OS10.5.A BrainWear: Longitudinal, objective assessment of physical activity in 42 HGG patients

Abstract BACKGROUND In patients with High Grade Glioma (HGG), QoL and physical function decline with progressive disease (PD). Objective assessment of physical functioning is challenging as patients spend most of their time away from the hospital. Wearable technology allows measurement of objective, continuous activity data in a non-obtrusive manner. BrainWear is a phase II feasibility study, collecting longitudinal physical activity (PA) data from patients with primary and secondary brain tumours. MATERIAL AND METHODS All agreed to wear an Axivity AX3 triaxial accelerometer and completed the EORTC QLQ C30 and BN20, the Montreal Cognitive Assessment (MoCA) and Multidimensional fatigue inventory (MFI) questionnaires. Accelerometers were changed at 14-day intervals, and PRO questionnaires completed at pre-specified study intervals. Age-sex matched controls were identified from the UK Biobank 7-day accelerometer study. Raw accelerometer data was processed using UK Biobank accelerometer software and inclusion of high-quality wear time selected as ≥72 hours of data in a 7-day data collection and data in each 1-hour period of a 24-hour cycle over multiple days. We analysed variation in activity by patient demographics and treatment days. The wilcoxin-signed rank test was used to compare participant activity between radiotherapy treatment days and non-treatment days, mixed effects models were used to evaluate longitudinal changes in activity and we used k-means clustering to characterise clusters of PA behaviours. RESULTS We have collected 3458 days of accelerometer data from 42 HGG patients with a median age of 59, 80% of which has been classified as high quality. Patients >60 years spend more time doing moderate activity compared to those <60 years (52 vs 33 minutes/day, p=0.012), and there are significant differences in mean vector magnitude (17.12 vs 16.85 mg, p=0.013) and walking (91 vs 72 minutes/day) between radiotherapy and non-radiotherapy days. In patients having a 6-week RT course, time spent in daily moderate activity falls 4-fold between week 1 and the second week after RT completion (70 minutes to 16 minutes/day). Comparing HGG patients to healthy controls shows a significant difference in time spent across all activities (p<0.05). K-means clustering analysis shows three distinct clusters, with 87% of HGG patients falling into the very inactive or moderately active groups. CONCLUSION Digital remote health monitoring is feasible and acceptable with 80% of data classified as high-quality wear-time suggesting good patient adherence. Triaxial accelerometer data collection captures objective evidence of a significant reduction in moderate daily activity at the time of expected peak RT side-effects and patients walk almost 30% less on non-RT treatment days. HGG patients show significantly lower levels of activity compared to matched healthy controls.

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BrainWear: Longitudinal, objective assessment of physical activity in 42 High Grade Glioma (HGG) patients

Neuro-Oncology ◽

10.1093/neuonc/noab195.006 ◽

2021 ◽

Vol 23 (Supplement_4) ◽

pp. iv3-iv3

Author(s):

Seema Dadhania ◽

Lillie Pakzad-Shahabi ◽

Kerlann Le Calvez ◽

Waqar Saleem ◽

James Wang ◽

...

Keyword(s):

