Investigating young children's physical activity through time and place

BACKGROUND

Previous research indicates the start of primary school (4-5-year-old) as an essential period for the development of children's physical activity (PA) patterns, as from this point, the age-related decline of PA is most often observed. During this period, young children are exposed to a wider variety of environmental- and social contexts and therefore their PA is influenced by more diverse factors. However, in order to understand children's daily PA patterns and identify relevant opportunities for PA promotion, it is important to further unravel in which (social) contexts throughout the day, PA of young children takes place.

METHODS

We included a cross-national sample of 21 primary schools from the Startvaardig study. In total, 248 children provided valid accelerometer and global positioning (GPS) data. Geospatial analyses were conducted to quantify PA in (social) environments based on their school and home. Transport-related PA was evaluated using GPS speed-algorithms. PA was analysed at different environments, time-periods and for week- and weekend days separately.

RESULTS

Children accumulated an average of 60 min of moderate-to-vigorous PA (MVPA), both during week- and weekend days. Schools contributed to approximately half of daily MVPA during weekdays. During weekends, environments within 100 m from home were important, as well as locations outside the home-school neighbourhood. Pedestrian trips contributed to almost half of the daily MVPA.

CONCLUSIONS

We identified several social contexts relevant for children's daily MVPA. Schools have the potential to significantly contribute to young children's PA patterns and are therefore encouraged to systematically evaluate and implement parts of the school-system that stimulate PA and potentially also learning processes. Pedestrian trips also have substantial contribution to daily MVPA of young children, which highlights the importance of daily active transport in school- and parental routines.

Validation of physical activity levels from shank-placed Axivity AX6 accelerometers in older adults

This cross-sectional study aimed to identify and validate cut-points for measuring physical activity using Axivity AX6 accelerometers positioned at the shank in older adults. Free-living physical activity was assessed in 35 adults aged 55 and older, where each participant wore a shank-mounted Axivity and a waist-mounted ActiGraph simultaneously for 72 hours. Optimized cut-points for each participant's Axivity data were determined using an optimization algorithm to align with ActiGraph results. To assess the validity between the physical activity assessments from the optimized Axivity cut-points, a leave-one-out cross-validation was conducted. Bland-Altman plots with 95% limits of agreement, intraclass correlation coefficients (ICC), and mean differences were used for comparing the systems. The results indicated good agreement between the two accelerometers when classifying sedentary behaviour (ICC = 0.85) and light physical activity (ICC = 0.80), and moderate agreement when classifying moderate physical activity (ICC = 0.67) and vigorous physical activity (ICC = 0.70). Upon removal of a significant outlier, the agreement was slightly improved for sedentary behaviour (ICC = 0.86) and light physical activity (ICC = 0.82), but substantially improved for moderate physical activity (ICC = 0.81) and vigorous physical activity (ICC = 0.96). Overall, the study successfully demonstrated the capability of the resultant cut-point model to accurately classify physical activity using Axivity AX6 sensors placed at the shank.

Association between wrist-worn free-living accelerometry and hand grip strength in middle-aged and older adults

INTRODUCTION

Wrist-worn activity monitors have seen widespread adoption in recent times, particularly in young and sport-oriented cohorts, while their usage among older adults has remained relatively low. The main limitations are in regards to the lack of medical insights that current mainstream activity trackers can provide to older subjects. One of the most important research areas under investigation currently is the possibility of extrapolating clinical information from these wearable devices.

METHODS

The research question of this study is understanding whether accelerometry data collected for 7-days in free-living environments using a consumer-based wristband device, in conjunction with data-driven machine learning algorithms, is able to predict hand grip strength and possible conditions categorized by hand grip strength in a general population consisting of middle-aged and older adults.

RESULTS

The results of the regression analysis reveal that the performance of the developed models is notably superior to a simple mean-predicting dummy regressor. While the improvement in absolute terms may appear modest, the mean absolute error (6.32 kg for males and 4.53 kg for females) falls within the range considered sufficiently accurate for grip strength estimation. The classification models, instead, excel in categorizing individuals as frail/pre-frail, or healthy, depending on the T-score levels applied for frailty/pre-frailty definition. While cut-off values for frailty vary, the results suggest that the models can moderately detect characteristics associated with frailty (AUC-ROC: 0.70 for males, and 0.76 for females) and viably detect characteristics associated with frailty/pre-frailty (AUC-ROC: 0.86 for males, and 0.87 for females).

CONCLUSIONS

The results of this study can enable the adoption of wearable devices as an efficient tool for clinical assessment in older adults with multimorbidities, improving and advancing integrated care, diagnosis and early screening of a number of widespread diseases.

Quantifying time spent outdoors: A versatile method using any type of global positioning system (GPS) and accelerometer devices

Spending time outdoors is associated with increased time spent in physical activity, lower chronic disease risk, and wellbeing. Many studies rely on self-reported measures, which are prone to recall bias. Other methods rely on features and functions only available in some GPS devices. Thus, a reliable and versatile method to objectively quantify time spent outdoors is needed. This study sought to develop a versatile method to classify indoor and outdoor (I/O) GPS data that can be widely applied using most types of GPS and accelerometer devices. To develop and test the method, five university students wore an accelerometer (ActiGraph wGT3X-BT) and a GPS device (Canmore GT-730FL-S) on an elastic belt at the right hip for two hours in June 2022 and logged their activity mode, setting, and start time via activity diaries. GPS trackers were set to collect data every 5 seconds. A rule-based point cluster-based method was developed to identify indoor, outdoor, and in-vehicle time. Point clusters were detected using an application called GPSAS_Destinations and classification were done in R using accelerometer lux, building footprint, and park location data. Classification results were compared with the submitted activity diaries for validation. A total of 7,006 points for all participants were used for I/O classification analyses. The overall I/O GPS classification accuracy rate was 89.58% (Kappa = 0.78), indicating good classification accuracy. This method provides reliable I/O clarification results and can be widely applied using most types of GPS and accelerometer devices.

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.

Using functional principal component analysis (FPCA) to quantify sitting patterns derived from wearable sensors

BACKGROUND

Sedentary behavior (SB) is a recognized risk factor for many chronic diseases. ActiGraph and activPAL are two commonly used wearable accelerometers in SB research. The former measures body movement and the latter measures body posture. The goal of the current study is to quantify the pattern and variation of movement (by ActiGraph activity counts) during activPAL-identified sitting events, and examine associations between patterns and health-related outcomes, such as systolic and diastolic blood pressure (SBP and DBP).

METHODS

The current study included 314 overweight postmenopausal women, who were instructed to wear an activPAL (at thigh) and ActiGraph (at waist) simultaneously for 24 hours a day for a week under free-living conditions. ActiGraph and activPAL data were processed to obtain minute-level time-series outputs. Multilevel functional principal component analysis (MFPCA) was applied to minute-level ActiGraph activity counts within activPAL-identified sitting bouts to investigate variation in movement while sitting across subjects and days. The multilevel approach accounted for the nesting of days within subjects.

RESULTS

At least 90% of the overall variation of activity counts was explained by two subject-level principal components (PC) and six day-level PCs, hence dramatically reducing the dimensions from the original minute-level scale. The first subject-level PC captured patterns of fluctuation in movement during sitting, whereas the second subject-level PC delineated variation in movement during different lengths of sitting bouts: shorter (< 30 minutes), medium (30 -39 minutes) or longer (> 39 minute). The first subject-level PC scores showed positive association with DBP (standardized β ^ : 2.041, standard error: 0.607, adjusted p = 0.007), which implied that lower activity counts (during sitting) were associated with higher DBP.

CONCLUSION

In this work we implemented MFPCA to identify variation in movement patterns during sitting bouts, and showed that these patterns were associated with cardiovascular health. Unlike existing methods, MFPCA does not require pre-specified cut-points to define activity intensity, and thus offers a novel powerful statistical tool to elucidate variation in SB patterns and health.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03473145; Registered 22 March 2018; https://clinicaltrials.gov/ct2/show/NCT03473145 ; International Registered Report Identifier (IRRID): DERR1-10.2196/28684.

Reliability and validity of rapid assessment tools for measuring 24-hour movement behaviours in children aged 0-5 years: the Movement Behaviour Questionnaire Baby (MBQ-B) and child (MBQ-C)

BACKGROUND

The development of validated "fit-for-purpose" rapid assessment tools to measure 24-hour movement behaviours in children aged 0-5 years is a research priority. This study evaluated the test-retest reliability and concurrent validity of the open-ended and closed-ended versions of the Movement Behaviour Questionnaire for baby (MBQ-B) and child (MBQ-C).

METHODS

300 parent-child dyads completed the 10-day study protocol (MBQ-B: N = 85; MBQ-C: N = 215). To assess validity, children wore an accelerometer on the non-dominant wrist (ActiGraph GT3X+) for 7 days and parents completed 2 × 24-hour time use diaries (TUDs) recording screen time and sleep on two separate days. For babies (i.e., not yet walking), parents completed 2 × 24-hour TUDs recording tummy time, active play, restrained time, screen time, and sleep on days 2 and 5 of the 7-day monitoring period. To assess test-retest reliability, parents were randomised to complete either the open- or closed-ended versions of the MBQ on day 7 and on day 10. Test-retest intraclass correlation coefficients (ICC's) were calculated using generalized linear mixed models and validity was assessed via Spearman correlations.

RESULTS

Test-retest reliability for the MBQ-B was good to excellent with ICC's ranging from 0.80 to 0.94 and 0.71-0.93 for the open- and closed-ended versions, respectively. For both versions, significant positive correlations were observed between 24-hour diary and MBQ-B reported tummy time, active play, restrained time, screen time, and sleep (rho = 0.39-0.87). Test-retest reliability for the MBQ-C was moderate to excellent with ICC's ranging from 0.68 to 0.98 and 0.44-0.97 for the open- and closed-ended versions, respectively. For both the open- and closed-ended versions, significant positive correlations were observed between 24-hour diary and MBQ-C reported screen time and sleep (rho = 0.44-0.86); and between MBQ-C reported and device-measured time in total activity and energetic play (rho = 0.27-0.42).

