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 nationwide study of adults admitted to hospital with diabetic ketoacidosis or hyperosmolar hyperglycaemic state and COVID‐19

AimsTo investigate characteristics of people hospitalized with coronavirus-disease-2019 (COVID-19) and diabetic ketoacidosis (DKA) or hyperosmolar hyperglycaemic state (HHS), and to identify risk factors for mortality and intensive care admission.Materials and methodsRetrospective cohort study with anonymized data from the Association of British Clinical Diabetologists nationwide audit of hospital admissions with COVID-19 and diabetes, from start of pandemic to November 2021. The primary outcome was inpatient mortality. DKA and HHS were adjudicated against national criteria. Age-adjusted odds ratios were calculated using logistic regression.ResultsIn total, 85 confirmed DKA cases, and 20 HHS, occurred among 4073 people (211 type 1 diabetes, 3748 type 2 diabetes, 114 unknown type) hospitalized with COVID-19. Mean (SD) age was 60 (18.2) years in DKA and 74 (11.8) years in HHS (p < .001). A higher proportion of patients with HHS than with DKA were of non-White ethnicity (71.4% vs 39.0% p = .038). Mortality in DKA was 36.8% (n = 57) and 3.8% (n = 26) in type 2 and type 1 diabetes respectively. Among people with type 2 diabetes and DKA, mortality was lower in insulin users compared with non-users [21.4% vs. 52.2%; age-adjusted odds ratio 0.13 (95% CI 0.03-0.60)]. Crude mortality was lower in DKA than HHS (25.9% vs. 65.0%, p = .001) and in statin users versus non-users (36.4% vs. 100%; p = .035) but these were not statistically significant after age adjustment.ConclusionsHospitalization with COVID-19 and adjudicated DKA is four times more common than HHS but both associate with substantial mortality. There is a strong association of previous insulin therapy with survival in type 2 diabetes-associated DKA

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; 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 ages 17, 19, 21 and 23 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 (DXA, Hologic QDR4500A) were assessed at age 23.Valid data, available for 220 participants (124 females),were analysed 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 = ∆0.082g·cm-2and ∆169.8g, respectively). or males’ only spine aBMD intensity was associated independently of volume(low-intensity cf. high-intensity = ∆0.049g.cm-2). For hip structural geometry, volume was associated independently of intensity(low-volume cf. high-volume = ∆4.8-6.6%).Conclusion: 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, while high volumes of lower intensity activity may be beneficial for hip structural geometry.</p

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

ObjectivesTo 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.MethodWe 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.ResultsAt 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).ConclusionThose 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

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 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.</p

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

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

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 g 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