Bibliographic record
Abstract
Emerging evidence suggests that sedentary behaviour is independently associated with cardiometabolic disease risk in school-aged children and youth. This thesis includes 4 related studies in the pursuit of 2 objectives: (i) To determine the cross-sectional association of sedentary time, interruptions in sedentary time, sedentary bout length, and total movement variability with markers of cardiometabolic disease risk among children and youth; and (ii) to examine the impact of 1-day of prolonged sedentary behaviour, with and without interruptions or structured physical activity, on markers of cardiometabolic disease risk, hunger, food intake and spontaneous physical activity levels in children and youth. In Study 1, we found that interruptions in sedentary time and short bouts of sedentary time were beneficially associated with clustered cardiometabolic disease risk in boys and girls aged 8–11 years, independent of total sedentary time, moderate-and-vigorous physical activity (MVPA), and other confounders (all p < 0.05), while the opposite was true for screen-based sedentary behaviours. In Study 2, we found that movement variability (minute-to-minute changes in movement intensity) was negatively associated with clustered cardiometabolic disease risk and systolic blood pressure independent of MVPA, sedentary time and other covariates in a representative sample of American children and youth aged 12–17 years (all p < 0.05). In Studies 3 and 4, we found that prolonged sitting, with or without interruptions and structured MVPA, did not result in acute changes in markers of cardiometabolic disease risk or subsequent ad libitum food intake or physical activity levels in healthy children aged 10–14 years (all p ≥ 0.05). Taken together, the studies that make up this thesis suggest that optimal levels of cardiometabolic disease risk are most likely to be seen in children who limit their time engaging in screen-based sedentary behaviours, who frequently interrupt their sedentary time, and who have high levels of variability in their movement behaviours.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".