CONCLUSIONS

The MBQ-B and MBQ-C are valid and reliable rapid assessment tools for assessing 24-hour movement behaviours in infants, toddlers, and pre-schoolers. Both the open- and closed-ended versions of the MBQ are suitable for research conducted for policy and practice purposes, including the evaluation of scaled-up early obesity prevention programs.

Energy Expenditure Prediction from Accelerometry Data Using Long Short-Term Memory Recurrent Neural Networks

The accurate estimation of energy expenditure from simple objective accelerometry measurements provides a valuable method for investigating the effect of physical activity (PA) interventions or population surveillance. Methods have been evaluated previously, but none utilize the temporal aspects of the accelerometry data. In this study, we investigated the energy expenditure prediction from acceleration measured at the subjects' hip, wrist, thigh, and back using recurrent neural networks utilizing temporal elements of the data. The acceleration was measured in children (N = 33) performing a standardized activity protocol in their natural environment. The energy expenditure was modelled using Multiple Linear Regression (MLR), stacked long short-term memory (LSTM) networks, and combined convolutional neural networks (CNN) and LSTM. The correlation and mean absolute percentage error (MAPE) were 0.76 and 19.9% for the MLR, 0.882 and 0.879 and 14.22% for the LSTM, and, with the combined LSTM-CNN, the best performance of 0.883 and 13.9% was achieved. The prediction error for vigorous intensities was significantly different (p < 0.01) from those of the other intensity domains: sedentary, light, and moderate. Utilizing the temporal elements of movement significantly improves energy expenditure prediction accuracy compared to other conventional approaches, but the prediction error for vigorous intensities requires further investigation.

The Analytical Validity of Stride Detection and Gait Parameters Reconstruction Using the Ankle-Mounted Inertial Measurement Unit Syde®

The increasing use of inertial measurement units (IMU) in biomedical sciences brings new possibilities for clinical research. The aim of this paper is to demonstrate the accuracy of the IMU-based wearable Syde® device, which allows day-long and remote continuous gait recording in comparison to a reference motion capture system. Twelve healthy subjects (age: 23.17 ± 2.04, height: 174.17 ± 6.46 cm) participated in a controlled environment data collection and performed a series of gait tasks with both systems attached to each ankle. A total of 2820 strides were analyzed. The results show a median absolute stride length error of 1.86 cm between the IMU-based wearable device reconstruction and the motion capture ground truth, with the 75th percentile at 3.24 cm. The median absolute stride horizontal velocity error was 1.56 cm/s, with the 75th percentile at 2.63 cm/s. With a measurement error to the reference system of less than 3 cm, we conclude that there is a valid physical recovery of stride length and horizontal velocity from data collected with the IMU-based wearable Syde® device.

Accelerometer-Measured Physical Activity, Sedentary Time, and Heart Failure Risk in Women Aged 63 to 99 Years

Importance

Heart failure (HF) prevention is paramount to public health in the 21st century.

Objective

To examine incident HF and its subtypes with preserved ejection fraction (HFpEF) and reduced EF (HFrEF) according to accelerometer-measured physical activity (PA) and sedentary time.

Design, Setting, and Participants

This was a prospective cohort study, the Objective Physical Activity and Cardiovascular Health (OPACH) in Older Women study, conducted from March 2012 to April 2014. Included in the analysis were women aged 63 to 99 years without known HF, who completed hip-worn triaxial accelerometry for 7 consecutive days. Follow-up for incident HF occurred through February 2022. Data were analyzed from March to December 2023.

Exposure

Daily PA (total, light, moderate to vigorous PA [MVPA], steps) and sedentary (total, mean bout duration) behavior.

Main Outcomes and Measures

Adjudicated incident HF, HFpEF, and HFrEF.

Results

A total of 5951 women (mean [SD] age, 78.6 [6.8] years) without known HF were included in this analysis. Women self-identified with the following race and ethnicity categories: 2004 non-Hispanic Black (33.7%), 1022 Hispanic (17.2%), and 2925 non-Hispanic White (49.2%). There were 407 HF cases (257 HFpEF; 110 HFrEF) identified through a mean (SD) of 7.5 (2.6) years (range, 0.01-9.9 years) of follow-up. Fully adjusted hazard ratios (HRs) for overall HF, HFpEF, and HFrEF associated with a 1-SD increment were 0.85 (95% CI, 0.75-0.95), 0.78 (95% CI, 0.67-0.91), and 1.02 (95% CI, 0.81-1.28) for minutes per day total PA; 0.74 (95% CI, 0.63-0.88), 0.71 (95% CI, 0.57-0.88), and 0.83 (95% CI, 0.62-1.12) for steps per day; and 1.17 (95% CI, 1.04-1.33), 1.29 (95% CI, 1.10-1.51), and 0.94 (95% CI, 0.75-1.18) for minutes per day total sedentary. Cubic spline curves for overall HF and HFpEF were significant inverse for total PA and steps per day and positive for total sedentary. Light PA and MVPA were inversely associated with overall HF (HR per 1 SD: 0.88; 95% CI, 0.78-0.98 and 0.84; 95% CI, 0.73-0.97) and HFpEF (0.80; 95% CI, 0.70-0.93 and 0.85; 95% CI, 0.72-1.01) but not HFrEF. Associations did not meaningfully differ when stratified by age, race and ethnicity, body mass index, physical function, or comorbidity score. Results for sedentary bout duration were inconsistent.

Conclusions and Relevance

Higher accelerometer-measured PA (MVPA, light PA, steps per day) was associated with lower risk (and greater total sedentary time with higher risk) of overall HF and HFpEF in a racially and ethnically diverse cohort of older women. Increasing PA and reducing sedentary time for primary HFpEF prevention may have relevant implications for cardiovascular resilience and healthy aging in later life.

Isotemporal substitution analysis of time between sleep, sedentary behavior, and physical activity on depressive symptoms in older adults: a cross-sectional study

BACKGROUND

Compared to young individuals, older adults participate more in sedentary behavior (SB) and less in physical activity (PA). These behaviors are associated with numerous adverse health factors.

OBJECTIVE

The purpose of the study was to examine the hypothetical effects of substituting time spent sleeping, performing SB, and performing moderate-to-vigorous physical activity (MVPA) on depressive symptomatology in older adults.

DESIGN AND SETTING

An analytical cross-sectional study employing exploratory survey methods was conducted in the city of Alcobaça in the state of Bahia, Brazil.

METHODS

The study included 473 older adults who answered a structured questionnaire during an interview. Exposure time to SB and PA level were assessed using the International Physical Activity Questionnaire, and depressive symptoms were analyzed using the short version of the Geriatric Depression Scale. An isotemporal replacement model was used to evaluate the effects of different SB sessions on depressive symptomatology.

RESULTS

An increase in the risk of depressive symptoms was observed when MVPA and sleep time were substituted for the same SB time at all times tested, with maximum values of 40% and 20%, respectively. Opposite substitution of MVPA and sleep time increments reduced the risk of depressive symptomatology by 28% and 17%, respectively.

CONCLUSIONS

The results of the present study indicate that replacing SB with the same amount of sleep or MVPA may reduce depressive symptoms. The longer the reallocation time, the greater are the benefits.

Isotemporal substitution effect of 24-hour movement behavior on the mental health of Chinese preschool children

The 24-h movement behavior of preschoolers comprises a spectrum of activities, including moderate-to-vigorous intensity physical activity (MVPA), light-intensity physical activity (LPA), screen-based sedentary behavior (SCSB), non-screen-based sedentary behavior (NSCSB), and sleep. While previous research has shed light on the link between movement behaviors and children's mental health, the specific impacts on the unique demographic of Chinese preschoolers remain underexplored. This study significantly contributes to the literature by exploring how 24-h movement behavior affects the mental health of preschoolers in a Chinese context. The study involved205 Chinese preschool children (117 boys and 88 girls) between the ages of 3 and 6 years wore accelerometers to measure their LPA, MVPA, and sedentary behavior (SB), while their parents reported the time spent on sleep and SCSB. The parents also completed the Strength and Difficulties Questionnaire to assess their children's mental health. The study used compositional regression and isotemporal substitution models to examine the relationship between the various components of 24-h movement behavior and mental health. The results showed that greater NCSSB compared to MVPA, LPA, sleep, and SCSB was associated with good prosocial behavior and lower scores on externalizing problems. This highlights the potential of NSCSB as a beneficial component in the daily routine of preschoolers for fostering mental well-being. Replacing 15 min of sleep and SCSB with 15 min of NSCSB was associated with a decrease of 0.24 and 0.15 units, respectively, in externalizing problems. Reallocating 15 min of sleep to NSCSB was linked to an increase of 0.11 units in prosocial behavior. There were no significant substitution effects between LPA and MVPA time with any other movement behavior on prosocial behavior and externalizing problems. Given the positive associations observed, further longitudinal studies are necessary to explore the link between 24-h movement behavior and mental health in preschool children.

Accelerometry-assessed daily physical activity and compliance with recommendations in Spanish children: importance of physical education classes and vigorous intensity

Background

Physical activity (PA) is associated with numerous health benefits. Vigorous PA (VPA) may have a greater impact on public health than lower-intensity PA. The incorporation of a specific recommendation on VPA could complement and improve existing recommendations for average daily moderate-vigorous PA (MVPA). Physical education classes could have a positive impact on children's adherence to average daily physical activity recommendations. The aim was to investigate the association between MVPA and VPA in children, as well as adherence to recommendations, and obesity and the presence of physical education classes.

Methods

A cross-sectional study of physical activity was conducted in a sample of 8 and 9-year-old children in Andalusia (Spain). GENEActiv accelerometers were used, placed on the non-dominant wrist for at least eight consecutive days (24-h protocol). School days with and without physical education class, and weekend days were defined. ROC curves were used to calculate the threshold associated with obesity for average daily MVPA and VPA for recommendations.

