Effects of a school-based intervention on active commuting to school and health-related fitness
Villa-González et al. BMC Public Health
Effects of a school-based intervention on active commuting to school and health- related fitness
Emilio Villa-González 0 1
Jonatan R. Ruiz 0
Jason A. Mendoza
Palma Chillón 0
0 PROFITH “PROmoting FITness and Health through physical activity” research group, Department of Physical Education and Sport, Faculty of Sport Sciences, University of Granada , Ctra. Alfacar, s/n, 18011, Granada , Spain
1 Department of Physical Culture, School of Health Sciences, National University of Chimborazo , Avda. Antonio José de Sucre, Km. 1 1/2 vía a Guano, Riobamba , Ecuador
Background: Active commuting to school has declined over time, and interventions are needed to reverse this trend. The main objective was to investigate the effects of a school-based intervention on active commuting to school and health-related fitness in school-age children of Southern Spain. Methods: A total of 494 children aged 8 to 11 years were invited to participate in the study. The schools were non-randomly allocated (i.e., school level allocation) into the experimental group (EG) or the control group (CG). The EG received an intervention program for 6 months (a monthly activity) focused on increasing the level of active commuting to school and mainly targeting children's perceptions and attitudes. Active commuting to school and health-related fitness (i.e., cardiorespiratory fitness, muscular fitness and speed-agility), were measured at baseline and at the end of the intervention. Children with valid data on commuting to school at baseline and follow-up, sex, age and distance from home to school were included in the final analysis (n = 251). Data was analyzed through a factorial ANOVA and the Bonferroni post-hoc test. Results: At follow up, the EG had higher rates of cycling to school than CG for boys only (p = 0.04), but not for walking to school for boys or girls. The EG avoided increases in the rates of passive commuting at follow up, which increased in the CG among girls for car (MD = 1.77; SE = 0.714; p = 0.010) and bus (MD = 1.77; SE = 0.714; p = 0.010) modes. Moreover, we observed significant interactions and main effects between independent variables (study group, sex and assessment time point) on health-related fitness (p < 0.05) over the 6-month period between groups, with higher values in the control group (mainly in boys). Conclusion: A school-based intervention focused on increasing active commuting to school was associated with increases in rates of cycling to school among boys, but not for walking to school or health-related fitness. However, the school-based intervention avoided increases in rates of passive commuting in the experimental group, which were significantly increased in girls of the control group.
Physical activity; Active transport; Public health; Cardiovascular fitness
The increasing prevalence of obesity in Spain is a major
public health problem. Data from Spain reveals the
alarming increase of the prevalence of obesity in children
and youth, with a 15.9% of obesity prevalence in children
aged from 6 to 9 years . An analysis of the food habits
of this population describes that the energy consumption
has not increased in the recent past. As such, the decrease
in energy expenditure should have association with the
increasing prevalence of obesity. To address obesity, the
Spanish Ministry of Health and Consumer Affairs drew
up the Strategy for Nutrition, Physical Activity and the
Prevention of Obesity (NAOS), which aims to promote
healthy diets and encourage physical activity by all
citizens, with special emphasis on children. Currently, there
is evidence that active commuting to school (defined as
walking and cycling to and from school) may have
important health implications for youth. Previous reviews [2, 3]
reported a positive association between active commuting
to school and overall physical activity levels. Further,
active commuting to school has been positively associated
with higher cardiorespiratory fitness in young people
[4, 5] and there is some evidence of a relationship with
other health-related fitness markers . A 12-week
schoolbased intervention study investigated the association
between active commuting to school and physical
fitness variables, and showed that 10–13 year old children
who cycled to school improved their cardiorespiratory
fitness . A cross-sectional study showed that 15–19
years old adolescents who bicycled to school had higher
aerobic power, muscle endurance and flexibility than
walkers or passive commuters .
