Xanne Janssen

Predictive validity and classification accuracy of actigraph energy expenditure equations and cut-points in young children

Objectives Evaluate the predictive validity of ActiGraph energy expenditure equations and the classification accuracy of physical activity intensity cut-points in preschoolers. Methods Forty children aged 4–6 years (5.3±1.0 years) completed a ∼150-min room calorimeter protocol involving age-appropriate sedentary, light and moderate-to vigorous-intensity physical activities. Children wore an ActiGraph GT3X on the right mid-axillary line of the hip. Energy expenditure measured by room calorimetry and physical activity intensity classified using direct observation were the criterion methods. Energy expenditure was predicted using Pate and Puyau equations. Physical activity intensity was classified using Evenson, Sirard, Van Cauwenberghe, Pate, Puyau, and Reilly, ActiGraph cut-points. Results The Pate equation significantly overestimated VO2 during sedentary behaviors, light physical activities and total VO2 (P<0.001). No difference was found between measured and predicted VO2 during moderate-to vigorous-intensity physical activities (P = 0.072). The Puyau equation significantly underestimated activity energy expenditure during moderate-to vigorous-intensity physical activities, light-intensity physical activities and total activity energy expenditure (P<0.0125). However, no overestimation of activity energy expenditure during sedentary behavior was found. The Evenson cut-point demonstrated significantly higher accuracy for classifying sedentary behaviors and light-intensity physical activities than others. Classification accuracy for moderate-to vigorous-intensity physical activities was significantly higher for Pate than others. Conclusion Available ActiGraph equations do not provide accurate estimates of energy expenditure across physical activity intensities in preschoolers. Cut-points of ≤25counts⋅15 s−1 and ≥420 counts⋅15 s−1 for classifying sedentary behaviors and moderate-to vigorous-intensity physical activities, respectively, are recommended.

Timing of the decline in physical activity in childhood and adolescence: Gateshead Millennium Cohort Study

Background and aim There is a widely held and influential view that physical activity begins to decline at adolescence. This study aimed to identify the timing of changes in physical activity during childhood and adolescence. Methods Longitudinal cohort study (Gateshead Millennium Study) with 8 years of follow-up, from North-East England. Cohort members comprise a socioeconomically representative sample studied at ages 7, 9, 12 and 15 years; 545 individuals provided physical activity data at two or more time points. Habitual total volume of physical activity and moderate-to-vigorous intensity physical activity (MVPA) were quantified objectively using the Actigraph accelerometer over 5–7 days at the four time points. Linear mixed models identified the timing of changes in physical activity across the 8-year period, and trajectory analysis was used to identify subgroups with distinct patterns of age-related changes. Results Four trajectories of change in total volume of physical activity were identified representing 100% of all participants: all trajectories declined from age 7 years. There was no evidence that physical activity decline began at adolescence, or that adolescent declines in physical activity were substantially greater than the declines during childhood, or greater in girls than boys. One group (19% of boys) had relatively high MVPA which remained stable between ages 7 and15 years. Conclusions Future policy and research efforts to promote physical activity should begin well before adolescence, and should include both boys and girls.

Longitudinal levels and bouts of sedentary time among adolescent girls

BackgroundAdolescent girls are one of the most sedentary demographic groups. A better understanding of their accumulation of sedentary time is needed to inform future interventions. The purpose of this study was to examine the longitudinal levels and bouts of objectively measured sedentary time accumulated during different days of the week and periods of the weekday among a large sample of adolescent girls.MethodsThe results are based on 655 adolescent girls from the Girls in Sport Intervention and Research Project. Levels and bouts of sedentary time were derived from accelerometer data collected at baseline and 18-month follow-up. Total, weekday, weekend, school (i.e., morning bell to afternoon bell), after school (i.e., afternoon bell to 19:00), and evening (i.e. 19:01 to 23:59) sedentary time levels and bouts were calculated. Repeated-measures ANCOVAs were conducted to examine differences in sedentary time levels and bouts between days and time periods after adjusting for wear time, accelerometer model, and intervention group.ResultsCross-sectional analyses revealed that levels and bouts of sedentary time were higher on weekdays compared to weekend days at baseline. Similar trends were observed at follow-up. In addition, percentage of wear time spent sedentary and bouts/hr of sedentary time were highest in the evening compared to the school and after school periods at both baseline and follow-up. Longitudinal analyses revealed that levels and bouts of sedentary time were higher at follow-up compared to baseline across the different days of the week and periods of the weekday examined, with the biggest increase (15%) occurring in the school period.ConclusionsFuture interventions targeting sedentary time among adolescent girls should consider developing strategies to reduce and break up prolonged sedentary time during the school day and in the evening.