Results

A total of 360 schoolchildren were included in the analyses (184 girls). An average of 7.7 (SD 1.4) valid days per participant were evaluated, with 19.9 (SD 10.5) and 11.4 (SD 5.1) minutes of VPA performed by boys and girls respectively. 25.8% of the participants were classified with central obesity. The optimal threshold determined with ROC analysis was 12.5 and 9.5 minutes of average daily VPA for boys and girls, respectively (RecVPA), and 75 minutes of average daily MVPA for both sexes (RecMVPA). The RecVPA showed stronger association with obesity. On school days with physical education class, compared to days without this class, children showed increased VPA and MVPA engagement and better compliance with recommendations, with smaller differences in adherence according to sex or obesity.

Conclusions

On days with physical education class, more physical activity was accumulated at all intensities and greater adherence to the recommendations than on days without this class. VPA had a stronger correlation with the absence of obesity than lower-intensity activity. It was also observed that boys were physically more active and had higher adherence to the recommendations than girls.

Physical activity in adults with and without rheumatoid arthritis: cross-sectional results from the Survey of Health, Ageing and Retirement in Europe (SHARE)

OBJECTIVE

Studies examining habitual physical activity levels and patterns in adults with rheumatoid arthritis (RA) using raw data from modern accelerometers are lacking. We aimed (i) to examine physical activity levels and patterns in adults with RA in their familiar environment, and (ii) to investigate whether physical activity levels differ throughout the day.

METHOD

Data were taken from Wave 8 of the Survey of Health, Ageing and Retirement in Europe, including N = 607 men and women who wore a triaxial accelerometer and had adequate information for RA and accelerometry data summarized as Euclidean norm minus one (ENMO, mg). Growth-curve models and simple contrast analysis were used to examine the effect of RA on daily patterns of physical activity levels, including mean total ENMO in mg, mean minutes of light-intensity physical activity (ENMO values ≥ 25 mg and ≤ 75 mg), and moderate-to-vigorous-intensity physical activity (ENMO values > 75 mg).

RESULTS

Total physical activity averaged throughout the day was 25.0 and 28.6 mg for respondents with and without RA, respectively. Respondents with RA spent more time in light-intensity physical activity throughout the day (p < 0.001), but less time in moderate-to-vigorous-intensity physical activity between 4 am and 11 pm (p < 0.001) than respondents without RA.

CONCLUSION

Adults with RA were less physically active than adults without RA. However, there were no diurnal differences in physical activity.

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.

The effectiveness of simple heuristic features in sensor orientation and placement problems in human activity recognition using a single smartphone accelerometer

BACKGROUND

Human activity Recognition (HAR) using smartphone sensors suffers from two major problems: sensor orientation and placement. Sensor orientation and sensor placement problems refer to the variation in sensor signal for a particular activity due to sensors' altering orientation and placement. Extracting orientation and position invariant features from raw sensor signals is a simple solution for tackling these problems. Using few heuristic features rather than numerous time-domain and frequency-domain features offers more simplicity in this approach. The heuristic features are features which have very minimal effects of sensor orientation and placement. In this study, we evaluated the effectiveness of four simple heuristic features in solving the sensor orientation and placement problems using a 1D-CNN-LSTM model for a data set consisting of over 12 million samples.

METHODS

We accumulated data from 42 participants for six common daily activities: Lying, Sitting, Walking, and Running at 3-Metabolic Equivalent of Tasks (METs), 5-METs and 7-METs from a single accelerometer sensor of a smartphone. We conducted our study for three smartphone positions: Pocket, Backpack and Hand. We extracted simple heuristic features from the accelerometer data and used them to train and test a 1D-CNN-LSTM model to evaluate their effectiveness in solving sensor orientation and placement problems.

RESULTS

We performed intra-position and inter-position evaluations. In intra-position evaluation, we trained and tested the model using data from the same smartphone position, whereas, in inter-position evaluation, the training and test data was from different smartphone positions. For intra-position evaluation, we acquired 70-73% accuracy; for inter-position cases, the accuracies ranged between 59 and 69%. Moreover, we performed participant-specific and activity-specific analyses.

CONCLUSIONS

We found that the simple heuristic features are considerably effective in solving orientation problems. With further development, such as fusing the heuristic features with other methods that eliminate placement issues, we can also achieve a better result than the outcome we achieved using the heuristic features for the sensor placement problem. In addition, we found the heuristic features to be more effective in recognizing high-intensity activities.

Gait Event Detection and Travel Distance Using Waist-Worn Accelerometers across a Range of Speeds: Automated Approach

Estimation of temporospatial clinical features of gait (CFs), such as step count and length, step duration, step frequency, gait speed, and distance traveled, is an important component of community-based mobility evaluation using wearable accelerometers. However, accurate unsupervised computerized measurement of CFs of individuals with Duchenne muscular dystrophy (DMD) who have progressive loss of ambulatory mobility is difficult due to differences in patterns and magnitudes of acceleration across their range of attainable gait velocities. This paper proposes a novel calibration method. It aims to detect steps, estimate stride lengths, and determine travel distance. The approach involves a combination of clinical observation, machine-learning-based step detection, and regression-based stride length prediction. The method demonstrates high accuracy in children with DMD and typically developing controls (TDs) regardless of the participant's level of ability. Fifteen children with DMD and fifteen TDs underwent supervised clinical testing across a range of gait speeds using 10 m or 25 m run/walk (10 MRW, 25 MRW), 100 m run/walk (100 MRW), 6-min walk (6 MWT), and free-walk (FW) evaluations while wearing a mobile-phone-based accelerometer at the waist near the body's center of mass. Following calibration by a trained clinical evaluator, CFs were extracted from the accelerometer data using a multi-step machine-learning-based process and the results were compared to ground-truth observation data. Model predictions vs. observed values for step counts, distance traveled, and step length showed a strong correlation (Pearson's r = -0.9929 to 0.9986, p < 0.0001). The estimates demonstrated a mean (SD) percentage error of 1.49% (7.04%) for step counts, 1.18% (9.91%) for distance traveled, and 0.37% (7.52%) for step length compared to ground-truth observations for the combined 6 MWT, 100 MRW, and FW tasks. Our study findings indicate that a single waist-worn accelerometer calibrated to an individual's stride characteristics using our methods accurately measures CFs and estimates travel distances across a common range of gait speeds in both DMD and TD peers.

Optimizing Epoch Length and Activity Count Threshold Parameters in Accelerometry: Enhancing Upper Extremity Use Quantification in Cerebral Palsy

Various accelerometry protocols have been used to quantify upper extremity (UE) activity, encompassing diverse epoch lengths and thresholding methods. However, there is no consensus on the most effective approach. The aim of this study was to delineate the optimal parameters for analyzing accelerometry data to quantify UE use in individuals with unilateral cerebral palsy (CP).

METHODS

A group of adults with CP (n = 15) participated in six activities of daily living, while a group of children with CP (n = 14) underwent the Assisting Hand Assessment. Both groups performed the activities while wearing ActiGraph GT9X-BT devices on each wrist, with concurrent video recording. Use ratio (UR) derived from accelerometry and video analysis and accelerometer data were compared for different epoch lengths (1, 1.5, and 2 s) and activity count (AC) thresholds (between 2 and 150).

RESULTS

In adults, results are comparable across epoch lengths, with the best AC thresholds being ≥ 100. In children, results are similar across epoch lengths of 1 and 1.5 (optimal AC threshold = 50), while the optimal threshold is higher with an epoch length of 2 (AC = 75).

CONCLUSIONS

The combination of epoch length and AC thresholds should be chosen carefully as both influence the validity of the quantification of UE use.

Classification of human walking context using a single-point accelerometer

Real-world walking data offers rich insights into a person's mobility. Yet, daily life variations can alter these patterns, making the data challenging to interpret. As such, it is essential to integrate context for the extraction of meaningful information from real-world movement data. In this work, we leveraged the relationship between the characteristics of a walking bout and context to build a classification algorithm to distinguish between indoor and outdoor walks. We used data from 20 participants wearing an accelerometer on the thigh over a week. Their walking bouts were isolated and labeled using GPS and self-reporting data. We trained and validated two machine learning models, random forest and ensemble Support Vector Machine, using a leave-one-participant-out validation scheme on 15 subjects. The 5 remaining subjects were used as a testing set to choose a final model. The chosen model achieved an accuracy of 0.941, an F1-score of 0.963, and an AUROC of 0.931. This validated model was then used to label the walks from a different dataset with 15 participants wearing the same accelerometer. Finally, we characterized the differences between indoor and outdoor walks using the ensemble of the data. We found that participants walked significantly faster, longer, and more continuously when walking outdoors compared to indoors. These results demonstrate how movement data alone can be used to obtain accurate information on important contextual factors. These factors can then be leveraged to enhance our understanding and interpretation of real-world movement data, providing deeper insights into a person's health.

Correlates of Toddlers' Physical Activity Levels and Sedentary Behavior During Unstructured Outdoor Play in Early Childhood Education and Daycare Settings

Despite recent research showing that early childhood education and daycare settings (ECEC) have an important role in promoting toddlers' physical activity (PA), crucial information gaps remain regarding toddlers' PA and sedentary behavior (SB) in these outdoor settings. We aimed in this study to: (a) analyze PA patterns and SB during unstructured outdoor play time in preschool and daycare environments using accelerometry and systematic observation; (b) provide concurrent accelerometry and observational data to help validate the Observational System for Recording Physical Activity in Children-Preschool Version (OSRAC-P); and (c) examine individual, social and environmental correlates of PA and SB during toddlers' unstructured outdoor play time. We found that: (a) toddlers displayed high amounts of PA with no sex, BMI, and/or age differences in PA and SB levels,; (b) environmental variables (e.g., fixed equipment and playground density) were not associated with PA levels or SB intensity; (c) the OSRAC-P was a reliable and valid means of observing and analyzing toddlers' PA patterns during unstructured outdoor play time; and (e) different social patterns between boys and girls did not impact PA levels or patterns. Combining different measurement methods permitted an improved understanding of unstructured outdoor play in preschool and daycare settings.

