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Background: Recently, research focus has shifted to the combination of all 24-h movement behaviors (physical activity, sedentary behavior and sleep) instead of each behavior separately. Yet, no reliable and valid proxy-report tools exist to assess all these behaviors in 0-4-year-old children. By involving end-users (parents) and key stakeholders (researchers, professionals working with young children), this mixed-methods study aimed to 1) develop a mobile application (app)-based proxy-report tool to assess 24-h movement behaviors in 0-4-year-olds, and 2) examine its content validity., Methods: First, we used concept mapping to identify activities 0-4-year-olds engage in. Parents (n = 58) and professionals working with young children (n = 21) generated a list of activities, sorted related activities, and rated the frequency children perform these activities. Second, using multidimensional scaling and cluster analysis, we created activity categories based on the sorted activities of the participants. Third, we developed the My Little Moves app in collaboration with a software developer. Finally, we examined the content validity of the app with parents (n = 14) and researchers (n = 6) using focus groups and individual interviews., Results: The app has a time-use format in which parents proxy-report the activities of their child, using eight activity categories: personal care, eating/drinking, active transport, passive transport, playing, screen use, sitting/lying calmly, and sleeping. Categories are clarified by providing examples of children's activities. Additionally, 1-4 follow-up questions collect information on intensity (e.g., active or calm), posture, and/or context (e.g., location) of the activity. Parents and researchers considered filling in the app as feasible, taking 10-30 min per day. The activity categories were considered comprehensive, but alternative examples for several activity categories were suggested to increase the comprehensibility and relevance. Some follow-up questions were considered less relevant. These suggestions were adopted in the second version of the My Little Moves app., Conclusions: Involving end-users and key stakeholders in the development of the My Little Moves app resulted in a tailored tool to assess 24-h movement behaviors in 0-4-year-olds with adequate content validity. Future studies are needed to evaluate other measurement properties of the app., (© 2023. The Author(s).)

Background: Accurate accelerometer-based methods are required for assessment of 24-h physical behavior in young children. We aimed to summarize evidence on measurement properties of accelerometer-based methods for assessing 24-h physical behavior in young children., Methods: We searched PubMed (MEDLINE) up to June 2021 for studies evaluating reliability or validity of accelerometer-based methods for assessing physical activity (PA), sedentary behavior (SB), or sleep in 0-5-year-olds. Studies using a subjective comparison measure or an accelerometer-based device that did not directly output time series data were excluded. We developed a Checklist for Assessing the Methodological Quality of studies using Accelerometer-based Methods (CAMQAM) inspired by COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN)., Results: Sixty-two studies were included, examining conventional cut-point-based methods or multi-parameter methods. For infants (0-12 months), several multi-parameter methods proved valid for classifying SB and PA. From three months of age, methods were valid for identifying sleep. In toddlers (1-3 years), cut-points appeared valid for distinguishing SB and light PA (LPA) from moderate-to-vigorous PA (MVPA). One multi-parameter method distinguished toddler specific SB. For sleep, no studies were found in toddlers. In preschoolers (3-5 years), valid hip and wrist cut-points for assessing SB, LPA, MVPA, and wrist cut-points for sleep were identified. Several multi-parameter methods proved valid for identifying SB, LPA, and MVPA, and sleep. Despite promising results of multi-parameter methods, few models were open-source. While most studies used a single device or axis to measure physical behavior, more promising results were found when combining data derived from different sensor placements or multiple axes., Conclusions: Up to age three, valid cut-points to assess 24-h physical behavior were lacking, while multi-parameter methods proved valid for distinguishing some waking behaviors. For preschoolers, valid cut-points and algorithms were identified for all physical behaviors. Overall, we recommend more high-quality studies evaluating 24-h accelerometer data from multiple sensor placements and axes for physical behavior assessment. Standardized protocols focusing on including well-defined physical behaviors in different settings representative for children's developmental stage are required. Using our CAMQAM checklist may further improve methodological study quality., Prospero Registration Number: CRD42020184751., (© 2022. The Author(s).)

