Cardiorespiratory fitness in flemish adolescents and its relationship with leisure-time physical activity, active travel to school and screen-based sedentariness.
The objective of this study was to evaluate associations of cardio-respiratory fitness (CRF) with leisure-time sports participation, active travel to school and screen-based sedentary activities in a sample of Flemish adolescents. Participants were 11- to 13-year-old boys (N=138) and girls (N=180). CRF was indirectly assessed using a 20-m endurance shuttle run test. A self-reported questionnaire was used to assess gender, age, weight status, leisure-time physical activity, active commuting to school and screen-based media use.
In boys, the significant parameters in the age-adjusted regression model to predict CRF were Body-Mass-Index (Beta = -.320, p.001) and the degree of leisure-time sports participation (Beta = .390, p .001) (total adjusted R squared = .320). In girl, Body-Mass-Index (Beta -.294, p.001), leisure-time sports participation (Beta = .272, p .001) and screen-basedsedentary behaviour (Beta = -.198 p.01) were identified as significant predictors of their prformance on the 20-m endurance shuttle run test (total adjusted R squared = .186).
This study confirmed that sports participation during leisure time is positively associated with CRF in adolescents. A significant inverse relationship between screen-based sedentary behaviour and CRF was only observed in girls. No clear relationship between active commuting to school and CRF was found.
Physical fitness is a multifactorial phenomenon consisting of cardiovascular functioning, muscular strength and endurance, flexibility and body composition. Despite its multifactorial nature, cardiorespiratory fitness is a key component of overall physical fitness and higher levels of cardiorespiratory fitness are associated with a healthier cardiovascular profile in children and adolescents (Anderssen et al., 2007; Ortega et al., 2008b). Cardiorespiratory fitness is in part genetically determined, but it can also be greatly influenced by environmental, social and lifestyle factors.
With respect to lifestyle, physical activity has been identified as one of the main determinants (Ortega et al., 2008b). A positive relationship between physical activity and aerobic fitness is established in adults (Blair, 1989). However, the apparently obvious association between cardiorespiratory fitness and physical activity is less clear in children and adolescents and requires further research (Ortega et al., 2008b).
When considering the assessment of physical activity, it is important to acknowledge the multidimensional nature of the term, and the impact of different elements of physical activity (duration, intensity, frequency and type) on health-related outcomes. Furthermore, physical activity is a behaviour that occurs in a variety of forms and contexts (e.g. leisure-time physical activity, school physical education, household chores, and physical activity for transport). It is unclear which physical activity domains are positively related to cardiorespiratory fitness.
There is also growing evidence that increased involvement in sedentary pursuits present a major health problem, contributing to chronic diseases and psychological distress (Biddle et al., 2004; Hills et al., 2007). Nevertheless, the mechanisms by which sedentary behaviours contribute to negative health outcomes are not well understood and only limited evidence is available on the relationship between sedentary behaviours and physical fitness (Katzmarzyck et al., 1998; Grund et al., 2001). Moreover, existing studies of youth sedentariness and fitness typically focus on single behaviours such as TV viewing rather than studying the impact of multiple sedentary behaviours (Marshall et al., 2006).
Given this background, the objective of the present study was to test the hypothesis that cardiorespiratory fitness was positively related with multiple forms of physical activity, but negatively related with the amount of screen-based sedentary activities. Identifying those behavioural factors that are linked with aerobic fitness in youth may be useful for guiding future health-related lifestyle interventions.
A sample of 328 seventh grade pupils (138 boys and 180 girls) aged 11-13 years were recruited from four randomly selected middle schools in Flanders, the northern Dutch speaking part of Belgium. Mean (± SD) age of the participants was 11.32 (± .57) years and 11.25 (± .48) years in boys and girls, respectively. An informed consent was obtained from school board and all parents. The study protocol was approved by the Ethical Committee of the Katholieke Universiteit Leuven.
Measurements and procedure
Cardiorespiratory fitness. The level of cardiorespiratory or aerobic fitness was indirectly assessed using the 20-m endurance shuttle run test with one minute stages (Léger et al., 1988). The test has been shown to be a reliable and valid field test and has probably been the most widely used test to assess the aerobic fitness of children and adolescents (Ortega et al., 2008a). The test was finished when the subject failed to reach the end lines concurrent with the audio signals on 2 consecutive occasions or when the subject stopped because of fatigue.
