Event-based analysis of free-living behaviour

The Effect of Using Anchored Wake Time to Derive 24-h Device Measured Circadian Physical Behavior Patterns

INTRODUCTION

Tailoring physical activity interventions to individual chronotypes and preferences by time of day could promote more effective and sustainable behavior change; however, our understanding of circadian physical behavior patterns is very limited.

OBJECTIVE

To characterize and compare 24-h physical behavior patterns expressed relative to clock time (the standard measurement of time-based on a 24-h day) versus wake-up time in a large British cohort age 46.

METHODS

Data were analyzed from 4979 participants in the age 46 sweep of the 1970 British Cohort Study who had valid activPAL accelerometer data across ≥4 days. Average steps and upright time (time standing plus time stepping) per 30-min interval were determined for weekdays and weekends, both in clock time and synchronized to individual wake-up times.

RESULTS

The mean weekday steps were 9588, and the mean weekend steps were 9354. The mean weekday upright time was 6.6 h, and the mean weekend upright time was 6.4 h. When synchronized to wake-up time, steps peaked 1 h after waking on weekdays and 2.5 h after waking on weekends. Upright time peaked immediately, in the first 30-min window, after waking on both weekdays and weekends.

CONCLUSIONS

Aligning accelerometer data to wake-up times revealed distinct peaks in stepping and upright times shortly after waking. Activity built up more gradually across clock time in the mornings, especially on weekends. Synchronizing against wake-up times highlighted the importance of circadian rhythms and personal schedules in understanding population 24-h physical behavior patterns, and this may have important implications for promoting more effective and sustainable behavior change.

Cross-sectional associations between patterns and composition of upright and stepping events with physical function: insights from The Maastricht Study

INTRODUCTION

Age-related declines in physical functioning have significant implications for health in later life. 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 accelerometer-determined daily PA patterns, including composition and temporal distribution (burstiness) of upright and stepping events, with physical function.

METHODS

Data was from participants who wore an activPAL3 accelerometer as part of The Maastricht Study. Exposures included a suite of metrics describing the composition and the temporal distribution (burstiness) of upright and sedentary behaviour. Physical function outcomes included the six-minute walk test (6MWT), timed chair-stand test (TCST), grip strength (GS), and SF-36 physical functioning sub-scale (SF-36pf). Multivariable linear regression models were used to assess associations, adjusting for covariates including overall PA volume (daily step count).

RESULTS

Participants(n = 6085) had 6 or 7 days of valid data. Upright and stepping event metrics were associated with physical function outcomes, even after adjusting PA volume. Higher sedentary burstiness was associated with better function (6MWT, TCST, and SF-36pf), as was duration and step volume of stepping events (6MWT, TCST, GS, and SF-36pf), step-weighted cadence (6MWT, TCST, and SF-36pf). Number of stepping events was associated with poorer function (6MWT, GS, and SF-36pf), as was upright event burstiness (SF-36pf). Associations varied according to sex.

CONCLUSION

Our study reveals that diverse patterns of physical activity accumulation exhibit distinct associations with various measures of physical function, irrespective of the overall volume. Subsequent investigations should employ longitudinal and experimental studies to examine how changing patterns of physical activity may affect physical function, and other health outcomes.

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.

Associations of between- and within-day patterns of physical activity accumulation with arterial stiffness and indices of microvascular health-Evidence from The Maastricht study

While physical activity (PA) is understood to promote vascular health, little is known about whether the daily and weekly patterns of PA accumulation associate with vascular health. Accelerometer-derived (activPAL3) 6- or 7-day stepping was analyzed for 6430 participants in The Maastricht Study (50.4% women; 22.4% Type 2 diabetes mellitus (T2DM)). Multivariable regression models examined associations between stepping metrics (average step count, and time spent slower and faster paced stepping) with arterial stiffness (measured as carotid-femoral pulse wave velocity (cfPWV)), and several indices of microvascular health (heat-induced skin hyperemia, retinal vessel reactivity and diameter), adjusting for confounders and moderators. PA pattern metrics were added to the regression models to identify associations with vascular health beyond that of stepping metrics. Analyses were stratified by T2DM status if an interaction effect was present. Average step count and time spent faster paced stepping was associated with better vascular health, and the association was stronger in those with compared to those without T2DM. In fully adjusted models a higher step count inter-daily stability was associated with a higher (worse) cfPWV in those without T2DM (std β = 0.04, p = 0.007) and retinal venular diameter in the whole cohort (std β = 0.07, p = 0.002). A higher within-day variability in faster paced stepping was associated with a lower (worse) heat-induced skin hyperemia in those with T2DM (std β = -0.31, p = 0.008). Above and beyond PA volume, the daily and weekly patterns in which PA was accumulated were additionally associated with improved macro- and microvascular health, which may have implications for the prevention of vascular disease.

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.