Physical Activity ◽

Physical Function ◽

High Grade Glioma ◽

Moderate Activity ◽

Accelerometer Data ◽

High Grade ◽

Uk Biobank ◽

High Quality ◽

Wear Time ◽

Vector Magnitude

Abstract Aims In patients with HGG, we know that QoL and physical function decline with progressive disease (PD) and fatigue is a strong predictor of survival in recurrent disease. Despite notable technical advances in therapy for in the past decade, survival has not improved. The role of physical function as a predictor of QoL, treatment tolerance and as an early indicator of worsening morbidity (e.g. tumour recurrence) is an area of growing importance. Recent advancements in wearable technology allow us the opportunity to gather high-quality, continuous and objective data BrainWear is a feasibility study collecting longitudinal physical activity (PA) data from patients with primary and secondary brain tumours and we hypothesise changes in PA over time, are a potentially sensitive biomarker for PD both at diagnosis and relapse. Method Here we show early analysis of this novel dataset of 42 HGG patients and will present: 1) feasibility and acceptability 2) how digitally captured PA changes through treatment and at PD/hospitalization 3) the correlation between patient reported outcomes (PRO) and PA data 4) how PA in HGG patients compares with healthy UK Biobank participants. PA data is collected via a wrist-worn accelerometer. Raw accelerometer data is processed using the UK Biobank Accelerometer Analysis pipeline in python 3.7, and evaluated for good quality wear-time. Overall activity is represented as vector magnitude in milligravity units(mg) and a machine-learning classifier classifies daily activity into 5 separate groups (walking, tasks-light, moderate, sedentary and sleep). Descriptive statistics summarise baseline characteristics and unadjusted mean used to present vector magnitude and accelerometer-predicted functional behaviours (in h/day) by age, sex, radiotherapy and weekend days. Mixed effect models for repeated measures are used for longitudinal data evaluation of PA. Results Between October 2018 and March 2021, 42 patients with a suspected HGG were recruited; 16 females and 26 males with a median age of 59. 40 patients had surgery and 35 patients had adjuvant primary radiotherapy, 23 of whom had a 6-week course. They have provided 3458 days of accelerometer data, 80% of which has been classified as good quality wear-time. There are no statistical differences in mean activity between gender, patients >60 years show statistical difference in time spent doing moderate activity compared to those <60 years, and there are significant differences in mean vector magnitude and walking between radiotherapy and non-radiotherapy days. In patients having a 6-week RT course, time spent in daily moderate activity falls 4-fold between week 1 and the second week following RT completion (70 minutes to 16 minutes). HGG versus healthy UK Biobank participants shows significant differences in all measures of PA. Conclusion Here we present preliminary analysis of this highly novel dataset in adult high grade glioma patients, and show digital remote health monitoring is feasible and acceptable with 80% of data classified as high quality wear-time suggesting good patient adherence. We are able to objectively describe how PA changes through standard treatments and understand the inter and intra-patient variation in PA, and whether there are correlates with patient-centred measures, clinical measures and early indicators of worsening disease. We will present further data on changes in PA prior to hospitalisation and at disease progression, and discuss some of the challenges of running a digital health trial. The passive and objective nature of wearable activity monitors gives clinicians the opportunity to evaluate and monitor the patient in motion, rather than the episodic snapshot we currently see, and in turn has the potential to improve our clinical decision making and potentially outcomes.

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Association of genetic liability for psychiatric disorders with accelerometer-assessed physical activity in the UK Biobank

PLoS ONE ◽

10.1371/journal.pone.0249189 ◽

2021 ◽

Vol 16 (3) ◽

pp. e0249189

Author(s):

Charlotte A. Dennison ◽

Sophie E. Legge ◽

Matthew Bracher-Smith ◽

Georgina Menzies ◽

Valentina Escott-Price ◽

...

Keyword(s):

Physical Activity ◽

Psychiatric Disorders ◽

Genetic Correlations ◽

Autism Spectrum ◽

Moderate Activity ◽

Activity Levels ◽

Accelerometer Data ◽

Uk Biobank ◽

Genetic Liability ◽

Shared Risk

Levels of activity are often affected in psychiatric disorders and can be core symptoms of illness. Advances in technology now allow the accurate assessment of activity levels but it remains unclear whether alterations in activity arise from shared risk factors for developing psychiatric disorders, such as genetics, or are better explained as consequences of the disorders and their associated factors. We aimed to examine objectively-measured physical activity in individuals with psychiatric disorders, and assess the role of genetic liability for psychiatric disorders on physical activity. Accelerometer data were available on 95,529 UK Biobank participants, including measures of overall mean activity and minutes per day of moderate activity, walking, sedentary activity, and sleep. Linear regressions measured associations between psychiatric diagnosis and activity levels, and polygenic risk scores (PRS) for psychiatric disorders and activity levels. Genetic correlations were calculated between psychiatric disorders and different types of activity. Having a diagnosis of schizophrenia, bipolar disorder, depression, or autism spectrum disorders (ASD) was associated with reduced overall activity compared to unaffected controls. In individuals without a psychiatric disorder, reduced overall activity levels were associated with PRS for schizophrenia, depression, and ASD. ADHD PRS was associated with increased overall activity. Genetic correlations were consistent with PRS findings. Variation in physical activity is an important feature across psychiatric disorders. Whilst levels of activity are associated with genetic liability to psychiatric disorders to a very limited extent, the substantial differences in activity levels in those with psychiatric disorders most likely arise as a consequences of disorder-related factors.

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Effect of Incentive Amount on U.S. Adolescents’ Participation in an Accelerometer Data Collection Component of a National Survey

Field Methods ◽

10.1177/1525822x21989841 ◽

2021 ◽

pp. 1525822X2198984

Author(s):

April Y. Oh ◽

Andrew Caporaso ◽

Terisa Davis ◽

Laura A. Dwyer ◽

Linda C. Nebeling ◽

...

