Factors associated with active commuting among a nationally representative sample of Canadian youth.
Bookwala, Ammar ; Elton-Marshall, Tara ; Leatherdale, Scott T. 等
Data from the 2007-09 Canadian Health Measures Survey (CHMS)
suggest that among Canadian youth aged 15 to 19, 31% of boys and 26% of
girls are overweight or obese. (1) This represents a dramatic
population-level increase from 25 years ago when only 14% of boys and
14% of girls were considered overweight or obese. (1) Given these
changes, obesity prevention among youth should be considered a public
health priority in Canada.
In recent years, numerous policy- and community-level initiatives
have been launched to change one or both sides of the energy-balance
equation for children and adolescents (youth) by reducing calories
consumed or increasing calories expended from physical activity (PA).
(2) However, since evidence suggests that dietary factors are not
strongly associated with obesity in youth populations, (3,4) efforts to
reduce or prevent obesity among youth may be more effective if they
focus on PA. (5) Given the challenges associated with increasing PA
among the youth populations, (6) further investigation into the
predictors of different forms or types of PA that are amenable to
intervention is warranted.
One form of PA receiving interest in recent years is active
commuting to school. (7,8) Active commuting to school is considered
important as evidence suggests that youth who walk and bike to school
are more active than their non-commuting counterparts. (9,10) Given the
interest among policy-makers, the potential reach and impact and the
relatively low cost associated with school-based programming to promote
active commuting, this activity has been identified as an important
population-based intervention to increase PA levels. (9) For instance,
in a recent provincial report "Taking Action to Prevent Chronic
Disease--Recommendations for a Healthier Ontario", active commuting
to school was recommended as an important intervention to improve the
health of youth in Ontario. (11) Similar provincial strategy documents
in other Canadian provinces (e.g., British Columbia (12) and Manitoba
(13)) have also recommended promoting active commuting to school. As
such, understanding the prevalence of and the factors associated with
active commuting among Canadian youth would help to inform the
development and potential implementation of such policy initiatives.
Existing research has identified various modifiable student
characteristics associated with active commuting. For instance, youth
are more likely to actively commute if they are a nonsmoker (8) or are
physically active. (8-10) However, it has also been suggested that there
is a need to move beyond only examining individual student
characteristics if we want to understand how to best target school-based
interventions so that they are most likely to have impact. (8) As such,
there is also evidence demonstrating that youth are more likely to
actively commute if they attend a school located in an urban setting.
(14-17) Considering that within the Canadian context, much of the work
examining correlates of active commuting has focused on students in the
province of Ontario, (8,14,15,18) the aim of the current study is to
assess the prevalence of active commuting and explore the factors
associated with active commuting and mixed (active/inactive) commuting
using nationally representative data.
METHODS
Design
This study used data collected from 50,949 students in grades 6 to
12 (aged 11 to 19 years) who participated in the 2010-11 Canadian Youth
Smoking Survey (2010 YSS), a nationally representative school-based
survey of youth in Canada. In brief, the population of interest for the
data used in this study consisted of all young Canadian residents in
grades 6 to 12 attending public and private secondary schools in nine
Canadian provinces; youth residing in the Yukon, Nunavut, the Northwest
Territories and New Brunswick were excluded from the population of
interest, as were youth living in institutions or on First Nation
Reserves, and youth attending special schools or schools on military
bases. While New Brunswick participated in all prior cycles of YSS, the
provincial government chose not to participate in 2010 YSS. As described
in more detail in the user guide, the sampling of schools for the 2010
YSS was based on a stratified single-stage design. Within most
provinces, stratification was based on two classifications: 1) health
region smoking rate, and 2) type of school (elementary or secondary).