Does physical activity moderate the association between shorter leukocyte telomere length and incident coronary heart disease? Data from 54,180 UK Biobank participants

Telomere shortening is a biological aging hallmark. The effect of short telomere length may be targeted by increased physical activity to reduce the risk of multiple aging-related diseases, including coronary heart disease (CHD). The objective was to assess the moderation effect of accelerometer-based physical activity (aPA) on the association between shorter leukocyte telomere length (LTL) relatively in the population sample and incident CHD. Data were from the UK Biobank participants with well-calibrated accelerometer data for at least 6.5 days (n = 54,180). Relative mean LTL at baseline (5-6 years prior to aPA assessment) was measured in T/S ratio, using a multiplex quantitative polymerase chain reaction (qPCR) technology, by comparing the amount of the telomere amplification product (T) to that of a single-copy gene (S). aPA measures included total number of events (at least 10-s continued physical activity > 32 milligravities [mg]), total volume, mean duration, mean intensity, and peak intensity of all events. LTL, aPA measures, and their interactions were associated with incident CHD (mean follow-up 6.8 years) using Cox proportional hazards models adjusting for covariates. Longer LTL (relative to the sample distribution) was associated with reduced incidence of CHD (adjusted hazard ratio [aHR] = 0.94 per standard deviation [SD] increase in LTL, [95% CI, 0.90 to 0.99], P = .010). Incidence of CHD was reduced by higher total volume of aPA (aHR = 0.82 per SD increase in LTL, [95% CI, 0.71 to 0.95], P = .010) but increased by higher total number of events (aHR = 1.11 per SD increase in LTL, [95% CI, 1.02 to 1.21], P = .020) after controlling for other aPA measures and covariates. However, none of the interactions between LTL and aPA measures was statistically significant (P = .171).

The Analytical and Clinical Validity of the pfSTEP Digital Biomarker of the Susceptibility/Risk of Declining Physical Function in Community-Dwelling Older Adults

Measures of stepping volume and rate are common outputs from wearable devices, such as accelerometers. It has been proposed that biomedical technologies, including accelerometers and their algorithms, should undergo rigorous verification as well as analytical and clinical validation to demonstrate that they are fit for purpose. The aim of this study was to use the V3 framework to assess the analytical and clinical validity of a wrist-worn measurement system of stepping volume and rate, formed by the GENEActiv accelerometer and GENEAcount step counting algorithm. The analytical validity was assessed by measuring the level of agreement between the wrist-worn system and a thigh-worn system (activPAL), the reference measure. The clinical validity was assessed by establishing the prospective association between the changes in stepping volume and rate with changes in physical function (SPPB score). The agreement of the thigh-worn reference system and the wrist-worn system was excellent for total daily steps (CCC = 0.88, 95% CI 0.83-0.91) and moderate for walking steps and faster-paced walking steps (CCC = 0.61, 95% CI 0.53-0.68 and 0.55, 95% CI 0.46-0.64, respectively). A higher number of total steps and faster paced-walking steps was consistently associated with better physical function. After 24 months, an increase of 1000 daily faster-paced walking steps was associated with a clinically meaningful increase in physical function (0.53 SPPB score, 95% CI 0.32-0.74). We have validated a digital susceptibility/risk biomarker-pfSTEP-that identifies an associated risk of low physical function in community-dwelling older adults using a wrist-worn accelerometer and its accompanying open-source step counting algorithm.

Walking Behaviour of Individuals with Intermittent Claudication Compared to Matched Controls in Different Locations: An Exploratory Study

Individuals with intermittent claudication (IC) are less physically active than their peers, but how this varies with location is unclear. Individuals with IC and matched controls [sex, age ±5 years, home < 5 miles] wore an activity monitor (activPAL) and carried a GPS device (AMOD-AGL3080) for 7 days. GPS data categorised walking events as occurring at home (<=50 m from home co-ordinates) or away from home, and indoors (signal to noise ratio <= 212 dB) or outdoors. Number of walking events, walking duration, steps and cadence were compared between groups and each location pair using mixed model ANOVAs. In addition, the locus of activity (distance from home) at which walking was conducted was compared between groups. Participants (n = 56) were mostly male (64%) and aged 54-89 years. Individuals with IC spent significantly less time walking and took fewer steps than their matched controls at all locations, including at home. Participants spent more time and took more steps away from home than at home, but were similar when walking indoors and outdoors. The locus of activity was significantly smaller for individuals with IC, suggesting that it is not just physical capacity that influences walking behaviour, and other factors (e.g., social isolation) may play a role.

Physical Activity and Sedentary Behavior in People With Inflammatory Joint Disease: A Cross-Sectional Study

OBJECTIVE

To determine whether patients with inflammatory joint disease (IJD) meet current guidelines on physical activity, and to determine which factors influence physical activity levels and sedentary behavior (SB) in patients with IJD.

METHODS

This was a cross-sectional study of 137 patients with a medical diagnosis of an IJD prior to commencing an NHS-run inflammatory arthritis exercise program. Physical activity and SB were measured objectively using a thigh-worn physical activity monitor for 7 consecutive days. Activity levels were subdivided into low physical activity (LPA) and moderate-to-vigorous physical activity (MVPA). First, activity levels were analyzed against current guidelines of 150 minutes of MVPA per week. Second, time spent in SB, LPA, and MVPA was analyzed against possible determinants.

