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Environmental changes significantly impact health behavior. Active travel behavior is mostly affected by increasing motorization, urban sprawl, and traffic safety. Especially for children, active and independent travel can contribute to physical activity, social and motor development, and other health-related outcomes. A reduced number of children engaging in independent mobility over the last 20 years demanded researchers to further examine the construct of children’s independent mobility. By examining relevant literature, this narrative review aims to provide the current state of knowledge on children’s independent mobility, and identify future directions in research, as well as practical implications. From a public health perspective, considering children’s independent mobility in intervention programs is recommended, since it is associated with numerous health and environmental benefits. To develop interventions, multilevel socio-ecological influences on children’s independent mobility are widely examined; however, evidence is limited due to heterogeneous measurements and a lack of high-quality prospective studies. To oppose the decline in children’s independent mobility, further analysis using comparable measures is needed to understand the determinants of children’s independent mobility and to enable international comparison.

Background: Children's independent mobility (CIM) is an important contributor to physical activity and health in children. However, in the last 20 years CIM has significantly decreased. To develop effective intervention programs to promote CIM, the impact of the environment on CIM must be identified. This review seeks to provide an overview of sex/gender-specific socio-ecological correlates of CIM. Methods: A systematic literature search of five databases (PubMed, PsycInfo, Scopus, Medline, Web of Science) was conducted with a priori defined eligibility criteria and identified 1838 potential articles published between January 1990 and November 2017. Two independent reviewers screened the literature and identified and rated methodologi- cal quality of the studies. Related factors of CIM were summarized separately for CIM license (parental permission to travel independently) and CIM destination (destinations to which a child travels independently), and separately for boys and girls using a semi-quantitative method. Results: Twenty-seven peer-reviewed journal articles were identified which examined the relationship between the social and physical environment and CIM. Only seven studies reported results divided by sex/gender. Most associa- tions between the environment and CIM were found in the expected direction (positive or negative) or not associ- ated at all. The social environment seemed to be more influential for ensuring CIM than the physical environment. Neighborhood safety, fear of crime and stranger, parental support, and perception of traffic were important social environmental factors influencing CIM, while car ownership, distance, and neighborhood design were relevant physi- cal environmental attributes. Few studies examined sex/gender-related environmental correlates of independent mobility, and those findings were inconsistent. Conclusion: The findings of this systematic review serve as suggestions for intervention programs to increase CIM and to identify future directions in research. To establish a robust comprehension of the impact of the social and physical environment on CIM, further sex/gender-sensitive studies using comparable measurements for CIM and environmental correlates are needed. (Autor).

Physical activity (PA) as a precondition of child development is related with social environmental correlates. However, domain-specific PA and gender issues have been neglected in studies on social support and modelling and PA in school-aged children. The aim of this study was to assess the relationships of parental and peer modelling and social support with domain-specific PA participation in a large sample of school-aged children, taking gender into account. 3,505 school children aged 6 to 17 years old participated in the German nationwide 'MoMo' cohort-study. By using the MoMo-PAQ the participants and their parents provided self-report data on perceived social support and social modelling and domain-specific PA participation. Relationships of social environmental variables and the physical outcomes were analysed by logistic regression analyses. At secondary school level, girls were less likely than boys to participate in physical activity in and outside of sports clubs, extra-curricular physical activity and in outdoor play (p < 0.05), but at primary school level this pattern only applied to club sport (p < 0.01). Girls also received less social support than boys (p < 0.01). Physical activity participation in all domains was associated with any of the social support and modelling variables and differences between physical activity domains and between boys and girls occurred. Most consistently physical activity in sports clubs was related with the social environmental correlates in boys (primary school: R2 = 0.60; secondary school: R2 = 0.45) and girls (primary school: R2 = 0.53; secondary school: R2 = 0.47). In future, reciprocal relationships of social environmental variables and PA should be considered in longitudinal studies to obtain insights into the direction of the associations. Furthermore, interventions encompassing the social environment and focussed particularly on the promotion of domain-specific PA in girls in secondary school-age are warranted.

