufacturing), moulds or endotoxins
(e.g. schools) and latex/glutaraldehyde
or industrial cleaning agents (e.g. health
care services).2,12,13
We had access to health databases for
population health and health services
Author references:
1.
2.
3.
4.
School of Population and Public Health, University of British Columbia, Vancouver, British Columbia, Canada
Centre for Health Services and Policy Research, University of British Columbia, Vancouver, British Columbia, Canada
Occupational Cancer Research Centre, Cancer Care Ontario, Toronto, Ontario, Canada
Pharmaceutical Sciences, University of British Columbia, Vancouver, British Columbia, Canada
Correspondence: Mieke Koehoorn, School of Population and Public Health, University of British Columbia, 2206 East Mall, 1st Floor, Vancouver, BC V6T 1Z3; Tel.: 604-822-5756; Fax: 604822-4994; Email: mieke.koehoorn@ubc.ca
Vol 33, No 2, March 2013 – Chronic Diseases and Injuries in Canada
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research via Population Data BC.14
The data included longitudinal, personspecific, de-identified health data on
British Columbia’s 4.5 million residents
across multiple data sources. The use of
these linked administrative health databases provided a novel approach to
work-related health surveillance, beyond
workers’ compensation statistics. As surveillance tools, the databases can provide
evidence of the relationship between
exposures and disease outcomes for
further investigation of high-risk groups
and recognition of work-related illness, as
well as education and prevention efforts.
Methods
Study population
Using the provincial health registry, we
identified individuals aged 15 to 64 years
who had been continuously registered (i.e.
living in the province) for a minimum of
3 years at entry into the study. The study
population excluded individuals with
missing data on sex or with a diagnosis
of chronic obstructive pulmonary disease
(International Classification of Disease,
version 9 [ICD-9] codes 491, 492, 496)
given the potential overlap between
asthma and chronic obstructive lung
disease diagnoses in older adults. Among
continuously registered residents, we
identified workers using an employer-paid
health premium code in the health registry. As a dynamic study population,
individuals could enter the study at any
time from 1999 to 2003 providing they met
the inclusion criteria.
Exposure groups
The employer-paid health premium codes
were used to assign a standardized industry of employment (North American
Industry Classification System or NAICS
code15). To identify industries with
known or suspected allergen exposures,
defined here as at-risk or high-risk industries, we used an asthma-specific job
exposure matrix2 previously developed
for population-based studies. All matches
between the matrix and our study sample
were reviewed by investigators (MK, PD)
with expertise in occupational asthma
and occupational hygiene as well as
knowledge of British Columbia industries
and their exposures.
Health data sources
Health data on physician visits and hospitalizations, workers’ compensation claims
and filled prescriptions for the population
of British Columbia were available to
researchers for approved projects from
the Ministry of Health, WorkSafeBC and
PharmaNet, respectively, via Population
Data BC. Data are linkable at the individual
level but were provided to researchers
with personal identifiers removed from
the records. Use of the data for this project
was governed by data access and confidentiality agreements between the data
stewards and the researchers, as well as
by the Behavioural Ethics Research Board
of the University of British Columbia
(Certificate #B05-0664). Given a universal
health care system for physician visits
and hospitalizations, over 93% workforce
coverage by the workers’ compensation
system and a provincial prescription database (all prescriptions filed in pharmacies
in British Columbia), the health data are
considered comprehensive for provincial
residents. Follow-up of asthma outcomes
was limited to the study years given the
availability of health records across all data
sources and the availability of industry
of employment codes in the provincial
health registry.
Case definition
Physician-diagnosed asthma was identified using the ICD-9 code 493. The case
definition was met if a worker had one
diagnosed hospitalization, two diagnosed
physician visits in a 12-month period, one
diagnosed workers’ compensation claim,
or two prescriptions for any asthmarelated drugs confirmed by at least one
diagnosed physician visit within a
12-month period.7 In the event of two
physician visits or two prescriptions
within 12 months but spanning calendar
years, the year of the first visit or
prescription was attributed to the asthma
case. Asthma-related drugs were defined
by the pharmacist on the research team
(LL) and extracted based on the Drug
Identification Number (list available
upon request).
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For the purposes of surveillance, we were
interested in ‘‘active’’ asthma among the
working study population during each
year of follow-up. Focusing on active
asthma is important as both asthma onset
(incident cases during follow-up) and
aggravation of existing asthma (prevalent
cases requiring health care during followup) are compensable conditions associated with workplace exposures in
British Columbia. Individuals who met
the case definition before entry into the
study were prevalent cases. Individuals
who met the case definition during the
study follow-up period (i.e. were asthmafree for a minimum of three years before
entry into the study) were incident cases.
Incident cases were considered active
asthma in the year they became an
incident case and each subsequent year
that they had a health care contact for
asthma. Prevalent cases were considered
active asthma in each year that they had a
health care contact for asthma. Active
asthma was defined as contact with the
health care system (physician visit, hospitalization, prescription or compensation
claim) during the year.
Analysis
Rates of active asthma were calculated per
year of follow-up using Stata version 10.1
(StataCorp, College Station, TX, US). Ageand sex-adjusted rates with 95% confidence intervals (CIs) were compared by
industry of employment groups and for
high-risk versus low-risk industries.
Results
Study population
A total of 2.7 million residents of working
age were continuously registered for
health services during the study period,
1999 to 2003. Less than 0.3% of individuals were excluded for missing data
on sex (n = 4001) and for a diagnosis of
chronic obstructive pulmonary disease
(n = 3456). Altogether, 908 896 workers
were identified by industry of employment
using the employer-paid health premium
codes. They represented 33% of the
registered population but 60% of the working population in British Columbia.16 This
method of identifying a population-based
Vol 33, No 2, March 2013 – Chronic Diseases and Injuries in Canada
working cohort using the employer-paid
health premium codes underrepresents the
self-employed, small worksites (i.e. < 5
employees) and females as these groups
have lower rates of employer-paid health
premiums.
In 2003, females made up 42.8% of the
included working study population, compared to 47.2% of the overall British
Columbia workforce17 and to 50.6% in the
continuously registered population from
which the working population was drawn.
The mean age of the working study
population was 42.1 years; this compares
to an average age of 40.7 years among
workers in the province 18 and to 39.4 years
among the registered population.
The included working study population
was distributed over 843 distinct industrial
sectors. Males were concentrated in Wood
and Paper Manufacturing (14.8% in 1999
and 13.4% in 2003), Public Administration
(11.7% and 11.0%) and Transport and
Warehousing (8.2% and 7.7%). Females
were concentrated in Health Care and
Social Assistance (22.8% and 23.3%) and
Education (14.9% and 14.8%). This is
comparable to the top industries of employment by gender in the overall provincial
workforce, with the exception of Trades for
both genders, Construction among males
and Accommodation and Food Services
among females.19
Active asthma rates
Overall, we identified a total of 41 966
cases of asthma, of which 30 080 were
prevalent at the time of entry into the
study (for a prevalence rate of 33.1 cases
per 1000 workers) and 11 886 were new
cases identified during the study follow-up
period (for a cumulative incidence rate
of 13.1 cases per 1000 workers). The
majority of asthma cases were identified
through physician visits (20.8%) or a
combination of prescriptions with a
physician visit (55.2%). Only 302 cases
(0.7%) were captured by a workers’
compensation claim.
Rates of active asthma for the years 1999
to 2003 (Table 1) ranged from 22.3 to
26.2 cases per 1000 male workers, and
from 33.7 to 40.6 cases per 1000 female
workers. A small annual increase was
observed from 1999 through to 2003. Ageadjusted active asthma rates by industry
are shown for the year 2003 only, as
results for 1999 to 2002 were similar
(Table 2). For males, the active asthma
rate was significantly higher than the
overall rate in the working population for
workers employed in Wood and Paper
Manufacturing (including Sawmills),
Health Care and Social Assistance, and
Schools industries. Higher rates (although
95% confidence interval [CI] included the
rate for the working population) were also
observed for male workers in the Utilities;
Transport and Warehousing; Educational
Services; Mining, Oil and Gas; Finance
and Insurance; and Public Administration
industries. For females, the active asthma
rate was significantly higher in the Waste
Management and Remediation and Health
Care and Social Assistance (including
general hospitals and nursing care facilities) industries. Higher rates (95% CI
overlapped with the overall rate in the
working population) were also observed
for the female workers in the Public
Administration, Information and Cultural,
and Educational Services industries.
During follow-up, rates of active asthma
for ‘‘at-risk’’ industries among males
ranged from 25.2 to 28.6 cases per 1000
workers and were higher than those
observed for ‘‘low-risk’’ industries. Rates
for ‘‘at-risk’’ industries among females
ranged from 35.2 to 41.6 cases per 1000
workers. While rates tended to be slightly
higher for at-risk industries compared
to low-risk industries for females, the
differences were not as consistent or as
high as that observed for males.
Discussion
The purpose of this study was to investigate the feasibility of using linked health
data for population-based surveillance of
asthma among workers and to investigate
at-risk industry groups for on-going
monitoring and future prevention efforts.
To do this we estimated the active asthma
rate among a population-based workforce
sample by industry of employment and
among at-risk industry groups with known
or suspected allergen exposures.
The use of an active asthma measure for
the surveillance of work-related disease
does not enable comparisons with many
other studies using more traditional
measures of asthma incidence and prevalence for population-based estimates.
Nevertheless, our overall annual rate of
active asthma of approximately 30 cases
per 1000 workers is consistent with an
TABLE 1
Active asthmaa rates per 1000 workers, British Columbia, Canada, 1999–2003
1999
Rate (95% CI)
Males
2000
Rate (95% CI)
2001
Rate (95% CI)
2002
Rate (95% CI)
2003
Rate (95% CI)
22.3 (21.8–22.7)
23.7 (23.2–24.1)
25.0 (24.5–25.5)
25.5 (25.0–25.9)
26.2 (25.7–26.7)
High risk industries
25.2 (24.1–26.3)
27.1 (25.9–28.2)
27.8 (26.7–29.0)
28.5 (27.3–29.6)
28.6 (27.4–29.8)
Low risk industries
21.5 (20.9–22.0)
22.8 (22.3–23.3)
24.3 (23.8–24.9)
24.8 (24.2–25.3)
25.6 (25.0–26.2)
Females
33.7 (33.0–34.4)
36.1 (35.4–36.8)
37.4 (36.7–38.1)
38.2 (37.5–38.9)
40.6 (39.9–41.3)
High risk industries
35.2 (33.7–36.6)
36.0 (34.5–37.5)
38.0 (36.5–39.4)
38.2 (36.8–39.7)
41.6 (40.1–43.0)
Low risk industries
33.3 (32.5–34.1)
36.1 (35.3–36.9)
37.3 (36.5–38.1)
38.2 (37.4–39.0)
40.2 (39.4–41.0)
Abbreviations: CI, confidence interval.
a
Active asthma is defined by a physician visit, hospitalization, workers’ compensation claim or prescription for asthma. It includes incident cases and prevalent cases who had at least one of
these health care contacts in the year of follow-up.