RESULTS

In total, 29% of patients with IJD met current physical activity guidelines. Patients on average spent 10 hours per day in SB. Poor physical fitness measured by the 6-minute walk test was the only significant predictor (P = 0.019) of high SB (R2  = 4.7%). Attending an exercise facility in the community (P = 0.034) and low role limitations due to physical health (P = 0.008) predicted high levels of LPA, following a backward multiple regression (R2  = 8.0%). Low role limitations due to emotional problems (P = 0.031), higher physical fitness (P = 0.002), and healthier exercise attitudes and beliefs (P = 0.021) predicted meeting current physical activity guidelines, following a backward conditional logistic regression, explaining between 22.2% and 31.7% of variance.

CONCLUSION

Patients with IJD are inactive and spent much time in SB. Good general health predicts high activity levels. No disease-specific factors were found to determine SB, LPA, or MVPA.

Defining Continuous Walking Events in Free-Living Environments: Mind the Gap

In free-living environments, continuous walking can be challenging to achieve without encountering interruptions, making it difficult to define a continuous walking event. While limited research has been conducted to define a continuous walking event that accounts for interruptions, no method has considered the intensity change caused by these interruptions, which is crucial for achieving the associated health outcomes. A sample of 24 staff members at the University of Salford were recruited. The participants wore an accelerometer-based device (activPAL™) for seven days continuously and completed an activity diary, to explore a novel methodological approach of combining short interruptions of time between walking events based on an average walking cadence. The definition of moderate-to-vigorous physical activity (MVPA) used was a minimum walking cadence of either 76, 100, or 109 steps/min. The average daily time spent in MVPA increased from 75.2 ± 32.6 min to 86.5 ± 37.4 min using the 76 steps/min, 48.3 ± 29.5 min to 53.0 ± 33.3 min using the 100 steps/min threshold, and 31.4 ± 20.5 min to 33.9 ± 22.6 min using the 109 steps/min threshold; the difference before grouping and after grouping was statistically significant (p < 0.001). This novel method will enable future analyses of the associations between continuous walking and health-related outcomes.

A Machine Learning Classification Model for Monitoring the Daily Physical Behaviour of Lower-Limb Amputees

There are currently limited data on how prosthetic devices are used to support lower-limb prosthesis users in their free-living environment. Possessing the ability to monitor a patient's physical behaviour while using these devices would enhance our understanding of the impact of different prosthetic products. The current approaches for monitoring human physical behaviour use a single thigh or wrist-worn accelerometer, but in a lower-limb amputee population, we have the unique opportunity to embed a device within the prosthesis, eliminating compliance issues. This study aimed to develop a model capable of accurately classifying postures (sitting, standing, stepping, and lying) by using data from a single shank-worn accelerometer. Free-living posture data were collected from 14 anatomically intact participants and one amputee over three days. A thigh worn activity monitor collected labelled posture data, while a shank worn accelerometer collected 3-axis acceleration data. Postures and the corresponding shank accelerations were extracted in window lengths of 5-180 s and used to train several machine learning classifiers which were assessed by using stratified cross-validation. A random forest classifier with a 15 s window length provided the highest classification accuracy of 93% weighted average F-score and between 88 and 98% classification accuracy across all four posture classes, which is the best performance achieved to date with a shank-worn device. The results of this study show that data from a single shank-worn accelerometer with a machine learning classification model can be used to accurately identify postures that make up an individual's daily physical behaviour. This opens up the possibility of embedding an accelerometer-based activity monitor into the shank component of a prosthesis to capture physical behaviour information in both above and below-knee amputees. The models and software used in this study have been made open source in order to overcome the current restrictions of applying activity monitoring methods to lower-limb prosthesis users.

Physical Activity and Cardiac Self-Efficacy Levels During Early Recovery After Acute Myocardial Infarction: A Jordanian Study

BACKGROUND

Regular physical activity is important for patients with established coronary heart disease as it favorably influences their coronary risk profile. General self-efficacy is a powerful predictor of health behavior change that involves increases in physical activity levels. Few studies have simultaneously measured physical activity and self-efficacy during early recovery after a first acute myocardial infarction (AMI).

PURPOSE

The aims of this study were to assess changes in objectively measured physical activity levels at 2 weeks (T2) and 6 weeks (T3) and self-reported cardiac self-efficacy at hospital discharge (T1) and at T2 and T3 in patients recovering from AMI.

METHODS

A repeated-measures design was used to recruit a purposive sample of patients from a single center in Jordan who were diagnosed with first AMI and who did not have access to cardiac rehabilitation. A body-worn activity monitor (activPAL) was used to objectively measure free-living physical activity levels for 7 consecutive days at two time points (T2 and T3). An Arabic version of the cardiac self-efficacy scale was administered at T1, T2, and T3. Paired t tests and analysis of variance were used to examine differences in physical activity levels and cardiac self-efficacy scores, respectively.

RESULTS

A sample of 100 participants was recruited, of which 62% were male. The mean age of the sample was 54.5 ± 9.9 years. No statistically significant difference in physical activity levels was measured at 2 weeks (T2) and 6 weeks (T3). Cardiac self-efficacy scores improved significantly between T1, T2, and T3 across subscales and global cardiac self-efficacy.

CONCLUSIONS/IMPLICATIONS FOR PRACTICE

Participants recovering from AMI in Jordan did not increase their physical activity levels during the early recovery phase, although cardiac self-efficacy scores improved. This may be because the increase in cardiac self-efficacy was not matched by the practical skills and knowledge required to translate this positive psychological construct into behavioral change. This study provides a first step toward understanding the complex relationship between cardiac self-efficacy and physical activity in this population. The authors hope that these findings support the design of culturally appropriate interventions to increase physical activity levels in this population.

