Accuracy of Posture Allocation Algorithms for Thigh- and Waist-Worn Accelerometers

A cardiac-rehab behaviour intervention to reduce sedentary time in coronary artery disease patients: the SIT LESS randomized controlled trial

BACKGROUND

High sedentary times (ST) is highly prevalent in patients with coronary artery disease (CAD), highlighting the need for behavioural change interventions that effectively reduce ST. We examined the immediate and medium-term effect of the SIT LESS intervention on changes in ST among CAD patients enrolled in cardiac rehabilitation (CR).

METHODS

CAD patients participating in CR at 2 regional hospitals were included in this randomized controlled trial (1:1, stratified for gender and hospital). The control group received CR, whereas SIT LESS participants additionally received a 12-week hybrid behaviour change intervention. The primary outcome was the change in accelerometer-derived ST from pre-CR to post-CR and 3 months post-CR. Secondary outcomes included changes in ST and physical activity characteristics, subjective outcomes, and cardiovascular risk factors. A baseline constrained linear mixed-model was used.

RESULTS

Participants (23% female; SIT LESS: n = 108, control: n = 104) were 63 ± 10 years. Greater ST reductions were found for SIT LESS compared to control post-CR (-1.7 (95% confidence interval (CI): -2.0; -1.4) versus - 1.1 (95% CI: -1.4; -0.8) h/day, pinteraction=0.009), but not at 3 months post-CR (pinteraction=0.61). Besides, larger light-intensity physical activity (LIPA) increases were found for SIT LESS compared to control post-CR (+ 1.4 (95% CI: +1.2; +1.6) versus + 1.0 (95% CI: +0.8; +1.3) h/day, pinteraction=0.020). Changes in other secondary outcomes did not differ among groups.

CONCLUSION

SIT LESS transiently reduced ST and increased LIPA, but group differences were no longer significant 3 months post-CR. These findings highlight the challenge to induce sustainable behaviour changes in CAD patients without any continued support.

TRIAL REGISTRATION

Netherlands Trial Register: NL9263. Registration Date: 24 February 2021.

Cross-sectional associations between temporal patterns and composition of upright and stepping events with physical function in midlife: Insights from the 1970 British Cohort Study

INTRODUCTION

Age-related decline in physical functioning has significant implications for health in later life but declines begin earlier in midlife. Physical activity (PA) volume is associated with physical function, but the importance of the pattern in which PA is accumulated is unclear. This study investigates associations between patterns of PA accumulation, including the composition, variation, and temporal distribution of upright and stepping events, with physical function in midlife.

METHODS

Participants (n = 4378) from the 1970 British Cohort Study wore an activPAL3 accelerometer on the thigh for 7 consecutive days. Exposure measures included a suite of metrics describing the frequency, duration, and composition of upright events, as well as the duration and volume (total steps) of stepping events. In addition, patterns of accumulation of upright and sedentary events were examined including how fragmented/transient they were (upright-to-sedentary transition probability [USTP]) and their burstiness (the tendency for events to be clustered together followed by longer interevent times). Physical function outcomes included grip strength (GS), balance, and SF-36 physical functioning subscale (SF-36pf). Cross-sectional analyses included multivariable linear regression models to assess associations, adjusting for covariates including overall PA volume (mean daily step count).

RESULTS

Higher upright event burstiness was associated with higher GS, and higher USTP was associated with lower GS. Duration and step volume of stepping events were positively associated with SF-36pf in females. Step-weighted cadence was positively associated with SF-36pf and balance. Contradictory findings were also present (e.g., more transient stepping events were associated with better GS) particularly for GS in males. Inconsistencies between sexes were observed across some associations.

CONCLUSION

Our study reveals that diverse patterns of PA accumulation exhibit distinct associations with various measures of physical function in midlife, irrespective of the overall volume. Contradictory findings and inconsistency between sexes warrant further investigation. Patterns of PA accumulation, in addition to volume, should be considered in future PA research. Longitudinal studies are required to determine whether a given volume of activity accumulated in different patterns, impacts associations between PA and health outcomes.

Temporal relationships in the movement behaviour of adolescents: Testing and methodological considerations of the ActivityStat hypothesis

The study aimed to investigate the ActivityStat hypothesis by examining the presence and the timeframe of the temporal relationships among physical activity (PA) levels and stationary time (ST) in adolescents. A secondary analysis was performed on data involving 356 adolescents in Dunedin, New Zealand. Participants wore a waist-worn accelerometer for several consecutive days to assess PA levels [i.e. light PA (LPA), and moderate-to-vigorous PA (MVPA)] and ST. Bayesian continuous-time structural equation modelling (CT-SEM) was used to examine the relationship between the behaviours over time and the timeframe during which these relationships occur. Increases in LPA, MVPA, and ST were positively associated with their later behaviours until 2.5, 1.7, and 2 days later, respectively. A cross-behavioural reciprocal and negative relationship between LPA and ST was demonstrated 0.4 days later. A positive relationship between ST and MVPA was observed until about 0.4 days later. This is the first study to investigate the ActivityStat hypothesis using Bayesian CT-SEM in adolescents, examining the multivariate relationships among different behaviours and the associated timeframes. To conclude, evidence of activity synergy was suggested for the within-behavioural relationships, while behavioural compensation was noted for ST. Thus, the findings provide some support for the ActivityStat hypothesis in adolescents.

Measurement of Sedentary Behavior-The Outcomes of the Angle for Posture Estimation (APE) Method

Hip-worn accelerometers are commonly used to assess habitual physical activity, but their accuracy in precisely measuring sedentary behavior (SB) is generally considered low. The angle for postural estimation (APE) method has shown promising accuracy in SB measurement. This method relies on the constant nature of Earth's gravity and the assumption that walking posture is typically upright. This study investigated how cardiorespiratory fitness (CRF) and body mass index (BMI) are related to APE output. A total of 3475 participants with adequate accelerometer wear time were categorized into three groups according to CRF or BMI. Participants in low CRF and high BMI groups spent more time in reclining and lying postures (APE ≥ 30°) and less time in sitting and standing postures (APE < 30°) than the other groups. Furthermore, the strongest partial Spearman correlation with CRF (r = 0.284) and BMI (r = -0.320) was observed for APE values typical for standing. The findings underscore the utility of the APE method in studying associations between SB and health outcomes. Importantly, this study emphasizes the necessity of reserving the term "sedentary behavior" for studies wherein the classification of SB is based on both intensity and posture.

Unravelling upright events: a descriptive epidemiology of the behavioural composition and temporal distribution of upright events in participants from the 1970 British Cohort Study

BACKGROUND

Continued proliferation of accelerometers in physical activity research has opened new avenues for understanding activity behaviours beyond simple aggregate measures of frequency and duration. This study explores the standing and stepping composition, and the temporal distribution, of upright events, and investigates their associations with sociodemographic and health factors.

METHODS

Participants from the 1970 British Cohort Study wore activPAL3 accelerometers for seven days. Event-based analysis was used to extract a time series of upright, standing, and stepping events. Derived metrics included daily number of upright and stepping events, total upright and stepping time, the burstiness of upright events and burstiness of sedentary events (burstiness refers to the pattern of how physical activity and sedentary behaviour are distributed throughout a given time period), within-event stepping proportion, within-event step count, and stepping cadence. Generalized linear regression models, adjusted for total step count, were employed to explore associations between derived metrics and sociodemographic and health-related factors.

RESULTS

A total of 4527 participants, provided 30992 valid days (≥ 10 h of waking wear) and 1.64 million upright events. Upright event composition and temporal distribution varied across a range of sociodemographic and health-related factors. Females had more upright events than males (4.39 [3.41,5.38] n), spent more time upright, and exhibited burstier patterns of upright events (0.05 [0.04,0.05] Bn). Individuals with higher BMI had fewer upright events and a lower daily step count, but their temporal distribution of upright events was less bursty (overweight -0.02 [-0.02,-0.01] Bn; obese -0.03 [-0.04,-0.02] Bn), and upright events had a higher step count. People in active occupations were upright for longer, displayed burstier patterns of upright events (standing 0.04 [0.03,0.05] Bn; physical work 0.05 [0.04,0.05] Bn; heavy manual 0.06 [0.04,0.07] Bn), with more variable durations and shorter, slower paced stepping events compared with sedentary occupations.

CONCLUSIONS

This study has revealed novel phenotypes of standing and sitting that go beyond simple aggregate measures of total steps, step event duration or time between events. People with the same volume of stepping and frequency of gaps between upright events can accumulate their steps in very different ways. These differences and associations with population sub-groups, which persisted after adjustment for total stepping volume, may have important relations with functional and health outcomes. The findings lay the groundwork for future studies to investigate how different sitting and standing phenotypes can add to our understanding of the relationship between physical activity and health.

Concurrent Validity of Four Activity Monitors in Older Adults

Sedentary behaviour (SB) and physical activity (PA) have been shown to be independent modulators of healthy ageing. We thus investigated the impact of activity monitor placement on the accuracy of detecting SB and PA in older adults, as well as a novel random forest algorithm trained on data from older persons. Four monitor types (ActiGraph wGT3X-BT, ActivPAL3c VT, GENEActiv Original, and DynaPort MM+) were simultaneously worn on five anatomical sites during ten different activities by a sample of twenty older adults (70.0 (12.0) years; 10 women). The results indicated that collecting metabolic equivalent (MET) data for 60 s provided the most representative results, minimising variability. In addition, thigh-worn monitors, including ActivPAL, Random Forest, and Sedentary Sphere-Thigh, exhibited superior performance in classifying SB, with balanced accuracies ≥ 94.2%. Other monitors, such as ActiGraph, DynaPort MM+, and GENEActiv Sedentary Sphere-Wrist, demonstrated lower performance. ActivPAL and GENEActiv Random Forest outperformed other monitors in participant-specific balanced accuracies for SB classification. Only thigh-worn monitors achieved acceptable overall balanced accuracies (≥80.0%) for SB, standing, and medium-to-vigorous PA classifications. In conclusion, it is advisable to position accelerometers on the thigh, collect MET data for ≥60 s, and ideally utilise population-specific trained algorithms.

