Assessing sedentary behavior with the GENEActiv: introducing the sedentary sphere

Accelerometer-Measured Physical Activity, Fitness and Indicators of Cardiometabolic Risk among Rural Adolescents: A Cross-Sectional Study at 15-Year Follow-up of the MINIMat Cohort

BACKGROUND

Little is known about the relationship of physical activity (PA) and fitness with cardiometabolic risk among rural adolescents in low- and middle-income countries. Thus, we examined the associations of PA and fitness with selected cardiometabolic indicators along with potential gender-based differences in a birth cohort of rural adolescents from southeast Bangladesh.

METHODS

We utilized data from the 15-year follow-up of Maternal and Infant Nutrition Interventions in Matlab (MINIMat) cohort (n = 2253). Wrist-worn ActiGraph wGT3x-BT accelerometers were used to estimate sedentary time (ST) and PA. Fitness was assessed using: handgrip strength, standing long jump, and Chester Step Test. Anthropometric parameters, systolic blood pressure (SBP), and fasting lipid, insulin and glucose levels were measured. We calculated insulin resistance using the Homeostasis Model Assessment equation (HOMA-IR). Linear regression and isotemporal substitution models were fitted.

RESULTS

The adolescents spent 64 min/day (inter-quartile range: 50-81) in moderate-to-vigorous physical activity (MVPA). A 10-minute-per-day higher vigorous PA (VPA) was associated with: 4.9% (95% confidence interval (CI): 2.9-6.8%) lower waist circumference (WC), 3.2 mmHg (95% CI: 1.5-4.8) lower SBP, 10.4% (95% CI: 2.9-17.3%) lower TG, and 24.4% (95% CI: 11.3-34.9%) lower HOMA-IR. MVPA showed similar associations of notably smaller magnitude. Except for WC, the associations were more pronounced among the boys. Substituting ST with VPA of equal duration was associated with lower WC, SBP, triglyceride and HOMA-IR. Grip strength was favorably associated with all indicators, displaying considerably large effect sizes.

CONCLUSION

Our findings indicated beneficial roles of PA- particularly VPA- and muscular fitness in shaping cardiometabolic profile in mid-adolescence. VPA and grip strength may represent potential targets for preventive strategies tailored to adolescents in resource-limited settings.

Physical Activity Patterns Within Dementia Care Dyads

Previous research has explored the physical activity habits of people with dementia and their family carers separately, with little consideration of how physical habits are associated within dyads. In this observational study, we sought to explore the relationship between people with dementia and their carers' physical activity, at a group level and at a dyadic level. Twenty-six participant dyads (persons with dementia and their carer spouses) were asked to wear an accelerometer for 30 days continuously. Comparisons were made at a group level and a dyadic level. People with dementia did not participate in significantly more moderate to vigorous physical activity (M = 15.44 min/day; SD = 14.40) compared with carers (M = 17.95 min/day; SD = 17.01). Within dyads, there were moderately strong associations between daily moderate to vigorous physical activity (r = .48-.54), but not with overall activity levels (r = .24). Despite physical activity habits remaining relatively low within people with dementia and carers, respectively, moderate to vigorous physical activity levels appear to be correlated within dyads. Understanding mutual influence on physical activity levels within dyads is an important pathway to promote an active lifestyle.

A review of the evidence for the utility of physical activity monitor use in patients with idiopathic inflammatory myopathies

Few proven therapies exist for patients with idiopathic inflammatory myopathies (IIMs), partly due to the lack of reliable and valid outcome measures for assessing treatment responses. The current core set measures developed by the International Myositis Assessment and Clinical Studies group were developed to standardize assessments of disease activity and treatment effect. None of the current measures address functional improvement in muscle weakness. Therefore, supplemental measures to more objectively assess physical activity levels and fatiguability in free-living settings are needed to assess disease activity more comprehensively. Validated physical activity monitors (PAMs) have the potential to serve as an objective functional outcome measure in clinical trials and observational studies. This review examines the current evidence for the use of body-worn PAMs in clinical settings with IIM patients. A practical overview of methods for PAM use in clinical patient populations (including measurement details and data processing) that focuses on IIM patients is also presented.

Effects of dietary nitrate and vitamin C co-ingestion on blood pressure and hand-grip strength in young adults

Background: Co-administration of vitamin C and inorganic nitrate ([Formula: see text]) may reduce oxidative stress, boost the conversion of nitrite ([Formula: see text]) into NO and elicit positive vascular effects. Aims: We aimed to test the effects of oral inorganic [Formula: see text] and vitamin C co-supplementation on vascular function, muscular strength, and on concentrations of urinary [Formula: see text], vitamin C, 8-isoprostanes and salivary [Formula: see text] in healthy young adults. Methods: Ten young healthy participants were enrolled in a randomised, double-blind (only for the [Formula: see text] intervention) crossover clinical trial. Participants consumed in random order: 1) nitrate-rich beetroot juice and vitamin C (N+VC), 2) nitrate-rich beetroot juice alone (N) or 3) nitrate-depleted beetroot juice alone (ND). Resting blood pressure (BP) was measured at the research centre and at home. Non-invasive, continuous measurements of BP and cardiac function parameters were performed using a Finometer device. Free-living physical activity and hand-grip strength were assessed. Salivary [Formula: see text] and [Formula: see text] and urinary [Formula: see text], 8-isoprostanes and vitamin C concentrations were measured. Results: There were no significant differences for any of the vascular outcomes between the three interventions groups. However, analyses of within-intervention changes showed a significant lower daily systolic BP in the [Formula: see text]+vitamin C (N+VC) group only (P=0.04). Urinary [Formula: see text] (P=0.002) and salivary [Formula: see text] (P=0.001) were significantly higher in the N+VC group compared to the N and ND groups. Conclusion: These preliminary findings suggest that combining dietary [Formula: see text] with vitamin C could have protective effects on vascular function in young adults and could represent an effective strategy for the maintenance of healthy cardiovascular trajectories.

Comparison of raw accelerometry data from ActiGraph, Apple Watch, Garmin, and Fitbit using a mechanical shaker table

The purpose of this study was to evaluate the reliability and validity of the raw accelerometry output from research-grade and consumer wearable devices compared to accelerations produced by a mechanical shaker table. Raw accelerometry data from a total of 40 devices (i.e., n = 10 ActiGraph wGT3X-BT, n = 10 Apple Watch Series 7, n = 10 Garmin Vivoactive 4S, and n = 10 Fitbit Sense) were compared to reference accelerations produced by an orbital shaker table at speeds ranging from 0.6 Hz (4.4 milligravity-mg) to 3.2 Hz (124.7mg). Two-way random effects absolute intraclass correlation coefficients (ICC) tested inter-device reliability. Pearson product moment, Lin's concordance correlation coefficient (CCC), absolute error, mean bias, and equivalence testing were calculated to assess the validity between the raw estimates from the devices and the reference metric. Estimates from Apple, ActiGraph, Garmin, and Fitbit were reliable, with ICCs = 0.99, 0.97, 0.88, and 0.88, respectively. Estimates from ActiGraph, Apple, and Fitbit devices exhibited excellent concordance with the reference CCCs = 0.88, 0.83, and 0.85, respectively, while estimates from Garmin exhibited moderate concordance CCC = 0.59 based on the mean aggregation method. ActiGraph, Apple, and Fitbit produced similar absolute errors = 16.9mg, 21.6mg, and 22.0mg, respectively, while Garmin produced higher absolute error = 32.5mg compared to the reference. ActiGraph produced the lowest mean bias 0.0mg (95%CI = -40.0, 41.0). Equivalence testing revealed raw accelerometry data from all devices were not statistically significantly within the equivalence bounds of the shaker speed. Findings from this study provide evidence that raw accelerometry data from Apple, Garmin, and Fitbit devices can be used to reliably estimate movement; however, no estimates were statistically significantly equivalent to the reference. Future studies could explore device-agnostic and harmonization methods for estimating physical activity using the raw accelerometry signals from the consumer wearables studied herein.

Improving wheelchair user sitting posture to alleviate lumbar fatigue: a study utilizing sEMG and pressure sensors

Background

The wheelchair is a widely used rehabilitation device, which is indispensable for people with limited mobility. In the process of using a wheelchair, they often face the situation of sitting for a long time, which is easy to cause fatigue of the waist muscles of the user. Therefore, this paper hopes to provide more scientific guidance and suggestions for the daily use of wheelchairs by studying the relationship between the development of muscle fatigue and sitting posture.

Methods

First, we collected surface Electromyography (sEMG) of human vertical spine muscle and analyzed it in the frequency domain. The obtained Mean Power Frequency (MPF) was used as the dependent variable. Then, the pose information of the human body, including the percentage of pressure points, span, and center of mass as independent variables, was collected by the array of thin film pressure sensors, and analyzed by a multivariate nonlinear regression model.

Results

When the centroid row coordinate of the cushion pressure point is about 16(range, 7.7-16.9), the cushion pressure area percentage is about 80%(range, 70.8%-89.7%), and the cushion pressure span range is about 27(range, 25-31), the backrest pressure point centroid row coordinate is about 15(range, 9.1-18.2), the backrest pressure area percentage is about 35%(range, 11.8%-38.7%), and the backrest pressure span range is about 16(range, 9-22). At this time, the MPF value of the subjects decreased by a small percentage, and the fatigue development of the muscles was slower. In addition, the pressure area percentage at the seat cushion is a more sensitive independent variable, too large or too small pressure area percentage will easily cause lumbar muscle fatigue.

