Associations of sedentary time patterns and <scp>TV</scp> viewing time with inflammatory and endothelial function biomarkers in children
Bibliographic record
Abstract
OBJECTIVE: Investigate associations of TV viewing time and accelerometry-derived sedentary time with inflammatory and endothelial function biomarkers in children. METHODS: Cross-sectional analysis of 164 7-10-year-old children. TV viewing time was assessed by parental proxy report and total and patterns of sedentary time accumulation (e.g. prolonged bouts) were assessed by accelerometry. C-reactive protein (CRP), homeostasis model assessment of insulin resistance, interleukin-2, -6, -8, -10, tumour necrosis factor alpha, adiponectin, resistin, brain-derived neurotrophic factor, soluble intercellular and vascular adhesion molecule 1, plasminogen activator inhibitor 1 and soluble E-selectin were assessed. Generalised linear models assessed the associations of TV viewing and sedentary time with biomarkers, adjusting for sex, waist circumference, moderate- to vigorous-intensity physical activity and diet density. RESULTS: Each additional h week(-1) of TV viewing was associated with 4.4% (95% CI: 2.1, 6.7) greater CRP and 0.6% (0.2, 1.0) greater sVCAM-1 in the fully adjusted model. The association between frequency and duration of 5-10 min bouts of sedentary time and CRP was positive after adjustment for sex and waist circumference but attenuated after adjustment for diet density. CONCLUSIONS: This study suggests that TV viewing was unfavourably associated with several markers of inflammation and endothelial dysfunction. The detrimental association between 5 and 10 min bouts of sedentary time and CRP approached significance, suggesting that further research with a stronger study design (longitudinal and/or experimental) is needed to better understand how the accumulation of sedentary time early in life may influence short and longer term health.
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".