Evolution of accelerometer methods for physical activity research

Monitoring postures and motions of hospitalized patients using sensor technology: a scoping review

BACKGROUND

Sensor technology could provide solutions to monitor postures and motions and to help hospital patients reach their rehabilitation goals with minimal supervision. Synthesized information on device applications and methodology is lacking.

OBJECTIVES

The purpose of this scoping review was to provide an overview of device applications and methodological approaches to monitor postures and motions in hospitalized patients using sensor technology.

METHODS

A systematic search of Embase, Medline, Web of Science and Google Scholar was completed in February 2023 and updated in March 2024. Included studies described populations of hospitalized adults with short admission periods and interventions that use sensor technology to objectively monitor postures and motions. Study selection was performed by two authors independently of each other. Data extraction and narrative analysis focused on the applications and methodological approaches of included articles using a personalized standard form to extract information on device, measurement and analysis characteristics of included studies and analyse frequencies and usage.

RESULTS

A total of 15.032 articles were found and 49 articles met the inclusion criteria. Devices were most often applied in older adults (n = 14), patients awaiting or after surgery (n = 14), and stroke (n = 6). The main goals were gaining insight into patient physical behavioural patterns (n = 19) and investigating physical behaviour in relation to other parameters such as muscle strength or hospital length of stay (n = 18). The studies had heterogeneous study designs and lacked completeness in reporting on device settings, data analysis, and algorithms. Information on device settings, data analysis, and algorithms was poorly reported.

CONCLUSIONS

Studies on monitoring postures and motions are heterogeneous in their population, applications and methodological approaches. More uniformity and transparency in methodology and study reporting would improve reproducibility, interpretation and generalization of results. Clear guidelines for reporting and the collection and sharing of raw data would benefit the field by enabling study comparison and reproduction.

Multilevel Longitudinal Functional Principal Component Model

Sensor devices, such as accelerometers, are widely used for measuring physical activity (PA). These devices provide outputs at fine granularity (e.g., 10-100 Hz or minute-level), which while providing rich data on activity patterns, also pose computational challenges with multilevel densely sampled data, resulting in PA records that are measured continuously across multiple days and visits. On the other hand, a scalar health outcome (e.g., BMI) is usually observed only at the individual or visit level. This leads to a discrepancy in numbers of nested levels between the predictors (PA) and outcomes, raising analytic challenges. To address this issue, we proposed a multilevel longitudinal functional principal component analysis (mLFPCA) model to directly model multilevel functional PA inputs in a longitudinal study, and then implemented a longitudinal functional principal component regression (FPCR) to explore the association between PA and obesity-related health outcomes. Additionally, we conducted a comprehensive simulation study to examine the impact of imbalanced multilevel data on both mLFPCA and FPCR performance and offer guidelines for selecting optimal methods.

Predicting physical functioning status in older adults: insights from wrist accelerometer sensors and derived digital biomarkers of physical activity

OBJECTIVE

Conventional physical activity (PA) metrics derived from wearable sensors may not capture the cumulative, transitions from sedentary to active, and multidimensional patterns of PA, limiting the ability to predict physical function impairment (PFI) in older adults. This study aims to identify unique temporal patterns and develop novel digital biomarkers from wrist accelerometer data for predicting PFI and its subtypes using explainable artificial intelligence techniques.

MATERIALS AND METHODS

Wrist accelerometer streaming data from 747 participants in the National Health and Aging Trends Study (NHATS) were used to calculate 231 PA features through time-series analysis techniques-Tsfresh. Predictive models for PFI and its subtypes (walking, balance, and extremity strength) were developed using 6 machine learning (ML) algorithms with hyperparameter optimization. The SHapley Additive exPlanations method was employed to interpret the ML models and rank the importance of input features.

RESULTS

Temporal analysis revealed peak PA differences between PFI and healthy controls from 9:00 to 11:00 am. The best-performing model (Gradient boosting Tree) achieved an area under the curve score of 85.93%, accuracy of 81.52%, sensitivity of 77.03%, and specificity of 87.50% when combining wrist accelerometer streaming data (WAPAS) features with demographic data.

DISCUSSION

The novel digital biomarkers, including change quantiles, Fourier transform (FFT) coefficients, and Aggregated (AGG) Linear Trend, outperformed traditional PA metrics in predicting PFI. These findings highlight the importance of capturing the multidimensional nature of PA patterns for PFI.

CONCLUSION

This study investigates the potential of wrist accelerometer digital biomarkers in predicting PFI and its subtypes in older adults. Integrated PFI monitoring systems with digital biomarkers would improve the current state of remote PFI surveillance.

Cardiorespiratory Fitness and Sleep, but not Physical Activity, are Associated with Functional Connectivity in Older Adults

BACKGROUND

Aging results in changes in resting state functional connectivity within key networks associated with cognition. Cardiovascular function, physical activity, sleep, and body composition may influence these age-related changes in the brain. Better understanding these associations may help clarify mechanisms related to brain aging and guide interventional strategies to reduce these changes.

METHODS

In a large (n = 398) sample of healthy community dwelling older adults that were part of a larger interventional trial, we conducted cross sectional analyses of baseline data to examine the relationships between several modifiable behaviors and resting state functional connectivity within networks associated with cognition and emotional regulation. Additionally, maximal aerobic capacity, physical activity, quality of sleep, and body composition were assessed. Associations were explored both through correlation and best vs. worst group comparisons.

RESULTS

Greater cardiovascular fitness, but not larger quantity of daily physical activity, was associated with greater functional connectivity within the Default Mode (p = 0.008 r = 0.142) and Salience Networks (p = 0.005, r = 0.152). Better sleep (greater efficiency and fewer nighttime awakenings) was also associated with greater functional connectivity within multiple networks including the Default Mode, Executive Control, and Salience Networks. When the population was split into quartiles, the highest body fat group displayed higher functional connectivity in the Dorsal Attentional Network compared to the lowest body fat percentage (p = 0.011; 95% CI - 0.0172 to - 0.0023).

CONCLUSION

These findings confirm and expand on previous work indicating that, in older adults, higher levels of cardiovascular fitness and better sleep quality, but not greater quantity of physical activity, total sleep time, or lower body fat percentage are associated with increased functional connectivity within key resting state networks.

Reliable measures of rest-activity rhythm fragmentation: how many days are needed?

BACKGROUND

A more fragmented, less stable rest-activity rhythm (RAR) is emerging as a risk factor for health. Accelerometer devices are increasingly used to measure RAR fragmentation using metrics such as inter-daily stability (IS), intradaily variability (IV), transition probabilities (TP), self-similarity parameter (α), and activity balance index (ABI). These metrics were proposed in the context of long period of wear but, in real life, non-wear might introduce measurement bias. This study aims to determine the minimum number of valid days to obtain reliable fragmentation metrics.

METHODS

Wrist-worn accelerometer data were drawn from the Whitehall accelerometer sub-study (age: 60 to 83 years) to simulate different non-wear patterns. Pseudo-simulated data with different numbers of valid days (one to seven), defined as < 1/3 of non-wear during both day and night periods, and with omission or imputation of non-wear periods were compared against complete data using intraclass correlation coefficient (ICC) and mean absolute percent error (MAPE).

RESULTS

Five days with valid data (97.8% of participants) and omission of non-wear periods allowed an ICC ≥ 0.75 and MAPE ≤ 15%, acceptable cut points for reliability, for IS and ABI; this number was lower for TPs (two-three days), α and IV (four days). Overall, imputation of data did not provide better estimates. Findings were consistent across age and sex groups.

CONCLUSIONS

The number of days of wrist accelerometer data with at least 2/3 of wear time for both day and night periods varies from two (TPs) to five (IS, ABI) days for reliable RAR measures among older adults.

Association between lower extremity physical function and physical activity after ischemic stroke: Longitudinal findings from the MOBITEC-Stroke project

Background

Stroke often results in physical impairments. Physical activity is crucial for rehabilitation, enhancing mobility, strength, and overall health. This study examines the association between Timed Up-and-Go (TUG) test performance and changes in physical activity to improve lower extremity physical function.

Methods

The MOBITEC-Stroke Cohort Study ("Recovery of mobility function and life-space mobility after ischemic stroke") included patients with a first incidence of stroke. Data assessed 3 and 12 months after stroke were used for analysis. Linear regression model adjusted for age, sex, instrumental activities of daily living, Falls Efficacy Scale-International, modified Ranking Scale, and National Institutes of Health Stroke Scale-score was used to examine the relationship between lower extremity physical function (i.e., TUG) and change in physical activity (i.e., minutes of physical activity measured with a wrist-worn accelerometer over 1 week).

Results

Longitudinal data of 49 patients (65% male, mean age 71.2 (SD: 10.4) years) were analyzed. Mean daily physical activity was 291.6 (SD: 96.2) min at 3 months and 298.9 (SD: 94.4) min at 12 months, with a change from 3 to 12 months of 7.3 min (95% CI: -9.4 to 24.0; p = 0.394) post-stroke. We observed significant relationships between the baseline TUG performance and the change in total physical activity over 9 months (p = 0.011) and between the change of TUG performance over time and the change in total physical activity (p = 0.022).

Conclusion

Our findings indicate that better initial lower extremity physical function and higher improvements in function over time are associated with a greater increase in physical activity levels after stroke. This suggests that interventions aimed at maintaining and improving lower extremity physical function may positively affect physical activity levels.

Exploring the Association between Daily Distributional Patterns of Physical Activity and Cardiovascular Mortality Risk among Older Adults in NHANES 2003-2006

PURPOSE

Cardiovascular disease (CVD) is one of the leading causes of death worldwide. Physical activity (PA) has previously been shown to be a prominent risk factor for CVD mortality. Traditionally, measurements of PA have been self-reported and based on various summary metrics. However, recent advances in wearable technology provide continuously monitored and objectively measured physical activity data. This facilitates a more comprehensive interpretation of the implications of PA in the context of CVD mortality by considering its daily patterns and compositions.

METHODS

This study utilized accelerometer data from the 2003-2006 National Health and Nutrition Examination Survey (NHANES) on 2,816 older adults aged 50-85 and mortality data from the National Death Index (NDI) in December 2019. A novel partially functional distributional analysis method was used to quantify and understand the association between daily distributional patterns of physical activity and cardiovascular mortality risk through a multivariable functional Cox model.

RESULTS

A higher mean intensity of daily PA during the day was associated with a reduced hazard of CVD mortality after adjusting for other higher order distributional summaries of PA and age, gender, race, body mass index (BMI), smoking and coronary heart disease (CHD). A higher daily variability of PA during afternoon was associated with a reduced hazard of CVD mortality, after adjusting for the other predictors, particularly on weekdays. The subjects with a lower variability of PA, despite having same mean PA throughout the day, could have a lower reserve of PA and hence could be at increased risk for CVD mortality.

