Introduction

Despite the many health benefits of physical activity (PA) [1], overall PA levels among children decline when they enter adolescence and make the transition from primary (age 11–12 years) to secondary school (age 13–14 years) [2–4]. Furthermore, some sex- and domain-specific changes in PA were found during this transition. Active transportation to school increased and sports during leisure time decreased among boys and girls, whereas total daily step counts decreased among girls and walking for transport during leisure time decreased among boys during this transition [5]. The transition from primary to secondary school can be seen as a critical life event and an experience that greatly influences a child’s daily routines.

According to ecological models, PA is influenced by multiple factors such as individual (e.g., age and self-efficacy), social environmental (e.g., social support), and physical environmental factors (e.g., walkability) [6]. It is likely that the transition to secondary school is accompanied by changes in these individual, social, and environmental factors. Insight into these changes, and their relation with changes in PA, is necessary to develop effective interventions to prevent the decrease among children’s PA when they make the transition to secondary school [7]. If changes in individual or environmental factors are associated with decreases in PA across the transition from primary to secondary school, minimizing these changes or trying to increase these factors may be an effective intervention strategy for reducing the decline in PA that usually occurs when children make the transition from primary to secondary school.

Different studies have investigated the association between individual [8], social [8, 9], and environmental factors [10, 11] and children’s PA. However, the main limitation of these studies is their cross-sectional design, and only few previous studies focused specifically on changes in correlates of PA during the critical life event of the transition from primary to secondary school. In two previous Belgian studies conducted on the current sample, longitudinal associations of changes in the school environment and changes in the perceived neighborhood environment with changes in PA during the transition from primary to secondary school were investigated [5, 12]. It was found that an increase in promotion of active transportation to school (ATS), an increase in availability of school facilities and sport equipment, and the presence of a health education policy at school were related to increased PA in different domains [12]. However, only few changes in children’s and parents’ perceived neighborhood environment were significantly related to changes in PA [5]. Both previous studies mainly focused on changes in physical environmental (school and neighborhood) factors. Based on the results of these previous studies, it can be concluded that a large part of the variance in PA changes during the transition from primary to secondary school remains unexplained.

As according to ecological models, behavior is not only influenced by physical environmental factors but also by individual and social environmental factors [6]; more insight into these factors in relation to PA during the transition to secondary school is needed. It is likely that individual and social environmental factors change when children make the transition to secondary school, as this transition occurs around the start of puberty and is accompanied by changes in peer groups. Furthermore, individual (e.g., self-efficacy) and social environmental (e.g., friend support) correlates of PA among children differ from correlates among adolescents. Cross-sectional studies showed that self-efficacy, parental modeling (only among boys), and parental support are positively related to children’s PA [9]. Among adolescents, positive associations with PA were found for attitude, self-efficacy, and friend support [9]. To our knowledge, no previous studies investigated if changes in these individual and social environmental factors are related to changes in PA during the transition to secondary school. As different individual and social environmental factors were associated with PA among children and adolescents in cross-sectional studies, it might be that changes in these factors are important to explain changes in PA during the transition from primary to secondary school.

Therefore, the first aim of this study was to investigate how individual (i.e., attitude toward PA, self-efficacy toward PA, and perceived benefits and barriers of PA) and social environmental factors (i.e., parental support, friend co-participation for PA, parental trust in their child’s ability to be physically active, and social norm) toward PA change when children (11–12 years) make the transition to secondary school (13–14 years). It was hypothesized that individual and social environmental factors would become less positive, as adolescents probably attach more value to other (academic or leisure) activities and less to PA compared to their childhood. As parents are seen as the main decision makers for their children and parents play an important role in determining children’s PA [13, 14], parental report of individual and social environmental factors was also included in the study. The second aim of this study was to investigate how changes in individual and social environmental factors were related to changes in different PA domains. It was hypothesized that an adverse change in individual and social environmental factors would be related to less favorable PA levels. Because changes in PA are dependent on children’s sex and the domain of PA [5], changes in PA correlates were investigated in relation to changes in the different PA domains (objectively measured daily steps, sports during leisure, ATS, walking for transportation during leisure, and cycling for transportation during leisure) and for boys and girls separately.

Methods

Participants and Procedure

Data collection of this longitudinal study took place during the school year 2009–2010. Two years later, follow-up measures were collected.

