Physical activity, participation in sports competition and school transport in spanish adolescents
ABSTRACT
Different domains of physical activity (PA) are particularly important contributors to energy expenditure (Jurj, Wen, Gao, Matthews, yang, Li, et al., 2007) The purpose of this study was to describe the patterns and relationships between some PA domains, including participation in sports competition and transport, and PA levels. The sample comprised 82 adolescents (13.57 SD = 1.12 years) in Huesca (Spain), 53 boys (13.63 SD = 1.21 years) and 29 girls (13.45 DT = 0.97 years). Accelerometer (GT1M Actigraph) data were collected during seven days from 7:00 am until 12:00 pm to know PA levels in time of moderate to vigorous PA (MVPA). Participation in sports and school transport were evaluated using two items. We used the statistical program SPSS 15.0 to conduct the analysis.
Gender (β = .185, p < 0.01), age (β = .149, p < 0.05) and participation in sports competition (β = .736, p < 0.001) significantly predicted participation in PA, independently of BMI (p> 0.05) and type of school transport (p> 0.05). These three variables explained 71,9% of the variance in MVPA. In conclusion, participation in sports competition is related strongly, and personal variables, age and gender, are related lightly with PA levels.
INTRODUCTION
The role of Physical Activity (PA) in adolescents’ health and general well-being is clearly established. PA is associated with lower blood pressure levels, more favorable serum and lipoprotein levels and decreased adiposity (Dietz, 1998). But PA also favors beneficial social and psychological effects such as increased social acceptance (Weiss & Duncan, 1997), elevated self-esteem and feelings of well-being (Martinsen & Stephens, 1994). Although the health benefits of regular PA are increasingly documented, PA habits in western countries remain lower than the recommended levels (World Health Organization, 2004).
Participation in PA at early age can predict future practice (Blair et al. 1989, Mendoza, 2000), most studies certify a decrease in PA in adolescent period (e.g. Meusel, et al., 2007). In most studies with these age groups show a series of special features for PA levels (Sallis, et al., 2000): men are more active than women, physical activity declines with age and only a small percentage of adolescents fulfill PA for health guidelines.
The assessment of PA in young people is a complex task, hampered by methodological difficulties. The development of accurate methods for monitoring PA in children and adolescents continues to be a relevant research issue (Puyau, et al., 2002). Accelerometers are recognised as one of the most effective ways to produce objective information (frequency, duration, intensity) on young people’s habitual PA, which is typically sporadic in nature (Baquet, et al., 2007).
In order to maximize the effectiveness of interventions programs to implement and promote this critical life habit, the complex arrangement of correlates of PA in adolescence needs to be understood.
Personal variables, age, gender and Body Mass Index (BMI) influence physical activity levels (PAL) in adolescence (Van Der Horst, et al., 2007).
As Physical Activity (PA) occurs in multiple social aspects, different domains of PA are particularly important contributors to energy expediture (Jurj, et al., 2007). Daily health habits, such as active transport to school or participation in sports competition can be an opportunity to increase PAL (Davison & Lawson, 2006).
Participation in sports competition is related strongly with PA and physical fitness (Nuponnen, et al., 2003). School transport was studied in different countries and different populations (Chillón, 2008), but there aren’t a consensus in results: Americans (Gordon-Larsen, 2005; Sirard et al., 2005), Asians (Tudor-Locke et al., 2003), Australians (Timperio, et al., 2006) and Europe (Cooper, et al., 2003; Cooper, et al., 2006).
The purpose of this study was to describe the patterns and relationships between some PA domains, including personal variables, participation in sports competition and transport, and MVPA.
METHODS
Study population.
Two urban state secondary schools in the District of Huesca (Aragon region) in Spain, participated in this study. The potential sample included 166 children (80 boys and 86 girls). Schools were selected on the basis of willingness to cooperate in the study and absence of health- or nutrition-related interventions, which could bias the results. Before participating, all adolescents were informed of the nature of the study. The general inclusion criteria were: (1) all secondary schools were in the District of Huesca and participants had lived in this district for at least 3 years, (2) both a parent and student had to provide informed consent and (3) all students had to be enrolled in physical education (PE) because PE is mandatory in the Spanish.