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TABLE 2
Age-adjusted activea asthma rates per 1000 workers, British Columbia, Canada, 2003
Industry, Subsectorb
Industry, Subsectorb
Males
Rate (95% CI)
Females
Rate (95% CI)
Overall
26.5 (26.0, 27.0)
Overall
Utilities
31.9 (26.3–37.6)
Waste Management, Remediation
47.3 (40.8–53.8)
Transport and Warehousing
30.2 (26.0–34.4)
Health Care and Social Assistance
45.6 (43.7–47.4)
Wood and Paper Manufacturing
30.2 (28.7–31.7)
Nursing Care Facilities
47.0 (40.8–53.3)
30.8 (28.5–33.2)
General Hospitals
42.9 (40.9–45.0)
Sawmills
Health Care and Social Assistance
29.8 (26.8–32.8)
General Hospitals
27.8 (24.0–31.7)
Educational Services
28.1 (26.0–30.1)
40.6 (39.9–41.3)
Specialty Hospitals
41.6 (36.8–46.4)
Public Administration
42.7 (40.3–45.0)
Municipal Public Administration
43.2 (38.2–48.1)
Schools
29.6 (27.0–32.3)
Information and Cultural Industries
41.6 (37.9–45.2)
Universities
26.2 (21.8–30.5)
Educational Services
41.5 (39.5–43.5)
Mining, Oil and Gas
27.9 (22.8–33.0)
Colleges
44.5 (38.5–50.5)
Finance and Insurance
27.3 (24.6–30.0)
Universities
41.7 (36.6–46.8)
Public Administration
26.9 (25.2–28.7)
Schools
41.5 (39.1–43.8)
Municipal Public Administration
Information and Cultural Industries
Telecommunications
26.7 (24.0–29.5)
Mining, Oil and Gas
40.6 (23.1–58.1)
26.2 (23.9–28.6)
Utilities
40.2 (28.9–51.6)
39.3 (35.5–43.1)
26.0 (23.9–28.6)
Professional/Scientific/Technical Services
Transportation
26.0 (24.1–28.0)
Finance and Insurance
38.0 (35.7–40.2)
Real Estate
26.0 (21.0–31.1)
Arts, Entertainment, Recreation Services
37.7 (30.8–44.7)
Waste Management, Remediation
25.9 (21.6–30.3)
Retail Trade (General)
37.1 (32.0–42.2)
Accommodation and Food Services
25.3 (22.0–28.6)
Accommodation and Food Services
36.7 (33.0–40.3)
Wholesale
24.7 (22.8–26.6)
Wholesale
36.5 (32.5–40.5)
Retail (Foods and Goods)
24.5 (22.7–26.3)
Retail (Foods and Goods)
36.4 (33.6–39.2)
Metals, Machinery
24.5 (22.5–26.4)
Real Estate
34.7 (27.6–41.9)
Food and Textiles Manufacturing
23.9 (20.7–27.1)
Wood and Paper Manufacturing
33.8 (29.7–37.8)
Professional/Scientific/Technical Services
23.7 (21.5–26.0)
Warehousing
33.8 (27.1–40.4)
27.8 (22.7–32.8)
Transportation
33.6 (29.8–37.4)
Arts/Entertainment/Recreation Services
23.1 (18.4–27.8)
Construction
32.6 (24.4–40.7)
Agriculture, Forestry
22.8 (19.4–26.1)
Metals, Machinery
30.9 (26.1–35.7)
30.7 (25.7–35.8)
Computer Systems Design
Construction
22.6 (20.4–24.9)
Food and Textiles Manufacturing
Retail (General)
21.7 (17.2–26.2)
Management
30.5 (16.9–44.1)
Management
20.7 (10.8–30.7)
Agriculture, Forestry
25.1 (16.4–33.8)
Abbreviation: CI, confidence interval.
Note: grey shading, rate is higher than overall rate in working population; bold, 95% CI does not include the overall rate.
a
Active asthma is defined by a physician visit, hospitalization, workers’ compensation claim or prescription for asthma. It includes incident cases and prevalent cases who had at least one of
these health care contacts for asthma in 2003.
b
North American Industry Classification System (NAICS) Coding15 with subsectors where sample size allows.
overall rate of 3% (or 30 cases per 1000)
for active asthma (as defined by an
asthma attack in the past year) observed
in the European Community Respiratory
Health Survey (ECRHS).20 Our study
definition of active asthma includes incident as well as prevalent cases requiring
health care, and we expected our estimates to fall within the range of previous
incidence and prevalence studies. An
asthma incidence rate of 3% (or 30 cases
per 1000 workers) among high-risk or
exposed occupations in the ECRHS II
study 21 falls within the range we observed
in our study among high-risk groups of
male and female workers. Estimates of the
prevalence of work-related asthma using
administrative data from a sample of the
labour force in the Canadian province of
Manitoba found rates as high as 48 cases
per 1000 workers among some occupational groups,12 close to our highest
$
91
estimate observed among women in
high-risk groups. Observed differences
with previous studies may be attributed
to different case ascertainment definitions,
trying to compare with an annual active
asthma rate, and the use of industry
versus occupation to assign exposure risk.
Finally, a study of new-onset adult asthma
among a working sample in the province
of Alberta found an incidence rate of 1.6%
(or 16 cases per 1000)13 over a 10-year
Vol 33, No 2, March 2013 – Chronic Diseases and Injuries in Canada
follow-up period. Although higher than
our estimate of cumulative incidence at
13 cases per 1000 workers, this may be
explained by differences in the definition
for case ascertainment (one physician
visit for asthma in the Alberta study).
Collectively, our surveillance system produced estimates that were within the
range of other studies despite differences
in methods, case definitions and workforce characteristics.
The higher rate of asthma among female
workers compared to male workers is
consistent with surveillance results from
the neighbouring province of Alberta,13 as
well as self-reported estimates from
national health surveys22 and those from
other jurisdictions.5 The Alberta study
relied on health records similar to our
methodology for case ascertainment
among a worker population and found
twice the incidence rate of adult asthma
among females compared to males,13
consistent with our findings. Again, higher
rates in the current study may be due to
our case definition of active asthma in the
follow-up year, but females having almost
twice the rate of males overall was
consistent with our findings. Possible
occupational explanations for the gender
difference in a working population include
more females working in high-risk jobs
(i.e. teaching or health care)17 or in highrisk jobs with exposures that are not as
obvious or amenable to personal protective equipment, leading to more active
asthma symptoms and medical attention
(i.e. food services versus wood and paper
products23). It may also reflect a gender
difference associated with the ‘‘healthy
worker effect’’ whereby males have a
‘‘stronger healthy worker hire effect’’
while females have a ‘‘stronger healthy
worker survivor effect.’’24,25 With a strong
healthy worker hire effect, males with
childhood-onset asthma or existing adultonset asthma would be less likely to be
hired into high-risk jobs. With a stronger
healthy worker survivor effect, females
would be more likely to be in the workforce with asthma (although less likely to
remain at work over the longer term). It
may also be plausible that women are
more likely to work with asthma symptoms. Evidence suggests that socioeconomic factors may differentially impact
vulnerable groups such as females
with less job mobility, placing them at
increased risk for adverse effects of workplace exposures.24,26
Our study identified industries with higher
than average rates of active asthma.
Industries dealing with wood/wood dust
as well as individuals working in schools
and health services were at an increased
risk of asthma compared with those working in other industries. This is in keeping
with known or suspected exposures
related to dusts, moulds/endotoxins, and
latex/glutaraldehyde or industrial cleaning agents.2 It is also consistent with
surveillance studies investigating high-risk
groups by occupation, including the
Manitoba and Alberta studies that identified a higher risk among workers in
teaching and related occupations.12,13
The previous studies were able to identify
other high-risk groups likely due to
differences in type of employment by
province (i.e. forestry is a major industry
in British Columbia) but also due to a finer
level of detail for exposures by occupation. For example, the Alberta study was
able to identify a higher risk among
workers in industries dealing with flour/
food, fibreglass and vehicles. Similarly,
the Manitoba study identified higher risks
among fabricating, installing and repairing
occupations of electrical, electronic and
related equipment.
Conversely, some industrial groups such
as Metals/Machinery or Manufacturing
(Food and Textiles) did not appear at an
increased risk relative to other industries.
The reliance on industry of employment
as a surrogate measure of exposure for
at-risk jobs in this surveillance project
may be subject to more misclassification
for these types of industries. Industrial
groups such as Manufacturing may be
made up of multiple and diverse occupational groups. Some have known or
suspected exposures such as textiles,
wood dust or metal working fluids, but
others do not (i.e. beverage manufacturing), resulting in a conservative bias
on the estimates. Industries such as
Educational Services or Health Services,
on the other hand, may be dominated by
several large occupational groups such
as teachers or nurses/cleaners all with
Vol 33, No 2, March 2013 – Chronic Diseases and Injuries in Canada
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92
known or suspected allergens (e.g. mould
or chemical irritants), resulting in better
estimates of exposure using this method of
at-risk industries of employment. Overall,
the misclassification of exposure using
industry of employment exerts a conservative bias attenuating the risk estimates.
Ultimately, it would be ideal to improve
this surveillance method with more
detailed occupation information at the
population level. This is currently not
captured by any of the administrative
datasets with the exception of the
workers’ compensation claim records.
Including occupation of employment in
medical registries or health records/databases would be an invaluable source of
data for surveillance studies, as concluded
by others involved in similar work.27
Novel approaches to obtaining occupation
and industry of employment data from
administrative databases for populationbased health surveillance are also warranted, as was done by Cherry et al. in
Alberta.13
While Ministry of Health employer coding
is assumed to be valid for billing purposes,
there may still be limitations in terms of
assigning exposure based on the industry
of employment codes. Not all individuals
within an industry are working in an
occupation with exposures, and we were
not able to investigate high-risk occupational groups. We relied on an exposure
matrix to investigate at-risk industrial
groups; some misclassification with bias
towards the null is unavoidable using this
approach and may explain why we did not
observe greater differences between the
high- and low-risk groups. It is also
possible that the misclassification is
greater for women than men using industry coding for exposure as women may
work in more diverse occupations in highrisk industries such as construction.28 This
would explain the smaller observed differences in asthma rates between high- and
low-exposed industrial groups for women.
There is also some uncertainty about
whether the industry of employment at
the time of case ascertainment is the
industry of exposure. Current symptoms
may be as a result of past exposures (i.e.
employment in an industry other than
the current one). Our population-based
surveillance approach overcomes some of
the biases associated with the healthy
worker effect in previous occupational
cohort studies and provides information
about asthma in the working population
by following workers forward even after
they leave the workforce (or if they change
industries). Further, as we have emphasized, women as well as self-employed
workers or those who work for small
employers are underrepresented using the
employer-paid health premium codes in
the provincial medical registry.
