Wear compliance, sedentary behaviour and activity in free-living children from hip-and wrist-mounted ActiGraph GT3X+ accelerometers

McLellan, Gillian; Arthur, Rosemary; Buchan, Duncan S.

doi:10.1080/02640414.2018.1461322

Cited by 42 publications

(37 citation statements)

References 34 publications

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“…Nonetheless, the proliferation of physical activity studies using wrist-worn accelerometers is indicative of a major shift in the field, potentially driven by the desire to obtain reliable 24 h behavioural profiles including accurate sleep data. Indeed, there is a current movement to develop and test algorithms for the detection of sedentary behaviours using wrist-worn accelerometers [ 28 , 29 ]. A three-unit AX3 system, integrating wrist, back, and thigh motion detection, may enable even more complex physical activity recognition and sleep characterisation; however, the ideal combination of sensors for assessing specific behaviours requires further investigation.…”

Section: Discussionmentioning

confidence: 99%

Wear-Time Compliance with a Dual-Accelerometer System for Capturing 24-h Behavioural Profiles in Children and Adults

Duncan

Mackay

Neville

et al. 2018

IJERPH

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To advance the field of time-use epidemiology, a tool capable of monitoring 24 h movement behaviours including sleep, physical activity, and sedentary behaviour is needed. This study explores compliance with a novel dual-accelerometer system for capturing 24 h movement patterns in two free-living samples of children and adults. A total of 103 children aged 8 years and 83 adults aged 20-60 years were recruited. Using a combination of medical dressing and purpose-built foam pouches, participants were fitted with two Axivity AX3 accelerometers—one to the thigh and the other to the lower back—for seven 24 h periods. AX3 accelerometers contain an inbuilt skin temperature sensor that facilitates wear time estimation. The median (IQR) wear time in children was 160 (67) h and 165 (79) h (out of a maximum of 168 h) for back and thigh placement, respectively. Wear time was significantly higher and less variable in adults, with a median (IQR) for back and thigh placement of 168 (1) and 168 (0) h. A greater proportion of adults (71.6%) achieved the maximum number of complete days when compared to children (41.7%). We conclude that a dual-accelerometer protocol using skin attachment methods holds considerable promise for monitoring 24-h movement behaviours in both children and adults.

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Section: Discussionmentioning

confidence: 99%

Wear-Time Compliance with a Dual-Accelerometer System for Capturing 24-h Behavioural Profiles in Children and Adults

Duncan

Mackay

Neville

et al. 2018

IJERPH

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“…With more varying everyday activities, the explained variance is exceptionally low with the wrist placement at 0.033 compared to 0.32 with the hip . In a free‐living setting, there is a strong correlation between MVPA estimated from the hip and the wrist ( r = 0.80–0.84) , but the correlation is much weaker between these positions regarding LPA ( r = 0.18–0.63) . Overall, more physical activity across all intensities and less SED is recorded with wrist placement .…”

Section: Section 1: Backgroundmentioning

confidence: 95%

“…In a free-living setting, there is a strong correlation between MVPA estimated from the hip and the wrist (r = 0.80-0.84) [55,56,61,62], but the correlation is much weaker between these positions regarding LPA (r = 0.18-0.63) [57,61,62]. Overall, more physical activity across all intensities and less SED is recorded with wrist placement [56,57,61]. The difference between the placements is larger at LPA [57,61] and has been shown to be the largest during school hours [61].…”

Section: Accelerometer Body Locationmentioning

confidence: 98%

“…Overall, more physical activity across all intensities and less SED is recorded with wrist placement [56,57,61]. The difference between the placements is larger at LPA [57,61] and has been shown to be the largest during school hours [61]. This suggests that sedentary activities involving movement of the upper extremities is misclassified by an accelerometer at the wrist because of the movement of the hip and wrist is being decoupled [61].…”

Section: Accelerometer Body Locationmentioning

confidence: 99%

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Measurement of physical activity in clinical practice using accelerometers

2019

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Accelerometers are commonly used in clinical and epidemiological research for more detailed measures of physical activity and to target the limitations of self‐report methods. Sensors are attached at the hip, wrist and thigh, and the acceleration data are processed and calibrated in different ways to determine activity intensity, body position and/or activity type. Simple linear modelling can be used to assess activity intensity from hip and thigh data, whilst more advanced machine‐learning modelling is to prefer for the wrist. The thigh position is most optimal to assess body position and activity type using machine‐learning modelling. Frequency filtering and measurement resolution needs to be considered for correct assessment of activity intensity. Simple physical activity measures and statistical methods are mostly used to investigate relationship with health, but do not take advantage of all information provided by accelerometers and do not consider all components of the physical activity behaviour and their interrelationships. More advanced statistical methods are suggested that analyse patterns of multiple measures of physical activity to demonstrate stronger and more specific relationships with health. However, evaluations of accelerometer methods show considerable measurement errors, especially at individual level, which interferes with their use in clinical research and practice. Therefore, better objective methods are needed with improved data processing and calibration techniques, exploring both simple linear and machine‐learning alternatives. Development and implementation of accelerometer methods into clinical research and practice requires interdisciplinary collaboration to cover all aspects contributing to useful and accurate measures of physical activity behaviours related to health.

