Insights into children's cycling for transport: a socio ...

Insights into children’s cycling for transport: a socio-ecological approach

Ariane Ghekiere

Thesis submitted in the fulfilment of the requirements for the degree of Doctor in Health Sciences

Gent 2016

Supervisor:

Prof. dr. Benedicte Deforche (UGent)

Co-supervisors:

Prof. dr. Ilse De Bourdeaudhuij (UGent) Prof. dr. Peter Clarys (VUB)

Supervisory board: Prof. dr. Benedicte Deforche (UGent) Prof. dr. Ilse De Bourdeaudhuij (UGent) Prof. dr. Peter Clarys (VUB) Prof. dr. Greet Cardon (UGent) Prof. dr. Bas de Geus (VUB) Prof. dr. Jo Salmon (Deakin University, Melbourne, Australia)

Examination board: Prof. dr. Patrick Calders (UGent) Prof. dr. Jorge Mota (University of Porto, Portugal) Prof. dr. Frank Witlox (UGent) Prof. dr. Tine Vervoort (UGent) Prof. dr. Eva D’Hondt (VUB) dr. Delfien Van Dyck (UGent)

Acknowledgements: The research reported in this thesis was funded by a grant from the Research Council of the Vrije Universiteit Brussel (OZR1937BOF), a grant from the Research Foundation Flanders (FWO, GA11111N) and a Ghent University Special Research Fund (BOF, 01DI2915).

Cover by Daphne Reiner © 2016 Department of Public Health, De Pintelaan 185, 9000 Gent All rights reserved. No parts of this book may be reproduced, or published, in any form or in any way, by print, photoprint, microfilm or any other means without prior permission from the author.

Table of content Summary/samenvatting................................................................................................................ 1 PART ONE : GENERAL INTRODUCTION

1. Physical activity during childhood: guidelines, prevalence and health effects ............................... 7 2. Active transport and cycling for transport .................................................................................... 9 3. A socio-ecological approach to study children’s cycling for transport ..........................................10 4. Measuring cycling for transport and its correlates .......................................................................13 4.1 Methods to asses cycling for transport ...................................................................................13 4.1.1 Objective measurements .....................................................................................................13 4.1.2 Subjective measurements ....................................................................................................14 4.2 Methods to assess individual and psychosocial factors associated with cycling for transport ..15 4.3 Methods to assess physical environmental factors associated with cycling for transport .........17 4.3.1 Objective measurements .....................................................................................................18 4.3.1.1 Audit Tools .....................................................................................................................19 4.3.1.2 Geographic Information Systems .....................................................................................20 4.3.2 Subjective measurements ....................................................................................................22 4.3.2.1 Questionnaires ................................................................................................................22 4.3.2.2 Qualitative research methods ...........................................................................................23 4.3.2.3 Experimental research with manipulated photographs ......................................................24 5. Socio-ecological factors associated with children’s cycling for transport .....................................26 5.1 Individual factors ..................................................................................................................26 5.2 Social factors ........................................................................................................................28 5.3 Physical environmental factors ..............................................................................................30 6. Problem statement and outline of this thesis ................................................................................34 7.

Publications included in this thesis .............................................................................................40

8. References ..................................................................................................................................44

PART TWO: ORIGINAL RESEACH

Chapter 1: Children’s psychosocial characteristics associated with their cycling for transport ......59 Chapter 2.1: Socio-ecological factors associated with children’s independent mobility for transportation cycling .................................................................................................................69 Chapter 2.2: Neighborhood environmental factors associated with children’s active transport and the potential moderation of family co-participation ...........................................................................90 Chapter 3.1: Critical environmental factors associated with children’s cycling for transport: a qualitative study using bike-along interviews ..............................................................................98 Chapter 3.2: Creating cycling-friendly environments for children: are micro-scale environmental factors equally important across different street settings? .......................................................... 110 Chapter 3.3: Creating cycling-friendly environments for children: which micro-scale environmental factors are most important? ....................................................................................................... 130

PART THREE : GENERAL DISCUSSION 1. Are children’s individual characteristics important for their cycling for transport? ..................... 169 2. The role of parents and friends in children’s cycling for transport.............................................. 172 3.

Which physical environmental factors may create cycling-friendly environments for children? 175 3.1 Importance of macro-scale environmental factors for children’s cycling for transport ......... 175 3.2 Can micro-scale environmental factors influence the supportiveness of the environment for children’s cycling for transport? ................................................................................................ 177

4. How do factors across different levels of the socio-ecological model interact? .......................... 181 4.1 Individual moderators ......................................................................................................... 181 4.2 Parent-related moderators................................................................................................... 181 4.3 Physical environmental moderators ..................................................................................... 182 5. Factors associated with children’s independent mobility ........................................................... 186 6. Strengths and limitations ........................................................................................................... 189 7. Practical implications ................................................................................................................ 192

8. Directions for further research .................................................................................................. 195 9. Conclusions .............................................................................................................................. 199 10. References ................................................................................................................................ 200 11. Overview of A1 publications .................................................................................................... 209 Acknowledgements/dankwoord ................................................................................................ 211

Summary The development of a healthy lifestyle starts at a young age, and health behavior such as physical activity is known to track from childhood into adolescence and adulthood. One type of physical activity is cycling for transport. Currently, children’s cycling for transport levels are low, although it is an accessible, inexpensive and social-inclusive way to obtain the recommended daily hour of moderate-tovigorous physical activity. Prior to develop interventions aiming to increase children’s cycling for transport, insights are needed into which factors are associated with children’s cycling for transport. Therefore, the overall objective of this PhD study was to obtain insight into individual, social and physical environmental factors associated with children’s (aged 10-12 years old) cycling for transport. This overall objective was divided into three sub-objectives. The first objective of this PhD thesis was to explore whether children’s psychosocial characteristics were associated with their cycling for transport. Results indicated that children’s self-efficacy and perceptions of parental norm and modeling, and friends’ co-participation were positively associated with their cycling for transport. Parental defined independent mobility was positively associated with children’s cycling for transport. Additionally, children’s psychosocial characteristics were stronger related with children’s cycling for transport among children with a low compared to high independent mobility. The second objective of this PhD thesis was to examine how parents’ psychosocial factors and environmental perceptions were associated with children’s independent mobility and cycling for transport. Parents’ perceptions of children’s cycling and traffic skills were positively associated with children’s independent mobility. Additionally, presence and maintenance of cycling facilities and presence of a public transit stop were positively associated with independent mobility levels among girls with low socio-economic status. Finally, parents’ co-participation in active transport was positively associated with children’s active transport levels. The final objective was to investigate which physical environmental factors were associated with an environment’s supportiveness for children’s cycling for transport. The findings highlighted that

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providing cycling facilities well-separated from traffic is the most important factor to create cyclingfriendly environments for children. If a physical separation (such as a hedge or curb) is not possible to provide, line markings indicating a clear space where children are suggested to cycle may provide an alternative. Other micro-scale environmental factors (e.g. speed limitations, good maintenance, low traffic density) could also increase the supportiveness of an environment for children’s cycling for transport. Based on these results, it is suggested to develop future interventions with a multidimensional approach. Interventions should include both the child, by increasing self-efficacy and cycling/traffic skills, and the social environment, by increasing parental norm and modeling, and friends’ co-participation. Additionally, efforts should be made to create more cycling-friendly environments for children thereby targeting an increase in safety (perceptions) among children and parents. Providing cycling infrastructure well-separated from motorized traffic may be considered as an essential first step to increase traffic safety in order to promote cycling for transport among children.

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Samenvatting Het is belangrijk dat kinderen voldoende bewegen en deze gezonde levensstijl meenemen tot op latere leeftijd. Kinderen worden aanbevolen om dagelijks 60 minuten matig tot intens fysiek actief te zijn, door te spelen, te sporten, fietsen, lopen, … Zo kunnen kinderen zich dagelijks verplaatsen met de fiets naar bestemmingen in de buurt, zoals de school, sportclub, vrienden of familie. Deze vorm van fysieke activiteit, ook wel fietsen voor transport genoemd, kan redelijk eenvoudig geïntegreerd worden in de dagelijkse routine van het kind. Momenteel is er slechts een klein aantal kinderen die regelmatig fietst voor transport, en initiatieven zijn nodig om dit aantal te doen stijgen om zo meer kinderen voldoende te laten bewegen. Om deze initiatieven te ontwikkelen is het belangrijk inzicht te verkrijgen in welke factoren een associatie vertonen met het fietsen voor transport bij kinderen. Het hoofddoel van deze doctoraatsthesis was daarom na te gaan welke individuele, sociale en fysieke omgevingsfactoren geassocieerd zijn met het fietsen voor transport bij 10- tot 12-jarige kinderen. Het eerste doel van deze thesis was om na te gaan of bij kinderen psychosociale factoren geassocieerd zijn met het fietsen voor transport van het kind. Eigen-effectiviteit van het kind, percepties van ouderlijke norm en positieve voorbeeldfunctie van de ouders waren positief geassocieerd met fietsen voor transport van het kind. Kinderen die aangaven dat hun vrienden regelmatig met hen meefietsten, hadden een grotere kans om te fietsen voor transport. De associaties tussen de psychosociale kenmerken van het kind en fietsen voor transport waren sterker bij kinderen met een lage zelfstandige mobiliteit. De mate van zelfstandige mobiliteit was ook positief geassocieerd met fietsen voor transport. Als tweede doel werd er nagegaan welke ouderlijke (individuele, omgevings- en psychosociale) factoren geassocieerd zijn met de zelfstandige mobiliteit van kinderen. Zo bleek de perceptie van ouders over de fietsen verkeersvaardigheden van het kind positief gerelateerd te zijn met de zelfstandige mobiliteit. De aanwezigheid en het onderhoud van fietspaden en de aanwezigheid van een halte van openbaar vervoer waren positief geassocieerd met zelfstandige mobiliteit bij meisjes met een lage socioeconomische status. Ook bleek dat kinderen die vaker vergezeld werden door hun ouders tijdens het fietsen/wandelen, vaker fietsten/wandelen voor transport.

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Het laatste doel van deze thesis was om inzicht te verkrijgen in welke fysieke omgevingsfactoren een invloed hebben op de uitnodigendheid van een straat om te fietsen voor transport bij kinderen. Het voorzien van goed afgescheiden fietspaden bleek de grootste invloed te hebben op het creëren van fietsvriendelijke straten. Als een fysieke afscheiding (door een haag of borduur) niet mogelijk is, kunnen lijnmarkeringen een goed alternatief zijn om zo de plaats aan te duiden waar kinderen best fietsen. Andere micro-omgevingsfactoren (zoals snelheidsbeperkingen, goed onderhoud, lage verkeersdrukte) zijn eveneens factoren die een omgeving fietsvriendelijker kunnen maken. Samengevat tonen deze resultaten aan dat wanneer er interventies ontwikkeld worden die trachten het fietsgebruik van kinderen te stimuleren, er gebruik moet gemaakt worden van een multidimensionele aanpak. Hierbij zouden zowel kinderen als hun ouders en vrienden betrokken moeten worden. Dit kan onder andere door het kind zijn/haar fietsen verkeersvaardigheden alsook de eigen-effectiviteit te verbeteren, de perceptie van ouderlijke normen en de ouderlijke voorbeeldfunctie te verbeteren, en door kinderen te stimuleren om samen met hun vrienden te fietsen. Verder werd het belang van het creëren van een veilige fietsomgeving aangetoond. Het voorzien van voldoende fietspaden die goed afgescheiden zijn van het verkeer blijken hierbij een essentiële eerste stap te zijn.

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PART ONE: GENERAL INTRODUCTION

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GENERAL INTRODUCTION

1. Physical activity during childhood: guidelines, prevalence and health effects Being regularly physically active has been considered as one essential part of a strategy to adopt and maintain a healthy life style (Warburton et al. 2006). Physical activity is defined as any bodily movement of the skeletal muscles that requires energy expenditure (World Health Organization 2011). Four domains of physical activity exist, i.e. recreation, transportation, occupation and household (Sallis et al. 2006). For children, physical activity may include active play, games, sports, transportation, recreation, physical education or planned exercise as a sports club member (World Health Organization 2011). Children and youth between 5 and 17 years old are recommended to be active during 60 minutes daily at a moderate- to- vigorous intensity. In this PhD thesis we focus on children aged 10 to 12 years old and their parents as the transition from primary to secondary school has been identified as a risk period for decreases in physical activity levels (Cooper et al. 2012). Therefore, children from the last years of primary school (5th and 6th grade) seems an important target group to stimulate physical activity. Scientific evidence is clear: physical activity provides fundamental health benefits across the lifespan (Strong et al. 2005, Janssen et al. 2010), and physical inactivity is considered to be the fourth leading risk factor for global mortality (following high blood pressure, tobacco use and high blood glucose, respectively)(World Health Organization 2009). One hour of daily moderate- to vigorous-intensity physical activity was found to be protective against high blood cholesterol, high blood pressure, metabolic syndrome, low bone density and depression among children (Andersen et al. 2009, Janssen et al. 2010). Additionally, children who are sufficiently physical active have shown to have a better social and cognitive development (Kytta 2004) and have better fundamental movement skills (Lubans et al. 2010, Zwerts et al. 2015). Furthermore, children with insufficient physical activity have higher adiposity levels, lower cardiovascular fitness and lower self-esteem levels (Strong et al. 2005). The dose-response relationship indicates that the more time children spent being active, the more health benefits they obtain (Warburton et al. 2006). Furthermore, children’s physical (in)activity is known to track from childhood into adolescence and adulthood (Craigie et al. 2011). The tracking of children’s physical activity into

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GENERAL INTRODUCTION adulthood implies that children’s physical activity behavior is (indirectly) associated with health during later life. It seems therefore essential to promote physical activity already from an early age. Despite the many health benefits of regular physical activity, children’s physical activity levels are low (Hallal et al. 2012, Verloigne et al. 2012). Currently, only 30 to 40% of the 10- to 12-year olds meet the daily recommended guidelines (Telford et al. 2013). The secular trend of decreasing physical activity levels has been particularly dramatic among children, where outdoor play is being replaced by TV viewing or playing computer games whilst many children are driven to destinations rather than using active transport modes (walking or cycling) (Dollman et al. 2005). One of the best known consequences of children being insufficiently active is an imbalance between energy intake and expenditure, which resulted in the current childhood obesity epidemic (Lustig 2001). Currently, one out of three children aged 11 years is overweight or obese in Europe (World Health Organization 2012). Decreasing childhood obesity levels has therefore been considered as one of the most serious public health challenges of the early 21th century (World Health Organization 2012). Being overweight during childhood has serious health consequences at young age (e.g. cardiovascular problems) (Ebbeling et al. 2002), but 60% of the children being obese are likely to be obese when growing into adolescence and adulthood (World Health Organization 2012). In summary, it can be concluded that physical activity levels are low among 10- to 12- year old children and this has serious health consequences during childhood, but also in later life. Therefore, initiatives are needed to develop strategies to increase physical activity levels in this age group.