The years of follow-up were limited based
on the availability of the industry coding.
Workplace processes (and exposures)
have not changed so dramatically over
the past decade as to render these findings
irrelevant for workers in the same industries today (i.e. forestry workers are still
exposed to wood dust, teachers to moulds
or endotoxins, cleaners to industrial cleaning agents, and metal workers to metal
working fluids), and the job exposure
matrix used in this study is based on
known risk factors for asthma still present
in industries. The retrospective data available for this study represent the only
known source of employment codes for a
large proportion of the working population, linked to multiple health databases.
An advantage of using population-based
administrative data is that the larger
number of individuals involved allows
for robust analysis of age, sex and other
demographic trends, compared to data
limited by sample size. Another advantage
is that the ability to link multiple health
databases improves case ascertainment
for occupational outcomes.29
We are not suggesting that all of the cases
of asthma among workers in our study are
work-related, but it appears that workers’
compensation claims data underestimate
asthma in the population, necessitating
the use of additional data sources to
capture asthma among workers and identify work groups with higher rates. Less
than 1% of our cases were captured by
the workers’ compensation system as
an accepted claim7 despite a recognized
population-attributable risk estimate of
asthma associated with occupational
exposures of 15%,4 including Canadian
estimates.30,31 Given the face validity
associated with higher rates among industries with known allergens, the current
study offers a surveillance tool for ongoing monitoring among at-risk groups, as
well as evidence of the need for additional
education on the association between
workplace exposures and asthma morbidity. The study also offers a tool for
identifying new or emerging at-risk groups
for further investigation, such as the
workers in the waste management industry and the public sector, as we observed.
4.
Balmes J, Becklake M, Blanc P,
Henneberger P, Kreiss K, Mapp C, et al.
American Thoracic Society statement on
occupational contribution to the burden of
airway disease. Am J Respir Crit Care Med.
2003;167(5):787–97.
5.
Karjalainen A, Kurppa K, Martikainen R,
Klaukka T, Karjalainen J. Work is related to
a substantial portion of adult-onset asthma
incidence in the Finnish population. Am J
Respir Crit Care Med. 2001;164(4):565–8.
6.
Arif AA, Whitehead LW, Delclos GL,
Tortolero SR, Lee ES. Prevalence and risk
factors of work related asthma by industry
among United States workers: data from
the third national health and nutrition
examination survey (1988–94). Occ Env
Med. 2002;59(8):505–11.
7.
McLeod CB, Bogyo T, Demers P, Edeer D,
Hertzman C, Kennedy S, et al. Asthma in
British Columbia [Internet]. Vancouver
(BC): Centre for Health Services and
Policy Research, University of British
Columbia; 2007 Jan [cited 2011 Jul 19].
Available
from:
http://pwhr.sites.olt.ubc.ca/files/2012/03
/Asthma-Report-2007.pdf
8.
Kraut A. Estimates of the extent of morbidity and mortality due to occupational
diseases in Canada. Am J Ind Med.
1994;25(2):267–78.
9.
National Institute for Occupational Health
and Safety (NIOSH). Tracking occupational
injuries, illnesses, and hazards: the NIOSH
surveillance strategic plan. Cincinnati
(OH): National Institute for Occupational
Health and Safety; 2001. Report No.: DHHS
(NIOSH) Publication Number 2001–118.
Acknowledgments
This research was supported in part by
operating funds provided by AllerGen NCE
Inc (The Allergy, Genes and Environment
Network, Networks of Centres of
Excellence of Canada) and WorkSafeBC
(the Workers Compensation Board of
British Columbia). M. Koehoorn was
supported in part by a Michael Smith
Foundation for Health Research Senior
Scholar Award. The authors wish to thank
Population Data BC as a resource for
access to linked, administrative health
data for research purposes. The British
Columbia Ministry of Health, WorkSafeBC
and PharmaNet approved access to and
use of the data facilitated by Population
Data BC for this study.
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Unintentional injury mortality and external causes in Canada
from 2001 to 2007
Y. Chen, PhD (1); F. Mo, PhD (2); Q. L. Yi, PhD (1); Y. Jiang, MSc (2); Y. Mao, PhD (2)
This article has been peer reviewed.
Abstract
Introduction: To understand the distribution pattern and time trend of unintentional
injury mortalities is crucial in order to develop prevention strategies.
Methods: We analyzed vital statistics data from Canada (excluding Quebec) for 2001 to
2007. Mortality rates were age- and sex-standardized to the 2001 Canadian population.
An autoregressive model was used for time-series analysis.
Results: Overall mortality rate steadily decreased but unintentional injury mortality rate
was stable over the study period. The three territories had the highest mortality rates.
Unintentional injury deaths were less common in children than in youths/adults. After
60, the mortality rate increased steadily with age. Males were more likely to die of
unintentional injury, and the male/female ratio peaked in the 25- to 29-year age group.
Motor vehicle crashes, falls and poisoning were the three major causes. There was a
substantial year after year increase in mortality due to falls. Deaths due to motor vehicle
crashes and drowning were more common in summer months, and deaths caused by
falls and burns were more common in winter months.
Conclusion: The share of unintentional injury among all-cause mortality and the
mortality from falls increased in Canada during the period 2001 to 2007.
Keywords: age standardization, burn, Canada, consumer product, drowning, fall,
mortality, poisoning, unintentional injury, suffocation, vehicle traffic crash, vital statistics
Introduction
Injuries are among the leading causes of
death and disabilities worldwide.1 They
represent about 16% of the global burden
of disease2 and are the leading cause of
death in people aged under 60 years.3 In
2004, World Health Organization estimated that injuries caused over 5 million
deaths per year, of which 3.9 million were
unintentional.4 Compared to many other
diseases, injuries affect more young
people, and therefore result in more years
of life lost.1 In Canada, the total economic
burden of injury was about $20 billion in
2004, of which $16 billion was as a result
of unintentional injuries.5
Unintentional injury is any injury that is
not caused on purpose or with intention to
harm. Since not all unintentional injuries
are random events and some of them can
be prevented, it is not usually appropriate
to use the word ‘‘accident’’ to define
unintentional injury. Unintentional injury
can be further classified according to
external causes such as motor vehicle
collisions, falls, poisoning, drowning, suffocations and so on.6 Unintentional injuries may be work-related or sports-related.
Different types of unintentional injury
may have unique patterns in different
subpopulations, for example, motor vehicle crashes are most common among
young people7 while falls are more likely
to cause a fatal outcome among the
elderly.8 Monitoring the changing patterns
of overall and cause-specific unintentional
injury mortalities gathers information
essential to developing new programs on
unintentional injury prevention and intervention and modifying existing ones. In
this study, we conducted a descriptive
analysis of vital statistics data to investigate the distribution patterns and time
trends of overall and cause-specific unintentional injury mortalities in Canada
(excluding Quebec).
Methods
The study was based on mortality data
from the Canadian Vital Statistics Death
Database (excluding deaths registered in
the province of Quebec, since these were
not available on the Data Extraction and
Analysis System, Public Health Agency of
Canada) for the period from January 1,
2001, to December 31, 2007. Death statistics are based on information abstracted
and compiled from death certificates, and
are provided to Statistics Canada by the
vital statistics registrars in each province
or territory. The mortality data in this
analysis are coded using the International
Classification of Diseases, 10th Revision
(ICD-10), in which external causes are
classified under a series of alphanumeric
codes, V01–Y98. These codes were used to
identify unintentional injury deaths (ICD10: V01–X59, Y85–Y86) and unintentional
Author references:
1. Department of Epidemiology and Community Medicine, University of Ottawa, Ottawa, Ontario, Canada
2. Consumer Product Safety and Injury Risk Assessment Program Working Group, Science Integration Division, Centre for Chronic Disease Prevention and Control, Public Health Agency of
Canada Ottawa, Ontario, Canada
Correspondence: Yue Chen, Department of Epidemiology and Community Medicine, Faculty of Medicine, University of Ottawa, 451 Smyth Road, Ottawa, ON K1H 8M5;
Tel.: 613 562-5800 ext. 8287; Fax: 613 562-5465; Email: ychen@uottawa.ca
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Vol 33, No 2, March 2013 – Chronic Diseases and Injuries in Canada
injury deaths by cause including motor
vehicle traffic crashes (V02–V04 [.9],
V09.2, V12–V14 [.3–.9], V19 [.4–.6], V20–
V28 [.3–.9], V29 [.4–.9], V30–V79 [.4–.9],
V80 [.3–.5], V81–V82 [.1], V83–V86 [.0–.3],
V87 [.0–.8], V89.2); pedal cycle (ICD-10:
V10–V14, V16–V19); pedestrian (trafficrelated) (ICD-10: V02–V04 [.1], V09.2,
V09.3); recreation boating (ICD-10: V90.2–
V90.8, V91.2–V91.8, V92.2–V92.8, V93.2–
V93.8, V94.2–V94.8); drowning (ICD-10:
V90, V92, W65–W74); falls (ICD-10: W00–
W19); burns or fire (ICD-10: W85–W91,
X00–X19); suffocations (ICD-10: W75–
W84); poisoning (ICD-10: X40–X49) and
other unintentional causes.
We took annual population estimates from
Statistics Canada’s annual demographic
statistics.9,10 Age- and sex-standardized
mortality rates were calculated using the
direct method with reference to the 2001
Canadian population. For each province
and for the three territories (Northwest
Territory, Yukon and Nunavut) combined,
average overall mortality rates were calculated for the 7-year study period, that is,
the total number of deaths during the
period divided by the sum of the annual
populations, which is equivalent to a
weighted average of annual rates using
the annual population as a weight.
To explore time trends for unintentional
injury mortality rates from 2001 to 2007
and seasonal pattern for cause-specific
unintentional injury mortalities in males
and females, we conducted time-series
analysis. The mortality rates were calculated by using average annual population
as the denominator since there were no
monthly population estimates. Because
the numbers of death per month were
small and could not be further stratified by
age, we conducted age and sex-standardization by using the ratios of annual
standardized versus crude rates (crude
monthly rate 6 standardized/crude mortality for the year). The adjusted monthly
rates were then plotted to visually display
their time trends and seasonal patterns.
Autoregressive models were fitted to
determine the associations of secular year
and month with various unintentional
injury mortalities. In the models, the first
order autocorrelation was considered,
with monthly rates being dependent vari-
ables and year and month indicators being
independent variables.
Results
tional injury mortality versus all mortality
increased significantly (p = .003) in the 7year period. Males accounted for 61.1% of
all unintentional injury deaths. However,
males and females had similar time trends
for unintentional injury mortality, overall
mortality (all causes combined) and their
ratio (Table 1).