Different sampling strategies were used in Prince Edward Island (all
schools) and Quebec (schools in 30 of 36 targeted health regions). The
survey design and sample weights allow us to produce population-based
weighted sample estimates. The University of Waterloo Office of Research
Ethics and appropriate School Board Ethics committees approved all
procedures. Detailed information on the 2010 YSS sample design, methods,
response rates and measures are available. (19)
Measures
Consistent with previous research, (8) students were asked
"How do you usually get to and from school?", with response
options of "Actively (e.g., walk, bike)",
"Inactively" (e.g., car, bus)", or "Mixed (actively
and inactively)." Students who reported being inactive commuters
(referent) were compared to students who reported being either active
commuters [Active (1) vs. Inactive (0)] or mixed commuters [Mixed (1)
vs. Inactive (0)].
Using previously validated measures of self-reported height and
weight, (20) body mass index (BMI) was calculated for each student using
the measures of weight (kg) and height (m) (BMI=kg/[m.sup.2]). Weight
status was then determined using the BMI classification system of the
World Health Organization, (21) based on age- and sex-adjusted BMI
cut-points where students within the lowest 5th percentile for BMI
adjusted for age and sex were classified as underweight, those within
the 6th-84th percentile as normal weight, and those within the highest
15th percentile as overweight or obese. Using previously validated
measures, (20) students were asked how many minutes of vigorous PA (VPA)
they engaged in on each of the last 7 days. Consistent with Wong et al.,
(20) our measure of PA was based on the average kilocalories per
kilogram of body weight per day (KKD) expended in VPA calculated as: KKD
= (Hours of VPA*6MET)/7 days. Tobacco use was assessed by asking
respondents, "Have you ever smoked 100 or more whole cigarettes in
your life?" and "On how many of the last 30 days did you smoke
one or more cigarettes?" Consistent with validated measures of
smoking, (22) students who reported ever smoking 100 cigarettes and any
smoking in the previous 30 days were classified as current smokers and
students who had smoked 100 or more cigarettes but had not smoked in the
previous 30 days were classified as former smokers; non-smokers were
defined as those who had not smoked 100 or more whole cigarettes in
their lifetime but might have smoked a whole cigarette. Sedentary
behaviour was assessed with a single item asking students to report the
amount of time (hours per day) they spent: watching movies/TV, playing
computer/video games, surfing on the internet, talking on the
phone/instant messaging and reading over each of the previous 7 days.
(8) Students who reported <1 hour per day (low sedentary) were
compared to students who reported 1 to 3 hours (moderate sedentary) and
>3 hours (high sedentary) per day of sedentary behaviour. According
to Statistics Canada, population centres are geographic areas with a
population of at least 1,000 people and a population density of at least
400 people per square kilometre. (23) Based on this definition, an urban
location was defined as the school being located in a large urban
population centre with a population of 100,000 people or more, and a
suburban location was defined as the school being located in a small or
medium population centres with a population between 1,000 and 99,999
people; a school was defined as being in a rural location if it was
located outside a population centre of less than 1,000 people or in a
region with a residential density of less than 400 people per square km.
Analyses
Survey weights were used in all analyses to adjust for non-response
between provinces and groups, thereby minimizing any bias caused by
differential response rates across regions or groups. Weighted
descriptive analyses of active commuting rates were examined by
province, by grade and by sex. Generalized linear mixed models using
proc glimmix analysis were used to explore the association between
active or mixed commuting and the predictor correlates, while adjusting
for clustering within schools. The statistical package SAS 9.2 was used
for all analyses.
RESULTS
Descriptive statistics
Among Canadian youth in grades 6 to 12 in 2010, 52.2% (n
=1,420,000) were inactive commuters, 22.1% (n=600,900) were active
commuters and 25.7% (n=699,400) were mixed commuters. As shown in Table
1, males were more likely than females to actively commute (x2=37.08,
df=2, p<0.001). Students attending a school in an urban location were
more likely to actively commute than students attending a school in a
suburban or rural location ([chi square]=397.96, df=4, p<0.001).There
were also differences identified across Canadian regions (see Figure 1).
