A comparison of physical activity from Actigraph GT3X+ accelerometers worn on the dominant and non-dominant wrist

Large-scale assessment of physical activity in a population using high-resolution hip-worn accelerometry: the German National Cohort (NAKO)

Large population-based cohort studies utilizing device-based measures of physical activity are crucial to close important research gaps regarding the potential protective effects of physical activity on chronic diseases. The present study details the quality control processes and the derivation of physical activity metrics from 100 Hz accelerometer data collected in the German National Cohort (NAKO). During the 2014 to 2019 baseline assessment, a subsample of NAKO participants wore a triaxial ActiGraph accelerometer on their right hip for seven consecutive days. Auto-calibration, signal feature calculations including Euclidean Norm Minus One (ENMO) and Mean Amplitude Deviation (MAD), identification of non-wear time, and imputation, were conducted using the R package GGIR version 2.10-3. A total of 73,334 participants contributed data for accelerometry analysis, of whom 63,236 provided valid data. The average ENMO was 11.7 ± 3.7 mg (milli gravitational acceleration) and the average MAD was 19.9 ± 6.1 mg. Notably, acceleration summary metrics were higher in men than women and diminished with increasing age. Work generated in the present study will facilitate harmonized analysis, reproducibility, and utilization of NAKO accelerometry data. The NAKO accelerometry dataset represents a valuable asset for physical activity research and will be accessible through a specified application process.

Risk of metabolic syndrome among law enforcement officers due to physical activity and posture behaviors

BACKGROUND

There are limited data on objectively measured activity and postural behaviors of law enforcement officers (LEOs) in relation to risk of metabolic syndrome (MetS).

OBJECTIVES

To examine the associations between objectively measured activity and postural behaviors and MetS risk among LEOs.

METHODS

Thirty-one LEOs, mean (SD) age 33 (10) years, participated in the study. LEOs had their metabolic risk factors measured using blood samples after fasting for at least 10 hours prior to testing. Participants wore activity-monitoring devices for 7 consecutive days during on-duty and off-duty shifts. Eighteen participants adhered to wearing the devices. Descriptive statistics were used to determine means for all MetS risk factors; time in intensity-specific physical activity behaviors; and time in various postural shifts. Correlation analyses were employed to examine relationships between activity behaviors, postures, and MetS risk factors.

RESULTS

Over half (51.6%; n = 16) of the participants had 2 or more positive MetS risk factors. Mean (SD) on-duty sedentary behavior was 273 (59) minutes compared with off-duty sedentary behavior of 401 (146) minutes. Mean on-duty moderate-intensity activity was 236 (40) minutes compared with off-duty moderate-intensity activity of 305 (80) minutes. Average on-duty sitting time was 435 (69) minutes compared with off-duty sitting time of 528 (142) minutes. Average on-duty standing time was 116 (43) minutes compared with off-duty standing time of 171 (51) minutes. There were negative correlations between on-duty sedentary activity and Systolic Blood Pressure (r = -0.48) and Diastolic Blood Pressure (r = -0.48), respectively.

CONCLUSIONS

Law enforcement officers have unfavorable activity and postural behaviors during a typical day regardless of working status and may be at risk for developing MetS.

Wrist-worn accelerometers: Influence of decisions during data collection and processing: A cross-sectional study

Background and Aims

Accelerometers collect data in an objective way, however, a number of decisions must be done during data collection, processing and output-interpretation. The influence of those decisions is seldom investigated, reported, or discussed. Herein, we examined the influence of different decisions on the outcomes: daily minutes of moderate-to-vigorous physical activity (MVPA), inactivity and light physical activity (LPA).

Methods

In total, 156 participants wore an accelerometer (ActiGraph wGT3X-BT) on their nondominant wrist for 7 days. Data collection was conducted from February 2017 to June 2018. Data was processed using the R-package GGIR and default settings were compared to by-the-literature-suggested options. The output was examined using paired t-tests.