Background Active travel behavior such as walking and cycling is associated with several health benefits. Especially the family environment seems to be important for active travel in children and adolescents. Currently, little is known regarding travel behavior in leisure time and associations of travel behavior within parent-adolescent dyads. Methods The present analysis is based on the German ARRIVE study (Active tRavel behavioR in the famIly enVironmEnt), which incorporated a large scale, representative cross-sectional online survey including 517 parent–child dyads consisting of adolescents ( N  = 517; boys = 263, girls = 254) aged 11–15 years and one of their parents ( N  = 517; fathers = 259, mothers = 258). Based on that survey which took place in June 2021 (during the COVID-19 pandemic), we calculated the prevalence of active travel to four commonly visited destinations (school/work, friends/relatives, shopping stores and recreational activities) using an adapted version of the travel to school questionnaire by Segura-Diaz JM, Rojas-Jimenez A, Barranco-Ruiz Y, Murillo-Pardo B, Saucedo-Araujo RG, Aranda-Balboa MJ, et al. (Int J Environ Res Public Health 17(14), 2020). In addition, we investigated the associations between parents’ and adolescents’ travel behavior using scores for school/work, leisure time (friends/relatives, shopping stores and recreational activities) and overall (school/work and leisure time). Results Across all destinations, prevalence of active travel in adolescents (63.08%) was higher than in parents (29.21%). Active travel to school (47.33%) as well as to work (20.43%) indicated the lowest prevalence. Linear regression models revealed significant associations in overall active travel between mothers and adolescents (girls: β = 0.308, p  < 0.001; boys: β = 0.302, p  = 0.001) and in leisure time active travel behavior between mothers and daughters (β = 0.316, p  < 0.001). Related to school/work active travel there were no associations between parents and adolescents. Conclusion The associations between adolescents’ and parents’ travel behavior differ depending on gender: they are solely seen in mother-adolescents dyads. Furthermore, our findings conclude that travel is a routine and independent of the destination.

IntroductionActive travel is an important source of physical activity and a primary contributor to overall health among adolescents. To understand and promote active travel behaviour in adolescents, developing a more robust understanding of the predictors of active travel and its associated decision-making processes is needed. Situated within a theoretical socioecological framework for adolescent travel behaviour, the mixed-methods Active tRavel behavioR in the famIly enVironmEnt study aims to quantitatively assess the influence of several predictors of adolescent travel behaviour, and to qualitatively understand the associated decision-making processes of both adolescents and parents.Methods and analysisOur mixed-methods approach will feature online surveys and semistructured interviews. The online questionnaire, developed in accordance with a theoretical framework of adolescent active travel, will examine adolescent travel behaviour with respect to four different destinations while controlling for multiple relevant individual, social and physical environment factors. To enable the comparison of adolescent and parental perspectives, the questionnaire will be answered by a representative sample of German adolescents (11–15 years old) and their parents.Our semistructured interviews, likewise framed based on the central tenets of the theoretical framework of adolescent active travel, will seek to explore the decision-making process of families regarding travel mode choice via conducting interviews with each member (ie, father, mother, adolescent). To investigate travel decision-making processes, adolescents and their parents will be invited to talk about trips they undertook using both active and passive transport modes during the last week. Thematic analyses will be conducted to highlight the central concerns, priorities and values of participants’ decision-making processes.Ethics and disseminationThis study has received ethical approval from the ethics commission of the Friedrich-Alexander-University Erlangen-Nuremberg. Study results will be disseminated at scientific conferences and published in peer-reviewed journals. Additionally, study findings will be made publicly available to relevant health, policy, and research stakeholders and groups.

Background To assess physical activity (PA) there is a need of objective, valid and reliable measurement methods like accelerometers. Before these devices can be used for research, they need to be calibrated and validated for specific age groups as the locomotion differs between children and adults, for instance. Therefore, the aim of the present study was the calibration and validation of the Move4 accelerometer for children aged 8–13 years. Methods 53 normal weighted children (52% boys, 48%girls) aged 8–13 years (mean age = 10.69 ± 1.46, mean BMI = 17.93 kg/m − 2 , 60th percentile), wore the Move4 sensor at four different body positions (thigh, hip, wrist and the Move4ecg including heart rate measurement at the chest). They completed nine activities that considered the four activity levels (sedentary behavior (SB), light PA (LPA), moderate PA (MPA) and vigorous PA (VPA)) within a test-retest design. Intensity values were determined using the mean amplitude deviation (MAD) as well as the movement acceleration intensity (MAI) metrics. Determination of activities and energy expenditure was validated using heart rate. After that, cut-off points were determined in Matlab by using the Classification and Regression Trees (CART) method. The agreement for the cut-off points between T1 and T2 was analyzed. Results MAD and MAI accelerometer values were lowest when children were lying on the floor and highest when running or doing jumping jacks. The mean correlation coefficient between acceleration values and heart rate was 0.595 (p = 0.01) for MAD metric and 0.611 (p = 0.01) for MAI metric, indicating strong correlations. Further, the MAD cut-off points for SB-LPA are 52.9 mg (hip), 62.4 mg (thigh), 86.4 mg (wrist) and 45.9 mg (chest), for LPA-MPA they are 173.3 mg (hip), 260.7 mg (thigh), 194.4 mg (wrist) and 155.7 mg (chest) and for MPA-VPA the cut-off points are 543.6 mg (hip), 674.5 mg (thigh), 623.4 mg (wrist) and 545.5 mg (chest). Test-retest comparison indicated good values (mean differences = 9.8%). Conclusion This is the first study investigating cut-off points for children for four different sensor positions using raw accelerometer metrics (MAD/MAI). Sensitivity and specificity revealed good values for all positions. Nevertheless, depending on the sensor position, metric values differ according to the different involvement of the body in various activities. Thus, the sensor position should be carefully chosen depending on the research question of the study.