Monitoring mobility in older adults using a Global Positioning System (GPS) smartwatch and accelerometer: A validation study

There is growing interest in identifying valid and reliable methods for detecting early mobility limitations in aging populations. A multi-sensor approach that combines accelerometry with Global Positioning System (GPS) devices could provide valuable insights into late-life mobility decline; however, this innovative approach requires more investigation. We conducted a series of two experiments with 25 older participants (66.2±8.5 years) to determine the validity of a GPS enabled smartwatch (TicWatch S2 and Pro 3 Ultra GPS) and separate accelerometer (ActiGraph wGT3X-BT) to collect movement, navigation and body posture data relevant to mobility. In experiment 1, participants wore the TicWatchS2 and ActiGraph simultaneously on the wrist for 3 days. In experiment 2, participants wore the TicWatch Pro 2 Ultra GPS on the wrist and ActiGraph on the thigh for 3 days. In both experiments participants also carried a Qstarz data logger for trips outside the home. The TicWatch Pro 3 Ultra GPS performed better than the S2 model and was similar to the Qstarz in all tested trip-related measures, and it was able to estimate both passive and active trip modes. Both models showed similar results to the gold standard Qstarz in life-space-related measures. The TicWatch S2 demonstrated good to excellent overall agreement with the ActiGraph algorithms for the time spent in sedentary and non-sedentary activities, with 84% and 87% agreement rates, respectively. Under controlled conditions, the TicWatch Pro 3 Ultra GPS consistently measured step count in line with the participants' self-reported data, with a bias of 0.4 steps. The thigh-worn ActiGraph algorithm accurately classified sitting and lying postures (97%) and standing postures (90%). Our multi-sensor approach to monitoring mobility has the potential to capture both accelerometer-derived movement data and trip/life-space data only available through GPS. In this study, we found that the TicWatch models were valid devices for capturing GPS and raw accelerometer data, making them useful tools for assessing real-life mobility in older adults.

Determining minimum number of valid days for accurate estimation of sedentary behaviour and awake-time movement behaviours using the ActivPAL3 in nursing home residents

INTRODUCTION

Scarce evidence is available about the minimum number of valid days wearing the activPAL3 to obtain a precise estimate of sedentary behaviour (SB) and awake-time movement behaviours (ATMB) in nursing home (NH) residents. The study aimed to determine the minimum number of valid days required for accurately estimate SB and ATMB using the activPAL3 device in NH residents. It also investigated how the starting point of a day (the 24-h period) impacted reliability.

METHODS

Participants wore an activPAL3 for 7 consecutive days. The data was classified in two-time blocks (00:00 Ante Meridiem (AM)-00:00 AM midnight vs 12:00 Post Meridiam (PM) -12:00 PM midday) and the sample was stratified into two groups according to their capacity to stand and walk, to examine if timing of sampling or physical functioning affected minimum wear time. SB, ATMB, sociodemographic, and health-related variables were collected. Sensitivity of the time-blocks were tested through the dispersion frequencies and differences between blocks through Kolmogorov-Smirnov test for normality; parametric variables through two-related means T-test and Wilcoxon test for non-parametric data. Reliability was assessed with the Cronbach's Alpha and the intra-class correlation coefficient (ICC), using a one-factor model estimating the reliability for each measurement day loading in the same latent factor.

RESULTS

Ninety-five NH residents (81.1% women; age = 85.8 ± 7.2 years) were included. The midnight block had higher reliability, sensitivity and no statistically significant differences between days were found. At least three consecutive days of monitoring were necessary to achieve a reliability of ICC ≥ 0.8 for those NH residents able to stand and walk and six days for those unable.

CONCLUSIONS

NH residents who are able to stand and walk require a minimum of three consecutive days wearing the device, while those who are unable require at least six days due to their highly homogenous daily routines and sensitivity to PA events. Regardless of the activPAL3 recording start time, data processing should reference the midnight time block.

Association of physical activity with endothelial dysfunction among adults with and without chronic kidney disease: The Maastricht Study

BACKGROUND AND AIMS

Physical activity (PA) constitutes an established protective factor while sedentary behavior (SB) an emerging independent risk factor for cardiovascular diseases. This study evaluated the association of PA and SB with endothelial dysfunction (ED) depending on kidney function status.

METHODS

Cross-sectional data from the prospective, population-based Maastricht Study were used. PA and SB were measured using the ActivPAL3 accelerometer 24h/day for eight consecutive days. ED was evaluated by plasma levels of soluble vascular cell adhesion protein-1, intercellular adhesion molecule-1, E-selectin and von Willebrand factor, which were combined into an ED score with higher values depicting higher ED.

RESULTS

Overall, 2,668 participants, 323 with chronic kidney disease, were included. In normal kidney function individuals, the ED score presented a significant negative association with total, lower-intensity and moderate-to-vigorous PA duration and a positive association with total sedentary time, sedentary breaks and sedentary bout duration. In participants with chronic kidney disease, a significant negative association of ED score with total [β: -4.42, 95% confidence intervals (95% CI): -7.98; -0.87] and lower-intensity (β: -7.08, 95% CI: -13.41; -0.74) PA duration, as well as a positive association of ED score with sedentary bout duration (β: 43.72, 95% CI: 9.85; 77.59) were noted. The strength of associations did not significantly differ across kidney function subgroups (p > 0.05).

CONCLUSIONS

This analysis showed that PA duration is inversely associated with ED both among patients with normal kidney function and chronic kidney disease. In chronic kidney disease, longer sedentary bouts were associated with greater endothelial dysfunction.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

A multicomponent intervention to reduce daily sitting time in office workers: the SMART Work & Life three-arm cluster RCT

Background

Office workers spend 70-85% of their time at work sitting. High levels of sitting have been linked to poor physiological and psychological health. Evidence shows the need for fully powered randomised controlled trials, with long-term follow-up, to test the effectiveness of interventions to reduce sitting time.

Objective

Our objective was to test the clinical effectiveness and cost-effectiveness of the SMART Work & Life intervention, delivered with and without a height-adjustable workstation, compared with usual practice at 12-month follow-up.

Design

A three-arm cluster randomised controlled trial.

Setting

Councils in England.

Participants

Office workers.

Intervention

SMART Work & Life is a multicomponent intervention that includes behaviour change strategies, delivered by workplace champions. Clusters were randomised to (1) the SMART Work & Life intervention, (2) the SMART Work & Life intervention with a height-adjustable workstation (i.e. SMART Work & Life plus desk) or (3) a control group (i.e. usual practice). Outcome measures were assessed at baseline and at 3 and 12 months.

Main outcome measures

The primary outcome was device-assessed daily sitting time compared with usual practice at 12 months. Secondary outcomes included sitting, standing, stepping time, physical activity, adiposity, blood pressure, biochemical measures, musculoskeletal issues, psychosocial variables, work-related health, diet and sleep. Cost-effectiveness and process evaluation data were collected.

Results

A total of 78 clusters (756 participants) were randomised [control, 26 clusters (n = 267); SMART Work & Life only, 27 clusters (n = 249); SMART Work & Life plus desk, 25 clusters (n = 240)]. At 12 months, significant differences between groups were found in daily sitting time, with participants in the SMART Work & Life-only and SMART Work & Life plus desk arms sitting 22.2 minutes per day (97.5% confidence interval -38.8 to -5.7 minutes/day; p = 0.003) and 63.7 minutes per day (97.5% confidence interval -80.0 to -47.4 minutes/day; p < 0.001), respectively, less than the control group. Participants in the SMART Work & Life plus desk arm sat 41.7 minutes per day (95% confidence interval -56.3 to -27.0 minutes/day; p < 0.001) less than participants in the SMART Work & Life-only arm. Sitting time was largely replaced by standing time, and changes in daily behaviour were driven by changes during work hours on workdays. Behaviour changes observed at 12 months were similar to 3 months. At 12 months, small improvements were seen for stress, well-being and vigour in both intervention groups, and for pain in the lower extremity and social norms in the SMART Work & Life plus desk group. Results from the process evaluation supported these findings, with participants reporting feeling more energised, alert, focused and productive. The process evaluation also showed that participants viewed the intervention positively; however, the extent of engagement varied across clusters. The average cost of SMART Work & Life only and SMART Work & Life plus desk was £80.59 and £228.31 per participant, respectively. Within trial, SMART Work & Life only had an incremental cost-effectiveness ratio of £12,091 per quality-adjusted life-year, with SMART Work & Life plus desk being dominated. Over a lifetime, SMART Work & Life only and SMART Work & Life plus desk had incremental cost-effectiveness ratios of £4985 and £13,378 per quality-adjusted life-year, respectively.

Limitations

The study was carried out in one sector, limiting generalisability.

Conclusions

The SMART Work & Life intervention, provided with and without a height-adjustable workstation, was successful in changing sitting time.

Future work

There is a need for longer-term follow-up, as well as follow-up within different organisations.

Trial registration

Current Controlled Trials ISRCTN11618007.

Physical Activity Assessed by Wrist and Thigh Worn Accelerometry and Associations with Cardiometabolic Health

Physical activity is increasingly being captured by accelerometers worn on different body locations. The aim of this study was to examine the associations between physical activity volume (average acceleration), intensity (intensity gradient) and cardiometabolic health when assessed by a thigh-worn and wrist-worn accelerometer. A sample of 659 office workers wore an Axivity AX3 on the non-dominant wrist and an activPAL3 micro on the right thigh concurrently for 24 h a day for 8 days. An average acceleration (proxy for physical activity volume) and intensity gradient (intensity distribution) were calculated from both devices using the open-source raw accelerometer processing software GGIR. Clustered cardiometabolic risk (CMR) was calculated using markers of cardiometabolic health, including waist circumference, triglycerides, HDL-cholesterol, mean arterial pressure and fasting glucose. Linear regression analysis assessed the associations between physical activity volume and intensity gradient with cardiometabolic health. Physical activity volume derived from the thigh-worn activPAL and the wrist-worn Axivity were beneficially associated with CMR and the majority of individual health markers, but associations only remained significant after adjusting for physical activity intensity in the thigh-worn activPAL. Physical activity intensity was associated with CMR score and individual health markers when derived from the wrist-worn Axivity, and these associations were independent of volume. Associations between cardiometabolic health and physical activity volume were similarly captured by the thigh-worn activPAL and the wrist-worn Axivity. However, only the wrist-worn Axivity captured aspects of the intensity distribution associated with cardiometabolic health. This may relate to the reduced range of accelerations detected by the thigh-worn activPAL.

Beyond the Clinic: Maximum Free-Living Stepping as a Potential Measure of Physical Performance

Measures of physical performance captured within a clinical setting are commonly used as a surrogate for underlying health or disease risk within an individual. By measuring physical behaviour within a free-living setting, we may be able to better quantify physical performance. In our study, we outline an approach to measure maximum free-living step count using a body-worn sensor as an indicator of physical performance. We then use this approach to characterise the maximum step count over a range of window durations within a population of older adults to identify a preferred duration over which to measure the maximum step count. We found that while almost all individuals (97%) undertook at least one instance of continuous stepping longer than two minutes, a sizeable minority of individuals (31%) had no periods of continuous stepping longer than six minutes. We suggest that the maximum step count measured over a six-minute period may be too sensitive to the adults' lack of opportunity to undertake prolonged periods of stepping, and a two-minute window could provide a more representative measure of physical performance.

