Implementation and engagement of the SMART Work & Life sitting reduction intervention: an exploratory analysis on intervention effectiveness.

BACKGROUND: To enhance the impact of interventions, it is important to understand how intervention engagement relates to study outcomes. We report on the level of implementation and engagement with the SMART Work & Life (SWAL) programme (delivered with (SWAL plus desk) and without a height-adjustable desk (SWAL)) and explore the effects of different levels of this on change in daily sitting time in comparison to the control group. METHODS: The extent of intervention delivery by workplace champions and the extent of engagement by champions and participants (staff) with each intervention activity was assessed by training attendance logs, workplace champion withdrawal dates, intervention activities logs and questionnaires. These data were used to assess whether a cluster met defined criteria for low, medium, or high implementation and engagement or none of these. Mixed effects linear regression analyses tested whether change in sitting time varied by: (i) the number of intervention activities implemented and engaged with, and (ii) the percentage of implementation and engagement with all intervention strategies. RESULTS: Workplace champions were recruited for all clusters, with 51/52 (98%) attending training. Overall, 12/27 (44.4%) SWAL and 9/25 (36.0%) SWAL plus desk clusters implemented all main intervention strategies. Across remaining clusters, the level of intervention implementation varied. Those in the SWAL (n = 8 (29.6%) clusters, 80 (32.1%) participants) and SWAL plus desk (n = 5 (20.0%) clusters, 41 (17.1%) participants) intervention groups who implemented and engaged with the most intervention strategies and had the highest percentage of cluster implementation and engagement with all intervention strategies sat for 30.9 (95% CI -53.9 to -7.9, p = 0.01) and 75.6 (95% CI -103.6 to -47.7, p < 0.001) fewer minutes/day respectively compared to the control group at 12 month follow up. These differences were larger than the complete case analysis. The differences in sitting time observed for the medium and low levels were similar to the complete case analysis. CONCLUSIONS: Most intervention strategies were delivered to some extent across the clusters although there was large variation. Superior effects for sitting reduction were seen for those intervention groups who implemented and engaged with the most intervention components and had the highest level of cluster implementation and engagement. TRIAL REGISTRATION: ISRCTN11618007. Registered on 24 January 2018. https://www.isrctn.com/ISRCTNISRCTN11618007 .

Participant and workplace champion experiences of an intervention designed to reduce sitting time in desk-based workers: SMART work & life.

BACKGROUND: A cluster randomised controlled trial demonstrated the effectiveness of the SMART Work & Life (SWAL) behaviour change intervention, with and without a height-adjustable desk, for reducing sitting time in desk-based workers. Staff within organisations volunteered to be trained to facilitate delivery of the SWAL intervention and act as workplace champions. This paper presents the experiences of these champions on the training and intervention delivery, and from participants on their intervention participation. METHODS: Quantitative and qualitative feedback from workplace champions on their training session was collected. Participants provided quantitative feedback via questionnaires at 3 and 12 month follow-up on the intervention strategies (education, group catch ups, sitting less challenges, self-monitoring and prompts, and the height-adjustable desk [SWAL plus desk group only]). Interviews and focus groups were also conducted at 12 month follow-up with workplace champions and participants respectively to gather more detailed feedback. Transcripts were uploaded to NVivo and the constant comparative approach informed the analysis of the interviews and focus groups. RESULTS: Workplace champions rated the training highly with mean scores ranging from 5.3/6 to 5.7/6 for the eight parts. Most participants felt the education increased their awareness of the health consequences of high levels of sitting (SWAL: 90.7%; SWAL plus desk: 88.2%) and motivated them to change their sitting time (SWAL: 77.5%; SWAL plus desk: 85.77%). A high percentage of participants (70%) reported finding the group catch up session helpful and worthwhile. However, focus groups highlighted mixed responses to the group catch-up sessions, sitting less challenges and self-monitoring intervention components. Participants in the SWAL plus desk group felt that having a height-adjustable desk was key in changing their behaviour, with intrinsic as well as time based factors reported as key influences on the height-adjustable desk usage. In both intervention groups, participants reported a range of benefits from the intervention including more energy, less fatigue, an increase in focus, alertness, productivity and concentration as well as less musculoskeletal problems (SWAL plus desk group only). Work-related, interpersonal, personal attributes, physical office environment and physical barriers were identified as barriers when trying to sit less and move more. CONCLUSIONS: Workplace champion and participant feedback on the intervention was largely positive but it is clear that different behaviour change strategies worked for different people indicating that a 'one size fits all' approach may not be appropriate for this type of intervention. The SWAL intervention could be tested in a broader range of organisations following a few minor adaptations based on the champion and participant feedback. TRIAL REGISTRATION: ISCRCTN registry (ISRCTN11618007).

