Daily physical activity assessment with accelerometers: new insights and validation studies

Validity of predictive equations for total energy expenditure against doubly labeled water

Variations in physical activity energy expenditure can make accurate prediction of total energy expenditure (TEE) challenging. The purpose of the present study was to determine the accuracy of available equations to predict TEE in individuals varying in physical activity (PA) levels. TEE was measured by DLW in 56 adults varying in PA levels which were monitored by accelerometry. Ten different models were used to predict TEE and their accuracy and precision were evaluated, considering the effect of sex and PA. The models generally underestimated the TEE in this population. An equation published by Plucker was the most accurate in predicting the TEE in our entire sample. The Pontzer and Vinken models were the most accurate for those with lower PA levels. Despite the levels of accuracy of some equations, there were sizable errors (low precision) at an individual level. Future studies are needed to develop and validate these equations.

Understanding frictional behavior in fascia tissues through tribological modeling and material substitution

The objective of this study is to develop a reliable tribological model to enable a more thorough investigation of the frictional behavior of fascia tissues connected to non-specific lower back pain. Several models were designed and evaluated based on their coefficient of friction, using a low-frequency, low-load reciprocating motion. The study found that two technical elastomers, layered on PDMS to simulate the fascia and underlying muscle, are suitable substitutes for biological tissue in the model. The influence of tribopair geometry was also examined, and the results showed that greater conformity of contact leads to a lower COF, regardless of the material combination used. Finally, the friction properties of HA of various molecular weights and concentrations were tested.

Ecological momentary assessment of physical activity and sedentary behaviour in shift workers and non-shift workers: Validation study

This study examined the criterion validity of an ecological momentary assessment (EMA)-reported physical activity and sedentary time compared with accelerometry in shift workers and non-shift workers. Australian workers (n = 102) received prompts through a mobile EMA app and wore the Actigraph accelerometer on the right hip for 7-10 days. Participants received five EMA prompts per day at 3-hour intervals on their mobile phones. EMA prompts sent to shift workers (SW-T) were tailored according to their work schedule. Non-shift workers (NSW-S) received prompts at standardised times. To assess criterion validity, the association of EMA-reported activities and the Actigraph accelerometer activity counts and number of steps were used. Participants were 36 ± 11 years and 58% were female. On occasions where participants reported physical activity, acceleration counts per minute (CPM) and steps were significantly higher (β = 1184 CPM, CI 95%: 1034, 1334; β = 20.9 steps, CI 95%: 18.2, 23.6) than each of the other EMA activities. Acceleration counts and steps were lower when sitting was reported than when no sitting was reported by EMA. Our study showed that EMA-reported physical activity and sedentary time was significantly associated with accelerometer-derived data. Therefore, EMA can be considered to assess shift workers' movement-related behaviours with accelerometers to provide rich contextual data.

Virtual fitness buddy ecosystem: a mixed reality precision health physical activity intervention for children

6-11-year-old children provide a critical window for physical activity (PA) interventions. The Virtual Fitness Buddy ecosystem is a precision health PA intervention for children integrating mixed reality technology to connect people and devices. A cluster randomized, controlled trial was conducted across 19 afterschool sites over two 6-month cohorts to test its efficacy in increasing PA and decreasing sedentary behavior. In the treatment group, a custom virtual dog via a mixed reality kiosk helped children set PA goals while sharing progress with parents to receive feedback and support. Children in the control group set PA goals using a computer without support from the virtual dog or parents. 303 children had 8+ hours of PA data on at least one day of each of the 3 intervention time intervals. Conversion of sedentary time was primarily to light-intensity PA and was strongest for children with low baseline moderate-to-vigorous PA than children above 45 min of baseline moderate-to-vigorous PA. Findings suggest that the VFB ecosystem can promote sustainable PA in children and may be rapidly diffused for widespread public health impact.

Responsiveness of Patient-Reported and Device-Based Physical Activity Measures: Secondary Analysis of Four Randomized Trials

PURPOSE

This study aimed to compare the responsiveness of patient-reported and device-based instruments within four physical activity trials.

METHODS

This was a secondary analysis of four randomized trials that used both a patient-reported outcome measure (the Incidental and Planned Exercise Questionnaire (IPEQ)) and a device-based instrument (ActiGraph or ActivPAL) to measure physical activity. The four trials included were (i) Activity and MObility UsiNg Technology (AMOUNT), digitally enabled exercises in those undertaking aged care and neurological rehabilitation; (ii) Balance Exercise Strength Training at Home, home-based balance and strength exercises in community-dwelling people 65 yr or older; (iii) Coaching for Healthy Ageing (CHAnGE), physical activity coaching and fall prevention intervention in community-dwelling people 60 yr or older; and (iv) Fitbit trial, fall prevention and physical activity promotion with health coaching and activity monitor in community-dwelling people 60 yr or older. We estimated treatment effects for all variables within each physical activity instrument using regression analyses and expressed results as effect sizes (ES).

RESULTS

Overall, device-based instruments were more responsive among healthy older adults (ES range, 0.01 to 0.32), whereas the IPEQ was more responsive among adults requiring rehabilitation (ES range, -0.06 to 0.35). Both the IPEQ and device-based instruments were more responsive in trials that promoted walking via coaching participants to increase their daily steps (AMOUNT (ES range, -0.06 to 0.35), CHAnGE (ES range, -0.24 to 0.22), and Fitbit trial (ES range, -0.23 to 0.32)). Individual variables within the IPEQ and device-based instruments varied in their responsiveness (ES range, -0.13 to 0.20).

CONCLUSIONS

Both the IPEQ and device-based instruments are able to detect small changes in physical activity levels. However, responsiveness varies across different interventions and populations. Our findings provide guidance for researchers and clinicians in selecting an appropriate instrument to measure changes in physical activity.

The use of commercial wrist-worn technology to track physiological outcomes in behavioral interventions

PURPOSE OF REVIEW

The aim of this review is to provide an overview of the use of commercial wrist-worn mobile health devices to track and monitor physiological outcomes in behavioral interventions as well as discuss considerations for selecting the optimal device.

RECENT FINDINGS

Wearable technology can enhance intervention design and implementation. The use of wrist-worn wearables provides the opportunity for tracking physiological outcomes, thus providing a unique approach for assessment and delivery of remote interventions. Recent findings support the utility, acceptability, and benefits of commercial wrist-worn wearables in interventions, and they can be used to continuously monitor outcomes, remotely administer assessments, track adherence, and personalize interventions. Wrist-worn devices show acceptable accuracy when measuring heart rate, blood pressure, step counts, and physical activity; however, accuracy is dependent on activity type, intensity, and device brand. These factors should be considered when designing behavioral interventions that utilize wearable technology.

SUMMARY

With the continuous advancement in technology and frequent product upgrades, the capabilities of commercial wrist-worn devices will continue to expand, thus increasing their potential use in intervention research. Continued research is needed to examine and validate the most recent devices on the market to better inform intervention design and implementation.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

The dilemma of physical activity questionnaires: Fitter people are less prone to over reporting

Physical activity questionnaires (PAQs) are a popular method of monitoring physical activity, although their validity is usually low. Descriptions of physical activity levels in questionnaires usually rely on physical responses to physical activity. Therefore, we hypothesised that the validity of PAQs would be higher in the more physically fit group of participants. To test this, we conducted a validation study with 179 adults whom we divided into three fitness groups based on their cardiovascular fitness and age. Participants were measured for one week using the UKK RM42 accelerometer and self-reported their physical activity using IPAQ-SF, GPAQ, and EHIS-PAQ. We analysed the differences between fitness groups in terms of validity for each PAQ using ANOVA. We also performed an equivalence testing to compare the data obtained with the PAQs and the accelerometers. The results showed a significant trend toward higher validity for moderate to vigorous physical activity from the low to high fitness group as assessed by GPAQ and IPAQ-SF (low, intermediate and high fitness group: 0.06-0.21; 0.26-0.29; 0.40, respectively). The equivalence testing showed that all fitness groups overestimated their physical activity and underestimated their sedentary behaviour, with the high fitness group overestimating their physical activity the least. However, EHIS-PAQ was found to agree best with accelerometer data in assessing moderate to vigorous physical activity, regardless of fitness group, and had a validity greater than 0.4 for all fitness groups. In conclusion, we confirmed that when using PAQs describing physical responses to physical activity, participants' fitness should be considered in the interpretation, especially when comparing results internationally.