Number of days required to reliably measure weekday and weekend total sleeping time with accelerometer: A secondary data analysis with National Health and Nutritional Survey (NHANES) 2011-2014 data

The current standard practice for measuring sleeping time with accelerometer is to ask the participants to wear it for 7 consecutive days and analysing data from participants who have provided at least 4 days of valid data. However, this standard lacks supporting evidence. This study aims to evaluate this standard of practice by examining the reliability of measuring total sleeping time in a representative sample of US adults using accelerometer data from the National Health and Nutritional Survey (NHANES) waves 2011-2012 and 2013-2014. The sample included a total of 14,676 participants, out of which only those who provided data for seven days (n = 9510) were included in the analysis. The results revealed that the intra-class correlation coefficient (ICC) for a single day of measurement was 0.38 for weekdays and 0.27 for weekends. To achieve a reliability of 0.7, measurements for 4 and 7 nights were necessary for weekdays and weekends, respectively. Our simulation study found that the randomly-selected 3-day average of weekday sleeping time strongly correlated with the actual mean (ρ = 0.92), capturing at least 80 % of the variance. However, the randomly-selected 1-day average of weekend sleeping time only captured about 60 % of the variance. In conclusion, we recommend that future accelerometer research adopts a 9-day continuous measurement period, covering four weekend days, to reliably estimate both weekday and weekend sleeping time.

Physical Activity Questionnaire for Children: Validity and Cut-Points to Identify Sufficient Levels of Moderate- to Vigorous-Intensity Physical Activity Among Children and Adolescents Diagnosed With HIV

PURPOSE

To investigate the validity of the Physical Activity Questionnaire for Older Children (PAQ-C) to assess the moderate- to vigorous-intensity physical activity (MVPA) level of children and adolescents diagnosed with HIV and propose cut-points, with accelerometer measures as the reference method.

METHOD

Children and adolescents, aged 8-14 years (mean age = 12.21 y, SD = 2.09), diagnosed with HIV by vertical transmission, participated in the study. MVPA was investigated through the PAQ-C and triaxial accelerometer (ActiGraph GT3X+). Receiver operating characteristic curve and sensitivity and specificity values were used to identify a cut-point for PAQ-C to distinguish participants meeting MVPA guidelines.

RESULTS

Fifty-six children and adolescents participated in the study. Among those, 16 met MVPA guidelines. The PAQ-C score was significantly related to accelerometry-derived MVPA (ρ = .506, P < .001). The PAQ-C score cut-point of 2.151 (sensitivity = 0.625, specificity = 0.875) was able to discriminate between those who met MVPA guidelines and those that did not (area under the curve = 0.751, 95% confidence interval, 0.616-0.886).

CONCLUSION

The PAQ-C was useful to investigate MVPA among children and adolescents diagnosed with HIV and to identify those who meet MVPA guidelines.

Concurrent Validity of Four Activity Monitors in Older Adults

Sedentary behaviour (SB) and physical activity (PA) have been shown to be independent modulators of healthy ageing. We thus investigated the impact of activity monitor placement on the accuracy of detecting SB and PA in older adults, as well as a novel random forest algorithm trained on data from older persons. Four monitor types (ActiGraph wGT3X-BT, ActivPAL3c VT, GENEActiv Original, and DynaPort MM+) were simultaneously worn on five anatomical sites during ten different activities by a sample of twenty older adults (70.0 (12.0) years; 10 women). The results indicated that collecting metabolic equivalent (MET) data for 60 s provided the most representative results, minimising variability. In addition, thigh-worn monitors, including ActivPAL, Random Forest, and Sedentary Sphere-Thigh, exhibited superior performance in classifying SB, with balanced accuracies ≥ 94.2%. Other monitors, such as ActiGraph, DynaPort MM+, and GENEActiv Sedentary Sphere-Wrist, demonstrated lower performance. ActivPAL and GENEActiv Random Forest outperformed other monitors in participant-specific balanced accuracies for SB classification. Only thigh-worn monitors achieved acceptable overall balanced accuracies (≥80.0%) for SB, standing, and medium-to-vigorous PA classifications. In conclusion, it is advisable to position accelerometers on the thigh, collect MET data for ≥60 s, and ideally utilise population-specific trained algorithms.

Feasibility of Using a GENEActiv Accelerometer with Triaxial Acceleration and Temperature Sensors to Monitor Adherence to Shoulder Sling Wear Following Surgery

BACKGROUND

Self-reported adherence to sling wear is unreliable due to recall bias. We aim to assess the feasibility and accuracy of quantifying sling wear and non-wear utilising slings pre-fitted with a GENEActiv accelerometer that houses triaxial acceleration and temperature sensors.

METHODS

Ten participants were asked to wear slings for 480 min (8 h) incorporating 180 min of non-wear time in durations varying from 5-120 min. GENEActiv devices were fitted in sutured inner sling pockets and participants logged sling donning and doffing times. An algorithm based on variability in acceleration in three axes and temperature change was developed to identify sling wear and non-wear and compared to participants' logs.

RESULTS

There was no significant difference between algorithm detected non-wear duration (mean ± standard deviation = 172.0 ± 6.8 min/participant) and actual non-wear (179.7 ± 1.0 min/participant). Minute-by-minute agreement of sensor-detected wear and non-wear with participant reported wear was 97.3 ± 1.5% (range = 93.9-99.0), with mean sensitivity 94.3 ± 3.5% (range = 86.1-98.3) and specificity 99.1 ± 0.8% (range = 93.7-100).

CONCLUSION

An algorithm based on accelerometer-assessed acceleration and temperature can accurately identify shoulder sling wear/non-wear times. This method may have potential for assessing whether sling wear adherence after shoulder surgeries have any bearing on patient functional outcomes.

Fundament for a methodological standard to process hip accelerometer data to a measure of physical activity intensity in middle-aged individuals

BACKGROUND

There is a lack of a methodological standard to process accelerometer data to measures of physical activity, which impairs data quality and comparability. This study investigated the effect of different combinations of settings of multiple processing components, on the measure of physical activity and the association with measures of cardiometabolic health in an unselected population of middle-aged individuals.

METHODS

Free-living hip accelerometer data, aerobic fitness, body mass index, HDL:total cholesterol ratio, blood glucose, and systolic blood pressure were achieved from 4391 participants 50-64 years old included in The Swedish CArdioPulmonary bioImage Study (SCAPIS) baseline measurement (cross-sectional). Lab data were also included for calibration of accelerometers to provide comparable measure of physical activity intensity and time spent in different intensity categories, as well as to enhance understanding. The accelerometer data processing components were hardware recalibration, frequency filtering, number of accelerometer axes, epoch length, wear time criterium, time composition (min/24 h vs. % of wear time). Partial least regression and ordinary least regression were used for the association analyses.

RESULTS

The setting of frequency filter had the strongest effect on the physical activity intensity measure and time distribution in different intensity categories followed by epoch length and number of accelerometer axes. Wear time criterium and recalibration of accelerometer data were less important. The setting of frequency filter and epoch length also showed consistent important effect on the associations with the different measures of cardiometabolic health, while the effect of recalibration, number of accelerometer axes, wear time criterium and expression of time composition was less consistent and less important. There was a large range in explained variance of the measures of cardiometabolic health depending on the combination of processing settings, for example, 12.1%-20.8% for aerobic fitness and 5.8%-14.0% for body mass index.

CONCLUSIONS

There was a large variation in the physical activity intensity measure and the association with different measures of cardiometabolic health depending on the combination of settings of accelerometer data processing components. The results provide a fundament for a standard to process hip accelerometer data to assess the physical activity in middle-aged populations.

Validity of the activPAL and ActiGraph for measuring sitting time and steps in hospitalised orthopaedic patients with altered weight bearing

PURPOSE

To determine the criterion validity of the activPAL and ActiGraph for measuring steps and sitting/sedentary time, compared to observation, in people hospitalised following orthopaedic lower limb injury who were weight bearing (WB) (i.e., walking) or non-weight bearing (NWB) (i.e., hopping).

MATERIALS AND METHODS

Participants wore an activPAL and ActiGraph on the hip/thigh/unaffected (UA)/affected ankle (AA) while completing bouts of walking and sitting. Lin's concordance correlation coefficient, Bland-Altman methods, and ratio of agreement were used to compare device-measured to observed (videoed) step count, sitting/sedentary time.

RESULTS

In 42 participants, the ActiGraph demonstrated excellent concordance with the observed step count when worn on the ankle (LCC 0.91-0.92) compared to the hip (LCC 0.56) in participants that were WB. The ActiGraph AA achieved the highest concordance (LCC 0.71) with observed steps in participants NWB. The activPAL had poor concordance with observed steps, particularly at slow gait speeds, in participants that were WB (LCC 0.38-0.46), however was less influenced by gait speed and had good concordance in NWB participants (LCC 0.52-0.69). The activPAL (LCC 0.79-0.88) and ActiGraph UA (LCC 0.94) showed excellent concordance with observed sitting and sedentary time, respectively.

CONCLUSIONS

The ActiGraph worn at the ankle provided the most valid measure of steps in people who are WB and NWB following orthopaedic injury, while the activPAL was best for measuring sitting time.Implications for rehabilitationTo accurately measure both steps and sitting time in people with lower limb orthopaedic injuries, a combination of activity monitors should be used (i.e., ActiGraph for steps, activPAL for sitting time).The ActiGraph device when worn on the ankle demonstrated the strongest agreement with observed step count in people who were weight bearing and non-weight bearing.Caution is needed when using thigh- or hip-worn devices in people who walk slowly.