Breaking up sitting with short frequent or long infrequent physical activity breaks does not lead to compensatory changes in appetite, appetite-regulating hormones or energy intake.

The aim of this study was to determine the appetite-related responses to breaking up prolonged sitting with physical activity bouts differing in frequency and duration among adult females. Fourteen sedentary females aged 34 ± 13 years with a body mass index of 27.1 ± 6.3 kg/m2 (mean ± SD) took part in a randomised crossover trial with three, 7.5 h conditions: (1) uninterrupted sitting (SIT), (2) sitting with short frequent 2-min moderate-intensity walking breaks every 30 min (SHORT-BREAKS), and (3) sitting with longer duration, less frequent 10-min moderate-intensity walking breaks every 170-180 min (LONG-BREAKS). The intensity and total duration of physical activity was matched between the SHORT-BREAKS and LONG-BREAKS conditions. Linear mixed models were used to compare the outcomes between conditions with significance being accepted as p ≤ 0.05. There were no significant between-condition differences in hunger, satisfaction, prospective food consumption or overall appetite area under the curve (AUC) (all p ≥ 0.801). Absolute ad libitum energy intake and relative energy intake (REI) did not differ significantly between conditions (all p ≥ 0.420). Acylated ghrelin and total peptide YY incremental and total AUC did not differ significantly between conditions (all p ≥ 0.388). Yet, there was a medium effect size for the higher acylated ghrelin incremental AUC in SHORT-BREAKS versus SIT (d = 0.61); the reverse was seen for total AUC, which was lower in SHORT-BREAKS versus SIT (d = 0.69). These findings suggest that breaking up sitting does not lead to compensatory changes in appetite, appetite hormones or energy intake regardless of physical activity bout duration and frequency among adult females.

Comparison of physical activity metrics from two research-grade accelerometers worn on the non-dominant wrist and thigh in children.

This study compared physical activity metrics from the activPAL (AP) worn on the thigh with the ActiGraph worn on the non-dominant wrist using open-source methods. Measures included average acceleration, intensity gradient (IG) and the minimum acceleration value of the most active X mins (MX). Fifty-two children (26 boys; age: 10.4 ± 0.6 years) provided≥1 day (24 h) of concurrent wear time from the activPAL and ActiGraph. Measures tended to be lower from the activPAL versus the ActiGraph. Poor agreement was evident for average acceleration but good for the IG. For the IG, the absolute and relative zones needed to reach equivalence was 4% and 0.4 SDs, respectively and for average acceleration were 10% and 1.2 SDs, respectively. Good agreement was evident for M60, M30, M20, M15 and M10 between devices. Regardless of the reference device used, equivalent estimates for the intensity gradient, M60, M30, M20, M15 and M10 were observed with relative and absolute equivalence zones being≤4% and≤0.5 SDs, respectively. The IG, M60, M30, M20, M15 and M10 appear good candidates for comparing activity data collected from the activPAL and ActiGraph. Future research can use the AP to report on sedentary behaviours as well as PA outcomes.

Self-reported walking pace: A simple screening tool with lowest risk of all-cause mortality in those that 'walk the talk'.