Prediction of the Physical Activity Level of Community-Dwelling Older Japanese Adults with a Triaxial Accelerometer Containing a Classification Algorithm for Ambulatory and Non-Ambulatory Activities

Accurate methods for the prediction of the total energy expenditure and physical activity level (PAL) in community-dwelling older adults have not been established. Therefore, we examined the validity of estimating the PAL using an activity monitor (Active style Pro HJA-350IT, [ASP]) and proposed correction formulae for such populations in Japan. Data for 69 Japanese community-dwelling adults aged 65 to 85 years were used. The total energy expenditure in free-living conditions was measured with the doubly labeled water method and the measured basal metabolic rate. The PAL was also estimated from metabolic equivalent (MET) values obtained with the activity monitor. Adjusted MET values were also calculated with the regression equation of Nagayoshi et al. (2019). The observed PAL was underestimated, but significantly correlated, with the PAL from the ASP. When adjusted using the Nagayoshi et al. regression equation, the PAL was overestimated. Therefore, we developed regression equations to estimate the actual PAL (Y) from the PAL obtained with the ASP for young adults (X) as follows: women: Y = 0.949 × X + 0.205, mean ± standard deviation of the prediction error = 0.00 ± 0.20; men: Y = 0.899 × X + 0.371, mean ± standard deviation of the prediction error = 0.00 ± 0.17.

Impact of an Interdisciplinary Educational Programme on Students' Physical Activity and Fitness

Educational initiatives and actions are needed to provide students with skills to create active habits and lifestyles in order to increase the physical activity and fitness levels of young people. The main objective of this study was to analyse the effects of a classroom-based physical activity and life skills programme on students' physical activity and fitness levels. The sample consisted of 65 students in the 6th grade of Primary Education, aged between 11 and 13 years (11.86 ± 0.53), divided into a control group (CG) and an experimental group (EG) for convenience and accessibility. This was a quasi-experimental, repeated measures, longitudinal cut-off research design. For 16 weeks, an interdisciplinary educational programme based on a combination of classroom-based physical activity and life skills was implemented. The results showed that the educational programme had a positive effect on students' physical activity levels during school hours, specifically on reducing sedentary time (p < 0.001) and increasing light (p < 0.001) and moderate-to-vigorous (p < 0.001) physical activity. Positive effects were also found on the variables of explosive strength (p < 0.05) and aerobic capacity (p < 0.05) related to physical fitness. In conclusion, interdisciplinary educational programmes based on the promotion of physical activity and life skills could contribute to the development of responsible daily physical activity habits in students to facilitate their transfer to other environments (social and family) outside school.

Mining Sensor Data to Assess Changes in Physical Activity Behaviors in Health Interventions: Systematic Review

BACKGROUND

Sensors are increasingly used in health interventions to unobtrusively and continuously capture participants' physical activity in free-living conditions. The rich granularity of sensor data offers great potential for analyzing patterns and changes in physical activity behaviors. The use of specialized machine learning and data mining techniques to detect, extract, and analyze these patterns has increased, helping to better understand how participants' physical activity evolves.

OBJECTIVE

The aim of this systematic review was to identify and present the various data mining techniques employed to analyze changes in physical activity behaviors from sensors-derived data in health education and health promotion intervention studies. We addressed two main research questions: (1) What are the current techniques used for mining physical activity sensor data to detect behavior changes in health education or health promotion contexts? (2) What are the challenges and opportunities in mining physical activity sensor data for detecting physical activity behavior changes?

METHODS

The systematic review was performed in May 2021 using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. We queried the Association for Computing Machinery (ACM), IEEE Xplore, ProQuest, Scopus, Web of Science, Education Resources Information Center (ERIC), and Springer literature databases for peer-reviewed references related to wearable machine learning to detect physical activity changes in health education. A total of 4388 references were initially retrieved from the databases. After removing duplicates and screening titles and abstracts, 285 references were subjected to full-text review, resulting in 19 articles included for analysis.

RESULTS

All studies used accelerometers, sometimes in combination with another sensor (37%). Data were collected over a period ranging from 4 days to 1 year (median 10 weeks) from a cohort size ranging between 10 and 11615 (median 74). Data preprocessing was mainly carried out using proprietary software, generally resulting in step counts and time spent in physical activity aggregated predominantly at the daily or minute level. The main features used as input for the data mining models were descriptive statistics of the preprocessed data. The most common data mining methods were classifiers, clusters, and decision-making algorithms, and these focused on personalization (58%) and analysis of physical activity behaviors (42%).

CONCLUSIONS

Mining sensor data offers great opportunities to analyze physical activity behavior changes, build models to better detect and interpret behavior changes, and allow for personalized feedback and support for participants, especially where larger sample sizes and longer recording times are available. Exploring different data aggregation levels can help detect subtle and sustained behavior changes. However, the literature suggests that there is still work remaining to improve the transparency, explicitness, and standardization of the data preprocessing and mining processes to establish best practices and make the detection methods easier to understand, scrutinize, and reproduce.

The energetics of childhood: Current knowledge and insights into human variation, evolution, and health

How organisms capture and ultimately use metabolic energy-a limiting resource of life-has profound implications for understanding evolutionary legacies and current patterns of phenotypic variation, adaptation, and health. Energetics research among humans has a rich history in biological anthropology and beyond. The energetics of childhood, however, remains relatively underexplored. This shortcoming is notable given the accepted importance of childhood in the evolution of the unique human life history pattern as well as the known sensitivity of childhood development to local environments and lived experiences. In this review, I have three objectives: (1) To overview current knowledge regarding how children acquire and use energy, highlighting work among diverse human populations and pointing to recent advances and remaining areas of uncertainty; (2) To discuss key applications of this knowledge for understanding human variation, evolution, and health; (3) To recommend future avenues for research. A growing body of evidence supports a model of trade-offs and constraint in childhood energy expenditure. This model, combined with advancements on topics such as the energetics of immune activity, the brain, and the gut, provides insights into the evolution of extended human subadulthood and the nature of variation in childhood development, lifetime phenotype, and health.

Recognizing Human Activity of Daily Living Using a Flexible Wearable for 3D Spine Pose Tracking

The World Health Organization recognizes physical activity as an influencing domain on quality of life. Monitoring, evaluating, and supervising it by wearable devices can contribute to the early detection and progress assessment of diseases such as Alzheimer's, rehabilitation, and exercises in telehealth, as well as abrupt events such as a fall. In this work, we use a non-invasive and non-intrusive flexible wearable device for 3D spine pose measurement to monitor and classify physical activity. We develop a comprehensive protocol that consists of 10 indoor, 4 outdoor, and 8 transition states activities in three categories of static, dynamic, and transition in order to evaluate the applicability of the flexible wearable device in human activity recognition. We implement and compare the performance of three neural networks: long short-term memory (LSTM), convolutional neural network (CNN), and a hybrid model (CNN-LSTM). For ground truth, we use an accelerometer and strips data. LSTM reached an overall classification accuracy of 98% for all activities. The CNN model with accelerometer data delivered better performance in lying down (100%), static (standing = 82%, sitting = 75%), and dynamic (walking = 100%, running = 100%) positions. Data fusion improved the outputs in standing (92%) and sitting (94%), while LSTM with the strips data yielded a better performance in bending-related activities (bending forward = 49%, bending backward = 88%, bending right = 92%, and bending left = 100%), the combination of data fusion and principle components analysis further strengthened the output (bending forward = 100%, bending backward = 89%, bending right = 100%, and bending left = 100%). Moreover, the LSTM model detected the first transition state that is similar to fall with the accuracy of 84%. The results show that the wearable device can be used in a daily routine for activity monitoring, recognition, and exercise supervision, but still needs further improvement for fall detection.

