Comparison of intensity-based cut-points for the RT3 accelerometer in youth

Association of accelerometer-measured physical activity and its change with progression to chronic kidney disease in adults with type 2 diabetes and overweight/obesity

OBJECTIVE

To examine the long-term association of objectively measured moderate-to-vigorous physical activity (MVPA) and its longitudinal changes with progression to chronic kidney disease (CKD) in patients with type 2 diabetes (T2D) and overweight/obesity.

METHODS

This study included 1746 participants in the Look AHEAD trial with baseline estimated glomerular filtration rate (eGFR)≥60 mL/min/1.73 m2. MVPA was measured at baseline, year 1, year 4 and year 8 using an RT3 accelerometer. The outcome was progression to CKD, defined as eGFR<60 mL/min per 1.73 m2 with a drop of ≥30% or end-stage kidney disease. Cox hazards models were fitted to examine the association between MVPA and outcomes.

RESULTS

Over a median follow-up of 12.0 years, 567 participants experienced progression to CKD. Overall, there was a linear inverse association of cumulative average total MVPA (per 100 min/week higher amount, HR: 0.91; 95% CI: 0.86 to 0.96) and MVPA accumulated in bouts of ≥10 min (per 100 minutes/week higher amount, HR: 0.81; 95% CI: 0.72 to 0.91) with progression to CKD. Moreover, an increase in total MVPA from baseline to year 4 (the fourth quartile, ≥63.2 min/week) was associated with a 33% lower risk of progression to CKD compared with the largest MVPA reduction (the first quartile, <-198.3 min/week). A lower risk of progression to CKD was also observed for increases in MVPA accumulated in bouts of both <10 min and ≥10 min.

CONCLUSIONS

Longer MVPA time and increases in MVPA was associated with a reduced risk of progression to CKD in adults with overweight/obesity and T2D.

Utility of the Actiwatch Spectrum Plus for detecting the outdoor environment and physical activity in children

PURPOSE

To describe the performance of the Actiwatch Spectrum Plus (Philips, Respironics) for determining real world indoor and outdoor environments and physical activity in children.

METHODS

Children wore the device while performing 10 different activities, ranging from sedentary to vigorous physical-activity, and under different indoor and outdoor conditions. Repeated measures ANOVA was implemented via mixed effects modeling to determine illuminance (lux) and physical activity (counts per 15 s, CP15) across conditions. Receiver operator characteristics (ROC) analysis assessed the accuracy to detect indoor versus outdoor settings.

RESULTS

Illuminance was found to be statistically different across indoor (793 ± 348 lux) and outdoor (4,413 ± 518 lux) conditions (P<.0001), with excellent diagnostic accuracy to detect indoor versus outdoor settings (Area under the ROC Curve, AUC 0.94); 1088 lux was identified as the optimal threshold for outdoor illuminance (sensitivity: 93.0%; specificity: 85.0%). Using published activity ranges, we found that when children were sitting, 94% of the physical-activity readings were classified as sedentary or light. When children were walking, 88% of readings were classified as light, and when children were running, 77% of readings were classified as moderate or vigorous.

CONCLUSION

The Actiwatch Spectrum Plus performed well during real world activities in children, showing excellent diagnostic accuracy at 1088 lux as a threshold to detect indoor versus outdoor environments and in categorizing physical activity.

Device-based measurement of physical activity in pre-schoolers: Comparison of machine learning and cut point methods

INTRODUCTION

Machine learning (ML) accelerometer data processing methods have potential to improve the accuracy of device-based assessments of physical activity (PA) in young children. Yet the uptake of ML methods by health researchers has been minimal and the use of cut-points (CP) continues to be the norm, despite evidence of significant misclassification error. The lack of studies demonstrating a relative advantage for ML approaches over CP methods maybe a key contributing factor.

PURPOSE

The current study compared the accuracy of PA intensity predictions provided by ML classification models and previously published CPs for preschool-aged children.

METHODS

In a free-living study, 31 preschool-aged children (mean age = 4.0 ± 0.9 y) wore wrist and hip ActiGraph GT3X+ accelerometers while completing a video recorded 20-minute free play session. Ground truth PA intensity was coded continuously using the Children's Activity Rating Scale (CARS). Accelerometer data was classified as sedentary (SED), light intensity (LPA), or moderate-to-vigorous intensity (MVPA) using ML random forest PA classifiers and published CPs for preschool-aged children. Performance differences were evaluated in a hold-out sample by comparing weighted kappa statistics, classification accuracy for each intensity band, and equivalence testing.