Effects of ActiGraph's filter, epoch length and non-wearing time algorithm on step counts in people with COPD

The influence of the ActiGraph® processing criteria on estimating step counts in chronic obstructive pulmonary disease (COPD) remains uncertain. This study aimed to assess the influence of filters, epoch lengths and non-wearing time (NWT) algorithms on steps/day in people with COPD. ActiGraph GT3X+ was worn on the waist for seven days. Steps were detected using different filters (normal and low-frequency extension [LFE]), epoch lengths (15s and 60s), and NWT algorithms (Choi and Troiano). Linear mixed-effects model was applied to assess the effects of filter, epoch length, NWT algorithm on steps/day. Lin's concordance correlation and Bland-Altman were used to measure agreement. A total of 136 people with COPD (107 male; 69 ± 8 years; FEV1 51 ± 17% predicted) were included. Significant differences were found between filters (p < 0.001), but not between epoch lengths or NWT algorithms. The LFE increased, on average, approximately 7500 steps/day compared to the normal filter (p < 0.001). Agreement was poor (<0.3) and proportional bias was significant when comparing steps/day computed with different filters, regardless of the epoch length and NWT algorithm. Filter choice but not epoch lengths or NWT algorithms seem to impact measurement of steps/day. Future studies are needed to recommend the most accurate technique for measuring steps/day in people with COPD.

Comparative Analysis of ActiGraph Step Counting Methods in Adults: A Systematic Literature Review and Meta-Analysis

PURPOSE

The primary aim of this study was to compare steps per day across ActiGraph models, wear locations, and filtering methods. A secondary aim was to compare ActiGraph steps per day to those estimated by the ankle-worn StepWatch.

METHODS

We conducted a systematic literature review to identify studies of adults published before May 12, 2022, that compared free-living steps per day of ActiGraph step counting methods and studies that compared ActiGraph to StepWatch. Random-effects meta-analysis compared ActiGraph models, wear locations, filter mechanisms, and ActiGraph to StepWatch steps per day. A sensitivity analysis of wear location by younger and older age was included.

RESULTS

Twelve studies, with 46 comparisons, were identified. When worn on the hip, the AM-7164 recorded 123% of the GT series steps (no low-frequency extension (no LFE) or default filter). However, the AM-7164 recorded 72% of the GT series steps when the LFE was enabled. Independent of the filter used (i.e., LFE, no LFE), ActiGraph GT series monitors captured more steps on the wrist than on the hip, especially among older adults. Enabling the LFE on the GT series monitors consistently recorded more steps, regardless of wear location. When using the default filter (no LFE), ActiGraph recorded fewer steps than StepWatch (ActiGraph on hip 73% and ActiGraph on wrist 97% of StepWatch steps). When LFE was enabled, ActiGraph recorded more steps than StepWatch (ActiGraph on the hip, 132%; ActiGraph on the wrist, 178% of StepWatch steps).

CONCLUSIONS

The choice of ActiGraph model, wear location, and filter all impacted steps per day in adults. These can markedly alter the steps recorded compared with a criterion method (StepWatch). This review provides critical insights for comparing studies using different ActiGraph step counting methods.

Joint modeling the frequency and duration of accelerometer-measured physical activity from a lifestyle intervention trial

Physical activity (PA) guidelines recommend that PA be accumulated in bouts of 10 minutes or more in duration. Recently, researchers have sought to better understand how participants in PA interventions increase their activity. Participants can increase their daily PA by increasing the number of PA bouts per day while keeping the duration of the bouts constant; they can keep the number of bouts constant but increase the duration of each bout; or participants can increase both the number of bouts and their duration. We propose a novel joint modeling framework for modeling PA bouts and their duration over time. Our joint model is comprised of two sub-models: a mixed-effects Poisson hurdle sub-model for the number of bouts per day and a mixed-effects location scale gamma regression sub-model to characterize the duration of the bouts and their variance. The model allows us to estimate how daily PA bouts and their duration vary together over the course of an intervention and by treatment condition and is specifically designed to capture the unique distributional features of bouted PA as measured by accelerometer: frequent measurements, zero-inflated bouts, and skewed bout durations. We apply our methods to the Make Better Choices study, a longitudinal lifestyle intervention trial to increase PA. We perform a simulation study to evaluate how well our model is able to estimate relationships between outcomes.

Association between accelerometer-derived physical activity and incident cardiac arrest

AIMS

Studies on objectively measured physical activity (PA) have investigated acute cardiovascular outcomes but not cardiac arrest (CA). Our study aimed to investigate the dose-response relationship between accelerometer-measured PA and CA by intensity of PA.

METHODS AND RESULTS

This prospective cohort study included 98 893 UK Biobank participants whose PA data were measured using wrist-worn accelerometers. Total PA volume was measured using the average overall acceleration. Minutes per week of light PA (LPA), moderate PA (MPA), and vigorous PA (VPA) were recorded. The incident CA was identified using diagnostic codes linked to hospital encounters and death records. Cox proportional hazard models with restricted cubic splines were used to study the associations, including sex differences. During the follow-up period (median: 7.31 years; interquartile range: 6.78-7.82 years), 282 incident CAs (0.39 per 1000 person-years) occurred. Total PA was inversely related to CA risk. The CA risk decreased sharply until the time spent in MPA or VPA reached ∼360 min or 20 min per week, respectively, after which it was relatively flat. The LPA was not associated with CA risk. Subgroup analyses showed a more pronounced association between PA and a reduced risk of CA in women compared to men.

CONCLUSION

Accelerometer-measured PA, particularly MPA and VPA, was associated with a lower CA risk. Furthermore, a stronger association was observed in women than men.

Determining energy expenditure in a large seabird using accelerometry

The trade off between energy gained and expended is the foundation of understanding how, why and when animals perform any activity. Based on the concept that animal movements have an energetic cost, accelerometry is increasingly being used to estimate energy expenditure. However, validation of accelerometry as an accurate proxy for field metabolic rate in free-ranging species is limited. In the present study, Australasian gannets (Morus serrator) from the Pope's Eye colony (38°16'42″S 144°41'48″E), south-eastern Australia, were equipped with GPS and tri-axial accelerometers and dosed with doubly labelled water (DLW) to measure energy expenditure during normal behaviour for 3-5 days. The correlation between daily energy expenditure from the DLW and vectorial dynamic body acceleration (VeDBA) was high for both a simple correlation and activity-specific approaches (R2=0.75 and 0.80, respectively). Varying degrees of success were observed for estimating at-sea metabolic rate from accelerometry when removing time on land using published energy expenditure constants (R2=0.02) or activity-specific approaches (R2=0.42). The predictive capacity of energy expenditure models for total and at-sea periods was improved by the addition of total distance travelled and proportion of the sampling period spent at sea during the night, respectively (R2=0.61-0.82). These results indicate that accelerometry can be used to estimate daily energy expenditure in free-ranging gannets and its accuracy may depend on the inclusion of movement parameters not detected by accelerometry.

Accelerometer-measured absolute versus relative physical activity intensity: cross-sectional associations with cardiometabolic health in midlife

BACKGROUND

Observational studies investigating the association between accelerometer-measured physical activity and health all use absolute measures of physical activity intensity. However, intervention studies suggest that the physical activity intensity required to improve health is relative to individual fitness. The aim of this study was to investigate the associations between accelerometer-measured absolute and relative physical activity intensity and cardiometabolic health, and what implications these associations may have on the interpretation of health-associated physical activity.

METHODS

A sample of the cross-sectional Swedish CArdioPulmonary bioImage Study (SCAPIS) consisting of 4,234 men and women aged 55-64 years was studied. Physical activity intensity was measured by accelerometry and expressed as absolute (e.g., metabolic equivalents of task) or relative (percentage of maximal oxygen consumption). Fitness was estimated by the submaximal Ekblom-Bak test. A composite ('metabolic syndrome') score combined measures of waist circumference, systolic blood pressure, high-density lipoprotein, triglycerides, and glycated hemoglobin. Associations of absolute and relative physical activity intensity with the health indicators (i.e., fitness and metabolic syndrome score) were studied by partial least squares regression. Analyses were stratified by fitness level.

RESULTS

Both absolute and relative physical activity intensity associated with the health indicators. However, the strongest associations for absolute intensity varied depending on fitness levels, whereas the associations for relative intensity were more synchronized across fitness groups. The dose-response relationship between moderate-to-vigorous intensity and the health indicators was stronger for relative than for absolute intensity. The absolute and relative moderate-to-vigorous intensity cut-offs intersected at the 5th fitness percentile, indicating that the absolute intensity cut-off is too low for 95% of individuals in this sample. While 99% of individuals fulfilled the general physical activity recommendations based on absolute intensity measures, only 21% fulfilled the recommendations based on relative intensity measures. In relation to a "sufficient" fitness level, 9% fulfilled the recommendations.

CONCLUSIONS

Accelerometer-measured relative physical activity intensity represents the intensity related to health benefits regardless of fitness level. Traditional absolute moderate intensity accelerometer cut-offs are too low for most individuals and should be adapted to the fitness level in the sample studied. Absolute and relative physical activity intensity cannot be used interchangeably.

Accelerometer derived physical activity and subclinical coronary and carotid atherosclerosis: cross-sectional analyses in 22 703 middle-aged men and women in the SCAPIS study

OBJECTIVES

The aim included investigation of the associations between sedentary (SED), low-intensity physical activity (LIPA), moderate-to-vigorous intensity PA (MVPA) and the prevalence of subclinical atherosclerosis in both coronaries and carotids and the estimated difference in prevalence by theoretical reallocation of time in different PA behaviours.

DESIGN

Cross-sectional.

SETTING

Multisite study at university hospitals.

PARTICIPANTS

A total of 22 670 participants without cardiovascular disease (51% women, 57.4 years, SD 4.3) from the population-based Swedish CArdioPulmonary bioImage study were included. SED, LIPA and MVPA were assessed by hip-worn accelerometer.

