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

Agreement Between Apple Watch and Actical Step Counts in a Community Setting: Cross-Sectional Investigation From the Framingham Heart Study

BACKGROUND

Step counting is comparable among many research-grade and consumer-grade accelerometers in laboratory settings.

OBJECTIVE

The purpose of this study was to compare the agreement between Actical and Apple Watch step-counting in a community setting.

METHODS

Among Third Generation Framingham Heart Study participants (N=3486), we examined the agreement of step-counting between those who wore a consumer-grade accelerometer (Apple Watch Series 0) and a research-grade accelerometer (Actical) on the same days. Secondarily, we examined the agreement during each hour when both devices were worn to account for differences in wear time between devices.

RESULTS

We studied 523 participants (n=3223 person-days, mean age 51.7, SD 8.9 years; women: n=298, 57.0%). Between devices, we observed modest correlation (intraclass correlation [ICC] 0.56, 95% CI 0.54-0.59), poor continuous agreement (29.7%, n=957 of days having steps counts with ≤15% difference), a mean difference of 499 steps per day higher count by Actical, and wide limits of agreement, roughly ±9000 steps per day. However, devices showed stronger agreement in identifying who meets various steps per day thresholds (eg, at 8000 steps per day, kappa coefficient=0.49), for which devices were concordant for 74.8% (n=391) of participants. In secondary analyses, in the hours during which both devices were worn (n=456 participants, n=18,760 person-hours), the correlation was much stronger (ICC 0.86, 95% CI 0.85-0.86), but continuous agreement remained poor (27.3%, n=5115 of hours having step counts with ≤15% difference) between devices and was slightly worse for those with mobility limitations or obesity.

CONCLUSIONS

Our investigation suggests poor overall agreement between steps counted by the Actical device and those counted by the Apple Watch device, with stronger agreement in discriminating who meets certain step thresholds. The impact of these challenges may be minimized if accelerometers are used by individuals to determine whether they are meeting physical activity guidelines or tracking step counts. It is also possible that some of the limitations of these older accelerometers may be improved in newer devices.

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.

Fitbit's accuracy to measure short bouts of stepping and sedentary behaviour: validation, sensitivity and specificity study

Objective

This study aims to assess the suitability of Fitbit devices for real-time physical activity (PA) and sedentary behaviour (SB) monitoring in the context of just-in-time adaptive interventions (JITAIs) and event-based ecological momentary assessment (EMA) studies.

Methods

Thirty-seven adults (18-65 years) and 32 older adults (65+) from Belgium and the Czech Republic wore four devices simultaneously for 3 days: two Fitbit models on the wrist, an ActiGraph GT3X+ at the hip and an ActivPAL at the thigh. Accuracy measures included mean (absolute) error and mean (absolute) percentage error. Concurrent validity was assessed using Lin's concordance correlation coefficient and Bland-Altman analyses. Fitbit's sensitivity and specificity for detecting stepping events across different thresholds and durations were calculated compared to ActiGraph, while ROC curve analyses identified optimal Fitbit thresholds for detecting sedentary events according to ActivPAL.

Results

Fitbits demonstrated validity in measuring steps on a short time scale compared to ActiGraph. Except for stepping above 120 steps/min in older adults, both Fitbit models detected stepping bouts in adults and older adults with sensitivities and specificities exceeding 87% and 97%, respectively. Optimal cut-off values for identifying prolonged sitting bouts achieved sensitivities and specificities greater than 93% and 89%, respectively.

Conclusions

This study provides practical insights into using Fitbit devices in JITAIs and event-based EMA studies among adults and older adults. Fitbits' reasonable accuracy in detecting short bouts of stepping and SB makes them suitable for triggering JITAI prompts or EMA questionnaires following a PA or SB event of interest.

A Comparison of Objectively Measured Free-Living Physical Behaviour in Adults with and without Lower Limb Amputation

Objectively monitored free-living physical behaviours of adults with and without lower limb amputation (LLA) were compared.

METHODS

57 adults with LLA wore an activPAL3™ for 8 days. A comparison data set (n = 57) matched on gender, age and employment status was used. Variables included: time sitting; standing; stepping; sit-to-stand transitions; step count and cadence. Comparisons were made between adults with and without LLA and between gender, level and cause of amputation.

RESULTS

Participants with LLA due to trauma versus circulatory causes were less sedentary and more active; however, no difference in physical behaviour was recorded across gender or level of amputation. Participants with LLA spent more time sitting (p < 0.001), less time standing and stepping (p < 0.001) and had a lower step count (p < 0.001). Participants with LLA took more steps in cadence bands less than 100 steps·min-1 and fewer steps in cadence bands greater than 100 steps·min-1 compared to participants without LLA.

CONCLUSIONS

People with LLA were less active and more sedentary than people without LLA and participated in less activity at a moderate or higher intensity when matched on age, gender and employment. Interventions are needed to promote active lifestyles in this population.

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.

Concurrent Agreement Between ActiGraph and activPAL for Measuring Physical Activity in Pregnant Women and Office Workers

INTRODUCTION

Current best practice for objective measurement of sedentary behavior and moderate-to-vigorous intensity physical activity (MVPA) requires two separate devices. This study assessed concurrent agreement between the ActiGraph GT3X and the activPAL3 micro for measuring MVPA to determine if activPAL can accurately measure MVPA in addition to its known capacity to measure sedentary behavior.

METHODS

Forty participants from two studies, including pregnant women (n = 20) and desk workers (n = 20), provided objective measurement of MVPA from waist-worn ActiGraph GT3X and thigh-worn activPAL micro3. MVPA from the GT3X was compared with MVPA from the activPAL using metabolic equivalents of task (MET)- and step-based data across three epochs. Intraclass correlation coefficient and Bland-Altman analyses, overall and by study sample, compared MVPA minutes per day across methods.

RESULTS

Mean estimates of activPAL MVPA ranged from 22.7 to 35.2 (MET based) and 19.7 to 25.8 (step based) minutes per day, compared with 31.4 min/day (GT3X). MET-based MVPA had high agreement with GT3X, intraclass correlation coefficient ranging from .831 to .875. Bland-Altman analyses revealed minimal bias between 15- and 30-s MET-based MVPA and GT3X MVPA (-3.77 to 8.63 min/day, p > .10) but with wide limits of agreement (greater than ±27 min). Step-based MVPA had moderate to high agreement (intraclass correlation coefficient: .681-.810), but consistently underestimated GT3X MVPA (bias: 5.62-11.74 min/day, p < .02). For all methods, activPAL appears to better estimate GT3X at lower quantities of MVPA. Results were similar when repeated separately by pregnant women and desk workers.

CONCLUSION

activPAL can measure MVPA in addition to sedentary behavior, providing an option for concurrent, single device monitoring. MET-based MVPA using 30-s activPAL epochs provided the best estimate of GT3X MVPA in pregnant women and desk workers.

The impact of different step rate threshold methods on physical activity intensity in older adults

BACKGROUND

Older adults benefit most from engaging in higher-intensity physical activity, which is often determined using step rate thresholds. Fixed step rate thresholds that correspond to moderate (MPA) and vigorous-intensity physical activity (VPA) have been developed for heuristic activity promotion. The activPAL monitor uses step rate thresholds to determine activity intensity. Stepping thresholds may also vary based on body mass index (BMI) or aerobic fitness level in older adults. Despite the various thresholds used in the literature, it is unclear whether they produce similar outcomes.