Background: Accurate proxy-report questionnaires, adapted to the child's developmental stage, are required to monitor 24-h movement behaviors in young children, especially for large samples and low-resource settings., Objectives: This review aimed to summarize available studies evaluating measurement properties of proxy-report questionnaires assessing physical activity, sedentary behavior and/or sleep in children aged 0-5 years., Methods: Systematic literature searches were carried out in the PubMed, Embase and SPORTDiscus databases, up to January 2021. For physical activity and sedentary behavior questionnaires this is a review update, whereas for sleep questionnaires we included all relevant studies published up to now. Studies had to evaluate at least one of the measurement properties of a proxy-report questionnaire assessing at least duration and/or frequency of physical activity, sedentary behavior and/or sleep in 0- to 5-year-old children. The COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) guideline was used to evaluate the quality of evidence., Results: Thirty-three studies were included, examining a total of 37 questionnaires. Ten questionnaires were designed for infants, two for toddlers, 11 for preschoolers, and 14 for a broader age range targeting multiple of these age groups. Twenty questionnaires assessed constructs of sleep, four assessed constructs of physical activity, two assessed screen behavior, five assessed constructs of both physical activity and sedentary behavior, and six assessed constructs of all 24-h movement behaviors. Content validity was evaluated for six questionnaires, structural validity for two, internal consistency for three, test-retest reliability for 16, measurement error for one, criterion validity for one, and construct validity for 26 questionnaires. None of the questionnaires were considered sufficiently valid and/or reliable for assessing one or more movement behaviors in 0- to 5-year-old children, and the quality of evidence was mostly low or very low., Conclusions: Valid and/or reliable questionnaires assessing 24-h movement behaviors in 0- to 5-year-olds are lacking. High-quality studies are therefore required, to develop proxy-report questionnaires and evaluate their measurement properties., Prospero Registration Number: CRD42020169268., (© 2022. The Author(s).)

Background: Early childhood is a critical period for growth and development, yet the association with physical activity during this important period is unknown. The aim of this review is to critically summarize the evidence on the prospective associations between physical activity and health and development in children aged < 5 years., Methods: A systematic search in three electronic databases (Pubmed, PsycINFO, and Sportdiscus) was conducted to identify prospective studies examining the associations between physical activity (all types; specified by quantity) and health indicators (body composition, cardiometabolic health, bone health and risks/harm) or development (motor, cognitive and social-emotional development) in young children (mean age < 5 years at baseline). Two independent researchers assessed the methodological quality using the 'Quality Assessment Tool for Quantitative Studies' (EPHPP). This tool covers eight quality criteria: selection bias, study design, confounders, blinding, data collection methods, withdrawals and drop-outs, intervention integrity and data-analysis., Results: Thirty-nine studies, predominantly conducted in preschoolers (ages 3-5 years), were included of which nine were rated as high methodological quality. There was moderate evidence for a positive association between physical activity and motor (n = 11 studies) and cognitive development (n = 10 studies) based on consistent findings from studies having low-to-moderate methodological quality. There was insufficient evidence for an association between physical activity and body composition (n = 15 studies), cardiometabolic health indicators (n = 7 studies), social-emotional development (n = 2 studies) and bone health (n = 2 studies) based on inconsistent findings from studies having weak-to-high methodological quality., Conclusions: There is a need for more high-quality research in order to determine the dose-response relationship between physical activity and health and development in early childhood. Special attention should be paid to studies in children below the age of 3 years.