Results

When comparing two commonly used MVPA-cut-points, default and Hildebrand et al. we found a marginal difference (0.4 min, 1.0%, p < 0.001) in MVPA/day. When no bout criteria for MVPA/day was applied, MVPA/day was twice as high as bouted MVPA/day. Further, when we changed the epoch-length from 5 to 1 s, statistically significant changes were seen for MVPA/day (-6.6 min, 19%, p < 0.001), inactivity/day (-22 min, 3.0%, p < 0.001) and LPA/day (28 min, 81%, p < 0.001).

Conclusion

Decisions made during data processing of wrist-worn accelerometers has an influence on the output and thus, may influence the conclusions drawn. However, there may be situations when these settings are changed. If so, we recommend examining if the variables of interest are affected. We encourage researchers to report decisions made during data collection, processing and output-interpretation, to facilitate comparisons between different studies.

Is Cognitive Reserve a Determinant of Functional and Mental Health in Older People of the Sardinian Blue Zone? A Mediational Approach

The main purpose of this study was to examine the mediating role of cognitive reserve in the relationship between functional health (expressed through the amount and intensity of performed physical activity objectively assessed using wearable accelerometers) and psychological well-being (i.e., assessed in terms of self-reported depressive signs) of older people living in an area of exceptional longevity, the so-called Sardinian Blue Zone. A further goal was to investigate the impact of gender on the cognitive reserve and physical health of our participants, using global cognitive functioning as a covariate. A battery of tests assessing motor efficiency, cognitive reserve, global cognitive functioning, and self-reported depressive symptoms was individually presented to 120 community dwellers (Mage = 82 years, SD = 8.4 years) of the Sardinian Blue Zone. Significant associations were found between cognitive reserve, motor efficiency, and self-reported depressive signs. Moreover, three mediation analyses documented that distinct indexes of cognitive reserve and motor efficiency explain 27.2-31% of the variance in the self-reported depression condition. Following this, it was also found that people with scarce cognitive reserve tended to exhibit significant signs of depression and showed worse motor abilities. In addition, after controlling for the effect of global cognitive functioning, motor efficiency, and cognitive reserve were generally more preserved in males than in females. Overall, these findings suggest that cognitive reserve is a compensatory resource that contributes significantly to the enhancement of health-related quality of life in the last decades of life.

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).

Effect of a Smartphone Application on Physical Activity and Weight Loss After Bariatric Surgery-Results from a Randomized Controlled Trial

PURPOSE

Ways to motivate and support patients in being physically active after bariatric surgery are needed. This trial was aimed at evaluating the effect of using a smartphone application targeting physical activity during 12 weeks on moderate-to-vigorous physical activity (MVPA, primary outcome) and secondary outcomes of inactivity, light physical activity (LPA), body mass index (BMI), and percent total weight loss (%TWL) after bariatric surgery.

MATERIALS AND METHODS

Data from a randomized controlled trial comprising 146 patients (79.5% women) undergoing bariatric surgery was analyzed. Mean age and BMI pre-surgery were 40.9 years and 40.5 kg/m2, respectively. Participants were randomized 1:1 to an intervention or a control group. Physical activity and body weight were objectively measured at baseline pre-surgery and post-surgery follow-ups after 6 weeks (weight only), 18 weeks, 6 months, and 1 year. Linear mixed models were fitted to assess longitudinal differences in outcomes between the groups.

RESULTS

A significant effect of the intervention (group-by-time interaction 16.2, 95% CI 3.5 to 28.9) was seen for MVPA at 18 weeks; the intervention group had increased their MVPA since baseline, while the control group had decreased their MVPA. The control group had lowered their BMI approximately 1 kg/m2 more than the intervention group at follow-up after 18 weeks and 12 months, yet, mean BMI did not differ between the groups. No intervention effect was seen on inactivity, LPA, or %TWL.

CONCLUSION

Our results indicate that use of a smartphone application targeting physical activity may have the potential to promote short-term MVPA post bariatric surgery.

TRIAL REGISTRATION

Clinicaltrials.gov : NCT03480464.

