Reference values for wrist-worn accelerometer physical activity metrics in England children and adolescents

A comparative analysis of 24-hour movement behaviors features using different accelerometer metrics in adults: Implications for guideline compliance and associations with cardiometabolic health

BACKGROUND

Movement behavior features such as time use estimates, average acceleration and intensity gradient are crucial in understanding associations with cardiometabolic health. The aim of this study was to 1) compare movement behavior features processed by commonly used accelerometer metrics among adults (i.e. Euclidian Norm Minus One (ENMO), Mean Amplitude Deviation (MAD) and counts per minute (CPM)), 2) investigate the impact of accelerometer metrics on compliance with movement behavior guidelines, and 3) explore potential variations in the association between movement behavior features and cardiometabolic variables depending on the chosen metric.

METHODS

This cross-sectional study collected movement behavior features (Actigraph GT3X+) and cardiometabolic variables. Accelerometer data were analyzed by four metrics, i.e. ENMO, MAD, and CPM vertical axis and CPM vector magnitude (GGIR). Intraclass correlations and Bland‒Altman plots identified metric differences for time use in single movement behaviors (physical activity, sedentary behavior), average acceleration and intensity gradient. Regression models across the four metrics were used to explore differences in 24-hour movement behaviors (24h-MBs; compositional variable) as for exploration of associations with cardiometabolic variables.

RESULTS

Movement behavior data from 213 Belgian adults (mean age 45.8±10.8 years, 68.5% female) differed according to the metric used, with ENMO representing the most sedentary movement behavior profile and CPM vector magnitude representing the most active profile. Compliance rates for meeting integrated 24h-MBs guidelines varied from 0-25% depending on the metric used. Furthermore, the strength and direction of associations between movement behavior features and cardiometabolic variables (body mass index, waist circumference, fat% and HbA1c) differed by the choice of metric.

CONCLUSION

The metric used during data processing markedly influenced cut-point dependent time use estimates and cut-point independent average acceleration and intensity gradient, impacting guideline compliance and associations with cardiometabolic variables. Consideration is necessary when comparing findings from accelerometry studies to inform public health guidelines.

Data Analytics in Physical Activity Studies With Accelerometers: Scoping Review

BACKGROUND

Monitoring free-living physical activity (PA) through wearable devices enables the real-time assessment of activity features associated with health outcomes and provision of treatment recommendations and adjustments. The conclusions of studies on PA and health depend crucially on reliable statistical analyses of digital data. Data analytics, however, are challenging due to the various metrics adopted for measuring PA, different aims of studies, and complex temporal variations within variables. The application, interpretation, and appropriateness of these analytical tools have yet to be summarized.

OBJECTIVE

This research aimed to review studies that used analytical methods for analyzing PA monitored by accelerometers. Specifically, this review addressed three questions: (1) What metrics are used to describe an individual's free-living daily PA? (2) What are the current analytical tools for analyzing PA data, particularly under the aims of classification, association with health outcomes, and prediction of health events? and (3) What challenges exist in the analyses, and what recommendations for future research are suggested regarding the use of statistical methods in various research tasks?

METHODS

This scoping review was conducted following an existing framework to map research studies by exploring the information about PA. Three databases, PubMed, IEEE Xplore, and the ACM Digital Library, were searched in February 2024 to identify related publications. Eligible articles were classification, association, or prediction studies involving human PA monitored through wearable accelerometers.

RESULTS

After screening 1312 articles, 428 (32.62%) eligible studies were identified and categorized into at least 1 of the following 3 thematic categories: classification (75/428, 17.5%), association (342/428, 79.9%), and prediction (32/428, 7.5%). Most articles (414/428, 96.7%) derived PA variables from 3D acceleration, rather than 1D acceleration. All eligible articles (428/428, 100%) considered PA metrics represented in the time domain, while a small fraction (16/428, 3.7%) also considered PA metrics in the frequency domain. The number of studies evaluating the influence of PA on health conditions has increased greatly. Among the studies in our review, regression-type models were the most prevalent (373/428, 87.1%). The machine learning approach for classification research is also gaining popularity (32/75, 43%). In addition to summary statistics of PA, several recent studies used tools to incorporate PA trajectories and account for temporal patterns, including longitudinal data analysis with repeated PA measurements and functional data analysis with PA as a continuum for time-varying association (68/428, 15.9%).