For instance, the highest prevalence of youth who commute actively was
in British Columbia (30.3%) and Ontario (26.4%), whereas, Atlantic
Canada (9.8%) and Quebec (15.1%) had the lowest rates of active
commuting.
Factors associated with active commuting
As shown in Table 2 (Model 1), male students were more likely than
female students to actively commute (OR=1.45, 95% CI 1.44-1.45). Low
sedentary students were more likely to be active commuters compared to
those who were highly sedentary (OR=1.20, 95% CI 1.16-1.24). Current
smokers also had a higher likelihood of being active commuters compared
to non-smokers (OR=1.64, 95% CI 1.63-1.66). Compared to grade 6
students, students in grade 7 (OR=1.10, 95% CI 1.08-1.11), grade 8
(OR=1.03, 95% CI 1.02-1.05), grade 9 (OR=1.25, 95% CI 1.23-1.27) and
grade 10 (OR=1.06, 95% CI 1.04-1.08) were more likely to commute
actively, whereas students in grade 11 (OR=0.86, 95% CI 0.84-0.87) and
grade 12 (OR=0.73, 95% CI 0.71-0.74) were less likely to actively
commute. Overweight/obese youth were less likely than normal weight
youth to actively commute (OR=0.82, 95% CI 0.82-0.83). Students
attending a school in a rural location were less likely to be active
commuters compared to students attending a school in an urban location
(OR=0.15, 95% CI 0.06-0.38). As shown in Figure 2, as the amount of PA
increases, the relative odds of being an active commuter increase.
[FIGURE 2 OMITTED]
Factors associated with mixed commuting
As shown in Table 2 (Model 2), male students were more likely than
female students to be mixed commuters (OR=1.09, 95% CI 1.091.10). Former
smokers were more likely to be mixed commuters than non-smokers
(OR=2.08, 95% CI 2.04-2.11). Compared to grade 6 students, students in
grade 7 (OR=1.41, 95% CI 1.39-1.43), grade 8 (OR=1.16, 95% CI
1.14-1.17), grade 9 (OR=1.23, 95% CI 1.21-1.25), grade 10 (OR=1.22, 95%
CI 1.20-1.24) and grade 11 (OR=1.08, 95% CI 1.06-1.09) were more likely
to be mixed commuters, whereas students in grade 12 were less likely to
be mixed commuters (OR=0.86, 95% CI 0.85-0.88). Overweight/obese youth
were less likely than normal weight youth to be mixed commuters
(OR=0.86, 95% CI 0.85-0.88). Low sedentary students were less likely to
be mixed commuters compared to highly sedentary students (OR=0.54, 95%
CI 0.52-0.56). Students attending a school in a rural location were less
likely to be mixed commuters compared to students attending a school in
an urban location (OR=0.26, 95% CI 0.13-0.55). As shown in Figure 2, as
the amount of PA increases, the relative odds of being a mixed commuter
increases.
DISCUSSION
Using nationally representative data, we found that a majority of
Canadian students in grades 6 to 12 commute to school using inactive
modes of transportation; only roughly 1 in 5 Canadian students reported
actively commuting to school. This is consistent with previous research
that identified that more than half of students in a large sample of
Ontario high schools commuted using inactive forms of transportation.
(8) Given that the majority of Canadian youth are not currently active
commuters, these results suggest that there is ample opportunity to
intervene with programs and policies designed to promote active
commuting among youth populations in Canada. As a first step, it will be
important to identify the underlying facilitators or barriers to active
commuting in order to develop appropriate interventions.
As expected, PA was found to be positively associated with active
and mixed commuting. (7,8,24-26) However, given that the temporal
relationship between active commuting and PA has yet to be determined,
it is important for future research to identify if there is a causal
association between PA and active commuting, and to determine if PA is
the antecedent to active commuting or if active commuting is the
antecedent to kids being more physically active. Longitudinal data from
the COMPASS study can be used to examine such relationships within the
Canadian context moving forward. (27) Such insight would be valuable for
developing future obesity prevention and activity promotion
interventions for youth.