At baseline, primary schools (n = 148) in East and West Flanders (Belgium) were randomly contacted by phone. In total, 44 principals gave permission to collect data for this study among students of the sixth grade in their school (response rate = 29.7 %). In each school, a research assistant visited one class from the sixth grade and all children in these classes (11–12 years, n = 976) and their parents were invited to participate. This resulted in 749 children who were allowed by their parents to participate in the study (response rate = 76.7 %).

The participating children and one of their parents were asked to complete a questionnaire. Children were also asked to wear an activity monitor for seven consecutive days; 297 children received an accelerometer, and due to the limited availability of accelerometers, 439 children received a pedometer.

Two years after baseline measurements, children and parents who participated at baseline were asked by phone if they were willing to participate in the follow-up measurements of the study. In total, 502 children and their parents agreed to participate in the second phase of the study, but 75 of them were not willing to wear an activity monitor.

In total, 420 child questionnaires and 416 parent questionnaires returned after the follow-up measurements; 369 children had complete pedometer or accelerometer step count data for at least three weekdays, and 370 had complete pedometer or accelerometer step count data for at least one weekend day. In total, data of 321 (321/976 = 32.9 %) children were complete and were included in the analyses (157 girls, 48.9 %). Further details of sample selection are published elsewhere [5]. The study protocol was approved by the Ethics Committee of Ghent University Hospital.

Measures

Demographic Factors

Children reported their age and sex in the questionnaire. The educational level of the mother and father was measured using the parental questionnaire and determined based on the following four options: less than secondary school, completed secondary school, completed college, or completed university. The educational levels of mother and father were recorded into “attained a college or a university education level” or “did not attain a college or a university education level.”

Individual and Social Environmental Factors

Children’s attitude toward PA, their perception of parental support, friends’ co-participation, perceived social norm, self-efficacy, perceived benefits (i.e., health, meeting (new) friends, fun, being better than others, not feeling bored, and weight loss), and barriers (i.e., lack of time, not liking sports, not being good at sports, not being allowed to sport, and lack of transportation to sport activities) toward PA were assessed using questions derived from previous studies in adults and adolescents [15–20] and were based on the theory of planned behavior [21]. Parents reported on their attitude toward their child’s PA, on parental support for their child’s PA, social norm, parental trust in their child’s ability to be physically active, and on the perceived benefits and barriers of PA for their child. Parents answered the questions from their child’s perspective (e.g., perceived benefits, My child thinks that doing sports is good because he/she gets in contact with (new) friends). Table 1 gives an overview of the content and response options of the individual and social environmental factors for children and their parents. Adolescents and parents answered the same questions at follow-up.

Table 1 Content and response options of the individual and social environmental factors
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Physical Activity

Objectively Measured Step Counts

The Yamax Digiwalker SW-200 and the Actigraph accelerometer, model GT1M, were used to measure step counts. The Yamax Digiwalker is valid and reliable to measure free-living step counts among children and adolescents [22]. The GT1M accelerometer has demonstrated good reliability for measuring steps [23]. Although the step counts measured by the Yamax Digi-walker CW-701 (the update of the Yamax Digiwalker SW-200) and the step counts of the GT1M accelerometer have been shown to be highly correlated, the overall agreement between the step counts of both monitors is rather low [24]. Therefore, all analyses including average daily steps were controlled for the type of activity monitor (pedometer or accelerometer) that was worn. The children wore the monitor for seven consecutive days during waking hours and were asked to remove the activity monitor during aquatic activities. Children were also asked to complete an activity diary with activities for which the activity monitor was removed. Children wearing a pedometer were also asked to register the date of their daily steps in the activity diary.

Protocol of Data Reduction for Pedometer and Accelerometer

Accelerometer data were downloaded using Actilife, and data were screened, cleaned, and scored using data-reduction software MeterPlus [25].

For each registered minute of moderate- to vigorous-intensity PA for which the activity monitor was removed, 150 steps were added to the daily number of registered step counts [26].

Based on the average daily steps, a weekly average of steps was calculated. Inclusion criteria were set at having at least three valid weekdays and one weekend day (between 1000 and 30,000 steps/day [27]) of monitoring [28, 29].

Self-Reported PA

Children filled out the Flemish Physical Activity Questionnaire (FPAQ), which is a reliable and reasonably valid questionnaire for the assessment of different dimensions of PA among children [30] and adolescents [31]. The FPAQ was used to determine the duration of walking and cycling to and from school and walking and cycling for transport during leisure time and sports during leisure time.

Data Analysis

Binomial (for parental education and sex) and linear (for PA) regressions in MLwiN (two levels, school and individual) with parental education, children’s sex, and PA measures as dependent variables and the availability of data at follow-up (1 = yes, 0 = no) as independent variable were conducted to analyze differences in socio-demographic variables and PA between children included in the sample and children who dropped out after baseline measures.