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2. Active transport and cycling for transport Active transport, or walking and cycling to destinations within the neighborhood, is one type of physical activity which can be integrated in children’s daily life relatively easy. Rather than finding additional time to spend on exercise, active transport can be part of a daily routine by traveling actively to destinations within the neighborhood, such as school, their friends, to shops etc. It can be considered as an inexpensive, accessible and social-inclusive type of physical activity, since it requires minimal skills and equipment. D’Haese and colleagues studied a feasible walking/cycling distance for children within primary school (D'Haese et al. 2011). These feasible distances were set at 1.5 kilometer for walking and 3.0 kilometer for cycling. By cycling, children can cover larger distances, but also at a faster pace increasing the attractiveness of cycling for children. Compared to walking, cycling is somewhat more physically intense, which results in better cardiovascular fitness compared to walking for transport (Andersen et al. 2011). Furthermore, children who cycle to school have higher odds of meeting the physical activity guidelines, compared to children walking to school (Roth et al. 2012).Children who cycle had also lower odds of being overweight or obese and had a lower Body Mass Index, while children who walked to school had only lower odds of being overweight (Ostergaard et al. 2012). Other health benefits of regularly cycling for transport are conform the benefits of being regularly physical active at a moderate intensity, including a better body composition, better cardiovascular fitness and cardiovascular health (Cooper et al. 2005, Cooper et al. 2006, Cooper et al. 2008, Andersen et al. 2009, Andersen et al. 2011, Oja et al. 2011). The benefits of cycling for transport are not limited to the individual’s health, but increasing cycling levels has also ecological and economic benefits as cycling may reduce traffic noise and traffic congestion, air pollution and carbon emissions (Woodcock et al. 2009). In Flanders, cycling to school is more prevalent than walking (D'Haese et al. 2011). However, only 30 % of Flemish children between 10 and 12 years old use the bicycle as their main transport mode for trips shorter than 3 kilometers (Mobiel Vlaanderen 2014). In Belgium, 8% of all trips across all ages are conducted by bicycle, which is much lower than cycling levels in countries with a well-developed cycling culture, such as the Netherlands (27%) and Denmark (18%) ,(Pucher et al. 2008, European

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GENERAL INTRODUCTION Commission 2014). It can therefore be concluded that there is still a large potential to increase cycling for transport levels among Flemish children aged 10-12 years old.

3. A socio-ecological approach to study children’s cycling for transport When aiming to increase children’s cycling for transport, it is essential to obtain insights into the key determinants of the behavior (Baranowski et al. 1998). In 2006, Sallis and colleagues developed a theoretical framework of the determinants of active living (Sallis et al. 2006). This framework includes four domains of active living, i.e. active recreation, active transport, household activities and occupational activities. When aiming to examine the key determinants of children’s cycling for transport, it is thus suggested to study behavior specific factors (e.g. variables which may be specifically important for cycling for transport may differ from factors being important for active play). Factors associated with cycling for transport might differ from factors associated with walking for transport, although studies exploring factors associated with active transport trips (including walking and cycling) might provide useful insights into how to increase both walking and cycling simultaneously. Secondly, the model is structured in different ‘onion’ layered levels, and each level represents a level of influence (see Figure 1).

In the center of the model, intrapersonal variables are shown representing the individual. This may include demographics (such as age), biological factors (gender, maturity), psychological factors (selfefficacy, attitude) and family situation (family socio-economic status, one or two-parents’ family). The four domains of active living are shown between the individual perceptions of the environment and the objective environment. The environment can be considered as both the physical as well as the social environment (Sallis et al. 2006). The physical environment can be defined as the characteristics of the physical context in which the individual spends its time, for example in the neighborhood or at home (Davison et al. 2006). This may include elements from the urban planning (e.g. natural elements, buildings), transportation systems (e.g. walking and cycling infrastructure) and land-use planning (i.e. relative locations of different land-uses such as workplaces, shopping areas and parks)(Handy et al. 2002). The social environment may be defined as the environment in which children’s social interaction

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GENERAL INTRODUCTION takes place, which includes peers, family, teachers, parents etc. who can provide support, can act as a role model, and may act as social partners to be physically active together (co-participation)(Verloigne et al. 2012). It is hypothesized that the environment can influence children’s behavior directly or indirectly through these perceptions of the environment. The third level of the model shows the behavioral settings in which physical activity may take place (e.g. neighborhood environment, school environment, home environment etc.) and its relevant environmental factors (i.e. walkability, parking etc.) that may influence behavior. These environmental factors may be relevant for only one domain of active living(Sallis et al. 2006). For example, provision of cycling facilities may be positively related with active transport, but it is probably not relevant for active recreation. In the fourth and last layer of the socio-ecological model, the policy environment is illustrated. Policy may affect all different layers of the model by developing laws (e.g. zone 30 km/h around schools), providing budget for healthenhancing programs and new (recreational/transport) facilities, media-attention, etc. (Sallis et al. 2006). Finally, the socio-ecological model posits that individual and environmental factors may interact (Sallis et al. 2006). This implies that individual characteristics may moderate associations between environmental factors and the behavior, as well that environmental factors may interact with each other (Bauman et al. 2002). At the start of this PhD, little information was available about which factors are associated with children’s cycling for transport. The scarcity in knowledge can be attributed to several reasons. Firstly, most of the studies conducted until 2012 considered walking and cycling as one behavior, or ‘active transport’, and studied the correlates of active transport in general rather than behavior-specific. Factors that are related to transportation cycling may differ from factors associated with walking for transport. Furthermore, the majority of studies focused on active travel to school, and limited evidence was available for active transport to other destinations. For example, when the distance to school may be too far to be covered by means of active transport, other destinations such as the sports club, a playground, friends and family may be suitable to be reached by bicycle. Prior to providing an overview on which factors have been identified as possibly associated with children’s cycling for transport, a brief overview is provided on how to assess cycling for transport and its potentially associated factors.

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Figure 1: the socio-ecological model of active living (Sallis, 2006).

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4. Measuring cycling for transport and its correlates 4.1 Methods to asses cycling for transport 4.1.1 Objective measurements To assess children’s cycling for transport objectively, children may be asked to wear an accelerometer in combination with a Global Positioning System (GPS). Accelerometers measure the accelerations made by the participant and provide an objective measure of the amount and intensity of physical activity (expressed as activity counts per minutes (cpm) (Sherar et al. 2011)). Physical activity categories can be created using specific cut points for the count per minutes. For example, the cut points of Evenson create four physical activity categories: sedentary behavior (0-100 cpm), light intensity (100-2295 cpm), moderate intensity (2296-4011) and vigorous intensity (≥ 4012 cpm) (Evenson et al. 2008). Although often used in physical activity research among children, hip-mounted accelerometers underestimate physical activities such as cycling due to the limited movement occurring at the trunk region while cycling (Robertson et al. 2011) and are therefore suggested to be complemented with a GPS-device (Duncan et al. 2009, Oliver et al. 2010, Dessing et al. 2014). The GPS-device measures the speed of the child’s movement, and based on the average and maximum speed, it can be defined whether the child is walking (1-10 km/h), cycling (> 10 km/h, < 25 km/h) or using motorized transport modes (>25 km/h). This may provide the number and duration of the cycling trips, as well as information about the route taken to reach the destination (e.g. distance, altitude, speed) (Carlson et al. 2015). This information can be combined with the accelerometer data, as in some situations, different transport modes may have similar speeds (e.g. cycling speed may be similar as a car being stuck in traffic), but differences in the accelerometer data may indicate that the child was physically active during that trip. The combination of accelerometer data and GPS coordinates allows to establish different outcome measures, such as minutes cycling per week and distance cycled per week (Demant Klinker et al. 2015). Furthermore, based on the GPS coordinates, purpose-specific amount of cycling can be obtained (either cycling for transport or recreational purposes) (Demant Klinker et al. 2015). Although highly accurate and objective

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GENERAL INTRODUCTION data can be obtained on cycling behavior among children, these measurements are costly and require a lot of experience in processing the data. 4.1.2 Subjective measurements Alternatively, children’s cycling for transport can be measured by self-reported measures, completed by the child or the parent. For example, the International Physical Activity Questionnaire (IPAQ) questions how many days the child cycled for transport during the last seven days, and questions how many minutes the child cycled on such a day, resulting in an outcome measure of minutes cycling per week (Craig et al. 2003). The IPAQ has been identified as a reliable and valid assessment of physical activity levels (Craig et al. 2003). Its questions, however, may be difficult to complete for children aged 10 to 12 years old, and are suggested to be completed by the child’s parent (i.e. proxy report) (Craig et al. 2003). Children may self-report their cycling for transport based on a five point Likert-scale, e.g. how many times did you cycle to school/other destinations within this week (response options: none, 1-2 times, 3-4 times, 5-6 times, more than 7 times)(Evenson et al. 2006). Another way to assess cycling for transport levels is asking the participant (child/parent of child) to keep a travel diary in which they report their cycling for transport per day (Oliver et al. 2014). These travel diaries can be added to accelerometer/GPS measurement to provide more context about the conducted trips, and may be used in case of technical deficits of the GPS/accelerometers. In travel diaries, the number and duration of each cycle trip are reported, which can be multiplied to obtain minutes cycling for transport per week. The advantage of these questionnaires and travel diaries is their low cost and their ability to assess physical activity behavior in specific contexts.

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4.2 Methods to assess individual and psychosocial factors associated with cycling for transport Theories such as the Theory of Planned Behavior (Ajzen 2011) and the Social Cognitive Theory (Bandura 1998) posit that children’s behavior is influenced by the child’s own psychosocial characteristics towards that behavior. In the current PhD dissertation, individual factors are considered to be proximal factors such as demographics, but also psychological factors such as attitude and selfefficacy. Social factors are in the current thesis defined as all factors which are related to the individual situated within its social environment. Factors such as social modeling, social norms and coparticipation are considered to be social factors. Together they are described as psychosocial characteristics of an individual. Psychosocial characteristics in physical activity research have most often been assessed by asking the participant to complete a questionnaire. Saunders and colleagues developed a questionnaire according to the Social Cognitive Theory, which assesses children’s selfefficacy, heath beliefs and social aspects towards their physical activity, and showed good reliability and validity (Saunders et al. 1997). Strauss and colleagues also developed questions to assess children’s self-efficacy, social influences and health beliefs towards physical activity, and used it to examine its potential correlation with children’s physical activity levels (Strauss et al. 2001). They found that selfefficacy and social influences were positively correlated with physical activity levels. It is likely that psychosocial characteristics of overall physical activity may differ to some extend from psychosocial characteristics of cycling for transport (Sallis et al. 2006). Therefore it is important to assess the context-specific correlates of cycling when this is the behavior of interest. Among adults, one study conducted in Flanders examined the association between their psychosocial characteristics towards cycling for transport and their cycling for transport levels (de Geus et al. 2008). These psychosocial questions were adapted from questions aiming to assess psychosocial characteristics towards overall physical activity (De Bourdeaudhuij et al. 2005). Instruments specifically designed to assess children’s self-reported psychosocial characteristics towards cycling for transport are currently not available. In most studies examining the association between children’s psychosocial characteristics

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GENERAL INTRODUCTION and active transport, parents were asked about their child’s psychosocial characteristics towards cycling for transport (Salmon et al. 2007, Panter et al. 2010, Ducheyne et al. 2012). One study conducted in the UK asked children on a two-point scale (yes-no) whether their friends and parents encouraged them to use active transport modes (Panter et al. 2010). This implies that when interested in assessing children’s own psychosocial characteristics towards their cycling for transport, a new questionnaire should be developed based on existing questionnaires (Sallis et al. 2006, Seabra et al. 2013, Seabra et al. 2013) on psychosocial characteristics towards overall physical activity. This questionnaire could include both questions regarding the individual (e.g. self-efficacy and attitudes) as well as perceptions of their social environment (e.g. social norms, social support).

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4.3 Methods to assess physical environmental factors associated with cycling for transport To study associations between the physical environment and cycling for transport (and active transport in general), a wide variety of methodologies have been used. An overview of different methodologies to assess these associations is given below, where the different methods are described accompanied with their advantages and disadvantages. This overview is based on a book chapter published in Cycling Future: from Research into Practice (Ghekiere et al. 2015). Both objective and subjective measures can provide researchers or urban planners insights into which environmental changes could be most effective in promoting cycling and walking (Brownson et al. 2009). A brief overview of each method can be found in Table 1 and further information is given below. It should be noted that this overview does not represent all potential assessment methods, but highlights some methods that are when studying physical environmental factors related with cycling for transport. For a complete overview of all potential methods to assess the physical environment, we would like to refer to the Active Living Research website: (http://activelivingresearch.org/toolsandresources/toolsandmeasures).