There were a total of 51 178 deaths due to
unintentional injuries, which accounted
for 4.2% of all deaths in Canada excluding
Quebec during the study period from 2001
to 2007. The age- and sex-standardized
mortality for all causes steadily decreased
from 702 per 100 000 in 2001 to 631 per
100 000 in 2007 (p < .001) while the
mortality due to unintentional injuries was
relatively stable year after year (p = .571).
As a result, the proportion of uninten-
After age- and sex-standardization, the
three territories combined had the highest
overall mortality (842.3 per 100 000) and
unintentional injury mortality (69.1 per
100 000) (Table 2). British Columbia had
the lowest overall mortality (626.8 per
100 000) while Newfoundland and
Labrador had the lowest mortality due to
unintentional injuries (24.8 per 100 000).
The unintentional injury mortality for the
three territories was almost triple that of
All analyses were conducted using SAS
version 9.1 statistical software (SAS
Institute Inc., Cary, NC, US).
TABLE 1
Crude and standardized mortality by calendar year, total and by sex, Canada (excluding
Quebec), 2001–2007
Calendar
year
a
Crude mortality
Standardized mortality
All causes,
per 100 000
Unintentional
injury,
per 100 000
All causes,
per 100 000
Unintentional
injury,
per 100 000
Unintentional
injury/All
causes, %
2001
701.8
28.7
702.1
28.7
4.09
2002
704.3
29.9
692.3
29.6
4.28
2003
710.3
29.5
685.3
28.8
4.20
2004
702.2
28.7
664.6
27.7
4.27
2005
708.5
30.1
656.8
28.6
4.35
2006
699.2
30.5
633.6
28.5
4.50
2007
709.7
32.0
631.0
29.7
4.71
2001
725.0
36.4
879.5
39.9
4.54
2002
720.3
37.1
857.7
40.6
4.73
2003
729.5
36.2
851.2
39.3
4.62
2004
718.7
35.2
824.1
37.8
4.59
2005
722.6
37.3
811.2
39.6
4.88
2006
715.1
36.8
783.2
38.5
4.92
2007
725.9
39.0
778.3
40.4
5.19
2001
679.1
21.2
572.7
18.5
3.23
2002
688.5
22.8
571.3
19.7
3.45
2003
691.4
22.9
564.3
19.3
3.42
2004
686.0
22.4
547.8
18.4
3.36
2005
694.5
23.0
650.3
18.9
2.91
2006
683.5
24.3
626.4
19.4
3.10
2007
693.8
25.0
624.7
20.0
3.20
Total
Male
Female
a
Standardized according to the entire 2001 Canadian population.
Vol 33, No 2, March 2013 – Chronic Diseases and Injuries in Canada
$
96
Newfoundland and Labrador. Ontario also
had a low unintentional injury mortality
(26.3 per 100 000), which was similar to
Newfoundland and Labrador, but all-cause
mortality was very different in the two
provinces, 655.9 per 100 000 in Ontario
versus 802.9 per 100 000 in Newfoundland
and Labrador. The differences between the
other provinces were relatively small for
both all-cause mortality and unintentional
injury mortality (Table 2). Table 2 also
shows that the unintentional injury mortality and the ratio of unintentional injury
versus all-cause mortalities were higher in
males than in females across all provinces/
territories.
Unintentional injury deaths were less
common among children (< 7 per
100 000) than among youths and adults
(Table 3). Unintentional injury mortality
was generally similar for those aged 15 to
59 years (28.5–37.7 per 100 000 in males
and 8.5–12.7 per 100 000 in females). After
age 60 years, mortality increased steadily
with age from 35.3 per 100 000 in the 60- to
64-year age group to 801.0 per 100 000 in
the 90-year-plus age group in men and
from 14.4 to 663.1 per 100 000 in women.
In all the age groups, males were more
likely to die of unintentional injuries
(Table 3). The male to female mortality
ratio increased with age after 5 to 9 years
(1.34), peaked at 25 to 29 years (3.76) and
then steadily decreased with age. Table 3
also shows that of unintentional injury
deaths from identified causes, motor vehicle traffic crashes were most common in
males, with a mortality rate of 10.2 per
100 000, followed by falls (7.7 per 100 000)
and poisoning (5.1 per 100 000). In
females, the first three identified causes
for unintentional injury death were falls,
motor vehicle traffic crashes and poisoning
with the mortality rates being 7.9, 4.5 and
2.2 per 100 000, respectively. Cause-specific unintentional injury mortalities were all
higher in males than in females except for
fall mortality (Table 3). Overall, falls
accounted for 26% of all unintentional
injury deaths, motor vehicle traffic crashes
for 24% and poisoning for 12% (Figure 1).
Although unintentional injury mortality
increased sharply after 60 years of age, it
comprised a much higher proportion of
all deaths in younger age groups
TABLE 2
Average mortality by province/territory, Canada (excluding Quebec), total and by sex,
2001–2007
Province
a
Crude mortality
Standardized mortality
All causes,
per 100 000
Unintentional
injury,
per 100 000
All causes,
per 100 000
Unintentional
injury,
per 100 000
Unintentional
injury/All
causes, %
715.7
32.1
626.8
30.1
4.80
Total
British Columbia
Alberta
582.4
27.8
660.7
28.7
4.34
Saskatchewan
896.0
42.5
693.8
37.5
5.41
Manitoba
843.7
38.1
720.3
34.7
4.82
Ontario
680.7
27.0
655.9
26.3
4.01
New Brunswick
831.2
38.3
713.2
35.3
4.95
Nova Scotia
871.2
35.6
733.9
31.8
4.33
Prince Edward
Island
837.9
35.5
703.7
32.4
4.60
Newfoundland
and Labrador
841.0
25.2
802.9
24.8
3.09
396.5
52.3
842.3
69.1
8.20
British Columbia
741.7
42.0
769.8
42.5
5.52
Alberta
603.3
37.3
822.0
41.0
4.99
Saskatchewan
926.4
53.3
881.0
52.8
5.99
Manitoba
850.1
44.9
903.0
46.6
5.16
Ontario
691.7
31.5
808.1
35.0
4.33
New Brunswick
856.7
49.8
906.6
50.9
5.61
Nova Scotia
892.3
43.1
921.3
44.3
4.81
Prince Edward
Island
852.6
43.4
895.2
45.3
5.06
Newfoundland
and Labrador
905.2
32.9
1022.9
34.7
3.39
486.9
74.8
1023.9
92.1
9.00
British Columbia
690.0
22.3
520.0
18.6
3.58
Alberta
561.0
18.1
543.9
17.6
3.24
Saskatchewan
866.1
31.9
557.7
23.5
4.21
Manitoba
837.5
31.4
587.7
24.4
4.15
Territories
b
Male
Territories
b
Female
Ontario
670.1
22.7
544.7
18.7
3.43
New Brunswick
806.5
27.2
572.9
21.4
3.74
Nova Scotia
851.2
28.4
596.4
20.7
3.47
Prince Edward
Island
823.9
28.0
566.9
20.1
3.55
Newfoundland
and Labrador
778.6
17.8
647.5
15.3
2.36
300.5
28.5
695.6
45.2
6.50
Territories
b
a
Standardized according to the entire 2001 Canadian population.
b
Yukon, Northwest Territory, Nunavut.
(Table 4), peaking at age 15 to 19 years
(45.2%) for both males (46.7%) and
females (41.8%), then gradually decreasing (Table 4).
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97
We investigated major external causes for
unintentional injury mortality separately,
including motor vehicle traffic crashes,
falls, poisoning, pedestrian (traffic-
Vol 33, No 2, March 2013 – Chronic Diseases and Injuries in Canada
TABLE 3
Mortality and male to female ratio for
mortality due to unintentional injury by age
and external causes, Canada (excluding
Quebec), 2001–2007
Mortality,
per 100 000
Male
FIGURE 1
Proportion of unintentional injury deaths by cause in Canada excluding Quebec, 2001–2007
Ratio
Male:Female
Others
24%
Female
Age group,
years
0–4
7.5
5.3
Motor vehicle
24%
Pedestrian
3%
1.42
5–9
4.3
3.2
1.34
10–14
6.2
3.5
1.77
15–19
29.0
12.0
2.42
20–24
37.7
12.1
3.12
25–29
32.0
8.5
3.76
30–34
28.5
8.6
3.31
35–39
30.4
9.8
3.10
40–44
33.1
10.6
3.12
45–49
34.8
11.9
2.92
50–54
33.3
11.5
2.90
55–59
33.3
12.7
2.62
60–64
35.3
14.4
2.45
65–69
42.8
21.0
2.04
70–74
56.9
32.3
1.76
75–79
98.0
61.4
1.60
80–84
187.2
122.5
1.53
85–89
362.9
271.4
1.33
§90
801.0
663.1
1.21
Motor vehicle
crashes
10.2
4.5
2.3
Pedestrian
(traffic-related)
1.3
0.8
1.6
Pedal cycle
0.4
0.1
5.4
Recreation
boating
0.2
0.0
10.4
Drowning
1.5
0.4
4.3
Falls
7.7
7.9
1.0
Burns
1.1
0.6
1.9
Suffocation
1.6
1.1
1.4
Poisoning
5.1
2.2
2.3
Others
7.9
5.6
1.4
External
causes
related), drowning, burns, and suffocation
in males (Table 5; Figure 2) and in
females (Table 6; Figure 3). There was a
substantial year after year increase in
mortality as a result of injuries due to
falls in both males (p < .01) and females
(p < .01). For other type of injuries, agestandardized mortalities either decreased
Poisoning
12%
Suffocation
5% Burns
Drowning
3%
Falls
26%
3%
slightly (burns and drowning in males,
motor vehicle crashes and burns in
females) or showed no significant
changes. The risk of death caused by
motor vehicle traffic crashes and drowning was significantly higher in summer
months and was more marked in males
than females. Deaths caused by falls and
burns were more common in winter
months. More poisoning deaths could be
seen in March and April (p < .05) and
pedestrian accident deaths in September
and October (p < .05) and November and
December (p < .01) when compared with
January and February. There was no
significant difference between the month
periods for suffocation.
Discussion
Our study demonstrated that age- and sexstandardized mortality from all unintentional injuries was stable during the 7-year
study period whereas overall mortality
declined approximately 10% and the
proportion of unintentional injury versus
overall mortalities increased from 4.1% to
4.7%. This indicated that the share of
unintentional injury in all causes for
mortality is on the increase in Canada.
All unintentional injury mortality in
males, as well as cause-specific injury
mortalities but with the exception of fall
mortality, exceeded those in females.
