The high prevalence of overweight and obesity among children urges the need to develop effective programmes to prevent obesity. A first step is to identify the energy balance-related behaviours (EBRB) that are related to overweight and obesity. The next step is then to provide theory-based empirical evidence on the most important and modifiable determinants, correlates and predictors of those EBRB that can be targeted in an obesity prevention programme(Reference Brug, Oenema and Ferreira1). Preferably, a theoretical framework should guide the research to gain insight into the complexity of the factors that are associated with EBRB. Kremers et al.(Reference Kremers, de Bruijn and Visscher2) have proposed the Environmental Research framework for weight Gain prevention (EnRG framework), which integrates environmental factors (inspired by the ANalysis Grid for Environments Linked to Obesity (ANGELO) framework)(Reference Swinburn, Egger and Raza3) with more psychological or ‘cognitive’ factors (based on insights from the Theory of Planned Behaviour(Reference Ajzen4)) and identifies personal and behavioural moderators to understand the processes that underlie EBRB. According to the framework, environmental factors can have a direct impact on the behaviours or can be mediated by the cognitive factors. Specifically for children, it is important to focus on family environmental factors, because research has indicated that parents (and not peers) have the most impact on children's EBRB by influencing both the physical and social environment of their children(Reference Edwardson and Gorely5–Reference Brug, te Velde and Chinapaw7) and it has been argued that intervention strategies for children need a major focus on the family context and parental involvement(Reference Golley, Hendrie and Slater8). Next to the family environment, the school environment can be considered important as well, since schools have the capacity to provide several opportunities to practise healthy dietary behaviours and to engage in physical activity (PA)(Reference De Bourdeaudhuij, Van Cauwenberghe and Spittaels9–Reference Wechsler, Devereaux and Davis12). Moreover, the majority of children can be easily accessed through schools and children spend a significant amount of time at school. Thus, a better understanding of the specific family- and school-based factors of the most important EBRB in youngsters will enable the development of an effective intervention programme.
A recent systematic review aimed at identifying family- and school-based correlates of four EBRB (PA, sedentary behaviour, breakfast and soft drink consumption) in children in the transition from childhood to adolescence (10–12 years old)(Reference Verloigne, Van Lippevelde and Maes13), i.e. an age group where children gain increasing autonomy and decision-making power(Reference Golan and Crow14). The results suggested the important role of parental role modelling in influencing schoolchildren's EBRB (e.g. parental behaviour was related to the child's behaviour for all EBRB) and also indicated the general lack of published research to identify school-based correlates of EBRB in 10- to 12-year-olds. Further, it was concluded that more and better-designed research is needed on the parental and school-based factors related to EBRB in schoolchildren, as 75 % of the reviewed studies had a cross-sectional design. Cross-sectional studies can only establish associations, and not prediction or causation, suggesting that longitudinal studies are preferred. Results from a longitudinal study could inform an intervention programme for 10- to 12-year-old children that consequently might have positive effects on children's behaviour in the long term. Moreover, only three out of nineteen longitudinal studies included in the review were conducted in Europe(Reference Gillander Gådin and Hammarström10, Reference Van Lenthe, Boreham and Twisk15, Reference Bois, Sarrazin and Brustad16), and it is doubtful whether evidence regarding correlates and predictors of EBRB from non-European populations can be applied within Europe(Reference Branca, Nikogosian and Lobstein17).
Therefore, the first aim of the present study was to investigate which family and school environmental factors at age 10 years can predict EBRB at age 16 years in a Flemish sample. It is important to investigate predictors of several EBRB to focus on energy intake as well as expenditure, since both contribute to the development or prevention of overweight and obesity. Previous research has provided convincing or at least strongly suggestive evidence that breakfast consumption(Reference Moreno, Rodriguez and Fleta18), soft drink consumption(Reference Moreno, Rodriguez and Fleta18–Reference Malik, Schulze and Hu21) and PA(Reference Jiménez-Pavon, Kelly and Reilly22) are associated with overweight and obesity in childhood and adolescence. Moreover, lack of physical activities, breakfast skipping and high intakes of sugary drinks are highly prevalent in children on the brink of adolescence across Europe(Reference Brug, van Stralen and te Velde23). Therefore, the present study investigated predictors of breakfast consumption, soft drink consumption and PA.