Acceptability and use of waist-worn physical activity monitors in Jamaican adolescents: lessons from the field

OBJECTIVE

We report our experience with a validated waist-worn activity monitor in Jamaican adolescents attending urban high schools. Seventy-nine adolescents from the Global Diet and Activity Research (GDAR) study, recruited from 5 urban Jamaican high schools (two coeducational (n = 37), two all-female schools (n = 32) and one all-boys school (n = 10)) were asked to wear Actigraph wGT3X-BT accelerometers for 7 days (24-h), removing the device only when bathing or swimming. They also logged wake up and bed times in an activity diary. Accelerometry was considered valid if at least 4 days with ≥ 10-h monitor wear were recorded. Validity was compared by adolescent demographic and school characteristics. We also reviewed the students' written feedback on objective physical activity measurement.

RESULTS

Participants, 80.5% female, had a mean age of 15.5 ± 0.8 years with 60% attending schools in low-income communities. Accelerometer return rates were > 98% with 84% providing valid data. Validity did not vary by age group, sex and school setting. While participants were excited about participating in the accelerometer sub-study, commonly reported challenges included monitor discomfort during sleep and maintaining the study diary. Objective measurement of physical activity using 24-h waist-worn accelerometers is feasible and acceptable in Jamaican adolescents.

High daily energy expenditure of Tuvan nomadic pastoralists living in an extreme cold environment

Research investigating thermoregulatory energy costs in free-living humans is limited. We determined the total energy expenditure (TEE) of Tuvan pastoralists living in an extreme cold environment and explored the contribution of physical activity and cold-induced thermogenesis. Twelve semi-nomadic pastoralists (47 ± 8 years, 64 ± 8 kg) living under traditional circumstances, in Tuva, south-central Siberia, Russia, were observed during two consecutive 6-day periods in winter. TEE was measured via the doubly labelled water technique. Skin and ambient temperatures, and physical activity were continuously monitored. The outdoor temperature during the observation period was - 27.4 ± 5.4 °C. During the daytime, the participants were exposed to ambient temperatures below 0 °C for 297 ± 131 min/day. The Tuvan pastoralists were more physically active compared to western populations (609 ± 90 min/day of light, moderate, and vigorous physical activity). In addition, TEE was 13.49 ± 1.33 MJ/day (3224 ± 318 kcal/day), which was significantly larger by 17% and 31% than predicted by body mass, and fat-free mass, respectively. Our research suggests the daily cold exposure combined with high levels of physical activity contributed to the elevated TEE. Future research should reconsider the assumption that energy costs due to thermoregulation are negligible in free-living humans.

Validation of accelerometer placement to capture energy expenditure using doubly labeled water

This study compared accelerometer-measured physical activity by body placement to daily total energy expenditure (TEE) and activity energy expenditure (AEE) measured using doubly labeled water (DLW). Forty-nine adult participants wore accelerometers placed on the nondominant wrist, dominant wrist, and chest while also undergoing DLW assessments. In adjusted models, wrist-measured physical activity (p < 0.05), but not chest-measured physical activity (p > 0.05), was associated with TEE and AEE and explained a significant amount of variance that was not explained by age, sex, height, or body composition (R2 change = 0.04-0.08; all p < 0.05). Accelerometer placement location is an important consideration when using accelerometry to provide information about energy expenditure.

Agreement between Fitbit and ActiGraph Estimates of Physical Activity in Young Children

Physical activity (PA) estimates from the Fitbit Flex 2 were compared to those from the ActiGraph GT9X Link in 123 elementary school children. Steps and intensity-specific estimates of PA and 3-month PA change were calculated using two different ActiGraph cut-points (Evenson and Romanzini). Fitbit estimates were 35% higher for steps compared to the ActiGraph. Fitbit and ActiGraph intensity-specific estimates were closest for sedentary and light PA while estimates of moderate and vigorous PA varied substantially depending upon the ActiGraph cut-points used. Spearman correlations between device estimates were higher for steps (rs=.70) than for moderate (rs =.54 to .55) or vigorous (rs =.29 to .48) PA. There was low concordance between devices in assessing PA changes over time. Agreement between Fitbit Flex 2 and ActiGraph estimates may depend upon the cut-points used to classify PA intensity. However, there is fair to good agreement between devices in ranking children's steps and MVPA.

Wearables for Measuring the Physical Activity and Sedentary Behavior of Patients With Axial Spondyloarthritis: Systematic Review

Background

Axial spondyloarthritis (axSpA) is an inflammatory rheumatic disease associated with chronic back pain and restricted mobility and physical function. Increasing physical activity is a viable strategy for improving the health and quality of life of patients with axSpA. Thus, quantifying physical activity and sedentary behavior in this population is relevant to clinical outcomes and disease management. However, to the best of our knowledge, no systematic review to date has identified and synthesized the available evidence on the use of wearable devices to objectively measure the physical activity or sedentary behavior of patients with axSpA.

Objective

This study aimed to review the literature on the use of wearable activity trackers as outcome measures for physical activity and sedentary behavior in patients with axSpA.

Methods

PubMed, PEDro, and Cochrane electronic databases were searched in July 2021 for relevant original articles, with no limits on publication dates. Studies were included if they were original articles, targeted adults with a diagnosis of axSpA, and reported wearable device–measured physical activity or sedentary behavior among patients with axSpA. Data regarding the study’s characteristics, the sample description, the methods used for measuring physical activity and sedentary behavior (eg, wearable devices, assessment methods, and outcomes), and the main results of the physical activity and sedentary behavior assessments were extracted.

Results

A total of 31 studies were initially identified; 13 (13/31, 42%) met the inclusion criteria, including 819 patients with axSpA. All the studies used accelerometer-based wearable devices to assess physical activity. Of the 13 studies, 4 (4/31, 31%) studies also reported outcomes related to sedentary behavior. Wearable devices were secured on the wrists (3/13 studies, 23%), lower back (3/13, 23%), right hip (3/13, 23%), waist (2/13, 15%), anterior thigh (1/13, 8%), or right arm (1/13, 8%). The methods for reporting physical activity and sedentary behavior were heterogeneous. Approximately 77% (10/13) of studies had a monitoring period of 1 week, including weekend days.

Conclusions

To date, few studies have used wearable devices to quantify the physical activity and sedentary behavior of patients with axSpA. The methodologies and results were heterogeneous, and none of these studies assessed the psychometric properties of these wearables in this specific population. Further investigation in this direction is needed before using wearable device–measured physical activity and sedentary behavior as outcome measures in intervention studies in patients with axSpA.

Trial Registration

PROSPERO CRD42020182398; https://tinyurl.com/ec22jzkt

International Registered Report Identifier (IRRID)

RR2-10.2196/23359

Validity and Relative Validity of Alternative Methods of Assessing Physical Activity in Epidemiologic Studies: Findings From the Men's Lifestyle Validation Study

In the Men's Lifestyle Validation Study (2011-2013), we examined the validity and relative validity of a physical activity questionnaire (PAQ), a Web-based 24-hour recall (Activities Completed Over Time in 24 Hours (ACT24)), and an accelerometer by multiple comparison methods. Over the course of 1 year, 609 men completed 2 PAQs, two 7-day accelerometer measurements, at least 1 doubly labeled water (DLW) physical activity level (PAL) measurement (n = 100 with repeat measurements), and 4 ACT24s; they also measured their resting pulse rate. A subset (n = 197) underwent dual-energy x-ray absorptiometry (n = 99 with repeated measurements). The method of triads was used to estimate correlations with true activity using DLW PAL, accelerometry, and the PAQ or ACT24 as alternative comparison measures. Estimated correlations of the PAQ with true activity were 0.60 (95% confidence interval (95% CI): 0.52, 0.68) for total activity, 0.69 (95% CI: 0.61, 0.79) for moderate-to-vigorous physical activity (MVPA), and 0.76 (95% CI: 0.62, 0.93) for vigorous activity. Corresponding correlations for total activity were 0.53 (95% CI: 0.45, 0.63) for the average of 4 ACT24s and 0.68 (95% CI: 0.61, 0.75) for accelerometry. Total activity and MVPA measured by PAQ, ACT24, and accelerometry were all significantly correlated with body fat percentage and resting pulse rate, which are physiological indicators of physical activity. Using a combination of comparison methods, we found the PAQ and accelerometry to have moderate validity for assessing physical activity, especially MVPA, in epidemiologic studies.