Background: Promoting cycling to school may benefit establishing a lifelong physical activity routine. This systematic review aimed to summarize the evidence on strategies and effects of school-based interventions focusing on increasing active school transport by bicycle., Methods: A literature search based on "PICo" was conducted in eight electronic databases. Randomized and non-randomized controlled trials with primary/secondary school students of all ages were included that conducted pre-post measurements of a school-based intervention aimed at promoting active school travel by bicycle and were published in English between 2000 and 2019. The methodological quality was assessed using the "Effective Public Health Practice Project" tool for quantitative studies. Applied behavior change techniques were identified using the "BCT Taxonomy v1". Two independent researchers undertook the screening, data extraction, appraisal of study quality, and behavior change techniques., Results: Nine studies investigating seven unique interventions performed between 2012 and 2018 were included. All studies were rated as weak quality. The narrative synthesis identified 19 applied behavior change techniques clustered in eleven main groups according to their similarities and a variety of 35 different outcome variables classified into seven main groups. Most outcomes were related to active school travel and psychosocial factors, followed by physical fitness, physical activity levels, weight status, active travel and cycling skills. Four studies, examining in total nine different outcomes, found a significant effect in favor of the intervention group on bicycle trips to school (boys only), percentage of daily cycling trips to school, parental/child self-efficacy, parental outcome expectations, moderate-to-vigorous intensity physical activity (total, from cycling, before/after school), and total basic cycling skills. Seven of these outcomes were only examined in two studies conducting the same intervention in children, a voluntary bicycle train to/from school accompanied by adults, including the following clustered main groups of behavior change techniques: shaping knowledge, comparison of behavior, repetition and substitution as well as antecedents., Conclusions: The applied strategies in a bicycle train intervention among children indicated great potential to increase cycling to school. Our findings provide relevant insights for the design and implementation of future school-based interventions targeting active school transport by bicycle., Trial Registration: This systematic review has been registered in the international prospective register of systematic reviews "PROSPERO" at (registration number: CRD42019125192 ).

Background: To gain more understanding of the potential health effects of sedentary time, knowledge is required about the accumulation and longitudinal development of young people's sedentary time. This study examined tracking of young peoples' total and prolonged sedentary time as well as their day-to-day variation using the International Children's Accelerometry Database., Methods: Longitudinal accelerometer data of 5991 children (aged 4-17y) was used from eight studies in five countries. Children were included if they provided valid (≥8 h/day) accelerometer data on ≥4 days, including ≥1 weekend day, at both baseline and follow-up (average follow-up: 2.7y; range 0.7-8.2). Tracking of total and prolonged (i.e. ≥10-min bouts) sedentary time was examined using multilevel modelling to adjust for clustering of observations, with baseline levels of sedentary time as predictor and follow-up levels as outcome. Standardized regression coefficients were interpreted as tracking coefficients (low: < 0.3; moderate: 0.3-0.6; high: > 0.6)., Results: Average total sedentary time at study level ranged from 246 to 387 min/day at baseline and increased annually by 21.4 min/day (95% confidence interval [19.6-23.0]) on average. This increase consisted almost entirely of prolonged sedentary time (20.9 min/day [19.2-22.7]). Total (standardized regression coefficient (B) = 0.48 [0.45-0.50]) and prolonged sedentary time (B = 0.43 [0.41-0.45]) tracked moderately. Tracking of day-to-day variation in total (B = 0.04 [0.02-0.07]) and prolonged (B = 0.07 [0.04-0.09]) sedentary time was low., Conclusion: Young people with high levels of sedentary time are likely to remain among the people with highest sedentary time as they grow older. Day-to-day variation in total and prolonged sedentary time, however, was rather variable over time.

Background: All 24-h movement behaviors, i.e. physical activity, sedentary behavior and sleep, are important for optimal health in children. Currently, no tools exist that include all 24-h behaviors and have been proven to be both reliable and valid. Potential reasons for the inadequate validity and reliability of existing questionnaires are the lack of focus on the content validity and lack of involvement of children in the development. Therefore, the aim of this study was to co-create a 24-h movement behavior tool together with 9-12-year-old children., Methods: Concept mapping and photovoice meetings were held to identify children's physical activity behaviors. During concept mapping meetings with four groups of children (n = 40), children generated an extensive list of physical activities they engaged in, sorted the activities in categories and rated the frequency and perceived intensity of these activities. Using photovoice, three groups of children (n = 24) photographed their physical activities during one weekday and one weekend day, named the photographs, and placed them on a timeline. Furthermore, researchers obtained information on relevant items regarding sleep and sedentary behavior by screening existing questionnaires. Thereafter, we developed the first version of MyDailyMoves. Subsequently, we examined the content validity of the tool together with three groups of children (n = 22) and one group of researchers (n = 7) using focus group meetings., Results: MyDailyMoves has a timeline format, onto which children add the activities they performed the previous day. Based on the concept mapping and photovoice studies, eight physical activity categories were included: playing inside, playing outside, sports, hobbies, chores, personal care, transport, and others. Sleep questions and two more sedentary categories (schoolwork and screen time) were added to MyDailyMoves to define and complete the timeline. The content validity study showed that all items in the tool were relevant. However, children mentioned that the activity category 'eating' was missing and the understandability of how to use the tool should be improved by adding an explanatory video. Both suggestions were adopted in the second version., Conclusion: Including the children's perceptions throughout the tool development process resulted in a comprehensive and practical tool which is easy for children to use.

