Workplace sitting and height-adjustable workstations: a randomized controlled trial

Background Desk-based office employees sit for most of their working day. To address excessive sitting as a newly identified health risk, best practice frameworks suggest a multi-component approach. However, these approaches are resource intensive and knowledge about their impact is limited. Purpose To compare the efficacy of a multi-component intervention to reduce workplace sitting time, to a height-adjustable workstations-only intervention, and to a comparison group (usual practice). Design Three-arm quasi-randomized controlled trial in three separate administrative units of the University of Queensland, Brisbane, Australia. Data were collected between January and June 2012 and analyzed the same year. Setting/participants Desk-based office workers aged 20-65 (multi-component intervention, n=16; workstations-only, n=14; comparison, n=14). Intervention The multi-component intervention comprised installation of height-adjustable workstations and organizational-level (management consultation, staff education, manager e-mails to staff) and individual-level (face-to-face coaching, telephone support) elements. Main outcome measures Workplace sitting time (minutes/8-hour workday) assessed objectively via activPAL3 devices worn for 7 days at baseline and 3 months (end-of-intervention) . Results At baseline, the mean proportion of workplace sitting time was approximately 77% across all groups (multi-component group 366 minutes/8 hours [SD=49]; workstations-only group 373 minutes/8 hours [SD=36], comparison 365 minutes/8 hours [SD=54]). Following intervention and relative to the comparison group, workplace sitting time in the multi-component group was reduced by 89 minutes/8-hour workday (95% CI=-130, -47 minutes;

The impact of behavioural screening on intervention outcomes in a randomised, controlled multiple behaviour intervention trial

Background: With an increasing research focus on multiple health behaviour change interventions, a methodological issue requiring further investigation is whether or not to employ pre-trial behavioural screening to exclude participants who are achieving a pre-specified level of one or more behaviours. Behavioural screening can be used to direct limited resources to participants most in need of a behaviour change intervention; but may reduce the representativeness of the sample and limit comparability with trials that do not employ pre-trial behavioural screening. Furthermore, the impact of this type of screening on intervention participation and intervention effects is unknown

Cardio-metabolic impact of changing sitting, standing, and stepping in the workplace

According to cross-sectional and acute experimental evidence, reducing sitting time should improve cardio-metabolic health risk biomarkers. Furthermore, the improvements obtained may depend on whether sitting is replaced with standing or ambulatory activities. Based on data from the Stand Up Victoria multi-component workplace intervention, we examined this issue using compositional data analysis - a method that can examine and compare all activity changes simultaneously.Participants receiving the intervention (n=136 ≥0.6 full-time equivalent desk-based workers, 65% women, mean±SD age=44.6 ±9.1 years from seven worksites) were asked to improve whole-of-day activity by standing up, sitting less and moving more. Their changes in the composition of daily waking hours (activPAL-assessed sitting, standing, stepping) were quantified, then tested for associations with concurrent changes in cardio-metabolic risk (CMR) scores and 14 biomarkers concerning body composition, glucose, insulin and lipid metabolism. Analyses were by mixed models, accounting for clustering (3 months, n=105-120; 12 months, n=80-97).Sitting reduction was significantly (

Correlates of pedometer use: Results from a community-based physical activity intervention trial (10,000 Steps Rockhampton)

Background: Pedometers have become common place in physical activity promotion, yet little information exists on who is using them. The multi-strategy, community-based 10,000 Steps Rockhampton physical activity intervention trial provided an opportunity to examine correlates of pedometer use at the population level. Methods: Pedometer use was promoted across all intervention strategies including: local media, pedometer loan schemes through general practice, other health professionals and libraries, direct mail posted to dog owners, walking trail signage, and workplace competitions. Data on pedometer use were collected during the 2-year follow-up telephone interviews from random population samples in Rockhampton, Australia, and a matched comparison community (Mackay). Logistic regression analyses were used to determine the independent influence of interpersonal characteristics and program exposure variables on pedometer use. Results: Data from 2478 participants indicated that 18.1% of Rockhampton and 5.6% of Mackay participants used a pedometer in the previous 18-months. Rockhampton pedometer users (n = 222) were more likely to be female (OR = 1.59, 95% CI: 1.11, 2.23), aged 45 or older (OR = 1.69, 95% CI: 1.16, 2.46) and to have higher levels of education (university degree OR = 4.23, 95% CI: 1.86, 9.6). Respondents with a BMI > 30 were more likely to report using a pedometer (OR = 1.68, 95% CI: 1.11, 2.54) than those in the healthy weight range. Compared with those in full-time paid work, respondents in 'home duties' were significantly less likely to report pedometer use (OR = 0.18, 95% CI: 0.06, 0.53). Exposure to individual program components, in particular seeing 10,000 Steps street signage and walking trails or visiting the website, was also significantly associated with greater pedometer use. Conclusion: Pedometer use varies between population subgroups, and alternate strategies need to be investigated to engage men, people with lower levels of education and those in full-time 'home duties', when using pedometers in community-based physical activity promotion initiatives

Correlates of Omani adults' physical inactivity and sitting time

Objective: To inform public health approaches for chronic disease prevention, the present study identified sociodemographic, anthropometric and behavioural correlates of work, transport and leisure physical inactivity and sitting time among adults in Oman

Temporal features of sitting, standing and stepping changes in a cluster-randomised controlled trial of a workplace sitting-reduction intervention