Measuring change in adolescent physical activity: Responsiveness of a single item

Self-report measures are frequently used to assess change in physical activity (PA) levels. Given the limited data from adolescent populations, the primary objective of this study was to examine the responsiveness of a single item measure (SIM) of PA for adolescents to detect change in moderate-to-vigorous physical activity (MVPA) using accelerometer data as the reference measure. A secondary objective was to provide further data on the validity of the measure at one point in time. The validity of the SIM to determine the number of days ≥60 minutes of MVPA was based on data from 200 participants (62% female; age: 14.0 ± 1.6 years) and analysis of change was based on data from 177 participants (65% female; age: 14.0 ± 1.6 years). Validity of change in days ≥60 minutes of MVPA was examined through agreement in classification of change between the SIM and accelerometry as the reference measurement and Spearman’s correlation. Cohen’s d and standardised response means were used to assess the responsiveness to change of the measure. The responsiveness of the SIM and accelerometer data were comparable and modest (0.27–0.38). The correlation for change in number of days ≥60 minutes MVPA between the SIM and accelerometery was low (r = 0.11) and the accuracy of the SIM for detecting change, using accelerometry as the reference, was only marginally above chance (53%). Therefore, the adolescent version of the SIM is adequate for assessing PA at a single time point but not recommended for assessing change.

Using digital health tools for the Remote Assessment of Treatment Prognosis in Depression (RAPID): a study protocol for a feasibility study

INTRODUCTION

Digital health tools such as smartphones and wearable devices could improve psychological treatment outcomes in depression through more accurate and comprehensive measures of patient behaviour. However, in this emerging field, most studies are small and based on student populations outside of a clinical setting. The current study aims to determine the feasibility and acceptability of using smartphones and wearable devices to collect behavioural and clinical data in people undergoing therapy for depressive disorders and establish the extent to which they can be potentially useful biomarkers of depression and recovery after treatment.

METHODS AND ANALYSIS

This is an observational, prospective cohort study of 65 people attending psychological therapy for depression in multiple London-based sites. It will collect continuous passive data from smartphone sensors and a Fitbit fitness tracker, and deliver questionnaires, speech tasks and cognitive assessments through smartphone-based apps. Objective data on sleep, physical activity, location, Bluetooth contact, smartphone use and heart rate will be gathered for 7 months, and compared with clinical and contextual data. A mixed methods design, including a qualitative interview of patient experiences, will be used to evaluate key feasibility indicators, digital phenotypes of depression and therapy prognosis. Patient and public involvement was sought for participant-facing documents and the study design of the current research proposal.

ETHICS AND DISSEMINATION

Ethical approval has been obtained from the London Westminster Research Ethics Committee, and the Health Research Authority, Integrated Research Application System (project ID: 270918). Privacy and confidentiality will be guaranteed and the procedures for handling, processing, storage and destruction of the data will comply with the General Data Protection Regulation. Findings from this study will form part of a doctoral thesis, will be presented at national and international meetings or academic conferences and will generate manuscripts to be submitted to peer-reviewed journals.

TRIAL REGISTRATION NUMBER

https://doi.org/10.17605/OSF.IO/PMYTA.

Wearable activity trackers-advanced technology or advanced marketing?

Wearable devices represent one of the most popular trends in health and fitness. Rapid advances in wearable technology present a dizzying display of possible functions: from thermometers and barometers, magnetometers and accelerometers, to oximeters and calorimeters. Consumers and practitioners utilize wearable devices to track outcomes, such as energy expenditure, training load, step count, and heart rate. While some rely on these devices in tandem with more established tools, others lean on wearable technology for health-related outcomes, such as heart rhythm analysis, peripheral oxygen saturation, sleep quality, and caloric expenditure. Given the increasing popularity of wearable devices for both recreation and health initiatives, understanding the strengths and limitations of these technologies is increasingly relevant. Need exists for continued evaluation of the efficacy of wearable devices to accurately and reliably measure purported outcomes. The purposes of this review are (1) to assess the current state of wearable devices using recent research on validity and reliability, (2) to describe existing gaps between physiology and technology, and (3) to offer expert interpretation for the lay and professional audience on how best to approach wearable technology and employ it in the pursuit of health and fitness. Current literature demonstrates inconsistent validity and reliability for various metrics, with algorithms not publicly available or lacking high-quality validation studies. Advancements in wearable technology should consider standardizing validation metrics, providing transparency in used algorithms, and improving how technology can be tailored to individuals. Until then, it is prudent to exercise caution when interpreting metrics reported from consumer-wearable devices.

The Validity of the Energy Expenditure Criteria Based on Open Source Code through two Inertial Sensors

Through this study, we developed and validated a system for energy expenditure calculation, which only requires low-cost inertial sensors and open source R software. Five healthy subjects ran at ten different speeds while their kinematic variables were recorded on the thigh and wrist. Two ActiGraph wireless inertial sensors and a low-cost Bluetooth-based inertial sensor (Lis2DH12), assembled by SensorID, were used. Ten energy expenditure equations were automatically calculated in a developed open source R software (our own creation). A correlation analysis was used to compare the results of the energy expenditure equations. A high interclass correlation coefficient of estimated energy expenditure on the thigh and wrist was observed with an Actigraph and Sensor ID accelerometer; the corrected Freedson equation showed the highest values, and the Santos-Lozano vector magnitude equation and Sasaki equation demonstrated the lowest one. Energy expenditure was compared between the wrist and thigh and showed low correlation values. Despite the positive results obtained, it was necessary to design specific equations for the estimation of energy expenditure measured with inertial sensors on the thigh. The use of the same formula equation in two different placements did not report a positive interclass correlation coefficient.

Digital health tools for the passive monitoring of depression: a systematic review of methods

The use of digital tools to measure physiological and behavioural variables of potential relevance to mental health is a growing field sitting at the intersection between computer science, engineering, and clinical science. We summarised the literature on remote measuring technologies, mapping methodological challenges and threats to reproducibility, and identified leading digital signals for depression. Medical and computer science databases were searched between January 2007 and November 2019. Published studies linking depression and objective behavioural data obtained from smartphone and wearable device sensors in adults with unipolar depression and healthy subjects were included. A descriptive approach was taken to synthesise study methodologies. We included 51 studies and found threats to reproducibility and transparency arising from failure to provide comprehensive descriptions of recruitment strategies, sample information, feature construction and the determination and handling of missing data. The literature is characterised by small sample sizes, short follow-up duration and great variability in the quality of reporting, limiting the interpretability of pooled results. Bivariate analyses show consistency in statistically significant associations between depression and digital features from sleep, physical activity, location, and phone use data. Machine learning models found the predictive value of aggregated features. Given the pitfalls in the combined literature, these results should be taken purely as a starting point for hypothesis generation. Since this research is ultimately aimed at informing clinical practice, we recommend improvements in reporting standards including consideration of generalisability and reproducibility, such as wider diversity of samples, thorough reporting methodology and the reporting of potential bias in studies with numerous features.