Conclusion

The results show that people should sit in the middle and back of the seat cushion when riding the wheelchair, so that the Angle of the hip joint can be in a natural state, and the thigh should fully contact the seat cushion to avoid the weight of the body concentrated on the buttocks; The back should be fully in contact with the back of the wheelchair to reduce the burden on the waist, and the spine posture can be adjusted appropriately according to personal habits, but it is necessary to avoid maintaining a chest sitting position for a long time, which will cause the lumbar spine to be in an unnatural physiological Angle and easily lead to fatigue of the waist muscles.

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.

Mobility level and factors affecting mobility status in hospitalized patients admitted in single-occupancy patient rooms

BACKGROUND

Although stimulating patients' mobility is considered a component of fundamental nursing care, approximately 35% of hospitalized patients experience functional decline during or after hospital admission. The aim of this study is to assess mobility level and to identify factors affecting mobility status in hospitalized patients admitted in single-occupancy patient rooms (SPRs) on general wards.

METHODS

Mobility level was quantified with the Johns Hopkins Highest Level of Mobility Scale (JH-HLM) and EQ-5D-3L. GENEActiv accelerometer data over 24 h were collected in a subset of patients. Data were analyzed using generalized ordinal logistic regression analysis. The STROBE reporting checklist was applied.

RESULTS

Wearing pajamas during daytime, having pain, admission in an isolation room, and wearing three or more medical equipment were negatively associated with mobilization level. More than half of patients (58.9%) who were able to mobilize according to the EQ-5D-3L did not achieve the highest possible level of mobility according to the JH-HLM. The subset of patients that wore an accelerometer spent most of the day in sedentary behavior (median 88.1%, IQR 85.9-93.6). The median total daily step count was 1326 (range 22-5362).

CONCLUSION

We found that the majority of participating hospitalized patients staying in single-occupancy patient rooms were able to mobilize. It appeared, however, that most of the patients who are physically capable of walking, do not reach the highest possible level of mobility according to the JH-HLM scale. Nurses should take their responsibility to ensure that patients achieve the highest possible level of mobility.

Determination of cut-off points for the Move4 accelerometer in children aged 8-13 years

BACKGROUND

To assess physical activity (PA) there is a need of objective, valid and reliable measurement methods like accelerometers. Before these devices can be used for research, they need to be calibrated and validated for specific age groups as the locomotion differs between children and adults, for instance. Therefore, the aim of the present study was the calibration and validation of the Move4 accelerometer for children aged 8-13 years.

METHODS

53 normal weighted children (52% boys, 48%girls) aged 8-13 years (mean age = 10.69 ± 1.46, mean BMI = 17.93 kg/m- 2, 60th percentile), wore the Move4 sensor at four different body positions (thigh, hip, wrist and the Move4ecg including heart rate measurement at the chest). They completed nine activities that considered the four activity levels (sedentary behavior (SB), light PA (LPA), moderate PA (MPA) and vigorous PA (VPA)) within a test-retest design. Intensity values were determined using the mean amplitude deviation (MAD) as well as the movement acceleration intensity (MAI) metrics. Determination of activities and energy expenditure was validated using heart rate. After that, cut-off points were determined in Matlab by using the Classification and Regression Trees (CART) method. The agreement for the cut-off points between T1 and T2 was analyzed.

RESULTS

MAD and MAI accelerometer values were lowest when children were lying on the floor and highest when running or doing jumping jacks. The mean correlation coefficient between acceleration values and heart rate was 0.595 (p = 0.01) for MAD metric and 0.611 (p = 0.01) for MAI metric, indicating strong correlations. Further, the MAD cut-off points for SB-LPA are 52.9 mg (hip), 62.4 mg (thigh), 86.4 mg (wrist) and 45.9 mg (chest), for LPA-MPA they are 173.3 mg (hip), 260.7 mg (thigh), 194.4 mg (wrist) and 155.7 mg (chest) and for MPA-VPA the cut-off points are 543.6 mg (hip), 674.5 mg (thigh), 623.4 mg (wrist) and 545.5 mg (chest). Test-retest comparison indicated good values (mean differences = 9.8%).

CONCLUSION

This is the first study investigating cut-off points for children for four different sensor positions using raw accelerometer metrics (MAD/MAI). Sensitivity and specificity revealed good values for all positions. Nevertheless, depending on the sensor position, metric values differ according to the different involvement of the body in various activities. Thus, the sensor position should be carefully chosen depending on the research question of the study.

Comparison of postoperative mobilization measurements by activPAL versus Johns Hopkins Highest Level of Mobility scale after major abdominal surgery

BACKGROUND

The Johns Hopkins Highest Level of Mobility scale is a validated tool for assessing patient mobility in the hospital. It has excellent inter-rater and test-retest reliabilities, but it is unknown how accurately Johns Hopkins Highest Level of Mobility documentation reflects the patients' mobility performance in the immediate postoperative period compared to objective measures such as accelerometers.

METHODS

In this single-center observational study, consented adults undergoing open abdominal surgery wore a research-grade accelerometer, activPAL, starting immediately postoperatively until hospital discharge or up to 7 days. We collected the Johns Hopkins Highest Level of Mobility scores documented by hospital staff via retrospective chart review and evaluated their accuracy in describing the type, frequency, and volume of postoperative out-of-bed mobilization using the activPAL as the criterion.

RESULTS

We analyzed data from 56 participants. The activPAL showed that participants spent 97.7% of their time lying in bed or sitting in a chair. Meanwhile, the Johns Hopkins Highest Level of Mobility documentation of preambulatory activities (scores 1-5) was rare. The activPAL detected 4 times more out-of-bed mobilization than routine Johns Hopkins Highest Level of Mobility documentation. Whereas the frequency of activPAL-measured out-of-bed mobilization increased steadily to a median of 9 sessions by postoperative day 6, the number of Johns Hopkins Highest Level of Mobility documentation remained around twice daily. ActivPAL measurements demonstrated that Johns Hopkins Highest Level of Mobility documentation of ambulatory sessions (scores 6-8) was accurate.

CONCLUSIONS

We found that routine Johns Hopkins Highest Level of Mobility documentation did not accurately detect preambulatory activities or the overall frequency of out-of-bed mobility sessions, poorly reflecting the highly sedentary behaviors of the acute postoperative inpatients and highlighting the need to improve clinical documentation or use alternative methods to track postoperative mobilization.

Feasibility and Acceptability of an INtervention TO Increase MOBility in Older Hospitalized Medical Patients (INTOMOB): A Mixed-Methods Pilot Study

Background: To reduce adverse outcomes of low hospital mobility, we need interventions that are scalable in everyday practice. This study assessed the feasibility and acceptability of the INTOMOB multilevel intervention addressing barriers to hospital mobility without requiring unavailable resources. Methods: The INTOMOB intervention, targeting older patients, healthcare professionals (HCPs) and the hospital environment, was implemented on acute general internal medicine wards of three hospitals (12/2022-03/2023). Feasibility and acceptability of the intervention were assessed and two types of accelerometers compared in a mixed methods study (patient and HCP surveys and interviews). Quantitative data were analyzed descriptively and qualitative data using a deductive approach. Results were integrated through meta-inferences. Results: Of 20 patients (mean age 74.1 years), 90% found the intervention helpful and 82% said the environment intervention (posters) stimulated mobility. The majority of 44 HCPs described the intervention as clear and helpful. There was no major implementation or technical issue. About 60% of patients and HCPs preferred a wrist-worn over an ankle-worn accelerometer. Conclusions: The INTOMOB intervention is feasible and well accepted. Patients' and HCPs' feedback allowed to further improve the intervention that will be tested in a cluster randomized trial and provides useful information for future mobility-fostering interventions.

Within-day bidirectional associations between physical activity and affect: A real-time ambulatory study in persons with and without depressive and anxiety disorders

BACKGROUND

Ambulatory assessments offer opportunities to study physical activity level (PAL) and affect at the group and person-level. We examined bidirectional associations between PAL and affect in a 3-h timeframe and evaluated whether associations differ between people with and without current or remitted depression/anxiety.

METHODS

Two-week ecological momentary assessment (EMA) and actigraphy data of 359 participants with current (n = 93), remitted (n = 176), or no (n = 90) Composite International Diagnostic Interview depression/anxiety diagnoses were obtained from the Netherlands Study of Depression and Anxiety. Positive affect (PA) and negative affect (NA) were assessed by EMA 5 times per day. Average PAL between EMA assessments were calculated from actigraphy data.

RESULTS

At the group-level, higher PAL was associated with subsequent higher PA (b = 0.109, p < .001) and lower NA (b = -0.043, p < .001), while higher PA (b = 0.066, p < .001) and lower NA (b = -0.053, p < .001) were associated with subsequent higher PAL. The association between higher PAL and subsequent lower NA was stronger for current depression/anxiety patients than controls (p = .01). At the person-level, analyses revealed heterogeneity in bidirectional associations.

CONCLUSIONS

Higher PAL may improve affect, especially among depression/anxiety patients. As the relationships vary at the person-level, ambulatory assessments may help identify who would benefit from behavioral interventions.