CONCLUSIONS

Our results demonstrate that not only the mean intensity of daily PA during daytime, but also the variability of PA during afternoon could be an important protective factor against the risk of CVD-mortality. Considering circadian rhythm of PA as well as its daily compositions can be useful for designing time-of-day and intensity-specific PA interventions to protect against the risk of CVD mortality.

Painful distortions: people with painful knee osteoarthritis have biased visuospatial perception of the environment

ABSTRACT

Visuospatial perception is thought to be adaptive-ie, hills are perceived as steeper when capacity is low, or threat is high-guiding appropriate interaction with the environment. Pain (bodily threat) may similarly modulate visuospatial perception, with the extent of modulation influenced by threat magnitude (pain intensity, fear) and associated with behaviour (physical activity). We compared visuospatial perception of the environment between 50 people with painful knee osteoarthritis and 50 age-/sex-matched pain-free control participants using 3 virtual reality tasks (uphill steepness estimation, downhill steepness estimation, and a distance-on-hill measure), exploring associations between visuospatial perception, clinical characteristics (pain intensity, state and trait fear), and behaviour (wrist-worn accelerometry) within a larger knee osteoarthritis group (n = 85). People with knee osteoarthritis overestimated uphill (F 1,485 = 19.4, P < 0.001) and downhill (F 1,480 = 32.3, P < 0.001) steepness more so than pain-free controls, but the groups did not differ for distance-on-hill measures (U = 1273, P = 0.61). There was also a significant group x steepness interaction for the downhill steepness task (F 4,480 = 3.11, P = 0.02). Heightened overestimation in people with knee osteoarthritis relative to pain-free controls increased as downhill slopes became steeper. Results were unchanged in a replication analysis using all knee osteoarthritis participants (n = 85), except the downhill steepness interaction was no longer significant. In people with knee osteoarthritis, higher state fear was associated with greater over-estimation of downhill slope steepness (rho = 0.69, P < 0.001), and greater visuospatial overestimation (distance-on-hill) was associated with lower physical activity levels (rho = -0.22, P = 0.045). These findings suggest that chronic pain may shift perception of the environment in line with protection, with overestimation heightened when threat is greater (steeper hills, more fearful), although impact on real-world behaviour is uncertain.

Raw Photoplethysmography as an Enhancement for Research-Grade Wearable Activity Monitors

Wearable monitors continue to play a critical role in scientific assessments of physical activity. Recently, research-grade monitors have begun providing raw data from photoplethysmography (PPG) alongside standard raw data from inertial sensors (accelerometers and gyroscopes). Raw PPG enables granular and transparent estimation of cardiovascular parameters such as heart rate, thus presenting a valuable alternative to standard PPG methodologies (most of which rely on consumer-grade monitors that provide only coarse output from proprietary algorithms). The implications for physical activity assessment are tremendous, since it is now feasible to monitor granular and concurrent trends in both movement and cardiovascular physiology using a single noninvasive device. However, new users must also be aware of challenges and limitations that accompany the use of raw PPG data. This viewpoint paper therefore orients new users to the opportunities and challenges of raw PPG data by presenting its mechanics, pitfalls, and availability, as well as its parallels and synergies with inertial sensors. This includes discussion of specific applications to the prediction of energy expenditure, activity type, and 24-hour movement behaviors, with an emphasis on areas in which raw PPG data may help resolve known issues with inertial sensing (eg, measurement during cycling activities). We also discuss how the impact of raw PPG data can be maximized through the use of open-source tools when developing and disseminating new methods, similar to current standards for raw accelerometer and gyroscope data. Collectively, our comments show the strong potential of raw PPG data to enhance the use of research-grade wearable activity monitors in science over the coming years.

Data Analytics in Physical Activity Studies With Accelerometers: Scoping Review

BACKGROUND

Monitoring free-living physical activity (PA) through wearable devices enables the real-time assessment of activity features associated with health outcomes and provision of treatment recommendations and adjustments. The conclusions of studies on PA and health depend crucially on reliable statistical analyses of digital data. Data analytics, however, are challenging due to the various metrics adopted for measuring PA, different aims of studies, and complex temporal variations within variables. The application, interpretation, and appropriateness of these analytical tools have yet to be summarized.

OBJECTIVE

This research aimed to review studies that used analytical methods for analyzing PA monitored by accelerometers. Specifically, this review addressed three questions: (1) What metrics are used to describe an individual's free-living daily PA? (2) What are the current analytical tools for analyzing PA data, particularly under the aims of classification, association with health outcomes, and prediction of health events? and (3) What challenges exist in the analyses, and what recommendations for future research are suggested regarding the use of statistical methods in various research tasks?

METHODS

This scoping review was conducted following an existing framework to map research studies by exploring the information about PA. Three databases, PubMed, IEEE Xplore, and the ACM Digital Library, were searched in February 2024 to identify related publications. Eligible articles were classification, association, or prediction studies involving human PA monitored through wearable accelerometers.

RESULTS

After screening 1312 articles, 428 (32.62%) eligible studies were identified and categorized into at least 1 of the following 3 thematic categories: classification (75/428, 17.5%), association (342/428, 79.9%), and prediction (32/428, 7.5%). Most articles (414/428, 96.7%) derived PA variables from 3D acceleration, rather than 1D acceleration. All eligible articles (428/428, 100%) considered PA metrics represented in the time domain, while a small fraction (16/428, 3.7%) also considered PA metrics in the frequency domain. The number of studies evaluating the influence of PA on health conditions has increased greatly. Among the studies in our review, regression-type models were the most prevalent (373/428, 87.1%). The machine learning approach for classification research is also gaining popularity (32/75, 43%). In addition to summary statistics of PA, several recent studies used tools to incorporate PA trajectories and account for temporal patterns, including longitudinal data analysis with repeated PA measurements and functional data analysis with PA as a continuum for time-varying association (68/428, 15.9%).

CONCLUSIONS

Summary metrics can quickly provide descriptions of the strength, frequency, and duration of individuals' overall PA. When the distribution and profile of PA need to be evaluated or detected, considering PA metrics as longitudinal or functional data can provide detailed information and improve the understanding of the role PA plays in health. Depending on the research goal, appropriate analytical tools can ensure the reliability of the scientific findings.

Beyond validation: getting wearable activity trackers into cardiovascular care-a discussion paper

This paper addresses the challenge of integrating wearable activity trackers (WATs) into cardiovascular disease care. Despite evidence supporting the use of trackers for monitoring and promoting physical activity, implementation challenges persist in clinical settings. The paper emphasizes the lack of systematic, evidence-based implementation approaches for integrating trackers. It underscores the urgent need for stakeholder collaboration between clinicians, patients, implementation scientists, researchers, health and technology partners, and the use of proven implementation science methodologies. This is crucial for bridging the gap and ensuring effective translation of WATs into cardiovascular care, meeting the increasing demand from patients and clinicians.

Accelerometer-Based Physical Activity and Health-Related Quality of Life in Korean Adults: Observational Study Using the Korea National Health and Nutrition Examination Survey

BACKGROUND

Health-related quality of life (HRQoL) reflects an individual's perception of their physical and mental health over time. Despite numerous studies linking physical activity to improved HRQoL, most rely on self-reported data, limiting the accuracy and generalizability of findings. This study leverages objective accelerometer data to explore the association between physical activity and HRQoL in Korean adults.

OBJECTIVE

The objective of this study is to analyze the relationship between objectively measured physical activity using accelerometers and HRQoL among Korean adults, aiming to inform targeted interventions for enhancing HRQoL through physical activity.

METHODS

This observational study included 1298 participants aged 19-64 years from the Korea National Health and Nutrition Examination Survey (KNHANES) VI, who wore an accelerometer for 7 consecutive days. HRQoL was assessed using the EQ-5D questionnaire, and physical activity was quantified as moderate-to-vigorous physical activity accelerometer-total (MVPA-AT) and accelerometer-bout (MVPA-AB). Data were analyzed using logistic regression to determine the odds ratio (ORs) for low HRQoL, adjusting for socioeconomic variables and mental health factors.

RESULTS

Participants with higher HRQoL were younger, more likely to be male, single, highly educated, employed in white-collar jobs, and had higher household incomes. They also reported less stress and better subjective health status. The high HRQoL group had significantly more participants meeting MVPA-AB ≥600 metabolic equivalents (P<.01). Logistic regression showed that participants meeting MVPA-AB ≥600 metabolic equivalents had higher odds of high HRQoL (OR 1.55, 95% CI 1.11-2.17). Adjusted models showed consistent results, although the association weakened when adjusting for mental health factors (OR 1.45, 95% CI 1.01-2.09).

CONCLUSIONS

The study demonstrates a significant association between HRQoL and moderate to vigorous physical activity sustained for at least 10 minutes, as measured by accelerometer. These findings support promoting physical activity, particularly sustained moderate to vigorous activity, to enhance HRQoL. Further interventional studies focusing on specific physical activity domains such as occupational, leisure-time, and commuting activities are warranted.

Evaluation of indoor activities for moderate-to-vigorous physical activity in preschoolers

The study objectives were 1) to determine the feasibility and acceptability of indoor activities to achieve moderate-to-vigorous physical activity (MVPA) in preschoolers, and 2) compare MVPA estimates between direct observation (DO) and various accelerometry placements. In this cross-sectional study, 35 preschoolers (51% female, 54% 3-year-olds) performed six, 6-minute activities (dancing to video, balloon/bubbles, stationary exergame cycling, circuits, running-in-place, and cleaning up) in sequential order, facilitated by a trained staff member. Triaxial accelerometers (Actigraph Gt3×BT) at the ankle, waist, and wrist measured MVPA using age-specific cut-points. Total activity and MVPA time were quantified via DO of video recordings. Feasibility and acceptability were assessed via parent and child report. Preschoolers contributed 4339, 15-second epochs of accelerometry and DO data (~31.0 minutes/preschooler). Preschoolers achieved MVPA ≥ 50% of the time while engaging in balloon/bubbles, cycling, and circuits; but not while dancing to video (15%), running-in-place (48.5%), or cleaning up (8%). There were no differences in MVPA by age, sex, or between screen and non-screen activities. Parents and preschoolers reported most activities were feasible (≥4.0/5.0). Waist and ankle accelerometry had strong agreement with DO (ICCs range: 0.70-0.84) while wrist had fair to low agreement (ICCs: 0.22-0.58). Multiple indoor activities show promise to increase preschoolers' MVPA.