We also identified that low sedentary students were more apt to
commute actively. This finding was contrary to the existing evidence,
(8) which previously reported that there was no association between
sedentary behaviour and active commuting. Our new finding with this
nationally representative sample suggests that it is possible that
students may be less sedentary if they actively commute, possibly due to
reducing the amount of time available to participate in sedentary
pursuits before or after school. Additional research is required to
determine the nature of the relationship between active commuting and
sedentary behaviour. If interventions designed to promote and sustain
active commuting have an additional benefit of reducing the amount of
time youth spend in sedentary behaviour, this would be important
knowledge moving forward, especially as research has previously
identified youth sedentary behaviour as a public health concern in
Canada. (28)
Unlike previous research which identified that youth smokers were
less likely to actively commute, (8) we identified that being a current
smoker was associated with an increased likelihood of being an active
commuter. While it cannot be determined with these data, it is possible
that youth smokers may use the time when actively commuting back and
forth from school to smoke, especially since students in many
jurisdictions (e.g., Ontario) are not allowed to smoke on school
property and many youth smokers report that their parents do not know
they smoke. (29) Further research is needed to understand the
association between smoking and active commuting as it may have
implications for tobacco control prevention programming (i.e.,
developing and testing interventions to dissuade youth from smoking
during the commute to and from school). It would also be beneficial to
understand why non-smokers are less likely to actively commute than
smokers so that appropriate interventions can be developed to promote
more active commuting among this subpopulation of youth.
The current study also identified some non-modifiable factors that
were associated with being an active or mixed commuter. For instance,
girls and older students (Grades 11 and 12) were less likely to commute
actively than boys and younger students (Grades 6-10). Similar patterns
were also observed among mixed commuters versus inactive commuters.
Higher rates among boys of walking to and from school may be reflective
of social tendencies of parents to be more protective of girls and to
place greater restrictions upon their mobility. (9) Although it cannot
be determined with these data, the finding that active commuting
declined among youth in older grades may be reflective of the
acquisition of a driver's license in later grades, which increases
vehicle access for students and peers within their social group. (9,30)
Additionally, regional differences in the size and location of middle
and high schools may result in their not being as accessible by active
modes of transportation. (9,30) However, this finding is not surprising
considering that students in rural schools would tend to live farther
away from school, making it more likely they will use inactive forms of
transportation. The research community interested in promoting active
commuting may have to determine that active commuting interventions may
not be as relevant or appropriate for rural or suburban settings, or
will need to develop interventions that are feasible and practical
within the rural context. Given that some youth in rural and suburban
settings do report being active commuters (see Table 1), additional
research could explore how or why such youth are able to commute
actively.
Several limitations of this study must be considered. Because no
data on socio-economic status were collected, we were unable to measure
how active commuting may vary across different socioeconomic groups.
Furthermore, we were unable to determine how far students lived from
schools, so we were not able to model the impact that distance to school
would have on active commuting. In addition to lack of information on
distance to school, we did not have detailed information about the
walkability characteristics of different neighbourhoods which may impact
the likelihood of actively commuting to school. Distance to school may
be an important mitigating factor for large levels of inactive commuting
among the rural population. Furthermore, we did not address the impact
of school board bussing policy on high school student populations. The
use of single-item questionnaires also limits the breadth of data (e.g.,
mode of commuting, time, frequency) collected. Additionally, causal
relationships cannot be inferred from these cross-sectional data.
Despite these limitations, our findings highlight that few Canadian
students consistently use active transportation as a means of getting to
and from school. While active commuting may be considered a simple and
cost-effective method for increasing PA levels among youth populations,
we identified both modifiable and non-modifiable characteristics
amenable to future intervention that are associated with both increased
and decreased likelihoods of being an active or mixed commuter. Future
research should evaluate whether active commuting has a meaningful
population-level impact on obesity prevention among youth populations.