Background: Youth-led Participatory Action Research (YPAR) involves children throughout the process of developing and implementing interventions. Combining YPAR with a structural approach for designing and planning interventions, such as Intervention Mapping (IM), may further improve implementation and effectiveness of interventions. This paper describes how YPAR and IM were combined in the Kids in Action study., Methods: The Kids in Action study aims to improve health behaviors of 9-12-year old children living in a low socioeconomic neighborhood in Amsterdam, by co-designing interventions with these children. At each of four schools 6-8 children (N = 18-24 total per year) and two academic researchers formed participatory groups that met weekly or every fortnight during two school years. An IM expert panel advised the participatory groups on the application of IM., Results: Following the IM protocol, we conducted a participatory needs assessment with children, parents and professionals, in IM-step 1. In IM-step 2, the IM expert panel constructed matrices of program objectives, and the children provided feedback. In collaboration with children programs were designed and produced using an iterative process during IM-steps 3-4. In IM-step 5, the participatory groups and professional community partners designed the implementation plan. Finally, in IM-step 6, the protocol of the process and effect evaluation - executed by academic researchers with input from children - was developed., Conclusions: By combining YPAR and IM, several interventions have been developed and implemented, varying from a school water policy to extracurricular sports activities. Sharing responsibility with children was challenging when combining IM with YPAR. In YPAR children are given as much autonomy as possible, while traditional IM development work is primarily done by academic researchers. Strengths in combining IM and YPAR include the involvement of the end-users - children - throughout the process while at the same time developing interventions based on existing evidence. Time-management, a multidisciplinary team, and flexibility are important conditions when combining IM with YPAR. A strong community project group, with professionals who were willing to help children develop and execute their ideas, was an important success factor. This study can serve as an example to other YPAR studies developing interventions using the IM protocol.

Background: Active school travel by bike may provide appropriate means to promote physical activity through commuting to and from school, expanding the mobility during leisure time, and integrating a lifelong positive behavior routine. However, bicycling seems to be a less common form of active school transport and declining cycling to school trends in some European countries have been observed. Therefore, effective interventions aiming at promoting biking to school are warranted. To gain a better understanding of effective programs, the systematic review will summarize strategies and effects of school-based interventions targeted on positively influencing active school travel by bicycle., Methods: The databases ERIC, PsycINFO, PSYNDEX, PubMed, Scopus, SPORTDiscus, SURF, and Web of Science will be searched utilizing a detailed search strategy according to "PICo". Consequently, there will be no restriction regarding the outcomes measured in studies. For inclusion in the review, the identified primary studies (i.e. randomized and non-randomized controlled trials) should be published between 2000 and 2019 due to their current relevance, and written in English. The screening, data extraction, and appraisal of study quality as well as behavior change techniques will be undertaken by two independent researchers. To assess the methodological quality of every included study, the quality assessment tool "Effective Public Health Practice Project" for quantitative studies will be used. Behavior change techniques will be identified by utilizing the "BCT Taxonomy v1". If data permits, meta-analyses for intervention effects will be conducted where appropriate., Discussion: The planned systematic review can provide information about how bicycling is considered in school-based interventions as an effective strategy to promote active commuting to school among students. In this regard, the conclusions drawn from the review will establish a basis for researchers to plan and implement a comprehensive cycling intervention in the school setting., Systematic Review Registration: PROSPEROCRD42019125192.

