Socio-Demographic Correlates of Cycling to School among 12- to 15-Year Olds in Southern Germany

Abstract

Depending on the region and urbanization level, the rate of cycling to school in Germany varies largely. The influence of distance from home to school, educational level, the school’s region, and parents’ socio-demographic characteristics on cycling to secondary school in Germany is unclear. Therefore, this study analyzed students’ and parents’ socio-demographic correlates of cycling to school, including separate analyses by gender, among 12- to 15-year-olds attending different (sub)urban schools in Southern Germany. In 2019, 121 students (girls: 40.5%, boys: 59.5%) aged 13.1 ± 0.9 and 42 parents (mothers: 81%, fathers: 19%) aged 47.8 ± 5.5 participated. Students completed a self-report questionnaire; parents completed a self- and proxy-report questionnaire. In total, between 61.7% and 67.5% of students sometimes cycled to school. Binary logistic regressions revealed that being a girl, increasing age, attending an intermediate educational level combined with a suburban school region (small or medium-sized town), increasing distance from home to school, and having parents who did not cycle to work led to declining odds of cycling to school. Many 12- to 15-year-olds sometimes cycled to school in (sub)urban school regions in Southern Germany. As several socio-demographic characteristics correlated with cycling to school, this should be considered when developing a future school-based bicycle intervention.

Study Protocol of a School-Based Randomized Controlled Trial to Promote Cycling to School Among Students in Germany Using Intervention Mapping: The ACTS Project

“…As none of these mentioned needs stood out as particularly (un)important and/or (un)feasible, we treated all of them as equally relevant. In this study, almost all students owned a bicycle (girls: 87.8%, boys: 100%) and all were able to cycle ( 5 ). When examining the habits of the students in cycling to school, we found that approximately two-thirds of students stated to sometimes cycle to school (girls: 44.4%, boys: 72.9%), of whom approximately one-third cycled to school daily (girls: 31.6%, boys: 37.3%).…”

“… Logic model of the problem: Factors that influence cycling to school based on concept mapping ( 5 , 17 ). …”

“…As illustrated in Table 2 , the intervention will be structured in two phases: (a) preparation for and (b) practice of the targeted behavior. All chosen components and some of their descriptions were based on the findings and conclusions from our concept mapping study ( 5 , 17 ) and our systematic review ( 11 ), which was conducted to identify effective strategies of school-based interventions to promote ACTS by bicycle among children and adolescents. We also used the following documents to design the mobility and traffic education components in the preparatory phase: (a) The content of the three-cycle training sessions off-road was based on a German research report on road safety education concepts for children and adolescents in secondary schools ( 25 ).…”

“…The optimal sample size for our chosen study design in the main study was calculated based on a formula by Rutterford et al ( 34 ). This formula considers the confidence level (97.5%), power (80%), variance of days per week in cycling to school at the individual level [4.1 days ( 5 )], our estimated clinically important difference in treatment means of days per week in cycling to school at the individual level (1.75 days), number of students per secondary school (based on the mean value in our concept mapping study: 51 students), and ICC of days per week students cycled to school at school level [0.2 days ( 17 )]. According to this formula, the required number of students per intervention condition is 231.…”

“…Living in a small town (5,000–19,999 inhabitants) and a city (>100,000 inhabitants) or attending an intermediate educational level providing a general education school leaving certificate lowered the chance of cycling to school among children and adolescents in Germany compared with those living in a medium-sized town (20,000–99,999 inhabitants) or attending a high educational level providing a general higher education entrance qualification ( 3 , 4 ). These associations may vary based on the context (i.e., sampled regions of residential or school area) ( 5 ).…”