Changes in physical activity and sleep following the COVID-19 pandemic on a university campus: Perception versus reality

It has been hypothesized that key lifestyle behaviors of physical activity and sleep worsened in response to the Coronavirus disease (COVID-19) pandemic. However, there have been inconsistencies in findings of changes in these key lifestyle behaviors across populations likely due to the wide variety of assessment methods. The purpose of the study was to compare physical activity and sleep before and after the COVID-19 pandemic using accelerometers and self-reported behaviors. A longitudinal follow-up was conducted on students, faculty, and staff at a university campus in the United States. In the periods before March 2020 (covering the academic years of 2018-2019 or 2019-2020) and again in April-June 2021, participants completed surveys to evaluate their physical activity and sleep behaviors and wore an accelerometer. A total of 44 participants completed the survey at both timepoints and 32 completed accelerometer assessment at both timepoints. Fifty-seven percent of participants reported a perceived decline in physical activity, while 30% reported a worsening in sleep. From self-reported data, overall physical activity did not change, but there was a decrease in active transport (p ​< ​0.001) and increase in domestic physical activity (p ​= ​0.012). Sleep quality decreased as evidenced by an increase in Pittsburgh Sleep Quality Index scores (p ​= ​0.045). There were no changes in accelerometer measured physical activity or sleep. There were no changes in physical or mental health. While perceptions of physical activity declined from prior to the COVID-19 pandemic, there were no changes in device-measured physical activity, and changes in self-reported physical activity differed by domain.

Associations of accelerometry-measured and self-reported physical activity and sedentary behavior with skeletal muscle energetics: The Study of Muscle, Mobility and Aging (SOMMA)

BACKGROUND

Skeletal muscle energetics decline with age, and physical activity (PA) has been shown to offset these declines in older adults. Yet, many studies reporting these effects were based on self-reported PA or structured exercise interventions. Therefore, we examined the associations of accelerometry-measured and self-reported PA and sedentary behavior (SB) with skeletal muscle energetics and explored the extent to which PA and sedentary behavior would attenuate the associations of age with muscle energetics.

METHODS

As part of the Study of Muscle, Mobility and Aging, enrolled older adults (n = 879), 810 (age = 76.4 ± 5.0 years old, mean ± SD; 58% women) had maximal muscle oxidative capacity measured ex vivo via high-resolution respirometry of permeabilized myofibers (maximal oxidative phosphorylation (maxOXPHOS)) and in vivo by 31phosphorus magnetic resonance spectroscopy (maximal adenosine triphosphate (ATPmax)). Accelerometry-measured sedentary behavior, light activity, and moderate-to-vigorous PA (MVPA) were assessed using a wrist-worn ActiGraph GT9X over 7 days. Self-reported sedentary behavior, MVPA, and all PA were assessed with the Community Healthy Activities Model Program for Seniors (CHAMPS) questionnaire. Linear regression models with progressive covariate adjustments evaluated the associations of sedentary behavior and PA with muscle energetics, as well as the attenuation of the age/muscle energetics association by MVPA and sedentary behavior. As a sensitivity analysis, we also examined activPAL-measured daily step count and time spent in sedentary behavior and their associations with muscle energetics.

RESULTS

Every 30 min/day more of ActiGraph-measured MVPA was associated with 0.65 pmol/(s × mg) higher maxOXPHOS and 0.012 mM/s higher ATPmax after adjusting for age, site/technician, and sex (p < 0.05). Light activity was not associated with maxOXPHOS or ATPmax. Meanwhile, every 30 min/day spent in ActiGraph-measured sedentary behavior was associated with 0.39 pmol/s × mg lower maxOXPHOS and 0.006 mM/s lower ATPmax (p < 0.05). Only associations with ATPmax held after further adjusting for socioeconomic status, body mass index, lifestyle factors, and multimorbidity. CHAMPS MVPA and all PA yielded similar associations with maxOXPHOS and ATPmax (p < 0.05), but sedentary behavior did not. Higher activPAL step count was associated with higher maxOXHPOS and ATPmax (p < 0.05), but time spent in sedentary behavior was not. Additionally, age was significantly associated with muscle energetics for men only (p < 0.05); adjusting for time spent in ActiGraph-measured MVPA attenuated the age association with ATPmax by 58% in men.

CONCLUSION

More time spent in accelerometry-measured or self-reported daily PA, especially MVPA, was associated with higher skeletal muscle energetics. Interventions aimed specifically at increasing higher intensity activity might offer potential therapeutic interventions to slow age-related decline in muscle energetics. Our work also emphasizes the importance of taking PA into consideration when evaluating associations related to skeletal muscle energetics.

Physical activity, sedentary behavior, and risk of sepsis: a two-sample mendelian randomization study

Objective

This investigation aimed to explore the potential causal relationship between physical activity, sedentary behavior and the risk of sepsis.

Methods

Using a two-sample Mendelian randomization approach, this study evaluated the association between physical activity (including moderate to vigorous physical activity [MVPA], vigorous physical activity [VPA], and accelerometer assessed physical activity) and sedentary behaviors (including television watching, computer use, and driving) with the risk of sepsis. This assessment was based on whole-genome association study data from the UK Biobank and the FinnGen database. Causal inferences were estimated using inverse variance-weighted, weighted median, and MR-Egger methods. Sensitivity analyses were performed using Cochran's Q test, the MR-Egger intercept test, and the leave-one-out method.

Results

The risk of sepsis was significantly inversely associated with genetically predicted MVPA (odds ratio [OR] 0.47, 95% confidence interval [CI] 0.24-0.93, P = 0.0296) and VPA alone (OR 0.19, 95% CI 0.04-0.87, P = 0.0324). Conversely, prolonged driving time showed a significant positive association with the risk of sepsis (OR 3.99, 95% CI 1.40-11.40, P = 0.0097).

Conclusion

This study provides preliminary evidence of a causal relationship between MVPA and VPA and a reduced risk of sepsis, while prolonged sedentary behaviors such as driving are positively associated with an increased risk of sepsis. These findings provided essential scientific evidence for the development of effective sepsis prevention strategies.

Daily-Life Walking Speed, Quality and Quantity Derived from a Wrist Motion Sensor: Large-Scale Normative Data for Middle-Aged and Older Adults

Walking is crucial for independence and quality of life. This study leverages wrist-worn sensor data from UK Biobank participants to establish normative daily-life walking data, stratified by age and sex, to provide benchmarks for research and clinical practice. The Watch Walk digital biomarkers were developed, validated, and applied to 92,022 participants aged 45-79 who wore a wrist sensor for at least three days. Normative data were collected for daily-life walking speed, step-time variability, step count, and 17 other gait and sleep biomarkers. Test-retest reliability was calculated, and associations with sex, age, self-reported walking pace, and mobility problems were examined. Population mean maximal and usual walking speeds were 1.49 and 1.15 m/s, respectively. The daily step count was 7749 steps, and step regularity was 65%. Women walked more regularly but slower than men. Walking speed, step count, longest walk duration, and step regularity decreased with age. Walking speed is associated with sex, age, self-reported pace, and mobility problems. Test-retest reliability was good to excellent (ICC ≥ 0.80). This study provides large-scale normative data and benchmarks for wrist-sensor-derived digital gait and sleep biomarkers from real-world data for future research and clinical applications.

Analytic Methods for Understanding the Temporal Patterning of Dietary and 24-H Movement Behaviors: A Scoping Review

Dietary and movement behaviors [physical activity (PA), sedentary behavior (SED), and sleep] occur throughout a 24-h day and involve multiple contexts. Understanding the temporal patterning of these 24-h behaviors and their contextual determinants is key to determining their combined effect on health. A scoping review was conducted to identify novel analytic methods for determining temporal behavior patterns and their contextual correlates. We searched Embase, ProQuest, and EBSCOhost databases in July 2022 to identify studies published between 1997 and 2022 on temporal patterns and their contextual correlates (e.g., locational, social, environmental, personal). We included 14 studies after title and abstract (n = 33,292) and full-text (n = 135) screening, of which 11 were published after 2018. Most studies (n = 4 in adults; n = 5 in children and adolescents), examined waking behavior patterns (i.e., both PA and SED) of which 3 also included sleep and 6 included contextual correlates. PA and diet were examined together in only 1 study of adults. Contextual correlates of dietary, PA, and sleep temporal behavior patterns were also examined. Machine learning with various clustering algorithms and model-based clustering techniques were most used to determine 24-h temporal behavior patterns. Although the included studies used a diverse range of methods, behavioral variables, and assessment periods, results showed that temporal patterns characterized by high SED and low PA were linked to poorer health outcomes, than those with low SED and high PA. This review identified temporal behavior patterns, and their contextual correlates, which were associated with adiposity and cardiometabolic disease risk, suggesting these methods hold promise for the discovery of holistic lifestyle exposures important to health. Standardized reporting of methods and patterns and multidisciplinary collaboration among nutrition, PA, and sleep researchers; statisticians; and computer scientists were identified as key pathways to advance future research on temporal behavior patterns in relation to health.

The associations of chronic pain and 24-h movement behaviors with incident mental disorders: evidence from a large-scale cohort study

BACKGROUND

Chronic pain was associated with a higher risk of mental disorders (e.g., depression and anxiety). However, the role of 24-h movement behaviors in the association remains unclear.

METHODS

A total of 72,800 participants with accelerometer data and free of mental disorders from the UK Biobank were analyzed. The compositional mediation model and isotemporal substitution model were used to explore the associations between chronic pain, 24-h movement behaviors, and the incidence of overall mental disorders, depression, and anxiety.

RESULTS

With a median follow-up of 13.36 years, participants with chronic pain had a higher rate of incident overall mental disorders (hazard ratio (HR): 1.281, 95% confidence interval (CI): 1.219 to 1.344), anxiety (HR: 1.391, 95% CI: 1.280 to 1.536), and depression (HR: 1.703, 95% CI: 1.551 to 1.871). Increased sedentary behavior (SB) and reduced moderate-to-vigorous physical activity (MVPA) caused by chronic pain both increased the risk of mental disorders. Twenty-four-hour movement behaviors explained the relationship between chronic pain and overall mental disorders, depression, and anxiety by 10.77%, 5.70%, and 6.86%, respectively. Interaction effects were found between MVPA and chronic pain when predicting the incidence of depression and between MVPA, sleep (SLP), and chronic pain when predicting the incidence of mental disorders. People with chronic pain would recommend at least 0.5 h per day of MVPA and 7 h per day of SLP and restricting SB below 11.5 h per day.

CONCLUSIONS

Twenty-four-hour movement behaviors played a significant mediating role in the association between chronic pain and mental disorders. Individuals with chronic pain should engage in more MVPA, less sedentary behavior, and have 7-h sleep per day.

