BJMB
Brazilian Journal of Motor Behavior
Research Article
!
Silva, Bezerra,
Cancela
2021
VOL.15
N.2
107 of 117
Young adults’ physical activity and physical function: 12 months follow up
BRUNO SILVA
1,2*
| PEDRO BEZERRA
1,2
| JOSÉ M. CANCELA
3
1
Escola Superior de Desporto e Lazer, Instituto Politécnico de Viana do Castelo, Melgaço, Portugal.
2
Research Center in Sports Science, Health and Human Development (CIDESD), Vila Real, Portugal.
3
Faculty of Education and Sports Science, University of Vigo, Pontevedra, Spain.
Correspondence to:!Escola Superior de Desporto e Lazer, Portugal, Complexo Desportivo e Lazer Comendador Rui Solheiro, Monte de Prado, Zip Code 4960-320,
Melgaço, Portugal.!Tel.: +351-258-809-678.
email: silvabruno@esdl.ipvc.pt
https://doi.org/10.20338/bjmb.v15i2.200
HIGHLIGHTS
• After 12 months, young adults’ physical
function accessed by the Functional Movement
Screen changes in accordance with gender and
habitual PA.
• Functional Movement Screen may be sensitive
to improvements or decrements due to
contextual environments that over-or under-
produce the stimulation required to develop
those skills.
• Sports Science university students’ daily
routines may be interceding physical activity
patterns and consequently PFn.
• After 12 months, Sports Science men students
improve more sports-specific physical function
skills.
• After 12 months, Sports Science women
students improve total physical function and
core stability tasks.
ABBREVIATIONS
ASLR Active straight-leg raise
DS Deep squat
EF Effect size
FMS Functional Movement Screen
HS Hurdle step
ILL In-line lunge
PA Physical activity
PFn Physical function
RS Rotary stability
SM Shoulder mobility
TSP Trunk stability push-up
PUBLICATION DATA
Received 26 09 2020
Accepted 06 01 2021
Published 01 06 2021
BACKGROUND: The knowledge about university students generally demonstrates that they do not meet current
recommendations for Physical Activity (PA). However, PA and Physical Fitness are not an indicator for Physical
Function (PFn), being PFn a separate construct that is related to movement skill proficiency.
AIM: To analyze the rate of changes in PFn accessed by the Functional Movement Screen (FMS) and PA levels
(sports and leisure) in a group of Sport Science university students after one year.
METHOD: 41 men (22.3±5.7years) and 22 women (20.7±0.9years) participated in this research. The data were
collected in the first month of the academic year and after 12 months in the following order: Baecke Habitual
Physical Activity Questionnaire, anthropometrics, and FMS.
RESULTS: PFn assessment, from baseline to second assessment, revealed significant changes in Trunk Stability
Push-up (p=0.003; ES=0.656) and total score (p=0.026; ES=0.497) for women and in Deep Squat (p=0.003;
ES=0.334) for men. No significant changes were found in women PA levels. Men decreased in leisure PA
(p=0.002; ES=0.538) and total PA (p=0.003; ES=0.519).
CONCLUSION: Sports Science university students’ daily routines may mediate physical activity patterns with
following physical function improvements or decrements, occurring due to contextual environments that over-or
under-produce the stimulation required to develop those skills.
KEYWORDS: Functional fitness | University students | Physical fitness | Functional Movement Screen
INTRODUCTION
The literature demonstrates that university students do not meet current
recommendations for physical activity (PA) levels
1
and are less active than children and
adolescents.
2
The transition from high school to college involves the development of
individual habits. During this transition, students undergo emotional, physiological, and
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environmental changes that influence several behaviors (e.g., consumer habits and lifestyle
aspects, such as PA and weight status).
3
Generally, studies from different cultures and countries demonstrate that female
students tend to be more sedentary and perform less PA than male students.
1,4
A recent
study compared university students from the Vocational School of Health Services, the
School of Physical Therapy and Rehabilitation, the Faculty of Nursing, the School of Sports
Sciences and Technology, and the Faculty of Medicine. The study revealed that students
from the School of Sports Sciences performed more PA than other students.