Validation of activPAL Defined Sedentary Time and Breaks in Sedentary Time in 4- to 6-Year-Olds

This study examined the classification accuracy of the activPAL, including total time spent sedentary and total number of breaks in sedentary behavior (SB) in 4- to 6-year-old children. Forty children aged 4-6 years (5.3 ± 1.0 years) completed a ~150-min laboratory protocol involving sedentary, light, and moderate- to vigorous-intensity activities. Posture was coded as sit/lie, stand, walk, or other using direct observation. Posture was classified using the activPAL software. Classification accuracy was evaluated using sensitivity, specificity and area under the receiver operating characteristic curve (ROC-AUC). Time spent in each posture and total number of breaks in SB were compared using paired sample t-tests. The activPAL showed good classification accuracy for sitting (ROC-AUC = 0.84) and fair classification accuracy for standing and walking (0.76 and 0.73, respectively). Time spent in sit/lie and stand was overestimated by 5.9% (95% CI = 0.6-11.1%) and 14.8% (11.6-17.9%), respectively; walking was underestimated by 10.0% (-12.9-7.0%). Total number of breaks in SB were significantly overestimated (55 ± 27 over the course of the protocol; p < .01). The activPAL performed well when classifying postures in young children. However, the activPAL has difficulty classifying other postures, such as kneeling. In addition, when predicting time spent in different postures and total number of breaks in SB the activPAL appeared not to be accurate.

Issues related to measuring and interpreting objectively measured sedentary behavior data

The use of objective measures of sedentary behavior has increased over the past decade; however, as is the case for objectively measured physical activity, methodological decisions before and after data collection are likely to influence the outcomes. The aim of this article is to review the evidence on different methodological decisions made by researchers when examining sedentary behavior. The different issues researchers may encounter when measuring sedentary behavior have been divided into (a) activity monitor placement; (b) epochs, cut points, and non-wear time definitions; (c) criteria for sedentary behavior bouts and breaks; and (d) combining motion and posture data. This article recommends that (a) activity monitors should be placed on the thigh and combined with a data reduction approach that estimates inclination, especially in children and adults; and (b) researchers should clearly report their data processing decisions to enhance the ability to evaluate and compare studies in the future. However, the article also highlights a dearth of methodological evidence to inform the use of objective measures of sedentary behavior. Based on the gaps in the literature, research recommendations, which require addressing to develop a best practice protocol when measuring sedentary behavior objectively, have been made.

Evaluation of Actical equations and thresholds to predict physical activity intensity in young children

Abstract This study examined the validity of current Actical activity energy expenditure (AEE) equations and intensity cut-points in preschoolers using AEE and direct observation as criterion measures. Forty 4–6-year-olds (5.3 ± 1.0 years) completed a ~150-min room calorimeter protocol involving age-appropriate sedentary behaviours (SBs), light intensity physical activities (LPAs) and moderate-to-vigorous intensity physical activities (MVPAs). AEE and/or physical activity intensity were calculated using Actical equations and cut-points by Adolph, Evenson, Pfeiffer and Puyau. Predictive validity was examined using paired sample t-tests. Classification accuracy was evaluated using weighted kappas, sensitivity, specificity and area under the receiver operating characteristic curve. The Pfeiffer equation significantly overestimated AEE during SB and underestimated AEE during LPA (P < 0.0125 for both). There was no significant difference between measured and predicted AEEs during MVPA. The Adolph cut-point showed significantly higher accuracy for classifying SB, LPA and MVPA than all others. The available Actical equation does not provide accurate estimates of AEE across all intensities in preschoolers. However, the Pfeiffer equation performed reasonably well for MVPA. Using cut-points of ≤6 counts · 15 s−1, 7–286 counts · 15 s−1 and ≥ 287 counts · 15 s−1 when classifying SB, LPA and MVPA, respectively, is recommended.

Sedentary time, physical activity and compliance with IOM recommendations in young children at childcare

The aim of this study was to report patterns of sitting, standing and physical activity (PA) and compliance with Institute of Medicine (IOM) recommendations for sedentary behavior (SB) and PA among children aged 1 to 5 years at childcare, and examine sociodemographic variations. Sitting, standing and PA time was assessed using an activPAL inclinometer over a period of 1 to 5 days in 301 children (49% boys; mean age = 3.7 ± 1.0 years) across 11 childcare services in Illawarra, NSW, Australia. Breaks and bouts of sitting and standing were calculated and categorized. Height and weight were assessed and parents completed a demographic survey. Differences by sex, age category (< 3 vs ≥ 3 years), weight status and SES were examined. Children spent 48.4% of their time at childcare sitting, 32.5% standing, and 19.1% in PA. Boys spent significantly more time in PA compared to girls (20.8% vs 17.7%; P = 0.003). Toddlers (< 3 years) spent significantly more time in PA compared to preschoolers (≥ 3 years) (22.2% vs 18.3%; P < 0.001). Children who were underweight spent significantly more time sitting compared with their overweight peers (52.4% vs 46.8%; P = 0.003). 56% and 16% of children met the IOM SB and PA recommendations, respectively. Girls (odds ratio [OR]; 95%CI = 0.26; 0.13 to 0.55) and preschoolers (0.16; 0.07 to 0.38) were less likely to meet the IOM PA recommendation compared to boys and toddlers. Young children spent ~ 50% of their time at childcare sitting. Girls and preschoolers sit more and are less likely to meet PA recommendations, making them important groups to target in future interventions.