Two criteria were established for the criterion validity: complete data for a period of 7 consecutive days (Monday-Sunday), except at night while sleeping or during water-based activities, and a minimum of 10 registered hours of data per day (Riddoch, et al., 2004). During the night when asleep, the instrument was still turned on but put aside with the sensors placed horizontally as this mimics the recording of lying still. The participants put the device back on when they got out of bed in the morning (Matthiessen, et al., 2008).
Due to the limited number of accelerometers available, a sub-sample of the study population, 92 adolescents (aged 13.85 ± 1.10 years-old), 59 males (body mass index, 19.99 ± 3.35 kg/m-2) and 33 females (body mass index, 19.66 ± 2.46 kg/m-2), were randomly selected to wear the instruments. In line with previous studies (Craig, et al., 2003), 10 minutes or more of consecutive zero activity was considered time when the accelerometer was not worn and so 10 students (11.49%) were excluded (6 boys and 4 girls). These criteria decreased the sample from the initial accessible population of 82 adolescents (aged 13.57 ± 1.12 years-old): 53 males (BMI 20.00 ± 3.30 kg/m-2) and 29 females (BMI 19.54 ± 2,18 kg/m-2).
The University of Zaragoza provided ethical approval for this research protocol. Written informed consent was obtained from children’s parents and individual school participants. In order to ensure confidentiality, each subject’s data was coded and stored in a computer file.
Instruments.
Objective measurement of daily physical activity: Physical activity was measured during 7 consecutive days (Monday to Sunday) using the MTI accelerometer, model 7164 activity monitor, worn on the waist. Both verbal and written instructions for taking care of and correctly placing the monitor were given to the children and their parents. The accelerometer in question is a lightweight (27 grams), small (4.5*3.5*1.0 cm) and unobtrusive, single plane (vertical) accelerometer. Its acceleration signal is filtered by an analog bandpass filter (0.1-3.6Hz) and digitised by a 9-bit A/D converter rate of 10 samples per second, storing data at user-defined intervals.
Movement on the vertical plane is detected as a combined function of the frequency and intensity of the movement, while an electronic filter rejects motion outside the range of normal human movement. Validation studies examining this accelerometer suggest that it is a valid and reliable measurement of children’s PA and has a highly significant correlation (r= 0.86) with energy expenditure, assessed by indirect calorimetry, as well as a high degree of inter-instrument reliability (Ekelund, et al., 2000). The epoch duration or sampling period was set at 1′ for this study and the output was expressed as counts per minute (counts•min-1).
For each measurement period, the total number of counts was divided by the number of hours recorded in order to adjust unequal monitoring times, and then converted into counts.minute-1, in accordance with other studies (Sirard, et al., 2000). We chose to use the specific cut off points for young people developed by Treuth, et al. (2004), as they have been used in other studies of young populations in Europe (Andersen, et al., 2006). For the purpose of this study, moderate-to-vigorous physical activity (MVPA) (min day-1) provided by the accelerometer were used in the analysis.
Anthropometric measures: The height, weight and body mass index (BMI) of all children were recorded. Height was measured using a Holtain stadiometer, without shoes and recorded in metres to the nearest millimetre, using standard protocols recommended by the International Society for the Advancement of Kinanthropometry as described by Norton and Olds (1996). Weight was measured in light clothing to the nearest 0.1 kg with a calibrated, beam balance scale (Model 780, SECA). The BMI was calculated using the ratio weight/height2 (Kg.m-2).
Participation in sports and school transport were evaluated using two item,
Design and data collection procedure
The questionnaires were completed after taking the objective measurements. To assist children in their recall, interviewers made sure that vocabulary and language levels used were familiar to young people. Participants were instructed to wear the accelerometer every day from the time they got up in the morning at 7am until midnight, and only remove it when engaging in water activities. Each student was scheduled to wear the CSA for a whole week in order to provide a representative picture of weekly activity.
Statistical analysis
Two separate types of analyses were planned:
- Characteristics of participants and outcomes of the study are described as mean ± SD.
- Differences in Gender, age, type of school transport and participation in sport competition in PA were assessed by one-way analysis of variance (ANOVA).