Thigh-worn accelerometry: a comparative study of two no-code classification methods for identifying physical activity types

BACKGROUND

The more accurate we can assess human physical behaviour in free-living conditions the better we can understand its relationship with health and wellbeing. Thigh-worn accelerometry can be used to identify basic activity types as well as different postures with high accuracy. User-friendly software without the need for specialized programming may support the adoption of this method. This study aims to evaluate the classification accuracy of two novel no-code classification methods, namely SENS motion and ActiPASS.

METHODS

A sample of 38 healthy adults (30.8 ± 9.6 years; 53% female) wore the SENS motion accelerometer (12.5 Hz; ±4 g) on their thigh during various physical activities. Participants completed standardized activities with varying intensities in the laboratory. Activities included walking, running, cycling, sitting, standing, and lying down. Subsequently, participants performed unrestricted free-living activities outside of the laboratory while being video-recorded with a chest-mounted camera. Videos were annotated using a predefined labelling scheme and annotations served as a reference for the free-living condition. Classification output from the SENS motion software and ActiPASS software was compared to reference labels.

RESULTS

A total of 63.6 h of activity data were analysed. We observed a high level of agreement between the two classification algorithms and their respective references in both conditions. In the free-living condition, Cohen's kappa coefficients were 0.86 for SENS and 0.92 for ActiPASS. The mean balanced accuracy ranged from 0.81 (cycling) to 0.99 (running) for SENS and from 0.92 (walking) to 0.99 (sedentary) for ActiPASS across all activity types.

CONCLUSIONS

The study shows that two available no-code classification methods can be used to accurately identify basic physical activity types and postures. Our results highlight the accuracy of both methods based on relatively low sampling frequency data. The classification methods showed differences in performance, with lower sensitivity observed in free-living cycling (SENS) and slow treadmill walking (ActiPASS). Both methods use different sets of activity classes with varying definitions, which may explain the observed differences. Our results support the use of the SENS motion system and both no-code classification methods.

Daily physical activity in older adults across levels of care: the HUNT Trondheim 70 + study

BACKGROUND

Physical activity (PA) is imperative for healthy ageing and is a modifiable lifestyle factor. Accurate, clinically meaningful estimates of daily PA among older adults can inform targeted interventions to maintain function and independence. This study describes daily PA in older adults across levels of care as a first step contributing to the limited evidence on potential associations between PA and the use of care services.

METHODS

This study used data from the Trondheim 70 + cohort in the population-based Norwegian HUNT Study. In total, 1042 participants aged 70 years or older with valid activity data were included. PA was assessed using two accelerometers over 7 consecutive days and was classified into PA (walking, standing, running, and cycling) and sedentary behavior (sitting and lying). Data on received care services were retrieved from municipal registers and participants were classified into four levels of care: 1) independently living (81.9%), 2) independently living with low-level home care services (6.5%), 3) recipients of home care services (6.0%), and 4) nursing home residents (5.7%). Time spent in the activity types and duration of bouts are presented across levels of care.

RESULTS

Participants mean age was 77.5 years (range: 70.1-105.4, 55% female) and PA was lower with higher age. Across levels of care, significant group differences were found in the total time spent in PA, particularly in walking and standing. Daily PA, duration of active bouts, and number of daily walking bouts were lower for participants receiving higher levels of care. Standing was the dominant type of PA and walking appeared predominantly in short bouts at all care levels.

CONCLUSIONS

This is the first population-based study using device-measured PA to describe daily PA across levels of care. The results showed that low-intensity activities constitute the primary component of everyday PA, advocating for placing greater emphasis on the significant role these activities play in maintaining daily PA at older age. Furthermore, the study demonstrated that activity types and bout durations are related to the ability to live independently among older adults. Overall, these findings can contribute to better target interventions to maintain function and independence in older adults.

Reliability, validity and minimal detectable change of the Chinese Version of the Assessment of Physical Activity in Frail Older People (APAFOP-C)

BACKGROUND

Physical activity (PA) is essential in mitigating frailty syndrome, and it is necessary to measure PA in older adults with frailty. Assessment of Physical Activity in Frail Older People (APAFOP) is a suitable patient-reported outcome measure (PROM) for assessing PA among older adults with frailty. This study aimed to determine the reliability, validity and minimal detectable change of the Chinese version of the APAFOP (APAFOP-C).

METHODS

This cross-sectional validation study was designed to measure the reliability and criterion validity of the APAFOP-C with 124 frail community-residing older adults. APAFOP-C was completed twice within an interval of 7-17 days to determine test-retest reliability. The investigator triangulation method was used to investigate inter-rater reliability, and a pedometer was used as the reference measurement to assess the criterion validity. Reliability and criterion validity were assessed using the intraclass correlation coefficient (ICC2,1), Pearson correlation coefficient for normally distributed variables, Spearman correlation coefficient, Wilcoxon signed-rank test for skewed variables, and the minimal detectable change at 95% level of confidence (MDC95). Agreement assessment was conducted using Bland-Altman plots for inter-rater reliability and criterion validity. Kendall's W test assessed absolute agreement among three raters in inter-rater reliability. The Mann-Whitney U test was used to evaluate whether any particular day was more representative of certain daily activities.

RESULTS

Total PA on any arbitrarily chosen day illustrates daily activity (Z= -0.84, p = 0.40). The APAFOP-C exhibited strong-to-very strong test-retest reliability (ICC2,1=0.73-0.97; Spearman ρ = 0.67-0.89), and the total PA score demonstrated MDC95 < 10%. Inter-rater reliability was also strong-to-very strong (ICC2,1=0.96-0.98; Spearman ρ = 0.88-1.00), and moderate criterion validity when compared with total PA score on pedometer readings (Spearman ρ = 0.61). Limits of agreement among different raters regarding the APAFOP-C and the pedometer were narrow.

CONCLUSION

The APAFOP-C was found to have limited but acceptable psychometric properties for measuring PA among community-dwelling older adults with frailty in China. It was a feasible comparative PROM for assessing PA worldwide. Practitioners can develop individualized exercise programs for frail older adults and efficiently track changes in PA utilizing the APAFOP-C.

Factors impacting physical activity among post-treatment pediatric cancer survivors with overweight and obesity

BACKGROUND

Pediatric cancer survivors (PCS) with overweight and obesity are at risk for various secondary chronic diseases. Although previous research has found physical activity (PA) as beneficial after treatment, the PA levels are low among PCS, highlighting the need for lifestyle interventions targeting PA.

METHODS

A secondary analysis of preliminary baseline data from a multi-site trial, NOURISH-T + , a healthy lifestyle intervention for PCS with overweight and obesity, and their caregivers, was conducted to assess factors related to PCS PA (i.e., moderate to vigorous intensity PA, MVPA). Kendall's Tau-b was used to assess correlations between PCS MVPA, health and treatment-related factors, and caregivers' sedentary behavior and MVPA. Wilcoxon Signed Ranks Test was used to assess the differences between PCS and caregiver sedentary behavior and MVPA. A multiple linear regression analysis was performed to determine predictors of PCS MVPA.

RESULTS

Seventy-three PCS-caregiver dyads were included in this analysis (N = 146). Many of the PCS were female, diagnosed with Acute Lymphoblastic Leukemia, stage 1, with a mean body mass index (BMI) percentile of 94.4 ± 4.7. Caregivers were female and parents to the PCS. Significant correlations were found between PCS MVPA, time since treatment, PCS weight change since COVID, caregiver sedentary behavior and MVPA. Significant differences were observed between PCS and caregiver sedentary behavior and MVPA. Household income, radiation treatment, and caregiver MVPA were significant predictors of PCS MVPA.   Conclusions: Demographics, cancer treatment type, and caregiver role modeling are important factors to consider when developing future lifestyle interventions for PCS. (NCT04656496, registered 12-07-2020).

WHAT IS KNOWN

• Parents/caregivers are presumed to be a potential influence on their children's physical activity What is new: • Parents/caregivers' moderate-to-vigorous physical activity is the strongest predictor of their children's (pediatric cancer survivors') physical activity.

Cross-sectional associations between accelerometer-measured physical activity and hip bone mineral density: the Tromsø Study 2015-2016

Positive associations between physical activity and bone health have been found in population-based studies, however, mostly based on self-reported physical activity. Therefore, we investigated the association between accelerometer-measured physical activity, measured in steps per day and minutes of moderate to vigorous physical activity (MVPA) per day, and total hip areal BMD (aBMD) measured by DXA in a general population, utilizing multiple regression models. The study participants, 1560 women and 1177 men aged 40-84 yr, were part of the seventh survey of the Tromsø Study (2015-2016). In both genders, we found a positive association between the number of daily steps and aBMD adjusted for age, BMI, and smoking status (P < .001). In women, an increase of 1000 steps per day was associated with 0.005 g/cm2 higher aBMD. For men, a polynomial curve indicated a positive association with aBMD up to 5000 steps per day, plateauing between 5000 and 14 000 steps, and then increasing again. Additionally, MVPA duration was positively associated with aBMD in both women (P < .001) and men (P = .004) when adjusted for age, BMI, and smoking status. Specifically, each 60-min increase in daily MVPA was associated with 0.028 and 0.023 g/cm2 higher aBMD in women and men, respectively. Despite positive associations, the clinical impact of physical activity on aBMD in this general population of adults and older adults was relatively small, and a large increase in daily MVPA might not be achievable for most individuals. Therefore, further longitudinal population-based studies incorporating device-based measures of physical activity could add more clarity to these relationships.

Accelerometer-Based Estimates of Physical Activity and Sedentary Time Among Samoan Adults

BACKGROUND

The prevalence of obesity-related cardiometabolic disease in Samoa is among the highest globally. While physical activity is a modifiable risk factor for obesity-related disease, little is known about physical activity levels among adult Samoans. Using wrist-worn accelerometer-based devices, this study aimed to characterize physical activity among Samoan adults.

METHODS

Samoan adults (n = 385; 55% female, mean [SD] age 52 [10] y) wore Actigraph GT3X+ devices for 7 to 10 days. General linear models were used to examine mean daily minutes of sedentary time, light physical activity, and moderate to vigorous physical activity by various participant characteristics.

RESULTS

Time spent in moderate to vigorous physical activity did not differ statistically between men (88 [5] min; 95% confidence interval [CI], 80-97) and women (78 [4] min; 95% CI, 70-86; P = .08). Women, however, spent more time than men in light physical activity: 380 (7) minutes (95% CI, 367-393) versus 344 (7) minutes (95% CI, 329-358; P < .001). While there were no differences in physical activity by census region, education, or occupation among women, men in urban areas spent significantly less time in moderate to vigorous physical activity than those in peri-urban and rural areas (P = .015). Women with class II/III obesity spent more time in sedentary activities than those with healthy weight or overweight/class I obesity (P = .048).