To determine whether the association between self-reported walking pace and all-cause mortality (ACM) persists across categories of accelerometer-assessed physical activity status. Data from 93,709 UK Biobank participants were included. Physical activity was assessed using wrist-worn accelerometers for 7-days. Participants accumulating <150 min/week moderate-to-vigorous- activity were classed as "inactive", ≥150 min/week moderate (≥3 METs) activity as "somewhat active" excluding those with ≥150 min/week upper-moderate-to-vigorous activity (≥4.3 METs), who were classed as "high-active". Over a 6.3 y (median) follow-up, 2,173 deaths occurred. More than half of slow walkers were "inactive", but only 26% of steady and 12% of brisk walkers. Associations between walking pace and ACM were consistent with those for activity. "High active" brisk walkers had the lowest risk of ACM (Hazard Ratio (HR) 0.22; 95% CI: 0.17,0.28), relative to "inactive" slow walkers. Within those classed as "inactive", steady (HR 0.54; 0.46,0.64) and brisk walkers (HR 0.42; 0.34,0.52) had lower risk than slow walkers. In conclusion, self-reported walking pace was associated with accelerometer-assessed physical activity with both exposures having similar associations with ACM. "inactive", steady, and brisk walkers had lower ACM risk than slow walkers. The pattern was similar for "High active" participants. Overall, "High active" brisk walkers had lowest risk.

Accelerometer-Assessed Physical Activity in People with Type 2 Diabetes: Accounting for Sleep when Determining Associations with Markers of Health.

High physical activity levels during wake are beneficial for health, while high movement levels during sleep are detrimental to health. Our aim was to compare the associations of accelerometer-assessed physical activity and sleep disruption with adiposity and fitness using standardized and individualized wake and sleep windows. People (N = 609) with type 2 diabetes wore an accelerometer for up to 8 days. Waist circumference, body fat percentage, Short Physical Performance Battery (SPPB) test score, sit-to-stands, and resting heart rate were assessed. Physical activity was assessed via the average acceleration and intensity distribution (intensity gradient) over standardized (most active 16 continuous hours (M16h)) and individualized wake windows. Sleep disruption was assessed via the average acceleration over standardized (least active 8 continuous hours (L8h)) and individualized sleep windows. Average acceleration and intensity distribution during the wake window were beneficially associated with adiposity and fitness, while average acceleration during the sleep window was detrimentally associated with adiposity and fitness. Point estimates for the associations were slightly stronger for the standardized than for individualized wake/sleep windows. In conclusion, standardized wake and sleep windows may have stronger associations with health due to capturing variations in sleep durations across individuals, while individualized windows represent a purer measure of wake/sleep behaviors.

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

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

Ethnic differences in the relationship between step cadence and physical function in older adults.

This study investigated associations between step cadence and physical function in healthy South Asian (SA) and White European (WE) older adults, aged ≥60. Participants completed the 60-s Sit-to-Stand (STS-60) test of physical function. Free-living stepping was measured using the activPAL3™. Seventy-one WEs (age = 72 ± 5, 53% male) and 33 SAs (age = 71 ± 5, 55% male) were included. WEs scored higher than SAs in the STS-60 (23 vs 20 repetitions, p = 0.045). Compared to WEs, SAs had significantly lower total and brisk (≥100 steps/min) steps (total: 8971 vs 7780 steps/day, p = 0.041; brisk: 5515 vs 3723 steps/day, p = 0.001). In WEs, 1000 brisk steps and each decile higher proportion of steps spent brisk stepping were associated with STS-60 (ß = 0.72 95% CI 0.05, 1.38 and ß = 1.01 95% CI 0.19, 1.82, respectively), with associations persisting across mean peak 1 min (ß = 1.42 95% CI 0.12, 2.71), 30 min (ß = 1.71 95% CI 0.22, 3.20), and 60 min (ß = 2.16 95% CI 0.62, 3.71) stepping periods. Associations were not observed in SAs. Ethnic differences in associations between ambulation and physical function may exist in older adults which warrant further investigationi.

Stepping up with GGIR: Validity of step cadence derived from wrist-worn research-grade accelerometers using the verisense step count algorithm.