CONCLUSIONS

Summary metrics can quickly provide descriptions of the strength, frequency, and duration of individuals' overall PA. When the distribution and profile of PA need to be evaluated or detected, considering PA metrics as longitudinal or functional data can provide detailed information and improve the understanding of the role PA plays in health. Depending on the research goal, appropriate analytical tools can ensure the reliability of the scientific findings.

Enhancing clinical and public health interpretation of accelerometer-assessed physical activity with age-referenced values based on UK Biobank data

BACKGROUND

Higher accelerometer-assessed volume and intensity of physical activity (PA) have been associated with a longer life expectancy but can be difficult to translate into recommended doses of PA. We aimed to: (a) improve interpretability by producing UK Biobank age-referenced centiles for PA volume and intensity; (b) inform public-health messaging by examining how adding recommended quantities of moderate and vigorous PA affect PA volume and intensity.

METHODS

92,480 UK Biobank participants aged 43-80 years with wrist-worn accelerometer data were included. Average acceleration and intensity gradient were derived as proxies for PA volume and intensity. We generated sex-specific centile curves using Generalized Additive Models for Location Scale and Shape (GAMLSS) and modeled the effect of adding moderate (walking) or vigorous (running) activity on the combined change in the volume and intensity centiles (change in PA profile).

RESULTS

In men, volume was lower as age increased while intensity was lower after age 55; in women, both volume and intensity were lower as age increased. Adding 150 min of moderate PA weekly (5 × 30 min walking) increased the PA profile by 4 percentage points. Defining moderate PA as brisk walking approximately doubled the increase (9 percentage points) while 75 min of vigorous PA weekly (5 × 15 min running) trebled the increase (13 percentage points).

CONCLUSION

These UK Biobank reference centiles provide a benchmark for interpretation of accelerometer data. Application of our translational methods demonstrate that meeting PA guidelines through shorter duration vigorous activity is more beneficial to the PA profile (volume and intensity) than longer duration moderate activity.

'Walk Buds': A walking intervention to increase physical activity, physical fitness, and emotional wellbeing, in 9-13 year old children with intellectual disabilities. Results of a clustered randomised feasibility trial

BACKGROUND

Children with intellectual disability are less physically active and more sedentary than typically developing peers. To date no studies have tested the feasibility of a school-based walking intervention for children with Intellectual Disability.

METHOD

A clustered randomised controlled trial (cRCT), with an embedded process evaluation, was used to test the feasibility of a school-based walking intervention. Eight schools (n = 161 pupils aged 9-13 years) were randomised into either an intervention arm or an 'exercise as usual' arm. Measures included physical activity, physical fitness and emotional wellbeing. Baseline and 3-month follow-up data were collected.

RESULTS

The 'Walk Buds' intervention was found to be acceptable to teaching staff and pupils, with an uptake rate of the walking sessions offered of 84%.

CONCLUSION

A number of challenges were experienced, relating to the COVID-19 pandemic, and difficulties collecting accelerometer data. Barriers, facilitators and required changes identified through the mixed methods process evaluation are discussed.

School-level intra-cluster correlation coefficients and autocorrelations for children's accelerometer-measured physical activity in England by age and gender

BACKGROUND

Randomised, cluster-based study designs in schools are commonly used to evaluate children's physical activity interventions. Sample size estimation relies on accurate estimation of the intra-cluster correlation coefficient (ICC), but published estimates, especially using accelerometry-measured physical activity, are few and vary depending on physical activity outcome and participant age. Less commonly-used cluster-based designs, such as stepped wedge designs, also need to account for correlations over time, e.g. cluster autocorrelation (CAC) and individual autocorrelation (IAC), but no estimates are currently available. This paper estimates the school-level ICC, CAC and IAC for England children's accelerometer-measured physical activity outcomes by age group and gender, to inform the design of future school-based cluster trials.

METHODS

Data were pooled from seven large English datasets of accelerometer-measured physical activity data between 2002-18 (> 13,500 pupils, 540 primary and secondary schools). Linear mixed effect models estimated ICCs for weekday and whole week for minutes spent in moderate-to-vigorous physical activity (MVPA) and being sedentary for different age groups, stratified by gender. The CAC (1,252 schools) and IAC (34,923 pupils) were estimated by length of follow-up from pooled longitudinal data.

RESULTS

School-level ICCs for weekday MVPA were higher in primary schools (from 0.07 (95% CI: 0.05, 0.10) to 0.08 (95% CI: 0.06, 0.11)) compared to secondary (from 0.04 (95% CI: 0.03, 0.07) to (95% CI: 0.04, 0.10)). Girls' ICCs were similar for primary and secondary schools, but boys' were lower in secondary. For all ages, combined the CAC was 0.60 (95% CI: 0.44-0.72), and the IAC was 0.46 (95% CI: 0.42-0.49), irrespective of follow-up time. Estimates were higher for MVPA vs sedentary time, and for weekdays vs the whole week.