The three territories had the highest overall mortality and unintentional injury
Vol 33, No 2, March 2013 – Chronic Diseases and Injuries in Canada
$
98
mortality. The unintentional injury versus
overall mortality ratio was almost double
in the three territories compared with the
nine provinces. A previous populationbased case-control study conducted in the
Northwest Territories demonstrated that
being male, aged over 14 years, living in
remote communities, living in the far
north, and being Aboriginal were risk
factors for injury mortality.11 There is a
higher proportion of Aboriginal people in
the territories compared with the rest of
Canada. A study conducted among
Albertan children showed that Aboriginal
children had a significantly higher risk for
both intentional and unintentional injury
deaths.12 Injury mortality rates among
Indigenous people in the United States
and Australia are approximately 2 to 3
times greater than rates for non-Aboriginal
populations.13
Motor vehicle traffic crashes and falls
were two major causes for unintentional
injury deaths in Canada. The former was a
more common cause in males than
females and was a main reason for the
markedly increased mortality from unintentional injuries in youths and young
adults. The mortality due to motor vehicle
traffic crashes changed little year after
year during the study period in males and
declined slightly in females. However, the
data showed a clear seasonal pattern with
a significantly increased risk in summer
and more so in males than in females.
During the traditional summer vacation
TABLE 4
Overall and unintentional injury mortality (per 100 000) by age and sex, Canada (excluding Quebec), 2001–2007
Age
group,
years
Total
All
causes,
per
100 000
Unintentional
injury, per
100 000
Male
Unintentional
injury/All
causes, %
All
causes,
per
100 000
Unintentional
injury, per
100 000
Female
Unintentional
injury/All
causes, %
All, per
100 000
Unintentional
injury, per
100 000
Unintentional
injury/All
causes, %
0–4
124.4
6.43
5.2
135.4
7.5
5.5
112.9
5.3
4.7
5–9
11.7
3.73
31.9
13.0
4.3
33.1
10.3
3.2
30.8
10–14
14.3
4.89
34.2
16.2
6.2
38.3
12.3
3.5
28.2
15–19
45.9
20.78
45.2
62.1
29.0
46.7
28.8
12.0
41.8
20–24
60.0
25.19
42.0
85.8
37.7
43.9
33.1
12.1
36.6
25–29
58.5
20.35
34.8
82.6
32.0
38.7
34.0
8.5
25.0
30–34
69.6
18.60
26.7
92.1
28.5
30.9
46.8
8.6
18.4
35–39
95.9
20.12
21.0
122.1
30.4
24.9
69.4
9.8
14.1
40–44
140.6
21.91
15.6
174.9
33.1
18.9
106.0
10.6
10.0
45–49
221.8
23.35
10.5
272.9
34.8
12.8
170.8
11.9
7.0
50–54
349.8
22.34
6.4
431.0
33.3
7.7
269.7
11.5
4.3
55–59
545.1
22.92
4.2
674.1
33.3
4.9
417.8
12.7
3.0
60–64
881.9
24.67
2.8
1092.7
35.3
3.2
677.4
14.4
2.1
65–69
1406.4
31.51
2.2
1751.8
42.8
2.4
1082.9
21.0
1.9
70–74
2270.4
43.83
1.9
2850.2
56.9
2.0
1755.2
32.3
1.8
75–79
3711.0
77.39
2.1
4684.2
98.0
2.1
2953.0
61.4
2.1
80–84
6157.3
147.78
2.4
7759.1
187.2
2.4
5130.4
122.5
2.4
85–89
10708.7
302.40
2.8
13173.0
362.9
2.8
9445.9
271.4
2.9
§ 90
20590.7
700.09
3.4
23399.0
801.0
3.4
19562.0
663.1
3.4
injury mortality among youths and young
adults, especially for males.
months, people may drive longer distances while on vacation and teens and
young adults may have more opportunities to drive and ride in cars,1 and hence
are more likely to be exposed to vehicleand traffic-related risk factors. Effective
interventions on motor vehicle crashes are
most important for reducing unintentional
Mortality due to falls was the only causespecific mortality that showed a steady
increase during the study period, and it
was slightly more common in females
than males. Fall injury accounted for
about one-third of all unintentional injury
deaths in adults, and was the principal
reason for the dramatic increase in
mortality due to unintentional injury with
age in the elderly. Worldwide, motor
vehicle crashes account for 33% while
falls only account for 11% of unintentional injury death,1 but in this study they
TABLE 5
Results of time-series analysis (autoregressive model) for major types of unintentional injury mortality (per 100 000) in males
Regression coefficient (Standard error)
Variable
Secular year
Motor vehicle
Falls
–0.0080 (0.0072)
0.0342 (0.0039)
Poisoning
**
Drowning
Pedestrian
Burns
Suffocation
0.0090 (0.0062)
**
*
–0.0069 (0.0023)
0.0012 (0.0016)
–0.0729 (0.0325)*
–0.2976 (0.0170)**
0.0011 (0.0118)
0.0311 (0.0105)**
**
–0.0028 (0.0014)
–0.0023 (0.0021)
Month
1–2
–0.4768 (0.0490)**
–0.0742 (0.0280)**
3–4
**
–0.4310 (0.0490)
**
–0.0936 (0.0280)
0.0354 (0.0318)
–0.2743 (0.0169)
–0.0173 (0.0118)
0.0310 (0.0105)**
–0.0116 (0.0150)
5–6
–0.1822 (0.0484)**
–0.0701 (0.0287)*
–0.0053 (0.0281)
–0.1435 (0.0177)**
–0.0026 (0.0121)
0.0167 (0.0111)
–0.0227 (0.0154)
[Reference]
–0.0124 (0.0150)
7–8
[Reference]
[Reference]
[Reference]
[Reference]
[Reference]
[Reference]
9–10
–0.1600 (0.0484)**
–0.0521 (0.0287)
–0.0310 (0.0281)
–0.2383 (0.0177)**
0.0336 (0.0121)**
0.0138 (0.0111)
–0.0306 (0.0154)
11–12
–0.2846 (0.0490)**
0.0029 (0.0280)
–0.0243 (0.0317)
–0.2806 (0.0169)**
0.0281 (0.0118)*
0.0449 (0.0105)**
–0.0202 (0.0150)
* p < .05
** p < .01
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99
Vol 33, No 2, March 2013 – Chronic Diseases and Injuries in Canada
FIGURE 2
Monthly standardized mortality due to different types of unintentional injury in males, Canada (excluding Quebec), 2001–2007
1.6
Standardized mortality (1/100 000)
1.4
Vehicle
Pedestrian
Drowning
Burn
Suffocation
Poisoning
Fall
1.2
1.0
0.8
0.6
0.4
0.2
0.0
1 3 5 7 9 11 1 3 5 7 9 11 1 3 5 7 9 11 1 3 5 7 9 11 1 3 5 7 9 11 1 3 5 7 9 11 1 3 5 7 9 11
2001
2002
2003
2004
2005
falls in the Canadian population. Our study
also showed a seasonal pattern for fall
mortality, that is, it was the highest in
November and December. One study from
the United States found that fall injuries
were associated with holiday decorating or
related activities, which is also likely in our
current context.29 Weather is probably
another important reason.30,31
were 24% and 26%, respectively
(Figure 1). The aging process and low
levels of bone mineral density are closely
associated with the severity of an injury
and the consequence of the fall.8,14–19
However, we do not know if aging and
bone mineral density are the main reasons
for the steady increase in mortality in the
7-year study period. Other factors such as
medication use, especially in older people,20
overweight and obesity,21,22 engagement in
physical activity,23,24 utilization of medical
products and day-to-day activities25–28
warrant further investigation for possible
impact on the uptrend of mortality from
Poisoning was the third leading cause of
unintentional injury mortality in Canada,
and accounted for 14% of unintentional
injury deaths in males and 10% in females
(data not shown). Unintentional poisoning
2006
may be work-related, and other common
agents are household chemicals and pesticides, medications and plants.32–35 Other
causes of unintentional deaths such as
drowning and burns were less common.
Our data showed that deaths due to
drowning most frequently happened in
summer, and that males versus females
and children versus adults accounted for a
higher proportion of drowning-related
deaths. Most drowning accidents are
related to recreation or leisure. Our data
also showed an increased mortality due to
burns in winter but no seasonal variations
for suffocation.
TABLE 6
Results of time-series analysis (autoregressive model) for major types of unintentional injury mortality (per 100 000) in females
Regression coefficient (Standard error)
Variable
Secular year
Motor vehicle
Falls
*
Poisoning
**
Drowning
Pedestrian
20.0006 (0.0012)
Suffocation
**
0.0365 (0.0034)
0.0016 (0.0025)
20.0984 (0.0217)** 20.0277 (0.0230)
20.0005 (0.0157)
20.0360 (0.0049)**
20.0073 (0.0081)
0.0216 (0.0067)**
**
20.0069 (0.0033)
20.0001 (0.0007)
Burns
20.0026 (0.0009)
0.0028 (0.0011)*
Month
1–2
**
20.0079 (0.0080)
3–4
20.1435 (0.0217)
20.0158 (0.0230)
0.0297 (0.0156)
20.0317 (0.0049)
20.0094 (0.0081)
0.0097 (0.0067)
0.0011 (0.0080)
5–6
20.0859 (0.0211)** 20.0204 (0.0228)
0.0038 (0.0148)
20.0182 (0.0048)**
20.0155 (0.0079)
0.0040 (0.0070)
20.0074 (0.0082)
7–8
[Reference]
[Reference]
[Reference]
[Reference]
[Reference]
[Reference]
[Reference]
9–10
20.0516 (0.0211)*
0.0284 (0.0228)
20.0046 (0.0148)
20.0326 (0.0049)**
20.0063 (0.0079)
0.0022 (0.0069)
0.0007 (0.0082)
11–12
20.0422 (0.0217)
0.0388 (0.0230)
0.0094 (0.0156)
20.0357 (0.0049)**
0.0153 (0.0081)
0.0174 (0.0067)*
0.0029 (0.0080)
* p value < .05
** p value < .01
Vol 33, No 2, March 2013 – Chronic Diseases and Injuries in Canada
$
100
FIGURE 3
Monthly standardized mortality due to different types of unintentional injury in females in Canada (excluding Quebec), 2001–2007
0.9
Vehicle
Pedestrian
Drowning
Burn
Suffocation
Poisoning
Fall
Standardized mortality (1/100 000)
0.75
0.6
0.45
0.3
0.15
0
1 3 5 7 9 11 1 3 5 7 9 11 1 3 5 7 9 11 1 3 5 7 9 11 1 3 5 7 9 11 1 3 5 7 9 11 1 3 5 7 9 11
2001
2002
Limitations
Death registration is mandatory in Canada
and therefore there is minimal missing
vital statistics data. However, the underlying cause, defined as the disease or
injury that initiated the chain of events
leading directly to death, is considered.
Some people might not die instantly after
an injury, and subsequent conditions (e.g.
heart failure) might be coded as primary
cause of death. This method of death
registration relies on medical examiners or
coroners’ judgment; it may happen that an
injury is closely related to the death but is
not considered the underlying cause. Since
secondary diagnoses are excluded, it may
underestimate the true burden of unintentional injury mortality. Miscoding and
data entry errors may also result in
misclassification of information on cause
of deaths and external causes of injuries.
