Evaluation of Wrist Accelerometer Cut-Points for Classifying Physical Activity Intensity in Youth

Association of Recess Provision With Accelerometer-Measured Physical Activity and Sedentary Time in a Representative Sample of 6- to 11-Year-Old Children in the United States

PURPOSE

To assess the association between the amount of recess provision and children's accelerometer-measured physical activity (PA) levels.

METHODS

Parents/guardians of 6- to 11-year-olds (n = 451) in the 2012 National Youth Fitness Survey reported recess provision, categorized as low (10-15 min; 31.9%), medium (16-30 min; 48.0%), or high (>30 min; 20.1%). Children wore a wrist-worn accelerometer for 7 days to estimate time spent sedentary, in light PA, and in moderate to vigorous PA using 2 different cut points for either activity counts or raw acceleration. Outcomes were compared between levels of recess provision while adjusting for covariates and the survey's multistage, probability sampling design.

RESULTS

Children with high recess provision spent less time sedentary, irrespective of type of day (week vs weekend) and engaged in more light or moderate to vigorous PA on weekdays than those with low recess provision. The magnitude and statistical significance of effects differed based on the cut points used to classify PA (eg, 4.7 vs 11.9 additional min·d-1 of moderate to vigorous PA).

CONCLUSIONS

Providing children with >30 minutes of daily recess, which exceeds current recommendations of ≥20 minutes, is associated with more favorable PA levels and not just on school days. Identifying the optimal method for analyzing wrist-worn accelerometer data could clarify the magnitude of this effect.

Emerging methods for measuring physical activity using accelerometry in children and adolescents with neuromotor disorders: a narrative review

BACKGROUND

Children and adolescents with neuromotor disorders need regular physical activity to maintain optimal health and functional independence throughout their development. To this end, reliable measures of physical activity are integral to both assessing habitual physical activity and testing the efficacy of the many interventions designed to increase physical activity in these children. Wearable accelerometers have been used for children with neuromotor disorders for decades; however, studies most often use disorder-specific cut points to categorize physical activity intensity, which lack generalizability to a free-living environment. No reviews of accelerometer data processing methods have discussed the novel use of machine learning techniques for monitoring physical activity in children with neuromotor disorders.

METHODS

In this narrative review, we discuss traditional measures of physical activity (including questionnaires and objective accelerometry measures), the limitations of standard analysis for accelerometry in this unique population, and the potential benefits of applying machine learning approaches. We also provide recommendations for using machine learning approaches to monitor physical activity.

CONCLUSIONS

While wearable accelerometers provided a much-needed method to quantify physical activity, standard cut point analyses have limitations in children with neuromotor disorders. Machine learning models are a more robust method of analyzing accelerometer data in pediatric neuromotor disorders and using these methods over disorder-specific cut points is likely to improve accuracy of classifying both type and intensity of physical activity. Notably, there remains a critical need for further development of classifiers for children with more severe motor impairments, preschool aged children, and children in hospital settings.

Calibration and validation of physical behaviour cut-points using wrist-worn ActiGraphs for children and adolescents: A systematic review

OBJECTIVES

To review cut-points calibrated and independently validated from wrist-worn ActiGraph accelerometers to measure moderate to vigorous physical activity (MVPA) and time spent sedentary (SED) in children and adolescents.

DESIGN

Systematic literature review.

METHODS

Five databases were searched for relevant cut-point calibration and independent validation studies relating to wrist worn ActiGraphs in children and adolescents from inception through 30 April 2022. Extracted data included: country of publication; study name; population; device model; wear location; sampling frequency; epoch length; activity protocol; criterion method and definitions used to classify PA intensity; statistical methods for calibration; statistical methods for validation/cross-validation; and MVPA and SED outcome.

RESULTS

Fourteen calibration studies and seven independent validation studies were identified. Calibrated cut-points for MVPA vector magnitude counts ranged from 7065 to 9204 counts per minute (cpm) and 63.5 to 201 milli-gravitational units (mg). For SED, calibrated cut-points ranged from <2556 cpm to 4350 cpm and 30.8 to 48.1 mg. Classification accuracy values determined by independent validation studies varied, with kappa values ranging from 0.31 to 0.60 and area under the curve statistics ranging from 0.51 to 0.84 for MVPA and kappa values ranging from 0.31 to 0.44 and area under the curve statistics ranging from 0.70 to 0.85 for SED.

CONCLUSIONS

The results of this systematic literature review support the use of the Crouter and colleagues cut-points for the measurement of MVPA and SED for children and adolescents aged 6-12 years. Further work is required to independently validate cut-points developed in younger children and older adolescents.

A natural experiment to assess recess frequency on children's physical activity in Arizona (U.S.) elementary schools

BACKGROUND

In the United States, the number of state policies mandating recess in schools has rapidly increased over the past decade; however, few policies specify recess frequency. Informed by an ecological model of physical activity (PA) policy, this study examined and compared total amounts and intensity of PA expended during recess among children attending schools in compliance with Arizona recess policy ARS§ 15-118 mandating 2 + daily recess periods versus not.

METHODS

PA during recess was measured among grade three children (ages 8-10) in four randomly selected elementary schools (two complying averaging 30 daily recess minutes; two non-complying averaging 15 daily recess minutes) in Maricopa County, Arizona. Group-level PA was assessed by direct observation using the System for Observing Play and Leisure (137 observations). A subset of students (N = 134) from all schools wore ActiGraph GT3X + devices during recess to measure individual PA. General linear mixed effects models were used to analyze the impact of recess frequency on group and individual PA during recess.