RESEARCH QUESTION

How does time spent in physical activity intensities compare between different step rate thresholds in older adults?

METHODS

Thirty-eight participants (24♀; 67 ± 4 years; BMI: 26.6 ± 4.4 kg/m²) wore an activPAL monitor 24-hr/day for up to 7-d (total: 205-d). Aerobic fitness (V̇O₂max: 23 ± 8 ml/kg/min) was determined via indirect calorimetry during a maximal, graded cycling test. Time spent in each intensity category (light-physical-activity [LPA], MPA, VPA) was determined using the fixed (MPA/VPA) 100/130, 110/130, and activPAL step rate thresholds (74/212), as well as BMI-adjusted absolute (108.5 ± 2.5/134.0 ± 4.8) and BMI-adjusted relative (40%/60% V̇O₂max; 111.4 ± 14.7/132.0 ± 19.0) cut-offs. Times spent in each intensity category were compared between methods.

RESULTS

The activPAL and 100/130 thresholds yielded less LPA and more MPA than all other methods. The activPAL had no time spent in VPA at all. The BMI-adjusted absolute and relative thresholds produced statistically equivalent time in LPA and MPA (via equivalence testing), but not VPA. No two methods yielded similar time spent in LPA, MPA, or VPA.

SIGNIFICANCE

The choice of step rate threshold has a major impact on physical activity intensity outcomes in older adults. Inherently, strategies that adjust for older adults' body size and/or aerobic fitness level provide a more individualized data processing strategy than fixed thresholds that assume the same threshold for all older adults.

Daily steps and all-cause mortality: a meta-analysis of 15 international cohorts

BACKGROUND

Although 10 000 steps per day is widely promoted to have health benefits, there is little evidence to support this recommendation. We aimed to determine the association between number of steps per day and stepping rate with all-cause mortality.

METHODS

In this meta-analysis, we identified studies investigating the effect of daily step count on all-cause mortality in adults (aged ≥18 years), via a previously published systematic review and expert knowledge of the field. We asked participating study investigators to process their participant-level data following a standardised protocol. The primary outcome was all-cause mortality collected from death certificates and country registries. We analysed the dose-response association of steps per day and stepping rate with all-cause mortality. We did Cox proportional hazards regression analyses using study-specific quartiles of steps per day and calculated hazard ratios (HRs) with inverse-variance weighted random effects models.

FINDINGS

We identified 15 studies, of which seven were published and eight were unpublished, with study start dates between 1999 and 2018. The total sample included 47 471 adults, among whom there were 3013 deaths (10·1 per 1000 participant-years) over a median follow-up of 7·1 years ([IQR 4·3-9·9]; total sum of follow-up across studies was 297 837 person-years). Quartile median steps per day were 3553 for quartile 1, 5801 for quartile 2, 7842 for quartile 3, and 10 901 for quartile 4. Compared with the lowest quartile, the adjusted HR for all-cause mortality was 0·60 (95% CI 0·51-0·71) for quartile 2, 0·55 (0·49-0·62) for quartile 3, and 0·47 (0·39-0·57) for quartile 4. Restricted cubic splines showed progressively decreasing risk of mortality among adults aged 60 years and older with increasing number of steps per day until 6000-8000 steps per day and among adults younger than 60 years until 8000-10 000 steps per day. Adjusting for number of steps per day, comparing quartile 1 with quartile 4, the association between higher stepping rates and mortality was attenuated but remained significant for a peak of 30 min (HR 0·67 [95% CI 0·56-0·83]) and a peak of 60 min (0·67 [0·50-0·90]), but not significant for time (min per day) spent walking at 40 steps per min or faster (1·12 [0·96-1·32]) and 100 steps per min or faster (0·86 [0·58-1·28]).

INTERPRETATION

Taking more steps per day was associated with a progressively lower risk of all-cause mortality, up to a level that varied by age. The findings from this meta-analysis can be used to inform step guidelines for public health promotion of physical activity.

FUNDING

US Centers for Disease Control and Prevention.

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.

Comparison of habitual stepping cadence analysis methods: Relationship with step counts

BACKGROUND

Different approaches have been implemented to calculate stepping cadence (steps/min) that vary in the time demominator used. Given the differences in how stepping intensity are calculated, it is unclear if they are more so associated with total step counts.

RESEARCH OBJECTIVE

This study compared three methods of calculating stepping cadence and determined their relationship with total step counts.

METHODS

132 participants (74♀; 35 ± 20 years; body mass index: 24.9 ± 4.0 kg•m^-2) wore an activPAL monitor 24-hr/day for up to 8-d (total: 869-d). The total steps/day, time spent stepping (0.1 s resolution; to calculate bout stepping rate), time spent stepping in 60 s epochs (step accumulation), and awake time (awake cadence) were determined. Each cadence method (in steps/min) were compared via Spearman's rank correlation. The relationships versus total step count were determined, and the strength of these relationships compared between cadence measures (95% confidence interval of correlation differences).

RESULTS

Bout stepping rate (85 ± 14 steps/min) was larger than step accumulation (34 ± 12 steps/min) and awake cadence (10 ± 5 steps/min, both: P < 0.001). Step accumulation was positively strongly related to bout stepping rate (ρ = 0.813; P < 0.001) whereas awake cadence was weakly related to bout stepping rate (ρ = 0.496; P < 0.001). Step accumulation (ρ = 0.634; P < 0.001) and awake cadence (ρ = 0.964; P < 0.001) were more related to step counts than bout stepping rate (ρ = 0.497; P < 0.001; 95% confidence intervals of correlation differences: step accumulation=0.10-0.17, awake cadence: 0.42-0.52).

SIGNIFICANCE

Without a precise measure of time spent stepping, stepping cadence is lower using the step accumulation and awake cadence methods. Step accumulation and awake cadence are more related to total step counts than bout stepping rate. Bout stepping rate outcomes reflect continuous stepping rate, does not rely on a preset epoch, and may have less overlap with step counts, which may have implications for determining the unique contributions of step count versus stepping cadence on health outcomes.

Steps per Day and All-Cause Mortality in Middle-aged Adults in the Coronary Artery Risk Development in Young Adults Study

IMPORTANCE

Steps per day is a meaningful metric for physical activity promotion in clinical and population settings. To guide promotion strategies of step goals, it is important to understand the association of steps with clinical end points, including mortality.

OBJECTIVE

To estimate the association of steps per day with premature (age 41-65 years) all-cause mortality among Black and White men and women.

DESIGN, SETTING, AND PARTICIPANTS

This prospective cohort study was part of the Coronary Artery Risk Development in Young Adults (CARDIA) study. Participants were aged 38 to 50 years and wore an accelerometer from 2005 to 2006. Participants were followed for a mean (SD) of 10.8 (0.9) years. Data were analyzed in 2020 and 2021.

EXPOSURE

Daily steps volume, classified as low (<7000 steps/d), moderate (7000-9999 steps/d), and high (≥10 000 steps/d) and stepping intensity, classified as peak 30-minute stepping rate and time spent at 100 steps/min or more.

MAIN OUTCOMES AND MEASURES

All-cause mortality.