Background: Physical activity has beneficial effects on the health of cancer survivors. We aimed to investigate accelerometer-assessed physical activity and sedentary time in cancer survivors, and describe activity profiles. Additionally, we identify demographic and clinical correlates of physical activity, sedentary time and activity profiles., Methods: Accelerometer, questionnaire and clinical data from eight studies conducted in four countries (n = 1447) were pooled. We calculated sedentary time and time spent in physical activity at various intensities using Freedson cut-points. We used latent profile analysis to identify activity profiles, and multilevel linear regression analyses to identify demographic and clinical variables associated with accelerometer-assessed moderate to vigorous physical activity (MVPA), sedentary time, the highly active and highly sedentary profile, adjusting for confounders identified using a directed acyclic graph., Results: Participants spent on average 26 min (3%) in MVPA and 568 min (66%) sedentary per day. We identified six activity profiles. Older participants, smokers and participants with obesity had significantly lower MVPA and higher sedentary time. Furthermore, men had significantly higher MVPA and sedentary time than women and participants who reported less fatigue had higher MVPA time. The highly active profile included survivors with high education level and normal body mass index. Haematological cancer survivors were less likely to have a highly active profile compared to breast cancer survivors. The highly sedentary profile included older participants, males, participants who were not married, obese, smokers, and those < 12 months after diagnosis., Conclusions: Cancer survivors engage in few minutes of MVPA and spend a large proportion of their day sedentary. Correlates of MVPA, sedentary time and activity profiles can be used to identify cancer survivors at risk for a sedentary and inactive lifestyle.

Plain English Summary: Background: Society has to cope with a large burden of health issues. There is need to find solutions to prevent diseases and help individuals live healthier lifestyles. Individual needs and circumstances vary greatly and one size fit all solutions do not tend to work well. More tailored solutions centred on individuals' needs and circumstances can be developed in collaboration with these individuals. This process, known as co-creation, has shown promise but it requires guiding principles to improve its effectiveness. The aim of this study was to identify a key set of principles and recommendations for co-creating public health interventions. Methods: These principles were collaboratively developed through analysing a set of case studies targeting different health behaviours (such as reducing sitting and improving strength and balance) in different groups of people (such as adolescent schoolgirls and older adults living in the community). Results: The key principles of co-creation are presented in four stages: Planning (what is the purpose of the co-creation; and who should be involved?); Conducting (what activities can be used during co-creation; and how to ensure buy-in and commitment?); Evaluating (how do we know the process and the outcome are valid and effective?) and Reporting (how to report the findings?). Three models are proposed to show how co-created solutions can be scaled up to a population level. Conclusions: These recommendations aim to help the co-creation of public health interventions by providing a framework and governance to guide the process., Abstract: Background: Due to the chronic disease burden on society, there is a need for preventive public health interventions to stimulate society towards a healthier lifestyle. To deal with the complex variability between individual lifestyles and settings, collaborating with end-users to develop interventions tailored to their unique circumstances has been suggested as a potential way to improve effectiveness and adherence. Co-creation of public health interventions using participatory methodologies has shown promise but lacks a framework to make this process systematic. The aim of this paper was to identify and set key principles and recommendations for systematically applying participatory methodologies to co-create and evaluate public health interventions. Methods: These principles and recommendations were derived using an iterative reflection process, combining key learning from published literature in addition to critical reflection on three case studies conducted by research groups in three European institutions, all of whom have expertise in co-creating public health interventions using different participatory methodologies. Results: Key principles and recommendations for using participatory methodologies in public health intervention co-creation are presented for the stages of: Planning (framing the aim of the study and identifying the appropriate sampling strategy); Conducting (defining the procedure, in addition to manifesting ownership); Evaluating (the process and the effectiveness) and Reporting (providing guidelines to report the findings). Three scaling models are proposed to demonstrate how to scale locally developed interventions to a population level. Conclusions: These recommendations aim to facilitate public health intervention co-creation and evaluation utilising participatory methodologies by ensuring the process is systematic and reproducible., Competing Interests: Not applicable.Not applicable.The authors declare that they have no competing interests.Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Background: In today's society, few adolescents meet physical activity guidelines and effects of physical activity promoting programmes are disappointing. In studies exploring determinants of physical activity, the perspective of adolescents themselves is largely lacking. Also, there is a lack of knowledge on potential environmental determinants of adolescent physical activity. Therefore, this study aimed to explore adolescents' perspectives on characteristics of an activity-friendly environment., Methods: Concept mapping meetings were conducted with four secondary school classes, including 115 adolescents (13-17 years). Each student generated ideas regarding the characteristics of an activity-friendly environment. For each school class, ideas were combined and identical ideas were removed. Next, students individually sorted all ideas, based on self-perceived similarity, and rated their importance on a five-point Likert-scale. A concept map was created for each school class using multidimensional scaling and hierarchical cluster analysis. Finally, the researchers named the potential environmental determinants within the clusters., Results: The concept maps depicted 23 unique potential determinants of activity friendliness, of which 15 were similar across all school classes. Potential determinants were categorized in the physical-, social-, economic-, and motivational domain. The most frequent and important adolescent-perceived determinants of activity friendliness across all school classes belonged to the physical domain, e.g. a suitable area including a proper surface for a variety of sports, and good lighting in the playground., Conclusions: Our findings show that adolescents perceive potential determinants in the physical and economic domain as most important for activity friendliness, indicating that future interventions might benefit from targeting potential determinants within these domains.