Physical activity assessment and vascular function in adults with cystic fibrosis and their non-CF peers

An understanding of physical activity (PA) and related health benefits remains limited in adults with Cystic Fibrosis (CF). Raw acceleration data metrics may improve the quality of assessment and further this understanding. The study aimed to compare PA between people with CF (pwCF) and non-CF peers and examine associations between PA, vascular function and health outcome measures. PA was assessed in 62 participants (31 pwCF) using ActiGraph accelerometers. Vascular function (a marker of cardiovascular disease risk) was assessed using flow-mediated dilatation (FMD) in sub-groups of pwCF (n = 12) and matched controls. Average Euclidean norm minus one (ENMO) (total PA) was significantly lower (p = 0.005) in pwCF (35.09 ± 10.60 mg), than their non-CF peers (44.62 ± 13.78 mg). PwCF had PA profiles (intensity gradient) indicative of more time in lower intensity activity (-2.62 ± 0.20, -2.37 ± 0.23). Vigorous activity was positively associated with lung function (r_s = 0.359) and Quality of Life (r = 0.412). There were no significant differences (p = 0.313) in FMD% between pwCF (5.29 ± 2.76%) and non-CF peers (4.34 ± 1.58%) and no associations with PA. PwCF engaged in less moderate-to-vigorous PA and demonstrated a steeper PA profile than their non-CF peers.

Intensity and Duration of Physical Activity and Cardiorespiratory Fitness

OBJECTIVES

There is no clear guidance on the intensity and duration of physical activity (PA) that adolescents require to maximise cardiorespiratory fitness (CRF). We aimed to determine the strength of associations between each PA intensity and CRF, independently of other intensities, and the PA duration at each intensity associated with maximal CRF.

METHODS

PA and CRF were assessed in 339 adolescents aged 13 to 14 years by wrist-worn accelerometers and 20-m shuttle runs, respectively. Partial regression modeling was used to construct residualized PA variables at each PA intensity that were uncorrelated with each other. Moving average models were optimally fitted to determine relationships between residualized PA variables and CRF. Threshold regression models determined the duration of PA above which CRF improvement was minimal.

RESULTS

Greater vigorous PA (VPA) was associated with better CRF until about 20 minutes of daily VPA, when the relationship plateaued. Moderate and light PA, and sedentary time were not associated with CRF in partial models. Adolescents performing 14 (range 12-17) minutes of daily VPA had median CRF. Participants in the upper quartile of VPA had 1.03 z-scores higher CRF than those in the lowest quartile (95% confidence interval: 0.75 to 1.30).

CONCLUSIONS

Our data suggest that 20 minutes of daily VPA may be best for maximizing CRF in adolescence. As moderate-to-vigorous PA guidelines can be satisfied by only undertaking moderate PA, with no apparent independent benefit, we suggest that future guidelines focus on VPA alone, simplifying public health messaging.

Risk stratification for hospital-acquired venous thromboembolism in medical patients (RISE): Protocol for a prospective cohort study

Background

Hospital-acquired venous thromboembolism (VTE) is one of the leading preventable causes of in-hospital mortality. However, its risk assessment in medically ill inpatients is complicated due to the patients’ heterogeneity and complexity of currently available risk assessment models (RAMs). The simplified Geneva score provides simplicity but has not yet been prospectively validated. Immobility is an important predictor for VTE in RAMs, but its definition is inconsistent and based on subjective assessment by nurses or physicians. In this study, we aim to prospectively validate the simplified Geneva score and to examine the predictive performance of a novel and objective definition of in-hospital immobilization using accelerometry.

Methods and analysis

RISE is a multicenter prospective cohort study. The goal is to recruit 1350 adult inpatients admitted for medical illness in three Swiss tertiary care hospitals. We collect data on demographics, comorbidities, VTE risk and thromboprophylaxis. Mobility from admission to discharge is objectively measured using a wrist-worn accelerometer. Participants are followed for 90 days for the occurrence of symptomatic VTE (primary outcome). Secondary outcomes are the occurrence of clinically relevant bleeding, and mortality. The evolution of autonomy in the activities of daily living, the length of stay, and the occurrence of readmission are also recorded. Time-dependent area under the curve, sensitivity, specificity, and positive and negative predictive values are calculated for each RAM (i.e. the simplified and original Geneva score, Padua, and IMPROVE score) with and without the objective mobility measures to assess their accuracy in predicting hospital-acquired VTE at 90 days.

Ethics and expected impact

The ethics committee approved the protocol and the study was registered on ClinicalTrials.gov as NCT04439383. RISE has the potential to optimize VTE risk stratification, and thus to improve the quality of care of medically hospitalized patients.

Effect of goal-directed mobilisation intervention compared with standard care on physical activity among medical inpatients: protocol for the GoMob-in randomised controlled trial

INTRODUCTION

Despite the fact that immobilisation is a major contributor to morbidity and mortality, patients hospitalised in general internal medicine (GIM) wards spend up to 50% of time in bed. Previous studies in selected patient populations showed increased mobility after implementation of goal-directed mobilisation (GDM). Due to the study design used so far, the degree of evidence is generally low. The effect of GDM on clinical outcomes and economically relevant indicators in patients hospitalised in GIM wards is currently unknown. This study aims to evaluate a GDM intervention compared to standard care on physical activity (de Morton Mobility Index, DEMMI) in medical inpatients.

METHODS AND ANALYSIS

GoMob-in is a randomised, controlled, open-label study with blinded outcome assessment. We plan to enrol 160 inpatients with indication for physiotherapy on GIM wards of a tertiary hospital in Bern, Switzerland. Adult patients newly hospitalised on GIM wards will be included in the study. The primary outcome will be the change in the DEMMI score between baseline and 5 days. Secondary outcomes are change of DEMMI (inclusion to hospital discharge), mobilisation time (inclusion to day 5, inclusion to discharge), in-hospital delirium episodes, number of in-hospital falls, length of stay, number of falls within 3 months, number of re-hospitalisations and all-cause mortality within 3 months, change in independence during activities of daily living, concerns of falling, and quality of life within 3 months and destination after 3 months. Patients in the intervention group will be attributed a regularly updated individual mobility goal level made visible for all stakeholders and get a short educational intervention on GDM.

ETHICS AND DISSEMINATION

This study has been approved by the responsible Ethics Board (Ethikkommission Bern/2020-02305). Written informed consent will be obtained from participants before study inclusion. Results will be published in open access policy peer-reviewed journals.

TRIAL REGISTRATION NUMBER

NCT04760392.

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

Background

Wrist worn accelerometers are convenient to wear and provide greater compliance. However, methods to transform the resultant output into predictions of physical activity (PA) intensity have been slow to evolve, with most investigators continuing the practice of applying intensity-based thresholds or cut-points. The current study evaluated the classification accuracy of seven sets of previously published youth-specific cut-points for wrist worn ActiGraph accelerometer data.

Methods

Eighteen children and adolescents [mean age (± SD) 14.6 ± 2.4 years, 10 boys, 8 girls] completed 12 standardized activity trials. During each trial, participants wore an ActiGraph GT3X+ tri-axial accelerometer on the wrist and energy expenditure (Youth METs) was measured directly using the Oxycon Mobile portable calorimetry system. Seven previously published sets of ActiGraph cut-points were evaluated: Crouter regression vertical axis, Crouter regression vector magnitude, Crouter ROC curve vertical axis, Crouter ROC curve vector magnitude, Chandler ROC curve vertical axis, Chandler ROC curve vector magnitude, and Hildebrand ENMO. Classification accuracy was evaluated via weighted Kappa. Confusion matrices were generated to summarize classification accuracy and identify patterns of misclassification.

Results

The cut-points exhibited only moderate agreement with directly measured PA intensity, with Kappa ranging from 0.45 to 0.58. Although the cut-points classified sedentary behavior accurately (> 95%), classification accuracy for the light (3-51%), moderate (12-45%), and vigorous-intensity trials (30-88%) was generally poor. All cut-points underestimated the true intensity of the walking trials, with error rates ranging from 35 to 100%, while the intensity of activity trials requiring significant upper body and/or arm movements was consistently overestimated. The Hildebrand cut-points which serve as the default option in the popular GGIR software package misclassified 30% of the light intensity trials as sedentary and underestimated the intensity of moderate and vigorous intensity trials 75% of the time.

Conclusion

Published ActiGraph cut-points for the wrist, developed specifically for school-aged youth, do not provide acceptable classification accuracy for estimating daily time spent in light, moderate, and vigorous intensity physical activity. The development and deployment of more robust accelerometer data reduction methods such as functional data analysis and machine learning approaches continues to be a research priority.

The Relationship Between Physical Activity and Health-Related Quality of Life in People With Dementia: An Observational Study

Recent research suggests the positive effect of physical activity on health-related quality of life in people with dementia may be mediated through improved activities of daily living and reduced depressive symptoms. One hundred and twenty-four people with dementia and their informal carers were recruited from the South East of England for this observational study. A subset of participants wore an accelerometer for 30 days. A series of bivariate analyses were completed, alongside mediation analyses. In people with mild to moderate severity dementia, weak positive associations were widely reported between physical activity indices and health-related quality of life, though only a single association reached statistical significance (rs = .25, p = .03). Mediation analysis revealed no significant indirect effects across the models after controlling for cognition. Future research needs to explore such relationships with a greater emphasis on the modality and psychosocial components of physical activity rather than just frequency, duration, and intensity.

Is there a bidirectional association between sedentary behaviour and cognitive decline in older adults? Findings from the Irish Longitudinal Study on Ageing

Research on whether sedentary behaviour (SB) is related to cognitive decline in older individuals is conflicting, potentially caused by methodological differences in previous studies. To inform public health policies, we analysed both the forward and reverse association across four-years between subjective TV time and objectively-measured SB and four cognitive outcome measures in older adults. The Irish Longitudinal Study on Ageing (TILDA) quantified time spent watching TV using a questionnaire and objective physical activity patterns with a GENEActiv accelerometer. Mixed model analysis examined whether these two measures of SB related to changes in cognitive function (immediate and delayed recall, MMSE, and animal naming task) during a four-year follow-up period. Furthermore, the reverse association between changes in cognition over the preceding four years and SB was investigated. We included 1,276 participants (67 ± 9 years). Longitudinally, every hour of objective SB per day was associated with a -0.01 (95%CI = -0.03;-0.00) lower MMSE score per year. Reversely, a worse decline in immediate and delayed recall over the preceding waves was related to slightly more objective SB (B = -0.24 (95%CI = -0.41;-0.07)) and TV time (B = -0.25 (95%CI = -0.48;-0.03)) at the end of those four years. To conclude, in healthy older individuals, higher levels of objective SB are related to cognitive decline across a four-year follow-up, although the magnitude and clinical relevance are questionable. As preceding cognitive decline is associated with more SB across follow-up, this suggests that a bidirectional association is plausible.

