As far as we know, this is the first study of independent associations of parental education, occupation and income and physical activity and aerobic fitness outcomes among adolescents in Germany. In addition, it was performed in a nationally representative sample. Girls of parents with high PSEP were more physically active in their leisure time, spent less time using electronic media, showed better aerobic fitness and had higher total energy expenditure compared to girls of parents with low PSEP. Boys of parents with high PSEP also spent less time using media and showed better aerobic fitness than boys of parents with low PSEP; however, no substantial differences were observed for leisure time physical activity and total energy expenditure. Media use was the outcome indicator which showed the strongest associations with PSEP among boys and girls. Although boys of parents with low PSEP reported slightly higher levels of leisure time physical activity, they also reported much higher durations of electronic media use and as a result they showed slightly lower levels of total energy expenditure compared to boys of parents with high PSEP.
In line with our observations, in the Health Behaviour in School-aged Children (HBSC) survey it was observed that in most of the 32 participating countries girls of parents with high socio-economic position indicated higher levels of leisure time physical activity and that this association was less clear among boys . In addition, other studies observed that media use/television viewing was inversely related to PSEP [13, 44], which is also in line with our observations.
Apart from individual factors (psychological and biological dispositions) etiological models also identify interpersonal factors (parental support, cultural norms and practices) and the built environment (neighborhood walkability, pedestrian safety, and access to parks, recreation and sports facilities) [45, 46] as determinants of physical activity behavior in early life episodes .
In line with other studies [14–16], we observed that ‘BMI-for-age’ , ‘physical wellbeing’ and ‘parental support for leisure time activity’ were associated with both the PSEP and the adolescents’ physical activity and fitness variables. Furthermore, we observed that when adjusting for these factors, the effect sizes of the observed associations were reduced. Thus, these factors could be hypothesised as being mediators for the investigated relations, as they meet the criteria of transmitting the effect of the independent variable on the dependent variable and being in the causal sequence of the two-variable relation . Studies suggest that concerns about body shape and weight management are the main motivations to participate in physical activity among young girls . In addition, the perception of being overweight may be a barrier to becoming physically active among overweight individuals [19, 49], as they often feel more discomfort when being physically active . Also low physical wellbeing (e.g. feeling tired/sick, having a disease) and lack of parental support for physical activity have been identified as barriers to physical activity [17–21]. It was also shown that the parental physical activity level strongly correlates to the physical activity level of their children [8, 50], thus it could be the case that the existing SEP differences in adults’ physical activity are transferred to their children. Parents who are mainly sedentary at work and therefore exercise more in leisure time (mainly highly educated) , perhaps stimulate their children to exercise together with them more strongly, compared to parents who do physically demanding work and may therefore be less active in leisure time (mainly low educated) , as they more frequently recover from physical work by ‘staying home in the evenings and the weekends’ using media for entertainment. Overall, we observed that ‘parental education’ was more strongly associated with physical activity and aerobic fitness outcomes among adolescents as compared to ‘parental occupation’ and ‘household income’. In particular ‘household income’ showed no independent effects on the investigated outcomes. These observations correspond to the findings of a study among German adults which uses the same SEP measures and also suggest that education, followed by occupation, is most strongly associated with physical activity patterns and that income plays no important role . Assuming that the leisure time physical activity behaviour of children relates to that of their parents , it is plausible to conclude that the associations between parental education, occupation and income and physical activity and fitness among adolescents follow similar patterns as can be observed among adults.
The cross‒sectional study design does not allow for drawing causal inference upon the findings of this study. Furthermore, validation studies conducted among adolescents 12–17 years old have shown that physical activity questionnaires may overestimate physical activity level compared to objectively measured information using accelerometers. The validity of questionnaires seems to be lower among younger adolescents (12–14 years) compared to older adolescents (15–17 years) . Physical activity level might be over reported due to social desirability , inaccuracies may also occur from cognitive problems in recalling physical activity behaviour or in misunderstanding of the underlying concepts of the questions. We therefore decided to use the self-reported information only to rank individuals by calculating quintiles. We performed sensitivity analysis in order to see whether the choice of cut off points may have influenced the results. When using continuous variables (linear regression) or ordinal (quintile) variables (ordered logistic regression) as the dependent variables in the models, the directions of the associations were widely the same as observed for the binary outcome variables. The exception was that the observed positive association between parental education and leisure time physical activity among girls was only borderline significant when using the continuous variable (p-value: 0.055) and the ordinal variable (p-value: 0.057). We showed a clear positive association between measured aerobic fitness and parental education among boys, however, not so for self-reported leisure time physical activity and total energy expenditure. We cannot totally exclude the possibility that the degree of over-reporting of physical activity level differed according to parental education level, which would result in some degree of misclassification bias. Therefore, we propose using more objective methods for measuring physical activity in future studies, for instance through use of accelerometers. If physical activity is assessed with questionnaires however, we suggest using domain-specific physical activity questionnaires in order to be able to reveal physical activity disparities by PSEP in specific health promotion relevant settings. Studies have shown that adolescents of parents with high PSEP more often engage in sports activities in sports clubs, whereas adolescents of low PSEP are more often physically active travelling from place to place . Estimating the aerobic fitness via a sub-maximal exercise test based on heart rate parameters (PWC170) produces less accurate results than measuring the VO2max as the reference standard for cardiorespiratory fitness via a maximal exercise test [29–31]. However, maximal exercise tests are more expensive, because they require more safety equipment and better trained personal .
The relatively large group of persons with missing data for the aerobic fitness variable may however lead to a lower validity of the results. Finally, the generalisability of the results could be further compromised, since the respondents differed according to selected variables from the non-respondents.