Impact of Sit-to-Stand and Treadmill Desks on Patterns of Daily Waking Physical Behaviors Among Overweight and Obese Seated Office Workers: Cluster Randomized Controlled Trial

Abstract

Background Sit-to-stand and treadmill desks may help sedentary office workers meet the physical activity guideline to “move more and sit less,” but little is known about their long-term impact on altering the accumulation patterns of physical behaviors. Objective This study explores the impact of sit-to-stand and treadmill desks on physical behavior accumulation patterns during a 12-month multicomponent intervention with an intent-to-treat design in overweight and obese seated office workers. Methods In total, 66 office workers were cluster randomized into a seated desk control (n=21, 32%; 8 clusters), sit-to-stand desk (n=23, 35%; 9 clusters), or treadmill desk (n=22, 33%; 7 clusters) group. Participants wore an activPAL (PAL Technologies Ltd) accelerometer for 7 days at baseline, 3-month follow-up (M3), 6-month follow-up (M6), and 12-month follow-up (M12) and received periodic feedback on their physical behaviors. Analyses of physical behavior patterns included total day and workday number of sedentary, standing, and stepping bouts categorized into durations ranging from 1 to 60 and >60 minutes and usual sedentary, standing, and stepping bout durations. Intervention trends were analyzed using random-intercept mixed linear models accounting for repeated measures and clustering effects. Results The treadmill desk group favored prolonged sedentary bouts (>60 min), whereas the sit-to-stand desk group accrued more short-duration sedentary bouts (<20 min). Therefore, compared with controls, sit-to-stand desk users had shorter usual sedentary bout durations short-term (total day ΔM3: −10.1 min/bout, 95% CI −17.9 to −2.2; P=.01; workday ΔM3: −20.3 min/bout, 95% CI −37.7 to −2.9; P=.02), whereas treadmill desk users had longer usual sedentary bout durations long-term (total day ΔM12: 9.0 min/bout, 95% CI 1.6-16.4; P=.02). The treadmill desk group favored prolonged standing bouts (30-60 min and >60 min), whereas the sit-to-stand desk group accrued more short-duration standing bouts (<20 min). As such, relative to controls, treadmill desk users had longer usual standing bout durations short-term (total day ΔM3: 6.9 min/bout, 95% CI 2.5-11.4; P=.002; workday ΔM3: 8.9 min/bout, 95% CI 2.1-15.7; P=.01) and sustained this long-term (total day ΔM12: 4.5 min/bout, 95% CI 0.7-8.4; P=.02; workday ΔM12: 5.8 min/bout, 95% CI 0.9-10.6; P=.02), whereas sit-to-stand desk users showed this trend only in the long-term (total day ΔM12: 4.2 min/bout, 95% CI 0.1-8.3; P=.046). The treadmill desk group accumulated more stepping bouts across various bins of duration (5-50 min), primarily at M3. Thus, treadmill desk users had longer usual stepping bout durations in the short-term compared with controls (workday ΔM3: 4.8 min/bout, 95% CI 1.3-8.3; P=.007) and in the short- and long-term compared with sit-to-stand desk users (workday ΔM3: 4.7 min/bout, 95% CI 1.6-7.8; P=.003; workday ΔM12: 3.0 min/bout, 95% CI 0.1-5.9; P=.04). Conclusions Sit-to-stand desks exerted potentially more favorable physical behavior accumulation patterns than treadmill desks. Future active workstation trials should consider strategies to promote more frequent long-term movement bouts and dissuade prolonged static postural fixity. Trial Registration ClinicalTrials.gov NCT02376504; https://clinicaltrials.gov/ct2/show/NCT02376504

Ambiguity in Statistical Analysis Methods and Nonconformity With Prespecified Commitment to Data Sharing in a Cluster Randomized Controlled Trial

“…In a published cluster randomized controlled trial (cRCT) [ 1 ] on the effects of desks on physical behaviors, 66 individuals were randomized into 3 groups by their office space (ie, clusters): the seated desk control (n=21; 8 clusters), sit-to-stand desk (n=23; 9 clusters), or treadmill desk (n=22; 7 clusters) group.…”

“…The description of methods indicates using random intercept mixed linear models accounting for repeated measures and clusters. However, it is stated elsewhere that “[t]he cluster effect did not significantly (all P values >.05) account for the variability in any of the outcome variables….Therefore, aim 1 and aim 2 outcome observations…were analyzed at the participant level instead of cluster…” [ 1 ].…”

Authors’ Reply: Ambiguity in Statistical Analysis Methods and Nonconformity With Prespecified Commitment to Data Sharing in a Cluster Randomized Controlled Trial

“…Importantly, the current recommendation is to develop the analytical plan based on goals of the analyses (ie, exploratory outcomes in this study) and various study-specific characteristics (selected examples for our study: random cluster size independent of other data and wide physical distribution of within-cluster participants) [ 3 ]. Due to such study-specific considerations, clusters were deemed to be noninformative [ 4 ], and our approach—“random-intercept mixed linear models that accounted for repeated measures and clustering effects” [ 2 ]—included a random effect for clusters to model any potential correlational structure and interparticipant dependency within clusters [ 5 ]. Additionally, we used the Kenward-Rogers method to preserve nominal type I error.…”

“…The method adjusts for df to account for hierarchical complexity of data, including potential nesting and variable or small cluster sizes [ 3 ]. We also acknowledged uneven cluster size as a study limitation [ 2 ].…”

“…Second, while we clearly conveyed the exploratory nature of the analyses aimed at developing hypotheses, we were also conservative by avoiding confirmatory conclusions based on type I error rates [ 2 ]. While it is known that conservative analyses may be counterproductive for exploration [ 6 ], our careful approach—relying on sound, disparate methods sufficiently accounting for any potential within-cluster dependence and variable cluster size, along with a cautious interpretation strategy—was appropriate for the study objective.…”