Investigating Wrist-Based Acceleration Summary Measures across Different Sample Rates towards 24-Hour Physical Activity and Sleep Profile Assessment

Wrist-worn wearable sensors have attracted considerable research interest because of their potential in providing continuous, longitudinal, non-invasive measurements, leading to insights into Physical Activity (PA), sleep, and circadian variability. Three key practical considerations for research-grade wearables are as follows: (a) choosing an appropriate sample rate, (b) summarizing raw three-dimensional accelerometry data for further processing (accelerometry summary measures), and (c) accurately estimating PA levels and sleep towards understanding participants' 24-hour profiles. We used the CAPTURE-24 dataset, where 148 participants concurrently wore a wrist-worn three-dimensional accelerometer and a wearable camera over approximately 24 h to obtain minute-by-minute labels: sleep; and sedentary light, moderate, and vigorous PA. We propose a new acceleration summary measure, the Rate of Change Acceleration Movement (ROCAM), and compare its performance against three established approaches summarizing three-dimensional acceleration data towards replicating the minute-by-minute labels. Moreover, we compare findings where the acceleration data was sampled at 10, 25, 50, and 100 Hz. We demonstrate the competitive advantage of ROCAM towards estimating the five labels (80.2% accuracy) and building 24-hour profiles where the sample rate of 10 Hz is fully sufficient. Collectively, these findings provide insights facilitating the deployment of large-scale longitudinal actigraphy data processing towards 24-hour PA and sleep-profile assessment.

Information and communication technology for physical activity in persons living with dementia: A systematic review with implications for evidence-based practice

BACKGROUND

Persons living with dementia often encounter many difficulties in their community due to functional limitations. Information and Communication Technology (ICT) could be useful to monitor changes in their physical function. However, there is a lack of systematic reviews about using ICT for physical activity.

AIM

This review aimed to synthesize the literature regarding the use of ICT to monitor the physical activity of persons living with dementia.

METHODS

A systematic search was conducted in five electronic databases using search terms derived from the Patient, Intervention, Comparison, Outcome (PICO) framework. We included articles published in English from 2011 to 2021. Quality of the included studies was evaluated by two independent authors using the Mixed Methods Appraisal Tool (MMAT).

RESULTS

Thirty-three quantitative studies were included for review. Included studies showed fairly good quality in the MMAT evaluation. Wearable devices were mainly employed (88%). The ICTs were used to objectively measure physical activity, activity status, gait, and circadian rhythm. ICTs have been utilized for four purposes: (1) comparing physical activity within the dementia subgroups or with the normal group, (2) exploring the relationship with other variables, 3) examining the experimental study's outcomes, and (4) checking the sensors' feasibility. The results demonstrated that ICT devices were feasible to use in persons living with dementia in the community, helpful for monitoring the physical activity of persons living with dementia, and useful for improving physical activity when properly incorporated in care planning.

LINKING EVIDENCE TO ACTION

ICTs can help gather objective data regarding the type, intensity, and level of physical activity in persons living with dementia without time constraints. Also, ICTs use in persons living with dementia in the community was acceptable. We suggest future studies to activate and use ICTs in dementia research.

Equivalence of activity outcomes derived from three research grade accelerometers worn simultaneously on each wrist

This study evaluated the equivalence of activity outcomes from three accelerometer brands worn on both wrists during free living. Forty-four adults wore a GENEActiv, ActiGraph and Axivity accelerometer for 7 days. Outcomes were assessed between and within accelerometer brand and wrist location with average acceleration and the intensity gradient (IG) being of particular interest. Pairwise 95% equivalence tests and intra-class correlation coefficients (ICC) evaluated agreement. Average acceleration and the IG were largely equivalent between combinations of accelerometer device and wrists when applying a 10% equivalence zone. There was largely a lack of equivalence between pairings for time spent in acceleration values ≥100 mg. However, equivalence was largely achieved when applying an equivalence zone that encompassed values ranging from 0.3 to 0.45 SDs for IG and time spent above 100 mg and 150 mg. Agreement between pairings tended to be stronger between different brands on the non-dominant (ICCs ≥ 0.73-0.97) versus the dominant wrist (ICCs ≥ 0.57-0.97) and between wrists for the same accelerometer (ICCs ≥ 0.59-0.97) for average acceleration and the IG. These are important findings since device placement is not consistent in studies. Further work that applies an equivalence zone reflecting the variability of the outcome measure is encouraged.