All measurements were carried out under standardized conditions. All students were familiar with the test because the 20-m shuttle run test is a commonly used fitness test in the physical education curriculum in Flanders. The level of cardiorespiratory fitness was expressed as the running speed in km/h at the final completed stage. Body composition. Self-reported weight and height were used to calculate the Body-Mass-Index (BMI) (kg/m²).
To allow for direct comparison in body composition between participants of different sexes and ages within our sample, age- and sex-specific BMI z-scores were calculated and entered as independent variable in the multiple regression models. We also classified the pupils as overweight and/or obese as defined by the International Obesity Taskforce BMI cut-off criteria (Cole et al., 2000). Physical activity measures. Despite the many physical activity opportunities during school hours (e.g. school recess or physical education), a substantial proportion of young people’s daily PA occurs outside of school hours (Gidlow et al., 2008).
Therefore, pupils’ physical activity behaviour during leisure time was assessed in the present study by means of the Flemish Physical Activity Questionnaire (FPAQ). Philippaerts et al. (2006) reported moderate to high reliability of the FPAQ for indexes used in the present study. Test–retest intra-class correlation coefficients exceeded 0.70. To obtain validity measures, data from questionnaires were correlated to data derived from accelerometry. Pearson correlations were significant and ranged between 0.43 and 0.79, indicating acceptable validity of the instrument (Philippaerts et al., 2006). Leisure-time sports participation was assessed by asking for children’s main (structured and unstructured) sports activities practiced during leisure time. For each type of sports activity, they reported the frequency and the usual time they spend on that activity.
Based on this information, a ‘leisure-time sports participation index’ was calculated and expressed as minutes per week. In addition, pupils were asked to report the minutes of walking and cycling to school during a regular school week. Based on this information, a ‘walking to school index’ and ‘cycling to school index’ was calculated and expressed as minutes per week. Screen-based sedentary behaviours. There are specific domains of sedentary behaviour that have both content and face validity. To quantify the amount of screen-based sedentary behaviour, the pupils indicated how much time they spent watching television (TV) during the day.
This was asked first for a typical school day and then for a typical weekend day, allowing calculation of a weekly estimate. This same procedure was repeated for using the computer (excluding computer-based homework) and playing electronic video games, producing a weekly estimate of screen-based sedentary behaviour, which included TV watching, computer use and video game playing.
Data management and computations of descriptive statistics were performed using SPSS version 16.0 (SPSS Inc., Chicago, IL, USA) and the significance level was set at p .05. Gender differences in continuous measures were determined using an analysis of variance (ANOVA). A chi-square test was used for analyzing the differences in freuencies. A sequential regression analysis was used to analyze the significant predictors of performance on the 20-m shuttle run test.
Data were examined aligned with the assumption pertaining to multicollinearity. Unless stated, the data met this statistical assumption. For each regression analyses, age was entered in Step 1, whereas the standardized Body-Mass-Index (BMI) was entered in Step 2. For children and adolescents, the relation between fatness and BMI differs with age and gender. A standardized BMI (or BMI zscore) statistically adjusts for these factors. The use of a BMI z-score allows one to directly compare youth of different ages and genders.
Finally, physical activity variables (leisure time sports participation, walking to school, cycling to school) and screen-based sedentary behaviour were entered in Step 3. This procedure allowed us to examine the unique contribution of physical activity and sedentary behaviour, after taking into consideration the effects of age and body composition. The significance of the F-ratio for the change in variance (R²) indicated the significance addition of the variables entered in each step to the regression equation.
Sample characteristics are presented in table 1 and table 2. Gender differences were observed for leisure-time sports participation, cycling to school, screen-based sedentary behaviour and 20-m shuttle run test performance. In particular, boys reported a higher amount of leisure-time sports participation (on average 75 minutes per week more) and screen-based media use (on average 1 additional hour per day) compared to girls.