The second study aim was to examine the moderating effects of gender and socio-economic status (SES) on the association of family and school environmental factors with EBRB. Earlier research suggests that these behaviours may be influenced or predicted by different factors in girls and boys(Reference Barnett, O'Loughlin and Paradis24–Reference Salmon, Timperio and Telford27). For example, two previous studies have found that parental PA behaviour was only related to PA behaviour of boys, not girls(Reference Barnett, O'Loughlin and Paradis24, Reference Crawford, Cleland and Timperio25). To our knowledge, no previous studies have examined SES as a potential moderator of correlates of EBRB in early adolescence. However, the socio-economic inequalities in health behaviour(Reference Mutunga, Gallagher and Boreham28) could imply that the behaviour of children from low-SES v. high-SES backgrounds is affected by different factors as well.
Experimental methods
Procedure
Data were used from the Longitudinal Eating and Activity study (LEA study)(Reference Haerens, Vereecken and Maes29). One hundred elementary schools from two Flemish regions were randomly selected from the official list of the Flemish Government in 2002. The principals were sent a recruitment letter and afterwards contacted by telephone. Fifty-nine principals agreed to cooperate in the study. All children of the 5th grade (10-year-olds) in these fifty-nine schools were invited to participate in the study (n 1957) in October–December 2002. Informed consent to let their children participate was received from 1725 parents (88·1 %). The children completed a self-administered questionnaire on eating habits and PA, demographic variables and possible family- and school-based predictors in the classroom under the supervision of one researcher and their classroom teacher. In total, 1670 child questionnaires were collected. Every child was also given a questionnaire to be completed by one of the parents. This parent questionnaire collected data on sociodemographic characteristics, parenting style, parenting practices and family-based predictors of health behaviours. Response percentage and informed consent of the parents was 82·5 %, which resulted in 1614 child–parent couples of usable questionnaires. In 2004, all children left primary school and entered different secondary schools making classroom based administration of questionnaires impossible. In the autumn of 2008, all children were again contacted by a letter sent to their home addresses. The envelope also contained a questionnaire and a pre-stamped envelope to send the questionnaire back via regular mail. A total of 727 questionnaires were received that could be matched with the data of 2002 (45·0 %). Ethical approval for the LEA study was received from Ghent University Hospital.
Measures
Demographic variables
Self-reported weight and height were used to calculate BMI (kg/m2). Parental education level was used as a proxy for SES. The highest level of education of the parent who filled in the questionnaire in 2002 was used as a measure of SES, dichotomized into ‘higher education’ (college or university) or ‘no higher education’ (no education, primary or secondary school).
Behaviour measures
The items to assess breakfast and soft drink consumption are described in Table 1. The food frequency questions were found to have sufficient reliability (weighted κ = 0·66) and validity (Spearman correlation = 0·46) to be useful for ranking subjects(Reference Vereecken and Maes30). The questions to assess PA were derived from the reliable (intra-class correlation coefficient > 0·60) and validated (κ > 0·40) Flemish Physical Activity Questionnaire(Reference Philippaerts, Matton and Wijndaele31) and have already been used in previous research assessing PA among adolescents(Reference Haerens, De Bourdeaudhuij and Maes32, Reference Haerens, Deforche and Maes33). To assess active transportation, minutes spent in active transportation to school and in leisure time were added up. Sports participation was created by adding up time spent in physical activities in leisure time (times per week multiplied by minutes per time). Finally, total PA was assessed by adding up time spent in active transportation, time spent in sports and hours of physical education at school.
Overview of the dietary behaviour measures and family and school environmental variables
BC, breakfast consumption; SDC, soft drink consumption; PA, physical activity; PE, physical education.
Family- and school-based predictors
The child and parent questionnaire, completed at baseline in 2002, contained a wide range of questions related to children's health behaviour and well-being. For the current study, we only included family- and school-based variables that could be examined as a possible predictor of breakfast consumption, soft drink consumption and total PA level. In total, there were twenty-three family environmental variables (three general variables, one variable related to breakfast consumption, five variables related to soft drink consumption and fourteen variables related to total PA) and eight school environmental variables (four general variables and four variables related to total PA) that could be investigated as potential predictors. The EnRG framework(Reference Kremers, de Bruijn and Visscher2) was applied to categorize the predictors. Since the present study focused specifically on the family and school, only environmental factors were included, divided into family and school environmental factors. For a further classification of the variables, the types of environment according to the ANGELO framework – i.e. one of the key inputs for EnRG – were used(Reference Swinburn, Egger and Raza3): (i) the physical environment, referring to the availability and accessibility of behavioural choices; (ii) the sociocultural environment, referring to what is socially appropriate, acceptable or desirable as related to the behavioural choices; (iii) the economic environment, referring to the ‘affordability’ of the behavioural choices; and (iv) the political environment, referring to rules and regulations regarding the behavioural choices. An overview of the family and school environmental variables with their response scales is given in Table 1.