The Spanish rates of active commuting to school have
declined dramatically over the past several years , and
belonging to a large family was a main correlate of active
commuting to school among Spanish children. Initiatives
such as Safe Routes to School, the Walking School Bus,
the Walk to School, or the School Travel Plan program,
have been implemented to increase children’s walking and
cycling to school with some success. A systematic review
 concluded that more research with higher quality
study designs and measures should be conducted to
determine the most successful strategies for increasing active
commuting to school. Some intervention studies reported
an increase in the percentage of active commuting to
school; however, the degree of change varied widely from
3 to 64% .
The main objective of the present study was to
investigate the effects of a school-based intervention on
active commuting to school and health-related fitness
in school-age children of Southern Spain. Our
hypothesis was that a school-based intervention focused on
increasing the frequency of active commuting to and
from school would increase the levels of active
commuting to school and thereby improve
A total of 494 children aged 8 to 11 years were invited
to participate in the study. From these, 469 children
(94.9% of the total sample: 251 boys, 218 girls) were
included in the final analytic sample due to having valid
data on commuting to school. Participants were recruited
from five public schools in the provinces of Granada
(Salobreña, n = 119; Huétor Vega, n = 80; Santa Fe, n = 96;
the city of Granada, n = 128) and Jaén (Castillo de
Locoubín, n = 46) to participate in an intervention to increase
walking and cycling to school. Children with valid data on
commuting to school at baseline and follow-up, sex, age
and distance from home to school were included in the
final analysis (n = 251; 50.8% of the invited sample).
Non-random allocation to experimental group (EG) or
control group (CG) was performed at the school-level.
We conducted a quasi-experimental trial with a total of
141 participants from 3 schools in Salobreña, Huétor
Vega and Santa Fe, which took part in the experimental
group (EG) and received a 6-month intervention program
focused on increasing active commuting to school. A total
of 110 participants from 2 schools in Granada and Castillo
de Locoubín took part in the control group (CG), who did
not receive the intervention. EG schools were assigned by
the local government (Diputación de Granada) and
municipalities. Control schools were selected for comparison
by the researchers based on having similar characteristics
(socioeconomic level and setting – urban vs. rural) as the
experimental schools. Participants did not know the
assignment prior to being recruited. All the schools were
public and primary education schools within the National
Educational System. A flow chart corresponding to the
study design is shown in (Fig. 1). The outcome measures
were taken during school days prior to (baseline) and after
(follow-up) the intervention program in the months of
January and June of the academic year 2011/2012 in every
school, respectively. All measurements were taken in the
same period and the five schools belonged to the same
region and had similar weather conditions, i.e., average
temperature in January was 10 °C and in June was 20 °C
(https://www.wunderground.com). The study was
conducted within a public health initiative lead by Diputación
de Granada (Área de Medio Ambiente). The purpose of
this program was to promote safe and healthy ways of
commuting from home to school. An agreement was
signed by the school board (decision-making body of a
school), Diputación de Granada and the municipalities.
The school board, parents and students were informed
about the study and they agreed to participate.
The intervention focused on increasing the frequency of
active commuting to and from school among children.
Both teachers and the research team implemented the
intervention program at each school. The intervention
period lasted two school terms (6 months) from January
to June of 2012. Children from the EG participated in 6
monthly activities within the intervention program (each
activity ranged from 60–120 min each month) during
school hours in addition to their regular Physical
Education lessons. The intervention included: (i) introductory
activities such as a questionnaire on the mode of
commuting to school reported by families (parents or
grandparents). The objective of this activity was to know how
the families commuted in his/her youth and consider
whether currently, there were barriers to active
commuting to school for their children. (ii) Reading a story and
performing scenes related to active commuting to school.
The objective of this activity was to familiarize the
children with active commuting to school and the
neighborhood. (iii) Activity on knowledge about the
environmental characteristics around the school. The objective
was to know the urban environment (measuring the size
of sidewalks and crosswalks, understanding the traffic
signs) in the area surrounding the school. (iv) Activity on
road safety. The objective was to promote road safety, and
analyze the relation between vehicles (cars and bikes) and
pedestrians (supporting older people to cross crosswalks,
interviewing pedestrian and drivers, warnings for
inadequate behaviors of motor vehicle drivers and cyclists) (v)
Activity on behaviors in the street. The objective was to
know the appropriate behaviors of pedestrians, vehicles
and traffic police (measuring the time to cross a crosswalk
and the vehicle’s speed, collaborating with the traffic
police) (vi) Activity on traditional games. The objective was
to practice traditional games that were adapted to the
topic of road safety education and active commuting to
school (playing cooperative games integrating ethical and
social behaviors as if they were citizens and traffic police).