Girls, on the other hand, reported a higher frequency of cycling to school compared to boys. With respect to weight status, approximately 9.5% of our sample was categorized as overweight (incl. obesity) but no gender difference in prevalence rate was observed. Finally, boys performed significantly better on the 20-m shuttle run test compared to girls (on average +1.2 km/h which equals 2.5 additional laps).
Tabla 1. Cardiorespiratory fitness in flemish adolescents and its relationship with leisure-time physical activity, active travel to school and screen-based sedentariness.
Some gender differences were also observed regarding the type of sports practiced (table 2). Our data showed that 69.6% of the boys and 58.9% of the girls participated in club-organized sports during leisure time (?²=3.842, p < .05).
With respect to the sports preference, significantly more boys participated in competitive team sports such as soccer (41.3% compared to 2.2% for girls, p .001) and endurance-oriented sports such as athletics (30.4% compared to 15.0% for girls, p .01) and cycle touring (24.6% compared to 15.0% for girls, p .05). Girls, on the other han, can be more found as participants of aesthetic sports such as dance (36.8% compared to 2.9% for boys, p < .001).
Tabla 2. Cardiorespiratory fitness in flemish adolescents and its relationship with leisure-time physical activity, active travel to school and screen-based sedentariness.
Predicting cardio-respiratory fitness
A sequential regression analysis was conducted for each sex group separately to predict cardiorespiratory fitness (20-m shuttle run performance). Results of the regression analysis are displayed in table 3. The second regression model showed that the linear combination of age and BMI z-scores was significantly related to aerobic performance and accounted for 15.8% of the variance in boys (adjusted R² change=.156, p < 0.001) and 7.6% of the variance in girls (adjusted R² change=.072, p 0.001).
After controlling for age and BMI z-scores, the linear combination of the physical activity and sedentary behaviours was also significantly related to the performance on the 20-m SRT and accounted for 32% of the variance in boys (adjusted R² change=.162, p 0.001) and 18.6% of the variance in girls (adjusted R² change=.11, p 0.05). Taking into account the full regression model (model 3), BMI -scores and the leisure-time sports participation were the main predictors of cardio-respiratory fitness in both sx groups.
Adolescents’ BMI-value was inversely related with the performance on the 20-m shuttle run test, whereas the self-reported time spent on leisure time sports activities was positively related with cardio-respiratory fitness. With respect to walking and cycling to school, no significant relationship with cardio-respiratory fitness was observed in this study. Finally, screen-based media use exhibited a negative relation with aerobic endurance, but this effect only reached statistical significance in girls.
Tabla 3. Cardiorespiratory fitness in flemish adolescents and its relationship with leisure-time physical activity, active travel to school and screen-based sedentariness.
The main purpose of the present study was to explore the cross-sectional association between cardiorespiratory fitness and multiple health-related lifestyle behaviours in a sample of Flemish adolescents aged 11-13 years, taking into account age and weight status of the pupils. It was hypothesized that the level of cardiorespiratory fitness would be positively related with ‘health-enhancing’ lifestyle habits such as leisure-time sports participation and active commuting to school, but inversely related with ‘risk-related’ lifestyle habits such as screen-based sedentary activities.
Our results clearly showed that weight status and leisure-time sports participation are important predictors of cardio-respiratory fitness in adolescents. In line with other studies, a negative relationship between aerobic fitness and weight status was found in the present study (Deforche et al., 2003; Sveinsson et al., 2009). The poorer performances in individuals with higher BMI-values are probably due to the fact that their excess body fat is an extra load to be moved during weight-bearing tasks such as running tasks.
Another explanation may be that overweight children were less motivated than normal weight children to perform well on fitness tests which can be linked to the fact that overweight and obese adolescents usually have a less positive attitude towards physical activity (Deforche et al., 2006). However, a recent study among 11-to-16-year-old boys and girls showed that the 20-m shuttle run test provoked a maximal effort in normal weight as well as overweight children (Sandercock et al., 2008). Despite the positive relationship between leisure-time sports participation and cardio-respiratory fitness, the present study showed no significant relationship between the amount of walking or cycling to school with the performance on the 20-m shuttle run test.