A meta-analysis of Fitbit devices: same company, different models, different validity evidence

Fitbit devices are among the most commonly used physical activity devices used by the general public. Multiple studies have examined the validity evidence of Fitbit devices of estimating energy expenditure during physical activity compared to criterion references. However, the literature lacks objective, summary validity evidence that supports the use of various models of Fitbit devices. Therefore, this study aims (a) to examine the validity evidence among the various models of Fitbit devices and (b) to investigate the influence of several device factors on the validity evidence of Fitbit models using meta-analysis. A total of 402 articles were identified through five databases. Upon review of the articles, 29 studies were included in the meta-analysis. Seven different moderator variables, including Fitbit model, device placement, type of device, heart rate capability, release year of devices, activity types and sedentary activity, were identified and included in the meta-analysis to examine their impact on the validity evidence of Fitbit devices. The summarised validity coefficient of energy expenditure during physical activity estimated by Fitbit devices and measured by criterion references was r=.64 (k = 29, 95% CI [.59, .69], p<.001). Fitbit model was not found to be a significant factor impacting validity evidence of Fitbit devices, but heart rate capability, activity types and sedentary activity were found to be significant factors impacting validity evidence. This study found that not all Fitbit models have a similar ability in estimating energy expenditure during physical activity. Continued research is needed in examining the validity evidence of Fitbit devices, especially considering some factors may affect the validity evidence in measuring energy expenditure during physical activity.

Validity of Domain-Specific Sedentary Time Using Accelerometer and Questionnaire with activPAL Criterion

Accelerometers based on the cut-point method are generally the most used in sedentary time (ST) research. However, mixed cut-points are an issue, so an accelerometer based on metabolic equivalents (METs) could be used as an alternative. This study aimed to validate a METs-based accelerometer (HJA-750C, OMRON) and a questionnaire that estimates domain-specific sedentary time measures using activPAL as a criterion value. We also examined whether measurement validity differed according to gender and occupation. We used data from 242 workers in the validation study. Participants wore activPAL on the thigh and OMRON on the waist for seven consecutive days with daily recording logs. The Workers Living Activity-time Questionnaire (WLAQ) was administered once. The domain-specific ST assessed quantities of ST during commuting, working time, non-working time on a workday, and non-workday. Intraclass correlation coefficients (ICC) and Spearman's rho coefficients were then used to conduct analyses. The OMRON accelerometer showed acceptable values (r = 0.67-0.86 and ICC of 0.63-0.87) in the overall domain-specific ST. Additionally, each measurement result suggested that working time is the most accurate domain to measure ST (ICC of 0.87 for OMRON and 0.68 for WLAQ). Moreover, there were no differences in the overall validity of the results according to gender and occupation. The METs-based accelerometer has acceptable validity for ST measurements to be used among workers. Additionally, working time may be the preferred domain for the accurate assessment of ST in both objective and subjective measurements. These results can advance the quality of the sedentary research field.

Rolling out physical exercise and energy homeostasis: Focus on hypothalamic circuitries

Energy balance is the fine regulation of energy expenditure and energy intake. Negative energy balance causes body weight loss, while positive energy balance promotes weight gain. Modern societies offer a maladapted way of life, where easy access to palatable foods and the lack of opportunities to perform physical activity are considered the roots of the obesity pandemic. Physical exercise increases energy expenditure and, consequently, is supposed to promote weight loss. Paradoxically, physical exercise acutely drives anorexigenic-like effects, but the mechanisms are still poorly understood. Using an evolutionary background, this review aims to highlight the potential involvement of the melanocortin system and other hypothalamic neural circuitries regulating energy balance during and after physical exercise. The physiological significance of these changes will be explored, and possible signalling agents will be addressed. The knowledge discussed here might be important for clarifying obesity aetiology as well as new therapeutic approaches for body weight loss.

Monitoring work and training load in military settings - what's in the toolbox?

Military personnel are required to complete physically demanding tasks when performing work and training, which may be quantified through the physical stress imposed (external load) or the resultant physiological strain (internal load). The aim of this narrative review is to provide an overview of the techniques used to monitor work and training load in military settings, summarise key findings, and discuss important practical, analytical, and conceptual considerations. Most investigations have focused upon measuring external and internal load in military training environments; however, limited data exist in operational settings. Accelerometry has been the primary tool used to estimate external load, with heart rate commonly used to quantify internal load. Supplemental to heart rate, psychophysiological and biochemical measures have also been investigated to elucidate aspects of internal load. Broadly, investigations have revealed that military training requires personnel to perform relatively large volumes of physical activity (e.g. averaging ∼15,000 steps·day^-1) of typically low-moderate intensity activity (<6 MET), although considerable temporal and inter-individual variability is observed from these gross mean estimates. There are limitations associated with these measures and, at best, estimates of external and internal load can only be inferred. These limitations are particularly pertinent for military tasks such as load carriage and manual material handling, which often involve complex activities performed individually or in teams, in a range of operational environments, with multiple layers of protection, over a protracted duration. Comprehensively quantifying external and internal loads during these functional activities poses substantial practical and analytical challenges.

Perspective: Opportunities and Challenges of Technology Tools in Dietary and Activity Assessment: Bridging Stakeholder Viewpoints

The science and tools of measuring energy intake and output in humans have rapidly advanced in the last decade. Engineered devices such as wearables and sensors, software applications, and Web-based tools are now ubiquitous in both research and consumer environments. The assessment of energy expenditure in particular has progressed from reliance on self-report instruments to advanced technologies requiring collaboration across multiple disciplines, from optics to accelerometry. In contrast, assessing energy intake still heavily relies on self-report mechanisms. Although these tools have improved, moving from paper-based to online reporting, considerable room for refinement remains in existing tools, and great opportunities exist for novel, transformational tools, including those using spectroscopy and chemo-sensing. This report reviews the state of the science, and the opportunities and challenges in existing and emerging technologies, from the perspectives of 3 key stakeholders: researchers, users, and developers. Each stakeholder approaches these tools with unique requirements: researchers are concerned with validity, accuracy, data detail and abundance, and ethical use; users with ease of use and privacy; and developers with high adherence and utilization, intellectual property, licensing rights, and monetization. Cross-cutting concerns include frequent updating and integration of the food and nutrient databases on which assessments rely, improving accessibility and reducing disparities in use, and maintaining reliable technical assistance. These contextual challenges are discussed in terms of opportunities and further steps in the direction of personalized health.

Assessment of Physical Activity in Adults using Wrist Accelerometers

The health benefits of physical activity have been widely recognized, yet traditional measures of physical activity including questionnaires and category-based assessments of volume and intensity provide only broad estimates of daily activities. Accelerometers have advanced epidemiologic research on physical activity by providing objective and continuous measurement of physical activity in free-living conditions. Wrist-worn accelerometers have become especially popular due to low participant burden. However, the validity and reliability of wrist-worn devices for adults have yet to be summarized. Moreover, accelerometer data provide rich information on how physical activity is accumulated throughout the day, but only a small portion of these rich data have been utilized by researchers. Lastly, new methodological developments that aim to overcome some of the limitations of accelerometers are emerging. The purpose of this review is to provide an overview of accelerometry research, with a special focus on wrist-worn accelerometers. We describe briefly how accelerometers work, summarize the validity and reliability of wrist-worn accelerometers, discuss the benefits of accelerometers including measuring light-intensity physical activity, and discuss pattern metrics of daily physical activity recently introduced in the literature. A summary of large-scale cohort studies and randomized trials that implemented wrist-worn accelerometry is provided. We conclude the review by discussing new developments and future directions of research using accelerometers, with a focus on wrist-worn accelerometers.

Physical activity accumulation along the intensity spectrum differs between children and adults

PURPOSE

Detailed exploration of physical activity accumulation with fine grading along the intensity spectrum has indicated the potential pragmatic utility of such an approach. However, it is currently unclear what sorts of accumulation patterns along particular intensity bands are found in the children and adult populations. Therefore, we conducted a comparison of activity accumulation in specific intensity bands between four distinct populations: children, adults with sedentary lifestyles, habitual joggers, habitual marathon runners.

METHODS

Free-living waist-worn accelerometry records from 28 children aged 7 to 11, and 61 adults aged 25 to 35 were analysed. Activity intensity was evaluated in 5 s non-overlapping epochs as mean amplitude deviation (MAD) and normalised to acceleration intensities corresponding to walking at 3 metabolic equivalents of a task (METs). Adult data were normalised to 0.091 g MAD based on literature, and data from children to 0.170 g MAD based on laboratory experimentation. The normalised epoch values were divided into 100 intensity gradations.