Keyword(s):

Physical Activity ◽

Data Collection ◽

National Survey ◽

Monetary Incentive ◽

Behavioral Research ◽

Accelerometer Data ◽

Web Based ◽

Demographic Subgroups

Behavioral research increasingly uses accelerometers to provide objective estimates of physical activity. This study extends research on methods for collecting accelerometer data among youth by examining whether the amount of a monetary incentive affects enrollment and compliance in a mail-based accelerometer study of adolescents. We invited a subset of adolescents in a national web-based study to wear an accelerometer for seven days and return it by mail; participants received either $20 or $40 for participating. Enrollment did not significantly differ by incentive amount. However, adolescents receiving the $40 incentive had significantly higher compliance (accelerometer wear and return). This difference was largely consistent across demographic subgroups. Those in the $40 group also wore the accelerometer for more time than the $20 group on the first two days of the study. Compared to $20, a $40 incentive may promote youth completion of mail-based accelerometer studies.

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Children and Adolescents Treated for Valvular Aortic Stenosis Have Different Physical Activity Patterns Compared to Healthy Controls: A Methodological Study in a National Cohort

Pediatric Cardiology ◽

10.1007/s00246-021-02540-1 ◽

2021 ◽

Author(s):

Pia Skovdahl ◽

Cecilia Kjellberg Olofsson ◽

Jan Sunnegårdh ◽

Jonatan Fridolfsson ◽

Mats Börjesson ◽

...

Keyword(s):

Physical Activity ◽

High Resolution ◽

Aortic Stenosis ◽

Children And Adolescents ◽

Sedentary Time ◽

Heart Defects ◽

Sports Participation ◽

Accelerometer Data ◽

Healthy Controls ◽

Valvular Aortic Stenosis

AbstractPrevious research in children and adolescents with congenital heart defects presents contradictory findings concerning their physical activity (PA) level, due to methodological limitations in the PA assessment. The aim of the present cross-sectional study was to compare PA in children and adolescents treated for valvular aortic stenosis with healthy controls using an improved accelerometer method. Seven-day accelerometer data were collected from the hip in a national Swedish sample of 46 patients 6–18 years old treated for valvular aortic stenosis and 44 healthy controls matched for age, gender, geography, and measurement period. Sports participation was self-reported. Accelerometer data were processed with the new improved Frequency Extended Method and with the traditional ActiGraph method for comparison. A high-resolution PA intensity spectrum was investigated as well as traditional crude PA intensity categories. Children treated for aortic stenosis had a pattern of less PA in the highest intensity spectra and had more sedentary time, while the adolescent patients tended to be less physically active in higher intensities overall and with less sedentary time, compared to the controls. These patterns were evident using the Frequency Extended Method with the detailed PA intensity spectrum, but not to the same degree using the ActiGraph method and traditional crude PA intensity categories. Patients reported less sports participation than their controls in both age-groups. Specific differences in PA patterns were revealed using the Frequency Extended Method with the high-resolution PA intensity spectrum in Swedish children and adolescents treated for valvular aortic stenosis.

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Effects of Body Mass Index on Bone Loading Due to Physical Activity

Journal of Applied Biomechanics ◽

10.1123/jab.2016-0126 ◽

2018 ◽

Vol 34 (1) ◽

pp. 7-13

Author(s):

Tina Smith ◽

Sue Reeves ◽

Lewis G. Halsey ◽

Jörg Huber ◽

Jin Luo

Keyword(s):

Physical Activity ◽

International Physical Activity Questionnaire ◽

Short Form ◽

Effect Sizes ◽

Moderate Activity ◽

Activity Levels ◽

Accelerometer Data ◽

Light Activity ◽

Bone Loading ◽

Activity Questionnaire

The aim of the current study was to compare bone loading due to physical activity between lean, and overweight and obese individuals. Fifteen participants (lower BMI group: BMI < 25 kg/m2, n = 7; higher BMI group: 25 kg/m2 < BMI < 36.35 kg/m2, n = 8) wore a tri-axial accelerometer on 1 day to collect data for the calculation of bone loading. The International Physical Activity Questionnaire (short form) was used to measure time spent at different physical activity levels. Daily step counts were measured using a pedometer. Differences between groups were compared using independent t-tests. Accelerometer data revealed greater loading dose at the hip in lower BMI participants at a frequency band of 0.1–2 Hz (P = .039, Cohen’s d = 1.27) and 2–4 Hz (P = .044, d = 1.24). Lower BMI participants also had a significantly greater step count (P = .023, d = 1.55). This corroborated with loading intensity (d ≥ 0.93) and questionnaire (d = 0.79) effect sizes to indicate higher BMI participants tended to spend more time in very light activity, and less time in light and moderate activity. Overall, participants with a lower BMI exhibited greater bone loading due to physical activity; participants with a higher BMI may benefit from more light and moderate level activity to maintain bone health.

