Summary: Evidence for adverse health effects of excessive sedentary behaviour in children is predominantly based on cross‐sectional studies, measuring TV viewing as proxy for sedentary behaviour. This systematic review and meta‐analysis summarizes the evidence on the prospective relationship between childhood sedentary behaviour and biomedical health indicators, overall and stratified by type of sedentary behaviour (TV viewing, computer use/games, screen time and objective sedentary time).PubMed, EMBASE, PsycINFO and Cochrane were systematically searched till January 2015. Methodological quality of all included studies was scored, and a best evidence synthesis was applied.We included 109 studies of which 19 were of high quality. We found moderate‐to‐strong evidence for a relationship of overall sedentary time with some anthropometrics (overweight/obesity, weight‐for‐height), one cardiometabolic biomarker (HDL‐cholesterol) and some fitness indicators (fitness, being unfit). For other health indicators, we found no convincing evidence because of inconsistent or non‐significant findings. The evidence varied by type of sedentary behaviour. The meta‐analysis indicated that each additional baseline hour of TV viewing (β = 0.01, 95%CI = [−0.002; 0.02]) or computer use (β = 0.00, 95%CI = [−0.004; 0.01]) per day was not significantly related with BMI at follow‐up.We conclude that the evidence for a prospective relationship between childhood sedentary behaviour and biomedical health is in general unconvincing.

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.

Todays children spend a large amount of their time sedentary. There is limited evidence on the determinants of sedentary behavior in children, and qualitative studies are especially lacking. Therefore, this study aimed to explore determinants of children’s sedentary behavior from the child- and parent perspective. Qualitative data were collected during concept mapping sessions with four groups of 11–13 years old children (n = 38) and two online sessions with parents (n = 21). Children and parents generated sedentary behavior motives, sorted related motives, and rated their importance in influencing children’s sedentary time. Next, multidimensional scaling and hierarchical cluster analysis was performed to create clusters of motives resulting in a concept map. Finally, the researchers named the clusters in the concept map. Concept maps of children yielded eight to ten perceived determinants, and concept maps of parents six to seven. Children and parents identified six similar potential determinants, and both rated as important: Sitting because… “it is the norm (I have to)”, and “I can work/play better that way”. In addition, children rated “there is nobody to play with” as an important potential determinant for engaging in sedentary behavior. The most important child- and parent perceived determinants were related to the social/cultural and physical environment, indicating that these are promising targets for future interventions.

Evidence of adverse health effects of TV viewing is stronger than for overall sedentary behaviour in youth. One explanation may be that TV viewing involves less body movement than other sedentary activities. Variations in body movement across sedentary activities are currently unknown, as are age differences in such variations. This study examined body movement differences across various sedentary activities in children and adolescents, assessed by hip-, thigh- and wrist-worn accelerometers, muscle activity and heart rate. Body movement differences between sedentary activities and standing were also examined. Fifty-three children (aged 10–12 years) and 37 adolescents (aged 16–18 years) performed seven different sedentary activities, a standing activity, and a dancing activity (as a control activity) in a controlled setting. Each activity lasted 10 minutes. Participants wore an Actigraph on their hip and both wrists, an activPAL on their thigh and a heart rate monitor. The muscle activity of weight-bearing leg muscles was measured in a subgroup (n = 38) by surface electromyography. Variations in body movement across activities were examined using general estimation equations analysis. Children showed significantly more body movement during sedentary activities and standing than adolescents. In both age groups, screen-based sedentary activities involved less body movement than non-screen-based sedentary activities. This may explain the stronger evidence for detrimental health effects of TV viewing while evidence for child sedentary behaviour in general is inconsistent. Differences in body movement during standing and sedentary activities were relatively small. Future research should examine the potential health effects of differences in body movement between screen-based versus non-screen based and standing versus sedentary activities.

The primary aim was to examine child- and parent-related correlates of accelerometer-assessed overall total and prolonged (i.e., accumulated in bouts of ≥10 consecutive minutes) sedentary time (SED) in 5- to 6-year-old children. Second, child- and parent-related correlates of total and prolonged SED during weekend days and the after school period were examined, as associations with parent-related correlates may be stronger during these periods. SED and moderate-to-vigorous-intensity physical activity (MVPA) were assessed by ActiGraph accelerometers in children (n = 836) and one of their parents/carers. Parents completed a questionnaire examining potential parent-related correlates. Multilevel models examined associations between potential correlates and children’s total and prolonged SED. Children’s MVPA was the only correlate that was consistently negatively associated with both total and prolonged SED across the different time periods (overall, after school, and weekend days). Higher total SED in parents was associated with higher overall total SED and weekend total SED in children. Higher body mass index z-scores of children were associated with lower overall total and prolonged SED. Girls had lower prolonged SED after school than boys. Older children had lower total SED during the weekend. In conclusion, few potential correlates were associated with young children’s total or prolonged SED and most associations differed by time period.