RESULTS

A total of 2110 participants from the CARDIA study were included, with a mean (SD) age of 45.2 (3.6) years, 1205 (57.1%) women, 888 (42.1%) Black participants, and a median (interquartile range [IQR]) of 9146 (7307-11 162) steps/d. During 22 845 person years of follow-up, 72 participants (3.4%) died. Using multivariable adjusted Cox proportional hazards models, compared with participants in the low step group, there was significantly lower risk of mortality in the moderate (hazard ratio [HR], 0.28 [95% CI, 0.15-0.54]; risk difference [RD], 53 [95% CI, 27-78] events per 1000 people) and high (HR, 0.45 [95% CI, 0.25-0.81]; RD, 41 [95% CI, 15-68] events per 1000 people) step groups. Compared with the low step group, moderate/high step rate was associated with reduced risk of mortality in Black participants (HR, 0.30 [95% CI, 0.14-0.63]) and in White participants (HR, 0.37 [95% CI, 0.17-0.81]). Similarly, compared with the low step group, moderate/high step rate was associated with reduce risk of mortality in women (HR, 0.28 [95% CI, 0.12-0.63]) and men (HR, 0.42 [95% CI, 0.20-0.88]). There was no significant association between peak 30-minute intensity (lowest vs highest tertile: HR, 0.98 [95% CI, 0.54-1.77]) or time at 100 steps/min or more (lowest vs highest tertile: HR, 1.38 [95% CI, 0.73-2.61]) with risk of mortality.

CONCLUSIONS AND RELEVANCE

This cohort study found that among Black and White men and women in middle adulthood, participants who took approximately 7000 steps/d or more experienced lower mortality rates compared with participants taking fewer than 7000 steps/d. There was no association of step intensity with mortality.

Comparison of Activity Monitors Accuracy in Assessing Intermittent Outdoor Walking

PURPOSE

This study aimed to determine and compare the accuracy of different activity monitors in assessing intermittent outdoor walking in both healthy and clinical populations through the development and validation of processing methodologies.

METHODS

In study 1, an automated algorithm was implemented and tested for the detection of short (≤1 min) walking and stopping bouts during prescribed walking protocols performed by healthy subjects in environments with low and high levels of obstruction. The following parameters obtained from activity monitors were tested, with different recording epochs0.1s/0.033s/1s/3s/10s and wearing locationsscapula/hip/wrist/ankle: GlobalSat DG100 (GS) and Qstarz BT-Q1000XT/-Q1000eX (QS) speed; ActiGraph wGT3X+ (AG) vector magnitude (VM) raw data, VM counts, and steps; and StepWatch3 (SW) steps. Furthermore, linear mixed models were developed to estimate walking speeds and distances from the monitors parameters. Study 2 validated the performance of the activity monitors and processing methodologies in a clinical population showing profile of intermittent walking due to functional limitations during outdoor walking sessions.

RESULTS

In study 1, GS1s, scapula, QS1s, scapula/wrist speed, and AG0.033s, hip VM raw data provided the highest bout detection rates (>96.7%) and the lowest root mean square errors in speed (≤0.4 km·h-1) and distance (<18 m) estimation. Using SW3s, ankle steps, the root mean square error for walking/stopping duration estimation reached 13.6 min using proprietary software and 0.98 min using our algorithm (total recording duration, 282 min). In study 2, using AG0.033s, hip VM raw data, the bout detection rate (95% confidence interval) reached 100% (99%-100%), and the mean (SD) absolute percentage errors in speed and distance estimation were 9% (6.6%) and 12.5% (7.9%), respectively.

CONCLUSIONS

GPS receivers and AG demonstrated high performance in assessing intermittent outdoor walking in both healthy and clinical populations.

A Home-Based Mobile Health Intervention to Replace Sedentary Time With Light Physical Activity in Older Cancer Survivors: Randomized Controlled Pilot Trial

Background

Older cancer survivors are at risk of the development or worsening of both age- and treatment-related morbidity. Sedentary behavior increases the risk of or exacerbates these chronic conditions. Light-intensity physical activity (LPA) is more common in older adults and is associated with better health and well-being. Thus, replacing sedentary time with LPA may provide a more successful strategy to reduce sedentary time and increase physical activity.

Objective

This study primarily aims to evaluate the feasibility, acceptability, and preliminary efficacy of a home-based mobile health (mHealth) intervention to interrupt and replace sedentary time with LPA (standing and stepping). The secondary objective of this study is to examine changes in objective measures of physical activity, physical performance, and self-reported quality of life.

Methods

Overall, 54 cancer survivors (aged 60-84 years) were randomized in a 1:1:1 allocation to the tech support intervention group, tech support plus health coaching intervention group, or waitlist control group. Intervention participants received a Jawbone UP2 activity monitor for use with their smartphone app for 13 weeks. Tech support and health coaching were provided via 5 telephone calls during the 13-week intervention. Sedentary behavior and physical activity were objectively measured using an activPAL monitor for 7 days before and after the intervention.

Results

Participants included survivors of breast cancer (21/54, 39%), prostate cancer (16/54, 30%), and a variety of other cancer types; a mean of 4.4 years (SD 1.6) had passed since their cancer diagnosis. Participants, on average, were 70 years old (SD 4.8), 55% (30/54) female, 24% (13/54) Hispanic, and 81% (44/54) overweight or obese. Malfunction of the Jawbone trackers occurred in one-third of the intervention group, resulting in enrollment stopping at 54 rather than the initial goal of 60 participants. Despite these technical issues, the retention in the intervention was high (47/54, 87%). Adherence was high for wearing the tracker (29/29, 100%) and checking the app daily (28/29, 96%) but low for specific aspects related to the sedentary features of the tracker and app (21%-25%). The acceptability of the intervention was moderately high (81%). There were no significant between-group differences in total sedentary time, number of breaks, or number of prolonged sedentary bouts. There were no significant between-group differences in physical activity. The only significant within-group change occurred within the health coaching group, which increased by 1675 daily steps (95% CI 444-2906; P=.009). This increase was caused by moderate-intensity stepping rather than light-intensity stepping (+15.2 minutes per day; 95% CI 4.1-26.2; P=.008).

Conclusions

A home-based mHealth program to disrupt and replace sedentary time with stepping was feasible among and acceptable to older cancer survivors. Future studies are needed to evaluate the optimal approach for replacing sedentary behavior with standing and/or physical activity in this population.

Trial Registration

ClinicalTrials.gov NCT03632694; https://clinicaltrials.gov/ct2/show/NCT03632694

Movement at work: A comparison of real time location system, accelerometer and observational data from an office work environment

Office workers can spend significant periods of time being stationary whilst at work, with potentially serious health consequences. The development of effective health interventions could be aided by a greater understanding of the location and environmental context in which this stationary behaviour occurs. Real time location systems (RTLS) potentially offer the opportunity to gather this much needed information, but they have not been extensively trialled in office workplaces, nor rigorously compared against more familiar devices such as accelerometers. The aim of this paper was to determine whether an RTLS can measure and spatially locate the non-stationary and stationary behaviours of adults working in an office work environment. Data collected from a series of comparison studies undertaken in a commercial office building suggests that RTLS can measure the velocity at which people are moving and locate them, when stationary, with an accuracy of 0.668 m (SD 0.389). This opens up significant opportunities to further understand how people move within buildings, the indoor physical environmental influences on that movement, and the development of effective interventions to help people to move more whilst at work.