The Verisense Step Count Algorithm facilitates generation of steps from wrist-worn accelerometers. Based on preliminary evidence suggesting a proportional bias with overestimation at low steps/day, but underestimation at high steps/day, the algorithm parameters have been revised. We aimed to establish validity of the original and revised algorithms relative to waist-worn ActiGraph step cadence. We also assessed whether step cadence was similar across accelerometer brand and wrist. Ninety-eight participants (age: 58.6±11.1 y) undertook six walks (~500 m hard path) at different speeds (cadence: 92.9±9.5-127.9±8.7 steps/min) while wearing three accelerometers on each wrist (Axivity, GENEActiv, ActiGraph) and an ActiGraph on the waist. Of these, 24 participants also undertook one run (~1000 m). Mean bias for the original algorithm was -21 to -26.1 steps/min (95% limits of agreement (LoA) ~±65 steps/min) and mean absolute percentage error (MAPE) 17-22%. This was unevenly distributed with increasing error as speed increased. Mean bias and 95%LoA were halved with the revised algorithm parameters (~-10 to -12 steps/min, 95%LoA ~30 steps/min, MAPE ~10-12%). Performance was similar across brand and wrist. The revised step algorithm provides a more valid measure of step cadence than the original, with MAPE similar to recently reported wrist-wear summary MAPE (7-11%).

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

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

Cardiometabolic Response to a Single High-intensity Interval Exercise Session Versus Breaking up Sedentary Time with Fragmented High-intensity Interval Exercise.

This study compared the effects of interrupting prolonged sedentary time with high-intensity physical activity (SED-ACT), a volume- and duration-matched high-intensity interval exercise session followed by prolonged sedentary time (HIIE), and prolonged uninterrupted sedentary time (SED) on postprandial glucose, insulin and triglyceride concentrations. Twelve sedentary and inactive but otherwise healthy adults completed 3, 6.5 h conditions in an incomplete counterbalanced order. During SED, participants sat continuously. For HIIE, participants completed 10×60 s cycling bouts at 90% maximum oxygen update (V̇O2max) with 1 min active recovery between bouts. In SED-ACT, 60 s cycling bouts at 90% V̇O2max were completed every 30 min (10 times in total) with 30 s of active recovery immediately before and after. Standardised meals were consumed at 0 h and 3 h and capillary blood samples were collected fasted and every 30 min. Compared with SED, postprandial glucose incremental area under the curve (iAUC) was significantly lower in SED-ACT by 1.91 mmol/L∙6.5 h (p=0.022) and triglyceride iAUC was significantly lower in HIIE by 1.02 mmol/L∙6.5 h (p=0.030). Interrupting sedentary time with high-intensity physical activity can lower postprandial glucose concentrations, whereas a HIIE session can lower postprandial triglyceride concentrations.

Effects of Frequency and Duration of Interrupting Sitting on Cardiometabolic Risk Markers.

Interrupting prolonged sitting with short multiple bouts of moderate-intensity physical activity (PA) can improve postprandial cardiometabolic risk markers. This study examined the effect of high and low frequency PA bouts (matched for total PA duration and energy expenditure) on postprandial cardiometabolic responses when compared with prolonged sitting. In this three-condition randomised crossover trial, 14 sedentary, inactive females (33.8±13.4 years, BMI 27.1±6.3 kg/m2) completed 3, 7.5 h conditions: 1) prolonged sitting (SIT), 2) high-frequency PA breaks (HIGH-FREQ) consisting of 15 ×2 min bouts of moderate-intensity treadmill PA every 30 min, and 3) low-frequency PA breaks (LOW-FREQ) consisting of 3 ×10 min bouts of moderate-intensity treadmill PA every 180 min. The PA bouts were performed at 65% of peak oxygen uptake. Net incremental area under the curve (iAUC) for each 7.5 h condition was calculated for glucose, insulin and triacylglycerol (TAG) concentrations. Insulin iAUC was significantly (p<0.026) lower during HIGH-FREQ (mean [95%CI]; 82.86 [55.02, 110.70] µU/mL∙7.5 h) than LOW-FREQ (116.61 [88.50, 144.73] µU/mL∙7.5 h) and SIT (119.98 [92.42, 147.53] µU/mL∙7.5 h). Glucose and TAG iAUC did not differ between conditions. Engaging in higher-frequency PA breaks may be effective in attenuating postprandial insulin responses compared with lower-frequency PA breaks and prolonged sitting.