4
This factor
was mediated by being involved in PA in earlier years and the fact that these students’ family
members also tended to be physically active. According to other schools, these students
were considered a reference point for determining physical inactivity status.
4
Being involved
in PA practice early in life and continuing this involvement as a lifestyle choice can influence
one’s involvement in PA during later years.
5
Moreover, university students who engage in
PA use on-campus sports facilities—one of the most often cited reasons for physical
inactivity is inadequate on-campus sports facilities.
4
A few studies have analyzed PA
patterns in university students in Portugal.
1
However, recently research that includes very
active university students demonstrated that similar than in children and adolescents, the
levels of motor competence positively influence weight status.
6
For practical reasons, most studies use questionnaires to assess PA.
7
In general,
these questionnaires are designed to minimize potential confounding effects. However,
there is no consensus on which questionnaire is the best among the several validated and
widely used but the need to choose the questionnaire that best suits the objectives.
8
However, this information is not an indicator of physical function (PFn) related to
movement skill proficiency.
9
PFn and physical fitness are separate constructs.
10
PFn is more closely associated
with functional movement, which relates to the body’s multi-planar and multi-joint
movements (specifically, simultaneous mobility and stability) and optimal movement.
11
Optimal movement can be defined for all age ranges and trends to refine coordination,
strength, and endurance, concluding in improvements to daily living activities, physical well-
being and/or sports performance.
12
Gray Cook et al.
13
developed the Functional Movement Screen (FMS) to perform
pre-participation functional evaluations. This screening tool comprises a battery of tests to
evaluate joint mobility and stability simultaneously based on a series of seven movements.
13
Although none of the tests was designed with a specific sport in mind, they challenge the
upper and lower extremities and the trunk to establish which physical or functional limitation
is the most significant.
13
The current knowledge about the relationship between FMS and PA is limited. Some
research demonstrate that FMS scores can change during a soccer or volleyball season
among collegiate players.
14
However, recent studies demonstrate that FMS is only linked to
motor competence stability and not to all motor competence constructs (locomotor,
manipulative, and stability)
15
,thus, might be suitable for determining PFn but not for
discriminating performance.
16
This is because it has been linked to only some sport-specific
performance tasks.
17
Compared to men, women have lower mean motor competence values
and perform differently in some FMS tasks.
15
Men usually yield higher scores in the FMS
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trunk stability push-up test, while women perform better in the FMS active straight leg raise.
15
Therefore, this research aimed to analyze the rate of changes in PFn accessed by
FMS and PA levels (sports and leisure) in a group of sports science students after one year.
METHODS
Participants
All participants were volunteers, consisting of 41 men (22.3±5.7 years; 74.0±1.4 kg;
176.7±0.9 meters) and 22 women (20.7±0.9 years; 59.4±1.7 kg; 162.5±1.1 meters).
Participants had no motor, cognitive, or health impairments that could affect their
performance. The criteria of inclusion were: (i) be enrolled and attending the Sports and
Leisure degree; (ii) participate in both assessments (before and after one-year); (iii) be
enrolled in more than 60% of the sports applied disciplines; (iv) injury-free at the time of the
evaluation (injury is understood as any complaint of physical or psychological parameters
that result in instability to practice or normally complete in a particular sport or physical
activity); (v) at the end of the academic year do not fail any practical disciplines due to
absenteeism.
After being briefed about the study design and potential risks and benefits of their
participation, participants signed a free informed consent following the ethical standards for
the study in humans as suggested by the Declaration of Helsinki. The study was approved
by the Scientific Council (CTC-ESDL-CE002-2017).