RESULTS

Students attending complying schools spent significantly greater proportions of time in moderate-to-vigorous PA (MVPA) based on direct observation (5%) and accelerometry (15%) and less time being sedentary based on accelerometry (14%) during recess. Across the school day, this would equate to 5.1 more MVPA minutes based on systematic direct observation and 9.5 more MVPA minutes based on accelerometry, and 4.1 less minutes being sedentary based on accelerometry if students received two daily 15-minute recess periods compared to one.

CONCLUSIONS

Students attending elementary schools implementing 2 + recesses, in accordance with state policy, demonstrated greater MVPA and less sedentary time, providing preliminary evidence that recess frequency is associated with greater PA intensity among children during recess. Schools that adhere to state-level PA policies may provide a more supportive environment for PA, resulting in increased movement among students. Specifying recess frequency should be considered in statewide recess policy.

The effects of active classroom breaks on moderate to vigorous physical activity, behaviour and performance in a Northern NSW primary school: A quasi-experimental study

ISSUE ADDRESSED

Approximately 77% of NSW children aged 5 to 15 years do not meet physical activity guidelines and many spend a considerable amount of time sitting. Active breaks at primary school are feasible, may increase daily moderate to vigorous physical activity (MVPA) and decrease off-task behaviour without adversely affecting cognitive function and learning.

METHODS

In this quasi-experimental study, 101 primary school children in six intervention classrooms participated in three 10-minute active breaks per day for six-weeks during class time, while five control classrooms were run as usual (n = 89). Physical activity levels were measured using wrist-worn Actigraph wGT3X-BT accelerometers and analysed using a random forest model. Students' off-task behaviour, wellbeing, cognitive function and maths performance were also measured. School staff completed a brief feedback survey.

RESULTS

Children in the intervention group engaged in 15.4 and 10.9 minutes more MVPA per day at 3 and 6 weeks respectively (P < .001). Participation significantly increased the proportion of children who met the Australian 24-Hour Movement Guidelines (P < .001). At pre, middle and end of intervention, 44.4%, 60.8% and 55.1% of intervention children and 46.5%, 45.9% and 45.8% of controls met the guidelines. Significantly fewer students engaged in off-task behaviour in the intervention classes at mid and final weeks of intervention (-1.4 students, P = .003). No significant intervention effects were found for wellbeing, cognitive and maths performance.

CONCLUSIONS

Active classroom breaks are an effective way to increase physical activity among primary school children while reducing off-task classroom behaviour. SO WHAT?: Primary school students' health would benefit from active breaks with no detrimental effects on wellbeing, maths and cognitive performance.

Healthy weight and overweight adolescents with type 1 diabetes mellitus do not meet recommendations for daily physical activity and sleep

AIMS

Physical activity (PA) plays an important role in the prevention of cardiovascular disease (CVD), particularly in individuals with type 1 diabetes mellitus (T1DM) who are at increased risk. Our aim was to determine levels of moderate-to-vigorous physical activity (MVPA), sedentary behaviour and sleep in adolescents with T1DM, and identify barriers to PA.

METHODS

Participants aged 12-18 with T1DM wore an accelerometer and continuous glucose monitor for 24 h over 7-days. Data was processed into PA metrics and sleep. Pearson correlations were used to test associations between MVPA and metabolic measures. Barriers to PA were measured using a questionnaire.

RESULTS

Thirty-seven adolescents provided valid accelerometer data. Mean daily MVPA was 44.0 min [SD 17.6] with 16.2% achieving the guideline of ≥ 60 min/day. Participants had 11 h [SD 1.2] of sedentary behaviour and 7.6 h [SD 1.5] of sleep/day. There was no difference in MVPA in overweight or obese (53.8%) vs. healthy weight (44.2%) adolescents (45.0 min [SD 16.6] vs. 43.1 min [SD 18.8]). Only 39.6% reported one or more diabetes specific barrier to PA.

CONCLUSION

Adolescents with T1DM engage in insufficient MVPA and sleep, irrespective of body weight status, suggesting the need for targeted interventions.

Establishing Accelerometer Cut-Points to Classify Walking Speed in People Post Stroke

While accelerometers could be used to monitor important domains of walking in daily living (e.g., walking speed), the interpretation of accelerometer data often relies on validation studies performed with healthy participants. The aim of this study was to develop cut-points for waist- and ankle-worn accelerometers to differentiate non-ambulation from walking and different walking speeds in people post stroke. Forty-two post-stroke persons wore waist and ankle accelerometers (ActiGraph GT3x+, AG) while performing three non-ambulation activities (i.e., sitting, setting the table and washing dishes) and while walking in self-selected and brisk speeds. Receiver operating characteristic (ROC) curve analysis was used to define AG cut-points for non-ambulation and different walking speeds (0.41−0.8 m/s, 0.81−1.2 m/s and >1.2 m/s) by considering sensor placement, axis, filter setting and epoch length. Optimal data input and sensor placements for measuring walking were a vector magnitude at 15 s epochs for waist- and ankle-worn AG accelerometers, respectively. Across all speed categories, cut-point classification accuracy was good-to-excellent for the ankle-worn AG accelerometer and fair-to-excellent for the waist-worn AG accelerometer, except for between 0.81 and 1.2 m/s. These cut-points can be used for investigating the link between walking and health outcomes in people post stroke.