Accelerometer-Measured Physical Activity Data Sets (Global Physical Activity Data Set Catalogue) That Include Markers of Cardiometabolic Health: Systematic Scoping Review

BACKGROUND

Cardiovascular disease accounts for 17.9 million deaths globally each year. Many research study data sets have been collected to answer questions regarding the relationship between cardiometabolic health and accelerometer-measured physical activity. This scoping review aimed to map the available data sets that have collected accelerometer-measured physical activity and cardiometabolic health markers. These data were then used to inform the development of a publicly available resource, the Global Physical Activity Data set (GPAD) catalogue.

OBJECTIVE

This review aimed to systematically identify data sets that have measured physical activity using accelerometers and cardiometabolic health markers using either an observational or interventional study design.

METHODS

Databases, trial registries, and gray literature (inception until February 2021; updated search from February 2021 to September 2022) were systematically searched to identify studies that analyzed data sets of physical activity and cardiometabolic health outcomes. To be eligible for inclusion, data sets must have measured physical activity using an accelerometric device in adults aged ≥18 years; a sample size >400 participants (unless recruited participants in a low- and middle-income country where a sample size threshold was reduced to 100); used an observational, longitudinal, or trial-based study design; and collected at least 1 cardiometabolic health marker (unless only body mass was measured). Two reviewers screened the search results to identify eligible studies, and from these, the unique names of each data set were recorded, and characteristics about each data set were extracted from several sources.

RESULTS

A total of 17,391 study reports were identified, and after screening, 319 were eligible, with 122 unique data sets in these study reports meeting the review inclusion criteria. Data sets were found in 49 countries across 5 continents, with the most developed in Europe (n=53) and the least in Africa and Oceania (n=4 and n=3, respectively). The most common accelerometric brand and device wear location was Actigraph and the waist, respectively. Height and body mass were the most frequently measured cardiometabolic health markers in the data sets (119/122, 97.5% data sets), followed by blood pressure (82/122, 67.2% data sets). The number of participants in the included data sets ranged from 103,712 to 120. Once the review processes had been completed, the GPAD catalogue was developed to house all the identified data sets.

CONCLUSIONS

This review identified and mapped the contents of data sets from around the world that have collected potentially harmonizable accelerometer-measured physical activity and cardiometabolic health markers. The GPAD catalogue is a web-based open-source resource developed from the results of this review, which aims to facilitate the harmonization of data sets to produce evidence that will reduce the burden of disease from physical inactivity.

Rapid Improvements in Physical Activity and Sedentary Behavior in Patients With Acute Myocardial Infarction Immediately Following Hospital Discharge

Background Little is known about changes in physical activity (PA) and sedentary behavior (SB) patterns in the acute phase of a myocardial infarction (MI). We objectively assessed PA and SB during hospitalization and the first week after discharge. Methods and Results Consecutively admitted patients hospitalized with an MI were approached to participate in this prospective cohort study. SB, light-intensity PA, and moderate-vigorous intensity PA were objectively assessed for 24 h/d during hospitalization and up to 7 days after discharge in 165 patients. Changes in PA and SB from the hospital to home phase were evaluated using mixed-model analyses, and outcomes were stratified for predefined subgroups based on patient characteristics. Patients (78% men) were aged 65±10 years and diagnosed with ST-segment-elevation MI (50%) or non-ST-segment-elevation MI (50%). Sedentary time was high during hospitalization (12.6 [95% CI, 11.8-13.7] h/d) but substantially decreased following transition to the home environment (-1.8 [95% CI, -2.4 to -1.3] h/d). Furthermore, the number of prolonged sedentary bouts (≥60 minutes) decreased between hospital and home (-1.6 [95% CI, -2.0 to -1.2] bouts/day). Light-intensity PA (1.1 [95% CI, 0.8-1.6] h/d) and moderate-vigorous intensity PA (0.2 [95% CI, 0.1-0.3] h/d) were low during hospitalization but significantly increased following transition to the home environment (light-intensity PA: 1.8 [95% CI, 1.4-2.3] h/d; moderate-vigorous intensity PA: 0.4 [95% CI, 0.3-0.5] h/d; both P<0.001). Improvements in PA and SB were similar across groups, except for patients who underwent coronary artery bypass grafting and who did not improve their PA patterns after discharge. Conclusions Patients with MI demonstrate high levels of SB and low PA volumes during hospitalization, which immediately improved following discharge at the patient's home environment. Registration URL: trialsearch.who.int/; Unique identifier: NTR7646.

Development and performance of a sleep estimation algorithm using a single accelerometer placed on the thigh: an evaluation against polysomnography

Accelerometers placed on the thigh provide accurate measures of daily physical activity types, postures and sedentary behaviours, over 24 h and across consecutive days. However, the ability to estimate sleep duration or quality from thigh-worn accelerometers is uncertain and has not been evaluated in comparison with the 'gold-standard' measurement of sleep polysomnography. This study aimed to develop an algorithm for sleep estimation using the raw data from a thigh-worn accelerometer and to evaluate it in comparison with polysomnography. The algorithm was developed and optimised on a dataset consisting of 23 single-night polysomnography recordings, collected in a laboratory, from 15 asymptomatic adults. This optimised algorithm was then applied to a separate evaluation dataset, in which, 71 adult males (mean [SD] age 57 [11] years, height 181 [6] cm, weight 82 [13] kg) wore ambulatory polysomnography equipment and a thigh-worn accelerometer, simultaneously, whilst sleeping at home. Compared with polysomnography, the algorithm had a sensitivity of 0.84 and a specificity of 0.55 when estimating sleep periods. Sleep intervals were underestimated by 21 min (130 min, Limits of Agreement Range [LoAR]). Total sleep time was underestimated by 32 min (233 min LoAR). Our results evaluate the performance of a new algorithm for estimating sleep and outline the limitations. Based on these results, we conclude that a single device can provide estimates of the sleep interval and total sleep time with sufficient accuracy for the measurement of daily physical activity, sedentary behaviour, and sleep, on a group level in free-living settings.

Effectiveness of an intervention to reduce sedentary behaviour as a personalised secondary prevention strategy for patients with coronary artery disease: main outcomes of the SIT LESS randomised clinical trial

BACKGROUND

A high sedentary time is associated with increased mortality risk. Previous studies indicate that replacement of sedentary time with light- and moderate-to-vigorous physical activity attenuates the risk for adverse outcomes and improves cardiovascular risk factors. Patients with cardiovascular disease are more sedentary compared to the general population, while daily time spent sedentary remains high following contemporary cardiac rehabilitation programmes. This clinical trial investigated the effectiveness of a sedentary behaviour intervention as a personalised secondary prevention strategy (SIT LESS) on changes in sedentary time among patients with coronary artery disease participating in cardiac rehabilitation.

METHODS

Patients were randomised to usual care (n = 104) or SIT LESS (n = 108). Both groups received a comprehensive 12-week centre-based cardiac rehabilitation programme with face-to-face consultations and supervised exercise sessions, whereas SIT LESS participants additionally received a 12-week, nurse-delivered, hybrid behaviour change intervention in combination with a pocket-worn activity tracker connected to a smartphone application to continuously monitor sedentary time. Primary outcome was the change in device-based sedentary time between pre- to post-rehabilitation. Changes in sedentary time characteristics (prevalence of prolonged sedentary bouts and proportion of patients with sedentary time ≥ 9.5 h/day); time spent in light-intensity and moderate-to-vigorous physical activity; step count; quality of life; competencies for self-management; and cardiovascular risk score were assessed as secondary outcomes.

RESULTS

Patients (77% male) were 63 ± 10 years and primarily diagnosed with myocardial infarction (78%). Sedentary time decreased in SIT LESS (- 1.6 [- 2.1 to - 1.1] hours/day) and controls (- 1.2 [ ─1.7 to - 0.8]), but between group differences did not reach statistical significance (─0.4 [─1.0 to 0.3]) hours/day). The post-rehabilitation proportion of patients with a sedentary time above the upper limit of normal (≥ 9.5 h/day) was significantly lower in SIT LESS versus controls (48% versus 72%, baseline-adjusted odds-ratio 0.4 (0.2-0.8)). No differences were observed in the other predefined secondary outcomes.

CONCLUSIONS

Among patients with coronary artery disease participating in cardiac rehabilitation, SIT LESS did not induce significantly greater reductions in sedentary time compared to controls, but delivery was feasible and a reduced odds of a sedentary time ≥ 9.5 h/day was observed.

TRIAL REGISTRATION

Netherlands Trial Register: NL9263. Outcomes of the SIT LESS trial: changes in device-based sedentary time from pre-to post-cardiac rehabilitation (control group) and cardiac rehabilitation + SIT LESS (intervention group). SIT LESS reduced the odds of patients having a sedentary time >9.5 hours/day (upper limit of normal), although the absolute decrease in sedentary time did not significantly differ from controls. SIT LESS appears to be feasible, acceptable and potentially beneficial, but a larger cluster randomised trial is warranted to provide a more accurate estimate of its effects on sedentary time and clinical outcomes. CR: cardiac rehabilitation.

Sedentary behaviour, but not moderate-to-vigorous physical activity, is associated with respiratory responses to acute psychological stress

BACKGROUND

Acute psychological stress induces respiratory responses, and stress-induced respiratory changes can be used to non-invasively reflect metabolic regulation. Respiratory and cardiovascular responses to stress are both driven by sympathetic mechanisms. Higher volumes of sedentary behaviour and lower volumes of physical activity are associated with elevated sympathetic tone and larger cardiovascular responses to stress. The aim of this study was to test whether these associations translate to measures of respiratory stress reactivity.

METHODS

Daily hours of sedentary behaviour (thigh-mounted activPAL) and moderate-to-vigorous physical activity (MVPA; wrist-mounted ActiGraph) were assessed across seven days. Breath-by-breath respiratory (e.g., breathing frequency [BF], end-tidal carbon dioxide partial pressure [PetCO₂], carbon dioxide output [V̇CO₂] and respiratory exchange ratio [RER]) responses to an 8-min Paced Auditory Serial Addition Test were then measured using a Cortex MetaLyzer3B.

RESULTS

Healthy participants (N = 61, mean age ± SD = 25.7 ± 8.9 years) recorded high volumes of sedentary behaviour (9.96 ± 1.48 h/day) and MVPA (1.70 ± 0.71 h/day). In adjusted models (with the inclusion of sedentary behaviour, MVPA, and other a priori selected covariates) hours of daily sedentary behaviour were associated with baseline to stress changes in BF (Β = 0.695, 95% CI = 0.281 - 1.109, p = .014), V_T (Β = -0.042, 95% CI = -0.058 - -0.026, p = .014), PetCO₂ (Β = -0.537, 95% CI = -0.829 - -0.245, p = .014), V̇CO₂ (Β = -0.008, 95% CI = -0.014 - -0.003, p = .030), and RER (Β = -0.013, 95% CI = -0.021 - -0.005, p = .022). Daily hours of MVPA were not linked with respiratory responses to stress.

