Appropriateness of the definition of 'sedentary' in young children: Whole-room calorimetry study

Low movement, deep-learned sitting patterns, and sedentary behavior in the International Study of Childhood Obesity, Lifestyle and the Environment (ISCOLE)

BACKGROUND/OBJECTIVES

Sedentary behavior (SB) has both movement and postural components, but most SB research has only assessed low movement, especially in children. The purpose of this study was to compare estimates and health associations of SB when derived from a standard accelerometer cut-point, a novel sitting detection technique (CNN Hip Accelerometer Posture for Children; CHAP-Child), and both combined.

METHODS

Data were from the International Study of Childhood Obesity, Lifestyle, and the Environment (ISCOLE). Participants were 6103 children (mean ± SD age 10.4 ± 0.56 years) from 12 countries who wore an ActiGraph GT3X+ accelerometer on the right hip for approximately one week. We calculated SB time, mean SB bout duration, and SB breaks using a cut-point (SBmovement), CHAP-Child (SBposture), and both methods combined (SBcombined). Mixed effects regression was used to test associations of SB variables with pediatric obesity variables (waist circumference, body fat percentage, and body mass index z-score).

RESULTS

After adjusting for MVPA, SBposture showed several significant obesity associations favoring lower mean SB bout duration (b = 0.251-0.449; all p < 0.001) and higher SB breaks (b = -0.005--0.052; all p < 0.001). Lower total SB was unexpectedly related to greater obesity (b = -0.077--0.649; p from <0.001-0.02). For mean SB bout duration and SB breaks, more associations were observed for SBposture (n = 5) than for SBmovement (n = 3) or SBcombined (n = 1), and tended to have larger magnitude as well.

CONCLUSIONS

Using traditional measures of low movement as a surrogate for SB may lead to underestimated or undetected adverse associations between SB and obesity. CHAP-Child allows assessment of sitting posture using hip-worn accelerometers. Ongoing work is needed to understand how low movement and posture are related to one another, as well as their potential health implications.

Decreasing Sedentary Behaviors in Youth to Prevent and Manage Childhood Obesity: Is It Realistic?

PURPOSE OF REVIEW

Decreasing sedentary behaviors has been proposed as one approach to reduce the rate of obesity in youth. This review summarizes the contemporary literature examining the efficacy of these interventions in the school and community along with an additional focus on the role of socioeconomic status in these interventions.

RECENT FINDINGS

Studies that focus on decreasing sedentary behavior have utilized a wide variety of strategies in a number of settings. The effects of these interventions are often hindered by non-standard outcome measures, study infidelity, and subjective measures of sedentary time. However, interventions that incorporate engaged stakeholders and include younger subjects appear to be the most likely to succeed. Promising interventions to decrease sedentary behaviors have been shown in recent clinical trials; however, replicating and sustaining these results is challenging. From the available literature, school-based interventions have the potential of reaching the largest group of children. In contrast, interventions in younger children, particularly those with invested parents, seem to be the most effective.

Energy Cost of Common Physical Activities in Preschoolers

BACKGROUND

To determine the energy cost of common physical activities in preschoolers and to compare it with the Compendium of Energy Expenditure for Youth (CEEY).

METHODS

In total, 42 children [age: 4.8 (0.8) y; body mass index: 15.3 (2.0) kg/m²; 22 boys] completed 13 common physical activities covering sedentary to vigorous intensities, while energy expenditure (EE) was measured continuously by indirect calorimetry. Activity-specific metabolic equivalents (AME) were calculated as the EE observed during each single activity divided by the EE during observed rest. Independent t tests were applied to analyze differences between boys and girls and between AME and CEEY.