All statistical analyses were done separately for boys and girls, as changes in PA and PA correlates differ between sexes [5, 8, 32–36]. To account for clustering of children within primary schools and secondary schools, data were analyzed using MLwiN 2.30. For all analyses, primary schools and secondary schools were treated as cross-classified. The Markov chain Monte Carlo method (MCMC) was used to fit the cross-classified multilevel models applying an orthogonal parameterization [37]. Tests for normal distribution revealed some skewed PA variables; therefore, logarithmic transformations were made to improve normality. The transformed variables were used in the analyses. For ease of interpretation, summary data of untransformed PA variables are reported in minutes per day.

To investigate longitudinal changes in individual and social environmental factors, four-level (time, child, primary school, and secondary school) cross-classified multilevel regression models were conducted. These changes were investigated by regressing the dependent individual and social environmental factors onto the time point variable. Cohen’s d effect sizes were calculated based on the difference between the score on the individual and social environmental variables in primary and in secondary schools [38]. Effect sizes of ≥0.80 were considered large, ≥0.50 were considered moderate, and ≥0.20 were small effects [39].

Measures of change in individual and social environmental factors and PA between the two time points were computed by regressing the individual and social environmental factors and PA variables at follow-up onto their respective baseline values. Based on these regression outcomes, residualized change scores were computed. These scores represent the amount of decrease or increase in individual and social environmental factors and PA between baseline and follow-up [39, 40]. Before multilevel regression analyses were conducted, multicollinearity within the child and parental individual and social environmental factors residualized change scores was checked by conducting Pearson’s correlations in SPSS20. If the magnitude of the correlation coefficients did exceed 0.60, only the factor with the highest correlation with the dependent variable was kept in the regression model. In a next step in SPSS20, correlations of children’s and parental individual and social environmental factors residualized change scores with the dependent PA variables were analyzed and only those child and parental individual and social environmental factors that were related (p < 0.15) to the dependent variable were included in the multilevel regression models [41]. One regression model was conducted for each dependent variable. To investigate if the changes in individual and social environmental factors were related to changes in PA, the residualized change scores of the individual and social environmental factors were regressed onto the residualized change scores of PA.

All analyses were controlled for two proxy measures of individual SES (educational attainment of mother and father), and analyses concerning overall steps/day were also controlled for the type of monitor used by entering a variable “type of monitor (accelerometer/pedometer)” in the regression models. Children who did not wear the same type of monitor at both time points (n = 12) were excluded from the analyses concerning total daily step counts. To estimate the local effect size of the significant correlates of changes in PA, we calculated the proportional reduction in variance statistic to determine the explained variance of each correlate at the individual level [42].

P values <0.05 were considered significant.

Results

Descriptive Characteristics

Descriptive sample characteristics at baseline are shown in Table 2. The children who are included in the analyses and those who dropped out after baseline measurements did not differ concerning sex (p = 0.392) and father’s education level (p = 0.718). Mother’s education level of children participating at both baseline and follow-up was higher compared to children who did not participate at follow-up (p = 0.003).

Table 2 Descriptive characteristics of the sample
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The children who dropped out after baseline measurements did not differ concerning average daily steps, sports during leisure, walking for transportation during leisure, and cycling for transportation during leisure. Children who dropped out after baseline measurements were less engaged in active transportation to school at baseline compared to children who did not drop out after baseline (p = 0.018).

Mean ages at baseline were 11.1 ± 0.5 and 13.4 ± 0.6 years at follow-up. The final sample (n = 321) consisted of 164 boys (51.1 %).

Changes in Individual and Social Environmental Factors

Table 3 summarizes changes in PA-related individual and social environmental factors. Among girls, parental support (p < 0.001), lack of time (p < 0.01), and the perceived barrier of not liking sports (p < 0.05) increased from baseline to follow-up. Attitude toward PA (p < 0.001), self-efficacy (p < 0.001), perceived benefits of meeting new friends (p < 0.01), fun (p < 0.001), and not feeling bored (p < 0.001) decreased from baseline to follow-up. Also according to their parents, girls’ parental support (p < 0.05), perceived benefit of weight loss (p < 0.01), and perceived barrier of not liking sports (p < 0.01) increased and their trust in their child’s ability to be physically active (p < 0.001), social norm (p < 0.001), and perceived benefit of fun (p < 0.05) decreased from baseline to follow-up.