PRIMARY AND SECONDARY OUTCOMES

Any and significant subclinical coronary atherosclerosis (CA), Coronary Artery Calcium Score (CACS) and carotid atherosclerosis (CarA) were derived from imaging data from coronary CT angiography and carotid ultrasound.

RESULTS

High daily SED (>70% ≈10.5 hours/day) associated with a higher OR 1.44 (95% CI 1.09 to 1.91), for significant CA, and with lower OR 0.77 (95% CI 0.63 to 0.95), for significant CarA. High LIPA (>55% ≈8 hours/day) associated with lower OR for significant CA 0.70 (95% CI 0.51 to 0.96), and CACS, 0.71 (95% CI 0.51 to 0.97), but with higher OR for CarA 1.41 (95% CI 1.12 to 1.76). MVPA above reference level, >2% ≈20 min/day, associated with lower OR for significant CA (OR range 0.61-0.67), CACS (OR range 0.71-0.75) and CarA (OR range 0.72-0.79). Theoretical replacement of 30 min of SED into an equal amount of MVPA associated with lower OR for significant CA, especially in participants with high SED 0.84 (95% CI 0.76 to 0.96) or low MVPA 0.51 (0.36 to 0.73).

CONCLUSIONS

MVPA was associated with a lower risk for significant atherosclerosis in both coronaries and carotids, while the association varied in strength and direction for SED and LIPA, respectively. If causal, clinical implications include avoiding high levels of daily SED and low levels of MVPA to reduce the risk of developing significant subclinical atherosclerosis.

Two- and three-dimensional measurements of leg length change using an accelerometer-based portable navigation system in total hip arthroplasty

BACKGROUND

The aim of this study was examining the accuracy of accelerometer-based portable navigation systems (HipAlign) when measuring leg length changes using two-dimensional (2D) and three-dimensional (3D) methods.

METHODS

Inclusion criteria were patients ≥ 20 years old with symptomatic hip disease who underwent primary total hip arthroplasty (THA) in the supine position using HipAlign between June 2019 and April 2020. The exclusion criteria were patients who underwent THA via a posterior approach. We examined correlations between the leg length change measurement with HipAlign and either 2D or 3D measurement. We performed a multivariate analysis to determine which factors may have influenced the absolute error results.

RESULTS

This study included 34 patients. The absolute error in leg length change between the HipAlign and 3D measurement (4.0 mm) was greater than the HipAlign and 2D measurement (1.7 mm). There were positive correlations between leg length change with HipAlign and 2D and 3D measurements. Male patients had larger errors with 2D measurement. No significant factors were identified for 3D measurement.

CONCLUSION

HipAlign provided acceptable measurement accuracy for leg length changes.

Compositional isotemporal substitution analysis of physical activity, sedentary behaviour and cardiometabolic biomarkers in US adults: A nationally representative study

Substantial evidence links physical activity and sedentary behaviour (SB) with cardiovascular health. However, studies usually examine time-use behaviours independently, rather than considering daily activities as a 24-hour time-use composition. This study aimed to use compositional data models to investigate how time reallocations from SB to moderate-to-vigorous physical activity (MVPA)/ light physical activity (LPA) were associated with changes in cardiometabolic biomarkers. Compositional isotemporal substitution analysis was conducted using data from a representative cross-sectional sample of adults aged 20 years or older (n = 5213 full sample; n = 2221 fasting subsample) from the 2003-2004 and 2005-2006 cycles of the National Health and Nutrition Examination Survey. Overall as well as gender- and age-specific estimates were obtained for reallocating time between the behaviours associated with cardiometabolic outcomes. Replacing SB with MVPA was associated with decreased levels of C-reactive protein (CRP), white blood cells (WBCs), red blood cell distribution width (RDW), insulin, insulin resistance homeostasis model assessment (HOMA-IR) and 2-hour glucose, and increased high-density lipoprotein cholesterol (HDL-C), except for WBCs in older adults, insulin and HOMA-IR in females and older adults, 2-hour glucose in young and older adults, and HDL-C in older adults. Substituting LPA for SB resulted in lower CRP in older adults, lower RDW in males and older adults, lower insulin in young and middle-aged adults, lower HOMA-IR in females and middle-aged adults, and higher HDL-C in males and young adults. Our findings provide new evidence for the potential benefits of LPA and MVPA in cardiovascular health and help make population-specific recommendations for physical activity.HighlightsShorter sedentary behaviour (SB) time and longer active behaviours time are associated with a lower cardiovascular disease risk profile.Although replacing SB with MVPA has stronger positive health effects, LPA, as a simpler and more feasible activity, may has greater potential in promoting cardiovascular health.The expected changes in cardiometabolic biomarkers caused by time reallocations from SB to MVPA/LPA vary with gender and age, and physical activity guidelines with specific recommendations should be tailed to the subpopulations.

Low movement, deep-learned sitting patterns, and sedentary behavior in the International Study of Childhood Obesity, Lifestyle and the Environment (ISCOLE)

BACKGROUND/OBJECTIVES

Sedentary behavior (SB) has both movement and postural components, but most SB research has only assessed low movement, especially in children. The purpose of this study was to compare estimates and health associations of SB when derived from a standard accelerometer cut-point, a novel sitting detection technique (CNN Hip Accelerometer Posture for Children; CHAP-Child), and both combined.

METHODS

Data were from the International Study of Childhood Obesity, Lifestyle, and the Environment (ISCOLE). Participants were 6103 children (mean ± SD age 10.4 ± 0.56 years) from 12 countries who wore an ActiGraph GT3X+ accelerometer on the right hip for approximately one week. We calculated SB time, mean SB bout duration, and SB breaks using a cut-point (SBmovement), CHAP-Child (SBposture), and both methods combined (SBcombined). Mixed effects regression was used to test associations of SB variables with pediatric obesity variables (waist circumference, body fat percentage, and body mass index z-score).

RESULTS

After adjusting for MVPA, SBposture showed several significant obesity associations favoring lower mean SB bout duration (b = 0.251-0.449; all p < 0.001) and higher SB breaks (b = -0.005--0.052; all p < 0.001). Lower total SB was unexpectedly related to greater obesity (b = -0.077--0.649; p from <0.001-0.02). For mean SB bout duration and SB breaks, more associations were observed for SBposture (n = 5) than for SBmovement (n = 3) or SBcombined (n = 1), and tended to have larger magnitude as well.

CONCLUSIONS

Using traditional measures of low movement as a surrogate for SB may lead to underestimated or undetected adverse associations between SB and obesity. CHAP-Child allows assessment of sitting posture using hip-worn accelerometers. Ongoing work is needed to understand how low movement and posture are related to one another, as well as their potential health implications.

Greater accelerometer-measured physical activity is associated with better cognition and cerebrovascular health in older adults

OBJECTIVES

Physical activity (PA) may help maintain brain structure and function in aging. Since the intensity of PA needed to effect cognition and cerebrovascular health remains unknown, we examined associations between PA and cognition, regional white matter hyperintensities (WMH), and regional cerebral blood flow (CBF) in older adults.

METHOD

Forty-three older adults without cognitive impairment underwent magnetic resonance imaging (MRI) and comprehensive neuropsychological assessment. Waist-worn accelerometers objectively measured PA for approximately one week.

RESULTS

Higher time spent in moderate to vigorous PA (MVPA) was uniquely associated with better memory and executive functioning after adjusting for all light PA. Higher MVPA was also uniquely associated with lower frontal WMH volume although the finding was no longer significant after additionally adjusting for age and accelerometer wear time. MVPA was not associated with CBF. Higher time spent in all light PA was uniquely associated with higher CBF but not with cognitive performance or WMH volume.

CONCLUSIONS

Engaging in PA may be beneficial for cerebrovascular health, and MVPA in particular may help preserve memory and executive function in otherwise cognitively healthy older adults. There may be differential effects of engaging in lighter PA and MVPA on MRI markers of cerebrovascular health although this needs to be confirmed in future studies with larger samples. Future randomized controlled trials that increase PA are needed to elucidate cause-effect associations between PA and cerebrovascular health.

Association of perceived and objective neighborhood walkability with accelerometer-measured physical activity and sedentary time in the Maastricht Study

BACKGROUND

We investigated the association of neighborhood walkability with accelerometer-measured physical activity (PA) and sedentary behavior (SB) and examined whether objective and subjective measures of walkability resulted in similar findings.

METHODS

PA and SB from the first 7689 Maastricht Study participants ages 40-75 from 2010 to 2017 were measured using accelerometers for 7 days. Mean daily step count, light-intensity PA, moderate- to vigorous- intensity PA (MVPA), and SB were calculated. Objective walkability was measured by the 7-component Dutch Walkability Index within 500 m Euclidean buffers around residential addresses of participants. Subjective walkability was obtained from the Abbreviated Neighborhood Environment Walkability Scale. Linear regression models analyzed the associations of walkability with PA and SB, controlling for potential confounders.

RESULTS

Objective walkability was negatively associated with light intensity PA in the most walkable quartile (b = -14.58, 95% CI = -20.94, -8.23). Compared to participants living in the least walkable neighborhoods, those in the most walkable quartile had statistically significantly higher SB levels (b = 11.64, 95% CI = 4.95, 18.32). For subjective walkability, mean daily step count was significantly higher in the most walkable quartile (b = 509.60, 95% CI = 243.38, 775.81). Higher subjective walkability was positively associated with MVPA (b = 4.40, 95% CI = 2.56, 6.23).

CONCLUSION

Living in a neighborhood with higher objective walkability was associated with lower levels of PA and higher SB levels while higher subjective walkability was associated with higher levels of PA. These results show discordant findings and thus, the effect of walkability on participant PA and SB within our sample is to be determined.