Background: This study examined the frequency of and differences in sedentary bouts of different durations and the total time spent in sedentary bouts on a weekday, a weekend day, during school hours, during after-school hours and in the evening period in a sample of 10- to 12-year-old Belgian children., Methods: Accelerometer data were collected as part of the ENERGY-project in Belgium (n = 577, 10.9 ± 0.7 years, 53% girls) in 2011. Differences in total sedentary time, sedentary bouts of 2-5, 5-10, 10-20, 20-30 and ≥30 min and total time accumulated in those bouts were examined on a weekday, a weekend day, during school hours, during after-school hours and in the evening period, using multilevel analyses in MLwiN 2.22., Results: More than 60% of the participants' waking time was spent sedentary. Children typically engaged in short sedentary bouts of 2-5 and 5-10 min, which contributed almost 50% towards their total daily sedentary time. Although the differences were very small, children engaged in significantly fewer sedentary bouts of nearly all durations during after-school hours compared to during school hours and in the evening period. Children also engaged in significantly fewer sedentary bouts of 5-10, 10-20, and 20-30 min per hour on a weekend day than on a weekday., Conclusions: Although primary school children spend more than 60% of their waking time sedentary, they generally engaged in short sedentary bouts. Children's sedentary bouts were slightly longer on weekdays, particularly during school hours and in the evening period, although the differences were very small. These results suggest that in this age group, interventions focusing on reducing total sedentary time rather than interrupting prolonged sedentary time are needed.

Background: The prominence of sedentary behavior research in health science has grown rapidly. With this growth there is increasing urgency for clear, common and accepted terminology and definitions. Such standardization is difficult to achieve, especially across multi-disciplinary researchers, practitioners, and industries. The Sedentary Behavior Research Network (SBRN) undertook a Terminology Consensus Project to address this need., Method: First, a literature review was completed to identify key terms in sedentary behavior research. These key terms were then reviewed and modified by a Steering Committee formed by SBRN. Next, SBRN members were invited to contribute to this project and interested participants reviewed and provided feedback on the proposed list of terms and draft definitions through an online survey. Finally, a conceptual model and consensus definitions (including caveats and examples for all age groups and functional abilities) were finalized based on the feedback received from the 87 SBRN member participants who responded to the original invitation and survey., Results: Consensus definitions for the terms physical inactivity, stationary behavior, sedentary behavior, standing, screen time, non-screen-based sedentary time, sitting, reclining, lying, sedentary behavior pattern, as well as how the terms bouts, breaks, and interruptions should be used in this context are provided., Conclusion: It is hoped that the definitions resulting from this comprehensive, transparent, and broad-based participatory process will result in standardized terminology that is widely supported and adopted, thereby advancing future research, interventions, policies, and practices related to sedentary behaviors.

An increasing number of interventions targeting sedentary behaviour in children have emerged in recent years. Recently published reviews included sedentary behaviour and physical activity interventions. This review critically summarizes evidence on the effectiveness of intervention strategies that exclusively targeted reducing sedentary time in children and adolescents. We performed a systematic literature search in Pubmed, Embase and the Cochrane Library through November 2015. Two independent reviewers selected eligible studies, extracted relevant data and rated the methodological quality using the assessment tool for quantitative studies. We included 21 intervention studies, of which 8 studies scored moderate on methodological quality and 13 studies scored weak. Four out of eight moderate quality studies reported significant beneficial intervention effects.Although descriptions of intervention strategies were not always clearly reported, we identified encouragement of a TV turnoff week and implementing standing desks in classrooms as promising strategies. Due to a lack of high quality studies and inconsistent findings, we found no convincing evidence for the effectiveness of existing interventions targeting solely sedentary behaviour. We recommend that future studies apply mediation analyses to explore which strategies are most effective. Furthermore, to increase the effectiveness of interventions, knowledge of children's motives to engage in sedentary behavior is required, as well as their opinion on potentially effective intervention strategies.