RESULTS

Children accumulated more activity in 0.74 to 1.58 normalised acceleration intensities (all p < 0.005) compared to adults. Adult joggers/runners accumulated more activity in normalised acceleration intensities from 7.1 to 11.1 compared to the other groups (p < 0.008).

CONCLUSION

The primary bulk of children's free-living activities are of relatively low intensity not likely to provoke cardiometabolic improvement. These sorts of explorations could be used in informing intervention development aiming at optimising healthy development. Evidence is mounting to justify randomised controlled trials based on intervention targets identified based on exploring the intensity spectrum.

Associations between the built environment and dietary intake, physical activity, and obesity: A scoping review of reviews

There exists a large body of literature examining the association between built environment factors and dietary intake, physical activity, and weight status; however, synthesis of this literature has been limited. To address this gap, we conducted a scoping review of reviews and identified 74 reviews and meta-analyses that investigated the association between built environment factors and dietary intake, physical activity, and/or weight status. Results across reviews were mixed, with heterogeneous effects demonstrated in terms of strength and statistical significance; however, preliminary support was identified for several built environment factors. For example, quality of dietary intake appeared to be associated with the availability of grocery stores, higher levels of physical activity appeared to be most consistently associated with greater walkability, and lower weight status was associated with greater diversity in land-use mix. Overall, reviews reported substantial concern regarding methodological limitations and poor quality of existing studies. Future research should focus on improving study quality (e.g., using longitudinal methods, including natural experiments, and newer mobile sensing technologies) and consensus should be drawn regarding how to define and measure both built environment factors and weight-related outcomes.

Factors associated with validity of consumer-oriented wearable physical activity trackers: a meta-analysis

The purposes of this study were to examine (1) the strength of the criterion validity evidence of various consumer-oriented wearable physical activity trackers, (2) the influence of brands of consumer-oriented wearable physical activity on validity evidence and (3) factors that may contribute to differences in the strength of the criterion validity evidence. A total of 589 articles were identified through four databases. Pairs of researchers reviewed the articles to determine eligibility. A total of 29 studies with 96 validity coefficients were included in the meta-analysis. Five different moderators, including the brands of physical activity trackers, placement of devices, type of activities (ambulatory vs. lifestyle activities), population, and release year, were analysed to examine which factors impact the validity evidence. The summarised validity coefficient between activity trackers and energy expenditure ranged from r = .41 to r = .91. Moderator analyses revealed that the brand, placement of the device, and population significantly impact the magnitude of the validity evidence, while the type of activity and release year of the devices do not. Device brand, population, andplacement are each factor that significantly affects the validity coefficientsbetween consumer-oriented wearable physical activity trackers. Efforts should be made to improve the accuracy of these devices to maintain the credibility of the research and the trust of consumers.

Childhood Daily Energy Expenditure Does Not Decrease with Market Integration and Is Not Related to Adiposity in Amazonia

BACKGROUND

Childhood overweight and obesity (OW/OB) is increasingly centered in low- and middle-income countries (LMICs) as rural populations experience market integration and lifeway change. Most explanatory studies have relied on imprecise estimates of children's energy expenditure, restricting understanding of the relative effects of changes in diet and energy expenditure on the development of OW/OB in transitioning contexts.

OBJECTIVES

This study used gold-standard measurements of children's energy expenditure to investigate the changes that underlie OW/OB and the nutrition/epidemiologic transition.

METHODS

Cross-sectional data were collected from "rural" (n = 43) Shuar forager-horticulturalist children and their "peri-urban" (n = 34) Shuar counterparts (age 4-12 y) in Amazonian Ecuador. Doubly labeled water measurements of total energy expenditure (TEE; kcal/d), respirometry measurements of resting energy expenditure (REE; kcal/d), and measures of diet, physical activity, immune activity, and market integration were analyzed primarily using regression models.

RESULTS

Peri-urban children had higher body fat percentage (+8.1%, P < 0.001), greater consumption of market-acquired foods (multiple P < 0.001), lower concentrations of immune activity biomarkers (multiple P < 0.05), and lower REE (-108 kcal/d, P = 0.002) than rural children. Despite these differences, peri-urban children's TEE was indistinguishable from that of rural children (P = 0.499). Moreover, although sample-wide IgG concentrations and household incomes predicted REE (both P < 0.05), no examined household, immune activity, or physical activity measures were related to children's overall TEE (all P > 0.09). Diet and energy expenditure associations with adiposity demonstrate that only reported consumption of market-acquired "protein" and "carbohydrate" foods predicted children's body fat levels (multiple P < 0.05).

CONCLUSIONS

Despite underlying patterns in REE, Shuar children's TEE is not reliably related to market integration and-unlike dietary measures-does not predict adiposity. These findings suggest a leading role of changing dietary intake in transitions to OW/OB in LMICs.

Criterion validity of The International Physical Activity Questionnaire-Short Form (IPAQ-SF) for use in clinical practice in patients with osteoarthritis

BACKGROUND

To tailor physical activity treatment programs for patients with osteoarthritis, clinicians need valid and feasible measurement tools to evaluate habitual physical activity. The widely used International Physical Activity Questionnaire-Short Form (IPAQ-SF) is not previously validated in patients with osteoarthritis.

PURPOSE

To assess the concurrent criterion validity of the IPAQ-SF in patients with osteoarthritis, using an accelerometer as a criterion-method.

METHOD

Patients with osteoarthritis (n = 115) were recruited at The Division of Rheumatology and Research at Diakonhjemmet Hospital (Oslo, Norway). Physical activity was measured by patients wearing an accelerometer (ActiGraph wGT3X-BT) for seven consecutive days, followed by reporting their physical activity for the past 7 days using the IPAQ-SF. Comparison of proportions that fulfilled physical activity recommendations as measured by the two methods were tested by Pearson Chi-Square analysis. Differences in physical activity levels between the IPAQ-SF and the accelerometer were analyzed with Wilcoxon Signed-Rank Test and Spearman rank correlation test. Bland-Altman plots were used to visualize the concurrent criterion validity for total- and intensity-specific physical activity levels.

RESULTS

In total, 93 patients provided complete physical activity data, mean (SD) age was 65 (8.7) years, 87% were women. According to the IPAQ-SF, 57% of the patients fulfilled the minimum physical activity recommendations compared to 31% according to the accelerometer (p = 0.043). When comparing the IPAQ-SF to the accelerometer we found significant under-reporting of total physical activity MET-minutes (p = < 0.001), sitting (p = < 0.001) and walking (p < 0.001), and significant over-reporting of moderate-to-vigorous physical activity (p < 0.001). For the different physical activity levels, correlations between the IPAQ-SF and the accelerometer ranged from rho 0.106 to 0.462. The Bland-Altman plots indicated an increased divergence between the two methods with increasing time spent on moderate-to-vigorous intensity physical activity.

CONCLUSION

Physical activity is a core treatment of osteoarthritis. Our finding that patients tend to over-report activity of higher intensity and under-report low-intensity activity and sitting-time is of clinical importance. We conclude that the concurrent criterion validity of the IPAQ-SF was weak in patients with osteoarthritis.

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

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

Strength Training Characteristics of Different Loads Based on Acceleration Sensor and Finite Element Simulation

Deep squat, bench press and hard pull are important ways for people to improve their strength. The use of sensors to measure force is rare. Measuring strength with sensors is extremely valuable for people to master the intensity of exercise to scientifically effective exercise. To this end, in this paper, we used a real-time wireless motion capture and mechanical evaluation system of the wearable sensor to measure the dynamic characteristics of 30 young men performing deep squat, bench press and hard pull maneuvers. The data of tibia were simulated with AnyBody 5.2 and ANSYS 19.2 to verify the authenticity. The result demonstrated that the appropriate force of the deep squat elbow joint, the hip joint and the knee joint is 40% 1RM, the appropriate force of the bench press is 40% 1RM and the appropriate force of the hard pull is 80% 1RM. The external force is the main factor of bone change. The mechanical characteristics of knee joint can be simulated after the Finite Element Analysis and the simulation of AnyBody model are verified.