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GENERAL INTRODUCTION Table 1: A brief overview of the described methods

Assessment method

Objective measures

Comments Micro-environmental factors can be easily assessed but some training is needed. Some difficulties with assessing temporary items

Audit tools

such as traffic density, amount of shadow, etc. Auditing entire neighbourhoods is time consuming and researchers

Direct (on-site) Indirect

are restricted by weather and time constraints.

(Google Audits can be done at any time and place, but some sources may be

Street View)

out dated and some detailed features are difficult to assess. Different layers provide objective information of environmental features (e.g. walkability). Expertise is needed for analyzing this

GIS

information. Subjective measures

When perceptions of environments are of interest, practical to use in

Questionnaires

Walk-

and

large samples bike-

along interviews

Manipulated photographs

Discussing context-specific and detailed environmental factors while being in the target environment allows that no recall bias can occur, but no statistical relations can be determined. Causal relationships can be determined between various microenvironmental factors and the appeal to walk or cycle in that environment.

GIS: Geographical Information System; GPS: Global Positioning System

4.3.1 Objective measurements Using objective measures is appropriate when researchers or urban planners want to know exactly which, and how many, elements are actually present in a certain environment. Two objective measurements are described in the literature: 1. Audit tools and 2. Geographical Information Systems.

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4.3.1.1 Audit Tools A research team can use audit tools if they aim to assess the physical properties of a specific neighbourhood objectively. The researchers complete a checklist querying the presence or absence of certain physical elements for specific street segments (i.e. part of the street between two intersections) or neighbourhoods. These elements may include, for example presence of a cycle path, presence and number of trees, and traffic speed. The checklist can be completed on-site or using Google Street View. Recently, an audit tool was developed which assesses street characteristics of children’s cycling routes to school (Vanwolleghem et al. 2014). Audits using the Environmental Google Street View Based Audit – Cycling to school (EGA-Cycling) can be conducted either on-site or via Google Street View, and the methodology can be recommended when interested in assessing cycling-friendliness of environments or routes. This audit tool focusses specifically on detailed factors related to cycling to school. For example, it includes items such as alternatives for cyclists to swerve, degree of separation from motorized traffic and width of the cycle path. This Google Street view-based audit tool is a helpful instrument to assess macro-environmental features along cycling routes to school such as connectivity, distance to destination, number of houses etc. However, to assess environmental features at a microlevel in a cycling setting (detailed and temporary features), this Google Street view-based audit is recommended to be complemented with direct observations (Vanwolleghem et al. 2014).

Recent studies have shown that observations of the neighbourhood environment conducted by Google Street View show good inter-rater reliability (Kelly et al. 2013) and have a good validity against on-site audits (Badland et al. 2010, Clarke et al. 2010, Rundle et al. 2011). However, the level of agreement between a virtual neighbourhood audit using Google Street View and on-site field work was lower when qualitative and more detailed data (for example, quality of street conditions, presence of litter, openness of a street) and temporal items were assessed (for example, traffic volume can only be assessed based on a single time point of the Google Street View image) (Clarke et al. 2010, Rundle et al. 2011). A great advantage of using indirect observations is that conducting a virtual audit by Google Street View is

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GENERAL INTRODUCTION much quicker than on-site auditing (Badland et al. 2010), because the researcher can save time by staying indoors and it takes less time to complete audit tools since the researcher does not have to walk through the entire neighbourhood (Vanwolleghem et al. 2014). Additionally, observers are not restricted by weather conditions and can use Google Street View from any location and at any time of day.

4.3.1.2 Geographic Information Systems Geographic Information Systems (GIS) software is commonly used to objectively study the environmental factors influencing physical activity (Clifton et al. 2007, Clarke et al. 2008, Duncan et al. 2009, Wong et al. 2011). GIS-software is designed to capture, store, manipulate, analyze, manage and present all types of geographical data. In GIS, different layers (for example one layer with residential density, one layer with land-use mix and one layer with the locations of parks) show each physical environmental factor and can be objectively quantified and spatially assessed. The use of these layers (see Figure 2) allows for a visual analysis of the factors included in the layer for the selected spatial units of interest (Leslie et al. 2007). For example, GIS allows the measurement of distances between participant’s houses and parks, shops or recreation facilities. GIS is a straightforward method for objectively assessing the physical environment, but conducting good GIS analyses requires expertise (Wong et al. 2011). GIS-measures can also provide information about more detailed and qualitative factors (for example, evenness of cycle path, speed of cars) obtained from an audit and inserted in a GIS-layer.

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Figure 2: A simplified model of a Geographic Information System. GIS cuts vertically through data layers for analysis at known spatial locations (Leslie et al. 2007).

Global Positioning Systems (GPS) are useful tools to assess walking and cycling behaviour. They are preferably worn in combination with a device measuring physical activity (for example an accelerometer) as the researcher is then able to see where the participant is when activities of moderateto-vigorous intensity are performed (Duncan et al. 2009, Maddison et al. 2009, Cooper et al. 2010, Southward et al. 2012). The exact location where people are active can be determined based on the GPS coordinates. These GPS coordinates can then be linked to GIS measures and data from the accelerometer, to see the characteristics of the areas in which the participant is active. As the GPS coordinates change depending on the speed of movement, it is also possible to determine if someone is walking or cycling through these locations. GPS has been for example used in research tracking active transport through environments and it provided accurate measures of travel distances and travel speed (Duncan et al. 2007).

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4.3.2 Subjective measurements 4.3.2.1 Questionnaires Subjective measurements, such as those derived from questionnaires, are used by researchers if they want to obtain participants’ perception about the presence/absence of physical environmental factors. The use of questionnaires allows assessment of environmental perceptions of a large group of participants. Questionnaires can be administered face-to-face or by telephone interview, sent via post or can be completed online. In the next section, the Neighbourhood Environment Walkability Scale (NEWS), the most commonly used questionnaire, is briefly described. Additionally,

Neighbourhood Environment Walkability Scale (NEWS): The NEWS assesses perceived residential density, proximity and access to facilities, street connectivity, cycling and walking facilities, aesthetics, traffic safety and safety from crime (Saelens et al. 2003, Saelens et al. 2003). Ninety-eight items are scored on a four point Likert scale, ranging from one (strongly disagree) to four (strongly agree), with a higher score indicating a more favorable perception of the physical environmental element. This questionnaire is also available in an abbreviated version (A-NEWS) and one specifically adapted to younger populations (aged 11 and above) and their parents (NEWS-Y) (Cerin et al. 2006, Rosenberg et al. 2009). All these versions of the NEWS have shown good reliability and validity (Saelens et al. 2003, Cerin et al. 2006, Cerin et al. 2009, Rosenberg et al. 2009). Several studies have identified a relationship between items from the NEWS and various forms of physical activity (De Bourdeaudhuij et al. 2005, D'Haese et al. 2011, De Meester et al. 2013).

Physical Activity Neighborhood Environment Survey (PANES): PANES is a brief questionnaire which assesses the perceived neighborhood characteristics of the participants, based on a five pointscale (0=totally disagree, 5= totally agree) (Sallis et al. 2010). Given its shortness, PANES can be easily used within large scale surveys to obtain an indication about how participants perceive their neighborhood environment for walking and cycling behaviour. PANES has shown good reliability and good validity against the validated Abbreviated NEWS (Sallis et al. 2010).

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GENERAL INTRODUCTION Self-reported questionnaires are the most commonly used methods to assess the physical environment related to cycling for transport (or active transport in general) (Davison et al. 2006, Davison et al. 2008, Panter et al. 2008, Pont et al. 2009, Ding et al. 2012). At least three limitations are inherent to the use of questionnaires. Firstly, participants are asked to recall detailed and specific physical environmental factors within their neighborhood while not being in that target-environment, which may cause a mismatch with the actual neighborhood characteristics being present (Kusenbach 2003). Secondly, there is no consistent definition of ‘neighborhood’ across the different studies. For example, the neighborhood for children’s active transport was previously defined as the area surrounding the child’s residence within a 10 minutes’ walk (Rosenberg et al. 2009), but other studies used no definition of neighborhood, which may cause that participants interpret ‘neighborhood’ differently (Tappe et al. 2013). Finally, physical environmental factors may co-vary, i.e. some environmental factors tend to occur together. For example, benches are more prevalent in neighborhoods with a lot of vegetation. This co-variation of environmental factors makes it difficult to examine the effects of each environmental factor separately.

4.3.2.2 Qualitative research methods In addition to quantitative research methods, qualitative methods can be used to understand the relation between the physical environment and cycling for transport. These methods are beneficial, as not only can the potential environmental factors be identified, but they can also determine how and why these factors influence cycling and walking (Carpiano 2009). When the research team is mainly interested in the meaning of various environmental factors to an individual, qualitative research methods are the most appropriate ones. These can, for example, identify which environmental factors are important for increasing the amount of cycling and walking, but simultaneously, participants are able to explain why these factors are influencing their behaviour (Kusenbach 2003, Carpiano 2009). When physical environmental changes are planned in a specific neighbourhood, urban planners and researchers should be aware of what inhabitants want and need, in order to adjust the planned changes to these preferences and needs. The use of qualitative research methods is very appropriate for gathering this in-depth, personal and subjective information (Kusenbach 2003, Carpiano 2009).

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Walk- and bike-along interviews: The disadvantage of using surveys (such as the NEWS or PANES) or indoor qualitative individual or focus group interviews is that they require the participants to remember the physical environmental factors influencing cycling/walking while not being in the target environment (Kusenbach 2003, Carpiano 2009). To counteract these difficulties, researchers can visit participants at home and cycle or walk with them in their neighbourhoods. These methods are called bike- and walk-along interviews. During these cycle or walking tours, the participant is able to discuss his/her experiences, feelings or ideas while cycling/walking through his/her neighborhood. The participant interacts with the physical environment and can clearly indicate which environmental factors hinder or facilitate their cycling/walking for transport. Additionally, the participants are able to explain how these factors might influence their cycling/walking for transport and explain why they are important to them. As it would be unsafe to conduct the complete interview during cycling, a sport camera can be installed on the participant’s bicycle helmet, which records the physical environment and the accompanying comments of the participant. The video and voice recordings can be viewed afterwards, which allows in-depth discussion of the physical environmental factors. This unique interplay between participant, environment and researcher can provide in-depth, context-specific and detailed information that are difficult to captured by using qualitative indoor interviews, questionnaires or objective measurements.

4.3.2.3 Experimental research with manipulated photographs The use of photographs to study the association between the physical environment and physical activity has been suggested by Nasar in 2008 (Nasar 2008). Within photographs, environmental factors of depicted streets can relatively easy be modified compared to real-life environmental factors. Additionally, photographs may overcome disadvantages inherent to other methodologies (e.g. recall bias, definition of neighbourhood needed, co-variation between factors). Photographs neither require a specific definition of a neighborhood, as the street is depicted in the photograph, nor do participants have to recall specific elements from that neighborhood/street while not being in that neighborhood/street (Nasar 2008, Stamps 2010). Additionally, photographs allow to conduct

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GENERAL INTRODUCTION manipulations in a very controlled way, which is not always possible to do in real-life situations. Experimental research is considered as the best way to examine causality between physical environmental factors and cycling for transport. Researchers may conduct a natural experiment by observing the effect on cycling behavior when one environmental factor is modified in a specific street. Conducting this type of on-site experimental research is needed, but very time-consuming and expensive. Additionally, it is advisable to conduct extensive explorative research on how the physical environment might affect cycling for transport and which environmental changes might be most effective to change cycling behavior. Rather than making guesses about which changes could be effective, this explorative research provides insight into which physical environmental factors would be best to change within the neighborhood and thus may prevent conducting ineffective structural changes to the physical environment. The experimental use of manipulated photographs seems therefore a potential strategy to explore the causal association between the physical environment and cycling for transport. As photographs do not allow to study the effects on changes in actual cycling behaviour, this may be a suitable methodology to study associations between physical environmental changes and supportiveness of an environment for cycling for transport. At the start of this PhD, the use of manipulated photographs had not been applied yet to study the association between the physical environment and cycling for transport.

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5. Socio-ecological factors associated with children’s cycling for transport 5.1 Individual factors When young children age, children’s walking and cycling levels increase until they reach adolescence (Timperio et al. 2006, Trapp et al. 2011, De Meester et al. 2014) and steeply declines during adolescence and adulthood (Chillón et al. 2011, European Commission 2014). Most previous studies indicated that boys are more engaged in active transport compared to girls, and this difference is observed globally (Davison et al. 2008, Davison et al. 2008, Panter et al. 2008, Biddle et al. 2011, Trapp et al. 2011). In an Australian study, area level socio-economic status was positively associated with children’s active transport (Timperio et al. 2006). In contrast, children from parents with a low income had higher active transport levels compared to children from middle- or high-income families in Sweden (Johansson et al. 2012). However, in a Flemish study, no associations were found between educational attainment of the parents and active transport to school (D'Haese et al. 2011). Despite the positive association between children’s socio-economic status and general physical activity (Stalsberg et al. 2010), there is no consistent association between children’s socio-economic status and involvement in active transport.