Statistical analyses
Analyses were conducted using the SPSS statistical software package version 15·0. First, to examine the possible family- and school-based predictors of breakfast consumption, soft drink consumption and PA, single linear regressions were conducted for every family- and school-based variable per behaviour. All variables were treated as continuous variables. Variables that were significant in the single linear regressions were entered in a multiple linear regression model, after controlling for multicollinearity (r > 0·60, only the predictor with the highest bivariate correlation with the behaviour was included). In total, there were three multiple linear regression models, one model per behaviour.
Second, to check for moderating effects of gender and SES on the association between the family and school environmental predictors and the behaviour, the cross-product terms of the possible moderator and predictors were entered in a hierarchical regression (step 3), after the main effects of the possible moderator (step 1) and of the predictor (step 2). To avoid high correlations between the main effects and the interaction terms, centred variables were used (raw data minus mean data). P < 0·05 was considered significant.
Results
Study sample
The study sample consisted of 727 children (51·9 % girls, 99 % Belgian nationality and 51·9 % high SES as defined by parental education). Mean age of the sample of 2002 was 9·9 (sd 0·4) years with a mean BMI of 16·5 (sd 2·3) kg/m2. Drop-out analyses were conducted to look at baseline differences between the 727 children included and those who dropped out (n 987). No differences were found for gender, nationality, involvement in sports, active transportation, eating breakfast on weekdays or weekend days and consumption of soft drinks. The children who dropped out were somewhat older (P = 0·01), had a somewhat higher BMI (P = 0·03) and were less likely to have parent(s) with a higher education (P < 0·001). Mean age of the 2008 sample was 16·0 (sd 0·4) years (range 15–17 years) with a mean BMI of 20·4 (sd 2·6) kg/m2. Mean levels of breakfast consumption, soft drink consumption and PA in 2008 are reported in Table 2. Descriptive results for all family- and school-based predictors are provided in Supplementary Materials, Table A.
Mean values of the energy balance-related behaviours at age 16 years among Flemish children (n 727)
PA, physical activity.
Family and school environmental predictors of energy balance-related behaviours
We only present the results from the multiple linear regression analyses. Results from the single linear regression analyses can be consulted in Supplementary Materials, Table B.
Family and school environmental predictors of breakfast consumption
Three family environmental variables and two school environmental variables were studied (see Table 3). All variables together explained 6·7 % of the variance in frequency of breakfast consumption at age 16 years (F = 10·93, P < 0·001). One significant family environmental predictor was identified. Having breakfast together with the parents at the age of 10 years was significantly associated with eating breakfast on more days of the week at the age of 16 years (P < 0·001). No significant school environmental variables were identified for breakfast consumption. Gender and SES did not significantly moderate the associations between these predictors and the frequency of breakfast consumption.
Family and school environmental predictors of breakfast consumption, soft drink consumption and total PA at age 16 years among Flemish children (n 727)
PA, physical activity; PE, physical education.
Family and school environmental predictors of soft drink consumption
Six family environmental variables and one school environmental variables were studied for soft drink consumption (see Table 3). All variables together explained 18·2 % of the variance in soft drink consumption at age 16 years (F = 17·93, P < 0·001). Four significant family environmental predictors were identified. More availability of soft drinks at home at age 10 years was related to more soft drink consumption at age 16 years (P < 0·001). A higher parental consumption of soft drinks at age 10 years was related to more soft drink consumption at age 16 years (P = 0·04). Finally, children who received soft drinks from their parents whenever they asked for it at age 10 years, and children who could take soft drinks whenever they wanted at age 10 years, consumed more soft drinks at age 16 years (P = 0·02 and P = 0·001, respectively). Availability of soft drinks at home was the strongest predictor with a β value of 0·23. There were no significant school environmental predictors of soft drink consumption. Gender and SES did not significantly moderate the associations between these predictors and soft drink consumption.