DISCUSSION

Sedentary behaviour, but not MVPA, is associated with respiratory stress reactivity. Future work should untangle the underlying mechanisms of these findings and explore the consequences for cardiometabolic disease.

Stepping towards More Intuitive Physical Activity Metrics with Wrist-Worn Accelerometry: Validity of an Open-Source Step-Count Algorithm

Stepping-based targets such as the number of steps per day provide an intuitive and commonly used method of prescribing and self-monitoring physical activity goals. Physical activity surveillance is increasingly being obtained from wrist-worn accelerometers. However, the ability to derive stepping-based metrics from this wear location still lacks validation and open-source methods. This study aimed to assess the concurrent validity of two versions (1. original and 2. optimized) of the Verisense step-count algorithm at estimating step-counts from wrist-worn accelerometry, compared with steps from the thigh-worn activPAL as the comparator. Participants (n = 713), across three datasets, had >24 h continuous concurrent accelerometry wear on the non-dominant wrist and thigh. Compared with activPAL, total daily steps were overestimated by 913 ± 141 (mean bias ± 95% limits of agreement) and 742 ± 150 steps/day with Verisense algorithms 1 and 2, respectively, but moderate-to-vigorous physical activity (MVPA) steps were underestimated by 2207 ± 145 and 1204 ± 103 steps/day in Verisense algorithms 1 and 2, respectively. In summary, the optimized Verisense algorithm was more accurate in detecting total and MVPA steps. Findings highlight the importance of assessing algorithm performance beyond total step count, as not all steps are equal. The optimized Verisense open-source algorithm presents acceptable accuracy for derivation of stepping-based metrics from wrist-worn accelerometry.

A multicomponent structured health behaviour intervention to improve physical activity in long-distance HGV drivers: the SHIFT cluster RCT

Background

Long-distance heavy goods vehicle drivers are exposed to a multitude of risk factors associated with their occupation. The working environment of heavy goods vehicle drivers provides limited opportunities for a healthy lifestyle, and, consequently, heavy goods vehicle drivers exhibit higher than nationally representative rates of obesity and obesity-related comorbidities, and are underserved in terms of health promotion initiatives.

Objective

The aim of this trial was to test the effectiveness and cost-effectiveness of the multicomponent Structured Health Intervention For Truckers (SHIFT) programme, compared with usual care, at both 6 months and 16–18 months.

Design

A two-arm cluster randomised controlled trial, including a cost-effectiveness analysis and process evaluation.

Setting

Transport depots throughout the Midlands region of the UK.

Participants

Heavy goods vehicle drivers.

Intervention

The 6-month SHIFT programme included a group-based interactive 6-hour education session, health coach support and equipment provision [including a Fitbit® (Fitbit Inc., San Francisco, CA, US) and resistance bands/balls to facilitate a ‘cab workout’]. Clusters were randomised following baseline measurements to either the SHIFT arm or the control arm.

Main outcome measures

Outcome measures were assessed at baseline, with follow-up assessments occurring at both 6 months and 16–18 months. The primary outcome was device-measured physical activity, expressed as mean steps per day, at 6-month follow-up. Secondary outcomes included device-measured sitting, standing, stepping, physical activity and sleep time (on any day, workdays and non-workdays), along with adiposity, biochemical measures, diet, blood pressure, psychophysiological reactivity, cognitive function, functional fitness, mental well-being, musculoskeletal symptoms and work-related psychosocial variables. Cost-effectiveness and process evaluation data were collected.

Results

A total of 382 participants (mean ± standard deviation age: 48.4 ± 9.4 years; mean ± standard deviation body mass index: 30.4 kg/m2 ± 5.1 kg/m2; 99% male) were recruited across 25 clusters. Participants were randomised (at the cluster level) to either the SHIFT arm (12 clusters, n = 183) or the control arm (13 clusters, n = 199). At 6 months, 209 (54.7%) participants provided primary outcome data. Significant differences in mean daily steps were found between arms, with participants in the SHIFT arm accumulating 1008 more steps per day than participants in the control arm (95% confidence interval 145 to 1871 steps; p = 0.022), which was largely driven by the maintenance of physical activity levels in the SHIFT arm and a decline in physical activity levels in the control arm. Favourable differences at 6 months were also seen in the SHIFT arm, relative to the control arm, in time spent sitting, standing and stepping, and time in moderate or vigorous activity. No differences between arms were observed at 16–18 months’ follow-up. No differences were observed between arms in the other secondary outcomes at either follow-up (i.e. 6 months and 16–18 months). The process evaluation demonstrated that the intervention was well received by participants and that the intervention reportedly had a positive impact on their health behaviours. The average total cost of delivering the SHIFT programme was £369.57 per driver, and resulting quality-adjusted life-years were similar across trial arms (SHIFT arm: 1.22, 95% confidence interval 1.19 to 1.25; control arm: 1.25, 95% confidence interval 1.22 to 1.27).

Limitations

A higher (31.4%) than anticipated loss to follow-up was experienced at 6 months, with fewer (54.7%) participants providing valid primary outcome data at 6 months. The COVID-19 pandemic presents a major confounding factor, which limits our ability to draw firm conclusions regarding the sustainability of the SHIFT programme.

Conclusion

The SHIFT programme had a degree of success in positively impacting physical activity levels and reducing sitting time in heavy goods vehicle drivers at 6-months; however, these differences were not maintained at 16–18 months.

Future work

Further work involving stakeholder engagement is needed to refine the content of the programme, based on current findings, followed by the translation of the SHIFT programme into a scalable driver training resource.

Trial registration

This trial is registered as ISRCTN10483894.

Funding

This project was funded by the National Institute for Health and Care Research (NIHR) Public Health Research programme and will be published in full in Public Health Research; Vol. 10, No. 12. See the NIHR Journals Library website for further project information.

Physical Activity Behaviors of a Middle-Age South African Cohort as Determined by Integrated Hip and Thigh Accelerometry

PURPOSE

Descriptive studies of objectively measured physical activity behaviors in African populations are rare. We developed a method of combining hip and thigh accelerometery signals to quantify and describe physical behaviors in middle-age South African men and women.

METHODS

We integrated signals from two triaxial accelerometers worn simultaneously during free-living, in a subsample of the Middle-age Soweto Cohort ( n = 794; mean (SD) age, 53.7 (6.3) yr). Acceleration time series from the accelerometers were combined and movement-related acceleration was derived using Euclidean Norm Minus One (in milligrams), to determine total movement volume (mean Euclidean Norm Minus One) and nonmovement time (<28 m g ), light-intensity physical activity (LPA; 28-85 m g ), and moderate- to vigorous-intensity physical activity (MVPA; >85 m g ); thigh pitch angle and a sleep diary were used to divide nonmovement time (in minutes per day) into sleep, awake sitting/lying, and standing. Sociodemographic factors were self-reported, and weight and height were measured.

RESULTS

Mean (SD) wear time was 128 (48) h. Movement volume was 15.0 (6.5) m g for men and 12.2 (3.4) m g for women. Men spent more time in MVPA and sitting/lying, whereas women spent more time standing. Age was inversely associated with movement volume, MVPA, and LPA. When compared with their normal-weight counterparts, men who were overweight or obese spent less time in MVPA, whereas women who were overweight or obese spent less time in LPA and more time sitting/lying. Socioeconomic status was inversely associated with total movement volume, MVPA, and time spent sleeping, and positively associated with time spent sitting/lying, in both men and women.

CONCLUSIONS

Integrating signals from hip and thigh accelerometers enables characterization of physical behaviors that can be applied in an African population.

A Deep Learning Approach to Classify Sitting and Sleep History from Raw Accelerometry Data during Simulated Driving

Prolonged sitting and inadequate sleep can impact driving performance. Therefore, objective knowledge of a driver's recent sitting and sleep history could help reduce safety risks. This study aimed to apply deep learning to raw accelerometry data collected during a simulated driving task to classify recent sitting and sleep history. Participants (n = 84, Mean ± SD age = 23.5 ± 4.8, 49% Female) completed a seven-day laboratory study. Raw accelerometry data were collected from a thigh-worn accelerometer during a 20-min simulated drive (8:10 h and 17:30 h each day). Two convolutional neural networks (CNNs; ResNet-18 and DixonNet) were trained to classify accelerometry data into four classes (sitting or breaking up sitting and 9-h or 5-h sleep). Accuracy was determined using five-fold cross-validation. ResNet-18 produced higher accuracy scores: 88.6 ± 1.3% for activity (compared to 77.2 ± 2.6% from DixonNet) and 88.6 ± 1.1% for sleep history (compared to 75.2 ± 2.6% from DixonNet). Class activation mapping revealed distinct patterns of movement and postural changes between classes. Findings demonstrate the suitability of CNNs in classifying sitting and sleep history using thigh-worn accelerometer data collected during a simulated drive. This approach has implications for the identification of drivers at risk of fatigue-related impairment.

A-REST (Activity to Reduce Excessive Sitting Time): A Feasibility Trial to Reduce Prolonged Sitting in Police Staff

The aim of this study was to evaluate the acceptability and feasibility of a theory-derived sedentary workplace intervention for police office staff. Twenty-four staff participated in an 8-week intervention (single arm, pre-post design) incorporating an education session, team competition with quick response (QR) codes, team trophy, weekly leaderboard newsletters, a self-monitoring phone app, and electronic prompt tools. The intervention supported participants to reduce and break up their sitting time with three minutes of incidental movement every 30 min at work. Feasibility and acceptability were assessed using mixed methods via the RE-AIM QuEST and PRECIS-2 frameworks. The intervention was highly pragmatic in terms of eligibility, organisation, adherence, outcome, and analysis. It was slightly less pragmatic on recruitment and setting. Delivery and follow-up were more explanatory. Reach and adoption indicators demonstrated feasibility among police staff, across a range of departments, who were demographically similar to participants in previous office-based multi-component interventions. The intervention was delivered mostly as planned with minor deviations from protocol (implementation fidelity). Participants perceived the intervention components as highly acceptable. Results showed improvements in workplace sitting and standing, as well as small improvements in weight and positive affect. Evaluation of the intervention in a fully powered randomised controlled trial to assess behaviour and health outcomes is recommended.

Physical behaviors and their association with type 2 diabetes mellitus risk markers in urban South African middle-aged adults: an isotemporal substitutionapproach

INTRODUCTION

To examine the associations between physical behaviors and type 2 diabetes mellitus (T2DM) risk markers in middle-aged South African men and women.