RELATIONSHIP BETWEEN PHYSICAL ACTIVITY PARTICIPATION AND RECOVERY OUTCOMES IN COLLEGE-AGED ADULTS WITH A CONCUSSION

CONTEXT

Previously, the most common treatment for a concussion was prolonged physical and cognitive rest. Recent research suggests that earlier physical activity (PA) may be better at promoting recovery. Research has not evaluated the relationship between free-living PA (e.g., walking) and symptom reporting or recovery duration.

OBJECTIVE

To assess the relationship between free-living physical activity (PA) participation and two recovery outcomes in college-aged adults with a concussion.

DESIGN

Prospective Cohort Setting: Division 1 & 3 Universities Participants: Thirty-two college-aged adults (68.8% female, age: 19.8±1.4) with a concussion.

MAIN OUTCOME MEASURES

Participants completed a post-concussion symptom evaluation at visits 1 (<72 hours from concussion) and 2 (8 days later). Between visits, participants' PA was monitored using an Actigraph GT9X Link PA monitor and expressed as total PA (counts per minute) and percent time of PA spent in moderate-to-vigorous intensity (%MVPA). Recovery time was the number of days from injury occurrence to medical clearance. Separate hierarchical multiple regressions evaluated the relationship between total PA and each recovery variable (visit 2 symptom severity, recovery time). Additionally, separate exploratory hierarchical multiple regressions evaluated the relationship between %MVPA and each recovery variable. Statistical significance was set a priori at p ≤ .05.

RESULTS

Participants averaged 2446±441 counts per minute and spent 12.1±4.2% of their PA performing MVPA. Participants yielded median symptom severities of 28[24] and 2[8] for visit 1 and 2, respectively. Average recovery time was 14.7±7.5 days. Total PA did not significantly contribute to the model for visit 2 symptom severity (p=.122) or recovery time (p=.301). Similarly, %MVPA had little contribution to the model for visit 2 symptom severity (p=.358) or recovery time (p=.276).

CONCLUSION

Results suggest that free-living PA may not be enough to reduce symptoms or shorten recovery. Thus, clinicians may need to provide patients with more structured PA protocols mimicking previous research.

Generation and validation of ActiGraph GT3X+ accelerometer cut-points for assessing physical activity intensity in older adults. The OUTDOOR ACTIVE validation study

The study of physical activity in older adults is becoming more and more relevant. For evaluation of physical activity recommendations, intensity-specific accelerometer cut-points are utilized. However, research on accelerometer cut-points for older adults is still scarce. The aim of the study was to generate placement-specific cut-points of ActiGraph GT3X+ activity counts and raw measures of acceleration to determine physical activity intensity in older adults. A further aim was to compare the validity of the generated cut-points for a range of different physical activities. The study was a single experimental trial using a convenience sample. Study participants were 20 adults aged 59 to 73 years. Accelerometers were worn at six different placements (one on each wrist, one on each ankle, and two at the hip) and breath-by-breath indirect calorimetry was used as the reference for energy. The experiment comprised of two parts; a) The first required participants to walk on a treadmill at incremental speeds (3.0-5.0 km·h-1), and b) Five different everyday activities (reading, cleaning, shopping, cycling, aerobics) were staged in the laboratory setting. Accelerometer cut-points (activity counts, raw data) were derived for each of the investigated placements by linear regression using the treadmill part. Performance of the cut-points was assessed by applying the cut-points to the everyday activities. We provide cut-points for six placements and two accelerometer metrics in the specific age group. However, the derived cut-points did not outperform published ones. More research and innovative approaches are needed for improving internal and external validity of research results across populations and age groups.