Procedures
All participants had their anthropometrics, habitual physical activity, and physical
function assessed. Firstly, to characterize the Physical Activity profile, all subjects fulfilled
the Habitual Physical Activity Questionnaire validated for the Portuguese Population
18
and
gave their informed consent. During the morning, the assessments were made in an indoor
facility with groups of around 20 participants at an average temperature of 26° C and relative
humidity of 18°. The data were collected in the biomechanics laboratory in the first month of
the academic year (from October to November) and repeated after 12 months. The tests
were conducted in the following sequence: Physical Activity questionnaire; anthropometric
and physical function.
Habitual Physical Activity Questionnaire
The Portuguese version of the Baecke Habitual Physical Activity Questionnaire
18
was applied. This 12 months retrospective questionnaire comprehend habitual physical
activity scores that includes eight items grouped in two dimensions: 1- Physical Activity –
Sports (4 items) - evaluate the physical activity performed in the sport or programmed
physical exercise practiced during leisure hours and 2- Physical Activity – Leisure (4 items)
– evaluate physical activity in activities other than sport, practiced during leisure time (e.g.,
walking, cycling). The answers are scored on a five-point scale, except for the sports
question, with a higher score for each item corresponding to higher physical activity. Each
of the two groups or dimensions results in a partial index of physical activity (Sports and
Leisure). The total physical activity was calculated by the sum of the two partial values.
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Anthropometric
During the evaluations, all participants stood barefoot and dressed in light clothing
with the heights measured through a portable stadiometer (SECA 217, Germany) and body
mass with a scale (SECA 760, Germany). Height measurements were rounded to the
nearest 0.1 cm, with the head oriented according to the Frankfurt plane and body mass to
the nearest 0.5 kg.
Physical Function
Physical function was measured following the battery developed by Gray Cook and
associates.
13
The Functional Movement Screen (FMS) is a screening tool that simplifies the
assessment of fundamental movement patterns
13
according to seven movements – deep
squat (DS), hurdle step (HS), in-line lunge (ILL), shoulder mobility (SM), active straight-leg
raise (ASLR), trunk stability push-up (TSP), and rotary stability (RS) – and three clearing
examinations. The clearing examinations (shoulder clearing test, spinal extension clearing
test, and spinal flexion clearing test) were not scored. However, they were performed to
determine whether the participant was able to perform the assessments. Three attempts of
each pattern were completed, and the best-performed repetition was scored on a scale of 0
to 3 as follows: 0 = pain anywhere in the body; 1 = unable to complete the movement pattern
or unable to assume the position to perform the movement, 2 = able to complete the
movement but must compensate in some way to perform the fundamental movement, 3 =
able to perform the movement correctly without any compensation, complying with standard
movement expectations associated with each test.
13
A certified FMS specialist with four years of experience conducted the tests
according to the standard protocol
13
with an official FMS test kit. Approximately 10 seconds
of rest were provided between trials, and one minute of rest was allowed between tests.
Except for the DS and TSP, each side of the body was assessed unilaterally with the best
scores for each of the seven tests registered for analysis and used to calculate a composite
score.
These assessment protocols' reliability has been established with moderate to
excellent levels of agreement in trained raters.
13
For each FMS test, all participants were
assigned to one of the three groups (low, medium, and high limit) according to the archived
score (0 or 1 = low, 2 = medium, 3 = high).
Statistical Analyses
Averages and 95% confidence intervals for lower and upper limits were calculated
according to descriptive statistics. After applying the Shapiro-Wilk test in conjunction with a
histogram, it was verified that the sample distribution was not normal, and the Wilcoxon
signed-rank test was applied. The effect size (ES) to non-parametric tests was obtained
19
:
r
!
=
|z|
√
N
, where N is the total sample size, and the value of z is reported after applying the
Wilcoxon signed-rank test. The classification of ES was obtained by using the following
criteria (19): very small effect (r <0.1); small effect (0.1 ≤ r <0.3); medium effect (0.3 ≤ r <
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0.5); and large effect (r ≥ 0.5). The analyses were performed separated by gender since
women tend to be less physically active than men
1,4
and perform differently in specific FMS
tasks.