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“…Wrist-worn monitors are easier to wear and may increase compliance. 108 At the outset of this study, wrist-worn accelerometry was evolving and we wished to use an established technology so that we could relate the findings to other studies. Research suggests that the results from wrist-worn accelerometers differ from waist-worn accelerometers, with the wrist attachment producing a higher average step count than the waist attachment in free-living conditions.…”

Section: Measuring Physical Activitymentioning

confidence: 99%

A workplace-based intervention to increase levels of daily physical activity: the Travel to Work cluster RCT

et al. 2019

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Background There may be opportunities for working adults to accumulate recommended physical activity levels (≥ 150 minutes of moderate-intensity physical activity in bouts of ≥ 10 minutes throughout the week) during the commute to work. Systematic reviews of interventions to increase active transport indicate that studies are predominantly of poor quality, rely on self-report and lack robust statistical analyses. Objectives To assess the effectiveness, cost and consequences of a behavioural intervention to increase walking during the commute to work. Design A multicentre, parallel-arm, cluster randomised controlled trial incorporating economic and process evaluations. Physical activity outcomes were measured using accelerometers and GPS (Global Positioning System) receivers at baseline and the 12-month follow-up. Setting Workplaces in seven urban areas in south-west England and south Wales. Participants Employees (n = 654) in 87 workplaces. Interventions Workplace-based Walk to Work promoters were trained to implement a 10-week intervention incorporating key behaviour change techniques. Main outcome measures The primary outcome was the daily number of minutes of moderate to vigorous physical activity (MVPA). Secondary outcomes included MVPA during the commute, overall levels of physical activity and modal shift (from private car to walking). Cost–consequences analysis included employer, employee and health service costs and consequences. Process outcomes included barriers to, and facilitators of, walking during the daily commute. Results There was no evidence of an intervention effect on MVPA at the 12-month follow-up [adjusted difference in means 0.3 minutes, 95% confidence interval (CI) –5.3 to 5.9 minutes]. The intervention cost was on average, £181.97 per workplace and £24.19 per participating employee. In comparison with car users [mean 7.3 minutes, standard deviation (SD) 7.6 minutes], walkers (mean 34.3 minutes, SD 18.6 minutes) and public transport users (mean 25.7 minutes, SD 14.0 minutes) accrued substantially higher levels of daily MVPA during the commute. Participants who walked for ≥ 10 minutes during their commute were more likely to have a shorter commute distance (p < 0.001). No access to a car (p < 0.001) and absence of free workplace car parking (p < 0.01) were independently related to walking to work and using public transport. Higher quality-of-life scores were observed for the intervention group in a repeated-measures analysis (mean 0.018, 95% CI 0.000 to 0.036; scores anchored at 0 indicated ‘no capability’ and scores anchored at 1 indicated ‘full capability’). Conclusions Although this research showed that walking to work and using public transport are important contributors to physical activity levels in a working population, the behavioural intervention was insufficient to change travel behaviour. Broader contextual factors, such as length of journey, commuting options and availability of car parking, may influence the effectiveness of behavioural interventions to change travel behaviour. Further analyses of statistical and qualitative data could focus on physical activity and travel mode and the wider determinants of workplace travel behaviour. Trial registration Current Controlled Trials ISRCTN15009100. Funding This project was funded by the National Institute for Health Research (NIHR) Public Health Research programme and will be published in full in Public Health Research; Vol. 7, No. 11. See the NIHR Journals Library website for further project information. Living Streets, a UK charity promoting everyday walking, provided funding for the intervention booklets and free pedometers for distribution to participants in the intervention group.

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Wear compliance, sedentary behaviour and activity in free-living children from hip-and wrist-mounted ActiGraph GT3X+ accelerometers

Cited by 42 publications

References 34 publications

Wear-Time Compliance with a Dual-Accelerometer System for Capturing 24-h Behavioural Profiles in Children and Adults

Wear-Time Compliance with a Dual-Accelerometer System for Capturing 24-h Behavioural Profiles in Children and Adults

Measurement of physical activity in clinical practice using accelerometers

A workplace-based intervention to increase levels of daily physical activity: the Travel to Work cluster RCT

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