A systematic review of the physical activity levels of acutely ill older adults in Hospital At Home settings: an under-researched field

PURPOSE

The purpose of this review was to identify, evaluate and synthesise existing evidence reporting the physical activity levels of acutely ill older patients in a 'Hospital At Home' setting and compare this to patients with similar characteristics treated in a traditional hospital inpatient setting. Functional changes and any adverse outcomes due to physical activity (e.g. falls) in both settings where PA was reported or recorded were also evaluated as secondary outcomes.

METHODS

A search strategy was devised for the MEDLINE, CINAHL, AMed, PEDRO, OT Seeker and Cochrane databases. Search results were title, abstract and full-text reviewed by two independent researchers. Data were extracted from included articles using a custom form and assessed for quality and risk of bias using the Appraisal Tool for Cross-Sectional Studies.

RESULTS

No studies set in the Hospital at Home environments were identified. 16 hospital inpatient studies met the criteria for inclusion. Older patients managed in inpatient settings that would be eligible for Hospital at Home services spent 6.6% of their day active and undertook only 881.8 daily steps. Functional change was reported in four studies with both improvement and decline during admission reported.

CONCLUSION

There is a lack of published research on the physical activity levels of acutely-ill older adults in Hospital at Home settings. This review has identified a baseline level of activity for older acutely ill patients that would be suitable for Hospital at Home treatment. This data could be used as a basis of comparison in future hospital at home studies, which should also include functional change outcomes to further explore the relationship between physical inactivity and functional decline.

Developing and validating an accelerometer-based algorithm with machine learning to classify physical activity after acquired brain injury

Purpose: To develop and validate an accelerometer-based algorithm classifying physical activity in people with acquired brain injury (ABI) in a laboratory setting resembling a real home environment.Materials and methods: A development and validation study was performed. Eleven healthy participants and 25 patients with ABI performed a protocol of transfers and ambulating activities. Activity measurements were performed with accelerometers and with thermal video camera as gold standard reference. A machine learning-based algorithm classifying specific physical activities from the accelerometer data was developed and cross-validated in a training sample of 11 healthy participants. Criterion validity of the algorithm was established in 3 models classifying the same protocol of activities in people with ABI.Results: Modeled on data from 11 healthy and 15 participants with ABI, the algorithm had a good precision for classifying transfers and ambulating activities in data from 10 participants with ABI. The weighted sensitivity for all activities was 89.3% (88.3-90.4%) and the weighted positive predictive value was 89.7% (88.7-90.7%). The algorithm differentiated between lying and sitting activities.Conclusion: An algorithm to classify physical activities in populations with ABI was developed and its criterion validity established. Further testing of precision in home settings with continuous activity monitoring is warranted.

Sleep and cardiometabolic health in children and adults: examining sleep as a component of the 24-h day

STUDY OBJECTIVES

Sleep, physical activity and sedentary time are all known to play a role in cardiometabolic health. Compositional data analysis (CoDA) enables us to examine associations between 24-h use of time and health outcomes.

METHODS

Data were collected in the Child Health CheckPoint study, a one-off national population-cohort study conducted between February 2015 and March 2016. Wrist-worn actigraphy monitors (GENEActiv Original, Cambs, UK) were used to measure activity behaviours (sleep, physical activity and sedentary time) and sleep characteristics (sleep variability, midsleep, efficiency). CoDA was applied to determine the association between 24-h use of time and cardiometabolic risk markers (blood pressure; body mass index; apolipoprotein B/A1; glycoprotein acetyls; and composite metabolic syndrome score). Substitution modelling (one-for-remaining and one-for-one) examined the associations of reallocating sleep time with other activity behaviours.

RESULTS

Data were available for 1073 Australian children aged 11-12 years (50% male) and 1337 adults (13% male). Strong association was found between 24-h use of time and all cardiometabolic health outcomes. Longer sleep was associated with more favourable cardiovascular health. Sleep characteristics other than duration (efficiency, timing, variability) were weakly and inconsistently associated with outcomes. Reallocating time from sleep to moderate-vigorous physical activity (MVPA) had favourable associations with cardiometabolic health, but reallocating from sleep to sedentary time was associated with less favourable cardiometabolic health.

CONCLUSION

The 24-h activity composition is strongly associated with cardiometabolic health in children and adults. Days with more sleep and MVPA are associated with improved cardiometabolic health.

Objective and subjective measurement of sedentary behavior in human adults: A toolkit

OBJECTIVES

Objectives: Human biologists are increasingly interested in measuring and comparing physical activities in different societies. Sedentary behavior, which refers to time spent sitting or lying down while awake, is a large component of daily 24 hours movement patterns in humans and has been linked to poor health outcomes such as risk of all-cause and cardiovascular mortality, independently of physical activity. As such, it is important for researchers, with the aim of measuring human movement patterns, to most effectively use resources available to them to capture sedentary behavior.

METHODS

This toolkit outlines objective (device-based) and subjective (self-report) methods for measuring sedentary behavior in free-living contexts, the benefits and drawbacks to each, as well as novel options for combined use to maximize scientific rigor. Throughout this toolkit, emphasis is placed on considerations for the use of these methods in various field conditions and in varying cultural contexts.

RESULTS

Objective measures such as inclinometers are the gold-standard for measuring total sedentary time but they typically cannot capture contextual information or determine which specific behaviors are taking place. Subjective measures such as questionnaires and 24 hours-recall methods can provide measurements of time spent in specific sedentary behaviors but are subject to measurement error and response bias.

CONCLUSIONS

We recommend that researchers use the method(s) that suit the research question; inclinometers are recommended for the measurement of total sedentary time, while self-report methods are recommended for measuring time spent in particular contexts of sedentary behavior.

Accelerometry assessed physical activity of older adults hospitalized with acute medical illness - an observational study

Background

In a hospital setting and among older patients, inactivity and bedrest are associated with a wide range of negative outcomes such as functional decline, increased risk of falls, longer hospitalization and institutionalization. Our aim was to assess the distribution, determinants and predictors of physical activity (PA) levels using wrist-worn accelerometers in older patients hospitalized with acute medical illness.

Methods

Observational study conducted from February to November 2018 at an acute internal medicine unit in the University hospital of Lausanne, Switzerland. We enrolled 177 patients aged ≥65 years, able to walk prior to admission. PA during acute hospital stay was continuously recorded via a 3D wrist accelerometer. Clinical data was collected from medical records or by interview. Autonomy level prior to inclusion was assessed using Barthel Index score. PA levels were defined as < 30 mg for inactivity, 30–99 mg for light and ≥ 100 for moderate PA. Physically active patients were defined as 1) being in the highest quartile of time spent in light and moderate PA or 2) spending ≥20 min/day in moderate PA.

Results

Median [interquartile range - IQR] age was 83 [74–87] years and 60% of participants were male. The median [IQR] time spent inactive and in light PA was 613 [518–663] and 63 [30–97] minutes/day, respectively. PA peaked between 8 and 10 am, at 12 am and at 6 pm. Less than 10% of patients were considered physically active according to definition 2. For both definitions, active patients had a lower prevalence of walking aids and a lower dependency level according to Barthel Index score. For definition 1, use of medical equipment was associated with a 70% reduction in the likelihood of being active: odds ratio (OR) 0.30 [0.10–0.92] p = 0.034; for definition 2, use of walking aids was associated with a 75% reduction in the likelihood of being active: OR = 0.24 [0.06–0.89], p = 0.032.

Conclusion

Older hospitalized patients are physically active only 10% of daily time and concentrate their PA around eating periods. Whether a Barthel Index below 95 prior to admission may be used to identify patients at risk of inactivity during hospital stay remains to be proven.

Validity of long-term and short-term recall of occupational sitting time in Finnish and Chinese office workers

BACKGROUND

As sedentary behavior is a global health issue, there is a need for methods of self-reported sitting assessment. The accuracy and reliability of these methods should also be tested in various populations and different cultural contexts. This study examined the validity of long-term and short-term recall of occupational sitting time in Finnish and Chinese subgroups.

METHODS

Two cohort groups of office-based workers (58.6% female, age range 22-67 years) participated: a Finnish group (FIN, n = 34) and a Chinese group (CHI, n = 36). Long-term (past 3-month sitting) and short-term (daily sitting assessed on 5 consecutive days) single-item measures were used to assess self-reported occupational sitting time. Values from each participant were compared to objectively measured occupational sitting time assessed via thigh-mounted accelerometers, with Spearman's rho (ρ) used to assess validity and the Bland-Altman method used to evaluate agreement. Coefficients of variation depicted day-to-day variability of time spent on sitting at work.