Considerations in Processing Accelerometry Data to Explore Physical Activity and Sedentary Time in Older Adults

Processing decisions for accelerometry data can have important implications for outcome measures, yet little evidence exists exploring these in older adults. The aim of the current study was to investigate the impact of three potentially important criteria on older adults, physical activity, and sedentary time. Participants (n = 222: mean age 71.75 years [SD = 6.58], 57% male) wore ActiGraph GT3X+ for 7 days. Eight data processing combinations from three criteria were explored: low-frequency extension (on/off), nonwear time (90/120 min), and intensity cut points (moderate-to-vigorous physical activity ≥1,041 and >2,000 counts/min). Analyses included Wilcoxon signed-rank test, paired t tests, and correlation coefficients (significance, p < .05). Results for low-frequency extension on 90-min nonwear time and >1,041 counts/min showed significantly higher light and moderate-to-vigorous physical activity and lower sedentary time. Cut points had the greatest impact on physical activity and sedentary time. Processing criteria can significantly impact physical activity and/or sedentary time, potentially leading to data inaccuracies, preventing cross-study comparisons and influencing the accuracy of population surveillance.

Evaluating the Performance of Sensor-based Bout Detection Algorithms: The Transition Pairing Method

Bout detection algorithms are used to segment data from wearable sensors, but it is challenging to assess segmentation correctness.

Purpose

To present and demonstrate the Transition Pairing Method (TPM), a new method for evaluating the performance of bout detection algorithms.

Methods

The TPM compares predicted transitions to a criterion measure in terms of number and timing. A true positive is defined as a predicted transition that corresponds with one criterion transition in a mutually exclusive pair. The pairs are established using an extended Gale-Shapley algorithm, and the user specifies a maximum allowable within-pair time lag, above which pairs cannot be formed. Unpaired predictions and criteria are false positives and false negatives, respectively. The demonstration used raw acceleration data from 88 youth who wore ActiGraph GT9X monitors (right hip and non-dominant wrist) during simulated free-living. Youth Sojourn bout detection algorithms were applied (one for each attachment site), and the TPM was used to compare predicted bout transitions to the criterion measure (direct observation). Performance metrics were calculated for each participant, and hip-versus-wrist means were compared using paired T-tests (α = 0.05).

Results

When the maximum allowable lag was 1-s, both algorithms had recall <20% (2.4% difference from one another, p<0.01) and precision <10% (1.4% difference from one another, p<0.001). That is, >80% of criterion transitions were undetected, and >90% of predicted transitions were false positives.

Conclusion

The TPM improves on conventional analyses by providing specific information about bout detection in a standardized way that applies to any bout detection algorithm.

A Pilot Randomised Clinical Trial of a Novel Approach to Reduce Sedentary Behaviour in Care Home Residents: Feasibility and Preliminary Effects of the GET READY Study

Care-home residents are among the most sedentary and least active of the population. We aimed to assess the feasibility, acceptability, safety, and preliminary effects of an intervention to reduce sedentary behaviour (SB) co-created with care home residents, staff, family members, and policymakers within a pilot two-armed pragmatic cluster randomized clinical trial (RCT). Four care homes from two European countries participated, and were randomly assigned to control (usual care, CG) or the Get Ready intervention (GR), delivered by a staff champion one-to-one with the care home resident and a family member. A total of thirty-one residents participated (51.6% female, 82.9 (13.6) years old). GR involves six face to face sessions over a 12-week period with goal-oriented prompts for movement throughout. The feasibility and acceptability of the intervention were assessed and adverse events (AEs) were collected. The preliminary effects of the GR on SB, quality of life, fear of falling, and physical function were assessed. Means and standard deviations are presented, with the mean change from baseline to post-intervention calculated along with 95% confidence intervals. The CG smoked more, sat more, and had more functional movement difficulties than the GR at baseline. The GR intervention was feasible and acceptable to residents and staff. No AEs occurred during the intervention. GR participants showed a decrease in daily hours spent sitting/lying (Cohen’s d = 0.36) and an increase in daily hours stepping, and improvements in health-related quality of life, fear of falling, and habitual gait speed compared to usual care, but these effects need confirmation in a definitive RCT. The co-created GR was shown to be feasible and acceptable, with no AEs.

Quantifying sit-to-stand and stand-to-sit transitions in free-living environments using the activPAL thigh-worn activity monitor

PURPOSE

Standing up, sitting down and walking require considerable effort and coordination, which are crucial indicators to rehabilitation (e.g. stroke), and in older populations may indicate the onset of frailty and physical and cognitive decline. Currently, there are few reports robustly quantifying sit-to-stand and stand-to-sit transitions in free-living environments. The aim of this study was to identify and quantify these transitions using the peak velocity of sit-to-stand and stand-to-sit transitions to determine if these velocities were different in a healthy cohort and a mobility-impaired population.

METHODS

Free-living sit-to-stand and stand-to-sit acceleration data were recorded from 21 healthy volunteers and 34 stroke survivors using activPAL3™ monitors over a one-week period. Thigh inclination velocity was calculated from these accelerometer data. Maximum velocities were compared between populations.