RESEARCH DESIGN AND METHODS

This cross-sectional study included middle-aged men (n=403; age: median (IQR), 53.0 (47.8-58.8) years) and women (n=324; 53.4 (49.1-58.1) years) from Soweto, South Africa. Total movement volume (average movement in milli-g) and time (minutes/day) spent in different physical behaviors, including awake sitting/lying, standing, light intensity physical activity (LPA) and moderate-to-vigorous intensity physical activity (MVPA), were determined by combining the signals from two triaxial accelerometers worn simultaneously on the hip and thigh. All participants completed an oral glucose tolerance test, from which indicators of diabetes risk were derived. Associations between physical behaviors and T2DM risk were adjusted for sociodemographic factors and body composition.

RESULTS

Total movement volume was inversely associated with measures of fasting and 2-hour glucose and directly associated with insulin sensitivity, basal insulin clearance, and beta-cell function, but these associations were not independent of fat mass, except for basal insulin clearance in women. In men, replacing 30 min of sitting/lying, standing or LPA with the same amount of MVPA time was associated with 1.2-1.4 mmol/L lower fasting glucose and 12.3-13.4 mgl2/mUmin higher insulin sensitivity. In women, substituting sitting/lying with the same amount of standing time or LPA was associated with 0.5-0.8 mmol/L lower fasting glucose. Substituting 30 min sitting/lying with the same amount of standing time was also associated with 3.2 mgl2/mUmin higher insulin sensitivity, and substituting 30 min of sitting/lying, standing or LPA with the same amount of MVPA time was associated with 0.25-0.29 ng/mIU higher basal insulin clearance in women.

CONCLUSION

MVPA is important in reducing T2DM risk in men and women, but LPA appears to be important in women only. Longitudinal and intervention studies warranted to provide more specific PA recommendations.

Sedentary behaviour is associated with heightened cardiovascular, inflammatory and cortisol reactivity to acute psychological stress

BACKGROUND

Sedentary behaviour is a risk factor for cardiovascular disease (CVD), but the underlying mechanisms remain unclear. Exaggerated psychobiological responses to acute psychological stress increase CVD risk. Sedentary behaviour is associated with characteristics that can predict large psychobiological stress response patterns (e.g., elevated resting blood pressure and systemic inflammation), but it is currently unknown whether sedentary behaviour and stress reactivity are directly linked. The aim of this study was to examine associations between device-assessed sedentary behaviour and measures of stress reactivity.

METHODS

Sixty-one healthy adults wore an activPAL (thigh) and ActiGraph (wrist) for seven days to measure habitual levels of sedentary behaviour (mean ± SD = 9.96 ± 1.48 h/day) and moderate-to-vigorous physical activity (mean ± SD = 101.82 ± 42.92 min/day). Participants then underwent stress reactivity testing, where beat-to-beat cardiovascular (e.g., blood pressure, total peripheral resistance), inflammatory (plasma interleukin-6, leukocytes) and salivary cortisol measurements were taken in response to an 8-minute socially evaluative Paced Auditory Serial Addition Test.

RESULTS

Higher volumes of daily sedentary behaviour were associated with larger stress responses for diastolic blood pressure (Β=1.264, 95%CI=0.537-1.990, p = .005), total peripheral resistance (Β=40.563, 95%CI=19.310-61.812, p < .001), interleukin-6 (Β=0.219, 95%CI=0.109-0.329, p < .001) and cortisol (Β=1.844, 95%CI=1.139-2.549, p < .001). These findings emerged independent of a priori determined covariates, including daily levels of moderate-to-vigorous physical activity and adiposity.

DISCUSSION

Exaggerated stress reactivity is characteristic of high sedentary behaviour and could be a novel mechanism linking sedentary behaviour with CVD. Future work should examine the impact of reducing sedentary behaviour on measures of stress reactivity, as this may have clinical relevance for preventing CVD.

Sedentary Behaviour Intervention as a Personalised Secondary Prevention Strategy (SIT LESS) for patients with coronary artery disease participating in cardiac rehabilitation: rationale and design of the SIT LESS randomised clinical trial

Patients with coronary artery disease (CAD) are more sedentary compared with the general population, but contemporary cardiac rehabilitation (CR) programmes do not specifically target sedentary behaviour (SB). We developed a 12-week, hybrid (centre-based+home-based) Sedentary behaviour IntervenTion as a personaLisEd Secondary prevention Strategy (SIT LESS). The SIT LESS programme is tailored to the needs of patients with CAD, using evidence-based behavioural change methods and an activity tracker connected to an online dashboard to enable self-monitoring and remote coaching. Following the intervention mapping principles, we first identified determinants of SB from literature to adapt theory-based methods and practical applications to target SB and then evaluated the intervention in advisory board meetings with patients and nurse specialists. This resulted in four core components of SIT LESS: (1) patient education, (2) goal setting, (3) motivational interviewing with coping planning, and (4) (tele)monitoring using a pocket-worn activity tracker connected to a smartphone application and providing vibrotactile feedback after prolonged sedentary bouts. We hypothesise that adding SIT LESS to contemporary CR will reduce SB in patients with CAD to a greater extent compared with usual care. Therefore, 212 patients with CAD will be recruited from two Dutch hospitals and randomised to CR (control) or CR+SIT LESS (intervention). Patients will be assessed prior to, immediately after and 3 months after CR. The primary comparison relates to the pre-CR versus post-CR difference in SB (objectively assessed in min/day) between the control and intervention groups. Secondary outcomes include between-group differences in SB characteristics (eg, number of sedentary bouts); change in SB 3 months after CR; changes in light-intensity and moderate-to-vigorous-intensity physical activity; quality of life; and patients' competencies for self-management. Outcomes of the SIT LESS randomised clinical trial will provide novel insight into the effectiveness of a structured, hybrid and personalised behaviour change intervention to attenuate SB in patients with CAD participating in CR. Trial registration number NL9263.

Validity of the ActivPAL monitor to distinguish postures: A systematic review

BACKGROUND

Posture has been recently integrated into activity guidelines, advising people to limit their sedentary time and break up sedentary postures with standing/stepping as much as possible. The thigh-worn activPAL is a frequently used objective measure of posture, but its validity has only been investigated by individual studies and has not been systematically reviewed.

RESEARCH QUESTION

Can the activPAL accurately characterize different postures?

METHODS

A rigorous systematic review protocol was conducted, including multiple study screeners and determiners of study quality. To be included, validation studies had to examine the accuracy of an activPAL posture outcome relative to a criterion measure (e.g., direct observation) in adults (>18 years). Citations were not restricted to language or date of publication. Sources were searched on May 16, 2021 and included Scopus, EMBASE, MEDLINE, CINAHL, and Academic Search Premier. The study was pre-registered in Prospero (ID# CRD42021248240). Study quality was determined using a modified Hagströmer Bowles checklist. The results are presented narratively.

RESULTS

Twenty-four studies (18 semi-structured laboratory arms, 8 uncontrolled protocol arms; 476 participants) met the inclusion criteria. Some studies (5/24) incorporated dual-monitor (trunk: 4/5; shin: 1/5) configurations. While heterogenous statistical procedures were implemented, most studies (n = 22/24) demonstrated a high validity (e.g., percent agreement >90%, no fixed bias, etc.) of the activPAL to measure sedentary and/or upright postures across semi-structured (17/18 arms) and uncontrolled study designs (7/8 arms). Specific experimental protocol factors (i.e., seat height, fidgeting, non-direct observation criterion comparator) likely explain the divergent reports that observed valid versus invalid findings. The study quality was 11.3 (standard deviation: 2.3) out of 19.

CONCLUSION

Despite heterogeneous methodological and statistical approaches, the included studies generally provide supporting evidence that the activPAL can accurately distinguish between sedentary and standing postures. Multiple activPAL monitor configurations (e.g., thigh and torso) are needed to better characterize sitting versus lying postures.

The Flares of Low back pain with Activity Research Study (FLAReS): study protocol for a case-crossover study nested within a cohort study

BACKGROUND

Although it is generally accepted that physical activity and flares of low back pain (LBP) are related, evidence for the directionality of this association is mixed. The Flares of Low back pain with Activity Research Study (FLAReS) takes a novel approach to distinguish the short-term effects of specific physical activities on LBP flares from the cumulative effects of such activities, by conducting a longitudinal case-crossover study nested within a cohort study. The first aim is to estimate the short-term effects (≤ 24 h) of specific physical activities on LBP flares among Veterans in primary care in the Veterans Affairs healthcare system. The second aim is to estimate the cumulative effects of specific activities on LBP-related functional limitations at 1-year follow-up.

METHODS

Up to 550 adults of working age (18-65 years) seen for LBP in primary care complete up to 36 "Scheduled" surveys over 1-year follow-up, and also complete unscheduled "Flare Window" surveys after the onset of new flares. Each survey asks about current flares and other factors associated with LBP. Surveys also inquire about activity exposures over the 24 h, and 2 h, prior to the time of survey completion (during non-flare periods) or prior to the time of flare onset (during flares). Other questions evaluate the number, intensity, duration, and/or other characteristics of activity exposures. Other exposures include factors related to mood, lifestyle, exercise, concurrent treatments, and injuries. Some participants wear actigraphy devices for weeks 1-4 of the study. The first aim will examine associations between 10 specific activity categories and participant-reported flares over 1-year follow-up. The second aim will examine associations between the frequency of exposure to 10 activity categories over weeks 1-4 of follow-up and long-term functional limitations at 12 months. All analyses will use a biopsychosocial framework accounting for potential confounders and effect modifiers.

DISCUSSION

FLAReS will provide empirically derived estimates of both the short-term and cumulative effects of specific physical activities for Veterans with LBP, helping to better understand the role of physical activities in those with LBP.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04828330 , registered April 2, 2021.

Measuring sedentary behavior using waist- and thigh-worn accelerometers and inclinometers – are the results comparable?

Background:

Objective sensor-based quantification of sedentary behavior is an important tool for planning and evaluating interventions for excessive sedentary behavior in patients with musculoskeletal diseases. Although waist-worn accelerometers are the standard for physical activity (PA) assessment, only thigh-worn inclinometers can clearly distinguish sedentary behavior from any light PA or standing activity.

Methods:

In this study, 53 adults (ages 20–85 years) wore two ActiGraph wGT3X-BT monitors, each containing an inclinometer and accelerometer (set for acquisition of slow movements in all three planes), attached to the right waist and thigh for a period of about 4 days. Both monitors recorded total sedentary time and continuous sedentary 10-min bouts by synchronous accelerometry and inclinometry. Differences and correlations between methods and wearing positions were evaluated against participant age, body mass index (BMI), and number of steps taken. Thigh-worn inclinometry was used as reference.

Results:

Data from thigh-worn inclinometry and waist-worn accelerometry were highly correlated for total sedentary time [rho = 0.888; intraclass correlation coefficient (ICC) = 0.937] and time in sedentary bouts (rho = 0.818; ICC = 0.848). Nevertheless, accelerometry at the waist underestimated sedentary time by ≈17% (p < 0.001) and time in sedentary bouts by ≈54% (p < 0.001). A satisfactory concordance thus could be demonstrated only for total sedentary time, based on the Bland–Altmann method (≈96% of data within the limits of agreement). The differences between waist-worn accelerometry and thigh-worn inclinometry did not correlate with age but did correlate with BMI and PA for both sedentary behavior parameters (r ⩾ 0.240, p ⩽ 0.043).