Determinants of changes in sedentary time and breaks in sedentary time among 9 and 12 year old children

The current study aimed to identify the determinants of objectively measured changes in sedentary time and sedentary fragmentation from age 9- to age 12 years. Data were collected as part of the Gateshead Millennium Birth Cohort study from September 2008 to August 2009 and from January 2012 to November 2012. Participants were 9.3 (± 0.4) years at baseline (n = 508) and 12.5 (± 0.3) years at follow-up (n = 427). Sedentary behaviour was measured using an ActiGraph GT1M accelerometer. Twenty potential determinants were measured, within a socio-ecological model, and tested for their association with changes in sedentary time and the extent to which sedentary behaviour is prolonged or interrupted (fragmentation index). Univariate and multivariate linear regression analyses were conducted. Measurements taken during winter and a greater decrease in moderate-to-vigorous intensity physical activity (MVPA) over time were associated with larger increases in sedentary time (seasonality β: − 3.03; 95% CI: − 4.52, − 1.54; and change in MVPA β: − 1.68; 95% CI: − 1.94, − 1.41). Attendance at sport clubs was associated with smaller increases in sedentary time (− 1.99; − 3.44, − 0.54). Girls showed larger decreases in fragmentation index (− 0.52; − 1.01, − 0.02). Interventions aimed at decreasing the decline in MVPA and increasing/maintaining sport club attendance may prevent the rise in sedentary time as children grow older. In addition, winter could be targeted to prevent an increase in sedentary time and reduction in sedentary fragmentation during this season.

Practical utility and reliability of whole-room calorimetry in young children

The use of whole-room calorimetry (WRC) in young children can increase our understanding of childrens energy balance. However, studies using WRC in young children are rare due to concerns about its feasibility. To assess the feasibility of WRC in young children, forty children, aged 4–6 years, were asked to follow a graded activity protocol while in a WRC. In addition, six children participated in two additional resting protocols to examine the effect of diet-induced thermogenesis on resting energy expenditure (REE) measures and the reliability of REE measurement. Refusals to participate and data loss were quantified as measures of practical utility, and REE measured after an overnight fast and after a 90-min fast were compared. In addition, both were compared to predicted BMR values using the Schofield equation. Our results showed that thirty (78·9 %) participants had acceptable data for all intensities of the activity protocol. The REE values measured after a 90-min fast (5·07 (SD 1·04) MJ/d) and an overnight fast (4·73 (SD 0·61) MJ/d) were not significantly different from each other (P= 0·472). However, both REE after an overnight fast and a 90-min fast were significantly higher than predicted BMR (3·96 (SD 0·18) MJ/d) using the Schofield equation (P= 0·024 and 0·042, respectively). We conclude that, with a developmentally sensitive approach, WRC is feasible and can be standardised adequately even in 4- to 6-year-old children. In addition, the effect of a small standardised breakfast, approximately 90 min before REE measurements, is likely to be small.

Promoting physical activity among adolescent girls: the Girls in Sport group randomized trial

BackgroundSlowing the decline in participation in physical activity among adolescent girls is a public health priority. This study reports the outcomes from a multi-component school-based intervention (Girls in Sport), focused on promoting physical activity among adolescent girls.MethodsGroup randomized controlled trial in 24 secondary schools (12 intervention and 12 control). Assessments were conducted at baseline (2009) and at 18 months post-baseline (2010). The setting was secondary schools in urban, regional and rural areas of New South Wales, Australia. All girls in Grade 8 in 2009 who attended these schools were invited to participate in the study (N = 1769). Using a Health Promoting Schools and Action Learning Frameworks, each school formed a committee and developed an action plan for promoting physical activity among Grade 8 girls. The action plan incorporated strategies in three main areas – i) the formal curriculum, ii) school environment, and iii) home/school/community links – based on the results of formative data from target girls and staff and on individual needs of the school. A member of the research team supported each school throughout the intervention. The main outcome measure was accelerometer-derived total physical activity (TPA) spent in physical activity. Data were analyzed from December 2011 to March 2012.Results1518 girls (mean age 13.6y ±0.02) were assessed at baseline. There was a significant decline in TPA from baseline to 18-month follow-up with no differences between girls in the intervention and control schools. Only one-third of schools (4/12) implemented the intervention as per their action plan. Per-protocol analyses on these schools revealed a smaller decline in percentage of time spent in MVPA among girls in the intervention group (adjusted difference 0.5%, 95% CI = -0.01, 0.99, P = 0.05).ConclusionsThe Girls in Sport intervention was not effective in reducing the decline in physical activity among adolescent girls. Lack of implementation by most intervention schools was the main reason for a null effect. Identifying strategies to enhance implementation levels is critical to determining the true potential of this intervention approach.Trial registrationThis study was retrospectively registered with the Australian New Zealand Clinical Trials Registry ACTRN12610001077055.Date of registration: 7 December 2010.