Table 3 Changes in individual and social environmental factors
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Among boys, only perceived benefit of fun (p < 0.05) decreased from baseline to follow-up, whereas perceived benefit of being better than others (p < 0.01) increased. Boys’ parents reported a decrease in social norm (p < 0.05), in their trust toward their child’s ability to be physically active (p < 0.01), in the perceived benefits of meeting (new) friends (p < 0.01), fun (p < 0.001), and not feeling bored (p < 0.05). Boys’ parents reported an increase of the perceived benefit of weight loss (p < 0.05), the perceived barrier of not liking sports (p < 0.001), and not being good at sports (p < 0.01).

Associations of Changes in Individual and Social Environmental Factors with Changes in Objectively Measured Daily Steps

An overview of the variables included in the regression analyses concerning objectively measured daily steps is given in Table 4. Among girls, increased attitude (more positive) toward PA was related to an increase in daily steps (p = 0.007).

Table 4 Associations of changes in individual and social environmental factors with changes in objectively measured physical activity
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Among boys, a decrease in lack of time (p = 0.036) and a decrease in the parental perceived barrier of lack of transportation to sport activities were related to an increase in daily steps.

Associations of Changes in Psychosocial Factors with Changes in Self-Reported PA

An overview of the variables included in the regression analyses concerning self-reported PA is given in Table 5. An increase in self-efficacy (p = 0.038) relates to an increase in sports during leisure among girls. Among girls, increases in the perceived benefit of health (p = 0.040), the barrier of not being allowed to sport, and in the parental perceived benefit of being better than others (p = 0.035) were related to an increase in active transportation to school.

Table 5 Associations of changes in individual and social environmental factors with changes in self-reported physical activity
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Among boys, an increase in parental support (p = 0.018) and a decrease in the parental perceived barrier of not liking sports (p = 0.005) were related to an increase in sports during leisure (p = 0.018). An increase in parental reported parental support (p = 0.033) and in the parental perceived barrier of not liking sports (p = 0.030) were related to an increase among boys’ walking for transportation.

Discussion

As expected, the transition from primary to secondary school occurred with changes in individual and social environmental factors toward PA and sports among boys and girls. However, the changes in individual and social environmental factors were small. In general, these factors were less positive in secondary school compared to primary school and these findings were in line with our hypotheses. Most of the factors that changed, changed among girls. Among boys, only a decrease in the perceived benefit of fun was observed. This indicates that boys did not largely change their opinions and feelings toward PA and sports when entering secondary school in contrast to girls, whose individual and social factors toward PA became less positive. It is likely that, compared to boys, girls attach more value to other activities than PA (e.g., academic and social activities) and are less interested in PA when they enter secondary school. The only factor that became more positive toward PA was parental support; this was only reported by girls and their parents. This indicates that parents more frequently encouraged their daughters to be physically active when they were in secondary school compared to primary school. This can be explained by the fact that girls’ parents might believe that girls need more encouragement for PA when they enter adolescence, as it was found in a previous study in the current sample that girls’ average daily steps and sports during leisure decreased during the transition to secondary school [5]. Among boys, parental support did not change. This can be due to the fact that overall daily steps among boys did not decrease during the transition from primary to secondary school and the decrease in boys’ sports during leisure was smaller among boys than among girls [5]. So, it is likely that parents of boys assumed that boys do not need additional support for PA after the transition to secondary school. Another unexpected finding was the fact that the perceived benefit of being better than others increased among boys from primary to secondary school, whereas it was expected that variables would be less positive toward PA after the transition to secondary school.

In general, decreases in individual and social environmental factors toward PA related to a decrease in PA levels and vice versa. This finding is in line with the hypothesis. Among girls, an increase in attitude toward PA was related to an increase in average daily steps and an increase in self-efficacy was related to an increase in sports during leisure. Self-efficacy was found to be an important correlate of PA in previous cross-sectional [9] and longitudinal studies [43, 44], and this study confirmed this finding but only among girls. Self-efficacy reflects girls’ belief in their ability to be physically active in difficult circumstances (e.g., if they have to get up early and if they have a lot of work for school). Attitude toward PA was measured as pleasantness of being physically active. So, girls took more steps per day, if they thought that PA was pleasant, or in other words, when they are autonomously motivated. This is a positive result, as autonomous motivation is related to PA in the long term [45]. Future interventions aiming to increase overall PA and sports among girls should focus on the increase of individual factors such as attitude and self-efficacy toward PA. However, effect sizes that were found in the current study were low, so efforts to increase attitude and self-efficacy should not be conducted as a stand-alone intervention but as part of multicomponent interventions in order to obtain larger effects on PA. Interventions focusing on the enhancement of girls’ beliefs in their ability to be physically active may lead to higher PA levels. This can be done using different behavior change techniques such as prompting barrier identification, providing instructions on how to perform the behavior, and setting graded tasks [46]. Offering girls pleasant physical activities and allowing girls to choose in which sport they prefer to participate may lead to a more positive attitude toward PA and consequently to more average daily steps among girls.