15
Percentages of difference were calculated using a Microsoft Excel spreadsheet by
determining the coefficient of variation (by dividing the standard deviation by the mean and
multiplying the result by one hundred) of each variable and then subtracting the first
assessment values and the second assessment. The use of the variation coefficient allows
the observation of the extent of variation concerning the mean, thus increasing the precision
of comparisons of different values measures. The remaining statistical analyses were done
using the Statistical Package for Social Sciences (SPSS, Version 25.0, Chicago, IL) with the
significance level set at p< 0.05.
RESULTS
A drop out of 4.5% for women in the FMS assessment and 19.5% in the
anthropometric and PA assessment for men was verified.
Significant improvements between the first and second assessments of women
were found in FMS TSP (p= 0.003) and FMS total score (p= 0.026) (Table 1).
Significant improvements between assessments were found on FMS DS (p= 0.003)
in men (Table 2).
Table 1 – Differences between the first and second physical function assessments for women.
.
N=21
1
st
Assessment
Mean (SD)
[95%CI]
2
nd
Assessment
Mean (SD)
[95%CI]
Percentage
difference
Effect
size
FMS Squat
2.1 (0.2)
[1.7 – 2.4]
2.2 (0.1)
[2.0 – 2.4]
5.0%
0.178
FMS Hurdle Step
1.6 (0.1)
[1.3 – 1.9]
1.9 (0.1)
[1.7 – 2.2]
1.0%
0.350
FMS In Line Lunge
2.1 (0.2)
[1.8 – 2.4]
2.2 (0.1)
[2.0 – 2.4]
5.0%
0.126
FMS Shoulder Mobility
2.1 (0.2)
[1.7 – 2.5]
2.2 (0.2)
[1.8 – 2.5]
0.4%
0.126
FMS Straight Leg Raise
2.8 (0.1)
[2.6 – 3.0]
2.6 (0.1)
[2.4 – 2.9]
- 0.3%
0.178
FMS Rotary Stability
2.0 (0.0)
[2.0 – 2.0]
1.9 (0.1)
[1.7 – 2.1]
- 5.3%
0.218
FMS Trunk Stability Push-up
(0.1)
[0.8 – 1.3]
1.9 (0.1)*
[1.3 – 2.5]
14.7%
0.656
FMS total score
13.8 (0.5)
[12.7 – 14.8]
15.0 (0.6)*
[13.8 – 16.1]
0.4%
0.497
FMS - Functional Movement Screen;
*
significant differences, p<0.05;
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Women significantly increased the body mass (p = 0.000). Descriptive statistics of
anthropometric conducted on women can be found in Table 3. No significant changes in PA
levels were found in women.
Table 4 presents the descriptive statistics of anthropometric and PA levels of men
in both assessments. It was also observed a significant decrease in leisure PA score at 0.8
points (p= 0.002) and total PA score at 1.1 points (p= 0.003).
Table 2 – Differences between the first and second physical function assessments for men.
.
N=41
1
st
Assessment
Mean (SD)
[95%CI]
2
nd
Assessment
Mean (SD)
[95%CI]
Percentage
difference
Effect
size
FMS Squat
2.0 (0.1)
[1.8 – 2.2]
2.2 (0.1)*
[2.1 – 2.4]
0.5%
0.334
FMS Hurdle Step
1.7 (0.1)
[1.5 – 1.9]
1.9 (0.1)
[1.7 – 2.0]
0.6%
0.276
FMS In Line Lunge
(0.1)
[1.9 – 2.0]
1.9 (0.1)
[1.8 – 2.0]
- 0.3%
0.089
FMS Shoulder Mobility
1.9 (0.1)
[1.6 – 2.1]
(0.1)
[1.7 – 2.3]
0.3%
0.166
FMS Straight Leg Raise
2.2 (0.1)
[2.2 – 2.6]
2.3 (0.1)
[2.1 – 2.4]
0.2%
0.187
FMS Rotary Stability
2.0 (0.1)
[1.9 – 2.0]
2.0 (0.1)
[1.9 – 2.1]
0.0%
0.154
FMS Trunk Stability Push-up
2.4 (0.1)
[2.1 – 2.6]
2.5 (0.1)
[2.2 – 2.8]
0.2%
0.180
FMS total score
14.2 (0.3)
[13.5 – 14.9]
14.7 (0.3)
[14.2 – 15.3]
0.1%
0.233
FMS - Functional Movement Screen;
*
significant differences, p<0.05;
Table 3 – Differences between the first and second anthropometric and physical activity levels assessment for women.