RESULTS

A total of 10,299 and 11,392 sit-to-stand and stand-to-sit transitions were recorded in healthy volunteers and stroke survivors, respectively. Healthy volunteers had significantly higher overall mean peak velocities for both transitions compared with stroke survivors [70.7°/s ± 52.2 versus 44.2°/s ± 28.0 for sit-to-stand, P < 0.001 and 74.7°/s ± 51.8 versus 46.0°/s ± 31.9 for stand-to-sit; P < 0.001]. Mean peak velocity of transition was associated with increased variation in peak velocity across both groups.

CONCLUSION

There were significant differences in the mean peak velocity of sit-to-stand and stand-to-sit transitions between the groups. Variation in an individual's mean peak velocity may be associated with the ability to perform these transitions. This method could be used to evaluate the effectiveness of interventions following injury such as stroke, as well as monitor decline in functional ability.

A randomised feasibility study to investigate the impact of education and the addition of prompts on the sedentary behaviour of office workers

Background

Office workers have been identified as being at risk of accumulating high amounts of sedentary time in prolonged events during work hours, which has been associated with increased risk of a number of long-term health conditions.

There is some evidence that providing advice to stand at regular intervals during the working day, and using computer-based prompts, can reduce sedentary behaviour in office workers. However, evidence of effectiveness, feasibility and acceptability for these types of intervention is currently limited.

Methods

A 2-arm, parallel group, cluster-randomised feasibility trial to assess the acceptability of prompts to break up sedentary behaviour was conducted with office workers in a commercial bank (n = 21). Participants were assigned to an education only group (EG) or prompt and education group (PG). Both groups received education on reducing and breaking up sitting at work, and the PG also received hourly prompts, delivered by Microsoft Outlook over 10 weeks, reminding them to stand. Objective measurements of sedentary behaviour were made using activPAL monitors worn at three time points: baseline, in the last 2 weeks of the intervention period and 12 weeks after the intervention. Focus groups were conducted to explore the acceptability of the intervention and the motivations and barriers to changing sedentary behaviour.

Results

Randomly generated, customised prompts, delivered by Microsoft Outlook, with messages about breaking up sitting, proved to be a feasible and acceptable way of delivering prompts to office workers. Participants in both groups reduced their sitting, but changes were not maintained at follow-up. The education session seemed to increase outcome expectations of the benefits of changing sedentary behaviour and promote self-regulation of behaviour in some participants. However, low self-efficacy and a desire to conform to cultural norms were barriers to changing behaviour.

Conclusions

Prompts delivered by Microsoft Outlook were a feasible, low-cost way of prompting office workers to break up their sedentary behaviour, although further research is needed to determine whether this has an additional impact on sedentary behaviour, to education alone. The role of cultural norms, and promoting self-efficacy, should be considered in the design of future interventions.

Trial registration

This study was registered retrospectively as a clinical trial on ClinicalTrials.gov (ID no. NCT02609282) on 23 March 2015.

The influence of dog ownership on objective measures of free-living physical activity and sedentary behaviour in community-dwelling older adults: a longitudinal case-controlled study

Background

There is some evidence to suggest that dog ownership may improve physical activity (PA) among older adults, but to date, studies examining this, have either depended on self-report or incomplete datasets due to the type of activity monitor used to record physical activity. Additionally, the effect of dog ownership on sedentary behaviour (SB) has not been explored. The aim of the current study was to address these issues by using activPAL monitors to evaluate the influence of dog ownership on health enhancing PA and SB in a longitudinal study of independently-mobile, community-dwelling older adults.

Methods

Study participants (43 pairs of dog owners and non-dog owners, matched on a range of demographic variables) wore an activPAL monitor continuously for three, one-week data collection periods over the course of a year. Participants also reported information about their own and their dog demographics, caring responsibilities, and completed a diary of wake times. Diary data was used to isolate waking times, and outcome measures of time spent walking, time spent walking at a moderate cadence (>100 steps/min), time spent standing, time spent sitting, number of sitting events (continuous periods of sitting), and the number of and of time spent sitting in prolonged events (>30 min). For each measure, a linear mixed effects model with dog ownership as a fixed effect, and a random effects structure of measurement point nested in participant nested in pair was used to assess the effect of dog ownership.

Results

Owning a dog indicated a large, potentially health improving, average effect of 22 min additional time spent walking, 95%CI (12, 34), and 2760 additional steps per day, 95%CI (1667, 3991), with this additional walking undertaken at a moderate intensity cadence. Dog owners had significantly fewer sitting events. However, there were no significant differences between the groups for either the total time spent sitting, or the number or duration of prolonged sedentary events.

Conclusions

The scale of the influence of dog ownership on PA found in this study, indicates that future research regarding PA in older adults should assess and report dog ownership and/or dog walking status.

Electronic supplementary material

The online version of this article (doi:10.1186/s12889-017-4422-5) contains supplementary material, which is available to authorized users.

Empirically derived cut-points for sedentary behaviour: are we sitting differently?