Acknowledgements: The Youth Smoking Survey is a product of the
pan-Canadian capacity building project funded through a contribution
agreement between Health Canada and the Propel Centre for Population
Health Impact from 2004 to 2007 and a contract between Health Canada and
the Propel Centre for Population Health Impact from 2008-2011. The YSS
consortium includes Canadian tobacco control researchers from all
provinces and provided training opportunities for university students at
all levels. The views expressed herein do not necessarily represent the
views of Health Canada. STL is a Chair in Applied Public Health funded
by the Public Health Agency of Canada (PHAC) in partnership with the
Canadian Institutes of Health Research (CIHR).
Conflict of Interest: None to declare.
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Received: May 6, 2014
Accepted: July 11, 2014
Ammar Bookwala, BSc, [1], Tara Elton-Marshall, PhD, [2], Scott T.
Leatherdale, PhD [3]
Author Affiliations
[1.] Department of Kinesiology, University of Waterloo, Waterloo,
ON
[2.] Social and Epidemiological Research Department, Centre for
Addiction and Mental Health, London, ON
[3.] School of Public Health and Health Systems, University of
Waterloo, Waterloo, ON
Correspondence: Scott T. Leatherdale, School of Public Health and
Health Systems, University of Waterloo, 2000 University Avenue,
Waterloo, ON N2L 3G1, Tel: 519-888-4567, ext. 37812, E-mail:
sleather@uwaterloo.ca
Table 1. Descriptive statistics for Canadian youth in grades 6
to 12 (weighted)
Active Mixed
(N=600,900) (N=699,400)
(22.1%) (25.7%)
% %
Gender
Female 43.4 49.9
Male 56.6 50.1
Grade
6 20.8 13.0
7 15.0 14.8
8 15.2 15.2
9 13.6 15.2
10 12.0 15.5
11 11.3 14.7
12 12.1 11.6
Weight status *
Underweight 3.3 2.6
Healthy weight 75.3 74.3
Overweight/obese 21.4 23.1
Smoking status
Current smoker 5.5 4.3
Former smoker 0.7 1.3
Non-smoker 93.8 94.4
Sedentary
behaviour
([dagger])
Low 1.1 0.6
Moderate 25.2 21.9
High 73.7 77.5
School
location
([double
dagger])
Rural 5.3 5.9
Urban 62.1 34.6
Suburban 32.6 59.5
Non-active Chi-square
(N=1,420,000) (df)
(52.2%)
%
Gender
Female 50.8 37.08 (2)
Male 49.2 p < 0.001
Grade
6 10.5 215.59 (12)
7 13.1 p < 0.001
8 13.4
9 14.4
10 16.2
11 16.4
12 16.0
Weight status *
Underweight 2.8 3.27 (4)
Healthy weight 74.1 p = 0.51
Overweight/obese 23.1
Smoking status
Current smoker 6.0 10.69 (4)
Former smoker 1.0 p < 0.05
Non-smoker 93.0
Sedentary
behaviour
([dagger])
Low 0.8 17.33 (4)
Moderate 22.2 p < 0.01
High 77.0
School
location
([double
dagger])
Rural 13.4 397.96 (4)
Urban 39.6 p < 0.001
Suburban 47.0
* Weight status: Underweight (0-5th percentile BMI), Healthy
weight (6-84th percentile BMI), Overweight/obese (>85th
percentile BMI).
([dagger]) Sedentary behaviour: Low (< 1 hour/day), Moderate (1-3
hours/day), High (> 3 hours/day).
([double dagger]) School location: Rural (residential density <
400 people/[km.sup.2]), Suburban (population = 1000-99,999 and
residential density > 400 people/[km.sup.2]); Urban (population
> 100,000 and residential density > 400 people/[km.sup.2]).