N= 22
1
st
Assessment
Mean (SD)
[95%CI]
2
nd
Assessment
Mean (SD)
[95%CI]
Percentage
difference
Effect size
Body mass (kg)
57.5 (1.7)
[54.2 – 61.1]
59.4 (1.7)*
[55.8 – 63.1]
0.1%
0.734
Height (cm)
162.3 (1.2)
[159.9 – 164.7]
162.5 (1.1)
[160.2 – 164.9]
0.1%
0.245
PAQ – Sport
4.1 (0.3)
[3.5 – 4.6]
(0.2)
[3.5 – 4.5]
- 2.3%
0.400
PAQ – Leisure
4.3 (0.1)
[4.1 – 4.6]
4.1 (0.3)
[3.5 – 4.7]
- 5.0%
0.800
PAQ – Total
8.3 (0.3)
[7.8 – 9.0]
8.1 (0.4)
[7.3 – 8.9]
- 1.4%
0.800
PAQ - Physical Activity Questionnaire;
cm – centimetres; kg – kilograms; % - percent; g/cm
2
– grams per square centimetre;
*
significant differences, p<0.05;
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DISCUSSION
This research provides an insight into the rate of changes in PFn accessed by FMS
and PA levels in a group of sports science students for one year. The results suggest that
some specific aspects of PFn accessed by FMS are sensitive to improvements or decreases
due to contextual environments that over-or under-produce the stimulation required to
develop specific skills. It seems that young adults’ PFn accessed by the Functional
Movement Screen presents different trajectories based on sex and PA practice.
After 12 months, no significant changes were seen in women's PA levels, whereas
men’s leisure and total PA decreased. The daily routines associated with university life (e.g.,
time management, academic activities, leisure activities, and motivation)
20
might be
responsible for the significant decreases observed in mean total PA (-0.6%) and leisure PA
(-21.7%). Thus, such routines might influence physical fitness and other physical health
outcomes.
21
Humans are motivated by their fundamental psychological needs for competence,
autonomy, and relatedness.
22
Compared with the normative for the FMS total score,
23
men
and women present lower baseline and average scores. However, after 12 months, men
significantly improved FMS DS, and women improved FMS TSP and FMS total scores.
These results are in line with other studies that have reported that specific movements can
change during a season in soccer and among collegiate volleyball players.
14
When
observing the amount of PA practice, we can assume that PA habits were different between
the study groups throughout these 12 months. However, we have not analyzed the
differences statistically.
Men’s PA practice decreased substantially, but their performance improved
regarding movements that challenge total body mechanics, which are needed in most
athletic events.
13
This change could be related to the fact that PFn and physical
Table 4 – Differences between the first and second anthropometric and physical activity levels for men.
N= 33
1
st
Assessment
Mean (SD)
[95%CI]
2
nd
Assessment
Mean (SD)
[95%CI]
Percentage
difference
Effect
size
Body mass (kg)
73.8 (1.3)
[71.1 – 76.5]
74.0 (1.4)
[71.2 – 76.8]
0.1%
0.083
Height (cm)
176.3 (0.8)
[174.6 – 177.9]
176.7 (0.9)*
[175.0 – 178.4]
0.1%
0.376
PAQ – Sport
4.0 (0.2)
[3.6 – 4.3]
3.6 (0.2)
[3.6 – 4.3]
- 0.6%
0.274
PAQ – Leisure
4.4 (1,2)*
[4.0 – 4.7]
3.6 (0.2)
[3.2 – 3.9]
- 21.7%
0.495
PAQ – Total
8.3 (0.3)*
[7.6 – 8.9]
7.2 (0.3)
[6.7 – 7.7]
- 0.6%
0.477
PAQ - Physical Activity Questionnaire; cm – centimetres; kg – kilograms; g/cm
2
– grams per square centimetre;
*
significant differences,
p<0.05.
