Can quantifying the relative intensity of a person's free-living physical activity predict how they respond to a physical activity intervention? Findings from the PACES RCT.

OBJECTIVES: To determine whether quantifying both the absolute and relative intensity of accelerometer-assessed physical activity (PA) can inform PA interventions. We hypothesised that individuals whose free-living PA is at a low relative intensity are more likely to increase PA in response to an intervention, as they have spare physical capacity. METHOD: We conducted a secondary data analysis of a 12-month randomised controlled trial, Physical Activity after Cardiac EventS, which was designed to increase PA but showed no improvement. Participants (N=239, 86% male; age 66.4 (9.7); control N=126, intervention N=113) wore accelerometers for 7 days and performed the incremental shuttle walk test (ISWT) at baseline and 12 months. PA intensity was expressed in absolute terms (intensity gradient) and relative to acceleration at maximal physical capacity (predicted from an individual's maximal ISWT walking speed). PA outcomes were volume and absolute intensity gradient. RESULTS: At baseline, ISWT performance was positively correlated with PA volume (r=0.50, p<0.001) and absolute intensity (r=0.50, p<0.001), but negatively correlated with relative intensity (r=-0.13, p=0.025). Relative intensity of PA at baseline moderated the change in absolute intensity (p=0.017), but not volume, of PA postintervention. Low relative intensity at baseline was associated with increased absolute intensity gradient (+0.5 SD), while high relative intensity at baseline was associated with decreased absolute intensity gradient (-0.5 SD). CONCLUSION: Those with low relative intensity of PA were more likely to increase their absolute PA intensity gradient in response to an intervention. Quantifying absolute and relative PA intensity of PA could improve enables personalisation of interventions.

Snacktivity™ to promote physical activity and reduce future risk of disease in the population: protocol for a feasibility randomised controlled trial and nested qualitative study.

BACKGROUND: Many people do not regularly participate in physical activity, which may negatively impact their health. Current physical activity guidelines are focused on promoting weekly accumulation of at least 150 min of moderate to vigorous intensity physical activity (MVPA). Whilst revised guidance now recognises the importance of making small changes to physical activity behaviour, guidance still focuses on adults needing to achieve at least 150 min of MVPA per week. An alternative 'whole day' approach that could motivate the public to be more physically active, is a concept called Snacktivity™. Instead of focusing on achieving 150 min per week of physical activity, for example 30 min of MVPA over 5 days, Snacktivity™ encourages the public to achieve this through small, but frequent, 2-5 min 'snacks' of MVPA throughout the whole day. METHODS: The primary aim is to undertake a feasibility trial with nested qualitative interviews to assess the feasibility and acceptability of the Snacktivity™ intervention to inform the design of a subsequent phase III randomised trial. A two-arm randomised controlled feasibility trial aiming to recruit 80 inactive adults will be conducted. Recruitment will be from health and community settings and social media. Participants will be individually randomised (1:1 ratio) to receive either the Snacktivity™ intervention or usual care. The intervention will last 12 weeks with assessment of outcomes completed before and after the intervention in all participants. We are interested in whether the Snacktivity™ trial is appealing to participants (assessed by the recruitment rate) and if the Snacktivity™ intervention and trial methods are acceptable to participants (assessed by Snacktivity™/physical activity adherence and retention rates). The intervention will be delivered by health care providers within health care consultations or by researchers. Participants' experiences of the trial and intervention, and health care providers' views of delivering the intervention within health consultations will be explored. DISCUSSION: The development of physical activity interventions that can be delivered at scale are needed. The findings from this study will inform the viability and design of a phase III trial to assess the effectiveness and cost-effectiveness of Snacktivity™ to increase physical activity. TRIAL REGISTRATION: ISRCTN: 64851242.

A Case for Unifying Accelerometry-Derived Movement Behaviors and Tests of Exercise Capacity for the Assessment of Relative Physical Activity Intensity.