Studies considering traffic accidents show that cycling children are mostly involved in single-bicycle accidents, stressing the importance of children’s cycling and traffic skills (Schepers et al. 2012). Therefore, programs have been developed in different countries aiming to increase these essential cycling and traffic skills among primary school-aged children. Children who participated in such cycling training programs have been shown to have better cycling skills (Ducheyne et al. 2013, Goodman et al. 2016), and thus useful when aiming to increase children’s skills to safely navigate within the neighborhood. However, current cycling training programs were unable to induce a behavior change regarding the participants’ cycling for transport levels (Ducheyne et al. 2013, Goodman et al. 2016). These researchers suggest that other strategies are needed to increase children’s cycling for transport levels as increasing cycling skills and children’s cycling for transport levels are two different goals. For example, Chillon and colleagues evaluated interventions aiming to increase active transport levels, and found that several strategies can be used to increase active transport levels to school (Chillon et al. 2011).

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GENERAL INTRODUCTION Traffic safety improvements such as sidewalk improvements, crossing improvements and speed control improvements were effective strategies to increase children’s walking to school (Boarnet et al. 2005). Insight into how to increase children’s cycling for transport levels are needed as only one intervention aiming to increase children’s cycling to school levels was found. This intervention did not succeeded in increasing children’s cycling levels when schools adopted a cycling promotional campaign (Ostergaard et al. 2015). Theories such as the Theory of Planned Behavior (Ajzen 2011) and the Social Cognitive Theory (Bandura 1998) posit that children’s behavior is influenced by the child’s own psychological characteristics towards that behavior. Currently, limited knowledge exists on how children’s own psychological characteristics are associated with their transportation cycling. There are a few studies available considering the influence of children’s psychological characteristics on active transport, with most of them being parent-reported and formulated in a non-context-specific way (e.g. barriers of general physical activity rather than focused on barriers for active transport/cycling for transport). For example, Salmon and colleagues concluded that Australian children’s preference (parent-reported) for being driven to school was negatively associated with walking to school (Salmon et al. 2007). Additionally, children with a positive attitude towards cycling to school (parent-reported) were more likely to cycle to school in a Flemish study (Ducheyne et al. 2012). There is a scarcity in research providing insight into the association between children’s psychological characteristics and their cycling for transport, and more research is therefore warranted to further elaborate the current knowledge on this association.

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5.2 Social factors Children should be observed in their broader social context in which their family and friends play an important role in stimulating healthy behavior. Evidence regarding parent’s role in children’s physical activity has emerged during the last decades. Biddle and colleagues concluded in their review of reviews that parents have a very important role in determining children’s physical activity (Biddle et al. 2011). Strong evidence has been found for the positive association between parental encouragement, involvement and facilitation of children’s physical activity and their child’s physical activity levels (Gustafson et al. 2006, Van Der Horst et al. 2007). Parents provide their child also logistic support (Verloigne et al. 2012). Evidence from a systematic review on the influence of friends on children’s physical activity indicated that having friends’ being physically active with them (co-participation) as well as friends’ modeling and friends’ encouragement are positively associated with children’s physical activity (Maturo et al. 2013). Given the importance of significant others on overall physical activity, it can be hypothesized that parents and friends may play an important role in determining cycling for transport as well (Griffith et al. 2007). However, the evidence for these associations is less extensively studied. Parental perceived convenience of driving children to a destination is known to be negatively associated with the amount of active transport among children (Van Der Horst et al. 2007, Faulkner et al. 2010). Additionally, parents encouragement to cycle to school may be positively associated with children’s cycling to school (Ducheyne et al. 2012). Similarly, when parents perceived that their child has friends encouraging them to cycle to school, children were more likely to cycle to school in a Flemish study (Ducheyne et al. 2012). In another study conducted among Flemish children, the social aspect of traveling together was considered to be important for children’s travel behavior (Zwerts et al. 2010). Brown and colleagues also found that traveling in groups was more important among girls compared to boys (Brown et al. 2008). Furthermore, parents’ attitude towards cycling and their own cycling for transport are likely to be associated with cycling for transport levels of their child. For example, in California, children cycled more often to soccer training when their parents also cycled for transport, compared to children whose parents never cycled for transport (Tal et al. 2008).

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GENERAL INTRODUCTION Parents’ decision to let their child cycle (independently) is also hypothesized to be influenced by parents’ perceptions of the supportiveness of the physical environment within a neighborhood, or along a particular cycling route (Carver et al. 2008). Parental perceptions and objectively assessed physical environmental factors previously found to be associated with children’s active transport and cycling for transport are discussed in the next section (5.3 Physical environmental factors). In addition to providing their child social support towards cycling for transport and their judgement of whether the neighborhood is sufficiently supportive, parents may implement rules regarding their child’s cycling (Salmon et al. 2005). For example, parents may indicate whether children are allowed to cycle (a specific distance) without adult supervision, a parenting practice which has been identified as setting children’s independent mobility (Hillman et al. 1990). During the last decades, children’s independent mobility has dramatically decreased worldwide (Hillman et al. 1991, Kytta 2004, Fyhri et al. 2011, Villanueva et al. 2012, Mitra 2013, Schoeppe et al. 2015). For example, in Australia, the proportion of children walking or cycling independent (without adult supervision) to school has decreased from 61% in 1991 to 32% in 2012 (Schoeppe et al. 2015). This is an undesirable trend that has been observed in many countries (Fyhri et al. 2011). Children who are allowed to be independently mobile for some distance are more likely to use active transport, and are generally more physically active (Page et al. 2009, Schoeppe et al. 2013). Additionally, when children are more driven to activities, children’s knowledge of the neighborhood is less developed, and children are less experienced in finding their way in the neighborhood (Fyhri et al. 2011). Furthermore, children who are allowed some independent mobility have improved development of motor and cognitive skills (Brown et al. 2008). When children mature, parents are more comfortable with children’s ability to safely navigate within their neighborhood, and parents are more likely to let their child cycle without adult supervision (McDonald 2012). Insights are thus needed into which factors make parents restrict their children’s independent mobility levels.

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5.3 Physical environmental factors Until the year 2000, public health researchers were mainly interested in individual and psychosocial determinants of physical activity (Sallis et al. 2006). Interventions aiming to increase physical activity based on changing individual characteristics reached only a small number of people, had limited effect on increasing physical activities and these increases were not maintained in the long therm. Therefore, public health researchers have made a shift to situate individuals within a broader environment (Sallis et al. 2006), with the idea that when the environment is supportive for physical activity, people will be more likely to be physically active. Next to public health scientists who are interested in how to create supportive environments to improve individuals’ health, geographers and urban planners have conducted many interesting studies, in which their major aim was to obtain information on individual’s mobility behavior and the reasons why people behave in this way. In what follows, we provide evidence from both the public health as the transport geography perspective on which physical environmental factors might stimulate children’s cycling for transport. The physical environment can be defined as objective and perceived characteristics of the physical context where people spend their time, for example in their neighborhood or in streets (Davison et al. 2006, Pont et al. 2009, Ding et al. 2012). The physical environment as defined here can reflect the potential path area, which refers to the spatial extent in which individuals could spent their time (Patterson et al. 2015). Additionally, it reflects the children’s activity spaces, which are those areas in which children have direct contact with the environment as a result of day-to-day activities, which are considered to be better known by the children (Patterson et al. 2015). Physical environmental factors can be divided into two broad categories: (1) macro-scale environmental factors, including the raw urban planning characteristics from a neighborhood environment (e.g. street connectivity, diversity in landuse) and, (2) micro-scale environmental factors which are smaller and more detailed characteristics in the environment or street (e.g. width of cycle path, amount of vegetation in the street, traffic speed).

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GENERAL INTRODUCTION There is currently no systematic review available on physical environmental factors related to children’s cycling for transport. At the start of this PhD, there were three reviews available which studied the associations between physical environmental factors and children’s active transport in general (Panter et al. 2008, Pont et al. 2009) and active transport to school (Wong et al. 2011). Two of these reviews had a limited number of studies included (Panter et al. 2008, Wong et al. 2011) (24 and 14, respectively). This resulted in only a few studies examining the same physical environmental factors and limited the ability to draw conclusions based on these results. All reviews studied active transport as one single behavior, rather than studying the correlates for walking and cycling separately. Additionally, the reviews emphasized the importance of studying the associations between the physical environment and children’s active transport in a European context, as most of the studies were conducted in Australia and the United States. The three reviews agreed on the negative association between distance to destinations and children’s active transport (Panter et al. 2008, Pont et al. 2009, Wong et al. 2011). A more recent study within a Flemish sample of children observed that when children live within a feasible cycling-distance (i.e. 3km) from a destination, they are more likely to cycle for transport (D'Haese et al. 2011).. Some evidence was found for a positive relationship between land-use mix and active transport, with having a mixed or commercial land-use being associated with more active transport (Pont et al. 2009). Furthermore, evidence suggests that residential density might be positively associated with children’s active transport (Pont et al. 2009). Route directness appeared to be negatively related with children’s active transport, as children used more often indirect routes to reach their destination (Panter et al. 2008, Wong et al. 2011). Distance to destination, residential density, land-use mix and route directness are all factors that can be considered as macro-scale factors, which are relatively difficult to change within existing neighborhoods. When creating new neighborhoods, urban planners should acknowlegde the importance of these factors in stimulating children’s active transport. However, it might be more relevant to examine the effect of more amenable, micro-scale factors, as these can be changed relatively easy in existing neighborhoods as these factors are the responsibility of local actors within the community. The number of studies that examined these micro-scale factors is much lower compared to studies for example on

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GENERAL INTRODUCTION the association of distance with cycling for transport. This makes it difficult to identify the importance of these micro-scale factors, given the limited studies examining the same micro-scale factors. The associations of several micro-scale factors are therefore inconsistent across the reviews, and some environmental factors that are hypothesized to have an influence on children’s cycling for transport have not been studied yet. For example, Pont and colleagues and Wong and colleagues found a possible positive association between the presence of walking and cycling infrastructure and children’s active transport (Pont et al. 2009, Wong et al. 2011), although Panter’s review was not able to confirm this association (Panter et al. 2008). Panter and colleagues indicated the importance of safety en-route, but safety was consistently not associated with active transport within the review of Pont and colleagues (Panter et al. 2008, Pont et al. 2009),. Carver and colleagues however stressed the importance of traffic safety for children’s physical activity in general (Carver et al. 2008). Finally, the reviews found mixed results for aesthetical features such as trees, presence of litter and bad smells (Panter et al. 2008, Pont et al. 2009). As children are more physically active at places which are aesthetically appealing (Ding et al. 2011), it may be that maintenance and vegetation are also of importance for cycling for transport among children. Very recently, a systematic review was published by D’Haese and colleagues which investigates crosscontinental differences in associations between the physical environment and active transport among children (D'Haese et al. 2015). This was the first review which explored physical environmental factors associated specifically with cycling for transport, and distinguished between factors associated with cycling to school and cycling for leisure (to other destinations than school). Results indicated a possible positive association between cycling to school and traffic safety, but no association was found for street connectivity, walk/cycle facilities, aesthetics and overall safety (D'Haese et al. 2015). Cycling for transport during leisure was not associated with traffic safety or presence of recreational facilities (D'Haese et al. 2015). Currently, little evidence is established on which cycling-specific environmental factors may inhibit or stimulate children’s cycling for transport. For example, provision of cycling infrastructure, motorized traffic speed and traffic density might affect both perceptions of safety as well objectively measured

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GENERAL INTRODUCTION safety (i.e. number of accidents) (Reynolds et al. 2009) and might therefore be related with children’s cycling for transport. Parents and children indicated that they both preferred cycling over other transport modes, but traffic safety perceptions prevented parents to allow their child to cycle (Christie et al. 2011). Children disliked to cycle in streets with heavy traffic (Christie et al. 2011). There is currently no evidence about which type of cycling infrastructure is preferred for children’s cycling for transport, although research indicated that there are less accidents on cycling paths compared to shared paths (both walking and cycling) (de Rome et al. 2014). Furthermore, it could be hypothesized that evenness of cycling facilities could affect children’s cycling for transport, given the needed skills to handle the bicycle when cycling on uneven surfaces. It can be concluded that children’s cycling for transport is more prevalent when distance to destinations are short. Additionally, cycling for transport is likely to be related with physical environmental factors within the neighborhood, as well as en-route, but little evidence exists for micro-scale environmental factors and factors specifically related to cycling for transport. It is currently unclear which physical environmental factor might be most important for children’s cycling for transport. Furthermore, obtaining insight into what children like in the physical environment to stimulate them to cycle for transport might be important, as environments should be made supportive for their cycling (Fusco et al. 2012). A study using photo-voice highlighted that children’s perspectives on environmental supportiveness might differ from adults’ perspectives (Buliung et al. 2012, Fusco et al. 2012).