RESULTS

In the total study sample, the results showed that both long-term and short-term recall correlated with accelerometer-derived sitting time (ρ = 0.532, 95% confidence intervals (CI): 0.336-0.684, p< 0.001; ρ = 0.533, 95%CI: 0.449-0.607, p< 0.001, respectively). Compared to objectively measured sitting time, self-reported occupational sitting time was 2.4% (95%CI: -0.5% to 5.3%, p = 0.091) and 2.2% (95%CI: 0.7%-3.6%, p = 0.005) greater for long-term and short-term recall, respectively. The agreement level was within the range -21.2% to 25.9% for long-term recall, and -24.2% to 28.5% for short-term recall. During a 5-day work week, day-to-day variation of sitting time was 9.4% ± 11.4% according to short-term recall and 10.4% ± 8.4% according to accelerometry-derived occupational sitting time.

CONCLUSION

Overall, both long-term and short-term self-reported instruments provide acceptable measures of occupational sitting time in an office-based workplace, but their utility at the individual level is limited due to large variability.

Health impacts of seated arm ergometry training in patients with a diabetic foot ulcer: protocol for a randomised controlled trial

INTRODUCTION

Once diagnosed with a diabetic foot ulcer (DFU), patients are advised to offload, keeping pressure off the foot in order to facilitate ulcer healing. An increase in offloading is often accompanied by reductions in physical activity which can worsen the overall health of patients.While unable to perform traditional forms of upright activity, one mode of exercise that would allow patients to be physically active while adhering to offloading instruction is seated arm ergometry. The merits of tailored aerobic exercise in DFU remain unexplored.

METHODS AND ANALYSIS

This is a prospective open-label randomised controlled trial. Participants will be randomised to one of two groups, an exercise intervention group or control. The intervention group are required to undertake arm ergometry training at a moderate intensity (65%-75% HRpeak), three times per week for 12 weeks as individually prescribed by an exercise physiologist, while the control group will continue to receive standard care alone. Assessment of outcome measures will occur at baseline and after the intervention period, these will include: a seated VO₂ peak test, a blood sample, a short physical performance battery, a dual-energy X-ray absorptiometry scan and completing a range of health-based questionnaires. The above will be used to determine: cardiorespiratory fitness, metabolic health, physical function, body composition and quality of life, respectively. Ulcer area will also be measured as an approximate marker of ulcer healing.

ETHICS AND DISSEMINATION

This trial has been approved by 'Yorkshire & The Humber-Leeds West Research Ethics Committee' (19/YH/0269). Trial results will be published in peer-reviewed journals and through conference presentations.

TRIAL REGISTRATION NUMBER

ISRCTN16000053. Registered in accordance with WHO Trial Registration Data Set (version 1.3.1).

Association Between Physical Activity Levels in the Hospital Setting and Hospital-Acquired Functional Decline in Elderly Patients

IMPORTANCE

The effects of in-hospital physical activity (PA) on outcomes among elderly patients has seldom been assessed.

OBJECTIVES

To assess PA levels among elderly patients hospitalized for acute medical illness and to examine the association between PA levels and functional decline and other clinical outcomes at discharge.

DESIGN, SETTING, AND PARTICIPANTS

This monocentric cohort study was performed among patients 65 years or older who were admitted for acute medical illness to the internal medicine ward of Lausanne University Hospital, Lausanne, Switzerland, from February 1 through November 30, 2018. Data were analyzed from January 1 through December 2, 2019.

EXPOSURES

Daytime and 24-hour PA levels assessed via wrist accelerometers and measured in millig units (mG; 1 mG = 9.80665 × 10-3 m/s2).

MEAN OUTCOMES AND MEASURES

Functional decline (defined as a ≥5-point decrease in the modified Barthel Index), risk of bedsores, length of stay (LOS), and inability to return home.

RESULTS

A total of 177 patients (106 [59.9%] men; median age, 83 [interquartile range, 74-87] years) were included. Lower mean (SD) PA levels were found in patients using walking aids before admission (daytime, 12 [5] vs 15 [7] mG; 24-hour, 10 [3] vs 11 [5] mG), those admitted for a reason associated with functional decline (daytime, 12 [6] vs 14 [7] mG; 24-hour, 10 [4] vs 11 [4] mG), or those prescribed physiotherapy (daytime, 12 [5] vs 15 [7] mG; 24-hour, 10 [4] vs 12 [5] mG). At discharge, functional decline was found in 63 patients (35.6%; 95% CI, 25.6%-43.1%), bedsore risk in 78 (44.1%; 95% CI, 36.6%-51.7%), and inability to return home in 82 (46.3%; 95% CI, 38.8%-54.0%). After multivariate analysis, no association was found between PA levels and functional decline (multivariable-adjusted mean [SE], 13 [1] vs 13 [1] mG for daytime levels [P = .69] and 10 [1] vs 11 [1] mG for 24-hour PA levels [P = .45]) or LOS (Spearman rank correlation, ρ = -0.06 for daytime PA levels [P = .93] and -0.01 for 24-hour PA levels [P = .52]). Patients at risk of bedsores had significantly lower PA levels than those not at risk (multivariable-adjusted mean [SE], 12 [1] vs 15 [1] mG for daytime PA levels [P = .008]; 10 [1] vs 12 [1] mG for 24-hour PA levels [P = .01]). Patients able to return home had significantly higher PA levels than those institutionalized (multivariable-adjusted mean [SE], 14 [1] vs 12 [1] mG for daytime PA levels [P = .04]; 11 [1] vs 10 [1] mG for 24-hour PA levels [P = .009]).

CONCLUSIONS AND RELEVANCE

In this study, lower in-hospital daytime and 24-hour PA levels were associated with risk of bedsores and inability to return home on discharge. These findings are important given that one-third of elderly patients present with hospital-acquired functional decline.

Sedentary Behavior and Chronic Disease: Mechanisms and Future Directions

Background: Recent updates to physical activity guidelines highlight the importance of reducing sedentary time. However, at present, only general recommendations are possible (ie, “Sit less, move more”). There remains a need to investigate the strength, temporality, specificity, and dose–response nature of sedentary behavior associations with chronic disease, along with potential underlying mechanisms. Methods: Stemming from a recent research workshop organized by the Sedentary Behavior Council themed “Sedentary behaviour mechanisms—biological and behavioural pathways linking sitting to adverse health outcomes,” this paper (1) discusses existing challenges and scientific discussions within this advancing area of science, (2) highlights and discusses emerging areas of interest, and (3) points to potential future directions. Results: A brief knowledge update is provided, reflecting upon current and evolving thinking/discussions, and the rapid accumulation of new evidence linking sedentary behavior to chronic disease. Research “action points” are made at the end of each section—spanning from measurement systems and analytic methods, genetic epidemiology, causal mediation, and experimental studies to biological and behavioral determinants and mechanisms. Conclusion: A better understanding of whether and how sedentary behavior is causally related to chronic disease will allow for more meaningful conclusions in the future and assist in refining clinical and public health policies/recommendations.

Association among Weather Conditions, Ambient Air Temperature, and Sedentary Time in Chinese Adults

This study is aimed to quantify the association among weather conditions, ambient air temperature, and sedentary time in Chinese adults. The participants were 3,270 Chinese users of a wrist-worn activity tracker. Their daily activity data were collected using an algorithm based on raw data to determine the sedentary time. The data of ambient air temperature and weather were collected from the meteorological data released by China Central Meteorological Observatory. Two-level linear regression analyses showed that weather conditions had a significant influence on sedentary time in Chinese adults after adjustments for some covariates were made. When the weather condition changed from rainy days to sunny and cloudy days, sedentary time might decrease by about 6.89 and 5.60 min, respectively. In conclusion, weather conditions were independently associated with sedentary time in Chinese adults. The daily sedentary time was shorter on sunny and cloudy days than on rainy days.

The difference in sleep, sedentary behaviour, and physical activity between older adults with 'healthy' and 'unhealthy' cardiometabolic profiles: a cross-sectional compositional data analysis approach

Background

Studies have seldom used Compositional Data Analysis (CoDA) to map the effects of sleep, sedentary behaviour, and physical activity on older adults' cardio-metabolic profiles. This study therefore aimed to illustrate how sleep, sedentary behaviour, and physical activity profiles differ between older adult groups (60-89 years), with 'low' compared to those with 'high' concentrations of endocrine cardio-metabolic disease risk markers, using CoDA.

Method

Ninety-three participants (55% female) wore a thigh-mounted triaxial accelerometer for seven consecutive free-living days. Accelerometer estimates of daily average hours of engagement in sedentary behaviour (SB), standing, light-intensity physical activity (LIPA), sporadic moderate-vigorous physical activity (sMVPA, accumulated with bouts between 1 and 10 min), 10-min moderate-vigorous physical activity (₁₀MVPA, accumulated with bouts ≥10 min), in addition to self-reported sleeping hours were reported. Fasted whole blood concentrations of total cholesterol, triglyceride, glucose, and glycated haemoglobin, and serum lipoprotein lipase (LPL), interleukin-6 (IL-6), and procollagen III N-terminal propeptide were determined.

Results

Triglyceride concentration appeared to be highly dependent on ₁₀MVPA engagement as the 'low' and 'high' concentration groups engaged in 48% more and 32% less ₁₀MVPA, respectively, relative to the geometric mean of the entire study sample. Time-use composition of the 'low' LPL group's engagement in ₁₀MVPA was 26% less, while the 'high' LPL group was 7.9% more, than the entire study sample. Time-use composition of the 'high' glucose and glycated haemoglobin groups appeared to be similar as both engaged in more Sleep and SB, and less ₁₀MVPA compared to the study sample. Participants with a 'low' IL-6 concentration engaged in 4.8% more Sleep and 2.7% less ₁₀MVPA than the entire study sample. Time-use composition of the Total Cholesterol groups was mixed with the 'low' concentration group engaging in more Standing and ₁₀MVPA but less Sleep, SB, LIPA, and sMVPA than the entire study sample.

