Teun Remmers

184 | Chapter 10 are closely related to the essential question of whether children either compensate their PA levels to maintain an innate total PA set point (i.e. activitystat hypothesis) (62), or that children do not compensate so that increases in one context are related to increases in another context (active synergy hypothesis) (63). Namely, increases of PA in small time- segments may be more likely to be compensated with increases in sedentary time during subsequent hours. Chapter 9 describes the development of PA patterns (segmented by time and location) throughout the whole day and across the transition from primary to secondary school, and some indications for potential compensation were found. To date, the available evidence regarding compensation of PA is however mixed (64). This greatly depends on the variable measured (activity energy expenditure versus PA) and the time- frame on which compensation is measured (day by day or across several months) (64). Potentially important innovations in investigating compensation-mechanisms in children may relate to the ability to measure posture with accelerometers (i.e. sitting, standing, lying) (44), and the integration of these accelerometers with 24-hour wear time protocols. In these designs, compositional data analyses may account for potential co-dependencies between sedentary behaviors, sleep and PA (65, 66). Measurement of Environmental Exposure Measuring exposure to environmental determinants of PA can be done by questionnaires (i.e. perceived environment) or by observation (i.e. objective environment). In this thesis, both types were used. Chapters 4 and 5 focused on the perceived environment. Previous studies that compared perceived with objective environmental determinants suggest that the two are interrelated, but different concepts (67-69). Namely, a person's exposure to the environment is influenced by personal factors and selective daily mobility (3, 70). In addition, children's definition of a 'neighborhood' or 'activity space' may be highly individual (34, 71, 72). Therefore, perceived environmental measures are still indispensable for understanding environment-behavior relationships. The study in chapter 7 conceptualized objective environmental determinants of afterschool PA by systematic environmental audits of playgrounds in the school environment. These audits were conducted using the SPACE checklist (73), based on the Neighborhood Environment Walkability Survey (74). This study applied GIS Euclidean and network buffer analyses to examine whether the distance from school to home would influence our relationship of interest. Whereas Euclidean buffers simply identify the environment within a circular distance, the network buffer accounts for barriers, such as rivers and highways. The study presented in chapter 7 showed no difference between network- and Euclidean buffers. In addition, as to date there is no consensus on what buffer size would be appropriate in Dutch primary school children, the study in chapter 7 investigated associations with various buffers sizes ranging from 400- to 1600 meters (69). As the SPACE checklist also included quality-indices (e.g. accessibility, availability of playing devices of playgrounds), this study was able to go beyond the opportunities of most objective measurements such as GIS. Future studies combining qualitative data (e.g. audits, interviews, or perceived environment questionnaires from both parents and children) may further enhance our understanding of which environmental attributes are PA-supportive in youth (75, 76).