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6. Problem statement and outline of this thesis Currently, more than 60% of 10- to 12- year old children is insufficiently physically active, despite the strong evidence of health benefits of regular physical activity (Hallal et al. 2012). Increasing children’s physical activity levels is considered as one of the key strategies in fighting the obesity epidemic among children. Cycling for transport is considered as accessible, socially-inclusive and inexpensive type of physical activity, which can easily be integrated in children’s daily routine. When aiming to develop effective interventions targeting an increase in children’s cycling for transport, extensive explorative research is needed to gain insight into which factors might be most effective to change in order to increase children’s cycling for transport. The main objective of this PhD thesis was to obtain insights into which factors from the socioecological model are associated with children’s cycling for transport. At the start of this PhD thesis, correlates of cycling for transport were examined in only a very limited number of studies. Most previous studies investigated correlates of general active transport (including cycling and walking) among children (Panter et al. 2008, Fraser et al. 2011). However, cycling and walking for transport are two different behaviors which might be influenced by a variety of different factors. It is not likely that changing factors in favor of walking would stimulate cycling for transport as well. Additionally, most previous studies were conducted in Australia and the United States (Panter et al. 2008, Pont et al. 2009, Wong et al. 2011), and findings from these studies may not be generalizable to a European context. Furthermore, most previous studies focused on active transport to school, although active transport to other destinations than school might also be of interest, as children may walk or cycle within their neighborhood, to friends, family or leisure activities (Panter et al. 2008, D'Haese et al. 2011). The first aim of this thesis was to examine associations between children’s own psychosocial characteristics and their cycling for transport (Chapter 1). A few previous studies investigated associations between parent-reported psychosocial correlates of the child and their active transport (Salmon et al. 2007, Panter et al. 2010, Ducheyne et al. 2012). But, no evidence exists on how children’s own psychological factors (such as self-efficacy, perceived barriers/benefits) and social characteristics (such as modeling and support from parents, friends, siblings) as reported by the child

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GENERAL INTRODUCTION might be associated with their cycling for transport. Additionally, we aimed to explore how this association between children’s psychosocial factors and their cycling for transport might differ according to the amount of independent mobility, family socio-economic status and gender of the child. It might be that children’s psychosocial characteristics are not associated with their cycling for transport when they are not allowed to cycle some distance without adult supervision (low independent mobility). Furthermore, associations between children’s psychosocial characteristics and their cycling may differ according to the child’s gender and socio-economic status. Insight into these moderating effects may improve the tailoring of future interventions aiming to increase children’s psychosocial characteristics towards their cycling for transport. Finally, we aimed to identify the association between children’s independent mobility and their cycling for transport in a Flemish sample of children, as a strong positive association was previously found in Australian and Canadian studies (Mitra 2013, Schoeppe et al. 2013).

The socio-ecological model posits that individuals should be situated within their broader context, which includes both the social as well as the physical environment (Sallis et al. 2015). The second aim of this PhD thesis was to explore the role of independent mobility and other parentrelated factors in relation to children’s cycling for transport. Parents are acknowledged to play an important role in determining children’s general physical activity (Verloigne et al. 2012). Therefore, it is suggested that this is also the case for active transport and cycling for transport (Panter et al. 2008), although these associations are less extensively studied. In order to accomplish this objective, two studies were conducted (Chapter 2.1 and Chapter 2.2). Our study described in Chapter 1 highlighted the importance of parental-defined independent mobility. When children are allowed to cycle some distance on their own, the chance of being involved in cycling for transport is higher compared to children who are not allowed to cycle without adult supervision. In addition to the benefits of independent mobility for active transport, children’s spatial, social, motor and analytical skills may be better developed when they are allowed to cycle some distance without adult supervision (Davis et al. 1996, Bixler et al. 2002, Mackett et al. 2007, Brown et al. 2008). Children who travel and play on their own may also demonstrate greater knowledge about their neighborhoods and a

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GENERAL INTRODUCTION more sophisticated sense of community compared with those who are less independent (Rissotto et al. 2002). Despite the benefits of children being independently mobile, children’s independent mobility has decreased dramatically worldwide (Fyhri et al. 2011, Schoeppe et al. 2015). Currently, it is not clear what may have induced this decline, and what factors are associated with children’s independent mobility. Factors that are suggested to be related with children’s independent mobility are parental perceptions of the neighborhood environment (for example safety perceptions, presence of cycle infrastructure) (Fyhri et al. 2009, Page et al. 2010, Alparone et al. 2012), as well as individual characteristics of the child and parents themselves (Mitra 2013). It is currently known that independent mobility increases with age, and that boys have more independent mobility compared to girls (Brown et al. 2008, Mitra 2013). However, insights into which other factors may be associated with children’s independent mobility are needed, given the scarcity of the studies examining this association. Therefore, the objective of the first study within our second aim was to determine which factors from the socioecological model are associated with children’s independent mobility (Chapter 2.1). In addition to examining these direct associations, it was investigated whether these associations differed according to the gender of the child, family socio-economic status and urbanization level. In the second study, it was examined whether the association between objectively assessed physical environmental factors and children’s walking/cycling was moderated by frequency of parental accompaniment when walking/cycling (Chapter 2.2). Parental co-participation during active transport might mitigate the importance of the physical environmental factors, as parents can teach their child to safely navigate within the neighborhood, and teach them to use the safest routes to the destination. By studying moderating effects of parental co-participation in the association between active transport and the physical environmental factors, insight may be obtained on why previous studies examining the associations between the physical environment and active transport yielded inconsistent results (Davison et al. 2006, Panter et al. 2008).

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GENERAL INTRODUCTION Besides individual and social environmental factors, the socio-ecological model emphasizes the importance of physical environmental factors (Sallis et al. 2015). To address the limitations inherent to traditional research methods such as using questionnaires, the third aim was to develop and apply innovative research methods to examine which physical environmental factors are (potentially) associated with children’s cycling for transport. Three consecutive studies were conducted to achieve this objective. Given the limited amount of studies investigating the environmental correlates of children’s cycling for transport specifically, a first qualitative study was conducted to obtain an overview of all environmental factors that could potentially be associated with children’s cycling for transport (Chapter 3.1). Therefore, Flemish children and their parents cycled to a destination together with a researcher, and discussed all environmental factors that could facilitate or hinder their (child’s) cycling for transport. As described in the introduction, the use of bike-along interviews benefits from the fact that context-specific environmental factors can be discussed while being in the target environment and this limits the recall bias inherent to self-reported questionnaires. Additionally, children and parents were able to explain why certain environmental factors were important for them. This qualitative study provided in-depth information about environmental factors that might be associated with children’s cycling for transport. Although informative, qualitative study designs do not allow to examine causal associations. In the current literature, there is a paucity of studies using experimental research designs, which are considered as the best research designs to study causal relationships between the physical environment and cycling for transport (Ogilvie et al. 2010). Conducting on-site real-life experiments is expensive, time-consuming and difficult to control within a research context. Nasar suggested therefore to use photographs in an experimental way (Nasar 2008), as photographs are much easier and less expensive to change, and the manipulations can be conducted in a very controlled manner. However, at the start of this PhD, no studies were conducted that used manipulated photographs to study the physical environment – physical activity associations among children.

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GENERAL INTRODUCTION The experimental use of manipulated photographs allows to determine in a laboratory setting factors influencing the supportiveness of a street for cycling for transport. Prior to the development of the current study among children, two studies among adults successfully used manipulated photographs to study the effect on changing physical micro-scale environmental factors (such as presence of a bench, amount of vegetation, width of the cycle path etc.) on the supportiveness of a street for walking (Van Cauwenberg et al. 2014) and cycling for transport (Mertens et al. 2014). Despite the innovative approach of these studies, they were limited in their generalizability of the findings, as the environmental factors were only manipulated in one typical urban street in Flanders. It was unclear whether these findings may hold for other types of streets, for example in less densely built streets, or in streets with a higher landuse mix. Additionally, there was no quantitative evidence on whether micro-scale environmental factors could have an influence on the supportiveness for a specific street to cycle along among children. Therefore, in the first experimental pilot study, we aimed to determine whether changing a limited number of micro-scale environmental factors had an effect on the supportiveness of a street for children’s cycling for transport, and whether changing these micro-scale environmental factors was equally effective across different street settings (Chapter 3.2). Therefore, we used a choice-based conjoint methodology, in which children and parents were shown two different manipulated photographs of a street and they were asked which route they preferred (their child) to cycle along to a friend living in their neighborhood. This methodology allows many environmental factors to be included at the same time, mimicking real-life choices, rather than studying the effect of each micro-scale environmental factor on its own. Additionally, choice-based conjoint analyses allows studying the relative importance of each micro-scale environmental factor without showing the participant all potential combinations of photographs, which limits the time needed to complete the questionnaire. As the effect of changing micro-scale environmental factors was similar across different street settings (Chapter 3.2), the use of only one street setting could be justified. In our second and last experimental study, we aimed to investigate which micro-scale environmental factor was most important to change in order to create a cycling-friendly environment for children (Chapter 3.3). Secondly, the aim was to identify whether subgroups exist. Participants within one subgroup have similar preferences for

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GENERAL INTRODUCTION environmental factors, but they may differ in other characteristics such as cycling levels, gender, SES etc. The existence of subgroups could explain why previous cross-sectional studies found inconsistent associations between micro-scale environmental factors and children’s cycling from transport. Insights into how individual factors might affect preferences for specific environmental factors is lacking, although this knowledge is essential for tailoring future environmental changes based on the individuals’ needs.

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7. Publications included in this thesis Chapter 1: Ghekiere A, Van Cauwenberg J, Carver A, Mertens L, de Geus B, Clarys P, Cardon G, De Bourdeaudhuij I, Deforche B: Pyschosocial factors associated with children's cycling for transport: A cross-sectional moderation study. Preventive Medicine 2016, 86:141-146.

Chapter 2.1: Ghekiere A, Carver A, Veitch J, Salmon J, Deforche B, Timperio A: Does parental accompaniment when walking or cycling moderate the association between physical neighbourhood environment and active transport among 10–12 year olds? Journal of Science and Medicine in Sport 2016, 19:149-153.

Chapter 2.2: Ghekiere A, Deforche B, Carver A, Mertens L, de Geus B, Clarys P, Cardon G, De Bourdeaudhuij I, Van Cauwenberg J: Insights into children's independent mobility for transportation cycling: which socio-ecological factors matter? Journal of Science and Medicine in Sport under re-review.

Chapter 3.1: Ghekiere A, Van Cauwenberg J, de Geus B, Clarys P, Cardon G, Salmon J, De Bourdeaudhuij I, Deforche B: Critical Environmental Factors for Transportation Cycling in Children: A Qualitative Study Using Bike-Along Interviews. Plos One 2014, 9 (9): e106696.

Chapter 3.2: Ghekiere A, Van Cauwenberg J, Mertens L, de Geus B, Clarys P, Cardon G, Salmon J, Nasar, De Bourdeaudhuij I, Deforche B: Assessing cycling-friendly environments for children: are microenvironmental factors equally important across different street settings? International Journal of Behavioral Nutrition and Physical Activity 2015, 12 (1): 54.

Chapter 3.3: Ghekiere A, Deforche B, Mertens L, de Geus B, Clarys P, Cardon G, Salmon J, Nasar, De Bourdeaudhuij I, Van Cauwenberg J: Creating Cycling-Friendly Environments for Children: Which Micro-Scale Factors Are Most Important? An Experimental Study Using Manipulated Photographs. Plos One, 2015, 10 (12): e0143302.

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GENERAL AIM: To obtain insights into the socio-ecological factors associated with children's cycling for transport Aim 1: To identify children's individual characteristics related to cycling for transport CHAPTER

STUDY DESIGN -

Chapter 1 -

Cross-sectional online survey Random sample of 5th and 6th grade children across 45 primary schools in Flanders, Belgium (November – December 2014) N=1232

STUDY AIMS METHODS - To examine direct associations between - children reported on a 5-point Likert-scale children’s psychosocial characteristics and their perceived benefits, perceived their odds of being a cyclist/volume of cycling barriers, social norms, self-efficacy, co- To examine the role of independent mobility participation, encouragement and on children’s cycling for transport modeling. - To explore whether associations between - Outcome: Parents reported minutes children’s psychosocial characteristics and children’s cycling for transport in a usual children’s cycling for transport were week (IPAQ) moderated by children’s gender, independent Hurdle models: odds ratio and gamma mobility and family SES regression coefficient

Aim 2: To explore the role of independent mobility and other parent-related factors in relation to children's cycling for transport CHAPTER

STUDY DESIGN -

Chapter 2.1 -

Cross-sectional online survey Random sample of parents of children from 5th and 6th grade across 45 primary schools in Flanders, Belgium (November 2014 – January 2015) N=1286

STUDY AIMS - To examine direct associations between parents’ and children’s demographics, children’s cycling/traffic skills, parents’ psychosocial characteristics and parents’ neighborhood perceptions and children’s independent mobility - To explore whether these associations differ according to gender of the child, family SES or urbanization level

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METHODS - Parents completed their and their child’s demographics, their psychosocial characteristics towards cycling for transport and their neighborhood perceptions - Parents reported perceptions of children’s cycling and traffic skills - Outcome: Parents reported distance their child is allowed to cycle without adult supervision (independent mobility) - Multilevel linear regressions


-

Chapter 2.2

Cross-sectional survey Parents of children from 5th and 6th grade across 19 schools in Melbourne, Australia (2001) - N=677 - Secondary data analysis

- To examine the direct association between the objectively assessed neighborhood environmental factors and children’s number of active trips (including walking/cycling) - To examine the moderating role of parental coparticipation on the association between the objective physical environmental factors and children’s number of active trips

- Physical neighborhood environmental factors were objectively assessed with GIS within a 800m buffer around participants’ residence. - Parents reported how often they accompany their child during walking/cycling (=coparticipation) - Outcome: Parents reported children’s usual walking/cycling trips per week to 8 local destinations. - Multilevel linear regressions

Subaim 3: To explore which physical environmental factors are (potentially) associated with children’s cycling for transport using two innovative research methods CHAPTER

STUDY DESIGN -

Chapter 3.1

-

Qualitative bike-along interviews Convenience sample of children from 5th and 6th grade and one of their parents, in Flanders, Belgium (February – May 2013) N= 35 children and 35 parents

STUDY AIMS METHODS - To examine which physical environmental - Children and one of their parents cycled to factors might be associated with children’s a destination within their neighborhood, cycling for transport and discussed all environmental factors facilitating/inhibiting children’s cycling - To develop a new way of gaining in-depth and for transport context specific information on potential correlates of children’s physical activity - Grounded theory approach, inductive behavior

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CHAPTER

STUDY DESIGN -

Chapter 3.2

-

Chapter 3.3 -

Experiment with manipulated photographs Random sample of children from 5th and 6th grade and one of their parents across 12 primary schools in Flanders, Belgium (March - April 2014) N=305 matched child-parent pairs