Conclusion

Older adults should aim to increase 10MVPA engagement to improve lipid profile and decrease SB engagement to improve glucose profile.

Towards a Portable Model to Discriminate Activity Clusters from Accelerometer Data

Few methods for classifying physical activity from accelerometer data have been tested using an independent dataset for cross-validation, and even fewer using multiple independent datasets. The aim of this study was to evaluate whether unsupervised machine learning was a viable approach for the development of a reusable clustering model that was generalisable to independent datasets. We used two labelled adult laboratory datasets to generate a k-means clustering model. To assess its generalised application, we applied the stored clustering model to three independent labelled datasets: two laboratory and one free-living. Based on the development labelled data, the ten clusters were collapsed into four activity categories: sedentary, standing/mixed/slow ambulatory, brisk ambulatory, and running. The percentages of each activity type contained in these categories were 89%, 83%, 78%, and 96%, respectively. In the laboratory independent datasets, the consistency of activity types within the clusters dropped, but remained above 70% for the sedentary clusters, and 85% for the running and ambulatory clusters. Acceleration features were similar within each cluster across samples. The clusters created reflected activity types known to be associated with health and were reasonably robust when applied to diverse independent datasets. This suggests that an unsupervised approach is potentially useful for analysing free-living accelerometer data.

Validity of energy expenditure estimation methods during 10 days of military training

Wearable physical activity (PA) monitors have improved the ability to estimate free-living total energy expenditure (TEE) but their application during arduous military training alongside more well-established research methods has not been widely documented. This study aimed to assess the validity of two wrist-worn activity monitors and a PA log against doubly labeled water (DLW) during British Army Officer Cadet (OC) training. For 10 days of training, twenty (10 male and 10 female) OCs (mean ± SD: age 23 ± 2 years, height 1.74 ± 0.09 m, body mass 77.0 ± 9.3 kg) wore one research-grade accelerometer (GENEActiv, Cambridge, UK) on the dominant wrist, wore one commercially available monitor (Fitbit SURGE, USA) on the non-dominant wrist, and completed a self-report PA log. Immediately prior to this 10-day period, participants consumed a bolus of DLW and provided daily urine samples, which were analyzed by mass spectrometry to determine TEE. Bivariate correlations and limits of agreement (LoA) were employed to compare TEE from each estimation method to DLW. Average daily TEE from DLW was 4112 ± 652 kcal·day^-1 against which the GENEActiv showed near identical average TEE (mean bias ± LoA: -15 ± 851 kcal^. day^-1 ) while Fitbit tended to underestimate (-656 ± 683 kcal·day^-1 ) and the PA log substantially overestimate (+1946 ± 1637 kcal·day^-1 ). Wearable physical activity monitors provide a cheaper and more practical method for estimating free-living TEE than DLW in military settings. The GENEActiv accelerometer demonstrated good validity for assessing daily TEE and would appear suitable for use in large-scale, longitudinal military studies.

Wrist-worn Accelerometry for Runners: Objective Quantification of Training Load

Purpose

This study aimed to apply open-source analysis code to raw habitual physical activity data from wrist-worn monitors to: 1) objectively, unobtrusively, and accurately discriminate between “running” and “nonrunning” days; and 2) develop and compare simple accelerometer-derived metrics of external training load with existing self-report measures.

Methods

Seven-day wrist-worn accelerometer (GENEActiv; Activinsights Ltd, Kimbolton, UK) data obtained from 35 experienced runners (age, 41.9 ± 11.4 yr; height, 1.72 ± 0.08 m; mass, 68.5 ± 9.7 kg; body mass index, 23.2 ± 2.2 kg·m⁻²; 19 [54%] women) every other week over 9 to 18 wk were date-matched with self-reported training log data. Receiver operating characteristic analyses were applied to accelerometer metrics (“Average Acceleration,” “Most Active-30mins,” “Mins≥400 mg”) to discriminate between “running” and “nonrunning” days and cross-validated (leave one out cross-validation). Variance explained in training log criterion metrics (miles, duration, training load) by accelerometer metrics (Mins≥400 mg, “workload (WL) 400-4000 mg”) was examined using linear regression with leave one out cross-validation.

Results

Most Active-30mins and Mins≥400 mg had >94% accuracy for correctly classifying “running” and “nonrunning” days, with validation indicating robustness. Variance explained in miles, duration, and training load by Mins≥400 mg (67%–76%) and WL400–4000 mg (55%–69%) was high, with validation indicating robustness.

Conclusions

Wrist-worn accelerometer metrics can be used to objectively, unobtrusively, and accurately identify running training days in runners, reducing the need for training logs or user input in future prospective research or commercial activity tracking. The high percentage of variance explained in existing self-reported measures of training load by simple, accelerometer-derived metrics of external training load supports the future use of accelerometry for prospective, preventative, and prescriptive monitoring purposes in runners.

Validating the Sedentary Sphere method in children: Does wrist or accelerometer brand matter?

This study aimed to validate the Sedentary Sphere posture classification method from wrist-worn accelerometers in children. Twenty-seven 9-10-year-old children wore ActiGraph GT9X (AG) and GENEActiv (GA) accelerometers on both wrists, and activPAL on the thigh while completing prescribed activities: five sedentary activities, standing with a phone, walking (criterion for all 7: observation) and 10-min free-living play (criterion: activPAL). In an independent sample, 21 children wore AG and GA accelerometers on the non-dominant wrist and activPAL for two days of free-living. Per cent accuracy, pairwise 95% equivalence tests (±10% equivalence zone) and intra-class correlation coefficients (ICC) analyses were completed. Accuracy was similar, for prescribed activities irrespective of brand (non-dominant wrist: 77-78%; dominant wrist: 79%). Posture estimates were equivalent between wrists within brand (±6%, ICC > 0.81, lower 95% CI ≥ 0.75), between brands worn on the same wrist (±5%, ICC ≥ 0.84, lower 95% CI ≥ 0.80) and between brands worn on opposing wrists (±6%, ICC ≥ 0.78, lower 95% CI ≥ 0.72). Agreement with activPAL during free-living was 77%, but sedentary time was underestimated by 7% (GA) and 10% (AG). The Sedentary Sphere can be used to classify posture from wrist-worn AG and GA accelerometers for group-level estimates in children, but future work is needed to improve the algorithm for better individual-level results.

Acceptability and feasibility of wearing activity monitors in community-dwelling older adults with dementia

OBJECTIVES

Measuring physical activity is complicated particularly in people with dementia, where activity levels are low and subjective measures are susceptible to inaccurate recall. Activity monitors are increasingly being used within research; however, it is unclear how people with dementia view wearing such devices and what aspects of the device effect wear time. The aim of the study was to evaluate the acceptability and feasibility of people with dementia wearing activity monitors.

METHODS

Twenty-six, community-dwelling, people with mild dementia were asked to wear an activity monitor (GENEactiv Original) over a 1-month period. Perceptions of the device were measured using the Quebec User Evaluation of Satisfaction with Assistive Technology (QUEST) 2.0, alongside qualitative interviews. Device diary and activity monitor data were used to assess compliance.

RESULTS

Participants tended to find wearing the activity monitors acceptable, with only three participants (12%) withdrawing prior to the study end date. Participants were generally satisfied with wearing the devices as measured by the QUEST (Mdn = 4.4, IQR = 1.1). Four themes were identified that influenced perceptions of wearing the device: external influences, design, routine, and perceived benefits.

DISCUSSION

Asking people with dementia to wear a wrist-worn activity monitor for prolonged periods appears to be both feasible and acceptable. Researchers need to consider the needs and preferences of the sample population prior to selecting activity monitors.

The backwards comparability of wrist worn GENEActiv and waist worn ActiGraph accelerometer estimates of sedentary time in children

OBJECTIVES

To examine the backward comparability of a range of wrist-worn accelerometer estimates of sedentary time (ST) with ActiGraph 100countmin^-1 waist ST estimates.

DESIGN

Cross-sectional, secondary data analysis METHODS: One hundred and eight 10-11-year-old children (65 girls) wore an ActiGraph GT3X+ accelerometer (AG) on their waist and a GENEActiv accelerometer (GA) on their non-dominant wrist for seven days. GA ST data were classified using a range of thresholds from 23 to 56mg ST estimates were compared to AG ST 100countmin^-1 data. Agreement between the AG and GA thresholds was examined using Cronbach's alpha, intraclass correlation coefficients (ICC), limits of agreement (LOA), Kappa values, percent agreement, mean absolute percent error (MAPE) and equivalency analysis.

RESULTS

Mean AG total ST was 492.4min over the measurement period. Kappa values ranged from 0.31 to 0.39. Percent agreement ranged from 68 to 69.9%. Cronbach's alpha values ranged from 0.88 to 0.93. ICCs ranged from 0.59 to 0.86. LOA were wide for all comparisons. Only the 34mg threshold produced estimates that were equivalent at the group level to the AG ST 100countmin^-1 data though sensitivity and specificity values of ∼64% and ∼74% respectively were observed.

CONCLUSIONS

Wrist-based estimates of ST generated using the 34mg threshold are comparable with those derived from the AG waist mounted 100countmin^-1 threshold at the group level. The 34mg threshold could be applied to allow group-level comparisons of ST with evidence generated using the ActiGraph 100countmin^-1 method though it is important to consider the observed sensitivity and specificity results when interpreting findings.