RESULTS

ML classification models (hip: κ = 0.76; wrist: κ = 0.72) exhibited significantly higher agreement with ground truth PA intensity than CP methods (hip: κ = 0.38-0.49; wrist: κ = 0.31-0.44). For the ML models, classification accuracy for SED and LPA ranged from 83% - 88%, while classification accuracy for MVPA ranged from 68% - 78%. For the CP's, classification accuracy ranged from 50% - 94% for SED, 19% - 75% for LPA, and 44% - 76.1% for MVPA. ML classification models showed equivalence (within ± 0.5 SD) with directly observed time in SED, LPA, and MVPA. None of the CP's exhibited evidence of equivalence.

CONCLUSIONS

Under free living conditions, ML classification models for hip or wrist accelerometer data provide more accurate assessments of PA intensity in young children than CP methods. The results demonstrate the relative advantage of ML methods over threshold-based approaches and adds to a growing evidence base supporting the feasibility and accuracy of ML accelerometer data processing methods.

Objectively measured sedentary behaviour in overweight and obese prepubertal children: challenging the school

Sedentary lifestyle is associated with unfavourable health outcomes; however, few studies have analysed the daily fluctuations of sedentary behaviour in children. The aim was to characterise sedentary behaviour in low active, overweight/obese prepubertal children and to examine whether there were daily, age- or gender-based differences. In this observational study free-living movement was measured by accelerometry for one week. Eighty-eight low active, overweight/obese children (8- to 12-year-olds) were included. Analysis was conducted for weekends, weekdays, school time and non-school time on weekdays. Participants spent half of their waking hours engaged in sedentary behaviour (48.1%). Short sedentary bouts (1-4 min) accounted for 86% of sedentary time. Sedentary time was similar on weekends and non-school time, while it was highest during school time. Interventions for the management of childhood obesity should include strategies for shifting sedentary time to physical activity on weekends and non-school time and implementing more activity-permissive classroom lessons.

Validity of Accelerometry to Measure Physical Activity Intensity in Children With an Acquired Brain Injury

PURPOSE

To evaluate the validity of the ActiGraph accelerometer (AG) to differentiate between standardized, physical activity tasks using oxygen consumption ((Equation is included in full-text article.)O2) as the criterion measure in children and adolescents with an acquired brain injury; to determine vector magnitude activity intensity cut-points; to compare performance of cut-points to previously published cut-points.

METHODS

Twenty-seven children performed standardized walking and stepping activities wearing a portable indirect calorimeter, AG, and heart rate monitor. Differences in (Equation is included in full-text article.)O2 and AG vector magnitude activity counts were measured during activities. Receiver operating characteristic curves were determined for intensity cut-points.

RESULTS

(Equation is included in full-text article.)O2 and AG activity counts significantly increased as walking speed increased. Discrimination of the newly derived cut-points was excellent and demonstrated greater agreement compared with the previously published cut-points.

CONCLUSION

Output from accelerometers can differentiate physical activity intensity in children with an acquired brain injury. Future studies can apply these cut-points to evaluate physical activity performance.

Comparison of Patterns of Physical Activity and Sedentary Behavior Between Children With Cerebral Palsy and Children With Typical Development

BACKGROUND

Reduced participation in physical activity and increased time spent in sedentary behavior are associated with overweight, chronic disease, and disability. In order to optimize recommendations and interventions to increase physical activity and reduce sedentary behavior in children with cerebral palsy (CP), knowledge of their physical activity and sedentary behavior is needed.

OBJECTIVES

The aim of this study was to describe light, moderate, and vigorous physical activity and sedentary behavior in preadolescent children with and without CP and compare physical activity and sedentary behavior between the 2 groups.

DESIGN

This was a cross-sectional study of 33 children, aged 6 to 10 years, with CP (Gross Motor Function Classification System [GMFCS] levels I-III) and 33 age- and sex-matched children with typical development.

METHODS

Physical activity was measured using the RT3 accelerometer over 7 days.

RESULTS

Children with CP spent more time in sedentary behavior and accumulated less total activity, moderate activity, vigorous activity, and sustained bouts of moderate-to-vigorous activity (MVPA). They also accumulated a fewer number of bouts of MVPA and vigorous activity, despite spending a similar amount of time in each bout.

LIMITATIONS

The small number of children in GMFCS levels II and III did not allow for adjustment for GMFCS level when comparing physical activity between children with and without CP.

CONCLUSIONS

Preadolescent children with CP spent less time in moderate and vigorous activity and more time in sedentary behavior than children with typical development. Children with CP also accumulated less continuous MVPA and vigorous activity as a result of achieving fewer sustained bouts of MVPA and vigorous activity throughout the day.