Background: To support policy development, a number of tools are available to inform policy-makers about the current status of physical activity (PA) promotion in a specific country. However, a recent exchange between policy-makers and researchers in Germany revealed two major gaps: First, examples of successful good practice projects are often not selected in an objective and systematic process. Second, there is usually no systematic assessment of \"routine practice,\" ie, PA promotion activities already taking place on large scale and regular basis. These issues are addressed by the newly developed TARGET:PA tool. Methods: The TARGET:PA tool was developed in a co-production process involving researchers from the World Health Organization Collaborating Centre for Physical Activity and Public Health (WHO CC) at FAU Erlangen-Nürnberg and the policy unit in charge of cardiovascular diseases, diabetes and non-communicable diseases at the German Ministry of Health. We documented the development process, details on the structure of the tool itself, and the outputs produced using the tool. Results: The development process involved a negotiation process between researchers and policy-makers and the need to adapt to extended decision-making timelines within the ministry. With regard to PA behavior at the individual level, the TARGET:PA tool includes an overview about (1) PA recommendations and (2) national PA prevalence rates. At the organizational/policy level, it contains information on (3) recommendations for PA promotion, (4) routine practice, (5) good practice projects, and (6) policies. Key outputs of the tool are policy briefs as well as scientific background documents. Conclusion: The TARGET:PA tool provides added value as it can support the integration of \"good\" and \"routine\" practices into the monitoring of PA promotion. While the tool has been developed and tested in Germany, it has the potential to be adapted to other countries, either by directly utilizing the tool or by emulating the collaborative development process to design new instruments adapted to specific contexts.

Active travel in adolescence contributes to improved health outcomes. Self-Determination Theory suggests that motivation and basic psychological needs influence travel behavior. Person-centered approaches can examine interrelationships of these constructs underlying travel behavior. The aim of this study was to investigate (i) which clusters can be identified in adolescents, (ii) whether clusters explain overall active travel behavior, (iii) whether clusters were associated with travel mode to various destinations or distance, and (iv) whether differences across clusters appear regarding sex/gender, age, and weight status. The sample included 517 (263 male, 254 female) adolescents from Germany, aged 11–15. Self-organizing maps analysis identified six clusters from nine input variables: intrinsic motivation, integrated regulation, identified regulation, introjected regulation, external regulation, amotivation, autonomy satisfaction, competence satisfaction, and relatedness satisfaction. The most beneficial cluster regarding active travel demonstrated highest basic psychological needs satisfaction and autonomous motivation with low controlled motivation and amotivation. The most vulnerable cluster was characterized by generally low levels of motivation except for external regulation and amotivation. Clusters were not associated with distance to school, friends/relatives, shopping facilities, or leisure facilities. The findings support the importance of high quality and high quantity of motivation for active travel in adolescents.

Active travel can contribute to multiple health benefits in youth. Previous research has identified several factors influencing travel behavior. This study investigates how adolescents process these factors during their decision-making process on travel mode choice. Semi-structured interviews were conducted with 13 adolescents (11–14 years) and analysed using deductive–inductive thematic analysis. Four themes were generated from which the decision-making process on mode choice was conceptualized according to adolescents. The step-by-step process in which travel mode options were gradually reduced, was dependent on the context (Theme 1), the perceived availability of travel mode choice options, which was influenced by factors beyond the individual’s perceived control (Theme 2), and on adolescents’ pros/cons assessment to identify the most convenient option. Adolescents’ habitually used travel mode influenced the decision at several stages throughout the process (Theme 4). To promote healthy travel behaviors, interventions should consider contextual circumstances, balance between enabling autonomous choices and promoting advantages of active travel modes, address individual travel modes and include practices that foster conscious processing of decision-making.

Background: Policy action is required to address physical inactivity in boys and girls. This action can be supported by international data collection, comparisons and sharing of good practices. Thus, this study aims to present and discuss the ongoing monitoring of physical activity (PA) indicators in children and adolescents in the 28 EU Member States. Methods: Data on PA recommendations, PA prevalence, physical education (PE) and PA promotion programs for children and adolescents were provided by governments in a joint EU/WHO survey on the implementation status of the EU Council Recommendation on Health-Enhancing Physical Activity (HEPA) across Sectors. Results: In 23 countries, national recommendations on PA are available. Detailed PA prevalence data among children and adolescents was available in 27 countries, in most cases separately for sex/gender and age groups. The total amount of PE lessons in schools differed greatly between countries and lessons were predominantly mandatory. After-school HEPA promotion programs were mostly implemented in EU Member States (78.6%), followed by active school breaks (57.1%), active travel to school (57.1%) and active breaks during school lessons (53.6%). Conclusions: This study summarizes the monitoring of PA indicators among children and adolescents in all EU Member States by providing a comprehensive overview of the status of PA promotion and monitoring across the region. Based on our findings, it could be concluded that the current EU monitoring system on PA promotion should be adapted to provide evidence that can inform future policy development. (Autor).