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Development and Evaluation of an Accelerometer-Based Protocol for Measuring Physical Activity Levels in Cancer Survivors: Development and Usability Study

JMIR mhealth and uhealth ◽

10.2196/18491 ◽

2020 ◽

Vol 8 (9) ◽

pp. e18491

Author(s):

Tracy E Crane ◽

Meghan B Skiba ◽

Austin Miller ◽

David O Garcia ◽

Cynthia A Thomson

Keyword(s):

Physical Activity ◽

Ovarian Cancer ◽

Data Collection ◽

Cancer Survivors ◽

Accelerometer Data ◽

Activity Tracking ◽

Activity Data ◽

Convenience Sample ◽

Time Points ◽

Activity Measurements

Background The collection of self-reported physical activity using validated questionnaires has known bias and measurement error. Objective Accelerometry, an objective measure of daily activity, increases the rigor and accuracy of physical activity measurements. Here, we describe the methodology and related protocols for accelerometry data collection and quality assurance using the Actigraph GT9X accelerometer data collection in a convenience sample of ovarian cancer survivors enrolled in GOG/NRG 0225, a 24-month randomized controlled trial of diet and physical activity intervention versus attention control. Methods From July 2015 to December 2019, accelerometers were mailed on 1337 separate occasions to 580 study participants to wear at 4 time points (baseline, 6, 12, and 24 months) for 7 consecutive days. Study staff contacted participants via telephone to confirm their availability to wear the accelerometers and reviewed instructions and procedures regarding the return of the accelerometers and assisted with any technology concerns. Results We evaluated factors associated with wear compliance, including activity tracking, use of a mobile app, and demographic characteristics with chi-square tests and logistic regression. Compliant data, defined as ≥4 consecutive days with ≥10 hours daily wear time, exceeded 90% at all study time points. Activity tracking, but no other characteristics, was significantly associated with compliant data at all time points (P<.001). This implementation of data collection through accelerometry provided highly compliant and usable activity data in women who recently completed treatment for ovarian cancer. Conclusions The high compliance and data quality associated with this protocol suggest that it could be disseminated to support researchers who seek to collect robust objective activity data in cancer survivors residing in a wide geographic area.

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Classification and Processing of 24-Hour Wrist Accelerometer Data

Journal for the Measurement of Physical Behaviour ◽

10.1123/jmpb.2017-0008 ◽

2018 ◽

Vol 1 (2) ◽

pp. 51-59 ◽

Cited By ~ 7

Author(s):

Anna Pulakka ◽

Eric J. Shiroma ◽

Tamara B. Harris ◽

Jaana Pentti ◽

Jussi Vahtera ◽

...

Keyword(s):

Physical Activity ◽

Sedentary Time ◽

Total Activity ◽

Sleep Time ◽

Accelerometer Data ◽

Classification Methods ◽

Wake Time ◽

Wear Time ◽

Aging Study ◽

Activity Measures

Background: An important step in accelerometer data analysis is the classification of continuous, 24-hour data into sleep, wake, and non-wear time. We compared classification times and physical activity metrics across different data processing and classification methods.Methods: Participants (n = 576) from the Finnish Retirement and Aging Study (FIREA) wore an accelerometer on their non-dominant wrist for seven days and nights and filled in daily logs with sleep and waking times. Accelerometer data were first classified as sleep or wake time by log, and Tudor-Locke, Tracy, and ActiGraph algorithms. Then, wake periods were classified as wear or non-wear by log, Choi algorithm, and wear sensor. We compared time classification (sleep, wake, and wake wear time) as well as physical activity measures (total activity volume and sedentary time) across these classification methods.Results:M(SD) nightly sleep time was 467 (49) minutes by log and 419 (88), 522 (86), and 453 (74) minutes by Tudor-Locke, Tracy, and ActiGraph algorithms, respectively. Wake wear time did not differ substantially when comparing Choi algorithm and the log. The wear sensor did not work properly in about 29% of the participants. Daily sedentary time varied by 8–81 minutes after excluding sleep by different methods and by 1–18 minutes after excluding non-wear time by different methods. Total activity volume did not substantially differ across the methods.Conclusion: The differences in wear and sedentary time were larger than differences in total activity volume. Methods for defining sleep periods had larger impact on outcomes than methods for defining wear time.