Also, increases in the perceived benefits of health and being better than others and the perceived barrier of not being allowed to sport were related to increases among girls’ active transportation to school. The positive association between changes in the perceived barrier of not being allowed to sport and changes among girls’ active transportation to school was in the other direction than expected. However, the explained variance in active transportation to school due to these factors was very low (<2 %). This might be due to the fact that the individual and social environmental factors were formulated toward PA and sports in general. It is possible that changes in individual and social environmental factors that are specifically formulated toward active transportation would explain more of the variance in active transportation among boys and girls. It is also possible that changes in other factors (e.g., physical environmental factors such as the availability of walk/cycle facilities [5]) are more important to explain changes in active transportation.

Among boys, a decrease in the perceived barriers lack of time and in the parental perceived barrier of lack of transportation to sport activities were related to an increase in boys’ average daily steps. Furthermore, an increase in parental support was related to an increase in boys’ sports during leisure and to an increase in walking for transportation during leisure. This indicates that, although children’s autonomy increases when they make the transition to secondary school, it remains important for parents to encourage their son to be physically active when they grow older and to provide transportation to sport activities, after the transition to secondary school. In another Belgian study, the supportive role of parents during primary school was also identified as an important positive predictor of adolescents’ PA in secondary school [47]. As changes in the perceived barrier lack of time were negatively related to changes in average daily steps, action planning might help boys to engage more in PA [46]. An increase in the parental perceived barrier of not liking PA explained a relatively large proportion (7.7 %) of the variance in sports during leisure among boys. So, similar as among girls, it is important to offer sports activities to boys that are attractive and pleasant.

Based on the results of this study, it can be concluded that changes in individual factors (i.e., attitude and self-efficacy) mainly explain the declines among girls’ PA, whereas changes in barriers toward sports (i.e., barrier of lack of time, lack of transportation, and not liking sports) and parental support mainly explained changes among boys’ PA during the transition from primary to secondary school.

Changes in social norm and friend co-participation were unrelated to changes in any PA domain, indicating that increasing social norm and friend co-participation would probably not lead to more PA during the transition from primary to secondary school among boys and girls. However, in a longitudinal study in the UK during the transition from primary to secondary school, it was found that an increased number of friends and friend support for physical activity were related to increases in girls’ moderate- to vigorous-intensity physical activity [48]. So, it is likely that other forms of friend support than co-participation may be important to explain changes in PA among girls.

The longitudinal design, the relatively high response rate (considering the 2-year time gap and the multiple sources of data), and the combination of self-reported and objective assessment of PA were strengths of this study. A first limitation of the study is the combination of accelerometers and pedometers that was used to determine average daily steps. To overcome this problem, all analyses concerning daily steps were controlled for the type of monitor used, and only children who wore the same device type at baseline and follow-up were included. Furthermore, mothers of children who participated in the follow-up measurements were slightly higher educated compared to parents who did not participate at follow-up. This could limit the generalizability of the current findings. It is possible that children from lower-educated parents were less allowed by their parents to participate at follow-up, as their parents are probably less aware of the benefits of PA research. Besides, children who dropped out were also less engaged in active transportation to and from school at baseline. A possible explanation might be that these children were less interested in PA research than children who were more engaged in active transportation at baseline.

Besides, only individual and social environmental variables were included in the analyses. Previous research has shown that also physical neighborhood environmental [5] and school environmental variables [12] explain changes in PA, so in future studies, including these factors to explain PA levels is important.

Conclusions

Individual and social environmental factors toward PA were less positive toward PA and sports when children made the transition from primary to secondary school. These changes were mainly present among girls. The prevention of adverse changes in attitude and self-efficacy may lead to a smaller decrease or an increase in PA when girls made the transition to secondary school, whereas among boys, more focus is needed on the decrease of barriers and the increase of parental support. However, the explained variance of changes in individual and social environmental factors in changes in PA during the transition from primary to secondary school was small. So, multicomponent interventions that focus on other factors besides individual and social environmental factors are needed, in order to obtain large effects on PA.