Albert Einstein taught us that "everything is relative." People's experience of physical activity (PA) is no different, with "relativism" particularly pertinent to the perception of intensity. Markers of absolute and relative intensities of PA have different but complimentary utilities, with absolute intensity considered best for PA guideline adherence and relative intensity for personalized exercise prescription. Under the paradigm of exercise and PA as medicine, our Technical Note proposes a method of synchronizing accelerometry with the incremental shuttle walking test to facilitate description of the intensity of the free-living PA profile in absolute and relative terms. Our approach is able to generate and distinguish "can do" or "cannot do" (based on exercise capacity) and "does do" or "does not do" (based on relative intensity PA) classifications in a chronic respiratory disease population, facilitating the selection of potential appropriate individually tailored interventions. By synchronizing direct assessments of exercise capacity and PA, clearer insights into the intensity of PA performed during everyday life can be gleaned. We believe the next steps are as follows: (1) to determine the feasibility and effectiveness of using relative and absolute intensities in combination to personalize the approach, (2) to determine its sensitivity to change following interventions (eg, exercise-based rehabilitation), and (3) to explore the use of this approach in healthier populations and in other long-term conditions.

Device-assessed sleep and physical activity in individuals recovering from a hospital admission for COVID-19: a multicentre study.

BACKGROUND: The number of individuals recovering from severe COVID-19 is increasing rapidly. However, little is known about physical behaviours that make up the 24-h cycle within these individuals. This study aimed to describe physical behaviours following hospital admission for COVID-19 at eight months post-discharge including associations with acute illness severity and ongoing symptoms. METHODS: One thousand seventy-seven patients with COVID-19 discharged from hospital between March and November 2020 were recruited. Using a 14-day wear protocol, wrist-worn accelerometers were sent to participants after a five-month follow-up assessment. Acute illness severity was assessed by the WHO clinical progression scale, and the severity of ongoing symptoms was assessed using four previously reported data-driven clinical recovery clusters. Two existing control populations of office workers and individuals with type 2 diabetes were comparators. RESULTS: Valid accelerometer data from 253 women and 462 men were included. Women engaged in a mean ± SD of 14.9 ± 14.7 min/day of moderate-to-vigorous physical activity (MVPA), with 12.1 ± 1.7 h/day spent inactive and 7.2 ± 1.1 h/day asleep. The values for men were 21.0 ± 22.3 and 12.6 ± 1.7 h /day and 6.9 ± 1.1 h/day, respectively. Over 60% of women and men did not have any days containing a 30-min bout of MVPA. Variability in sleep timing was approximately 2 h in men and women. More severe acute illness was associated with lower total activity and MVPA in recovery. The very severe recovery cluster was associated with fewer days/week containing continuous bouts of MVPA, longer total sleep time, and higher variability in sleep timing. Patients post-hospitalisation with COVID-19 had lower levels of physical activity, greater sleep variability, and lower sleep efficiency than a similarly aged cohort of office workers or those with type 2 diabetes. CONCLUSIONS: Those recovering from a hospital admission for COVID-19 have low levels of physical activity and disrupted patterns of sleep several months after discharge. Our comparative cohorts indicate that the long-term impact of COVID-19 on physical behaviours is significant.

Importance of Overall Activity and Intensity of Activity for Cardiometabolic Risk in Those with and Without a Chronic Disease.

INTRODUCTION: Higher levels of physical activity are associated with lower cardiometabolic risk. However, the relative contribution of overall activity and the intensity of activity are unclear. Our aim was to determine the relative contribution of overall activity and intensity distribution of activity to cardiometabolic risk in a cross-sectional analysis of apparently healthy office workers and in people with one or more chronic disease. METHODS: Clustered cardiometabolic risk score was calculated from mean arterial pressure, high-density lipoprotein cholesterol, triglycerides and HbA1c. Open-source software (GGIR) was used to generate average acceleration and intensity gradient from wrist-worn accelerometer data for two data sets: office-workers who did not have a self-reported medical condition ( n = 399, 70% women) and adults with one or more chronic disease ( n = 1137, 34% women). Multiple linear regression analyses were used to assess the relative contribution of overall activity and intensity of activity to cardiometabolic risk. RESULTS: When mutually adjusted, both overall activity and intensity of activity were independently associated with cardiometabolic risk in the healthy group ( P < 0.05). However, for the CD group, although mutually adjusted associations for average acceleration were significantly associated with cardiometabolic risk ( P < 0.001), intensity was not. In healthy individuals, cardiometabolic risk was lower in those with high overall activity and/or intensity of activity, and who also undertook at least 10 min brisk walking. In those with a chronic disease, risk was lower in those who undertook at least 60 min slow walking. CONCLUSIONS: These findings suggest interventions aiming to optimize cardiometabolic health in healthy adults could focus on increasing both intensity and amount of physical activity. However, in those with chronic disease, increasing the amount of activity undertaken, regardless of intensity, may be more appropriate.