Assessment of Free-Living Cadence Using ActiGraph Accelerometers Between Individuals With and Without Anterior Cruciate Ligament Reconstruction

CONTEXT

Anterior cruciate ligament reconstruction (ACLR) and gait speed are risk factors for developing knee osteoarthritis (OA). Measuring minute-level cadence during free-living activities may aid in identifying individuals at elevated risk of developing slow habitual gait speed and, in the long term, OA.

OBJECTIVE

To assess differences in peak 1-minute cadence and weekly time in different cadence intensities between individuals with and without ACLR.

DESIGN

Cross-sectional study.

SETTING

Short-term, free-living conditions.

PATIENTS OR OTHER PARTICIPANTS

A total of 57 participants with ACLR (34 women, 23 men; age = 20.9 ± 3.2 years, time since surgery = 28.7 ± 17.7 months) and 42 healthy control participants (22 women, 20 men; age = 20.7 ± 1.7 years).

MAIN OUTCOME MEASURE(S)

Each participant wore a physical activity monitor for 7 days. Data were collected at 30 Hz, processed in 60-second epochs, and included in the analyses if the activity monitor was worn for at least 10 hours per day over 4 days. Mean daily steps, peak 1-minute cadence, and weekly minutes spent at 60 to 79 (slow walking), 80 to 99 (medium walking), 100 to 119 (brisk walking), ≥100 (moderate- to vigorous-intensity ambulation), and ≥130 (vigorous-intensity ambulation) steps per minute were calculated. One-way analyses of covariance were conducted to determine differences between groups, controlling for height and activity-monitor wear time.

RESULTS

Those with ACLR took fewer daily steps (8422 ± 2663 versus 10 033 ± 3046 steps; P = .005) and spent fewer weekly minutes in moderate- to vigorous-intensity cadence (175.8 ± 116.5 minutes versus 218.5 ± 137.1 minutes; P = .048) than participants without ACLR. We observed no differences in minutes spent at slow (ACLR = 77.4 ± 40.5 minutes versus control = 83.9 ± 34.3 minutes; P = .88), medium (ACLR = 71.6 ± 40.2 minutes versus control = 82.9 ± 46.8 minutes; P = .56), brisk (ACLR = 115.3 ± 70.3 minutes versus control = 138.3 ± 73.3 minutes; P = .18), or vigorous-intensity (ACLR = 24.3 ± 36.5 minutes versus control = 38.1 ± 60.9 minutes; P = .10) cadences per week.

CONCLUSIONS

Participants with ACLR walked approximately 40 fewer minutes per week in moderate- to vigorous-intensity cadence than participants without ACLR. Increasing the time spent at cadence ≥100 steps per minute and overall volume of physical activity may be useful as interventional targets to help reduce the risk of early development of OA after ACLR.

Validity of accelerometry for predicting physical activity and sedentary time in ambulatory children and young adults with cerebral palsy

Background

/Objectives: This study aimed to validate five published ActiGraph (AG) cut-off points for the measurements of physical activity (PA) and sedentary time (ST) in ambulatory children and young adults with cerebral palsy (CP). Additionally, four energy expenditure (EE) prediction equations based on AG counts and activPAL (AP) steps were examined in this population, using oxygen uptake (VO₂) as the criterion.

Methods

Four male and six female participants with CP (Gross Motor Function Classification System levels I-III, ages 9-21 years) completed seven activities while simultaneously wearing an AG, AP monitor and indirect calorimetry unit. VO₂ was measured on a breath-by-breath basis using the indirect calorimetry and was converted into EE using metabolic equivalents. AG counts were classified as sedentary, light PA (LPA) or moderate-to-vigorous PA (MVPA) using five cut-off points: Puyau, Evenson, Romanzini, Clanchy and Baque. The predicted EE was computed using three AG-based equations (Freedson, Trost and Treuth) and an AP step-based equation.

Results

Based on 1920 available data points from the 10 participants, Baque (r = 0.896, κ = 0.773) and Clanchy (r = 0.935, κ = 0.721) AG cut-off points classified PA and ST most accurately. All the equations overestimated EE during sitting activities and underestimated EE during rapid walking. The Freedson, Treuth and AP equations exhibited systematic bias during rapid walking, as their differences from the criterion measure increased progressively with increasing activity intensity.

Conclusions

The AG accurately classified PA and ST when the Baque and Clanchy cut-off points were used. However, none of the available AG or AP equations accurately predicted the EE during PA and ST in children and young adults with CP. Further development is needed to ensure that both devices can estimate EE accurately in this population.

The Bout Cadence Method Improves the Quantification of Stepping Cadence In Free-Living Conditions

BACKGROUND

Existing analytical approaches used to measure free-living stepping cadence (steps per minute; spm) characterize stepping two-ways: 1) 60 s epochs without considering time spent stepping during the epoch (step accumulation; SA), or 2) a bout-based analysis that considers both number of steps and time spent stepping during stepping bouts (total event cadence; TEC). SA and TEC may incorrectly characterize cadence in epochs that do not consist of continuous stepping or if there are marked changes in cadence within a stepping bout, respectively.

RESEARCH QUESTION

How does a bout-based analytical method that examines each stepping bout individually and considers within-bout changes in stepping cadence during epochs ≥120 s (Bout Cadence; BC) compare to SA and TEC?

METHODS

ActivPAL™-derived data from 122 participants were analyzed (790 total days). SA and TEC were calculated according to previous literature. BC calculated cadence bout-by-bout and stride-by-stride for bouts lasting <120 s and ≥120 s, respectively. Time spent stepping between 0-140 spm (divided into 20 spm bins) or >140 spm were determined for each method. Time spent in slow (0-80 spm), medium (80-120 spm) and fast (>120 spm) cadences for each method were compared via Bland-Altman analyses.

RESULTS

Almost half (43 %) of the total number of 60 s epochs included ≥2 stepping bouts, and 37 % of total stepping time was accumulated in continuous stepping bouts ≥120 s. Compared to TEC, BC identified more daily time spent in the 20-40 spm and >120 spm cadence bins, but less time spent in the 60-120 spm range. Both SA (fixed bias: -11.0 ± 12.4 min/day) and TEC (fixed bias: -10.0 ± 13.6 min/day) underestimated faster stepping cadences compared to BC.

SIGNIFICANCE

Existing analytical approaches largely underestimate faster stepping cadences, resulting in inaccurate measurements of vigorous-intensity stepping activity. The BC better characterizes higher intensity stepping activity, which could have important implications for assessing participants' true habitual stepping activity levels.

Wearable Sensors Quantify Mobility in People With Lower Limb Amputation During Daily Life

It is necessary to effectively assess functional mobility for appropriate prosthetic prescription and post-amputation rehabilitation. As part of this process, patients' ability for variable cadence and community ambulation are assessed in-clinic, often through visual assessments and without objective standards. The purpose of this study was to explore the clinical viability of using wearable sensors to characterize the functional mobility of people with lower limb amputation. We collected inertial measurement unit (IMU) and global positioning system (GPS) data over two weeks, from 17 individuals with lower limb amputation and 14 healthy non-amputee controls. We calculated stride-by-stride cadence, walking speed and stride lengths, along with whether they occurred in or out of the home. Self-selected walking speed was also assessed in the lab. Compared to the lab, both groups walked slower and with a lower cadence during their daily lives. There were no differences in cadence variability between groups or between strides taken in and out of the home. Both groups walked faster and with greater stride lengths away from the homes. The results suggest that functional capacity measured in the lab was not necessarily reflected in routine walking during daily life. The walking measures derived in this approach can be used to aid in the prosthetic prescription process or in the assessment of different interventions.