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performances are separate constructs
10
. Engaging in PA is not the only factor that positively
influences PFn and the various physical fitness components. Even when total PA was not
improved, during this period, all individuals were required to practice soccer, volleyball,
handball, roller hockey, athletic running, throwing, and jumping events, and rock climbing.
This variety of physical demands led to new adaptations and improvements in general motor
proficiency.
24
Such outcomes were more evident in women than in men since women tend
to be less physical active
1,4
and possess fewer motor competence
15
than men. These
aspects and the significant height growth (verified only in men) might also lead to new
adaptations and changes in PFn. Indeed, women tend to produce lower scores in the FMS
TSP than men,
11
but the present improvement was based on a comparison with mean values
at baseline. This comparison indicates low mean scores and normal scores after 12 months.
The FMS TSP in women has been described as more sensitive to core stability than upper
extremity strength.
25
When considered separately of other factors, FMS TSP can be a
reliable measure of PFn in specific populations.
10
This improvement might be directly linked
to new and/or more challenging motor experiences related to the implication of curriculum
practices that demand different sports/skills expertise. The FMS total score directly depends
on the remaining scores,
13
and a significant improvement was mediated by a one-point
improvement in the FMS TSP mean value.
As mentioned, this study showed that men’s PA significantly decreased and more
sports-specific PFn skills improved. Women maintained about the same level of PA practice
while improving total PFn and core stability. However, further inquiry is necessary to
determine how university students’ time management, academic activities, leisure activities,
and study time influence PFn and healthy habits, such as PA routines. When promoting PA
among college students, it might be worth considering the role of sex differences and the
extent to which PFn is accessed by FMS. These factors are common fundamental aspects
of the human movement that can be changed based on the contextual environment. As such,
they can either over-or under-produce the stimulation required to develop those skills.
This study has other potential limitations aside from that concerning sample size.
Namely, the distribution between groups and the changes in each group's fundamental
movement might have been influenced by other formal strength and conditioning training
practices or a lack of training. Future research should clarify the role of the interaction
between FMS and physical fitness, consider the influence of daily university routines, and
the fact that a single year may not provide a broad enough framework considering the age
group and the lack of studies addressing PFn in this population.
CONCLUSION
After 12 months, young adults’ physical function presents different trajectories in
accordance with gender, suggesting that some specific aspects of physical function
accessed by the Functional Movement Screen may be sensitive to improvements or
decrements due to contextual environments that over-or under-produce the stimulation
required to develop those skills.
Sports Science university students’ daily routines may be interceding physical
activity patterns with men physical activity practice significantly decrease, and more sports
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specific physical function skills improve. Women maintaining about the same physical
activity practice improve total physical function and core stability.
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ACKNOWLEDGEMENTS
The authors would like to thank all participants for their availability in collecting the
data.
Citation: Silva B, Bezerra P, Cancela JM. Young adults’ physical activity and physical function: 12 months follow up.
BJMB. 2021. 15(2): 107-117.
Editors: Dr Fabio Augusto Barbieri - São Paulo State University (UNESP), Bauru, SP, Brazil; Dr José Angelo Barela -
São Paulo State University (UNESP), Rio Claro, SP, Brazil; Dr Natalia Madalena Rinaldi - Federal University of
Espírito Santo (UFES), Vitória, ES, Brazil.
Copyright: © 2021 Silva, Bezerra and Cancela and BJMB. This is an open-access article distributed under the terms
of the Creative Commons Attribution-Non Commercial-No Derivatives 4.0 International License which permits
unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: This research received no external funding.
Competing interests: The authors have declared that no competing interests exist.
DOI:!https://doi.org/10.20338/bjmb.v15i2.200