Family and school environmental predictors of physical activity
Five family environmental variables and three school environmental variables were studied (see Table 3). All variables together explained 9·8 % of the variance in the total PA level at age 16 years (F = 9·48, P < 0·001). Three significant family environmental predictors were identified. A more positive parental attitude towards PA at the age of 10 years was significantly related to more PA at age 16 years (P = 0·009). More parental encouragement at the age of 10 years was significantly related to more PA at the age of 16 years (P = 0·002). A higher parental rating of PA's benefit ‘relaxing after school’ was related to more PA at age 16 years (P < 0·001). The strongest predictor was the rating of PA's benefit ‘relaxing after school’ with a β value of 0·17. No significant school environmental predictors were identified for PA. Gender and SES did not significantly moderate the associations between these predictors and total PA.
Discussion
The current study, exploring longitudinal associations between the family and school environment and three EBRB among Flemish schoolchildren with a 6-year follow-up, provides further evidence for the major role of parents in influencing children's health behaviours, which is in line with a recent systematic review(Reference Verloigne, Van Lippevelde and Maes13). Regarding the frequency of breakfast consumption, one significant family environmental predictor was found, namely having breakfast together with the parents at the age of 10 years. A review of family correlates of breakfast consumption in children(Reference Pearson, Biddle and Gorely34) already concluded that parental breakfast eating was positively associated with breakfast consumption in children, but our results add that it is important for parents to eat that breakfast together with their children to have an impact on future breakfast consumption. Parents act as a role model for their children and breakfast consumption might become a routine then for children, resulting in more days of eating breakfast at an older age.
For soft drink consumption, a number of family environmental predictors were revealed. Availability of soft drinks at home was the strongest family environmental predictor. Given that parents are the primary gatekeepers of purchases at home(Reference Patrick and Nicklas35), parents could restrict the availability of soft drinks and, as a consequence, have an impact on the soft drink consumption of their children. Further, parents should avoid using a permissive parenting style, since two indicators of permissiveness were related to more soft drink consumption. Previous studies have found as well that a permissive parenting style had pernicious consequences in the long term for the intake of unhealthy foods in children(Reference De Bourdeaudhuij36, Reference Vereecken, Haerens and De Bourdeaudhuij37). In contrast, some studies suggested that a strict parental control or an authoritarian parenting style could also lead to the development of unhealthy behaviours(Reference Carper, Orlet and Birch38, Reference Fisher, Mitchell and Smiciklas-Wright39). As both parenting styles seem to be inversely associated with healthy behaviour, it is recommended for parents to adopt a more authoritative parenting style to promote healthy behaviours among children. This parenting style represents a balance between an authoritarian and a permissive parenting style and is characterized by encouraging children to perform healthy behaviour and offering them choices rather than forcing them or leaving the child to his or her own devices(Reference Patrick and Nicklas35). Finally, the positive association between parental soft drink consumption at the age of 10 years and children's soft drink consumption at the age of 16 years confirmed the positive role model function of parents. It has been suggested that parents who regularly consume soft drinks are less likely to have rules regarding their children's soft drink consumption(Reference Grimm, Harnack and Story40). The findings of the present study regarding predictors of soft drink consumption are all in line with the findings of our previous review, although these were based on solely cross-sectional studies(Reference Verloigne, Van Lippevelde and Maes13). Thus, the longitudinal results of the current study contribute to the cross-sectional evidence found in the review.
Our findings showed that a higher parental rating of PA's benefit ‘relaxing after school’ at age 10 years was the strongest predictor of PA at age 16 years. A possible explanation for this significant relationship is that if parents perceive relaxing after school by means of PA as important, they are more apt to stimulate their children to be physically active after school. Further, parental encouragement at the age of 10 years predicted PA at the age of 16 years as well. This finding is not in line with the results of the review where parental encouragement was found to show mixed associations with children's PA(Reference Verloigne, Van Lippevelde and Maes13). However, the great majority of the included studies were cross-sectional and the studies that used a longitudinal design did find a positive association(Reference Cleland, Dwyer and Blizzard41, Reference Sallis, Alcaraz and McKenzie42). It has been suggested that parental encouragement, a form of emotional parental support, could affect children's PA behaviour in a direct way as well as in an indirect way, because of its influence on self-efficacy(Reference Brug, van Stralen and te Velde23, Reference DiLorenzo, Stucky-Ropp and Van der Wal43, Reference Dzewaltowski, Karteroliotis and Welk44) and on competence(Reference Biddle and Goudas45). Moreover, it has been stated that parental encouragement could mediate the relationship between parental and child activity(Reference Gustafson and Rhodes46). These different manners of influencing children's PA might implicate a significant role for parental encouragement.