Bidirectional Day-to-Day Associations of Reported Sleep Duration With Accelerometer Measured Physical Activity and Sedentary Time Among Dutch Adolescents: An Observational Study

OBJECTIVES

To examine the bidirectional association of sleep duration with proportions of time spent in physical behaviors among Dutch adolescents.

METHODS

Adolescents (n = 294, 11-15 years) completed sleep diaries and wore an accelerometer (ActiGraph) over 1 week. With linear mixed-effects models, the authors estimated the association of sleep categories (short, optimal, and long) with the following day's proportion in physical behaviors. With generalized linear mixed models with binomial distribution, the authors estimated the association of physical behavior proportions on sleep categories. Physical behavior proportions were operationalized using percentages of wearing time and by applying a compositional approach. All analyses were stratified by gender accounting for differing developmental stages.

RESULTS

For males (number of observed days: 345, n = 83), short as compared with optimal sleep was associated with the following day's proportion spent in sedentary (-2.57%, p = .03, 95% confidence interval [CI] [-4.95, -0.19]) and light-intensity activities (1.96%, p = .02, 95% CI [0.27, 3.65]), which was not significant in the compositional approach models. Among females (number of observed days: 427, n = 104), long sleep was associated with the proportions spent in moderate- to vigorous-intensity physical activity (1.69%, p < .001, 95% CI [0.75, 2.64]) and in sedentary behavior (-3.02%, p < .01, 95% CI [-5.09, -0.96]), which was replicated by the compositional approach models. None of the associations between daytime activity and sleep were significant (number of obs.: 844, n = 204).

CONCLUSIONS

Results indicate partial associations between sleep and the following day's physical behaviors, and no associations between physical behaviors and the following night's sleep.

Physical activity and cold pain tolerance in the general population

BACKGROUND

The relationship between habitual physical activity (PA) and experimental pain tolerance has been investigated in small samples of young, healthy and/or single-sex volunteers. We used a large, population-based sample to assess this relationship in men and women with and without chronic pain.

METHODS

We used data from the sixth and seventh Tromsø Study surveys (2007-2008; 2015-2016), with assessed pain tolerance of participants with the cold pressor test (CPT: dominant hand in circulating cold water at 3°C, maximum test time 106 s), and self-reported total amount of habitual PA in leisure time (n = 19,087), exercise frequency (n = 19,388), exercise intensity (n = 18,393) and exercise duration (n = 18,343). A sub-sample had PA measured by accelerometers (n = 4,922). We used Cox regression to compare CPT tolerance times between self-reported PA levels. For accelerometer-measured PA, we estimated hazard ratios for average daily activity counts, and for average daily minutes of moderate-to-vigorous PA done in bouts lasting 10 min or more. Models were tested for PA-sex, and PA-chronic pain and PA-moderate-to-severe chronic pain interactions.

RESULTS

Leisure-time PA, exercise intensity and exercise duration were positively associated with CPT tolerance (p < .001; p = .011; p < .001). More PA was associated with higher CPT tolerance. At high levels of leisure-time PA and exercise intensity, men had a significantly higher CPT tolerance than women. Accelerometer-measured PA was not associated with CPT tolerance.

CONCLUSIONS

This study is one of the first to show that higher self-reported habitual PA was connected to higher experimental pain tolerance in a population-based sample, especially for men. This was not found for accelerometer-measured PA.

SIGNIFICANCE

This study finds that higher level of self-reported leisure-time physical activity is associated with increased cold pressor pain tolerance in a large population-based sample. Though present in both sexes, the association is strongest among men. Despite the robust dose-response relationship between pain tolerance and self-reported activity level, no such relationship was found for accelerometer-measured activity, reflecting a possible discrepancy in the aspect of physical activity measured. Though the study design does not permit causal conclusions, the findings suggest that increasing physical activity may increase pain tolerance in the general population.

Motivational climate, need satisfaction, self-determined motivation, and physical activity of students in secondary school physical education in China

Background

On the basis of the integration constructs from self-determination theory (SDT) and achievement goal theory (AGT), this study aims to investigate the relationship among classroom motivational climate from four perspectives (i.e. autonomy support, relatedness support, task-involving climate and ego-involving climate), three psychological needs (i.e. autonomy, competence and relatedness), self-determined motivation and physical activity (PA) in secondary physical education (PE).

Methods

Participants consisted of 1186 Chinese students aged 11 to 16 years from three secondary schools in Shanghai. Accelerometers were utilized to measure moderate to vigorous physical activity (MVPA). Questionnaires were used to measure SDT variables (i.e. classroom motivational climate, perceived competence, autonomy, relatedness and self-determined motivation). Structural equation modelling (SEM) was adopted to analyse the hypothesised relationship.

Results

SEM analysis revealed that task-involving climate and autonomy support were positively associated with autonomy, relatedness and competence. Relatedness support was positively related with autonomy and relatedness, whereas ego-involving climate was only associated with competence. The three psychological needs positively affected self-determined motivation, and self-determined motivation positively affected the MVPA time of secondary school students in PE lessons.

Conclusion

These findings support a model of motivation that integrates SDT and AGT, provides new insight into understanding MVPA in Chinese PE, and establishes a solid basis for intervention research.

Daily- and Person-Level Associations Between Physical Activity and Alcohol Use Among College Students

Emerging adults, particularly university students, who are physically active, drink more than their less physically active peers. We extended this between-person relationship to the within-person level of analysis, by examining whether students are more likely to drink on days when they exercise, and whether this within-person association remains after controlling for potential confounding factors. We also explored the temporal sequence of the physical activity (PA)-alcohol use association. University students (N = 426) completed a 30-day online diary. The small positive within-person association between PA and alcohol use was not retained after controlling for day of the week. However, previous day's drinking was inversely associated with next day's PA on weekdays. These findings suggest that the previously reported positive PA-alcohol association does not necessarily align with the within-person daily association. Future studies with more nuanced measurement strategies, such as ecological momentary assessment, are needed to better understand the association between PA and alcohol use.

Assessing physical activity and function in patients with chronic kidney disease: a narrative review

Physical activity potentially improves health outcomes in patients with chronic kidney disease (CKD) and recipients of kidney transplants. Although studies have demonstrated the beneficial effects of physical activity and exercise for primary and secondary prevention of non-communicable diseases, evidence for kidney patients is limited. To enlarge this evidence, valid assessment of physical activity and exercise is essential. Furthermore, CKD is associated with a decline in physical function, which may result in severe disabilities and dependencies. Assessment of physical function may help clinicians to monitor disease progression and frailty in patients receiving dialysis. The attention on physical function and physical activity has grown and new devices have been developed and (commercially) launched on the market. Therefore the aims of this review were to summarize different measures of physical function and physical activity, provide an update on measurement instruments and discuss options for easy-to-use measurement instruments for day-to-day use by CKD patients. This review demonstrates that large variation exists in the different strategies to assess physical function and activity in clinical practice and research settings. To choose the best available method, accuracy, content, preferable outcome, necessary expertise, resources and time are important issues to consider.

How to Improve the Functional Capacity of Frail and Pre-Frail Elderly People? Health, Nutritional Status and Exercise Intervention. The EXERNET-Elder 3.0 Project

Aging is associated with the impairment of health and functional capacity, and physical exercise seems to be an effective tool in frailty prevention and treatment. The purpose of this study was to present the methodology used in the EXERNET-Elder 3.0 project that aims to evaluate the immediate and residual effects and of a multicomponent exercise training program called Elder-fit on frailty, fitness, body composition and quality of life, and also to analyse a possible dietary intake interaction according to health and metabolic status. A total of 110 frail and pre-frail elders participated in this study and were divided into a control group (CG = 52) and an intervention group (IG = 58). The IG performed a supervised multicomponent exercise training program of 6 months and 3 days per week, which included strength, endurance, balance, coordination and flexibility exercises, while the CG continued with their usual daily activities. Both groups received four speeches about healthy habits along the project. Four evaluations were performed: at baseline, after 3 months of training, at the end of the training program (6 months) and 4 months after the program had ended to examine the effects of detraining. Evaluating the efficacy, safety and feasibility of this program will help to develop efficacious physical interventions against frailty. Further, protocols should be described accurately to allow exercise programs to be successfully replicated.