The Effect of Sensor Placement and Number on Physical Activity Recognition and Energy Expenditure Estimation in Older Adults: Validation Study

BACKGROUND

Research has shown the feasibility of human activity recognition using wearable accelerometer devices. Different studies have used varying numbers and placements for data collection using sensors.

OBJECTIVE

This study aims to compare accuracy performance between multiple and variable placements of accelerometer devices in categorizing the type of physical activity and corresponding energy expenditure in older adults.

METHODS

In total, 93 participants (mean age 72.2 years, SD 7.1) completed a total of 32 activities of daily life in a laboratory setting. Activities were classified as sedentary versus nonsedentary, locomotion versus nonlocomotion, and lifestyle versus nonlifestyle activities (eg, leisure walk vs computer work). A portable metabolic unit was worn during each activity to measure metabolic equivalents (METs). Accelerometers were placed on 5 different body positions: wrist, hip, ankle, upper arm, and thigh. Accelerometer data from each body position and combinations of positions were used to develop random forest models to assess activity category recognition accuracy and MET estimation.

RESULTS

Model performance for both MET estimation and activity category recognition were strengthened with the use of additional accelerometer devices. However, a single accelerometer on the ankle, upper arm, hip, thigh, or wrist had only a 0.03-0.09 MET increase in prediction error compared with wearing all 5 devices. Balanced accuracy showed similar trends with slight decreases in balanced accuracy for the detection of locomotion (balanced accuracy decrease range 0-0.01), sedentary (balanced accuracy decrease range 0.05-0.13), and lifestyle activities (balanced accuracy decrease range 0.04-0.08) compared with all 5 placements. The accuracy of recognizing activity categories increased with additional placements (accuracy decrease range 0.15-0.29). Notably, the hip was the best single body position for MET estimation and activity category recognition.

CONCLUSIONS

Additional accelerometer devices slightly enhance activity recognition accuracy and MET estimation in older adults. However, given the extra burden of wearing additional devices, single accelerometers with appropriate placement appear to be sufficient for estimating energy expenditure and activity category recognition in older adults.

Clinical and demographic correlates of accelerometer-measured physical activity in participants enrolled in the OPTIMISE HFpEF study

AIMS

This study aimed to measure physical activity (PA) in participants with suspected heart failure with preserved ejection fraction (HFpEF) and assess associations between PA and participant characteristics.

METHODS AND RESULTS

Adults with presumed HFpEF were recruited and received diagnostic evaluation and clinical assessment. Physical activity was objectively measured using accelerometers over 7 days. To examine predictors of PA, a best subset analysis was used, with the optimal model defined as that with the lowest Bayesian information criterion. One hundred and twenty-four participants with presumed HFpEF who had valid accelerometer data were included in this study. Seventy-six were confirmed by a cardiologist as meeting the European Society of Cardiology diagnosis criteria for HFpEF. The median age of all participants was 80.1 years, and 47.4% were female. Patients spent most of each 24-h period at low-intensity PA and few or no durations at high-intensity PA, with lower activity for those with HFpEF. Gait speed was the best univariate correlate of activity levels (adjusted R2 0.29). The optimal model using best subsets regression included six variables and improved adjusted R2 to 0.47. In the model, lower levels of PA were associated with slower gait speed, lower levels of anxiety, higher levels of depression, past smoking history, a confirmed HFpEF diagnosis, and higher body mass index.

CONCLUSION

Participants demonstrated very low PA levels. The study has identified important patient characteristics associated with PA, which may help to identify those most in need of interventions. Notably, participants with confirmed HFpEF were more inactive than participants with other heart failure phenotypes.

What gait features influence the amount and intensity of physical activity in people with multiple sclerosis?

