Cross-validation of cut-points in preschool children using different accelerometer placements and data axes

The present study cross-validated various cut-points to assess physical activity and sedentary behaviour in preschoolers, using hip- and wrist-worn accelerometers and both vertical axis and vector magnitude data. Secondly, we examined the influence of epoch length on time estimates of physical activity and sedentary behaviour. Sixty-four preschoolers (34 girls) wore two accelerometers, on their right hip and dominant wrist, during 1 hour of free play. Preschoolers’ activities were observed by two trained researchers. Area under the curve (AUC) was calculated for the receiving operating characteristic (ROC) curves as a measure of precision. AUC ranges were 0.603–0.723 for sedentary behaviour, 0.472–0.545 for light physical activity and 0.503–0.661 for moderate-to-vigorous physical activity (MVPA), indicating poor to fair precision. Percentage of time classified as sedentary behaviour, light or MVPA according to observation and accelerometer data varied largely between cut-points, accelerometer placements and axes. The influence of epoch length on time estimates was minimal across cut-points, except for one hip-based vector magnitude cut-point. Across all accelerometer placements and data axes, no set of cut-points demonstrated adequate precision for sedentary behaviour, light physical activity and MVPA. The highly variable and omnidirectional activity pattern of preschoolers may explain the lack of adequate cut-points

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

Standing is not enough: A randomized crossover study on the acute cardiometabolic effects of variations in sitting in healthy young men

Objectives: Standing desks and stability balls are increasingly popular to increase muscle activity and thereby prevent potential adverse cardiometabolic effects of prolonged sitting. The present study examined the effects of (1) sitting on a stability ball (‘active sitting’) and (2) hourly 10-min standing interruptions during prolonged sitting on postprandial cardiometabolic biomarkers. Design: Experimental crossover study. Methods: Twenty healthy-weight males (19.2 ± 0.6 years) participated randomly in three 5-h conditions: (1) sitting on an office chair (SIT), (2) sitting on a stability ball (SIT-ACTIVE) and (3) sitting with hourly 10-min standing interruptions (SIT-STAND). In each condition, participants consumed a standardized mixed meal at baseline. Hourly blood samples and pre/post saliva samples were collected and analyzed for levels of insulin, glucose and cortisol. Pre/post hemodynamic monitoring (middle finger; Nexfin-monitoring) was conducted; heart rate was measured continuously (Polar) and muscle activity (leg and lower-back, Portilab) was measured during periods of sitting (on an office chair and on a stability ball) and standing. Results: Muscle activity and heart rate during standing periods were significantly higher than during sitting (both SIT and SIT-ACTIVE). Generalized estimating equations revealed no significant difference in any of the biomarkers between the three experimental conditions. Systolic blood pressure was lower during SIT-STAND, while stroke volume was lower during SIT-ACTIVE than during SIT. Although significant, these differences were small, approximating the day-to-day variability in blood pressure and stroke volume. Conclusions: We conclude that hourly standing interruptions during 5 h prolonged sitting or continuously sitting on a stability ball do not significantly affect postprandial cardiometabolic biomarkers in healthy young men. Trial registration: This trial is registered in the NTR trial register (NTRcode 5723)

A novel method to promote physical activity among older adults in residential care: An exploratory field study on implicit social norms

Background: Physical activity (PA) levels of older adults living in a care setting are known to be very low. This is a significant health(care) problem, as regular PA has many health benefits also at advanced age. Research on automatic processes underlying PA behaviour in physically inactive older adults is yet non-existing. Since people are unconsciously influenced by people around them (i.e. by 'social norms') automatic processes could be used to promote PA. We developed an explorative intervention method to assess the effects of automatically processed (implicit) descriptive social norms ('What most people do') on behavioral intention and participation in PA offered in a local residential care setting. Methods: Forty-seven care clients met the inclusion criteria. Participants (response 45%; unaware of the intention of the research) were randomly assigned to an experimental (N = 10) or a control group (N = 11). The experimental group was exposed to photos and text heading on active peers (physically active implicit descriptive norm) using a draft newsletter article they were asked to comment on, whereas the control group was exposed to a newsletter with photos and text heading of inactive peers (physically inactive implicit descriptive norm). Subsequently, we tested (Fishers exact p < 0.10) whether this unaware exposure predicted intention (implicit and explicit) to participate in PA offered and organized by the care center (e.g. walking, gymnastics) and self-reported participation in organised PA at three months follow-up. Participants were debriefed later. Results: Mean age was 87 years (SD = 3.6; range 80-95) and 53% of the participants were male. At baseline, there were no significant differences in self-rated health and PA between the experimental and control group. Results indicated that implicit descriptive norm information was associated with implicit PA intention (p =.056, Fisher's exact test). No significant effects were found on explicit intention. At 3 months follow-up the experimental group self-reported 80% participation in PA versus 22% in the control group (Fisher's exact test p = 0.027). Conclusion: Implicit descriptive social norm information could indeed be a potentially effective way to encourage inactive older adults in residential care to engage in organized PA

Why do children engage in sedentary behavior? Child- and parent-perceived determinants

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 childand 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