Sedentary behaviour (SB) is associated with a number of adverse health outcomes. Studies that have used ActiGraph monitors to define sedentary time tend to use a threshold of  <100 counts per minute (cpm) for classifying SB; however, this cut-point was not empirically derived for adults. It is not known whether ActiGraph cut-points for SB differ depending on the context in which it occurs. We aimed to: (1) empirically derive an optimal threshold for classifying SB, using the cpm output from the ActiGraph GT3X+, compared to the sedentary classification from the activPAL3^™; and (2) ascertain whether this varied by day of the week and in working time versus non-working time. A convenience sample of 30 office-based university employees (females (66.67%); age 40.47  ±  10.95 years; BMI 23.93  ±  2.46 kg m^-2) wore the ActiGraph GT3X+ and activPAL3^™ devices simultaneously for seven days. Data were downloaded in 1 min epochs and non-wear time was removed. Generalised estimating equations were used to make minute by minute comparisons of sedentary time from the two devices, using sedentary minutes (when all 60 s were classified as sitting/lying) from the activPAL3^™ as the criterion measure. After data reduction participants provided on average 11 h 27 min of data per day. The derived cut-points from the models were significantly higher on a Saturday (97 cpm) compared to weekdays (60 cpm) and Sunday (57 cpm). Derived cpm for sedentary time during working time were significantly lower compared to non-working time (35 (95%CI 30-41) versus 73 (54-113)). Compared to the 100 cpm and 150 cpm thresholds, the empirically derived cut-points were not significantly different in terms of area-under-the-curve, but had lower mean bias for working and non-working times. Accelerometer cut-points for SB can depend on day and also domain, suggesting that the nature of sitting differs depending on the context in which sedentary time is accrued.

Associations of Monitor-Assessed Activity with Performance-Based Physical Function

The purpose of this study was to investigate the cross-sectional associations of monitor-derived measures of sedentary time and physical activity with performance-based physical function in healthy Australian adults. Data from 602 participants (mean age 58.1±10.0 years; 58% female) from the 2011/12 wave of the Australian Diabetes, Obesity and Lifestyle (AusDiab3) study were analyzed. The thigh-worn activPAL3^™ monitor (7-days continuous wear) was used to derive time during waking hours spent: sitting/reclining; standing; and, stepping (overall, and separately as light [<3 METs] and moderate-to-vigorous physical activity [MVPA; ≥3 METs]), and number of sit-stand transitions. Associations of these (in hours/day, or 15 transitions/day) with physical function measures (8ft Timed Up and Go [TUG-8; log-transformed seconds] and Knee Extensor Strength [KES; kg]) were tested via linear regression, adjusting for confounders. Interactions by sex and age-category (<45; 45–54; 55–64; ≥65 years) were tested. In all participants, KES was significantly (p<0.05) associated with stepping and MVPA stepping only; none of the activity measures were associated with TUG-8. However, subgroup analysis revealed that in older adults (≥65 years), TUG-8 was associated with stepping and MVPA stepping (both p<0.05). All associations with sitting time, standing, sit-stand transition and sex interactions were not statistically significant. In summary, sitting time was not significantly associated with impaired muscle strength or gait/mobility in Australian adults aged 36–80 years, but light- to moderate activity (stepping) was positively associated with muscle strength, and gait/mobility in older adults aged ≥65 years. The direction of causation is not known and remains important to investigate considering the high prevalence of both poor function and limited activity in older age.

Quantifying the cadence of free-living walking using event-based analysis

PURPOSE

Free-living walking occurs over a wide range of durations and intensities (cadence). Therefore, its characterisation requires a full description of the distribution of duration and cadence of these walking events. The aim was to use event-based analysis to characterise this in a population with intermittent claudication (IC) and a healthy matched control group.

METHODS

Seven-day walking activity was recorded using the activPAL activity monitor in a group of people with IC (n=30) and an age-matched control group (n=30). The cadence, number of steps and duration of individual walking events were calculated and outcomes were derived, and compared (p<0.05), based on thresholds applied.

RESULTS

Both groups had similar number of walking events per day (392±117 vs 415±160). The control group accumulated a greater proportion of their walking at higher cadences and 32% of their steps were taken at a cadence above 100 steps/min, for the IC group this was 20%. Longer walking events had higher cadences and the IC group had fewer of these. As walking events became longer the cadence increased but the inter-event cadence variability decreased. More purposeful walking might occur at a higher cadence, and be performed at a preferred cadence. Individuals with IC had a smaller volume of walking, but these differences occurred almost entirely above a cadence of 90 steps/min.

CONCLUSIONS

This is the first study which has quantified the cadence of continuous periods of free-living walking. The characteristics (duration, number of steps and cadence) of all the individual walking events were used to derive novel outcomes, providing new insights into free-living walking behaviour.