A summarized scheme of the study design is presented in
(Fig. 2). These activities were carried out in the classroom
Fig. 2 Summary of the study design. PE, Physical Education
(i to ii) and in the school neighborhood (iii to vi). Children
in the CG and EG received the usual Physical Education
sessions according to the National Education Program in
Spain, i.e. 55 min sessions twice per week.
Mode of commuting to school
Participants completed a self-report questionnaire
regarding the latest weekly patterns of commuting to and
from school (Monday to Friday). The questionnaire has
been proposed as the most appropriate measurement for
asking about mode of commuting to school after
reviewing 158 studies within the scientific literature . The
questionnaire included sociodemographic data and a
question about the frequency and mode of commuting:
How did you commute to and from school the last week?.
The modes of commuting were: 1) walking, 2) cycling, 3)
car, 4) motorcycle or 4) bus. While this particular question
for assessing commuting to school has not been formally
validated, it is very similar to other 1-item questionnaires
on children’s commuting to school that have demonstrated
acceptable validity in this age group [11–13]. Walking and
cycling were categorized as active commuting, whereas
travelling by car, motorcycle and bus were categorized as
passive commuting. Children completed the questionnaire
with the help of the teacher and the research team in about
20 min. The weekly frequency of commuting to school was
expressed as numbers of active travels per week to and
from school (range: 0 to 10). A Spanish and English version
of the questionnaire is provided at http://profith.ugr.es/
Physical fitness was assessed by the ALPHA
healthrelated fitness test battery of high priority , which is
a valid and reliable fitness test battery for children and
adolescents. All participants completed the fitness tests
during physical education class. The same researchers
performed all the measurements. Measurements were
organized in a circuit, and participants performed each
test consecutively, except the cardiorespiratory fitness test
where several participants performed it at the same time.
Cardiorespiratory fitness was assessed by the 20-m
shuttle run test . In brief, the child was required to
run between 2 lines 20 m apart while keeping pace with
audio signals emitted from a prerecorded CD. The initial
speed was 8.5 km/h, and the speed was increased by
0.5 km/h per minute. The test was completed when the
participants failed to reach the end lines concurrent with
the audio signals on 2 consecutive occasions, or when
the participants stopped because of fatigue. The
equations of Leger  previously validated in children and
adolescents, were used to estimate maximum oxygen
consumption (VO2max) from the test scores.
Lower body muscular fitness was assessed by means of
the standing long jump. The child stood behind the
starting line, with feet together, and pushed off vigorously and
jumped forward as far as possible. The distance was
measured from the takeoff line to the point where the back of
the heel nearest to the takeoff line landed on the mat or
non-slippery floor. The test was repeated twice, and the
best score was retained (in cm).
Upper body muscle strength was assessed by means of
handgrip strength using a hand dynamometer with
adjustable grip (TKK 5401 Grip D; Takey, Tokyo, Japan).
Children were given a brief demonstration and verbal
instructions for the test and, if necessary, the
dynamometer was adjusted according to the child’s hand
size. The test was done in the standing position with
the wrist in the neutral position and the elbow extended.
Children were given verbal encouragement to ‘squeeze as
hard as possible’ and apply maximal effort for at least 2 s
(sec). Two attempts per hand were performed. The
average of the best scores achieved by each hand was used in
Speed-agility was measured by the 4×10 shuttle run
test. Two lines, at a distance of 10 m, and two cones
were placed at the distant line. The participants ran as
fast as possible from the starting line, picked up one
sponge at the distant line, returned to the start line and
placed the cone on this line, before repeating the same
run and retrieving the second sponge. Two attempts
were performed, and the best score was retained (in sec).