CONCLUSIONS

This study characterizes physical activity among Samoan adults and highlights variation by sex, urbanicity, and weight status. In providing initial device-measured estimates of physical activity in Samoa, this analysis establishes a baseline from which the success of future attempts to intervene on physical activity may be assessed.

Using Wearable Sensors and Machine Learning to Assess Upper Limb Function in Huntington's Disease

Huntington's disease (HD), like many other neurological disorders, affects both lower and upper limb function that is typically assessed in the clinic - providing a snapshot of disease symptoms. Wearable sensors enable the collection of real-world data that can complement such clinical assessments and provide a more comprehensive insight into disease symptoms. In this context, almost all studies are focused on assessing lower limb function via monitoring of gait, physical activity and ambulation. In this study, we monitor upper limb function during activities of daily living in individuals with HD (n = 16), prodromal HD (pHD, n = 7), and controls (CTR, n = 16) using a wrist-worn wearable sensor, called PAMSys ULM, over seven days. The participants were highly compliant in wearing the sensor with an average daily compliance of 99% (100% for HD, 98% for pHD, and 99% for CTR). Goal-directed movements (GDM) of the hand were detected using a deep learning model, and kinematic features of each GDM were estimated. The collected data was used to predict disease groups (i.e., HD, pHD, and CTR) and clinical scores using a combination of statistical and machine learning-based models. Significant differences in GDM features were observed between the groups. HD participants performed fewer GDMs with long duration (> 7.5 seconds) compared to CTR (p-val = 0.021, d = -0.86). In velocity and acceleration metrics, the highest effect size feature was the entropy of the velocity zero-crossing length segments (HD vs CTR p-val <0.001, d = -1.67; HD vs pHD p-val = 0.043, d=-0.98; CTR vs pHD p-val = 0.046, d=0.96). In addition, this same variable showed a strongest correlation with clinical scores. Classification models achieved good performance in distinguishing HD, pHD and CTR individuals with a balanced accuracy of 67% and a 0.72 recall for the HD group, while regression models accurately predicted clinical scores. Notably the explained variance for the upper extremity function subdomain scale of Unified Huntington's Disease Rating Scale (UHDRS) was the highest, with the model capturing 60% of the variance. Our findings suggest the potential of wearables and machine learning for early identification of phenoconversion, remote monitoring in HD, and evaluating new treatments efficacy in clinical trials and medicine.

Quantifying Hitting Load in Racket Sports: A Scoping Review of Key Technologies

PURPOSE

This scoping review aims to identify the primary racket and arm-mounted technologies based on inertial measurement units that enable the quantification of hitting load in racket sports.

METHODS

A comprehensive search of several databases (PubMed, SPORTDiscus, Web of Science, and IEEE Xplore) and Google search engines was conducted following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) extension for scoping reviews guidelines. Included records primarily focused on monitoring hitting load in racket sports using commercialized racket or arm-mounted inertial sensors through noncompetitive and competitive racket-sports players.

RESULTS

A total of 484 records were identified, and 19 finally met the inclusion criteria. The largest number of systems found were compatible with tennis (n = 11), followed by badminton (n = 4), table tennis (n = 2), padel (n = 1), and squash (n = 1). Four sensor locations were identified: grip-attached (n = 8), grip-embedded (n = 6), wrist (n = 3), and dampener sensors (n = 2). Among the tennis sensors, only 4 out of the 11 (36.4%) demonstrated excellent reliability (>.85) in monitoring the number of shots hit either during analytic drills or during simulated matches. None of the other racket-sports sensors have undergone successful, reliable validation for hitting-volume quantification.

CONCLUSIONS

Despite recent advancements in this field, the quantification of hitting volume in racket sports remains a challenge, with only a limited number of tennis devices demonstrating reliable results. Thus, further progress in technology and research is essential to develop comprehensive solutions that adequately address these specific requirements.

Maternal 24-h movement patterns across pregnancy and postpartum: The LIFE-Moms consortium

Objective

Time spent among the 24-h movement behaviors (physical activity [PA], sleep, sedentary behavior [SB]) in the perinatal period is important for maternal and child health. We described changes to 24-h movement behaviors and behavior guideline attainment during pregnancy and postpartum and identified correlates of behavior changes.

Methods

This secondary data analysis included the standard of care group (n = 439) from the U.S.-based Lifestyle Interventions For Expectant Moms (LIFE-Moms) consortium, including persons with overweight and obesity. Wrist-worn accelerometry was used to measure movement behaviors early (9-15 weeks) and late (35-36 weeks) pregnancy, and ∼ 1-year postpartum. Sleep and moderate-to-vigorous PA (MVPA) were compared to adult and pregnancy-specific guidelines, respectively. SB was classified into quartiles. PA and SB context were quantified using questionnaires. Mixed models were used to examine changes in behaviors and guidelines and identify correlates.

Results

Participants were 31.3 ± 3.5 years, 53.5 % were Black or Hispanic, and 45.1 % had overweight. Sleep duration decreased across time, but participants consistently met the guideline (range: 85.0-93.6 %). SB increased during pregnancy and decreased postpartum, while light PA and MVPA followed the inverse pattern. Participants met slightly fewer guidelines late pregnancy (1.2 ± 0.7 guidelines) but more postpartum (1.7 ± 0.8 guidelines) than early pregnancy (1.4 ± 0.8 guidelines). Black or Hispanic race/ethnicity, higher pregravid body mass index, and non-day work-shift (e.g., night-shift) were identified correlates of lower guideline adherence and varying PA and SB context.

Conclusion

Perinatal interventions should consider strategies to prevent SB increase and sustain MVPA to promote guideline adherence.

Contribution of youth sport participation to physical activity levels and cardiovascular disease risk factors in 5-year-old to 14-year-old children: a study protocol for systematic review and meta-analysis

INTRODUCTION

Cardiovascular disease (CVD) accounts for 18 million deaths per year, disproportionately burdens under-represented racial and ethnic groups, and has economic costs greater than any other health condition. Participation in youth sport may be an effective strategy to improve CVD-related risk factors but studies of youth sport participation have shown mixed results for improving health outcomes. Therefore, the objective of this systematic review is to examine how participation in youth sport contributes to physical activity levels and CVD risk factors in children aged 5-14 years old. A secondary objective is to determine if outcomes are different in racial and ethnic groups.

METHODS AND ANALYSIS

The search will encompass studies published in English, Spanish or Portuguese between January 1995 and April 2024, including five databases (PubMed, Medline, Embase, Cochrane Library and SPORTDiscus). Studies will be included if they are experimental or observational studies, conducted in youths of any health background and assess the relationship of sport participation to physical activity levels or CVD risk factors. Studies must report on at least one of the following outcomes: (1) physical activity levels, (2) blood pressure, (3) lipid fractions, (4) body mass index (5) central adiposity, (6) systemic inflammation and (7) glucose levels/insulin resistance. Study quality will be assessed using the Cochrane Risk of Bias version 1 tool. Narrative descriptions and summary tables will be created to describe studies, results and methodological quality and be synthesised by subsets of studies based on study design and outcomes. In the systematic review, we will categorise the included studies into two subgroups (ie, observational studies, experimental studies) and meta-analyse them separately prior to exploring sources of heterogeneity.

ETHICS AND DISSEMINATION

Ethical approval is not required. The results will be disseminated via peer-reviewed publication and presentation at conferences relevant to this field.

PROSPERO REGISTRATION NUMBER

CRD42023427219.

Does intervention engagement mediate physical activity change in a web-based computer-tailored physical activity intervention?-Secondary outcomes from a randomised controlled trial

Introduction

The relationship between intervention engagement and behaviour change may vary depending on the specific engagement metric being examined. To counter this composite engagement measures may provide a deeper understanding of the relationship between engagement and behaviour change, though few studies have applied such multidimensional engagement metrics. The aim of this secondary analysis of RCT data was to examine how a composite engagement score mediates the effect of a web-based computer-tailored physical activity intervention.

Methods

501 inactive Australian adults were randomised to a no-treatment control or intervention group. Intervention participants received 8 sessions of web-based personalised physical activity advice over a 12-week intervention period and the ability to complete action plans. Change in physical activity was assessed using Actigraph accelerometers at baseline, 3-months and 9-months. Engagement with the intervention (i.e., a composite score including frequency, intensity, duration and type) was continuously assessed during the intervention period using website tracking software and database metrics. Generalised structural equation models were used to examine how a composite engagement score mediated intervention effects at 3 months and 9 months.

Results

At 3 months, mediation analysis revealed that the intervention group had significantly higher engagement scores than the control group [a-path exp(b) = 6.462, 95% CI = 5.121-7.804, p < 0.001]. Further, increased engagement with the intervention platform was associated with an increased time spent in moderate-to-vigorous physical activity [ab-coefficient exp(b) = 1.008, 95% CI = 1.004-1.014, P < 0.001]; however, the magnitude of this effect was small. There were no significant mediation effects at the 9-month time point.

Discussion

The findings suggest that a composite intervention engagement score has a small positive influence on physical activity changes and that other factors (e.g., behaviour change techniques) are likely to be more important drivers of behaviour change.

A blended face-to-face and eHealth lifestyle intervention on physical activity, diet, and health outcomes in Hong Kong community-dwelling older adults: a study protocol for a randomized controlled trial

Background

Aging individuals are vulnerable to various Noncommunicable Diseases (NCDs). Different behaviors are closely related to a decreased risk of suffering from NCDs: sufficient Physical Activity (PA) (e.g., at least 150 mins Moderate-to-vigorous Physical Activity (MVPA) per week) and a healthy daily diet (e.g., at least five portions of Fruit and Vegetable Intake (FVI), 5-6 taels (189.0-226.8 g) Meat, Fish, Egg and Alternatives (MFEA)). Traditional face-to-face interventions were effective in behavior change. However, it was revealed to be resource-intensive and limited transfer due to poor self-regulation skills outside of face-to-face sessions. Thus, eHealth could be a supplement for older adults outside traditional face-to-face settings. The blended approach combining these two interventions might optimize the intervention effects on lifestyle behavior initiation and maintenance, but little research can be found among Hong Kong older adults. Therefore, the study aims to test a blended intervention to promote PA, diet, and health outcomes among Hong Kong community-dwelling older adults.