Reducing prolonged sedentary time using a treadmill desk acutely improves cardiometabolic risk markers in male and female adults.

This study evaluated the acute effects of interrupting prolonged sitting with an accumulated 2 h of light-intensity walking on postprandial cardiometabolic risk markers. In this randomised crossover trial, 24 participants (twelve males) aged 18-55 years took part in two, 6.5 h conditions: 1) prolonged sitting (SIT) and 2) sitting interrupted hourly with 20 min light-intensity treadmill desk walking at between 1.2-3.5 km/h-1 (INT-SIT). Standardized meals were provided at 0 h and 3 h. Blood samples and blood pressure measures were taken hourly. Statistical analyses were completed using linear mixed models. Postprandial incremental area under the curve responses (mmol/L∙6.5 h) for glucose (4.52 [3.47, 5.56] and 6.66 [5.62, 7.71] for INT-SIT and SIT, respectively) and triglycerides (1.96 [0.96, 2.96] and 2.71 [1.70, 3.71] for INT-SIT and SIT, respectively) were significantly lower in INT-SIT than SIT. Mean systolic and diastolic blood pressure responses were lower by 3% and 4%, respectively, in INT-SIT than SIT (P < 0.05). There was no significant condition x sex interaction effect for any outcomes (P > 0.05). These findings suggest that interrupting sitting with an accumulated 2 h of light-intensity walking acutely improves cardiometabolic risk levels in males and females compared with prolonged sitting.

Effects of breaking up prolonged sitting following low and high glycaemic index breakfast consumption on glucose and insulin concentrations.

PURPOSE: Breaking up prolonged sitting can attenuate the postprandial rise in glucose and insulin. Whether such effects are dependent of the glycaemic index (GI) of the consumed carbohydrate is unknown. This study examined the acute effects of breaking up prolonged sitting following a low GI and a high GI breakfast on postprandial glucose and insulin concentrations. PROCEDURES: Fourteen adult males aged 22.1 ± 1.2 years completed four, 4 h experimental conditions: high GI breakfast followed by uninterrupted sitting (HGI-SIT), low GI breakfast followed by uninterrupted sitting (LGI-SIT), high GI breakfast followed by 2 min activity breaks every 20 min (HGI-ACT), and low GI breakfast followed by 2 min activity breaks every 20 min (LGI-ACT). Positive incremental area under the curve (iAUC) for glucose and insulin (mean [95% CI]) for each 4 h experimental condition was calculated. Statistical analyses were completed using linear mixed models. RESULTS: The sitting × breakfast GI interaction was not significant for glucose positive iAUC (P = 0.119). Glucose positive iAUC (mmol/L 4 h-1) was significantly lower in the activity breaks conditions than the uninterrupted sitting conditions (2.07 [2.24, 2.89] vs. 2.56 [1.74, 2.40], respectively, P = 0.004) and significantly lower in the low GI conditions than the high GI conditions (2.13 [1.80, 2.45] vs. 2.51 [2.18, 2.84], respectively, P = 0.022). Insulin concentrations did not differ between conditions (P ≥ 0.203). CONCLUSIONS: Breaking up prolonged sitting and lowering breakfast GI independently reduced postprandial glucose responses. This indicates that interrupting prolonged sitting and reducing dietary GI are beneficial approaches for reducing cardiometabolic disease risk.

Short, frequent high-intensity physical activity breaks reduce appetite compared to a continuous moderate-intensity exercise bout.