Background There is now a body of evidence on the effectiveness of interventions to reduce workplace sitting time. However, there has been limited reporting of how such interventions may impact behaviour both during and outside of work. Sitting, standing and stepping changes following a workplace intervention were examined across five timeframes (work time on work days; non-work time on work days; work days; non-work days; overall (i.e. work and non-work time on all days)), and the relationships between changes during and outside of work was assessed. Methods The cluster-randomised controlled trial, ‘Stand Up Victoria’, delivered a multi-component workplace-delivered intervention that successfully reduced workplace and overall sitting time (relative to controls). Separately, over the five timeframes, changes in device (activPAL3)-assessed outcomes — sitting; prolonged sitting (≥30 min bouts); standing; and, stepping — were compared between intervention (n = 114) and controls (n = 84), along with the time-course of sitting changes during work hours, using mixed models. The potential relationships of changes during work with changes outside of work were examined using compositional data analysis. Results On workdays, intervention participants significantly (p < 0.05) improved their activity profile relative to controls, with reduced sitting (− 117 min/8-h workday, 95% CI: − 141, − 93) and prolonged sitting (− 77 min/8 h workday, 95% CI: − 101, − 52); increased standing (114 min/8 h workday, 95% CI: 92, 136) and maintenance of stepping (3 min/8 h workday, 95% CI: − 7, 11, p = 0.576). Effects were nearly identical for time at work; similar but slightly weaker for overall; and, small and non-significant outside of work on workdays and non-work days. Improvements occurred at all times, but not equally, during work hours (p < 0.001). Correlations between changes during and outside of work on workdays were very weak in both the intervention group (r = − 0.07) and controls (r = − 0.09). Conclusions Sitting time was reduced almost exclusively during work hours (via replacement with standing), with reductions evident during all working hours, to varying degrees. There was no evidence of compensation, with minimal change in activity outside of work, in response to changes in activity at work. Future interventions may benefit from exploring how best to elicit change throughout the whole day, and across work and non-work domains

Responsiveness to change of self-report and device-based physical activity measures in the Living Well with Diabetes trial

Background: This study evaluated the responsiveness to change in physical activity of 2 self-report measures and an accelerometer in the context of a weight loss intervention trial. Methods: 302 participants (aged 20 to 75 years) with type 2 diabetes were randomized into telephone counseling (n = 151) or usual care (n = 151) groups. Physical activity (minutes/week) was assessed at baseline and 6-months using the Active Australia Survey (AAS), the United States National Health Interview Survey (USNHIS) walking for exercise items, and accelerometer (Actigraph GT1M; >= 1952 counts/minute). Responsiveness to change was calculated as responsiveness index (RI), Cohen's d (postscores) and Cohen's d (change-scores). Results: All instruments showed significant improvement in the intervention group (P .05). Accelerometer consistently ranked as the most responsive instrument while the least responsive was the USHNIS (responsiveness index) or AAS (Cohen's d). RIs for AAS, USNHIS and accelerometer did not differ significantly and were, respectively: 0.45 (95% CI: 0.26-0.65); 0.38 (95% CI: 0.20-0.56); and, 0.49 (95% CI: 0.23-0.74). Conclusions: Accelerometer tended to have the highest responsiveness but differences were small and not statistically significant. Consideration of factors, such as validity, feasibility and cost, in addition to responsiveness, is important for instrument selection in future trial

Moderators of health behavior initiation and maintenance in a randomized telephone counseling trial

Objective. This study compares moderators of initiation and maintenance of health behavior changes

Reducing office workers' sitting time: rationale and study design for the Stand Up Victoria cluster randomized trial

Background: Excessive time spent in sedentary behaviours (sitting or lying with low energy expenditure) is associated with an increased risk for type 2 diabetes, cardiovascular disease and some cancers. Desk-based office workers typically accumulate high amounts of daily sitting time, often in prolonged unbroken bouts. The Stand Up Victoria study aims to determine whether a 3-month multi-component intervention in the office setting reduces workplace sitting, particularly prolonged, unbroken sitting time, and results in improvements in cardio-metabolic biomarkers and work-related outcomes, compared to usual practice

Characteristics of control group participants who increased their physical activity in a cluster-randomized lifestyle intervention trial

<p>Abstract</p> <p>Background</p> <p>Meaningful improvement in physical activity among control group participants in lifestyle intervention trials is not an uncommon finding, and may be partly explained by participant characteristics. This study investigated which baseline demographic, health and behavioural characteristics were predictive of successful improvement in physical activity in usual care group participants recruited into a telephone-delivered physical activity and diet intervention trial, and descriptively compared these characteristics with those that were predictive of improvement among intervention group participants.</p> <p>Methods</p> <p>Data come from the Logan Healthy Living Program, a primary care-based, cluster-randomized controlled trial of a physical activity and diet intervention. Multivariable logistic regression models examined variables predictive of an improvement of at least 60 minutes per week of moderate-to-vigorous intensity physical activity among usual care (n = 166) and intervention group (n = 175) participants.</p> <p>Results</p> <p>Baseline variables predictive of a meaningful change in physical activity were different for the usual care and intervention groups. Being retired and completing secondary school (but no further education) were predictive of physical activity improvement for usual care group participants, whereas only baseline level of physical activity was predictive of improvement for intervention group participants. Higher body mass index and being unmarried may also be predictors of physical activity improvement for usual care participants.</p> <p>Conclusion</p> <p>This is the first study to examine differences in predictors of physical activity improvement between intervention group and control group participants enrolled in a physical activity intervention trial. While further empirical research is necessary to confirm findings, results suggest that participants with certain socio-demographic characteristics may respond favourably to minimal intensity interventions akin to the treatment delivered to participants in a usual care group. In future physical activity intervention trials, it may be possible to screen participants for baseline characteristics in order to target minimal-intensity interventions to those most likely to benefit. (Australian Clinical Trials Registry, <url>http://www.anzctr.org.au/default.aspx</url>, ACTRN012607000195459)</p