RESULTS

No significant differences in AME were observed between girls and boys. Except for playing hide-and-seek, all indoor activities revealed significantly higher energy costs compared with those stated in the compendium. Significant differences in outdoor activities were found for riding a tricycle [5.67 (95% confidence interval, 4.94-6.4) AME vs 6.2 metabolic equivalents, riding a bike, P < .05] and for fast walking [5.42 (95% confidence interval, 4.84-6.0) AME vs 4.6 metabolic equivalents, P < .05].

CONCLUSIONS

Applying the CEEY to preschoolers will lead to a substantial underestimation of EE. Therefore, we recommend that a CEEY for preschool children be developed if measurement of EE is not feasible.

Calibration of GENEActiv accelerometer wrist cut-points for the assessment of physical activity intensity of preschool aged children

This study sought to validate cut-points for use of wrist-worn GENEActiv accelerometer data, to analyse preschool children's (4 to 5 year olds) physical activity (PA) levels via calibration with oxygen consumption values (VO₂). This was a laboratory-based calibration study. Twenty-one preschool children, aged 4.7 ± 0.5 years old, completed six activities (ranging from lying supine to running) whilst wearing the GENEActiv accelerometers at two locations (left and right wrist), these being the participants' non-dominant and dominant wrist, and a Cortex face mask for gas analysis. VO₂ data was used for the assessment of criterion validity. Location specific activity intensity cut-points were established via receiver operator characteristic curve (ROC) analysis. The GENEActiv accelerometers, irrespective of their location, accurately discriminated between all PA intensities (sedentary, light, and moderate and above), with the dominant wrist monitor providing a slightly more precise discrimination at light PA and the non-dominant at the sedentary behaviour and moderate and above intensity levels (area under the curve (AUC) for non-dominant = 0.749-0.993, compared to AUC dominant = 0.760-0.988).

CONCLUSION

This study establishes wrist-worn physical activity cut-points for the GENEActiv accelerometer in preschoolers. What is Known: • GENEActiv accelerometers have been validated as a PA measurement tool in adolescents and adults. • No study to date has validated the GENEActiv accelerometers in preschoolers. What is New: • Cut-points were determined for the wrist-worn GENEActiv accelerometer in preschoolers. • These cut-points can be used in future research to help classify and increase preschoolers' compliance rates with PA.

Sedentary Behavior Research Network (SBRN) - Terminology Consensus Project process and outcome

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.

Kids are not little adults: what MET threshold captures sedentary behavior in children?

PURPOSE

The study compares MET-defined cutpoints used to classify sedentary behaviors in children using a simulated free-living design.

METHODS

A sample of 102 children (54 boys and 48 girls; 7-13 years) completed a set of 12 activities (randomly selected from a pool of 24 activities) in a random order. Activities were predetermined and ranged from sedentary to vigorous intensities. Participant's energy expenditure was measured using a portable indirect calorimetry system, Oxycon mobile. Measured minute-by-minute VO2 values (i.e., ml/kg/min) were converted to an adult- or child-MET value using the standard 3.5 ml/kg/min or the estimated child resting metabolic rate, respectively. Classification agreement was examined for both the "standard" (1.5 adult-METs) and an "adjusted" (2.0 adult-METs) MET-derived threshold for classifying sedentary behavior. Alternatively, we also tested the classification accuracy of a 1.5 child-MET threshold. Classification accuracy of sedentary activities was evaluated relative to the predetermined intensity categorization using receiver operator characteristic curves.

RESULTS

There were clear improvements in the classification accuracy for sedentary activities when a threshold of 2.0 adult-METs was used instead of 1.5 METs (Se1.5 METs = 4.7%, Sp1.5 METs = 100.0%; Se2.0 METs = 36.9%, Sp2.0 METs = 100.0 %). The use of child-METs while maintaining the 1.5 threshold also resulted in improvements in classification (Se = 45.1%, Sp = 100.0%).

CONCLUSION

Adult-MET thresholds are not appropriate for children when classifying sedentary activities. Classification accuracy for identifying sedentary activities was improved when either an adult-MET of 2.0 or a child-MET of 1.5 was used.