Validation of five minimally obstructive methods to estimate physical activity energy expenditure in young adults in semi-standardized settings

We compared the accuracy of five objective methods, including two newly developed methods combining accelerometry and activity type recognition (Acti4), against indirect calorimetry, to estimate total energy expenditure (EE) of different activities in semi-standardized settings. Fourteen participants performed a standardized and semi-standardized protocol including seven daily life activity types, while having their EE measured by indirect calorimetry. Simultaneously, physical activity was quantified by an ActivPAL³, two ActiGraph GT3X+’s and an Actiheart. EE was estimated by the standard ActivPAL³ software (ActivPAL), ActiGraph GT3X+ (ActiGraph) and Actiheart (Actiheart), and by a combination of activity type recognition via Acti4 software and activity counts per minute (CPM) of either a hip- or thigh-worn ActiGraph GT3X+ (AGhip + Acti4 and AGthigh + Acti4). At group level, estimated physical activities EE by Actiheart (MSE = 2.05) and AGthigh + Acti4 (MSE = 0.25) were not significantly different from measured EE by indirect calorimetry, while significantly underestimated by ActiGraph, ActivPAL and AGhip + Acti4. AGthigh + Acti4 and Actiheart explained 77% and 45%, of the individual variations in measured physical activity EE by indirect calorimetry, respectively. This study concludes that combining accelerometer data from a thigh-worn ActiGraph GT3X+ with activity type recognition improved the accuracy of activity specific EE estimation against indirect calorimetry in semi-standardized settings compared to previously validated methods using CPM only.

Extracting objective estimates of sedentary behavior from accelerometer data: measurement considerations for surveillance and research applications

BACKGROUND

Accelerometer-based activity monitors are widely used in research and surveillance applications for quantifying sedentary behavior (SB) and physical activity (PA). Considerable research has been done to refine methods for assessing PA, but relatively little attention has been given to operationalizing SB parameters (i.e., sedentary time and breaks) from accelerometer data - particularly in relation to health outcomes. This study investigated: (a) the accrued patterns of sedentary time and breaks; and (b) the associations of sedentary time and breaks in different bout durations with cardiovascular risk factors.

METHODS

Accelerometer data on 5,917 adults from the National Health Examination and Nutrition Survey (NHANES) 2003-2006 were used. Sedentary time and breaks at different bout durations (i.e., 1, 2-4, 5-9, 10-14, 15-19, 20-24, 25-29, and ≥ 30-min) were obtained using a threshold of < 100 counts per minute. Sedentary time and breaks were regressed on cardiovascular risk factors (waist circumference, triglyceride, and high-density lipoprotein cholesterol) and body mass index across bout durations.

RESULTS

The results revealed that the majority of sedentary time occurred within relatively short bout durations (≈ 70% and ≈ 85% for < 5-min and < 10-min, respectively). The associations of sedentary time and breaks with health outcomes varied depending on how bout time was defined. Estimates of SB parameters based on bout durations of 5 min or shorter were associated with reduced cardiovascular risk factors while durations longer than 10-min were generally associated with increased risk factors.

CONCLUSIONS

The present study demonstrates that the duration of sedentary bouts should be further considered when operationalizing the SB parameters from accelerometer data. The threshold of 5 minutes to define a bout is defensible, but a 10 minute threshold would provide a more conservative estimate to clearly capture the prolonged nature of sedentary behavior. Additional research is needed to determine the relative sensitivity and specificity of these thresholds.

True cadence and step accumulation are not equivalent: the effect of intermittent claudication on free-living cadence

'True cadence' is the rate of stepping during the period of stepping. 'Step accumulation' is the steps within an epoch of time (e.g. 1min). These terms have been used interchangeably in the literature. These outcomes are compared within a population with intermittent claudication (IC). Multiday, 24h stepping activity of those with IC (30) and controls (30) was measured objectively using the activPAL physical activity monitor. 'True cadence' and 'step accumulation' outcomes were calculated. Those with IC took fewer steps/d 6531±2712 than controls 8692±2945 (P=0.003). However, these steps were taken within approximately the same number of minute epochs (IC 301±100min/d; controls 300±70min/d, P=0.894) with only slightly lower true cadence (IC 69 (IQ 66,72) steps/min; controls 72 (IQ 68,76) steps/min, P=0.026), giving substantially lower step accumulation (IC 22 (IQ 19,24) steps/min; controls 30 (IQ 23,34) steps/min) (P<0.001). However, the true cadence of stepping within the blocks of the 1, 5, 20, 30 and 60min with the maximum number of steps accumulated was lower for those with IC than controls (P<0.05). Those with IC took 1300 steps fewer per day above a true cadence of 90 steps/min. True cadence and step accumulation outcomes were radically different for the outcomes examined. 'True cadence' and 'step accumulation' were not equivalent in those with IC or controls. The measurement of true cadence in the population of people with IC provides information about their stepping rate during the time they are stepping. True cadence should be used to correctly describe the rate of stepping as performed.

Motivational counseling to reduce sitting time: a community-based randomized controlled trial in adults

BACKGROUND

Sedentary behavior is regarded as a distinct risk factor for cardiometabolic morbidity and mortality, but knowledge of the efficacy of interventions targeting reductions in sedentary behavior is limited.

PURPOSE

To investigate the effect of an individualized face-to-face motivational counseling intervention aimed at reducing sitting time.

DESIGN

A randomized, controlled, observer-blinded, community-based trial with two parallel groups using open-end randomization with 1:1 allocation.

SETTING/PARTICIPANTS

A total of 166 sedentary adults were consecutively recruited from the population-based Health2010 Study.

INTERVENTION

Participants were randomized to a control (usual lifestyle) or intervention group with four individual theory-based counseling sessions.