Background: Evidence on the association between different screen behaviours and cardiometabolic biomarkers in children is limited. We examined the independent relationship of TV time and PC time with cardiometabolic biomarkers in Dutch 5-6 year old children., Methods: Cross-sectional analyses were conducted December 2012-March 2013 using data from a multi-ethnic cohort (the ABCD study, n = 1,961). TV and PC time and physical activity were assessed by parent-report. Body weight, height, waist circumference and blood pressure were measured using a standard protocol. Fasting capillary blood samples were collected. A cardiometabolic function score was computed as the mean of the inverted standardised values of waist circumference, mean of systolic and diastolic blood pressure, glucose, HDLC (not inverted), and triglycerides., Results: Mean TV time was 1.2 (± 0.8) hr/day and mean PC time was 0.2 (± 0.4) hr/day. After adjustment for birth weight, height, maternal education, PC time, and physical activity, excessive TV time (>2 hrs/day) was adversely associated with waist circumference (b = 0.39, 95% CI: 0.004;0.78) while PC time was beneficially associated with HDLC levels (b = 0.04, 95% CI: 0.001;0.08). We found no additional significant associations of TV time, or PC time with any of the cardiometabolic biomarkers., Conclusions: We found no convincing evidence for an association between TV or PC time and cardiometabolic function in apparently healthy 5-6 yr olds.

Background: Sedentary time has been identified as an important and independent risk factor for the development of type 2 diabetes mellitus (T2DM) and cardiovascular diseases (CVD) in adults. However, to date most studies have focused on TV time, few also included other sedentary behaviours such as computer use and reading, and most studies had a cross-sectional design. We aimed to examine the prospective relationship between time spent on sedentary behaviours in different domains with individual and clustered cardiometabolic risk in adults., Methods: Longitudinal data of 622 adults aged 30-50 years (42% males) at increased cardiometabolic risk were used. Leisure time TV viewing, computer use, reading and other sedentary activities (e.g. passive transport) were assessed using a subscale of the Activity Questionnaire for Adolescents and Adults (AQuAA), and summed into overall sedentary behaviour (min/day). Weight and blood pressure were measured, waist-to-hip ratio and BMI calculated, and fasting plasma levels of glucose, HbA1c, total cholesterol, HDL-cholesterol, LDL-cholesterol and triglycerides determined. T2DM risk score was estimated according to the ARIC formula and CVD mortality risk according to the SCORE formula., Results: Generalized Estimating Equation analysis demonstrated that over a two-year period higher levels of overall sedentary time and TV time were weakly but negatively associated with one out of 13 studied cardiometabolic risk factors (i.e. HDL cholesterol)., Conclusion: Overall sedentary time, as well as sedentary time in different domains, was virtually not related with cardiometabolic risk factors.

Background: Screen time has been associated with pediatric overweight. However, it is unclear whether overweight predicts or is predicted by excessive amounts of screen time. The aim of this study was to examine the direction of the association between screen time and body fatness in Dutch adolescents., Methods: Longitudinal data of 465 Dutch adolescents (mean age at baseline 13 years, 53% boys) was used. Body fatness (objectively measured BMI, four skin folds and waist- and hip circumference), self-reported time spent watching TV and computer use, and aerobic fitness (shuttle run test) were assessed in all participants at three time points during 12 months. Multi-level linear autoregressive analyses was used to examine whether screen time predicted body fatness in the following time period and whether body fatness predicted screen time. Analyses were performed for boys and girls separately and adjusted for ethnicity and aerobic fitness., Results: Time spent TV viewing did predict changes in BMI and hip circumference in boys, but not in girls, in the subsequent period. Computer time significantly predicted increases in skinfolds in boys and girls and increases in BMI in girls. Body fatness did not predict any changes in screen time., Conclusion: The present study only partly supports the widely posited hypothesis that higher levels of screen time cause increases in body fatness. In addition, this study demonstrates that high levels of body fatness do not predict increases in screen time.