Association of Daily Step Count and Step Intensity With Mortality Among US Adults

IMPORTANCE

It is unclear whether the number of steps per day and the intensity of stepping are associated with lower mortality.

OBJECTIVE

Describe the dose-response relationship between step count and intensity and mortality.

DESIGN, SETTING, AND PARTICIPANTS

Representative sample of US adults aged at least 40 years in the National Health and Nutrition Examination Survey who wore an accelerometer for up to 7 days ( from 2003-2006). Mortality was ascertained through December 2015.

EXPOSURES

Accelerometer-measured number of steps per day and 3 step intensity measures (extended bout cadence, peak 30-minute cadence, and peak 1-minute cadence [steps/min]). Accelerometer data were based on measurements obtained during a 7-day period at baseline.

MAIN OUTCOMES AND MEASURES

The primary outcome was all-cause mortality. Secondary outcomes were cardiovascular disease (CVD) and cancer mortality. Hazard ratios (HRs), mortality rates, and 95% CIs were estimated using cubic splines and quartile classifications adjusting for age; sex; race/ethnicity; education; diet; smoking status; body mass index; self-reported health; mobility limitations; and diagnoses of diabetes, stroke, heart disease, heart failure, cancer, chronic bronchitis, and emphysema.

RESULTS

A total of 4840 participants (mean age, 56.8 years; 2435 [54%] women; 1732 [36%] individuals with obesity) wore accelerometers for a mean of 5.7 days for a mean of 14.4 hours per day. The mean number of steps per day was 9124. There were 1165 deaths over a mean 10.1 years of follow-up, including 406 CVD and 283 cancer deaths. The unadjusted incidence density for all-cause mortality was 76.7 per 1000 person-years (419 deaths) for the 655 individuals who took less than 4000 steps per day; 21.4 per 1000 person-years (488 deaths) for the 1727 individuals who took 4000 to 7999 steps per day; 6.9 per 1000 person-years (176 deaths) for the 1539 individuals who took 8000 to 11 999 steps per day; and 4.8 per 1000 person-years (82 deaths) for the 919 individuals who took at least 12 000 steps per day. Compared with taking 4000 steps per day, taking 8000 steps per day was associated with significantly lower all-cause mortality (HR, 0.49 [95% CI, 0.44-0.55]), as was taking 12 000 steps per day (HR, 0.35 [95% CI, 0.28-0.45]). Unadjusted incidence density for all-cause mortality by peak 30 cadence was 32.9 per 1000 person-years (406 deaths) for the 1080 individuals who took 18.5 to 56.0 steps per minute; 12.6 per 1000 person-years (207 deaths) for the 1153 individuals who took 56.1 to 69.2 steps per minute; 6.8 per 1000 person-years (124 deaths) for the 1074 individuals who took 69.3 to 82.8 steps per minute; and 5.3 per 1000 person-years (108 deaths) for the 1037 individuals who took 82.9 to 149.5 steps per minute. Greater step intensity was not significantly associated with lower mortality after adjustment for total steps per day (eg, highest vs lowest quartile of peak 30 cadence: HR, 0.90 [95% CI, 0.65-1.27]; P value for trend = .34).

CONCLUSIONS AND RELEVANCE

Based on a representative sample of US adults, a greater number of daily steps was significantly associated with lower all-cause mortality. There was no significant association between step intensity and mortality after adjusting for total steps per day.

Improvements in Objectively Measured Activity Behaviors Do Not Correlate With Improvements in Patient-Reported Outcome Measures Following Total Knee Arthroplasty

BACKGROUND

Activity monitors have added a new dimension to our ability to objectively measure physical activity in patients undergoing total knee arthroplasty (TKA). The aim of the study is to assess whether changes in the time spent sitting, standing, and stepping were associated with changes in patient-reported outcome measures (PROMs) before and after TKA.

METHODS

Valid activPAL data (>3 days) and PROMs were obtained from 49 men and women (mean [SD] age, 62.8 [8.6] years; body mass index, 33.8 [7.1] kg/m²) who underwent primary TKA, before and at 6 weeks or 6 months after surgery. Patient-reported symptoms of pain, stiffness, and knee function were obtained using the Knee injury and Osteoarthritis Outcome Score and Oxford Knee Score questionnaires.

RESULTS

Mean (SD) Knee injury and Osteoarthritis Outcome Score (80.1 [16.3] to 41.6 [6.5], P < .001) and Oxford Knee Score (12.0 [9.8] to 17.7 [22.8], P < .001) scores improved 6 months after TKA. Walking time (mean [95% confidence interval]; min/d) increased from before (79 [67-91]) to 6 months after TKA (101 [88-114], P = .006). Standing time (318 [276-360] to 321 [291-352], P = .782) and sitting time (545 [491-599] to 509.0 [459.7-558.3], P = .285) did not change from before to 6 months after TKA. Participants took more steps (2559 [2128-2991] to 3515 [2983-4048] steps/day, P = .001) and accumulated more steps (31 [30-34] to 34 [33-35] steps/min, P < .001) after TKA compared to before. There were no associations between changes in activity behaviors and changes in PROMs (P > .05).

CONCLUSION

Despite improvements in self-reported knee pain and functional ability, these changes do not correlate with improvements in objectively measured light-intensity and sedentary activity behaviors.

Comparability of ActivPAL-Based Estimates of Meeting Physical Activity Guidelines for Preschool Children

The activPAL (PAL Technologies, Glasgow, UK) has been increasingly used on children to assess sedentary time and physical activity (PA). However, there is no consensus on how it can estimate PA at different intensities. This study compared three commonly used, activPAL-based classifications of moderate-to-vigorous physical activity (MVPA) (daily steps, acceleration counts, and step rate) in determining compliance with the World Health Organization (WHO)’s PA guidelines for preschool children on a daily basis. One hundred and fourteen preschool children aged 3–6 years wore an activPAL^TM for 24 h over 7 consecutive days and provided valid data for a total of 548 days. MVPA was calculated based on published cut-points of counts (MVPA-counts) and step rate (MVPA-step rate). Compliance with standard PA guidelines (≥180 min/day of PA including ≥60 min/day of MVPA) was determined based on three criteria: ≥11,500 steps/day, a threshold of 1418 acceleration counts/15 s, and 25 steps/15 s for MVPA. Applying cut-points of daily steps and acceleration counts provided the same estimates of compliance with the WHO PA guidelines (20%), while the estimated compliance based on the step rate was lower (7.7%). There was a moderate agreement between the daily steps- (or counts-) derived and step rate-derived compliances (κ = 0.41; 95% confidence interval (CI): 0.31, 0.51). The amount of MVPA derived from counts (1.95 ± 0.72 h/day) was significantly higher than that from step rates (0.47 ± 0.31 h/day). The activPAL may be useful for surveillance studies to estimate total PA in preschool children. Further development of the activPAL algorithms based on either counts or step rate is warranted before it can be used to accurately estimate MVPA in this age group.

Cardiometabolic thresholds for peak 30-min cadence and steps/day

PURPOSE

To provide empirically-supported thresholds for step-based intensity (i.e., peak 30-min cadence; average of the top 30 steps/min in a day) and steps/day in relation to cardiometabolic health outcomes.