The agility measure was the time to complete this 40-m
run with correct placement of the cones.
Distance to school
The distance from home to school was estimated using
the Internet program Google Maps V.6 . The shortest
network path between each student’s home address and
school was measured in meters.
Differences in socio-demographics characteristics (sex, age
and distance from home to school) between included and
excluded participants were compared using the chi-square
test for categorical variables and Mann–Whitney U test
for non-normal continuous variables. Differences in the
distance from home to school between CG and EG were
tested using the Mann–Whitney U test. The normality of
the fitness test variables was tested using the
KolmogorovSmirnov test. The participants were analyzed by study
group (CG or EG), sex (boys and girls) and assessment
time point (baseline and follow-up). Thus, a 2×2×2
Factorial ANOVA was used to analyze the interactions and
main effects of the three independent variables or factors
(study group, sex and assessment time point) on
frequency of active commuting, modes of commuting and
health-related fitness. Age and distance were used as
covariates. Post-hoc comparisons were performed by
Bonferroni test. Level of significance was set at 0.05. Analyses
were performed using the PASW (v. 20.0 for Windows,
Chicago, IL, USA).
There were significant differences between included and
excluded participants for age only; included participants
had a lower age than excluded participants (9.13 vs.
9.51 years; p < 0.01). No other differences between
included and excluded participants were observed for sex
and distance to school. Examining baseline data, there
were differences between the CG and EG for distance
from home to school whereby the CG had a greater
distance than the EG (1467.0 vs. 604.6 m; p < 0.01). Children
with valid data on commuting to school at baseline and
follow-up, sex, age and distance from home to school were
included in the final analysis (n = 251).
Interactions and main effects of study groups, sex and
assessment time point on frequency of active commuting
and on modes of commuting
No significant interactions between any independent
variable (study groups, sex and assessment time point)
on frequency of active commuting (number of active
travels per week) and on modes of commuting (number
of travels per week) were observed. However, a
significant main effect of the independent variable study
groups was detected on the frequency of active
commuting (F[1, 565] = 15.04, p < 0.001, 2p = 0.02), and several
modes of commuting: walk (F[1, 565] = 14.41, p < 0.001,
ƞ2p = 0.025), car (F[1,565] = 9.49, p = 0.002, ƞ2p = 0.01)
and bus (F[1,565] = 11.08, p = 0.001, ƞ2p = 0.019). The
Bonferroni pair comparisons of active commuting to
school and mode of commuting by study group, sex and
assessment time point are presented in Table 1.
Interactions and main effects of study groups, sex and
assessment time point on health-related fitness
Several significant interactions in all health-related fitness
tests were observed. Significant interactions between study
groups and sex, and between study groups and assessment
time point were observed for VO2max (F[1,486] = 18.92,
p < 0.001, ƞ2p = 0.03 and F[1, 486] = 13.44, p < 0.001,
ƞ2p = 0.02, respectively), 20-m shuttle run test (F[1,
489] = 19.81, p < 0.001, ƞ2p = 0.03 and F[1, 489] = 12.33,
p < 0.001, ƞ2p = 0.02, respectively), and standing long
jump test (F[1, 490] = 6.74, p = 0.010, ƞ2p = 0.01 and
F[1, 490] = 7.11, p = 0.008, ƞ2p = 0.01, respectively).
Significant interactions between study groups and
assessment time point was observed for handgrip strength test
(F[1, 495] = 14.48, p < 0.001, ƞ2p = 0.03). In the 4 × 10
shuttle run test a significant interaction between study
groups and sex was observed (F[1, 489] = 6.41, p = 0.01,
ƞ2p = 0.01).
Main effects of the study groups and sex were observed
in VO2max (F[1,489] = 6.92, p = 0.009, ƞ2p = 0.01 and F[1,
489] = 51.43, p < 0.001, ƞ2p = 0.09, respectively) and in
20m shuttle run test (F[1,489] = 7.93, p = 0.005, ƞ2p = 0.04
and F[1, 489] = 59.97, p < 0.001, ƞ2p = 0.02, respectively).