STUDY AIMS - To test whether micro-scale environmental factors influence route choice among children and parents (for their child’s cycling) - To examine the relative importance of the four environmental factors to create cyclingfriendly environments for children’s cycling for transport - To identify whether the importance of microscale environmental factors differs according to the type of street stetting

Experiment with manipulated photographs Random sample of children from 5th and 6th grade and one parent across 45 primary schools in Flanders, Belgium (November – December 2014) N=1232 matched child-parent pairs

To examine the relative importance of these micro-scale environmental factors in route choices to (let their child) cycle for transport To explore whether subgroups exists which share similar preferences for particular environmental factors To identify the characteristics of these subgroups

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METHODS - Online questionnaire with an integrated choice-based conjoint task - Photographs manipulated in 4 environmental factors: street setting (macro), evenness of cycle path, degree of separation, traffic speed - Hierarchical Bayes analyses to examine main effects and two-way interaction effects between the street setting and the three other micro-scale environmental factors - Online questionnaire with an integrated choice-based conjoint task - Photographs manipulated in 7 micro-scale environmental factors: type of cycle path, evenness of cycle path, traffic speed, traffic density, maintenance, speed bump, vegetation. - Hierarchical Bayes analyses to examine main effects - Latent class analyses to identify subgroups


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PART TWO: ORIGINAL RESEARCH

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CHAPTER 1: Children’s psychosocial characteristics associated with their cycling for transport

Ghekiere A, Van Cauwenberg J, Carver A, Mertens L, de Geus B, Clarys P, Cardon G, De Bourdeaudhuij I, Deforche B. Psychosocial factors associated with children's cycling for transport: a cross-sectional moderation study Preventive Medicine, 2016: 86: 141-145

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Preventive Medicine 86 (2016) 141–146

Contents lists available at ScienceDirect

Preventive Medicine journal homepage: www.elsevier.com/locate/ypmed

Pyschosocial factors associated with children's cycling for transport: A cross-sectional moderation study Ariane Ghekiere a,b,c,⁎, Jelle Van Cauwenberg a,b,c, Alison Carver d, Lieze Mertens e, Bas de Geus f, Peter Clarys b, Greet Cardon e, Ilse De Bourdeaudhuij e, Benedicte Deforche a,b a

Department of Public Health, Faculty of Medicine and Health Sciences, Ghent University, De Pintelaan 185, 4K3, B-9000 Ghent, Belgium Department of Movement and Sport Sciences, Faculty of Physical Education and Physical Therapy, Vrije Universiteit Brussel, Pleinlaan 2, B-1050 Brussels, Belgium Fund for Scientific Research Flanders (FWO), Egmontstraat 5, B-1000 Brussels, Belgium d School of Exercise and Nutrition Science, Deakin University, Melbourne, Australia e Department of Movement and Sport Sciences, Faculty of Medicine and Health Sciences, Ghent University, Watersportlaan 2, B-9000 Ghent, Belgium f Human Physiology Research Group, Faculty of Physical Education and Physical Therapy, Vrije Universiteit Brussel, Pleinlaan 2, B-1050 Brussels, Belgium b c

a r t i c l e

i n f o

Article history: Received 12 October 2015 Received in revised form 22 January 2016 Accepted 6 March 2016 Available online 9 March 2016 Keywords: Transport Parents Active transport Self-efficacy Safety Social cognitive theory Active living

a b s t r a c t Promoting children's cycling for transport is a useful strategy to increase their physical activity levels. No studies have examined to which extent children's psychosocial characteristics play a role in their transportation cycling. Furthermore, insights into the association between children's independent mobility (IM) and transportation cycling is lacking in Europe. This study examined (1) the association of children's psychosocial characteristics with transportation cycling and its moderating effect of child's gender, parents' educational attainment and IM, and (2) the association between children's IM and transportation cycling. Children (n = 1232, aged 10–12 yrs) completed an online questionnaire at school assessing their psychosocial characteristics related with transportation cycling. Parents reported child's usual transportation cycling and the distance their child is allowed to cycle unsupervised (IM). Hurdle models were used to estimate associations between independent variables and odds of being a cyclist and with minutes of transportation cycling among those cycling. Data were collected during November–December 2014 across Flanders, Belgium. Children's perceived parental modeling, parental norm, peers' co-participation, self-efficacy and IM were positively related to the odds of being a cyclist, perceived benefits were negatively associated. Parental modeling, siblings' modeling, self-efficacy and parental norm were more strongly related to the odds of being a cyclist among children with a low IM. Friends' modeling was significantly related with odds of being a cyclist among boys. IM and parental norm (only among boys) were positively related to the time spent cycling. Targeting children, their friends and parents seems therefore most appropriate when aiming to increase children's transportation cycling. © 2016 Elsevier Inc. All rights reserved.

1. Introduction More than 60% of children worldwide fail to achieve the physical activity (PA) recommendations of 60 min/day moderate-to-vigorousintensity PA (Brug et al., 2012; Sjöström et al., 2006). Insufficient PA during childhood has adverse health consequences later in life, i.e. an increased risk of cardiovascular diseases, type II diabetes and overweight and obesity (Craigie et al., 2011). PA promotion is therefore considered Abbreviations: PA, physical activity; IM, independent mobility; SES, socio-economic status. ⁎ Corresponding author. E-mail addresses: [email protected] (A. Ghekiere), [email protected] (J. Van Cauwenberg), [email protected] (A. Carver), [email protected] (L. Mertens), [email protected] (B. de Geus), [email protected] (P. Clarys), [email protected] (G. Cardon), [email protected] (I. De Bourdeaudhuij), [email protected] (B. Deforche).

http://dx.doi.org/10.1016/j.ypmed.2016.03.001 0091-7435/© 2016 Elsevier Inc. All rights reserved.

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as essential among children, because their PA levels tend to decline during adolescence and adulthood (Craigie et al., 2011). Transportation cycling is one form of PA that can easily be integrated into children's daily routine (Pabayo et al., 2012). Children can cycle to destinations such as school, sport clubs or shops that are located within a reasonable distance (less than 3 km) from their residence (D'Haese et al., 2011; Dessing et al., 2014). Children's transportation cycling has been associated with higher PA levels (Cooper et al., 2003; Southward et al., 2012), better cardiovascular health (Andersen et al., 2011; Ostergaard et al., 2012a), better physical fitness (Andersen et al., 2009; Chillón et al., 2012), lower Body Mass Index (Bere et al., 2011; Ostergaard et al., 2012b), a healthier body composition (Lubans et al., 2011) and higher PA levels in later life (Yang et al., 2014). Despite these benefits, 40% of Flemish 10- to 12-year-old children residing within 3 km from school uses motorized travel to commute to school (Ducheyne et al., 2012b). In order to develop effective interventions aiming to increase children's transportation cycling, correlates of this behavior must be

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Researchers visited each school twice. During the first visit, children from the 5th and 6th grade (primary school, 10–12 yrs old) received a letter including information about the study, a link to the study website and a personalized login which enabled parents to participate in the study by completing an online questionnaire at home. Parents had to give active written consent for their child to participate at school. One week later, researchers returned to the schools to collect the informed consent forms and the children completed an online questionnaire at school. School visits were conducted in November and December 2014, while the parental questionnaire was closed at the end of January 2015. The Ethics Committee of the Ghent University Hospital approved the study protocol.

understood (Baranowski et al., 1998). The Social Cognitive Theory suggests that individual factors as well as environments influence behavior (Bandura, 1998). The reciprocal determinism of the Social Cognitive Theory highlights that all relationships between individuals, environments and behavior are bi-directional (Bandura, 1998). In this study, associations between children's psychosocial characteristics and their cycling for transport were examined. Psychosocial characteristics of interest were psychological factors (such as self-efficacy, perceived barriers and benefits) and perceived characteristics (encouragement, norms, modeling and co-participation) from the social environment (parents, siblings and friends). Previous studies indicate that parents play a key role in deciding whether the child cycles for transport. For example, parents determine the distance children are allowed to roam without adult supervision (i.e. territorial range, as a proxy for independent mobility (IM) (Carver et al., 2014b)). Studies from Australia and Canada previously demonstrated a positive association between children's IM and active transport (Mitra, 2013; Schoeppe et al., 2013). However, insight is lacking on how IM is related to cycling for transport within a more European context. When children age, they become more involved in transport-related decisions (Panter et al., 2008). Currently, it is unclear to what extent the child's preferences and psychosocial variables contribute to those decisions. Only few studies have investigated the association between children's psychosocial factors and active transport. In all these studies, parents reported child's psychosocial characteristics. For example, a Flemish study examined whether children's psychosocial factors were related to cycling to school and showed that children being more encouraged by their parents and their friends (parent-reported) were more likely to cycle to school (Ducheyne et al., 2012b). Similarly, Salmon and colleagues concluded that Australian children's preference (parent-reported) for being driven to school was negatively associated with walking to school (Salmon et al., 2007). The only study that used children's reports of their attitudes and preference showed that children perceiving higher levels of peer and parent support were more likely to walk or cycle to school in the UK (Panter et al., 2010). This indicates that more insight is needed into whether children's psychosocial characteristics are associated with their transportation cycling. Additionally, it might be that some children, very motivated to cycle for transport, do not do so due to low IM (Hillman et al., 1990; Mitra, 2013). This interaction between children's characteristics and parentdefined IM needs further investigation. Furthermore, gender and educational attainment are proposed as other potential moderators, because girls, overall, and children from lower SES (those with the lowest PA levels) may need a specific approach in order to increase their cycling for transport (Brodersen et al., 2007). Insight on how to target these specific subgroups will add to the current knowledge. The current study examined how parent-defined IM and childreported psychosocial factors relate to their transportation cycling, to explore whether future interventions aiming to increase children's cycling need to focus on improving children's psychosocial characteristics towards cycling. Secondly, we examined the moderating effect of IM, gender and educational attainment on the relation between childreported psychosocial factors and their transportation cycling to obtain more insight on how to develop targeted interventions.

2.2. Study protocol and measures 2.2.1. Children's questionnaire Children self-reported their gender, age and the school they attended. Additionally, they completed 31 questionnaire items assessing psychosocial factors specific for transportation cycling. These items were based on validated questionnaires of psychosocial correlates of PA among youth (Reynolds et al., 1990; Saunders et al., 1997; Verplanken and Orbell, 2003) and complemented with cycling-specific items based on previously used cycling-specific questionnaires (de Geus et al., 2008; Ducheyne et al., 2012a). The 31 items represented eight psychosocial constructs: perceived benefits, perceived barriers, self-efficacy, encouragement, co-participation in cycling, social norms and modeling. Average scores for psychosocial constructs were computed. As the internal consistency of the items for the constructs co-participation in cycling (3 items; from parents, peers, siblings), social norms (2 items; from peers and parents) and modeling (3 items; from parents, peers, siblings) were moderate (Cronbach's α = 0.54, 0.63 and 0.59, respectively), the following 12 items were examined as independent variables: perceived benefits, perceived barriers, parental modeling, sibling's modeling, peers' modeling, parental norm, peers' norm, parental co-participation, siblings' co-participation, peers' co-participation, self-efficacy and encouragement). A test–retest with a one week interval was conducted prior to the start of the data collection among a separate sample of 39 children from one primary school not participating in the study (40% girls, 51% 5th grade students, 10.4 yrs old), and indicated moderate to very good reliability of the items and constructs (see additional file 1). 2.2.2. Parental questionnaire Parents reported highest education of father and mother of the child. Parents' educational attainment was defined as low if neither parents had a college or university degree, and high if at least one parent had a college or university degree (D'Haese et al., 2015; De Meester et al., 2014; Verloigne et al., 2012). Educational attainment was considered as a proxy of children's socio-economic status. Parents indicated their urbanization level (urban: living in the city center, border of city and the town center, rural: living outside the center of a town). Parents completed questions about their child's usual transportation cycling within their neighborhood based on the International Physical Activity Questionnaire (IPAQ; usual week (Craig et al., 2003)). Additionally, parents reported their own cycling behavior in the same way. Finally, as a measure of the child's independent mobility (IM), parents were asked how far their child was allowed to cycle alone to a destination (response options: not, 500 m, 1 km, 3 km, 5 km, 10 km and 15 km).

2. Materials and methods 2.1. Participants and procedure We recruited children via randomly selected primary schools across Flanders, Belgium. Researchers telephoned 109 primary schools across Flanders of which 45 agreed to participate in the study (participation rate = 41%). The participation rate was higher for schools located in rural (b300 inh/km2, 80% participation) compared to semi-urban (300–600 inh/km2, 41% participation) or urban areas (N 600 inh/km2, 21% participation) (Lenders et al., 2005).