A single exercise session can affect appetite-regulating hormones and suppress appetite. The effects of short, regular physical activity breaks across the day on appetite are unclear. This study investigated the effects of breaking up sitting with high-intensity physical activity vs a single bout of moderate-intensity exercise and prolonged sitting on appetite control. In this randomised crossover trial, 14 sedentary, inactive adults (7 women) completed 3, 8-h experimental conditions: (i) prolonged sitting (SIT); (ii) 30 min of moderate-intensity exercise followed by prolonged sitting (EX-SIT), and (iii) sitting with 2 min 32 s of high-intensity physical activity every hour (SIT-ACT). Physical activity energy expenditure was matched between EX-SIT and SIT-ACT. Subjective appetite was measured every 30 min with acylated ghrelin and total peptide-YY (PYY) measured hourly in response to two standardised test meals. An ad libitum buffet meal was provided at the end of each condition. Based on linear mixed model analysis, total area under the curve for satisfaction was 16% higher (P = 0.021) and overall appetite was 11% lower during SIT-ACT vs EX-SIT (P = 0.018), with no differences between SIT-ACT and SIT. Time series analysis indicated that SIT-ACT reduced subjective appetite during the majority of the post-lunch period compared with SIT and EX-SIT, with some of these effects reversed earlier in the afternoon (P < 0.05). Total PYY and acylated ghrelin did not differ between conditions. Relative energy intake was 760 kJ lower during SIT-ACT vs SIT (P = 0.024). High-intensity physical activity breaks may be effective in acutely suppressing appetite; yet, appetite-regulating hormones may not explain such responses.

Stress and Work Performance Responses to a Multicomponent Intervention for Reducing and Breaking up Sitting in Office Workers: A Cluster Randomized Controlled Trial.

OBJECTIVE: The aim of the study is to explore the potential of a sitting reduction workplace intervention for improving stress and work performance. METHODS: A cluster randomized controlled trial evaluated an intervention to reduce and break up occupational sitting in 12 clusters ( n = 89 office workers) over 8 weeks. Outcomes were physiological stress (cortisol concentrations), perceived stress, and work performance. RESULTS: Linear mixed model group × time interaction effects were nonsignificant. Exploratory analyses showed a trend, with a large effect, for lower cortisol concentrations over the day in the intervention group relative to controls at 8 weeks (-0.85; 95% confidence interval, -1.70 to 0.03 nmol·L -1 ; P = 0.06, d = 0.79). The intervention group had higher vigor and cognitive liveliness at 8 weeks relative to controls ( P ≤ 0.05). CONCLUSIONS: This exploratory study suggests that there could be meaningful changes in physiological stress and work-related outcomes that should be investigated in future studies.

Four-Year Increase in Step Cadence Is Associated with Improved Cardiometabolic Health in People with a History of Prediabetes.

PURPOSE: To investigate associations between 4-yr change in step cadence and markers of cardiometabolic health in people with a history of prediabetes and to explore whether these associations are modified by demographic factors. METHODS: In this prospective cohort study, adults, with a history of prediabetes, were assessed for markers of cardiometabolic health (body mass index, waist circumference, high-density lipoprotein cholesterol [HDL-C], low-density lipoprotein cholesterol [LDL-C], triglycerides, and glycated hemoglobin A1c [HbA1c]), and free-living stepping activity (activPAL3™) at baseline, 1 yr, and 4 yr. Brisk steps per day were defined as the number of steps accumulated at ≥100 steps per minute and slow steps per day as those accumulated at <100 steps per minute; the mean peak stepping cadence during the most active 10 minutes of the day was also derived. Generalized estimating equations examined associations between 4-yr change in step cadence and change in cardiometabolic risk factors, with interactions by sex and ethnicity. RESULTS: Seven hundred ninety-four participants were included (age, 59.8 ± 8.9 yr; 48.7% women; 27.1% ethnic minority; total steps per day, 8445 ± 3364; brisk steps per day, 4794 ± 2865; peak 10-min step cadence, 128 ± 10 steps per minute). Beneficial associations were observed between change in brisk steps per day and change in body mass index, waist circumference, HDL-C, and HbA1c. Similar associations were found between peak 10-min step cadence and HDL-C and waist circumference. Interactions by ethnicity revealed change in brisk steps per day and change in peak 10-min step cadence had a stronger association with HbA1c in White Europeans, whereas associations between change in 10-min peak step cadence with measures of adiposity were stronger in South Asians. CONCLUSIONS: Change in the number of daily steps accumulated at a brisk pace was associated with beneficial change in adiposity, HDL-C, and HbA1c; however, potential benefits may be dependent on ethnicity for outcomes related to HbA1c and adiposity.