Although the mutual relationship between ambulation and physical activity (PA) in people with multiple sclerosis (pwMS) has been described in several studies, there is still a lack of detailed information about the way in which specific aspects of the gait cycle are associated with amount and intensity of PA. This study aimed to verify the existence of possible relationships among PA parameters and the spatio-temporal parameters of gait when both are instrumentally assessed.Thirty-one pwMS (17F, 14 M, mean age 52.5, mean Expanded Disability Status Scale (EDSS) score 3.1) were requested to wear a tri-axial accelerometer 24 hours/day for 7 consecutive days and underwent an instrumental gait analysis, performed using an inertial sensor located on the low back, immediately before the PA assessment period. Main spatio-temporal parameters of gait (i.e., gait speed, stride length, cadence and duration of stance, swing, and double support phase) were extracted by processing trunk accelerations. PA was quantified using average number of daily steps and percentage of time spent at different PA intensity, the latter calculated using cut-point sets previously validated for MS. The existence of possible relationships between PA and gait parameters was assessed using Spearman rank correlation coefficient rho.Gait speed and stride length were the parameters with the highest number of significant correlations with PA features. In particular, they were found moderately to largely correlated with number of daily steps (rho 0.62, P< .001), percentage of sedentary activity (rho = -0.44, P < .001) and percentage of moderate-to-vigorous activity (rho = 0.48, P < .001). Small to moderate significant correlations were observed between PA intensity and duration of stance, swing and double support phases.The data obtained suggest that the most relevant determinants associated with higher and more intense levels of PA in free-living conditions are gait speed and stride length. The simultaneous quantitative assessment of gait parameters and PA levels might represent a useful support for physical therapists in tailoring optimized rehabilitative and training interventions.

The Validity of MotionSense HRV in Estimating Sedentary Behavior and Physical Activity under Free-Living and Simulated Activity Settings

MotionSense HRV is a wrist-worn accelerometery-based sensor that is paired with a smartphone and is thus capable of measuring the intensity, duration, and frequency of physical activity (PA). However, little information is available on the validity of the MotionSense HRV. Therefore, the purpose of this study was to assess the concurrent validity of the MotionSense HRV in estimating sedentary behavior (SED) and PA. A total of 20 healthy adults (age: 32.5 ± 15.1 years) wore the MotionSense HRV and ActiGraph GT9X accelerometer (GT9X) on their non-dominant wrist for seven consecutive days during free-living conditions. Raw acceleration data from the devices were summarized into average time (min/day) spent in SED and moderate-to-vigorous PA (MVPA). Additionally, using the Cosemed K5 indirect calorimetry system (K5) as a criterion measure, the validity of the MotionSense HRV was examined in simulated free-living conditions. Pearson correlations, mean absolute percent errors (MAPE), Bland–Altman (BA) plots, and equivalence tests were used to examine the validity of the MotionSense HRV against criterion measures. The correlations between the MotionSense HRV and GT9X were high and the MAPE were low for both the SED (r = 0.99, MAPE = 2.4%) and MVPA (r = 0.97, MAPE = 9.1%) estimates under free-living conditions. BA plots illustrated that there was no systematic bias between the MotionSense HRV and criterion measures. The estimates of SED and MVPA from the MotionSense HRV were significantly equivalent to those from the GT9X; the equivalence zones were set at 16.5% for SED and 29% for MVPA. The estimates of SED and PA from the MotionSense HRV were less comparable when compared with those from the K5. The MotionSense HRV yielded comparable estimates for SED and PA when compared with the GT9X accelerometer under free-living conditions. We confirmed the promising application of the MotionSense HRV for monitoring PA patterns for practical and research purposes.

Does Multiple Sclerosis Differently Impact Physical Activity in Women and Man? A Quantitative Study Based on Wearable Accelerometers

In people with multiple sclerosis (pwMS), fatigue, weakness and spasticity may reduce mobility and promote sedentary behavior. However, little is known about the existence of possible differences in the way MS modifies the propensity to perform physical activity (PA) in men and women. The present study aimed to partly close this gap by means of quantitative analysis carried out using wearable sensors. Forty-five pwMS (23 F, 22 M, mean age 50.3) and 41 unaffected age- and sex-matched individuals wore a tri-axial accelerometer 24 h/day for 7 consecutive days. Raw data were processed to calculate average number of daily steps, vector magnitude (VM) counts, and percentage of time spent in sedentary behavior and in PA of different intensities (i.e., light and moderate-to-vigorous, MVPA). Women with MS spent more time in sedentary behavior and exhibited a reduced amount of light intensity activity with respect to men, while MVPA was similar across sexes. However, in comparison with unaffected individuals, the overall PA patterns appear significantly modified mostly in women who, in presence of the disease, present increased sedentary behavior, reduced MVPA, number of daily steps and VM counts. The findings of the present study highlight the urgency of including sex as variable in all studies on PA in pwMS.