METHODS

Receiver operating characteristic curve analysis was applied to the National Health and Nutrition Examination Survey (NHANES) 2005-2006 accelerometer-derived step data to determine steps/day and peak 30-min cadence as risk screening values (i.e., thresholds) for fasting glucose, body mass index, waist circumference, high blood pressure, triglycerides, and HDL cholesterol. Thresholds for peak 30-min cadence and steps/day were derived that, when exceeded, classify the absence of each cardiometabolic risk factor. Additionally, logistic regression models that included the influence of age and smoking were developed using the sample weights, primary sampling units (PSUs), and stratification variables provided by the NHANES survey. Finally, a decision tree analysis was performed to delineate criteria for at-risk versus healthy populations using cadence bands.

RESULTS

Peak 30-min cadence thresholds across cardiometabolic outcomes ranged from 66-72 steps/min. Steps/day thresholds ranged from 4325-6192 steps/day. Higher thresholds were observed in men compared to women. In men, higher steps/day thresholds were observed in age ranges of 30-39, while in women, higher thresholds were observed in the age-range 50-59 years. Decision trees for classifying being at low risk for metabolic syndrome contained one risk-free leaf at higher cadence bands, specifically for any time accumulated at ≥120 steps/min.

CONCLUSIONS

Minimum thresholds representing absence of cardiometabolic risk range from 4325-6192 steps/day and 66-72 steps/min for peak 30-min cadence. Any time accumulated at ≥120 steps/min was associated with an absence of cardiometabolic risk. Although based on cross-sectional data, these thresholds represent potentially important and clinically interpretable daily physical activity goals.

Week and Weekend Day Cadence Patterns Long-Term Post-Bariatric Surgery

Obesity can negatively influence walking cadence, reducing the overall intensity of daily activities and increasing the risk of weight gain.

PURPOSE

Objectively describe the walking cadence of individuals' long-term post-bariatric surgery.

METHODS

Fifty-eight participants, 51.2 ± 8.9 years old, with a BMI of 34.6 ± 10.1 kg/m², 10.0 ± 3.1 years post-surgery wore an activPAL accelerometer for 7 consecutive days. Data was analyzed using participants' current BMI, dichotomized by obesity status, < or ≥ 30 kg/m².

RESULTS

On average, participants walked 5124 ± 2549 steps/day on weekdays and 6097 ± 2786 steps/day on weekend days (p = .003). Participants spent the majority (75%) of their daily steps at a slow-walking average cadence (non-obese: week = 65.3 ± 5.0 steps/min and weekend = 63.8 ± 6.7 steps/min; obese: week = 67.8 ± 8.2 steps/min and weekend = 63.3 ± 6.9 steps/min), with no difference between groups for week or weekend days (p = .153 and .774). The cadence of participants with obesity was significantly lower on weekends compared to weekdays for walking events > 30 s (p = .002) and > 60 s (p = .008) in duration. Weekday cadence of participants without obesity was similar to weekend day cadence across all walking event durations. The majority of walking events occurred below 30 s in duration for all participants.

CONCLUSIONS

Long-term post-bariatric surgery, movement occurs in short duration bouts at a slow-walking cadence for the majority of movement. Individuals without obesity had similar movement patterns from week to weekend days while participants with obesity significantly lowered their cadence on weekend days.

Sensor Data Acquisition and Multimodal Sensor Fusion for Human Activity Recognition Using Deep Learning

In this paper, we perform a systematic study about the on-body sensor positioning and data acquisition details for Human Activity Recognition (HAR) systems. We build a testbed that consists of eight body-worn Inertial Measurement Units (IMU) sensors and an Android mobile device for activity data collection. We develop a Long Short-Term Memory (LSTM) network framework to support training of a deep learning model on human activity data, which is acquired in both real-world and controlled environments. From the experiment results, we identify that activity data with sampling rate as low as 10 Hz from four sensors at both sides of wrists, right ankle, and waist is sufficient in recognizing Activities of Daily Living (ADLs) including eating and driving activity. We adopt a two-level ensemble model to combine class-probabilities of multiple sensor modalities, and demonstrate that a classifier-level sensor fusion technique can improve the classification performance. By analyzing the accuracy of each sensor on different types of activity, we elaborate custom weights for multimodal sensor fusion that reflect the characteristic of individual activities.

Gait Type Analysis Using Dynamic Bayesian Networks

This paper focuses on gait abnormality type identification—specifically, recognizing antalgic gait. Through experimentation, we demonstrate that detecting an individual’s gait type is a viable biometric that can be used along with other common biometrics for applications such as forensics. To classify gait, the gait data is represented by coordinates that reflect the body joint coordinates obtained using a Microsoft Kinect v2 system. Features such as cadence, stride length, and other various joint angles are extracted from the input data. Using approaches such as the dynamic Bayesian network, the obtained features are used to model as well as perform gait type classification. The proposed approach is compared with other classification techniques and experimental results reveal that it is capable of obtaining a 88.68% recognition rate. The results illustrate the potential of using a dynamic Bayesian network for gait abnormality classification.

How fast is fast enough? Walking cadence (steps/min) as a practical estimate of intensity in adults: a narrative review

Background

Cadence (steps/min) may be a reasonable proxy-indicator of ambulatory intensity. A summary of current evidence is needed for cadence-based metrics supporting benchmark (standard or point of reference) and threshold (minimums associated with desired outcomes) values that are informed by a systematic process.

Objective

To review how fast, in terms of cadence, is enough, with reference to crafting public health recommendations in adults.

Methods

A comprehensive search strategy was conducted to identify relevant studies focused on walking cadence and intensity for adults. Identified studies (n=38) included controlled (n=11), free-living observational (n=18) and intervention (n=9) designs.

Results

There was a strong relationship between cadence (as measured by direct observation and objective assessments) and intensity (indirect calorimetry). Despite acknowledged interindividual variability, ≥100 steps/min is a consistent heuristic (e.g, evidence-based, rounded) value associated with absolutely defined moderate intensity (3 metabolic equivalents (METs)). Epidemiological studies report notably low mean daily cadences (ie, 7.7 steps/min), shaped primarily by the very large proportion of time (13.5 hours/day) spent between zero and purposeful cadences (<60 steps/min) at the population level. Published values for peak 1-min and 30-min cadences in healthy free-living adults are >100 and >70 steps/min, respectively. Peak cadence indicators are negatively associated with increased age and body mass index. Identified intervention studies used cadence to either prescribe and/or quantify ambulatory intensity but the evidence is best described as preliminary.

Conclusions

A cadence value of ≥100 steps/min in adults appears to be a consistent and reasonable heuristic answer to ’How fast is fast enough?' during sustained and rhythmic ambulatory behaviour.