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

Background: Office workers spend 70-85% of their time at work sitting. High levels of sitting have been linked to poor physiological and psychological health. Evidence shows the need for fully powered randomised controlled trials, with long-term follow-up, to test the effectiveness of interventions to reduce sitting time. Objective: Our objective was to test the clinical effectiveness and cost-effectiveness of the SMART Work & Life intervention, delivered with and without a height-adjustable workstation, compared with usual practice at 12-month follow-up. Design: A three-arm cluster randomised controlled trial. Setting: Councils in England. Participants: Office workers. Intervention: SMART Work & Life is a multicomponent intervention that includes behaviour change strategies, delivered by workplace champions. Clusters were randomised to (1) the SMART Work & Life intervention, (2) the SMART Work & Life intervention with a height-adjustable workstation (i.e. SMART Work & Life plus desk) or (3) a control group (i.e. usual practice). Outcome measures were assessed at baseline and at 3 and 12 months. Main outcome measures: The primary outcome was device-assessed daily sitting time compared with usual practice at 12 months. Secondary outcomes included sitting, standing, stepping time, physical activity, adiposity, blood pressure, biochemical measures, musculoskeletal issues, psychosocial variables, work-related health, diet and sleep. Cost-effectiveness and process evaluation data were collected. Results: A total of 78 clusters (756 participants) were randomised [control, 26 clusters (n = 267); SMART Work & Life only, 27 clusters (n = 249); SMART Work & Life plus desk, 25 clusters (n = 240)]. At 12 months, significant differences between groups were found in daily sitting time, with participants in the SMART Work & Life-only and SMART Work & Life plus desk arms sitting 22.2 minutes per day (97.5% confidence interval -38.8 to -5.7 minutes/day; p = 0.003) and 63.7 minutes per day (97.5% confidence interval -80.0 to -47.4 minutes/day; p < 0.001), respectively, less than the control group. Participants in the SMART Work & Life plus desk arm sat 41.7 minutes per day (95% confidence interval -56.3 to -27.0 minutes/day; p < 0.001) less than participants in the SMART Work & Life-only arm. Sitting time was largely replaced by standing time, and changes in daily behaviour were driven by changes during work hours on workdays. Behaviour changes observed at 12 months were similar to 3 months. At 12 months, small improvements were seen for stress, well-being and vigour in both intervention groups, and for pain in the lower extremity and social norms in the SMART Work & Life plus desk group. Results from the process evaluation supported these findings, with participants reporting feeling more energised, alert, focused and productive. The process evaluation also showed that participants viewed the intervention positively; however, the extent of engagement varied across clusters. The average cost of SMART Work & Life only and SMART Work & Life plus desk was £80.59 and £228.31 per participant, respectively. Within trial, SMART Work & Life only had an incremental cost-effectiveness ratio of £12,091 per quality-adjusted life-year, with SMART Work & Life plus desk being dominated. Over a lifetime, SMART Work & Life only and SMART Work & Life plus desk had incremental cost-effectiveness ratios of £4985 and £13,378 per quality-adjusted life-year, respectively. Limitations: The study was carried out in one sector, limiting generalisability. Conclusions: The SMART Work & Life intervention, provided with and without a height-adjustable workstation, was successful in changing sitting time. Future work: There is a need for longer-term follow-up, as well as follow-up within different organisations. Trial registration: Current Controlled Trials ISRCTN11618007.