The benefits of daily exercise on blood glucose levels and affect among adults with type 1 diabetes

The purpose of this study was to investigate the concurrent and lagged effects of daily exercise on daily blood glucose level and affect among persons with type 1 diabetes (T1D). 199 persons with T1D (M_age = 46.82) completed a 14-day diary in which they reported on their engagement in moderate to vigorous exercise for 30 min and positive and negative affect. Daily blood glucose (BG) was gathered through study-provided glucometers. Multilevel modeling examined the effects of daily variability in (within-person effects) and average levels of (between-person effects) daily exercise on BG and affect. On days when persons with T1D reported they exercised moderately to vigorously for 30 min, they had lower mean BG, higher risk for low BG, lower negative affect, and higher positive affect on the same day as well as lower mean BG on the following day. Engaging in daily exercise is important in managing daily blood glucose and affect among persons with T1D, but can be complicated by hypoglycemia.

Evaluating the performance of raw and epoch non-wear algorithms using multiple accelerometers and electrocardiogram recordings

Accurate detection of accelerometer non-wear time is crucial for calculating physical activity summary statistics. In this study, we evaluated three epoch-based non-wear algorithms (Hecht, Troiano, and Choi) and one raw-based algorithm (Hees). In addition, we performed a sensitivity analysis to provide insight into the relationship between the algorithms’ hyperparameters and classification performance, as well as to generate tuned hyperparameter values to better detect episodes of wear and non-wear time. We used machine learning to construct a gold-standard dataset by combining two accelerometers and electrocardiogram recordings. The Hecht and Troiano algorithms achieved poor classification performance, while Choi exhibited moderate performance. Meanwhile, Hees outperformed all epoch-based algorithms. The sensitivity analysis and hyperparameter tuning revealed that all algorithms were able to achieve increased classification performance by employing larger intervals and windows, while more stringently defining artificial movement. These classification gains were associated with the ability to lower the false positives (type I error) and do not necessarily indicate a more accurate detection of the total non-wear time. Moreover, our results indicate that with tuned hyperparameters, epoch-based non-wear algorithms are able to perform just as well as raw-based non-wear algorithms with respect to their ability to correctly detect true wear and non-wear episodes.

Comparability of accelerometer signal aggregation metrics across placements and dominant wrist cut points for the assessment of physical activity in adults

Large epidemiological studies that use accelerometers for physical behavior and sleep assessment differ in the location of the accelerometer attachment and the signal aggregation metric chosen. This study aimed to assess the comparability of acceleration metrics between commonly-used body-attachment locations for 24 hours, waking and sleeping hours, and to test comparability of PA cut points between dominant and non-dominant wrist. Forty-five young adults (23 women, 18–41 years) were included and GT3X + accelerometers (ActiGraph, Pensacola, FL, USA) were placed on their right hip, dominant, and non-dominant wrist for 7 days. We derived Euclidean Norm Minus One g (ENMO), Low-pass filtered ENMO (LFENMO), Mean Amplitude Deviation (MAD) and ActiGraph activity counts over 5-second epochs from the raw accelerations. Metric values were compared using a correlation analysis, and by plotting the differences by time of the day. Cut points for the dominant wrist were derived using Lin’s concordance correlation coefficient optimization in a grid of possible thresholds, using the non-dominant wrist estimates as reference. They were cross-validated in a separate sample (N = 36, 10 women, 22–30 years). Shared variances between pairs of acceleration metrics varied across sites and metric pairs (range in r²: 0.19–0.97, all p < 0.01), suggesting that some sites and metrics are associated, and others are not. We observed higher metric values in dominant vs. non-dominant wrist, thus, we developed cut points for dominant wrist based on ENMO to classify sedentary time (<50 mg), light PA (50–110 mg), moderate PA (110–440 mg) and vigorous PA (≥440 mg). Our findings suggest differences between dominant and non-dominant wrist, and we proposed new cut points to attenuate these differences. ENMO and LFENMO were the most similar metrics, and they showed good comparability with MAD. However, counts were not comparable with ENMO, LFENMO and MAD.