Trial registration number

NCT02650258

Step Counting: A Review of Measurement Considerations and Health-Related Applications

Step counting has long been used as a method of measuring distance. Starting in the mid-1900s, researchers became interested in using steps per day to quantify ambulatory physical activity. This line of research gained momentum after 1995, with the introduction of reasonably accurate spring-levered pedometers with digital displays. Since 2010, the use of accelerometer-based “activity trackers” by private citizens has skyrocketed. Steps have several advantages as a metric for assessing physical activity: they are intuitive, easy to measure, objective, and they represent a fundamental unit of human ambulatory activity. However, since they measure a human behavior, they have inherent biological variability; this means that measurements must be made over 3–7 days to attain valid and reliable estimates. There are many different kinds of step counters, designed to be worn on various sites on the body; all of these devices have strengths and limitations. In cross-sectional studies, strong associations between steps per day and health variables have been documented. Currently, at least eight prospective, longitudinal studies using accelerometers are being conducted that may help to establish dose–response relationships between steps/day and health outcomes. Longitudinal interventions using step counters have shown that they can help inactive individuals to increase by 2500 steps per day. Step counting is useful for surveillance, and studies have been conducted in a number of countries around the world. Future challenges include the need to establish testing protocols and accuracy standards, and to decide upon the best placement sites. These challenges should be addressed in order to achieve harmonization between studies, and to accurately quantify dose–response relationships.

Free-living and laboratory gait characteristics in patients with multiple sclerosis

Background

Wearable sensors offer the potential to bring new knowledge to inform interventions in patients affected by multiple sclerosis (MS) by thoroughly quantifying gait characteristics and gait deficits from prolonged daily living measurements. The aim of this study was to characterise gait in both laboratory and daily life conditions for a group of patients with moderate to severe ambulatory impairment due to MS. To this purpose, algorithms to detect and characterise gait from wearable inertial sensors data were also validated.

Methods

Fourteen patients with MS were divided into two groups according to their disability level (EDSS 6.5–6.0 and EDSS 5.5–5.0, respectively). They performed both intermittent and continuous walking bouts (WBs) in a gait laboratory wearing waist and shank mounted inertial sensors. An algorithm (W-CWT) to estimate gait events and temporal parameters (mean and variability values) using data recorded from the waist mounted sensor (Dynaport, Mc Roberts) was tested against a reference algorithm (S-REF) based on the shank-worn sensors (OPAL, APDM). Subsequently, the accuracy of another algorithm (W-PAM) to detect and classify WBs was also tested. The validated algorithms were then used to quantify gait characteristics during short (sWB, 5–50 steps), intermediate (iWB, 51–100 steps) and long (lWB, >100 steps) daily living WBs and laboratory walking. Group means were compared using a two-way ANOVA.

Results

W-CWT compared to S-REF showed good gait event accuracy (0.05–0.10 s absolute error) and was not influenced by disability level. It slightly overestimated stride time in intermittent walking (0.012 s) and overestimated highly variability of temporal parameters in both intermittent (17.5%–58.2%) and continuous walking (11.2%–76.7%). The accuracy of W-PAM was speed-dependent and decreased with increasing disability. The ANOVA analysis showed that patients walked at a slower pace in daily living than in the laboratory. In daily living gait, all mean temporal parameters decreased as the WB duration increased. In the sWB, the patients with a lower disability score showed, on average, lower values of the temporal parameters. Variability decreased as the WB duration increased.

Conclusions

This study validated a method to quantify walking in real life in people with MS and showed how gait characteristics estimated from short walking bouts during daily living may be the most informative to quantify level of disability and effects of interventions in patients moderately affected by MS. The study provides a robust approach for the quantification of recognised clinically relevant outcomes and an innovative perspective in the study of real life walking.

"What Is a Step?" Differences in How a Step Is Detected among Three Popular Activity Monitors That Have Impacted Physical Activity Research

(1) Background: This study compared manually-counted treadmill walking steps from the hip-worn DigiwalkerSW200 and OmronHJ720ITC, and hip and wrist-worn ActiGraph GT3X+ and GT9X; determined brand-specific acceleration amplitude (g) and/or frequency (Hz) step-detection thresholds; and quantified key features of the acceleration signal during walking. (2) Methods: Twenty participants (Age: 26.7 ± 4.9 years) performed treadmill walking between 0.89-to-1.79 m/s (2–4 mph) while wearing a hip-worn DigiwalkerSW200, OmronHJ720ITC, GT3X+ and GT9X, and a wrist-worn GT3X+ and GT9X. A DigiwalkerSW200 and OmronHJ720ITC underwent shaker testing to determine device-specific frequency and amplitude step-detection thresholds. Simulated signal testing was used to determine thresholds for the ActiGraph step algorithm. Steps during human testing were compared using bias and confidence intervals. (3) Results: The OmronHJ720ITC was most accurate during treadmill walking. Hip and wrist-worn ActiGraph outputs were significantly different from the criterion. The DigiwalkerSW200 records steps for movements with a total acceleration of ≥1.21 g. The OmronHJ720ITC detects a step when movement has an acceleration ≥0.10 g with a dominant frequency of ≥1 Hz. The step-threshold for the ActiLife algorithm is variable based on signal frequency. Acceleration signals at the hip and wrist have distinctive patterns during treadmill walking. (4) Conclusions: Three common research-grade physical activity monitors employ different step-detection strategies, which causes variability in step output.

Prediction of sustained harmonic walking in the free-living environment using raw accelerometry data

OBJECTIVE

Using raw, sub-second-level accelerometry data, we propose and validate a method for identifying and characterizing walking in the free-living environment. We focus on sustained harmonic walking (SHW), which we define as walking for at least 10 s with low variability of step frequency.

APPROACH

We utilize the harmonic nature of SHW and quantify the local periodicity of the tri-axial raw accelerometry data. We also estimate the fundamental frequency of the observed signals and link it to the instantaneous walking (step-to-step) frequency (IWF). Next, we report the total time spent in SHW, number and durations of SHW bouts, time of the day when SHW occurred, and IWF for 49 healthy, elderly individuals.

MAIN RESULTS

The sensitivity of the proposed classification method was found to be 97%, while specificity ranged between 87% and 97% and the prediction accuracy ranged between 94% and 97%. We report the total time in SHW between 140 and 10 min d^-1 distributed between 340 and 50 bouts. We estimate the average IWF to be 1.7 steps-per-second.

SIGNIFICANCE

We propose a simple approach for the detection of SHW and estimation of IWF, based on Fourier decomposition.

The activPALTM Accurately Classifies Activity Intensity Categories in Healthy Adults

The activPAL (AP) monitor is well established for distinguishing sitting, standing, and stepping time. However, its validity in predicting time in physical activity intensity categories in a free-living environment has not been determined.

PURPOSE

This study aimed to determine the validity of the AP in estimating time spent in sedentary, light, and moderate-to-vigorous physical activity (MVPA) in a free-living environment.

METHODS

Thirteen participants (mean ± SD age = 24.8 ± 5.2 yr, BMI = 23.8 ± 1.9 kg·m) were directly observed for three 10-h periods wearing an AP. A custom R program was developed and used to summarize detailed active and sedentary behavior variables from the AP. AP estimates were compared with direct observation.

RESULTS

The AP accurately and precisely estimated time in activity intensity categories (bias [95% confidence interval]; sedentary = 0.8 min [-2.9 to 4.5], light = 1.7 min [2.2-5.7], and -2.6 min [-5.8 to 0.7]). The overall accuracy rate for time in intensity categories was 96.2%. The AP also accurately estimated guideline minutes, guideline bouts, prolonged sitting minutes, and prolonged sitting bouts.

CONCLUSION

The AP can be used to accurately capture individualized estimates of active and sedentary behavior variables in free-living settings.

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.