Conclusion:

A waist-worn accelerometer can be used to determine total sedentary time under free-living conditions with sufficient accuracy if the correct settings are chosen. Further investigations are necessary to investigate why short sedentary bouts cannot be reliably assessed.

Trial registration:

DRKS00024060 (German Clinical Trials Register)

High Levels of Sedentary Time in Patients with COVID-19 after Hospitalisation

Many patients with COVID-19 experience severe and even fatal disease. Survivors may have long-term health consequences, but data on physical activity and sedentary behaviour are scarce. Therefore, we objectively assessed physical activity (PA) patterns among post-hospitalised patients with COVID-19 and explored associations with patient characteristics, disease severity and cardiac dysfunction. We objectively assessed PA, sedentary behaviour and sleep duration for 24 h/day during 8 days at 3-6 months after COVID-19 hospitalisation. PA and sedentary time were compared across pre-defined subgroups based on patient and disease characteristics, cardiac biomarker release during hospitalisation, abnormal transthoracic echocardiogram at 3-6 months post-hospitalisation and persistence of symptoms post-discharge. PA and sedentary behaviour were assessed in 37 patients (60 ± 10 years old; 78% male). Patients spent 4.2 [3.2; 5.3] h/day light-intensity PA and 1.0 [0.8; 1.4] h/day moderate-to-vigorous intensity PA. Time spent sitting was 9.8 [8.7; 11.2] h/day, which was accumulated in 6 [5; 7] prolonged sitting bouts (≥30 min) and 41 [32; 48] short sitting bouts (<30 min). No differences in PA and sedentary behaviour were found across subgroups, but sleep duration was higher in patients with versus without persistent symptoms (9.1 vs. 8.3 h/day, p = 0.02). Taken together, high levels of sedentary time are common at 3-6 months after COVID-19 hospitalisation, whilst PA and sedentary behaviour are not impacted by patient or disease characteristics.

Free-Living Standing Activity as Assessed by Seismic Accelerometers and Cognitive Function in Community-Dwelling Older Adults: The MIND Trial

BACKGROUND

Few older adults are able to achieve recommended levels of moderate-vigorous physical activity despite known cognitive benefits. Alternatively, less intense activities such as standing can be easily integrated into daily life. No existing study has examined the impact of free-living standing activity during daily life as measured by a device on cognition in older adults. Our purpose was to examine the association between free-living standing activity and cognitive function in cognitively healthy older adults.

METHOD

Participants were 98 adults aged 65 years or older from the ongoing MIND trial (NCT02817074) without diagnoses or symptoms of mild cognitive impairment or dementia. Linear regression analyses tested cross-sectional associations between standing activity (duration and intensity from the MoveMonitor+ accelerometer/gyroscope) and cognition (4 cognitive domains constructed from 12 cognitive performance tests).

RESULTS

Participants were on average 69.7 years old (SD = 3.7), 69.4% women, and 73.5% had a college degree or higher. Higher mean intensity of standing activity was significantly associated with higher levels of perceptual speed when adjusting for age, gender, and education level. Each log unit increase in standing activity intensity was associated with 0.72 units higher of perceptual speed (p = .023). When we additionally adjusted for cognitive activities and moderate-vigorous physical activity, and then also for body mass index, depressive symptoms, prescription medication use, and device wear time, the positive association remained.

CONCLUSIONS

These findings should be further explored in longitudinal analyses and interventions for cognition that incorporate small changes to free-living activity in addition to promoting moderate-vigorous physical activity.

Impact of prehabilitation on objectively measured physical activity levels in elective surgery patients: a systematic review

OBJECTIVE

To systematically review the impact of prehabilitation on objectively measured physical activity (PA) levels in elective surgery patients.

DATA SOURCES

Articles published in Web of Science Core Collections, PubMed, Embase (Ovid), CINAHL (EBSCOHost), PsycInfo (EBSCOHost) and CENTRAL through August 2020.

STUDY SELECTION

Studies that met the following criteria: (1) written in English, (2) quantitatively described the effect(s) of a PA intervention among elective surgery patients prior to surgery and (3) used and reported objective measures of PA in the study.

DATA EXTRACTION AND SYNTHESIS

Participant characteristics, intervention details, PA measurement, and clinical and health-related outcomes were extracted. Risk of bias was assessed following the revised Cochrane risk of bias tool. Meta-analysis was not possible due to heterogeneity, therefore narrative synthesis was used.

RESULTS

6533 unique articles were identified in the search; 21 articles (based on 15 trials) were included in the review. There was little evidence to suggest that prehabilitation is associated with increases in objectively measured PA, but this may be due to insufficient statistical power as most (n=8) trials included in the review were small feasibility/pilot studies. Where studies tested associations between objectively measured PA during the intervention period and health-related outcomes, significant beneficial associations were reported. Limitations in the evidence base precluded any assessment via meta-regression of the association between objectively measured PA and clinical or health-related outcomes.

CONCLUSIONS

Additional large-scale studies are needed, with clear and consistent reporting of objective measures including accelerometry variables and outcome variables, to improve our understanding of the impact of changes in PA prior to surgery on surgical and health-related outcomes.

PROSPERO REGISTRATION NUMBER

CRD42019151475.

Associations of Sedentary Time with Heart Rate and Heart Rate Variability in Adults: A Systematic Review and Meta-Analysis of Observational Studies

PURPOSE

To evaluate if sedentary time (ST) is associated with heart rate (HR) and variability (HRV) in adults.

METHODS

We systematically searched PubMed and Google Scholar through June 2020. Inclusion criteria were observational design, humans, adults, English language, ST as the exposure, resting HR/HRV as the outcome, and (meta-analysis only) availability of the quantitative association with variability. After qualitative synthesis, meta-analysis used inverse variance heterogeneity models to estimate pooled associations.

RESULTS

Thirteen and eight articles met the criteria for the systematic review and meta-analysis, respectively. All studies were cross-sectional and few used gold standard ST or HRV assessment methodology. The qualitative synthesis suggested no associations between ST and HR/HRV. The meta-analysis found a significant association between ST and HR (β = 0.24 bpm per hour ST; CI: 0.10, 0.37) that was stronger in males (β = 0.36 bpm per hour ST; CI: 0.19, 0.53). Pooled associations between ST and HRV indices were non-significant (p > 0.05). Substantial heterogeneity was detected.

CONCLUSIONS

The limited available evidence suggests an unfavorable but not clinically meaningful association between ST and HR, but no association with HRV. Future longitudinal studies assessing ST with thigh-based monitoring and HRV with electrocardiogram are needed.

Modelling the Reallocation of Time Spent Sitting into Physical Activity: Isotemporal Substitution vs. Compositional Isotemporal Substitution

Isotemporal substitution modelling (ISM) and compositional isotemporal modelling (CISM) are statistical approaches used in epidemiology to model the associations of replacing time in one physical behaviour with time in another. This study’s aim was to use both ISM and CISM to examine and compare associations of reallocating 60 min of sitting into standing or stepping with markers of cardiometabolic health. Cross-sectional data collected during three randomised control trials (RCTs) were utilised. All participants (n = 1554) were identified as being at high risk of developing type 2 diabetes. Reallocating 60 min from sitting to standing and to stepping was associated with a lower BMI, waist circumference, and triglycerides and higher high-density lipoprotein cholesterol using both ISM and CISM (p < 0.05). The direction and magnitude of significant associations were consistent across methods. No associations were observed for hemoglobin A1c, total cholesterol, or low-density lipoprotein cholesterol for either method. Results of both ISM and CISM were broadly similar, allowing for the interpretation of previous research, and should enable future research in order to make informed methodological, data-driven decisions.

Device-assessed total and prolonged sitting time: associations with anxiety, depression, and health-related quality of life in adults

OBJECTIVE

Assessment of sitting has been challenging and nuances in the length of sitting are often missed.

METHODS

The present study assessed total, short and prolonged sitting time, and number of breaks from sitting, and their association with anxiety, depression, and health-related quality of life (HRQoL). Adults (M=59.1 years) in three studies (n=1,574) wore the activPAL accelerometer (thigh) to obtain a measure of sitting, and the Actigraph accelerometer (hip) for estimating moderate-to-vigorous physical activity (MVPA). Anxiety and depression were assessed using the Hospital Anxiety and Depression Scale, and HRQoL using the EQ-5D-5L (for health state and utility scores). Generalised linear modelling tested associations.

RESULTS

Total and prolonged sitting were associated with higher depression [total: β = 0.132 (0.010, 0.254); prolonged: β = 0.178 (0.053, 0.304)] and worse HRQoL health state scores [(total: β = -0.985 (-1.471, -0.499); prolonged: β = -0.834 (-1.301, -0.367)] and utility scores [(total: β = -0.008 (-0.012, -0.003); prolonged: β = -0.008 (-0.012, -0.004)], after controlling for covariates. MVPA was associated with better HRQoL health state and utility scores [health state: β =0.554 (0.187, 0.922); utility: β = 0.001 (0.001, 0.002)]. Total and prolonged sitting were associated with a 14% increased odds of being in the borderline/abnormal category for depression. No interactions were observed between MVPA status (active vs. inactive) and total or prolonged sitting. Anxiety was unrelated to any sitting variable.

CONCLUSION

Device-based measures of both total and prolonged sitting time were associated with depression and health-related quality of life, but not anxiety.

A randomised-controlled feasibility study of the REgulate your SItting Time (RESIT) intervention for reducing sitting time in individuals with type 2 diabetes: study protocol

Background

People with type 2 diabetes mellitus (T2DM) generally spend a large amount of time sitting. This increases their risk of cardiovascular disease, premature mortality, diabetes-related complications and mental health problems. There is a paucity of research that has evaluated interventions aimed at reducing and breaking up sitting in people with T2DM. The primary aim of this study is to assess the feasibility of delivering and evaluating a tailored intervention to reduce and break up sitting in ambulatory adults with T2DM.

Methods

This is a mixed-methods randomised controlled feasibility trial. Participants (n=70) with T2DM aged 18-85 years who sit ≥7 h/day and are able to ambulate independently will be randomly allocated to receive the REgulate your SItting Time (RESIT) intervention or usual care (control group) for 24 weeks. RESIT is a person-focused intervention that delivers a standardised set of behaviour change techniques to the participants, but the mode through which they are delivered can vary depending on the tools selected by each participant. The intervention includes an online education programme, health coach support, and a range of self-selected tools (smartphone apps, computer-prompt software, and wearable devices) that deliver behaviour change techniques such as self-monitoring of sitting and providing prompts to break up sitting. Measures will be taken at baseline, 12 and 24 weeks. Eligibility, recruitment, retention and data completion rates will be used to assess trial feasibility. Sitting, standing and stepping will be measured using a thigh-worn activity monitor. Cardiometabolic health, physical function, psychological well-being, sleep and musculoskeletal symptoms will also be assessed. A process evaluation will be conducted including evaluation of intervention acceptability and fidelity.