Segmenting accelerometer data from daily life with unsupervised machine learning

Purpose

Accelerometers are increasingly used to obtain valuable descriptors of physical activity for health research. The cut-points approach to segment accelerometer data is widely used in physical activity research but requires resource expensive calibration studies and does not make it easy to explore the information that can be gained for a variety of raw data metrics. To address these limitations, we present a data-driven approach for segmenting and clustering the accelerometer data using unsupervised machine learning.

Methods

The data used came from five hundred fourteen-year-old participants from the Millennium cohort study who wore an accelerometer (GENEActiv) on their wrist on one weekday and one weekend day. A Hidden Semi-Markov Model (HSMM), configured to identify a maximum of ten behavioral states from five second averaged acceleration with and without addition of x, y, and z-angles, was used for segmenting and clustering of the data. A cut-points approach was used as comparison.

Results

Time spent in behavioral states with or without angle metrics constituted eight and five principal components to reach 95% explained variance, respectively; in comparison four components were identified with the cut-points approach. In the HSMM with acceleration and angle as input, the distributions for acceleration in the states showed similar groupings as the cut-points categories, while more variety was seen in the distribution of angles.

Conclusion

Our unsupervised classification approach learns a construct of human behavior based on the data it observes, without the need for resource expensive calibration studies, has the ability to combine multiple data metrics, and offers a higher dimensional description of physical behavior. States are interpretable from the distributions of observations and by their duration.

Establishing Raw Acceleration Thresholds to Classify Sedentary and Stationary Behaviour in Children

This study aimed to: (1) compare acceleration output between ActiGraph (AG) hip and wrist monitors and GENEActiv (GA) wrist monitors; (2) identify raw acceleration sedentary and stationary thresholds for the two brands and placements; and (3) validate the thresholds during a free-living period. Twenty-seven from 9- to 10-year-old children wore AG accelerometers on the right hip, dominant- and non-dominant wrists, GA accelerometers on both wrists, and an activPAL on the thigh, while completing seven sedentary and light-intensity physical activities, followed by 10 minutes of school recess. In a subsequent study, 21 children wore AG and GA wrist monitors and activPAL for two days of free-living. The main effects of activity and brand and a significant activity × brand × placement interaction were observed (all p < 0.0001). Output from the AG hip was lower than the AG wrist monitors (both p < 0.0001). Receiver operating characteristic (ROC) curves established AG sedentary thresholds of 32.6 mg for the hip, 55.6 mg and 48.1 mg for dominant and non-dominant wrists respectively. GA wrist thresholds were 56.5 mg (dominant) and 51.6 mg (non-dominant). Similar thresholds were observed for stationary behaviours. The AG non-dominant threshold came closest to achieving equivalency with activPAL during free-living.

Validity of objective methods for measuring sedentary behaviour in older adults: a systematic review

Background

The evidence showing the ill health effects of prolonged sedentary behaviour (SB) is growing. Most studies of SB in older adults have relied on self-report measures of SB. However, SB is difficult for older adults to recall and objective measures that combine accelerometry with inclinometry are now available for more accurately assessing SB. The aim of this systematic review was to assess the validity and reliability of these accelerometers for the assessment of SB in older adults.

Methods

EMBASE, PubMed and EBSCOhost databases were searched for articles published up to December 13, 2017. Articles were eligible if they: a) described reliability, calibration or validation studies of SB measurement in healthy, community-dwelling individuals, b) were published in English, Portuguese or Spanish, and c) were published or in press as journal articles in peer-reviewed journals.

Results

The review identified 15 studies in 17 papers. Of the included studies, 11 assessed the ActiGraph accelerometer. Of these, three examined reliability only, seven (in eight papers) examined validity only and one (in two papers) examined both. The strongest evidence from the studies reviewed is from studies that assessed the validity of the ActiGraph. These studies indicate that analysis of the data using 60-s epochs and a vertical magnitude cut-point < 200 cpm or using 30- or 60-s epochs with a machine learning algorithm provides the most valid estimates of SB. Non-wear algorithms of 90+ consecutive zeros is also suggested for the ActiGraph.

Conclusions

Few studies have examined the reliability and validity of accelerometers for measuring SB in older adults. Studies to date suggest that the criteria researchers use for classifying an epoch as sedentary instead of as non-wear time (e.g., the non-wear algorithm used) may need to be different for older adults than for younger adults. The required number of hours and days of wear for valid estimates of SB in older adults was not clear from studies to date. More older-adult-specific validation studies of accelerometers are needed, to inform future guidelines on the appropriate criteria to use for analysis of data from different accelerometer brands.

Trial registration

PROSPERO ID# CRD42017080754 registered December 12, 2017.

Electronic supplementary material

The online version of this article (10.1186/s12966-018-0749-2) contains supplementary material, which is available to authorized users.

Accelerometer-assessed Physical Activity in Epidemiology: Are Monitors Equivalent?

PURPOSE

Accelerometers are increasingly being used to assess physical activity in large-scale surveys. Establishing whether key physical activity outcomes can be considered equivalent between three widely used accelerometer brands would be a significant step toward capitalizing on the increasing availability of accelerometry data for epidemiological research.

METHODS

Twenty participants wore a GENEActiv, an Axivity AX3, and an ActiGraph GT9X on their nondominant wrist and were observed for 2 h in a simulated living space. Participants undertook a series of seated and upright light/active behaviors at their own pace. All accelerometer data were processed identically using open-source software (GGIR) to generate physical activity outcomes (including average dynamic acceleration (ACC) and time within intensity cut points). Data were analyzed using pairwise 95% equivalence tests (±10% equivalence zone), intraclass correlation coefficients (ICC) and limits of agreement.

RESULTS

The GENEActiv and Axivity could be considered equivalent for ACC (ICC = 0.95, 95% confidence interval (CI), 0.87-0.98), but ACC measured by the ActiGraph was approximately 10% lower (GENEActiv/ActiGraph: ICC = 0.86; 95% CI, 0.56-0.95; Axivity/ActiGraph: ICC = 0.82; 95% CI, 0.50-0.94). For time spent within intensity cut points, all three accelerometers could be considered equivalent to each other for more than 85% of outcomes (ICC ≥0.69, lower 95% CI ≥0.36), with the GENEActiv and Axivity equivalent for 100% of outcomes (ICC ≥0.95, lower 95% CI ≥0.86).

CONCLUSIONS

GENEActiv and Axivity data processed in GGIR are largely equivalent. If GENEActiv or Axivity is compared with the ActiGraph, time spent within intensity cut points has good agreement. These findings can be used to inform selection of appropriate outcomes if outputs from these accelerometer brands are compared.

Moving Forward With Accelerometer-Assessed Physical Activity: Two Strategies to Ensure Meaningful, Interpretable, and Comparable Measures

Significant advances have been made in the measurement of physical activity in youth over the past decade. Monitors and protocols promote very high compliance, both night and day, and raw measures are available rather than "black box" counts. Consequently, many surveys and studies worldwide now assess children's physical behaviors (physical activity, sedentary behavior, and sleep) objectively 24 hours a day, 7 days a week using accelerometers. The availability of raw acceleration data in many of these studies is both an opportunity and a challenge. The richness of the data lends itself to the continued development of innovative metrics, whereas the removal of proprietary outcomes offers considerable potential for comparability between data sets and harmonizing data. Using comparable physical activity outcomes could lead to improved precision and generalizability of recommendations for children's present and future health. The author will discuss 2 strategies that he believes may help ensure comparability between studies and maximize the potential for data harmonization, thereby helping to capitalize on the growing body of accelerometer data describing children's physical behaviors.

Physical activity among hospitalised older people: insights from upper and lower limb accelerometry

Background

Few studies have explored the activity levels of hospitalised older people and the intra-daily activity patterns in this group have not been described.

Aims

To describe the quantity and daily pattern of physical activity among hospitalised older people using two accelerometers: the ankle-worn StepWatch Activity Monitor (SAM), and the wrist-worn GENEActiv.

Methods

This cross-sectional observational study was conducted on the acute medical wards for older people in one UK hospital. Inclusion criteria: participants aged ≥ 70 years, and able to mobilise prior to admission. Participants wore both devices for up to seven consecutive days, or until hospital discharge, whichever was sooner. Intra-daily activity levels were analysed hourly over each 24 h period.

Results

38 participants (mean age 87.8 years, SD 4.8) had their activity levels measured using both devices. The SAM median daily step count was 600 (IQR 240–1427). Intra-daily activity analysis showed two peak periods of ambulatory activity between 9 am–11 am and 6 pm–7 pm. With physical activity defined as ≥ 12 milli-g (GENEActiv), the median time spent above this cut-off point was 4.2 h. 62% of this activity time was only sustained for 1–5 min. Acceptability of both devices was high overall, but the wrist-worn device (96%) was more acceptable to patients than the ankle-worn device (83%).

Conclusion

Activity levels of these hospitalised older people were very low. Most physical activity was sustained over short periods. The intra-daily pattern of activity is an interesting finding which can help clinicians implement time-specific interventions to address the important issue of sedentary behaviour.

Association between Objectively Measured Physical Activity and Gait Patterns in People with Parkinson's Disease: Results from a 3-Month Monitoring

Background

Although physical activity (PA) is known to be beneficial in improving motor symptoms of people with Parkinson's disease (pwPD), little is known about the relationship between gait patterns and features of PA performed during daily life.

Objective

To verify the existence of possible relationships between spatiotemporal and kinematic parameters of gait and amount/intensity of PA, both instrumentally assessed.