Walking Cadence to Exercise at Moderate Intensity for Adults: A Systematic Review

Background. Most adults choose walking as a leisure activity. However, many do not reach the international physical activity guidelines for adults, which recommend moderate intensity aerobic activity for at least 150 minutes/week in bouts of 10 minutes. Purpose. This systematic review provides an update on the walking cadence required to reach moderate intensity in adults and older adults, identifies variables associated with reaching moderate intensity, and evaluates how walking cadence intensity should be measured, but the main purpose is to report the interventions that have been attempted to prescribe walking cadence to increase time spent at moderate intensity or other outcomes for adults and older adults. Methods. SportDISCUS, Scopus, and PubMed databases were searched. We identified 3,917 articles and 31 were retained for this systematic review. Only articles written in English were included. Results. In general, 100 steps/minute is prescribed for adults to achieve moderate intensity, but older adults may require a higher cadence. Currently, few studies have explored using walking cadence prescription as an intervention to increase physical activity levels. Conclusion. Prescribing walking cadence as a way to increase physical activity levels has potential as a practical and useful strategy, but more evidence is required to assess its ability to increase physical activity levels at moderate intensity.

Do older adults with higher daily ambulatory activity have lower central blood pressure?

BACKGROUND AND AIMS

We aimed to test the hypothesis that central blood pressure (BP) would be lower in healthy older adults with greater daily ambulatory activity.

METHODS

Forty-three (24 women, 19 men) older adults wore a triaxial accelerometer at the hip for 1 week. The volume of ambulatory activity was estimated by average steps per day. As a proxy of intensity of ambulatory activity, 1-min peak step accumulation, or the maximum number of steps taken within a minute was averaged from each day. Participants were considered "active" if they had >7500 steps per day or >105 steps per min. Radial arterial tonometry was used to estimate central (aortic) BP from pulse wave analysis.

RESULTS

After adjusting for age and sex, adults with higher steps per day (n = 18) tended to have lower central pulse pressure (p = 0.08). Interestingly, adults with higher peak step accumulation (n = 25) had significantly lower central pulse pressure (40.4 ± 1.6 vs. 46.8 ± 2.0 mmHg; p = 0.02) after adjusting for age and sex. Stepwise regression including age, sex, body mass index, and peak step accumulation found body mass index to be the strongest predictor of central systolic BP [β = 0.42, 95 % CI (0.13, 0.70), p = 0.004] while peak step accumulation was the strongest predictor of central pulse pressure [β = -0.31, 95 % CI (-0.01, -0.60), p = 0.043].

CONCLUSIONS

These results find older adults with an "active" daily walking pattern, particularly having a higher number of maximal steps in a minute, have lower central pulse pressure than older adults with lower daily ambulatory activity.

Understanding walking activity in multiple sclerosis: step count, walking intensity and uninterrupted walking activity duration related to degree of disability

In multiple sclerosis (MS), physical activity (PA) is most commonly measured as number of steps, while also walking intensity and walking activity duration are keys for a healthy lifestyle. The aim of this study was to investigate (1) the number of steps persons with MS (PwMS) take; (2) the number of steps they take at low and moderate intensity; and (3) their walking activity duration for 2, 3, 6, 10, 12 and 14 uninterrupted minutes; all related to the degree of disability. 64 PwMS participated, distinguished in a mild (n = 31) and moderate MS subgroup (n = 34) based on their ambulatory dysfunction (Disease Steps). Standardized clinical tests were performed, and step data from the StepWatch Activity Monitor were collected for seven consecutive days. The results showed that (1) step count in PwMS was lower than PA recommendations, and is negatively influenced by a higher disability degree. (2) No walking was registered during 77 % of the day. PwMS are making steps for 22 % at low and only 1 % at moderate intensity. (3) Both MS subgroups rarely walk for more than six uninterrupted minutes, especially not at moderate intensity. PwMS need to be encouraged to make steps at moderate intensity, and to make steps for longer periods of time (minimal ten uninterrupted minutes).

Decline in physical activity during adolescence is not associated with changes in mental health

Background

The majority of studies investigating associations between physical activity and mental health in adolescents have been cross-sectional in design. Potential associations between physical activity and mental health may be better examined longitudinally as physical activity levels tend to decrease in adolescence. Few studies have investigated these associations longitudinally in adolescents and none by measuring physical activity objectively.

Methods

A total of 158 Dutch adolescents (mean age 13.6 years, 38.6 % boys, grades 7 and 9 at baseline) participated in this longitudinal study. Physical activity, depressive symptoms and self-esteem were measured at baseline and at the 1-year follow-up. Physical activity was objectively measured with an ActivPAL3™ accelerometer during one full week. Depressive symptoms were measured with the Center for Epidemiologic Studies Depression Scale (CES-D) and self-esteem was assessed with the Rosenberg Self-Esteem Scale (RSE). Results were analysed using structural equation modelling.

Results

Physical activity levels decreased 15.3 % over a 1-year period (p < .001), with significantly (p = .001) greater decreases during grade 7 (-20.7 %) than during grade 9 (-5.0 %). Overall, depressive symptoms decreased (-12.1 %, p < .001) over a 1-year period, while self-esteem did not change significantly (+2.9 %, p = .066). Higher levels of depressive symptoms at baseline predicted a greater decline in depressive symptoms (β = -.51, p < .001) and higher levels of self-esteem at baseline predicted a smaller increase in self-esteem (β = -.48, p < .001). The decline in physical activity did not appear to predict any change in depressive symptoms and self-esteem.

Conclusion

The decline in physical activity over a 1-year period during adolescence is not associated with a change in mental health. Further studies in adolescents aiming to investigate whether a change in physical activity is associated with a change in mental health should control for baseline levels of mental health and academic year differences.

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.

Pattern changes in step count accumulation and peak cadence due to a physical activity intervention

OBJECTIVES

The purpose was to determine if a 12-week weight loss intervention with a physical activity (PA) component would lead to changes in steps/day, step count accumulation patterns, and peak cadence.

DESIGN

Randomized clinical trial.

METHODS

Overall, 121 overweight/obese White and African-American adults (ages 35-64yrs) were randomized to a diet education plus PA education and behavior change intervention group (DE+PA) or diet education and behavior change group (DE). The DE+PA intervention was designed to increase steps/day, and steps at moderate-to-vigorous intensity. The Actigraph GT3X+ accelerometer was used to measure steps accumulated in different cadence bands (1-19, 20-39, 40-59, 60-79, 80-99, 100-119, 120+ steps/min), and peak 1-min, 30-min and 60-min cadence. Pre- to post-intervention changes in steps/day, step count within each cadence band, and peak cadences were compared within groups using paired sample t-test and between groups after adjustment for baseline values of the same variable using ANCOVA.

RESULTS

Ninety participants had valid data (44 in the DE+PA group). Change in steps/day was not significantly different between the groups. However, participants in the DE+PA group accumulated significantly more steps at post-intervention in the 80-99, 100-119, and 120+ cadence bands, all p<0.02. The DE+PA group increased step counts accumulated within the 100-119 (463±1092 vs 56±546 step counts; p=0.01) and 120+ (390±999 vs 34±321 step counts; p=0.03) cadence bands, as well as peak 60-min cadence when compared to the DE group.

CONCLUSIONS

Non-significant changes in steps/day following a PA intervention may mask changes in steps accumulated at moderate-to-vigorous intensity cadences.

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.