2.3. Analyses For the current analyses, children were only included when their parents also completed the questionnaire. Differences between characteristics of the study sample and children whose parents did not complete the questionnaire were determined via independent sample

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t-tests for continuous variables and chi2-tests for categorical variables (drop-out analysis). The dependent variable (minutes cycling for transport per week) was positively skewed and contained a large number of zeros (26.3% of the children) implying that the assumption of normality was violated and that general linear regression analyses could not be performed. Therefore, hurdle models, adjusting for the clustering of participating children within schools, were performed using the lme4-package in R version 3.1.1 (http://cran.r-project.org/web/packages/lme4/index.html) (Bolker et al., 2009). First, hurdle models evaluate associations between the independent variables (i.e. psychosocial items) and the odds of participation in cycling for transport among children (using a logistic regression model: binomial variance and logit link function). Second, hurdle models analyze the association between the independent variables and the total time spent cycling for transport among those children who engaged in cycling for transport. Appropriate variance and link functions (i.e. gamma variance and log link function) were selected based on Akaike's Information Criterion (AIC). Hence, the hurdle models resulted in two regression coefficients for each independent variable: an odds ratio (OR), which reflects the association between the independent variable and the odds of any cycling for transport, and a gamma regression coefficient. The latter, i.e. the exponent of the estimated B, reflects the proportional change in minutes of cycling for transport in a usual week with a one-unit increase in the independent variable among children who cycled for transport. The models were fitted by Adaptive Gauss-Hermite Quadrature with 25 quadrature points as recommended (Bolker et al., 2009). First, a basic model including all main effects of the twelve independent variables, and three potential moderators (i.e. gender, educational attainment and IM) was estimated. Second, all interaction effects between the psychosocial items and the potential moderators were entered separately into the basic model (resulting in 36 separate models). Third, all interaction effects from the second step with p b 0.05 were added simultaneously to the basic model. To keep the table simple and readable, the results of the basic model were presented in Table 2, while significant interaction effects observed in the final model were described in text. Significant interaction terms were probed according to established procedures (Aiken et al., 2003). Associations moderated by IM are described for a low (mean minus one standard deviation), an average (mean) and high (mean plus one standard deviation) IM. All analyses were adjusted for the child's age and residential area, level of significance was set at α = 0.05. 3. Results In total, 2101 (response rate = 85.4%) children and 1284 (52.2%) parents completed the online questionnaire, resulting in 1232 child– parent pairs. Table 1 shows descriptive characteristics of the children. Boys had higher IM (p b 0.001) and cycling for transport levels (p = 0.021) compared to girls. Children with participating parents were, on average, younger than those excluded from analyses (10.52 vs 10.62 yrs; p b 0.001). We found no differences for the child's gender, IM, educational attainment or psychosocial variables. In the logistic model (see Table 2, left column), IM, parental modeling, parental norm, peers' co-participation and self-efficacy were associated with higher odds of being a cyclist, while perceived benefits were associated with lower odds of being a cyclist. Gender and educational attainment were not related to the odds of being a cyclist. One kilometer increase in IM was associated with 46% higher odds of being a cyclist. A one-unit increase in children's perceived modeling from parents was associated with a 23% higher odds of being a cyclist, while a one-unit increase in parental norm and peer's co-participation was associated with 65% and 50% higher odds of being a cyclist, respectively. A one unit increase in the child's self-efficacy was associated with 47% higher odds of being a cyclist, while a one unit increase in perceived benefits was associated with 32% lower odds of being a cyclist. The association of modeling by peers and the odds of being a cyclist was significantly

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Table 1 Descriptive characteristics of the sample of children in Flanders, Belgium (n = 1232; data collected between October and December 2014).

Individual factors Age (M ± SD, years) Educational attainment (% low) Independent mobility (M ± SD, km)

Total sample

Boys (n = 611)

Girls (n = 621)

10.5 ± 0.6 28.9 2.6 ± 2.7

10.5 ± 0.6 29.4 3.0 ± 3.0

10.6 ± 0.6 28.5 2.3 ± 2.3

Psychosocial characteristics (M ± SD, 5 point scale; 1 = totally disagree, 5 = totally agree) Perceived benefits 3.9 ± 0.6 4.0 ± 0.6 Perceived barriers 2.4 ± 0.7 2.3 ± 0.7 Parental modeling 2.7 ± 1.0 2.6 ± 1.0 Siblings' modeling 3.2 ± 1.4 3.2 ± 1.4 Peers' modeling 3.4 ± 1.0 3.5 ± 1.0 Parental norm 3.1 ± 1.2 3.2 ± 1.2 Peers' norm 2.4 ± 1.1 2.5 ± 1.2 Parental co-participation 2.8 ± 1.1 2.8 ± 1.1 Siblings' co-participation 2.6 ± 1.2 2.5 ± 1.2 Peers' co-participation 2.7 ± 1.2 2.8 ± 1.2 Encouragement 2.7 ± 1.0 2.7 ± 1.0 Self-efficacy 3.1 ± 0.9 3.2 ± 0.9

3.9 ± 0.5 2.5 ± 0.6 2.7 ± 1.0 3.3 ± 1.4 3.4 ± 1.0 3.0 ± 1.1 2.3 ± 1.1 2.9 ± 1.1 2.7 ± 1.2 2.7 ± 1.1 2.7 ± 1.0 3.0 ± 0.9

Cycling behavior (Median; Q1–Q3) Children's cycling for transport, mins/week Parents' cycling for transport, mins/week

30; 0–75 0;0–45

35; 0–81 0; 0–50

40; 3–90 0; 0–60

M = mean; SD = standard deviation; Q1 = first quartile; Q3 = third quartile. % low educational attainment = none of the parents has tertiary education.

Table 2 Main effects of the psychosocial variables related to cycling for transport, within a sample of Flemish (Belgian) 10–12 years old children (n = 1232).

Potential moderators Gender (ref. = girl) Educational attainment (ref. = low) Independent mobility Psychosocial characteristics Perceived benefits Perceived barriers Parental modeling Siblings' modeling Peers' modeling Self-efficacy Parental norm Peers' norm Parental co-participation Siblings' co-participation Peers' co-participation Encouragement

Logistic modela

Gamma modelb

OR of being cyclist

95% CI

expBc

95 CI%

0.95

0.68

1.31

1.05

0.92

1.22

0.86

1.73

0.90

0.78

1.05

1.46⁎⁎⁎

1.32

1.61

1.07⁎⁎⁎

1.03

1.09

0.68⁎ 0.89 1.23⁎

0.49 0.69 1.01 0.92 0.82 1.19 1.40 0.82 0.70 0.90 1.28 0.78

0.94 1.16 1.50 1.16 1.14 1.82 1.94 1.13 1.02 1.20 1.75 1.13

1.00 1.00 1.07 1.05 1.01 1.06 1.08⁎⁎ 0.99 0.92 0.99 1.06 1.01

0.89 0.90 0.98 0.99 0.93 0.97 1.02 0.93 0.84 0.93 0.99 0.93

1.14 1.11 1.16 1.11 1.08 1.15 1.15 1.06 1.00 1.05 1.13 1.09

1.03 0.96 1.47⁎⁎⁎ 1.65⁎⁎⁎ 0.96 0.85 1.04 1.50⁎⁎⁎ 0.94

1.20

[Changes in AIC values in logistic model: null model = 1362.9, main effect model = 1092.0, interaction model = 1079.0; gamma model: null model = 630.2, main effect model = 582.2, interaction model = 576.9]. OR = odds ratio; C.I. = confidence interval; italics = variable which is significantly moderated. Variables in italics are those variables which are moderated by one or more moderators. a The logistic model estimates the association between the independent variables and the odds of being a cyclist. b The gamma model estimates the association between the independent variables and the amount of minutes of cycling among the cyclists. c expB = exponent of B, all gamma models were fitted using a log link function. The exponent of B can be interpreted as the proportional increase of the dependent variable with a one-unit increase in the independent variable. ⁎ p b 0.05. ⁎⁎ p b 0.01. ⁎⁎⁎ p b 0.001.

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moderated by the child's gender. Modeling by friends was significantly related to the odds of being a cyclist only among boys (OR = 0.58; 95% CI = 0.36–0.95), but not among girls (OR = 1.60; 95% CI = 0.95–2.62). IM moderated the relation with perceived benefits, parental modeling, siblings' modeling, self-efficacy and parental norm. Perceived benefits were not associated with the odds of being a cyclist among children with low (OR = 1.37; 95% CI = 0.77–2.48) or average IM (0.80; 95% CI = 0.57–1.11), but it was negatively related among children with high IM (OR = 0.46; 95% CI = 0.30–0.70). Parental and siblings' modeling were positively related with the odds of being a cyclist, among children with low (OR = 1.79; 95% CI = 1.18–2.72 and OR = 1.51; 95% CI = 1.14–2.00) and average (OR = 1.38; 95% CI = 1.10–1.73 and OR = 1.15; 95% CI = 1.00–1.32) IM but not among children with high IM (OR = 1.06; 95% CI = 0.83–1.35 and OR = 0.87; 95% CI = 0.74– 1.03). Self-efficacy was positively related with the odds of being a cyclist among children with low (OR = 2.60; 95% CI = 1.66–4.06) and average IM (OR = 1.72; 95% CI = 1.35–2.19), but not among children with high IM (OR = 1.14; 95% CI = 0.86–1.49). Finally, parental norm was more strongly related among children with low (OR = 2.32; 95% CI = 1.67– 3.22) compared to average (OR = 1.79; 95% CI = 1.50–1.41) or IM (OR = 1.38; 95% CI = 1.11–1.71). According to the gamma model (see Table 2, right column), IM and parental norm were positively associated with minutes cycling per week among the cyclists. An increase in IM of one kilometer was associated with 7% more minutes of cycling per week. The association between parental norm and the volume of transportation cycling was significantly moderated by gender, i.e. parental norm was only positively associated with the volume of transportation cycling among boys (ExpB = 1.37; 95% CI = 1.14–1.64) but not among girls (ExpB = 0.88; 95% CI = 0.75–1.04).

to cycle), increasing the child's self-efficacy may be a potential strategy to increase children's cycling for transport. The negative association between perceived benefits and the chance of being a cyclist was not in the hypothesized direction, as studies among adolescents and adults reported a positive association between perceived benefits and their cycling for transport (de Geus et al., 2008). However, IM moderated the association between perceived benefits and the odds of being a cyclist, and indicated a negative association with transportation cycling only among children with a high IM. These children with a high IM may be forced to cycle for transport although they are not intrinsically motivated to cycle for transport. Children with a lower IM may perceive benefits from cycling, but their parents restrict their child's transportation cycling as parents may perceive their child incapable to cycle for transport due to unsafe environments or other reasons (Janssen, 2014). IM also moderated the association between other psychosocial factors (i.e. parental modeling, sibling's modeling and parental norm) and the odds of cycling. Children's psychosocial characteristics were most strongly associated with cycling among children with a low IM. These findings were unexpected, as it was hypothesized that children's psychosocial factors would not be associated among children with low IM. However, the results may indicate that although children have a low IM, psychosocial factors may prevent the children from not cycling for transport at all and demonstrate the complex interplay between parental and children's factors regarding transportation cycling. In summary, it could be hypothesized that interventions targeting increases in children's cycling for transport may need a multidimensional approach. Both parents, the child and their friends were identified as being important for children's cycling for transport. Most identified associations were parent-related, which may indicate that parents may be the most important group of individuals to focus on in future interventions. Additionally, children's self-efficacy was positively associated with the chance of cycling for transport. The idea of encouraging parents to cycle with their child therefore seems promising and concurs with the findings of a longitudinal study of children's active transport in England (Carver et al., 2014a). Interventions may aim to induce a shift from parents driving their children, to parents accompanying their children during cycling and, finally, to children cycling independently. This may increase cycling levels in general, and may establish a habit of cycling for transport among children. Additionally, cycling together may increase parental trust in children's cycling skills in traffic, which could lead to a higher IM and in turn, to more transportation cycling in children. Furthermore, it may increase the child's selfefficacy which was also related to the odds of being a cyclist. However, more research is needed regarding the complex interplay between children's psychosocial factors and the role of parents in determining children's transportation cycling.

4. Discussion The current study examined whether children's IM and children's psychosocial characteristics were associated with their transportation cycling and whether the associations between psychosocial characteristics and cycling were moderated by children's gender, educational attainment and IM. Results indicate that whether a child uses the bicycle to travel around, is largely influenced by the child's social environment, including parents and friends. Children are deeply embedded in their family contexts, and so behaviors such as cycling for transport, are largely influenced by how their parents think about cycling and to which extent they motivate their children to cycle for transport (Pont et al., 2009). For example, both children's perceived parental modeling and parental norms were positively related to the odds of being a cyclist. Additionally, IM seemed to play an important role in both predicting the odds of being a cyclist, and the time spent cycling for transport. Further research on determinants of children's IM is therefore warranted. Friends' co-participation was positively associated with the odds of being a cyclist. Social support was previously identified as an important correlate of adolescents' active transport (Hohepa et al., 2007; Simons et al., 2013). Our study results indicate the importance of peers next to parents for children's transportation cycling. Parents play an important role in child's cycling behavior by determining the child's IM, being a role model and contributing to a social norm of cycling. Additionally, future interventions could benefit from encouraging children to cycle together with friends (Panter et al., 2010). In addition to the association with social environmental factors, there is some evidence that children's individual characteristics may play a role in the decision to cycle for transport. Children who are confident in their ability to cycle in difficult situations (e.g. when raining, when tired), i.e. those with higher self-efficacy, were more likely to cycle compared to children with lower self-efficacy. Interventions aiming to increase the child's self-efficacy, may promote cycling for transport. Especially among children with lower IM (who are less likely

4.1. Strengths and limitations To our knowledge, this was the first study to examine children's perceived cycling-specific psychosocial correlates of cycling for transport. To our knowledge, this was the first study to examine children's cycling-specific psychosocial correlates of cycling for transport. As no questionnaire was available for children to report their psychosocial characteristics towards cycling, a new questionnaire was developed based on other validated questionnaires and this questionnaire showed good reliability. Future research could further optimize the questionnaire and test its validity. However, our study provided first insights into children's psychosocial correlates of cycling for transport among a large sample of Flemish children. However, our study provided first insights into children's psychosocial correlates of cycling for transport among a large sample of Flemish children. We call for more research in other European countries and across different continents to confirm our study findings. Flanders is characterized with a relatively well developed cycling infrastructure with relatively high cycling rates (13% of the general population uses