Comparison of methods for the analysis of relatively simple mediation models

Background/aims: Statistical mediation analysis is an often used method in trials, to unravel the pathways underlying the effect of an intervention on a particular outcome variable. Throughout the years, several methods have been proposed, such as ordinary least square (OLS) regression, structural equation modeling (SEM), and the potential outcomes framework. Most applied researchers do not know that these methods are mathematically equivalent when applied to mediation models with a continuous mediator and outcome variable. Therefore, the aim of this paper was to demonstrate the similarities between OLS regression, SEM, and the potential outcomes framework in three mediation models: 1) a crude model, 2) a confounder-adjusted model, and 3) a model with an interaction term for exposure-mediator interaction. Methods: Secondary data analysis of a randomized controlled trial that included 546 schoolchildren. In our data example, the mediator and outcome variable were both continuous. We compared the estimates of the total, direct and indirect effects, proportion mediated, and 95% confidence intervals (CIs) for the indirect effect across OLS regression, SEM, and the potential outcomes framework. Results: OLS regression, SEM, and the potential outcomes framework yielded the same effect estimates in the crude mediation model, the confounder-adjusted mediation model, and the mediation model with an interaction term for exposure-mediator interaction. Conclusions: Since OLS regression, SEM, and the potential outcomes framework yield the same results in three mediation models with a continuous mediator and outcome variable, researchers can continue using the method that is most convenient to them. Keywords: Mediation analysis, Indirect effect, Ordinary least square regression, Structural equation modeling, Potential outcomes framework, Cross-sectional dat

Systematic review of accelerometer-based methods for 24-h physical behavior assessment in young children (0-5 years old)

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

Perspectives of health practitioners and adults who regained weight on predictors of relapse in weight loss maintenance behaviors: a concept mapping study

Background: Preventing people from relapsing into unhealthy habits requires insight into predictors of relapse in weight loss maintenance behaviors. We aimed to explore predictors of relapse in physical activity and dietary behavior from the perspectives of health practitioners and persons who regained weight, and identify new predictors of relapse beyond existing knowledge. Methods: We used concept mapping to collect data, by organizing eight concept mapping sessions among health practitioners (N=39, five groups) and persons who regained weight (N=21, three groups). At the start of each session, we collected participants’ ideas on potential predictors. Subsequently, participants individually sorted these ideas by relatedness and rated them on importance. We created concept maps using principal component analysis and cluster analysis. Results: 43 predictors were identified, of which the majority belonged to the individual domain rather than the environmental domain. Although the majority of predictors were mentioned by both stakeholder groups, both groups had different opinions regarding their importance. Also, some predictors were mentioned by only one of the two stakeholder groups. Practitioners indicated change in daily structure, stress, maladaptive coping skills, habitual behavior, and lack of self-efficacy regarding weight loss maintenance as most important recurrent (mentioned in all groups) predictors. Persons who regained weight indicated lifestyle imbalance or experiencing a life event, lack of perseverance, negative emotional state, abstinence violation effect, decrease in motivation and indulgence as most important recurrent predictors. Conclusions: For several predictors associations with relapse were shown in prior research; additionally, some new predictors were identified that have not been directly associated with relapse in weight loss maintenance behaviors. Our finding that both groups differed in opinion regarding the importance of predictors or identified different predictors, may provide an opportunity to enhance lifestyle coaching by creating more awareness of these possible discrepancies and including both points of view during coaching

What are the determinants of children's sleep behavior? A systematic review of longitudinal studies

To develop evidence-based healthy sleep interventions for children, this review provides insight into the behavioral determinants of sleep behavior. Hence the objective of this review is to systematically review the longitudinal evidence on determinants of children's sleep behavior. Studies were identified from searches in PubMed, PsycINFO, and Web of Science, until January 2017. Longitudinal studies investigating the association between potential determinants and sleep behavior (duration, quality and timing) in healthy children aged 4–12 years were included. The methodological quality was scored and the results were summarized using a best-evidence synthesis. We followed the PRISMA statement guidelines in order to summarize the evidence accurately and reliably. Twelve of the 45 included studies were rated as ‘high quality’. We found strong evidence for child age and moderate evidence for screen time, past sleep behavior, and a difficult temperament as determinant of sleep duration. For determinants of sleep quality, evidence was either insufficient or inconsistent. We found moderate evidence for week schedule as a determinant of sleep timing, with later bed- and wake times in weekends. More high quality studies, which are extensive, collaborative, and multidisciplinary, are needed into the determinants of all dimensions of sleep behavior

Validation of predictive equations for resting energy expenditure in obese adolescents

Background: When the resting energy expenditure (REE) of overweight and obese adolescents cannot be measured by indirect calorimetry, it has to be predicted with an equation. Objective: The aim of this study was to examine the validity of published equations for REE compared with indirect calorimetry in overweight and obese adolescents. Design: Predictive equations based on weight, height, sex, age, fatfree mass (FFM), and fat mass were compared with measured REE. REE was measured by indirect calorimetry, and body composition was measured by dual-energy X-ray absorptiometry. The accuracy of the REE equations was evaluated on the basis of the percentage of adolescents predicted within 10% of REE measured, the mean percentage difference between predicted and measured values (bias), and the root mean squared prediction error (RMSE). Results: Forty-three predictive equations (of which 12 were based on FFM) were included. Validation was based on 70 girls and 51 boys with a mean age of 14.5 y and a mean (6SD) body mass index SD score of 2.93 6 0.45. The percentage of adolescents with accurate predictions ranged from 74% to 12% depending on the equation used. The most accurate and precise equation for these adolescents was the Molnar equation (accurate predictions: 74%; bias: –1.2%; RMSE: 174 kcal/d). The often-used Schofield-weight equation for age 10–18 y was not accurate (accurate predictions: 50%; bias: +10.7%; RMSE: 276 kcal/d). Conclusions: Indirect calorimetry remains the method of choice for REE in overweight and obese adolescents. However, the sex-specific Molnar REE prediction equation appears to be the most accurate for overweight and obese adolescents aged 12–18 y. This trial was registered at www.trialregister.nl with the Netherlands Trial Register as ISRCTN27626398