As mentioned in the introduction to the present paper, it is known that at the ages of 10–12 years, parents (and not peers) have the most impact on children's behaviour. When children reach an older age, it has been stated that peer influences become more important than parental influences(Reference Duncan, Duncan and Strycker47). However, the current study results suggest that parental factors at the age of 10 years associate with adolescents’ behaviour at age 16 years. Consequently, an obesity prevention programme with a strong focus on the identified parental predictors at age 10 years might have positive effects on children's behaviour in the long term.
No significant relationships were found between primary school environmental variables and future breakfast and soft drink consumption. Thus, the family environment appears to be of more importance in predicting breakfast and soft drink consumption, which is in line with the findings of the review of de Vet et al.(Reference de Vet, de Ridder and de Wit48). Another possible explanation could be that the investigated school environmental variables were not sufficiently behaviour-specific (e.g. relation with classmates). For PA, it has been advocated that as physical activities often occur outside the home, other environments such as the school environment might be of greater importance than the family environment(Reference de Vet, de Ridder and de Wit48). The present study results do not support this hypothesis, as no school environmental factors significantly predicted PA at age 16 years. Although there were some PA-specific school environmental variables available to investigate (e.g. hours of physical education lessons), the low variance within the school environmental variables could be partly responsible for the non-significant results for PA. It may be that the change in school environment from baseline to follow-up (i.e. primary to secondary school) is responsible for the fact that school environmental factors were poor predictors of adolescents’ EBRB.
To sum up, several family environmental factors should be taken into account when developing an obesity prevention programme. Based on all significant study results, the following recommendations can be made: to have a positive impact upon EBRB in later adolescence, parents of 10-year-olds should be encouraged to have breakfast together with their children, to restrict their children's and their own intake of soft drinks, to reduce soft drink availability at home, to encourage their children during activities, to develop a positive attitude towards PA and to consider PA as an excellent way of relaxing after a long school day. These predictors applied to both boys and girls and to children from low-SES and high-SES families, suggesting that an intervention programme focusing on these predictors does not have to specifically pay attention to a subgroup of children.
There are some limitations that need to be acknowledged. A first limitation is the use of the self-report measures by children and parents which could have led to socially desirable answers. Further, we have used brief scales to report the complex EBRB, although they have been proven sufficiently reliable and valid(Reference Vereecken and Maes30). A second limitation is the relatively large drop-out which could have consequences for the generalizability of the results. However, drop-out analyses did indicate that drop-out may not have been that selective and the study still had a relatively large study sample with 727 children. Inherent to secondary data analyses, a final limitation of the study is that we were only able to include the family and school environmental variables that were at our disposal in the baseline questionnaire. As a result, a larger number of variables related to PA could be investigated, suggesting further research is needed to gain more insight into the predictors of the dietary behaviours, particularly breakfast consumption. Moreover, future research should investigate more behaviour-specific school environmental variables, as this was not the case in the present study. Finally, most variables were situated in the sociocultural domain and although the sociocultural environment appeared to be the most important one to predict future EBRB, future research should investigate variables in other domains as well. An important strength of the current study is the 6-year follow-up period going from childhood to adolescence which is unique for a European study examining several family- and school-based predictors.
Conclusions
The current study shows that several family environmental factors at age 10 years predicted breakfast consumption, soft drink consumption and PA at age 16 years. No school environmental predictors were identified. An obesity prevention programme in the final years of primary school focusing on the significant parental factors might lead to healthy behaviour in adolescence.
Acknowledgements
Source of funding: The ENERGY project is funded by the Seventh Framework Programme (CORDIS FP7) of the European Commission, HEALTH (FP7-HEALTH-2007-B), Grant Agreement no. 223254. The contents of this article reflect the authors’ views only and the European Community is not liable for any use that may be made of the information contained herein. Conflicts of interest: The authors declare that they have no competing interests. Authors’ contribution: J.B. developed the concept and design of the ENERGY project. L.M. and I.D.B. provided the data set. M.V. conducted the secondary analyses with help from W.V.L., L.M. and I.D.B.M.V. wrote the first draft of the paper. All authors read and approved the final manuscript.
Supplementary Materials
For Supplementary Materials for this article, please visit http://dx.doi.org/10.1017/S1368980012004120.