- We conduct a linear regression analysis to know the relationships between PA and personal variables and the different domains
The level of statistical significance was set at p<0.05. The data was analyzed using SPSS (version 15.0).
RESULTS
The physical characteristics of the participants are displayed in Table 1.
Table 1. Sample characteristics, mean scores and standard deviations (SD)
Table 1. Physical activity, participation in sports competition and school transport in spanish adolescents
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In table 2, descriptive data on objective PA measurements was show. There were significant gender differences in total activity (counts min day-1) and MVPA (min day-1). Males presented higher scores than girls for all the variables that were measured.
Table 2. Descriptive data for the Actigraph and self-report PA variables, mean scores and standard deviations (SD)
Table 2. Physical activity, participation in sports competition and school transport in spanish adolescents
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We weren’t found significant differences in MVPA between cicle (Figue 1). First cicle (13 and 14 years old) registered 78,65 minutes and second cicle (15 and 16 years old) registered 72,09 minutes.
Figure 1. Physical activity, participation in sports competition and school transport in spanish adolescents
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Figure 1. MVPA by cycle
There were significant differences (p< ,001) in MVPA between adolescents who present active transport and passive transport. Adolescents with an active transport presented higher scores than passive transport, 84,02 minutes and 69,49 minutes respectively.
Figure 2. Physical activity, participation in sports competition and school transport in spanish adolescents
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Figure 2. MVPA by type of school transport
There weren’t significant differences (p> ,05) in MVPA between adolescents who participate or not participate in sports competition, 75 minutes and 71,74 minutes respectively.
Figure 3. Physical activity, participation in sports competition and school transport in spanish adolescents
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Figure 3. MVPA by participation in sports competition
Results about regression analysis are presented in Figure 4. Gender (β = .185, p < 0.01), age (β = .149, p < 0.05) and participation in sports competition (β = .736, p < 0.001) significantly predicted participation in PA, independently of BMI (β = 0.015, p> 0.05) and type of school transport (β = 0.066, p> 0.05). These three variables explained 71,9% of the variance in MVPA.
Figure 4. Physical activity, participation in sports competition and school transport in spanish adolescents
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Figure 4. Regression analysis
DISCUSSION
We found that gender and age as personal variables had a direct influence on the explanation of the variance in PA levels, excluding BMI. In this survey, studied domains of PA had different effect. Participation in sports competition is related strongly with the PA levels, variable that determines the MVPA of the study population, but not active transport school. In relation with descriptive analysis, we found differences in MVPA by gender and type of transport, but not by age (cicle) and participation in sport competition.
Consistent with previous research, boys show higher PA levels than girls (Martínez-Gómez, et al., 2009; Springer, et al., 2009). In our study, PA decline with age and we found significant (p< ,001) relationships between age and PA levels. Knuth & Hallal (2009), in their review, emphasize that in young people, there is a decrease in PA levels in adolescence like in our study. Trost et al. (2002) and Butte et al. (2007) measured PA levels with accelerometers, also finds that the MVPA and VPA have a significant inverse relationship to age.
We don’t found significant differences in PA by BMI and not significant relationship between these two variables. These results are consistent with a review developed by Sallis et al. (2000), because only the 29% (6/21) of the analyzed studies found relationships between BMI and PA.
Regarding school transport, there is no consensus in the studies (Ferreira, et al., 2007), but our results are similar with another investigations in European population (Sirard, et al., 2005). On the other hand, other studies point out the negative aspects of participation in sports competition (Cruz-Feliú, 1997), like competitive stress or burnout, but in our case, the relationships was significant, strongly and positive.
There are a number of limitations associated with the accelerometer which could explain these results. The CSA is not sensitive to some activities like swimming and cycling (Freedson & Miller, 2000), which are common among both American (Sallis, et al., 1993) and European young people (Esculcas & Mota, 2000). They have a limited ability to assess cycling, locomotion on a gradient or other activity with limited torso movement, and they may not be sensitive to many of the complex movement patterns exhibited by children during free play (Trost et al., 1998).
In conclusion, participation in sports competition is related strongly, and personal variables, age and gender, are related lightly with PA levels.
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