Main effects of the assessment time point were observed
in 20-m shuttle run test (F[1,489] = 12.51, p < 0.001, ƞ2p =
0.02) and 4 × 10 shuttle run test (F[1,489] = 8.08, p =
0.005, ƞ2p = 0.02). Main effects of sex were observed for
standing long jump test (F[1,490] = 36.39, p < 0.001,
ƞ2p = 0.07), handgrip strength (F[1,495] = 4.12, p = 0.043,
ƞ2p = 0.08), and 4 × 10 shuttle run test (F[1,489] = 24.06,
Table 1 Active commuting to school and mode of commuting by study group, sex and assessment time point (Continued)
Data are shown as mean and standard deviation adjusted by age and distance
EG experimental group, CG control group, SD standard deviation
aNumber of active travels to and from school per week (Range: 0–10). Factorial ANOVA analysis (study group, sex and assessment time point). Pair comparisons by
Bonferroni test. Statistical differences (p < 0.05). Statistical signals are presented in the higher mean of the pair comparisons: bEG vs CG; cboys vs girls
p < 0.001, ƞ2p = 0.04). The Bonferroni test for
healthrelated fitness by study groups, sex and assessment
time point are presented in Table 2.
The analyses were repeated using the log-transformation
of the frequency of active travels per week (n°/week) and
the results remained consistent. The analyses were repeated
including school as a covariate and the results remained
consistent. Intention-to-treat analysis was used by last
observation carry-forward and the results remained constant
(data not shown).
The current school-based intervention focused on
increasing children’s active commuting to school was
associated with a small but significant increase in cycling to
school at follow-up only for boys compared to controls
(p = 0.04), but was not associated with increases in rates
of walking to school or health-related fitness for boys or
girls. However, the school-based intervention avoided
increases in rates of passive commuting in the EG, which
were significantly increased in the CG. The increase in
passive commuting in the CG was in girls, for car and
bus modes. Moreover, we observed significant interactions
and main effects between independent variables (study
groups, sex and assessment time points) on health-related
fitness over the 6-months period between CG and EG,
with higher values in the CG, and mainly in boys.
Previous school-based intervention studies that
promoted active commuting to school among children have
found increases in the rates of active commuting to
school (increasing walking or cycling to school) [17, 18],
daily physical activity levels (total daily steps) [19–21], and
several behaviors (children’s pedestrian safety behaviors)
[22, 23]. However, there is little evidence on fitness-related
outcomes . Comparisons between studies should be
interpreted cautiously, because the scope and content of
the interventions to increase active commuting to school,
the measurement of the main outcome (active commuting
to school) and the socioeconomic and geographical
contexts differ .
Active commuting to school
Most of the identified studies that implemented
schoolbased interventions promoting active commuting to
school reported a positive effect on the rate of active
commuting to school [17–19, 24–28]. The increase in active
commuting across these studies ranged from 2 to 63%.