Discussion

This study will identify the feasibility of delivering a tailored intervention to reduce and break up sitting in ambulatory adults with T2DM and evaluating it through a randomised controlled trial (RCT) design. The findings will inform a fully powered RCT to evaluate the effectiveness of the intervention.

Trial registration

ISRCTN, ISRCTN14832389; Registered 6 August 2020.

Concurrent and discriminant validity of ActiGraph waist and wrist cut-points to measure sedentary behaviour, activity level, and posture in office work

Background

Sedentary Behaviour (SB) gets an increasing attention from ergonomics and public health due to its associated detrimental health effects. A large number of studies record SB with ActiGraph counts-per-minute cut-points, but we still lack valid information about what the cut-points tell us about office work. This study therefore analysed the concurrent and discriminant validity of commonly used cut-points to measure SB, activity level, and posture.

Methods

Thirty office workers completed four office tasks at three workplaces (conventional chair, activity-promoting chair, and standing desk) while wearing two ActiGraphs (waist and wrist). Indirect calorimetry and prescribed posture served as reference criteria. Generalized Estimation Equations analysed workplace and task effects on the activity level and counts-per-minute, and kappa statistics and ROC curves analysed the cut-point validity.

Results

The activity-promoting chair (p < 0.001, ES ≥ 0.66) but not the standing desk (p = 1.0) increased the activity level, and both these workplaces increased the waist (p ≤ 0.003, ES ≥ 0.63) but not the wrist counts-per-minute (p = 0.74) compared to the conventional chair. The concurrent and discriminant validity was higher for activity level (kappa: 0.52–0.56 and 0.38–0.45, respectively) than for SB and posture (kappa ≤0.35 and ≤ 0.19, respectively). Furthermore, the discriminant validity for activity level was higher for task effects (kappa: 0.42–0.48) than for workplace effects (0.13–0.24).

Conclusions

ActiGraph counts-per-minute for waist and wrist placement were – independently of the chosen cut-point – a measure for activity level and not for SB or posture, and the cut-points performed better to detect task effects than workplace effects. Waist cut-points were most valid to measure the activity level in conventional seated office work, but they showed severe limitations for sit-stand desks. None of the placements was valid to detect the increased activity on the activity-promoting chair. Caution should therefore be paid when analysing the effect of workplace interventions on activity level with ActiGraph waist and wrist cut-points.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-021-10387-7.

The active workplace study: Protocol for a randomized controlled trial with sedentary workers

OBJECTIVES

Sedentary behavior is pervasive in the workplace and is harmful to health. Research on the effectiveness of comprehensive workplace interventions to reduce sedentary behavior and improve worker health and safety is crucial as sedentary jobs become more common.

METHODS

We developed a Total Worker Health intervention targeting sedentary behavior in call centers, and are evaluating intervention effectiveness in a randomized controlled trial. Four worksites will be randomly assigned to an intervention or control condition. The intervention condition includes the provision of active workstations along with programs and procedures at environmental, organizational, and individual levels. Control worksites will receive active workstations with no additional support, following common organizational practices.

RESULTS

Outcomes include objectively measured physical activity, biological markers of health, and self-report survey data at baseline, after the 6-month intervention or control period, and at a 12-month follow-up.

CONCLUSIONS

The aims of the study are to determine whether a Total Worker Health intervention has stronger impacts on workplace sedentary behavior, uninterrupted bouts of sitting, and worker health and safety compared to a usual practice control condition. The study will inform future workplace sedentary behavior intervention and dissemination research, along with organizational best practices for reducing sedentary behavior in the workplace.

Hip Positioning and Sitting Posture Recognition Based on Human Sitting Pressure Image

Bad sitting posture is harmful to human health. Intelligent sitting posture recognition algorithm can remind people to correct their sitting posture. In this paper, a sitting pressure image acquisition system was designed. With the system, we innovatively proposed a hip positioning algorithm based on hip templates. The average deviation of the algorithm for hip positioning is 1.306 pixels (the equivalent distance is 1.50 cm), and the proportion of the maximum positioning deviation less than three pixels is 94.1%. Statistics show that the algorithm works relatively well for different subjects. At the same time, the algorithm can not only effectively locate the hip position with a small rotation angle (0°–15°), but also has certain adaptability to the sitting posture with a medium rotation angle (15°–30°) or a large rotation angle (30°–45°). Using the hip positioning algorithm, the regional pressure values of the left hip, right hip and caudal vertebrae are effectively extracted as the features, and support vector machine (SVM) with polynomial kernel is used to classify the four types of sitting postures, with a classification accuracy of up to 89.6%.

Sustained Long-Term Efficacy of Motivational Counseling and Text Message Reminders on Daily Sitting Time in Patients With Rheumatoid Arthritis: Long-Term Follow-up of a Randomized, Parallel-Group Trial

OBJECTIVE

To evaluate the 18-month postintervention efficacy following a 4-month individually tailored behavioral intervention on daily sitting time in patients with rheumatoid arthritis (RA).

METHODS

In an observer-blinded randomized trial, 150 RA patients were included. During 4 months, the intervention group (n = 75) received 3 motivational counseling sessions and tailored text messages aimed at increasing light-intensity physical activity through reduction of sedentary behavior. The control group (n = 75) maintained their usual lifestyle. The primary outcome was change from baseline to 18 months postintervention in objectively measured daily sitting time (using ActivPAL). Secondary outcomes included changes in clinical patient-reported outcomes and cardiometabolic biomarkers. A mixed-effect repeated measures analysis of covariance model in the intent-to-treat population was applied.

RESULTS

At 22 months follow-up from baseline, 12 participants were lost to follow-up. Compared to baseline, sitting time in the intervention group decreased 1.10 hours/day, whereas it increased by 1.32 hours/day in the control group, a between-group difference of -2.43 hours/day (95% confidence interval [95% CI] -2.99, -1.86; P < 0.0001) favoring the intervention group. For most secondary outcomes, between-group differences favored the intervention: visual analog scale (VAS) pain -15.51 mm (95% CI -23.42, -7.60), VAS fatigue -12.30 mm (95% CI -20.71, -3.88), physical function -0.39 Health Assessment Questionnaire units (95% CI -0.53, -0.26), total cholesterol -0.86 mmoles/liter (95% CI -1.03, -0.68), triglycerides -0.26 mmoles/liter (95% CI -0.43, -0.09), and average glucose -1.15 mmoles/liter (95% CI -1.39, -0.91).

CONCLUSION

The 4-month postintervention results showed that patients in the intervention reduced their daily sitting time and improved patient-reported outcomes and total cholesterol levels compared to the control group. Eighteen months after intervention, patients in the intervention group were still significantly less sedentary than controls. Findings suggest that a behavioral approach is beneficial for promoting long-term physical activity and health in patients with RA.

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Biomechanical monitoring and machine learning for the detection of lying postures

BACKGROUND

Pressure mapping technology has been adapted to monitor over prolonged periods to evaluate pressure ulcer risk in individuals during extended lying postures. However, temporal pressure distribution signals are not currently used to identify posture or mobility. The present study was designed to examine the potential of an automated approach for the detection of a range of static lying postures and corresponding transitions between postures.

METHODS

Healthy subjects (n = 19) adopted a range of sagittal and lateral lying postures. Parameters reflecting both the interactions at the support surface and body movements were continuously monitored. Subsequently, the derivative of each signal was examined to identify transitions between postures. Three machine learning algorithms, namely Naïve-Bayes, k-Nearest Neighbors and Support Vector Machine classifiers, were assessed to predict a range of static postures, established with a training model (n = 9) and validated with new input from test data (n = 10).

FINDINGS

Results showed that the derivative signals provided a means to detect transitions between postures, with actimetry providing the most distinct signal perturbations. The accuracy in predicting the range of postures from new test data ranged between 82%-100%, 70%-98% and 69%-100% for Naïve-Bayes, k-Nearest Neighbors and Support Vector Machine classifiers, respectively.

INTERPRETATION

The present study demonstrated that detection of both static postures and their corresponding transitions was achieved by combining machine learning algorithms with robust parameters from two monitoring systems. This approach has the potential to provide reliable indicators of posture and mobility, to support personalised pressure ulcer prevention strategies.

activPAL and ActiGraph Assessed Sedentary Behavior and Cardiometabolic Health Markers

PURPOSE

To establish whether associations between sedentary behavior and cardiometabolic health differ when assessed by thigh-worn and waist-worn accelerometry.

METHODS

Participants were recruited from several areas in the United Kingdom. Sedentary behavior was assessed using the activPAL worn on the thigh and ActiGraph worn on the waist. Average total (TST), prolonged (bouts ≥30 min; PST) and breaks (BST) in sedentary time were calculated. Cardiometabolic health markers included: adiposity (body fat) and surrogate markers of adiposity ((waist circumference, body mass index [BMI]), lipids (total, low density lipoprotein, and high-density lipoprotein [HDL] cholesterol, triglycerides), blood pressure, and glucose (fasting, 2 h and glycated hemoglobin A1c). A clustered cardiometabolic risk score was calculated. Linear regression analysis examined the associations with cardiometabolic health.

RESULTS

There were 1457 participants (mean age [± standard deviation], 59.38 ± 11.85 yr; 51.7% male; mean BMI, 30.19 ± 5.59 kg·m) included in the analyses. ActivPAL and ActiGraph sedentary variables were moderately correlated (0.416-0.511, P < 0.01); however, all variables were significantly different from each other (P < 0.05). Consistency was observed across devices in the direction and magnitude of associations of TST and PST with adiposity, surrogate markers of adiposity, HDL, triglycerides, and cardiometabolic risk score and for BST with adiposity, surrogate markers of adiposity, and cardiometabolic risk. Differences across devices were observed in associations of TST and PST with diastolic blood pressure, for TST with 2-h glucose and for BST with HDL. No other associations were observed for any other health marker for either device.

CONCLUSIONS

Results suggest that associations with cardiometabolic health are largely comparable across the two common assessments of sedentary behavior but some small differences may exist for certain health markers.

Metabolic Effects of Breaking Prolonged Sitting With Standing or Light Walking in Older South Asians and White Europeans: A Randomized Acute Study

Background

Prolonged sitting is common in older adults and is associated with insulin resistance and poor cardiometabolic health. We investigate whether breaking prolonged sitting with regular short bouts of standing or light walking improves postprandial metabolism in older white European and South Asian adults and whether effects are modified by ethnic group.