Table 2. Logistic regression models examining factors
associated with active commuting and mixed
commuting among Canadian youth in
grades 6 to 12 (weighted)
Variables Odds ratio (95% CI) *
Model 1 Active vs. Model 2 Mixed vs.
non-active non-active
Female 1.00 1.00
Male 1.45 (1.44, 1.45) *** 1.09 (1.09, 1.10) ***
Grade
6 1.00 1.00
7 1.10 (1.08, 1.11) *** 1.41 (1.39, 1.43) ***
8 1.03 (1.02, 1.05) *** 1.16 (1.14, 1.17) ***
9 1.25 (1.23, 1.27) *** 1.23 (1.21, 1.25) ***
10 1.06 (1.04, 1.08) *** 1.22 (1.20, 1.24) ***
11 0.86 (0.84, 0.87) *** 1.08 (1.06, 1.09) ***
12 0.73 (0.71, 0.74) *** 0.86 (0.85, 0.88) ***
Weight status
([dagger])
Normal weight 1.00 1.00
Underweight 1.03 (1.02, 1.05) *** 1.09 (1.08, 1.09) ***
Overweight 0.82 (0.82, 0.83) *** 0.86 (0.85, 0.88) ***
Physical activity
Each 1 unit 1.02 (1.02, 1.02) *** 1.01 (1.01, 1.01) ***
change in KKD
Smoking status
Non-smoker 1.00 1.00
Current smoker 1.64 (1.63, 1.66) *** 0.86 (0.86, 0.87) ***
Former smoker 1.05 (1.03, 1.08) *** 2.08 (2.04, 2.11) ***
Sedentary
behaviour
([double
dagger])
High 1.00 1.00
Moderate 0.95 (0.94, 0.95) *** 0.96 (0.96, 0.97) ***
Low 1.20 (1.16, 1.24) *** 0.54 (0.52, 0.56) ***
School location
([section])
Urban 1.00 1.00
Rural 0.15 (0.06, 0.38) *** 0.26 (0.13, 0.55) ***
Suburban 0.58 (0.27, 1.23) 0.59 (0.32, 1.09)
* Values are adjusted for all other variables in the model.
([dagger]) Weight status: Underweight (0-5th percentile BMI),
Healthy weight (6-84th percentile BMI), Overweight/obese (> 85th
percentile BMI).
([double dagger]) Sedentary behaviour: Low (< 1 hour/day),
Moderate (1-3 hours/day), High (> 3 hours/day).
([section]) School location: Rural (residential density < 400
people/[km.sup.2]), Suburban (population = 1000-99,999 and
residential density > 400 people/[km.sup.2]); Urban (population
[greater than or equal to] 100 000 and residential density > 400
people/[km.sup.2]).
CI = Confidence interval.
KKD = kilocalories per kilogram per day.
* p < 0.05, ** p < 0.01, *** p < 0.001.
Model 1: Active N = 600,900; Inactive N = 1,420,000.
Model 2: Mixed N = 699,400; Inactive N = 1,420,000.
Figure 1. Prevalence of active, inactive and mixed
commuting among Canadian students in Grade 6
to 12 by region, 2010/2011 (weighted)
Source: 2010/2011 Canadian Youth Smoking Survey.
Active N = 600, 900; Inactive N = 1420, 000; Mixed N = 699, 400.
Commuting Trends of Canadian Youth (%)
Active Inactive Mixed
Commuting Commuting Commuting
Atlantic Canada ([dagger]) 9.8 71.6 18.6
Quebec 15.1 59.3 25.6
Ontario 26.4 47.0 26.6
Prairies ([double dagger]) 16.5 60.0 23.5
British Columbia 30.3 40.0 29.7
([dagger]) New Brunswick, Nova Scotia, Prince Edward Island,
Newfoundland and Labrador.
([double dagger]) Alberta, Saskatchewan, Manitoba.
Note: Table made from bar graph.