Consistent with those studies, our study showed a modest
increase in cycling to school at follow-up for boys in the
EG. Other studies reported no effect on changing rates of
active commuting to school [7, 23, 29], which is consistent
with our results, where after intervention, the EG did not
increase the frequency of active commuting (walking and
cycling together), however, the intervention avoided
increases the rates of passive commuting, whereas CG
increased passive commuting (car and bus modes) mainly in
girls. The lack of change in walking to school could be
attributed to the intervention being of insufficient intensity
and duration, i.e. one activity per month during 6-months
across the intervention such as in the present study may
be insufficient to produce behavior change. In Norwegian
children, the intervention had no significant impact on
cycling to school, since a high rate of children reported
cycling to school prior to the intervention . In contrast
the present study, which had low rates of cycling to school
at baseline, the intervention was associated with a modest
but significant increase in cycling to school among boys
only (p = 0.04). In Canadian children there was no
significant increase for active commuting to school at follow-up
after a one-year intervention. However, there was
considerable variation in active commuting at the school level
. In British children, there was no evidence for
changing the mode of commuting at follow-up , also
possibly due to the low intensity of the intervention (16 h of
expert assistance over one school year). Experimental
trials that showed significant changes to active commuting
to school had more intensive and durable intervention
Table 2 Health-related fitness by study groups, sex, assessment time point
Health-related fitness Study groups Sex Assessment time point
VO2max (mL/kg per min) EG boys
20-m suttle run (stage)
Hand-grip strength (kg)
Data are shown as mean and standard deviation adjusted by age and distance
EG, experimental group; CG, control group; SD, standard deviation
Factorial ANOVA analysis (study group, sex and assessment time point). Pair comparisons by Bonferroni test. Statistical differences (p < 0.05). Statistical signals are
presented in the higher mean of the pair comparisons: aEG vs CG; b boys vs girls and cbaseline vs follow-up
time with the children, e.g. adult-chaperoned walk to
school groups offered daily or twice daily [21, 25], rather
than once monthly.
analyses, the results may reflect inherent group differences
between EG and CG and may not necessarily be entirely
attributable to the active commuting to school intervention.
In the current study we found a significant difference
between groups on physical fitness variables (i.e.,
cardiorespiratory fitness, muscular fitness and speed-agility)
after the intervention with higher values in the CG. To
the best of our knowledge there is little evidence of the
effect of school-based interventions to increase active
commuting to school on health-related fitness. A
previous study investigated the effect of a 12-week
cycling-toschool intervention on cardiorespiratory fitness, and
children who cycled to school improved their
cardiorespiratory fitness . At follow up, a significant difference
between those starting cycling and those who did not
start cycling was observed for VO2peak. Different results
were observed in the current study, since we found that
the EG had significantly greater decreases in VO2max
and 20-m shuttle run tests compared to the CG. There
is previous cross-sectional evidence that commuting by
cycling is associated with expected physical fitness
variables such as aerobic power or muscle endurance, and
even other unexpected physical fitness variables such as
flexibility; however, other physical fitness variables such
as muscle strength or speed-agility did not differ between
bikers and walkers or passive commuters . In the
previous two studies, a high percentage of the participants used
cycling for commuting to school and the health-related
fitness effects could be studied. In the current study, only
a 0.1% of the participants cycled to school, which is too
small in size to consider its effects. Most of the
participants in the current study walked to school and the
walking rate did not show significant differences after the
intervention in either the EG and CG. On the other hand,
there is previous cross-sectional evidence that walking as
a mode of commuting may be insufficient to modify
health-related fitness [4, 30]. However, the results in the
current study showed that the health-related fitness levels
in the CG improved more than in the EG at follow-up.
Mostly, boys in both groups (CG and EG) presented better
health-related fitness than girls at baseline and follow-up.
We speculate that other variables not included in the
current study such as differences in total daily physical
activity, sexual maturation or dietary intake might explain
the observed health-related fitness improvement in the
participants from the CG. Furthermore, the CG had a
longer distance from home to school than EG; consequently,
the CG had to cover longer walking and cycling distances
which provide a greater opportunity for improvement in
their physical fitness levels compared to the EG.
Moreover, since the present study had nonrandom allocation to
EG or CG and had substantial participants dropped from
The present intervention was focused mainly on children
and not on parents. The intervention was based on the
conceptual framework of active travel in children
proposed by Panter  targeting mainly individual factors
such as children’s perceptions (safety perception on the
way to school) and attitudes (independence or motivation
to walk). The intervention weakly targeted other
determinants previously described, such as the urban form
or parental perceptions [32–34]. However, Spain is a
novel country regarding the implementation and
evaluation of interventions to promote active commuting to
school and the effectiveness of these programs are still
unknown. The inclusion of strategies which promote
ACS should be carried out and evaluated progressively.