Methods

This study will adopt a 10-week three-arm randomized controlled trial. The blended group will receive weekly (1) two 60-min face-to-face sessions with one for PA and one for diet, and (2) two web-based sessions with one for PA and one for diet. The face-to-face group will receive the same intervention content as the face-to-face sessions in the blended group. The control condition will receive a biweekly telephone call. The outcomes will include MVPA (minutes/week), FVI (portions/day), MFEA consumption (taels/day), social-cognitive factors (self-efficacy, planning, social support, action control), physical health outcomes (clinical indicators, senior physical fitness), mental health outcomes (depression, loneliness) and health-related quality of life. Data collection will be implemented at the pre-test, post-test, and 3-month follow-up test.

Discussion

This is the first study evaluating a blended intervention promoting multiple health behaviors among Hong Kong community-dwelling older adults. If the effect of the blended intervention is superior to the traditional face-to-face group and the control group, it will enrich lifestyle intervention approaches and can be applied to older adults, helping them obtain health benefits. Furthermore, a better understanding of mechanisms will also have implications for theory-building.

Clinical trial registration

https://www.isrctn.com/ISRCTN32329348, ISRCTN32329348.

Comparison of patient-reported outcomes of physical activity and accelerometry in people with multiple sclerosis and ambulatory impairment: A cross-sectional study

BACKGROUND

Accelerometers and patient-reported outcomes (PRO) are used to assess physical activity (PA) in people with multiple sclerosis (pwMS). So far it is unknown, however, whether these assessments represent mobility limitations in pwMS with mild and moderate to severe disability alike. The primary aim of the study was to assess the correlation between accelerometry and International Physical Activity Questionnaire (IPAQ) scores in pwMS with different degrees of ambulatory impairment. Taken its frequent use into account, the Godin Leisure Time Exercise Questionnaire (GLTEQ) was investigated as additional PRO.

METHODS

In a prospective cohort of pwMS, correlational analyses were performed between the number of daily steps, time spent in light, moderate to vigorous PA (MVPA) and time spent sitting as assessed using accelerometry (ActiGraph®-GT3X), and the respective IPAQ and GLTEQ scores. Additionally, associations of PA with disease-specific characteristics, aerobic capacity (VO2peak), walking assessments (Timed 25-Foot Walk, T25FW; 2-Minute Walk Test, 2MWT) and walking perception (Multiple Sclerosis Walking Scale-12; MSWS-12) were explored. Patient subgroups with mild (Expanded Disability Status Scale; EDSS score <4.0) and moderate to severe disability (EDSS ≥4.0) were analysed for the impact of ambulatory impairment on PA. Multiple linear regression was used to determine predictors of PA.

RESULTS

A total of 56 pwMS completed the study, with a mean (standard deviation, SD) age of 48.4 (10.3) years, disease duration of 14.8 (9.6) years and median (interquartile range) EDSS score of 3.5 (2.0 - 4.4). Moderate to weak correlations were found between daily step count and IPAQ total metabolic equivalent (MET) minutes/week (p < 0.001; r = 0.506), MVPA MET-minutes/week (p < 0.01; r = 0.479) and walking MET-minutes/week (p < 0.05; r = 0.372) in the total cohort. Time spent sitting was inversely correlated with total MET-minutes/week and MVPA MET-minutes/week (p < 0.05; r = -0.358 and r = -0.365). Subgroup analysis revealed, that daily step count was significantly correlated with total MET-minutes/week, MVPA MET-minutes/week and walking MET-minutes/week (p < 0.01, r = 0.569; p < 0.01, r = 0.531 and p < 0.05, r = 0.480, respectively) in the "mild disability" subgroup only, whereas time spent sitting was inversely correlated with total MET-minutes/week (p < 0.05; r = -0.582) in the "moderate to severe disability" subgroup. There was no association between objectively assessed PA and GLTEQ scores in any group. In the total cohort, moderate to weak correlations were found between daily step count and walking assessments (T25FW: p < 0.01, ρ = -0.508; 2MWT: p < 0.01, ρ=0.463) and MSWS-12 (p < 0.001; ρ = -0.609). Moderate to weak correlations were also observed between VO2peak and walking assessments (T25FW: p < 0.01; ρ = -0.516; 2MWT: p < 0.01, ρ=0.480). Multiple linear regression analysis identified disability and VO2peak as predictors of PA (p = 0.045; β=0.25 and p < 0.001; β=0.49).

CONCLUSION

Significant associations of objective PA measurements using accelerometry with IPAQ were found only in pwMS with "mild disability". In pwMS with "moderate to severe disability", IPAQ did not reflect the objectively assessed amount of PA. In our cohort, GLTEQ showed no association with objectively assessed PA. Thus, an MS-specific self-reported questionnaire for assessing PA is warranted.

Wearable Sensors to Monitor Physical Activity in Heart Failure Clinical Trials: State-of-the-Art Review

BACKGROUND

Estimation of the effects that drugs or other interventions have on patients' symptoms and functions is crucial in heart failure trials. Traditional symptoms and functions clinical outcome assessments have important limitations. Actigraphy may help to overcome these limitations due to its objective nature and the potential for continuous recording of data. However, actigraphy is not currently accepted as clinically relevant by key stakeholders.

METHODS AND RESULTS

In this state-of-the-art study, the key aspects to consider when implementing actigraphy in heart failure trials are discussed. They include which actigraphy-derived measures should be considered, how to build endpoints using them, how to measure and analyze them, and how to handle the patients' and sites' logistics of integrating devices into trials. A comprehensive recommendation based on the current evidence is provided.

CONCLUSION

Actigraphy is technically feasible in clinical trials involving heart failure, but successful implementation and use to demonstrate clinically important differences in physical functioning with drug or other interventions require careful consideration of many design choices.

Remote monitoring of amyotrophic lateral sclerosis using wearable sensors detects differences in disease progression and survival: a prospective cohort study

BACKGROUND

There is an urgent need for objective and sensitive measures to quantify clinical disease progression and gauge the response to treatment in clinical trials for amyotrophic lateral sclerosis (ALS). Here, we evaluate the ability of an accelerometer-derived outcome to detect differential clinical disease progression and assess its longitudinal associations with overall survival in patients with ALS.

METHODS

Patients with ALS wore an accelerometer on the hip for 3-7 days, every 2-3 months during a multi-year observation period. An accelerometer-derived outcome, the Vertical Movement Index (VMI), was calculated, together with predicted disease progression rates, and jointly analysed with overall survival. The clinical utility of VMI was evaluated using comparisons to patient-reported functionality, while the impact of various monitoring schemes on empirical power was explored through simulations.

FINDINGS

In total, 97 patients (70.1% male) wore the accelerometer for 1995 days, for a total of 27,701 h. The VMI was highly discriminatory for predicted disease progression rates, revealing faster rates of decline in patients with a worse predicted prognosis compared to those with a better predicted prognosis (p < 0.0001). The VMI was strongly associated with the hazard for death (HR 0.20, 95% CI: 0.09-0.44, p < 0.0001), where a decrease of 0.19-0.41 unit was associated with reduced ambulatory status. Recommendations for future studies using accelerometery are provided.

INTERPRETATION

The results serve as motivation to incorporate accelerometer-derived outcomes in clinical trials, which is essential for further validation of these markers to meaningful endpoints.

FUNDING

Stichting ALS Nederland (TRICALS-Reactive-II).

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

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

Fatness but Not Fitness Linked to BrainAge: Longitudinal Changes in Brain Aging during an Exercise Intervention

PURPOSE

Fitness, physical activity, body composition, and sleep have all been proposed to explain differences in brain health. We hypothesized that an exercise intervention would result in improved fitness and body composition and would be associated with improved structural brain health.

METHODS

In a randomized controlled trial, we studied 485 older adults who engaged in an exercise intervention ( n = 225) or a nonexercise comparison condition ( n = 260). Using magnetic resonance imaging, we estimated the physiological age of the brain (BrainAge) and derived a predicted age difference compared with chronological age (brain-predicted age difference (BrainPAD)). Aerobic capacity, physical activity, sleep, and body composition were assessed and their impact on BrainPAD explored.

RESULTS

There were no significant differences between experimental groups for any variable at any time point. The intervention group gained fitness, improved body composition, and increased total sleep time but did not have significant changes in BrainPAD. Analyses of changes in BrainPAD independent of group assignment indicated significant associations with changes in body fat percentage ( r (479) = 0.154, P = 0.001), and visceral adipose tissue (VAT) ( r (478) = 0.141, P = 0.002), but not fitness ( r (406) = -0.075, P = 0.129), sleep ( r (467) range, -0.017 to 0.063; P range, 0.171 to 0.710), or physical activity ( r (471) = -0.035, P = 0.444). With linear regression, changes in body fat percentage and VAT significantly predicted changes in BrainPAD ( β = 0.948, P = 0.003) with 1-kg change in VAT predicting 0.948 yr of change in BrainPAD.

CONCLUSIONS

In cognitively normal older adults, exercise did not appear to impact BrainPAD, although it was effective in improving fitness and body composition. Changes in body composition, but not fitness, physical activity, or sleep impacted BrainPAD. These findings suggest that focus on weight control, particularly reduction of central obesity, could be an interventional target to promote healthier brains.

Examining the Association Between Objective Physical Activity and Momentary Pain: A Systematic Review of Studies Using Ambulatory Assessment

Chronic pain (CP) is a debilitating and increasingly common health condition that adversely impacts function, including physical activity (PA). Research using ambulatory assessment (AA) methods (eg, ecological momentary assessment, actigraphy) offers promise for elucidating the relationship between momentary pain and objective PA in CP populations. This study aimed to systematically review articles assessing the association between momentary pain and PA in adults with CP as measured using AA and to make recommendations for the measurement and study of this relationship. Five databases were systematically searched, and 13 unique records (N = 768) met the inclusion criteria. CP conditions included mixed/nonspecific CP (k = 3), low back pain (k = 2), fibromyalgia (k = 1), unspecified arthritis (k = 1), and hip/knee osteoarthritis (k = 6). The average age of participants across studies was 55.29 years, and the majority identified as women (60.68%) and White (83.16%). All studies measured objective PA via actigraphy, and momentary pain with either a diary/log or ratings on an actigraph. Studies varied in the quantification of PA (ie, activity counts, step count, moderate-vigorous PA), statistical method (ie, correlation, regression, multilevel modeling), and inclusion of moderators (eg, pain acceptance). Studies reported mixed results for the pain-PA relationship. This heterogeneity suggests that no summarizing conclusions can be drawn about the pain-PA relationship without further investigation into its complex nuances. More within-person and exploratory examinations that maximize the richness of AA data are needed. A greater understanding of this relationship can inform psychotherapeutic and behavioral recommendations to improve CP outcomes. PERSPECTIVE: This article presents a systematic review of the literature on the association between momentary pain and PA in adults with CP as measured using AA methods. A better understanding of this nuanced relationship could help elucidate areas for timely intervention and may inform clinical recommendations to improve CP outcomes. PROSPERO REGISTRATION NUMBER: CRD42023389913.