In addition, the study period of 7 years is
relatively short.
Conclusion
Overall unintentional injury mortality
changed little from year to year while
overall mortality showed a steady decline
2003
2004
2005
in Canada. The three territories had the
highest unintentional injury mortality,
both absolutely and as a share of overall
mortality. Motor vehicle traffic crashes
and falls were the leading causes of injury
death. Fall mortality was the only type of
unintentional injury mortality that showed
an annual increase. Death from fall injury
was more common in females than males
while other types of injury death were
stable and were more common in males
than in females. There were seasonal
patterns for some types of unintentional
injury mortalities such as higher risks of
death due to motor vehicle traffic crashes
and drowning in summer and falls and
burns/fire in winter. The increasing share
of overall unintentional injury mortality
versus all-cause mortality and the increasing trend for fall mortality call for more
research on risk factor identification and
effective interventions.
2006
2007
manager of the project; and Ms. Caroline
Da Silva, responsible for the management
and coordination of the project.
References
1.
Chandran A, Hyder AA, Peek-Asa C. The
global burden of unintentional injuries and
an agenda for progress. Epidemiol Rev.
2010;32:110–20.
2.
Krug EG, Sharma GK, Lozano R. The global
burden of injuries. Am J Public Health.
2000;90:523–6.
3.
Peden MM, McGee K, Krug E, editors.
Injury: a leading cause of the global burden
of disease, 2000. Geneva (CH): World
Health Organization; 2002.
4.
Violence, injuries and disability biennial
report, 2006–2007. Geneva (CH): World
Health Organization; 2008.
Acknowledgments
5.
We would like to thank the following for
their role in the ‘‘Consumer product- related
injury and risk assessment’’ project: Dr.
Howard Morrison, senior supervisor and
director of the project; Mr. Doug Hopkins,
Mulholland E; Advisory Committee on the
Economic Burden of Injury in Canada. The
economic burden of injury in Canada.
Toronto (ON): SMARTRISK; 2009.
6.
Harrison JE. Injury classification: balancing
continuity and utility. Inj Control Safety
Promot. 2000;7:51-63.
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Vol 33, No 2, March 2013 – Chronic Diseases and Injuries in Canada
7.
Curry AE, Hafetz J, Kallan MJ, Winston FK,
Durbin DR. Prevalence of teen driver errors
leading to serious motor vehicle crashes.
Accid Anal Prev. 2011;43:1285-90.
8.
Kannus P, Parkkari J, Niemi S, Palvanen M.
Fall-induced deaths among elderly people.
Am J Public Health. 2005;95:422-4.
9.
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Report summary – Health-Adjusted Life Expectancy in Canada:
2012 Report by the Public Health Agency of Canada
The Public Health Agency of Canada Steering Committee on Health-Adjusted Life Expectancy (1)
Health-adjusted life expectancy is an
indicator of the average number of years
that an individual is expected to live in a
healthy state. It is a summary measure
that combines both quantity of life and
quality of life. In other words, it combines
mortality and morbidity experience into a
single summary measure of population
health. It can be used to measure the
burden of disease and injury in the
population, risk factors and the performance of public health efforts.
This report, entitled Health-Adjusted Life
Expectancy in Canada: 2012 Report by the
Public Health Agency of Canada,1 provides
estimates of health-adjusted life expectancy among Canadians with and without
selected chronic diseases (diabetes and
cancer) and chronic conditions (hypertension), and by socio-economic status
(income). Estimates are provided for
females and males and for people of
different ages.
Low socio-economic status is associated
with a loss in health-adjusted life expectancy. In 2001, Canadian women and men
in the top one-third income group had a
health-adjusted life expectancy at birth of
72.3 years and 70.5 years, respectively.
Compared with being in the highest
income group, being in the bottom onethird income group was associated with a
loss of health-adjusted life expectancy at
birth of 3.2 years for women and 4.7 years
for men.
Chronic diseases and conditions also are
associated with a significant loss in healthadjusted life expectancy. The estimates of
health-adjusted life expectancy by chronic
disease status in this report were calculated based on the mortality and morbidity
experience of people with and without
diabetes and/or hypertension (high blood
pressure) for the 2004–2006 period and of
people with and without cancer for the
2002–2005 period. According to the results
of this study, the diabetes cohort at age 55
had a loss in health-adjusted life expectancy of 5.8 years for women and 5.3
years for men. The cohort of people with
high blood pressure at age 55 had a loss of
2.0 years and 2.7 years for females and
males, respectively. The cancer cohort at
age 65 had a loss in health-adjusted life
expectancy of 10.3 years for women and
9.2 years for men.
This report provides information for use in
public health research, policy development and practice. Future reports could
extend the scope to include healthadjusted life expectancy by behavioural
risk factor status (such as obesity, physical
inactivity and smoking).
The full report is available at http://www.
phac-aspc.gc.ca/cd-mc/hale-evas-pdf-eng.php
References
1.
Public Health Agency of Canada Steering
Committee on Health-Adjusted Life Expectancy. Health-Adjusted Life Expectancy in
Canada: 2012 Report by the Public Health
Agency of Canada. Ottawa (ON): Public
Health Agency of Canada; 2012. Available
from: http://www.phac-aspc.gc.ca/cd-mc
/hale-evas-eng.php
Author references:
1. Members of the Public Health Agency of Canada Steering Committee on Health-Adjusted Life Expectancy: Priya Bakshi, Bernard C. K. Choi (Chair), Alan Diener, Eric Driscoll, Joellyn Ellison,
XiaoHong Jiang, Albert Kwan, Lidia Loukine, Wei Luo, Howard Morrison, Heather Orpana, August J. Saaltink, Robert Semenciw, Feng Wang, Chris Waters, Carl Yue, Rita Zhang.
Correspondence: Dr. Bernard C.K. Choi, Senior Research Scientist, Centre for Chronic Disease Prevention, Public Health Agency of Canada, A/L 6806B, 785 Carling Avenue Ottawa ON K1A 0K9;
Tel.: 613-957-1074; Email: Bernard.Choi@phac-aspc.gc.ca
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Vol 33, No 2, March 2013 – Chronic Diseases and Injuries in Canada
CSEB Student Conference 2012 abstract winners
Preface
Chronic Diseases and Injuries in Canada
(CDIC) was pleased to manage, once
again, the student abstract contest for the
Canadian Society for Epidemiology and
Biostatistics (CSEB) Student Conference,
which was held at the University of
Saskatchewan in May 2012. An editorial
panel from the Public Health Agency of
Canada judged 42 abstract submissions
and selected the top 7 to be published in
this issue of the journal.
The editorial panel consisted of the following members:
Since 2009, CDIC has collaborated with
CSEB to foster publishing opportunities for
students. CDIC is proud to collaborate
with CSEB again this year and to encourage students in their publishing efforts.
On behalf of the CDIC editorial team, I
would like to thank all students who
submitted their abstracts and to congratulate the winners. Having one’s abstract
published in a peer-reviewed journal is a
good place to start in science publishing!
We look forward to seeing future submissions of full research articles.
Michelle Tracy, MA
Managing Editor, Chronic Diseases and
Injuries in Canada
N
Howard Morrison, PhD, Editor-inChief, CDIC
N Kenneth Johnson, PhD, Senior
Epidemiologist
N Ania Syrowatka, MSc, Epidemiologist
N Michelle Tracy, MA, Managing Editor,
CDIC
The selected abstracts were judged on
their originality, clarity, scientific and
technical excellence, and potential impact.
The following questions helped guide the
judges:
1.
2.
3.
4.
5.
6.
7.
Is it relevant to chronic diseases and/
or injuries?
Are the data Canadian, or if not, do
the authors place the issue in the
context of Canada?
Does the study have national relevance? Local studies are of interest
only to the extent that they provide
sufficient details to allow them to be
useful to other, non-local researchers.
Does the study address a significant
public health issue?
Is the study scientifically rigorous?
Are the methods and/or results
novel, or is it a significant improvement on previous studies of the same
issue?
Can you imagine any reasonable
circumstance where a different
author would reference this study?
Vol 33, No 2, March 2013 – Chronic Diseases and Injuries in Canada
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The effect of gender and geography on the self-rated mental
health of single parents
A. Banerjee, MBBS (1); B. Janzen, PhD (1)
Introduction: Single parents, one of the
most
socio-economically
vulnerable
groups in Canada, consistently report
poorer mental health compared with
cohabiting parents. However, most of the
studies examining the mental health of
single parents typically fail to consider
whether they live in urban or rural areas,
or else focus exclusively on urban dwellers. This is despite that 1) a growing body
of research points to place (e.g. rurality) as
a determinant of health and 2) in 2006,
just over 13% of families residing in rural
Canada were headed by a single parent. In
addition, little is known about the mental
health of single fathers despite their
increasing numbers in Canada.
Objective: To determine if the mental
health of single parents varies by gender
and/or rurality and what factors (e.g.
economic, social) contribute to variations
in mental health by gender and/or rurality.
Methods: From Statistics Canada’s 2007/
2008 Canadian Community Health Survey
(Master file), we selected for analysis a
subsample of 18- to 64-year-old single
parents with at least one child aged under
25 years living with them. The dependent
variable was self-rated mental health, and
the primary independent variables were
sex and residence, the latter based on
Statistics Canada’s metropolitan influenced
zone (MIZ) classification. Covariates
included age, employment status, household income, home ownership, food security and sense of belonging to a community.
A series of univariate, bivariate and multivariable logistic regression analyses were
conducted to answer the research questions. Sampling weights and a bootstrap
variance estimation program were used to
address the complex sampling strategy.
Results: The sample (weighted) consisted
of 1 024 856 single parents. Single mothers
made up 81% of the sample, and the
majority of single parents (86%) lived in
urban areas. Overall, 9.3% of single
mothers and 7.0% of single fathers reported
fair/poor mental health. The proportion of
single fathers with fair/poor mental health
was 6.7% in Census Metropolitan Areas/
Census Agglomerations (CMAs/CAs),
11.0% in strong/moderate MIZ and 4.6%
in weak/no MIZ. Among single mothers,
the proportion with fair/poor mental health
was 9.5% in CMA/CA, 7.9% in strong/
moderate MIZ and 8.2% in weak/no MIZ.
Inspection of the preliminary results are
suggestive of variation in self-rated mental
health and access to economic/social
resources (e.g. employment, food security,
sense of belonging) according to gender
and/or degree of rurality; however, additional analyses applying the appropriate
variance estimation techniques are required
to determine whether these differences are
statistically significant. In addition, multiple
logistic regression needs to be conducted to
determine if any observed gender/residence differences in single parents’ mental
health remain statistically significant after
adjustment for key covariates.