It is noteworthy, however, that low prevalence rates of daily walking or cycling to school were observed in the present study (table 1). Furthermore, a trend towards a positive relationship between cycling to school and aerobic fitness was found in girls (p = 0.079). Previous research showed that children and adolescents who cycled to school were significantly more fit than those who walked or travelled by motorized transport (Cooper et al., 2006; Andersen et al., 2009). In these previous studies, however, aerobic fitness was assessed by a progressive cycle test and familiarity with the bike might have affected the observed positive relationship.
Although active school transport may be an important source of daily physical activity, it seems that walking to school may be insufficient in terms of intensity to increase the level of aerobic fitness. In reviewing the health outcomes of active commuting, it was concluded that the usual intensity of walking may be insufficient to benefit the cardiovascular health (Shephard, 2008). Furthermore, previous research also showed that active commuting per se does not provide sufficient amounts of physical activity to affect adolescents’ BMI and that walking or cycling distance has to be taken into account (Landsberg et al., 2008).
Consequently, in order to enhance physical fitness levels in youth, intervention programs might need to focus on physical activities with appropriate duration and intensity (5-8 METs) (Strong et al., 2005; Ruiz et al., 2007). Nonetheless, much more information is needed before we can make definitive conclusions regarding the contribution of active school transport, and in particular cycling, to the physical fitness and health of young people. The present study also showed a negative association between the level of screen-based sedentary activities and performance on the 20-m shuttle run test. Unfortunately, this relationship failed to reach statistical significance in boys (Beta = -.104, p = .204).
To our knowledge, only one previous cross-sectional study among Australian adolescents has explored the relationship between different components of sedentariness (not only TV viewing) and cardiorespiratory endurance, assessed by means of a 20-m shuttle run test (Hardy et al., 2009). These authors also reported a significant inverse association between sedentariness and cardiorespiratory endurance, particularly among adolescent girls. In boys, however, this relationship was less clear. Sedentary behaviours are often thought to displace more physically active pursuits, yet the degree to which sedentary behaviours prohibit an active lifestyle in young people is equivocal (Biddle, 2007). In the present study, it was also found that the level of leisure-time sports participation was unrelated with the amount of screen-based sedentary behaviour (r = .029, p = .640), which is a consistent finding in literature (Marshall et al., 2006).
Furthermore, a recent study identifying clusters of sedentary and physical activity behaviour among adolescents showed that young people, and particularly boys, may be interested in both sedentary activities as well as being active in sports (Seghers and Rutten, 2010). The present study had some limitations that need to be considered when interpreting the findings. First, the cross-sectional study design is limited in its ability to explain causal associations. For instance, cross-sectional study designs prevents determining whether less-fit girls are more sedentary, or whether sedentariness leads to low fitness. Longitudinal studies are required to determine the direction of the association. Secondly, although the 20-m shuttle run test is an objective measure, it may be affected by factors such as maturation, which was not assessed in this study, temperature, time of day, and motivation (Malina, 1990).
Furthermore, subjective measurement of time spent in physical activity and sedentary behaviour is subject to recall bias. Thus, under- or overestimation of the true prevalence may have occurred due to socially desirable response bias. The use of more objective physical activity measurements such as pedometers or accelerometer could enhance the quality and validity of this survey. We were also not able to assess the total level of physical activity, since school-related physical activity was not reported by the pupils. However, previous studies showed that in-school physical activity accounts for approximately 30% of children’s total moderate-to-vigorous physical activity (Gidlow et al., 2009). Moreover, as children progress from primary to secondary school, the amount of total physical activity they are able to acquire at school is reduced (Gidlow et al., 2009). Therefore, studying behaviour after school is appropriate, especially in adolescents.
The findings of the present study partially confirmed our hypothesis. Specifically, our results confirmed that leisure time physical activity and weight status were important predictors of cardio-respiratory fitness in our sample of adolescents. Unfortunately, no significant relationship was found between active commuting to school and aerobic fitness in the present study. Furthermore, a significant inverse relationship between aerobic fitness and screen-based sedentary activities was observed in adolescent girls.
Nevertheless, based upon our findings, it seems that health promotion for adolescents should focus on promoting appropriate levels of physical activity in terms of duration (at least 60 minutes) and intensity (5-8 METs) (Strong et al., 2005) as well as reducing sedentary behaviour (< 2 hours per day), particularly in adolescent girls.
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