The energy expenditure benefits of reallocating sedentary time with physical activity: a systematic review and meta-analysis
Bibliographic record
Abstract
Background: We compared direct and daily cumulative energy expenditure (EE) differences associated with reallocating sedentary time to physical activity in adults for meaningful EE changes. Methods: Peer-reviewed studies in PubMed, Medline, EMBASE, CINAHL, PsycINFO, Cochrane Central Register of Controlled Trials and Cochrane Database of Systematic Reviews were searched from inception to March 2017. Randomized and non-randomized interventions with sedentary time and EE outcomes in adults were included. Study quality was assessed by the National Heart Lung and Blood Institute tool, and summarized using random-effects meta-analysis and meta-regression. Results: In total, 26 studies were reviewed, and 24 studies examined by meta-analysis. Reallocating 6-9 h of sedentary time to light-intensity physical activity (LIPA) (standardized mean difference [SMD], 2.501 [CI: 1.204-5.363]) had lower cumulative EE than 6-9 h of combined LIPA and moderate-vigorous intensity physical activity (LIPA and moderate-vigorous physical activity [MVPA]) (SMD, 5.218 [CI: 3.822-6.613]). Reallocating 1 h of MVPA resulted in greater cumulative EE than 3-5 h of LIPA and MVPA, but <6-9 h of LIPA and MVPA. Conclusions: Comparable EE can be achieved by different strategies, and promoting MVPA might be effective for those individuals where a combination of MVPA and LIPA is challenging.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.016 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".