Wearable device adherence among insufficiently-active young adults is independent of identity and motivation for physical activity

Wearable devices are increasingly being integrated to improve prevention, chronic disease management and rehabilitation. Inferences about individual differences in device-measured physical activity depends on devices being worn long enough to obtain representative samples of behavior. Little is known about how psychological factors are associated with device wear time adherence. This study evaluated associations between identity, behavioral regulations, and device wear adherence during an ambulatory monitoring period. Young adults who reported insufficient physical activity (N = 271) were recruited for two studies before and after the SARS-COVID-19 pandemic declaration. Participants completed a baseline assessment and wore an Actigraph GT3X + accelerometer on their waist for seven consecutive days. Multiple linear regression indicated that wear time was positively associated with age, negatively associated with integrated regulation for physical activity, and greater after (versus before) the pandemic declaration. Overall, the model accounted for limited variance in device wear time. Exercise identity and exercise motivation were not associated with young adults' adherence to wearing the physical activity monitors. Researchers and clinicians can use wearable devices with young adults with minimal concern about systematic motivational biases impacting adherence to device wear.

The feasibility and acceptability of an app-based intervention with brief behavioural support (APPROACH) to promote brisk walking in people diagnosed with breast, prostate and colorectal cancer in the UK

INTRODUCTION

Increased moderate to vigorous physical activity (MVPA) can improve clinical and psychosocial outcomes for people living with and beyond cancer (LWBC). This study aimed to assess the feasibility and acceptability of trial procedures in a pilot randomised controlled trial (RCT) of a theory-driven app-based intervention with behavioural support focused on promoting brisk walking (a form of MVPA) in people LWBC (APPROACH).

METHODS

Participants diagnosed with breast, prostate or colorectal cancer were recruited from a single UK hospital site. Assessments at baseline and 3 months included online questionnaires, device-measured brisk walking (activPAL accelerometer) and self-reported weight and height. Participants were randomised to intervention or control (care as usual). The intervention comprised a non-cancer-specific app to promote brisk walking (National Health Service 'Active 10') augmented with print information about habit formation, a walking planner and two behavioural support telephone calls. Feasibility and acceptability of trial procedures were explored. Initial estimates for physical activity informed a power calculation for a phase III RCT. A preliminary health economics analysis was conducted.

RESULTS

Of those medically eligible, 369/577 (64%) were willing to answer further eligibility questions and 90/148 (61%) of those eligible were enrolled. Feasibility outcomes, including retention (97%), assessment completion rates (>86%) and app download rates in the intervention group (96%), suggest that the trial procedures are acceptable and that the intervention is feasible. The phase III RCT will require 472 participants to be randomised. As expected, the preliminary health economic analyses indicate a high level of uncertainty around the cost-effectiveness of the intervention.

CONCLUSIONS

This pilot study demonstrates that a large trial of the brisk walking intervention with behavioural support is both feasible and acceptable to people LWBC. The results support progression onto a confirmatory phase III trial to determine the efficacy and cost-effectiveness of the intervention.

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

OBJECTIVE

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

METHOD

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

RESULTS

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

CONCLUSION

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

Upper limb movements as digital biomarkers in people with ALS

BACKGROUND

Objective evaluation of people with amyotrophic lateral sclerosis (PALS) in free-living settings is challenging. The introduction of portable digital devices, such as wearables and smartphones, may improve quantifying disease progression and hasten therapeutic development. However, there is a need for tools to characterize upper limb movements in neurologic disease and disability.

METHODS

Twenty PALS wore a wearable accelerometer, ActiGraph Insight Watch, on their wrist for six months. They also used Beiwe, a smartphone application that collected self-entry ALS Functional Rating Scale-Revised (ALSFRS-RSE) survey responses every 1-4 weeks. We developed several measures that quantify count and duration of upper limb movements: flexion, extension, supination, and pronation. New measures were compared against ALSFRS-RSE total score (Q1-12), and individual responses to specific questions related to handwriting (Q4), cutting food (Q5), dressing and performing hygiene (Q6), and turning in bed and adjusting bed clothes (Q7). Additional analysis considered adjusting for total activity counts (TAC).

FINDINGS

At baseline, PALS with higher Q1-12 performed more upper limb movements, and these movements were faster compared to individuals with more advanced disease. Most upper limb movement metrics had statistically significant change over time, indicating declining function either by decreasing count metrics or by increasing duration metric. All count and duration metrics were significantly associated with Q1-12, flexion and extension counts were significantly associated with Q6 and Q7, supination and pronation counts were also associated with Q4. All duration metrics were associated with Q6 and Q7. All duration metrics retained their statistical significance after adjusting for TAC.

INTERPRETATION

Wearable accelerometer data can be used to generate digital biomarkers on upper limb movements and facilitate patient monitoring in free-living environments. The presented method offers interpretable monitoring of patients' functioning and versatile tracking of disease progression in the limb of interest.

FUNDING

Mitsubishi-Tanabe Pharma Holdings America, Inc.

Validation of ActiGraph and Fitbit in the assessment of energy expenditure in Huntington's disease

BACKGROUND

Consumer and research activity monitors have become popular because of their ability to quantify energy expenditure (EE) in free-living conditions. However, the accuracy of activity trackers in determining EE in people with Huntington's Disease (HD) is unknown.

RESEARCH QUESTION

Can the ActiGraph wGT3X-B or the Fitbit Charge 4 accurately measure energy expenditure during physical activity, in people with HD compared to Indirect Calorimetry (IC) (Medisoft Ergo Card)?

METHODS

We conducted a cross-sectional, observational study with fourteen participants with mild-moderate HD (mean age 55.7 ± 11.4 years). All participants wore an ActiGraph and Fitbit during an incremental test, running on a treadmill at 3.2 km/h and 5.2 km/h for three minutes at each speed. We analysed and compared the accuracy of EE estimates obtained by Fitbit and ActiGraph against the EE estimates obtained by a metabolic cart, using with Intra-class correlation (ICC), Bland-Altman analysis and correlation tests.

RESULTS

A significant correlation and a moderate reliability was found between ActiGraph and IC for the incremental test (r = 0.667)(ICC=0.633). There was a significant correlation between Fitbit and IC during the incremental test (r = 0.701), but the reliability was poor at all tested speeds in the treadmill walk. Fitbit significantly overestimated EE, and ActiGraph underestimated EE compared to IC, but ActiGraph estimates were more accurate than Fitbit in all tests.

SIGNIFICANCE

Compared to IC, Fitbit Charge 4 and ActiGraph wGT3X-BT have reduced accuracy in estimating EE at slower walking speeds. These findings highlight the need for population-specific algorithms and validation of activity trackers.

Associations between physical activity, sedentary time, and neurocognitive function during adolescence: Evidence from accelerometry and the flanker P300

Physical activity and sedentary behavior are two lifestyle factors related to overall health during adolescence. Public health efforts emphasize the importance of increasing physical activity to improve physical and mental health outcomes, including neurocognitive functioning. However, the unique effects of sedentary behavior on neurocognitive functioning remain unclear. This study aimed to investigate associations between daily moderate-to-vigorous physical activity (MVPA), sedentary time, and neurocognitive functioning during adolescence. Fifty-seven participants (37% female) between the ages of 13 and 17 years wore an accelerometer on their non-dominant wrist for approximately 1 week to quantify daily MVPA and sedentary time prior to completing a flanker task to elicit P300 amplitude at a laboratory visit. Results indicated that daily MVPA and sedentary time exhibited unique, significant associations with P300 amplitude in opposing directions: increased daily MVPA was correlated with larger P300 amplitudes, while increased daily sedentary time was linked to reduced P300 amplitudes. Notably, these associations remained significant even after adjusting for age, sex, and BMI-for-age percentile. These findings underscore the independent influence of daily MVPA and sedentary time on neurocognitive functioning during adolescence. Future research should explore whether modifying MVPA levels can improve neurocognitive outcomes-including the P300-during adolescence, and determine whether reducing sedentary time results in similar or differential effects.

Accelerometer-measured 24-hour movement behaviours over 7 days in Malaysian children and adolescents: A cross-sectional study

BACKGROUND

Quantifying movement behaviours over 24-hours enables the combined effects of and inter-relations between sleep, sedentary time and physical activity (PA) to be understood. This is the first study describing 24-hour movement behaviours in school-aged children and adolescents in South-East Asia. Further aims were to investigate between-participant differences in movement behaviours by demographic characteristics and timing of data collection during Ramadan and COVID-19 restrictions.

METHODS

Data came from the South-East Asia Community Observatory health surveillance cohort, 2021-2022. Children aged 7-18 years within selected households in Segamat, Malaysia wore an Axivity AX6 accelerometer on their wrist for 24 hours/day over 7 days, completed the PAQ-C questionnaire, and demographic information was obtained. Accelerometer data was processed using GGIR to determine time spent asleep, inactive, in light-intensity PA (LPA) and moderate-to-vigorous PA (MVPA). Differences in accelerometer-measured PA by demographic characteristics (sex, age, ethnicity, socioeconomic group) were explored using univariate linear regression. Differences between data collected during vs outside Ramadan or during vs after COVID-19 restrictions, were investigated through univariate and multiple linear regressions, adjusted for age, sex and ethnicity.

RESULTS

The 491 participants providing accelerometer data spent 8.2 (95% confidence interval (CI) = 7.9-8.4) hours/day asleep, 12.4 (95% CI = 12.2-12.7) hours/day inactive, 2.8 (95% CI = 2.7-2.9) hours/day in LPA, and 33.0 (95% CI = 31.0-35.1) minutes/day in MVPA. Greater PA and less time inactive were observed in boys vs girls, children vs adolescents, Indian and Chinese vs Malay children and higher income vs lower income households. Data collection during Ramadan or during COVID-19 restrictions were not associated with MVPA engagement after adjustment for demographic characteristics.

CONCLUSIONS

Demographic characteristics remained the strongest correlates of accelerometer-measured 24-hour movement behaviours in Malaysian children and adolescents. Future studies should seek to understand why predominantly girls, adolescents and children from Malay ethnicities have particularly low movement behaviours within Malaysia.

Does Wrist-Worn Accelerometer Wear Compliance Wane over a Free-Living Assessment Period? An NHANES Analysis

PURPOSE

Accelerometers are used to objectively measure physical behaviors in free-living environments, typically for seven consecutive days or more. We examined whether participants experience "wear fatigue," a decline in wear time day over day, during typical assessment period acquired in a nationally representative sample of 6- to 80-yr-olds in the United States.