Office workers spend a large proportion of their day sitting. High levels of sitting have been linked to diseases, such as type 2 diabetes, heart disease and some cancers. The SMART Work & Life intervention is designed to reduce office workers' sitting time inside and outside work. The SMART Work & Life intervention involves organisational, environmental, group and individual strategies to encourage a reduction in sitting time and was designed to be delivered with and without a height-adjustable workstation (which allows the user to switch between sitting and standing while working). To test whether or not the SMART Work & Life intervention worked, we recruited 756 office workers from councils in Leicester/Leicestershire, Greater Manchester and Liverpool, UK. Participants were from 78 office groups. One-third of the participants received the intervention, one-third received the intervention with a height-adjustable workstation and one-third were a control group (and carried on as usual). Workplace champions in each office group were given training and resources to deliver the intervention. Data were collected at the start of the study, with follow-up measurements at 3 and 12 months. We measured sitting time using a small device worn on the thigh and collected data on weight, body fat, blood pressure, blood sugar and cholesterol levels. We asked participants about their health and work and spoke to participants to find out what they thought of the intervention. Our results showed that participants who received the intervention without workstation sat for 22 minutes less per day, and participants who received the intervention with workstation sat for 64 minutes less per day, than participants in the control group. Levels of stress, well-being, vigour (i.e. personal and emotional energy and cognitive liveliness) and pain in the lower extremity appeared to improve in the intervention groups. Participants viewed the intervention positively and reported several benefits, such as feeling more energised, alert, focused and productive; however, the extent to which participants engaged with the intervention varied across groups.

Lower Amounts of Daily and Prolonged Sitting Do Not Lower Free-Living Continuously Monitored Glucose Concentrations in Overweight and Obese Adults: A Randomised Crossover Study.

This study compared the short-term continuously monitored glucose responses between higher and lower amounts of prolonged sitting in overweight and obese adults under free-living conditions. In a randomised crossover design, 12 participants (age 48 ± 10 years, body mass index 33.3 ± 5.5 kg/m2) completed two four-day experimental regimens while wearing a continuous glucose monitor, as follows: (1) uninterrupted sitting (participants were instructed to sit for ≥10 h/day and accrue ≥7, 1 h sitting bouts each day), and (2) interrupted sitting (participants were instructed to interrupt sitting every 30 min during ten of their waking hours with 6−10 min of activity accrued in each hour). Linear mixed models compared outcomes between regimens. None of the continuously monitored glucose variables differed between regimens, e.g., 24 h net incremental area under the glucose curve was 5.9 [95% CI: −1.4, 13.1] and 5.6 [95% CI: −1.7, 12.8] mmol/L∙24 h, respectively (p = 0.47). Daily sitting (−58 min/day, p = 0.001) and sitting bouts lasting ≥30 min (−99 min/day, p < 0.001) were significantly lower and stepping time significantly higher (+40 min/day, p < 0.001) in the interrupted sitting than the uninterrupted sitting regimen. In conclusion, lower amounts of daily and prolonged sitting did not improve free-living continuously measured glucose among overweight and obese adults.

A More Intense Examination of the Intensity of Physical Activity in People Living with Chronic Obstructive Pulmonary Disease: Insights from Threshold-Free Markers of Activity Intensity.

Physical activity (PA) intensity of people living with chronic obstructive pulmonary disease (COPD) is typically evaluated using intensity thresholds developed in younger, healthier populations with greater exercise capacity and free from respiratory symptoms. This study therefore compared (i) PA differences between COPD and non-COPD controls using both traditional intensity thresholds and threshold-free metrics that represent the volume and intensity of the whole PA profile, and (ii) explored the influence of exercise capacity on observed differences. Moderate-to-vigorous physical activity (MVPA), average acceleration (proxy for volume, mg) and intensity distribution of activity were calculated for 76 individuals with COPD and 154 non-COPD controls from wrist-worn ActiGraph accelerometry. PA profiles representing the minimum intensity (acceleration, mg) during the most active accumulated 5-960 min were plotted. Estimated VO2peak and relative intensity were derived from the incremental shuttle walk test distance. Compared to the non-COPD control group, individuals with COPD recorded fewer MVPA minutes (59 vs. 83 min/day), lower overall waking activity (29.1 vs. 36.4 mg) and a poorer waking intensity distribution (-2.73 vs. -2.57). Individuals with COPD also recorded a lower absolute intensity (acceleration, mg) for their most active 5-960 min, but higher intensity relative to their estimated exercise capacity derived from the ISWT. People with COPD have a lower volume and absolute intensity of PA than controls but perform PA at a higher relative intensity. There is a need to move away from absolute intensity thresholds, and towards personalised or relative-intensity thresholds, to reflect reduced exercise capacity in COPD populations.