CONCLUSIONS

Adequately powered studies are important to evidence effective physical activity strategies. Our estimates of the ICC, CAC and IAC may be used to plan future school-based physical activity evaluations and were fairly consistent across a range of ages and settings, suggesting that results may be applied to other high income countries with similar school physical activity provision. It is important to use estimates appropriate to the study design, and that match the intended study population as closely as possible.

Insulin resistance, C-reactive protein, diastolic to systolic blood pressure ratio and epicardial fat are related to sedentary time, and inversely related to physical activity in school-aged children

Background

Physical activity (PA) is beneficial for the overall health. Objectives are: (1) To compare metabolic (MRM) and cardiovascular-risk-markers (CRM) in children according to their PA-level; (2) to explore the associations of MRM and CRM with PA and sedentary time (ST); and (3) to identify the associations between MRM and CRM in less (LA) and more active (MA) children.

Methods

A total of 238 apparently healthy school-aged children were enrolled (132 boys/106 girls; 9.1 ± 1.8 years) and body mass index standard deviation score (BMI SDS) and blood pressure were assessed. Fasting venous blood sampling was performed to assess insulin resistance (HOMA-IR) and high-sensitivity-C-reactive protein (hsCRP). Epicardial fat, interventricular septal and left ventricular posterior wall thicknesses were assessed by high-resolution ultrasonography. PA and ST were assessed by enKid-questionnaire. Children were classified based on enKid-score as being LA and MA (below and above 50th percentile for PA).

Results

MA-children had lower values for: BMI SDS, diastolic-to-systolic blood pressure ratio, HOMA-IR and hsCRP (7.02 to 61.5% lower, p = 0.040 to p < 0.0001) compared to LA-children. MRM and CRM were positively associated with ST (p = 0.003 to p < 0.001), and negatively associated with PA (p = 0.044 to p < 0.001). Finally, MRM were positively associated with CRM (p = 0.008 to p < 0.0001). Interestingly, the latter associations were observed in LA-children but were not present in MA-children.

Conclusion

More PA is associated with better cardio-metabolic profile in school-aged children. PA seems to modulate the associations between MRM and CRM, thus reinforcing the idea that fostering PA in children may lower the risk for development of a cardio-metabolic disease.

Physical activity and sleep changes among children during the COVID-19 pandemic

Daily routines, including in-person school and extracurricular activities, are important for maintaining healthy physical activity and sleep habits in children. The COVID-19 pandemic significantly disrupted daily routines as in-person school and activities closed to prevent spread of SARS-CoV-2. We aimed to examine and assess differences in objectively measured physical activity levels and sleep patterns from wearable sensors in children with obesity before, during, and after a period of school and extracurricular activity closures associated with the COVID-19 pandemic. We compared average step count and sleep patterns (using the Mann-Whitney U Test) before and during the pandemic-associated school closures by using data from activity tracker wristbands (Garmin VivoFit 3). Data were collected from 94 children (aged 5-17) with obesity, who were enrolled in a randomized controlled trial testing a community-based lifestyle intervention for a duration of 12-months. During the period that in-person school and extracurricular activities were closed due to the COVID-19 pandemic, children with obesity experienced objectively-measured decreases in physical activity, and sleep duration. From March 15, 2020 to March 31, 2021, corresponding with local school closures, average daily step count decreased by 1655 steps. Sleep onset and wake time were delayed by about an hour and 45 min, respectively, while sleep duration decreased by over 12 min as compared with the pre-closure period. Step counts increased with the resumption of in-person activities. These findings provide objective evidence for parents, clinicians, and public health professionals on the importance of in-person daily activities and routines on health behaviors, particularly for children with pre-existing obesity. Trial Registration: Clinical trial registration: NCT03339440.

Accelerometer-measured 24-hour movement behaviours over 7 days in Malaysian children and adolescents: A cross-sectional study

BACKGROUND

Quantifying movement behaviours over 24-hours enables the combined effects of and inter-relations between sleep, sedentary time and physical activity (PA) to be understood. This is the first study describing 24-hour movement behaviours in school-aged children and adolescents in South-East Asia. Further aims were to investigate between-participant differences in movement behaviours by demographic characteristics and timing of data collection during Ramadan and COVID-19 restrictions.