Sleep, physical activity, and psychological outcomes in children and adolescents with pediatric onset multiple sclerosis

BACKGROUND

Sleep, physical activity (PA) and sedentary behavior (SED) have bidirectional associations with mental health in children. The relationships among sleep, PA, SED, with depressive and fatigue symptoms have not been investigated in Pediatric Onset Multiple Sclerosis (POMS) but are needed to inform sleep and PA behavior change interventions.

OBJECTIVES

(1) To describe sleep quality including: sleep efficiency, latency, total sleep time, number of awakenings, time in bed, and wake after sleep onset using actigraphy in children and adolescents ages 11 to 18 diagnosed with POMS, and to compare these sleep metrics to those of an age- and sex-matched non-MS group (2) To examine the relationship between time spent in sedentary, light (LIPA), moderate and vigorous PA (MVPA), sleep quality, with depression, fatigue, and quality of life in children and adolescents with POMS and an age and sex matched non-MS group.

METHODS

A cross-sectional study recruited children and adolescents with POMS ages 11 to 18 years followed at a tertiary pediatric hospital (Toronto, Canada) and an age and sex matched non-MS group from the general population. Participants were consented prior to initiation of study procedures. Participants wore an Actiwatch monitor and GT3X accelerometer and completed standardized questionnaires validated to capture data on sleep disturbances, depression, fatigue, and quality of life. Objective sleep data were collected using an Actiwatch including sleep efficiency, total sleep time, number of awakenings, wake after sleep onset (WASO), and sleep latency. A GT3X accelerometer was used to collect PA data including time spent in SED, light (LPA), and moderate to vigorous (MVPA) PA. Correlational analyses and tests of difference were used to compare the groups.

RESULTS

25 POMS (21F; 16.6 years ±1.1 yrs., median Expanded Disability Status Scale (EDSS) =1.5, IQR=1) and 25 Non-MS (22 F; 16±1.3 yrs.) took part. POMS had higher BMI (T= -5.1, P<0.001) compared to Non-MS. No differences in sleep efficiency (MS mean = 87%, vs. 88%) sleep time (MS Mean = 7.3 hrs. vs. 7.4 hrs.,), WASO (MS mean=37 mins. vs. 36 mins), latency (MS mean=15 mins vs. 11 mins), SED (MS mean =763 mins. vs. 730 mins) or PA (MS, mean LPA = 68 mins. vs 60 mins; MS mean MVPA = 12.7 mins. vs. 12.4 mins). Within POMS, higher sleep efficiency was associated with more SED (SR= 0.4, p = 0.05), while higher sleep efficiency was associated with less SED in Non-MS (SR = -0.7, p< 0.0). In children with POMS, less sleep time, shorter sleep onset latency and more WASO was associated with more SED (SR range = -0.45 to -0.58, P< 0.01). Higher sleep efficiency was associated with less fatigue. Less WASO was associated with lower depression, lower fatigue (SR = 0.67, p<0.01) and better quality of life (SR= -0.6, p<0.01). Greater LPA was associated with lower sleep onset latency (-0.45, p<0.05).

CONCLUSIONS

Children with POMS did not differ in Actiwatch monitored sleep quality metrics. However, within the POMS group sleep quality was associated with better fatigue, depression and QOL. Further, total sleep time, WASO and latency associated with time spent SED and LPA, which independently associate with mental health outcome. Longitudinal work should determine the temporal associations between WASO, sleep latency, sleep time, PA, and mental health outcomes and whether reallocation of specific sleep or PA behaviors (time to sleep, total sleep time, sedentary to MVPA) result in improved depression fatigue, or quality of life in children and adolescents with POMS.

Accelerometric Classification of Resting and Postural Tremor Amplitude

Clinical rating scales for tremors have significant limitations due to low resolution, high rater dependency, and lack of applicability in outpatient settings. Reliable, quantitative approaches for assessing tremor severity are warranted, especially evaluating treatment effects, e.g., of deep brain stimulation (DBS). We aimed to investigate how different accelerometry metrics can objectively classify tremor amplitude of Essential Tremor (ET) and tremor in Parkinson's Disease (PD). We assessed 860 resting and postural tremor trials in 16 patients with ET and 25 patients with PD under different DBS settings. Clinical ratings were compared to different metrics, based on either spectral components in the tremorband or pure acceleration, derived from simultaneous triaxial accelerometry captured at the index finger and wrist. Nonlinear regression was applied to a training dataset to determine the relationship between accelerometry and clinical ratings, which was then evaluated in a holdout dataset. All of the investigated accelerometry metrics could predict clinical tremor ratings with a high concordance (>70%) and substantial interrater reliability (Cohen's weighted Kappa > 0.7) in out-of-sample data. Finger-worn accelerometry performed slightly better than wrist-worn accelerometry. We conclude that triaxial accelerometry reliably quantifies resting and postural tremor amplitude in ET and PD patients. A full release of our dataset and software allows for implementation, development, training, and validation of novel methods.

A Scoping Review of the Validity and Reliability of Smartphone Accelerometers When Collecting Kinematic Gait Data

The aim of this scoping review is to evaluate and summarize the existing literature that considers the validity and/or reliability of smartphone accelerometer applications when compared to 'gold standard' kinematic data collection (for example, motion capture). An electronic keyword search was performed on three databases to identify appropriate research. This research was then examined for details of measures and methodology and general study characteristics to identify related themes. No restrictions were placed on the date of publication, type of smartphone, or participant demographics. In total, 21 papers were reviewed to synthesize themes and approaches used and to identify future research priorities. The validity and reliability of smartphone-based accelerometry data have been assessed against motion capture, pressure walkways, and IMUs as 'gold standard' technology and they have been found to be accurate and reliable. This suggests that smartphone accelerometers can provide a cheap and accurate alternative to gather kinematic data, which can be used in ecologically valid environments to potentially increase diversity in research participation. However, some studies suggest that body placement may affect the accuracy of the result, and that position data correlate better than actual acceleration values, which should be considered in any future implementation of smartphone technology. Future research comparing different capture frequencies and resulting noise, and different walking surfaces, would be useful.

Predicting a Fall Based on Gait Anomaly Detection: A Comparative Study of Wrist-Worn Three-Axis and Mobile Phone-Based Accelerometer Sensors

Falls by the elderly pose considerable health hazards, leading not only to physical harm but a number of other related problems. A timely alert about a deteriorating gait, as an indication of an impending fall, can assist in fall prevention. In this investigation, a comprehensive comparative analysis was conducted between a commercially available mobile phone system and two wristband systems: one commercially available and another representing a novel approach. Each system was equipped with a singular three-axis accelerometer. The walk suggestive of a potential fall was induced by special glasses worn by the participants. The same standard machine-learning techniques were employed for the classification with all three systems based on a single three-axis accelerometer, yielding a best average accuracy of 86%, a specificity of 88%, and a sensitivity of 86% via the support vector machine (SVM) method using a wristband. A smartphone, on the other hand, achieved a best average accuracy of 73% also with an SVM using only a three-axis accelerometer sensor. The significance analysis of the mean accuracy, sensitivity, and specificity between the innovative wristband and the smartphone yielded a p-value of 0.000. Furthermore, the study applied unsupervised and semi-supervised learning methods, incorporating principal component analysis and t-distributed stochastic neighbor embedding. To sum up, both wristbands demonstrated the usability of wearable sensors in the early detection and mitigation of falls in the elderly, outperforming the smartphone.

Accelerometry applications and methods to assess standing balance in older adults and mobility-limited patient populations: a narrative review

Accelerometers provide an opportunity to expand standing balance assessments outside of the laboratory. The purpose of this narrative review is to show that accelerometers are accurate, objective, and accessible tools for balance assessment. Accelerometry has been validated against current gold standard technology, such as optical motion capture systems and force plates. Many studies have been conducted to show how accelerometers can be useful for clinical examinations. Recent studies have begun to apply classification algorithms to accelerometry balance measures to discriminate populations at risk for falls. In addition to healthy older adults, accelerometry can monitor balance in patient populations such as Parkinson's disease, multiple sclerosis, and traumatic brain injury. The lack of software packages or easy-to-use applications have hindered the shift into the clinical space. Lack of consensus on outcome metrics has also slowed the clinical adoption of accelerometer-based balance assessments. Future studies should focus on metrics that are most helpful to evaluate balance in specific populations and protocols that are clinically efficacious.

Day-to-day variability in accelerometer-measured physical activity in mid-aged Australian adults

PURPOSE

The aim was to use accelerometer data to describe day-to-day variability in physical activity in a single week, according to sociodemographic variables, in mid-aged Australian adults.

METHODS

Data were from participants in the How Areas in Brisbane Influence HealTh and AcTivity (HABITAT) study who took part in a 2014 sub-study (N = 612; Mean age 60.6 [SD 6.9; range 48-73]). Participants wore a triaxial accelerometer (ActiGraph wGT3X-BT) on their non-dominant wrist for seven days, and data were expressed as acceleration in gravitational equivalent units (1 mg = 0.001 g). These were, used to estimate daily acceleration (during waking hours) and daily time spent in moderate-vigorous physical activity (MVPA, defined as ≥ 100mg). Coefficient of variation (calculated as [standard deviation/mean of acceleration and MVPA across the seven measurement days] * 100%) was used to describe day-to-day variability.

RESULTS

Average values for both acceleration (24.1-24.8 mg/day) and MVPA (75.9-79.7 mins/day) were consistent across days of the week, suggesting little day-to-day variability (at the group level). However, over seven days, average individual day-to-day variability in acceleration was 18.8% (SD 9.3%; range 3.4-87.7%) and in MVPA was 35.4% (SD 15.6%; range 7.3-124.6%), indicating considerable day-to-day variability in some participants. While blue collar workers had the highest average acceleration (28.6 mg/day) and MVPA (102.5 mins/day), their day-to-day variability was low (18.3% for acceleration and 31.9% for MVPA). In contrast, variability in acceleration was highest in men, those in professional occupations and those with high income; and variability in MVPA was higher in men than in women.