Methods

Eighteen individuals affected by PD (10F and 8M, age 68.0 ± 10.8 years, 1.5 ≤ Hoehn and Yahr (H&Y) < 3) were required to wear a triaxial accelerometer 24 h/day for 3 consecutive months. They also underwent a 3D computerized gait analysis at the beginning and end of the PA assessment period. The number of daily steps and PA intensity were calculated on the whole day, and the period from 6:00 to 24:00 was grouped into 3 time slots, using 3 different cut-point sets previously validated in the case of both pwPD and healthy older adults. 3D gait analysis provided spatiotemporal and kinematic parameters of gait, including summary indexes of quality (Gait Profile Score (GPS) and Gait Variable Score (GVS)).

Results

The analysis of hourly trends of PA revealed the existence of two peaks located in the morning (approximately at 10) and in the early evening (between 18 and 19). However, during the morning time slot (06:00–12:00), pwPD performed significantly higher amounts of steps (4313 vs. 3437 in the 12:00–18:00 time slot, p < 0.001, and vs. 2889 in the 18:00–24:00 time slot, p=0.021) and of moderate-to-vigorous PA (43.2% vs. 36.3% in the 12:00–18:00 time slot, p=0.002, and vs. 31.4% in the 18:00–24:00 time slot, p=0.049). The correlation analysis shows that several PA intensity parameters are significantly associated with swing-phase duration (rho = −0.675 for sedentary intensity, rho = 0.717 for moderate-to-vigorous intensity, p < 0.001), cadence (rho = 0.509 for sedentary intensity, rho = −0.575 for moderate-to-vigorous intensity, p < 0.05), and overall gait pattern quality as expressed by GPS (rho = −0.498 to −0.606 for moderate intensity, p < 0.05) and GVS of knee flexion-extension (rho = −0.536 for moderate intensity, p < 0.05).

Conclusions

Long-term monitoring of PA integrated by the quantitative assessment of spatiotemporal and kinematic parameters of gait may represent a useful tool in supporting a better-targeted prescription of PA and rehabilitative treatments in pwPD.

Association between Air Quality and Sedentary Time in 3270 Chinese Adults: Application of a Novel Technology for Posture Determination

This study investigated the association between ambient air quality and sedentary time in Chinese adults. The participants were 3270 Chinese users (2021 men and 1249 women) of wrist-worn activity trackers. The data of participants’ daily activities were collected from July 2015 to October 2015. A novel algorithm based on raw accelerometer data was employed to determine sedentary time. Personal data, including sex, age, weight and height, were self-reported by the participants. Data of air quality, ambient temperature and weather were collected from the data released by the China National Environmental Monitoring Centre and the China Central Meteorological Observatory and matched in accordance with the Global Positioning System and time information. Multilevel regression analyses were conducted to investigate the association between air quality and sedentary time and adjusted for gender, age, region, body mass index, weather, temperature, weekday/weekend and monitored wake time per day. Better air quality index levels and lower concentrations of fine particulate matter were significantly associated with approximately 20 and 45 min reduction in sedentary time, respectively. Poor air quality appears to be an independent factor associated with prolonged sedentary time in Chinese adults.

Analyzing walking speeds with ankle and wrist worn accelerometers in a cohort with myotonic dystrophy

Background: Accelerometers are accurate tools to assess movement and physical activity. However, interpreting standardly used outputs is not straightforward for populations with impaired mobility.

Methods: The applicability of GENEActiv was explored in a group of 30 participants with myotonic dystrophy and compared to a group of 14 healthy-controls. All participants performed a set of tests while wearing four different accelerometers (wrists and ankles): [1] standing still; [2] ten-meters walk test; [3] six-minutes walking test; and, [4] ten-meters walk/run test.

Results: Relevant findings were: [1] high intra-accelerometer reliability (i.e. 0.97 to 0.99; p < 0.001); [2] each test acceleration values differ significantly between each other; [3] no inter-accelerometer reliability between wrist-worn devices and ankle-worn; and [4] a significant difference between the myotonic dystrophy group and the healthy-controls detectable at each test (i.e. Left-ankle values at six-minutes walking test: 48±17 for the myotonic dystrophy group, vs, 74±16 for the healthy-controls; p < 0.001).

Conclusions: GENEActiv demonstrated to be valid and reliable, capable of detecting walking periods and discriminating different speeds. However, inter-accelerometer reliability only applied when comparing opposite sides of the same limb. Specific movement characteristics of the myotonic dystrophy group were identified and muscle strength showed not to be a full determinant of limb acceleration.

Implications for rehabilitation

Rehabilitation professionals in the field of neuromuscular disorders should be aware of the potential use of objective monitoring tools such as accelerometers whilst acknowledging the implications of assessing populations with altered movement patterns.

Researchers should be cautious when translating accelerometry outputs previously validated in healthy populations to functionally impaired cohorts like myotonic dystrophy.

Accelerometers can objectively expose movement disturbances allowing further investigations for the source of these disturbances.

Measuring activity in patients with sarcoidosis - a pilot trial of two wrist-worn accelerometer devices

Introduction: Increasing physical activity is associated with health benefits. Reduced physical activity has been noted in sarcoidosis, particularly where fatigue co-exists. Monitoring physical activity is possible with wrist-worn devices. This study compared two available devices to determine patient preference and compare wear-time, with a secondary outcome of comparing device outputs with fatigue scores. Methods: Patients with sarcoidosis wore two wrist-worn activity monitors (GENEActiv actiwatch and Actigraph GT3X-bt) separately for seven days each. Participants were randomly allocated to receive either device first. Participants completed the Fatigue Assessment Scale (FAS) questionnaire immediately before wearing the first device. All participants completed a questionnaire of their perception regarding each device after the wear period. Data from the devices was analysed for total wear time, time spent in moderate or vigorous activity (MVPA) and for time spent in sedentary behaviours. Results: Twelve patients with sarcoidosis were included. The GENEActiv device was preferred by ten (83.3%) participants. Wear time was greater with the GENEActiv device (1354 minutes/day vs 1079 minutes/day). Time spent in MVPA was slightly higher when recorded by the GENEActiv compared with the Actigraph. Moderately strong correlation was seen between FAS scores and sedentary time (r=-0.554), light activity (r=-0.585) and moderate activity (r=0.506). Discussion: A clear preference was demonstrated for the GENEActiv. This was reflected in higher wear time and suggests the device can be comfortably worn 24 hours per day. Data from this small cohort also suggests there is correlation between fatigue and activity scores in patients with sarcoidosis. (Sarcoidosis Vasc Diffuse Lung Dis 2018; 35: 62-68).

Comparability of children's sedentary time estimates derived from wrist worn GENEActiv and hip worn ActiGraph accelerometer thresholds

OBJECTIVES

To examine the comparability of children's free-living sedentary time (ST) derived from raw acceleration thresholds for wrist mounted GENEActiv accelerometer data, with ST estimated using the waist mounted ActiGraph 100count·min^-1 threshold.

DESIGN

Secondary data analysis.

METHOD

108 10-11-year-old children (n=43 boys) from Liverpool, UK wore one ActiGraph GT3X+ and one GENEActiv accelerometer on their right hip and left wrist, respectively for seven days. Signal vector magnitude (SVM; mg) was calculated using the ENMO approach for GENEActiv data. ST was estimated from hip-worn ActiGraph data, applying the widely used 100count·min^-1 threshold. ROC analysis using 10-fold hold-out cross-validation was conducted to establish a wrist-worn GENEActiv threshold comparable to the hip ActiGraph 100count·min^-1 threshold. GENEActiv data were also classified using three empirical wrist thresholds and equivalence testing was completed.

RESULTS

Analysis indicated that a GENEActiv SVM value of 51mg demonstrated fair to moderate agreement (Kappa: 0.32-0.41) with the 100count·min^-1 threshold. However, the generated and empirical thresholds for GENEActiv devices were not significantly equivalent to ActiGraph 100count·min^-1. GENEActiv data classified using the 35.6mg threshold intended for ActiGraph devices generated significantly equivalent ST estimates as the ActiGraph 100count·min^-1.

CONCLUSIONS

The newly generated and empirical GENEActiv wrist thresholds do not provide equivalent estimates of ST to the ActiGraph 100count·min^-1 approach. More investigation is required to assess the validity of applying ActiGraph cutpoints to GENEActiv data. Future studies are needed to examine the backward compatibility of ST data and to produce a robust method of classifying SVM-derived ST.

Segregating the Distinct Effects of Sedentary Behavior and Physical Activity on Older Adults' Cardiovascular Profile: Part 2-Isotemporal Substitution Approach

BACKGROUND

The aim of the study was to provide an isotemporal substitution model to predict how changes in physical behavior may affect the cardiovascular parameters (CVPs) of older adults.

METHODS

Participants wore a thigh-mounted accelerometer for 7 days. Phenotype of the carotid, brachial, and popliteal artery was conducted using ultrasound. Isotemporal substitution was used to simulate the degree to which replacing 1 hour of physical behavior with another would affect CVP.

RESULTS

Substitution of sedentary behavior with Standing and sporadic moderate- to vigorous-intensity physical activity (MVPA accumulated in bouts <10 min) would reduce resting heart rate [-6.20 beats per minute (-12.1 to -0.22) and -3.72 beats per minute (-7.01 to -0.44), respectively]. Substitution of sedentary behavior with light-intensity physical activity would reduce carotid artery diameter [-0.54 mm (-1.00 to -0.07)]. Substitution of Standing with sporadic MVPA would increase popliteal artery diameter [1.31 mm (0.11 to 2.51)].

CONCLUSIONS

Our modeling suggests that an accumulation of MVPA bouts that are shorter than the recommended 10-minute minimum may still improve CVP, with lower intensity physical activity also influencing CVP. Our findings are a promising avenue for lifestyle interventions in older adults to reduce the aging effects on CVP for those who cannot engage or sustain sufficient MVPA.