Normative wrist-worn accelerometer values for self-paced walking and running: a walk in the park.

This study aimed to a) determine whether wrist acceleration varies by accelerometer brand, wear location, and age for self-paced "slow", "normal" and "brisk" walking; b) develop normative acceleration values for self-paced walking and running for adults. One-hundred-and-three adults (40-79 years) completed self-paced "slow", "normal" and "brisk" walks, while wearing three accelerometers (GENEActiv, Axivity, ActiGraph) on each wrist. A sub-sample (n = 22) completed a self-paced run. Generalized estimating equations established differences by accelerometer brand, wrist, and age-group (walking only, 40-49, 50-59, 60-69, 70-79 years) for self-paced walking and running. Brand*wrist interactions showed ActiGraph dominant wrist values were ~10% lower than GENEActiv/Axivity values for walking and running, and non-dominant ActiGraph values were ~5% lower for running only (p < 0.001). Acceleration during brisk walking was lower in those aged 70-79 (p < 0.05). Normative acceleration values (non-dominant wrist, all brands; dominant wrist GENEActiv/Axivity) for slow and normal walking were 140 mg and 210 mg. Brisk walking, values were 350 mg in those aged 40-69 years, but 270 mg in those aged 70-79 years. Accelerations >600 mg approximated running. These values facilitate user-friendly interpretation of accelerometer-determined physical activity in large cohort and epidemiological datasets.

Differences in Accelerometer-Measured Patterns of Physical Activity and Sleep/Rest Between Ethnic Groups and Age: An Analysis of UK Biobank.

BACKGROUND: Physical activity and sleep are important for health; whether device-measured physical activity and sleep differ by ethnicity is unclear. This study aimed to compare physical activity and sleep/rest in white, South Asian (SA), and black adults by age. METHODS: Physical activity and sleep/rest quality were assessed using accelerometer data from UK Biobank. Linear regressions, stratified by sex, were used to analyze differences in activity and sleep/rest. An ethnicity × age group interaction term was used to assess whether ethnic differences were consistent across age groups. RESULTS: Data from 95,914 participants, aged 45-79 years, were included. Overall activity was 7% higher in black, and 5% lower in SA individuals compared with white individuals. Minority ethnic groups had poorer sleep/rest quality. Lower physical activity and poorer sleep quality occurred at a later age in black and SA adults (>65 y), than white adults (>55 y). CONCLUSIONS: While black adults are more active, and SA adults less active, than white adults, the age-related reduction appears to be delayed in black and SA adults. Sleep/rest quality is poorer in black and SA adults than in white adults. Understanding ethnic differences in physical activity and rest differ may provide insight into chronic conditions with differing prevalence across ethnicities.

Comparing 24 h physical activity profiles: Office workers, women with a history of gestational diabetes and people with chronic disease condition(s).