Conclusion: The results of the study
enhance understanding of the diverse
experiences of Canadian single parents
and inform the development of more
targeted policies directed at improving
their mental health.
Keywords: health policy, social policy,
mental health, social epidemiology,
behavioural epidemiology, Canadian
Community Health Survey
Author references:
1. Department of Community Health and Epidemiology, College of Medicine, University of Saskatchewan, Saskatchewan, Canada
Correspondence: Ankona Banerjee; Email: asb426@mail.usask.ca
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Vol 33, No 2, March 2013 – Chronic Diseases and Injuries in Canada
Sitting, screen time and suicide: the relationship between
sedentary activity and suicide ideation in Canadian adolescents
and young adults
M. A. Bélair, BSSc (2); I. Colman, PhD (2)
Introduction: Suicide is the second leading cause of death among 15- to 24-yearolds in Canada. At 21.4%, suicide rates
among adolescents have remained constant despite declining rates in other
developed countries. More than 50% of
adolescents who commit suicide have a
major depressive disorder.
Objective: To investigate whether a link
exists between sedentary activity and
suicide ideation in Canadians aged 15 to
24 years.
Methods: Using an initial sample of 8356
from the Canadian Community Health
Survey (CCHS), Cycle 4 (2007/2008), 7914
adolescents and young adults aged 15 to 24
years were included in the analysis. We
conducted Breslow-Day tests for effect
modification to determine the need for
stratification and multivariate logistic
regression analysis to assess the relationship between sedentary activity and lifetime
suicide ideation. Sedentary activity was
classified into three categories: 0 to 15, 15
to 34 and 35 plus hours per week.
Results: Those who were sedentary 15
to 34 h/wk had odds ratio (OR) of
lifetime suicidal ideation 1.18 times
higher (95% confidence interval [CI]:
0.99–1.41) than those who were sedentary 0 to 15 h/wk, while those who were
sedentary 35+ h/wk had OR 1.41 times
higher (95% CI: 1.15–1.74) than those in
the least sedentary group. When controlling for sex, age, self-perceived health,
self-perceived mental health and body
mass index (BMI), as well as modelling
an interaction between sex and selfperceived health and between sex and
BMI, the relationship between suicide
ideation and sedentary activity for youth
and young adults in the 35+ h/wk
exposure category remained significant
with an adjusted OR of 1.33 (95% CI:
1.06–1.68), whereas that for those in the
15 to 34 h/wk exposure category was
non-significant at 1.11 (95% CI: 0.92–
1.35). To interpret the interaction terms,
we explored sex-stratified models. For
males reporting poor/fair self-perceived
health, OR of lifetime suicidal ideation
was 1.26 (95% CI: 0.82–1.26) whereas
Author references:
2. Department of Epidemiology and Community Medicine, University of Ottawa, Ottawa, Ontario, Canada
Correspondence: Marc-André Bélair; Email: mabelair@mabelair.com
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for females OR was 2.33 (95% CI: 1.68–
3.23) compared with the reference
(good/very good/excellent self-perceived
health). A 10-unit increase in BMI
decreased odds of lifetime suicide ideation for males by 0.97 (95% CI: 0.73–
1.28), whereas it increased odds of
lifetime suicide ideation by 1.58 times
(95% CI: 1.29–1.92) for females.
Conclusion:
A
relationship
exists
between sedentary activity levels and
lifetime suicide ideation among youth
and young adults with 35 or more hours
of sedentary activity per week. This is of
concern as a greater proportion of
adolescents and young adults spends
more time being sedentary. However,
the cross-sectional nature of the CCHS
does not permit us to comment on the
direction of this relationship. Further
research using longitudinal data is
recommended.
Keywords: mental health, Canadian
Community Health Survey, depression,
suicide
Health status and service use among homeless individuals with
mental illness: consistency between self-report and
administrative health records in the At Home/Chez Soi
Multi-site Trial
A. Hinds, MSc (3); J. Distasio, PhD (4); P. J. Martens, PhD (3, 5); M. Smith, MSc (5)
Introduction: Homeless individuals with
poor health use health care services
frequently.
Objective: To examine health status,
health care and prescription drug use
among mentally ill, homeless individuals
and compare self-report and administrative data claims to estimate the degree of
agreement between the two sources.
Methods: Baseline survey data from 100
participants of the Winnipeg site of the
Mental Health Commission of Canada’s At
Home / Chez Soi research project were
linked to de-identified administrative
health records stored in the Repository at
the Manitoba Centre for Health Policy. We
analyzed demographic characteristics,
homelessness histories and health service
use as well as disease status for asthma,
hypertension, arthritis and diabetes (using
previously
validated
definitions).
Participants were similarly classified using
their survey responses. The degree of
agreement between the two data sets
was evaluated using cross tabulations
and the kappa [k] statistic.
Results: There was 100% linkage of
surveyed homeless people with the
Repository data. In one year, 97% of
participants had at least one ambulatory
physician visit, with an age- and sexadjusted rate of 14.82 per person-years
(overall Manitoba rate = 4.99 per personyears); 34% were hospitalized (adjusted
hospital separation rate = 491 per thousand person-years versus the Manitoba
rate of 137 per thousand person-years);
and 95% filled at least one prescription
with 65% of drugs targeting the nervous
system (the majority were psycholeptics).
The degree of agreement between the
disease-related data sources ranged from
poor (k = 0.27) for arthritis to moderate
(k = 0.57) for hypertension. Individuals
were more likely to be classified as having
one of the four selected conditions based
on the administrative data than on the
survey data.
Conclusion: Compared to the general
population, homeless participants had
high health service use and high prescription drug use. There was poor to moderate
agreement between the two data sources
with regard to disease detection.
Researchers studying homeless persons
with mental illness should consider using
multiple data sources to estimate disease
prevalence and health service use.
Keywords: mental health, epidemiological
methods, health care services use, administrative health records, homelessness
Author references:
3. Department of Community Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
4. Institute of Urban Studies, University of Winnipeg, Winnipeg, Manitoba, Canada
5. Manitoba Centre for Health Policy, University of Manitoba, Winnipeg, Manitoba, Canada
Correspondence: Aynslie Hinds; Email: umhinds0@cc.umanitoba.ca
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Vol 33, No 2, March 2013 – Chronic Diseases and Injuries in Canada
Modelling costs of episodes of care for exacerbations of chronic
obstructive pulmonary disease
J. P. Kuwornu, MSc (6); L. M. Lix, PhD (6, 7); J. M. Quail, PhD (6, 7); E. Wang, MSc (7); M. Osman, MA (7)
Introduction: An episode of care (EoC) is
the cluster of health care services associated with an acute or chronic condition.
EoCs are used to examine variations in
cost and use of different treatment pathways. Predictive models of EoC utilization
and costs can be used to identify the
pathways that result in optimal treatment
outcomes. However, a major issue associated with making valid and accurate
predictions is the selection of an appropriate statistical model.
hospitalization with a primary diagnosis
of COPD from 2000/2001 to 2009/2010,
and calculated total hospital, physician
and drug costs for each EoC, adjusting for
inflation. We compared marginal generalized estimating equation (GEE) and random effects models with a gamma or
negative binomial distribution for mean
EoC cost and quantile regression model
for median EoC costs. Covariates
included demographic, socio-economic
and disease-related variables.
Objective: To compare different statistical
models for predicting EoC costs for
exacerbations of chronic obstructive pulmonary disease (COPD).
Results: From the study cohort (n = 41
848), we identified 20 999 EoCs for COPD
exacerbations initiated by hospitalisation.
Average age of those who had COPD EoCs
was 71 (standard deviation [SD]: 12)
years, and 53% were male. Total costs
were highly skewed. The median total cost
was $4,506, while the mean (SD) was
$7,968 ($13,354). The median was higher
for episodes (n = 2400) in which the
individual died ($8,380) than not die (n =
18 599; $4,400). The random effects and
GEE models failed to converge for the
Methods: The study data included hospital separations, physician billing claims,
prescription drug records and population
registration files from Saskatchewan. The
study cohort was made up of individuals
aged 35 years and older with a COPD
diagnosis in hospital or physician
claims. We identified EoCs initiated by a
Author references:
6. School of Public Health, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
7. Health Quality Council, Saskatoon, Saskatchewan, Saskatchewan, Canada
Correspondence: John Paul Kuwornu; Email: paul.kuwornu@usask.ca
Vol 33, No 2, March 2013 – Chronic Diseases and Injuries in Canada
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gamma distribution. The model with a
negative binomial distribution fit the data
well based on the deviance statistic. All
covariates in this model were statistically
significant except for sex (p = .8179) and
age (p = .0610).The quantile regression
model also converged; only the Charlson
comorbidity score was not statistically
significant (p = .5791).
Conclusion: Quantile regression and marginal models with negative binomial distribution appear to be valid approaches to
addressing the small proportion of individuals with high EoC costs for COPD. The
models produced different results about
the significance of the covariates. The
choice of models will influence the patient
characteristics associated with health care
costs and treatment trajectories, and could
lead to different conclusions about optimal
treatment pathways for COPD patients.
Keywords: longitudinal analysis, epidemiological methods, respiratory epidemiology
Characteristics associated with increased pain and low
functional recovery three to five years following total knee
arthroplasty
J. E. Mollins, MSc (8); C. A. Jones, PhD (9, 10); M. Clark, MD (11); L. Beaupre, PhD (9, 10)
Introduction: The incidence of total knee
arthroplasty (TKA) performed in Canada
is steadily increasing; however, 9% to
19% of all TKA patients experience little
or no improvement in physical function
and pain relief postoperatively. A lack of
consensus exists about the factors associated with these poor outcomes.
Determining baseline characteristics and
demographics associated with increased
pain and negated postoperative functional
status could assist in identifying patients
who are less likely to benefit from this
operation. If these factors are modifiable,
they could be addressed before TKA to
improve postoperative outcome; if not,
patients could be given realistic postoperative expectations.
Objective: To identify modifiable and nonmodifiable baseline patient demographics
associated with poor pain and physical
function scores on the Western Ontario
McMaster Osteoarthritis Index (WOMAC)
at 3 to 5 years following TKA.
Methods: This was a secondary analysis
of prospectively collected data from the
Alberta Arthroplasty Study, a large randomized clinical trial. We performed initial
descriptive analyses and compared baseline scores between responders and
non-responders as well as univariate
linear regression for the following independent variables: age, gender, group
allocation, body mass index (BMI), categorical comorbidities (ƒ 2 or § 3 conditions), presence of back pain, diabetes
status, presence of lung disease, smoking
status, baseline Medical Outcomes Study
36-item Short Form (SF-36) mental health
(MH) scores, baseline WOMAC physical
function scores and baseline WOMAC
pain scores. This initial model building
step was performed twice: once with
WOMAC pain scores and once with
WOMAC function scores as the dependent
variable. A multivariate regression was
then developed using purposeful selection
techniques. Final stability of the model
was assessed using forward and backward
stepwise regression methods to determine
agreement among significant variables;
variance inflation factors were calculated
to test for collinearity.