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Physical activity and breast cancer risk: results from the UK Biobank prospective cohort

British Journal of Cancer ◽

10.1038/s41416-019-0700-6 ◽

2020 ◽

Vol 122 (5) ◽

pp. 726-732 ◽

Cited By ~ 6

Author(s):

Wenji Guo ◽

Georgina K. Fensom ◽

Gillian K. Reeves ◽

Timothy J. Key

Keyword(s):

Breast Cancer ◽

Physical Activity ◽

Breast Cancer Risk ◽

Cancer Risk ◽

Cox Regression ◽

Postmenopausal Breast Cancer ◽

Protective Role ◽

Accelerometer Data ◽

Uk Biobank ◽

Relative Risks

Abstract Background Previous studies suggest a protective role of physical activity in breast cancer risk, largely based on self-reported activity. We aimed to clarify this association by examining breast cancer risk in relation to self-reported physical activity, informed by accelerometer-based measures in a large subset of participants. Methods We analysed data from 47,456 premenopausal and 126,704 postmenopausal women in UK Biobank followed from 2006 to 2014. Physical activity was self-reported at baseline, and at resurvey in a subsample of 6443 participants. Accelerometer data, measured from 2013 to 2015, were available in 20,785 women. Relative risks (RRs) and 95% confidence intervals (CIs) were calculated by using multivariable-adjusted Cox regression. Results A total of 3189 cases were diagnosed during follow-up (mean = 5.7 years). Women in the top compared with the bottom quartile of self-reported physical activity had a reduced risk of both premenopausal (RR 0.75; 95% CI 0.60–0.93) and postmenopausal breast cancer (RR 0.87; 95% CI 0.78–0.98), after adjusting for adiposity. In analyses utilising physical activity values assigned from accelerometer measurements, an increase of 5 milli-gravity was associated with a 21% (RR 0.79; 95% CI 0.66–0.95) reduction in premenopausal and a 16% (RR 0.84; 95% CI 0.73–0.96) reduction in postmenopausal breast cancer risk. Conclusions Greater physical activity is associated with a reduction in breast cancer risk, which appears to be independent of any association it may have on risk through its effects on adiposity.

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Objective assessment of childhood adherence to Canadian physical activity guidelines in relation to body composition

Applied Physiology Nutrition and Metabolism ◽

10.1139/h06-083 ◽

2007 ◽

Vol 32 (2) ◽

pp. 217-224 ◽

Cited By ~ 22

Author(s):

Kristy Diane Marie Wittmeier ◽

Rebecca Christine Mollard ◽

Dean Johannes Kriellaars

Keyword(s):

Physical Activity ◽

Body Composition ◽

Body Fat ◽

Objective Assessment ◽

Fat Free Mass ◽

Moderate Activity ◽

Physical Activity Guidelines ◽

Beneficial Effects ◽

School Year ◽

Childhood Physical Activity

Low levels of childhood physical activity (PA) are a contributing factor to obesity. The objective of this study was to determine the adherence of children to PA guidelines in relation to body composition. Body fat (Slaughter equation) and body mass index (BMI) were determined during the school year (n = 251, ages 8–11 y). Daily energy expenditure (EE, kcal·kg–1·d–1) and activity time (AT, min·d–1) above moderate and vigorous intensity thresholds were assessed (accelerometry). Using EE criteria, 35.9% expended < 3.0 kcal·kg–1·d–1, 27.9% expended between 3.0 and 5.9 kcal·kg–1·d–1, 13.5% expended between 6.0 and 7.9 kcal·kg–1·d–1, and 22.9% expended ≥ 8.0 kcal·kg–1·d–1. Using AT criteria, 52.2% accumulated < 30.0 min, 31.1% accumulated 30.0–59.9 min, 12.7% accumulated 60.0–89.9 min, and 4.0% accumulated ≥ 90.0 min of AT. The EE corresponding to accumulation of AT > 90 min was 14.8 kcal·kg–1·d–1. The AT corresponding to ≥ 8 kcal·kg–1·d–1 was 73.0 min. Inverse relationships were observed between EE and body fat (p = 0.0004), BMI (p = 0.002), mass (p = 0.008), and fat mass index (FMI) (p = 0.001), as well as between AT and body fat (p = 0.001), BMI (p = 0.008), mass (p = 0.017), and FMI (p = 0.002). Controlling for BMI, FMI was inversely related to EE (p = 0.049) and AT (p = 0.039). Fat-free mass index and AT were positively related (p = 0.038). Physical activity had beneficial effects on body composition for children independent of BMI. The relationship between AT and daily EE guidelines was rationalized (60 min·d–1 with 8 kcal·kg–1·d–1) and demonstrated association with acceptable body composition. The 60 min·d–1 of moderate activity may be a more suitable initial target than 90 min·d–1, as so few children met the upper tiers of PA guidelines.

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