Methods

Thirty South Asian (15 women) and 30 white European (14 women) older adults (aged 65–79 years) undertook three experimental conditions in random order. (a) Prolonged sitting: continuous sitting during an observation period if 7.5 hours consuming two standardized mixed meals. (b) Standing breaks: sitting interrupted with 5 minutes of standing every 30 minutes (accumulating 60 minutes of standing over the observation period). (c) Walking breaks: sitting interrupted with 5 minutes of self-paced light walking every 30 minutes (accumulating 60 minutes of walking). Blood samples (glucose, insulin, triglycerides) and blood pressure were sampled regularly throughout each condition.

Results

Compared with prolonged sitting, walking breaks lowered postprandial insulin by 16.3 mU/L, (95% CI: 19.7, 22.0) with greater reductions (p = .029) seen in South Asians (22.4 mU/L; 12.4, 32.4) than white Europeans (10.3 mU/L; 5.9, 14.7). Glucose (0.3 mmol/L; 0.1, 0.5) and blood pressure (4 mm Hg; 2, 6), but not triglycerides, were lower with walking breaks, with no ethnic differences. Standing breaks did not improve any outcome.

Conclusions

Breaking prolonged sitting with short bouts of light walking, but not standing, resulted in clinically meaningful improvements in markers of metabolic health in older adults, with South Asians gaining a greater reduction in postprandial insulin.

Trial Registration

NCT02453204

Machine Learning to Quantify Physical Activity in Children with Cerebral Palsy: Comparison of Group, Group-Personalized, and Fully-Personalized Activity Classification Models

Pattern recognition methodologies, such as those utilizing machine learning (ML) approaches, have the potential to improve the accuracy and versatility of accelerometer-based assessments of physical activity (PA). Children with cerebral palsy (CP) exhibit significant heterogeneity in relation to impairment and activity limitations; however, studies conducted to date have implemented “one-size fits all” group (G) models. Group-personalized (GP) models specific to the Gross Motor Function Classification (GMFCS) level and fully-personalized (FP) models trained on individual data may provide more accurate assessments of PA; however, these approaches have not been investigated in children with CP. In this study, 38 children classified at GMFCS I to III completed laboratory trials and a simulated free-living protocol while wearing an ActiGraph GT3X+ on the wrist, hip, and ankle. Activities were classified as sedentary, standing utilitarian movements, or walking. In the cross-validation, FP random forest classifiers (99.0–99.3%) exhibited a significantly higher accuracy than G (80.9–94.7%) and GP classifiers (78.7–94.1%), with the largest differential observed in children at GMFCS III. When evaluated under free-living conditions, all model types exhibited significant declines in accuracy, with FP models outperforming G and GP models in GMFCS levels I and II, but not III. Future studies should evaluate the comparative accuracy of personalized models trained on free-living accelerometer data.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

Sit–stand desks to reduce sedentary behaviour in 9- to 10-year-olds: the Stand Out in Class pilot cluster RCT

Background

Sedentary behaviour (sitting) is a highly prevalent negative health behaviour, with individuals of all ages exposed to environments that promote prolonged sitting. The school classroom represents an ideal setting for environmental change through the provision of sit–stand desks.

Objectives

The aim of this study was to undertake a pilot cluster randomised controlled trial of the introduction of sit–stand desks in primary school classrooms, to inform a definitive trial. Objectives included providing information on school and participant recruitment and retention, acceptability of the intervention, and outcome measures. A preliminary estimate of the intervention’s effectiveness on the proposed primary outcome (change in weekday sitting time) for inclusion in a definitive trial was calculated, along with a preliminary assessment of potential cost-effectiveness. A full process evaluation was also undertaken.

Design

A two-armed pilot cluster randomised controlled trial with economic and qualitative evaluations. Schools were randomised on a 1 : 1 basis to the intervention (n = 4) or control (n = 4) trial arms.

Setting

Primary schools in Bradford, West Yorkshire, UK.

Participants

Children in Year 5 (i.e. aged 9–10 years).

Intervention

Six sit–stand desks replaced three standard desks (sitting six children) in the intervention classrooms for 4.5 months. Teachers were encouraged to ensure that all pupils were exposed to the sit–stand desks for at least 1 hour per day, on average, using a rotation system. Schools assigned to the control arm continued with their usual practice.

Main outcome measures

Trial feasibility outcomes included school and participant recruitment and attrition, acceptability of the intervention, and acceptability of and compliance with the proposed outcome measures [including weekday sitting measured using activPAL™ (PAL Technologies Ltd, Glasgow, UK) accelerometers, physical activity, adiposity, blood pressure, cognitive function, musculoskeletal comfort, academic progress, engagement and behaviour].

Results

Thirty-three per cent of schools approached and 75% (n = 176) of eligible children took part. At the 7-month follow-up, retention rates were 100% for schools and 97% for children. Outcome measure completion rates ranged from 63% to 97%. A preliminary estimate of intervention effectiveness, from a weighted linear regression model (adjusting for baseline sitting time and wear time) revealed a mean difference in change in sitting of –30.6 minutes per day (95% confidence interval –56.42 to –4.84 minutes per day) between the intervention and control trial arms. The process evaluation revealed that the intervention, recruitment and evaluation procedures were acceptable to teachers and children, with the exception of minor issues around activPAL attachment. A preliminary within-trial economic analysis revealed no difference between intervention and control trial arms in health and education resource use or outcomes. Long-term modelling estimated an unadjusted incremental cost-effectiveness ratio of Stand Out in Class of £78,986 per quality-adjusted life-year gained.

Conclusion

This study has provided evidence of the acceptability and feasibility of the Stand Out in Class intervention and evaluation methods. Preliminary evidence suggests that the intervention may have a positive direction of effect on weekday sitting time, which warrants testing in a full cluster randomised controlled trial. Lessons learnt from this trial will inform the planning of a definitive trial.

Trial registration

Current Controlled Trials ISRCTN12915848.

Funding

This project was funded by the National Institute for Health Research (NIHR) Public Health Research programme and will be published in full in Public Health Research; Vol. 8, No. 8. See the NIHR Journals Library website for further project information.

Are all Sedentary Behaviors Equal? An Examination of Sedentary Behavior and Associations with Indicators of Disease Risk Factors in Women

Sedentary behavior increases risk for non-communicable diseases; associations may differ within different contexts (e.g., leisure time, occupational). This study examined associations between different types of sedentary behavior and disease risk factors in women, using objectively measured accelerometer-derived sedentary data. A validation study (n = 20 women) classified sedentary behavior into four categories: lying down; sitting (non-active); sitting (active); standing. A cross-sectional study (n = 348 women) examined associations between these classifications and disease risk factors (body composition, metabolic, inflammatory, blood lipid variables). Participants spent an average of 7 h 42 min per day in sedentary behavior; 58% of that time was classified as non-active sitting and 26% as active sitting. Non-active sitting showed significant (p ≤ 0.001) positive correlations with BMI (r = 0.244), body fat percent (r = 0.216), body mass (r = 0.236), fat mass (r = 0.241), leptin (r = 0.237), and negative correlations with HDL-cholesterol (r = −0.117, p = 0.031). Conversely, active sitting was significantly (p ≤ 0.001) negatively correlated with BMI (r = −0.300), body fat percent (r = −0.249), body mass (r = −0.305), fat mass (r = −0.320), leptin (r = −0.259), and positively correlated with HDL-cholesterol (r = 0.115, p = 0.035). In summary, sedentary behavior can be stratified using objectively measured accelerometer-derived activity data. Subsequently, different types of sedentary behaviors may differentially influence disease risk factors. Public health initiatives should account for sedentary classifications when developing sedentary behavior recommendations.

A comparison of self-reported and device measured sedentary behaviour in adults: a systematic review and meta-analysis

BACKGROUND

Sedentary behaviour (SB) is a risk factor for chronic disease and premature mortality. While many individual studies have examined the reliability and validity of various self-report measures for assessing SB, it is not clear, in general, how self-reported SB (e.g., questionnaires, logs, ecological momentary assessments (EMAs)) compares to device measures (e.g., accelerometers, inclinometers).

OBJECTIVE

The primary objective of this systematic review was to compare self-report versus device measures of SB in adults.

METHODS

Six bibliographic databases were searched to identify all studies which included a comparable self-report and device measure of SB in adults. Risk of bias within and across studies was assessed. Results were synthesized using meta-analyses.

RESULTS

The review included 185 unique studies. A total of 123 studies comprising 173 comparisons and data from 55,199 participants were used to examine general criterion validity. The average mean difference was -105.19 minutes/day (95% CI: -127.21, -83.17); self-report underestimated sedentary time by ~1.74 hours/day compared to device measures. Self-reported time spent sedentary at work was ~40 minutes higher than when assessed by devices. Single item measures performed more poorly than multi-item questionnaires, EMAs and logs/diaries. On average, when compared to inclinometers, multi-item questionnaires, EMAs and logs/diaries were not significantly different, but had substantial amount of variability (up to 6 hours/day within individual studies) with approximately half over-reporting and half under-reporting. A total of 54 studies provided an assessment of reliability of a self-report measure, on average the reliability was good (ICC = 0.66).

CONCLUSIONS

Evidence from this review suggests that single-item self-report measures generally underestimate sedentary time when compared to device measures. For accuracy, multi-item questionnaires, EMAs and logs/diaries with a shorter recall period should be encouraged above single item questions and longer recall periods if sedentary time is a primary outcome of study. Users should also be aware of the high degree of variability between and within tools. Studies should exert caution when comparing associations between different self-report and device measures with health outcomes.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO CRD42019118755.

The SED-GIH: A Single-Item Question for Assessment of Stationary Behavior-A Study of Concurrent and Convergent Validity

The unfavorable health consequences of prolonged time spent sedentary (stationary) make accurate assessment in the general population important. However, for many existing questionnaires, validity for identifying stationary time has not been shown or has shown low validity. This study aimed to assess the concurrent and convergent validity of the GIH stationary single-item question (SED-GIH). Data were obtained in 2013 and 2014 from two Swedish cohorts. A total of 711 men and women provided valid accelerometer data (Actigraph GT3X+) and were included for concurrent validity analyses. A total of 560 individuals answered three additional commonly used sedentary questions, and were included for convergent validity analysis. The SED-GIH displayed a significant correlation with total stationary time (r_s = 0.48) and time in prolonged stationary time (r_s = 0.44). The ROC analysis showed an AUC of 0.72 for identifying individuals with stationary time over 600 min/day. The SED-GIH correlated significantly with other previously used questions (r = 0.72-0.89). The SED-GIH single-item question showed a relatively high agreement with device-assessed stationary behavior and was able to identify individuals with high levels of stationary time. Thus, the SED-GIH may be used to assess total and prolonged stationary time. This has important implications, as simple assessment tools of this behavior are needed in public health practice and research.