Results: A total of 388 patients consented to
further evaluation 3 to 5 years after TKA.
We observed significant improvements in
both WOMAC pain and function scores. In
the multivariate analyses, older age, presence of back pain, and overweight or
obesity were indicators of both worse pain
levels and inferior functional status. Better
preoperative WOMAC pain and SF-36 MH
scores were associated with improved postoperative pain levels. Higher WOMAC
function and SF-36 MH scores at baseline
were predictive of better functional outcomes post-TKA. Coefficients of determination (R2) were 0.15 for the pain model and
0.19 for the function model.
Conclusion: Older age is associated with
poorer pain outcomes several years postTKA; however, older individuals experienced changes in pain similar to that of
younger patients. Thus, older age should
not be a limiting factor when considering
candidates for TKA. Increased BMI was
also a significant predictor of long-term
pain and function scores. Interventions to
manage BMI and back pain should be
considered preoperatively to maximize
TKA outcomes. Based on the identified
risk factors, patient expectations may be
revised regarding outcomes. Low R2
values indicate limited ability of the model
to predict patient outcomes 3 to 5 years
following surgery. Future research may
consider including more psychosocial
variables in medically based models when
assessing TKA outcomes.
Keywords: clinical epidemiology, longitudinal analysis, aging
Author references:
8. Faculty of Rehabilitation Medicine, University of Alberta, Edmonton, Alberta, Canada
9. Department of Physical Therapy, University of Alberta, Edmonton, Alberta, Canada
10. Alberta Innovates - Health Solutions, Edmonton, Alberta, Canada
11. Department of Surgery, University of Alberta, Edmonton, Alberta, Canada
Correspondence: Juliana Mollins; Email: mollins@ualberta.ca
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Vol 33, No 2, March 2013 – Chronic Diseases and Injuries in Canada
Variable importance measures for non-normal data: an
application to patient-reported outcomes on their healthrelated quality of life
T. T. Sajobi, PhD (12); B. M. Dansu, PhD (12); L. M. Lix, PhD (12)
Introduction: Health-related quality of life
(HRQOL) measures are widely used in
clinical trials to assess the effectiveness of
new treatments across physical, psychological and social domains. Variable importance measures derived from descriptive
discriminant analysis (DDA) and multivariate analysis of variance (MANOVA)
procedures have been developed for evaluating the importance of domain for HRQOL
data collected at a single time point. This
includes standardized discriminant function coefficients, discriminant ratio coefficients, and F-to-remove statistics. However,
these measures may result in inconsistent
rank ordering of domains in HRQOL data
characterized by non-normal distributions.
Objective: To develop and apply measures
of relative importance derived from DDA
and MANOVA procedures based on
trimmed means and Winsorized covariances for evaluating domain importance
in non-normal multivariate data.
Methods: DDA and MANOVA procedures
that are insensitive (i.e. robust) to departures
from
multivariate
normality
assumption were developed by replacing
the least squares estimates of means and
covariances with trimmed means and
Winsorized covariances, respectively.
Variable importance measures derived
from the coefficients of these robust DDA
and MANOVA procedures were used to
rank order variables in non-normal multivariate data. Variable importance measures based on least squares and robust
estimators were illustrated using data
from the Manitoba Inflammatory Bowel
Disease Cohort Study, an on-going longitudinal cohort study that is investigating
psychosocial predictors of health outcomes. Study participants with selfreported active (n = 265) and inactive
(n = 116) disease were compared on the
four domains of the disease-specific
inflammatory bowel disease questionnaire
(IBDQ) and the eight domains of the
Medical Outcomes Study 36-item Short
Form (SF-36) Questionnaire that measured the physical and mental aspects of
participants’ health and well-being.
estimators were used to evaluate domain
importance, the IBDQ bowel symptom
and the SF-36 general health domains
were identified as the most important
domains. In contrast, the IBDQ emotional
health and the SF-36 general health
domains were identified as the most
important domains that discriminate
between active and inactive disease
groups when variable importance measures based on trimmed means and
Winsorized covariances were used to
evaluate domain importance. The rank
ordering of the remaining domains varied
across variable importance measures and
estimation methods.
Results: When measures of relative
importance based on least squares
Keywords:
biostatistics,
public health
Author references:
12. School of Public Health, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
Correspondence: Tolulope Sajobi; Email: tts229@mail.usask.ca
Vol 33, No 2, March 2013 – Chronic Diseases and Injuries in Canada
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Conclusion: These relative importance
measures can be used to choose a parsimonious subset of domains that best
discriminate between groups in non-normal HRQOL data. Further research is
needed to investigate the properties of
these measures under a variety of data
analytic conditions.
population,
Women’s health care utilization among HIV-positive women on
ART in British Columbia*
X. Wang, MPH (13); K. A. Salters, MPH (14); H. Wang, MSc (14); W. Zhang, MSc (14); N. Pick, MD (15, 16);
J. S. Montaner, MD (14, 15); R. S. Hogg, PhD (13, 14); A. Kaida, PhD (13)
*This abstract appears in a full version of the article with the following citation: Wang X, Salters KA,
Zhang W, McCandless L, Money D, Pick N, Montaner JSG, Hogg RS, Kaida A. Women’s Health Care
Utilization among Harder-to-Reach HIV-Infected Women ever on Antiretroviral Therapy in British
Columbia. AIDS Research and Treatment. 2012; doi:10.1155/2012/560361
multivariable logistic regression analyses
were conducted to identify factors
associated with women’s health care
utilization.
longitudinal HIV clinical data available
through the provincial Drug Treatment
Program. For this analysis, inclusion was
restricted to LISA participants who identified as female. The outcome measure
was current utilization of women’s health
care. The answers were dichotomous (yes
vs. no) based on responses to the LISA
survey question, ‘‘I have a physician who
I see regularly for women’s health care.’’
Independent covariates included demographic variables (age, ethnicity, health
authority, rural/urban residency, marital
status), sociodemographic variables (education, employment, income, housing
stability, food security), psychosocial
variables (stigma, perceived neighbourhood problems or cohesion, quality of
life), substance-use variables (alcohol
use, illicit drug use, drug injection),
sexual health variables (sexual activity,
condom use, sex trade history, pregnancy
intention, number of births, history of
sexually transmitted infections, abnormal
Pap smear in last 6 months), mental
health variables (symptoms of depression), and HIV clinical variables (ART
status, CD4 cell count, plasma viral load,
viral load suppression, duration of immunosuppression). Bivariate analyses and
Results: Of the 231 women participants,
77% regularly accessed women’s health
care. Median age was 41 years, 49%
reported Aboriginal ancestry, 72% had an
annual income less than $15,000, 62% had
stable housing and 23% were food secure.
In the multivariate analysis, factors associated with women’s health care utilization
included not living in Vancouver Island
Health Authority (odds ratio [OR] = 0.12,
95% confidence interval [CI]: 0.04–0.37),
no current illicit drug use (OR = 0.42, 95%
CI: 0.19–0.92), higher annual income (OR
= 6.73, 95% CI: 1.85–24.54) and increased
provider trust (QoL scale) (OR = 1.03,
95% CI: 1.00–1.05).
Introduction: Women make up more than
50% of HIV-positive (HIV+) population
globally and about 22% nationally. That
there are experiences unique to women
living with HIV has been well established.
Compared with their HIV-negative counterparts, HIV+ women are more likely to
have abnormal gynecological conditions
and menopause-related problems such as
osteoporosis. However, several studies
have suggested that medical care specific
to women was underutilized among HIV+
women despite that appropriate use of
women’s health care has been shown to
reduce HIV-related burden of diseases.
Objective: To estimate the prevalence and
covariates of women’s health care utilization among HIV+ women who ever
received antiretroviral therapy (ART) in
British Columbia (BC).
Methods: The Longitudinal Investigations
of Supportive and Ancillary Health
Services (LISA) study is a study of people
living with HIV who have ever received
ART in various BC clinics. The crosssectional interview data on sociodemographic factors, supportive service use
and quality of life were linked to the
Conclusion: Despite a relatively high
prevalence of women’s health care utilization among HIV+ women on ART in BC, a
health service gap persists along geographic
and social axes. To effectively integrate
women’s health care into routine HIV care,
programs and services need to be tailored to
women’s needs by addressing social and
structural determinants of health.
Keywords: social epidemiology, behavioural epidemiology, women’s health,
health services research
Author references:
13.
14.
15.
16.
Faculty of Health Sciences, Simon Fraser University, Burnaby, British Columbia, Canada
BC Centre for Excellence in HIV/AIDS, Vancouver, British Columbia, Canada
Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada
Oak Tree Clinic, BC Women’s Hospital and Health Centre, Vancouver, British Columbia, Canada
Correspondence: Xuetao Wang; Email: wangxtk@gmail.com
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Vol 33, No 2, March 2013 – Chronic Diseases and Injuries in Canada
With thanks to our 2012 peer reviewers
We are grateful to the following people for their significant contribution to Chronic Diseases and Injuries in Canada as peer reviewers
in 2012. Their expertise ensures the quality of our journal and promotes the sharing of new knowledge among peers in Canada and
internationally.
Rebecca Armstrong
Philip Groff
Joel Monárrez-Espino
Laurent Azoulay
Marguerite Guiguet
Lisa Oliver
Shelina Babul
Ken Johnson
Sai Yi Pan
Claude Bégin
Marie-Jeanne Kergoat
Louise Parker
Claudia Blais
Kyungsu Kim
Jennifer Payne
Robert Brison
Malcolm King
William Pickett
Mariana Brussoni
Lucie Laflamme
Karen Poon
Stephanie Burrows
Rachel Lane
Virginia Powell
Leslie Campbell
Kristian Larsen
Bob Prosser
Mary Chipman
Bernard-Simon Leclerc
Brian Rowe
Rachel Colley
Gilles Légaré
Conor Sheridan
Sarah Connor Gorber
Bing Li
Richard Stanwick
Michael Cusimano
Lisa Lix
Gerold Stucki
Fernando De Maio
Alice Lytwyn
Eva Suarthana
Jessica Dennis
Alison Macpherson
Katherine Teng
Helen Edwards
Ruth Martin-Misener
Wendy Thompson
Tewodros Eguale
Ian McDowell
Bliss Tracy
Mariam El-Zein
Steven McFaull
Jean-Pierre Villeneuve
Marie-Pierre Gagnon
Elizabeth McGregor
Michelle Vine
Alain Gauthier
Larry McKeown
Kathryn Wilkins
Julie Green
Leia Minaker
Katrina Zanetti
Vol 33, No 2, March 2013 – Chronic Diseases and Injuries in Canada
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