CONCLUSION

Results show group-level estimates of average acceleration and MVPA in a single week conceal considerable day-to-day variation in how mid-age Australians accumulate their acceleration and MVPA on a daily basis. Overall, there was no clear relationship between overall volume of activity and variability. Future studies with larger sample sizes and longitudinal data are needed to build on the findings from this study and increase the generalisability of these findings to other population groups.

Criterion validity of wrist accelerometry for assessing energy intake via the intake-balance technique

BACKGROUND

Intake-balance assessments measure energy intake (EI) by summing energy expenditure (EE) with concurrent change in energy storage (ΔES). Prior work has not examined the validity of such calculations when EE is estimated via open-source techniques for research-grade accelerometry devices. The purpose of this study was to test the criterion validity of accelerometry-based intake-balance methods for a wrist-worn ActiGraph device.

METHODS

Healthy adults (n = 24) completed two 14-day measurement periods while wearing an ActiGraph accelerometer on the non-dominant wrist. During each period, criterion values of EI were determined based on ΔES measured by dual X-ray absorptiometry and EE measured by doubly labeled water. A total of 11 prediction methods were tested, 8 derived from the accelerometer and 3 from non-accelerometry methods (e.g., diet recall; included for comparison). Group-level validity was assessed through mean bias, while individual-level validity was assessed through mean absolute error, mean absolute percentage error, and Bland-Altman analysis.

RESULTS

Mean bias for the three best accelerometry-based methods ranged from -167 to 124 kcal/day, versus -104 to 134 kcal/day for the non-accelerometry-based methods. The same three accelerometry-based methods had mean absolute error of 323-362 kcal/day and mean absolute percentage error of 18.1-19.3%, versus 353-464 kcal/day and 19.5-24.4% for the non-accelerometry-based methods. All 11 methods demonstrated systematic bias in the Bland-Altman analysis.

CONCLUSIONS

Accelerometry-based intake-balance methods have promise for advancing EI assessment, but ongoing refinement is necessary. We provide an R package to facilitate implementation and refinement of accelerometry-based methods in future research (see paulhibbing.com/IntakeBalance).

PIPTO: Precise Inertial-Based Pipeline for Threshold-Based Fall Detection Using Three-Axis Accelerometers

After traffic-related incidents, falls are the second cause of human death, presenting the highest percentage among the elderly. Aiming to address this problem, the research community has developed methods built upon different sensors, such as wearable, ambiance, or hybrid, and various techniques, such as those that are machine learning- and heuristic based. Concerning the models used in the former case, they classify the input data between fall and no fall, and specific data dimensions are required. Yet, when algorithms that adopt heuristic techniques, mainly using thresholds, are combined with the previous models, they reduce the computational cost. To this end, this article presents a pipeline for detecting falls through a threshold-based technique over the data provided by a three-axis accelerometer. This way, we propose a low-complexity system that can be adopted from any acceleration sensor that receives information at different frequencies. Moreover, the input lengths can differ, while we achieve to detect multiple falls in a time series of sum vector magnitudes, providing the specific time range of the fall. As evaluated on several datasets, our pipeline reaches high performance results at 90.40% and 91.56% sensitivity on MMsys and KFall, respectively, while the generated specificity is 93.96% and 85.90%. Lastly, aiming to facilitate the research community, our framework, entitled PIPTO (drawing inspiration from the Greek verb "πι´πτω", signifying "to fall"), is open sourced in Python and C.

Association of Sit-to-Stand Capacity and Free-Living Performance Using Thigh-Worn Accelerometers among 60- to 90-Yr-Old Adults

PURPOSE

Five times sit-to-stand (STS) test is commonly used as a clinical assessment of lower-extremity functional ability, but its association with free-living performance has not been studied. Therefore, we investigated the association between laboratory-based STS capacity and free-living STS performance using accelerometry. The results were stratified according to age and functional ability groups.

METHODS

This cross-sectional study included 497 participants (63% women) 60-90 yr old from three independent studies. A thigh-worn triaxial accelerometer was used to estimate angular velocity in maximal laboratory-based STS capacity and in free-living STS transitions over 3-7 d of continuous monitoring. Functional ability was assessed with short physical performance battery.

RESULTS

Laboratory-based STS capacity was moderately associated with the free-living mean and maximal STS performance ( r = 0.52-0.65, P < 0.01). Angular velocity was lower in older compared with younger and in low- versus high-functioning groups, in both capacity and free-living STS variables (all P < 0.05). Overall, angular velocity was higher in capacity compared with free-living STS performance. The STS reserve (test capacity - free-living maximal performance) was larger in younger and in high-functioning groups compared with older and low-functioning groups (all P < 0.05).

CONCLUSIONS

Laboratory-based STS capacity and free-living performance were found to be associated. However, capacity and performance are not interchangeable but rather provide complementary information. Older and low-functioning individuals seemed to perform free-living STS movements at a higher percentage of their maximal capacity compared with younger and high-functioning individuals. Therefore, we postulate that low capacity may limit free-living performance.

Observational longitudinal association between waking movement behaviours and psychological distress among adolescents using isotemporal analysis: DADOS study

This study aimed to examine the impact of reallocating time spent in waking movement behaviours at baseline on indicators of psychological distress at 24-month follow-up using isotemporal substitution regression models among a sample of Spanish adolescents. The DADOS (Deporte, ADOlescencia y Salud) study is a 3-year longitudinal observational research project carried out between years 2015-2017. The analyses included 197 adolescents (91 girls) aged 13.9 ± 0.3 years at baseline. Waking movement behaviours were assessed by a wrist-worn GENEActiv triaxial accelerometer and expressed as minutes/day of light physical activity (LPA), moderate-vigorous physical activity (MVPA) and time spent in sedentary behaviour (SB). The Behaviour Assessment System for Children and Adolescents (level 3 for adolescents) was used to assess psychological distress indicators (i.e., anxiety, social stress, and risk of depression). Results showed significant associations only for girls. The substitution of 10 min/day of SB or LPA at baseline with 10 min/day of MVPA was associated with lower levels of anxiety (both p ≤ 0.01) and social stress (both p < 0.05) at follow-up. The substitution of 10 min/day of SB with 10 min/day of LPA was associated with higher levels of anxiety at follow-up (p = 0.01). These findings highlight the need of specific physical activity recommendations for mental health paying special attention to sex-differences.

Validation of an accelerometer system for measuring physical activity and sedentary behavior in healthy children and adolescents

The study aims to assess the concurrent validity of the SENS motion® accelerometer system for device-based measurement of physical activity and sedentary behavior in healthy children and adolescents. Thirty-six healthy children and adolescents (mean ± standard deviation (SD) age, 10.2 ± 2.3 years) were fitted with three SENS sensors while performing standardized activities including walking, fast walking, sitting/lying, and arm movements. Data from the sensors were compared with video observations (reference criteria). The agreement between SENS motion® and observation was analyzed using Student's t-test and illustrated in Bland-Altman plots. The concurrent validity was further evaluated using intraclass correlation coefficient (ICC) and was expressed as standard error of measurement (SEM) and minimal detectable change (MDC). Strong agreement was found between SENS and observation for walking time, sedentary time, and lying time. In contrast, moderate agreement was observed for number of steps, sitting time, and time with and without arm movement. ICC2.1 values were overall moderate to excellent (0.5-0.94), with correspondingly low SEM% for walking time, sedentary time, lying time, and time with arm movement (2-9%). An acceptable SEM% level was reached for both steps and sitting time (11% and 12%). For fast walking time, the results showed a weak agreement between the measurement methods, and the ICC value was poor.

CONCLUSION

SENS motion® seems valid for detecting physical activity and sedentary behavior in healthy children and adolescents with strong agreement and moderate to excellent ICC values. Furthermore, the explorative results on arm movements seem promising.

WHAT IS KNOWN

• Inactivity and sedentary behavior follow an increasing trend among children and adolescents. • SENS motion® seems to be valid for measuring physical activity and sedentary behavior in adults and elderly patients.

WHAT IS NEW

• SENS motion® seems valid with strong agreement between video observations and SENS measurement, and ICC values are moderate to excellent when measuring physical activity and sedentary behavior in healthy children and adolescents. • SENS motion® seems promising for detection of arm movements.

Global Accelerometer-derived Physical Activity Levels from Preschoolers to Adolescents: A Multilevel Meta-analysis and Meta-regression

BACKGROUND

Global level physical activity surveillance studies were primarily based on self-report data that could generate inaccurate results.

PURPOSE

To investigate global accelerometer-measured daily moderate to vigorous physical activity (MVPA) changes from preschool age to adolescence as well as gender differences in MVPA while adjusting for the geographic regions and major MVPA cut points.

METHODS

A comprehensive search was conducted through August 2020 that includes 30 databases such as Academic Search Ultimate, Child Development & Adolescent Studies, Education Full Text, ERIC, General Science, PsycINFO, ScienceDirect, and SPORTDiscuss. We included both cross-sectional and longitudinal MVPA tracking studies with daily MVPA being measured by waist-worn accelerometers and determined by either Freedson 3 METs, 4 METs, or Evenson cut points for preschoolers, children, and adolescents.

RESULTS

Researchers analyzed 84 studies reporting on 124 effect sizes with a total of 57,587 participants. The combined data showed significant MVPA differences among various continents of participants (p < .001) or cut points (p < .05-.001) for both preschoolers, children, and adolescents. Globally, when continents and cut points were controlled, individuals' daily MVPA time decreased every year by an average of 7.88, 10.37, and 6.68 min from preschool age to adolescence, preschool age to children, and children to adolescence, respectively. When cut points and continents were controlled, boys had significantly higher daily MVPA than girls for all three age groups (p < .001).

CONCLUSIONS

Globally, individuals' daily MVPA starts to decline dramatically as early as the beginning of preschool age. Early intervention is needed to counteract the high decline rate in MVPA.