Comparison of accelerometer-derived physical activity levels between individuals with and without cancer: a UK Biobank study

Aim: To identify the difference in physical activity (PA) levels between individuals with and without cancer, and to estimate all-cause mortality associated with this difference. Methods: Current cancer, cancer survivor and cancer-free groups were identified from the UK Biobank. We used multivariate and Cox regression to estimate PA differences and association of PA with all-cause mortality. Results: Compared with the cancer-free individuals, participants in the two cancer groups had fewer minutes in moderate-to-vigorous PA per day in adjusted analyses. The PA difference was associated with higher mortality in the current cancer group. Conclusion: Patients with a history of cancer were less active than those without cancer, and PA is associated with increased mortality. PA improvement strategies in cancer patients must be explored.

Providing a Basis for Harmonization of Accelerometer-Assessed Physical Activity Outcomes Across Epidemiological Datasets

Introduction: To capitalize on the increasing availability of accelerometry data for epidemiological research it is desirable to compare and/or pool data from surveys worldwide. This study aimed to establish whether free-living physical activity outcomes can be considered equivalent between three research-grade accelerometer brands worn on the dominant and non-dominant wrist. Of prime interest were the average acceleration (ACC) and the intensity gradient (IG). These two metrics describe the volume and intensity of the complete activity profile; further, they are comparable across populations making them ideal for comparing and/or pooling activity data. Methods: Forty-eight adults wore a GENEActiv, Axivity, and ActiGraph on both wrists for up to 7-days. Data were processed using open-source software (GGIR) to generate physical activity outcomes, including ACC and IG. Agreement was assessed using pairwise 95% equivalence tests (±10% equivalence zone) and intra-class correlation coefficients (ICC). Results: ACC was equivalent between brands when measured at the non-dominant wrist (ICC ≥ 0.93), but approximately 10% higher when measured at the dominant wrist (GENEActiv and Axivity only, ICC ≥ 0.83). The IG was equivalent irrespective of monitor brand or wrist (ICC ≥ 0.88). After adjusting ACC measured at the dominant wrist by −10% (GENEActiv and Axivity only), ACC was also within (or marginally outside) the 10% equivalence zone for all monitor pairings. Conclusion: If average acceleration is decreased by 10% for studies deploying monitors on the dominant wrist (GENEActiv and Axivity only), ACC and IG may be suitable for comparing and/or collating physical activity outcomes across accelerometer datasets, regardless of monitor brand and wrist.

On Placement, Location and Orientation of Wrist-Worn Tri-Axial Accelerometers during Free-Living Measurements

Wearable accelerometers have recently become a standalone tool for the objective assessment of physical activity (PA). In free-living studies, accelerometers are placed by protocol on a pre-defined body location (e.g., non-dominant wrist). However, the protocol is not always followed, e.g., the sensor can be moved between wrists or reattached in a different orientation. Such protocol violations often result in PA miscalculation. We propose an approach, PLOE ("Placement, Location and Orientation Evaluation method"), to determine the sensor position using statistical features from the raw accelerometer measurements. We compare the estimated position with the study protocol and identify discrepancies. We apply PLOE to the measurements collected from 45 older adults who wore ActiGraph GT3X+ accelerometers on the left and right wrist for seven days. We found that 15.6% of participants who wore accelerometers violated the protocol for one or more days. The sensors were worn on the wrong hand during 6.9% of the days of simultaneous wearing of devices. During the periods of discrepancies, the daily PA was miscalculated by more than 20%. Our findings show that correct placement of the device has a significant effect on the PA estimates. These results demonstrate a need for the evaluation of sensor position.