A novel scaling methodology to reduce the biases associated with missing data from commercial activity monitors

Background

Commercial physical activity monitors have wide utility in the assessment of physical activity in research and clinical settings, however, the removal of devices results in missing data and has the potential to bias study conclusions. This study aimed to evaluate methods to address missingness in data collected from commercial activity monitors.

Methods

This study utilised 1526 days of near complete data from 109 adults participating in a European weight loss maintenance study (NoHoW). We conducted simulation experiments to test a novel scaling methodology (NoHoW method) and alternative imputation strategies (overall/individual mean imputation, overall/individual multiple imputation, Kalman imputation and random forest imputation). Methods were compared for hourly, daily and 14-day physical activity estimates for steps, total daily energy expenditure (TDEE) and time in physical activity categories. In a second simulation study, individual multiple imputation, Kalman imputation and the NoHoW method were tested at different positions and quantities of missingness. Equivalence testing and root mean squared error (RMSE) were used to evaluate the ability of each of the strategies relative to the true data.

Results

The NoHoW method, Kalman imputation and multiple imputation methods remained statistically equivalent (p<0.05) for all physical activity metrics at the 14-day level. In the second simulation study, RMSE tended to increase with increased missingness. Multiple imputation showed the smallest RMSE for Steps and TDEE at lower levels of missingness (<19%) and the Kalman and NoHoW methods were generally superior for imputing time in physical activity categories.

Conclusion

Individual centred imputation approaches (NoHoW method, Kalman imputation and individual Multiple imputation) offer an effective means to reduce the biases associated with missing data from activity monitors and maximise data retention.

Validity and reliability of subjective methods to assess sedentary behaviour in adults: a systematic review and meta-analysis

BACKGROUND

Subjective measures of sedentary behaviour (SB) (i.e. questionnaires and diaries/logs) are widely implemented, and can be useful for capturing type and context of SBs. However, little is known about comparative validity and reliability. The aim of this systematic review and meta-analysis was to: 1) identify subjective methods to assess overall, domain- and behaviour-specific SB, and 2) examine the validity and reliability of these methods.

METHODS

The databases MEDLINE, EMBASE and SPORTDiscus were searched up to March 2020. Inclusion criteria were: 1) assessment of SB, 2) evaluation of subjective measurement tools, 3) being performed in healthy adults, 4) manuscript written in English, and 5) paper was peer-reviewed. Data of validity and/or reliability measurements was extracted from included studies and a meta-analysis using random effects was performed to assess the pooled correlation coefficients of the validity.

RESULTS

The systematic search resulted in 2423 hits. After excluding duplicates and screening on title and abstract, 82 studies were included with 75 self-reported measurement tools. There was wide variability in the measurement properties and quality of the studies. The criterion validity varied between poor-to-excellent (correlation coefficient [R] range - 0.01- 0.90) with logs/diaries (R = 0.63 [95%CI 0.48-0.78]) showing higher criterion validity compared to questionnaires (R = 0.35 [95%CI 0.32-0.39]). Furthermore, correlation coefficients of single- and multiple-item questionnaires were comparable (1-item R = 0.34; 2-to-9-items R = 0.35; ≥10-items R = 0.37). The reliability of SB measures was moderate-to-good, with the quality of these studies being mostly fair-to-good.

CONCLUSION

Logs and diaries are recommended to validly and reliably assess self-reported SB. However, due to time and resources constraints, 1-item questionnaires may be preferred to subjectively assess SB in large-scale observations when showing similar validity and reliability compared to longer questionnaires.

REGISTRATION NUMBER

CRD42018105994.

Birth weight, cardiometabolic risk factors and effect modification of physical activity in children and adolescents: pooled data from 12 international studies

Objectives

Low and high birth weight is associated with higher levels of cardiometabolic risk factors and adiposity in children and adolescents, and increases the risk of cardiovascular diseases, obesity, and early mortality later in life. Moderate-to-vigorous physical activity (MVPA) is associated with lower cardiometabolic risk factors and may mitigate the detrimental consequences of high or low birth weight. Thus, we examined whether MVPA modified the associations between birth weight and cardiometabolic risk factors in children and adolescents.

Methods

We used pooled individual data from 12 cohort- or cross-sectional studies including 9,100 children and adolescents. Birth weight was measured at birth or maternally reported retrospectively. Device-measured physical activity (PA) and cardiometabolic risk factors were measured in childhood or adolescence. We tested for associations between birth weight, MVPA, and cardiometabolic risk factors using multilevel linear regression, including study as a random factor. We tested for interaction between birth weight and MVPA by introducing the interaction term in the models (birth weight x MVPA).

Results

Most of the associations between birth weight (kg) and cardiometabolic risk factors were not modified by MVPA (min/day), except between birth weight and waist circumference (cm) in children (p = 0.005) and HDL-cholesterol (mmol/l) in adolescents (p = 0.040). Sensitivity analyses suggested that some of the associations were modified by VPA, i.e., the associations between birth weight and diastolic blood pressure (mmHg) in children (p = 0.009) and LDL- cholesterol (mmol/l) (p = 0.009) and triglycerides (mmol/l) in adolescents (p = 0.028).

Conclusion

MVPA appears not to consistently modify the associations between low birth weight and cardiometabolic risk. In contrast, MVPA may mitigate the association between higher birth weight and higher waist circumference in children. MVPA is consistently associated with a lower cardiometabolic risk across the birth weight spectrum. Optimal prenatal growth and subsequent PA are both important in relation to cardiometabolic health in children and adolescents.

Review of Validity and Reliability of Garmin Activity Trackers

Purpose

A systematic review to summarize the validity and reliability of steps, distance, energy expenditure, speed, elevation, heart rate, and sleep assessed by Garmin activity trackers.

Methods

Searches included studies published through December 31, 2018. Correlation coefficients (CC) were assessed as low (<0.60), moderate (0.60-<0.75), good (0.75-<0.90), or excellent (>=0.90). Mean absolute percentage errors (MAPE) were assessed as acceptable at <5% in controlled conditions and <10% for free-living.

Results

Overall, 32 studies of adults documented validity. Four of these studies also documented reliability. The sample size ranged from 1 to 95 for validity and 4 to 31 for reliability testing. Step inter- and intra-reliability was good-to-excellent and speed intra-reliability was excellent. No other features were explored for reliability. Step validity, across 16 studies, generally indicated good-to-excellent CC and acceptable MAPE. Distance validity, tested in three studies, generally indicated poor CC and MAPE that exceeded acceptable limits, with both over and underestimation. Energy expenditure validity, across 12 studies, generally indicated wide variability in CC and MAPE that exceeded acceptable limits. Heart rate validity in five studies had low-to-excellent CC and all MAPE exceeded acceptable limits. Speed, elevation, and sleep validity were assessed in only one or two studies each; for sleep, the criterion relied on self-report rather than polysomnography.

Conclusion

This systematic review of Garmin activity trackers among adults indicated higher validity of steps; few studies on speed, elevation, and sleep; and lower validity for distance, energy expenditure, and heart rate. Intra- and inter-device feature reliability needs further testing.

A Lean and Performant Hierarchical Model for Human Activity Recognition Using Body-Mounted Sensors

Here we propose a new machine learning algorithm for classification of human activities by means of accelerometer and gyroscope signals. Based on a novel hierarchical system of logistic regression classifiers and a relatively small set of features extracted from the filtered signals, the proposed algorithm outperformed previous work on the DaLiAc (Daily Life Activity) and mHealth datasets. The algorithm also represents a significant improvement in terms of computational costs and requires no feature selection and hyper-parameter tuning. The algorithm still showed a robust performance with only two (ankle and wrist) out of the four devices (chest, wrist, hip and ankle) placed on the body (96.8% vs. 97.3% mean accuracy for the DaLiAc dataset). The present work shows that low-complexity models can compete with heavy, inefficient models in classification of advanced activities when designed with a careful upstream inspection of the data.