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cycling as their main transport mode (EuropeanCommission, 2014)) and therefore the study results may not be generalizable to other countries or regions varying in cycling-friendliness. Participating schools were somewhat more likely to be located in rural areas (n = 20), compared to semi-urban (n = 15) or urban areas (n = 10). As children's cycling behavior (outcome variable) was obtained via subjective parental report, time spent cycling per week may have been overestimated. Objective measurements of children's actual time spent cycling for transport may increase the quality of the outcome measure. Additionally, children were asked to report perceptions of their parents' norms, encouragement, co-participation and modeling, rather than investigating these characteristics for mothers/fathers separately. It might be that, for example, modeling of the father may be a stronger predictor of children's cycling for transport compared to modeling of the mother. The role of parents should therefore be explored in more detail (with specific questions for fathers/mothers) in future studies. Furthermore, as parental educational attainment was used as a proxy of family SES, our findings regarding SES should be interpreted with some caution. The Social Cognitive Theory posits that associations between individual, environment and behavior are bi-directional, but due to the crosssectional design of the study, no direction of the identified associations could be determined. Therefore, longitudinal or experimental studies are required to assess causality. Finally, this study focused on the social environmental and individual factors in relation to transportation cycling, but the interaction with physical environmental factors should be determined in future studies. 5. Conclusion Parents are the gatekeepers of children's cycling for transport and should therefore be the first to target in future interventions aiming to increase children's transportation cycling. They could be stimulated to encourage their child to cycle for transport, act as a role model and set a subjective norm. Encouraging children to cycle with their friends may be another strategy to increase transportation cycling. Additionally, there is some evidence that children's own characteristics are related to cycling for transport, as self-efficacy was related to the odds of being a cyclist. Finally, we found that some associations were moderated by child's gender and level of IM, but not by educational attainment. Competing interests The authors declare to have no competing interest. Authors' contributions AG, LM, JVC, IDB and BD drafted the concept of the study. AG and LM performed data collection. AG together with JVC conducted the analysis. All authors critically reviewed and approved the final version of the manuscript. Acknowledgments The authors want to thank all master students for their assistance with data collection. The authors want to thank all school principals who agreed to be involved in the study. We also want to thank all the participating children and their parents for their interest in the study. AG is funded by a grant from Scientific Research Foundation Flanders (FWO, GA11111N). JVC is funded by a PhD fellowship from Scientific Research Foundation Flanders (FWO, 11N0313N) Appendix A. Supplementary data Supplementary data to this article can be found online at http://dx. doi.org/10.1016/j.ypmed.2016.03.001.

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Additional file 1 Reliability and internal consistency within a sample of 39 children aged 10-12 years.

When cycling, I can be together with others

Cronbach’s α=0.78 ICC = 0.77 5 point Likert-scale

When cycling, I can be in the fresh air

1: totally disagree

When I go cycling, I can decide myself when I leave

2: somewhat disagree

Cycling is good to keep a healthy weight

3: somewhat agree, somewhat disagree

I think cycling is fun

4: somewhat agree

I think cycling is cool

5: totally agree

Perceived benefits

Cycling is good for your health

I think cycling is exhausting

Cronbach’s α=0.73 ICC= 0.73 5 point Likert-scale

I think cycling is boring

1: totally disagree

A barrier of cycling is that I can fall during cycling


A barrier of cycling is that I sweat during cycling


A barrier of cycling is that I get wet when it rains

4: somewhat agree

A barrier of cycling is that you have to cycle on your own

5: totally agree Cronbach’s α= 0.86 ICC=0.76

Perceived barriers

Self-efficacy

I am sure I am able to go by bike, even when the weather is 5 point Likert-scale bad I am sure I am able to go by bike, even if all others (friends, 1: totally disagree parents, brother/sister) would go by car I am sure I am able to go by bike, even if I have to carry 2: somewhat disagree much material with me I am sure I am able to go by bike, even if I am tired


I am sure I am able to go by, even if the road is uphill

4: somewhat agree

I am sure I am able to go by bike, even if I have to wake up 5: totally agree earlier Encouragement

Cronbach’s α= 0.81 ICC=0.78

My parents encourage me to cycle to a destination

5 point Likert-scale

My siblings encourage me to cycle to a destination

1: totally disagree

My friends encourage me to cycle to a destination


Other family members encourage me to cycle to a destination 3: somewhat agree, somewhat disagree 4: somewhat agree 5: totally agree

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Co-participation 5 response categories:

By parents (ICC= 0.76)

How often do your parents go cycling with you to a 1: never destination? 2: rarely

By brothers/sisters (ICC=0.62)

How often do your siblings go cycling with you to a 3: now and then destination? 4: often

By peers (ICC=0.78)

How often do your friends go cycling with you to a 5: always destination? Modeling From parents (ICC=0.86) How often do your parents cycle to a destination? From brothers/sisters (ICC=0.91) How often does your brother/sister cycle to a destination? From peers (ICC=0.66) How often do your friends cycle to a destination? Social norms From parents (ICC=0.56) My parents think I should cycle regularly to a destination From peers (ICC=0.55) My friends think I should cycle regularly to a destination

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5 response categories: 1: never 2: rarely 3: now and then 4: often 5: always 5 point Likert-scale 1: totally disagree 2: somewhat disagree 3: somewhat agree, somewhat disagree 4: somewhat agree 5: totally agree

CHAPTER 2.1: Socio-ecological factors associated with children’s independent mobility for transportation cycling

Ghekiere A, Deforche B , Carver A, Mertens L, de Geus B, Clarys P, Cardon G, De Bourdeaudhuij I, Van Cauwenberg J. Insights into children's independent mobility for transportationcycling: which socio-ecological factors matter? Journal of Science and Medicine in Sport. Under re-review

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Abstract Objectives: To assess the associations of socio-ecological factors with independent mobility (IM) for transportation cycling among 10-to-12-year-old boys and girls. Additionally, we examined whether associations differed across family socio-economic status (SES) and urbanization level. Design: Cross-sectional survey Methods: Parents (n=1286) were recruited via 45 primary schools across Flanders, Belgium. They completed an online questionnaire assessing demographic and psychosocial factors, neighborhood environmental perceptions, as well as some characteristics of their child. IM was assessed as the distance children were allowed to cycle for transport without adult supervision. Multilevel linear regression analyses stratified by gender were performed to examine the associations between the independent variables and children’s IM and the moderating effects of family SES and urbanization level. Results: IM was higher among boys compared to girls. Perception of children’s cycling and traffic skills and children’s grade were positively associated with IM among boys and girls. Perceived presence of cycling infrastructure was positively associated with IM among boys, but not among girls. Perceived traffic safety was positively associated with IM only among boys living in high urbanized areas. In contrast, perceived traffic safety was positively associated with IM among girls living in low urbanized areas. Perceived presence of public transit stops and maintenance of cycling facilities were positively associated with IM among low SES girls. Conclusions: Our findings suggest that interventions targeting increases in children’s cycling and traffic skills may be effective to increase their IM. The study highlights that different factors are associated with children’s IM according to gender, family SES and urbanization level. Keywords: active transport ; built environment ; socio-ecological model ; physical activity ; cycling for transport ; perceptions

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Introduction The promotion of 60 minutes moderate- to vigorous-intensity physical activity per day is one of the key factors in fighting the childhood obesity epidemic1. In Europe, the majority of children is insufficiently physically active, which has been associated with adverse health outcomes not only in childhood, but also in later life2. Active transport (i.e. walking or cycling for transport) is an accessible and inexpensive type of physical activity, which can be easily integrated within children’s daily routines. Children’s independent mobility (IM), which refers to children’s freedom to move around in their neighbourhoods without adult supervision3, is considered as one of the most important determinants of active transport4-6. In a previous study in Flanders, IM was strongly associated with the odds of being a cyclist, as well as the volume of cycling for transport6. Next to the physical activity-related benefits of IM, independently mobile children have a better well-being, educational attainment and experience a better physical, social and emotional development 7-9. In this paper, we focus on IM for children’s transportation cycling. By cycling, children can cover larger distances more quickly compared to walking for transport. Children’s transportation cycling has also been associated with better health outcomes, including increased cardiovascular fitness and better body composition compared to walking10, 11. Furthermore, whilst Flemish children prefer to travel by bicycle over other transport modes13,, 36% of the 10-to-12 year-old children are still driven by car or use public transport as their main transport mode to travel to destinations within 3 km from their residence12, 13. This is the first study that examined correlates of IM specific for transportation cycling to various destinations, as previous research focused on IM for school transport14 or park-based play15. Despite the benefits of granting children freedom to roam within their neighborhood, IM has dramatically decreased during the last decades16. It is therefore important to study what determines children’s IM, in order to prevent further declines in IM levels, or potentially increase IM levels. As mainly parents determine the distance children are allowed to travel independently, it is essential to study parent-perceived correlates. By using a socio-ecological approach, both individual (i.e. children’s

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demographics, and parents’ demographics and psychological factors) and environmental factors (i.e. social and physical environmental factors) are covered17. Individual factors previously associated with children’s IM are age and gender 7, 18. Children’s IM levels increase when children grow older, and boys have more IM compared to girls. Environmental factors previously cited to be related with IM are parental perceptions of traffic safety and stranger danger9. It is unclear which other environmental factors may play a role in determining children’s IM for transportation cycling. For example, it may be possible that children living in a more cycling-friendly neighborhood (e.g., presence of cycling infrastructure, low traffic density and traffic speed) are allowed to have higher IM levels compared to their peers in a neighborhood that is less supportive for cycling. There is also inconsistency on whether IM levels differ according to urbanization level in a European context19. Additionally, it is hypothesized that parents will be more likely to grant their children some independence when they have positive attitudes and perceptions towards active transport themselves14. However, to the author’s knowledge, there are currently no studies available that have examined these associations. As children’s IM differs significantly according to gender, Stone and colleagues recommended to investigate correlates of IM gender-specific20. Other factors that are hypothesized to moderate the associations between socio-ecological factors and children’s IM are family socio-economic status (SES) and urbanization level of the neighborhood. Regulation of children’s IM can be considered as a parenting practice, which has been shown to vary according to the educational level of the parents21. Different associations may be found according to urbanization level. For example, it is possible that in high urbanized areas, where there is a higher traffic density, cycling facilities may become more important for IM compared to low urbanized areas where traffic density is lower. Therefore, the aim of the present study was to examine how socio-ecological factors (including child and parents’ demographics, parents’ psychosocial factors and parents’ neighborhood perceptions) are associated with children’s IM for transportation cycling. Additionally, we examined whether these associations were moderated by family SES and urbanization level. As IM levels have been shown to differ according to gender 20, analyses were stratified by gender.

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Methods We recruited parents via children primary schools (5th and 6th grade, aged 10 to 12 years) across Flanders, Belgium. Schools were randomly selected to obtain schools located across the different regions in Flanders and these were supplemented by schools where one of the researchers knew a contact person (e.g. primary school of the researcher). We telephoned 109 primary schools across Flanders, of which 45 agreed to participate (participation rate=41%). During a school visit by researchers, children received a letter to invite their parents to participate in the study, by completing an online questionnaire at home. The letter included a link to the online questionnaire and a personalized login code. School visits were conducted during November and December 2014 and parents were able to complete the online questionnaire until the end of January 2015. Informed consent was automatically obtained from the parents when they voluntarily completed the questionnaire. The Ethic Committee of Ghent University Hospital approved the study protocol.

Parents reported their child’s gender and school grade (5th or 6th grade). They also reported their own gender and age, as well as the highest educational level obtained by the father and the mother of the child. Family-level SES was defined as high if at least one of the parents had a college or university degree22. Parents indicated their usual transportation cycling based on the International Physical Activity Questionnaire (IPAQ, usual week23). Additionally, parents reported the degree of urbanization of their area of residence categorized as low if they lived outside the centre of a town, and high if they lived in the city centre, at the border of the city centre or in the town centre. Parents indicated whether their child is able to cycle on his/her own, based on his/her cycling skills (Are your child’s cycling skills good enough to cycle on his/her own; yes/no), and based on their traffic skills (Are your child’s traffic skills good enough to cycle on his/her own; yes/no). Parents reported their psychosocial characteristics regarding their transportation cycling, using a questionnaire previously used among adults 24, 25. Each construct (perceived benefits, perceived barriers, social norms, social support and self-efficacy) was created by calculating the mean across the different

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single items (see additional file 1). Three unique items were entered in the analyses for modeling, representing the different sources of modeling (friends, partner and colleagues/employer). Finally, parents indicated their perceived neighborhood characteristics, based on the Physical Activity Neighborhood Environment Survey (PANES)26. Eleven questions assessed the perceived neighborhood environment of the participants, based on a 5-point scale (0=totally disagree; 5=totally agree). Perceived land use mix was calculated by averaging responses of ‘presence of many shops’ and ‘many places within walking distance’. All other items (presence of public transit stop, recreation facilities, aesthetic qualities, traffic safety, crime safety, pedestrian safety, presence cycling infrastructure, maintenance of cycling infrastructure, vegetation) were entered as individual predictors in the analyses. Traffic and crime safety were reversely coded when entered in the analyses. Children’s IM, the outcome variable, was defined as the distance their child is allowed to cycle without adult supervision (response options: not, 0.5 km, 1 km, 3 km, 5 km, 10 km, 15 km) 3. All analyses were performed in SPSS version 21. Multilevel linear regression analyses (level 1= parents, level 2= schools) were used to examine how parental and children’s demographics and parental psychosocial characteristics and perceived neighborhood characteristics are associated with children’s IM. Separate analyses were performed for boys and girls. A first basic model was estimated including all main effects of the independent variables and the two potential moderators (family SES and urbanization level). Secondly, one interaction between an independent variable and moderator was added to the basic model, which resulted in 48 separate models. Results from the basic model were presented in table format. To keep the table simple and readable, significant interactions were described in text. Level of significance was set at p

Insights into children's cycling for transport: a socio ...

Insights into children's cycling for transport: a socio ...

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