The first step is to conduct interventions focused on
changing children’s and families’ perceptions about the
awareness of active commuting to school. The second
step is to create more ambitious interventions which
include changes to the environment and/or provides
opportunities to walk to school (e.g. Safe Routes to
School encouragement programs). The effectiveness of
interventions on active commuting to school is related
to three main elements: schools, parents, and communities
. These were included in the current school-based
intervention study, but the involvement of both parents and
communities was weak, and the involvement of the school
might be insufficient for success. However, our study
showed a modest increase in cycling to school at follow-up
for boys in the EG, although we only carry out an activity
related to cycling to school (iv: Activity on road safety).
Parents participated in one activity (activity i) and the
community participated in two activities (activity iv and v)
with support from police, neighbors and municipalities.
The interventions with the highest effectiveness 
reported strong involvement of schools through principals
and teachers working actively in the intervention.
However, in the current intervention, all schools agreed to
participate in the intervention through the principals, but the
involvement of some teachers was poor and this could
affect the motivation of children to actively commute to
school. Furthermore, the dose of the intervention could
be insufficient, since this only included one activity per
month. Previous successful active commuting to school
interventions have provided daily opportunities for the
intervention [21, 25]. Another reason for explaining the
lack of effectiveness might be the lack of financial
support. Several studies had financial support for providing
resources and staff for the intervention but in the current
study, there was no similar financial support .
The present intervention study has limitations and
strengths. We conducted a quasi-experimental design (no
group randomized allocation) with a self-reported
questionnaire administered to children that does not have
established validity evidence. There was a relatively small
final sample size, with 50% of participants which were
dropped from analyses (CG = 63%, EG = 47%) due to
missing data mainly on distance from home to school, since
children did not provide a full and accurate home address.
External validity is limited due to the relatively narrow
age range and the small number of schools in cities
from a single country, although this information is very
important to implement future interventions in Spain.
Additionally, there was no information on participant’s
socio-economic status (SES) and weather conditions. The
method used to estimate home-school distance (Google
Maps) may not represent the actual route taken as well as
the shortest distance from home to school. Unfortunately,
we were not able to measure total daily physical activity or
dietary intake, which may influence our results. A major
strength of the study is the measurement of different
components of fitness through several physical fitness tests
and the rigorous analyses of the school-based
intervention including both EG and CG that allow comparisons
between groups. Future research should focus on how to
assist children and their families to use active travel
behaviors in the longer term, with a focus on more intensive
A school-based intervention focused on increasing active
commuting to school was associated with increasing
rates of cycling to school among boys only, but was not
effective on increasing the rates of walking to school and
the health-related fitness. However, the school-based
intervention avoided increases to the rates of passive
commuting in the experimental group, which were significantly
increased in girls of the control group. These findings have
important implications for research reporting the
implementation of an intervention to promote active commuting
to school. Future work should seek to build on this
foundation by incorporating more rigorous research designs,
including objective measures, random experimental group
assignment, and longitudinal sampling.
ALPHA: Assessing levels of physical activity; BMI: Body max index; CG: Control
group; Cm: Centimeters; EG: Experimental group; Km/h: Kilometers per hour;
M: Meters; M2: Meters squared; S: Seconds; SD: Standard deviation;
SES: Socio-economic status; VO2max: Maximal oxygen consumption;
WC: Waist circumference
The authors acknowledge the help of the participants that took part in the
study and thank their parents for their collaboration. We are grateful to the
research team who helped in the field tests and questionnaires in schools
and they were undergraduate university students.
EV participated in the design of the study, collection of data, data cleaning
and wrote the manuscript. JR performed the statistical analyses, contributed
to the interpretation of the results and revised the manuscript critically. JM
contributed to the interpretation of the results and revised the manuscript
critically. PC conceived and coordinated the study, contributed to its design,
statistical analysis, interpretation of the results and revised of the manuscript.
All authors approved the final version of the manuscript.
Consent for publication
Ethics approval and consent to participate
The Medical Ethics Committee of Hospital Virgen de las Nieves (Granada, Spain)
approved the study design, study protocols and informed consent procedure
(case n°\ 817, 26-9-2013). Written consent from parents was obtained.
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