MAIN OUTCOME MEASURES

Objectively measured overall sitting time (ActivPAL 3TM, 7 days); secondary measures were breaks in sitting time, anthropometric measures, and cardiometabolic biomarkers, assessed at baseline and after 6 months. Data were collected in 2010-2012 and analyzed in 2013-2014 using repeated measures multiple regression analyses.

RESULTS

Ninety-three participants were randomized to the intervention group and 73 to the control group, and 149 completed the study. The intervention group had a mean sitting time decrease of -0.27 hours/day, corresponding to 2.9% of baseline sitting time (hours/day); the control group increased mean sitting time by 0.06 hours/day. The between-group difference in change, -0.32 hours/day (95% CI=-0.87, 0.24, p=0.26), was not statistically significant. Significant differences in change in fasting serum insulin of -5.9 pmol/L (95% CI=-11.4, -0.5, p=0.03); homeostasis model assessment-estimated insulin resistance of -0.28 (95% CI=-0.53, -0.03, p=0.03); and waist circumference of -1.42 cm (95% CI=-2.54, -0.29, p=0.01) were observed in favor of the intervention group.

CONCLUSIONS

Although the observed decrease in sitting time was not significant, a community-based, individually tailored, theory-based intervention program aimed at reducing sitting time may be effective for increasing standing and improving cardiometabolic health in sedentary adults.

TRIAL REGISTRATION

This study is registered at Clinicaltrials.gov (NCT00289237).

Duration and patterns of habitual physical activity in adolescents and young adults with cerebral palsy

AIM

Adolescents and young adults with cerebral palsy (CP) show reduced motor function and gait efficiency, and lower levels of habitual physical activity (HPA), than adolescents with typical development and children with CP. This study examined activity duration and patterns in this population in the Middle East through long-term monitoring of a large sample using accelerometers.

METHOD

Adolescents and young adults with bilateral CP at Gross Motor Function Classification System (GMFCS) levels II, III, and IV, were monitored in their habitual environment for four consecutive days with ActivPAL3 monitors. Time spent in sedentary, standing, and walking activities, and frequency of walking steps and transitions, were analysed for each GMFCS level.

RESULTS

Measurements were made on 222 participants (132 males, 90 females; mean age 16 y 9 mo SD 2y, range 13 y 4 mo-22 y). The Mann-Whitney U test demonstrated significant differences (p<0.05) between GMFCS levels, showing reduced walking and standing activity and increased sedentary duration at higher GMFCS levels (p<0.001), except for increased standing time between GMFCS levels II and III (p=0.07). Participants in educational facilities exhibited less sedentary behaviour than those who were homebound (p<0.05).

INTERPRETATION

These descriptions of duration and frequency of active and sedentary behaviours may serve as a basis for recommendations to minimize inactivity in this population. Adolescents and young adults with CP in the Middle East demonstrate similar patterns of HPA to their peers in other regions.

Step accumulation per minute epoch is not the same as cadence for free-living adults

PURPOSE

The term cadence has been used interchangeably to describe both the rate of stepping and the number of steps in a minute epoch. This is only strictly true if walking is continuous within that epoch. This study directly compared these two outcomes in minute epochs of data from free-living adults to assess the scale of any difference between them.

METHODS

A convenience sample of healthy adults wore an activPAL activity monitor for 7 d. The event record output of the activPAL, providing the start time and duration of each stride to the nearest 0.1 s, was used to calculate step accumulation (number of steps), duration of walking, and cadence (number of steps/duration of walking) for each minute of measurement.

RESULTS

Data from 117 individuals (78 females; mean age, 46 ± 16 yr; mean body mass index, 24.9 ± 3.7 kg·m-2) were analyzed. Twenty-one percent of minutes (n = 310d-1) contained walking. The distribution (most minutes fewer than 40 steps per minute) and mean (34 ± 9 steps per minute) of step accumulation were very different from that of cadence (most minutes between 60 and 100 steps per minute; mean, 76 ± 6 steps per minute). Only 12% of minutes with stepping were walked continuously, whereas 69% of minutes with stepping contained less than 30 s of walking. This is key to the difference between step accumulation and cadence, and means that cadence cannot be reconstructed from step accumulation without also knowing the duration that was walked.

CONCLUSION

Step accumulation, the number of steps in a fixed period, and cadence, the rate of stepping while walking, are not interchangeable outcome measures. It is vitally important that unambiguous terminology is used to describe the rate of stepping so that the outcomes of studies can be correctly interpreted.

Monitoring human health behaviour in one's living environment: a technological review

The electronic monitoring of human health behaviour using computer techniques has been an active research area for the past few decades. A wide array of different approaches have been investigated using various technologies including inertial sensors, Global Positioning System, smart homes, Radio Frequency IDentification and others. It is only in recent years that research has turned towards a sensor fusion approach using several different technologies in single systems or devices. These systems allow for an increased volume of data to be collected and for activity data to be better used as measures of behaviour. This change may be due to decreasing hardware costs, smaller sensors, increased power efficiency or increases in portability. This paper is intended to act as a reference for the design of multi-sensor behaviour monitoring systems. The range of technologies that have been used in isolation for behaviour monitoring both in research and commercial devices are reviewed and discussed. Filtering, range, sensitivity, usability and other considerations of different technologies are discussed. A brief overview of commercially available activity monitors and their technology is also included.