This study demonstrates a novel data-driven method of summarising accelerometer data to profile physical activity in three diverse groups, compared with cut-point determined moderate-to-vigorous physical activity (MVPA). GGIR was used to generate average daily acceleration, intensity gradient, time in MVPA and MX metrics (acceleration above which the most active X-minutes accumulate) from wrist-worn accelerometer data from three datasets: office-workers (OW, N = 697), women with a history of post-gestational diabetes (PGD, N = 267) and adults with ≥1 chronic disease (CD, N = 1,325). Average acceleration and MVPA were lower in CD, but not PGD, relative to OW (-5.2 mg and -30.7 minutes, respectively, P < 0.001). Both PGD and CD had poorer intensity distributions than OW (P < 0.001). Application of a cut-point to the M30 showed 7%, 17% and 28%, of OW, PGD and CD, respectively, accumulated 30 minutes of brisk walking per day. Radar plots showed OW had higher overall activity than CD. The relatively poor intensity distribution of PGD, despite similar overall activity to OW, was due to accumulation of more light and less higher intensity activity. These data-driven methods identify aspects of activity that differ between groups, which may be missed by cut-point methods alone. Abbreviations: CD: Adults with ≥1 chronic disease; mg: Milli-gravitational unit; MVPA: Moderate-to-vigorous physical activity; OW: Office workers; PGD: Women with a history of post-gestational diabetes; VPA: Vigorous physical activity.

Physical Activity for Bone Health: How Much and/or How Hard?

PURPOSE: High-impact physical activity is associated with bone health, but higher volumes of lower-intensity activity may also be important. The aims of this study were to: 1) investigate the relative importance of volume and intensity of physical activity accumulated during late adolescence for bone health at age 23 yr; and 2) illustrate interpretation of the results. METHODS: This is a secondary analysis of data from the Iowa Bone Development Study, a longitudinal study of bone health from childhood through to young adulthood. The volume (average acceleration) and intensity distribution (intensity gradient) of activity at age 17, 19, 21, and 23 yr were calculated from raw acceleration ActiGraph data and averaged across ages. Hip areal bone mineral density (aBMD), total body bone mineral content (BMC), spine aBMD, and hip structural geometry (dual-energy X-ray absorptiometry, Hologic QDR4500A) were assessed at age 23 yr. Valid data, available for 220 participants (124 girls), were analyzed with multiple regression. To elucidate significant effects, we predicted bone outcomes when activity volume and intensity were high (+1SD), medium (mean), and low (-1SD). RESULTS: There were additive associations of volume and intensity with hip aBMD and total body BMC (low-intensity/low-volume cf. high-intensity/high-volume = [INCREMENT]0.082 g·cm and [INCREMENT]169.8 g, respectively). For males only, spine aBMD intensity was associated independently of volume (low-intensity cf. high-intensity = [INCREMENT]0.049 g·cm). For hip structural geometry, volume was associated independently of intensity (low-volume cf. high-volume = [INCREMENT]4.8-6.6%). CONCLUSIONS: The activity profile associated with optimal bone outcomes was high in intensity and volume. The variation in bone health across the activity volume and intensity distribution suggests intensity is key for aBMD and BMC, whereas high volumes of lower intensity activity may be beneficial for hip structural geometry.

Enhancing the value of accelerometer-assessed physical activity: meaningful visual comparisons of data-driven translational accelerometer metrics.

The lack of consensus on meaningful and interpretable physical activity outcomes from accelerometer data hampers comparison across studies. Cut-point analyses are simple to apply and easy to interpret but can lead to results that are not comparable. We propose that the optimal accelerometer metrics for data analysis are not the same as the optimal metrics for translation. Ideally, analytical metrics are precise continuous variables that cover the intensity spectrum, while translational metrics facilitate meaningful, public-health messages and can be described in terms of activities (e.g. brisk walking) or intensity (e.g. moderate-to-vigorous physical activity). Two analytical metrics that capture the volume and intensity of the 24-h activity profile are average acceleration (volume) and intensity gradient (intensity distribution). These allow investigation of independent, additive and interactive associations of volume and intensity of activity with health; however, they are not immediately interpretable. The MX metrics, the acceleration above which the most active X minutes are accumulated, are translational metrics that can be interpreted in terms of indicative activities. Using a range of MX metrics illustrates the intensity gradient and average acceleration (i.e. 24-h activity profile). The M120, M60, M30, M15 and M5 illustrate the most active accumulated minutes of the day, the M1/3DAY the most active accumulated 8 h of the day. We demonstrate how radar plots of MX metrics can be used to interpret and translate results from between- and within-group comparisons, provide information on meeting guidelines, assess individual activity profiles relative to percentiles and compare activity profiles between domains and/or time periods.