METHODS

Data came from the South-East Asia Community Observatory health surveillance cohort, 2021-2022. Children aged 7-18 years within selected households in Segamat, Malaysia wore an Axivity AX6 accelerometer on their wrist for 24 hours/day over 7 days, completed the PAQ-C questionnaire, and demographic information was obtained. Accelerometer data was processed using GGIR to determine time spent asleep, inactive, in light-intensity PA (LPA) and moderate-to-vigorous PA (MVPA). Differences in accelerometer-measured PA by demographic characteristics (sex, age, ethnicity, socioeconomic group) were explored using univariate linear regression. Differences between data collected during vs outside Ramadan or during vs after COVID-19 restrictions, were investigated through univariate and multiple linear regressions, adjusted for age, sex and ethnicity.

RESULTS

The 491 participants providing accelerometer data spent 8.2 (95% confidence interval (CI) = 7.9-8.4) hours/day asleep, 12.4 (95% CI = 12.2-12.7) hours/day inactive, 2.8 (95% CI = 2.7-2.9) hours/day in LPA, and 33.0 (95% CI = 31.0-35.1) minutes/day in MVPA. Greater PA and less time inactive were observed in boys vs girls, children vs adolescents, Indian and Chinese vs Malay children and higher income vs lower income households. Data collection during Ramadan or during COVID-19 restrictions were not associated with MVPA engagement after adjustment for demographic characteristics.

CONCLUSIONS

Demographic characteristics remained the strongest correlates of accelerometer-measured 24-hour movement behaviours in Malaysian children and adolescents. Future studies should seek to understand why predominantly girls, adolescents and children from Malay ethnicities have particularly low movement behaviours within Malaysia.

Associations between motor competence and physical activity levels of children with intellectual disabilities and/or autism spectrum disorder: Movement matters

Motor competence is important for lifelong physical activity (PA). The current study aimed to examine associations between PA and motor competence. In total, 43 children aged 7-12 years with intellectual disabilities and/or autism spectrum disorder completed anthropometric measures, the Bruininks-Oseretsky Test of Motor Proficiency-2, and wore a wrist accelerometer to capture total PA, moderate-to-vigorous PA (MVPA), average acceleration, and intensity gradient. No significant associations were found between PA outcomes and motor competence. Motor competence performance was commonly 'below average' or 'average'. The weakest subtests were upper limb coordination and strength. The strongest subtest was running speed and agility. Total weekly MVPA was 336.1 ± 150.3 min, higher than UK recommendations of 120-180 per week for disabled children and young people. Larger scale studies are needed to better understand the relationship between PA and motor competence. Future research should also consider the influence of environmental factors on PA in this group.

Daily energy requirements of male academy soccer players are greater than age-matched non-academy soccer players: A doubly labelled water investigation

This study aimed to test the hypothesis that the total daily energy expenditure (TDEE) of male academy soccer players is greater than players not enrolled on a formalised academy programme. English Premier League academy (ACAD: n = 8, 13 years, 50 ± 6 kg, 88 ± 3% predicted adult stature, PAS) and non-academy players (NON-ACAD: n = 6, 13 years, 53 ± 12 kg, 89 ± 3% PAS) were assessed for TDEE (via doubly labelled water) during a 14-day in-season period. External loading was evaluated during training (ACAD: 8 sessions, NON-ACAD: 2 sessions) and games (2 games for both ACAD and NON-ACAD) via GPS, and daily physical activity was evaluated using triaxial accelerometry. Accumulative duration of soccer activity (ACAD: 975 ± 23 min, NON-ACAD: 397 ± 2 min; p < 0.01), distance covered (ACAD: 54.2 ± 8.3 km, NON-ACAD: 21.6 ± 4.7 km; p < 0.05) and time engaged in daily moderate-to-vigorous (ACAD: 124 ± 17 min, NON-ACAD: 79 ± 18 min; p < 0.01) activity was greater in academy players. Academy players displayed greater absolute (ACAD: 3380 ± 517 kcal · d-1, NON-ACAD: 2641 ± 308 kcal · d-1; p < 0.05) and relative TDEE (ACAD: 66 ± 6 kcal · kg · d-1, NON-ACAD: 52 ± 10 kcal · kg · d-1; p < 0.05) versus non-academy players. Given the injury risk associated with high training volumes during growth and maturation, data demonstrate the requirement for academy players to consume sufficient energy (and carbohydrate) intake to support the enhanced energy cost of academy programmes.