Effect of an office-based intervention on visceral adipose tissue: the WorkACTIVE-P randomized controlled trial
Bibliographic record
Abstract
Office-based activity reduces sedentariness, yet no randomized controlled trials (RCTs) have assessed how such activity influences visceral adipose tissue (VAT). This study examined the effect of an office-based, multicomponent activity intervention on VAT. The WorkACTIVE-P RCT enrolled sedentary office workers (body mass index: 31.4 (standard deviation (SD) 4.4) kg/m2) to an intervention (n = 20) or control (n = 20) group. For 3 months, the intervention group received an office-based pedal desk, further to an intervention promoting its use and increased walking. The control group maintained habitual activity. At baseline and follow-up, VAT, cardiometabolic disease risk markers, physical activity, and food intake were measured. Steps/day were not altered relative to control (P ≥ 0.51), but the pedal desk was utilized for 127 (SD 61) min/day. The intervention reduced VAT relative to control (−0.15 kg; 95% confidence interval (CI) = −0.29 to −0.01; P = 0.04). Moreover, the intervention decreased fasting glucose compared with control (−0.29 mmol/L; 95% CI = −0.51 to −0.06; P = 0.01), but no differences in other cardiometabolic disease markers or food intake were revealed (P ≥ 0.11). A multicomponent intervention decreased VAT in office workers who were overweight or obese. Though longer-term studies are needed, office-based, multicomponent activity regimens may lower cardiometabolic disease risk. Trial registered at ClinicalTrials.gov (NCT02561611). Novelty: In WorkACTIVE-P, a multicomponent activity intervention decreased visceral adipose tissue relative to control in office workers. The intervention also reduced glucose compared with control, though other metabolic risk markers and food intake were not altered. Such multicomponent interventions could help reduce cardiometabolic disease risk, but longer studies are needed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".