METHODS

Participants were instructed to wear an ActiGraph GT3X+ on their nondominant wrist continuously for seven consecutive days. Participants with seven complete days of recorded data, regardless of wear status, were included in the analyses ( N = 13,649). Wear was scored with the sleep, wake, and nonwear algorithm.

RESULTS

Participants averaged 1248 ± 3.6 min·d -1 (mean ± SE) of wear over the assessment, but wear time linearly decreased from day 1 (1295 ± 3.2 min) to day 7 (1170 ± 5.3 min), resulting in a wear fatigue of -18.1 ± 0.7 min·d -1 ( β ± SE). Wear fatigue did not differ by sex but varied by age-group-highest in adolescents (-26.8 ± 2.4 min·d -1 ) and lowest in older adults (-9.3 ± 0.9 min·d -1 ). Wear was lower in evening (1800-2359 h) and early morning (0000-0559 h) compared with the middle of the day and on weekend days compared with weekdays. We verified similar wear fatigue (-23.5 ± 0.7 min·d -1 ) in a separate sample ( N = 14,631) with hip-worn devices and different wear scoring. Applying minimum wear criteria of ≥10 h·d -1 for ≥4 d reduced wear fatigue to -5.3 and -18.7 min·d -1 for the wrist and hip, respectively.

CONCLUSIONS

Patterns of wear suggest noncompliance may disproportionately affect estimates of sleep and sedentary behavior, particularly for adolescents. Further study is needed to determine the effect of wear fatigue on longer assessments.

Calibration and validation of physical behaviour cut-points using wrist-worn ActiGraphs for children and adolescents: A systematic review

OBJECTIVES

To review cut-points calibrated and independently validated from wrist-worn ActiGraph accelerometers to measure moderate to vigorous physical activity (MVPA) and time spent sedentary (SED) in children and adolescents.

DESIGN

Systematic literature review.

METHODS

Five databases were searched for relevant cut-point calibration and independent validation studies relating to wrist worn ActiGraphs in children and adolescents from inception through 30 April 2022. Extracted data included: country of publication; study name; population; device model; wear location; sampling frequency; epoch length; activity protocol; criterion method and definitions used to classify PA intensity; statistical methods for calibration; statistical methods for validation/cross-validation; and MVPA and SED outcome.

RESULTS

Fourteen calibration studies and seven independent validation studies were identified. Calibrated cut-points for MVPA vector magnitude counts ranged from 7065 to 9204 counts per minute (cpm) and 63.5 to 201 milli-gravitational units (mg). For SED, calibrated cut-points ranged from <2556 cpm to 4350 cpm and 30.8 to 48.1 mg. Classification accuracy values determined by independent validation studies varied, with kappa values ranging from 0.31 to 0.60 and area under the curve statistics ranging from 0.51 to 0.84 for MVPA and kappa values ranging from 0.31 to 0.44 and area under the curve statistics ranging from 0.70 to 0.85 for SED.

CONCLUSIONS

The results of this systematic literature review support the use of the Crouter and colleagues cut-points for the measurement of MVPA and SED for children and adolescents aged 6-12 years. Further work is required to independently validate cut-points developed in younger children and older adolescents.

Comparison of actigraphy-measured and parent-reported sleep in association with weight status among preschool children

This study compared weekday and weekend actigraphy-measured and parent-reported sleep in relation to weight status among preschool-aged children. Participants were 3-6 years old preschoolers from the cross-sectional DAGIS-study with sleep data for ≥2 weekday and ≥2 weekend nights. Parents-reported sleep onset and wake-up times were gathered alongside 24 h hip-worn actigraphy. An unsupervised Hidden-Markov Model algorithm provided actigraphy-measured night time sleep without the guidance of reported sleep times. Waist-to-height ratio and age-and-sex-specific body mass index characterised weight status. Comparison of methods were assessed with consistency in quintile divisions and Spearman correlations. Associations between sleep and weight status were assessed with adjusted regression models. Participants included 638 children (49% girls) with a mean ± SD age of 4.76 ± 0.89. On weekdays, 98%-99% of actigraphy-measured and parent-reported sleep estimates were classified in the same or adjacent quintile and were strongly correlated (rs  = 0.79-0.85, p < 0.001). On weekends, 84%-98% of actigraphy-measured and parent-reported sleep estimates were respectively classified and correlations were moderate to strong (rs  = 0.62-0.86, p < 0.001). Compared with actigraphy-measured sleep, parent-reported sleep had consistently earlier onset, later wake-up, and greater duration. Earlier actigraphy-measured weekday sleep onset and midpoint were associated with a higher body mass index (respective β-estimates: -0.63, p < 0.01 and -0.75, p < 0.01) and waist-to-height ratio (-0.004, p = 0.03 and -0.01, p = 0.02). Though the sleep estimation methods were consistent and correlated, actigraphy measures should be favoured as they are more objective and sensitive to identifying associations between sleep timing and weight status compared with parent reports.

Validation of a Zio XT Patch Accelerometer for the Objective Assessment of Physical Activity in the Atherosclerosis Risk in Communities (ARIC) Study

BACKGROUND

Combination devices to monitor heart rate/rhythms and physical activity are becoming increasingly popular in research and clinical settings. The Zio XT Patch (iRhythm Technologies, San Francisco, CA, USA) is US Food and Drug Administration (FDA)-approved for monitoring heart rhythms, but the validity of its accelerometer for assessing physical activity is unknown.

OBJECTIVE

To validate the accelerometer in the Zio XT Patch for measuring physical activity against the widely-used ActiGraph GT3X.

METHODS

The Zio XT and ActiGraph wGT3X-BT (Actigraph, Pensacola, FL, USA) were worn simultaneously in two separately-funded ancillary studies to Visit 6 of the Atherosclerosis Risk in Communities (ARIC) Study (2016-2017). Zio XT was worn on the chest and ActiGraph was worn on the hip. Raw accelerometer data were summarized using mean absolute deviation (MAD) for six different epoch lengths (1-min, 5-min, 10-min, 30-min, 1-h, and 2-h). Participants who had ≥3 days of at least 10 h of valid data between 7 a.m-11 p.m were included. Agreement of epoch-level MAD between the two devices was evaluated using correlation and mean squared error (MSE).

RESULTS

Among 257 participants (average age: 78.5 ± 4.7 years; 59.1% female), there were strong correlations between MAD values from Zio XT and ActiGraph (average r: 1-min: 0.66, 5-min: 0.90, 10-min: 0.93, 30-min: 0.93, 1-h: 0.89, 2-h: 0.82), with relatively low error values (Average MSE × 106: 1-min: 349.37 g, 5-min: 86.25 g, 10-min: 56.80 g, 30-min: 45.46 g, 1-h: 52.56 g, 2-h: 54.58 g).

CONCLUSIONS

These findings suggest that Zio XT accelerometry is valid for measuring duration, frequency, and intensity of physical activity within time epochs of 5-min to 2-h.

Incentivised physical activity intervention promoting daily steps among university employees in the workplace through a team-based competition

Introduction

The benefits of walking on health and well-being is well established and regarded as the most accessible form of physical activity (PA) that most individuals can incorporate into their lives. Despite the benefits, the impact of a competitive walking intervention combined with a prize incentive in the workplace is yet to be established. The aim of this intervention was to promote PA among university employees through teams-based competition with a prize incentive targeted towards the recommended 10,000 steps per day.

Methods

A total of 49 employees participated and formed eight departmental teams ranging from Senior Admin management, Educational & Social work, Nursing & Midwifery, Sport & Exercise, Health Sciences, Admin Assistant, Library, and IT to compete in a walking intervention. Each team was handed an ActiGraph wGT3X-BT from Monday to Friday to record their walking steps. Steps. Post intervention participants completed an open-ended survey to provide their views about the intervention.

Results

The ActiGraph findings determined that steps increased by 4,799 per day from daily baseline of 5,959 to 10,758 throughout this intervention. The themes from qualitative data showed that the prize incentive and competitive nature of this intervention has motivated staff to walk more, changed their behaviour, enjoyed the team-based competition, and improved perceived productivity in the workplace.

Discussion and conclusion

This intervention increased employees' daily steps by 4,799 and met the 10,000 steps guideline. The 'Health Sciences' team recorded the highest steps 531,342 followed by the 'Education and Social Work' accumulating 498,045 steps throughout this intervention. This intervention with prize incentive demonstrated a positive impact on employees personal and work-based outcomes as well as contributed to the workplace PA, health, and wellbeing literature, and more specifically, to the scarce research focused on university settings.

Trajectories of physical activity from mid to older age in women: 21 years of data from the Australian Longitudinal Study on Women's Health

BACKGROUND

Women's physical activity varies across the adult lifespan. However, changes in physical activity among mid-aged women are not well understood. We analysed 21 years of data from women born in 1946-51 to identify: (1) trajectories of physical activity in the transition from mid- to old-age and (2) determinants of different physical activity trajectories.

METHODS

Data were from the 1946-51 cohort of the Australian Longitudinal Study on Women's Health (N = 10,371). Surveys were mailed at three-year intervals from 1998 (age 47-52) to 2019 (age 68-73) to collect data on physical activity, sociodemographic factors (country of birth, area of residence, educational attainment, marital status, income management, paid work hours, living with children age < 18, providing care), health indicators (menopause status, BMI, physical and mental health, chronic conditions), and health behaviours (smoking, alcohol status). Group-based trajectory modelling was used to identify trajectories of physical activity. Multinomial logistic regression models were used to examine the determinants of physical activity trajectories.

RESULTS

Five trajectories were identified: Low-stable (13.3% of participants), Moderate-stable (50.4%), Moderate-increasing (22.2%), High-declining (7.7%), and High-stable (6.6%). Sociodemographic characteristics (area of residence, education, income management, living with children, and providing care) were determinants of physical activity trajectories, but the strongest factors were BMI, physical and mental health. Women who were overweight/obese and had poor physical and mental health were less likely to be in the High-stable group than in any other group. Changes in these variables (increasing BMI, and declining physical and mental health) and in marital status (getting married) were positively associated with being in trajectories other than the High-stable group.

CONCLUSIONS

Although most women maintained physical activity at or above current guidelines, very low physical activity levels in the Low-stable group, and declining levels in the High-declining group are concerning. The data suggest that physical activity promotion strategies could be targeted to these groups, which are characterised by socioeconomic disadvantage, high (and increasing) BMI, and poor (and worsening) physical and mental health. Removing barriers to physical activity in these women, and increasing opportunities for activity, may reduce chronic disease risk in older age.